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The effect of the transition toward digital technologies on today’s businesses (i.e. Industry 4.0 transition) is becoming increasingly relevant, and the number of studies that have examined this phenomenon has grown rapidly. However, systematizing the existing findings is still a challenge, from both a theoretical and a managerial point of view. In such a setting, the knowledge management (KM) discipline can provide guidance to address such a gap. Indeed, the implementation of fundamental digital technologies is reshaping how firms manage knowledge. Thus, this study aims to critically review the existing literature on Industry 4.0 from a KM perspective.

First, the authors defined a structuring framework to highlight the role of Industry 4.0 transition along with absorptive capacity (ACAP) processes (acquisition, assimilation, transformation and exploitation), while specifying what is being managed, that is data, information and/or (actual) knowledge, according to the data-information-knowledge (DIK) hierarchy. The authors then followed the systematic literature review methodology, which involves the use of explicit criteria to select publications to review and outline the stages a process has to follow to provide a transparent and replicable review and to analyze the existing literature according to the theoretical framework. This procedure yielded a final list of 150 papers.

By providing a clear picture of what scholars have studied so far on Industry 4.0 transition, in terms of KM, this literature review highlights that among all the studied digital technologies, the big data analytics technology is the one that has been explored the most in each phase of the ACAP process. A constructive body of research has also emerged in recent years around the role played by the internet of things, especially to explain the acquisition of data. On the other hand, some digital technologies, such as cyber security and smart manufacturing, have largely remained unaddressed. An explanation of the role of these technologies has been provided, from a KM perspective, together with the business implications.

This study is one of the first attempts to revise the literature on Industry 4.0 transition from a KM perspective, and it proposes a novel framework to read existing studies and on which to base new ones. Furthermore, the synthesis makes two main contributions. First, it provides a clear picture of the different digital technologies that support the four ACAP phases in relation to the DIK hierarchy. Accordingly, these results can emphasize what the literature has looked at so far, as well as which digital technologies have gained the most attention and their impacts in terms of KM. Second, the synthesis provides prescriptive considerations on the development of future research avenues, according to the proposed research framework.

The aim of this paper is to identify and analyse workforce development challenges in the digital age by first, presenting these challenges and relationship between them, and then proposing a structural model that categorizes these challenges and proposes suggestions for managers to improve human resources practices and firm performance.

Fuzzy total interpretive structural modelling (TISM) is used as the methodology, which gives an interpretive structural model by presenting direct and transitive relationship between workforce development challenges and categorizes them under autonomous, dependent, independent and linkage groups.

In total, 13 different workforce development challenges are presented in this study. Results showed that lack of IT/digital skills has a critical role in workforce development in terms of affecting other challenges. Dependent group includes requirements for longer learning time and specialized training, lack of analytical thinking and dealing with complexity, and lack of interdisciplinary thinking and acting. On the other hand, lack of ability in decentralized decision-making and shortage of workforce with adequate skillset within the labour market have more macro-impacts on others. Most of the challenges located in the linkage group, which means that most of the challenges are interrelated with each other.

Originality of this paper is presenting a systematic structure for workforce development in Industry 4.0 that considers challenges systematically.

Using a dynamic capabilities approach, the present study aims to identify and assess the effects of organizational determinants on capabilities underlying Industry 4.0 design principles, such as integration, virtualization, real-time, automation and servitization.

PLS-SEM enables a two-stage hierarchical latent variable reflective-formative model which was used for assessing the effect of organizational determinants on Industry 4.0 design principles. Five hundred six manufacturing companies constitute the effective sample, representing a population of manufacturing companies in an industrialized country.

The findings reveal that Industry 4.0 design principles extensively depend on digitalization resource availability. At the same time, companies that possess digitalization and change management capabilities tend to devote more resources to digitalization. Finally, the paper reveals that networking and partnership capability is the critical enabler for change management and digitalization capabilities.

The paper provides empirical evidence that the successful development of Industry 4.0 design principles and their underlying integration, virtualization, real-time, automation and servitization capabilities are resource dependent, requiring significant upfront investment and continuous resource allocation. Further, the study implies that companies with networking and partnership, change management and digitalization capabilities tend to allocate more resources for Industry 4.0 transformation.

Exclusively focusing on empirical research that reported applied insights into determinants of Industry 4.0 design principles, the study offers unique implications for promoting Industry 4.0 digital transformation among manufacturing companies.

