INTRODUCTION

Do strategic alliances explain competitive performance differentials? Departing from this much-debated question, the research reported here aims to introduce and test some important variables that are involved in this relationship, with diversified roles. This research will assemble a nomological network that unfolds some relationships that are encapsulated in the simple, direct link between an alliance-related construct and a performance measure.

THE ROLE OF DYNAMIC CAPABILITIES

The dynamic capabilities view (DCV) was chosen as the theoretical perspective due to its promising explanatory ability.^{1, 2 and 3} The dynamic capabilities (DCs) focus is the analysis of the fit between the organisation's changing external environment and the dynamics of their portfolio of resources and capabilities.^{1, 4} Alliances are believed to be a means for such reconfiguration, and alliancing will next be characterised as a DC, as was originally proposed.²

ALLIANCE MANAGEMENT CAPABILITY AS A DC

DCs refer to the integration of functional capabilities and resources, through a knowledge-rich process.¹ Alliance management capability^{5, 6 and 7} was defined as a process that involves coordinating resources (including experience and knowledge) and organisational routines in order to: develop an alliance portfolio, particularly to anticipate problems and explore new opportunities; to exploit each alliance fully; and to mobilise resources and seek synergies in the current portfolio. Hence, alliance management is a DC, because it is of a higher order, aimed at integrating resources and functional capabilities in order to adapt firms to external dynamics. Examples of the results of this capability are: identification of new partners; increased knowledge of markets; support for product introduction; analysing new markets.

STRATEGIC ALLIANCES AND COMPETITIVE PERFORMANCE

The impact of strategic alliances is still an important subject of debate. The departure point for this investigation was the claim that there is a direct link between making alliances and having a superior performance.^{8, 9, 10 and 11} This research attempts to enhance this perspective by proposing a more complex and innovative view of this relationship between strategic alliances and competitive performance.

A CONCEPTUAL AND EMPIRICAL AGENDA

As mentioned earlier, the present research aims to explain the relationship between alliances and competitive performance by proposing a novel role for the alliance management capability. The main research questions are: (a) How can the relationship between alliances and performance be further explained? and (b) What is the role of the alliance management capability in this explanation?

The anticipated answers to these questions are: (a) competitive performance depends on strategic alliances and (b) the size of the impact of alliances depends on the role of knowledge-rich capabilities that are associated with alliancing,^{12, 13 and 14} and this role is, by hypotheses, not a causal one, but that of a moderator.

DEVELOPMENT OF A RESEARCH MODEL

The ability to integrate resources in an innovative manner may be a key source of value to firms.¹⁵ In order to innovate, firms need to offer new products or to raise new business processes, by integrating resources and capabilities that are either new to the firm or previously existent.¹⁶ The firms' external network can be a vehicle for the identification (or transmission, or acquisition) of these resources.¹⁷ Next, the first research hypothesis proposes a relationship between the portfolio of alliances — as a proxy for the degree of abundance of external resources — and performance outcomes:^{8, 10, 11}

H₁:

The firms' performance measures are, causally and positively, related to the structural dimension of the firms' portfolio of alliances.

Hunt and Morgan presented an integrated model¹⁸ between competing explanations for competitive performance. Accordingly, value-generating processes, and ultimately performance outcomes, depend on innovation — adding value to the customers and adapting to evolving markets. In our research, the degree of innovation is proxied by the degree of the reconfiguration of the portfolio of products. It is hoped that there has been a reconfiguration of the firms' portfolio of products, reflecting a significant evolution of their base of resources and capabilities. It is also hoped that DCs have had a significant role in preparing this competitive counter-move to these contingencies.¹

With regard to the pharmaceutical industry, it is expected that either generic drugs or innovative drugs have been important for the reconfiguration of the firms' basis of resources and capabilities. Thus, the results of such a reconfiguration in its portfolio — the degree of incorporation of either generic brands or innovative brands — can explain performance differences.

H₂:

The ability to carry out an effective reconfiguration of the portfolio of products adds to performance outcomes.

The third hypothesis draws from the idea that the dynamics of managing relationships with other firms and of managing portfolios of products are, to some extent, connected. In other words, that innovation is a desired outcome of a significant number of alliances forged in the pharmaceutical industry.¹⁹

H₃:

The alliances prevailing during a certain time period explain, to some degree, the reconfiguration of the product portfolios that have occurred during the same period.

Competitive performance is a complex concept and it is probably the result of a continuum of choices by firms interacting²⁰ in order to produce a set of market positions (both in the productive factors market and the products markets). Some of the outcomes that researchers usually measure are intermediate financial perspectives of performance.^{18, 20, 21} Hence, the following hypothesis regarding the relationship between performance indicators is proposed:

H₄:

Financial performance is explained by the firms' relative positions in the products market, which is a positive causal link.

