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arxiv: 2508.06162 · v2 · submitted 2025-08-08 · 💰 econ.GN · q-fin.EC

To Each Their Own: Heterogeneity in Worker Preferences for and Responses to Peer Information

Zhi Hao Lim This is my paper

Pith reviewed 2026-05-19 01:02 UTC · model grok-4.3

classification 💰 econ.GN q-fin.EC
keywords heterogeneous preferencespeer informationworkplace feedbackreal-effort experimentwillingness to payproductivity responseswelfare analysisinformation timing
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The pith

Workers show large differences in wanting peer performance information, which predict their effort responses.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper shows that workers differ in their demand for information about how peers performed on a task. In an experiment, willingness-to-pay for this information before or after the work reveals that some avoid it early because it causes stress, while others seek it when they are ahead. These preferences strongly predict whether receiving the information raises or leaves unchanged their productivity. Because of this, giving the same feedback to everyone can lower welfare for the stressed group, but choosing the right timing for each worker can raise total welfare by up to 48 percent. Readers should care since many jobs use peer comparisons and uniform rules may waste effort or harm motivation.

Core claim

In a real-effort experiment with 793 workers, we document substantial heterogeneity in demand for peer information: some workers are indifferent, some prefer to avoid it before the task, and others value it more as their relative performance increases. These differences strongly predict effort responses to peer information. Notably, 15% of workers would pay to avoid information ex ante due to stress and exhibit no productivity gains from it. Uniform feedback policies can impose welfare losses on such workers, while tailoring the timing of peer information increases welfare by up to 48%.

What carries the argument

Elicited willingness-to-pay for receiving peer performance information either before or after completing the task, used to classify workers and predict their subsequent effort provision.

If this is right

  • Uniform policies that deliver peer information to all workers reduce welfare for those who prefer to avoid it.
  • Allowing workers to choose the timing of peer information can raise aggregate welfare by up to 48%.
  • Preferences for peer information correlate with actual changes in productivity when the information is provided.
  • About 15% of the workforce may experience stress from early peer information without any offsetting productivity benefit.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Workplace managers might improve outcomes by letting employees opt into or out of certain feedback timings based on their stated preferences.
  • Similar heterogeneity could appear in other performance metrics, such as individual sales targets or team goals, suggesting broader use of personalized information delivery.
  • Testing these patterns in field settings with real compensation tied to output would strengthen the case for policy changes.

Load-bearing premise

That the amount workers are willing to pay to receive or avoid peer information before the task truly captures the stress or disutility they feel when they later receive that information.

What would settle it

Finding that the workers who stated they would pay to avoid early peer information still increase their effort when they receive it anyway, or that the link between pre-task willingness-to-pay and post-task effort disappears under different task conditions.

Figures

Figures reproduced from arXiv: 2508.06162 by Zhi Hao Lim.

Figure 1
Figure 1. Figure 1: Average Preferences for Peer Information [PITH_FULL_IMAGE:figures/full_fig_p024_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Average Effect of Peer Information on Worker Effort [PITH_FULL_IMAGE:figures/full_fig_p025_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: WTP for Peer Information by Preference Type [PITH_FULL_IMAGE:figures/full_fig_p029_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Distribution of Worker Motivations for Choosing Information [PITH_FULL_IMAGE:figures/full_fig_p033_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: WTP for Peer Information by BERT-based Cluster [PITH_FULL_IMAGE:figures/full_fig_p036_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Realized Payoffs Induced by Peer Information [PITH_FULL_IMAGE:figures/full_fig_p039_6.png] view at source ↗
read the original abstract

Information about peers' performance is pervasive in workplaces, yet its effects on worker behavior are mixed. We show that a key reason is that workers differ in how they value such information. In a real-effort experiment with 793 workers, we elicit willingness-to-pay for peer information delivered either before or after the task. We document substantial heterogeneity in demand for peer information: some workers are indifferent, some prefer to avoid it before the task, and others value it more as their relative performance increases. These differences strongly predict effort responses to peer information. Notably, 15% of workers would pay to avoid information ex ante due to stress and exhibit no productivity gains from it. We further show that uniform feedback policies can impose welfare losses on such workers, while tailoring the timing of peer information increases welfare by up to 48%. Our results highlight the importance of accounting for heterogeneous information preferences when designing workplace feedback policies.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper reports results from a real-effort experiment with 793 workers. It elicits willingness-to-pay (WTP) for peer performance information delivered either before or after the task, documents substantial heterogeneity in demand for this information, and shows that these differences predict effort responses. Notably, 15% of workers would pay to avoid pre-task information due to stress and exhibit no productivity gains; uniform feedback policies impose welfare losses on such workers while tailoring the timing of information can increase welfare by up to 48%.

