Strategy of Start-up for Initial Public Offering with the Motivation of Going Public

Transcription

1 Strategy of Start-up for Initial Public Offering with the Motivation of Going Public Yoon-Jun Lee a* a* Associate Research Fellow at Science & Technology Policy Institute, 20 th Fl., Specialty Construction Center , Shindaebang-dong, Dongjak-gu, Seoul , South Korea *Tel: , Fax: , Abstract The technology-based start-ups have emerged as important drivers of innovative activities across many industries. For these start-ups, the initial public offering (IPO) has been used as an important measure for performance and leads to an influx of capital that enables these firms to implement their ideas. This study brings the IPO strategy of start-up companies into focus by investigating their performance after IPO in the Korean new stock market. For entrepreneurs, this study has two important implications. The first one is that the timing of technology acquisition is more important than the type of technology sourcing. The second one is that an early IPO is more effective for startups with the purpose of future sales growth rather than start-ups with the purpose of future acquisition. Key words: Start-up; Initial Public Offering; High Technology Industry

2 1. Introduction Though the technology-based start-ups have emerged as important drivers of innovative activities across many industries, research indicates, however, that the survival of them is rather limited. Stinchcombe (1965) labeled this phenomenon the liability of newness, and argued that new organizations lack of resources in general, lack of legitimacy, and weak ties with external players limit their capacity to compete with established players. The most important way for these start-ups to gain resources as well legitimacy is to conduct an IPO. By going public, firms increase their legitimacy in the business community, improve their access to debt financing, and create a means of exit for major shareholders (Sutton and Benedetto, 1988). Thus, the IPO has been used as a measure for start-up performance since conventional measures for performance, such as profit or sales, are not available for very young firms (Deeds et al., 1997; Stuart et al., 1999). In addition, many researchers have studied IPO market in many countries, e.g. Unlu et al. (2004) for UK and Ghosh (2005) for India. Then, which start-ups go public? Many researchers have studied this question. For example, Wilbon (1999, 2002) showed that high-technology firms who survive at least five years after an IPO have more intellectual property rights, more experienced senior executives, and spend less on R&D as a proportion of sales at the time of the IPO than their cohorts. Deeds et al. (1997) showed that the total amount of capital raised through a firm s IPO is affected by the scientific capabilities of the firm including the location of the firm, the quality of the research staff, and the number of products under development. Another empirical study by Chang (2004) found that three factors positively influenced a start-up s time to IPO; the better the reputations of participating venture capital firms and strategic alliance partners were, the more money a start-up raised, and the larger was the scale of a startup s network of strategic alliances. However, technology-related factors that are very important to technology-based firms are not considered sufficiently. Therefore, the first objective of this paper is to find the effects of technology-related factors, i.e. sourcing and timing of technology acquisition on IPO. There are several motivations or benefits for going public. Arkebauer (1991) argued that the most important reason for going public was to infuse a significant amount of investment capital into a firm. In other words, an IPO is likely to be driven by expectations of future growth opportunities. On the other hand, Brau and Fawcett (2006) found the primary motivation for going public is to facilitate acquisitions. Pagano et al. (1998) argued that companies appeared to go public not to finance future investment and growth, but to rebalance their accounts after high investment and growth.

3 These are likely to reflect the desire to exploit a window of opportunities suggested by Ritter (1991). Anyway, the firm will attempt to maximize the value by finding the optimal timing for its IPO depending on the motivation for going public. Then, when is the optimal timing for going public? Benninga et al. (2005) studied the dynamics of IPOs by examining the trade-off between an entrepreneur s private benefits of control, which are lost whenever the firm is publicly traded, and the gains from diversification of capital. Jovanovic and Roussear (2001) view the duration of the pre-ipo waiting phase as the result of a trade-off between firm learning and the opportunity cost related to delay to market. The greater the opportunity cost, in other words, the better the technology or business model, the sooner a firm will go public. A proposition that firms having greater capital intensity and are characterized by greater technological uncertainty go public earlier has been made by Chemmanur and Fulghieri (1999). These researches are based on the theoretical model and their results are not from empirical studies. Thus, the second objective of this paper is to empirically find the optimal IPO timing with the motivation for going public. This study is focused on determining the optimal timing for IPO by analyzing the effects of IPO both on the value of a firm at the time of IPO and on the post-ipo performance, while my previous research is to determine the relationship between time to IPO and the value of IPO just at the time of IPO (Lee and Lee, 2007). This study is unique in that it analyzes the timing of IPO with a two-equation recursive system model. In ex-ante stage, the time to an IPO is analyzed with several factors; the experience of CEO, venture capital financing, the sourcing of technology, the timing of technology acquisition, R&D activities and other firm characteristics. In ex-post stage, the effects of IPO timing on the probability of future acquisition and the future growth opportunity are analyzed. This study guides us into the policy for startups as well their strategy for IPO. In the empirical analysis, I use the corporate disclosure data including IPO prospectus and data for patenting indicators of 201 hightechnology start-ups that are registered on the KOSDAQ between 2000 and Key findings of this study is that a quick acquisition of the first technology is very important to lead the start-up to an early IPO regardless of the type of technology sourcing, while active internal development becomes more important when it is near to IPO. This result stresses the timing of technology acquisition rather than the type of technology sourcing at the beginning of the business. In addition, the strategy for IPO timing should be different depending on the motivation of going public. To capture the future growth opportunity, start-ups should improve their chances of going public more quickly. If the primary motivation of an IPO is to exploit the window of opportunities,

