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Identification and Systematic Analysis of the Influencing Factors on the Development of Agricultural Industrial Cluster

By Jay Sullivan,2014-06-18 10:37
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Identification and Systematic Analysis of the Influencing Factors on the Development of Agricultural Industrial Cluster

Identification and Systematic Analysis of the

    Influencing Factors on the Development of

    Agricultural Industry Clusters

    Qiao Penghua

    Lecturer, Ph.D. candidate

    Qiqihar University, Harbin Institute of Technology

    Qiqihar, China

    qph@qqhru.edu.cn

    Wang Wei

    Professor, Doctor

    Qiqihar University, Harbin Engineering University

    oldbridge1221@126.com

AbstractSince the development of agricultural industry clusters are affected by its internal and external

    factors in the system, so how to choose the main influencing factors has become an important link in the

    research on agricultural industry clusters. By screening and classifying numerous factors, we construct the

    system of facilitation factors in agricultural industry clusters, and by using DEMATEL method, we made a

    qualitative and quantitative identification on the factors affecting the development of agricultural industry

    clusters of Heilongjiang province, then we also analyzed the main influencing factors systematically. Finally

    we come to the conclusion that the main factors of the agricultural industry clusters development include

    government industry policies, the leading enterprise, agricultural technology innovation, the marketization

    degree of agricultural product circulation and the marketization degree of agricultural investment.

    Keywords: agriculture industry cluster, Influencing factors, DEMATEL method

Industrial cluster is one of the mainstreams of economic development in the world today, which is also

    a powerful force that promotes regional economy and industrial development. According to the

    [1]OECD's definition, agricultural industry clusters are an organic whole formed by a group of

    enterprises and complementary institutions due to their commonness or complementarity, which are

    geographically and mutually closing, with a target of producing and processing agricultural products

    around the agricultural production base. Agriculture, as a traditional industry, also has the industrial

    cluster phenomena, which plays an important role in the local economy. Therefore, analyzing the

    influencing factors on agricultural industry clusters to acquire the analysis on key elements in the process of development in the agricultural industry clusters can help us to understand the origin of the stage development in agricultural industry clusters as well as the pertinence and effectiveness of policies and promote the healthy development of industrial clusters.

    ?. The motive analysis of the development of agricultural industry clusters Agricultural industry clusters, as a phenomenon in the evolution process of the development of agricultural production, its formation and development follows certain logics and has its own rules, rather than a number of same types of specialized enterprises with a simple aggregation of space, is a

    [2]. There are various factors product of agricultural production in a certain stage of development

    influencing the formation and development process of the agricultural industry clusters. With theories from many scholars integrated, it can be mainly attributed to three categories: resource endowment, endogenous power, and the exogenous thrust.

    Resource endowment is the material basis for development and it can be divided into two kinds: one is natural resources, such as soil, climate, minerals, forests, lakes, geographic location, etc; the other is non-natural resources, such as labor, knowledge and skills, capital, etc. Seen from the initial industry cluster phenomenon, making full use of natural resources to develop regional economy is the original driving force to form industrial clusters. For instance, agricultural industry clusters rely on absolute or relative comparative advantages such as agricultural planting or planting large areas of crops, geographical environment, transportation conditions and cost of agricultural products, to form the initial agricultural industry clusters.

    Endogenous power is the inner development power of the cluster. The influencing factors on the development in the agricultural industry clusters from internal body or internal relationship can be summarized as internal factors of the cluster. Firstly, the leading enterprise is the core of the agricultural industry clusters. Only if the core is strengthened, can we bring more inflow effect into the

    [3]development of the cluster and give full play to its radiating drive of farmers from tens of thousands

    of households. Secondly, with the tremendous development in agricultural industrialization, leading enterprises grow rapidly and homogeneous leading enterprises are closely linked together with the farm produce industry association, which is with strength and capacity or homogeneous farmer cooperative organizations through the industrial chain. And then with continuously gathering for scale effect, eventually develop the agricultural industry clusters. Thirdly, as for the agricultural industry clusters, technology plays an equally important role as talents do in agricultural industry clusters and they are the powerhouse to upgrade the industrial cluster and the sustainable development.

