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Volume 19, September
 
 

J. Theor. Appl. Electron. Commer. Res., Volume 19, Issue 4 (December 2024) – 2 articles

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23 pages, 2853 KiB  
Article
Unraveling the Influential Mechanisms of Smart Interactions on Stickiness Intention: A Privacy Calculus Perspective
by Jinyi He, Xinjian Liang and Jiaolong Xue
J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2582-2604; https://doi.org/10.3390/jtaer19040124 (registering DOI) - 26 Sep 2024
Abstract
Artificial intelligence (AI) technologies are changing the ways of interaction between humans and machines, and smart interactions have become one of the hot topics of artificial intelligent in-home voice assistants (AVAs) by connecting humans, machines, content, and AVAs. Based on the privacy calculus [...] Read more.
Artificial intelligence (AI) technologies are changing the ways of interaction between humans and machines, and smart interactions have become one of the hot topics of artificial intelligent in-home voice assistants (AVAs) by connecting humans, machines, content, and AVAs. Based on the privacy calculus theory (PCT), the authors conducted an online questionnaire-based survey to investigate the influential mechanisms of smart interactions on stickiness intention (SI), demonstrated the positive (negative) effects of smart interactions on benefits and risks, and verified the moderating role of susceptibility to normative influence (SNI). The results show that smart interactions positively impact SI via utilitarian benefit and hedonic benefit; humanness has a U-shaped effect on privacy risk; personalization, connectivity, and linkage positively impact privacy risk; multimodal control negatively impacts privacy risk; and SNI positively moderates the effects of smart interactions on stickiness intention. The study enriched and expanded the literature on smart interactions in the context of AIoT and offered practical implications for AVA service providers and developers to design or optimize smart interactions for AI interactive services. By examining the double-edged sword effects of personalization and humanness, our findings offer novel insights into the privacy calculus in smart interactions. Full article
(This article belongs to the Topic Interactive Marketing in the Digital Era)
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25 pages, 508 KiB  
Article
Strategic Interactions in Omnichannel Retailing: Analyzing Brand Competition and Optimal Strategy Selection
by Jing Yu, Yufei Ren and Chi Zhou
J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2557-2581; https://doi.org/10.3390/jtaer19040123 (registering DOI) - 25 Sep 2024
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Abstract
The rapid advancement of digital technology has blurred the line between online and brick-and-mortar stores, leading to the proliferation of omnichannel retailing. Two widely adopted strategies are Buy Online and Pick Up in Store (BOPS) and Ship from Store (SFS). This study examines [...] Read more.
The rapid advancement of digital technology has blurred the line between online and brick-and-mortar stores, leading to the proliferation of omnichannel retailing. Two widely adopted strategies are Buy Online and Pick Up in Store (BOPS) and Ship from Store (SFS). This study examines a supply chain where a manufacturer sells national brand products through an e-commerce platform (e-platform) that also offers its own brand products. We analyze the optimal omnichannel strategies for both the e-platform and the manufacturer, considering scenarios of cooperation and brand competition, across four strategy combinations. Our findings highlight that the profits of both the e-platform and manufacturer are primarily influenced by the commission rate, product category valuation and competition intensity. The commission rate plays a pivotal role in shaping the e-platform’s strategy: a low rate leads to direct competition with the manufacturer, while a high rate prioritizes the manufacturer’s products. When the spillover profit is less than the net difference between the customer’s additional benefits and the firm’s additional costs for SFS compared to BOPS, and the commission rate is high, an equilibrium is achieved. Sensitivity analyses reveal that as the product differentiation decrease, the manufacturer’s profits decline, while the e-platform’s profits rise with an increasing commission rate. Full article
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