Factors model affecting competitiveness of Vietnamese exporting enterprises to european market after the eu – vietnam free trade agreement (EVFTA)

Nội dung text: Factors model affecting competitiveness of Vietnamese exporting enterprises to european market after the eu – vietnam free trade agreement (EVFTA)

1. FACTORS MODEL AFFECTING COMPETITIVENESS OF VIETNAMESE EXPORTING ENTERPRISES TO EUROPEAN MARKET AFTER THE EU – VIETNAM FREE TRADE AGREEMENT (EVFTA) Ph.D Nguyen Thi Bich Vuong1 – Ph.D Pham Thi Dieu Anh2 Abstract: Corporate competitiveness has long been a hot topic, attracting much attention from scholars over the past two decades and has provided many valuable findings for society. Especially after Vietnam officially signed a Free Trade Agreement with the European Union and the outbreak of the epidemic Covid–19, the competitiveness of Vietnam exporting enterprises to the European market becoming more and more fierce. Many empirical studies have shown that the competitiveness of exporting enterprises is affected by many different factors. Therefore, the topic has surveyed 280 people who are senior managers, middle managers and chief accountants of 30 typical Vietnamese exporting enterprises to the European market to analyze and evaluate the influence of these factors on the competitiveness of Vietnamese exporting enterprises to the European market. The article conducted Cronbach's Alpha test, Exploratory Factor Analysis (EFA), Pearson correlation analysis and regression analysis; The results show that all 5 factors including: Financial capacity, reputation of the enterprises, technology capacity, marketing capacity, organizational and management capacity have the positive impact and the factor of export price has the opposite impact with the competitiveness of Vietnamese exporting enterprises to the European market. With these research results, the article will serve as a scientific basis for state management agencies to have supportive policies to improve the competitiveness of Vietnamese exporting enterprises to the European market during the period of international economic integration and the context of the EU – Vietnam Free Trade Agreement. Keywords: competitiveness, influencing factors, Vietnamese exporting enterprise, European market, EU – Vietnam Free Trade Agreement. 1. INTRODUCTION Europe is currently one of Vietnam's leading trading partners in the import and export of goods and services. On June 30, 2019 Vietnam and the EU officially signed a Free Trade Agreement (EVFTA). EVFTA is a comprehensive, high-quality, and balanced agreement of interests for both Vietnam and the EU. EVFTA will be a huge boost to Vietnam's export activities, helping to diversify markets and export products, especially Vietnamese products that have many competitive advantages such as fruits, agricultural products, textiles, footwear However, importers from Europe "set up" many strict criteria, setting up the requirements to strengthen the linkage model of domestic production to ensure the quality of products and goods in all processes of production, processing, storage, packaging and transportation. This has partly reduced the competitiveness of Vietnamese exporting enterprises in recent years. Especially, the outbreak of Covid–19 epidemic in the first few months of 2020 has further reduced Vietnam's export turnover to the European market, making Vietnamese exporting enterprises more at risk of reducing their competitiveness. For the above reasons, the selection 1 Faculty of Banking and Finance, Bac Ha International University, Vietnam. Email: Violet1072007@gmail.com. 2 Vinataba Training Center, Vietnam Tobacco Corporation. Email: Anhptdhanoi@gamil.com. 235
