Scientific report: "The factors affecting the productivity of fabric and fabric channel selection consumption of fresh produce cloth in Thanh Ha district, Hai Duong Province, Vietnam" pptx

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Scientific report: "The factors affecting the productivity of fabric and fabric channel selection consumption of fresh produce cloth in Thanh Ha district, Hai Duong Province, Vietnam" pptx

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J. Sci. Dev. 2009, 7 (Eng.Iss.1): 123 - 129 HA NOI UNIVERSITY OF AGRICULTURE 123 Factors affecting lychee productivity and the choices of fresh lychee marketing channels of producers in Thanh ha district, Hai duong province, Vietnam Các yếu tố ảnh hưởng đến năng suất vải và sự lựa chọn kênh tiêu thụ vải tươi của người sản xuất vải ở huyện Thanh Hà, tỉnh Hải Dương, Việt Nam Nguyen Anh Tru Faculty of Accounting and Business Management TÓM TẮT Vải là một sản phẩm có giá trị cao, được trồng ở nhiều địa phương khác nhau ở Việt Nam như Hải Dương, Bắc Giang, Quảng Ninh, Lạng Sơn, v.v… Ở Việt Nam, vải được trồng đầu tiên ở huyện Thanh Hà, tỉnh Hải Dương. Tuy nhiên, trong những năm gần đây thu nhập của người trồng vải có xu hướng giảm do ảnh hưởng của điều kiện thời tiết, sự tăng giá vật tư đầu vào (phân bón, thuốc bảo vệ thực vật, v.v…) và sự giảm giá của sản phẩm vải. Mặt khác, người sản xuất phải đối mặt với nhiều khó khăn trong sản xuất, thu hoạch và tiêu thụ vải tươi. Nghiên cứu này được thực hiện nhằm xác định và đánh giá ảnh hưởng của các yếu tố đến năng suất vải và lựa chọn các kênh tiêu thụ vải tươi của người sản xuất vải ở huyện Thanh Hà, tỉnh Hải Dương. Các phương pháp nghiên cứu bao gồm lựa chọn địa điểm nghiên cứu, chọn mẫu và phân tích mô hình kinh tế lượng. Trong phương pháp kinh tế lượng, hàm sản xuất Cobb-Douglas và mô hình logit đã được sử dụng để đánh giá ảnh hưởng của các yếu tố đến năng suất vải và lựa chọn kênh tiêu thụ vải tươi của người sản xuất vải ở huyện Thanh Hà, tỉnh Hải Dương. Từ khóa: Kênh tiêu thụ, logit, lựa chọn, năng suất, vải tươi. SUMMARY Lychee is a high value commodity. Lychee is planted in the different provinces in Vietnam such as Haiduong, Bacgiang, Quangninh, Langson, etc. Thanhha district in Haiduong province is considered as one of the original production areas of lychee in Vietnam. However, benefits of lychee production in Thanhha district, Haiduong province tended to be declined in recent years because of climate, increasing in input prices (fertilizer, chemical, pesticides, etc.) and decreasing in lychee prices. Lychee producers had to face therefore several challenges in production, postharvest and marketing of fresh lychee. The study was designed to identify and estimate the effects of factors on lychee production and the choices of fresh lychee marketing channels of producers in Thanhha district, Haiduong province. Research methodologies are used in the study consisted of selection of the study area, sampling design and econometric analysis. In terms of econometric analysis, the Cobb-Douglas production function and the binary logit model are used to evaluate the effects of factors on the lychee productivity and the choices of fresh lychee marketing channels of producers in Thanhha district, Haiduong province. Key words: Choices, fresh lychee, logit, marketing channels, productivity. Factors affecting lychee productivity and the choices of fresh lychee marketing 124 1. INTRODUCTION Lychee is a high value commodity. Hence, commercial lychee growing has advantages to improve the farmer’s income. The profit generated in producing lychee is estimated to be five times more than that by rice production (Vandeveer, 2000). With 14,000 hectares of planted area and production of 21,813 tons, Haiduong becomes the second largest lychee producing province after Bacgiang province. Additionally, Haiduong is known as an origin of important varieties of lychee in Vietnam such as Thieu, Thieu Thanhha and Lai Thanhha. After the economic transformation in the country, production and marketing of fresh lychee have changed. In Thanhha district (Haiduong province), there are various stakeholders who participate in production, processing, marketing and distribution of fresh lychee. These included growers, collectors, processors, wholesalers, retailers and consumers. The study mentioned factors affecting lychee productivity, included producers’ experience, and number of family labor, capital, planted area, manure, fertilizers, pesticides, density, gender and participation in the lychee association. In the other word, several factors that affect the choices of fresh lychee marketing channels of producers in Thanhha district, Haiduong province, included producers’ experiences in lychee growing, number of family labor, volume of lychee, selling prices, distance to markets, gender of producers and participation in the lychee association. In this study, influences of these factors are estimated through applying the binary logit model. Research objectives  Estimate the factors that affect the lychee productivity in Thanhha district, Haiduong province;  Estimate the effects of factors on the choices of fresh lychee marketing channels of producers in Thanhha district, Haiduong province. 