I Investigating and Analyzing the Challenges of Human Resources in the Agricultural Sector of Rural Areas of Malayer

After many years of experience, the world has realized that countries need specialized motivated human resources in order to be among the leading countries, and human resources is considered the most important factor determining and accelerating countries' growth and development process. Agriculture, industry and services are of particular importance because they are three main sectors of the economy of each country.This study sets out to identify the factors affecting the human resources (HR) challenge of the agricultural sector in rural areas of Malayer and the priorities and actions that are necessary to maintain the human resources in the agricultural sector of rural areas and consequently achieve the sustainable development of villages and the whole country and supply sustainable food resources and livelihoods. In other words, it seeks to determine the factors leading to a challenge in the human resources of the agricultural sector of rural areas in the central district of Malayer. For this purpose, the following hypotheses are formulated:• Economic factors, including lack of employment due to inappropriate policies in rural areas have led to the greatest HR challenge.• Service-related and infrastructural factors affect the HR challenge of the agricultural sector in rural areas of Malayer.• Socio-cultural factors affect the HR challenge of the agricultural sector in rural areas of Malayer.

This study was conducted through a descriptive - analytical method in several stages. The desk-documentary research method was used in the first stage, which was related to the theoretical part of the research. The data were collected in the second stage using field methods such as observation, interviewing, surveying, and attending residential areas. The third stage was related to the analysis of data and providing suggestions. The statistical population of the study was 73 villages of the central district of Malayer. Due to the large number of population, 100 households from 5 villages in the center of the district were selected as the research sample. The main instrument of the research was a researcher-made questionnaire, the validity and reliability of which were confirmed by using the views of a panel of experts, calculating the Cronbach's alpha coefficient and other approved methods. Data were analyzed in SPSS. Thus, considering factors such as administrative political citizenship, distance from the city, population, and cultural differences, 5 villages of Joozan, Joorab, Aznav, Mehrabad and Alavi, as the centers of the rural districts of Malayer, were selected as the sample. The heads of the households under study were the surveyed population of the study. For a more accurate analysis, the number of households was determined using quota sampling from among the households of 5 sample villages, and finally, a survey was conducted using the simple random sampling method. This part contained descriptive and analytical (inferential) statistics. In the first part, the demographic characteristics, as well as the variables related to the research hypotheses were presented in descriptive statistics tables and figures. In the analytical statistics part, Kolmogorov-Smirnov, one-sample t-test, Friedman, Kendall's Correlation, Chi-square and Eta tests were used. SPSS was also used to analyze the extracted data.

Economic factors such as lack of employment due to inappropriate policies in rural areas have given rise to the greatest challenge in human resources with the highest mean score. This suggests that these factors are the most important factors in creating HR challenges in rural areas in the central district of Malayer, and the next ranks belonged to socio-cultural factors and service-related and infrastructural factors, respectively. Moreover, the significance level obtained from the Chi-square statistic from Friedman test indicates that the confirmation error percentage of the significance level of the above test is significant at the 95% confidence interval. It can, therefore, be said that economic factors such as lack of employment due to inappropriate policies at the village level have created the greatest challenge in human resources. Therefore, the first hypothesis is confirmed and the null hypothesis is rejected.H2: Service-related and infrastructural factors affect the HR challenge in rural areas. The parametric one-sample t-test was used to test the above hypothesis. The significance level obtained from the t-statistic was less than 0.05, which shows that there is a significant difference between the value score (standard limit) and the mean value of the population. Given that the mean of the sample presented in the table is higher than the value score (mean difference = 0.14), so the effect of service-related and infrastructural factors on the HR challenge of the rural areas is confirmed, thereby confirmation of the second hypothesis of the research.In relation to the third hypothesis, the significance level obtained from the t-test was much smaller than 0.05, which shows that there is a significant difference between the value score (standard limit) and the mean value of the population. Moreover, considering that the mean of the sample is higher than the value score (mean difference = 0.445), so socio-cultural factors are effective in the HR challenge in rural areas and the third hypothesis is confirmed.

According to Friedman's test, economic factors such as lack of employment due to inappropriate policies in rural areas have created the greatest challenge in human resources with the mean rank of 2.3. The second and third ranks go to socio-cultural, and service-related and infrastructural factors with the mean ranks of 2.08 and 1.63, respectively. Keywords: Human Resource Development, Rural Areas, Agriculture Sector, Malayer.ConclusionAccording to Friedman's test, economic factors such as lack of employment due to inappropriate policies in rural areas have created the greatest challenge in human resources with the mean rank of 2.3. The second and third ranks go to socio-cultural, and service-related and infrastructural factors with the mean ranks of 2.08 and 1.63, respectively.