Preference Relations Research Articles

A study of entrepreneur and innovative university index by entropy-based grey relational analysis and PROMETHEE

In recent years, the concept of entrepreneurial and innovative universities has gained widespread prominence. Many universities have been paying more attention to being entrepreneurial and innovative by improving their organizational systems, advancing their infrastructure, and increasing financial support. Since numerous criteria with different weights exist, ranking universities based on entrepreneurial and innovative performance can be considered a multi-criteria decision-making (MCDM) problem. This article aims to investigate how different multi-criteria decision-making methods with different criterion weights can affect university rankings and to highlight the reasons that contribute to these differences. In this scope, Grey Relational Analysis (GRA) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) methods were used to rank and compare the universities in Türkiye according to the 2022 Entrepreneur and Innovative University Index (EIUI). In addition to the current weights of each EIUI dimension, entropy-based weights and equal weights were used in MCDM methods. Three ranking approaches with varying weights provided different rankings for universities. The effect of criterion weights was found to be more important in the ranking difference than the method used. The ranks for universities coded U1 and U2 as the most entrepreneurial and innovative universities remained the same. In addition, the performance of each university according to each dimension was evaluated graphically using the GAIA plane to enable them to identify areas for improvement in their rankings.

Order-Fulfillment Coalitions in a Hybrid E-Commerce Platform: Myopic versus Farsighted Stability

This paper considers the order-fulfillment coalitions among an e-tailer and two third-party sellers in a hybrid e-commerce platform. The e-tailer uses a self-supported logistics system to fulfill the orders, and the seller can either use the former or turn to third-party logistics systems. By investigating the equilibrium order quantities, the strong preference relations, and the possible deviations for all the possible coalition structures, we discuss both myopic stability and farsighted stability for all the coalition structures. We find that if economies of scale are absent, fulfilling the orders independently is unique Nash stable and farsightedly stable; however, if alliances generate economies of scale, there may not exist Nash stable, but the farsightedly stable outcome always exists, which further depends on the interaction between the e-tailer’s order-fulfillment cost advantage and economies of scale. Further discussions on extremely high economies of scale and the proportional commission fee are also conducted.

Research outcomes informing the selection of public health interventions and strategies to implement them: A cross-sectional survey of Australian policy-maker and practitioner preferences

BackgroundA key role of public health policy-makers and practitioners is to ensure beneficial interventions are implemented effectively enough to yield improvements in public health. The use of evidence to guide public health decision-making to achieve this is recommended. However, few studies have examined the relative value, as reported by policy-makers and practitioners, of different broad research outcomes (that is, measures of cost, acceptability, and effectiveness). To guide the conduct of research and better inform public health policy and practice, this study aimed at describing the research outcomes that Australian policy-makers and practitioners consider important for their decision-making when selecting: (a) public health interventions; (b) strategies to support their implementation; and (c) to assess the differences in research outcome preferences between policy-makers and practitioners.MethodAn online value-weighting survey was conducted with Australian public health policy-makers and practitioners working in the field of non-communicable disease prevention. Participants were presented with a list of research outcomes and were asked to select up to five they considered most critical to their decision-making. They then allocated 100 points across these – allocating more points to outcomes perceived as more important. Outcome lists were derived from a review and consolidation of evaluation and outcome frameworks in the fields of public health knowledge translation and implementation. We used descriptive statistics to report relative preferences overall and for policy-makers and practitioners separately.ResultsOf the 186 participants; 90 primarily identified as policy-makers and 96 as public health prevention practitioners. Overall, research outcomes of effectiveness, equity, feasibility, and sustainability were identified as the four most important outcomes when considering either interventions or strategies to implement them. Scores were similar for most outcomes between policy-makers and practitioners.ConclusionFor Australian policy-makers and practitioners working in the field of non-communicable disease prevention, outcomes related to effectiveness, equity, feasibility, and sustainability appear particularly important to their decisions about the interventions they select and the strategies they employ to implement them. The findings suggest researchers should seek to meet these information needs and prioritize the inclusion of such outcomes in their research and dissemination activities. The extent to which these outcomes are critical to informing the decision of policy-makers and practitioners working in other jurisdictions or contexts warrants further investigation.