4 e.g. acquisition, start-ups had better wait refining the enterprise s idea and strategy until the stock market becomes bullish. This paper is organized as follows. Section 2 describes factors influencing the time to an IPO and hypotheses on the effects of an IPO. Section 3 provides methodology including a detailed description of the data and a regression model. Section 4 presents the regression results. Lastly, concluding remarks summarize the key findings and suggest implications. 2. Factors and hypotheses 2.1. Factors influencing time to an IPO Since IPO has been used as an early-stage measure for performance of technologybased start-ups, it is important for both academics and practitioners to understand what factors have affected start-ups performance, i.e. IPO. Thus, many researches have been conducted on this topic. Regarding the experiences of management team, several empirical studies support the fact that technology and management experience at the executive level of an organization has a bearing on the ultimate success of firms, particularly those in technology-intensive industries. For example, McGee and Dowling (1994) found a direct relationship between prior technical experience of the management team and average sales growth in high-technology start-ups. Wilbon (1999) also found a relationship between executive s experience in technology and IPO performance. In addition, founding teams experiences in related industries and social network characteristics are related to a start-up s performance (Cooper et al., 1994). Venture capital firms also provide financial resources to start-ups, which significantly affects start-ups survival, growth, and strategic options since the lack of financial resources is the most limiting factor for the growth of start-ups. Davila et al. (2003) argue that start-ups that receive more funding are able to hire, retain, and pay talented employees, who are critical to start-ups growth and help them go public more quickly. They found that increases in salaries and the number of employees happened only after start-ups had received the cash associated with the early financing round. In later rounds of financing, they found the amount of funding was associated with faster increases in personnel, higher average salaries, and lower turnover. Shane and Stuart (2002) found that the cumulative amount of venture capital funding had a strong positive effect on the rate of IPO.

5 Internal R&D has traditionally been used as an indicator of innovative activity and patents have been associated with innovation and performance at many levels (Pakes and Griliches, 1984; Pegels and Thirumurthy, 1996). They also found an empirical evidence that the number of patents contribute significantly to the increase of a firm s performance. Substantial empirical research on the impact of R&D investment and firm success has been published to support the premise that the R&D spending to sales ratio has a positive impact on firm performance (Pegels and Thirumurthy, 1996; Zahra, 1996). However, investors do not always view this measure positively, particularly if they have short-term profit motives. One reason is that R&D spending is typically charged as direct expenses which companies take away from their profits (Mitchell and Hamilton, 1988; Wilbon, 1999). Especially in this study, the focus is on the technology strategy, especially on the technology sourcing and timing of start-ups until the IPO. Though these technologyrelated factors are very important, but they have not been considered sufficiently. The theoretical literatures treat the internal development or the external sourcing decision question with transaction cost economics (Pisano, 1990). This theoretical framework to explain R&D outsourcing stresses the advantage of tapping existing and often more specialized knowledge if available. This outsourcing leads to time gains and lower innovation costs. However, technology outsourcing may create considerable transaction costs, ex ante in terms of search and negotiation costs and ex post to execute and enforce the contract. From the viewpoint of property rights theory (Grossman and Hart, 1986), they found two opposing effects of low levels of appropriation. On the one hand, a low level of appropriation might lead to a disincentive effect. Firms reduce their in-house investments in research and development below the efficient levels because they are unable to appropriate the full benefit of their investment (Spence, 1984). On the other hand, however, low levels of appropriation lead to high spillovers between firms. In order to capitalize on these spillovers, firms need to develop sufficient absorptive capacity which implies more in-house investment in research and development (Cohen and Levinthal, 1990; Kamien and Zang, 1998). Recent empirical studies have shown that successful management of internal resources and innovation can significantly improve start-up performance and the likelihood of survival (Bamford et al., 1999; Shephard et al., 2000). On the other hand, strategic alliances can affect start-ups growth and their likelihood of having an IPO faster by providing both legitimacy and needed resources. Start-ups can use these alliances to gain legitimacy and overcome the liability of newness (Zimmerman and Zeitz, 2002; Cesaroni, 2004).

