Studies in systems, decision and control, Год журнала: 2024, Номер unknown, С. 199 - 217
Опубликована: Янв. 1, 2024
Язык: Английский
Technovation, Год журнала: 2024, Номер 135, С. 103063 - 103063
Опубликована: Июнь 25, 2024
Recently, Gen AI has garnered significant attention across various sectors of society, particularly capturing the interest small business due to its capacity allow them reassess their models with minimal investment. To understand how and medium-sized firms have utilised AI-based tools cope market's high level turbulence caused by COVID-19 pandemic, geopolitical crises, economic slowdown, researchers conducted an empirical study. Although is receiving more attention, there remains a dearth studies that investigate it influences entrepreneurial orientation ability cultivate resilience amidst market turbulence. Most literature offers anecdotal evidence. address this research gap, authors grounded theoretical model hypotheses in contingent view dynamic capability. They tested using cross-sectional data from pre-tested survey instrument, which yielded 87 useable responses medium enterprises France. The used variance-based structural equation modelling commercial WarpPLS 7.0 software test model. study's findings suggest EO influence on building as higher-order lower-order capabilities. However, negative moderating effect path joins resilience. results assumption will positive effects capabilities competitive advantage not always true, linear does hold, consistent some scholars' assumptions. offer contributions open new avenues require further investigation into non-linear relationship
Язык: Английский
Процитировано
26
Business Strategy and the Environment, Год журнала: 2025, Номер unknown
Опубликована: Фев. 11, 2025
ABSTRACT In the era of rapid technological advancement, generative artificial intelligence (AI) has emerged as a transformative force in various sectors, including environmental sustainability. This research investigates factors and consequences using AI to access information influence green purchasing behavior. It integrates theories such adoption model, value–belief–norm theory, elaboration likelihood cognitive dissonance theory pinpoint prioritize determinants usage for Data from 467 participants were analyzed hybrid methodology that blends partial least squares (PLS) with neural networks (ANN). The PLS outcomes indicate interactivity, responsiveness, knowledge acquisition application, concern, ascription responsibility are key predictors use information. Furthermore, concerns, values, personal norms, responsibility, individual impact, emerge ANN analysis offers unique perspective discloses variations hierarchy these predictors. provides valuable insights stakeholders on harnessing promote sustainable consumer behaviors
Язык: Английский
Процитировано
2
Transportation Research Part E Logistics and Transportation Review, Год журнала: 2024, Номер 189, С. 103689 - 103689
Опубликована: Июль 25, 2024
Язык: Английский
Процитировано
12
Journal of Systems and Information Technology, Год журнала: 2025, Номер unknown
Опубликована: Янв. 14, 2025
Purpose The purpose of this study is to investigate the primary determinants influencing acceptance generative artificial intelligence (GAI) adoption within Blockchain-enabled environments. Further research will examine impact GAI on supply chain efficiency (SCE) through enhancement Blockchain. Design/methodology/approach Drawing innovation diffusion theory (IDT), used partial least square structural equation modelling (PLS-SEM) look into hypotheses. data were gathered via online questionnaires from employers Chinese enterprises that have already integrated Findings findings demonstrate relative advantages (RAs), compatibility, trialability and observability a significant positive effect adoption, while complexity harms adoption. Above all, has significantly enhanced Blockchain, thus effectively improving SCE. Practical implications outcomes furnish organizations with valuable insights proficiently integrate Blockchain capability, optimize management bolster market competitiveness. Also, help accelerate successful integration business processes attain Sustainability Development Goals 9, industrial growth diversification. Originality/value To extent author’s knowledge, current status remains largely exploratory, there limited empirical evidence integrating capability GAI. This bridges knowledge gap by fully revealing optimal these two transformative technologies leverage their potential in management.
Язык: Английский
Процитировано
1
Asia-Pacific Journal of Business Administration, Год журнала: 2024, Номер unknown
Опубликована: Ноя. 25, 2024
Purpose In this research, we seek to understand the effects of artificial intelligence (AI) and knowledge management (KM) processes in enhancing proactive green innovation (PGI) within oil gas organizations. It also aims investigate moderator role trust sustainability these relationships. Design/methodology/approach This paper employs a quantitative analysis. Surveys have been gathered from middle-line managers twenty-four government organizations evaluate perceptions towards AI, KM processes, trust, measures toward innovation. Analytical statistical tools that were employed study, including structural equation modeling with SmartPLSv3.9, used analyze data examine measurement models study. Findings The study results reveal significant positive impact AI utilization, PGI Furthermore, turn out be viable moderators affecting, influencing strength direction particular, higher levels more substantial commitments enhance on outcomes. Practical implications Understanding KM, offers valuable insights for organizational leaders policymakers seeking promote industry. Thus, can increase efficiency sustainable product development, process improvement environmental by using robust technologies effective systems. fostering among stakeholders embedding principles into culture amplify effectiveness initiatives driving Originality/value extends current assessing effect while accounting as moderators. Utilizing methods nuanced understanding complex interactions between variables, thereby advancing theoretical fields management, behavior. Additionally, identification specific mechanisms contextual factors enriches practical practitioners striving dynamics complexities an AI-driven era.
Язык: Английский
Процитировано
6
Advanced Engineering Informatics, Год журнала: 2025, Номер 65, С. 103102 - 103102
Опубликована: Янв. 9, 2025
Язык: Английский
Процитировано
0
Procedia Computer Science, Год журнала: 2025, Номер 253, С. 2645 - 2654
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
International Journal of Logistics Research and Applications, Год журнала: 2025, Номер unknown, С. 1 - 28
Опубликована: Март 17, 2025
Язык: Английский
Процитировано
0
Tourism Management, Год журнала: 2025, Номер 110, С. 105179 - 105179
Опубликована: Март 31, 2025
Язык: Английский
Процитировано
0
Technology in Society, Год журнала: 2025, Номер unknown, С. 102898 - 102898
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
0