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Growing concern over sustainability adoption has presented an array of challenges to businesses. While vital to an economy's success, banking is not immune to societal, environmental and economic consequences of business practices. The study has examined the sustainable performance of banking institutions on the suggested multidimensional framework comprising economic, environmental, social, governance and financial dimensions and 52 sustainability indicators. The study benchmarks the significant performance indicators of leading banks indispensable to sustainable banking performance. The findings attempt to address research questions concerning the extent of sustainable banking performance, ranking the sustainability dimensions and indicators and standardizing sustainability adoption metrics.

To determine the responsiveness of the banking industry to sustainability dimensions, content analysis was conducted using NVivo software for the year 2021–2022. Furthermore, a hybrid multicriteria decision-making (MCDM) approach is used by integrating entropy, the technique for order preference by similarity to ideal solution (TOPSIS) and VlseKriterijumska Optimizacija KOmpromisno Resenje (VIKOR) to provide relative weights to performance indicators and prioritize banks based on their sustainable performance. Sensitivity analysis is used to ensure the robustness of results.

In the context of the Indian banking industry, the pattern of sustainability reporting is inconsistent and concentrated on addressing environmental and social concerns. The results of the entropy methodology prioritized “Environmental” sustainability over other selected dimensions while “Financial” dimension has been assigned the least priority in the ranking order. The significant sustainable performance indicators delineated in this study should be used as standards to ensure the accountability and credibility of the sustainable banking industry. Additionally, the research findings will provide valuable inputs to policymakers and regulators to assure better contribution of the banking sector in meeting sustainability goals.

Considering the paucity of studies on sustainable banking performance, this study makes two significant contributions to the literature. First, the suggested multidimensional disclosure model integrating financial and nonfinancial indicators would facilitate banking institutions in addressing the five aspects of sustainability. As one of the first studies in the context of the Indian banking industry, the findings would pave the way for better diffusion of sustainability practices. Second, the inclusion of MCDM techniques prioritizes the significance of sustainability indicators and benchmarks the performance of leading banks to achieve better profits and more substantial growth.

Rice is an important grain in Indian scenarios, and the purpose of the research work is to identify the attributes which can be the possible barriers in the traditional rice supply chain network.

A multilevel conceptual model is developed based on the literature review, and a field study is conducted by administering a questionnaire from the experts. Fuzzy logic methodology and a ranking score method is applied to identify the rice supply chain performance and the barriers of the traditional rice supply chain network.

The rice supply chain performance index for the traditional rice supply chain network is obtained, and the performance of the existing rice supply chain is found to be “fair”. The “information flow” is the attribute that can be a critical weak attribute in the traditional rice supply chain network. A proposed model of the blockchain technology-enabled rice supply chain network is developed as a solution for the “information flow” barrier.

The present research work is focussed on the generalized rice supply chain model of the Indian scenario, and more detailed studies can be carried out based on the regional issues.

The rice supply chain plays an important role in Indian economic development, and hence the current research paper focusses on identifying the barriers and the performance of the existing rice supply chain network.

The objectives of this paper are twofold. First, it aims to investigate the impact of the COVID-19 pandemic on the activities and performance of small and medium-sized enterprises (SMEs) government suppliers involved in government green procurement (GGP). Second, it examines the differences in the impact of COVID-19 between small and medium-sized groups.

The study used a questionnaire survey that was distributed to SMEs listed in the MyHIJAU directory that supply green goods and services to the government. Of the total 394 sample respondents, 126 usable questionnaires were received, representing a usable response rate of 31.98%. Descriptive analysis of mean score, standard deviation and mean score ranking was used to analyse the overall results. A t-test analysis was carried out to examine the differences between the small and medium-sized groups of companies.

The study discovers that the SME government suppliers involved in GGP were impacted by the COVID-19 pandemic. The top ranked impacts are that “the COVID-19 pandemic has heightened health and safety practices among the employees”, “the COVID-19 pandemic has reduced company’s turnover”, “the COVID-19 pandemic has forced the company to implement a cost reduction strategy”, “the COVID-19 pandemic has had a negative impact on the company’s ability to deliver work, supplies or services to the government” and “the COVID-19 pandemic has forced the company to incur higher production costs for green products or services provided”. However, there is no significant difference between the impact of the COVID-19 pandemic on the small and medium-sized group of enterprises.

The present study is among the fewer studies on the impact of the COVID-19 pandemic, with particular focus on SME government suppliers involved in GGP.

The digital direct-to-consumer (D2C) approach has seen widespread adoption across many industries, but its application to regional food products has been slower. This study aims to identify and rank the most significant challenges to the widespread use of digital D2C for regional food products.

