Framework for adoption of generative AI for information search of retail products and services DOI
Astha Sanjeev Gupta, Jaydeep Mukherjee

International Journal of Retail & Distribution Management, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 5, 2024

Purpose Generative artificial intelligence (GAI) can disrupt how consumers search for information on retail products/services online by reducing overload. However, the risk associated with GAI is high, and its widespread adoption product/service purposes uncertain. This study examined psychological drivers that impact consumer of platforms search. Design/methodology/approach We conducted 31 in-depth, semi-structured interviews lead users regarding The data were analysed using a grounded theory paradigm thematic analysis. Findings Results show experience uncertainty about GAI’s functioning. Their trust in impacts usage this technology provides unique settings to investigate potential additional factors, leveraging UTAUT as theoretical basis. identified three overarching themes – characteristics, readiness characteristics possible adoption. Originality/value Consumers seek exhaustive reliable purchase decisions. Due abundance information, they reduce overload providing synthesized customized results. reliability, trustworthiness accuracy have been questioned. functioning opaque; popular model such general unlikely explain totality GAI. Hence, research context. It identifies determinants/antecedents relevant variables develops an integrated conceptual explaining

Language: Английский

Braving digital retail frontier through artificial intelligence: rhetoric, reality, institutionalization DOI
Tharaka Liyanage,

Ishini Gunasekara,

Sasuni Sipnara

et al.

International Journal of Retail & Distribution Management, Journal Year: 2025, Volume and Issue: unknown

Published: March 5, 2025

Purpose This study explores how artificial intelligence (AI) has been intertwined with rhetoric and the journey of institutionalization in selected case firms. The mechanism institutionalizing AI into organizational processes, future technology transformation driving forces behind implementation is being explored. Design/methodology/approach It adopts qualitative methodology multiple approach, drawing evidence from ten leading retail sector organizations that have practicing for over a decade. main data collection method was face-to-face in-depth interviews, supplemented by focus group discussion documentary reviews. From theoretical stance, paper draws on notions institutionalism. Findings Empirical findings revealed rhetorical power word convinces management firm to embrace AI. In contrast hype media, real application not lived up. Therefore, delves noticeable discrepancy between buzz surrounding its actual use sectors. Originality/value contributes research postulating even though carries prompt implementation, far excitements. Foregrounding institutionalism, it extends existing institutional theory-inspired research. also offers learning points practitioners illustrating rise fall story. further showcases tools techniques could be used business, gets implicated firm’s business excellence ensuing control ramifications.

Language: Английский

Citations

0

When humble AI meets narcissistic customers: A terror management perspective DOI

Jing Liu,

Fu‐Chieh Hsu,

Jing Yu

et al.

International Journal of Information Management, Journal Year: 2025, Volume and Issue: 83, P. 102904 - 102904

Published: March 31, 2025

Language: Английский

Citations

0

Navigating Uncertainty: Exploring Consumer Acceptance of Artificial Intelligence Under Self-Threats and High-Stakes Decisions DOI Creative Commons
Darius‐Aurel Frank, Polymeros Chrysochou,

Panagiotis Mitkidis

et al.

Technology in Society, Journal Year: 2024, Volume and Issue: unknown, P. 102732 - 102732

Published: Oct. 1, 2024

Language: Английский

Citations

3

Framework for adoption of generative AI for information search of retail products and services DOI
Astha Sanjeev Gupta, Jaydeep Mukherjee

International Journal of Retail & Distribution Management, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 5, 2024

Purpose Generative artificial intelligence (GAI) can disrupt how consumers search for information on retail products/services online by reducing overload. However, the risk associated with GAI is high, and its widespread adoption product/service purposes uncertain. This study examined psychological drivers that impact consumer of platforms search. Design/methodology/approach We conducted 31 in-depth, semi-structured interviews lead users regarding The data were analysed using a grounded theory paradigm thematic analysis. Findings Results show experience uncertainty about GAI’s functioning. Their trust in impacts usage this technology provides unique settings to investigate potential additional factors, leveraging UTAUT as theoretical basis. identified three overarching themes – characteristics, readiness characteristics possible adoption. Originality/value Consumers seek exhaustive reliable purchase decisions. Due abundance information, they reduce overload providing synthesized customized results. reliability, trustworthiness accuracy have been questioned. functioning opaque; popular model such general unlikely explain totality GAI. Hence, research context. It identifies determinants/antecedents relevant variables develops an integrated conceptual explaining

Language: Английский

Citations

2