A Critical Analysis of the Value Chain in the Rice Industry and Its Effects on the Export Rice Industry in Kien Giang Province, Vietnam

The study of a critical analysis of the value chain in the rice industry and its effects on the export rice industry in Kien Giang province, Vietnam conducted during the period from December 2012 to November2015. The research result showed that there were 450 persons who are rice exporters and farmers (412 processed and 48 missed) who to be interviewed and answered nearly 27 questions. The researcher had analyzed KMO test, the result of KMO analysis used for multiple regression analysis. The person responses measured through an adapted questionnaire on a 5-point Likert scale. Hard copy and interviewrice exporters and farmersby questionnaire distributed among rice exporters and farmers in KienGiang province. The regression analysis results showed that there were seven factors, which included of factors following: Development strategy; Control policy; Planning; Support policy; Rice seeds;Cultivation techniques andPost-harvest processingactually affected the export rice industry with 5 % significance level. The main objectives of this study were to to conduct a survey to find value chain that affecting the export rice industry in KienGiang province, to identify value chain that affected on the export rice industry in KienGiang province and to analyze and to test value chain that affected the export rice industry in KienGiang province.


Introduction
Agriculture plays a relatively important role in the economy of Vietnam. Agriculture contributes 24% of GDP and generates 20% of export revenues. Over 70% of the national labor force is employed in the agriculture sector, and a further 6% is employed in the agricultural postproduction sector. Vietnam exported some 7. also because farmers are facing high production costs for fertilizer and gasoline," Phong said. Despite the start of the harvest season in the Mekong Delta region, high global demand continues to push prices of exportable rice higher in the local market. Most of Vietnam's rice for export is grown in the Mekong Delta region.

Literature Review
Often multinational enterprises (MNEs) developed global value chains, investing abroad and establishing affiliates that provided critical support to remaining activities at home. To enhance efficiency and to optimize profits, multinational enterprises locate "research, development, design, assembly, production of parts, marketing and branding" activities in different countries around the globe. MNEs offshore labor-intensive activities to China and Mexico, for example, where the cost of labor is the lowest (Gurría, 2012).The emergence of global value chains (GVCs) in the late 1990s provided a catalyst for accelerated change in the landscape of international investment and trade, with major, far-reaching consequences on governments as well as enterprises. (Gurría 2012) Through global value chains, there has been growth in interconnectedness as MNEs play an increasingly larger role in the internationalization of business. In response, governments have cut corporate income tax (CIT) rates or introduced new incentives for research and development to compete in this changing geopolitical landscape. (LeBlanc et al). In an (industrial) development context, the concepts of Global Value Chain analysis were first introduced in the 1990s (Gereffi et al.) and have gradually been integrated into development policy by the World Bank, Unctad, the OECD and others. Value chain analysis has also been employed in the development sector as a means of identifying poverty reduction strategies by upgrading along the value chain. Although commonly associated with export-oriented trade, development practitioners have begun to highlight the importance of developing national and intra-regional chains in addition to international ones.
The value-chain concept has been extended beyond individual firms. It can apply to whole supply chains and distribution networks. The delivery of a mix of products and services to the end customer will mobilize different economic factors, each managing its own value chain. The industry wide synchronized interactions of those local value chains create an extended value chain, sometimes global in extent. Porter terms this larger interconnected system of value chains the "value system". A value system includes the value chains of a firm's supplier (and their suppliers all the way back), the firm itself, the firm distribution channels, and the firm's buyers (and presumably extended to the buyers of their products, and so on).
The agricultural value chain. It concept has been used since the beginning of the millennium, primarily by those working in agricultural development in developing countries. Although there is no universally accepted definition of the term, it normally refers to the whole range of goods and services necessary for an agricultural product to move from the farm to the final customer or consumer.The term value chain was first popularized in a book published in 1985 by Michael Porter, who used it to illustrate how companies could achieve what he called "competitive advantage" by adding value within their organization. Subsequently the term was adopted for agricultural development purposes and has now become very much in vogue among those working in this field, with an increasing number of bilateral and multilateral aid organizations using it to guide their development interventions.
The Rice Value Chain. The Bill & Melinda Gates Foundation are focusing on rice as a key crop in their fight to improve nutrition and increase smallholder farmer incomes. TechnoServe worked with the Gates Foundation to analyze the rice sector throughout India and Bangladesh, providing detailed studies of the rice value chains in selected states and identifying potential regions, partners and intervention models for future interventions on a large scale across India and Bangladesh. Besides, the rice value chain analysis was undertaken at the request of International Fund for Agriculture Development and Community Based Agriculture & Rural Development Project. The analysislooked how rice was produced, processed and ultimately marketed to the consumers. Theobjective was to see how the value chain could be enhanced for the primary benefit of thesmallholder producers.
The analysis indicted the value chain was similar to the value chain of most commoditiesproduced and marketed domestically in financially suppressed economies common to thedeveloping world including Nigeria. That is the value chain was dominated by a multitude ofsmall family enterprises, each vying for a limited market share. This includes the smallholderproducers as family enterprises. The value chain could be conveniently divided betweenproduction which is mostly the farmers and support services, processing which is a combinationof parboiling and milling, and marketing which is mostly bulk through the open air markets.
Enhancing the value chain for the benefit of the smallholder producers should start at theproduction end where the smallholder farmers have the most direct involvement. Here the initialneed is to increase the rice area allocated to each farmer, so the farmers will concentrate on riceproduction as their primary farm enterprise. With the present small allocations farmers have littleincentive to concentrate on rice cultivation.  H 6 : There is a positive relationship between Cultivation techniquesand the export rice industry. H 7 : There is a positive relationship between Post-harvest processing and the export rice industry.

