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Interplay of entrepreneur, government, and industry in the development of ventures: the case of emerging IT industry in Korea

EURASIP Journal on Wireless Communications and Networking20132013:49

Received: 27 December 2012

Accepted: 7 January 2013

Published: 22 February 2013


This article examines how an entrepreneur’s strategic choice influences corporate development leading to the initial public offering. The data come from Korean startups in information technology industry. We consider the dynamic interplay between an entrepreneur’s attributes and government’s institutional support as key factors. An empirical analysis of 615 listed companies shows that an entrepreneur’s attributes play a significant role in market entry especially in information technology industry which tends to have shorter lead time to the initial public offering. Government certification and venture capital investment also facilitated corporate growth toward the public company status.


  • Entrepreneur
  • Corporate growth
  • Government support
  • Initial public offering
  • Strategic choice

1. Introduction

When there is a paradigm shift in technology, the concept of entrepreneurship becomes exceedingly important because technological innovation starts to lead the market creating chances of generating new profit. An entrepreneur is an innovator who implements change within markets through the carrying out of new combinations[1]. Innovation offers an entrepreneur a chance to pursue profit and to take the chance; an entrepreneur creates an organization as a means to achieve a business goal. Many governments around the world have tried to intervene in this innovative process by supporting high technology industries for national competitive advantage[2]. The research question of our study is how entrepreneurs, government, and industry interact with each other in ventures’ development. The research context of our study is Korean case.

The 1990s in Korea were a period of technological advancement, which stimulated entrepreneurial activities. It is crucial to take into account which attributes of entrepreneurs encouraged them to choose the information technology industry as their new business field. In order to fasten the growth of information technology industry, the Korean government created a policy to facilitate venture capital investment.

The purpose of this study is to examine the effects of entrepreneurial attributes and this institutional resource support on market entry and corporate development. Specifically, we analyze if the growth of industry itself was positively influenced by the government policy of promoting entrepreneurial efforts.

2. Theoretical background and hypothesis

2. 1 The entrepreneur’s managerial background and strategic choice

Regarding initial conditions for entrepreneurial efforts, literature suggests that social structural change and cultural differences influence the founding rate[35]. Government policy plays a significant role in the decision to open a new business[6] and to attract potential entrepreneurs[7]. Technical improvement[810], globalization[11], and economic growth[6, 12] also induce entrepreneurs to start a business.

In information technology industry, the founding and growth of venture firms have exponentially increased due to the following reasons[13]. First, the information technology industry is a growing industry, in which technical innovation is fast and technology changes rapidly such that developing products and services and their applications are rather straightforward. In information technology industries, start-up and growth of venture businesses are active because venture businesses can flexibly adapt to and cope with technical and market changes. Second, the information technology industry requires lean production since the consumers’ demands are diverse and unequal. So, as innovation and differentiation are relatively easy, venture firms have a relative advantage against large enterprises. Third, the information technology industry has a lower entry barrier in fixed assets especially in the area of instruments, accessories, software, and contents. For example, they only need a work space and a few computers for software. They can separate research and development and production in accessories and instruments.

As a result, the information technology industry is known to be a high growth industry, in which unlimited innovation and differentiation are possible and capital concentration is low. If an entrepreneur chooses the information technology industry as a new business area, it can be said that he/she has made a strategic choice. According to the UEP theory[14], organizational outcomes such as organizational strategy and effectiveness are determined by entrepreneurs’ attributes.

High growth industries have the characteristics like the expansion of market size, the need for introducing new products, and the various types of competition. In high growth industries, changes are important as it required complex decision making and capability of sourcing information. When it comes to controlling these changes, CEOs with a background in marketing, R&D, product development are more desirable than a background in production or finance[15, 16]. Complicated decisions must be made in industries that are undergoing a high growth stage. In circumstances that require complicated decisions, accurate recognition of problems is necessary and such ability is positively related to the level of formal education[17, 18].