6 Meanwhile, Kotabe and Murray (1990) found that the fast sourcing of key components has a positive impact on market performance. Aspenlund et al. (2005) argued that the first technology sourcing and technological capability are the most critical factors for the performance and future growth potential of start-ups, and after all, it is an urgent issue to determine how fast firms achieve these two critical factors. Hypothesis 1: Start-ups which acquire technology quickly regardless of the type of sourcing may go into IPO early. Of course, the firm s characteristics representing its size, age and the profitability, and the stock market environments are considered. The firm size and profitability are the main listing requirements of the KOSDAQ. Evans (1987) found that firm s growth as well as probability of failure decrease with firm s age. Therefore, these firm s characteristics and stock market environments should be considered because the possibility of going to public is contingent on the general environment of the IPO market. Both entrepreneurs and venture capital firms will be more likely to go public in a bullish market, when a start-up s valuation tends to be higher. Ritter (1984) used an index of a hot issue market as time-varying covariates Effects of a timing of IPO There are several motivations or benefits for going public. A firm increases its legitimacy in the business community, improves access to debt financing, and creates a means of exit for major shareholders by going public (Sutton and Benedetto, 1988). In addition, start-ups that receive more investment capital from IPO are able to hire, retain, and pay talented employees, who are critical to start-ups growth (Davila et al., 2003). Anyway, start-ups go public to establish or enhance a market value for them at the time of IPO and this establishment of a market value may also serve as the first step in the acquisition process. As it is mentioned before, the establishment of a firm s value and the future acquisition reflect the desire to exploit a window of opportunities. In addition, they go public to capture the future growth opportunities after IPO. For these young technology firms, innovative activities are an important manure to make them grow. Since the primary stakeholders are voluntary risk bearers in that they invest some form of capital, e.g. human, financial, or something else of value in the organization, the value of start-ups at IPO is important for them and it may be said that the value of startups is determined by them. The stakeholder literature suggests that systematic

7 managerial attention to stakeholder interests is critical organizational success (Choi and Shepherd, 2005). Stakeholder perceptions are particularly salient for new organizations. New organizations are likely to be perceived by resource providers as a more uncertain investment than an established organization. On the basis of stakeholder theory, an organization s newness has been used to indicate the negative aspects of new organizations in addressing and responding to major management challenges of adaptation, which is supposed to create their high mortality risk (Stinchcombe, 1965). Even when controlling for size, organizational age is associated with lower mortality rates. For example, in a study of the biomedical industry, Mitchell (1994) found significant negative effects of age on dissolution rates. Thus, management scholars continue to assume that mortality rates decline with age over organizations life spans (Barron et al., 1994). In addition, Choi and Shepherd (2005) argued that stakeholder support is more likely for old organizations using survey results. Hypothesis 2-1: Early IPO may not induce high value of a firm at IPO. In other words, time to IPO may positively influence the value of the firm at IPO. The establishment of a market price may also serve as the first step in the acquisition process (Zingales, 1995). In addition, an IPO primarily enables a firm to acquire another company rather than positioning itself to be acquired and the capital raised through IPO may also facilitate cash acquisitions (Brau and Fawcett, 2006). Therefore, the start-ups valued high at IPO are more likely to acquire another company than their counterparts. Hypothesis 2-2: The probability of acquisition may keep pace with the value of a firm. In other words, time to IPO may positively influence the probability of acquisition. The notion of an organization s newness was originated to describe the liabilities of new organizations (Stinchcombe, 1965). As was described before, these liabilities are obstacles to the survival of new organizations. However, the aging effects may vary in the industries undergoing rapid technological change. If obsolescence is a concomitant of age, then as firms age, their innovative outputs may become increasingly mismatched with the current environmental demands and irrelevant to the innovative activities of other firms. In this sense, age can be considerable disadvantages when compared with inexperience and youth (Henderson, 1993). From a viewpoint of efficiency, aging leads to decreases in

8 the efficiency, with which organizations carry out their routines and, hence, to a decline in organizational competence (Sorensen and Stuart, 2000). Further, recent studies (Katila and Shane, 2005) found that new firm innovation is greater in crowded and small markets. Cohen and Levinthal (1990) suggested that a firm s ability to use its existing knowledge base for further innovation depends critically on the patterns of communication and distribution of knowledge within the firm. Thus, if aging leads to increased rigidity and an ossification of communication patterns, firms may produce fewer innovations as they age. As Bierly and Chakrabarti (1996) stated, firms establish momentum, and their flexibility in the way they learn becomes limited by a number or organizational rigidities in many parts of the organization. These factors suggest that faster learning should translate into faster growth. Thus, Autio et al. (2000) argued that the age of a high-technology firm is negatively related to its subsequent growth in the international sales. Hypothesis 3: Aging leads to decrease in efficiency, thus, early IPO may induce faster growth after IPO. 3. Data and Methodology 3.1. Data and Variables The corporate disclosure data including IPO prospectus describes a firm, its business plan, financial data, management structure, products, risks, and many other detailed data. These corporate disclosure data can be obtained from electronic disclosure system of Data Analysis, Retrieval and Transfer (DART) System. A content analysis is performed on the disclosure data of 201 high-technology firms (36 BT firms and 165 IT-H/W firms) that are registered on the KOSDAQ between 2000 and Especially, data for external sources of technology, e.g. M&A, technical tie-up, technology transfer from other institutes can be obtained through content analysis using corporate disclosure data. The data for patenting indicators can be retrieved from available databases of the Korea Industrial Property Rights Information Service (KIPRIS). The definitions of variables are reported in Table 1 and Table 2 respectively. In addition, some detailed explanations are presented below the Tables.

