A study on the growth strategy and the role of Korea national oil corporation using empirical analysis of worldwide oil companies

Đỗ Đình Long và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 105(05): 65 - 73 65 A STUDY ON THE GROWTH STRATEGY AND THE ROLE OF KOREA NATIONAL OIL CORPORATION USING EMPIRICAL ANALYSIS OF WORLDWIDE OIL COMPANIES Do Dinh Long1, Zhang Yanping2, Zulfikar Yurnaidi2, Shin Young Um2, Suduk Kim2* 1College of Economics and Business Administration - TNU, Vietnam 2 Ajou University, Korea SUMMARY Korea National Oil Corporation (KNOC) is planning to be a first-class world leading company while there is still much debate regarding the efficiency of National Oil Company (NOC) model. The purpose of this paper is to discuss the growth strategy and the role of KNOC in Korea. To facilitate the comparison of KNOC and other companies, national oil companies (NOCs) experience are examined. Additionally, we use 520 NOC samples from the year 2000 to 2008 for an empirical analysis. The empirical results indicate that the state owned oil companies underperform the private oil companies and a political preference for a state ownership oil companies will come at an economic cost. Even though the results seem to suggest privatization for KNOC, there are some empirical evidences that the existence of state ownership is still important for the stability of the domestic energy market. Key words: Growth strategy, KNOC, NOCs, State Ownership, Private Ownership INTRODUCTION* Since late 1990s, the liberalization and privatization trends of NOCs have been gone to the opposite way compared with the previous periods [13]. Many countries ruled out the steps toward privatization and even forced nationalization of major foreign-owned oil assets such as the cases of Bolivia, Ecuador, Russia and Venezuela [9]. As a result, a re- emergence of fundamental debate between State Ownership oil companies and Private Oil companies has been seen recently(1) [10]. Korea National Oil Corporation (KNOC) is a state-owned company whose main role is to build a stable balance between petroleum supply and demand through the smooth execution of domestic and global oil development and stockpiling project since its establishment. KNOC is planning to become a world-class state-owned company. In order to achieve this goal, the company has implemented a strategy called “Great KNOC 3020” which symbolizes the daily production capacity of 300 thousand barrels and the 2 * Tel: 0912 547 767 billion barrels of oil and gas reserve. The initiative also aims at transforming KNOC into a top 50 global oil company. However, the arguments against national oil companies both in economics and politics in the last three decades have put the Korean government under the pressure of privatizing KNOC(2). There are many studies on the relationship between state ownership and corporate performance both in term of theoretical and empirical analysis. While most of the theoretical studies or reviews find no conclusive arguments in favor of either state or private ownership, the majority of empirical studies show evidences in favor of private ownership rather than public ownership. However, the number of researches focusing on the oil and gas industry is limited so far, especially the empirical studies. Al-Obaidan and Scully (1991) use various frontier analysis methods to investigate the efficiency differences between private and state-owned international petroleum industry (44 companies observed between 1976 and 1982). Their results show that state-owned enterprises are only 61-65 70Số hóa bởi Trung tâm Học liệu – Đại học Thái Nguyên Đỗ Đình Long và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 105(05): 65 - 73 66 percent as technically efficient as private enterprises [1]. Using both non-parametric Data Envelopment Analysis and parametric Stochastic Frontier Analysis on a sample of 80 companies for the period 2002-2004, Eller et al. (2007) find that NOCs’ score for technical efficiency is, on average, only 0.27 compared to the total average of 0.4, while the average score for the five biggest private companies is 0.73 [8]. Another study of Victor (2007) using a single-variate regression on a sample of 90 companies observed in 2004 shows that the biggest private oil companies are nearly one-third better at converting reserves into output and tend to generate significantly more revenue per unit of output compared with