Decision Maker's Preferences Research Articles

The influence of externality in the graph model for conflict resolution under fuzzy preferences

The Graph Model for Conflict Resolution (GMCR) is a flexible and comprehensive methodology for systematically investigating strategic conflicts. However, most existing studies solely focus on internal conflicts among decision makers (DMs), often disregarding the influence of external stakeholders (ESs) on DMs’ preferences. Consequently, this leads to insufficient stability in equilibrium outcomes. The objective of this study is to address the conflict issue faced by DMs with subjective uncertain preferences who are influenced by externality. Building upon the framework of GMCR, this study proposes the graph model for conflict resolution with fuzzy preference based on externality (FEGMCR) which introduces fuzzy numbers to measure both uncertain preferences of DMs and uncertain expectations of ESs. Furthermore, four forms of stability are extended-- Fuzzy Nash Stability based on externality (FER), Fuzzy General Metarationality based on externality (FEGMR), Fuzzy Symmetric Metarationality based on externality (FESMR), and Fuzzy Sequential Stability based on externality (FESEQ). The optimal equilibrium is achieved by dynamically adjusting the weight of the impact of externalities. Finally, the method is applied to the case of plastic ban in Hainan. It is found that the expectations of ESs do change the preferences of DMs and affect the final equilibrium, which provides a sustainable solution for the issue.

Assessment of Iranian airlines using network cross-efficiency DEA and the regret theory

Network Data Envelopment Analysis (NDEA) has been extensively applied to evaluate the air transportation sector. NDEA provides a tool for evaluating the internal processes of Decision-Making Units (DMUs). Optimistic Network Cross-Efficiency (ONCE) has recently been extended to the basic two-stage system. However, there are still two main shortcomings that need to be addressed. First, the ONCE evaluates DMUs based only on the optimistic viewpoint, neglecting the pessimistic viewpoint. The optimistic viewpoint assumes that there is only one set of reference points, which includes the best practice DMUs. The first contribution of this study is to develop a new Pessimistic Network Cross-Efficiency (PNCE) method. This method is based on a new set of reference points, which includes the worst-performing DMUs. The PNCE is developed as an extension of the ONCE. Second, both the ONCE and newly developed PNCE methods may lead to unrealistic results because they neglect the subjective preferences of Decision Makers (DMs). These NDEA models employ the Arithmetic Mean (AM) as the cross-evaluation aggregation method, which not only underestimates the importance of self-evaluation but also overestimates the importance of peer evaluations. Consequently, ONCE and PNCE may lead to biased efficiency results. To address this drawback, the second contribution of this study is to develop a new Aggregation method based on the Regret theory and Consensus (ARC). This method aims to reflect the psychological preferences of DMs when estimating cross-evaluation weights. To achieve this goal, we obtained new optimistic and pessimistic efficiencies by utilizing the newly developed ONCE-ARC and PNCE-ARC methods. Subsequently, a Double-Frontier Network Cross-Efficiency with ARC (DFNCE-ARC) is developed as a more comprehensive NDEA. Finally, a practical application is conducted to assess the performance of a set of Iranian airlines, demonstrating the usefulness and applicability of DFNCE-ARC.

Managing flexible linguistic expressions with subjective preferences and objective information in group decision-making: A perspective based on personalized individual semantics

