Retracted: Artificial Intelligence Relationship on Consumer Behavior in Marketing Theory

Abdur Rakib Nayeem, Mohammad Khairul Islam, Md. Khorshed Alam, Mst. Fatema Akter, Md. Shahab Ali Raja
2020 Asian Journal of Economics Business and Accounting  
Various recently-introduced applications of artificial intelligence (AI) operate at the interface between businesses and consumers. This paper looks at whether these innovations have relevant implications for marketing theory. The latest literature on the connection between AI and marketing has emphasized a great variety of AI applications that qualify this relationship. Based on these studies but focusing only on the applications with a direct impact on the relationship at the very heart of
more » ... he very heart of marketing, i.e., the one between firms and consumers, the paper analyzes three categories of AI applications: AI-based shipping-then-shopping, AI-based service robots, and AI-based smart products and domestic robots. The main result of this first analysis is that all three categories have to do, each in their own way, with mass customization. A discussion of this common trait leads us to recognize their ways to mass customization that – unlike the traditional approach developed thanks to flexible automation and product modularity technologies – place the customization process within a broader perspective of consumer needs management. This change in approach means that marketing should focus more on managing consumers' needs than directly on the satisfaction of those needs. This finding marks a genuine discontinuity that opens up a new space for reflection for scholars and marketing managers alike. Retraction Notice: This paper has been retracted from the journal after receipt of written complains. This journal is determined to promote integrity in research publication. This retraction is in spirit of the same. After formal procedures editor(s) and publisher have retracted this paper on 10th November-2020. Related policy is available here: http://goo.gl/lI77Nn
doi:10.9734/ajeba/2020/v19i130296 fatcat:fosbqxiagjc3rhwdxgb7qm26oq