Assessing Ethical Influences

Mental Models and Ethical Decision Making: The Mediating Role of Sensemaking

Zhanna Bagdasarov1 • James F. Johnson2 • Alexandra E. MacDougall3 •

Logan M. Steele3 • Shane Connelly3 • Michael D. Mumford3

Received: 10 January 2014 / Accepted: 13 March 2015 / Published online: 19 March 2015

� Springer Science+Business Media Dordrecht 2015

Abstract The relationship between mental models and

ethical decision making (EDM), along with the mechan-

isms through which mental models affect EDM, are not

well understood. Using the sensemaking approach to EDM,

we empirically tested the relationship of mental models (or

knowledge representations about an ethical situation) to

EDM. Participants were asked to depict their mental

models in response to an ethics case to reveal their un-

derstanding of the ethical dilemma, and then provide a

response, along with a rationale, to a different ethical

problem. Findings indicated that complexity of respon-

dents’ mental models was related to EDM, and that this

relationship was mediated by sensemaking processes (i.e.,

cause and constraint criticality, and forecast quality). The

implications of these findings for improving integrity

training in organizations, as well as ultimately under-

standing the role of mental models in EDM, are discussed.

Keywords Ethics � Knowledge � Mental models � Sensemaking � Ethical decision making

Introduction

A great deal of research over the course of several decades

has focused on identifying factors important to ethical

decision making (EDM) in organizational contexts (e.g.,

Craft 2013; Ford and Richardson 1994; Loe et al. 2000;

Tenbrunsel and Smith-Crowe 2008; Treviño et al. 2006).

Among these are individual and organizational variables,

including but not limited to, personality, age, experience,

locus of control, moral awareness and sensitivity, codes of

ethics, significant others, and opportunity (Antes et al.

2007; Craft 2013; O’Fallon and Butterfield 2005). Recent

ethical downfalls in large organizations such as Ameri-

quest, SAC Capital, and countless major banks, as well as

latest statistics from the Ethics Resource Center (2013)

indicating that 41 % of over 6400 responding employees

reported observing ethical misconduct at work, have

heightened our awareness of the need for further research

into both facilitating and hindering factors in EDM. In-

terestingly, although the representation of knowledge in the

form of a mental model has been suggested to underlie

ethical decision making (Mumford et al. 2008), researchers

have yet to investigate the specific impact of mental

models on EDM. Using the sensemaking framework of

EDM (Mumford et al. 2008), our intent in this study was to

examine the relationship between mental models and

EDM, while also investigating the underlying mechanisms

through which mental models exert their influence.

Sensemaking

Problems involving ethical implications are inherently

complex, ill-defined, multifaceted, and implicate multiple

stakeholders (Werhane 2002). Sensemaking can help one

navigate these complexities by triggering a cognitive

& Zhanna Bagdasarov zhannab@csufresno.edu

1 Department of Management, Craig School of Business,

California State University, Fresno, 5245 N. Backer Avenue,

M/S PB7, Fresno, CA 93740, USA

2 Strategic Research & Assessment Branch, Air Force

Personnel Center, Randolph Air Force Base, USA

3 University of Oklahoma, Norman, USA

123

J Bus Ethics (2016) 138:133–144

DOI 10.1007/s10551-015-2620-6

thought process (Mumford et al. 2008; Sonenshein 2007).

This particular form of complex cognition encompasses the

identification of key aspects impacting an ethical decision

and the construction of a mental model incorporating and

representing these important elements. Ultimately, the re-

sultant mental model facilitates decision making and action

(Drazin et al. 1999; Hogarth and Makridakis 1981; Weick

1995). It is imperative to note, however, that an accurate

construction of the mental model is crucial to sensemaking,

and is facilitated via certain sensemaking processes, in-

cluding a thorough identification and analysis of causes and

constraints, and effective short- and long-term forecasting.

These sensemaking processes, in turn, enable a more in-

formed selection and construction of a mental model by

providing a framework for appraisal of downstream con-

sequences and evaluation of the causes and constraints of

the ethical event (Mumford et al. 2006, 2008).

Literature is replete with evidence demonstrating the

value of sensemaking in EDM (Bagdasarov et al. 2012,

2013; Brock et al. 2008; Caughron et al. 2011; Harkrider

et al. 2012, 2013; Johnson et al. 2013; Kligyte et al. 2008;

