Predicting the Reward System of Knowledge Sharing in the Industrialized Engineering Sector Based on Regulatory Mechanisms

Boamah, Fredrick Ahenkora; Zhang, Jianhua; Danso, Nana Ama Asi; Alam, Sajjad; Naqvi, Khadija; Tariq, Maryam

doi:10.1007/s40996-023-01093-y

Iran J Sci Technol Trans Civ Eng

2023

DOI: 10.1007/s40996-023-01093-y

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Predicting the Reward System of Knowledge Sharing in the Industrialized Engineering Sector Based on Regulatory Mechanisms

Fredrick Ahenkora Boamah

Jianhua Zhang

Nana Ama Asi Danso

et al.

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2024

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Cited by 4 publications

References 49 publications

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Mechanism of green and knowledge process toward minimizing innovation risks: A direct and configuration approach

Alam,

Zhang,

Khan

et al. 2024

Bus Strat Env

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Due to a significant reduction in the availability and standard of natural resources, numerous firms are claiming to implement environmentally sustainable practices. This research constructs and validates green variables within the knowledge management (KM) process, drawing on resource‐based views (RBV) and organizational learning theory. It aims to explain how manufacturing firms minimize innovation risk. The author followed a combined methodology of Smart partial least squares structural equation modeling (PLS‐SEM) and fuzzy set qualitative comparative analysis (fsQCA). Primary response data were collected from industry experts and literature studies to develop items for the knowledge aptitude model to decrease innovation risk (KMIR). The mixed variables of the KM and green process were validated through the fsQCA technique. The outcome of PLS‐SEM showed a positive connection between certain green variables to minimize innovation risk. fsQCA examines the combined approach of green implementation and KM practice; the finding indicated significant connections between green variables and the KM process to KMIR. This study can be measured as innovative in the KMIR field, as it has validated and developed its constructs based on primary data. It can help scholars and industry experts acquire a head start in the KMIR field, and this mechanism will assist with the investigation of the green variables and knowledge domain, providing an outline for future studies.

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Mechanism of green and knowledge process toward minimizing innovation risks: A direct and configuration approach

Alam,

Zhang,

Khan

et al. 2024

Bus Strat Env

View full text Add to dashboard Cite

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Optimizing Sustainable Manufacturing: An Integrated Approach of Green Information’s Systems and Knowledge-Based Decisions in Industry 4.0: A Comparative Analysis

Wu,

Gao,

Alam

2024

Engineering Management Journal

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Factors of tacit knowledge acquisition and its mechanism of action on academic research performance: an empirical research from Chinese universities

Zhang,

Li,

Alam

et al. 2024

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PurposeThis study examines the relationship between higher education improvement and tacit knowledge importance. In this context, the scarcity of empirical and theoretical studies on acquiring tacit knowledge to enhance academic performance in higher education suggests that this research area holds significant importance for experts and policymakers. Consequently, this study aims to explore the factors that influence academic research performance at Chinese universities by acquiring tacit knowledge.Design/methodology/approachTo achieve the study aims, the current approach utilizes the research technique based on the socialization, externalization, internalization and combination (SECI) model and knowledge management (KM) theory. To analyze the study objective, the authors collected data from post-graduate students at Chinese universities and analyzed it using structural equation modeling (SEM) to test the model and hypotheses.FindingsThe results indicated that social interaction, internalization and self-motivation have a positive impact on academic research performance through the acquisition of tacit knowledge. Furthermore, the findings suggest that academic researchers can acquire more knowledge through social interaction than self-motivation, thereby advancing research progress.Originality/valueThis study addresses the critical issues surrounding the acquisition of tacit knowledge and presents a comprehensive framework and achievements that can contribute to achieving exceptional academic performance.

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Predicting the Reward System of Knowledge Sharing in the Industrialized Engineering Sector Based on Regulatory Mechanisms

Cited by 4 publications

References 49 publications

Mechanism of green and knowledge process toward minimizing innovation risks: A direct and configuration approach

Mechanism of green and knowledge process toward minimizing innovation risks: A direct and configuration approach

Optimizing Sustainable Manufacturing: An Integrated Approach of Green Information’s Systems and Knowledge-Based Decisions in Industry 4.0: A Comparative Analysis

Factors of tacit knowledge acquisition and its mechanism of action on academic research performance: an empirical research from Chinese universities

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