Green, resilient, and inclusive supplier selection using enhanced BWM-TOPSIS with scenario-varying Z-numbers and reversed PageRank

Firms need a reliable decision-making framework to select suppliers who are Green, Resilient, and embrace Inclusive Development (GRID). However, GRID supplier selection is challenged by events that are uncertain and often dependent. Such events affect supplier rankings in a fuzzy decision environment. This paper builds a GRID-based criteria system and applies an enhanced Best Worst Method (BWM) and Technique for Order Preferencing using the Similarity to the Ideal Solution (TOPSIS), with Scenario-Varying Z-numbers (SVZs) and reversed PageRank. The decision criteria are extracted from the literature and confirmed by expert judgement. The SVZs and SVZ Preference Relations (SVZPRs) are developed by combining the Concept of Stratification Theory (CST) with Z-numbers, to reflect the impact of Dependent Uncertain Events (DUEs). Reverse PageRank is then used to find the occurrence probability of the scenarios due to DUEs. BWM is applied in an SVZPR environment to obtain the weights of the decision criteria. TOPSIS, incorporating SVZs, is used to rank the suppliers. An example is used to highlight the enhanced BWM-TOPSIS, to find the priority ranking of the GRID weights. Comparative and sensitivity analyses are conducted to validate the proposed method.

Decision-making for supplier selection problems based on QUALIFLEX technique using likelihood method in LIVIFS environment

The notion of linguistic interval-valued intuitionistic fuzzy set (LIVIFS) is one of the best tools in order to deal with the qualitative decision making problems. Therefore, in this paper a linguistic interval-valued intuitionistic fuzzy (LIVIF) QUALIFLEX method with a likelihood-based comparison approach is proposed. First, the notion of likelihood of fuzzy preference relation (FPRs) to compare the linguistic interval valued intuitionistic fuzzy numbers (LIVIFNs). By employing a criterion-wise preference assessment of alternatives through the comparison of likelihoods, we introduce a novel QUALIFLEX-based model. This model aims to quantify the degree of concordance in the complete preference order for effective management of decisions involving multiple criteria. We demonstrate the practicality and applicability of the proposed methods through an illustrative example, specifically focusing on the context of Supplier Selection Problems. To validate the efficacy of the proposed methodology, a comparative analysis is performed against other existing methods.

Mapping the neural mechanism that distinguishes between holistic thinking and analytic thinking

Holistic and analytic thinking are two distinct modes of thinking used to interpret the world with relative preferences varying across cultures. While most research on these thinking styles has focused on behavioral and cognitive aspects, a few studies have utilized functional magnetic resonance imaging (fMRI) to explore the correlations between brain metrics and self-reported scale scores. Other fMRI studies used single holistic and analytic thinking tasks. As a single task may involve processing in spurious low-level regions, we used two different holistic and analytic thinking tasks, namely the frame-line task and the triad task, to seek convergent brain regions to distinguish holistic and analytic thinking using multivariate pattern analysis (MVPA). Results showed that brain regions fundamental to distinguish holistic and analytic thinking include the bilateral frontal lobes, bilateral parietal lobes, bilateral precentral and postcentral gyrus, bilateral supplementary motor areas, bilateral fusiform, bilateral insula, bilateral angular gyrus, left cuneus, and precuneus, left olfactory cortex, cingulate gyrus, right caudate and putamen. Our study maps brain regions that distinguish between holistic and analytic thinking and provides a new approach to explore the neural representation of cultural constructs. We provide initial evidence connecting culture-related brain regions with language function to explain the origins of cultural differences in cognitive styles.

ALM for insurers with multiple underwriting lines and portfolio constraints: a Lagrangian duality approach

We investigate how an insurance firm can optimally allocate its assets to back up liabilities from multiple non-life business lines. The insurance risks are modeled by a multidimensional jump-diffusion process that accounts for simultaneous claims in different insurance lines with policy limits. We use Lagrangian convex duality techniques to derive optimal investment-underwriting strategies that maximize the expected utility from dividends and final wealth over a finite horizon. We examine how risk aversion, prudence, portfolio constraints, and multivariate insurance risk affect the firm’s earnings retention. We obtain explicit solutions for optimal strategies under constant relative risk aversion preferences. Finally, we illustrate our results with numerical examples and show the impact of co-integration for asset-liability management with multiple sources of insurance risk.

