Research Policy 36 (2007) 227–246
Regional economic integration and R&D investment夽 Alvaro Cuervo-Cazurra a,1 , C. Annique Un b,∗ a b
Sonoco International Business Department, Moore School of Business, University of South Carolina, 1705 College Street, Room 557, Columbia, SC 29208, USA Sonoco International Business Department, Moore School of Business, University of South Carolina, 1705 College Street, Room 555, Columbia, SC 29208, USA Received 16 June 2004; received in revised form 5 December 2005; accepted 13 November 2006 Available online 21 December 2006
Abstract We analyze the influence of a regional economic integration agreement (REIA) on a firm’s investments in research and development (R&D). A country’s entry into a REIA creates two competing influences on the firm’s R&D investments. On the one hand, increased competition in product markets after the REIA would induce the firm to invest in internal R&D to improve its distinctive technological competitiveness. On the other hand, better access to sources of inputs in factor markets after the REIA would induce the firm to purchase external R&D because it can outsource technology more easily. Surprisingly, the empirical analysis shows that the REIA’s impact on R&D investment is driven primarily by product markets rather than by factor markets. After the REIA, product markets induce firms not only to invest more in internal R&D but also purchase more external R&D. In contrast, after the REIA factor markets have limited influence on internal or external R&D investments. © 2006 Elsevier B.V. All rights reserved. JEL classification: L2; O3 Keywords: R&D; Regional economic integration; Product markets; Factor markets
1. Introduction 夽 The paper benefited from suggestions from the associate editor Stephan Thomke and three anonymous reviewers, comments from participants at the Strategy Seminar, Cornell University, Academy of Management annual meeting, Academy of International Business annual meeting and discussions on the topic of regional economic integration with Omar Toulan. We thank the Ministry of Industry and Energy of Spain and the Fundaci´on Empresa P´ublica for making the data available. The paper was developed while the first author was a Visiting Assistant Professor at the Department of Applied Economics and Management at Cornell University and the second author was an Assistant Professor at the Johnson School of Management at Cornell University. All errors remain ours. ∗ Corresponding author. Tel.: +1 803 777 0315; fax: +1 803 777 3609. E-mail addresses:
[email protected] (A. Cuervo-Cazurra), annique
[email protected] (C.A. Un). 1 Tel.: +1 803 777 0314; fax: +1 803 777 3609.
0048-7333/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.respol.2006.11.003
We analyze the influence of regional economic integration agreements (REIAs) on the firm’s investments in research and development (R&D). REIAs are intergovernmental treaties through which signatory countries agree to more advantageous conditions in the conduct of their mutual trade and investment relationships than those conditions applied to other, non-signatory, partners (adapted from World Trade Organization, 2003a, p. 26). They take different forms, from free trade areas such as NAFTA in North America, to custom unions like MERCOSUR in South America, to economic unions like the European Union, to name but a few. REIAs have been spreading throughout the world at an increasing pace. By the end of 2002, there were 176 in force, an additional
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70 in operation but not yet officially informed to the Organization, and another 70 under negotiation, among the 144 World Trade Organization (WTO) members (WTO, 2003b, p. 46). Only four years earlier, in 1998, there were just 69 agreements in force (WTO, 1998). Most countries belong to several agreements. By the end of 2002, only four WTO members, Hong Kong, Macao, Taiwan, and Mongolia, were outside a notified REIA. Despite the widespread existence of REIAs, there are no studies of their impact on the firm’s R&D investment decisions. A REIA induces the firm to improve its competitiveness. The REIA provides opportunities for the expansion of operations and better use of existing resources, since the firm has easier access to a larger market to sell its products. It also creates the opportunity to improve efficiency, since the firm enjoys better access to foreign suppliers. However, at the same time, the REIA also creates threats to the firm’s profitability and survival because of the increase in competition, which results from the reduction of barriers that previously protected domestic firms from foreign ones (Robson, 1998; Eden, 2002). The firm can invest in R&D to improve its technological capabilities and competitiveness (Helfat, 1997). However, it is not clear how the firm’s investment in R&D will be affected by the REIA. Previous analyses studied how a technological change in the industry renders the firm’s technological capabilities obsolete and induce the firm to develop new ones (e.g., Pisano, 1990; Nagarajan and Mitchell, 1998). These studies indicate that the more disruptive the technological change is, the higher the likelihood that the firm will use external methods rather than internal ones to develop the new technology. In contrast, a REIA alters not only the industry or product market but also the suppliers in the factor market. As a result, the firm faces competing influences on its investment in R&D. On the one hand, increased competition in product markets after the REIA would induce the firm to invest in internal R&D to improve its distinctive competitiveness. On the other hand, better access to sources of inputs in factor markets after the REIA would induce the firm to purchase external R&D because it can outsource technology more easily. We analyze these competing influences on a sample of industrial firms’ R&D investments before and after a REIA. Surprisingly, the empirical analysis shows that the REIA’s impact on the firm’s R&D investment is driven primarily by product markets rather than by factor markets. After the REIA, product markets induce firms not only to invest more in internal R&D but also purchase
more external R&D. In contrast, after the REIA factor markets have limited influence on internal or external R&D investments. The rest of the paper is organized as follows. In Section 2 we discuss the impact of REIAs on the firm’s investments in R&D and present two hypotheses. In Section 3 we describe the research design, and in Section 4 the results of the analysis. In Section 5 we provide our conclusions, the contribution and limitations of the current paper, and avenues for future research. 2. Regional economic integration agreements and R&D investment We argue that a REIA alters both the product and factor markets in which the firm operates and as a result, the impact of the product and factor markets on the firm’s R&D investment varies. We first provide the definition of R&D investments and of REIAs that we use in this paper and draw links with previous literature. We then discuss how the impact of product markets and of factor markets on R&D investments changes after the country enters a REIA and generate hypotheses. We use multiple theoretical approaches to provide a more complete understanding of the phenomenon, building on the complementary insights of different theories (e.g., Poppo and Zenger, 1998; Un and Cuervo-Cazurra, 2005). 2.1. Changes in the firm’s environment and R&D investment We analyze the firm’s investments in R&D as a way to develop technological capabilities. Technological capabilities are the ability to develop and exploit technological know-how, which is the application of scientific knowledge for commercial purposes (Pisano, 1990, p. 153). The firm can develop its technological capabilities using several learning approaches (Malerba, 1992, p. 848). We focus on investments in R&D because of its importance in generating new knowledge, which can help the firm achieve an advantage that is difficult to replicate by competitors (Helfat, 1994). The company can invest in R&D internally or externally. Internal R&D investments are expenditures on personnel and assets in the firm dedicated to the creation of new scientific or technological knowledge or to the development of commercially-viable innovations. External R&D investments are expenditures paid to other firms, to universities, or to other entities dedicated to scientific or technological research, to create new scientific or technological knowledge or to develop commercially-viable innovations for the firm. Thus,
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internal and external R&D investments in this paper are directly comparable concepts. Both of them are monetary expenditures. We do not include the acquisition of firms or alliances with other companies in these external R&D investments as done in other studies (e.g., Capron et al., 1998; Vanhaverbeke et al., 2002). The use of acquisitions of, and alliances with, other firms involves factors not exclusively related to R&D that distort the investment decision, such as the complementarity of product lines, or similarities in corporate culture. Existing literature on the impact of environmental changes on the firm’s R&D investment has discussed the impact of technological discontinuities. These studies indicate that radical changes in the technological environment induce the firm to make more intensive use of external providers of technology2 . For example, Pisano (1990) found that, after a technological shift, pharmaceutical firms are more likely to subcontract rather than use internal development of new technologies when there are many suppliers of the new technology and when the firm has little prior experience in the field. Another example is Nagarajan and Mitchell (1998), who found that companies in the lithotripsy industry use purchase, alliance, or internal development of technology depending on whether they face a complementary, encompassing or incremental technological change, respectively. The present paper complements the insights of these studies in two ways. First, we discuss the impact of the influences of changes in the product and in the factor markets on internal and external investments in R&D. This complements previous studies that have focused on the influence of technological or industry changes only. Second, we analyze monetary expenditures in both internal and external R&D rather than the decision to 2 This literature is an extension of the analysis of the decision to undertake R&D internally or subcontract it. This broader research stream can be traced back to traditional make-or-buy decision in economics (e.g., Williamson, 1985) and to studies of make-or-buy technology (e.g., Mowery, 1983; Teece, 1986). There is also an intermediate form of governance of R&D: collaboration with other firms or with universities and research centers (e.g., Fritsch and Lukas, 2001; Cassiman and Veugelers, 2002; Sakakibara, 2001). Moreover, the firm may not always choose one method or another to develop R&D, but instead use both internal and external methods because these methods are complementary (e.g., Cohen and Levinthal, 1989; Veugelers, 1997; Veugelers and Cassiman, 1999; Leiponen, 2005a). In this paper we will not study alliances to develop technology because we are assessing relative monetary expenditures, but we will touch upon the possibility of undertaking both internal and external R&D. The subset of literature to which we directly speak has the distinctive feature of highlighting the role of changes in the environment on the decision to undertake R&D internally or externally.
