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Over the past decade, many small‐ and medium‐sized enterprises have incurred dramatic losses due to major disasters, causing loss of their business information systems and transaction data, so, they have started to outsource their information operations to data centers (DCs), in order to monitor critical business data operations. The purpose of this paper is to propose a dual‐sided business data integrity policy framework.

Based on a review of the available literature, case studies, and in‐depth interviews with top CEOs and experts in the field, a fuzzy Delphi method is proposed in two frameworks. In addition, a risk evaluation rule is derived by applying Bayesian decision analysis to mitigate the risk and lower the cost in their outsourcing policy; and Delphi method is used to extract 11 DC service quality evaluation indicators and also use these indicators to conduct a benchmark in Taiwan. Furthermore, the proposed framework is applied to figure out critical service advantages as well as suggestions for the DC involved in the benchmark.

The results of framework point out that enterprises should monitor the four operation elements (facility and infrastructure, server system management, information security management, and disaster recovery (DR) mechanism) to ensure and improve their data integrity; and DC firms need to build robust facilities and services in the five operation elements (customizability, serviceability, information technology infrastructure, security management, and knowledge intensity).

This paper uses a hybrid Delphi‐Bayesian method to propose a new framework, which is adequately integrated with the consensus of experts and business decision makers; higher professionalism and content validity are achieved. Enterprises can use these indicators to evaluate the service quality of DCs among DC firms.

In a globalised environment, market volatility makes risk management an essential component of the supply chain. Similar to conventional supply chains, a Halal supply chain (HSC) is also affected by several factors making it vulnerable to risks. Therefore, the purpose of this study is to identify and analyse the elements of Halal supply chain management (HSCM) and their significant risk dimensions.

In total, 72 risk elements of HSCM are identified through a review of contemporary scientific literature along with news items and official websites related to risk management of conventional supply chain management, HSC and sustainable supply chain. Further, 42 risk elements are finalised using fuzzy Delphi and then these risk elements are categorised into 7 dimensions. The interrelationships among the risk dimensions as well as risk elements are developed using fuzzy DEMATEL.

Results suggest that production, planning, logistic & outsourcing and information technology-related risk are prominent risk dimensions. The causal relationships among the significant risk dimensions and elements related to the HSCM may help managers and policy planners.

This study faces a challenge due to inadequate availability of the literature related to risk management in the area of HSCM. Further, this study has used inputs from experts, which can be biased.

To the best of the author's knowledge, it is the first comprehensive study towards investigating the interrelationships among the risks in the context of the HSCM.

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.

The purpose of this research is to determinate the criteria weight in a fashion design scheme evaluation system.

The first stage is to use the fuzzy Delphi method (FDM) by fashion design experts of academia and industries for fashion design evaluation criteria. The second stage is based on the use of a fuzzy analytic hierarchy process (FAHP) to find the criteria weight. Finally, an empirical example is used to illustrate the procedure of obtaining the criteria weights for the evaluation of a fashion design scheme.

The result shows that there are eight evaluation criteria to be obtained for fashion design scheme selection. The evaluation characteristic weights of theme and innovation score almost 90 percent (88.93 percent), the criteria weights of the first five, fashion forecast theme story, best‐seller modification, new idea and product position, score almost 80 percent (79.96 percent) and the criteria weights of the first two, fashion forecast and theme story, score almost 40 percent (39.93 percent) when selecting a design scheme in the fashion design process.

This paper proposes the vital characteristic and criteria for the selection of the fashion design scheme. In selecting fashion design scheme, this study uncovers that the marketing is less important than theme and innovation characteristics. Additionally, the results of this study, indicate the important five criteria, offered designer a set of useful indicators in preparing fashion design scheme and improving the quality of fashion design decision.

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.

International collaboration is a crucial requirement of entrepreneurship, particularly in developing emerging economies. This collaboration seems so necessary in the food industry as a major contributor to environmental, social and economic problems. This paper aims to identify, analyse the influential network relationship and prioritise the key success factors (KSFs) of international collaboration formation in the entrepreneurial food industry with a case study on Iran's emerging economy.

To identify a list of KSFs, a qualitative method, literature review, is initially used. A quantitative method, fuzzy-Delphi, then is employed to finalise the main KSFs based on the entrepreneurial food industry experts' opinion. To analyse the causal relationship, and prioritise the KSFs, a fuzzy decision-making trial and evaluation laboratory (DEMATEL)-analytic network process (ANP) methodology, i.e. FDANP, is applied. At the first stage, the cause–effect diagram of KSFs is extracted using fuzzy DEMATEL and then, the KSFs weights and priorities are evaluated using a fuzzy ANP.