    Exogenous thrust is the external push factor and is also a supplementary promoting factor for the development of the cluster. It is mainly divided into the government behavior and the external environment. Government behavior is shown mainly through related industrial policies greatly affecting the cluster, the implementation of agricultural standardization system, the promotion of agricultural application technology and regional industrial distribution. Besides, the development of the

agricultural industry clusters is inseparable from the direct or indirect government policy support, such

    as a good institutional environment and the marketization environment of investment and circulation,

    which are of vital importance in enhancing the trust among enterprises in the cluster, enriching local

    social capital, coordinating the joint actions among enterprises and promoting healthy competition and

    cooperation pattern among enterprises.

According to the above analysis, we can conclude that the resource endowment is the material base for

    agricultural industry clusters to survive and develop, endogenous power is the inner motive power and

     exogenous thrust is the external push factor of agricultural industry clusters, as is shown in Chart 1-1.

    FIGURE 1-1

     外在推力内在推力

     政府产业政策(F15农产品交易市场数量(F716地区产业布局(F8农民专业合作组织数量(F17农业应用技术项目(F 9 科技示范户数量(F18农业科技创新(F10农产品加工利税(F19农业投资市场化程度(F 11农产品转化率(F20农产品标准化体系(F12从业人员内部流动率(F 21农产品质量控制体系(F13农业技术人员比例(F农产品流通市场化(F2214农业科研经费投入(F外源推力因素内源动力因素

     农产品加工产值(F2农产品产值(F)13农作物播种面积(F 基础因素)农产品价格(F45交通运输条件(F

     资源禀赋

    ?. Identification of Influencing Factors on Agricultural industry clusters Development

There are many mature methods to identify the main elements in the influence system by modeling the

    statistic data as well as analyzing and identifying the factors, such as statistic analysis, econometrics

    and computing science. However, when it comes to the analysis of influencing factors on agricultural

    industry clusters, usual modeling methods may lose effect due to a lack of data. While using

    DEMATEL method, even without many quantitative data, the research can be done with the assistance

    of the participants’ consciousness and their viewpoints to analyze the existing problems and the effect

    [4]of countermeasures quantitatively, so DEMATEL method is a system method oriented to problems.

A. The DEMATEL method and the implementation step

DEMATEL method (Decision Making Trial and Evaluation Laboratory), literally translated as decision

    making trial and evaluation laboratory, is a methodology introduced by the Bastille National

    Laboratory in 1971 to solve complex and difficult problems in real world. It is a method using graph

    theory and matrix tool to analyze system factors. Through the logical relationship between the factors

and the direct influence matrix in the system, we can calculate influence degree and the affected degree,

    and thus calculate the cause degree and centrality. The essentials of the DEMATEL method suppose The essentials of the DEMATEL method suppose that a system contains a set of criteria C = {C1, C2, . . . ,Cn}, and the particular pair wise relations are that a system contains a set of criteria C = {C1, C2, . . . ,Cn}, and the particular pair wise relations are determined for modeling with respect to a mathematical relation. The solving steps are as follows: determined for modeling with respect to a mathematical relation. The solving steps are as follows: Step 1: Generating the direct correlation matrix. Directed graph is constructed with the direct Step 1: Generating the direct correlation matrix. Directed graph is constructed with the direct correlation among factors and figures such as 3, 2, 1 separately representing strong, medium and weak correlation among factors and figures such as 3, 2, 1 separately representing strong, medium and weak are used to indicate the correlation among factors in the radial. Measuring the relationship between are used to indicate the correlation among factors in the radial. Measuring the relationship between criteria requires that the comparison scale be designed as four levels: 0 (no influence),1 (very low criteria requires that the comparison scale be designed as four levels: 0 (no influence),1 (very low influence), 2 (low influence),3 (high influence), and 4 (very high influence). Experts make sets of the influence), 2 (low influence),3 (high influence), and 4 (very high influence). Experts make sets of the pair wise comparisons in terms of influence and direction between criteria; the initial data can be pair wise comparisons in terms of influence and direction between criteria; the initial data can be obtained as the direct correlation matrix that is a n×n matrix A, in which aij is denoted as the degree to obtained as the direct correlation matrix that is a n×n matrix A, in which aij is denoted as the degree to which the criteria I affects the criteria j. which the criteria I affects the criteria j.

