Improving the food waste composting facilities site selection for sustainable development using a hybrid modified MADM model

Psychological resilience factors in intensive care nursing: a hybrid multi-criteria decision-making model

PURPOSE

To analyze the key factors influencing the psychological resilience of intensive care unit (ICU) nurses during the COVID-19 pandemic and put forward suggestions promoting resilience based on key improvement factors and clinical experience.

METHODS

Data were collected from 35 ICU nurses in a hospital in Zhejiang Province, China, through a questionnaire survey conducted between January and February 2023. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was then used to construct and visualize the relationship structure between the factors. The DEMATEL-based Analytical Network Process (DANP) was applied to determine the influential weights of all factors. Finally, the key improvement factors were identified using importance-performance analysis (IPA).

RESULTS

Based on the cause-effect impact network diagram (CEIND), it was concluded that (C 11), (C 22), and (C 32) are the key factors that promote the improvement of psychological resilience among ICU nurses. Additionally, these factors were the key factors that influence psychological resilience. The confidence levels of these results and the gap were 99.6% and 0.4%, respectively, which exceed the threshold value of 95%, indicating good stability. Finally, for the case hospitals, (C 13) was identified as the key improvement factor.

CONCLUSIONS

Hospital administrators should support ICU nurses in enhancing their psychological resilience during major epidemics by: (i) Providing training on comprehensive protective measures and nursing skills; (ii) Effectively managing the human resources of nurses in the hospital to reduce their workload; (iii) Increasing social and organizational support for nurses to alleviate anxiety caused by large-scale public health events and improve their psychological resilience.

Applying DEMATEL-ANP approach to explore the intention to hold roadside wedding banquets in Penghu: A consumers' perspective

Most people associate Penghu with the roadside banquet, an iconic banquet in the area. Nevertheless, market demand for these banquets has lately fallen drastically, causing a severe impact on the industry. In this study, the critical factors influencing the choice to conduct roadside wedding banquets were investigated from the consumer's standpoint. Initially, on the basis of expert screening and literature study, 14 criteria covering five dimensions were developed. Subsequently, causal connections and impact weights were determined using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and DANP (DEMATEL-based analytic network process) models. The findings indicate that customers prioritise service quality in improvement initiatives. Dish quality, hygiene, and marketing are the most appreciated dimensions. Overall, customers place the highest significance on pricing. The industry is recommended to create online marketing platforms, raise the standard of wedding banquet services, combine the value chains of wedding services, and support the sustainable growth of the industry. The method used enriches existing theoretical approaches concerning roadside wedding banquets and is applicable in assisting wedding banquet providers' management in holding roadside weddings.

Spatiotemporal footprints of odor compounds in megacity's food waste streams and policy implication

Odor pollution is one of the most critical issues in food waste (FW) recycling and has significant implications for human health. However, knowledge of their occurrence and spatiotemporally dynamic in urban FW streams is limited, making it not conducive to implement targeted odor management. This work followed the occurrence of 81 odor compounds (OCs) in nine FW-air environments along the Shanghai's FW streams for one year. Results showed that NH₃, acetic acid, acetaldehyde, acetone, 2-butanone, and methylene chloride were consistently the predominant OCs, despite the distinct differences in OCs profiles across seasons and treatment sites. Ridge regression and principal coordinate analysis demonstrated that seasons might play a non-negligible role in shaping odor profiles, and ambient temperature and humidity could account for the seasonal variation in OCs levels. Based on the modified fuzzy synthetic evaluation system, the screened priority pollutants in different FW-air environments were found broadly similar and the regulated air pollutants released via FW should be expanded to aldehyde and ketone compounds, especially for acetaldehyde. To our knowledge, this study is the first to track the spatiotemporal footprints of OCs within urban FW streams, and provides new insights into the control policy on FW-derived odor issues for megacities.

Application of ArcGIS and QFD-based model for site selection for bio-medical waste disposal

With the increasing formalisation of the health sector in India, the bio-medical waste (BMW) disposal regulations are getting stringent and its implementation is being enforced strictly. The coronavirus disease 2019 (COVID-19) created a healthcare crisis because of the highly contagious nature of the novel virus. Measures employed for the prevention and management of COVID-19 resulted in the generation of an unprecedented amount of BMW in Indian medical history. This BMW needs to be disposed of safely at a suitable site to prevent secondary infection and the potential spread of the virus in the environment. The selection of an appropriate site for BMW disposal requires comparing a wide range of social, economic and environmental factors corresponding to different site locations, which makes it a multi-criteria decision-making (MCDM) problem. This study aims to solve the BMW site selection problems using a quality function deployment-based model that can consider both the subjective and the objective criteria, and evaluate them as per the user's requirements. The proposed model is applied to evaluate the suitability of waste disposal sites in the city of Bilaspur in Chhattisgarh, India. At first, eight possible locations for BMW disposal are identified, while utilising geographical information system (GIS). Consequently, the developed model is applied to evaluate the identified sites, taking 18 relevant criteria into consideration. A software prototype is developed in Visual BASIC 6 to automate the entire decision-making process, further adding to the novelty of the work.

