Self-Monitoring in Military Consumer Research
Chapter 1: Introduction to the Study
Some military consumer decisions are made in fast-paced, complex
environments of threat and risk. Studies have shown soldiers may
underutilize resources such as food when compared with civilian
counterparts (Hirsch et al., 2005; Kramer, 1995; Kullen et al., 2016; Tassone
& Baker, 2017). Assessing and predicting how well soldiers receive and use
rations, clothing, and personal equipment is difficult (Ahmed et al., 2017,
McClung et al., 2009) but important to war-fighting efforts. Military
consumer researchers have worked for decades to address a persistent need
to better understand and predict military consumer attitudes and behavior
(Meiselman & Schutz, 2003). Selfmonitoring theory is a psychological
construct that defines how people differ in their degree of expressive control.
High self-monitors act in ways to gain social favor. Low self-monitors act in
ways to validate intrinsic self-definitions (DeBono, 2006; Laverie et al.,
2002). Self-monitoring theory has not been used in military consumer
research before. However, it has been used to predict consumer attitudes and
behavior (DeBono 2006) in the civilian sector. Therefore, it is logical to
assume that self-monitoring theory may also help military planners make
similar predictions for military consumers about food, clothing, and
equipment. This will occur through better understanding of military
consumer motivations and making products that appeal better to those
motivations resulting in better utilized products, improved soldier morale,
and less waste of military resources.
The purpose of this study was to determine the extent to which self-
monitoring can be used to predict military consumer attitudes and behavior.
More specifically, the study determined the extent to which self-monitoring
constructs (Self-Monitoring, Acting, Extraversion, and Other-Directedness),
gender, leadership, length of service, deployment, and combat experience
predicted military consumer responses in scenariobased ratings of
liking/disliking of military food, clothing, and equipment products. In
Chapter 1, I discuss the background, problem statement, purpose of the
study, research questions and hypotheses, theoretical framework, nature of
the study, definitions, scope and delimitations, limitations, and significance.
Background
Snyder (1974) suggested that people differ in the degree of self-
monitoring related to executive control and social presentation. Politicians,
for example, were seen to pick up on social cues and engage with their
constituents. Actors observed and reacted to attitudes conveyed by their
audiences. Patients in psychiatric wards lacked social awareness and did not
interact well with others. Self-monitoring theory uses these differences to
predict behavior. DeBono (2006) and others (Hye-Jin et al., 2008; Shavitt et
al., 1992; Slama & Singley, 1996) have reported use of self-monitoring
theory in civilian consumer research. The theory has not been used to predict
military consumer behavior.
Civilian consumer research has shown that high self-monitoring
consumers possess attitudes and behaviors different from their low self-
monitoring counterparts. Differences can be seen in consumer activities. For
example, high self-monitoring consumers make consumer decisions that
help them gain social favor. External circumstances, culture, and audiences
influence high self-monitoring consumers’ attitudes and behavior (DeBono,
2006; Slama & Singley, 1996). The term “audiences” is used because high
self-monitoring consumers tend to perform for their audience (others they
desire social reward from). Their actions can seem chameleon-like as they
possess a persona adapted to appeal to various audiences. The appeal effort
may be directed to those who see the way they dress, the cars they drive, the
homes they live in, the food they buy, and other types of consumer behavior.
When dining, an audience might be dining companions. When purchasing a
car, an audience may be work clients, esteemed colleagues, supervisors,
romantic interests, family members, or others a high selfmonitoring
consumer wants to impress.
Low self-monitoring consumers are driven differently. Instead of a
changing external audience, the more constant internal audience of “self”
matters. The low selfmonitoring consumer looks at her/himself and adjusts
consumer behavior to be congruent with the attitudes and behaviors of the
persona of who they think they are. Low selfmonitoring consumer behavior
is more consistent and predictable. Nantel and Strahle (1986) demonstrated
this concept. Consumers were privately asked about their interest in music
types and their intentions to buy music. Later in the study, the consumers
were afforded an opportunity to receive significant discount coupons for
music they had expressed interest in, yet a style of music that lacked uniform
social appeal. To receive the coupons, the consumers simply had to publicly
raise their hands amongst a group of other consumers. All the low self-
monitoring consumers raised their hands and accepted the coupons.
However, less than half of the high self-monitoring consumers were willing
to raise their hands publicly and receive the coupons.
Prior to self-monitoring theory’s introduction, most consumer research
used personal disposition or situational context to examine consumer
behavior. Becherer and Richard (1978) demonstrated that self-monitoring
theory allowed researchers to see consumer behavior differences between
low and high self-monitoring consumers. Low self-monitoring consumers
began to emerge as consumers who made decisions more to reinforce self-
concepts whereas high self-monitoring consumers emerged as consumers
who gave more regard to external social influences and cues (DeBono,
2006).
Consequently, low self-monitoring consumer behavior was more predictable
if a targeted consumer group’s personal values were known, whereas high
self-monitoring consumer groups were more predictable if social and
cultural values were known. Effects have not been seen in all product types.
Products that communicate something about image tend to be those products
where self-monitoring theory is best expressed (DeBono, 2006).
Civilian consumer research based on self-monitoring theory acts as a
springboard to initiate and explore the use of self-monitoring theory in
military consumer behavior. Currently, there are no studies reporting use of
self-monitoring theory to predict military consumer behavior. Therefore, this
research fills a gap by evaluating basic selfmonitoring theory assumptions
with military consumers like those explored in civilian consumer research.
The extent of a military culture’s influence on discriminating factors of self-
monitoring theory have yet to be researched. In this study, I examined the
utility of self-monitoring constructs in military consumer attitudes about
products with assumed meaningful social cues and limited product types.
Differences between military and civilian cultures exist and are not always
known or fully understood (Hajjar, 2014). Selfmonitoring theory helps
explain influences of social cues with low and high selfmonitoring military
consumers. According to Snyder (1974) and DeBono (2006), social favor,
image, and utility mark differences between high and low self-monitoring
consumers. Debono (2006) showed that high self-monitoring consumers
liked certain products more when they were associated with social
prominence. The same products were liked more by low self-monitoring
consumers when associated with quality and pragmatic usefulness.
Military consumers are often issued, rather than allowed to choose,
consumable items. They are also expected to use those items and function as
a team regardless of personal preferences for those items. These two aspects
of consumerism are not typical of civilian consumer behavior. Many such
atypical influences may exist with the military consumer. These differences
might impact military consumer responses differently than civilian
consumers as distinguished by self-monitoring. This research seeks to
understand the theory’s application to military consumers and the extent to
which self-monitoring constructs predict military consumer attitudes related
to scenarios of military products.
Scales (2018) underscored the need for predictive power and
understanding of military consumer motivation factors and dispositions.
Similarly, Major General Cedric T. Wins (2019) recently reaffirmed the
need for military research entities to modernize, adapt, and get more in
alignment with civilian research capabilities. This research helps fulfill that
need in the area of consumer research methods utilizing a new method of
gathering consumer information through application of the self-monitoring
construct.
Problem Statement
Scales (2018) and Wins (2019) encouraged Army researchers to
continue to innovate, make new products, and explore new research
practices to understand soldiers and make products that help them be more
efficient, lethal, and overmatched against adversaries who are constantly
seeking to match or exceed U.S. military soldier capabilities. Those
capabilities fall into an unnecessary deficit when soldiers do not like and
fully use products in their possession. Inefficient military product usage may
reduce morale and create waste and risks to soldier safety (Tassone & Baker,
2017). To address this problem, product developers need to understand
military consumer’s attitudes and behaviors to create products that appeal to
soldiers. Applying self-monitoring constructs to military consumer research
may bridge gaps of understanding about soldiers’ level of liking and use of
military products. One issue is that no data have been reported of
selfmonitoring constructs being used to predict military consumer attitudes
or behaviors. These constructs have been applied successfully to predict
civilian consumer attitudes and behaviors.
Conducting this research with soldier-consumer data using constructs
from selfmonitoring theory fills a gap of understanding about what drives
soldiers’ attitudes of liking about military products. A first step is to apply
self-monitoring theory by testing constructs of self-monitoring with military
consumers and see if those constructs help predict attitudes and behavior.
O’Cass (2000) emphasized the benefit of new knowledge that self-
monitoring theory offered and that it could be very useful in understanding
many consumer behavior issues if researchers would continue to examine
theoretical elements and push for congruency in how self-monitoring is
measured. This research fills an important gap because soldiers’ use of
resources can impact their survival and lethality rates during military
operations. The dynamics of the battlefield have changed significantly over
the last few decades and existing consumer research may not be applicable
in the military culture (Hajjar, 2014; Scales 2018; Wins 2019). A soldier’s
underutilization of military consumable products is based on multiple
factors. Motivational factors related to consumer behavior may be difficult
to pinpoint, however primary motivational factors such as liking a product
are known to drive military consumer behavior (Baker-Fulco, 1995;
Cardello, 1995). This research seeks to fill a gap in the consumer behavior
literature by using self-monitoring constructs to determine the extent to
which soldiers’ degree of self-monitoring is related to liking/disliking ratings
of military products after reading written product scenarios from three
military product categories: clothing, food, and equipment.
Attendant to maximizing soldier lethality and effectiveness is the need
to maximize utilization of products available to soldiers. Products are
underutilized when they are not liked. To increase liking of products, an
associated research problem is that typical self-monitoring assumptions have
not been examined in military consumer behavior research. In this research,
I evaluated typical assumptions with military consumers. Scales (2018)
explained that the military is aligning its research organizations to better use
civilian research efforts. Although the self-monitoring theory has not been
used with military consumers, it is considered an emerging method of
promise in civilian consumer research (Wilmot, 2011). It has been used to
identify motivational differences between low and high self-monitors in
civilian consumer populations and may do the same with military consumer
populations. Too often, food, clothing, and equipment have gone
underutilized because soldiers were not motivated to use them despite the
intended benefits of the items. Self-monitoring theory offers a framework to
evaluate and explain attitudes and behaviors of military consumers.
Social expectation differences between collective and individual
cultures can also elicit different consumer behaviors (Gregory et al., 2002;
Sharma et al., 2010). Military culture is unique and exhibits characteristics
of both individualist and collectivist cultures (Hill, 2015). Teamwork is
fundamental to the military but so is individual character. Soldiers are faced
with significant challenges such as battlefield dynamics, society gender role
expectations, warrior ethos changes, and ever-increasing complexity of
military operations and rules of engagement (Dunivin, 1994; Hajjar, 2014;
Lawrence, 2011). These conditions put soldiers in a unique group of
consumers whose consumer choice context is different from that of typical
civilian consumers (Hill, 2015). Self-monitoring theory is based on social
expectations which are impacted by culture. Testing similar assumptions of
civilian and military consumers may reveal military consumer motivations
and the validity of assumptions used by researchers.
Self-monitoring theory has been used with civilian consumer
populations successfully to discriminate liking of products. Constructions of
the theory have shown predictive power for various products in branding
influence on high and low selfmonitoring groups. Individual differences
between low and high self-monitoring personalities cause different
responses to product branding attempts (DeBono, 2006). Self-monitoring
theory was anticipated to explain motivations and why some products are
better received by military consumers.
Purpose of the Study
For this study, I used a quantitative, nonexperimental, correlational
design to analyze archival survey data. The purpose of this study was to
determine the extent to which self-monitoring constructs (i.e., Self-
Monitoring, Acting, Extraversion, and OtherDirectedness) and specific
demographic variables (i.e., gender, leadership, time in service, deployment
experience, and combat experience) predicted military consumer ratings
(i.e., liking/disliking). The relevance was that self-monitoring research could
open new avenues to predict attitudes and behaviors of military consumers
towards products and make them more desirable.
Research Questions
The research questions and the hypotheses for this study included the
following:
Research Question 1: To what extent does gender relate to military
consumer liking/disliking ratings (as measured by a 9-point Hedonic scale)?
H01: Gender is not a significant predictor of liking/disliking ratings by
military consumers.
H11: Gender is a significant predictor of liking/disliking ratings by
military consumers.
Research Question 2: To what extent does the military consumer
profile attribute of rank/grade (labelled as leader vs. nonleader) relate to
military consumer liking/disliking ratings?
H02: Leadership role is not a significant predictor of liking/disliking
ratings by the military consumer.
H12: Leadership role is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 3: To what extent does the military consumer
profile attribute of years of service relate to military consumer
liking/disliking?
H03: Years of service is not a significant predictor of liking/disliking
ratings by the military consumer.
H13: Years of service is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 4: To what extent does the military consumer
profile attribute of deployment experience relate to military consumer
liking/disliking ratings?
H04: Previous deployment is not a significant predictor of
liking/disliking ratings by the military consumer.
H14: Previous deployment is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 5: To what extent does the military consumer
profile attribute of combat experience relate to military consumer
liking/disliking ratings?
H05: Prior combat experience is not a significant predictor of
liking/disliking ratings by the military consumer.
H15: Prior combat experience is a significant predictor of
liking/disliking ratings by the military consumer.
Research Question 6: To what extent does self-monitoring (total
score) as measured by the Self-monitoring Scale-Revised (SMS-R), relate to
military consumer liking/disliking ratings?
H06: Self-monitoring is not a significant predictor of liking/disliking
ratings by the military consumer.
H16: Self-monitoring is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 7: To what extent does the Acting subscale of the
SMS-R relate to military consumer liking/disliking ratings?
H07: The Acting subscale is not a significant predictor of
liking/disliking ratings by the military consumer.
H17: The Acting subscale is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 8: To what extent does the Extraversion subscale
of the SMS-
R relate to military consumer liking/disliking ratings?
H08: The Extraversion subscale is not a significant predictor of
liking/disliking ratings by the military consumer.
H18: The Extraversion subscale is a significant predictor of
liking/disliking ratings by the military consumer.
Research Question 9: To what extent does the other-directedness
subscale of the
SMS-R relate to military consumer liking/disliking ratings?
H09: The other-directedness subscale is not a significant predictor of
liking/disliking ratings by the military consumer.
H19: The other-directedness subscale is a significant predictor of
liking/disliking ratings by the military consumer.
Theoretical Framework
Self-monitoring theory is based on individual differences in the way
people monitor and express behavior within a social context (Snyder, 1974).
The theory first assumed that self-monitoring was a single categorical trait
(someone was a high selfmonitor or was not). Now, researchers and theorists
lean toward the assumption that selfmonitoring tendencies are multivariate
and exist along a continuum like other personality traits. For example, one
could possess high self-monitoring tendencies in degrees from very little to
very much (Wilmot et el., 2017). Self-monitoring theory says that
selfmonitoring styles are personality propensities towards high or low self-
monitoring. Behavior and attitudes are driven differently between the styles.
High self-monitors have an external focus (concerned with how others
perceive things), whereas low self-monitors have an internal focus
(concerned with self-perceptions). High self-monitors recognize and respond
to social cues and social values as others would see them. With that
perspective, the theory proposed that high self-monitors act in ways to
acquire or
preserve social favor. For example, high self-monitors may express their
motivation to gain social status by acting assertively and telling amusing
sports stories in order to appeal to a crowd of sports enthusiasts from whom
they want recognition. Wilmot et al. (2017) discussed styles of high self-
monitoring. One is acquisitive in nature as it pertains to gains in social
status. Another high-self monitoring style is protective in nature and is
motivated by fear or a desire to avoid a loss of social status. This style of
high selfmonitoring could be expressed, for example, in dressing modestly
and using conservative speech to avoid negative attention from a
conservative group of church goers whose esteem is desired.
Low self-monitors differ in that their focus is inward on their own
selfperceptions. They are not motivated to recognize and respond to social
cues like high self-monitors. Low self-monitoring styles rely on internal self-
concepts and self-identity traits to guide attitudes and behaviors. Low self-
monitors seek to maintain behavioral alignment with their internally held
views and values (Kauppinen-Räisänen et al., 2018; O’Cass, 2000). The
presumption was that self-monitoring constructs would capture differences
in self-monitoring styles and distinguish between low and high self-
monitors.
The general self-monitoring construct identifies both high and low
self-monitors. The construct captures acquisitive and protective styles of
high self-monitoring. Scoring allows low self-monitors to be identified
(Wilmot et al., 2017). An even more finegrained distinction is made for high
self-monitors such that the Acting and Extraversion subdomains are
associated with Acquisitive high self-monitors, whereas the
OtherDirectedness (i.e., desire to please others over one’s own self)
subdomain is associated with Protective high self-monitors. The Acting and
Extraversion self-monitoring constructs both identify high self-monitors
with an Acquisitive self-monitoring style. The Other-Directedness self-
monitoring construct identifies those high self-monitors who are likely to
engage in a Protective self-monitoring style (i.e., they protect themselves
from social status losses). The Other-Directedness style of high self-
monitors includes acts to lose oneself to please others. Actions of this high
self-monitoring style are associated with shyness, low self-esteem, anxiety,
and neuroticism (Wilmot, 2015).
In this study, I looked at military consumer responses to product
scenarios oriented to appeal to social favor or to appeal to product quality
and utility (a focus of low self-monitors). Military consumers rated their
liking/disliking of each of the product scenarios. The theory of self-
monitoring suggests that scenarios with the higher product quality and utility
should appeal more to low self-monitors, and product scenarios with higher
social favor should appeal more to high self-monitors. Self-monitoring
theory provides a framework for comparing motivations inherent in low and
high selfmonitoring military consumers. Self-monitoring theory is discussed
in greater detail in
Chapter 2 along with research applied to consumer behavior.
Nature of the Study
For this quantitative correlational study, I used archival survey data
obtained from active-duty soldiers at Fort Riley, Kansas. There were nine
independent variables used. They fall into one of two independent variable
groupings. The one group of independent variables consisted of four self-
monitoring constructs. These included the general SelfMonitoring scale and
three subscales of self-monitoring (Wilmot, 2015). The three subscales are
Acting, Extraversion, and Other-Directedness. Researchers believe
selfmonitoring theory is not unidimensional and therefore recommend using
subdimensions as well as the entire scale (Lennox & Wolfe, 1984; O’Cass,
2000; Slama & Celuch, 1995; Wilmot, 2015). The other group of
independent variables consisted of demographic attributes often used on
survey forms to characterize military consumers. Those attributes were
gender, leadership roles, service years, deployments, and combat experience.
The dependent variable was the military consumer rating of
liking/disliking for each military product scenario. The choice of factors
used for evaluation was based on the data from an archival data set that was
provided by the Consumer Research Team
(CRT) of the U.S. Army Natick Soldier Research, Development and
Engineering Center.
The data were analyzed with a quantitative, nonexperimental, correlational
design using IBM SPSS Statistics 28.0.1 to calculate descriptive statistics,
evaluate statistical assumptions, and perform standard multiple linear
regression analyses.
Definitions
Self-monitoring—a psychological construct that says individual
differences exist between people in the degree to which they express control
over their self-presentation in public (Snyder, 1974; Wilmot, 2015).
Acting—a psychological construct of self-monitoring that reflects a
person’s proclivity to spontaneous public speaking, acting, and entertaining.
Acting is associated with the ability to lie and present oneself in ways not
congruent with one’s true self
(Briggs & Cheek, 1988; Briggs et al., 1980; Wilmot, 2015).
Extraversion—a psychological construct of self-monitoring that
reflects a person’s social self-confidence and willingness to exert oneself
into social presentation acts such as telling stories, jokes, and being the
center of attention. Extraversion and Acting are moderately correlated and
have positive relations to self-esteem, social competence, and adjustment
(Wilmot, 2015).
Other-Directedness—a psychological construct of self-monitoring that
reflects a person’s willingness to change oneself to suit others. Other-
Directedness is positively correlated with shyness and neuroticism. It is
inversely correlated with self-esteem
(Wilmot, 2015).
High self-monitors—people who monitor and regulate their behavior
to achieve a desired public appearance. High self-monitors are very
responsive to interpersonal and social cues related to situational
appropriateness (Snyder, 1974; Wilmot, 2015).
Low self-monitors—people who are less responsive to social contexts
but instead are more motivated to act in ways that are more in alignment
with internal dispositions and attitudes (Snyder, 1974; Wilmot, 2015). Low
self-monitors tend to be more consistent in their consumer behavior because
product value is placed on quality and utility factors that reinforce internally
held views of self which are less dynamic than social cues and social
environmental factors (DeBono, 2006; Kauppinen-Räisänen et al., 2018).
Military consumer—an active-duty person serving in the U.S. military
who is a user and consumer of military products that are typically issued and
not purchased.
Includes things such as food, clothing and equipment. These types of
products are often provided by the government or “issued” to the military
consumer because of their duties and rank (Baker-Fulco, 1995; Scales 2018).
Leader—military leaders will be based upon their grade. Enlisted
Grade 5 and above, all Officers, and all Warrant Officers will be considered
as leaders. Ranks of
Enlisted Grades 1-4 are not considered leaders.
Deployment—means to have been activated into service as a
scheduled time away from a normal duty station and usually outside of the
United States. But it can also mean 7 months on a ship, 12 months at a
forward operating base or a few months stateside during a natural disaster or
civic distress. Deployment durations can vary and may be for various
situations that involve movement of military personnel and equipment in
preparation for military engagements typically away from peace-time
military locations.
Combat—physical engagement with an enemy, oppositional force.
Typically involving weapons.
Military culture—a pattern of basic assumptions (invented,
discovered, or developed) and used by the military to cope with its
challenges of internal integration and external adaptation related to the
challenges. The assumptions have worked well enough in the past to be
accepted as valid and are taught to new members as the correct way to
perceive, think, and feel relative to challenges faced by military personnel
(Hill, 2015;
Schein, 2010).
Assumptions
Scenario-based surveys with vignettes describing products and
circumstances were assumed able to provide useful military consumer
research data. Evaluations using scenarios and vignettes have been used
previously to present manipulated information to respondents to elicit
responses that provide consumer insights about products (Cardello et al.,
1996; Otterbring & Bhatnagar, 2022; Pitts et al., 1991; Sánchez et al., 2012).
Scenario use in product surveys is considered a valid means to conduct
research (Otterbring & Bhatnagar, 2022; Robinson & Clore, 2001).
The three product types (i.e., socks, snacks, and ammo magazine)
were assumed adequate to represent military consumer products and yield
meaningful results because they are frequently used by soldiers. They also
represent major product categories (i.e., clothing, food, equipment) often
used in civilian self-monitoring research (DeBono, 2006; DeBono & Rubin,
1995; Hogg et al., 2000; Hu & Parsa, 2011; Lovaas, 2020; O’Cass, 2001;
Shavitt et al., 1992; Snyder & DeBono, 1985). In prior studies, written
product scenarios were manipulated to appeal to low or high self-monitors.
For example, Hogg et al. (2000) created various scenarios for consumers to
consider and then evaluated aspects of adult beverages. Specific aspects of
the adult beverages were written to appeal to a positive or negative social
image, after which the beverage evaluations were compared and
demonstrated differences between low and high self-monitoring consumers.
Generally, clothing, food, and equipment products have resulted in
consumer attitude and behavior differences between low and high self-
monitoring consumers if some social image conveyance was related to the
use of those items. Equipment items that are strictly utilitarian in nature
usually are rated similarly for quality between low and high self-monitors.
This was the case with air conditioners (Shavitt et al., 1992). It is assumed
that the scenarios used in this research appeal to a positive or negative social
image and thus will evoke different response ratings of liking between low
and high selfmonitoring military consumers. The details of the manipulated
product scenarios are discussed in Chapter 3.
A final assumption was that the archival data collected from
respondents included honest responses not influenced by data collection
methods. Those administering the surveys were skilled practitioners of the
process. The anonymous nature of the data does not allow follow-up
confirmation or further questions.
Scope and Delimitations
To support soldier lethality and efficiency by improving liking of
military products, the aim of this consumer research was to predict military
consumers’ liking of socially favorable and unfavorable scenarios of socks,
snacks, and ammo-magazine complaint resolutions. More specifically, I
determined the extent to which selfmonitoring constructs (i.e., Self-
Monitoring, Acting, Extraversion, and OtherDirectedness) and demographic
variables (i.e., gender, leadership, length of service, deployments, and
combat experience) predicted liking/disliking ratings of military products.
Archival data included soldier evaluations of six scenarios with
products and consumer complaint choices where the dependent variable was
the degree of liking on a 9-point Likert-type scale. Product scenarios were
written to appeal to low or high selfmonitoring traits. No products were
directly used or evaluated. Rather, soldiers read written scenarios about the
products. The study did not attempt to compare or test cultural differences
between military and civilian consumer populations.
This study focused on the consumer dependent variable referred to as
“liking.”
Degree of liking is a common consumer indicator associated with consumer
products (O’Sullivan, 2017). Other consumer variables such as cost,
convenience, and availability were not considered in this research.
The respondents were from combat units stationed at Fort Riley,
Kansas, USA in 2013. The sampling was intended to be a convenience
sampling. Convenience sampling is commonly used in military consumer
studies due to the need to minimize interference in training regimens and to
respect the soldier’s privacy and agency. Soldiers are controlled to the
degree that they can be required to receive briefings. But after being briefed
on the study, they were then given a choice whether to participate or not.
Limitations
This research included a convenience sample (i.e., sampling based on
selfselection). Thus, the sample may not be representative of the population.
This may limit my ability to make generalizations and inferences about the
entire population. The target population was combat arms personnel on foot
or mounted on vehicles. This population of soldiers may also demonstrate
different tendencies than soldiers in noncombat arms positions. The survey
site location was geographically in the Midwestern United States and did not
include any other military sites. Sampling and data collection occurred over
a 2-week period on the Fort Riley installation at various sites, in moderate
weather conditions, and during standard training events. The results may not
be generalized across multiple environmental conditions or locations.
Scenario-based surveys also have limitations. Some of these are
ecological limitations. For example, text-based shopping scenarios have
been shown to have less real-world generalizability compared to observable
behavior from actual contexts (Otterbring et al., 2022). The use of scenarios
may have unanticipated effects different from those for actual product use
since scenarios themselves are not true experiments with actual product
being examined.
Time and funding constraints available at the time of the evaluation
limited the extent of the data collection. Only three product categories were
used (food, clothing, equipment). Two scenarios were used for each product
category. In each category, one scenario was written to appeal to low self-
monitoring traits and the other scenario was written to appeal to high self-
monitoring traits. Two sample scenarios for each product category (one
socially favorable, the other not) may not be sufficient to fully explain
selfmonitoring’s effects within each product category. However, the survey
was five pages long and survey fatigue was a concern. The decision to not
add more scenarios was considered an acceptable risk.
Another limitation was that there was no validity check of the written
product scenarios. The product scenarios were written to appeal to low and
high self-monitoring traits. However, there was no data demonstrating the
validity of the written scenarios. Though undesirable, this limitation is
considered an acceptable short-coming because the wording of the scenarios
was written to specifically appeal to main construct elements of
quality/utility (low self-monitors) and social favor (high self-monitors). In a
review of the scenarios designed to appeal to the high self-monitoring group,
an obvious appeal to a sense of social favor was made. For example, specific
phrases were used such as: “wearing these socks usually invites praise from
your peers,” “this snack is popular and praised by some people you know,”
and “leaders and peers … will think well of you.” Other scenarios
emphasized quality and utility with statements such as: “functionally above
average,” “greater nutritional value than most MRE snacks,” and “strong
resolution chain … works effectively.”
