A longitudinal study of IT-enabled crowdsourcing performance in a business context

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Minoo Modaresnezhad (Creator)
Institution
The University of North Carolina at Greensboro (UNCG )
Web Site: http://library.uncg.edu/
Advisor
Lakshmi Iyer

Abstract: Advances in internet-mediated collaborative technologies have allowed for a wide range of “open” and “crowdsourced” approaches. IT-enabled crowdsourcing (referred to as CS in this dissertation) is defined as technology enabled phenomenon of outsourcing tasks through an open call to the masses via the internet. CS practices have played an important role in facilitating search for external sources of innovation in online communities and open platforms. Over the past decade, research and practices on the new phenomenon of CS enabled by technological advances have continued to grow, evolve and revolutionize the way work gets done (e.g. Wikipedia, Kaggle, GalaxyZoo, Uber, Amazon Mechanical Turk, GoFundMe). Although several studies have been conducted in this area, few of them focused on understanding the interaction and integration of all the main components involved in the process. The concepts, components, and performance of IT-enabled crowd-sourced activities are not clear yet. Additionally, the power of (a) crowd has been largely ignored in idea generation and business consulting activities where the crowd needs to have specialized skills and high level of creativity to solve complex business problems. To address these knowledge gaps, the first section of this study identifies the main components involved in a CS process by developing a conceptual framework based on the current literature and applications. The conceptual model presented in this study takes a holistic view of the CS projects considering all the operations and factors involved. The framework allows for full, yet parsimonious, consideration of the factors that may affect the crowd’s participation effort and performance. Developing a conceptual framework expands our understanding of this phenomenon and helps to differentiate various cases based on fundamental dimensions and characteristics. The conceptual framework suggests that in order to define the dimensions of any IT-enabled CS process, we need to answer the following questions: Who? (who initiates the process? who benefits from it? who performs the task?) Why? (why does the crowd participate in the process?) What? (what is the task?) How? (how does the crowd perform the task [platform]?). Different combinations of answers to these questions, describe different types of CS processes. In the second part of this dissertation, a longitudinal study is conducted to investigate the dynamics of the major components involved in the process and their impact on individual participant’s effort and level of performance over time. Applying a longitudinal study might be the most appropriate way of studying the CS process which, to our knowledge, has not been reported in the literature before. Data from an open-source community is used to assess the dissertation model. This platform selects and crowd-sources real-life business challenges. Thousands of people from around the world take part in the competition and try to develop solutions for these challenges. The best solutions are being rewarded by monetary prizes and post-market compensation. Analyzing over 2,500 records of data, we find that the crowd characteristics (skill level, IT efficacy, international experience), their motivation (learning and direct compensations), task clarity, and communication and collaboration platform’s characteristics (ease-of-use, usefulness, media richness) impact the crowd’s participation behavior and performance. In the case of this study, since individuals compete in groups, perception of team’s behavior also has correlations with individual effort and performance. Additionally, the longitudinal study verifies that these relationships change throughout the process. In the third part of the dissertation, a qualitative study is conducted by interviewing some of the individual members of the crowd to further explain the results of the quantitative study. The interviews provide rich insights, help expand our understanding of the process, and better define the characteristics of each component involved in the process. The interpretive study also shows that the relationships between these components and the crowd’s participation behavior and performance change over time. A modified version of the CS conceptual framework in a business context is presented at the end of this section. Overall, this dissertation provides a better understanding of a technology-enabled CS process and examines the characteristics of its main components that might influence crowd’s participation behavior and performance in a business context. The results of this study could potentially fill the knowledge gap in the literature on the crowd’s performance in an IT-enabled CS process in a business domain. Understanding the crowd’s behavior can guide initiators to design proper mechanisms to attract and maintain participation of the right crowd. It provides guidance for organizations to leverage CS for activities such as business consulting, product development, and idea generation in the best possible way. The results of this study make substantial contributions to identifying the main characteristics of a CS process as a legitimate, IT-enabled form of problem solving.

Additional Information

Publication
Dissertation
Language: English
Date: 2017
Keywords
Business Context, Conceptual Framework, IT-Enabled Crowdsourcing, Longitudinal Study, Mixed Method Study, Performance
Subjects
Human computation $x Economic aspects
Online social networks in business
Human computation $x Social aspects
Business enterprises $x Technological innovations
Information technology $x Management

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