Pairwise Comparison Matrix Research Articles

Determining the relative importance of key drivers influencing source separation behaviour of waste producers

The European Union aims to recycle 60% of its total waste by 2030, for which waste collection infrastructure and the source-separation behaviour of waste producers are among the crucial prerequisites. Proper source separation increases the chances of waste getting recycled. For this, identifying the key drivers influencing the source separation behaviour is crucial. The present study identified 12 drivers for each non-demographic and demographic category from 43 scientific publications and calculated their relative importance based on the perceptions of three groups: (i) the expert group, (ii) the population group from Leoben (Austria), and (iii) population group from Barcelona (Spain). Using the pairwise comparison matrix of the Analytical Hierarchy Process, weights were calculated based on the relative importance of the drivers. From the non-demographic category, ‘Beliefs and values’, ‘Environmental concern’, and ‘Habits’ were rated as most important, while from the demographic category, ‘Level of education’ and ‘Location’ had the highest importance. The results were discussed in terms of biodegradable plastic waste.

Palm Oil Plantations in West and Central Kalimantan, Indonesia: Sustainability Analysis Using a Hierarchy Process Method

There are quite significant differences in the management of palm oil businesses in West Kalimantan and Central Kalimantan Provinces. In fact, West Kalimantan has a very large area of oil palm land, but its production output is smaller compared to Central Kalimantan province. Based on these facts, this research aims to determine the policy strategy for sustainable palm oil management, which includes economic, social, environmental and legal aspects to be implemented in the provinces of West Kalimantan and Central Kalimantan. This research applies the Analysis Hierarchy Process (AHP) method with a pairwise comparison matrix approach to calculate the weight of each index and create sustainable palm oil based on primary data collection through questionnaires. The research results show that in developing sustainable oil palm plantations, environmental aspects can be considered first, with a primary focus on oil palm land conservation. Conservation of oil palm land is an important part because it is a form of protection, restoration, improvement and maintenance of land functions in accordance with land capabilities and use. The results obtained from calculations carried out using the AHP model show that there are 3 policy alternatives, namely Agribusiness Public Partnership, Agribusiness Private Partnership, and Agribusiness Public - Private Partnership. This can provide benefits for economic growth through increasing agricultural productivity. Agribusiness Public-Private Partnerships have a very important role as a benchmark for sustainable palm oil plantation policies in Central and West Kalimantan.

Using IT in Area Suitability Modeling To Plan Urban Areas: Case of Kabul City, Afghanistan

The goal of this work was to determine the optimal locations for urban growth in Kabul city using an integrated GIS-AHP model and Land Suitability Analysis (LSA). The study’s findings demonstrated that GIS-AHP is a useful approach for urban planning and ecological management. Maps were normalized using the pairwise comparison matrix technique using the generated criteria. Each model’s weights were created by comparing them according to their relative importance. Weight Age Average (OWA) and Weighted Linear Combination (WLC) were used to combine criteria weights and maps. To assess if a piece of land is suitable for urban development to determine which area was suitable for urban development, six thematic layers—slope, road, land use, river, settlement, and elevation—were used. AHP calculated their weighted scores based on the pairwise comparison. The linear combination approach was used to multiply each factor’s weight and score, and the outcome was then multiplied to make the urban development appropriate. 45.3 square kilometers of land were deemed highly suitable, 191.77 square kilometers were deemed fairly acceptable, 72.14 square kilometers were deemed marginally suitable, and 0.79 square kilometers were deemed unsuitable.

Groundwater potential assessment in the Eastern Cape, South Africa, using analytical hierarchical process (AHP) technique

