Multiple Criteria Decision Analysis Techniques Research Articles

Water Utility Service Quality Index: A customer-centred approach for assessing the quality of service in the water sector

This work delves into the crucial role of service quality in the water supply and sanitation sector. Despite extensive research and implementation of quality management practices in this sector, a universally accepted definition of quality is still lacking, resulting in various service quality assessment procedures that are difficult to compare. To address this issue, the World Bank launched the ‘Utility of the Future’ (UoF) programme, aiming to guide water service providers in their efforts to become future-focused utilities that offer reliable, safe, inclusive, transparent, and responsive services through best-fit practices. Building upon the framework provided by the UoF programme, this study proposes the Water Utility Service Quality Index (WUSQI) - a composite indicator that reflects the quality of service provided by water supply and sanitation utilities from a customer perspective. Based on Data Envelopment Analysis, the Benefit-of-the-Doubt approach is employed to assign weights for aggregating the indicators representing the diverse performance dimensions. The study operationalises the WUSQI to assess the quality of Portuguese wholesale water and wastewater companies using data collected by the national regulator of water and waste services. A Multiple Criteria Decision Analysis technique, the Deck of Cards method, is used to specify an indicator of transparency from the information made available by the regulated utilities. The results show the effectiveness of this tool for evaluating and measuring service quality at the company level. Additionally, the findings highlight areas for improvement in the utilities’ performance. By enabling companies and regulators to identify areas for improvement, the WUSQI can support the delivery of high-quality services to customers.

Selecting the Flexible Last-Mile Delivery Models Using Multicriteria Decision-Making

Postal service providers can reorganize the last-mile delivery process within the scope of universal service and apply some of the flexible models for the organization of the delivery process. In this paper, the question of the selection of Flexible Last-Mile Delivery Models (FLMDM) is treated using multicriteria decision-making. We have identified four different sustainable models of last-mile delivery with an emphasis on the number of delivery workers. One postal service provider from Europe was selected, where proposed FLMDM are tested. The proposed last-mile delivery models are ranked using Multiple Criteria Decision Analysis (MCDA) technique. In this context, MCDA techniques are used to make a comparative assessment of alternatives. This paper aims to find the optimal delivery costs in each variant of the delivery model - an optimal number of workers for the last-mile delivery. The obtained results suggest the AB delivery model as the optimal choice for the last-mile delivery. Also, results ensure the complete allocation of the required number of technological workers in the delivery (the number of delivery workers), by applying the originally proposed, flexible solution (models) for the organization of last-mile delivery.

Proper and improper uses of MCDA methods in energy systems analysis

Over the past few decades, the strategies to perform energy systems analysis have evolved into multiple criteria-based frameworks. However, there still remains a lack of guidance on how to select the most suitable Multiple Criteria Decision Analysis (MCDA) method. These methods provide different decision recommendations for the Decision Makers, including ranking, sorting, choice, and clustering of the alternatives (e.g., technologies or scenarios) under evaluation. They deal with a variety of data typologies and preferences, and lead Decision Makers in shaping the energy systems of the future. Here, we evaluate the MCDA methods used in 56 case studies performing energy systems analysis at different scales. We find that close to 60% of these studies chose an MCDA method that was not the most adequate for the respective decision problem. In particular, this concerned the use of weighting methods (e.g., Analytical Hierarchy Process) in MCDA approaches not suited for this type of weights, sub-optimal selection of MCDA techniques for specific types of problem statements, and lack of handling rather evident interactions in preference models. Our analysis demonstrates that these deficiencies can be overcome by using a recently developed methodology and software that support Decision Makers and analysts in selecting the most suitable MCDA method for a given type of decision-making problem.

A PROMETHEE Multiple-Criteria Approach to Combined Seismic and Flood Risk Assessment at the Regional Scale

Social vulnerability is deeply affected by the increase in hazardous events such as earthquakes and floods. Such hazards have the potential to greatly affect communities, including in developed countries. Governments and stakeholders must adopt suitable risk reduction strategies. This study is aimed at proposing a qualitative multi-hazard risk analysis methodology in the case of combined seismic and flood risk using PROMETHEE, a Multiple-Criteria Decision Analysis technique. The present case study is a multi-hazard risk assessment of the Ferrara province (Italy). The proposed approach is an original and flexible methodology to qualitatively prioritize urban centers affected by multi-hazard risks at the regional scale. It delivers a useful tool to stakeholders involved in the processes of hazard management and disaster mitigation.

