Different driver's perception in routing is one of motivations to different driver's routing models. Drivers routing are usually based on undeterminstic general costs of available routs which the fact of uncenteainity is the background of logit models. Independence of Irrelevant alternatives is the core of logit models which is not satisfied in multinominal logit models, therefore extended logit models have been extended to overhelming this problem. Great mathematical literature review of different logit and extended logit models have been investigated in this paper with its methodlogy and usage on unic Allsop and Charlsworth proposed network. Results of these various logit models have been obtained based on proposed procedure and there are evidences that various logit models tend to have same result in low and also high(about twice of low) demands. Between these levels of demand there are different results by each of these models. Beside proposed algorithm for different logit model's applications, the chance to recognize their effect on link volumes and use of volume-based link-cost models are the distictive effort of this paper. The main innovation of the paper came out by taking into account the intersections effects on rout costs and their delays as a cost to network's performance index.

The main purpose of this study is to estimate the probability of banking crisis using the second generation of early warning systems (logit models), for 13 selected high-middle income countries over the period of 1980-2016. In this regard, two types of logit models; binomial and multinomial, are estimated. The results of estimated binomial logit model show that three leading indicators of the crisis are broad liquidity ratio, stock price index and inflation, which are the main causes of crisis in the studied countries. These variables account for about 17 percent of the probability of a banking crisis. Then, to avoid post-crisis bias, the multinomial logit model is estimated. The empirical results confirm that above three leading indicators are warning. Also, among the above three variables, only stock price index variable with a probability of 12.68%, causes the economy to exit the banking crisis and change its situation from the crisis/recovery period to the tranquil period. The multinomial logit model exhibit significantly better in-sample predictive abilities than the binomial logit model.

Having a plan of crop pattern suitable to climatic conditions ensures the sustainability of agricultural production and food security and makes the capacities of each region be used properly, this possibility can be investigated and implemented in the form of policy packages and by designing targeted incentive packages and According to the needs of the farmers and then providing the packages to the farmers, they will stimulate the farmers to implement the cultivation pattern, which can play an effective role in the operationalization of the cultivation pattern in the fields by the farmers. The purpose of this study is Investigating the influencing factors on the willingness of farmers to accept incentive packages for operationalizing the crop pattern proposed by the government in Khorasan Razavi province.In this study, 283 farmers were selected using the available non-random sampling method, and the necessary data and information were collected using a questionnaire and face-to-face interview. Also, using multinomial logit regression, the purpose of the study was examined.The results of the research showed that the variables of The number of household labour, market risk, financial risk, attitude, perceived behavioral control and membership in social institutions have a positive and significant effect on the selection of the management-infrastructure package and the variables of Amount of non-agricultural income, medium-scale farmers, subjective norms, financing willingness, marital status and Enough access to Water have a negative and significant effect. Also, variables of place of residence, The number of household labour, participation and cooperation with agricultural jihad, attitude, perceived behavioral control, cultural factors and membership in social institutions have a positive and significant effect and variables of large-scale farmers, weather risk, subjective norms, behavioral intention, satisfaction with The policy and objectives of the agricultural jihad and the activity and participation in the farmers' group have a negative and significant effect on the choice of a subsidy package.

Coping strategies are a set of reactions adopted by people in food insecurity condition, a common one of which includes eating less-preferred and less-expensive foods; thus, this study tries to determine factors affecting its selection as a coping strategy by rural households in rural areas of Gorgan County in Iran. For this purpose, the primary data are utilized via a sample size of 267 rural households. Direct interviews with the people in charge of preparing food for the family members are conducted during winter and spring in 2013. In addition, the ordered logit model is used to analyze the data. The study results show that the factors like annual income, education of spouse, having an agricultural job, village distance from market and chronic illness of one of the household members affect choosing less-preferred food as coping strategy.

This study has aimed to provide a model for predicting the severity of accidents in road and rail crossings of Iran with a fresh look at the data of recent years' crashes in these areas. Although Iran has a considerably smaller number of level crossings in its transportation network, however, considering the number and severity of accidents occurring in these crossings, the importance of the safety in these points. In order to have a more comprehensive understanding of the issue of safety at the level crossings, this section looks at the statistics of traffic accidents. Currently, in many countries, including Iran, the safety of level crossing is evaluated based on the frequency of accidents occurring in them. Considering the severity of these accidents is a subject that has recently been considered by researchers. In addition to the frequency of accidents, cross-country crashes in severity can also be investigated. It is noteworthy that trains, pedestrians and pedestrians are usually associated with high severity. This method is one of the methods for identifying hazardous and risky crossings in the rail transport network. In the context of the severity of crashes in the level crossing of Iran, only one study has been done so far. The study is aimed at presenting an intensive prediction model with a fresh look at the crash data of recent years. In this study, the specifications of the 240 authorized passageways in Iran and the crash data used therein are used. In addition, the logit model is used to predict the severity of accidents. It should be noted that the data used in this study are for the years 2009 to 2013. The results of this study indicate the importance of factors such as type of vehicle, type of collision, number of carriages, street lighting and type of train and road drivers' perception of the severity of road accidents.

