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Chapter 1: Introduction to the Study
One of the primary goals of a salesperson is to achieve sales results (Behrman &
Perreault, 1982). Sales managers are in a position to significantly influence the actions
and behaviors of the salespeople they manage (Anderson & Oliver, 1987). Sales
managers struggle with the transition from salesperson to sales manager (Russ, McNeilly,
& Comer, 1996), often receive very little effective training (Dubinsky, Mehta, &
Anderson, 2001), and are not given specific guidance on how to best allocate their time
and effort (Beck, 2006). A key element of organization theory involves the role
expectations communicated to salespeople by their sales managers (Jones, Kantak,
Futrell, & Johnston, 1996). Manager behavior matters and can have devastating effects if
applied inappropriately. According to CEB Sales and Service (2012), the cost of a failed
sales manager exceeds four million dollars due to the direct and indirect costs of lost
productivity, attrition, recruitment, salary, and training. On the positive side, management
behavior applied appropriately can have very positive effects. Leader role clarity in
communicating role-based expectations had a statistically significant negative effect on
salesperson turnover via salesperson role clarity and job satisfaction (Jones et al., 1996).
According to Doyle and Shapiro (1980), leader clarity setting and communicating
expectations regarding salesperson activities was the most significant contributor to
salesperson motivation.
Sales management behavior involved in creating role clarity is not a one-size-fits-
all affair and should be influenced by the nature of the situational characteristics that
define the roles of the salespeople being managed (Flaherty, Arnold, & Hunt, 2007).
Sales managers can focus on the behaviors sellers are expected to execute, the results
2
sellers are held accountable to achieve, or both (Ouchi, 1979). Seller behaviors and
outcomes are largely defined by the roles sellers occupy in an organization (Eisenhardt,
1985). By examining specific elements of the salesperson’s role characteristics and the
connection between sales management approach (control) and salesperson performance, I
contributed new insights to the nature and type of management control that are
appropriate for different sales roles that differ in terms of their characteristics (e.g., the
complexity of the product sold and the process buyers use to purchase the seller’s
product). By examining the moderating role of product complexity, task complexity, and
number of accounts on the relationship between management control (both behavior and
outcome control) and salesperson performance, I provided guidance to sales managers on
the best application and level of sales management control for various individual sales
role characteristics. As a result of this study, I provided specific details organizations can
use to design management procedures and associated management training to better
prepare managers to behave in ways that are appropriate for salespeople they manage. In
addition to providing improved clarity for the sales manager, I identified the appropriate
type and level of sales management control by salesperson role characteristics to reduce
job stress, improve salesperson job satisfaction, and positively impact salesperson
performance (see Cravens, Ingram, & LaForge, 1993). This may lead to an overall
positive change to the work environment of both salespeople and sales managers.
This chapter begins with an examination of the background of prior management
control research and the justification for the study. This is followed by a discussion of the
gaps/limitations associated with previous research findings. The purpose of the study is
then discussed, including the type of study, study intent, and a description of the
3
independent, dependent, and moderating variables. The research questions are stated,
including null and alternative hypotheses. The theoretical framework for the study is
described including the origin of the theory and the nature of the link between the theory
and the research questions posed in this study. A description of the nature of the study is
provided, including the study variables and the methodology used to conduct the study.
Definitions of key terms are provided, key assumptions stated, and scope and
delimitations of the study are shared. Significance of the study is discussed, including the
both the extension of the extant literature on management control as well as the practical
application to leaders of sales organizations. The chapter ends with a summary and
introduction to the literature review.
Background
This study addressed the relationships between sales management control and
salesperson performance, including the potential moderating effect of salesperson role
characteristics. Although many studies have been conducted on the impact of sales
management control on salesperson performance (Baldauf, Cravens, & Piercy, 2005),
findings have been inconsistent (Miao & Evans, 2011). Panagopoulos, Johnson, and
Mothersbaugh (2015) found that the two most prevalent measures of management
control, introduced by Jaworksi and MacInnis (1989) and Oliver and Anderson (1987),
measured different constructs. Panagopoulos et al. also found that the use of both scales
in the same study, with the same population, resulted in different results regarding the
relationship between management control and salesperson performance.
The three types of management control mechanisms of interest to this study were
(a) outcome control, (b) capability control, and (c) activity control. Salesperson outcome
4
performance was defined as the degree to which a salesperson meets sales objective
targets (Behrman & Perreault, 1982). Outcome control was defined as the degree to
which an individual seller is evaluated against the results of individual seller effort
(Challagalla & Shervani, 1996). Outcome control has been found to be positively related
to salesperson outcome performance (Babakus, Cravens, Grant, Ingram, & LaForge,
1996; Piercy, Cravens, & Lane, 2009; Cravens, Lassk, Low, Marshall, & Moncrief, 2004;
Evans, Landry, Po-Chien, & Shaoming, 2007), indirectly related to salesperson outcome
performance (Cravens et al., 1993), and unrelated to salesperson outcome performance
(Joshi & Randall, 2001; Miao & Evans, 2013; Oliver & Anderson, 1994). The variation
in study findings may be attributed to differences in the populations studied. The
populations were varied and included sales executives (Babakus et al., 1996), sales
managers (Piercy et al., 2009), and salespeople (Cravens et al., 2004; Evans et al., 2007;
Piercy et al., 2009). There were also differences in the types of salesforces studied. Some
studies included business-to-consumer sales (Joshi & Randall, 2001), some contained a
mixture of business-to-consumer and business-to-business salesforces (Evans et al.,
2007), and others addressed business-to-business sales (Oliver & Anderson, 1994). This
variation in level of position (chief executive, sales manager, salesperson) and type of
sale (business-to-consumer versus business-to-business) may have contributed to the
variation in findings from prior studies.
In addition to variation in positions examined (chief executive officers, sales
manager, salesperson) and populations studied (business-to-business versus business-to-
consumer), there were variations in management control conceptualizations (Anderson &
Oliver, 1987; Jaworski, 1988) and associated measurement instruments used (Jaworski &
5
MacInnis, 1989; Oliver & Anderson, 1994) to examine the control-performance
relationship. Anderson and Oliver (1987) proposed that behavior control (activity and
capability control) and outcome control were opposite ends of a continuum and that the
level of outcome control was determined by the lack of behavior control. Associated
measurement scales (Babakus et al., 1996; Cravens et al., 1993; Oliver & Anderson,
1994) included a continuum of control in which lower scores indicated an outcome-
control orientation and higher scores indicated a behavior-control orientation. Jaworski
(1988) proposed that behavior control and outcome control were two separate constructs.
Associated measurement instruments (Jaworksi & MacInnis, 1989) included separate
scales for behavior and outcome control. Panagopoulos, et al. (2015) used both
management control conceptualizations (Anderson & Oliver, 1987; Jaworksi, 1988) and
associated measurement scales (Jaworksi & MacInnis, 1989; Oliver & Anderson, 1994)
to examine the relationship between management control and salesperson performance.
Panagopoulos et al. found that the size and nature of the effect of sales controls on
salesperson performance differed depending on the conceptualization and associated
scales used. Challagalla and Shervani (1996) argued for an adjusted conceptualization of
process control. Challagalla and Shervani proposed that measures of process control were
too blunt and may have contributed to variation in study findings. Challagalla and
Shervani proposed that behavior control should consist of the two separate constructs of
capability and activity control.
Capability control is defined as management behaviors that emphasize the
development of individual skills and abilities of salespeople (Challagalla & Shervani,
1996). Challagalla and Shervani (1996) found no direct association between capability
6
control and salesperson outcome performance. This lack of direct association was
replicated by Miao and Evans (2013). In another study, capability control was found to be
positively related to salesperson outcome performance (Flaherty et al., 2007). As
mentioned earlier, the type of sales environments in these studies varied between
business-to-business and business-to-consumer.
Activity control involves the sales manager’s attempt to influence routine
activities undertaken by salespeople (Challagalla & Shervani, 1996). Challagalla and
Shervani (1996) found no direct influence of activity control on salesperson outcome
performance. This lack of direct association between activity control and salesperson
outcome performance was replicated by Evans et al. (2007) and Miao and Evans (2013).
Activity controls and capability controls have been found to interact negatively to affect
problem-solving, such that capability control significantly and positively impacted
problem-solving when activity control was weak, and significantly negatively impacted
problem-solving when activity control was strong (Wang, Dou, & Zhou, 2012).
Piercy et al. (2009) found that management control was positively and
significantly related to salesperson behavior and outcome performance; however,
Challagalla and Shervani (1996) asserted that this relationship may be moderated by the
difference in tasks associated with a salesperson’s role. Task complexity (John & Weitz,
1989) and product complexity (Slater & Olson, 2000) are two sales role characteristics
researchers have studied relative to salesperson performance (Atuahene-Gima & Li,
2002; Bello & Gilliland, 1997; Flaherty et al., 2007; Menguc & Tansu Barker, 2003),
although the moderating effect of these constructs on the relationship between sales
management control and salesperson performance has not been studied. Number of
7
accounts is another sales role characteristic researchers have used to codify a taxonomy
of sales roles (Moncrief, Marshall, & Lassk, 2006); however, the potential moderating
effect of number of accounts on the relationship between management control and
salesperson performance has not been studied.
Task complexity concerns the nature of the purchase decision from the buyer’s
perspective (John & Weitz, 1989). Menguc and Tansu Barker (2003) examined the
relationships between sales management control, task complexity, sales volume, and
profitability. Menguc and Tansu Barker found that when behavior-based management
control was high, incentive pay was negatively related to sales volume. High levels of
task complexity were positively and significantly related to sales volume but not
profitability (Menguc & Tansu Barker, 2003).
Product complexity concerns the nature of the product being sold from the seller’s
perspective (Slater & Olson, 2000). Flaherty et al. (2007) examined the relationship
between sales management control, product complexity, and sales performance. Flaherty
et al. found a significant positive effect of output control on salesperson performance
when product complexity was high, but no effect when product complexity was either
moderate or low.
Number of accounts represents the total number of existing customers and
potential customers assigned to a given seller (Menguc & Tansu Barker, 2003).
According to Menguc and Tansu Barker (2003), when sellers are assigned a large number
of accounts, they are more likely to focus on high-volume, low-effort transactions instead
of sales that are more complex and take longer to close. Although the impact of number
of accounts on the relationship between management control and salesperson
8
performance has not been empirically examined, Moncrief et al. (2006) considered
number of accounts as an important consideration when they developed a taxonomy of
salesperson positions. Moncrief et al. suggested that salesperson positions differ and
should be considered when evaluating salesperson performance.
In summary, variations have been found in the conceptualizations of management
control (Anderson & Oliver, 1987; Challagalla & Shervani, 1996; Jaworski, 1988),
measurement scales (Challagalla & Shervani, 1996; Jaworski & MacInnis, 1989; Oliver
& Anderson, 1994), populations studied (business-to-business, business-to-consumer),
types of samples examined (chief executive officers, sales managers, salespeople), and
intervening variables explored (task complexity, product complexity, number of
accounts). Findings of the relationship between management control and salesperson
performance have been found to be significant and positive (Babakus et al., 1996; Piercy
et al., 2009; Cravens et al., 2004; Evans et al., 2007), indirect (Cravens et al., 1993), and
unrelated (Cravens et al., 1993). According to Panagopoulos et al. (2015), the variation in
study findings can be directly attributed to the choice of management control
conceptualization and associated measurement scales.
Problem Statement
Sales managers in direct, business-to-business sales environments have the most
frequent direct contact with frontline salespeople, and are in the best position to impact
individual seller performance. Although many studies focused on salesperson
effectiveness by attempting to isolate determinants of individual seller performance
(Churchill, Ford, Hartley, & Walker, 1985), fewer studies have targeted the sales
manager level within organizations (Babakus et al., 1996). Although management control
9
of the sales force is an important element of management decision-making, little research
has focused on the specific mechanisms of effective sales force control exerted by sales
management, regardless of type of sales environment (Cravens et al., 2004). Of the large
number of empirical studies that addressed the relationship between sales management
control and salesperson performance, only four studies considered the effect of the
salesperson task characteristics of task complexity and product complexity (Atuahene-
Gima & Li, 2002; Bello & Gilliland, 1997; Flaherty et al., 2007; Menguc & Tansu
Barker, 2003). Across these four studies (Atuahene-Gima & Li, 2002; Bello & Gilliland,
1997; Flaherty et al., 2007; Menguc & Tansu Barker, 2003), researchers examined
different populations and used different management control conceptualizations and
associated measurement scales.
Researchers examined salespeople in business-to-business sales (Atuahene-Gima
& Li, 2002; Flaherty et al., 2007), sales managers in business-to-business sales (Menguc
& Tansu Barker, 2002), and sales managers in a mix of business-to-business and
business-to-consumer sales (Bello & Gilliland, 1997). Results obtained in a pure
business-to-business sales environment (Atuahene-Gima & Li, 2002; Flaherty et al.,
2007) may not be directly comparable to results obtained in a mixed population of
business-to-business and business-to-consumer sample (Bello & Gilliland, 1997).
Management control conceptualizations and associated measurements scales used were
also notably different across the four studies. Three of the four studies (Atuahene-Gima
& Li, 2002; Bello & Gilliland, 1997; Flaherty et al., 2007) included the Jaworksi (1988)
conceptualization of separate constructs of process and output control, and the associated
measurement scales developed by Jaworski and MacInnis (1989). Menguc and Tansu
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Barker (2003) used the Anderson and Oliver (1987) conceptualization of behavior and
output control as separate ends of a single control spectrum, as well as the associated
measurement scales developed by Babakus et al. (1996). The Babakus et al. (1996)
measurement scales do not permit the examination of the individual effects of output and
process controls on salesperson outcome performance, or the impact of task complexity,
product complexity, or number of accounts on the control-performance relationship.
In addition to variation in management control conceptualizations and associated
scales, there were variations in the constructs and associated measurement scales for
product complexity. Two studies (Atuahene-Gima & Li, 2002; Bello & Gilliland, 1997)
included a scale developed by Anderson (1995) to measure product complexity.
Anderson (1995) defined product complexity as the technical attributes of the product.
Flaherty et al. (2007) used the scale developed by Slater and Olson (2000) to measure the
nature of the product being sold from the buyer’s perspective. Menguc and Tansu Barker
(2003) examined purchase complexity using the scale developed by John and Weitz
(1989) concerning the complexity of the purchasing task from the customer’s perspective.
Although all constructs and associated scales are related to the sales process, each
measure has a unique focus, and study findings cannot be directly compared.
Number of accounts associated with a specific sales assignment was considered
within multiple studies (Menguc & Tansu Barker, 2003; Moncrief et al., 2006); however,
the effect of number of accounts on the control-performance relationship was not
examined. Although Menguc and Tansu Barker (2003) included number of accounts in
their study, they used the Jaworski and MacInnis (1989) management control scales to
measure process and output control. According to Challagalla and Shervani (1996),
11
process control includes two separate types of management control. Challagalla and
Shervani’s conceptualization of capability and activity control being separate constructs
was not used in any of the studies addressing the impact of product complexity, task
complexity, or number of accounts on the control-performance relationship. In summary,
inconsistencies exist regarding types of populations studied (sales managers,
salespeople), types of sales environments (business-to-business, business-to-consumer),
conceptualizations of management control (Anderson & Oliver, 1987; Challagalla &
Shervani, 1996; Jaworski, 1988), scales used to measure management control (Babakus et
al., 1996; Challagalla & Shervani, 1996; Jaworski & MacInnis, 1989), and scales used to
measure product and task complexity (Anderson, 1995; John & Weitz, 1989; Slater &
Olson, 2000).
Purpose of the Study
The purpose of this quantitative study was to examine the relationships between
three types of management control (outcome, capability, activity) and salesperson
outcome performance. The second purpose of this study was to examine whether product
complexity, task complexity, and number of accounts moderated the above relationships.
Research Questions and Hypotheses
Research Question 1: Are there relationships between the three types of sales
management control and salesperson outcome performance?
H01: Outcome control, capability control, and activity control are not related to
salesperson outcome performance.
Ha1: Outcome control, capability control, and activity control are positively
related to salesperson outcome performance.
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Research Question 2: Does task complexity, product complexity, and number of
accounts in direct, business-to-business sales moderate the effects of outcome control on
salesperson outcome performance?
H02: Task complexity, product complexity, and number of accounts does not
moderate the relationship between outcome control and salesperson outcome
performance.
Ha2: Task complexity, product complexity, and number of accounts moderates the
relationship between outcome control and salesperson outcome performance.
Research Question 3: Does task complexity, product complexity, and number of
accounts in direct, business-to-business sales moderate the effects of behavior-based
capability control on salesperson outcome performance?
H03: Task complexity, product complexity, and number of accounts does not
moderate the relationship between capability control and salesperson outcome
performance.
Ha3: Task complexity, product complexity, and number of accounts moderates the
relationship between capability control and salesperson outcome performance.
Research Question 4: Does task complexity, product complexity, and number of
accounts in direct, business-to-business sales moderate the effects of activity control on
salesperson outcome performance?
H04: Task complexity, product complexity, and number of accounts does not
moderate the relationship between activity control and salesperson outcome performance.
Ha4: Task complexity, product complexity, and number of accounts moderates the
relationship between activity control and salesperson outcome performance.
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Nature of the Study
This study was quantitative and included a nonexperimental design. Quantitative
studies of the behavior and outcome-based management control constructs within sales
and marketing have been pervasive since 1975 (Baldauf et al., 2005; Jaworski &
MacInnis, 1989; Papangapoulos et al., 2015). Of interest in the current study was the
examination of salesperson role characteristics as moderator variables in determining the
influence of behavior and outcome-based sales management control on salesperson
performance. Hierarchical regression analysis was performed to determine the
moderating effects of the salesperson role characteristics of task complexity, product
complexity, and number of accounts on the effects of activity, capability, and outcome
control on salesperson outcome performance.
Outcome control was an independent variable that indicated the degree to which
an individual seller is evaluated against the results of their effort (see Miao & Evans,
2013). Capability control was an independent variable indicating the development of
individual skills and abilities. Activity control involved the sales manager’s attempt to
influence routine activities. Outcome control, capability control, and activity control were
each measured using a 5-item, 7-point Likert scale initially developed by Jaworski and
Macinnis (1989) and adapted by Challagalla and Shervani (1996). Salesperson outcome
performance indicated the extent to which sellers achieve company volume and profit
targets (see Behrman & Perreault, 1982). This construct was the dependent variable.
Task complexity was a potential moderating variable indicating the nature of the
purchase decision from the buyer’s perspective (see John & Weitz, 1989). Task
complexity was measured using a 7-item scale. These included 0%, 10%, 30%, 50%,
14
70%, 90%, and 100%. The total number of points for all four questions was averaged to
determine the task complexity felt by the individual salesperson. Product complexity was
a potential moderating variable indicating the nature of the product being sold from the
seller’s perspective (Slater & Olson, 2000). Product complexity was measured using a 2-
item scale developed by Slater and Olson (2000). Each item was measured using a 7-
point scale from strongly disagree to strongly agree. The total number of points for the
two questions was averaged to determine the product complexity felt by the individual
salesperson. Number of accounts was the total number of accounts assigned to a
particular seller. Age, sex, and years as a salesperson were extraneous variables that had
been used in prior studies as control variables (Flaherty et al., 2007; Panagopoulos et al.,
2015).
The target population for this study was salespeople who report directly to a
frontline sales manager in a business-to-business environment. The data were collected
via salespersons’ responses to a survey about their sales manager’s level of outcome,
capability, and activity control, as well as task complexity, product complexity, and
number of accounts. Salespeople also responded to questions about their individual
outcome performance. The nature of the sales environment in this study was business-to-
business sales. There was no limitation regarding size of sales team managed, and there
was no tenure requirement. Distributor representatives who sell through channels were
not included in this study, nor were sellers of business-to-consumer sales such as real
estate or retail sales. The research was conducted with a sample of salespeople from a
security services firm in the business-to-business, direct sales environment.
15
Desired participants were identified via a target list of clients and prospects of a
sales management training and consulting company. Sales executives within the target
organizations were invited to have their sales managers evaluated as part of the study. A
description of the study was provided along with my prospectus. Once the participating
company agreed to participate, a sample e-mail was drafted and sent to all participating
sales managers to explain the study and request the participation of their salespeople. The
survey was deployed via Fluid Surveys. A unique link was developed for the
participating company. All appropriate permissions required were secured prior to survey
deployment and participation.
Conceptual and Theoretical Frameworks
The framework for this study was based in the concept of organizational control
(see Ouchi, 1979). Organizational control is an element of organizational theory (Etzioni,
1965; Ouchi & Maguire, 1975). Ouchi (1977) asserted that control within an organization
and the structure of an organization are not interchangeable, and that the control system
in place consists of a process for monitoring and evaluating performance. Ouchi (1977)
was the first to propose that control within organizations consists of two fundamental
types of phenomena that can be measured: behavior and the outputs resulting from the
behavior.
Several additional frameworks have been proposed as a result of Ouchi’s (1977)
seminal work to further define the control exerted by managers within an organization.
Anderson and Oliver (1987) proposed a framework for management control that has been
studied extensively in the literature. Their proposed framework for management control
involves the level to which managers use a behavior-based approach to (a) monitor, (b)
16
direct, (c) evaluate, and (d) reward individual sellers. Based on an extensive analysis of
management control studies, Panagopoulos and Avlonitis (2008) found the framework
proposed by Anderson and Oliver was by far the most widely studied and suggested that
it formed the benchmark for further studies.
Another framework for behavioral control introduced by Jaworski and Merchant
(1988) extended the idea of management control by going beyond behavioral and output
control, and adding the additional elements of self-control and social control. Jaworski
and Merchant suggested that behavioral control and output control are the formal
mechanisms organizations use to monitor and evaluate performance, and that self-control
and social control are the informal means organizations use to monitor and evaluate
performance. The constructs of formal and informal management control (Jaworski &
Merchant, 1988) and associated scales (Jaworski & MacInnis, 1989) have been widely
used and reported extensively in the management control literature (Baldauf et al., 2005).
To further refine the approach to management control research, Challagalla and
Shervani (1996) disaggregated the global behavioral control construct into activity
control and capability control. Jaworski and MacInnis (1989) and Oliver and Anderson
(1994) considered behavioral control to be a global construct; however, the behaviors that
sales managers can influence include both the day-to-day activities of salespeople, as
well as the more complex behaviors necessary to enhance salesperson capability
(Challagalla & Shervani, 1996). Activity control involves the sales manager’s attempt to
influence routine activities undertaken by salespeople, and capability control refers to the
development of individual skills and abilities (Challagalla & Shervani, 1996). This
conceptualization of activity control, capability control, output control, and associated
17
scales (Challagalla & Shervani, 1996) was relevant to this study and was used as the
measure of both behavioral control (activity and capability control) and output control.
