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Enhancing value in customer journey by considering the (ad)option of artificial intelligence tools

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  • Dhiman, Neeraj
  • Jamwal, Mohit
  • Kumar, Ajay

Abstract

Artificial intelligence(AI) technologies are revolutionizing the customer journey remarkably. Current research employsextended value-based adoption model (VAM) incorporating mediating and moderating variables to predict the adoption intentions of AI technologies. Using a structured questionnaire, 392 responses were collected and analyzed using partial least square structural equation modelling. Results showed that AI technology's usefulness, fascinating features, and trustpositively impact its value in customers' eyes. Technological anxiety related to AI dampensAI tools’ value. Making AI tools human like (anthropomorphic) do not enhance its value. This study establishes that the value associated with AI tools leads to relationship (parasocial) formation with them and itincreases the possibility of AI technologies use. Study showed that the users who have different liking towards AI tools usage (AI fans, detractors and indifferent) influence the relationship between AI tools’ value and intentions to use AI differently. The study further offers valuable theoretical and practical implications.

Suggested Citation

  • Dhiman, Neeraj & Jamwal, Mohit & Kumar, Ajay, 2023. "Enhancing value in customer journey by considering the (ad)option of artificial intelligence tools," Journal of Business Research, Elsevier, vol. 167(C).
  • Handle: RePEc:eee:jbrese:v:167:y:2023:i:c:s0148296323005015
    DOI: 10.1016/j.jbusres.2023.114142
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    as
    1. Dwivedi, Yogesh K. & Hughes, Laurie & Ismagilova, Elvira & Aarts, Gert & Coombs, Crispin & Crick, Tom & Duan, Yanqing & Dwivedi, Rohita & Edwards, John & Eirug, Aled & Galanos, Vassilis & Ilavarasan, , 2021. "Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy," International Journal of Information Management, Elsevier, vol. 57(C).
    2. Kasilingam, Dharun Lingam, 2020. "Understanding the attitude and intention to use smartphone chatbots for shopping," Technology in Society, Elsevier, vol. 62(C).
    3. Jyoti Rana & Loveleen Gaur & Gurmeet Singh & Usama Awan & Muhammad Imran Rasheed, 2021. "Reinforcing customer journey through artificial intelligence: a review and research agenda," International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 17(7), pages 1738-1758, December.
    4. Zhong, Yongping & Oh, Segu & Moon, Hee Cheol, 2021. "Service transformation under industry 4.0: Investigating acceptance of facial recognition payment through an extended technology acceptance model," Technology in Society, Elsevier, vol. 64(C).
    5. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    6. Porter, Constance Elise & Donthu, Naveen, 2006. "Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics," Journal of Business Research, Elsevier, vol. 59(9), pages 999-1007, September.
    7. Mike Grimsley & Anthony Meehan, 2007. "e-Government information systems: Evaluation-led design for public value and client trust," European Journal of Information Systems, Taylor & Francis Journals, vol. 16(2), pages 134-148, April.
    8. Kamal, Syeda Ayesha & Shafiq, Muhammad & Kakria, Priyanka, 2020. "Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM)," Technology in Society, Elsevier, vol. 60(C).
    9. Hoyer, Wayne D. & Kroschke, Mirja & Schmitt, Bernd & Kraume, Karsten & Shankar, Venkatesh, 2020. "Transforming the Customer Experience Through New Technologies," Journal of Interactive Marketing, Elsevier, vol. 51(C), pages 57-71.
    10. Yuhan Ge & Qing Yuan & Yaxi Wang & Keunsoo Park, 2021. "The Structural Relationship among Perceived Service Quality, Perceived Value, and Customer Satisfaction-Focused on Starbucks Reserve Coffee Shops in Shanghai, China," Sustainability, MDPI, vol. 13(15), pages 1-19, August.
    11. Ronan De Kervenoael & Alexandre Schwob & Rajibul Hasan & Yak Shu Ting, 2021. "Consumers' perceived value of healthier eating: A SEM analysis of the internalisation of dietary norms considering perceived usefulness, subjective norms, and intrinsic motivations in Singapore," Post-Print hal-03344709, HAL.
    12. Bonsón Ponte, Enrique & Carvajal-Trujillo, Elena & Escobar-Rodríguez, Tomás, 2015. "Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents," Tourism Management, Elsevier, vol. 47(C), pages 286-302.
    13. Lalicic, Lidija & Weismayer, Christian, 2021. "Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents," Journal of Business Research, Elsevier, vol. 129(C), pages 891-901.
    14. Andrew Baker & Naveen Donthu, 2021. "Fight or flight?: Understanding customer response to CRM tactics," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 31(3), pages 318-336, July.
    15. Fernandes, Teresa & Oliveira, Elisabete, 2021. "Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption," Journal of Business Research, Elsevier, vol. 122(C), pages 180-191.
    16. Subero-Navarro, à urea & Pelegrín-Borondo, Jorge & Reinares-Lara, Eva & Olarte-Pascual, Cristina, 2022. "Proposal for modeling social robot acceptance by retail customers: CAN model + technophobia," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    17. Se-Joon Hong & Kar Yan Tam, 2006. "Understanding the Adoption of Multipurpose Information Appliances: The Case of Mobile Data Services," Information Systems Research, INFORMS, vol. 17(2), pages 162-179, June.
    18. Prasad Naik & Chih‐Ling Tsai, 2000. "Partial least squares estimator for single‐index models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 763-771.
    19. Jaiswal, Deepak & Kaushal, Vikrant & Kant, Rishi & Kumar Singh, Pankaj, 2021. "Consumer adoption intention for electric vehicles: Insights and evidence from Indian sustainable transportation," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    20. Gansser, Oliver Alexander & Reich, Christina Stefanie, 2021. "A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application," Technology in Society, Elsevier, vol. 65(C).
    21. Saboo, Alok R. & Kumar, V. & Ramani, Girish, 2016. "Evaluating the impact of social media activities on human brand sales," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 524-541.
    22. Meuter, Matthew L. & Ostrom, Amy L. & Bitner, Mary Jo & Roundtree, Robert, 2003. "The influence of technology anxiety on consumer use and experiences with self-service technologies," Journal of Business Research, Elsevier, vol. 56(11), pages 899-906, November.
    23. Grewal, Dhruv & Guha, Abhijit & Satornino, Cinthia B. & Schweiger, Elisa B., 2021. "Artificial intelligence: The light and the darkness," Journal of Business Research, Elsevier, vol. 136(C), pages 229-236.
    24. Naik, Prasad A. & Peters, Kay, 2009. "A Hierarchical Marketing Communications Model of Online and Offline Media Synergies," Journal of Interactive Marketing, Elsevier, vol. 23(4), pages 288-299.
    25. Sheehan, Ben & Jin, Hyun Seung & Gottlieb, Udo, 2020. "Customer service chatbots: Anthropomorphism and adoption," Journal of Business Research, Elsevier, vol. 115(C), pages 14-24.
    26. Verhoef, Peter C. & Lemon, Katherine N. & Parasuraman, A. & Roggeveen, Anne & Tsiros, Michael & Schlesinger, Leonard A., 2009. "Customer Experience Creation: Determinants, Dynamics and Management Strategies," Journal of Retailing, Elsevier, vol. 85(1), pages 31-41.
    27. Xinshu Zhao & John G. Lynch & Qimei Chen, 2010. "Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(2), pages 197-206, August.
    28. Pankaj Aggarwal & Ann L. McGill, 2007. "Is That Car Smiling at Me? Schema Congruity as a Basis for Evaluating Anthropomorphized Products," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 468-479, June.
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