Poverty, Migration, and Marginalization: Socioeconomic Consequences of Climate‐Induced Land Degradation in Sub‐Saharan Africa

Ecological restorations enhance ecosystem stability by improving ecological resilience in a typical basin of the Yangtze River, China

Multi expert and multi criteria evaluation of sectoral investments for sustainable development: An integrated fuzzy AHP, VIKOR / DEA methodology

Developing a Multi-Criteria Decision-Making model for nuclear power plant location selection using Fuzzy Analytic Hierarchy Process and Fuzzy VIKOR methods focused on socio-economic factors

Land degradation poses a critical threat to the stability and security of ecosystems, especially in salinized areas. Monitoring the land degradation of salinized areas facilitates land management and ecological restoration. In this research, we integrated the salinization index (SI), albedo, normalized difference vegetation index (NDVI) and land surface soil moisture index (LSM) through the principal component analysis (PCA) method to establish a salinized land degradation index (SDI). Based on the SDI, the land degradation of a typical salinized area in the Central Asia Amu Darya delta (ADD) was analysed for the period 1990–2019. The results showed that the proposed SDI had a high positive correlation (R2 = 0.89, p < 0.001) with the soil salt content based on field sampling, indicating that the SDI can reveal the land degradation characteristics of the ADD. The SDI indicated that the extreme and strong land degradation areas increased from 1990 to 2019, mainly in the downstream and peripheral regions of the ADD. From 1990 to 2000, land degradation improvement over a larger area than developed, conversely, from 2000 to 2019, and especially, from 2000 to 2010, the proportion of land degradation developed was 32%, which was mainly concentrated in the downstream region of the ADD. The spatial autocorrelation analysis indicated that the SDI values of Moran’s I in 1990, 2000, 2010 and 2019 were 0.82, 0.78, 0.82 and 0.77, respectively, suggesting that the SDI was notably clustered in space rather than randomly distributed. The expansion of unused land due to land use change, water withdrawal from the Amu Darya River and the discharge of salt downstream all contributed to land degradation in the ADD. This study provides several valuable insights into the land degradation monitoring and management of this salinized delta and similar settings worldwide.

Investigation of the Potentials and Obstacles for Diversifying Livelihood Leading to Sustainable Rural Development (Case Study: Rezvanshahr County)

A wide range of product lifecycle management (PLM) maturity models are proposed to assess the relative position of companies on their road to complete PLM implementation. However, it is a tough job for the company to dynamically evaluate the gradual process of PLM maturity by using existing values and accurately make decisions of improving PLM maturity by selecting the optimum alternative. A fuzzy PLM components maturity model (PCMA) is presented to build the internal logical relationship between maturity levels and existing values that can automatically predict the unknown PLM maturity levels. A fuzzy AHP–VIKOR methodology is used to make a decision among option PLM strategies. The weights of the criteria are determined by fuzzy pairwise comparison matrices (PCM). The weights of alternatives with respect to criteria are calculated by fuzzy VIKOR. The fuzzy AHP–VIKOR is a compromise solution and has the ability of transfer subjective and implicit linguistics into objective and transparent data. A numerical example illustrates and clarifies the running steps of the proposed methodology.

A new Fine-Kinney-based risk assessment framework using FAHP-FVIKOR incorporation

Supplier selection is not an easy process as it typically involves multiple criteria and it requires human judgment. Therefore, there is a need to have a better system for supplier selection due to uncertainty and vagueness that exist in dealing with the multiple criteria decision making (MCDM) problem. This study is aimed to identify the important criteria for the selection of the best pharmaceutical raw materials supplier for XYZ Pharmaceutical Manufacturing company by using Fuzzy Analytical Hierarchy Process (AHP) and Fuzzy VIKOR approaches. Furthermore, this paper also presents the comparison results between the two methods in determining the best supplier. Fuzzy theory was used since it provides a right tool to encounter the uncertainties and complexity of decision making environment. This study investigated eight alternative suppliers based on seven criteria evaluated by two decision makers from the company. This study has successfully identified the top three most important criteria for the selection of supplier, namely, Regulatory Compliance, Price, and Product Variety. This study highlighted that Regulatory Compliance is a new important criterion for the pharmaceutical company to consider in future supplier selection. Based on the alternative results of Fuzzy AHP, it was found that the top three most important supplier were A5, A3 and A1. While based on the alternative results of Fuzzy VIKOR, it showed that the top three most important supplier were A5, A3 and A7. The comparison results between the two methods have shown that the Fuzzy VIKOR method is more suited to the problem of supplier selection.

