Challenges and Strategies of E-Commerce in Iran s Agriculture.

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1 AGRICULTURAL COMMUNICATIONS, 2014, 2(1): Challenges and Strategies of E-Commerce in Iran s Agriculture. HASSAN ASADIHKOOB AND MOHAMMAD SADEGH EBRAHIMI* Department of Rural Development, College of Agriculture, Isfahan University of Technology, Isfahan, Iran. *Corresponding Author: ebrahimi_ms@cc.iut.ac.ir (Accepted: 1 Nov. 2013) ABSTRACT Internet is a key for globalization and a tool for communication around the world. E-commerce has been introduced as a global phenomenon in the twenty-first century by internet development. The main goal of this research is to investigate the challenges and solutions of e-commerce in Iran s agriculture. The paper is based on a descriptive analytical type of field research, therefore a questionnaire was prepared as our data collection tool. The population of this research was a panel of agriculture faculty members in Iran. The overall results showed that the use of e-commerce in Iran s agriculture has many obstacles ahead in infrastructural, cultural, social and educational fields. The research findings showed that e-commerce can provide many advantages like profitability, elimination of intermediaries, agricultural production market development, farmers' awareness of market prices, and access to national and international markets, increasing competition and improving the quality of agricultural products. According to the results it seems that infrastructure development, culture and security and confidence production, and internet training to all classes of people are the most important strategies for e-business development in agriculture. Further research in this area and using other countries experiences are some other proposed solutions for e- commerce development in Iranian agriculture. Keywords: Development, e-business, economist intelligence unit, farmers, globalization, profitability. Abbreviations: BTS: Bartlett s tests of sphericity; EIU: Economist Intelligence Unit; ICT: Information Communication Technology; IT: information technology; KMO: Kaiser- Meyer-Olkin. INTRODUCTION Recent developments in information technology have caused important economic consequences. E- commerce is a new way of internet business or using electronic means to exchange information and relevant activities and transactions (Louis and Lefebvre, 2002). E-commerce is one of the genuine outcomes of information technology that has many advantageous like world trading, removing temporal and spatial constraints, reduced costs of purchased resources, increased sales, easy access to information, significant reduction of transaction costs and decreasing the time of transaction. One of the problems of agricultural production is marketing and customer acquisition. Although the total turnover of agricultural production in the world is high, farmers income is low, and in some cases, the farmers profits are close to zero or even negative. (Wen, 2007). Nowadays as a consequence of the spread of e- commerce, anyone can be easily informed about the latest market prices, buyers, and major producing centers. With the help of information technology and the internet (Saki, 2007), Iran's agricultural sector has a high potential to expand and grow. Iran has a varied climate and conditions for the production of various products. According to the Statistical Center of Iran database, there are approximately 4,332,423 farmers in Iran, so 25% of the economically active population is engaged in agriculture and agriculture has 13% of the GDP. According to the Statistical Center of Iran report in 2011, nearly 29 percent of the country's population lives in rural areas where agriculture is the dominant activity (Iran Statistical Center, 2011). In Iran the internet is used generally to conduct research at universities, and the centers in the cities have limited activities, also the users use the internet mostly as remote telephone and electronic instrument. In addition, many of the rules and infrastructures needed for e-commerce are not yet available in the country. So quick development of e-commerce in society cannot be expected (Hanafizaade, 2011). Also the Economist Intelligence Unit (EIU) has investigated the e-readiness of an estimated 60 to 70 of the world's top economies since This study reviews 100 qualitative and quantitative

2 ASADIHKOOB AND EBRAHIMI criteria in the following five categories, to rank the countries e-readiness: technological infrastructures, the society's business environment, the amount of e-business use by consumers and manufacturers, social and cultural conditions, and the availability of support services for e-business. Each country has a score between 0 to10 in this rating. Iran is located at position 65 among the 68 countries surveyed in The EIU ratings of electronic commerce classification for 60 countries in 2006, confirms the claim that Iran has many obstacles against e-commerce development yet. In this ranking, which in fact the ease and availability of e-commerce in the countries are shown, two overall indexes of business environment and communication are used (Fatheyan and Movlanapoor, 2008). Iran s Information Communication