Another limitation pertains to the use of correlational designs.
Correlational assessments can measure relationships between two or more
variables, but one cannot conclude from those relationships that there are
causal relationships between the variables. Causal effects may exist but to
infer they exist requires a true experiment. For example, suppose research
demonstrated higher self-monitoring scores were positively and significantly
correlated with higher liking ratings of stylish socks. A true experiment with
controls and manipulation of independent variables would be needed to
confirm a cause-and-effect relationship was driven by the independent
variables.
Significance
The results of this study determined the relative strength of
relationships between different self-monitoring styles and military
consumers’ liking of military products under certain conditions. The study
served to identify which self-monitoring styles to follow up on with further
research. The study confirmed usefulness of self-monitoring theory
constructs in predicting military consumer behavior. Ultimately, this
research may lead to new strategies in the development, packaging, and
marketing of military products.
Potential benefits also included increased soldier morale and positive social
change for the military culture’s approach to consumerism. Increased
consumer behavior knowledge leads to improved product designs and
training relative to the use of such products. These refinements increase the
efficiency of soldier performance and resource management.
Summary
Self-monitoring theory provides a framework to understand military
consumer attitudes and behavior relative to low and high self-monitoring
tendencies. Selfmonitoring theory’s relative value to military consumer
research had not been tested. This study filled a gap in the literature on
consumer research for military consumers using self-monitoring constructs.
High self-monitors pursue social favor in consumer choices. Low self-
monitors make consumer choices based on functional quality that supports
their self-identity. The purpose of this study was to assess the extent to
which self-monitoring constructs predicted military consumer liking of
military products. Results of this study may lead to positive social change by
providing military consumer knowledge used to enhance liking of military
products that improves product use and soldier morale. Improved liking also
leads to reduced waste of military resources. Chapter 2 provides a review of
the theoretical foundation and practical applications of self-monitoring
theory with examples of consumer research that used the construct to
understand consumer behavior.
Chapter 2: Literature Review
Warfighters who underutilize products like food, clothing, and
equipment increase threats to their safety from adversaries, reduce their
effectiveness in carrying out their duties, and waste resources (Ahmed et al.,
2017; Baker-Fulco, 1995; Hirsch et al., 2005; Kullen et al., 2016; O’Leary et
al., 2020; Tassone & Baker, 2017). Army researchers are charged with
developing and providing optimal products that increase warfighters’
lethality and effectiveness (Scales, 2018; Wins 2019). The purpose of this
study was to determine the extent to which self-monitoring constructs (i.e.,
SelfMonitoring, Acting, Extraversion, and Other-Directedness) and specific
demographic variables (i.e., gender, leadership, time in service, deployment
experience, and combat experience) predict military soldiers’ ratings
(liking/disliking) of military products. This can be done by adopting new
consumer research tools such as those based on selfmonitoring theory.
Underutilization of food is a dilemma that illustrates the relevance of the
problem.
This common problem persists across many militaries around the world
(O’Leary et al., 2020). The underutilization of rations is associated with
reduced performance, weight loss, and increased health vulnerability
(O’Leary, et al., 2020). One of the causes for the underconsumption has
been that the products simply were not liked. But liking is not a univariate
problem (such as physical flavor). Liking is considered contextually related
to various factors and expectations of the soldiers (Baker-Fulco, 1995).
Soldiers have repeatedly not eaten enough food even when there was an
abundance of food (BakerFulco, 1995; Cardello, 1995). In an overview of
military dietary intakes during military exercises, six studies spanning 5
years listed an average soldier energy expenditure of 4,319 kcal/day (Baker-
Fulco, 1995). At the same time, average intakes were 2,840 kcal/day,
leaving an average energy-expenditure deficit of 1,479 kcal/day. That
translates to a loss of nearly 3 pounds of body fat per week, which exceeds
healthy weight-loss recommendations of the National Institutes of Health
and is a rate that over time leads to a loss of muscle mass and performance
ability (Nesheim et al., 1995). Other researchers reported daily calorie
expenditures of very active soldiers to be over 6,000 kcal/day (Ahmed et al.,
2017). The U.S. Surgeon General recommended that military meals
contribute 3600 kcal/day for active young male soldiers (Hirsch et al., 2005).
When consumption deficits occur over a prolonged period, it is detrimental
to health and performance (Tassone & Baker, 2017). Some of the deficits are
attributed to disliking products, supporting the need to increase product
appeal where possible.
Self-monitoring theory can address the issue in part. It describes
individual differences in self-expression where high self-monitors, seeking
others’ approval, will comply with situational norms whereas low self-
monitors seek to maintain internally held self-identity values. Understanding
the role of social and self-identity values to different consumers helps
researchers use factors of liking in product designs to make them more
appealing. This research offered a chance to fill a gap in understanding about
what drives soldiers’ liking preferences with the aim of fostering better
utilization of military products.
Chapter 2 reviewed the literature related to self-monitoring theory and
consumer research and some of the attendant problems in conducting that
research. Studies that have applied self-monitoring were reviewed. This was
followed by an exhaustive review of the literature related to self-monitoring
in civilian consumer behavior, consumer research and information related to
military consumer behavior, and self-monitoring as it may related to military
consumer behavior. The chapter ends with a summary and conclusion.
Literature Search Strategy
The strategy used to conduct the literature search included the use of
multiple data bases and search engines. These included Walden Library’s
collection EBSCO, PsycINFO, PsycARTICLES, SAGE Premier, Google
Scholar (linked with Walden), Purdue OWL, Walden’s Thoreau, PubMED,
PsycEXTRA, MEDLINE, PsycTESTS, APA PsycNET, ISI web of
knowledge (Reuters Web of Science), ORCA (Cardiff University), ILLIAD
interlibrary loan system, R&E Gateway (DoD research), and ScienceDirect.
Additional resources included the Alvin O. Ramsey library at U.S. Army
NSRDEC, the National Archives, and Brigham Young University library.
Initially, the literature search included all years from 1974 to the present
with the key words: selfmonitoring scale, military, leader, soldier, self-
monitoring axis, consumer, behavior, prediction, food, liking, acceptance,
self-monitor, theory of self-monitoring, selfmonitoring, and personality.
After reviewing the literature from those searches and the seminal writings
of Snyder (1974), Snyder and Gangestad (1986), and Gangestad and Snyder
(1985, 2000), further searches included following the citation trails of the
works cited within those seminal works and other key word combinations
such as purchasing behavior, product, or advertising with self-monitoring.
Key words provided in these resources included: self-monitor, military,
consumer, mindset, signaling, cues, behavior, culture, individualist,
individualistic, collective, self-identity, self-expression, socialidentity,
implicit theory, functional theory, individualism, acquisitive, protective,
alternative bivariate model, and self-identity. Additional searches focused on
2010 to the present.
Theoretical Foundation
The theory of self-monitoring proposed by Snyder (1974) was
introduced to explain individual differences of self-control in expressive and
self-presentational behaviors related to social situations (Fuglestad &
Snyder, 2009). Snyder (1974) recognized that actors and politicians had an
ability to create audience appeal by being attentive and responding
expressively to social cues such as body language, facial expressions, and
voice. This recognition helped Snyder develop and propose the theory.
Surveys conducted with Stanford University undergraduates, professional
actors, and psychiatric patients provided initial evidence that self-monitoring
was tied to individual differences where high self-monitors could express
emotions that were sensitive and appropriate to social cues. Low self-
monitors were lacking in this regard. Their expressions instead appeared
controlled from within based on their experience rather than interpersonal
conditions of social appropriateness (Snyder, 1974).
Eric Goffman influenced Snyder’s theory development (Snyder,
1974). Goffman (1959) advanced the concept of self-presentation as a type
of character portrayal whereby expressive control was used to manage social
impressions. In self-monitoring, the general concept was that high self-
monitors’ dispositions would lead to predictable behaviors because of social
circumstances. High self-monitors acted as social chameleons, responding to
social cues in order to win social rewards. Low self-monitors, less concerned
with winning the approval of others, sought to act in harmony with their own
internal self-concepts, making it harder to predict their attitudes and
behavior (Snyder, 1974).
After Snyder (1974) introduced self-monitoring theory, considerable
effort was expended by researchers for the next 40 plus years clarifying
nuances in meaning as pertains to low and high self-monitors (Briggs et al.,
1980; Briggs & Cheek, 1988; Gangestad & Snyder, 1985, 2000; Lennox &
Wolfe, 1984; O’Cass, 2000; Snyder & Gangestad, 1986; Wilmot, 2011,
2015; Wilmot et al., 2017). In that period, selfmonitoring evolved from its
original conception as a categorical trait to a continuous personality trait
(Wilmot, 2015). Low self-monitors focused on maintaining congruity
between their behavior and their internal self-concepts (Aaker, 1999; Kwak,
2021) whereas high self-monitors were sensitive to social cues and adept at
responding to situational demands in order to acquire or maintain social
influence (KauppinenRäisänen, 2018; Kwak, 2021). High self-monitors
were thought to be of two types: acquisitive self-monitors sought social
influence, praise, and status, whereas protective self-monitors sought to
avoid reprisal, criticism, or negative social attention (Wilmot, 2015; Wilmot
et al., 2017). These two tendencies were referred to as the bivariate model of
acquisitive and protective self-monitoring. Self-monitoring subscales offered
an even more fine-grained distinction between the two high self-monitoring
types: Acquisitive self-monitors were characterized as actors (i.e., likes and
is good at entertaining) and extraverts (i.e., is sociable and assertive;
Gangestad & Snyder, 2000; Wilmot et al., 2017). On the other hand,
protective self-monitors were characterized as other-directed (i.e., seeks to
please others).
As a personality trait, self-monitoring offers predictable and
measurable consumer information that can guide product development and
marketing by linking product image to preferences associated with
differences between high and low self-monitors. For example, to appeal to
high self-monitoring consumers, a high-profile person could be shown
making a public purchase from a known, environmentally responsible
company. Marketing agents could highlight the company’s environmental
activity and have the high-profile person mention the social responsibility
practiced by the company as the reason why she/he shops there. Then
marketing could show the high-profile person being admired by others as a
patron of a socially responsible company. Because the low selfmonitor’s
product choices will necessarily align with their self-perception, appealing to
the low self-monitoring consumer can be difficult if the consumer’s self-
image and personal values are not known. Focus groups of targeted
customers may help reveal this. Otherwise, it is generally safe to emphasize
the quality aspects of the product being sold as low self-monitors tend to
value product quality and focus on those product attributes to determine
interest. The social aspects are likely to have little effect on them.
Recent research examined both aggregate (i.e., the general self-
monitoring scale) and parsed self-monitoring datasets (i.e., the Acting,
Extraversion, and Other-Directed subscales). Fuglestad et al. (2019) aimed
to determine whether self-monitoring is best understood as two or more
separate and distinct self-monitoring types. Their research examined
participants’ motivations in interpersonal relationships through self-
reporting questionnaires and self-monitoring measures. Using an adult
attachment questionnaire (Simpson et al., 1996) and Experiences in Close
Relationships, Relationship Structures scale (ECR-RS; Fraley et al., 2011),
Fuglestad et al. found significant differences between acquisitive and
protective self-monitoring and their relationships to significant others (i.e.,
parents, best friends, romantic partners). Essentially, those high in protective
self-monitoring were found to express more avoidance, anxiety, and general
uneasiness with intimacy. Fuglestad et al. also noted that a reliable (but
weak) relationship between self-monitoring and gender and age was seen
such that acquisitive and protective selfmonitoring tendencies were more
prevalent for males and younger study participants. These results
demonstrated how high self-monitoring consumers were motivated in close
relationships differently when viewed using Acquisitive and Protective self-
monitoring scales. Those motivations influenced the way they interacted in
relations with people they deemed important. Understanding self-monitoring
subdomains helped distinguish interpersonal motivations.
Wilmot (2015, 2016) and others (Fuglestad et al., 2019; Pillow et al.,
2017) made a case for studying self-monitoring as a multidimensional
construct. To better predict soldier behaviors and capture moderating effects
of self-monitoring, the multidimensional nature of self-monitoring must be
understood. Wilmot’s 2015 report helped the field of self-monitoring move
forward and embrace a view that self-monitoring is more valuable as a
multidimensional rather than univariate trait. Use of the subdomains was
shown to help researchers better identify the motivating elements in
behavior. Researchers who
rely upon Wilmot’s (2015) alternate bivariate model or at least view self-
monitoring multi-dimensionally, will want to parse their data to determine if
high self-monitoring behavior is more acquisitive or more protective in
nature. Wilmot et al. (2017) concluded that past findings in self-monitoring
research and theoretical progress can now be largely attributable to
acquisitive self-monitoring. Wilmot et al. pointed out that too little attention
had been given to analyzing self-monitoring’s subdomains. For purposes of
this research, the global Self-Monitoring construct and its three subscales
(i.e., Acting, Extraversion, and Other-Directedness) may contribute
information that help explain military consumers’ failure to fully utilize
products.
Self-monitoring theory has been used often to explain behavioral
differences across various contexts. One reason for varying appeal suggested
by Kardes et al. (1986) dealt with choice-making processes. They
hypothesized that low self-monitors form attitudes differently from high
self-monitors. They compared low and high selfmonitoring groups using
object-evaluation associations that are more easily and quickly accessed
from memory. Object-evaluation associations included relationships where
attitude objects such as bombs, war, pizza, beer, and taxes were related to
attitudes of good and bad. Examples included bombs-bad, war-bad, pizza-
good, beer-good, taxesbad, and so forth. As attitude-object words emerged
on a computer screen, people would respond “good” or “bad” to the word as
quickly as they could determine the objectattitude relationship. The
researchers measured latency of responses to inquiries about an attitude
object. Participants were 34 students who responded in three sessions (a 1-
hour session for each of the 3 weeks). Recognition timing of 125 attitude
objects revealed that low self-monitors were faster at responding, indicating
relatively more accessible attitudes. Internal consistency was good. The
average of the accessibility scores was used to compare low and high self-
monitors. Kardes et al. (1986) reasoned that low-self monitors’ internal
values were already reviewed and in place, so they did not rely upon an
external assessment of the social conditions to make a choice. They also
reasoned that delayed decision-making for high self-monitors was
moderated by the importance of the decision (e.g., when participants were
led to expect that the experimenter would review their data or not review it
afterwards).
Consumer product evaluations have been difficult to interpret when
test product images lacked saliency and congruency with consumer
expectations (Pillow et al., 2017). Studies have found that acquisitive self-
monitoring was more prevalent and more influential than protective self-
monitoring (Wilmot et al., 2015). When conducting consumer research
where product image is presented, products have greater appeal when a
salient image is congruent with a salient, value-constructed goal or need.
Those needs can be derived from the consumer’s self-monitoring style. For
example, acquisitive selfmonitors value social status and protective self-
monitors want to avoid negative social consequences. Depending on the
targeted customer, marketing cues should align with those acquisitive and
protective values in salient ways that accentuate product value to the
targeted consumer’s value system (Lee & Shavitt, 2006).
Czellar (2004) sought to determine whether the attitude accessibility
hypothesis or the alternative self-presentation hypothesis would better
explain the latency task response differences of low and high self-monitors.
Czellar found a similar effect to Kardes et al.’s (1986), demonstrating that
when persons were tasked to respond in high motivation conditions (i.e.,
they knew that their responses would be reviewed and discussed with others
as opposed to low motivation conditions where they knew their responses
were anonymous), the high self-monitor had longer response latencies than
did the low selfmonitor. Using the implicit association test (Greenwald et al.,
1998), Czellar noted that high self-monitors deliberated more in certain
attitude-response tasks. A longer response for high self-monitors was found
for high-motivation conditions. This contrasted with DeBono et al.’s (1995)
related work that found no significant difference between low and high self-
monitors. However, that work used group sessions that minimized the high
motivation condition.
The differences seen by both Czellar (2004) and Kardes et al. (1986)
suggested that when more cognitive resources are needed, responses to
consumer decisions will take longer. High self-monitors with social
ramifications at stake are in a condition of “higher motivation.” High self-
monitors appeared to consider more information that led to slowed
responses. They also appeared to invest more time because they naturally
looked at social factors with added regard for deeper levels of consideration
to the greater number of implications and concern for achieving desirable
social consequences. Czellar concluded that in conditions of high
motivation, high self-monitors deliberated more than in low-motivation
conditions where high and low self-monitors compared similarly. Czellar
said that like explicit cognition tasks, there was strong evidence that implicit
cognition tasks were sensitive to the effects of self-presentation under lab
conditions with high self-monitors who acted with expressive control over
their behavior.
Other influences on self-monitoring and consumer behavior worth
mentioning include a product’s intended use, context of use, frequency of
use, whether the product is used in public or in private, and other aspects of
functionality that tie into functional theory. Functional theories (Katz, 1960;
Smith et al., 1956) suggested attitudes serve a functional purpose. In
consumer behavior, that means the attitudes provide meaning and mental
classification for a product’s value and use. The product’s function needed
to align with or be congruent with an attitude. These thought process
connections were deemed fundamental to how self-monitoring theory was
operationalized in consumer behavior. Product conveyances that were salient
and congruent with notions of self would be expressed for low self-monitors.
Product conveyances that were salient with congruent notions of social
approval would be expressed for high self-monitors. A few other points that
influence self-monitoring theory are worth a brief mention.
Whenever consumers evaluate products, they use decision-making
strategies (Bettman et al., 1998). When consumers consider their identity,
they use a self-appraisal process that also involves a strategy of
identification. This strategy involves mediation between social presentation
and self-definitions (Laverie et al., 2002). Disruptions to those strategies
may occur at any point through priming. Priming may appear in the form of
advertising or through other means that redirect a person’s attention. Further
discussion of priming and self-identity is discussed in the next section. One
outcome of the redirection is that it leads to inconsistency between consumer
choices and attitudes. Strength and type of cue can trigger behavior related
to the consumer’s redirected attention and different versions of self
(interdependent vs. independent or utilitarian vs. social identity). Those
views influence the expressions governed by self-monitoring. As per self-
monitoring theory, if marketing efforts trigger a social identity focus on self,
a high self-monitor is more likely to view the product in terms of how it will
help them achieve social influence.
Literature Review Related to Key Variables
Self-Monitoring and Civilian Consumer Behavior
Value in the Consumer Mind
Finding what the consumer values in a product is critical to addressing
better product utilization challenges among military consumers. Using self-
monitoring theory in consumer research enables researchers to understand
motivating factors for consumer behavior. Understanding those factors
allows product developers to appeal to them through the products they offer.
Applications of self-monitoring theory in civilian consumer research have
increased understanding of motivating factors in the civilian consumer sector
(DeBono, 2006; Kudret et al., 2019). Applications using protective
selfmonitoring are more limited historically. Insights are expected from
greater use of acquisitive and protective self-monitoring (Lovaas, 2020;
Wilmot 2017).
According to Shavitt (1989), there are two functions that distinguish
low and high self-monitors. They are utility for low self-monitors and social
identity for high selfmonitors. Low self-monitoring consumers fall under a
private identity, utilitarian function that is quality based, whereas high self-
monitoring consumers fall under a social identity, situational function that is
image based. Functional theories suggest that marketing messages are
persuasive to the extent that they align with an attitude’s functional
underpinnings, meaning that low and high self-monitors could hold equally
favorable but differently derived attitudes towards products. Shavitt et al.
(1992) looked at products with clear utilitarian functions, products with clear
social identity functions, and products spanning both functions to see if low
and high self-monitoring attitude differences would emerge. Consumers
involved in the study described their attitudes about various products;
descriptions were coded and evaluated for social identity (products that were
primarily image enhancing), utilitarian (products that primarily fulfilled a
functional or utility purpose), and multiple function (products that could
fulfill both image enhancing and utilitarian perceptions). Consumers also
wrote advertisements for products and their arguments were evaluated. For
social identity products, high self-monitors used social terms (e.g., “don’t be
left out,” “stylish,” and “loyalty”) and less utilitarian terms (e.g., “sour,”
“durable,” and “over-priced”) to describe the products. Low self-monitors
used more quality-based thoughts, whereas high self-monitors’ attitudes
were influenced by image-based thoughts.
Though the basis of their attitudes differed, low and high self-
monitors held equally favorable attitudes with advertising of products that
appealed solely to utilitarian or social identity products (e.g., air conditioners
and aspirin or class ring and flag, respectively). It is logical to assume that
by refining one’s understanding of the notions of self and the constructive
processes consumers used for basing their attitudes and decision making,
there would also be an opportunity to increase understanding of the
motivational underpinnings behind self-monitoring (Bettman et al., 1998).
These processes have differed between individualist and collectivist cultures,
the latter being where norms work better (Shavitt & Nelson, 2002).
Markus and Kitayama (1991) provided a clear narrative on
individualistic vs.
collectivistic cultures and the culture’s impact on thinking, cognition, and
notably for this discussion—self. Because of the relationship between self-
concept and self-monitoring, it is important to account for the impact things
like culture, context, and indoctrination may have on self-conceptualizations.
Their findings of collective cultures indicated that views of self being
interdependent on each other were a hallmark of collective cultures. Those
views included the fundamental relatedness of individuals to each other.
They emphasized harmonious interdependence, fitting in, and attending to
others. Whereas the individualist self-view was based on discovery of self,
expressing one’s unique inner attributes, and maintaining one’s
independence from others by attending to the self. Markus and Kitayama
believed that self-construal differences impacted cognition and the way high
self-monitors were motivated and made decisions. They even questioned the
ability to use self-monitoring across cultures because of those differences.
Things such as culture that impact the notion of self are important
considerations in self-monitoring theory because a consumer’s view of self
appears to mediate behavior related to selfmonitoring (Markus & Kitayama,
1991). The different notions of “self” can help explain some of the mixed
results found in self-monitoring literature. Certainly, there are influences
military culture has on aspects of self that need to be considered through the
lens of self-monitoring to obtain a better understanding of military consumer
behavior.
Researchers have sought to understand the values motivating
consumers. Kardes et al. (1986) discussed consumer choice-making thought
processes. Such processes included consumers’ views of themselves.
Delayed choice responses were seen in high self-monitors and attributed to
the additional cognitive load of considering how others might perceive them.
Whereas primary decision factors of low self-monitors were based on
already developed self-perception models that allowed them to have faster,
more easily accessed cognitive processes.
Constructions of self-monitoring theory tap into consumer motivations
related to consumer self-concepts. These are integral to building a
consumer’s value proposition for goods and services. When consumers
develop a value proposition, they appraise a product’s value by considering
product attributes that are salient to them (Lee & Shavitt, 2006; Shavitt et
al., 1992). Some products convey salient meanings that cause consumers to
feel good and validate perceptions of self-worth. A consumer’s source of
self-esteem and self-worth provide motivation and logic to the consumer
about how, where, when, and why a product has worth. Those sources differ
for low and high self-monitors. Low self-monitors focus on intrinsic sources
like self-identity and quality of products and behavior that are congruent
with that self-identity. High self-monitors may likewise use intrinsic sources
for utilitarian items, but they also focus on external sources (people they
esteem, social approval, etc.) for products that can provide social identity
benefits. Consumer products and services can convey a variety of meanings
and images such as simple utilitarian functionality, elite public social
personas, and privately held value symbolisms. The conveyances appeal in
different ways to low and high self-monitors.
According to Hogg et al. (2000), a product’s symbolic meanings influence
the consumer’s evaluation and choice of products. Hogg et al. developed a
conceptual model that illustrated how self-esteem and self-worth are
maintained and supported differently for low and high self-monitors. Their
evaluations of consumer products led them to acquire products that reinforce
self-identity and self-worth. The low self-monitor’s path to self-worth is
through self-identity. The high self-monitor’s path includes social identity.
Consumer tendencies and perceptual abilities are individualized and
limited (Buschman et al., 2011, Miller, 2020, Rigotti et al., 2013).
Consequently, a consumer’s ability to focus on product attributes is also
limited. Attributes that do catch the consumer’s interest are associated with
the consumers’ self-identity which acts as a guide for attaching value to a
product. Other researchers have modeled consumer thought processes.
Kleine et al. (1993) conceptualized a consumer appraisal process model that
includes emotional and cognitive components. The process model stated that
ordinary consumer consumption activities could be organized and
understood through selfdefinition (Laverie et al., 2002).
Self-identity is influenced by things like employment, gender,
physical appearance, race, and culture. And according to the model of Hogg
et al. (2000), social identity functions of low and high self-monitors can
function on entirely different mental pathways. This matters for this study
because identity functions might be very different between groups of people
who have strong cultural differences. Military culture has strong cultural
differences. For example, the military does not operate the same way as
civilian legal systems of constitutional law. They instead operate somewhat
as a distinct society governed by their own criminal code (Beaumont, 2009).
They have a Uniform Code of Military Justice (UCMJ) that holds them
accountable and can impose severe penalties for violations of military law.
According to Hogg et al. (2000), strong cultural differences should be
possible to discriminate using self-monitoring. Using research and
knowledge explained by the model, developers should be able to tailor and
market products and services that appeal to the respective social identity
functions that can vary between low and high self-monitoring military
consumers. This is done by creating valued and salient product images that
appeal to the salient identity functions characteristic of low and high self-
monitoring military consumers.
Saliency of product image and self-image of the consumer are
important factors to consider when looking to observe self-monitoring
effects. A salient product image relevant to the consumer allows high self-
monitoring consumers to perceive a social benefit to be derived from use of
a consumer product when others see them using it. Likewise, a tailored
image allows the low self-monitoring consumer to see a benefit when the
image reinforces internally held self-identity views. Lee and Shavitt (2006)
demonstrated that store reputation and product image carried different
weights depending on their context and relevance to the consumer. Saliency
of conveyed images coupled with relevance to the consumer distinguished
low and high self-monitors, especially when goals were in alignment with
those images.
Goals often differ between low and high self-monitoring consumers.
For low selfmonitoring consumers, alignment of salient self-identities with
salient images conveyed through consumer products and services allowed
self-monitoring theory to be useful in making predictions of consumer
behavior more easily (Graeff, 1996; Lee & Shavitt, 2006). For high self-
monitors, the salient self-identity may not matter if the social identity
function is fulfilled. Failure to provide products that have saliency and
congruency between low self-monitor consumer self-views or high self-
monitor consumer views of social value, cause self-monitoring guided
efforts to fail or lack consistency (Hogg et al., 2000).
Even if a consumer has a clear self-view and consumer behavior very
much in alignment with motivations supporting that view, a researcher’s
wrong assumptions about the motivations of the consumer can yield mixed
results due to poor experimental design measures. At other times, the wrong
assumptions become learning points. For example, researchers studied high
self-monitoring consumers to understand consumer complaint processes and
wrongly assumed that high self-monitors from both cultures would share the
same aversion to complaining in public. The researcher’s hypothesis failed
because the two cultures esteemed public behavior differently. Nevertheless,
researchers were able to determine that high self-monitors from a Western
culture sought public esteem by complaining publicly. Consumers in Asian
culture sought public esteem by not complaining publicly (Sharma et al.,
2010). Such assumption failures are understandable when one considers the
complex and dynamic nature of how consumers evaluate products over a
broad set of dimensions within a malleable self (Aaker, 1999).