Stenmark et al. 2010, 2011; Thiel et al. 2013). Specifically,

multiple studies have exemplified the merits of having

people carry out sensemaking processes (i.e., identify cri-

tical causes and constraints of the ethical event, and fore-

cast consequences) when thinking through ethical problems

(Mumford et al. 2001b; Stenmark et al. 2010). In one study

of the impact of forecasting on EDM, investigators asked

participants to assume the role of a manager dealing with

various organizational problems and forecast potential

consequences before resolving the dilemmas at hand

(Stenmark et al. 2011). Results of this study indicated that

identification of possible outcomes was positively related

to more effective ethical decisions. Similarly, Harkrider

et al. (2012) manipulated forecasting content (along with

codes of conduct information) in an ethics case to include

either short- or long-term forecasts, ultimately measuring

participants’ sensemaking and EDM. This study showed

that inclusion of forecasting information in case content not

only enriched the case, but it also resulted in increased

knowledge acquisition, sensemaking strategy use, and

better ethical decisions. In another experimental investi-

gation, Stenmark et al. (2010) asked undergraduates to take

on a role of the key character in various ethical dilemmas,

followed by a task requiring the participants to identify and

analyze key causes, forecast potential consequences, and

make a final decision. Findings of this work indicated that

both forecast quality and identification of critical causes

(two key sensemaking processes) of the problem were as-

sociated with more effective ethical decisions. Likewise,

Johnson et al. (2012) supported Stenmark et al.’s (2011)

findings by manipulating cause complexity in an ethics

case, either embedding causes of high or low complexity as

indicated by the relative number of causes in a case.

Among the many findings in this study, Johnson et al.

(2012) revealed the usefulness of a clear, simple descrip-

tion of causes in an ethics case for the purposes of sense-

making (e.g., forecasting) and EDM. Taken as a whole, the

findings of these and other relevant studies suggest that

application of sensemaking processes results in decisions

of higher ethical caliber. Thus, it is reasonable to suggest

that sensemaking may serve as one mechanism underlying

cognitive relationships with EDM.

Mental Models

Mental models, by nature, represent a particularly complex

form of knowledge displaying the interrelationships be-

tween causal attributes, as well as other key factors in-

volved in a problem (Johnson-Laird 1983). Specifically,

mental models involve a number of concepts and a set of

assumptions regarding the causal relationships between

these concepts (Goldvarg and Johnson-Laird 2001). In-

herent to mental models is the identification of causal re-

lationships among concepts, which, in turn, has been

shown to promote people’s ability to comprehend events

and predict outcomes (Rouse and Morris 1986). As we

discussed earlier, even EDM has been shown to benefit

from identification of key causes and their relationships

(Johnson et al. 2012; Stenmark et al. 2010). Aside from

directing people’s attention to important causal relation-

ships, mental models also allow for forecasting of alter-

native solutions (Doerner and Schaub 1994), and, as

demonstrated on numerous occasions, forecasting has been

shown to be an important sensemaking process for EDM

(Harkrider et al. 2012; Stenmark et al. 2011). The con-

sideration of multiple courses of action according to

Mumford et al. (2008) suggests that ‘‘…mental models used to formulate decision alternatives can be expected to

have a substantial impact on subsequent ethical decision

making’’ (p. 317). Chermack (2003), too, spoke to the

established importance of mental models in critical envi-

ronments. And, although EDM would constitute a complex

cognition known to involve high-stakes consequences in-

herent to critical environments, its relationship to mental

models has yet to be directly examined.

While studies investigating the role of mental models in

ethical decision making have not been conducted, research

pertaining to the importance of mental models in other

complex cognitive processes, such as creative problem

solving, can inform our understanding of the possible role

mental models may play in EDM. This is relevant because

some evidence exists for an association between creative

thought and ethical decision making (Gino and Ariely

2012; Gino and Wiltermuth 2014; Mumford et al. 2010;

Riley and Gabora 2012), suggesting relevance of this

134 Z. Bagdasarov et al.

123

cognitive process to EDM. Furthermore, creative and

ethical problems share many similar features. For instance,

both types of problems commonly have multiple answers,

are bound by numerous constraints, and are characterized

by uncertainty (Mumford et al. 2008).

Laboratory and field research have demonstrated that

knowledge in the form of mental models is, indeed, im-

portant to complex cognitive processes. For example, in a

study examining the role of mental models in creative

problem solving, Mumford et al. (2012) asked participants

to solve either a marketing or an education problem by

generating relevant solutions. Prior to this, the participants

were asked to depict the mental models they utilized to

comprehend the various components of the problem. These

resultant mental models were then assessed using both

objective (e.g., number of concepts, number of causes) and

subjective (e.g., model coherence, completeness, logic)

criteria. Findings indicated that objective and subjective

features of people’s mental models were related to the

quality, originality, and elegance of the ultimate problem

solutions. Authors concluded that knowledge in the form of

mental models is an important consideration in creative

problem solving.

In another experimental investigation, Hester et al.

(2012) showed that knowledge in the form of mental

models is a critical component of creative problem solving.

Participants underwent training in the use of causal rela-

tionships in applying mental models in creative problem

solving. The effect of this training was assessed on both the

mental models and problem solutions. Findings indicated

that causal analysis training culminated in better mental

models (measured via subjective and objective attributes)

and better quality solutions to the creative problems.

Similarly, Barrett et al. (2013) asked participants to de-

velop an advertising campaign for a new energy drink.

Before performing this task, undergraduates were trained in

considering applications of the creative problem solutions

by thinking about the uses of ideas and preparation for idea

implementation. Training in consideration of ultimate ap-

plication contributed to the production of higher quality

campaigns and stronger mental models. Finally, in one

field study by Mumford et al. (2001a), participants were

exposed to a shared mental model using a training inter-

vention prior to developing solutions to a management

problem. As opposed to their untrained counterparts, par-

ticipants who had undergone the training generated solu-

tions of higher quality and originality.