Preferences, risk neutrality and risk-sensitive MDPs

Preferences, risk neutrality and risk-sensitive MDPs

Group decision making with incomplete triangular fuzzy multiplicative preference relations for evaluating third-party reverse logistics providers

The strategic management of reverse logistics (RL) is essential for enterprises to enhance their operational efficiency, customer satisfaction, and sustainability performance in today's competitive marketplace. Many manufacturing firms have to cooperate with professional RL providers to overcome resource constraints and technological limitations, ultimately driving business success. Thus, it is critical for every enterprise to select the most suitable third-party RL provider (3PRLP). This paper provides a novel group decision making (GDM) method with incomplete triangular fuzzy multiplicative preference relations (TFMPRs) to cope with the selection of the most optimal 3PRLP. Firstly, a definition of acceptable incomplete TFMPRs is given. Then, the sufficient and necessary condition of an acceptable incomplete TFMPR is proposed. By analyzing the properties of consistent TFMPRs, a graph-based algorithm is designed to estimate the unknown elements in incomplete TFMPRs. Based on the proposed acceptable consistency definition of TFMPRs, an optimization model is set up to improve the consistency degree of inconsistent TFMPRs. The optimal normalized triangular fuzzy multiplicative weight vector (Tri-MWV) is obtained by computing two analytic expressions and solving a linear programming model. To measure the closeness degree of two TFMPRs, the concept of logarithmic correlation coefficient (LCC) between two TFMPRs is proposed. Combining the incomplete preference information in incomplete TFMPRs with the LCCs of any two TFMPRs, an algorithm of computing experts’ weights is displayed. Subsequently, a novel method of GDM with incomplete TFMPRs is presented. Lastly, a practical example of evaluating 3PRLPs is conducted to illustrate the effectiveness of the proposed GDM method with incomplete TFMPRs.

Algebraic Structures Formalizing the Logic of Quantum Mechanics Incorporating Time Dimension

AbstractAs Classical Propositional Logic finds its algebraic counterpart in Boolean algebras, the logic of Quantum Mechanics, as outlined within G. Birkhoff and J. von Neumann’s approach to Quantum Theory (Birkhoff and von Neumann in Ann Math 37:823–843, 1936) [see also (Husimi in I Proc Phys-Math Soc Japan 19:766–789, 1937)] finds its algebraic alter ego in orthomodular lattices. However, this logic does not incorporate time dimension although it is apparent that the propositions occurring in the logic of Quantum Mechanics are depending on time. The aim of the present paper is to show that tense operators can be introduced in every logic based on a complete lattice, in particular in the logic of quantum mechanics based on a complete orthomodular lattice. If the time set is given together with a preference relation, we introduce tense operators in a purely algebraic way. We derive several important properties of such operators, in particular we show that they form dynamic pairs and, altogether, a dynamic algebra. We investigate connections of these operators with logical connectives conjunction and implication derived from Sasaki projections in an orthomodular lattice. Then we solve the converse problem, namely to find for given time set and given tense operators a time preference relation in order that the resulting time frame induces the given operators. We show that the given operators can be obtained as restrictions of operators induced by a suitable extended time frame.

Effect of Heated Saline Solution on Pain Intensity, Wound Bed Temperature, and Comfort during Chronic Wound Dressing Changes: Crossover Randomized Clinical Trial.