Determination of the most appropriate tools of multi-criteria decision analysis for underground mining method selection—a case study

Selecting the optimal mining method is one of the most critical issues in mining design. It entirely depends on different parameters, such as geotechnical, geological, economic, and geographic factors. Although many researchers have tried to apply a various multiple-criteria decision analysis (MCDA) technique to select the most appropriate mining method, there are no clear reasons for choosing a specific decision method. For this purpose, a new methodology has been presented in this research work to find the most appropriate MCDA techniques for selecting the optimal underground mining method in the Anguran zinc deposit, north-west of Iran. At the first step, a list of fifty parameters, including geomechanical, geometrical, technical, economic, environmental, and social parameters, has been made for selecting the optimal underground mining method. Then, the most influential parameters, including thickness, RMR of the hanging wall, and production rate, were chosen the most crucial parameters according to the experts’ opinions in this matter. Also, among all conventional MCDA methods, including ELECTRE, MAUT, ANP, MACBETH, AHP, TOPSIS, PROMETHEE, VIKOR, TODIM, Grey, MULTIMOORA, and MAHP, the TODIM has been selected as the best MCDA method for further studies on the case. Applying this technique, the cut and fill mining was chosen as the best method for the Anguran zinc mine while the square set mining was the worst method in this case. The results also revealed that the proposed method could be extensively applied to find the most appropriate MCDA in mining engineering.

Analytic Method for Decision Support of Blockchain Technology Supplier Selection in Industry 4.0 Era

Abstract The article presents the issues covering the modern methods of securing data in both manufacturing processes and companies within the concept of Industry 4.0. In this approach, research problems arose how to implement the right method of secure data sending in sales, manufacturing and distribution processes. It is a very important issue for manufacturing companies as well as how the process of sending electronic data should be safely conducted. While current researches concentrated on the method of blockchain secured electronic documents, there is almost no research concentrating on blockchain integrator selection criteria. The main purpose of this paper is to provide a decision assistance model based on multiple criteria decision analysis technique. Also, mutual relationships between parameters for the assessment of integrators are established. In the article, a Multi-Criteria Decision Analysis (MCDA) was used to assess these characteristics. The Decision Making Trial and Evaluation Laboratory (DEMATEL) technique was chosen for this assessment.

Multi-Criteria Efficiency Analysis of Using Waste-Based Fuel Mixtures in the Power Industries of China, Japan, and Russia

This paper presents the results of analyzing the efficiency of the following five fuel types: dry coal, wet coal processing waste, coal–water slurry, and two waste-derived slurries. In the calculations, we employed 16 criteria related to the energy industry, economy, social aspects, safety at plants, and environmental protection. We used the experimental data, obtained from the combustion of the fuels under study at three heating temperatures (700 °C, 800 °C, and 900 °C). Three countries were analyzed, where all of them have a high share of using fossil fuels in the energy industry: Japan, China, and Russia. The total performance indicator was calculated using three multiple-criteria decision analysis techniques (weighted sum method, weighted product method, and analytic hierarchy process). The choice of weight coefficients was confirmed for each method. We found that coal and coal–water slurry had the lowest integral efficiency indicators (0.016–0.535 and 0.045–0.566, respectively). The maximum effect was achieved when using waste-derived slurry with used turbine oil (0.190–0.800) and coal processing waste (0.535–0.907). There were, on average, 3%–60% differences in the integral efficiency indicator for the same fuel in different countries. The difference in the efficiency indicator of the same fuel in different countries was on average 3%–60%; with changes in temperature, the difference in efficiency was 5%–20%; and when changing the calculation procedure, the difference was 10%–90%.

