Technology Sourcing Through Acquisitions: Evidence from the US Drug Industry

Technology sourcing through acquisitions: evidence from the US drug industry

1 Karen Ruckman Abstract There were a large number of US drug company takeovers in the 1990s by 1Simon Fraser University, Burnaby, British both foreign and domestic acquirers. Observation of the absolute difference Columbia, Canada between target and acquirer R&D intensity suggests there is no difference between foreign and domestic technology-sourcing patterns. However, a firm- Correspondence: level estimation of the acquirers’ choice of targets reveals that foreign and Dr Karen Ruckman, Simon Fraser University, domestic acquirers differ with respect to the relationship between target and 8888 University Drive, Burnaby, British Columbia, Canada V5A 1S6. acquirer R&D intensity. Foreign acquirers with low R&D intensity choose Tel: þ 1 604 291 3708; targets with high R&D intensities, which suggests technology sourcing as a Fax: þ 1 604 291 4920; motivation. Domestic acquirers prefer targets with high R&D intensities the E-mail: [email protected] higher their own R&D intensity, which suggests a synergy story. Journal of International Business Studies (2005) 36, 89–103. doi:10.1057/palgrave.jibs.8400110

Keywords: acquisitions; technology transfer; research and development

Introduction Acquisitions of companies in high-technology industries are a common and important method of gaining access to technology. Between 1993 and 1999, there were 93 acquisitions in the US drug industry (biotechnology1 and pharmaceutical industries com- bined), which had an average of 330 firms each year during the time period. One quarter of the acquirers were foreign companies, and three quarters were domestic. This study clarifies the difference in motivation for acquisitions between foreign and domestic acquirers of the US drug industry, with a particular focus on the motivation to source technology. The primary method used in this study to reveal the acquisition motivation is examination of the characteristics of the target firms in comparison with those of their acquirers. Traditional technology- sourcing investigations, starting with Kogut and Chang (1991), compare industry-level R&D industry of home and host country to determine motivation for foreign direct investment (FDI). This paper extends the traditional analysis from the industry level to the firm level.2 An initial analysis of the acquisition pairings reveals that the absolute difference between R&D intensity of the target and acquirer does not differ drastically between foreign and domestic acquisitions. This predicts that the acquisition patterns with respect to Received: 22 July 2003 Revised: 23 June 2004 technology sourcing do not differ between the two types of acquirer. Accepted: 28 July 2004 A more descriptive method of understanding the difference in Online publication date: 18 November 2004 acquisition motivation is to examine the relationship between Technology sourcing by acquisitions Karen Ruckman 90 acquirer and target R&D intensity. By examining technology sourcing. Kuemmerle (1999) deter- the R&D intensity of the target relative to the R&D mines that multinationals establish R&D facilities intensity of the acquirer, this study uncovers that to source existing skills more often when their there is a distinct motivational difference between country-level R&D intensity is lower than the the two types of acquisition. The acquirer’s choice source country’s. Recently, Chung and Alcacer of its target from the pool of all potential targets is (2002) find strong evidence that foreign acquirers estimated using a nested logit estimation. The choose to acquire targets in states where R&D results reveal that potential targets with high R&D intensity is high if they come from a country whose intensity are more attractive to a domestic acquirer industry R&D intensity is low. the higher its own R&D intensity, and to a foreign Studies investigating domestic technology sour- acquirer the lower its own R&D intensity. This cing also yield mixed results. Blonigen and Taylor implies a synergy story for domestic acquisitions (2000) investigate the US electronics industry and with respect to target and acquirer R&D intensity, find that domestic acquirer R&D intensity is and suggests the acquisitions were motivated to strongly negatively related to acquisitions, imply- build on an existing strength. Conversely, the ing that acquisitions may be used to externally results imply that foreign acquirers with low R&D source R&D. Hall (1987) analyzes domestic acquisi- intensity are technology-sourcing the US drug tions across all manufacturing industries and finds industry by using their acquisitions to compensate that mergers tend to occur between firms of like for their low internal R&D intensity. Foreign size and R&D intensity. Hall’s study implies a acquirers with a high R&D intensity appear to be synergy story between acquirer and target R&D motivated to secure a manufacturing target to intensity. It is possible for technology sourcing to distribute an existing innovation. An explanation occur even when both parties have high R&D for these results may lie in the fact that the US is intensity if the research is in different areas. expending the most amount of R&D in the world Because her study does not identify research biotechnology industry, and foreign acquirers with streams, it is impossible to determine whether low R&D intensity may be attempting to use their technology sourcing had occurred. Regardless of acquisitions to capture some of this innovative the conclusions of these studies, none has com- activity more than domestic acquirers, who, in pared foreign and domestic acquirers in the same theory, already have access to the innovative study. activity. The secondary contribution of this paper is that it The main contribution of this paper to the evaluates, at the firm level, the characteristics of literature is its comparison of domestic and foreign acquirers with their targets. With the exception of motivation for sourcing technology through acqui- Hall (1987), firm-level technology-sourcing studies sitions. Other technology-sourcing studies focus on investigate either the acquirer (Blonigen and Taylor, foreign investment or domestic investment (to a 2000) or the target characteristics (Shan and Song, lesser degree), but not both. The results have been 1997), but not both. Shan and Song (1997) investi- mixed for both types of investment. Beginning gate target patent counts as an incentive for foreign with studies on FDI, Kogut and Chang (1991) acquisitions in the US biotechnology industry and pioneered the technology-sourcing literature by find a significant correlation with probability of comparing acquirer and target R&D intensities at acquisition. Both the Blonigen and Taylor (2000) the industry level. They found that the count of study and the Shan and Song (1997) study suggest Japanese FDI in the US is strongly correlated with technology sourcing as a motivation, but, without a both countries’ R&D intensities and weakly corre- comparison to the other party involved, the infer- lated with the US’s relative research dominance. ence is only half convincing. Chung and Alcacer Similar results are found for acquisitions. Their (2002) almost constitute an exception by comparing findings do not rule out technology sourcing, but firm-level foreign acquirer and target state-level (not suggest that Japanese FDI in the US market is industry-specific) R&D intensity to determine moti- motivated by a synergy of total industry R&D vations for foreign direct investment in the US. They expenditure. Neven and Siotis (1996) do a parallel find weak evidence that acquirers choose targets study for Japanese FDI into Europe, and Anand where the state has high R&D intensity if their own and Kogut (1997) for total FDI into the US. Both firm-level R&D intensity is low (or vice versa), found similar results to Kogut and Chang (1991). concluding that foreign acquirers are using technol- More recent studies find stronger evidence for ogy sourcing as a motivation.

