Strategic Alliances: Do They Affect New Venture Performance and Growth By Joette M. Wisnieski 304 Eberly College of Business Indiana, PA 15701

ABSTRACT

Initial Public Offerings (IPOs) of 189 firms issued between the years 1986 and 1994 were studied to determine the use of strategic alliances by high-technology new ventures. Content analysis was performed on the IPOs for several variables including new venture business strategy, new venture motivation for the alliance and the governance structure of the alliance. Accounting data was also coded. This database was then updated in 1999 to provide longitudinal performance figures. A multiple regression analysis was conducted with several performance variables. Discriminant analysis was also performed to determine if alliance motives and structures had any impact on survival rates. INTRODUCTION Strategic alliances have received much attention in both academic research and the popular press (Gulati, 1998). Firms have traditionally chosen to expand either through diversification or internal growth. Both of these methods use considerable resources--resources that new ventures do not traditionally have. Strategic alliances offer an additional avenue of growth to new ventures (Powell, 1990; Hennart, 1993, Gulati, 1998). For purposes of this paper, we will use the term "strategic alliance" to refer to any long-term, formal linkage between organizations that offers actual or potential strategic advantage to both (Jarillo, 1988; Olleros & Macdonald, 1988). These linkages may include minority investments, joint ventures, long-term contracts involving supply, manufacturing, marketing, and technology exchange agreements. Due to the proliferation of these alliances, management researchers from many disciplines have begun to closely investigate them. Besides the anecdotal information abounding in the news, studies show that both small and large firms use strategic alliances (Harrigan, 1988; Dollinger & Golden, 1992), and that the use of these cooperative arrangements is growing (McGee, Dowling, & Megginson, 1995; Wisnieski & Dowling, 1997). Much of the research to date has focusd on short-term performance. This paper will address this gap by focusing on long-term performance implications. Importance to New Ventures

Strategic linkages with wholesalers and suppliers offer new ventures an important competitive strategy to the small entrepreneurial firm. Benefits include better exchange of product/market information, greater availability of marketing and management expertise, more competitive pricing, access to new channels and markets, shorter lead times for product development, and financial resources (Gales and Blackburn, 1990; Larson, 1991). Research has shown that strategic alliances are particularly prevalent in technologically intensive firms. These alliances often occur between small high tech new ventures and large companies (Olleros & Macdonald, 1988). Considering the important role that technology-based new ventures play in the development and commercialization of new products, processes and technologies, and of new industries (Kazanjian, 1988), this adds yet another reason to study strategic alliances in this type of firm. Most importantly, research has shown that strategic alliances do impact performance (McGee et. al., 1995; Mosakowski, 1991; Wisnieski & Dowling, 1997). Mosakowski (1991) found that firms contracting for R & D and service had lower performance than those that did not. She also found that this relationship was moderated by the firm’s strategy. In a subsequent study by McGee, Dowling, and Megginson (1995), they found that strategic alliances had a positive impact on firm performance when the alliance was chosen in a functional area that the firm’s management team had prior experience. They also found that a firm’s strategy was an important variable in the effectiveness of a strategic alliance. Wisnieski and Dowling ( 1997) found that it was the interaction between the firm’s reason for entering into an alliance (motive) and how the new venture chose to structure the alliance that had an impact on short-term performance. This paper will build on these studies by looking at long-term performance implications of using strategic alliances. Considering the importance new ventures have on our economy and the dismal survival rate of most new ventures, determining whether using strategic alliances have long-term implications is an important research question. THEORETICAL DEVELOPMENT Resource dependency theory, transaction cost theory, and strategic choice theory offer complementary, and in some ways competing explanations for why new ventures would choose to form strategic alliances and how best to organize them Resource dependency theory There are many reasons suggested for why new venture’s choose to form alliances. Resource dependency theory (Pfeffer & Salancik, 1978) suggests that no organization can survive alone. It must constantly interact with its environment either to purchase resources such as labor, supplies, or equipment, or to distribute its finished products. Organizations seek to gain control over their environment through alliances. These alliances can insulate an organization from its external environment and lessen the effects of environmental uncertainty (Pfeffer & Salancik, 1978; Galaskiewicz, 1985; Miner & Stearns, 1990) and guarantee more stable flows of resources in times of scarcity (Stearns, Hoffman & Heide, 1987; Miner & Stearns., 1990).

