Effects of Ambiguous Common Uncertainty on Employees’
Preference for Relative Performance Contracts
GE BAIRANJANI KRISHNAN

Carey Business School
THE JOHNS HOPKINS UNIVERSITY

Department of Accounting & Information Systems
BROAD COLLEGE OF BUSINESSMICHIGAN STATE UNIVERSITY

ABSTRACT
We distinguish ambiguous common uncertainty (with unknown probability
distribution) from risky common uncertainty (with known probability distribution) andexamine how employee preference for relative performance contracts differs between
the two conditions. Using economics and psychology theory in decision making under
uncertainty, we hypothesize that (i) preference for relative performance contracts is low(high) when common uncertainty is ambiguous (risky); and (ii) confidence mediates
the relation between ambiguity and preference for relative performance contracts.
Results from a controlled laboratory experiment support these predictions. A follow-up
experiment provides evidence that the direct effect of ambiguity and the mediating
effect of confidence disappear if the contract is based on independent performancemeasures. Our study contributes to the literature on performance measurement,
employee contract preference, and decision making under uncertainty.
JEL Classification: M41
Keywords: Contract Preference; Relative Performance; Ambiguity Aversion

Corresponding Author. Address The Johns Hopkins Carey Business School 1717 Massachusetts Avenue NW,
Washington DC 20036, USA. Telephone +1-202-580-7573 E-mail gbai@jhu.edu
Received April 15, 2016; accepted October 10, 2016 available Online December 19, 2016 (Advance publications by JSTAGE)
DOI: 10.11640/tjar.6.2016.02

Copyright©2016 Research Institute for Economics & Business Administration – Kobe University.

66

The Japanese Accounting Review, 6 (2016), 65-93

1. Introduction
The primary benefit of using relative performance measures is to filter out common
uncertainty and increase contracting efficiency (Homstrom 1982; Antle and Smith 1986;
Gibbons and Murphy 1990; Gibbons 1998). The probability distribution for the occurrence ofcommon uncertainty is always assumed to be readily quantified (Homstrom 1982; Antle andSmith 1986; Dye 1992; Aggarwal and Samwick 1999; Hannan et al. 2008; Tafkov 2012; Hannan
et al. 2013) Yet, in most real-world scenarios, the probability distribution is neither specified inadvance nor assessable based on available evidence (Knight 1921; Ellsberg 1961; Fox and Tversky
1995; Gajdos et al. 2008; Abdellaoui et al. 2011; Maafi 2011). Intuitively, whether the
probability distribution of common uncertainty is known or unknown should not make adifference in employee preference for relative performance contracts, because relative
performance contracts are designed to insulate employees from common uncertainty. In thisstudy, we rely on economics and psychology theory in decision making under uncertainty toinvestigate whether this seemingly plausible proposition is true.
Knight (1921) distinguishes between measurable uncertainty or risk, for which the exact
probability distributions of the outcomes are known, and unmeasurable uncertainty or ambiguity,
for which the probability distributions are unknown (Fox and Tversky 1995; Maccheroni et al.
2006; Abdellaoui et al. 2011). In his seminal study, Ellsberg (1961) finds that people generally
strive to avoid ambiguity even if it leads to a violation of the axioms of expected utility theory(Savage 1954). This preference for known rather than ambiguous probabilities, or simply
ambiguity aversion, has subsequently motivated numerous studies in psychology, economics, andfinance. Behavioral studies, using variations of Ellsberg (1961)’s original design, demonstrate therich domain of ambiguity and ambiguity aversion behavior (Becker and Brownson 1964; Slovic
and Tversky 1974; Einhorn and Hogarth 1985; Hogarth and Kunreuther 1988; Camerer andWeber 1992; Sarin and Weber 1993; Keren and Gerritsen 1999; Abdellaoui et al. 2011; Maafi2011). Neuroscientists, applying functional brain imaging, provide biological evidence that
distinctive neural functions correspond to ambiguity (Hsu et al. 2005; Bach et al. 2009).
Ambiguity aversion has also been incorporated into various versions of generalized subjective
expected utility models (Gilboa 1987; Segal 1987; Fishburn 1988; Schmeidler 1989; Epstein andZhang 2001; Ghirardato and Marinacci 2002; Maccheroni et al. 2006; Gajdos et al. 2008).
Moreover, the finance literature documents that individuals are more prudent, invest less, andseek more insurance under ambiguous conditions than under risk conditions. This behavior
provides a powerful explanation for market nonparticipation, price volatility, persistentmispricing, and market incompleteness (Mukerji and Tallon 2001; Epstein and Schneider 2008;
Caskey 2009; Bossaerts et al. 2010; Easley and O’Hara 2009). A small accounting literature alsouses ambiguity aversion to explain the behavior of auditors, auditees, and the cost of bargaining(Nelson and Kinney 1997; Zimbelman and Waller 1999; Haka et al. 2000; Bigus 2012).
In this study, we examine ambiguity through the managerial accounting lens and focus on
the implications of ambiguity on employee preference for relative performance contracts.
Employee preference for contracts is an understudied but important research area. It directly
affects the level of employee resistance to contract implementation and employees’ work-related
attitudes, such as job satisfaction and propensity to engage in organization citizenship behavior(Lee et al. 2011). In addition, the main purpose of incentive contracts is to attract, retain, andenhance employee motivation, all of which are influenced to some extent by employee preferenceBai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

67

for the contract (Bolino and Turnley 2007; Scott et al. 2015). There is a small literature thatexamined employee pay preference. For example, Lee et al. (2011) recognized a preference for
performance-related pay over seniority-based pay in a Japanese firm.
Consider a simple situation in which employees’ independent performance is heavily
influenced by an uncontrollable common event. The presence of this event makes it desirable touse relative performance contracts to filter out the performance measurement noise generated by
the event. In scenario one, employees do not have information about the likelihood that the event
occurs; in scenario two they are told that the chance for the event to occur is 50%. The questionof interest here is whether employees exhibit different preferences for participating in identical
relative performance contracts in those two scenarios.
We argue that employees will develop a distaste from the common uncertainty’s ambiguous
nature, despite the fact that their peers are also subject to the same uncertainty. They will likely
find relative performance contracts unattractive and prefer to have a larger proportion of theircompensation based on fixed pay as compared with what they would prefer if the common
uncertainty is not ambiguous. Employees are expected to behave as if they are seeking insurance
to compensate for the disutility generated from the ambiguous common uncertainty. Thisbehavior is an analogy of the trade-off between risk and incentive (Feltham and Xie 1994;
Bushman et al. 1996; Ittner et al. 1997; Prendergast 1999; Krishnan et al. 2005), that is, as aperformance measure becomes noisy, incentive weight decreases to compensate for the increased
risk imposed on employees. Consequently, we hypothesize that employees have a low (high)preference for relative performance contracts when common uncertainty is ambiguous (risky).
The purpose of this paper is not only to identify ambiguity aversion in a relative performance
contract setting, but to demonstrate the underlying mechanism. Fox and Tverskey (1995)
recognize “comparative ignorance” as the root cause for ambiguity aversion. They suggest that in
a comparative context ambiguity undermines confidence, causing individuals to feel ignorant. In a
principal-agent setting, employees judge a relative performance contract’s appeal in light of theirchance to outperform their peers, and those with higher confidence have a higher probability
assessment of their chance for outperformance.1 Taken together, employee confidence is likely to
be undermined by the existence of ambiguous common uncertainty, and the undermined
confidence reduces their preference for relative performance contracts. We, therefore,
hypothesize that confidence mediates the relation between ambiguous common uncertainty andemployee preference for relative performance contracts.
We exploit the freedom of laboratory experiment to manipulate ambiguity in a way similar tothe classical experiment in Ellsberg (1961). We develop a case setting in which experimentparticipants assume the role of employees and are asked to reveal their preferences forcomparative incentive contracts. The elicited preferences also serve to measure their willingness
to accept a contract and the equilibrium risk or ambiguity premiums they require.
The experiment results provide robust evidence to support the hypotheses. First, the average
preference for relative performance contracts decreases by 38% when the common uncertainty is
ambiguous as compared with when it is risky. After we control for potential confounding factors
such as gender, GPA, risk attitude, and competition preference, the conservative estimatedambiguity effect is still 31%. Second, subjects report lower confidence in the ambiguity condition
1

Confidence is a key factor determining individuals’ tendency toward self-selecting into competition (Camerer andLovallo 1999; Niederle and Vesterlund 2007; Bartling et al. 2009; Eriksson et al. 2009).