Although work establishing a connection between

mental models and EDM has not yet been conducted, in-

formation regarding the link between mental models and

sensemaking is available. It has been established that

forecasting, an important process in sensemaking, depends

on the mental models applied to specific situations

(Mumford et al. 2008). Well-constructed mental models

aid people in predicting possible outcomes or conse-

quences to complex events (Westbrook 2006). Addition-

ally, individuals’ ability to understand and interpret

information is principally dependent on available mental

models constructed in response to a problem (Westbrook

2006). Mental models are used to make sense out of

complex issues and, thus, trigger sensemaking, which then

facilitate the decision-making process.

Thus, mental models are evident in complex problem

solving in laboratory experiments and field work and have

demonstrable benefits in real-world, complex problem-

solving activities. Mental models also trigger sensemaking,

which, in turn, has an impact on EDM. Given these con-

nections, explicating the influences of mental models on

EDM processes and outcomes is important and we submit

the following hypotheses in that pursuit:

H1 Knowledge in the form of mental models will be

associated with greater ethicality of decisions as assessed

by two measures of EDM.

H2 Sensemaking processes will mediate the relationship

between mental models and ethical decision making.

Method

Participants and Design

To test these hypotheses, a cross-sectional design was

employed. A total of 218 students from undergraduate

psychology courses were recruited using an online ex-

periment management system. Of this sample, 156 were

females and 60 were males, with 2 remaining unidentified.

On average, participants were 19 years of age. All indi-

viduals were given course credit for their voluntary par-

ticipation in this study.

General Procedures

Individuals took part in the study in groups of one to ten

people depending on how many participants had signed up

for any given session (a maximum of ten slots was allotted

for each session).

The experimenter began the study by providing basic

instructions, explaining the nature of the study, and al-

lowing participants to read and respond to the consent

form. During the first part of the study, participants were

asked to complete a brief demographic survey. Following

this, all participants were asked to complete a self-paced

instructional program designed to train individuals in il-

lustrating their mental models. Directly after the training in

model articulation, participants were provided with an

Mental Models and EDM 135

123

ethics case and asked to develop a mental model repre-

senting their understanding of the case and its central

dilemma. Once participants completed generating their

mental models of the ethics case, they were asked to

complete a low fidelity task comprised another ethics case

and questions designed to tap sensemaking processes. Fi-

nally, all participants were given an ethical decision mak-

ing measure which took them roughly an hour to complete.

Training Task

The training task required participants to complete a self-

paced packet of pen-and-paper exercises intended to pro-

vide them with guidelines for illustrating their mental

models. They were asked to work through four modules

contained in the training packet and submit it to the ex-

perimenter when finished.

In the first module, participants were asked to assume

the role of a general manager of a new professional football

team and presented with a problem facing the manager. A

brief description of four key concepts comprising sports

management (i.e., sponsorship, selection of coaches, se-

lection of team members, and direct profits) was provided

along with operational definitions of each element. An il-

lustrative mental model was then presented depicting

causal relationships between these four factors, including

lines portraying connections between concepts, and posi-

tive and negative signs indicating the nature of the rela-

tionships between the concepts. Participants were then

asked to answer two questions about the relationships im-

plied by the diagram.

In a second module, four new concepts were added to

the original elements. These included size of industry,

salary contracts, injuries, and public promotion. Similar to

the first module, these additional concepts were defined and

the relationships between them depicted in a mental model

building upon the original. New elements of mental model

articulation were also supplied in this module. Specifically,

participants were introduced to curved lines to imply a

correlation, multiple lines indicating reciprocal relation-

ships, and use of two pluses and two minuses to indicate

additive positive or negative effects. Again, two questions

were asked of the participants to gage their understanding

of these new elements.

The third module introduced another two new concepts:

stadium quality and fan attendance. These additional con-

cepts were then added to the existing model. Here, par-

ticipants were familiarized with feedback loops in

diagrams and nesting concepts within one another. Once

again, participants were able to exemplify their under-

standing of the mental model by answering two questions

about the implied relationships. Finally, in the fourth

module, participants were given an opportunity to apply

their newly gained knowledge of mental model articulation

by incorporating two additional concepts (competitor

strength and win/loss ratio) into the diagram and redrawing

the final mental model.

Using this scaffolding approach to training, coupled

with hands-on application of the learned material and re-

lated questions, allowed for ample opportunity to gain full

understanding of mental model illustration. Review of

participants’ answers to the questions following each

module and the drawing of the final mental model in

module four suggested that participants had received suf-

ficient training in how to illustrate mental models.

Mental Model Drawing Task

Prior to actually drawing mental models, participants were

asked to read a brief ethics case titled Big Pharma (Ap-

pendix 1 section). A blank page followed the presentation

of the case to provide sufficient space for participants to

illustrate their mental representations of the ethical

dilemma described in the case. All participants were given

time to draw their mental models and were asked to submit

them to the administrator before receiving the next packet

with instructions. Resultant drawings were later appraised

by trained coders. Discussion of coding procedures and

descriptions of variables are provided below.