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invest in internal R&D or to purchase a technology. Thus, we are able to assess the relative weight put on each type of R&D. This is an important distinctive feature of this study given that firms often use both internal and external R&D because they are complementary (e.g., Cohen and Levinthal, 1989; Veugelers, 1997; Veugelers and Cassiman, 1999; see Leiponen, 2005a for a recent review of this literature). Hence, to be clear, the discussion in this paper is about the decision to invest relatively more or less in internal R&D than in external R&D, rather than the decision to invest in internal R&D or in external R&D. We measure this relative R&D investment as internal R&D to total R&D investment. 2.2. Regional economic integration agreements and R&D investment There are many different definitions and types of REIAs (Jovanovic, 1998, pp. 5–10)3 . Consistent across the definitions is the idea that REIAs involve the reduction and standardization of government controls and policies over the flows of products, factors, or both among a limited set of countries. Thus, REIAs differ from the multilateral liberalization of trade promoted in the WTO in several aspects, as they: are restricted to a limited set of countries, tend to be accompanied by the standardization of policies rather than simply the reduction of barriers to trade, and may involve the liberalization of not just trade but also the flow of factors of production. REIAs affect firm behavior, but previous studies have not explored the impact on the firm’s R&D investment. There is a large literature on the impact of REIAs on country-level trade and foreign direct investment flows (for a review, see Eden, 2002). The more limited literature on the impact of REIA on firms has traditionally
3 REIAs can be classified in different types depending on the degree of reduction in the controls over the flow of products and factors among the countries in question (Jovanovic, 1998, p. 10): (1) preferential tariff agreements (PTA) which consist of the partial reduction of internal tariffs to levels below those charged to trade with third countries; (2) free-trade areas (FTA), such as the North American Free Trade Area (NAFTA), which consist of a reduction in internal limitations to the movements of products among participating countries; (3) customs unions (CU), such as the Southern African Customs Union (SACU), which demarcate a free-trade area with a common external tariff against products of third countries; (4) common markets (CM), such as the Common Market of the South (MERCOSUR), which are customs unions with the free movement of factors of production among participating countries; and (5) economic unions (EU), such as the European Union, which are common markets also involving the harmonization of economic policies.
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focused on the changes in multinational enterprises (MNEs) (e.g., Kindleberger, 1956; Almor and Hirsch, 1995; Pearce and Papanastassiou, 1997; Buckley et al., 2001). These studies indicate that a REIA induces the MNE to alter the location of its investments and rationalize its operations. A few studies focus on domestic firms and recommend changing strategy in the face of the new environment (e.g., Buigues and Jacquemin, 1989; Smallbone, 1999). REIAs have a competing influence on R&D investments, one through product markets and another through factor markets. The REIA results in an expanded client base and new competitors. These changes will induce the firm to invest in internal R&D after the REIA to improve its distinctive competitiveness. At the same time, the REIA results in increased outsourcing opportunities and improved supplies in factor markets. We argue that these will induce the firm to invest in external R&D after REIA to benefit from the easier access to sources of technology. We now explore each of these arguments. 2.2.1. Impact of product markets on R&D investments after the REIA The product markets where the firm sells its products in competition with other firms pressure it to invest in internal R&D to improve its technological capabilities. The characteristics of product markets affect not only the firm’s competitive advantage within the country of origin, but also its international competitiveness (Porter, 1985, 1990). Thus, a firm operating in a demanding environment is induced to invest internally in R&D to develop its technological capabilities because internal development increases the difficulty of imitation by competitors (Cool et al., 2002). A REIA entails the reduction of barriers to trade and investment, and the standardization of policies across countries, creating incentives to sharpen the technological edge. After the REIA, the firm has easier access to foreign markets, enabling it to expand its activities and serve new clients more easily (Buckley et al., 2001). R&D investments can be used to generate better and new products that are sold in an expanded market. However, selling abroad also entails facing new competitors and serving new clients, both of which have different demands from local ones (Prahalad and Doz, 1987). These create new pressures, reinforcing the already-present pressures to develop new and distinctive technological capabilities. At the same time, the REIA generates an increase in competitive pressures within the domestic market. Foreign competitors can more easily enter the country and operate there. The barriers to trade and investment
that kept foreign competitors out, or that limited their operations in the domestic market, disappear or are significantly reduced after the REIA (Robson, 1998). At the same time, the domestic clients are now able to buy from new competitors, which may offer better or different products. Thus, the firm faces higher pressures in its domestic market to develop a distinct technological advantage as well. These two forces, an expanded market base abroad and an increase in pressures at home, create incentives for the firm to focus its R&D efforts internally to achieve a distinct advantage. Whereas the firm may purchase external R&D, this may not enable the firm to develop as distinctive an advantage compared to investing in internal R&D. There are several reasons for this. First, external R&D can result in new technologies that become available to competitors as well, thus, limiting competitive advantages. Second, external R&D results in a limited transfer of new technology to the firm because of the difficulty of transferring tacit knowledge generated in the R&D process. Third, the exploratory nature of R&D limits the ability of the firm to properly contract ex-ante the outcomes of the R&D effort. Fourth, internal R&D can result in interdependencies and causal ambiguity regarding the source and application of ideas that reinforces the difficulty in imitating the research effort. In sum, the increase in competition and expanded market that follows the REIA will result in the firm focusing its investments in internal rather than in external R&D to sharpen its distinct technological edge. Whereas the firm may have had pressures from competitors and clients to invest in internal R&D before the REIA, these pressures increase after the REIA. Hence, we hypothesize that: H1. Product markets are likely to have a larger positive influence on relative internal R&D investment after the REIA than before the REIA. 2.2.2. Impact of factor markets on R&D investments after the REIA The factor markets where the firm can obtain its inputs also affect R&D investments. In general, the characteristics of the factor markets influence the ability of the firm to achieve an advantage (Barney, 1986). A firm that is able to easily obtain resources from its environment will have less need to invest in the development of these resources on its own (Stigler, 1951; Toulan, 2002; Fisman and Khanna, 2004). The REIA results in easier access to foreign suppliers and foreign sources of technology. The difficulties
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that foreign suppliers faced in serving the local market are reduced or disappear altogether thanks to the reduction of barriers to trade and investment that accompany the REIA. This reduction in barriers enables the firm to access “foreign” inputs that might have been unavailable previously in the country, and to change suppliers more easily if it so desires, reducing opportunism threats. This is particularly important when the firm is not in a country at the forefront of technology while the suppliers are. Additionally, the REIA induces an improvement in the competitiveness of domestic suppliers, which further enables the firm to obtain better external technologies. Foreign suppliers are now free to enter the country and compete against domestic suppliers. As a result of the increase in competition, these domestic suppliers are forced to increase their competitiveness, thus, providing the firm with better technology, than was previously the case. Moreover, the increase in number and quality of competitors in the supplier market reduces potential transaction cost of relying on external suppliers of technology. These two improved sources of technology provide the firm with additional opportunities to obtain new technology, reducing the incentive to invest internally in R&D. The firm can now directly and indirectly obtain better or different technology from its suppliers. Better foreign technology now available to the firm can help it improve its technological capabilities and help it leapfrog domestic technology. The company may just purchase new technology rather than try to replicate it internally as it may take too much time and may be unsuccessful. In sum, we expect that the expansion in the factor market after the REIA will result in the firm focusing its R&D effort in purchasing external R&D rather than investing internally, to benefit from the better availability of technology. Although, the firm may have purchased R&D before the REIA, the expanded supplier market would induce the firm to further reduce the internal investment and instead focus on external purchase of R&D. We thus, hypothesize that: H2. Factor markets are likely to have a larger negative influence on relative internal R&D investment after the REIA than before the REIA. 3. Research design We test these arguments on a sample of manufacturing firms operating in Spain. Data comes from a survey of manufacturing firms conducted by the Ministry of Industry and Energy in Spain, and covers the
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years 1991–1994. This period of time is appropriate for testing the arguments presented here, since on December 31, 1992, Spain gained full access to the European Union. Although Spain formally joined the European Economic Community (EEC) in 1986, it was granted an adaptation period of 6 years. In 1992, the Maastricht Treaty transformed the EEC, which was a customs union, into the European Union, an economic union. This forced the transformation of Spanish firms as the new agreement facilitated the free flow, not only of products but also of production factors. Although the treaty had been announced earlier, many of the conditions were not implemented until the end of 1992. Thus, we have two distinct periods, before and after the end of 1992, as in other studies (e.g., Aghion et al., 2002). The study of manufacturing firms is also appropriate for testing the arguments put forward here. Tangible products, in comparison to services, are more likely to be influenced by the reduction in barriers to trade and investment that accompany the REIA. The sample includes 1441 firms for which information was available over the 4 years. Data was collected by the Ministry of Industry and Energy (Ministerio de Industria y Energ´ıa) in collaboration with the Foundation State-Owned Enterprise (Fundaci´on Empresa P´ublica). Only firms with more than 10 workers are included in the sample. The firms are chosen based on size. All firms with more than 200 employees are surveyed. Firms with between 10 and 200 employees are selected through a random stratified sample. The survey is collected through a detailed questionnaire of 107 questions with 500 fields designed to capture all aspects of the strategy of the firm. The collection and distribution of the database helps reduce biases inherent in any survey and increase the confidence on the quality of the data. First, the survey is explicitly collected for research purposes. Hence, there is no incentive to present the state of the firm in a better light to obtain subsidies or to present the state of the firm in a worse manner to avoid tax liabilities. Second, data is collected under a confidentiality agreement. As a result, the database we have access to does not contain variables that would help identify the firm. This limits our ability to collect additional information or verify the data because we do not know the identity of the firm. However, it has the benefit of reducing the incentive of misrepresentation by the managers. Third, the survey uses specific questions about the existence of or the level of the variables. To reduce respondent biases, it does not use Likert-type scales on the perception of the manager about a particular variable.