The resource dependency literature suggests that these alliances often represent one of three forms. The first alliance is a horizontal alliance between organizations that compete for the same resources, such as customers or suppliers (MacMillan & Jones, 1978; Astley & Fombrun, 1983; Oliver, 1990) and usually represent exchanges in one direction. In horizontal alliances, the organizations exchange or pool their resources toward some overarching goal, such as research consortia or trade unions. The second is a vertical alliance--an alliance between a firm and those organizations supplying inputs or using its outputs, such as suppliers, buyers, financial institutions, or the labor pool. Vertical alliances also usually represent exchanges in one direction. The third type of alliance is reciprocal, where firms exchange both inputs and outputs (Borys & Jemison, 1989; Oliver, 1990) and the exchanges flow in both directions. In reciprocal alliances, firms exchange ideas, people and equipment, share lab space and pass designs back and forth such as in joint R&D projects. As the alliance moves from a single exchange flow (horizontal or vertical) to a reciprocal alliance with multiple exchanges, the interdependence between the organizations increases as does the need for close interaction and stability in the relationship. Given a less interdependent alliance, contractual forms of governance structure offer sufficient interaction. But as interdependence increases, so does the need for interaction, leading to governance structures with more institutional control, such as acquisitions or joint ventures (Borys & Jemison, 1989).

Transaction Cost Theory Transaction cost theory (Williamson, 1981) rests on the assumption that markets are most efficient for transactions. The unit of analysis is the transaction and the idea of minimizing transaction costs is central to this approach. Williamson (1981) defines transactions as the goods or services being transferred across some boundary. Some of these transfers occur smoothly and need no attention. Williamson (1981) suggests that these types of transfers are like the gears in a well oiled machine. Other transactions do not go as smoothly, and, in these cases, the transaction cost represents the friction in the transfer process. These costs include the planning, monitoring and adapting of these transfers under the various governance structure choices available (Mosakowski, 1991). When transaction costs exceed the benefits of non-ownership, Williamson (1991) suggests that firms will internalize the transaction through ownership. The three environmental factors transaction cost specifically deals with are technological uncertainty, asset specificity and small numbers bargaining. In highly uncertain technical environments, the fear of opportunistic behavior by alliance partners can cause a lack of trust (Jarillo, 1988; Pisano, 1990; Folta, 1998). Firms are likely to be particularly concerned about the control of proprietary knowledge, products and services (Osborn & Baughn, 1990). Asset specificity arises when a transaction requires an investment that has value only in this transaction. There are three types of asset specificity: site specificity occurs when partners’ assets are located near each other to economize on inventory and transportation expenses; physical assets such as specialized

dies needed to manufacture a component; and human assets such as specialized knowledge gained through previous experience in a learning by doing situation not easily duplicated (Jones & Pustay, 1988; Williamson, 1987). Small numbers bargaining situations arise when there are few alternate suppliers. But with few suppliers and consumers who are not perfectly informed, this creates an incentive for one partner to behave in an opportunistic manner (Hennart, 1993; Pisano, 1990). The presence of these factors may lead to firms needing more control over these transactions and provide an incentive for firms to look for alternate arrangements such as long-term contracts, quasihierarchies or vertical integration to internalize the transaction and eliminate altogether the bargaining problems (Hennart, 1988; Osborn & Baughn, 1990; Pisano, 1990; Williamson, 1987). Strategic Choice Theory While transaction cost theory suggests cost-minimization as a major motivation for firms entering into strategic alliances, strategic choice theory views alliances as complementary to the new venture’s core competence. Alliances can allow firms to capitalize on their functional expertise and contract for other needed functions. The choice of a governance structure is influenced by the strategic importance of the business strategy often represented by functional expertise and expenditures (Fagre & Wells, 1982; Kogut, 1988; Porter, 1980). When the alliance does not impact a firm’s major functional area or major product line, firms will want the flexibility of non-equity contractual arrangements. When contemplating alliances involving the firm’s functional expertise, firms will have a higher need for specifying performance and control. This would suggest that the closer the alliance is to the strategy of the new venture, the more likely that the new venture would choose an equity structure. These three different theories offer competing theories as to why new ventures might enter alliances and suggested very different organizational structures for these alliances. These theories also suugest that firm performance will be improved through the use of alliances. Performance Implications of Strategic Alliances Empirical support has been provided that alliances do help buffer organizations from their dependence on the environment and thus prevent organizational failure (Miner et al, 1990). In the Miner and Stearns study (1990), a population of more than 1000 Finnish newspapers was studied using event-history analysis. They looked at whether resource buffering aided a firm’s survival. They found that newspapers with alliances enjoyed a lower failure rate than all other types of newspapers and were protected from failure in periods of exogenous shock as well. Their findings have important implications for researchers studying new ventures as high failure rates are a particular problem. H1: Do strategic alliances help new ventures survive? Another study that looked at the impact of resource scarcity on alliance formation and firm performance found that alliances positively affected performance. In a study of

