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Medical equipment’s supply chains play a vital role in performance of national 1healthcare systems. This supply chain is confronted with different internal and external risks. The purpose of this study is to investigate and find the key factors affecting the resilience of the supply chain of medical equipment and to examine the dynamic relations among these factors.

A hybrid methodology is used for meeting the purpose of this study. First, the Delphi method is extended by using hesitant fuzzy linguistic term sets to identify the key factors of supply chain resilience. At the second phase, using the system dynamic methodology, the dynamic relations among identified resilience factors are analyzed.

Using the Delphi method, agility, collaboration among actors, sharing of information, trust among actors, explicitness of supply chain, risk management culture, adaptability, structure, funding and environment conditions are identified as ten major factors affecting medical equipment’s supply chain resilience. Also, four scenarios are simulated along with their impacts on the system.

The main contribution of this study is extending a hesitant fuzzy linguistic term sets-based Delphi and applying it along a system dynamic analysis to identify the key factors affecting resilience of medical equipment’s supply chain for the first time.

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.

Many European businesses are small and medium enterprises (SMEs), contributing significantly to the well-being of local economies and regions. Even so, SMEs face many challenges in fostering innovation and improving performance. Furthermore, the raw material consumption is increasing globally, necessitating the development of strategies that will reduce the number of raw materials extracted and imported while improving the sustainability of small and medium-sized businesses. Consequently, promoting circular economy (CE) strategies, such as industrial symbiosis (IS) partnerships, whereby waste products from other industries serve as a source of raw materials for companies, is critical. Identifying and analysing enablers or drivers that support IS collaborations among SMEs is necessary to achieve this goal. In this regard, the purpose of this study will explore the enablers of IS among SMEs considering sustainability dimensions (environmental, social and economic). As facing a decision-making (DM) problem, the multiple attribute decision-making (MADM) approach was applied in a hesitant fuzzy (HF) environment in this research to answer the research questions. In this regard, in phase 1, IS enablers were identified and extracted using a literature review and experts’ opinions. In phase 2, the hesitant fuzzy Delphi (HFD) method was implemented to screen and finalise the enablers identified. In phase 3, casual relations among final enablers were determined using the hesitant fuzzy ANP (HF-ANP) method. Finally, in phase 4, the relative importance of enablers was calculated using the hesitant fuzzy best–worst method (HF-BWM). Consequently, this study provided potential strategies for IS that can be implemented quickly and used by local authorities to support SMEs in achieving circular waste management.

The decision to become international is a highlighted organisational decision that affects all dimensions at all firm levels. Human resources are also among the parts of the organisation affected by this decision. Paying attention to employees can speed up and facilitate this process. Organisational integrity is one of the most significant issues that must be considered. In this regard, identifying, investigating and planning to deal with the destructive effects that may influence the employees of small and medium-sized enterprise (SMEs) in internationalisation, are among the subjects that have so far received less attention and should be studied more. The present study explores the destructive influences of internationalisation on the employees of SMEs by a hybrid multi-layer decision-making model-psychological solution. First, by reviewing the literature, the destructive impacts of internationalisation on employees are extracted. In the next stage, these factors are screened according to the condition of the SMEs in an emerging economy by interval-valued intuitionistic hesitant fuzzy Delphi (IVIHF-Delphi). The impact of these factors on each other is then evaluated applying interval-valued intuitionistic hesitant fuzzy DEMATEL-based ANP (IVIHF-DANP). Consequently, the highlighted destructive impacts are determined and the psychological solutions to face them are provided.

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.

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

This paper aims to classify journal papers in the context of hybrid quality function deployment QFD and multi-criteria decision-making (MCDM) methods published during 2004–2021.

A conceptual classification scheme is presented to analyze the hybrid QFD-MCDM methods. Then some recommendations are given to introduce directions for future research.

The results show that among all related areas, the manufacturing application has the most frequency of published papers regarding hybrid QFD-MCDM methods. Moreover, using uncertainty to establish a hybrid QFD-MCDM the relevant papers have been considered during the time interval 2004–2021.

