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Ability, Team Composition, and Moral Hazard: Evidence from the Laboratory

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Schmalenbach Business Review Aims and scope

Abstract

An important question when assigning individuals to groups concerns the benefits and drawbacks of homogeneity and heterogeneity with respect to the group members’ ability levels. We design a laboratory experiment, in which we assume that the output is just the sum of the group members’ performances. This allows us to isolate the impact of ability-based matching principles on the degree of moral hazard. In line with theories on team cohesion, we find that the degree of moral hazard is larger in heterogeneous groups. As the incentive structure is the same, this can exclusively be attributed to motivational effects. We consider two settings, one where the roles to high- and low-productivity levels are randomly assigned, and one where those roles are earned. Results are robust with respect to these two role assignments.

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Notes

  1. The belief was incentivized with the following formula: payoff = 20 Taler * (1 − |R − r|), where R represents the subject’s belief about the average participant behavior (percental change of effort reduction in teams compared to individual effort decision and r represents the actual participant behavior (see Appendix C for descriptive statistics)).

  2. We fully acknowledge that our group setting deviates from Moral hazard in team (based on Alchian and Demsetz 1972; Newhouse 1973; Holmström 1982). Of course, as our production function is additively-separable, one could easily implement separate piece rates, thereby eliminating the free-rider problem. However, we preferred not to use a production function with positive cross partial derivates as the decision that maximize individual payments are then interdependent, which makes identifiably a far more difficult issue.

  3. Correlations between APM-test scores and optimal optima are positive by 0.102 (p-value 0.16) and 0.081 (p-value 0.26) for high- and low-types, respectively. However, as both correlations are not significant, the claim that this experimental setup allows for a clear-cut distinction of ability (or productivity) and effort cannot be rejected.

  4. The full sample of elicited variables can be extracted from the instructions.

  5. P-values of the Wilcoxon rank-sum test for relative (to the benchmark of individual effort decision) effort reduction are 0.014 and 0.017 for high- and low-types, respectively.

  6. We are grateful to an anonymous referee for pointing to this explanation.

  7. P-values of the Wilcoxon rank-sum test for relative (to the benchmark of individual effort decision) effort reduction are 0.069 and 0.105 for high- and low-types, respectively.

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Author information

Authors and Affiliations

  1. TUM School of Management, Chair of Corporate Management, Technische Universität München, Arcisstr. 21, 80333, Munich, Germany

    Dominik Doll & Alwine Mohnen

  2. Frankfurt School of Finance and Management, Sonnemannstraße 9–11, 60314, Frankfurt/Main, Germany

    Eberhard Feess

Authors
  1. Dominik Doll
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  2. Eberhard Feess
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  3. Alwine Mohnen
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Corresponding author

Correspondence to Dominik Doll.

Additional information

We are grateful to two anonymous referees for very valuable comments. We also wish to thank participants at the CedEX Brown Bag series at the School of Economics of the University of Nottingham, especially Simon Gächter and Daniele Nosenzo, participants at the GEABA conference 2015, especially Jan Wilhelm and Florian Englmaier for helpful comments. The funding for the experiments was granted by the TUM School of Management.

Appendices

Appendix A

1.1 Control Questions for Individual Effort Decision

Example of windfall treatment and translated from German (original questions can be retrieved from the authors upon request).

For answering the control questions, you do not receive any payoff.

In the following you find seven comprehension questions. Please answer them and click on the button “Send entries”. In case you do not answer all question correctly, you have to answer the questions again. In case you need assistance to answer the questions, please rise your hand and wait for the instructor. For answering the comprehension questions, the following table is provided:

Effort decision

1

2

3

4

5

6

7

8

9

10

Output

3.5

6.8

9.9

12.8

15.5

18.0

20.3

22.4

24.3

26.0

Effort decision

11

12

13

14

15

16

17

18

19

20

Output

27.5

28.8

29.9

30.8

31.5

32.0

32.3

32.4

32.3

32.0

Question 1.

Assume that your effort decision is 5. What is the resulting cost of your decision?

Question 2.

Assume that your effort decision in 5. What is your payoff you receive after deducting your related costs?

Question 3.

Assume that your effort decision is 6. What is your payoff you receive after deducting your related costs?

Question 4.

Assume that you change your effort decision from 5 to 6. How many Taler do you receive more as payoff by such a change in the decision?

Question 5.

Assume that your effort decision is 10. What is your payoff you receive after deducting your related costs?

Question 6.

Assume that your effort decision is 19. What is your payoff you receive after deducting your related costs?

Question 7.

Assume that you change your effort decision from 10 to 19. How many Taler do you receive less as payoff by such a change in the decision?

Appendix B

2.1 Control Questions for Effort Decision in Groups

Example of windfall treatment (homogeneous matching and high-type) and translated from German (original questions can be retrieved from the authors upon request).

For answering the control questions, you do not receive any payoff.

In the following you find four comprehension questions. Please answer them and click on the button “Send entries”. In case you do not answer all question correctly, you have to answer the questions again. In case you need assistance to answer the questions, please rise your hand and wait for the instructor. As a recap the calculation formula:

Taler for subject X = 1/2 of the resulting payoff based on effort decision subject X + 1/2 of the resulting payoff based on effort decision subject Y − cost of effort decision of subject X.

For answering the comprehension questions, the following table is provided both to you and the your group member:

Effort decision

1

2

3

4

5

6

7

8

9

10

Output

3.9

7.6

11.1

14.4

17.5

20.4

23.1

25.6

27.9

30

Effort decision

11

12

13

14

15

16

17

18

19

20

Output

31.9

33.6

35.1

36.4

37.5

38.4

39.1

39.6

39.9

40

Question 1.

Assume that your effort decision is 5 and your group member’s is 6. What are your cost you have to bear of these decisions (you only bear your own cost)?

Question 2.

Assume that your effort decision is 5 and your group member’s is 6. What is your payoff after deducting your related costs?

Question 3.

Assume that your effort decision is 5 and your group member’s is 7. What is your payoff after deducting your related costs?

Question 4.

Assume that your effort decision is 6 and your group member’s is 6. What is your payoff after deducting your related costs?

Appendix C

3.1 Descriptive Statistic for Belief Elicitation

Relative frequency in percent and mean belief about participants’ relative effort (in percent compared to individual decision) in brackets, respectively.

 

Belief decrease

Belief same

Belief increase

N

Random assignment

HighHom

45.8

(72.3)

33.3

(100.0)

20.8

(134.3)

48

HighHet

53.3

(73.2)

24.4

(100.0)

22.2

(124.5)

45

LowHom

62.5

(75.7)

16.7

(100.0)

20.8

(116.3)

48

LowHet

48.9

(75.6)

22.2

(100.0)

28.9

(120.7)

45

Earned-roles

HighHom

71.7

(76.8)

23.9

(100.0)

4.3

(119.0)

46

HighHet

81.3

(75.6)

12.5

(100.0)

6.3

(113.3)

48

LowHom

34.8

(77.7)

28.3

(100.0)

37.0

(132.6)

46

LowHet

45.8

(75.0)

18.8

(100.0)

35.4

(117.8)

48

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Doll, D., Feess, E. & Mohnen, A. Ability, Team Composition, and Moral Hazard: Evidence from the Laboratory. Schmalenbach Bus Rev 18, 49–70 (2017). https://doi.org/10.1007/s41464-016-0025-4

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