Combining multi-criteria decision analysis with GIS approaches for decentralized organic wastes composting plants site selection in Tiassalé, Southern Côte d'Ivoire

In recent years, decentralized composting appeared as one of the most appropriate treatment options for organic waste valorization in low- and middle-income countries. In Cote d'Ivoire, a pilot project has proved the feasibility of organic municipal solid waste composting for the city of Tiassalé. However, numerous issues still need to be addressed for the establishment of a sustainable decentralized composting system in this city. One of the key issues is site selection. Until now, there is no clear model for such plant site selection. In this study, multi-criteria decision analysis (MCDA) and geographical information system (GIS) approaches were combined to develop an appropriate model for selecting decentralized composting sites in the city of Tiassalé. The methodology used involved two different and complementary phases. First, MCDA and GIS techniques were used to identify the most suitable site areas. Seven criteria clustered in three main factors (environmental, social and economic), and five constraints were considered in the analysis process. Second, five sites were selected within the most suitable areas after a basic field visit and ranked using the Analytic Hierarchy Process. The results showed that the most suitable spaces for decentralized composting plant siting represent only 2.6% of the study area. The investigation yielded on the selection of the two best options for decentralized composting plant siting for the city of Tiassalé. This study proved that the combination of MCDA and GIS is a practical and efficient method to identify suitable sites for decentralized composting plants.

The Determinants of Passengers’ Consumption Motivation at High-Speed Rail Stations

Exploring passengers’ consumption motivation can provide the basis for arranging commercial activities in high-speed rail (HSR) stations to generate more revenue for operations. This study uses a mixed multiple-attribute decision-making model for exploring the consumption motivation at HSR stations and complex influential relationships from the passengers’ perspective. The passenger traffic at five major HSR stations in Taiwan were evaluated. Based on the results of decision-making trial and evaluation laboratory (DEMATEL) and DEMATEL-based on the analytical network process methods, it is shown that station attributes and consumption environment attributes are key factors that impact product attributes. Moreover, store location, commercial activities offered, product diversity, time pressure, and service convenience have a “cause” characteristic and, therefore, should be focused on when deploying commercial services at HSR stations. The findings from the modified VlseKriterjumska Optimizacija I Kom-promisno Resenje method reveal that time pressure has the largest gap to aspiration level at almost all the stations. Finally, corresponding management implications to HSR stations are proposed.

Evaluate the locations for smart waste bins using BWM and WASPAS methods under a probabilistic linguistic environment

 The decreasing resources of the earth and the deterioration of the environment are offering new challenges for handling waste management practices. The establishment of the smart waste bins plays an important role in promoting the development of waste classification and treatment fundamentally. We developed the evaluation system for the location selection problem of smart waste bins. Considering the uncertainty in the location selection of smart waste bins, the probabilistic linguistic term sets (PLTSs) are selected to express the evaluation information. Because of the excellent performance in weight-determing, the best worst method (BWM) is chosen to get the weight of criteria. While the weighted aggregated sum product assessment (WASPAS) method could handle both the qualitative and quantitative information, which are considered to derive the final ranking of the alternatives. This paper proposed a new group multi-criteria decision making approach integrating the BWM and the WASPAS with probabilistic linguistic information. Finally, in the empirical example, a sensitivity analysis shows that the proposed method is stable, a comparison analysis with PL-TOPSIS, PL-VIKOR, and PL-TODIM reflects its effectiveness and rationality, and the managerial implication verifies its usefulness and practicability, which also give guide to the company, government and resident.

Redesigning the Municipal Solid Waste Supply Chain Considering the Classified Collection and Disposal: A Case Study of Incinerable Waste in Beijing

The output of municipal solid waste is growing rapidly, which has brought tremendous pressure to urban development. The supply chain of municipal solid waste (MSW) in China mainly contains three processes: collection, transportation, and disposal. The waste is sorted at the collection and disposed of according to the classification. However, it is mixed at the transportation stage. Mixed transportation remixes the separately collected waste, which seriously affects the disposal effect. The supply chain of MSW urgently needs to be redesigned to improve the MSW disposal effect. First of all, on the ground of the waste treatment situation, we redesigned the supply chain of MSW in China. Secondly, combined with the redesign of the MSW supply chain, this paper established the function allocation model for collection stations, making a collection station only gather one type of waste, and built the transportation path planning model for vehicles, reducing the impact of waste storage on residents. Finally, based on the data of Xuanwu District in Beijing, the supply chain redesigning practical example of incinerable waste was given. The supply chain redesigning model in this paper not only makes full use of the existing infrastructure but also improves the disposal effect of waste. The supply chain redesigning model has practical application value.