Appropriate planning for choosing the location of residential units by urban managers, housing construction companies, and urban and rural property organizations involves understanding the preferences of the homeowner's households in this area. The purpose of this paper is to investigate the factors affecting the choice of house quality and residential location and the extent of the impact of each of these factors on the probability of choice. Choice Experiment Method (CEM) was used to determine the factors influencing housing choice and valuation of housing features. To this end, the desired values were used based on Random Utility Theory (RUT) of a discrete Multinomial Logit Model (MNL) and randomly selected from 300 households in Isfahan city. The data were collected using questionnaires of empirical and face-to-face interviews and analyzed using EXCEL and STATA software. The results showed that the final effect of the variable of increasing the facilities and facilities outside the interior of the home has the greatest impact on the choice of housing, and then the size variable in the choice of housing is very influential. Based on the findings of this study, it was found that the preferences of different households, mainly by prioritizing residential location indicators, could be very important in urban planning.

The final energy consumption per capita in Iran in the agricultural sector is 3.4, as well for household sector is 2, besides the commercial and public sectors are 1.6, and transportation and industry are 1.4 times the global average. This is due to low efficiency in operation, high energy consumption, as well as the use of energy goods and services. The use of renewable energy in the agricultural sector, while increasing the security of energy supply, will reduce global warming, stimulate economic growth, create jobs, and increase per capita income and social justice and environmental protection in all areas. The purpose of this study is to investigate farmers' preferences for using solar energy in Sari. The Choice Experiment methods allow researchers to focus on valuing final changes as multidimensional features rather than discrete changes. Choosing between options encourages respondents to examine their preferences in detail related to different management programs. The Choice Experiment test approach consists of several steps, which include designing the Choice Experiment test, determining the sample size and method of data collection, estimation process, and modeling the Choice Experiment test. Designing a Choice Experiment test consists of five important steps which are defining attributes, determining the relevant levels, conducting an experimental design, constructing Choice sets, and measuring preferences. After determining the criteria affecting the prioritization of renewable energy, liketechnical, environmental, economic, social, and political criteria, in order to investigate the willingness to Pay of Sari farmers, a test questionnaire was designed. The criteria obtained from the review of prioritization of renewable energy were considered as the attributes of the Choice Experiment and the price attribute was added to the above criteria. A total of six technical, economic, social, political, environmental, and price attributes were considered to investigate farmers' willingness to pay. In the review of the studies and the current situation, the levels of each of the attributes were determined. To determine the levels of price attribute, these points were considered; the price of agricultural electricity per kilowatt-hour is 383 Rials, which was approximately 400 Rials for the current situation. To investigate the farmers' preferences for using solar energy, 98 questionnaires of farmers in Sari were completed in September 2019. Each questionnaire included 8 choice set cards and each card included three options, based on which, the number of observations in Sari is equal to 2352 observations. The purpose of this study is to investigate the preferences of farmers in Sari for the use of solar energy. For this purpose, the Multinomial logit, the Random parameter logit, the latent class, and the Random parameter logit latent class are used. Based on the results of the Multinomial logit method, environmental and price attributes at the level of one percent and economic attribute at the level of five percent are statistically significant, but political, social, and technical attributes are not statistically significant. The Alternative-specific Constants (ASC) in the first and second options are not statistically significant. Based on the results of the Random Parameter Logit estimation method, environmental, economic and price attributes are statistically significant at the level of one percent. Technical, political, and social attributes are not statistically significant, which shows that farmers do not make a significant difference between these two attributes. The Alternative-specific Constants (ASC) are significant in the first option at the level of five percent and the second option at the level of one percent. The results of latent class estimation show that in the first class, environmental, economic, political, social, and price attributes are statistically significant at the level of one percent and technical attribute at the level of ten percent. The Alternative-specific Constants (ASC) are statistically significant at the level of one percent in the first class. In the second class, technical attribute at the level of five percent and environmental attribute at the level of ten percent are significant, besides other attributes in the second class are not statistically significant. The most sensitive class is the first class and farmers of the second class are considered the base class. The results obtained from the Bayesian and Akaike criteria of different classes showed that the two classes have the lowest values of BIC and AIC criteria and the class is appropriate. After determining the appropriate class, the model was estimated. The results of model estimation were calculated by the Latent Class Random Parameter logit method. In the first class, environmental attributes and price are significant at the level of one percent and economical attributes at the level of five percent. Also, the Alternative-specific Constants (ASC) is significant at the level of one percent, but, in the second class, the attributes are not statistically significant. Technical, environmental, economic, political, social, and price attributes, as well as the option of status quo or the Alternative-specific Constants (ASC) in the second class, do not affect farmers' utility due to the lack of statistical significance. A comparison of the results obtained from the four methods shows that the highest value of the estimated coefficient for environmental attributes was in the latent class method and the lowest value was in the multinomial logit method; Comparison of fitted methods shows that the highest Log-likelihood is related to the latent class random parameter logit method and the lowest value is related to the multinomial logit method. Accordingly, the highest value of Akaike and Bayesian criteria is related to the multinomial logit method and the lowest value is related to the latent class random parameter logit method which is better than other methods according to the good fit criterion.

