Organizing for Innovation Ambidexterity in Emerging Markets

Abstract

Firms struggle to be ambidextrous in the sense of being able to successfully manage both new and incremental innovation activities simultaneously. Applying the knowledge-based view, we examine the important moderating influences of supplier involvement and foreignness on the relationship between innovation ambidexterity and performance. We test our hypotheses at the business-unit level of analysis in the emerging market of Brazil. We examine two types of innovation ambidexterity: the balanced dimension and the combined dimension. We found that firms possessing greater supplier involvement reap higher performance benefits from the combined dimension of innovation ambidexterity. Last, foreign subsidiaries also achieved higher levels of performance than domestic firms from the combined dimension of innovation ambidexterity.

Keywords

innovation ambidexterity suppliers foreign subsidiaries knowledge sourcing emerging markets

Few firms are ambidextrous in their approaches to innovation (Durisin & Todorova, 2012; O’Reilly & Tushman, 2008, 2013). The process of attaining innovation ambidexterity is fraught with serious challenges, as firms must be adept at having competitive advantage in both exploration (i.e., the creation of new product possibilities through discovery, risk taking, and flexibility) and exploitation (i.e., the repurposing of old knowledge through incremental improvements to existing product lines via refinement, local search, and production; March, 1991; Tushman & O’Reilly, 1996). Firms capable of managing these contrasting innovation activities simultaneously (Adler, Goldoftas, & Levine, 1999; March, 1991; Tushman & O’Reilly, 1996) have been associated with better firm performance and survival (Gibson & Birkinshaw, 2004; He & Wong, 2004) in different organizational configurations (Simsek, 2009), industries, and environments (Cao, Gedajlovic, & Zhang, 2009). Much scholarly attention to this topic has been examined in terms of its antecedents, such as organizational culture, strategic leadership, and organizational learning (Lin, McDonough, Lin, & Lin, 2013), strategic intent, customer orientation, and personal drivers (Andriopoulos & Lewis, 2009). Yet little is known about the factors that may affect a firm’s ability to manage its exploratory and exploitative innovations activities in a manner that results in better performance, or about how a firm balances these factors across different dimensions of innovation ambidexterity (Raisch, Birkinshaw, Probst, & Tushman, 2009).

In this research, we apply a knowledge-based view (KBV) to the innovation ambidexterity literature and examine how the acquisition of external knowledge, either through greater supplier involvement or through taking advantage of the rich pool of knowledge embedded within a multinational enterprise (MNE), helps firms pursue both exploratory and exploitative innovations simultaneously in a manner that leads to higher levels of performance. To explore these external relationships and influence on innovation ambidexterity, we turn our lens to the study of foreign and domestic business units operating within an emerging market in the complex automotive industry. This context represents an increasing opportunity to study how managers deal with the dynamics of innovation development patterns between domestic firms and foreign subsidiaries of MNEs (Un, 2011). Until quite recently, both domestic and foreign subsidiaries operating in emerging markets focused on providing low-cost raw materials, contract manufacturing, and services to more prominent innovation players located in developed countries (Govindarajan & Ramamurti, 2011). These firms, however, are rapidly migrating up the value chain (Awate, Larsen, & Mudambi, 2012) and showing signs of “catching up,” as evidenced by progressively higher levels of technological innovativeness through complex technological capabilities (Lamin & Dunlap, 2011) and patent activities (Gaze & Roderick, 2012) in key industries such as electronics, information technology, and automotive (Lamin & Dunlap, 2011).

Yet, while this discussion is gaining momentum in the literature (Cao et al., 2009; He & Wong, 2004; Lin et al., 2013), there remains a lack of extensive empirical research on why some firms are better able than others to translate their innovation efforts into higher levels of firm performance (Un, 2011). In this study, we examine two dimensions of innovation ambidexterity and their impact on firm performance. Specifically, we focus on the balanced dimension (i.e., the capacity to simultaneously create new products and incremental product innovations) and the combined dimension (i.e., the capacity to leverage new and incremental product innovations; Cao et al., 2009; He & Wong, 2004) due to their complementary characteristics regarding how firms manage their innovation activities.

Drawing on the KBV perspective, we argue that firms should engage in external knowledge sharing to increase and broaden their stock of knowledge assets available (Leonard-Barton, 1992) and appropriate value from their product innovation endeavors. We study the role that external knowledge acquired from suppliers (e.g., Dyer & Hatch, 2006; Un, Cuervo-Cazurra, & Asakawa, 2010) and being part of an MNE network (Dunlap, Marion, & Friar, 2014; Un et al., 2010) plays in converting innovation ambidexterity into higher levels of firm performance. Empirical studies have found that MNE firms have a knowledge-sourcing advantage over domestic firms (Un, 2011) because they have greater opportunities to share knowledge, values, and assumptions with other subsidiaries (Phene & Almeida, 2008) and with headquarters (Phene & Almeida, 2008; Un, 2011). Research has shown that the acquisition and utilization of knowledge available within a foreign subsidiary network leads to more exploratory innovations (Dunlap et al., 2014; Dunlap-Hinkler, Kotabe, & Mudambi, 2010) and innovative products compared with domestic firms (Un, 2011). Much of this research has been focused on foreign subsidiaries located in developed countries. A goal of this study is to extend this research inquiry to an emerging market context, since it is not yet clear whether foreign subsidiaries enjoy a ubiquitous advantage over domestic firms in both developed and developing countries (Mata & Freitas, 2012; Un, 2011).

Our study contributes to the KBV perspective by advancing our understanding of the role that supplier involvement plays in knowledge acquisition and transfer to firms engaging in both new (i.e., exploratory) and incremental (i.e., exploitative) product innovations in an emerging market context. Specifically, this research sheds light on the dynamic nature of managing and leading innovation ambidexterity successfully and how external knowledge sharing via greater supplier involvement (Narasimhan & Narayanan, 2013) and the advantage of foreignness (Un, 2011) both positively influence the innovation ambidexterity–performance relationship. Our findings bring a new understanding about the characteristics of supplier involvement related to firms’ value appropriation from innovation ambidexterity. Interestingly, we find that greater supplier involvement yields mixed performance results. For the balanced dimension (i.e., the ability to simultaneously create new and incremental innovations), supplier involvement led to negative firm performance. We find, however, that firms achieved higher levels of performance from the combined dimension when suppliers were actively involved. The combined dimension indicates that firms can leverage both exploratory and exploitative innovations as supportive of one another rather than in competition for organizational resources, which can be emblematic of the balanced dimension. This is an important finding, as previous literature has shown that firms can become myopic when reconfiguring the knowledge embedded within different types of innovations, limiting opportunities for both new and incremental innovations (Levinthal & March, 1993). Developing supplier relationships is of key importance if firms want to foster improved innovation ambidexterity. Last, we contribute to the literature by advancing our understanding about the value of foreignness and how it can be a source of innovation. We find that for the combined dimension of innovation ambidexterity, being a foreign subsidiary yielded a positive advantage over domestic firms in reaping performance benefits. Specifically in our sample, foreign subsidiaries from developed markets (Europe, Japan, and the United States) were better able to capitalize on and maximize learning and knowledge-related opportunities embedded within their MNE network (Birkinshaw & Hood, 2001; Frost, 2001). From an organizational leadership perspective, this research also sheds light on how firms can leverage their vendor network for both exploitive and explorative innovations.

