A Study on Factors Influencing the Added Value Improvement of Vietnam Tea Export Industry Phung Thi Trung, Dai Nam University, Vietnam. Abstract Tea is an important export product contributing significantly to the development of the agriculture of Vietnam. Until now, Vietnam businesses have exported tea to over 100 countries in the world and become one of the five largest tea exporters of the world. However, the added value of tea products of Vietnam is not considered high. Thus, the author conducted this study to investigate factors that have influence on the added value improvement of Vietnam tea export industry. The result showed that the added value improvement of Vietnam export tea industry is influenced the most by the factor Marketing (ß2= 0,293), followed by the factors Logistics (ß5= 0,228), Management (ß3= 0,187), Input (ß1= 0,174) and Information Technology (ß4= 0,136). The ANOVA test also showed that state companies have higher value than private companies and joint-venture companies. Businesses that have operated in the industry longer tend to have higher added value of tea products. However, the added value of Vietnam tea industry is relatively low in several countries such as Russia or Taiwan. Key Words: Added Value, Vietnam Tea Industry, Tea Export Market 1
1. Introduction Tea is a product contributing significantly to the agricultural export volume of Vietnam, thus, reducing the trade deficit of the country s economy. According to the Trade Stimulation Organization (2015), Vietnam s tea product has been exported to 100 countries all over the world. Vietnam has become one of the top five tea exporters of the world, only stay behind Kenya, China, Srilanka and India. According to the statistics of Vietnam Tea Association in 2012, the total export volume of tea was 148,000 tons, increased by 10.8% compared to 2011, and the exported tea product reached the value of 227 million USD, increased by 11.5% compared to that of 2011. In 2013, the export volume reached 141,400 tons and export value was 229.7 million USD. According to the Vietnam Office of Customs, in the first two months of 2015, the total export volume of tea product was 16,000 tons which valued 26,26 million USD. However, the exported products are mostly raw products; thus, the added value of tea product of Vietnam is still low compared to other countries. Judging by the value, the export price of Vietnam is still very low (1,200 USD/ha) while other countries such as Sri Lanka has reached 5,700 USD/ha, Kenya has reached 6,000 USD/ha. According to Le Viet Nga (2015), the reason of the low export price is because 90% of the export tea product are still raw materials, with only a few companies care about branding or packaging to improve their product vales. Besides, there are too many companies participating in exporting tea product which are only low quality products or raw materials. Thus, the appearance of these companies also damages the quality and competitiveness of Vietnam s tea product. Thus, it is necessary for the author to conduct a study titled A study on factors influencing the added value of Vietnam tea export industry. The author expects to provide companies and policy-makers of the tea industry with insights of the factors that have impact on the added value of tea industry, thus, helping them to make better decisions and plans to successfully join the global value chain of the product. 2. Literature Review Value chain is a concept first introduced by Michael Porter in 1985 in his famous book on competitive advantages. According to Porter (1985), value chain is a sequence of activities conducted by a company in a specific industry. The value of a product will increase as it goes through each activity. At the end of the sequence of activities, the added value of a product will be increased significantly compared to the beginning phase. Kaplinsky & Morris (2001) had built a model of activities in a value chain and proposed that added values are created the most at the R&D and Marketing phases, while the added values are added lower in the Design and Distribution phases and lowest at Production phase. A finished product will gain added value at every phase of the sequence. Among all phases of 2
