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This paper uses dialectical inquiry to explore tensions that arise when adopting Industry 4.0 technologies in a lean production system and their reconciliation mechanisms.

We conducted an in-depth qualitative case study over a 3-year period on an Italian division of an international electrotechnical organisation that produces electrical switches. This organisation successfully adopted Industry 4.0 technologies in a lean production system. The study is based on primary data such as observations and semi-structured interviews, along with secondary data.

We identify four empirically validated dialectic tensions arising across different Industry 4.0 adoption stages due to managers’ and workers’ contrasting interpretations of technologies. Consequently, we define the related reconciliation mechanisms that allow the effective adoption of various Industry 4.0 technologies to support a lean production system.

This is the first empirical investigation of tensions in the adoption of Industry 4.0 technologies in a lean production system. Furthermore, the paper presents four theoretical propositions and a conceptual model describing which tensions arise during the adoption of Industry 4.0 technologies in a lean production system and the reconciliation mechanisms that prevent lean production system deterioration.

Franchising contributes significantly to national economies but is overlooked in supply chain literature. This study aims to contribute to the franchising and supply chain literature by examining how the digitisation of the franchising supply chain improves firm performance.

A single longitudinal case study approach was selected to investigate how a leading coffee brand digitised its franchising supply chain. Resource constraints theory and agency theory provide the theoretical framework. Data collection included both qualitative and quantitative data. Over two years, chronological, supply chain and thematic analyses and interpretation uncovered important findings and developed four research propositions.

Findings show that digitisation can impact performance in eight areas: Resource management, Resource constraints, Efficiency, Business-to-Business (B2B)/Business-To-Customer (B2C) links, Rapid expansion, Risk mitigation, Information asymmetries and Faster supply chain responses. Four digital technologies (advanced analytics, Internet of Things, Autonomous Mobile Robots and B2B e-shop) impacted three franchisor functions (Machine maintenance, Inventory management, Franchisee and end-customer relations). The study develops four research propositions on how digitisation impacts performance in terms of (1) resource monitoring and control, (2) learning and knowledge creation, (3) coordination and collaboration and (4) competition.

Franchising supply chains have been overlooked in the literature; this study provides insights into using resource constraints theory and agency theory complementarily to explain supply chain digitisation and provides actionable practical implications for selecting, implementing and continuously improving Industry 4.0 technologies in franchising supply chains.

This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.

In this study, an algorithm for job scheduling and cooperative work of multiple AGVs is designed. In the first part, with the goal of minimizing the total processing time and the total power consumption, the niche multi-objective evolutionary algorithm is used to determine the processing task arrangement on different machines. In the second part, AGV is called to transport workpieces, and an improved ant colony algorithm is used to generate the initial path of AGV. In the third part, to avoid path conflicts between running AGVs, the authors propose a simple priority-based waiting strategy to avoid collisions.

The experiment shows that the solution can effectively deal with job scheduling and multiple AGV operation problems in the workshop.

In this paper, a collaborative work algorithm is proposed, which combines the job scheduling and AGV running problem to make the research results adapt to the real job environment in the workshop.

Climate change and digitisation are unquestionably the two defining features of this era. Both present immense challenges with unimaginable consequences for humankind while promising enormous rewards for those who can adequately address their adverse effects. These two critical factors must be considered while establishing strategies for the businesses' future operations. Hence, post-pandemic, especially with the rise of online commerce, packages and documents are delivered around the globe nearly every day, propelling the logistics industry's growth. This is not the critical challenge in logistics, the issue of sustainability, particularly as the returns are increasing exponentially, leading to a significant impact on transportation is and its reliance on fossil fuel has made it a prime target for society's growing environmental concerns. Thus, real-time visibility, collaboration and integration in reverse logistics (RL) are imperative for business sustainability. The most applicable Industry 4.0 technologies in RL are the Internet of Things (IoT), cloud computing, blockchain and digital twin that enable the defragmentation of the RL market.

