Intensity Of Preference Research Articles

A Boss Like Me*

There is extensive evidence of hiring decisions being biased with respect to applicant race and gender. We look at the other side of the hiring transaction, presenting what we believe to be first systematic investigation of bias in labor supply. In a choice experiment we examine decisions of job seekers faced with 14,544 pairs of job offers, with varying characteristics. White job seekers are around 11% more likely to choose a job offered by a white manager than an otherwise identical job offered by a black, while black respondents are 17% less likely. Estimates of intensity of preference, measured by willingness to accept a lower hourly wage, over employer attributes are reported. We find little evidence of bias with respect to gender. The results suggest a mechanism for disadvantage on basis of race in a competitive market for managerial or entrepreneurial roles

Parents’ preferences for follow-up care in a type 1 diabetes paediatric population: a survey-based study in Quebec, Canada

ObjectivesExamine variations in parent’s preferences for their child’s type 1 diabetes (T1D) follow-up care and the determinants of the preferred intensity of care. Clinical guidelines recommend multidisciplinary management of T1D,...

Voter Turnout and Preference Aggregation

We study how voter turnout affects the aggregation of preferences in elections. Under voluntary voting, election outcomes disproportionately aggregate the preferences of voters with low voting cost and high preference intensity. We show identification of the correlation structure among preferences, costs, and perceptions of voting efficacy, and explore how the correlation affects preference aggregation. Using 2004 US presidential election data, we find that young, low-income, less-educated, and minority voters are underrepresented. All of these groups tend to prefer Democrats, except for the less educated. Democrats would have won the majority of the electoral votes if all eligible voters had turned out. (JEL D12, D72)

Effects of chronic and acute predation risk on sexual ornamentation and mating preferences

AbstractPhenotypic plasticity is widespread in animals. Still, how plastic responses to predator presence affect traits under sexual selection and influence mating preferences is not well understood. Here, we examined how simulated chronic predator presence during development and acute predator presence during mate choice affect the expression of male secondary sexual traits and female mating preference in the three-spined stickleback, Gasterosteus aculeatus. Males reared under chronic predator presence developed less intense red breeding coloration but showed higher courtship activity than males that grew up in a predator-free environment. Acute predator presence during mate choice trials did not influence male behavior or ornamentation. Predator presence experienced during development did not affect female mating preferences, whereas acute predator presence altered preferences for male courtship activity. Male body size and eye coloration influenced the intensity of female mating preferences, while the trait changing most in response to predator presence during development (red coloration) had no significant impact. The observed interplay between developmental plasticity in male ornamental traits and environment-dependent female mating preferences may lead to dynamic processes altering the strength and direction of sexual selection depending on both the chronic and acute risk of predation. These processes may contribute to the maintenance of within- and among-population variation in secondary sexual traits, and may, ultimately, facilitate speciation.

PENGARUH PENGUNGKAPAN CORPORATE SOCIAL RESPONSIBILITY, PREFERENSI RISIKO EKSEKUTIF, DAN CAPITAL INTENSITY TERHADAP TAX AVOIDANCE PERUSAHAAN SEKTOR PERTANIAN DAN PERTAMBANGAN YANG TERDAFTAR DI BEI

This study aims to find empirical evidence on the influence of corporate social responsibility disclosure, executive risk preference and capital intensity against tax avoidance. population in this study are all companies of agriculture and mining sector listed in BEI year 2013-2016. The type of research used in this study is empirical research. The sampling technique used is purposive sampling. Based on sampling through purposive sampling, then obtained as many as 14 samples of banking companies with a total observation of research as much as 56 observations. The results of this study found that disclosure of corporate social responsibility, executive risk preference and capital intensity did not affect tax avoidance.

From Complexity to Clarity

From Complexity to Clarity

Assessment of Personal Relaxation in Indoor-Air Environments: Study in Real Full-Scale Laboratory Houses.

