Purpose The Internet of Things (IoT) envisions a global infrastructure of networked physical objects that render radical transparency to supply chain management. Despite the perceived advantages of IoT, industry has still not widely adopted IoT-enabled logistics and supply chain management. The purpose of this paper is to understand the incentives and concerns behind firms’ decisions to adopt IoT, explore the determinant factors affecting IoT adoption in logistics and supply chain management. Design/methodology/approach This study uses mixed methods research to explore the determinants of IoT adoption intention in logistics and supply chain management. Qualitative analysis using the Grounded Theory methodology reveals the underlying perceptions regarding logistic innovation with IoT. Quantitative hypotheses are then developed based on qualitative investigation and adoption literature. Survey data were collected from the managerial staff of Taiwanese firms across various industries. Structural equation modeling with partial least square is used for data analysis. Findings The results of the qualitative study identify uncertainties and issues regarding firms’ intention to accept or reject IoT technology in logistics and supply chain management, including the benefit and cost aspects of adopting IoT, uncertainties about the trustworthiness of IoT technology, and the external motivating force to embrace IoT. The resulting quantitative model shows that perceived benefits, perceived costs, and external pressure are significant determinants of IoT adoption intention, while technology trust is not. However, technology trust does indirectly influence IoT adoption intention through perceived benefits. Practical implications The empirical findings of this study provide some guidelines for logistics and supply chain managers to evaluate IoT adoption in their firms. Likewise, IoT solution providers can also benefit from this study by improving their solutions to mitigate the IoT adoption concerns addressed herein. Originality/value This paper is among the first known to examine IoT adoption intention in logistics and supply chain management using mixed methods research. The mixed methods approach offers a better insight in understanding incentives behind firms’ decisions to adopt IoT vs the use of either a qualitative or quantitative method alone.

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Purpose-The objective of this paper is threefold: (1) to present IoT-based CPS architecture framework to facilitate the integration of IoT and CPS; (2) to implement an IoT-based CPS prototype based on the architecture framework for a PL application scenario of in a case study; and (3) to devise evaluation methods and conduct experimental evaluations on IoT-based CPS prototype Design/methodology/approach-The design research method, case study, emulation experiment method, and cost-benefit analysis are applied in this research. An IoT-based CPS architecture framework is proposed, and followed by the development of prototype system and testbed platform. Then, the emulation and experimental evaluation of IoT-based CPS are conducted on the testbed, and the experimental results are analyzed. Findings-The emulation experiment results show that the proposed IoT-based CPS outperforms current barcode-based system regarding labor cost, efficiency, and operational adaptiveness. The evaluation of the IoT-based CPS prototype indicates significant improvements in PL tasks and reduced part inventory under a dynamic changing shop-floor environment. Practical implications-The case study shows that the proposed architecture framework and prototype system can be applied to many discrete manufacturing industries, such as automobile, airplane, bicycle, home appliance, and electronics. Originality/value-The proposed IoT-based CPS is among the first to address the need to integrate IoT and CPS for PL applications, and to conduct experimental evaluations and cost-benefit analysis of adopting IoT-based CPS for PL. This paper also contributes to the IoT research by using diverse research methods to offer broader insights into understanding IoT and CPS.

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Purpose The lack of reference architecture for Internet of Things (IoT) modeling impedes the successful design and implementation of an IoT-based production logistics and supply chain system (PLSCS). The authors present this study in two parts to address this research issue. Part A proposes a unified IoT modeling framework to model the dynamics of distributed IoT processes, IoT devices, and IoT objects. The models of the framework can be leveraged to support the implementation architecture of an IoT-based PLSCS. The second part (Part B) of this study extends the discussion of implementation architecture proposed in Part A. Part B presents an IoT-based cyber-physical system framework and evaluates its performance. The paper aims to discuss this issue. Design/methodology/approach This paper adopts a design research approach, using ontology, process analysis, and Petri net modeling scheme to support IoT system modeling. Findings The proposed IoT system-modeling approach reduces the complexity of system development and increases system portability for IoT-based PLSCS. The IoT design models generated from the modeling can also be transformed to implementation logic. Practical implications The proposed IoT system-modeling framework and the implementation architecture can be used to develop an IoT-based PLSCS in the real industrial setting. The proposed modeling methods can be applied to many discrete manufacturing industries. Originality/value The IoT modeling framework developed in this study is the first in this field which decomposes IoT system design into ontology-, process-, and object-modeling layers. A novel implementation architecture also proposed to transform above IoT system design models into implementation logic. The developed prototype system can track product and different parts of the same product along a manufacturing supply chain.