THE ANALYSIS OF THE PROGRESSIVE AND PREVENTIVE FACTORS OF DEVELOPING AGRICULTURAL FAST BENEFITING AGENCIES IN BIRJAND CITY

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1 THE ANALYSIS OF THE PROGRESSIVE AND PREVENTIVE FACTORS OF DEVELOPING AGRICULTURAL FAST BENEFITING AGENCIES IN BIRJAND CITY * Pourya Nasrabadi 1, Saeed Najafi 2, Ali Asadi 3 and Naser Moteiei 3 1 Rural Development Master Level Student, Tehran University, Iran 2 Master of Rural Development, Islamic Azad University of Birjand Branch, Iran 3 Faculty Member of Tehran University, Iran *Author for Correspondence ABSTRACT Turning and focusing on the growth and development of agricultural fast benefiting agencies, as one of the economical development during the last three decades, has always been a concern to countries and governments. The need for little wealth, high revenue return and flexibility shows the economical explanation of fast benefiting agencies more than before. These agencies face with limitations, obstacles and problems such as human resource limitation, lack of facilities to develop produce and lack of fair distribution of financial resources. Therefore, this research which is a discovering one has dealt with the progressive and preventive factors of developing fast benefiting agricultural agencies in the city of Birjand in the year The causative of the data showed that the six factors of economical, legal-programming, relations and connections, market management, knowledge and skill and policy making were identified as progressive factors of developing agricultural fast benefiting agencies which have totally determined percent of the variance of all progressive factors. The inhibitive factors of the agricultural fast benefiting agencies include the five ones in order of priority of legal-office, current expenses, financial, attitude-agricultural and deep structural which determined percent of the variance of all the inhibitive factors. Key Words: Progressive, Inhibitive and Agricultural Fast Benefiting Agencies INTRODUCTION The increase of unemployment and globalization has lead millions of people all over the world move to create jobs and understand opportunities in new jobs. Job creation is the engine of economical growth in countries. There have been many definitions for job creator with this concept in foreign sources. For example, in one definition, it is said defined as one who makes policies for job and income and accepts the financial risks of it. And in another source it is defined as one who manages and organizes an economical institute, especially a job and income one, which usually demands considerable novelty and risk (taken from Random House English dictionary). In the majority of countries, the development of agricultural agencies and small and average businesses is considered as one of the major policies and priorities of the governments, and a special decision is made to support the creation, growth and survival of such units. Although this topic has a long history in the world, the importance and position of this sector has not received enough attention, while about 68% of all the economical agencies of the country are small or average. It is clear that any programming to economical and industrial development of the country, job creation, development of non-oil exports and novelty may not be successful without the support and backing of the small and average agencies. This is the lesson to be learned from developed and developing economies (Shafiei & Shaghaghi, 2004). Rural areas in developing countries deal with challenges such as unemployment, poverty, economical stoppage, being abandoned, low income, low exploitation, migration, economical difference, lack of resources, environmental pollution and so on which are due to not understanding creativity, innovations and successes as stated by Hezarjaribi (2001). In this field, understanding and paying attention to successful people and village job creators and activity and living models and their behavior and thinking type, a the economical engine, can be the base of stable rural development, and successful and job creating farmers integrate job creating mind and existing potentials and create new economical activities that produce ever-lasting flow of income and wealth for them (Habbershon, 2006). Smalbone (2007) classified the problem ahead of small and average rural job creating agencies in the seven factors of small size of local markets, limitations in choosing work force, inadequate access to the bases of business, weakness in connection and transportation deep structure, proper access to information and counseling services related to business issues, lack of proper access to financial resources and suitable organizational environment. Shepherd et al., (2003) also believe that the failure of an agricultural agency happens when the income of a company is severely low or its expenses are so high that it breaks down, and it is not possible to continue activities with the 74

