Industry 4.0 implementation and Triple Bottom Line sustainability: An empirical study on small and medium manufacturing firms

Prospects and current scenario of industry 4.0 in Bangladeshi textile and apparel industry

This study aims to explore the scopes and challenges, rank the challenges, and provide strategic solutions for adopting Industry Revolution 4.0 (IR 4.0) in Bangladesh's textile and apparel industry. A random survey was administered to a total of 142 factories in Bangladesh. Both quantitative and qualitative methods of analysis were used in this study. The survey includes questions on important study variables, such as big data, smart factories, cyber-physical systems (CPS), the Internet of Things (IoT), interoperability, textile production, and industry performance. The Variable Destination Multiple Access (VDMA) Model has been adopted to design the questionnaire, focusing on qualitative and quantitative questions. The survey dataset was investigated through SmartPLS 4.0 by normality and confirmatory tests. Likert scale data have been analyzed through IBM SPSS software version 26.0 by the exploratory factor analysis method to rank the IR 4.0 adoption variables. Analysis of the survey data indicates the level of adoption of Industry 4.0 in terms of organizational strategy, investment, infrastructure, IT (Information Technology), Ready Made Garments (RMG) skilled workers, smart operations, and smart factories. The study shows that the variable "Review of the strategy using indicators" got the highest ranking in the external factor, 0.791. This clearly indicates that strategy formulation is the topmost priority among other IR 4.0 adoption variables. Consequently, "digital integration" got the lowest loading at 0.620, as IR 4.0 digital technology adoption is very low. The overall maturity level for IR 4.0 adoption in the Bangladesh textile and apparel industry is 1.91 on a 5-point scale, indicating a low adoption level. This study can help concerned policymakers and industrialists who want to implement Industry 4.0 in the textile and RMG sectors to stay competitive in the global market. Alongside this study, it also summarizes the IR 4.0 adoption level in 9 broad categories.

Analysis of barriers affecting Industry 4.0 implementation: An interpretive analysis using total interpretive structural modeling (TISM) and Fuzzy MICMAC

The purpose of this study is to build a structural relationship model based on total interpretive structural modeling (TISM) and fuzzy input-based cross-impact matrix multiplication applied to classification (MICMAC) for analysis and prioritization of the barriers influencing the implementation of Industry 4.0 technologies. 10 crucial barriers that affect the deployment of Industry 4.0 techniques are identified in the literature. Also, the Fuzzy MICMAC approach is applied to classify the barriers. The importance of TISM over traditional interpretive structural modeling (ISM) is shown in this work. Results proved that the barriers, namely IT infrastructure, lack of cyber physical systems, and improper communication models, are identified as the most dependent barriers, and the barriers of lack of top management commitment and inadequate training are identified as the most driving barriers. This study makes it easier for decision-makers to take the necessary steps to mitigate the barriers. The bottom level of the TISM hierarchy is occupied by barriers that need more attention from top management in order to be effectively monitored and managed. This study explains the steps to execute TISM in detail, making it easy for researchers and practitioners to comprehend its principles.

The impact of sustainable public procurement on corporate ESG performance-The Chinese evidence

Public procurement is an important bridge between public demand and market supply and may affect corporate behavior. However, in the advocacy of sustainable development, the extant research has rarely combined sustainable public procurement (SPP) with corporate ESG performance, to explore whether governments have contributed to the development of sustainable corporate performance through their sustainable procurement activities. This paper fills in the gap by matching the actual implementation of SPP of 42,369 projects in China over 2015~2020 with 20,125 corporate ESG performance data, to analyze the relationship between SPP implementation and corporate ESG performance. The results show that the implementation of SPP has a significant positive impact on corporate ESG performance. Further heterogeneity analysis reveals that the impact is stronger in China's eastern and central regions than in other regions, and corporates at a mature stage are more likely to follow the government sustainable behavior. In addition, the implementation of SPP has a long-term effect on corporate ESG performance. The above findings have important policy implications: firstly, there is a better role for government to play as the "invisible hand", to participate in the market economy; Specifically, SPP policy should be added to government policy tool box to improve corporate ESG performance in addition to disclosure requirement, and the SPP policy employed should in particular attend to the "missing sectors" of sustainability in SPP for the good of corporate ESG; secondly, the government should implement differentiated policies tailored to the region's economic development conditions and corporate development characteristics; thirdly, a long-term evaluation mechanism should be established so that the government can play a more long-term demonstration and leading role.