commercial television stations, Steams, Hoffman and Heide (1987) suggested organizations choose to form alliances when the environment is uncertain or complex, or resources are scarce. This would be consistent with both resource dependency theory and transaction cost theory, but performance was not affected by strategic alliances. Alliances did enhance performance under conditions of market scarcity and complexity. These particular studies did not look at how these alliances were structured to see if there were performance affects associated with these different organizational structures. On the other hand, Mosakowski (1991) found that in new ventures, where R&D was a critical part of their strategy, a new venture’s performance was lower when it contracted for R&D, but higher when it contracted for sales. She had similar findings for new ventures emphasizing marketing differentiation. New ventures with a customized service strategy had lower performance with sales and service contracts than do new ventures that did not have this strategy. Her findings provide support for the strategic choice model which suggests that activities that are related to the new venture’s strategy should be handled through equity structures while alliances for other functions should be contracted. McGee, Dowling and Megginson (1994) have also found support for strategic choice theory by finding a relationship between business strategy and use of alliances. They found that new ventures following a marketing differentiation strategy and using a marketing cooperative arrangement were positively associated with sales growth. Wisnieski and Dowling (1977) also looked at these questions. Their findings indicated that marketing alliances associated with a low cost strategy was significant and positive as predicted by strategic choice theory. Also, the interaction effect for new venture’s with a marketing alliance and marketing strategy and was significant and negative. New ventures using a marketing alliance and following a technical differentiation strategy was also significant and negative. This suggests that more research on the impact of both motives and governance structures needs to be continued. H2: Does the use of strategic alliances impact long-term firm performance? METHODOLOGY The sample for this research consisted of high-technology new ventures issuing an Initial Public Offering (IPO) from 1986-1994. The firm must have been an independent startup less than 10 years old and listed as being in one of the hightechnology industries included in this study. National Science Foundation defines “high” technology industries based on direct and indirect R&D product expenditures as a percentage of net sales of that particular product (National Science Board, 1988). Specifically, these two digit SIC categories were fabricated metals (34), machinery including computer and computer related equipment (35), electronic equipment (36), professional and scientific instruments (38), specifically those companies dealing with computer programming, data processing and other computer related services (73) were the high-technology industries chosen for this study. These industries were selected due to their similarity to each other and, the fact that they were cited as high-technology industries in the National Science Board study. The database I created for this study contains 189 new ventures from five hightechnology industries. As expected, the firms in the database were small. At the time of

the IPO, the average venture reported annual revenues of $27 million, and 196 employees. Size was used as a control variable as theory suggests that the larger firms would have more resources and less need of alliances and therefore alliances would have less impact on performance. Several other characteristics of the sample are worth mentioning. The average year of incorporation was 1985. The average number of alliances was 1.73, which was a surprising result as we did not expect multiple alliances per company. Non-equity alliances were the most frequently found alliance structure. Data was collected from the IPO statements including Security and Exchange Commission (SEC) Form 5-1 which is the registration statement companies use under the securities act of 1933. The use of IPO registration statements as a source of data is considered relatively reliable due to reporting requirements, SEC scrutiny, and sanctions for falsifications (Marino, Castaldi, & Dollinger, 1989; Mosakowski, 1991; McGee et.al., 1995). Accounting data was recorded from financial statements and accompanying footnotes. Other data such as strategic alliance motivations, governance structures and business strategies required a content analysis of the SEC documents. The variables collected from the IPO statements included continuous measures of firm performance and control measures for size, age and industry. Categorical measures of business strategy, alliance motivation and governance structure were coded from the descriptive portions of the IPO documents.. Independent Variables The independent variables included dummy variables representing motives, alliance structure and strategy. Forty seven companies had no recognizable motive for a strategic alliance. Of those with alliance motives, the largest group fell in the resource dependency motive for vertical alliances. For purposes of this study, resource dependency motives for horizontal and vertical alliances were grouped together, as theory predicted these motives would produce alliances with the same structure. This combined group represented 136 of the alliance motives. The third resource dependency motive, which suggested that firms could have reciprocal alliances where resources are exchanged, represented 61 of the alliance motives found. Transaction cost motives represented 77 cases and strategic choice motives represented 73 of the cases. All of the above dummy variables were coded from the IPO statements. Very explicit statements concerning the alliance strategies and risk factors are part of IPOs. The principal coder was Joette Wisnieski. The second coder was an MBA student trained in strategy but not familiar with the hypotheses. Approximately 50 of the IPOs were recoded. In terms of the strategy, the interrater reliability for strategy was 92%; governance structure, 94%; and motivations, 78%. Follow-up data was collected from the internet through Edgar. A dummy variable was created for survival. Firms were considered to survive if they were an independent firm in 1998. Measures of performance Average growth in sales was adopted as the measure of performance since it has been suggested that sustained growth in revenues is often indicative of overall new