EDM Task-Based Measure: Sensemaking

Following the reading of the Big Pharma case and depic-

tion of the mental model used to understand that case,

participants were asked to read another ethics case titled

Friendswood City Council and complete seven questions

(Appendix 2 section) designed to tap sensemaking pro-

cesses known to be critical to EDM (Mumford et al. 2008).

For this task, participants were asked to take on the role of

a council member involved in an ethical problem regarding

a new construction project for the town. Directly after

reading this case, participants were asked to respond to

seven questions meant to elicit the use of sensemaking

processes (Appendix 1 section). These included questions

asking participants to identify key causes of the issue,

challenges and constraints, and the possible outcomes. The

final two questions asked participants to make a decision in

response to the ethical problem outlined in the case and

provide a rationale for the decision.

Coding

Four expert raters were tasked with coding all responses for

application of sensemaking processes according to Mum-

ford et al. (2008) sensemaking model of EDM. Prior to

scoring participants’ responses, raters received a thorough

136 Z. Bagdasarov et al.

123

20-hour modified frame-of-reference training (Woehr and

Huffcutt 1994). Training consisted of providing operational

definitions along with benchmarks for each variable and

practicing rating on a randomly selected pool of responses.

A follow-up meeting for calibration purposes was held

1 week after the initial training meeting. Raters were then

given all participants’ responses and allowed to begin

coding. Variables coded are detailed below.

Causes

Two variables were included in the causal analysis and

coded for by trained raters: number of causes and cause

criticality. Number of Causes was assessed using a basic

frequency count, while Cause Criticality was measured

using a 5-point Likert scale (1 = few critical causes

identified, 5 = many critical causes identified). Inter-rater

reliability, assessed using the intra-class correlation coef-

ficient (ICC), was high for both variables (ICC = .93 and

.87, respectively).

Constraints

Two variables were assessed for the constraint analysis:

Breadth of Constraints and Criticality of Constraints.

Breadth of Constraints referred to the extent to which

constraints identified by the participant covered a large

number of factors (i.e., both personal and situational con-

straints) and various elements (i.e., people, tasks, groups,

etc.). This variable was measured on a 5-point Likert scale

(1 = narrow breadth, 5 = very broad). Criticality of

Constraints was defined as the extent to which participants

were able to identify crucial constraints to decisions, and

was also measured on a 5-point Likert scale (1 = few

critical constraints identified, 5 = many critical con-

straints identified). Inter-rater reliability was acceptable for

both variables (ICC = .84 and .79, respectively).

Forecasting

The extent to which participants’ predicted outcomes ap-

plied to the scenario were detailed and realistic, and

demonstrated consideration of critical aspects of the case

was indicated via Forecast Quality. This variable was rated

on a 5-point Likert scale (1 = poor quality, 5 = very good

quality) and resulted in high inter-rater agreement

(ICC = .86).

Decision ethicality

Participants’ decisions were coded for ethicality, which

served as one measure of EDM, on a 5-point Likert scale

(1 = poor ethical decision-making, 5 = very good ethical

decision-making). Decision Ethicality was assessed ac-

cording to three benchmarks: 1) regard for the welfare of

others, 2) attention to personal responsibilities, and 3) ad-

herence to/knowledge of social obligations. Inter-rater

agreement was high (ICC = .87).

Mental model complexity

Participants’ mental model drawings were assessed by the

same coders who rated the EDM task-based responses.

Model complexity was defined as involving an intricate

arrangement of concepts, lines, and arrows. This item was

rated on a 5-point Likert scale (1 = not complex, 5 = very

complex). Inter-rater reliability for this item was also high,

ICC = .89.

EDM Measure

EDM was assessed using two different methods, via the

task-based measure previously described and using an ad-

ditional validated, reliable measure (Mumford et al. 2006).

This measure consisted of 25 multiple-choice questions

and comprised five overarching scenarios that were each

followed by five question items reflecting ethical dilem-

mas. Each question was followed by eight answer choices,

and participants were asked to choose the two most ap-

propriate answers to each ethical dilemma. The answer

items were constructed by subject matter experts on ethics

and experts from various fields in the social sciences and

were structured to differentially reflect high (3), moderate

(2), and low (1) levels of ethical decision making. Par-

ticipant answers were scored by averaging the two selected

responses for each question, which resulted in one nu-

merical representation of EDM.

Results

Analyses

In order to evaluate our hypotheses, we tested two multiple

mediator models using Preacher and Hayes’ (2008) macro

for multiple mediation. Using multiple mediator models

rather than testing each mediator separately allows re-

searchers to provide a more accurate assessment of me-

diation effect (MacKinnon et al. 2007). Specifically, we

assessed the indirect effect of mental model complexity on

two different measures of EDM through five sensemaking

processes (Number of Causes, Criticality of Causes,

Breadth of Constraints, Criticality of Constraints, and

Forecast Quality). Particulars of the findings are discussed

below.

Mental Models and EDM 137

123

The intercorrelations among all variables are shown in

Table 1.

