Mobile Maps and More – Extending Location-Based Services with Multi-Criteria Decision Analysis

Human decisions about the design, deployment, and governance of AI systems are increasingly complex, involving multiple desiderata such as accuracy, fairness, transparency, cost, and environmental impact. This paper proposes a novel and scalable framework for managing this complexity through application of resources from the field of Multi-Criteria Decision Analysis (MCDA). After an introduction to the “ n > 2 Criteria Problem” in decision-making about AI, an introduction to MCDA methods, and a review of prior applications of MCDA to decision support in decisions involving AI, we lay out our own novel and scalable framework for applying MCDA to such decisions. We illustrate the framework through application to four simulated scenarios involving a medical institution’s choice among AI-powered diagnostic tools with varying performance on accuracy, fairness, transparency, and cost. We apply five multi-criteria decision analysis (MCDA) methods — namely, the Weighted Sum Model (WSM), the Analytic Hierarchy Process (AHP), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the VIKOR method (VlseKriterijumska Optimizacija I Kompromisno Resenje), and the Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE) — to rank ten AI models under four distinct weight configurations reflecting realistic deployment contexts. Sensitivity analyses are then conducted to examine how variations in criterion weight assignments affect model rankings across methods and scenarios. In concluding sections we discuss the scalability of these techniques for design, deployment, and policy decisions involving AI, as well as the likely limitations of MCDA methods for decision support involving AI.

Participatory management is a working method of paramount importance based on the principles of knowledge sharing and accountability for addressing the sustainable management of the fishery sector. To approach this multidimensional problem we applied two Multi Criteria Decision Analysis (MCDA) methods, the Analytic Hierarchy Process (AHP) and the Non-Structural Fuzzy Decision Support System (NSFDSS), which were applied incorporating uncertainty to generate probabilistic rankings. The NSFDSS technique was applied for the first time to address a fishery problem. Two surveys were carried out among Mediterranean Advisory Council (MEDAC) stakeholders with different backgrounds. By the two surveys we: i) made an AHP test for exploring stakeholders’ perception of the objectives and indicators used in the monitoring of the stocks, ecosystem, and fisheries, and ii) introduced the NSFDSS technique, gathering feedback on stakeholders’ preferences on management options for improving fishery sustainability (e.g., reducing discards, improving ecosystem state and economic yield in the long term). In the AHP the respondents were asked to evaluate the importance of one objective against another according to a scale of semantic scores from 1 to 5, whereas a simpler scoring scale, with only 3 possible options, was used in the NSFDSS. The two MCDA methods were proven to be useful to elicit stakeholders’ view on the potential effects of key issues on economic and environmental fishery sustainability. The results showed stakeholders’ awareness of the fact that the reproductive potential should be secured by checking mortality and/or fishing intensity. Consistently, among the ecological indicators that are tracking the fisheries policy objectives, a higher rank was attributed to “mean size of the spawners,” while cost efficiency was considered to be essential for improving profits. Regarding the economic indicators, stakeholders gave higher priority to “revenue” in comparison to “production (catches),” which is a sign of awareness that increasing fish production does not necessarily turn into increased revenue. Among the different management strategies, “fleet withdrawal” (scraping) was considered as the worst option, while the “combination of measures” was considered to be the best alternative for achieving a sustainable fishery in the long term.

Siting of a central healthcare waste incinerator using GIS-based Multi-Criteria Decision Analysis

