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Background: The participation of local communities is considered as one of the major factors contributing to social and economic growth and development in rangeland management. Therefore, an analysis of variables affecting their participation contributes greatly to foreseeing the needs and fulfilling the shortages of a participation program. The present paper is an attempt to investigate the impact of socio- economic variables effecting local communities’ participation.
Materials and Methods:The pilot area of the present study was Gomorgan village in Malard County (Tehran Province). Regression function was used for examining the impact of explanatory variables (socio-economic) upon participation of local communities to rangeland protection. Shazam 9 software was applied for logit regression function analysis.
Results: It was found out that the variables such as age, education, bid and importance of rangelands as livestock production inputs had negative effects upon local communities’ participation in Malard’s rangeland protection, whileincome had positive effects.
Conclusions: It can be concluded that enhancing the socio- economic condition of local community could be a useful tool to increase the success level of the conservation projects in rangeland management.

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This study examined the nature and patterns of rice consumption in Nigeria, using Kwara State as a case study. The study methodology comprised a two stage sampling technique which was used to survey 110 rice consumer households across two villages and six towns in Kwara State. Analytical tools used in the study include descriptive statistics and the multinomial logit model. The major factors that significantly influence household preferences for either a combination of local and imported rice or the imported rice only to the local rice were the income of the head of household, household size and the educational status of the heads of household, the price per unit kilogramme of rice, however, was not a significant factor. This study therefore recommends that an effort should be made to increase rice production coupled with the provision of standard processing facilities. This will help to make the local rice sufficiently more competitive thereby increasing its demand.

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Due to the rapid modernization process, we can see the inefficiency and obsolescence of urban textures in Isfahan alike the most Iran’s cities. Hence, renovation development of old textures should be one of the main goals in modernization of Isfahan. Analyzing the widespread dimensions of housing and identifying the ranking ways of different attributes of residential units by consumers is the most important step for being successful in housing projects. Since housing attributes are the non-marketed goods, we need to use non-market evaluation method to evaluate them.  In this paper Choice Experiment Method (CEM) has been used to evaluate and determine the consumer willingness to pay for various housing attributes. For this purpose, one of the old textures of Isfahan was selected and a sample of households living in that area was randomly drawn with 120 observations. Data was collected using choice experiment questionnaires and analyzed using STATA and EXCEL softwares. The results show that choice of residential unit is a function of 7 attributes including land area, quality and type of materials used in residential units, neighborhood security, access to major city centers, exemption from charge payments for construction, the amount of loan paid for construction and price of residential unit. Based on the results, the most effective variable is the land area; and residents have a high willingness to pay for this attribute rather than the other attributes.

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The objective of this study was to assess the level of knowledge of the Turkish farmers with regard to fertilizer usage. Farmers in the Kazova district of Turkey's Tokat Province were interviewed regarding their soil maintenance practices. The interview was based on a standardized questionnaire the answers being recorded at the time of interview. Simple random sampling method was used to determine the sample size of the research. According to the results, sample size was determined as 61 farmers. The fundamental question (dependent variable) was to determine if farmers have the soil in their fields analysed. The independent variables were: education level of farmers (EDU); whether the farmer shares information regarding fertilization (EI); whether the farmer sows according to the results of the soil analysis (SA); whether the farmer uses pesticides (UPI); and the level of concern the farmer has for production rate (PQ). With the exception of farmers' concern over production rate (PQ), all the independent variables had a positive effect on weather or not farmers have the soil in their fields analysed. The econometric model selected for the analysis is a binomial logit model in which the dependent variables take only two values: either 1 or 0. Cronbach’s Alpha coefficient was calculated as 0.7358.