Significance. If the central empirical links hold, the results highlight the importance of accounting for heterogeneous preferences when designing workplace feedback policies. The sizable sample and experimental design provide credible evidence on how individual differences in information valuation shape behavioral responses and welfare outcomes. The policy implication that tailoring can yield substantial welfare gains is relevant for organizational practice.

major comments (2)
  1. [Experimental Design and Results sections] The headline claim that 15% of workers pay to avoid information ex ante 'due to stress' and show no productivity gains rests on interpreting the pre-task WTP elicitation as a direct measure of anticipated disutility that subsequently shapes effort. Without within-subject stress proxies or a direct test that high-WTP-to-avoid subjects exhibit effort reductions specifically attributable to information receipt (rather than correlation alone), alternative factors such as curiosity or belief updating cannot be ruled out. This mapping is load-bearing for both the heterogeneity prediction and the welfare calculations.
  2. [Welfare Analysis section] The welfare analysis showing that uniform policies impose losses while tailoring timing increases welfare by up to 48% depends on the WTP-to-stress interpretation. If the elicited WTP captures factors other than the disutility affecting effort, the quantitative welfare estimates may be overstated. A robustness exercise using an alternative welfare metric or subgroup-specific effort regressions that isolate the information effect would strengthen the result.
minor comments (2)
  1. [Methods] Clarify the exact randomization protocol for information provision and any pre-analysis plan or multiple-testing adjustments in the heterogeneity analysis.
  2. [Results] Report effect sizes and confidence intervals alongside the 'strongly predict' statement for the effort-response regressions.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments, which help clarify the interpretation of our results. We address each major comment below and outline revisions to strengthen the manuscript.

read point-by-point responses

  1. Referee: [Experimental Design and Results sections] The headline claim that 15% of workers pay to avoid information ex ante 'due to stress' and show no productivity gains rests on interpreting the pre-task WTP elicitation as a direct measure of anticipated disutility that subsequently shapes effort. Without within-subject stress proxies or a direct test that high-WTP-to-avoid subjects exhibit effort reductions specifically attributable to information receipt (rather than correlation alone), alternative factors such as curiosity or belief updating cannot be ruled out. This mapping is load-bearing for both the heterogeneity prediction and the welfare calculations.

    Authors: We agree that the WTP-to-disutility mapping is interpretive and that direct stress proxies are not available in the design. The pre-task WTP is a revealed-preference measure elicited before information receipt, and the subsequent finding that these workers show zero effort response (while others respond positively) is consistent with avoidance reflecting factors that offset any motivational benefit. We will revise the text to discuss alternative interpretations (curiosity, belief updating) more explicitly, add subgroup effort regressions that control for baseline performance and other observables, and clarify that the 'stress' language is one plausible mechanism rather than a directly measured construct. revision: partial

  2. Referee: [Welfare Analysis section] The welfare analysis showing that uniform policies impose losses while tailoring timing increases welfare by up to 48% depends on the WTP-to-stress interpretation. If the elicited WTP captures factors other than the disutility affecting effort, the quantitative welfare estimates may be overstated. A robustness exercise using an alternative welfare metric or subgroup-specific effort regressions that isolate the information effect would strengthen the result.

    Authors: We concur that the welfare numbers are sensitive to the interpretation of WTP. In the revision we will add (i) an alternative welfare metric that relies only on observed effort differences across information-timing arms without invoking the stress channel, and (ii) subgroup-specific regressions that isolate the information-treatment effect while controlling for potential confounders. These exercises will be reported alongside the original calculations so readers can assess sensitivity. revision: yes

Circularity Check

0 steps flagged

No significant circularity in this empirical experimental study

full rationale

This is a purely empirical real-effort experiment with 793 workers that elicits willingness-to-pay for peer information delivered before or after the task and measures subsequent effort responses. The abstract and design contain no derivations, equations, fitted parameters renamed as predictions, or self-citation chains that reduce any central claim (heterogeneity in demand, 15% avoiding information due to stress, welfare effects of uniform vs. tailored policies) to its own inputs by construction. All reported results follow from direct experimental data and statistical associations rather than self-referential definitions or ansatzes.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claims rest on standard experimental-economics assumptions about truthful preference revelation in incentive-compatible mechanisms and that the real-effort task validly measures productivity responses.

axioms (1)
  • domain assumption Workers reveal their true preferences via the willingness-to-pay elicitation for peer information.
    Invoked implicitly in the abstract when linking WTP heterogeneity to subsequent effort responses.

pith-pipeline@v0.9.0 · 5681 in / 1345 out tokens · 61731 ms · 2026-05-19T01:02:33.035126+00:00 · methodology

