The Effects of Goals and Pay Structure on Managerial Reporting Dishonesty

Abstract

Organizations often address agency concerns through reward systems such as goal setting and monetary incentives, and while these are important mechanisms for increasing and aligning employee effort, they can lead to undesirable or unethical behaviors. In this article, we explore the interactive effects of goals and pay structures on the amount of dishonesty that occurs in managerial reporting. Using a simulation replicating the cost reporting decisions made by managers, we find that having cost goals decreases dishonesty when managers are paid a flat wage and increases dishonesty when managers are paid a bonus for hitting certain targets. We also observe a “slippery step” effect, wherein dishonest behavior becomes increasingly worse once managers have crossed a certain threshold of dishonesty. This research helps disentangle the effects of goals and monetary incentives and identifies an important boundary condition to warnings about the dangers of goal setting in organizations.

Full text

THE EFFECTS OF GOALS AND PAY STRUCTURE ON
MANAGERIAL REPORTING DISHONESTY
Stephen J. Sauer
Clarkson University
Matthew S. Rodgers
Ithaca College
William J. Becker
Virginia Tech
Key Words: goalsetting, incentives, dishonesty
JEL Classification(s): C92, D91, M52
Abstract
Organizations often address agency concerns
through reward systems such as goal setting and
monetary incentives, and while these are important
mechanisms for increasing and aligning employee
effort, they can lead to undesirable or unethical
behaviors. In this article, we explore the interactive
effects of goals and pay structures on the amount of
dishonesty that occurs in managerial reporting.
Using a simulation replicating the cost reporting
decisions made by managers, we find that having
cost goals decreases dishonesty when managers are
paid a flat wage and increases dishonesty when
managers are paid a bonus for hitting certain
targets. We also observe a “slippery step” effect,
wherein dishonest behavior becomes increasingly
worse once managers have crossed a certain

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378
threshold of dishonesty. This research helps
disentangle the effects of goals and monetary
incentives and identifies an important boundary
condition to warnings about the dangers of goal
setting in organizations.
INTRODUCTION
Organizations continually face challenges in which the
desires of the employees do not align with the desires of the firm.
To address these concerns, organizations often use incentive
compensation schemes and goal-setting to motivate desired
behaviors. Although they are often effective at increasing and
aligning employee effort, both of these motivation mechanisms
can also contribute to unethical behavior (Treviño, den
Nieuwenboer, & Kish-Gephart, 2014). More importantly, these
organizational practices and structures can interact, and it is
critical to understand how that interaction affects the likelihood
that people will act dishonestly. In this article, we take up the
pursuit of that question directly, linking theory from the areas of
accounting, management, and psychology to help understand the
effects of goals and incentives on cost reporting behavior. In doing
so, our research serves to complement the basic tenets of goal
theory by systematically exploring what happens when goals and
incentives are used together. In examining the potential boundary
conditions that exist when both goal-setting practices and incentive
payment structures are employed, this work addresses a gap in the
literature.
The benefits of goal-setting are well documented, and a
broad and rigorous literature indicates that giving employees
precise, challenging goals leads to greater effort and performance
(Atkinson, Kaplan, Matsumura, & Young, 2007; Banker, Chang, &
Das, 1998; Locke & Latham, 1990, 2002, 2006; Merchant, 1998;
Shantz & Latham, 2011; Yukl & Latham, 1978). Because of these
advantages, goals are often a critical part of organizations’

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performance management systems and are embedded in annual
reviews, budgets, and measurement systems such as the balanced
scorecard and benchmarking. While goals can be formally tied to
compensation, they can also be used as a non-compensated means
of directing employees’ effort as well as communicating an
organization’s intentions and expectations (Locke & Latham,
2002). There is increasing recognition, however, that goals can
have unintended negative consequences (Harris & Bromiley, 2007;
Larrick, Heath, & Wu, 2009; Ordoñez, Schweitzer, Galinsky, &
Bazerman, 2009a). Research has confirmed some of the potential
goal-setting dangers initially posited by Locke & Latham (1990),
such as dishonesty, unethical behavior, increased risk-taking,
escalation of commitment, and depletion of self-control (e.g.,
Mead, Baumeister, Gino, Schweitzer, & Ariely, 2009; Schweitzer,
Ordoñez, & Douma, 2004).
The attributed reasons for these effects stem from the
psychological reward that comes from goal pursuit (Bandura,
1991; Gellatly & Meyer, 1992) as well as the tendency to direct
attention solely toward the goal and away from other important
factors (Heath, Larrick, & Wu, 1999; Schweitzer et al., 2004). This
goal fixation can have a profound impact on employee behavior,
and the damaging effects appear to be growing stronger in today’s
competitive business landscape. A 2013 survey of more than 3,500
employees in the United States found that 24 percent of employees
in general management and administration functions reported
observing employees falsifying or manipulating financial reporting
information, double the percentage in 2009.
The survey also found that 33 percent of employees in
operations and service functions reported observing employees
falsifying time and expense reports, up from 21 percent in 2009.
When asked what factors might cause managers and employees to
engage in such misconduct, the most common response was “the
pressure to do whatever it takes to meet business goals,” cited by
64 percent of respondents (KPMG, 2013).

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Because of the growing literature on the dangers of goal
setting, there is some debate regarding the indiscreet use of goals
and their broader implications. Current research implies that the
use of goals can be counterproductive or detrimental to
organizations’ welfare (Locke & Latham, 2009; Niven & Healy,
2016; Ordoñez et al., 2009a; Ordoñez, Schweitzer, Galinsky, &
Bazerman, 2009b).
Therein lies the tension. On one hand, goals can increase
employees’ effort-based contributions, leading to greater
productivity and thus, increased firm value. On the other hand, the
presence of challenging goals can decrease firm value via the
agency costs associated with employee dishonesty and sub-optimal
decision making. Absent from this debate is an examination of
how organizational controls such as compensation systems, which
are primarily structural in nature, might influence the negative or
positive impact of goals, which can be primarily psychological in
nature (Locke & Latham, 2009).
In this article we begin to address this theoretical gap by
incorporating the accounting controls literature with management
research looking at the effects of goals on employee dishonesty.
This discussion often emphasizes the relationship between pay
structures and motivation (Bonner, Hastie, Sprinkle, & Young,
2000) but has tended to under-emphasize relevant management
and psychology findings on the relationships between goals and
motivation (Sprinkle, 2003). Likewise, there are few studies in the
goals literature that are multi-disciplinary. Yet, together these
disparate research streams provide valuable insights into the
interplay of goals and pay structures on dishonest behavior.
We integrate these areas by adopting a setting where
employees have discretion over whether costs are reported
accurately and honestly to superiors and/or firm owners. These
types of cost reporting situations are common in today’s
workplace. For example, most organizational departments are cost
centers, where expenses are reported against a budget and the
opportunity for revenue growth is nonexistent. Similarly, service