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In recent years, consumers’ concerns about environmental and health issues related to food products have risen; consequently, the demand for organically grown products has increased. In this respect, the aim of this study was to investigate factors affecting consumers’ potential willingness to pay premium prices for organic food products in Tabriz, Iran. An Ordered Logit regression model was applied to obtain the value of willingness to pay and determine the factors affecting it. Survey results showed that about 95 percent of the respondents were willing to pay a premium; while about 10 percent of them were willing to pay more than 35 percent premium for organic food products. Results revealed that factors like "individual’s income", "family dimension", “environmental concerns" and "wholesome diet", besides "the general criteria of shopping", and "consumers’ awareness of these products’ characteristics" significantly increased consumers’ willingness to pay a premium. According to the results, married respondents as well as females were willing to pay a higher premium. In addition, those who had children younger than 10 years old, elderly, or people with family members having special disease were significantly willing to pay a higher premium price for these products. More than 80 percent of the consumers mentioned "absence of certifications and organic labels", "lack of advertisement", and "higher prices" as their most important problems in purchasing organic food products.

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Higher education attainment and labour force participation, especially among females, have been increasing for the past decades in Iran. If labour market is not flexible enough to adjust with the new trends, it may have negative effect on female education and participation rate. In this paper, we investigate the effects of higher education attainment on labour force participation, with an emphasis on female education in Iran using the data from the household budget surveys for the period 2001-2007. We use a logit model with cross section and pooled data and control for personal and household characteristics such as age, gender, marriage, and family income. Our findings show that participation rate is at maximum for middle-aged groups, and the married people are of more participation rates in labor market than current and former singles. The results also indicate that probability of labour force participation increases with the level of education especially for females and decreases with the family income.   

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The aim of this study was investigation of the factors affecting the primary choice of consumers in food purchasing in Mashhad city by applying cross section data of 201 households in 2012. In this study, 56, 30, and 14% of the consumers chose healthiness of food, price of food, and taste of food, respectively, as the primary preference in food purchase. Results of applying multinomial logit model illustrated that older respondents and females were more careful for health than young respondents and males. Also, results indicated that the households with high income and high educational levels were more likely to choose healthy foods. Moreover, respondents who had knowledge of food health were more likely to select healthiness of foods. In addition, comparison of the findings of this study with similar studies indicates that results are analogous. Based on the results of this study, some recommendations are provided for policy makers and food producers.

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 In recent decades, large investments have been made to introduce soil conservation methods, but most of these efforts have had limited success in achieving the goals. As a result, attempt to identify the factors deterring or promoting adoption of soil conservation practices is important. Therefore, this study aimed to investigate factors affecting adoption of soil conservation practices by rain-fed farmers.Data were gathered from 178 farmers of Izeh County in Khuzestan Province, Iran, during 2010 crop season. An ordered Logit regression model was applied to analyze the data. The results have revealed that farmers’ perception of soil erosion and their knowledge about soil conservation practices, farms size, and grant funding have a positive effect, while farmers’ levels of academic education and number of plots have negative effects on farmers’ adoption. To promote adoption of conservation practices, awarding grants, holding targeted training/extension classes to increase farmers’ knowledge about soil erosion, and methods of coping with it are suggested.

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One of the really important challenges facing agricultural producers is the choice of their product distribution channels. The present study is aimed at investigating the citrus marketing channel strategy and its determinants among citrus orchardists of Mazandaran using a Nested Logit model. Some two hundred and fifty two orchardists from 15 cities of Mazandaran were taken as the study samples. Four distribution channels and three nests were considered in determining the factors influencing the choice of marketing channel. Since the estimated structural parameter did satisfy the condition of lying between 0 and 1, the nested logit model was proved as appropriate for the intended application. The results indicated that the orchard distance from the nearest city, orchardist’s experience, sale time, marketing costs, the kind of product and the dominant marketing channel constitute the most important factors of distribution channel selection as regards the citrus producers in Mazandaran. According to the obtained results, by increase in the orchards’ distance from the nearest city, the producers' tendency to sell their products through channels of shorter distances from buyers also increases. Also, results revealed that the older the orchardist, the higher his/her degree of risk aversion. An estimation of binomial Logit Model for the second and third nests had consistent results regarding the marketing costs. As the marketing costs increases, the orchardist’s tendency to sell his/her products through other channels of a lower marketing cost will increase. Furthermore, results revealed that as the citrus price rises, the producers get further intended to sell their products in the market rather than selecting either the pre-sale method or selling their produce to the local dealers.

