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Significant developments in the service sector have been brought about by Industry 4.0. Automated digital technologies make it possible to upgrade existing services and develop modern industrial services. This study prioritizes critical factors for adopting Industry 4.0 in the Indian service industries.

The author identified four criteria and fifteen significant factors from the relevant literature that have been corroborated by industry experts. Models are then developed by the analytical hierarchy process (AHP) and analytical network process (ANP) approach to ascertain the significant factors for adopting Industry 4.0 in service industries. Further, sensitivity analysis has been conducted to determine the sensitivities of the rank of criteria and sub-factors to corroborate the results.

The outcome reveals the top significant criteria as organizational criteria (0.5019) and innovation criteria (0.3081). This study prioritizes six significant factors information technology (IT) specialization, digital decentralization of all departments, organizational size, smart services through customer data, top management support and Industry 4.0 infrastructure in the transition toward Industry 4.0 in the service industries.

The potential factors identified in this study will assist managers in determining strategies to effectively manage the Industry 4.0 transition by concentrating on top priorities when leveraging Industry 4.0. The significance of organizational and innovation criteria given more weight will lay the groundwork for future Industry 4.0 implementation guidelines in service industries.

Our research is novel since, to our knowledge, no previous study has investigated the potential critical factors from organizational, environmental, innovation and cost dimensions. Thus, the potential critical factors identified are the contributions of this study.

The process of redesigning is one of the essential steps in upcycling, which comprises ideation, reconstruction and fitting. This paper aims to study the best practice of upcycling in the clothing industry. This study is an attempt to standardise upcycling/redesign process.

An exploratory approach was adopted to perform the research. This study draws on the multiple organisations involved in the upcycling of clothes. The organisations chosen for this study are located in Sweden and Romania using the snowball technique. Semi-structured interviews, direct and participatory observation approaches were used to collect information. The collected data are systematically analysed using NVivo 10 software.

This paper provides empirical insights into the diverse practices of upcycling. Process, product and demand-based were three fundamental approaches to performing the redesigning process. The fabric quality and durability, variations in size, colour and pattern, skills and efforts required in the extraction of parts and environmental consciousness and awareness were the main factors influencing upcycling process.

The use of the European case may miss best practices from the other region. This study may help scholars to understand the method of upcycling. A practitioner of upcycling can use the findings to improve and standardise the existing process. This research is beneficial for society, as this leads to the reduction of textile wastage.

This paper conceptualises some of the best practices of clothes redesign. This provides a good insight for the organisation for the improvement in the redesign business.

The research objective is rooted in the principle of providing new insights and a collective perspective regarded as Supply Chain Quality Management 4.0 (SCQM4.0), an integration of all three concepts – Industrie 4.0, quality management and supply chain management.

A thorough review of historical developments and existing integration trends among Industrie 4.0, quality and supply chain approaches along with future research directions outlined in the main literature, was conducted. This work establishes a knowledge base on research topics, issues of integration and synergies with a concentration on the potential for deeper integration with supply chain operations.

This article not only introduced the term SCQM4.0 and proposed a definition for it, but also contributed a novel conceptual SCQM4.0 framework and evolutionary perspective through the SCQM4.0 maturation model. Stemming from the gaps, opportunities and benefits identified in the literature, the conceptual SCQM4.0 framework builds on the high potential of the SCQM4.0 constructs to achieve successful governance and implementation. Under the SCQM4.0 maturity framework, it provides a clear evolutionary path underpinned by the SCQM4.0 constructs.

In the effort toward a successful SCQM4.0 implementation, the proposed SCQM4.0 maturity frameworks will be a “road map” for businesses to develop fully and actively in supply chain operations, bringing quality products and services for the company. Industry practitioners are encouraged to perform gap analysis and direct the implementation of the strategy to establish an excellent SCQM4.0.

This is one of the pioneering studies integrating all three concepts (Industrie 4.0, quality management and supply chain management), connecting the link and discovering more synergies to support the future development of more holistic management models. SCQM4.0 is expected to expand on the strengths, synergies and established relationships between technologies 4.0, quality and supply chain, contributing toward a pioneering and quality supply chain.