venture success (Feeser & Willard, 1990; McGee et.al., 1995). The following formula was used: Average Sales Growth = ((Sales3 / Sales1)1/3- 1)*100 where Sales3 was the annual sales of the firm at the time of the IPO and the annual sales 3 years prior to the IPO respectively. I also looked at the average sales, average assets, and average profits for these companies in 1996, 1997, and 1998. Control Variables Assets at the time of the initial IPO and Employee totals at that time were used to control for size. YRINC and IPO date were used to control for timing in entering the industry and age effects. Data Analysis Two different methodologies were used. Discriminant analysis was used to look at the impact of using strategic alliances on new venture survival rates. Regression was used to test the various motivations and alliance structures on new venture long term performance. In descriptive discriminant analysis, the grouping variable (structure) is viewed as the explanatory variable or independent variable, while the other variables are considered outcome variables or dependent variables. Outcome variables are the characteristics or traits of the units under study in addition to group membership. Outcome variables are what group members have in common or share. This study looks at the relationship between surviving new ventures and those that did not and to see if strategic alliances could explain these differences. This is represented by the following null hypothesis. H0: u1 =u2=u3 In this case, specifically, the researcher is interested in whether there are differences between the surviving firms and nonsurvivors on a number of variables including age, motive for the alliance, and the new venture’s choice of governance structure. The oldest and perhaps most widely used test criterion is the Wilks~ lambda criterion. Regression analysis was used to test the various relationships of governance structure and motivation on performance. This procedure was used to test the individual hypotheses since they suggest that the relationship between the independent variables of motivations and structure and the dependent variable new venture performance. The basic form of the regression equation was: Y=Bo+B1X+B2X2+B3X3+...+ BpXp where Y= Dependent variable (sales growth, asset growth, average sales over a 3 year period, average assets over 3 years, average profits over 3 years)

B0 = Intercept B1 = Number of alliances B2 = Age B3 = Employee Total B4 = Assets in year of IPO B5 = Year Incorporated B6 = Date of IPO Motive variables and structure variables were added depending on the hypothesis being tested. The actual test of the hypotheses relationships used either a t-test of an individual variable, Beta or a partial F-test if more than one variable was involved in the hypotheses. After the models were developed a battery of diagnostic techniques were administered to ensure that the data was appropriate for multiple regression techniques. Specifically, tests were performed to ensure that the model was linear, error terms had constant variance, error terms were independent and normally distributed, and the model fit all but a few outliers.

RESULTS Hypotheses 1 suggested that strategic alliances may improve new venture’s ability to survive. A chi-square test was performed to see if having an alliance impacted new venture’s survival. Of the 189 firms in the original sample, 93 survived. Of those surviving 59 had some type of strategic alliance but this was not a statistically significant result. Discriminant analysis was also use to test a variety of variables to see if they explained the difference between surviving and non-survivng new ventures. This analysis showed there were no significant difference between the new ventures that survived and those that did not based on either choosing to use an alliance or how that alliance was structured or the number of alliances the new venture had. Hypothesis 2 looked at the impact strategic alliances had on the long-term performance of survival. Here the results were much more positive. Using average sales for the years 1996, 1997, 1998 as the dependent variable, the results were statistically significant. The equation along with several variables including number of alliances, employee totals in the year of the IPO, and new ventures with the motives for its alliance as either horizontal or vertical arrangements were all found to be statistically significant. Table 1

Using asset growth in 1996, 1997, 1998 as the dependent variable found both the number of alliances and employee totals in the year of the IPO as statistically significant.

Table 2

Finally I also looked at Sales growth over the years 1996-1998. Again, these results were statistically significant. Table 3

Other dependent variables such as those associated with profit and asset growth were not significant.

Discussion This paper examined three different theories regarding motivations of strategic alliances and the type of governance structure firms should choose and what affect these alliances would have on long term performance. While alliances did not appear to impact new venture survival, the number of alliances did appear to impact new venture longterm performance. CONCLUSION These findings suggest that strategic alliances appear to be a viable strategy for new ventures to follow. Previous research has demonstrated their affect on short term performance and this research suggests that there may be some long term benefits to new ventures pursuing multiple alliances. In the future, a larger sample could be gathered that may allow the researcher to also look at the interaction of alliance structures and the various motives for forming an alliance on long-term performance. Additional research involving primary data could provide more detail regarding these alliances. In particular, information could be gathered on the partner of the alliance, previous alliance experience with this partner or other partners, and length of time the alliance was intended. Information gathered from the managers involved in negotiating the alliance would also prove invaluable information. Understanding when and under what conditions strategic alliances are of benefit to new ventures will continue to be an important issue for practitioners and academics alike. REFERENCES

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