Organic agriculture is one of the sustainable farming systems that emphasizes economic, social, and environmental aspects to achieve sustainability targets. This study aims to identify the economic, social, and environmental factors affecting organic product production from the perspective of experts and 150 farmers in Jiroft County. The results revealed that low government financial support for organic farmers (average rating of 3.8133) is the most effective factor, while lack of adequate marketability (average rating of 2.6733) is the least effective factor among the barriers to achieving organic agriculture. from the farmers' perspective. According to experts, organic farming serves as a tool for improving public health conditions, (average rank of 11.66), which it is determined as the most effective factor. However, it does not significantly contribute to self-sufficiency in agricultural production, with an average rank of 6.07, being the least influential factor among the factors affecting organic farming. Among the average ranks of the components of influential factors in organic farming (educational, economic, social-managerial indicators), the lowest ranking is the government's financial support for organic farmers (average rank of 3.13), making it the most influential. Whereas, the lack of suitable marketability with an average rank of 2.67 is the least influential factor among the factors affecting organic farming. Furthermore, the results show that holding promotional and educational classes has a positive and significant impact on the acceptance of organic cultivation, as following the recommendations of promoters and having the necessary education can increase production and reduce costs.

In contrast to the classical discrete choice experiment, the respondent in a rank-order discrete choice experiment, is asked to rank a number of alternatives instead of the preferred one. In this paper, we study the information matrix of a rank order nested Multinomial Logit model (RO.NMNL) and introduce local D-optimality criterion, then we obtain Locally D-optimal design for RO.NMNL models in the discrete choice experiment.

Small area estimation methods have been considered in various fields, especially medicine, agriculture, economics, social sciences, and political Science. These methods have many applications in providing reliable statistics for small-sample or non-sample statistical areas. In estimating the small area, there are two approaches: the basic design and the basic model. In this paper, a model-based approach to labor force indicators is considered using a Multinomial mixed Logit model. The practical application of the method proposed in this article is to estimate the total number of employees, unemployed and unemployment rate using household income and expenditure data for Semnan province by cities; Semnan, Shahroud, Damghan and Garmsar concerning the period 2011-2016. Finally, we have found the estimates of unemployment rate for Garmsar (9.14), Semnan (9.84), Damghan (11.29), and Shahroud (12.40) in 2016. The more distance from Tehran (the Iranian Capital), the more is the unemployment rate!

Identifying the factors that contribute to injury as a result of crashes will help policy makers and road designers implement countermeasures, which could reduce crash injury severity, and cost. In result, objective of this study is identifying factors are more likely to contribute to crashes severity. Today, Researchers have utilized mathematical and statistical modelingschemes to solve this complex road-safety problem. For this, discrete choice modeling is widely used to model injury severity of the crash. From the models, factors contributing to the injury severity are identified. MNL is the most prominent discrete choice model for modeling crash severity. For modeling, the data of a 5-year period of crashes occurred at the rural roads of Ilam province has been used. The input variables of the model were selected after a significance evaluation test. These variables included Age, Speed, Alcohol, Head-on, Airbag, Ejection, Seatbelt, following too Close, Gender, and Curved. After selecting the variables, the accuracy of the model was also studied. To validate the model, the likelihood ratio and the percent correctly predicted by the model at each crash severity level were used. After evaluating the model accuracy in the prediction of accidents severity, it was found that the model provides acceptable results for evaluating crashes severity, and it was found that except curve and following too close variables, all selected variables contributing in crashes severity.

This study aimed at investigating air travellers’ behaviour with regard to choices for ground access to Imam Khomeini International Airport. The choices included subway, bus, carpooling, taxi, private car (parking) and private car (car drop-off). Data collection for this study was done during three days in summer, 2014, and Multinomial Logit modelling was employed for this purpose. The survey was administered as a face to face interview in Imam Khomeini International Airport, which is located in Tehran, Iran. A total number of 257 questionnaires were collected, with the degree of validation being 34%. The most important results of this research indicate that the majority of imam Khomeini passengers have a high income(%90of them have 1. 5 million tomans per month or higher) and car ownership(%92 of them have at least one car in their household). Considering that these passengers don’ t have intention for using metro, with increasing the travel time, public transportation costs (e. g. parking cost) and improving metro service qulity (e. g. increasing the reliability and decreasing the travel time), it may be possible to absorb them to use metro.

The current study attempted to investigate the climatic factors impacts on land use change between annually crops groups including cereals, beans, industrial crops, vegetables, cucurbits and forage crops in Iran counties. To doing this, agricultural data during 2012-2013 and climatic data in 1391 were used. To estimating of spatial fractional Multinomial Logit model, the agricultural and climatic variables were matched with geographical data and 336 counties were studied regarding available data. According to the results, industrials crops cultivation area shares have positive spatial dependence and increasing of industrials crops land shares in each county increases industrials crops land shares in nearby counties. Considering estimated marginal effects, one degree temperature increasing raises cereals, vegetables and cucurbits land shares 1, 0.1 and 0.2 percent respectively and decreases beans land share 0.3 percent and one millimeter rainfall increasing decreases vegetables land share 0.008 percent. So, The ongoing process of climate change, specially temperature increasing will increase cereals, vegetables and cucurbits land shares and will decreases beans land share in future years. Therefore, to meeting the part of future population food needs, taking of adaptive strategies for beans is more advised comparing to other annually crops.

Nowadays, marketing is considered as one of the most important parts of all manufacturing and service activities. In order to reach more share of goal market, different companies always update and change their marketing policies. These companies have to know that different customers impressed by different marketing policies and them, they should choose most suitable policies for one goal group. The other words, they have manage their cost beside managing market and income. Applying Multinomial Logit model and collecting data form 201 food customers in Mashhad in 2012, the current research tries to investigate effective factors on effectiveness of each advertisement method. The results show that married people, high-income ones, youth, women, educated people and larger families are more affected by media and sellers. In addition these results indicate that men, aged, single, low-income and low-literate people are more affected by their friends.

In this study, the influencing factors on farmers' participation in use of soil and water conservation practices were investigated using the farmers' experiences in Shahroud river basin. For achieving this goal was used from Multinomial Logit model. The required dates are related to year 2011-2012 that by completing the questionnaire from 138 sample farmers were collected. To select the sample farmers were used of stratified random sampling method and Cochrane formula. The results showed that only 42.7 percent of farmers in Shahroud river basin employ conservation practices moderately. Logit regression model results showed that education, slope of lands, knowledge of conservation practices, the annual gross income, receiving of grants, participation in promotional classes have positive and significant effects and age and employment in non-agricultural sector have negative and meaningful effects on the probability of farmers' participation in use of soil and water conservation practices. Multinomial Logit model in high confidence level by likelihood ratio test statistics with 30.57 for mechanical practices, 19.68 for non-mechanical practices and 24.32 for management practices was significant. The maximum probability value is equal to 0.065 and for non-mechanical practices was obtained.