Multi-criteria Decision Analysis Techniques Research Articles

A GIS-based multiple ecotourism sustainability assessment of West Azerbaijan province, Iran

Ecotourism is a major tourism dimension that has received significant attention in recent years. It is widely known that the tourism industry, and in particular ecotourism, makes a significant contribution to sustainable development. In this context, the West Azerbaijan province is one of most important tourist destinations in Iran for attracting tourists interested in nature. The main purpose of this study was to analyze and map the potential for sustainable ecotourism development. The research methodology was developed based on GIS multi-criteria decision analysis (GIS-MCDA) techniques, using 28 spatial indicators. For this purpose, areas with the potential for attracting tourists were identified and the effective factors for increasing and decreasing tourism development activities were evaluated by GIS analysis. The method used as a multi-criteria spatial decision-making technique is based on the network analysis process and its combination with fuzzy logic is very effective for increasing the accuracy of the model and obtaining more realistic results. According to the results of this study, West Azerbaijan, due to its potential, including some areas unknown to tourists and even tourism planners, could be introduced as a nature tourism hub in the northwest of the country. The detailed tourism sustainability map obtained, at the scale of 1/25,000, could be used as a basis for regional planning and sustainable ecotourism development. In this context, the results could also be critical for tourism companies, agencies and local stakeholders and organizations for various applications, such as investment and development of tourism hospitality facilities and infrastructure in high potential areas. The research can also be considered as progressive in tourism research and supports future research on the selection of beneficial criteria and the application of efficient methods for tourism sustainability assessment and mapping.

Integrating GIS-Based MCDA Techniques and the SCS-CN Method for Identifying Potential Zones for Rainwater Harvesting in a Semi-Arid Area

An increasing scarcity of water, as well as rapid global climate change, requires more effective water conservation alternatives. One promising alternative is rainwater harvesting (RWH). Nevertheless, the evaluation of RWH potential together with the selection of appropriate sites for RWH structures is significantly difficult for the water managers. This study deals with this difficulty by identifying RWH potential areas and sites for RWH structures utilizing geospatial and multi-criteria decision analysis (MCDA) techniques. The conventional data and remote sensing data were employed to set up needed thematic layers using ArcGIS software. The soil conservation service curve number (SCS-CN) method was used to determine surface runoff, centered on which yearly runoff potential map was produced in the ArcGIS environment. Thematic layers such as drainage density, slope, land use/cover, and runoff were allotted appropriate weights to produced RWH potential areas and zones appropriate for RWH structures maps of the study location. Results analysis revealed that the outcomes of the spatial allocation of yearly surface runoff depth ranging from 83 to 295 mm. Moreover, RWH potential areas results showed that the study areas can be categorized into three RWH potential areas: (a) low suitability, (b) medium suitability, and (c) high suitability. Nearly 40% of the watershed zone falls within medium and high suitability RWH potential areas. It is deduced that the integrated MCDA and geospatial techniques provide a valuable and formidable resource for the strategizing of RWH within the study zones.

Assessment of groundwater potential zone using GIS-based multi-influencing factor (MIF), multi-criteria decision analysis (MCDA) and electrical resistivity survey techniques in Raipur city, Chhattisgarh, India

Abstract The present study involved the combined applications of advanced techniques and tools like remote sensing, geographic informatic system (GIS), electrical resistivity, MCDA, to assess the potential zones of groundwater occurrence. Several prepared thematic layers, including geology, geomorphology, rainfall, lineament, land use land cover (LULC), drainage density, soil type, slope, and soil texture, were assigned with a weight, depending on their influence on groundwater potential. Normalization concerned with relative contribution is applied in this study using the AHP method. Vertical electrical sounding has been conducted on different points to locate water-bearing formations/fracture zones. The resulting groundwater potential areas that are delineated applying these methods have been categorized into five zones, low, medium, medium-high, high, and very high potential. The groundwater potential zones demarcated show that high potential zones are present in the west and north-eastern portion, while low to medium groundwater potential is located in the central and eastern portion. The obtained result was validated using well yield data, and ROC method from which result accuracy obtained is 80% and the area under the ROC curve is found to be 0.857 at a significance value of less than 0.001, which justifies the efficacy of the proposed approach in the demarcation of groundwater potential zone.

