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The cyber-physical system (CPS) is a well proven technology for improving system performance, resilience, and interconnectivity. In emerging nations like India, the logistics industry lacks practices connecting logistical equipment with cyberspace. This paper aims to bridge this gap by identifying and evaluating the performance metrics of connectivity solutions. Its goal is to establish an appropriate infrastructure that enables seamless connectivity within the CPS-enabled logistics ecosystem.

A novel integrated decision method is employed to classify the optimal connectivity solution for CPS. It integrates Regret Theory (RT) and Preference Ranking for Organization Method for Enrichment Evaluation (PROMETHEE-1) method in a Hesitant Fuzzy (HF) environment. This method considers the psychological traits of decision-makers and effectively incorporates their hesitancy for the classification.

The findings highlight security (c10) as the foremost critical performance metric, followed by cost (c6), scalability (c9), traceability (c2) and trustworthiness (c1) to build connective infrastructure for CPS. For extensive coverage scenarios, like freight transportation, cellular connectivity (a2) emerges as the most suitable connectivity solution.

This study provides a roadmap to logistics managers for selecting a suitable connectivity infrastructure to enhance seamless connectivity in logistics operations and processes. Technology providers can utilize the findings to develop the CPS infrastructure for effective freight logistics management.

This research introduces a novel decision-making tool for making choices related to advanced technology assessment. It holds significant value in facilitating well-informed decisions in the digital transformation era.

The digital evolution of production and logistics systems requires seamless integration of various functions. Cyber-physical systems (CPS) can streamline operations, reduce costs and optimise freight transport dynamics. Therefore, CPS adoption is essential to transform existing logistics infrastructure by connecting logistical equipment to cyberspace. This research addresses the critical issue of low CPS adoption in logistics. By analysing the barriers, the study proposes effective strategies to increase CPS integration significantly.

This study used the technology-organisation-environment (TOE) framework and identified 18 barriers to CPS adoption in freight logistics. The barriers were then analysed using the fuzzy data-driven multi-criteria decision-making (MCDM) method, i.e. fuzzy-based decision-making trial and evaluation laboratory (Fuzzy-DEMATEL).

The computational analysis of the proposed framework shows that “the complexity of CPS and lagged data-driven logistics infrastructure” (T₁) is a major technological inhibitor to CPS adoption. The “high cost of CPS technology” (O₈) and a “lack of top management support” (O₃) are the top causal inhibitors at the organisational level. “Lack of data governance and regulatory framework” (E₂) is the main environmental inhibitor.

The causal mapping of the TOE-based barriers helps policymakers and logisticians to develop strategies or follow recommended adoption strategies to improve CPS adoption in logistics.

This study is a pioneering effort to unveil the adoption barriers of CPS in the freight logistics industry and suggest strategies for fostering adoption. This research could provide valuable insights for logistics organisations to support CPS-driven logistics modernisation.