And also, as CEOs are older, they have rather restricted information and are inclined to pursue the past practice and stability[19, 20]. As the tenure of CEOs increases, they are inclined to catch the restricted information[1921].

In the industries under high differentiation with innovation, the companies need many factors and especially innovation strategy rather than status quo strategy to maintain competitive position[22, 23]. So, Thomas et al.[16] demonstrated that product differentiation had positive relation with innovation strategy. In the industries under high differentiation, when it comes to CEO function background, the output background like marketing, R&D, production development is more desirable than the throughput background like production, finance[14, 15]. And studies supported that formal education had positive relation with innovation[14, 24]. As the tenure of CEO increases, they are inclined to pursue status quo than innovation[25]. Especially, as the tenure in the same industry increases, the conservative tendency increases[2628].

In capital-intensive industries, the behavior of CEO is restricted due to much investment on fixed assets[29, 30]. Such restricted behavior of CEOs in capital-intensive industries leads to a point where CEOs remain caught in the practice and custom carried out by the previous CEOs. In turn, CEOs’ restricted behavior impedes them from undertaking risk-taking strategy, only making efficient management of fixed assets. So, competition strategy to focus on efficiency becomes important and only cost control can be a key success factor[22]. Thus, the throughput background of CEO tends to have a positive relationship with a strategy to focus on efficiency[14, 15]. In these situations, CEOs will be inclined not to pursue new tries to avoid mistake-related new investments. However, there are studies suggest that the formal education of CEO has a positive relationship with risk taking than efficient management[16, 31]. Overall, the following hypotheses can be derived in relation to entrepreneur’s attributes which will affect their choices when it comes to starting a new business in information technology industry.

Hypothesis 1 The entrepreneur’s attributes will be significantly associated with his choice to enter the information technology industry.

Hypothesis 1a. The age of entrepreneur will be negatively associated with the choice of the information technology industry.

Hypothesis 1b. The output background of entrepreneur will be positively associated with the choice of information technology industry.

Hypothesis 1c. Entrepreneur’s level of education will be positively associated with the choice of information technology industry.

Hypothesis 1d. Entrepreneur’s experience as a corporate executive will be negatively associated with the choice of information technology industry. The contingency theory states that the manager’s attributes are a result of specific situations, and in turn, the attributes’ effects on business performance differ according to different situations[32]. Since 1990s, the fast-growing information technology industry has created not only a simple change in the technological environment, but also in social, cultural, and political environment. When undergoing such changes, the entrepreneur’s attributes will affect organizational strategies and effectiveness at a greater level.

Hypothesis 2A higher level of growth in the business domain will increase the impact of the entrepreneur’s background on strategic choice.

2.2. Efficiency of IT industry and government support

Favorable environments in growth rate increase survival chances in venture businesses. When new ventures enter high-growth industries, their success rates would be higher than when they enter the industries under low growth and high competition[33, 34]. The information technology industry in the 1990s was in the initial stage of growth with a high potential for growth and excessive demands.

Acs and Audresch[35] paid attention to industrial organization aspects that affected companies’ R&D activities. They find that big companies’ R&D activities are active in industries that were capital-intensive, concentrated, and heavy in advertisement, whereas small companies’ R&D activities are active in high technology where a lot of big companies play. From this point of view, information technology industry has led the growth of conglomerates and opened many business opportunities to small and medium enterprises. We predict that firms entering in information technology industry will grow faster than firms in other industries.

Hypothesis 3Entrepreneurial companies started up in information technology industry will grow faster than other industries.

Technological advancement is known as the most important determinant for continuous economic development. Previous studies have discussed the function of knowledge, technology, government intervention, and its role in fostering economic development[3639]. Roobeek[40] emphasizes that government’s interventions in industries’ R&D and innovations are a general phenomenon, and especially governments in developing countries play a role of entrepreneur than those in advanced countries. Although big companies have spent double the amount of R&D expenditure per patent than small companies, small companies enjoy the benefits from patents most. In various industries, the true innovators are rather small companies than big companies. The representative model is small German companies. They are technologically innovative and they are even called “hidden champions” because they lead the global markets with the ability[41, 42].