9 Table 1. Definition of variables in ex-ante stage Variables Definition Experiences of CEO CEO s experience in research field CEO s experience in industrial field The dummy variable that takes on the value 1 if the CEO has research experience, e. g. researcher or professor, and zero otherwise. The dummy variable that takes on the value 1 if the CEO has experience of working in the related industries, and zero otherwise. Equity share of CEO (%) The equity share of CEO just before IPO. Venture Capital Financing Equity share of venture capital (%) The equity share of venture capitalists just before IPO. Technology Sourcing and Timing First source of technology Source of technology near IPO Time to first technology (month) Share of technology near IPO (%) Research and Development Patent application R&D expenditure to sales (%) Firm Characteristics Sales 3) (100,000,000 won) Sales growth Profit (100,000,000 won) The dummy variable that takes on the value 1 if the first source of technology is internal development, and zero otherwise 1). The dummy variable that takes on the value 1 if the primary source of technology for last 3 years before IPO is internal development, and zero otherwise 2). The time taken from company establishment to the first technology acquisition. The ratio of technology acquisitions for last 3 years before IPO to total technology acquisitions. The number of patent applications before IPO. The last 3-year average ratio of R&D expenditures to total sales before IPO. The real sales at IPO. The last 3-year average sales growth before IPO calculated by the ratio of sales to the previous year s sales. The real trading profit at IPO. Setup year The index for the setup-year of a firm 4). Stock market environment IPO market index Dependent Variable Time to IPO (month) The 3-month average ratio of public offering stock price to the par-value for all IPO firms in each quarter. The time taken from company establishment to the IPO. notes: 1) Internal development means patent application, and external sources are M&A, technical tie-up, technology transfer from other institutes, and jointly applied patents. 2) Since there is little case that the source of technology is external source only, zero means that the technologies come from both internal development and external source. 3) 1,050 Korean won=1$. The sales include the sales of intangible assets, e.g. licensing as well as product sales. 4) If a firm is established before opening the OTC market (April, 1987), this value is 0. If a firm is established between opening the OTC market and introducing the OTC dealer system (October, 1991), this value is 1. This value is 2 if a firm s setup-year is between introducing the OTC dealer system and opening the KOSDAQ (July, 1996). This value is 3 if a firm s setup-year is between opening the KOSDAQ and introducing the preliminary examination system (August, 1999). Firms that are established after August, 1999 have value 4 for this index.

10 Table 2. Definition of variables in ex-post stage Variables Definition Independent Variables Equity share of CEO after IPO (%) Equity share of venture capital after IPO (%) Source of technology after IPO R&D expenditure to sales after IPO (%) Employee Profit after IPO (100,000,000 won) Predicted IPO time The equity share of CEO just after IPO. The equity share of venture capitalists just after IPO. The dummy variable that takes on the value 1 if the primary source of technology for first 3 years after IPO is internal development, and zero otherwise. Since there is little case that the source of technology is external source only, zero means that the technologies come from both internal development and external source. The first 3-year average ratio of R&D expenditures to total sales after IPO. The number of employees just after IPO. The first 3-year average real trading profit after IPO. Predicted time to IPO The predicted value of Time to IPO calculated by regression model in ex-ante stage. Dependent Variable Firm value Acquirer Target Sales growth after IPO Patent application after IPO 1) The ratio of offered price at IPO to asset value. In other words, this means PBR (Price Book-value Ratio) at IPO. The dummy variable that takes on the value 1 if the firm acquire another company or operation divisions for first 3 years after IPO, and zero otherwise. The dummy variable that takes on the value 1 if the firm is acquired by another company or the heaviest stockholder is changed for first 3 years after IPO, and zero otherwise. The ratio of the first 3-year average real sales after IPO to the last 3-year average real sales before IPO. The number of patent applications for the first 3 years after IPO. notes: 1) Since the focus of this stage is the change of innovative activities rather than the performance of R&D activities, the patent application is used as the dependent variable. Table 3 shows the descriptive statistics of data from 201 high-technology firms. On an average, CEO has experience in related industry more than in the research. The ratio of firms whose CEO has research experience is about 38%, and that of IT firms is higher than that of BT firms. The average equity shares of CEO and venture capitalists are 32.6% and 12.8% respectively. The ratio of internal development for technology acquisition is about 81%, and that of IT firms is higher than that of BT firms. The average ratio of R&D expenditures to sales is about 7.1%. From the viewpoint of size and growth, IT firms are bigger and growing more rapidly than BT firms. On the average, IT start-ups go public earlier and they are valued higher than BT start-ups. IT start-ups have more chances to acquire another company than BT start-ups do. However, one of the performances after IPO, for example, the average sales growth after IPO of BT start-ups is higher than that of IT start-ups. On the other hand, firms showing the

