International Journal of Agricultural Management and Development
Volume:7 Issue: 3, Sep 2017

The purpose of this study was to identify factors which affect rural women's participation in rice cultivation (RWPRC) in Mazandaran Province, Iran. The population of this research consisted of all rural women in Mazandaran Province, Iran. By using a multi-stage random sampling, 300 rural women were selected as statistical sample. The research instrument was a structured questionnaire including some close-ended questions whose validity and reliability were confirmed by a panel of expert and through a Cranach’s alpha test (α= 0.86), respectively. The descriptive results indicated that RWPRC was close to a moderate level. Furthermore, it was shown that the main reasons for rural women's participating in rice cultivation were helping family economy, obtaining extra income, and gaining production surplus, in the order of importance. In addition, these results illustrated the highest RWPRCs were in selecting seed, transplanting and Preparing pre-germinated seedling storage, respectively. Moreover, the findings showed significant relationships between RWPRC and some of its individual and professional characteristics. Finally, the results of the multivariate regression analysis revealed that 42.9 % of variability in RWPRC stems from household income, family size, and land size under rice cultivation. Finally, it is recommended for extension organizations to give attention to the role of gender in agriculture for better extension planning.

While migration is a basic element of population dynamics in most societies, in Iran, rural-urban migration is a particular concern of both social scientists and policy makers. Rural-urban migration accounts for over half of the growth of most Iranian cities. On the other hand, this movement is often cited as having negative effects on rural area, including a shortage of supply of agricultural labor. It is becoming common to blame rural-urban migration among young people on factors such as education and employment opportunities. This research examines the psychological factors influencing the intentions and decisions of rural young people aiming to migrate to Khuzestan Province. This study used the extend theory of planned behaviour. A questionnaire was developed using the latent variables of attitude, subjective norm, perceived behavioural control, behavioural intention, community satisfaction, and youth personal characteristics. The face and content validity of the questionnaire was confirmed by a panel of experts. The questionnaire’s internal reliability was investigated using the Cronbach’s alpha coefficient. All scales indicated a good-to-excellent reliability index (0.75–0.85). Samples of young people were identified through a multi-stage, stratified random sampling strategy from two groups (young people who are ‘well educated’ and those who were not). A total of 163 valid questionnaires were analyzed. Our results showed that adding community satisfaction as additional construct to the original Theory of Planned Behavior could significantly increase the explanatory power of the basic model. Hierarchical regression analysis showed that attitude, perceived behaviour control, as well as community satisfaction can predict 51.3% of variances in migration intentions.

The study investigated the effect of Community-Based Paid Extension (CPE) on vulnerability reduction of smallholder dairy farmers. Randomly sampled 255 farmers were interviewed together with 15 key informants’ interview. Both statistical analysis and thematic approach were employed to achieve triangulation. In about 68 % of cases, CPE reduced vulnerability to a degree experienced as ‘moderate’, whereas 20 % of them experienced a ‘high’ reduction in vulnerability. The CPE has addressed wide ranges of vulnerability of smallholder dairy system. The regression analysis confirmed the importance of sustainable and frequent paid extension service at community level. Others factors such as education level of the farmers, use of different interpersonal and mass extension media, as well as positive change in livelihood assets also significantly influence vulnerability reduction of the smallholder dairy farmers. CPE deserves dissemination throughout the country and seeks special dairy extension policy organized around it for rapid rural development.

In this paper, the authors present new indices for estimating technical change, return to scale, and TFP growth, as well as its decomposition. These indices, Modified General Index (MGI), Generalized Modified General Index (GMGI), and General Time Trend index (GTTI), are generalization of General Index approaches. These approaches were used for productivity decomposition of Iran's barely production across the period 2000-2012 in 20 provinces. To select the best approaches, estimated TFP growth of TT, GI, MGI and GTTI are compared with Divisia Index. Results show that differences between Barley TFP growth of TT, GI, MGI, and GTTI approaches with Divisia Index are 39.12, 17.94, 9.71, and 1.61 percent, respectively. The findings revealed that MGI method is appropriate when time series data or panel data with limited cross-section data are used. In addition, when only need to compare periods of time that are not regular (for evaluation plan or policies), it is suggested GMGI method. When time series data or panel data with limited cross section data are used, and there is a trend in every period, the GTTI method is recommended for estimating technical change, return to scale, and TFP growth.