When using self-monitoring, the idea of a malleable self needs to be
factored into a consumer’s thinking of value. Factors like environmental
priming can change the saliency of social identity goals (Lee & Shavitt,
2006). When this happens, consumer decisions can be made with a view of
self that is temporary or altered from a predominant state. Aaker (1999)
described the self as being relatively stable even though it is malleable and
subject to situational conditions. Aaker showed a significant difference
between low and high self-monitors’ attitude effects based on different
forms of priming. Low self-monitors attitudes improved when a brand’s
image increased in congruency with the consumer’s self traits. High self-
monitors’ attitudes improved when the brand’s image increased congruency
with situational expectations.
Aaker’s research looked at conceptions of self that are more
chronologically accessible as well as at aspects of self that are malleable and
made to be more salient and thus accessible based on social situations and
cues. She discussed low and high selfmonitoring, and how self-concepts
include malleability that can change across situations.
She also discussed forms of congruency a consumer seeks that can enhance
self-esteem. Aaker (1999) suggested that a person’s self-definition had a
malleable nature and included various notions of oneself. These could
include the ideal self, the actual self, the private self, and the public self.
These various identities of self might mediate how brand identity influences
consumer behavior. Aaker used the Harley Davidson motorcycle and its
corporate businessman-rider as an example to illustrate how an apparent
incongruity might be explained. In this case, the Harley Davidson
motorcycle had a certain rugged, tough, and outdoorsy brand image that the
corporate businessman did not perceive in himself. Yet, he desired or hoped
for that image and therefore owned and rode a Harley on the weekends to
obtain congruency with his ideal self-identity vs. the actual identity he saw
in himself as a corporate businessman.
Another form of congruency Aaker (1999) discussed pertained to
consumer expectations of their activity outcomes. A consumer might have
judged a past consumer behavior motivated to gain social favor as a failure.
That failure was incongruent with the consumer’s expectations and
weakened their self-esteem. If the behavior had been successful in gaining
the social favor, that would have been congruent with the consumer’s
expectations and seen as successful impression management that reinforced
the behavior; that congruency increased self-esteem (Schlenker, 2011).
Aaker suggested that product brands had power when associated clearly with
both a personality trait and situational cues that were salient because of
message congruity. The congruency traits that mattered would be associated
with the social identity function (low or high selfmonitoring) and its
attendant attitudes, self-concept, strategies to achieve ‘self-worth,’ and any
reinforcing of products and brands that coincided with the consumer’s
respective self-monitoring type (Hogg et al., 2000). Aaker suggested that
low self-monitors used self-identities to establish congruity whereas high
self-monitors relied more on situational congruity.
Aaker (1999) suggested that self-schemas played a greater role in
determining brand preference for low vs. high self-monitors. She
hypothesized that situational cues played a greater role in determining brand
preference for high vs. low self-monitors. She further hypothesized that self-
schemas played a greater role in determining brand preference for low vs.
high self-monitors when exposed to a salient situational cue, and that
situational cues were more influential in determining brand preference in
aschematic vs. schematic high self-monitors. The results supported the
hypotheses such that situational cues influenced high self-monitors more and
self-congruity cues influenced low-self monitors more.
Aaker (1999) challenged the notion that multiple aspects of self were
worth looking at individually and that all were relevant. Instead, she asserted
that the more important factors relating to consumer behavior and valuation
of products were based upon a more frugal framework where the chronically
available aspects of self would integrate themselves with the set of
personality traits that were salient in the usage situation. This created a more
elegant problem by making prediction of consumer thoughts and behavior a
more thoughtful problem to resolve because it was based on a limited
selection of chronic and salient traits. It was perhaps more difficult because
the salient traits were dynamic and based on the situation and context at
hand.
Aaker’s (1999) descriptions included the public vs. private self. Graeff
(1996) wanted to examine the effects of self-monitoring within the context
of image congruence because of the belief that high self-monitoring
consumers would be more responsive to branding that reflected the ideal
self-image or social identity they sought for themselves. Graeff’s study
included 132 high and low self-monitors who evaluated two publicly and
two privately consumed brands. The brands were described as well as the
actual and ideal self-images. Scores were calculated that represented the
amount of congruence between brand image and actual self-image (actual
congruence) or ideal self-image (ideal congruence). Those scores were then
correlated with scores of the overall brand evaluation. Then the congruence
scores were analyzed to see if the effect was greater with high self-
monitoring consumers than with low self-monitoring consumers. Four items
were evaluated for effect and intention to buy and then a composite score
was determined to reflect an overall evaluation of the brand. The public
brands were Camaro and Reebok. The private brands were Budweiser, and
Reader’s Digest. A Euclidean distance model was used such that the smaller
the distance between the image congruence and brand evaluation, the more
favorable was the brand evaluation. Camaro and Reebok (the two public
brands) had much higher correlations for the ideal congruence than the
actual congruence. Whereas Budweiser and Reader’s Digest (the two private
brands) were not significantly correlated for ideal or actual congruence. This
suggested that product preference and ideal congruence were more closely
related than product preference and actual congruence.
In the latter part of Graeff’s (1996) study, image congruence was
hypothesized to have a stronger effect on brand evaluations for high self-
monitoring consumers with publicly consumed but not with privately
consumed brands. This bore out to be true. Selfmonitoring had a significant
moderating effect on Camaro and Reebok’s actual congruence as well as on
Camaro and Reebok’s ideal congruence. Whereas selfmonitoring had no
significant moderating effect on Budweiser and Reader’s Digest actual
congruence or on Budweiser and Reader’s Digest ideal congruence. Graeff’s
work supports the importance of image congruence as well as the
moderating effects of selfmonitoring for publicly and privately consumed
products.
When a consumer prepares to make an exchange with a vendor, there
may be multiple versions of self the consumer draws upon to think about the
value of a purchase. But to Aaker’s (1999) pursuit of a more parsimonious
framework, those multiple versions may not matter as much as the salient
and chronological views of self. If that is the case, Lee and Shavitt’s (2006)
ideas about cues may be very relevant in predicting consumer behavior,
especially if those cues can be controlled to make salient factors
instrumental to consumer thinking and behavior.
When consumer self-views are moderated by cues in the environment,
it allows marketing agents a means to influence consumer thinking and
behavior through branding and advertising. Lee and Shavitt’s (2006)
investigated the role cues played in a customer’s judgment of product
quality. Two consumer identity groups were created, one was told to think of
themselves and their goals in interdependent social settings (i.e., social
identity made salient) and the other group was told to think of themselves
and their goals in individual independent settings (i.e., individual identity
and utility made salient). Participants sat in front of a computer screen where
product information, including which store the products came from, was
presented. Both groups saw the same information/products (ASICS running
shoes and GE microwaves). However, one group was shown retailers that
were low reputation stores (Sears and Kmart) as the retailers providing the
products while the other group was shown high reputation stores (Nordstrom
and Marshall Fields) as the retailers providing the products. Two influences
were observed. Results indicated that interdependent social identity groups
were more sensitive to the store reputations and rated the products to be of
lower quality that came from the lower reputation retailers whereas
individual identity groups were less sensitive to the store reputations and
rated the products similarly regardless of the retailer’s reputation.
Chronically salient social identity goals could change consumer reception of
products and services. Goal salience was primed by questionnaires
completed prior to product evaluations such that questionnaires designed to
prime social identity goals vs. independent individual goals primed high and
low self-monitoring goals, respectively. Thus, one sees how value in the
consumer’s mind is influenced. Salient goals heightened by meaningful
contextual cues congruent with self-construals, positively influence the
consumers’ quality judgments (Kim et al., 2012; Lee & Shavitt, 2006).
As mentioned earlier, consumer goals often differ between low and
high selfmonitors. Aaker (1999) described the self as being generally stable
(i.e., having a certain set of self-conceptions that are chronically accessible)
“while also being malleable” (i.e., having self-conceptions that could be
made available depending on social situations). The malleable nature of self
leaves the consumer goals subject to influence from cues and prompts.
Consumers’ goals are related to self-monitoring via the way ‘self’ is
supported when consumer goals are formed and even at the moment
consumer decision making occurs. Lee and Shavitt (2006) established that
the cues used by self-monitors for decision making have limits to their
effect. The power of the cue can be mediated and even superseded by other
information and environmental conditions. For example, one’s attention can
be temporarily hijacked due to other influences such as a previously run
radio jingle that is heard again in a store while the consumer is shopping.
The jingle may influence the consumer to think thoughts of a particular self-
identity which influences the consumer to make an impulse purchase that a
different version of self would avoid. Versions of self can be mediated by a
functional role consumers see themselves in (such as a caretaker, a coach, a
judge, a teacher, etc.). When these roles are considered at the time of a
purchase, the thought of fulfilling the role influences how products are
valued. Thinking about roles, consequently, influences a person’s purchasing
decisions.
For example, variables of store reputation and the salience of social
identity goals (independent vs. interdependent self-construals) were believed
to be related (Lee & Shavitt, 2006). Lee and Shavitt (2006) argued that when
social identity goals are salient and that when image-relevant information
like store reputation is available in the consumer evaluation process,
consumers will use that information to determine a product’s quality. They
formed hypotheses that tested a consumer’s quality ratings of a utility
product (General Electric microwave) sold at K-Mart (low reputation store)
and the same microwave sold at Marshall Field’s (high reputation store).
They also looked at consumer evaluations of a social identity product
(ASICS running shoes) when it was sold at Sears (low reputation store) and
when it was sold at Nordstrom (high reputation store). The consumers were
primed with procedures that could influence their thinking and focus relative
to notions of self. One procedure involved heightening the salience of social
identity. Another procedure involved heightening the salience of utilitarian
goals. These two groups and their consumer choices were compared.
Participants were primed through use of questionnaires designed to
heighten the salience of social identity or utilitarian goals (Shavitt & Fazio,
1991). Priming of social identity significantly influenced the weight of store
reputation in the evaluation of microwaves. Results indicated a significant
effect for product evaluations (social identity vs. utilitarian; Kmart vs.
Marshall Field’s). Store reputation mattered more when social identity goals
were heightened, but there was no effect seen with priming for heightened
utilitarian goals. Those primed for utilitarian goals did not differ in their
evaluations of the microwaves due to the store’s reputation. These results
demonstrated (irrespective of self-monitoring) that a person’s focused
attention and consumer behavior could be variably influenced by priming in
the environment. This research suggested that self, within the context of
social identity could be influenced by environmental conditions.
Furthermore, it was not too far a stretch to conceive how this type of
sensitization can occur within the domain of self-monitoring and influence
high self-monitoring consumer behavior.
As another example of consumer thinking and valuation processes,
DeMarree et al. (2005) used an active-self account approach to alter self-
perceptions temporarily. They wanted to see if priming low and high self-
monitors with already established predispositions would be influenced to
feel and act differently after the priming. The belief was that they would
alter self-perceptions and, theoretically, this would translate to altered
behavior as well. Self-monitoring was used to establish the predispositions
of the participants. The active-self account suggested that a person was
potentially capable of being biased temporarily in their self-representations
and behave consistent with the prime while in the activated-self state
(Americas et al., 2010). According to this approach, the low self-monitor
would behave differently because the prime would influence the self-
representation. The reason behavior change was expected was that low self-
monitors were believed to make decisions guided by internal factors based
on their sense of self, which, in this case, was altered through a stereotyping
priming activity. High self-monitors’ behavior was not expected to be
influenced because their behavior was guided by cues from the external
environment which had not changed. Three dependent variables were
evaluated: a) implicit aggressive feelings, b) implicit lucky feelings, and c)
information-processing behavior. In each case, the prime type influenced the
result for low self-monitors. As predicted, the prime did not impact the result
for the high self-monitoring consumers. This manipulation demonstrated that
a low selfmonitoring consumer’s sense of self did influence their feelings
and behavior and that advertising and marketing cues impact consumer
behavior by influencing the low selfmonitor’s sense of self (DeMarree et al.,
2005).
This study looks at self-monitoring as a tool for consumer research in
the military. To be effective, it is important to understand that the theoretical
basis for self-monitoring rests on the consumer’s self-concept and the
consumer’s strategies to achieve self-worth through consumer behavior.
Self-monitoring style directs consumers’ attention to value areas important
to the consumer. Consequently, one should intuitively as well as empirically
be able to see significant relationships between consumer behavior,
selfmonitoring, and notions of self which in concert work to regulate
consumer behavior (Hogg et al. 2000).
One aspect of self is the consumer’s ideal self and its relationship to
the interdependent self and the environment. Kim et al. (2012) demonstrated
that people pay more attention when a public outcry against a manufacturer
is in the media spotlight for their influence on global warming or when there
is another issue of neglected corporate social responsibility that gets
consumer attention. When this happens, consumer responsiveness to ads that
highlight a socially responsible company will translate to greater consumer
interest in the use of products made by that company. As Kim et al. (2012)
pointed out, this becomes a social influence that high and low self-monitors
can respond to differently or even respond to in the same way but for
different motivational reasons. The high self-monitor may purchase and
publicly use a product because of the impression of supporting corporate
responsibility but not use the product privately, whereas the low self-monitor
may purchase the same product and use it privately because it represents the
consumer’s intrinsically held values. Shavitt and Nelson (2002) explained
that high self-monitors’ general attitudes work to support a public identity
that the consumer may want to keep, maintain, or develop. The social role of
attitudes is significantly integrated in many aspects of people’s lives.
Attitude functions are part of public and private identity motives. The social
role of attitudes is referred to as the social identity function (Shavitt, 1989)
and has been mentioned previously. Products convey various images that
can meet this function. Some are utilitarian in nature. Others are image
oriented, and other products are combinations of these two primary product
attributes.
Self-monitoring identifies paths consumers use to ascribe product
value. The path is a function of their self-monitoring style. High self-
monitoring consumers have multiple paths to ascribe value, while low self-
monitoring consumers choose products consistently that reinforce their
intrinsic views of self. In some cases, the value path will be the same for
high and low-self monitoring consumers alike (particularly for utility
products). Otherwise, high self-monitoring consumers are motivated to
choose products and services based on the external perceptions others have
of them. These are situational perceptions based on culture and other factors.
This personality difference between high and low self-monitors makes self-
monitoring useful for developing and marketing products. It makes sense,
therefore, to consider what is known from the literature about self-
monitoring and civilian consumers.
Since the ultimate purpose of the study was to consider self-
monitoring theory’s applicability to the military consumer, it was important
to understand why culture (military or any significant cultural or group
effect) matters. The simple answer is that culture directly influences the
notions of self that one possesses and the norms and expectations of the
society at large. Two primary cultures (Western and Eastern) illustrate the
fundamental differences in their notions of ‘self.’ Western cultures are more
selfcentric and individualistic. They focus more on individual progress and
accomplishment. Eastern cultures are more collectivistic and view the self as
part of a group and in relation to others and choices that impact others are
weighed more heavily.
Choi et al. (2003) demonstrated that those from an integrated self
(collectivistic) culture were typified and shown to have a much more holistic
and complex way of judging and making decisions. In Choi et al.’s (2003)
study of Americans and Koreans, a method of inclusion and exclusion
practices helped determine how much information from a list was important
in judging/making decisions. Koreans consistently had larger lists of both
inclusionary and exclusionary types of information, with the exclusionary
lists consistently longer. Markus and Kitayama (1991) provided illustrative
anecdotes of social norm differences in American and Asian cultures. For
example, in America “the squeaky wheel gets the grease.” In Japan, “the nail
that stands out gets pounded down.” Another example is what parents say to
induce their children to eat their dinners. In America it is: “think of the
starving kids in Ethiopia and appreciate how lucky you are to be different
from them.” In Japan it is: “think about the farmer who worked so hard to
produce this rice for you; if you do not eat it, he will feel bad, for his efforts
will have been in vain.” These types of influences on consumer value
perceptions affect the social identity and judgments of consumers in
different cultural or group settings where group dynamics can exert a strong
influence. Such influences were expected to exist for reasons unique to the
military.
Consumer Research With Self-Monitoring
Consumer behavior is related to self-monitoring styles (Snyder &
DeBono, 1985) and these styles are related to maintenance of self-esteem
associated with image congruence hypothesis (Grubb & Grathwohl, 1967;
Hogg et al. 2000). The hypothesis model essentially says that a consumer’s
evaluation of a product is influenced by what the item will do for them in
reinforcing their self-concept through internal messages to self and external
messages to important reference groups (parents, peers, teachers, or
significant others). The model shows that high self-monitoring consumers
have a more complex evaluation system that includes a value-expressive
attitude for the private selfconcept separated from a social adjustment
attitude for both a public and a collective self.
On the other hand, low self-monitoring consumers make all decisions from a
single value-expressive attitude where the point of views for both private
and public self are part of an integrated self-concept.
Self-defined concepts seem to have a contextual element for both
types of selfmonitoring consumers. Hogg et al.’s (2000) self-esteem
maintenance model of congruency (developed by both qualitative and
quantitative methods) and Aaker (1999) explained that self-monitoring
consumers have multiple views of self that differ in their meanings as well
as their intensities. These types of variances were triggered differently by
situational cues. Aaker’s malleable self-research confirmed not only cue
difference effects between low and high self-monitors but also how
consumer valuations can vary due to different cues in time and place for the
individual consumer.
Hogg et al. (2000) used alcohol (names, images, flavor, packaging,
alcohol content, etc.) to demonstrate distinct differences between self-
monitoring groups. For example, low self-monitors were shown to avoid
drinking situations which required them to project a self-image different
from their own. Similarly, consumers considered the audience and whether
the situation was “public” or “private” in making an appraisal as to which
alcohol they would use. The “audience” could be peers or even the
consumers themselves. Social cues, such as work associates or a boss,
prompted high selfmonitoring consumers to act differently from how they
acted with family members. Products that conveyed an image were
evaluated differently by low and high selfmonitoring consumers. Variances
in value occurred based on the consumer’s perceived image conveyed by the
product and the context of how the product was anticipated to be used.
DeBono (2006) discussed how qualitative consumer research showed
low selfmonitoring consumers to be perceptive of favor-enhancing social
image cues with alcohol packaging but less inclined to use the cues to
impress others like they observed in high self-monitoring consumers.
Instead, low self-monitoring consumers looked for products that matched
internally held values such as flavor quality and alcohol content. Low self-
monitoring consumers acknowledged that high self-monitoring consumers
chose to have ornately packaged beverages in one’s possession to impress
others. In the case of alcohol, it appeared that high self-monitoring
consumers sought to raise their status by serving ornately packaged alcohol
they thought would impress esteemed guests. Low self-monitoring
consumers judged quality and value by internal views and standards such as
how they perceived beverage flavor and alcohol content. This was
irrespective of a costly package appearance.
Becherer and Richard (1978) conducted consumer research to evaluate
the influence of disposition (internal personality) versus situation (external
context) variables as moderated by self-monitoring. They found that
dispositional factors (personality) were more influential with low self-
monitors and situational factors (group situations) were more influential with
high self-monitors in regulating consumer behavior. Differences were seen
in consumer affinities towards product brands. Using regression analyses,
they found that low self-monitoring consumer behavior was driven more by
personality for both socially and nonsocially prominent products than it was
for high self-monitoring consumers. Personality dispositions were
significantly different in degrees of proneness towards socially prominent
and nonprominent products. Becherer and Richard (1978) hypothesized that
students’ proneness to private brands (affinity to brand names associated
with the retailer) as opposed to proneness for national brands (affinity to
brand names branded by the manufacturer) would be influenced by how
socially visible the product was. Products used were cologne, mouthwash,
complexion aides, and alcohol (all of which were considered social
products) and vitamins, pocket calculators, coffee, and candy bars (all of
which were considered nonsocial products). Private brand proneness
(preference for a private brand versus a national brand) was the dependent
variable. Participants were asked to rate private and national brands to create
private brand proneness indices. Eighteen personality variables were
measured with the California Psychological Inventory. The results from this
evaluation showed private brand proneness differed between the low and
high self-monitoring groups. A significant difference was found between
low and high self-monitoring groups such that appealing product bands were
preferred by high self-monitoring consumers. Overall, results suggested that
personality variables had a moderating effect on consumer behavior for both
low and high self-monitoring consumers. For high self-monitoring
consumers, situational factors were more likely to be related to consumption
whereas for low selfmonitoring consumers, personality factors were related
to private brand proneness for products that were both nonsocial and social.
Related to Becherer and Richard’s (1978) work that characterized
self-monitoring style’s relationship to product brands, Hogg et al. (2000)
indicated that low selfmonitoring consumers’ value-expressive attitude
caused consumers to integrate consumer decisions with self-concept in
similar ways for both public self and private self without a need for a social
adjustment attitude. They claimed a low self-monitoring consumer’s
motivation for self-worth fell under a single value expressive attitude that
could accommodate both private and public forms of self-concept. Both
forms derived selfworth solely from internalized standards. Low self-
monitoring style was deemed compatible with the idea that internal
standards were achieved through product and brand choices congruent with
internalized standards used to maintain self-worth.
A high self-monitoring consumer style needed a social adjustment
attitude to maintain self-worth. Maintenance in the high self-monitoring
style was a more complex path wherein product/brand choices were made
based upon both internal and external standards. Like low self-monitoring
style, internal standards pertained to a private selfconcept. But additional
external standards were derived from the evaluations and expectations of
others used in a public and/or collective self-concept. Achievement of those
standards relied on consumer behavior congruent with those standards. High
selfmonitoring style allowed consumers to see if their consumer behavior
was congruent with those standards. Congruency with either internal or
external standards reinforced selfworth for the high self-monitoring
consumer. High self-monitoring consumers need to be adept at securing
positive evaluations from others as well as adept at meeting goals of
important reference groups in order to have their self-worth reinforced.
Hence the motivation to be as some have termed, a “social chameleon.” In
short, self-monitoring styles were seen to govern a consumers’ use of
situational and dispositional factors.
Consumer complaint behavior of low and high self-monitoring
consumers illustrate differences between low and high self-monitoring
consumers. Bearden and Crocket (1981) examined consumers of automobile
services. They demonstrated that the intentions formed to complain about
service failures differed significantly between low and high self-monitoring
consumers. High self-monitoring consumers had a greater tendency to
consider variations in social standards than did low self-monitoring
consumers. Low self-monitoring consumers differed significantly from high
selfmonitors in their greater tendency to consider internal moral standards.
Liu and McClure (2001) discussed differences in the U.S.
(individualist) and South Korean (collectivist) cultures. They pointed out
that South Koreans are more likely to engage in private complaint behavior
responses with those of their ‘in-groups’ (closeknit circles of families,
friends, and others they thought had an interest in their welfare). United
States consumer in-groups were composed of those similar in social class,
race, values, and attitudes (Triandis, 1972). Wan (2013) argued that Asian
consumers were not necessarily less likely to complain about service failures
than Western consumers. Degree of embarrassment involved in a failure was
integral to collectivist social standards and drove the type and degree of
complaining. Chinese consumers were significantly less likely than
American consumers to complain in nonembarrassing failures (i.e., when a
product or service is not witnessed by others such in a private moment alone
with a salesman). But the pattern reversed when the service failure was
embarrassing (i.e., when the product or service is witnessed in a group such
as a disrespectful waiter treating the host with contempt in front of all the
host’s guests). Chinese consumers in that instance were significantly more
likely to complain than American consumers.
Sharma et al. (2010) conducted survey studies on consumer complaint
behavior in Singapore, South Korea, and the United States. Study results
suggested cultural standards and personality differences helped explain the
different consumer complaint behaviors. Sharma et al. (2010) showed that
high self-monitoring U.S. consumers were significantly more likely to
complain about a computer product and mobile phone service failures than
high self-monitoring South Korean consumers who were significantly less
likely to complain about the same computer product and mobile phone
service failures.
Sharma et al. (2010) suggested that a company’s practice of consumer
complaint behavior typing (placing behaviors into categories) did not get at
the root cause nor help companies understand and effectively resolve
complex and variable consumer complaint behaviors. Relative to the
example mentioned in the preceding paragraph, Sharma et al. examined
situational variables (customer dissatisfaction and involvement) along with
two consumer traits (impulsivity and self-monitoring). Students participated
from three countries (Singapore, South Korea, and the United States). Two
consumer complaint situations were presented: (a) a product failure (a
recently purchased laptop computer with a screen that went blank) and (b) a
service failure (a new mobile phone plan with a recent bill where the rate
had doubled). The purpose of the study was to explore individual differences
in complaint behavior. Involvement, impulsivity, and selfmonitoring were
considered factors of influence. Consumer complaint behavior was
significantly and positively associated with impulsivity (i.e., the tendency to
act spontaneously without reflection or deliberation) and involvement (i.e.,
effort and time involved personally with a product). The more impulsive a
person was, the more they tended to complain and the more involved they
were with the product or service, the more likely they were to complain
when there was a failure. Self-monitoring had mixed results across cultures.
This was true of complaint behavior for both service and product failures.
High self-monitoring consumers in collective cultures were less likely to
complain compared to high self-monitoring U.S. consumers. In an
individualistic culture, a standard of one’s strength of character was to voice
dissatisfaction and expect resolution to service and product failures. The
collectivist cultural standard, on the other hand, recognized that a person’s
strength of character was manifested in self-restraint such that complaints
about service or product failures would be withheld. Collectivist cultures
view individual behavior such as consumer complaint behavior as a
reflection on the collective self and therefore avoid it as a negative societal
behavior. In these cases, consumer complaint behavior was expressed
differently for high self-monitoring consumers and could be a status
enhancing or diminishing behavior for high selfmonitors, depending on the
cultural context.
The ability to predict consumer responses to advertising and
marketing efforts is a desirable skill that requires an understanding of
consumer behavior as it relates to selfmonitoring styles. In terms of self-
monitoring theory, understanding how a consumer perceives social benefit is
critical. For example, alignment of an advertiser’s appeal to be salient and
congruent with consumers’ value perceptions would be a useful marketing
strategy. Low self-monitoring consumer appeal might be directed at utility in
vision acuity and protection for sunglasses. For high self-monitoring
consumers, social identity status conveyed by the sunglasses could be
emphasized. Aaker’s (1999) ideas discussed previously support the concept
that salient messages about products need to be in alignment with low or
high self-monitoring consumer goals in order to be effective. DeBono
(2006) discussed how some products can appeal well to both low and high
self-monitoring types of consumers. A multiple-function product such as
sunglasses can present both quality and image enhancing aspects that appeal
to the value-constructed thought processes of both low and high self-
monitors. With sunglasses, for example, a high self-monitor’s reasons could
be linked to social influence such as branding and style. Whereas the low-
self monitor’s reasons could be linked to functional utility such as durability,
lens hardness, light polarization, and UV protective qualities. Aaker (1999)
noted that successful consumer advertising of dual-purpose products (those
that can serve both value expressive and social adjustment attitudes) would
need to emphasize mixed information that appealed to factors important to
the different self-monitoring consumer types. In other cases, the functional
cooling quality of an air conditioner not seen in public, or the functional
effect of an aspirin may only require a one dimensional, valueexpressive-
function advertisement in order to appeal to both low and high
selfmonitoring consumers. That is why self-monitoring theory has more
discrimination power for some product categories than in others. This
awareness helps utilize selfmonitoring in consumer research.