Comparison among multi-criteria decision analysis techniques: a novel method

This paper proposes a novel method of comparison among the various multi-criteria decision analysis (MCDA) techniques. The motivation behind proposing novel method of comparison comes from the fact that in spite of the presence of significant number of MCDA techniques, decision makers face difficulty in selecting appropriate MCDA technique for a particular problem under study. The reason behind this is that the applications of different MCDA techniques may result in different sets of rankings for the same problem. Such dilemma makes it difficult for the decision makers to identify the most appropriate ranking and thus the most appropriate MCDA technique for their problem. In order to solve this problem, this paper proposes to emphasize on the performance of the obtained rankings so as to identify the most appropriate ranking. Thus, the proposed performance-based comparison method is based on the performance of the obtained rankings. A total of fourteen different MCDA techniques have been compared for the purpose. These methods have been applied to a case study so as to get the rankings of the alternatives. The proposed method is applied on these obtained rankings so as to identify the most effective ranking among them, for the problem at hand. The comparison with the help of the case study establishes the effectiveness of the proposed method of comparison among MCDA techniques.

Evaluation of parameter sensitivity for groundwater potential mapping in the mountainous region of Nepal Himalaya

Groundwater potential (GWP) mapping of an area is the initial stage of assessing groundwater for further investigation leading towards exploitation of the resources to meet the water demand for various sectors. Groundwater availability is explicitly important especially in the mountainous area in the Himalayan region. In practice, different combinations of parameters are used to prepare GWP map, however, the sensitivity of parameters are poorly assessed. This paper aims to evaluate the sensitivity of parameter for delineating groundwater potential using GIS and remote sensing. Multi-Criteria Decision Analysis (MCDA) technique is used to prepare groundwater potential map of Khadadevi-Manthali area, Ramechhap district, of Bagmati Province, Nepal. Nine influencing parameters are considered in the present analysis, which were integrated through assigning normalized weight to the thematic layers and their classes using Analytical Hierarchical Process (AHP). Further, groundwater potential maps have been prepared for 7 different cases using different combination of parameters and for each case, the results were successively validated with 21 springs and 3 tube wells spatially distributed within the study area. The results show that the GWP maps prepared using the lineament and hydro-geomorphic maps yield better result. The ROC/AUC Curve (Receiver operating characteristic curve/Area under curve) for GWP map prepared using 9 parameters shows higher prediction accuracy (72.4%) as compared to other cases\\. Thus, we conclude that lineament and hydro-geomorphology of an area are most influencing factors in delineating GWP zones in mountainous area of Himalayan region and the nine parameters considered in the present study can be applied in also other areas of the region for preparing GWP map.

Landslide detection and susceptibility mapping using geological and remote sensing data: A case study of Azad Kashmir, NW Sub-Himalayas

Azad Kashmir has undergone sever landslide episodes in the past. The main reasons behind the occurrence of landslides in this area are heavy rainfall, weak geological strata, seismic zones and active faults. Several episodes of roads blockage due to landslide is one of the major problem in this area, therefore, this study is carried out for landslide susceptibility analysis along the roads of Kotli to Trar Khel, Azad Kashmir, NW Sub-Himalayas. Geographic information system (GIS) is used to interpret remote sensing, geological strata and topographical data. Total ten anthropogenic and physical factors (aspects, fault, lithology, drainage density, curvature, distance to roads, landuse landcover, slope, seismic and elevation) were examined by Multi-criteria Decision Analysis (MCDA) technique. The thematic layers of all factors were prepared for the preparation of the final susceptibility map by using a weighted overlay method (WOM). The susceptibility map classified the study area into four susceptible classes of low, moderate, high and very high. The spatial analysis and result outcomes depicted that active faults, slope gradient and landuse landcover may facilitate landslide phenomena. The results were verified by landslide density analyses (LDA), receiver operator characteristics (ROC) and area under curve (AUC) with predictive accuracy of 77 % that is rated as satisfactory by many researchers.