NOCs [11]. Wolf (2009) uses a comprehensive dataset of 1001 NOCs from 1987-2006 to investigate whether ownership matters in economic terms. He finds that private oil firms perform better than state oil firms by between 21 percent and 30 percent. NOCs are also found to produce a significantly lower annual percentage of upstream reserves [12]. Guriev and Kolotilin (2009) study the nationalization in the oil industry around the world during 1960-2006 using a simple dynamic model of the interaction between a government and a foreign-owned oil company. They show that governments are, both theoretically and empirically, more likely to nationalize when oil prices are high and when political institutions are weak [9]. In this paper, we discuss the growth strategy and the role of KNOC in Korea. NOCs’ experiences from various perspectives such as past history, current development, the role and the growth strategy are investigated in comparison with the KNOC. A dataset of 520 samples of NOCs covering both private and public owned firms over the period of 2000-2008 is utilized to see which type of ownership may result to a better performance. Through this study, we also examine whether state ownership has an important role for the stability of energy market. Both literature survey and empirical results may derive some implications for KNOC’s expected role and future strategy and related energy policy in Korea. NATIONAL OIL COMPANIES AND KNOC NOCs in China and India China’s NOCs(3): China has three main NOCs, namely China Petroleum Corporation (CNPC), the China Petroleum and Chemical Corporation (Sinopec) and China National Offshore Oil Corporation (CNOOC). Chinese NOCs have pursued an aggressive strategy of acquiring oil and gas assets which is actively supported by government diplomacy [13]. Learning from the experience of Japan National Oil Corporation which discovered that focusing on exploration projects in unproven fields is too risky and unprofitable, Chinese NOCs then focus on acquiring stakes in some high-potential exploration blocks and holding companies with proven assets. High- ranking officials, up to the premier of the state council, have facilitated NOC investment by offering aid packages to host countries, providing subsidized loans to NOCs and encouraging them to bid competitively for energy properties. China has offered political side benefits to countries with oil reserves, such as supporting Kazakhstan’s bid to join the World Trade Organization (WTO) or endorsing the Uzbek crackdown on Andijan protestors [5]. In Africa, where the need for development is the most urgent, the Chinese president’s visit to Nigeria in 2006 resulted in the right of first refusal on four blocks for CNPC in return of the company’s commitment to expand the Kaduna refinery (an investment of $US 2 billion), several infrastructure deal (power and telecoms), also anti-malaria medication and education for medical staff [7]. India’s NOCs(4): India’s state companies, primarily the Oil and Natural Gas Company (ONGC), have been emulating Chinese NOCs in recent years. They are also seeking more opportunities of abroad acquisitions. But just like the Chinese NOCs, Indian NOCs do not 71Số hóa bởi Trung tâm Học liệu – Đại học Thái Nguyên Đỗ Đình Long và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 105(05): 65 - 73 67 have the expertise to tackle ultra deep water yet. India’s companies have also followed a strategy of acquiring upstream assets in order to guarantee energy supplies to domestic markets. ONGC has been willing to pay premium prices for upstream assets, largely in the form of bonuses. India’s NOCs have received much support from the Indian government with diplomatic and economic initiatives. Ministers are capitalizing on links with countries less favourably disposed to the Chinese such as Russia. India has also enhanced its aid, trade and diplomatic relations with West African countries in order to easily acquire foreign assets. In comparison with China, India has superior strengths in information technology training, sustainable agriculture and pharmaceutical sectors, which match the needs of many resource-rich countries in Africa and Central Asia. These aspects could be leveraged to add significant value to Indian NOC bids in future. Therefore, Indian NOCs have begun to link downstream and infrastructure to upstream bids—especially in African countries. For example, ONGC completed a 