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Capabilities Pathway To Firm Performance: Moderating Role Of Environmental Dynamism In The Food Manufacturing Firms Of Pakistan

Author

Listed:
  • SHEHLA NAZ

    (Department of Business and Management Sciences, Superior College Lahore, Pakistan)

  • NAVEED UL HAQ

    (��Office of Research Innovation and Commercialization, Lahore, Pakistan)

  • SOBIA NASIR

    (��Department of Business and Management Sciences, Superior College, Lahore, Pakistan)

Abstract

This study examines the significant influence of entrepreneurial orientation (EO), big data analytics capabilities (BDACs), and artificial intelligence capabilities (AICs) on the firm performance (FP) of manufacturing industries of Pakistan using environmental dynamism (ED) as a moderator. For this purpose, we developed a model based on the dynamic capabilities (DCs) view of enterprises and contingency theory (CT) that describes EO’s role in adopting big data analytics, artificial intelligence, and FP. The data of 240 respondents were collected and analysed using SPSS and Smart PLS software from the survey of Pakistani food manufacturing firms. The results of our study extend the DC perspective and CT to provide a clearer understanding of the organisation’s DCs while also giving managers theoretically supported counsel on matching their EO with their firms’ technology capabilities. The findings discovered that EO, big data analytics, and AICs were positively related to FP. Moreover, it illustrates that ED does not moderate the relationship between BDACs, AICs and FP. The findings of this study have important implications for the manufacturing industry in terms of improving an effective method and organisation performance through EO.

Suggested Citation

  • Shehla Naz & Naveed Ul Haq & Sobia Nasir, 2022. "Capabilities Pathway To Firm Performance: Moderating Role Of Environmental Dynamism In The Food Manufacturing Firms Of Pakistan," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 26(04), pages 1-31, May.
    • Handle: RePEc:wsi:ijimxx:v:26:y:2022:i:04:n:s136391962250030x
    DOI: 10.1142/S136391962250030X
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