Development of a model using matter element, AHP and GIS techniques to assess the suitability of land for agriculture

Land suitability assessment is an essential step for land use planning and development. Over the last decade, many researchers, organizations, research institutes and governments have tried to provide a comprehensive procedure for the optimal use of agricultural land, but have failed to balance competing issues in a systematic way. Matter element is a multiple criteria decision analysis (MCDA) technique which has shown high potential for solving complicated issues. The use of MCDA techniques such as matter element and analytic hierarchy process (AHP) based on remote sensing (RS) and GIS is a flexible and effective framework to assess and map several different criteria for the strategic placement of cropping. We used data from 167 soil profiles covering 12,000 ha of land located in Ardabil province, northwest of Iran to assess criteria using MCDA techniques that may limit barley production under irrigation. After soil sampling and analysis, 24 soil series (all Aridisols) and 66 land units were identified and separated in the study area. Several criteria were limiting, but the most limiting criteria included: soil depth, slope, climate characteristics, pH, electrical conductivity, exchangeable sodium percentage, calcium carbonate equivalent and gypsum content. Combining and analyzing criteria in an AHP-matter element model generated a land suitability map for barley production. The coefficient of determination (R2) between land suitability index and observed barley yield was 0.947 for AHP-matter element hybrid model. Modeled estimates were compared and showed that the hybrid approach of AHP and matter element techniques was more accurate than the storie and square root methods in selecting the most suitable areas for barley production. The AHP-matter element hybrid method can therefore improve planning and decision making regarding land which is suitable for barley cultivation. This approach may also be suitable other crops.

Two decades on the MACBETH approach: a bibliometric analysis

MACBETH stands for measuring attractiveness by a categorical based evaluation technique. It is a multiple criteria decision analysis technique created by Carlos Bana e Costa and Jean-Claude Vansnick in the early 1990s. Due to both the increasing application of the technique and progress achieved to date, this study aims to conduct a bibliometric literature review on MACBETH. The database for the review contains 192 scientific articles published in scholarly publications indexed in the Scopus database from 1994 to 2016. Although other literature reviews of the technique exist, this study has a different emphasis and uses two distinct citation analysis methods—bibliographic coupling and co-citation—, allowing us to generate new insights regarding some of the most active and influential articles, journals and authors, as well as to reveal rankings, clusters of contributions and collaboration networks. The results obtained are important to enhance our understanding of the technique’s anatomy (i.e., its intellectual structure), and can support the identification of new lines of application and development.

PMD136 - THE FEASIBILITY OF APPLYING THE MULTIPLE CRITERIA DECISION ANALYSIS FOR THE EVALUATION OF MEDICAL DEVICES IN THE CONTEXT OF HOSPITAL-BASED HEALTH TECHNOLOGY ASSESSMENT IN TURKEY

Health technology assessment (HTA), which draws from medical, social and economic studies, has become an integral part of healthcare resource allocation decisions in many countries. Multiple Criteria Decision Analysis (MCDA) has been proposed for use in HTA due to the failure of Cost-Effectiveness Analysis (CEA) capturing all dimensions of the health benefits of medical technologies. The objective of this study, therefore, is to assess the applicability of MCDA in the context of hospital-based HTA (HB-HTA) for the evaluation of medical devices in Turkey. The EU funded AdHopHTA (Adopting Hospital Based Health Technology Assessment) project, conducted a case study at the Ankara Numune Training and Research Hospital in Turkey to examine the dynamics of the decision-making process of hospital managers on the uptake of health technologies. The survey results, based on the interviews with hospital managers, were further analysed for the purpose of this study. The Multi Attribute Value Theory (MAVT) is used as an MCDA technique here. The methodological stages of MAVT are applied to the current economic evaluation part of the HB-HTA processes in Turkey. The survey results demonstrated two needs of hospital managers in the decision-making process: 1) reaching a high level of consensus on the final HTA decision and 2) making a comparative analysis that captures the medical, social and economic benefits of medical devices in a scientific way. This study showed that the methodological stages of MAVT are very similar to the overall processes of HB-HTA in Turkey, with an addition of a formal mathematical approach that considers all relevant criteria transparently with the involvement of various stakeholders. MCDA has the great potential to support the decision-making process of HB-HTA bodies and hospital managers in evaluating the value of medical devices in Turkey, although further discussions and pilots are needed.

