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In this study, a novel framework was proposed to assess the trust in e-government (e-Gov) services under an uncertain environment. The proposed framework was applied in Iranian municipality websites of e-Gov services to evaluate the readiness score of trust in e-Gov services.

A unique hybrid research methodology was proposed. In the first phase, a comprehensive set of indices were determined from an extensive literature review and finalized by employing the fuzzy Delphi method. In the second phase, interval-valued intuitionistic fuzzy set (IVIFS) -was utilized to model the problem's uncertainty with analytic called IVIFS- hierarchy process (AHP) to determine the importance of indices and indicators by assigning the weights. In the third phase, the fuzzy evaluation method (FEM) is followed for assessing the readiness score of indices in case studies.

The findings indicated that “Trust in government” is the most significant index affecting citizen's trust in e-Gov services while “Maintenance and support” has the least impact on user's intention to use e–Gov services.

The study contributes by introducing a unique research methodology that integrates three phases, including fuzzy Delphi, IVIFS AHP and fuzzy evaluation method. Moreover, the fuzzy sets theory helps to reach a more accurate result by modeling the inherent ambiguity of indicators and indices. Interval-valued intuitionistic fuzzy models the ambiguity of experts' judgments in an interval.

The study helps policy makers to monitor wider aspects of trust in e-Gov services as well as understanding their importance. The study enables policy makers to apply the framework to any potential case studies to evaluate the readiness score of indices and recognizing strengths and weakness of trust dimensions as well as recommending advice for improving the situation.

The study is one of the few to indicate significant indices of trust in e-Gov services in developing countries. The study shows the importance of indicators and indices by assigning a weight. Additionally, the framework can assess the readiness score of various case studies.

Supply chain finance (SCF) is an advanced financing solution for medium and small organizations. However, due to its nascent stage, SCF is still struggling with its application in the supply chain. The blockchain application in SCF can bring lots of opportunities and smart techniques to deal with financing to organizations. However, some factors restrict the proper adoption of blockchain in SCF. Therefore, this study aims to identify and analyze the factors obstructing blockchain adoption in SCF.

The present study applied a hybrid fuzzy DELPHI-AHP-DEMATEL to validate and analyze the factors. The fuzzy Delphi techniques were adopted to validate the identified factors. Thereafter, the analytic hierarchy process (AHP) has been used to prioritize the validated factors. Further, the decision-making trial and evaluation laboratory (DEMATEL) method has opted to classify the factors into cause-and-effect groups.

The result of the study revealed that lack of technological competence and confidentiality leaking are the most prioritized factors and act as the prime factors for the obstacles in the blockchain application in the SCF. The application of the DEMATEL method revealed that the highest causing factor is authenticity, and the highest effecting factor is high cost.

The current study enhances the knowledge and information of managers and policymakers about the challenges associated with the blockchain application in SCF as well as provides better insight to deal with various factors obstructing blockchain adoption in SCF.

The current study is the first of its kind, where factors obstructing blockchain adoption in SCF are identified and validated with the help of experts and practitioners by incorporating the fuzzy Delphi method. Thereafter, the validated factors are prioritized by using fuzzy AHP and fuzzy DEMATEL techniques helps to identify the cause-and-effect group, which opens the door for future research work.

With the emergence of the basis of intellectual capital, competitive advantage was considered as the focus of competitive strategies, and the knowledge resulting from this approach became the basis for the development and strategic directions of companies in various fields of the company such as finance and accounting. The purpose of this study is sustainable intellectual capital reporting framework and evaluation of key examples in the context of capital market companies.

The methodology of this study was exploratory from the point of view of the developmental result and based on the type of objective and qualitative and quantitative basis was used to collect the data. The statistical population in the qualitative part was university experts and in the quantitative part financial managers of capital market companies. Data collection tools were interviews in the qualitative part and fuzzy scales and language comparison checklists in the quantitative part. Therefore, first through three stages of coding, the dimensions of the model were identified, and based on the fuzzy Delphi analysis, the reliability level was determined through the average between the first round and the second round of Delphi. Finally, through the default tests, the appropriate fuzzy model was first determined, and then hierarchical fuzzy analysis based on TODIM's approach was used to determine the most favorable axis of sustainable intellectual capital reporting.

The results in the qualitative part indicate the existence of 3 categories and 6 components and 39 conceptual themes in the form of a six-dimensional model. In the quantitative part, the results showed that by confirming the dimensions identified through fuzzy Delphi analysis, the most desirable axis of intellectual capital reporting is the component of technological capital reporting, which can play a more effective role in sustainable reporting.