68

The Japanese Accounting Review, 6 (2016), 65-93

than in the risk condition. Deflated confidence further reduces subjects’ preference for relative
performance contracts. Overall, confidence mediates 35% of the total effect of ambiguity on thepreference for relative performance contracts. The results are robust to the inclusion of risk
attitude and competition preference as control variables. To the extent that ambiguity negatively
affects risk attitude and competition preference, we provide conservative estimations ofambiguity’s direct effect and confidence’s mediating effect on employee preference for relative
performance contracts.
These results underscore the effect of ambiguity and the mediating effect of confidence on
employees’ perceived utility of relative performance contracts. These economically andstatistically significant effects are obtained after a simple experimental manipulation that removes
the information regarding the common uncertainty’s probability distribution. It is compellingthat confidence was also dampened by the ambiguity condition. Subjects behaved as if they losttheir confidence and strived to avoid relative performance contracts. From an alternative
perspective, the results indicate that providing employees with an expected probability
distribution for common uncertainty can boost their confidence and enhance their willingness toparticipate in relative performance contracts.
In a follow-up experiment, we examine whether similar effects of ambiguity and confidence
exist when the incentive contract is based on an independent performance measure. We do notfind evidence that employee preference or confidence is different between ambiguity and risk
conditions, consistent with the notion that ambiguity aversion is an inherently comparative effect,
triggered by the comparison characterized in relative performance measures and muted when an
independent performance measure is used (Fox and Tversky 1995).
Th is paper makes important contributions to three streams of literature − relative
performance, employee contract preference, and decision making under ambiguity. The relative
performance literature has assumed that the common uncertainty's probability distribution is
known and does not allow for the existence of ambiguity. This study is the first to relax thisassumption and finds that employees display a strong aversion to ambiguity. Second, this study
adds to the small literature on employee contract preference that aims to understand how todesign attractive incentive contracts to select and retain employees as well as to motivate
behaviors desired by the organization (Bolino and Turnley 2007; Lee et al. 2011; Scott et al.
2015). The impact of ambiguity on employee preferences, as recognized in this study, implies
that ambiguity is an important factor in designing and implementing incentive contracts. Third,
our study contributes to the literature on decision making under uncertainty, a fundamental
problem in modern decision theory (Fox and Tverskey 1995; Abdellaoui et al. 2011). Although
prior literature suggests that ambiguity undermines confidence, no empirical study has tested the
mediating role of confidence or any other traits. Our study is the first in this direction. Finally,
this study provides important evidence on the critical role of comparison in triggering ambiguity
aversion and the associations among gender, risk attitude, competition preference, and ambiguity
aversion.
This study also has important practical implications. Given that relative performance
contracts usually stimulate higher performance and more risk-taking behaviors (Frederickson
1992; Coles et al. 2006; Matsumura and Shin 2006; Hannan et al. 2008), our finding that theprobability information on common uncertainty induces participation in relative performance
contracts is nontrivial. For an owner with the objective of encouraging employees to accept a
relative performance contract, to provide them with the expected probability of common

Bai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

69

uncertainties can be an effective and efficient way to enhance the attractiveness of the contract
and achieve the owner’s objective. This approach, however, is not equally effective if the contract
is based on independent performance measures. Under the circumstances in which ambiguity
cannot be remedied, perhaps it is not efficient to use relative performance contracts, which
generate employee disutility.
This paper is organized as follows: The next section develops the hypotheses. Section III
explains the experiment design. Section IV reports results. Section V discusses the limitations
and concludes this study.

2. Theory and hypotheses development
Uncontrollable random events add noise to individual performance measures and impose risk
on employees who are evaluated based on these measures (Holmstrom 1982; Feltham and Xie
1994). Agency theory suggests that relative performance contracts, by filtering common
uncertainty out of employees’ evaluation, reduce employees’ exposure to risk without reducing
their incentive (Baiman and Demski 1980; Holmstrom 1980; Lazear and Rosen 1981;
Holmstrom 1982; Nalebuff and Stiglitz 1983; Wolfson 1985; Antle and Smith 1986; Gibbons
and Murphy 1990; Prendergast 1999).2 Relative performance’s positive effect on performance has
been widely documented (Antle and Smith 1986; Gibbons and Murphy 1990; Frederickson
1992; Janakiraman et al. 1992; Matsumura and Shin 2006; Matsumura and Shin 2006; Hannan
et al. 2008; Hannan et al. 2013; Eriksson et al. 2009).
In relative performance literature, common uncertainty has been assumed to be a vector of
normally distributed random variables, and the probability distributions of the random variables
are assumed to be known to both principals and agents (e.g., Gibbons 1998). In the real world,
however, employees’ knowledge about the likelihood of a common random event is not always
sufficient enough to inform them of a probability distribution in the standard Bayesian fashion.
Examples include the demand fluctuation of natural gas, the equity market movement, and asupervisor’s subjective performance evaluation noise. Intuitively, common uncertainties,
regardless of their probability distribution being known or unknown, can be filtered out in a
relative performance contract and thus should not affect employee preference for the contract.
This notion is supported by expected utility theory (Savage 1954), which suggests that individuals
maximize expected utility according to subjective priors and that not being informed about an
uncertainty’s probability distribution should have no effect on behavior.
Ellsberg (1961), however, argues that agents distinguish between risk (known probabilities)
and ambiguity (unknown probabilities) and may display aversion to ambiguity.3 An example ofsuch a situation is the so-called Ellsberg paradox. The original experiment involves two urns,
each containing red and black balls. Urn A contains 50 red and 50 black balls, whereas urn B
contains 100 red and black balls in an unknown proportion. Suppose a subject draws a ball froman urn at random. He receives $100 or nothing depending on the outcome. Most people are
indifferent between betting on red or on black for either urn, indicating that the subjective
2

We define relative performance evaluation schemes as any competitive compensation scheme in which pay depends
on relative performance evaluation. It includes cases in which output is linear in effort (i.e., magnitude of relative
performance enters into the compensation scheme) and cases in which output is nonlinear in effort (i.e., rank-order
tournament scheme).
3Knight (1921) was the first to distinguish between these two concepts.

70

The Japanese Accounting Review, 6 (2016), 65-93

probabilities of red and black are the same at 50%. However, most people prefer to bet on the 5050 urn rather than the urn with unknown composition as if they strive to avoid ambiguity. Suchbehavior is paradoxical and inconsistent with the axioms of expected utility theory (Savage 1954)
and other theories of rational behavior under uncertainty in which probabilities are additive(Segal 1987). Ambiguity aversion is a robust phenomenon documented in the experimental
decision-making literature (Becker and Brownson 1964; Slovic and Tversky 1974; Einhorn and
Hogarth 1985; Hogarth and Kunreuther 1988; Sarin and Weber 1993; Keren and Gerritsen
1999; Cherry and Shogren 2007; Hsu et al. 2005). Ambiguity aversion has informed a large bodyof economics and finance research (Mukerji and Tallon 2001; Epstein and Schneider 2008;
Caskey 2009; Easley and O’Hara 2009; Bossaerts et al. 2010; Abdellaoui et al. 2011).
Fox and Tversky (1995) suggest that ambiguity aversion is an inherently comparative effectand signifies itself in comparative contexts. In other words, the predominant source of ambiguity
aversion is comparison. In relative performance contracts, employees are subject to a comparative
context, and evaluating ambiguous common uncertainty in such a context can induce ambiguity
aversion – employees generate distaste from the uncertainty’s ambiguous nature and find the
incentive contract unattractive, despite the fact that the ambiguous uncertainty is also faced bytheir peers. In contrast, common risky uncertainty does not induce such distaste, and relative
performance contracts with common risky uncertainty should appeal more to employees thanrelative performance contracts with common ambiguous uncertainty.
From the perspective of agency theory, the weight attached to any measure in acompensation contract is decreasing in the noisiness of that measure, reflecting a trade-off
between risk and incentives. This trade-off occurs because risk-averse agents are imposed withrisk by the noisy performance measure and thus seek insurance through reduced incentive weight(Feltham and Xie 1994; Gibbons 1998; Prendergast 1999). In the same light, due to the distaste
for ambiguity induced in a relative performance setting, we expect employees to exhibit a tradeoff between ambiguity and incentive. When the common uncertainty is ambiguous instead ofrisky, ambiguity-averse agents will seek insurance against ambiguity and display low preference
for ambiguity-based relative incentive contracts as compared with risk-based incentive contracts.
Based on the above discussion, we predict that ambiguity has a negative effect on employee
preference for relative incentive contracts. Stately formally,
H1: Employees have a lower preference for relative performance contracts when the common
uncertainty is ambiguous as compared with when the common uncertainty is risky.
Next, we examine whether confidence plays a mediating role in the relation between
ambiguity and preference for relative performance contracts. Ellsberg (1961) implies thatambiguity aversion reflects a link between the antecedent condition – “quality and quantity of
information" – and the consequent psychological event – "degree of confidence in estimates ofprobabilities". Fox and Tversky (1995) propose “comparative ignorance” as the explanation for
the root cause of ambiguity aversion. They argue that in a comparative context such as adependent evaluation of uncertain prospects, individuals tend to feel ignorant, their confidence isundermined, and they subsequently exhibit distaste for ambiguous prospects. “Comparative
ignorance” has been supported by numerous subsequent empirical studies (e.g., Chow and Sarin
2001; Kuhberger and Perner 2003; Epstein and Schneider 2008; Abdellaoui et al. 2011). The
notion that ambiguity undermines confidence, as suggested Fox and Tversky (1995), has alsoBai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

