Date of Award

Spring 2018

Document Type

Dissertation

Degree Name

Doctor of Science in Information Systems

Department

Computer Science

First Advisor

Dr. Jun Liu

Second Advisor

Dr. Insu Park

Third Advisor

Dr. Jack H. Walters

Abstract

Employees are a main source of innovative ideas via their insights on companies’ products, processes, customers, and competitors. Enterprise crowdsourcing systems (ECSs) are used to collect, refine, and realize ideas. However, only a small percentage of employees submit ideas – about 7.7% at Pfizer, 2% at HCL Technologies, and 3% at Polaris Industries. Why is employee participation low? More specifically, what factors can lead employees to actively use ECS to submit and share their innovative ideas for improving their job performance? In this research, we used a multi-actor dyadic survey to survey 183 employees and their managers and conducted data analysis to understand the impact of ECS factors on employees’ job performance. Partial Least Squares (PLS) approach using Smart PLS was used to test both the measurement and structural models, and the results lend support for the proposed research model. The findings of the study confirm that knowledge sharing and employees’ cognitive features have a positive effect on effective knowledge application (EKA), and in turn, EKA increases employees’ ECS satisfaction, innovative behavior, and job performance. The study also confirmed that employees’ ECS satisfaction and innovative behavior have a positive effect on their job performance. The findings of this study can help organizations refine their ECSs and innovation initiatives to increase employees’ participation, innovative behavior, and job performance by enabling and supporting knowledge sharing among them, and implementing ECS with a solid, reward system meeting employees’ intrinsic and extrinsic motivational factors.

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