    Step 2: Standardizing the direct correlation matrix. Set direct correlation matrix A and the direct Step 2: Standardizing the direct correlation matrix. Set direct correlation matrix A and the direct influence matrix aij in which indicates the correlation between i and j, and then the standardized direct influence matrix aij in which indicates the correlation between i and j, and then the standardized direct correlation matrix X obtained are shown in the following formulas: correlation matrix X obtained are shown in the following formulas:

     XkA??

    1kijn??,,1,2,..., nmaxaij??1j1??in

    Step 3: Calculating the comprehensive correlation influence matrix. Once the normalized direct Step 3: Calculating the comprehensive correlation influence matrix. Once the normalized direct correlation matrix X is obtained, the comprehensive correlation influence matrix T can be acquired by correlation matrix X is obtained, the comprehensive correlation influence matrix T can be acquired by formula below, in which I is denoted as the identity matrix to analyze the indirect correlation among formula below, in which I is denoted as the identity matrix to analyze the indirect correlation among factors. factors.

    ?1TXIXt???()()ij

    TijStep4: Investigate factor in T and figure out the influence degree, the affected degree and the Step4:

    Tjijicentrality of each factor. Factor means the direct and indirect impact of on , or the

    jicombined influence from . Summation of elements, which is from each row in T and known as the affected degree, is the value of combined influence for the corresponding factor from all the other

    elements. The difference between the influence degree and the affected degree is called the cause

    degree, if it is greater than 0, it shows that the factor has greater influence than the others, which

    implies the causal logic correlation between the factor and the others. The summation of the influence

    degree and the affected degree is called centrality which stands for the position and the function of the

    factor in the system.

    With the comprehensive analysis, we can conclude the significance level of all the factors on the

    development of agricultural industry clusters to find out the significant factors.

B. Determination of the Main Influencing Factors on the Development of Agricultural industry clusters

The industrial cluster development results from both internal and external factors where different

    factors have different effects. In order to promote rapid and healthy development in the agricultural

    industry clusters, we must find the main influencing factors, and make a concrete analysis on their characteristics. In this study we adopt DEMATEL method to ultimately determine the main factors affecting the development by sorting numerous factors.

    The relevant data comes from the research on Heilongjiang Province agriculture industry cluster from April to June, 2009. We investigated 20 agricultural professionals associated with agricultural industry clusters, such as government officials and experts on agricultural research. And we have investigated their views of the influencing factors on the development capacity in agricultural industry clusters by means of in-depth interviews. Meanwhile we select five leading agricultural processing enterprises and 20 SMEs in Heilongjiang province to make a questionnaire survey. It is by sorting the analysis of data that the direct influence matrix of influencing factors on the capacity of agricultural products processing cluster is established as is shown in Table 2-1.