the sequence, the factors that have the highest impract on the added value of a product are Input, Marketing and Sales, Human Resource Management, Information Technology and Logistics. According to Huu Anh et al (2015), Input refer to all activities of receiving, storing and managing input factors including raw material, transporting plan, storage plan. The operating activties such as producing, packaging and checking are employed to transfer input elements into a finished product. The improvement of each activity will lead to higher product quality, higher efficiency and faster response to the ups and downs of market, thus, helping a company to lower costs, improve productivity and added value. Kotler (2001) proposed that the marketing and sales of a company involve 4 main factors called 4P: Price, Product, Promotion and Place. Every product is subject to a life-cycle including a growth phase followed by a maturity phase and finally an eventual period of decline as sales fall. Marketers must do careful research on how long the life cycle of the product they are marketing is likely to be and focus their attention on different challenges that arise as the product moves. Price refers to the amount a customer pays for the product. The price is very important as it determines the company's profit and hence, survival. Adjusting the price has a profound impact on the marketing strategy and, depending on the price elasticity of the product, often it will affect the demand and sales as well. The marketer should set a price that complements the other elements of the marketing mix. Promotion refers to All of the methods of communication that a marketer may use to provide information to different parties about the product. Promotion comprises elements such as: advertising, public relations, sales organisation and sales promotion. Place refers to providing the product at a place which is convenient for consumers to access. Various strategies such as intensive distribution, selective distribution, exclusive distribution and franchising can be used by the marketer to complement the other aspects of the marketing mix. The role of the marketing channels is not only focus on the participate in demand satisfaction by offering goods, but also need to stimulate demand through information, creating proximity and promotion by customer. In other words, distribution channels for the product is a system process. Management influences all the activities of the sequence of values. According to Dinh Ton (2012), the cost of human resource management is not easy to identify. A lot of costs for management are rising quickly. Thus, improving the labor skills and maintaining good relationship among employers and employees are very important to improve productivity and value, and lower costs. According to Pham The Cong (2015), information system can be used to improve the competitve advangetages of a company, thus, improving added value for its products/services. For example, the Just-in-time approach has helped a lot of company to reduce its stored 3
materials as well as improving the productivity and lowering cost (Issar, G., & Navon, L. R., 2016). As a agricultural product, added value in the tea value chain is created the most in the distribution and marketing phases, then in R&D and processing phases. The phase that bring lowest added value is planting. The added value creation is also influenced by other factors such as input, management, information technology and logistics. The research model is shown below: Input Marketing Added value improvement of Export Tea Industry Management Information Technology Logistic Business Information - Business type - Length of operation - Export markets Research Model 2.1 Hypotheses H1. Input has influence on the increase of added value improvement of tea industry H2. Marketing has influence on the increase of added value improvement of tea industry H3: Management has influence on the increase of added value improvement of tea industry H4: Information Technology has influence on the increase of added value improvement of tea industry H5: Logistics has influence on the increase of added value improvement of tea industry H6: There are differences between variables of business information in the improvement of added value of tea industry - H6a: There are difference between business types in the improvement of added value of tea industry - H6b: There are difference between length of operation in the improvement of added value of tea industry - H6c: There are difference between exporting markets in the improvement of added value of tea industry 4