Technology (ICT) expenditure per capita is not very good in comparison with some selected countries of the region and the world; it is about 10 percent of the world average and is lower than some countries such as Turkey, Saudi Arabia, Kuwait, Jordan and Malaysia. In other words, less attention has been invested in this sector (Paryab and et al., 2007). Table 1 shows the internet penetration rates and the percent of households which have a computer. The internet penetration coefficient is the percentage of the people who have used the internet at least once in the 12 months preceding the census, to the total population in the same age group. Scale Iran (Whole country) United Kingdom Internet users Table 1. Internet access in the Iran in 2011 (Statistics Center of Iran). Internet penetration Internet penetration Internet index (6 years and index (10 years and penetration index older) older) (15-24 years old) percent of households which have a computer 20,504, % 17.5% 29.1% 33.4% 54,861, % 93% Fig. 1. Internet users per 100 inhabitants (Source: International Telecommunications Union). Fig. 2. Number of Internet users in Iran per 100 people, from 2000 to 2011 (Source: World Bank). Based on the nature of the transactions, the following classification of electronic commerce is provided. 1. Business to Business (B2B): Nowadays, most e-commerce transactions are B2B. Today, 85% of e-commerce transactions are B2B. This type of trade is exchanging business information between two businessmen or two companies. 2. Business to Consumer (B2C): all retail transactions and individual buyers are classified as B2C. This type of business grew quickly by web development, and now you can easily purchase all kinds of goods by B2C. B2C began with the launch of sites like AMAZON and CDNOW. Also, providing public services to customers and consumers (G2C) fall into this category. 3. Consumer to Consumer (C2C): In this class, buyers and sellers are persons. Sales of cars and accessories, personal service advertising on the internet and skills and knowledge sale, are examples of C2C. An example of this type of electronic commerce that currently is growing quickly can be seen on the ebay site. 4. Consumer to Business (C2B): This class includes the people who use the internet to sell products or services to organizations and persons that are expecting to purchase at the offered price. 5. Business to Government (B2G): This business class includes business information exchange between the Manufacturer Businessman and the Government (Turban et al., 2006). The Research Background: Economical, social, political and educational problems which are more common in rural communities are the major obstacles to e- commerce development in agriculture than in other sectors of the economy (Geng et al., 2007). 81

3 AGRICULTURAL COMMUNICATIONS. Statistics show that China's B2C commerce is expanding rapidly in agriculture (Kun, 2011). The United States Department of Agriculture has set four different performances which e-commerce companies are doing in the field of agriculture: 1. Distributing information. 2. Incoming request or amount of demand. 3. Classification of goods trade. 4. Demand chain management. Unlike industrial products, agricultural products are very diverse and are difficult to control and process. For example, vegetables and fruit crops should reach consumers in a short time due to their perishability. (Geng et al., 2007). One of the problems with IT applications in agriculture is the lack of standardization scales about the characteristics and quality of products. Standards are important and determinant in e-business process; they accelerate the demand chain, reduce errors and support technological investment. Standardization of agricultural products in United States and Europe started by formation of a specialist committee for coding (UGCP) since 1969, and in 1974, the council set standards for agricultural products (Geng et al., 2007). The number of websites in China has increased from 1500 in 1997 to 2.79 million in There are 420 million internet users in China, with more than 100 million of them in rural places. They are 15% of the total rural population in China. In 2009, China had more than 6,000 agriculture-related websites. China s internet penetration coefficient has reached to 31.8% in 2010 (Kun, 2011). Removing brokers can effectively reduce transaction costs, farmers will gain more benefits, and it will cause supply to be offered at lower prices. According to standard index of international products, E-commerce can cause more competition in the production and sale of agricultural products in the world. Although agricultural products have high financial value, most farmers receive little or no benefit (Wen, 2007). E-commerce via the internet has had an 80% profit, which includes entertainment activities, shopping, transactions, etc. (Louis and Lefebvre, 2002). In order to bring agricultural products into the field of e-commerce, they should be coded and standardized and understandable for transaction. This is because contrary to industrial products, agricultural products have various and different attributes and qualities. E-business problems in agriculture are: economical, social, political, and educational which are more common in rural areas (Geng et al., 2007). The results of research showed that cultural differences play an important role in the development of e-commerce. For example, for Spain and Italy which are similar in terms of economic, technology and IT indicators like their European neighbor countries, e-commerce was 3% and 3.3%, respectively, but it was 10.7% for Britain, 8% for Germany and 7.4% for Switzerland. Online retail trade is 3% in Spain. United States share of retail e-commerce was close to 3% in Results show that consumer confidence is affected by the usability of web sites, reputation, customer satisfaction and security policies of the websites, and all these are connected (Luis, 2011). Cultural features of countries can affect e-commerce development, the same as or more than economic, technological or market factors (Aqueveque and Fernandez, 2004). Purcell believes that one of the barriers to the growth of e-commerce in rural areas is the lack of access to the means of telecommunications (Purcell, 2004). A system was set up in Taiwan so that the customer can log in and after viewing products and prices, they can add the product and its amount to their shopping cart. After verifying customer information, he can choose the nearest shopping center through the internet map and go there or receive it at home (Wen, 2007). The number of e-commerce web sites, hich were created in 2008 to 2010 in China, count for 25% of the entire available sites. Nearly 73% of those sites have been B2C (Kun, 2011). Some believe that although e-commerce has made a new revolution in economics, the impact of e- commerce should be investigated in all economic, social, political and cultural features (Louis and Lefebvre, 2002). According to table 2, developing countries, especially in Middle East and Africa, have low e- commerce content. In a study (2007) which took place in Iran, findings indicate that 31.99% of the literate farmers are convinced that ICT e-commerce can cause economic advantages and 95.98% believed the e-commerce can cause limitations and consequences for agricultural production and also 5.92% believed the e-commerce can cause better marketing for agricultural products (Saki, 2007). According to the commerce net organization study, the ten main obstacles to e-commerce were security, reliability and risk, lack of trained staff, lack of business models, cultural issues, lack of public infrastructures, organizations, defraud, low internet speed and legal issues, respectively. Cultural issues, organizations, B2B middlemen, international trade barriers, and lack of standards were the important global obstacles (Hanafizaade, 2011). Villages like Shahkooh in Iran and Varnadr in India are typical examples of rural internet development. These village farmers get farming operation data required for different products, diseases and pest control, marketing and dairy production units, etc. and therefore their computer literacy increases. In a number of villages in India some internet and phone kiosks were made to 82

4 ASADIHKOOB AND EBRAHIMI share some information about market conditions, pests and weather conditions with farmers. The results showed that it has helped the area s rural development (Saki, 2007). Table 2. B2C and B2B trade volume by region in 2010 (billions of dollars). Area B2B Percent % B2C Percent % North America Asia - Pacific Western Europe Latin America Eastern Europe Africa and Middle East Total Statement of Problem: Globalization and rapid changes, particularly in technology, are two important features of present time that are challenging organizations and countries, and ignoring these developments will cause backwardness undoubtedly. According to these issues, information and communication technology, which are mentioned as "information revolution", have a huge contribution to the development of nations and organizations, and they going to impact all aspects of people s personal and social life (Saidi and Mirabi, 2004). Marketing, access to customers and the lack of knowledge about the market prices are some problems of the agricultural production cycle. So the villagers and farmers who are generally small producers, have to accept middlemen prices and as a consequence they will not gain enough benefit. Another problem of farmers is insufficient awareness of prices and market demand (Saki, 2007). Statistics show that the total volume of agricultural products in the world is much more than market demands. This means that farmers produce regardless of market needs, and there is no balance between supply and demand. So most of the products will rot unless the farmer reduces product prices and receives very low or zero benefit (Wen, 2007). ICT has removed many of the challenges and obstacles of business. Electronic markets can cause competitive product prices and quality improvement that also can help to increase the efficiency of rural manufacturing process (Jalalzade and Fami, 2007). Although agriculture makes up about 25 percent of the economically active labor of Iran, it unfortunately it contributes relatively little to the economy and trade. According to a FAO report in 2012, the share of agriculture