    TABLE 2-1 THE DIRECT INFLUENCE MATRIX

    1111111111222 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2

    1 0 2 1 0 0 1 1 1 1 0 0 0 1 1 2 1 1 1 1 1 1 2

    2 2 0 1 0 0 3 0 1 1 1 0 0 0 0 2 0 1 0 0 0 0 0

    3 1 1 0 0 0 1 2 1 1 0 1 1 0 0 3 1 0 0 0 0 0 0

    4 0 0 0 0 0 2 1 0 0 0 0 2 0 1 2 1 0 0 2 0 0 3

    5 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 0 0 1

    6 1 3 2 2 0 0 0 0 0 0 0 0 2 1 2 1 0 2 2 0 0 2

    7 1 0 0 0 0 0 0 1 0 0 1 1 0 0 0 1 0 2 0 0 0 2

    8 1 1 1 0 0 0 1 0 0 0 0 1 0 0 0 1 1 0 1 0 1 1

    9 1 1 1 0 0 0 0 0 0 0 1 0 0 0 2 1 0 0 0 0 0 0

    10 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 2 0 0 0

    11 0 0 1 0 0 0 0 1 1 0 0 0 2 0 1 1 0 2 0 0 0 0

    12 0 0 1 2 1 0 1 1 0 0 0 0 2 0 1 1 0 2 0 0 1 0

    13 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 0

    14 1 0 0 1 0 0 0 0 0 0 0 0 2 0 1 1 0 1 2 1 1 0

    15 2 2 3 2 2 0 0 0 0 0 0 1 0 0 0 1 0 2 0 0 0 0

    16 1 0 1 1 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 1 0 2

    17 1 1 0 0 3 0 0 0 1 1 0 0 2 1 0 1 0 0 0 0 0 1

    18 1 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 1 1 0

    19 1 0 0 2 0 0 0 0 0 0 0 0 0 0 2 1 0 2 0 1 0 2

    20 1 0 0 0 0 0 0 0 1 2 1 0 0 0 0 1 0 2 0 0 1 0

    21 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 2 1 0 0

    22 2 0 0 3 1 0 0 0 1 1 0 0 0 1 2 1 1 1 1 0 1 0

    2 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 2 1 0 2 1 0 0 1 1 1 1 0 0 0 1 1 2 1 1 1 1 1 1 2 2 2 0 1 0 0 3 0 1 1 1 0 0 0 0 2 0 1 0 0 0 0 0 3 1 1 0 0 0 1 2 1 1 0 1 1 0 0 3 1 0 0 0 0 0 0 4 0 0 0 0 0 2 1 0 0 0 0 2 0 1 2 1 0 0 2 0 0 3 5 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 0 0 1 6 1 3 2 2 0 0 0 0 0 0 0 0 2 1 2 1 0 2 2 0 0 2 7 1 0 0 0 0 0 0 1 0 0 1 1 0 0 0 1 0 2 0 0 0 2 8 1 1 1 0 0 0 1 0 0 0 0 1 0 0 0 1 1 0 1 0 1 1 9 1 1 1 0 0 0 0 0 0 0 1 0 0 0 2 1 0 0 0 0 0 0 10 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 2 0 0 0 11 0 0 1 0 0 0 0 1 1 0 0 0 2 0 1 1 0 2 0 0 0 0 12 0 0 1 2 1 0 1 1 0 0 0 0 2 0 1 1 0 2 0 0 1 0 13 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 0

    14 1 0 0 1 0 0 0 0 0 0 0 0 2 0 1 1 0 1 2 1 1 0

    15 2 2 3 2 2 0 0 0 0 0 0 1 0 0 0 1 0 2 0 0 0 0

    16 1 0 1 1 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 1 0 2

    17 1 1 0 0 3 0 0 0 1 1 0 0 2 1 0 1 0 0 0 0 0 1

    18 1 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 1 0 0 1 1 0

    19 1 0 0 2 0 0 0 0 0 0 0 0 0 0 2 1 0 2 0 1 0 2

    20 1 0 0 0 0 0 0 0 1 2 1 0 0 0 0 1 0 2 0 0 1 0 In accordance with the train of thought in DEMATEL method, we figure out the comprehensive 21 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 2 1 0 0 correlation matrix by the MATLAB operation software to calculate the direct influence matrix. Due to 22 2 0 0 3 1 0 0 0 1 1 0 0 0 1 2 1 1 1 1 0 1 0

    limited space, we only list the final result of the comprehensive correlation matrix as is shown in Table

    2-2.

    TABLE 2-2 THE COMPREHENSIVE CORRELATION MATRIX

     1 2 3 4 5 6 7 8 9 10 11

    

     0.8481 0.3924 0.4101 0.4203 0.1546 1.8567 0.4031 0.7382 0.422 0.358 0.3628

    

     0.1737 -0.1492 -0.1565 0.2289 0.0916 0.2793 0.0593 0.064 -0.196 -0.1422 -0.189

    TABLE 2-2 (Continued) THE COMPREHENSIVE CORRELATION MATRIX

     12 13 14 15 16 17 18 19 20 21 22

    

     0.4927 0.9153 0.3895 1.7631 0.4361 0.3927 1.8037 1.5883 0.3349 0.4194 1.6947

    

     -0.1425 0.2573 -0.2949 0.2511 -0.0178 -0.2255 0.3179 0.2307 -0.0595 -0.0758 0.3951

    Based on the comparison and analysis of the cause degree and centrality degree in the comprehensive

    correlation matrix, we conclude that the influencing factors on the development of agricultural industry

    clusters are: FFFFFFFFFFF, where the centrality degree of F6 (driving 1456781315181922

    force of leading enterprises) located in 1.8567, tops the 22 factors concerned; F18 (agriculture science

    and technology innovation) and F15 (government industry policy) respectively corresponds to the

    centrality of 1.8037 and 1.7631. Therefore, these three factors play an important role in the

    development of agricultural industry clusters. Meanwhile, as seen from the table, F22 (the

    marketization of agricultural circulation) and F19 (the marketization of agricultural investment) are

    both with a centrality more than 1.0, thus can be viewed as decisive in industrial development.