Gully Erosion Mapping by Multi-criteria Decision Analysis Techniques and Geoinformatics in Adana Province, Turkey

Gully Erosion Mapping by Multi-criteria Decision Analysis Techniques and Geoinformatics in Adana Province, Turkey

Investigating Crucial Factors of Agile Software Development Through Composite Approach

The major emphasis of Software Engineering (SE) discipline is to produce successful software systems. The success of software projects is estimated through quadruple measures including budget, cost, scope, and quality. To meet this aim of SE, several software development processes are presented in the literature. Such processes are categorized into two different methodologies which are known as traditional and agile software development methodologies. The issue with traditional software development methodologies is that they had not shown any remarkable progress towards the fundamental goal of SE. Consequently, software development organizations have started to adopt agile methodologies in the pursuit of successful software development. However, agile adoption does not come without challenges that vary from one context to another. Therefore, it is necessary to figure out the key factors of agile software development for successful project outcomes. In the wake of such need, this study investigated the Critical Success Factors (CSFs), categorized and prioritized them through a mixed-method approach. Such an approach was based on the detailed literature review and Delphi method accompanied with Multi-Criteria Decision Analysis (MCDA) technique. Twelve CSFs were revealed and categorized into people, organization and technical dimensions. Among these factors, ‘team capability’ was found the most significant factor where ‘culture’ was revealed as the least significant factor. The findings of the study would be promising for agile software development that is carried on in the local software industry.

Prioritization in wildfire restoration using GIS-based ordered weighted averaging (OWA): A case study in southern California

<abstract> <p>Wildfires are a prevalent natural disaster that can significantly impact human populations and result in considerable losses. With a changing climate, wildfires in many countries have increased in intensity and frequency, making effective restoration efforts in affected areas crucial. This paper aims to evaluate the efficacy of ordered weighted averaging (OWA), a GIS-based multi-criteria decision analysis technique, in identifying priority areas for wildfire restoration. A case study using the 2009 Station Fire in California is presented, using the restoration criteria of slope, erodibility, proximity to forest cover, and proximity to surface water. By applying both importance and order weights, multiple OWA decision strategies with varying risk levels were examined. Different strategies greatly influence the spatial distribution of land considered high and low priority for wildfire restoration, each with varying levels of trade off. In the OWA decision space, placing full emphasis on the highest (best) values (using the risk-taking OR operator) or the lowest values (using the risk-averse AND operator) resulted in composite priority maps that cannot be recommended for practical use. More nuanced scenarios are achieved with the OWA operators representing a range of compromise decision strategies between these extremes. The OWA technique in GIS can thus help to explore the impact of decision-makers' risk attitudes in a wildfire restoration setting.</p> </abstract>

USING GIS-BASED MULTI-CRITERIA DECISION ANALYSIS TECHNIQUES IN THE SMART CITIES

Abstract. The population of cities is increasing rapidly nowadays, and therefore, rational use of urban resources is required. With developing technology, the amount of data obtained from different sources also increases. This situation sometimes causes complex geographic decision problems in cities where many factors must be evaluated simultaneously. Difficulties in this decision-making process can be overcome by using Multi-Criteria Decision Analysis (MCDA) techniques. In this study, how the different MCDA techniques can be used in geographic-based problems and the most commonly used methods were examined in this context. The case applications on the adaptation of GIS-based MCDA techniques in smart cities were examined and explained. All of the examined case applications were carried out in the Pendik district of Istanbul. The subjects of the investigated case applications are, respectively, the evaluation of land suitability for determining urban development areas, producing a land value map for the management of the urban real estate, parking areas selection for sustainable urban transportation planning, and prioritizing suitable/alternative car parking areas. This study provides an effective implementation methodology for the hybrid use of GIS-based MCDA techniques within the scope of sustainable urban land management practices in smart cities.

A public participatory GIS and multi criteria decision analysis framework for the evaluation of transport scenarios

The decision-making process of transport projects is very complex, especially for public administrations which have to take into account often incomparable criteria of judgment. In addition, in order to achieve a good social sharing and robustness of the decision, policy makers have to include in the process not only the transport planning experts but also the stakeholders of the community. The purpose of this study is to propose an evaluation framework to support the decision making process, able to allow public participation in the assessment of transport planning and design scenarios while, at the same time, ensuring a high level of technical quality of the final decision. The designed framework includes a method to analyze monetary and non-monetary parameters, easily understandable for all decision makers. It is based on the application of Multi Criteria Decision Analysis (MCDA) techniques, an evaluation process that can take into account different quantitative and qualitative objectives and criteria; in order to favor public participation, the implementation of this technique takes advantage of Geographic Information System (GIS) for its ability to easily represent the impact of spatially based alternative project scenarios. The analysis of several case studies on transport planning and design scenarios allowed to assess the level of implementation of the three main ingredients of the framework: MCDA, GIS and public participation.