Flexible linguistic expression (FLE) is a complex linguistic representation that almost generalizes all distributed representations, posing the following challenges for the personalized individual semantics (PIS) issues in group decision-making (GDM) with FLEs. (1) The available measurement methods for FLEs are limited and suffer from some unreasonable or poorly discriminated deficiencies. (2) The existing research on FLEs has failed to fully utilize decision information incorporating subjective preferences and objective information, and the format of FLEs may be altered when optimizing PISs. To address these challenges, this paper focuses on the GDM problems under subjective preferences and objective information, both of which are characterized by FLEs, and introduces a novel FLE-based GDM method with PIS. Firstly, a new similarity measure for FLEs is proposed, considering both external and internal characteristics, namely semantics, elements, and symbolic proportions of linguistic term subsets. Secondly, by utilizing the similarity between the decision-maker's preference matrix and decision matrix, as well as the consistency of the preference matrix, a PIS optimization model is constructed to determine the personalized semantics of individual decision-makers. Subsequently, an optimization model is constructed, focused on maximizing the consensus level to determine the differentiated weights of decision-makers. Furthermore, individual evaluation information is aggregated into group evaluation information, a personalized semantic model is constructed to determine the personalized semantics of the group, and the selection process for alternatives is implemented. Finally, the effectiveness and advantages of our method are illustrated through its application in airline service quality assessment and by comparing it with alternative approaches.

Translation and cultural adaption of the control preference scale across various care settings in a Danish hospital

BackgroundIn recent decades, there has been a growing emphasis on involving patients in healthcare decision-making, driven by political, ethical, and research considerations. Although patient involvement is associated with improved health outcomes, understanding patient preferences regarding their role in decision-making is crucial for effective interventions. The Control Preferences Scale (CPS) measures patient preferences along a continuum from passive to active participation. However, its application in Denmark necessitates translation and cultural adaptation.MethodologyThis study aimed to translate and culturally adapt the CPS for Danish use across diverse healthcare settings: acute care, cancer care, elective surgery, chronic medical treatment, and parental involvement in pediatric care. Following a cross-sectional design, the translation process was systematically planned and executed using Beaton’s guidelines, including the five stages: forward and back translation, synthesis, expert review, and pre-testing.ResultsThe translation and adaption process was carried out successfully. Few linguistic challenges were identified and resolved by the expert review. The findings of the pre-testing indicated high acceptability and usability of the adapted CPS among 152 Danish patients and parents. The collaborative role emerged as the most preferred across settings (69.8%), with passive roles more prevalent among cancer patients (30%) and parents waiting with their child to see a pediatrician (23.3%). Notable, more women preferred collaborative or active roles (83.9%) than men (73.9%). The content validity assessment yielded positive feedback, affirming the relevance and comprehensiveness of the CPS.ConclusionsIn summary, the adaptation and validation of the CPS for Danish use proved successful, providing a valuable tool for assessing patient’s role preferences in healthcare decision-making. However, future studies are recommended to ensure construct validity and reliability through psychometric testing.

Evaluating Taiwan’s Geothermal Sites: A Bounded Rationality Data Envelopment Analysis Approach

Amid rising global demand for renewable energy, geothermal power emerges as a vital, low-carbon solution to enhance energy security and sustainability. Taiwan, strategically located on the seismically active Pacific Ring of Fire, possesses an untapped geothermal potential that is underutilized due to complex site selection challenges. This study specifically addresses the need for a more precise and psychologically attuned site selection process, aiming to optimize the development of geothermal resources in regions with complex geological settings. Utilizing the Modified Bounded Rationality Data Envelopment Analysis (MB-DEA) model, this research integrates traditional DEA with bounded rationality to factor in the risk preferences of decision-makers, offering a novel approach that enhances accuracy in evaluating geothermal sites. This study addresses the critical challenge of accurately selecting geothermal energy sites in geologically complex regions like Taiwan, where traditional methods fall short, aiming to significantly boost the efficiency and effectiveness of geothermal energy exploitation as part of Taiwan’s transition to renewable energy sources. Applied to 30 potential sites across Taiwan, our model provides a detailed assessment based on technical, economic, and psychological criteria, revealing variations in site suitability influenced by stakeholder risk attitudes. Key locations such as Datun Mountain, Maoxing, and Taolin consistently rank highly, confirming their robust potential irrespective of risk preferences. At the same time, other sites show marked sensitivity to shifts in decision-making attitudes. This work significantly advances the methodology of renewable energy site selection by demonstrating the utility of incorporating psychological factors into analytical models, which not only refines decision-making processes but also aligns with Taiwan’s strategic energy planning goals. This study also underscores the importance of accurate geographical data in complex terrains, suggesting further refinement and dynamic integration of bounded rationality for future research.