Multiple Criteria Decision Analysis Based Overlapped Latent Fingerprint Recognition System Using fuzzy Sets

Latent fingerprints have attracted considerable attention from researchers in the fields of forensics and law enforcement applications. Public demand for these applications may be the driving force behind further progress in biometrics research. Although great effort has been taken to devise algorithms for overlapped latent fingerprint classification system, there are still many challenging problems involved in fingerprint classification systems. Most of the fingerprint-based applications will prolong with fingerprint recognition because of its proven performance, the existence of large databases and the availability of the fingerprint devices with minimum cost. There are various issues that need to be addressed to develop fingerprint classification system. In this connection, there are some designing challenges such as nonlinear distortion, low-quality image, segmentation, sensor noise, skin conditions, overlapping, inter-class similarity, intra-class variations and template ageing. In crime scenes, the latent images can be overlapped with some background images or more number of fingerprint images from same person or different person. An overlapped fingerprint image should be processed for fingerprint classification. This proposed recognition system suggests multiple criteria decision analysis technique to assess the overlapped latent fingerprints. The proposed multiple criteria such as first-order, second-order and third-order features are used to classify the overlapped latent fingerprints. The proposed system designs the novel classification system for overlapped latent fingerprint images using ANFIS classifier. Extensive experiments are performed on the simultaneous latent fingerprint databases, and National Institute of Standards and Technology-Special Database 27, Fingerprint Verification Competition 2006 Database1-A and Database2-A databases. The planned work enables accurate and fast data retrieval by using one-to-N fingerprint classification for overlapped latent images. The experimental results are highly promising, and they outperform the existing systems in classifying overlapped images. The performance of adaptive neuro fuzzy inference system classifier is evaluated by applying the k-fold cross-validation technique. The outcome of the work shows that the overlapped fingerprint is classified in a successful manner, and the results are compared with Bayes, SVM and MLP classifiers. The obtained results show that the proposed system achieves a better classification rate of 90.66% with 5 s, 86.66% with 12 s compared to the existing system.

MCDA in knowledge-based economies: Methodological developments and real world applications

The importance of knowledge in creating value, driving productivity and promoting economic growth has long been recognized. Accompanying this recognition of the central role of knowledge in today's economies has been an added focus on information technology, learning and the accelerated pace of technical and scientific advance that results therefrom. Closely connected to these developments has been the advent of big data; and as information becomes available at greater volumes and higher speed, the focus is shifting from quantity to the quality of the information collected and the manner in which it is used. In this respect, Multiple Criteria Decision Analysis (MCDA) techniques constitute valuable tools for structuring and evaluating complex decision situations, and can allow for more informed, potentially better decisions. MCDA techniques are able to build on the knowledge of expert participants in a given field, and produce assessment systems based on values and experience. Constructivist in nature, this approach has grown exponentially over the past few decades, causing a change in the decision-making arena in general, and in the field of decision support systems (DSS) in particular. The objective of this special issue is to bring together recent developments and methodological contributions within MCDA, with the challenges which characterize the knowledge-based economy, as they pertain to the themes of technological forecasting and social change.

GIS-based multi-criteria approach for identification of rainwater harvesting zones in upper Betwa sub-basin of Madhya Pradesh, India

The emergent water paucity calls for more resourceful alternatives of water conservation. Rainwater harvesting (RWH) is one of the most capable systems to increase availability of water and agriculture output in the semi-arid regions. Nevertheless, the assessment of RWH potential and selection of appropriate RWH locations pose a great challenge for the water managers due to lacking biophysical data and infrastructure. The present study attempts to assess the RWH potential and identifying probable RWH locations in the Betwa sub-basin using geospatial and multiple criteria decision analysis techniques (MCDA). The spatial theme such as land use land cover was derived by supervised classification method and lineament and drainage by edge enhancement method from Landsat ETM + satellite image and other secondary published maps. The surface runoff was determined from modified Soil Conservation Service Curve Number (SCS-CN) method. These parameters were assigned suitable weights and integrated with a geospatial (GIS) technique to generate RWH site suitability map and to identify possible locations for RWH structures. SCS-CN technique displays that the water-body and built-up areas have high runoff potential, while forest area shows low runoff. The analysis indicates that 5.6% (87.7 km2) is suitable for percolation tanks, 3% (46.6 km2) suitable for farm ponds and for check dams (0.7 km2) of the study area. The study reveals combined methodology of geospatial and MCDA procedures in planning of rainwater harvesting at a regional scale.