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professionals such as auditors, contractors, lawyers, and
consultants report hours billed against a target budget which is
often based upon a fixed contract price. These settings offer
considerable potential for both under-reporting and over-reporting
costs, which can undermine organizational objectives and
negatively impact the interests of the firm (Zimmerman, 2014).
These settings also represent an arena for agency issues to
arise, where the interests of the firm and the employee are not
aligned. To address these agency concerns and to mitigate their
deleterious effects, organizations often use incentive schemes
where they pay a bonus for hitting certain targets, thereby creating
a context where goals and incentives are used together. Relying on
both goal-setting research found in the management literature and
the agency theoretic perspective used in accounting, we predict
that the interaction of goals and incentives in these types of
settings will determine the amount of dishonesty that occurs in
managerial cost reporting.
This article advances knowledge in this field in a number
of important ways. First, by considering the psychological impact
of goals as well as the structural impact of organizational payment
schemes, the article identifies an important boundary condition to
the usage of goal-setting as a management tool in organizations.
Second, it incorporates social and psychological factors into
standard agency models to demonstrate the effectiveness of using
agency theory as a broad framework from which to think about
organizational problems. This work also highlights the importance
of context in understanding the influence of organizational
practices and organizational structures in stimulating motivation
and honesty in employees. Finally, this research reveals that people
establish a threshold for dishonesty early on, but have a tendency
to engage in ever-increasing levels of dishonest behavior once they
have cleared that threshold.

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Relevant literature and theory development
Research scholars from a variety of disciplines have
examined the use of both intrinsic and extrinsic rewards to address
the issue of motivation in organizations (see Sorauren, 2000 for a
review), and invariably, this line of inquiry touches upon the usage
of goal-setting as a management tool. Theoretically, having a goal
increases motivation because goal achievement gives rise to
psychological rewards such as positive self-evaluations and higher
self-satisfaction (Bandura, 1991). Empirical evidence largely
supports the claim that specific and challenging goals increase
motivation which then improves employee effort and performance
(Locke & Latham, 1990, 2002, 2006; Schweitzer et al., 2004; Yukl
& Latham, 1978), and thus, goal setting has become accepted
practice in most organizations (Locke & Latham, 2002).
However, the question of whether the effects of goals are
always beneficial is a source of much debate (Ordóñez et al.,
2009a; Locke & Latham, 2009). Because goals provide powerful
psychological rewards, employees can become fixated on goal
achievement. This fixation focuses attention and effort in such a
way that employees may try to achieve their goals at any cost,
engaging in behavior that was not specifically intended. For
example, Schweitzer et al. (2004) found that participants working
on a word production task were more honest about their
production when they were simply told to do their best compared
to when they were given a specific goal.
Overstating performance allowed participants to claim goal
achievement and receive the psychological reward which
outweighed the psychological cost of dishonesty. Schweitzer et al.
(2004) concluded that goal-setting should be used cautiously
because difficult goals, which are often unmet, can lead employees
to behave dishonestly. Building on this perspective, other studies
find that goals can have other unintended effects, including risky
or non-compliant behavior, poor information exchange, and
tactical deception (e.g. Larrick et al., 2009; Mayer, Gerber,

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McDermott, Volkamer, & Vogt, 2017; Poortvliet, Anseel, Janssen,
Van Yperen, & Van de Vliert, 2012). The overall implication of
this research is that employees who are under the direction of
difficult goals may not always act in the best interests of the
organization.
From an organization’s perspective, the problematic feature
of goals leading to dishonesty is analogous to an agency problem
where the desires of employees are not in alignment with the
desires of the firm. Recognizing that this misalignment exists, one
of the key issues for agency theory is motivation. The theory
emphasizes the use of financial incentives to motivate employees
and to realign employees’ interests with those of owners
(Eisenhardt, 1989; Jensen & Murphy, 1990; Murphy, 1999). While
incentives can be effective at increasing productivity, they, like
goals, can also stimulate dishonesty (e.g. Harris & Bromiley,
2007). Therefore, both goals and incentives may spark dishonest
behavior individually, but there is little research that systematically
explores what happens when these two tools are used together.
A number of studies have found that goals, when precise
and difficult, have an additive effect on worker effort and
performance above that of financial incentives alone (e.g.,
Campbell, 1984; Latham, Mitchell, & Dossett, 1978; Locke,
Bryan, & Kendall, 1968), with more recent work (e.g., Corgnet,
Gómez-Miñambres, & Hernán-Gonzalez, 2015; Fatseas & Hirst,
1992; Lee, Locke, & Phan, 1997; Wright, 1992) indicating a
potential multiplicative relationship.
However, it is unclear whether this effect holds in regards
to dishonesty. Schweitzer and colleagues (2004) did begin to
investigate dishonesty when both a performance goal and an
incentive to achieve that goal were present. Specifically,
participants reported less honestly with the financial incentive and
a goal than with the goal alone, suggesting that the psychological
reward associated with the goal and the financial reward
associated with the incentive were additive. However, this study
leaves some important questions unanswered. First, the study is

