Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/27307
Title: Toward the role of organizational culture in data-driven digital transformation
Authors: Ghafoori, Arman
Gupta, Manjul
Merhi, Mohammad I.
Gupta, Samrat
Shore, Adam P.
Keywords: Data-driven digital transformation;Organizational culture;Operational performance;Hofstede;Competing values model;Manufacturing culture;Data analytics
Issue Date: 19-Mar-2024
Publisher: Elsevier
Abstract: Data-driven digital transformation is increasingly recognized as a crucial element of unlocking new business value, leveraging data-driven approaches in organizational business strategies and operations. Concurrently, organizational culture emerges as a critical factor in the organizational transformation process and success. However, current literature offers sparse insights into how organizational culture affects data-driven digital transformation. To gain deeper insights, this study leverages two complementary organizational culture frameworks to examine their relationship with data-driven digital transformation. Moreover, we investigate the link between data-driven digital transformation and operational performance in a manufacturing context. Utilizing data from 317 surveys, our findings show that organizational culture significantly affects data-driven digital transformation, which consequently impacts operational performance. This study advances understanding of the critical role of organizational culture in facilitating data-driven digital transformation, addressing a previously underexplored area in Operations and Supply Chain Management literature. By employing a dual-framework approach, it provides a more nuanced comprehension of organizational culture's impact on data-driven digital transformation while clarifying the complex relationship between digital transformation and operational performance within the manufacturing sector. Our study also delivers significant practical contributions, guiding organizations in effectively implementing and benefiting from data-driven digital transformation initiatives.
URI: http://hdl.handle.net/11718/27307
ISSN: 1873-7579
Appears in Collections:Journal Articles

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