Groundwater is crucial for the growth of any country. It is a vital resource for drinking water, agriculture, industry, and economic development. However, delineating the groundwater potential zones requires a systematic approach. This study assessed the groundwater potential zones (GWPZ) in the Ntabankulu municipality using remote sensing, geographic information systems, and analytical hierarchical process (AHP) techniques. Six groundwater controlling parameters were integrated to assess groundwater potential zones, including lithology, slope, lineaments density, land use/land cover, drainage density, and rainfall. The AHP pairwise comparison matrix was utilized to determine the normalized weight of the parameters. The parameters and their classes were assigned ranks, taking into account their influence on groundwater accumulation. The resultant GWPZ map was generated by integrating the parameters and their assigned weights in ArcGIS 10.8 software. The final map from the AHP technique showed five GWPZ, including very poor (13.06%), poor (25.36%), moderate (26.93%), good (22.72%), and very good (11.93%). Validation was done by using the existing 242 boreholes in the study area. Furthermore, the receiver operating characteristics (ROC) curve was plotted, and the area under the curve (AUC) analysis indicated a satisfactory accuracy prediction (AUC = 61%). The results of this study will assist in developing a proper plan for sustainable utilization of groundwater resources within the Ntabankulu municipality.

An analytical hierarchical process approach to assessing local food preferences among foreign tourists

PurposeThis study evaluates the relative preference for local foods among foreign tourists. It also assessed how the sociodemographic profiles of tourists influence their local food preferences.Design/methodology/approachThis research utilized a mixed-methods approach. The initial qualitative analysis phase involved semi-structured, in-depth interviews with stakeholders in Fiji’s local food sector, providing feedback on tourists’ preferred dishes. In the second phase, 204 foreign tourists were surveyed through the location intercept approach at various local restaurants, street food joints and eateries across Fiji. The preferences of these foreign tourists for the local food were subsequently analyzed utilizing the analytical hierarchical process (AHP) model and Chi-square statistics.FindingsThis research identified 25 local food dishes most preferred by foreign tourists. A pairwise comparison matrix revealed that “Kokoda” was most preferred, while “Tuna Ika Vakalolo” was the least preferred, and the normalized matrix presented the estimated overall priorities of the local foods based on taste and flavor. Among all the factors analyzed for their potential influence on the local food preferences of foreign tourists, “education attainment” and “marital status” were found to have no significant influence.Originality/valueThis study highlights the varied local dishes preferred by tourists, assessed through the AHP model, and provides the sociodemographic factors influencing these preferences. By identifying and presenting local Fijian dishes across regions and examining sociodemographics’ impact on food preference, this research provides invaluable implications for significantly benefiting the local food vending sector.

Identifying and Prioritizing the Educational Needs Professors of Medical Sciences in the Field of E-Learning with the Analytic Hierarchy Process Approach

Background: Professors in universities and educational institutions hold a crucial role in crafting educational approaches utilizing cutting-edge technologies. They need to possess significant expertise in e-learning and tackle the obstacles associated with delivering education and utilizing Information and communication technologies within higher education. To effectively navigate these challenges and adaptations, professors need to equip themselves with new educational techniques through training and readiness to adeptly incorporate emerging technologies into their teaching practices, thus enhancing the educational journey for students. By identifying, understanding, and ranking professors' requirements and preferences, effective and diverse educational initiatives can be tailored to meet their needs. Objectives: This research aimed to recognize the educational needs of medical science professors in the field of e-learning from the experts' point of view and prioritize these needs utilizing the analytic hierarchy process (AHP). Methods: This practical study was conducted in 2022 using a process-oriented approach and AHP. The main stages included the creation of a hierarchical structure, comparative judgment, and determining priorities. In the first step, 13 criteria were identified, which were derived from scientific articles and previous research. In the second step, the pairwise comparison matrix was used for comparative judgment, and the weight of each criterion was calculated. The third step involved determining priorities based on the weight of each criterion and the inconsistency ratio. The participants of this study included professors of basic and clinical sciences from different faculties. Results: The results of this study demonstrated that from the point of view of experts and participants, among the 13 criteria, the skills of virtual teaching (with weights of 0.146 and 0.148), electronic content production (with weights of 0.093 and 0.092), and holding online training courses (with the weights of 0.092 and 0.100) formed the three main needs of medical science professors in the field of e-learning and had the highest degree of importance and necessity compared to other criteria. Conclusions: Identifying the educational needs of medical science professors for organizing and designing necessary programs to enhance knowledge, skills, and empowerment will lead to improving the quality of e-learning, and eventually, reducing professors’ concerns in this area.

