Graduation Semester and Year

Summer 2026

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Business Administration

Department

Information Systems and Operations Management

First Advisor

Dr. Jennifer Jie Zhang

Second Advisor

Dr. Sridhar Nerur

Third Advisor

Dr. Mahmut Yasar

Abstract

This dissertation comprises three independent essays that engage related themes at the intersection of gender, technology, and organizational outcomes in information systems. The first essay investigates the market's reaction to the appointment of female CEOs in ICT firms, analyzing whether and how investor perceptions shift following such leadership changes. Drawing on role incongruity theory, the study explores the extent to which gendered CEO appointments in different economic environments influence stock market outcomes in the IT industry. The second essay examines the relationship between a firm's AI resources and its performance. Drawing on the resource-based view, it tests whether AI intangible resources and AI human capital resources enhance market value and profitability, thereby underscoring the strategic importance of AI in driving firm performance. Extending this logic through the knowledge-based view, the essay further examines how industry heterogeneity moderates these relationships. The third essay shifts focus to the entrepreneurial landscape, examining how women-led startups leverage artificial intelligence to fuel venture growth. Drawing on legitimacy theory, it argues that ventures positioning AI at the core of their business identity gain legitimacy with investors. Complementing this, signaling theory suggests that protected AI innovations serve as credible signals of technological capability. Together, these mechanisms are expected to improve women-led startups' access to funding. Collectively, these essays contribute to two enduring streams of information systems research, women's leadership in technology and the performance implications of technology adoption, advancing our understanding of women's roles in technology-intensive contexts and of the conditions under which technology translates into economic value.

Keywords

artificial intelligence, women in tech, information systems, women entrepreneur, digital transformation, firm performance

Disciplines

Leadership | Management Information Systems | Technology and Innovation

License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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Available for download on Monday, July 31, 2028

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