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 91

Hall (1987) is the only firm-level paper that any domestic firm can externally source technology compares acquirer and target characteristics through acquisition rather than innovating in- directly. Hall’s study is the closest in research house. method to this investigation, but it differs by The technology-sourcing literature predicts that, examining only domestic acquisitions. It will, if a home country’s industry-level R&D intensity is however, offer many opportunities for comparison lower than the host country, one would expect of domestic acquisitions results. There have been higher counts of FDI in that industry in the host enough inconsistent conclusions in this field that country (Kogut and Chang, 1991; Neven and Siotis, more research is necessary. This study will do that 1996; Anand and Kogut, 1997). The literature also by extending Kogut and Chang’s (1991) study to predicts that, if a home country’s R&D intensity is the firm level and expanding Hall’s (1987) study by lower than the host country, one would expect a comparing foreign with domestic acquisitions. higher number of multinational personnel to be The next section of the paper will describe in working on technology-sourcing projects (Kuem- greater detail technology as a motivation for merle, 1999). The common thread appears to be acquisition in the drug industry. The third section that an R&D intensity deficiency on one country’s describes the model and the fourth section esti- part leads to a greater impulse on the part of the mates the model. The final section elaborates on multinationals based there to capture existing the results of the analysis. technology from another country that can boast an R&D intensity abundance. Technology as a motivation for acquisition The firm-level equivalent of the industry-level The drug industry comprises the biotechnology and technology-sourcing argument is as follows: if an pharmaceutical industries3 (see Appendix A for a acquirer’s R&D intensity is lower than a potential description of SIC categories), and is considered target’s, one would expect a higher probability of high technology because of the amount of R&D acquisition of the target. This hypothesis utilizes expended relative to total costs. ‘The most valuable the same logic as employed in the industry-level assets of biotechnology companies are their intan- argument. The only difference is that the firm-level gible research capabilities, which represent the hypothesis cannot comment on forms of FDI other potential to develop and deliver new drugs. These than acquisition, because the direct comparison of research bases need to be continually nurtured and target and acquirer characteristics requires two pre- developed’ (DeCarolis and Deeds, 1999: 954). existing parties. Because research and innovation are so highly It is important to clarify that this paper does not valued in this industry, it follows that acquisitions differentiate whether acquisitions are motivated to would be more likely for targets with high R&D attain information about new and unfamiliar intensity.4 product lines or processes. The R&D intensity In high-technology industries, FDI is primarily variable at the firm level does not distinguish thought to be motivated to capitalize on a com- which R&D pipeline has received the expenditure. pany’s own technological assets in an attempt to Because product lines are not distinguished in this garner as much rent as possible from the in-house study, R&D expenditure in the drug industry is technological investment. However, an equally – if assumed to be generic in nature, and a higher R&D not more – important motivation for FDI may be to intensity suggests that a firm is highly innovative capture other companies’ existing technological relative to its size. assets. The companies that are technological lea- One of the benefits of investigating techno- ders have accumulated substantial scientific and logy sourcing at the firm level is that it becomes technological capacities. These technological possible to comment on technology sourcing in the endowments can be attained through acquisition domestic arena. The industry-level argument can- of existing companies, and the knowledge that the not predict technology sourcing to occur domes- acquirer gains can be transferred back to the parent tically because industry-level R&D intensities are company. If a company is being acquired for this identical for home and host countries in the purpose, then the acquirer is said to be technology domestic setting. In reality, a firm can be acquired sourcing. This is sometimes also referred to as by a foreign or domestic acquirer to source its knowledge sourcing, knowledge seeking or external proprietary knowledge. See Blonigen and Taylor sourcing. Technology sourcing usually implies that (2000) for an example of domestic technology the action is done by a foreign multinational, but sourcing.

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 92

Table 1 displays some R&D intensity statistics Model for the US drug industry, which will be used to test Let an acquirer a’s value of a potential target t in the technology-sourcing hypothesis. I follow Hall year y be (1987) and Blonigen and Taylor (2000) in measur- a Vyt ¼ VRyt ; Rya; Xyt ; Xya; Lt ; eyta À Vyt ð1Þ ing R&D intensity as the ratio of R&D expenditure over assets. Assets were used instead of sales because where Ryt and Rya are the R&D intensities of the some companies in this industry have zero or close target and acquirer in year y, Xyt is the size of the to zero sales, reflecting the length of time necessary target in year y, Lt is an index that reflects the to develop products. Assets are the sum of current target’s research location, eyta is an idiosyncratic assets, net property, plant and equipment, good- effect, and Vyt is the value of firm t as a standalone will, and any costs associated with patenting or company in year y. The variables of interest in this licensing. Another possible denominator for R&D investigation are those related to technology, but it intensity measurements is total costs. In this is important to control for the size of the acquirer industry, however, a high ratio of R&D expendi- and target because there are known negative tures to total costs usually reflects the youth of the correlations between R&D intensity and firm size company. Companies with a marketable product (Hall, 1987). a will thus have a lower R&D to costs ratio and yet The linear representation of the function Vyt that still be highly R&D-intensive firms. Yet another will be used in this paper is a measure for R&D intensity would be R&D expen- Vyt ¼ aRyt þ bRya þ gRyt Rya þ dXyt þ lXyt Xya diture to employee ratio. However, in this industry þ mL þ e À V ð2Þ there are many firms with extremely high R&D t yta yt a expenditure relative to the size of the company. For The function Vyt is the maximum willingness that these firms, the ratio of R&D expenditure to acquirer a has to pay for target t in year y, and it can employees would, to some degree, resemble the be thought of as the present discounted value of the average wage of the company. Assets were chosen revenue streams that could be generated from because they are considered to be an accurate target t’s assets in combination with acquirer a’s reflection of the size of a company. assets. In a well-working market for corporate Table 1 displays two similar statistics for both control, a firm acquires a target because it places a foreign and domestic acquisitions. The first is the higher value on that target than all other acquirers average of target R&D intensity less acquirer R&D and higher than the stock market valuation. Some- intensity for all acquirers and their eventual targets. times an acquirer finds a particular firm attractive The second is the same, except that each acquirer is for acquisition because its capabilities complement paired with every target that was available for the parent firm, and the value of the potential acquisition (potential targets). The pool of potential union is greater than the value of the two firms as targets is all the US drug industry companies in standalones. This may occur because the acquirer existence during the year of acquisition. For both values some technology that the target already statistics, the average foreign and domestic acquirer possesses that would cost the acquirer more to R&D intensity is substantially lower than the attain through other means. target’s. As all the statistics are positive, this table The pool of domestic US firms existing in a given indicates that technology sourcing is probably a year is the set of potential targets (T), and it is motivation for both foreign and domestic assumed that each acquirer evaluates all potential acquirers. targets relative to itself. The appropriate estimation method for this situation is a two-level nested logit model,5 where the acquirer first chooses a year in which to acquire a target and then chooses a target from the pool of potential targets available during Table 1 Firm-level technology sourcing statistics that year. A one-level nested logit model is the same Average difference of R&D intensity Foreign Domestic as a conditional logit model. The conditional logit between acquisitions acquisitions model assumes the independence of irrelevant alternatives (IIA). When this assumption is vio- Eventual target and acquirer 0.145 0.266 lated, the nested logit model is used to group the Every potential target and 0.302 0.156 alternatives into subgroups such that the IIA acquirer assumption is still valid within each subgroup.

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 93

Separating acquisition choice into yearly subgroups logit model is known as a type of choice analysis. It is necessary because there may have been changes is because of the group structure of a nested logit in policies applicable to acquisitions across the estimation that any variable that reflects an sample time period, which would lead to a viola- acquirer characteristic drops out of the estimation. tion of the independence assumption. Any potential target in the same group would be If the first-level alternative of choosing which subject to the same acquirer variable, and hence it year to acquire a target in is labeled ‘y’, and the does not vary within the group and cannot be second-level alternative of choosing which target to estimated. Variables that reflect acquirer character- acquire is ‘t’, then the probability that a represen- istics relative to target characteristics (in the form of tative acquirer a will choose target t is an interaction variable) remain in the model owing a a a to the variance in the target characteristics. Pyt ¼ PrtjyPry ð3Þ The nested logit model assumes that each where the conditional probability that an acquirer acquisition is independent. The list of acquisitions a will choose target t given a first-level choice to in Appendix A shows that there are seven domestic acquire during year Y is and three foreign acquirers that performed multiple expðVa Þ acquisitions during the time period. These acquisi- a P ytjY PrytjY ¼ a ð4Þ tions are clearly not independent from each other. expðVysjY Þ sT The estimation will account for this by including a a series of variables that interact with the focal Recall that the value function, Vyt, is defined as linear y variable of the study (the cross-product of target (equation (2)). The inclusive"# values for year are X and acquirer R&D intensity) with a dummy for each a a acquirer that took over more than one acquisition. Iy ¼ ln expðVysÞ ð5Þ sT Table 2 displays the number of acquisitions each The probability of acquirer a choosing to acquire year from 1993 to 1999. Appendix A lists the names any target in year y is of the acquirers, their targets, and – for foreign acquisitions – the acquirer’s country of origin. expða0Xa þ t IaÞ a P y y y Three quarters of the foreign acquisitions were Pry ¼ 0 a a ð6Þ expða Xn þ tnInÞ made by companies in European countries (the UK nY had the most, followed by Germany and France). where ty are the nested logit branch-specific para- One quarter of the foreign acquisitions were made meters. If they equal 1, then the equation reduces by companies from Canada, Israel, and Japan. down to a conditional logit model. Nested logit Table 3 displays some statistics of the main relaxes this assumption. variables of interest that will be used in the estimations. The statistics are across all years, for Estimation all potential targets and for each known acquirer. In the version of nested logit to be used, each Because there are, on average, 333 potential targets known acquirer forms a group and chooses its in each year, this amounts to over 160 000 domestic target from the subgroup composed of the potential observations and almost 50 000 foreign observa- targets. In this case, the potential targets are all the tions. The asset variables Xt; Xa were converted to US drug companies that exist during the year when logs because their large ranges amplified in the cross- the acquirer takes over its ultimate target. The product term, so that any meaningful relationship acquirer observes each potential target’s character- with the dependent variable was difficult to capture. istics (R&D intensity, size, location) as well as its The logged form of the variable decreased the initial own R&D intensity and size relative to each range and allowed relationships between large potential target’s. The company it ultimately takes acquirers and small targets (and between small over is its ‘choice’, which explains why the nested acquirers and large targets) to be interpreted.

Table 2 Number of domestic and foreign acquisitions of US drug companies

Type 1993 1994 1995 1996 1997 1998 1999 Total

Domestic acquisitions 5 5 13 8 13 15 13 73 Foreign acquisitions 1 4 1 2 2 5 6 21

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 94

Table 3 Statistics of variables

Variable Definition Measurement Subset St. dev. Minimum Mean Maximum

Rt Potential target R&D expenditure to assets ratio 0.5510 0 0.382 7.796 R&D intensity

Rt Ra R&D intensity (Potential target R&D intensity) Domestic acquisitions 0.2742 0 0.086 18.670 cross-product (Acquirer R&D intensity) Foreign acquisitions 0.0641 0 0.029 3.451

Xt Potential Assets in billions (in logs) 2.1317 À12.429 À3.520 3.461 target size

Xt Xa Asset (Potential target assets) Domestic acquisitions 10.6681 À38.338 4.937 112.428 cross-product (Acquirer assets), both in logs Foreign acquisitions 10.9241 À43.750 À0.239 110.009

Lt Potential target No. of R&D drug plants within 1.0892 0 3.873 5.505 research location 10 miles of target (in logs)

The cross-product of target and acquirer R&D The location where each US drug company does intensity indicates how the acquirer values target research was determined using the Directory of R&D intensity relative to its own R&D intensity. It American Research and Technology 1994: Organiza- does not indicate how the absolute levels of R&D tions Active in Product Development for Business intensities for the acquirer and target relate to each (Bowker, 1994). This book lists, in order of impor- other. Kogut and Chang (1991) considered the tance, every company active in R&D and the absolute difference between acquirer and target location of their R&D plants. For the purposes of R&D intensity, albeit at the industry level. The this study, the first plant listed was used as the shortcoming of Kogut and Chang’s method is that location where the company does most of its two possible acquisitions with the same absolute R&D. Many of these cities are geographically difference between acquirer and target R&D inten- located in close proximity, and therefore are sity would be viewed as equally likely whether the subject to the same potential innovation spillovers. acquirer is of an extremely high R&D intensity or The city with the highest number of R&D an extremely low R&D intensity. The method used plants was deemed an R&D center, or hub, and it in this paper assigns a different probability to the was grouped with every plant located in a 10 occurrence of these two potential acquisitions, mile (16 km) radius. The plant not in this depending on whether the acquirer is attracted to group with the next highest number of R&D plants higher target R&D intensity as its own intensity is was considered the hub of the next group, and so increasing or decreasing. It would be useful to on. Some groups overlap state borders. Table 4 compare the results using absolute differences, but displays the top 10 R&D cities with the highest the regression technique used to estimate the number of drug industry R&D plants in a 10 mile acquisition decision in this paper (nested logit) radius. does not allow for absolute differences between The estimated coefficients in the nested logit acquirer and target, only relative differences. estimation will determine the validity of the The variable for target research location (Lt) hypotheses. For the R&D location variable, a deserves further explanation. It is expected that positive estimated coefficient implies that acquirers acquirers will place higher value on potential prefer targets in locations with high R&D activity. targets located in highly innovative areas for the The implications for target R&D intensity and drug industry.6 It is arguably more important for target size are somewhat complicated by the domestic acquirers who would have an easier time presence of the cross-product terms. It is informa- gaining access to other close-by R&D intensive tive in this case to examine marginal effects. The firms because of familiar language, culture and marginal effect of target R&D intensity is depen- business practices. Foreign acquirers may realize, dent on acquirer R&D intensity, and is defined as7 pre-acquisition, that the indirect method of gaining f 0ðVa Þ a^ þ ^gR ð7Þ access to technology through locational spillovers yt ya may not be as fruitful for them, and they may where f0 is the probability density function of the choose not to put emphasis on this route. logistic distribution, a^ is the estimated coefficient

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 95

Table 4 Top 10 cities with most R&D plants within 10 mile the full sample is estimated with or without the (16 km) radius cross-product terms. This can be interpreted as R&D centers No. of plants in evidence that the first stage of this nested logit 10 mile radius estimation has merit, and that the one-stage conditional logit is not appropriate for this model. Cambridge, MA 246 The first estimation in Table 5 confirms that San Diego, CA 174 domestic acquirers strongly value targets with high Palo Alto, CA 171 S. San Francisco, CA 88 R&D intensities, with large size, and which are New York, NY 85 located in hotbeds of drug research activity. The Fairfield, NJ 77 second model proves the most interesting, as it Malvern, PA 76 adds in the cross-product terms of focal interest Irvine, CA 74 to the paper and also allows some comparison Seattle, WA 73 with Hall’s (1987) results. A likelihood ratio test Gaithersburg, MD 63 that compares the estimations in column 2 with column 1 (w2(2)¼43.60; prob4w2¼0.0000) confirms that adding the two cross-product terms enhances the model’s fit. For domestic acquisitions, the cross- on target R&D intensity, and ^g is the estimated product of target and acquirer R&D intensity is coefficient on the R&D cross-product term. The estimated to be positive and significant. For marginal effect is best displayed in a graph against a domestic acquisitions, the marginal effect of target range of acquirer R&D intensity values. Marginal R&D intensity is rising with acquirer R&D intensity, effects for target size can be defined in a similar as shown in Figure 1. fashion. There are over 168 000 observations in Figure 1. Table 5 displays the results for the nested logit Acquirer R&D intensity ranges from a minimum of estimation for the domestic acquisitions, and 0 to a maximum of 3.45. The corresponding Table 6 does the same for the foreign acquisitions. marginal effect of target R&D intensity ranges from The dependent variable is 0 for the potential targets a low of 0.01 for some of the acquirers with the and 1 for the actual target, for each known acquirer. lowest R&D intensity to a high of 0.17 for some of In total, there are 72 domestic acquirers and 21 the acquirers with the highest R&D intensity. The foreign acquirers. Each table displays three columns marginal effect of target R&D intensity for domestic of estimations. The first column shows the estima- acquisitions is always positive. The figure indicates tion with only the base variables, the second that domestic acquirers value targets with high regression adds the cross-product of R&D intensity R&D intensity, and they value it more as their own and size variables, and the third regression is R&D intensity rises. This suggests that domestic estimated only on the sample of acquirers that acquirers with high R&D intensity are pursuing a make one acquisition in the time period. A positive strategy of building on strength. That is, a firm (negative) sign on an estimated coefficient in choosing this strategy already has a comparative the estimation indicates that an acquirer tends advantage in innovation, and is using economies of to choose (not choose) targets with this character- scale to further this advantage. They may do this istic. Each branch (year of acquisition) was because the potential union of the two companies’ interacted with the acquirer size variable (Xya), research assets may synthesize more easily at higher and these results are displayed in the bottom levels of R&D intensity. Domestic acquirers with portion of each table. Those results indicate low R&D intensity still appear to be attracted to whether there was a significant difference in size targets with high R&D intensity, reinforcing the of acquirers, perhaps as a result of changes in hypothesis that R&D intensity is valued in this investment policy from year to year or in general industry. Without knowing the research lines of economic environment. each acquirer and target pair, it is impossible to The last statistic in each table tests whether the determine whether domestic acquisitions are moti- estimated branch-specific parameters in the nested vated by technology sourcing or not. logit estimation are equal to zero (the null hypoth- The value that domestic acquirers put on target esis). For domestic acquisitions the null is rejected size can be determined similarly. Domestic acquirer soundly when the cross-product terms are included. size (US billions, in logs) ranges from a minimum of For foreign acquisitions the null is rejected when À10.48 to a maximum of 3.57. The corresponding

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 96

Table 5 Nested logit estimation, domestic acquisitions

Variable Definition Column 1: Column 2: Column 3: sample full sample full sample without acquirers that made multiple acquisitions

Est’d coeff. Est’d coeff. Est’d coeff. (std error) (std error) (std error)

Rt Target R&D intensity 0.610*** (0.1186) 0.570*** (0.1143) 0.616*** (0.1252) Rt Ra Cross-product of 0.034** (0.0151) 0.026** (0.0127) target and acquirer R&D intensity

Xt Target assets (in logs) 0.308*** (0.0535) 0.283*** (0.0513) 0.291*** (0.0599) Xt Xa Cross-product of À0.008*** (0.0023) À0.006*** (0.0022) target and acquirer assets (in logs)

Lt No. of R&D drug plants 0.247** (0.1229) 0.245** (0.1216) 0.249* (0.1420) within 10 miles of target (in logs)

Branches:

D93 Xa D93¼1 if branch À0.215 (0.2371) À0.412 (0.2625) À0.535 (0.3044) (choice year) 1993

D94 Xa D94¼1 if branch À0.183 (0.2327) À0.171 (0.2572) À0.275 (0.2831) (choice year) 1994

D95 Xa D95¼1 if branch À0.152 (0.1706) À0.704*** (0.2469) À0.819*** (0.2873) (choice year) 1995

D96 Xa D96¼1 if branch À0.351 (0.2183) À0.944*** (0.2829) À1.187*** (0.3675) (choice year) 1996

D97 Xa D97¼1 if branch À0.475** (0.2159) À0.837*** (0.2637) À1.415*** (0.4731) (choice year) 1997

D98 Xa D98¼1 if branch À0.198 (0.1703) À0.390* (0.2073) À0.542** (0.2529) (choice year) 1998

Log likelihood: À508.77 À486.97 À352.11 LR test of estimation fit, w2 (16) or (18): 53.11*** 81.19*** 71.61*** LR test of homoskedasticity, w2(7): 6.93 31.62*** 29.65***

*Significance below 10%; **Significance below 5%; ***Significance below 1%. All variables D are dummy variables that equal 1 under the condition stated and 0 otherwise.

marginal effect of target size ranges from almost research location, but many of the other variables zero to 0.09. A figure similar to Figure 1 would in this study are at least superficially comparable. reveal that, even though the range of marginal Her study found that (domestic) acquirers are effect of target size gets smaller as acquirer size attracted to targets with high R&D intensity, increases, because the marginal effects are always and that ‘the shadow value placed on R&D capital positive, domestic acquirers are always attracted to is steeply rising with the acquiring firms’ R&D large targets. intensity’ (p. 91). This finding is confirmed in Hall (1987) investigated domestic acquisitions this study. across all manufacturing industries. Her study The third estimation is the same as the second, used a conditional logit model that did not except that the sample excludes acquirers that account for investment policy differences between made more than one acquisition in the time years in the sample period (1977–86) and did not period. All variables are robustly estimated, and a account for multiple acquisitions. Also, she did not joint test on all the coefficients in the third include a motivation for acquisition that related to regression cannot reject the null hypothesis that

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 97

Table 6 Nested logit estimation, foreign acquisitions

Variable Definition Column 1: Column 2: Column 3: sample full sample full sample without acquirers that made multiple acquisitions

Rt Target R&D intensity À0.923 (1.137) 0.852 (0.7062) 0.805 (0.7929) Rt Ra Cross-product of target À56.118 (30.689) À60.552* (34.403) and acquirer R&D intensity

Xt Target assets (in logs) 0.255*** (0.0997) 0.200** (0.0969) 0.218*** (0.1104) Xt Xa Cross-product of target 0.093** (0.0457) 0.085 (0.0554) and acquirer assets (in logs)

Lt No. of R&D drug plants 0.011 (0.2251) 0.094 (0.2135) À0.003 (0.2445) within 10 miles of target (in logs)

Branches:

D93 Xa D93¼1 if branch 0.481 (0.5967) 0.471 (0.6061) 0.820 (0.7817) (choice year) 1993

D94 Xa D94¼1 if branch 0.345 (0.3484) 0.359 (0.3411) À0.218 (0.4596) (choice year) 1994

D95 Xa D95¼1 if branch 340.52 (8242.72) 241.186 (303.628) 296.314 (401.715) (choice year) 1995

D96 Xa D96¼1 if branch 0.128 (0.3931) 0.104 (0.4392) À0.016 (0.7828) (choice year) 1996

D97 Xa D97¼1 if branch À0.228 (0.3616) À0.206 (0.3621) À0.205 (0.4432) (choice year) 1997

D98 Xa D98¼1 if branch 0.722 (0.4660) 0.681* (0.3819) 1.070* (0.6599) (choice year) 1998

Log likelihood: À145.85 À140.24 À97.43 LR test of estimation fit, w2 (16) or (18): 34.14*** 45.37*** 37.88*** LR test of homoskedasticity, w2 (7): 13.61** 14.05** 9.57

*Significance below 10%; **Significance below 5%; ***Significance below 1%. All variables D are dummy variables that equal 1 under the condition stated and 0 otherwise.

they equal those found in the regression with the full sample (w2(11)¼3.52, prob4w2¼0.9819). Domestic acquirers that made only one acquisition have the same decision patterns as those that made more than one acquisition. The interactions of each branch (or acquisition year) with acquirer size are estimated robustly over the three models, and appear to have more overall significance in the regressions that include the cross-product terms. The results suggest that acquirer size in 1995–1997 is significantly smaller than other years. This effect could be due to changes in investment policy in this industry, or due to general economic conditions in the national Figure 1 Marginal effect of target R&D intensity vs acquirer economy, which facilitated investment for smaller R&D intensity, domestic acquisitions. acquirers.

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 98

The estimation of the foreign acquisitions dis- internal R&D intensity are not attracted to targets played in Table 6 shows, by including the cross- with high R&D intensity. This may signify that an product terms, that foreign acquirers have an acquirer is choosing to take over a target that is interesting relationship with target R&D intensity. principally engaged in manufacturing, to facilitate A likelihood ratio test between the estimations in its own distribution. columns 1 and 2 proves that adding the cross- Foreign acquirer size (US billions, in logs) ranges product terms contributes positively to the from a minimum of À9.63 to a maximum of 3.79. model’s fit (w2(2)¼11.23, prob4w2¼0.0036). The The corresponding marginal effect of target size estimation in the first column suggests that foreign ranges from À0.17 for some of the smallest acquirers do not value target R&D intensity, but the acquirers to 0.14 for some of the largest. This estimation in the second column extracts the reveals that foreign acquirers are attracted to large reason for this confusing result. The second targets more as their own size increases. This is estimation shows that foreign acquirers do value perhaps is a precursor to the mergers starting high target R&D intensity, as predicted, but they during 1999 between pharmaceutical giants the value this more the lower is their own R&D world over. intensity. The marginal effect of target R&D The results in the third column of Table 6 show intensity is falling with acquirer R&D intensity, as that the estimation in column 2 regressed on the shown in Figure 2. subsample of acquirers that made only one acquisi- There are almost 50 000 observations in Figure 2. tion during the time period contributes positively Foreign acquirer R&D intensity ranges from a to the model’s overall fit. However, a joint test on minimum of almost 0 to a maximum of 0.15. The all the coefficients in the third regression cannot corresponding marginal effect of target R&D inten- reject the null hypothesis that they equal those sity ranges from 0.07 for some of the acquirers with found in the regression with the full sample the lowest R&D intensity to À1.16 for some of the (w2(11)¼2.80, prob4w2¼0.9932). It appears that acquirers with the highest R&D intensity. This the decision process of foreign acquirers that made suggests that foreign acquirers with low R&D only one acquisition does not differ from those that intensity are pursuing a strategy of gap filling with made more than one acquisition. respect to R&D intensity. They value target R&D Foreign acquirers do not significantly value intensity more as their own R&D intensity targets located in areas with large amounts of decreases. They may be using their acquisitions to drug research activity. This was correctly hypothe- compensate for a low internal R&D intensity. This sized to be due to the larger amount of time, suggests that foreign acquirers with low R&D effort, and money that foreign acquirers would intensity may be technology-sourcing the US drug need to expend to collaborate with domestic firms industry. A negative marginal effect of target R&D compared with domestic acquirers, who already intensity indicates that foreign acquirers with high share the same culture, language, and social familiarity. As with domestic acquisitions, the interactions of each branch, or year in the sample period, with acquirer size are estimated robustly over the three models. The results suggest that there is weak evidence for a difference in the size of the acquirer during 1998 relative to the other years. It appears that foreign acquirers during that year were significantly larger than in other years. Table 2 revealed that a large number of foreign acquisitions occurred in 1998. It is possible, but not likely, that there were changes in foreign investment policies during that year that would exclude smaller foreign acquirers. It is more likely that, because the majority of acquirers that are willing to risk foreign investment are large to begin with, Figure 2 Marginal effect of target R&D intensity vs acquirer there were changes in the worldwide economic R&D intensity, foreign acquisitions. environment that made foreign investment in the

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 99 drug industry necessary or more attractive during targets to choose from. The combination of the size that time. and the overall high R&D intensity of the industry make the US attractive for investment and potential technology sourcing. Conclusions An observation of the difference between target and acquirer R&D intensities using the methodology Acknowledgements pioneered by Kogut and Chang (1991) predicts that This work was funded in part by SSHRC. I am grateful foreign and domestic acquirers are using their to Keith Head and Barbara Spencer, the Strategy and acquisitions to source existing technology in the Business Economics Division seminar participants at US drug industry by taking over companies with the University of British Columbia, and the Academy of higher R&D intensities than their own, but not to International Business conference participants in July any greater degree than each other. By examining 2003. In addition, I would like to thank the JIBS the R&D intensity of the target relative to the R&D department editor, Myles Shaver, and the anonymous intensity of the acquirer, while controlling for other reviewer. motivations for acquisitions, this study uncovers a distinct difference between the two types of acquisition. Notes The results from the nested logit estimation of 1Biotechnology is a general term describing the the acquirer choice model suggest that foreign directed modification of biological processes. In its acquirers with low R&D intensity are technology- purest form, the term ‘biotechnology’ refers to the use sourcing the US drug industry. They appear to be of living organisms or their products to modify human using their acquisitions to compensate for a low health and the human environment. internal R&D. As their own R&D intensity 2This extension of the industry-level technology- increases, they are attracted to targets with low sourcing argument to the firm level considers only R&D intensity, which suggests that they are more acquisitions as the definitive method of sourcing interested in facilitating manufacturing for their technology. This paper does not investigate greenfield own products in the US market. The results do not investments as a method of technology sourcing show the same dynamic for domestic acquirers. through locational spillovers although it is an impor- Domestic acquirers are found to be motivated by a tant method of technology sourcing (e.g. Chung, synergy-type strategy with respect to R&D intensity 2001; Florida, 1997; Jaffe et al., 1993), the primary with their targets. They always value target R&D investigation of this paper is to compare acquirer and intensity, and this attraction increases as their own target characteristics with each other. In forms of FDI R&D intensity increases. This suggests a story of other than acquisitions, one party is missing for that synergy of resources, which Hall (1987) also found comparison. in domestic acquisitions. With regard to the 3Essentially, a pharmaceutical firm is a mature traditional concept of technology sourcing, both biotechnology company. The following quote from types of acquirer are indeed sourcing the US drug the US annual industry report Biotech ’99 explains the industry for existing technology, but they are doing relationship: ‘Understanding the biotech industry is it in different ways. akin to understanding the pharmaceutical industry. An explanation for the results may lie in the fact That’s because a successful biotechnology company at that the US is expending the largest amount of R&D maturity is a pharmaceutical company that discovers, in the world biotechnology industry, and foreign develops, and distributes therapeutic products. acquirers may be attempting to use their acquisi- Despite slight differences in product offerings (biolo- tions to capture some of this innovative activity gics versus small molecules), more similarities than more than domestic acquirers, who, in theory, differences exist. y Over the last two years, many already have access to the innovative activity. biotech firms became operational, and Hence Foreign acquirers may be using their acquisitions became pharmaceutical companies’ (Ernst and Young, to get as much possible R&D intensity for their 1999: 20). money, as this is the most valuable resource in the 4R&D intensity is used as a proxy for technological drug industry. In addition, the US drug industry has capacity. R&D intensity is usually thought of as a the largest amount of production in the world, technology (or innovation) input, whereas patents are allowing foreign acquirers to have more potential a technology (or innovation) output. In the context of

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 100 this study, the delays between the expenditure of with similar interests promotes the natural exchange of R&D, subsequent innovation, the application for a ideas through networks established (DeCarolis and patent, and the final awarding of a patent are the Deeds, 1999). This is considered to be an indirect biggest problems with using patents as a definitive method of technology sourcing, as opposed to proxy for firm innovativeness. A prospective acquirer attaining technology directly through acquisition. may instead value the amount of R&D expenditure Audretsch and Feldman (1996) found that, even after already invested in the firm as an indication of the accounting for the geographic concentration of the future technology capacity (or innovation rents) that production location, industries for which research is the target may bring to the acquirer. In this paper, important have a higher propensity to cluster ‘technology’ is a general term used to denote together. Jaffe et al. (1993) investigated localization technology assets, ideas, knowledge or processes. of innovativeness through patent citations, and 5See Greene (2000: 865–871) for a thorough found evidence that they are indeed geographically description. localized. 6Acquirers may value a target’s geographic location 7Ai and Norton (2003) give a thorough analysis of because of the potential access to innovation spil- the marginal effects of interaction terms in nonlinear lovers. The close proximity of research organizations models.

References Ai, C. and Norton, E. (2003) ‘Interaction terms in logit and Neven, D. and Siotis, G. (1996) ‘Technology sourcing and FDI in probit models’, Economics Letters 80: 123–129. the EC: an empirical evaluation’, International Journal of Anand, J. and Kogut, B. (1997) ‘Technological capabilities of Industrial Organization 14: 543–560. countries, firm rivalry and foreign direct investment’, Journal of Shan, W. and Song, J. (1997) ‘Foreign direct investment and the International Business Studies 28(3): 445–465. sourcing of technological advantage: evidence from the Audretsch, D. and Feldman, M. (1996) ‘R&D spillovers and the biotechnology industry’, Journal of International Business geography of innovation and production’, American Economic Studies 28(2): 267–283. Review 86(3): 630–640. Blonigen, B. and Taylor, C. (2000) ‘R&D intensity and acquisitions and high technology industries: evidence from the US electronic and electrical equipment industries’, Journal of Appendix A Industrial Economics 48: 47–70. Bowker, R. (1994) Directory of American Research and Technology Data sources 1994: Organizations Active in Product Development for Business, R.R. Bowker Co.: New York. Company financial information: Compustat. Chung, W. and Alcacer, J. (2002) ‘Knowledge seeking and Acquisition information: Mergers & Acquisitions location choice of foreign direct investment in the United States’, Management Science 48(12): 1534–1554. journal (M&A). DeCarolis, D. and Deeds, D. (1999) ‘The impact of stocks and Foreign acquirers’ information: Compustat 20-F flows of organizational knowledge on firm performance: an empirical evaluation of the biotechnology industry’. Strategic forms or annual reports. Management Journal 20: 953–968. R&D location information: Directory of Amer- Ernst & Young (1999) Biotech 99: Bridging the Gap, 13th Annual ican Research and Technology, 1994. Biotechnology Industry Report, Ernst & Young: New York. Florida, R. (1997) ‘The globalization of R&D: results of a survey The companies in the dataset are publicly traded of foreign-affiliated R&D laboratories in the USA’, Research Policy 26: 85–103. and are of the following Standard Industrial Greene, W. (2000) Econometric Analysis, 4th edn, Prentice-Hall: Classifications (SICs): 2833 (Drugs: Medicinals Englewood Cliffs, NJ. and Botanicals), 2834 (Pharmaceutical Prepara- Hall, B. (1987) ‘The Effect of Takeover Activity on Corporate Research and Development’, in A. Auerbach (ed.) Corporate tions), 2835 (Prepared Diagnostic Substances), Takeovers: Causes and Consequences (NBER Conference 2836 (Biological Products), and 8731 (Biotech Volume). Chicago: University of Chicago. Research). Other companies were added to the data Jaffe, A., Trajtenberg, M. and Henderson, R. (1993) ‘Geographic localization of knowledge spillovers as evidenced by patent set whose SICs are not listed above. They were citations’, Quarterly Journal of Economics 434: 577–598. classified in Compustat under SICs that probably Kogut, B. and Chang, S. (1991) ‘Technological capabilities and Japanese foreign direct investment in the US’, Review of described the company at its conception, but using Economics and Statistics 73: 401–413. the ‘description of business’ in their 10k reports Kuemmerle, W. (1999) ‘The drivers of foreign direct invest- these companies clearly should be classified in ment into research and development: an empirical investigation’, Journal of International Business Studies 30: the drug categories above. Those companies are 1–24. listed below:

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 101

SIC Description Company name

2800 Chemicals and allied products American Cyanamid Co. Monsanto Co. 3841 Surgical and medical instruments and apparatus Becton Dickinson & Co. C.R. Bard Inc. Cohesion Technologies Inc. Research Medical Inc. 2840 Soaps, cleaning products, perfumes, cosmetics, other toilet preparations Procter & Gamble Co. 5122 Wholesale drugs: proprietary Cardinal Health Inc. 8734 Services: commercial physical and biological research Chrysalis Intl Corp. 3842 Orthopedic, prosthetic & surgical appliances and supplies Collagen Aesthetic Inc. 5912 Retail: drugs stores and proprietary stores Omnicare Inc. 3826 Laboratory analytical instruments Perseptive Biosystems Inc.

List of acquisitions

Year Foreign acquirer Country Target

1997 B. Braun Melsungen AG Germany Ivax Corp. 1998 Bayer AG Germany Chiron Corp. 1996 Biomerieux SA France Aquila Biopharm Inc. 1999 Biovail Corp. International Canada Fuisz Technologies Ltd 1998 Elan Corp. plc UK Neurex Corp. 1998 Elan Corp. plc UK Sano Corp. 1994 Fresenius AG Germany Gull Laboratories Inc. 1998 Fujirebio Inc. Japan Centocor Inc. 1995 Hoechst AG Germany Marion Merrell Dow Inc. 1993 Novo Nordisk A/S Denmark Bristol Myers Squibb 1999 Peptide Therapeutics Group plc UK Oravax Inc. 1999 Phoenix International Life Science Canada Chrysalis Intl Corp. 1997 Rhone-Poulenc SA France Chirex Inc. 1994 Roche Holding AG Switzerland Genentech Inc. 1994 Roche Holding AG Switzerland Syntex Corp. 1999 Shire Pharmaceuticals Grp UK Roberts Pharmaceutical Corp. 1999 Skyepharma plc UK Depotech Corp. 1996 Teva Pharmaceutical Industries Ltd. Israel Biocraft Laboratories Inc. 1999 Teva Pharmaceutical Industries Ltd. Israel Copley Pharmaceutical Inc. 1994 Trinity Biotech plc UK Disease Detection Intl 1998 VIAG AG Germany Nexstar Pharmaceuticals

Year Domestic acquirer Target

1998 Abbott Laboratories Intl Murex Tech Corp. 1997 Agouron Pharmaceuticals Inc. Alanex Corp. 1996 Akorn Inc. Johnson & Johnson 1998 Akorn Inc. ALZA Corp. 1999 Alza Corp. Sequus Pharmaceuticals Inc. 1993 American Cyanamid Co. Immunex Corp. 1994 American Home Products Corp. American Cyanamid Co. 1995 American Home Products Corp. Repligen Corp. 1996 American Home Products Corp. Genetics Institute Inc. 1998 American Home Products Corp. Apollon Inc. 1994 Amgen Inc. Synergen Inc. 1998 Aquila Biopharm Inc. Procept Inc. Continued

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 102

1998 Avant Immunotherapeutics Inc. Virus Research Institute Inc. 1998 Axys Pharmaceuticals Inc. Sequana Therapeutics Inc. 1995 Bristol Myers Squibb Merck & Co. 1995 C.R. Bard Inc. Medchem Products Inc. 1997 Cambrex Corp. Biowhittaker Inc. 1998 Cambrex Corp. Celgene Corp. 1998 Cardinal Health Inc. Scherer (R P) 1997 Cell Genesys Inc. Somatix Therapy Corp. 1994 Chattem Inc. Procter & Gamble Co. 1993 Chiron Corp. Centocor Inc. 1995 Chiron Corp. Viagene Inc. 1996 Collagen Aesthetic Inc. Cohesion Technologies Inc. 1999 Corixa Corp. Anergen Inc. 1999 Corixa Corp. RIBI Immunochem Research Inc. 1995 Cytogen Corp. Cellcor Inc. 1995 Dura Pharmaceuticals Inc. Abbott Laboratories 1996 Dynagen Inc. Alpharma Inc. 1994 Eli Lilly & Co. Sphinx Pharmaceuticals Corp. 1995 Genetics Institute Inc. Scigenics Inc. 1996 Genzyme Corp. Consolidated Neozyme II Corp. 1999 Gilead Sciences Inc. Nexstar Pharmaceuticals 1996 Hemagen Diagnostics Inc. Cellular Products 1993 IGI Inc. Univax Biologics Inc. 1998 Incara Pharmaceuticals Corp. Interneuron Pharmaceuticals 1995 Integra Lifesciences Hldgs Telios Pharmaceuticals Inc. 1994 Ivax Corp. Zenith Laboratories 1999 Johnson & Johnson Centocor Inc. 1998 King Pharmaceuticals Inc. Warner-Lambert Co. 1995 Ligand Pharmaceutical Glycomed Inc. 1997 Ligand Pharmaceutical Allergan Ligand Retnd Therap 1998 Ligand Pharmaceutical Seragen Inc. 1995 Mallinckrodt Inc. Syntro Corp. 1997 Medarex Inc. Houston Biotechnology Inc. 1999 Medimmune Inc. US Bioscience Inc. 1999 Merck & Co. Sibia Neurosciences Inc. 1998 Meridian Diagnostics Inc. Gull Laboratories Inc. 1999 Millennium Pharmaceuticals Inc. Leukosite Inc. 1995 Monsanto Co. Merck & Co. 1998 Mylan Laboratories Penederm Inc. 1995 NABI Inc. Univax Biologics Inc. 1997 Nexell Therapeutics Inc. Innovir Laboratories Inc. 1996 North American Vaccine Inc. Cephalon Inc. 1998 Omnicare Inc. Ibah Inc. 1996 Perseptive Biosystems Inc. ChemGenics Pharmaceuticals Inc. 1999 Pharmacia & Upjohn Inc. Sugen Inc. 1999 Quidel Corp. Metra Biosystems Inc. 1993 Roberts Pharmaceutical Corp. Bristol Myers Squibb 1997 Schein Pharmaceutical Inc. Marsam Pharmaceuticals Inc. 1997 Selfcare Inc. American Home Products Corp. 1999 Supergen Inc. Sparta Pharmaceuticals Inc. 1998 Techne Corp. Genzyme Corp. Consolidated 1997 Titan Pharmaceuticals Inc. discovery laboratories Inc. 1999 Valentis Inc. Genemedicine Inc. 1997 Vaxcel Inc. Zynaxis 1999 Warner-lambert co. Agouron Pharmaceuticals Inc. 1995 Watson Pharmaceuticals Inc. Circa Pharmaceuticals Inc. 1997 Watson Pharmaceuticals Inc. Royce Laboratories Inc. 1997 Watson Pharmaceuticals Inc. Cocensys Inc.

Journal of International Business Studies Technology sourcing by acquisitions Karen Ruckman 103

About the author Strategy and International Business at the Karen Ruckman is an Assistant Professor of John Molson School of Business at Concordia Strategy at Simon Fraser University (Burnaby, University (Montreal, Canada) from 2001 Canada). She was an Assistant Professor of to 2004.

Accepted by J. Myles Shaver, Departmental Editor 28 July 2004. This paper has been with the author for two revisions.

Journal of International Business Studies