71

received attention. Ghosh and Ray (1997) find that individuals who are more tolerant of
ambiguity exhibit greater confidence in their choice, indicating a positive relation between aperson’s ambiguity tolerance and confidence. Epstein and Schneider (2008) link ambiguity withinvestor confidence in the financial markets. Chateauneuf and Faro (2009) model a confidence
function to capture the effect of ambiguity on decision confidence. In a relative performance
contract, an individual employee’s performance is compared with the performance of others todetermine his/her payoff. This comparative setting sensitizes employees to ambiguity. Whenambiguous common uncertainty is present, it is likely to undermine employee confidence.
Confidence is a crucial factor in determining employee preference for relative performance
contracts. Individuals have different degrees of confidence and thus different probability
assignments on their decision option (Knight 1921; Chateauneuf and Faro 2009). Moreconfident individuals have a higher estimation of their own relative ability, are more optimistic
about the future probability of winning a competition, and are more likely to enter into
competitive games or markets (Camerer and Lovallo 1999; Niederle and Vesterlund 2007;
Bartling et al. 2009; Eriksson et al. 2009). In relative performance contracts, the appeal of relative
performance is the expected probability that employees can perform well relative to one another.
Individuals with higher confidence project a higher probability assessment of success, view
relative performance contracts as more attractive, and thus are more likely to prefer such contracts
to maximize expected payoff.
Taken together, we expect that confidence will be reduced by ambiguity in relative
performance contracts and this muted confidence will reduce the preference for relative
performance contracts. Although the effect of ambiguity on confidence has been recognized in
the literature, no prior study to our knowledge has tested whether confidence mediates therelation between ambiguity and decision outcomes. In this paper, we formally hypothesize thisrelation.
H2: Confidence mediates the relation between ambiguity and employee preference for relative
performance contracts.
We demonstrate H1 and H2 in Figure 1.

3. Method
Archival data often lack information on employees' preferences and motives, and causal
inference is difficult to make due to confounding factors. To overcome these obstacles, we test
the hypotheses in a controlled laboratory environment. Participants in our main experiment were
34 students (sophomores and juniors) recruited from undergraduate business courses at a liberalarts college in the United States.4 The experiment employs a 2 X 1 between-subject design. We
manipulate uncertainty at two levels (ambiguity vs. risk).

Experimental Task and Procedure
We design a case setting to conduct the experiment. Subjects chose their preferredcompensation contract in a hypothetical case setting, assuming the role of a sales associate for a
medical equipment company that sells a diagnostic device to a foreign country. They were told
4

35 students participated, with one student failing to choose a weight, which reduced the valid subjects to 34.

72

The Japanese Accounting Review, 6 (2016), 65-93

FIGURE 1: HYPOTHESIZED MODEL

H1:

Independent
Variable (IV)

Direct EffectPreference for Relative
Performance Contracts

Ambiguity

Dependent Variable (DV)H2: Independent
Variable (IV)
Ambiguity

Dependent Variable (DV)Declined Direct Effect due to Mediator

Preference for Relative
Performance Contracts

Mediator
Confidence
Notes:
1. This figure illustrates the hypothesized relationships among ambiguity, confidence, andemployee preference for relative performance contracts

that they are going to sell the device together with three other sales associates with similar
backgrounds. How many units of that device they can sell depends on the foreign country’s
economy and personal factors that are specific to individuals, such as skills, knowledge, and effort,
etc. The country's economy can be either good or bad. A sales associate is expected to sell
between 60 and 120 units if the economy is bad and between 100 and 160 units if the economy isgood. Their compensation contains two parts: fixed pay and bonus pay. They are entitled toBai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

73

receive the fixed pay no matter how many units they sell. They can receive a bonus only if thenumber of devices they sell next year is in the top half among the four sales associates. The
experimental task was to choose a compensation plan from eleven alternatives with different
combinations of fixed pay and bonus pay. Participants were randomly assigned to two conditions(ambiguity and risk). They read the instructions and the case and subsequently chose thecompensation contract that they preferred. Finally, they were asked a series of post-experimental
questions. The experiment instrument and post-experiment questionnaire are presented inAppendixes A and B, respectively. The experiment took thirty minutes, and participants
completed it for class credit without monetary compensation.

Independent Variable
We manipulate the two types of uncertainty (i.e., ambiguity vs. risk) following Ellsberg(1961) and subsequent experiments that use “having a known estimated probability” versus“having unknown probability”. The only difference between the two conditions is information
regarding the probability for the uncontrollable common uncertainty (i.e., the foreign country’s
economy) that affects all sales associates. This information is absent in the ambiguity conditionand present in the risk condition. Specifically, in the risk condition, participants were told that“there is a 50-50 chance that the foreign country is going to have a good economy versus a bad
economy”. In the ambiguity condition, the above sentence is removed. We code the variable
Ambiguity as 1 (0) if a subject is in the ambiguity (risk) condition.

Dependent Variable
The dependent variable, Preference, is the preference for relative performance contracts. Twoforms of relative performance contracts have been studied in behavioral accounting literature.
Employees are paid a bonus for each unit of output greater than the average output of the agent’s
compensation group (e.g., Frederickson 1992), or paid a bonus if their performance is in a certain
rank (e.g., Hannan et al. 2008). For the sake of simplicity, we use a form similar to that in
Hannan et al. (2008), except that employees receive a bonus if their performance is among the
top half. We offer participants eleven alternative compensation plans as shown in Table 1. The
compensation plans differ in their combinations of potential bonus pay and fixed pay. For choice
A, only fixed pay will be offered. We code this choice 0, indicating the lowest preference forrelative performance contracts. For choice K, only bonus pay will be offered. We code this choice
10, indicating the highest preference for relative performance contracts. Under subjective
expected utility theory (Savage 1954), if an employee expects his chance of receiving bonus pay to
be 50%, he should be indifferent about the compensation plans because their expected values are
the same. As his preference for the relative performance contract increases (decreases), he shouldmake a higher (lower) valued choice. Thus, Preference indicates subjects’ preference for relative
performance contracts. Indirectly, Preference reveals their willingness to accept relative
performance contracts, since the fixed pay is offered independent of performance. A low (high)Preference indicates a low (high) willingness to accept, a high (low) risk or ambiguity premium
required to compensate for the uncertainty the subject bears, and a high (low) relative
performance contracting cost.

74

The Japanese Accounting Review, 6 (2016), 65-93

TABLE 1: PREFERENCE FOR RELATIVE PERFORMANCE CONTRACTS
Bonus Plan
A
B
C
D
E
F
G
H
I
J
K

Coded Value
0
1
2
3
4
5
6
7
8
9
10

Fixed Pay ($1,000)
100
90
80
70
60
50
40
30
20
10
0

Bonus Pay ($1,000)
0
20
40
60
80
100
120
140
160
180
200

Notes:
1. This table presents the alternatives used in the experiment to elicit subjects’ preferences for
relative performance contracts.
2. A high value indicates a high preference for relative performance contracts.

Mediating Variable
The mediating variable, Confidence, is measured through self-reported ratings obtained in the
post-experiment questionnaire. Following Barnsley et al. (2004), participants were asked to what
extent they describe themselves as confident. They chose a rating between 1 and 7, with 7
indicating to the greatest extent. Answers to this question indicate subjects’ general confidence
levels, not decision-specific confidence. 5 In previous experimental studies on ambiguity (e.g.,
Heath and Tversky (1991) and Ghosh and Ray (1997)), participants’ confidence in their answers
or choices are evaluated. For example, participants were asked to indicate how confident they arein their answer to a geography question or in the number of quality inspections that they decideto carry out. In these cases, the confidence level in the answer or choice is not a predictor of theanswer or choice. In the current study, however, participants’ confidence in their chances ofreceiving a bonus in a relative performance contract is a direct predictor of their preference for the
incentive contract.6 Therefore, we ask participants to evaluate their confidence in general rather
than their specific confidence in facing the relative performance contract. By doing so, we prevent
participants from being sensitized to justify their earlier choice on the incentive weight. If they
were asked to describe their confidence specifically about entering the relative performance
contract, then they would have chosen ratings that justify their previous choices for incentive
contracts. It might be argued that participants’ general confidence levels are independent of theexperimental task and thus are unlikely to be influenced by ambiguity or risk that is specific to theexperimental task. Despite this seemingly insensitive nature of general confidence in relation to5

Specific-decision confidence is defined as a subjective probability assessment of an outcome specific to a decision(Chateauneuf and Faro 2009).
6
It is worth noting that we are not interested in knowing participants’ confidence in their choices but their confidencewith respect to accepting the contract.