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Reference graph

Works this paper leans on

40 extracted references · 40 canonical work pages

  1. [1]

    B., and Raymond, C

    Abeler, J., Huffman, D. B., and Raymond, C. (2023). Incentive complexity, bounded ratio- nality and effort provision. Technical report, IZA Discussion Papers

    work page 2023

  2. [2]

    Allcott, H. (2011). Social norms and energy conservation. Journal of public Economics , 95(9-10):1082–1095

    work page 2011

  3. [3]

    and Kessler, J

    Allcott, H. and Kessler, J. B. (2019). The welfare effects of nudges: A case study of energy use social comparisons. American Economic Journal: Applied Economics , 11(1):236–276

    work page 2019

  4. [4]

    and Rogers, T

    Allcott, H. and Rogers, T. (2014). The short-run and long-run effects of behavioral inter- ventions: Experimental evidence from energy conservation. American Economic Review, 104(10):3003–3037

    work page 2014

  5. [5]

    A., Goette, L., Price, M

    Andor, M. A., Goette, L., Price, M. K., Tilling, A. S., and Tomberg, L. (2023). Differences in how and why social comparison and real-time feedback impact resource use: Evidence from a field experiment. Technical report, National Bureau of Economic Research

    work page 2023

  6. [6]

    and Nielsen, K

    Arrieta, G. and Nielsen, K. (2024). Procedural decision-making in the face of complexity. Technical report, Working Paper

    work page 2024

  7. [7]

    and Iriberri, N

    Azmat, G. and Iriberri, N. (2010). The importance of relative performance feedback infor- mation: Evidence from a natural experiment using high school students. Journal of Public Economics, 94(7-8):435–452

    work page 2010

  8. [8]

    and Iriberri, N

    Azmat, G. and Iriberri, N. (2016). The provision of relative performance feedback: An analysis of performance and satisfaction. Journal of Economics & Management Strategy , 25(1):77–110

    work page 2016

  9. [9]

    Barankay, I. (2011). Rankings and social tournaments: Evidence from a crowd-sourcing experiment. Technical report, Working Paper

    work page 2011

  10. [10]

    Barankay, I. et al. (2012). Rank incentives: Evidence from a randomized workplace experi- ment. Technical report, Working Paper. B´ arcena-Mart´ ın, E., Cort´ es-Aguilar, A., and Moro-Egido, A. I. (2017). Social comparisons on subjective well-being: The role of social and cultural capital. Journal of Happiness Studies, 18:1121–1145

    work page 2012

  11. [11]

    M., DeGroot, M

    Becker, G. M., DeGroot, M. H., and Marschak, J. (1964). Measuring utility by a single- response sequential method. Behavioral science, 9(3):226–232. Blanes i Vidal, J. and Nossol, M. (2011). Tournaments without prizes: Evidence from personnel records. Management science, 57(10):1721–1736

    work page 1964

  12. [12]

    Bolton, G. E. and Ockenfels, A. (2000). Erc: A theory of equity, reciprocity, and competition. American economic review, 91(1):166–193. 40

    work page 2000

  13. [13]

    J., Gennaioli, N., Kwon, S

    Bordalo, P., Conlon, J. J., Gennaioli, N., Kwon, S. Y., and Shleifer, A. (2023). How people use statistics. Technical report, National Bureau of Economic Research

    work page 2023

  14. [14]

    Breza, E., Kaur, S., and Shamdasani, Y. (2018). The morale effects of pay inequality. The Quarterly Journal of Economics , 133(2):611–663

    work page 2018

  15. [15]

    R., Jimenez, R., and Roth, C

    Bursztyn, L., Handel, B. R., Jimenez, R., and Roth, C. (2023). When product markets become collective traps: The case of social media. Technical report, National Bureau of Economic Research

    work page 2023

  16. [16]

    Butera, L., Metcalfe, R., Morrison, W., and Taubinsky, D. (2022). Measuring the welfare effects of shame and pride. American Economic Review, 112(1):122–168

    work page 2022

  17. [17]

    Buunk, A. P. and Dijkstra, P. (2017). Social comparisons and well-being. The happy mind: Cognitive contributions to well-being , pages 311–330

    work page 2017

  18. [18]

    Charness, G., Masclet, D., and Villeval, M. C. (2010). Competitive preferences and status as an incentive: Experimental evidence. Groupe d’Analyse et de Th´ eorie Economique working paper

    work page 2010

  19. [19]

    L., Schonger, M., and Wickens, C

    Chen, D. L., Schonger, M., and Wickens, C. (2016). otree—an open-source platform for laboratory, online, and field experiments.Journal of Behavioral and Experimental Finance, 9:88–97

    work page 2016

  20. [20]

