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In disrupted environments, the concept of digitalisation, viability, and sustainability have attracted considerable attention for the last decade. Digital, lean, and green capabilities have stimulated enormous advances in the development of industries. This paper discusses the current state of the art literature regarding sustainable and digital supply chain management performance. It reviews the relationship between digital technologies, lean, green, sustainability, and supply chain performance. A literature review approach, combined with a bibliometric analysis was adopted for robust field analysis. A set of 86 papers has been analysed and synthesised. The analysis of these papers has enabled the identification of the impact of Industry 4.0 technologies on the supply chain performance; the relationship of lean, green, and sustainability capabilities and digital supply chain; and the implications of the digital transformation of those capabilities. It presents a roadmap model integrating lean and green for viable, sustainable, and digital supply chain performance. The study is useful for academics and practitioners as it provides a roadmap framework and a solid background for integrating lean and green in the digital supply chain to achieve sustainable and viable performance as it outlines the necessity for incorporating the sustainability and viability performances in the digital supply chains. [ABSTRACT FROM AUTHOR]

This paper provides firm-level evidence on how subsidies to buyers of advanced digital production technologies work in sustaining private investments in innovation, and how such investments correlate with firms' demand for labor. By exploiting the introduction in 2017 of a fiscal incentive granted to all Italian companies purchasing tangible goods instrumental to their digital transformation, we are able to quantify the volume of the subsidized investments within the national economy, to correlate the decision to invest with ex-ante structural and strategic characteristics of the beneficiary firms, and to evaluate the labor market effects (hirings and separations) of these investments at the firm level, for different classes of workers and firms. Overall, the analysis suggests that the policy has been so far an effective means to support the advanced digital technology transformation of the Italian production system and that such transformation has been positively correlated with employment growth at investing firms. [ABSTRACT FROM AUTHOR]

Health organisations have adopted technologies since the 1960s, but only after the Industry 4.0 were such technologies systematized and organised under the H4.0 acronym. The pace at which digital information and communication applications have been developed in recent years challenge healthcare managers to choose assertively those with the largest potential impacts on their operations. In this paper, we propose using value stream mapping, a technique from the lean healthcare (LH) toolbox, to guide the choice of H4.0 digital applications that are more likely to support the improvement of value flows in healthcare organisations. We propose a three-step method, starting with mapping current and future value streams of the process under analysis, gathering data from team members on the indicated kaizen bursts and H4.0 digital applications, and finally assessing and ranking H4.0 digital applications that best support improvements and comply with attributes that characterise successful technological innovations. Our propositions are illustrated through a case study conducted in the sterilisation unit of a large public university hospital. Our findings indicate that three H4.0 digital applications should be prioritised to support the improvement of the value stream under analysis. Our method combines the simplicity of LH with more sophisticated solutions brought by H4.0. [ABSTRACT FROM AUTHOR]

The unfolding of the digital transformation, often associated with the advent of the Fourth Industrial Revolution, has been attracting increasing attention in diverse academic disciplines. The related research has already populated several special issues that represent important guideposts for future studies on the topic. However, a paper collection with an 'Industry and Innovation' perspective, dealing with how firms behave, innovate, and perform in the new industrial paradigm, is still missing. This special issue aims to fill this gap. The six research articles investigate how firms face digital transformation from three different angles, looking at its determinants, the patterns of its unfolding, and its techno-economic effects. The variety of the theoretical backgrounds, data sources, and empirical methodologies, along with the originality and managerial/policy relevance of their results, make the special issue a privileged point of view to investigate the new industrial paradigm. [ABSTRACT FROM AUTHOR]

The Fourth Industrial Revolution, also known as Industry 4.0, stems from the rapid advancement of digital technologies such as the Internet of Things and Cyber-Physical Production Systems. It has the potential to weave positive changes to firms and impact organizational structure layers. Therefore, it provides an impetus for the collaboration of factories, suppliers, and customers. Nevertheless, due to the difference of Industry 4.0 vision among companies, there is a lack of unified perception and approach of its implementation roadmap. Therefore, many firms in both developed and developing countries that step in the way of digital transformation encounter not only organizational, technological, and operational challenges but are also compelled to cope with a large deal of confusion. Hence, this paper aims to identify the main concepts, characteristics, and technology enablers related to Industry 4.0 to provide stakeholders with a clear understanding of this paradigm. It then clusters and matches the derived concepts and characteristics associated with Industry 4.0. Further, the paper provides an analysis of how these clusters are supported by technology enablers of Industry 4.0, as well as managerial implications. [ABSTRACT FROM AUTHOR]