Tan and Tay[43] suggest that government’s financial support influences corporate growth in Singapore. Chrisman and Leslie[44] find that small businesses’ main benefits from the government are administrative and operational aids. To test the effect of government support, Lerner[45] analyzes the Small Business Innovation Research (SBIR) program of the USA and concludes that it has actually been quite effective. The effect of government support is greater for high-tech industries, especially in the regions where there are active venture capitalists. The quality rather than the quantity of aids matters. The companies supported by the SBIR tended to attract venture capital investments, and in turn, further financing became available with the support of SBIR as a positive signal. Considering this government effect, we hypothesize as follows.

Hypothesis 4Government support positively influences startup growth.

Hypothesis 4a. The growth of a venture firm with government certification in Korea will be faster than those without it.

Hypothesis 4b. The growth of a venture with venture capital investment will be faster than those without it.

Freeman[2] suggests that fast-growing industries in modern economy such as chemistry, electronics, computer, information technology, and aerospace have been based on organized R&D activities. He emphasizes that government should not wait for freewheeling entrepreneurs’ role alone. Branscomb[46] points out that strong national technology policy was required since the late part of 1980s in the USA. Studies support that science policies were important to catch up with the developed countries. The important government interventions include high technology, small companies R&D in addition to traditional industries R&D[4751].

The information technology industry is the high-tech industry of the late 20th century where government support was indispensable. Since the 1990s, the Korean government has also acknowledged its importance and supported information technology industry as a generative power for the growth of entrepreneurial activities in general. In the case of Korea, with the opening of the Korea Securities Dealers Automated Quotation (KOSDAQ) stock market in the mid-1990s, a new financial market was created within the national economy where resource allocation for the support of venture industry was made possible. Moreover, the Korean government has continuously induced additional resource allocation outside than inside the market through the venture capital certification scheme. The Korean government has encouraged more investment from domestic venture capital firms in information technology industry by becoming an active investor itself in various investment consortia.

Hypothesis 5Government support policies have a positive effect on the growth of venture businesses.

3. Methods

3.1. Data

The original target research sample consists of 1,253 KOSDAQ stock market listed firms from July 1, 1996 to December 31, 2005. Basically, we collected disclosures from DART (Data Analysis, Retrieval and Transfer System), which is an electronic disclosure system that allows companies to submit disclosures online ( We also supplemented the database with diverse approaches such as newspaper articles, publications, corporate homepages, and phone calls to the firms. Of the 1,253 firms, 638 firms were excluded because the information was not complete or the CEO of the firm was not a founder. The final sample used here is 615 KOSDAQ-listed firms.

3.2. Variables

The characteristics and measurements of variables of our final sample are summarized in Table 1.
Table 1

Characteristics and measurements




Entrepreneur’s attribution


Time period from the year of birth to establishment year


Functional background

Output background 1, throughout background 0


Level of education

Master’s degree or higher 1, bachelor’s degree or lower 0


Former executive leadership experience

Yes 1, no 0

Information technology industry

KOSDAQ information technology index

Yes 1, no 0

Software business

Software, internet, contents

Software 1, hardware 0

Hardware business

Facilities, components


Venture certification

KOSDAQ venture index

Yes 1, no 0

Venture capital invested

Venture capital investment before IPO

Yes 1, no 0

Entrepreneurial growth

Period until IPO status

Time period from establishment year to IPO year

4. Results

Hypotheses were tested with logistic regression and survival analysis. First, for hypotheses 1 through 3, we test if an entrepreneur’s attributes have an influence in starting up a new business in information technology industry. We measured entrepreneurs’ personal attributes and analyzed to see if they affected the market entry into information technology. Second, for hypothesis 4 through 6, we test if the entry into information technology and the government support policy have influenced corporate growth. With survival analysis, we check if startups in information technology industry and government support (the venture certification scheme and venture capital aids) have affected the lead time from startup to IPO. As the hazard function of covariates changes in time in this case, we used time-dependent Cox regression.