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The database has been used by other researchers to study diversification (e.g., Merino and Rodr´ıguez, 1997) or internationalization (e.g., Salomon and Shaver, 2005). However, it has not been used to explore the impact of REIA on R&D investment. 3.1. Variables and measures Table 1 summarizes the variables and measures. The dependent variable is R&D investment. The independent variables of interest are characteristics of competitors, clients, and suppliers. The controls are other firm characteristics that affect R&D investment. 3.1.1. Dependent variable: R&D investment We derived hypotheses about the determinants of the relative investment in internal R&D. We measure this by dividing the expenditures on internal R&D over total R&D expenditures and multiply this by 100. The variable is constrained to a 0–100 interval. Since a firm can invest in both internal and external R&D, this variable helps asses the relative importance given to one or another type of R&D investment. We also analyze absolute internal and external R&D investment to check for the robustness of and provide additional depth to the results. The first one is internal R&D intensity, which we measure as the money invested in R&D undertaken in the firm divided by the firm’s sales multiplied by 1000. The second one is external R&D intensity, which we measure as the money paid to other firms, universities, or research centers to perform R&D for the firm divided by the firm’s sales and multiplied by 1000. Data on internal and external R&D expenditures comes from the profit and loss statement4 . We divide R&D expenditures by sales to take into account that larger firms have larger R&D expenditures, as done by other researchers (e.g., Cohen et al., 1987). We use per thousand to increase the magnitude of the coefficients, but this change in scale does not alter their statistical significance. These two variables take positive values. 4
Under the Spanish general accounting plan, firms indicate the total amount of R&D investments in account 210 and the externally purchased R&D in account 620. R&D investment is defined in account 210 as: (1) research is the original and planned investigation with the purpose of discovering new knowledge and superior understanding in the scientific of technical domains; (2) development is the concrete investigation of the achievements obtained in the research until the beginning of commercial production. External R&D is defined in account 620 as: expenditures in research and development for services commissioned to other companies, universities, or research centers. Internal R&D investment is the difference between the total amount of R&D investment and the externally purchased R&D.
3.1.2. Independent variables of interest: product and factor market characteristics We are interested in the impact of product and factor market characteristics on R&D investment after the REIA. In product markets, we study competitors’ and clients’ pressures. In factor markets we examine suppliers’ characteristics. We measure competitors’ pressures in two ways: concentration of competitors and intensity of competition. First, the concentration of competition determines the industry dynamics and the need to invest in R&D (Aghion et al., 2002; Blundell et al., 1999; Schumpeter, 1942). With concentrated competition firms cease to be price takers; each firm can have an impact on the price and quantity exchanged (Tirole, 1988). The firm has an incentive to invest internally in R&D to improve its distinctive competitiveness and the credibility of its retaliation. Technology purchased externally may be available to competitors and may not provide the firm with a distinct advantage (Dierickx and Cool, 1989). We measure the concentration of competitors as the market share of the top four competitors. This measure is similar to other studies (e.g., Kumar and Saqib, 1996). Second, the intensity of competition induces the firm to invest internally in R&D to improve its technological capabilities (Quirmbach, 1993). Price competition is a common and easily-altered method of increasing the intensity of competition. Unlike investments in capacity, which take a long time to complete and are irreversible (Ghemawat, 1991), price reductions can be implemented quickly and are reversible. For the firm to be able to respond without incurring losses every time it engages in a price war, it must be flexible in its production system. This can be better achieved through internal investments in R&D because employees who are most knowledgeable about the strengths and weaknesses of the current production system participate in the improvement (Nonaka, 1994). We measure the intensity of competition using an indicator that the firm reduced prices over the previous year. We measure clients’ pressures in two ways: concentration of clients and existence of foreign clients. First, a firm that has concentrated clients needs to keep updating its technological capabilities to avoid the defection of large clients to competitors with superior technologies, which would result in a large proportion of its production system suddenly becoming idle. For example, in the Toyota supplier network, the suppliers specialize on developing their own technologies to maintain their competitiveness and success (Takeishi, 2002). This tight collaboration with the client results in the transfer of technologies (Kotabe et al., 2003), reducing the firm’s need to purchase external R&D to obtain technologi-
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Table 1 Variables and measures Construct
Variables
Measures
Values
R&D investment
Relative internal R&D
Expenditure on internal R&D divided by total expenditure on R&D multiplied by 100 Amount of money invested in R&D developed in the firm over total sales multiplied by 1000 Amount of money invested in R&D subcontracted to other firms, universities, or research centers over total sales multiplied by 1000 Percentage of the market that is controlled by the largest four competitors Firm reduced prices in comparison to previous year’s prices Percentage of sales to the three main clients The firm exports some of its products
0–100
Percentage of total purchases from the three main suppliers Firm imports some of its inputs
0–100
((Value of sales, variation in products, and other revenue)–(value of purchases, employee expenses, advertisement expenses, and other expenses))/(value of purchases, employee expenses, advertisement expenses, and other expenses), all multiplied by 100 Debt divided by equity multiplied by 100 Percentage of stock owned by another local firm Percentage of stock owned by a foreign company Employees with a university degree divided by total number of employees multiplied by 100 Value of products subcontracted to other firms over total purchases multiplied by 100 Value of sales in millions of pesetas Age of the firm in years The main product at the 3-digit CNAE level represents less than 70% of sales Industry of the main activity of the firm at the 2-digit CNAE level
Continuous
Absolute internal R&D intensity Absolute external R&D intensity
Product market characteristics
Concentration of competition Intensity of price competition Concentration of clients Foreign clients
Factor market characteristics
Concentration of suppliers Foreign suppliers
Controls
Value added
Leverage Local ownership Foreign ownership Employee’s education Subcontract manufacturing Size Experience in business Diversification Industry
cal capabilities that it lacks. The concentration of clients is measured as the percentage of sales to the top three clients. This measure parallels the measure of concentration of competitors, although we only have data for the largest three clients. Second, selling to foreign clients is more difficult than serving local ones because the firm faces difficulties in its internationalization (CuervoCazurra and Un, 2004a; Cuervo-Cazurra, Maloney, and Manrakhan, 2007). To compensate for this, the firm needs to be highly competitive (Cuervo-Cazurra and Un, 2004b), and internal investments in R&D can give the company this competitive edge abroad. We measure the existence of foreign clients using an indicator that the firm exports some of its products, following Galende and Suarez (1999). We measure two characteristics of suppliers: their concentration and the existence of foreign suppliers.