741 km pipeline linking the Khartoum refinery to the port in 2005, showing their commitment to the development of Sudan’s oil sector [6]. PETRONAS - Malaysia Petroliam Nasional Berhad—PETRONAS has strong relationship with government and in particular with the Prime Minister. The government do not interfere its activities or question its investment decisions except the investments of PETRONAS are instrumental in government foreign policy and diplomatic initiatives. PETRONAS’ investment strategy focuses to maximize profit and minimize risk. However, the company’s investment portfolio shows a significant level of tolerance for political and reputational risk. Furthermore, Malaysia has built strong relationship with neighboring Asian and Muslim countries. As a result, in some parts of Africa, the company benefits from this cooperation. PETRONAS has been a partner of Chinese companies for long time, its choice of partner also included major International Oil Companies (IOCs) and now with NOCs from the producing countries in which it is operating for investment in third countries [6]. KNOC’s strategy The global expansion strategy of KNOC has not been announced until June 2008. The growth strategy includes a key numerical target of boosting production output from 50,000 bbl per day to 300 bbl per day by 2012 and 500,000 bbl per day by 2017(5) and the six specific strategic measures [4]. Compared with KNOC, Chinese and Indian NOCs are much bigger and have stronger influence on the international market. The three Chinese NOCs, two Indian NOCs, Petroleum Authority of Thailand (PTT) and PETRONAS are also in top 100 NOCs ranking by PIW in 2008. KNOC’s strategy seems to be late in the game in comparison with those NOCs. In this context, the support of the Korean government is very important for KNOC to compete with other NOCs both in financial and diplomacy measures. In addition, KNOC also can take its advantage in terms of technology and high skilled employees. The cooperation with bigger Oil companies including those NOCs in acquiring foreign assets can help KNOC to achieve its strategic goals. DATA AND METHODOLOGY The annual ranking of the world largest oil and gas companies, published as a supplement to the “Petroleum Intelligence Weekly” (PIW) from 2000-2008(6) are the main data source for this study. Data on over 520 firms are gathered including operating data: oil reserves, gas reserves, oil production, gas production and refinery capacity volumes and financial data: revenues, net income, balance sheet assets, number of employees and the level of state ownership. Operating data is usually available for all companies while financial indicators are often lacking. 72Số hóa bởi Trung tâm Học liệu – Đại học Thái Nguyên Đỗ Đình Long và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 105(05): 65 - 73 68 Additional data are used including the annual crude oil price from BP Statistical Review of World Energy [3], the IMF’s annual consumer price indices, and the annual data on domestic fuel prices and per-capital GDP (PPP), both from the World Bank. The General Model Yit = C + β. Xit + eit Where Yit is dependent variable, C is constant, β is coefficient of independent variables, Xit is independent variables, eit is the error term, i is index for specific oil company, and t is index for year. In this paper, several independent variables are utilized, as shown in table 1. Multivariate regression analysis based on time series- cross-sectional dataset is used in this study to compare the performance efficiency between state oil companies and private oil companies as well as to examine the role of NOCs on maintaining the stability of domestic energy market. Output efficiency and financial performance of oil companies will be tested, by setting them as dependent variable of the model above. In this regard, the role of the level of state ownership variable (SOit) is very important for comparing the state owned companies and the private companies. Further, all the models also use the binary variable for OPEC membership as all previous studies. RESULTS Upstream production and total output Table 2 reports the impact of state ownership on the conversion of petroleum reserves and total assets into upstream oil and gas production, controlling for the national economic development and real-term oil prices. Employment is not included because it is not found to be significant in explaining upstream