The results illustrate that the characteristics of effective development workers are the leading dimension of a successful international collaboration that directly affects other dimensions. On the other hand, increased marketing and trading is the most important KSF that is directly related to international entrepreneurial collaboration team capabilities and professionalism. The leading and casual role of team members also plays a vital role in strategic and communication issues affecting the collaboration success, e.g. market research and new product development. Availability of financial resources and the ability of partners in continuous financing is also a crucial and required factor for a successful collaboration.

Using an extensive review of the literature to extract the KSFs of international entrepreneurial collaboration and finalising them using a fuzzy-Delphi method and examining the cause-effect relations between them, as well as prioritising the KSFs are the main contributions of this paper.

In this research, extracting the innovation drivers of successful crowdfunding from the literature review, screening them for the entrepreneurial small- and medium-sized enterprises (SMEs), analysing the cause-and-effect relationship amongst them and presenting a basic causal conceptual model and eventually determining the importance/weight of each relevant driver were the primary purposes of this research. As a result, the authors have also designed a score function to measure the future innovative crowdfunding score for SMEs.

A multi-layer multi-criteria decision-making (MCDM) approach has been designed and employed to achieve research objectives. After extracting the initial list of drivers, Fuzzy Delphi was applied to screen the relevant innovation drivers of successful crowdfunding for entrepreneurial SMEs. Decision-making trial and evaluation laboratory (DEMATEL) was used to analyse the cause-and-effect relationship amongst the drivers and illustrate a basic conceptual model. Analytical network process (ANP) and Stepwise Weight Assessment Ratio Analysis (SWARA) were applied to determine the importance of the drivers and by aggregating them to measure the innovative crowdfunding score.

Initially, 28 innovation drivers of successful crowdfunding were extracted from the literature. Then by employing the first-round Delphi fuzzy method amongst 15 international entrepreneurs in SMEs, the relevant drivers, including eleven items, were screened and selected. Then by implementing the DEMATEL method, the relationship amongst these screened drivers was identified, and seven drivers were determined as causes and the rest as effects. Subsequently, a conceptual model based on the causal analysis of the drivers from the DEMATEL method was designed. Eventually, by aggregating the weight of drivers emanated from SWARA, DEMATEL and DANP, the score function for measuring the situation of an SME was designed.

According to the crowdfunding scores in this research from entrepreneurs of SMEs, influential factors in developing countries were recognised as two times more prominent in developing countries. This might be rooted in the circumstances of developing countries where many startups and SMEs are emerging in vast areas and different fields due to investment in innovation management. In these countries, the authorities and officials support these companies to empower their capabilities and innovative ideas to (1) deal with the severe competitive market and (2) benefit from them as potential economic engines. Therefore, crowdfunding platforms and public initiatives can be considered one of the most effective government supports, which may involve financial risks.

To the best knowledge of the authors, investigating the innovation drivers of successful crowdfunding via quantitative analysis by multi-layer decision-making approaches has not been considered previously. Moreover, the authors have designed a crowdfunding score function to determine the situation of an entrepreneurial SME in this area. A combination of different MCDM methods, including Fuzzy Delphi, SWARA, DEMATEL, ANP and DANP, to investigate the innovation drivers of successful crowdfunding in SMEs has not been considered previously.

A hybrid approach for integrating group Delphi, fuzzy logic and expert systems for developing marketing strategies is proposed in this paper. Within this approach, the group Delphi method is employed to help groups of managers undertake SWOT analysis. Fuzzy logic is applied to fuzzify the results of SWOT analysis. Expert systems are utilised to formulate marketing strategies based upon the fuzzified strategic inputs. In addition, guidelines are also provided to help users link the hybrid approach with managerial judgement and intuition. The effectiveness of the hybrid approach has been validated with MBA and MA marketing students. It is concluded that the hybrid approach is more effective in terms of decision confidence, group consensus, helping to understand strategic factors, helping strategic thinking, and coupling analysis with judgement, etc.

The purpose of the paper is to present the common use of the Delphi method, the analytical hierarchy process (AHP) and dynamic fuzzy cognitive maps for the development of a future scenario in correlation with climate warming.

A combination of the Delphi method, the analytical hierarchy process (AHP) and dynamic fuzzy cognitive maps was employed to construct a future scenario as a learning device.

Based on the data, the future is not going to be so bad but also not very attractive even if it is assumed that human consciousness about global warming issues will remain high. After a few years or so it will be possible to stop negative climate processes but not possible to fix the problem in the sense that the situation we have now can be substantially improved.

This paper is of interest for foresight practitioners and policy makers who want to employ a hybrid approach to scenario development.

The paper is the first to try to use a combination of different methods for scenario development related to climate change.

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.