Site Suitability Analysis for Farmlands in Agro-Climatic Zone of Andhra Pradesh using Geo-Spatial Techniques

Abstract: The Anantapur region has moderately healthy vegetation, which produces impressive biodiversity, climate variations, and a variety of wildlife and flora. As a result, the southern areashave a lot of room for agricultural growth to support rural economies. The Northern part's potential for agriculture in this region has been limited by several physical obstacles, including ahigh slope and elevation, built-up area, a lack of irrigation infrastructure, dry soil, poor rainfall, and socio-economic problems. Planning the expansion of agricultural output can benefit from researching a location's suitability for a particular purpose. Using a GIS-based multi-criteria decision-making technique based on DEM and Landsat 8 satellite data, AHP will be utilised to evaluate site suitability for agricultural production in unused areas. A pairwise comparison matrix will be used to set the weights. It will help to determine whether hilly terrain is suitable for farming using the study's techniques, approaches, and findings.

Identification of Spatial Patterns of Soil Erosion Based on the Combination of RUSLE and MCDA in the Ahferom District, Northern Ethiopia

Soil erosion is a widespread concern that is indeed considered to be a significant environmental issue, and it has particularly severe consequences in less developed countries like Ethiopia. An effective watershed management procedure for establishing priority is supported by the identification of erosion-susceptible areas. Therefore, the main objective of the study was to assess soil erosion dynamics and its spatial pattern using a novel methodological framework combining the RUSLE and MCDA. The study used data on land use and cover, topography, soil, and climatic data. The analytical hierarchy process (AHP) were used to identify soil erosion-susceptible areas and the factors were weighted using a pairwise comparison matrix, and weights were combined using weighted overlay in GIS. Our results indicated that the mean annual soil loss rate was 27.10 t ha−1 yr−1, while the total soil loss from the entire study area was 3.11 Mt. The highest soil loss was observed in bare land (30.54 t ha−1 yr−1) and farmland (23.65 t ha−1 yr−1), which were considered as the most susceptible land types to erosion. Likewise, 10.3% of the study area is very highly susceptible; 20.2% is highly susceptible, 24.2% of the area is moderately susceptible, 27.1% is low, and 18.2% has very low susceptibility. The district’s most significant erosion-susceptible areas are characterized by steep slopes that are composed of farmland and bare land. This suggests the majority of the area is susceptible to erosion, requiring interventions to reverse the alarming degradation level. The presented framework has a board application to estimate regional soil erosion and to identify spatial patterns of soil erosion.

Integrated Geospatial and Analytical Hierarchy Process Approach for Assessing Sustainable Management of Groundwater Recharge Potential in Barind Tract

Groundwater depletion in Bangladesh’s Barind tract poses significant challenges for sustainable water management. This study aims to delineate groundwater recharge potential zones in this region using an integrated geospatial and Analytical Hierarchy Process (AHP) approach. The methodology combines remote-sensing data with GIS analysis, considering seven factors influencing groundwater recharge: rainfall, soil type, geology, slope, lineament density, land use/land cover, and drainage density. The AHP method was employed to assess the variability of groundwater recharge potential within the 7586 km2 study area. Thematic maps of relevant factors were processed using ArcGIS software. Results indicate that 9.23% (700.22 km2), 47.68% (3617.13 km2), 37.12% (2816.13 km2), and 5.97% (452.70 km2) of the study area exhibit poor, moderate, good, and very good recharge potential, respectively. The annual recharge volume is estimated at 2554 × 106 m3/year, constituting 22.7% of the total precipitation volume (11,227 × 106 m3/year). Analysis of individual factors revealed that geology has the highest influence (33.57%) on recharge potential, followed by land use/land cover (17.74%), soil type (17.25%), and rainfall (12.25%). The consistency ratio of the pairwise comparison matrix was 0.0904, indicating acceptable reliability of the AHP results. The spatial distribution of recharge zones shows a concentration of poor recharge potential in areas with low rainfall (1200–1400 mm/year) and high slope (6–40%). Conversely, very good recharge potential is associated with high rainfall zones (1800–2200 mm/year) and areas with favorable geology (sedimentary deposits). This study provides a quantitative framework for assessing groundwater recharge potential in the Barind tract. The resulting maps and data offer valuable insights for policymakers and water resource managers to develop targeted groundwater management strategies. These findings have significant implications for sustainable water resource management in the region, particularly in addressing challenges related to agricultural water demand and climate change adaptation.