production. The regression equation: LOUTPUTOG = c(1) + c(2)*LRESOG + c(3)*LASS + c(4)*SO + c(5)*OPEC + c(6)*LPERGDP + c(7)*LOP Table 1. List of Independent Variables Variable Explanation Variable Explanation LRESOG Logarithm of sum of oil and gas reserves (millions of barrels) SOLTOUPUT Interaction variable between state ownership and total output LASS Logarithm of real-terms total assets (US$ millon) PROBALOIL Ratio of oil production to sum of oil and gas production SO state voting ownership (%) LREV Logarithm of annual real-terms revenues (US$ million) OPEC Dummy variable with value =1 for membership LOUTPUTOG Logarithm of total oil and gas production (millions of barrels) LPERGDP Logarithm of GDP per capital- (PPP, constant 2005$) SOLOUPOG Interation variable between state ownership and logarithm of oil and gas production LOP Logarithm of real-terms oil price SOLPERGDP Interaction variable between state ownership and GDP per capital LEMP Logarithm of number of employees LTOUPUT Logarithm of annual total output (sum of oil and gas production and refining capacity, millions of barrels) ROROG Ratio of oil reserves to sum of oil and gas reserves UPLNT Ratio of oil production to sum of oil production and refining capacity 73Số hóa bởi Trung tâm Học liệu – Đại học Thái Nguyên Đỗ Đình Long và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 105(05): 65 - 73 69 Table 2. Regression results for logarithm of annual oil and gas production - LOUTPUTOG (millions of barrels) Coeff. Stand. E t-statistic c(1) -8.0361 0.4355 -18.4490*** c(2) 0.6295 0.0261 24.0590*** c(3) 0.2915 0.0277 10.5087*** c(4) -0.0013 0.0006 -1.9652** c(5) -0.3303 0.1102 -2.9954*** c(6) 0.0431 0.0333 1.2952 c(7) -0.2293 0.0632 -3.6238*** AR(1) 0.1549 0.0531 2.9151*** N 367 R squared 0.89 F statistic 435.52 D-W statistic 2.01 Notes: */**/***: 10%/5%/1% level of significant, respectively AR (1): First-order autocorrelation coefficient Hydrocarbon reserves are confirmed as one of the fundamental driver of upstream production with a coefficient (elasticity) of 0.62. Total assets also play an important role in explaining oil and gas production. The impact of state ownership and OPEC membership both reduce the reserves- elasticity of production by about 0.001 and 33.03 percent, respectively. However, the impact of state ownership is insignificant in scale. GDP per capita is found to be insignificant in explaining upstream production while the negative sign of the oil price variable might be surprising. The possible explanation is that although the high oil prices are an incentive to raise production levels, technically this is very difficult, and rarely any firm has short-term spare production capacity [15]. Another possible explanation for that result is the firms’ expectation of higher prices in the future. When the state ownership and OPEC dummy variables are replaced by the interaction variables between state ownership/OPEC membership and reserve, the results are similar to that of table 2. Higher oil and gas reserves and higher level of state ownership will cause lesser production, so do OPEC membership. OPEC NOCs and other high reserves state oil companies always try to reduce output production to keep high oil prices and secure oil supplies for the future. Table 3 shows the regression for logarithm of annual oil and gas production with interaction variables between state ownership and Gross Domestic Product per capita. The regression equation: LOUTPUTOG=c(1)+c(2)*LRESOG+c(3)*L ASS+c(4)*SOLPERGDP+c(5)*OPEC+c(6)* LPERGDP+c(7)*LOP Table 3. Regression results for logarithm of annual oil and gas production with interaction variables 2 (millions of barrels) Coeff. Stand. E t-statistic c(1) -8.0423 0.4229 -19.015*** c(2) 0.6319 0.0261 24.180*** c(3) 0.2910 0.0276 10.523*** c(4) -0.0001 6.83E-05 -2.4715** c(5) -0.3201 0.1097 -2.9172*** c(6) 0.0434 0.0313 1.3865 c(7) -0.2305 0.0631 -3.6485*** AR(1) 0.1572 0.0531 2.9582*** N 367 R squared 0.89 F statistic 438.53 D-W statistic 2.01 Notes: */**/***: 10%/5%/1% level of significant, respectively AR (1): First-order autocorrelation coefficient As shown in the table, the increasing level of state ownership in an oil company of high GDP per capita countries will lead to the reduction of upstream production. Table 4 presents the regression results for logarithm of annual total output on the state ownership, OPEC membership and several other variables. 