Positive Positive
0–100 1 or 0 0–100 1 or 0
1 or 0
Positive 0–100 0–100 0–100 Positive Positive Positive 1 or 0 1 or 0
Unfortunately, we do not have direct measures of R&D providers. We use instead measures of the general suppliers of the firm. First, a firm that has concentrated suppliers can rely on them for some of its technology and reduce its internal investments in R&D. The input that is transferred to the firm has the necessary knowledge and technology embedded in it (Carlile, 2002). Thus, the firm obtains technology from its concentrated suppliers and needs to invest less in internal R&D. This does not mean that the firm will not invest internally. It means that it will invest relatively less than if it did not have concentrated suppliers. Additionally, this reliance on concentrated suppliers can help the firm better rely on external technology providers. The firm learns how to cope with the transaction costs of having to rely on concentrated suppliers. It will be more adept at relying on suppliers of technologies. We measure the
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concentration of suppliers by the percentage of total input that is purchased from the leading three suppliers, in line with the measure of the concentration of clients. Second, the use of foreign suppliers can also induce the firm to reduce its internal investments in R&D. Foreign suppliers may provide products that are of higher quality or more sophisticated than local products for the same price, particularly if the country is not at the forefront of technological development. This compensates for the additional difficulties in bringing the products into the country5 . As a result, the firm obtains external technologies that may not even be available in the country, reducing the need to invest internally to develop them. We measure the existence of foreign suppliers though an indicator that the firm imports some of its inputs, which is similar to the measure of serving foreign clients. 3.1.3. Controls R&D investments are affected by other variables, many of which have been discussed in other studies. We now discuss the logic of controlling for them. First, to invest in R&D the firm needs to have financial resources. Because lack of funds constrains investments (Fazzari et al., 1988; Hubbard, 1998), the firm may finance R&D investments using internally generated funds. These enable the company to invest in internal R&D (Kamien and Schwartz, 1982), particularly in the case of small companies (Himmelberg and Petersen, 1994). The firm will use internally generated funds because external sources of finance face problems of adverse selection and moral hazard for investments that do not have collateral, such as internal R&D (Long and Ravenscraft, 1993; Myers and Majluf, 1984; Stiglitz and Weiss, 1981; Vicente-Lorente, 2001). Additionally, the firm may not be willing to disclose internal information and reveal the proprietary technologies to external providers to access the fund (Teece, 1980). Therefore, we control for internally generated funds in terms of the firm’s value-added. We measure it by using the ratio of revenues (value of sales, variation in products, and other revenue) minus costs (value of purchases, employee expenses, advertisement expenses, and other expenses) divided by costs and multiplied by 100. Alternatively, the firm may use external debt to fund R&D investments. However, as we discussed, debt may not be appropri5
As we discussed before, the firm may still invest in internal R&D to be able to understand the technology brought from abroad directly as R&D or indirectly as technologically-sophisticated products. However, the availability of foreign suppliers may reduce the need to invest internally in R&D to develop technology that the firm can purchase from abroad.
ate to fund R&D investment. Nevertheless, we need to control for it because high levels of debt may limit the firm’s ability to invest (Hubbard, 1998). We control for the leverage of the firm with the debt over equity ratio multiplied by 100. An alternative source of funds is the parent of the firm. A firm that belongs to another enjoys the benefit of a parent that has better access to financial markets (Chandler, 1962; Williamson, 1985). This helps the firm invest in R&D even if it generates sufficient internal funds. The parent acts as an internal capital market, with divisions requesting funds for investment (Scharfstein and Stein, 2000). Hence, we control for the ownership of the firm with indicators of the percentage of stock controlled by a domestic firm, and the percentage of stock controlled by a foreign firm. We treat ownership by a foreign firm separately because a foreign MNE has the additional benefit of its worldwide learning (Bartlett and Ghoshal, 1989) and access to foreign locations of technology (Kuemmerle, 1999) that further aids the subsidiary. Second, to benefit from the investment in R&D the firm needs to be able to absorb the technology (Cohen and Levinthal, 1989; Zahra and George, 2002). This depends on the ability of employees to use advanced technologies (Galende and Suarez, 1999; Galende and de la Fuente, 2003; Leiponen, 2005b). A firm may be willing to invest in R&D, but may be unable to understand it if its employees do not have the necessary skills. Employees need a minimum degree of knowledge to not only develop new technologies but also use externallygenerated technologies. Whereas acquisition of external R&D may require simply that employees know how to use the technology, internal investment in R&D requires both that they know how to develop new technology and why they do so. Therefore, we control for the level of education of the employees. We measure it by dividing the number employees with a university degree by the total number of employees and multiplying by 100. Additionally, in the case of purchased R&D, the firm will be better at absorbing R&D if it already has the expertise to absorb external activities from subcontracting them to other firms. A firm that subcontracts production to other firms has made a conscious decision to invest in managing external sources of technology and knowledge, and may as well be more adept at absorbing external R&D. Hence, we control for subcontracting of manufacturing, measuring it as the value of products subcontracted to other firms over total purchases, multiplied by 100. Third, R&D investments also depend on the firm’s ability to use the technology. A large firm is better able to use R&D because it is better positioned to spread the fixed costs of R&D over a larger customer base,
A. Cuervo-Cazurra, C.A. Un / Research Policy 36 (2007) 227–246
to enjoy the complementarities between technology and other resources in the firm, such as marketing, and to benefit from the economies of scale in undertaking R&D (Fisher and Temin, 1973; Schumpeter, 1942; for a review of the relationship between size and R&D investments, see Cohen and Kleppler, 1996). We control for the size of the firm in terms of sales in millions of pesetas. Additionally, the firm’s business experience enables it to better use technology because as the firm operates, it faces an obsolescence of its technologies and at the same time learns better which technologies will be more useful to its activities. We control for experience in business in terms of the firm’s age in years. Finally, the diversification of the firm also affects its ability to use technology and the method used. There are two competing arguments. On the one hand, internally generating new technologies for a diverse array of products may be too complex for the diversified firm to undertake (Baysinger and Hoskisson, 1989; Hoskisson and Hitt, 1988). Purchasing the technologies is easier for a diversified firm that has an ability to manage this diversity. On the other hand, a diversified firm can better invest in R&D to develop new technological capabilities and redeploy them in new activities (Henderson and Cockburn, 1996; Helfat, 1997). We control for the diversification of the firm with an indicator that the main product represents less than 70% of sales at the three-digit CNAE level, the Spanish equivalent of the SIC codes. Finally, the characteristics of the industry, such as technological opportunities and appropriability conditions, affect investment in R&D (Arrow, 1962; Levin et al., 1985; Levin et al., 1987; Cassiman and Veugelers, 2002; for a review of the relationship between industry structure and R&D investments, see Cohen and Levin, 1989). Unfortunately, we do not have measures for these variables. Hence, we can only control for the firm’s industry using an indicator of its two-digit industry classification in the CNAE.
235
provide a detailed discussion of the use of tobit in the context of R&D decisions. We average the data across years to suppress year-to-year random annual variations. This is a procedure commonly found in other studies (e.g., Cohen et al., 1987; Kumar and Saqib, 1999). We take the average of the variables for the two years before the REIA, and for the two years after the REIA. We then run the same model with these two subsamples and compare the size and significance of the coefficients of the product and factor market variables. This method establishes the lowest number of restrictions on the comparison. As we discuss later, we also use pooled and panel tobit model to test for the robustness of results generated with the tobit model using averaged data. The general model used in the analyses is the following: R&D investment = b0 + b1 × Concentration of competitors + b2 × Intensity of competition + b3 × Concentration of clients + b4 × Foreign clients + b5 × Concentration of suppliers + b6 × Foreign suppliers + b7 × Value added + b8 × Leverage + b9 × Division of a local firm + b10 × Subsidiary of a foreign firm + b11 × Employee’s education + b12 × Subcontract manufacturing + b13 × Size + b14 × Experience in business + b15 × Diversification + bj × Industry dummiesj + e 4. Results
3.2. Method of analysis 4.1. R&D investments in Spain We use a tobit specification to test the relationships because the dependent variables are either constrained to an interval or to positive numbers (Tobin, 1958). If we restrict the analysis to only those firms that undertook R&D, the truncation of the error term will bias the resulting parameter estimates (Cohen et al., 1987: 551). The tobit model avoids this problem. It takes into account the result of two decisions, the decision to undertake R&D and the decision as to the amount to invest in internal R&D in proportion to all R&D investment (MacDonald and Moffitt, 1980). Cohen et al. (1987) and Helfat (1997)