This study aims to examine the influence of reward personalization on financing outcomes in the Industry 5.0 era, where reward-based crowdfunding meets the personalized needs of individuals.

The study utilizes a corpus of 218,822 crowdfunding projects and 1,276,786 reward options on Kickstarter to investigate the effect of reward personalization on investors’ willingness to participate in crowdfunding. The research draws on expectancy theory and employs quantitative and qualitative approaches to measure reward personalization. Quantitatively, the number of reward options is calculated by frequency; whereas text-mining techniques are implemented qualitatively to extract novelty, which serves as a proxy for innovation.

Findings indicate that reward personalization has an inverted U-shaped effect on investors’ willingness to participate, with investors in life-related projects having a stronger need for reward personalization than those interested in art-related projects. The pledge goal and reward text readability have an inverted U-shaped moderating effect on reward personalization from the perspective of reward expectations and reward instrumentality.

This study refines the application of expectancy theory to online financing, providing theoretical insight and practical guidance for crowdfunding platforms and financiers seeking to promote sustainable development through personalized innovation.

In today's fast developing era, the volume of data is increasing day by day. The traditional methods are lagging for efficiently managing the huge amount of data. The adoption of machine learning techniques helps in efficient management of data and draws relevant patterns from that data. The main aim of this research paper is to provide brief information about the proposed adoption of machine learning techniques in different sectors of manufacturing supply chain.

This research paper has done rigorous systematic literature review of adoption of machine learning techniques in manufacturing supply chain from year 2015 to 2023. Out of 511 papers, 74 papers are shortlisted for detailed analysis.

The papers are subcategorised into 8 sections which helps in scrutinizing the work done in manufacturing supply chain. This paper helps in finding out the contribution of application of machine learning techniques in manufacturing field mostly in automotive sector.

The research is limited to papers published from year 2015 to year 2023. The limitation of the current research that book chapters, unpublished work, white papers and conference papers are not considered for study. Only English language articles and review papers are studied in brief. This study helps in adoption of machine learning techniques in manufacturing supply chain.

This study is one of the few studies which investigate machine learning techniques in manufacturing sector and supply chain through systematic literature survey.

1. A comprehensive understanding of Machine Learning techniques is presented.

2. The state of art of adoption of Machine Learning techniques are investigated.

3. The methodology of (SLR) is proposed.

4. An innovative study of Machine Learning techniques in manufacturing supply chain.

A comprehensive understanding of Machine Learning techniques is presented.

The state of art of adoption of Machine Learning techniques are investigated.

The methodology of (SLR) is proposed.

An innovative study of Machine Learning techniques in manufacturing supply chain.

The study aims to identify the central paradoxical tensions existing in developing resilience in organisations. The main thrust of this study is to develop a thorough understanding of diverse conflicting tensions in building resilience and develop the possible strategies to surmount these tensions.

Using the case study approach, the study applied theory-elaboration strategy as this study is based on well-established literature from both digitalisation and resilience. The study uses the paradox theory lens in a case study to reconcile both theories with contextual idiosyncrasies.

The paradox theory lens provides perspectives to understand tensions during resilience development and the role of digital transformation in this process. It assesses the potential solutions for surmounting tensions in resilient operations. The mapping of workable solutions with different paradoxes and propositions has been proposed for future empirical research.

The study suggests that practitioners should not consider resilience and sustainability as mutually exclusive; instead, managers must embrace ongoing tensions to bring solutions to address these two essential organisational priorities.

To the best of the authors' knowledge, this is the first empirical study that applies paradox theory to understand how an organisation can build resilience while confronting several paradoxes. The study findings support that resilience practices can move in tandem with environmental sustainability goals rather than being usually mutually exclusive.

