The Moderating Effects of Task Complexity
and Task Attractiveness on the Impact of
Monetary Incentives in Repeated Tasks
Charles D. Bailey
The University of Memphis
Memphis, TN 38152-3120
Nicholas J. Fessler
University of Central Missouri
Warrensburg, MO 64093
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JOURNAL OF MANAGEMENT ACCOUNTING RESEARCH 2011
EXTENDS OUR TWO JMAR STUDIES
CONCERNING THE LIMITATIONS OF MONETARY INCENTIVES

C. Bailey L. D. Brown, and A. F. Cocco. The effects of
monetary incentives on worker learning and
performance in an assembly task (1998)
Monetary incentives will not affect the rate of improvement
(slope of the learning curve).
 Improvement will be reflected in faster initial performance
time on the task (the intercept of the learning curve).


N. Fessler. Experimental evidence on the links
among monetary incentives, task attractiveness,
and task performance (2003)

Incentive compensation degraded individual performance of
an attractive and complex task, while finding no such
degradation in the other combinations of attractive/simple,
unattractive/simple, or unattractive/complex.
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FACTORS THAT MAY MODERATE EFFECTS
OF AN INCENTIVE CONTRACT FOR A TASK
1.
Task complexity


As task complexity increases, the requirements for
skill and knowledge increase, and performance at a
task become less sensitive to increases in effort
(Bonner et al. 2000, 22).
Financial incentives’ impact on overall task performance
is mediated by effort (Bonner and Sprinkle 2002).
Incentives  Effort  Performance
Weaker link for
complex tasks.
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TWO FACTORS THAT MAY MODERATE EFFECTS
OF INCENTIVE CONTRACT FOR A TASK
2.
Perception of the task as being interesting and
attractive (Bonner and Sprinkle 2002).
Ceiling effect: already intrinsically motivated.
 Activation theory: can exceed optimal arousal (stress).
 When an individual is intrinsically motivated, the extrinsic
motivation can interfere with and “crowd out” the intrinsic
motivation of the task’s attractiveness and potentially
degrade performance (Frey and Jegen 2000).

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RESEARCH HYPOTHESIS (PERFORMANCE)
We predict that the relative advantage of piece-rate compensation (versus
fixed wage compensation) for a less complex task will be reduced for a more
attractive task. This leads to the following substantive hypothesis about the
nature of the three-way interaction:

H1: Incentive-based compensation will be more effective
for less complex tasks than for complex tasks, but this
relative advantage will be reduced if the task is attractive.
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EFFECTS ON LEARNING-CURVE PARAMETERS

The theory in Bailey et al. (1998) is grounded in economic
agency theory. But insights from cognitive theory of memory,
including recent evidence from neuroscience, provide a more
plausible basis to support the expectation that piece-rate
compensation is unlikely to improve the rate of learning.
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LEARNING AND INCENTIVES

This study concerns a repetitive, “skill” task



Learn by doing.
Would not apply to, say academic learning.
P. 192:
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REASONS FOR THE WEAK CONNECTION BETWEEN
EXPLICIT MONETARY INCENTIVES AND
IMPROVEMENT

Such tasks rely on tacit, versus explicit, knowledge.
Tacit knowledge is expressed by doing and is difficult for
the doer to explain. Process not accessible to the learner.
 A coach or instruction manual helpful during the learning
phase, showing the student by example or giving advice
about principles, stance, etc.



But a pro golfer may be unable to explain exactly how to make
the swing; has internalized the skill, ‘‘grooved’’ the swing.
Focusing on the details of the act (e.g., when incented to
do so by piece-rate incentives) will only undermine its
effectiveness (Kleiman-Weiner and Berger 2006).
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AUTOMATIC ENCODING OF MEMORY

Certain processes of memory encoding are automatic,
neither requiring conscious attention nor benefitting from
intentional effort. These include the encoding of
information about space, time, and frequency of
occurrence.