The relationship between chemical concentrations in indoor air and the human sense of comfort and relaxation have been reported. We investigated the effect of the sum of volatile organic compounds (ΣVOCs; sum of 79 VOCs) on the level of relaxation in two laboratory houses with almost identical interior and exterior appearances. The electroencephalogram (EEG) was monitored to evaluate the degree of personal relaxation objectively. The experiments were conducted in laboratory houses (LH) A and B with lower and higher levels of ΣVOCs, respectively. A total of 168 healthy volunteers participated, who each performed the task for 20 min, followed by a 10-min break, and EEG was measured during the break. Simultaneously as subjective evaluations, the participants were asked to fill a questionnaire regarding the intensity of odor and preference for the air quality in each LH. The subjective evaluation showed a significant association between ΣVOCs and participants’ relaxation (OR: 2.86, 95%CI: 1.24–6.61), and the objective evaluation indicated that the participants were more relaxed in the LH with lower levels of ΣVOCs than that with higher levels (OR: 3.03, 95%CI: 1.23–7.50). Therefore, the reduction of ΣVOCs and odors in indoor air would have an effect, which is the promotion of relaxation.

A likelihood‐based ORESTE method for failure mode and effect analysis (FMEA) based risk analysis problem under interval type‐2 fuzzy environment

AbstractThe failure mode and effect analysis (FMEA) model is an effective safety system analysis method to identify and analyze potential risks. Nevertheless, the traditional FMEA possesses deficiencies associating with questionable multiplication procedure, overlooking uncertainty and interaction relationships among risk factors. Besides, determining the risk priority considering the detailed interrelation among the failure modes is beyond the capability of current FMEA models, especially in the case of complex preference information. Thus, this paper proposed an extended FMEA by integrating ORESTE (organization, rangement et Synthèse de données relarionnelles, in French) method, Heronian Mean (HM) operator, and interval type‐2 fuzzy sets (IT2FSs). First, the IT2FSs are utilized to depict the complex risk preference information. Second, the HM operator, as an aggregated tool, is utilized to obtain collective evaluation information, which can fully reflect the overall correlations among individual risk assessment information. Then, an extended ORESTE method based on the likelihood of IT2FSs is utilized to obtain the priority ranking orders of failure modes. In this extended method, a new IT2FSs global preference score is constructed to determine the weak ranking. And, three new preference intensities based on the likelihood of IT2FSs are constructed to determine PIR (preference, indifference, and incomparability) structure which can show the detailed relationships between failure modes. Finally, an illustrative example of a nuclear reheat valve system is selected to verify its application and efficiency.

Flight to Safety: COVID-Induced Changes in the Intensity of Status Quo Preference and Voting Behavior

The relationship between anxiety and investor behavior is well known enough to warrant its own aphorism: a “flight to safety.” We posit that anxiety alters the intensity of voters’ preference for the status quo, inducing a political flight to safety toward establishment candidates. Leveraging the outbreak of the novel coronavirus during the Democratic primary election of 2020, we identify a causal effect of the outbreak on voting, with Biden benefiting between 7 and 15 percentage points at Sanders’s expense. A survey experiment in which participants exposed to an anxiety-inducing prompt choose the less disruptive hypothetical candidate provides further evidence of our theorized flight to safety among US-based respondents. Evidence from 2020 French municipal and US House primary elections suggests a COVID-induced flight to safety generalizes to benefit mainstream candidates across a variety of settings. Our findings suggest an as-yet underappreciated preference for “safe” candidates in times of anxiety.

Schadenfreude and General Anti-Social Behaviours: The Role of Violent Content Preferences and Life Satisfaction