This study, relying on the importance of the consequences of sustainable intellectual capital reporting, tries to evaluate the consequences of this field of financial reporting due to the lack of a coherent theoretical framework about capital market companies. In addition, the framework presented in this study promotes integrated thinking for firms to it would provide some level of incentive to those charged with governance concerning the voluntary compliance with the sustainable intellectual capital reporting framework.

Hospital structures serve to protect and improve public health; however, they are recognized as a major source of environmental degradation. Thus, an effective performance evaluation framework is required to improve hospital sustainability. In this context, this study presents a holistic methodology that integrates the sustainability balanced scorecard (SBSC) with fuzzy Delphi method and fuzzy multi-criteria decision-making approaches for evaluating the sustainability performance of hospitals.

Initially, a comprehensive list of relevant sustainability evaluation criteria was considered based on six SBSC-based dimensions, in line with triple-bottom-line sustainability dimensions, and derived from the literature review and experts’ opinions. Then, the weights of perspectives and their respective criteria are computed and ranked utilizing the fuzzy analytic hierarchy process. Subsequently, the hospitals’ sustainable performance values are ranked based on these criteria using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution.

A numerical application was conducted in six public hospitals to exhibit the proposed model’s applicability. The results of this study revealed that “Patient satisfaction,” “Efficiency,” “Effectiveness,” “Access to care” and “Waste production,” respectively, are the five most important criteria of sustainable performance.

The new model will provide decision-makers with management tools that may help them identify the relevant factors for upgrading the level of sustainability in their hospitals and thus improve public health and community well-being.

This is the first study that proposes a new hybrid decision-making methodology for evaluating and comparing hospitals’ sustainability performance under a fuzzy environment.

The current study aims to identify and classify the financial resilience measurement indices using the intuitive fuzzy approach.

The present study aims to identify and classify firms' indices of financial resilience measurement using the Fuzzy–Delphi combined method and the intuitive fuzzy DEMATEL technique with interval values. For the study and the literature review, 29 financial resilience indices were identified, and 12 were finalised after screening and localisation. Next, the selected indices were classified into two groups of influencing and being influenced, and the significant range of each one was determined. Finally, the executive and research suggestions were presented based on the obtained results.

The study results indicate a higher significance level of redundancy and visibility in financial resilience.

The present study is the pioneer study to assess, identify and classify the contributing indices to financial resilience.

This paper aims to investigate Supply Chain (SC) Performance Measurement Systems (PMSs) (SCPMSs) that are suitable and applicable to evaluate SC performance during unexpected events such as global pandemics. Furthermore, the contribution of Industry 4.0 Disruptive Technologies (IDTs) to implement SCPMSs during such Black Swan events is investigated in this study.

The research methodology is based upon a novel qualitative and quantitative mixed-method. A Systematic Literature Review (SLR) was initially employed to identify two complete lists of SCPMSs and IDTs. Then, a novel Interval-Valued Intuitionistic Hesitant-Fuzzy (IVIHF)-Delphi method was firstly developed in this paper to screen the extracted SCPMSs. Afterward, the Propriety, Economic, Acceptable, Resource, Legal (PEARL) indicator of the Hanlon method was innovatively applied to prioritize the identified IDTs for each finalized SCPMS.

Two high-score SCPMSs including the SC operations reference (SCOR) model and sustainable SCPMS were recommended to improve measuring the performance of the pharmaceutical SC of emerging economies such as Iran in which the societal, biological and economic issues were undeniable, particularly during unexpected events. Employing nine IDTs such as simulation, big data analytics, cloud technologies, etc., would facilitate implementing sustainable SCPMS from distinct perspectives.

This is one of the first papers to provide in-depth insights into determining the priority of contribution of IDTs in applying different SCPMSs during global pandemics. Proposing a novel multi-layer mixed-methodology involving SLR, IVIHF-Delphi, and the PEARL indicator of the Hanlon method is another originality offered by this paper.

The apparel industry of Bangladesh is rethinking lean manufacturing (LM) deployment because of the challenges imposed by the COVID-19 pandemic. Due to COVID-19, LM implementation in the apparel industry has become more difficult. Thus, the purpose of this study is to explore the barriers to implementing LM practices in the apparel industry of Bangladesh in the context of COVID-19 pandemic.

For evaluating the barriers, an integrated framework that combines the Delphi method and fuzzy total interpretive structural modeling (TISM) has been designed. The application of fuzzy TISM has resulted in a structured hierarchical relationship model of the barriers with driving and driven power.

The findings reveal that “lack of synchronization of lean planning with strategic planning”, “lack of proper understanding of lean concept” and “low priority from the top management” are the three top most important barriers of LM implementation in apparel industry.