Role of smart technologies for implementing industry 4.0 environment in product lifetime extension towards circular economy: A qualitative research

Since sustainability has grown in prominence over the past two decades, the impetus for improving the lifetime of durable and semi-durable manufactured goods has never been stronger. In order to decrease the level of natural resources extraction, as well as the increasing amounts of residuals and solid waste, product lifetime extension (PLE) strategies, such as improved design, maintenance, redistribution, access, and recovery, show great potential, especially if paired with smart technologies in the Industry 4.0 (I4.0) environment. Much research has investigated the contribution of I4.0 technologies to sustainability and the circular economy. Yet, only a few studies have focused on exploring the contribution of smart technologies to the specific area of PLE. This paper advances knowledge regarding the impact of four specific types of smart technologies on PLE strategies: Additive Manufacturing, the Internet of Things, Big Data, and Artificial Intelligence. This study consists of exploratory qualitative research to explore the mechanism underlying the implementation of these I4.0 technologies in PLE for a circular economy. Qualitative data is collected through twenty semi-directed, in-depth interviews with business leaders and executives involved in product development and research and development (R&D) in Quebec, Canada. An analytical approach parented to grounded theory and consisting of open, axial, and selective coding led to identifying four emerging themes explaining how focal smart technologies contribute to PLE. These include (1) empowerment and acceleration of R&D (improvement of prototypes, prototype validation), (2) smarter production (tooling assistance, manufacturing assistance), (3) automation of managerial and operational processes (automation of management, automation of production), and (4) help with decision-making (anticipation, identification, and solving of problems). These findings have broad relevance for sustainability theory and practice by highlighting the specific mechanisms through which technology contributes to product sustainability.

Integrating Industry 4.0 and Total Productive Maintenance for global sustainability

Purpose

The integration of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) is an emerging model, and the global pressure of various stakeholders raises scepticism of any emerging model towards providing sustainability. Therefore, this research aims to identify and rank the potential significant drivers of an integrated model of I4.0 and TPM to guide manufacturing enterprises towards sustainability.

Design/methodology/approach

This research follows a four-phase methodology including literature review and expert opinion to select the sustainability indicators and I4.0-integrated TPM key drivers, followed by employing the analytic hierarchy process approach for weight determination of sustainability indicators. The research then deploys the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritise the I4.0-integrated TPM key drivers based on their effect on various sustainability indicators. Finally, a sensitivity analysis is conducted to check the robustness of the TOPSIS.

Findings

The findings establish the top five most influential key drivers of an I4.0-integrated TPM system, which include top management support, formal I4.0 adoption program, mid-management involvement and support, solid TPM baseline knowledge and high engagement of the production team. These top drives can lead manufacturing firms towards sustainability.

Research limitations/implications

The digitalisation of shop floor practices, such as TPM, could be adapted by shop floor managers and policymakers of manufacturing companies to deliver sustainability-oriented outcomes. In addition, this research may aid decision-makers in the manufacturing sector in identifying the most important drivers of I4.0 and TPM, which will assist them in more effectively implementing an integrated system of I4.0 and TPM to practice sustainability. The scope of TPM applicability is wide, and the current research is limited to manufacturing companies. Therefore, there is a huge scope for developing and testing the integrated system of I4.0 and TPM in other industrial settings, such as the textile, food and aerospace industries.

Originality/value

This research makes a first-of-its-kind effort to examine how an I4.0-integrated TPM model affects manufacturing companies' sustainability and how such effects might be maximised.

Business transformation through sustainability based on Industry 4.0

The growing global concern with sustainability has driven companies to rethink their business model and seek new ways to operate and face this challenge. Industry 4.0 (I4.0) has shown itself capable of contributing to the development or reformulation of organizational processes to make them more competitive and sustainable. Thus, this article aims to propose drivers for the development of corporate sustainability via I4.0. To this end, a literature review and content analysis were used as research methods to identify and analyze, in recent scientific literature, boosting elements that enable organizational processes to become more sustainable via I4.0. Based on these elements, six drivers were systematized and proposed: strategy; product and process design; energy and material resources; people; smart production; and supply chain. Each driver was discussed in light of the scientific literature to generate recommendations for companies to develop the economic, social, and environmental dimensions of sustainability. The main theoretical-scientific contribution of this work is the deepening and expansion of the knowledge block that articulates corporate sustainability with I4.0, which strengthens the basis for the development of new research on these topics and creates a reference for the analysis and discussion of empirical studies. As an applied-managerial contribution, the drivers proposed in this work will provide organizations and their managers with a point of reference to effectively move towards sustainability, making their businesses greener, fairer, and more profitable. A limitation of this study is that the proposed drivers were based on the 30 most cited articles and did not consider other sources, such as documentation from companies. Therefore, for future studies, we suggest increasing the article base and include organizational repositories and identify how SMEs can become sustainable through I4.0 in a way that strengthens the social dimension of sustainability.