In the intellectual capital literature, no studies have examined the causal relationship between Italian Fintech companies' performance and intellectual capital, especially the impact of digital industrialization on human capital. This paper aims to fill this gap in measuring human capital efficiency in the Italian Fintech market.

The authors adopt Pulic's model and define the intellectual capital through three components (human capital, structural capital and capital employed) and perform an exploratory analysis of the Italian Fintech companies by using principal component analysis. Then the authors investigate the effects of the intellectual capital and its components on the Italian Fintech companies' performance by using parametric and nonparametric regression models.

Results of regression models reveal that human capital and employed capital are positively related to the companies' performance, except for the structural capital.

The study focuses on the Italian level, and future research could be extended to different European countries or to the global Fintech market. Moreover, it is advised to explore more components that contribute to intellectual capital measurement inside the companies operating in the 4.0 industrial revolution, such as the innovative capital and the relational capital.

This study proposes a new vision for managerial procedures to find which features are critical for achieving profitability in this digital era. The study offers interesting reflections on the management decisions for both companies and public decision-makers. Results suggest that, among intellectual capital components, human capital plays a strategic role for the knowledge-intensive companies that are interested in potentiating their performance and competitiveness. Furthermore, this study finds that human capital is critical factor for achieving profitability in this digital era.

The Fintech sector is one that most benefited from the Digital Revolution, and if it is adequately managed, it can bring great benefits in terms of major employment, especially for the young population, and bring major financial inclusiveness all over the world.

This is the first study that examines the Italian Fintech market and analyzes the dependence relationship between companies' performance and intellectual capital components, identifying the role of human capital in a new completely digital sector. The analysis findings are strategic for the business decisions-making process.

This paper aims to design, build and evaluate a blockchain platform in the accounting domain, taking an ecosystem perspective. To achieve this aim, the research provides evidence for developing a decentralised architecture rooted on blockchain technology, designing a proof of concept and modelling an accounting blockchain-based system.

Moving from the analysis of previous literature and leveraging on the design science approach, this paper provides a framework grounded on the main pillars of blockchain and accounting functions, identifying technical and non-technical issues that must be addressed embrace blockchain technology's full potential.

We propose and discuss a conceptual framework for a blockchain-based accounting context, moving from the identification of a typical accounting scenario. The framework is organised around three scalable levels: the first level is a technological infrastructure based on a distributed database with peer-to-peer storage; second, in the intermediate level, increasing control levels are assured through permissions and validation and third, in the higher level, the system provides the integration of business and security applications. The deployment of this system relies on a private network of nodes that validates transactions.

The proposed conceptual framework about blockchain development in accounting allows closing the knowledge gap between blockchain developers and accounting experts by suggesting technological and strategic issues for practitioners.

We provide practical guidelines to design and adopt blockchain in the accounting domain.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.

The research aims to develop an assessment framework that evaluates critical success factors (CSFs) for the Quality 4.0 (Q 4.0) transition among Indian firms.

The authors use the fuzzy-Delphi method to validate the results of a systematic literature review (SLR) that explores critical aspects. Further, the fuzzy decision-making trial and laboratory (DEMATEL) method determines the cause-and-effect link. The findings indicate that developing a Q 4.0 framework is essential for the long-term success of manufacturing companies. Utilizing the power of digital technology, data analytics and automation, manufacturing companies can benefit from the Q 4.0 framework. Product quality, operational effectiveness and overall business performance may all be enhanced by implementing the Q 4.0 transition framework.

The study highlights significant awareness of Q 4.0 in the Indian manufacturing sector that is acquired through various means such as training, experience, learning and research. However, most manufacturing industries in India still follow older quality paradigms. On the other hand, Indian manufacturing industries seem well-equipped to adopt Q 4.0, given practitioners' firm grasp of its concepts and anticipated benefits, including improved customer satisfaction, product refinement, continuous process enhancement, waste reduction and informed decision-making. Adoption hurdles involve challenges including reliable electricity access, high-speed Internet, infrastructure, a skilled workforce and financial support. The study also introduces a transition framework facilitating the shift from conventional methods to Q 4.0, aligned with the principles of the Fourth Industrial Revolution (IR).

This research exclusively examines the manufacturing sector, neglecting other fields such as medical, service, mining and construction. Additionally, there needs to be more emphasis on the Q 4.0 implementation frameworks within the scope of the study.

This may be the inaugural framework for transitioning to Q 4.0 in India's manufacturing sectors and, conceivably, other developing nations.

