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This paper aims to identify potential barriers to Industry 4.0 adoption for manufacturers and examine the changes that must be made to production processes to implement Industry 4.0 successfully. It aims to develop technology by assisting with the successful implementation of Industry 4.0 in the manufacturing process by using smart system techniques.

Multiple case studies are used in this paper by using the smart system and Matlab, and semi-structured interviews are used to collect qualitative data.

Standardization, management support, skills, and costs have been cited as challenges for most businesses. Most businesses struggle with data interoperability. Complexity, information security, scalability, and network externalities provide challenges for some businesses. Environmental concerns are less likely to affect businesses with higher degrees of maturity. Additionally, it enables the Technical Director’s expertise to participate in the measurement using ambiguous input and output using language phrases. The outcomes of the numerous tests conducted on the approaches are extensively studied in the provided method.

In this research, a multiple-case study aims to carry out a thorough investigation of the issue in its actual setting.

Considering the problems faced by the home appliance industry in Iran, such as the increase in waste, lack of information transparency and lack of traceability of manufactured products, etc. the companies in the home appliance industry are moving toward Industry 4.0 and have been prompted to use it. On the other hand, the adoption of Industry 4.0 is associated with challenges that may lead to the failure of the adoption project and the bankruptcy of home appliance manufacturers. This study identified the challenges in the implementation of Industry 4.0 on current status and provided suitable solutions to overcome the identified challenges.

In this study, a review of the literature and background of Industry 4.0 identified the challenges that influence the adoption of Industry 4.0. To measure the current status of the identified challenges, the opinions of experts in the Iranian home appliance industry were used. To find solutions to the challenges in the adoption of Industry 4.0 in the Iranian home appliance industry, a fuzzy cognitive mapping and scenario design were used.

The results of this study show that to face the challenge of data sharing, skilled personnel should be effectively promoted among workers in the home appliance industry. The results of this study also show that the barriers to cooperation should be removed to reduce the impact of the IT Security Concerns challenge.

This paper is the first article that identifies the challenges and effective solutions for implementing Industry 4.0 in the home appliance industry.

The purpose of this study is to explore the relationship between Lean manufacturing and Industry 4.0 for small and medium size of enterprise in Japan and Brazil.

The authors conducted a quantitative survey (20 companies in Japan and 30 companies in Brazil) combined with a qualitative interview (2 companies in Japan and 15 companies in Brazil).

According to the quantitative study, 90% of them practice Lean manufacturing and 40% of them practice Industry 4.0. In the qualitative study in Brazil, four managers responded that the Lean manufacturing is a prerequisite for Industry 4.0 since any production process with waste cannot be productive, even with sophisticated digitalization technology.

The authors explored further the relationship between “defensive Digital Transformation (DX),” which is based mainly on Lean manufacturing, and “offensive DX,” which relates to customer value creation through Industry 4.0. This study clarifies the relationship and plays as a roadmap to develop better the manufacturing from current status to the vision of Industry 4.0.

This study aims to provide an overall framework that connects and explains a macro-perspective of the findings from the five studies of this special issue. Through this, we aim to answer two main questions: How can Lean and Industry 4.0 be integrated, and what are the outcomes for workers from such integration?

The special issue received 64 papers that were evaluated in multiple stages until this final sample of five papers that describe different facets of the integration between Lean and Industry 4.0 and their relationship with worker activities. In this introduction, we review the main findings of these five studies and propose an integrative view and associated propositions. A discussion provides directions to advance the field further.

The framework shows that when Lean and Industry 4.0 are integrated, companies will face two types of tensions, dialectical and paradoxical, which require different managerial approaches. By managing such tensions, the Lean-Industry 4.0 integration can help improve social performance, as well as develop systematic problem-solving and cumulative learning capabilities. Five important themes for this field of research are outlined: the importance of work routines, legitimation, competence, sense and mental flexibility.

This study brings a new theoretical perspective to the integration of Lean with Industry 4.0-related digital technologies. The results go beyond the usual view of improving operational performance and dig into the effects on workers. It also shows that the integration process relies on and can enhance human capabilities such as learning and problem-solving.

The purpose of this study is to develop a conceptual framework to understand how industry 4.0 technologies can help firms building supply chain resilience (SCR). With the increasing in turbulent business environment and other disruptive events, firms want to build robust and risk resilience supply chains. The study also explores the role of supply chain visibility (SCV) and environmental dynamism (ED) on the relationship between Industry 4.0 and SCR.

Survey data from 354 firms designated by the Indian Ministry of Petroleum and Natural Gas, as well as organizations that work with these oil and gas firms was analyzed with structural equation modelling, hierarchical linear regression and necessary conditions analysis.

The findings reveal that Industry 4.0 base technologies enable firms to develop and exploit SCV to build SCR. Furthermore, Industry 4.0 base technologies substantially correlate with SCV under the differential effect of ED, improving SCR.

The cross-sectional data restrict the generalizability of the findings to other geographies and sectors.

This study can assist managers in making well-informed decisions about the strategic use of technology to increase SCV and foster resilient supply chains.