2. of research on competitiveness of Vietnamese exporting enterprises, point out factors affecting the competitiveness of Vietnamese exporting enterprises to have appropriate solutions to improve the competitiveness of Vietnamese exporting enterprises to the European market is a very necessary in both theory and practice in terms of international economic integration. 2. OVERVIEW OF RESEARCH The topic of competitiveness is a familiar topic studied by many domestic and foreign authors in many different fields. Such as: Onar and Polat (2010) researched on factors affecting competitiveness of 104 listed companies on the Istanbul Stock Exchange – Turkey through interviews with general directors or directors based on questionnaires with Likert 7 levels. This study has analyzed the factors affecting the competitiveness of businesses including: organizational and management capacity; production capacity; sales capacity; marketing capacity; capacity for logistics; technology capacity; financial resource; Human resources; customer care; supply ability; research and development capabilities. This research has confirmed that the more correct the strategic decision, the more competitive it will be. Research by Sauka (2015) on “Measuring the competitiveness of enterprises in Latvia”. The research results have identified 7 factors affecting the competitiveness of enterprises, including: Ability to access resources, employees' working capacity, financial capacity, business strategy of enterprises, environmental impacts, business capacity compared to competitors. This study only identifies the factors that affect the competitiveness of enterprises and measures their level through surveys, but does not mention the relationship with enterprises' competitiveness. Nguyen Thanh Long (2016) researched on factors affecting competitiveness of tourism businesses in Ben Tre. Accordingly, 8 factors affecting competitiveness of tourism enterprises in Ben Tre associated with the characteristics of socio-economic conditions and local natural conditions, including: Marketing capacity; Organization and management capacity; Social responsibility; Quality of products and services; Human resources; Price competition; Destination environmental conditions (policy mechanisms, local people, natural environment). Nguyen Duy Hung (2016) applied the internal factor assessment model of Thompson and Strickland (2007) to measure 07 internal factors affecting the competitiveness of Vietnamese securities companies, including: Financial capacity; Intellectual capital; Product quality; Technology level; Service quality; Brand name, reputation and promotion activities; Active network. Nguyen Manh Hung (2013) applied the diamond model of ME Porter to identify factors affecting the competitiveness of the telecommunications industry including: Structure and competition in the telecommunications industry (Number of enterprises in industry, revenue growth rates of telecommunications businesses, measures and methods of competition, service prices); Telecommunication market demand (GDP, living standard of the population, spending on telecommunications services); Foreign Direct Investment; Production factors (human resources, investment capital, telecommunications technology, infrastructure); Relevant industries and supporting industries (Equipment supply, hardware industry, software and digital content, supply of terminal equipment); Government (Mechanism and policy). Bui Duc Tuan (2011) assessed the barrier factors affecting the competitiveness of Vietnam's seafood processing industry today, in addition to certain competitive advantages compared to other countries on the world such as: natural advantages, domestic demand, domestic competitive environment The research shows that the current results of the new industry are mainly achieved on the basis of exploiting and taking advantage of natural advantages (incentives in natural resources, advantages of labor) that have not been placed on a solid foundation of other national advantages (domestic demand, domestic competitive environment, supporting industries). 236
3. In summary, through the fact that domestic and foreign researches on competitiveness above show that most of the researches on competitiveness of enterprises operating in the field of tourism, telecommunications, seafood processing, securities without research on the competitiveness of enterprises operating in the export sector. 