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

Yousif Elsamani, Cristian Mejia and Yuya Kajikawa

PLOS ONE, 2023, vol. 18, issue 1, 1-38

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.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0280005 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 80005&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0280005

DOI: 10.1371/journal.pone.0280005

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().