2. METHODS 2.1. Selection of the study area The study covered Thanhha district (Haiduong province) due to the following reasons: 1) Thanhha district is known as an origin of lychee tree in Vietnam; 2) the quality of lychee in Thanhha district is greater than that in other locations; 3) lychee planted area (5,600 hectares) and productivity (15,000 tons/year) in Thanhha are ranked as the second largest lychee production zone behind Chilinh district (Haiduong province); and 4) lychee distribution and marketing in Thanhha district has to face several challenges. 2.2. Sampling design According to Salvatore and Reagle (2002), a random sample size (n) is satisfied if it is at least equal to 5% of the population size (N) and the number of observations is at least equal to 30 (n ≥ 30). There are 25 communes (N = 25) in Thanhha district. Lychee is cultivated in all of communes in Thanhha. However, Thanhha is divided into three lychee cultivated zones consisting of zone 1 (5 communes), zone 2 (16 communes), and zone 3 (4 communes). Therefore, the study included only three communes in each zone (n = 3). Three communes (Thanhson, Thanhbinh and Viethong) were selected because: (1) farmers in these communes have more experiences in lychee cultivation compared to other locations; (2) these communes have the largest lychee planted area and highest lychee productivity in Thanhha district; (3) lychee markets are quite active in these communes; and (4) lychee planted area of each commune is over 60% of total agricultural area. According to the Chairman of three communes (Thanhson, Thanhbinh and Viethong), there are 880 lychee farms in Thanhson, 763 lychee farms in Thanhbinh and 679 lychee farms in Viethong. Based on population above, the sample respondents given the criteria (n = 5%N; n ≥ 30) were selected: Thanhson commune (44 farmers); Thanhbinh commune (39 farmers); and Viethong commune (34 farmers). Lychee farmers were chosen randomly from the lists of farmers provided by heads of villages. Therefore, a total of 117 farmers were interviewed in the study (Figure 1). 2.3. Econometric analysis 2.3.1. The Cobb-Douglas production function The Cobb-Douglas production function is used to assess the impacts of determinants (explanatory variables) such as producers’ experience, number of family labor, capital, planted area, manure, fertilizers, pesticides, density, gender and participation in the lychee association on the lychee productivity (dependent variable). Nguyen Anh Tru 125 Figure 1. Number of lychee farmers interviewed in Thanhha district, Haiduong province, Vietnam The Cobb-Douglas production function form: Y = A.X 1 α1 X 2 α2 X 3 α3 X 4 α4 X 5 α5 X 6 α6 X 7 α7 X 8 α8 e β1.D1 + β2.D2 +Ui (1) Where: Y: lychee productivity (kg/sao) A: the intercept that reveals combined impact of these fixed factors on lychee productivity X 1 : producers’ experience in lychee growing (years) X 2 : family labor (person) X 3 : started capital of farmers when growing lychee (VND 1,000) X 4 : planted area of lychee (sao) X 5 : manure (kg/sao/year) X 6 : fertilizers (kg/sao/year) X 7 : pesticides (VND 1,000/sao/year) X 8 : tree density (tree/sao) D 1 : gender dummy variable (male = 1; female = 0) D 2 : participation in the lychee association dummy variable (member = 1; non-member = 0) (α 1 ,…, α 8 ): coefficients of explanatory variables (X 1 ,…, X 8 ) β 1 : coefficient of gender dummy variable β 2 : coefficient of participation in the lychee association dummy variable e: natural lagarithms (e = 2.718) Ui: error term. Based on equation (1), we can transform the Cobb-Douglas function to logarithm form: LnY = LnA + α 1 lnX 1 + α 2 lnX 2 + α 3 lnX 3 + α 4 lnX 4 + α 5 lnX 5 + α 6 lnX 6 + α 7 lnX 7 + α 8 lnX 8 + β 1 D 1 + β 2 D 2 + Ui (2) Parameters (α 1,…, α 8 ) and (β 1, β 2 ) are estimated by OLS (Ordinary Least Square) methodology through SPSS 12.0 program. 