The alliance management capability can be derived from accumulated experience with alliances, from managers having the appropriate type of expertise²² or the firm having a strategic vision that reinforces the role of alliances as a means to create wealth and business opportunities. These elements can combine together to forge that higher-order capability.⁷

Following the definition of DCs, these are neither a necessary nor an adequate condition for improved performance; however, they can play a positive and significant role when acting as moderators of that claimed relationship between alliances and competitive performance.

H₅:

The positive effects of an alliance portfolio on performance measures are moderated by the firm's alliance management capability.

Figure 1 portrays the relationships proposed by hypotheses from H₁ to H₅.

Figure 1.

The proposed role for alliance management capability

Full figure and legend (13K)

RESEARCH METHODOLOGY

Analytical technique

This purpose of this research is to test a theory. A quantitative approach was planned for the empirical testing, based on a survey aimed at a specific industry (the Portuguese pharmaceutical industry), in order to provide a control for contextual forces and secondary sources.

The model that derives from these hypotheses is clearly structural, where the constructs are related to their generative mechanisms. Partial least squares (PLS) should be able to analyse empirical problems:^{23, 24 and 25} with small samples; or non-normal distributions of data; or whenever there is a significantly complex model; or when there are formative constructs. Therefore, PLS is a suitable technique for performing a structural equation analysis with the proposed model and the expected type of data.

Data collection

With the contribution of Infarmed (the national authority for regulatory issues with regard to pharmaceuticals), 140 firms were identified as forming this industry. A survey was sent to all of these and 45 firms (32 per cent) returned valid, fully completed questionnaires. These firms, however, accounted for 78 per cent of the 2004 sales in the Portuguese drug market. Furthermore, this sample represented 58 per cent of all products and 86 per cent of all hospital sales. Thus, in spite of the apparently modest 32 per cent response rate, the sample covered a large share of the drug market.

Measures

Table 1 summarises the measures that will implement the theoretical constructs.

Table 1 - Measures.

Full table

THE RESEARCH FINDINGS

The evaluation of the PLS estimations procedure encompasses two steps: the analysis of the measurement model and the evaluation of the structural model.

Analysis of measurement model

All individual measures are individually reliable (their loadings over the latent constructs are all above the 0.70 threshold²⁴).

All the latent constructs are reliable according to the measure of composite reliability.²⁶ Again, it was expected to find scores superior to 0.70. In addition, in order to evaluate convergent validity, all constructs should signal at least 0.50 in the AVE (average variance extracted) measure, and the least recorded value is 0.840. Finally, all the constructs provide an adequate discriminant validity: the square roots of the AVE of each construct superceded the values of the cross-correlations among these constructs. Formative constructs, of either the first or second order, were evaluated according to their individual statistical significance and their ability to predict the endogenous variables of the model.

Since all measures are valid and reliable, they can be used and interpreted within the context of the present research objectives. More detailed results are available from the corresponding author, upon request.

Analysis of the structural model

This section refers to the relationships between constructs that are postulated by hypotheses H₁–H₅. Table 2 allows us to analyse the proposed model and, in particular, the proposed role for alliance management capability.

Table 2 - Results of the structural model estimation.

Full table

All the research hypotheses were validated, except one: the relationship between alliances and profitability. Only once was it necessary to apply the lower level of confidence (90 per cent), and the most frequent confidence level is 99 per cent.

With reference to the role of the alliance management capability, 'the moderator hypothesis is supported if the interaction is significant'.²⁷ This condition is verified for the relationship between alliances and growth (p-value<0,01) and market share (p-value<0,025). Therefore, the symbol 'n/a' next to the path linking the DC to the outcomes signifies that it is not theoretically meaningful (according to the proposed definition of DCs), or statistically relevant for testing this moderation hypothesis.^{27, 28} To sum up, the moderation hypothesis is proven to be true according to the statistical t-test.

It can be concluded that, although alliances have a positive effect in growth and a positive association with market share, these relationships improve significantly when there is a high level of alliance management capability. Hence, as predicted before, DCs — defined here as alliance management capability — further enhance the positive effects that alliances have on firms.

Discussion

The estimation of the model that is portrayed in Figure 1 confirmed that the reconfiguration of the resource base (or innovation, proxied here by the portfolio of products) is capable of explaining two of the outcomes dimensions identified by Hunt and Morgan¹⁸: position in markets (represented here by market share and sales growth) and financial performance (profitability).

The reconfiguration of the portfolio of products distinguishes between two important categories of products: innovative drugs and generic drugs. These two categories account for about 80 per cent of the Portuguese drug market. Each of these categories explains different performance outcomes: generic drugs are able to explain growth and profitability, while a successful reconfiguration based on innovative drugs relates to larger firms (or leads to higher market shares). Moreover, alliances (the index that represents the alliancing activity of firms) explain the reconfiguration of product portfolios, if they are based on innovative drugs. In fact, alliances are not of importance for introducing generic drugs. Finally, the role of the alliance management capability is proven to be true, within the context of the present analysis.