(ProQuest: ... denotes formulae omitted.)1.IntroductionEnergy is one of the most important parts of economic and social development. In addition, it is indispensable and non-substitutable in numerous fields of daily life. The importance of energy is increasing day by day in consequence of rapid development in technology, population growth and increase in life standards in the public life. Net growth of the consumption of energy is actualized by developing economies. Turkey has an increasing population with its developing economy. It performs transformation from agriculture to industry in contrast to developed economies and it also takes part in the most rapid developing energy markets. While the global energy needs which increases with the amount of %2 in a year, it is at %6-%8 level that 3-4 times more than world average energy need in Turkey (dogaka.gov.tr). From this point, in developing economies like Turkey, energy sectors have important structural links with other sectors of economy. Following the developments of these sectors which provide substantially input to other sector of economy is quite important. Profitability which is one of the main purposes of firms has more importance in competitive business environment. It is the fact that the high performing firms will exist in this competition environment. The performance of these firms will be important not only for their subsistence but also for investors, creditors and economy of the country.In this sense, it is inevitable to evaluate the performances of the energy firms. Financial ratios are widely used for evaluating a firm's performance and financial situation. The performance evaluation of a firm helps investors to make investment decisions as well as gives information about the firms. In the literature, researchers have used various multi-criteria decision making models (MCDM) for the performance evaluation in different sectors. For instance, Feng and Wang (2000); Wang (2008) carried out TOPSIS and Fuzzy TOPSIS methods for the performance evaluation in aviation, Yurdakul and ic (2003) used TOPSIS method in automotive sectors respectively. Chou and Liang (2001) used AHP in shipping, Xia and Wu (2007); Chamodrakas and Martakos (2010) utilized AHP and Fuzzy AHP for supplier selection respectively. Also Yalcin, Bayraktaroglu and Kahraman (2012) used Fuzzy AHP, VIKOR and TOPSIS methods in manufacturing sector. Fuzzy AHP and TOPSIS are carried out in performance evaluation of airports (Chang, Cheng & Wang, 2003); cement firms (Ertugrul & Karakasoglu, 2009) and banks (Mandic, Delibasic, Knezevic & Benkovic, 2014; Mahrooz, Maedeh & Morteza, 2013; Secme, Bayraktaroglu & Kahraman, 2009). Fuzzy AHP (Weifeng & Huihuan, 2008) and Fuzzy TOPSIS methods are also used in banking (Akkoc & Vatansever, 2013). Sun (2010) also utilized Fuzzy AHP and Fuzzy TOPSIS methods for computer companies. Kalogeras, Baourakis, Zopounidis and Van Dijk (2005) employed PROMETHEE for food firms. Ignatius, Behzadian, Malekan and Lalitha (2012) used PROMETHEE II for the performance evaluation of the automotive firms. Erginel and Senturk (2011) carried out Fuzzy ANP for the ranking of GSM operators. For the energy firms Ergul (2010) and Sakarya, Yildirim and Akku§ (2015) used TOPSIS method.As it is seen there are few studies in the literature that Fuzzy AHP and Fuzzy TOPSIS methods are integrated for the performance evaluation of energy firms. In the study, we evaluate the financial performances of energy firms for the period of 2008-2013 with utilizing the Fuzzy AHP and Fuzzy TOPSIS methods. The weights of the criteria are determined by Fuzzy AHP method and then Fuzzy TOPSIS method is used for the rankings of the energy firms. Traditional multi-criteria decision making methods are not used in this study, due to the fact that they are insufficient under uncertainty. After 2008 global crisis, the uncertainty has increased all over the world hence the usage of fuzzy methods can provide better results under these conditions. …