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devoid of the accounting controls context that can reveal
dishonesty as being associated with both under-reporting and over-
reporting. Second, the study did not fully investigate the mutual
effects of goals and incentives. In particular, it did not consider the
effect of incentives on dishonesty without the presence of a goal.
As a result, there is still a need to explore these combined effects
on dishonest behavior in an environment where accounting
controls are relevant.
To assist in this effort, we turn to the accounting literature,
where organizational design related to management control
systems is a principal focus of study (Zimmerman, 2014).
Management controls can influence ethical behavior, and the
accounting perspective suggests that both goals and the type of
monetary incentive system in use will, at least partially, determine
whether employee behavior is positively or negatively influencing
firm value (Brickley, Smith, & Zimmerman, 2015; Ittner &
Larcker, 2001; Zimmerman, 2014).
For example, a key assumption is that lower-level
managers have private information that is of value to owners. This
information may relate directly to the production process, the cost
of direct material, the cost of manufacturing overhead, or what was
actually produced. Optimally, owners would like managers to
truthfully reveal their private information so that costs can be kept
low. This private information is a source of advantage to managers
because it affords them the opportunity to build slack into the
budget and engage in dishonesty that benefits themselves.
The nature of this dishonesty, however, is likely to be
affected by the way managers are paid. Under a flat-wage pay
structure, managers are tempted to report higher than actual
production costs to pad their budget and increase the funds
available to them for other purposes (i.e., perquisite consumption)
(Jensen & Meckling, 1976; Evans, Hannan, Krishnan, & Moser,
2001; Hannan, Krishnan, & Newman, 2008; Rankin et al., 2008).
This over-reporting is difficult to observe, making it problematic
from an owner’s perspective.

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Consequently, owners, in line with agency theory, may
attempt to incorporate incentives for staying within budget, thus
motivating managers to avoid over-reporting costs. However, an
incentive pay structure can also lead managers to engage in
dishonesty by under-reporting costs in order to come in under
budget and receive their bonus. Thus, in a cost reporting setting,
the potential for dishonesty is present regardless of the pay
structure, but the direction of reporting dishonesty changes
depending upon the type of pay structure – a flat wage encourages
over-reporting while an incentive structure encourages under-
reporting costs.
Because goals can influence unethical behavior, the use of
goals in these different pay contexts is also likely to influence the
level of dishonesty. Although specific, challenging goals are not
commonly studied in a cost reporting setting in accounting, their
usage is no less applicable. The setting of nonbinding,
uncompensated goals by an organization represents a control
mechanism that communicates organizational priorities to
employees. When a non-compensated goal is set, it signals that the
firm is monitoring performance and may be willing to increase
monitoring or replace an employee if underperformance is
significant. Goals in a cost reporting context are intended to
minimize the costs of the activities under workers’ control in order
to meet budgetary objectives. Goals therefore focus employee
attention on cost reporting and away from other considerations
such as the accuracy of reporting or the broader implications for
the firm.
As with performance-oriented goals, cost goals provide a
psychological reward if they are met, which energizes behavior
toward that end (Latham, 2004). This priming toward
psychological rewards can suppress more rational considerations
such as ethicality. If the goal is not met, the cost goal can, like a
performance goal, motivate the employee to engage in dishonest
behavior as they strive to obtain the psychological reward (Niven
& Healy, 2016; Schweitzer et al., 2004). Because cost goals are

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typically associated with a budgetary target, the primary way to
meet a cost goal is to under-report costs. Therefore, the
psychological reward associated with meeting a cost goal
motivates the under-reporting of costs in order to achieve or get
closer to the goal.
This effect of goals, with regards to reporting dishonesty,
will yield different results when considered in concert with
different pay structures. Managers in a flat-wage payment system,
where compensation is unrelated to cost outcomes, face conflicting
interests. The flat wage creates a financial incentive to over-report
costs (to pad their budget, for example), yet the psychological
rewards derived from goal pursuit provide an emotional incentive
to under-report costs. This combination suggests that the direction
of the dishonesty promoted by the flat wage will be mitigated by
the direction of the dishonesty encouraged by an unmet cost goal.
Therefore, in a flat-wage context, managers are more likely to be
dishonest when they do not have a specific cost goal and more
likely to be honest when there is a cost goal.
Hypothesis 1a: Under a flat-wage pay structure, managers
will report costs more dishonestly without a specific goal than with
a specific goal.
This is not the case when managers work within an
incentive pay structure where they stand to receive a bonus if they
are able to keep costs within budget. In this context, the incentive
pay structure encourages under-reporting costs (Lightner, Adams,
& Lightner 1982; Lightner, Leisenring, & Winters 1983; Smith,
Thompson, & Iacovou 2009). As we have argued above, the
presence of a cost goal also encourages managers to under-report
their costs. This means that both financial and psychological
rewards work in the same direction to motivate dishonest behavior.
Therefore, in an incentive context, we expect cost goals and
incentives to have an additive effect, exacerbating the under-
reporting of costs.

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Hypothesis 1b: Under an incentive pay structure, managers
will report costs more dishonestly with a specific goal than without
a specific goal.
Implicit in the development of these hypotheses is the idea
that setting cost targets for managers will impact the effects of the
type of compensation system an organization employs. This leads
us to propose that having a cost goal will act as a moderator in the
relationship between payment structure and dishonest behavior.
Under a flat-wage structure, having a goal will mitigate dishonesty,
and under an incentive pay structure, having a goal will increase
dishonesty.
Hypothesis 1c: The presence of a specific goal will
moderate the relationship between the pay structure (flat-wage vs.
incentive pay) and managerial reporting dishonesty.
We tested these hypotheses in a specially designed
simulation where participants played the role of either production
manager or firm owner. Each participant in the manager role was
paired with an owner, and they made production decisions and
reported their costs to the owner over multiple periods and rounds.
We manipulated the presence of cost goals and managers’ pay
structure and we measured the extent to which managers reported
their costs inaccurately.
METHODS
Participants
Participants for this study were 160 business school
students recruited from a large Midwestern university in the
United States. The majority (70 percent) of students were juniors
or seniors. The average age for participants was 20.5 (SD = 1.1).
51 percent were male. We administered the simulation using z-tree