74Số hóa bởi Trung tâm Học liệu – Đại học Thái Nguyên Đỗ Đình Long và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 105(05): 65 - 73 70 The regression equation: LTOUPUT = c(1)+c(2)*LRESOG + c(3)*LASS+c(4)*LEMP+c(5)*SO+c(6)*OPE C + c(7)*ROROG +c(8)*UPLNT +c(9)*LPERGDP + c(10)*LOP Table 4. Regression results for logarithm of annual total output LTOUPUT (sum of oil and gas production, refining capacity -millions of barrels) Coeff. Std. E t-statistic c(1) -6.6504 0.4023 -16.5277*** c(2) 0.34459 0.0267 12.9347*** c(3) 0.4905 0.0323 15.1643*** c(4) 0.0992 0.0226 4.3872*** c(5) -0.0014 0.0005 -2.4531** c(6) 0.1619 0.0851 1.9018* c(7) 0.4966 0.0852 5.8254*** c(8) -0.9059 0.1163 -7.7844*** c(9) -0.0630 0.0316 -1.9922** c(10) -0.2865 0.0516 -5.5500*** N 251 R squared 0.92 F statistic 317.85 D-W statistic 2.07 Notes: */**/***: 10%/5%/1% level of significant, respectively In Table 4, the impact of state ownership on the total output is statistically significant in favor of the private sector even though this influence is small, with only about 0.001 percent. Regression with the interaction variables between state ownership/total assets and state ownership/GDP per capita yields the same results. Further, state oil companies with larger total asset or in developed countries have total output lower than other companies. The reported results generally support the hypothesis that NOCs tend to be less efficient than private firms both in terms of upstream production and total output production. Revenue generation The regression results in table 5 are the estimation for revenue generation, i.e. the ability to translate physical output into operating revenues. The regression equation: LREV=c(1)+c(2)*LTOUPUT+c(3)*SOTOU PUT+c(4)*OPEC+c(5)*LASS+c(6)*PROBA LOIL + c(7)*UPLNT+c(8)*LPERGDP+c(9)*LOP Table 5. Regression results for logarithm of annual real –terms revenues –LREV (US$ million) Coeff. Std. E t-statistic c(1) -0.1005 0.4308 0.8156 c(2) 0.3660 0.0544 6.5459*** c(3) -0.0015 0.0004 -3.3467*** c(4) 0.2643 0.0939 2.8150*** c(5) 0.7133 0.0525 13.57.9*** c(6) 0.5426 0.1212 4.4768*** c(7) -1.0244 0.1170 -8.7515*** c(8) 0.1694 0.0312 5.4167*** c(9) 0.3605 0.0650 5.4323*** N 248 R squared 0.92 F statistic 334.92 D-W statistic 2.13 Notes: */**/***: 10%/5%/1% level of significant, respectively As expected, total output, total assets and oil prices have positive impact on total revenues. OPEC memberships also have positive impact on total revenue. Intriguingly, state owned oil companies with higher output seem to have lower level of revenues. The cause behind this phenomenon can be blamed on the price subsidies of energy in so many countries now. Profitability To investigate profitability, the link between revenue and profit generation, operating ratios variable is used in addition to others. The results are shown in table 6. The regression equation: INCOME=c(1)+c(2)*LREV+c(3)*SO+c(4)* OPEC+c(5)*PROBALOIL+c(6)*UPLNT+c( 7)*LPERGDP + c(8)*LOP 75Số hóa bởi Trung tâm Học liệu – Đại học Thái Nguyên Đỗ Đình Long và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 105(05): 65 - 73 71 Table 6. Regression results for annual real-terms of net income-INCOME (US$ million) Coeff. Std. E t-statistic c(1) -25397.46 5819.208 -4.3644*** c(2) 3226.817 284.1851 11.3546*** c(3) -21.59636 10.15393 -2.12689** c(4) 247.2671 1382.601 0.1788 c(5) -2074.151 1853.872 -1.1188 c(6) 4570.126 1826.911 2.5015** c(7) -754.5831 513.4823 -1.4695 c(8) 1240.480 748.8371 1.6565* N 247 R squared 0.42 F statistic 24.76 D-W statistic 1.89 Notes: */**/***: 10%/5%/1% level of significant, respectively Table 6 indicates that even though OPEC membership, GDP per capita and ratio of oil production to sum of oil and gas production are not found to be statistically significant, the impact of state ownership is statistically significant. Its negative coefficient also supports for the hypothesis that state owned companies underperform private companies. One percent increase of state ownership may lead to about US$ 21million decrease of real- terms income. The inclusion of interaction variables between state ownership/GDP per capita, ratio of upstream production to upstream production and refinery capacity and oil prices yields similar results. That means state ownership with higher GDP per capita or higher “UPLNT” ratio gets lower profit compared with others The results of regression for annual real terms of net income with interaction between state ownership