2 present ownership and management. He also defines the failure of a project as finishing a project due to low and not acceptable performance which is determined in practice by the financial resource providers of the project. The results of the research by Tanbunan (2009) in Indonesia reveals that lack of wealth, the high price of units, the high price of work force, lack of suitable technology and skillful personnel are of the most important obstacles for small and average agricultural job creating agencies. Evans (1978) in the United States, using data related to American agricultural small business agencies, evaluated a positive and strong relation between probability of agencies survival and their sizes. After Evans (1987), Dunne et al., (1989), also Philips and Kirdroff (1989) analyzed the subject of survival and growth of agencies entering the American business. Decrease of failure rate of an agricultural agency as a result of increasing its size is the result of the study by Dunne et al (1989). The study by Philips and Kirchoff (1989) which is done by using American small agencies data also confirms the results of the study by Evans (1987). RESEARCH METHODOLOGY In this research, the two common methods which are documentary (library) and field are used to collect data. To calculate the volume of the sample for the population of agents in Birjand, first, based on the sample volume of the total statistical population under study (N) which was 1130 ones, 30 ones were analyzed for pretest. The standard deviation of this pretest was 1.1. Then the volume of the sample was calculated by using the Cocaran formula, and by using the completely random sampling method, the designed questionnaires were distributed among 130 agencies by the researcher. In this research, the data were analyzed by the SPSS software and the statistical-descriptive and inferential methods. RESEARCH FINDINGS Descriptive statistics In this part, the status of the variables in the population under study is analyzed through descriptive data such as frequency, percentage, collective percentage, mean and standard deviation. Table 1: The summary of the descriptive research results of individual s identification variables Row Variables Mean Standard deviation Frequency percentage 1 Age 39 years % between Education % ones with diploma 3 Interest to work % ones a lot 4 Activity experience 8.3 years % between 5-10 years 5 Number of employees in each agency % agencies less than 10 employees 6 Agency area square meters % of agencies bigger than 1400 square meters Prioritizing indices related to progressive and preventive factors of development in agricultural fast benefiting agencies. In this research, to identify progressive factors of developing agricultural fast benefiting agencies, people under study were asked some questions. Then, using the formula of change coefficient the changes of parameters under study was ranked. CV=STD/Mean*100 Change coefficient formula The reason for change coefficient for ranking is that the mentioned statistic is a criterion the low amount of which expressed the agreement of individuals in the field under analysis therefore, the less the amount of it, the more the agreement of the individuals and therefore, the higher the importance. 75

3 Table 2: Prioritizing indices related to progressive factors of developing agricultural fast benefiting agencies Variables Progressive Preventive Standard Mean Change deviation coefficient Rank Giving variation to the quality and quantity of products Management and employment skills of agents The legal procedure of starting agricultural job creating agencies Knowledge and ability of agencies in marketing Access to deep structures (transportation, banking system, market, ) Clear rules for supporting agricultural job creators Right and skillful workforce in agencies The economical base in a society The quality of agricultural products Facilities and financial supports to fast benefiting agencies The ability of the agency to use the internet and e-commerce Organizing web relations between job creators in agriculture The agency having suitable size and structure The relation between the agency and other parts of the society such as the agriculture organization, banks, corporation department, commerce department State system of agriculture development Cooperation between organizations related to the process of agricultural job creation developing process Financing from banks and investors and Providing special counseling (management, marketing, accounting, )to agricultural job creators Access of employees to required facilities Focus of the agency on some specific roles

4 The quality of the standard related to the rights of consumers Required guarantee and insurance for the agency with the least investment and interest The relation between educational system and agricultural environment Access to wealth to start a business Obligatory state rules and regulations to support agricultural agencies Arranging producers providers of agricultural businesses in the form of unities and empowering them in programming, providing services and supervision Security in investment Access to market Economical and non-economical inspirations Access to active non state local organizations (NGOs), national ones and international ones in the area Request for agricultural produce, especially healthy foods, with quality and organic, the growth of agricultural produce market Selection and appreciation of successful and unique agricultural job creators The presence of customers in the market Tax exemption and exemption related to business interest for agricultural businesses Access to information and communication deep structures (ICT)in agricultural sector Access to specialists in agricultural businesses Based on the findings of the research in the above table, it can be observed that, in the attitude of the agents, the first priority is with coefficient f changes that is 0.204, related to the index of variation to produces in quality and quantity, and the last priority with the change coefficient of is related to the index of access to individual specialists in agricultural businesses. 77

