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The study analyses how Industry 4.0 and underlying digital technologies influence the design of ecosystems in global value chains (GVCs).

A qualitative-exploratory research design is used. It deploys a multiple case study based on semi-structured interviews with 73 German managers of multinational enterprises. Applying a qualitative content analysis, the expert interviews are inductively analyzed and triangulated with secondary data to develop a synthesized data structure.

The analysis reveals a general tendency towards decentralization of value chain activities. Depending on the nature of each activity and several contextual factors, however, hybrids between centralization and decentralization of processes can be observed in Industry 4.0 environments. Consequences for global ecosystems are altered cooperation with business partners, new organizational forms and novel market environments.

Given inherent limitations in scope and methodology, the study calls for cross-industry and cross-country analyses. Further studies should research implications of Industry 4.0 changes in ecosystems and GVCs, and the role digital platforms can play in this context.

The results help companies to analyze and adapt their role in ecosystems and associated GVC activities to Industry 4.0 environments, thus staying competitive in changing market conditions.

This study is among the first to empirically investigate the influence of Industry 4.0 on ecosystems embedded in GVCs. Reflecting existing company environments, it adds an international and company-external perspective to Industry 4.0 research.

The purpose of this paper is to identify actions and guidelines for enabling and fostering the Industry 4.0 adoption, as well as to understand the role of three ecosystem actors in these actions (i.e. companies, educational organizations and regional policy makers).

52 semi-structured expert interviews in the Tyrol-Veneto cross-border macro-region were carried out and interpreted using the innovation ecosystem concept. In particular, drawing from this latter, six ecosystem building blocks were identified and used to analyze the interviews' content.

The findings allow not only to build a comprehensive framework for action to support Industry 4.0 adoption, but also to confirm the importance of exploring Industry 4.0 through the lens of the ecosystem concept. Indeed, the authors show that R&D activities should be complemented with interorganizational actions, such as training and networking, and that all ecosystem actors should be involved in the Industry 4.0 adoption.

This is among the few studies that adopt the innovation ecosystem perspective to explore best practices for Industry 4.0 adoption, thus overcoming the weakness of existing papers based on a firm-level perspective. It also complements previous ecosystem-based research on Industry 4.0 by exploring the technology adoption side, rather than the technology provision one, and by considering the adoption of a wide set of technologies.

This study analyzes how the innovation ecosystem helps integrate technology-push and market-pull strategies in the Industry 4.0 paradigm.

This study investigates companies' involvement in the Industry 4.0 paradigm through technology-push strategies, and through both technology-push and market-pull strategies. The authors perform two econometric logit models to test the influence of collaborations with heterogeneous actors, research and university relationships, and relations with business incubator (the pivot actor) on companies' involvement in Industry 4.0.

The study empirically shows that developing relationships with a greater diversity of actors, collaborating with university and research laboratories, and developing intense relationships with business incubator increase the likelihood for companies to integrate both technology-push and market-pull strategies in companies' involvement in the Industry 4.0 paradigm.

This study provides insights to practitioners who are interested or involved in the new Industry 4.0 paradigm. The authors' study explains how specific features of an innovation ecosystem, such as complex interactions among actors, can stimulate creative ideas and successfully implement innovations to address Industry 4.0 challenges.

First, the authors confirm the role of the innovation ecosystem on companies' involvement in the Industry 4.0 paradigm. Second, the authors study highlights that the innovation ecosystem is a new relevant framework that enables companies to integrate both technology-push and market-pull strategies. Third, we provide empirical evidence about the role of business incubator on firms' strategies to get involved in the Industry 4.0 paradigm.

The purpose of this paper is to develop an industry 4.0 (I4.0) innovation ecosystem framework by exploring the essential components of the same to ensure the collaborative efforts of different stakeholders.

In this research work, important perspectives and their sub-components for the I4.0 innovation ecosystem framework are identified by performing a systematic literature survey of peer-reviewed journal articles. Then, I4.0 challenges among higher education (HE) institutions students and industries in India are explored by adopting the questionnaire-based research approach. Finally, the importance of the identified perspectives and their sub-components and causal relations among components are analyzed by using the decision-making trial and evaluation laboratory method.

From the literature survey, three perspectives and their 45 sub-components are identified for the I4.0 innovation ecosystem framework. The outcomes show that the industry has a direct impact on HE institutions and the government. While HE institutions are most influenced by the industry and government.

I4.0 innovation ecosystem framework is developed by analyzing responses received through questionnaires. There are other methods also available for ecosystem framework development, which are beyond this study.

This research work will facilitate policy formulation by the government. It will also help the managers to develop strategies for the adoption of I4.0 enabling technologies in their business.