Research Method
This study has not been fully considered all factors that influence sustainability. This dissertation focuses on considering the impacts of components. The researcher had surveyed 150 exporters and 300 farmers (450 persons who are rice exporters and farmers in KienGiang province). In this study, there are consists of two phases: First: it is a preliminary study and the second phase is a formal and more comprehensive study. This study is done by qualitative methods. The research is done by formal quantitative methods. Unit of analysis is a student. Study subjects are persons who are rice exporters and farmers in KienGiang province.
The preliminary study for exporters and farmersconducted in 10/2014, using qualitative methods to interview 30 persons who are rice exporters in KienGiang province to examine the content and meaning of the words used in the scale. Following this, the formal study conducted in May 2014, using qualitative methods to interview 450 persons who are rice exporters and farmers in KienGiang province. The researcher should select one of these methods of collecting the data taking into consideration the nature of investigation, objective and scope of the inquiry, financial resources, available time and the desired degree of accuracy.However, I should pay attention to all these factors but much depends upon the ability and experience of the researcher.
The population of this study was all 350 exporters and 3000 farmers in KienGiang province. The values of the random variable of interest could possibly be determined. This notion corresponds directly to the frame in sample survey literature. The difference between the attributes of interest in the study population and the corresponding attributes in the target population called the study error. This is a simple quantitative assessment for numerical attributes but can be challenging to define for graphical ones. The study population and the study units were very different from the target in this instance. The statistical method ensures consideration of the relevance of the study population to the target population by forcing investigators to deal directly with the study error. Criteria beyond the study error such as cost, convenience, and ethics is important in determining the study population.
After preliminary investigations, formal research done by using quantitative methods questionnaire survey of 150 exporters and 300 farmers (450 persons who are rice exporters and farmers in KienGiang province).The reason tested measurement models, model and test research hypotheses. Data collected were tested by the reliability index (excluding variables with correlation coefficients lower<0.30 and variable coefficient Cronbach's alpha <0.60), factor analysis explored (remove the variable low load factor <0.50). The hypothesis tested through multiple regression analysis with linear Enter method. The subjects of this survey are exporters and farmers and sample size 450 persons. The survey will be done by surveying exporters and farmers who have been treatment in KienGiang province. Now, Kien Giang provinceAdministrative divisions: Kien Giang is divided into one city (Rach Gia), one town (Ha Tien), and 13 districts (Kien Luong, Hon Dat, Tan Hiep, Chau Thanh, Giong Rieng, Go Quao, An Bien, An Minh, Vinh Thuan, Phu Quoc, Kien Hai, U Minh Thuong, Giang Thanh).

Research Results
The researcher collected 150 exporters and 300 farmers (450 persons who are rice exporters and farmers in KienGiang province) to analyze multiple regressions. Data from questionnaires analyzed using the descriptive statistics with the help of data analysis software -Statistical Package for Social Sciences (SPSS 20.0) package. We can see the demographic characteristics of the exporters and farmers table 1 following. The Government should build the safe production of raw materials on a large scale and advanced technology as standard VietGap and international standard  PL3: State planning system enterprises exporting rice processing industry planning of rice processing  PL4: Application of modern processing technology to produce qualified products that meet the demanding markets 

Support policy (SP)
Level of Agreement SP1: The Government and relevant ministries need support policies as policies on preferential credit support to enterprises and farmers to grow rice  SP2: Policies to encourage scientific research activities to create rice varieties with high yield and good quality  SP3: Policies to attract foreign investment in order to boost investment process in depth 

RS2: Tight control element for rice disease 
RS3: Elements of plant protection products for rice   Table 2 showed there were 26 questions for the value chain affecting the export rice industry. 26 questions following: Development strategy (DS) has 4 items, Control policy (CP) has 3 items, Planning (PL) has 4 items, Support policy (SP)has 3 items, Rice seeds (RS) has 3 items, Cultivation techniques (CT) has 3 items and Post-harvest processing (PH)has 3 items. The export rice industry has 3 items. We used scales 5 five score following: 1: Strongly disagree; 2: Disagree; 3: Normal; 4: Agree and 5: Strongly agree.

