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Employee well-being and innovativeness: A multi-level conceptual framework based on citation network analysis and data mining techniques

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  • Yousif Elsamani
  • Cristian Mejia
  • Yuya Kajikawa

Abstract

This study proposes a multilevel conceptual framework for a deeper understanding of the relationship between employee well-being and innovativeness. We overview 49 years of well-being research [1972–2021] and 54 years of research on innovativeness [1967–2021] to uncover 24 dominant themes in well-being and ten primary topics in innovativeness research. Citation network analysis and text semantic similarity were used to develop a conceptual framework featuring 21 components and three levels: individual, organizational, and market. These components consist of constructs, domains, and factors that can influence or be influenced by employee well-being and innovativeness either directly or indirectly. This is the first study to use citation network analysis and data mining techniques to investigate the relationship between employee well-being and innovativeness. This novel framework can aid organizations in identifying more holistic and efficient strategies for fostering innovativeness and enhancing the well-being of their workforce. It can also assist in developing new theories and serve as a roadmap for future research. We discuss the research limitations and theoretical and practical implications and propose three research themes that future studies may address.

Suggested Citation

  • Yousif Elsamani & Cristian Mejia & Yuya Kajikawa, 2023. "Employee well-being and innovativeness: A multi-level conceptual framework based on citation network analysis and data mining techniques," PLOS ONE, Public Library of Science, vol. 18(1), pages 1-38, January.
    • Handle: RePEc:plo:pone00:0280005
    DOI: 10.1371/journal.pone.0280005
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