Evaluating Brownfield Redevelopment using an Modified Multilevel Grey Method - A Case Study of Xi’an

A novel multiple criteria decision analysis (MCDA) method is designed for comparing and ranking resolution solutions to a brownfield redevelopment project. In particular, an MCDA technique called the modified multilevel grey evaluation method is developed using concepts from grey systems theory, entropy and the analytical hierarchical process (AHP). To obtain weights for the range of criteria and sub-criteria used to assess and compare the resolution solutions, results obtained using AHP and an entropy technique are combined. In order to reflect uncertainty in the evaluation scores of the resolutions according to the sub-criteria, a grey systems class is employed to appropriately transform the scores. Subsequently, the evaluation method for the resolutions along with the combined weights is used to rank the resolutions. To demonstrate how this new methodology can be conveniently used in practice and provide valuable insights for aiding decision making, it is applied to a brownfield site in Xi’an, China, created by a former chemical factory.

Multi-criteria Routing in a Partitioned Wireless Sensor Network

Energy efficiency is one of the key challenges for designing routing algorithms for wireless sensor networks (WSN). Fast data delivery from source node to sink node is also required for many applications. Sometimes data transmission towards the sink may be interrupted because of failure of nodes in a particular area. The various such requirements of routing data in a WSN are sometimes contradictory and routing algorithms must be designed keeping in mind all these requirements. In this paper three routing algorithms are proposed for multi-sink partitioned network. In these three algorithms, the source nodes or intermediate nodes select a next node to forward the data to the destination or sink. This process repeats until the data reaches the sink. In the first technique, the next node is chosen considering its distance from sink node as a criterion. In the second technique, remaining energy of the neighboring nodes is used as a criterion for selection of the next node. The combination of these two criteria is considered in the third technique and a multiple criteria decision analysis technique is used. A recovery technique from area failure is also proposed and incorporated in the above mentioned algorithms. The algorithms are designed and implemented in multi-sink environment for partitioned wireless sensor networks. Performances of the algorithms are studied in a simulation environment and compared with other well-known algorithms to understand their effectiveness.

Multiple criteria decision analysis methodologies and an application to the Istanbul Stock Exchange

In the business world, effective decision making is one of the most important things at all times. The decision maker should take into account all objectives simultaneously. Multiple criteria decision analysis (MCDA) methodologies can take into consideration many criteria during effective decision making process. The most widely used MCDA techniques are AHP, ELECTRE and TOPSIS. In this paper, we discuss these techniques and their advantages/disadvantages. These techniques were applied to ISE-30 from 2002-2012 in Turkey and the most effective three stocks were found. The results of applications are compared within the terms of the techniques' properties and the year-end returns.

A hybrid model for learning from failures: The Hurricane Katrina disaster

There is a need to facilitate learning from failures in the context of natural and man-made disasters. This paper investigates the multi-faceted nature of research in disasters and the aspect of hybrid approaches in modelling within this domain. The paper applies a framework of reliability and multiple criteria decision analysis techniques to the case of the Hurricane Katrina disaster of 2005. It is shown how this hybrid model can be used through an integrative approach to perform a systematic analysis that can lead to learning from failures.The proposed framework incorporates and integrates Fault Tree Analysis (FTA), Reliability Block Diagram (RBD) analysis and the Risk Priority Number (RPN) concept, together with the Analytic Hierarchy Process (AHP) which is used as a simulation model for decision support. It is shown how the proposed integrated framework can contribute to our understanding of failures and enhances the ability to extract lessons from failures or disasters. Such lessons are then mapped into specific decisions for prevention, and resource allocations, to help avoid a repeat disaster.

