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The purpose of this paper is to adopt fuzzy interpretive structural modeling (ISM) to develop a precise evaluation framework and provide a theoretical basis for enhancing the understanding of responsible consumption and production (RCP) in academic and industrial fields.

An integration of fuzzy set theory and ISM is proposed to maintain a higher level of consistency and reduce the uncertainty inherent in expert responses.

RCP can be categorized into seven levels, which represent the driving power from higher to lower. The top aspect is management style; the remaining aspects are stakeholder management, regulation compliance, efficiency improvement, sustainable awareness, sustainable production and social responsibility.

This study attempts to integrate the triple bottom line (TBL) concept and corporate sustainability to develop a significant framework for evaluating RCP. Although the proposed aspects and criteria can be used to evaluate the Chinese construction industry, these may be insufficient for other industries. In addition, further discussion regarding important aspects and criteria is required to complete the theoretical basis.

The results indicate that the top two criteria are establishing transparent communication channels and promoting managerial attitudes and behavior, which are followed by technology capabilities, organizational culture and stakeholder engagement. These five criteria play important roles when implementing RCP practices among Chinese construction firms.

This study is the first to discuss RCP via an integration of the TBL concept and corporate sustainability. The framework developed herein provides a precise guideline for Chinese construction firms to improve their performance, and it also promotes the efficient use of resources via sustainable practices.

This study integrates economic/ecology (eco)-attributes and performance to build a sustainable service supply chain management (SSCM) model.

This study proposes the use of the fuzzy Delphi method to screen for the less important attributes and applies a network data envelopment analysis to explore the hierarchical and eco-efficient network interrelationships. The causality and hierarchal eco-efficient model is acquired using a fuzzy decision-making trial and evaluation laboratory analysis

The findings are as follows: (1) the information and technology management process is derived by enhancing sustainable customer and supplier relationship management, and (2) the eco-efficient model is improved based on long-term relationships with suppliers – that is, synergistic suppliers improve the service chain quality and provide services in an appropriate and timely manner – and research and development coordination. The theoretical and managerial implications are discussed.

The eco-efficient model reveals that the sustainable customer relationship management process, sustainable supplier relationship management process and information and technology management process are the major causal attributes in the model.

The eco-efficient model must be based on (1) long-term relationships with suppliers, (2) synergistic suppliers to improve service chain quality, (3) the provision of services in a timely manner and (4) research and development coordination.

Prior studies neglect to build an ecological economy model using the efficiency causality model of hierarchical interrelationships. Traditional SSCM fails to involve the triple bottom line performance toward sustainability.

This study establishes a set of seafood processing circular supply chain capabilities (CSCCs) in Vietnam using qualitative data analytics. This study specifies the interrelationships and hierarchical structure comprising six aspects and 24 criteria for the seafood processing circular supply chain in Vietnam.

Fuzzy Delphi method is used to confirm the validity. Fuzzy set theory is used to deal with the complexity and uncertainties from the qualitative information. The decision-making trial and evaluation laboratory method is used to examine the interrelationships among attributes. The analytical network process segregates (or displays) the capabilities in a hierarchical structure.

The results show that management control and technological capability dominate in circular design, circular sourcing, circular production and resource recovery. In practices, the strategic planning, action planning, information technology and technological facilities are important to seafood processing industry.

The CSCCs are pivotal in establishing a concrete foundation for the execution of circular supply chain management, with the aim of optimizing resource utilization and eliminating waste; however, prior studies have lacked a focus on the capability associated interrelationships and hierarchical structure in qualitative data analytics.

This study is to reconfigure a hierarchical supply chain model utilizing databases and text files to understand future pathways due to COVID-19 pandemic has had a bullwhip effect, disrupting the global supply chain, and a mechanism is needed to address this disruptive event under pandemic uncertainties.

To address this mechanism, this study employs bibliometric analysis and text mining to reconfigure a hierarchical supply chain model under pandemic conditions and associates it with social media to conduct an intuitive visual analysis.

The current academic concerns are related to an overconcentration on risk management and a data-driven approach, generating an enormous gap between the concerns of academics and those of the public. The evidence shows that for both countries with outstanding performance and those that need improvement, the efficiency in terms of preventing the spread of the pandemic should be promoted.

This study contributes to (1) reconfiguring a hierarchical supply chain model under pandemic uncertainties and (2) bridging theory and practice by offering comparable interrelated attributes to guide post-COVID-19 strategies in the supply chain. The findings are that the supply management approach and big data are attributes that involve the concerns of world public and academics under pandemic uncertainties.

The purpose of this paper is to propose a subcontractor selection model to fully consider the impact of construction enterprise demands on subcontractor selection. The objectives are to understand the translating process of specific enterprise demands to the evaluating criteria and the weight calculation process.

A three-stage model of subcontractor selection was designed based on quality function deployment (QFD), analytic hierarchy process (AHP) and improved grey correlation analysis (IGCA). In the proposed model, specific enterprise demands are translated by the QFD method, and the weights of the criteria are determined by the IGCA. The AHP is used to quantify the exporters' experience and construct the judgment matrix, which is used as inputting of the grey correlation analysis.