To provide background to and establish boundaries of the applicability of the analysis, we first discuss R&D investment in Spain. Table 2 provides data on gross domestic expenditure on R&D (GERD) as a percentage of gross domestic product (GDP) for OECD countries. Countries are ranked by average R&D investment over GDP for the period 1990–2002. There is a wide disparity of R&D investments. The USA, where many of the studies on R&D have been done, appears high in the ranking, with an average GERD of 2.63% of GDP. There are other
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Table 2 Gross domestic expenditure on R&D as percentage of GDP in the OECD, 1990–2002
Sweden Japan Switzerland United States Finland Korea Germany France Total OECD United Kingdom Netherlands Iceland European Union Denmark Belgium Canada Norway Austria Australia Czech Republic Slovak Republic Ireland Italy New Zealand Hungary Spain Poland Portugal Turkey Greece Mexico
Average 1990–2002
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
3.44 2.87 2.71 2.63 2.58 2.46 2.40 2.29 2.20 1.98 1.97 1.90 1.86 1.80 1.73 1.73 1.68 1.65 1.51 1.31 1.18 1.17 1.09 1.02 0.89 0.86 0.71 0.69 0.46 0.44 0.33
2.84 2.85 2.83 2.65 1.88 n/a 2.75 2.37 2.3 2.16 2.07 0.98 1.96 1.57 1.64 1.54 1.69 1.39 1.31 n/a 1.75 0.83 1.29 1 1.46 0.81 n/a 0.51 0.32 0.37 n/a
2.79 2.82 n/a 2.72 2.04 1.92 2.53 2.37 2.24 2.08 1.97 1.16 1.9 1.64 1.62 1.6 1.65 1.47 n/a 2.02 2.25 0.93 1.23 0.99 1.06 0.84 n/a n/a 0.53 0.36 n/a
n/a 2.76 2.66 2.65 2.13 2.03 2.41 2.38 2.2 2.09 1.9 1.33 1.89 1.68 n/a 1.66 n/a 1.45 1.52 1.72 1.88 1.04 1.18 1.01 1.04 0.88 n/a 0.61 0.49 n/a n/a
3.27 2.68 n/a 2.52 2.17 2.22 2.35 2.4 2.15 2.12 1.92 1.33 1.88 1.74 1.75 1.71 1.73 1.47 n/a 1.21 1.45 1.17 1.13 1.02 0.97 0.88 n/a n/a 0.44 0.47 0.22
n/a 2.63 n/a 2.42 2.29 2.44 2.26 2.34 2.1 2.07 1.95 1.38 1.83 n/a 1.74 1.77 n/a 1.54 1.57 1.1 0.96 1.31 1.05 n/a 0.88 0.81 0.76 n/a 0.36 n/a 0.29
3.46 2.77 n/a 2.5 2.29 2.5 2.26 2.31 2.11 1.98 1.99 1.54 1.81 1.84 1.74 1.74 1.71 1.56 n/a 1.01 0.98 1.34 1 0.97 0.73 0.81 0.69 0.57 0.38 0.49 0.31
n/a 2.83 2.73 2.54 2.54 2.6 2.26 2.3 2.14 1.91 2.01 n/a 1.81 1.85 1.82 1.7 n/a 1.6 1.65 1.03 0.97 1.4 1.01 n/a 0.65 0.83 0.71 n/a 0.45 n/a 0.31
3.67 2.9 n/a 2.57 2.72 2.69 2.29 2.22 2.16 1.84 2.04 1.84 1.8 1.94 1.83 1.71 1.66 1.69 n/a 1.17 1.13 1.39 0.99 1.13 0.72 0.82 0.71 0.62 0.49 0.51 0.34
n/a 3.04 n/a 2.6 2.89 2.55 2.31 2.18 2.18 1.83 1.95 2.04 1.81 1.92 n/a 1.71 n/a 1.8 1.49 1.27 0.82 n/a 1.02 n/a 0.68 0.9 0.72 n/a n/a n/a 0.46
3.8 3.04 n/a 2.64 3.19 2.46 2.44 2.17 2.21 1.87 n/a 2.32 1.85 2 n/a 1.66 1.7 1.8 n/a 1.29 0.68 n/a 1.04 n/a 0.68 0.89 0.75 0.77 n/a n/a 0.4
n/a 2.98 2.63 2.72 3.4 2.65 n/a 2.18 2.25 1.85 1.94 2.77 1.89 n/a n/a 1.87 n/a 1.84 1.53 1.33 0.67 1.15 1.07 n/a 0.8 0.94 0.7 0.79 0.64 n/a n/a
4.27 3.09 n/a 2.82 3.4 2.96 2.49 2.2 2.33 1.9 n/a 3.06 1.93 n/a n/a 1.94 1.62 1.9 n/a 1.3 0.65 1.17 n/a n/a 0.95 0.96 0.67 0.83 n/a n/a n/a
n/a n/a n/a 2.82 n/a n/a 2.5 n/a n/a n/a n/a 3.04 n/a n/a n/a 1.85 n/a 1.94 n/a n/a n/a n/a n/a n/a n/a n/a n/a 0.78 n/a n/a n/a
Source: OECD (2004), MSTI database. Note: n/a, not available.
countries with high levels of GERD over GDP, like Sweden with a staggering 3.44%, Japan with 2.87%, Switzerland with 2.71%, Finland with 2.58%, or South Korea with 2.46%. In contrast, Spain appears at the lower level of the scale, with an average GERD of 0.86% of GDP. This has increased to 0.96% in recent years. This lower level is not necessarily a sign of lack of development, but of a different approach to R&D. Other countries traditionally considered developed also have low levels of R&D investments, like Ireland with a GERD over GDP of 1.17%, Italy with 1.09%, New Zealand with 1.02%, Portugal with 0.69%, or Greece with 0.44%. Therefore, the insights from this study are more likely to apply to firms in countries with a lower level of technological investment, which are the majority in the world. In these countries, the REIA may have a larger impact on R&D investment than in countries with very high levels of R&D investment because the firm and its competitors, clients, and suppliers may not be at the forefront of the
technological development. The lowering of barriers to foreign competitors, clients, and suppliers that follows the REIA will result in deep changes on the behavior of domestic players. As a result, this study empirically complements the literature by analyzing firms in a country that is not at the forefront of R&D investment. We focus on R&D investment by manufacturing firms6 . According to data from the OECD (2004), manufacturing firms represent the majority of firm 6 Hence, we exclude from the analysis R&D performed by the government and by other entities like non-governmental research centers and universities. In Spain in 1995 government spending in R&D accounted for 43.6% of all spending and other entities accounted for 5.2%, while domestic firms accounted for 44.5% and foreign sources accounted for 6.7%. These figures for the USA are 35.6% by government, 4.0% by other entities, and 60.4% by domestic firms. The expenditure by source for the EU are 38.9% by government 1.8% by other entities, 52.6% by domestic firms, and 6.7% by foreign sources. For the OECD the figures are 33.8% by government, 3.9% by other entities, and 59.8% by domestic firms.
A. Cuervo-Cazurra, C.A. Un / Research Policy 36 (2007) 227–246
R&D investment in Spain. For the period 1990–2002, average R&D investment by manufacturing was 77% of all firm R&D investment, services was 18%, electricity, gas, and water was 3%, and construction was less than 1%. These figures are quite similar to those of other countries. The averages for the European Union were 86%, 12%, 2%, and less than 1%, respectively. For the USA, these figures were 74%, 26%, less than 1%, and less than 1%, respectively. Investigating the firms comprising our study, it is noticeable that the majority of companies do not undertake R&D. Approximately, 65% of the firms do not invest in R&D. While this may be initially surprising, it is less so if one places the data in context. Many analyses of R&D only study R&D active firms. Others study public firms, which are larger and tend to be R&D active. In contrast, studies that include a broad variety of firms are in line with our findings. For example, Bound et al. (1984) found that 40% of firms in their sample of US companies did not invest in R&D, while Galende and Suarez (1999) found that 71% of the firms in their sample of Spanish companies in Castilla-Leon did not have positive R&D expenditures. Other interesting findings emerge from analyzing the method of R&D investment used by R&D active firms. Throughout the period of analysis (1991–1994), the percentage of firms that only invest in internal R&D is a surprisingly low 10%. In contrast, about 45% of R&D active firms purchase external R&D only. The rest, 45% of R&D active firms, do both internal and external R&D. These percentages do not vary more than two percentage points from one year to another. Although internal and external R&D are complementary and internal R&D investments may help the firm to better use external technology (Cohen and Levinthal, 1989), almost half of the R&D active firms R&D choose to invest only in external R&D. In addition to having more firms invest in external R&D, these investments are larger than those done internally. Firms that invested internally in R&D spent an average of 144 thousand pesetas or 0.87% of sales. In contrast, firms that invested externally in R&D spent an average of 852 thousand pesetas or 1.71% of sales. We do not have figures from other countries to establish comparisons, but Spanish firms appear to subcontract a very large proportion of their R&D efforts. We leave for future studies a more in-depth analysis of external R&D. 4.2. REIA and R&D investment We now turn to the analysis of how the impacts of product and factor markets on R&D investments change
237
after the REIA. Tables 3 and 4 present the summary statistics and correlation matrix, one for data before the REIA and another for data after the REIA. Some of the variables show statistically significant correlations with others, but only foreign clients, foreign suppliers, and foreign ownership show sizable correlations. We conducted additional tests to check for potential multicollinearity, running models with and without the correlated variables. The results do not change significantly, indicating few problems of multicollinearity (Greene, 2000). 4.2.1. REIA and relative R&D investment Table 5 presents the results of the analyses of the determinants of relative R&D investments before and after the REIA. We are interested in comparing the sign and significance of the measures of product and factor markets before and after the REIA on relative R&D investment. The likelihood ratio test included tests that all coefficients do not vary between the subsets of the data. We present three alternative models to check for the robustness of the results to different specifications: a tobit model with averaged data, a pooled tobit model, and a panel tobit model. The results of the three analyses are similar in sign and significance. We observe that before the REIA, among the product market variables, only foreign clients had a positive and statistically significant relationship with relative R&D investment. In contrast, after the REIA, the concentration of competitors, the concentration of clients, and foreign clients have positive and statistically significant coefficients. These results provide support for H1. In other words, after the REIA product markets become stronger determinants of relative R&D investment. Firms that served foreign clients invested relatively more in internal R&D to be able to serve these more demanding clients, regardless of the existence or not of a REIA. However, only after the REIA are firms with concentrated clients and concentrated competitors induced to invest relatively more in internal R&D. The additional pressures of foreign competitors, who are now free to enter the country, transform the pressures of concentrated competitors and demands of concentrated clients on the firm. The firm is induced to invest relatively more on internal R&D to improve the distinctiveness of its technology and advantage. We also observe that among the factor market variables, before the REIA only the existence of foreign suppliers has a statistically significant relationship with relative internal R&D. After the REIA, foreign suppliers still have a positive and statistically significant relationship, but the concentration of suppliers become negative
238
Table 3 Descriptive statistics and correlation matrix (before REIA) Mean
S.D.
