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Wenkai Zhou

Wenkai Zhou, Ph.D.

Associate Professor of Marketing

At Crummer, we don’t just follow the evolution of graduate and executive business education—we drive it. As forward-thinking innovators fueled by curiosity, we place value creation at the center of our offerings. Embracing emerging fields like AI and sustainability, we constantly improve. We’re not just preparing for the future—we’re creating it.

Dr. Wenkai Zhou is an Associate Professor of Marketing at the Crummer Graduate School of Business. Before joining Crummer, he taught marketing at the University of Central Oklahoma and the University of Wisconsin–Green Bay.

Originally from Xi’an, China’s ancient capital, Wenkai brings deep insights into Chinese culture and its impact on business thinking. His global perspective is enriched by his childhood years in Australia and extensive academic and professional experiences across the United States. With a unique blend of Eastern and Western backgrounds, Wenkai is passionate about helping individuals and organizations navigate global trends like technological transformations and cross-cultural consumer decision-making. He aims to enhance strategic marketing decisions in today’s interconnected and unpredictable global economy.

Wenkai prides himself on viewing marketing from a holistic perspective rather than a fragmented one. He’s curious about many aspects of marketing, especially how emerging trends reshape the field. His teaching philosophy centers on value creation and overcoming siloed and dualistic thinking in marketing strategy for managers and executives. His current research interests include the intersection of AI and marketing, marketing in emerging markets, digital technology adoption and organizational adaptability, consumer decision-making, and innovative survey methods. He has presented at various academic conferences, and his work has been featured in numerous journals, including Technological Forecasting and Social Change, Journal of Business Research, European Journal of Marketing, Journal of Knowledge Management, and many others.

Wenkai’s research has won track best paper awards at the Society for Marketing Advances annual conferences. In 2022, his co-authored study on what drives salespeople to accept AI received an honorable mention for the Marvin Jolson Award for Best Contribution to Selling and Sales Management Practice from the Journal of Personal Selling & Sales Management. He has served as a co-guest editor for special issues of the International Marketing Review and the International Journal of Market Research. He also sits on the editorial boards of the Journal of Global Marketing and the Journal of Information Technology Case and Application Research.

In his free time, you can find Wenkai playing with his two dogs, traveling, or diving into documentaries that blend science and philosophy. His favorite part of teaching at Crummer is engaging in deep discussions with curious minds, sparking insights that go beyond the classroom.

Research & Articles

Yao, Q., Hu, C., & Zhou, W. (2024). | Technological Forecasting and Social Change, 198, 122948.

Customer privacy concerns and service scenarios are important influencing factors affecting the adoption of service robots. This research examines the mechanism and boundary conditions associated with the interaction effect between customers’ privacy concerns and service type on their willingness to adopt service robots. Based on the “credence/experience” service classification, we conducted two scenario experiments and demonstrated that the interaction effect between privacy concerns and service type influences customers’ willingness to adopt service robots. The findings suggest that individuals with high privacy concerns are less willing to utilize service robots in credence services (vs. experience services) than are individuals with low privacy concerns. Customer data vulnerability plays a mediating role in this relationship, which is moderated by personalization declaration. Theoretical and managerial implications are discussed.

https://doi.org/10.1016/j.techfore.2023.122948

Zhou, W., Zhang, C., Wu, L., & Shashidhar, M. (2023). | Journal of Marketing Analytics, 11(4), 693-706.

Despite the significant interest generated by the Generative AI model ChatGPT, there is still a lack of understanding regarding its impact on marketing from the perspective of early informants. In order to address this gap, our research investigates the initial posts made by Twitter users concerning the relationship between ChatGPT and marketing. Using BERTopic-based topic modeling, we determined the primary themes related to this subject and monitored their popularity over time. Our analysis identified ten distinct clusters of tweets related to ChatGPT and marketing, and we provide a thorough examination of these themes. We also investigated the temporal patterns of these clusters within the timeframe studied and outlined the implications of our findings for both marketing academia and practice.

https://doi.org/10.1057/s41270-023-00250-6

Chen, J., & Zhou, W. (2022). | Journal of Personal Selling & Sales Management, 42(2), 107-120.

This research is among the first to examine salespeople’s acceptance of AI (artificial intelligence) and we investigate the drivers of their AI acceptance from the perspective of the managers. In this study, we propose and empirically demonstrate that perceived ease of use, self-efficacy, perceived management support, and digitalization are positively related to salespeople’s acceptance of AI. Moreover, we show that digitalization mediates the relationship between salespeople’s prospecting/adaptive selling capabilities and their AI acceptance. The results suggest that in order to incentivize AI acceptance, managers need to build adequate digital infrastructure, cultivate organizational support to encourage AI adoption and usage, provide professional training to educate salespeople on the proper usage of AI, and reduce salespeople’s perceived risk of AI usage. Theoretical and managerial implications are discussed subsequently.

https://doi.org/10.1080/08853134.2021.2016058