Industry 4.0 or digitization, from a regional innovation system (RIS) and policy perspective to improve regional innovation, is over-looked. Specifically, this paper aims to focus on analyzing the nascent European Commission (EC) digital innovation hub (DIH) program, designed for fostering transition into Industry 4.0 in regions and facilitating new path development.

Empirically, 10 Spanish DIH is explored through interviews and secondary data analysis.

The results suggest that DIHs despite their emerging and trial-and-error stage are designed for promoting multi-actor collaborative platforms including non-local actors to stimulate transition into Industry 4.0 by promoting place-based collaboration alliances that respond to local/regional contextual specificities and demands. These regional-based platforms facilitate public-private partnerships that co-design policy initiatives resulting from co-participation and negotiation of spatially-bounded oriented initiatives for digitizing.

The authors answer: what are the key characteristics of emerging European-level regional innovation policies aimed at facilitating Industry 4.0 in regions? This is the first study on the topic.

The purpose of this paper is to conduct a state-of-the-art review of the ongoing research on the Industry 4.0 phenomenon, highlight its key design principles and technology trends, identify its architectural design and offer a strategic roadmap that can serve manufacturers as a simple guide for the process of Industry 4.0 transition.

The study performs a systematic and content-centric review of literature based on a six-stage approach to identify key design principles and technology trends of Industry 4.0. The study further benefits from a comprehensive content analysis of the 178 documents identified, both manually and via IBM Watson’s natural language processing for advanced text analysis.

Industry 4.0 is an integrative system of value creation that is comprised of 12 design principles and 14 technology trends. Industry 4.0 is no longer a hype and manufacturers need to get on board sooner rather than later.

The strategic roadmap presented in this study can serve academicians and practitioners as a stepping stone for development of a detailed strategic roadmap for successful transition from traditional manufacturing into the Industry 4.0. However, there is no one-size-fits-all strategy that suits all businesses or industries, meaning that the Industry 4.0 roadmap for each company is idiosyncratic, and should be devised based on company’s core competencies, motivations, capabilities, intent, goals, priorities and budgets.

The first step for transitioning into the Industry 4.0 is the development of a comprehensive strategic roadmap that carefully identifies and plans every single step a manufacturing company needs to take, as well as the timeline, and the costs and benefits associated with each step. The strategic roadmap presented in this study can offer as a holistic view of common steps that manufacturers need to undertake in their transition toward the Industry 4.0.

The study is among the first to identify, cluster and describe design principles and technology trends that are building blocks of the Industry 4.0. The strategic roadmap for Industry 4.0 transition presented in this study is expected to assist contemporary manufacturers to understand what implementing the Industry 4.0 really requires of them and what challenges they might face during the transition process.

The digital transformation under Industry 4.0 is complex and resource-intensive, making a strategic digitalization guideline vital to small and medium-sized enterprises' success in the Industry 4.0 transition. The present study aims to provide manufacturing small and medium-sized enterprises (SMEs) with a guideline for digital transformation success under Industry 4.0.

The study first performed a content-centric literature review to identify digital transformation success determinants. The study further implemented interpretive structural modeling to extract the order at which the success determinants should be present to facilitate the SMEs’ digital transformation success optimally. The interpretive model and interpretive logic knowledge base matrix were also used for developing the digital transformation guideline.

Eleven success determinants are vital to SMEs’ digital transformation efforts. For example, results revealed that external support for digitalization is the first step in ensuring digital transformation success among SMEs, while operations technology readiness is the most inaccessible success determinant.

The study highlights the degree of importance of the 11 success determinants identified, which magnifies each determinant's strategic priority based on its driving power and dependence power. Theorizing the dependent variable of “digital transformation success” and quantitatively measuring the extent to which each success determinant contributes to explaining “digital transformation success” offers an exciting opportunity for future research.

Digital transformation success phenomenon within the Industry 4.0 context is significantly different from the digitalization success concept within the traditional literature. The digital transformation under Industry 4.0 is immensely resource-intensive and complex. Smaller manufacturers must have specific capabilities such as change management and digitalization strategic planning capability to reach a certain degree of information, digital, operations and cyber maturity.

The digital transformation success guide developed in the study describes each success determinants' functionality in relation to other determinants and explains how they might contribute to the digital transformation success within the manufacturing sector. This guide enables smaller manufacturers to better understand the concept of manufacturing digital transformation under Industry 4.0 and devise robust strategies to steer their digital transformation process effectively.