in Iran s GDP is about 11.2%. In the world agricultural production rankings, Iran holds the first position in production of some horticultural products such as pistachio, saffron, pomegranate, and second position in production of apricot, cucumber, watermelon, melon, and third position in production of walnuts, dates, cherries and almonds. So there is a great need for extensive and competitive marketing in order to develop market and to gain greater access to global markets and also to compete in global markets (FAO, 2012). RESEARCH METHOD This study was descriptive analytic research. The main data used were collected through questionnaires and field studies. The population of this research was a panel of faculty members of agriculture in Iran. A sample of 110 people was selected by using random sampling. The questionnaire consisted of four parts, including: barriers to e-commerce (20 items), e-commerce development strategies (16 items), benefits of e- commerce (13 items) and disadvantages of e- commerce development (8 items). The questionnaire questions were designed in a Likert Scale. Subsequently, these questionnaires were analyzed for perpetuity utilizing SPSS software and the Cranach s alpha method. Alpha value is in a range of 0 to 1; so that internal reliability of items could be found through this coefficient. If this coefficient is zero, it will show full unreliability of items and if it is one, it will show full reliability. If alpha value is more than 0.7, questions and items are suitable for testing the concept or the related variable. In this study, as seen in Table 3, the amount of Cranach s alpha were 0.65 and 0.88, respectively for the four parts of the questionnaire. Table 3. Cranach s alpha coefficient of the research questionnaire. Name of structure Number of variables Cranach s alpha coefficient Barriers Guidelines Benefit Disadvantages In this study Characteristics of descriptive statistics such as average, exponent (or index), standard deviation and coefficient of variation were used. Besides them, factor analysis was also used to purify the information. In probability theory and statistics, the coefficient of variation (CV) is a normalized measure that is used to measure the distribution of statistical data. This coefficient is achieved by dividing the standard 83

5 AGRICULTURAL COMMUNICATIONS. deviation by the average (below formula): This value is defined when the average is not zero. The coefficient of variation is only applicable for the relative scales and cannot be used to measure negative values. Formula 1. To determine the appropriateness of the data and to measure the homogeneity of variables that attract farmers to group activities, the Kaiser- Meyer-Olkin (KMO) and Bartlett s test measures were applied. These statistics show the extent to which the indicators of a construct belong to each other. KMO and Bartlett s test for these variables show that the data are proper for factor analysis, as shown in Table 4. Table 4. KMO measure and Bartlett s test to assess appropriateness of the data for factor analysis. KMO Bartlett s test of sphericity Approx. chi- square Sig As the KMO= s larger than 0.5, it is concluded that the number of samples is suitable for factor analysis, since KMO value is between 0 and 1 and the closer to one, the higher the sample validity. According to the above table, Bartlett s test of sphericity was with a significance of p= Therefore it is concluded that the factors have not been classified well and the questions in each factor have congeneric correlative factor with each other. Factor analysis was applied as the main statistical technique for analyzing the data. The main object of this technique is to classify many variables into a few factors based on relationships among variables. Factor analysis is a statistical method that is based on the correlation analysis of multivariables. The purpose is to cut most variables to smaller underlying factors that are measured by the variables. Factors are formed by grouping the variables that have a correlation with each other. There are mainly four stages in factor analysis (Emin et al., 2007). a. First solution: Variables were selected and an inter correlation matrix is generated for including all variables. An inter-correlation matrix is a k (where k equals variables) array of the correlation coefficients of the variables with each other. When correlation between the variables is weak, it is not feasible for these variables to have a common factor, and a correlation between these variables is not studied. Kaiser Meyer Olkin (KMO) and Bartlett s tests of sphericity (BTS) were then applied to the studied variables to validate if the remaining variables are factorable. The KMO value should be greater than 0.5 for a satisfactory factor analysis. BTS, on the other hand, should show that the correlation matrix is not an identity matrix by giving a significance value smaller than b. Extracting the factors: A parts (factors) were extracted from the correlation matrix based on the first solution. In the first solution, each variable was standardized to have a mean of 0.0 and a standard deviation of Therefore, the eigenvalue of the factor should be greater than or equal