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software over a computer network in order to maintain anonymity
(Fischbacher, 2007). Each simulation session lasted approximately
45 minutes and participants were paid $13.50, on average, for their
time.
Simulation overview
We designed the simulation to be realistic and rich in
context, and to put participants in a mixed-motive cost reporting
environment similar to that used in other studies which looked at
managerial honesty (Clor-Proell, Kaplan, & Proell, 2015; Evans et
al., 2001; Hannan, Rankin, & Towry, 2006; Rankin et al., 2008) as
well as research on goal-setting by Schweitzer et al. (2004). The
use of experimental methods can be quite useful in assessing
ethical behavior, and this simulation replicated an organizational
setting with two types of roles, referred to as the owner and the
production manager, with participants randomly assigned to one of
these roles.
Owners were assigned a complex set of operating
characteristics that varied product delivery method (JIT or batch),
economic outlook (very good, good, average, or poor), and labor
skill (high, low, or mixed). Based on their owner’s operating
characteristics, production managers made decisions regarding raw
material suppliers (balancing reliability, liquidity, and quality of
raw materials), raw material reserves (small, medium, or large),
and level of quality control of production (high, medium, or low).
After making their choices, production managers reported their
costs to owners over multiple periods and rounds. Overall, the
simulation was designed with all the features of an interactive
simulation, but it did not possess a performance algorithm in
determining the cost feedback. Instead the simulation used
standardized feedback (i.e., the same for everyone) to maintain
consistency across participants.
However, participants were not aware of this approach.
Post-study debriefing suggested that subjects believed they were
participating in an interactive simulation and they took their

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decision-making responsibility seriously. This approach has been
used successfully in other simulations (e.g. Chng, Rodgers, Shih,
& Song, 2012). A fuller description of the simulation’s
standardized feedback is provided below.
Procedure
For each participant, the simulation lasted a total four
rounds with a decision-making period and three cost reporting
periods within each round (twelve periods in total). After they had
finished all four rounds, participants responded to a post-
simulation questionnaire that elicited demographic data and brief
explanations about how they had made their decisions.
We assigned participants to a different owner-production
manager dyad in each round. Prior to the first round, we
introduced participants to their role assignment, had them read an
overview of the task and rules for how they and others would be
compensated, and instructed them on how to make their
recommendations for production. To ensure that they understood
the task and the compensation scheme, we quizzed each
participant using the z-tree software and allowed them to advance
only after they had successfully answered all of the questions.
In the first period of each round, the production manager
made the recommendations regarding raw material reserve, raw
material supplier, and quality control level for production. Once
recommendations were made, the owner reviewed the
recommendations and accepted them. After the owner accepted
their recommendations, the production manager learned the actual
production cost for the first period of the round (all participants
were aware of the range for production cost, which was always
greater than 0 and less than 200 simulation dollars (s$)).
Importantly, the production manager alone learned the actual
production cost in each period - the owner never learned the actual
cost. After learning the actual cost, the production manager
reported a cost to the owner. After the owner had reviewed and
accepted the reported cost for the first period, we gave the

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production manager a summary of earnings. The production
manager then received the second period actual cost and again
reported a cost to the owner, who then reviewed and accepted the
reported costs. This process was repeated for a third period.
After they had completed the third period, we moved
participants on to the next round, where they were randomly paired
with a new owner and thus a new set of operating characteristics.
We used this pairing procedure so that dishonesty on the part of
the person playing the role of production manager (resulting in real
financial gain) would come at the expense of other participants in
the same session. Following this approach allowed us to create a
lifelike tension where production managers’ dishonest decisions
not only benefited them but also imposed a cost for the owners.
Consequently, the owner role is a key role in the
simulation. While owners are not involved in any of the decision-
making, their presence made the simulation more realistic and
amplified the perceived implications for production managers’
decisions. Dishonesty on the part of the manager would cost the
participant playing the role of owner real money in terms of their
payment for the task, and even though the managers and owners
never met and the owners did not know who the managers were,
there was still a moral or ethical burden associated with being
dishonest because one person’s gain resulted in another person’s
loss. In this regard, our organizational setting is similar to that used
by Gino and her colleagues in their research on cheating, and
assured that the costs of dishonest behavior were “salient, well
understood, and meaningful to participants” (Gino, Krupka,
&Weber, 2013, pg. 2192).
Design and manipulations
We used a 2 x 2 between-subjects experimental design,
manipulating the presence of a specific cost goal (specific goal vs.
no specific goal) and the type of wage contract (flat-wage contract
vs. incentive contract).

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Cost goal manipulation. We manipulated the presence of a
specific cost goal in four ways. First, in the specific goal condition,
we told production managers prior to round 1 that their owners felt
it was important for them to keep costs low and therefore they
were given a specific goal for production cost. We reinforced this
manipulation by instructing production managers: “owners are
very concerned that you reach your production cost goals (lower
production costs are generally better for owners because reaching
cost goals may assure a profit for the owner)” (Clor-Proell et al.,
2015, p. 786). Consistent with prior work on goal-setting which
requires goal precision and difficulty (e.g., Schweitzer et al., 2004;
Seijts & Latham, 2001), the cost goal was set so that it was lower
than the lowest actual cost period of any given round, but only
slightly (within 10%).
Second, we described a cost goal as being part of the owner
characteristics, and production managers confirmed this goal
before they made their recommendation. Third, production
managers rated their commitment to the specific goal, both before
making their recommendation and again when they reported their
costs to the owners. Finally, after their owners had reviewed and
accepted their recommendation, production managers saw on their
computer screen a report of their actual cost, which included a
history box with prior round cost goals, actual and reported costs,
and their earnings. There was also a current round box that
contained the current cost goal, actual cost and reported costs for
each period. Below these informational boxes was the current
period cost information upon which the production manager was to
base their cost report to the owner. Underneath that information
was a reminder of the current round cost goal.
In the no specific goal condition, we told production
managers that their owners felt it was important for them to keep
costs low, but we made no mention of a specific cost goal. In the
beginning of each round there was no mention of a cost goal under
the owner characteristics and therefore the production managers
were not asked to confirm one. Finally, on the actual cost report

