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Relationships Among Knowledge Management, Organisational Innovativeness and Performance: Covariance-Based Versus Partial Least-Squares Structural Equation Modelling

Author

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  • José Roberto Frega

    (School of Business, Universidade Federal do Paraná (UFPR), CEP 80210-170, Jardim Botânico, Curitiba, PR, Brazil)

  • Alex Antonio Ferraresi

    (School of Business, Pontifícia Universidade Católica do Paraná (PUCPR), CEP 80215-901, Prado Velho, Curitiba, PR, Brazil)

  • Carlos Olavo Quandt

    (School of Business, Pontifícia Universidade Católica do Paraná (PUCPR), CEP 80215-901, Prado Velho, Curitiba, PR, Brazil)

  • Claudimar Pereira da Veiga

    (School of Business, Universidade Federal do Paraná (UFPR), CEP 80210-170, Jardim Botânico, Curitiba, PR, Brazil)

Abstract

The relationships among effective knowledge management (KM), organisational innovativeness (OI), market orientation (MO) and organisational performance (OP) have been explored in the literature. These constructs are generally analysed in pairs, such as the influence of KM on OI, or KM on OP, and other combinations, but the relationships among the full set of constructs in question are not fully understood yet. In the extant literature, the relationships among them are analysed for the most part with covariance-based structural equation modelling (CB-SEM). Partial least-squares (PLS) path modelling is a component-based approach to SEM that is not as widely used as CB-SEM, but it has the potential to allow increased flexibility in handling various modelling problems in comparison with CB models, particularly for predictive and exploratory purposes. This paper aims to verify whether the PLS method could confirm or reject the results of the more restrictive covariance-based method in modelling the relationships among KM, OI, MO and OP. The results indicate that both methods yielded convergent and discriminant validity for the constructs, displaying stability across model analysis and depuration. The PLS model revealed the influence of KM on MO, OI and OP. It also shows that OI is the main driving factor for OP. KM seems to have a direct effect on OP, which is greatly magnified when mediated by OI. The sample size, although borderline adequate for the CB method, was more than adequate for PLS, yielding excellent model stability.

Suggested Citation

  • José Roberto Frega & Alex Antonio Ferraresi & Carlos Olavo Quandt & Claudimar Pereira da Veiga, 2018. "Relationships Among Knowledge Management, Organisational Innovativeness and Performance: Covariance-Based Versus Partial Least-Squares Structural Equation Modelling," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-19, March.
    • Handle: RePEc:wsi:jikmxx:v:17:y:2018:i:01:n:s0219649218500089
    DOI: 10.1142/S0219649218500089
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    References listed on IDEAS

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    Cited by:

    1. Carlos Alano Soares de Almeida & Jansen Maia Del Corso & Leonardo Andrade Rocha & Wesley Vieira da Silva & Claudimar Pereira da Veiga, 2019. "Innovation and Performance: The Impact of Investments in R&D According to the Different Levels of Productivity of Firms," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1-21, August.
    2. Babak Sohrabi & Iman Raeesi Vanani & Seyed Mohammad Jafar Jalali & Ehsan Abedin, 2020. "Evaluation of Research Trends in Knowledge Management: A Hybrid Analysis through Burst Detection and Text Clustering," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1-27, January.

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