to 1.0, if it is to be extracted. c. Rotating the factors: Sometimes one or more variables may load about the same on more than one factor, making the interpreting of the factors ambiguous. Therefore, factors were rotated to clarify the relationship between the variables and the factors. While various methods can be used for factor rotation, the Varimax method, which is the most commonly used, was applied. d. Naming the factors: Results were then derived by analyzing the factor load of each variable. Proper names were given to each factor by considering the factor loads (Emin et al., 2007). RESULT AND DISCUSSION Based on the research findings the respondents, the most important factors barriers for e- commerce development in Iran s agriculture are prioritized in Table 5. The respondents believe that from 20 barriers of e-commerce development that were questioned from them, the following factors are the most important barriers for e-commerce development in Iran s agriculture: farmer s low level of literacy, not having computer as a business tool among farmers, lack of information technology (IT) knowledge among the general public and lack of trust in electronic transactions (The less value of C.V Coefficient indicates the more agreement of respondents for this factor). Based on the research findings by the respondents, the most important factors for e- commerce development in Iran s agriculture are prioritized in Table 6. The respondents believe the following factors are the most important solutions to the development of e-commerce in Iran s agriculture: cheap and convenient public access to the internet at all times and places for people, involvement of more educated and literate people in agriculture, public education on information technology at all levels and development of internet lines all over the country. According to the study results (Table 7), the respondents believe that the following factors are the most important advantages of e-commerce in Iran s agriculture: up to date awareness of prices in the market, awareness of the market demands, development of agricultural product markets in to international markets, elimination of brokers and middlemen in agriculture and increment of 84

6 ASADIHKOOB AND EBRAHIMI farmers' knowledge regarding marketing mechanisms (The less value of C.V Coefficient indicates the more agreement of respondents for this factor). Table 5. Barriers to e-commerce in Iran s agriculture. Priority Variable (barriers to e-commerce) Average (of 5) Standard deviation Coefficient of Variation 1 Farmers low levels of literacy Not having computer as a business tool among farmers Lack of IT knowledge among the general public Lack of trust in electronic transactions Cultural lack of using computer among all Iranians People s traditional interest to physical presence in the market 7 Rural sprawl in Iran Lack of communication and network equipment and infrastructures for quick and easy access to the internet 9 Lack of internet service centers Lack of internet in rural areas Activity of elderly farmers in agricultural sector in Iran Lack of characteristics recognition for agricultural products in cyberspace 13 Lack of funds allocated by the government for rural connectivity facilities 14 Non-compliance of nationwide broadband internet lines Small plotted agriculture in Iran Perishability of most agricultural products High cost of computer and internet use Lack of electronic banking systems around the country Large Farmers count in Iranian agriculture Lack of standard coding system for agricultural products in Iran Table 6. Prioritized e-commerce solutions in Iran s agriculture. Priority Variable (prioritized e-commerce solutions) Average (of 5) Standard deviation Coefficient of Variation 1 Cheap and convenient public access to the internet at all times and places for people 2 Involvement of more educated and literate people in agriculture Public education on information technology at all levels Development of internet lines all over the country Creation a comprehensive public education network Reforms in educational system of the country in order to promote the use of information and communication technologies among younger populations 7 Development of credit centers and banks within the community Providing security and trust in electronic commerce Entry of private sectors in e-commerce Encouragement of agricultural producers to participate in the virtual marketplace 11 Development of electronic government Creation of a new law in order to protect e-commerce Creation of awareness and culture in villages through effective institutions 14 Better access to computers for all classes of people Cooperation between government body and educational institutions (universities) in providing infrastructure 16 Internet education to farmers Despite all the advantages, any form of technology may also have some disadvantages, so the respondents believe that the following factors are the most important disadvantages of e-commerce in Iran s agriculture: impossibility of viewing agricultural products in cyberspace, increment in internet fraud, anonymity for seller and buyer in cyberspace and elimination of farmers that have not high competition ability. 85