We are genetically prepared because of the environmental
importance of these factors (e.g., we need to remember
where our belongings are, and this normally occurs without
effort). Hasher and Zacks (1979)
An advantage for the organism is that automatic
processes do not require attention, of which we have a
limited capacity.

‘‘Automatic encoding of information only minimally diminishes
one’s capacity to process other components of the flow of
information. Such encoding insures that certain basic aspects
of both internal and external events are entered into long-term
memory despite other, concurrent demands upon capacity’’
(Hasher and Zacks 1979, 358).
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HYPOTHESES: EFFECTS ON LEARNING-CURVE
(Note that a learning curve has two parameters, generally
representing the initial performance and the rate of
improvement.)
 H2: When, in a repetitive skill-based task, piece-rate
compensation leads to higher levels of total performance
than fixed-wage compensation, the rate of learning for
participants paid piece-rate compensation will be the
same as the rate of learning for individuals paid fixedwage compensation.
The following hypothesis is a corollary to H2:
 H3: For a repetitive skill-based task, when piece-rate
compensation leads to higher levels of total performance
than fixed-wage compensation, individuals receiving
piece-rate compensation will require less time for the
initial performance cycle than individuals paid fixedwage compensation.
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ONLINE EXPERIMENT WITH JIGSAW
PUZZLES

Laboratory experiment with a 2×2×2 design
Monetary compensation (fixed-pay, piece-rate)
 Task complexity (simple, complex)
 Task attractiveness (attractive, unattractive)


DV = task performance (puzzles assembled)

And two components of performance
Initial performance
 Learning rate (Improvement)

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EXPERIMENTAL MATERIALS
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13
14
15
16
[Fixed pay treatment.]
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[Incentive (piece rate) pay treatment.]
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19
20
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MANIPULATIONS

Monetary compensation
Fixed-wage participants received $15.00 for
participating in the study (about 1 hour).
 The piece-rates established after pre-testing to be
approximately equal in both piece-rate tasks, roughly
$15 per participant.
 Pay min. $5, max. $30


Task complexity


Simple: shuffled; Complex: shuffled and rotated.
Task attractiveness

Two layers: pre-screening; then giving most/least-liked
pictures first.
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RESULTS
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HYPOTHESIS 1—3-WAY INTERACTION
Our fn. 12: Cohen (1988, 375) recommends setting a higher
alpha level for interaction effects, suggesting 0.10 instead of 0.05.
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HYPOTHESIS-1 INTERACTION
Unattractive
Task
t = 3.85, p < 0.001, one-tailed
Attractive
Task
N.S.
n.s.
Pay Scheme
N.S.
Pay Scheme
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RESULTS: HYPOTHESIS

H2 (paraphrased): Where incentive pay is effective,
it does not affect the rate of learning.

Based on overall performance in the experiment:

No main effect of compensation on learning rate (F = 0.271, p
= 0.604) and no interaction effect.

Power of the test to detect a moderate effect size is 0.60
Same for the simple task (which drove the payeffectiveness result) in isolation.
 Finding is consistent with H2 (null).

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RESULTS: HYPOTHESIS 3

H3 (paraphrased): Where incentive pay is
effective, it does positively affect the initial
performance.

Based on overall performance in the experiment:


Same for the simple task (which drove the payeffectiveness result) in isolation.


Main effect of compensation on initial performance is
significant (F = 5.165, p = 0.026) (Table 4; no interactions.)
Same result, F = 9.713, p = 0.004. (Table 4; no interactions.)
These results support H3.
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CONTRIBUTIONS

Provides further evidence that piece-rate incentive
pay is ineffective for tasks that are attractive or
complex
Extends Fessler’s (2003) finding of degraded
performance of an attractive, complex task
 Employs an assembly task versus his water-jug
puzzles.


Replicates Bailey, Brown & Cocco’s (1998) finding
that incentive pay affects initial performance but not
improvement rate in a repeated task

Employs a different type of assembly task
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THE END
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