The constructs and associated scales developed by Challagalla and Shervani have been
used widely for empirical studies in the management control literature (Evans et al.,
2007; Fang, Evans, & Zou, 2005; Miao & Evans, 2011, 2014; Wang et al., 2012).
Definition of Terms
The following terms are operationally defined for the purpose of this study:
Activity control: A sales manager’s attempt to influence routine activities
undertaken by salespeople (Challagalla & Shervani, 1996).
Behavior control: Management surveillance of employee activities (Eisenhardt,
1985).
Business-to-business sales: A sales environment characterized by salespeople
selling directly to one or more buyers within a business context.
Business-to-consumer sales: A sales environment characterized by salespeople
selling directly to individual consumers.
Capability control: Management behaviors that emphasize the development of
individual skills and abilities of salespeople (Challagalla & Shervani, 1996).
Management control: Written, management-initiated mechanisms that increase
the probability that marketing employees will behave in ways that support stated
marketing objectives (Jaworski, 1988).
Number of accounts: The number of existing customers and prospective
customers assigned to an individual salesperson.
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Process control: Management focus on seller behaviors rather than seller end
results (Jaworski, 1988).
Product complexity: Nature of the product being sold from the seller’s perspective
(Slater & Olson, 2000).
Output control: Performance standards measured as end results, such as quota or
revenue targets (Jaworski, 1988).
Sales role: Situational or task characteristics associated with a given sales position
(Flaherty et al., 2007).
Salesperson outcome performance: A measure of salesperson objective
achievement (Behrman & Perreault, 1982).
Task complexity: The nature of the purchase decision from the buyer’s perspective
(John & Weitz, 1989).
Assumptions
One assumption of this study was that salespeople provided accurate reporting of
their level of objective sales performance. Actual salesperson performance data are
always the most reliable measure; however, the perceived risk to organizational
executives in providing performance data to outside entities often prohibits provision of
individual employee data. Another assumption was that measures of capability, activity,
outcome control, task complexity, product complexity, number of accounts, and sales
objective performance were face valid and easily understood by salespeople when
evaluating levels of these constructs. This assumption was necessary to ensure the
findings of this study would be useful to researchers and sales practitioners who want
19
tactical guidance regarding the relationships of management control, sales person
characteristics, and salesperson performance.
Scope and Delimitations
This study addressed the relationships between the sales management control
elements of output control (Jaworski & MacInnis, 1989), capability control (Challagalla
& Shervani, 1996), activity control (Challagalla & Shervani, 1996), salesperson outcome
performance (Behrman & Perreault, 1982), and the moderating effects of task complexity
(John & Weitz, 1989), product complexity (Slater & Olson, 2000), and number of
accounts on the above relationships. This study took place in a business-to-business sales
context and involved feedback from a salesperson population. The selection of
instruments, constructs, and population provided practical insights for both researchers
and practitioners regarding the types of management control to employ to drive higher
levels of sales performance, and under what conditions those controls should be
employed. The Challagalla and Shervani (1996) conceptualization was selected because
it provided a more sensitive measure of behavior control as compared to earlier
conceptualizations (Anderson & Oliver, 1987; Jaworksi, 1988).
The instruments developed by Jaworksi and MacInnis (1989) to measure output
control differ from other measures of outcome control, namely those of Oliver and
Anderson (1994) and Babakus at al. (1996), both of which align with the theoretical
propositions set forth by Anderson and Oliver (1987). Anderson and Oliver proposed that
behavior control and output control are opposite ends of a control spectrum and that
management control is an either/or proposition consisting of a primarily output
orientation or a behavior orientation. Jaworksi and MacInnis designed instruments to
20
measure output and behavior control as separate constructs, proposing that both types of
control can be used at the same time. The concept of behavior control (Anderson &
Oliver, 1987) was articulated by Jaworksi and MacInnis (1989) as process control and
was measured with a separate scale from output control.
A large number of studies aligned with the Anderson and Oliver
1987management control framework and associated instruments measuring a continuum
of control (Babakus et al., 1996; Cravens, Ingram, LaForge, & Young, 1993; Oliver &
Anderson, 1994) as either output-oriented or behavior-oriented. The other primary
management control conceptualization (Jaworski, 1988) and associated measurement
scales (Jaworski & MacInnis, 1989) aligned with Jaworksi’s (1988) proposition that
output and process control can both be present and relevant in a sales context. Challagalla
and Shervani (1996) further expanded the scales developed by Jaworski and MacInnis
(1989) by disaggregating the global construct of process control (behavior control in the
Anderson & Oliver, 1987 conceptualization) into two separate behavior-related
constructs of capability and activity control. All three of these conceptualizations
(Anderson & Oliver, 1987; Jaworksi & MacInnis, 1989; Challagalla & Shervani, 1996)
are used to measure different constructs using different measurement scales. According to
Panagopoulos et al. (2015), the results of any management control study depend heavily
on the instrument used. Panagopoulos et al. found that the Oliver and Anderson (1994)
instrument produced markedly different results than the Jaworski and MacInnis (1989)
instrument, such that no statistically significant relationship was identified between
output control and salesperson performance based on the use of the Oliver and Anderson
(1994) instrument, compared to a linear positive and statistically significant relationship
21
between output control and salesperson performance using the Jaworksi and MacInnis
(1989) measurement. Consequently, results of the current study cannot be compared to
results of studies using either the Anderson and Oliver (1987) conceptualization and
associated scales (Babakus et al., 1996; Cravens et al., 1993; Oliver & Anderson, 1994)
or the Jaworski (1988) conceptualization and associated scales (Jaworksi & MacInnis,
1989) regarding the relationship between management control and salesperson
performance. Results of this study can be discussed only in terms of the constructs
measured based on the scales used and the associated relationships identified.
The population studied provided another practical consideration for the validity of
the results. A business-to-business sales force was selected for this study because it
provided the best context in which to study the interactive effects of management control
and sales performance (see Challagalla & Shervani, 1996). Although other management
controls studies included business-to-consumer retail sales (Joshi & Randall, 2001) and a
mix of sales and marketing audiences (Jaworski, Stathakopoulos, & Krishnan, 1993), the
results of the current study can only be compared to other studies conducted in a
business-to-business sales context.
Finally, the moderator variables incorporated in this study were vastly different
from moderators examined in other studies where the researchers were interested in
indirect relationships between management control and salesperson performance. This
study incorporated product complexity, task complexity, and number of accounts as
moderators. Other studies included dysfunctional seller behaviors (Jaworski & MacInnis,
1989; Ramaswami, 1996), salesperson location (Challagalla, Shervani, & Huber, 2000),
and other consequences such as salesperson satisfaction (Jaworksi & Kohli, 1991) and
22
organizational commitment (Agarwal, 1999). These and other related constructs relevant
to a salesperson’s role were not considered as part of the current study. In summary, the
selection of the management control conceptualization (Challagalla & Shervani, 1996)
and associated measurement scales of output, capability, and activity control, as well as
the business-to-business sales context provided both useful boundaries for this study, as
well as practical limitations as to the applicability of the study findings.
Limitations
Studies are valid if the instrument used to test consistently measures what it is
intended to measure. Internal consistency of the survey responses was examined with
Cronbach’s alpha values for the three sales management control scales (outcome,
activity, and capability) and outcome performance. The process ensured that the survey
questions were internally consistent through examination of the internal consistency of
the responses of the different respondents.
Construct validity is the extent to which a measurement is truthful, accurate,
authentic, or free of system error with evidence supporting the conclusion. Studies are
valid if the instrument used to test a construct consistently measures what it is intended to
measure. Construct validity for all measures other than product complexity were strong.
Cronbach’s alpha of .67 for product complexity was the only reliability estimate that was
below the .70 acceptable level. This may call into question any findings of moderation of
the relationship between sales management controls and salesperson performance.
The internal validity of a quantitative study is “the degree to which observed
changes in a dependent variable can be attributed to changes in an independent variable”
(Pedhazur & Schmelkin, 2013, p. 154). For this study, one major threat to internal
23
validity was the direction of the causal influence of the variables studied. This study was
not designed to determine a cause-and-effect relationship. I could not assert that increases
in one or more types of management control led to improved sales performance. In
addition to a lack of causal influence, there were other factors such as market turbulence
and competitive intensity that may have impacted sales performance. Those and other
complicating factors were beyond the scope of this study.
External validity concerns the degree to which conclusions from a study can be
generalized to other categories of people, settings, or times (Green & Salkind, 2010).
Results from this study are not generalizable to other study population groups other than
salespeople in business-to-business sales. Neither salespeople in business-to-consumer
sales nor marketing personnel can apply the findings from my study due to the variation
in job type and evaluation measures. Statistical conclusion validity was also a concern.
The data were evaluated to ensure the data did not violate the assumptions of the
statistical tests.
Significance
Researchers have been studying the relationship between management control and
salesperson performance for many years (Babakus et al., 1996); however, wide variation
exists between conceptualizations of management control, scales used to measure
management control, and populations studied (business-to-business, business-to-
consumer). These variations in conceptualizations and associated measurement scales can
be confounding to a researcher interested in identifying specific variables that impact the
control-performance relationship. The current study provided further clarification to sales
management control researchers as to which types of variables affect the control-
24
performance relationship and the nature of that effect within a business-to-business sales
context. In addition, this study advanced the understanding of sales management control
by providing the first empirical study to address the specific moderating effects of
product complexity, task complexity, and number of accounts on the relationships
between capability control, activity control, and outcome control on salesperson outcome
performance. This provided a very specific context within which researchers could
compare results of prior studies of the control-performance relationships, and provided
potential guidance for the design of future studies. From a practical perspective, the
results of this study may help guide sales managers and leaders regarding the appropriate
types of management control to implement based on variation in sales role
characteristics. Sales managers are provided with concrete insights regarding which
approach to use in a given situation to drive the best performance outcomes for their sales
teams.
Summary
This chapter began with a brief introduction, followed by the background of the
study including a review of relevant literature. The problem statement provided evidence
of a gap in the current literature and justification for the specific parameters of this study.
The purpose of the study was articulated regarding the relationship between the
independent, dependent, and moderating variables. Research questions and associated
hypotheses were presented, followed by the underlying theoretical foundation for the
constructs and associated hypotheses. The nature of the study was discussed including
independent, dependent, and moderating variables in addition to the specific
methodology, population, and analysis to be used. Key definitions of independent,
25
dependent, and moderator variables were provided. Important assumptions for the study
were stated, as well as the scope and delimitations of this study. Limitations were
explored regarding internal and external validity, construct validity, and statistical
conclusion validity. Finally, the significance of the study was discussed regarding the
contribution to academic literature and practical application within a sales context.
Chapter 2 provides a review of relevant research into organizational theory, sales
management control, salesperson role characteristics, and salesperson performance, as
well as the identification a specific gap in the empirical literature related to the effect of
task complexity, product complexity, and number of accounts on the relationships
between capability control, activity control, and outcome control on salesperson outcome
performance. Chapter 3 presents the specifics of the research methodology including the
design and rationale of the study, population and sampling procedures, instrumentation
and operationalization of constructs, threats to validity, and ethical procedures. Chapter 4
provides specific results of this study and the degree to which the results differed from
the research questions and associated hypotheses. Chapter 5 provides a thorough
discussion of the results of this study compared with other studies of management control
using similar constructs, as well as limitations and suggestions for future research.
26
Chapter 2: Literature Review
This quantitative study addressed the relationships between three constructs of
sales management control (outcome control, activity control, and capability control) and
salesperson outcome performance. The second purpose of this study was to examine
whether task complexity, product complexity, or number of accounts moderated the
above relationships. In this chapter, I review existing studies on topics concerning
management control and work performance in the context of business-to-business and
business-to-consumer sales organizations. I present the theoretical background for
management control, various proposed constructs for management control, as well as
empirical studies examining how these psychological concepts impact a sales
organization, particularly the extent of the relationship between sales management
control and performance of an individual salesperson.
Literature Search Strategy
I queried multiple databases to identify the material for this literature review,
including EBSCOHost, ProQuest Central electronic research databases, Emerald
Research Journals, SAGE Journals, Academic Search Complete, Education Research
Complete, and Business Source Complete. I used the search terms sales management
control, outcome control, activity control, capability control, marketing, salesperson
outcome performance, task complexity, product complexity, leadership, and sales’
professional. Although database searches of the key words provided significant results, I
found some of the most useful articles through reference lists of articles identified in the
primary searches. I identified the initial articles via the aforementioned databases
27
associated with the Walden library; however, Google Scholar became my primary source
for articles due to a change in the Walden library search parameters.
Theoretical Background
Organization Theory
Blau and Scott (1962) defined the term organization as a group of individuals
working together in delineated roles to achieve a shared purpose. An organization is a
means of consolidating the strengths of individuals within a group to achieve holistic
accomplishments (Joshi & Randall, 2001). The establishment of a business organization
stems from the belief that the delivery of goods and services is profitable at the end of the
transaction (Jaworski, 1988).
Task characteristics and control systems are two basic principles in organization
theory (Eisenhardt, 1985; Ouchi, 1979). In determining appropriate control, Eisenhardt’s
(1985) value-based framework requires the assessment of two environmental factors: (a)
task programmability, and (b) outcome observability. Task programmability is the extent
to which sales managers articulate the sales and nonsales activities that agents must
perform to attain desired sales targets (Eisenhardt, 1985; Ouchi, 1977). According to
Eisenhardt, a known task’s programmability assists in the identification of appropriate
behavior for positive performance. Behavior control is a rational choice when task
programmability is high but outcome observability is low (Eisenhardt, 1985).
Eisenhardt (1985) associated a transformation process with that of task
programmability because system outcome is a function of employees’ behavior in the
system. When there is high knowledge of the transformation process, explicit behavior
28
control mechanisms are defined for use by sales force leaders to standardize the selling
and nonselling activities of the sales agents (Eisenhardt, 1985). Ouchi (1977) proposed
that a decrease in knowledge of the transformation process affects the identification of
the behaviors to be controlled. Therefore, if the transformation process is not clearly
understood, managers will have difficulty identifying the appropriate behaviors to be
monitored to evaluate the behavior and intentions of the sales agent (Eisenhardt, 1985).
In organization theory, control is determined either through behaviors or
outcomes (Ouchi, 1977). Behavior control is a direct control mechanism that business
leaders may impose (Ouchi, 1977, 1979). Ouchi’s (1979) interpretation of organization
theory suggested that managers disregard inequities of performance and generally assess
actions of the sales agent that affect his or her outcome performance. However, behavior
control requires personal surveillance that affects the length of control imposition
(Eisenhardt, 1985). Outcome observability indicates the degree of sales outcomes (Ouchi,
1979). Outcome control is a proactive choice for sales leaders to consider when there is
high outcome observability and low task programmability (Eisenhardt, 1985, Ouchi,
1979).
Agency Theory
Agency theory (Ross, 1973) is a value-based microeconomics accounting method
for determining optimal, revenue-oriented forms of organizational control. Agency theory
is used to explain the role of the principal, agent, and environmental uncertainty, and the
resulting outcomes of the participation of all actors (Ross, 1973). Researchers have
claimed that agency relationships emerge when work delegation from the principal to the
agent occurs in exchange for compensation (Bergen, Dutta, & Walker, 1992; Eisenhardt,
29
1985; Ross, 1973). Ross (1973) proposed that the principal who possesses the decision-
making authority to secure the optimum level of objective achievement would assert the
control mechanisms. The fundamental principle of agency theory is that although the
principal and agents aspire to accomplish organizational goals, both have opposing
individual goals (Ross, 1973). For example, the principal in an insurance company would
direct sales agents to focus on finding new accounts, whereas the interest of the sales
agent would be to assist accountholders with current yet delinquent accounts.
Agency theory focuses on the resolution of potential conflicts that may arise
between the principal and agents in agency relationships (Ross, 1973). The propositions
of agency theory (Ross, 1973) include the resolutions of conflict (a) arising from the
differences of principal and agents’ goals and that these differences are unverified
because of the inability to provide additional resources, and (b) arising from the
differences of principal and agent perceptions and behaviors toward business risk. The
differences existing between the principal and the agents could potentially hinder the
development of the agency.
The concept of control in agency theory is based on either behavior or outcome
(Eisenhardt, 1985). For instance, agents’ observable behavior could be controlled by
reinforcing desired behavior to achieve the principal’s business advantage. Two
environmental conditions are noted in agency theory: (a) conditions of complete
information, and (b) conditions of incomplete information (Ross, 1973). Under agency
theory, agents could opt to act in conflict with the goal of the principal without
demonstrating observable behavior (Ross, 1973). Agents are most likely to act in ways
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that conflict with the goals of the principal in conditions of high uncertainty and low
programmability, in which available information is incomplete (Ross, 1973).
The second theoretical proposition of agency theory is that the principal (sales
manager) can use outcome control to address uncertainties and transfer financial risk to
the agents (salespeople) (Ross, 1973). Baiman (1982) believed that business outcomes
are the results of agents’ actions. Baiman claimed that outcomes may be positive or
negative depending on the efforts invested by the salesperson. The actions of a
salesperson could be penalized or rewarded depending on the resulting outcomes that are
beyond the salesperson’s control (Baiman, 1982). The selection of rewards or penalties
depends on how behaviors and outcomes are measured and how the process transfers the
risk to the agents (Baiman, 1982).
Transaction Cost Analysis
Transaction cost analysis theory of Williamson (1985) is an appropriate
theoretical model in determining control mechanisms for a salesforce. In the context of
this study, transaction cost was the cost of implementing, monitoring, and controlling the
activities of sales agents. Certain circumstances warrant outcome-based control
mechanisms (John & Weitz, 1989). Highly competitive markets demand outcome-based
controls because of the perceived cost efficiency (John & Weitz, 1989). This means that
the indicator or basis for control are the sales results generated by the sales agents, which
determine sales performance and the efficiency of the agents engaged in the sales
activities (John & Weitz, 1989).
Within transaction cost analysis, internal and external costs associated with
business transactions are weighted and acted on (Williamson, 1985). According to
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Williamson (1985), transaction costs are incurred in the process of delivering a good or
service from one point to the other. Williamson also noted that the factors influencing
transaction costs include (a) environmental uncertainty, (b) opportunism, (c) risks, (d)
bounded rationality, and (e) essential organizational assets. These factors potentially
contribute to the increase or decrease of transaction cost.
Theories of Sales Management and Control
Anderson and Oliver
Anderson and Oliver (1987) offered theoretical propositions to guide researchers
in determining the consequences of the behavior and outcome-based salesforce control
systems. Consolidating the findings from early management scholars (Walker, Churchill,
& Ford, 1977; Weitz, 1979, 1981), Anderson and Oliver (1987) stated that although
outcome control has been cited as a useful system in sales management, behavior control
is more effective as a formal control system. Anderson and Oliver differentiated the two
control systems in terms of the monitoring activities of the final process outcomes and the
process in which the individual sales agent participates to produce those outcomes. Under
the outcome-based control system, Anderson and Oliver proposed that to achieve positive
performance, managers will (a) invest little monitoring time for sales agents, (b) provide
little direction for sales agents, and (c) rely on verifiable measures of outcomes on the
sale agents’ approach. Conversely, a behavior-based control system requires (a) intensive
time in monitoring the sales agents’ activities and outcomes, (b) intensive direction and
activity intervention from the sales managers, and (c) managers combining the approach
of sales agents’ selling knowledge, activities, and sales strategies in rewarding and
penalizing the individuals (Anderson & Oliver, 1987).
32
Anderson and Oliver (1987) reviewed the literature on salesforce control systems
to identify potential moderating variables to provide justification for the selection of an
appropriate control system to affect sales performance. Anderson and Oliver incorporated
the following dimensions in their theoretical framework: (a) control system strategies, (b)
salesperson cognition and capabilities, (c) salespersons affect and attitude, (d) salesperson
motivation, (e) salesperson behavioral strategies, and (f) salesperson’s performance.
Anderson and Oliver stated the first theoretical proposition as follows:
In behavior-based control systems, salespeople are monitored closely, subject to
considerable direction, evaluated on an input basis by subjective and more
complex measures, and rewarded with higher proportion of fixed compensation.
In outcome-based control systems, salespeople are monitored less frequently,
offered little direction, evaluated on outcome measures by objective and simple
methods, and rewarded with a higher portion of incentive compensation. (p. 85)
In this first proposition, Anderson and Oliver (1987) articulated that the
demonstrated behaviors of sales agents form the basis for all performance interventions.
Under this proposition, Anderson and Oliver compared commission-based sales agents
and employed sales agents, in which employed sales agents received more professional
development activities than their commission-based counterparts. Anderson and Oliver
further identified their second proposition: “The more a control system is behavior-based
rather than outcome-based, the more product knowledge, company knowledge, and
integrated sales expertise the salesperson will have and the more professionally
competent the salesperson will be” (p. 85).
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In their third theoretical proposition, Anderson and Oliver (1987) claimed that the
commitment of a sales agent is high in sales organizations that use a behavior-based
control system. Values such as acceptance, cooperation, and receptivity to assessment
from supervisors can be found in sales agents receiving behavior-based control strategies
from their supervisors (Anderson & Oliver, 1987). As such, in their fourth proposition,
Anderson and Oliver proposed that sales agent attrition is high in companies with
outcome-based control systems. This proposition is further supported in Anderson and
Oliver’s fifth theoretical proposition: “The more a control system is behavior-based
rather than outcome-based, the more the salesperson has higher levels of intrinsic
motivation, is motivated by peer recognition, and is motivated to serve the sales agency”
(p. 86).
Anderson and Oliver (1987) also proposed that although intrinsic motivation
among employees is higher in sales organizations with behavior-based control systems as
opposed to outcome-based control systems, individual agents differentiated their
motivational needs depending on the approach their sales supervisors would implement.
Therefore, the Anderson and Oliver’s sixth proposition was: “The salesperson’s hierarchy
of motivation differs across outcome-based and behavior-based systems” (p. 86).
Anderson and Oliver (1987) further believed that a behavior-based control system
generates more new account volume than that of the outcome-based control system.
Anderson and Oliver linked supervisor’s guidance, coaching, and providing of feedback
to the abilities of sales agents to engage in more sales meetings and client prospecting.
Anderson and Oliver (1987) proposed:
34
The more a control system is behavior-based rather than outcome-based, the more
a salesperson can be expected to plan for each call, make fewer calls, operate at a
lower ratio of selling to non-selling time, and spend more time on sales support
activities. Further, salespeople are more likely to use an “expertise sell” and
“open” rather than “closed” techniques in behavior-based systems and to use
“customer-oriented” strategies (p. 86).