3. Research Method 3.1 Scale Measurement The author used the quantitative research method for this study. A Likert 5-point scale (1- completely disagree to 5 completely agree) was applied for the survey questionnaire to investigate the opinion of respondents upon the factors influencing the added value of Vietnam tea export industry. 3.2 Sample Size There were 400 questionnaire delivered to personnel of tea businesses in the North of Vietnam. The author received 326 answered questionnaires back. After screening phase, there were 240 questionnaires accepted (73.6%). 3.3 Descriptive Statistics The descriptive statistics was used to describe the demographic information of sample in the study. 3.4 Reliability Test Cronbach's alpha (α) is the coefficient of reliability used testing scale measuring correlations between pairs of variables observed. The purpose of this test is to determine the reliability of the observed variable for the scale. The variables that have the item-total correlation less than 0.3 will be removed and only variables with the item-total correlation higher than 0.65 are chosen. (Nunnally, 1994). 3.5 Exploratory Factor Analysis After running Cronbach s Alpha test, the EFA test was used to identify the underlying structure of variables and exploring the relationship between variables. Variables that factor loading value lower than 0.3 would be removed. The study used the principle components method that requires the total variance explained higher than 0.5. 3.6 Regression Analysis After running the exploratory factor analysis, the author conducted the regression analysis to investigate the impact of independent variables upon the dependent variable. The multiple regression analysis was run by the software SPSS version 20. The regression model was evaluated first through the R-Square and Adjusted R square. Then, the F-test and regression test would be conducted to check the relationship between independent variables and the dependent variable (Hoang & Chu, 2008) 4. Results 4.1 Demographic Result Gender: There are 162 male respondents (67.5%) and 78 female respondents (32.5%) taking part in the survey 5
Age: 33 respondents are in the age group 20-30 years old (13.8%), 105 respondents in the group 31-40 years old (57.5%), 78 respondents in the group 41-50 years old (32.5%) and only 24 respondents in the group over 50 years old (10%). Working position: there are 49 front-line manager (20.4%), 79 middle managers (32.9%), 112 senior managers (46.7%). Education: there are 19 respondents (7.9%) who have master degree, 131 respondents have bachelor degree (54.6%) and 90 respondents have college degree (37.5%). Working experience: Only 14 respondents have less than 5 years of experience working in the tea export industry (5.8%), 35 respondents have 5-10 years of experience (14.6%), 106 respondents have 11-15 years of experience (64.6%) and 85 respondents have over 15 years of experience (35.4%). This result shows that the majority of respondents have a lot of experience with the industry, thus, the opinion of the respondents can be considered reliable and significant. Exporting markets: respondents were asked to name their biggest exporting market, 46 respondents chose Pakistan (19.2%), 47 respondents named Russia (19.6%), 29 respondents named Taiwan (12.1%), 26 respondents named The United States of America (10.8%), 34 respondents chose China (14.2%), and 58 respondents named other markets such as UAE, Saudi Arabia, Indonesia, Poland (24%). Business types: there are 117 respondents working in state companies (48%), 66 respondents working in private companies (27.5%), 57 respondents working in joint venture companies (23.8%). The result shows that state companies still take the main role in exporting tea. Length of operation: there are 43 respondents said that their businesses have operated less than 5 years (17.9%), 71 respondents said that the length of operation of their businesses is 6-10 years (29.6%), 67 respondents pointed the length of operation is 10-15 years (27.9%) and 59 respondents said the length of business operation is over 15 years (24.6%). 4.2 Reliability Test and EFA Results The result indicated that businesses only showed moderate agreement with the statements listed in the questionnaires (mean = 2.88 3.90) The reliability test result of the independent factors showed that the Cronbach s Alpha value of 24/25 observed variables listed in the questionnaires is higher than 0.7. Besides, the Corrected Item Total Correlation of the observed variables is also higher than 0.3. Thus, the author concluded that except one observed variable of is removed, all the other observed variables are reliable and can used in the official questionnaire. After the reliability test, the author used the EFA to investigate the latent construct of the observed variables of the independent factors. 24 variables were put in the EFA and grouped into 5 independent factors. The KMO and Barlett s Test results satisfied the requirement of 6
