IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v35y2024i2p783-806.html
   My bibliography  Save this article

Seek and Ye Shall Find: An Empirical Examination of the Effects of Seeking Real-Time Feedback on Employee Performance Evaluations

Author

Listed:
  • Michael Rivera

    (Fox School of Business, Temple University, Philadelphia, Pennsylvania 19122)

  • Cheng Jiang

    (Carroll School of Management, Boston College, Chestnut Hill, Massachusetts 02467)

  • Subodha Kumar

    (Fox School of Business, Temple University, Philadelphia, Pennsylvania 19122)

Abstract

Many companies use real-time feedback applications to increase employee engagement with their performance evaluation programs and disseminate the results. Yet beyond giving and receiving employee feedback, important dynamics such as feedback-seeking behavior and feedback rating are not well addressed in the literature. To fill this gap, we examine employee behavior related to two dimensions of real-time feedback: (i) seeking performance feedback from supervisors, peers, and direct reports and (ii) evaluating the helpfulness of received performance feedback. Specifically, we examine the effects of feedback-seeking and rate-the-feedback behaviors on in-kind evaluations. After analyzing nearly 11,000 feedback instances from employees at four major organizations that use real-time performance feedback applications, we find that seeking feedback enhances constructive communication among colleagues. We show that feedback receivers who sought feedback receive lower feedback scores, have a higher likelihood of receiving comments, and receive longer, more positive, and more subjective comments. Feedback givers who opt not to provide comments or opt to provide shorter comments to feedback seekers choose to provide feedback anonymously. We document that feedback seekers care less about the high feedback scores and prefer longer comments when they rate received feedback. Low feedback scores received motivate feedback seekers to continue to seek feedback in the future. To address the endogeneity issues, we use identification approaches such as instrumental variable, matching, and Heckman-type analysis. Sought feedback may be more useable than unsolicited feedback because text-based feedback responses may provide sufficient insight for the recipient to act on. Hence, managers and organizations should promote a culture of constructive feedback through this feedback-seeking dynamic and orientation. When implementing feedback applications that allow for seeking and rating feedback, managers should be aware that feedback ratings can be informative, but feedback results might be notably lower when feedback is sought. Thus, based on our results, we identify several managerial insights that firms could use to manage feedback mechanisms.