Operationalizing and measuring individual entrepreneurial orientation using cognitive mapping and MCDA techniques

Despite the widely acknowledged importance of entrepreneurial orientation in the establishment of successful ventures, identifying entrepreneurship attitudinal orientation, and finding its determinants in particular, is a complex undertaking due to the variety of intuition- or subjectivity-based factors underlying individual entrepreneurial orientation (IEO). Grounded on the integrated use of cognitive maps and the measuring attractiveness by a categorical-based evaluation technique (MACBETH), this paper aims to develop a multiple criteria decision analysis (MCDA) framework to assist the measurement of IEO. This evaluation mechanism makes it possible to classify individuals according to their entrepreneurial profiles, allowing managers and investors to make more informed decisions regarding business partnerships or funding allocations. Specific guidelines on how to construct such a mechanism, implications for scholars and practitioners, as well as the strengths and shortcomings of our measurement system, are also discussed.

Development, test and comparison of two Multiple Criteria Decision Analysis (MCDA) models: A case of healthcare infrastructure location

When planning a new development, location decisions have always been a major issue. This paper examines and compares two modelling methods used to inform a healthcare infrastructure location decision. Two Multiple Criteria Decision Analysis (MCDA) models were developed to support the optimisation of this decision-making process, within a National Health Service (NHS) organisation, in the UK. The proposed model structure is based on seven criteria (environment and safety, size, total cost, accessibility, design, risks and population profile) and 28 sub-criteria. First, Evidential Reasoning (ER) was used to solve the model, then, the processes and results were compared with the Analytical Hierarchy Process (AHP). It was established that using ER or AHP led to the same solutions. However, the scores between the alternatives were significantly different; which impacted the stakeholders’ decision-making. As the processes differ according to the model selected, ER or AHP, it is relevant to establish the practical and managerial implications for selecting one model or the other and providing evidence of which models best fit this specific environment. To achieve an optimum operational decision it is argued, in this study, that the most transparent and robust framework is achieved by merging ER process with the pair-wise comparison, an element of AHP. This paper makes a defined contribution by developing and examining the use of MCDA models, to rationalise new healthcare infrastructure location, with the proposed model to be used for future decision. Moreover, very few studies comparing different MCDA techniques were found, this study results enable practitioners to consider even further the modelling characteristics to ensure the development of a reliable framework, even if this means applying a hybrid approach.

Systems methodologies in Vitae Systems of Systems

Systems methodologies constitute an implementation science to address complex environmental problems from a Vitae Systems of Systems perspective. The aim of Implementation Science is to obtain sustainable, fair and responsible solutions that satisfy as much as possible the value systems of stakeholders while upholding the Vitae principles of survivability, viability and conviviality. To represent the environmental and other societal problems under investigation, the insightful concept of a system of systems is adopted. For example, the Vitae viewpoint on solutions to global warming problems at the regional, national or international level is captured in the interactions of societal systems, such as industrial and service systems, with atmospheric, oceanic and land systems. To tackle the strategic aspects of complex systems of systems problems, there is a rich variety of systems engineering decision tools that can handle multiple stakeholders with multiple objectives; these tools are explained and compared according to their inherent capabilities. To demonstrate how systems tools can implement a Vitae Systems of Systems philosophy, three different techniques are applied to complex large-scale environmental and water resources management problems. The Graph Model for Conflict Resolution is used to address the large-scale environmental problem that arose over a massive irrigation project proposed for the US state of North Dakota - the infamous Garrison Diversion Unit. Next, a large-scale optimization model, integrating concepts from hydrology, economics and cooperative game theory, is employed to identify fair and feasible allocations of water resources among users in the South Saskatchewan River Basin located in southern Alberta, Canada. Finally, Multiple Criteria Decision Analysis techniques are used to assess different strategies to satisfy future water demand from multiple stakeholders within the Regional Municipality of Waterloo situated in southern Ontario, Canada.