11 highest performance after IPO are IT start-ups. The Pearson correlations between important variables are shown in Table 4. As it is described in hypothesis, there is a strong positive relation between time to IPO and time to the first technology. On the other hand, the relationship between time to IPO and firm value is contrary to my hypothesis which early IPO may not induce high value to a firm at IPO. However, since these correlations do not fully account for the relationships among variables, a regression analysis is also conducted. Table 3. Descriptive statistics Variables Mean Standard Deviation All IT BT Max Min Mean Mean CEO s experience in research field CEO s experience in industrial field Equity share of CEO (%) Equity share of venture capital (%) First source of technology Source of technology near IPO Time to first technology (month) Share of technology near IPO (%) Patent application R&D expenditure to sales Sales (1,000,000 won) Sales growth Profit (1,000,000 won) Employee (persons) Time to IPO (month) Firm value Acquirer Patent application after IPO Sales growth after IPO

12 Table 4. Pearson correlations Variables Time to IPO Firm value Equity share of CEO 4. Equity share of venture capital Time to first technology 6. Share of technology near IPO 7. Patent application * * R&D expenditure to sales Sales * * Sales growth Profit * IPO market index % level significancy 5% level significancy * 10% level significancy 3.2. Regression framework These data are used to analyze the IPO as a measure for start-up performance in exante stage. To find out the effects of IPO timing both on the value of firms at IPO and on the performance of start-ups after IPO, a two-equation recursive system is used. In ex-post stage, the dependent variables used in the ex-ante stage serve, i.e. time to IPO, as one of the inputs. Thus the predicted value, i.e. predicted time to IPO, is used to avoid the endogenous problem. Basically, a linear regression analysis was performed to provide a mathematical description of a predictive relationship between the dependent and independent variables through a linear equation with the following specifications for firm i. 1 ' 1 i = α i + i (1) P X u : ex-ante stage

13 2 ' 2 1 i β i λ i i 1 (2) P = X + P + v : ex-post stage where P 1 i denotes the start-up performance in the ex-ante stage measured by time to IPO, and P 2 i denotes the performance in the ex-post stage measured by one of firm value, the probability of acquisition, patent applications, and sales growth. X is a vector of firm level indicators and, u i and v i are the unobservable error terms. For the Pearson correlations between all the variables, the most significant correlation is between the number of patent applications and sales (correlation=0.693). There are other significant correlations between the following pair wise correlations; the sales and the profit (correlation=0.621), the sales and the number of employees (correlation=0.549). Another significant correlation is between profit and the number of employees (correlation=0.395). The sales and the number of employees are not used at the same time because they are all the proxy for the size of firms. Tests for multicollinearity are performed to ensure that high correlations do not exist between the explanatory variables. By the tolerance of variances, the variance inflation factor (VIF) test and the collinearity diagnostics, it has been confirmed that there is no multicollinearity problem because the lowest tolerance of variance is over 0.4, the VIF is less than 2.5 and the eigenvalues are not approximately the same (Hocking, 1996). Another problem is heteroskedasticity, which is often encountered in cross section data. Heteroskedasticity does not affect the parameter estimates, but rather creates a bias in the variance of the estimated parameters. To overcome this problem, White s robust variance-covariance matrix was used to generate the corrected standard errors for our t- statistics (White, 1980). Cox proportional hazard model is used in regressing the time to IPO in ex-ante stage because the time (duration) to IPO is not completely continuous. Cox model does not require some particular probability distribution to represent survival times. Another advantage of using Cox s method is that it is relatively easy to incorporate time dependent covariates. In Cox proportional hazard model, the hazard rate is a continuous-time version of the sequence of conditional probabilities and is defined as (1). This hazard rate duration model is used mainly in labor economics which deals with the employment problem (Collier, 2005; Cueto and Mato, 2006). 1 1 P i is the predicted value of 1 P i which is calculated from equation (1). That is, 1 P i is Predicted time to IPO.