Literature Review and Hypotheses

Knowledge Sourcing and Innovation Ambidexterity

Innovation at its core is the translation of knowledge by the firm into the creation of new products and services (Grant, 1996). The knowledge to inform the innovation process can come from internal or external sources, from lead users to suppliers and vendors. The literature has noted that knowledge is a strategic resource of the organization, and those that are better at translating knowledge into new or incremental innovations to seek a competitive advantage are more successful (Eisenhardt & Santos, 2002). This research is grounded in the KBV of the firm (Grant, 1996), as better and more informed sources of knowledge, regardless of their source, can improve the ability of the firm to execute both new and incremental product innovations (Benner & Tushman, 2002; Phene & Almeida, 2008; Subramaniam & Venkatraman, 2001).

While research has shown that nearly 40% of new products or services fail (Barczak, Griffin, & Kahn, 2009), scholars argue in the ambidexterity literature that firms must balance the demands between the exploration of new possibilities through new products (discovery, risk taking, and flexibility) and the exploitation of old knowledge through incremental improvements to existing product lines (refinement, local search, and production) (March, 1991; Tushman & O’Reilly, 1996). In this regard, the study of ambidexterity has been broadly defined in the literature as balancing the seemingly contradictory tensions between exploratory and exploitative activities and the organizational arrangements that support them (Adler et al., 1999; March, 1991; Tushman & O’Reilly, 1996). Various literature streams from strategic management (Lavie & Rosenkopf, 2006), organizational theory, adaptation and behavior (Gibson & Birkinshaw, 2004; Levinthal & March, 1981; ; O’Reilly & Tushman, 2008), and technological and innovation management (Tushman & O’Reilly, 1996) have contributed to the study of organizational ambidexterity (see Raisch & Birkinshaw, 2008; Raisch et al., 2009).

Regarding innovation ambidexterity, which is the focus of this study, scholars (Cao et al., 2009; Gibson & Birkinshaw, 2004; He & Wong, 2004; Lubatkin, Simsek, Ling, & Veiga, 2006) have begun to explore an alternative dimension of ambidexterity—the combined dimension. Unlike the more traditionally known and studied balanced dimension, the combined dimension captures how exploratory and exploitative innovation processes can be supportive of one another rather than in competition for resources. Scholars suggest that the combined dimension requires separate analysis from the balanced dimension. A high level of combinative capabilities indicates that firms are able to leverage the effects of exploratory and exploitative processes. For instance, new products can result from repeated use of existing knowledge (i.e., a high degree of exploitative innovation) that can later create a “pool of competences” that help the firm become more capable of leveraging its resources toward more exploratory innovations and vice versa. For instance, Intel’s existing knowledge in its memory chip business led the firm to seize new trends in the microprocessor industry (Burgelman, 1994; Cao et al., 2009).

Empirically, Cao et al. (2009) found that both balanced and combined types of innovation ambidexterity were positively related to firm performance for 122 small- to medium-size (SMEs) high-tech firms in China. He and Wong (2004) also found that innovation ambidexterity had two positive outcomes: (a) the interaction between exploratory and exploitative innovation (combined dimension) had a positive effect on sales growth and (b) the balance between exploratory and exploitative innovation (balanced dimension) had a positive effect on sales growth. Furthermore, Lin et al. (2013) found that the combination of high levels of both new product and incremental innovations led to higher levels of business performance.

Ambiguity in the literature remains, however, on how firms can appropriate value from their innovation ambidexterity endeavors, be they balanced, combined, or a combination of both, via important moderators and mediators (Raisch et al., 2009). Past research has focused on the moderating effects of a firm’s entrepreneurial orientation (Yang, Lang, & Li, 2010), absorptive capacity (Rothaermel & Alexandre, 2009), size, and other resource endowments (Cao et al., 2009) on the innovation ambidexterity–performance relationship. There is, however, a dearth of research that addresses how learning from and sourcing in external knowledge moderates this relationship (Lee & Veloso, 2008; Lin et al., 2013; Raisch & Birkinshaw, 2008; Raisch et al., 2009). Drawing on the KBV, we investigate the impact of two key sources of knowledge (supplier involvement and MNE–subsidiary network) on a firm’s innovation ambidexterity–performance relationship. The effective use and application of such knowledge can be seen as a key component of successful innovation (Gottfredson, Puryear, & Phillips, 2005). We next discuss how managing innovation ambidexterity can be enhanced through greater external linkages with suppliers, and through the knowledge advantages provided to subsidiaries as part of an MNE network (see Figure 1 for our conceptual model).

Figure 1.

Conceptual model.

Managing Innovation Ambidexterity: The Role of Supplier Involvement and the MNE Network

A primary avenue for firms to source-in the kind of external knowledge diversity required to be ambidextrous is through multiple interorganizational collaborations with clients, suppliers, competitors, alliances, and institutions (Snow, 2015). Recently, scholars have found that collaborations with suppliers provide the greatest amount of essential knowledge and learning benefits for innovation and, thus, is of paramount importance (Dyer & Hatch, 2006; Lau, Tang, & Yam, 2010; Lee & Veloso, 2008; Song & Di Benedetto, 2008). Until recently, much of this research stream has viewed supplier involvement primarily as resources provided, tasks carried out, and responsibilities assumed on the part of the supplier in product or component development (Van Echtelt, Wynstra, Van Weele, & Duysters, 2008). Moreover, supplier involvement is directly and positively associated with improved total product quality, cost reduction, and a decrease in development outlays (Clark, 1989; Kotabe, Parente, & Murray, 2007), as well as radical innovation (Song & Di Benedetto, 2008). Recent literature reviews on this topic highlight an important gap in the ambidexterity literature on how firms source-in knowledge from their suppliers and, moreover, merge this knowledge into their current innovation activities in a manner that leads to higher levels of performance (Narasimhan & Narayanan, 2013; West & Bogers, 2013).

