How big data-driven organizational capabilities shape innovation performance? An empirical study from small and medium manufacturing enterprises

Author:

Al-Khatib Ayman WaelORCID

Abstract

PurposeThis study mainly aims to explore the causal nexus between big data-driven organizational capabilities (BDDOC) and supply chain innovation capabilities (SCIC) and innovation performance (IP), then explore the indirect effect of SCIC and also test the moderating effects for both internal supply chain integration (ISCI) and external supply chain integration (ESCI) into the relationship between BDDOC and SCIC.Design/methodology/approachIn order to test the conceptual model and the hypothesized relationships between all the constructs, the data were collected using a self-reported questionnaire by workers in Jordanian small and medium manufacturing enterprises. Partial least squares-structural equation modeling (PLS-SEM) was employed to test the model.FindingsThe paper reached a set of interesting results where it was confirmed that there is a positive and statistically significant relationship between BDDOC, SCIC and IP in addition to confirming the indirect effect of SCIC between BDDOC and IP. The results also showed that there is a moderating role for both ESCI and ISCI.Originality/valueThis study can be considered the first study in the current literature that investigates these constructs as shown in the research model. Therefore, the paper presents an interesting set of theoretical and managerial contributions that may contribute to covering part of the research gap in the literature.

Publisher

Emerald

Subject

Computer Science (miscellaneous),Social Sciences (miscellaneous),Theoretical Computer Science,Control and Systems Engineering,Engineering (miscellaneous)

Reference132 articles.

1. Influencing models and determinants in big data analytics research: a bibliometric analysis;Information Processing and Management,2020

2. Examining the relationship between dimensions of supply chain integration, operational performance and firm performance: evidence from Ghana;Management Research Review,2022

3. The role of big data analytics and decision-making in achieving project success;Journal of Engineering and Technology Management,2022

4. Evaluation of data analytics-oriented business intelligence technology effectiveness: an enterprise-level analysis;Business Process Management Journal,2023

5. Reshaping competitive advantages with analytics capabilities in service systems;Technological Forecasting and Social Change,2020

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