Bai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

75

ambiguity, we used this construct in the experiment, which arguably makes it difficult to observe
any effect of ambiguity on confidence.

Control Variables
We collect self-reported gender (Gender, coded as 1 female and 0 male), GPA (GPA, coded
as 0 if < 3.0, 2 if > 3.5, and 1 if in between), risk tolerance rating (Risk), and competition attitude
rating (Competition). Prior research suggests that these factors are related to ambiguity attitude
and the willingness to enter a competition (Eriksson et al. 2009). By including these variables in
the analysis, we are able to (i) test whether the results for hypotheses testing are robust; and (ii)
investigate how these variables are influenced by the independent variable (i.e., Ambiguity) as well
as affect the dependent variable (i.e., Preference) and mediating variable (i.e., Confidence). We
measure risk tolerance by asking subjects how likely it is that they will bet a day’s income at horseraces. Subjects chose a rating between 1 and 5, with 5 indicating very likely. We measurecompetition attitude by asking subjects to what extent they are likely to participate in acompetition. Subjects chose a rating between 1 and 7, with 7 indicating to the greatest extent.

Discussion on Experimental Design
Some aspects of our experiment design require additional discussion. First, in both risky andambiguous conditions participants are placed in a comparative context due to the nature of
relative performance contracts. In one of their experiments, Fox and Tversky (1995) manipulatedcomparison by suggesting the presence of more knowledgeable individuals to participants in a
between-subject design. Our study does not suggest the same to participants but instead imposes
an inherently comparative contract on participants. This manipulation of the comparative context
is a departure from Fox and Tversky (1995) and arguably a weaker manipulation than theirs, andthus is less likely to induce a comparative effect that leads to ambiguity-aversion. Another reason
we do not suggest the presence or absence of more knowledgeable individuals in our experimentis that in relative performance contracts this matter often depends on individual employees’assessment.
Second, Fox and Tversky (1995) recognized that most tests of ambiguity aversion employeda within-subject design in which participants compared risky and ambiguous information. Theysuggest that the within-subject design highlights the contrast between risk and ambiguity andthat the between-subject design can better answer whether ambiguity aversion still exists when
the risk benchmark is absent. They used a within-subject design in their experiment thatexamines the effect of knowledge comparison on ambiguity aversion. Consistent with Fox andTversky (1995), we used a between-subject design in this study, which does not induce acomparison between one contract with risky common uncertainty and the other contract with
ambiguous common uncertainty. If we had used a within-subject design, we would not have
known whether the ambiguity aversion behavior, if any, is due to participants’ comparison
between the two conditions or due to the comparative nature of the contract. This design,
therefore, offers a clean test of the ambiguity aversion behavior, if any, induced solely by thecomparative nature of the relative performance contract.
Third, the design of the eleven bonus plan choices indicates that if a participant, with aconcave utility function, believes his/her probability of receiving a bonus is 50% or lower, thenhe/she will always prefer plan A (fixed wage with no incentive). We adopted this design because

76

The Japanese Accounting Review, 6 (2016), 65-93

numerous psychological studies show that most people are overconfident about their own relative
abilities (e.g., Camerer and Lovallo 1999). This study focuses on the difference, if any, inparticipants’ preference between risky and ambiguous conditions.

4. Results
Manipulation Checks
We begin with an analysis of the effectiveness of our ambiguity manipulation. We ask eachsubject to recall whether the probability distribution regarding the foreign country’s economy is
known. All subjects, except for one, answered this question successfully. We also ask subjects toindicate whether the foreign country’s economy and their personal factors influence the numberof devices they can sell and whether their incentive pay depends on others’ performance. These
questions are aimed to assess to what extent subjects understand the experimental setting. All
subjects, except for the same one who missed the first question, performed well on theseeffectiveness check questions.7

Descriptive Statistics
In Table 2 Panel A, we compare the average value for Preference and Confidence under thetwo conditions (i.e., risk and ambiguity). The average Preference is 3.75 in the risk condition and2.33 in the ambiguity condition (p< 0.01). The average Confidence is 5.69 in the risk condition
and 4.67 in the ambiguity condition (p < 0.01). We demonstrate this relation in Figure 2. These
results are consistent with the predictions in H1 and H2 as well as the notion that most people
are overconfident. Even in the ambiguous condition, on average participants chose a 2.33 weighton the relative performance contract. Although 2.33 is lower than the average weight of 3.75 in
the risk condition, it indicates that the average subjective assessment of receiving the bonus issignificantly greater than 50% despite ambiguity aversion.
To rule out the possibility that these between-group differences are due to demographic
differences, we compare Gender, GPA, Risk, and Competition between two conditions and present
the result in Table 2 Panel B. None of these variables is statistically different between the two
conditions, suggesting that the between-condition difference in incentive weight and confidence
is likely caused by experiment manipulation.
In Table 2 Panel C, we present a correlation table for all variables used in the empiricaltesting. Ambiguity is negatively correlated with Preference and Confidence, providing preliminary
supporting evidence to the hypotheses. Preference is positively associated with Confidence and Risk,suggesting that more confident and more risk-seeking individuals find incentive schemes more
attractive. This is not particularly surprising because these individuals require a relatively low risk
premium and evaluate relative performance contracts more favorably. In addition, Confidence ispositively associated with Risk and Competition, consistent with the notion that more confident
individuals are also more risk-taking and more likely to compete (Eriksson et al. 2009). Finally,
Gender is negatively correlated with Confidence, Risk, and Competition, reflecting that women are
not as confident as men and are less willing to enter a competition (Niederle and Vesterlund
2007; Borghans et al. 2009; Dohmen and Falk 2011).
7

This subject, who was assigned in the risky condition, was removed from the sample. The final sample of 34 students
does not include him/her.

Bai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

77

4

6

3.5

5.5

3

5

2.5

4.5

2

4
Risk

Confidence

Preference

FIGURE 2: CONFIDENCE AND EMPLOYEE PREFERENCE FOR
RELATIVE PERFORMANCE CONTRACTS

Preference
Confidence

Ambiguity

Notes:
1. This figure demonstrates subjects’ average preference for relative performance contracts (theleft vertical axis) and confidence rating (the right vertical axis) in the risk vs. ambiguity
conditions.
2. Table 2 Panel A presents the numeric values used in the figure.

Hypotheses Testing
H1 predicts that ambiguity reduces employee preference for relative performance contracts.
As shown in Table 2 Panel A, the average Preference is 3.75 in the risk condition and 2.33 in the
ambiguity condition (p< 0.01), suggesting a negative effect of ambiguity consistent with H1. We
then used the Wilcoxon’s rank sum test (Wilcoxon 1945), a nonparametric test, and the result issimilar (Z =2.75; p < 0.01). We also use multiple regression analysis to quantify the effect of
ambiguity, the results of which are reported in Table 3. In Model 1 without any control variable,
Ambiguity significantly reduces Preference (-1.42, P< 0.01). In Model 2, in which Gender and GPA
are controlled for, we obtain similar result (-1.39, P<0.01). In Model 3, we control for Risk andCompetition and find that Ambiguity’s effect is still robust (-1.17, P <0.05).8 Given that the
average Preference under risk condition is 3.75, the above results suggest that the existence of

8

As shown in Table 2 Panel B Model 3, we also find that Risk preference is positively associated with higher
preference for relative performance contracts, suggesting that risk-taking individuals find relative performance
contracts attractive.

78

The Japanese Accounting Review, 6 (2016), 65-93

TABLE 2: DESCRIPTIVE STATISTICS
Panel A: Dependent Variable and Mediating Variable
Risk Condition
3.75 (3.50; 1.48)
5.69 (5.50; 0.95)
16Preference
ConfidenceN

Ambiguity Condition
2.33 (2.00; 1.19)
4.67 (5.00; 1.19)
18

T-TestP < 0.01
P < 0.01

Notes:
1. This panel presents average values for Preference and Confidence under the two conditions,with the median and the standard deviation in the parentheses.
2. P values are based on two-tailed t-tests of the mean.

Panel B: Control Variable
Gender
GPA
Risk
Competition
N

Risk Condition
0.38 (0.00; 0.50)
1.19 (1.00; 0.54)
2.44 (2.50; 1.09)
5.88 (6.00; 1.20)
16

Ambiguity Condition
0.56 (1.00; 0.51)
1.33 (1.00; 0.69)
1.94 (2.00; 0.87)
5.28 (5.00; 1.49)
18

T-TestP = 0.31
P = 0.50
P = 0.15
P = 0.21

Notes:
1. This panel presents average values for control variables under the two conditions, with themedian and the standard deviation in the parentheses.
2. P values are based on two-tailed t-tests of the mean.