While firms recognize that they need to forge and leverage their most critical supplier relationships to deliver value to their consumers (Dyer & Hatch, 2006), scholars note that to build knowledge-sharing routines with suppliers in order to create new product innovations outside expertise areas can challenge the firm (Lee & Veloso, 2008). For instance, with new product in contrast to product improvements, Wynstra, Von Corswant, and Wetzels (2010) found that suppliers were not always easily influenced to meet the demands of their buyers’ new product requirements. In part, this occurs because such requirements are inherently associated with higher levels of technological uncertainty and failure (Johnsen, 2009; Song & Di Benedetto, 2008), and in some cases, current suppliers may not possess the capabilities to cope with the uncertainty and nonroutine processes necessary to manage new product innovations (Jansen, Van Den Bosch, & Volberda, 2006). Simply put, while the buyer firm may have created something novel, for the supplier to meet the firm’s product demands may be cost prohibitive (Song & Di Benedetto, 2008). Researchers have even suggested that maintaining past collaborative relationships is not as valuable as developing new relationships (Primo & Amundson, 2002) especially for complex tasks involving product development (Zhao, Cavusgil, & Cavusgil, 2014). Faems, Van Looy, and Debackere (2005) argued that firms should approach interorganizational innovation collaboration with a portfolio approach because innovation can be dependent on the type of partner involved. Yet such decisions are not so easily resolved in an emerging market context where interfirm collaborations are not always developed and/or maintained based on efficiency and economic reasons (Luo, 2003; Ó hUallacháin & Wasserman, 1999).

In spite of these challenges and lack of research, we argue that firms will reap higher levels of performance from their innovation ambidexterity when they invest in supplier relationships. Toyota offers an illustrative example. Dyer and Hatch (2006) explored how Toyota was capable of creating a competitive advantage through an identical supplier network shared by its competitors. With the “Toyota Production System,” Toyota was able to replicate “best practice” production routines throughout its supplier network. The firm created a network of learning that resulted in unique knowledge spillovers that were not divulged to their competitors. By engaging in greater knowledge sharing exchanges with its suppliers, Toyota was able to enhance its overall product quality more so than its competitors using the same network. Lau et al. (2010) also found that product codevelopment with suppliers had a positive impact on firm innovation.

In this vein, we argue that investing in suppliers with knowledge, and even financially, can result in an increase in knowledge assets necessary to manage innovation ambidexterity. A KBV perspective recognizes that reciprocal knowledge exchanges of this kind can enhance communication, and decrease issues of mistrust (Barczak & McDonough, 2003; Ó hUallacháin & Wasserman, 1999). Moreover, greater collaboration with suppliers benefits both partners in a way that enhances product development activities (e.g., Khurana & Rosenthal, 1998; Un et al., 2010). Greater synchronized interactions with suppliers can put firms in a better position to cope with the unexpected product development issues that arise from managing simultaneously the exploratory and exploitative innovation processes of innovation ambidexterity (Jansen et al., 2006). Moreover, building knowledge-sharing routines with suppliers may offer the firm greater combinative capabilities, thereby increasing its ability to cope with changing market dynamics (Kogut & Zander, 1993) and improve product development and financial performance (Cousins, Lawson, Petersen, & Handfield, 2011). For these reasons, we hypothesize that greater supplier involvement can act as an important moderator in the innovation ambidexterity–performance relationship for both the balanced and combined dimensions. Stated formally, we hypothesize that

Hypothesis 1a and Hypothesis 1b: Greater supplier involvement will positively moderate the relationship between innovation ambidexterity and performance for (a) the balanced dimension and (b) the combined dimension.

In addition to the valuable knowledge obtained through greater supplier involvement, a recent study found that the knowledge embodied within an MNE and its foreign subsidiaries was one of the most critical knowledge resources in the innovation process, and, more specifically, for exploratory innovations (Dunlap et al., 2014; Dunlap-Hinkler et al., 2010). Increasingly, firms are locating “competence-creating” subsidiaries (Cantwell & Mudambi, 2000, 2005) in strategic international locations to reap the benefits of different national systems of innovation (Coombs, Narandren, & Richards, 1996), and to tap into valuable local knowledge not readily accessible to the firm (Kasper, Lehrer, Mühlbacher, & Müller, 2009; Luo, 2003). There remains a dearth of research, however, and even a debate in the literature on whether and to what degree there is a foreignness innovation advantage (Awate et al., 2012; Duysters & Lokshin, 2011; Zaheer, 1995), particularly in the context of developing economies (Un, 2011). We argue that in such circumstances, managing ambidexterity can be problematic for domestic firms as they likely face greater challenges in creating new products than do foreign firms from developed markets (e.g., Lamin & Dunlap, 2011).

Scholars have suggested that foreign subsidiaries of MNEs have an advantage over domestic firms in being able to capitalize on and maximize learning and knowledge-related opportunities embedded within the MNE (Birkinshaw & Hood, 2001; Frost, 2001). An MNE can be seen as a network of foreign subsidiaries that share knowledge, values, and assumptions with one another (Phene & Almeida, 2008). As part of a network, knowledge that can be used toward the introduction of new products, can be shared within the subsidiary itself, with other subsidiaries located in different countries, and with the MNE’s headquarters (Phene & Almeida, 2008; Un, 2011). For instance, Rugman and Verbeke (2001) identified 10 different types of knowledge developed and diffused within MNEs. In this regard, foreign firms are likely to have greater knowledge and learning opportunities to draw from, compared with domestic firms (Birkinshaw & Hood, 2001; Frost, 2001).

At times, however, foreign subsidiaries can compete with each other for resources (Luo, 2003), yet such competition has been linked to greater innovation capabilities (Un, 2011). Foreign subsidiaries also face pressures to localize their products to meet host country consumer demands. With greater consumer loyalty favoring local products, foreign subsidiaries have an incentive to innovate and provide superior value compared with domestic firms (Un, 2011). In this context, foreign subsidiaries from developed countries may tend to initially develop more exploitative innovations initially, until they gain sufficient local knowledge from which they can create more exploratory innovations (Figueiredo & Brito, 2012). Exploratory innovations are heavily influenced by host country factors such as local consumers, institutions, competitors, and suppliers (Frost, 2001). Given that MNEs are exposed to a greater diversity of knowledge from other host countries and their headquarters (Luo & Jayaraman, 2013; Un, 2011), we argue that foreign subsidiaries from developed countries can have significant advantages over emerging market domestic firms in managing their innovation ambidexterity successfully.

Several studies have characterized firms operating in emerging markets as innovation “laggards” (Altenburg, Schmitz, & Stamm, 2008). The realities of innovation in the emerging market environment can put a strain on domestic firms, especially those with limited innovation capabilities and resources (Luo & Tung, 2007), and outdated technology (Child & Rodrigues, 2005). We argue that facing these disadvantages, coupled with a weaker institutional environment, can cause these firms to be less competitive and also less innovative than developed country foreign subsidiaries. This aggregation of disadvantages can further create a lack of readily available knowledge capabilities for the emerging market firm to apply toward more exploratory product initiatives. As a result of these organizational weaknesses, domestic firms tend to have greater problems in acquiring and transferring knowledge efficiently and effectively within the firm (Keen & Wu, 2011). Their weaknesses can create problems, since developing exploratory and exploitative innovations require greater learning and knowledge transfer (He & Wong, 2004). We hypothesize that foreign subsidiaries from MNEs located in developed country markets possess the “advantage of foreignness” and are more likely to achieve better performance from both dimensions of innovation ambidexterity compared with domestic firms. Thus, we hypothesize that

Hypothesis 2a and Hypothesis 2b: Foreign subsidiaries from developed country markets will have a higher innovation ambidexterity–performance relationship than domestic firms for (a) the balanced dimension and (b) the combined dimension.