2.3.2. The binary logit model The binary logit model was applied to estimate the effects of explanatory variables on marketing channel choices of lychee producers (dependent variable). The explanatory variables affecting marketing channel choices of producers consisted of producers’ experiences in lychee growing, number of family labor, volume of lychee, selling prices, distance to markets, gender of producers and participation in the lychee association. Then, the Thanhha district (n = 117) Zone 1 Villages Thanhson commune (44 farmers) Thanhbinh commune (39 farmers) Viethong commune (34 farmers) Zone 2 Zone 3 Factors affecting lychee productivity and the choices of fresh lychee marketing 126 parameters were estimated by maximum likelihood technique throughout the SPSS 12.0 program. In logit model, the dependent variable is generated from binary response. This model is based on the cumulative logistic probability function. It is used assuming that the probability of an individual making a choice is a linear function of the individual attributes (Pindyck and Rubinfeld, 1981). The logit technique allows examination of the effect of a number of variables on the underlying probability of a dichotomous dependent variable. In the binary logit model, marketing channel choices of producers (dependent variable) obtained 2 values: P = 0: if producers sell lychee to consumers P = 1: if producers sell lychee to local collectors Linear form of the logit function: Ln[P i /(1 – P i )] = α + ß i X i + ε i (3) Where: i presents the individual i, ε i is error term. The parameters were estimated by maximum likelihood technique. The marginal effects of X i on P i were measured by taking partial derivative of P i with respect to X i . In logit model, marginal effect represents the change in probability affected by a unit change in X i , ceteris paribus. The logit function form: Ln[P i /(1 – P i )] = α o + α 1 .X 1 + α 2 .X 2 + α 3 .X 3 + α 4 .X 4 +α 5 .X 5 +β 1 .D 1 + β 2 .D 2 + ε i (4) Where: P i : the probability of marketing channel choices α o : intercept, that implies the combined impact of these fixed factors on decisions of producers in marketing channel selection X 1 : producers’ experiences in lychee growing (years) X 2 : number of family labor (person) X 3 : volume of lychee (ton/year) X 4 : selling prices (VND 1,000/kg) X 5 : distance to markets (km) D 1 : gender dummy variable (male = 1; female = 0) D 2 : participation in the lychee association dummy variable (member = 1; non-member = 0) α 1,…, α 5 : coefficients of explanatory variables (X 1 ,…,X 5 ) β 1 : coefficient of gender dummy variable β 2 : coefficient of participation in the lychee association dummy variable ε i : error term. 3. RESULTS 3.1. Factors affecting the lychee productivity In Thanhson commune R squared equaled 0.866 implied that 86.6% changes of lychee productivity are affected by explanatory variables in the model and the rest (13.4%) changes due to other variables. Producers’ experience, number of family labor, capital and gender had positive effects on lychee productivity. 1% increasing in producers’ experience, number of family labor and capital, respectively led to increasing 1.59%, 20.45% and 0.01% in lychee productivity, respectively, ceteris paribus. This implied that if producers have more experience, labor, and capital then they gain higher productivity. Variables (planted area, manure and density) affected negatively lychee productivity. 1% increasing in planted area, manure and density, respectively led to decreasing 3.66%, 0.32% and 15.71% in lychee productivity, respectively, ceteris paribus. Other variables were not significant (Table 1). In Thanhbinh commune R squared equaled 0.764 implied that 76.4% changes of lychee productivity are affected by explanatory variables in the model and the rest (23.6%) changes due to other variables. Producers’ experience, number of family labor and capital had positive effects on lychee productivity. 1% increasing in producers’ experience, number of family labor and capital, respectively led to increasing 0.45%, 28.27% and 0.01% in lychee productivity, respectively, ceteris paribus. This implied that if producers have more experience, labor, and capital then they gain higher productivity. Other variables were not significant (Table 1). In Viethong commune R squared equaled 0.863 implied that 86.3% changes of lychee productivity are affected by explanatory variables in the model and the rest (13.7%) changes due to other variables. Capital had positive effects on lychee productivity. 1% increasing in capital led to increasing 0.02% in lychee productivity, ceteris paribus. This implied that if producers use more capital then they gain higher productivity. Density affected negatively lychee productivity. 