One of the key aspects of digitalization brought by Industry 4.0 is driven by the Internet of Things. Perhaps, the most interesting component of digital transformation is Augmented Reality. Augmented reality is merging the digital and physical worlds in the same experience. This new technology is accepted and applications are initiated in various areas including manufacturing. The main usage area in manufacturing is planning, execution, and verification of the assembly and maintenance operations. Likewise, augmented reality is used in the training of inexperienced people and to guide them by remote expert support. However, the augmented reality application selection, especially for non-technology savvy manufacturing organizations is challenging. Detailed and time-consuming analyses are required to understand the key features to compare and select the most suitable augmented reality application. In this paper, the most critical nine augmented reality software selection criteria are identified. To help organizations to apply such criteria and make a selection that is most suitable for the enterprise, a multi criteria decision-making approach is suggested. The suggested method is based on a fuzzy spherical number. The complex proportional assessment method is used to calculate the rankings. Therefore, the suggested method is called SF-COPRAS. Moreover, the detailed definition of augmented reality features and terminologies is explained. Several augmented reality use-case scenarios are discussed for manufacturing organizations on their Industry 4.0 initiatives. This paper aims to guide decision makers on their augmented reality software selection journey. The offered framework aims to save time for investigating augmented reality solution features systematically and objectively. [ABSTRACT FROM AUTHOR]

The fourth Industrial Revolution is in full swing, the whole world is pondering the same question: Where is the core breakthrough? With the continuous breakthrough and extensive application of cloud computing, big data, artificial intelligence and other next-generation information technologies, One sign has emerged: digital economy is becoming a new driving force for global economic growth. The impact of digital transformation on enterprises is to improve the quality and efficiency、Improve information quality, Or spread out limited resources and reduce productivity, There is no consensus among academics. To fill that gap, this paper aims to sort out the internal mechanism of how digital transformation improves the output quality of the technological innovation of enterprises from a theoretical perspective, and to establish a digital transformation index at the micro level. On this basis, this study empirically examines how digital transformation affects the output quality of technological innovation.we adopts panel data. It uses data collected from 159 manufacturing enterprises in China. By adopting the methods of PLS structural equation and fuzzy set qualitative comparative analysis (fsQCA), it empirically tests the research model and conducts a mediation analysis through regression analysis. The findings indicated that, Digital transformation can help manufacturing enterprises to improve the output quality of their technological innovation; digital infrastructure plays a significant mediating role between digital transformation and the output quality of technological innovation; the investment of manufacturing enterprises in software and hardware digital infrastructure have a positive impact on the output quality of technological innovation. There is a complementary relationship between the two. The paper was conducted in the context of Chinese culture and can be generalized to other Asian countries. We believe that the research conclusions of this study have important practical significance for how manufacturing enterprises can effectively carry out digital transformation and improve the output quality of technological innovation. [ABSTRACT FROM AUTHOR]

Although the term Operational Excellence (OE) has been widely applied over the past few decades, its meaning is still ill-defined. This issue may be especially aggravated after the advent of the Industry 4.0 (I4.0), which introduces disruptive digital technologies that may help to overcome traditional barriers in operations management. This paper examines the concept of OE in the Fourth Industrial Revolution. For that, we conducted semi-structured interviews with experts from both academia and manufacturing companies, focusing on the shifts in OE's concepts implied by the I4.0 with regards to four key aspects (people, partnerships, processes, and products and services). Experts' responses had their content analysed through the lens of General Systems Theory, which allowed the formulation of propositions towards the conceptualization of OE in the digital transformation era. Our findings indicated that, although some attributes may remain the same, the emphasis of OE in the Fourth Industrial Revolution is likely to change. The extensive integration of digital technologies into manufacturing companies tends to entail different expectations in terms of excellence in people, partnerships, processes, and products and services. As interconnectivity and cyber-physical systems gain prominence, a more integrative and systemic perspective of OE is facilitated, expanding its meaning and understanding. [ABSTRACT FROM AUTHOR]