3. RESEARCH MODEL AND HYPOTHESIS Through a research overview of factors affecting the competitiveness of enterprises in general, with the topic of the article being factors affecting the competitiveness of Vietnamese exporting enterprises to the Europe market, therefore the research model is as follows: Y = β0 + β1 * X1+ β2 * X2 + β3 * X3 + β4 * X4 + β5 * X5 + β6 * X6 in which: – The dependent variable Y = Competitiveness. – β0 is the intercept, β1 → β6 is the angular coefficient in the relationship between the independent variable Xi and the dependent variable Y. – Independent variables: X1, X2, X3, X4, X5, X6 with: X1 is the financial capacity of the enterprise. X2 is the technological capacity of the enterprise. X3 is the reputation of the enterprise. X4 is the Marketing capacity of the enterprise. X5 is the organizational and management capacity of the enterprise. X6 is the Export price. From the above research model, the author gives the research hypotheses including: H1: The factor "Financial capacity" has a positive impact with "Competitiveness” of Vietnamese exporting enterprises to the European market. H2: The factor "Technological capacity" has a positive impact with "Competitiveness” of Vietnamese exporting enterprises to the European market. H3: The factor "Reputation of the enterprise" has a positive impact with "Competitiveness” of Vietnamese exporting enterprises to the European market. H4: The factor "Marketing capacity" has a positive impact with "Competitiveness” of Vietnamese exporting enterprises to the European market. H5: The factor "Organizational and management capacity of the enterprise" has a positive impact with "Competitiveness” of Vietnamese exporting enterprises to the European market. H6: The factor "Export price" has a negative impact with “Competitiveness" of Vietnamese exporting enterprises to the European market. 4. RESEARCH METHODOLOGY The research is done through two steps: preliminary research and formal research. The preliminary research was done by qualitative methods through group discussion in open-question format with 2 groups of subjects: Group 1: Including 15 experts, of which 5 are lecturers or scientific researchers with a doctorate or higher degree who are teaching and researching International Business majors at several major universities in Vietnam; 10 people are 10 senior managers (Directors) of 10 typical Vietnamese exporting enterprises to the European market. 237
4. Group 2: Includes the subjects that need to be surveyed are 20 middle managers (heads/deputy heads of departments) and 10 chief accountants of 10 typical European exporting enterprises in Vietnam. This discussion aims to develop scales that are appropriate for the research context. The scales in the study used the Likert 5 form ranging from 1. Strongly disagree to 5. Strongly agree, and 3. Normal. The discussion results of qualitative research have given 20 scales to measure 06 factors affecting the competitiveness of exporting enterprises, including: The factor "Financial capacity" includes 4 scales encoded from TC1 to TC4. Factor "Technological capacity" includes 3 scales encoded from CN1 to CN3. The factor "Reputation of the enterprise" includes 3 scales encoded from UT1 to UT3. Factor "Marketing capacity" includes 4 scales encoded from MA1 to MA4. Factor "Organizational and management capacity of the enterprise" includes 3 scales encoded from QL1 to QL3. The factor "Export price" includes 3 scales encoded from GXK1 to GXK3. Formal research was conducted using quantitative methods by self-filling questionnaires with the surveyed subjects. Data of this study were conducted to test scale, Exploratory Factor Analysis (EFA), Pearson correlation analysis, regression analysis and hypothesis testing using SPSS 25.0 software. 5. RESEARCH RESULTS The author has conducted a survey of 300 people who are senior managers, middle managers and chief accountants of 30 typical Vietnamese exporting enterprises to the European market and collected 280 valid survey forms. The data collected from these 280 votes will be used to analyze the impact of these factors on the competitiveness of Vietnamese exporting enterprises to the European market based on the evaluation of above. The research results are as follows: 5.1. Results assess the reliability of the scale Cronbach's Alpha coefficient is a statistical test of the degree to which the question items on the scale are correlated. This relates to two aspects: the correlation between the variables and the correlation of the scores of each variable with the scores of all variables for each respondent. This method allows the analyst to remove the non-conforming variables that limit the trash processing in the research model because otherwise we cannot know the exact variability and error of the variables. Accordingly, only variables with total correlation coefficients of greater than 0.3 and Cronbach's alpha coefficient greater than 0.6 are considered acceptable and suitable for inclusion in the next analysis steps. Test results for groups of observed variables are shown as follows: Table 1. Summary of scale measurement results Corrected Item – Total Cronbach's Alpha if Item Cronbach's Alpha Correlation Item Deleted Scales of variable "Financial capacity" TC1 0.712 0.814 TC2 0.678 0.816 0.846 TC3 0.711 0.805 TC4 0.674 0.821 Scales of variable "Technology capacity" CN1 0.693 0.734 0.825 238
