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This chapter reflects on the understanding of the phenomenon known as Smart Industry, Industry 4.0, fourth industrial revolution, and many other labels. It does so by reflecting on the issue of terminology, as well as the existing diversity regarding the description of the phenomenon. The issue of meaning is addressed by assessing the results from Culot, Nassimbeni, Orzes, and Sartor (2020) and Habraken and Bondarouk (2019) which are, subsequently, used to develop a workable description. Findings from the two assessed studies raise the question of whether a workable construction of the phenomenon is to be understood as the key technologies or the distinctive developments? A question without a definitive answer, but I will present my view by taking inspiration from the manner in which the prior industrial revolutions are commonly understood. This leads to a, still multifaceted though, more focused understanding of the phenomenon. The insights, formulated proposition and developed model stemming from the reflection of terminology and meaning of the phenomenon helps move the current technology-related phenomenon forward. They assist with the establishment of well-documented papers. A critical aspect if we aim to understand how management will look like in the era of this phenomenon.

The purpose of this paper is to introduce, summarize and combine the results of 11 articles in a special issue on the implementation of Industry 4.0. Industry 4.0 emerged as a phenomenon about a decade ago. That is why, it is interesting now to explore the implementation of the concept. In doing so, four research questions are addressed: (1) What is Industry 4.0? (2) How to implement Industry 4.0? (3) How to assess the implementation status of Industry 4.0? (4) What is the current implementation status of Industry 4.0?

Subgroups of articles are formed, around one or more research questions involving the implementation of Industry 4.0. The articles are carefully analyzed to provide comprehensive answers.

By comparing definitions systematically, the authors show important aspects for defining Industry 4.0. The articles in the special issue explore several cases of manufacturing companies that implemented Industry 4.0. In addition, systematic approaches to aid implementation are described: an approach to combine case-study results to solve new implementation problems, approaches to assess readiness or maturity of companies regarding Industry 4.0 and surveys showing the status of implementation in larger samples of companies as well as showing relationships between company characteristics and type of implementation. Small and large firms differ considerably in their process of implementing Industry 4.0, for example.

This special issue discusses implementation of Industry 4.0. The issue is limited to 11 articles, each of which with its own strengths and limitations.

The practical relevance of the issue is that it focuses on the implementation of Industry 4.0. Cases showing successful implementation, measurement instruments to assess degree of implementation and advice how to build a database with cases together with large-scale studies on the state of implementation do provide a wealth of information with a large managerial relevance.

The paper introduces an original take on Industry 4.0 by focusing on implementation. The special issue contains both literature reviews, articles describing case studies of implementation, articles developing systematic measurement instruments to assess degree of implementation and some articles reporting large-scale studies on the state of implementation of Industry 4.0 and thereby combine several perspectives on implementation of Industry 4.0.

Internet of Things’ (IoT’s) first wave started with tracking services for better inventory management mainly using radio frequency identification (RFID) technology. Later on, monitoring services became one of the major interests, including sensing technologies, and then more actuation for remote control-type of IoT applications such as smart homes, smart cities and Industry 4.0. In this paper, the authors focus on the RFID technology impairment. They propose to take advantage of the mature IoT technologies that offer native service discovery such as blutooth or LTE D2D ProSe or Wifi Direct. Using the automatic service discovery in the new framework will make heterogeneous readers aware of the presence of other readers and this will be used by the proposed distributed algorithm to better control the multiple RFID reader interference problem. The author clearly considers emerging Industry 4.0 use case, where RFID technology is of major interest for both identification and tracking. To enhance the RFID tag reading performance, collisions in the RFID frequency should be minimized with reader-to-reader coordination protocols. In this paper, the author proposes a simple distributed reader anti-collision protocol named DiSim that makes use of proximity services of IoT network and is compliant with the current RFID standards. The author evaluates the efficiency of the proposal via simulation.

