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THE ACCOUNTING REVIEW American Accounting AssociationVol. 89, No. 6 DOI: 10.2308/accr-508522014pp. 1979–2010

The Effect of Performance-Based IncentiveContracts on System 1 and System 2

Processing in Affective Decision Contexts:fMRI and Behavioral Evidence

Anne M. Farrell

Miami University

Joshua O. Goh

National Taiwan University

Brian J. White

The University of Texas at Austin

ABSTRACT: Managers may rely on emotional reactions to a setting to the detriment of

economic considerations (‘‘System 1 processing’’), resulting in decisions that are costly for

firms. While economic theory prescribes performance-based incentives to align goals and

induce effort, psychology theory suggests that the salience of emotions is difficult to

overcome without also inducing more deliberate consideration of both emotional and

economic factors (‘‘System 2 processing’’). We link these perspectives by investigating

whether performance-based incentives mitigate the costly influence of emotion by inducing

more System 2 processing. Using functional magnetic resonance imaging and traditional

experiments, we investigate managers’ brain activity and choices under fixed wage and

We are indebted to the staff at the University of Illinois Beckman Institute Biomedical Imaging Center (especially TraceyWszalek, Shelly Yambert, Nancy Dodge, and Holly Tracy) for their help and patience in administering the fMRIexperiment; to Michael Chandler for his programming help and beyond; to Anthony Christodoulou for his fMRI dataanalysis skills; to Radhika Mani and Carol Sung for their volunteer research assistance; to Kurt Bielema for his photo-processing work; to Kimberly Moreno for permission to derive our experiment materials from hers; to John Chandler,Susan Curtis, Adel Ibrahim, Rachel Schwartz, Julie Shapland, and Ken Trotman for help recruiting participants; and toNeal Cohen, Vinod Venkatraman, and Michelle Voss for background on fMRI methodologies. For helpful feedback wethank John Harry Evans III (senior editor), Donald V. Moser (editor), two anonymous reviewers, Jon Grenier, FrankHartmann, Mark Peecher, and Michael Williamson; workshop participants at Iowa State University, University ofNevada, Las Vegas, and The University of Texas at Austin; and participants at the 2012 European AccountingAssociation Annual Congress and the 2012 American Accounting Association ABO Meeting and 2013 MAS MidyearMeeting. We are grateful for significant financial support from the Institute of Management Accountants Foundation forApplied Research and the University of Illinois at Urbana–Champaign Campus Research Board. This study was alsosupported in part by the Intramural Research Program, National Institute on Aging, NIH.

Supplemental materials can be accessed by clicking the links in Appendix C.

Editor’s note: Accepted by Donald V. Moser.

Submitted: May 2013Accepted: June 2014

Published Online: July 2014

1979

performance-based contracts. Under both, brain regions associated with System 1

processing are more active when emotion is present. Relative to fixed wage contracts,

performance-based contracts induce System 2 processing in emotional contexts beyond

that observed absent emotion, and decrease the proportion of economically costly choices.

Keywords: performance-based incentives; affect; dual process models; knowledgeaccessibility; System 1 and System 2 processing; fMRI.

Data Availability: Contact the authors.

I. INTRODUCTION

In his book, Thinking, Fast and Slow, Kahneman (2011) synthesizes research across several

disciplines that suggests decision-makers often make decisions based on ‘‘System 1’’ cognitive

processing, in which they rely on a subset of information made salient by the decision context.

For example, when contextual features of a decision evoke emotion, individuals frequently rely on

those reactions more heavily than on other information (Kahneman 2011; Schwarz and Clore 1983,

2003; Slovic, Finucane, Peters, and MacGregor 2007). In accounting, several studies demonstrate

that managers may rely on affect-based, rather than economics-based, decision rules and, thus,

make choices that are inefficient and, hence, costly for firm owners (Kida, Moreno, and Smith

2001; Moreno, Kida, and Smith 2002; Sawers 2005; Ding and Beaulieu 2011). For example, when

faced with a choice of working on projects proposed by two different colleagues, managers who are

paid a fixed wage frequently choose (or forgo) the project proposed by the colleague they like (or

dislike), even when doing so is less desirable to the firm from an economic standpoint (Kida et al.

2001; Moreno et al. 2002).1

In such settings, firms may want to implement mechanisms that encourage managers to more

carefully consider the decision relevance of both emotional and economic factors—or as Kahneman

(2011, 20–24) describes it, to engage in ‘‘System 2’’ processing. Economic theory suggests linking

managers’ pay to their decisions in order to induce more effort and/or more closely align managers’

goals with those of firm owners and, thus, reduce the frequency of choices that are less

economically desirable (Milgrom and Roberts 1992). However, economic theory does not speak

directly to how more effort or goal alignment reduces or eliminates emotions’ impact on decisions,

and psychology theory suggests that emotions are so salient to decision-makers that their

dominance over other information is difficult to reduce or eliminate (Zajonc 1984, 1998; Lavine,

Thomsen, Zanna, and Borgida 1998; Kahneman and Frederick 2004, 2005; Kahneman 2011). Our

goal in this study is to link the perspectives of both domains to clarify how performance-based pay

mitigates the influence of emotion in managers’ cognitive processing and decisions.

As such, we conduct two experiments—one using functional magnetic resonance imaging

(fMRI), and the other a traditional behavioral approach—to investigate both the activity in

managers’ brains during choice and the choices themselves in emotion-laden and emotion-free

contexts under both fixed wage and performance-based incentive contracts. The fMRI experiment

allows us to compare brain activity and investment choices when participants do or do not have

affective reactions to colleagues under each contract type. Because the fMRI setting necessitates a

within-subjects design and a restricted subject pool, we conduct the behavioral experiment to

examine whether the investment choice results also hold with a between-subjects design and a

broader subject pool in a more natural decision-making setting. In sum, using two approaches to

investigate our research questions provides reasonable convergent validity.

1 We characterize managers’ choices as ‘‘less (more) economically desirable’’ if they are inconsistent (consistent) withthe decision alternative with the highest expected value.

1980 Farrell, Goh, and White

The Accounting ReviewNovember 2014

Our predictions about the effects of emotion and contract type are based in dual process

theories, which distinguish between two types of cognitive processing (Epstein 1994; Kahneman

and Frederick 2004, 2005; Evans 2006, 2008; Lieberman 2007). System 1 processing is more

automatic and reliant on affect and intuition; System 2 processing is more analytic and reliant on

logic and evidence. Dual process theories suggest that while performance-based incentives are

unlikely to eliminate salient affect-based reactions from System 1, they may increase the likelihood

that managers will also engage in System 2 processing by making economics-based decision rules

more accessible and salient. Thus, managers will more carefully consider the relevance of both

affective and economic considerations. We couple these theories with research in neuroscience that

has identified brain regions associated with System 1 (in particular, emotional) and System 2 (in

particular, analytical) processing.

Using fMRI technology offers a unique advantage in testing these ideas over an approach

based on managers’ choices alone. Specifically, fMRI allows us to shed light on whether System 1

processing is present under both a fixed wage and a performance-based contract, and whether

performance-based contracts induce more System 2 processing when managers react emotionally to

decision contexts than when they do not. In other words, we can observe System 1 brain activity

associated with managers’ affective reactions, and System 2 activity that may constrain or eliminate

the impact of those reactions when performance-based pay is used. In contrast, a strictly behavioral

approach to our research questions, based only on decision outcomes, would not open the ‘‘black

box’’ of how emotion and contract type affect cognitive processing.

Participants in both of our experiments act as division managers in a large organization who

must make a series of choices that involve pairs of investment projects proposed by hypothetical

colleagues under a fixed wage and under a performance-based incentive contract. We induce

affective reactions to some of those colleagues, and the pairs of choices are designed so that those

based on affective reactions are less economically desirable.

Our results provide several insights regarding cognitive processes. First, we find that brain

regions commonly associated with System 1 processing show greater responses during investment

choices in which we induced emotional reactions to colleagues, relative to those in which we did

not. Second, we observe this greater response in System 1 regions during affect-laden choices

whether pay is based on a fixed wage or a performance-based contract, suggesting that affective

reactions can persist under performance-based contracts. Third, we find the greatest level of System

2 processing when managers’ pay is based on a performance-based incentive contract and they face

affect-laden decisions. This level of System 2 processing is greater than under an incentive contract

in the absence of affect, consistent with our expectation that it is not the performance-based

incentive contract alone that induces greater System 2 processing. Rather, performance-based

contracts appear to induce more analytical processing precisely when it matters most, i.e., when

managers’ affective reactions are potentially costly to their firms.

With respect to investment choices, we find that when pay is based on either the fixed wage or

the performance-based contract, the proportion of more economically desirable investment choices

is significantly lower when affect is present than when it is not. More importantly, we find that the

proportion of more economically desirable choices is greater when pay is based on a

performance-based contract rather than a fixed wage contract. This proportion is also closer to,

albeit still lower than, the proportion when affect was not present. Taken together, the patterns of

results for both cognitive processes and outcomes suggest that the additional System 2 processing

employed in affect-laden contexts under a performance-based contract leads managers to more

frequently choose investments with more desirable economic returns. However, the influence of

affective reactions on processing and choice is reduced, but not eliminated, by a performance-based

incentive contract.