and real terms oil price show that even when the oil prices increase, the impact of state ownership on real-terms income is still negative. These results once again confirm that state oil companies underperform private oil companies in term of profitability. Labor efficiency Here we would like to check the labor efficiency for oil companies and compare it based on their state ownership. The first regression equation is for logarithm of employees/assets variable on state ownership, OPEC membership, and some other variables. Controlling for operational business mix, oil prices and reserves, total assets, state owned companies tend to have a greater workforce in order to manage a comparable assets base In table 7, the regression of revenues per employee (with an interaction variable between state ownership and total output) is shown. The regression equation: REV/EMP = c(1) + c(2)*LTOUPUT + c(3)*SOLTOUPUT + c(4)*OPEC + c(5)*LASS + c(6)*PROBALOIL + c(7)*UPLNT + c(8)*PERGDP + c(9)*LOP Table 7. Regression results for logarithm of revenues per employees-REV/EMP Coeff. Std. E t-statistic c(1) -13.031 1.0282 -12.673*** c(2) -0.5198 0.1298 -4.0040*** c(3) -0.0022 0.0011 -2.0305** c(4) 1.2922 0.2241 5.7654*** c(5) 0.5827 0.1254 4.6452*** c(6) -0.2354 0.2892 -0.8137 c(7) -1.4007 0.2793 -5.0134*** c(8) 0.5954 0.0746 7.9757*** c(9) 0.5784 0.1552 3.7253*** N 251 R squared 0.63 F statistic 52.32 D-W statistic 2.09 Notes: */**/***: 10%/5%/1% level of significant, respectively As can be seen, table 7 yields the similar results which indicate that state ownership has negative impact on revenues per employee e.g. the higher level of state ownership with bigger total output will have lower level of revenues per employee. The stability of energy market Table 8 shows the results of the impact of state ownership on domestic fuel price, i.e. diesel and gasoline (the regression results for gasoline are not presented within this paper format). 76Số hóa bởi Trung tâm Học liệu – Đại học Thái Nguyên Đỗ Đình Long và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 105(05): 65 - 73 72 The regression equation: DIEZEL = c(1) + c(2)*LOP + c(3)*SOLTOUPUT + c(4)*SO + c(5)*OPEC + c(6)*LPERGDP+ c(7)*LTOUPUTOG Table 8. Regression results for domestic diesel price-DIEZEL (US$ per liter) Coeff. Std. E t-statistic c(1) -1.0045 0.3155 -3.1834*** c(2) 0.3037 0.0482 6.2917*** c(3) -0.0014 0.0003 -3.6344*** c(4) -0.0015 0.0006 -2.3618** c(5) -0.2317 0.0742 -3.1202*** c(6) 0.0684 0.0300 2.2738** c(7) 0.0495 0.0261 1.8959* AR(1) 0.0939 0.0657 1.4290 N 251 R squared 0.4419 F statistic 27.37 D-W statistic 1.968 Notes: */**/***: 10%/5%/1% level of significant, respectively AR (1): First-order autocorrelation coefficient The negative coefficient for state ownership variable implies that the existence of state oil companies may help their respective countries to stabilize domestic fuel prices. These results account for the re-emergence of state owned companies’ establishment at the period of high oil prices. CONCLUSION The literature survey suggests that the government’s support is very important for KNOC in comparison with other NOCs. In addition, KNOC should create a distinct competitive edge in the fields of technology and high skilled employees. International cooperation also can help KNOC to achieve its strategic goals. In terms of empirical analysis, NOCs—including OPEC NOCs— which are holding the majority (77 percent) of the world’s oil and gas reserves are found to have lower upstream production than the private firms [2]. The proper explanation might be the conservative depletion policy or the overstatement of existing reserves. The impact of state ownership on the total output, total revenues, and profit are statistically significant in favor of the private sector. These results seem to confirm that state owned companies underperform private sector as shown by the literature survey. That means maintaining the state ownership will come at the cost of consumers. However, the regression results of domestic fuel prices indicate that the existence of state ownership may help stabilizing energy market even in high volatility of energy prices. The lower oil prices in the market may lead to a slower depletion of energy reserves. In summary, even though a change of KNOC from a fully state-owned to a major state- owned company may result in performance improvement, state control is still important because of the following