Judgments Of Decision Makers Research Articles

Applications of artificial intelligence in anesthesia: A systematic review.

This review article examines the utility of artificial intelligence (AI) in anesthesia, with a focus on recent developments and future directions in the field. A total of 19,300 articles were available on the given topic after searching in the above mentioned databases, and after choosing the custom range of years from 2015 to 2023 as an inclusion component, only 12,100 remained. 5,720 articles remained after eliminating non-full text. Eighteen papers were identified to meet the inclusion criteria for the review after applying the inclusion and exclusion criteria. The applications of AI in anesthesia after studying the articles were in favor of the use of AI as it enhanced or equaled human judgment in drug dose decision and reduced mortality by early detection. Two studies tried to formulate prediction models, current techniques, and limitations of AI; ten studies are mainly focused on pain and complications such as hypotension, with a P value of <0.05; three studies tried to formulate patient outcomes with the help of AI; and three studies are mainly focusing on how drug dose delivery is calculated (median: 1.1% ± 0.5) safely and given to the patients with applications of AI. In conclusion, the use of AI in anesthesia has the potential to revolutionize the field and improve patient outcomes. AI algorithms can accurately predict patient outcomes and anesthesia dosing, as well as monitor patients during surgery in real time. These technologies can help anesthesiologists make more informed decisions, increase efficiency, and reduce costs. However, the implementation of AI in anesthesia also presents challenges, such as the need to address issues of bias and privacy. As the field continues to evolve, it will be important to carefully consider the ethical implications of AI in anesthesia and ensure that these technologies are used in a responsible and transparent manner.

Comprehensive Performance Evaluation of an Unmanned Excavator Based on Signal Stability Extraction

The comprehensive performance of unmanned excavators is crucial for the development and optimization of the field of construction machinery. To effectively improve the unmanned excavator to meet the needs of the market, it is imperative to quantify the evaluation method of the comprehensive performance of unmanned excavators. In this study, an evaluation method combining a fuzzy analytic hierarchy process and multivariate image area analysis method is proposed. Firstly, based on the feature extraction of the signal stability of the unmanned excavators, fifteen evaluation indexes were proposed. Then, the case study is used to obtain the scores corresponding to these indexes. The fuzzy analytic hierarchy process is applied to determine the relative weight of the selected evaluation criteria, in which the uncertain and imprecise judgments of decision makers are converted into fuzzy numbers. At the same time, the braking performance of the three types of unmanned excavators was comprehensively evaluated and ranked using the multivariate image area analysis method as an empirical example. Finally, a weight analysis is performed to check the robustness of the ranking results. The results show that the proposed method is effective and feasible. It provides a reference for the performance improvement and efficiency optimization of unmanned excavators.

A Pathophysiological Approach for Selecting Medications to Treat Nociceptive and Neuropathic Pain in Servicemembers.

The prevalence of chronic pain of service members (SMs) in the U.S. is estimated to be higher (roughly 31-44%) compared to that of civilian population (26%). This higher prevalence is likely due to the high physical demands related combat and training injuries that are not immediately resolved and worsen over time. Mental Health America reports that chronic pain can lead to other mental health conditions such as severe anxiety, depression, bipolar disorder, and post-traumatic stress disorder. Such mental health conditions can negatively affect job performance, reduce readiness for military duties, and often lead to patterns of misuse of opioid after SMs entering civilian life. The primary objective of this narrative review is to present a summarized guideline for the treatment of two types of pain that likely affect SMs, namely nociceptive somatic pain and neuropathic pain. This review focused on a stepwise approach starting with nonopioid interventions prior to opioid therapy. The secondary objective of this review is to elucidate the primary mechanisms of action and pathways associated with these two types of pain. We followed the Scale for Assessment of Narrative Review Articles when transcribing this narrative review article to enhance the quality and brevity of this review. This Scale has 0.77% an intra-class coefficient of correlation, 95% confidence interval and 0.88 inter-rater reliability. We searched PubMed, Google Scholar, WorldCAT, and the Cochrane Library for the primary and secondary articles that targeted mechanisms of action, pathways, and pharmacological modalities for nociceptive somatic and neuropathic pain that were published from 2011 to 2022. We excluded articles related to pediatric, some specific pain conditions such as cancer-related pain, palliative care, end-of-life care, and articles that were not written in English language. For pharmacologic selection, we adopted the guidelines from the Policy for Implementation of a Comprehensive Policy on Pain Management by the Military Health Care system for the Fiscal Year 2021; the Clinical Practice Guidance for Opioid Therapy for Chronic Pain by the Department of Defense/Veterans Health Administration (2022); the (2021) Implementation of a Comprehensive Policy on Pain Management by the Military Health Care System; and the (2022) Guideline for Prescribing Opioids for Chronic Painby the Centers for Disease Control. From the knowledge of the mechanisms of action and pathways, we can be more likely to identify the causative origins of pain. As a result, we can correctly diagnose the type of pain, properly develop an efficient and personalized treatment plan, minimize adverse effects, and optimize clinical outcomes. The guideline, however, does not serve as a substitute for clinical judgment in patient-centered decision-making. Medication choices should be individualized judiciously based on the patient's comorbid conditions, available social and economic resources, and the patient's preferences to balance the benefits and risks associated with various pain medications and to achieve optimal pain relief and improve the patient's quality of life.