Effect of Incentive Contracts on System 1 and 2 Processing: fMRI and Behavioral Evidence 1981


We contribute to prior literature in several ways. First, prior accounting research has investigated

the influence of emotion on managers’ decisions, but has generally used settings in which pay was a

flat wage rather than a payment based on those decisions (Kida et al. 2001; Moreno et al. 2002;

Sawers 2005). We extend literature that sheds light on the extent to which incentive contracts can

reduce bias in decision-making (e.g., Ding and Beaulieu 2011) by showing that performance-based

incentive contracts reduce, but do not eliminate, emotion’s impact on choice. Most importantly,

unlike prior accounting literature, our fMRI experiment allows us to provide more direct evidence of

the cognitive processes underlying choice in affect-laden settings. As such, we link theory from

economics and psychology by showing how performance-based pay, a common remedy from

economics, alters cognitive processes in ways that psychology suggests are necessary to overcome or

reduce the costly influence of emotion on decision-making. More broadly, our work suggests that

when managers have conflicting signals about what may be the ‘‘best’’ choice, incentives can prompt

cognitive processing differences that appear to lead to more careful consideration of the weights to

place on those signals. As such, our research helps us understand the effects of contract design on

managers’ cognitive processing and choices that impact firm returns. Firms may prefer that managers

process decision-relevant information more analytically across a wide variety of decisions, and we

provide evidence that performance-based contracts can prompt managers to do so.

Second, we contribute to prior neuroscience research in psychology and economics, which, to

our knowledge, has not examined brain processes in the presence and absence of affective reactions

under different compensation contracts. Related psychology and economics-based neuroscience

studies have generally focused on the neural basis of the experience and control of affect; the

anticipation and experience of gains/rewards and losses/punishments; responses and attitudes to risk

and uncertainty; or the estimation of value.2

Third, we are among the first studies in accounting to use fMRI technology. Barton, Berns, and

Brooks (2014) conduct a contemporaneous fMRI study in financial accounting, while Dickhaut,

Basu, McCabe, and Waymire (2010) and Birnberg and Ganguly (2012) discuss how neuroscience

can contribute to accounting research. We use an fMRI task that includes a richer ecological context

than found in many related neuroscience studies. This allows us to provide more direct evidence of

the cognitive processes underlying choice, and the impact of contract type on those processes in a

rich managerial setting.

II. THEORY AND HYPOTHESES

Affect in Accounting Research

Previous research finds that emotional reactions—both positive and negative—associated with

investment decisions can lead to unpredictable and economically less-desirable budgeting and

investment decisions. Kida et al. (2001) and Moreno et al. (2002) show that managers choose

investment alternatives based on their affective reactions to colleagues, and make decisions that are

both economically less desirable and less predictable (Kahneman and Tversky 1979); in other

2 For reviews of such research, see Bechara and Damasio (2005); Cohen (2005); Knutson and Peterson (2005);Peterson (2007); Loewenstein, Rick, and Cowen (2008); Rick (2011). For work on the experience and regulation ofaffect, see Banks, Eddy, Angstadt, Nathan, and Phan (2007); Barrett, Bliss-Moreau, Duncan, Rauch, and Wright(2007); Berntson, Bechara, Damasio, Tranel, and Cacioppo (2007); Ochsner et al. (2009); Waugh, Hamilton, andGotlib (2010). For work on the anticipation and experience of gains/rewards and losses/punishments, see Elliott,Newman, Longe, and Deakin (2003, 2004); McClure, Laibson, Loewenstein, and Cohen (2004); Tom, Fox, Trepel,and Poldrack (2007); Cooper, Hollon, Wimmer, and Knutson (2009). For work on responses and attitudes to risk anduncertainty, see Smith, Dickhaut, McCabe, and Pardo (2002); Hsu, Bhatt, Adolphs, Tranel, and Camerer (2005);Huettel, Song, and McCarthy (2005); Kuhnen and Knutson (2005). For work on the estimation of value, see Knutson,Taylor, Kaufman, Peterson, and Glover (2005); Rustichini, Dickhaut, Ghirardato, Smith, and Pardo (2005).



words, these studies find that affective reactions cause decisions that are inconsistent with both

normative and descriptive models of decision-making. Sawers (2005) finds that managers’ negative

affective reactions lead them to avoid making difficult decisions even when doing so is costly.

These results suggest that the influence of affect on decisions can potentially have economic

consequences for firm owners.3

In this study, we examine a setting in which division managers in a decentralized firm have

decision rights to engage in capital investment projects. Assuming that firm owners prefer that

managers choose investment projects with higher economic returns, moral hazard arises if managers

forgo potential economic returns because of affective reactions. As such, firm owners may be interested

in ways to encourage managers to more carefully consider their reliance on affective reactions.4

Agency theory prescribes two mechanisms to reduce moral hazard. The first is monitoring, but

this can be costly when decision-making is decentralized (Christie, Joye, and Watts 2003).

Alternately, performance-based incentive contracts can induce effort and better align managers’

goals with those of firm owners (Milgrom and Roberts 1992). We draw on theories of human

information processing to predict how performance-based incentive contracts could moderate the

influence of affect on managers’ investment decisions.

Dual Process Theories of Cognitive Processing

Dual process theories have a long history in psychology (see Evans [2008] for a review). Most

theories distinguish between what we label System 1 processes that are more automatic and

heuristics-based, and System 2 processes that are more deliberate and logical.5 Epstein (1994)

details characteristics of each of the systems, which we summarize in Table 1. For our purposes, a

key difference is that System 1 processing relies on affective reactions as inputs to a decision, while

System 2 relies on logic and reason.

Of the many dual process models in the literature, ‘‘default-interventionist’’ models (Kahneman

and Frederick 2004, 2005; Evans 2006, 2008) are often viewed as the most descriptive of

individuals’ cognitive processing given the existing evidence (e.g., Schwarz and Clore 1983;

Schwarz 1996; Finucane, Alhakami, Slovic, and Johnson 2000). A depiction of a default-

interventionist model is in Figure 1. According to the model, System 1 is the default decision-

making system; System 2 processing can override System 1 processing, but System 1 cannot be

switched off even with a System 2 intervention. The processing associated with System 1 can be

highly efficient, but can also lead to lower-quality decisions, since judgments are based on

heuristics in which an initial judgment is formed by applying immediately accessible mental models

or rules of thumb based on an incomplete set of information.

One such heuristic is called ‘‘affect as information’’ or simply the ‘‘affect heuristic’’ (Schwarz

and Clore 1983, 2003; Slovic et al. 2007). When affective reactions are triggered by contextual or

task features, System 1 will generate a default response based on emotion. This is consistent with

the view in psychology that reactions based on affect often dominate those based on other

information (Zajonc 1984, 1998; Lavine et al. 1998; Kahneman and Frederick 2004, 2005). Further,

3 We do not assert that the influence of affect is always costly, or that affect cannot convey useful information. Indeed,incorporating affective reactions may result in choices that are consistent with those desired by firms’ owners and canbe beneficial in other ways—for example, if it leads ordinarily risk-averse managers to make beneficial risk-neutralchoices. Nevertheless, performance-based incentive contracts are widely used in practice, and firms may believe thatperformance-based contracts are better than fixed wage contracts because performance-based contracts induce effort.As such, firms are likely interested in how these contracts influence decision-making in affective contexts.

4 We acknowledge that from a manager’s perspective, it may be rational to make decisions based on affective reactionsto maximize his or her total utility. However, our focus is on potential firm-level costs of managers doing so.

5 In some literature, System 1 processing is called ‘‘experiential,’’ ‘‘automatic,’’ or ‘‘affective’’ processing, while System2 processing is called ‘‘rational,’’ ‘‘controlled,’’ or ‘‘deliberative’’ processing.



results from prior research in which managers make investment decisions in settings similar to ours

(Kida et al. 2001; Moreno et al. 2002) suggest that managers may rely on affect-based heuristics

rather than economic reasoning.

System 2 has two roles. First, it plays a supervisory role, deciding whether to endorse the

judgment of System 1. System 2 is not infallible, so some such endorsements could result in poor

judgments. When System 2 endorses (or fails to intervene in) the judgment of System 1, affective

reactions are likely to be weighted more heavily in the judgment, regardless of the relevance of the

affective information to the judgment. Second, when System 2 does intervene, it engages in more

deliberative processing before arriving at a judgment, and if the judgment is different, then it

replaces the judgment formed by System 1. However, when System 2 intervenes in processing,

System 1 does not ‘‘shut down’’ such that decision-makers ignore affective information; rather, it

increases the likelihood that decision-makers will more carefully consider the weight to put on

affective and other information in forming a judgment. In our setting, if firm owners want managers

to shift weight from affective reactions to economic considerations, then their problem becomes

how to increase the likelihood that System 2 will intervene in processing.

Whether System 2 intervenes depends on individual differences like general intelligence, and

environmental factors like the time available to make a choice, as well as on the accessibility of

relevant knowledge structures (Evans 2008). We assert that the accessibility of relevant knowledge

structures influences perceptions of what Evans (2006) calls the ‘‘instructional set.’’ While this set

may include explicit instructions to process information more or less analytically, it may also

include the decision-maker’s understanding of the nature of the task and the process required in

order to complete it successfully. For example, in our capital investment setting, a System 2

intervention depends on whether the manager recognizes (consciously or unconsciously) that a

reasoned weighting of affective and economic information, rather than a heuristics-based reaction,

is necessary to arrive at a decision.