5. CN2 0.625 0.812 CN3 0.714 0.728 Scales of variable “Reputation of the enterprise” UT1 0.613 0.591 UT2 0.548 0.671 0.736 UT3 0.527 0.675 Scales of variable "Marketing capacity" MA1 0.781 0.817 MA2 0.619 0.875 0.866 MA3 0.628 0.872 MA4 0.872 0.762 Scales of variable “Organizational and management capacity” QL1 0.793 0.681 QL2 0.756 0.734 0.837 QL3 0.585 0.892 Scales of variable “Export price” GXK1 0.654 0.657 GXK2 0.613 0.712 0.783 GXK3 0.575 0.754 Scales of the variable "Competitiveness of exporting enterprises" CT1 0.543 0.654 CT2 0.417 0.735 0.732 CT3 0.473 0.692 CT4 0.658 0.577 Source: Results from author's survey data The analysis results shown in Table 1 show that: Cronbach's Alpha coefficient of all survey scales is greater than 0.7, in which the lowest is the scale of the dependent variable “Competitiveness of exporting enterprises" with Cronbach's Alpha coefficient = 0.732 and the highest is the scale "Marketing capacity" with Cronbach's Alpha coefficient = 0.866. This shows that the survey data is completely reliable. Moreover, the correlation coefficients of the total variables of all observed variables with the factors they represent are greater than 0.3, the lowest is the CT2 scale with the total variable correlation coefficient of 0.417 and the highest is the scale MA4 has a total variable correlation coefficient of 0.872. This shows that the respondents have a concept of the group of factors given by the scales/observed variables representing that factor, so the scales are reliable. So the scales/observed variables and factors are retained for the next analysis. 239
6. 5.2. Results of Exploratory Factor Analysis (EFA) After the data is reliable, the next analysis is to analyze the Exploratory Factor Analysis (EFA) to make a judgment about the convergence of the factors and the number of factors given from the survey data. In factor analysis results, it is necessary to satisfy the following requirements: KMO coefficient (Kaiser – Meyer – OlKIN) ≥ 0.5, significance level of Bartllett test ≤ 0.05. Factor Loading ≥ 0.50, if any observed variable has factor load factor <0.50, it will be disqualified. The scale is accepted when the total variance extracted is ≥ 50%. Eigenvalue coefficients must be ≥ 1. From the 06 factors in the proposed research model, the factor analysis will give new factors and the results, if the analytical criteria are met, will be the root to conduct regression analysis to determine the impact of each factor on the competitiveness of Vietnamese exporting enterprises to the European market. Factor analysis results are as follows: Table 2. Results of Exploratory Factor Analysis (EFA) with independent variables Item 1 2 3 4 5 6 MA3 0.932 MA2 0.823 MA4 0.756 MA1 0.683 TC3 0.840 TC1 0.834 TC4 0.826 TC2 0.813 GXK1 0.869 GXK3 0.831 GXK2 0.726 QL1 0.923 QL2 0.912 QL3 0.754 CN3 0.868 CN1 0.862 CN2 0.836 UT1 0.841 UT3 0.761 UT2 0.768 KMO = 0.709, Sig = 0.000, Eigenvalues = 2.304; Variance = 74.023 Source: Results from author's survey data 240
7. According to the analysis results in Table 2 shows that: – Bartlett's test results show that there is correlation between the variables in the population (Sig = 0.000 < 0.05) and the coefficient KMO = 0.709 proves that the factor analysis results to group the variables together are guaranteed reliability. – The above observed variables all have factor load coefficients greater than 0.5, ensuring the standard, and the difference between the factor load coefficients of the observed variables is greater than 0.3. Therefore, it is not necessary to exclude any observed variables in the analysis. – Eigenvalues coefficient of the sixth factor is 2.304, confirming that there are 06 factors drawn from the analysis; The total variance