The main purpose of this study was to analyze the effective solutions in the field of waste management in municipalities. The statistical population in this survey –based study consisted of the citizens that lived in Orumiyeh city in West Azerbaijan Province. By using Cochran formula, sample size was estimated to include 180 people. The data collection tool was a questionnaire. The reliability coefficient of the questionnaire was obtained by a Cronbach's alpha that turned out to be 0.87.Results showed that a positive and significance relationship exists between the transport collection and landfill management solution, expense management solution, executive management solution, the strategy management system, as well as the importance of waste management. Also in addition, multi regression results shows that about 55.9 percent of the solid waste management system is determined by variables such as collection and transportation of waste and landfill, executive management, costs management, and improvement of the management system of the organization.

The purpose of this study was to identify external factors affecting strategic management in agricultural knowledge and information system and to examine their relative importance from experts’ point of view. Five factors were identified based on the interviews, examination of relevant literature and previous researches; In line with that, a questionnaire was developed to suit this purpose. Face and content validity of the research instrument verified by the research committee. To determine the reliability of the instrument, a pilot study was conducted with 30 Agriculture - Jihad Organization personnel from Qazvin Province. The reliability coefficient (Cronbach’s Alpha) was computed 0.95, which indicated that the questionnaire had a high reliability index. External factors consisted of sociocultural, policy, economic, technological, and ecological factors. The statistical population was consisted of line and staff experts of Agriculture Organizations of Alborz and Tehran Provinces (N=161). Data was analyzed by SPSSwin20 software. The results showed that sociocultural, economic, ecological, policy and technological factors were the most important external factors affecting strategic management in agricultural knowledge and information respectively.

This study aimed to investigate the personality characteristics related to entrepreneurial spirit of rural women. The statistical population of the study included rural women in the central district of Nimrooz County in Sistan and Baluchistan Province (N=406). Krejcie and Morgan Table was used to determine the sample size. To this end, 186 participants were selected through stratified random sampling with proportional allocation. Data were collected by a questionnaire that validity was confirmed via face validity procedure and its reliability was measured by calculating a Cronbach's alpha coefficient. SPSS software was used to analyze data. The results showed that more than 50 % of rural women were strong in terms of balanced risk taking, internal locus of control, need for achievement, mental fluency, tolerance for ambiguity, daydreaming, and innovation. Yet, around 30 % of rural women were weak in terms of balanced risk taking, mental fluency, independence, and innovation. Furthermore, 17 % were weak in terms of daydreaming and challenging. The results of one sample t-test also indicated that 10 dimensions of rural women's entrepreneurial spirit were significantly higher than the average. Therefore, in order to increase rural women’s entrepreneurial spirit, it seems necessary to strengthen such characteristics as balanced risk taking, innovation, independence, mental fluency, challenging, and daydreaming.

This study aims to segment the market based on demographical, psychological, and behavioral variables, and seeks to investigate their relationship with green consumer behavior. In this research, self-organizing maps are used to segment and to determine the features of green consumer behavior. This was a survey type of research study in which eight variables were selected from the demographical, psychological, and behavioral dimensions. Data were gathered through researcher-made questionnaire and distributing it among the statistical population (Supermarket Chains in Rasht city). The sample size was 392. The result showed that among the demographical variables, age, sex, and education had a direct contribution with green consumer behavior, whereas income had an adverse relationship with that. Psychological and behavioral variables including personal values, religiosity, environmental knowledge and attitudes, and personal habits are key predictors of green consumer behavior. The results identified four segments, which were called intense greens, potential greens, selfish darks, and intense darks. Green product marketers and producers can determine the target market using the results and employ an appropriate combined marketing strategy for consumer's based on their respective features.