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One of the main challenges facing the Agriculture Bank of Iran regarding lending loans is the high probability of default by farmers. Several factors could be involved in this issue and should be considered in order to control and reduce the risk in the failure of repayment. This study aimed to examine the factors affecting the repayment performance of agricultural loans in the city of Maragheh in East Azarbaijan Province of Iran. Required data were obtained from a sample of 779 individual farmers who had previously received loans from Agricultural Bank during the period 2004-2008. Nested Logit Model (NLM) was applied for analyzing the data and, for this purpose, STATA software was used in the study. Results revealed that having an activity besides farming, extension of the repayment period of the loan, and large volume of received loans are the factors that had significant negative impacts on loan repayment. On the other hand, factors including high interest rates of loans, having collateral of guarantor, services received from the banks, and long term maturity period for the loans increase the probability of timely loan repayment significantly. 

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Unexpected events always occur without any alert about where or when they will happen. According to history of earthquake in Tehran, Iran, the probability of a huge earthquake occurrence (about 7 Richter) is high. The Unpredictable human behavior in disasters can affect the performance of the transportation networks. Considering the specific effects of an earthquake on the travel demand (i.e. the influx of travel demand in a short period and chaotic behavior of the users of the transport network), the issue of post-earthquake travel demand needs to be investigated. Since people travel behavior would be quite different from the ordinary situation, this research proposes a method to estimate the demand based upon the interview survey. The goal of this study is to determine the trip purposes immediately after the earthquake and the factors affecting the individuals' decisions on their trip purposes. In most previous literatures, the majority of policies which have been modeled are based on unrealistic assumed demand. Many previous studies have acknowledged that more trip purposes in response to earthquake exist but few, if any, have examined it in-depth. For example, Since an earthquake cannot be predicted, in a study conducted by Chang et al. to estimate the post-earthquake travel demand, it is assumed that people will evacuate directly from their current locations immediately after earthquakes because under the no-notice earthquake scenarios, there is no time or considerably less time for people to return home or go to other places to pick up their relatives or friends [Chang et al. 2012] while most people will return to home to rescue their family [Hara, 2013]. This research developed discrete choice (Multinomial Logit) model to represent effective factors on travel demand behavior after 2 earthquake scenarios (Strong & weak) in a workday, with 4 trip purposes (rescue and Inquiry on Safety, return-to-home, evacuation and no-action). This study investigated on travel behavior after an earthquake, based on a statistical analysis on stated preference (SP) questionnaires which were answered by 364 interviews in Tehran. The survey data indicated that, 90% of people may prefer to make trips in order to return to home or to rescue survivals after a powerful day earthquake The collected data expressed that although, it is not expected to have a problem in transportation network after a weak earthquake, the statistics from this study represented that about 35% of people will travel with different purposes because of their fear and it should be considered that despite a moderate earthquake will not destroy transport infrastructures, heavy traffic congestion will cause an emergency situation in transportation network. The goodness of fit (ρ2 statistic) of the model was obtained 0.425 that is a fairly good indicator for the discrete choice models. The model has also predicted the trip purposes in 67% of the observations correctly. The results of the model show that the most effective factors on destination choice behavior are gender, age, travel time, magnitude of earthquake, house ownership and family number. Also unrelated education to the earthquake is not effective on people travel behavior. Informing people about probable open routs after earthquake in advance would help planners for disaster management.