4.1. Startups in IT industry: logistic regression analysis

This model defines that independent variables are founder’s age, functional background, formal education, and previous career as an executive. The dependent variable is the startup in information technology industry. We use logistic regression, because the dependent variable is whether the founders established information technology venture or not.

An entrepreneur’s choice to enter the business industry depends on the variables such as entrepreneur’s age, functional background, level of education, and executive experience. It is more probable that information technology is selected as the business area if an entrepreneur is younger with low level of education and executive leadership experience, as shown Table 2. Hypotheses 1a, 1b, and 1d are supported whereas hypothesis 1c is rejected.
Table 2

Results of logistic regression analyses



Control of the year of founding since 1990











Independent variables

Entrepreneur’s age





Functional background





Level of education





Former executive leadership experience






−2log likelihood = 717.814, Cox & Snell R 2 = 0.155


−2log likelihood = 416.510, Cox & Snell R 2 = 0.134


+|P| < 0.1, *|P| < 0.05, **|P| < 0.01, ***|P| < 0.001.

For the samples founded after 1990, the entrepreneur’s age, functional background, level of experience, and executive leadership experience are positively related to the dependent variable. However, the second hypothesis testing indicates that the entrepreneur’s age and the level of executive experience and education are significantly influential in determining the area of business whereas functional background and the level of education are not.

4.2. Effect on the time to IPO: survival analysis

This model defines the status as an information technology venture, government certification, and venture capital investment as independent variables and the time to IPO as the dependent variable. We ran survival analyses. As shown in Table 3, starting up in information technology industry had a significant effect on the time to IPO. Starting up in information technology reduced the time to IPO by 49% (1 – Exp (−0.674) = 0.49). Thus, hypothesis 3 is supported.
Table 3

Results of survival analyses






Firm in IT industry

Entrepreneur’s age




Functional background




Level of education




Former executive leadership experience




Choice of information technology industry

−0.674*** (53.114)


Venture certification


−0.324*** (12.883)


VC investment


−0.708*** (54.317)

−0.509*** (14.629)


−2log likelihood = 6,299.670 Chi-square = 134.255

−2log likelihood = 6,264.322 Chi-square = 172.410

−2log likelihood = 2,878.515 Chi-square = 35.367

Government-certified ventures and venture capital-backed companies had a significantly less lead time in getting into IPO. Government-certified ventures had 27.7% (1 – Exp (−0.324) = 0.277) less time to IPO than other companies. Thus, hypothesis 4a is supported. Venture capital-backed companies had 50.7% (1 – Exp (−0.708) = 0.507) less time to IPO than other companies. So, hypothesis 4b is also supported.

In information technology samples only, venture capital-backed companies had 39.96% (1 – Exp (−0.509) = 0.399) less time to IPO than other companies. Thus, hypothesis 5 suggesting that the influence of government support in informational technology is supported. But, the venture certification scheme was not that effective in this industry.

5. Discussions

So far, we have discussed the entrepreneur’s attributes, strategic choice, and their effect on the growth of enterprise, and also the parallel effects of government policy drivers supporting venture businesses. First of all, our results suggest that the entrepreneur’s attributes such as age, functional background, and former executive experience are significant factors in market entry. However, the level of education had the opposite effect. Therefore, the hypothesis which states that a younger, R&D, or marketing-based entrepreneur without any executive experience tends to choose information technology industry as their field of new business is supported. However, an entrepreneur with a relatively low level of education chose the information technology industry as their new business. This results from the fact that the level of education is divided into bachelor’s degree or lower and post graduate, which is justified by that fact that most of samples are college graduates or above.