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screen, there was no mention of specific cost goals in the history
box or current period box.
Wage contract manipulation. We gave participants in the
flat-wage condition a fixed contract worth s$175 in every period,
and we told them that the costs they reported to the owner would
be reimbursed fully, but they (the production managers
themselves) would have to cover the actual production cost.
Therefore, the production manager’s payout formula was: salary +
(reported – actual cost). We also emphasized that because
production managers were only responsible for the actual cost,
they would earn higher compensation for themselves but lower
compensation for the owner if they reported costs that were higher
than actual, and vice versa.
Specifically, the production manager read the following
example before they started the task: “if the actual cost of the
production process you recommended is s$100 and you report a
cost to the owner of s$150, you retain an additional s$50 of
compensation for yourself (s$150 reported cost - s$100 actual cost)
but the owner loses an additional s$50. Conversely, if the actual
cost is s$100 and you report a cost to the owner of s$50, you lose
s$50 of your base compensation (s$50 reported cost - s$100 actual
cost) but the owner gains s$50”) (Clor-Proell et al., 2015, p. 779).
In the incentive condition, we gave production managers a
wage payout that contained a lower base salary (s$75 per period)
and focused participants on reducing costs. This payout was: salary
+ (actual – reported cost). In addition, we told production
managers that owners would like to keep production costs as low
as possible and therefore would pay a dollar for dollar bonus for
costs reported under s$200. Thus, if the production manager
reported a production cost of s$50, he or she would receive a
bonus of s$150 in addition to their flat wage (200 – 50). Similar to
the flat-wage contract condition, we emphasized that if a
production manager under-reported production costs, their
compensation would be increased but the owner’s compensation
would be decreased, and vice versa. Specifically, the production

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manager read the following before starting the task: “if the actual
cost of the production process you recommended is s$100 and you
report a cost to the owner of s$50, you gain an additional s$50
bonus but the owner loses an additional s$50. Conversely, if the
actual production cost is s$100 and you report a cost of s$150, you
lose s$50 of your base pay and the owner gains s$50.”
Under the flat-wage contract, production managers stood to
make the most if they reported a production cost of s$200, whereas
under the incentive contract, production managers could maximize
their earnings by reporting production costs of s$0. Table 1
outlines the payoff structure for each wage contract condition.
We calculated base salaries for all participants so that
regardless of the role they played or the type of payment contract
they held, if production managers reported honestly (in other
words, reported costs were the same as actual costs), participants
would each earn $13.50 (this average includes a $3 payout for
showing up for the simulation). This ensured economical
equivalency across all roles and conditions. However, if
production managers always made reporting decisions that
maximized their earnings, production managers under both a flat-
wage and an incentive contract could earn $18.50 while the owners
under both types of monetary contracts would earn $7.50.
Conversely, if production managers always made reporting
decisions that minimized their earnings, production managers
would earn $7.50 while owners would earn $18.50.

Sauer, Rodgers & Becker: Goals and managerial dishonesty
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Table 1:
Agent Payoff Functions a, b
Panel A: Payoff function before value substitution for the
production managers
Flat Wage Contract $175 + (reported cost–actual cost)
Incentive Contract $75 + ($200 – actual cost) + (actual cost –
reported cost)
Panel B: Payoff function simplified with values used in simulation
for the production managers
Flat Wage Contract $75 + reported cost
Incentive Contract $275 – reported cost
Reported cost range $0…$200
Actual cost = $100
a Note that the participants did not receive the full payoff function information.
For the production managers in the incentive condition, the payoff was simplified
for ease of comprehension. The production mangers were told that their pay was
simply $75 + ($200 – reported cost) but that under-reporting actual cost
increased their bonus earnings and decreased the owner’s earnings.
b Consistent with the focus of this study on agent’s behavior, neither the owner’s
payoff nor the revenues generated from production were ever specified to any
participants. The agents were simply told that under and over reporting actual
costs would affect the amount of money the owners made. The owner’s presence
in the simulation was only needed so that participants did not assume they were
taking money from an endless pot of money or simply the experimenter as well as
to assure no deceit in the simulation.

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395
Dependent variable. Consistent with prior accounting
research in this area (e.g., Clor-Proell et al., 2015; Evans et al.,
2001; Hannan et al., 2006; Rankin et al., 2008), we measured
managerial reporting dishonesty as the difference between reported
and actual cost. Because under-reporting and over-reporting costs
carried different meanings depending upon the contract type, the
difference between reported cost and actual cost is calculated so
that an increasing dishonesty value uniformly represents a
production manager deviating further from actual costs in their
own favor (the production manager’s compensation is increasing
while the owner’s compensation is decreasing).
Thus, the higher the production manager’s dishonesty
value, the greater the amount of additional simulation dollars
claimed by the participant. All 12 simulation periods were
collapsed into an average dishonesty mean for each individual. In
this manner, each participant represents one independent (as
opposed to 12 non-independent) observations. Furthermore, as
noted earlier, the potential cost range over all periods was between
s$0 and s$200 but the overall actual cost mean was s$100.
Accordingly, the theoretical maximum dishonesty value that
participants could have over the 12 periods is s$100.
To enable us to make cross-treatment comparisons, we
drew costs at random prior to the study and applied the same
(yoked) costs to all of the treatment conditions. Thus, all
participants, regardless of condition, observed the same costs (in
four different sequences). Upon completion, a third party who had
no knowledge of the simulation paid each participant in cash and
in private, handing each participant an envelope marked with their
unique ID.
This process maintained anonymity and ensured that
neither the experimenter nor any other participants were aware of
how much any specific participant had earned. By protecting
participant anonymity in this way, the simulation is biased towards
finding straight agency theoretic predictions that individuals are
self-interested and will maximize their own earnings to the extent

Sauer, Rodgers & Becker: Goals and managerial dishonesty
396
possible. Because the production managers alone knew the actual
cost of production, they were free to maximize their payout by
claiming a cost of s$200 under a flat-wage contract (over-reporting
costs) or cost of s$0 under a bonus incentive contract (under-
reporting costs) without having to worry that anyone would know
that they acted in that manner. In this way, the experimental design
precludes any effects that concerns about monitoring, auditing, or
reputation might have on the results (Evans et al., 2001).
RESULTS
To ensure that the four cost sequences observed by
participants had no impact on the results, we conducted a 2 (goal:
specific goal vs. no specific goal) x 2 (pay structure: flat-wage
contract vs. incentive contract) x 4 (cost sequence) ANOVA on the
dependent variable of dishonesty. The cost sequence had no
impact on the dependent measure (F = 1.89, ns.) and there was no
interaction between cost sequence and either goal presence or pay
structure. Accordingly, cost sequence was dropped from all
subsequent analyses. In addition, a repeated measures ANOVA
revealed that there was no effect for period.
Hypothesis testing
In Hypothesis 1a we predicted that under a flat-wage
contract, production managers without specific cost goals will
report more dishonestly than production managers with specific
goals. Results support our hypothesis: under a flat-wage contract,
production managers without specific goals claimed an average of
an additional s$37.88, while production managers with specific
goals claimed only an additional s$19.19 on average (see Table 2).
These results are statistically significant (t = 2.11, p = .02) (one-
tailed).

