Why Should Users Take the Risk of Sustainable Use of Generative Artificial Intelligence Chatbots DOI Open Access
Serge-Lopez Wamba-Taguimdje, Samuel Fosso Wamba, Hossana Twinomurinzi

et al.

Journal of Global Information Management, Journal Year: 2024, Volume and Issue: 32(1), P. 1 - 32

Published: Dec. 28, 2024

Despite the risks associated with generative AI (GenAI) chatbots, people increasingly use these technologies, which may seem contradictory. This study identified and explored factors related to trust, perceived values, satisfaction, sustainable of GenAI chatbots. Relying on IS theories build a stimulus-organism-response model, authors tested model using PLS-SEM data from 393 ChatGPT users. The results show that user competence autonomy dramatically increase user's trust in ChatGPT, improves hedonic value (HV), utilitarian (UV), value-in-use, task-technology fit (TTF), information accuracy, knowledge acquisition, informativeness, satisfaction. In addition satisfaction depends HV, UV, TTF. sustainability HV However, privacy concerns, risks, awareness do not affect consumer trust. There is complete mediation between sustainability, as well sustainability.

Language: Английский

Identifying Key Nodes and Enhancing Resilience in Grain Supply Chains Under Drought Conditions DOI Creative Commons
Shuiwang Zhang, Zhou Chuan-sheng

Systems, Journal Year: 2025, Volume and Issue: 13(1), P. 49 - 49

Published: Jan. 14, 2025

Grain supply chains remain stable in the face of natural disasters, and resilience grain chain plays an important role. In a complex scenario exposure to shocks, it is significant identify critical nodes propose countermeasures accordingly enhance chain. this paper’s study, firstly, triangular model contradictory events used describe scenarios obtain Bayesian network nodes. Secondly, fragmentation based on description scene, scene stream constructed, event obtained, structure built basis. Then, combining expert knowledge D–S evidence theory, parameters are determined, built. Finally, key identified context 2022 drought data Yangtze River Basin China, and, accordingly, strategy for improving proposed stages. This study provides new research perspective issues related supply-chain enriches theoretical foundation resilience.

Language: Английский

Citations

0
The mechanism of human-machine collaboration driving sustainable business models: A single case study from the electric vehicle industry DOI
Yanying Shang, Junfeng Jiang, Ruochen Zhang

et al.

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 145152 - 145152

Published: Feb. 1, 2025

Language: Английский

Citations

0
Generative AI capabilities for green supply chain management improvement: extended dynamic capabilities view DOI
Taufik Kurrahman,

Feng Ming Tsai,

Ming K. Lim

et al.

International Journal of Logistics Research and Applications, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 28

Published: March 17, 2025

Language: Английский

Citations

0
The transformative power of generative AI for supply chain management: Theoretical framework and agenda DOI
Huamin Wu, Guo Li, Dmitry Ivanov

et al.

Frontiers of Engineering Management, Journal Year: 2025, Volume and Issue: unknown

Published: March 29, 2025

Language: Английский

Citations

0
Revolutionizing Supply Chain Forecasting With Generative AI and Machine Learning DOI
James Kanyepe,

Rudolph L. Boy,

Munyaradzi Chibaro

et al.

Advances in business strategy and competitive advantage book series, Journal Year: 2025, Volume and Issue: unknown, P. 435 - 462

Published: Jan. 23, 2025

This chapter examines the paradigm shift in supply chain forecasting brought about by generative AI and machine learning technologies. Through real-world examples case studies, proposed explores how these technologies enhance forecast accuracy, streamline operations, drive cost efficiency. The study employed systematic analysis of literature, drawing upon prominent academic databases such as Google Scholar, Scopus, Web Science, IEEE Xplore. Academic publications, reports, related materials were obtained via comprehensive keyword searches to serve primary sources data, with a focus on English-language literature ensure consistency accessibility. synthesis data extracted from selected this provides structured overview discussing implications for theory, practice, future research forecasting.

Language: Английский

Citations

0
Why Should Users Take the Risk of Sustainable Use of Generative Artificial Intelligence Chatbots DOI Open Access
Serge-Lopez Wamba-Taguimdje, Samuel Fosso Wamba, Hossana Twinomurinzi

et al.

Journal of Global Information Management, Journal Year: 2024, Volume and Issue: 32(1), P. 1 - 32

Published: Dec. 28, 2024

Despite the risks associated with generative AI (GenAI) chatbots, people increasingly use these technologies, which may seem contradictory. This study identified and explored factors related to trust, perceived values, satisfaction, sustainable of GenAI chatbots. Relying on IS theories build a stimulus-organism-response model, authors tested model using PLS-SEM data from 393 ChatGPT users. The results show that user competence autonomy dramatically increase user's trust in ChatGPT, improves hedonic value (HV), utilitarian (UV), value-in-use, task-technology fit (TTF), information accuracy, knowledge acquisition, informativeness, satisfaction. In addition satisfaction depends HV, UV, TTF. sustainability HV However, privacy concerns, risks, awareness do not affect consumer trust. There is complete mediation between sustainability, as well sustainability.

Language: Английский

Citations

0