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Drawing on the integrative perspective of the technology acceptance model (TAM) and theory of planned behaviour (TPB) and extending it further by examining the role of organisational facilitators and perceived HR effectiveness in this integrative perspective, we examine HR professionals’ AI-augmented HRM (HRM^(AI)) acceptance in this research.

The data (N=375) were collected from HR professionals working in different organisations in India. Structural equation modelling (SEM) was employed to analyse the data.

The results of the study suggest that along with organisational facilitator antecedents to the relevant components of both TAM and TPB, perceived HR effectiveness also enhanced the HRM^(AI) acceptance levels of HR professionals.

The research findings are expected to contribute to the understanding of the factors that influence the acceptance of AI-augmented HRM in organizations. The results may also help organisations to identify the facilitators that can enhance the adoption and implementation of AI-augmented HRM by HR professionals. Finally, the study provides a composite TAM-TPB theoretical framework that can guide future research on the acceptance of AI-augmented HRM.

To the best of our knowledge, this is one of the first attempts to factor in the effect of contextual factors (i.e. organisational facilitators and perceived HR effectiveness) in the TAM and TPB equations.

The relationship between perceived overqualification and knowledge sharing has always been a hot topic, but scholars have come to different conclusions on this issue. The purpose of this study is to integrate conflicting conclusions by considering the moderating role of rewards for knowledge sharing and the mediating role of intrinsic motivation in the relationship between perceived overqualification and knowledge sharing based on self-determination theory.

The authors collected three-wave survey data from 246 research and development employees in four companies in China.

The results showed that when rewards for knowledge sharing was higher, employees with perceived overqualification would have higher intrinsic motivation, which could promote their knowledge-sharing behavior. However, when rewards for knowledge sharing was lower, employees with perceived overqualification would have lower intrinsic motivation, thus inhibiting their knowledge-sharing behavior. This result supported the informational function rather than the controlling function of rewards for knowledge sharing.

By considering the important boundary condition of rewards for knowledge sharing, this study reconciles the contradictory conclusions on the relationship between perceived overqualification and knowledge-sharing behavior. At the same time, the authors tell organizations that they can increase the knowledge-sharing behavior of overqualified employees through rewards for knowledge sharing.

Construction activities generate overwhelming waste that is typically disposed of in landfills, which has significant environmental consequences and hinders national progress. However, with the appropriate competencies, there is an opportunity to identify construction activities that produce recyclable materials, offering a path to a sustainable future. This study aims to assess the competencies for identifying construction activities that produce recyclable materials. To attain that aim, the study seeks to identify the key competencies and assess the index level of the competencies.

A systematic literature review was conducted, and 20 competencies were identified and categorized into knowledge, skills, and abilities. A questionnaire survey was developed based on the competencies and completed by 101 individuals. The collected data were analyzed using normalized mean analysis, confirmatory factor analysis, and fuzzy synthetic evaluation (FSE).

The results revealed that the key competencies are problem-solving skills, communication skills, skills in providing vocational training, and knowledge of the environmental impacts of construction activities. The FSE ranks the constructs in order of skills, knowledge, and abilities. Also, the FSE illustrated that the overall index level is inclined to be important.

This study leads to saving natural resources, using raw materials efficiently, protecting from environmental pollution, and mitigating resource depletion by providing the index level of the competencies.

The findings can guide professionals in effective waste management, policymakers in creating new policies and regulations, and researchers in compiling a list of competencies for identifying construction activities that produce recyclable materials.