The present study evaluates the effect of some of the most important variables affecting the preferences of bank loan applicants, based on the discrete choice test method. Initially, the variables and their levels were identified after consultation with banking experts and the required information was collected through a questionnaire. The results show that any increase in interest rates, intensification of bank supervision over the use of facilities, no grace period, and the existence of personal guarantees of company managers reduce the desire to obtain facilities and therefore the possibility of referring to the banking system for financing Obtaining facilities from banking resources will reduce. Given that the facility interest rate is considered as a monetary (normalizing) variable, the calculations showed that each respondent (investor) is willing to pay an average of 1. 06 percent more facility interest rate to be under the supervision of the bank or institution. In exchange for a 6-month grace period, pay 2. 17 percent more interest rate on the facility, and finally pay no risk from personal capital in exchange for paying 2. 67 percent interest rate on the facility,Therefore, the comparison of the results showed that the variable of personal guarantee of company managers has the greatest impact on the decision-making portfolio and preferences of investors so that people are willing to pay the highest cost for the protection of their personal assets and the lowest cost for exemption from bank supervision. This indicates that the type of bank supervision is not effective and serious from the point of view of the respondents.

Choosing housing is the most basic need of every household. Therefore, identification and evaluation of effective factors in choosing housing from the viewpoint of the homeowner's households will play an important role in helping urban managers to promote and improve the housing conditions of the people. Accordingly, the present study was conducted to investigate and evaluate the factors affecting the probability of choosing housing with emphasis on the demographic characteristics of homeowning households in Isfahan. The research method is applied in terms of purpose and is descriptive-survey based on the data collection method. Data gathering method, documentary method by studying and investigating previous research, and field method. Data collection was done by designing empirical questionnaire, randomly from 300 households. These data were categorized in the EXCEL software and analyzed using the discrete multinomial logit model (MNL) in STATA software based on Random Utility Theory (RUT). The results of this study, taking into account the Z statistic of the variables, indicated that 11 variables were confirmed related to the properties of the housing, as well as the confirmation of 20 variables demographic variables defined in The model is relevant. The most influential demographic variables include: having children aged 18 and above, the number of home purchases, the reason for settling in Isfahan and the level of social relationships between the individual and his family, respectively, with 41, 37, 36, 33%, the coefficient of positive effect on the probability of choosing in the multiple logit function. The results showed that the socio-economic are important and, in urban housing studies, should be specifically considered

Background: The preferences of Iranians concerning the attributes of health insurance benefit packages are not well studied. This study aimed to elicit health insurance preferences among insured people in Iran during 2016. Methods: A mixed methods study using a discrete choice experiment (DCE) approach was conducted to elicit health insurance preferences on a total sample of 600 insured Iranians residing in Tehran. The final design of the DCE included 8 health insurance attributes. Data were analyzed using conditional logistic regression models. Results: The final model of this DCE study included 8 attributes, and the findings indicated statistically significant (P <. 001) increase in the odds ratio (OR) of choosing health insurance at all levels of cost coverage except for the rehabilitation and para-clinical benefits, where at 70% cost coverage there was insignificant (P =. 485) disutility (OR = 0. 95). With the increase in cost coverage level, the probability of choosing health insurance was significantly (P <. 001) the highest for the private hospitals’ benefits (OR = 2. 82) followed by public hospitals’ benefits (OR = 2. 02) and outpatient benefits (OR = 1. 75), and the premium revealed statistically significant (P <. 001) disutility (OR = 0. 96). Conclusion: Our findings revealed that participants would be willing to choose health insurance plans with higher cost coverage of healthcare services and with lower premiums. However, the demographic characteristics, income, and health status of the insured individuals affected their health insurance preferences. The findings can contribute to the design of better health insurance policies, improve the participation of individuals in health insurance, and increase the insured individuals’ utility from the insurance benefits packages.

Background: In addition to clinical and technical considerations, patients’ preferences are essential for evaluating interventions such as precision medicine (PM). Objectives: This study aimed to identify and prioritize attributes of precision oncology that are important for patients to develop and validate a standard stated preference instrument. Methods: The key attributes of precision oncology and their related levels were extracted from the systematic literature review and were presented on a validated 5-point Likert scale questionnaire to experts (n = 35). In two rounds of Delphi, participants scored and prioritized the attributes through this personally administered questionnaire to identify the five most important ones to develop a discrete choice experiment (DCE) instrument. The developed DCE questionnaire was subsequently validated, providing a robust and standard instrument for evaluating patients’ preferences for precision oncology. Results: Based on the consensus criteria, the final DCE included four attributes and a total of 14 levels, which were access to treatment (easy/not easy), out-of-pocket (OOP) expenditures (four levels according to treatment costs in the country), change in life expectancy (LE, six levels from an average gain of three months to four years), and change in quality of life (QoL, improvement or no change). Conclusions: The above-mentioned attributes represent patients’ main preferences from the views of the Iranian experts. The developed DCE questionnaire can be used to assess patients’ preferences and willingness to pay (WTP) in precision oncology.

Background: Physician shortages in rural areas is a universal concern, and most countries face this challenge. Many attributes influence the physician preferences about the choice of working location. The aim of this systematic review was to investigate which attributes were included in discrete choice experiment studies and which of them valued the most by physicians. Methods: The following databases were searched: PubMed, Embase, and Web of Science Core Collection. Further studies were retrieved from reference lists of included studies, and grey literature. Studies used discrete choice experiments methods to elicit preferences for working in the deprived area, focus on physicians or medical students, and published between 2000 and 2017 in the English language were included. Results: The literature search yielded 192 studies, of which 14 studies met inclusion criteria. The attributes and attribute levels were identified by literature review and qualitative research. The number of attributes varied from five to ten, and the most frequent number was six attributes. In most studies, maximum of sixteen different scenarios were given to the study samples. The “ salary or income” attribute was the most important in fifty percent of the studies and the attributes related to “ study and education” was at the next level. Conclusion: Financial attributes are not the only significant attributes considered by the physicians for deciding where to practice, but also the other non-financial attributes are important. It is suggested that based on the economic, social and cultural conditions of each country, a specific incentive package, including a set of financial and non-financial incentives, is developed to attract physicians to the deprived areas.

Background: Health workforce shortages in rural and remote areas are a global challenge that almost every health system has to deal with. This study aimed to discover neurosurgeons’ job preferences and propose policy interventions that could possibly increase their retention in rural, remote, or underserved areas.Methods: A discrete choice experiment (DCE) was conducted in November 2014 with a sample of Iranian neurosurgeons selected from five contrary’s provinces representing the geographical diversity. Job attributes included income, dual practice opportunities, workload, proximity to family, clinical infrastructure, housing, educational facilities, and work location. Probit regression model was used to estimate the importance of different job attributes and examine the extent to which neurosurgeons were willing to tradeoff between monetary and nonmonetary attributes.Results: Findings indicated that increased salary, permission to undertake dual practice and access to adequate clinical infrastructure were the most important retention policies. Provision of subsidized housing and educational facilities also increased neurosurgeons’ attraction and retention in rural areas.Conclusion: A range of policy interventions focusing on both monetary and nonmonetary incentives are required to increase neurosurgeons’ retention in rural, remote, or underserved areas.