This chapter analyses the technological impact of Industry 4.0 on RL. This research investigates the challenges faced by the logistics industry in the context of sustainability and how digital transformation can bring many potential benefits across the entire value chain. This chapter also presents a guidance for a framework based on the literature review that tends to favour the development of elastic logistics, implying improved company responsiveness to market conditions. The study contributes to the body of literature and the establishment of the framework for planning on the application of various Industry 4.0 technologies in developing eco-friendly and sustainable reverse logistics framework.

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 pressure to survive in a highly competitive market by using artificial intelligence (AI) has further demonstrated the need for automation in business operations during a crisis, such as COVID-19. Prior research finds managers' mixed perceptions about the use of technology in business, which underscores the need to better understand their perceptions of adopting AI for automation in business operations during COVID-19. Based on social exchange theory, the authors investigated managers' perceptions of using AI in business for effective operations during the COVID-19 pandemic.

This study collected data through a survey conducted in China (N = 429) and ran structural equation modeling to examine the proposed research model and structural relationships using Smart PLS software.

The results show that using AI in supply chain management, inventory management, business models, and budgeting are positively associated with managers' satisfaction. Further, the relationship between managers' satisfaction and effective business operations was found to be positively significant. In addition, the findings suggest that top management support and the working environment have moderating effects on the relationship between managers' satisfaction and effective business operations.

The results of this study can guide firms to adopt an AI usage policy and execution strategy, according to managers' perceptions and psychological responses to AI.

The study can be used to manage the behavior of managers within organizations. This will ultimately improve society's perception of the employment of AI in business operations.

The study's outcomes provide valuable insights into business management and information systems with AI application as a business response to any crisis in the future.

Many countries and regions have recognised the potential of automated transport as a solution to cover mobility needs in a sustainable way. They have implemented dedicated strategies and allowed trial operations of Automated Vehicles (AVs) within their national frameworks.

This chapter conducts an analysis of the legal frameworks for AV trial operations in 11 European countries. It reviews existing laws and regulations and includes results from an online survey with national stakeholders and experts experienced in AV testing.

The results reveal very different approaches among European countries. Moreover, results indicate a stronger focus on technical safety aspects of the vehicles rather than on operational procedures and mobility integration, such as incorporating AV services into existing public transport systems.

This high level of disparity between the different European legal frameworks poses a considerable barrier to a rollout of the technologies and methodologies for AVs without cross-border and cross-supplier conflicts. Furthermore, when moving to the deployment of real services in the near future a common European framework and a stronger focus on operational procedures are essential for the implementation of automated transport services in order to cover the mobility needs of people in a more sustainable way (e.g. first/last mile to public transport).

European countries should further integrate operational aspects in the terms of services that are integrated in public transport, align deployment of AVs with national and local sustainability goals and focus on use cases beyond private vehicles to foster the transition to a more sustainable future of transport.

The purpose of this study is to explore how Industry 4.0 (I40) technologies support workers' engagement in soft total quality management (TQM) practices for organisational performance.

The authors conducted a multiple case study of six Italian manufacturing organisations that operate with I40 production and implement TQM practices. The authors concentrated on the relationship between I40 technologies and soft TQM aspects.

I40 technologies provide two forms of engagement with workers. Workers can act as machine supervisors and expert assembly operators. Organisations use five soft TQM practices to involve and develop workers for TQM that vary according to automation levels. The five soft TQM practices are top management design around workers, incremental trials with I40 technologies, worker empowerment, I40 sociotechnical collaboration and individual feedback systems.

In the literature that focusses primarily on how I40 technologies support the hard side of TQM by creating a data-driven and automated quality management system, the authors illustrate how the workforce can be engaged in I40 with five soft TQM practices to improve organisational performance. Thus, the authors complement the theory of hard and soft TQM aspects for I40 production systems.