Computerized Tomography Scanners (CT-SCAN) provide detailed cross-sectional images of the human body which are employed for the easier detection and further analysis of abnormalities concerning the functionality and structure of the skeleton, tissues, and organs. However, the appropriate CT-SCAN selection is an arduous task considering the complexity and high cost of these medical devices. This decision is even more sharpener in hospitals from Low-and-Middle-Income-Countries (LMIC) where the available budget is usually restricted and correct resource allocation should be therefore ensured while granting the greatest impact on the timeliness and efficacy of healthcare services. In this framework, multiple criteria from diverse fields need to be taken into account to satisfy the intricate requirements of users. In this regard, it is necessary to fully elicit the expectations of stakeholders as well as identify their importance in an overall decision-making context. To address these gaps, this study proposes a novel integration between the Fuzzy Analytic Hierarchy Process (FAHP) and VIKOR methods for the CT-SCAN selection problem. Initially, a Multi-Criteria Decision-Making (MCDM) model will be designed for selecting the most suitable CT-SCAN option for a particular LMIC hospital. Then IF-AHP will be applied to calculate the relative priorities of criteria and sub-criteria under uncertainty. Ultimately, VIKOR will be implemented for obtaining an overall decision-making context. To address these gaps, this study proposes a novel integration between the Fuzzy Analytic Hierarchy Process (FAHP) and VIKOR methods for the CT-SCAN selection problem. Initially, a Multi-Criteria Decision-Making (MCDM) model will be designed for selecting the most suitable CT-SCAN option for a particular LMIC hospital. Then IF-AHP will be applied to calculate the relative priorities of criteria and sub-criteria under uncertainty. Ultimately, VIKOR will be implemented for obtaining an overall appropriateness index per CT-SCAN candidate and thereby identifying the most pertinent one (s) for a specific LMIC medical institution.

Energy storage systems are becoming increasingly important, with a growing focus on renewable energy sources that provide highly fluctuating output. Therefore, sound decisions regarding the energy storage systems to be employed need to be made, especially with a systematic and semantic approach. This paper considers the problem of evaluation and selection of energy storage technologies (ESTs). The objective of the proposed research is to decide the best technology for energy storage under the novel idea of hybrid multicriteria decision-making technique under fuzzy environment, that is, fuzzy AHP with fuzzy VIKOR. Electrochemical storage, electrical storage, magnetic storage, mechanical storage, and chemical storage are considered as five alternative energy storage technologies. Energy density, life cycles, cycle efficiency, investment level, suitability to climatic conditions, and required space are considered as six main evaluation criteria. Under each of the main criteria, a set of subcriteria are also considered. The weights of main criteria and subcriteria are determined using fuzzy AHP. With the help of the weights of each set of subcriteria, the weights of alternatives are determined using fuzzy VIKOR. Further, with the help of the main criteria weights and the weights of alternatives determined with respect to each set of subcriteria, the final normalized weights of alternatives are determined. Based on these weights, energy storage technologies are ranked. In addition, the sensitivity analysis is carried out to analyze the variation in ranking pattern of alternatives. From the research findings of this paper, the results are found to be more practical as the evaluation is carried out on an objective basis.