Methodology

Empirical Context

We selected an industry within an emerging market that is increasingly innovative. Brazil opened its market to foreign firms in the early 1990s, and its automotive industry now plays a key role in the national economy, accounting for about 5% of gross domestic product today (Gaze & Roderick, 2012). The Brazilian automotive industry has exhibited increased levels of innovation development judged by patents approved from 2001 to 2010, ranking third after industrial electric equipment and digital computers (Gaze & Roderick, 2012). It is known that the automotive industry’s supply chain configuration is characterized by strong interdependencies between assemblers and their suppliers (MacDuffie & Fujimoto, 2010). In this case, scholars have noted that when global automotive manufacturers enter into new markets, they end up developing or creating a whole new supply chain (Humphrey & Memedovic, 2003). Thus, one of the key reasons why countries promote the automotive industry is to incentivize local components industries and to benefit from technological spillover effects (Zilbovicius, Marx, & Salerno, 2002). This pattern was more pronounced in the case of the emerging markets of Brazil, Argentina, and China, during a period of increased trade liberalization policies in the early 1990s. Since these countries had very underdeveloped automotive supplier bases, global assemblers had to invest heavily in the development of local suppliers and also support foreign subsidiaries of key suppliers (Humphrey & Memedovic, 2003).

Investigations of how automotive suppliers utilize their resources and capabilities to sustain competitive advantages abound in the literature (Dyer & Hatch, 2006; Lakshman & Parente, 2008; Lazzarini, Claro, & Mesquita, 2008). However, most of these studies have taken for granted the differences between foreign and domestic firms. In this case, the Brazilian automotive industry is of great relevance for this investigation, as it hosts virtually all global automotive manufacturers and as a consequence, possesses a heterogeneous supply chain composed by foreign and domestic firms. This industry is also ranked as the world’s fifth largest market and the seventh largest producer (Muller, 2012). For these reasons, the Brazilian automotive industry is an appropriate setting for our research objectives (Kotabe et al., 2007).

Sample and Data Collection

To test our hypotheses, we gathered primary data from automotive manufacturers located in Brazil. These firms are well organized through two business associations, Sindipeças and Anfavea. Access to their directories of members was obtained through annual reports. The two lists were cross-referenced with the Brazilian Automotive News magazine, an independent annual publication that profiles firms in the industry. We combined these three data sources, deleting duplicate entries, and sent the questionnaire to 493 firms at the business-unit level, and did so in late 2005 and late 2008. The survey tool was administered to managers at the plant level. To ensure the authenticity of their answers, we administered the survey via mail, kept questions in the third person, and reassured managers that their responses were confidential. We sent follow-up letters and e-mails to managers in an effort to increase our sample size. A total of 136 questionnaires were returned; a response rate of 28% in 2005. In 2008, a second round of questionnaires was sent to these 136 firms. Our matched sample included 123 firms at the business-unit level; 42 were domestic firms and 81 were foreign subsidiaries from developed countries. The matched data set includes firms composed of a variety of ages, sizes, and geographical scope.¹ This sample is representative of similar research studies on foreign subsidiaries (e.g., Un, 2011) and of Brazil’s automotive industry ownership distribution (34% domestic and 66% foreign). Twelve countries were represented: Argentina (n = 1), Austria (n = 1), Brazil (n = 42), France (n = 6), Germany (n = 22), Italy (n = 7), Japan (n = 14), Spain (n = 3), Sweden (n = 1), Switzerland (n = 1), the United Kingdom (n = 2 companies), the United States (n = 23). Firms ranged from 25 to 35 years old and had, on average, between 100 and 500 employees.

Measures

The questionnaire was originally constructed in English, then translated into Portuguese by native speakers, and then back-translated into English to reduce ambiguity in the meanings of the questions. The final questionnaire was administered in Portuguese. All constructs were measured on a 5-point Likert-type scale.

Dependent Variable

Based on previous ambidexterity studies, our firm performance construct was not one dimensional but attempted to measure a broader perspective of performance by including both financial and market measures (e.g., Cao et al., 2009; He & Wong, 2004; Lin et al., 2013; Raisch & Birkinshaw, 2008). Our construct, based on items used in previous studies, consisted of seven measurements: sales growth, market share, profitability, return on investment, return on sales, customer satisfaction, and customer loyalty (Barczak & McDonough, 2003; Narasimhan & Kim, 2002; Worren, Moore, & Cardona, 2002). Respondents were asked to indicate on a 5-point Likert-type scale how their performance compared on these measures with their major competitors’, ranging from much lower (1) to much higher (5). Cronbach’s alpha was .88 (see the appendix for items). The innovation literature notes that new products can take several years to affect a firm’s actual performance (e.g., Blackburn, 2002). To ensure that new products on the market meet safety standards, the development process in this industry is lengthy, highly structured, and highly monitored. Considering the specifics of these product development processes, we used a 3-year time period, given the expected lag effects between innovativeness and its impact on performance.

Independent Variables

Our innovation ambidexterity construct measures the firm’s ability to attain both exploratory and exploitative product innovations simultaneously. We collected information on the firm’s development of both of types of innovation. For our exploratory innovation construct, we asked our respondents to report on the number of entirely new models/products that the firm developed in the past 12 months, an approach that is consistent with previous innovation research (Subramaniam & Venkatraman, 2001) and recent studies (Un, 2011). For our exploitative innovation construct, we recorded the number of new model updates or variant introductions the firm developed in the past 12 months. This delineation is similar to that of Chaney, Devinney, and Winer (1991). We then developed two measures of innovation ambidexterity: the balanced dimension and combined dimension. Early operationalization of both dimensions relied on perceptual measurements of exploratory and exploitative strategies/orientations coming from ex-ante objectives in pursuing innovation. For the balanced dimension (BD), scholars have used the absolute difference between both innovations (i.e., where a higher difference means that the firm has an imbalanced innovation strategy; Cao et al., 2009; He & Wong, 2004). For the combined dimension (CD), scholars have measured ambidexterity as either the sum (Lubatkin et al., 2006) or the product (Cao et al., 2009; Gibson & Birkinshaw, 2004; He & Wong, 2004) of exploration and exploitation strategies and/or orientations. Our measure builds on these ambidexterity measures from an ex-post outcome perspective. For the balanced dimension, our measure captures the proportion of new product innovations to incremental product innovations. Values closer to 1 indicate that the firm has a balance of exploratory and exploitative innovations. For the combined dimension, we measured ambidexterity as the product of exploratory and exploitative innovations. This variable was built by mean centering both measures to reduce multicollinearity.