Knowledge Accessibility and System 2 Processing

Models of knowledge accessibility suggest that contextual features of a setting can make

relevant stored knowledge more accessible to a decision-maker (e.g., Collins and Loftus 1975;

TABLE 1

System 1 and System 2 Processing ComparisonAdapted from Epstein (1994)a

System 1 System 2

Holistic Analytic

Affective; pleasure-pain oriented Logical; reason oriented

Associationistic connections Logical connections

Behavior mediated by ‘‘vibes’’ from past experiences Behavior mediated by conscious appraisal of events

Encodes reality in concrete images, metaphors,

and narratives

Encodes reality in abstract symbols, words,

and numbers

More rapid processing; oriented toward immediate

action

Slower processing; oriented toward delayed action

Self-evidently valid; ‘‘experiencing is believing’’ Requires justification via logic and evidence

a This table summarizes and compares features of System 1 and System 2 processing commonly noted in dual processmodels of cognitive processing.



Wyer and Srull 1986), and supporting evidence has been found in psychology and accounting

studies (e.g., Fazio and Williams 1986; Posavac, Sanbonmatsu, and Fazio 1997; Bargh and

Ferguson 2000; Denison 2009). In addition, studies suggest that contextual features of a decision

can increase the likelihood of a System 2 intervention during decision-making (e.g., Schul and

Mayo 2003; Godek and Murray 2008).

We predict that in our investment decision setting, a performance-based contract will induce

managers to incorporate economics-based decision rules into their choices. By their very nature,

performance-based incentive contracts prompt analytical processing by basing compensation on

quantitative measures of performance such as profit margins, hurdle rates, or expected values. Such

measures serve as inputs into economic decision models and, thus, increase the probability that

FIGURE 1System 1 and System 2 Processing Model

Adapted from Evans (2006)a

a This figure provides a graphical representation of how decision inputs are cognitively processed to form a choice usingSystem 1 and System 2 processing, according to dual process theories.



economic decision rules for investments become more salient and accessible, thereby increasing the

likelihood that System 2 will intervene in the decision process.

Dual Processes in the Brain

Neuroscience research has identified regions of the brain associated with System 1 and System

2 processing that are relevant to our setting. For example, the insula is associated with negative

emotions like anger and disgust (Sanfey, Rilling, Aronson, Nystrom, and Cohen 2003), supporting

its involvement in System 1 processing. By contrast, the lateral prefrontal cortex (in particular, its

middle frontal region) is associated with effortful and deliberative processing tasks, including

reasoning, logic, mathematics, and cause and effect (Satpute et al. 2005; Satpute and Lieberman

2006), and is, thus, associated with System 2 processing.6

This mapping of System 1 and System 2 processing regions is subject to two caveats. First,

distinguishing between two processing systems in the brain is a coarse (albeit useful) classification

system; prior research provides insights into which brain regions may be associated with different

types of processing, but the work of associating brain regions with processing type is constantly

evolving. Second, System 1 and System 2 should not be viewed as distinct, but rather as

overlapping and interactive (Satpute and Lieberman 2006).

Taken together, prior literature on the dual process framework, knowledge accessibility, and

the brain regions associated with System 1 and System 2 processing lead us to two predictions:

H1a: Under both a fixed wage and a performance-based incentive contract, brain regions

associated with System 1 processing will be more responsive during decision-making in

affective decision contexts than in non-affective decision contexts.

H1b: Under a performance-based incentive contract, brain regions associated with System 2

processing will be more responsive during decision-making in affective decision

contexts than in non-affective decision contexts.

Performance-Based Incentive Contracts, Affect, and Choice

We also consider the joint effects of contract type and affective reactions on managers’

investment decisions. Recall that we expect performance-based incentive contracts to increase the

accessibility of economic decision rules. When judgments made on the basis of an affect heuristic

differ from those made based on economics-based rules, increasing the accessibility of these rules

should result in a higher frequency of more economically desirable choices under a performance-

based incentive contract than a fixed wage contract. Thus, since we expect performance-based

incentive contracts to induce System 2 processing and reduce the costly influence of affect on

decisions, we expect to observe a greater proportion of economically desirable choices under such a

contract. This predicted interaction is shown in Figure 2, Panel A:

H2: In affective decision contexts, managers will make a higher proportion of economically

desirable choices under a performance-based incentive contract compared to a fixed wage

contract (A . B in Figure 2, Panel A), and there will be a smaller difference between the

proportion of these choices in affective than non-affective contexts ((C�A) , (D� B) in

Figure 2, Panel A).

6 For the sake of brevity, we defer further discussions of specific System 1 and System 2 brain regions until we discussthe results of our fMRI experiment. For detailed analyses of regions thought to be associated with System 1 andSystem 2 processing, see Satpute and Lieberman (2006), Lieberman (2007, 2009), and Sanfey and Chang (2008).



FIGURE 2Hypothesis 2

Proportion of More Economically Desirable Choicesa

Panel A: Prediction

Panel B: Results

a Panels A and B graphically present the predictions and results, respectively, for H2, which predicts that the

frequency with which managers choose more economically desirable alternatives depends on contract type (i.e.,

either a fixed wage or a performance-based incentive) and the presence or absence of affective reactions to decision

contexts. In Experiment 1, graduate business student participants made 90 investment choices twice, under a fixed

wage contract and under a performance-based contract; in Experiment 2, a different group of graduate business

students made two investment choices under either a fixed wage or a performance-based contract. Choices were

coded 1 (0) if the project with the higher expected economic value was (was not) chosen.



III. RESEARCH DESIGN OVERVIEW

Overview of Both Experiments and Research Setting

To test our hypotheses, we conducted two experiments that together provide a reasonable level

of convergent validity. Experiment 1 used fMRI to gather data on individuals’ brain activity and

investment choices under both a fixed wage and a performance-based contract. Experiment 2 used a

traditional behavioral experiment with a richer context to gather data on investment choices under

the two contracts. The fMRI technology used in Experiment 1 provides a more direct test of System

1 and System 2 processing than would self-insights into decision processes (Evans 2005) and

allowed us to simultaneously observe brain activity and choices. Experiment 2 mitigates concerns

about limitations that arise from Experiment 1’s design and provides evidence that our investment

choice results from Experiment 1 hold in a richer, more natural context.

In both experiments, participants assumed the role of a division manager in Universal

Incorporated, a large manufacturing organization. They had worked for the company for a long

time, and were known to be among the top-performing managers in the company. As division

managers, one of their roles was to evaluate potential investments in projects their division could

undertake with other Universal divisions; these potential investments were proposed by managers

of the other divisions. Participants were told that because resources were limited, they had to be

selective about which projects they chose. Participants were also provided with background and

other financial information relevant to their investment decisions.7 Affective reactions to some, but

not all, hypothetical managers of other divisions were induced, and participants made choices

between pairs of investment projects proposed by these managers.8 The inducement of affect, the

design of the investment choices, and other procedures varied across experiments. We provide more

details with each experiment, and include a table of design choices for both experiments in

supporting online materials (see Appendix C for the downloadable Word document). Important

differences are highlighted in the next section.

Comparing Design Choices between Experiments

Two important features of measuring brain activity with fMRI drove many of our Experiment 1

design choices. First, fMRI uses the blood oxygenation level-dependent (BOLD) signal to proxy for

neural activity in the brain when an individual processes a stimulus (in our setting, an investment

choice). The BOLD signal measures the ratio of oxygenated to deoxygenated blood in different

regions of the brain; regions that are activated in response to a stimulus require higher levels of

oxygenated blood and, thus, BOLD signals are stronger. A BOLD signal peaks after five to six

seconds and lasts for 12 to 20 seconds. Second, regions of the brain are constantly active to

maintain basic functioning and in response to many different environmental stimuli, but patterns of

this ‘‘baseline’’ activity differ significantly across individuals (Purves et al. 2008, 74–77; Gazzaniga,

Ivry, Mangun, and Steven 2009, 154–156). As such, each individual’s pattern of baseline brain

activity must serve as a control that can be ‘‘subtracted out’’ from activity in response to a stimulus

of interest.

7 The financial information included the initial investment required for projects, time to completion, and the target (i.e.,hurdle) profit rate and amount.

8 To increase the likelihood that our participants would react similarly to participants in previous studies, we derivedour materials from Moreno (1998) with permission. While we are interested in the effects of affect regardless of itsnature, we induced both positive and negative affect since prior research has found that managers’ investment choicesmay differ across the two (e.g., Kida et al. 2001; Moreno et al. 2002).



Given these two features of fMRI, several design choices were essential to capture a pattern of

brain activity across multiple participants that could be reasonably attributed to the treatment stimuli

rather than to other factors. First, because of the short duration of the BOLD signal, each investment

choice had to be presented for a short duration and, thus, had to be stripped of as much context as

possible. Therefore, we provided task context and induced affective reactions before participants

entered the fMRI scanner, and provided only limited information in the scanner. To ensure that

affective reactions would remain salient during the in-scanner portion of the task, we provided

photos of the managers with their descriptions, and provided brief reminders about the managers

twice in the scanner.9

Second, due to significant individual differences in baseline brain activity, we manipulated

contract type on a within-subjects basis so participants could serve as their own controls. In fMRI

research, a within-subjects design is the ‘‘gold standard’’ to control for individual differences in

baseline responses in BOLD signals.10 Thus, participants made the same set of investment choices

twice, once under a fixed wage contract and once under a performance-based contract.11 We

acknowledge that our within-subjects design could make affective reactions under a fixed wage

contract so salient that they overwhelm the economic incentives of a performance-based contract.

