
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
* Author to whom correspondence should be addressed.
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.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
Disclaimer/Publisher's Note
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
About volume
Journal:Journal of Applied Economics and Policy Studies
© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license. Authors who
publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons
Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this
series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published
version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial
publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and
during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See
Open access policy for details).