EXPLORING LOCATION DETERMINANTS OF ASIA’S UNIQUE BEVERAGE SHOPS BASED ON A HYBRID MADM MODEL

Identifying relevant location determinants is a good starting point for shop operators, help to increase profitability and, thus, avoiding business failure. Traditional Analytic Hierarchy Process (AHP) or the Analytic Network Process (ANP) have shortages that require improvement. Herein, Decision-Making Trial and Evaluation Laboratory (DEMATEL), ANP based on DEMATEL (DANP), and modified Vlse Kriterijumska Optimizacija I Kompromisno Resenje (modified VIKOR) are used to construct a hybrid multiple-attribute decision making (MADM) model, encompassing three dimensions and thirteen criteria in exploring the location determinants of Asia’s unique Bubble Tea Shops (BTSs) and to evaluate three preselected alternatives in Nanjing, China. The empirical findings of the DEMATEL method reveal that traffic traits (D1) and site traits (D2) are critical to BTSs, and that once these are enhanced, shop traits (D3) are also improved. Criteria deemed as important, based on the DEMATEL and DANP methodology, are (in descending order): proximity to a street corner (C2), proximity to public transportation systems (C1), road width (C3), proximity to communities (C5), proximity to commercial areas (C6), types of shop (C9), and proximity to schools (C7). Different decision-making rankings among alternatives are indicated based upon the modified VIKOR method and corresponding strategies for improvement are presented.

Sustainable waste disposal technology selection: The stratified best-worst multi-criteria decision-making method

Waste disposal technology selection is a key problem in the field of municipal solid waste (MSW). This decision may have long-term impacts on environmental development and economic growth. The literature suggests using multi-criteria decision-making (MCDM) methods to address this problem. MCDM techniques commonly require decision makers to assign weightings of importance to the decision criteria based on which, the available technologies are ranked. However, this technology selection problem is concerned with selecting a technology to be used for a relatively long period of time. It is important to take into consideration any uncertainty the decision maker may have with regard to the weightings of the criteria in the future. To take this uncertainty into consideration, this study suggests utilizing a recently developed MCDM technique, namely the stratified MCDM. This technique is designed to help decision makers structure the uncertain future through the consideration of a set of states, which are placed in different strata. The paper shows how the stratified MCDM technique in combination with the best-worst method (labelled stratified BWM) can be employed to compute the ranking of the available technologies. This research is expected to stimulate future applications of the stratified BWM to facilitate long-term decision making.

A Conceptual Framework to Analyze Food Loss and Waste within Food Supply Chains: An Operations Management Perspective

Alongside the development of the circular economy and sustainable food supply chains (FSCs), research on food loss and waste (FLW) reduction and prevention has drawn much attention from academia, practitioners, and governments. The significance of FLW has been highlighted in the literature due to its impact on society, economy, and the environment. We propose a conceptual framework to systematically examine FLW issues within FSCs in the field of operations management (OM). We discuss various types and distribution modes of FSCs where FLW occurs, definitions of FLW, the impacts of FLW, and measures to reduce FLW in the OM field. We further introduce the methodologies that have been applied in existing FLW studies. The contribution of this paper is threefold. First, it proposes a conceptual framework to identify FLW problems within FSCs. Second, it helps to comprehensively understand FLW occurrence and thus stimulate research focusing on FLW from different perspectives. Third, it motivates researchers to discuss FLW issues by applying different methodologies.

Sustainable Smart Healthcare Information Portfolio Strategy Evaluation: An Integrated Activity-Based Costing Decision Model

Smart city and smart hospital development comprise a mainstream strategy worldwide to enhance the achievement of Sustainable Development Goals (SDGs) and Corporate Social Responsibility (CSR) practices. The smart healthcare industry needs to optimize its smart healthcare information strategies, creating the process-activity value and reducing the cost of healthcare without sacrificing the quality of patient care. This study proposes an decision model of Activity-Based Costing (ABC) concept and Multi-Criteria Decision-Making (MCDM) techniques that integrates the Decision-Making Trial and Evaluation Laboratory (DEMATEL), Analytic Network Processes (ANP), the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Zero-One Goal Programming (ZOGP) to achieve optimal smart healthcare information system portfolio strategy decisions. The resulting data shows that the perspective of government policy support and the criterion of Minimize Equipment Maintenance Costs are the most significant evaluation factors, and that the Health Data Informational System and Hospital Device and Drug Management System comprise by far the optimal portfolio of smart healthcare information system which strengthen the connection between ABC and MCDM techniques in evaluation process. The major contributions of this study are as follows: (1) the proposed model contributes to the management accounting innovation development of a sustainable city and Operation Research (OR) application; (2) the integrated model can promote the smart healthcare industry development and help decision makers to more accurately understand how to allocate resources and planning for intelligent-related activities to each smart healthcare information system through appropriate cost drivers.

