Appealing to the Crowd: Motivation Message Framing and Crowdsourcing Performance in Retail Operations
Ha Ta,
Terry L. Esper and
Travis Tokar
Production and Operations Management, 2021, vol. 30, issue 9, 3192-3212
Abstract:
For the execution of many supply chain operations tasks, firms are increasingly engaging in crowdsourcing—the act of dynamically delegating work via digital channels to for‐hire individuals intermittently available in the marketplace (also called “the crowd”). The success of this practice hinges on the ability to efficiently attract workers who produce quality work from among the crowd. We draw on the foundations of Self‐Determination Theory and the heuristic‐systematic model to examine the ways that variations in messages presented to crowdsourced agents can serve as a mechanism to enhance participation and associated performance outcomes. Data from a field experiment involving a retail inventory audit task reveal that messages appealing to the crowd's consumer identity, as opposed to crowdsourcing platform identification or firm identification, generally lead to superior performance outcomes, particularly shorter reservation time, higher task quality approval, and post‐task satisfaction. However, these effects are contingent on the valence of the message frame and the nature of the task. These findings shed light on elements critical to the successful utilization of this new type of crowdsourced “employment” in supply chain and operations tasks and suggest the careful crafting of crowdsourced task messages as a low‐cost way for managers to improve task performance outcomes.
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://doi.org/10.1111/poms.13423
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:popmgt:v:30:y:2021:i:9:p:3192-3212
Ordering information: This journal article can be ordered from
http://onlinelibrary ... 1111/(ISSN)1937-5956
Access Statistics for this article
Production and Operations Management is currently edited by Kalyan Singhal
More articles in Production and Operations Management from Production and Operations Management Society
Bibliographic data for series maintained by Wiley Content Delivery ().