However, this works against finding the predicted increase in the proportion of more economically

desirable investment choices with the latter contract. In addition, in Experiment 2, we manipulate

contract type between subjects to mitigate this concern.

Third, to eliminate differences in brain activity that could be attributed to handedness, gender,

or language processing, we recruited only right-handed, male, native English speakers to

participate. As with the use of a within-subject design, this choice allowed us to control for

incidental participant-specific differences that were unrelated to our research questions.

To mitigate concerns about limitations that arise from our fMRI design choices, we conducted

Experiment 2 to provide additional evidence about investment choices (H2). First, in Experiment 2,

participants had no time constraint to make only two investment choices that each included more

contextual information to mitigate concerns that decision outcomes would differ in more natural

settings. Second, we manipulated fixed wage and performance-based contracts between subjects to

rule out the possibility that salient affective reactions, salient economic considerations, or the order

of the contract type manipulation in Experiment 1 drove differences in investment choice across

contract types. Third, we induced affective reactions to managers immediately prior to each

investment choice, rather than well before the task as in Experiment 1, to provide a more powerful

manipulation and reduce concerns about the dissipation of affect over time. Fourth, we did not

present photos of hypothetical managers to rule out the possibility that photos drive investment

choices. Fifth, we recruited participants without regard to handedness, gender, or native language to

test whether the pattern of decision outcomes holds in a broader population.

Comparing Participants between Experiments

Participants in both experiments were full-time graduate business students, and all provided

informed consent as required by the local Institutional Review Board. Although some previous

studies have used practicing managers as participants (e.g., Kida et al. 2001; Moreno et al. 2002;

9 Adaval, Isbell, and Wyer (2007) provide evidence that affective reactions to, and the comprehension of, descriptiveinformation are stronger when the information includes an accompanying photo.

10 For example, Goh, Suzuki, and Park (2010) examine differences in neural reactions to faces in older and youngeradults. While brain activity in response to faces might differ systematically between older and younger adults, the keycomparisons in the study were within the same age group rather than across age groups.

11 While participants made the same set of choices twice, the order of the choices within each set differed across thefixed wage and performance-based contracts.



Sawers 2005), our graduate business students provide a reasonable proxy for practicing managers

because there is no theoretical reason to predict that the behavior of managers and graduate business

students would differ in systematic ways in our decision setting (Peecher and Solomon 2001).

Further, given the time and location constraints of Experiment 1, it was not practical to use

practicing managers as participants.

Participants in Experiment 1 were 30 healthy, right-handed, male, native English-speaking

graduate business students, with no health concerns for MRI scanning. Of the 30, three did not

complete the in-scanner part of the task due to claustrophobia or discomfort, and three moved

excessively in the scanner but completed all parts of the task. Thus, analyses of brain activity are

based on the 24 participants for whom we have a complete set of readable brain scans, and analyses

of investment choices are based on the 27 participants who completed the task.

Of the 27 participants, 18 were Master’s of Accountancy students and nine were M.B.A.

students. Twelve participants (44 percent) had full-time work experience, averaging 19 months.

Participants reported that they understood their task (mean of 8.8, using a scale anchored on 0 [10]

¼ extremely unclear [clear] instructions) and were familiar with making similar investment

decisions (mean of 6.3, using a scale anchored on 0 [10] ¼ extremely unfamiliar [familiar]). On

average, participants earned $43.62.12 The average time to complete all parts of the task was

approximately 105 minutes, of which approximately 55 minutes was in the MRI scanner.13

Participants in Experiment 2 were 96 graduate business students from four Master’s programs

who did not participate in Experiment 1, of whom 28 (29.2 percent) had full-time work experience

averaging 25 months. Participants reported that they understood their task (mean of 9.0, using a

scale anchored on 0 [10] ¼ extremely unclear [clear] instructions) and were familiar with making

similar investment decisions (mean of 7.3, using a scale anchored on 0 [10]¼ extremely unfamiliar

[familiar]). Participants earned $16.54, on average, and took approximately 40 minutes to complete

the task.

IV. EXPERIMENT 1

Setting and Procedures

Recall from Section III that participants acted as division managers whose task was to evaluate

potential investment projects that their division could undertake with other divisions in their

company. We induced affective reactions to some colleagues who proposed those projects, and

manipulated contract type within subjects.

Experiment 1 consisted of four sections: a pre-scanner section that described the setting and

task and induced affective reactions to colleagues; two in-scanner sections for the investment

choices—one for a fixed wage contract and one for a performance-based contract; and a post-task

section for follow-up questions and payment processing.

Pre-Task Section

Each participant reported to an office in the MRI scanning facility at a prearranged time. He

was situated in a mock fMRI scanner to complete a mock choice task to ensure he was comfortable

12 Descriptive statistics are similar for the subset of 24 participants for which we have readable brain scans.13 As a point of comparison, we reviewed total in-scanner time in ten other fMRI studies (all of which are cited as

references elsewhere in the paper). In these studies, participants spent between 12 and 60 minutes in the fMRIscanner. Four studies report in-scanner time of 45 minutes or longer. Thus, 55 minutes is within the normal range ofin-scanner time for studies in this area, albeit at the upper end of the range.



and familiar with the setting he would encounter in the actual scanner. The participant then had to

elect to continue with the experiment.

The participant was then given information on the setting described in Section III, the format of

the investment choices he would see in the task, and the time he would have to make each choice in

the fMRI scanner. Next, the participant was introduced to six other hypothetical division managers

(hereafter, the familiar managers). Using photos, names, and prose describing interactions with

these managers, we induced affective reactions to four (the affect managers—two positive and two

negative; see Appendix A for a sample), but not the other two (neutral managers). The participant

then answered six questions for each of the affect managers to measure the extent to which the

inducement of affect was successful and in the desired directions. Finally, the participant had to

successfully match the names and descriptions of each familiar manager to their photos to ensure

the information was internalized. He was then escorted to the basement of the facility to complete

the in-scanner sections of the task.

In-Scanner Sections

After undergoing a safety check, the participant was situated in the scanner and began the in-

scanner sections of the task, in which he made investment choices under both contract types.

Investment choice design and presentation for both in-scanner sections. To create

investment choices, we used 21 black-and-white portrait photos of middle-aged white males in

business suits to portray hypothetical managers. Six of the manager photos were assigned to the

familiar manager set described earlier (four affect and two neutral managers), and 15 to the

unfamiliar manager set (to whom we did not induce affective reactions—i.e., neutral managers).14

To create the investment choices, we paired the six familiar managers with each of the 15

unfamiliar managers for a total of 90 different investment choices—30 choices each for positiveaffect, negative affect, and neutral affect. By including familiar neutral managers with familiaraffect managers in pre-task materials and then using these managers for the in-scanner investment

choices, we control for brain activity induced by familiarity alone.

For each investment choice, participants were presented with a screen divided into two sides

(see Appendix B for a sample). Each side included a photo of a manager (one familiar manager, the

other unfamiliar), a pie chart showing possible profit outcomes and respective probabilities for that

manager’s proposed project, and the expected profit for the proposed project.15 At the top of the

screen, the words ‘‘left button’’ and ‘‘right button’’ reminded participants to press the button held in

the hand that corresponded to their choice of project. Familiar and unfamiliar managers appeared

on the left and right sides of the screens with the same frequency.

14 Restricting the photos to be of the same gender, race, age, style of dress, background, etc., controls for brain activitythat is unrelated to our manipulations. To ascertain which photos from a large set provided elicited the strongestaffective responses, we surveyed 13 men who worked in a business field and who did not participate in theexperiments. We asked respondents: (1) to list which photos they thought depicted the four most attractive and thefour least attractive men, (2) ‘‘If you had heard positive things about a man, but had never met him or seen his picture,which two photos would make you like him even more?’’ and (3) ‘‘If you had heard negative things about a man, buthad never met him or seen his picture, which two photos would make you like him even less?’’ We based our choicesof photos for the six familiar managers on a compilation of survey responses; in particular, we chose photos for thepositive and negative affect managers to increase the strength of our affect manipulation, and to aid recall of thefamiliar managers given the length of and uncomfortable environment for the fMRI task. We then selected photos forthe unfamiliar managers to provide a variety of neutral and smiling expressions, as was the case in the photos for thefamiliar managers; thus, regardless of familiarity or affect, we attempted to control for the effects of facial expressionson brain activity.

15 Expected profit for the proposed projects was provided so participants did not need to compute it (which might itselfinduce System 2 processing and, thus, confound our ability to make inferences about System 2 processing effects ofcontract type).



For all investment choices with a positive affect manager, the project with the higher expected

economic profit was the one proposed by the unfamiliar manager he was paired with. For all

choices with a negative affect manager, the project with the higher expected economic profit was

always the one proposed by him rather than the unfamiliar manager he was paired with. Thus,

choices based on affective reactions were inconsistent with maximizing expected economic returns

and were costly to the firm. Since our research questions focus on contexts in which affect-based

decisions are potentially costly, we did not include pairings of unfamiliar neutral managers or affect

managers alone.