This research study gives an idea about the innovation ecosystem framework for the successful adoption of I4.0 enabling technologies in Indian Manufacturing Industries.

Company goals, behaviors and decision-making processes may differ depending on whether a given company decides to engage in the Industry 4.0 (I4.0) paradigm as a user or as a provider of I4.0-based solutions. This paper will consider this question in-depth by focusing on the extent to which the innovation ecosystem (IES) affects these two main strategies.

The authors' study aims to analyze the impact of a regional information and communication technology (ICT) ecosystem on the implementation of I4.0 at the company level by using an original survey of 123 companies that are already engaged in the implementation of I4.0 in the French region of Hauts-de-France and by employing two sets of logit models.

The authors' empirical study demonstrates the importance of an innovation ecosystem-based strategy for I4.0 technology provision. It reveals that engaging in R&D collaborative projects and developing links and complex relationships with heterogeneous actors within the IES positively affects the likelihood of a given firm deciding to implement I4.0 as a provider of I4.0-based solutions. This does not, however, affect the probability of a firm engaging in the I4.0 paradigm as a user of technologies and solutions.

From a policy standpoint, this study could encourage decision-makers to engage with I4.0 development by developing policies targeting the reinforcement of IES at a regional level. This could also help to accelerate the adoption of I4.0 technologies by manufacturing companies and foster the development of I4.0-based solutions through specific company-targeted policies. The authors' study supports the need for manufacturing company managers to evaluate and identify the best technological strategies related to the I4.0 paradigm that meet their specific needs.

The authors' study shows that the decision to engage in the I4.0 paradigm as providers of I4.0-based solutions is more likely to rely on an innovation ecosystem-based strategy, while the decision to engage in the I4.0 paradigm as users of I4.0-based solutions is more likely to rely on the company’s internal strategies, resources and demand-side benefits.

In the digital economy era, digital platforms are vital infrastructure for innovation subjects to perform digital innovation activities. Achieving efficient and smooth knowledge transfer between innovation subjects through digital platforms has become a novel research subject. This study aims to examine the knowledge transfer mechanism of digital platforms in the digital innovation ecosystem through modeling and simulation to offer a theoretical basis for digital innovation subjects to acquire digital value through knowledge-sharing and thus augment their competitive advantage.

This study explores the optimal symbiotic interaction rate between different users based on the classic susceptible-infected-removed (SIR) model. Additionally, it constructs a knowledge transfer mechanism model for digital platforms in the digital innovation ecosystem by combining the theories of communication dynamics and symbiosis. Finally, Matrix Laboratory (MATLAB) software is used for the model and numerical simulation.

The results demonstrate that (1) the evolutionary path of the symbiotic model is key to digital platforms' knowledge transfer in the digital innovation ecosystem. In the symbiotic model, the knowledge transfer path of digital platforms is “independent symbiosis—biased symbiosis (user benefit)—reciprocal symbiosis,” aligning with the overall interests of the digital innovation ecosystem. (2) Digital platforms' knowledge transfer effects within the digital innovation ecosystem show significant differences. The most effective knowledge transfer model for digital platforms is reciprocal symbiosis, whereas the least effective is parochial symbiosis (platform benefit). (3) The symbiotic rate has a significant positive impact on the evolutionary dynamics of knowledge transfer on digital platforms, especially in the reciprocal symbiosis model.

This study's results aid digital innovators in achieving efficient knowledge transfer through digital platforms and identify how symbiotic relationships affect the knowledge transfer process across the ecosystem. Accordingly, the authors propose targeted recommendations to promote the efficiency of knowledge transfer on digital platforms.

The purpose of this article is to explore the new concept of TQM 4.0 as a way of adapting quality management (QM) in Industry 4.0 (I4.0), guiding industries to this new phase, which has generated adaptations in numerous areas, one of which is QM and human resources.

A systematic review of the literature was carried out. Methodi Ordinatio was applied to build the portfolio of articles with scientific relevance, which is the source of data collections and content analysis. To help out in the analysis, NVivo 12 and VOSviewer software programs were used.

The results demonstrate that when adapting the QM to the technologies of I4.0, the result is an ecosystem that supports the integration between technology, quality and people in the industrial scenario.

This article presents a systematic review of the literature, but without delving into specific issues such as the different industrial sectors and the culture of countries in which industries may be inserted, for example, which characterizes a limitation of this research.

This study provides an ecosystem model that can guide future research, regarding the concept of TQM 4.0, in addition to pointing out some ways of combining technologies, quality and people in the industrial context.