Diversity and potentiality of multi-criteria decision analysis methods for agri-food research

There is a growing demand for moving towards sustainable agri-food systems which per nature covers a complex network of activities and domains; such systems will benefit from multi-criteria decision analysis (MCDA) methods. Although some reviews on MCDA in agri-food research have been published, none of them covered the whole value chain. In this article, a corpus of 954 articles published by INRA scientists from 2007 to 2017 was used to study the diversity and potentiality of MCDA techniques. For the first time, experts from more than 10 agri-food domains worked altogether to annotate the articles, carry out a multivariate analysis, and finally interpret the statistical results to identify the specificities of certain domains and the complementarities between domains and to suggest avenues for future agri-food research. One-third of the studies were based only on a list of indicators, even when their purpose was to choose, sort, or rank options. Regardless of the scientific discipline in the agri-food sector, MCDA studies rarely considered temporal dynamics, spatial scale changes, or stakeholder contributions. As the agri-food system becomes increasingly sustainable in the near future, the use of MCDA methods will accelerate. To become more effective, they will have to include ecosystem services, even outside the scope of ecological studies. Similarly, MCDA studies will need to include participatory science to involve stakeholders (i.e., public authorities, governmental agencies) and end-users (i.e., farmers, producers, industrials, consumers) in the construction of the multi-criteria evaluation but also in the resulting decisions.

Regional Assessment of Groundwater Potential Zone Using Remote Sensing, GIS and Multi Criteria Decision Analysis Techniques

The growing demand for freshwater for domestic and industrial purposes is a current challenge in the Upper Niger River Basin Development Authority area. Consequently, there is heavy demand for groundwater resources to meet this need. This challenge has worsened due to the non-incorporation of integrated methods in groundwater exploration campaigns. Innovative scientific principles and quantitative assessment of groundwater resources are required for sustainable and proper management of the resources. Therefore, the objective of this paper is to exploit the potential application of remote sensing, Geographic Information System (GIS), and Multi-Criteria Decision Analysis (MCDA) techniques in mapping groundwater potential zones. To achieve this, seven factors deemed to have significant control over the occurrence and movement of groundwater viz. geology, lineament density, slope, drainage density, rainfall, land-use/land cover, and soil class were produced. These factors were assigned weights and normalized with respect to their relative contributions to groundwater occurrence using the Analytic Hierarchy Process (AHP). This resulted in groundwater potential zones that have been classified into four: Very good, Good, Moderate and Poor representing 7%, 27%, 43%, and 23% respectively. This result represents groundwater potential in the area and should be used as a preliminary reference in selecting prospective sites for detailed groundwater resource exploitation

An Improved Approach to Analyze Accidents and Promote Road Safety using Association Rule Mining and Multi-Criteria Decision Analysis Methods

Background: Road accidents have become a major social and health problem for being dramatically increasing day after day worldwide. Scientists are conducting their studies to define the main attributes that share the severity of road accidents. Finding a new approach to analyze road accidents is of great urgency. Data mining techniques are best fitting to discover useful information out of enormous data which are used to make proactive decisions. Methods: This paper tempts a rule-based machine learning method known as association rule mining, which can identify strong rules discovered in databases using interesting measures. Given a data- set from the Lebanese territory for the years 2016-2017, the application of association rule mining, the Apriori method takes its place. However, its implementation leads to a very large number of rules. The task that is the most difficult is extracting meaningful and non-redundant rules. In order to find out the most interesting and relevant rules out of fatal rules such, ELECTRE TRI and PROMETHEE methods, the most significant methods of decision making, Multi-Criteria Decision Analysis (MCDA) are integrated to resolve the outranking problem. The integration is presented by the use of the same set of weights and the same constant values of Indifference and Preference thresholds used in ELECTRE-TRI method to define the linear preference function needed by PROMETHEE method. Realizing the sensitivity of the final output of alternatives ranking to the changes of the input parameters of the decision-making tool, this proposed integration helps the decision makers to overcome their ambivalence between preference and indifference thresholds and to cope adequately with the issue of the uncertainty of MCDA procedures; it comes up with the complete ranking of rules. Results: The obtained ranked rules declare the most significant attributes or combinations of attributes that influence the severity of road accidents. Four main factors of fatal road accidents are pinpointed: over-speeding mainly leading up to rollover crashes, pedestrians encountering in the context, distracted driving leading to fatal road vehicle collisions with Pedestrian victims; and wet roads particularly in the case of single car accidents. Meanwhile, the importance of ELECRE-TRI and PROMETHEE and their integration in dealing with such complex phenomena and corresponding database with a large number of involved attributes have been validated. Conclusion: This paper studies the phenomenon of road accidents. Association rule mining has been applied to discover all possible relations between the various attributes. The integration of ELECTRE- TRI and PROMETHEE MCDA techniques aims at extracting meaningful information from the big dataset. The obtained results have shown how influencing the behavior of the driver is on the occurrence of fatal road accidents. These findings contribute to supporting decision makers to draw new design conceptions for road infrastructure and develop preventive measures that improve road safety in Lebanon.