Each investment choice was displayed for eight seconds, during which the participant could

respond by pressing the button in his left or right hand. When a participant made a choice, text

appeared that read, ‘‘Your choice has been recorded,’’ but the investment choice remained on the

screen for the full eight seconds. Consistent with norms for the presentation of stimuli in fMRI

research, the investment choices were organized into ‘‘runs’’ and ‘‘blocks.’’ Technical specifications

and protocols for the MRI scanner and a sample block of investment choices are included in

supporting online materials.

Fixed wage contract section. After being situated in the scanner, but before making

investment choices, the participant viewed a single screen of photos and brief summaries of prior

interactions with the four affect managers. He was then told he would receive a fixed wage of $25

for the first set of investment choices in the task (the fixed wage contract type). He then proceeded

to make those investment choices.

At the end of the fixed wage portion of the experiment, the participant remained in the scanner,

but had a break of about seven minutes. During this time, structural scans of the participant’s brain

were taken while the participant watched a distractor animated video, Pixar’s For the Birds, that

was chosen since it was engaging, but unlikely to elicit emotional reactions.

Performance-based incentive contract section. Next, the participant again reviewed a single

screen of photos and brief descriptions of prior interactions with the affect managers. Details of the

performance-based contract were then provided. Specifically, participants were informed that for a

given project choice, they were eligible for a bonus equal to 10 percent of the profit the project

earned that was above a hurdle rate, and that their actual pay would be based on four projects

chosen from the set of 90. However, participants were not told which four choices would be used so

they had incentives to make the more economically desirable choice for each trial (additional details

of this manipulation are available in supporting online materials).

Participants then proceeded to make investment choices under the performance-based contract.

These choices were the same 90 choices used in the fixed wage section of the task, but the blocks

and the trials within the blocks were reordered to reduce the likelihood that participants would

remember and simply repeat their responses from the fixed wage section.

Post-Task Section

Following the second set of investment choices, the participant was escorted back to the office

where the experiment began. There, he completed paper-and-pencil materials that included

questions about what he focused on when making investment choices in the scanner, post-task

measures of affective reactions, questions about perceptions of the task, and demographic

information. The participant was then paid in cash before leaving the facility.16

16 For ease of administration, performance-based pay for all participants was based on their choices in the same fourtrials. If participants chose an investment with probabilistic outcomes, then a random number generator was run intheir presence to determine the actual project outcome.



Experiment 1 Results

Manipulation Checks

To ensure that participants reacted affectively to our affect managers, we compare mean

responses to three positive affect measures (happiness, liking, and elation) and two negative affect

measures (anger and frustration) to 5, the midpoint of the scale used to elicit these measures (where

higher values mean stronger reactions).17 For the two positive affect managers, average responses to

the positive (negative) affect measures were significantly above (below) the midpoint of the scale,

both before and after participants made investment choices in the scanner (overall positive mean¼8.65, overall negative mean ¼ 0.32, all p , 0.05, one-tailed). Further, for the two negative affectmanagers, average responses to the positive (negative) affect measures were significantly below

(above) the midpoint of the scale, both before and after participants made investment choices

(overall positive mean¼ 2.06, overall negative mean¼ 6.39, all p , 0.05, one-tailed). Thus, affectmanagers elicited the intended reactions, and participants experienced these reactions toward these

managers for the duration of the experiment.

To examine whether participants’ reported affective reactions intensified or diminished during

the course of the experiment, we also compare pre- and post-scanner measures of affect. Results

indicate that participants’ positive affective reactions toward positive affect managers are slightly

lower, but still highly positive, after making investment decisions (pre-scanner mean¼ 8.96, post-

scanner mean ¼ 8.35, p ¼ 0.01, two-tailed). Participants’ negative affective reactions toward

negative affect managers showed no significant differences between the pre- and post-scanner

measures (pre-scanner mean ¼ 6.57, post-scanner mean ¼ 6.20, p ¼ 0.24, two-tailed), suggesting

that participants’ affective reactions toward these managers did not change significantly during the

course of the experiment.

To ensure that participants understood our manipulation of contract type, they verbally verified

that they understood how they would be compensated under the performance-based contract before

proceeding with their investment choices. In addition, in post-task questions, we asked how clear

task instructions were; the mean response of 8.8 on an 11-point scale (where 0 [10] ¼ extremely

unclear [clear]) suggests that participants found the task easy to understand.

Hypothesis 1 Results

Dependent variable for brain image analysis. Brain images were processed and analyzed

using protocols that are common in fMRI research (technical details are provided in supporting

online materials). Two steps were required to develop a whole-brain analysis to test for statistically

significant differences in brain activity for decisions involving affect managers and those involving

neutral managers under each of the contract types. First, images based on each participant’s BOLD

responses were developed for six groups: (1) fixed wage/positive affect (POSFW); (2) fixed wage/

negative affect (NEGFW); (3) fixed wage/neutral affect (NEUTFW); (4) performance-based/positiveaffect (POSPB); (5) performance-based/negative affect (NEGPB); and (6) performance-based/

neutral affect (NEUTPB).

Second, these responses were fed into a group-level analysis that used t-tests to identify brain

regions that responded more to affective relative to neutral investment choices under fixed wage and

performance-based contracts. Specifically, we identified: (1) regions more active for affective

17 We also measured fear of affect managers. However, we exclude fear from our negative affect measure because priorresearch indicates that fear is distinct from other negative emotions, and we did not expect our affect managers toelicit fear in participants (Lerner and Keltner 2000). Consistent with this, responses to the fear measure weresignificantly lower than the midpoint of the scale (indicating disagreement) for all affect managers, both before andafter making choices in the scanner (all p , 0.01, two-tailed).



stimuli relative to neutral stimuli during investment choices made under the fixed wage contract, or

[(POSFW þ NEGFW) � NEUTFW], and (2) regions more active for affective stimuli relative to

neutral stimuli during investment choices made under the performance-based contract, or [(POSPB

þ NEGPB) � NEUTPB]. Thus, investment choices involving only neutral managers serve as a

baseline to control for processing that was not associated with our manipulation. As such, the

resulting images show brain activity in decisions involving affect managers that is above and

beyond that observed for decisions involving neutral managers.

A color figure provided with the supporting online materials (hereafter, ‘‘online figure’’) depicts

the results of the whole-brain analysis (see Appendix C for the downloadable figure). Shaded areas

indicate brain regions that responded more to affective stimuli relative to neutral stimuli while

making investment decisions under the fixed wage contract (in red) and the performance-basedcontract (in blue). We combine these into one figure so regions that overlap across the two contract

types are evident (in purple shading, which we predict to be primarily regions associated with

System 1 processing). Table 2 lists the peak coordinates of these regions in affective relative to non-

affective decision contexts for each contract type that is the basis for the figure.

Results for H1a. H1a predicts that under both a fixed wage and a performance-based contract,

brain regions associated with System 1 processing will be more responsive during decision-making

in affective decision contexts than in non-affective contexts.

As predicted in H1a, several regions associated with System 1 processing showed greater

response to affective relative to neutral stimuli during investment choices made under the fixedwage contract (online figure, red and purple shading). First, the superior medial frontal/anterior

cingulate (online figure, region a) is involved in emotional processing, and interacts with other

System 1 areas (Gazzaniga et al. 2009, 383). Second, the posterior cingulate/precuneus and the

bilateral (i.e., left and right) angular gyri (online figure, regions b and c) function in parallel with

other System 1 regions and are associated with introspective and social cognitive processes,

including intuition and framing effects (Bechara, H. Damasio, Tranel, and A. Damasio 1997; Deppe

et al. 2005; Buckner, Andrews-Hanna, and Schacter 2008). Third, bilateral inferior temporal

regions (online figure, region d) are associated with visual perception (especially faces) and person

recognition (Miyashita 1993; Purves et al. 2008, 489). Fourth, the left inferior insula (online figure,

region e) is associated with negative emotions such as anger and disgust (Sanfey et al. 2003).

During choices made under the performance-based contract, many of these same System 1 regions

similarly showed greater responses to affective relative to neutral stimuli (online figure, purple

shading, regions a, b, and c).18 These results support H1a, indicating that brain regions associated

with System 1 processing were more responsive to affective than to neutral stimuli under both fixed

wage and performance-based contracts.

Results for H1b. H1b predicts that under a performance-based contract, brain regions

associated with System 2 processing will be more responsive during decision-making in affective

compared to non-affective decision contexts.

In support of H1b, several additional brain regions associated with System 2 were more responsive

during processing of affective, relative to neutral, choices under the performance-based contract (online

figure, blue shading).19 First, the bilateral middle frontal region of the lateral prefrontal cortex (online

figure, region f ) is associated with deliberative processing involving logic and math (Berkman and

Lieberman 2009). Second, the inferior frontal/pars orbitalis region (online figure, region g) is associated

18 In addition to providing support for the prediction in H1a and our theory that System 1 processing works inconjunction with System 2, this also provides corroborating evidence that affective reactions did not dissipate over thecourse of the study and played a role in choice regardless of contract type.

19 In whole-brain analyses, we do not observe significant differences in brain regions activated for investment choicesinvolving only the positive affect and only the negative affect managers when analyzed separately.