This research succeeded at finding significant relationships that confirm the theoretical template under which a certain causality chain explains the impact of alliancing on performance measures. As expected, the firms' bases of resources and capabilities have been adapting to external contingencies, revealing that firms are trying to select relevant information from the market and are integrating this into their operations and strategic positioning.²⁹ In fact, during the period studied in this paper, the Portuguese pharmaceutical industry was under major pressure from the Government for containment. Specifically, there has been a great promotion on behalf of generic drugs. Hence, the relevance of this component of the firms' portfolios of products for explaining performance is understandable. In spite of these efforts, the overall market grew at an annual rate of 8 per cent.³⁰ Therefore, growth — either due to generic drugs or others — was expected.

The way in which firms adapt their bases of resources and capabilities should also reveal a certain persistency, or path dependence.^{1, 31} In this case, the implication is that firms with a tradition (i.e. a specific set of resources and capabilities) of aiming for innovative drugs were not expected to abandon this segment and focus on competing in the generic (substitution) market segments. Thus, both types of portfolio reconfiguration should be relevant for competition.

It was shown that there is a hidden value in alliancing. In fact, evaluating alliances only on the basis of their direct impact on the performance indicators can underestimate their benefits. Alliances support portfolio reconfiguration and are associated with important capabilities that leverage the process of change inside firms. Thus, alliances are generators of externalities (learning, building reputation, etc) that managers should evaluate together with the most immediate impact. To sum up, it was shown that alliances are a meaningful way to bring forward new and innovative drugs.

CONCLUSION AND RECOMMENDATIONS FOR FURTHER RESEARCH

The main research question stated that some generating mechanisms should exist that contribute to explaining the relationship between alliances and competitive performance. It has been shown that a simple relationship between alliances and performance measures can underestimate the benefits of alliances over their outcomes. In fact, the model that was tested offered some new insights into the mechanisms or intermediate results that can lead to such outcomes.

The second research question considered the role of the alliance management capability. This role was that of a moderator of certain relationships, that is whenever they are present, they can supplement a relationship that otherwise would still exist even though probably weaker. This role was proven to be true, at least in the context of the present analysis.

Firms can benefit from this research from several perspectives. First, it was demonstrated that alliances are associated with higher levels of performance. Secondly, this research focused on investigating the reason 'why' this association exists. Indeed, it was shown that under specific circumstances, the effect that alliances have on performance could be stronger.

In order to help firms in their economic reasoning (forecasting, assessing risks, etc), it is important to clearly identify the dimensions of performance on which alliances can have a significant impact. In this research, alliances have an influence on the positioning of firms as far as the introduction of innovative products is concerned, as firms depend on alliances (either marketing alliances or R&D alliances) to effectively launch new and innovative drugs.

The experience and learning that derives from accumulating knowledge about alliances is one of the components of the 'alliance management capability', together with two other, and equally relevant, variables: the managers' individual skills at managing alliances and the proactivity in the procurement and analysis of new alliancing opportunities. These processes can be deliberately managed and therefore, this section underscores the importance of these constructs to firms. Capabilities build from crystallisation and thorough evaluation of experiences and these efforts put firms on the path of building capabilities and influencing their outcomes.

Future research may address the issue of 'how'³² new combinations of resources are brought forward, in particular, investigating the actual tools and mechanisms involved in alliance management.

In conclusion, this research succeeded in offering three main contributions. First, it presented an innovative view on the issue of how alliances relate to performance, emphasising the role of a DC and explaining how managers can develop and map this capability. Secondly, it performed an empirical application of certain constructs, thus contributing to its crystallisation and to its nomological validation. Thirdly, the research underlined the explanatory ability of the DCV.