A multi-criteria decision-making method called a fuzzy analytic hierarchy process (FAHP) was used to determine the order in which these obstacles were evaluated. Thirty-five barriers were identified and categorized into six categories named technological, operational, sociocultural, financial, market and institutional and regulatory barriers.

Market barriers ranked as the top barrier, and the technological barrier ranked the least significant amongst the main barrier categories for the adoption of digital D2C model for the regional food products. Lack of consumer awareness ranked number one globally, and lack of government subsidies ranked the least amongst the thirty-five identified barriers. Operational barriers came out to be second most significant barrier followed by institutional and regulatory barrier, sociocultural barrier, financial barrier and technological barrier.

The findings of this research were derived through a numerical examination of data gathered from the Indian setting. It follows that the technological, sociocultural, financial, market, operational and institutional constraints, among others, outlined here are all unique to India. Because of the unique nature of the Indian setting, the results of this study can only be used there and not elsewhere. It is possible that future research will broaden the aims of this one and refine its methodology. Digital D2C adoption for regional food products may be prioritized and ranked using quantitative and qualitative data sources like ANP and TOPSIS. It is possible that similar studies may be conducted in nations which have a different set of operational, technological, sociocultural market and financial and regulatory barriers. Conceptual framework can be formed by integrating TAM and TPB to understand the buying behavior of regional food products via digital D2C.

This research is the first to identify challenges to the widespread use of the digital D2C model for regional food products. Policymakers and other interested parties can use this information to better understand the difficulties of expanding the distribution of regional food products beyond their immediate regions.

Just transition is a fundamental concept for supply chain management but neither discipline pays attention to the other and little is known about how supply chains can be orchestrated as socioecological systems to manage these transitions. Building from a wide range of just transition examples, this paper explores just transition to understand how to move beyond instrumental supply chain practices to supply chains functioning in harmony with the planet and its people.

Building from a systematic review of 72 papers, the paper identifies just transition examples while interpreting them through the theoretical lens of supply chain management, providing valuable insights to help research and practice understand how to achieve low-carbon economies through supply chain management in environmentally and socially just ways.

The paper defines, elaborates, and extends the just transition construct by developing a transition taxonomy with two key dimensions. The purpose dimension (profit or shared outcomes) and the governance dimension (government-/industry-led versus civil society-involved), generating four transition archetypes. Most transitions projects are framed around the Euro- and US-centric, capitalist standards of development, leading to coloniality as well as economic and cultural depletion of communities. Framing just transition in accordance with context-specific plural values, the paper provides an alternative perspective to the extractive transition concept. This can guide supply chain management to decarbonise economies and societies by considering the rights of nature, communities and individuals.

Introducing just transition into the supply chain management domain, this paper unifies the various conceptualisations of just transition into a holistic understanding, providing a new foundation for supply chain management research.

To overcome the limitations of traditional multi-attribute decision making (MADM) methods, which only provide deterministic rankings of decision objects, this paper proposes a novel multi-attribute 3WD model. This model presents three-parameter interval grey number decision-theoretic rough sets (TPIGNDTRSs), aiming to offer a reasoned interpretation of loss functions in grey environments and ensure objective assessment of conditional probabilities.

Firstly, the traditional equivalence relation is replaced with the probabilistic dominance relation (PDR), categorizing decision objects into two state sets in DTRS for more objective conditional probabilities. Secondly, as the three-parameter interval grey number (TPIGN) introduces the most probable value on the basis of the traditional two-parameter interval grey number, it provides a more comprehensive method for describing grey information. Consequently, integrating TPIGN into DTRS refines the interpretations of loss functions in grey environments. Finally, by utilizing two main sorting techniques, relative kernel and degree of accuracy ranking and possibility ranking, two types of 3WD rules with TPIGNDTRSs, are constructed.

This study has successfully developed and validated a new multi-attribute 3WD model. The model was tested in two distinct domains: evaluating innovation efficiency in high-tech enterprises and recommending movies in a practical case. The findings reveal that the model can effectively integrate relevant information of high-tech enterprises, provide the government with enterprise-level assessments, and gather consumer preferences to recommend the most suitable movies.

This study treats the loss function as grey information in the 3WD model but overlooks the grey nature of evaluation values, limiting its applicability. Additionally, the model’s reliance on subjective expert judgments and historical data to establish the loss function may affect its objectivity. The implications of this research are that the novel model overcomes traditional MADM limitations, enhancing decision-making quality and efficiency in complex and grey scenarios. The model’s successful application in evaluating high-tech enterprises and recommending movies illustrates its dual value in both theory and practice.