The proposed model provides a feasible process for subcontractor selection by fully considering the actual requirements of the project. By combining the company requirements and project requirement to put forward the requirements of the target subcontractor, the selection process ensures that the selected subcontractor and the project have a higher “fit”

Few researches on construction subcontractor selection have taken into account the “voice” of the company's stakeholders. Therefore, this paper designs a three-stage construction subcontractor selection model by introducing QFD to achieve the transmission of “voice” in the subcontractor selection process, so as to take full consideration of the project objectives and the needs of the company's stakeholders. Meanwhile, in order to decrease the subjective of weight calculation, this paper designs an AHP-IGCA allocation method to determine the weight of relevant indicators. By integrating the proposed weight calculation method and QFD method, the subcontractor selection results become more reasonable and objective.

The purpose of this paper is to enhance the understanding of sustainable supply chain management (SSCM) and provide a comprehensive and quantitative method to assess performance.

The study applied interval-valued triangular fuzzy numbers associated with grey relational analysis to improve the insufficient information and overcome the incomplete system under uncertainty.

The findings support the argument that the triple bottom line is insufficient to cover the entire concept of SSCM; in particular, the aspects of operations, stakeholders and resilience have not been addressed in previous studies.

The results reveal that the triple bottom line concept is insufficient to illustrate the principles of SSCM and to provide an extensive basis for theory development. The aspects and criteria considered in the study only relate to the studied company and may need to be reviewed when applied to other industries.

The methodology and findings of the study demonstrate the core applications of criteria ranking and identify priority areas that utilize less investment but that may maintain the studied company’s current performance. Suggestions for the prioritization of criteria to enhance SSCM performance are provided.

The present study provides three valuable contributions. First, it adopts collaboration theory to furnish a theoretical foundation for SSCM. Second, the proposed hybrid method is able to overcome uncertainty and subsequently evaluate SSCM while utilizing incomplete and imprecise information. Third, the evaluation provides significant results for consideration in decision making by the studied company.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

The new age of entrepreneurs recognizes crowdfunding as an innovative and effective means of obtaining funding from backers. However, attracting backers is challenging and related scholarly knowledge lacking. Therefore, this study investigates the diverse factors influencing backer funding intention in reward-based crowdfunding.

This study conducted an online survey of 401 registered backers from two reward-based crowdfunding platforms in Taiwan. Data were analyzed using covariance-based structural equation modeling.

Results show that entrepreneur activeness has a negative effect on perceived risk but positively, while entrepreneur activeness and platform interactivity have a positive effect on backer engagement and backer value creation. Although it had no significant impact on backer engagement, project novelty positively influenced backer value creation. Perceived risk had no influence on either backer engagement or backer value creation. Backer engagement positively influenced backer value creation and backer funding intention, with the former having a positive impact on the latter.

This study provides a multi-perceptual lens by proposing an integration of diverse factors such as entrepreneurial- (entrepreneur activeness), project- (project novelty and perceived risk) and platform-related characteristics (platform interactivity) as antecedents to backer funding intention. By integrating a service-dominant logic perspective into the stimulus-organism-response model, this study highlights the essence of value creation by perceiving backers as value co-creators.

The purpose of this paper is to develop an extended Push-Pull-Mooring-Habit (PPMH) framework in order to better understand users’ intention of switching from offline to an online real-person English learning platform service.

Based on 301 valid responses collected from an online survey questionnaire, structural equation modeling was employed to examine the research model.

The causal model was validated using SmartPLS 3.0, and all study hypotheses were supported. The results show that push effects (learning convenience, service quality and perceived price), pull effects (e-learning motivation, perceived usefulness), mooring effects (learning engagement, switching cost and social presences) and habit effects (relationship inertia) all significantly influence users’ switching intentions from offline to an online real-person English learning platform.

The findings should help online English learning service providers and marketers to understand the intention of offline English learning users to switch to an online real-person English learning platform, and develop related theories, services and regulations.

The present study extends the prior research of an online real-person English learning platform by providing PPMH as the general framework and demonstrating its efficacy in explaining user switching intentions.

In his autobiography, Chen Shui-bian (1999, p. 40) condemned the Koumintang's (KMT's) corruption and praised the Democratic Progressive Party (DPP) for being free from money politics and corruption. The DPP fought the 1992 Legislative Yuan election campaign effectively on an anticorruption platform and used the same strategy in subsequent elections. If Chen Shui-bian had criticized the KMT for its involvement with “black gold” politics and had won the 2000 presidential election on his anticorruption platform, why was he and his family found guilty of corruption after his second term of office? The short answer is that even though he had promised to curb corruption, President Chen himself had succumbed to corruption after assuming office. In June 2002, Keesing's Contemporary Archives cited a poll in Taiwan that indicated that more respondents had perceived the DPP to be more corrupt than the KMT (Copper, 2006, p. 14).