1% increasing in density led to decreasing 17.08% in lychee productivity. Other variables were not significant (Table 1). Nguyen Anh Tru 127 Table 1. Estimation of coefficients affecting lychee productivity in Thanhha district, Haiduong province, Vietnam, 2007 Variable Thanhson (n = 44) Thanhbinh (n = 39) Viethong (n = 34) Overall (n = 117) (Constant) 558.64*** 411.72*** 547.01*** 476.76*** Producers’ experience in lychee growing (years) 1.597** 0.456 NS -0.623 NS 1.078** Number of family labor (person) 20.453*** 28.277** 2.588 NS 16.162*** Capital (VND 1,000) 0.015*** 0.015*** 0.024*** 0.018*** Planted area (sao) -3.665*** -0.873 NS -0.019 NS -1.961** Manure (kg/sao/year) -0.324* -0.049 NS -0.004 NS -0.107 NS Fertilizers (kg/sao/year) -0.011 NS 0.008 NS 0.004 NS 0.005 NS Pesticides (VND 1,000/sao/year) -0.105 NS -0.070 NS 0.486 NS -0.009 NS Density (tree/sao) -15.713*** -3.898 NS -17.086*** -9.337*** Gender dummy variable 32.796* 0.012 NS 1.931 NS 9.579 NS Participation in the lychee association dummy variable 12.286 NS 18.753 NS 24.436 NS 18.218** R squared 0.866 0.764 0.863 0.798 Ajusted R squared 0.826 0.68 0.803 0.779 F 21.414 9.089 14.447 41.898 Note: 1 sao equals 360 square meter ***, ** and * mean significant at the 1%, 5% and 10%, respectively NS means not significant Source: Based on survey data, 2007 In the overall model (Thanhha district) R squared equaled 0.798 implied that 79.8% changes of lychee productivity are explained by explanatory variables in the model and the rest (20.2%) changes of lychee productivity due to other determinants. Variables (producers’ experience, number of family labor, capital, and participation in the lychee association) had positive effects on lychee productivity. 1% increasing in producers’ experience, number of family labor and capital, respectively led to increasing 1.07%, 16.16% and 0.01% in lychee productivity, respectively, ceteris paribus. This implied that if producers have more experience, labor, and capital or they participate to association then they gain higher productivity. Variables (planted area and density) affected negatively lychee productivity. 1% increasing in planted area and density, respectively led to decreasing 1.96% and 9.33% in lychee productivity, respectively, ceteris paribus. If farmers have large planted area of lychee (30 sao) then it is so difficult for them to consider planting protection, irrigation, harvest, fertilizers and so on. On the other hand, some farmers planted lychee with a rich density (13 trees/sao). Based on scientists, the appropriate density of lychee tree was 8 trees per sao. Therefore, they gained lower productivity compared to others. Other variables were not significant (Table 1). Factors affecting lychee productivity and the choices of fresh lychee marketing 128 Table 2. Coefficients of the logit model on marketing channel choices of producers in Thanhha district, Haiduong province, Vietnam, 2007 Variable Coefficients (B) Exp(B) (Constant) -3.834 NS (α 0 ) 0.022 Producers’ experience in lychee growing (years) 0.027 NS (α 1 ) 1.027 Number of family labor (person) -0.233 NS (α 2 ) 0.792 Volume of lychee (ton/year) -0.008* (α 3 ) 0.992 Selling price (VND1,000/kg) 0.060*** (α 4 ) 0.848 Distance to markets (km) 0.183** (α 5 ) 0.791 Gender dummy variable 1.027* (β 1 ) 2.792 Participation in the lychee association dummy variable -0.749 NS (β 2 ) 0.473 LR chi2(7) 27.566 Number of observations 117 Note: ***, ** and * mean significant at 1%, 5%, and 10%, respectively NS means not significant Source: Based on survey data, 2007 3.2. Influences of factors on the choices of fresh lychee marketing channels The binary logit model was used to estimate the effects of explanatory variables on marketing channel choices of producers (dependent variable). Of 117 producers interviewed, 97 producers sold fresh lychee to local collectors, whereas 20 producers traded these fruits to consumers. 3.2.1. Influences of qualitative variables on the choices of fresh lychee marketing channels Assumption: β 1 and β 2 were coefficients of qualitative variables in the model. Exp (B) of gender dummy variable was 2.792 (e 1.027 = 2.718 1.027 ) implied that the number of male producers was greater than that of female producers by 2.792 times (Table 2). In the model, variables (producers’ experience in lychee growing, number of family labor and participation in the lychee association) were not significant (Table 2). 3.2.2. Influences of quantitative variables on the choices of fresh lychee marketing channels Assumption: α 1 , …, α 5 were coefficients of quantitative variables in the model. In terms of quantitative variables, we could measure the expected values by: ∂P/∂X i = {Exp(X i , α)/[1 + Exp(X i , α)] 2 }.α i Let Exp(X i , α) = a, we have: ∂P/∂X i = [a/(1 + a) 2 ].α i  The effect of volume of lychee (X 3 ) on marketing channel choices ∂P/∂X 3 = [a/(1 + a) 2 ].