Forest fire susceptibility mapping via multi-criteria decision analysis techniques for Mugla, Turkey: A comparative analysis of VIKOR and TOPSIS

Turkey has a high forest fire potential along the Aegean and Mediterranean coasts, related to climate and extremely sensitive forests. In Turkey over 10,000-ha forest area has been destroyed every year and inevitable damage has been revealed. Forest fires not only destroy forest areas, but also cause damage to ecosystems, habitats and especially human lives. Because Muğla province has 90% of total pine honey production in the world and a high potential forest fire occurrence rate, sustainability of ecosystems, productivity and economic income require determining forest fire susceptibility zones. Generating forest fire susceptibility zones is a complex study which requires considering environmental, forestry, topographic, economic, and meteorological parameters within a decision support platform. At this point, Geographical Information System (GIS) aided Multi-Criteria Decision Analysis (MCDA) techniques can provide sufficient and effective solutions for fire susceptibility mapping due to the comparable and scalable structure of the criteria that are used to determine the susceptibility map when deciding. In this study, the weight of each criterion is calculated via the Analytical Hierarchy Process (AHP). Then, TOPSIS and VIKOR methods were used to generate forest fire susceptibility maps in Muğla province. The results indicated that 1659.44 ha (13%) and 3952.14 ha (31%) of the study area were assigned as highly prone to forest fire according to the TOPSIS and VIKOR calculations respectively, and an 81% correlation coefficient was calculated between methods. The reliabilities of the maps were verified with 1454 forest fire locations. Considering the respective 89.54%, 86.94% and 88.99% accuracy rate of VIKOR, TOPSIS and AHP susceptibility maps, all the methods could be used in forest fire susceptibility map generation which has comprehensive decision making process.

Composite indicators as an innovative methodology for Communication Sciences: implementation for the assessment of European public service media

The currently dominant scientific production model in the field of Communication exhibits an excess of standardization towards mainly empirical work that is overwhelming caried out using quantitative techniques based on simple statistical analyses, in many cases limiting the presentation of results to a reading of the available data. This article presents an innovative proposal in this area, designed as a new form of dissemination and scientific presentation, with the objective of constructing three composite indicators that, when applied to European public service media, will enable the assessment of the perception of their social value, independence, and management efficiency. Another aim of the study is to provide a comparative vision of these three aspects in all the countries of the European Union except Malta and Luxembourg. This methodology is innovative because it explains the process in detail and justifies the validity of the documentary sources that were used to facilitate its replication or questioning, and reinforces the discussion of the results obtained by evaluating the robustness of the indicators created, before determining which was the most appropriate and comparing the results with a multicriteria decision analysis technique, the Topsis method (technique for order preference by similarity to ideal solution), proposed by Hwang and Yoon (1981). The results show that the synthetic indicators constitute an innovative, original, and validatable methodological tool that can contribute to the advancement of research in Communication.

Evaluating the Application of Decision Analysis Methods in Simulated Alternatives Assessment Case Studies: Potential Benefits and Challenges of Using MCDA.