Suggested Citation

  • Michael Rivera & Cheng Jiang & Subodha Kumar, 2024. "Seek and Ye Shall Find: An Empirical Examination of the Effects of Seeking Real-Time Feedback on Employee Performance Evaluations," Information Systems Research, INFORMS, vol. 35(2), pages 783-806, June.
    • Handle: RePEc:inm:orisre:v:35:y:2024:i:2:p:783-806
    DOI: 10.1287/isre.2021.0130
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.2021.0130
    Download Restriction: no
    File URL: https://libkey.io/10.1287/isre.2021.0130?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Matthew Blackwell & Stefano Iacus & Gary King & Giuseppe Porro, 2009. "cem: Coarsened exact matching in Stata," Stata Journal, StataCorp LP, vol. 9(4), pages 524-546, December.
    2. Arabmazar, Abbas & Schmidt, Peter, 1981. "Further evidence on the robustness of the Tobit estimator to heteroskedasticity," Journal of Econometrics, Elsevier, vol. 17(2), pages 253-258, November.
    3. Hoffmann, Christin & Thommes, Kirsten, 2020. "Can digital feedback increase employee performance and energy efficiency in firms? Evidence from a field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 49-65.
    4. Fedor, Donald B. & Eder, Robert W. & Buckley, M. Ronald, 1989. "The contributory effects of supervisor intentions on subordinate feedback responses," Organizational Behavior and Human Decision Processes, Elsevier, vol. 44(3), pages 396-414, December.
    5. J. H. Jung & Christoph Schneider & Joseph Valacich, 2010. "Enhancing the Motivational Affordance of Information Systems: The Effects of Real-Time Performance Feedback and Goal Setting in Group Collaboration Environments," Management Science, INFORMS, vol. 56(4), pages 724-742, April.
    6. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2014. "Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue," Management Science, INFORMS, vol. 60(7), pages 1632-1654, July.
    7. Mariia Petryk & Michael Rivera & Siddharth Bhattacharya & Liangfei Qiu & Subodha Kumar, 2022. "How Network Embeddedness Affects Real-Time Performance Feedback: An Empirical Investigation," Information Systems Research, INFORMS, vol. 33(4), pages 1467-1489, December.
    8. Podsakoff, Philip M. & Farh, Jiing-Lih, 1989. "Effects of feedback sign and credibility on goal setting and task performance," Organizational Behavior and Human Decision Processes, Elsevier, vol. 44(1), pages 45-67, August.
    9. Patrick Puhani, 2000. "The Heckman Correction for Sample Selection and Its Critique," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 53-68, February.
    10. F. Javier Lerch & Donald E. Harter, 2001. "Cognitive Support for Real-Time Dynamic Decision Making," Information Systems Research, INFORMS, vol. 12(1), pages 63-82, March.
    11. Robert G. Eccles & Ioannis Ioannou & George Serafeim, 2014. "The Impact of Corporate Sustainability on Organizational Processes and Performance," Management Science, INFORMS, vol. 60(11), pages 2835-2857, November.
    12. Kimmy Wa Chan & Stella Yiyan Li & Jian Ni & John JianJun Zhu, 2021. "What Feedback Matters? The Role of Experience in Motivating Crowdsourcing Innovation," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 103-126, January.
    13. Krishnamurthy, Sandeep & Ou, Shaosong & Tripathi, Arvind K., 2014. "Acceptance of monetary rewards in open source software development," Research Policy, Elsevier, vol. 43(4), pages 632-644.
    14. Jennifer R. Burnett & Timothy C. Lisk, 2019. "The Future of Employee Engagement: Real-Time Monitoring and Digital Tools for Engaging a Workforce," International Studies of Management & Organization, Taylor & Francis Journals, vol. 49(1), pages 108-119, January.
    15. Anastasia A. Katou, 2012. "Investigating reverse causality between human resource management policies and organizational performance in small firms," Management Research Review, Emerald Group Publishing Limited, vol. 35(2), pages 134-156, January.
    16. John W. Gardner*, 2020. "Managing Production Yields and Rework through Feedback on Speed, Quality, and Quantity," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2182-2209, September.
    17. Hewawasam Puwakpitiyage Rasika Priyankara & Fan Luo & Amer Saeed & Saviour Ayertey Nubuor & Mahabaduge Prasad Fernando Jayasuriya, 2018. "How Does Leader’s Support for Environment Promote Organizational Citizenship Behaviour for Environment? A Multi-Theory Perspective," Sustainability, MDPI, vol. 10(1), pages 1-20, January.
    18. Richard T. Carson & Yixiao Sun, 2007. "The Tobit model with a non-zero threshold," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 488-502, November.
    19. I.M. Jawahar, 2006. "Correlates of Satisfaction with Performance Appraisal Feedback," Journal of Labor Research, Transaction Publishers, vol. 27(2), pages 213-236, April.
