Xueyan Dong, Yuxin Tian, Mingming He and Tienan Wang
The purpose of this study was to investigate the impact of artificial intelligence (AI) adoption on knowledge workers' innovative work behaviors (IWB), as well as the mediating…
Abstract
Purpose
The purpose of this study was to investigate the impact of artificial intelligence (AI) adoption on knowledge workers' innovative work behaviors (IWB), as well as the mediating role of stress appraisal and the moderating role of individual learning abilities.
Design/methodology/approach
This study analyzed the questionnaire results of 313 knowledge workers, and data analysis was conducted by using SPSS 25.0, SPSS 25.0 macro-PROCESS and AMOS 28.0.
Findings
This study found that AI adoption has a double-edged sword effect on knowledge workers' IWB. Specifically, AI adoption can promote IWB by enhancing knowledge workers' challenging stress appraisal, while inhibiting IWB by fostering their hindering stress appraisal. Moreover, individual learning ability significantly moderated the relationship between AI adoption and stress appraisal, which further influenced IWB.
Originality/value
This study integrates the conflicting findings of previous studies and proposes a comprehensive theoretical model based on the theory of cognitive appraisal of stress. This study enriches the research on AI in the field of knowledge management, especially extending the understanding of the relationship between AI adoption and knowledge workers’ IWB by unraveling the psychological mechanisms and behavior outcomes of users' technology usage. Additionally, we provide new insights and suggestions for organizations to seek the cooperation and support of employees in introducing new technologies or driving intelligent transformation.
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Hongjie Lin, Faqun Qi, Yuxin Liu, Xiang Chen and Wenfei Zha
This paper aims to develop an optimal maintenance and spare parts policy for an urban micro wind power system, focusing on two urban micro wind farms (UMWF). The reliability and…
Abstract
Purpose
This paper aims to develop an optimal maintenance and spare parts policy for an urban micro wind power system, focusing on two urban micro wind farms (UMWF). The reliability and efficiency of these systems are sought to be enhanced by considering the relationship between urban wind parameters and wind turbine degradation.
Design/methodology/approach
A proportional hazards (PH) model is utilized to describe how urban wind conditions impact turbine degradation. The maintenance strategy includes preventive maintenance (PM), corrective maintenance (CM) and opportunistic maintenance (OM). A multi-objective optimization algorithm is developed to optimize the joint policy of OM plans and spare parts resource allocation.
Findings
The proposed maintenance and spare parts policy effectively balances the trade-offs between PM, CM and OM strategies. Numerical experiments demonstrate that the policy improves the reliability of UMWF, reducing downtime and maintenance costs while ensuring the availability of spare parts when needed. The results show a significant enhancement in system performance compared to traditional maintenance approaches.
Originality/value
A novel maintenance policy and spare parts management approach for urban micro wind power systems is proposed. A multi-objective optimization algorithm is developed to optimize the OM schedule and maintenance spare parts resource management strategy for wind farms in urban wind environments.
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Jiangjun Wan, Yuxin Zhao, Miaojie Chen, Xi Zhu, Qingyu Lu, Yuwei Huang, Yutong Zhao, Chengyan Zhang, Wei Zhu and Jinxiu Yang
The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are…
Abstract
Purpose
The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are still unclear. This study aims to gain a more comprehensive insight into the current development status of the regional construction industry under China's HQD orientation and the obstructive factors affecting its development and to provide informative suggestions for its HQD prospects.
Design/methodology/approach
In this study, the construction industry of 16 cities in the Chengdu-Chongqing economic circle (CCEC), a new region in southwest China, was used as the research object to collect data from the 2006–2019 yearbooks, construct an evaluation index system for HQD of the construction industry, derive the development level of the construction industry using the entropy value method and spatial autocorrelation method and then apply the barrier Diagnostic model was used to compare and analyze the impact level of each index.
Findings
In terms of the time dimension, the development of the construction industry in CCEC is characterized by “high in the twin core and low in the surrounding area”, with unbalanced and insufficient development; in terms of spatial correlation, some factors have positive aggregation in spatial distribution, but the peripheral linkage decreases; through barrier analysis, the impact of different barrier factors is different.
Originality/value
This paper will help governments and enterprises in developing countries to make urban planning and management policies to fundamentally improve the development of the construction industry in underdeveloped regions.