TABLE 2

Hypothesis 1Statistical Results of Image Analysisa

Contract Type Regions (L ¼ left, R ¼ right)Brodmann’s

Area

MNI Coordinates

tx y z

Fixed wage L Superior Medial Frontal 32 0 38 28 4.57

R Superior Medial Frontal 6 12 26 58 3.49

L Superior Frontal 8 �14 34 54 3.82


R Middle Frontal 9 36 20 44 3.78

L Inferior Frontal (Pars Orbitalis) 47 �42 20 �10 3.67

L Insula 13 �28 14 �10 3.89

L Supplementary Motor Area 6 �6 14 64 3.58

L Inferior Temporal 21 �46 2 �38 4.23

R Inferior Temporal 21 50 4 �36 4.65

L Posterior Cingulate 31 �10 �52 32 5.08

R Posterior Cingulate 31 10 �48 26 4.91

L Precuneus 7 �4 �60 36 4.56

L Angular 39 �52 �68 34 5.90

R Angular 40 52 �62 38 7.05

R Middle Cingulate 24 2 �24 36 4.13

L Supplementary Motor Area 6 �12 �8 70 �4.80

R Supplementary Motor Area 6 12 �5 70 �4.39

L Precentral 6 �40 �12 50 �3.52

L Fusiform 37 �36 �48 �14 �3.70

L Hippocampus 20 �36 �26 �16 �4.36

L Superior Parietal 40 �26 �48 60 �4.21

R Postcentral 3 30 �36 62 �4.13

L Superior Occipital 18 �18 �86 10 �4.18

R Middle Occipital 19 32 �74 24 �3.76

Performance-based R Superior Medial Frontal 8 12 28 48 5.17


L Middle Frontal 9 �34 20 32 4.84

R Middle Frontal 8 32 18 40 4.98

L Inferior Frontal (Pars Orbitalis) 47 �46 32 �12 3.94

R Inferior Frontal (Pars Orbitalis) 47 46 24 �12 3.79

L Precentral 6 �42 0 46 3.47

L Middle Temporal — �52 �38 �6 4.11

L Middle Temporal 21 �50 6 �30 3.63

R Middle Temporal 21 64 �32 �6 3.93

L Fusiform 37 �46 �56 �20 3.42

L Postcentral 6 �52 �6 24 3.88

R Posterior Cingulate 23 6 �46 22 3.96

L Precuneus 7 0 �56 40 4.80

L Angular 40 �52 �58 30 4.70

R Angular 40 56 �52 26 4.58

L Thalamus — �10 �4 8 4.17

R Thalamus — 6 �2 8 3.53

R Caudate — 16 �2 20 3.63

(continued on next page)



with inhibiting automatic responses (Berkman and Lieberman 2009). Third, the bilateral thalamus/

caudate (online figure, region h), part of the ventral striatum, is thought to function as a ‘‘switchboard’’for information processing (Gazzaniga et al. 2009, 81–82). Fourth, the bilateral middle temporal regions

(online figure, region i) are associated with memory retrieval and processing (Menon, Boyett-

Anderson, Schatzberg, and Reiss 2002; Cabeza et al. 2004; Gilboa, Winocur, Grady, Hevenor, and

Moscovitch 2004; Lieberman 2007; Squire 2009), reflective appraisal of what others think (Ochsner et

al. 2004; Lieberman 2007), and also with visual perceptual face representation (Purves et al. 2008, 560).

These results support H1b, indicating that brain regions associated with System 2 processing were more

responsive to affective than to neutral stimuli under a performance-based contract.

Additional evidence for H1—Regions-of-interest analysis. To provide further evidence of

processing differences across contract types, we complemented the whole brain results with a

regions-of-interest analysis. This analysis identifies brain regions with significant activity in the

whole-brain analysis that are relevant to the research questions (in our case, the regions associated

with Systems 1 and 2 processing identified earlier), and then conducts more extensive statistical

tests of only these regions to confirm results of the whole-brain analysis.

Based on the whole-brain analysis, we identified key regions of interest in representative regions

commonly and uniquely sensitive to affective (relative to neutral) investment choice stimuli during

investment decision-making under the fixed wage and performance-based contracts. Brain activity

that was significantly greater during choices involving the affect managers relative to the neutralmanagers under each contract type is depicted in Figure 3. The bars in Figure 3 represent brain

activity during affective choices over and above activity during neutral choices under the fixed wage(black bars) and performance-based (grey bars) contracts. The shading of the backgrounds for a set of

regions indicates whether there were significant differences in brain responses between affective and

neutral choices under both contract types (white background), under only the fixed wage contract

(light grey background), or under only the performance-based contract (dark grey background).20

With respect to H1a, regions associated with System 1 processing that were statistically

more active during affective, compared to neutral, choices under both contract type conditions

(Figure 3, white background) included the bilateral superior medial frontal/anterior cingulate

(online figure, region a), the bilateral posterior cingulate/precuneus (online figure, region b), and

the bilateral angular gyri (online figure, region c). Brain responses in these regions were similar

under both contracts, with the exception of the bilateral angular gyri, which showed greater

response under the fixed wage. This supports our prediction in H1a and the related whole-brain

TABLE 2 (continued)

t-statistics are significant based on a threshold of p , 0.001 (uncorrected), with cluster-size of at least 20 voxels.a This table provides peak MNI (Montreal Neurological Institute) coordinates of brain regions showing significant

differences during affective stimuli relative to neutral stimuli under the fixed wage contract and under the performance-based contract (in other words, for each contract type, brain regions in which activity in affective decision contexts isabove and beyond that in non-affective contexts).

The Brodmann’s Area and the MNI coordinates (where x, y, and z represent coordinates on the left to right or sagittalplane, the up to down or axial plane, and the front to back or coronal plane) are two systems used in imaging analysis toidentify brain regions that show significant responses to stimuli. These are three-dimensional analogies to two-dimensional coordinates on a geographic map.

20 Note that for regions that showed significantly greater activity under only the fixed wage or only the performance-based contract (i.e., the light grey and dark grey backgrounds), bars representing activity for the other contractcondition (i.e., grey bars in the light grey background, and black bars in the dark grey background, respectively) arefor illustration only—this activity is not significantly greater during affective than non-affective choices.



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lati

ve

toneu

tral

stim

uli

inth

efix

edw

age

condit

ion

(and

not

inth

epe

rfor

mance

-base

dco

ndit

ion).

Reg

ions

wit

hin

the

dar

kgre

ybac

kgro

und

wer

esi

gnifi

cantl

ym

ore

resp

onsi

ve

for

affe

ctiv

ere

lati

ve

toneu

tral

stim

uli

inth

eper

form

ance

-base

dco

ndit

ion

(and

not

inth

efixe

dw

age

condit

ion).

Thes

ein

clude

regio

ns

asso

ciat

edw

ith

Syst

em2

pro

cess

ing,

incl

udin

gth

ebil

ater

alm

iddle

fronta

l(o

nli

ne

figure

,re

gio

nf)

;bil

ater

alin

feri

or

fronta

l/par

sorb

ital

is(o

nli

ne

figure

,re

gio

ng);

the

bil

ater

alth

alam

us

and

right

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e(o

nli

ne

figure

,re

gio

nh);

and

the

bil

ater

alm

iddle

tem

pora

l(o

nli

ne

figure

,re

gio

ni)

.

Sta

tist

ical

anal

yse

sfo

rth

isfi

gure

are

bas

edon

those

report

edin

Tab

le2.



evidence that brain regions associated with System 1 processing were relatively more active in

affective decision contexts than neutral decision contexts under both fixed wage and

performance-based contracts. The only regions that were statistically more active during

affective relative to neutral choices under only the fixed wage contract (Figure 3, light grey

background) were the bilateral inferior temporal (online figure, region d) and the left insula

(online figure, region e).

With respect to H1b, regions statistically more active during affective relative to neutral

choices under only the performance-based contract (and not the fixed wage contract) include

regions associated with System 2 processing (Figure 3, dark grey background). Consistent with the

whole-brain analysis, these include the bilateral middle frontal (online figure, region f ), bilateral

inferior frontal/pars orbitalis (online figure, region g), bilateral thalamus and right caudate (online

figure, region h), and bilateral middle temporal regions (online figure, region i ). Thus, consistent

with H1b, several additional regions associated with System 2 are activated by the performance-based contract in affective decision contexts.21

Summary of results for H1. Taken together, results of the whole-brain and regions-of-interest

analyses provide support for H1. Under a fixed wage contract, brain regions commonly associated

with System 1 processing are more responsive when managers make choices that involve affective

reactions to decision contexts than when they make neutral choices. Further, under a performance-

based contract, brain regions associated with both System 1 and System 2 processing are more

responsive when managers have affective reactions to decision contexts, above and beyond any

responsiveness in affect-free, but otherwise identical, choices. Together, these results provide

support for a dual process model, and suggest that in affective decision contexts, a performance-

based contract does not eliminate affective reactions, but rather induces more analytical processing

that offsets, at least in part, reliance on default responses based on affect.22

H2 Results

H2 predicts that managers will more frequently make more economically desirable choices

when they have affective reactions to decision contexts and their pay is based on a performance-

based rather than a fixed wage contract, and the difference in the extent of these choices across

affective and non-affective contexts will be smaller. We used investment choices made in the

scanner to test H2. Recall that for choices that included an affect manager, choices based on

affective reactions were less desirable from an economic standpoint. We code trials as 1 if the

21 In the regions-of-interest analysis, in some, but not all, regions, choices that involved the negative affect managersexhibited a higher level of activation in that region than did choices that involved the positive affect managers. Aregions-of-interest analysis of positive versus negative stimuli is beyond the scope of this paper.