Self-monitoring theory has been used to guide consumer research in
predicting things such as purchase intent, consumer satisfaction, liking, and
complaint behavior. Self-monitoring theory provides a framework for
researchers to use with other psychological principles in order to consider
consumer decision making based on a selfmonitoring style that includes an
appraisal process made of a series of back-and-forth reviews that help
consumers establish and maintain a self-concept that allows for consumer
behavior that supports it. Consumers’ mental mediation processes augment
social presentation and self-definitions. Laverie et al. (2002) observed that
the appraisal process is a proximal cognitive antecedent to emotion and
therefore important in predicting the importance of an identity that is, in
turn, strongly related to consumer behavior manifestations.
Degree of liking is commonly used to predict success of a product and
has been measured in civilian and military consumer products for decades
(Meiselman & Schutz, 2003; Peryham et al. 1954; Peryham & Hanes, 1957).
Product quality is a dimension used by consumers to determine acceptance
and liking of a product. Perceptions of what constitutes quality in a product
vary between low and high self-monitoring consumers.
Some consumers consider country of origin to be a factor of finer quality
foods (DeBono & Rubin, 1995). In a study by DeBono and Rubin (1995),
117 college students were told by a researcher that she was interested in taste
preferences. Two cheeses were presented to consumers who were misled to
believe the cheeses were from Mulburry, Kansas, USA or from Strasbourg,
France. One cheese was a higher quality cheddar cheese, the other a lower
quality and less pleasant tasting Edam cheese. With misleading product
origin information, students were asked to taste the cheese and rate it for
quality and other items related to acceptance such as “would you buy this
cheese?” and “would you recommend this cheese to a friend?” Ten items
were rated using a 10-point scale. As participants left, they were asked if
they would help a fellow researcher who was collecting survey data.
All participants agreed and completed the self-monitoring scale. Results
showed that there was a significant main effect for country of origin for high
self-monitors such that the cheese was rated significantly higher for quality
when they thought it was from France. No significant differences were due
to actual cheese quality for high selfmonitors. In contrast, there was a
significant main effect for cheese quality for low selfmonitors; the pleasant-
tasting cheese was rated significantly more favorably than the less pleasant-
tasting cheese. The results indicated that low self-monitoring consumers
relied on objective information for product quality and high self-monitoring
consumers relied on what they perceived was more socially valued.
Similar effects were obtained in other studies. DeBono and Snyder
(1989) tested consumer acceptance of different types of products with
different types of packaging. DeBono et al. (2003) conducted two studies. In
the first, results showed that when product quality was held constant, high
self-monitors rated products significantly higher in quality when packaged
more attractively. In the second study with perfumes of different quality,
consumers high in self-monitoring again rated perfumes significantly higher
in quality when container and packaging were more attractive. Low-self
monitoring consumers used product quality aspects to form their evaluation
of the product, focusing on perfume scent quality to rate the perfumes. As in
the cheese study, results revealed that low self-monitoring consumers judged
products by more objective and stable product quality standards. High self-
monitoring consumers judged product quality by more subjective and
external social standards relative to the situation.
Quality assessment differences between high and low self-monitoring
consumer groups suggest the two groups differ in how they focus their
attention and determine product value. In fact, Kjeldal (2003) reviewed
consumer research related to selfmonitoring and found that theorists were
characterizing the focus of low and high selfmonitoring consumers along
one of two general paths—quality and image. Low selfmonitoring
consumers were primarily focused on product quality-based characteristics.
High self-monitoring consumers were focused mainly on image-related
product characteristics. Kjeldal (2003) noticed that researchers used various
words besides “quality” and “image” and that these terms appeared to be
treated with assumed equivalency to “quality” and “image.” Other words in
lieu of “quality” were “utility” and “function.” In lieu of “image,” other
terms were “social identity,” “form,” and “valueexpressiveness.” Kjeldal
(2003) was concerned that treating the terms “quality” and “image” with
equivalency to other related words was a definitional problem that could be
blamed for sometimes tepid or weak comparisons of self-monitoring styles
in consumer research. She could not see where research had been conducted
to confirm that the terms were conceptual equivalents that should be used
interchangeably. Kjeldal conducted a qualitative-in-nature study in response
to that concern. She looked for a conceptual link for low and high self-
monitors. The terms and concepts used were in two groups: (1) image/social
identity/form/value-expressive and (2) quality/utilitarianism/function.
Kjeldal (2003) used word-association in an unstructured, context-free
environment wherein 337 respondents looked at images of 10 fruits and 10
vegetables then provided up to ten associations for each image. Words were
coded into major and minor categories with five primary categories,
including sense, function, horticulture, idiosyncratic, and evaluation. Kjeldal
found a clear conceptual link between low and high self-monitors and their
consumer behavior areas of focus. The link was not to quality and image.
Instead, she found that low self-monitors focused on intellective,
nonpersonal, and factual information when describing fruits and vegetable
products while high selfmonitors focused on experiential and highly
individualized ideas. In summary, using the words ‘quality’ and ‘image’ to
represent low self-monitor and high self-monitor styles, respectively, yields
the most definitive consumer behavior research.
Kjeldal suggested refinements are needed to conceptual links for a few
areas such as ‘sense’ (appearance factors) and ‘function’ (utilitarianism).
More word association differences were expected between low and high
self-monitoring respondents in some areas, likely due to an overly broad
application of these terms (Kjeldal, 2003). Theorists use similar terms too
broadly as if they were equivalent in meaning for quality and image-based
characteristics of products. This may be weakening the ability of
selfmonitoring to discriminate to compare research findings. More consistent
and universally understood terms by researchers could help. Yet, if self-
monitoring has a moderate effect on consumer behavior, as suggested by
several researchers (Kjeldal, 2003), then insightful diligence will be required
to identify and use subtle influences.
Kauppenen-Räisänen et al. (2018) discovered the complexity of
identifying subtle influences when they sought to understand how social and
personality traits impact luxury brand prominence. The authors conducted a
study using a convenience sample of students from three European
universities (Hanken School of Economics in Finland, University of Milan
in Italy, and Bordeaux École de Management in France). The average age
was 22.6 years old with 139 females and 76 males. The students were
presented with paired images of the same brand luxury item (e.g., Prada,
Gucci, Louis Vuitton, Mulberry and Burberry). Each pair included a
prominent logo on one image of the item and on the other image of the same
item the branding was hidden. The researchers hypothesized that high self-
monitoring consumers would select the prominent brand. Contrary to
expectations, the majority of both female and male high selfmonitoring
consumers selected the less prominent brand. Kauppenen-Räisänen et al.
(2018) found significant relationships between self-expression and self-
monitoring as well as between brand prominence and self-monitoring (but in
the reverse direction of their hypotheses). Nine of their fourteen hypotheses
were rejected, acknowledged as evidence of the complex structure existing
between brand, personality, and social, traits.
Kauppenen-Räisänen et al. (2018) reasoned that some high self-
monitors preferred low prominent branded luxury items because they were
content to have a smaller and closer circle of social recognition from
significant people who were more brand savvy. Their findings did not allow
them to construct a theoretical framework that explained how the degree of
brand prominence related to the function of social identity and social needs.
Some of the limitations of the study included a disproportionate number of
females and the fact that the participants (students) were aspiring owners of
luxury items and not actual owners. Also, the self-monitoring measure was
based on a poorly defined and limited sub-dimension of self-monitoring
(Lennox & Wolfe, 1984)—a poorly defined dimension by Lennox and
Wolfe’s own admission. Nevertheless, Kauppenen-Räisänen et al.’s (2018)
reasoning is in line with other theories related to needs for uniqueness.
Abosag et al. (2020) discussed the tension between two theories
whereby consumers are pulled in two directions: brand congruence theory
and need for uniqueness theory. Theory of brand congruence emphasizes
brand images that are congruent with self-concepts will be more favorable to
consumers. However, need for uniqueness theory states consumers have a
need for uniqueness. As brands become more common, consumers look for
ways to distinguish themselves through more unique aspects of
consumerism. This is supported by Vainikka (2015) who discussed the
foundations of consumer behavior and consumer decision-making processes,
explaining that the basis of this tension is rooted in the consumer’s need to
validate their self-concepts. Less prominent branding fulfills self-worth
notions because blending into excessively large groups is perceived to
diminish self-identity, whereas belonging to a smaller, more distinctive
group is perceived to add value to the self-concept.
Harnish and Bridges (2016) believed that some forms of advertising
were motivated by and could be distinguished by self-monitoring
propensities. They believed that low self-monitors were motivated by a
value-expressive function and high selfmonitors by a social adjustive
function. They looked at consumers and video bloggers of young women
with “Mall Haul Videos” or vlogs, which are short videos where young
women present beauty and fashion purchases along with evaluations and
opinions about the deals to other potential buyers. This form of advertising
was akin to word-of-mouth feedback and deemed valuable to consumers
who trust 92% of that form of consumer information. This was
comparatively higher than trust in consumer opinions posted online (70%)
and ads on TV (47%). Vlogs, therefore, were seen as an important marketing
medium. To see if the motivation existed, three vlogs were created to
represent retailers who were high status (Nordstrom), medium status (JC
Penny), and low status (Walmart). The videos were pretested to insure they
were perceived with those brand equity status differences. Participants
viewed the videos after which they were asked to rate how much they would
like to view another mall hall video using a 7-point Likerttype scale (1 = not
at all to 7 = very much). After that, participants completed the SMS-R 18-
item Self-Monitoring Scale (Snyder, 1986; Snyder & Gangestad, 1986). The
results showed that high self-monitoring consumers were significantly more
likely to watch another vlog when the retailer portrayed in the first video
was a higher status retailer and, predictably, low self-monitoring consumers
were more likely to watch another vlog when the retailer portrayed in the
first video was a lower status retailer. Harnish and Bridges (2016) concluded
that high self-monitors were fulfilling a social-adjustive function (i.e.,
gaining status) and that low self-monitors were fulfilling a value-expressive
function (i.e., finding functional value such as variety, pricing, and
convenience).
Past mixed results for self-monitoring appear largely avoidable if
selfmonitoring’s dimensionality and the complexities of consumer
motivations are considered. Other researchers have given cause to consider
other dimensions of selfmonitoring that may matter. Fuglestad et al. (2019)
argued that broader personality traits should be considered to frame self-
monitoring theory. They discussed for example, acquisitive and protective
self-monitoring (subsets of the general self-monitoring personality trait) how
they were differentially related to facets of neuroticism. For the acquisitive
self-monitor, there was a negative relationship and for the protective
selfmonitor, there was a positive relationship to neuroticism (facets such as
depression, anxiety, impulsivity, vulnerability, and self-consciousness).
Wilmot et al. (2016) found that acquisitive self-monitoring had a strong,
positive relationship to the plasticity meta
trait.
Snyder and DeBono (1985) looked at the impact of quality-based and
imagebased advertisements for Canadian Club whiskey, Barclay cigarettes,
and Irish Mocha Mint flavored instant coffee among low and high self-
monitors, measuring their evaluative and behavioral reactions. Two
advertising strategies were used, one to appeal to product image and the
other to appeal to product quality. Participants were presented with three
experiences: (a) questionnaires comparing advertisements and their
evaluative responses, (b) image-oriented or quality-oriented words in picture
ads presented and then surveyed to see what they would pay for the
products, and (c) participants contacted in phone survey and presented with
either an image-based or quality-based description about a shampoo and
then asked to rate their degree of willingness to try the product. In each
situation where products were presented to low and high self-monitors, the
graphics were the same, but the print was different to represent the two
general situations. One focused on the product with the print highlighting the
product’s quality and content while the other print focused on social benefits
by explaining how owning or using the product defined the kind of person
one could be. Snyder and DeBono (1985) demonstrated that high self-
monitors were significantly more responsive to image-enhancing appeal
advertising and willing to pay more for the product. Also, the quality-based
advertising appeals were significantly more influential with low self-
monitors who would pay more for quality-promoted products.
DeBono et al. (2003) used perfumes and colognes to assess how low
and high self-monitors characterized consumer choices and perceptions.
Two variables were manipulated: (a) the packaging (different levels of
attractiveness and image association) and (b) the aroma (scents with more or
less degree of pleasantness). The participants assessed the
perfume/cologne’s quality. The low self-monitors utilized functional
properties of the perfume and cologne products to determine their quality.
Regardless of the bottle’s attractiveness, low self-monitors used the
pleasantness of aroma to determine the quality. As expected, high self-
monitoring consumer ratings were driven by image enhancing attributes
such as the packaging. High self-monitors found the attractiveness of the
packaging more influential to determining product quality than the
pleasantness of perfume or cologne scent.
DeBono (2006) pointed out that decades of research have established
dispositional differences shown as important factors in attempting to
influence consumer behavior. Normally, the objective is to increase the
likelihood that the target consumer will be influenced to act more favorably
towards the product(s) being represented. The dispositional traits within self-
monitoring theory have been used to tailor ad campaigns. The campaigns
varied according to the appeal sought for, the context of use of the product,
and whether the product was used for private or public consumption. In
some cases, appeal was generated by the type of spokesperson being used.
For example, a physically attractive or famous spokesperson used to achieve
social influence appeal. In other cases, an expert spokesperson was used to
establish a quality, utilitarian appeal. For example, low self-monitors were
responsive to quality-based versions of the advertisement that explained in
detail the quality of the coffee; for example, Irish Mocha Mint was described
as “a delicious blend of three great flavors—coffee, chocolate, and mint.”
Though there were exceptions, DeBono (2006) indicated that low self-
monitors were not always responsive to quality-based ads, particularly when
the quality arguments were weak. The reasons appeared due to construct
generalizations and lack of congruency between the advertisement’s quality
appeal and the consumer’s quality objectives.
Hu and Parsa (2011) examined the effects of self-monitoring, dining
companions, and segments of industry with respect to using alternative
currencies in dining out situations. They observed that low and high self-
monitoring consumers differed in spending practices when dining. High self-
monitors were more inclined to pay with cash than with other more
economical means. They avoided appearing “cheap” with highstatus dining
companions such as a boss who they wanted to impress, whereas with
friends or alone, the high self-monitoring consumer was more inclined to
utilize discount meal purchase mechanisms. The changes in their behavior
were based on dining companions and other social influence factors such as
the amount of the purchase, vendor-listed currency types, demographic
factors, and the type of purchase unit (i.e., single restaurant or restaurant
chain). While high self-monitors were significantly more likely to make
spending choices to impress, low self-monitors were significantly more
likely to purchase in ways that were more economical and pragmatic, such
as getting a discount by using frequent user points. At other times, high self-
monitoring consumers sought to impress associates by conveying other
attributes such as frugality and resource efficiency, being interesting, being
grateful, being prestigious, or being vested in the eating companion(s). In
general, the motivation for high self-monitoring consumers appeared driven
by impression management. Whereas low self-monitoring consumers were
more consistent and congruent with a fixed, internal self-definition.
According to DeBono (2006), self-monitoring theory demonstrated a
degree of utility for consumer research relative to product evaluations and
advertising. His research and writings demonstrated the existence of
moderating effects in predictive power of selfmonitoring theory due to
multiple factors, including value differences in the consumers, cultural
influences, the context wherein the product was to be used, the product type,
the audience who would see the product, and whether the use was public or
private. The study provides important information regarding military
consumers and the potential for self-monitoring theory to explain/predict
consumer attitudes and behavior. Using an important consumer variable of
product liking to assess military consumer behavior, this study offers a first
application of self-monitoring theory to military consumers.
In sum, differences between low and high self-monitors can reliably
predict consumer behavior when there is congruency between what the
product is perceived to stand for and the internalized standards (goals)
important to the consumer. High selfmonitoring consumers have more
complexity with both internal and external standards; internal standards are
based on whatever is important to the individual consumer and external
standards are based on what the consumer perceives to be valued by others
who are deemed important. High self-monitors adjust their behavior to
appeal to external standards to secure positive evaluations from significant
others or to meet goals of important reference groups. High self-monitoring
consumers tend to be adept at adapting their behavior. Low self-monitoring
consumers tend to be consistent in their allegiance to their internal standards.
Mixed results tend to come from marginal or poor congruence between
internal or external consumer standards and product-image conveyances.
Saliency of product-image conveyances and saliency of the consumer’s
valued standards are essential to efficient use of self-monitoring. Over-
generalized product-image conveyances and vague consumer-valued
standards produce less clear and less consistent results.
Consumer Research in the Military
Military culture is unique, complex, and not fully understood
(Dunivin, 1994; Hajjar, 2014; Scales, 2018). The complex (Hajjar, 2014)
and changing nature of military culture (Dunivin, 1994; Rueb et al., 2008)
can put the soldier in a position where selfidentity is challenged, and an
appraisal process can lead to changes that influence what kind of military
consumer products will validate the self-worth of both low and high
selfmonitoring military consumers. Soldiers are trained to work in teams and
rely on individual and group strengths, roles, and identities. Soldiers are
taught to exercise selflessness and courage in the face of danger (TRADOC,
2019). These factors likely influence self-identities and social expectations
and, therefore, how self-monitoring is expressed in consumer behavior.
Studying these influences should provide information useful in marketing
products that are more appealing and better utilized by military consumers.
Self-monitoring has the potential to predict military consumer behavior if
the notions of self, group expectations, and product image are salient and
congruent with salient consumer values.
Within the military there are unique social conditions such as being
deployed, reduced contact with family, strenuous team expectations and
drills, austere environments, loss of personal freedom, violence, and death.
The environmental conditions naturally raise and lower the importance of
some consumer decisions. For example, a meal changes from a relaxed
social event to a rushed event focused on refueling the body’s energy stores.
Situational cues may become vague or become more salient and as Aaker
(1999) points out, the malleable self-concept associated with those changes
will result in changes to how brands and products are used. Disruptions and
dynamics of military culture leave military consumers in a position where
influences on consumer behavior and the interrelated notions of self, self-
esteem, self-worth, and selfmonitoring are worth studying. Especially since
some of these disruptions are complex and commonplace in the military.
Things can be learned from self-monitoring even if cultural influences
are not understood. For example, using self-monitoring theory, Sharma et al.
(2010) discovered a difference between collectivist and individualist cultures
on civilian consumer complaint behavior. They assumed that civilian
consumers who were high self-monitors would avoid consumer complaints
because they believed all cultures viewed consumer complaint behavior as
something socially undesirable. However, the results showed that high self-
monitoring consumers from the United States (predominantly an
individualistic culture) regarded speaking up as a positive individual trait
that garnered social enhancement. High self-monitors from Asian societies
(predominantly interdependent/collectivistic cultures), avoided consumer
complaints as socially undesirable behavior. Researchers were not expecting
this. They assumed the behavior and values would be the same across
cultures. Generally, cultural impact is understood as a mediating variable to
be reconciled (Arnould & Thompson, 2005), but it sometimes is neglected.
Just as differences in collectivist and individualist cultures impacted
consumer behavior in Sharma et al.’s (2010) study, military culture can
impact consumer behavior making consumer identities and values different
between military and civilian cultures. That is why self-monitoring theory
was applied to understand military consumers and how they may differ from
civilian consumers. This study allowed self-monitoring to be evaluated in
the context of military consumers relative to characteristics of military
consumers (e.g., gender, rank, years of service, deployment experience, and
combat experience).
Military consumer researchers in the past used liking ratings of
products to determine if the products would be accepted and used by
military consumers. For example, Graaf et al. (2005) wanted to see if
differences existed between field and lab evaluation methods. Liking ratings
were used. Food products were rated by soldiers in the field, and the same
food products were rated by civilians in the lab. For snack food ratings, there
was no significant difference between the liking ratings of the two groups.
However, significant differences did exist between groups for liking ratings
of main dishes and other meal components. The soldiers in the field rated the
main dishes and components higher in liking than did the civilians in the lab.
The authors gave possible explanations for these differences. One
explanation was that snack foods were more consistently made products
with consistent sensory qualities. Also, snack products didn’t require
preparations such as warming and were often eaten standalone in smaller
portions without much preparation and in a variety of conditions and
quantities. This made the product consumption conditions more similar
between the two groups. Explanations for meal differences included: meals
eaten with different preparations (heated versus cold) in conjunction with
other items; sample portion sizes eaten (in the field soldiers normally ate the
entire meal portion where a main entrée was 150 grams and civilians
typically only sample about 15 grams of the entrée); time and location of
sampling (soldiers rated the meals at unstructured times and places as
circumstances afforded them, whereas civilians were in a more controlled
condition where they sampled and rated food at the same time and one item
at a time). Other explanations offered by the researchers for the differences
included the fact that soldiers in the field were free to choose the order and
which foods they liked the best. In the lab, the subjects had no choice and
tasted foods they might not have liked in the order as directed. When given a
choice in a follow-up choice simulation lab study (Graaf et al., 2005), the
average civilian responses were higher than in the nonchoice study implying
that as civilian evaluation conditions neared that of the soldier, the results of
the evaluations became more similar. The studies confirmed earlier research
(Cardello et al., 1996) that civilian and military liking ratings of food eaten
by soldiers could be similar or dissimilar to civilians due to food types and
other contextual factor differences between civilians and military consumers
consuming the same foods.
Various survey instruments have been used; however, Cardello et al.
(2010) pointed out the prevalent usage of the 9-point hedonic scales with
military consumers. Scientific methods such as standardized sensory
practices and consumer feedback questions have been used and
acknowledged as standard practices for consumer and military rations for
many years by many researchers (Cardello et al., 2012; Meilgaard et al.,
2016; Yantis, 1992). Periodically, the measures may include conditions
familiar to the warfighter. For example, Wansink et al. (2012) conducted
research to assess liking of rations that were being eaten in the dark. Focus
groups and other survey work have also helped identify military consumer
issues both in the lab and in the field. Meiselman and Schutz (2003)
highlighted the historical perspective of sensory analysis and consumer
research with military rations over the last several decades. The military has
historically and necessarily pushed for many improvements with food
products. Military consumer satisfaction standards have existed and been
researched for decades. Requirements for Napoleon’s army established
standards for shelf-stable, palatable foods for military consumers (Appert,
1812; Mrak, 1970).
Meiselman and Schutz (2003) described the military consumer
research path as a long course of historical influences related to food
acceptance in the United States Army with most emphasis from the 1940s
onward. Consumer research work in the military has evolved from a focus
on food stability and liking (Appert, 1812; Meiselman & Schutz,
2003) to include other consumer research programs such as clothing comfort
(Cardello et al., 2003). Scales (2018) emphasized the urgent need to better
understand the factors motivating military consumers’ liking of personal
items such as food, clothing, and equipment because if soldiers did not like
those items, they simply were not going to use them. That kind of resource
underutilization would be a failure related to unrefined knowledge of what
soldiers disliked or liked and would translate into a compromise of their
ability to perform their difficult and essential duties. Scales (2016) also
described the need for military planners to more aggressively explore the
warfighter in terms of the human elements of behavior, cultural influences,
and social context. He emphasized the need for military researchers to
increase their understanding of what drives warfighter performance and
behavior in order to keep the warfighter integral to maintaining the nation’s
future peace and safety in the face of emerging threats in today’s complex
world.
Recent changes in the military are impacting social values of
warfighters and therefore likely to impact high self-monitoring consumers’
behavior. Dunivin (1994) discussed the ongoing and evolving nature of
social conflicts within the military that impact social norms. One example
was the traditional model of a married man and woman versus the new
model of a same-sex couple. As Dunivin (1994) expressed it, the “cult of
masculinity” was challenged by a world of outsiders who were considered
deviants in a man’s world. The family model within the military went
through extensive restructuring against a tide of tradition as well as self-
concepts. Changed cultural influences have impacted perceptions of military
consumer products such as clothing styles (e.g., dress slacks versus skirts
and related body image conveyances). Cultural sensitivity and awareness of
changes within the culture allow clothing designers a broader range of
acceptable clothing options that will be used by military consumers.
Other changes in the military culture are also noteworthy. The nature
of warfare has undergone change that impacts the duration, frequency, and
nature of deployments (Hajjar, 2014; Scales, 2018). Warfare has changed in
the nature of the size, lethality, and speed of force-on-force combat.
Powerful and significant physical changes have occurred in planned,
symmetrical large-scale military operations to unplannable, small-scale,
asymmetrical warfare that rely on different, complex, and unpredictable
fighting environments with dynamic and small-scale resources needed to
fight in complex and unknowable situations (Hajjar, 2014; Scales, 2018).
These changes impact soldiers’ sense of threat management and what is
socially appropriate among their peers.
Military consumer researchers have underscored the need to facilitate
warfighter performance by presenting products in ways that increase product
acceptability. Cardello et al. (1996) conducted research to validate previous
consumption-attitude related studies (Cardello, 1994; Cardello et al., 1985;
Cardello & Sawyer, 1992; Tuorila et al., 1994). This included an effort to
confirm the notion that negative stereotypes of institutionalized foods biased
perceptions of products. In a series of studies, Cardello et al. (1996)
examined the impact of civilian and military consumer perceptions on rating
products from various sources. Using a 9-point hedonic scale, soldiers and
civilians rated how much they thought they would like the items before
eating them. Consideration was based on foods imagined to be from
different sources. For example, the consumers were asked to rate how much
they thought they would like the food items when the source was home, a
military dining hall, or a restaurant. The researchers assessed levels of
dislike/like for common food items soldiers ate (i.e., scrambled eggs, toast,
steak, hamburger, spaghetti and meatballs, French fries, baked beans, dinner
rolls, apple pie, gelatin, coffee, and soft drinks). Cardello et al. (1996) found
military food acceptability ratings were significantly lower because of a bias
against institutionalized military food. They found that soldiers had
significantly more negative attitudes about food items (excluding gelatin,
coffee, and soda) when the soldiers thought the items would be served in a
military setting as opposed to a noninstitutionalized setting such as at home
or a restaurant. Nonmilitary personnel had similar responses to the soldiers.
Civilians gave significantly poorer ratings of their expectations for food
items served in military dining halls. This indicated a common negative bias
existed toward items served in military dining facilities compared to home
and restaurants. The expectation differences in both military and civilian
consumer groups caused them to rate military foods lower than name-brand
foods even when the foods were essentially the same. Cardello et al. (1996)
also found that this food-source bias continued to influence ratings of the
food products after eating.