This study aims to analyze how ready a firm is to transform into Industry 4.0 using the Readiness Index (INDI 4.0) assessment. It also investigates the differences (before and after) of the program “Making Indonesia 4.0” in 2018 in socioeconomic and demographic aspects.

The INDI 4.0 assessment involved a self-evaluation by 622 companies across 13 industry sectors, subsequently verified by the Ministry of Industry. This study incorporates discussions with industry experts to enhance the interpretation of the analytical findings.

This study explores the interrelation among the components of INDI 4.0 across different levels, assessing the readiness of each sector for Industry 4.0. The findings reveal the diverse impact of implementing Industry 4.0 in Indonesia on socioeconomic and demographic aspects. Furthermore, the study proposes several policy recommendations for the Indonesian government’s consideration.

This study’s scope is confined to the industrial context of Indonesia, as the assessment components are tailored to the specific characteristics and culture of the country’s industry. Subsequent research endeavors can leverage this study as a foundational reference, adapting the components to align with the particular interests of other nations.

Businesses, especially those in Indonesia, can employ these findings to evaluate their position in the context of Industry 4.0 transformation compared to their industry. Simultaneously, the Indonesian government can use these results as a starting point to evaluate and potentially enhance their policies related to Industry 4.0. We recommend five policy proposals for the Indonesian government: diversifying measurement models, shifting terminology, emphasizing soft skills, promoting continuous learning and implementing Center of Digital Industry Indonesia 4.0 (PIDI 4.0) initiatives.

This study offers a broad impact of Industry 4.0 implementation in socioeconomic and demographic aspects in Indonesia, such as income, job-shifting, age, educational background and gender.

To the best of our knowledge, no prior research has explored the repercussions of industrial implementation on socioeconomic and demographic facets.

The purpose of this paper is to present a practical data-based framework for the prioritization of investment in manufacturing technologies, methods and tools, and to demonstrate its applicability and practical relevance through two case studies of manufacturing firms of different industrial segments.

The proposed framework is based on network theory applied on technology adoption. For this, the database of Industry 4.0 maturity assessments of SENAI was used to develop data visualization tools named “Technology Networks”. Thus, this study is descriptive research with correlational design. Besides, the framework was applied in two companies and semi-structured interviews were carried out with domain experts.

The technology networks highlight the technological adoption patterns of six industrial segments, by considering the answers of 863 Brazilian companies. In general, less sophisticated technologies were positioned in the center of the networks, which facilitates the visualization of adoption paths. Moreover, the networks presented a well-balanced adoption scenario of Industry 4.0 related technologies and lean manufacturing methods and tools.

Since the database was not built under an experimental design, it is not expected to make statistical inferences about the variables. Furthermore, the decision to use an available database prevented the editing or inclusion of technologies. Besides, it is estimated that the technology networks given have few years for obsolescence due to the fast pace of technological development.

The framework is a tool that may be used by practicing manufacturing managers and entrepreneurs for taking assertive decisions regarding the adoption of manufacturing technologies, methods and tools. The proposition of using network theory to support decision making on this topic may lead to further studies, developments and adaptations of the framework.

This paper addresses the topics of lean manufacturing and Industry 4.0 in an unprecedented way, by quantifying the adoption of its technologies, methods and tools and presenting it in network visualizations. The main value of this paper is the comprehensive framework that applies the technology networks for supporting decision making regarding technology adoption.

This paper aims to empirically examine the impact of dynamic capabilities on Industry 4.0 capabilities in small and medium enterprises (SMEs) in Jordan. It also aims to examine the potential impact of industry 4.0 capabilities on technological innovation.

Data were collected from 210 respondents who work and own SMEs in Jordan. SmartPLS software based on the partial least squares-structural equation modeling approach was used to test hypotheses.

The findings reveal the positive effects of the three components of dynamic capabilities, including sensing, seizing and reconfiguring, on Industry 4.0 capabilities. They also confirm the positive effect of Industry 4.0 capabilities on technological innovation.

This study provides valuable practical implications and enriches the literature on the determinants of Industry 4.0 capabilities and its role in developing the dynamic capabilities of SMEs, such as technological innovation.

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.

This study explores the adoption of Industry 4.0 in developing countries' export industries, focusing on factors influencing this adoption, the moderating role of market pressure and prioritizing key factors for sustainable growth.

Based on the “TOE theory” this study has proposed a research framework to identify the factors influencing the adoption and sustainable implementation of Industry 4.0 in the export industry. This study has collected valid datasets from 387 export-oriented industries and applied SEM-ANN dual-stage hybrid model to capture linear and nonlinear interaction between variables.

Results revealed that Technical Capabilities, System Flexibility, Software Infrastructure, Human Resource Competency and Market pressure significantly influence the Adoption of Industry 4.0. Higher market pressure as a moderator also improves the Industry 4.0 adoption process. Results also pointed out that system flexibility is a gray area in Industry 4.0 adoption, which can be enhanced in the export industry to maintain a sustainable adoption and implementation of Industry 4.0.

Minute information is available on the factors influencing the adoption of Industry 4.0 in export-oriented industries. This study has empirically explored the role of influential factors in Industry 4.0 and ranked them based on their normalized importance.