Anything but Representative Democracy: Explaining Conspiracy Believers’ Support for Direct Democracy and Technocracy

Conspiracy theories gained considerable attention during the Covid-19 pandemic. Although studies have extensively explored their (mostly) negative impacts on various political and social aspects, like participation, health-related behavior, and violence, their influence on support for democracy remains relatively unexplored. The few existing studies offer conflicting findings, prompting my focus to shift from assessing generic support for democracy to examining preferences for alternative decision-making models. To address some limitations of prior research on alternative models of decision-making, I combine a trade-off item with a ranking methodology: respondents were prompted to indicate their first and second preferences for different democratic and non-democratic models over representative democracy. The study is based on data from a representative survey in Germany (July/August 2022; N = 2,536). My findings confirm that the belief in conspiracy theories is positively associated with a preference for direct democratic decision-making. However, conspiracy believers also favor expert-based decision-making over elected politicians—but direct democracy would be their primary choice. Although the evidence for a preference for autocracy over representative democracy is associated with a higher degree of uncertainty, it does suggest that conspiracy believers tend to favor “anything but” representative democracy. These findings contribute to the broader discourse on the impact of conspiracy beliefs on democratic systems.

Decision on the introduction of blockchain technology in green supply chains considering altruistic preferences

Purpose This paper aims to examine the blockchain introduction and altruistic preference decisions of the supplier in agricultural food supply chains and discuss how the supplier decisions are influenced by blockchain technology and altruistic preference levels. Design/methodology/approach The author considers a single period two-level supply chain model to describe the supplier’s decisions. The supplier, as the leader of the game, decides whether to introduce blockchain technology and his own level of altruistic preferences. Consumers have environmental awareness and heterogeneity in green trust. Supply chain members determine their own product pricing and green effort level under Stackelberg game. Findings The results reveal the negative impact of unit verification cost in the technology introduction process on the supply chain. In addition, the supplier can adjust their profits by adjusting their altruistic preferences after introducing blockchain to offset the impact of blockchain through the influence of altruistic preferences as discussed by the author. Originality/value This paper investigates how the profits and green efforts of supply chain members are influenced by blockchain technology and altruistic preferences.

Exploring the Relationship Between Psychological Constructs and Decision-Making Preferences in Psychiatric Outpatients.

This study aimed to elucidate the relationships among health locus of control, psychological reactance, attitudes toward psychiatric treatment, and patient decision-making preferences within a psychiatric outpatient population. A total of 200 consecutive psychiatric outpatients from a community mental health center in Tenerife, Spain, were approached for participation between September 2023 and March 2024. Of these, 151 patients consented to participate in this cross-sectional study. Participants were selected based on their willingness to participate and were provided with informed consent forms. Data were collected using the Patient's Health Belief Questionnaire on Psychiatric Treatment (PHBQPT) and the Control Preferences Scale (CPS). The PHBQPT evaluates health beliefs impacting adherence to psychiatric treatment, while the CPS assesses the preferred level of involvement in medical decision-making. Sociodemographic data were also collected to contextualize the findings. Significant correlations were found between patients' control preferences and their attitudes towards medication, compliance with psychiatric advice, and perceptions of treatment control. A collaborative control preference was notably associated with positive attitudes toward medication and trust in the psychiatrist. These findings suggest that tailored treatment approaches prioritizing patient involvement could enhance adherence and outcomes. The study underscores the importance of considering psychological constructs in psychiatric care to foster a holistic, patient-centered approach. Recognizing and integrating patients' control preferences, attitudes towards medication, and psychological reactance can improve the therapeutic relationship and treatment adherence. Future research should explore longitudinal and interventional studies to further understand the impact of aligning treatment approaches with patient preferences and psychological profiles.

