Buyer-Side Institution-Based Trust-Building Mechanisms: A 3S Framework with Evidence from Online Labor Markets

ABSTRACT

Buyer-side, institution-based trust-building mechanisms, which usually appear in the form of guarantee-required schemes, are prevalently provided by the online labor marketplace for buyers to voluntarily adopt. We integrate signaling theory and organization theories of organizational slack and contractual incompleteness to propose a 3S (screening, signaling, and slack) effect framework to explain how the adoption of buyer-side trust-building mechanisms (i.e., guarantee-required schemes) affects freelancers’ participation and bidding behavior. Based on a data set from one of the leading online labor markets in China, this study finds that guarantee-required tasks attract fewer but higher-quality freelancers. Furthermore, freelancers bid shorter durations but less-detailed proposals in guarantee-required tasks. This research also examines and finds support for the moderating role of task complexity in weakening screening and slack effects. Our research complements literature on trust-building mechanisms and online labor markets by providing a new framework (i.e., 3S effect framework) and empirical evidence with large-scale observational real-life data. Our study suggests that buyers should take both the advantages (e.g., bidders with higher-quality features, bids with shorter bidding durations) and disadvantages (e.g., fewer bids, bids with less-detailed proposals) into consideration and make appropriate trade-offs when making decisions on the adoption of buyer-side trust-building mechanisms.

KEY WORDS AND PHRASES:

• Bidding behavior
• bidding strategy
• freelancer participation
• institution-based mechanisms
• online labor markets
• trust-building mechanisms

Acknowledgments

This work was supported by National Natural Science Foundation of China (Project No. 71902097, 71572043); Natural Science Foundation of Shandong Province, China (Project No. ZR2019PG003, ZR2019MG037); Social Science Planning and Research Project of Shandong Province, China (Project No. 19DGLJ03); and Higher Education Research and Planning Project of Shandong Province, China (Project No. J18RA135). We are very thankful for their generous support.

Notes

¹ https://www.statista.com/statistics/507881/ebays-annual-net-revenue/(accessed in June 2019).

² https://www.chinainternetwatch.com/29315/alibaba-q1-2019/(accessed in June 2019).

³ https://www.freelancer.com/(accessed in June 2019).

⁴ http://www.witmart.com/about/overview.html (accessed in June 2019).

⁵ Note that the usage of some of these mechanisms is mandatory, whereas other mechanisms are optional for buyers or freelancers to voluntarily choose.

⁶ This third guarantee scheme is usually used by bidders when bidding for design tasks.

⁷ For variables that contain zero (BidNum, BuyerExp), we add the lowest nonzero value (+1) before the log transformation [27, 44].

⁸ The variables are first standardized to construct the instruments for the interaction terms.

Additional information

Notes on contributors

Zhijuan Hong

Zhijuan Hong ([email protected], corresponding author) is an assistant professor in the School of Management Science and Engineering at the Shandong University of Finance and Economics, China. She received her Ph.D. from Fudan University, China. Her research interests include electronic commerce, online labor markets and online volunteering.

Hui Zhu

Hui Zhu ([email protected]) is an assistant professor in the School of Information Technology at Jiangxi University of Finance and Economics, China. He received his Ph.D. in School of Economics and Management from Southeast University, China. He specializes in the data-driven optimization techniques with applications in decision and supply chain management. His research interests include business analytics, production and operations management, scheduling and data mining. His work has been published in Computers & Industrial Engineering and International Journal of Production Research.

Kunxiang Dong

Kunxiang Dong ([email protected]) is an assistant professor in the School of Management Science and Engineering at the Shandong University of Finance and Economics, China. He received his Ph.D. from Nankai University, China. His research interests include information security and electronic commerce.