In a digitally developed civilization access to different kinds of content and information can be easily acquired. From all the available content, some individuals chose and prefer to consume aggressive or violent content. In this light, the scope of this investigation is to determine the connection between the level of Violent Content Preferences (VC) and the levels of General Antisocial Behaviour (AS) and Schadenfreude (SCH) and the relationship between the intensity of life satisfaction (LS) and the intensity of Violent Content Preferences (VC), General Antisocial Behaviour (AS) and Schadenfreude (SCH). The present investigation is part of a chain of studies with reference to violent behaviours and cognitions. In this study, a number of 81 students (M = 27.57 SD = 9.25) from Arad, Romania, Aurel Vlaicu University, were investigated. VC and SCH were measured with the explorative affirmations, AS scores were obtained with the help of the How I Think Questionnaire (HIT) and LS was calculated with the help of the Satisfaction with life scale (SWLS). The obtained data ilustrates that VC is positively associated with AS an SCH, furthermore, AS is positively related with SCH, and LS was negatively associated with VC, AS and SCH. These outcomes point out the requirement to take into consideration the content we consume in regard to one’s satisfaction with life and can offer literature meaningful information in regards to the prevention or reduction of anti-social tendencies or cognitions.

The federalization of trade politics in Switzerland, Germany and Austria

ABSTRACT Since the 1990s, sub-federal units have become increasingly active in trade politics, a domain that is usually an exclusive jurisdiction of the federal level. Conceptualizing this process of institutional change as federalization, this paper adopts a most similar case design to examine how four factors interact to generate different patterns of trade policy engagement in Switzerland, Austria and Germany. The study suggests that institutional resources and preference intensity are crucial to explain long-term variation in all three federations, while the role of party politics and social mobilization are contextual rather than causal factors.

Democracy and Intensity of Preferences: A Test of Storable Votes and Quadratic Voting on Four California Propositions

Can direct democracy overcome the “problem of intensity,” treating everyone equally and yet allowing an intense minority to prevail if, but only if, the majority’s preferences are weak? Storable vo...

Ranking recovery from limited pairwise comparisons using low-rank matrix completion

This paper proposes a new methodology for solving the well-known rank aggregation problem from pairwise comparisons using low-rank matrix completion. Partial and noisy data of pairwise comparisons is first transformed into a matrix form. We then use tools from matrix completion, which has served as a major component in the low-rank based completion solution for the Netflix challenge, to construct the preference of different objects. In our approach, the data from multiple comparisons is used to create an estimate of the probability of object i winning (or be chosen) over object j, where only a partial set of comparisons between the N objects is known. These probabilities can be transformed to take the form of a rank-one matrix. An alternating minimization algorithm, in which the target matrix takes a bilinear form, is used in combination with maximum likelihood estimation for both factors. The reconstructed matrix is used to obtain the true underlying preference intensity. We start by exploring the asymptotic case of an infinitely large number of comparisons (“noiseless case”). We then extend our solution to the case of a finite number of comparisons for a subset of pairs (“noisy case”). This work demonstrates the improvement of our proposed algorithm over the state-of-the-art techniques in both simulated scenarios and real data.

From social choice to inequality-decomposition: in the spirit of Arrow and Atkinson by way of Sen and Shorrocks

ABSTRACT This article forges connections between social choice theory and inequality-measurement to deliver a series of advances to the latter. It discusses the ethical and formal aspects connecting the fields, linking the roles played by the intensity of preferences and interpersonal comparability (in social choice) and, respectively, inequality-aversion and interpersonal comparability (in inequality-measurement). This extends naturally to relaxing the assumption of symmetry in group-wise inequality-decompositions, allowing a measure capable of unambiguous decomposition that, overcoming well-known limitations of existing measures, still incorporates different degrees of inequality-aversion through the use of its demonstrated duality with inter-group comparability. The framework is then applied to inequality in Brazil and the changes it underwent between 2003 and 2015, focusing on labour-market incomes of white men and non-white women. We show how sensitive are measures of (changes in) inequality to assumptions regarding the interpersonal comparability of the groups’ income and inequality-aversion, pinpointing the precise trade-offs between the two. The results indicate that, for a reasonable range of parameters, overall inequality changed by between −28.6% and −12.2% over the period. This highlights the analysis of the trade-off between interpersonal comparability and inequality-aversion warrants being addressed explicitly in empirical measurements of, or judgements over, levels and variations of inequality.

