جستجوی مقالات مرتبط با کلیدواژه "structural equation modeling" در نشریات گروه "کشاورزی"

Rural production cooperatives play an important role in reducing rural poverty by increasing production efficiency and providing services that governments are unable to provide for poor people. This research aimed to investigate the 12 components of the Legatum Index improving the welfare of rural households that are members and non-members of rural production cooperatives in Miandoab Township.

The present research was conducted using a survey and descriptive-correlational methodology. The size of the target population includes 17493 rural households, members and non-members of rural production cooperatives, and 377 households were randomly selected. Questionnaire was the main tool for data collecting. Validity of the questionnaire was confirmed by a panel of agricultural extension and education specialists at Tarbiat Modares University and its reliability was confirmed by calculating Cronbach’s alpha coefficient. To investigate the components of improving the welfare of rural households and checking the goodness of fit index, confirmatory factor analysis and structural equation modeling were used. Data were collected through structured interviews and analyzed using SPSS and LISREL software.

The results showed that there is a significant difference between member and non-member rural households in terms of welfare component status. So in the components of safety and security; individual freedom; governance; social capital; investment environment; entrepreneurial conditions; market access and infrastructure; economic quality; living conditions; sanitation and health; and education; there was a significant difference between member and non-member households, and only in the natural environment component, no significant difference was seen.

Rural production cooperatives played an effective role in improving the welfare of rural households in Miandoab City, and its average was calculated as 3.56; which shows the positive effect of cooperatives in improving the overall welfare of rural households. In this regard, it is suggested to provide entrepreneurship training to increase agricultural production, diversify the rural economy, and create the necessary foundation for increasing wealth.

Supplying fresh water is one of the issues of humanity today and among the concerns of the United Nations and the FAO. Due to sudden changes in freshwater supply and demand patterns in the current world, its supply management is followed as a challenge. The purpose of this research is to design a conceptual model and structuring of fresh water supply chain using the combined approach of soft systems methodology and structural equation modeling. By conducting an open interview and posing a single and comprehensive question to 20 active experts and experts in a snowball manner, and then the role of researchers in system placement, the model will be presented. Qualitative model extraction was done with the SSM method and then in the quantitative part, the factors involved and identified by this method were measured in the form of hypothesis generation by researchers and their testing in PLS-SMART software, the findings showed that if the fresh water supply chain is considered as a system, The input and supply of this high-quality water system, rain and flood; disruption in the processing and analysis of this stakeholder tapping system; control for culturalization as an influencing and modulating factor of this system; Multiple weather, policy instability, natural disasters as environmental and political factors; The policy of order and quantity consumption and quality control to shape the cultural control; disturbing demand and output in this logistics distribution system are water wastage and prediction of wrong consumption and tax evasion and finally the optimal achievements of the water footprint identification model, analysis of water sustainability issues and water shortage control.

The following research aims to provide a structural model for the development of essential soft skills in agricultural students. In this regard, a mixed approach (qualitative-quantitative) was used. In the qualitative part of the research, the data was collected through semi-structured interviews with 19 Participants (faculty members of agricultural majors) who are expert in the subject of research. Participants were selected using purposeful and snowball sampling methods. In qualitative phase, "grounded theory strategy" was used to design the initial model of the research. In the quantitative part of the research, after confirming the reliability and validity of the instrument, data were collected from 384 of the senior students of agricultural majors. In order to evaluate the research model, Structural equation modeling with partial least squares approach was used. The results of the research confirmed the research model. Based on this model, the factors affecting on essential soft skills and essential soft skills consequences for agricultural students were clarified.

Paying attention to the needs and wants of consumers is the first step to develop the market of organic products, because recognizing consumer behavior and examining the factors affecting it has a very important role in the success of any economic system. Therefore, this study aimed at examining the intention to buy organic food in the critical situation of the existence of the corona virus and risk perception posed by it as one of the factors affecting the consumer's intention to buy using the theory of planned behavior. For this purpose, the required data and information were collected in 2020 through field surveys and completing a questionnaire. The statistical population of the study included all the organic food consumers in Torbat-e Heydarieh county of Iran. Based on Cochran's formula, the sample size consisted of 210 people. Stratified random sampling method was used for sampling and selecting the individuals in the studid community and structural equation modeling was used for data analysis. The results showed that the correlation coefficients of the organic food consumers' risk perception of corona virus with their attitudes, subjective norm, perceived behavioral control and anticipated fear were 0.222, 0.65, 0.625 and 0.592, respectively and the consumer's attitude (0.452), risk perception (0.268) and anticipated fear (0.101) had the greatest impact on the intention to buy organic food. Therefore, by introducing the benefits of organic products through mass media, people's attitudes towards organic products can be changed; also, by informing the people of the society about the risk of the corona virus, it is possible to create the intention of placing organic products in the consumption basket of the household.