14 Prob( t T t+ h T t) f ( t) (3) λ( t) = lim = h 0 h S( t) where S(t) is the survivor function and is defined as (4). (4) S( t) = 1 F( t) = Prob( T t) The method of maximum partial likelihood is used to estimate the parameters in Cox s model. What s remarkable about partial likelihood is that we can estimate the coefficients without having to specify the baseline hazard function. The Cox s model is represented as: (5) λ ( t) = λ ( t)exp( β x β x ) i 0 1 i1 p ip whereλ 0 ( t) is the baseline hazard function andβ 1,..., β p are parameters to be estimated. In ex-post stage, one of the discrete choice model, i.e. Probit Model is used to regress the probability of acquiring another company after IPO because we can know only whether the start-up acquire another company or not. For the sales growth and patent number, Ordinary Least Squares (OLS) is used since the values of sales growth and the patent number are approximately continuous. 4. Results 4.1. Results of the ex-ante stage The results of the ex-ante stage, i.e. pre-ipo regression, are used to find the important factors affecting the time to IPO. Table 5 presents the results of the regression analysis with the time to IPO, i.e. time to IPO as the dependent variable. The positive signs of Cox model mean that if the hazard is high, then events occur quickly and duration times for IPO are short. From the results of a positive sign of IT variable, IT firms are verified to go public earlier than BT firms do. However it is not significant. The significant positive sign of CEO s experiences means that both CEO s experience in related industry and research experience are helpful to lead the firm to an IPO early. Meanwhile, equity share of

15 venture capital variable representing the role of venture capitalist is not statistically significant. This is due to the low average equity share (around 10%) of venture capitalist as it is shown in Table 3. Consequently, the role of venture capitalist is weak for IPOs in Korea. Table 5. Results of the ex-ante stage (pre-ipo) Field CEO Venture Capital Technology Sourcing R&D Activity Firm Characteristics Stock Market Environment Variables IT CEO s experience in research field CEO s experience in industrial field Equity share of CEO Equity share of venture capital First source of technology Source of technology near IPO Log(Time to first technology) Share of technology near IPO Log(Patent application) R&D expenditure to sales (0.2207) ** (0.1815) *** ( ) (0.0044) (0.0077) (0.1108) (0.1703) *** (0.0591) *** (0.0026) * (0.0762) (0.0030) Log(Sales) Sales growth Log(Profit) Setup year *** (0.1329) Time to IPO (Cox Model) (0.2318) ** (0.1853) *** (0.1651) (0.0046) (0.0078) (0.1123) ** (0.1757) *** (0.0598) *** (0.0026) (0.0795) (0.0037) ** (0.1387) (0.0893) ** (0.0436) *** (0.1427) IPO market index (0.2323) ** (0.1852) *** (0.1664) (0.0046) (0.0078) (0.1122) ** (0.1767) *** (0.0602) *** (0.026) (0.0800) (0.0037) ** (0.1394) (0.0894) ** (0.0438) *** (0.1424) (0.0136) R 2 F-Value Chi squared *** *** *** Log likelihood Sample 201 notes: standard errors in parentheses. *** 1% level significancy ** 5% level significancy * 10% level significancy For technology sourcing, though the first sourcing type is not important, but the

16 internal development becomes more important when it is near IPO. This fact is derived from the result that first source of technology is not statistically significant but source of technology near IPO is significantly negative. Meanwhile, timing of technology acquisition is very important to lead the firm to an IPO. From the result of significantly negative sign of time to first technology, it is known that the faster the timing of the first technology acquisition, the shorter the time to an IPO. These results imply that the hypothesis 1 may not be rejected. In addition, the more technology are acquired near IPO, the earlier the start-up go public, which is verified in the result of significantly positive sign of share of technology near IPO. The variables for R&D activities are not statistically significant. Sales and profit variables show significantly negative, which means that sales and profit are not helpful to quick IPO. One of the firm characteristics, i.e. sales growth does not affect time to IPO. At last, it can be known that the bullishness of stock market is not important for the time to IPO from the result of insignificance of IPO market index variable. Consequently, early acquiring of the first technology is very important to lead the start-up to an IPO regardless of the type of technology sourcing, while active internal development becomes more important when it is near IPO Results of the ex-post stage Effects of IPO timing on the firm value at IPO To know the effects of IPO timing at IPO stage, the firm value is regressed on the predicted value of time to IPO, i.e. predicted time to IPO. The result is displayed in Table 6. Patent application and sales growth show significantly positive, which mean that the number of patents and the sales growth are important in enhancing the value of the firm at IPO. It is known that the stock market environment is statistically significant, which means that the bullishness of stock market is very important factor in enhancing the value of the firm. After controlling these factors, predicted time to IPO does not have a significant effect on the value of the firm. However, if the second order polynomial of the IPO time variable is introduced, the result changes to be significant. The significantly positive sign of predicted time to IPO and negative sign of (predicted time to IPO) 2 imply that there is inverted u-shaped relation between time to IPO and

