How to Make a Partnership with International Stranger Successful
The Comparison of International Strategic Alliance Network between Chinese and American Pharmaceutical Industry
Chih-Sheng Hsu, National Taiwan University, Taiwan
ABSTRACT
Strategic collaboration has become an important and worldwide mechanism for pharmaceutical firms to succeed in drug discovery, development, and commercialization under the pressure of mass resources needed in R&D and increasingly intense competition in the global drug market. How collaboration network of pharmaceutical industry evolve in China versus United States? This article contributes to the literature on the networks of international strategic alliance by comparing geographic distance, economic distance, mean number of partner, density of network and the type of international strategic alliances in China and the United States. Taking both static and dynamic view of network and focusing on the pharmaceutical industry, we propose not only the framework of different motivations for alliances, but also the different forms of alliance network between Chinese and American firms. Additionally, we advance and examine the hypotheses using 20 years of pharmaceutical industry data and find some new outcomes.
Keywords: International Strategic Alliance, Network, Pharmaceutical Industry
INTRODUCTION
Chinese firms, which are different from firms in western countries, might have different motivations and partner selection for strategic alliance. Although strategic motives and partner selection criteria have become popular research themes in the examination of ISAs, few researchers have conducted a detailed analysis of Chinese firms. How has the alliance network of the pharmaceutical industry evolved in both China and the United States? This is one of the most interesting questions in global business research.
The purpose of this study is to compare the strategic alliance of pharmaceutical firms from China with those in the United States in order to understand the different motivations of alliance and how it affects partner selection. We are most interested in understanding the differences in (1) cross-national or domestic alliances; (2) the economic distance between partners; (3) numbers of partner per alliance; (4) average number of partners (per firm); (5) density of alliance network; and (6) types of alliance network between Chinese firms and American firms in pharmaceutical industry. This study also examines their dynamic evolution.
This research is unique in several ways. First, unlike prior research on alliance network in any industry, we focus explicitly on the pharmaceutical industry. As a result, our analysis yields important insights. Second, few studies of strategic alliance network have distinguished Chinese from American firms. Our research is designed to address the explicit differences between the two. Third, most of the recent research on alliance networks investigates their static patterns. In this paper we integrate this research stream with the dynamic evolution by empirically analyzing the longitudinal data. Fourth, Chinese firms generally have more simultaneous cross-national partners than American firms do. Nevertheless, we find that the result is the opposite. The study thus provides academic researchers, managers in pharmaceutical companies, and governments with a more precise understanding of the differences between the alliance networks created in China and those in the United States from both static and dynamic perspectives.
CONCEPTUAL BACKGROUND AND PROPOSITIONS
1.Different Motivations for Strategic Alliances between Chinese Firms and Firms from the U.S.
The major motivations for strategic alliance differ between Chinese firms and those from the U.S. Many businesses in China are young or have recently been privatized, and their resource endowments are unlikely to be strong. They may have specific resource endowments but may need additional resources to be competitive. Such a need is a primary reason for strategic alliances. Therefore, Chinese firms may use alliance as a means of acquiring the tangible and intangible resources to develop their capability to compete in their domestic and international markets (Hitt et al., 2000). In contrast, firms from the U.S. have richer resource and experience. They are motivated to form strategic alliances in several ways. First, through interaction with other firms in the same country, a firm can combine its own knowledge with external knowledge, thereby generating collective competencies or new knowledge. Additionally, for cross-national alliance, they can extend the scope of current operations, achieve scale economies, and reduce entry costs, labor costs and risks in new foreign markets.
2.Partner Selection for International Strategic Alliances
The specific motive for alliance formation is likely to have an impact on the partner selection process, as firms are likely to place different value on the resources or capabilities of a potential partner based on this initial motive. For instance, if a Chinese firm’s main motivation for forming an alliance is to learn advanced technology, selecting an international partner with the technology that is needs may be most important. Conversely, if a American firm’s main motivation for alliance is international expansion and entry into an emerging market, selecting a local partner may be of higher value. Therefore, partner selection in strategic alliances will differ with the strategic motives for alliance formation.
(1) Cross-national or Domestic Alliances
The formation of cross-border or domestic alliances often follows directly from the motivation for alliance. For Chinese firms, most of which lack the resources and critical technologies or skills for survivorship, cross-national alliance with firms from developed countries are most often used, especially for high-tech industry (such as the pharmaceutical industry) and new business start-ups.
However, as several traditional internationalization theories suggest, geographic distance has had a major impact on the target country selected for alliance (Ojala, 2007) because the costs of trade rise with geographic distance (Chang, 2004). In general, the geographic distance of a cross-national alliance is greater than a domestic alliance, and firms from the U.S. are tend to make alliances with domestic firms to leverage complementary resources rather than search a foreign partner with higher cost of trade, culture distance and behavior uncertainty. Therefore:
Hypothesis 1a: Chinese firms are more likely to make cross-national alliances; however, American firms are more likely to make domestic alliances.