Model 1: EDM Task-Based Ethicality

Multiple regression analyses were conducted to assess each

component of the proposed mediational model using

Preacher and Hayes’ (2008) macro. Three of the five pro-

posed sensemaking processes were revealed as significant

mediators in the first model: Cause Criticality, Constraint

Criticality, and Forecast Quality. Examination of specific

indirect effects indicated that Number of Causes and

Constraint Breadth were not significant mediators since

their 95 % confidence intervals (CI) contained zeros. This

suggested that neither Number of Causes nor Constraint

Breadth contributed to the indirect effect above and beyond

Cause Criticality, Constraint Criticality, and Forecast

Quality. Please review Table 2 for information associated

with each variable.

The first multiple mediation model revealed Cause

Criticality as one significant sensemaking mediator. First,

it was found that mental model complexity was positively

associated with ethicality (c path) (b = .27, t(216) = 3.88, p \ .001). It was also found that mental model complexity was positively related to cause criticality (a path) (b = .39, t(216) = 6.07, p \ .001). Lastly, it was revealed that the

mediator, cause criticality, was positively associated with

ethicality, the dependent variable (b path) (b = .19, t(216) = 2.14, p \ .05). Because both the a and b paths were significant, mediation analyses were tested using the

bootstrapping method with bias-corrected and accelerated

confidence estimates (MacKinnon, Lockwood, and Wil-

liams 2004; Preacher and Hayes 2004). In the present

study, the 95 % CI of the indirect effects was obtained with

5000 bootstrap resamples (Preacher and Hayes 2008).

Results confirmed the mediating role of cause criticality in

the relationship between mental model complexity and

ethicality (b = .07, CI = .0046 to .1675). Mental model complexity was also positively related to

the second significant mediator, Constraint Criticality

(a path) (b = .30, t(216) = 4.89, p \ .001). And, con- straint criticality was also positively related to ethicality

(b path) (b = .35, t(216) = 3.05, p \ .01). Mediation through constraint criticality indicated that it is an impor-

tant, significant mediator between mental model com-

plexity and ethicality (b = .11, CI = .0408 to .1995). Finally, the third significant mediator, Forecast Quality,

was also positively related to the independent variable,

mental model complexity (b = .25, t(216) = 3.97, p \ .001). Additionally, the mediator was positively re- lated to decision ethicality (b = .39, t(216) = 5.64, p \ .0001). Mediation analysis revealed that forecast

Table 1 Correlation matrix Variables 1 2 3 4 5 6 7 8

1 Mental Model Complexity –

2 Decision Ethicality .26** –

3 EDM .18** .40** –

4 Number of Causes .26** .23** .07 –

5 Cause Criticality .38** .51** .29** .68** –

6 Constraint Breadth .29** .52** .17* .33** .49** –

7 Constraint Criticality .32** .59** .29** .23** .53** .86** –

8 Forecast Quality .26** .60** .19** .17* .48** .48** .52** –

* Correlations are significant at p \ .05; ** Correlations are significant at p \ .01

Table 2 Mediation of the effect of mental model

complexity on decision

ethicality through five

sensemaking processes (Model

One)

Sensemaking processes Point estimates Product of coefficients Bootstrapping

BCa 95 % CI

SE Z Lower Upper

Number of Causes -.0063 .0201 -.3133 -.0580 .0328

Cause Criticality .0743 .0364 2.0434 .0046 .1675

Constraint Breadth .0005 .0303 .0155 -.0526 .0657

Constraint Criticality .1071 .0410 2.6129 .0408 .1995

Forecast Quality .0966 .0296 3.2693 .0416 .1692

TOTAL .2722 .0522 5.2198 .1679 .3875

BCa bias corrected and accelerated; 5000 bootstrap samples

138 Z. Bagdasarov et al.

123

quality is an important mediator between mental models

and ethicality (b = .10, CI = .0416 to .1692). Furthermore, results indicated that the direct effect of

mental model complexity on ethicality became non-sig-

nificant (b = -.0012, t(216) = -.02, p [ .05) when con- trolling for all mediators, thus suggesting complete

mediation. The difference between the total and direct ef-

fects is the total indirect effect through all five mediators,

with a point estimate of .2722 and a 95 % CI of .1679 and

.3875, which is different from zero. Thus, taken as a whole,

sensemaking processes mediate the effect of mental model

complexity and decision ethicality (measured via the task-

based measure), suggesting that greater knowledge as

indicated by complexity of one’s mental model leads to

greater usage of sensemaking processes, which, in turn,

leads to greater ethical decision making (Table 2).

Model 2: EDM

The second multiple mediator model tested the mediating

effects of all five sensemaking processes on the relation-

ship between mental model complexity and ethical deci-

sion making. Steps to testing this model remained the same

as those described in the previous section.

