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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 research proposes and examines a theoretical model grounded in anthropomorphism theory considering the curvilinear and linear relationships between service robot anthropomorphism and consumer usage intention and explores the mediating effect of perceived risk.

To examine the developed model, two complementary studies are designed. In Study 1, multi-time data of 511 participants show that service robot anthropomorphism inverts U-shaped (curvilinear) relationship on consumer usage intention and perceived risk mediates this curvilinear relationship. In Study 2, multi-source data of 460 volunteers are used to confirm the findings of Study 1 and examine that consumer empathy moderates the complex nonlinear effect of service robot anthropomorphism on perceived risk, and the indirect curvilinear effect of service robot anthropomorphism on consumer usage intention through perceived risk.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

The purpose of this paper is to propose a dedication-constraint-temptation (DCT) model to study the factors influencing customers’ loyalty to mobile data service (MDS) providers. The DCT model explicitly explores the important yet overlooked role of alternative attractiveness (the temptation-based mechanism) as a mediator and the boundary condition of their interrelationships (e.g. relationship length). The model also integrates new and established antecedents of customer-based brand equity (C-BBE) (the dedication-based mechanism) and switching barriers (the constraint-based mechanism).

The proposed model is tested using partial least squares–structural equation modeling with a sample of 331 MDS users.

The results indicate that C-BBE has an indirect effect on customer loyalty (via alternative attractiveness) in both relationship groups (shorter- vs longer-term). However, the indirect effect of switching barriers on customer loyalty only exists in longer established relationships. The results from multi-group analysis reveal that the effect of switching barriers on alternative attractiveness significantly differs across groups. In addition, customer value anticipation and procedural switching costs appear to be the most salient antecedents of C-BBE and switching barriers for both groups.

This study makes an incremental contribution by incorporating the temptation-based mechanism as a mediator and relationship length as a moderator into the dedication-constraint model. This study also extends the information systems and brand management literatures by demonstrating the strategic importance of customer value anticipation in the information and communication technology brand equity-building.

This paper aims to contribute significantly to the empirical investigations on adopting Industry 4.0–circular economy in the Malaysian palm oil industry. The paper also aims to theorise and empirically assess a comprehensive model incorporating three aspects and 51 criteria.

A two-stage methodology is proposed using the fuzzy Delphi method and the fuzzy-based analytical network process. Twenty-seven criteria on adoptability of industry 4.0–circular economy were selected for the first-stage methodology, followed by identifying each criteria's intersection with the overall objectives.

The findings indicate that financial constraints, the lack of a collaborative I4.0–CE model, laws and policy, low management support and the training of dedicated employers in I4.0–CE-application are the top five criteria requiring critical attention from the POI.

The overall sustainability advantages of the POI are identified and discussed in depth to establish criteria for industry 4.0–circular economy applications.

This study fills the previous research gap by theoretically explaining POI's industry 4.0 adoption–circular economy from the perspective of two underpinning theories. Due to the pressure towards sustainability, the industry must be ready to adopt industry 4.0–circular economy applications, and resources must be managed appropriately and effectively by sharing and integrating. Advanced industry 4.0 technologies and pragmatic practices such as a circular economy are needed to achieve optimal sustainable development while retaining commercial success.

Sustainable waste management (SWM) leads to human safety by eliminating dangerous substances, increasing cost efficiency and reducing environmental impacts. Integrating social, economic and environmental factors is the standard for successfully implementing SWM. However, prior studies have not incorporated the triple bottom line with technological performance and occupational safety in establishing SWM. To drive sustainability in waste management, this study aims to provide a set of SWM attributes and identify a causality model based on the interrelationships among the attributes.

This study used the Delphi method to list the relevant attributes and the decision-making trial and evaluation laboratory (DEMATEL) involving 18 experts from the medical and health-care industry to present the interrelationships indicating the group of cause–effect attributes of SWM.

The study selected 5 aspects and 20 criteria as the relevant attributes of SWM. The cause group consists of environmental impacts and occupational safety, with positive values of 27.031 and 24.499, respectively. The effect group includes technological performance, economic performance and social performance. In particular, the challenges and practices of technological performance are linked to environmental impacts and occupational safety.

The top four criteria for industrial improvement are green practices, government policy and rules, the awareness of workers and waste separation and collection. These results present deeper insights into theoretical and managerial implications.

This study contributes to addressing the challenges and practices of SWM in technological performance leading to environmental impacts and occupational safety. Studies on the technological performance aspect in the causality relationships between environmental impacts and occupational safety are lacking. This study describes SWM using qualitative information and quantitative data.

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.

