Hybrid Fuzzy Multi-Criteria Analysis for Selecting Discrete Preferable Groundwater Recharge Sites

This study proposes a hybrid fuzzy multi-criteria methodology for the selection of the most preferable site for applying managed aquifer recharge (MAR) systems by utilizing floodwaters. The use of MAR can increase water resources for later water utilization in case of drought. In this multi-criteria problem, seven recharge sites are under consideration, based on nine criteria, aiming to make a final list of their relative ranking. A fuzzy analytic hierarchy process (FAHP) based on the logarithmic fuzzy preference programming (LFFP) method is used to determine the weights of criteria. LFFP is an optimization-based method that produces a priority vector from a fuzzy pairwise comparison matrix. Furthermore, fuzzy inference systems (FIS) based on the Mamdani approach are used to estimate the rating of each alternative with respect to the criterion examined, and then the final evaluation of the alternatives is obtained. A FIS is a fuzzy if–then rule-based system where the experts’ qualitative knowledge is translated into numerical reasoning for each individual criterion. The proposed methodology is applied in the aquifer system of the agricultural plain located to the southeast of the city of Xanthi in the Prefecture of Xanthi, NE Greece.

Creating a common priority vector in intuitionistic fuzzy AHP: a comparison of entropy-based and distance-based models

In the case of conflicting individuals or evaluator groups, finding the common preferences of the participants is a challenging task. This statement also refers to Intuitionistic Fuzzy Analytic Hierarchy Process models, in which uncertainty of the scoring of individuals is well-handled, however, the aggregation of the modified scores is generally conducted by the conventional way of multi-criteria decision-making. This paper offers two options for this aggregation: the relatively well-known entropy-based, and the lately emerged distance-based aggregations. The manuscript can be considered as a pioneer work by analyzing the nature of distance-based aggregation under a fuzzy environment. In the proposed model, three clearly separable conflicting groups are examined, and the objective is to find their common priority vector, which can be satisfactory to all participant clusters. We have tested the model results on a real-world case study, on a public transport development decision-making problem by conducting a large-scale survey involving three different stakeholder groups of transportation. The comparison of the different approaches has shown that both entropy-based and distance-based techniques can provide a feasible solution based on their high similarity in the final ordinal and cardinal outcomes.

COMPARATIVE ASSESSMENT OF COMPETENCE LEVEL OF TRANSPORT SYSTEM EXPERTS

The paper deals with the comparative assessment of competence level of transport system experts. The high level of competence of the experts is the premise to ensure the quality of the expertise of the systems insufficiently formalized from a mathematical point of view and characterized with a high degree of uncertainty. Six factors for assessing the competence of transport system experts were summarized. The values of the priority vector of the competence factors were established with the application of the Saaty algorithm and scale in nine points by the method of comparisons in pairs. The value of the concordance ratio of the experts' opinion for the prioritization matrix was calculated. The comparative competence coefficient of the experts in transport systems was calculated and the hierarchy of experts was established according to the value of the nominal coefficient.

Drivers of sustainable healthcare supply chain performance: multi-criteria decision-making approach under grey environment

PurposeThis paper aims to explore the drivers of sustainable healthcare supply chain (SHCSC) performance measurement through extensive literature review and experts' opinions. The drivers are then scrutinized and their priority vector is calculated to provide quality and cost-effective healthcare supply chain (HCSC) services.Design/methodology/approachThe drivers of the SHCSC performance measurement are validated using the grey-Delphi technique. After validating the drivers, they are prioritized using the grey-analytic hierarchy process (G-AHP), a multi-criteria decision-making tool.FindingsThe findings of the study highlight the prioritized drivers based on the preferences given by the experts. The findings of the study highlight the most prioritized drivers of healthcare (HC) by-product management system, coordinating and facilitating green suppliers in the HCSC and green packaging of pharmaceutical as well as other essential items.Practical implicationsThe HCSC managers should coordinate with all the stakeholders across the supply chain and involve them in the decision-making process to make products and services greener and become complicit in complying with the sustainable policy guidelines. The study highlights the strategic policy and managerial implications for implementing sustainability in the HCSC.Originality/valueThe validation and prioritization of the drivers of SHCSC in developing nations' contexts is the key contribution of the study. Grey-AHP enables a practical approach towards enhancing the sustainability of the HCSC and opening the doors for generalizing the study for future research works.

On the Statistical Discrepancy and Affinity of Priority Vector Heuristics in Pairwise-Comparison-Based Methods

There are numerous priority deriving methods (PDMs) for pairwise-comparison-based (PCB) problems. They are often examined within the Analytic Hierarchy Process (AHP), which applies the Principal Right Eigenvalue Method (PREV) in the process of prioritizing alternatives. It is known that when decision makers (DMs) are consistent with their preferences when making evaluations concerning various decision options, all available PDMs result in the same priority vector (PV). However, when the evaluations of DMs are inconsistent and their preferences concerning alternative solutions to a particular problem are not transitive (cardinally), the outcomes are often different. This research study examines selected PDMs in relation to their ranking credibility, which is assessed by relevant statistical measures. These measures determine the approximation quality of the selected PDMs. The examined estimates refer to the inconsistency of various Pairwise Comparison Matrices (PCMs)—i.e., W = (wij), wij > 0, where i, j = 1,…, n—which are obtained during the pairwise comparison simulation process examined with the application of Wolfram’s Mathematica Software. Thus, theoretical considerations are accompanied by Monte Carlo simulations that apply various scenarios for the PCM perturbation process and are designed for hypothetical three-level AHP frameworks. The examination results show the similarities and discrepancies among the examined PDMs from the perspective of their quality, which enriches the state of knowledge about the examined PCB prioritization methodology and provides further prospective opportunities.