min
max
1
2
8.82
23.87
0
100
1.72
8.21
0
150.51
0.50*
3
4
5
6
7
8
5.39
17.7
0
310.99
0.03
0.25*
19.21
27.43
0
100
0.05*
0.02
0.03
0.14
0.35
0
1
0.02
−0.03
−0.01
39.01
27.59
0
100
0.00
0.04
0.02
0.53 46.42
0.5 24.24
0 0
1 100
0.19* 0.09* 0.16* 0.13* 0.11* −0.12* 0.22* −0.27* −0.06* −0.04* −0.10* −0.02 −0.02
0.54 9.67 16.73 1344 13.95 7.51
0.5 25.76 34.9 30093 33.84 10.89
0 0 0 0 −748 0
1 100 100 1462206 988 100
0.20* 0.09* 0.18* 0.18* 0.12* −0.11* 0.58* 0.06* 0.02 0.11* 0.05* 0.08* 0.06* 0.16* 0.11* 0.05* 0.05* 0.18* 0.06* 0.02 0.34* −0.01 −0.01 −0.01 −0.01 −0.01 0.01 −0.03 0.01 0.00 −0.05* −0.03 −0.03 −0.01 −0.06* 0.12* 0.13* 0.22* 0.12* 0.04* −0.01 0.16*
7.62
0
72
0.07*
0.06*
0.08*
0.05* −0.03
0 0
632907 219
0.06* 0.02
0.03 0.02
0.04* 0.02
0.08* 0.03
0
1
0.03
0.03
0.09*
0.05*
0.02
2.5 5900 24.79 0.21
Significance level, * p < 0.5.
30118 56.6 0.41
9
10
11
12
13
14
15
16
17
A. Cuervo-Cazurra, C.A. Un / Research Policy 36 (2007) 227–246
1. Relative internal R&D investment 2. Absolute internal R&D intensity 3. Absolute external R&D intensity 4. Concentration competitors 5. Intensity of price competition 6. Concentration clients 7. Foreign clients 8. Concentration suppliers 9. Foreign suppliers 10. Local ownership 11. Foreign ownership 12. Leverage 13. Value added 14. Employees’ education 15. Subcontract manufacturing 16. Size 17. Experience in business 18. Diversification
0.13* −0.05* −0.03
−0.23* −0.08* 0.16* −0.10* 0.36* −0.15* 0.00 −0.03 −0.01 −0.01 −0.02 −0.05* −0.04* −0.03 0.01 −0.06* 0.25* 0.10* 0.25* −0.02
−0.03
0.08* −0.03
0.06* −0.01
0.01
−0.01
−0.03
0.04* −0.03 0.01 −0.04*
0.15* −0.03 0.14* −0.07*
0.16* 0.11*
0.03 0.04*
0.20* 0.00 0.13* −0.01
0.01 0.00
−0.15*
0.11* −0.09*
0.16*
0.04*
0.14* −0.02
0.04*
0.05* 0.08* 0.10* 0.02 0.00 0.05*
−0.05* 0.15* 0.04* 0.02
0.04*
Table 4 Descriptive statistics and correlation matrix (after REIA) Mean
Std dev
Min
Max
1
2
3
4
5
6
8.49
23.08
0
100
1.71
8.03
0
133.87
0.49*
5.73
19.44
0
335.74
0.03
0.24*
18.85
26.84
0
100
0.10*
0.04*
0.04*
0.11
0.32
0
1
0.04*
0.05*
0.08*
39.81 0.56 47.39
27.51 0.5 23.29
1 0 0
100 1 100
0.57 10.49 17.32 455.25 10.32 8.56
0.5 27.17 35.56 2356 19.97 12.88
0 0 0 0 −124 0
1 100 100 64264 229 100
2.45
7.48
0
76
0.09*
0.12*
0.08*
0.04* −0.01
0 2
731215 221
0.10* 0.04
0.12* 0.00
0.04* 0.05*
0.10* 0.01
0
1
0.01
0.03
0.08*
0.04*
6360 26.79 0.22
30536 56.6 0.41
7
8
9
10
11
12
−0.23* −0.05* −0.05* 0.00 0.01 −0.08*
0.17* 0.37* −0.16* 0.00 −0.01 −0.01 0.01 −0.07* 0.03 −0.06* 0.25* 0.11* 0.24* −0.03
13
14
15
16
17
0.07*
0.03 0.06* 0.04* −0.04* 0.03 0.18* 0.11* 0.17* 0.11* 0.06* −0.12* −0.07* −0.03 −0.09* 0.00 −0.01 0.21* −0.22* 0.21* 0.12* 0.18* 0.15* 0.09* 0.07* 0.04* 0.10* 0.09* 0.01 0.14* 0.10* 0.05* 0.14* 0.13* −0.02 −0.01 0.00 −0.01 −0.02 0.00 −0.01 −0.08* −0.04* −0.02 0.08* 0.11* 0.21* 0.07* 0.05*
−0.09* 0.07* 0.03 −0.01 −0.03 −0.04*
0.59* 0.15* 0.33* 0.01 0.00 0.18*
0.02
0.03
0.07* −0.04* 0.05*
0.00
0.04* −0.01
−0.05* 0.06*
0.00 0.01
−0.03 −0.03
0.15* −0.04* 0.16* 0.13* −0.05* 0.13*
0.03 0.05*
0.21* −0.01 0.13* −0.01
0.06* 0.14* 0.20* −0.06* 0.02 0.01 0.05*
0.02
−0.12*
0.09* −0.04* 0.12*
0.03
0.15* −0.02
−0.04* 0.14* 0.10* 0.07* 0.05*
A. Cuervo-Cazurra, C.A. Un / Research Policy 36 (2007) 227–246
1. Relative internal R&D investment 2. Absolute internal R&D intensity 3. Absolute external R&D intensity 4. Concentration competitors 5. Intensity of price competition 6. Concentration clients 7. Foreign clients 8. Concentration suppliers 9. Foreign suppliers 10. Local ownership 11. Foreign ownership 12. Leverage 13. Value added 14. Employees’ education 15. Subcontract manufacturing 16. Size 17. Experience in business 18. Diversification
Significance level, * p < 0.5.
239
240
Table 5 Result of the analysis of product and factor markets influence on relative internal R&D investment Relative internal R&D investment Tobit Before REIA Model 1a
After REIA Model 1b
0.073 (0.121) 3.745 (7.688) 0.128 (0.127) 41.657*** (8.681) −0.110 (0.146) 44.048*** (9.139) 0.279* (0.118) −0.0001 (0.0004) 0.093 (0.113) −0.010 (0.091) 0.591* (0.280) 0.719+ (0.409) 0.00008 (0.00007) −0.010 (0.056) −14.697+ (8.246) n/a −111.155 (44.303) 1441 210.40*** −2094.449 26.86
0.178*
(0.084) 10.088 (6.929) 0.309** (0.111) 20.978** (7.581) −0.297* (0.129) 40.526*** (8.225) −0.108 (0.169) −0.0009 (0.0015) 0.076 (0.106) 0.022 (0.081) 0.738** (0.266) 0.860* (0.386) 0.00008 (0.00007) 0.007 (0.044) −10.921 (7.092) n/a −111.305* (43.766) 1441 230.40*** −2169.372
Panel Tobit
Before REIA Model 2a
After REIA Model 2b
Before REIA Model 3a
After REIA Model 3b
0.040 (0.098) −4.785 (7.441) 0.132 (0.108) 41.547*** (7.195) −0.182 (0.119) 49.754*** (7.531) 0.167* (0.083) −0.002 (0.002) 0.176+ (0.098) 0.019 (0.079) 0.717* (0.245) 0.787* (0.314) 0.00012* (0.00006) −0.002 (0.046) −8.380 (6.480) 4.744 (5.153) −160.684*** (39.922) 2882 379.56*** −3425.453 33.27
0.276***
0.0878 (0.1012) −7.2399 (6.9879) 0.1160 (0.1153) 40.6877*** (7.7049) −0.0934 (0.1225) 45.1274*** (7.8981) 0.1916* (0.0787) −0.0007 (0.0009) 0.2303+ (0.1189) 0.1284 (0.0953) 1.1041*** (0.2802) 0.5004+ (0.3071) 0.0001+ (0.00008) 0.0027 (0.0557) −1.1501 (6.7017) 3.198 (3.374) −161.542*** (12.7049) 2882 158.68*** −3290.511 −520.74
0.2973*** (0.0871) 6.7850 (6.8219) 0.2934*** (0.0890) 30.3268*** (6.4598) −0.2376* (0.1081) 48.7642*** (6.9685) 0.0491 (0.1276) −0.0036 (0.0024) 0.2720*** (0.0828) 0.1266+ (0.0686) 0.3936* (0.1728) 0.8994*** (0.2819) 0.0001* (0.00006) 0.0130 (0.0372) −3.7435 (5.6455) −0.893 (4.570) −145.804*** (10.9493) 2882 214.63*** −3403.827
(0.090) 4.531 (7.242) 0.391*** (0.100) 33.281*** (6.753) −0.324** (0.112) 47.729*** (7.200) 0.005 (0.134) −0.003 (0.002) 0.207* (0.086) 0.051 (0.072) 0.229 (0.196) 1.094*** (0.297) 0.0001+ (0.00006) 0.010 (0.039) −5.376 (5.904) −2.068 (4.859) −147.597*** (39.472) 2882 425.29*** −3379.951
Controls for industry not reported in the table. Standard error appears in parenthesis after the coefficient. The panel tobit controls for random firm effects. n/a, not applicable. Significance levels, + p < 0.10, * p < 0.5, ** p < 0.01, *** p < 0.001.