To compare after eating results, Cardello et al. (1996) conducted
another test whereby military and civilian consumer groups were each
provided two lists of 30 different yet common foods. The foods on the lists
were the same for each group. Consumers were asked to rate the food items
on the lists by how much they thought they would like the foods if they were
to eat them. For one list, the consumer groups were to assume the items were
from home, a restaurant, or purchased at a supermarket. For the other list,
the consumer groups were to assume the food items were in standard
mealready-to-eat (MRE) field rations. The consumers were instructed to rate
what they expected the foods to be like if served under normal conditions
(i.e., at home/restaurant or in the field). The ratings for military foods were
significantly lower than the home/restaurant/supermarket foods for both
civilian and military consumer groups. Then Cardello et al. (1996) provided
soldiers a list of foods to rate how much they would normally like/dislike
those foods when served at home, a restaurant, or when they were from a
supermarket. Those ratings acted as a baseline for a second part of the study.
The 30 foods were served to them later in the week to be eaten in the field as
a part of their MREs. After receiving and eating the foods, the soldiers rated
the foods. The researchers compared the two different sets of ratings and
found the ratings for the foods actually eaten were significantly higher than
the baseline ratings soldiers gave earlier. They determined that this
confirmed the negative bias against military foods.
Cardello et al. (1996) also sought to manipulate expectations for food
(by labeling it as commercial or MRE) and compared those results against a
baseline measure of the same food to look for a label effect. The consumers
tasted the leading commercial brand of corn. The corn was not labeled nor
was there any other identifying information provided to consumers as to its
source. After tasting, consumers rated the corn on a 9point hedonic
liking/disliking scale. This established a baseline score for the corn
independent of labeling. Days later in two separate tests, the same corn was
presented to civilian consumers to evaluate under two different contexts. In
context one, the corn was labeled and identified as if it were the leading
commercial brand of corn. In context two, the corn was labeled and
identified as if it were MRE corn. In each context, before tasting, the
consumers were asked to rate how much they thought they would
dislike/like the labeled corn. Then the consumers tasted the corn and rated
again how much they disliked/liked the corn after tasting. Results showed
corn labeled as the leading commercial brand (context one) was rated
significantly higher than MRE labeled corn (context two) in both conditions
(i.e., before and after tasting). This study demonstrated a pre-existing bias
against military labeled/packaged food that influenced the liking of the food.
Consumers consistently rated the MRE labeled corn significantly lower than
the leading commercial brand. The study also showed a positive bias for
other label expectations. When the leading commercial label was used, there
was an unjustified boost pushing the score above the baseline rating. The
results showed that the two identical corn products were rated significantly
differently from each other based solely on the commercial label and MRE
label used to identify them. These results demonstrated an anticipation or
expectation bias associated with labeling.
MRE and commercial label brands biased the ratings in the two
evaluations to reflect significant differences between the two. The branding
effect was positive for the commercial label and negative for the MRE label.
The authors (Cardello et al. 1996) indicated that these series of studies
demonstrated a negative bias conveyed from institutional foods like the
military’s MRE. They further concluded that even if actual improvements
were made to the ration’s quality, this would be a slower and less desirable
approach of improving acceptability of military rations because the reason
for being unacceptable was due to brand-image-perceptual notions rather
than due to actual quality attributes of the foods. They recommended efforts
be focused on developing better consumer marketing strategies based on the
origins of the negative biased consumer attitudes and expectations. It was
reasoned that addressing the origins would lead to better advertising and
labeling approaches that could convey a positive image to reduce negative
stereotypes, biases, and misconceptions. Use of self-monitoring constructs
may help confirm origins of perceptual notions or create improved
perceptual notions. Biasing effects can be seen as a sort of self-fulfilling
prophecy whereby a person’s thoughts and behavior are biased by the
preconceived expectations of others. These expectations are sometimes
related to social values or personal identity values.
The existence of bias against military institutionalized food is
important to recognize because it impacts military nutritional health
programs such as “THOR3” (Tactical Human Optimization, Rapid
Rehabilitation and Reconditioning). The THOR3 program uses a holistic
approach to improve diet, physical performance, and mental performance
under the United States Special Operations Command (Fisch, 2015). Such
programs rely on marketing and presenting information about food to break
down stereotypes and to provide nutrition training based on science and
evidence derived from research that exposes faulty ideas and brings facts to
light. Effective marketing translates to improved product utilization and
consequently a more effective warfighter.
Kramer (1995) described the overall feeding situation soldiers find
themselves in. He emphasized an economic viewpoint of the eating
situation. Such a viewpoint, he suggested, is one where soldiers make eating
decisions with a view to minimize use of limited resources. These decisions
are based on a complex environment where an acceptable balance must be
achieved that considers the soldier’s mission, physical and nutritional needs,
and desires. Kramer emphasized that the economy of eating in the field often
leads to under consumption. Social eating (in the company of other soldiers)
generally produced higher consumption rates of food (de Castro, 1995). This
is a desirable state because soldiers often lose weight when in the field;
soldiers entering a field condition may under consume and lose weight too
quickly, leading to a loss of lean muscle mass and diminished performance
(Friedl, 1995). Diet is not the only factor associated with reduced
performance, yet it was important enough that scientists on the Committee
on Military Nutrition Research recommended a general effort to increase
eating of foods by soldiers in the field as a hedge to stave off diminished
performance Nesheim et al., 1995). Social considerations should be used to
help identify opportunities for increasing consumption in the field (de
Castro, 1995; Nesheim et al., 1995; Mays, 1995). Self-monitoring represents
a tool to help increase consumption through better understanding of the
drivers of liking and consumption among military consumers.
Decision making in complex environments such as those experienced
by warfighters, can cause cognitive overload (Chérif et al., 2018).
Complexity and cognitive decision constraints are part of the culture and
environment military consumers live and work in, especially when on the
battlefield. Consequently, environmental variables may cause consumer taste
and flavor attributes to influence their acceptability less than basic functional
attributes such as bulk and weight. Dewitte et al. (2005) found cognitive
loads on consumers to have a significant effect on consumer decision-
making abilities with respect to product evaluations, brand choices, and food
quantities consumed. Neurophysiological constraints also limit human
sensory perceptual abilities. As mentioned earlier, the average adult human
is only able to perceive about four things in mind at a given time (Buschman
et al., 2011, Miller, 2020, Rigotti et al., 2013). Constraints on warfighters
such as limited decision-making time, limited experience, limited retention
of information, limited ability to perceive situational cues, limited cognitive
abilities, physical fatigue, and higher order cognition needs might all be
considered to be part of the consumer’s economic viewpoint for
consumption behavior referred to by Kramer (1995). These constraint
factors in the military environment demonstrate conditions that impact
cultural norms which may be discovered in the way low and high self-
monitoring consumers respond differently to the scenarios analyzed in this
study. Consumer cognitive overloads inhibit a contemplative approach to
consumer choices and expedite or force choices when the environment is
dynamic and complex (Chérif et al. 2018). Constructive decision-making
strategies are based on thought patterns, experience, and accessible
information within an environment where there has been time to process and
formulate product valuations (Bettman et al., 1998).
Another aspect of the warfighter that self-monitoring impacts is the
notion of personal property and the attachment a soldier may make with it.
Many of the items a soldier possesses or uses are not “personal property.”
The government issues food, clothing, and equipment to soldiers to use or
consume. Therefore, these may not hold the same personal identity
relationship to the soldier as they might to civilians who purchased similar
items. Identity theory tells us that self-definition emerges from the iterative
process of appraisal regarding possessions and performance (Laverie et al.
2002). Thus, a soldier’s notions of self or self-identity as they relate to
products may be different from civilians. What appeals to a low-self
monitoring civilian consumer may not appeal to a low-self monitoring
military consumer.
Definitions of self are driving factors of behavior for low self-
monitoring consumers. Changes to self-identity impact both low and high
self-monitoring military consumers. Some identity influences are imposed
upon the soldier by nature of the military culture and are not necessarily of
their own choosing. If self-monitoring trends in civilian consumer data are
reflected in the military, whatever is salient and meaningful to the soldier
may become the decision criteria used to evaluate products. Hence, to
increase product liking (and utilization), the military may need to consider
notions of self that relate to military consumer decisions and attitudes. That
means product branding should be clear and unmistakable. It means the
message conveyed in the branding should be very well aligned with the
attitudes warfighters have and sensitive to the type of decisions warfighters
make and the context in which they are made
Another difference with military consumers has to do with freedom to
choose their goals and manager their time. Self-monitoring is influenced by
a consumer’s goals, roles, time constraints, and motivations (e.g., consider
the subtle luxury branding for the wealthy elite and bold luxury branding for
those aspiring to wealth) (KauppinenRäisänen et al., 2018). The options to
exercise these types of freedoms are controlled by military leaders (e.g.,
leadership roles, mission objectives, commendation practices, etc.) and often
imposed on soldiers. Soldiers give up a number of freedoms to commanders
and are subject to punishment if not compliant with all lawful orders. This is
because the military culture also includes a different legal system and
punishments than the typical civilian judicial system. The military utilizes a
legal system called the Uniform Code of Military Justice (UCMJ).
Under the UCMJ, the soldier can be forced to do things (such as wear
a particular item of clothing) or be punished for disobeying orders that
civilians are not accustomed to (Dunivin, 1994). For example, as
“government property” soldiers could be punished for not putting on
sunscreen when told to do so if they get a sunburn. There is a clear
command hierarchy, persistently reminding a soldier that not all decisions
get to be based on what they personally want but are based more on a
collective need. Military consumers are taught and compelled to consider the
needs of the group and essentially trained in the interdependent self-
construal way of thinking. Military society deliberately teaches values such
as loyalty, duty, respect, selfless service, honor, integrity, and personal
courage. These cultural values may provide enhanced identity for the
soldier, and clearer structure for important social appeals in a well-defined
command structure. Consequently, these values that may influence social
identity and social enhancement can be very different from those in the
civilian world. These factors directly impact the value constructs and
attention of the high self-monitoring military consumer. They also impact
the low self-monitor who seeks congruency between self-identity and
products that reinforce that identity.
The military culture may impact social identity and as such may be a
source for Pygmalion effects (i.e., when a person’s positive expectations of
another target person led to a positive influence on the target). Several meta-
analyses suggested differences between military organizations and civilian
organizations, indicating that military groups experienced a stronger
Pygmalion effect (Kierein & Gold, 2000). Fleenor et al. (2010) reported
Pygmalion effects seem more sizeable in the military than they do in
business settings. Business and military personnel seem to share a core
element of the Pygmalion effect, both having strong hierarchal relationships
between leaders and subordinates. McNatt (2000) predicted that military
culture would lend itself to better Pygmalion effects due to the natural
setting where soldiers adhere to commands and would, therefore, be more
open to sources that were credible. Hence, a stronger Pygmalion effect
should be seen in the military as opposed to a civilian setting. However,
McNatt’s (2000) meta-analysis did not confirm the prediction. McNatt
(2000) did note some differences between military and civilian studies that
could explain this result. For example, the sample size of civilian
comparisons was small (6 studies). In addition, the researchers who
conducted military studies used stronger Pygmalion interventions than those
conducting the civilian studies.
Kierein and Gold (2000) also conducted a meta-analysis of Pygmalion
effects with similar results to McNatt’s (2000). They considered the
organization as a moderator because the Pygmalion phenomenon in different
organizations might operate differently. Pygmalion effects in military
settings were significantly stronger than in business settings. Kierein and
Gold (2000) suggested five explanations for the result differences: (a)
military leaders had more overt control, (b) military personnel were more
closely monitored, (c) military personnel were more likely to adopt a
leader’s perspective because they are not in a position to question leaders
who play a more salient role, (d) subordinates were typically younger in the
military than subordinates in business settings, and (e) methodological
nuances and differences among researchers. Regardless, if the suppositions
are correct, differences between the military and business cultures could be
seen; the military was more positively impacted by positive expectations.
Whether or not those differences are due to external standards related to
culture and social norms within the military, or due to internal personal
standards related to individuals in that segment of the military, remains
unclear. Self-monitoring can reveal those differences between low and high
self-monitoring groups.
According to Hajjar (2014), military consumers have complex and
fragmentary elements to deal with such as battlefields, nontraditional
missions, emergence of “peace missions” with complexity and the general
chaotic nature of warfare. These cultural elements are changing
dramatically. The military culture includes harmony, tradition, symbolism,
and other multiple-overlapping cultural influences such as leadership,
followership, multirole versatility, tools, and orientations. Recently, two
influential orientations were identified that currently co-exist within the
military culture (Hajjar, 2014). These orientations are oppositional and
conflicting. One is the warrior orientation, and the other is the peacekeeper-
diplomat orientation. Their presence in the culture likely puts soldiers in a
position of reflection regarding their internally held standards and society’s
standards. This thought chain appraisal process influences self-monitoring,
product valuation, and brand choices (Laverie et al., 2002).
From 1900 to 1990, the military consisted of a dominating orientation.
This era included the warrior identity, a command orientation to actively
direct, impose, order, tell, demand, and take charge. It also included a
traditional combat orientation to destroy, kill, capture, dominate and
dehumanize. Rigid rule enforcement and a United Statescentric orientation
were hallmarks of this era (Hajjar, 2014). This culture was generally more
stable, and the self-identity of the soldier was clearer and more predictable.
The more stable self-identity of the soldier could allow for less diverse and
more predictable self-monitoring cues to be presented to the soldier to
influence their consumer behavior and attitudes.
From 1990 to the present, the soldier’s self-identity is influenced by a
peacekeeper-diplomat orientation now associated with the warrior identity,
multicultural worldview, humanization and sensitivity, and similar
leadership efforts to listen and learn from people who are diverse and
empower them, engage in unconventional tasks, and stretch rules (Hajjar,
2014). Present challenges in the military include complex views and span a
large domain of multidimensional considerations. Though soldiers from both
orientations are present in today’s military, these significant and impactful
orientations are expected to merge, and cultural adaptation will arise to
constitute what will be an emergent postmodern United States military
culture (Hajjar, 2014). This military cultural turbulence influences military
consumerism because they influence notions of self. Changing self-notions
can be expected because of the appraisal process and malleable self-concept
(Aaker, 1999; Laverie et al., 2002). Saliency of a military consumer’s
strate7gies to achieve self-worth through consumer behavior that is
congruent to selfconcepts can diminish when there are cultural changes and
uncertainties that influence self-identity. The result to providers of military
consumer goods is reduced certainty in how to predict and provide products
the military consumer will like. However, results from the study may assist
military leaders and producers of military consumer goods to develop
products that convey salient images that are congruent with healthy self-
notions being fostered by military leaders.
Hajjar (2014) discussed other cultural complexities such as the
military’s handling of social issues related to sexuality. The inception and
then abolition of the “don’t ask, don’t tell” policy (1993 and 2011,
respectively) created cultural missteps in different directions that would push
soldiers into positions of reflection and the appraisal process wherein
questions of their self-identity could emerge with altered strategies to
achieve self-worth through consumer behavior. Actual organizational and
cultural practices changed in order to accommodate social expectations
related to these policy changes.
Hajjar (2014) reported complexity in the United States’ military strategy in
Afghanistan. The complex relations of many coalitions required strong skills
within the peacekeeperdiplomat orientation. These issues pertain to the
culture of the military consumer’s life and help form a warfighter’s cultural
identity and aspects of self-identity.
Self-Monitoring as it May Relate to Military Consumer Decisions and
Behavior
The study used self-monitoring constructs as independent variables
with military consumers through analysis of archival data. Self-monitoring
and self-monitoring subdomain styles are included in this study. Acquisitive
and Protective scales similar to
Acting, Extraversion, and Other-Directedness scales were not evaluated
(Wilmot, 2015). Military demographics were included as additional
independent variables. The relative strength of the independent variables to
predict the dependent variable of liking.
Demographic information and liking scores based upon a nine-point hedonic
scale have been used in the past to improve military consumer products for
decades (Meiselman & Schutz, 2003). The same factors were used in
conjunction with self-monitoring constructs for comparison. The results
provide direction in future use of self-monitoring constructs to improve
military products in the future.
Military cultural values form the basis of military indoctrination and
help forge the soldier’s value system. Seven values are taught during initial
training and emphasized throughout a soldier’s military career, including
loyalty, duty, respect, selfless-service, honor, integrity, and personal courage
(TRADOC, 2019). Clothing, ribbons, ceremonies, and other military
traditions impact military consumers’ thinking. One would expect
motivation, emotions, and cognitive processes to be affected. Consider the
soldier’s creed taught repeatedly in the U.S. Army and, like the values, the
creed is included in the soldier’s guide for initial entry training (TRADOC,
2019). The soldier’s creed (soldiers are encouraged to memorize and live
their lives by the creed), summarizes the American Soldier’s role, duties,
and attitudes and is meant to inspire and sustain them when in harm’s way.
The values and creed are only two of many institutionalized efforts
meant to teach and exemplify military culture. They underscore group
membership with an interdependent element of self. Loyalty to the group
and subjugation of individual selfambitions are typical of collective cultures
that emphasize the impact of an individual’s behavior on the group. These
factors influence self-definitions and group expectations.
They influence one’s social identity. They are integral to self-monitoring
theory’s usefulness in understanding military consumer behavior.
The military culture has been shown to differ from civilian culture
(Dunivin,
1994; Hajjar, 2014). Another obvious difference is the clothing and emblems
worn. Tradition and uniformity are important and what one wears is dictated
to personnel within the military culture as opposed to civilians who have
more freedom to wear clothing of their own choosing. Culture is an
influencing factor for military consumers who have their own unique and
complex cultural conditions. The military culture includes both collectivist
and individualist traits. The United States, Australia, and other Westernized
countries such as those in Western Europe exemplify regions where
individualistic cultures dominate. These cultures explain social thinking and
behavior through individual attributions of self-reliance, independence, and
personal uniqueness (Moosavi, 2018). The military culture values other traits
such as loyalty, duty, respect, selfless service, honor, integrity, personal
courage, and tradition that could impact military consumer behavior as well.
One would expect these cultural factors to impact a person’s motivation,
emotions, cognitive processes and, consequently, self-monitoring theory’s
usefulness in understanding military consumer behavior (Christopher &
Bickhard, 2007; Markus & Kitayama, 1991).
This study was conducted because military consumers should be
viewed separately from civilian consumers. Gudykunst et al. (1989)
examined five cultures and found weaknesses in how self-monitoring fit
cross culturally. Snyder (1979) concluded that high self-monitors would
imagine a prototypic person’s behavior for a given situation and then seek to
emulate that. In contrast, low self-monitors would refer to an enduring self-
conception of how they imagined they would act in a given situation.
Gudykunst et al. (1989) argued that Snyder’s scale focused on aspects that
predominate in individualistic cultures and do not predominate in
collectivistic cultures. The military possesses some collectivistic tendencies
and should be examined separately.
Gudykunst et al. (1989) argued that collectivist cultures include active
selfmonitors who are not captured in Snyder’s (1974, 1979)
conceptualization of selfmonitoring. The cultures utilized in-groups where
the “we” mattered in maintaining social harmony more than the “I”
perceptions central to individualistic cultures (Liu & McClure, 2001). The
original self-monitoring framework accounted for aspects of self that
dominated individualistic cultures. Aspects of collectivistic cultures included
a selfidentity that was fundamentally tied to an individual’s relatedness to
each other. Americans for instance do not assume nor value an over
connectedness but instead seek to attend to their uniqueness. Consequently,
self-identity, self-esteem, and self-worth are viewed and pursued differently
with respect to high self-monitors (Markus & Kitayama, 1991). Since most
researchers in the last four decades were focused on a unidimensional view
that used aggregated data; subtle nuances which might otherwise have been
revealed using more narrowed and multidimensional framing (i.e.,
acquisitive vs. protective self-monitoring) were sometimes hidden in the
aggregate. A culturally sensitive approach is needed by researchers to ensure
self-monitoring-theory-based research considers salient consumer goals and
salient, congruent consumer products images.
Blind spots to cultural mediations can come in the form of traditions
and expectations that the researcher is unaware of. Take for example the
case of public humiliation. In collectivist cultures, the humiliation of one
person is a humiliation of the self-identity of others as well because the
identities are interrelated. In Spanish cultures there is a term for this called
“pena ajena” (the embarrassment felt when watching the humiliation of
another person). Contrast that with another culturally derived word
“shadenfreude” (the pleasure one feels from someone else’s humiliation or
misfortune) a
German word from Western cultures and one’s self-esteem attempts to
protect oneself (Hoffman, 2020). These words are derived from cultures
where those sentiments are more common and suggestive of the differences
between collectivistic and individualistic cultures. Motivations in self-
monitoring are tied to words a culture uses to influence a person’s
perception of self. Commonly understood motivations related to the
interdependent nature of collectivistic societies were overlooked when self-
monitoring constructs were first formed. This study helps redress that gap.
The complexity and multidimensionality of military culture makes it
ideal for examining the suitability of self-monitoring to evaluate influences
on consumer behavior (Dunivin, 1994; Hajjar, 2014). Military culture offers
dimensional aspects associated with self-monitoring theory that can be
reviewed and refined. These dimensions include group expectations and
individual values. It includes various product types (utilitarian and social
identity) and audiences (public or private) that the products are designed for.
Civilian-oriented products transferred for use in the military may be
underutilized because they have less appeal to military consumers. Product
developers should keep this in mind. Product optimization occurs in part
through military consumer feedback and complaints (Cardello et al., 2012;
Headquarters, 1990; Meiselman & Schutz, 2003; Scales, 2018).
Understanding what motivates military consumers to provide or withhold
complaints may help foster a more effective complaint process and product
improvement system. Self-monitoring theory has been useful in explaining
complaint processes in some civilian situations (Baker et al., 2013;
Gudykunst et al., 1989; Hu & Parsa, 2011; Liu & McClure 2001; Sharma et
al., 2010; Wan, 2013). The current study examined the role of self-
monitoring relative to consumer complaint behavior in the military culture.
There are several factors involved in understanding consumer
complaint behavior. Use of self-monitoring theory has shown its utility in
identifying motivations for civilian consumers. It was reasonable to assume
that the construct may be used to clarify some of the consumer complaint
behavior challenges seen in the military. Not all challenges in the military
are dissimilar to challenges in the civilian sector. For example, according to
the Institute of Medicine (2003), obesity is a problem for the U.S. Military
as well as for the civilian population (Almond et al., 2008). It is a complex
issue to maintain proper body weight and health. Even though there are
problems with soldiers not eating enough under some circumstances (Baker-
Fulco, 1995), there are other circumstances wherein they share the civilian
plight of obesity. Shared elements of culture between civilian and military
consumers suggest self-monitoring theory might have answers or at least
merit its use in consumer research. That is why self-monitoring theory was
used here. The caveat here is that researchers who are also individualistic (as
opposed to interdependent in their self-construals) tend to expect consumer
behavior to be motivated also by individualistic tendencies. In reality, those
motivations are complex and need vetting. The core issue is to identify the
consumer’s individual consumer goals, which are often determined by the
salient version of self-occupying the consumer’s mind at the time of making
a consumer decision. Then, assure saliency of the product’s conveyances are
congruent with the consumer goals. Self-monitoring theory can confirm
these relationships.
Scales (2018) discussed how effective military consumer research
provides knowledge that leads to increased military consumer satisfaction
and effectiveness within the military. This, in turn, results in more successful
military campaigns and greater protection for the nation. Giving civilian
consumer products to the soldier that mismatch expectations or goals can
lead to disgruntled or discouraged soldiers. Some aspects of the military
culture are unique and need further characterization to understand. Just as
Liu and McClure (2001) pointed out, the culture itself may be defining who
the “in-group” is and consequently how a high self-monitor might want to
adapt their behavior to in order to appeal to that cultural ideal. Knowledge is
critical to understanding how high selfmonitoring warfighters would target
his or her behavior to acquire a social benefit. Military culture may uniquely
define who is in the social class of influence and importance. The military’s
dynamic changing culture (Dunivin, 1994; Hajjar, 2014; John, 2021; Kieran,
2020), may have social sub-classes that value products differently (e.g.,
combat arms versus logistical support). For example, the flavor of a
breakfast entrée may be of low value to elite members of an infantry platoon
on a mission but to those working in a tedious office out of harm’s way, it
matters more. Culture, context, self-identity, all matter and can be couched
within the self-monitoring theory.
A continuum of environmental stressors associated with life and death
decisions in the military culture may nudge otherwise carefully considered
consumer goals outside the domain of the military consumer’s chronically
normal decision-making processes. At that point, the context, exigency, and
reliance on habits and trained actions may prevail (Lin et al., 2016).
Consumer behavior decisions are often constructed in ways that consider the
importance of different identities and salient product attributes that appeal to
one’s perception of who they are (Kleine et al., 1993). These notions of self
are developed and influenced by culture and other environmental conditions
and experiences. Cultural influences in the military are unique and complex
because they deal with different laws of accountability imposed by the
commander in chief and other leaders where behavior is compulsory, and
choices are limited. There can be extreme consequences for those who join
the military (deployments, separation from family, difficult training, killing,
formidable opposition, witnessing death, austere living conditions).
Uncertainty for combat soldiers with an oppositional foe, who must be
sought out in environments where the soldiers have little background or
familiarity, can be stressful. In short, research is needed to expand
information and mediate negative influences in the lives of military
consumers to give them products that provide the best chance possible to
survive and thrive in military environments. Self-monitoring provides
another tool to help characterize what is meaningful to soldiers and help
provide products that meet their individual and collective needs.
Summary and Conclusions
Self-monitoring refers to individual differences in tendencies defined
in terms of low and high self-monitors. Low self-monitors focus more on
maintaining congruency with salient notions of self. High self-monitors use
social norms and cues to focus on acting in ways that enhance social
identity. Self-monitoring tendencies have been used in civilian consumer
research to understand and predict consumer behavior and attitudes. Military
practices influence self-identity and social enhancing values. Self-
monitoring may be used to better characterize military consumers to help
them better accept and use military products. This research offered a chance
to establish self-monitoring as a research tool to evaluate military consumer
attitudes and behavior. In Chapter 3, I discuss the research design and
rationale, the methodology, the instrumentation and operationalization of
constructs, the data analysis plan, threats to validity, and ethical
considerations.
Chapter 3: Research Method
I used a quantitative, nonexperimental, correlational design to
determine the extent to which self-monitoring constructs (Self-Monitoring,
Acting, Extraversion, and Other-Directedness) and specific demographic
variables (gender, leadership, time in service, deployment experience, and
combat experience) predicted military soldiers’ ratings (liking/disliking) of
military products. This chapter includes sections that describe the research
design and rationale, methodology (population, sampling and sampling
procedures, and procedures for recruitment, participation, and data
collection), instrumentation and operationalization of constructs, data
analysis plan and research questions, description of archival data, threats to
validity, and ethical procedures.
Research Design and Rationale
This research study used a quantitative, nonexperimental, correlational
design using archival survey data. The data were collected from surveys
administered to military personnel in 2013. The surveys included product
scenarios, military consumer evaluation ratings, a soldier demographic form,
and a self-monitoring personality instrument. Product scenarios were read by
soldiers. The scenarios described the use of each product type (i.e., food,
clothing, equipment) in typical military situations. Soldiers provided
consumer liking/disliking ratings based on the product scenarios. The
product ratings of liking/disliking served as the criterion variable. The
criterion variable utilized a 9-point liking/disliking (hedonic) scale.
