Consumer reactions to chatbot versus human service: An investigation in the role of outcome valence and perceived empathy DOI
Dmitri G. Markovitch, Rusty A. Stough, Dongling Huang

et al.

Journal of Retailing and Consumer Services, Journal Year: 2024, Volume and Issue: 79, P. 103847 - 103847

Published: April 9, 2024

Language: Английский

Chatbots in e-commerce: The effect of chatbot language style on customers’ continuance usage intention and attitude toward brand DOI

Meichan Li,

Rui Wang

Journal of Retailing and Consumer Services, Journal Year: 2022, Volume and Issue: 71, P. 103209 - 103209

Published: Nov. 25, 2022

Language: Английский

Citations

116

What (de) motivates customers to use AI-powered conversational agents for shopping? The extended behavioral reasoning perspective DOI Creative Commons
Ihsan Ullah Jan, Seong-Goo Ji, Changju Kim

et al.

Journal of Retailing and Consumer Services, Journal Year: 2023, Volume and Issue: 75, P. 103440 - 103440

Published: June 16, 2023

Artificial Intelligence (AI)-powered conversational agents have become ubiquitous tools in the digital transformation of conventional customer-company interactions. Despite widespread implementation agents, there is still a limited understanding how customers use and resist these technologies for shopping. To address this gap, study investigates factors that influence usage resistance AI-based shopping using extended behavioral reasoning theory (BRT) partial least squares-based structural equation modeling (PLS-SEM). test proposed framework, conducted two empirical studies South Korea. Study 1 focused on text-based chatbots with sample 232 participants, while 2 examined voice-based 234 participants. The results both mainly supported hypotheses driven by BRT. Theoretically, contributes offering comprehensive customer motivation, attitudes, intentions toward AI-powered Managerially, provides important insights retail managers developers By drive resistance, managers, can better design deploy innovative to enhance experience improve business outcomes.

Language: Английский

Citations

89

Emotional expression by artificial intelligence chatbots to improve customer satisfaction: Underlying mechanism and boundary conditions DOI Open Access
Junbo Zhang, Qi Chen,

Jiandong Lu

et al.

Tourism Management, Journal Year: 2023, Volume and Issue: 100, P. 104835 - 104835

Published: Sept. 11, 2023

Language: Английский

Citations

79

I Am ChatGPT, the ultimate AI Chatbot! Investigating the determinants of users' loyalty and ethical usage concerns of ChatGPT DOI
Ben Niu, Gustave Florentin Nkoulou Mvondo

Journal of Retailing and Consumer Services, Journal Year: 2023, Volume and Issue: 76, P. 103562 - 103562

Published: Sept. 22, 2023

Language: Английский

Citations

74

Decisions with ChatGPT: Reexamining choice overload in ChatGPT recommendations DOI Creative Commons
Jungkeun Kim, Jeong Hyun Kim, Changju Kim

et al.

Journal of Retailing and Consumer Services, Journal Year: 2023, Volume and Issue: 75, P. 103494 - 103494

Published: July 13, 2023

This research examines how individuals respond differently to recommendation options generated by ChatGPT, an AI-powered language model, in five studies. In contrast previous on choice overload, Studies 1 and 2 demonstrate that people tend positively a large number of (60 options), revealing diverse consumer perceptions AI-generated recommendations. 3 4 further illustrate the moderating effect agents indicate overload elicits distinct patterns reactions depending whether recommendations are from human or AI agent. Lastly, Study 5 directly measures preferences for agents, general preference particularly when available. These findings have significant implications system design user regarding

Language: Английский

Citations

72

What drives tourists’ continuance intention to use ChatGPT for travel services? A stimulus-organism-response perspective DOI

Hong Chuong Pham,

Cong Doanh Duong,

Giang Khanh Huyen Nguyen

et al.

Journal of Retailing and Consumer Services, Journal Year: 2024, Volume and Issue: 78, P. 103758 - 103758

Published: Feb. 9, 2024

Language: Английский

Citations

62

Chatbots’ effectiveness in service recovery DOI Creative Commons

Arpita Agnihotri,

Saurabh Bhattacharya

International Journal of Information Management, Journal Year: 2023, Volume and Issue: 76, P. 102679 - 102679

Published: July 11, 2023

Leveraging the computers are social actors theory, in this study, we explore traits of artificial intelligence-based chatbots that make them perceived as trustworthy, drive consumers to forgive firm for service failure, and reduce their propensity spread negative word-of-mouth against firm. Across two scenario-based studies with UK consumers: one a utilitarian product category (n = 586) another hedonic 508), qualitative our findings suggest safety enhances consumers' ability empathy, anthropomorphism benevolence integrity chatbots, i.e., three affect components trustworthiness differently. Further, these have positive influence on customer forgiveness word-of-mouth.

Language: Английский

Citations

45

Understanding the relationship between marketing analytics, customer agility, and customer satisfaction: A longitudinal perspective. DOI Creative Commons
Gomaa Agag, Yasser Moustafa Shehawy, Ahmed Almoraish

et al.

Journal of Retailing and Consumer Services, Journal Year: 2023, Volume and Issue: 77, P. 103663 - 103663

Published: Dec. 8, 2023

Shifting towards a more data-driven culture is key antecedent of business success in today's digital era. Previous research has paid attention to exploring the influence marketing analytics on performance, and rarely examined how use influences customer agility satisfaction. According dynamic capabilities view using previous studies, we developed conceptual framework explore effect In Study 1, utilised cross-sectional data collected from 468 managers various industries. study 2, employed longitudinal three-wave utilising cross-lagged panel model. 1 indicated that acquisition tool are drivers adopting analytics. Marketing stronger when market turbulence high. They also revealed satisfaction such conditions stronger. 2 at time point T1 significant positive T2, while T2 T3. These findings indicate strong temporal effects between use, agility, The suggest researchers should look beyond direct shift their can be leveraged enable support

Language: Английский

Citations

45

Dissecting the mixed effects of human-customer service chatbot interaction on customer satisfaction: An explanation from temporal and conversational cues DOI
Ying Xu,

Nan Niu,

Zixiang Zhao

et al.

Journal of Retailing and Consumer Services, Journal Year: 2023, Volume and Issue: 74, P. 103417 - 103417

Published: May 24, 2023

Language: Английский

Citations

42

How does AI technology integration affect employees’ proactive service behaviors? A transactional theory of stress perspective DOI
Yingying Huang, Doğan Gürsoy

Journal of Retailing and Consumer Services, Journal Year: 2024, Volume and Issue: 77, P. 103700 - 103700

Published: Jan. 4, 2024

Language: Английский

Citations

37