22 We also examined response times for investment choices. There is considerable debate in the dual process literatureon whether System 1 and System 2 processing operate sequentially or simultaneously (e.g., Evans 2008). Given thistheoretical debate and the fact that cognitive response times in a task could decrease over time due to learning whilephysical response times could increase due to fatigue, it is difficult to predict what pattern of response times forinvestment choices we would expect across the contract types in our study. Nonetheless, we attempted to control forchanges over time unrelated to our theory by sequentially numbering each investment choice across both the fixedwage and performance-based contract sections of the task, and calling this variable order. We included order in twoanalyses: (1) as a covariate in an analysis with response time as the dependent variable and contract type, affect, andtheir interaction as independent variables; and (2) in a two-step regression, first regressing response time on order,then regressing residuals from that regression on contract type, affect, and their interaction. Both analyses yieldedinferentially similar results; there were positive main effects for both contract type (i.e., longer response times underthe performance-based contract, consistent with a greater likelihood of a System 2 intervention) and for affect (i.e.,longer response times for affective compared to neutral choices, suggesting additional processing when affective andeconomic considerations conflict). The interaction of contract type and affect was not significant. While interesting,these results do not provide definitive evidence to support a theory for either sequential or simultaneous System 1 andSystem 2 processing.



investment project with the higher expected profit was chosen, and 0 otherwise, and call this

dependent measure investment choice.

Descriptive statistics for investment choice across contract type and affect conditions are in Table 3,

Panel A, and are graphically displayed in Figure 2, Panel B. When affect was absent, the proportion of

more economically desirable choices was comparable in the fixed wage (96.3 percent) and performance-based (95.1 percent) contract conditions. When affect was present, the proportion of more economically

desirable choices was lower under both the fixed wage (66.2 percent) and performance-based (82.7

percent) contracts; this pattern was consistent across positive and negative affective reactions.

To test H2, we use a repeated measures logistic model with investment choice as the dependent

measure. To account for dependence in responses from our repeated measures design, the model

clusters observations by participant. Results are reported in Table 3, Panel B. Consistent with H2,

we find a significant contract type 3 affect interaction (p ¼ 0.01). We also observe a significant

main effect of affect (p , 0.01), but the main effect of contract type is not significant (p¼ 0.28).

Simple effects tests are reported in Table 3, Panel C. Results show that contract type does not

influence participants’ choices when affect is absent (p¼ 0.56). However, when affect is present,participants are significantly more likely to make more economically desirable choices under the

performance-based than the fixed wage contract (p , 0.01). Finally, participants are significantly

less likely to choose projects with higher expected returns when investment alternatives are

presented by affect rather than neutral managers under both the fixed wage (p , 0.01) and the

performance-based contracts (p , 0.01). Inferences are the same if positive affect and negativeaffect managers are analyzed separately (Table 3, Panels B and C).23

Taken together, these results support H2. When managers’ affective reactions could lead to

choices that are not in the best economic interests of their firms, a performance-based incentive

contract increases the likelihood that they will instead make choices that are more economically

desirable. However, while the performance-based incentive contract reduces the influence of

affective reactions on investment choice, it does not eliminate it.

V. EXPERIMENT 2

Setting and Procedures

We again used the setting described in Section III. Participants acted as division managers

whose task was to evaluate potential investment projects that their division could undertake with

other divisions in their company. We induced affective reactions to some colleagues who proposed

those projects, and manipulated contract type between subjects.

Experiment 2 was administered using an online program in a computer lab. For our between-

subjects manipulation of contract type, we randomly assigned participants to contract type conditions

as they arrived at the lab. Participants in the fixed wage contract condition received $17.50 to complete

the task. Participants in the performance-based contract condition received a $7.50 fixed wage, and

were eligible for a bonus of $5.00 for each of their two investment decisions.24 The description of the

performance-based contract provided to participants was virtually identical to that in Experiment 1 (see

supporting online materials), except for the difference in the fixed wage rate, the fact that participants

could earn a bonus for each investment choice (rather than for a subset of choices), and the required

23 For H2, results are consistent with those reported when we analyze Master’s of Accountancy and M.B.A. participantsseparately. For H1, because of the lack of participant-specific control in between-subjects designs that we describe inSection III, we did not compare brain images across these two groups.

24 Participants were graduate business students from four different degree programs. Given the sample sizes for each ofthese groups and the fact that they were randomly assigned to experimental conditions, we do not compare resultsacross degree programs.



TA

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ve

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ect

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siti

ve

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ect

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.1%

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][3

0o

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1]

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ance

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6

aIn

Exper

imen

t1,

par

tici

pan

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ake

two

sets

of

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esbet

wee

nin

ves

tmen

tpro

posa

lsfr

om

one

of

six

fam

ilia

rm

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san

done

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mil

iar

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s(s

eeA

ppen

dix

Bfo

ra

sam

ple

inves

tmen

tch

oic

esc

reen

).B

efore

par

tici

pan

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ake

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rin

ves

tmen

tch

oic

es,

we

intr

oduce

dth

emto

two

fam

ilia

rm

anag

ers

wit

hw

hom

they

hav

ehad

posi

tive

inte

ract

ions,

two

wit

hw

hom

they

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ehad

nega

tive

inte

ract

ions

(toget

her

,th

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fect

man

ager

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ppen

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ra

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ple

),an

dtw

ow

ith

whom

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neu

tral

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ract

ions.

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ore

they

mak

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efi

rst

set

of

90

inves

tmen

tch

oic

es,

par

tici

pan

tsar

eto

ldth

atth

eyw

ill

be

pai

da

fixed

wage

of

$25.

Aft

era

dis

trac

tor

task

,par

tici

pan

tsm

ake

the

sam

e90

inves

tmen

tch

oic

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na

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fere

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er),

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told

that

they

wil

lbe

pai

dunder

ape

rfor

man

ce-b

ased

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act

for

thes

ech

oic

es.

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each

inves

tmen

tch

oic

epre

sente

d,

the

dep

enden

tvar

iable

inve

stm

ent

choi

ceis

coded

as1

(0)

when

par

tici

pan

tsch

ose

the

inves

tmen

tw

ith

the

hig

her

(low

er)

expec

ted

val

ue.

bIn

Exper

imen

t2,par

tici

pan

tsw

ere

random

lyas

signed

toei

ther

the

fixed

wag

eor

the

perf

orm

ance

-bas

edco

ntr

act

condit

ion.T

hey

mad

etw

och

oic

esbet

wee

nin

ves

tmen

tpro

posa

lsfr

om

one

man

ager

tow

hom

we

induce

dei

ther

aposi

tive

or

neg

ativ

eaf

fect

ive

reac

tion

(as

inA

ppen

dix

A)

and

one

man

ager

wit

hw

hom

they

had

aneu

tral

inte

ract

ion.

For

each

inves

tmen

tch

oic

epre

sente

d,

the

dep

enden

tvar

iable

inve

stm

ent

choi

ceis

coded

as1

(0)

when

par

tici

pan

tsch

ose

the

inves

tmen

tw

ith

the

hig

her

(low

er)

expec

ted

val

ue.



investments for the projects varied across the investment choices, so were provided with the project

descriptions.

Next, participants made two investment choices. For each choice, we described ordinary

interactions with one of the managers proposing a project (similar to the familiar neutral managersin Experiment 1) and induced an affective reaction to the manager proposing the other project. For

the latter, we used one positive and one negative affect manager used in Experiment 1 (as in

Appendix A, although photos were not provided).25 In both investment choices, the estimated profit

for the project proposed by one manager was certain, and was equal to the highest possible

probabilistic profit of the project proposed by the other manager. As in Experiment 1, expected

profit for the projects was provided so participants did not need to compute it. Further, the more

economically desirable project alternatives were inconsistent with induced affective reactions.

After making the two investment choices, participants answered questions to measure (1) the

extent to which the inducement of affect was successful (the same measures as in Experiment 1), (2)

what they focused on when making their investment choices, (3) perceptions of the task, and (4)

demographic information. Participants were paid in cash before leaving the computer lab.

Results

Manipulation Checks

Participants reacted in the expected directions to positive and negative affect managers. For the

positive affect manager, average responses to the positive (negative) affect questions were

significantly above (below) 5, the midpoint of the scale (positive mean ¼ 8.07, negative mean ¼0.80, both p , 0.01, two-tailed). By contrast, for the negative affect manager, average responses to

the positive (negative) affect measures were significantly below (above) 5 (positive mean ¼ 2.07,

negative mean¼ 6.82; both p , 0.01, two-tailed). Participants in the performance-based condition

all indicated they understood how their pay would be computed.

