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Effects of Conversation Politeness on Hiring Decision in Online Labor Markets: An Inverted U-Shaped Relationship Exploration

Author

Listed:
  • Lingfeng Dong

    (Alibaba Business College, Hangzhou Normal University, Hangzhou 311121, China)

  • Ting Ji

    (School of Management, Zhejiang University, Hangzhou 310058, China)

  • Jie Zhang

    (Institute of Digital Finance, Zhejiang University City College, Hangzhou 310015, China)

Abstract

This study examined the effect of politeness, as a key reflection of linguistic features of conversation in the online labor marketplace, on hiring behavior. Drawing on the politeness theory, a non-linear relationship was theorized. A hypothesis was put forward and examined against a large-scale archival dataset from a Chinese online labor market. Using an econometric model, the results demonstrated that there was an inverted U-shaped relationship between politeness and hiring decisions. The study offers theoretical implications to the online labor market literature and politeness theory by providing empirical insights on the role of politeness in hiring decision. In addition, our findings offer beneficial and practical contributions for vendors and platform operators.

Suggested Citation

  • Lingfeng Dong & Ting Ji & Jie Zhang, 2022. "Effects of Conversation Politeness on Hiring Decision in Online Labor Markets: An Inverted U-Shaped Relationship Exploration," Sustainability, MDPI, vol. 14(22), pages 1-11, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:15351-:d:977037
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    References listed on IDEAS

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    1. Yi Wang, 2021. "The price of being polite: politeness, social status, and their joint impacts on community Q&A efficiency," Journal of Computational Social Science, Springer, vol. 4(1), pages 101-122, May.
    2. Marios Kokkodis, 2021. "Dynamic, Multidimensional, and Skillset-Specific Reputation Systems for Online Work," Information Systems Research, INFORMS, vol. 32(3), pages 688-712, September.
    3. Yili Hong & Paul A. Pavlou, 2017. "On Buyer Selection of Service Providers in Online Outsourcing Platforms for IT Services," Information Systems Research, INFORMS, vol. 28(3), pages 547-562, September.
    4. Irfan Kanat & Yili Hong & T. S. Raghu, 2018. "Surviving in Global Online Labor Markets for IT Services: A Geo-Economic Analysis," Information Systems Research, INFORMS, vol. 29(4), pages 893-909, December.
    5. Xue (Jane) Tan & Youwei Wang & Yong Tan, 2019. "Impact of Live Chat on Purchase in Electronic Markets: The Moderating Role of Information Cues," Information Systems Research, INFORMS, vol. 30(4), pages 1248-1271, December.
    6. Yili Hong & Jing Peng & Gordon Burtch & Ni Huang, 2021. "Just DM Me (Politely): Direct Messaging, Politeness, and Hiring Outcomes in Online Labor Markets," Information Systems Research, INFORMS, vol. 32(3), pages 786-800, September.
    7. Coussement, Kristof & Van den Bossche, Filip A.M. & De Bock, Koen W., 2014. "Data accuracy's impact on segmentation performance: Benchmarking RFM analysis, logistic regression, and decision trees," Journal of Business Research, Elsevier, vol. 67(1), pages 2751-2758.
    8. Gordon Burtch & Yili Hong & Senthil Kumar, 2021. "When Does Dispute Resolution Substitute for a Reputation System? Empirical Evidence from a Service Procurement Platform," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1565-1582, June.
    9. Mingfeng Lin & Yong Liu & Siva Viswanathan, 2018. "Effectiveness of Reputation in Contracting for Customized Production: Evidence from Online Labor Markets," Management Science, INFORMS, vol. 64(1), pages 345-359, January.
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