Purpose: This article aims to investigate the organisational implications of adopting Industry 4.0 (I4.0) technologies, giving specific attention to operations. The paper addresses these implications in two directions: organisational prerequisites for, and consequences of, I4.0 technologies.Design/methodology/approach: The research is based on a multiple case study of Italian small and medium enterprises (SMEs) in manufacturing. Ten case studies have been developed through interviews, company visits and secondary data collection.Findings: The multiple case study results show that: (1) a lean organisational structure supports effective adoption of I4.0 technologies; (2) introducing such technologies is linked to developing a new kind of job profile (i.e. the “Autonomous Operative Job Profile”); and (3) higher levels of technology adoption create a higher need for non-technical competences.Research limitations/implications: A limitation of this research relates to the highly heterogeneous maturity levels of the sampled companies, due to the relative newness of the I4.0 paradigm. Future research could, therefore, longitudinally analyse the technology integration process within organisations.Practical implications: This research provides preliminary evidence about how organisations and technologies co-evolve, thus suggesting that managers should co-design these areas. It also demonstrates the extreme importance of designing a structured process and a clear set of human resource management tools to favour SME organisational development.Originality/value: The study is built upon a conceptual framework derived from the sociotechnical perspective that analyses the interconnections between technology implementation and organisational change. From the results, three research propositions are derived to be tested on a larger scale.

This paper investigates blockchain technology from a Triple Bottom Line (TBL) perspective. Transparency is vital for achieving accountability, improving the environmental footprint and ensuring that workers’ rights are respected. Blockchain-enabled capabilities provide opportunities to support improved information transparency to sub-suppliers and customers. Case study research is used within the complex multi-tier global fashion industry to explore the application of blockchain technology in enhancing TBL performance. This paper responds to calls from the literature to provide practice-based research on blockchain and supply chain management challenges. The research is based on three technology-based start-ups (at different Technology Readiness Levels (TRL)) and investigates their practical experiences to date, in transforming and advancing supply chain TBL. As this research focuses on the early adoption of blockchain technology within the fashion industry, it demonstrates the practicalities of implementation including its capabilities, operational improvements, challenges and limitations.

The article concerns the revision of earlier decisions to offshore production activities (so called “relocation of second degree”); more specifically it is focused on the “reshoring” (also referred as “relocation to the home country”, “back-reshoring” or “back-shoring”). The research aims are to investigate what types of mistakes occur along the decision-making and implementation process and how they affect the outcome, in terms of success or failure, of a relocation strategy. A multiple case study involving four companies in the fashion industry from Portugal and Italy was conducted. The cross-case analysis allowed to differentiate decision-making mistakes from implementation ones and to assess differences and similarities among the cases in terms of content of the relocation, drivers and outcomes. The research contributes to previous literature on reshoring by bringing evidence of different types of mistakes to be considered, thus requiring further conceptualization of the reshoring process. Managers and entrepreneurs should consider the importance of doing the things right also during the implementation, too often underestimated. The present article is the first one in the reshoring literature bringing evidence of cases of failure in the relocation decisions and discriminating among different kinds of mistakes.