The final theoretical proposition of Anderson and Oliver (1987) predicted that
although behavior-based control systems influence sales agents’ commitment to the
organization and encourage sales agent interest in selling activities, the outcome-based
control system remains significantly important for the organizations to meet sales quota.
Anderson and Oliver stated this proposition as: “In control systems that are more
behavior-based than outcome-based, individual salespeople will come closer to achieving
the sales agency’s goals and to serving customer needs, but will perform more poorly on
traditional output measures of individual-level performance” (p 86).
Anderson and Oliver (1987) were clear in favoring behavior-based rather than
outcome-based control in managing sales relationships with salespeople. Anderson and
Oliver undermined outcome-based control as a formal measure in the performance of the
salesperson in the organization. The authors’ propositions implied that the sales
performance of a salesperson depends on their intrinsic motivation and commitment in
the product they sell rather than the compensation they could receive from the sale of the
product (Anderson & Oliver, 1987). Although they indicated a preference for behavior-
based control, Anderson and Oliver acknowledged that both behavior and outcome-based
control systems are important to sales performance.
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Related Empirical Studies
This section includes empirical studies using four separate measurement scales
based upon the Anderson and Oliver (1987) management control conceptualization
(Babakus et al., 1996; Cravens, et al., 1993; Oliver & Anderson, 1994; Robertson &
Anderson, 1993). The four measurement scales were vastly different and likely
contributed to the wide range of findings, many of which were conflicting.
Cravens et al. (1993) developed the first scale to measure management control
aligned with the Anderson and Oliver (1987) conceptualization. This scale had only two
items designed to measure extent of monitoring of salesforce activities and amount of
direction provided by the manager concerning salesperson activities (Cravens, et al.,
1993). In this study of chief executive officers in a combination of business-to-business
and business-to-consumer sales organizations, Cravens et al found an indirect
relationship between behavior-based sales management control and salesperson outcome
performance via salesperson behavior performance and salesperson characteristics. This
finding supports the Anderson and Oliver proposition that behavior-based management
control will positively impact seller behavior, but not seller outcomes. This was the only
study that used the Cravens et al. measurement scale to examine the impact of sales
management control on salesperson performance.
The second measurement scale to examine the Anderson and Oliver (1987)
management control conceptualization was developed by Robertson and Anderson
(1993). This scale included three categories with two items each to measure extent of
supervision, contact with manager, and subjectivity of evaluation (Robertson &
Anderson, 1993) bearing no apparent overlap with the scale developed by Cravens et al.
36
(1993). Robertson and Anderson were the only researchers to use this scale in an
empirical study. In a study of salespeople and sales managers in a business-to-business
sales context, Robertson and Anderson examined the relationship between behavior-
based management control and salesperson ethical reactions. A characteristic of interest
in this study was whether sellers pursued a few large sales or many smaller ones
(Robertson & Anderson, 1993). The researchers found that salespeople within a
behavior-based management control system were less likely to make unethical
recommendations to customers than their counterparts operating in a more outcome-
based control system (Robertson & Anderson, 1993). Sales managers and salespeople
were more likely to take ethical shortcuts when sales were larger (Robertson & Anderson,
1993). The relationship between sales management control and salesperson performance
was not examined in this study (Robertson & Anderson, 1993).
The third scale developed to measure the Anderson and Oliver (1987)
conceptualization of management control was developed by Oliver and Anderson (1994).
This scale included eight items to measure extent of supervision, four items to measure
absence of a bottom-line orientation, three items to measure infrequent use of objective
outcomes, three items to measure use of paper inputs, three items to measure use of
subjective inputs, and two items to measure the percentage of salary in the seller’s
compensation plan (Oliver & Anderson, 1994). Six studies included the use of this scale
to measure the degree of behavior-based management control in use. Three of these six
studies examined the relationship between behavior-based management control and
associated salesperson characteristics (Matuso, 2009; Mullins, Ahearne, Lam, Hall &
Boichuk, 2014; Rouzies & Macquin, 2003).
37
Rouzies and Macquin (2003) studied the relationship between behavior-based
management control, smart selling strategies, and level of seller contact in customer
organizations with a sample of salespeople in a combination of business-to-business and
business to-consumer sales organizations. Behavior-based management control was
positively and statistically significantly related to both smart selling strategies and high
levels of contact in customer organizations (Rouzies & Macquin, 2003). This positive
relationship between behavior-based management control and salesperson characteristics
was similar to the findings of Matuso (2009) who found that salespeople operating under
a behavior-based management controls system were significantly more likely to innovate.
Additional support for the hypothesized positive relationship between behavior-based
management control and salesperson characteristics was provided by Mullins et al.
(2014) who found that the use of behavior-based management control reduced the level
of seller bias related to customer relationship quality. The measurement scale developed
by Oliver and Anderson (1994) was also used to examine the relationship between
behavior-based management control and salesperson performance, although the findings
were inconsistent. In their study of salespeople operating as manufacturer’s
representatives, Oliver and Anderson (1994) found that behavior-based management
control was significantly and positively related to salesperson capabilities and
motivational states, but unrelated to salesperson performance outcomes. These findings
supported the proposed link between behavior-based management control and
salesperson behavior proposed by Anderson and Oliver (1987); however, they conflicted
with Anderson and Oliver’s (1987) proposition that the use of behavior-based
management control would impede salesperson performance outcomes. In contrast to the
38
findings of Matuso (2009), two studies using these same scales found an indirect
relationship between behavior-based management control and salesperson performance
(Ahearne, Hughes, & Jindal, 2010; Panagopoulos, & Mothersbaugh, 2015); however,
their findings were inconsistent.
Ahearne et al. (2010) examined the relationship between behavior-based
management control and new product sales and found that sellers in a behavior-based
control system produced a less-successful shift of customer product perceptions,
adversely affecting new product sales. Those sellers operating within an outcome-based
control system produced a significant increase in customer product perceptions,
positively impacting new product sales (Ahearne et al., 2010). This finding supports
Anderson and Oliver’s (1987) proposition that behavior-based management control will
likely lead to reduced seller outcome performance. In a study of senior executives in
business-to-business sales organizations, Panagopoulos et al. (2015) found behavior-
based management control had a significant and positive effect on salesperson behavior
performance, but no effect on salesperson outcome performance. The researchers found a
positive indirect relationship between behavior-based management control and
salesperson outcome performance via salesperson behavior performance (Panagopoulos
et al., 2015). In this study, Panagopoulos et al. evaluated the validity and reliability of the
management control scale developed by Oliver and Anderson (1994) and eliminated five
items due to poor item properties.
In the five studies that included the Oliver and Anderson (1994) measurement
scales, none of the researchers reported a direct relationship between behavior-based
management control and salesperson outcome performance. Researchers identified that
39
behavior-based management control was unrelated to salesperson performance (Oliver &
Anderson, 1994), positively and indirectly related to salesperson performance
(Panagopoulos, et al., 2015), and negatively and indirectly related to seller performance
(Ahearne et al., 2010). Although few studies were conducted using the Oliver and
Anderson (1994) scales, the inconsistent results of empirical studies using the Anderson
and Oliver (1987) conceptualization of management control were repeated with the most
widely used scales developed by Babakus et al. (1996).
Babakus et al. (1996) developed the fourth and final scale to date used to measure
behavior-based management control aligned to the Anderson and Oliver (1994)
conceptualization. This scale was by far the most comprehensive of the four and included
seven items to measure monitoring, five items to measure directing, five items to measure
evaluation, and eight items to measure level of reward (Babakus et al., 1996). Fifteen
studies included the use of the Babakus et al. scales to measure behavior-based
management control. Of these fifteen studies, some researchers found that behavior-based
management control was unrelated to salesperson outcome performance (Baldauf,
Cravens, & Piercy, 2001; Katsikea, Theodosiou & Morgan, 2007), indirectly related to
outcome performance (Babakus et al., 1996; Baldauf, Cravens, & Grant, 2002; Longino,
2007; Theodosiou & Katsikea, 2007), and directly related to outcome performance
(Piercy et al., 1999; Piercy, Cravens, & Lane, 2009, 2012) In a study of sales managers
in a combination of business-to-business and business-to-consumer sales, Baldauf et al.
(2001) found a significant and positive relationship between behavior-based management
control and salesperson behavior performance, but not salesperson outcome performance.
The researchers used only a subset of the Babakus et al. (1996) scale items in their study.
40
Katsikea et al. (2007) studied export sales managers in business-to-business sales
organizations and found that behavior-based management control was unrelated to either
sales person behavior performance or outcome performance. This study by Katsikea et al.
included only a subset of the Babakus et al. management control scale. In a related study
of export sales managers, Theodosiou and Katsikea (2007) found a significant and
positive relationship between behavior-based management control and salesperson
behavior performance, and between salesperson behavior performance and salesperson
outcome performance. The study by Theodosiou and Katsikea included the full scale of
the Babakus et al. measurement scale which could be a factor in the difference between
this study and the findings of Katsikea et al. (2007). Menguc and Tansu Barker (2003)
also identified an indirect relationship between behavior-based management control and
salesperson volume via complexity of the customer’s purchase decision. At high levels of
purchase complexity, the relationship between behavior-based management control and
sales volume was positive and significant. Longino (2007) replicated these findings in his
study of salespeople in business-to-business sales and found a positive and significant
relationship between behavior-based management control and salesperson behavior
performance, and between salesperson behavior performance and salesperson outcome
performance.
In two separate studies of sales managers in business-to-business sales
organizations, Piercy, Cravens, and Morgan (1997, 1998) found that when behavior-
based management control was present, sellers had high levels of both behavior and
outcome performance. Although both conditions of high behavior control and high
salesperson performance were present, the researchers did not identify a causal
41
relationship between the constructs (Piercy et al., 1997, 1998). These findings were
similar to a study by Grant and Cravens (1996) in which the researchers divided the
sellers into low and high performing groups on measures of behavior and outcome
performance. The high behavior performance group also had higher outcome
performance than the low behavior performance group (Grant & Cravens, 1996). In a
study of sales managers in business-to-business sales, Piercy, et al. (1999) found that the
behavior-based management control elements of directing, evaluating, and rewarding
showed significant positive effects on salesperson behavior performance, and between
salesperson behavior performance and outcome performance. This study was different
from the prior two studies (Piercy et al., 1997, 1998) in that the Piercy et al. (1999) also
identified a significant and positive direct effect of behavior-based management control
on salesperson outcome performance.
In addition to the direct and indirect effects of sales management control on
salesperson performance, Piercy, Cravens and Lane (2001) examined gender differences
relative to sales management control and the consequences in salesperson outcomes.
Piercy et al. found that female sales managers employed higher levels of behavior-based
management control than their male counterparts, but no differences in outcome
performance were identified based on gender. In a separate study, Piercy, Cravens, and
Lane (2003) found that teams led by female sales managers had a lower propensity to
leave compared to teams led by male sales managers; however, the teams led by female
manages had lower outcome performance than teams led by male sales managers. This
finding conflicted with Piercy et al.’s (2001) findings that indicated no difference in
outcome performance between teams led by male or female managers. One possible
42
reason for the difference in findings may be due to the populations studied. The study by
Piercy et al. (2001) involved a salesperson sample and the study by Piercy et al. (2003)
involved a sales management sample. Both studies used a subset of the management
control scales developed by Babakus et al. (1996).
Piercy and associates conducted two separate studies examining the relationship
between sales management control and salesperson performance (Piercy et al., 2009,
2012). Both studies (Piercy et al., 2009, 2012) included sales managers from business-to-
business sales organizations and employed the full measurement scale developed by
Babakus et al. (1996). The authors of these two studies expanded the scope of the
relationship between behavior-based management control and salesperson performance
by examining not only the degree to which managers employed management control
strategies, but also in the manager’s perception of their effectiveness in implementing
these strategies (Piercy et al., 2009, 2012). Piercy et al. (2009, 2012) found a significant
positive relationship between behavior-based management control and salesperson
behavior and outcome performance. The direct effect of behavior-based management
control on both salesperson behavior and outcome performance were consistent with the
findings of Piercy, Cravens, and Morgan (1997, 1999); however, the outcome of these
later studies (Piercy et al., 2009, 2012) included evidence of a causal relationship. The
measure of salesperson performance in the Piercy et al. (2009, 2012) studies was a
combined measure that included both behavior and outcome performance in one
measurement scale, which may have contributed to the finding of a direct relationship
between behavior-based management control and salesperson performance.
43
Although the majority of studies using the Babakus et al. (1996) measurement
scales involved the relationship between behavior-based management control and
salesperson performance, other studies addressed sales situation characteristics other than
performance outcomes (Krafft, 1999). In a study of chief executive officers from a
combination of business-to-business and business-to-consumer sales organizations, Krafft
(1999) examined the relationship between uncertainty and the use of behavior-based
management control. Krafft used number of accounts as a proxy for level of uncertainty
and claimed that a high number of accounts equated to a low level of uncertainty. Krafft
found that uncertainty (low number of accounts) had a positive and significant effect on
the use of behavior control. Krafft did not examine the relationship between behavior-
based management control and salesperson performance. In summary, researchers have
employed a variety of different measurement scales (Babakus et al., 1996; Cravens et al.,
1993; Oliver & Anderson, 1994; Robertson & Anderson, 1993) to examine the
relationship between behavior-based management control and salesperson performance to
test the propositions put forth by Anderson and Oliver (1987). Studies included sales
managers (Baldauf & Cravens, 1999; Matuso, 2009), salespeople (Piercy et al., 2003),
and chief executive officers (Babakus et al., 1996). The varied findings related to the
Anderson and Oliver (1987) conceptualization of management control and associated
sales performance may be due to the diversity of measurement scales used as well as the
populations studied.
Jaworski
Jaworski (1988) introduced a theory of management control that includes
environmental context, controls, and consequences. Environmental context describes the
44
general situational circumstances of the marketing unit. According to Jaworski, these
environmental variables influence the types of controls that are emphasized and moderate
the relationships between control types and psychological, behavioral, or performance
outcomes. Environmental context is divided into three primary areas: the macro
environment, the operating environment, and the internal environment. The macro
environment is the national and global context of social, political, and economic
conditions (Jaworski, 1988). The operating environment is the set of suppliers,
customers, and other groups with which the firm deals directly. The internal environment
consists of elements controlled within the firm (Jaworski, 1988).
Jaworski (1988) identified formal and informal controls as two broad classes used
within organizations. Formal controls are written, management-initiated mechanisms that
increase the probability that marketing employees will behave in ways that support stated
marketing objectives (Jaworski, 1988). Formal controls are divided into three control
mechanisms, distinguishable based on the timing of a manager’s intervention (Jaworski,
1988). Input control is defined as a measurable action taken by a firm prior to the
implementation of an activity (Jaworski, 1988). Typical input controls include selection
criteria, training programs, and marketing plans (Jaworski, 1988). Process control focuses
on the behavior used rather than end results (Jaworski, 1988). Standard operating
procedure within a firm is an example of process control (Jaworski, 1988). In a situation
of complete process control, a salesperson may be asked to follow specific procedures for
new account acquisition, but will not be held accountable for the extent of new business
development (Jaworski, 1988). Output controls are performance standards that are
measured as end results, such as quota or revenue targets (Jaworski, 1988). In a situation
45
of complete output control, an organization does not need to know means-ends
relationships and delegates this knowledge to the salesperson (Jaworski, 1988). For
example, a case of complete output control would occur when a manager notifies a seller
to improve sales volume without specifying the process to accomplish the increase in
volume (Jaworski, 1988). Informal controls are divided into three types based on level of
aggregation of the control such as self, small group, or large social units (Jaworski,
1988).
Jaworski’s (1988) conceptualization of formal process and output control is
relatively similar to Anderson and Oliver’s (1987) conceptualization of behavior and
outcome-based control systems. Jaworski and Anderson and Oliver proposed that process
control (as in the case of Jaworski) and behavior-based control (in the case of Anderson
and Oliverare unmeasurable, if not difficult to measure. The use of both process controls
(Jaworski) and behavior-based controls (Anderson & Oliver) rely on the assessment of
the sales supervisor, which requires control over his or her biases.
Jaworksi (1988) proposed that when a connection exists between the
environmental context and the control system in use, managerial performance will be
higher than it would be in a non-fit situation. Jaworski suggested that for more highly
programmable tasks, a formal control system is most effective. Conversely, for more
variable, less programmable tasks, an informal system is most effective (Jaworski, 1988).
Jaworski’s conceptualization of formal control as input, process, and output control can
be aligned to some degree to behavior and outcome control suggested by Ouchi (1979)
and Anderson and Oliver (1987). Jaworski’s concept of process control is conceptually
similar to Ouchi and Anderson and Oliver’s concept of behavior control. Output control
46
is similarly defined by Jaworksi, Ouchi , and Anderson and Oliver as the setting of
performance standards.
Jaworski Empirical Studies
The most commonly used scales used to measure sales management control
within the Jaworski (1988) framework were developed by Jaworksi and MacInnis (1989).
These measurement scales include items to measure output control, process control,
professional control, and cultural control (Jaworski & MacInnis, 1989). The most widely
used of the four scales were those designed to measure output and process control
(Baldauf, et al., 2005). The output control scale consists of five items that measure the
extent to which managers focuses on end results (Jaworski & MacInnis, 1989). The
process control scale consists of four items that measure the degree to which managers
focus on the procedures employees follow to achieve end results (Jaworski & MacInnis,
1989). Because the majority of the studies aligned to the Jaworski (1988)
conceptualization use the measurement scales developed by Jaworski and MacInnis
(1989), I have chosen to organize the review of these studies by both the nature of the
constructs examined and the types of populations studied. The first group of studies
involve the relationship between sales management control and consequences other than
salesperson performance.
Empirical studies unrelated to sales performance. Jaworksi and MacInnis
(1989) conducted a study of senior marketing executives to determine the degree to
which marketing personnel task characteristics impacted the use of output and process
controls, as well as the impact controls had on job tension and information asymmetry.
This was the first study that aligned with the Jaworski (1988) conceptualization. In this
47
study, Jaworski and MacInnis (1989) developed and validated the scales used in the
majority of studies reviewed in this section.
Jaworski and MacInnis (1989) examined the degree of procedural knowledge and
process documentation within an organization. Procedural knowledge relates to the
knowledge of the transformation process (Eisenhardt, 1985) as well as knowledge of
means-ends relationships (Ouchi, 1979), both key elements of organization theory.
Jaworski and MacInnis found a significant positive relationship between procedural
knowledge and the use of process controls. Procedural knowledge was unrelated to
output controls (Jaworski & MacInnis, 1989). This finding supports Ouchi’s (1979)
proposition that organizations must have knowledge of means-ends relationships to
control the behavior of marketing employees. Performance documentation represents the
degree to which marketing leaders have available forms of documentation to assess a
marketing employee’s performance (Ouchi, 1979). Jaworski and MacInnis found that
performance documentation was positively and significantly related to the use of output
controls. Both output and process controls significantly reduced information asymmetry
(Jaworski & MacInnis, 1989). Information asymmetry occurs when employees have
information that supervisors do not, which may be used opportunistically (Williams,
1975).
The findings of the Jaworski and MacInnis (1989) study were in direct contrast
with the findings of Ramaswami (1996). In a study of various marketing personnel
(product managers and marketing research analysts) and sales personnel (sales people
and sales managers), Ramaswami examined the degree to which the task characteristics
of procedural knowledge and performance documentation impacted the relationship
48
between process and output controls and dysfunctional employee behaviors. Contrary to
the findings of Jaworksi and MacInnis, Ramaswami found that output and process
controls significantly increased dysfunctional behavior: Output controls contributed to
falsification of information and process controls contributed to reduced feelings of
autonomy and increased defensiveness. The existence of performance documentation did
not reduce the effect of output controls on dysfunctional behavior; however, the use of
process controls was associated with reduced dysfunctional behavior when procedural
knowledge was high versus when it was low (Ramaswami, 1996). In a separate study,
Agarwal (1999) examined the impact of job formalization and administrative controls on
the attitudes of business-to-business salespeople. Agarwal examined the degree to which
process and output controls moderated the relationships between job formalization, role
ambiguity, and organizational commitment. Job formalization was defined as the level of
job codification and rule observation and role ambiguity was defined as the degree of
uncertainty about one’s job. Agarwal found a significant relationship between
formalization, increased role ambiguity, and reduced organizational commitment. Output
control moderated the impact of formalization, reducing the negative impact of
formalization on role ambiguity and organizational commitment. Agarwal’s findings
about the moderating influence of output control on dysfunctional behavior were in
contrast with Ramawami’s (1996) finding that process controls, rather than output
controls reduced dysfunctional behaviors in conditions of high procedural knowledge.
Formalization is a similar construct to procedural knowledge and involves knowledge of
means-ends relationships (Ouchi, 1979). The relationship between management controls
and dysfunctional behavior was examined again by Ramawami (2002). Similar to the
49
findings of Agarwal (1999), Ramaswami found that output control was associated with
reduced role ambiguity. Similar to the findings of Jaworksi and MacInnis (1989),
Ramaswami found that availability of performance documentation was associated with
output control, and output control reduced information asymmetry. Output control was
also associated with increased opportunistic behavior, providing further evidence of
Ramaswami’s (1996) earlier findings regarding the link between output control and
falsification of information.
Although the above studies included similar constructs and measures of
management control (Jaworksi & MacInnis, 1989), the population’s studied were quite
different (marketing executives, marketing analysts, sales people, sales managers). This
variation in populations studied may have contributed to ambiguity in findings regarding
the relationship of management control, task characteristics, and dysfunctional behavior.
Empirical studies related to job performance in business-to-consumer sales.
The sales environment and associated sales tasks are markedly different between
business-to-business industrial selling and business-to-consumer retail selling
(Challagalla & Shervani, 1996). This first set of empirical studies that linked
management control to sales performance involved a business-to-consumer sales
environment. Of the three studies conducted in the business-to-consumer environment,
one study resulted in an indirect effect of sales management control on salesperson
performance (Joshi & Randall, 2001), one study resulted in a direct effect (Jaworski &
Kohli, 1991), and one study resulted in no effect (Lusch & Jaworski, 1991). The
measurement scales of salesperson performance in the studies with indirect (Joshi &
Randall) and direct effects (Jaworski & Kohli) of management control on salesperson
50
performance were developed by Behrman and Perreault (1982). The study that resulted in
no effect of management control on performance involved items unrelated to output, but
more closely aligned to behavior performance (Lusch & Jaworski). In addition to the
differences in measurement scales, the researchers studied different populations. In the
two studies that addressed the relationship between management control and seller
performance (Jaworski & Kohli, 1991; Joshi & Randall, 2001), the researchers studied
business-to-consumer salespeople. In the one study where no effect between management
control and performance was found, the researchers studied store managers (Lusch &
Jaworski).
Jaworski and Kohli (1991) conducted a study of retail automobile salespeople to
determine the degree to which output and process feedback and role clarity impacted both
satisfaction with supervisor and sales outcome performance. In this study, Jaworski and
Kohli reworded the original items developed by Jaworski and MacInnis (1989) to reflect
output and behavioral (process) feedback as both positive and negative. Positive output
feedback had a significant positive effect on salesperson outcome performance (Jaworksi
& Kohli, 1991). Positive output and behavioral feedback had a statistically significant
positive effect on satisfaction with supervisor (Jaworski & Kohli). Negative output and
behavioral feedback had no effect on either outcome performance or satisfaction with
supervisor. Behavioral feedback was motivational, positively impacting satisfaction with
supervisor, but did not impact seller performance. Joshi and Randall (1991) conducted a
study of independent salespeople in business-to-consumer cosmetic sales to examine the
relationships between process and output controls, task clarity, affective commitment,
customer orientation, and salesperson outcome performance. The measurement scales for
51
process and output control were developed by Jaworski and MacInnis (1989) and the
measure of salesperson outcome performance was developed by Behrman and Perreault
(1982). Both process and output controls had statistically significant and positive effects
on task clarity, although output control had the strongest effect (Joshi & Randall, 1991).
Task clarity was related statistically significantly and positively to salesperson outcome
performance, but unrelated to customer orientation. Both output and process controls had
a statistically significant and positive effect on affective commitment, and affective
commitment had a statistically significant and positive effect on both salesperson
outcome performance and customer orientation. This study provides directional evidence
for the Jaworksi and Kohli’s (1991) findings of a positive relationship between output
control and salesperson performance; however, in this study, Joshi and Randall also
found a positive indirect relationship between process control and salesperson outcome
performance via task clarity, which differed from the lack of relationship between
process control and salesperson outcome performance in the Jaworski and Kohli (1991)
study.
Lusch and Jaworski (2001) studied store managers in a business-to-consumer
retail setting to determine the relationship between management control, role stress, and
manager performance. Although the scales used to measure management control were
similar to those in the studies by Jaworski and Kohli (1999) and Joshi and Randall
(2001), the measure of performance was remarkably different. Lusch and Jaworksi used a
measure of store manager performance that more closely related to manager behavior
than to outcome performance. Lusch and Jaworksi found that output control did not
reduce role stress and role stress had a statistically significant negative effect on store
52
manager performance. Output control did not impact store manager performance, which
was contrary to expectations and contradictory to the findings of Jaworski and Kohli
(1991) who found a direct effect, and Joshi and Randall (1999) who found an indirect
effect. In summary, although the three studies reviewed all reflected a business-to-
consumer sales environment, the populations studied varied (managers, retail sellers,
independent sellers), and the instruments used to measure performance varied
(salesperson outcome performance, store manager behavior performance).
Empirical studies related to sales performance in business-to-business sales.
Although many empirical studies were conducted to examine the relationship between
sales management control and salesperson performance in the business-to-business sales
environment, researchers reported conflicting findings similar to studies conducted in the
business-to-consumer environment. Researchers identified direct relationships between
management control and salesperson performance (Bello & Gilliland, 1997; Cravens,
Lassk, Low, Marshall, & Moncrief, 2004; Flaherty et al., 2007; Jaworski,
Stathakopoulos, & Krishnan, 1993), indirect relationships between management control
and salesperson performance (Atuahene-Gima & Li, 2002), and a negative relationship
between management control and salesperson performance (Aulakh & Gencturk, 2000).
In a study of sales executives from United States companies with international
internal and external sales agents, Aulakh and Gencturk (2000) examined the
relationships between process and output controls, governance, agent compliance, and
agent economic performance. The scales used to measure process and output controls
were developed by Jaworksi and MacInnis (1989) and reworded to match the distributor
environment. Aulakh and Gencturk found a significant negative effect of output control
53
on agent compliance in cases of external governance as compared to internal governance.
The researchers identified a significant negative effect of output control on agent
economic performance for external agents, but not for internal agents. Aulakh and
Gencturk’s found a negative effect of output control on agent economic performance for
external agents, and lack of effect of output control on economic performance for internal
agents is in direct contrast to other studies (Bello & Gilliland, 1997; Joshi & Randall,
2001) whose authors identified a significant positive effect of output control on
salesperson outcome performance. Process control was unrelated to economic
performance for both internal and external agents, similar to the findings of Atuahene-
Gima and Li (2002).
In contrast to the negative effect of output control reported by Aulakh and
Gencturk (2000), Atuahene-Gima and Li (2002) found an indirect effect of output control
on salesperson performance via the relationship between product complexity and
employee trust in their study of salespeople in the United States and China. The
measurement scales Atuahene-Gima and Li used to measure process and output controls
were developed by Jaworski and MacInnis (1989) and the product complexity scale was
developed by Anderson (1995). Anderson’s product complexity scale measured product
sophistication, technical nature, and engineering content from the seller’s perspective.
Atuahene-Gima and Li found that output control was unrelated to supervisee trust for
either the United States or Chinese populations; however, the effect of process control on
supervisee trust was positive and significant for the Chinese sample only. Product
complexity had a positive and significant effect on supervisee trust for both samples.
Supervisee trust enhanced sales performance when output control was high in the
54
Chinese sample, but not in the United States sample, indicating an indirect relationship
between outcome control and salesperson performance for the Chinese sample. This
indirect positive relationship between output control and salesperson performance is in
direct contrast with the findings of Jaworksi et al., (1993) who found a significant and
positive direct effect of output control on salesperson performance.
In a study of marketing and sales executives, Jaworski, Stathakopoulos, and
Krishnan (1993) examined the relationship between sales management control, task
complexity, role ambiguity, person-role conflict, and job performance. It is important to
note that task complexity in this study (Jawroski et al., 1993) was defined as the extent of
predictability and variety in the activities to be performed by a given position within a
business unit. This conceptualization of task complexity was different than the measure
of task complexity developed by John and Weitz (1989) which measured the nature of the
purchase decision from the buyer’s perspective. The measure of performance Jaworski et
al.’s study reflected quality and completion of work, as compared to quantitative
salesperson outcomes reflected in the scale developed by Behrman and Perreault (1982).
Jaworksi et al. found that output control had a positive significant effect on job
satisfaction and process control had no effect on job satisfaction. Output control reduced
role ambiguity and person-role conflict, whereas process control increased person-role
conflict, and had no effect on role ambiguity. These findings regarding the negative
relationship between output control and both role ambiguity and person-role conflict are
consistent with the findings of Agarwal (1999) and Ramaswami (2002). Jaworksi et al.
found that output control had a statistically significant and positive effect on job
performance.
55
Bello and Gilliland (1997) reported a similar positive effect on output control on
performance; however, the measure of performance in their study included quantitative
measures of sales profit, growth, and achievement of economic goals. In their study of
manufacturing companies that exported products through foreign distributors, Bello and
Gilliland examined the relationships between product complexity, process and output
control, psychic distance, and channel sales performance. The scale used to measure
product complexity in this study was developed by Anderson (1995) and measured
product sophistication, technical nature, and engineering content from the seller’s
perspective, which differed from the scale developed by Slater and Olson (2000), which
measured the degree of difficulty a buyer may experience in understanding the seller’s
product. Bello and Gilliland found that the use of process control failed to influence
channel performance; however, output control had a positive and significant effect on
channel performance. This finding is similar to the positive relationship between output
control and job performance reported by Jaworski et al. (1993). Product complexity had a
significant positive effect on the use of process and output controls, whereas psychic
distance, due to cultural or language differences, significantly impeded the use of output
controls.
The positive relationship between output control and performance (Bello &
Gilliland, 1997) was consistent with the findings of Cravens, Lassk, Low, Marshall, and
Moncrief (2004) in their study of salespeople. Cravens et al. (2004) found a positive
significant effect of high management control on salesperson performance. A
complicating factor in the Cravens et al. study was the way in which they examined
management control. In their study, Cravens et al. used the Jaworksi and MacInnis
56
(1989) measurement scales; however, they evaluated process and output controls together
as either both high output and high process, or both low output and low process control.
For purposes of analysis, Cravens et al. did not separate process control and output
control as separate measures allowing them to vary in opposite directions. An additional
complication in comparing Craven et al.’s study to the Jaworski et al. (1993) study was
the measure of performance. In the original performance scale developed by Behrman
and Perreault (1982), salesperson outcome performance and other elements of
performance such as making sales presentations were separate scales. Cravens et al.
combined all of the Behrman and Perreault (1982) scales to produce a single performance
scale. The measure of salesperson outcome performance within the Behrman and
Perreault measurement scales used by Cravens et al. is similar to that quantitative
measure used by Bello and Gilliland (1999), providing further evidence of the positive
effect of management control on salesperson performance. Although directionally similar
to the findings of Jaworski et al. (1993) regarding the positive effect of controls on
performance, the measures of performance in the Cravens et al. study included
quantitative outcome measures, whereas the performance measures used by Jaworski et
al. (1993) were qualitative in nature.
Flaherty et al.(2007) replicated the findings of Jaworski et al. (1993), Bello and
Gilliland (1997), and Cravens et al (2004) regarding the positive effect of management
controls on salesperson outcome performance; however, the positive effect was not found
for all sales situations. In their study of salespeople, Flaherty et al. examined the
relationship between sales management control, product complexity, and sales
performance. Flaherty et al. divided their sales population into different clusters based on
57
situational characteristics of the sales positions. The approach to this study was unique
because the authors identified three clusters of sales situation elements and then
examined the relationship between sales management controls and sales performance
across the different clusters. Flaherty et al. used this clustering approach because they
proposed that no single set of sales activities were effective for all salespeople, therefore
no one type of control should be considered superior to another. The authors identified
three separate sales situational clusters representing different degrees of product
complexity. The sink or swim transactional cluster was characterized by low experience
and high product complexity, the tried but true relationship builder was characterized by
high experience and low product complexity, and the fixed but stable account manager
was characterized by moderate experience and moderate product complexity. Whereas
findings from other studies indicated a significant positive effect of output control on
salesperson performance (Bello & Gilliland, 1997; Cravens et al., 2004), Flaherty et al.
found this positive effect only for the sink or swim transactional cluster characterized by
high product complexity. Flaherty et al. found no significant correlation between output
control and sales performance for the tried but true relationship builders or the fixed but
stable account managers where product complexity was either low or moderate. Contrary
to prior studies where researchers found no relationship between process control and
sales performance (Bello & Gilliland, 1997), Flaherty et al. found a significant positive
effect of process control on sales performance for sellers in the sink or swim transactional
cluster characterized by high product complexity, as well as in the tried and true
relationship builder cluster characterized by low product complexity. This finding is hard
to interpret and may be due to situational factors other than product complexity not
58
examined in Flaherty et al.’s study. Neither output or process controls had a significant
effect on salesperson performance for the fixed but stable account managers
characterized by moderate product complexity. Both output and process controls had the
most significant effect on salesperson performance in the sink or swim transactional
cluster characterized by high product complexity.
Panagopoulos et al. (2015) replicated the statistically significant and positive
effect of output control on salesperson outcome performance in their study of sales
managers. The first part of their study involved an examination of the construct validity
of both the Oliver and Anderson (1994) management control scales and the Jaworski and
MacInnis (1989) management control scales. Several of the items from the Oliver and
Anderson (1994) scale were eliminated due to poor item properties and excluded from
the final analysis. Panagopoulos et al. compared the two scales and found the Oliver and
Anderson scale related equally well to both the process and output control scales of
Jaworski and MacInnis, making it difficult for the researchers to determine whether the
Oliver and Anderson scale was a measure of process or output control. A major finding
Panagopoulos et al. reported in this study was that the size and nature of the effect of
sales controls on salesperson performance differed depending upon the conceptualization
and associated scales used. For the Jaworski and MacInnis scales, the direct effect of
outcome control on sales performance was liner, statistically significant, and positive. In
contrast, Panagopoulus et al. found that the Oliver and Anderson index exerted a
significant negative direct effect on performance. Similar to the findings of Bello and
Gilliland (1997), process control (Jaworski & MacInnis, 1989) had no effect on
salesperson performance. This study and associated analyses by Panagopoulos et al. may
59
help explain some of the ambiguous results of prior studies of the management control-
sales performance relationship.
Challagalla and Shervani
Challagalla and Shervani (1996) cited conflicting evidence in the control research
regarding the impact of behavioral control on salesperson outcome performance due to a
restrictive perspective on the types of behavior controls used. Oliver and Anderson
(1994) found that behavior control was negatively related to end performance, and
Jaworskiet al. (1993) found behavioral control to be unrelated to end performance.
Because of these conflicting findings, Challagalla and Shervani disaggregated the global
construct of behavioral control into activity control and capability control. Challagalla
and Shervai defined activity control as the specification of the activities a salesperson is
expected to perform on a regular basis, and capability control as the development of
individual salesperson skills and abilities. Implementing activity control requires
supervisors to monitor salespeople frequently, and is therefore expected to increase
communication. Implementing capability control requires supervisors to commit time and
effort to assessing the capabilities of each salesperson to provide guidance for
improvement. Challagalla and Shervani suggested that activity and capability control
have different effects on salesperson performance. Challagalla and Shervani developed
measurement scales to identify the extent to which information was provided, rewards
were offered, and punishment was applied for capability, activity, and output controls.
Challagalla and Shervani’s scales included four items each for output information,
rewards, and punishments, five items for activity information, and three items each for
activity rewards and punishments, five items for capability information, and three items
60
each for capability rewards and punishments. The information component of each of the
control scales (output, activity, capability) were based on the management control scales
for output and process control developed by Jaworski and MacInnis (1989). All empirical
studies reviewed in the following section include the information elements only of the
Challagalla and Shervani scales for output, capability, and activity control.
Empirical studies related to sales performance. Empirical studies of the
relationship between sales management control and salesperson performance using the
scales developed by Challagalla and Shervani (1996) have resulted in a direct effect
(Evans et al., 2007; Miao, Evans, & Shaoming, 2007), indirect effect (Challagalla &
Shervani, 1996; Fang, Evans, & Zou, 2005; Kohli, Shervani, & Challagalla, 1998), and
no effect (Challagalla, Shervani, & Huber, 2000). In addition to the sales management
control-salesperson performance relationship, researchers have also studied the
relationship between sales management control and dysfunctional behaviors (Choi,
Dixon, & Jung, 2004; Wang, Dou, & Zhou, 2012).
In a study of salespeople in business-to-business sales, Evans et al., (2007)
examined the mediating effects of customer orientation, sales supportiveness, and
innovation on the management control-sales performance relationship. The scales used to
measure output and process control were developed by Jaworski and MacInnis (1989).
The process control items in this study were 4 of the 5 items used by Challagalla and
Shervani (1996) to measure activity control. The capability control items were developed
by Challagalla and Shervani (1996). The scale used to measure salesperson outcome
performance was developed by Behrman and Perreault (1982).
61
Evans et al. (2007) found a positive significant relationship between output
control and salesperson outcome performance. Outcome control had a positive significant
effect on sales supportiveness and sales innovation. Activity control had a positive and
significant effect on organizational customer orientation, but was unrelated to either sales
supportiveness or sales innovation. Capability control had positive significant effects on
customer orientation, sales supportiveness, and sales innovation. Sales innovativeness
and sales supportiveness both had positive and significant effects on job satisfaction,
supporting Evans et al.’s hypotheses regarding a mediating effect of sales innovativeness
and sales supportiveness on the capability control-satisfaction relationship and the
outcome control-satisfaction relationship. Organization customer orientation was
unrelated to either job satisfaction or performance, failing to support Evans et al.’s
hypothesis regarding a mediating role of organization customer orientation on the
control-performance, or control-satisfaction relationships. In summary, Evans et al. found
a significant positive relationship between outcome control and outcome performance,
similar to prior studies (Cravens, et al., 2004; Panagopoulos & Johnson, 2015), and an
indirect relationship between capability control and salesperson satisfaction via sales
innovativeness and sale supportiveness.
Miao, Evans, and Shaoming (2007) replicated the significant positive effect of
outcome control on salesperson performance in their study of salespeople in a
combination of business-to-business and business-to-consumer sales. Miao, et al. (2007)
examined the impact of salesperson motivation on the relationship between sales
management control and salesperson behavior and outcome performance. Outcome,
activity and capability control were measures using scales developed by Challagalla and
62
Shervani (1996). Salesperson behavior and outcome performance were measured using
scales developed by Cravens et al. (1993) and adapted from Behrman and Perreault
(1982).
Miao et al. (2007) found that outcome control had a significant positive impact on
outcome performance, capability control had a significant negative effect on outcome
performance, and activity control was unrelated to outcome performance. Miao et al.
identified a more complex relationship between activity control and outcome
performance via challenge seeking and behavior performance such that activity control
had a significant positive effect on challenge seeking, challenge seeking had a significant
positive effect on behavior performance, and behavior performance had a positive
significant effect on outcome performance. This finding by Miao et al. supports
Challagalla and Shervani’s (1996) assertion that the control-performance relationship is
complex and is impacted by intervening variables.
Challagalla and Shervani (1996) found an indirect relationship between sales
management control and salesperson performance via supervisor role ambiguity, which
was consistent with the findings of Miao et al. (2007). In their study of salespeople in a
business-to-business sales force, Challagalla and Shervani, examined the way outcome
control, activity control, and capability control impacted salesperson performance and
satisfaction. Challagalla and Shervani chose to study salespeople in a business-to-
business setting because they felt this environment was most likely to allow observation
of all three types of control. Challagalla and Shervani used the Jaworski and MacInnis
(1989) scale to measure outcome control, and adapted the Jaworksi and MacInnis process
control scale to mesure activity and capability control. As I indicated previously in this
63
literature review, this was the seminal study Challagalla and Shervani conducted to
develop and justify separate scales for activity and capability control versus a single
process control scale used in prior research (Jaworksi and MacInnis, 1989). Salesperson
performance was measured using the Sujan, Weitz, and Kumar (1994) scale, which was
an adaptation of the Behrman and Perreault (1982) sales objective achievement scale.
Challagalla and Shervani (1996) found that capability, activity, and outcome
control were negatively and significantly related to supervisor role ambiguity, as
expected. None of the control elements directly impacted salesperson performance, also
as expected, providing justification for Challagalla and Shervani’s assertion that
inconstant findings regarding the direct effect of controls on performance in prior
research studies were most likely due to the instruments used, as well as the likelihood
that many of the effects of controls on performance were indirect. Challagalla and
Shervani found that supervisor role ambiguity had a significant negative effect on
salesperson performance. This finding supported their hypothesis that management
control impacted salesperson performance indirectly through a reduction in supervisor
role ambiguity. Capability and activity control had a positive significant effect on
satisfaction with supervisor, and satisfaction with supervisor was positively and
significantly related to performance, providing further evidence of an indirect effect.
Challagalla and Shervani’s (1996) proposition regarding an indirect relationship
between sales management control and salesperson performance was supported in a study
by Kohli, Shevani, and Challagalla (1998). In their study of salespeople in business-to-
business sales, Kholi et al. (1998) examined the impact of supervisor behavior on
salespeople’s learning orientation and performance orientation. The three scales used to
64
measure sales management control in this study were developed by Challagalla and
Shervani and reflected outcome control, capability control, and activity control. As I
pointed out earlier in this chapter, a primary difference between the Challagalla and
Shervani scales and those developed by Jawoski and MacInnis (1989) was the separation
of process (behavior) control into two sub-scales: activity control, and capability control.
The scale used to measure salesperson performance was developed by Sujan et al. (1994),
similar to Cravens et al. (1993), and adapted from Behrman and Perreault (1982), all
reflective of achievement of sales objective results.
Both outcome and capability control significantly and positively impacted
salespeople’s learning orientation (Kohli et al., 1998). Activity orientation was unrelated
to learning orientation. Outcome and activity control positively and statistically
significantly influenced salesperson performance orientation; however, capability control
was unrelated to salesperson performance orientation. These findings are in-line with
Challagalla and Shervani’s (1996) proposition that capability control and activity control
have different impacts on seller behavior and should be measured separately, providing
empirical justification for disaggregating process (behavior) control into two separate
constructs.
Ultimately, Kohli et al. (1998) were interested in the relationship between seller
orientation and performance. Kohli et al. found that salesperson performance orientation
was significantly and positively related to salesperson performance. Learning orientation
was unrelated to salesperson performance. Kohli et al. also examined the moderating
effects of experience on the above relationships. They found experience moderated the
relationship between outcome control and learning orientation such that for more
65
experienced sellers, outcome control increased learning orientation, but was unrelated to
learning orientation for less-experienced sellers. Activity orientation was negatively and
statistically significantly related to learning orientation for more experienced sellers, but
unrelated to learning orientation for less-experienced sellers. Although activity control
had a positive and significant effect on performance orientation for all sellers, the effect
was stronger for sellers with more experience.
Fang, Evans, and Zou (2005) found evidence for an indirect effect of sales
management control on salesperson performance (Challagalla & Shervani, 1996; Kohli et
al., 1998) via goal-setting characteristics. In two separate studies, Fang, et al. examined
the degree to which goal setting characteristics moderated the relationship between sales
management control and salesperson performance. The first study involved salespeople
from a variety of industries representing both business-to-consumer and business-to-
business sales in the United States. The second study involved a similar population of
salespeople from China. Fang et al. used Challagalla and Shervani’s (1996) scales to
measure outcome, capability, and activity control, and Behrman and Perreault’s (1982)
scales to measure performance. Fang et al. examined the goal setting characteristics of
difficulty and specificity as moderators of the control-performance relationship as high,
moderate, or low.
In the first study, Fang et al. (2005) found that when goal difficulty was moderate,
outcome control had a significant and positive effect on salesperson outcome
performance. When goal specificity was high, the relationship between outcome control
and salesperson outcome performance was positive and significant. In the second study
involving the Chinese sample, Fang et al. found that the relationship between outcome
66
control and salesperson outcome performance was significant and positive only under
low goal specificity conditions, versus high goal specificity for the United States sample.
Goal setting characteristics failed to moderate the relationship between activity control or
capability control and salesperson outcome performance in either sample.
In a separate study of industrial salespeople, Challagalla, Shervani, and Huber
(2000) examined the degree to which salesperson work location impacted the relationship
between management control and salesperson consequences. Challagalla et al. used the
Challagalla and Shervani (1996) scales to measure management control and salesperson
performance, and the John and Weitz (1989) task complexity scale. Challagalla et al.
used task complexity, sales experience, and supervisor role ambiguity as control variables
in this study to isolate the effects of moderator relationships between controls and
salesperson consequences. Challagalla et al. examined salesperson location as the
primary moderator of the control – consequence relationship, identified as either co-
located with or remote from their sales supervisor.