An integrated GBWM-PROMETHEE-CLOUD & MCGP model for green supplier selection and order allocation (GSSOA) in an oil refinery

With the increase of environmental concerns in recent years and the prevalence of such issues, which originate mainly from large industries and manufacturing plants, green supply chain management (GSCM) issues have been given special attention among researchers. GSCM is a group of management applications integrating supply chain management with criteria related to environment and supplier selection with the purpose of reducing environmental pollution caused by processes involved in a company supply chain. In this research the main contributions is to draw a decision-making structure addressing the applicability of the green supplier selection (GSS) and order allocation (OA) problem in an Iranian Oil refinery company. A combination of Cloud-PROMETHEE along with using GBWM was taken into account for GSS as the first phase and MCGP method for OA as the second phase, in order to solve the GSSOA problem. The proposed technique lets the vagueness and uncertainty of experts' judgments be obtained by assisting uncertain linguistic variable derived from the cloud model. Furthermore, the group best-worst method (GBWM) obtains the optimal criteria weights by forming a nonlinear programing model and the prioritizing of nominated suppliers is established using the PROMETHEE method with the possibility to pick a distinct preference function for each criterion and draw a graph of supplier preferences. At last, MCGP method was applied considering with the possibility of multi-choice aspiration levels (MCAL) for each goal. The suggested model illustrated with actual figures in an oil refinery to provide insight to decision-makers of green supplier selection and order allocation. To do so, initially nine criteria have been derived after vast research on literature and experts’ opinions. Then the suppliers was successfully evaluated with considering uncertainties and randomness in a group of decision maker judgments. The order allocation was also completed by minimizing total cost and delays and maximizing purchase using results of supplier ranking in the first phase. Results have shown that the supplier with better ranking in GSS is preferred in allocating orders. A sensitivity analysis then performed and confirmed that the suggested method is highly stable against different changes in the data. The proposed method was also compared with the basic MCGDM cloud model and the method is approved. Finally, managerial implications and conclusions for additional researches are demonstrated.

English

Customer profiling tools have been introduced in recent years to protect investors against the increasing complexity of financial instruments. Advisor experts have to combine measures of finance and behavioural finance studies in their evaluation. The need to integrate different competences and compare complex criteria naturally leads to the modelling of the portfolio selection problem as a group decision problem. The Analytic Network Process (ANP) is a useful technique that helps decision-makers evaluate the available alternatives and aggregate their professional knowledge. In this context, the Reaching Consensus Process (RCP) is crucial for the validity of choices due to the strong sensitivity of the ANP to the decision maker's judgement. However, the RCP may be affected by the behavioural characteristics of experts, the vulnerability of judgements and the uncertainty that characterises the decision-making context, leading to unbiased judgements that are not based on different expertise. Similarly, without the involvement of more experts, the process could be inefficient due to the sensitivity of the ANP decision-maker’s judgement. In order to maximise the aggregation of experts' knowledge, to minimise the influence of the individual in quantifying the relationships between criteria and alternatives, and to preserve the impartiality of evaluations, the present paper discusses RCP through Choquet’s discrete integral. This aggregation captures the non-linearity of preferences and includes the fuzziness of judgments. Thus, there is no need to reach a consensus when evaluating the criteria: each expert manages a single ANP whose synthesis are aggregated using Choquet’s discrete integral. In this sense, the aggregation defines an unbiased consensus which mitigates the sensitivity of the ANP to the preferences of the decision-maker. The methodology is applied to a case study in which several experts evaluate investment alternatives of an individual, simultaneously incorporating behavioural criteria and Markets in Financial Instruments Directive (MiFID) client profiling criteria.

