International Review of Research in Emerging Markets and the Global Economy (IRREM)
An Online International Research Journal (ISSN: 2311-3200)
2016 Vol: 2 Issue: 3
A Study on Factors Influencing the Added Value Improvement of
Vietnam Tea Export Industry
Phung Thi Trung,
Deputy Head, Institute of Post Graduate Studies,
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
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International Review of Research in Emerging Markets and the Global Economy (IRREM)
An Online International Research Journal (ISSN: 2311-3200)
2016 Vol: 2 Issue: 3
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 Srilanka 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 products are still raw materials, with only a few companies care about
branding or packaging to improve their product value. 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
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International Review of Research in Emerging Markets and the Global Economy (IRREM)
An Online International Research Journal (ISSN: 2311-3200)
2016 Vol: 2 Issue: 3
the sequence, the factors that have the highest impact 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
activities 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 organization 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 participates in demand satisfaction by offering goods, but also
need to stimulate demand through information, creating proximity and promotion by
customer. In other words, a distribution channel 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
competitive advantages 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
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International Review of Research in Emerging Markets and the Global Economy (IRREM)
An Online International Research Journal (ISSN: 2311-3200)
2016 Vol: 2 Issue: 3
materials as well as improving the productivity and lowering cost (Issar, G., & Navon, L. R.,
2016).
As an 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:
Research Model
Input
Added value improvement of
Export Tea Industry
Marketing
Management
Information Technology
Logistic
Business Information
- Business type
- Length of operation
- Export markets
3. 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
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International Review of Research in Emerging Markets and the Global Economy (IRREM)
An Online International Research Journal (ISSN: 2311-3200)
2016 Vol: 2 Issue: 3
4. Research Method
4.1 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.
4.2 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%).
4.3 Descriptive Statistics
The descriptive statistics was used to describe the demographic information of sample in the
study.
4.4 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).
4.5 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.
4.6 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
5. Results
5.1 Demographic Result
Gender: There are 162 male respondents (67.5%) and 78 female respondents (32.5%)
taking part in the survey
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International Review of Research in Emerging Markets and the Global Economy (IRREM)
An Online International Research Journal (ISSN: 2311-3200)
2016 Vol: 2 Issue: 3
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 managers (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 610 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%).
5.2 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
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International Review of Research in Emerging Markets and the Global Economy (IRREM)
An Online International Research Journal (ISSN: 2311-3200)
2016 Vol: 2 Issue: 3
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.
5.3 Regression Analysis Result
The Adjusted R2 is 0.671 indicating that the research model accounts for 67.1% of the
variability of the data. Besides, 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 + 0,174X1+ 0,293X2+ 0,187X3+ 0,136X4+ 0,228X5
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 (ß2= 0,293), followed by Logistics (ß5= 0,228), Management (ß3= 0,187), Input
(ß1= 0,174) and Information Technology (ß4= 0,136).
Table 1: Regression Results
Coefficientsa
Model
1
a.
Unstandardized Coefficients
B
(Constant)
-.407
YTDV
.174
HDM
.293
QT
.187
CNTT
.136
LGT
.228
R2 = 0,671 ; F= 95,530
Dependent Variable: GTGT
Std. Error
.176
.038
.043
.042
.036
.040
( P = 0,000)
Standardized
Coefficients
Beta
.215
.324
.187
.155
.261
t
-2.312
4.634
6.755
4.470
3.774
5.672
Sig.
.022
.000
.000
.000
.000
.000
6. 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 (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.
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International Review of Research in Emerging Markets and the Global Economy (IRREM)
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2016 Vol: 2 Issue: 3
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 variable. Besides, 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.
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