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Impact of business analytics and π-shaped skills on innovative performance: Findings from PLS-SEM and fsQCA

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  • Hayajneh, Jamal Abdelrahman .M.
  • Elayan, Malek Bakheet Haroun
  • Abdellatif, Mamdouh Abdallah Mohamed
  • Abubakar, A. Mohammed

Abstract

This paper proposes that the relationship between business analytics and innovative performance is somewhat more complex than originally thought, as firms still struggle to leverage the benefits of business analytics and artificial intelligence capabilities. To expand on the scholarship in this area of knowledge, our paper cross-fertilizes the literature by amalgamating business analytics capabilities with π-shaped skills. We draw on resource orchestration theory to examine the effects of business analytics and π-shaped skills on a firm's innovative performance, and the moderating role of π-shaped skills. Field data (n = 450) were obtained from individuals with supervisory positions in large Saudi firms and SMEs and analyzed with PLS-SEM and fsQCA techniques. PLS-SEM results reveal that business analytics and π-shaped skills are relevant antecedents for innovative performance. However, the expected moderating role of π-shaped skills on the relationship between business analytics and innovative performance did not hold. FsQCA results reveal that business analytics and π-shaped skills are sufficient but not necessary conditions for high innovative performance. This paper contributes not only to empirical evidence, but also to theory by furthering our understanding of the emergent π-shaped skills concept. Our findings echo the need to expand inquiry into business analytics and skill sets capabilities for better innovative outputs. Implications for theory and practice are discussed.

Suggested Citation

  • Hayajneh, Jamal Abdelrahman .M. & Elayan, Malek Bakheet Haroun & Abdellatif, Mamdouh Abdallah Mohamed & Abubakar, A. Mohammed, 2022. "Impact of business analytics and π-shaped skills on innovative performance: Findings from PLS-SEM and fsQCA," Technology in Society, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:teinso:v:68:y:2022:i:c:s0160791x22000550
    DOI: 10.1016/j.techsoc.2022.101914
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