H2 Results

Results provide support for H2 (see Table 3, Panel D, and Figure 2, Panel B). As in Experiment

1, we code trials as 1 if the investment project with the higher expected profit was chosen, and 0

otherwise. The proportion of more economically desirable choices increases from 46.1 percent (47 of

102) in the fixed wage condition to 58.9 percent (53 of 90) in the performance-based condition (p¼0.05, Fisher’s one-tailed exact test). This increase is largely driven by the increase in the proportion of

more economically desirable choices for the positive affect manager (from 58.8 percent to 75.6

percent under the fixed wage and performance-based contracts, respectively); the change in the

proportion for the negative affect manager (from 33.3 percent to 42.2 percent) is positive, but not

statistically significant.26

Summary of H2 Results across Both Experiments

Overall, results of the between-subjects lab experiment provide additional support for H2, but

use a different set of design choices. This suggests that the investment choice results from the

within-subjects fMRI experiment generalize to a more diverse participant group in a richer and

more natural decision-making setting.

25 We randomized the order in which participants made the two investment choices.26 Experiment 2 included both male and female participants. We detect no significant differences between male and

female participants’ responses (p . 0.50).



We also note two points with respect to these choice results. First, the proportion of more

economically desirable investment choices in affective contexts is lower in Experiment 2 than in

Experiment 1 under both contract types (see Table 3, Panels A and D). Specifically, under the fixed

wage contract, the proportions are 66.2 percent and 46.1 percent in Experiments 1 and 2,

respectively; under the performance-based contract, the proportions are 82.7 percent and 58.9

percent in Experiments 1 and 2, respectively. We attribute these differences to the additional

contextual information provided and to the closer proximity of the inducement of affect to those

choices in Experiment 2. Second, while the increase in the proportion of more economically

desirable choices from the performance-based contract is not statistically significant for negative

affect managers in Experiment 2, the percentage change in that proportion is fairly consistent across

both positive and negative affect managers in both experiments, with increases in the range of 20

percent to 30 percent. This suggests that the cognitive processing effects of contract type and the

concomitant effects on choice are robust to the different settings examined in the two experiments,

and may generalize to real-world decision settings.27

VI. DISCUSSION AND CONCLUSION

We provide evidence that brain regions commonly associated with System 1, which involves

more heuristics-based and automatic processing, are more responsive when managers have affective

reactions to decision contexts than when they do not. Consistent with the idea that decision-makers

spontaneously experience affective reactions, results of our fMRI experiment show that System 1

regions continue to be responsive to decisions that include affective reactions even under a

performance-based contract. In other words, performance-based contracts do not suppress affective

reactions. Rather, they activate additional brain regions associated with System 2, which involves

more analytical processing, in response to affective decision contexts.

Our study is the first in accounting to provide evidence of how brain activity during

decision-making can be influenced by performance measurement and control systems. As such, our

methodology allows us to provide more direct evidence of the related information processing in the

brain. This evidence can be more readily generalized to situations without obvious benchmarks for

decision quality (for example, settings in which signals provide conflicting evidence about the most

desirable choice). In addition, our results suggest the possibility that other institutional features,

such as monitoring or commitment devices, could prompt similar processing changes that yield

economic benefits for firms.

We also find that performance-based incentive contracts influence the extent to which

managers make more economically desirable investment choices in the presence of potentially

costly affective reactions. Prior research in this area has generally used fixed wage contracts (e.g.,

Kida et al. 2001; Moreno et al. 2002). Our results suggest that studies on affect should be

interpreted in light of the incentives present in the setting. Specifically, we find that

performance-based contracts reduce, but do not eliminate, affect-based bias, and provide evidence

on the cognitive processes behind these findings.

27 We can also compare results for our fixed wage conditions to results for the gain conditions in Moreno et al. (2002,Table 2). Specifically, with affect absent, the proportion of more economically desirable investment choices inMoreno et al. (2002) ranged from 80 percent to 93 percent. In our Experiment 1, we find the proportion to be 96percent (see Table 3, Panel A). With affect present, the proportion of more economically desirable investment choicesin Moreno et al. (2002) was approximately 39 percent across all scenarios; in our Experiment 2, we find theproportion to be 66 percent in Experiment 1 and 46 percent in Experiment 2 (which has more context and is, thus,more comparable to Moreno et al. [2002]; see also Table 3, Panel D). Thus, our investment choice results appearcomparable to those in prior research using a fixed wage contract.



Our study has several limitations that provide opportunities for future research. First, because

of the constraints that fMRI technology places on experimental design, it is difficult to know

whether brain responses would differ in more context-rich settings. While we provide evidence

from a traditional behavioral experiment that decision outcomes are similar to those in our fMRI

task, investigating the extent to which other imaging technologies (e.g., PET, TMS, EEG)

complement our fMRI evidence could be a fruitful avenue for future work. Second, we

investigate only one mechanism for moderating the impact of affect on cognitive processing;

other, less-costly mechanisms (e.g., other contract forms, commitment devices, prompts) should

also be examined and could be useful to practice. Third, we use a System 1-System 2 framework

as a way to connect dual process theories and neuroscience research. However, neuroscience is

far from definitively establishing the functions of individual brain regions and how regions

interact when performing particular tasks. As such, our use of the System 1-System 2 framework

and our identification of relevant brain regions within them is an early step in bringing this work

to accounting.

Future neuroscience work in accounting could examine brain regions thought to be

associated with processing conflicting information signals, and how contextual features of

decision settings affect that processing. Research could also investigate conditions under which

more deliberative processing might lead to less desirable decision-making. Further, while people

are the source of affective reactions in our study, this need not be the case. For example, Elliott,

Jackson, Peecher, and White (2014) find that corporate social responsibility disclosures evoke

emotional responses; future studies could examine whether cognitive reactions to different types

of accounting information mirror those found in our study. Beyond studies that examine

individuals’ processing and choice, since decision-making rarely happens in a vacuum, future

research could examine how social preferences (e.g., honesty, fairness) or interactions among

various stakeholders (e.g., superiors and subordinates, auditors and clients) affect cognitive

processing of accounting information.

In sum, our study extends prior research in accounting on the impact of affect on decisions. Further,

our theory and results suggest that well-designed incentive contracts are useful not only for better

aligning managers’ goals with those of firm owners, but also for inducing managers to process various

inputs into decisions more analytically. We also extend prior neuroscience research in psychology and

economics by examining brain processes in the presence and absence of affect under different

compensation contracts. Finally, we are among the first to use fMRI methodology in accounting

research as a means to provide more direct evidence on the decision processes underlying choice.

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APPENDIX A

Experiments 1 and 2Sample Experimental Materials for Inducement of Affect28

In the recent past, you were impressed by a proposal that Ken (shown above) had submitted to

you, so you had contacted him directly to discuss it. Ken’s attitude and tone during that conversation

surprised you. Although you and he are both division managers (and, thus, peers), he spoke to you as

if you were his subordinate, using a condescending tone that you would never use with anyone on

your team. For example, Ken told you that you should value the opportunity to work with him

because he was a ‘‘key player at Universal,’’ and that working with him would be a ‘‘great learning

experience’’ for you. You have enjoyed a very successful career with Universal—equally as

successful as Ken’s, if not more so—and you certainly are not accustomed to being spoken to in such

an arrogant and condescending way, especially by a peer. Nevertheless, after this conversation, you

decided to give Ken the benefit of the doubt—the idea still seemed impressive and, after all, you had

never been formally introduced to each other, so perhaps Ken may have had the wrong impression

about your level of experience within the firm or was simply having a bad day.

After that extremely unpleasant conversation with Ken, you hoped that a face-to-face meeting

would ease your concerns about his attitude. However, the meeting with Ken served to not only

confirm, but also strengthen, your initial impressions. Although the meeting took place in your

division’s conference room, Ken immediately brushed past you and seated himself at the head of the

table, and instructed your assistant to ‘‘fetch’’ him a cup of coffee. Furthermore, while you had

expected a fairly brief, conversational meeting, Ken directed one of his staff to ‘‘fire up the highlight

reel,’’ an elaborate PowerPoint presentation listing details of his team’s recently completed projects, or

‘‘conquests,’’ as he insisted on calling them. While you admitted to yourself that Ken’s track record

was impressive, you could not help but note that it was no more impressive than your own. When the

‘‘highlight reel’’ finished, you and your team listened in stunned silence as Ken gave you chapter and

verse on the power of his ‘‘signature’’ management style. He was particularly keen to impress upon

you how much more efficiently and effectively his division’s employees work than yours, a fact he

attributed to the hands-on supervision he personally provided to each one of them, in contrast to what

he derisively called your ‘‘too-soft mentoring approach.’’ Finally, after more than an hour of self-

promotion, Ken and his team confirmed the original estimates in the proposal they had submitted, and

you ended the meeting as quickly as you could.

In short, Ken is arrogant, egotistical, and condescending, making him a difficult person to work

with.

28 In both experiments, we induced positive or negative affective reactions to certain managers. This appendix providesa sample of a negative affect manipulation.



APPENDIX B

Experiment 1Sample Investment Choice Screen

This is a sample screen from the investment choice task completed in the fMRI scanner.

Participants made 90 investment choices of pairings of familiar and unfamiliar managers grouped

into three affect conditions: positive (30 trials), negative (30 trials), and neutral (30 trials), and they

did so twice—once under a fixed wage contract and once under a performance-based contract.

APPENDIX C

Whole Brain Analysis Figure: http://dx.doi.org/10.2308/accr-50852.s1

Supporting Online Materials: http://dx.doi.org/10.2308/accr-50852.s2



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