Focusing on structural changes and future risks of ecosystems: An opportunity-cost based ecosystem service account for riparian ecosystems and its case study

The riparian is a buffer zone between the river and human society, and improper land development will increase the ecological vulnerability of the river basin. Different evaluation methods for the ecological impact of development behavior will produce different value perception results, which in turn will affect the judgment and choice of decision-makers and the public. Based on the construction of an opportunity-cost-based monetary valuation method in the SEEA-EA (System of Environmental Economic Accounting-Ecosystem Accounting), this study took the riparian under the influence of the Xiaolangdi Project of the Yellow River from 1990 to 2020 as the research object, and evaluated the impact of land development decisions on ecosystem services under the superimposed influence of major projects, policies and socio-economic changes. The results show that: (1) The inclusion of opportunity costs can reduce the distortion of ecological value caused by economic factors and supply–demand state. In the case study, the opportunity cost of each 5-year accounting period in 30 years reduced the total accounting value respectively by 196.76, 25.88, 80.57, 84.33, 27.96, and 577.48 million yuan. (2) Opportunity cost can effectively reflect the ecological profit and loss caused by land transformation between different ecosystem types caused by decision-making in different periods. From 2015 to 2020, the opportunity cost of ecosystems was high when the total ecological land in the riparian increased, which reflected the drastic changes in land use during the decision-making period. (3) Opportunity costs are included in the monetary account as part of the “stock reduction”, which directly reflects the risk of ecological land reduction and structural change caused by development behavior. This mixed account of physical and monetary stocks can reflect both physical changes in ecosystem services and ecological risks, thereby improving stakeholders’ scientific understanding of the fluctuations in the value of ecosystem services caused by riparian land use.

ARTIFICIAL INTELLIGENCE IN THE INDIAN JUDICIARY: A SYSTEMATIC ANALYSIS OF POTENTIAL APPLICATIONS AND CHALLENGES IN ADDRESSING CASE BACKLOGS

This paper examines the potential role of artificial intelligence (AI) in addressing the critical issue of case backlogs plaguing the Indian judiciary. With over 40 million pending cases, Indian courts face a crisis of delayed justice that undermines the rule of law and public trust in the legal system. This research analyzes how AI technologies could be leveraged to streamline court processes, enhance judicial productivity, and ultimately reduce case pendency. Drawing on examples of AI implementation in judiciaries worldwide, the paper explores applications in case management, legal research, document review, and decision support. While acknowledging the transformative potential of AI, the analysis also grapples with significant challenges around data quality, algorithmic bias, privacy concerns, and the need to preserve human judgment in judicial decision-making. The paper argues that a carefully implemented AI strategy, combined with institutional reforms, could significantly improve efficiency in the Indian courts. However, any technological solutions must be tailored to the unique context of the Indian legal system and subject to appropriate governance frameworks. The research concludes with recommendations for a phased adoption of AI in the judiciary, emphasizing the need for further empirical study on the impacts of AI on judicial processes and outcomes.

New model of sports tourism with sustainable tourism development to increase tourist arrivals in Central Aceh Regency, Indonesia.