Overall, the entrepreneur’s attributes for selecting the information technology industry are younger, and they have significant marketing and R&D experience, with low level of executive leadership experience. But, in the case of founding a business during 1990s, the relationship is shown to be relatively loose. This is caused by the fact that the importance of throughput background such as planning and management are emphasized more than the output background such as R&D and marketing in the 1990s, especially after late 1990s.

Second, the decision to start up a business in the information technology sector has positively affected entrepreneurial growth. In other words, businesses in the information technology industry tended to go public faster than businesses in other industries. Similarly, both the government venture certification scheme and venture capital investment support in Korea had a positive influence in time to IPO. Also, in the information technology industry, the companies funded by venture capital had gone public faster.

The implications of this study are as follows. First, the typical roles of an entrepreneur are a capital allocator, a CEO who makes important decision, and a strategic leader among the founding members. It means that policy makers and venture capitalists should carefully consider entrepreneurs’ attributes when making important decisions. Simple demographic characteristics used in the UEP theory alone are proven to be insufficient to draw up a universal conclusion.

Since the appearance of computer software, Internet, and contents-based businesses in the 1990s, the effect of output background of entrepreneurs has weakened. This is due to the fact that entrepreneurial attributes themselves are very critical.

Second, the effect of indirect governmental support through venture capital aids is found to be quite significant. Such results present an important message to policy makers, suggesting that indirect support is more effective than the direct one when making a support policy for venture industry.

We limited our samples to KOSDAQ stock market-listed firms, which means only relatively successful firms were included and other unsuccessful or early growth firms are excluded. Although we measured the enterprise growth with the time to IPO, this measure presents an obvious difficulty in showing unique and diverse stages of entrepreneurial growth, contingent on corporate conditions and decisions. In the future research, it is suggested to investigate entrepreneurs’ diverse strategic decisions under similar industry and policy environments.