5 Table 3: Prioretizing indices related to preventive factors of agricultural fast benefiting agencies Variable Preventive Progressive Standard Mean Coefficient Rank deviation change Risk of starting a fast benefiting agency Burocracy structures and nonreflective office affairs Inflation rate Bank interest rate for loans paid to fast benefiting agencies Supervision on how to use the loans given to fast benefiting agencies Worker wage Price of product in the market or high fluctuation of prices Material expenses of fast benefiting agencies Geographical distribution of agencies in a city Access to materials and facilities required by fast benefiting agencies Price of raw material Exploiting the production factors Policies of agricultural sector Presence of office corruption in the area Transportation and vehicles Cultural dominance of agency and business middling in agricultural markets Relative advantage of agricultural activities and creating tax and finance policies Bank loan interest Developing the private sector Relative advantage of agricultural activities over other sectors Timing the payment of credit and increasing the time of rest in repaying the credits Providing products with lower prices than rivals (inner and outer) Providing programs for the repaying of rial and other currency credit Price of required facilities and machines Credits and non-financial supports of fast benefiting agencies Foreign relations of agricultural job creators Based on the findings of the research recorded in the above table, it can be observed that, in agents ideas, the first priority with a change coefficient of is related to the index of the risk of starting agricultural fast benefiting 78

6 agencies, and the last priority with the change coefficient of is related to the index of beyond the border connections of agricultural job creators. Inferential statistics: In the inferential statistics, by using the correlation analysis methods, tests of mean comparison and factor analysis are used to identify progressive and preventive factors in developing agricultural fast benefiting agencies. Table 4: Correlation coefficient of the variable of fast benefiting agencies and research variables Variable Test Correlation Level of coefficient significance Age Pierson Education Spearman 0.349** Attending job creation training classes Pierson 0.286** History of working in fast benefiting agencies Pierson ** Number of employees Pierson 0.317** Number of investors Pierson Motivation and economical-social and professional purposefulness Spearman 0.240* The findings of the research showed that there was no significant relation between the variable of fast benefiting agencies produce and age variables and the number of investors. The findings of the research reveals that there is a significant relation with 99% of certainty between the variable of fast benefiting produce and education, experience of activity in fast benefiting agencies and the number of agency employees. The findings of the research reveal that there is a significant relation with a certainty of 95% between the variable of fast benefiting agencies produce and motivation and economical-social purposefulness. Table 5: Correlation coefficient of the variable of fast benefiting agencies income and research variables Variable Test Correlation coefficient Level of significance Age Pierson Number of family work force Pierson ** Number of wager workforce Pierson 0.488** Size of agency Pierson 0.393** Interest to work Spearman 0.210** Distance from the market Pierson ** The findings of the research revealed that there was no statistical relation between the variable of fast benefiting agencies income and age. The findings of the research reveal that there is a positive and significant relation between the variable of fast benefiting agencies income and the number of wager workforce. The findings of the research reveal that there is a negative and significant relation between the variable of fast benefiting agencies income and the variable of family workforce and the distance to market. The findings of the research reveal that there is a significant relation with 95% of certainty between the variable of the fast benefiting agencies income and interest to work. Table 6: Determining the relation between the degrees of the attitude to work creation with other research variables Variable Test Correlation coefficient Level of significance Age Pierson ** Experience of attending educational and job creation classes Pierson 0.299** Motivation and economical-social and professional purposefulness Spearman 0.450** The findings of this research reveal that there is a positive and significant relation between the variable of level of attitude to job creation and the variables of experiencing job creating training classes, motivation and economicalsocial purposefulness. The findings of the research reveal that there is a negative and significant relation with 99% certainty between the variable of attitude to job creation. 79

