The data was analyzed using ordinary least squares regression. Descriptive statistics of the variables and the correlation matrices are presented in Tables 1, 2, 3 & 4 presents the regression analyses with the various market values of the firm as the dependent variables. Three different models were run corresponding to the firm's market value at the end of the first day, week, and month of trading. All three models are significant at the .001 level (model 1 F-statistic = 7.85, model 2 F-statistic = 7.61, model 3 F-statistic = 8.30). These statistics indicate our model is explaining a significant amount of the variation in the market value of firms.

In each of the three models, the total number of products in the pipeline and the firms' R&D intensity were significant thus supporting hypotheses four and five. In model three, patents and the completeness of the top management team were significant thus giving partial support for hypotheses three and seven. Hypotheses one, two, six, and eight were not supported.



From the entrepreneur's perspective, the purpose of this paper has been to present how the market values the intangible resources of their firms. Effective managers will be able to gain insight into what resources are highly valued and can then maximize the value of their firm by accumulating these resources (when relevant to their specific firm, industry, etc.), especially when the firm is preparing its initial public offering of stock. Ambiguity concerning the research potential and future profitability of biotechnology firms poses significant informational obstacle for financial markets. This forces biotechnology firms and investors to rely upon credible signals to communicate the value of the firm. Our results support the hypothesized relationship between firm market value and four of our hypotheses, patents, R&D intensity, total products in the pipeline, and completeness of the top management team. This clearly demonstrates that investors in biotechnology firms believe that several of these indicators are signals of the future value of the firm. High levels of these variables significantly the market value of the firm.

A major implication of our results is the importance of the credibility of the signal being sent by the firm to investors. Each of the significant predictors are easily verified by potential investors. All of our variables related to the scientific capabilities of the firm, except firm citations, were significant in our third model. This suggests that the market needs some time to put a value on the firm's scientific capabilities. Firm citations may not reflect a true measure of the firm's scientific capabilities because Scientific Advisory Board members are typically not full time employees and largely act as consultants to the top management team. Scientific capabilities also appear more important to investors than top management team variables. Only the completeness of the top management team was significant in the third model. This suggests that the value of the firm is carried in its scientific knowledge and commercialization capabilities rather than the ability of its top management team.

While our results provide strong support for our conclusions, we must also acknowledge that our focus on biotechnology firms raises questions about the generalizability of our findings. Despite the unique characteristics of the biotechnology industry, we believe our results are generalizable. Basic science appears to be playing a greater role in the success or failure of individual firms (Dasgupta & David, 1994). This increases the importance of scientific capabilities to investors in all types of high technology firms, and the importance of effectively signaling these capabilities to investors by entrepreneurs interested in taking their companies public.

While we have found strong empirical support for our model, there is still a significant amount of variation in the market value of the firm that is unexplained. Obviously there remain other variables which demand further study. Additional research needs to expand this study by including firms from other industries. Finally, the value of the initial stock of resources need to be measured at other points in time such as at the end of the first year of trading to determine if and when this initial stock of assets begins to lose its value.

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Last Updated 1/15/97 by Geoff Goldman & Dennis Valencia

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