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Table 2:
Summary of Dishonesty Means
Goal
Monetary Contract
No Specific Goal
Specific Goal
All
Flat Wage Contract
N = 20
N = 20
37.88
19.19
28.54
[32.40]
[22.74]
[29.21]
Incentive Contract
N = 20
N = 20
9.26
25.38
17.32
[17.19]
[33.02]
[27.24]
All
23.57
22.28
22.93
[29.42]
[28.16]
[28.62]
We also expected that under an incentive pay structure
production managers with specific cost goals would report more
dishonestly than production managers without specific goals.
Results indicate that under an incentive contract, production
managers with specific goals claimed an average of an additional
s$25.38 while production managers without specific goals claimed
an average of an additional s$9.26. These results are statistically
significant (t = 1.94, p = .03) (one-tailed), providing support for
Hypothesis 1b.
Taken together, our hypotheses predicted that goal
presence and type of monetary contract would interact to impact
production managers’ dishonesty in reporting, as shown in Figure
1.

Sauer, Rodgers & Becker: Goals and managerial dishonesty
398
Figure 1
Plot of Dishonestya Means
a The dishonesty value is calculated as the difference between actual production
costs and reported production costs. Because the two monetary contracts
differently affected how production managers benefitted by under or over-
reporting actual costs, the dishonesty variable was calculated as cost report less
actual cost for the flat wage contract and actual cost less cost report for the
incentive contract. A higher dishonesty value can be interpreted as production
managers claiming for themselves additional simulation dollars production
managers above/below (depending upon contract type) actual production costs.
A 2 (goal: specific goal vs. no specific goal) x 2 (pay
structure: flat-wage contract vs. incentive contract) ANOVA
reveals a significant interaction between goal presence and type of
monetary contract (F = 8.21, p = .005) (see Table 3).

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Table 3:
Results of ANOVA Test of Dishonesty
Source
DF
S.S.
M.S.
F-Value
p-value
(two-
tailed)
Corrected Model
3
8,608.149
2,869.383
3.887
.012
Intercept
1
42,055.913
42,055.913
56.971
.000
Goal
1
33.261
33.261
0.045
.832
Monetary Contract
1
2,515.338
2,515.338
3.407
.069
Goal * Monetary
Contract
1
6,059.551
6,059.551
8.209
.005
Error
76
56,103.486
738.204
Total
80
Corrected Total
79
As mentioned above, the presence of specific goals under a
flat-wage contract mitigates dishonesty compared to when goals
are not present. However, under an incentive contract, the presence
of specific goals increases dishonesty compared to when goals are
not present. Therefore, Hypothesis 1c is supported; the presence of
cost goals moderates the relationship between type of payment
scheme and managers’ dishonesty in cost reporting.
Supplemental Analyses
The richness of the simulation allowed us to capture some
additional data not included in our primary analyses. In this section
we explore the data further to confirm the primary results as well
as to provide additional insights into our research question and
related questions. Specifically, we were interested in learning
whether dishonest behavior in one period increased the propensity
for participants to lie in future periods. Because participants made
repeated decisions, our data contained a hierarchical structure in

Sauer, Rodgers & Becker: Goals and managerial dishonesty
400
which these decisions were nested within individuals. In order to
investigate how dishonesty in one round carried over to future
rounds, we included lagged measures of dishonesty as within-
person variables. To explore both within- and between-person
relationships in the data, we used random coefficient modeling
with HLM 6 (Bryk, Raudenbush, & Congdon, 1996), which
accounts for the fact that decisions were nested within individuals
and therefore not independent of one another.
To separate within- and between-person effects, we
centered Level 1 predictors around individuals’ means and Level 2
predictors around their grand means (Hofmann, Griffin, & Gavin,
2000). First, we ran a null multilevel model to determine the
relative amount of within-person variance. This analysis found that
48% of the variance in dishonesty on a round by round basis
resided between individuals, leaving 52% of the variance within-
individual. This relatively even split between within- and between-
subjects variance suggests that conducting multilevel analysis is
appropriate.
Table 4 presents these multilevel analyses. Model 1
confirms the findings of our primary analyses as indicated by the
significant interaction between the goal condition and the
incentive condition (b = 34.81, p < .01). The form of the
interaction is consistent with Figure 1. Next, we included the level
of dishonesty in the preceding round to investigate whether
participants’ past choices influenced future behavior. The results
in Model 2 indicate that dishonesty in the current round was
positively related to dishonesty in the preceding round (b = .17, p <
.01). This indicated that individuals who exceeded their typical
level of dishonesty in one round tended to trend upward in their
dishonesty in the following round. Interestingly, participants
seemed to establish a baseline level of dishonesty in the early
periods and once they departed significantly above that baseline,
tended to continue to push their average level of dishonesty higher.
The magnitude of the coefficient suggests that only large
departures had meaningful effects, while relatively minor

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401
departures had very little effect on future dishonesty. These results
suggest that there exists a “slippery step” (rather than a slippery
slope) where small lies do not have long-term effects, but once
dishonesty exceeds a certain threshold, the dishonest behavior
becomes increasingly worse.
Table 4:
HLM Results
Variable
Model 1
Model 2
Model 3
Model 4
Intercept
22.93**
23.51**
23.51**
23.51**
Level 2
Specific Goal
-1.29
.19
-1.61
-1.61
Incentive Contract
-11.21†
-15.31†
-11.64†
-11.64†
Goal x Incentive
34.81**
33.20**
33.47**
36.02**
Level 1
DISlast
.17**
.17**
.16**
Cross-level Interactions
DISlast X Goal
-.13†
-.12†
DISlast X INC
.20**
.20**
DISlast X Goal X INC
.10
Note: Level 1 N = 880, Level 2 =80.
DIS = Dishonesty
INC = Incentive
** = p < 0.01, * = p < 0.05, † = p < 0.10
Next, we investigated whether the effect of past behavior is
influenced by the experimental conditions involving goals and pay
structure. In Model 3, we first tested the two way cross-level
interactions between each condition and the level of dishonesty in
the preceding round (measured as one standard deviation above or
below the mean). The results show that the effect of previous
dishonesty was marginally influenced by the presence of specific
goals (b = -.13, p = .07). Figure 2 shows the nature of the goal
conditional effect. While the slopes of the lines were only