7 Statistical analysis In this part, first, to evaluate inner unity of the data, to exploit the technique of factorial analysis, the KMO and Bartlet statistic are used. In this analysis, considering Caser criterion, six factors had a special amount of higher than one. Then, factors are turned by using the Rimax method and the variables related to each factor are identified based on which the exploited factors were obtained from the factorial analysis of progressive and preventive factors of agricultural fast benefiting agencies development. Table 7: Exploited factors from factorial analysis of progressive factors in developing agricultural fast benefiting agencies Row Factor name Special amount Special amount Collective variance variance percent percentage 1 Economical Legal-programming Relations and connections Market management Knowledge and skill Policy making The findings of the research reveal that the amount of the determined collective variance amount by these six factors was 62.90%. Based on this, the economical factors with the determined variance of are considered as one of the most important progressive factors of developing agricultural fast benefiting agencies. Table 8: Explained factors of the factorial analysis of preventive factors in developing agricultural fast benefiting agencies Row Factor name Special amount Special amount variance Collective variance percentage percentage 1 Legal-office Current expenses Financial Attitude-cultural Deep structure The results of the research showed that the amount of the determined collective variance by these five factors was Based on legal-office factors the determined variance of is one of the preventive factors of developing agricultural fast benefiting agencies. CONCLUSION The findings of the research revealed that the variable of fast benefiting agencies production level has a significant and negative relation with the variable of age and a positive and significant relation with education, experience of attending educational-job creating classes, history of the agency, number of employees, motivation and economicalsocial and professional purposefulness. These findings are similar to the findings of Masoudi (2005); Sohrabi et al., (2006) and Sharifzadeh et al., (2009). Also, the results of the research showed that the level of attitude to job creation had a negative and significant relation with the variable of age, and it had a positive and significant relation with the variable of experiencing attendance in educational-job creation classes and motivation and socialeconomical and professional purposefulness at the level of one percent. Also, the findings of the research showed that there is a positive and significant relation between the variable of level of income and from the activity of an agency and number of employees in an agency, the size of an agency and interest to work. The results from factorial analysis showed that the progressive variable of creating and developing agricultural fast benefiting agencies can be summarized in 6 factors which totally determined % of the total variance. Also, the preventive variables of 80

8 creating and developing agricultural fast benefiting agencies can be summarized in 5 factors that totally determined % of the total variance. Suggestions Creating the supporting bank of agents as a supportive policy to specifically help agents resolve their problems. This is a guideline to increase motivation to create and develop job creating units in agricultural sector. Including job creating training during the agricultural education period and also practicing these trainings by different agricultural organizations can be effective in increasing tendency in creating agencies. Insurance centers can familiarize agents with the advantages of insurance through suitable classes, decrease insurance expenses or encourage agents to use insurance advantages through guidelines such as paying through installment. Access to markets inside the country through increasing commercial cost to identify a product, increasing the quality of the product in order to produce a unique product and also creating horizontal and vertical connections. Designing and editing the through project of job creators-specific tax which has no interference from other agricultural rules which agents are usually engaged with. REFERENCES Dunne T, Roberts MJ & Samuelson L (1989).The Growth and Failure of U.S. Manufacturing Plants. Quarterly Journal of Economics, 104(4) Evans D (1987). The Relationship between Firm Growth, Size and Age-Estimates for 100 Manufacturing Industries. Journal of Industries Economics, 35(4) Habbershon TG (2006). The Family as a Distinct Context for Entrepreneurship, from: Praeger Perspectives on Entrepreneurship, Volume (3) Edited by Timothy G. Habbershon& Mark Rice. Hezarjaribi J (2006). Job creation, Tehran, Economical affairs research center. Phillips BD & Kirchoff BA (1989). Formation, Growth and Survival. Small business Economics, Shafiei M & Shaghaghi AR (2004). Increasing effective and competitive cooperation in the small and average industry sector, Tehran, Rasq cultural service institute. Shepherd DA, Covin JG & Kuratko DF (2009). Project failure from corporate entrepreneurship: Managing the grief process. Journal of Business Venturing, 24(6) Smallbone D (2007). Fostering Entrepreneurship in Rural Areas. Key Policy Issues in Entrepreneurship and SME Development, Retrieved Dec from (Accessed 12 October 2013). Tambunan T (2009). Women entrepreneurship in Asian developing countries: Their development and main constraints. Journal of Development and Agricultural Economics, 1(2)