Moderating Variables

Our supplier involvement construct measures external knowledge sharing and joint collaboration activities between firms and their suppliers. Recent contributions in the literature have found supplier involvement critical to the innovation process. Greater supplier involvement broadens the firm’s technological opportunities and specialized knowledge more so than other external collaborative arrangements (with customers or competitors; e.g., Duysters & Lokshin, 2011; Un et al., 2010). Our construct consisted of seven questions (see the appendix) drawn from items used in previous studies (Dyer & Singh, 1998; Kaufman, Wood, & Theyel, 2000; Takeishi, 2001). First, we asked respondents how well their suppliers grasped their product design, process design, product development, and manufacturing facilities. Second, we asked how well their suppliers interacted with them about different projects. Third, we asked managers how many times they interacted with their suppliers face-to-face. Last, we investigated the strength of the firm–supplier relationship by asking managers how frequently they exchanged information and knowledge with their suppliers. All questions were based on a 5-point Likert-type scale ranging from strongly disagree (1) to strongly agree (5); Cronbach’s alpha was .76.

The level of foreignness is recognized in the literature as being both an opportunity (e.g., Duysters & Lokshin, 2011; Un, 2011) and a disadvantage for new innovation (e.g., Awate et al., 2012; Zaheer, 1995). We created a foreign subsidiary variable, which took the value of 1, if a foreign subsidiary, and 0 if a domestic firm, an approach consistent with previous research (Mezias, 2002; Un, 2011).

Control Variables

To control for firm-level effects on innovation within the emerging market context, we included key variables: age, size, degree of globalization, and modularization. The innovation literature has established that firm size and age can influence the firm’s propensity to innovate (Ahuja & Lampert, 2001). We measured firm size across five categories based on the number of employees: (a) 50 and fewer, (b) 50 to 100, (c) 100 to 250, (d) 250 to 500, and (e) more than 500. We also measured age across five categories according to the firm’s foundation year: (a) before 1920, (b) 1920 to 1970, (c) 1970 to 1980, (d) 1980 to 1990, and (e) after 1990. Given the highly globalized nature of the automotive industry, we asked respondents to report on the degree to which their operations were geographically dispersed. Since this industry has a high degree of modular production, we controlled for the firm’s degree of modularity using items developed in previous studies (Worren et al., 2002); Cronbach’s alpha was .89.

Measurement Validation

We incorporated procedures recommended by researchers to address nonresponse bias, common method variance, construct reliability, and discriminant validity (e.g., Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). We evaluated nonresponse bias using Armstrong and Overton’s (1977) procedure. We performed t tests comparing early (53.5% of the returned questionnaires) and late (46.5%) respondents on randomly selected items involving all variables. There were no signiﬁcant differences on any variables, suggesting a lack of nonresponse bias.

To diminish the possibility of common method variance, we utilized procedural and statistical techniques (Podsakoff et al., 2003). First, we split apart some questions pertaining to the same construct to assure proximal separation in the questionnaire (Podsakoff et al., 2003). Second, we reverse scored some questions to minimize causal connections by respondents on the items (Chang, van Witteloostuijn, & Eden, 2010). Third, before distributing the final version of the questionnaire, we administered the pilot version at the Ford plant in São Bernardo do Campo. An expert at the University of São Paulo helped us refine key terms of the questionnaire items. A Ford plant manager assisted to further refine the items. These experts helped us verify that we were measuring the latent variables completely and consistently.

Fourth, based on the results of our pilot study, we refined and removed some of our measures that exhibited low interquestion correlations. Fifth, we used Harman’s one-factor test to address the common method variance issue. If common method variance were a serious problem, we would expect a single factor to emerge from a factor analysis, or one general factor to account for most of the covariance in the independent and criterion variables (Podsakoff & Organ, 1986). A factor analysis using the entire questionnaire revealed no single factor explaining the majority of the covariance among the variables (Podsakoff et al., 2003). Scholars suggest that independent and dependent variables should not be measured at the same point in time (Podsakoff et al., 2003). We measured dependent variables in 2008 and independent variables in 2005. Then, we performed a robustness check for our dependent variable, firm performance. Few firms in Brazil’s automotive industry have publically available data, but we were able to source performance data for 38 firms in our sample from data provided by two premier business magazines in 2008 (Exame’s top 500 firms and Valor Economico’s top 1,000 firms). Data included total sales, sales growth, profitability, and return on sales. Correlations between the perceptual responses and archival data were high and significant (sales growth: r = .47; profitability: r = .59; return on sales: r = .61, p < .05). We did not detect any common method variance problem.

Regarding the measurement properties and reliability of our constructs, we ran an exploratory factor analysis to assess the discriminant validity of the constructs, which provided acceptable factor loadings (see the appendix). The reliability index of each construct is reported in the appendix. They have acceptable reliability coefficients (Cronbach’s alpha) according to the .70 criterion recommended by Nunnally and Bernstein (1978) and Mendelson and Pillai (1999). Next, we employed a confirmatory factor analysis on the items pertaining to all independent and dependent variables separately. For the independent variables, we found satisfactory results regarding the fit of the data (χ² = 74.46, p < .05; goodness-of-fit index = 0.95; Tucker–Lewis index = 0.94; comparative fit index = 0.96; and root mean square error of approximation = 0.03). For the dependent variable, the confirmatory factor analysis model also produced an adequate fit to the data (χ² = 17.35, p < .01; goodness-of-fit index = 0.98; Tucker–Lewis index = 0.98; comparative fit index = 0.97; and root mean square error of approximation = 0.03). Additionally, we addressed the discriminant validity of our constructs through the analysis of correlation coefficients between constructs (Bagozzi, Yi, & Phillips, 1991). In this case, a high correlation between every two factors indicates a low discriminant validity of constructs where the correlation between pairs of traits should be statistically different than 1 (Schmitt & Stults, 1986). Our analysis shows that all pairs of constructs have a correlation that is statistically different from 1 at p < .001. Since no violations were detected, we concluded that the data were appropriate for our analysis.

Analytical Procedures

To test our hypotheses, we employed multiple regression analysis. We ran several tests to ensure that our data did not violate the assumptions of our methodological procedure. The analysis of variance inflation factors showed mean values below 3 for all models (and highest individual variable variance inflation factor of 4.51 in Model 8), far below the ceiling threshold of 10 (Kleinbaum, Kupper, & Muller, 1988), indicating that our model has no collinearity problems. To examine the moderating effect that supplier involvement (Hypotheses 1a and 1b) and foreign subsidiaries (Hypotheses 2a and 2b) had on the relationship between our innovation ambidexterity–performance relationship, we mean centered our variables before running our interaction terms, which reduced multicollinearity (Jaccard, Wan, & Turrisi, 1990). To verify the impact of our interaction terms, we compared the R² values of the independent-variables model with the interactions-terms model in order to observe changes in the variance explained.

Results

Table 1 provides an overview of all correlations, means, and standard deviations for the variables in this study. Table 1 also shows that the correlation between both ambidexterity measurements (BD and CD) is nonsignificant, which corroborates the fact that both measurements are two distinct dimensions of organizational ambidexterity (Cao et al., 2009; He & Wong, 2004).

Table 1.

Correlation Matrix (N = 123).

	M	SD	1	2	3	4	5	6	7	8	9	10	11
1. Firm performance	3.49	0.63	1.00
2. Age	2.34	1.09	−.08	1.00
3. Size	3.53	1.36	.43	−.20*	1.00
4. Level of internationalization	3.68	1.06	.27**	−.07	.11	1.00
5. Degree of modularization	3.91	0.62	.33**	.01	.37**	.32	1.00
6. Foreign subsidiary	0.65	0.48	.29**	−.19*	.25**	.18*	.30	1.00
7. Supplier involvement	3.83	0.69	.51**	−.02	.53**	.13	.33**	.16	1.00
8. New product innovation	4.25	2.80	.32**	−.13	.09	.09	.03	.17*	.20*	1.00
9. Incremental product innovation	7.45	4.85	.14	−.12	.06	.05	.01	.21*	.11	.76**	1.00
10. Balanced ambidexterity (BD)	0.68	0.32	.31**	−.02	.05	.04	−.03	.05	.21**	.37**	−.15	1.00
11. Combined ambidexterity (CD)	9.46	17.87	−.28**	.05	−.09	−.02	−.13	−.11	−.11	−.15	−.15	−.09	1.00

Significant at the 5% level. **Significant at the 1% level.

Table 2 provides a summary of our hypothesis testing, including the interaction terms. Results for our control variables, from Model 1 (see Table 2), reveal that the effect of firm age on performance was not significant. This result was not surprising since firms in our study were relatively young (younger than 35 years). Moreover, larger firms performed better than smaller firms (b = 0.166, p < .05). Highly internationalized firms also had better levels of performance (b = 0.113, p < .05). Degree of modularization was found to be not significant. Following the innovation ambidexterity literature (Cao et al., 2009; He & Wong, 2004), we added our independent variables incrementally. Model 2 reveals that foreign firms had a marginally significant positive relationship with firm performance. Regarding the effect of supplier involvement, our results show a positive and significant association with firm performance (b = 0.383, p < .01). The innovation variables had differential effects on firm performance. The main effect of new product innovations on firm performance was positive and significant (b = .024, p < .05), and the main effect of incremental innovations on firm performance was negative and significant (b = −0.009, p < .05, see Table 2). Model 3 tests the impact of the balanced dimension of ambidexterity on firm performance (b = 0.748, p < .01) and Model 4 tests the impact of the combined dimension of ambidexterity on firm performance (b = −0.255, p < .01). Model 5 tests both ambidexterity measures concurrently and confirms their particular effect on firm performance.

Table 2.

Results of Multivariate Multiple Regression Analysis (N = 123).

Dependent variable: Firm performance
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8
Age	0.003 (0.052)	0.013 (0.046)	−0.001 (0.043)	0.017 (0.044)	0.004 (0.042)	0.006 (0.039)	0.011 (0.041)	0.007 (0.039)
Size	0.166** (0.038)	0.081** (0.044)	0.083** (0.043)	0.082** (0.041)	0.086** (0.041)	0.098** (0.039)	0.097** (0.042)	0.112*** (0.039)
Level of Internationalization	0.113** (0.048)	0.087** (0.043)	0.092** (0.043)	0.093** (0.043)	0.098** (0.042)	0.078** (0.041)	0.099** (0.041)	0.066* (0.086)
Modularization	0.139 (0.095)	0.065 (0.088)	0.056 (0.086)	0.042 (0.086)	0.041 (0.085)	0.065 (0.092)	0.051 (0.081)	0.078 (0.041)
Foreign subsidiaries		0.186* (0.099)	0.169* (0.101)	0.174* (0.097)	0.158 (0.098)	0.158* (0.097)	0.143 (0.101)	0.152 (0.100)
Supplier involvement		0.383*** (0.127)	0.377*** (0.128)	0.370*** (0.123)	0.363*** (0.128)	0.360*** (0.123)	0.342*** (0.127)	0.339*** (0.121)
New product innovation		0.024*** (0.007)	0.029* (0.017)	0.023*** (0.007)	0.027* (0.016)	0.022 (0.014)	0.031** (0.015)	0.025* (0.014)
Incremental product innovation		−0.009** (0.005)	−0.069** (0.034)	−0.010** (0.005)	−0.057* (0.033)	−0.043 (0.032)	−0.061** (0.031)	−0.042 (0.029)
Balanced dimension (BD)			0.748*** (0.228)		0.665*** (0.223)	0.487** (0.210)	0.589** (0.278)	0.113 (0.309)
Combined dimension (CD)				−0.255*** (0.097)	−0.230** (0.090)	−0.219*** (0.075)	−0.451*** (0.130)	−0.417*** (0.122)
BD * Supplier involvement						−0.632** (0.329)		−0.685** (0.335)
CD * Supplier involvement						0.401*** (0.154)		0.507*** (0.149)
BD * Foreign subsidiaries							0.146 (0.318)	0.549* (0.309)
CD * Foreign Subsidiaries							0.363** (0.178)	0.312** (0.141)
_cons	1.933*** (0.370)	2.471*** (0.392)	2.599*** (0.413)	2.540*** (0.383)	2.590 (0.405)	2.542*** (0.425)	2.491*** (0.393)	2.461*** (0.400)
F value	12.46	10.07	11.24	10.31	11.06	10.59	11.90	12.25
R ²	.34	.37	.43	.45	.46	.48	.49	.52

Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.

For the hypothesis testing, we first examined the moderating effect of supplier involvement on the relationship between the balanced dimension of innovation ambidexterity and firm performance. We hypothesized that higher levels of supplier involvement would positively affect this relationship (see Table 2, Model 6). However, higher levels of supplier involvement negatively and significantly affected the balanced dimension firm performance relationship (b = −0.632, p < .01). Thus, we did not find support for Hypothesis 1a. For Hypothesis 1b, supplier involvement positively moderated the combined dimension of innovation ambidexterity and firm performance (b = 0.401, p < .01), which supports our hypothesis. Regarding the moderating role of foreign subsidiaries on the ambidexterity performance relationship (see Table 2, Model 7), we found a positive but nonsignificant effect for the balanced dimension thus rejecting Hypothesis 2a. With regard to the combined dimension, we found a positive and significant effect, which confirms Hypothesis 2b (b = 0.363, p < .05). This result indicates that foreign subsidiaries from developed countries have an advantage over domestic firms when it comes to managing the combined dimension of innovation ambidexterity. Model 8 shows the regression including all interaction terms, which confirms the aforementioned results.