In this paper, the author proposes a simple distributed reader anti-collision protocol named DiSim that makes use of proximity services of IoT network and is compliant with the current RFID standards. The author evaluates the efficiency of the proposal via simulation to study its behavior in very dense and heterogeneous RFID environments. Specifically, the author explores the coexistence of powerful static readers and small mobile readers, comparing the proposal with a standard ETSI CSMA method. The proposal reduces significantly the number of access attempts, which are resource-expensive for the readers. The results show that the objectives of DiSim are met, producing low reader collision probability and, however, having lower average readings per reader per time.

DiSim is evaluated with the ETSI standard LBT protocol for multi-reader environments in several environments with varied levels of reader and tag densities, having both static powerful RFID readers and heterogeneous randomly moving mobile RFID readers. It effectively reduces the number of backoffs or contentions for the RFID channel. This has high reading success rate due to the avoided collisions; however, the readers are put to wait, and DiSim has less average readings per reader per time. As an additional side evaluation, the ETSI standard LBT mechanism was found to present a good performance for low-density mid-coverage scenarios, however, with high variability on the evaluation results.

To show more results, the author needs to do real experimentation in a warehouse, such as Amazon warehouse, where he expects to have more and more robots, start shelves, automatic item finding on the shelve, etc.

Future work considers experimentation in a real warehouse equipped with heterogeneous RFID readers and real-time analysis of RFID reading efficiency also combined with indoor localization and navigation for warehouse mobile robots.

More automatization is expected in the future; this work makes the use of RFID technology more efficient and opens more possibilities for services deployment in different domains such as the industry which was considered not only in this paper but also in smart cites and smart homes.

Compared to the literature, the proposal offers the advantage to not be dependent on a centralized server controlling the RFID readers. It also offers the possibility for an existing RFID architecture to add new readers from a different manufacturer, as the readers using the approach will have the possibility to discover the capabilities of the new interaction other RFID readers. This solution takes advantage of the available proximity service that will be more and more offered by the IoT technologies.

Industry 4.0 is assumed to yield extensive industry-spanning opportunities. However, exploiting these opportunities requires a targeted implementation of Industry 4.0. The purpose of this paper is to generate a deeper understanding of relevant implementation action. Existing recommendations are mostly general, highly aggregated and difficult to grasp. Yet, specific and concrete actions that need to be taken to accelerate the realization of Industry 4.0 are essential.

The article uses 13 semi-structured in-depth expert interviews as the source of empirical data. The interviews were conducted with managers from Industry 4.0-experienced German manufacturing companies. All interviews are analyzed using qualitative content analysis.

The study reveals relevant and targeted aspects for Industry 4.0 implementation: the development of Industry 4.0-specific know-how, securing financial resources, integrating employees into the implementation process and establishing an open-minded and flexible corporate culture. Further aspects include comprehensive planning processes, cooperation with external partners, proper handling of data interfaces, interdisciplinary communication, an adaptable organizational structure and data security.

The paper is limited to German manufacturing enterprises and should be transferred to other industries and countries.

The study supports managers to effectively implement Industry 4.0 within their organizations and consequently benefit from Industry 4.0 and derives recommendations for future research.

The paper is among the first to give specific and concrete examples for lessons learned from Industry 4.0 implementation, directly obtained from industrial application.

The purpose of this paper was to assess and determine the impact of the five core technologies of Industry 4.0 (3D Printing, Big Data Analytics, Cloud Computing, Internet of Things (IoT) and Robotics) on the organizational performance of the retail industry in the context of Pakistan.

Pakistan's retail industry was chosen as the target sector, and the target population was composed of senior-level employees, including managers from first-level positions to top-level positions, as well as subordinate employees working under the supervision of first-level managers, possessing the technological know-how of Industry 4.0. The data were collected through a matrix-based survey questionnaire that was based on a five-point Likert scale, ranging from “strongly agree” to “strongly disagree.” The process of data analysis was conducted using IBM SPSS Statistics.

The findings obtained by this research work showed a significant relationship among the five core pillars of Industry 4.0 and the organizational performance of Pakistan's retail industry. Besides, the obtained findings provided preliminary evidence that Industry 4.0's disruptive technologies, particularly, 3D printing, big data analytics, cloud computing, IoT and robotics, could help Pakistan's retail industry solve various problems and challenges, such as meager revenues, increased expenses and unorganized systems.

