Internet of things, big data analytics and operational performance: the mediating effect of supply chain visibility

Abstract

Purpose

This paper aims to investigate hypothesized relationships between the Internet of things (IoT) and big data analytics (BDA) with supply chain visibility (SCV) and operational performance (OP) in the pharmaceutical manufacturing sector in Jordan. The paper also aims to test the conceptual model related to the indirect effects of SCV.

Design/methodology/approach

To achieve the objectives of this paper, a conceptual model was developed through a review of the current literature. Data analysis was performed by covariance-based structural equation modelling using Amos 25 software, and the convergent validity, discriminant validity, reliability and confirmatory factor analysis were verified. Then the hypotheses were tested.

Findings

The results of the study indicate that there is a positive and statistically significant relationship between the IoT and BDA on SCV and OP. The relationship was positive and statistically significant between SCV and OP. In addition, support for the mediation hypothesis that SCV mediates the relationship among IoT, BDA and OP was confirmed.

Originality/value

This paper provides new theoretical and managerial contributions that have not been covered in previous studies, and it is considered the first study that uses this conceptual model with this mechanism in terms of the theoretical lens and empirical application. This paper contributes to understanding the dynamic mechanisms of the IoT and BDA in enhancing OP, which contributes to creating a supply chain capable of facing various environmental fluctuations and pressures. This study presents new implications that can be used in the supply chain literature.

Citation

Al-Khatib, A.W. (2023), "Internet of things, big data analytics and operational performance: the mediating effect of supply chain visibility", Journal of Manufacturing Technology Management, Vol. 34 No. 1, pp. 1-24. https://doi.org/10.1108/JMTM-08-2022-0310