Abstract
The extraordinary importance of collaboration for biotechnology manifests itself in an over-proportionally high frequency of alliance formation vis-à-vis other research-intensive industries. As Fig. 1 indicates, biotechnology accounted for over half of all technology alliances in the U.S., compared to having for instance only 7% of all R&D employees. That is, whereas other R&D-intensive industries rely on in-house research, alliances are an integral part of business models in biotechnology.
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Notes
- 1.
As biotechnology is arguably the industry most reliant on collaborative activities, it provides a suitable setting for studying the value of strategic alliances. Indeed, much alliance-related research has used it as a background (e.g., Lerner, Shane, & Tsai, 2003; Baum & Silverman, 2004). Some studies have even addressed the effect of collaborative agreements on pharmaceutical and biotechnology firm value (e.g., Campart & Pfister, 2003; Karamanos, 2002). While biotechnology collaboration thus has been extensively addressed in general, industry-specific aspects have been largely neglected.
- 2.
More broadly defined, biotechnology would encompass all applications of biological systems and processes (cf. Christensen, Davis, Muent, Ochoa, & Schmidt, 2002), including fermentation (e.g., in beer brewing) and the cultivation of crops or breeding of animals.
- 3.
- 4.
About 10,000 substances evaluated in the drug discovery stage on average correspond to one new drug eventually introduced to the market (cf. PhRMA, 2003).
- 5.
As Gambanos and Sturchio (1998) find, several Big Pharma firms did not even build general biotechnological know-how internally, thus effectively relying on collaboration with biotech firms. Those, who chose to internalize such knowledge, often acquired biotech firms as a basis of their biotechnology activities.
- 6.
Definitions of corporate collaboration are quite diverse. The present study considers as collaborative ventures (or alliances) all voluntary agreements between independent firms to jointly pursue complementary objectives. For a similar definition, see (Häussler, 2005). To distinguish between the different organizational modes, the terms ‘joint venture’ (or JV) or equity-based alliance as well as contractual alliance (or collaboration) will be used.
- 7.
- 8.
Technology or service provisions were earlier deemed equally viable business models vis-à-vis proprietary drug discovery. Recent trends have seen most firms abandon pure-play technology or service strategies in favor of own drug discovery activities or hybrid forms (e.g., Anonymous, 2003). Some firms, however, compete successfully by providing state-of-the-art process technologies (e.g., Qiagen) or biopharmaceutical services (e.g., Evotech OAI) due to superior skills and technologies.
- 9.
The approaches available in this context can be roughly classified into studies of short-term (or announcement) and long-term effects. In the domain of alliance-related research, the former approach has been prevalent. While long-run effects have been considered in M&A research, such an approach may not be feasible in a collaborative context due to (a) the greater number of similar transactions per firm and (b) the substantially smaller operational magnitude of these events. Complementarily, indirect value effects, i.e., interactions of collaborative portfolios with other events such as IPOs, will be considered.
- 10.
See Farag (2009) for a more detailed review of prior research into the value created by strategic alliances and joint ventures.
- 11.
In this context, the internalization of successful collaborative projects (Kogut, 1991) may be considered as an expansive form of alliance adaptation. As such events are rare in the biotechnology setting, internalization will not be considered separately.
- 12.
Liu (2000) distinguishes six types of innovation-related news announcements and documents significantly positive announcement ARs, but negative long-run returns (BAHR).
- 13.
Note that not all sample firms are publicly traded over the entire period of study. However, only events related to stock-listed companies have been considered in the empirical analysis.
- 14.
Table 1 of the appendix provides the explicit definitions for the types of alliance-related news considered as part of this study. It also takes account of a number of complementary news items to validate the findings regarding the primary event types. These include reruns of previously announced alliances, publicized alliance-related rumors, and news including information on multiple alliances or alliances outside the human healthcare sector.
- 15.
For confounding events and missing return data has been corrected ex ante.
- 16.
Several authors have provided overviews of the methodologies used in event-study research. Bowman (1983), Peterson (1989), Strong (1992), Armitage (1995), MacKinlay (1997), McWilliams and Siegel (1997), and Bhagat and Romano (2001), among others. Another line of literature provides evidence on the performance of alternative event-study methodologies. This includes (Brown & Warner, 1980, 1985) as well as (Cable & Holland, 1999).
- 17.
See Farag (2009) for details.
- 18.
This negative AR trend following the announcement may be attributed to market overreaction or investors cashing-in on the announcement gains and is not uncommon in event-study research. Similar patterns have also been observed in the ARs to M&A announcements (e.g., Bae, Kang, & Kim, 2002) ].
- 19.
Note that the summed ARs exhibited in Fig. 4 differ from the CARs referred to in Table 1 and further analyzed in this paper. Specifically, the daily AR forming the basis of Fig. 4 only were corrected for confounding events on the announcement date itself. Contrarily, CARs are only calculated based on events without any confounding items during the entire observation period.
- 20.
Specifically, multiple and other alliance announcements (as well as some rumors) should entail a significant market reaction, whereas restatement of existing information (follow) should not.
- 21.
While the tables included in the text are only based on the standard market model, the results obtained for the 2-Factor-Model and the Intra-Sample-Model are highly similar.
- 22.
Note that while non-standardized CAARs are positive for the 11- and 12- event windows, the Dodd-Warner-type test results are significantly negative. As this approach standardizes daily returns, the wealth gains reported by some firms around alliance termination are smaller relative to the firms’ historic volatility than the wealth losses experienced by other firms.
- 23.
Similar to the case of alliance termination, the effects of alliance rumors are not homogeneously significant across test statistics. Specifically, the Brown-Warner-type test consistently provides a more positive assessment than the Dodd-Warner-type statistic (long-window negative significance). Consequently, the positive value of rumors is mostly driven by securities also underlying a higher volatility in general (i.e., during the estimation period). Additionally, significantly positive abnormal returns following the announcement (esp. day +1) render CAARs positive on average.
- 24.
While a strategic perspective highlights the adaptive advantages of collaboration, transaction cost economics argue that the need to adapt represents a source of coordination costs. The findings presented here, however, do not distinguish between these two elements, representing a joint hypothesis test. Consequently, the overall insignificant ARs may also result from adaptive gains being mitigated by intra-alliance rivalry. Note that high levels of uncertainty may increase the benefits of hierarchical (rather treuhan hybrid) coordination.
- 25.
Consequently, milestone and termination announcements may not be fully independent from each other, which would violate the basic assumptions underlying event-study analysis. In the present study, however, the share of non-positive milestone announcements is negligibly small. Moreover, such information is often first reported as part of the termination announcement itself. Nonetheless, the market may have anticipated alliance termination without explicit news on collaborative failure, e.g., based on rumors or the lack of positive milestone announcements.
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Farag, H., Hommel, U. (2010). The Value Impact of R&D Alliances in the Biotech Industry. In: Gerybadze, A., Hommel, U., Reiners, H., Thomaschewski, D. (eds) Innovation and International Corporate Growth. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10823-5_23
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