Application of Multi-Criteria Decision-Making Analysis to Rural Spatial Sustainability Evaluation: A Systematic Review

A system dynamics model and analytical hierarchy process: an integrated approach for achieving sustainable solid waste management system

Waste management in low-income countries faces challenges with an average cost of $35/ton approximately 51% collection efficiency. Despite investments in treatment, processing, and recycling, the system remains unsustainable owing to poor planning and policies. The current analysis of Lahore's solid waste management (SWM) system, selected as a major city of a low-income country as a case study, focuses on collection efficiency and waste generation. However, it neglects the complex and dynamic nature of SWM systems. To capture the complexities and dynamic nature of the SWM system, system dynamic (SD) modeling is proposed for its effectiveness in modeling complex and dynamic systems. Unlike previous attempts at SD modeling that mostly consider only some components of the SWM system with varying success, this study attempts to use a holistic approach by considering all aspects of an integrated SWM system. In addition, this study explores different financial and management policies, highlighting the weaknesses of the system through a quantitative comparison of three scenarios: (1) business-as-usual (BAU) which considers the current trends in waste generation and practices of collection and disposal to landfill, (2) waste treatment system (WTS) in which various waste treatment systems are included to reduce burden on landfill, and (3) introduction of user fee with awareness campaigns (UFAC) which encourages community participation towards reduction in waste generation and financially supports the SWM. All three scenarios use four indices: waste generation, waste ending up in landfill, uncollected waste, and annual budget deficit as performance indices. These scenarios were simulated over a 25-year period using an SD model, covering all six components of the SWM system. The BAU scenario shows a 16% increase in waste generation, a 173% increase in landfill waste, an 11% reduction in uncollected waste, and a 64% increase in the budget deficit over the simulation period, indicating an unsustainable SWM system. The WTS scenario exhibits a 16% increase in waste generation, a 155% increase in landfill waste, an 11% reduction in uncollected waste, and a 61% increase in the budget deficit, showing a significant reduction in landfill waste and a slight reduction in deficit but it remains unsustainable. The UFAC scenario, however, results in a 40% reduction in waste generation, a 67% decrease in uncollected waste, an 8% decrease in landfill waste, and a 59% decrease in the budget deficit. These results demonstrate that instituting user fees for SWM services and incentivizing community participation towards waste reduction and segregation can make the SWM system of Lahore sustainable. This SD model provides insights for policymakers, aiding what-if analyses and long/short-term waste management plans for metropolitan cities in low-income countries. To validate the sustainability judgments based on performance indices, the analytical hierarchy process (AHP), a multi-criteria decision analysis (MCDA) tool commonly used for ranking policy decisions based on competing criteria, was employed. It considered the same four criteria as in the SD model. The results of the AHP analysis aligned with those of the SD model, ranking the UFAC scenario as the most sustainable option.

Siting MPAs for multiple protecting purposes by co-consideration of ecological importance and anthropogenic impacts

The global marine ecosystem has been significantly altered by the combined effects of multiple anthropogenic impacts. Systematic planning of marine protected areas (MPAs) is of paramount importance in alleviating conflicts between humans and the sea. Existing approaches, however, merely integrate both ecological and anthropogenic factors for multiple conservation purposes. By combining the three main anthropogenic impact factors with two main ecological importance factors, this study used a GIS-based AHP-OWA method to identify different levels of priority protection for MPAs in Zhejiang, China. Our results proved that: 1) the multi-objective MPA siting issues can be addressed by the GIS-based AHP-OWA method through scenario simulation; 2) the best locations for MPAs are in the northeast, central, and southern marine areas of Zhejiang; 3) considering the trade-off degree, spatial conservation efficiency, and spatial heterogeneity, an optimized MPA siting scheme can be developed for decision-makers. The proposed MPA siting method and case study may provide an effective technical reference for solving regional marine spatial planning (MSP) issues in the future.