17 firm value. Some reasons can be given to support such a relationship. In changing environments in which a radical innovation emerges and the rate of obsolescence gets faster, organizations may find themselves at a strategic disadvantage as they mature and the environment changes (Boeker, 1997; Szulanski, 1996). In general, older organizations are more likely to rely on existing routines. Some younger organizations, on the other hand, are unwilling to change their routine. For example, consider the management team of a new venture that is composed of scientists. Therefore, after controlling the experiences of management team, although the age of a firm may initially have a positive effect on the value of the firm, past some point it is possible that negative returns set in. Consequently, some duration of the pre-ipo waiting phase is needed to enhance the value of the firm. That means there exists a critical mass in time to IPO. In other words, the hypothesis 2-1 is valid till some point of firm s age, i.e. about 5 year in this analysis. Table 6. Effects of IPO time on the firm value at IPO Variables Firm value OLS (White s correction) Constant IT CEO s experience in research field CEO s experience in industrial field Log(Patent application) Sales growth Stock market environment Log(Predicted value of time to IPO) (1.8658) (0.5835) *** (6.9320) (0.5742) *** (0.1595) *** (0.3457) *** (0.0407) (0.2950) [Log(Predicted value of time to IPO)] *** (0.1546) *** (0.3496) *** (0.0390) ** (3.1533) ** (0.3650) (1.9275) (0.5991) (0.4749) (0.4626) *** (0.1671) *** (0.3548) *** (0.0417) (0.2956) *** (7.4675) (0.5899) (0.4790) (0.4740) *** (0.1657) *** (0.3557) *** (0.0402) *** (3.4853) *** (0.4070) R F-Value 20.62*** 18.61*** 14.67*** 14.00*** Sample 194 notes: standard errors in parentheses. *** 1% level significancy ** 5% level significancy * 10% level significancy

18 Effects of IPO timing on the post-ipo performance The results of the post-ipo regression are used to find out the effects of the time to IPO on the probability of acquisition, innovativeness, and sales growth of start-ups in the post-ipo. Table 7 presents the results of the regression analysis with the merger and acquisition (M&A) activity, sales growth, and the patent applications after IPO as the dependent variable. For the future acquisition, there is no special relationship between the time to IPO and the probability of acquiring another company since the negative sign of predicted time to IPO is not significant. If the second order polynomial of the IPO time variable is introduced, the result shows that there is inverted u-shaped relation, while it is not significant. To the contrary, the probability of being acquired decreases with the time to IPO, i.e. age of the start-up. In other words, the younger the firm is, the higher the probability of being a target. For growth opportunity, more profitable firms will grow more, which is verified from the result of significantly positive sign of profit after IPO variable. After controlling other factors, predicted time to IPO has a significant effect on the sales growth after IPO. The negative sign of predicted time to IPO means that firms going public quickly are growing faster than their counterparts. In addition, bigger firms doing more R&D activities are more innovative from the fact that R&D expenditure to sales after IPO and employee are significantly positive. After controlling the size and R&D activities and profit after IPO, predicted time to IPO variable has a significantly negative effect on the level of innovation after IPO. This means that firms going public quickly are more innovative than their counterparts. Consequently, start-ups which go public early achieve higher performance after IPO than their counterparts from the viewpoint of innovativeness and growth. In other words, early IPO may induce a faster growth after IPO, which verifies that the hypothesis 3 may not be rejected. The effect of an early IPO is higher on the innovativeness than on the sales growth. However, the early IPO does not always enable the firm to acquire another company.

19 Table 7. Effects of IPO time on the post-ipo performance Future Acquisition Growth Opportunity Variables Acquirer Target Sales growth after IPO Patent application after IPO Probit Model OLS (White s correction) Constant IT Equity share of CEO after IPO Equity share of venture capital after IPO Source of technology after IPO R&D expenditure to sales after IPO Log(Employee) Log(Profit after IPO) Log(Predicted value of time to IPO) (1.0026) (0.2879) (0.0062) (0.0106) (0.2149) (0.0065) (0.1658) (0.0277) (0.2399) (4.9382) (0.2909) (0.0062) (0.0108) (0.2154) (0.0065) (0.1668) * (0.0279) (2.9979) [Log(Predicted value of time to IPO)] (0.3475) * (1.2310) ** (0.3821) ** (0.0071) *** (0.0141) (0.2528) (0.0120) (0.1869) *** (0.0321) ** (0.2338) (1.2516) (0.3288) (0.0033) (0.0087) (0.1895) (0.0101) (0.1608) *** ** (0.1878) (0.8256) (0.1835) (0.0057) (0.0091) ** (0.1659) ** (0.0049) *** (0.1294) (0.0213) * (0.1558) R F-Value 3.70*** 2.66*** Log Likelihood Chi Squared *** Sample notes: standard errors in parentheses. *** 1% level significancy ** 5% level significancy * 10% level significancy 5. Concluding remarks A pioneering firm that goes public early may gain an advantage in terms of attracting investment in R&D and production. However, the firm faces the risk of revealing its valuable information to potential entrants via investment and financing decisions. This situation presents a strategic challenge to an entrepreneur who is trying to lead his or her firm to go public. Key findings of this study is that quick acquiring of the first technology is very important to lead the start-up to an IPO early regardless of the type of technology