Panel C: Pearson Correlations among Variables
Ambiguity
Preference
Confidence
GenderGPA
Risk

Preference-0.22*

Confidence-0.26**
0.55***

Gender
-0.03-0.28-0.63***

GPA
0.12
0.16
-0.22
0.07

Risk
-0.13
0.43**
0.31*-0.29*-0.03

Competition
-0.15
0.25
0.58***-0.61***
0.03
0.06

Notes:
1. This panel presents the Pearson correlations among all variables used in empirical testing.
2. ***, **, and * denote 1%, 5%, and 10% significance levels, respectively.

ambiguity in common uncertainty reduces preference for relative performance contracts by 31%
to 38%, depending on what control variables are included.9 Overall, we find strong and robust
evidence in support of H1. Although relative performance contracts are used to insulate
employees from common uncertainty, employees are sensitive to whether the common

931% is 1.17/3.75. 38% is 1.42/3.75, with 1.17 and 1.42 as coefficients for Ambiguity estimated from regression
analysis as per Table 3 Panel B.

Bai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

TABLE 3: EFFECT OF AMBIGUITY ON PREFERENCE (H1)
Ambiguity

Model 1-1.42***(-3.09)Model 2
-1.39***(-3.05)-0.63(-1.39)0.57(1.55)

0.21
34

0.26
34

Gender
GPA
Risk
Competition
Adjusted R2
N

Model 3
-1.17**(-2.54)-0.25(-0.43)0.54(1.50)
0.45*(1.90)
0.09(0.45)
0.29
34

Notes:
1. This panel presents the multiple regression analysis result to test the effect of Ambiguity on
Preference.
2. T-scores are reported in the parentheses.
3. ***, **, and * denote 1%, 5%, and 10% significance levels, respectively, based on two-tailed
tests.

TABLE 4: EFFECT OF AMBIGUITY ON CONFIDENCE (H2−STEP ONE)

Ambiguity

Model 1-1.02***(-2.75)Model 2-0.75**(-2.46)-1.30***(-4.31)-0.27(-1.10)

0.17
34

0.47
34

Gender
GPA
Risk
Competition
Adjusted R2
N

Model 3-0.59*(-1.95)-0.78**(-2.05)0.33(-1.39)0.15(0.95)
0.28*(2.02)
0.51
34

Notes:
1. This panel presents the multiple regression analysis result to test the effect of Ambiguity on
Confidence.
2. T-scores are reported in the parentheses.
3. ***, **, and * denote 1%, 5%, and 10% significance levels, respectively, based on two-tailed
tests.

79

80

The Japanese Accounting Review, 6 (2016), 65-93

TABLE 5: EFFECT OF CONFIDENCE ON PREFERENCE (H2−STEP TWO)

Ambiguity
Confidence

Model 1-0.88*(-1.88)0.53**(2.63)

Model 2-0.87*(-1.94)0.69***(2.77)
0.26(0.50)
0.76**(2.23)

0.33
34

0.47
34

Gender
GPA
Risk
Competition
Adjusted R2
N

Model 3-0.76*(-1.71)0.69**(2.63)
0.29(0.51)
0.77**(2.27)
0.35(1.60)-0.10(-0.47)0.42
34

Notes:
1. This panel presents the multiple regression analysis result to test the effect of Confidence on
Preference.
2. T-scores are reported in the parentheses.
3. ***, **, and * denote 1%, 5%, and 10% significance levels, respectively, based on two-tailed
tests.

uncertainty has an ambiguous nature. H2 predicts that confidence mediates the relation between
ambiguity and preference for relative performance contracts. Following Sobel (1982), we takethree steps to test this hypothesis: First, we test the effect of the independent variable (i.e.,
Ambiguity) on the mediating variable (i.e., Confidence); Second, we test the effect of themediating variable (i.e., Confidence) on the dependent variable (i.e., Preference); Third, we test themediating effect of the independent variable (i.e., Ambiguity) on the dependent variable (i.e.,
Preference) through the mediating variable (i.e., Confidence). As shown in Table 2 Panel A, theaverage Confidence is 5.69 in the risk condition and 4.67 in the ambiguity condition (p < 0.01),
suggesting that participants’ confidence in the ambiguity condition is significantly lower than thatin the risk condition. The Wilcoxon’s rank sum test provides a similar result (Z =2.34; p = 0.02).
Regression results are presented in Table 4. In all three models, the coefficient on Ambiguity issignificantly negative, supporting that ambiguity in common uncertainty dampens confidence. In
addition, as per Model 2 and Model 3 we find that males and subjects who are more willing toenter a competition have higher confidence, consistent with the findings from prior literature(Niederle and Vesterlund 2007; Borghans et al. 2009; Dohmen and Falk 2011).
The results for the second step of testing – whether confidence decreases preference forrelative performance contracts – are presented in Table 5. The coefficients for Confidence fromthe regression analysis demonstrate a similar pattern. It is worth noting that the regression result
is obtained after Ambiguity is controlled for. Confidence, therefore, has an effect on Preference
independent from the direct effect from Ambiguity. GPA is positively related to Preference,Bai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

81

TABLE 6: MEDIATING EFFECT OF CONFIDENCE (H2−STEP THREE)

Indirect EffectModel 1-0.54**(-1.97)

Model 2-0.51*(-1.91)Model 3-0.41*(-1.65)

Gender

No

Yes

Yes

GPA

No

Yes

Yes

Risk
Competition
Adjusted R2
N

No

No

Yes

No
0.33
34

No
0.47
34

Yes
0.42
34

Notes:
1. This table presents the Sobel (1982) test result for the mediating effect of Confidence in therelation between Ambiguity and Preference.
2. Z-scores are reported in the parentheses.
3. **, and * denote 5%, and 10% significance levels, respectively, based on two-tailed tests.

suggesting positive feedback regarding personal skills enhances subjects' willingness to accept
relative performance contracts.10 Competition and Risk are possibly affected by Ambiguity as well,since they are both positively correlated with Confidence (as per Table 2 Panel C). By including
competition attitude and risk tolerance in regression analysis, we limit the extent of variation in
confidence and offer a conservative estimation of the effect of confidence on employee preference
for relative performance contracts.
In the final step, we quantify the mediating effect of confidence in employee preference forrelative performance contracts using the Sobel (1982) test. As shown in Table 6, the indirect
effect of Ambiguity through Confidence is negative and robust to the inclusion of control variables.
The most (least) conservative estimation for the indirect effect is -0.41(-0.54), indicating that
Ambiguity reduces Preference indirectly through Confidence by 0.41 (0.54). Given that the total
effect from Ambiguity to Preference is -1.17 (-1.42), the mediating effect is 35% (38%) of the total
effect. Moreover, when comparing the results from Table 3 and Table 5, we find that if
Confidence is included in the regression model, the direct effect of Ambiguity on Preference isreduced in both magnitude and significance, but not eliminated, suggesting a partial mediation.
We illustrate this relationship in Figure 3, presenting the estimated coefficients both with andwithout control variables.
Taken together, part of ambiguity’s impact on employee preference for relative performance
contracts is mediated through confidence. This finding is consistent with prior literature thatsuggests ambiguity might also be due to discomfort, disturbing and aversive feelings, and change
in the anchoring and adjustment process (Einhorn and Hogarth 1985, 1986; Chow and Sarin
2001; Pulford and Colman 2007).
10

Lower skilled employees tend to choose low incentive weight (Chow 1983; Waller and Chow 1985; Shields andWaller 1988; Bonner and Sprinkle 2002).

82

The Japanese Accounting Review, 6 (2016), 65-93

FIGURE 3: EMPIRICAL MODEL

Independent
Variable (IV)[-1.17**, -1.42***]

Ambiguity

Dependent Variable(DV)
Preference for
Relative PerformanceContracts[-0.76*, -0.88*]
Independent
Variable (IV)

Declined Direct Effect due to Mediator

Dependent Variable(DV)
Preference for Relative
PerformanceContracts

Ambiguity[-0.59*, -1.02***][0.53**, 0.69**]Mediator
Confidence

Notes:
1. This figure illustrates the estimated relationships among ambiguity, confidence, and employee
preference for relative performance contracts.
2. Values at the right-hand side in the brackets are obtained from regression analysis when nocontrol variables are included. Values at the left-hand side in the brackets are obtained from
regression analysis when all control variables are included.
3. Tables 3-5 Panel B present the numeric values used in the figure.

