@ARTICLE{Azizi-Khalkheili, author = {Azizi-Khalkheili, Taher and Zamani, GholamHosein and Karami, Ezatollah and }, title = {Job Motivation and Optimal Occupational Decision Making: The Case of Farmers in Marvdasht Township}, volume = {5}, number = {10}, abstract ={Optimal decision making is a prerequisite for job success, and decisions are influenced by motivations. This research was conducted to assess the optimal level of farmers' occupational decision making and the impact of job motivation and other factors on it by descriptive - correlational research and using a survey technique in Marvdasht Township of Fars province. The sample size (249 people) was determined by Mendenhall formula, which up to 307 people to increase research accuracy. A multi stage stratified random sampling method was used for sampling. The data gathering tool was a questionnaire whose validity was confirmed by the professors of agricultural extension and education and a pilot study was carried out to determine its reliability. Cronbach's alpha coefficient for research scales ranged from 0.71 to 0.86, indicating the accepted level of the measurement tool reliability. The results showed that farmers' attention to the optimal decision making criteria was moderate and all four types of job motivation had a positive and significant effect on optimal job decision making. Between the investigated criteria, the amount of hesitation in decision making and changing it has lower situation than the others. Moreover, one of the important factors in optimum decision making is the access of farmers to various information, especially meteorological information. According to the results, it is suggested that authorities and experts pay more attention to different types of farmers' motivations, and to increase their knowledge and information about decision making subjects, provide them with appropriate solutions. }, URL = {http://jea.sanru.ac.ir/article-1-184-en.html}, eprint = {http://jea.sanru.ac.ir/article-1-184-en.pdf}, journal = {Journal of Entrepreneurial Strategies in Agriculture}, doi = {10.29252/jea.5.10.27}, year = {2018} }