Challagalla et al. (2000) found that outcome control was positively and
significantly related to satisfaction with supervisor co-located salespeople, but unrelated
to satisfaction with supervisor for remote salespeople, providing evidence for a
moderating effect of salesperson location. Activity control was negatively and
statistically significantly related to satisfaction with supervisor for co-located salespeople,
but significantly and positively related to satisfaction with supervisor for remote
salespeople, providing additional evidence for the moderating effect of location.
Capability orientation was significantly and positively related to satisfaction for both
remote and co-located sellers, indicating that salesperson satisfaction increased when
67
they viewed their supervisors as coaches. Capability orientation was positively related to
performance for co-located salespeople, but unrelated to performance for remote
salespeople.
Challagalla et al. (2000) found that outcome control was unrelated to salesperson
performance for either remote or co-located salespeople. This finding was consistent with
prior studies in which researchers failed to find a relationship between outcome control
and performance (Atuahene-Gima & Li, 2002). However, Challagalla et al.’s findings
were in contrast to prior studies showing a positive relationship between outcome control
and performance (Cravens, et al., 2004; Panagopoulos & Johnson, 2015), and others
showing a negative relationship between outcome control and performance (Aulakh, &
Gencturk, 2000). None of the three studies, Atuahene-Gima and Li (2002), Cravens et al.
(2004), or Panagopoulos and Johnson (2015) addressed potential moderators of the
control-performance relationship. In Challagalla et al.’s study, task complexity,
experience, and role ambiguity failed to significantly influence the control-performance
relationship differently for co-located versus remote salespeople, in contrast to the
findings of Kohli et al. (1998) who found a moderating effect of salesperson experience.
Empirical studies unrelated to sales performance. In a study of business-to-
business salespeople, Choi, Dixon, and Jung (2004) examined the relationships between
sales management control, supervisee trust, and dysfunctional seller behavior. The scales
used Challagalla and Shervani’s (1996) scales to measure output, activity, and capability
controls. Choi et al. used the Jaworski and MacInnis (1989) scales to measure the
dependent variable, dysfunctional behavior. The term dysfunctional behavior in Choi et
68
al.’s study is synonymous with opportunistic behavior in other studies using the same
measure (Ramaswami, 2002).
Cho et al. (2004) found a significant negative relationship between output control
and dysfunctional seller behavior. This was in direct conflict with the findings of
Ramaswami (1996) that output control increased dysfunctional behavior. The conflicting
findings between these two studies could stem from the populations studied. Ramaswami
studied a widely varied sample of mostly marketing personnel, as compared to Choi, et
al.’s study of salespeople. Consistent with Ramaswami, Choi, et al. found that activity
control significantly increased dysfunctional behavior. Capability control was unrelated
to dysfunctional behavior; however, it was positively and significantly related to trust in
supervisors. Choi et al. found that because trust in supervisors reduced dysfunctional
behaviors, capability control mediated the relationship between trust and dysfunctional
behaviors.
In a study of industrial salespeople and their customers, Wang, Dou, and Zhou
(2012) examined the impact of sales management controls on salesperson behavior and
the associated customer experience. They used the Challagalla and Shervani (1996)
scales to measure activity and capability controls; however, the scale items for capability
control were adapted and reworded to reflect focus on seller skills relative to customer
relationships. Wang et al. used a combination of the Jaworksi and MacInnis (1989) scales
and Oliver and Anderson (1994) scales to measure outcome control. This was the only
study included in this literature review that combined items from the Jaworski and
MacInnis (1989) and Oliver and Anderson (1994) scales to measure outcome control.
This is particularly interesting because Jaworski and MacInnis conception of outcome
69
control was that it was a completely separate construct from behavior (process) control.
Oliver and Anderson based their instrument on the propositions put forth by Anderson
and Oliver (1987) that behavior (process) and outcome control are separate ends of the
control spectrum, not separate constructs. This variation in measurement instrument
could render the relationship between outcome control, seller behavior, and customer
experience difficult to compare to other studies.
Wang et al. (2012) used Raman and Ruiz (2005) scales to measure opportunism
assessed a buyer’s perception of the degree to which a salesperson intentionally misleads
a customer or applies pressure to a customer during sales interactions. This measure is
related, but not identical to Jaworksi and MacInnis’ (1989) measure of dysfunctional
behavior which focused on seller propensity to falsify internal information and reporting.
Wang, et al. (2012) found that output and capability control work together
synergistically so that high levels of both reduce opportunism; however, the effect of
capability control was only positive when used along with high levels of output control.
Activity control and capability control had a counteracting effect on opportunism such
that the effect of capability control on opportunism was positive when activity control
was strong, but negative when activity control was weak. The relationship between
activity control and opportunism was negative when capability control was weak, but
positive when capability control was strong. The level of opportunism when both controls
were high was similar to the level of opportunism when both controls were low, therefore
both controls reduced opportunism when used alone, but cancelled out each other’s
positive effect when used together. Wang et al.’s finding provides further support for
Challagalla and Shervani’s (1996) proposition that process control as defined by Jaworski
70
and MacInnis (1989) was too blunt of an instrument and needed to be disaggregated into
activity control and capability control.
Wang et al. (2012) found that output and capability controls had positive and
significant effects on customer relationship satisfaction. The researchers found no direct
effect for capability control and customer relationship satisfaction. In summary, Wang, et
al. found that activity and capability control have very different implications for
motivating salespeople to engage in customer-oriented sales behaviors. The significant
interaction effects between outcome, activity, and capability controls with seller
opportunism and associated customer satisfaction in Wang et al.’s study provided
evidence that main effects of controls in prior studies (Bello & Gilliland, 1997; Jaworski
& Kholi, 1991; Jaworski, Stathakopoulos, & Krishnan, 1993; Piercy, Cravens, & Lane,
2009, 2012; ) may be misleading (Challagalla & Shervani, 1996).
Literature Analysis and Study Justification
Because many of the studies I included in this literature review did not relate
directly to the specific relationship between sales management control, product
complexity, task complexity, number of accounts, and the associated impact on
salesperson performance, I chose to compare and contrast the few highly relevant studies
to highlight the gap in the extant literature. Table 1 shows all published studies that
investigated the relationship between sales management control, product complexity and
task complexity, and the impact on salesperson performance. The table is ordered by
author names and highlights studies that have been conducted with sales populations
within business-to-business sales organizations.
71
Table 1
Previous Studies on the Relationship Between Sales Management Control, Product
Complexity, Task Complexity, and Number of Accounts on Salesperson Performance.
Author
/ Date
Population
Studied/Type
of Sale
Constructs
Examined
Instruments Used Direct Effect Indirect Effect
Atuahene-
Gima and
Li (2002)
Sales people
Business-to-
business sales
Process
control
Outcome
control
Product
complexity
(as control
variable)
Supervisee
trust
Salesperson
outcome
performance
Jaworski and
MacInnis (1989)
for process and
output control
Sujan, Weitz,
and Kumar
(1994) for
salesperson
outcome
performance
Anderson
(1995) scale for
product
complexity
Product
complexity
had a
statistically
significant
and positive
effect on
supervisee
trust
No direct
effect of
output and
process
control on
sales
performance
was tested.
Supervisee trust
did not lead to
sales performance
in either sample
(in this case,
product
complexity did
not moderate the
relationship
between controls
and performance)
Bello and
Gilliliand
(1997)
Sales
managers
Industrial and
consumer
sales
Output
control
Process
control
Product
complexity
Jaworski and
MacInnis (1989)
for process and
output control
Madsen (1987)
for salesperson
channel
performance
Anderson
(1995) scale for
product
complexity
Process
control failed
to influence
channel sales
performance
Output
control
statistically
significantly
and positively
influenced
channel sales
performance
Product
complexity
statistically
significantly and
positively
increased the use
of process and
output control
with foreign
distributors
(mediating role)
Flahterty,
Arnold,
and Hunt
(2007)
Salespeople in
business-to-
business sales
Output
control
Process
control
Product
complexity
Jaworski and
MacInnis (1989)
for Output and
process control
Sujan, Weitz, &
Kumar (1994)
for Salesperson
performance
Slater and Olson
(2000) for
product
complexity
None tested.
Sales role
characteristics
were
combined
into three
separate
clusters and
not tested
separately
Process control
had statistically
significant
positive effect on
performance
within the
clusters, with low
product
complexity
Output control
had a statistically
significant
positive impact
sales performance
for reps within the
cluster with high
product
complexity
Menguc
and
Barker
(2003)
Sales
managers
Business-to-
business
sales
organizations
Behavior-
based
management
control
Purchase
complexity
Monitoring
element of
Babakus et al.
(1996) scale for
behavior-based
management
control
When purchase
complexity (task
complexity) was
high, incentive
pay (outcome
control) was
positively related
to sales volume.
72
(task
complexity)
Sales
volume
Customer
satisfaction
Profitability
Complexity of
customer
purchase
decision (John
& Weitz, 1989)
High levels of
purchase (task)
complexity was
positively related
to sales volume,
but not
profitability.
Of the four studies summarized in Table 1, none included the behavior-based
control elements of activity and capability control (Challagalla & Shervani, 1996). In
addition, no single study included task complexity and product complexity within the
same study. None of the studies examined number of accounts as an independent
variable. Thus, one limitation of the extant literature is the lack of examination of the
relationships between capability and activity control, and the salesperson role
characteristics of task complexity, product complexity, and number of accounts in the
same study. The populations studied were notably different. Sales people in business to
business sales were examined (Atuahene-Gima & Li, 2002; Flaherty et al., 2007), sales
managers in business-to-business sales (Menguc & Tansu Barker, 2003), and sales
managers in a mix of business-to-business and business-to-consumer sales (Bello and
Gilliland, 1997). It is reasonable to suspect that managers and salespeople might have
different perspectives regarding management control strategies in effect. It is also
relevant to point out that business-to-consumer sales tend to be less complex than
business-to-business sales leading to a variation in the levels of the sales role constructs
of task and product complexity. Results obtained in a pure business-to-business sample
(Atuahene-Gima & Li, 2002; Flahterty et al., 2007; Menguc & Tansu Barker, 2003) may
not be directly comparable results of a study using a mixed population of business-to-
business and business-to-consumer sample (Bello & Gilliliand, 1997).
73
Variation in the conceptualizations of management control and the instruments
used to measure the control constructs within the four studies were also notably different.
Three studies (Atuahene-Gima & Li, 2002; Bello and Gilliliand; 1997; Flahterty et al.,
2007) used the Jaworski (1988) conceptualizations of output and process control as
separate constructs, and the associated measurement scales developed by Jaworksi and
MacInnis (1989). The Jaworski and MacInnis (1989) conceptualization and scales
measure output and process control as separate constructs and can therefore provide a
measure for the independent effects of each control type on salesperson outcome
performance. The moderating effects of task and product complexity and number of
accounts can also be tested separately. The Menguc and Tansu Barker (2003) study used
the Anderson and Oliver (1987) conceptualization of behavior-based versus outcome-
based management control, and the associated scales developed by Babakus et al. (1996)
to measure the constructs. The Anderson and Oliver (1987) conceptualization considers
behavior-based and outcome-based controls as separate ends of a single spectrum of
control. The effects of outcome and process control on salesperson outcome performance
cannot be tested separately using the scales developed by Babakus et al. (1996). Nor can
the moderating effects of task and product complexity or number of accounts be
examined. To overcome this limitation, I used the conceptualizations and associated
scales developed by Challagalla and Shervani (1996) to examine direct effects of activity
and capability controls, and the moderating effects of task complexity, product
complexity, and number of accounts on salesperson outcome performance.
The conceptualizations and instruments used to examine product complexity also
differed. Two studies (Atuahene-Gima & Li, 2002; Bello & Gilliland, 1997) used a scale
74
developed by Anderson (1995) to measure product complexity. Anderson’s
conceptualization of product complexity concerned the technical attributes of the product.
If inherent product technical complexity is of interest, such as cases of computer
hardware or software products, this measure would be useful. Flaherty et al. (2007)
examined product complexity using the scale developed by Slater and Olson (2000)
concerning the nature of the product being sold from the seller’s perspective. This scale
would be most useful when evaluating seller perspective as an indicator of difficulty of
the sales effort. Menguc and Tansu Barker (2003) examined purchase complexity using
the scale developed by John and Weitz (1989) concerning the complexity of the
purchasing task from the customer’s perspective. This scale would be of interest in
studies concerning buying patterns and associated buyer behavior. Although all
measurements are tangentially tied to the sales process, each measure has a unique focus
that would allow researchers to study specific attributes of product complexity.
In addition to variation in conceptualizations and measurements of product and
task complexity, the results of the studies were difficult to compare. Atuahene-Gima and
Li (2002) found that product complexity did not moderate the relationship between
controls and performance. Bello and Gilliland (1997) found that product complexity
statistically significantly increased the use of process and output controls with foreign
distributors, providing a mediating role. Flaherty et al. (2007) found that product
complexity moderated the relationship between process and output controls on
salesperson performance such that process control had a significant positive impact on
salesperson performance when product complexity was low, and output control had a
75
positive and significant impact on salesperson performance when product complexity was
high.
Multiple researchers examined the number of accounts associated with a specific
sales assignment (Menguc & Barker, 2003; Moncrief et al.,2006); however, the
researchers did not examine the relationship between number of accounts and salesperson
performance. According to Menguc and Tansu Barker (2003), when sellers are assigned a
large number of accounts, they are more likely to focus on high-volume, low effort
transactions instead of sales that are more complex and take longer to close. Although
this hypothesis was not tested in Menguc and Tansu Barker’s study, it is of interest in my
study due to the potential impact that the number of accounts may have on seller effort.
Moncrief et al. (2006) identified number of accounts as a role characteristic that
contributed to taxonomy of six different sales positions; however, only the key account
manager position had an actual reference to number of accounts. Although Flaherty et
al.’s (2007) study of sales situations identified three separate clusters of sellers that reflect
a variety of organizational factors, number of accounts was not considered in the cluster
analysis.
In summary, inconsistencies exist regarding types of populations studied (sales
managers versus salespeople), nature of the sales context (business-to-business versus
business-to-consumer), conceptualizations of sales management control (Anderson &
Oliver, 1987; Jaworksi, 1988, Challagalla & Shervani, 1996), scales used to measure
management control (Babakus et al., 1996, Jaworski & MacInnis, 1989; Challagalla &
Shervani, 1996), scales used to measure product and task complexity (Anderson, 1995;
John & Weitz, 1989; Slater & Olson, 2000). An empirical study examining the direct
76
effects of activity, capability, and outcome control (Challagalla and Shervani, 1996) on
salesperson outcome performance (Behrman and Perreault, 1982) was needed. In
addition, an examination of the moderating effects of task complexity, product
complexity, and number of accounts on the relationship between activity, capability, and
outcome control on salesperson outcome performance was needed.
Summary
In this chapter, I presented an extensive examination of organization theory,
agency theory, and transaction cost analysis as a theoretical basis for the study of sales
management control. I presented three separate theories of sales management control,
including a variety of measurement instruments designed and validated to measure each
theoretical construct. Within each section I included relevant studies related to
salesperson performance and other consequences such as salesperson satisfaction and
customer commitment. I further examined the few core studies that included the
moderating variables of product complexity, task complexity, and number of accounts,
demonstrating a gap in the literature relative to the relationship of management control to
salesperson outcome performance and how that relationship is moderated by these
variables. My study was designed to test the relationship between management control
and salesperson outcome performance, and examine the moderating effect of task
complexity, product complexity, and number of accounts on this relationship. In chapter
3, I detail the research methods used test my hypotheses regarding the moderating effects
of task complexity, product complexity, and number of accounts on the relationship
between sales management control and salesperson outcome performance.
77
Chapter 3: Research Methodology
This quantitative study addressed the relationships between three types of sales
management control (outcome control, activity control, and capability control) and
salesperson outcome performance. This study also addressed whether task complexity,
product complexity, and number of accounts moderated the above relationships. This
chapter includes a discussion of the methodology of the study. The chapter also includes
a discussion of the research design, population, sampling and sampling procedures,
instrumentation, operational definitions of variables, data collection procedures and
recruitment of participants, data analysis plan, threats to validity, and ethical procedures.
The chapter concludes with a summary.
Research Design and Rationale
This study included a nonexperimental quantitative design. Quantitative methods
are used when the objective is to investigate the relationships between two or more
variables (Babbie, 2012) and when the study involves measuring variables quantitatively
and analyzing them using statistical analysis to address a research hypothesis (Mustafa,
2011). Quantitative studies on behavior and outcome-based management control
constructs within sales and marketing have been pervasive since 1975 (Jaworski &
MacInnis, 1989). Of particular interest has been the examination of task complexity,
product complexity, and number of accounts as moderators (Baron & Kenny, 1986) in
determining the influence of behavior and outcome-based sales management control on
salesperson performance. A qualitative approach was not appropriate for this study
because it involves the collection of nonnumerical and nonstatistical data (Denzin, 2012)
and cannot be used to determine the relationship between variables (Bryman, 2012).
78
Population
The target population consisted of salespeople in business-to-business sales.
There was no sales team size limitation, and there was no salesperson tenure requirement.
Distributor representatives who sell through channels were not included in this study, nor
were sellers of business-to-consumer sales such as real estate or retail sales. The research
was conducted with a discrete company sample of salespeople in the business-to-
business, direct sales environment. Clients and prospects of a sales management training
and consulting company provided the target list of participating companies. This training
and consulting company specializes in research targeting sales managers and develops
training aimed at improving salesperson productivity through effective sales
management. The participating client was in the security services business.
Sampling and Sampling Procedure
The required sample size for this study was calculated based on the three factors of
power, effect size, and level of significance. The minimum sample size for this study was
200 based on 15 predictor variables including interaction effects (Sloper, 2006). A two-
tailed, nondirectional hypothesis test was conducted employing the statistical test of
moderated regression with 15 predictors: the three factors of sales management control
(outcome control, activity control, and capability control), the three moderators (task
complexity, product complexity, and number of accounts on these relationships), and the
nine interaction terms of sales management control and the moderators to represent the
moderating effects. A Cohen medium effect size of 0.15, a power of 0.95, and a level of
significance of 0.05 were also used. A low effect size was used due to low effect sizes in
other studies. For example, Flaherty et al. (2007) found large effect sizes of Jaworski and
79
MacInnis (1989) output and process control scale on sales outcome performance (R2 =
.429 and R2 = .369) as well as low effect sizes (R2 = .025 and R2 = .113) in the same
study. The difference in effect sizes was attributed to variations in the sales situation
studied. In another study that addressed the effect of process and output control on
salesperson outcome performance using similar measures, Atuahene-Gima and Li (2002)
found low effect sizes (R2 = .10 and R2 = .15). In the current study, a minimum sample
size of 200 allowed the statistical analysis to reach 80% to reject the null hypotheses.
I conducted purposeful sampling to recruit the sample from clients of the sales
management training and consulting company. Purposeful sampling was used because of
the accessibility advantage, quick implementation, and low costs to sample the study
participants (see Coy, 2008). A purposeful sampling strategy was chosen because the
study participants were required to meet a specific set of inclusion criteria to be eligible
for participation in the study. The inclusion criteria included salespeople who directly
report to a sales manager in a business-to-business environment. There was no tenure
requirement for salespeople in this study. The nature of the sales environment was
business-to-business sales in security services. The salespeople were recruited by sending
them an invitation letter regarding participation in the study. I asked for help from the
leaders of the organization in recruiting the salespeople to participate in the study.
Procedures for Recruitment, Participation, and Data Collection
Salespeople in business-to-business sales were surveyed. At least 2,000
salespeople were recruited via e-mail. The participants were identified via a target list of
companies from clients and prospects of sales management training and consulting
80
company, of which I am a partner. The nature of the sales environment was business-to-
business sales in the security services industry.
Sales executives within the target organizations were asked to solicit input from
their salespeople to participate in the study. A description of the study was provided
along with a prospectus in the invitation letter. Once the company agreed to participate, a
sample e-mail was drafted and sent to all participating salespeople. There was a single
organizational contact who provided approval for the salespeople to participate in the
study. The sales leader granted permission for the salespeople to participate in the study,
informed the sales managers, and sent the link directly to the salespeople. The invitation
letter provided a detailed background of the research purpose and methodology. A unique
link was developed for the participating company to ensure confidentiality. All
appropriate permissions from the sales leader were secured prior to survey deployment
and participation.
The data collection procedure for this quantitative study was conducted online to
ensure participants had easy access to the survey. The survey was deployed via Fluid
Surveys. Fluid Surveys is a Web-based survey platform that provides an online method
for survey participation. The link to the survey was e-mailed to the sample of
respondents. On the website in which the survey was uploaded, there was an introductory
page that provided an explanation of the study, instructions on how to answer the survey
items, an informed consent form providing a promise of confidentiality, and the different
questionnaires.
The participating individuals provided a digital signature by clicking on a button
in the survey that indicated “I understand the purpose of the survey and I’m willing to
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participate.” The selection was inserted at the beginning of the survey and required an
affirmative response prior to advancing to the actual questions. Through this process,
gaining the informed consent for the individual participants was ensured. Clicking the
negative response button of “I am not willing to participate” concluded the survey.
Respondents were not allowed to answer the survey and test questionnaires if they did not
provide electronic consent for participation.
The surveys did not have a time limit. Although the minimum size of the data set
was 200 salespeople, data collection was not stopped at 200 responses; additional
samples were obtained that exceeded the minimum 200 samples in anticipation of
potentially missing data and response style bias. Of the total population of 4,000
salespeople, 374 survey responses were collected. The participants’ responses were
posted directly into my Fluid Surveys account via the Internet once they were submitted.
After the required number of responses was collected from the sample of
salespersons, the data were downloaded in an Excel sheet. The different study variables
were enumerated in the columns of the Excel sheet, and the rows included the response
data of the different participants. Codes were assigned to each respondent to maintain
confidentiality.
Instrumentation and Operational Definition of Variables
The data were collected through salespersons’ responses to a survey about their
sales manager’s level of outcome, capability, and activity control, as well as task
complexity, product complexity, and number of accounts. Salespeople also responded to
questions about their individual outcome performance. The survey questions appear in
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Appendix A. The following section addresses how each of the study variables was
measured and how they were operationalized for the analysis.
Sales Management Controls (Independent Variables)
Outcome control, capability control, and activity control were measured using the
same instrument developed by Jaworski and MacInnis (1989) and adapted by Challagalla
and Shervani (1996). Each scale was measured using 5 items. Each item was scored on a
5-point scale ranging from strongly disagree to strongly agree. The total number of points
for all questions was averaged to determine the overall level of control felt by the
individual salesperson for output, capability, and activity control. A higher score on this
scale indicated higher control. The output control questions asked about the sales volume
or market share. The capability control questions asked about selling skills/abilities (e.g.,
negotiation, communication, presentation, etc.). The activity control questions asked
about the salesperson’s activities (e.g., call rate, number of demos, customers to be
contacted, reports to turn in, and so on). The internal consistency reliability of the
responses in this study was evaluated by computing the Cronbach’s alpha. The 5-item
questionnaire measuring outcome control had a coefficient of 0.87, the 5-item
questionnaire measuring capability control had a coefficient of .90, and the 5-item
questionnaire measuring activity control had a coefficient of .89 (Challagalla & Shervani,
1996). All coefficients exceeded the 0.70 acceptable level of reliability. Convergent
validity was demonstrated because the path coefficients from latent constructs to their
corresponding manifest indicators were significant at the level of significance of 0.05.
Discriminant validity was demonstrated because the pair-wise comparison of the different
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outcome control facets showed that all the latent-trait correlations of the constructs were
significantly different from 1.
One important contributor to construct validity is the degree to which
relationships between constructs occur in the hypothesized direction. Challagalla and
Shervani (1996) proposed that sales management controls had indirect effects on seller
performance via other intervening variables. In their seminal study of sales management
control, Challagalla and Shervani found support that scores on their scales for output
control (b= -.14, p<.05), activity control (b= -.19, p<.01), and capability control (b= -.32,
p<.001) correlated with lower scores on measures of supervisor role ambiguity. Scores
for activity control (b= -.19, p<.01) and capability control (b= -.21, p<.01) correlated with
lower scores on measures for customer role ambiguity (Challagalla & Shervani, 1996).
Supervisor role ambiguity (b= -.18, p<.05) and customer role ambiguity (b= -.24, p<.01)
had significant negative direct effects on salesperson performance, supporting the
hypothesized indirect effect of output, capability, and activity controls on salesperson
performance (Challagalla & Shervani, 1996). In a separate study of sales management
control’s indirect effect on seller performance, Kohli, Shervani, and Challagalla (1998)
found support for their hypotheses that scores on scales measuring supervisory end-
results orientation (b=.28, p<.01) and capability orientation (b=.25, p<.05) were
significantly and positively related to scores on scales measuring salesperson learning
orientation. Scores on scales measuring performance orientation correlated positively and
significantly to scores on scales related to supervisory end-results orientation (b=.17,
p<.05) and scores on scales measuring activity orientation (b=.33, p<.01) in support of
associated hypotheses. Scores on scales measuring performance orientation were
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positively and significantly correlated to scales for salesperson performance (b=.25,
p<.01), supporting the indirect effect of end-result and activity orientation on salesperson
performance.
Task Complexity (Moderator Variable)
Task complexity was a potential moderating variable and concerns the nature of
the purchase decision from the buyer’s perspective (John & Weitz, 1989). Task
complexity was measured using a 5-item scale developed by John and Weitz (1989). All
scale items are reflected in Appendix A. Task complexity was measured using a 7-anchor
scale. These include 0%, 10%, 30%, 50%, 70%, 90%, and 100%. The total amount of
points for all five questions was averaged to determine the task complexity felt by the
individual salesperson. The internal consistency reliability of the responses for task
complexity in this study was evaluated by computing the Cronbach’s alpha. Cronbach’s
alpha coefficient was computed by John and Weitz (1989) and the 5-item questionnaire
measuring task complexity has a coefficient of 0.86 which exceeds the 0.70 acceptable
level of reliability. The measure of task complexity showed good reliability.
Product Complexity (Moderator Variable)
Product complexity concerns the nature of the product being sold from the seller’s
perspective (Slater & Olson, 2000). Product complexity was measured using a 2-item,
Likert scale developed by Slater and Olson (2000). All scale items are reflected in
Appendix A. This was measured using a 7-point scale from “strongly disagree” to
“strongly agree” to assess product complexity. The total amount of points for the two
questions was averaged to determine the product complexity felt by the individual
salesperson. The two items in the Slater and Olson (2000) questionnaire measuring
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product complexity had correlation between the items of 0.67.
Number of Accounts (Moderator Variable)
Number of accounts was measured with a single question that indicated how
many accounts for which the salesperson was responsible.
Salesperson Performance (Dependent Variable)
This construct is the dependent variable. Self-report salesperson performance was
measured using six questions. All items were scored on a 6-point scale ranging from
“strongly disagree” to “strongly agree.” All scale items are reflected in Appendix A. The
total amount of points for all questions was averaged to determine the overall
performance level. A higher score on this scale indicated better performance. This
instrument was developed by Behrman and Perreault (1982). The internal consistency
reliability of the responses in the salesperson performance in this study was evaluated by
computing the Cronbach’s alpha. Cronbach’s alpha coefficient was computed by
Behrman and Parreault (1982) and the 6-item questionnaire measuring sales performance
was over 0.75 which exceeds the 0.70 acceptable level of reliability. The measure of sales
performance showed excellent reliability. Test-retest reliability estimate had a value of
0.70 which indicate that it had acceptable test-retest reliability. Manager ratings of
salesperson performance correlated significantly (r = .36, p <.001) with the achieving
overall sales objectives. Achievement of sales objectives correlated significantly with
salesperson need for achievement (r = .25, p <001), providing evidence of concurrent
validity. Objective salesperson performance was measured as a percentage of quota
attainment.
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Demographic Variables
The demographic variables of age, sex, and years as a salesperson are considered as
extraneous variables. Age was measured using a single open-ended question in which
participants were asked to input their age. Age is a continuous variable measured by the
actual age of the salesperson. Sex was measured by using a categorical question with two
nominal levels (male or female) asking participants to indicate their gender. Years as a
sales person was measured using a single open-ended question in which participants were
asked to input the number of years of experience as a salesperson. It is a continuous
variable to determine their actual number of years as a salesperson.
Data Analysis
This study aimed to answer the following four questions:
Research Question 1: Are there relationships between the three types of sales
management control and salesperson outcome performance?
H01: Outcome control, capability control, and activity control are not related to
salesperson outcome performance.
Ha1: Outcome control, capability control, and activity control are positively
related to salesperson outcome performance.
Research Question 2: Does task complexity, product complexity, and number of
accounts in direct, business-to-business sales moderate the effects of outcome control on
salesperson outcome performance?
H02: Task complexity, product complexity, and number of accounts does not
moderate the relationship between outcome control and salesperson outcome
performance.
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Ha2: Task complexity, product complexity, and number of accounts moderates the
relationship between outcome control and salesperson outcome performance.
Research Question 3: Does task complexity, product complexity, and number of
accounts in direct, business-to-business sales moderate the effects of behavior-based
capability control on salesperson outcome performance?
H30: Task complexity, product complexity, and number of accounts does not
moderate the relationship between capability control and salesperson outcome
performance.
Ha3: Task complexity, product complexity, and number of accounts moderates the
relationship between capability control and salesperson Outcome Performance.
Research Question 4: Does task complexity, product complexity, and number of
accounts in direct, business-to-business sales moderate the effects of activity control on
salesperson outcome performance?
H04: Task complexity, product complexity, and number of accounts does not
moderate the relationship between activity control and salesperson outcome performance.
Ha4: Task complexity, product complexity, and number of accounts moderates the
relationship between activity control and salesperson outcome performance.
Data were entered into SPSS version 21.0 for Windows. Descriptive statistics
were conducted to describe the sample demographics and the research variables used in
the analysis. Frequencies and percentages were calculated for nominal data such as
sex/gender, whereas means and standard deviations were calculated for continuous data
such as the independent variables of control scales (outcome control, capability control,
and activity control), the moderators of task complexity, product complexity, and number
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of accounts, dependent variable of salesperson performance, the demographic
information of age and years as a salesperson. The internal consistency reliability of the
survey responses was examined with Cronbach’s alpha values for the three factors of
sales management control scales (outcome, activity and capability) and outcome
performance. A test of internal consistency of the survey responses of each of the study
variables was investigated using the Cronbach’s coefficient alpha estimates of reliability.
Data were screened for accuracy, missing information, and outliers. The presence
of outliers was tested by the examination of standardized value. Standardized values
represent the number of standard deviations the value is from the mean. Values greater
than 3.29 standard deviations from the mean are considered to be outliers and were
removed from the data set (Tabachnick & Fidell, 2007). Cases with missing data were
examined for non-random patterns. To minimize missing data, it was ensured in the
survey site that the questions could not be skipped in order to force respondents to answer
all questions without skipping one. However, participants who did not complete major
sections of the survey were excluded.
Prior to the statistical analysis, normality testing was conducted on the data of the
study variables to ensure that the assumptions required for parametric statistical tests
were fulfilled. This is because a regression analysis is a parametric statistic test. The
study was conducted by investigating the skewness and kurtosis statistics and the
normality plots in the histograms.
A hierarchical regression analysis was performed to determine the moderating
effects of task complexity, product complexity, and number of accounts on activity
control, capability control, outcome control, and salesperson outcome performance.
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Moderation effects of product complexity, task complexity, and numbers of accounts
were explored using nine interaction terms. Interaction terms were created between each
of the sales management control variables and task complexity, product complexity, and
number of accounts by multiplying the variables. There was a total of 9 interaction terms
representing the moderation effects of the different moderators. A variable modifies a
relationship if it changes the direction or magnitude of the relationship between two
variables. The moderation effects of complexity (product and task) and number of
accounts were computed by multiplying each of these moderators by the independent
variables of the sales management control scales (outcome, activity, and capability).
The dependent variable (DV, the outcome) in the regression model was
salesperson outcome performance, whereas the independent variables (IV, the predictor)
were the sales management control scales of outcome, activity and capability. The nine
interaction terms were added to determine the moderation effects. A single regression
model was run with each of the three sales management control scales as the independent
variables and using task complexity, product complexity, and number of accounts as the
moderators.
A hierarchical regression model was used in which block 1 included the effects of
the independent variables on the dependent variable and block 2 included the individual
effects of the moderator variables to the dependent variable. Block 3 included the
moderation effect by including the 9 multiple terms in the regression model. A level of
significance of 0.05 was used in the hierarchical regression analysis.
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Threats to Validity
Studies are valid if the instrument used to test consistently measures what it is
intended to measure. As stated, internal consistency of the survey responses was
examined with Cronbach’s alpha values for the three sales management control scales
(outcome, activity and capability) and outcome performance. The process ensured that
the survey questions used were internally consistent by examining the internal
consistency of the responses of the different respondents.
Construct validity is the extent to which a measurement is truthful, accurate,
authentic, or free of system error with evidence supporting the conclusion. Studies are
valid if the instrument used to test consistently measures what it is intended to measure.
Construct validity for all measures other than product complexity are strong. Cronbach’s
alpha of .67 for product complexity is the only reliability estimate that is below the .70
acceptable level. This may call into question any findings of moderation of the
relationship between sales management controls and salesperson performance.
The internal validity of a quantitative study is “the degree to which observed
changes in a dependent variable can be attributed to changes in an independent variable”
(Pedhazur & Schmelkin, 2013, p. 154). In research studies, the degree to which threats to
internal validity influence the study are determined by the type of research design and the
degree of control that the researcher has regarding sampling, data collection, and data
analyses (Mertens, 2014). For this study, one major threat to internal validity was the
direction of the causal influence of the variables studied. This study was not designed to
determine a cause and effect relationship. I cannot assert that increases in one or more
types of management control led to improved sales performance. In addition to a lack of
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causal influence, there are many other factors such as market turbulence and competitive
intensity that impact sales performance. Those and many other complicating factors were
beyond the scope of this study.
External validity concerns the degree to which conclusions from a study can be
generalized to other categories of people, settings, or times (Green & Salkind, 2010).
Results from this study therefore may not be generalized to other study population groups
other than salespeople in business-to-business sales. Salespeople in business-to-consumer
sales will not be able to apply the findings from my study, nor will marketing personnel
due to the variation in job type and evaluation measures.
Statistical conclusion validity is also a concern. The data were evaluated to ensure
the data did not violate the assumption of the statistical tests.
Ethical Procedures
The data collection procedures designed for this study were comprehensive and
were reviewed by members of the Walden’s Institutional Review Board (IRB) to ensure
that the data collection procedure was accepted ethically and legally and did not violate
any human rights. Prior to conducting the data collection, the purpose of the study and
the data collection process the study participants would undergo were explained clearly to
the participating salespeople. After gaining permission from the organization heads to
recruit their salespeople to participate in the study, the salespeople were required to prove
consent by agreeing to the informed consent form. Participants of the survey were also
notified that they had the right to discontinue participation at any time, and their
responses to the different questionnaires was to be discarded if they requested withdrawal
from the study.
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Fluid Surveys automatically stores and encrypts information from the completed
questionnaires and I was only able to access the information obtained with a username
and password. The collected responses from the participants were coded to ensure
confidentiality in the data analysis and reporting of results. Codes were assigned to each
respondent rather than using names to maintain confidentiality.
The data received is being kept secure and confidential and will be held for only
three years after the conclusion of the research. Soft copies of the results obtained
digitally are being stored in a personal portable hard disk drive that is password
protected. The hard drive will be electronically wiped clean and physically destroyed and
will be non-functional after three years of the completion of the study.
Summary
Chapter 3 included a discussion of the research design, population, sampling,
sampling procedures, instrumentation, operational definition of constructs, data
collection procedures, recruitment of participants, data analysis plan, threats to validity,
and ethical procedures. This study included a quantitative, non-experimental research
design with the objective of determining the relationships between three constructs of
sales management control (outcome control, activity control, and capability control) and
salesperson outcome performance, and the moderating effects of task complexity,
product complexity and number of accounts on these relationships. Data were collected
via salesperson responses to a survey regarding their sales manager’s level of outcome,
capability, and activity control, as well as task complexity, product complexity, number
of accounts, and individual outcome performance as a salesperson. An online survey
method using Fluid Surveys was used in the data collection. The data analysis included
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the use of descriptive statistics and a hierarchical regression analysis to address the
research questions of the study.
Chapter 4 includes the findings of the data analysis and specifically exposes the
results of the data collected. Finally, Chapter 5 includes a discussion of the results as
well as the implications of the study for theory, research, and practice.
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Chapter 4: Results
The purpose of this quantitative study was to examine the relationships between
three types of management control (outcome, capability, activity) and salesperson
outcome performance as well as quota achievement. The second purpose of this study
was to examine whether product complexity, task complexity, and number of accounts
moderated the above relationships. Four research questions and hypotheses were
formulated to guide the analysis:
Research Question 1: Are there relationships between the three types of sales
management control and salesperson outcome performance?
H01: Outcome control, capability control, and activity control are not related to
salesperson outcome performance.
Ha1: Outcome control, capability control, and activity control are positively
related to salesperson outcome performance.
Research Question 2: Does task complexity, product complexity, and number of
accounts in direct, business-to-business sales moderate the effects of outcome control on
salesperson outcome performance?
H02: Task complexity, product complexity, and number of accounts does not
moderate the relationship between outcome control and salesperson outcome
performance.
Ha2: Task complexity, product complexity, and number of accounts moderates the
relationship between outcome control and salesperson outcome performance.
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Research Question 3: Does task complexity, product complexity, and number of
accounts in direct, business-to-business sales moderate the effects of behavior-based
capability control on salesperson outcome performance?
H03: Task complexity, product complexity, and number of accounts does not
moderate the relationship between capability control and salesperson outcome
performance.
Ha3: Task complexity, product complexity, and number of accounts moderates the
relationship between capability control and salesperson Outcome Performance.
Research Question 4: Does task complexity, product complexity, and number of
accounts in direct, business-to-business sales moderate the effects of activity control on
salesperson outcome performance?
H04: Task complexity, product complexity, and number of accounts does not
moderate the relationship between activity control and salesperson outcome performance.
Ha4: Task complexity, product complexity, and number of accounts moderates the
relationship between activity control and salesperson outcome performance.
In this chapter, I describe the data collection process, demographic information,
measures of internal consistency reliability, and results of regression analyses conducted
on these data using the subjective performance data as the dependent variable. Following
this, I presente results using objective performance data as the dependent variable. This
chapter concludes with a summary highlighting the significant findings in these analyses.
Results of Data Collection
The research was conducted with a large multinational security services company.
The participating company was selected due to convenience of the sampling frame. The
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participating company is a client of the company in which I am employed and represents
a business-to-business sales environment with salespeople selling directly to end
customers.
The data were collected via salespersons’ responses to a survey about their sales
manager’s level of outcome, capability, and activity control, as well as task complexity,
product complexity, and number of accounts. Salespeople responded to questions about
their individual outcome performance. Although the total population of salespeople
exceeded 6,500, only sellers in the United States and United Kingdom were invited to
participate. This reduced the population to 4,000 salespeople, all of whom were invited to
participate. There was no limitation regarding size of sales team managed, and there was
no tenure requirement.
Sales executives within the organization agreed to have their sales managers
evaluated as part of the study. A description of the study was provided along with my
prospectus. An e-mail was drafted and sent to all participating sales managers to explain
the study and request the participation of their salespeople. The survey was deployed via
Fluid Surveys (Fluid Surveys, 2017). A unique link was developed for the participating
company. All appropriate permissions were secured prior to survey deployment. Data
collection took 4 months because the participating company took almost 3 months to
obtain the objective performance data. The total number of responses was 379, which
exceeded the target sample size of 200 required for 80% statistical power. Data analysis
included descriptive statistics along with a series of hierarchical regression analyses.
A total of 472 survey responses was received. These data were inspected for
missing data among variables included in the regression models. As a result, 72 cases
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were removed due to missing data. Additionally, these data were examined for outlying
values, which were defined as any values more extreme than three standard deviations
above or below the mean. Analysis of outlying values resulted in 21 additional cases
being dropped from the data set, yielding a final data set of 379 cases.
Data were screened for accuracy, missing information, and outliers. The presence
of outliers was tested by the examination of standardized values. Standardized values
represent the number of standard deviations the value is from the mean. Values greater
than 3.29 standard deviations from the mean are considered to be outliers and were
removed from the data set (see Tabachnick & Fidell, 2007). Cases with missing data were
examined for nonrandom patterns. To minimize missing data, I reminded participants in
the survey site that questions could not be skipped. This encouraged respondents to
answer all questions. Participants who did not complete major sections of the survey were
excluded.
Prior to the statistical analysis, a series of diagnostics was conducted to determine
whether any of the assumptions of regression were violated with respect to these data.
These results are presented in Appendix B. These tests addressed the presence of
linearity, absence of multicollinearity, normality of the residuals, homoscedasticity of the
residuals, absence of influential observations, and statistical independence of
observations. Univariate normality was examined for all quantitative variables within
these regression models, including the dependent and independent variables, through the
construction of histograms and QQ plots. Within these plots, the normal curve was
superimposed, with measures of skewness and kurtosis also calculated. These results did
not indicate extreme nonnormality with respect to any of these measures.
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Next, with respect to each independent variable, a scatterplot was generated
illustrating the bivariate relationship between the independent variable and the dependent
variable. Additionally, a locally weighted smoothing (LOESS) curve was superimposed
on these plots in Statistical Package for the Social Sciences (SPSS) to help illustrate
whether the relationship was reasonably linear. The thickness of the scatterplot around
the superimposed curve was examined to determine whether it changed on the basis of
the level of the independent variable to check for homoscedasticity. These plots failed to
indicate heteroscedasticity, and these scatterplots suggested the potential for nonlinear
relationships with respect to task complexity and product complexity on salesperson
performance. New variables were constructed for the predictors of task complexity and
product complexity by subtracting the mean from the raw measures and squaring the
results. The inclusion of these two measures with respect to the relevant three regression
models failed to indicate statistical significance in any case. Based on these results, none
of the regression models were modified because nonlinearity was not indicated.
Next, plots were examined of the residuals versus the predicted values to ensure
that there were no trends and no outliers. An examination of these plots did not indicate
either trends or extreme outliers. Additionally, the variance inflation factors were also
calculated with respect to all regression analyses. The presence of outliers in the
regression analyses was tested by specifying that the studentized residuals be presented
within these models, along with measures of Cook’s distance. These results indicated a
maximum Cook’s distance of .101, with a small number of studentized residuals whose
absolute values were slightly above 3. Overall, these results did not suggest influential
outliers.
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Demographic Information
Table 2 reports the sample characteristics with the categorical measures of
respondent age, gender, ethnicity, region, current sales position, and yearly sales target.
With regard to age, 61% of respondents were between 35 and 55. Approximately 80% of
respondents were male and 91% of respondents were White. With respect to work
location, 82% of respondents were from the United States and 16% were from the United
Kingdom or Ireland. Regarding current sales position, 12% of respondents were involved
with product sales, 2% were involved with channel sales, 27% worked with service
contracts, 20% dealt with install contracts, and 36% worked in a hybrid sales position.
With respect to the yearly sales target, over 90% of respondents had targets less than $3
million, with over 50% of respondents between $300,000 and $1.5 million.
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Table 2
Descriptive Statistics: Frequencies
Measure N %
Age
25 and under 2 0.5%
26 to 35 60 15.8%
36 to 45 103 27.1%
46 to 55 131 34.5%
56 to 65 76 20.0%
Over 65 7 1.8%
Total 379 100.0%
Gender
Female 77 20.3%
Male 302 79.6%
Total 379 100.0%
Ethnicity
American Indian or Alaskan Native 7 1.8%
Asian or Pacific Islander 5 1.3%
Black or African American 12 3.1%
Hispanic or Latino 8 2.1%
White / Caucasian 347 91.5%
Total 379 100.0%
Region
United States 311 82.0%
Canada 1 0.2%
UK & Ireland 62 16.3%
Continental Europe 2 0.5%
Africa 1 0.2%
India 1 0.2%
Latin America 1 0.2%
Total 379 100.0%
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(table continues)
Descriptive Statistics: Frequencies
Measure N %
Current Sales Position
Install Contracts 78 20.5%
Service Contracts 104 27.4%
Products 52 13.7%
Hybrid 137 36.1%
Channel Sales 8 2.1%
Total 379 100.0%
Yearly Sales Target
$300,000 and Under 80 21.1%
$300,001 - $750,000 92 24.2%
$750,001 - 1,500,000 98 25.8%
$1,500,001 - $3,000,000 77 20.3%
$3,000,001 - $5,000,000 20 5.2%
$5,000,001 - $10,000,000 7 1.8%
Over $10,000,000 5 1.3%
Total 379 100.0%
Descriptive Statistics of Study Variables
Next, Table 3 reports the measures of central tendency of the mean and median as
well as measures of variability of the standard deviation, range, and minimum and
maximum scores associated with the continuous measures of interest, which consisted of
the following: outcome control, capability control, activity control, task complexity,
product complexity, salesperson performance, number of managed accounts, and years as
a salesperson.
