Understanding Crowdsourcing Contest Fitness Strategic Decision Factors and Performance: An Expectation-Confirmation Theo
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Understanding Crowdsourcing Contest Fitness Strategic Decision Factors and Performance: An Expectation-Confirmation Theory Perspective Emmanuel W. Ayaburi 1 & Jaeung Lee 2 & Michele Maasberg 2
# Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract Contest-based intermediary crowdsourcing represents a powerful new business model for generating ideas or solutions by engaging the crowd through an online competition. Prior research has examined motivating factors such as increased monetary reward or demotivating factors such as project requirement ambiguity. However, problematic issues related to crowd contest fitness have received little attention, particularly with regard to crowd strategic decision-making and contest outcomes that are critical for success of crowdsourcing platforms as well as implementation of crowdsourcing models in organizations. Using Expectation-Confirmation Theory (ECT), we take a different approach that focuses on contest level outcomes by developing a model to explain contest duration and performance. We postulate these contest outcomes are a function of managing crowdsourcing participant contest-fitness expectations and disconfirmation, particularly during the bidding process. Our empirical results show that contest fitness expectations and disconfirmation have an overall positive effect on contest performance. This study contributes to theory by demonstrating the adaptability of ECT literature to the online crowdsourcing domain at the level of the project contest. For practice, important insights regarding strategic decision making and understanding how crowd contestfitness are observed for enhancing outcomes related to platform viability and successful organizational implementation. Keywords Crowdsourcing . Contest-fitness . Expectation . Confirmation . Duration . Performance
1 Introduction Crowdsourcing refers to the process of a crowd-seeker tapping the intellect of a large pool of independent individuals (usually referred to as Bcrowd^) to either collaboratively or competitively fulfil the requirements of a project normally delegated to employees in an organization (Geiger and Schader 2014) or a task that requires human judgement (Xiao 2014). Advances in technology and electronic commerce have led to the establishment of third-party platforms known as intermediary crowdsourcing platforms to match business needs of institutions to the skills of the crowd who are usually outside the institution. In a typical intermediary crowdsourcing context,
* Emmanuel W. Ayaburi [email protected] 1
Department of Information Systems, The University of Texas Rio Grande Valley, 1201 W. University Dr., Edinburg, TX 78539, USA
2
Department of Computer Information Systems, Louisiana Tech University, Ruston, LA, USA
three entities are involved: 1) crowd-seekers; 2) platform operators; and 3) crowd. The crowd-seeker posts a project on the intermediary crowdsourcing platform with project requirements along with a fixed reward amount for the crowd member and the best solut
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