The Effects of Broadband Infrastructure on Carbon Emission Efficiency of Resource-Based Cities in China: A Quasi-Natural Experiment from the "Broadband China" Pilot Policy

Resource-based cities (RBCs) face serious environmental pollution, and there are efforts to try to overcome those challenges by transforming industrial structure through investing in new technologies. Based on the panel data of 114 prefecture-level resource-based cities in China, this paper uses the difference-in-differences (DID) method to identify the effects of the “Broadband China” pilot policy on the carbon emission efficiency of resource-based cities. The results show that the “Broadband China” pilot policy has a significant effect on the improvement of carbon emission efficiency of resource-based cities, and the results are still valid after parallel trend test, PSM-DID estimation and placebo test. This study also finds that there are differences in the carbon emission efficiency of different locations and types of resource-based cities. In addition, the results of the mechanism analysis show that the “Broadband China” pilot policy can promote the improvement of carbon emission efficiency by promoting the upgrading of the industrial structure, the accumulation of human capital and the improvement of the level of urban innovation of resource-based cities. The findings provide a reference for China’s resource-based cities to develop the Broadband infrastructure, realize industrial upgrading, accumulate human capital and improve urban innovation level, and promote low-carbon transformation and improve carbon emission efficiency.

Comparative analysis of variables that influence behavioral intention to use MOOCs

The purpose of this research was to investigate the key factors that influence behavioral intention to adopt MOOCs. The study was conducted in three countries namely, Poland, Thailand, and Pakistan. The study was considered significant considering the advancements in technology that have had an unprecedented impact on education, and the need to conduct learning online due to the COVID-19 to pandemics. The research adopted the Unified Theory of Acceptance and Use of Technology (UTAUT2) and extended it by including other variables including culture, social distancing, and absorptive capacity. The study was conducted using the quantitative methodology, where the data was collected using a structured questionnaire. The data was collected from a sample from each of the three countries, and sample sizes were 455, 490, and 513 for Poland, Thailand, and Pakistan respectively. The data were analyzed using Structural Equation Modeling (SEM) and multi-group SEM analysis. The results of the study indicated that effort expectancy and culture significantly and positively influenced behavioral intention to use MOOCs in all three countries. As well, absorptive capacity is mediated significantly by performance expectancy and effort expectancy. Facilitating conditions have a significant influence on MOOCs in both Thailand and Pakistan. Social influence has a significant influence on behavioral intention to use MOOCs in Thailand, hedonic motivation and price value have a significant influence on behavioral intention to use MOOCs in Poland, and the habit has a significant factor in Pakistan. The keys aspects influencing behavioral intention to Use MOOCs were different in Poland, Thailand, and Pakistan, in various factors which are performance expectancy, social distancing, price value, facilitating conditions, and social influence. The research recommended that it is important to evaluate the situation and prevailing conditions of the concerned country, before implementing the MOOCs and the associated online learning practices.

Sustainable Production Clauses and Positioning in the Global Value Chain: An Analysis of International Investment Agreements (IIA) of the ICT Industry in Developing and Developed Markets

Positioning in the global value chain (GVC) reflects the level and kinds of value creation of a firm or industry. The value creation can be on the upstream or downstream of the value chain. This study explores the effects of sustainable production clauses on the economic and physical positioning of information and communication technology (ICT) firms in the global value chain (GVC). We examined 2107 international investment agreements (IIA), signed by 54 countries that represent 70% of the global investment agreements. The empirical results show that the sustainable production intensity clauses in the IIAs have a significant impact on the positioning of ICT’s in the GVC. However, the degree of impact on the economic scale of participation and physical location in the GVC differs. The heterogeneity test shows that the sustainable production intensity clauses of IIAs between developed and developing countries affect positively and significantly the physical and economic locations in the GVCs. This is less significant while the IIAs are signed between the developed markets. These findings demonstrate that countries should consider sustainable production principles and responsible business conducts while signing the IIAs, and ensure their implementation while participating in the GVCs. This process can enhance value creation by moving towards higher value creation activities within the GVC.