(2007-6020) A consistency-driven approach to construction of Z-number-valued pairwise comparison matrices

The notion of consistency is used to estimate the quality of preference knowledge and its stability for reliable evaluation of decision alternatives. It is well-known that a set of strict consistency conditions are used to keep the rationality of preference intensities between compared elements. These requirements are not achievable in the real situations when decision maker has limited rationality and partially reliable preferences. In this study, we propose an approach to deriving consistency-driven preference degrees for such kind of situations. A preference degree is described by a Z-number to reflect imprecision and partial reliability of preference knowledge. An optimization problem with Z-number valued variables is used to formulate design of consistent preferences. A real-world decision making problem is considered to illustrate application of the proposed method and conduct comparison with an existing technique.

A nondominated selection procedure with partially consistent non-reciprocal probabilistic linguistic preference relations and its application in social donation channel selection under the COVID-19 outbreaks

A non-reciprocal fuzzy preference relation (NrFPR) can express partial relations of alternatives, including indifference relations, preference relations and incomparability relations, but cannot depict linguistic preference intensities. A probabilistic linguistic preference relation (PLPR) can represent preference intensities in forms of probabilities and linguistic terms, but the incomparability relations of alternatives were not defined in a PLPR. Given that the NrFPR and PLPR can overcome each other’s drawbacks, this study proposes the non-reciprocal probabilistic linguistic preference relation (NrPLPR). Six conditions are given to express the partial relations of alternatives. Since the P-cut of probabilistic linguistic term sets (PLTSs) is effective in the operations of PLTSs without information loss, we construct the P-cut matrix of an NrPLPR by an adaptive P-determination method. Afterwards, nine rules are provided to define the partially consistent NrPLPR. To repair the inconsistent NrPLPR, a two-stage consistency repairing process, containing the linguistic information and probability repairing stages, is introduced. In addition, a non-reciprocal probabilistic linguistic nondominated selection procedure is proposed to rank alternatives. A case study on selecting social donation channels under the COVID-19 outbreaks is given to demonstrate the applicability of the proposed method. A comparative analysis is done to show the effectiveness of the proposed method.

Sociodemographic, Health and Lifestyle, Sampling, and Mental Health Determinants of 24-Hour Motor Activity Patterns: Observational Study.

BackgroundAnalyzing actigraphy data using standard circadian parametric models and aggregated nonparametric indices may obscure temporal information that may be a hallmark of the circadian impairment in psychiatric disorders. Functional data analysis (FDA) may overcome such limitations by fully exploiting the richness of actigraphy data and revealing important relationships with mental health outcomes. To our knowledge, no studies have extensively used FDA to study the relationship between sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics and daily motor activity patterns assessed with actigraphy in a sample of individuals with and without depression/anxiety.ObjectiveWe aimed to study the association between daily motor activity patterns assessed via actigraphy and (1) sociodemographic, health and lifestyle, and sampling factors, and (2) psychiatric clinical characteristics (ie, presence and severity of depression/anxiety disorders).MethodsWe obtained 14-day continuous actigraphy data from 359 participants from the Netherlands Study of Depression and Anxiety with current (n=93), remitted (n=176), or no (n=90) depression/anxiety diagnosis, based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition. Associations between patterns of daily motor activity, quantified via functional principal component analysis (fPCA), and sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics were assessed using generalized estimating equation regressions. For exploratory purposes, function-on-scalar regression (FoSR) was applied to quantify the time-varying association of sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics on daily motor activity.ResultsFour components of daily activity patterns captured 77.4% of the variability in the data: overall daily activity level (fPCA1, 34.3% variability), early versus late morning activity (fPCA2, 16.5% variability), biphasic versus monophasic activity (fPCA3, 14.8% variability), and early versus late biphasic activity (fPCA4, 11.8% variability). A low overall daily activity level was associated with a number of sociodemographic, health and lifestyle, and psychopathology variables: older age (P<.001), higher education level (P=.005), higher BMI (P=.009), greater number of chronic diseases (P=.02), greater number of cigarettes smoked per day (P=.02), current depressive and/or anxiety disorders (P=.05), and greater severity of depressive symptoms (P<.001). A high overall daily activity level was associated with work/school days (P=.02) and summer (reference: winter; P=.03). Earlier morning activity was associated with older age (P=.02), having a partner (P=.009), work/school days (P<.001), and autumn and spring (reference: winter; P=.02 and P<.001, respectively). Monophasic activity was associated with older age (P=.005). Biphasic activity was associated with work/school days (P<.001) and summer (reference: winter; P<.001). Earlier biphasic activity was associated with older age (P=.005), work/school days (P<.001), and spring and summer (reference: winter; P<.001 and P=.005, respectively). In FoSR analyses, age, work/school days, and season were the main determinants having a time-varying association with daily motor activity (all P<.05).ConclusionsFeatures of daily motor activity extracted with fPCA reflect commonly studied factors such as the intensity of daily activity and preference for morningness/eveningness. The presence and severity of depression/anxiety disorders were found to be associated mainly with a lower overall activity pattern but not with the time of the activity. Age, work/school days, and season were the variables most strongly associated with patterns and time of activity, and thus future epidemiological studies on motor activity in depression/anxiety should take these variables into account.