A participatory multicriteria decision analysis of the adaptive capacity-building needs of Jordan's agribusiness actors discloses the indirect needs downstream the value chain as “post-requisites” to the direct upstream needs

Climate adaptive capacity-building initiatives and activities in developing countries, particularly those implemented by developmental agencies and international organizations, commonly focus on the upstream direct adaptive capacity-building needs of targeted vulnerable sectors. However, overlooking a holistic climate-adaptive capacity-building of a vulnerable sector down to the last link of its value chain renders inadequate contribution, jeopardizes the adaptation intervention, and prevents achieving a high level of buy-in of the chain actors for the results of the sought capacity-building programs. Thus, this study developed a hybrid system-wide and participatory (focus groups-based) multi-criteria decision analysis (MCDA) to conduct adaptive-capacity needs assessments for the actors of the agribusiness value chain of the developing country of Jordan. Our holistic approach enabled highlighting the sector's climate vulnerability along the value chain, conducting self-regulated adaptive training needs assessment (TNA) of the sector's actors and identifying and prioritizing their real adaptive capacity-building needs. This approach proved to be uniquely advantageous in comparison to the sector's commonly used questionnaire-based surveys that are limited-participatory, researcher-regulated, and subsystem-oriented approaches. The advantages of this hybrid hands-on and wide-ranging MCDA–TNA approach are evident from its revelation of unique results. The approach enabled actors of such a highly vulnerable sector to spontaneously identify and prioritize the indirect downstream climate adaptive capacity-building needs surprisingly over the direct needs. This is because the actors considered the indirect needs more important to their businesses and livelihoods than the direct needs, thus considering the indirect needs as “post-requisites” of the fate of the direct upstream needs. The hybrid approach also enabled the beneficiaries to formulate the intervention outcomes, unveil the factors ignored by the conventional researcher-controlled approaches, secure high buy-in of the self-attained results, and prioritize the actual adaptive capacity-building demands. This robust combination of qualitative research methods and tools could be straightforwardly applied to design and conduct efficient and cost-effective adaptive capacity-building programs, especially during time-restricted and resource-limited interventions. The results of such types of quick and cost-effective qualitative investigations of adaptive capacity-building needs could be considered a preliminary and a first step toward deeper and more extensive quantitative studies, if needed.

Performance and Obstacle Tracking to Qilian Mountains’ Ecological Resettlement Project: A Case Study on the Theory of Public Value

In Gansu Province, China, Wuwei City is an ecologically fragile migration area at the intersection of the Loess Plateau, the Qinghai-Tibet Plateau, and the Mongolia-New Plateau. Using the Triangular Fuzzy TOPSIS method and the obstacle factor diagnostic model, the implementation performance and follow-up support issues of the Ecological Resettlement Project were analyzed from the perspective of the eco-migrant and the public value theory. In contrast to traditional performance appraisal methods, Triangular Fuzzy TOPSIS breaks through the ambiguity of complex environments and subjective information and effectively quantifies the fuzziness of evaluator language variables to improve the validity. The overall performance of the Ecological Resettlement Project in Wuwei is good; the average closeness degree of process is higher than outcome. Migrants rated the fairness of the project as the highest, followed by support, economic outcome, and satisfaction. Gulang County’s performance in the Ecological Resettlement Project is the best, followed by Tianzhu County and Liangzhou District. Project obstacles were mostly related to the outcome dimension, especially the ecological restoration and management, the return to poverty risk, and industrial development on the resettlement site. The main obstacle to the process dimension is migrant satisfaction with government subsidies. Research results provide case study support and experience inspiration for migrant relocation models and their long-term livelihood improvement in the context of rural revitalization.

Creating a Healthy Environment for Children: GIS Tools for Improving the Quality of the Social Welfare Management System

Childhood is considered to be the most vital period for mental, physical, and social development. Even short-term deprivation of nutrition, health care, education, and affection in childhood can have long-term and irreversible negative consequences. Various social assistance programs are being launched around the world to eliminate or alleviate social problems, including those experienced by children in their immediate environment. Different solutions have been proposed around the world, but welfare systems in all countries share the following common features: social assistance is necessary and underfinanced, and social workers struggle to cope with caseloads. As a result, welfare work is stressful and not highly effective. In this study, modern Geographic Information System (GIS) tools for supporting the employees of social assistance centers (SACs) have been proposed. The data relating to welfare beneficiaries were analyzed by nonparametric kernel density estimation and divided into five datasets. The kernel density tool in ArcGIS Pro software (Esri Polska sp. z o.o., Warsaw, Poland) was used to visualize areas with a relatively high prevalence of social problems, as well as areas where the neighborhood can deliver synergistic effects. A multicriteria analysis (MCA) procedure for mapping social problems was proposed, and an algorithm was developed in the GIS environment. The generated maps deliver helpful information for supporting SAC employees, as well as monitoring, planning, and initiating preventive measures. Above all, the presented method was designed to improve living conditions by facilitating the management of welfare workers' duties. Therefore, the proposed approach had to be effective and easy to use without an advanced knowledge of GIS tools.