Balancing Sustainability and Decision Maker Preferences in Regional Development Location Selection: A Multi-criteria Approach Using AHP and Fuzzy Goal Programming

Balancing Sustainability and Decision Maker Preferences in Regional Development Location Selection: A Multi-criteria Approach Using AHP and Fuzzy Goal Programming

Correlation coefficients between normal wiggly hesitant fuzzy sets and their applications

The multi-criteria decision-making (MCDM) field has long sought tools capable of adeptly capturing the intricacies of human decision-making amidst uncertainty. Hesitant fuzzy sets (HFS) have become a cornerstone in the MCDM field due to their ability to capture the intricacies of human decision-making under uncertainty. Nonetheless, we identified a significant gap in traditional HFS formulations, which often fail to fully harness the nuanced and implicit preferences of decision-makers (DMs). This shortcoming can lead to suboptimal decision outcomes in complex and uncertain environments. We introduce the normal wiggly hesitant fuzzy set (NWHFS), a novel construct that encapsulates both explicit and implicit preferences within a more representative framework. This study pioneers the development of new correlation coefficients for NWHFSs, offering a robust quantitative measure to elucidate the intricate relationships between variables. Our findings demonstrate that NWHFSs significantly enhance the MCDM process, providing a nuanced perspective that traditional HFS models cannot match. The proposed correlation coefficients not only reveal the concealed preferences of DMs but also broaden the decision-making spectrum, offering a more profound understanding of the relationships between alternatives and criteria. We illustrate the superiority of our approach through comparative analysis with existing methods, highlighting its ability to discern subtleties that other models overlook. Moreover, we integrate NWHFSs into clustering analysis, showcasing their potential to classify data sources with shared attributes effectively. This integration is particularly noteworthy for its ability to navigate complex datasets, offering a new dimension in data mining and resource retrieval. In essence, our study redefines the MCDM paradigm by introducing NWHFSs and their correlation coefficients, setting a new standard for decision-making accuracy and insight. The implications of our work extend beyond theory, offering practical solutions to real-world decision-making challenges.

The impact of entrepreneurs’ wives participating in corporate management on company risk-taking

To investigate the influence of spouses of business leaders on corporate decision-making behavior, we use data from 2003 to 2019 from Chinese listed family-controlled companies to examine the impact of entrepreneurs’ wives participating in corporate management on the risk-taking of family businesses. We found that entrepreneurs’ wives participating in company management significantly reduce the risk taking of family businesses, particularly when the wife is a shareholder in the company. Additionally, the wife’s age, level of education, and professional experience also affect her attitude and behavior toward participating in company management. When the wife is older and has a higher degree of education, the risk taking of the enterprise decreases. However, the wife’s rich professional experience can mitigate female conservatism and increase the company’s risk taking. Our research has implications for understanding gender differences in the context of the extension of marital power of Chinese entrepreneurs’ wives from the family to corporate decision-making and risk preferences. This helps to deepen our understanding of the role and status of women in China’s family business management.

Antibiotic Use at the End of Life: Current Practice and Ways to Optimize.

Infections are common complications in end of life (EOL). However, clinicians have minimal guidance regarding antibiotic decision-making in EOL care, leading to the overuse of antibiotics. While symptom relief is frequently cited as a major reason for antibiotic use in EOL, antibiotics have not been shown to provide significant improvement in symptoms outside of urinary tract infections. In addition, when prognosis is expected to be in the range of days to weeks, antibiotics have not been shown to provide significant survival benefit. Antibiotics can be beneficial in EOL care in appropriate scenarios, but the current widespread use of antibiotics in EOL requires reevaluation. There needs to be broader efforts to think about antibiotics like other invasive medical procedures in which benefits and risks are weighed, recognizing that not all patients in EOL who receive antibiotics will benefit. In addition, during care planning process, discussing and documenting antibiotic preferences will be beneficial. Non-antibiotic symptom management should be incorporated to plan of care when infection is suspected. Ultimately, the use of antibiotics at EOL should be for the clear benefit for the recipient and should be guided by the type of infection and its clinical course, patients' primary disease and its prognosis, and the preferences of patients or surrogate decision makers.