The demographic information provided five military consumer
attribute measures that were used as predictor variables. Those attributes
included gender, leadership (based on grade), years of service, deployment
experience (i.e., being moved into position for military action), and combat
experience. Within the U.S. Army, pay-grade levels are generally
commensurate with leadership roles. There are three basic groups: Enlisted
(Egrades 1-9), Officer (O-grades 1-9), and Warrant Officers (W-grades 1-5).
E-grades 5-9, all O-grades, and all W-grades are generally considered
leadership grades. In some cases, an E4 can be leadership also. But for the
purposes of this study, E5-E9 and all O and W grades were considered
leaders. Grades E1, E2, E3, and E4 were counted as nonleaders. Deployment
was either “no” (for zero deployments) or “yes” for any number of
deployments. Combat experience was counted similarly to deployments:
“no” for zero number of times that combat has been experienced and “yes”
for any number of times that combat has been experienced.
The self-monitoring instrument measured four additional predictor
variables, namely the overall self-monitoring score and three self-monitoring
subscale scores
(Acting, Extraversion, and Other-Directedness). The variables are shown in
Table 1.
Table 1
Independent and Dependent Variables
Variable
category
Variable
type
Variable Scale of
measuremen
t
Instrumen
t
Scor
e
type
Criterion Dependent Liking/
disliking
Interval Hedonics 1-9
Demographi
c
Independen
t
Gender Dichotomou
s
Survey 0, 1
Demographi
c
Independen
t
Leadership Dichotomou
s
Survey 0, 1
Demographi
c
Independen
t
Years of
service
Dichotomou
s
Survey ≤5,
>5
Demographi
c
Independen
t
Deployment
exp.
Ratio Survey 0-6+
Demographi
c
Independen
t
Combat exp. Dichotomou
s
Survey 0, 1
Self-
Monitoring
Independen
t
Self-
Monitoring
Interval SMS-R 0-18
Self-
Monitoring
Independen
t
Acting Interval SMS-R 0-3
Self-
Monitoring
Independen
t
Extraversion Interval SMS-R 0-3
Self-
Monitoring
Independen
t
Other-
Directedness
Interval SMS-R 0-5
The design was intended to identify relationships between the
predictor variables and the criterion variable (liking/disliking). Six standard
multiple regression analyses were performed, one for each of six different
product-scenarios. The same criterion variable of military consumer
liking/disliking was used for each product type.
The nonexperimental correlational design of this study determined
relationships between the dependent (criterion) and independent (predictor)
variables. Although the relationships between independent and dependent
variables do not establish cause and effect, the strength of the relationship
may provide insights into how self-monitoring constructs are related to
military consumer behavior. Insights discovered through this study could
lead to future experimental studies that identify causal effects of the
selfmonitoring personality trait on military consumer behavior.
Methodology
Population
The target population was U.S. Military members stationed at or in
training at Fort Riley, Kansas, in September of 2013. During the time of the
sampling, Fort Riley had approximately 18,600 active-duty service
personnel at the post. This number does not include the approximately
20,000+/year National Guard, Reserve, and ROTC who trained there during
the year and who also might have been available to participate in the survey.
At the time of the survey, the post was a division-level training installation
for the First Infantry Division and included a mix of five brigades that
included armor, infantry, aviation, and combat support elements. The
population was not screened to exclude people of different races, religions,
genders, ranks/grades, or military experience.
Sampling and Sampling Procedures
The sampling plan relied on surveys being administered through a
convenience sampling. Access to soldiers was limited due to a command
structure culture where training and mission factors impact soldier’s
freedom, time, and ability to participate in surveys. Research that involves
military consumers is often done with a convenience sample due to these
inherent access limitations in the military. Researchers often consider these
data sets to be normally distributed because efforts are typically made to be
representative of a targeted population. The targeted sampling goal was
200+ participants. A total of 220 responded and completed the surveys. The
sampling was considered to be representative of the combat arms population
at Fort Riley, KS at that time.
The Operational Forces Interface Group (OFIG) was responsible for
acquiring access to soldiers for survey work. The CRT was responsible for
survey design and coordinating the sampling parameters with the OFIG. The
CRT and OFIG worked together to identify and stipulate criteria for
administration of the surveys. In the sampling effort, the researchers sought
as much as possible a representative sampling of combat arms soldiers who
were stationed at Fort Riley. The OFIG sampling procedures included
gaining background knowledge of various operational forces’ activities and
training schedules, establishing rapport with unit commanders, establishing
contact permission and troop availability. A pre-evaluation commitment
from commanders made it so that soldiers were given the time to participate
if they chose to. Soldiers received briefings regarding participation and were
told that their participation was voluntary. The CRT made the request for a
sample size greater than 200 during an evaluation scheduled to occur in
September 2013. The OFIG contacted the necessary military leadership. The
chain of command reviewed training schedules and identified soldiers that
met the criteria and then coordinated with those soldiers’ immediate unit
leaders to check their availability. Once confirmed available, the OFIG
coordinated briefing times with soldiers and their leaders. The OFIG
representative received the surveys from CRT members and presented
briefings to different groups of soldiers and their leaders. After the briefing,
those present who volunteered took the survey or agreed to complete it at a
later time. Leaders assisted by briefing soldiers and coordinating their
participation in assuring that surveys were distributed and recovered from
soldiers that chose to participate. The OFIG oversaw survey distribution in
conjunction with the coordinated efforts of the chain of command and was
responsible for ensuring that leaders briefed the respondents without bias on
how to complete the surveys. The OFIG and military leaders were
responsible for the surveys until they were returned to the CRT. The OFIG
representative and chain of command used discretion to determine the
timing of distribution and collection of surveys to maintain flow of military
training and operations. After the paper and pencil surveys were completed
(time to complete surveys was about 20 minutes) and collected by the OFIG
representative, the surveys were returned to a member of the CRT for
securing and sorting.
I performed a power analysis using G*Power to determine the sample
size needed for linear multiple regression (Faul et al., 2007). The parameters
entered into G*Power included: (a) an anticipated effect size of .15
(Gangestad & Snyder, 1985), (b) statistical power level of .95, (c) nine
predictor variables, (d) and an alpha of .01. An alpha level of .05 is often
used (Zint, 2015), but I used the more conservative level of .01 for this study
because I am conducting several multiple regression analyses and want to
reduce the chance of Type 1 error (Tabachnick & Fidell, 2013). Based on
these parameters, the recommended sample size was determined to be 214.
Procedures for Recruitment, Participation, and Data Collection
Data were collected in September 2013 as per OFIG and CRT
standard survey administration practices described earlier. The practices and
procedures for recruiting, as stipulated in the sampling section, involved
planning through military channels by the OFIG with target demographics
set by the CRT. As a member of the CRT, I had access to the data and
received permission (see Appendix F) from the CRT team leader to use the
data for the purposes of this dissertation project.
The target demographics were for active-duty soldiers in primarily
infantry and cavalry combat units. The CRT has primary responsibility for
that data and its usage. The data have no personally identifiable information
associated with them. Those who collected the data never analyzed them.
Informed consent for the participants was established verbally. After hearing
a briefing which included a short overview of the survey, the volunteers
were allowed to participate if they chose to. Military leaders were tasked
with briefing volunteers who missed the initial briefing but who later chose
to participate in the survey. Military leaders distributed and gathered
completed surveys from volunteers who participated when OFIG was not
present. The OFIG representative gathered the completed surveys either
directly from the soldiers or their respective leaders. After the surveys were
collected, no further follow-up or debriefing occurred with participating
soldiers. Participant anonymity was maintained. The OFIG representative
debriefed the leaders only to the point of confirming that the sampling target
number had been reached.
In some cases, surveys were completed with the OFIG representative
present. Other times, the OFIG representative returned the next day or
several days later to pick up the surveys either from the soldier or from the
leader of a group of soldiers. Such administrative freedom is a common
survey practice with soldiers who are in the field. Frequently, military
leaders determined when soldiers could have time to complete the surveys.
After OFIG received the completed surveys, the surveys were returned back
to the CRT. There were 220 survey packets returned. Data collection
occurred over approximately a 2-week period.
Instrumentation and Operationalization of Constructs
Product Scenarios
No actual products were used by soldiers. Instead, soldiers provided
evaluations of military products after reading written product scenarios.
There were three product categories: food, clothing, and equipment. Within
each category, there were two products or conditions—one with an appeal to
low self-monitors and the other with an appeal to high self-monitors. Thus,
within the three categories, there were the following: (a) food, two types of
MRE snacks; (b) clothing, two types of socks; and (c) equipment, two types
of complaint conditions with a faulty, rifle-ammunition magazine. One half
of the product category scenarios (MRE/sock/magazine) were written to
appeal to low selfmonitoring personality traits. The other half of the product
scenarios were written to appeal to high self-monitoring personality traits
(i.e., the low self-monitor’s appeal was based on functional quality traits and
the high self-monitor’s appeal was based on social influence traits).
The military consumer product scenarios were evaluated by the
soldiers using the liking/disliking rating. For example, in one food-category
scenario there was an appeal to functional quality with a description of an
unpopular but nutritional MRE snack. Soldiers were given the scenario and
asked to rate how much they would dislike or like that type of snack on a
scale of 1 to 9 with 9 being the highest degree of liking. The other
foodcategory scenario provided a social appeal by describing a popular but
less nutritional MRE snack. This pattern was repeated in all the scenarios. In
the clothing-category scenarios, one scenario required the soldier to rate
socks that were described as functionally above average but ugly. The other
clothing-category scenario described socks that were “great looking” but
were functionally below average.
In the third military-consumer-product category of equipment, the
scenarios asked participants to use the liking/disliking rating for two
different complaint conditions associated with a rifle ammunition magazine
failure. One complaint condition involved a scenario appealing to high-self
monitors with positive social benefits even though the complaint was
ineffective in resolving the equipment failure. In the second complaint
condition, the scenario appealed to the low self-monitor with a functionally
effective complaint result to the magazine failure despite negative social
influences. Soldiers rated each complaint condition for liking/disliking.
For each of the three product categories (food, clothing, and
equipment), a written narrative was provided to give soldiers a context for
each product’s use (see Appendix B, C, and D, respectively). In the food
scenario, one snack was described as socially unpopular but of great
nutritional value and the other food scenario described the snack as very
socially popular but of low nutritional value. In the clothing scenarios, the
narrative described a situation of being in the field, wearing one of two types
of socks all week in a hot, muggy, swamp-laden environment with periods
of rest where soldiers removed boots in each other’s presence to let socks
and feet air out. One sock type was ugly and invited ridicule from fellow
soldiers, but it performed and functioned well. The other sock type was
stylish and invited praise from other soldiers, but it did not function well. In
the rifle ammunition magazine failure, two complaint conditions existed. In
one scenario, complaining caused others to praise and think well of the
person complaining but yielded poor results in resolving the magazine
failure. In the other scenario, complaining caused others to resent the person
who did the complaining but yielded positive results in resolving the
magazine failure.
The theory of self-monitoring suggests that high self-monitors will
respond more favorably to products and services that have positive social
influences associated with them, whereas low self-monitors will tend to
respond more favorably to products and services which have functional
benefits associated with them or which resonate with the consumer’s self-
identity definitions. Furthermore, in some cases for both low and high self-
monitors, appeal of products appeared mediated by how and where the
product was typically used (DeBono, 2006).
The product scenarios with low self-monitor appeal emphasized
improved functionality. The product scenarios with high self-monitor appeal
emphasized positive social influence. The intention of giving product
scenario differences was to appeal to low or high self-monitoring attributes
to see if there would be differences in the way low and high self-monitors
responded using consumer liking/disliking ratings. High selfmonitors tend to
prefer socially enhancing products and low self-monitors tend to prefer
functional and value-expressive products. Because influences can vary
between product categories (DeBono, 2006), three common military
consumer categories of food, clothing, and equipment were included in the
study.
Surveys provided to the OFIG for distribution and administration
contained five pages. The top page (demographic survey) and bottom page
(18-item SMS-R instrument) were always in the first and last page positions,
respectively. The middle three pages were the product scenarios and were
presented in randomized order to eliminate order effects and to allow each
participant access to all six product scenarios.
SMS-R
The SMS-R (see Appendix E) provides a general factor measure of
the selfmonitoring personality trait and includes 18 true/false items (Snyder
& Gangestad, 1986). The SMS-R is a revised version of the original 25-item
Self-Monitoring Scale developed by Snyder (1974). Seven of the original
questions were dropped to increase the reliability while maintaining
comparable intrinsic validity to the original instrument. The SMS-R
provides a more factorially pure general self-monitoring factor. Furthermore,
the SMS-R measures three subscales that are all positively correlated with
the first un-rotated variable. The three subscale factors have been discussed
using different names at different times by different researchers. There are
some minor differences in their views but are considered equivalent for the
purposes of this research and the following factor labels are used
interchangeably: (a) expressive self-control or Acting, (b) social stage
presence or Extraversion, and (c) other-directed self-presentation or Other-
Directedness (Briggs et al., 1980; Gangestad & Snyder 1985; Snyder &
Gangestad, 1986).
The Acting (or expressive self-control) subscale measures the person’s
active ability to control expressive behavior. For example, acting could
mean deliberate lying about the way one feels to win favor with someone.
There are five items that comprise the Acting subscale (items 4, 6, 12, 13,
and 17).
The Other-Directed self-presentation subscale measures whether the
person presents themselves in a way that is according to the expectations
others have under a set of social circumstances (Snyder & Gangestad, 1986).
An example item is: “In different situations and with different people, I often
act like very different persons.” A “true” response would be in the category
of Other-Directed self-presentation. Four items comprise this subscale (items
5, 8, 10, and 18).
The Extraversion (or social stage presence) subscale measures the
ability to act in ways to draw the attention of others to oneself. There are
four items that pertain to this subscale (items 7, 9, 15, and 16). An example
is: “In a group of people I am rarely the center of attention.” A “false”
response to this question would indicate extraversion.
The SMS-R has good overall internal consistency with a Cronbach’s
alpha of .70 which is slightly higher than the original SMS, 25-item scale
(Cronbach’s alpha = .66).
The SMS-R’s acting/expressive self-control factor accounts for a higher
percentage of common variance (62%) compared to the same factor in the
original scale which accounted for 51% of the variance (Gangestad &
Snyder 1985). The SMS-R accounts for more variance and has fewer
subscales that more directly align with self-monitoring theory’s theoretical
basis (Snyder, 1974; Snyder & Gangestad, 1986). The subscales each had
respectable internal consistency as well with Cronbach’s alphas of .45, .58,
and .43 for high self-monitors in the three respective factors of
Acting/expressive self-control, Extraversion/social stage presence, and
Other-Directed self-presentation. Cronbach’s alphas for the same sub factors
for low self-monitors were .35, .64, and .51 respectively (Gangestad &
Snyder 1985).
Snyder and Cantor (1980) used the original scale to determine
construct validity in low and high self-monitors and then provided
converging and criterion-related evidence of self-monitoring theory with
relationships between social knowledge and selfknowledge reflected in self-
monitoring. They reported that low self-monitors were significantly more
adept (p < .001) than high self-monitors at identifying traits within
themselves. This result was congruent with the concept that low-self
monitors seek to validate self-perceptions and pay more attention to self-
relevant traits. They also reported that high self-monitors were significantly
better (p < .025) at identifying personality trait dimensions in others. This
result was congruent with the concept that high-self monitors were more
adept at identifying external/social cues observed in others. Snyder and
Cantor (1980) reported that high self-monitors were significantly better than
low self-monitors at providing more information (p = .004) about prototype
trait relevant situations and provided more vivid descriptions (p = .33) of
other trait-related behaviors (Snyder &
Cantor, 1980).
Snyder and Gangestad (1982) provided construct validity when they
demonstrated that high self-monitors’ possessed more ability to adapt their
behavior to various social situations and that this ability was used to choose
group-discussion social situations more frequently than low self-monitors. In
other words, the attributes of low self-monitors and high self-monitors were
seen to be congruent with the predictions of the investigators based on self-
monitoring theory wherein low self-monitor’s personal dispositions reflected
social interaction movement towards congruency of their individual
tendencies and high self-monitors personal dispositions reflected more
willingness to enter into varied social tendencies including behaviors of
extraversion. These differences between low and high self-monitors were
significant (p ranging from < .02 to < .001).
Data from SMS-R is analyzed as continuous (i.e., the number of
responses given that are high-self-monitoring-category responses). Scores on
the SMS-R range from zero (low self-monitoring) to eighteen (high self-
monitoring). The subscales are scored in the same manner. According to
Wilmot (2015), the Acting and Extraversion subscales should be excellent
indicators of self-monitoring. He is less confident of the Other-Directedness
subscale as an indicator of self-monitoring. Nevertheless, the three subscales
have not been compared with military consumers and further evaluations can
only help to clarify the subscale’s value to this population.
There is no known usage of the SMS-R with military consumers.
Researchers have reported various levels of success in its application to
civilian consumers (Gangestad & Snyder 2000). The SMS-R is one of the
most often used self-monitoring scales. Although some controversy is
associated with it, other measures of selfmonitoring also retain some
uncertainty that can only be resolved by further investigation
(Briggs & Cheek, 1988; DeBono, 2006; Gangestad & Snyder, 2000; Lennox
& Wolfe, 1984; Leone, 2006; Wilmot, 2015).
Another consideration for using the SMS-R is that other researchers
have claimed that the self-monitoring subscales should be able to stand as
independent predictor variables for further understanding of self-monitoring
theory (Wilmot, 2015). The SMSR provides clear subscale separation
compared to the original scale and the construct’s founders claim the SMS-R
is more in alignment with the construct’s theoretical foundations (Gangestad
& Snyder, 1986). For this reason, the operationalization of the construct
using the SMS-R was chosen for use in this study. The SMS-R allows for
the latent general variable as well as the related individual subscales of self-
monitoring to be discerned. The SMS-R should serve to help determine the
discrimination ability of selfmonitoring theory and its theoretical
underpinnings as they may relate to the military consumer.
Data Analysis Plan
Nine research questions and hypotheses were tested using standard
(enter method) multiple regression analyses. The data were analyzed by IBM
SPSS Statistics (version 28.0.1) to calculate descriptive statistics, evaluate
statistical assumptions, and perform multiple linear regression analyses. The
following assumptions for multiple regression analysis include: (a) the
dependent variable is an interval or ratio scale, (b) there are two or more
predictor variables that are interval, ratio, or categorical, (c) there is
independence of observations, (d) bivariate relationships of dependent and
independent variables as pairs and as a whole group are linear relationships,
(e) homoscedasticity (best fit of variance along the line) of the data, (f)
nonexistence of multicollinearity between predictor variables, (g) influential
outliers do not exist or are accounted for, and (h) normality of the
distribution of the errors (residuals; Tabachnick & Fidell, 2013).
As seen in Table 1, multiple interval scale variables satisfy the
requirement for the dependent and predictor variables mentioned in the
preceding paragraph. Independence of observations will be checked using
the Durbin-Watson statistic. Bivariate relationship and linear relationship
pairs and groups will be checked by examining scatterplots and partial
regression plots. Homoscedasticity will be checked by plotting the
standardized residuals against the unstandardized predicted values and SPSS
statistics. The absence of multi-collinearity between predictor variables will
be checked with SPSS statistics where correlation coefficients and
Tolerance/VIF values are inspected to determine if data violates this
assumption. To ensure influential outliers are detected, case-wise diagnostics
and studentized deleted residuals were used. And to ensure normality of the
residuals, they were checked by a histogram with a superimposed normal
curve or Normal Q-Q Plot. A comparison scores on the dependent variable
was done to ensure these had homogeneity of variance and were sampled
independently from each of the other values. For missing data, the average
of the column was used or the case was dismissed if multiple values were
missing.
The research questions and the hypotheses for this study included the
following:
Research Question 1: To what extent does gender relate to military
consumer liking/disliking ratings (as measured by a 9-point Hedonic scale)?
H01: Gender is not a significant predictor of liking/disliking ratings by
military consumers.
H11: Gender is a significant predictor of liking/disliking ratings by
military consumers.
Research Question 2: To what extent does the military consumer
profile attribute of rank/grade (labelled as leader vs. nonleader) relate to
military consumer liking/disliking ratings?
H02: Leadership role is not a significant predictor of liking/disliking
ratings by the military consumer.
H12: Leadership role is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 3: To what extent does the military consumer
profile attribute of years of service relate to military consumer
liking/disliking?
H03: Years of service is not a significant predictor of liking/disliking
ratings by the military consumer.
H13: Years of service is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 4: To what extent does the military consumer
profile attribute of deployment experience relate to military consumer
liking/disliking ratings?
H04: Previous deployment is not a significant predictor of
liking/disliking ratings by the military consumer.
H14: Previous deployment is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 5: To what extent does the military consumer
profile attribute of combat experience relate to military consumer
liking/disliking ratings?
H05: Prior combat experience is not a significant predictor of
liking/disliking ratings by the military consumer.
H15: Prior combat experience is a significant predictor of
liking/disliking ratings by the military consumer.
Research Question 6: To what extent does self-monitoring (total
score) as measured by the SMS-R, relate to military consumer
liking/disliking ratings?
H06: Self-Monitoring is not a significant predictor of liking/disliking
ratings by the military consumer.
H16: Self-monitoring is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 7: To what extent does the Acting subscale of the
SMS-R relate to military consumer liking/disliking ratings?
H07: The Acting subscale is not a significant predictor of
liking/disliking ratings by the military consumer.
H17: The Acting subscale is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 8: To what extent does the Extraversion subscale
of the SMS-
R relate to military consumer liking/disliking ratings?
H08: The Extraversion subscale is not a significant predictor of
liking/disliking ratings by the military consumer.
H18: The Extraversion subscale is a significant predictor of
liking/disliking ratings by the military consumer.
Research Question 9: To what extent does the Other-Directedness
subscale of the
SMS-R relate to military consumer liking/disliking ratings?
H09: The Other-Directedness subscale is not a significant predictor of
liking/disliking ratings by the military consumer.
H19: The Other-Directedness subscale is a significant predictor of
liking/disliking ratings by the military consumer.
Threats to Validity
Convenience sampling may pose an external threat to validity if the
sampling was not representative of the desired population. Sampling was
done with the intention of being representative in terms of gender, age, and
experience of the military combat arms population at Fort Riley. However,
the data is archival, and this claim cannot be verified.
With a larger sample (n > 200), it is hoped that the threat of sampling error is
reduced (Tabachnick & Fidell, 2013). The OFIG personnel administering the
surveys were directed by CRT personnel to make the sampling
representative of the Fort Riley combat arms unit’s population. Making
broader generalizations outside of combat arms units could be a validity
threat if there are unaccounted for influences associated with other types of
units. Furthermore, as noted in prior research (Moore, 2006), the military
population does have a certain homogeneity to it that may nullify certain
aspects of selfmonitoring. Another external threat to validity is the
intermediary personnel who administered the survey. They may have biased
respondents in some way that was not accounted for. I was not present for
the briefings and cannot verify the claims of administrating in an unbiased
manner. Yet, neither do I have reason to disbelieve their claims and
therefore assume this threat to validity is minimal.
Internal threats to the validity exist as well. The scenarios and product
descriptions were developed by the CRT with the understanding that
functionality of a product was an attribute that appealed to low self-
monitors. Social influence of a product was an attribute that appealed to high
self-monitors. The scenario and product conditions were selected to appeal
to self-monitoring attribute differences. However, the scenarios were not
validated with known high and low self-monitors because they are common
situations and products experienced by soldiers and such scenarios represent
the conditions that are desired to be assessed by self-monitoring theory
within a normal military consumer population. Nevertheless, nonvalidated
scenarios may prove to be a threat to validity or sensitivity of the construct.
Personality differences may clearly exist as definable by the construct but
lack effective predictive ability of the criterion variable within the context
seen by military consumers.
Ethical Considerations
As this archival data that has no personally identifiable information
associated with it, there is less concern for identification of a test participant
being identified. Data must be handled thoughtfully and reviewed to ensure
there is no personally identifiable information included on data sheets or
records. Since the data was under the responsibility of the CRT, permission
for its use was secured from the CRT team leader. A copy of the permission
letter is in Appendix F. The data set was also later released to the public with
no personally identifiable information associated with the data set.
Participation was voluntary and participants could quit at any time.
Participants were briefed prior to participation in the study. Military chain-
of-command leadership was contacted through the OFIG liaison to ensure
the appropriate support was in place. The questions were reviewed for
content appropriateness, deception, or otherwise offensive or misleading
information to protect participant’s rights. Verbal instructions were given
prior to the administration of the survey to military participants to let them
know that participation was voluntary, that they could quit at any time, and
that the data would be anonymous. Survey participation was voluntary and
no personally identifiable information was collected. Under federal
regulations, data collection exemptions to human use restriction policies are
allowed for research efforts involving the use of survey procedures that are
not injurious and in which human subjects cannot be identified and the
subject’s responses do not place them at unreasonable risk of civil/criminal
liability or cause harm to their reputation, financial standing, or
employability. Furthermore, exemption is allowed when the data in the study
is acquired by the investigator in a manner where identification of the
participant is not possible directly or indirectly. These exemption criteria
existed in the case of this study’s data.
All data were maintained on a secured laptop. No personally
identifiable information existed in the data set before sharing the data or
before analysis could occur. Data files will be kept for a minimum of five
years and deleted after no more than seven year’s maintenance on a secure
system.
Summary
Chapter 3 included the research design and methodology sections. A
quantitative approach was used utilizing a nonexperimental design and
archival data. Multiple regression was used to determine whether a
relationship exists between nine predictor variables and the dependent
variable of military consumers’ liking/disliking ratings for three product
categories (food, clothing, equipment). The predictor variables consisted of
five military demographic variables and four self-monitor variables. Chapter
4 reports the
results obtained from the analysis of the archive data set.
Chapter 4: Results
The purpose of this study was to determine the extent to which self-
monitoring constructs (Self-Monitoring, Acting, Extraversion, and Other-
Directedness) and specific demographic variables (gender, leadership, length
of service, deployments, and combat experience) predicted liking ratings of
military product scenarios by active-duty soldiers.
The research questions and the hypotheses for this study included the
following:
Research Question 1: To what extent does gender relate to military
consumer liking/disliking ratings (as measured by a 9-point Hedonic scale)?
H01: Gender is not a significant predictor of liking/disliking ratings by
military consumers.
H11: Gender is a significant predictor of liking/disliking ratings by
military consumers.
Research Question 2: To what extent does the military consumer
profile attribute of rank/grade (labelled as leader vs. nonleader) relate to
military consumer liking/disliking ratings?
H02: Leadership role is not a significant predictor of liking/disliking
ratings by the military consumer.
H12: Leadership role is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 3: To what extent does the military consumer
profile attribute of years of service relate to military consumer
liking/disliking?
H03: Years of service is not a significant predictor of liking/disliking
ratings by the military consumer.