To evaluate the use of heated saline solution during wound cleaning on the intensity of pain related to the procedure, the temperature of the wound bed, and the comfort of patients with chronic wounds. Further, to investigate patient preference in relation to the temperature of the solution used for cleaning. Crossover, single-blind, clinical trial with 32 people with chronic wounds. Providers cleaned the wounds with room temperature and heated saline solution. Participants were randomized into group 1 A/B (heated solution first, room temperature second) or group 2 B/A (room temperature solution first, heated solution second), with a 10-minute washout period. Investigators evaluated pain intensity, wound bed temperature, and patient-reported comfort and preference. The heated solution was preferred (P = .04) and more often referred to as comfortable (P = .04) by the participants. There was no difference in pain intensity before and after cleaning with room temperature (2.03; P = .155) and heated saline (2.25; P = .44). The heated solution increased the temperature of the wound bed by 0.5 °C. Although heating saline solution could be an important comfort measure during dressing changes, quantitatively, the temperature of the solution did not significantly change the temperature of the wound bed nor the intensity of pain patients experienced.

Breaking down barriers to bariatric care: a qualitative study on how telemedicine could transform patient experiences in a Swiss monocentric setting

ObjectiveTelemedicine is becoming an increasingly feasible option for patients with chronic diseases due to its convenience, cost-effectiveness and ease of access. While there are certain limitations, the benefits can be...

Investigating consumer preferences and experiences of telehealth services in Australian allied health practice: a study protocol

IntroductionTelehealth service provision and uptake has rapidly increased since the COVID-19 pandemic, allowing healthcare to be delivered safely and reducing non-essential face-to-face (F2F) contact. In Australia, the expansion of subsidisation...

Survey of the Barriers, Enablers, and Preferences to Swimming for People With Chronic Low Back Pain

Background and Purpose: It is common practice for health professionals to recommend swimming to people with chronic low back pain (CLBP) for rehabilitation and pain management and to improve levels of physical activity. Uptake and engagement in swimming involve a change in behavior, influenced by various factors including barriers, enablers, and preferences. The aim of this study was to identify the most common barriers, enablers, and preferences to swimming for people with CLBP and map them onto the Capability Opportunity Motivation-Behavior (COM-B) model. Methods: People with CLBP were invited to complete a survey collecting data regarding the barriers, enablers, and preferences in relation to swimming. The questions were scored on a 5-point Likert scale and mapped onto the COM-B model. Results: Eighty-two people completed the survey. More than 50% of participants agreed with the following barriers: I am not sure which swimming stroke is best for my back pain and I lack motivation to go swimming. These barriers mapped to the psychological capability and reflective motivation dimensions on the COM-B model. At least 50% of participants agreed with the following enablers: I would like to use swimming to improve my strength, flexibility, weight, fitness, health, mood, and well-being; setting goals and making an action plan could help me swim regularly, I am more likely to go swimming if a health professional advised me and I believe that swimming is good for my back. These enablers were also mapped to the reflective motivation and physical and social opportunity dimensions on the COM-B model. Discussion and Conclusions: The findings from this survey suggest that when recommending swimming, health professionals should discuss the wider health benefits of swimming, discuss specific swimming strokes and why swimming could be beneficial for back pain, and consider using motivational tools to encourage reflective motivation such as goal setting and action planning.

The relationship between working memory capacity, bilingualism, and ambiguous relative clause attachment.

Working memory (WM) capacity has been shown to influence how readers resolve syntactic ambiguities. Building on the work of Swets et al. (2007, Journal of Experimental Psychology: General, 136[1], 64-81), the goal of the present study was to assess the effects of working memory and language proficiency on first language (L1) relative clause attachment decisions across three different language samples: English monolinguals, L1-L2 Spanish-English heritage bilinguals, and L1-L2 Mandarin-English bilinguals. Binomial logistic regression analyses demonstrated that low WM span is associated with a preference to attach ambiguous relative clauses higher in the syntactic structure, as reported by Swets et al. (2007), and contrary to a recency strategy. We also observed that proficiency in L1 and L2 have little effect, suggesting that relative clause attachment preferences primarily reflect the properties of the language and the working memory capacity of the comprehender.