This study explores the development and implementation of a new sports tourism product called "Run H2O Ride" as a strategy for sustainable tourism in Indonesia. The research employs a research and development (R&D) methodology, focusing on identifying potential issues, conducting literature reviews, designing the product, validating the design, and undergoing product development. A combination of discussion group forums (FGD) and expert judgment decisions was used to design the new sport tourism model. The effectiveness of the model was assessed through limited product tests, main product tests, and operational product tests involving respondents from the local community and tourists. The results indicate that the "Run H2O Ride" model has been well-received, with positive feedback on its suitability and effectiveness in attracting tourists and enhancing the local economy. The study concludes by recommending further research to refine the model and emphasizes the importance of local government support and community participation in sustainable tourism development. Theoretical implications highlight the significance of sports tourism events in promoting tourism, while practical implications suggest alternative solutions for increasing tourist visits and improving destination image. Policy recommendations for local governments are proposed to adopt and implement sports tourism events, aligning with long-term development plans for regional tourism growth.

Self-truncated sampling produces more moderate covariation judgment and related decision than descriptive frequency information: The role of regressive frequency estimation.

Covariation judgment underlies a diversity of psychological theories and influences various everyday decisions. Information about covariation can be learned from either a summary description of frequencies (i.e., contingency tables) or trial-by-trial experience (i.e., sampling individual instances). Two studies were conducted to investigate the impact of information learning mode (i.e., description vs. self-truncated sampling) on covariation judgment and related decision. In each trial under the description condition, participants were presented with a contingency table with explicit cell frequencies, whereas in each trial under the self-truncated sampling condition, participants were allowed to determine when to stop sampling instances and thus the actual sample size. To eliminate sampling error, an other-yoked (i.e., between-subject) design was used in this research so that cell frequencies shown in a trial under the description condition were matched with those experienced in a trial under the self-truncated sampling condition. Experiment 1 showed that the self-truncated sampling condition led to more moderate covariation judgments than the description condition (i.e., a description-experience gap). Experiment 2 demonstrated further that the same gap extended to covariation-related decisions in terms of relative contingent preference (RCP). Regressive frequency estimation under self-truncated sampling appeared to underlie the consistent gaps found in the two studies, whereas the impact of regressive diagnosticity (i.e., the same sample of instances was viewed as less diagnostic under description than under self-truncated sampling) or simultaneous overestimation and underweighting of rare instances under experience was not supported by the observed data. Future research might examine alternative accounts of the observed gaps, such as the impacts of belief updating and stopping rule under self-truncated sampling.

Website quality and user satisfaction: A higher education perspective

&lt;p&gt;At the forefront of this digital revolution stands the omnipresent website, a virtual gateway that transcends geographical boundaries, providing us unparalleled access to information and services from anywhere on the globe. In this increasingly interconnected world, websites have become the digital storefronts and first impressions of entities, be they businesses, organizations, or individuals. Consequently, people often make swift and decisive judgments about an agency based solely on its online presence's user experience and interface design. Given how quickly the internet is developing, the online quality of an academic university website is essential to student satisfaction. This study explores the intricate relationship between student satisfaction and academic university website quality (usability quality, information quality, service interaction quality, and user satisfaction). It provides a detailed analysis of the student experience. We use multiple regression with a sample size of 104 student respondents. This study uses factual data and student input to analyze significant areas of academic university websites. The results show that user satisfaction with website quality is positively significant to user satisfaction. Repetitive interactions are more common on websites that excel in usability, accessibility, and responsiveness. We hope this research can help developers to improve academic university websites.&lt;/p&gt;

Technology Acceptance Model of ATM Machine Services: A Case Study of MyGraPARI within Analytical Hierarchy Process

Determining the priority level of acceptance of the MyGraPARI ATM machine service technology at Jam Gadang Bukit Tinggi is crucial for enhancing user satisfaction and streamlining financial transactions. The implementation of the Analytic Hierarchy Process (AHP) framework can effectively identify and prioritize factors that influence user acceptance and satisfaction. AHP systematically decomposes the decision-making process into a hierarchical structure, enabling the evaluation of various criteria based on their relative importance. AHP quantifies the subjective judgments of decision-makers, resulting in a comprehensive understanding of the factors that drive user acceptance and satisfaction. This predictive capability enables decision-makers to select the most effective strategies, optimizing the overall user experience and maximizing the adoption of MyGraPARI ATM machines at Jam Gadang Bukit Tinggi. In conclusion, the application of the AHP method is highly relevant and beneficial for overcoming existing challenges and enhancing the value proposition of MyGraPARI ATM machines. By prioritizing critical factors, implementing targeted strategies, and evaluating the impact of improvement efforts, AHP empowers decision-makers to optimize user acceptance and satisfaction, leading to a more successful and impactful MyGraPARI ATM service at Jam Gadang Bukit Tinggi.