Bai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

83

Follow-up Experiment
While our experiment supports the effect of ambiguity on employee preferences and the
mediating role of confidence, it is tempting to ask whether this phenomenon is sensitive to the
incentive scheme used. Fox and Tversky (1995) suggest that comparison is the predominantsource of ambiguity aversion and when evaluating uncertain prospects independently or separately,
people tend to pay little attention to ambiguity. If this suggestion is true, then the effect of
ambiguity on employee preferences as observed in relative performance incentive contracts should
be muted in an independent incentive contract. We examine this issue in a follow-up experiment,
in which we use a quota scheme as an example of an independent incentive scheme. Under aquota scheme, individuals typically receive a flat rate irrespective of performance until a certain
targeted level of performance is attained. Once individuals reach this quota, they receive a bonus(Bonner et al. 2000). The quota scheme is widely used in practice and has been extensively
examined in the economics literature (Herweg et al. 2010; Oyer 2000; Ericson and Fuster 2011;
Bako and Kalecz-Simon 2013).11
Consider a quota incentive scheme that offers a lump sum bonus if an agent achieves acertain level of performance, which is significantly impacted by uncontrollable events. Also
assume that the agent can easily reach the quota if the common environmental factors work in afavorable way, but will have difficulty reaching the quota if otherwise. The possibility that
common factors work favorably is 50%, which is known to the agent. The agent chooses how
much weight to assign to his incentive pay (i.e., to what extent he would like to have his pay
contingent on his performance measure). In the second scenario, both the impact ofenvironmental factors on performance and the possibility that environmental factors will occur is
unknown to the agent. If ambiguity aversion is unique to relative performance-based incentives,then we should not observe lower incentive weight in the ambiguity condition as compared withthe risk condition. Based on this idea, we design the follow-up experiment in identical format tothe main experiment, except that the incentive scheme is quota-based. If the number of units soldis above 110, then they can receive a bonus. In this case, whether they can receive a bonus
depends largely on the uncontrollable state of economy and does not rely on other employees’
performance. We use a 1 X 2 design and manipulate ambiguity the same way as in the main
experiment. 36 subjects (sophomores and juniors) are asked to choose the incentive weight they
prefer among eleven schemes, identical to those in the main experiment. None of theseparticipants was involved in the main experiment. The experiment instrument is presented inAppendix A. The post-experiment questionnaire is the same as that used in the main experiment(presented in Appendix B).
Table 7 shows descriptive statistics. The mean values for Preference and Confidence areslightly lower in the ambiguity condition, but the differences are not statistically significant.12
These results suggest that the reduced preference occurs only in relative performance-based
incentive contracts and disappears in quota-based incentive contracts in which performance is
11

The major attraction of the quota incentive scheme is expectation-based loss aversion. Specifically, increasing thenumber of different wages reduces the agent's expected utility without providing strong additional incentives(Herweg et al. 2010; Ericson and Fuster 2011). As suggested by Herweg et al. (2010), specifying many different
payments induces uncertainty for the agent and introduces an endogenous complexity cost into contracting based on
psychological foundations.
12
The Wilcoxon’s rank sum test and regression results (untabulated) indicate the same.

84

The Japanese Accounting Review, 6 (2016), 65-93

TABLE 7: FOLLOW-UP EXPERIMENT DESCRIPTIVE STATISTICS
Preference
ConfidenceN

Risk Condition
3.74 (4.00; 1.63)
5.47 (5.00; 0.90)
19

Ambiguity Condition
3.65 (4.00; 2.23)
5.41 (6.00; 0.87)
17

T-TestP = 0.89
P = 0.85

Notes:
1. This panel presents the average values for Preference and Confidence under two conditions
from the follow-up experiment, with the median and the standard deviation in parentheses.
2. P-values are based on two-tailed t-tests of the mean.

4

6

3.5

5.5

Weight Choice Independent

3

5

2.5

4.5

Confidence

Incentive Weight Choice

FIGURE 4: SUPPLEMENTARY ANALYSIS

Weight Choice Relative
Confidence Independent
Confidence Relative

2

4
Risk

Ambiguity

Notes:
1. This figure demonstrates subjects’ average preference for relative performance contracts (theleft vertical axis) and confidence rating (the right vertical axis) in the risk vs. ambiguity
conditions as well as subjects’ average preference for independent performance contracts (theleft vertical axis) and confidence rating (the right vertical axis) in the risk vs. ambiguity
conditions.
2. Table 2 Panel A and Table 7 present the numeric values used in the figure.

evaluated in isolation. This is consistent with prior research that ambiguity aversion, primarily
driven by a comparison between events or between individuals, is greatly reduced or eliminated in
the absence of such a comparison. We summarize the results from the main experiment and thefollow-up experiment in Figure 4

Bai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

85

5. Conclusion
This paper focuses on employee preference for relative performance contracts whenknowledge about common uncertainty is incomplete. We explicitly distinguish between
ambiguous common uncertainties and risky common uncertainties and address the question of
how ambiguity affects contract preferences. Results from laboratory experiments reveal that (i)employees have lower preference for relative performance contracts when the common
uncertainty is ambiguous than when the common uncertainty is risky, and (ii) the effect of
ambiguity on employee preference is mediated by confidence. The follow-up experiment reveals
that similar behaviors are not observed when the incentive contract is based on independent
performance measures, consistent with Fox and Tversky (1995)’s notion that ambiguity aversion
is an inherently comparative effect. By recognizing the effect of ambiguity in employee
contracting preferences, this study makes important contributions to the literatures on relative
performance, employee contract preference, and decision making under ambiguity and has
practical implications for the design and implementation of relative performance-based contracts.
Several important limitations of this study need to be taken into consideration. First, thisstudy does not examine employee effort level and thus cannot directly contribute to the optimal
contracting literature. In addition, recent experimental studies show that principal-agent
interactions, such as reciprocity and perceived fairness, are critical to contract efficiency (Fehr etal. 2007; Fehr et al. 2011; Kuang and Moser, 2009; Maas et al. 2011; Brown et al. 2014). In thisstudy, however, the focus is on employee preference. This rather narrow focus prevents us fromaddressing how such interactions affect contract optimality.
Second, all subjects participating in the experiment received class credit but not monetarycompensation. This reward scheme, consistent with that used in some experiments in Fox andTversky (1995), reflects our focus on employee contract preference rather than contract efficiency.
If we were to study contract efficiency, then we would design the experiment in a different way
that measures participants’ effort levels and links their rewards with effort levels. Nevertheless,this reward scheme prevents us from controlling the incentives of participants and imposes animportant limitation of this study.
Third, similar to many experimental studies, we use a case setting to elicit subjects’
preferences, which raises the question of generalizability. Although we believe that this setting isappropriate for this study, future research may benefit from using alternative business scenarios or
conducting field experiments. Finally, the ratings on confidence, competition preference, and risk
attitude are self-reported by experiment subjects and thus are potentially noisy. Future studies
may consider measuring these traits in alternative ways, such as engaging subjects with certain
tasks.
In this study we examine only two types of commonly used incentive contracts (i.e., relative
performance-based contracts and quota-based contracts). The effect of ambiguity on a broader
range of incentive schemes awaits further investigation. For example, what are employees’
preferences on piece rate-based contract under ambiguity?13 What is the effect of ambiguity ongroup-based compensation? Is it possible to eliminate ambiguity in subjective performancemeasures? These questions are warranted to further our understanding of performance13

In accounting literature, incentive schemes are generally classified into four categories: fixed pay, piece-rate, quota,
and tournament (Bonner et al. 2000).

86

The Japanese Accounting Review, 6 (2016), 65-93

measurement and contract design. Finally, the scope of this study is limited to employee contract
preference. The effect of employee sorting on performance, which arises from individual
preferences, is increasingly emphasized in the literature. Self-selected relative compensation
schemes attract employees with traits desirable to the company and thus have a higher
performance outcome (Niederle and Vesterlund 2007; Eriksson et al. 2009; Dohmen and Falk2011). It will be fruitful to explore the performance effects of employee sorting due to ambiguity.
We leave this topic for future exploration.