In reviewing these data, mean and median scores were found to be similar in all
cases except the number of managed accounts. For this reason, the mean values will be
focused upon with respect to this set of variables with the exception of the number of
managed accounts. Regarding the measures of outcome control, capability control,
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activity control, task complexity, product complexity, and salesperson performance,
mean values ranged from a minimum of 3.52 for task complexity to a maximum of 5.77
for outcome control. Regarding the respective standard deviations, these ranged from a
minimum of .58 for task complexity to a maximum of 1.42 for capability control. Next,
regarding the number of managed accounts, this had a median of 50 accounts with a
standard deviation of 422.78. Skewness and kurtosis were much closer to zero after log
transformation. Finally, regarding number of years spent working as a salesperson, this
had a mean of 15.01 years with a standard deviation of 10.14 years.
Table 3
Descriptive Statistics: Continuous Measures
Measure Mean Median SD Range Min Max. Q1 Q3
Outcome control 5.77 6.00 0.94 4.40 2.60 7.00 5.20 6.40
Capability control 5.07 5.40 1.42 5.80 1.20 7.00 4.00 6.00
Activity control 5.59 5.80 0.98 4.60 2.40 7.00 5.00 6.00
Task complexity 3.52 3.40 0.58 3.00 2.00 5.00 3.20 4.00
Product complexity 4.25 4.00 1.22 6.00 1.00 7.00 3.50 5.00
Salesperson performance 5.53 5.67 0.79 4.00 3.00 7.00 5.00 6.00
N. of Managed Accounts 221.52 50.00 422.78 2500.00 0.00 2500.00 10.00
250.00
N. Accounts (Log Trans.) 3.93 3.93 2.01 8.92 .00 8.92 2.40 5.53
Years as a Salesperson 15.01 15.00 10.14 49.00 1.00 50.00 6.0022.00
The internal consistency reliability of the survey responses was examined with
Cronbach’s alpha values for the three factors of sales management control scales
(outcome, activity and capability) and outcome performance. A test of internal
consistency of the survey responses of each of the study variables was investigated using
the Cronbach’s coefficient alpha estimates of reliability. The results of these analyses are
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presented in Table 4. As shown in this table, an acceptable level of internal consistency
reliability was found in all cases except Product Complexity, which had a Cronbach’s
alpha of .538.
Table 4
Internal Consistency Reliability Measures
Scale N of Items Cronbach’s Alpha
Outcome Control 5 .863
Capability Control 5 .951
Activity Control 5 .900
Task Complexity 5 .669
Product Complexity 2 .538
Salesperson Complexity 6 .833
Following this, a set of Pearson’s correlations were conducted between the
independent variables. These results are presented in Table 5. As shown, the highest
correlations were between outcome control and capability control as well as activity
control, and between capability control and activity control.
Table 5
Pearson’s Correlations Between Independent Variables
Measure 1 2 3 4 5
1. Outcome Control
2. Capability Control .701***
3. Activity Control .758*** .825***
4. Task Complexity -.009 -.062 -.044
5. Product Complexity -.114* -.158** -.147** .313***
6. Accounts (Log) .047 .101* .080 -.133** .001
Note. *p<.05, **p<.01, ***p<.001.
104
Inferential Statistics: Self-Report Performance Data
Initial descriptive statistics are reported, which consist of the sample size and
percentages of response associated with the categorical measures of interest included
within this study, along with measures of central tendency and variability calculated and
reported for the continuous measures of interest. One linear regression and three
hierarchical linear regression models were conducted on these data to explore this study’s
four research questions.
Hierarchical regression analysis was performed to determine the moderating
effects of task complexity, product complexity, and number of accounts on activity,
capability, outcome control, and salesperson outcome performance. Moderation effects of
product complexity, task complexity, and numbers of accounts were explored using nine
interaction terms. Interaction terms were created between each of the sales management
control variables and task complexity, product complexity, and number of accounts by
multiplying the variables. There was a total of 9 interaction terms that represent the
moderation effects of the different moderators.
A series of four hierarchical linear regression analyses were conducted to
investigate the four research questions included in this study. With respect to all
regression analyses, interaction terms were always calculated using the z-scores
associated with the original measures. The first research question included here consisted
of the following: Are there relationships between the three types of sales management
control and salesperson outcome performance?
The results of the linear regression analysis associated with this research question
are presented in Table 6. None of the independent variables achieved statistical
105
significance in this regression model. Additionally, this regression model also failed to
achieve significance.
Table 6
Regression Analysis for Salesperson Outcome Performance: Research Question 1
Measure B SE Beta t
Constant 4.99 .28 17.65***
Outcome Control .03 .07 .03 .38
Capability Control .05 .05 .09 .94
Activity Control .03 .08 .03 .34
Note. *p<.05, **p<.01, ***p<.001. F(3, 374) = 2.48, p = .061; R2 = .019, Adjusted R2 =
.012; B = Unstandardized regression coefficients; Beta = Standardized regression
coefficients.
The second research question included in this study consisted of the following:
Does task complexity, product complexity, and number of accounts in direct, business-to-
business sales moderate the effects of outcome control on salesperson outcome
performance?
Table 7 reports the results of the regression analyses conducted exploring this
research question. In these analyses, outcome control was found to achieve statistical
significance in all three models. Specifically, a one standard deviation increase in
outcome control was associated with a .11 standard deviation increase in salesperson
outcome performance in model two, with this figure increasing slightly to .12 in models
one and three. Additionally, model one was found to achieve statistical significance in the
ANOVA conducted, while this was non-significant in models two and three. With regard
to the change in the F-statistic, this was not significant in either case.
106
Table 7
Regression Analysis for Salesperson Outcome Performance: Research Question 2
Measure B SE Beta t
Model 1a
Constant 5.52 0.04 135.76***
Outcome Control (z) 0.11 0.05 0.12 2.29*
Model 2b
Constant 5.52 0.04 135.15***
N. of Accounts (z) 0.10 0.07 0.07 1.34
Outcome Control (z) 0.11 0.05 0.11 2.21*
Task Complexity (z) 0.02 0.04 0.03 0.56
Product Complexity (z) 0.01 0.04 0.01 0.24
N. of Accounts (z) 0.03 0.04 0.04 0.70
Model 3c
Constant 5.52 0.04 133.45***
Outcome Control (z) 0.12 0.05 0.12 2.39*
Task Complexity (z) 0.04 0.05 0.05 0.88
Product Complexity (z) -0.01 0.05 -0.01 -0.12
N. of Accounts (z) 0.04 0.04 0.05 0.93
OC (z) * TC (z) -0.07 0.05 -0.08 -1.34
OC (z) * PC (z) 0.08 0.05 0.10 1.63
OC (z) * A (z) 0.01 0.05 0.01 0.16
Note. *p<.05, **p<.01, ***p<.001; B = Unstandardized regression coefficients; Beta =
Standardized regression coefficients.
Model 1:
R2 = .014, Adjusted R2 = .011; F(1, 376) = 5.23, p < .05
Model 2:
R2 = .016, Adjusted R2 = .006; F(4, 373) = 1.54, p = .19
Model 3:
R2 = .025, Adjusted R2 = .006; F(7, 370) = 1.33, p = .236;
Model 2 vs Model 1:
ΔR2 = .02; ΔF(3, 373) = .318, p = .812
Model 3 vs Model 2:
ΔR2 = .09; ΔF(3, 370) = 1.047, p = .372
107
Next, the third research question included in this study was the following: Does
task complexity, product complexity, and number of accounts in direct, business-to-
business sales moderate the effects of behavior-based capability control on salesperson
outcome performance?
As shown in Table 8, in the first regression model conducted, statistical
significance was indicated regarding capability control, which was also achieved
significance in the second and third regression modes. In the first model, a one standard
deviation increase in capability control was associated with a .14 standard deviation
increase in the outcome. In the second model, this was.13, and was .14 in the third model.
Only the first model achieved statistical significance, whereas the change in the F-
statistics failed to achieve statistical significance in either case.
108
Table 8
Regression Analysis for Salesperson Outcome Performance: Research Question 3
Measure B SE Beta t
Model 1a
Constant 5.52 0.04 136.44***
Capability Control (z) 0.11 0.04 0.14 2.65**
Model 2b
Constant 5.52 0.04 135.85***
Capability Control (z) 0.11 0.04 0.14 2.60**
Task Complexity (z) 0.03 0.04 0.04 0.65
Product Complexity (z) 0.01 0.04 0.02 0.33
N. of Accounts (z) 0.03 0.04 0.03 0.62
Model 3c
Constant 5.51 0.04 132.85***
Zscore(Capability_control) 0.12 0.04 0.15 2.79**
Zscore(Task_complexity) 0.02 0.04 0.03 0.50
Zscore(Product_complexity) 0.02 0.04 0.02 0.41
N. of Accounts (z) 0.02 0.04 0.02 0.46
CC (z) * TC (z) -0.02 0.05 -0.03 -0.52
CC (z) * PC (z) -0.02 0.04 -0.03 -0.58
CC (z) * A (z) 0.06 0.05 0.07 1.32
Note. *p<.05, **p<.01, ***p<.001; B = Unstandardized regression coefficients; Beta =
Standardized regression coefficients.
Model 1:
R2 = .018, Adjusted R2 = .016; aF(1, 376) = 7.01, p < .01
Model 2:
R2 = .021, Adjusted R2 = .011; F(4, 373) = 2.01, p = .092
Model 3:
R2 = .029, Adjusted R2 = .010; F(7, 370) = 1.56, p = .145
Model 2 vs Model 1:
ΔR2 = .03; ΔF(3, 373) = .360, p = .782
Model 3 vs Model 2:
ΔR2 = .08; ΔF(3, 370) = .965, p = .409
109
The fourth research question included in the study consisted of the following:
Does task complexity, product complexity, and number of accounts in direct, business-to-
business sales moderate the effects of activity control on salesperson outcome
performance?
As shown in Table 9, the effect of activity control achieved statistical significance
in all three models. In models one and two, a one standard deviation increase in this
measure was associated with a .13 standard deviation increase in the outcome, while with
regard to the third regression model, this figure increased to .14. Only the first regression
model out of three achieved statistical significance, with the two changes in the F-statistic
failing to achieve significance in both cases.
110
Table 9
Regression Analysis for Salesperson Outcome Performance: Research Question 4
Measure B SE Beta t
Model 1a
Constant 5.51 0.04 136.72***
Activity Control (z) 0.12 0.05 0.13 2.48*
Model 2b
Constant 5.52 0.04 135.11***
Activity Control (z) 0.12 0.05 0.13 2.43*
Task Complexity (z) 0.03 0.04 0.04 0.66
Product Complexity (z) 0.01 0.04 0.01 0.27
N. of Accounts (z) 0.03 0.04 0.04 0.69
Model 3c
Constant 5.51 0.04 133.15***
Activity Control (z) 0.14 0.05 0.15 2.83**
Task Complexity (z) 0.03 0.04 0.03 0.58
Product Complexity (z) 0.01 0.04 0.01 0.12
N. of Accounts (z) 0.03 0.04 0.03 0.60
AC (z) * TC (z) -0.07 0.05 -0.09 -1.54
AC (z) * PC (z) 0.02 0.05 0.03 0.47
AC (z) * A (z) 0.06 0.05 0.07 1.28
Note. *p<.05, **p<.01, ***p<.001; B = Unstandardized regression coefficients; Beta =
Standardized regression coefficients.
Model 1:
R2 = .016, Adjusted R2 = .013; F(1, 376) = 6.14, p < .05
Model 2:
R2 = .019, Adjusted R2 = .008; F(4, 373) = 1.80, p = .128
Model 3:
R2 = .032, Adjusted R2 = .013; F(7, 370) = 1.73, p = .101
Model 2 vs Model 1:
ΔR2 = .03; ΔF(3, 373) = .366, p = .778
Model 3 vs Model 2:
ΔR2 = .13; ΔF(3, 370) = 1.615, p = .185
111
Regarding the regression analyses reported here, the regression assumptions were
systematically examined. Univariate normality was examined for all quantitative
variables within these regression models, including the dependent and independent
variables, through the construction of histograms and QQ plots. Within these plots, the
normal curve was superimposed, with measures of skewness and kurtosis also calculated.
These results did not indicate extreme non-normality with respect to any of these
measures. Next, , scatterplots were generated for each independent variable, illustrating
the bivariate relationship between the independent variable and the dependent variable.
Additionally, a LOESS curve was superimposed on these plots in SPSS to help illustrate
whether the relationship is reasonably linear. The thickness of the scatterplot around the
superimposed curve was examined to determine whether it changes on the basis of the
level of the independent variable in order to visually check for homoscedasticity. These
plots failed to indicate heteroscedasticity, and these scatterplots suggested the potential
for non-linear relationships with respect to task complexity and product complexity on
salesperson performance. New variables were constructed for the predictors of task
complexity and product complexity by subtracting the mean from the raw measures and
squaring the results. The inclusion of these two measures with respect to the relevant
three regression models failed to indicate statistical significance in any case. Based on
these results, none of the regression models were modified as non-linearity was not
indicated. Next, plots were examined of the residuals versus the predicted values to
ensure that there were no trends or outliers. An examination of these plots did not
indicate either trends or extreme outliers. Additionally, the variance inflation factors were
calculated with respect to all regression analyses. These results are reported in Appendix
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A and failed to indicate multicollinearity in any case. Additionally, whether there were
outliers in these regression analyses was tested by specifying that the studentized
residuals presented within these models, along with measures of Cook’s distance. These
results indicated a maximum Cook’s distance of .101, with a small number of studentized
residuals whose absolute values were slightly above three. Overall, these results do not
suggest influential outliers.
Inferential Statistics: Objective Performance Data
This section presents and discusses the results of the analysis conducted on the
second dependent variable, focusing upon the outcome of quota achievement. Initial
descriptive statistics are omitted from this section as they were reported previously. A
series of four linear regression analyses were conducted on these data, serving to explore
this study’s four research questions.
Initially, these data were analyzed for the presence of missing data. All variables
included in the regression models were focused on, and cases were dropped in any cases
where missing data was present regarding these variables. This reduced the total sample
size, which was originally 472, by 72 cases. Additionally, these data were analyzed for
outlying values, which were defined as any values more extreme than three standard
deviations above or below the mean. The removal of these outlying cases resulted in 26
additional cases being dropped from the dataset, producing a total sample size of 374.
A series of four linear regression analyses were conducted to explore the four research
questions included in this study. The first research question included here consisted of the
following: Are there relationships between the three types of sales management control
and quota achievement?
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The results of the linear regression analysis associated with this research question
are presented in Table 10. The independent variable of activity control achieved
statistical significance in this analysis. In this model, a one standard deviation increase in
activity control was associated with a .24 standard deviation increase in the outcome.
Additionally, this regression model achieved statistical significance based on the
ANOVA conducted.
Table 10
Regression Analysis for Quota Attainment: Research Question 1
Measure B SE Beta t
Constant 71.58 16.45 4.35***
Outcome Control -4.81 3.81 -0.10 -1.26
Capability Control -0.55 2.92 -0.02 -0.19
Activity Control 10.98 4.49 0.24 2.44*
Note. *p<.05, **p<.01, ***p<.001. F(3, 340) = 3.35, p < .05; R2 = .029, Adjusted R2 =
.020; B = Unstandardized regression coefficients; Beta = Standardized regression
coefficients.
The second research question included in this study consisted of the following:
Does task complexity, product complexity, and number of accounts in direct, business-to-
business sales moderate the effects of outcome control on quota achievement?
Table 11 reports the results of these analyses. Within these models, task
complexity was achieved statistical significance. In model two, a one standard deviation
increase in task complexity was associated with a .16 standard deviation decrease in the
outcome, while this figure increased in magnitude to -.18 in the third model. Only the
second of the three linear regression models achieved statistical significance on the basis
of the ANOVA conducted, with the change in the F-statistic achieving statistical
significance in the second but not the third model.
114
Table 11
Regression Analysis for Quota Attainment: Research Question 2
Measure B SE Beta t
Model 1a
Constant 102.45 2.37 43.15***
Outcome Control (z) 3.26 2.86 0.06 1.14
Model 2b
Constant 102.71 2.35 43.62***
Outcome Control (z) 2.96 2.89 0.06 1.02
Task Complexity (z) -6.76 2.57 -0.15 -2.63**
Product Complexity (z) -0.41 2.51 -0.01 -0.16
Accounts (z) 1.32 2.52 0.03 0.52
Model 3c
Constant 102.19 2.40 42.64***
Outcome Control (z) 2.53 2.97 0.05 0.85
Task Complexity (z) -7.37 2.64 -0.17 -2.79**
Product Complexity (z) 0.57 2.62 0.01 0.22
Accounts (z) 0.59 2.59 0.01 0.23
OC (z) * TC (z) 3.25 2.98 0.07 1.09
OC (z) * PC (z) -2.12 3.00 -0.05 -0.71
OC (z) * A (z) 4.02 3.16 0.07 1.27
Note. *p<.05, **p<.01, ***p<.001; B = Unstandardized regression coefficients; Beta =
Standardized regression coefficients.
Model 1:
R2 = .004, Adjusted R2 = .001; F(1, 319) = 1.30, p = .256
Model 2:
R2 = .031, Adjusted R2 = .019; F(4, 316) = 2.56, p < .05
Model 3:
R2 = .039, Adjusted R2 = .017; F(7, 313) = 1.80, p = .087
Model 2 vs Model 1:
ΔR2 = .027; ΔF(3, 316) = 2.97, p < .05
Model 3 vs Model 2:
ΔR2 = .008; ΔF(3, 313) = .79, p = .499
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Next, the third research question included in this study was the following: Does
task complexity, product complexity, and number of accounts in direct, business-to-
business sales moderate the effects of behavior-based capability control on quota
achievement?
As shown in Table 12, statistical significance in these regression models was
achieved with respect to the predictors of task complexity in the second and third models.
Regarding task complexity, a one standard deviation increase in this measure was
associated with a .16 standard deviation decrease in the outcome measure in both the
second and third models. Again, in this analysis only the second linear regression model
achieved statistical significance, with the change in the F-statistic also achieving
significance here, but not in the third model.
116
Table 12
Regression Analysis for Quota Attainment: Research Question 3
Measure B SE Beta t
Model 1a
Constant 102.45 2.34 43.70***
Capability Control (z) 4.43 2.49 0.10 1.78
Model 2b
Constant 102.75 2.33 44.12***
Capability Control (z) 3.65 2.52 0.08 1.45
Task Complexity (z) -6.53 2.56 -0.15 -2.55*
Product Complexity (z) -0.30 2.50 -0.01 -0.12
Accounts (z) 1.15 2.52 0.03 0.46
Model 3c
Constant 103.10 2.39 43.06***
Capability Control (z) 3.35 2.56 0.08 1.31
Task Complexity (z) -6.51 2.58 -0.15 -2.52*
Product Complexity (z) -0.47 2.54 -0.01 -0.18
Accounts (z) 1.48 2.59 0.03 0.57
CC (z) * TC (z) 1.33 2.75 0.03 0.48
CC (z) * PC (z) -0.34 2.45 -0.01 -0.14
CC (z) * A (z) -1.93 2.90 -0.04 -0.67
Note. *p<.05, **p<.01, ***p<.001; B = Unstandardized regression coefficients; Beta =
Standardized regression coefficients.
Model 1:
R2 = .010, Adjusted R2 = .007; F(1, 319) = 3.17, p = .076
Model 2:
R2 = .035, Adjusted R2 = .022; F(4, 316) = 2.83, p < .05
Model 3:
R2 = .037, Adjusted R2 = .016; F(7, 313) = 1.72, p = .103
Model 2 vs Model 1:
ΔR2 = .025; ΔF(3, 316) = 2.70, p < .05
Model 3 vs Model 2:
ΔR2 = .002; ΔF(3, 313) = .28, p = .841
117
The fourth research question included in this study consisted of the following:
Does task complexity, product complexity, and number of accounts in direct, business-to-
business sales moderate the effects of activity control on quota achievement?
As shown in Table 13, statistical significance was achieved with respect to the
effects of activity control in all three models, and task complexity in both models two and
three. First, regarding activity control, a one standard deviation increase in this measure
was associated with a .13 standard deviation increase in the outcome for model one, with
this figure decreasing slightly to .12 in models two and three. Next, regarding task
complexity, a one standard deviation increase in this measure was associated with a .16
standard deviation decrease in the outcome in the second model, with this figure
representing a .15 standard deviation decrease in the third model. All three regression
models achieved statistical significance, with the change in the F-statistic achieving
significance in the second, but not third, model.
118
Table 13
Regression Analysis for Quota Attainment: Research Question 4
Measure B SE Beta t
Model 1a
Constant 102.05 2.35 43.38***
Activity Control (z) 6.33 2.75 0.13 2.30*
Model 2b
Constant 102.35 2.34 43.81***
Activity Control (z) 5.77 2.77 0.12 2.08*
Task Complexity (z) -6.65 2.55 -0.15 -2.60**
Product Complexity (z) -0.16 2.49 0.00 -0.06
Accounts (z) 0.96 2.51 0.02 0.38
Model 3c
Constant 102.49 2.39 42.86***
Activity Control (z) 5.86 2.85 0.12 2.05*
Task Complexity (z) -6.35 2.58 -0.15 -2.46*
Product Complexity (z) -0.50 2.55 -0.01 -0.20
Accounts (z) 0.97 2.59 0.02 0.37
AC (z) * TC (z) -0.12 2.78 0.00 -0.04
AC (z) * PC (z) 2.84 2.80 0.06 1.01
AC (z) * A (z) 1.05 3.19 0.02 0.33
Note. *p<.05, **p<.01, ***p<.001; B = Unstandardized regression coefficients; Beta =
Standardized regression coefficients.
Model 1:
R2 = .016, Adjusted R2 = .013; F(1, 319) = 5.30, p < .05
Model 2:
R2 = .041, Adjusted R2 = .029; F(4, 316) = 3.40, p < .05
Model 3:
R2 = .045, Adjusted R2 = .024; F(7, 313) = 2.12, p < .05
Model 2 vs Model 1:
ΔR2 = .025; ΔF(3, 316) = 2.74, p < .05
Model 3 vs Model 2:
ΔR2 = .004; ΔF(3, 313) = .44, p = .724
The regression assumptions were examined through the use of diagnostic tests
and figures. Univariate normality was examined for all quantitative variables within these
119
regression models, including the dependent and independent variables, through the
construction of histograms and QQ plots. Within these plots, a normal curve was
superimposed, with measures of skewness and kurtosis also calculated. These results did
not indicate extreme non-normality regarding any of these measures. Next, with respect
to each independent variable, a scatterplot was generated illustrating the bivariate
relationship between the independent variable and the dependent variable. Additionally, a
LOESS curve was superimposed on these plots in SPSS to help illustrate whether the
relationship is reasonably linear. The thickness of the scatterplot around the
superimposed curve was examined to determine whether it changes on the basis of the
level of the independent variable in order to visually check for homoscedasticity. These
plots failed to indicate heteroscedasticity. Next, plots were examined of the residuals
versus the predicted values to ensure that there were no trends or outliers. An
examination of these plots did not indicate either trends or extreme outliers. Additionally,
the variance inflation factors were also calculated for all regression analyses. These
results are reported in Appendix B and failed to indicate multicollinearity in any case.