References

1. Teece, D., Pisano, G. & Schuen, A. (1997). Dynamic capabilities and strategic management. Strat. Manage. J. 18, 509–533. | Article |
2. Eisenhardt, K. & Martin, J. (2000). Dynamic capabilities: what are they? Strat. Manage. J. 21, 1105–1121. | Article |
3. Winter, S. (2003). Understanding dynamic capabilities. Strat. Manage. J. 24, 991–995. | Article |
4. Porter, M. (1991). Towards a dynamic theory of strategy. Strat. Manage. J. 12, 95–118. | Article |
5. Dyer, J. & Singh, H. (1998). The relational view: cooperative strategy and sources of interorganizational competitive advantage. Acad. Manage. Rev. 23, 660–680. | Article |
6. Draulans, J., de Man, A. & Volberda, H. (2003). Building alliance capability: management techniques for superior alliance performance. Long Range Plann. 36, 151–166. | Article |
7. Lambe, C., Spekman, R. & Hunt, S. (2002). Alliance competence, resources and alliance success: conceptualization, measurement and initial test. Acad. Market. Sci. 30, 141–158. | Article |
8. Tsai, W. & Ghoshal, S. (1998). Social capital and value creation: the role of intrafirm networks. Acad. Manage. J. 41, 464–473. | Article |
9. Ahuja, G. (2000). The duality of collaboration: inducements and opportunities in the formation of inter-firm linkages. Strat. Manage. J. 21, 317–343. | Article |
10. Bae, J. & Gargiulo, M. (2001). Network evolution and efficient alliance strategies. Working Paper, INSEAD, Fountainbleu, France.
11. Sarkar, M., Echambadi, R., Cavusgil, S. & Aulakh, P. (2001). The influence of complementarity, compatibility, and relationship capital on alliance performance. Acad. Market. Sci. J. 29, 358–374. | Article |
12. Cockburn, I. & Henderson, R. (1998). Absorptive capacity, coauthoring behavior, and the organization of research in drug discovery. J. Ind. Econ. 46, 157–183.
13. George, G., Zahra, S., Wheatley, K. & Khan, R. (2001). The effects of alliance portfolio characteristics and absorptive capacity on performance: a study of biotechnology firms. J. High Technol. Manage. Res. 12, 205–226. | Article |
14. Duysters, G. & Heimeriks, K. (2002). The influence of alliance capabilities on alliance performance: an empirical investigation. Working Paper, 02.08, Eindhoven Center for Innovation Studies, Technical University of Eindhoven , Eindhoven, Netherlands.
15. Hoskisson, R., Hitt, M., Wan, W. & Yiu, D. (1999). Theory and research in strategic management: swings of a pendulum. J. Manage. 25, 417–456. | Article |
16. Kogut, B. & Zander, U. (1992). Knowledge of the firm, combinative capabilities and the replication of technology. Org. Sci. 3, 383–397.
17. Grant, R. (1996). Toward a knowledge-based theory of the firm. Strat. Manage. J. 17, 109–122. | Article |
18. Hunt, S. & Morgan, R. (1997). Resource-advantage theory: a snake swallowing its tail or a general theory of competition? J. Market. 61, 74–82. | Article |
19. Simonet (2002). Licensing agreements in the pharmaceutical industry. Int. J. Med. Market. 2, 329–341.
20. Hunt, S. (2002). RAT and Austrian Economics: Toward and Austrian Theory of Competition?, Austrian Scholars Conference, Austria, Ludwig Von Mises Institute.
21. Ray, G., Barney, J. & Muhanna, W. (2002). Capabilities, business processes, and competitive advantage: choosing the dependent variable in empirical tests of the resource based view. Strat. Manage. J. 25, 23–37. | Article |
22. McGee, J., Dowling, M. & Megginson, W. (1995). Cooperative strategy and new venture performance: the role of business strategy and management experience. Strat. Manage. J. 16, 565–580. | Article |
23. Chin, W. (1998). Issues and opinion on SEM. MIS Quart. 22, 7–16.
24. Gefen, D., Straub, D. & Boudreau, M. -C. (2000). Structural equation modelling and regression: guidelines for research practice. Commun. Assoc. Inform. Syst. 4, 1–70.
25. Haenlein, M. & Kaplan, A. (2004). A beginner's guide to partial least squares (PLS) analysis. Understand. Stat. 3, 283–297. | Article |
26. Werts, C., Linn, R. & Jöreskog, K. (1974). Interclass reliability estimates: testing structural assumptions. Educ. Psychol. Measure. 34, 25–33. | Article |
27. Baron, R. & Kenny, D. (1986). The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J. Personal. Social Psychol. 51, 1173–1182. | Article |
28. Chin, W. & Newststed, P. (1999). SEM analysis with small samples using PLS in Hoyle, R. (ed.), Statistical Strategies for Small Sample Research, Sage Publications, Thousand Oaks, CA, pp. 307–341.
29. Stoenhorst, J. & Raaij, E. (2004). On explaining performance differentials — marketing and the managerial theory of the firm. J. Bus. Res. 57, 462–477. | Article |
30. Apifarma (2005). A indústria farmacêutica em números, Apifarma, Lisbon, Portugal.
31. Zollo, M. & Winter, S. (2000). Deliberate learning and the evolution of dynamic capabilities. Org. Sci. 13, 339–351. | Article |
32. Foss, N. & Ishikawa, I. (2006). Towards a dynamic RBV: insights from Austrian capital and entrepreneurship theory. Working Paper, available at http://www.nicolaifoss.com. Accessed on the 15th December 2006.