20 sourcing, while active internal development becomes more important when it is near IPO. This result stresses on the timing of technology acquisition rather than the type of technology sourcing at the beginning of the business. Though the type of technology sourcing is not important, buy, i.e. outsourcing strategy may lead to time gains. However, the absorptive capacity which implies more in-house investment in research and development becomes more important as the work gets on the track. In order to capitalize on the technology outside, firms need to develop sufficient absorptive capacity. Taking these results into consideration, buy strategy may be more efficient at the beginning, and hereafter, make strategy gets more efficient till IPO. This strategy for going public early may affect the capturing of the future growth opportunities. In other words, start-ups which will go public with the motivation of sales growth had better conduct an IPO early. For technology-based start-ups, innovation is fundamental not only because of its direct impact on the viability of firms but also because of its profound effects on long term growth. Though the effect of an early IPO on the innovation is not as much as sales growth, an early IPO may help produce patent after IPO. Thus, if the expectation of future growth is primary motivation of IPO, startups had better go public early if possible. However, an early IPO is not always effective. The age of a firm may initially have a positive effect on the value of the firm. In changing environments, however, firms may find themselves at a strategic disadvantage as they mature and the environment changes. Thus, past some point it is possible that negative returns of an early IPO set in. As a result, the inverted u-shaped relation is shown between time to IPO and the value of the firm. In addition, there is no special relationship between the timing of IPO and the possibility of future acquisition, especially for being an acquirer. Since the establishment of a market value serves as the first step in the acquisition process, these two results are not different things. Thus, if the exploitation of a window of opportunities is the main motivation of IPO, start-ups had better wait refining the enterprise s idea and strategy until the stock market becomes bullish. This study has several limitations. The data set is unbalanced, i.e. 36 BT firms are not comparable to 165 IT firms. This unbalanced data result from the fact that the biotech market in Korea is relatively new and the Korean KOSDAQ market requires the same listing requirements for both IT and BT firms. Thus, the results primarily may be applicable to IT industry. Nevertheless, this study is worthwhile since most of new stock market is IT-oriented market. The detailed analysis on the difference between the two industries will be conducted in the future. Another limitation is that there is not enough lag time in data to expect an effect on the performance after IPO. Since the Korean new

21 stock market, i.e. KOSDAQ does not have a long history, 3-year lag time may be sufficient. In spite of these limitations, this study gives some important implications for start-ups who want to go public through the Korean new stock market. Consequently, entrepreneurs may have two-stage strategy for IPO. In the first stage, they should bring out a product through the quick acquisition of technology. Then, they should enlarge the capability of internal R&D to absorb and capitalize the technology outside. After completing these activities, they may have the option of going to the next stage or waiting. They should decide to go public immediately if they want to capture the future growth opportunity such as sales growth, while they should decide to wait until the stock market becomes bullish if they want to exploit a window of opportunity such as M&A.

22 References Arkebauer, J.B. (1991) Cashing Out, Harper Business, New York. Aspelund, A., Utby, T.B., and Skjevdal, R. (2005) Initial resources influence on new venture survival: a longitudinal study of new technology-based firms, Technovation, 25(11), Autio, E., Sapienza, H.J., and Almeida, J.G. (2000) Effects of age at entry, knowledge intensity, and imitability on international growth, Academy of Management Journal, 43(5), Bamford, C.E., Dean T.J., and McDougall, P.P. (1999) An examination of founding conditions and decisions upon the performance of new bank start-ups, Journal of Business Venturing, 15(3), Barron, D.N., West, E., and Hannan, M.T. (1994) A time to grow and a time to die: Growth and mortality of credit unions in New York city, , American Journal of Sociology, 100, Benninga, S., Helmantel, M., and Sarig, O. (2005) The timing of initial public offerings, Journal of Financial Economics, 75, Bierly, P. and Chakrabarti, A. (1996) Generic knowledge strategies in the U.S. pharmaceutical industry, Strategic Management Journal, 17, Boeker, W. (1997) Executive migration and strategic change, Administrative Science Quarterly, 42, Brau, J.C. and Fawcett, S.E. (2006) Initial public offerings: An analysis of theory and practice, The Journal of Finance, 61(1), Cesaroni, F. (2004) Technological outsourcing and product diversification: do markets for technology affect firms strategies?, Research Policy, 33(10), Chang, S.J. (2004) Venture capital financing, strategic alliances, and the initial public offerings of Internet startups, Journal of Business Venturing, 19(5), Chemmanur, T.J. and Fulghieri, P. (1999) A Theory of the going-public decision, Review of Financial Studies, 12, Choi, Y.R. and Shepherd, D.A. (2005) Stakeholder perceptions of age and other dimensions of newness, Journal of Management, 31(4), Cohen, W. and Levinthal, D. (1990) Absorptive capacity: a new perspective on learning and innovation, Administrative Science Quarterly, 35, Collier, W. (2005) Unemployment duration and individual heterogeneity: a regional study, Applied Economics, 37(2), Cooper, A.C., Gimeno-Gascon, F.J., and Woo, C.Y. (1994) Initial human and financial