The Moderating Effects of Task Complexity and Task Attractiveness on the Impact of

1. 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 JOURNAL OF MANAGEMENT ACCOUNTING RESEARCH 2011

2. Extends our two JMAR studiesconcerning 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.

3. factors that may moderate effects of an incentive contract for a task • 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 taskperformance is mediated by effort (Bonner and Sprinkle 2002). Incentives  Effort  Performance Weaker link for complex tasks.

4. Two factors that may moderate effects of incentive contract for a task • 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).

5. 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.

6. 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.

7. Learning and incentives • This study concerns a repetitive, “skill” task • Learn by doing. • Would not apply to, say academic learning. • P. 192:

8. 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).

9. 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).

10. 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 fixed-wage 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 fixed-wage compensation.

11. 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)

12. experimental materials

17. [Fixed pay treatment.]

18. [Incentive (piece rate) pay treatment.]

24. 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.

25. Results

26. 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.

27. 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

28. 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 pay-effectiveness result) in isolation. • Finding is consistent with H2 (null).

29. Results: Hypothesis 3 • H3(paraphrased): Where incentive pay is effective, it does positively affect the initial performance. • Based on overall performance in the experiment: • Main effect of compensation on initial performance is significant (F = 5.165, p = 0.026) (Table 4; no interactions.) • Same for the simple task (which drove the pay-effectiveness result) in isolation. • Same result, F = 9.713, p = 0.004. (Table 4; no interactions.) • These results support H3.

30. 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

31. The end