7 AGRICULTURAL COMMUNICATIONS. Table 7. The advantages of e-commerce in Iran s agriculture. Priority Variable (advantages of e-commerce) Average (of 5) Standard deviation Coefficient of Variation 1 Up to date awareness of prices in the market Awareness of the market demands Development of agricultural product markets in to international markets 4 Elimination of brokers and middlemen in agriculture Increment of farmers' knowledge regarding marketing mechanisms 6 Farmers quick access to funds from the sale of their agricultural production 7 Acceleration to customer acquisition Eradication of geographical boundaries and access to national and international markets 9 Increment of farmers' income Selling period of product (24 hours every day-724) Standardization of agricultural products Competition increment and quality improvement of agricultural products 13 Decrement of products final price for customers Table 8. The disadvantages of e-commerce in Iran s agriculture. Priority Variable (disadvantages of e-commerce) Average (of 5) Standard deviation Coefficient of Variation 1 Impossibility of viewing agricultural products in cyberspace Increment in internet fraud Anonymity for seller and buyer in cyberspace Elimination of farmers that have not high competition ability Changes in indigenous and local cultures Social interaction reduction among people Rising unemployment Risk of reduction in the diversity of agricultural production (single-product) Factor analysis is one of the statistical methods for data analyzing among the whole data set. The main barriers to e-commerce in agriculture were examined using the factor analysis technique of principal components analysis. Five factors with eigenvalues greater than 0.5 were extracted and these factors explained 58.52% of the total variance of factors related to e-commerce development obstacles in Iran s agriculture. In other words, nearly 59% of e-commerce-related barriers were identified. After studying the variables associated with each factor and their factor loadings, the factors were named as follows: infrastructure factor, social factor, cultural factor, agricultural status factor and educational factor. The mentioned factors and their eigenvalues, eigenvalue s percentage of variance and cumulative percentage variance of each factor are presented in Table 9. In determining factors, factor loadings greater than 0.50 were considered to be significant. The first factor, i.e., infrastructural technical factor explained 21% of the total variance and 7 variables were loaded significantly. The eigenvalue of this factor is 4.02, which is placed at the first priority in obstacles of e-commerce in agriculture of Iran. In this factor the non-compliance of nationwide broadband internet lines and lack of electronic banking systems around the country are very important. (Table 10). Table 9. Number of extracted factors, eigenvalues and variance explained by each factor. Factors Factor Name Eigenvalue Variance percent of eigenvalue Cumulative percent of variance 1 Infrastructural technical factor Social Factor Cultural Factor Agricultural State Factor Educational Factor

8 ASADIHKOOB AND EBRAHIMI Table 10. Factor name and effective variables of each factor. Priority Factors Name Variables Factor load First Infrastructural technical factor lack of internet in rural areas cost of computer and internet use lack of funds allocated by the government for rural connectivity facilities Non-compliance of nationwide broadband internet lines lack of electronic banking systems around the country lack of communication and network equipment and infrastructures for quick and easy access to the internet lack of internet service centers Second Social Factor activity of elderly farmers in Iran s agriculture people s traditional interest to physical presence in the market lack of characteristics recognition of agricultural products in cyberspace Third Cultural Factor lack of IT knowledge among the general public lack of trust in electronic transactions lack of the culture of using computer in all Iranian people Fourth Agricultural State Factor Perishability of agricultural products small plotted agriculture in Iran large farmers count in Iran s agriculture Fifth Education Factor computer s unpopularity as a business tool among farmers farmers low levels of literacy The second factor was named as a social factor. On this factor 3 variables loaded significantly, and has appropriated 13% of the total variance. In this factor the people s traditional interest to physical presence in the market is very important. The third factor has been named as cultural factor. On this factor, 3 variables were loaded significantly, and makes up 9% of the total variance. Lack of trust in electronic transactions and lack of the culture of using a computer by Iranian people are very important. The fourth factor has been named as the agricultural state factor. Three variables loaded significantly on this factor and it makes up 8% of the total variance. The large number of farmers in Iran s agriculture is very important. The fifth factor has been named as the education factor. Two variables loaded significantly, and the factor makes up 7% of the total variance. The low