营销领域中算法推荐与消费者响应:研究评述与展望  

Algorithm-Based Recommendations and Consumer Response in Marketing:A Literature Review and Prospects

作　　者：陈昌东 江若尘 CHEN Chang-dong;JIANG Ruo-chen(College of Business,Shanghai University of Finance and Economics,Shanghai,200433,China;School of shanghai Development,Shanghai University of Finance and Economics,Shanghai,200433,China)

机构地区：[1]上海财经大学商学院,上海200433 [2]上海财经大学上海发展研究院,上海200433

出　　处：《经济管理》2021年第10期193-208,共16页Business and Management Journal ( BMJ )

摘　　要：在数字经济时代,数据成为了一种战略性生产要素参与到价值创造、分配、流通和消费的全过程,算法则成为了收集和处理数据的战略性工具,衍生出了基于算法的推荐,成为了近年来实务界营销创新和赋能的重要驱动力。在营销领域的国际顶级期刊上,均有不少的文献关注算法推荐在营销领域的应用与消费者响应问题,但研究点相对比较散乱。由于国内营销学者对该领域的研究还相对匮乏,亟需一个整合性的框架来分析和梳理现有研究成果与进展。同时,实务界也亟需一个一般性的算法嵌入型应用接受模型来指导企业相关的开发与应用。鉴于此,本文首先对推荐系统和算法推荐的概念和内涵进行了界定,通过全面梳理算法推荐在营销领域中的应用与消费者响应及其中介机制与边界条件,试图勾勒出现有研究脉络和研究进展,并提出了该领域未来值得关注的若干研究主题。In recent years, society has been undergoing subversive scientific and technological changes, and has stepped forward a digital economy era based on the fourth industrial revolution. Compared with the industrial economy era, the biggest feature of the digital economy era is that data has become the fifth factor of production to participate in social production activities, which is no longer just auxiliary information for decision-making, but a strategic factor of production, participating in the whole process of value creation, distribution, circulation and consumption. However, at the same time, massive data also increases the complexity, dynamics, and uncertainty of consumers’ purchase decisions. Thus, product recommendation plays an increasingly prominent and important role in consumers’ purchase decisions. In the past, human-based recommendation was the main source for consumers to obtain product information. In the era of digital economy, algorithm-based recommendation has been derived as algorithms have become a strategic tool for collecting and processing data, which has also become a hot topic in the field of marketing practice and theory in recent years.The previous research on algorithm-recommendation presents a multi-disciplinary and multi-level development trend, involving the fields of computer, Artificial Intelligence(AI), and marketing management. Although algorithms have made great progress and development in the fields of computer and AI, the technical field just regards algorithm-based recommendation as a neutral tool based on efficiency and accuracy evaluation. However, this goal of creating excellent technology(e.g., improving accuracy) may not necessarily achieve the goal of creating valuable consumer experience in the marketing field of management due to the ignorance of the complexity of personal and social circumstances that algorithm-recommendation are applied to. Consequently, marketing scholars began to integrate consumers’ psychological and behavioral insights into technology, to

关 键 词：人工智能 数字营销 算法推荐 消费者响应 情境变量 

分 类 号：F270[经济管理—企业管理]