coefficients extracted from 06 factors is 74,023, showing the variation of the factors given by the analysis, which can explain 74,023% of the variation of the original survey data. The extracted variance value is greater than 50%, so it also meets the analysis requirements. Table 3. Results of Exploratory Factor Analysis (EFA) with the dependent variable Item Value CT4 0.852 CT1 0.786 CT3 0.713 CT2 0.641 KMO 0.715 Sig 0.000 Eigenvalues 2.245 Variance 56.134 Source: Results from author's survey data According to the analysis results in Table 3 shows that: – Bartlett's test results show that there is a correlation between variables in the population (Sig = 0.000 < 0.05) and the coefficient KMO = 0.715 proves that the factor analysis results to group the variables together are guaranteed reliability. – The above observed variables all have factor load coefficients greater than 0.5, ensuring the standard, and the difference between the factor load coefficients of the observed variables is greater than 0.3. Therefore, it is not necessary to exclude any observed variables in the analysis. – Eigenvalues coefficient of the first factor is 2,245, confirming that there is 01 factor drawn from the analysis; The total variance coefficients extracted from one factor equal to 56,134, showing the variation of the factors given by the analysis, which can explain 56,134% of the variation of the original survey data. The extracted variance value is greater than 50%, so it also meets the analysis requirements. 5.3. Results of correlation analysis Before conducting regression analysis to evaluate the influence of the factors in the regression model on the dependent variable, it is necessary to test the correlation between the independent variables, between the independent variable and the dependent variable. The most commonly used test 241
8. in this case is correlation analysis using the Pearson correlation coefficient. Pearson correlation test is used to check linear relationships between the independent variables and the dependent variable. If the variables are strongly correlated, the multi–collinearity problem must be considered when analyzing regression (Hypothesis H0: correlation coefficient is 0). Table 4. Correlation matrix among the variables TC CN UT MA QL GXK CT TC 1 CN 0.004 1 UT –0.024 0.017 1 MA 0.046 0.083 0.09 1 QL 0.085 0.128 0.174* 0.016 1 GXK 0.047 0.047 –0.056 0.012 –0.033 1 CT 0.455 0.357 0.446 0.261 0.361 –0.124* 1 . Correlation is significant at the 0.01 level (2–tailed). *. Correlation is significant at the 0.05 level (2–tailed). Source: Results from author's survey data The results of correlation analysis show that the variables included in the model all show a statistically significant correlation with the dependent variable, so the use of these variables in regression analysis is appropriate. 5.4. Results of regression analysis Table 5. Results of regression analysis Standard Statistics change Model R R2 Adjusted R2 deviation of Changed Changed Durbin– Watson the estimate R2 F df1 df2 1 0.783a 0.624 0.612 0.409 0.617 48.142 6 179 2.170 Regression coefficient Coefficients are not Multi–collinear statistics standardized Standardized Value Significance Model Regression Standard Coefficient Acceptance VIF magnification t level Sig weighting deviation Beta coefficient coefficient (Constant) –0.687 0.274 –2.572 0.011 TC 0.321 0.034 0.442 9.475 0.000 0.985 1.013 CN 0.246 0.034 0.308 6.485 0.000 0.967 1.024 UT 0.304 0.036 0.372 7.934 0.000 0.948 1.056 MA 0.207 0.045 0.275 4.565 0.000 0.612 1.641 QL 0.185 0.043 0.217 4.451 0.000 0.945 1.054 GXK –0.112 0.048 –0.156 –2.593 0.010 0.624 1.627 Source: Results from author's survey data 242