There are various shortcomings in conventional QFD which limit its efficiency and potential applications. Since 2004, when MCDM methods were frequently adopted in the quality management context, increasing attention has been drawn from both practical and academic perspectives. Recently, the integration of MCDM techniques into the QFD model has played an important role in designing new products and services, supplier selection, green manufacturing systems and sustainability topics. Hence, this survey reviewed hybrid QFD-MCDM methods during 2004–2021.

This paper proposes a multi-layer hybrid decision-making approach to evaluate the capability alternatives for developing a collaborative network to operate in the international market.

The present study is contextualised in the Iranian pistachio export industry. An extensive review of the state-of-the-art literature on supplier collaboration was conducted to identify key capabilities that are essential to establish a collaborative network. The set of defined capabilities were then optimised through interviews with 14 experts from the relevant industry, academics and export authorities. A combination of the fuzzy Delphi method and the best–worst method (BWM) approach was, respectively, used to reduce the number of capability alternatives and assign priority weights to these alternatives. Subsequently, a weighted aggregated sum product assessment method (WASPAS) was employed to rank and evaluate the ability to creating a collaborative network for the export of pistachio.

From the extant literature review, 18 capabilities for the formation of coordination networks in the international markets were identified. Then, the prominent indicators in forming a global network were extracted. After ranking the top pistachio export countries/regions to formalise an efficient collaborative network, it was revealed that although Iran exports approximately 30% of the global market, it falls behind the USA and European Union. The competitors have scored higher in critical criteria, including “trust and commitment”, “strategy and management”, “managerial control and standardization” and “financial resources”.

The proposed hybrid approach encompassing fuzzy Delphi–BWM–WASPAS offers to solve the capability evaluation and selection as well as ranking the possible alternative to formalise a collaborative network in an integrated fashion. This combination of methods is capable to first identify the most important factors, then measuring their importance and eventually rank the possible alternatives. The suggested framework provides an approach to deal with the uncertainty of global collaborative network formation.

This paper analyses the voice of customers (VoCs) using a hybrid clustering multi-criteria decision-making (MCDM) approach. The proposed method serves as an efficient tool for how to approach multiple decision-making involving a large set of countrywide customer complaints in the Iranian automotive sector.

The countrywide data comprising 3,342 customer complaints (VoCs) were gathered. A total of seven determinant complaint criteria were identified in brainstorming sessions with three groups (six each) of experts employing the fuzzy Delphi method. The weights of these criteria were assigned by applying the fuzzy best–worst method (FBWM) to identify the severity of the complaints. Subsequently, the complaints were clustered into five categories with respective customer locations (province), car type and manufacturer using the K-mean method and further prioritised and ranked employing the fuzzy complex proportional assessment of alternatives (FCOPRAS) method.

The results indicated that the majority of complaints (1,027) from the various regions of the country belonged to one specific model of car made by a particular producer. The analyses revealed that only a few complaints were related to product quality, with the majority related to service and financial processes including delays in automobile delivery, delays in calculating monthly instalments, price variation, failure to provide a registration ( licence) and failure to supply the agreed product. The proposed method is an efficient way to solve large-scale multidimensional problems and provide a robust and reliable set of results.

The proposed method makes it much easier for management to deal with complaints by significantly reducing their number. The highest-ranked complaints from customers of the car industry in Iran are those related to delivery time, price alternations, customer service support and quality issues. Surveying the list of complaints shows that paying attention to the four most voiced complaints can reduce them more than 54%. Management can make appropriate strategies to improve the production quality as well as business processes, thus producing a significant number of customer complaints.

This paper proposes a comprehensive approach to critically analyse the VoCs by combining qualitative and decision-making approaches including K-mean, FCOPRAS, fuzzy Delphi and FBWM. This is the first paper that analyses the VoCs in the automotive sector in a developing country’s context involving large-scale decision-making problem-solving.