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Concentration of competitors Intensity of price competition Concentration of clients Foreign clients Concentration of suppliers Foreign suppliers Value added Leverage Local ownership Foreign ownership Employees’ education Subcontract manufacturing Size Experience in business Diversification Year Intercept N Chi square Log likelihood LR Chi2 test
Pooled Tobit
Table 6 Result of the analysis of product and factor markets influence on absolute internal R&D intensity Absolute internal R&D intensity Tobit
LR Chi2 test
Panel Tobit
Before REIA Model 1a
After REIA Model 1b
Before REIA Model 2a
After REIA Model 2b
Before REIA Model 3a
After REIA Model 3b
0.012 (0.025) −1.057 (1.631) 0.035 (0.026) 8.367*** (1.823) −0.050+ (0.030) 7.624*** (1.913) 0.042+ (0.025) −0.00001 (0.00005) 0.012 (0.023) −0.016 (0.019) 0.164** (0.057) 0.140+ (0.084) 0.00002 (0.00001) 0.002 (0.010) −1.729 (1.721) n/a −20.979* (9.157) 1441 231.07*** −1753.500
0.031 (0.023) 4.305** (1.519) 0.077** (0.025) 5.925*** (1.709) −0.065* (0.029) 8.346*** (1.850) 0.010 (0.037) −0.00003 (0.0003) −0.0002 (0.0237) −0.012 (0.018) 0.207*** (0.058) 0.215* (0.084) 0.00003* (0.00001) 0.0004 (0.0106) −1.326 (1.580) n/a −29.289** (9.701) 1441 283.94*** −1767.462
0.0088 (0.0240) −2.6460 (1.8337) 0.0394 (0.0264) 9.9026*** (1.7475) −0.0594* (0.0292) 9.9859*** (1.8172) 0.0341+ (0.0207) −0.0001 (0.0002) 0.0303 (0.0241) −0.0132 (0.0193) 0.2141*** (0.0587) 0.1871* (0.0755) 0.00003* (0.00001) 0.0053 (0.0104) −1.2807 (1.5751) 1.0470 (1.2552) −35.4076*** (9.5030) 2882 391.02*** −3075.738
0.0485* (0.0228) 1.7221 (1.8113) 0.0989*** (0.0250) 8.7023*** (1.7039) −0.0748** (0.0284) 0.4011*** (1.8090) 0.0119 (0.0336) −0.0005 (0.0005) 0.0423+ (0.0216) 0.0040 (0.0181) 0.1188* (0.0474) 0.3146*** (0.0729) 0.00003** (0.00001) 0.00003 (0.01090) −0.6878 (1.4802) −0.9306 (1.2238) −40.7255*** (9.9040) 2882 447.63*** −2994.208
0.0126 (0.0239) −2.2672 (1.7963) 0.0597* (0.0245) 9.9599*** (1.6744) −0.0623* (0.0290) 11.0170*** (1.8235) 0.0277 (0.0198) −0.0001 (0.0002) 0.0383 (0.0225) −0.0009 (0.0189) 0.3316*** (0.0532) 0.1742* (0.0755) 0.00003* (0.00001) 0.0044 (0.0105) −0.0877 (1.5627) 0.6562 (1.2007) −38.9118*** (2.7087) 2882 218.02*** −3112.206
0.0508* (0.0244) 0.7070 (1.5231) 0.0653* (0.0256) 7.3154*** (1.7985) −0.0453 (0.0299) 9.9667*** (1.8854) −0.0039 (0.0328) −0.0005 (0.0004) 0.0810*** (0.0215) 0.0533*** (0.0201) 0.0973* (0.0406) 0.2653*** (0.0723) 0.00004* (0.00002) −0.0020 (0.0130) 0.5595 (1.4678) −0.7689 (1.1181) −37.8081*** (2.8074) 2882 186.49*** −2896.463
31.48
37.81
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Concentration of competitors Intensity price competition Concentration of clients Foreign clients Concentration of suppliers Foreign suppliers Value added Leverage Local ownership Foreign ownership Employees’ education Subcontract manufacturing Size Experience in business Diversification Year Intercept N Chi square Log likelihood
Pooled Tobit
−12.16
Controls for industry not reported in the table. Standard error appears in parenthesis after the coefficient. The panel tobit controls for random firm effects. n/a, not applicable. Significance levels: + p < 0.10, * p < 0.5, ** p < 0.01, *** p < 0.001.
241
242
Table 7 Result of the analysis of product and factor markets influence on absolute external R&D intensity Absolute external R&D intensity Tobit
LR Chi2 test
Panel Tobit
Before REIA Model 4a
After REIA Model 4b
Before REIA Model 5a
After REIA Model 5b
Before REIA Model 6a
After REIA Model 6b
0.004 (0.031) −1.282 (1.994) 0.038 (0.032) 13.190*** (2.187) −0.147*** (0.038) 10.550*** (2.248) −0.016 (0.041) −0.00001 (0.00005) 0.053+ (0.028) −0.052* (0.023) 0.297*** (0.071) 0.203+ (0.108) 0.00001 (0.00002) −0.0004 (0.014) 1.164 (2.050) n/a 11.893 (11.132) 1441 474.47*** −2612.206
0.037 (0.031) 8.409*** (2.007) 0.069* (0.032) 13.354*** (2.222) −0.135*** (0.038) 11.284*** (2.381) −0.076 (0.051) 0.00003 (0.0004) 0.032 (0.030) −0.056* (0.023) 0.409*** (0.077) 0.150 (0.113) 0.000008 (0.00002) 0.020+ (0.010) 0.778 (2.009) n/a −25.818* (12.447) 1441 556.56* −2614.853
0.0045 (0.0299) −1.3081 (2.2597) 0.0334 (0.0331) 17.0951*** (2.1639) −0.1764*** (0.0374) 14.8665*** (2.1955) −0.0359 (0.0366) −0.00002 (0.00005) 0.1039*** (0.0297) −0.0360 (0.0239) 0.4026*** (0.0753) 0.2616** (0.1006) 0.00003 (0.00002) 0.0050 (0.0140) 2.0146 (1.9394) 2.2934 (1.5818) 1.8772 (11.2083) 2882 820.40* −5075.071
0.0529+ (0.0316) 6.6586** (2.5404) 0.0800* (0.0350) 19.7409*** (2.3935) −0.1859*** (0.0399) 17.5171*** (2.4855) −0.0903+ (0.0496) −0.0006 (0.0005) 0.0739* (0.0307) −0.0517* (0.0252) 0.2752*** (0.0681) 0.1623 (0.1087) 0.00003 (0.00002) 0.0223+ (0.0120) 0.7197 (2.0451) 1.5300 (1.7143) −41.1799** (13.2757) 2882 911.66*** −4972.647
−0.0115 (0.0338) 0.3161 (2.2652) 0.0392 (0.0387) 19.4028*** (2.5685) −0.1413*** (0.0430) 14.0551*** (2.5208) −0.0293 (0.0372) −0.00003 (0.00008) 0.1314*** (0.0389) 0.0424 (0.0313) 0.6949*** (0.0997) 0.3626*** (0.1096) 0.00003 (0.00003) −0.0022 (0.0202) 2.1888 (2.6987) 1.2992 (0.8234) −47.3979*** (3.8255) 2882 312.83*** −4973.769
0.0739+ (0.0388) 5.9302* (2.3430) 0.1397*** (0.0425) 21.6109*** (2.8329) −0.1855*** (0.0466) 20.6675*** (2.8200) −0.1029+ (0.0545) −0.0011+ (0.0005) 0.1202*** (0.0344) 0.0415 (0.0317) 0.2196*** (0.0648) 0.2609* (0.1154) 0.00002 (0.00004) 0.0209 (0.0133) 3.1882 (2.2722) 1.1841 (0.8738) −56.6293*** (4.2583) 2882 314.92*** −4900.272
29.60
45.37
−600.86
Controls for industry not reported in the table. Standard error appears in parenthesis after the coefficient. The panel tobit controls for random firm effects. n/a, not applicable. Significance levels: + p < 0.10, * p < 0.5, ** p < 0.01, *** p < 0.001.