?. System Analysis on the Main Influencing Factors of the Development in Agricultural industry

    clusters

    We start with the main influencing factors obtained from DEMATEL method and focus on correlations between the five factors which are government industry policy, driving force of leading enterprises, agriculture science and technology innovation, marketization of agricultural circulation and marketization of agricultural investment, and the development of agricultural industry clusters in Heilongjiang Province.

A. Industry Policy is a Guarantee for the Development in Agricultural industry clusters A. Industry Policy is a Guarantee for the Development in Agricultural industry clusters

    As a big agricultural province nationwide, the relevant government departments in Heilongjiang Province play an active role in making policy guidance in the agricultural industrialization process. Since the 16th national congress, the central government has issued several "No.1" documents on agriculture for years which make a policy of reasonable adjustment to the national income distribution pattern as well as the implementation of industry re-feeding agriculture and city supporting country. In the background of the policy, Heilongjiang actively promotes agricultural policy. Since 2004 Heilongjiang Provincial Government and Party Committee has brought the development of farm produce processing industry into an important agenda and taken a series of effective measures to speed up the development in the province. And it has issued several policy documents ,such as the Opinion on Accelerating the Development in Leading Enterprises , the Opinion on the Implementation of Brand Strategy and Promotion to Speed up the Development of Leading Enterprises, the Opinion on Further Accelerating the Development in Grain Processing Industry in Heilongjiang Province, established the outline of the Eleventh Five-Year Plan in Heilongjiang province and a series of planning for the development in Revitalization of the Soybean Industry, the overall industry distribution of ha-da-qi industrial corridor and the Potato Industry. In 2009, it unveiled some opinions on supporting “three

    rural and budgeted special expenditures 8.56 billion Yuan for “three rural with an increase of 1.73

    [5]. The series of billion Yuan and a rise up to 25.2% to support the development of modern agriculture

    policies and measures promoting agricultural development has laid a solid foundation to further enhance the development of agricultural industry clusters.

B. Leading Enterprises are the Driving Force of Development in the Agricultural industry clusters Leading Enterprises are the Driving Force of Development in the Agricultural industry clusters

    The driving ability of leading agricultural enterprises in Heilongjiang province gradually stood out, achieved good results and formed large quantities of leading enterprises such as Great Northern Wilderness Group, Jusan Oil and Fat Co.Ltd. In 2007, provincial leading enterprises drove 1.45 million peasant households with an average household income increased by 1950 Yuan, which respectively grew at 7.4% and 8.3% compared with 2006. In Heilongjiang Province, although farm produce processing industry has been developing rapidly, as a whole, the scale is generally small. In Heilongjiang province there are 129 leading enterprises setting foot in the field of food and the number of the enterprises with an annual output value of more than 100 million Yuan is only 12, less than 10% in the whole; only 46 more than 3 million Yuan. There are vast areas that can be a base for farm

    produce processing industry in which used for the production of green food is less than 1% of common farm produce and most of the land still maintains a traditional form of agricultural production. It is thus clear that the majority of enterprises in the agricultural industry clusters are with a low starting point and a small scale and the driving force of leading enterprises which guides the direction of the industry remains relatively weak.

    C. Technological Innovation is a Driving Force for the Sustainable Development of Industry Clusters

    Science and technology is the first productivity. Science and technology innovation is an inexhaustible resource of agricultural economic development. It makes a qualitative change in productivity through the materialization of productivity factors. In recent years, Heilongjiang government has actively promoted modern agriculture industry technology system, deeply implemented the project of agricultural science and technology to households and accelerated the promotion of the advanced application technology of agricultural mechanization, which effectively promoted and enhanced the capacity of agricultural science and technology innovation and conversion. Meanwhile, many local governments have implemented "science and technology increasing grain yield action plan", organized thematic and technical training to guide farmers in arranging varieties, sowing date and adjusting to the production distribution scientifically; promoted varieties adapted to the production area and increased efforts in the reconstruction of low and medium producing grain crop fields; done a good job in monitoring and forecasting as well as pest control against food crops and promoted pollution-free cultivation of food crops. All these have speed up the conversion and application of scientific and technological achievements in agriculture, improved the contribution of technology to agricultural growth rate and promoted agricultural aggregate production, cleaner production, safety production and sustainable development. According to statistics in 2007, in Heilongjiang province the scientific research funds have accounted for 10.05% of the R&D expenses and 1607 technical contracts were signed with technical contract turnover summed to 3.502 billion Yuan, increased by 123.20 percent compared with 2006. However, as is known from the research, agricultural application project is still not fully utilized. In recent 5 years the conversion of technological achievements in agriculture is relatively slow in Heilongjiang Province, and until now the conversion of technological achievements in rural areas are still relatively low, which is well below the level of more than 90% in developed countries.