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This study determines the consumers’ willingness to pay for organic milk in Tehran by using Contingent Valuation Method and Single Bounded Dichotomous Choice questionnaire. Logit regression model was used to evaluate the effect of explanatory variables on willingness to pay and the model parameters were estimated by using maximum likelihood approach. For this purpose, 450 questionnaires were completed in the city by respondents who had independent income in 2012. Shazam, SPSS, and Maple softwares were used to obtain the results. According to the results, variables such as income, family’s illness history, age, educational level, distance to the shopping center, apprising respondents, organic milk quality, and the offered price had a significant effect on consumers' willingness to pay for organic milk. Overall, 80.3% of the respondents were willing to buy organic milk. The average of consumers' willingness to pay was estimated at 28,600 Rials per liter of organic milk. The results showed this product to be important for people; and this point can help producers, planners, and managers for further development of this product.

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Customer satisfaction is the most important element for developing and sustaining organizational priorities and practices. Thus, we examined farmers’ overall satisfaction with agricultural extension services and its determinants using data collected from 150 beneficiary farmers in North West Ethiopia. The findings show that about 55% of the interviewees were satisfied whereas 45% of them were dissatisfied with the extension services, implying that the program still has a lot of room for improvement. The empirical result based on ordered logit model revealed that perceived economic return, regular extension contact, family size and off-farm income were driving factors for farmers’ satisfaction. On the other hand, limited technology choices, high price of inputs, inconvenient loan system and undefined boundary between the extension service and the local politics were among the reasons given by dissatisfied farmers. Thus, from a policy perspective, the findings suggest a need to develop demand-driven extension service instead of the existing supply-driven one. Such service should be aiming to enhance the rewards from farming in order to maintain participation and farmers` satisfaction, which influence the sustainability of the extension program.

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In signalized intersections and at the onset of the yellow phase, drivers often come across a dilemma situation where they are unable to stop comfortably before the stop line or clear the intersection (without excessive acceleration) prior to the onset of the red signal phase. yellow time is designed to inform drivers about passing time and preventing extreme changes in cars' speed in timing of intersections with traffic lights. However, studies have confirmed that drivers face high level of uncertainty during yellow time. drivers visually sample their surroundings while driving so they are able to change their behavior based on other vehicles’ movements, the roadway environment and traffic signal data. This implies that drivers’ behaviors are affected by surrounding factors such as other vehicles’ headway or intersection conditions. In the dilemma zone, drivers’ decisions are influenced not only by their own condition (e.g., distance to the stop line, speed, red time)but also by the surrounding environment at an intersection. The primary goal of the research described here was to develop a comprehensive knowledge of the stopping characteristics of dilemma zone drivers at signalized intersections. Physical, traffic, timing and phasing of intersections and weather conditions are assessed factors. The research performed here involved macroscopic evaluation of driver behavior; thus, characteristics of individual drivers were not investigated as it was not feasible to determine information such as age, experience, route familiarity, and sex of each driver. This study investigates actual data of traffic cameras and central smart program in four intersections in Qazvin in which traffic lights are set up. Peak, normal sunny and rainy conditions and drivers' behavior in yellow and red times are studied using binary logit model. A field study was performed using a video-based data collection system to record several attributes related to the behavior of the last vehicle to go through and the first vehicle to stop in each lane during each yellow interval. The researchers concluded that a driver’s decision to stop or go through when presented with a yellow indication is complex but can be predicted reasonably well based on several factors. Pedestrians in streets(Coef.=-0,61241; p-value=0,0177), time passed in red phase(Coef.=-0.53836; p-value=0,0177), and headway(Coef.=-1,89062; p-value=0,0854) are the most effective factors on drivers' pauses in yellow or red phase. High speed of cars(Coef.=+0,172; p-value=0,0087) and also waiting time (red phase) (Coef.=+0,864; p-value=0,0095) are the most influential factors on drivers motion in yellow or red phases. I addition, in the situations in which drivers distance to intersection is less than one meter at the beginning of yellow phase and speed is higher than 20 m/s, passing probabilities are 74 and 90%, respectively. One of the innovations of this study is evaluating the effect of rain on the behavior of drivers. The results of model show the possibility that the drivers pass the traffic light in yellow or red phase will be increased by rising the amount of rainfall. Our results are able to inform officials about drivers' behavior at intersections with traffic lights and facilitate their control and surveillance.