Hypothesis 1b: In a dynamic perspective, over the past 20 years, Chinese firms continue make more proportion on cross-national alliances, and American firms continue make more proportion on domestic alliances.
(2) Economic Distance
Economic distance is a measure of economic disparity between two countries (Ghemawat, 2001). The economic distance between two countries often reflects differences in factor costs (such as wages) and in technological capability, both important factors leading to the conflict and affecting the process of international alliance and performance (Tsang & Yip, 2007).
Johnson (2008) suggested that it is easier for a multinational enterprise to deal with host countries that are close in economic distance from their home country. There are several reasons. First, countries close in economic development have similar market segments that can afford to consume similar types of goods and services. Thus, knowledge about market demand transfers easily from home to host country. Second, countries that are similar in economic development have similar physical infrastructure, such as airports, roadways, railways, and seaports. Thus, firms serving a host country with an infrastructure similar to the home country will enjoy efficiencies in its operations, thus lowering costs. Third, firms develop competencies or knowledge-based resources that are related to their markets (Madhok, 1997). These resources can be best leveraged in countries that are similar in economic development because the skills learned in one market can be replicated in or adapted to the new markets. Besides, Dunning (1998) argued that firms entering countries that are widely different economically from their home country need to adjust to the new market conditions, thus reducing their likelihood of success. According to these articles on foreign direct investment, we may know that economic distance between partners seems will be negatively associated with successful alliance. Indeed, American firms tend to engage in cross-national alliances with partners that are in economic proximity to their countries; however, Chinese firms are still likely to make cross-national alliances with partners that are economically similar to China in order to learn the technologies or skills that are not possessed by partners that are in economic proximity to their countries. Thus:
Hypothesis 2a: Chinese firms are more likely to make cross-national alliances with partners that are great in economic distance from their countries; however, American firms are more likely to make cross-national alliances with partners that are close in economic distance.
Hypothesis 2b: In a dynamic perspective, over the past 20 years, in terms of the cross-national alliance, Chinese firms continue make more proportion on cross-national alliances with partners that are great in economic distance from their countries, and American firms continue make more proportion on alliances with partners that are short in economic distance.
3. Scale of Alliance Network
(1) Number of Partner (per Alliance)
Most studies on international strategic alliance have focused on those formed between two firms, where the underlying assumption has been that a strategic alliance involves only two-partner firms. Although this structure dominates, many firms enter into partnerships of three or more firms.
Franko (1971) theorized that as the number of parent firms in an international alliance increases, individual roles become more complex, thus leading to higher failure rates. Elaborating on this theory, Park and Russo (1996) examined the impact of the number of partners on performance and found a positive relationship. Hu and Chen (1996), however, claimed the relationship between alliance performance and number of partners was curvilinear; increasing the number of partners (up to five) is positively associated with alliance performance. Thereafter, increasing the number of partners tends to decrease alliance performance (Beamish, 2004).
In effect, although some researchers have found a positive impact of the number of partners (over two) on returns in the formation of alliance, there is evidence that more partners in one alliance is not good. Such a view underlies Esteban’s (2007) findings. First, a higher number of partner augments coordination and motivation costs (Oxley, 1997). Each new partner requires additional efforts so the total amount of relational investments needed to make the alliance work is higher. As a consequence, partners have fewer incentives to invest in the relationship, which may diminish the functioning of the alliance. Second, a higher number of partners make agreement more difficult. A new partner not only increases the required amount of relational investments, it also reduces the chances to profit from these investments, given that it is more difficult to define new projects which satisfy the requirements of all the partners. A final factor limiting the value created by these alliances is that each new partner makes it more difficult to put the reciprocity mechanism into practice (Parkhe, 1993). For all of these reasons, multi-partner alliances (over two) are seen as less stable, less successful and not as long-lasting as dyadic agreements (Oxley, 1997; Park & Russo, 1996).
Hypothesis 3: Two-partner strategic alliance is the most stable for both Chinese and American firms is two.
(2) Average Number of Partner (per Firm)
According to resource-based theory, firms earn returns because they possess sustainable competitive advantages (Amit & Shoemaker, 1993) that come from tangible and intangible resources (Beamish, 2004). Resource-based theory predicts that firms earn greater returns when they have more partners of alliance. First, they benefit from the environmental scanning mechanisms and managerial expertise of all partners, thus allowing them to identify and neutralize a greater number of potential opportunities and threats. Second, having more partners expresses more heterogeneous resources as partners draw from distinctly different resource pools, thus increasing the potential for synergy from integration, and this heterogeneity or diversity is increased when partners come from different countries. In other words, resource heterogeneity refers to different, complementary capabilities that help the organization create value (Roller & Sinclair-Desgagne, 1996).