Marketing Communication Program Design of Online Travel Agent Kliktrip Using Benchmarking and Analytical Hierarchy Process Methods

Kliktrip is an Online Travel Agent (OTA) that has trip & activities facilities and was established in 2018 in Bandung. Kliktrip sales are still experiencing a decline due to low public awareness of Kliktrip which is seen through the number of downloads on mobile apps and Instagram followers. Kliktrip sales are still experiencing a decline and public awareness of Kliktrip is still low because Kliktrip has not implemented 7 out of 8 marketing communication mix optimally. Therefore, research was conducted to design an effective marketing communication program for Kliktrip by using benchmarking and Analytical Hierarchy Process (AHP) methods. Based on the results of AHP data processing, it can be seen that the selected benchmark partner is Explorer.id with a total priority vector value of 0.44 and benchmark results with Explorer.id concluded that Kliktrip needs to increases the value of SEO, page views, and unique visitors on the website, creates a Tiktok’s account, webisode, and video podcasting, collaborates with cross-promotion, makes contests (giveaways), increase the number of downloads and reviewers on mobile apps, implementing mobile billboards and cause-related marketing, increasing customer service operational time, participating in exhibitions, and collaborating with influencers.

Analisa Penentuan Saham Terbaik Menggunakan Metode Analytic Hierarchy Process (AHP)

The number of stock investors has increased from the past to the present. Likewise, the number of companies listed on the Indonesia Stock Exchange (IDX). What makes investors confused about choosing the best stock from the hundreds of stocks that are regulated on the IDX. The method used for the best stock is the Analytic Hierarchy Process (AHP) method. Investors will enter criteria that take into account the specified criteria and criteria. The criteria used to determine stocks are C1 = PER, C2 = PBV, C3 = DER, C4 = ROE and C5 = ROA. The results of research conducted in the second rank show that alternative A1 = CPIN is in the first rank with a Priority Vector of 0.6536, alternative A2 = JFPA is in the second rank with a Priority Vector of 0.2013 and alternative A3 = UTAMA is in the second rank. second rank. second rank. second rank. ranked third with a Priority Vector of 0.1452.

Expected consistency-based model and multiplicative DEA cross-efficiency for group decision-making with incomplete distribution linguistic preference relations

Faced with complex decision problems, Distribution linguistic preference relation (DLPR) is an effective way for decision-makers (DMs) to express preference information. However, due to the complexity of the decision-making environment, DMs may not be able to provide complete linguistic distribution for all linguistic terms in DLPRs, which results in incomplete DLPRs. Therefore, in order to solve group decision-making (GDM) with incomplete DLPRs, this paper proposes expected consistency-based model and multiplicative DEA cross-efficiency. For a given incomplete DLPRs, we first propose an optimization model to obtain complete DLPR. This optimization model can evaluate the missing linguistic distribution and ensure that the obtained DLPR has a high consistency level. And then, we develop a transformation function that can transform DLPRs into multiplicative preference relations (MPRs). Furthermore, we design an improved multiplicative DEA model to obtain the priority vector of MPR for ranking all alternatives. Finally, a numerical example is provided to show the rationality and applicability of the proposed GDM method.

Increase in the employment rate of women with children as a priority vector of social development in the Republic of Bashkortostan

The application of content analysis allowed revealing that the improvement of the status of women in labor relations should become one of the key vectors of social transformation in the Republic of Bashkortostan. First and foremost it pertains to increase in employment rate of women with children of preschool age. The employment of this category of women, as part of human resources, is the crucial problem of the social sphere and social policy. The statistical analysis demonstrated that from the perspective of labor potential, namely this group is most promising due to their size, level of education, active occupational attitudes and values. However, the research indicates that up to 30 % of women in this category face difficulties with employment. In this case, single-parent families, when the main role for financial situation in the family is assigned to a woman, are particularly exposed to risk. The goal of this research is to determine the key barriers in employment of women with children in the regional job market, as well as offer mechanisms for their mitigation. The object of this research is the human resources of the region, while the subject is the employment of women. The theoretical and methodological framework is comprised of the theoretical provisions and methods of the following branches of sociology: sociology of labor, sociology of family, and economic sociology. The empirical base relies on the data from Rosstat and Territorial Federal Service of State Statistics for the Republic of Bashkortostan. In the course of this research, the author employs secondary data analysis and gender approach as a stratification approach. The comparative analysis of statistical data reveals the key trends in the sphere of women’s employment on the regional job market, as well as determines the major barriers in employment of women with children. The article offers mechanisms for alleviating a number of institutional and infrastructural barriers existing in the republic with regards to employment of women.