Cooperative Games for Group Decision Making Under Undirected Collaboration Network With Hesitant Fuzzy Preference Relations

Cooperative Games for Group Decision Making Under Undirected Collaboration Network With Hesitant Fuzzy Preference Relations

Forecasting the probability of successful deployment of internet of things and cloud computing in the building sector through consistent fuzzy preference relations method

Purpose This study aims to identify significant factors, analyse them using the consistent fuzzy preference relations (CFPR) method and forecast the probability of successful deployment of the internet of things (IoT) and cloud computing (CC) in Gujarat, India’s building sector. Design/methodology/approach From the previous studies, 25 significant factors were identified, and a questionnaire survey with personal interviews obtained 120 responses from building experts in Gujarat, India. The questionnaire survey data’s validity, reliability and descriptive statistics were also assessed. Building experts’ opinions are inputted into the CFPR method, and priority weights and ratings for probable outcomes are obtained to forecast success and failure. Findings The findings demonstrate that the most important factors are affordable system and ease of use and battery life and size of sensors, whereas less important ones include poor collaboration between IoT and cloud developer community and building sector and suitable location. The forecasting values demonstrate that the factor suitable location has a high probability of success; however, factors such as loss of jobs and data governance have a high probability of failure. Based on the forecasted values, the probability of success (0.6420) is almost twice that of failure (0.3580). It shows that deploying IoT and CC in the building sector of Gujarat, India, is very much feasible. Originality/value Previous studies analysed IoT and CC factors using different multi-criteria decision-making (MCDM) methods to merely prioritise ranking in the building sector, but forecasting success/failure makes this study unique. This research is generally applicable, and its findings may be utilised for decision-making and deployment of IoT and CC in the building sector anywhere globally.

Aggregation of I-transitive fuzzy relations and fuzzy preference relations

Aggregation of I-transitive fuzzy relations and fuzzy preference relations

No‐choice oviposition preferences predict neighborhood effects among host plants in a model system

Abstract Neighbouring plant species can indirectly affect each other's fitness through insect herbivores. For instance, the number of eggs an insect deposits on a focal plant can be influenced by the presence of a neighbouring plant species because of the herbivore's relative host plant preferences. Yet, the relationship between oviposition preferences (measured in no‐choice tests) and the strength and direction of such indirect effects among neighbouring plants remains poorly understood. We performed a lab experiment using bean beetles (Callosobruchus maculatus) and five species of beans to determine if beetles' no‐choice preferences for a neighbouring bean species correlated with the number of eggs laid on a focal species in two‐species environments (diculture). We predicted that as the preference for the neighbouring beans increased compared to the focal host, beetles would lay fewer eggs on the focal bean host. Across all pair‐wise combinations, our prediction was supported: as the relative no‐choice preference of neighbouring beans increased, the number of eggs laid on focal beans decreased. However, this relationship was relatively weak. We also found that beetles tended to lay more eggs in diculture compared to arenas with one bean species. These results provide empirical evidence linking herbivores' no‐choice preferences to the strength of neighbourhood effects and suggest that even within a relatively controlled environment, neighbourhood effects can be weak. Our results also highlight that unexpected changes to the total number of eggs laid by herbivores in mixed‐plant patches relative to monoculture can complicate predictions.

A two-stage consensus model based on personalized individual semantics under linguistic preference relations with self-confidence

Linguistic preference relations with self-confidence (LPRs-SC) are the preference relation that can reflect the decision maker’s (DM) confidence psychology and has received widespread attention for their simple form and multiple information. Currently, arithmetic studies of LPRs-SC are conducted separately for preference relations and self-confidence. In addition, personalized individual semantics (PIS) is an important tool in large-scale decision-making to reflect the differences in the semantic understanding of DMs. However, the confidence level in LPRs-SC limits the preference relation to a certain extent and the linguistic representations of these two components are usually different. This means that it is not only necessary to propose an arithmetic rule that can express the restrictive relationship between the two but also to construct a model that can extract the PIS of preference relation and confidence respectively. Besides, we constructed a two-stage consensus reaching process (CRP) based on the specificity of the LPRs-SC structure when enhancing group harmony. The process takes self-confidence as an independent source of information, delineates the adjusted categories in detail, and builds an adjustment model accordingly. Finally, the example and comparative analyses verify the merits of the proposed PIS in terms of consistency enhancement and CRP in terms of speed and accuracy harmonization.