Poverty has been linked to the reality of the world’s developing countries, especially in far-flung rural areas where the lack of energy access plays a significant role in the misery of the poor and disadvantaged people. To achieve universal access to energy, the role of rural electrification was emphasized, and off-grid small-scale electricity generation from renewable sources was expected to be a promising solution. However, in the Philippines, where off-grid island communities are scattered along its archipelago, the deployment of such systems in rural areas is still a challenge among stakeholders due to the consideration of various conflicting factors that may put the potential economic gains and other social and environmental benefits at risk. To better understand the multifaceted nature of off-grid energy system sustainability through the perspective of its stakeholders, the Fuzzy Analytical Hierarchy Process (FAHP) was used to determine their most prioritized factors in determining the viability and sustainability of such systems following the GPESTLE framework. This provides a comprehensive and more relevant approach to performing sustainability analysis by looking into the geographical (G), political (P), economic (E), social (S), technological (T), legal (L), and environmental (E) dimensions of these assemblies. The prioritization of 74 expert stakeholders, coming from the industry, academy, and government institutions, has been elucidated by having them perform pairwise comparisons among the various GPESTLE criteria through a survey. Using FAHP, prioritization or weights were already generated per G-PESTLE criterion and sub-criterion. It was found out that among the three institutions, the industry players have the lowest environmental prioritization and can be increased by developing them with cost-efficient renewable technologies. The availability of technology manufacturers and transportation accessibility has been the main consideration in ensuring the reliability of the system’s operation. Minimizing LCOE and increasing the people’s capacity to pay should also be a priority to secure the project’s financial viability. The presence of a community comprehensive land use plan has also been highly favored among developers, which can allow faster processing of permits on the use of indigenous resources and agricultural lands. With these findings, this framework aims to guide policymakers to properly address the challenges of islands lying low in prioritization due to problems on certain sustainability factors. These insights can be relevant in the drafting of a transitional framework on the renewable electrification of off-grid islands, which were usually left out or minimally given attention in the national electrification plans of governments.Poverty has been linked to the reality of the world’s developing countries, especially in far-flung rural areas where the lack of energy access plays a significant role in the misery of the poor and disadvantaged people. To achieve universal access to energy, the role of rural electrification was emphasized, and off-grid small-scale electricity generation from renewable sources was expected to be a promising solution. However, in the Philippines, where off-grid island communities are scattered along its archipelago, the deployment of such systems in rural areas is still a challenge among stakeholders due to the consideration of various conflicting factors that may put the potential economic gains and other social and environmental benefits at risk. To better understand the multifaceted nature of off-grid energy system sustainability through the perspective of its stakeholders, the Fuzzy Analytical Hierarchy Process (FAHP) was used to determine their most prioritized factors in determining the viability and sustainability of such systems following the GPESTLE framework. This provides a comprehensive and more relevant approach to performing sustainability analysis by looking into the geographical (G), political (P), economic (E), social (S), technological (T), legal (L), and environmental (E) dimensions of these assemblies. The prioritization of 74 expert stakeholders, coming from the industry, academy, and government institutions, has been elucidated by having them perform pairwise comparisons among the various GPESTLE criteria through a survey. Using FAHP, prioritization or weights were already generated per G-PESTLE criterion and sub-criterion. It was found out that among the three institutions, the industry players have the lowest environmental prioritization and can be increased by developing them with cost-efficient renewable technologies. The availability of technology manufacturers and transportation accessibility has been the main consideration in ensuring the reliability of the system’s operation. Minimizing LCOE and increasing the people’s capacity to pay should also be a priority to secure the project’s financial viability. The presence of a community comprehensive land use plan has also been highly favored among developers, which can allow faster processing of permits on the use of indigenous resources and agricultural lands. With these findings, this framework aims to guide policymakers to properly address the challenges of islands lying low in prioritization due to problems on certain sustainability factors. These insights can be relevant in the drafting of a transitional framework on the renewable electrification of off-grid islands, which were usually left out or minimally given attention in the national electrification plans of governments.

ABSTRACTAgriculture plays a vital role in meeting global food demands, yet its expansion is often linked to challenges such as land degradation and water scarcity. It is important to identify changes in cropping patterns, their interaction with soil condition and water availability. This study investigates the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Bare Soil Index (BSI), and Land Use Land Cover (LULC) by using multi‐temporal Sentinel‐2 satellite imagery during the winter cropping season (2018–2024). Results highlight pronounced temporal variability, with dense vegetation covered in 2020, while peak soil moisture was in 2022, reflecting the sensitivity of cropping systems to changing conditions. Furthermore, BSI index results show that the lowest values were observed in 2020, which indicate the highest vegetation cover in this year. However, the results of LULC reported that the cropping area decreased by −27.18%, while the built‐up area increased by 33.41%. This trend underscores the dual pressure of cropland loss and urban growth. The water bodies' covered area showed a minor increasing trend of 0.56%. The study emphasizes the complex association between the availability of water, the health of vegetation, and land degradation. To ensure food security and environmental sustainability in agricultural regions that have rapidly urbanized, it is crucial to implement integrated water and land management techniques.