Cultivation techniques (CT) Level of Agreement
The researcher used descriptive and summary statistics has an extensive history and, indeed, the simple tabulation of populations and of economic data was the first way the topic of statistics appeared. More recently, a collection of summarization techniques has been formulated under the heading of exploratory data analysis: an example of such a technique is the box plot.Descriptive statistics is the discipline of quantitatively describing the main features of a collection of information, or the quantitative description itself. Descriptive statistics are distinguished from inferential statistics (or inductive statistics), in that descriptive statistics aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent. This generally means that descriptive statistics, unlike inferential statistics, are not developed on the basis of probability theory. Even when a data analysis draws its main conclusions using inferential statistics, descriptive statistics are generally also presented the following of Table 3.  Table 3 showed that there were 412 persons who are rice exporters and farmers in KienGiang province. Theyinterviewed and processed from 10/2014 to 6/2015. The results showed that max value is 5, minimum is 1, mean is around 3.0 and Std. Deviation is around 1.0. Alpha = 0.720 The Table 4 revealed that all Development strategy; Control policy; Planning; Support policy; Rice seeds; Cultivation techniques and Post-harvest processing (26 items) are very good for this research. The researcher continuesto analyze the EFA to assess more accurately the scale, helping the uniform scale in research. Thus, based on EFA analysis, the researcher will evaluate the homogeneity of the observed variables and can be classified because of specific variables. Besides, Cronbach alpha coefficient if the removal variables is more than 0.6. In addition, the correlation coefficient of the total variations is more than 0.3.
KMO & Bartlett's Test of Sphericity is a measure of sampling adequacy that recommended checking the case to variable ratio for the analysis conducted. In most academic and business studies, KMO & Bartlett's test play an important role for accepting the sample adequacy. While the KMO ranges from 0 to 1, For Factor Analysis recommended suitable, the Bartlett's Test of Sphericity must be less than 0.05.  Table 5 showed that Kaiser-Meyer-Olkin Measure of Sampling Adequacy was statistically significantandhigh datareliability (KMO = 0.763> 0.6). This result was very good for data analysis. Table 5 showed that Cumulative percent was statistically significantandhigh datareliabilitywas 80.804 % (> 60 %). This is very good Data for next research.  Table 6 showed that Structure Matrix for the factors affecting the export rice industryhad sevenComponents. Component 1 was Development strategy (X1), Component 2 was Control policy (X2), Component 3 was Planning (X3), Component 4 is Support policy(X4), Component 5was Rice seeds (X5), Component 6 was Cultivation techniques(X6) and Component 7was Post-harvest processing (X7) affecting the export rice industry. .000 Source: The researcher's collecting data and SPSS Table 7 showed that KMO and Bartlett's Test for the sustainabilityshowed that Kaiser-Meyer-Olkin Measure of Sampling Adequacy was statistically significantandhigh datareliability (KMO = 0.649> 0.6).  Table 8 showed that the result was very good for data analysis. The export rice industryshowed that cumulative percent was statistically significantandhigh datareliabilitywas 63.198 % (> 60 %). Extraction Method: Principal Component Analysis.Rotation Method: Promax with Kaiser Normalization.Total variance explained for the export rice industry is 63.198 %. Besides, total of Initial Eigenvalues is 1.926> 1.

Conclusion
This study investigated how the export rice industry could be measured following: First of allDevelopment strategy (X1) affecting on the export rice industrywith significance level of five percent. The secondly, the Control policy (X2) affecting on the export rice industrywith significance level of five percent. Thirdly, the Planning (X3) affecting on the export rice industrywith significance level of five percent.Fourthly, the Support policy (X4) affecting on the export rice industrywith significance level of five percent.Fifthly, the Rice seeds (X5) affecting on the export rice industrywith significance level of five percent.Sixthly, the Cultivation techniques (X6) affecting on the export rice industry with significance level of five percent. Finally, the Post-harvest processing (X7) affecting on the export rice industry with significance level of five percent.
Although rice productivity of KienGiang province is high, with yields averaging 5.3 tonnes per hectare, there are significant differences between regions. In some areas of the KienGiang province, we have some farmers achieving up to 10-12 tonnes per hectare.
Rice plays an important role in the export earnings of the KienGiang province. Among the agricultural products, the rice is one of the commodity, which is exported to many countries in the world and contributing considerable share in the export earnings of total agricultural products. The KienGiang province had export earnings realized from the export of the rice during the last years.
The results of data analysis revealed that respondents consider the followingfactors as the most influential factors: