LITERATURE REVIEW AND HYPOTHESES
Intangible resources may be defined as "non-physical assets whose values are difficult to define and measure, yet appear to play a major role in competitiveness" (Williams, Tsai & Day, 1991, p. 316). Intangible assets may include assets such as patents, trademarks, copyrights and registered designs, trade secrets, contracts and licenses, data bases, information in the public domain, personal and organizational networks, employee know-how, reputation, organizational culture (Hall, 1993), management (Waghorn, 1985), R&D and software (Williams, et al., 1991). In general, an intangible asset may be thought of as any attribute which a firm's rivals cannot quickly or effectively imitate (Caves, 1982). The research of intangible resources has generally focused either on the perceived value of intangible resources by company CEOs (Hall, 1992; 1993), their value in building competitive advantage (Barney, 1991; Dierickx and Cool, 1989), or their role in the internationalization process (Denekamp, 1995). Accountants have difficulty among themselves when trying to determine the correct accounting technique for valuing intangible resources (Reekie and Bhoyrub, 1981; Swales, 1985). In this study, the value of intangible assets manifests itself in the market value of the firm.
New product development in high-technology environments is increasingly being driven by basic scientific research (Dasgupta and David, 1994). This makes the quality of a biotechnology firm's scientific team critical to the product development process. One part of this scientific team is the Scientific Advisory Board. This group consists of a number of individuals with extensive backgrounds in fields such as immunology, virology, and microbiology. These individuals act as consultants to the firm's management. One signal a biotechnology firm can give to potential investors is the quality of its Scientific Advisory Board. One measure of this quality is citation analysis.
Citation analysis uses the number of times a paper or an author is cited as an indication of the importance of the work to the field. The more frequently the paper or an individual's body of work is cited the more important, and hence, the higher the quality of work. In recent years, citation analysis has been used to map the development of science (Franklin & Johnston, 1988), to estimate the quality of the scientific capabilities of countries in specific fields (Healey, Rothman & Hock, 1986; Wallmark, McQueen & Sedig, 1988), the performance of academic departments (Wallmark, et al., 1988) and as the basis for the assessment of scientific and technical research programs (Narin & Rozek, 1988). In addition, citation analysis has recently entered into the discussion of strategic planning. Ven Der Eerden and Saelens (1991) discussed the use of citations as indicators of research group performance and the quality of the scientific research being undertaken by the group, as well as a tool to guide competitive assessment, mergers and acquisitions, targeting, and research strategy.
H1: The number of times Scientific Advisory Board members have been cited previous to the IPO will be positively related to firm market value.
Contracts and Licenses
According to Hall (1992), contracts, which may be in any number of forms (agency agreements, license agreements, property leases), are considered one of the most important intangible resources for some businesses. Contracts exist to regulate business and economic relationships (Walker, 1980). Contracts then define the terms of agreement so that each party to the contract can protect and enforce their rights. It should be noted, however, that parties to a contract cannot foresee all possible future contingencies which adds a dimension of risk to the contract (Teece, 1986b). In the case of biotechnology companies, contracts may be the source of important scientific knowledge which may add to or compliment that knowledge which the firm already holds (for example, licenses for the use of patented medical techniques). The need for production agreements may be particularly important for firms with new products or processes. According to Teece (1986a), innovating firms without a manufacturing capability may die even though they are best at innovation. Thus:
H2: The number of contracts held by the firm at the time of the IPO will be positively associated with market value.
Patents have been associated with innovation and performance at many levels including company, region, country. Patents are considered indicators of important technology positions and innovative activity (Ashton & Sen, 1988) and can be considered inputs in the new product development process (Mansfield, 1977; Pakes, 1985). A positive relationship between patents and firm market value has been reported by a number of researchers (Cockburn and Griliches, 1988; Pakes, 1985). Whether patents are a precursor to entering a product into trials, an important input into the development process, or an early stage in a process that leads to invention through development, testing and engineering (Pavitt, 1982), they will be positively related to the value of an entrepreneurial high-technology firm.
H3: The number of patents held by the firm at the time of the IPO will be positively related to firm market value.
Total Products in Pipeline
A common indicator of technological competence or expertise in the pharmaceutical industry is the number of drugs in development or in the "pipeline". Financial analysts and potential investors monitor the products being pursued (Burill & Lee, 1994). The strength of a firm's pipeline is considered an important indicator of a companies future cash flows although the exact value of any product in the pipeline is unknown. The amount and type of new drugs in a company's research pipeline reveals to the financial markets the future potential value of the company's current scientific capabilities.
H4: The number of new drugs in a firm's pipeline will be positively related to the firm's market value.
More important to this discussion, however, is the relationship between R&D expenditures and market value. This relationship has consistently been found to be significant and positive (Chauvin & Hirschey, 1993; Jaffe, 1986) especially so for high-technology firms (Doukas & Switzer, 1992). These results are to be expected given that management sets the firm's R&D budget to maximize the discounted value of the firms expected future cash flows and that the stock market measures the firm's expectations subject to measurement error. Thus:
H5: The total R&D expenditures by firms in the last five years prior to their IPO will be positively related to their market value.
Top management team characteristics have been investigated as determinants of high-technology venture success (Roure & Maidique, 1986), innovation (Bantel & Jackson, 1989), strategic change (Wiersema & Bantel, 1992), and corporate performance (Norburn & Birley, 1988) among others. This paper seeks to link the firm's top management team with its market value. Three variables, in particular, should reflect the market value of management in newly public high-technology firms: age, education and the completeness of the top management team.
An individual's education level reflects their cognitive ability and skills (Wiersema & Bantel, 1992). High levels are associated with higher levels of information processing capacity and the ability to discriminate among a variety of stimuli (Schroder, Driver, & Steufert, 1967; Wiersema & Bantel, 1992). Additionally, high levels of education have been associated with innovation receptivity (Bantel & Jackson, 1989). These characteristics are especially important for the top management teams of biotechnology companies.
Top management team members may be among only a handful of people in the world with the necessary expertise to understand the scientific discoveries their firms are attempting to commercialize. Top management team members holding a Ph.D. in a technical area are recognized as likely having the expertise necessary to develop their firm's discoveries.
H6: There will be a positive relationship between the percentage of the top management team holding a Ph.D. and firm market value.
Top Management Team Completeness
One underinvestigated feature of top management teams is the completeness of the team. A complete top management team includes a president and executives responsible for marketing, engineering, finance, and operations (Roure & Maidique, 1986). Due to the specialized nature of biotechnology firms, this list has been slightly amended to include an executive responsible for research and development in place of engineering. We also assume all firms have a president. Investigating technological start-ups, Roure and Maidique (1986) found that successful start-ups had teams either 100% or 80% complete teams while unsuccessful companies had teams ranging from 80% to 50% complete. Given that companies with higher degrees of top management team completeness appear to be more successful and that the market rewards success:
H7: The degree of completeness of the top management team will be positively associated with the market value of newly public biotechnology firms.
Top Management Team Experience
A manager's previous experience in an industry has been argued to be a predictor of successful entrepreneurs (Roure & Maidique, 1986). Siegel, Siegel and MacMillan (1993) found industry experience to be positively related to the success of high growth ventures while Roure and Maidique (1986) found industry experience to be positively related to the success of high-technology ventures.
H8: The percentage of the top management team with experience in the biotechnology or pharmaceutical industry will be positively related to market value.
DATA AND METHODOLOGY
The Sample and Data
The biotechnology industry of 225 publicly held companies provides the population of firms for this investigation (Burrill & Lee, 1993). These firms were contacted by phone with a request for a copy of the prospectus from their IPO. A total of 106 companies provided a prospectus representing a response rate of 47%. However, five of these companies were excluded from the sample because of incomplete data. Thus, our final sample consisted of 101 companies.
To test for potential biases in this sample, we compared the average total assets and average total liabilities of the firms in our sample in 1992 to the average total assets and average total liabilities reported by Burrill and Lee (1993) for all 225 public firms. Our sample averaged $11,123,000 in total assets and $3,515,000 in total liabilities. Burrill and Lee (1993) reported the average total assets and total liabilities of the 225 public biotechnology firms in 1992 as $11,377,00 and $3,313,000 respectively. In addition, the percentage of non-pharmaceutical health care companies in our sample was 15% and the industry wide percentage, as reported by Burrill and Lee (1993) was 17%. Based on these comparisons and the size of our sample, we believe we have a fairly representative sample of the publicly held biotechnology companies.
The data in our sample was gathered from (1) the prospectus from each of the initial public offerings by the firms in our sample, (2) the Science Citation Index and (3) the Center for Research in Security Prices (CRSP) tapes.
The dependent variables in our study are the total market value of the offering firms equity at the end of the first day (DAY), first week (WEEK), and first month (MONTH) of trading (1990 dollars). The market value at the end of the first day and week of trading were used to present the market's initial reaction to the IPO. The market value of the firm at the end of the first month of operations was used to present how the market values an initial set of intangible assets after having had time to more closely examine the firm.
In this study we used citation data as an indication of the quality of the scientific personnel of the biotechnology firm (CITATION). Names of all members of the Science Advisory Boards listed in the prospectus were compiled. We then used the Science Citation Index to gather the total number of citations for each scientist during his/her career. These citations were then totaled to create a measure of the quality of the scientific team employed by the biotechnology firm at the time of its IPO. Due to a skewed distribution, the total number of citations were transformed using a logarithmic transformation.
From the offering firm's prospectus, a count of the number of contracts and licenses (excluding sole licenses for patents) was obtained (CONTRAC). Licenses for the sole use of patents was included in the patent variable.
From the offering firm's prospectus, a count of the total number of patents held by that firm was obtained (PATENT). This includes both patents granted directly to the firm and patents in which the firm is the sole licensee. Patents which have been licensed are included here rather than under contracts/licenses because, as sole licensee, the firm has exclusive rights to the knowledge content of the patent as if the patent were directly granted.
In the business section of each prospectus, companies report the number of products under development or which have reached the market (PRODS). Only products which had reached the pre-clinical stage of development or beyond were included. Multiple applications of the same product were counted as a single product.
The measure of total research and development expenditures was defined as the total R&D spending divided by total expenditures in the year previous to the IPO (R&D). A logarithmic transformation was used to control for the skewness of the distribution.
The education level of the top management team was coded as a percentage of the members with a Ph.D. (EDUCAT).
The experience of the top management team was coded as the percentage of the members with experience in the biotechnology or pharmaceutical industries (EXP).
Finally, the completeness of the top management team was measured as the percentage of members of the top management team (as defined previously) each firm employed (TMTCOMP). All of the top management team data was collected from the prospectus for each firm's IPO.
The total assets of the offering firm prior to the IPO was used to control for the influence of size on market value (ASSET). A logarithmic transformation was used to control the skewness of the distribution.
It has been well documented (Ritter, 1984) that the market for initial public offerings experiences periods in which the value of firms going public is substantially higher. The years 1983, 1986, 1991 and 1992 were hot markets for biotechnology IPOs. Therefore, to control for the effects of the hot market on firm value a dummy variable was included in the model (HOT). Those firms which made offerings during hot years were coded as "1" and all other firms were coded as "0".
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