Robinson, Stacey, Orsingher, Chiara, Alkire, Linda, De Keyser, Arne, Giebelhausen, Michael, Papamichail, K. Nadia, Shams, Poja, Temerak, M.S. (2020) Frontline encounters of the AI kind: An evolved service encounter framework. Journal of Business Research, 116 . pp. 366-376. ISSN 0148-2963. (doi:10.1016/j.jbusres.2019.08.038) (KAR id:77834)
PDF
Author's Accepted Manuscript
Language: English
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
|
|
Download this file (PDF/831kB) |
Preview |
Request a format suitable for use with assistive technology e.g. a screenreader | |
Official URL: https://doi.org/10.1016/j.jbusres.2019.08.038 |
Abstract
Artificial intelligence (AI) is radically transforming frontline service encounters, with AI increasingly playing the role of employee or customer. Programmed to speak or write like a human, AI is poised to usher in a frontline service revolution. No longer will frontline encounters between customer and employee be simply human-to-human; rather, researchers must consider an evolved paradigm where each actor could be either human or AI. Further complicating this 2 × 2 framework is whether the human, either customer or employee, recognizes when they are interacting with a non-human exchange partner. Accordingly, we develop an evolved service encounter framework and, in doing so, introduce the concept of counterfeit service, interspecific service (AI-to-human), interAI service (AI-to-AI), and offer a research agenda focused on the implementation of AI in dyadic service exchanges.
Item Type: | Article |
---|---|
DOI/Identification number: | 10.1016/j.jbusres.2019.08.038 |
Uncontrolled keywords: | Service encounter, Artificial intelligence (AI), Technology Customer, experience, Frontline employee, Counterfeit |
Divisions: | Divisions > Kent Business School - Division > Department of Marketing, Entrepreneurship and International Business |
Depositing User: | Mohamed Temerak |
Date Deposited: | 25 Oct 2019 15:09 UTC |
Last Modified: | 05 Nov 2024 12:42 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/77834 (The current URI for this page, for reference purposes) |
- Link to SensusAccess
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):