Sauer, Rodgers & Becker: Goals and managerial dishonesty
402
marginally different, simple slopes analysis revealed that when a
specific cost goal was not present the relationship was positive (t =
6.16, p < .01) but the relationship was not significantly different
from zero when specific goals were present (t = 1.80, p = .08).
Therefore, the relationship between past and future dishonesty was
nullified by the presence of specific goals. A more nuanced
reading of the supplementary data suggests that although
individuals with goals exhibited some dishonesty, increases in
dishonesty in one round did not signal a trend toward greater
dishonesty overall as they did for participants when specific goals
were not present.
Figure 2:
Plot of Previous Dishonesty and Goals
The results also show a relationship between past and
future dishonesty that was moderated by pay structure (b = .20, p <
.01). This conditional effect is plotted in Figure 3. Simple slopes

Journal of Accounting, Ethics & Public Policy
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403
analysis indicated that under a flat-wage contract the relationship
was not significantly different from zero (t = 1.68, ns) while under
an incentive contract the relationship was positive (t = 4.69, p <
.01). The graph shows that individuals under a flat-wage contract
tended to show higher and relatively stable levels of dishonesty in
all rounds. However, their past dishonesty was not systematically
related to future dishonesty. In contrast, under an incentive
contract, individuals tended to be less dishonest overall, but once
they increased their level of dishonesty this signaled a trend toward
increasing dishonesty.
Figure 3:
Plot of Previous Dishonesty and Pay Structure
10
15
20
25
30
35
40
Low High
Dishonesty
Dishonesty in Preceding Round
Flat Wage Contract
Incentive Contract
Finally, we investigated whether the effect of previous
dishonesty was influenced by the conjunction of previous
dishonesty with goals and compensation. Model 4 includes a cross-
level, three-way interaction between previous dishonesty, the

Sauer, Rodgers & Becker: Goals and managerial dishonesty
404
presence of specific goals, and pay structure. While the interaction
term was not significant, Preacher, Curran, & Bauer, (2006)
indicate that these complex interactions are better explored
through simple slopes analysis. Figure 4 depicts these relationships
and the simple slopes analyses show that the relationship between
previous dishonesty and future dishonesty was not significantly
different from zero when specific goals were provided and
participants received a flat wage.
Figure 4:
Plot of Previous Dishonesty, Goals, and Pay Structure
0
10
20
30
40
50
60
Low High
Dishonesty
Dishonesty in Preceding Round
Flat Wage Contract & No Specific Goal
Flat Wage Contract & Specific Goal
Incentive Contract & No Specific Goal
Incentive Contract & Specific Goal
For all other conditions, the relationship was positive.
Therefore, we conclude that under a flat-wage contract without
specific goals, individuals showed the greatest level of dishonesty,
and positive departures in dishonesty tended to lead to greater
dishonesty in future periods. The presence of specific goals
reduced the level of dishonesty and also eliminated the trend

Journal of Accounting, Ethics & Public Policy
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toward increasing dishonesty. Under an incentive contract without
specific goals, individuals showed the least overall dishonesty,
even those who traveled down the slippery steps of increasing
dishonesty. Providing goals actually increased the level of
dishonesty with a similar propensity to become more dishonest in
subsequent periods. In summary, under an incentive contract,
managers were more honest without specific goals, while under a
flat-wage contract, specific goals helped to make managers more
honest.
DISCUSSION AND CONCLUSION
The organizational practices of setting goals and using
incentive pay structures are known to be effective ways to
motivate behavior in organizations, but they can also contribute to
unethical behavior. The use of goals in particular has come under
scrutiny in recent years, and we have seen a number of articles that
look at “the dark side” of goal-setting (Barsky, 2008; Niven &
Healy, 2016; Ordóñez et al., 2009a; Schweitzer et al., 2004). In
this article, we integrate theory from the accounting, management,
and psychology literatures to aid in our understanding of how goals
interact with managers’ pay structure to affect dishonesty. In
contrast to prior studies that have focused primarily on how these
two factors impact effort and performance, the present research
specifically investigates the issue of dishonesty in managerial
reporting behavior.
Consistent with our hypotheses, we found support for the
idea that organizations may not be better off using a combination
of incentives and specific goals to motivate employee behavior. In
an opaque environment where managers have private information,
organizations using goals need to consider not only how adding an
incentive pay structure may lead to increased effort but also how it
might lead to increased dishonesty. Conversely, organizations that
use a flat-wage contract may want to consider adding specific
goals as part of the organization’s control system. Not only could

Sauer, Rodgers & Becker: Goals and managerial dishonesty
406
this boost employee productivity, but it could also help attenuate
the risks of managerial dishonesty.
Research Contributions
This research contributes to the literature in several
important ways. First, rather than challenging the use of goal-
setting as a management practice, this study presents an important
boundary condition to arguments concerning its perils. It has been
argued theoretically (Jensen, 2003; Barsky, 2008; Ordóñez et al.,
2009a) and found (Schweitzer et al., 2004; Clor-Proell et al., 2015)
that the presence of difficult goals can lead to the unintended
consequence of increased dishonesty. Yet, Locke and Latham
(2009) warned that there needs to be more research exploring the
contexts where this finding is true.
Specifically, they noted that goals and monetary incentives
are often confounded and research needs to untangle their unique
effects. By considering the psychological impact of goal use as
well as the structural impact of payment schemes, our study helps
address this confound and suggests that while goals certainly can
lead to more dishonesty, the effect is contingent upon the type of
pay structure used in an organization.
Second, this research contributes to the growing literature
attempting to incorporate social and psychological factors into
standard agency models (e.g., Hannan, Rankin, & Towry, 2010;
Kachelmeier, Reichert, & Williamson, 2008; Pouryousefi &
Frooman, 2017; Towry, 2003; Webb, 2002; Zhang, 2008).
Specifically, although this study is focused solely on employee
dishonesty and does not in any way attempt to set up or test an
agency model, the results do suggest that agency theory intuition
serves as an important baseline from which to make behavioral
predictions. However, it also shows that an understanding of
psychological factors that exacerbate or mitigate these predicted
results can lead to a better understanding of behavior. This
contribution is consistent with Baiman (1990), who argues that the
most important contribution of agency theory is to provide a broad