In West Africa, low adoption of agricultural innovations by farmers has been partly due to the complexity of the innovation structure or new knowledge beyond the farmers’ socio-economic adaptive capacities. Different attempts have been made to improve cocoa beans quality in Nigeria among which was the recommendation of ‘improved cultural practices’ or ‘best known practices’ (ICMP). This had recorded little success because of the complexity and enormity of the ICMP. The present study, therefore, made an attempt to resolve this, in the major cocoa growing states of Nigeria, through farmers-researcher participatory approach with the aid of interview guide. Collected data were analyzed using descriptive statistics and the Principal Component Analysis procedures in SPSS to identify the minimum essential practices out of the overall ICMP for sustainable cocoa production. The result showed that cocoa farmers practiced 47 activities recognized as ICMP which were grouped as nursery, on farm, harvesting or post-harvest activities. The highest overall percentage use of any of these activities was 3 %, while the least being smaller than 1 %. It was found that 13 out of 47 activities contributed 71.45 % to the overall ICMP, whereas the current cumulative percent use of these 13 activities was 28 %. The individual percent use of each of the 13 activities was about 3 %. The highest contributors among the 13 activities were coded ba1 and ba11 while the least was bb4. Efforts to intensify the use of these 13 activities rather than the 47 activities should be encouraged among farmers for sustainable and high quality cocoa production.

In crop insurance design, the yield guarantee and the premium are very important parameters, both of which depend upon the yield distribution. Accordingly, the accurate modeling of yield distribution is essential for designing crop insurance contracts. This study employs historical county-level yield data for irrigated and dry wheat in East Azarbaijan Province, Iran for 1975-2013 to evaluate the effects of five alternative parametric distributions and generate the area yield crop insurance premiums. Results indicated that, in almost all cases, the premium rates with alternative distributions significantly differed from each other and that the beta distribution fitted the data the best except for some series for which the weibull distribution was the best. The results showed that premiums for wheat vary from 246,000 IRR per hectare in the coverage of 65% for Miyaneh to 460,000 IRR per hectare for Tabriz, and for dry wheat they vary from 265,000 IRR per hectare for Tabriz to 680,000 IRR per hectare for Maragheh. Moreover, it was found that the calculated premiums were less than traditional premiums, which would be affordable for both insured and insurers. The insured will pay lower premiums, and because the new methods are used to calculate the indemnities in this contract, and therefore there is no need for attending in individual farms to calculate the loss; it will be useful for the insurers, too.

By moving societies toward globalization and the expansion of competition in the industrial product market, human resource efficiency more than ever has become the determining factor in the competitiveness of industrial products in domestic and foreign markets and thus the profitability of the industry. The main objective of this study is to identify and explain the factors affecting the efficiency of human resources in the processing industry (rice) in Guilan Province. The research method is descriptive and analytical. The study sample consisted of officials and personnel working in rice mills that have at least a high school diploma and experts on rice processing industry in Agriculture Organization that, according to the relevant authorities, 3750 people in rice workshops and 130 people are working in the Agricultural Jihad Organization in Guilan Province. Out of these, a sample of 350 participants were selected by stratified and cluster sampling. To collect data, labor productivity questionnaire and ACHIEVE model containing 24 items were used. The validity of this study was estimated by a Cronbach's alpha, which was equal to 0.90 and was indicative of high validity of the questionnaire. To analyze the data, one sample t-test was employed using SPSS software. The results of the study revealed that employees had the required ability, understanding, organizational support, motivation, feedback, reliability, and compatibility. The results also suggested that there was not statistically significant difference between men and women in terms of the productivity of human resources. Human resources productivity was different between different age groups. According to the average productivity of human resources in different age categories, the average productivity of human resources among people ranging in age from 20-30 years was more likely than others. Variance analysis comparing the average of the four groups (diploma, associate degree, undergraduate, and graduate) with a significant level up to 0.05 showed that there was no statistically significant difference between people with different educational levels with the efficiency of human resources.

Production planning includes complex topics of production and operation management that according to expansion of decision-making methods, have been considerably developed. Nowadays, Managers use innovative approaches to solving problems of production planning. Given that the production plan is a type of prediction, models should be such that the slightest deviation from their reality. In this study, in order to minimize deviations from the values stated in the tea industry, two Particle Swarm optimization algorithm and genetic algorithm were used to solve the model. The data were obtained through interviews with Securities and Exchange Organization and those in financial units, industrial, commercial, and production. The results indicated the superiority of birds swarm optimization algorithm in the tea industry.