Purpose – The purpose of this paper is to primarily focus on labor in maintenance areas, addressing human rights issues, labor standards and safety standards. The main issue is to investigate how these factors are considered to drive the prioritization of maintenance interventions within maintenance plans. In particular, a method for criticality analysis of production equipment is proposed considering specific labor issues like age and gender, which can be useful to steer maintenance plans toward a more social perspective. Design/methodology/approach – The authors focus on the two main social issues of SA 8000 norms, age and gender, exploring how these issues may drive the selection of maintenance policies and the relative maintenance plans. The research is conducted through fuzzy analytical hierarchy process (AHP) implemented within a failure mode effects analysis (FMEA). Findings – The research is conducted through fuzzy AHP implemented within a FMEA. The maintenance plans resulting from the FMEA driven by social issues are evaluated by a benchmark of three different scenarios. The results obtained allowed the firm to evaluate maintenance plans, considering the impact on workers’ health and safety, the environment, social issues like gender and age. Research limitations/implications – One of the main limitation of this research is that it should also encompass maintenance costs under social and safety perspective. The method developed should be extended by further study of maintenance planning decisions subject to budget constraints. Moreover, it would be worth evaluating the effect of adopting more proactive maintenance policies aimed at improving plant maintainability in view of what emerged during the test case in the presence of an aged workforce and the subsequent need to prevent and/or protect people from hidden risks. Practical implications – With reference to the results obtained from the two models of this scenario, the authors observed an increase of equipment criticality, from B class to the A class, and similarly from C class to B class. No equipment has reduced its criticality. This depends on the particular context and the relative weights of drivers indicated in its AHP matrixes. Social implications – The paper addressed the main social implication as well as other social issues represented by age and gender factors, which are normally neglected. The Action Research (AR) proved the effects resulted from considering either gender factor or gender and age factors at the same time for maintenance policy selection. All in all, an increase of criticality is evident even if “people” is a driver with less importance than “environment” and “structures.” Originality/value – The present work focussed on a new definition of a criticality ranking model to assign a maintenance policy to each component based on workers’ know-how and on their status. The approach is conceived by the application of a fuzzy logic structure and AHP to overcome uncertainties, which can rise during a decision process when there is a need to evaluate many criteria, ranging from economic to environmental and social dimensions.

IntroductionNeedlestick injuries (NSIs) are a major hazard in the workplace for healthcare workers. To prevent these injuries, it is essential to determine the important factors affecting the occurrence of them. This study aimed to identify, classify and prioritize these factors using techniques of Delphi and fuzzy analytical hierarchy process (FAHP).MethodsThis descriptive-analytical study was conducted in 2022. Firstly, the factors affecting the occurrence of needlestick injuries were identified by the literature review. Moreover, the Delphi technique was used to identify the factors. 20 experts (physicians, nurses, and occupational health experts) participated in the steps of the Delphi method. Then, these factors were grouped into six groups. In the next step, the fuzzy analytical hierarchy process (FAHP) was applied to prioritize the factors. For this purpose, the pairwise comparison questionnaire was designed and filled out by 20 experts. Finally, data were analyzed using MATLAB software (version 2018a).Results42 factors (31 factors extracted from the literature review and 11 factors obtained from the Delphi technique) were identified in this study. These factors were categorized into six groups. Based on the results, the relative weight of non-demographic personal factors, tool and technology factors, job factors, organizational factors, demographic personal factors, and environmental factors were computed by 0.200, 0.185, 0.184, 0.157, 0.142, and 0.133, respectively.ConclusionThese results determined the importance of the factors affecting the occurrence of needlestick injuries. These findings can be useful for planning preventive measures.