Designing and evaluating alternative chemicals, materials, processes, or products using a Safe and Sustainable by Design (SSbD) approach can be facilitated by integrating decision support methods like multicriteria decision analysis (MCDA) to evaluate safety, environmental, economic, and social sustainability criteria. Clear guidance is needed to assess chemical, material, or product life cycles on various criteria, especially when a wide range of options is available, and multiple stakeholders’ interests must be accounted for. This study adds to guidance on the implementation of MCDA in SSbD assessments. Reviewing a set of 18 papers addressing MCDA and safety and sustainability assessments, we discuss various decision-making features (MCDA process characteristics) that require development for the application of MCDA in the SSbD framework. We identify six features for further exploration, including defining the decision-maker and problem statement, justifying the set of alternatives under evaluation, defining whether the system should allow for rank reversal, taking a life cycle perspective and defining the assessment scope, justifying the set of criteria used for the assessment, and managing uncertainties. These issues motivate the call for guidance on defining SSbD-specific issues that influence the selection of a suitable MCDA method for a specific problem, to ensure tailored decision-making recommendations. Addressing the identified features should help clear the path toward methodologically sound studies, useful results, and appropriate decision support. • The novel SSbD concept can be facilitated by MCDA methods. • Guidance on implementing MCDA for complex decision-making in SSbD is needed. • Six decision-making features toward sound decision support need further attention. • Addressing these features will pave the way toward methodologically sound studies.

BACKGROUND: In the context of the progressive movement towards patientcentred care, patient-specific decision support is an important focus of interest. Many diagnostic and treatment patient decision aids (PDAs) are now available to help patients make informed choice decisions. An increasing number of these are software-based, with some available online. Multi-Criteria Decision Analysis (MCDA) is a potentially useful technique on which to base a software-assisted PDA, especially when the decision is complex - as is the case in choosing the best treatment for non-small cell lung cancer – but it has so far been relatively little exploited in this area. The use of any from a number of existing MCDA-based software applications in the development and delivery of a MCDA-based interactive PDA can be an effective way of achieving “best-practice” or normative standards of decision making, such as 1) a well-constructed set of decision criteria or 2) logically consistent patient preferences. However, it also involves the use of resources such as the time and cognitive effort involved in decision-making. The comparative evaluation of alternative MCDA-based software applications in developing and delivering a PDA therefore involves trade-offs between decision effectiveness and decision resource criteria moving from the normative to the prescriptive. MCDA is an ideal tool for this meta-evaluation task as well as for the adoption decision itself. AIM: To analyse, as proof of concept, the use of MCDA for the development, implementation and evaluation of interactive PDAs in routine clinical practice. OBJECTIVES: 1. To assess the use with clinicians in the Spanish NHS of two alternative MCDA software applications which implement dissimilar MCDA techniques in the development of a PDA in routine clinical practice; 2. To assess the use with clinicians in the Spanish NHS of the same two alternative MCDA software applications in the implementation of a PDA in an environment replicating actual clinical consultations; 3. To build a meta-multi-criteria decision model based on the Decision Resources Decision Effectiveness Analysis (DRDEA) framework and assess the use of this model by clinicians in the Spanish NHS to make the choice between the two MCDA applications as the basis for a PDA. METHODS: 1) Two dissimilar MCDA software applications served as a basis for the development of a lung cancer clinical management PDA in close collaboration with two different groups of three clinicians from two different Spanish NHS hospitals (H1 and H2): 1) Expert Choice, which implements the Analytic Hierarchy Process (AHP) MCDA approach; 2) Annalisa in Elicia (ALEL), which implements the Simple Attribute Weighting (SAW) MCDA approach. The process of codevelopment of the PDA in hospitals H1 and H2 was documented; 2) Expert Choice was used to implement (i.e. deliver) the lung cancer clinical management PDA in three hypothetical consultations in hospital H1. In each consultation, one of the three clinicians involved in the development of the tool, with support by this researcher, guided a proxy patient (a non-clinical member of hospital staff) through the PDA. The same process was repeated with the MCDA software ALEL in hospital H2. The process of delivery of the PDA in hospitals H1 and H2 was documented; 3) This researcher built a meta-multi-criteria decision model based on the DRDEA framework to help clinicians choose between different MCDA software applications as the basis of a PDA. The MCDA approach used for this meta-model was Multi- Attribute Value Theory (MAVT). The model was implemented, using the software HiView 3, with three clinicians from hospital H3 for the choice between Expert Choice and ALEL as the basis of a lung cancer clinical management PDA. RESULTS: The thesis makes a three-fold contribution to research in patient-centred decision support. First, it presents two new MCDA software-based approaches to clinical decision support, based on joint work with clinicians in the Spanish NHS, for developing an interactive PDA for the clinical management of non-small cell lung cancer. Second, it describes the use of these decision support tools in the delivery of 5 an interactive PDA for the clinical management of non-small cell lung cancer in a hospital environment via simulated consultations between actual clinicians, with support from this researcher, and proxy lung cancer patients. Third, it presents and applies a new MCDA-based methodology for evaluating the use of alternative MCDA software applications in the development and delivery of interactive PDAs.