The right to translation in the criminal procedure and the meaning of essential documents – three recent cases of the European Court of Justice in the field of criminal cooperation between Member States

The case note concerns three preliminary rulings of the European Court of Justice (hereinafter referred to as ECJ). Case C-242/22 PPU TL, C-338/20 Prokuratura Rejonowa Łódź-Bałuty and case C-278/16 Sleutjes each concerned the right to translation in the criminal procedure and legal remedies in the event of not providing that right. Thus, the basis of adjudication of the cases was Directive 2010/64/EU of the European Parliament and of the Council on the right to interpretation translation and in the criminal proceedings. The case note sheds light on the deficiencies of the Directive which are the consequences of the legislative technique applied in this legislative instrument, namely that Member States retain great discretion in implementing its often-vague regulations on the right to translation. However, through the preliminary ruling procedure, the ECJ clarified the meaning of the essential document which is subject to translation according to the Directive, found that a final decision shall be considered a judgement even if formally it is not, and finally, it set out the essential parts of a judgement or other decision that are subject to translation for the purpose of safeguarding the right to a fair trial.

Integrated AHP & TOPSIS methodology using intuitionistic Z-numbers: An application on hydrogen storage technology selection

The reliability of decision makers' judgments together with their degree of hesitancy are often ignored in decision models. The inclusion of judgments with only triangular belonging functions causes a great deal of information loss since non-belongingness functions are ignored in those decision models. In the literature, a method on how to integrate the intuitionistic reliability function into the decision maker's judgment has not been clearly proposed. To handle these issues, we aim at developing a novel intuitionistic Z-AHP (Analytic Hierarchy Process) & Z-TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions) methodology in this paper. Z-numbers can be used to express uncertain quantities with different degrees of precision, which can be very useful in practical applications. Our methodology considers both the restriction function and its reliability function under intuitionistic fuzziness based on α-cut approach and uses non-linear intuitionistic belonging and unbelonging functions. We compare our approach with interval-valued fuzzy TOPSIS and conduct a sensitivity analysis to assess the effects of changes in criteria weights on the rankings of the alternatives. Our results show that the proposed methodology can effectively evaluate and rank the existing alternatives, considering the uncertainties and complexities of the decision environment. This research provides valuable insights for decision-makers and can take part in their decision support systems. The proposed methodology has been applied to a hydrogen storage technology selection problem. According to the results, the most favorable hydrogen storage option in the considered case is chemical storage alternative followed by liquid storage, compressed storage, carbon nanostructure storage, and metal–organic framework storage alternatives. The inference of the comparative analysis with intuitionistic Z-AHP and interval-valued fuzzy TOPSIS method is that the best two alternatives are same in both methodologies whereas the third and the fifth alternatives are replaced since a different linearization approach is applied to the non-linear restriction function multiplied by the reliability function.