The main purpose of this study was to explain the factors affecting the adoption and development of durum wheat cultivation in rural areas of five provinces of Fars, Khuzestan, Kerman, Ilam and Tehran in Iran using structural equation model. The required data were collrcted through a questionnaire, the reliability of which was determined by Cronbach's alpha coefficient and composite reliability index (CR); and the extracted mean variance index (AVE) was used to determine the convergent validity of the components. The statistical population of the study included all wheat farmers in the mentioned provinces. Statistical sample size was determined as 274 people using Krejcie and Morgan sample size table and statistical samples were selected using multi-stage sampling method with proportional assignment. The results indicated that the studid indices were desirable. Data analysis was performed in a structural equation modeling method using LISREL8.5 and SPSS22. The study results confirmed the positive and significant effect between the explanatory components affecting the willingness to adopt durum wheat cultivation; in addition, the structural equation model predicted, in total, 47 percent of the variable variations in the tendency to adopt durum wheat cultivation. Finally, the results of this study are expected to be useful in developing strategies for extension and development of durum wheat cultivation. In addition, this research can be useful for breeders to breed varieties appropriate to the wheat farmers` conditions and needs.

Present study aimed at designing a model for the technical development of greenhouses and analyzing its influencing factors through the survey of 1300 greenhouse owners in Pakdasht county. Based on the Cochran's formula, the sample size was estimated to be 150. To increase the accuracy of access to respondents, stratified random sampling technique with proportional assignment was employed. The face validity of researcher-developed questionnaire was confirmed by a panel of experts. Cronbach's alpha coefficient values for the variables ranged from 0.70 to 0.93, indicating acceptable reliability for the instrument. Partial least squares structural equation modeling using SmartPLS2 was used to validate the designed model. The results showed that the two factors of human capital and access to technical infrastructure were the most effective factors in the technical development process of greenhouses. The three variables market access, investment-credit, and cost-benefit in light of government support have been able to affect the level of technical development of greenhouses by improving the level of access to technical infrastructure. Educational-extensional programs and government support have also led to an increase in the level of human capital and, indirectly resulted in the technical development of greenhouses. Generally, the independent variables could account for 42 percent of the variance of greenhouses' technical development. Finally, it can be concluded that the development of technical infrastructure, human capital, market access, investment, extension programs, and appropriate government policies can lead to the technical development of the greenhouse.

Creating employment and improving entrepreneurial space processes in rural areas are one of the essentials of rural development program. This study aimed at providing a model for improving rural entrepreneurship development in Shazand County of Markazi province of Iran. The statistical population of the study included 900 rural entrepreneurs in the county. Random sampling method was used to select subjects for the study. According to the Krejcie-Morgan table, a sample of 265 rural entrepreneurs was selected for the survey. The required data were collected through a structured questionnaire, the validity of which was confirmed by university professors and entrepreneurship experts and its reliability was performed by pre-test. Cronbach's alpha coefficient for the variables and research structures ranged from 0.71 to 0.918. The relationships between the items and structures were analyzed using SPSS22 and Smart PLS3 statistical software. Then, the relations between educational, economic and institutional factors and the rural entrepreneurship development were investigated in a structural equation method. The results showed that the GOF criterion was 0.389, indicating that the model for improvement of rural entrepreneurship development was suitable. According to the model, respectively, the institutional factor over the economic factor and the educational factor over the institutional factor had the highest factor loadings; in other words, for the development of rural entrepreneurship, the paths indirectly affecting the entrepreneurship development should be considered. The results also showed that all three educational, economic and institutional factors affected the entrepreneurship development, but the economic factor could be considered as one with the most direct impact on the rural entrepreneurship development.

One of the important indicators in urban planning is the attention to the quality of life of the citizens. Because, growth and improvement of the quality of life affect other dimensions of development in the cities and villages and it paves the way for development and progress. Assessing the residents' satisfaction with the living environment can help assess the policies, rankings of places, and formulate strategies for urban and rural planning and management. Present research studied the satisfaction of residents of Mohammad Abad, Ali-Abad, and Yazdel villages in Aran-Bidgol district. The sample size of the study was 291 villagers. The main data collection tool was a researcher-made questionnaire and the statistical analyses and structural equation modeling have been done using AMOS and SPSS software. A single-sample T test was used to analyze the data and determine the status of quality of life indicators. T-test results showed that the social, economic quality, and physical-environmental and service-related indicators are at un-desirable, semi-desirable, and desirable levels, respectively. Structural equation modeling was also used to assess the components of quality of life. The results of the second-order confirmatory factor analysis indicated that paying attention to the social indicator in the studied villages might increase the life quality, economic, physical, service, and environmental indices by 0.87%, 0.82%, 0.77%, 0.26%, and 0.23%, respectively.