level of farmers literacy is a very important obstacle to e-commerce in agriculture of Iran. Since the low level of farmer s literacy is a very important obstacle of e-commerce in Iran s agriculture, therefore predisposing educated and literate people to enter in agriculture is one of the solutions to this problem. This factor can to be noted to educated for traditional farmers and also planning to enter of higher educated farmers in to agricultural sector. CONCLUSION Agriculture is one of the main economic sectors which always has resisted the introduction of innovation and technology while it faces many challenges. In this study the challenges and solutions for e-commerce in agriculture were discussed. The results indicate that there are many obstacles in all aspects of e-commerce development in Iran s agriculture. These obstacles are categorized into five categories: lack of appropriate infrastructure, social barriers, cultural barriers, educational barriers, and agricultural status barriers. The most important obstacles are farmers low levels of literacy, not seeing the computer as a business tool among farmers, lack of IT knowledge among the general public, lack of trust in electronic transactions, cultural lack of using computers among Iranians and people s traditional interest of physical presence in the market. The results showed that e-commerce development in agriculture needs investment and attention in all sectors. Totally, the solutions of e- commerce development in agriculture are the development of the cultural, infrastructural, social and educational backgrounds in Iranian society. The results indicate that the sale of agricultural products through e-business is profitable and efficient and it will provide farmers better access to national and international markets, and agricultural market development. E-Commerce will also create awareness of market demands and prices, increase competition, and improve the quality of agricultural products. The results of this research also shows anonymity of the people who transact in cyberspace, and the inabilities to observe and properly evaluate agricultural products in cyberspace are some of the agricultural e-commerce disadvantages. Since e-commerce development in Iran s agriculture faces many obstacles, long-term planning should be done in all fields of culture, education, infrastructure and society. Extension of internet lines in all parts of the country, general education of people at all levels of information technology and communication, creating e- commerce awareness and culture in the population, promoting the benefits of e-commerce, creating new rules to support and encourage e- commerce, moving towards healthier products, 87

9 AGRICULTURAL COMMUNICATIONS. empowering farmers, predisposing educated and literate people to enter agriculture and using the experiences of other countries are some suggested solutions. ACKNOWLEDGMENT Author would like to appreciate Isfahan University of Technology, Iran, for its financial support to this research project. REFERENCES Aqueveque, C. and C Fernandez. El Efecto de las Caracteristicas Culturales de un Pais en la Adopcion del Comercio Electronico B2C. Pensamiento y Gestion: Revista de la Division de Ciencias Administrativas de la Universidad del Norte. Vol. 17: Emin, M.O., L.O. Emel, E. Ercan and E. Gamze VIndustry financial ratios-application of factor analysis in Turkish construction industry. Building and Environment. 42: FAO Fathian, M. and R. Molanapour E-Commerce. Aninagar Publisher. Tehran, Iran. 120 p. Geng, S., R. Tian-zhi and X. Wang Technology and Infrastructure Considerations for E-Commerce in Chinese Agriculture. Agricultural Sciences in China. 6(1): Haghizadeh, P E-Commerce. Termeh Publisher. Tehran, Iran. 201 p. Iran Statistical Center Jalalzadeh, M. and H. Fami E-Commerce in Agricultural Sector. 4 th national Conference of E- Commerce. Tehran, Iran. Kun, F Comparative Analysis on E-Commerce Application of Agriculture in China. Journal of Convergence Information Technology. 6(7): Louis, A. and L. Lefebvre E-commerce and virtual enterprises: issues and challenges for transition economies. Technovation. 22: Luis V.C The Generation of Trust in the Online Services and Product Distribution: the Case of Spanish Electronic Commerce. Journal of Electronic Commerce Research. 12(3): Paryab, H., J. Aliakbai and M. Amini E-Commerce in Agricultural Sector- case study of Iran. 4 th national Conference of E-Commerce. Tehran, Iran. Purcell, R.D Comments on rural utility service. United States Department of Commerce (US DOC) Saki, M The economic impact of ICT (e-business) marketing of agricultural products in Kermanshah Province. Master thesis in Agricultural Economic. Iran. Sarmadsaidi, S. and V.R. Mirabi E-Commerce. Parsman Publisher. Tehran, Iran. 200 p. Snaieai. A E-Commerce in the three millennium. Jahad-e-Daneshgahi Publisher. Isfahan, Iran. 203 p. Turban, E., D. King, D. Viehland and J. Lee Information Technology for Management. Transforming Organizations in the Digital Economy. John Wiley and Sons Inc., Oxford, UK. Wen, W A knowledge-based intelligent electronic commerce system for selling agricultural products. Computers and Electronics in Agriculture. 57: