R&D alliances and the effect of experience on innovation: a focus on the semiconductor industry.

Moreover, the greater the repertoire in terms of experiences from which a firm can draw to make decisions, the more accurate the judgment of an environment characterized by high levels of uncertainty. Alliances are managerial practices that usually involve judgmental and idiosyncratic calls, where previous processes will shape many of the future decisions, particularly when a firm is stepping into new territories. Generally, managerial experience has the greatest potential to affect performance in situations that are characterized by greater complexity and/or where outcomes are highly idiosyncratic or uncertain (Sampson, 2005). Thus, greater complexity calls for greater managerial attention and skills. For instance, a firm may find it difficult to assess the benefits of an alliance if these are directly unobservable (improved R&D processes) and parties' contributions have not been agreed on in advance. This is the perfect environment for experience effect becoming an important source of competitive advantage.

The preceding discussion suggests that the greater a firm's experience, the larger its dynamic capabilities are in alliance management. However, there are also many arguments that limit the potential benefit a firm can obtain by learning from experience. Learning can potentially lead to the adoption of specific processes more frequently. These processes in turn will be seen as more reliable, and this perception can hinder a firm from exploring new alternatives or from adopting potentially beneficial new processes. This has been labeled as organizational inertia (Hannan& Freeman, 1984), which may reduce collaborative effects and thus transform the potential benefits of learning into a core rigidity (Leonard-Barton, 1992). Therefore, learning and imitation of prior experiences may inhibit experimentation that could, in turn, improve collaborative benefits (March, 1991).

More recently, empirical evidence finds that the benefit of learning from past experience will decay over time; namely, more dated experiences will contribute little to overcoming new challenges. In the selected setting, R&D alliances, this poses a significant threat because organizations can forfeit exploring new alliance-related practices and stay with those that have provided relative success. Thus, it is expected that the hypothesized relationship will show a decreasing marginal returns to alliance experience.

Hypothesis 1: There are decreasing marginal returns to prior alliance experience. Firm collaborative benefits initially increase with the firm's prior alliance experience, but this rate of increase diminishes at higher levels of experience.

Empirical Analysis

Empirical Design

The empirical test looks at the relationship between prior alliance experience and alliance outcomes. The dependent variable is firm innovation, measured after the announcement of the alliance, as a function of past experience with R&D collaborations. As discussed in the previous section, we expect to find supporting evidence of this relationship after relevant control variables have been accounted for. Firm innovation is selected as the left-hand variable because R&D alliances are the primary focus of this study and innovation is more closely linked to R&D than financial performance measures.

Collaborative activities are usually a central point in any R&D strategy, and benefits of this practice will primarily impact the firm's innovativeness. Thus, innovation is probably the most meaningful measure of R&D alliance successes. This is of course an indirect measure of alliance effectiveness, but we can rely on firms' innovativeness, operationalized here as postalliance patenting activity as a close proxy.

It is empirically difficult to capture the contribution of past alliances to the overall performance, but it can be accomplished, provided strong control variables that will capture the rest of the variability in the model are included.

Data and Method

The data set used to test the hypothesis was constructed with information about patents and alliances in the semiconductor industry. (2) This industry was selected because of its dynamic characteristics and the fact that many firms in this industry rely on alliances to overcome high R&D costs and to face a changing environment. Alliances in this industry are also important because they serve as a mechanism for gaining access to new capabilities and speeding up new technology adoptions. On the other hand, this industry has significant patenting activity associated with R&D collaborations, and patents have been related to firm performance (Macher, 2004). In this industry, patents are closely related to the ability of firm to appropriate the returns of innovation.

The source of alliance data is the Securities Database Corporation (SDC) Database on Joint Ventures and Alliances. This is a comprehensive database that contains information on all kind of alliances since 1988 and is compiled from publicly available sources, including SEC filings, industry and trade journals, and news reports. Clearly this database offers the desired characteristics for conducting empirical studies on alliances, (3) and it has been extensively used for similar and unrelated research studies (Anand & Khanna, 2000; Sampson, 2004).

The sample for this study contains R&D alliances for firms in the semiconductor industry for the years 1997 and 1998. This period of time is appropriate given the important number of alliances in these 2 years and because it is possible to track firms' patents after the alliance was announced. Each record in this data set corresponds to an R&D alliance exclusively or in addition to marketing, production, and/or supply activities and funding activities. The final sample includes 86 R&D alliances involving 137 firms. Some characteristics of this sample are presented in Table 1.

International alliances are the number of alliances where the involved parties' headquarters are in different nations. Clearly, the majority of alliances involve one (or more) American firms.

For each firm mentioned in the previous sample, information about its patenting activity was collected directly from the U.S. Patent and Trademark Office (USPTO) Web site. (4) This governmental portal contains all the information about patents issued in the United States for the last 215 years and more. Detailed information is only available however since 1976, and it includes assignee name, patent technological classification, inventor name, issue date, and announcement date. Patent information was collected for every firm involved in an alliance as well as the other firms in its corporate structure because patents are often assigned to the ultimate parent firm and not the single subsidiary where the innovation took place. Sampson (2004) found that 73% of patents are assigned to the ultimate parent firm; thus, corporate-level patents were considered to avoid noisy measures of firm innovation. For each firm in the alliance data set, the relevant affiliations were obtained from the Directory of Corporate Affiliations. (5) The patent portfolio therefore includes patents assigned to firms in the alliance sample as well as parent firms.

Measures

Dependent Variable

Firm innovative performance (PATENT) is measured via citation-weighted, firm patenting in a 4-year, postalliance window. For example, if an alliance commences in 1997, PATENT is the sum of the citation-weighted patents applied for between 1998 and 2001, inclusive. This I-year lag is consistent with Hausman, Hall, and Griliches (1984), who showed that there is an almost contemporaneous relationship between alliance commencement and patent assignation.

Each time a new patent is assigned by the USPTO, the record of that patent includes information about the patents on which it was based. Thus, the number of citation-weighted patents after the alliance has been formalized provides us with a better indicator of R&D alliances outcomes than R&D spending, for example. Even though this is an approximation, patents are closely related to new product development (Comanor & Scherer, 1969), literature-based invention counts (Basberg, 1982), and nonpatentable innovations (Patel & Pavitt, 1997). Furthermore, because each patent cites previous patented inventions, this lineage can be used to determine the relative importance of the original patent, namely, the patents produced as a result of an alliance can be weighted to capture its relative importance. Empirical evidence shows a strong correlation between the ex post citations of the patent and the estimated value of the underlying invention (Trajtenberg, 1990). As such, citation weighting provides a less noisy measure of innovation than simple patent counts (Griliches, 1990). As Sampson (2005) suggested, we use the application date because this date is the earliest point at which we can identify new firm technology.

Independent Variable

Previous alliance experience (EXPERIENCE) is the focal independent variable and is measured as the number of alliances that a firm has been part of from 1990 up to but not including the year of the focal alliance. No restriction on the type of alliance was imposed on this data, and alliances for this time period include marketing, manufacturing, supply, or funding alliances. Any kind of alliance was selected here because firms learn to manage the coordination difficulties inherent in R&D alliances with any type of prior alliance experience rather than just prior R&D alliance experience. As noted by Sampson (2005),

With any type of alliance, firms learn how to coordinate

across organizational boundaries, select appropriate