REFERENCESABDELLAOUI, M., A. BAILLON, L. PLACIDO, AND P. P. WAKKER. 2011. The rich domain of
uncertainty: Source functions and their experimental implementation. The American Economic Review
101 (2): 695-723.
AGGARWAL, R K., AND A. A. SAMWICK.1999. Executive compensation, strategic competition, andrelative performance evaluation: Theory and evidence. The Journal of Finance 54 (6): 1999-2043.
ANTLE, R., AND A. SMITH. 1986. An empirical investigation of the relative performance evaluation of
corporate executives. Journal of Accounting Research 24 (1): 1-39.
BACH, D. R., B. SEYMOUR, AND R. J. DOLAN. 2009. Neural activity associated with the passive
prediction of ambiguity and risk for aversive events. The Journal of Neuroscience 29 (6): 1648-1656.
BAIMAN, S., AND J. S. DEMSKI. 1980. Economically optimal performance evaluation and control systems.
Journal of Accounting Research 18: 184-220.
BAKÓ, B., AND A. KÁLECZ-SIMON. 2013. Quota bonuses with heterogeneous agents. Economics Letters
119 (3): 316-320.
BARNSLEY, L., P. M. LYON, S. J. RALSTON, E. J. HIBBERT, I. CUNNINGHAM, F. C. GORDON, AND M.
J. FIELD. 2004. Clinical skills in junior medical officers: a comparison of self-reported confidence andobserved competence. Medical Education 38 (4): 358-367.
BARTLING, B., E. FEHR, M. A. MARÉCHAL, AND D. SCHUNK. 2009. Egalitarianism andcompetitiveness. The American Economic Review 99 (2): 93-98.
BECKER, S. W., AND F. O. BROWNSON. 1964. What price ambiguity? Or the role of ambiguity indecision making. Journal Political Economy 72: 62-73.
BIGUS, J. 2012. Vague auditing standards and ambiguity aversion. Auditing: A Journal of Practice & Theory
31 (3): 23-45.
BOLINO, M. C., AND W. H. TURNLEY. 2007. Old faces, new places: Equity theory in cross-culturalcontexts. Journal of Organizational Behavior 29 (1): 29-50.
BONNER, S. E., R. HASTIE, G. B. SPRINKLE, AND S. M. YOUNG. 2000. A review of the effects offinancial incentives on performance in laboratory tasks: Implications for management accounting.
Journal of Management Accounting Research 12 (1): 19-64.
BONNER, S. E., AND G. B. SPRINKLE. 2002. The effects of monetary incentives on effort and task
performance: Theories, evidence, and a framework for research. Accounting, Organization and Society,27 (4): 303-345.
BORGHANS, L., J. J. HECKMAN, B. H. GOLSTEYN, AND H. MEIJERS. 2009. Gender differences in risk
aversion and ambiguity aversion. Journal of the European Economic Association 7 (2-3): 649-658.

Bai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

87

BOSSAERTS, P., P. GHIRARDATO, S. GUARNASCHELLI, AND W. R. Zame. 2010. Ambiguity in asset
markets: Theory and experiment. Review of Financial Studies 23 (4): 1325-1359.
BROWN, J. L., P. R. MARTIN, D. V. MOSER, AND R. A. WEBER. 2014. The consequences of hiring
lower-wage workers in an incomplete-contract environment. The Accounting Review 90 (3): 941-966.
BUSHMAN, R. M., R. J. INDJEJIKIAN, AND A. SMITH. 1996. CEO compensation: The role of individual
performance evaluation. Journal of Accounting & Economics 21 (3): 161-193.
CAMERER, C., AND D. LOVALLO. 1999. Overconfidence and excess entry: An experimental approach.
American economic review 89 (1): 306-318.
CAMERER, C., AND M. WEBER. 1992. Recent developments in modeling preferences: uncertainty andambiguity. Journal of Risk and Uncertainty 5 (4): 325-370.
CASKEY, J. A. 2009. Information in equity markets with ambiguity-averse investors. Review of Financial
Studies 22 (9): 3595-3627.
CHATEAUNEUF, A., AND J. H. FARO. 2009. Ambiguity through confidence functions. Journal of
Mathematical Economics 45 (9): 535-558.
CHERRY, T. L., AND J. F. SHOGREN. 2007. Rationality crossovers. Journal of Economic Psychology 28 (2):261-277.
CHOW, C. W. 1983. The effects of job standard tightness and compensation scheme on performance: an
exploration of linkages. The Accounting Review 58 (4): 667-685.
CHOW, C. C., AND R. K. SARIN. 2001. Comparative ignorance and the Ellsberg Paradox. Journal of Risk
and Uncertainty 22 (2): 129-139.
COLES, J. L., N. D. DANIEL, AND L. NAVEEN. 2006. Managerial incentives and risk-taking. Journal of
Financial Economics 79 (2): 431-468.
DOHMEN, T., AND A. FALK. 2011. Performance pay and multidimensional sorting: Productivity,
preferences, and gender. The American Economic Review 101 (2): 556-590.
DYE, R. A. 1992. Relative performance evaluation and project selection. Journal of Accounting Research 30(1): 27-52.
EASLEY, D., AND M. O’HARA. 2009. Ambiguity and nonparticipation: the role of regulation. Review of
Financial Studies 22 (5): 1817-1843.
EINHORN, H. J., AND R. M. HOGARTH. 1985. Ambiguity and uncertainty in probabilistic inference.
Psychological Review 92 (4): 433-461.
EINHORN, H. J., AND R. M. HOGARTH. 1986. Decision making under ambiguity. The Journal of Business
59 (4): IIS225.
ELLSBERG, D. 1961. Risk, ambiguity, and the savage axioms. Quarterly Journal of Economics 75: 643-669.
EPSTEIN, L. G., AND M. SCHNEIDER. 2008. Ambiguity, information quality, and asset pricing. The
Journal of Finance 63 (1): 197-228.
EPSTEIN, L. G., AND J. ZHANG. 2001. Subjective probabilities on subjectively unambiguous events.
Econometrica 69 (2): 265-306.
ERICSON, K. M., AND A. FUSTER. 2011. Expectations as endowments: evidence on reference-dependent
preferences from exchange and valuation experiments. The Quarterly Journal of Economics 126 (4):
1879-1907.
ERIKSSON, T., S. TEYSSIER, AND M. C. VILLEVAL. 2009. Self-selection and the efficiency of tournaments.
Economic Inquiry 47 (3): 530-548.

88

The Japanese Accounting Review, 6 (2016), 65-93

FEHR, E., A. KLEIN, AND K. M. SCHMIDT. 2007. Fairness and contract design. Econometrica 75 (1): 121154
FEHR, E., O. HART, AND C. A. ZEHNDERA. 2011. Contracts as reference points—experimental
evidence. The American Economic Review 101 (2): 493-525.
FELTHAM, G. A., AND J. XIE. 1994. Performance measure congruity and diversity in multi-task
principal/agent relations. The Accounting Review 69 (3): 429-453.
FISHBURN, P. eds. 1988. Uncertainty Aversion and Separated Effects in Decision Making under Uncertainty.
Berlin: Springer-Verlag.
FOX, C. R., AND A. TVERSKY. 1995. Ambiguity aversion and comparative ignorance. The Quarterly
Journal of Economics 110 (3): 585-603.
FREDERICKSON, J. R. 1992. Relative performance information: the effects of common uncertainty andcontract type on agent effort. The Accounting Review 67 (4): 647-669.
GAJDOS, T., T. HAYASHI, J. M. TALLON, AND J. C. VERGNAUD. 2008. Attitude toward imprecise
information. Journal of Economic Theory 140 (1): 27-65.
GHIRARDATO, P., AND M. MARINACCI. 2002. Ambiguity made precise: A comparative
foundation. Journal of Economic Theory 102 (2): 251-289.
GHOSH, D., AND M. R. RAY. 1997. Risk, ambiguity, and decision choice: some additional evidence.
Decision Sciences 28 (1): 81-104.
GIBBONS, R. 1998. Incentives in organizations (No. w6695). National bureau of economic research working
paper.
GIBBONS, R., AND K. J. MURPHY. 1990. Relative performance evaluations for chief executive officers.
Industrial & Labor Relations Review 43 (3): 30S-51S.
GILBOA, I. 1987. Expected utility with purely subjective non-additive probabilities. Journal of Mathematical
Economics 16 (1): 65-88.
HAKA, S. F., J. L. LUFT, AND B. BALLOU. 2000. Second-order uncertainty in accounting information andbilateral bargaining costs. Journal of Management Accounting Research 12 (1): 115-139.
HANNAN, R. L., R. KRISHNAN, AND D. NEWMAN. 2008. The effects of disseminating relative
performance feedback in tournament versus individual performance compensation plans. The
Accounting Review 83 (4): 893-913.
HANNAN, R. L., G. P. MCPHEE, A. H. NEWMAN, AND I. D. TAFKOV. 2013. The effect of relative
performance information on performance and effort allocation in a multi-task environment. The
Accounting Review 88 (2): 553-575.
HEATH, C., AND A. TVERSKY. 1991. Preference and belief: Ambiguity and competence in choice under
uncertainty. Journal of Risk and Uncertainty 4 (1): 5-28.
HERWEG, F., D. MÜLLER, AND P. WEINSCHENK. 2010. Binary payment schemes: Moral hazard and loss
aversion. The American Economic Review 100 (5): 2451-2477.
HOGARTH, R. M., AND H. KUNREUTHER. 1988. Risk, ambiguity, and insurance. Journal of Risk andUncertainty 2 (1): 5-35.
HOLMSTROM, B. 1980. A discussion of economically optimal performance evaluation and control systems.
Journal of Accounting Research 18 (Supplement): 221-226.
HOLMSTROM, B. 1982. Moral hazard in teams. The Bell Journal of Economics 13 (2): 324-340.
HSU, M., M. BHATT, R. ADOLPHS, D. TRANEL, and C. F. CAMERER. 2005. Neural systems respondingBai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts89

