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The advent of Industry 4.0 (I4.0) and the requirements imposed on companies still need to be clarified. Companies still strive to understand I4.0 requirements and technological, organizational, operational and management challenges. Current literature on I4.0 underlies the importance of a roadmap with structured steps to achieve the benefits of I4.0, mainly focused on augmenting operational performance. Therefore, this paper proposes a roadmap to implement I4.0 focused on operational management concepts, mainly aiming to augment operational performance and bridge the gap between theory and practice regarding roadmaps focused on the operational management dimension.

This paper follows a research approach divided into the following stages: a literature review to analyze the I4.0 roadmaps and identify the main components of I4.0; development of the proposed I4.0 roadmap presented; field research to test the roadmap by collecting data from a manufacturing company in the automotive industry; validation of the roadmap through modeling and simulation.

The authors presented a production line design with real-time control, fast response, shop floor coordination and predictive capacity. The results prove that the proposed I4.0 roadmap augments operation performance in the investigated automotive company. The main results were work in process reduction, lead time reduction, output increase, real-time control, shop floor coordination and fast response.

The main novelty of the proposed roadmap is to move toward I4.0 implementation with a focus on the operational management dimension. The roadmap has an innovative combination of the two approaches – lean manufacturing and factory physics – a straightforward roadmap with only three steps: (1) requirements, (2) real-time control and (3) predictive capacity, a structured definition of the approaches and operational management concepts fundamental in each step.

Organizational technologies can be classified according to the roles they play as either commodity or strategic. Commodity technologies support common operations, while strategic technologies address perceived threats to competitiveness, often identified by strategic foresight. These must go through an adoption process before playing an effective role in strategy execution. The adoption process includes known activities, ranging from sourcing (itself from in-house development to turn-key acquisition) to operational integration. This paper aims to reveal strategic technology adoption risks that arise during strategy execution.

A gradually developed causal loop diagram model, supported by general literature, introduces three general classes of technology adoption risks: mismatched requirements, supplier dependence and unmanaged life cycles.

Rather than managed, these risks are incurred or avoided depending on decisions made during the adoption process.

Despite the scarce literature coverage for the approach, examples revealing the presence of adoption risks are nevertheless available in the well-documented history of enterprise resource planning (ERP).

Although ERP is presented as a general-purpose strategic technology, the unique business features of maritime container terminals pose serious challenges to its adoption, which provides additional support to the discussion and reinforces the conclusions.

The approach to identifying risks in strategic technology adoption departs from the current risk paradigm in two significant ways. First, it emphasizes policy decision-making rather than external events. Second, it views risks as systemic rather than occurring independently.

This paper aims to propose an interpretive framework to understand how machine learning (ML) affects the way companies interact with their ecosystem and how the introduction of digital technologies affects the value co-creation (VCC) process.

This study bases on configuration theory, which entails two main methodological phases. In the first phase the authors define the theoretically-derived interpretive framework through a literature review. In the second phase the authors adopt a case study methodology to inductively analyze the theoretically-derived domains and their relationships within a configuration.

ML enables multi-directional knowledge flows among value co-creators and expands the scope of VCC beyond the boundaries of the firm-client relationship. However, it determines a substantive imbalance in knowledge management power among the actors involved in VCC. ML positively impacts value co-creators’ performance but also requires significant organizational changes. To benefit from VCC via ML, value co-creators must be aligned in terms of digital maturity.

The paper answers the call for more theoretical and empirical research on the impact of the introduction of Industry 4.0 technology in companies and their ecosystem. It intends to improve the understanding of how ML technology affects the determinants and the process of VCC by providing both a static and dynamic analysis of the topic.

This article aimed to propose and validate a roadmap to enhance the insertion of social sustainability practices in logistics activities considering the scenario of companies operating in Brazil.

The initial construction of the aforementioned roadmap was based on a detailed literature review and the fine-tuning as well as validation of it was carried out through a Delphi process developed with professionals specialized in the area of logistics and sustainability.