This study aims to investigate the conflicting views in supply chain and strategic management literature regarding cooperative supply chain relationships (CSCR) and firm performance. Supply chain literature suggests a universally positive impact of CSCR on performance, irrespective of a firm’s strategy. In contrast, strategic management literature contends that the effectiveness of CSCR depends on their alignment with the firm’s competitive strategy. The research aims to clarify this disparity, offering insights into the strategic use of CSCR for enhancing firm performance.

This paper theorizes the integration of perspectives for the impact of CSCR on firm performance by examining the relationships considering the alignment of cost leadership and product differentiation strategies with supplier and customer relationships. Plant-level survey data is analyzed using regression techniques to test four hypotheses.

All four main relationships (cost leadership, product differentiation, supplier relationship and customer relationship) on firm performance are statistically significant. However, cost leadership firms are better aligned to their chosen strategy when they have strong relationships with suppliers, whereas similar relationships with customers create misalignment, negatively influencing firm performance. In contrast, product differentiators benefit by investing in relationships with customers rather than with suppliers.

A firm’s performance does not solely depend on its CSCR efforts but on aligning them with the firm’s overall strategy. Therefore, managers need to be cognizant of the firm’s competitive strategy when investing in CSCR. Failing to do so could negatively impact firm performance and, eventually, its ability to compete in the marketplace.

Scholars have advocated for the importance of examining competing perspectives of phenomena, both within and across various bodies of literature, as cross-disciplinary analysis often brings enhanced focus and depth, leading to improved understanding. This research is one of the initial efforts to empirically analyze the varying perspectives on CSCR in supply chain and strategic management literature. This cross-disciplinary approach can yield a more integrated perspective.

3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.

A business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.

First, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.

The new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.

The new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.

A new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.

Discount grocery stores (DGSs) are attractive food supply chain (FSC) channels because many cost-conscious Indians use them for monthly needs. Despite capacity, DGSs must address customer concerns about store crowd densities and improve their COVID-19 preparedness. The purpose of this study is to learn how retail operations strategies can improve customer experience and how stores can benefit.

The study looked at a case study where retail operations are run more efficiently, and the customer experience is enhanced by standardizing and customizing customer transactions. The potential benefits that customers and retailers might anticipate are then statistically verified. Next, the potential benefits were examined to determine which ones from customers’ and retailers’ views should be prioritized to increase satisfaction.

The case situation analysis in the study demonstrates how DGSs can improve their retail operations to reduce customer wait times and provide greater convenience. The study also provides practitioners with potential benefits to pursue from the perspectives of retailers, customers and both retailers and customers.

This study requires many past transactions and can be considered an extension of the current study, so it does not capture floor space and capacity improvements.

This research can help FSC retailers compete with upstream supply chain partners and customers in omnichannel retailing. By improving DGS retailer capacity and customer experience, this study can benefit all FSC stakeholders.

Although there are numerous potential benefits that practitioners can pursue, the current study suggests that practitioners focus on those that can improve retailer and customer satisfaction.

Technology and market pressures are encouraging localized and small-series production in customer-driven industries. The purpose of this paper is to explore and understand the supply chain-, product- and process-design factors for small-series production in EU’s textile and apparel industry, to understand configuration decisions, priorities and challenges.

An interview study was undertaken with ten companies that represent diverse small-series production models and value chain roles. Interview data was analysed to identify supply network configuration characteristics, decision priorities and challenges.

Three small-series production models emerged from the analysis, differing with respect to adoption of process postponement and customization. The findings confirm and extend past research regarding diverse decision priorities and product, process, supply chain structure/relationship configurations. Challenges identified relate to planning (priorities) and implementation (configuration). Whereas competence availability and digital technology challenges are common, several difficulties are linked to production model like tensions related to priorities and small volumes, which are not found with customization.

Future research can make comparisons with other industry and location contexts; adopt dynamic approaches to distinguish between design and reconfiguration processes; and address indicated paradoxical-tensions.

The study findings can provide guidance for companies regarding identification of priorities and management of (planning/implementation) challenges impacting small-series production in T&A.

The paper brings a configuration perspective at the supply chain level to the problem of small-series production implementation, which demands holistic and context-specific understanding.