Authors’ Affiliations

SANGMYUNG University, Jongno-gu, South Korea


  1. Schumpeter JA: The Theory of Economic Development: An Inquiry into Profits, Capital, Interest and the Business Cycle. MA, Cambridge: Harvard University Press; 1934.Google Scholar
  2. Freeman C: The Economics of Industrial Innovation. London: Frances Printer; 1982.Google Scholar
  3. Cole AH: Business Enterprise in Its Social Setting . MA, Cambridge: Harvard University Press; 1959.Google Scholar
  4. Lynn R: The Secret of the Miracle Economy: Different National Attitudes to 23 Competitiveness and Money. London: The Social Affairs Unit; 1991.Google Scholar
  5. Shapero A, Sokol L: The Social of Dimensions of Entrepreneurship. Englewood Cliffs, NJ: Prentice-Hall; 1982.Google Scholar
  6. Carree MA, van Stel AJ, Thurik AR, Wennekers ARM: Economic development and business ownership: an analysis using data of 23 OECD countries in the period 1976–1996. Small Business Econ. 2001, 19(3):271-290.View ArticleGoogle Scholar
  7. Verheul I, Wennekers S, Audretsch D, Thurik R: An Eclectic Theory of Entrepreneurship: Policies, Institutions and Culture. Amsterdam, Netherlands: Discussion paper 01-030/3, Tinbergen Institute; 2001.Google Scholar
  8. Kylaheiko K, Miettinen A: Technology management and entrepreneurship: a critical view. In International Entrepreneurship. Edited by: Birley S, MacMillan I. London: Routledge; 1995:39-58.Google Scholar
  9. Klepper S, Simons KL: Dominance by birthright: entry of prior radio producer and competitive ramifications in the U.S. television receiver industry. In Paper Presented at the EARIE Conference. Turin; October 1999.Google Scholar
  10. Casson M: Entrepreneurship and Business Culture: Studies in the Economics of Trust. Volume 1. Aldershot, UK: Edward Elgar; 1995.Google Scholar
  11. Carree MA: Market Dynamics, Evolution and Smallness. Amsterdam: Thesis Publishers; 1997.Google Scholar
  12. Reynolds PD: Who start new firm?—preliminary explorations of firms-in-gestation. Small Business Econ. 1999, 9(5):449-462.View ArticleGoogle Scholar
  13. Lee IC, Park KY: Activation Plan for Small and Medium Enterprises in Info-communication Industry. Korea Information Society Development Institute Research Report; 2007:9705.Google Scholar
  14. Hambrick DC, Mason PA: Upper echelons: the organization as a reflection of its top managers. Acad. Manag. Rev. 1984, 9(2):193-206.Google Scholar
  15. Chaganti R, Sambharya R: Strategic orientation and characteristics of upper management. Strat. Manag. J. 1987, 8(4):393-401. 10.1002/smj.4250080409View ArticleGoogle Scholar
  16. Thomas AS, Litschert RJ, Ramaswamy K: The performance impact of strategy-manager coalignment: an empirical examination. Strat. Manag. J. 1991, 12(6):509-522.View ArticleGoogle Scholar
  17. Wally S, Baum JR: Personal and structural determinants of the pace of strategic decision making. Acad. Manag. J. 1994, 37(4):932-956. 10.2307/256605View ArticleGoogle Scholar
  18. Hitt MA, Tyler BB: Strategic decision models: integrating different perspectives. Strat. Manag. J. 1991, 12(5):327-351. 10.1002/smj.4250120502View ArticleGoogle Scholar
  19. Miller D: Stale in the saddle: CEO tenure and the match between organization and environment. Manag. Sci. 1991, 37(1):34-52. 10.1287/mnsc.37.1.34View ArticleGoogle Scholar
  20. Tushman ML, Romanelli E: Organizational evolution: a metamorphic model of inertia and reorientation. In Research in Organization Behavior Edited by: Staw BM, Cummings LL. 1985, 172-222.Google Scholar
  21. Aguilar FJ: Scanning the Business Environment. New York: Macmillan; 1967.Google Scholar
  22. Porter ME: Competitive Strategy: Techniques for Analyzing Industries and Competitors. New York: Free Press; 1980.Google Scholar
  23. Rajagopalan N, Prescott JE: Determinants of top management compensation: explaining the impact of economic, behavioral and strategic constructs and the moderating effects of industry. J. Manag. 1990, 16(3):515-538.Google Scholar
  24. Kimberly JR, Evanisko MJ: Organizational innovation: the influence of individual, organizational, and contextual factors on hospital adoption of technological and administrative innovations. Acad. Manag. J. 1981, 24(4):689-713. 10.2307/256170View ArticleGoogle Scholar
  25. Katz R: The effects of group longevity on project communication and performance. Admin. Sci. Q. 1982, 27(1):81-104. 10.2307/2392547View ArticleGoogle Scholar