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Concentration of competitors Intensity price competition Concentration of clients Foreign clients Concentration of suppliers Foreign suppliers Value added Leverage Local ownership Foreign ownership Employees’ education Subcontract manufacturing Size Experience in business Diversification Year Intercept N Chi square Log likelihood
Pooled Tobit
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and statistically significant. These results only partially support H2, however, we do find that after the REIA factor markets, in particular the concentration of suppliers, result in a weaker (negative) impact on relative internal R&D. However, although the impact of foreign suppliers is statistically significant both before and after the REIA, the sign is positive, contrary to the arguments presented. In other words, the opening of supplier markets that follows the REIA enables the firm to obtain better technology and thus, needs to invest relatively less in internal R&D. However, the firm that has foreign suppliers is still induced to invest relatively more in internal R&D. The firm needs to invest internally in R&D to be able to understand and fully benefit from the technology provided by foreign suppliers, especially since this technology may be more advanced than what is available in the country. 4.2.2. REIA and absolute R&D investment We now explore the effect of product and factor markets before and after the REIA on absolute internal and external R&D investments independently from one another. In the previous analysis, we studied relative R&D investments because, as we saw before, firms do choose both types of investments. We now assume that the decision to invest on one is independent from the decision to invest in another and explore how the influence of product and factor markets varies before and after the REIA. We use R&D intensity as the measure of absolute R&D investments. We measure internal R&D intensity as the expenditure on internal R&D over sales, and external R&D intensity as the expenditure on external R&D over sales. Using the same measures helps compare the two R&D methods. The results of the analysis appear in Tables 6 and 7. As we did before, we present three alternative specifications: tobit with averaged data, pooled tobit, and panel tobit. We first analyze the determinants of internal R&D intensity. Before the REIA, only foreign clients among product market characteristics and foreign suppliers among factor market characteristics have a positive and statistically relationship with internal R&D intensity. Although there is some variation across specifications, after the REIA other variables become statistically significant determinants. The concentration of clients and the intensity of competition have a positive relationship, while the concentration of suppliers has a negative relationship. In other words, before the REIA a firm is more likely to increase its internal R&D when it serves foreign clients and has foreign suppliers. The firm needs to sharpen its distinct technological edge to serve demanding foreign clients and to benefit fully from more
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advanced foreign inputs. After the REIA, the firm is also induced to increase its internal R&D to be able to serve the higher demands of current clients and to face new competitive pressures. However, those firms with more concentrated suppliers can benefit from the additional competitive pressures on their suppliers and rely on them for technology. In sum, after the REIA product markets induce the firm to invest more in internal R&D while factor markets have a weak negative effect on internal R&D. When we look at the determinants of external R&D intensity, we observe a similar behavior. Before the REIA, foreign clients, foreign suppliers and the concentration of suppliers have statistically significant relationship with external R&D intensity. After the REIA, these three factors continue to have statistically significant relationship. In addition, the concentration of clients and the intensity of price competition become positive and statistically significant determinants. The concentration of competitors has a weak positive relationship with external R&D intensity. In other words, before the REIA the firm would purchase more external R&D to satisfy demanding foreign clients and to complement the more sophisticated inputs of foreign suppliers, while it may rely on its concentrated suppliers for technology. After the REIA, the previous demands do not vary, but the firm is not compelled to purchase more external R&D to serve increasingly demanding clients and to counter the intensity of competition. In sum, after the REIA, product markets induce the firm to purchase more external R&D while factor markets do not change external R&D investments. 5. Conclusions Regional economic integration is beneficial for firms since it results in improved access to foreign clients and suppliers, but it also presents challenges for firms that were formerly protected, as they now face additional competition. Firms are faced with the decision of how much to invest in internal and in external R&D. However, the REIA creates two competing pressures. On the one hand, expanded markets and increased competition in product markets after the REIA would induce the firm to invest relatively more in internal R&D to improve its distinct advantage. On the other hand, better access to sources of inputs in factor markets after the REIA would induce the firm to purchase relatively more external R&D because it can outsource technology more easily. The results of the empirical analysis show that the influence of the REIA on R&D investment is driven primarily by product markets rather than by factor markets. After the REIA, product markets induce firms to invest
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relatively more in internal R&D. Factor markets only have a weak influence on the firm to invest relatively more in external R&D. Moreover, when analyzing absolute R&D investments, after the REIA, product markets induce firms not only to invest more in internal R&D but also purchase more external R&D. In contrast, after the REIA factor markets have limited influence on internal or external R&D investments. The present paper contributes to two streams of research. First, it contributes to the literature on the development of technological capabilities, highlighting how the conditions of the institutional environment in which the firm operates affect which factors are relevant in the investments in R&D. The development of technological capabilities is an area that despite recent advances still requires further research (Thomke and Kuemmerle, 2002). The paper indicates the importance of the conditions of product and factor markets on R&D investment, not only for internal R&D, but also for external R&D. This complements previous discussions on the internal or external investment in R&D to develop technological capabilities (Pisano, 1990; Nagarajan and Mitchell, 1998; Narula, 2001). The paper points to the complementarity between internal and external investments in R&D (Cohen and Levinthal, 1989; Veugelers, 1997; Veugelers and Cassiman, 1999; Leiponen, 2005a). Second, the paper contributes to the literature on REIAs, highlighting the impact of the agreements on the behavior of local firms. The paper is the first to analyze the change in the behavior of firm’s R&D investments after an REIA. It indicates that increased competition and more demanding clients in product markets take prevalence over easier access to inputs in factor markets as the driver of firm’s R&D investments. This complements previous studies on the impact of REIAs that have focused primarily on country-level flows of trade or investment (e.g., Frankel, 1997; Jovanovic, 1998) and on the reaction of multinational enterprises (MNEs) (e.g., Eden, 2002). These insights open directions for new analyses to solve some of the limitations of the current study. First, we analyzed a particular type of REIA, an economic union that reduces the barriers against the cross-country movement of products and factors of production. Future research can explore how the different types of REIA impact the use of the methods. It will be interesting to compare the differences in behavior that accompany the mere reduction of barriers to trade. Moreover, the competitive pressures may differ depending on the conditions of local firms in comparison to foreign ones (Fung, 1992). Second, we studied manufacturing companies. Future research can analyze the impact of a
REIA on service firms, which are less influenced by the reduction of trade barriers, but more affected by the free movement of factors of production. Third, we focused on ongoing R&D investments. Future research can analyze and compare the decision to develop a discrete technology, as has been done in previous studies (e.g., Pisano, 1990; Nagarajan and Mitchell, 1998), versus the decision to invest in the continuous development of the technological capabilities analyzed here. Fourth, we studied the development of one particular resource, technological capabilities that are developed through investments in R&D. This helped control for the characteristics of the resources and allowed a focused analysis. Future studies can analyze the development of other resources (e.g. Cuervo-Cazurra, 2002; Un and Cuervo-Cazurra, 2004). This would contribute to a better understanding of how particular characteristics of the resources affect the use of different methods of resource development. Fifth, the country is not at the forefront in terms of R&D investment. Future studies can analyze how the level of technological sophistication of the country alters the determinants of investments in R&D. Sixth, firms included in the sample have more than ten employees. Future studies can compare the difference in reaction to REIAs between very small firms and other companies. Managers can benefit from the insights discussed here. The study highlights the changing influence of the characteristics of product markets and factor markets on the use of methods of resource development. It helps managers better understand the drivers of the investments in their firms, and to be aware that the REIA will alter the factor and product markets, precipitating a change in the importance of the drivers of the use of methods to develop resources. In sum, the development of technological capabilities is crucial for the firm’s current operations and future survival. The present study is a step towards a better understanding of the ways in which the conditions in the firm’s country of operation have an influence on its investment decision. References Aghion, P., Bloom, N., Blundell, R., Griffith, R., Howitt, P., 2002. Competition and innovation: an inverted U relationship. NBER Working Paper No. w9269. Almor, T., Hirsch, S., 1995. Outsiders’ responses to Europe 1992: theoretical considerations and empirical evidence. Journal of International Business Studies 26, 223–237. Arrow, K., 1962. Economic welfare and the allocation of resources for inventions. In: Nelson, R.R. (Ed.), The Rate and Direction of Inventive Activity. Princeton University Press, Princeton, NJ.
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