In the context of globalization and rapid technological advancement, the introduction of Artificial Intelligence (AI) has brought new opportunities and challenges to Human Resource Management (HRM). This study constructs an evolutionary game model to explore the strategy choices and evolutionary paths of enterprises and employees in HRM value co-creation with AI involvement. We numerically simulated the dynamic evolution of strategies under different scenarios, revealing the equilibrium characteristics of strategic interactions between enterprises and employees in the AI context. The study finds that, first, the evolutionary game system between enterprises and employees converges to two equilibrium points: {cooperation, active} and {non-cooperation, passive}. Overall, the probability of the former is 2.39 times greater than that of the latter. Second, higher initial probabilities of cooperation and active involvement, along with lower costs for cooperation and active involvement, facilitate the system's evolution towards the {cooperation, active} equilibrium. Third, enterprises are more sensitive to the benefit distribution ratio than employees. This study provides theoretical support for effectively conducting HRM practices in the AI era through systematic analysis of HRM value co-creation behavior, along with practical policy recommendations.
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http://dx.doi.org/10.3390/bs14121220 | DOI Listing |
Behav Sci (Basel)
December 2024
School of Economics and Management, Tongji University, Shanghai 200092, China.
In the context of globalization and rapid technological advancement, the introduction of Artificial Intelligence (AI) has brought new opportunities and challenges to Human Resource Management (HRM). This study constructs an evolutionary game model to explore the strategy choices and evolutionary paths of enterprises and employees in HRM value co-creation with AI involvement. We numerically simulated the dynamic evolution of strategies under different scenarios, revealing the equilibrium characteristics of strategic interactions between enterprises and employees in the AI context.
View Article and Find Full Text PDFEClinicalMedicine
October 2024
Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Unity Health Toronto, Toronto, ON M5B 1W8, Canada.
Background: Use of health applications (apps) to support healthy lifestyles has intensified. Different app features may support effectiveness, including gamification defined as the use of game elements in a non-game situation. Whether health apps with gamification can impact behaviour change and cardiometabolic risk factors remains unknown.
View Article and Find Full Text PDFDairy farmers are grappling with serious business challenges, including rising operational costs, labour shortages, unstable milk prices, changing consumer preferences, long hours with minimal downtime and unstable weather patterns due to climate change impacts. Using a telephone-based representative survey and interviews with 147 Australian dairy farmers conducted in 2023, we employed a mixed-method approach combining quantitative and qualitative analysis to determine the challenges and primary concerns of the participants, as well as to explore potential solutions. Four key variables that contributed significantly to a binary logistic regression model of transition intentions were identified, namely: level of satisfaction with dairy farming, openness to exploring other agricultural alternatives to dairy farming, preference to receive financial and/or other support to remain in the industry and preference to receive financial and/or other support to transition into a different form of farming or business.
View Article and Find Full Text PDFLancet HIV
January 2025
Africa Health Research Institute, Durban, South Africa; HIV Pathogenesis Programme, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban, South Africa; Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA; University College London, London, UK.
This target product profile (TPP) highlights the minimal and optimal characteristics for ex-vivo and in-vivo cell and gene therapy-based products aimed at achieving an HIV cure (ie, durable antiretroviral-free viral control). The need for an effective, safe, scalable, affordable, accessible, and acceptable cure for HIV infection remains a major global priority. The possibilities for cell and gene therapy-based products for an HIV cure are rapidly expanding.
View Article and Find Full Text PDFLancet Respir Med
December 2024
Population Policy and Practice Department, UCL Great Ormond Street Institute of Child Health, University College London, London, UK; Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK. Electronic address:
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