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An empirical assessment of technological advancements on supply chain management performance: a mixed-methods sem approach using smartpls

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Abstract

Supply chain management (SCM) is being transformed by the rapid proliferation of digital technologies that open up pathways to greater resilience and agility. This study examines the impact of new technologies, such as cloud computing, blockchain, Internet of Things (IoT), artificial intelligence (AI), and predictive analytics, on the performance of SCM in India. Using a mixed-methods research design, this study fills an important literature gap, as most previous studies have examined these technologies separately. The study used measurement, structural modeling, and importance and performance analysis (IPMA) to identify the primary elements that can enhance SCM outcomes. The results suggest that digital technology adoption (DTA), data integration (DI) and predictive analytics (PA) are critical factors for SCM performance in improving supply chain flexibility and reliability. PLS-Predict was applied to evaluate the predictive performance out-of-sample and the model proved to be robust. This work contributes to the growing knowledge base since it provides empirical evidence on how digital tools optimize SCM best and thus delivers companies’ strategic insights on balancing proximity to demand centers and supply chain resilience.

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

  • Business Process Management
  • Logistics
  • Industrial Management
  • Performance Management
  • Supply Chain Management
  • Operations Management

Data availability

All the data is collected from the simulation reports of the software and tools used by the authors. Authors are working on implementing the same using real world data with appropriate permissions.

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Authors and Affiliations

  1. Sri Sai Ram Institute of Management Studies, Sri Sai Ram Engineering College, Chennai, India

    Ganesh Kumar R & Dinesh Kumar S

  2. TAPMI School of Business, Manipal University Jaipur, Jaipur, Rajasthan, India

    C. Anirvinna

  3. Veeravalli Vidya Sundar PG College, Rajahmundry, Andhra Pradesh, India

    Rapaka David Goodwin

Contributions

Author 1: Dr. Ganesh Kumar R.

He performed the conceptualization, Methodology, Data collection and writing the study.

Author 2: Dr S Dinesh Kumar.

He analysis the dataset and conceptualization in the study.

Author 3: Dr C. Anirvinna.

He Performed the Analysis the overall concept, writing and editing.

Author 4: Dr Rapaka David Goodwin.

He analysis the paper and supervisor of this paper.

Corresponding author

Correspondence to Ganesh Kumar R.

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The authors declare that they have no conflict of interest.

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R, G.K., S, D.K., Anirvinna, C. et al. An empirical assessment of technological advancements on supply chain management performance: a mixed-methods sem approach using smartpls. Oper Manag Res (2025). https://doi.org/10.1007/s12063-025-00556-x

  • Received
  • Revised
  • Accepted
  • Published
  • DOI https://doi.org/10.1007/s12063-025-00556-x

Keywords

  • Technological Advancements
  • Supply Chain Management (SCM)
  • Structural Equation Modeling (SEM)
  • India

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