We compare how several forms of multicriteria decision analysis (MCDA) can enhance the practice of alternatives assessment (AA). We report on a workshop in which 12 practitioners from US corporations, government agencies, NGOs, and consulting organizations applied different MCDA techniques to 3 AA case studies to understand how they improved the decision process. Participants were asked to select a preferred alternative in each case using a different decision analysis approach: their unaided decision-making method, individual or lightly facilitated group multiattribute value theory (MAVT), and more extensively facilitated group structured decision making (SDM). Surveys conducted after each exercise revealed that participants were positive toward the use of formal decision-making methods for AA, reporting meaningful increases in their understanding of the trade-offs involved and their own values. Participants also reported challenges with each approach. While the MCDA techniques were reported to enhance transparency and communication, they did not consistently lead to higher satisfaction with a decision and/or outcome, and they were not more likely to be adopted within their organizations than unaided approaches. More formal decision-making methods have promise in the context of AA, but practitioners will need more guidance to use such tools successfully. Practitioners will also need to define what "success" constitutes; different approaches may be called for depending on whether the objective is increased understanding, satisfaction with the outcome, satisfaction with the process, or something else. Integr Environ Assess Manag 2021;17:27-41. © 2020 SETAC.

Comparing potential risk of soil erosion using RUSLE and MCDA techniques in Central Ethiopia

Water erosion remains a threat to subsistence agriculture. Insofar, spatial-based soil erosion risk mapping is investigated to assist interventions across varying scales. The Revised Universal Soil Loss Equation (RUSLE) model and Multi-Criteria Decision Analysis (MCDA) techniques are most recently used to map soil erosion hotspots in Ethiopia. Aligned to that, this study aims to identify and compare the risk of soil erosion using the RUSLE and MCDA approach in Sodo watershed covering 80.54 km2, central Ethiopia. The adjusted parameters of RUSLE and MCDA demanding soil, land use, and terrain feature data were used for the study. Finally, cross-comparison was effected to check their consistency. The RUSLE model shows 68.91% of the study area accounted for a soil loss of 75 ton/ha/year. Generally, the mean annual gross soil loss amounts to 783,170 tons, with the mean soil loss rate of 35.28 tons/ha/year. This is 1.96 times higher than the tolerable limit for Ethiopian highlands. The MCDA result shows that 5.6%, 50.57%, and 43.83% of the watershed are highly, moderately, and slightly sensitive to soil erosion, respectively. The overlay result reveals that 49.4% of the risk and location of land susceptibility was similarly estimated by RUSLE and MCDA. This is a “good agreement” with a Kappa value of 0.62. The consistency increases with a decreasing level of sensitivity. Therefore, this could be an input for local decision-makers and experts at large.

Understanding the key performance parameters of green lean performance in manufacturing industries

The estimation and monitoring of key performance parameters of Green Lean in the manufacturing sector have recently attracted considerable attention. Performance measurement is an essential practice for measuring manufacturing industries’ competitiveness. In this era of global competitiveness and customer expectations, manufacturing firms face various challenges. To solve these challenges, researchers in the academic and manufacturing world have observed a keen interest in green lean manufacturing practices. The concept of lean manufacturing was developed to maximize the use of resources and minimize waste at all manufacturing activities. On the other hand, Green concept in manufacturing sector relates to the environmental and social concerns. The manufacturing firms strive to find and improve output performance by using key performance parameters to find the possibilities in Green-lean concepts in the manufacturing sector. The purpose of this study is to identify and examine the various key performance parameters (KPPs) of Green-Lean practices in manufacturing industries. Future research will focus on ranking these KPPs of green lean manufacturing using appropriate Multi-Criteria Decision Analysis (MCDA) technique.

Evaluating the Energy Potential of Solar PV Located on Mining Properties in the Northern Cape Province of South Africa

The lauded Renewable Energy Independent Power Producer Procurement Program (REIPPPP) has achieved much in stimulating private sector investment in the renewable energy market in South Africa. Yet, 95% of electricity generated is still from a single source, the state-owned utility Eskom. This paper set out to explore the policy sphere governing electricity generation and identifying possible avenues that can contribute to a more vibrant solar energy market in the most solar abundant province of South Africa, the Northern Cape Province. Licensed mines were identified as low hanging fruit due to a large policy overlap and leeway within existing mining policy. A solar audit of these areas was performed, based on accepted multi-criteria decision analysis techniques, and found that a potential 369 TWh to 679 TWh per annum can be generated, exceeding South Africa’s current electricity usage.