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Results of traffic assignment models are the main output of transportation planning studies and decision making for future developments is based on these results. Therefore, accuracy of these models is very important. Despite the mentioned importance, comparing the models and their solving methods to estimate actual traffic volume and network performance measures is rarely considered in previous studies. The traffic assignment process has started from the simplest methods like All-or-Nothing, then it has developed using the rules and supplement assumptions such as Wardrop principles and finally it has evolved by concepts such as Fuzzy theory. Traffic assignment models can be categorized by various factors into several groups: deterministic vs. stochastic, congestion considering vs. unconstrained capacity and being equilibrium or not. The main goal of this paper is a comparative and quantitative analysis of various traffic assignment methods to estimate the observed traffic volumes. In this regard, the main questions that this study seeks to answer is as follows: 1- Do the results of various traffic assignment methods have a significant difference in terms of overall network indices? 2- Is there a significant difference in the accuracy of traffic volume estimation in various traffic assignment methods? In this study various traffic assignment methods such as All-or-Nothing, Incremental, Stochastic, User Equilibrium, Stochastic User Equilibrium and System Optimum have been examined. To compare the results of traffic assignment methods, in addition to estimated link volumes, various performance measures such as vehicle-kilometers traveled, vehicle-hours traveled, fuel consumption and air pollutants emission are also used. In this regard the city of Qazvin is selected as a case study. This city has more than 400 thousands inhabitant, near 46 square kilometers area, 113 traffic analysis zone (TAZ) and its network has 2300 directional links and 1200 nodes. The results of applying these methods in Qazvin city network show that various traffic assignment methods based on User Equilibrium, despite different assumptions, have no significant difference in estimating the overall network performance measures as well as estimating traffic volume in links (correlation between estimated and actual link volumes using all of these models is approximately 0.88). But the other methods, which do not consider equilibrium assumption and volume-delay functions, produce different results (correlation between estimated and actual link volumes using all of these models is approximately 0.70). Although estimated link volumes in some of traffic assignment models are significantly different, overall network performance measures are approximately the same. In all of assignment models the differences between estimated and actual link volumes in average are high which are not negligible (approximately 20 percent). In addition to high average error in estimating link volumes, the distribution of these errors has significantly high standard deviation (approximately 20 percent). In spite of different and complicated assumptions, models and solving algorithms in various traffic assignment methods, on basis of Kolmogorov-Smirnov (K-S) test results, the distribution of links volume estimation error is not significantly different. According to this fact, it seems that should be careful in using the results of traffic assignment models to compare and assess minor network improvement alternatives, such as changing conventional streets function to pedestrian streets, upgrading intersections to interchanges, cross section widening, traffic signals optimization and changing traffic direction in streets.

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Packaging is considered as one of the sale attractions and motives. The impacts of socio-demographic variables on the customers’ selection procedure are conceptually interesting and have several managerial interests. The present study aimed to identify the effective personal, social, and economic factors in choosing milk packaging type in the Rasht City. To this end, the options were categorized into 4 groups including “milk without packaging”, “bagged milk”, “packet milk” and “bottled milk”. Data were gathered using a questionnaire and some interviews with people. Multinomial Logit Model was used as research method. The results of Hausman test indicated that the 4 groups of milk packaging were independent of each other and, therefore, the nested structure was not required. Results obtained from model estimates showed that age, gender, family size, educational level, and income variables were statistically significant. Among the variables, “family size” negatively affected selection of other alternatives over the reference group (bagged milk), while other variables had positive effect. Finally, marginal effects were calculated for all variables and for each group. After calculating the marginal effects for all variables of each group, it was observed that the dummy variable "gender" had the most marginal effect in packaged milk group.
 

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