Implications and Discussion

This study contributes to the literature by examining how firms appropriate value from innovation ambidexterity in an emerging market context. From a KBV perspective, our study provides evidence that the relationship between innovation ambidexterity and firm performance is dynamic (Raisch et al., 2009), and that supplier relationships and being part of an MNE are key contributors to performance. Specifically, we found that external knowledge-related variables such as supplier involvement and membership in a foreign subsidiary network do profoundly alter the combined dimension of innovation ambidexterity and firm performance relationship.

The Importance of Supplier Involvement

Our results provide noteworthy insights into how supplier involvement both affects performance directly, and moderates the relationship between innovation ambidexterity and performance. We find supporting evidence that supplier involvement has a positive impact on firm performance. Our results complement the past four decades of research on this topic (e.g., Clark, 1989; Kotabe et al., 2007). Additionally, we shed new light on the role of suppliers in emerging markets, traditionally overlooked in favor of Triad region research (Johnsen, 2009). We address recent calls in the literature for work on how suppliers can be utilized beyond their function as vehicles for reducing production costs (Johnsen, 2009; Narasimhan & Narayanan, 2013; West & Bogers, 2013). Our results suggest that they also act as valuable resources for tapping into external knowledge diversity (Dyer & Hatch, 2006; Johnsen, 2009; Zhao et al., 2014). As MNEs continue to expand into new and developing markers, being able to better manage and leverage vendor relationships becomes increasingly important. Just as firms such as Toyota have fostered concomitant, mutually beneficial supplier relationships in developed countries such as the United States, large firms seeking to develop beyond traditional original equipment manufacturing and Tiers 1 and 2 boundaries in emerging markets need to develop these knowledge-intensive bonds. Managers should consider this an important imperative for action.

We also examine if firms perform better when they continue to source-in tacit knowledge acquired from their suppliers. We conjecture that when firms face a mismatch in the capabilities and resources shared among their suppliers, they may miss out on opportunities to absorb the rich knowledge and learning opportunities embedded within these relationships. While we hypothesized that maintaining strong supplier relationships throughout the innovation process would lead to a firm’s competitive advantage, we found that, in actuality, the practice of transferring the knowledge obtained from suppliers was not as easy as we initially thought. From an organizational learning perspective, the interaction with suppliers needs to become embedded in the team structure, as this sharing of knowledge is difficult, and needs proactive cultivation. Our results indicate that sourcing-in relationship-specific knowledge from suppliers helped firms reap higher levels of performance from the combined rather than balanced dimension of innovation ambidexterity. For firms arranging their organizations to leverage knowledge of both types of innovation, MNEs from developed countries and their foreign subsidiaries need to implement teams and processes to be inclusive of team communication, collaboration, access to knowledge and information, and project specifics both internally and externally with suppliers. This unified and integrated combined approach reduces barriers to knowledge transfer and fosters the sharing of market specific knowledge so important to local efforts.

Possible reasons for this outcome include that the development of entirely new products in a complex industry like automobiles requires higher levels of tacit knowledge (Dyer & Hatch, 2006; Kotabe et al., 2007). Thus, firms may have more interorganizational knowledge sharing routines focused on incremental rather than entirely new products with their suppliers. Past knowledge of this kind, from a combined dimension perspective, may suggest that firms are able to leverage the knowledge gained from incremental innovations toward the development of entirely new products with their existing suppliers. To this point, having suppliers that have a better overall understanding of the manufacturer’s incremental products and processes may enhance the firm’s ability to appropriate value from the combined dimension. This is understandable, as the development and life cycles of the automotive industry are typically longer than others such as those in the consumer electronics industry.

However, as product development duration and life cycles are increasingly truncated due to global competition, we suggest that firms need to develop a better “match” between their technological product needs and their supplier-related capabilities that allows for greater opportunities to profit from the balanced dimension of innovation ambidexterity. Therefore, there needs to be conscious management and distinction between shorter term management of current products and technology versus longer term roadmaps. It may be advantageous for firms to be involved much earlier in long-term, new product development and technology roadmaps. This is even more critical in industries like automotive and aerospace, where suppliers are increasingly designing and supplying major subsystems. Again, organizations and their leaders need to be conscious of past lessons learned. Almost 30 years ago, Takeuchi and Nonaka (1986) recommended that firms replace their old, sequential process with a new approach—rugby style, passing the “ball” within the team down the field. Given the goal of MNEs seeking to develop subsidiaries and operations in emerging markets, “passing the ball” to cross-functional team members, including suppliers, is perhaps even more important than ever before.

Managing and Leading the Combined Dimension

MNE foreign subsidiaries from developed countries in our study managed the combined dimension of innovation ambidexterity more successfully than domestic firms. This finding supports the literature that foreign subsidiaries have an advantage in developed (Un, 2011) and also emerging market contexts. This finding sheds light on the important role that being part of a foreign subsidiary network plays in the new and incremental product innovation processes. It also supports the current literature’s finding that the acquisition and use of knowledge embedded within an MNE’s foreign subsidiary network, and especially if its headquarters is located in a developed country, has positive innovative outcomes (Dunlap et al., 2014), including those located in emerging markets. As more firms choose to locate “competence creating” subsidiaries in strategic locations (Cantwell & Mudambi, 2000, 2005) and give their managers autonomy to utilize the local knowledge accessible to them in these locations to create new products that fit the needs of local consumers, these decisions could yield long-term positive performance benefits. One example is Volkswagen’s Gol, a subcompact car manufactured by Volkswagen do Brasil for the South American market and the best-selling car in Brazil and Argentina for three decades. Other examples include the 2015 Ford Ranger, a truck developed for global markets, and not sold domestically in the United States. For managers, this research highlights the importance of cultivating a global supplier network that represents a virtuous cycle of knowledge sharing to develop both exploitive and explorative innovations. The lessons learned here go right to the organizational structure and how teams are formed and managed, both inside and outside the corporate walls. Teams need to engage these suppliers early and often. Leadership needs to ensure this type of interactive culture is developed and encouraged throughout the innovation process. To do this, executives and managers need to effectively lead efforts to instill the importance of these supplier relationships and interactions among their innovation teams. Current examples of firms doing this in the automotive industry include Tesla (with partnership with Panasonic) to General Motors (in partnership with LG Chemical). Both firms are intensifying their efforts to advance supplier relationships and knowledge creation, in ways that represent competitive advantages as they develop new innovations. As with many successful initiatives, from Total Quality Management to Lean Six Sigma deployed at firms such as General Electric, implementation and success over the long-term needs to come from strong leadership and persistence (e.g., CEO Jack Welch and the Six Sigma rollout in 1995; Harry & Schroeder, 2005). Moving to a combined dimension of innovation ambidexterity with suppliers may require multiple years of C-suite-level support to effectively embed changes to process and culture. In the Tesla and General Motors examples given above, both CEOs are heavily involved in ensuring these supplier involvement efforts are successful.