Establishing a Sustainable Sports Tourism Evaluation Framework with a Hybrid Multi-Criteria Decision-Making Model to Explore Potential Sports Tourism Attractions in Taiwan

In recent years, the awareness of sustainable tourism has risen around the world. Many tourism industries combine sports to attract more customers to facilitate the development of the economy and the promotion of local culture. However, it is an important task to establish a comprehensive tourism evaluation framework for sustainable sports tourism. This study proposes a Multi-Criteria Decision-Making (MCDM) model to discuss the above issues, using the Bayesian Best Worst Method (Bayesian BWM) to integrate multiple experts’ judgments to generate the group optimal criteria weights. Next, the modified Visekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) technique is combined with the concept of aspiration level to determine the performance of sports attractions and their priority ranks. In addition, this study adds a perspective of institutional sustainability to emphasize the importance of government support and local marketing. The effectiveness and robustness of the proposed model is demonstrated through potential sports tourism attractions in Taiwan. A sensitivity analysis and models comparison were also performed in this study. The results show that the proposed model is feasible for practical applications and that it effectively provides some management implications to support decision-makers in formulating improvement strategies.

Developing A Sustainable Urban-Environmental Quality Evaluation System in China Based on A Hybrid Model

In China, with the acceleration of urbanization, people pay more attention to the quality of urban environment. Air pollution, vegetation destruction, water waste and pollution, and waste sorting have restricted the sustainable development of urban environment. It is important to evaluate the impact of these environmental concerns as a prerequisite to implement an effective urban environmental sustainability policy. The aim of this paper is to establish a system for evaluating sustainable urban environmental quality in China. We extracted six dimensions and 29 criteria for assessing urban sustainable environment. Then, a fuzzy technique and the best worst method were applied to obtain the weights for the dimensions and criteria. Next, grey possibility values were applied to evaluate the sustainable environmental quality of five cities: Beijing, Shanghai, Shenzhen, Guangzhou, and Hangzhou in China. A sensitivity analysis was performed to identify how the ranking of these five cities changed when varying the weights of each criterion. The results show that pollution control, the natural environment, and water management are the three most important dimensions for urban environmental quality evaluation. We suggest that controlling pollutant emissions, strengthening food waste management, improving clean production processes, and utilizing heat energy are the effective measures to improve the urban environment and achieve sustainable urban environmental development.

Combining AHP-Entropy Approach with GIS for Construction Waste Landfill Selection-A Case Study of Shenzhen

With the recent fast economy development and rapid urbanization, the huge generation of construction waste has become a threat to sustainable development in China. Though efforts have been made to promote reuse and recycling of construction waste, landfilling of waste remains the most commonly adapted approach for construction waste disposal. As the space for landfills is limited and because of the negative issues in terms of environmental and social aspects that may be caused, the appropriate site selection of landfills is crucial. With this background, this paper aims to establish a framework for facilitating landfill selection for construction waste. To begin with, a total of sixteen factors that may influence landfill site selection were identified from a literature review. Then, based on the combined analytic hierarchy process (AHP) and entropy method, the weights and the final comprehensive scores of the identified factors were calculated. According to the derived results, potential sites for landfills were divided into three levels, namely the most appropriate (0.38%), appropriate (17.58%), and inappropriate (82.04%). The proposed decision-making methods in this paper can provide a valuable reference for the selection of construction waste landfill sites.

A comprehensive multi-criteria decision making-based land capability assessment for municipal solid waste landfill sitting

The municipal waste management has always been one of the most challenging environmental concerns. Today, although different strategies have been developed, sanitary disposal of municipal waste is still considered as one of the most widely used alternatives, especially in developing countries such as Iran. To investigate the land capability of Pishva, for landfill sitting, the important criteria were categorized in two groups of ecological and socioeconomic and then a multi-criteria decision-making model was used with decision-making trial and evaluation decision-making trial and evaluation (DEMATEL)-analytical network process (ANP) approach. First and foremost, the interaction of criteria was determined implementing DEMATEL. It was found that the soil depth criterion not only is the most effective but also is the most influenced one. Moreover, ANP structure was developed to weigh the criteria. In comparison to socioeconomic criteria, ecological ones play a more significant role. Afterwards, factor maps and constraints were standardized using fuzzy and Boolean logic, respectively, and all layers were combined to generate the final capability map of Pishva applying WLC method. The capability map showed that 71% of the area is not capable of landfilling, and only 5% of Pishva has a high capability. The results proved the great effectiveness of the methods proposed in this study.