As main results, it is highlighted that the validated roadmap includes actions ranging from meeting and adapting legal issues related to sustainability, through the initial diagnosis of the company, motivation and awareness of the importance of social sustainability, followed by encouraging the inclusion of social sustainability practices in logistic activities, and finally, the identification of opportunities for improvement and establishment of execution plans within the organization. The phases and actions of the validated roadmap converge towards restructuring and redefinition of the organizational culture oriented towards meeting sustainable guidelines, and also contemplate the dynamics of seeking continuous improvement throughout all levels and sectors belonging to a given organization.

The originality of this study lies in the fact that the roadmap focuses on the inclusion of social sustainability practices in logistic activities, since, according to the literature, social aspects are still relegated to the background when compared to environmental and economic aspects.

The purpose of this paper is to fill a gap in the literature regarding the open innovation management approaches that small and medium-sized enterprises (SMEs) can use to access digital technologies and incorporate them into their organizational processes. The research question is: What organizational and process-level managerial actions do SMEs take to successfully access and implement digital technologies within their organizational processes?

Using Guertler et al.'s (2020) Action Innovation Management Research (AIM-R) framework, this study examines the digital transformation experiences of 10 European SMEs to gain insights into the managerial actions that foster successful digital transformation.

The findings of the paper reveal two major contributions. First, a digital transformation roadmap for SMEs is proposed, with a focus on accessing external resources and reconfiguring internal ones to ease their digital transformation journey. Second, three distinct paradoxes that influence the digital transformation process in SMEs are highlighted, providing useful insights into the challenges and tensions SMEs face during this journey.

This paper provides a unique perspective on the digital transformation of SMEs by examining the managerial actions required for successful technology adoption and revealing the paradoxes that may emerge during this transformative process. The findings form the basis for future research, deepening our understanding of digital transformation in SMEs and providing actionable advice to managers and practitioners navigating this journey.

The purpose of this paper is to present an approach to start industry–university (I-U) collaboration through a stepped process aimed at building a portfolio of research and development (R&D) projects.

It devises from an 18-month action-research program held between a multinational automotive manufacturer and the a top-ranked Brazilian university.

The three-stage R&D shared portfolio methodology results from a combined application of quality function deployment-like correlation matrices and roadmapping. A first matrix tackles industry interests and correlates product performance dimensions and components to reveal broad research areas of interest. A second matrix correlates research areas and engineering competences, highlighting the types of the required know-how from the university standpoint. Thirdly, academic experts help to fill a roadmap-like layer with possible collaborative R&D deliverables over time.

Since the study lies on a single experience, extensions to other contexts should be made with care. However, the proposal offers robust rationale and a set of supporting tools to nurture new applications.

Theoretical and methodological reflections help managers tackling the long-standing problem of setting a shared R&D agenda.

Literature on I-U collaboration tends or to over-emphasize the role of technology transfer offices in promoting the partnerships or to seek implications for public policy. This research offers a valuable approach to build shared R&D project portfolio from a managerial viewpoint, filling an academic gap and offering guidance for managers in both sides.

This study investigates the enablers and challenges of digital supply chains (DSCs) adoption and develops a digital supply chain maturity (DSCM) model as a basis for developing guidelines for DSC adoption in the digital transformation journey.

The research involves a systematic literature review (SLR) of Industry 4.0 (I4) adoption in supply chain (SC) practices to identify key enablers and associated maturity levels. The literature search of published articles during the 1997–2020 period and subsequent screening resulted in 64 articles. A DSCM model was developed using the categorization of important enablers and associated levels transitioning from the traditional SC to the DSC ecosystem.

Four broader categories of DSC enablers and challenges were identified from the content analysis of SLR. Digital strategy alongside I4 technologies and human capital were prominent in DSC adoption as I4 technologies and human capital depend on other enablers such as dynamic capabilities (DCs). Lack of infrastructure and financial constraints to implementing I4 were significant challenges in the DSC adoption.

The proposed DSCM model provides a holistic view of enablers and maturity levels from traditional SC to DSC adoption. However, the DSCM model needs to be empirically validated and streamlined further using inputs from practitioners.

The proposed DSCM model can be used as a framework to guide practitioners in assessing maturity and developing implementation plans for successful DSC adoption.