Unbalanced probabilistic linguistic decision-making method for multi-attribute group decision-making problems with heterogeneous relationships and incomplete information

In group decision-making problems, decision makers prefer to use several linguistic terms to describe their own perception and knowledge, and give their preference intensity of each possible linguistic terms based on their own understanding and interpretation. Due to the nonlinearity of decision maker’s cognition, the gaps between adjacent linguistic terms are unbalanced. The unbalanced probabilistic linguistic term set (UPLTS) is proposed to present such situation. To this phenomenon, a resolution framework is constructed to analyze multiple attribute group decision-making problems under unbalanced probabilistic linguistic environment. Firstly, the integration model based on evidential reasoning theory is proposed to aggregate UPLTSs from different groups in view of incomplete probabilistic distributions in UPLTS. Secondly, the transformation function based on proportional 2 tuple is developed to transform UPLTS into probabilistic linguistic term set, making it easier for subsequent analysis and processing. Thirdly, Based on the multiple types of partitioned structure relationship among attributes, partitioned fuzzy measure is developed to globally capture these interactions among attributes. Then the probabilistic linguistic Choquet integral operator with partitioned fuzzy measure is proposed to obtain the comprehensive performances of alternatives. Lastly, the effectiveness and practicability of the proposed method is demonstrated using three numerical examples and comparing with other methods.

Revenue allocation in Formula One: a pairwise comparison approach

ABSTRACT A model is proposed to allocate Formula One World Championship prize money among the constructors. The methodology is based on pairwise comparison matrices, allows for the use of any weighting method, and makes possible to tune the level of inequality. We introduce an axiom called scale invariance, which requires the ranking of the teams to be independent of the parameter controlling inequality. The eigenvector method is revealed to violate this condition in our dataset, while the row geometric mean method always satisfies it. The revenue allocation is not influenced by the arbitrary valuation given to the race prizes in the official points scoring system of Formula One and takes the intensity of pairwise preferences into account, contrary to the standard Condorcet method. Our approach can be used to share revenues among groups when group members are ranked several times.

Q-ROF-SIR methods and their applications to multiple attribute decision making

q-rung orthopair fuzzy set (q-ROFS) is a useful tool to express uncertain information. With the parameter q increasing, q-ROFSs have broader space for describing uncertain information than intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs). This paper extends the superiority and inferiority ranking (SIR) methods to solve multiple attribute decision making (MADM) problems within the q-ROF environment, named q-ROF-SIR methods. In the q-ROF-SIR methods, the possibility degree (PD) for q-rung orthopair fuzzy numbers (q-ROFNs) is introduced to improve the preference intensity. Further, the q-ROF entropy weight (q-ROF-EW) method is constructed to determine the attribute weights suppose the weights of attribute are unknown. Finally, the effectiveness and applicability of the q-ROF-SIR methods are verified.