This paper proposes a new Readiness Model, 3D-CUBE, to assess the current state of manufacturing companies in the digital transformation context. Using a systematic literature review with 8-Steps-Search-Flow and a hypothetical-deductive framework (considering maturity as an 'input' enabler and not as an 'output'), the best information of 63 existing models was selected from 486 studies found in 10 databases. The 3D-CUBE was elaborated, with 3 dimensions (X = Organizational , Y = Technological , and Z = Process Maturity), 6 sub-dimensions, and 21 elements, including a scale 0-5 to assess the company readiness level. For the company's Data Collection, a 3D-CUBE Questionnaire was developed, which provides a radar graph and calculates the company's score with a readiness vector R=(X,Y,Z). Based on the existing model's shortcoming, 3D-CUBE is a new contribution to this research stream, to help companies in getting ready for Industry 4.0.. [ABSTRACT FROM AUTHOR]

Climate change, the growth in world population, high levels of food waste and food loss, and the risk of new disease or pandemic outbreaks are examples of the many challenges that threaten future food sustainability and the security of the planet and urgently need to be addressed. The fourth industrial revolution, or Industry 4.0, has been gaining momentum since 2015, being a significant driver for sustainable development and a successful catalyst to tackle critical global challenges. This review paper summarizes the most relevant food Industry 4.0 technologies including, among others, digital technologies (e.g., artificial intelligence, big data analytics, Internet of Things, and blockchain) and other technological advances (e.g., smart sensors, robotics, digital twins, and cyber-physical systems). Moreover, insights into the new food trends (such as 3D printed foods) that have emerged as a result of the Industry 4.0 technological revolution will also be discussed in Part II of this work. The Industry 4.0 technologies have significantly modified the food industry and led to substantial consequences for the environment, economics, and human health. Despite the importance of each of the technologies mentioned above, ground-breaking sustainable solutions could only emerge by combining many technologies simultaneously. The Food Industry 4.0 era has been characterized by new challenges, opportunities, and trends that have reshaped current strategies and prospects for food production and consumption patterns, paving the way for the move toward Industry 5.0. [ABSTRACT FROM AUTHOR]

Lean is a philosophy that helps organizations develop a continuous improvement culture by eliminating waste and minimizing the use of resources. On the other hand, Industry 4.0 is a complex high-tech model that contributes to flexible organizations using different technologies such as IoT, cloud computing, blockchain, virtual reality, and Artificial Intelligence. The concept of integrating Lean Principles and Industry 4.0 is still very recent and limited, and the literature lacks a bibliometric perspective. The integration is challenging in terms of contentment-wise and is a broad multi-dimensional research area. This study aims to analyze Lean Industry 4.0 or Lean 4.0 and Lean digital transformation literature using bibliometrics, identifying its state of art, benefits, challenges, and scientific gaps. In this study, articles published between 2010 and 2022 from the Scopus database are analyzed to identify significant publications, journals, authors, institutions, and countries based on the number of publications and frequently used keywords and subject areas. This study contributes to developing the state of art of Lean Industry 4.0 and Lean digital transformation and helps researchers and practitioners direct their future studies. The literature performance is measured based on both the number of publications and the number of citations; this bibliometric analysis covers most of the published papers in both research domains. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) empowers traditional firms to transform into Industry 4.0, enabling them to compete in an era of rapid technological advancements. However, AI adoption remains limited among Canadian firms. This research aims to identify the key dimensions of AI-driven digital transformation (AIDT) and develop a grounded theory that provides a rich and nuanced understanding of how the AIDT process unfolds within Canadian SMEs. The study reveals that the AIDT process is shaped by the interplay of five core dimensions: evaluating transformation context, auditing organisational readiness, piloting the AI integration, scaling the implementation, and leading the transformation. The first four dimensions follow a sequential, stage-like progression, while the fifth dimension is recurring and omnipresent, exerting a continuous impact on the other phases. AIDT is characterised as a path-dependent, slow evolutionary change spectrum that demands firms adapt by developing their sensing, seizing and reconfiguration capacities to evolve and sustain their evolutionary fitness. The study explores several theoretical and managerial implications that arise from the findings. [ABSTRACT FROM AUTHOR]