Site Suitability Analysis for Urban Development: A Case of Ranikhet, Uttrakhand

Identifying potential sites for urban development in hilly regions is a crucial aspect of planning. Conducting site suitability analysis is essential for determining appropriate locations for various developmental projects, particularly in the challenging terrain of hills. Unregulated and disorganized urban expansion, driven by population pressure, is a widespread issue in many cities within developing countries, leading to urban sprawl that encroaches on natural environments. As a result, selecting suitable areas for urban development while maintaining ecological balance has become a critical component of effective urban planning. This work demonstrates the application of Geographic Information System (GIS) and the Multi-Criteria Analysis (MCA) technique for identifying appropriate sites for urban development in Ranikhet, Uttarakhand. The aim is to identify optimal locations for future urban growth that minimize impacts on natural features. The work also calculates the potential transfer of land suitability from various land use and land cover categories, a unique aspect of this research. Eight criteria distance from roads, land use/cover, distance from water bodies, slope, elevation, soil, geological formation, and population density were used for land evaluation. The thematic maps generated for these criteria were standardized using the Analytical Hierarchy Process (AHP), which involved creating a pairwise comparison matrix. Each criterion was assigned a weight based on its relative importance, leading to the creation of a final site suitability map with five categories: very high suitable, high suitable, moderately suitable, less suitable, and restricted or not suitable. The study highlights the potential zones within the study area and offers valuable insights for sustainable urban development planning. The results are expected to assist planners, stakeholders, and policymakers in identifying the most suitable locations for future intensive development projects.

A Study for Calculating The Contribution of Group Members Using Pair-wise Comparison Matrix

A Study for Calculating The Contribution of Group Members Using Pair-wise Comparison Matrix

Combining Fuzzy MCDM and Machine Learning for Predictive Analytics in Diabetes Management

This study utilizes the Fuzzy Analytic Hierarchy Process (FAHP) to evaluate the factors influencing the risk of diabetes-related complications. Data was collected from diabetes specialists in Coimbatore, each with over 15 years of experience, to construct a pairwise comparison matrix based on expert opinions. The analysis identified six key criteria: Age (C1), Cardiopulmonary function (C2), Cardiovascular disease (C3), Family history of sudden death (C4), Smoking (C5), and Blood glucose (C6). The results reveal that Cardiopulmonary function (C2) is the most critical factor, with a weight of 0.1193, followed by Age (C1) and Family history of sudden death (C4). While long-term health indicators are more influential than immediate lifestyle factors, the contributions of Smoking (C5) and Alcoholism (C6) are still relevant. These findings emphasize the need for a comprehensive approach to diabetes management that balances inherent and lifestyle-related risks.

Sustainable Water Resource Planning for Alanda Micro Watershed Using Geospatial Techniques

Groundwater is a vital natural resource, especially in areas lacking surface water bodies. About one-third of the global population relies on it for drinking, irrigation and industrial purposes. However, excessive and unregulated exploitation has led to a rapid decline in water tables, emphasizing the need for sustainable groundwater management. The Alanda micro watershed in Barshitakli Taluka, Akola District, Maharashtra, spans 11.39 km², with a sub-humid climate and uneven monsoon rainfall averaging 780 mm. The region faces high water stress in summer, with dried bore wells and farmers relying on rain and groundwater for irrigation. The water resource development plan for Alanda micro watersheds integrates GIS, remote sensing and AHP to identify groundwater potential zones. The Alanda micro watershed soil and water conservation plans were developed using GIS, remote sensing and the AHP method. Thematic maps were overlaid in ArcGIS, applying weighted factors from a pairwise comparison matrix to identify groundwater potential zones. These zones, categorised as high, moderate and low potential, highlight that the largest area has moderate potential, suggesting good opportunities for conservation measures. The survey of the study area identified existing soil and water conservation structures, including 3 farm ponds, 1 check dam and a contour bund. Additional recommendations include 5 farm ponds, 4 check dams, contour trenches and bunding measures, along with agronomic practices for effective surface and groundwater management.

Why We Need Desirable Properties in Pairwise Comparison Methods?