  26. Hambrick DC: Environmental scanning and organizational strategy. Strat. Manag. J. 1982, 3(2):159-174. 10.1002/smj.4250030207View ArticleGoogle Scholar
  27. Spender JC: Industry Recipes: The Nature and Sources of Managerial Judgment. Oxford: Basil Blackwell; 1989.Google Scholar
  28. Burrell G, Morgan G: Sociological Paradigms and Organizational Analysis. London: Heinemann; 1979.Google Scholar
  29. Ghemawat P: Commitment: The Dynamic of Strategy. New York: Free Press; 1991.Google Scholar
  30. Harrigan KR: Barriers to entry and competitive strategies. Strat. Manag. J. 1981, 2(4):395-412. 10.1002/smj.4250020407View ArticleGoogle Scholar
  31. Norburn D, Birley S: The top management team and corporate performance. Strat. Manag. J. 1988, 9(3):225-237. 10.1002/smj.4250090303View ArticleGoogle Scholar
  32. Lawrence PR, Lorsch JW: Organization and Environment. MA, Cambridge: Harvard University Press; 1967.Google Scholar
  33. Romanelli E: Environments and strategies of organization start-up: effects on early survival. Admin. Sci. Q. 1989, 34(3):369-387. 10.2307/2393149MathSciNetView ArticleGoogle Scholar
  34. Tsai WMH, MacMillan IC, Low MB: Effects of strategy and environment on 25 corporate venture success in industrial markets. J. Bus. Ventur. 1991, 6(1):9-28. 10.1016/0883-9026(91)90003-VView ArticleGoogle Scholar
  35. Acs ZJ, Audresch DB: Innovation, market structure, and firm size. Rev. Econ. Stat. 1987, 69(4):567-574. 10.2307/1935950View ArticleGoogle Scholar
  36. Dosi G: Technological paradigms and technological trajectories: a suggested interpretation of the determinants and directions of technical change. Res. Policy 1982, 11(3):147-162. 10.1016/0048-7333(82)90016-6View ArticleGoogle Scholar
  37. Nelson RR, Winter S: In search of a useful theory of innovation. Res. Policy 1997, 6(1):36-76.View ArticleGoogle Scholar
  38. Romer PM: Increasing returns and long-run growth. J. Pol. Econ. 1986, 94(5):1002-1037. 10.1086/261420MathSciNetView ArticleGoogle Scholar
  39. Albach H: Innovationsstrategien zur verbesserung der wettbewerbsfahigkeit. Zeitschrift fur Betriebswirtschaft. 1989, 59(12):1338-1352.Google Scholar
  40. Roobeek AJM: Beyond Technology Race: An Analysis of Technology Policy in Seven Industrial Countries. Amsterdam: Elsevier; 1990.Google Scholar
  41. Simon H: Lessons from Germany’s midsize giants. Harvard Business Review March–April; 115-123.Google Scholar
  42. Simon H: Hidden Champion: Lessons from 500 of the World’s Best Unknown Companies. Boston, MA: Harvard Business School Press; 1996.Google Scholar
  43. Tan W, Tay STR: Factors contributing to the growth of SMES: the Singapore case. In Proceeding to the Fifth ENDAC World Conference on Entrepreneurship. Singapore; 1994:150-161.Google Scholar
  44. Chrisman JJ, Leslie J: Strategic, administrative and operating problems: the impact of outsiders on small firm performance. Entrepreneurship: Theory Practice 1989, 13(3):37-51.Google Scholar
  45. Lerner J: The government as venture capitalist: the long-run impact of the SBIR program. J. Bus. 1999, 72(3):285-318. 10.1086/209616MathSciNetView ArticleGoogle Scholar
  46. Branscomb LM: Does America Need a Technology Policy?. Harvard Business Review March–April; 1992:24-31.Google Scholar
  47. Gielow G, Krist H, Meyer-Krahmer F: Industrielle forschungs-und industrieforderung. Diskussion theoretischer Ansaetze und ihrer empirischen Evidenz. Birlinghoven: Fraunhofer Publica; 1985.Google Scholar
  48. Bruder W, Dose N: Forschungs-und technologie-politik in der Bundesrepublik Deutschlan. Opladen: West-deutscher Verlag; 1986.View ArticleGoogle Scholar
  49. Ewers HJ: Marktversagen und politikversagen als legitimation staatlicher forschungs-und technologiepolitik. In Technikpolitik angesichts der Umweltkatastrophe. Edited by: Krupp. Heidelberg: Physica; 1989:147-160.Google Scholar
  50. Fritsch M, Wein T, Ewers HJ: Marktversagen und wirtschaftspolitik: Mikrookonomische grundlagen staatlichen handelns. Munchen: Vahlen; 1982.Google Scholar
  51. Chung S: Technologiepolitik fur neue produktionstechnologien in Korea und Deutschland. Heidelberg: Deutsch, Physica-Verlag; 1996.View ArticleGoogle Scholar


© Choi and Kim; licensee Springer. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.