Journal of Accounting, Ethics & Public Policy
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407
framework from which to think generally about organizational
problems, but that more attention should be paid to commonly
observed organizational aspects and less to deriving optimal
contracts.
Third, this research suggests the importance of context in
understanding the influence of goal setting practice and pay
structure in stimulating motivation and honesty in employees. This
article specifically focuses on a cost reporting setting where
managers can either over-report or under-report costs. The findings
suggest that organizations may need to consider the level of
reporting environment opacity before attempting to motivate their
employees. In settings where there is significant private
information, the use of an incentive pay structure without goals
yields the highest level of honesty.
While some organizations may be inclined toward
incorporating expensive control mechanisms to prevent dishonesty,
the effectiveness of these mechanisms is limited because managers
are usually able to keep their under-reporting or over-reporting
practices hidden. An acknowledgement of organizational
conditions is essential in predicting ethical attitudes at the
workplace, hence, there is much to be gained, as suggested by
Salterio and Webb (2006), by investigating contexts that enhance
or detract from employee honesty. By investigating the contextual
influences on how goals and incentives stimulate dishonesty, as
done here, organizations and researchers alike can make
recommendations that promote honesty without incurring
significant monitoring costs.
Practical Implications
In addition to its academic contributions, this article also
presents important managerial implications. Perhaps the most
compelling finding for organizations concerns individuals’
tendency to observe a threshold when they increase their dishonest
behavior over time. The idea that there exists a slippery slope in
which small lies gradually lead to higher levels of unethical

Sauer, Rodgers & Becker: Goals and managerial dishonesty
408
behavior over time is hardly new (Gino & Bazerman, 2009; Welsh,
Ordóñez, Snyder, & Christian, 2015), and we witnessed this
tendency in our own study. But the idea that individuals establish a
baseline level of dishonesty early on and only continue to become
more dishonest after they significantly exceed a certain threshold
is a novel finding. In our study, relatively minor departures had
very little effect on future dishonesty, but once people had cleared
that first “slippery step” they effectively opened the door to ever-
increasing levels of dishonest behavior. This could be due to
competing tensions between reward seeking and ethical
considerations.
Early on these were relatively balanced, but for many
individuals that balance shifted toward reward seeking behavior at
some point during the simulation. Our study suggests that
organizations should consider how they might use goals and
incentive schemes wisely to make that first step high enough to
deter the type of morally disengaged reasoning (Kish-Gephart,
Detert, Treviño, Baker, & Martin, 2014; Moore, Detert, Treviño,
Baker, & Mayer, 2012) that might lead to the next - seemingly
easier - steps. The evolution of dishonest behavior over time was
not a central focus of the current research, but further exploration
of this finding could go a long way to increasing our understanding
of real world dishonesty and unethical behavior.
Limitations and Future Research
As with all research, this study is subject to limitations and
presents a number of unanswered questions that might serve as the
basis for future research. One limitation of this study is that it was
not designed to elicit the underlying psychological mechanisms
driving the behaviors we observed. Regarding the influence of
goals, we argued that reporting goal achievement, even
dishonestly, is a motivator because it offers participants a
psychological reward. However, Barsky (2008) and Clor-Proell et
al. (2015) have each put forward other reasons why the presence of
difficult goals would lead to more dishonesty. Among these,

Journal of Accounting, Ethics & Public Policy
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409
employees may want to punish employers for difficult goals
(reciprocity motivations), or employees may be so goal-focused
that they do not consider the ethical implications of lying (limited
attention argument), or they may simply be anchored to a goal.
Future research should attempt to identify the exact mechanisms
through which goal difficulty can lead to more dishonesty.
A second limitation is that the current research focuses on
situations where individuals fail to attain their goals, as is the case
in many organizations. Indeed, the very nature of benchmarking, a
common management practice (Atkinson et al., 2007; Banker et
al., 1998; Flaherty, Zimmermann, & Murray, 1995), sets up a
situation where optimal performance is never met. Nevertheless,
while goal failure might be the norm in organizations using goals
to motivate, it does not necessarily follow that everyone always
misses their goals. Some individuals might always achieve their
goals while others might miss their goals only occasionally. Future
research might examine how patterns of goal failure and success
lead to more or less dishonesty.
Finally, the current research was developed to isolate the
impact of goals and typical pay structures on managerial behavior.
As such, the use of a controlled laboratory environment with
specific treatment conditions was appropriate for this type of
exploration. This approach allowed us to hone in on production
managers’ willingness to engage in dishonest behavior in the
pursuit of goals and/or compensation, and enabled us to remove
any extraneous “noise” that might otherwise cloud our
observations.
Having said that, a variety of organizational characteristics
that were not included in our experimental design may be found to
exacerbate or attenuate the current results. For example,
organizations exert pressure on individuals which can sway their
judgment of what constitutes ethical behavior (Dempsey, 2015), so
in organizations where either the internal culture or external
expectations stress goal achievement (e.g., meeting analysts’
expectations) the findings in this study may be exacerbated.

Sauer, Rodgers & Becker: Goals and managerial dishonesty
410
Conversely, in organizations where the internal culture or external
expectations stress honesty, the results of this study may be
attenuated. Lastly, the evolution of dishonest behavior over time
was not a central focus of the current research, but we found it
very interesting that people tend to establish a threshold for
dishonesty early on and then engage in ever-increasing levels of
dishonest behavior once they have cleared that threshold. Future
research, both in the field and in the lab, could explore this
phenomenon along with other potential moderators of our results,
and this would go a long way to increasing our understanding of
real world dishonesty and unethical behavior.

Journal of Accounting, Ethics & Public Policy
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411
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