IF 6.7 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

摘要

随着人工智能(AI)技术的发展和广泛应用,各行各业都认识到了它的巨大潜力和意义,尤其是在电子商务领域。本研究考虑的是由制造商和可能提供人工智能服务的平台组成的电子商务平台供应链(EPSC)。本研究的主要目的是探讨不同客户服务策略(即人工或人工智能服务)与不同销售模式(即代理或转售模式)之间的战略互动。研究结果表明,如果人工服务敏感度相对较高,制造商更愿意制定较高的批发价格。当人工客户对需求的服务效率衰减效应较强时,人工智能服务会带来更多需求。此外,当服务效率衰减效应较强或较弱但人工智能服务效率较高时,易胜博主页可利用人工智能服务在转售模式下获得更多利润。在代理模式下,当服务效应衰减系数相对较大时,人工智能服务会使 EPSC 受益更多。最后,我们还发现,当人工智能服务成本系数相对较小时,转售模式能使 EPSC 受益更多。最重要的是,与人工服务相比,人工智能服务为 EPSC 提供了一个新的机会,使其更容易接受转售模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Selling mode selection and AI service strategy in an E-commerce platform supply chain

With the advancement and wide adoption of Artificial Intelligence (AI) technology, various industries have recognized its immense potential and significance, especially in the e-commerce sector. This study considers an E-commerce Platform Supply Chain (EPSC) consisting of a manufacturer and a platform that may provide AI service. The primary purpose of this research is to explore the strategic interaction between different customer service strategies (i.e., Manual or AI service) and different selling modes (i.e., Agency or reselling mode). The research results show that if the manual service sensitivity is relatively high, the manufacturer is more willing to set a higher wholesale price. When the service efficiency attenuation effect of the manual customer towards demand is stronger, AI service would bring about more demand. Additionally, when the service efficiency attenuation effect is stronger, or it is weaker but the AI service efficiency is higher, the EPSC could utilize AI service to obtain more profit under reselling mode. Under agency mode, AI service can benefit the EPSC more when the service effect attenuation coefficient is relatively larger. Last but not least, we find that when the AI service cost coefficient is relatively small, the reselling mode can benefit the EPSC more. Most importantly, compared with manual service, AI service provides the EPSC with a new opportunity to embrace the reselling mode more.

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来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
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