In product choice models, incorporating socio-demographic characteristics is conceptually appealing and has numerous managerial benefits. The main question is how socio-demographic characteristics differentiate customers or products in order to define relevant marketing strategies. Traditionally discrete choice models, also called the consolidated approach, have been used to understand, describe, and predict consumer choices for a particular product. In this study, a segment-oriented approach is introduced and compared with the consolidated approach. The proposed methodology uses principal component analysis to segment the population into different groups. The results indicate that principal component analysis is a robust method and outperforms the consolidated approach in terms of choice predictability and R-square index. These findings bring new insight to manufacturers as well as marketers regarding customer policies targeting.

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

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.

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: Across most healthcare systems, patients are the primary focus. Patient involvements enhance their adherence to treatment, which in return, influences their health. The objective of this study was to determine the characteristics (ie, attributes) and associated levels (ie, values of the characteristics) that are the most important for patients regarding telerehabilitation (TR) healthcare to support a future discrete choice experiment (DCE) study design. Methods: A mixed-methods systematic review was conducted from January 2005 to the end of July 2020 and the search strategy was applied to five different databases. The initial selection of articles that met the eligibility criteria was independently made by one researcher, two researchers verified the accuracy of the extracted data, and all researchers discussed about relevant variables to include. Reporting of this systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the Mixed Methods Appraisal Tool (MMAT) was used to assess the quality of the study. A qualitative synthesis was used to summarize findings. Results: From a total of 928 articles, 11 (qualitative [n = 5], quantitative [n = 3] and mixed-methods [n = 3] design) were included, and 25 attributes were identified and grouped into 13 categories: Accessibility, Distance, Interaction, Technology experience, Treatment mode, Treatment location, Physician contact mode, Physician contact frequency, Cost, Confidence, Ease of use, Feeling safer, and Training session. The attributes levels varied from two to five. The DCE studies identified showed the main stages to undertake these types of studies. Conclusion: This study could guide the development of interview grid for individual interviews and focus groups to support a DCE study design in the TR field. By understanding the characteristics that enhance patients’,preferences, healthcare providers can create or improve TR programs that provide high-quality and accessible care. Future research via a DCE is needed to determine the relative importance of the attributes.