All Theses and Dissertations
Degree
Doctor of Philosophy in Computer Science
Faculty / School
School of Mathematics and Computer Science (SMCS)
Department
Department of Computer Science
Date of Award
Fall 2024
Advisor
Dr. Zaheeruddin Asif, Assistant Professor School of Mathematics and Computer Science (SMCS), Institute of Business Administration (IBA), Karachi
Committee Member 1
Dr. Noman Islam
Committee Member 2
Dr. Syed Imran Jami
Committee Member 3
Dr. Shakeel Khoja
Project Type
Dissertation
Access Type
Restricted Access
Document Version
Final
Keywords
Crowdsourcing, Motivation, Capability, Performance, AMO Model, Human Capability Framework, Job Performance Model
Subjects
Computer Science
Abstract
Crowdsourcing has evolved to become an important business model since its inception. It offers cost effective and time efficient solutions by enabling large groups of individuals to contribute their knowledge, expertise, and resources via the Internet. Despite its advantages, the quality of tasks submitted by crowdworkers remains a significant concern, often influenced by their performance, which is driven by capability and motivation. Traditional performance metrics focus on an individual’s ability and effort, shaped by motivational factors. However, in the crowdsourcing domain, where worker associations are temporary and background information is limited, understanding how capability and motivation interact to influence performance is critical for improving task quality.
While prior research has explored crowdworker motivation, participation drivers, and reward mechanisms, the relationship between capability, motivation, and performance remains unexplored. Specifically, there is a lack of clarity on how to define, assess, and quantify a capable and motivated crowdworker, as well as how these constructs interactively affect performance. This research aims to address these gaps by thoroughly investigating the impact of capability and motivation on crowdworker performance. It explores which motivational elements most significantly influence performance, how to compute capability and motivation, and the nature of their combined effect – whether multiplicative or additive. Additionally, the study examines mediation effects i.e., whether capability mediates the motivation-performance relationship and vice versa.
The research is conducted in two parts: a survey analyzed using structural equation modeling (SEM) and an experimental study. The SEM analysis reveals that expectancy, extrinsic instrumentality and intrinsic valence are key drivers of motivation, while capacity, matching, and opportunity significantly enhance capability of crowdworker. Both constructs positively impact performance, with motivation fully mediating the capability-performance relationship and capability partially mediating the motivation-performance relationship, implying that an without motivation, capability alone may not significantly impact performance. The experimental study further confirms that the combined effect is multiplicative rather than additive.
This research is the first to formulate and validate the capability construct for crowdworkers and to investigate the multiplicative interaction of capability and motivation on performance. It provides valuable insights for practitioners in designing micro-tasks and identifying capable, motivated workers, even in contexts with limited monetary incentives. By understanding the interplay between capability and motivation, organization can improve the overall quality of crowdsourced submissions, ensuring more effective and culturally sensitive outcomes.
Recommended Citation
Karim Buksh, S. (2024). The Impact of Capability and Motivation on Performance of Crowdworkers in Crowdsourcing (Unpublished doctoral dissertation). Institute of Business Administration, Pakistan. Retrieved from https://ir.iba.edu.pk/etd/93
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