First, we checked the c path, or the total effects, of

mental model complexity on EDM, resulting in a positive

association (b = .04, t(215) = 2.66, p \ .01). Following this, examination of specific indirect effects indicated that

three of the five proposed mediators were significant,

Cause Criticality, Constraint Breadth, and Constraint

Criticality. We then found that mental model complexity

was positively related to cause criticality (a path) (b = .39, t(215) = 6.06, p \ .001). Cause criticality, in turn, was positively associated with EDM, the dependent variable

(b path) (b = .07, t(215) = 2.89, p \ .01). We once again present bootstrap estimates based on 5000 bootstrap sam-

ples. Results confirmed the mediating role of cause criti-

cality in the relationship between mental model complexity

and EDM (b = .03, CI = .0084 to .0482).

Mental model complexity was also positively related to the

second significant mediator, Constraint Breadth (a path)

(b = .27, t(215) = 4.47, p \ .0001). However, constraint breadth was negatively related to EDM (b path) (b = -.06, t(215) = -2.11, p \ .05). Results for the indirect effect of constraint breadth indicated that it is a marginally (p = .0533)

significant mediator between mental model complexity and

ethicality (b = -.02, CI = -.0398 to -.0025). Finally, mental model complexity was positively related

to the third significant mediator, Constraint Criticality

(b = .30, t(215) = 4.90, p \ .0001). Additionally, this mediator was positively related to EDM (b = .09, t(215) = 2.85, p \ .01). Mediation analysis revealed that constraint criticality is an important mediator between

mental models and EDM (b = .03, CI = .0084 to .0521). The direct effect, or c-prime path, revealed that the ef-

fect was no longer significant between mental models and

EDM once controlled for all mediators (b = .01, t(215) = .87, p [ .05). This suggests that sensemaking processes fully mediated the relationship between mental

models and EDM. We also calculated the total indirect

effect through all five mediators by assessing the difference

between total and direct effects. This resulted in a point

estimate of .03 and a 95 % CI of .0112 and .0429, which is

different from zero (see Table 3 for full results). Aside

from Constraint Breadth, the directions of the a and b paths

for Cause Criticality and Constraint Criticality are con-

sistent with the interpretation that greater knowledge in the

form of mental models results in greater usage of sense-

making processes, which then leads to better EDM. These

findings were largely consistent with those discovered in

the previous section.

Discussion

Although it has been suggested that knowledge in the form

of mental models may be crucial to effective EDM

(Mumford et al. 2008), previous empirical evidence

Table 3 Mediation of the effect of mental model

complexity on EDM through

five sensemaking processes

(Model Two)

Sensemaking processes Point estimates Product of coefficients Bootstrapping

BCa 95 % CI

SE Z Lower Upper

Number of Causes -.0087 .0056 -1.5460 -.0236 .0016

Cause Criticality .0260 .0098 2.6420 .0084 .0482

Constraint Breadth -.0168 .0087 -1.9323 -.0398 -.0025

Constraint Criticality .0259 .0104 2.4920 .0084 .0521

Forecast Quality -.0011 .0044 -.2534 -.0108 .0074

TOTAL .0253 .0079 3.2010 .0112 .0429

BCa bias corrected and accelerated; 5000 bootstrap samples

Mental Models and EDM 139

123

bearing on this supposition is nonexistent. Moreover, nu-

merous studies have indicated the usefulness of sense-

making in EDM within organizational contexts (Basu and

Palazzo 2008; Maitlis and Sonenshein 2010; Sonenshein

2007; Thiel et al. 2012; Waples and Antes 2011), sug-

gesting that sensemaking may serve as the underlying

mechanism by which mental models exert their influence.

Thus, in the present effort, we tested the relationship be-

tween mental models and EDM and the mediating influ-

ence of sensemaking processes.

Before turning to the broader discussion of this study,

certain limitations should be noted. First, this work was

carried out on an undergraduate student sample. Although

undergraduate students may have encountered ethical

dilemmas or discussed ethics cases in their classes, they

would hardly qualify as experts in this domain. Chermack

(2003) made it clear that there are contexts and expertise

(e.g., airline pilots, air traffic controller) that require very

particular mental models at the outset to prevent catastro-

phes. In these instances, the specific mental models are

assumed to develop over time and with adequate experi-

ence in the given domain. Taking this into account, it is

questionable whether a similar pattern of findings would

emerge in populations having greater expertise in EDM.

Second, mental models were elicited through a con-

ceptual mapping task, where mental models were ar-

ticulated through drawings of interrelated concepts selected

by participants. Although this is a commonly used method,

there are many other tools available for extracting mental

models (Chermack 2003). Future researchers may choose

to replicate and extend our findings using other methods,

such as Carley and Palmquist’s (1992) computer-based

method, or Swanson’s (1994) knowledge task analysis,

among others.

Third, in order to facilitate a structured appraisal of

mental models, we subjected all participants to a self-paced

training program meant to elicit standardized maps.

Although it was apparent that participants benefitted from

the training, it is also of note that such training programs

are not readily available in real-world settings. This, too,

should be considered when generalizing our findings to

other settings.

Finally, we only scored resultant mental models based

on one subjective criterion. Specifically, our expert raters

scored the drawings for the complexity of the model de-

picted by the participants. We recognize that this appraisal

does not capture all possible attributes of people’s mental

models, nor did we venture into assessing the models for

any objective attributes. We encourage future work in this

domain to incorporate both objective and subjective

criteria.

Despite these limitations, the current study produced a

few novel and notable results. Mainly, we demonstrated

that complexity of people’s mental models generated in

response to a convoluted ethics case is positively related to

two distinct measures of ethical decision making. This

finding supports Mumford et al. (2008) proposition that

mental models are likely to have an impact on people’s

ethical decision making. It seems, then, that providing

people with greater knowledge or more expertise is one

important element in effective EDM. It is essential to

recognize, however, that a variety of knowledge structures

exist. This study suggests that one of the knowledge

structures that might be critical to EDM is the mental

model people apply to understand the kind of complex

problems that arise during ethical decision making. Prior

research has already indicated that mental models represent

one form of knowledge influencing people’s performance

on complex cognitive tasks (Mumford et al. 2012). Results

obtained in this study further support those findings in a

new domain.

In addition to the above finding, we also revealed that

the relationship between mental models and EDM is fully

mediated by sensemaking. Specifically, we tested the im-

pact of mental models on EDM through sensemaking

processes (e.g., identification and analysis of causes, con-

straints, and forecasts). Outcomes generally supported the

interpretation that greater knowledge, as indicated by

complexity of one’s mental model, resulted in greater

usage of sensemaking processes, which, in turn, led to

greater EDM. This particular finding is important for a few

reasons. For one, revealing sensemaking as one mechanism

for the relationship between knowledge and EDM carries a

number of implications. Chermack (2003) suggested that if

people’s mental models are revealed to be inadequate for

dealing with the problem at hand, they must be altered.

Changing a mental model is an involved developmental

process requiring learning (Chermack 2003). With this in

mind, training decision makers in sensemaking processes is

likely to lead to the development of more complex mental

models, ultimately positively influencing EDM. Brock

et al. (2008) conducted a study which investigated this

potentiality. These researchers examined mental models of

graduate students (novices in their fields) and faculty (ex-

perts in their fields) six months after subjecting the novices

to sensemaking ethics training, and compared them to a

group of untrained counterparts. Comparison of mental

model structures of trained and untrained novices sug-

gested that the trained individuals produced more cogni-

tively complex mental models. What is more, trained

novices and experts generated similar final decisions re-

garding ethical dilemmas, suggesting the overall effec-

tiveness of sensemaking ethics training in improving one’s

ethical decision-making process. This outcome has great

implications for training in an organizational context.

Specifically, training employees and leaders in sensemaking

140 Z. Bagdasarov et al.

123

would result in greater knowledge, improving resultant

decisions to ethical dilemmas.

It is also important to consider the type of sensemaking

processes revealed to be significant mediators in this study.

Specifically, we found that identification of the most cri-

tical causes and constraints, as well as ability to forecast

downstream consequences, played a vital role in the

knowledge/mental models and EDM relationship. Ex-

trapolating from this, the ability to pick out the most cri-

tical causes and constraints in an ethical dilemma, and to

predict potential consequences, contributes to the con-

struction of a more cognitively complex mental model.

More complex mental models, in turn, are positively as-

sociated with the ethicality of decisions (Brock et al. 2008).

Thus, as models become more complex due to sensemak-

ing, information is bound to become more integrated, and

an increase in knowledge is more likely. With the link

between mental models and EDM made explicit, in the

future, it will be interesting to investigate how nuances in

this relationship may lead to more insight into EDM pro-

cesses, improve EDM outcomes, and might inform prac-

tical applications in training and education.

Appendix 1

Big Pharma

Jason is in his second year, and Robin is just finishing her

first year of postdoctoral training in a cell biology lab

where they share a good working relationship. They have

generous fellowships thanks mostly to their mentor’s en-

terprising associations with the pharmaceutical industry.

Davis, the mentor, performs drug toxicity screening, and

the work requires review and approval by industry scien-

tists before it can be submitted for publication. His uni-

versity objects to this, and has offered to negotiate with the

drug companies for better publication terms, but Davis has

so far refused on the grounds that he has no problem with

the policy and does not want to compromise his reputation

with the industry and the funding it provides for his team of

first rate graduate students and post-docs.

The two post-docs are using different animal models to

test the efficacy of a gene product. It is hoped that this gene

product will interfere with cancer cell-signaling and slow

or arrest meta-static activity. Jason’s results are extremely

encouraging, but Robin’s are not. She confides to her friend

that she is disappointed with her failing project and a year’s

loss in productivity. She is also frustrated because Davis

has hinted that she must be doing something wrong. After

all, Robin is working with the same protein as Jason, and it

is reasonable to expect that her results would at least show

a similar trend.

Jason replies candidly about what he learned in his first

year—that the industry’s emphasis is on getting results. He

points out that if the Davis group does not produce, the

project will be turned over to another team that will, and

the fellowships will follow the money.

What Jason said made sense, but Robin was uncom-

fortable with the implication she thought was being con-

veyed. She made a noncommittal remark and changed the

subject; however, the new information preyed on her mind.

Was she being naively idealistic about science?

