Modelling Factors Influencing IoT Adoption: With a Focus on Agricultural Logistics Operations

Purpose- In recent years, there has been a notable surge in the utilization of emerging technologies, notably the Internet of Things (IoT), within the realm of business operations. However, empirical evidence has underscored a disconcerting trend whereby a substantial majority, surpassing 70%, of IoT adoption initiatives falter when confronted with the rigors of real-world implementation. Given the profound implications of IoT in augmenting product quality, this study endeavors to scrutinize the extant body of knowledge concerning IoT integration within the domain of agricultural logistics operations. Furthermore, it aims to discern the pivotal determinants that exert influence over the successful assimilation of IoT within business operations, with particular emphasis on logistics. Design/Methodology/Approach- The research utilizes a thorough systematic review methodology coupled with a meta-synthesis approach. In order to identify and clarify the key factors that influence IoT implementation in logistics operations, the study is grounded in the Resource-Based View theory. It employs rigorous grounded theory coding procedures, supported by the analytical capabilities of MAXQDA software. Findings- The culmination of the meta-synthesis endeavor culminates in the conceptual representation of IoT adoption within the agricultural logistics domain. This representation is underpinned by the identification of three overarching macro categories/constructs, namely: (1) IoT Technology Adoption, encompassing facets such as IoT implementation requisites, ancillary technologies essential for IoT integration, impediments encountered in IoT implementation, and the multifaceted factors that influence IoT adoption; (2) IoT-Driven Logistics Management, encompassing IoT-based warehousing practices, governance-related considerations, and the environmental parameters entailed in IoT-enabled logistics; and (3) the Prospective Gains Encompassing IoT Deployment, incorporating the financial, economic, operational, and sociocultural ramifications ensuing from IoT integration. The findings underscore the imperative of comprehensively addressing these factors for the successful assimilation of IoT within agricultural logistics processes. Originality- The originality of this research study lies in its pioneering effort to proffer a conceptual framework that furnishes a comprehensive panorama of the determinants that underpin IoT adoption, thereby ensuring its efficacious implementation within the ambit of agricultural logistics operations. Practical Implications- The developed framework, by bestowing upon stakeholders an incisive comprehension of the multifaceted factors that steer IoT adoption, holds the potential to streamline the IoT integration process. Moreover, it affords an avenue for harnessing the full spectrum of IoT-derived benefits within the intricate milieu of agricultural logistics operations

COVID-19 and Supply Chain Disruption Management: A Behavioural Economics Perspective and Future Research Direction

The COVID-19 pandemic has been one of the most severe disruptions to normal life, impacting how businesses operate. The academic literature in the areas of supply chain and operations management has been trying to explain how this has affected decision-making in businesses. However, the existing literature has predominantly overlooked organisational culture and behavioural economic theories. This paper contends that considering the decisions made in supply chain disruption management involve groups and the individuals within them, the relevance of behavioural economic concepts becomes paramount. As such, the objective of this paper is to conduct an integrative literature review, utilising the purposive sampling method to explore the dearth of academic work connecting behavioural economic theories and organisational culture to supply chain disruption management. Additionally, the paper aims to offer guidelines for future research in this domain. Enhancing our comprehension of these domains concerning supply chain disruption management would empower firms to better anticipate their parties’ decisions, refine their decision-making models, and cultivate stronger relationships with suppliers and customers

Defining and assessing industry 4.0 maturity levels–case of the defence sector

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Firms do not currently fully appreciate the complex characteristics of Industry 4.0 and as a result are uncertain about what it represents for them. In this study, an assessment model is developed to measure the level of implementation of Industry 4.0 technologies, around three dimensions: ‘Factory of the Future’, ‘People and Culture’, and ‘Strategy’. The ‘Factory of the Future’ is the main dimension and is composed of eight attributes: Additive Manufacturing, Cloud, Manufacturing Execution System, Internet of Things and Cyber Physical Systems, Big Data, Sensors, e-Value Chains, and Autonomous Robots. The study uses a defence manufacturing firm to develop, test and validate the model and report on 12 partners. We concluded that the focal firm has an Industry 4.0 maturity level of 59.35, above the sector average of 55.58. This research contributes by empirically developing a model and providing an analysis of major firms in the Defence supply network

The Significance of Industry 5.0 in the Globalization of Supply Chain Management

In today's rapidly evolving global business landscape, the convergence of Industry 5.0 and the globalization process of supply chain management has emerged as a pivotal driver of competitiveness and sustainability for organizations worldwide. This paper delves into the critical importance of Industry 5.0 in reshaping the dynamics of supply chain management on a global scale. Industry 5.0 represents the latest phase in the ongoing industrial revolution, characterized by the seamless integration of advanced technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Big Data Analytics, and Cyber-Physical Systems. This transformation transcends traditional boundaries by fostering unprecedented levels of connectivity, intelligence, and automation across industrial processes. Globalization, on the other hand, has redefined supply chain management by expanding market reach, reducing costs, and enhancing access to diverse resources and markets. The interplay between globalization and Industry 5.0 introduces a new paradigm in supply chain management that demands exploration