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Author ORCID Identifier

https://orcid.org/0000-0001-7584-8274

AccessType

Campus-Only Access for Five (5) Years

Document Type

dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Management

Year Degree Awarded

2024

Month Degree Awarded

February

First Advisor

Bruce Skaggs

Second Advisor

Cristina Vlas

Third Advisor

Anurag Sharma

Fourth Advisor

Lisa Keller

Subject Categories

Strategic Management Policy

Abstract

My three-paper dissertation focuses on different teams that can impact innovation initiatives (e.g., executive directors and human capital with AI knowledge), while developing an understanding of the current literature on how artificial intelligence (AI) is changing organizational learning, firm innovation and firm human capital. By organizational innovation, I refer to “production or adoption, assimilation, and exploitation of a value-added novelty in economic and social spheres; renewal and enlargement of products, services, and markets; development of new methods of production; and establishment of new management systems. It is both a process and an outcome” (Crossan & Apaydin, 2010); as such, innovation is critical for firm performance. Organizational innovation can be manifested in product or service offerings, organizational processes or business models (Chesbrough, 2010; Cottrell & Nault, 2004; Tarfadar et al, 2019). While organizational innovation has garnered a great deal of scholarly work, there is a need to reexamine the current assumptions of how organizations innovate – specifically, the impact of different groups on innovation performance. I also believe that the current phenomenal advancements in technology can and do change what we know about organizational learning and firm human capital as critical aspects of organizations with ramifications on organizational innovation. These changes beg for further understanding of what we currently know about AI deployment and organizational learning, firm innovation and human capital, while developing a map for future research. To this end, in this dissertation I aim at reexamining some of the assumptions related to organizational innovation in the light of AI advancements and new perspectives of behavioral characteristics of different teams involved in innovation. To bring attention to the assumptions of organizational innovation and to contribute to this growing body of literature, this dissertation undertakes three distinct papers. In the first paper, I examine how executive directors’ behavioral characteristics impact the theorized negative relationship between executive directors and a firm’s innovation performance. By doing so, I aim at challenging the current assumption of executive directors’ homogeneity in interests and decisions. In the second paper, I build a contingency model around the AI- innovation link. In this paper, I examine how different external factors related to uncertainty and knowledge tacitness can impact the ability of a firm’s human capital with AI knowledge to advance innovation. The last paper of the dissertation reviews the current literature on AI and organizational learning, firm innovation and human capital with an aim to develop an agenda for future research.

DOI

https://doi.org/10.7275/36369286

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