H13: Years of service is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 4: To what extent does the military consumer
profile attribute of deployment experience relate to military consumer
liking/disliking ratings?
H04: Previous deployment is not a significant predictor of
liking/disliking ratings by the military consumer.
H14: Previous deployment is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 5: To what extent does the military consumer
profile attribute of combat experience relate to military consumer
liking/disliking ratings?
H05: Prior combat experience is not a significant predictor of
liking/disliking ratings by the military consumer.
H15: Prior combat experience is a significant predictor of
liking/disliking ratings by the military consumer.
Research Question 6: To what extent does self-monitoring (total
score) as measured by the SMS-R, relate to military consumer
liking/disliking ratings?
H06: Self-monitoring is not a significant predictor of liking/disliking
ratings by the military consumer.
H16: Self-monitoring is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 7: To what extent does the Acting subscale of the
SMS-R relate to military consumer liking/disliking ratings?
H07: The Acting subscale is not a significant predictor of
liking/disliking ratings by the military consumer.
H17: The Acting subscale is a significant predictor of liking/disliking
ratings by the military consumer.
Research Question 8: To what extent does the Extraversion subscale
of the SMS-
R relate to military consumer liking/disliking ratings?
H08: The Extraversion subscale is not a significant predictor of
liking/disliking ratings by the military consumer.
H18: The Extraversion subscale is a significant predictor of
liking/disliking ratings by the military consumer.
Research Question 9: To what extent does the Other-Directedness
subscale of the
SMS-R relate to military consumer liking/disliking ratings?
H09: The Other-Directedness subscale is not a significant predictor of
liking/disliking ratings by the military consumer.
H19: The Other-Directedness subscale is a significant predictor of
liking/disliking ratings by the military consumer
In this chapter, I review how the archival data were collected. I also
provide a discussion of the sample demographics. This is followed by a
presentation of the descriptive statistics, results of the statistical assumptions
for multiple regression, and the results from each multiple regression
analysis.
Data Collection
The archival data I used in this study were collected at Fort Riley
Kansas in 2013 over a 2-week period of time in September. Recruitment
involved planning through military channels by the OFIG with target
demographics set by the consumer research team. As a member of the CRT,
I had access to the data and received permission from the CRT leader to use
the data for the purposes of this dissertation project. The archival data from
this project was released by the CRT and the Natick Soldier Center for
public distribution in 2022. Soldiers who participated did so voluntarily and
were recruited through official military channels. No rewards or
punishments were associated with participation. No response rates for
participation were ever recorded.
The sample included soldiers from calvary, combat arms and direct
support units. Twelve of the 220 cases were excluded because of missing
data. The demographic categories are not proportional to all aspects of
combat and related units of the U.S. military. Women were overrepresented
in the sample compared to the population. At the time of the data collection
females constituted about 14% of the Army. They served in roles supporting
combat units but still experienced combat. Of those surveyed, 25% were
female. A surprising percentage of the females sampled reported
experiencing combat (75%). Women were not officially allowed in direct
combat units until 2015 (Moore,
2020). The proportion of males with combat experience was also high and
reported to be 56%. The number of soldiers with combat experience was
expected to be higher than normal as this was the target population.
Typically, about 10% in the military experience combat while the rest are in
support roles. Leaders (those in grades above E4) in the sample comprised
52%. In current Army demographics leaders throughout the U.S.
Army comprise 59% of the population (Army, 2022).
(https://api.army.mil/e2/c/downloads/2022/08/05/90d128cb/active-
componentdemographic-report-june-2022.pdf). The Army does not provide
data on the average ages of enlistments, but at the time of the data gathering
(2013), 52% of the all active-duty enlisted personnel and 42% of all active
duty were 25 years of age and younger (Office, 2013). The personnel
sampled who served 0 to 5 years (55.5%) would logically be a similar group
to the < 25-year group. Thus, the sampling of 0–5 years of service appears to
be similar but a slightly larger percentage than existed throughout the Army
at that time. The percent who had been deployed before in the sampling was
64.4%. According to 2011 data (Baiocchi, 2013), 73% of active duty had
been deployed to Afghanistan or Iraq. The current sample had 65% of
soldiers with previous deployment experience. In terms of gender, 82% of
females had been deployed, whereas only 60% of the males had been
previously deployed. Male soldiers had fewer deployments and less time in
service (< 5 years of service). Females had more years of service (59% with
> 5 years of service) compared to males (41% with > 5 years of service).
There was also a higher percentage of female leaders in the sample (63%)
compared to male leaders (48%). Combat experience was reported by 60.6%
of the soldiers in the sample, which is higher than the average of 10% seen
generally and historically across the military (Bartell, 2022). Table
2 shows the demographic characteristics of the soldiers sampled.
Table 2
General Demographic Characteristics of Soldier Sample
Variable Categories/values n %
Gender
Male
157
75.5%
Female 51 24.5%
Leadership
Leader
108
51.9%
Nonleader 100 48.1%
Years in military
0–5 years
113
54.3%
> 5 years 95 45.7%
Number of
deployments
0
72
34.6%
1 44 21.2%
2 20 9.6%
3 24 11.5%
4 30 14.4%
5 9 4.3%
6+ 9 4.3%
Combat experience
Combat experience
126
60.6%
No combat experience 82 39.4%
Note: Missing data points and rounding may cause n to not equal 208 and/or
percentages to not equal 100%.
Results
This section includes descriptive statistics and tests for assumptions
used with regression analysis. It is followed by regression analysis results of
each product scenario.
Descriptive Statistics
Table 3 provides descriptive statistics of the self-monitoring-scale
related predictor variables. Included is the SMS-R scale (self-monitoring)
and three subscales derived from the SMS-R (Acting, Extraversion, and
Other-Directedness subscales.
Table 3
Descriptive Statistics
IV#/label M Mdn SD n Min Max 95% 95%
LB UB
Self-Monitoring 8.08 8 2.694 208 0 15 7.71 8.45
Acting 1.92 2 1.199 208 0 5 1.75 2.08
Extraversion 2.42 2 1.096 208 0 4 2.27 2.57
Other-
Directedness 1.31 1 1.009 208 0 4 1.17 1.45
Descriptive statistics for the six dependent variables included 208
cases. Twelve of the original 220 cases were removed due to missing data.
The most common response across all scenarios was 5 (Neither like nor
dislike). These results are shown in Table 4.
Table 4
Descriptive Statistics for Liking Ratings of Six Scenarios
Scenario M Mdn SD n Min Max
95%
LB
95%
UB
1 (Ugly high function
sock)
5.87 5 1.876 208 1 9 5.61 6.12
2 (Great looking, low
function sock)
4.65 5 1.920 208 1 9 4.39 4.92
3 (High nutrition snack) 5.79 5 1.819 208 1 9 5.54 6.04
4 (Low nutrition snack) 5.28 5 1.639 208 1 9 5.05 5.50
5 (Weak resolution of
defective ammo
magazine)
5.67 5 1.410 208 1 9 5.48 5.87
6 (Strong resolution of
defective ammo
magazine)
5.75 5 1.375 208 2 9 5.56 5.93
The distribution shapes demonstrated some degree of skewness and
kurtosis. A skewness value of > 1.0 indicates a distribution skewed to the
right. A skewness value of < -1.0 describes distribution skewed to the left.
Kurtosis > 1.0 is leptokurtic (peaked).
Kurtosis values < -1.0 are platykurtic (broad). The results for the liking
ratings in each scenario showed that values were within the guidelines of
skewness and kurtosis; therefore, normality was found (see Table 5).
Table 5
Normality Testing for Dependent (Liking Ratings of Products) and
Independent Variables (Self-Monitoring Scores)
Variable Statistic df p Skewness Kurtosis
Scenario 1 (Ugly high function
sock)
.928 208 < .001 -.122 -.031
Scenario 2 (Great looking, low
function sock)
.930 208 < .001 -.238 -.247
Scenario 3 (High nutrition
snack)
.933 208 < .001 -.076 -.028
Scenario 4 (Low nutrition
snack)
.924 208 < .001 .196 .544
Scenario 5 (Weak resolution of
defective ammo magazine)
.894 208 < .001 .023 .913
Scenario 6 (Strong resolution of
defective ammo magazine)
.889 208 < .001 .457 -.263
Self-monitoring (total) score .981 208 .006 .043 -.204
Acting subscale score .921 208 < .001 .311 -.563
Extraversion subscale score .905 208 < .001 -.324 -.509
Other-directedness subscale .886 208 < .001 .338 -.602
score
Skewness and kurtosis were used to determine whether each
dependent variable conformed to ±2 for skewness and ±3 for kurtosis
(Westfall & Henning, 2013) wherein the symmetry about the mean is not
markedly different to produce outliers. The distribution was also evaluated
for normality using Kolmogorov-Smirnov and Shapiro-
Wilk tests. Those results and other assumptive statistics are discussed below.
Evaluations of Statistical Assumptions
The first assumption is that the dependent variable is an interval or
ratio scale (Tabachnick & Fidell, 2013). This hedonic scale was presented on
the survey with 1 through 9 integer anchors that are clearly interval. It
should be noted that scale descriptors were also included that can bias the
rater and cause the scale to produce lessuniform distances between points
and cause some respondents to hover near the neutral middle scale value
(Cardello & Jaeger, 2010).
The next assumption is that there are two or more predictor variables
that are interval, ratio, or categorical (Tabachnick & Fidell, 2013). The nine
independent variables consist of four interval, one ratio, and four categorical
measures. Years of service was recoded to categorical (ordinal) and the
deployment experience coded and analyzed as ratio (scale). The assumption
is satisfied.
The next assumption is that there is independence of observations.
The DurbinWatson statistic was used to test this assumption (Tabachnick &
Fidell, 2013). In DurbinWatson, the test results were all close to 2, meeting
the assumption that the residuals were independent. Values can range from 0
to 4 and a value of 2 means independence.
For liking ratings in each of the six scenarios, the respective values were
2.137, 1.824,
2.035, 2.020, 1.957, and 2.000.
The next assumption is that bivariate relationships of dependent and
independent variables as pairs and as a whole group are linear relationships
(Tabachnick & Fidell, 2013). This assumption was evaluated through
examining scatterplots and partial regression plots. When the relationship is
linear, the scatter plots will have a random appearance (e.g., not funnel or
curvilinear shaped) and the regression plots will generally follow a diagonal
line. In all cases of the scatterplots, the dispersion of plots appeared random
and did not demonstrate a patterned relationship. The P-P plots of dependent
variable and independent variables plots for all six scenarios demonstrated
that the plots generally fall along the straight diagonal line suggesting linear
relationships between the independent and dependent variables
The next assumption is that there is homoscedasticity of the data (the
residuals have constant variance at every point in the linear model)
(Tabachnick & Fidell, 2013). This was evaluated using a plot of
standardized residuals versus standardized values predicted and looking for
patterns. Examination of the residuals’ scatterplots suggested there were no
violations and thus the assumption for homoscedasticity was met (see
Appendix G).
The next assumption is that multicollinearity between predictor
variables does not exist (Tabachnick & Fidell, 2013). Additional evaluation
for multicollinearity was done using VIF statistic for the predictor variables.
There is no upper limit to VIF statistics, but generally, values greater than
five indicate potential multicollinearity. In these models, most values were
above five except for the independent variable of gender (3.221).
Experienced combat (5.200) was marginal. The other independent variables
ranged from
5.576 (Other-Directedness) to 50.726 (Self-Monitoring, total); see Table 6.
Table 6
Collinearity for Model
Predictor variables Tolerances VIF
Gender .310 3.221
Leadership .140 7.143
Years of Service .154 6.497
Deployments .161 6.226
Combat Experience .192 5.200
Self-monitoring (total) .020 50.726
Acting subscale .113 8.848
Extraversion subscale .065 15.274
Other-directedness subscale .179 5.576
Another assumption is that influential outliers do not exist or are
accounted for (Tabachnick & Fidell, 2013). These were checked by
examination of the Cook’s D values. Values less than one are considered
acceptable. The values were all considerably below one (range
was .051–.074) with a small standard deviation range (range was .007.009).
Thus, no multivariate outliers were identified.
Shapiro-Wilk (typically used on sample sizes < 50) was applied, but
Kilmogorov-
Smirnov is considered a more reliable number for sample sizes > 50
(Tabachnick & Fidell, 2013). The significance level did not differ between
the two methods, but the statistic was much lower for Kilmogorov-Smirnov
than the statistic for the Shapiro-Wilk. These results suggested a nonnormal
distribution (see Table 7). However, multiple regression can be used when
some variables are not normal if there is evidence of normally distributed
errors. An examination for normality of the distribution of the errors
(residuals) was checked with a Q-Q plot which suggested that the data were
acceptable
(see Appendix G). This suggested that the normality assumption was met.
Table 7
Tests for Normality of Standardized Residuals
Scenario
Kilmogorov-Smirnov Shapiro-Wilk
Statistic df p Statistic df p
1-Ugly high function sock .187 208 < .001 .928 208 < .00
1
2-Great looking, low function
sock
.225 208 < .001 .930 208 < .00
1
3-High nutrition snack .197 208 < .001 .933 208 < .00
1
4-Low nutrition snack .231 208 < .001 .924 208 < .00
1
5-Weak resolution of
defective ammo magazine
.260 208 < .001 .894 208 < .00
1
6-Strong resolution of
defective ammo magazine
.288 208 < .001 .889 208 < .00
1
I also assessed reliability of the scores on the SMS-R. Cronbach’s
alpha is an indicator of internal consistency of the items on a scale.
According to Ursachi et al. (2003), alpha values of .60 to .70 are acceptable,
with values over .80 demonstrating very good internal consistency. In this
study, the internal consistency was lower for the instrument than expected.
Based off standardized items, the Cronbach’s alphas for the SMS-R total
Self-Monitoring scale, Acting subscale, Extraversion subscale, and Other-
Directedness subscale were all < .500 (see Table 8).
Table 8
Internal Consistency for Scale Reliability with Cronbach’s Alpha
Scale Cronbach’s
Alpha
Cronbach’s Alpha
based on standardized
items
Number
of items
SMS-R General SM scale .463 .458 18
Acting subscale .261 .265 5
Extraversion subscale .327 .316 4
Other-Directedness
subscale
.199 .207 4
Multiple Regression Analyses
I conducted six separate multiple regression analyses. Each analysis
determined the extent to which self-monitoring scores (Self-Monitoring,
Acting, Extraversion, and Other-Directedness), gender, leadership, length of
service, deployments, and combat experience predicted liking ratings of six
different military products. Standard (enter method) multiple regression was
used to allow simultaneous entry of the independent (predictor) variables
into the regression model (Tabachnick & Fidell, 2013). The same nine
independent variables were used as predictor variables for the same
dependent variable of liking as measured by the 9-point liking/hedonic scale.
The dependent variable of liking was used for six different product
scenarios. The six scenarios were: a) ugly high-function sock, b) great
looking, low-function sock, c) unpopular high-nutrient snack, d) popular
low-nutrient snack, e) weak resolution of defective ammo magazine, and f)
strong resolution of defective ammo magazine. In each analysis, an alpha
level of .01 was used to reduce Type 1 error.
Multiple Regression for Product Scenario 1 Liking Ratings: Ugly High
Function
Sock
I conducted a standard multiple linear regression analysis to determine
the relative strength of the independent variables in predicting liking ratings
in the scenario that described socks that were highly functional but ugly. The
result of the multiple regression analysis was significant, F(9, 199) =
133.206, p < .001, R2 = 0.858. These findings indicted the overall model was
statistically significant. The model explained 86% of the variation in the
liking ratings of ugly functional socks.
The results showed that gender was a significant predictor of liking
ratings, B = 2.260, p < .001. This result showed that males had significantly
higher liking ratings for the ugly but functional socks compared to females.
On average, there was a 2.26 unit increase in the liking rating when the
participant was male. Table 9 shows the regression results for the
independent (predictor) variables for scenario 1.
Table 9
Results of Multiple Linear Regression of Independent Variables Predicting
Dependent
Variable (Liking) of Scenario 1 (Ugly, Functional Sock)
Variable B SE β t p
Gender 2.260 .340 .319 6.643 <.001
Leadership .761 .611 .089 1.247 .214
Years in service 1.139 .621 .125 1.833 .068
Number of deployments -.130 .160 -.054 -.814 .417
Combat Experienced .305 .482 .039 .633 .528
Self-monitoring total score .146 .138 .201 1.057 .292
Acting subscale score .157 .217 .058 .725 .469
Extraversion subscale score .554 .242 .239 2.289 .023
Other-Directedness subscale score .090 .235 .024 .383 .702
Note: F(9, 199) = 133.206, p < .001, R2 = 0.858
Multiple Regression for Product Scenario 2 Liking Ratings: Great Looking,
Low
Function Sock
I conducted a standard multiple linear regression analysis to determine
the relative strength of the independent variables in predicting liking ratings
in the scenario that described socks that were great looking but low
functionality. The result of the multiple regression analysis was significant,
F(9, 199) = 107.565, p < .001, R2 = 0.829. These findings indicted the
overall model was statistically significant. The model explained 83% of the
variation in the liking ratings of ugly functional socks.
The results showed that leadership was a significant predictor of
liking ratings, B = -1.688, p = .002. These results showed that those with
leadership experience had significantly lower liking ratings for the great
looking but less functional socks than nonleaders. On average, there was a
1.69 unit decrease in the liking rating when the participant was a leader.
Years in service was also a significant predictor of liking ratings, B =
1.540, p = .006. The results showed that those with more years in service
had significantly higher liking ratings for the great looking but less
functional socks than those with less years in service. On average, there was
a 1.54 unit increase in liking rating when the participant had more time in
service (>5 years).
Finally, combat experience was a significant predictor of liking
ratings, B = 1.553, p = .001. The results also showed that soldiers with
combat experienced had significantly higher liking ratings for the great
looking but less functional socks than those without combat experience. On
average, there was a 1.55 unit increase in liking rating when the soldier had
combat experience. Table 10 shows the regression results for the
independent
(predictor) variables for scenario 2.
Table 10
Results of Multiple Linear Regression of Independent Variables Predicting
Dependent
Variable (Liking) of Scenario 2 (Great Looking, Less Functional Sock)
Variable B SE β t p
Gender .776 .304 .134 2.551 .011
Leadership -1.688 .546 -.242 -3.089 .002
Years in service 1.540 .556 .207 2.772 .006
Number of deployments -.082 .143 -.042 -.571 .569
Combat Experienced 1.553 .432 .240 3.597 <.001
Self-monitoring total score .257 .123 .435 2.084 .038
Acting subscale score -.059 .194 -.027 -.307 .760
Extraversion subscale score .441 .217 .233 2.035 .043
Other-Directedness subscale score .141 .210 .046 .668 .505
Note. F(9, 199) = 107.565, p < .001, R2 = 0.829
Multiple Regression for Product Scenario 3 Liking Ratings: Unpopular High
Nutrition Snack
I conducted a standard multiple linear regression analysis to determine
the relative strength of the independent variables in predicting liking ratings
in the scenario that described a nutritional snack that was healthy but
unpopular. The result of the multiple regression analysis was significant,
F(9, 199) = 145.427, p< .001, R2 = 0.868. These findings indicted the overall
model was statistically significant. The model explained
87% of the variation in the liking ratings of the unpopular but highly
nutritious snack.
The results showed that gender was a significant predictor of liking
ratings, B = 1.919, p< .001. This result showed that males had significantly
higher liking ratings for the unpopular high nutrition snack than females. On
average, there was a 1.92 unit increase in the liking rating when the
participant was male. Table 11 shows the regression results for the
independent (predictor) variables for scenario 3.
Table 11
Results of Multiple Linear Regression of Independent Variables Predicting
Dependent
Variable (Liking) of Scenario 3 (Unpopular High Nutrition Snack)
Variable B SE β t p
Gender 1.919 .323 .275 5.947 <.001
Leadership .286 .579 .034 .494 .622
Years in service .665 .589 .074 1.129 .260
Number of deployments .036 .152 .015 .235 .815
Combat Experienced .462 .458 .059 1.009 .314
Self-monitoring total score .216 .131 .303 1.651 .100
Acting subscale score .199 .206 .074 .968 .334
Extraversion subscale score .558 .230 .245 2.431 .016
Other-Directedness subscale score -.193 .223 -.053 -.865 .388
Note. F(9, 199) = 145.427, p< .001, R2 = 0.868
Multiple Regression for Product Scenario 4 Liking Ratings: Popular Low
Nutrition
Snack
I conducted a standard multiple linear regression analysis to determine
the relative strength of the independent variables in predicting liking ratings
in the scenario that described a low nutrition snack that was less healthy but
popular. The result of the multiple regression analysis was significant, F(9,
199) = 144.218, p< .001, R2 = 0.867. These findings indicted the overall
model was statistically significant. The model explained 87% of the
variation in the liking ratings of the popular low nutrition snack.
The results showed that gender was a significant predictor of liking
ratings, B = 1.672, p < .001. This result showed that males had significantly
higher liking ratings for the popular low nutrition snack than females. On
average, there was a 1.67 unit increase in the liking rating when the
participant was male. The results also showed that combat experience was a
significant predictor of liking ratings, B = 1.318, p =.002. This result showed
that those with combat experience had significantly higher liking ratings for
the popular low nutrition snack than those without combat experience. On
average, there was a 1.32 unit increase in the liking rating when the
participant had combat experience. Table 12 shows the regression results for
the independent (predictor) variables for scenario 4.
Table 12
Results of Multiple Linear Regression of Independent Variables Predicting
Dependent
Variable (Liking) of Scenario 4 (Popular Low Nutrition Snack)
Variable B SE β t p
Gender 1.672 .295 .263 5.666 <.001
Leadership -.262 .530 -.034 -.494 .622
Years in service .759 .539 .093 1.409 .160
Number of deployments -.147 .139 -.068 -1.056 .292
Combat Experienced 1.318 .418 .186 3.150 .002
Self-monitoring total score .247 .120 .380 2.066 .040
Acting subscale score -.153 .188 -.063 -.815 .416
Extraversion subscale score .412 .210 .198 1.962 .051
Other-Directedness subscale score .215 .204 .064 1.055 .293
Note: F(9, 199) = 144.218, p< .001, R2 = 0.867
Multiple Regression for Product Scenario 5 Liking Ratings: Weak
Resolution of
Defective Ammo Magazine
I conducted a standard multiple linear regression analysis to determine
the relative strength of the independent variables in predicting liking ratings
in the scenario that described a popular but ineffective complaint process to
resolve a defective ammo magazine. The result of the multiple regression
analysis was significant, F(9, 199) = 182.574, p< .001, R2 = 0.892. These
findings indicted the overall model was statistically significant. The model
explained 89% of the variation in the liking ratings of the popular but low-
resolution complaint process for defective ammo magazines.
The results showed that gender was a significant predictor of liking
ratings, B = 1.877, p < .001. This result showed that males had significantly
higher liking ratings for the popular but weak complaint process to resolve
the defective ammo magazine. On average, there was a 1.88 unit increase in
the liking rating when the participant was male.
The results also showed that combat experience was a significant predictor
of liking ratings, B = 1.153, p =.004. This result showed that those with
combat experience had significantly higher liking ratings for the popular but
weak resolution process of a defective ammo magazine than those without
combat experience. On average, there was a
1.15 unit increase in the liking rating when the participant had combat
experience. Finally, the results showed that those that scored higher on the
Extraversion subscale had significantly higher liking ratings for the popular
but weak resolution process of a defective ammo magazine than those who
scored lower on Extraversion. On average, there was a .640 unit increase in
the liking rating for each unit increase in Extraversion scores. Table 13
shows the regression results for the independent (predictor) variables for
scenario 5.
Table 13
Results of Multiple Linear Regression of Independent Variables Predicting
Dependent
Variable (Liking) of Scenario 5 (Popular but Weak Complaint Process to
Resolve
Defective Ammo Magazine)
Variable B SE β t p
Gender 1.877 .281 .279 6.671 <.001
Leadership .552 .505 .068 1.093 .276
Years in service .031 .514 .004 .060 .953
Number of deployments -.046 .132 -.020 -.346 .729
Combat Experienced 1.153 .399 .154 2.890 .004
Self-monitoring total score .170 .114 .247 1.490 .138
Acting subscale score -.160 .179 -.062 -.895 .372
Extraversion subscale score .640 .200 .291 3.199 .002
Other-Directedness subscale score .297 .194 .084 1.527 .128
Note: F(9, 199) = 182.574, p< .001, R2 = 0.892
Multiple Regression for Product Scenario 6 Liking Ratings: Strong
Resolution of
Defective Ammo Magazine
I conducted a standard multiple linear regression analysis to determine
the relative strength of the independent variables in predicting liking ratings
in the scenario that described an unpopular but effective complaint process
to resolve a defective ammo magazine. The result of the multiple regression
analysis was significant, F(9, 199) = 182.551, p< .001, R2 = 0.892. These
findings indicted the overall model was statistically significant. The model
explained 89% of the variation in the liking ratings of the unpopular but
high-resolution complaint process for defective ammo magazines.
The results showed that gender was a significant predictor of liking
ratings, B = 1.767, p < .001. This result showed that males had significantly
higher liking ratings for the unpopular but strong complaint process to
resolve the defective ammo magazine. On average, there was a 1.77 unit
increase in the liking rating when the participant was male. The results also
showed that those that scored higher on the Extraversion subscale had
significantly higher liking ratings for the unpopular but strong resolution
process of a defective ammo magazine than those who scored lower on the
Extraversion subscale. On average, there was a .640 unit increase in the
liking rating for each unit increase in Extraversion. Table 14 shows the
regression results for the independent (predictor) variables for scenario 6.
Table 14
Results of Multiple Linear Regression of Independent Variables Predicting
Dependent
Variable (Liking) of Scenario 6 (Unpopular but Strong Complaint Process to
Resolve
Defective Ammo Magazine)
Variable B SE β t p
Gender 1.767 .284 .260 6.216 <.001
Leadership .338 .510 .041 .661 .509
Years in service .928 .519 .106 1.788 .075
Number of deployments -.173 .134 -.075 -1.290 .198
Combat Experienced .756 .403 .100 1.875 .062
Self-monitoring total score .191 .115 .276 1.660 .098
Acting subscale score -.006 .181 -.002 -.035 .972
Extraversion subscale score .657 .202 .296 3.248 .001
Other-Directedness subscale score .154 .196 .043 .785 .433
Note: F(9, 199) = 182.551, p< .001, R2 = 0.892
Summary
I investigated the predictive relationship of nine independent variables
on the affective liking scores (dependent variables) of six scenario-based
product evaluations. In five out of six scenarios, gender was a significant
predictor of liking ratings. Males generally had higher liking ratings across
all products. Combat experience also was a significant predictor in three out
of six product scenarios (one from each product category). Those with
combat experience rated three of the six products higher. Extraversion
subscale score was a significant predictor relative to the defective ammo
magazine. Those scoring higher on Extraversion generally gave higher
liking ratings for the defective ammo magazine scenarios. Leadership and
years’ experience were significant predictors in scenario 2 (great looking,
less functional sock). Leaders generally gave lower liking scores than
nonleaders for the great looking but less functional socks. Those with more
years’ experience (>5), gave higher liking scores than those with less time in
service (0–5 years) for the great looking but less functional socks. In Chapter
5, I will interpret the findings, describe the limitations of the study, make
recommendations, discuss the implications, and provide a conclusion.