Since there are different types of transportation modes and their corresponding time cost in cities, one way for minimizing transportation cost is finding the best transportation mod out. In this paper, the factors influencing the choice of trip mode in the framework of the polynomial logit model were investigated. 384 data were obtained by random sampling of intra-city trips to Azadi Square in winter of 2017 in Isfahan. The dependent variable (traveling mode selection) has four floors: personal car, regular bus, express bus and taxi.The personal car was selected as the reference class and the other classes were compared with the reference class. According to the results, in the Logit Model, between the reference alternative and the conventional bus, the cost variables, walking time and expectation of a negative relationship and lack of access to the fastest bus, personal ownership of the car and travel time have a positive relationship with the possibility of choosing a typical bus compared to the reference alternative. In the second Logit model, between the alternate reference and the taxi alternative, the travel time, walking time and expectations of the negative relationship and the cost and ownership variables are positively correlated with the probability of choosing a taxi mode than the reference alternative. In the Logit III model, there is a positive relationship between the alternate reference and the bus of the fast-moving travel time variables, the lack of ownership of the vehicle and access to the fast-moving bus, and the cost variables, walking time and waiting time are negatively related to the possibility of choosing a bus to the alternative than the reference. The results of clustering showed that clustering increased the prediction accuracy of the model relative to the ungrouped state.

 The forest ecosystem is one of the most important natural resources of any country, which provides various functions and services for human beings. Therefore, recognizing the functions and services related to the forest and determining the most appropriate valuation method for them is of particular importance. Also, the continuation of using the functions and services of forests requires programs to protect and improve their environmental status. This issue itself requires the participation of stakeholders and finding out about their preferences for forest ecosystem protection and valuing them. But estimating the real value of some functions, ecosystem services and developing appropriate mechanisms to obtain their economic value requires economic valuation methods using non-market methods. Although there are different interpretations of the economic valuation methods of functions and services forest ecosystems but among the various valuation methods, economists have more emphasis on the value of money that is estimated through stated preferences. One of these methods to estimate the stated preferences is the Choice Experiment.

 The purpose of this study is to evaluate the preferences and willingness to pay (WTP) of native communities for the conservation of Shiadeh and Diva forest ecosystems of Babol city located in Mazandaran province using the evaluation Choice Experiment (CE) method. The Choice Experiment is a subset of the choice modeling method and the stated preference method family. Choice modeling is based on Lancaster's value theory and random utility theory. Also, Shiadeh and Diva forests are one of the green areas with all kinds of forest covers, plants and valuable trees and as one of the useful and valuable resources for the residents of the region. These forests play an important role in the lives of the forest dwellers, herdsmen and villagers on its outskirts. Also, Shiadeh and Diva forests because of the presence of natural forest ecosystem, beautiful landscapes, unique vegetation and diverse animal species, as well as special human and cultural effects, are always one of the centers of interest. This forest ecosystem is very valuable and can provide services for the residents of this area. Therefore, in this study, the statistical population of the study includes 150 native households in the villages of Shiadeh and Diva forests. In the study, research data were completed and collected by field sampling in the summer of 2020 by native communities of the region. Socio-economic variables include eight variables: age, marriage, gender, job, household size, education, income and household expenditure. The effect of these variables on the WTP of communities was surveyed. In this study, the WTP of individuals for the forest ecosystems conservation was estimated by the CE method and conditional logit model. To validate the conditional logit model, the independence of irrelevant alternatives (IIA) was performed using Hassman-McFadden statistic. Also, a multinomial logit model was used to investigate the effect of socio-economic variables on the WTP.

 In this study, the reliability of the questionnaire was calculated using Cronbach's alpha test and was obtained as α=0.87, which indicates its reliability. WTP of each household for the conservation of Shiadeh and Diva forest ecosystem services, including regulatory, habitat and information services, from the status quo to the improvement situation was equal to 1020.68, 630.25 and 1026.49 thousand Rials per month, respectively. The study results showed that WTP native communities for the forest ecosystem conservation to provide regulatory services and its improvement is the first priority, and habitat and information services took the next positions.

 The aim of this study was to evaluate the preferences and willingness to pay (WTP) of native communities for the conservation of Shiadeh and Diva forest ecosystem using the evaluation Choice Experiment (CE) method. In general, it can be concluded that regulatory services was the most important forest ecosystem services in terms of native communities in the region. Also, the final WTP of native communities' estemated at 33329.04 Rials per year (2777.42 Rials per household per month).Therefore, considering the great importance of the regulatory services of Shiadeh and Diwa forest ecosystem, such as water protection, soil protection, carbon sequestration and climate regulation, etc., it is suggested that relevant institutions such as the country natural resources and watershed management organization, the general department of natural resources of the province Mazandaran, regional water organization and agricultural Jahad organization allocate the necessary investments for the protection of Shiadeh and Diwa forests, and implementation of projects such as forest management projects, water protection, soil protection, species protection flora and fauna of the region projects, etc.