Urban agriculture is a method for reducing vulnerability of the world's urban population in the face of ecological changes. The most important functions of urban agriculture are including energy management and reduction of product transfer, urban waste management, improvement in the quality of soil and water and cities air, improvement in the quality of food and food security, managing unexpected situations and dilemmas, and finally improving the status of citizenship and appearing desirable behaviors of citizenship. The aim of this study was to determine the capacities of urban agriculture from the perspective of agricultural students of Tabriz University. This study was applied and descriptive research in terms of data collection. The population of the study consisted 845 students. The sample (n=148) was selected using systematic random sampling method by Cochran's formula. For examining the reliability of the questionnaire a pre-test was conducted. The values of Cronbach's alpha coefficient for different concepts of the questionnaire varied between 0.81 – 0.92. The data was analyzed using SPSS 22 and Smart PLS software. Results showed that the greatest loading factor (0.898) and T statistics (39.441) are related to the urban agriculture capacity in using surface water resources to feed underground water reservoir.

The environmental impacts of pesticides, genetically modified organisms and other chemicals used to increase agricultural production have raised consumers' concerns about the quality and safety of agricultural products. And now, with the increase of environmental awareness, it has criticized modern agricultural activities. These factors have encouraged consumers to consume organic agricultural products. Way of producing the organic products can increase the production costs and, finally, increase the total price of these products. So, consumers should pay more for these products than the inorganic ones. In spite of higher prices of these products, consumers are increasingly tending to consume organic products. So that, consumers tend to pay more for better and more organic and safe agricultural products. Several factors influence the consumer payment preferences for organic products. In this study, these factors are classified into four groups and their impacts on consumer preferences are examined.

This study has used the Structural Equation Modeling (SEM). Structural Equation Modeling (SEM) is a powerful collection of multivariate analysis techniques, which specifies the relationships between variables through the use of two main sets of models: Measurement model and Structural model. Measurement model tests the accuracy of proposed measurements by assessing relationships between latent variables and their respective indicators. The structural model drives the assessment of the hypothesized relationships between the latent variables, which allow testing the statistical hypotheses for the study. Additionally, SEM considers the modeling of interactions, nonlinearities, correlated independents, measurement error, correlated error terms, and multiple latent independents that each one is measured by multiple indicators. Unlike conventional analysis, SEM allows the inclusion of latent variables into the analysis and it is not limited to relationships among observed variables and constructs. It allows the study to measure any combination of relationships by examining a series of dependent relationships simultaneously while considering potential errors of measurement among all variables. SEM has several advantages over conventional analysis, including greater flexibility regarding assumptions (particularly allowing interpretation even in the face of multicollinearity). SEM allows the use of confirmatory factor analysis to reduce measurement error by testing multiple indicators per latent variable while offering superior model visualization through its graphical modeling interface. Structural Equation Modeling include six steps (data collection, model specification, identification, estimation, evaluation and modification). In the present study, the variables including marketing factors, awareness and knowledge, demographic characteristics and attitudes towards organic products are considered as latent variables that the relationship of these variables with the payment preferences is investigated. In order to collect required data, a researcher-made questionnaire and simple random sampling method has been used.

Results indicate that given the significance of factor loadings, the indicators (observed variables) such as packaging, brand, advertising, discounts and shopping incentives, familiarity with different types of products, way to get information, familiarity with organic agricultural product stores have the required accuracy to measure latent variables. Regarding the model fitting indexes and being model values in the acceptable range, we can say that the measurement and structural models fit well with the data. The results of structural model and hypothesis testing show that awareness and knowledge, demographic characteristics, attitude towards organic products have a significant effect (0.27, 0.59 and 0.21, respectively) on consumer payments preferences. In other words, increasing the awareness of consumer about organic products, increasing household size and income, the positive attitude of consumers towards the characteristics of organic products would increase consumer payments preferences. Also, marketing factors have a significant effect (0.68) on the attitude toward organic products. So that, marketing factors including packaging, brand, advertising and discounts and shopping incentives have a positive effect on the attitude toward organic products. Therefore, hypotheses 2 through 5 are supported.

The Findings indicate that increasing the awareness of consumer about organic agricultural products, increasing household size and income, the positive attitude of consumers towards the characteristics of organic agricultural products will increase consumer payments preferences. Therefore, it is suggested that the relevant authorities take serious action to inform about the properties and nutritional value of organic agricultural products, the differences in the labels of food products, and the existing stores supplying of organic products. Also, it is recommended that the numbers of organic supply stores are boosted, especially in areas where high-income people live.