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This study aims to propose guidelines for developing circular products based on waste recovery that are aligned with sustainable production and consumption.

A systematic literature review and case studies on circular product development were conducted. In total, 15 companies with products based on waste recovery and aligned with sustainable production and consumption goal were studied.

The results show the decisions and strategies applied at each stage of the new product development process, including the design for recycling, the use of waste as a raw material for products and the concern for reducing pollution and recovering end-of-life products.

The cases studied meet the goals of efficient use of natural resources and waste reduction by preventing, reducing, recycling and reusing waste. For practitioners, a set of guidelines is proposed to help companies develop circular products based on waste recovery.

Previous studies have not evaluated the new product development process and circularity from the institutional theory and waste valorization perspectives.

Due to increasing socio-ecological concerns, manufacturers are paying ample attention to the strategic decision-making for enhancing customer satisfaction considering Industry 4.0 requirements. Customers' preferences are being considered vital into the decisions related to sustainable supplier selection for building competitive gain. Thus, the objective of this study is to develop a real-case-based empirical approach for evaluating performance of suppliers based on customers' feedback, an area not explored much in literature. The novelty of current study lies in the development of an integrated supplier evaluation and selection model involving three phases: (1) identifying sustainable criteria according to Industry 4.0 requirement through customers' feedback, (2) calculating relative scores of criteria using Z-numbers and (3) determining evaluation weights of suppliers using fuzzy-TOPSIS. The contribution of the study lies in effective validation of the model by considering the case of a manufacturing firm, which aids the firm in evaluating performance of suppliers based on customers' socio-ecological expectations while considering reliable information provided by decision-makers (DMs).

The purposes of this study are to identify the ways that luxury fashion brands can leverage in metaverse retailing, and give insights to practitioners in the fashion industry who are planning to launch metaverse retailing.

To offer a balanced view of available evidence, this study adopted a literature review approach and attempted to collect all existing academic journal articles on the issues related to metaverse retailing and luxury fashion brands. A comprehensive literature search was conducted in electronic databases Google Scholar, Web of Science, Scopus, Pro Quest and Science Direct from January 2023 to April 2024. Based on the results of the research in literature, real-life examples of luxury fashion brands were used to explain the ways that luxury fashion brands in the metaverse retailing can be put into practice.

The findings have revealed that there are many ways that luxury fashion brands can leverage in the metaverse retailing. The fusion of metaverse-related technologies provides brands with a wide platform of choices that can create immersive, personalized marketing experiences for customers. Four roles of metaverse are identified: (1) enhance of immersive experience; (2) provide big data interface to smart decision-making; (3) form high-fidelity simulated space; and (4) maintenance economic system and making of identification. To further enhance the four roles of metaverse, four types of technologies and 15 components for metaverse can be adopted by luxury fashion brands.

While this paper provides a literature review and real-life examples of luxury fashion brands in the metaverse retailing to explain the findings, further research is needed to evaluate the effectiveness of current efforts in the development of luxury fashion brands in the metaverse retailing through collecting both quantitative and qualitative data. Also, future studies may attempt to explore the challenges of investigating consumers in response to luxury fashion brands in the metaverse retailing.

The metaverse is turning imagination into reality through the integration of multiple technologies and is gaining momentum in tech. With technology leading the way, business leaders and brands must not only rethink retail but also bring immersive shopping experiences into the future. Metaverse has immense potential to transform the retail industry, thus the leading global and local firms must embrace innovation and new technologies, and prioritize “metaverse transformation” for their business. Based on the results of this study, some emerging practices pertaining to metaverse retailing are provided.

To the best of the authors’ knowledge, it would seem that this is the first work that conducts a literature review of the relevant academic journal articles addressed to the practitioners or managerial audiences in the area of luxury fashion industry who are concerned about the development of metaverse retailing. This paper identifies the ways that luxury fashion brands can leverage in the metaverse retailing and gives insights to practitioners in the luxury fashion industry who are planning to launch metaverse retailing.

The purpose of this paper is to develop a framework for the assessment of service quality of bus fleet services based on the service quality influencing factors. The paper also tries to evolve a quantitative measure for fleet service quality in the form of a fleet service quality index.

A graph theoretical approach is employed in this paper for bus fleet service quality assessment. Modelling of fleet service quality factors and their interrelations with due attention towards their structure is achieved through graph theory. A directed graph (digraph) of the service quality is developed, where its nodes represent factors influencing the quality while its edges show the degree of interrelationships. A matrix, which is equivalent to the digraph, is established that will generate a service quality function that will result in the development of a fleet service quality index (FSQI).

Attaining customer satisfaction through assurance of quality is the cornerstone of the existence and survival of any business organization, and bus fleet services are no exception to this. Several influential factors are there for the bus fleet service quality. This research paper has identified factors such as fleet management practices, operational characteristics, safety and reliability features, travel comfort, bus maintenance and environmental concerns that affect fleet service quality. Every factor is composed of distinct sub-factors. Furthermore, these factors are linked with one another. A higher value of the fleet service quality index indicates the adequate performance of the bus fleet service organization.

The methodology is useful for not only evaluating but also for comparison of service quality of different fleet agencies or organizations. The perceptions would be useful to the fleet service managers to create procedures and arrangements for improving the service quality.

The paper identifies various service quality factors of the bus fleet and an evaluation scheme for those factors has been developed. Based on these, a framework had been developed for the assessment of the service quality of different fleet service providers.

This systematic review of the current gender inequality issues in operations and supply chain management (OSCM) seeks to illuminate the multifaceted aspects of this issue and their various implications for the field.

Employing systematic literature review and Preferred Reporting Items for Systematic Literature Reviews and Meta-Analyses (PRISMA) methodologies, this research delves into an analysis of 238 journal articles spanning a 47-year period. The objective is to discern existing voids and put forth actionable suggestions that align with the United Nations’ Sustainable Development Goal Number 5 (SDG5) in the context of men and women, which pertains to realizing gender equality and empowering girls and women.

The results show a significant increase in published articles over the period. However, only five literature review articles were found that specifically address gender inequality in OSCM. The five common themes impacting gender inequality in this field are gender issues, mindset, transportation disparities, human resources and gender roles in OSCM, alongside sustainability, mobility and government policy intersections. The paper emphasizes the need for further research on these themes. It also suggests implications for educators, researchers, companies, OSCM departments and policymakers to achieve SDG5.

This study offers valuable insights by comprehensively reviewing and systematically analyzing the prevailing gender inequality issues within OSCM. It accentuates the significance of gender equality in OSCM, augmenting the burgeoning discourse and catalyzing concerted endeavors for gender equality.

Performance optimization algorithms based on node attributes are of great importance for sharding blockchain systems. Currently, existing studies on blockchain sharding algorithms consider only random selection sharding strategies. However, the random selection strategy does not perfectly utilize the performance of a node to break the bottleneck of blockchain performance.

This paper proposes a blockchain sharding algorithm called TOPSIS Optimization Sharding System (TOSS), which is based on entropy weight method, relative Euclidean distance and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). It defines a multi-attribute matrix to assess node performance and applies TOPSIS for scoring nodes. Then, an algorithm based on the TOPSIS method is proposed to calculate the performance score of each data node. In addition, an entropy weighting method is introduced to obtain the weights of each attribute to balance the impact of dimensional differences of attributes on the attribute weights. Nodes are ranked by composite scores to guide partitioning.

The effectiveness of the proposed algorithm in this paper is verified by comparing it with various comparative algorithms. The experimental results show that the TOSS algorithm outperforms the comparison algorithms in terms of performance improvement for the blockchain system, and the throughput metrics are improved by about 20% in comparison.

This study introduces a novel approach to blockchain sharding by incorporating the entropy weight method and relative Euclidean distance TOPSIS into the sharding process. This approach allows for a more effective utilization of node performance attributes, leading to significant improvements in system throughput and overall performance, addressing the limitations of the random selection strategy commonly used in existing algorithms.

This study aims to comprehend the smart city–built environment’s (SCBE) effect on citizens’ quality of life in the smart cities of a developing country such as India. This study also sought to investigate the moderating effect of technological anxiety on the association, as mentioned earlier.

This study’s hypotheses were tested using data from 494 sample respondents who lived in the top five smart cities of India using partial least square-based structural equation modeling.

This study validated five dimensions of an SCBE, including smart governance, smart economy, smart people, smart transportation, smart environment and smart living, and demonstrated a favorable connection between a SCBE quality of life. This study confirmed that technology anxiety strongly moderates the relationship between the built environment of smart cities and citizens’ quality of life.

This study is a pioneering effort that explores the relationship between SCBE and the quality of life of its residents and the moderating effect of technology anxiety on this relationship.

University–Industry Collaboration (UIC) is crucial for enhancing sectoral performance and competitiveness. This study focuses on investigating the challenges and solutions to achieving effective UIC in Brunei Darussalam’s agricultural sector. This sector is pivotal in diversifying the economy away from historical dependence on oil and gas, thereby promoting sustainability.

Adopting an interpretivist stance, this study prioritised subjective views through semi-structured interviews with 20 diverse participants, including government officials, agri-business professionals, farmers, an agri-tech company and academicians.

The findings highlight key challenges to successful UIC, including varying stakeholder needs and goals, limited proactive engagement and inadequate funding. Overcoming these barriers necessitates the provision of financial support and supportive mechanisms to agricultural stakeholders, along with fostering active participation in collaborative efforts. Enhancements in both academic and practical aspects are also essential for addressing these challenges effectively.

This study provides practical insights for stakeholders in industry, academia and government to collaboratively improve sectoral performance. Given its qualitative nature, the findings may not be universally generalisable beyond the contexts examined. Future research should validate these findings across diverse settings to enhance the transferability and applicability of UIC strategies.

This study addresses a crucial gap in the literature by examining UIC in agricultural contexts, particularly in developing countries such as Brunei, where research in this area is scarce. Moreover, this study’s findings may have relevance beyond the immediate context, as they provide rich and detailed insights into UIC dynamics from diverse stakeholders' perspectives, which can be applicable to similar settings in other developing countries.

ChatGPT is a new development in this technological era. This artificial intelligence-based tool responds to individuals’ queries and produces the requested content within seconds. Therefore, it is becoming popular among academics, the research community and library professionals. This study aims to test (through personal interaction with the tool) the authenticity of the ChatGPT’s produced records. Another objective of the research is to check the relevance between the individuals’ queries and the tool’s results. The research also intends to identify the challenges in retrieving information through ChatGPT.

The five researchers from different countries and organizations experienced ChatGPT by asking questions on more than 70 subjects. The responses were recorded in Notepad and converted into MS Excel and MS Access to standardize and analyze the data. The investigators consulted 11 reputed databases/sources, including Web of Science and Scopus, to assess the authenticity of the data retrieved through ChatGPT.

The findings confirmed that over 90% of results produced by ChatGPT were fake (the information did not exist in the literature). Similarly, the study sheds light on the discrepancies, such as irrelevant and incomplete information in the data generated by ChatGPT.

This is a unique study that shares the findings based on the different regions’ researchers’ personal experiences with ChatGPT. The researchers covered different subject areas (above 70) while asking questions to ChatGPT. The paper shares implications for researchers, students, faculty members, academic/research organizations and policymakers.

This paper aims to focus on the selection of an appropriate nature-inspired texture pattern for cutting tool tribological surface. The selection process uses the recognized skin textures of different snakes scrolling on highly rough and projected surface conditions to analyze suitability of texture based on the texture geometry and machining conditions. The work also aims to propose a texture pattern selection process to incorporate on cutting tool tribological surface.

The selection of alternative nature-inspired texture patterns based on the texture pattern geometry and machining properties leads to a multi-criteria decision-making problem. Thirteen criteria are considered for selecting an appropriate texture pattern among 14 alternatives, i.e. nature-inspired texture patterns. In the present work, an integrated analytical hierarchy process (AHP)-TOPSIS, AHP-multi-objective optimization on the basis of ratio analysis (MOORA) and AHP-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) approaches have been proposed for the selection of an appropriate nature-inspired texture pattern. AHP is used for the formulation of decision-making matrix and criteria weight calculations and ranking of alternatives is done by three methods. Spearman’s correlation compared and found positive relations between rank assigned by methods. Experimental validation is done in Lathe for selected texture effects.

The texture parameters C-1 (Width of texture) and C-2 (Depth of texture) are found significant, while T-2 (Blended Krait) and T-6 (Banded Racer-1) texture is found optimal to generate on cutting tool surface.

Only some nature-inspired texture patterns have been recognized before the selection; an infinite number of textures are available in nature. The size of the texture pattern is difficult to identify by the selection process because each texture pattern may have different effects on tribological surfaces.

The proposed selection methodology of nature-inspired texture patterns will help identify optimal texture geometry for specific tribological applications. The nature-inspired texture patterned tool has a significant impact on the cutting force and temperature due to its tribological effect on the cutting tool surface; it decreases the power required for machining. The machining characteristics like roughness are found to decrease by using nature-inspired texture patterned tools.

Various nature-inspire texture studies to generate specific effects on the tribological surfaces may be started study for the surface of aircraft, ships, bearings, etc. Small and big fabrication industries may benefit by decreasing the cost of machining using nature-inspired texture-patterned tools. Research society will pay attention to nature’s inspiration.

Novel snake-skin-inspired texture patterns are recognized and hybrid MCDM methods are proposed to select optimal texture pattern. Proposed method used single time normalization to effectively rank the alternatives. The insights gained from this research can be extrapolated to address similar challenges in selecting nature-inspired textures for various applications.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0163/