    C., Featherstone, C

    Coffman, L. C., Featherstone, C. R., and Kessler, J. B. (2017). Can social information affect what job you choose and keep? American Economic Journal: Applied Economics , 9(1):96–117

    work page 2017

  21. [21]

    and Perez-Truglia, R

    Cullen, Z. and Perez-Truglia, R. (2022). How much does your boss make? the effects of salary comparisons. Journal of Political Economy , 130(3):766–822

    work page 2022

  22. [22]

    A., Malmendier, U., and Rao, G

    DellaVigna, S., List, J. A., Malmendier, U., and Rao, G. (2022). Estimating social preferences and gift exchange at work. American Economic Review, 112(3):1038–1074

    work page 2022

  23. [23]

    and Pope, D

    DellaVigna, S. and Pope, D. (2018). What motivates effort? evidence and expert forecasts. The Review of Economic Studies , 85(2):1029–1069

    work page 2018

  24. [24]

    Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K. (2019). Bert: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 con- ference of the North American chapter of the association for computational linguistics: human language technologies, volume 1 (long and short papers) , pages 4171–4186

    work page 2019

  25. [25]

    Eriksson, T., Poulsen, A., and Villeval, M. C. (2009). Feedback and incentives: Experimental evidence. Labour Economics, 16(6):679–688

    work page 2009

  26. [26]

    and Schmidt, K

    Fehr, E. and Schmidt, K. M. (1999). A theory of fairness, competition, and cooperation. The quarterly journal of economics , 114(3):817–868

    work page 1999

  27. [27]

    con- ditional cooperation

    Frey, B. S. and Meier, S. (2004). Social comparisons and pro-social behavior: Testing “con- ditional cooperation” in a field experiment. American economic review, 94(5):1717–1722. 41

    work page 2004

  28. [28]

    Gill, D., Kissov´ a, Z., Lee, J., and Prowse, V. (2019). First-place loving and last-place loathing: How rank in the distribution of performance affects effort provision.Management Science, 65(2):494–507

    work page 2019

  29. [29]

    Gjedrem, W. G. (2018). Relative performance feedback: Effective or dismaying? Journal of Behavioral and Experimental Economics , 74:1–16

    work page 2018

  30. [30]

    Haaland, I., Roth, C., Stantcheva, S., and Wohlfart, J. (2025). Understanding economic behavior using open-ended survey data. Technical report, ECONtribute Discussion Paper

    work page 2025

  31. [31]

    Haaland, I., Roth, C., and Wohlfart, J. (2023). Designing information provision experiments. Journal of economic literature, 61(1):3–40

    work page 2023

  32. [32]

    L., Krishnan, R., and Newman, A

    Hannan, R. L., Krishnan, R., and Newman, A. H. (2008). The effects of disseminating relative performance feedback in tournament and individual performance compensation plans. The Accounting Review, 83(4):893–913

    work page 2008

  33. [33]

    Huet-Vaughn, E. (2015). Do social comparisons motivate workers? a field experiment on relative earnings, labor supply and the inhibitory effect of pay inequality. Technical report, Working Paper

    work page 2015

  34. [34]

    Jain, A. K. and Dubes, R. C. (1988). Algorithms for clustering data . Prentice-Hall, Inc

    work page 1988

  35. [35]

    Kaur, S., Mullainathan, S., Oh, S., and Schilbach, F. (2025). Do financial concerns make workers less productive? The Quarterly Journal of Economics , 140(1):635–689

    work page 2025

  36. [36]

    Kuhnen, C. M. and Tymula, A. (2012). Feedback, self-esteem, and performance in organi- zations. Management Science, 58(1):94–113

    work page 2012

  37. [37]

    Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics , 20:53–65

    work page 1987

  38. [38]

    Senn, J., Schmitz, J., and Zehnder, C. (2023). Leveraging social comparisons: the role of peer assignment policies. Technical report, Working Paper

    work page 2023

  39. [39]

    Subakti, A., Murfi, H., and Hariadi, N. (2022). The performance of bert as data representa- tion of text clustering. Journal of big Data , 9(1):15

    work page 2022

  40. [40]

    Do Not Care

    Villeval, M. C. (2020). Performance feedback and peer effects. Springer. 42 Online Appendix A. Supplementary Figures and Tables Figure A1: WTP for Peer Information by Hand-coded Categories (a) “Do Not Care” (b) “Stress or Distraction” (c) “Social Comparison” (d) “Goal or Motivation” Notes. This figure plots the average WTP for peer information that is pro...

    work page 2020