ABSTRACTPairwise comparison matrices (PCMs) are inevitable tools in some important multiple‐criteria decision‐making methods, for example AHP/ANP, TOPSIS, PROMETHEE and others. In this paper, we investigate some important properties of PCMs which influence the generated priority vectors for the final ranking of the given alternatives. The main subproblem of the Analytic Hierarchy Process (AHP) is to calculate the priority vectors, that is, the weights assigned to the elements of the hierarchy (criteria, sub‐criteria, and/or alternatives or variants), by using the information provided in the form of a pairwise comparison matrix. Given a set of elements, and a corresponding pairwise comparison matrix, whose entries evaluate the relative importance of the elements with respect to a given criterion, the final ranking of the given alternatives is evaluated. We investigate some important and natural properties of PCMs called the desirable properties, particularly, the non‐dominance, consistency, intensity and coherence, which influence the generated priority vectors. Usually, the priority vector is calculated based on some well‐known method, for example, the Eigenvector Method, the Arithmetic Mean Method, the Geometric Mean Method, the Least Square Method, and so forth. The novelty of our approach is that the priority vector is calculated as the solution of an optimization problem where an error objective function is minimised with respect to constraints given by the desirable properties. The properties of the optimal solution are discussed and some illustrating examples are presented. The corresponding software tool has been developed and demonstrated in some examples.

Special measures to promote supplementary professional education services: formation and evaluation of effectiveness

Introduction. The problem of promotion of supplementary professional education services is one of the important issues for attracting consumers of professional retraining and advanced development programmes, contributing to marketing attainments and a company’s efficiency in general. The solution largely depends on the developmental level of the market of supplementary professional education services at a regional level, the specifics and quality of training courses, as well as the relevance of promotion tools used by the organisation. Purpose of the research: development and approbation of the methodology for forming and evaluating the effectiveness of a special tool for the promotion of supplementary professional education services. Materials and methods. To determine the format of a special survey, an online questioning of 1,035 potential consumers was carried out; ten marketing and advertising experts were interviewed and selected by the Delphi method modified by J. Fowles; a questioning of 319 participants and 20 organisers of the special survey was undertaken. The expert judgement was arranged using the Hierarchy Analysis Method by T. Saati, including the processing of the data obtained in the course of the experts interviewing and the calculation of eigenvectors of the pairwise comparison matrix. Results. A methodology for forming and evaluating the effectiveness of a special survey was developed. As a result of the approbation, eleven qualitative indicators were evaluated, scoring 7.92 out of nine, totalling 88%. The quantitative indicators, particularly, the engagement index was 56.8%; the key performance indicator was 8.5% and the return on investment was 336.8%. As a result of the special survey, 27 participants acquired the Internet marketing course. Conclusion. The proposed methodology can extend the opportunities of organisations providing supplementary special education services in terms of selecting, planning and realisation of efficient promotion tools. The methodology can be applied to the formation and evaluation of different-format special surveys with regard to their specifics.

Landslide susceptibility zonation mapping using geospatial technologies and multi criteria evaluation techniques in the upper Didessa sub-basin, Southwest Ethiopia

ABSTRACT Landslides have a profound impact on landscape geology, resulting in extensive devastation and loss of human lives. Mapping landslide susceptibility is crucial for effective land use planning in mountainous country like Ethiopia. This study was conducted in the upper Didessa sub-basin, southwestern parts of Ethiopia using Geographic Information System (GIS) and multi criteria evaluation (MCE) technique. This study employed a blend of primary data, encompassing field surveys and interviews with experts, as well as secondary data derived from diverse source, such as remote sensing data, digital soil maps, and geological maps. A total of eleven critical factors were employed to assess the triggers of landslides. These factors include slope, aspect, drainage density, topographic wetness index (TWI), stream power index (SPI), topographic ruggedness index (TRI), hypsometric integral, lithology, land use land cover (LULC), soil texture, and distance from roads. The analytical hierarchy process (AHP) method was used to determine the significance of each indicator through pairwise comparison matrix. The study area was categorized into different zones based on the susceptibility to landslides, namely very high, high, moderate, low, and very low. Results revealed that cultivated land had the highest likelihood of experiencing landslides, with a total of nine incidents out of 25, followed by built-up areas with seven landslides. Conversely, dense forests, sparse forests, and grazing land experienced a lower likelihood of landslides. Out of the 11 factors contributing to landslides, 24% of the surveyed region was deemed to have a moderate susceptibility, with 12% and 6% falling into the categories of high and very high susceptibility to landslides, respectively. The findings of this research provide important information for policymakers to develop efficient measures for preventing and reducing the risks of landslides.