Additionally, whether there were outliers in these regression analyses was tested by
specifying that the studentized residuals be presented within these models, along with
measures of Cook’s distance. These results indicated a maximum Cook’s distance of
.149, with a small number of studentized residuals whose absolute values were slightly
above three. Overall, these results do not suggest influential outliers.
Conclusion
Regarding the first dependent variable, the results of the analyses conducted only
found statistical significance with respect to the effects of outcome control in the first
120
hierarchical regression, along with the effects of capability control and activity control in
the second and third hierarchical linear regression models, respectively. In all cases,
significant, positive impacts of these measures on the dependent variable were found.
Despite these significant results, none of the four research questions included in this
study were found to be supported on the basis of the analyses conducted.
In relation to the second dependent variable, the results of the analyses conducted
for this study indicated a substantial number of statistically significant results. With
regard to this study’s research questions, with respect to the first outcome analyzed,
support was not found for any of the four research questions as no significant results were
found in the first regression model conducted. Support was not found for research
questions two through four due to the lack of any significant findings relating to the
interaction effects, which served to test for the existence of significant moderation.
Regarding the outcome of quota achievement, the first hypothesis was supported as
activity control had a significant main effect. No significant interaction effects were
identified to support hypotheses two through four.
121
Chapter 5: Discussion
Salesperson performance is a key contributor to organizational performance, and
the primary goal of a salesperson is to achieve sales results (Behrman & Perreault, 1982).
Sales managers can significantly influence the actions and behaviors of the salespeople
they manage (Anderson & Oliver, 1987). Manager behavior can have both positive
(Doyle & Shapiro, 1980) and negative effects (CEB Sales and Service, 2012; Jones et al.,
1996) on salespersons’ ability to achieve their revenue targets. Although the role of sales
manager is a powerful one and can dramatically influence salesperson performance,
managers often receive very little training on how to do their job (Dubinsky et al., 2001)
and are not given specific guidance on how to best allocate their time and effort (Beck,
2006). Because the sales manager has a direct impact on seller performance, the purpose
of this quantitative study was to examine the relationships between three types of
management control (outcome, capability, activity) and salesperson outcome
performance. The second purpose of this study was to examine whether product
complexity, task complexity, and number of accounts moderated the above relationships.
The research questions for the study were examined by the two sets of regression
analyses—the first with a self-report measure of salesperson outcome performance as the
dependent variable and the second with sales quota achievement as the dependent
variable. A summary of the findings is provided in Table 14.
The study findings provided evidence for the relationships addressed in Research
Question 1: Are there relationships between the three types of sales management control
and salesperson outcome performance? In Ha1 it was hypothesized that outcome control,
capability control, and activity control would be positively related with salesperson
122
outcome performance. In the first set of analyses using the self-report measure of
salesperson outcome performance, statistical significance was found with respect to the
positive effects of outcome control in the first hierarchical regression, and for capability
and activity control in the second and third hierarchical regressions. In the analyses with
self-rated salesperson performance as the dependent variable, direct effects of outcome
control, capability control, and activity control were statistically significant when entered
separately but not when entered simultaneously as independent variables. High
correlations between the management control constructs may have contributed to the lack
of significant effects of the control variables when entered simultaneously.
In the second analysis conducted using the objective measure of percentage of
quota achievement, partial support was found for Ha1. Statistical significance was
indicated with respect to the positive impacts of activity control on quota achievement.
Unlike the first analysis, this analysis failed to indicate a significant effect of either
outcome or capability control on objective quota achievement. The positive relationship
between activity control and salesperson performance was significant for both the self-
rated and objective performance measures; however, the effect was much larger in the
objective measurement condition. The impact of activity control on salesperson outcome
performance (self-report) was significant and positive such that a one standard deviation
increase in activity control was associated with a 0.13 standard deviation increase in
salesperson outcome performance. The impact of activity control on quota attainment
was significant and positive such that a one standard deviation in activity control was
associated with a 0.24 standard deviation in quota attainment. This was a 54% difference
in effect size between the self-report and objective performance conditions.
123
No clear support was indicated for the moderating effects of task complexity,
product complexity, and number of accounts on the relationship between management
control (outcome, capability, activity) and the self-report measure of salesperson outcome
performance. This lack of significant moderation was evidenced through the fact that
absence of statistical significance for the interaction effects included in these models,
which served to test for moderation. A similar lack of significant moderation was found
with respect to task complexity, product complexity, and number of accounts on the
relationship between management control (outcome, capability, activity) and quota
achievement.
A direct negative effect of task complexity was found on quota achievement. In
all three of the hierarchical regression analyses with quota achievement as the dependent
variable, a statistically significant negative effect of task complexity was found.
However, the direct effect of task complexity was not significant in the regression
analyses with the self-report measure of salesperson outcome performance as the
dependent variable. In other words, task complexity had a significant negative effect on
salesperson quota attainment, but not salesperson outcome performance. This variation in
findings within the same study suggest the need to use objective performance data to
determine direct effects of controls, and role-based variables such as task complexity, on
salesperson performance.
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Table 14
Statistical Significance of the Independent Variables in the Regression Models Predicting
Sales Performance
Independent Variables Dependent Variable
Salesperson Outcome Performance
(self-rated)
Sales Quota Attainment
(objective measure)
Direct effects:
Outcome control Significant (positive) Not significant
Capability control Significant (positive) Not significant
Activity control Significant (positive) Significant (positive)
Task complexity Not significant Significant (negative)
Product complexity Not significant Not significant
No. of Accounts Not significant Not significant
Moderating Effects:
Outcome control X
Task complexity Not significant Not significant
Product complexity Not significant Not significant
No. of Accounts Not significant Not significant
Capability control X
Task complexity Not significant Not significant
Product complexity Not significant Not significant
No. of Accounts Not significant Not significant
Activity control X
Task complexity Not significant Not significant
Product complexity Not significant Not significant
No. of Accounts Not significant Not significant
Interpretation of Findings
The first objective was to determine whether a direct effect between sales
management control and salesperson performance existed in a population of business-to-
business salespeople selling directly to end customers. I chose the theoretical framework
125
of outcome control, activity control, and capability control put forth by Challagalla and
Shervani (1996) because they separated the construct of behavior control (Jaworski &
MacInnis, 1989) into two separate constructs. This study was the first to address the
moderating effects of task complexity, product complexity, and number of accounts on
the relationship between the three types of management control (outcome, activity,
capability) and salesperson performance in a business-to-business, direct sales
environment. By examining the way these three role-based factors (task complexity,
product complexity, number of accounts) influenced the control-performance
relationship, I hoped to provide additional clarity for researchers and sales managers
regarding the specifics of when different types of control are most useful. This additional
clarity could provide tactical guidance for sales managers and leaders when managing
salespeople with different role characteristics, as well as direct future research on this
important topic, which has been inconsistent at best, with mixed findings that have been
hard to compare and interpret.
In the first set of analyses using the subjective measure of salesperson outcome
performance, a direct positive effect of outcome control on salesperson performance was
found. This positive direct effect of outcome control on salesperson performance was
consistent with the findings of Evans et al. (2007) and Miao et al. (2007) but contradicted
the findings of Challagalla and Shervani (1996) who found no effect of outcome control
on salesperson outcome performance. Both Evans et al. and Miao et al. examined
salesperson populations in a business-to-business sales environment; however, Miao et al.
included business-to-consumer salespeople in their study. In the second set of analyses
using the objective measure of quota achievement as the dependent variable, a significant
126
effect of outcome control on salesperson quota achievement was not found. This
indicated that the use of performance measure (subjective or objective) is important and
could lead to different results within the same sample.
Although Challagalla and Shervani (1996) found no direct effect of management
controls (capability, activity, outcome) on salesperson performance in their study of
salespeople in a business-to-business sales environment, they did find an indirect effect
via supervisor role ambiguity. This indirect effect of management controls on salesperson
performance was supported in studies by Kohli et al. (1998) and Fang et al. (2005).
Challagalla and Shervani proposed that activity and capability controls have different
impacts on salesperson performance. Their assertion was supported by Kohli et al. in that
outcome and activity control positively and significantly influenced salespeople’s
performance orientation, but capability control had no impact on salespeople’s
performance orientation. Salesperson performance orientation was positively and
significantly related to salesperson performance (Kohli et al., 1998). Fang et al. found an
indirect effect of outcome control on salesperson performance via goal-setting
characteristics, providing further support for Challagalla and Shervani’s proposition.
Unlike the findings of Kohli et al. (1998), Challagalla and Shervani (1996), and
Evans et al. (2007), I found a direct positive effect of outcome, capability, and activity
control on the subjective measure of salesperson performance, and activity control when
using the objective measure of salesperson quota achievement. The direct positive effects
of both activity and capability control on the subjective measure of salesperson outcome
performance, as well as the direct positive effects of activity control on salesperson quota
achievement were in contrast with the findings of Miao et al. (2007), who found no effect
127
of activity control and a negative effect of capability control on salesperson performance.
The inconsistency between the findings of this present study and those of Miao et al.
could possibly be explained because the Miao et al. study involved a combination of
business-to-business and business-to-consumer salespeople, whereas this study included
only a business-to-business salesperson sample.
Challagalla et al. (2000) found a moderating effect of salesperson location on the
relationship between sales management control and salesperson performance. Challagalla
et al. examined the impact of task complexity on the management control-salesperson
performance relationship and found that task complexity failed to moderate the control-
performance relationship. This failure to find a moderating effect of task complexity was
similar to my study; however, I found a direct and significant negative effect of task
complexity on salesperson performance, which extended the findings of Challagalla et al.
Menguc and Tansu Barker (2003) were the only researchers to find a moderating
effect of task complexity on the management control-sales performance relationship;
however, they used the Anderson and Oliver (1987) conceptualization of behavior control
as a single construct as compared to the Challagalla and Shervani (1996)
conceptualization of behavior control as the separate constructs of activity and capability
control. This finding, using the Challagalla and Shervani scales for behavioral control,
was not replicated in the present study.
Flaherty et al. (2007) found that product complexity impacted the control
performance relationship such that process control positively and significantly impacted
salesperson performance when product complexity was high and low, but not when
product complexity was moderate. Output control had a positive significant effect on
128
performance when product complexity was high. Results from the present study did not
support this finding as neither a direct nor a moderating effect of product complexity was
found on salesperson performance. Atuahene-Gima and Li (2002) found that product
complexity failed to moderate the relationship between management control and
salesperson performance even though they studied the same population as Flaherty et al.
and used the same measurement scales developed by Jaworksi and MacInnis (1989) that
measure process (behavior) control as a single construct. In this present study, I used the
Challagalla and Shervani (1996) separate scales of activity and capability controls to
measure the behavioral elements of management control. It is likely that this variation in
scales used could explain the difference in study findings.
Theoretical Implications
A key element of organization theory (Ouchi, 1979) involves the role expectations
communicated to salespeople by their sales managers (Jones et al., 1996). According to
Doyle and Shapiro (1980), leader clarity setting and communicating expectations
regarding salesperson activities was the most significant contributor to salesperson
motivation. Challagalla and Shervani’s (1996) separation of activity and capability
controls was supported in my study as both types of control significantly and positively
impacted salesperson performance when using the subjective measure of salesperson
outcome performance, and activity control significantly and positively impacted objective
quota achievement. In other studies, behavior control was found to have no impact on
salesperson performance (Oliver & Anderson, 1994; Panagopoulos et al., 2015) or to
have a negative impact on salesperson performance (Ahearne et al., 2010).
129
Another consideration of organizational theory (Ouchi, 1979) is the link between
means-ends relationships (Eisenhardt, 1985). The more complex the means-ends
relationships, the more difficult it is to institute behavior or process controls, and
outcome controls are the control of choice. The less complex the means-ends
relationships, the more applicable behavior controls can be used to measure and impact
the means sellers use to achieve certain outcomes. In the current study, task complexity
was examined as the difficulty of the selling task from the salesperson’s perspective.
Higher levels of task complexity would indicate less clarity of the means-ends
relationship of the salesperson’s selling job. Although evidence was not found for the
moderating impact of task complexity on the relationship between management control
and salesperson performance, I found that task complexity was significantly and
negatively related to salesperson performance, which was consistent with organizational
theory (Ouchi, 1979) This is the only study that indicated this significant negative
relationship between task complexity and salesperson performance in a business-to-
business sales environment. Although this study indicated a direct effect versus a
moderating effect, this negative direct effect of task complexity on salesperson
performance has implications for how managers manage and coach using the various
forms of management control. When the means-ends relationships are less clear, outcome
control tends to be the control of choice (Eisenhardt, 1985); however, since task
complexity can hinder the seller’s ability to achieve quota attainment, it seems logical
130
that activity and capability control in the form of coaching when the seller’s task is
increasingly complex could reduce this negative effect.
One final consideration of organizational theory concerns the suggestion that
outcome control is the preferred type of management control when means-ends
relationships are unknown or unclear (Eisenhardt, 1985; Ouchi, 1979). The findings from
the second set of regression analyses using quota attainment as the dependent variable
were in direct contrast to this key tenet of organization theory. In this study, activity
control was significantly and positively associated with higher quota attainment at the
same time that task complexity (lack of clarity on means-ends relationships) was
significantly and negatively associated with quota attainment. According to
organizational theory, Ouchi and Eisenhardt would propose that when task complexity is
high (knowledge of means-ends relationships is low), outcome control would be the
control of choice, which was not indicated in the results of this study.
Limitations
This study was conducted in a business-to-business sales environment and cannot
be effectively compared to other sales environments such as business-to-consumer or
channel sales. Business-to-consumer sales tend to be less complex than business to
business sales. Consistent with organizational theory, the greater the knowledge of
means-ends relationships as in the case of a less complex business-to-consumer
environment, the more appropriate the application of behavioral controls (Eisenhardt,
1985). Channel sales involve indirect relationships between sales managers and
salespeople and can occur in both simple and complex sales environments. Any
comparison of the findings of this study to a channel sales environment would necessitate
131
consideration of the complexity of the sale: the lower the complexity of the channel sale,
the less relevant the findings of this study.
I conducted this study using the Challagalla and Shervani’s (1996)
conceptualizations of activity and capability control and the findings cannot be compared
to other studies using other instruments to measure behavior control as a single construct.
Jaworski and MacInnis (1989) and Anderson and Oliver (1996) measured behavior
control as a single construct as compared to Challagalla and Shervani’s (1996) separation
into activity and capability control. Researchers have cited the use of different measures
as one of the primary reasons for inconsistent findings of prior studies of the relationship
between behavioral controls and salesperson performance (Challagalla & Shervani,
1996).
In this study, I recruited salespeople to report their perspectives on all constructs.
It is reasonable to expect that salespeople will have different perspectives about the
management controls in effect as compared to the perspectives of sales managers and
sales and marketing executives. This study should only be compared to other studies that
used a similar salesperson population to assess management controls in effect.
The scope of this study was limited regarding the number of organizations, the
size of the population, and the study method. This study involved only one company and
may not be effectively compared to cross-organizational studies that survey one or two
people in each organization. Also, although the sample size of 374 was sufficient for
statistical analysis, the response rate represented only 9.35% of the total sales population.
It is possible that inclusion of the other 90.65% could have generated a very different set
of outcomes. In addition, this study was based on a convenience sample not a random
132
sample; therefore, generalizability to the broader population of salespeople is limited.
This was a correlational study, not an experimental study. Because correlation does not
necessarily imply causation, the reader is strongly cautioned when interpreting the
statistically significant regression results reported in this study.
Finally, despite the widespread use of self-report data in the social sciences, self-
report data are often viewed as lacking in validity and may call into question any
inferences drawn from the use of such data (Lance & Vandenberg, 2009, p. 309).
Although this study involved a self-report measure of salesperson outcome performance,
I also included an objective performance measured reported as percentage of quota
attainment. My findings of direct effects of outcome, capability control, and activity
control on salesperson performance in the self-report condition, and effects of only
activity control on salesperson performance in the objective performance condition,
corroborate the potential limitations associated with inferences drawn from self-report
measures.
Recommendations
Because I failed to identify moderating effects of the three sales role
characteristics (task complexity, product complexity, number of accounts) on the control-
performance relationship, the following recommendations are offered to potentially close
this gap in the management control literature.
One recommendation is to conduct a study of business-to-business salespeople
using the three primary theoretical constructs of Anderson and Oliver (1989), Jaworksi
and MacInnis (1989), and Challagalla and Shervai (1996) in the same study and compare
the results. Although I did not find moderating effects of product complexity, task
133
complexity, or number of accounts on the relationship between sales management control
and salesperson performance, it is possible that a moderating effect could be found using
alternative instruments to measure management control. In their study of salespeople in
business-to-business sales, Panagopoulos et al. (2015) found different results for the
management control – sales performance relationship based on the measures used.
Panagopoulos et al. used both the Jaworski and MacInnis (1989) management control
scales and the Anderson and Oliver (1989) scales in the same study and found that the
scales used impacted the results obtained. Since Panagopoulos et al. did not incorporate a
measure that separated behavior control into the separate constructs of activity and
capability control (Challagalla & Shervani, 1996), the use of this additional measure
could provide an important comparison of the difference in results using the three most
pervasive measures of sales management control.
A second recommendation is to conduct a study of both business-to-business and
business-to-consumer sales environments in the same study to examine the differences in
effects of management control on salesperson performance between the two populations.
The sales environment could be used as a moderating variable similar in nature to the
study conducted by Challagalla et al. (2000) who used salesperson location as a
moderating variable of the management control – sales performance relationship.
Although it would not make sense in this context to examine number of accounts in a
study of business-to-consumer sales, both task and product complexity could still be
considered and examined as potential moderators.
A final recommendation is to conduct a study of the management control – sales
performance relationship using the Challagalla and Shervani’s (1996) scales for activity,
134
capability, and outcome control and use length of sales cycle as a potential moderating
variable. This could provide an alternative way to examine product complexity because
the more complex the product, the longer it takes to sell. The measure of product
complexity that was used in this study (Slater & Olson, 2000) may not have been the best
measure to examine the way complexity of the sales task impacts the management
control – sales performance relationship.
All three of the above recommendations could benefit from gathering both
salesperson and sales manager perspectives, and then comparing the two perspectives
within studies. This could assist researchers in determining measure-to-measure variation
and population-to-population variation.
Practical and Social Implications
The confirmation that all types of management control examined in this study
(outcome, activity, capability) had a significant, positive effect on subjective salesperson
outcome performance highlights the need to ensure that sales managers in business-to-
business sales consider the degree to which they incorporate the three types of
management control into their everyday management practices. In the cases where
objective quota achievement is tracked and used to drive salesperson compensation, the
use of activity control was the only type of management control that had a positive and
significant impact. As the proliferation of customer relationship management systems
becomes more pervasive in sales organizations of all sizes, the ability to track and report
sales results (outcomes) is ubiquitous. The ability of sales managers and leaders to know
at any point in time how a salesperson is performing against their revenue targets could
give managers and leaders a false sense of control without paying attention to the means-
135
ends relationship (Ouchi, 1979) that generates the outcomes achieved. By ensuring that
sales managers incorporate activity measures and practices, sales managers can apply the
most relevant approach to managing their sales teams.
The social implications of this study are quite practical. Doyle and Shapiro (1980)
found that the degree to which salespeople see the direct relationship between the tasks
they are expected to perform and the results they are held accountable to achieve was the
most significant contributor to salesperson motivation. This examination of task clarity
was directly in line with the importance of knowing the means-ends relationship
(Eisenhardt, 1985; Ouchi, 1979) between activities and results. The finding that activity
control was significantly and positively related to salesperson performance gives
managers a practical way to improve the conditions in which salespeople work by
improving the seller’s understanding of what is needed to succeed in their job. This
finding is also practical from the sales manager’s perspective. Activities are the only type
of metric that are within the direct control of the sales manager (Jordan & Vazzana,
2012). Although revenue performance determines the level of compensation a seller
receives, sales managers cannot directly control revenue performance, they can only track
it. By directly linking seller activities to desired outcomes, and focusing on execution of
those activities, managers can have a direct and positive impact on seller performance.
Conclusion
The purpose of this study was to examine the moderating effects of task
complexity, product complexity, and number of accounts on the management control-
sales performance relationship. This study included examination of both subjective and
objective performance measures. The use of different measures produced different
136
results. Using the subjective performance measure as the dependent variable, statistically
significant and positive direct effects of outcome, capability, and activity control on
salesperson performance were found. However, with salesperson quota attainment as the
as the dependent variable, only activity control had a statistically significant positive
effect. Also task complexity had a significant negative association with salesperson quota
attainment; but there was not a significant relationship between task complexity and self-
rated salesperson performance, The differences in results for the two dependent variables
in the current study could call into question the validity of prior studies using subjective
measures of salesperson performance. In addition, a statistically significant negative
effect of task complexity on salesperson performance occurred when quota achievement
was used as the performance measure. This extends the findings of prior studies using the
Challagalla and Shervani (1996) management control scales.
These findings must be carefully considered due to several limitations. This study
involved sellers from one company in a business-to-business environment. These results
may not be effectively compared to studies involving multiple company samples, or
studies in a business-to-consumer environment. In addition, this study involved
perceptions of management control from a salesperson perspective as opposed to the
sales manager’s perspective.
Although the findings of this study extend findings of prior studies, additional
research is needed. Three recommendations could be useful in further extending
management control research. First, a study could be conducted in a business-to-business
context using all three of the primary management control measurement scales. A second
recommendation is to conduct a study of both business-to-business and business-to-
137
consumer populations within the same study and compare the results. Finally, it could be
useful to conduct a similar stud to this one, with the exception that sales cycle length is
examined as the moderating variable.
From a practical perspective, the findings from this study can help sales managers
drive better salesperson performance. Sales managers can achieve better performance
outcomes, specifically regarding quota attainment, by orienting their behaviors toward
activity control. In addition, sales manager use of activity control may reduce the
negative effects of task complexity on quota attainment by creating clarity of task for
sellers when the means-ends relationships (as is the case in more complex sales) are less
clear.
138
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