The implications of Industry 4.0 on supply chains amid the COVID-19 pandemic: a systematic review

Background: COVID-19 has caused significant disruptions in supply chains. It has increased the demand for products and decreased the supply of raw materials. This has interrupted many production processes. The emerging technologies of Industry 4.0 have the potential to streamline supply chains by improving time-sensitive customized solutions during this emergency.

Purpose: The study identifies the core technologies of Industry 4.0 and the role and impact of these technologies in managing the disruption caused by the COVID-19 outbreak in strengthening the supply chain resilience.

Design/methodology/approach: An extensive literature review using the “Preferred Reporting Items for Systematic Review and Meta-Analysis” method was carried out on the impact of the COVID-19 pandemic on supply chains and Industry 4.0 technologies. The study was undertaken by selecting keywords validated by experts, and a search was conducted in the Scopus, ProQuest, and Google Scholar databases. Publications from the leading journals on these topics were selected. The bibliographical search resulted in 1484 articles, followed by multiple layers of filtering. Finally, the most pertinent articles were selected for review, and a total of 42 articles were analyzed.

Findings: The findings of the study showed that the majority of the articles emphasized the digitalization of supply chain management, acknowledging the fundamentals, applications, and prospects, revealing the drivers and challenges of Industry 4.0 technologies to manage disruptions. Most of the authors identified IoT, big data, cloud computing, additive manufacturing, and blockchain to maintain the supply chain resilience.

Originality/value: Existing literature on epidemics lacks the basics and practices of utilizing Industry 4.0 technologies in the supply chain recovery process. To fill this research gap, the study summarizes the potential of Industry 4.0 technologies to lessen supply chain disruptions caused by COVID-19. The study findings are valuable for policymakers and practitioners and contribute to supply chain management studies.

Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

The birth of mass production started in the early 1900s. The manufacturing industries were transformed from mechanization to digitalization with the help of Information and Communication Technology (ICT). Now, the advancement of ICT and the Internet of Things has enabled smart manufacturing or Industry 4.0. Industry 4.0 refers to the various technologies that are transforming the way we work in manufacturing industries such as Internet of Things, cloud, big data, AI, robotics, blockchain, autonomous vehicles, enterprise software, etc. Additionally, the Industry 4.0 concept refers to new production patterns involving new technologies, manufacturing factors, and workforce organization. It changes the production process and creates a highly efficient production system that reduces production costs and improves product quality. The concept of Industry 4.0 is relatively new; there is high uncertainty, lack of knowledge and limited publication about the performance measurement and quality management with respect to Industry 4.0. Conversely, manufacturing companies are still struggling to understand the variety of Industry 4.0 technologies. Industrial standards are used to measure performance and manage the quality of the product and services. In order to fill this gap, our study focuses on how the manufacturing industries use different industrial standards to measure performance and manage the quality of the product and services. This paper reviews the current methods, industrial standards, key performance indicators (KPIs) used for performance measurement systems in data-driven Industry 4.0, and the case studies to understand how smart manufacturing companies are taking advantage of Industry 4.0. Furthermore, this article discusses the digitalization of quality called Quality 4.0, research challenges and opportunities in data-driven Industry 4.0 are discussed.

The Impact of Technological Innovation on Industry 4.0 Implementation and Sustainability: An Empirical Study on Malaysian Small and Medium Sized Enterprises

Small and Medium sized Enterprises (SMEs) are the pillars on which most of the economies worldwide rest. Without the support of qualified technological innovation, it will be very difficult for SMEs’ performance to improve and impossible for them to reach their sustainability goals. Small businesses should therefore be encouraged to embrace the next technological frontier, Industry 4.0 (I4.0). The main purpose of this research is to understand the relationship between the implementation of Industry 4.0 technologies and sustainability goals, along with an analysis of how innovation characteristics make implementing I4.0 easier for small businesses. To answer the research questions and analyse the high complex data, this research performed a structural equation model by using AMOS software. The results indicated that technology innovation characteristics have a positive significant effect on I4.0 implementation and sustainability goals. However, effective implementation of I4.0 mediates between the relationship of innovation characteristics and sustainability goals, except observability. The implications of this research are that SMEs should develop effective I4.0, implement it, and build innovation characteristics to reach sustainability goals.