Sustainable supply chain finance (SSCF) is a fascinated consideration for both academics and practitioners because the indicators are still underdeveloped in achieving SSCF. This study proposes a bibliometric data-driven analysis from the literature to illustrate a clear overall concept of SSCF that reveals hidden indicators for further improvement.

A hybrid quantitative and qualitative approach combining data-driven analysis, fuzzy Delphi method (FDM), entropy weight method (EWM) and fuzzy decision-making trial and evaluation laboratory (FDEMATEL) is employed to address the uncertainty in the context.

The results show that blockchain, cash flow shortage, reverse factoring, risk assessment and triple bottom line (TBL) play significant roles in SSCF. A comparison of the challenges and gaps among different geographic regions is provided in both advanced local perspective and a global state-of-the-art assessment. There are 35 countries/territories being categorized into five geographic regions. Of the five regions, two, Latin America and the Caribbean and Africa, show the needs for more improvement, exclusively in collaboration strategies and financial crisis. Exogenous impacts of wars, natural disasters and disease epidemics are implied as inevitable attributes for enhancing the sustainability.

This study contributes to (1) boundary SSCF foundations by data driven, (2) identifying the critical SSCF indicators and providing the knowledge gaps and directions as references for further examination and (3) addressing the gaps and challenges in different geographic regions to provide advanced assessment from local viewpoint and to diagnose the comprehensive global state of the art of SSCF.

This paper studies green vehicle routing problems of cold chain logistics with the consideration of the full set of greenhouse gas (GHG) emissions and an optimization model of green vehicle routing for cold chain logistics (with an acronym of GVRPCCL) is developed. The purpose of this paper is to minimize the total costs, which include vehicle operating cost, quality loss cost, product freshness cost, penalty cost, energy cost and GHG emissions cost. In addition, this research also investigates the effect of changing the vehicle maximum load in relation to cost and GHG emissions.

This study develops a mathematical optimization model, considering the total cost and GHG emission. The standard particle swarm optimization and modified particle swarm optimization (MPSO), based on an intelligent optimization algorithm, are applied in this study to solve the routing problem of a real case.

The results of this study show the extend of the proposed MPSO performing better in achieving green-focussed vehicle routing and that considering the full set of GHG costs in the objective functions will reduce the total costs and environmental-diminishing emissions of GHG through the comparative analysis. The research outputs also evaluated the effect of different enterprises’ conditions (e.g. customers’ locations and demand patterns) for better distribution routes planning.

There are some limitations in the proposed model. This study assumes that the vehicle is at a constant speed and it does not consider uncertainties, such as weather conditions and road conditions.

Prior studies, particularly in green cold chain logistics vehicle routing problem, are fairly limited. The prior works revolved around GHG emissions problem have not considered methane and nitrous oxides. This study takes into account the characteristics of cold chain logistics and the full set of GHGs.

The purpose of this paper is to propose a cradle-to-cradle (C2C) zero discharge production planning system with a fuzzy hybrid optimization model that uses fuzzy comprehensive evaluation to establish fuzzy indicators, and then defuzzify the fuzzy indicators to construct a fuzzy multiobjective programming (FMOP) model.

The FMOP model pursues overall satisfaction using a particle swarm optimization algorithm to produce the best output values for the maximum waste paper recovery rate, the condensate reuse quality and minimum total cost of the zero discharge production planning system.

Recovered waste heat is seldom recycled and consumed in Taiwan. There is a need to capture and utilize heat recovery and use it in the production process supply. In contrast, waste materials are used as resources to perform waste paper recovery and recycle the waste heat of evaporation collection in the production process.

This paper develops a system to establish the best output value for an overall high satisfaction level. According to the results, the waste paper recovery rate is 99.8 percent, condensate reuse quality water is 102.6 tons and the total cost of the zero discharge production planning system is NT$1,312,012.

The purpose of this paper is to analyze the wastewater discharge and a zero-wastewater-discharge (ZWD) reproduction plan is designed for a paper mill in Taiwan.

The proposed model of ZWD reproduction planning is established using the fuzzy comprehensive evaluation and Taguchi method to determine the overall wastewater recovery rate. Still the prior studies failed to address a systematic approach to optimize the waste water recovery rate.

The optimal solution for clean water is 500 tons, recovery electrodialysis reversal is 345 tons, the wastewater reuse performance is 1.3 and waste heat recycling performance is 0.8, the larger number is performed well. The results shows that the maximum overall waste water recovery rate is 97.8 percent.

A paper mill is strived for improving their sustainable development. In real situation, there is a need to address the qualitative information and qualitative data to carry out the optimal ZWD reproduction planning.