Summary by Mohamed Gomaa
Ph.D. Program in Accounting
University of South Florida, Spring 2002
The main purpose of this article is to examine the effects of common incentive schemes versus fixed-pay on the components of performance during the learning phase of a production run. The authors selected two typical incentive schemes:
1. A pure piece-rate of payment per item completed, and
2. A goal-congruent structure that consists of a fixed amount plus a bonus for reaching a performance standard.
Previous empirical studies that have examined the effects of monetary incentives on task learning fall into the following two categories:
1. Studies that introduced the incentive after work was underway and rewarded improved performance directly, and
2. Studies that introduced the financial incentive before work began, allowing the incentive to potentially influence both initial performance and learning.
In the first category, evidence suggests that incentives increase improvement rates. However, in the second category, the effects on improvement are unclear. One of the difficulties mentioned is that previous researchers have not explicitly employed a learning-curve model. This study devises hypotheses that may help reconcile the mixed results of previous studies and tests these hypotheses in a laboratory setting.
H1: The rate of learning in the piece-rate and goal-congruent plans is not greater than the fixed-pay plan.
H2: Initial performance with the piece-rate and goal-congruent methods is greater than with the fixed-pay method.
The authors offer two rationales for the first hypothesis. First, improvement of the rate of learning of a routine task would require a lot of effort relative to enhancing initial performance. Second, as improved performance is rewarded indirectly by incentive plans, improvement of the rate of learning is a less salient objective and the relative improvement rate through the fixed-pay plan is less likely to occur than with plans that do reward improvement directly. The second hypothesis follows directly from the first.
The authors conducted a laboratory experiment to test their hypotheses. The subjects used in the experiment were 72 university students divided into three treatment groups consisting of 24 students each. The task assigned to the subjects was an Erector Set® assembly that is similar to ones used by previous studies. The object of the task was to assemble the "crane of a wrecker" using the parts provided. The subjects received detailed instructional diagrams as well as verbal help. The subjects were oriented to the task by the researcher and were told what the expected standard of performance was and the exact method of payment. The compensation methods were as follows:
Fixed paymens: A flat fee of $20.00 for four hours of work.
Piece-rate: Payment of $1.80 for each unit completed.
Goal-contingent: A flat base amount of $17.50, plus a bonus of either $3.00 or $6.00 for achieving the standard.
Results and Conclusions
The authors found that subjects working under incentive-pay (i.e., piece-rate or goal contingent) plans outperformed those paid a fixed dollar amount per unit of time. They observed learning in all subjects in both fixed-pay and incentive-pay schemes. However, they did not observe differential learning between fixed-pay and either incentive plan. Their finding is consistent with their expectation that subjects who are not rewarded directly for learning allocate their limited resources toward improved initial performance rather than subsequent improvement. Their results also indicate that initial performance was faster for the incentive-pay than for the fixed-pay plan. Their findings are consistent with the notion in the industrial learning-curve literature that a fast learning rate might be because poor planning led to a bad start.
The results obtained in this study suggest that monetary incentives can influence “capable operator performance” by increasing concentration at the start which results in better initial performance. Although the researchers believe there was a lot of opportunity for further improvement, the incentives failed to affect the rate of improvement. They believe this can be attributed to two factors:
“The subject’s allocation of effort to improving initial performance, which may be easier than improving subsequent performance, and the nature of the incentive pay-plans, which do not reward improvement directly.” (p. 128)
Two control functions were noted by Kren and Liao (1988, 302) for economic incentives:
“To attract employees with differential skill levels, and
Determine the effort that the employee will exert.”
This study addresses only the second function and attempts to control for the first function through the skills questionnaire and by concealing the contractual details until subjects arrived for work. This study focuses on an assembly task while eliminating the time related to other activities such as disassembly, waiting and rest breaks. The authors did this to control for extraneous factors and to isolate the effects of incentives on the performance of the productive task.
Some questions remain unanswered about the timing of the introduction of the incentives. For example, would offering an additional incentive after production was underway improve performance? And how would they persist over time? A review of empirical literature by Kohn (1993) indicates that extrinsic rewards are ineffective in the long run. However, the authors believe they have a favorable short run impact. Future studies should examine the complex relationship between monetary incentives and the components of performance.
Kohn, A. 1993. Punished by Rewards: The Trouble with Gold Stars, Incentive Plans, A's, Praise, and Other Bribes. Boston: Houghton Mifflin.
Kohn, A. 1993. Why incentive plans cannot work. Harvard Business Review (September-October): 54-63. (Summary).
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