Forest fires have a significant impact on human life, property safety, and ecological environment. Deve-loping high-quality forest fire risk maps is beneficial for preventing forest fires, guiding resource allocation for firefighting, assisting in fire suppression efforts, and supporting decision-making. With a multi-criteria decision analysis (MCDA) method based on geographic information systems (GIS) and literature review, we assessed the main factors influencing the occurrences of forest fires in Youxi County, Fujian Province. We analyzed the importance of each fire risk factor using the analytic network process (ANP) and assigned weights, and evaluated the sub-standard weights using fuzzy logic assessment. Using ArcGIS aggregation functions, we generated a forest fire risk map and validated it with satellite fire points. The results showed that the areas classified as level 4 or higher fire risk accounted for a considerable proportion in Youxi County, and that the central and northern regions were at higher risk. The overall fire risk situation in the county was severe. The fuzzy ANP model demonstrated a high accuracy of 85.8%. The introduction of this novel MCDA method could effectively improve the accuracy of forest fire risk mapping at a small scale, providing a basis for early fire warning and the planning and allocation of firefighting resources.

Approximately 3000 papers concerning multi-criteria decision analysis (MCDA) in the environmental field were identified through a series of queries in the Web of Science database and classified by MCDA method and environmental application using text mining in R. Stemming and stop word removal techniques were used to remove irrelevant text from the literature. Trends in MCDA methods (AHP/ANP, TOPSIS, outranking, MAUT/MAVT) associated with specific environmental applications (water, air, energy, natural resources, and waste management) or interventions/tools applications (stakeholders, strategies, sustainability, and GIS) were identified. The results show a linear growth in the share of MCDA papers in environmental science across all application areas. Furthermore, the results show that AHP/ANP and MAUT/MAVT are the most frequently mentioned MCDA methods in the literature. For environmental applications, the results showed that natural resource and waste management keywords were, respectively, the most and least commonly discussed applications within the MCDA papers. For intervention/tool applications, we found that keywords associated with ‘strategy’ and ‘GIS’ applications are, respectively, the most and least commonly discussed keywords within the MCDA papers. The authors found that MCDA method keywords were evenly distributed across the environmental and intervention/tool applications, indicating a lack of preference in the environmental field for use of specific MCDA methods. This paper demonstrates that text mining is an applicable tool to assess specific textual trends and patterns when analyzing larger bodies of MCDA literature.

The main objectives of this article are 2-fold. First, we explore the application of multicriteria decision analysis (MCDA) methods in different areas of health care, particularly the adoption of various MCDA methods across health care decision making problems. Second, we report on the publication trends on the application of MCDA methods in health care. PubMed was searched for literature from 1960 to 2019 in the English language. A wide range of keywords was used to retrieve relevant studies. The literature search was performed in September 2019. Articles were included only if they have reported an MCDA case in health care. The search yielded 8,318 abstracts, of which 158 fulfilled the inclusion criteria and were considered for further analysis. Hybrid methods are the most widely used methods in health care decision making problems. When it comes to single methods, analytic hierarchy process (AHP) is the most widely used method followed by TOPSIS (technique for order preference by similarity to ideal solution), multiattribute utility theory, goal programming, EVIDEM (evidence and value: impact on decision making), evidential reasoning, discrete choice experiment, and so on. Interestingly, the usage of hybrid methods has been high in recent years. AHP is most widely applied in screening and diagnosing and followed by treatment, medical devices, resource allocation, and so on. Furthermore, treatment, screening and diagnosing, medical devices, and drug development and assessment got more attention in the MCDA context. It is indicated that the application of MCDA methods to health care decision making problem is determined by the nature and complexity of the health care problem. However, guidelines and tools exist that assist in the selection of an MCDA method.