43 Evaluating the Relationship Between Social Support, Executive Function, and Communicative Effectiveness

Objective:Research suggests greater perceived social support is associated with better general cognitive function in community-dwelling older adults. While these findings expand our understanding of the role of social support in healthy aging, further work is needed to investigate the role of social support in mild cognitive impairment (MCI). Of particular interest is the relationship between executive function (EF), communicative effectiveness, and social support, as these are common areas of decline and are likely to impact one’s ability to meaningfully interact with others. The present study aimed to evaluate the association between perceived social support, EF, and communicative effectiveness. We hypothesize better EF performance and communicative effectiveness would be associated with higher levels of perceived social support in older adults with MCI.Participants and Methods:One hundred and twenty-one older adults with MCI were included in the current study. All participants were enrolled in Charles and Harriett Schaffer Cognitive Empowerment Program (CEP) at Emory University, a comprehensive lifestyle program for individuals diagnosed with MCI and their care partners. Upon CEP enrollment, participants completed self-report questionnaires, including the Multidimensional Scale of Perceived Social Support (MSPSS), the Communicative Effectiveness Index (CETI), and EF assessments including Letter Fluency (phonemic fluency), Digit Span Backward (working memory), and the Test of Practical Judgment (decision making). Additionally, a subset of participants completed the written Trail Making Test - Part B (set-shifting; n = 63). Pearson bivariate correlations were utilized to explore the relationship between MSPSS, CETI, and EF performance.Results:Higher levels of perceived social support were significantly associated with communicative effectiveness (r = .210, p = .021), such that participants who endorsed having more social support also reported greater confidence in their communicative effectiveness. Perceived social support was associated with better working memory performance (r = .342, p &lt; .001), phonemic fluency output (r = .261, p = .041), and shorter time to complete TMT-B (r = -.244, p = .052), indicating individuals with higher perceived social support demonstrated better EF abilities. Finally, greater confidence in communicative effectiveness was associated with better performances in working memory (r = .274; p = .008), phonemic fluency output (r = .213; p = .020) and decision making (r =.192; p = .044), suggesting stronger working memory, phonemic fluency, and practical decision-making abilities support better communicative effectiveness. There was no association between social support and practical decision-making abilities (r = .146, p = .129).Conclusions:The current findings demonstrate a link between higher levels of social support, communicative effectiveness, and EF abilities, particularly in the subdomains of working memory, phonemic fluency, and set-shifting. This link suggests individuals with stronger EF abilities may have greater communicative effectiveness and, in turn, may be better able to maintain social relationships and garner social support. Future research is needed to evaluate the causality in this relationship, as it remains possible those with stronger social support networks maintain communicative effectiveness and EF for longer. Thus, further evaluation of the mechanism(s) underlying the relationships between social support, EF, and communicative effectiveness is needed.

Unpacking the impacts of programmatic approach to assessment system in a medical programme using critical realist perspectives

ABSTRACT Traditional, positivist assessment approaches generally fail to capture the nuances of learners’ clinical competence in medical programmes. This has led to the implementation of an alternate assessment approach known as ‘programmatic assessment’, which embraces subjectivity of human judgement in holistic decision making in clinical settings. Faculty and staff have found the introduction of programmatic assessment to be challenging because it is a major, complex change to the traditional way of carrying out assessment. Extending our previous work, where we used critical realism to explore students’ experiences of programmatic assessment, we here unpack the underlying conditions and mechanisms triggered by programmatic assessment’s implementation. We applied Bhaskar’s concept of ontological stratification, retroduction and Archer’s theoretical accounts of morphogenesis/stasis to theorize the interplay between the socio-cultural entities that constrain and enable desired changes in assessment practices, and those that condition students and staff to accept or reject the new ‘non-traditional’ assessment processes.

As Good as New: Embarrassment and Consumers’ Preference for Used versus New Products

The condition of a product (i.e., being used or new) plays an important role in consumer judgment and purchase decisions, yet this phenomenon has been relatively under-researched. Using an experimental approach, this study investigates the effect of embarrassment on choice of used and new products. We demonstrate that due to the embarrassment associated with buying used products, Chinese consumers are more likely than their US counterparts to choose new products over used ones. Furthermore, we find that this difference can be attenuated by reframing used products positively as antiques. Our findings enrich the theoretical understanding of consumer behavior across cultures, offer important managerial implications, and provide novel insights into future research directions.

Ontology of guided development of scientific abilities of young people. Part 1: basic concepts and models