This is one of the first articles to employ a systematic review of the literature using Methodi Ordinatio to build a bibliographic panorama on the intertwining of the themes total QM (TQM) and I4.0, focusing on the emerging concept of TQM 4.0.

This study aims to design appropriate micro-fintech models for Islamic microfinance institutions (IMFIs), especially Baitul Maal wat Tamwil (BMT) in Indonesia, thus enabling BMT to combine Islamic social and commercial microfinance optimally.

This study uses the analytic network process and Delphi methods, with three groups of experts as the respondents, namely, academician-regulators, BMT practitioners and Fintech practitioners.

The first results show that the micro-fintech tools needed by IMFI/BMT are digital banking, payment, peer-to-peer (P2P) financing, P2P social and e-commerce. These could be developed by a BMT alone or with an APEX or Association, which could also collaborate with an existing fintech company that specialises in micro-fintech, applying the offline to online approach. This means that commercial funding, as well as social fundraising of zakat and waqf, would be conducted online, whereas commercial financing for micro and small enterprise customers and the disbursement of zakat and waqf would be conducted offline. The second results show that the limited open ecosystem and hybrid ecosystem are the most appropriate micro-fintech ecosystems for IMFIs/BMT, with various alternative models. In addition, the private closed ecosystem preferred by BMT would be feasible if all criteria show improvement in the future.

This study is qualitative in nature. The methods used have limitations, meaning the models could be improved by incorporating other methods. Moreover, the case and respondents are all Indonesian, which means that the results may only be applicable to BMTs in Indonesia.

A BMT and/or BMT association could immediately apply micro-fintech with a limited open ecosystem, while in the future, they could apply micro-fintech with a private closed ecosystem.

The micro-fintech model could be used to optimise the collections of zakat, infaq and waqf, meaning BMT could provide more social programmes for those in need.

The growth of fintech in Islamic microfinance has occurred only recently, while only a limited number of studies have been conducted; therefore, no study exists on the development of a micro-fintech model appropriate for IMFIs, especially BMT.

The purpose of this paper is to synthesize a manufacturing value network for digital multinationals that combines the global reach of multinationals, the power of platform business models and digitalization. Toward this, the authors assess the critical roles platform ecosystems, and Industry 4.0 play in resolving the key challenges associated with asset specificity, location specificity and information asymmetry, inherent in the conventional business models of manufacturing multinationals.

The authors take an exploratory approach in reviewing industry literature and analyzing implementations of digital technologies in manufacturing and supply chain processes at four large manufacturing multinationals from diverse industry sectors, from electronics to packaged food production. The authors also identify how value-creation activities are relocated, and how players collaborate to create and capture value. Consequently, the authors abstract a framework for global value network of manufacturing multinationals.

With changing definitions of industry, competition and organizations, the authors’ framework for manufacturing value network establishes the ways digitalization can be integrated in the global businesses of manufacturing multinationals, realizing the combinatorial effect of Industry 4.0 and platform ecosystems. The transformation redefines the ways multinationals have been leveraging their ownership-location-internalization (OLI) advantages. The authors recognize that the multinational orchestrator plays a critical role in creating shared goals for platform participants and governing the dynamics. In addition, the participants' propensity to trust the platform and the perceived trustworthiness of the orchestrator shape the scope and boundaries of the platform.

The authors raise critical questions about the role of multinational orchestrator and trust dimensions. In addition, the OLI-platform paradigm that incorporates the combinatorial effect of platform ecosystem and Industry 4.0 explains how multinationals create and capture value in new ways.

The purpose of this paper is to identify, analyze and model Internet of Things (IoT) enablers essential for the success of Industry 4.0.

IoT enablers for Industry 4.0 are identified from literature and inferable discussions with industry experts. Three different techniques namely, principal component analysis (PCA), interpretive structural modeling (ISM) and decision making trial and evaluation laboratory (DEMATEL) are applied to model IoT enablers. In addition to this, DEMATEL is also applied under two different situations representing the behavioral characteristic of experts involved. These are termed as optimistic (maximum) and pessimistic (minimum).

The integrated approach of PCA-ISM-DEMATEL shows that IoT ecosystem and IoT Big Data are the most influential or driving IoT enablers. These two enablers have been identified as the pillars for Industry 4.0. On the other side, IoT interchangeability, consumer IoT, IoT robustness and IoT interface and network capability have also been identified as the most dependent enablers for Industry 4.0.

The findings enable the industry practitioners to select the most appropriate driving enablers for an effective implementation of Industry 4.0.

The integrated approach-based hierarchical model and cause-effect relationship among IoT enablers are proposed which is a novel initiative for Industry 4.0. Moreover, two different variants of DEMATEL namely, pessimistic and optimistic are applied first time.