This research introduces a novel DSC maturity model through a holistic view of enablers and maturity levels from traditional SC to DSC adoption.

This study aims to investigate the contribution of knowledge-intensive business services firms to small- and medium-sized manufacturers’ digital servitization journeys, addressing the standardization versus customization dichotomy of services and solutions provision.

To identify the challenges that small- and medium-sized firms must face in the digital servitization journey and the role that knowledge-intensive business services firms may play in the innovation processes, the authors conduct a review on two still unrelated literature streams and develop a longitudinal single-case study, with a particular focus on knowledge generation mechanisms.

Digital servitization is a particularly challenging transformational journey for minor firms. Knowledge-intensive business services firms can act as sources, facilitators, and carriers of knowledge, and they can orchestrate further contributions of other external partners and firms.

The paper contributes to theory describing the roadmap and the role of external service providers in digital servitization journeys of smaller firms’, that are frequently excluded from mainstream research although being the backbone of European economies.

Digital servitization in minor manufacturing firms requires a long-term orientation and a multi-stage roadmap. Mixing standardized technology-based solutions and complementary professional services, knowledge-intensive business services firms can significantly contribute to lowering the journey’s uncertainties, operational complexity, and costs.

The paper sheds lights on how the collaboration between knowledge-intensive business services firms and small manufacturers generates novel knowledge and capabilities that contribute to takle the challenges of the different stages of the digital servitization roadmap.

The Sendai framework for disaster risk reduction (DRR) 2015–2030 offers guidelines to reduce disaster losses and further delivers a wake-up call to be conscious of disasters. Its four priorities hinge on science, technology and innovations as critical elements necessary to support the understanding of disasters and the alternatives to countermeasures. However, the changing dynamics of current and new risks highlight the need for existing approaches to keep pace with these changes. This is further relevant as the timeline for the framework enters its mid-point since its inception. Hence, this study reflects on the aspirations of the Sendai framework for DRR through a review of activities conducted in the past years under science, technology and innovations.

Multidimensional secondary datasets are collected and reviewed to give a general insight into the DRR activities of governments and other related agencies over the past years with case examples. The results are then discussed in the context of new global risks and technological advancement.

It becomes evident that GIS and remote sensing embedded technologies are spearheading innovations for DRR across many countries. However, the severity of the Covid-19 pandemic has accelerated innovations that use artificial intelligence-based technologies in diverse ways and has thus become important to risk management. These notwithstanding, the incorporation of science, technology and innovations in DRR faces many challenges. To mitigate some of the challenges, the study proposes reforms to the scope and application of science and technology for DRR, as well as suggests a new framework for risk reduction that harnesses stakeholder collaborations and resource mobilizations.

The approach and proposals made in this study are made in reference to known workable processes and procedures with proven successes. However, contextual differences may affect the suggested approaches.

The study provides alternatives to risk reduction approaches that hinge on practically tested procedures that harness inclusivity attributes deemed significant to the Sendai framework for DRR 2015–2030.

This paper aims to explore the growth of the South African additive manufacturing (AM) industry over the past 31 years through the lens of the innovation system (IS) perspective, examining the actor dynamics and mechanisms that facilitated or hindered the industry’s development.

The study used a case study research approach, analysing semi-structured interviews with eight South African AM experts and documentary evidence. The IS framework and the realist evaluation perspective were used, using a context-intervention-mechanism-outcome (CIMO)-based event history analysis (EHA) framework to explore the actor dynamics and mechanisms of the case study.

The study used a case study research approach, analysing semi-structured interviews with eight South African AM experts and documentary evidence. The IS framework and the realist evaluation perspective were used, using a CIMO-based EHA framework to explore the actor dynamics and mechanisms of the case study.

This paper contributes to the South African AM industry literature by providing an overview of the industry events over the past three decades and analysing the industry through the IS framework. The study is among the first to analyse the development of the South African AM industry, presenting innovation scholars and managers with valuable decision-making support by providing insights into the innovation activities performed during each stage of the industry’s development, who performed them, the sequence in which they were performed and the outcomes they delivered.