    20. Verena Tiefenbeck & Lorenz Goette & Kathrin Degen & Vojkan Tasic & Elgar Fleisch & Rafael Lalive & Thorsten Staake, 2018. "Overcoming Salience Bias: How Real-Time Feedback Fosters Resource Conservation," Management Science, INFORMS, vol. 64(3), pages 1458-1476, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Michael Rivera & Liangfei Qiu & Subodha Kumar & Tony Petrucci, 2021. "Are Traditional Performance Reviews Outdated? An Empirical Analysis on Continuous, Real-Time Feedback in the Workplace," Information Systems Research, INFORMS, vol. 32(2), pages 517-540, June.
    2. Eric J. Tchetgen Tchetgen & Kathleen E. Wirth, 2017. "A general instrumental variable framework for regression analysis with outcome missing not at random," Biometrics, The International Biometric Society, vol. 73(4), pages 1123-1131, December.
    3. Martin, Will, 2020. "Making Gravity Great Again," 2020: Economic Implications of COVID-19, December 14-15, Virtual Platform 339376, International Agricultural Trade Research Consortium.
    4. Cory Koedel & Julian Betts, 2010. "Value Added to What? How a Ceiling in the Testing Instrument Influences Value-Added Estimation," Education Finance and Policy, MIT Press, vol. 5(1), pages 54-81, January.
    5. Zhao, Shangwei & Xie, Tian & Ai, Xin & Yang, Guangren & Zhang, Xinyu, 2023. "Correcting sample selection bias with model averaging for consumer demand forecasting," Economic Modelling, Elsevier, vol. 123(C).
    6. Jan Diebecker & Friedrich Sommer, 2017. "The impact of corporate sustainability performance on information asymmetry: the role of institutional differences," Review of Managerial Science, Springer, vol. 11(2), pages 471-517, March.
    7. Fatemi, Ali & Fooladi, Iraj & Sy, Oumar & Zaman, Ashraf, 2024. "Corporate headquarters relocation and CSR performance," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 622-637.
    8. Steve J. Bickley & Alison Macintyre & Benno Torgler, 2021. "Artificial Intelligence and Big Data in Sustainable Entrepreneurship," CREMA Working Paper Series 2021-11, Center for Research in Economics, Management and the Arts (CREMA).
    9. Hoffmann, Christin & Thommes, Kirsten, 2020. "Can digital feedback increase employee performance and energy efficiency in firms? Evidence from a field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 49-65.
    10. Gorton, Matthew & Sauer, Johannes & Peshevski, Mile & Bosev, Dane & Shekerinov, Darko & Quarrie, Steve, 2009. "Water Communities in the Republic of Macedonia: An Empirical Analysis of Membership Satisfaction and Payment Behavior," World Development, Elsevier, vol. 37(12), pages 1951-1963, December.
    11. Andiola, Lindsay M., 2014. "Performance feedback in the audit environment: A review and synthesis of research on the behavioral effects," Journal of Accounting Literature, Elsevier, vol. 33(1), pages 1-36.
    12. Leandro S. Pongeluppe, 2022. "The favela effect: Spatial inequalities and firm strategies in disadvantaged urban communities," Strategic Management Journal, Wiley Blackwell, vol. 43(13), pages 2777-2808, December.
    13. Mariia Petryk & Michael Rivera & Siddharth Bhattacharya & Liangfei Qiu & Subodha Kumar, 2022. "How Network Embeddedness Affects Real-Time Performance Feedback: An Empirical Investigation," Information Systems Research, INFORMS, vol. 33(4), pages 1467-1489, December.
    14. Miyeon Jung & Daegon Cho & Euncheol Shin, 2021. "Repairing a Cracked Mirror: The Heterogeneous Effect of Personalized Digital Nudges Driven by Misperception," Production and Operations Management, Production and Operations Management Society, vol. 30(8), pages 2586-2607, August.
    15. Lu, Hui & Hess, Stephane & Daly, Andrew & Rohr, Charlene, 2017. "Measuring the impact of alcohol multi-buy promotions on consumers' purchase behaviour," Journal of choice modelling, Elsevier, vol. 24(C), pages 75-95.
    16. Mnasri, Ayman & Nechi, Salem, 2019. "New Approach to Estimating Gravity Models with Heteroscedasticity and Zero Trade Values," MPRA Paper 93426, University Library of Munich, Germany.
    17. Lucas A. Mariani & Jose Renato Haas Ornelas & Bernardo Ricca, 2023. "Banks’ Physical Footprint and Financial Technology Adoption," Working Papers Series 576, Central Bank of Brazil, Research Department.
    18. Gary F. Peters & Andrea M. Romi & Juan Manuel Sanchez, 2019. "The Influence of Corporate Sustainability Officers on Performance," Journal of Business Ethics, Springer, vol. 159(4), pages 1065-1087, November.
    19. Babur De los Santos & Sergei Koulayev, 2017. "Optimizing Click-Through in Online Rankings with Endogenous Search Refinement," Marketing Science, INFORMS, vol. 36(4), pages 542-564, July.
    20. Gorodnichenko, Yuriy & Sabirianova Peter, Klara, 2007. "Public sector pay and corruption: Measuring bribery from micro data," Journal of Public Economics, Elsevier, vol. 91(5-6), pages 963-991, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orisre:v:35:y:2024:i:2:p:783-806. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.