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Micro- Small and Medium Enterprises (MSMEs) are very significant for a country’s economy due to their contribution to manufacturing, sales and Gross Domestic Product (GDP) growth. The global market competition and standards have been compelling MSMEs to improve quality, reduce waste, improve environmental performance and optimize the cost of products by implementing sustainable practices. The combined approach of lean and sustainable practices can help MSMEs to minimize emissions from waste and manufacture low-cost products with energy-efficient technology. However, MSMEs face many challenges while implementing lean and sustainability tools. Therefore, the main aim of this study is to identify the barriers which create obstruction in the implementation of lean-led sustainable manufacturing practices in Indian MSMEs and prioritize them by calculating their weights. The study also proposes a framework for the integration of blockchain technology in the supply chain to overcome the barriers for the implementation of lean and sustainable manufacturing practices. Extensive literature reviews and experts’ opinions have been used to identify the critical barriers for the implementation of lean-led sustainable manufacturing practices in manufacturing firms. A total of forty barriers were selected and further categorized under seven main categories of barriers. The main category barriers and subcategory barriers are ranked based on the weight obtained through Best Worst Method (BWM). The ranking results are further analysed to assess the reliability and robustness using sensitivity analysis. The study reveals that economic and managerial barriers, knowledge and awareness barriers and organizational barriers are the most prominent category of barriers for lean and sustainable manufacturing. The study found that ‘Lack of awareness among customers towards sustainability’, ‘initial capital investment and low financial profit’, ‘lack of knowledge about potential benefits from sustainable products and practices’ and ‘resistance to change due to past failure’ are the most critical barriers for implementation of lean-led sustainable practices in Indian MSMEs. The study has analysed the features of blockchain technology and their effect on the performance of lean-led sustainable supply chain. The findings of the study will help managers and practitioners in Indian MSMEs from certain perspectives to develop an effective and efficient strategy to overcome these barriers and become sustainable. Therefore, this study provides valuable insights for researchers and practitioners.

Population growth and rapid urbanization have consequences that are reflected in the economic, environmental, and social stability of city-residential neighborhoods. These impacts directly affect not only residents but also real estate markets and local governments. The professionals working in the latter entities have become increasingly concerned about urban sustainability and its strategic integration into their plans. Strategies have been implemented that focus on both addressing negative aspects of residential neighborhoods and enhancing positive features that can contribute to the continuous improvement of locals’ living conditions. This study applies the multiple-criteria decision analysis approach and a combination of cognitive mapping and the best-worst method (BWM) to identify the most relevant criteria and use these to rank residential neighborhoods according to their sustainability. To apply the selected techniques, two group meetings were held with a panel of decision makers. The results were validated by the panel members and the Funchal City Council councilor for urbanism, who concurred that the proposed ranking system facilitates the identification of the most sustainable residential neighborhoods. The contributions and limitations of the methodological approach are also discussed.

PurposeBlockchain is an evolving technology that has an impact on a variety of industries and related operations including food supply chain. There are several challenges associated in the implementation of blockchain in the food supply chain. As a result, the goal of this research is to identify and analyse the barriers associated with the implementation of blockchain in food supply chains.Design/methodology/approachA comprehensive literature review is conducted to identify 16 primary barriers associated with the implementation of blockchain technology in the food supply chain and experts finalise these identified barriers and further categorise them into four groups. Furthermore, the best worst method is used to prioritise the finalised barriers.FindingsThe findings suggest that “technological barriers” and “organisational barriers” are primary barriers among the identified barriers for the implementation of blockchain. These barriers could be mitigated through supply chain collaboration, efficient blockchain technology development through research and development, and increasing technical competence.Research limitations/implicationsIn terms of limitation, there is a possibility that some barriers were overlooked in the literature review process, and expert judgement might be prejudiced. This paper examines the blockchain implementation in the food supply chain, to assist policymakers in overcoming these barriers and ensuring effective adoption.Originality/valueThis study focuses on the effective implementation of blockchain technology in the food supply chain in the context of emerging economies.

Due to the manufacturing sector’s severe negative impacts on sustainable development, sustainable manufacturing is gaining more momentum than ever. Despite the advantages of sustainable manufacturing, academic literature resources report that practitioners still face several challenges while implementing sustainable manufacturing. To eliminate such challenges, numerous mitigation strategies have been proposed, including those that identify Industry 4.0 technologies as a key factor. However, current studies are generally more focused on the application of Industry 4.0 technologies/smart manufacturing in sustainable manufacturing; most fail to provide an in-depth understanding of how these technologies might mitigate the existing adoption challenges of sustainable manufacturing. In this study, the key challenges of sustainable manufacturing are identified through literature review and analyzed with MCDM tools such as the Best-Worst Method and WASPAS method. The results suggest that governmental challenge demonstrates the greatest weight in the final ranking, followed by technological and organizational challenges. Among the sub-challenges, “lack of support from the government in the form of regulations / policies” and “absence of subsidies and incentives” display the most weight. Further, a framework has been proposed to map the collected challenges with relevant mitigating smart manufacturing technologies to bridge the gap remaining from existing studies. Finally, this study contributes to the new field of approaching smart manufacturing as a mitigating strategy for sustainable manufacturing implementation through highlighting the implications and recommendations.

Service quality and sustainability are not only strategically important for achieving competitive advantage in the hotel industry but also serve as critical indicators of long-term resilience, customer loyalty, and multi-dimensional sustainability encompassing environmental, social, cultural, and economic responsibilities in a rapidly evolving global tourism market. Service quality practices that focus on immediate customer satisfaction- such as rapid service or high-consumption amenities - can conflict with sustainability goals. These goals require long-term planning and efficient resource use. This creates a strategic tension in hospitality management. While academic interest in these two concepts has increased in recent years, the interaction between them and how different stakeholder groups prioritize these concepts have not been sufficiently investigated. In this context, the present study aims to determine the prioritization of service quality and sustainability dimensions among different stakeholder groups (hotel managers, academics and institution representatives) in the hotel industry. To this end, we used the Best Worst Method (BWM), one of the Multi-Criteria Decision Making (MCDM) techniques known for its simplicity and consistency. The data were collected through interviews with a total of 18 experts. The findings revealed that, across all stakeholder groups, service quality dimensions were prioritized over sustainability dimensions. Hotel managers emphasized operational efficiency and environmental sustainability. Furthermore, while academicians focused on reliability and adopted a more balanced view of sustainability, institution representatives prioritized tangible aspects of service quality. Social and cultural sustainability dimensions were consistently assigned lower importance by hotel managers and institution representatives. The priority given to service quality highlights the short-term and performance-oriented mentality in the hotel industry. The limited emphasis placed on social and cultural sustainability, particularly among practitioners, suggests that these dimensions are still not sufficiently considered in strategic decision-making processes. Taken together, the results of the present study highlight the varying evaluation patterns among stakeholder groups and underscore the need for a more holistic perspective on managing service quality and sustainability in hotel businesses.

This study focused on extracting and integrating expert surgeons' opinions into a quantitative decision‐making model based on the best‐worst method and used eight significant criteria, including postoperative complications, suturing time, and the surgeon's skill level. Experts' opinions were combined with the standard set data from CholecInstanceSeg. The model achieved an accuracy of 91.3% with a very low inconsistency ratio of 0.03, robustly outperforming the analytic hierarchy process and simple weighting methods. Moreover, model execution time improved by almost 50%. This study fills the gaps left by previous works by reducing ergonomic biases and increasing automation and overall system reliability in the decision‐making process. The model provides a more efficient framework that can be further developed with artificial Intelligence (AI) for tailored surgical decision support systems, thus providing more accurate frameworks for suturing technique selection in oncological surgeries.

Not only the steadily growing demand for electricity generation but also the environmental concerns in recent years have led to the belief in the importance of renewable energy. Wind is one of the most important renewable energy sources utilized in electricity generation for a sustainable environment. This paper deals with performance assessment for existing onshore wind plants in terms of triple bottom line of sustainability and aims to propose a structural methodology. Furthermore, the proposed framework is essentially formed through two stages: the first stage is the determination of relative weights for sustainability factors through the best-worst method (BWM) and the second stage is a sustainability performance assessment of the available 42 wind plants in Izmir, Turkey. According to the findings, the environmental dimension is the most significant, followed by the economic and social dimensions. The results also reveal that distance to protected areas is the most important factor among others in terms of sustainability performance and that the wind plants throughout the north side of Izmir have a higher sustainability performance. To validate the robustness and reliability of the introduced framework, a sensitivity analysis is also conducted. The proposed framework could be employed successfully in other scientific applications.

The rationalization of logistics activities and processes is very important in the business and efficiency of every company. In this respect, transportation as a subsystem of logistics, whether internal or external, is potentially a huge area for achieving significant savings. In this paper, the emphasis is placed upon the internal transport logistics of a paper manufacturing company. It is necessary to rationalize the movement of vehicles in the company’s internal transport, that is, for the majority of the transport to be transferred to rail transport, because the company already has an industrial track installed in its premises. To do this, it is necessary to purchase at least two used wagons. The problem is formulated as a multi-criteria decision model with eight criteria and eight alternatives. The paper presents a new approach based on a combination of the Simple Additive Weighting (SAW) method and rough numbers, which is used for ranking the potential solutions and selecting the most suitable one. The rough Best–Worst Method (BWM) was used to determine the weight values of the criteria. The results obtained using a combination of these two methods in their rough form were verified by means of a sensitivity analysis consisting of a change in the weight criteria and comparison with the following methods in their conventional and rough forms: the Analytic Hierarchy Process (AHP), Technique for Ordering Preference by Similarity to Ideal Solution (TOPSIS) and MultiAttributive Border Approximation area Comparison (MABAC). The results show very high stability of the model and ranks that are the same or similar in different scenarios.

This study intends to identify, analyse, and evaluate sustainability assessment (SA) methods, along with the critical factors of sustainable manufacturing (SM) practice. Based on the opinion of experts and a literature review, 10 SA methods and 20 critical factors of SM practice were identified and analysed in relation to their optimal selection in sustainable operations. This research uses a fuzzy MULTIMOORA (Multi-Objective Optimisation on the basis of a Ratio Analysis plus the full multiplicative form) to rank SA methods based on the weights of the critical factors of SM practice obtained using a fuzzy analytic hierarchy process (AHP). A case study of the leather processing industry in India describes the use of the technique in practice. The ranks obtained using the AHP-fuzzy MULTIMOORA is compared with those obtained using the best–worst method (BWM)-fuzzy MULTIMOORA. The results reveal that the Index of Social Progress and the Social Life Cycle Assessment are the top two reliable SA methods based on the identified critical factors of SM practice. Among the critical factors, the ‘identification of alternative raw materials’, ‘methane mitigation’, and ‘opting for re-utilisation’ are identified as the prominent critical factors of SM practices. In addition to the critical factors of SM, this study also evaluates SA methods as they help to monitor industrial progress towards sustainability. These findings provide useful insights to practitioners and can help them select optimal and robust SA methods.

Purpose This study aims to propose a conceptual model indicating the impact of Industry 4.0 (I4.0) technologies on lean tools. Additionally, it prioritizes I4.0 technologies for the digital transformation of lean plants. Design/methodology/approach The authors conducted a questionnaire-based survey to capture the perception of 115 experts of manufacturing industries from Germany, India, Taiwan and China. The impact of I4.0 on lean tools, using analysis of variance (ANOVA). Further, the authors drew a prioritization map of I4.0 on the employment of lean tools in manufacturing, using the Best–Worst Method (BWM). Findings The findings indicate that cloud manufacturing, simulation, industrial internet of things, horizontal and vertical integration impact 100% of the lean tools, while both cyber-security, big data analytics impact 93% of the lean tools and advanced robotics impact 74% of the lean tools. On the other hand, it is observed that augmented reality and additive manufacturing will impact 21% and 14% of the lean tools, respectively. Practical implications The results of this study would help practitioners draw up a strategic plan and roadmap for implementing lean 4.0. The amalgamation of lean with I4.0 technologies in the right combination would enhance speed productivity and facilitate autonomous operations. Originality/value Studies exploring the influence of I4.0 on lean manufacturing lack comprehensiveness, testing and validation. Importantly, no studies in the recent past have explored mapping and prioritizing I4.0 technologies in the “lean” context. This study thereby attempts to establish a conceptual model, indicating the influence of I4.0 technologies on lean tools and presents the hierarchy of all digital technologies.