These findings will help the apparel industry to formulate strategy for implementing the LM practices successfully. The proposed model is expected to contribute to the sustainable development goals (SDGs) such as Responsible Consumption and Production (SDG 12); Decent Work and Economic Growth (SDG 8); Industry, Innovation and Infrastructure (SDG 9) via resilient strategies.

This study is one of few initial efforts to investigate LM implementation barriers during the COVID-19 epidemic in a real-world setting.

The purpose of this study is to identify and analyze the barriers associated with the adoption of Industry 4.0 technologies in agricultural supply chains.

The study initially identified thirteen barriers by conducting a literature review and semi-structured interviews with key stakeholders. Subsequently, these barriers were validated and modeled using an integrated Fuzzy Delphi-ISM approach. Finally, MICMAC analysis was employed to categorize the barriers into distinct clusters.

The results provide considerable insights into the hierarchical structure and complex interrelationships between the barriers as well the driving and dependence power of barriers. Lack of information about technologies and lack of compatibility with traditional methods emerged as the two main barriers which directly and indirectly influence the other ones.

The robust hybrid Fuzzy Delphi and ISM techniques used in this study can serve as a useful model and benchmark for similar studies probing the barriers to Industry 4.0 adoption. From a theoretical standpoint, this study expands the scope of institutional theory in explaining Industry 4.0 adoption barriers.

The study is timely for the post-COVID-19 recovery and growth of the agricultural sector. The findings are helpful for policymakers and agriculture supply chain stakeholders in devising new strategies and policy interventions to prioritize and address Industry 4.0 adoption barriers.

It is the first comprehensive, multi-country and multi-method empirical study to comprehensively identify and model barriers to Industry 4.0 adoption in agricultural supply chains in emerging economies.

This chapter aims to identify, analyse, classify and rank the sustainability indices and internationalisation challenges of the footwear industry in the emerging economy of Iran. This would provide deeper decision-making insights into Iranian footwear businesses. First, a list of sustainability indices and internationalisation challenges was obtained by reviewing the literature. Then, a combination of multi-criteria decision-making (MCDM) approaches was implemented. The initial sustainability indices and internationalisation challenges were screened using the fuzzy Delphi method, keeping a total of 14 criteria. The best–worst method (BWM) was employed to weigh and rank the criteria. The interpretive structural modelling (ISM) technique and cross-impact matrix applied in MICMAC were employed to visualise the conceptual model based on the levels and classification of the important criteria for the internationalisation of the Iranian footwear industry. The 14 criteria were demonstrated to be important in internationalisation. The most critical sustainability indices were reducing hazardous substances in leather tanning and labour education and training. In contrast, exchange rate instability in Iran’s economy and strict chemical regulations for clothing and footwear were found to be the most important internationalisation challenges. Hence, these criteria should be considered in the internationalisation strategies of the Iranian footwear industry. A combined multilayer sustainable decision-making approach was used to analyse the Iranian footwear industry’s essential sustainability indices and internationalisation challenges. Furthermore, implications and insights are offered to footwear businesses for future decision-making.

In this research, the initial list of internal capabilities in small and medium-sized enterprises (SMEs) leading to success in international markets has been extracted. Then, the most relevant capabilities to international SMEs under servitisation and hybrid offerings have been screened. Next, the selected capabilities have been classified, and ultimately the relationship amongst the capabilities has been analysed. The conceptual model for SMEs participating in international markets with hybrid offerings has been illustrated.

A literature review has been employed to extract the initial list of internal capabilities to address the research objectives. Then, a novel hesitant fuzzy Delphi (HFD) method has been developed to select the most relevant capabilities for SMEs for hybrid offerings in international markets by using the experts opinions. Subsequently, a novel hesitant fuzzy interpretive structural modelling (HFISM) has been developed to classify the capabilities, design a level-based conceptual model and present the relationship amongst the prominent capabilities.

After the literature review, sixteen internal capabilities leading to success in the international market via hybrid offerings have been extracted. Then, eight selected capabilities were chosen for further investigation by applying 15 expert opinions and via the HFD approach. According to HFISM results, a level-based conceptual model was emanated, and “ability to take advantage of international opportunities”, “financial strength”, “technology level” and “efficient innovation management” were considered as the most fundamental capabilities resulting in successful hybrid offerings in international markets.

Alongside the multi-layer decision-making approach developed in this manuscript to analyse the internal capabilities roles in hybrid offering success towards international markets, to the best knowledge of the authors, the hesitant fuzzy approaches developed in this article have not been previously presented by any other scholar. A novel HFD approach has been designed for consensus amongst the experts under uncertain circumstances. Furthermore, a novel HFISM has been suggested and employed in this research to comprehend the relationship amongst the internal capabilities.