Chapter 5: Discussion, Conclusions, and Recommendations
The purpose of this nonexperimental quantitative study was to determine the
extent to which gender, leadership, years of service, number of deployments,
combat experience, and self-monitoring variables (Self-Monitoring total
score, Acting subscale, Extraversion subscale, and Other-Directedness
subscale) are related to soldiers’ degree of liking/disliking ratings of military
products after reading product scenarios from three categories (clothing,
food, and equipment). Multiple linear regression analyses were used to
examine the relative strength of gender, leadership, years of service, number
of deployments, combat experience, and self-monitoring variables (Self-
Monitor total score, Acting subscale score, Extraversion subscale score,
Other-Directedness subscale score) in predicting military consumers’
liking/disliking ratings of military products. A military archival database of
military consumer attitudes was used for the study.
Gender was a significant predictor with males giving significantly
higher liking ratings than females for all the products, except for the product
in Scenario 2 (popular/great looking, low functioning sock). Leadership was
a significant predictor with leaders giving significantly lower liking ratings
than nonleaders in Scenario 2 (popular/great looking, low functioning sock).
Years of military service was a significant predictor with participants having
more years of service giving significantly higher liking ratings than those
with less military service in Scenario 2 (popular/great looking, low
functioning sock). Number of deployments was not a significant predictor of
liking ratings in any of the scenarios. Combat experience was a significant
predictor with participants having combat experience giving significantly
higher liking ratings than those not having combat experience in Scenarios
2, 4, and 5 (popular, low functioning scenarios). The Self-Monitoring total
score, Acting subscale score, and OtherDirectedness subscale score were not
significant predictors of liking/disliking ratings. More specifically, self-
monitoring scores did not significantly predict participants’ liking ratings in
hypothetical product scenarios that were designed to appeal to low or high
selfmonitors. Extraversion was the only self-monitoring subscale score that
significantly predicted liking ratings. Higher levels of Extraversion in
Scenarios 5 and 6 (complaint processes to resolve defective ammunition
magazines) were associated with higher liking ratings in both scenarios.
Interpretation of the findings will be discussed in the following sections in
terms of previous literature discussed in Chapter 2 and in the context of
selfmonitoring theory.
Interpretation of Findings
As noted in Chapter 2, civilian consumer research has shown that high
selfmonitoring consumers possess attitudes and behaviors different from
their low selfmonitoring counterparts (e.g., DeBono, 2006; Hye-Jin et al.,
2008). High self-monitoring consumers tend to make consumer decisions
that help them gain social favor. Low selfmonitoring consumers adjust their
consumer behavior to be congruent with the attitudes and behaviors of the
persona of who they think they are. Typically, product utility is an important
aspect for low self-monitoring consumers and a product’s conveyed social
identity is important for high self-monitors. Previous research has not
examined selfmonitoring theory in military consumers. Thus, the purpose of
this study was to evaluate the extent to which self-monitoring constructs
(Self-Monitoring, Acting, Extraversion, Other-Directedness) and
demographic variables (gender, leadership, deployments, combat
experience) predict liking ratings of military product scenarios among
active-duty soldiers. In the following sections, I analyze and interpret each
of the hypotheses/predictor variables in the context of literature described in
Chapter 2 and in the context of self-monitoring theory.
Hypothesis 1: Gender
In Hypothesis 1, I predicted a significant relationship between gender
and liking/disliking ratings by military consumers. The results showed that
gender was a significant predictor of liking ratings in 5 out of 6 product
scenarios. Except for Scenario 2 (popular/great looking, low functioning
sock), female soldiers gave significantly lower liking ratings compared to
male soldiers.
More negative perceptions of female soldiers appear to coincide with
other negative, gender-related experiences female veterans have
experienced. For example, female soldiers have reported that their service in
Afghanistan and Iraq was tainted by sexist stereotypes, hypermasculinity,
and various forms of sexual harassment (Minsberg, 2015). In 1995
government reports evaluated by Antecol and Dobb-Clark (2006), 70.9% of
active-duty females in the military reported they had experienced some form
of sexually harassing behavior over a 12-month period. Antecol and Dobb-
Clark compared the military female data to civilian female data from the
same time period (Laband & Lentz, 1998; Schneider et al., 1997) and found
that female employees in the civilian sector had lower rates of sexual
harassment over a longer, 24-month period (68% in the private sector, 63%
at a Midwestern university. Antecol and Cobb-Clark did a deeper analysis of
military female attitudes about sexual harassment that revealed military
women considered sexually harassing behavior a negative influence when it
was elevated (e.g., sexual coercion). Data revealed that when sexually
harassing behavior was elevated, it resulted in significantly lower job
satisfaction and lower intentions to stay in the military. Crude or offensive
behavior was the most frequently reported form of sexually harassing
behavior with 69.2% of female soldiers experiencing such behavior. That
form of sexual harassment did not make a difference in job satisfaction or
workemployment longevity. Sexual coercion (reported by 12.3% of the
women) was associated with significantly lower job satisfaction and
intentions to stay in the military when compared to males (Antecol & Cobb-
Clark, 2006). The U.S. Government Accountability Office (2020) reported
that females were 28% more likely than men to leave the military. Primary
reasons listed were family planning, lack of dependent care, sexism, and
sexual assault (see also Werner, 2020).
In some reports, females described being vulnerable and trying to
protect themselves from enemies outside the wire as well as from their
fellow soldiers inside the wire (Minsberg, 2015). Female soldiers also
reported feeling compelled to prove themselves in a hypermasculine world
that does not value their warfighting contributions and brands them with
demeaning stereotypes (Minsberg, 2015; Trobaugh, 2018). These are some
of the factors that might lead female soldiers to have lower general negative
perceptions of military experience. This general negative perception is
consistent with the findings from the current study regarding the evaluation
of military products. Female soldiers gave significantly lower liking ratings
of military products across different product scenarios.
Richard and Molloy (2020) examined military male attitudes about
themselves and attitudes toward female soldiers. They determined that
scripts used by male soldiers revealed that they expected males to be
providers, protectors, hardworking, family oriented, and physically fit. Male
soldiers also viewed ideal military personnel as being male and adhering to
the male script. Male soldiers viewed female soldiers as having more
extensive and varied scripts. These scripts centered around expectations that
females were weak, caring, and kind. For women in the military, the male
soldiers defined them as token/masculine women, sexualized, weak, or
wifey. Such sexist stereotypes undoubtedly can be frustrating for female
soldiers to deal with on a recurring basis. In fact, some observers say the
military is a self-perpetuating and reinforcing culture with practices that
support what has otherwise been called a hypermasculine hegemony
(Richard & Molloy, 2020; Steidl & Brookshire, 2018). Being hegemonic
makes it self-sustaining and rewarding to the existing power structure of
men (McVittie & Goodall, 2017). As such, this condition appears to be a
point of discontent and possibly generalized dissatisfaction for females that
manifested itself in this research in the form of consistent, lower liking
ratings of military products. This research emphasizes the importance of
addressing gender issues not only for job satisfaction and continued military
service, but also potentially to enhance product satisfaction as well.
Hypothesis 2: Leadership
In Hypothesis 2, I predicted a significant relationship between
leadership (leaders vs. nonleaders) and liking/disliking ratings by military
consumers. Leadership was a significant predictor of liking ratings in
product Scenario 2 (popular/great looking, low functioning sock). In
Scenario 2, soldiers in leadership positions gave significantly lower liking
ratings than soldiers who were nonleaders.
Lower functioning socks pose a foot-care problem to Army leaders
who are tasked with helping soldiers prevent injuries through common-sense
practices (Department of the Army, ATP 6-22.5, 2016; Lacdan, 2020).
Leaders are charged to promote footcare among soldiers, particularly when
they are in the field. Leaders are responsible for training and troop safety.
Leaders teach soldiers to take care of their feet and to use proper foot gear.
Combat military leaders are trained to be cognizant of health risks and must
be vigilant in communicating daily with medical personnel regarding any
health circumstances that could negatively impact the ability of soldiers to
operate in the field (Molloy, 2020). Low-function socks (despite looking
good) would logically be less liked from a safety-conscious leader’s
perspective. Product Scenario 2 was described as taking place in the field,
where soldier safety concerns are elevated and more important than
appearance concerns. In the field, a leader would have a duty to oversee and
encourage use of a more functional sock over a less functional sock that
looked nice. Significantly lower liking ratings by leaders for low-functioning
socks scenario is understandable given their leadership role and
responsibilities.
Hypothesis 3: Years of Service
Hypothesis 3 predicted a significant relationship between years of
military service and liking/disliking ratings of product scenarios by military
consumers. Years of service was a significant predictor of liking ratings in
product Scenario 2 (popular/great looking, low functioning sock). In
Scenario 2, soldiers with more years of military experience gave
significantly higher liking ratings than soldiers with fewer years of military
experience. This may be due to increased valuation of social ties created
from longer time in service. Socialization is strongly applied in military
organizations to lower heterogeneity among soldiers and direct them toward
unified strategic goals and behavior (Manekin, 2017). Initially, most soldiers
know little about the area of their first unit or the people they will be
forming strong social bonds with. They often start out with unrealistic
expectations of their military occupational skill and what Army life will be
like (Helmus, et al., 2018). Over time, and usually not until they reach their
first duty station after basic and advanced individual training, soldiers begin
to develop close social relationships with peers and leaders (Helmus et al.,
2018). The Army is successful in leading people and developing
relationships (Arkin & Dobrofsky, 1978).
Over time, relationships are developed, and strong camaraderie is
experienced by most soldiers (Helmus et al., 2018). Socialization of soldiers
often involves a period of uncertainty and tension between the former
culture of the civilian world and the new culture of the military world being
entered into (Ahlfs, 2018). This tension is followed by directives,
instruction, and activities that unify new recruits into a structured, social
network that provides valuable camaraderie, mutual support, growth
opportunities, and friendship that sustains many soldiers while serving in the
military (Lundquist, 2008). Military socialization impact is often so effective
that it leads new recruits to want to stay in the military (Helmus, et al.,
2018). Social connectedness for soldiers increases with time and results in
higher retention for soldiers. It has also been associated with motivations of
behavior, improved physical and mental health, and lower incidence of
posttraumatic stress disorder (PTSD; Helmus et al., 2018; Kintzle, 2018;
Nevarez et al.,
2017; UCLA, 2010).
Camaraderie and social connectedness are more difficult for some
soldiers transitioning to civilian life, especially if they have been exposed to
combat (Ahlfs, 2018; Arkin & Dobrofsky, 1978). Having social
connectedness increases soldier health and helps soldiers adapt to the lack of
structure in civilian life. More recently, fostering connectedness has become
recognized as a desirable and important goal to pursue by those helping
soldiers transition to civilian life (Kintzle et al., 2018). Despite socialization
efforts, those efforts have limits and regular soldier preferences may differ
from leader directives enough so that leaders must concede to the power of
the group (Manekin, 2017). For example, such differences led to
oppositional attitudes and rebellion that became major obstacles to Israeli
Defense Force campaign efforts. During the Second Intifada, reservists who
had served for a significant time resisted orders of their leaders to serve in
occupied territories. Resolution was eventually achieved after IDF
leadership made significant concessions (Manekin, 2017).
Similar differences may exist in this research between military leaders (who
rated
Scenario 2 lower) and those with greater time in service (who rated Scenario
2 higher).
Less experienced soldiers tend to be younger and more recently at basic and
advanced individual training environments where they are taught by leaders
to obey orders without question (Arkin & Dobrofsky, 1978; Levy & Sasson-
Levy, 2008; Zurbreggin, 2010). It may be that less experienced soldiers are
more influenced by leaders than are experienced soldiers such that the less
experienced soldiers are more likely to follow leaders and rate product
Scenario 2 in a similar manner as a leader would. This may help explain the
liking rating differences between experienced and less experienced soldiers.
Experienced soldiers have had more time to develop independent thinking
compared to younger recruits. They may recognize and value social
connectedness more, which can be achieved when wearing popular socks
that provide peer attention and praise. Either case would follow a value-
constructed path reasoned to by the soldier. Value-constructed consumer
thinking was discussed earlier in Chapter 2 (Lee & Shavit, 2006). Logically,
one might expect more experienced soldiers to understand the value of social
connectedness over unquestioning obedience. The current research supports
this hypothesis. More experienced soldiers gave significantly higher liking
ratings in product Scenario 2 (popular/great looking, low functioning sock),
which underscores social relationships.
Hypothesis 4: Deployment Experience
Hypothesis 4 predicted a significant relationship between deployment
experience and liking/disliking ratings by military consumers. Deployment
experience was not a significant predictor of liking ratings in any product
scenario. Deployment experiences can be diverse in terms of location,
duration, difficulty, enjoyment, etc. Congressional Research Services (2022)
provided the U.S. Congress a report of the instances of the United States
government’s use of armed forces abroad. The United States military has
been used extensively for a variety of instances throughout the world. Some
deployments are small. For example, on February 23, 2004, the President
sent a 55-person, armed security force to Port-au-Prince, Haiti to augment
the U.S. embassy security forces to protect American citizens and property
due to instability caused by an armed rebellion in Haiti. Other deployments
are large, such as the deployment in May, 2005 where the President sent a
consolidated list of deployments to congress in support of the global war on
terrorism with 139,000 U.S. military persons deployed to Iraq and other
areas
(Congressional Research Services, 2022).
Diversity in terms of type and length of deployment is considerable.
The dataset used in the current study only recorded the number of
deployments and did not include deployment factors that may influence
military consumer attitudes. Parker et al. (2019) determined that soldiers had
mixed views on whether their deployments were positive or negative. Parker
et al.’s work suggests a variety of deployment experiences (e.g., duration,
how austere, degree of battle engagement, time between deployments, etc.)
can influence attitudes and behaviors of soldiers. The current research did
not include distinguishing information about the deployment experiences.
Deployment was measured solely by the number of deployments the soldier
experienced and this variable was not a significant predictor of
liking/disliking ratings in any product scenario. This data limitation
regarding possible variation in positive and negative deployment
experiences could not be examined in terms of possible relationships to
military consumer attitudes
(i.e., liking ratings of military product scenarios).
Hypothesis 5: Combat Experience
Hypothesis 5 predicted a significant relationship between combat
experience and liking/disliking ratings by military consumers. Combat
experience was a significant predictor of liking ratings in product scenarios
2, 4, and 5 (popular/great looking sock, popular snack, and a peer-praised
complaint process). Those scenarios were similar in that all of them were the
only product scenarios that described positive social praise from peers.
These results demonstrated that soldiers with combat experience gave
significantly higher liking ratings in these scenarios than soldiers without
combat experience.
The combat-experienced soldiers’ higher liking ratings for product
scenarios that involved positive social connectedness with their peers is
notable. The need to belong is a universal human need (Allen, 2022). The
military addresses this need through an exceptionally powerful socializing
effort among its members (Ahlfs, 2018; Arkin & Dobrofsky, 1978; Levy &
Sasson-Levy, 2008). Though military socialization is powerful, it is not
absolute (Levy & Sasson-Levy, 2008). Combat exposure strains the social
fabric of military members and social connectedness is challenged
afterwards. Yet, it is even more essential for combat-exposed soldiers during
their service (i.e., to mitigate the risks associated with combat exposure) and
after their service as they seek to reintegrate into normal civil society
(Kintzle et al., 2018). For example, soldiers with high levels of social
connectedness have more effective coping skills and reduced incidence of
posttraumatic stress disorder symptoms (Kintzle et al., 2018). Military
efforts to build social connectedness results in unit cohesion and improves
soldiers’ ability to function as a unit under extreme conditions. In a recent
study by Parker et al (2019), 90% of soldiers with combat experience
reported that the military prepared them well for military life but only about
half said the same thing about preparing them for the transition to civilian
life. Soldiers with combat experience believe that combat experience
resulted in greater connectedness to those who served alongside them in
battle. This research demonstrated that soldiers with combat experience gave
significantly higher liking ratings in product scenarios, associated with
increased social connectedness, compared to soldiers without combat
experience.
Hypothesis 6: Self-monitoring
Hypothesis 6 predicted a significant relationship between self-
monitoring total scores and liking ratings by military consumers. High self-
monitors express themselves in ways to appeal to the social values of those
they are trying to impress (DeBono, 2006, Slama & Singley, 1996). Low
self-monitors are motivated to reinforce their own, internal value system
(DeBono, 2006; Kauppinen-Räisänen et al., 2018). For civilian consumers,
self-monitoring predicted product appeal in low and high self-monitors
based on product image, product quality, and product type (DeBono, 2006;
Hogg et al., 2000; KauppinenRäisänen et al., 2018). However, in the current
study the self-monitoring total score was not a significant predictor of liking
ratings in any of the product scenarios. In each of the three product
categories (clothing, food, equipment), one scenario was written to appeal to
social praise and low functionality (high self-monitoring appeals) and a
second
scenario was written to appeal to product functionality and low social praise
(low selfmonitoring appeals).
One possible explanation may be that the product scenarios lacked
saliency congruent to the social values high self-monitoring soldiers
perceive to exist (Shavitt & Fazio, 1991). The product scenarios used in the
present study were developed based on similar consumer research that
manipulated a product’s appeal to low self-monitoring personality traits.
However, the validity of the product scenarios was not tested. Alternatively,
self-monitoring may not be a significant factor in soldiers’ attitudes and
evaluations of military consumer products because a military culture does
not provide social status based on those consumer products. Rather, social
status may be the result of rank, awards, and achievements related to
military performance and not associated with the type of products issued to
military personnel. Self-monitoring may simply not be an important
personality characteristic with respect to evaluation of consumer products in
the military due to limited abilities of the soldiers to distinguish themselves
through product selection and use. Soldiers are trained to focus on
completion of their mission. Perhaps this focus leads soldiers to look for
social rewards elsewhere within the military culture (e.g., badges, feats of
accomplishment, the uniform itself, special assignments,
etc.).
Hypothesis 7: Acting Subscale
Hypothesis 7 predicted a significant relationship between Acting
subscale scores and liking/disliking ratings by military consumers. Acting
subscale scores did not significantly predict liking ratings in any of the
product scenarios. The Acting subscale relates to the aspect of one’s abilities
to willfully and effectively act and present oneself as something other than
their native self-dispositions. As in hypothesis 6, the selfmonitoring
construct may not be a factor in military consumer product evaluations.
Hypothesis 8: Extraversion Subscale
Hypothesis 8 predicted a significant relationship between Extraversion
subscale scores and liking/disliking ratings by military consumers.
Extraversion was a significant predictor of liking ratings in the scenarios
involving a product complaint (scenario 5 and 6). That is, participants with
higher levels of Extraversion gave significantly higher liking ratings in both
complaint scenarios (i.e., low praise but effective resolution of the
complaint, and high praise but ineffective result of complaint). Both
scenarios described a detachable ammunition magazine that randomly falls
out of the weapon which can lead to life-or-death circumstances and a
soldier’s ability to fight. It seems those high in Extraversion are motivated to
action regardless of the differing types of complaint process results.
Extraversion subscale relates to a person’s proactive tendencies (Briggs et
al., 1980). Logically, this can include their willingness to insert themselves
into socially challenging situations. In the present case, it appears that both
complaint scenarios involved taking an action with various rewards and
challenges. Both action paths were liked more by those with higher levels of
Extraversion. Extraversion has been linked to a dopaminergic response
wherein the neurotransmitter dopamine functions as a motivator (Wilmot et
al., 2016). Anticipation alone can be enough to raise dopamine levels
(Pietrangelo, 2019). It may be that scenarios 5 and 6 describe events and
activities with previous experiences or with enough significance and
consequence (weapon firing functionality and lethality) that reading and
thinking about the situation incentivizes or stimulates the brains of higher
Extraversion soldiers enough to trigger dopamine release and an increase of
motivation that leads to higher liking ratings (Volkow et al., 2011; Wise,
2006).
Both scenarios were associated with an effort to complain up the chain
of command to seek a resolution to the problem. One method was effective
in resolving the defect. The other method provided social regard among
peers. Regardless of the scenario’s context and social differences, liking was
the same. It seems that those higher in Extraversion chose taking action with
a vital military product (weapon operations) in the form of a complaint
process with varied rewards.
Military culture socially recognizes being proactive in battle with
various awards, such as the Bronze Star Medal with a “V” for valor. It is
reasonable to assume that those with higher levels of Extraversion see a
benefit being associated with any proactive efforts to resolve the defective
magazine through engaging in the complaint process regardless of positive
and negative social aspects. To those with higher levels of Extraversion,
both scenarios may offer different, yet equally valued forms of social status.
Hypothesis 9: Other-Directedness Subscale
Hypothesis 9 predicted a significant relationship between Other-
Directedness subscale scores and liking/disliking ratings by military
consumers. Self-monitoring’s Other-Directedness subscale scores pertain to
behavior where one shrinks and subjugates personal interests to suit the
interests of others. This construct is associated with shyness, low self-
esteem, anxiety, and neuroticism (Wilmot, 2015). The Other-Directedness
subscale scores did not significantly predict liking ratings in any of the
product scenarios. Wilmot (2015) examined Other-Directedness and found it
unsuitable as a subscale in self-monitoring because it had lower validity and
was orthogonal to the other subscales. Wilmot et al. (2017) proposed a
bivariate model founded on the same self-monitoring instrument questions
used by Snyder (1974, 1986). Wilmot questioned the original scoring
method and created two new subscales termed acquisitive and protective
selfmonitoring. Although not in the scope of this research, reanalysis of the
data using those two sub-domains might be useful. This study’s intent was to
focus on a military consumer group using traditional self-monitoring
subscales. It seems some of the evaluated components of self-monitoring
(subscales or total) do not influence military consumer attitudes toward
military products.
Limitations of the Study
One important limitation in the current study was that the scenarios
were not validated to ensure that they reflected meaningful and salient image
conveyances that low and high self-monitoring military consumers valued.
There were other limitations related to the measurements. In Chapter 4 I
noted that the self-monitoring subscales had low internal consistency values
(each subscale <.50). This certainly raises questions regarding the validity of
the self-monitoring scores for the sample. In addition, the assumption of
multicollinearity was not met for some of the predictor variables. This may
have reduced the precision of the estimated coefficients, which weakens the
statistical power of the regression models (Tabachnick & Fidell, 2013).
Finally, there were limitations regarding the lack of control in using an
archival dataset. The fact that the dataset was also relatively old (i.e.,
collected in 2013) also limits the ability to generalize the results. This study
did not find evidence to support self-monitoring as a factor that can be used
to predict military consumer attitudes of military products. However, it does
suggest that the military culture is different and self-monitoring personality
characteristics are not influential in evaluation of military consumer
products.
Recommendations
It is recommended that a similar study be conducted with validated
scenarios and confirmation that the manipulated military product scenarios
convey product images that are aligned with low and high self-monitoring
attributes. This would strengthen the conclusion of the current study that
self-monitoring personality characteristics are not influential in evaluation of
military products. It may also be useful to evaluate the original archival data
set using the bivariate self-monitoring scoring procedure proposed by
Wilmot et al. (2017). If that model yields similar results, this will provide
additional evidence confirming the lack of self-monitoring’s utility with
military consumer evaluation of military products.
Further research to characterize the relationship of specific military
cultural practices (e.g., potential influence of a hegemonic hypermasculinity,
gender scripts, social reward systems) and their relationship to product
satisfaction could help product developers identifying ways to develop and
present products that will be better utilized by the soldier. A grounded theory
approach to understanding male and female product utilization factors could
help. Relative to this, value is expected to be found in repeating with female
soldiers the same evaluation for perspective of scripts and expectations as
was done with male soldiers by Richard and Molloy (2020).
Finally, results from this current work suggests that social
connectedness may be a prominent factor that influences soldiers’ liking of
products. Learning more about the importance of social connectedness may
be useful to future research intended to enhance the warfighter’s use of
products that support health, performance, work environment, job
satisfaction, and retention.
Implications
Military consumer product liking impacts how well products are used
for their intended purposes at the individual soldier level. Improvement in
product liking can lead to benefits in many aspects of a soldier’s life. Failure
of products to appeal to soldiers may be due to oversights by product
developers or may even reflect deeper military cultural factors that need
further exploration. This research underscores some significant variables
related to product liking that may point to potential military cultural
influences in soldiers’ experiences that need further research. Some of these
variables include gender, time in service, leadership, and combat experience.
Discovering the causes of these differences presents an opportunity to gain
knowledge that may lead not only to improved individual product liking and
product usage but potentially to improved military cultural practices that
better support the demographic differences. Those improved practices may
also benefit the Army as a whole. That might mean a stronger, more diverse
military (i.e., a military with a stronger, more satisfied, and a more balanced
male: female ratio). A potential downside is that without improved practices
female representation and general satisfaction with the miliary will remain
low. The current study suggests that gender is an important factor not just to
military consumer research but to military culture.
Less waste of products and better prepared soldiers with higher morale
are obvious benefits derived from increasing a product’s liking level among
soldiers. Addressing potential underlying causes of lower product ratings
may have even larger implications. With respect to a potential gender-based
cultural deficit causing lower female product ratings, if cultural deficit is the
cause, and if the culture is not improved, females may continue to be
underrepresented in the military. Women serving in the military increased
six-fold from 1973 (when the all-volunteer force was established) to
1995, at which time females represented 13% of the total U.S. military force
(Antecol &
Cobb-Clark, 2006). Today that percentage is closer to 17% (Department of
Defense Office for Diversity, Equity, and Inclusion, 2022). A continued
female underrepresentation could impact all levels of our society with
incalculable losses related to female perspectives and insights that are lost or
never discovered. The causes for the gender-related product scenario liking
differences need to be understood. The implication is that improved military
cultural practices could also be implemented that potentially increase diverse
viewpoints added to the richness of the military culture and development of
products, practices, and systems that can be used to improve the safety and
effectiveness of all military personnel.
Conclusion
This research was conducted with the purpose helping the military and
warfighters be more effective and safer through liking and using military
consumer products more effectively. This study examined the strength of
self-monitoring and demographic variables in predicting military consumer
liking ratings of product scenarios. The research showed that self-monitoring
was not a significant predictor of liking ratings of military products. Self-
monitoring-relevant social rewards may not be relevant in military consumer
products. Gender was a significant predictor of liking with males providing
consistently higher liking ratings than females regardless of product or
scenario types. Gender issues related to liking products may relate to
military cultural elements impacting social rewards, retention, and possibly
other unknown losses or benefits. Other demographic variables also
demonstrated significant differences in liking of military products. Gaining
understanding of the causes of these differences may provide opportunities
to improve satisfaction of military products, reduce waste, and to make
improvements within the military culture.