to degrees of uncertainty in human decision-making. Science 310 (5754): 1680-1683.
ITTNER, C. D., D. F. LARCKER, AND M. V. RAJAN. 1997. The choice of performance measures in annual
bonus contracts. The Accounting Review 72 (2): 231-255.
JANAKIRAMAN, S. N., R. A. LAMBERT. AND D. F. LARCKER. 1992. An empirical investigation of therelative performance evaluation hypothesis. Journal of Accounting Research 30 (1): 53-69.
KEREN, G., AND L. E. GERRITSEN. 1999. On the robustness and possible accounts of ambiguity aversion.
Acta Psychologica, 103 (1): 149-172.
KNIGHT, F. H. 1921. Risk, Uncertainty and Profit. Boston: Hart, Schaffner & Marx.
KRISHNAN, R., J. L. LUFT, AND M. D. SHIELDS. 2005. Effects of accounting-method choices on
subjective performance-measure weighting decisions: experimental evidence on precision and error
covariance. The Accounting Review 80 (4): 1163-1192.
KUANG, X., AND D. V. MOSER. 2009. Reciprocity and the effectiveness of optimal agency contracts. The
Accounting Review 84 (5): 1671-1694.
KÜHBERGER, A., AND J. PERNER. 2003. The role of competition and knowledge in the Ellsberg task.
Journal of Behavioral Decision Making 16 (3): 181-191.
LAZEAR, E., AND S. ROSEN. 1981. Rank-order tournaments as optimum labor contracts. The Journal of
Political Economy 89 (5): 841-864.
LEE, H. J., Y. IIJIMA, AND C. READE. 2011. Employee preference for performance-related pay: predictors
and consequences for organizational citizenship behaviour in a Japanese firm. The International Journalof Human Resource Management 22 (10): 2086-2109.
MAAFI, H. 2011. Preference reversals under ambiguity. Management Science 57 (11): 2054-2066.
MAAS, V. S., M. VAN RINSUM, AND K. L. TOWRY. 2011. In search of informed discretion: an
experimental investigation of fairness and trust reciprocity. The Accounting Review 87 (2): 617-644.
MACCHERONI, F., M. MARINACCI, AND A. RUSTICHINI. 2006. Ambiguity aversion, robustness, and thevariational representation of preferences. Econometrica 74 (6): 1447-1498.
MATSUMURA, E. M., AND J. Y. SHIN. 2006. An empirical analysis of an incentive plan with relative
performance measures: evidence from a postal service. The Accounting Review 81 (3): 533-566.
MUKERJI, S., AND J. M. TALLON. 2001. Ambiguity aversion and incompleteness of financial markets. The
Review of Economic Studies 68 (4): 883-904.
NALEBUFF, B., AND J. STIGLITZ. 1983. Prizes and incentives: towards a general theory of compensationand competition. The Bell Journal of Economics 14 (1): 21-43.
NELSON, M. W., AND W. R. KINNEY Jr. 1997. The effect of ambiguity on loss contingency reporting
judgments. The Accounting Review 72 (2): 257-274.
NIEDERLE, M., AND L. VESTERLUND. 2007. Do women shy away from competition? Do men compete
too much? The Quarterly Journal of Economics 122 (3): 1067-1101.
OYER, P. 2000. A theory of sales quotas with limited liability and rent sharing. Journal of labor Economics
18 (3): 405-426.
PRENDERGAST, C. 1999. The provision of incentives in firms. Journal of Economic Literature 37 (1): 7-63.
PULFORD, B. D., AND A. M. COLMAN. 2007. Ambiguous games: evidence for strategic ambiguity
aversion. The Quarterly Journal of Experimental Psychology 60 (8): 1083-1100.
SARIN, R. K., AND M. WEBER. 1993. Effects of ambiguity in market experiments. Management Science 39

90

The Japanese Accounting Review, 6 (2016), 65-93(5): 603-615.
SAVAGE, L. 1954. The Founations of Statistics. New York: Wiley.
SCHMEIDLER, D. 1989. Subjective probability and expected utility without additivity. Econometrica 57 (3):571-587.
SCOTT, D., M. BROWN, J. SHIELDS, R. J. LONG, C. H. ANTONI, E. J. BECK-KRALA... AND S. J.
PERKINS. 2015. A global study of pay preferences and employee characteristics. Compensation &Benefits Review 47 (2): 66-70.
SEGAL, U. 1987. The Ellsberg Paradox and risk aversion: an anticipated utility approach. International
Economic Review 28 (1): 175-202.
SHIELDS, M. D., AND W. WALLER. 1988. An experimental labor market study of accounting variables in
employment contracting. Accounting, Organization and Society 13 (6): 581-594.
SlOVIC, P., AND A. TVERSKY. 1974. Who accepts savage's axiom? Behavioral Science 19 (6): 368-373.
SOBEL, M. E. 1982. Asymptotic confidence intervals for indirect effects in structural equation
models. Sociological Methodology 13: 290-312.
TAFKOV, I. D. 2012. Private and public relative performance information under different compensation
contracts. The Accounting Review 88 (1): 327-350.
WALLER, W., AND C. W. CHOW. 1985. The self-selection and effort effects of standard-based
employment contracts: a framework and some empirical evidence. The Accounting Review 60 (3): 458476.
WILCOXON, F. 1945. Individual comparisons by ranking methods. Biometrics Bulletin 1 (6): 80-83.
WOLFSON, M. A. 1985. Tax, incentive, and risk-sharing issues in the allocation of property rights: thegeneralized lease-or-buy problem. The Journal of Business 58 (2): 159-171.
ZIMBELMAN, M., AND W. WALLER. 1999. An experimental investigation of auditor-auditee interaction
under ambiguity. Journal of Accounting Research 37: 135-155.

Bai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

91

Appendix A: Experiment Instrument
Risk condition:
After receiving your Bachelor's degree, you jointed TM, Inc., a medical equipment company,
as a sales associate. Next year you are going to work at country P to sell a diagnostic device that
TM has recently developed, together with three other sales associates who graduated from college
and joined TM at the same time as you. How many units of that device you can sell depends onCountry P's economy and your personal factors, such as skills, knowledge, and effort etc. Country
P's economy can be either good or bad. There is a 50-50 chance that country P will have a good
economy versus a bad economy next year.14 A sales associate is expected to sell between 60 and 120
units if the economy is bad and between 100 and 160 units if the economy is good. The sales
price is determined by TM. You cannot change the selling price.
Your compensation next year contains two parts: fixed pay and bonus pay. You are entitled
to receive the fixed pay no matter how many units you sell. You can receive a bonus only if thenumber of devices you sell next year is in the top half of among the four sales associates. In other words,
the units sold by you and three other associates will be ranked in decreasing order. You will receive abonus if you are among the top two ranking associates and receive no bonus if otherwise.15 Your
supervisor gave you eleven different compensation package options for you to choose. Please open
envelope 2 to make a selection among compensation plans.

14This italicized sentence does not exist in the ambiguous condition.
In the follow-up experiment, the italicized part is replaced by “You can receive a bonus only if the number of units
you sell next year is equal to or above 110.”

15

92

The Japanese Accounting Review, 6 (2016), 65-93

Appendix B: Post-Experiment Questionnaire
Thank you for participating in the experiment. Please answer the following questions.
1. The chance that country P will have a good economy versus a bad economy next year is
known. (34 answered correctly)
True

False

2. Country P’s economy influences the number of devices sold. (34 answered true)
True

False

3. My personal factors, such as knowledge, skill, effort etc. influence the number of devices
sold. (34 answered true)
True

False

4. How many devices other sales managers sold influences my bonus pay. (34 answered
true)
True

False

5. My pay was based on the compensation plan I chose. (34 answered true)
True

False

6. I could choose among alternative compensation plans. (34 answered true)
True

False

7. To what extent do you describe yourself as confident?
1
2
3
4
5
Not at all
Somewhat
A good bit

6

7
Very much

Bai and Krishnan:
Effects of Ambiguous Common Uncertainty on Employees’ Preference for Relative Performance Contracts

93

8. How likely that you will bet a day’s income at horse races?
1

2

3

4

5

Very unlikely

Unlikely

Not sure

LikelyVery likely

9.

To what extent do you like to participate in a competition?
1

2

Not at all

3

4

5

Somewhat

6

A good bit

7
Very much

Please answer the following questions to tell us more about you:
1. What is your gender?

Male

2. What is your G.P.A at XXX University?

Female<3.0

3.0-3.5>3.5

Thank you! Please put your name on the Sign-in Sheet to earn three extra points.