The increasingly unprecedented incidents (e.g. COVID-19) have made the contemporary supply chains more vulnerable to divergent risks and disruptions. Encouragingly, the recent trend of digital transformation, adoption of Industry 4.0 technologies (I4Ts), could significantly improve business processes extenuating potential risks and disruptions. Yet, there is a paucity of quantitative studies on the risk or disruption mitigation and I4Ts, specifically on agri-food industry. Using a sample of 302 firms from the Australian agri-food supply chains, we explore if the firms that adopt I4Ts experience the different impact of operational risks (supply-demand mismatch, financial and transportation) compared to others. The findings unveil that albeit such risks can significantly undermine firm performance, their negative effect is non-significant for the firms that adopt I4Ts compared to those that do not adopt. We thus suggest digital transformation as an effective way to extenuate operational risks and disruptions amid unanticipated events like COVID-19. Numerous contributions to theory and practice, plus United Nations Sustainable Development Goals (1 & 2) have been discussed. [ABSTRACT FROM AUTHOR]

While the fourth industrial revolution continues to change manufacturing enterprises all over the world, not all enabling key technologies are taught sufficiently at universities. For this purpose, a new lecture at the Montanuniversität Leoben was designed, teaching students of miscellaneous engineering disciplines, the fundamentals of digitalization and digital transformation, tailored to the requirements of the industry. To elevate the necessary data from these segments, a representative part of the Austrian metal forming companies was analyzed by conducting a large-scale survey. For the sake of teaching efficiency, a survey revealing students' knowledge regarding digitalization and digital transformation and preferred learning methods were also carried out. As a result, a stakeholder-oriented lecture was developed. Furthermore, a general framework on how innovative transdisciplinary academic lectures in engineering can be developed in an efficient, effective, and practical way was derived, which aims to close the gap between modern engineering education and required practical skills. [ABSTRACT FROM AUTHOR]

Industry 4.0 mainly focuses on the application of modern technologies (digitalization) and the changing role of human beings (digital transformation) in modern production and logistics systems. Besides the basic principles of digitalization, interconnectivity, and autonomization, the importance of human-centered decision-making processes, such as the selection of strategic suppliers, is also increasing, as complex, novel, and unstructured decisions cannot be fully computerized. In this context, there is still a lack of understanding of which formal patterns in the strategic supplier selection process will lead to better supplier performance. Until now, most of the literature emphasizes a minor number of process-related factors in the strategic supplier selection process leading to limited support for the individual decision-maker. This study introduces a cause-effect model that extends prior research by investigating the impact of process formality, as a comprehensive measurement construct of target-, information-, organization-, and heuristics-related process factors in the strategic supplier selection process on supplier performance and purchaser satisfaction. Based on the usage of variancebased structural equation modeling in a large-scale field study, a significant relationship between process formality and supplier performance as well as between process formality and purchaser satisfaction is substantiated. [ABSTRACT FROM AUTHOR]

The work looks at how regions design policies to facilitate the transition of regional innovation systems to Industry 4.0. The research analyses how regional Industry 4.0 policies should take into account the integration of the position of the regional productive system into international supply chains, the games of legitimacy and power of the actors involved in the innovation system, the institutional structures that allow the exchange of knowledge on Industry 4.0. between the agents and the connection between the synthetic knowledge base (engineering driven) and the analytical knowledge base (science driven) of the region. Through a detailed case study of the background, structure and impact of Industry 4.0 in the Spanish regions of the Basque Country and Catalonia, the work demonstrates how it is not possible to define a policy of promoting Industry 4.0 that is generalizable to all regions and how each region will have to adapt the design and implementation of its Industry 4.0 policies to the specific characteristics of its regional innovation system. Therefore the replication of policies from other regions will not be an effective mechanism for promoting Industry 4.0 since the transition to Industry 4.0 is a very regional specific and diverse process. [ABSTRACT FROM AUTHOR]