Managing artificial intelligence in international business: Toward a research agenda on sustainable production and consumption DOI Creative Commons
Rakibul Hasan, Arto Ojala

Thunderbird International Business Review, Год журнала: 2024, Номер 66(2), С. 151 - 170

Опубликована: Фев. 6, 2024

Abstract The collaboration between artificial intelligence (AI) and humans is reshaping international business (IB) management dynamics, aiming to achieve global sustainable development. Recent IB literature indicates that managing AI brings benefits such as better resource reconfiguration, reduced transaction costs, However, existing provides only meager knowledge about the characteristics of how these can be employed for expansion at intersection In response, our aim construct by employing directed qualitative content analysis empirical research. Based on three constructed AI, we contribute current providing a framework balance economic social goals utilizing Further, provide future research themes guide toward achieving production consumption agenda.

Язык: Английский

Ai-capable relationship marketing: Shaping the future of customer relationships DOI Creative Commons
Sanjit Kumar Roy, Ali N. Tehrani, Ameet Pandit

и другие.

Journal of Business Research, Год журнала: 2025, Номер 192, С. 115309 - 115309

Опубликована: Март 11, 2025

Язык: Английский

Процитировано

1

The impact of artificial intelligence on digital enterprise innovation DOI
Yu Fu,

Jiacheng Ni,

Meiqi Fang

и другие.

Опубликована: Март 18, 2025

Язык: Английский

Процитировано

1

AI‐Powered Sustainable Tourism: Unlocking Circular Economies and Overcoming Resistance to Change DOI Open Access

Hwang Bang‐Ning,

Siriprapha Jitanugoon, Pittinun Puntha

и другие.

Business Strategy and the Environment, Год журнала: 2025, Номер unknown

Опубликована: Март 28, 2025

ABSTRACT This study examines the integration of artificial intelligence (AI) with circular economy (CE) principles in Thailand's tourism industry. It explores interactions between AI‐Enhanced Predictive Waste Analytics (AI‐PWA), Regenerative Resource Integration (RRI), Dynamic Material Flow Optimization (DMFO), and AI‐Induced Resistance to Change (AIRC). Using a mixed‐methods approach, qualitative insights from industry stakeholders are combined quantitative analysis via Partial Least Squares Structural Equation Modeling (PLS‐SEM). Findings reveal that AI‐PWA improves real‐time resource management, driving DMFO supporting regenerative practices through RRI. However, AIRC moderates AI's effectiveness sustainability transitions, concerns such as job displacement, mistrust, complexity hindering adoption. provides actionable strategies mitigate resistance, enhance stakeholder collaboration, scale AI adoption resource‐constrained settings, contributing SDG 12 13. The findings offer practical for aligning innovations sustainable development high‐variability industries.

Язык: Английский

Процитировано

1

Sustainable servitization for cleaner and resource-wise production and consumption: Past, present, and future DOI
Rodrigo Rabetino, Marko Kohtamäki, Vinit Parida

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер 469, С. 143179 - 143179

Опубликована: Июль 17, 2024

Язык: Английский

Процитировано

8

Managing artificial intelligence in international business: Toward a research agenda on sustainable production and consumption DOI Creative Commons
Rakibul Hasan, Arto Ojala

Thunderbird International Business Review, Год журнала: 2024, Номер 66(2), С. 151 - 170

Опубликована: Фев. 6, 2024

Abstract The collaboration between artificial intelligence (AI) and humans is reshaping international business (IB) management dynamics, aiming to achieve global sustainable development. Recent IB literature indicates that managing AI brings benefits such as better resource reconfiguration, reduced transaction costs, However, existing provides only meager knowledge about the characteristics of how these can be employed for expansion at intersection In response, our aim construct by employing directed qualitative content analysis empirical research. Based on three constructed AI, we contribute current providing a framework balance economic social goals utilizing Further, provide future research themes guide toward achieving production consumption agenda.

Язык: Английский

Процитировано

7