The article attempts to analyze new trends in work with gifted youth as a new form of systemic, organizational and scientifically oriented independent activity of a motivated schoolchild or student. This activity, firstly, is aimed at satisfying the cognitive, intellectual, as well as other needs of the student and the effective development of their creative potential; secondly, it is associated with the consistent solution of research problems with not foreknown results, increasing novelty, relevance and complexity; thirdly, it is supported by a specially organized unified developing scientific and educational environment within the framework of its educational organization, region, industry, country; and finally, it involves a scientifically based unified assessment of both the developing effect and the scientific significance of the current results of this activity . The article discusses the basic concepts characterizing this activity and illustrating their examples and mathematical models. These include the author's structuring of the functions and levels of research activity, a multifaceted system of criteria for evaluating the scientific and developmental results of research work performed by young researchers, a functional profile, a functional rating and a professional functional rating of a young researcher, calculated based on the assessment results of their research work. For the first time, a mathematical model for the formation of acceptable options for research activities is proposed, which allows forming the optimal developing methodological structure of planned research. One of the unique points of the proposed approach is the widespread use of ordinal rating scales with the transformation of the results of their application into quantitative estimates based on the method of confident judgments of decision makers. The introduced concepts are formed into a graphical scheme of the ontology of guided development of scientific abilities of young people.

On using pairwise comparison in the analytic hierarchy process: Validity is goal while consistency is means

To improve the quality of decision-making, the judgments of experts should be properly elicited. Pairwise Comparison (PC), kernel of the Analytic Hierarchy Process (AHP), is a prevalent method to manifest human judgments in Multiple Criteria Decision Making (MCDM). This study proposes a pragmatic guideline for using the PC matrix in the AHP to help decision makers (DMs) improve their decisions. First, extensive computer simulations indicate that, without strong evidence of linear relationship between an inconsistency index of a PC matrix and validity of priority vector derived from that matrix, it is questionable to set a threshold for this index to determine whether a PC matrix acceptable. Second, to resolve this problem, we propose a scale-validity (SV) index as an effective proxy for evaluating the validity of derived priority vector. Third, by integrating two paradigms (deterministic vs. statistical), we suggest a pragmatic guideline for DMs who have different epistemological views of inconsistency in order to improve their decision when using the AHP. To demonstrate the effectiveness and superiority of the proposed method, four examples of comparative analysis are illustrated. Finally, we summarize the results, contributions, and suggestions.

IMPLEMENTATION OF PROFILE MATCHING METHOD IN DECISION SUPPORT SYSTEM SMARTPHONE SELECTION BASED ON CONSUMER NEEDS

Smartphones are Internet-enabled phones and typically provide Personal Digital Assistant (PDA) functions such as calendar functions, to-do books, address books, calculators, and notes. At first, the smartphone is a rare item and considered luxurious. However, the lack of community information about smartphone specs also greatly affects the selection of smartphones they will use. Smartphones have a variety of specifications such as processor speed, clear screen, battery life, camera strength, and storage space that makes people tend to be confused in buying a smartphone. For that people need a computerized system that can assist consumers in obtaining a decision to choose a smartphone that suits the wants and needs. Decision Support System (SPK) is a process of selecting alternative actions to achieve a specific goal or goal. SPK is used as a tool for decision-makers to develop decision-making capabilities, but not to replace judgments of decision makers. This SPK test uses Profile Matching Method by looking at the calculation of Criteria Weight Value, Calculation of Sub-Criteria Weight Value, Gap Value calculation, Core Factor and Secondary Factor calculation, and Total Value Ranking Calculation. The end result of this system is ranking the existing smartphone according to the criteria that the buyer has input.

Comprehensive Evaluation of Hydrodynamic Retarders with Fuzzy Analytic Hierarchy Process and Improved Radar Chart

The braking performance of hydrodynamic retarders is critical for the safety and economy of heavy-duty vehicles. In order to effectively improve the braking system to meet the needs of the market, an evaluation method for quantifying the performance of hydrodynamic retarders is imperative. In this paper, ten evaluation criteria are put forward according to relevant national standards and market requirements, then the scores corresponding to these criteria are obtained by performance bench test. A fuzzy modification of the analytic hierarchy process (AHP) method is applied to determine the relative weights of the chosen evaluation criteria, where uncertain and imprecise judgments of decision-makers are translated into fuzzy numbers. Furthermore, the improved radar chart method is used to comprehensively evaluate and rank the braking performance of three types of hydrodynamic retarders as an empirical example. In addition, the weight sensitivity analysis is conducted to examine the robustness of the ranking results. The results show that the proposed method is effective and feasible. It provides a reference for multi-objective optimization control strategies and structure designs of hydrodynamic retarders.