Modelling the present and future scenario of urban green space vulnerability using PSR based AHP and MLP models in a Metropolitan city Kolkata Municipal Corporation

ABSTRACT Urban green spaces, despite their recognized importance for sustainable urban development, face significant challenges to their resilience and viability due to rapid urbanization and various associated pressures. The scientific problem addressed in this paper is the vulnerability of urban green spaces to various stressors, including proximity to settlement, land use and land cover changes, and proximity to roads, among others. Despite their importance, there is a lack of comprehensive assessments and frameworks to systematically evaluate and address this vulnerability. Therefore, this study aims to fill this gap by employing a multi-criteria decision-making framework, namely the Analytic Hierarchy Process (AHP), and the Pressure-State-Response (PSR) framework. By analyzing 10 indicators related to urban green space vulnerability through a pairwise comparison matrix, the study identifies critical factors influencing vulnerability and categorizes urban green spaces into different susceptibility levels. Additionally, the research extends its analysis to future scenario development for the years 2030 and 2040, using a Multi-Layer Perceptron (MLP) based Markov Chain model, incorporating various parameters such as distances from built-up areas, roads, rails, streams, slopes, and elevation. Through these methodologies, the study aims to provide valuable insights to urban planners, policymakers, and environmental practitioners, enabling them to make informed decisions to enhance the resilience and sustainability of urban green spaces and urban areas as a whole.

Optimization model for fair judging of large-scale innovation contests based on experts’ neutral weights

The group decision-making method and standard score method are commonly used for evaluating large-scale innovative contest entries. However, the standard score method assumes that the quality distribution of entries evaluated by each expert remains consistent, which is difficult to achieve in practice due to different experts reviewing different entries. To enhance fairness in judging results for such contests, we propose an improved standard score method based on weighting. First, we establish a mathematical model for cross-assignment of entries and design an algorithm to solve it while discussing one property on its optimal solution. This model enables any two experts to be assigned as many identical entries as possible, facilitating reliable pairwise comparisons matrix while avoiding assigning the best or worst entries to multiple experts in one judgment. Second, inspired by cross entropy concepts, we introduce a definition of “cross entropy-like” and establish a mathematical model using this concept along with minimum sum of squared errors method to determine neutral weights for experts. Finally, experiments demonstrate that our proposed improved standard score method is more scientific and reasonable than traditional standard score method while enhancing objectivity and fairness of evaluation results.

Algebraic analysis of pairwise comparisons with non-reciprocal property

The law of comparative judgement usually implies the reciprocal property of pairwise comparisons. But time error and position preference could yield some judgements that contradict this identity assumption. This paper proposes an algebraic approach to dealing with the challenge of non-reciprocal property in pairwise comparisons. The concept of non-reciprocal pairwise comparison matrix (NrPCM) is used to characterize the situation of non-reciprocal property. Algebraic analysis of NrPCMs is carried out, where a linear space is constructed by proposing a set of basis. Then the linear space is decomposed into the direct sum of some subspaces. The properties of the space are analyzed such as inner product, decomposition and coordinate. Finally, we apply the algebraic method to investigate the Condorcet paradox under the impact of indifferent voters. A novel transformation formula of non-reciprocal pairwise comparisons is proposed, where the non-reciprocal property holds. It is revealed that the occurrence of voting paradox can be understood clearly according to the transitivity property of NrPCMs.

Выбор альтернативы в принятии управленческих решений методом оценочных таблиц

The proposed methodology is based on the method of evaluation tables using expert assessments. The method makes it quite easy to convert criteria of various dimensions into dimensionless ones for subsequent comparison and integral evaluation, for example, using an additive convolution criterion. Management decision options are alternatives that are compared according to specific evaluation parameters (criteria). An example of constructing a normalized matrix of pairwise comparison of criteria is shown. The research material allows for a numerical assessment of various alternatives with sufficient reliability.