the test (KMO = 0.851 > 0.5, Sig. = 0.000 < 0.05). The factor loading of all items also higher than 0.5. Thus, the author used these 5 factors with 24 original items as independent variables of the research model. For the dependent variables, the author also applied EFA with 6 observed variables intended for the dependent factors. The KMO and Barlett s Test results satisfied the requirement of the test (KMO = 0.803 > 0.5, Sig. = 0.000 < 0.05). The factor loading of all items also higher than 0.5. Thus, the author kept the same items for the dependent variable. 4.3 Regression Analysis Result The Adjusted R 2 is 0.671 indicating that the research model accounts for 67.1% of the variability of the data. Beside, the ANOVA result showed Sig. = 0.000 < 0.01, thus, indicating that the regression model can be used in this study. The VIF values are smaller than 2 in all cases, thus, the multi collinearity does not occur in this case. Based on the regression result, the regression formula is written as the following: Y = -407 + 0,174X 1+ 0,293X 2+ 0,187X 3+ 0,136X 4+ 0,228X 5 The Beta coefficient indicated that all the independent variables have positive influence on the dependent variable. The factor that has the strongest impact on the dependent variable is Marketing (ß 2= 0,293), followed by Logistics (ß 5= 0,228), Management (ß 3= 0,187), Input (ß 1= 0,174) and Information Technology (ß 4= 0,136). Regression Results Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (Constant) -.407.176-2.312.022 YTDV.174.038.215 4.634.000 1 HDM.293.043.324 6.755.000 QT.187.042.187 4.470.000 CNTT.136.036.155 3.774.000 LGT.228.040.261 5.672.000 R 2 = 0,671 ; F= 95,530 ( P = 0,000) a. Dependent Variable: GTGT 5. Conclusion Through the analysis, the result showed that the added value improvement of Vietnam export tea industry is influenced the most by the factor Marketing (ß2= 0,293), followed by the factors Logistics (ß 5= 0,228), Management (ß 3= 0,187), Input (ß 1= 0,174) and Information Technology (ß 4= 0,136). The ANOVA test also showed that state companies have higher value than private companies and joint-venture companies. Businesses that have operated in the industry longer tend to have higher added value of tea products. However, the added value of Vietnam tea industry is relatively low in serveral countries such as Russia or Taiwan. 7
The results of this study can provide background for other research on topics such as the economy and green supply chain management of tea industry. The result also showed the difference between types of business and the added value of tea industry in different countries. Thus, the study helps businesses to understand better the situation of the tea market and prepare better plans. The limitation of the study is that the research model only accounts for 67,1 32,9% of the variability of the dependent variabel. Beside, the survey was conducted only in the businesses in the North of Vietnam, thus, limiting the generalization of the study. Thus, future researches should consider extending its research scale to improve their generalization. Reference Đình Tôn, V. (2012). Đánh giá hiệu quả xử lý chất thải bằng bể biogass của một số trang trại chăn nuôi lợn vùng đồng bằng sông Hồng. Tạp chí Khoa học và Phát triển, 6(6), 556-561. Đinh Văn Thành, Tăng cường năng lực tham gia của hàng nông sản vào chuỗi giá trị toàn cầu trong điều kiện hiện nay ở Việt Nam, NXB Công Thương, 2010, tr.31 Hữu Ảnh, L., Quốc Oánh, N., Duy Linh, N., Thị Hà, H., & Phương Nam, L. (2015). HÌNH THỨC HỢP ĐỒNG SẢN XUẤT GIỮA DOANH NGHIỆP VỚI HỘ NÔNG DÂN TRƯỜNG HỢP NGHIÊN CỨU TRONG SẢN XUẤT CHÈ VÀ MÍA ĐƯỜNG Ở SƠN LA. Tạp chí Khoa học và Phát triển, 9(6), 1032-1040. Issar, G., & Navon, L. R. (2016). Just in Time (JIT). In Operational Excellence(pp. 65-67). Springer International Publishing. Kaplinsky, R., & Morris, M. (2001). A handbook for value chain research (Vol. 113). Ottawa: IDRC. Kotler, P. (2001). Dirección de marketing. Pearson Education. Porter, M. (1996). America s green strategy. Business and the Environment: A Reader, 33. Thế Công, P. (2015). PHÁT TRIỂN CÁC NGÀNH CÔNG NGHIỆP SÁNG TẠO Ở VIỆT NAM TRONG BỐI CẢNH HỘI NHẬP QUỐC TẾ. Khoa học Xã hội Việt Nam, (1), 17. Trọng, H., & Chu, N. M. N. (2008). Thống kê ứng dụng trong kinh tế-xã hội. Vietnam Trade Stimulation Organization (2015), Report on Tea export industry. 8