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Process Structure Model of the Intelligent Experience Engine: A Multi-case Study Based on Grounded Theory
- 1 Beijing University of Posts and Telecommunications
- 2 Beijing University of Posts and Telecommunications
- 3 Beijing University of Posts and Telecommunications
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Abstract
Customer experience is an important strategic process for businesses to provide personalized services to customers in order to gain competitive advantages. As it enters the intelligent stage, how to manage the intelligent customer experience has become an urgent issue to explore. Based on the customer experience theory, this article uses the grounded theory research method to conduct a multi-case study, clarifies the concept of the intelligent experience engine, and proposes a process structure model for it. Its structural level includes the contact layer, data layer, and decision layer. The research results extend the customer experience theory and have good theoretical insights and practical guidance for businesses to carry out intelligent customer experience management activities.
Keywords
customer experience, intelligent customer experience, intelligent experience engine, grounded theory
[1]. Rajnish, Jain, Jayesh, Aagja, Shilpa, & Bagdare. (2017). Customer experience – a review and research agenda. Journal of Service Theory and Practice, 27(3), 642-662.
[2]. Pine, II, B., & Joseph. (1998). Welcome to the experience economy. Harvard Business Review, 78(1):97-105.
[3]. Gentile, C. , Spiller, N. , & Noci, G. . (2007). How to sustain the customer experience:. European Management Journal, 25( 5), 395-410.
[4]. Verhoef, P. C. , Lemon, K. N. , Parasuraman, A. , Roggeveen, A. , Tsiros, M. , & Schlesinger, L. A. . (2009). Customer experience creation: determinants, dynamics and management strategies. Journal of Retailing, 85(1), 31-41.
[5]. Sanjit, Kumar, Roy, M, S, & Balaji, et al. (2017). Constituents and consequences of smart customer experience in retailing. Technological Forecasting & Social Change, 124(nov.):257-270.
[6]. Swinyard, W. R. , & Rinne, H. J. . (1994). The six shopping worlds of baby boomers. Business Horizons, 37(5), 64-69.
[7]. Puccinelli, N. M. , Goodstein, R. C. , Grewal, D. , Price, R. , Raghubir, P. , & Stewart, D. . (2009). Customer experience management in retailing: understanding the buying process. Journal of Retailing, 85(1), 15-30.
[8]. Choi, E. K. , Wilson, A. , & Fowler, D. . (2013). Exploring customer experiential components and the conceptual framework of customer experience, customer satisfaction, and actual behavior. Journal of Foodservice Business Research, 16(4), 347-358.
[9]. Tynan, Caroline, McKechnie, & Sally. (2009). Experience marketing: a review and reassessment. Journal of Marketing Management, 25(5-6):501-517.
[10]. Terblanche, & Nic, S. . (2018). Revisiting the supermarket in-store customer shopping experience. Journal of Retailing & Consumer Services, 40, 48-59.
[11]. Guo, Lingyun, Zhang, Mingli, Hu, & Mu. (2017). Understanding relationships among customer experience, engagement, and word-of-mouth intention on online brand communities the perspective of service ecosystem. Internet Research Electronic Networking Applications & Policy, 27(4):839-857.
[12]. Gonalves, L. , Lia Patrício, Teixeira, J. G. , & Nancy V. Wünderlich. (2020). Understanding the customer experience with smart services. Journal of Service Management, 31(4), 723-744.
[13]. Neuhofer, B. , Magnus, B. , & Celuch, K. . (2020). The impact of artificial intelligence on event experiences: a scenario technique approach. Electronic Markets, 1-17.
[14]. Trivedi, J. . (2019). Examining the customer experience of using banking chatbots and its impact on brand love: the moderating role of perceived risk. Journal of Internet Commerce, 1-21.
[15]. David C. E. & Mark A. (2020). Customer Experience in the age of AI. Harvard Business Review, 181(3):116-125.
[16]. Stein, A. , & Ramaseshan, B. . (2016). Towards the identification of customer experience touch point elements. Journal of Retailing and Consumer Services, 30, 8-19.
[17]. Glaser, B. G., & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research. Chicago: Aldine.
[18]. Strauss, A. , & Corbin, J. . (1994). Grounded Theory Methodology. Handbook of Qualitative Research, 17:273-285.
[19]. Graebner, E. M. E. . (2007). Theory building from cases: opportunities and challenges. Academy of Management Journal, 50(1), 25-32.
[20]. Eisenhardt, & K., M. . (1991). Better stories and better constructs: the case for rigor and comparative logic. Academy of Management Review, 16(3), 620-627.
Cite this article
Yang,X.;Zhang,W.;Guo,J. (2024). Process Structure Model of the Intelligent Experience Engine: A Multi-case Study Based on Grounded Theory. Journal of Applied Economics and Policy Studies,2,16-24.
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