Deterring Unethical Behavior in Online Labor Markets

被引:0
|
作者
William D. Brink
Tim V. Eaton
Jonathan H. Grenier
Andrew Reffett
机构
[1] Miami University,
来源
Journal of Business Ethics | 2019年 / 156卷
关键词
Corporate ethics; Social norm theory; Online labor markets; Honesty; Mechanical Turk;
D O I
暂无
中图分类号
学科分类号
摘要
This study examines how codes of conduct, monitoring, and penalties for dishonest reporting affect reporting honesty in an online labor market setting. Prior research supports the efficacy of codes of conduct in promoting ethical behavior in a variety of contexts. However, the effects of such codes and other methods have not been examined in online labor markets, an increasingly utilized resource that differs from previously examined settings in several key regards (e.g., transient workforce, lack of an established culture). Leveraging social norm activation theory, we predict and find experimental evidence that while codes of conduct and monitoring without economic penalties are ineffective in online settings, monitoring with economic penalties activates social norms for honesty and promotes honest reporting in an online setting. Further, we find that imposing penalties most effectively promotes honest reporting in workers who rate high in Machiavellianism, a trait that is highly correlated with dishonest reporting. In fact, while in the absence of penalties we observe significantly more dishonest reporting from workers who rate high versus low in Machiavellianism, this difference is eliminated in the presence of penalties. Implications of these findings for companies, researchers, online labor market administrators, and educators are discussed.
引用
收藏
页码:71 / 88
页数:17
相关论文
共 50 条
  • [11] Accounting for Market Frictions and Power Asymmetries in Online Labor Markets
    Kingsley, Sara Constance
    Gray, Mary L.
    Suri, Siddharth
    POLICY AND INTERNET, 2015, 7 (04): : 383 - 400
  • [12] More for less: adaptive labeling payments in online labor markets
    Geva, Tomer
    Saar-Tsechansky, Maytal
    Lustiger, Harel
    DATA MINING AND KNOWLEDGE DISCOVERY, 2019, 33 (06) : 1625 - 1673
  • [13] More for less: adaptive labeling payments in online labor markets
    Tomer Geva
    Maytal Saar-Tsechansky
    Harel Lustiger
    Data Mining and Knowledge Discovery, 2019, 33 : 1625 - 1673
  • [14] Dynamic Recommendations for Sequential Hiring Decisions in Online Labor Markets
    Kokkodis, Marios
    KDD'18: PROCEEDINGS OF THE 24TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING, 2018, : 453 - 461
  • [15] With a Little Help from the Crowd: Receiving Unauthorized Academic Assistance through Online Labor Markets
    Harris, Christopher G.
    Srinivasan, Padmini
    Proceedings of 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing (SocialCom/PASSAT 2012), 2012, : 904 - 909
  • [16] A Deep Choice Model for Hiring Outcome Prediction in Online Labor Markets
    Ma, Y.
    Zhang, Z.
    Ihler, A.
    INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 2020, 15 (02)
  • [17] Hiring Preferences in Online Labor Markets: Evidence of a Female Hiring Bias
    Chan, Jason
    Wang, Jing
    MANAGEMENT SCIENCE, 2018, 64 (07) : 2973 - 2994
  • [18] Productivity and Task Heterogeneity in Online Labor Markets: A Bonus Payment Experiment
    Mourelatos, Evaggelos
    Giannakopoulos, Nicholas
    Tzagarakis, Manolis
    BULLETIN OF ECONOMIC RESEARCH, 2025, 77 (02) : 198 - 218
  • [19] Adjusting Skillset Cohesion in Online Labor Markets: Reputation Gains and Opportunity Losses
    Kokkodis, Marios
    INFORMATION SYSTEMS RESEARCH, 2023, 34 (03) : 1245 - 1258
  • [20] A Project Recommender Based on Customized Graph Neural Networks in Online Labor Markets
    Ma, Yixuan
    Ma, Zeyao
    Li, Yankai
    Gao, Haoyu
    Xue, Yukai
    INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 2023, 18 (04)