9. According to the analysis results in Table 5 shows that: – Coefficient R = 0.783 means the relationship between the variables in the model is quite tight. The coefficient R2 = 0.624 represents the suitability of the model, the adjusted R2 coefficient is 0.612, explaining 6 factors that affect 61.2% of the competitiveness of exporting enterprises. – The Durbin-Watson coefficient = 2.170 is close to the value 2, showing the residuals of the independent variables have no correlation with each other. – The coefficient F = 48.142, Sig = 0.000 in the ANOVA test shows that the reliability of the regression analysis results is guaranteed with low error. – The coefficient Sig of the factors in the regression coefficient table is also lower than 0.05, which confirms that the factors that affect the dependent variable. – VIF coefficients of all factors reach value less than 2, so there is no multicollinearity phenomenon between independent variables. Thus, the test results for the regression model achieved good results, this shows that the construction of the regression function represents the influence of the independent variables with the dependent variable in the model with high reliability confidence. The regression equation is built based on the adjusted regression coefficient as follows: Y = 0.442*TC + 0.308*CN+ 0.372*UT + 0.275*MA + 0.217*QL – 0.156*GXK Competitiveness of exporting enterprises = 0.442* Financial capacity + 0.308* Technological capacity + 0.372* Reputation of the enterprise + 0.275* Marketing capacity + 0.217* Organizational and management capacity – 0.156* Export price 5.5. The results of the model's suitability test The above R2 value evaluation results show that the built–up linear regression model is appropriate. However, to be able to deduce this model into a model of the whole, we need to conduct the F test through analysis of variance. Table 6. Analysis of variance (ANOVAb) Model Sum of squares df Average squared F Sig. Regression 48.334 6 8.051 48.142 0.000b 1 The remainder 29.856 175 0.164 Total 78.190 186 Source: Results from author's survey data According to the results in Table 6 analysis of variance (ANOVA) shows that Sig. = 0.000 <0.01. Thus, the model of factors affecting the competitiveness of Vietnamese exporting enterprises is consistent with actual research data. In other words, the independent variables are linearly related with the dependent variables with 99% confidence level. 6. CONCLUSION The research results show that the research hypotheses H1, H2, H3, H4, H5, H6 are accepted with high reliability. That means that factors including: Financial capacity, Technological capacity, Reputation of the eenterprise, Marketing capacity, Organizational and management capacity have the same impact and the factor “Export price” has a negative impact on the competitiveness of Vietnamese exporting enterprises to the European market. In which, the factor most strongly influencing the 243
10. “Competitiveness” of Vietnamese exporting enterprises to the European market is the factor “Financial capacity” with Beta coefficient = 0.442. Next is the factor "Reputation of the eenterprise" with Beta coefficient = 0.372. The third influencing factor is "Technology capacity" with Beta coefficient = 0.308. The fourth influencing factor is “Marketing capacity” with Beta coefficient = 0.275. The fifth influencing factor is "Organizational and management capacity" with Beta coefficient = 0.217. And the last factor that has a negative impact on the competitiveness of Vietnamese exporting enterprises is "Export price" with the coefficient Beta = –0.156. REFERENCES 1. Bui Duc Tuan (2011), Improving the competitiveness of Vietnam's seafood processing industry, PhD thesis in economics, National Economics University, Hanoi. 2. Michael E. Porter (1980, 1998), Competitive Strategy: Techniques for Analyzing Industries and Competitions, The Free Press, New York. 3. Nguyen Bach Khoa (2004), “Methods of determining the competitiveness and international economic integration of enterprises”, Journal of commercial science, No. 4, Hanoi. 4. Nguyen Duy Hung (2016), Improving the competitiveness of Vietnamese securities companies, PhD thesis in economics, National Economics University, Hanoi. 5. Nguyen Manh Hung (2013), Improving the competitiveness of Vietnam's telecommunications industry, PhD thesis in economics, National Economics University, Hanoi. 6. Nguyen Thanh Long (2016), Research on factors affecting competitiveness of tourism enterprises in Ben Tre, PhD thesis in economics, University of Economics, Ho Chi Minh City. 7. Sauka, A. (2015), Measuring the Competitiveness of Latvian Companies. 8. Thompson Jr, A. A. and Strickland, A. J. 1990, Strategic Management: Concepts and Cases, 5th Edition, Nomewood: Richard D. Irwin Inc., P.P. 8. 9. Thompson Jr, A. A., Strickland, A. J and Gamble, J. E. 2007, Crafting and Executing Strategy: The Quest for competitive advantage, 17th Edition,New York: Mc GrawHill. 244