The present study extended the theoretical body of knowledge through studying and examining Industry 4.0's five crucial factors that significantly contribute to the service sector, particularly, the retail industry, of the big emerging markets (BEM) economies, including Pakistan.

The purpose of this paper is to determine the factors that affect Industry 4.0 applications, the expected impacts of Industry 4.0 applications in companies and to analyze the importance of these factors and the importance of expected impacts correlatively.

This paper provides an empirical analysis of the factors affecting the adoption of Industry 4.0 transformation and its impacts on the companies. The paper is based on 103 valid answers to a questionnaire-survey distributed among companies in Turkey. The Pearson correlation analysis was conducted to determine the correlation between independent variables and dependent variables. Regression analyses were used to test the proposed hypotheses. A multiple regression analysis was used to investigate the causal relationship between independent and dependent variables. Linear regression method and stepwise regression method was employed for regression analyses. The factors that influence Industry 4.0 applications were determined as company size, technological level of products, budget allocation for R&D department, level of lean applications, level of agility/flexibility and level of automation; and the expected impacts of Industry 4.0 applications were determined as traceability of production processes, traceability of supply chain, flexibility of supply chains, communication between the partners of supply chain, productivity, real-time data analysis, integration between companies and integration in the company according to the literature review

The results of this research study revealed that, there is a stronger relationship between level of Industry 4.0 transformation and level of automation than there is between Industry 4.0 transformation and the other independent variables. From the analyses conducted, it can be stated that budget allocation for R&D and level of lean applications and level of automation had greater impacts on Industry 4.0 transformation than company size has. The independent variables included in the regression analysis had a positive effect on Industry 4.0 transformation of companies. However the effects of company size, technological level of products and level of agility/flexibility on Industry 4.0 transformation was weak. When the impacts of Industry 4.0 on companies were analyzed, it can be stated that there is a stronger relationship between Industry 4.0 transformation and real-time data analysis, traceability of production processes, integration in companies and productivity than there is between Industry 4.0 transformation and integration between companies, traceability of supply chains, flexibility of supply chains and communication between the partners of supply chain. It was determined that Industry 4.0 transformation generally impacts internal factors of company, while Industry 4.0 had limited impacts on the supply chains.

Although there are studies that separately investigated the factors affecting Industry 4.0 transformation and the impacts of Industry 4.0 transformation on companies, the present study provides important contributions to the literature in terms of considering the importance levels of the factors affecting Industry 4.0 transformation and the importance level of impacts of Industry 4.0 transformation on companies as a whole and in relation to each other.

This paper studies the impact of certain characteristics of companies to training programs in the Industry 4.0 (I4.0) context. Partial objective is to rank the main human barriers companies have to overcome so that they can digitalize.

To accomplish the objectives, a closed-ended questionnaire was sent to Slovak and Italian companies and analyzed using statistical nonparametric tests. The partial objective was achieved using the so-called Henry-Garrett’s ranking method.

Results show the significance impact of companies’ characteristics such as foreign participation and company dimension on training practices whereas economic situation (financial health) seems not to influence it.

The study may lack generalizability as only 102 answers were collected. Perhaps, the outcome would be different with another sample from other countries. Moreover, using closed-ended questions, certain features may not have been covered.

Companies should always guarantee training for the resulted benefits. It is fundamental for organizations to find a time gap, resources and professionals who can teach these programs. Even when companies are incurring financial problems they should do so since human capital development can increase their competitiveness. The most critical barriers should be carefully addressed by companies. Training can help to overcome I4.0 barriers related to Human Resources (HR) and contribute to its growth.

This paper gives insights of the impact of certain characteristics of companies to the training programs. Because past research has limited their analysis on the identification of barrier, its novelty lies in the attempt to rank the most significant barriers among those detected by other authors in previous research.

This paper has two objectives: first, to investigate the state-of-the-art of Industry 4.0 (I4.0) adoption in Italian manufacturing firms and, second, to understand variations in technologies implemented and business functions involved, benefits perceived, and obstacles encountered in I4.0 implementation over a three-year period.

