透视图(图形)
意外事故
业务
频道(广播)
电子商务
营销
功率(物理)
产业组织
电信
计算机科学
哲学
语言学
物理
量子力学
人工智能
万维网
作者
Guangkuan Deng,Jianyu Zhang,Ying Xu,Lijuan He
出处
期刊:Journal of Business & Industrial Marketing
[Emerald Publishing Limited]
日期:2024-07-12
被引量:1
标识
DOI:10.1108/jbim-08-2023-0444
摘要
Purpose The integration of e-commerce platforms and artificial intelligence (AI) into the marketing channel ecosystem is challenging the explanatory capacity of traditional channel power theories, indicating a significant yet unaddressed research gap concerning the impact of these digital entities and AI on channel power exercise dynamics. This study adopts a contingency perspective to critically revisit how e-commerce platforms exercise channel power and the ensuing effects on channel conflicts. The purpose of this study is to extend the boundaries of traditional channel power theories, enhancing their relevance in today’s digital marketplace. Design/methodology/approach Building on channel power theories, the authors developed a framework tested with survey data collected from 262 sellers. This framework incorporates three key contingent variables: inter-platform competition, AI capabilities and platform value co-creation. Regression analysis was used to perform the analyses. Findings This study finds that intense inter-platform competition mitigates the (positive) negative relationship between platform channel power and the exercise of (non-) coercive power. Moreover, a platform’s AI capabilities and value co-creation activities diminish the potential for channel conflicts induced by the exercise of coercive power. AI capabilities can also strengthen the negative relationship between the exercise of non-coercive power and channel conflicts. Originality/value This study contributes to the advancement of traditional channel power theories by integrating contemporary digital elements like AI and platform dynamics. This study provides theoretical and practical insights on navigating channel power in modern marketing environments, offering strategic guidelines for optimizing channel relationships.
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