Recall our earlier argument in which Chinese firms lack or need more capital and technology (resources and capabilities), and they can obtain the resources and capabilities that they lack from their partners, thus enhancing their own competencies and their competitive advantages through numerous alliances. Thus, if a Chinese firm’s main motivation for forming a cross-national alliance is to receive more resources or to get more capital and learn more advanced technology, they are likely to engage more gradually in cross-national alliance. The converse holds for American firms, since they already have comparatively more resources and capabilities, and their dominant motivation for cross-national alliances is to extend the scope of current operations, achieving scale economies, reducing entry costs, labor costs and risks in foreign markets. For this reason, we consider that American firms need less cross-national alliance than do Chinese firms.
Hypothesis 4: Chinese firms have more simultaneous cross-national partners than American firms.
(3) Density of Alliance Network
The interconnectedness of nodes in a network — the ratio of existing ties between team members relative to the maximum possible number of such ties — is the density of the network’s structure. Density is perhaps the most common way to index network structure; it reflects the level of interrelatedness, or reticulation, among all possible social ties (Balkundi, 2006). Density describes the linkages among the points in a graph. The more points that are connected, the denser the graph is (Scott, 2000).
As the last hypothesis suggests, Chinese firms have more cross-national partners, so they should have denser networks. The main reason is that the external networks can be looked upon as strategic resources influencing the firm’s future capability and expected performance. The resources and capabilities owned by the Chinese firms depend upon network density, the commonality of knowledge between firms, and the learning capability of firms. Industries with greater network density have a higher learning effect.
Hypothesis 5: In the pharmaceutical industry, the density of alliance networks made by Chinese firms is higher than of that made by American firms.
4. Alliance Network Types
Gomes-Casseres (1988) identified three types of alliance: supply based, learning-based, and market-based. Supply-based alliances are organized along the supply line and involve resource transfer beyond simple exchange relationship (finance, design, management skills and technology may flow between the partners). Its main objective is to reduce transaction costs and enhance the possibility for innovation. Learning-based alliances enable both creation and transfer of tacit knowledge across organizational boundaries. Market-based alliances are motivated by a need to reduce competition (Nielsen, 2003). There are two types of alliance networks: technical and business. The former are characterized by alliance with technology transfer, including R&D alliance, licensing, manufacturing outsourcing and the like; the latter have no technology transfer, including funding, supply, or marketing agreement.
Firms in a developing country need current technology to compete in global markets (Svetlicic and Rojec 1994). These firms often lack the knowledge and capabilities to develop or employ sophisticated manufacturing or product technologies (Luo 1999); thus, they seek alliance partners with technological capabilities (Hitt, 2004; Zahra et al. 2000). Gaining access to technology is important to Chinese firms because it takes a long time to internally develop the know-how to create new technology and use it independently. Conversely, in order to extend the scope of current operations, achieve scale economies, reduce entry costs, labor costs and risks in developing markets, American firms frequently license their technology to other firms in a developing country or make an outsourcing agreement with them to reduce costs. In other words, both Chinese and American firms make more technical alliances and shape technical alliance networks than form business alliance networks based on business alliance.
Hypothesis 6a: In terms of cross-national alliance, both Chinese and American firms are more likely to make technical alliances.
Hypothesis 6b: In a dynamic perspective, over the past 20 years, both Chinese and American firms continue make more proportion on technical alliances.
DATA AND METHODOLOGY
1. Data collection
In this article, we focus on the strategic alliances of pharmaceutical firms (SIC code including 2833, 2834, 2835 and 2836) from China and United States from 1989 to 2008. Our data comes from the SDC database. SDC database collects information about global merger and acquisition, venture capital, corporate restructuring, corporate governance, new issue, security trading and global finance. It is one of the most accurate and comprehensive databases available on strategic alliances.
Through the SDC database, we obtained the following information, which is available for strategic alliance: (1) announced alliance date; (2) participants in alliance; (3) participant alliance; (4) alliance type. To identify the economic level of each participant nations, we examined the divisions of the world’s economies based roughly on classifications used by the United Nations and The Economist. Developed countries, such as United States, Germany and Japan, have mature economies with substantial per capita GDPs and international trade and investments. The developing countries, including transition economies and emerging markets, such as China and India, have economies that have grown extensively over the past two decades. A total of 2,312 alliances over 20-years period (276 Chinese firms and 2,036 American firms) have been identified in this research.