Robin continues to feel uncomfortable with the climate

of the lab and her interactions with Jason. She contem-

plates discussing the issue with Davis but fears he will

react just like Jason. Ultimately, she decides that the best

course of action is to not change her results and to leave the

laboratory altogether. When she discusses her resignation

with Davis, he is surprised and asks for an explanation. She

circumvents the real issue, simply telling him that she does

not feel like she fits in very well and would like to take her

career in a different direction. Robin, admittedly, is con-

flicted over her decision to withhold information from

Davis but thinks that she might create a bigger issue if she

shares the entire truth.

Six months later, Robin finds herself in an entry-level

position at a small bio-medical company. She is satisfied

with her current work and is relieved that she no longer

faces the pressures of her previous lab. She is even more

relieved that she left her post-doc position when she re-

ceives word from a former lab mate that Davis’s laboratory

has lost its funding after being investigated by the Office of

Research Integrity on data fabrication charges.

Source Devenport (2005).

Appendix 2

Friendswood City Council

You are an expert building contractor. You have a master’s

degree in civil engineering, and after 20 years of working

as a licensed contractor, you decided to retire. You and

your spouse live in Friendswood, a small community in

which you are very active. You often volunteer your ser-

vices and expertise to local organizations that need your

help. For instance, when city structures are being built, you

often volunteer your expertise as a contractor free of

charge, so that the city can save money. Whenever such

opportunities arise, you are pleased to help because no one

will place restrictions on you or your ‘‘vision.’’ Most of the

time, you enjoy full autonomy to proceed with the projects

as you see fit.

You are on the board of the Friendswood city council.

There are twelve people that make up the council,

Mental Models and EDM 141

123

including you. Members of the city council are elected by

the residents of the city. You feel like the city council

elections have become somewhat of a popularity contest,

and it seems like the members of the council are the

wealthiest members of the community, not necessarily the

people who would benefit the community most. You feel

like some of the members of the city council have no in-

terest in giving back to the community; they just want to

feel important by being a part of this organization.

Recently, two of the members of the council have begun

to feud. Bill Knight and John Cosby got into an argument

over which of them owns a lake that borders both of their

property. The council members have begun to take sides,

and the council is dividing into two factions. It is getting to

the point where city council meetings are not productive.

The meetings always turn into a political forum for Bill and

John to voice why each is right in their arguments.

Furthermore, the in-fighting has caused the members not

to communicate well. There are subcommittees in the

council for various projects, including community

fundraising, maintenance of Main Street, and community

social events. The subcommittees have turned into cliques

that are not communicating their progress to each other,

and communication is essential for productive functioning

of the city council. You think the whole argument is silly,

and you refuse to take sides. You are still able to talk to

most of the council members and the community still

thinks highly of you. You are worried you will not be able

to prevent these conflicts and are doing what you can to

prevent public opinion from turning against you too.

Recently, the city council began looking to fund a

renovation project of your local community center. Be-

cause you are an expert in construction, you designed the

application for constructing companies to bid on this pro-

ject. Furthermore, because you did not want to work

closely with your colleagues on projects, given the in-

fighting, you decided to design the application by yourself.

You were given full autonomy in designing the application

and you applied your expertise to do what would be best

for the community.

You are now a part of the committee reviewing and

approving the proposals. The city has expressed a desire for

the renovations to begin as soon as possible, and you feel

like the committee is rushing the process a little. You are

concerned that you will miss something important in the

review that will result in critical errors that may result in

the city hiring a contractor that is less than satisfactory.

Nine proposals have passed a first screen by meeting the

criteria outlined in the application you designed. You and

several others conducted more extensive reviews of the

nine proposals. The team of reviewers has identified the

winning proposal, which has many outstanding features. As

you scan it one more time, however, you notice that it does

not meet one of the ten criteria used in the initial screening

process; this proposal should never have even made it past

the first round of evaluations. No one else has caught this.

Now you wonder what you should do.

Case Questions

What is the ethical dilemma in this situation?

________________________________________

___________________________________

________________________________________

__________________________________

____________________________________________

_________________________________

___________________________________________

_________________________________

List and describe the causes of the problem.

______________________________________

________________________________________

____________________________________________

__________________________________

_____________________________________________

_________________________________

_____________________________________________

___________________________________

What are the key factors and challenges of this ethical

dilemma?

___________________________________________

___________________________________

___________________________________________

___________________________________

___________________________________________

___________________________________

___________________________________________

___________________________________

What should you consider in solving this problem?

___________________________________________

___________________________________

__________________________________________

__________________________________

___________________________________________

_________________________________

_____________________________________________

_________________________________

What are some possible outcomes of this ethical

dilemma?

____________________________________________

__________________________________

__________________________________________

__________________________________

_________________________________________

__________________________________

142 Z. Bagdasarov et al.

123

_________________________________________

_________________________________

What is your final decision?

_____________________________________________

_________________________________

___________________________________________

__________________________________

___________________________________________

__________________________________

___________________________________________

_________________________________

What was your rationale for making this decision?

__________________________________________

___________________________________

___________________________________________

___________________________________

____________________________________________

____________________________________

____________________________________________

__________________________________

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