Multi-criteria decision analysis to select metrics for design and monitoring of sustainable ecosystem restorations

Mobile Geographic Information Systems (GIS) is an outcome of integrating GIS, wireless communication, embeds and mobile computing technologies. Based on .NET Compact Framework and GPRS a Mobile GIS with own patent is developed. Services in the system include: downloading map by General Packet Radio Service (GPRS), defining geographical coordinate system of maps, Global Position System (GPS) connection and information dynamically showing on map, sharing users' GPS information through SMS (Short Message Service) to establishes communication between system users, vector feature map and related property data editing and shortest route planning. The system is now used in field data collection and simple navigation. This paper introduces the implementation of some basic GIS services in mobile environment. And some implemented services are presented and studied in detail.

This study developed a mobile tour guiding system which uses mobile geographic information system (GIS) techniques to provide spatial and guiding information based on user evaluation. The system comprises four main functions, a graphic function, a global positioning system (GPS) function, a route function and a query function. A user evaluation of the system allows the voicing of different opinions and user perceptions about the system. The user evaluation is carried out by asking participants to complete importance-satisfaction questionnaires after using the system. The results of the evaluation provide valuable data to improve the system to meet user demands. It was also found that most participants would recommend the system to friends and agreed that using the system improved their level of satisfaction. Most users also agreed that the system can help the administration to protect the valuable landscape for which the park is famous. Therefore, the mobile tour guiding system is currently being used for guiding services and continues to be improved according to the user evaluations. Key words: Location-based services, geographic information system, global positioning system, tour guiding system, importance-performance analysis.

This research aims to leverage existing data sources to provide new insights into the usage of Multi-Criteria Decision Analysis (MCDA) in the built environment without creating a new data collection process. The study is focused upon built environment vocations, spanning the disciplines of architecture, construction management, urban planning, real estate, facilities management, and the numerous engineering domains that support capital projects. The method of the study utilized Google search engine data from Google Trends and academic literature metadata from Web of Science, which was analyzed using Bibliometrix via the Biblioshiny interface. These datasets were cross-referenced with original data collected from a Qualtrics delivered industry questionnaire to develop a more comprehensive understanding of MCDA adoption within the built environment. The research presents a ranked list of MCDA methods used within built environment vocations in order of level of adoption, with the top five being PROMETHEE, House of Quality, Monte Carlo Simulations, TOPSIS, and Utility Theory. The results include Biblioshiny visualizations for MCDA methods studied within built environment academic papers and findings related to tool associations via key clusters, such as GIS and drone based data collection tool usage, in concert with MCDA methods. The paper presents evidence that MCDAs are more frequently used in environmental science, geography, management, and sustainability studies within the built environment relative to other design or construction oriented use cases. By integrating diverse data sources—academic publications, search engine trends, and industry responses—the research explores a multi-faceted perspective on the current state of MCDA usage, highlighting the gaps between academic focus, industry practices, and public interest. The research notes that MCDAs are often considered on an individual basis instead of approached broadly as a set of mathematical tools, possibly serving as a barrier to a more expansive understanding of the means and methods practitioners might employ.

Modeling multi-criteria decision analysis in residential PV adoption

Clinical Decision Support Tools

Power requirements are growing day by day, and more power plants are being constructed all over the world. Now the goal has been to look for more sustainable sources of electricity. Sustainability of power plants is a complicated concept and depends on various criteria and sub-criteria. By evaluating them separately creates a complex problem. For this here Multi-Criteria Decision Analysis (MCDA) methods are used for overall assessment and make a sustainability index for seven mostly used power plants. Consideration is taken to both renewable and non-renewable sources. The goal is divided into three basic criteria (i.e. technology, safety & sustainability, economy) and each criterion is further sub-divided into different sub-criteria. The data is collected from various sources and then analyzed using AHP and PROMETHEE methods. The result indicate renewable sources are typically advantageous over non-renewable sources. In certain cases, nuclear has some benefits over other non-renewable energy sources.