The approach adopted in this research is descriptive, nesting longitudinal features. The paper presents a descriptive survey of 102 Italian manufacturing companies. The authors also evaluated non-response biases. The longitudinal approach was achieved by comparing the responses of the 40 sub-samples in common with a second similar survey launched three years prior, which aimed to identify patterns of evolution in the adoption of the I4.0 paradigm.

Survey findings demonstrate that Italian manufacturing companies still have limited awareness of I4.0 technologies, and the adoption of I4.0 technologies differs per technology. Company size and information system coverage level are the two factors that impact the company's technology adoption level. The comparative study shows that knowledge and adoption increase in a three-year interval with an unbalanced involvement of business functions regarding the I4.0 transformation. Indeed, companies are still seeking I4.0 solutions to reduce costs and lead times primarily, and the benefits perceived by companies are shown to be related to the number of I4.0 technologies in use. Finally, when companies put the I4.0 technologies into practice, competence is constantly considered the most significant barrier.

This paper aims at conducting a thorough investigation into the development of I4.0 adoption in manufacturing companies. The main limitation of this study concerns the limited number of subjects involved in the longitudinal study (40) and the focus on a limited geographical area (Italy). In addition, more I4.0 technologies could also be incorporated into the survey protocol to gain further insight into I4.0 development.

The authors provide one of the first attempts to assess the variations of I4.0 implementation concerning technology adoption, business function involvement, and the alteration of benefits and obstacles. Several studies presented in the literature highlight the lack of longitudinal studies investigating the development of the I4.0 paradigm in a specific manufacturing context: this paper is the attempt at filling this gap.

This paper aims to examine the moderated mediation effect of the lack of students’ socialization (as one of the COVID-19 consequences) and the university reputation on the relationship between the service innovation and students satisfaction. The relationship between students satisfaction and their loyalty is also examined.

This study adopts a quantitative research approach, whereas the study population consists of all universities’ students in Lebanon. Data were collected from 201 students, elected depending on snowballing sample technique. A questionnaire was used to gather data, whereby partial least squares structural equation modeling was used to check the proposed scales validity and the relationships between the study variables.

The findings reveal a significant direct effect for university’s service innovation on students satisfaction and an indirect effect through the mediation role for university reputation. Moreover, an evidence for weak negative significant effect for lack of socialization on students satisfaction exists. Whereby, lack of socialization does not moderate the relationship between university service innovation and students satisfaction. Finally, students satisfaction has a significant positive effect on their loyalty.

This paper advances the service innovation literature in the higher education sector. In addition, the paper might be the first paper to address the influence of lack of socialization as one of the COVID-19 consequences on students satisfaction. Furthermore, areas for future research are suggested.

Industry 4.0 (I40) is an open window of opportunity for Turkey, a developed country, to eliminate technological dependence and produce with maximum productivity. However, I40, which corresponds to the fourth wave of industrial revolutions, brings both opportunities and challenges. In this context, this study aims to reveal the foresight of managers in the Turkish white goods industry (TWGI) regarding the advantages and challenges of I40 and compare them with the literature.

The Delphi method was used for the study. Data were collected from managers of companies that are members of the White Goods Suppliers Association (BEYSAD). Seventy managers from 55 companies participated in the first round, and 19 managers participated in the second round of Delphi.

The results show that the most frequently cited advantages are productivity/resource efficiency, data and information-enabled effectiveness/productivity, quality 4.0 and competitiveness/strategy. The most frequently mentioned challenges are financial resources/investment, employee qualification/training, technical/processual challenges and organizational transformation/leadership.

The sample was limited to the managers of the TWGI.

Players in similar ecosystems and policymakers should consider the advantages and respond to potential challenges when creating roadmaps, taking the necessary steps and positioning themselves in the marketplace. In particular, the TWGI – Turkey’s showcase in international markets – should consider the undeniable benefits of the I40 transition to increase innovation.

The findings for the first time highlight the advantages and challenges of I40 in an industry in Turkey, and they will benefit the TWGI, which is among the leaders in Turkey in terms of digital maturity and innovation in its journey to I40.