    D. Marketization in Agricultural Investment is the Anchorage Force for the Development in the Agricultural industry clusters

    The financial demand of financing body in agricultural industry clusters shows the multilevel characteristics, it is very necessary to meet the reasonable financial demand from various bodies to jointly improve the strength of various bodies and secure the close relationship among the industrial chain. Over the years, the rural financial sector in Heilongjiang Province has given great support in the development in agriculture, which has made an outstanding contribution to promoting the overall development in agriculture and rural economy, accelerating the rational distribution in agricultural regions and actively developing agricultural industrialization management. According to the survey, the ratio of agricultural loan in Heilongjiang to the total increased from 3.1% in 2002 to 7.52% in 2007, an

    [6]increase of percentage year by year, but agricultural loan still remains a sign of credit deficiency.

    In recent years, Heilongjiang Province has developed agricultural leading enterprises, promoted projects and increased their potential to effective expand. However, China's capital market, whether the stock market or bond market are mainly oriented to state-owned enterprises and large enterprises and thus it is extremely difficult for agriculture industry to make use of the capital markets for securities financing. Only 2 of the 26 listed companies in Heilongjiang Province operate in agriculture and forestry as well as animal husbandry and fishery industries. At the same time, with the improvement of the degree of market economy, the phenomenon of rural capital outflows becomes increasingly serious, which has seriously hampered the pace of economic development in localities and formed a bottleneck for rural economic development. As a big agricultural province, rural financial services in Heilongjiang Province have not yet met the needs for further development in the agricultural industrialization. The lack of financial services, the slow process in the marketization of agricultural capital investment and the gap from the real market certainly will influence the development and expansion in agricultural industry clusters.

    E. Marketization in Agricultural Circulation is the booster for the Development in Agricultural Industry Clusters

    Over the past 20 years organizations for farm produce circulation in Heilongjiang have experienced the process of development from the non-standard to the relatively standard, from the loose to the dense, from the service-oriented to the solid and then the modern circulation system has basically formed. According to statistics, in 2007 Heilongjiang province has built 142 agricultural and sideline products wholesale markets, fair trade turnover reached 93.71 billion and there are 34 wholesale markets with the transaction amounted to more than 100 million Yuan as well as 1744 fair trade markets throughout the province. With the scale and grade continuously improving, the market network is basically formed, which is with the leading force from provincial wholesale markets, based on the various commercial networks in small and medium cities as well as the fair trade markets throughout urban and rural areas, and with the combination of domestic and foreign trade, the large, medium and small, the professional and the comprehensive, as well as the wholesale and the retail. However, due to the lack of unified planning and the blindness in the development of rural markets, circulation of agricultural products suffers from low efficiency. There are several problems in the rural commodity markets known as the insufficient total amount, the identical structure and the irrational distribution. More than 98% of the transaction in the wholesale markets of agricultural products is based on the traditional spot and rival transaction. Seen from the circulation subject, there's a significant decline in the rural distribution network of state-owned circulation enterprises, in which some like supply and marketing cooperatives, goods and materials and commerce have gone bankrupt in individual regions, thus can not play the role as the main channel. Although individual business acts actively, the limitation in transportation, operation and large storage facilities, results in the supply fault in large means of production and durable consumer goods, which forces quite a few farmers flow to town to buy large commodities, daily necessaries from the individual and general merchandise from the fair trade market. Agricultural circulation channel is too long, links are excessive, circulation time is too long and logistics costs are high in Heilongjiang, which can greatly influence the circulation efficiency of agricultural products.

    In general, due to the fact that logistics industry of agricultural products in Heilongjiang is still at the

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