Initially, the model proposed in this study is of significant importance for the development of the 3WD field, as it successfully addresses the challenges of uncertain loss functions and unknown conditional probabilities in grey information environments. Moreover, by integrating the 3WD model with MADM problems, it has broken through the bottlenecks of traditional MADM methods, offering new perspectives and strategies for solving MADM issues. Therefore, this research not only advances theoretical research but also provides powerful tools for practical applications.

This exploratory study aims to examine how wine stakeholders' are adopting innovative advancements in smart industry 4.0 application technology (SI4.0AT) coupled with electronic word-of-mouth (e-WOM) techniques to increase winery visitation and wine sales, prior to and during a global pandemic in the Yarra Valley in Victoria, Australia.

A qualitative interpretivist geographical bounded case study approach was used to collect data from fifteen Victorian wine stakeholder's prior to and during the global pandemic COVID-19. A thematic analysis was applied to interpret participant responses and how they viewed, reacted to and harnessed S14.0AT and e-WOM to continue and increase wine sales.

The findings suggest few wine stakeholders' were actively implementing SI4.0AT prior to the global pandemic, COVID -19. With the forced closure of wineries to visitors across Australia, most small to medium-sized wineries immediately changed their business models to concentrate on domestic e-commerce wine sales and home delivery. To support these new business models, e-WOM techniques were quickly adopted or increased whereas other S14.0AT technologies were not, due to financial restraints.

The number of participants used in this study is a limitation, however, this can be overcome by replicating this study in other wine regions. This research focused on the wine stakeholders' viewpoint only and may not be easily generalised. Future studies may examine the “what” aspect of SI4.0AT is being used and e-WOM content such as investigating what consumers are saying about these wineries, the method of communication and the motivations for consumers to engage with a winery.

The implications for the wine industry and overall results offer insight into the wine stakeholders' perceptions of SI4.0AT and e-WOM and consequent marketing strategy of wineries in the Yarra Valley, Victoria, both pre- and during forced face-to-face winery closures due to a global pandemic. Wineries need to continue to harness and leverage the benefits of e-WOM wine marketing in their marketing strategies and continue to explore the affordability of 4.0 app technology and Tourism 4.0 options.

This study is the first attempt at investigating how wine stakeholders' view; react to and harness SI4.0AT and e-WOM through formalised online marketing strategies which should continue to be investigated in the future.

This paper aims to propose a bed and breakfast (B&B) recommendation method that takes into account review timeliness and user preferences to help consumers choose the most satisfactory B&B.

This paper proposes a B&B ranking method based on improved intuitionistic fuzzy sets. First, text mining and cluster analysis are combined to identify the concerns of consumers and construct an attribute set. Second, an attribute-level-based text sentiment analysis is established. The authors propose an improved intuitionistic fuzzy set, which is more in line with the actual situation of sentiment analysis of online reviews. Next, subjective-objective combinatorial assignments are applied, considering the consumers’ preferences. Finally, the vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) algorithm, based on the improved score function, is advised to evaluate B&Bs.

A case study is presented to illustrate the use of the proposed method. Comparative analysis with other multi-attribute decision-making (MADM) methods proves the effectiveness and superiority of the VIKOR algorithm based on the improved intuitionistic fuzzy sets proposed in this paper.

Proposing a B&B recommendation method that takes into account review timeliness and user customization is the innovation of this paper. In this approach, the authors propose improved intuitionistic fuzzy sets. Compared with the traditional intuitionistic fuzzy set, the improved intuitionistic fuzzy set increases the abstention membership, which is more in line with the actual situation of attribute-level sentiment analysis of online reviews.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

Subway systems are highly susceptible to external disturbances from emergencies, triggering a series of consequences such as the paralysis of the internal network transportation functions, causing significant economic and safety losses to cities. Therefore, it is necessary to analyze the factors affecting the resilience of the subway system to reduce the impact of disaster incidents.

Using the interval type-2 fuzzy linguistic term set and the K-medoids clustering algorithm, this paper improves the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to construct a subway resilience factor analysis model for emergencies. Through comparative analysis, this study confirms the superior performance of the proposed approach in enhancing the precision of the DEMATEL method.

The results indicate that the operation and management level of emergency command organizations is the key resilience factors of subway operations in China. Furthermore, based on real case analyses, the corresponding suggestions and measures are put forward to improve the overall operation resilience level of the subway.

This paper identifies four emergency scenarios and 15 resilience factors affecting subway operations through literature review and expert consultation. The improved fuzzy DEMATEL method is applied to explore the levels of influence and causal mechanisms among the resilience factors of the subway system under the four emergency scenarios.