α 3 = [0.992/(1 + 0.992) 2 ](-0.008) = -0.002 = -0.2% implied that if the volume of lychee increases by 1 unit, then the probability of producers selling to local collectors decreases by 0.2%, ceteris paribus. Because of excess supply of fresh lychee and the shorter storage time, producers have to sell fresh lychee as soon as possible (Table 2).  The effect of price variable (X 4 ) on marketing channel choices ∂P/∂X 4 = [a/(1 + a) 2 ].α 4 = [0.848/(1 + 0.848) 2 ](0.060) = 0.0148 = 1.48% implied that if the price increases by 1 unit, then the probability of producers selling to local collectors increases by 1.48%, ceteris paribus. Because of the increase in price, producers prefer to sell to local collectors to reduce transportation cost, save time, and gain higher profits (Table 2).  The effect of distance variable (X 5 ) on marketing channel choices ∂P/∂X 5 = [a/(1 + a) 2 ].α 5 = [0.791/(1 + 0.791) 2 ](0.183) = 0.045 = 4.5% implied that if the distance increases by 1 unit, then the probability of producers selling to local collectors increases by Nguyen Anh Tru 129 4.5%, ceteris paribus because producers want to reduce transportation cost and save time (Table 2). 4. CONCLUSION AND POLICY IMPLICATIONS There were several factors affecting the lychee productivity and the choices of fresh lychee marketing of producers in Thanhha district, Haiduong province. In the overall model, variables (producers’ experience, number of family labor, capital, and participation in the lychee association) had positive effects on lychee productivity. Variables (planted area and density) affected negatively lychee productivity. Other variables were not significant. In terms of the binary logit model, results showed that selling price, distance to market and gender dummy variables had positive and significant influence on the choices of marketing channels of lychee producers. Exp(B) of gender dummy variable was 2.792, implied that in terms of marketing channel choices, the number of male producers was greater than that of female producers by 2.792 times. Coefficient (α 3 = -0.002) implied that if the volume of lychee is increased by 1 unit, then the probability of producers selling to local collectors decreases by 0.2%, ceteris paribus. Coefficient (α 4 = 0.0148) implied that if the selling price increases by 1 unit, then the probability of producers selling to local collectors increases by 1.48%, ceteris paribus. Coefficient (α 5 = 0.045) implied that if the distance to market increases by 1 unit, then the probability of producers selling to local collectors increases by 4.5%, ceteris paribus. Other variables were not significant. Based on estimated coefficients in overall model (Thanh Ha district), lychee producers should increase labor force and capital as well as participation in the lychee association to improve lychee productivity. In the other word, farmers should not plant lychee with a rich density because of lower productivity. Volume of lychee, selling price and distance to market affected marketing choices of producers in terms of selling lychee. Excess supply of fresh lychee led to decline in selling price. If selling price and distance to market increase, then producers tend to sell fresh lychee to local collectors because they expect to reduce transportation cost and gain higher profit. Transportation roads and distribution networks of fresh lychee should be reorganized to improve benefit of lychee producers. REFERENCES Gujarati, D.N. (2005). Basic Econometrics, 4 th Edition. Tata McGraw-Hill Publishing Company Limited, New Delhi, India. Haiduong Department of Agriculture and Rural Development. (2006). Report on Aspects and Solutions for Improvement of Economic Efficiency of the Thieu Lychee Tree in Haiduong province. Hellin, J. and M. Meijer. (2006). Guidelines for Value Chain Analysis. Food and Agriculture Organization of the United Nations (FAO), Rome, Italy. Tru, N.A. (2008). The Value Chain Analysis of Lychee in Haiduong Province, Vietnam. MS Thesis at the University of the Philippines Los Banos, Philippines. . choices of fresh lychee marketing channels of producers in Thanhha district, Haiduong province. 2. METHODS 2.1. Selection of the study area The study covered Thanhha district (Haiduong province). association. In the other word, several factors that affect the choices of fresh lychee marketing channels of producers in Thanhha district, Haiduong province, included producers’ experiences in lychee. - 129 HA NOI UNIVERSITY OF AGRICULTURE 123 Factors affecting lychee productivity and the choices of fresh lychee marketing channels of producers in Thanh ha district, Hai duong province,

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