Research on Risk-Averse Procurement Optimization of Emergency Supplies for Mine Thermodynamic Disasters

Reducing procurement risks to ensure the supply of emergency supplies is crucial for mitigating the losses caused by mine thermodynamic disasters. The risk preference of decision-makers and supply chain collaboration are the important aspects for this reductiom. In this study, a novel P-CVaR (Piecewise conditional risk value) distributionally robust optimization model is proposed to accurately assist the decision-makers’ decision of risk preference for reducing procurement risks. Meanwhile, the role of cooperation between procurement and reserves are considered for the weakening procurement risks. A risk-averse bi-level optimization model is proposed to obtain the optimal procurement strategy. Furthermore, by applying the Lagrange duality theorem, the complexity of the bi-level optimization model is simplified then solved using a PSO algorithm. Using empirical analysis, it has been verified that the model presented in this paper serves as a valuable guideline for mine thermodynamic pre-disaster emergency material procurement strategies for the prevention of thermodynamic disasters.

A GIS-based multi-criteria approach for identifying areas vulnerable to subsidence in the world's largest ongoing urban socio-environmental mining disaster

This study proposes a GIS-based multi-criteria approach to identify areas vulnerable to subsidence in the world's largest ongoing urban socio-environmental disaster, caused by salt-gem urban mining in Maceió, Alagoas State, Brazil. The analysis revealed critical areas concentrated in regions with salt-gem mines and soil composed of sedimentary rocks near water bodies, where the local population faces significant socio-economic challenges. In addition to addressing environmental vulnerabilities, the developed methodology considers social and economic risks, aiming for integrated actions between the population and the environment. The FITradeoff multi-criteria method used in the geospatial model showed benefits, including a significant reduction in the number of inconsistencies required for geospatial decision-making, ensuring efficiency in the development of prevention and mitigation strategies. The Spatial Inference model showed a high level of accuracy of 88.89 % in classifying the vulnerability of Maceió’s neighborhoods to subsidence, although it faced challenges when assessing neighborhoods with distinctive characteristics. The proposed preference-driven multi-criteria model incorporates decision-maker preferences, opinions, and knowledge of this disaster. Under specific conditions, this model can offer tailored solutions that align with stakeholders’ objectives. The results provide valuable insights for the development of public policies and risk management strategies in affected areas and areas vulnerable to subsidence due to urban mining in Maceió, and may be applicable to other regions of Brazil and the world facing similar challenges.

Risk-Adaptive Local Decision Rules

The decision rules developed in this paper help managers recognize relationships between data and decisions and prescribe courses of actions that are guaranteed near-optimal as well as transparent and interpretable. Transparency and interpretability are prerequisites for any decision support tool that needs to be conveyed, understood, and justified broadly. An understanding of the relationship between data and decisions is important for managers as they identify the critical factors, prioritize their focus, guide the resource allocation, and develop mitigation strategies for handling data uncertainty. The relationship between data and decision can be especially convoluted for combinatorial optimization problems. We consider simple decisions rules that ensure transparency and interpretability, but also allow nearly any continuous decision rule within a unified framework of analysis. Our preferred adaptive minimum decision rule prescribes decisions with 1% relative suboptimality gap, on average, even when facing distributional shifts in out-of-sample testing.

Preferences for ethical intermediaries and sustainable investment decisions in micro-firms: The role of financial literacy and digital financial capability

This study analyses the effects of financial literacy and digital financial capabilities in shaping entrepreneurs’ preferences for ethical financial intermediaries and sustainable investment decisions. Exploiting novel survey data on Italian micro-enterprises, we find that more financially literate business owners have higher preferences for intermediaries with a strong ethical stance, are more likely to make investments inspired by environmental and social criteria and have a higher awareness of sustainable financial products. Moreover, digital financial competencies are found to play a significant role in enhancing preferences for ethical intermediaries and sustainable investment decisions. Finally, we show that the beneficial effect of financial literacy is mostly direct, while the indirect effect operating through higher digital financial abilities, despite being statistically significant, impacts firms’ sustainable financing and investing decisions only to a lower extent.

Decision-making preferences and regret in rectal cancer patients undergoing restorative proctectomy: A prospective cohort study

BackgroundHow patients make treatment choices in rectal cancer is poorly understood and may affect long-term regret and satisfaction. The objective of this study is to characterize decision-making preferences and their effect on decisional regret in patients undergoing restorative proctectomy for rectal cancer. MethodsA prospective cohort study was conducted in a single academic specialist rectal cancer center from October 2018 to June 2022. Adult patients who underwent restorative proctectomy at least one year prior were recruited. Health literacy was assessed using the BRIEF instrument. Decision-making preferences regarding cancer treatment were assessed using the Control Preferences Scale. Decisional regret regarding their choice of restorative proctectomy was assessed using the Decision Regret Score. Bowel dysfunction was measured using the low anterior resection syndrome score. ResultsOverall, 123 patients were included. Health literacy was categorized as adequate in 63%, marginal in 25%, and limited in 12%. Patients with adequate health literacy were more likely to prefer a collaborative decision-making role compared with those with low health literacy (86% vs 65%, P = .016). Patients with incongruence between preferred and actual decision-making roles were more likely to report high regret (56% vs 25%, P = .003). Patients with major low anterior resection syndrome were also more likely to experience high regret compared with patients with no/minor low anterior resection syndrome (44% vs 25%, P = .036). ConclusionA significant proportion of patients with rectal cancer undergoing restorative proctectomy do not have a decision-making role that is congruent with their preferences, and these patients experience a high degree of regret.

Exploring communication preferences and risk thresholds of clinicians and parents of febrile infants under 90 days presenting to the emergency department: a qualitative study

BackgroundFebrile infants under 3 months of age are at higher risk of invasive bacterial illness (IBI) when compared with older children. Increasingly sequential assessment based on age, clinical appearance and...

Stakeholder involvement and preferences in landscape protection decision-making: a systematic literature review

Stakeholder involvement and preferences are pivotal in the decision-making process for landscape protection within a specific context. However, many decisions regarding landscape protection options still rely on management choices with little or no consideration of all stakeholders. Previous scholars emphasized the importance of establishing an integrated framework to gain an adequate understanding of the process of stakeholders’ decision-making in landscape protection. Therefore, a systematic literature review was conducted on the topic of stakeholders’ involvement and preferences in landscape protection decision-making. This review included research articles published from 2013 to 2023 using two databases and registers, namely, Science Direct and Google Scholar. A total of 110 research articles were identified and qualified for review based on the screening requirements, with an additional 15 documents for theories and backgrounds to provide a better understanding and outcomes for the study. The results of this study were organized based on concepts from the resulting research articles and were integrated to propose a conceptual framework for Stakeholders’ involvement and preferences in landscape protection. Additionally, this study’s findings indicate the significance of incorporating diverse stakeholders and their preferences in landscape protection processes to ensure awareness of inclusivity in decision-making and secure long-term support.

The Absurdity of Rational Choice: Time Travel, Foreknowledge, and the Aesthetic Dimension of Newcomb Problems

Nikk Effingham and Huw Price argue that in certain cases of Newcomb problems involving time travel and foreknowledge, being given information about the future makes it rational to choose as an evidential decision theorist would choose. Although the cases they consider have some intuitive pull, and so appear to aid in answering the question of what it is rational to do, we argue that their respective positions are not compelling. Newcomb problems are structured such that whichever way one chooses, one might be led by one’s preferred decision theory to miss out on some riches (riches which others obtain whilst employing their preferred decision theory). According to the novel aesthetic diagnosis we shall offer of the Newcomb dialectic, missing out in this way does not render one irrational but, rather, subject to being seen as absurd. This is a different kind of cost but not one that undermines one’s rationality.