reasons: first, KNOC can get stronger support from the Korean government both in terms of finance and diplomacy; second, KNOC can help the government to stabilize the domestic energy market. Lastly, KNOC might deplete their foreign oil reserves slowly, which can help Korea to face oil price shock in the future. However, the various quality measures could not be directly quantifiable in terms of evaluation. Therefore, the empirical results must be interpreted very carefully to get appropriate and meaningful implications. ACKNOWLEDGMENT We are grateful Mrs. Koh, Yu Kyung at Korea National Oil Corporation for the valuable dataset. REFERENCES [1] Al-Obaidan, A., Scully, G., 1991. Efficiency differences between private and state-owned enterprises in the international petroleum industry. Applied Economics 1991 (1991) 237-246. [2] Baker Institute Policy Report, 2007. The changing role of National Oil Companies. James A. Baker III Institute for Public Policy of Rice University 2007 [3. BP, 2010. Statistical Review of World Energy 2010. [4]. Byul-Hwa, K., 2009. KNOC’s Global Expansion Strategy. IEEJ December 2009. [5]. Chatham House, 2007. Trends in Asian NOC Investment Abroad. Working Background Paper. 77Số hóa bởi Trung tâm Học liệu – Đại học Thái Nguyên Đỗ Đình Long và Đtg Tạp chí KHOA HỌC & CÔNG NGHỆ 105(05): 65 - 73 73 [6]. Chatham House, 2007. Trends in Asian National Oil Company Investment Abroad: An Update [7].Chatham House, 2009. Thirst for African Oil Asian National Oil Companies In Nigeria and Angola. [8] Eller, S.L, Hartley, P., Medlock III, K., 2007. Empirical Evidence on the Operational Efficiency of National Oil Companies. The James A. Baker III Institute for Public Policy Rice University 2007. [9] Guriev, S., Kolotilin, A., 2009. Determinants of Nationalization in the Oil Sector: A Theory and Evidence from Panel Data. Working Paper. New Economic School. [10] Stevens, P., 2009. National Oil Companies: Good or Bad? – A Literature Survey. Center for Energy, Petroleum and Mineral Law and Policy. University of Dundee Scotland. [11] Victor, N.M., 2007. On Measuring the Performance of National Oil Companies (NOCs). Working Paper #64. Stanford University. [12] Wolf, C., 2009. Does Ownership Matter? The Performance and Efficiency of State Oil and Private Oil (1987-2006). Energy Policy 37 (2009) 2642-2652. [13] World Bank, 2009. Overview of the Political and Economic Arguments in favor of and against the establishment of a NOC. TÓM TẮT NGHIÊN CỨU CHIẾN LƯỢC TĂNG TRƯỞNG VÀ VAI TRÒ CỦA TẬP ĐOÀN DẦU KHÍ HÀN QUỐC SỬ DỤNG PHÂN TÍCH THỰC NGHIỆM CỦA CÁC CÔNG TY DẦU MỎ TRÊN THẾ GIỚI Đỗ Đình Long1*, Zhang Yanping2, Zulfikar Yurnaidi2, Shin Young Um2, Suduk Kim2 1Trường Đại học Kinh tế & Quản trị kinh doanh – ĐH Thái Nguyên, Việt Nam 2 Ajou University, Hàn Quốc Tập đoàn dầu mỏ Hàn Quốc (KNOC) đang có kế hoạch trở thành công ty hàng đầu thế giới trong bối cảnh có rất nhiều tranh luận về hiệu quả của mô hình công ty dầu mỏ quốc gia (NOC). Bài báo này thảo luận về chiến lược phát triển và vai trò của KNOC ở Hàn Quốc. Để làm dễ dàng hơn việc so sánh giữa KNOC và những công ty khác, kinh nghiệm về các công ty dầu mỏ quốc gia (NOCs) được khảo sát với nhiều khía cạnh khác nhau: sự phát triển trong quá khứ, sự phát triển ở hiện tại và chiến lược phát triển và vai trò của các công ty này. Thêm nữa, chúng tôi sử dụng số liệu của 520 NOCs từ năm 2000 đến năm 2008 cho những phân tích thực nghiệm. Kết quả cho thấy các công ty nhà nước hoạt động kém hiệu quả hơn các công ty tư nhân, sự lựa chọn mang tính chất chính trị cho các công ty nhà nước mang lại những thiệt hại về kinh tế. Mặc dù kết quả gợi ý tư nhân hóa KNOC, có những minh chứng thực nghiệm rằng sự tồn tại của công ty nhà nước vẫn quan trọng cho sự ổn định của thị trường năng lượng nội địa. Từ khóa: Chiến lược tăng trưởng, Tập đoàn dầu mỏ Hàn Quốc (KNOC), Các công ty dầu mỏ quốc gia (NOCs), Sở hữu nhà nước, sở hữu tư nhân Note: 1 Recently, new studies on NOCs including working papers, empirical analysis and literature surveys can be seen more than previous period. 1 KNOC’s website: 3 CNPC’s website 4EIA: 5 https://www.knoc.co.kr/ENG/sub01/sub01_1_1.jsp 6 The data of the year 2004 not available 7All regression results not included in table format within this paper are available upon request Ngày nhận bài: 21/3/2013; Ngày phản biện: 02/4/2013; Ngày duyệt đăng: 06/6/2013 * Tel: 0912 547 767 78Số hóa bởi Trung tâm Học liệu – Đại học Thái Nguyên