Limitations and Concluding Remarks

Our research is subject to the limitations typically associated with cross-sectional survey research. Longitudinal designs would permit more conclusive determinations regarding the direction of causality and the dynamic nature of innovation ambidexterity (Raisch et al., 2009). Moreover, our study is limited to a single industry, minimizing the generalizability of the findings. We acknowledge that the automotive industry has its nuances (i.e., longer product cycle times, capital investment required for new platforms, etc.), and therefore, the study of alternate industries will be essential going forward. Our research is likely to be more germane to highly competitive, mature, and increasingly technologically driven industries ordinarily dominated by large firms (e.g., pharmaceutical industry).

To conclude, our study highlights the possibilities and complexities of managing innovation ambidexterity. We attempted to provide a deeper understanding of how supplier involvement and membership in a foreign subsidiary network influence the dynamic relationship between innovation ambidexterity and firm performance in an emerging market. Our results provide a cautionary concern that supplier relationships may at times limit the firm’s ability to achieve higher levels of performance from the balanced rather than combined dimension of innovation ambidexterity. They also indicate that, while domestic firms and foreign firms operating in emerging markets are attempting to be ambidextrous, domestic firms face significantly more challenges than do foreign firms in the combined dimension. Domestic firms in these emerging markets seeking a combined approach need to strategically align their organizations and supplier relationships in order to realize improvements in their innovation efforts.

Footnotes

Appendix

Variable Descriptions.

Measure and sources	Factor loadings	Description
		Based on your personal opinion, please indicate the degree to which you agree with the following statements.
		1. strongly disagree, 2. somewhat disagree, 3. neither agree nor disagree, 4. agree somewhat, 5. strongly agree
		In the past 12 months, in comparison to our three major competitors
Firm performance
Barczak and McDonough (2003), Narasimhan and Kim (2002), Worren et al. (2002); Cronbach’s alpha = .88	.82	Our firm’s performance measured by sales growth rate was
	.72	Our firm’s performance measured by market share was
	.83	Our firm’s performance measured by profitability was
	.73	Our firm’s performance measured by customer loyalty was
	.72	Our firm’s performance measured by customer satisfaction was
	.78	Our firm’s performance measured by return on investment was
	.68	Our firm’s performance measured by return on sales (ROS) was
Supplier involvement
Dyer and Singh (1998), Kaufman et al. (2000), Takeishi (2001); Cronbach’s alpha = .76	.86	Our major suppliers have a good grasp of our product-design performance
	.77	Our major suppliers have a good grasp of our process-design performance
	.75	Our major suppliers have a good grasp of our product development process
	.79	Our major suppliers have a good grasp of our manufacturing facilities
	.68	Our people develop different product expertise from frequently working and interacting in different projects and product areas
	.79	The relationship between our product development staff and our major suppliers is characterized by considerable face-to-face contact
	.66	We frequently exchange information and knowledge with our suppliers by showing them in person how certain things (e.g., a part or a process) are done
Product modularization
Worren et al. (2002); Cronbach’s alpha = .89	.73	Most of our products have been decomposed into separate modules that can be recombined into new product designs to achieve higher variety and reduce development time
	.84	We can make changes in key components without having to redesign other components
	.69	For our main product(s), we reuse components (carryover) from previous product generations
	.74	We have a high degree of component sharing between different products in our main line
	.81	Overall our firm adopts a high degree of modularity in production

Acknowledgements

The authors gratefully acknowledge that the anonymous comments received from the reviewers affiliated with Bryant University greatly helped improve this article.

Authors’ Note

An earlier version of this article received a best paper award by the Academy of International Business Conference—U.S. Northeast.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Denise Dunlap is an associate professor of strategy and international business at the Keck Graduate Institute of the Claremont Colleges. Her research focuses on global strategy, innovation and global knowledge management, emerging markets, and ethics in international business.

Ronaldo Parente is a Knight Ridder fellow and associate professor of strategy and international business at Florida International University and visiting professor at FGV-EBAPE. His research interests include multinational management in emerging markets, strategic modularization, global supply chain management, innovation, and knowledge management.

José-Mauricio Geleilate is an assistant professor of management in the Manning School of Business at University of Massachusetts Lowell. He currently teaches strategic management courses and his research is focused on innovation management issues, emerging markets, and institutions.

Tucker J. Marion is the Altschuler fellow and associate professor of technological entrepreneurship at Northeastern University’s D’Amore-McKim School of Business. His interdisciplinary research is concentrated on product development, innovation, and entrepreneurship.

References

Adler

P. S.

Goldoftas

Levine

D. I.

(1999). Flexibility versus efficiency? A case study of model change overs in the Toyota production system. Organization Science, 10, 43-68.

Ahuja

Lampert

M. C.

(2001). Entrepreneurship in the large corporation: A longitudinal study of how established firms create breakthrough inventions. Strategic Management Journal, 22, 521-543.

Altenburg

Schmitz

Stamm

(2008). Breakthrough? China’s and India’s transition from production to innovation. World Development, 36, 325-344.

Andriopoulos

Lewis

M. W.

(2009). Exploitation-exploration tensions and organizational ambidexterity: Managing paradoxes of innovation. Organization Science, 20, 696-717.

Armstrong

J. S.

Overton

T. S.

(1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 396-402.

Awate

Larsen

M. M.

Mudambi

(2012). EMNE catch-up strategies in the wind turbin industry: Is there a trade-off between output and innovation capabilities? Global Strategy Journal, 2, 205-223.

Bagozzi

R. P.

Phillips

L. W.

(1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 36, 421-438.

Barczak

Griffin

Kahn

(2009). Perspective: Trends and drivers of success in NPD practices: Results of the 2003 PDMA best practices study. Journal of Product Innovation Management, 26, 3-23.

Barczak

McDonough

(2003, July). The role of trust and project commitment in new product development teams. Paper presented at Portland International Conference on Management of Engineering and Technology, Portland, OR.

10.

Benner

M. J.

Tushman

(2002). Process management and technological innovation: A longitudinal study of the photography and paint industries. Administrative Science Quarterly, 47, 676-707.

11.

Birkinshaw

Hood

(2001). Unleash innovation in foreign subsidiaries. Harvard Business Review, 79(3), 131-137.

12.

Blackburn

J. D.

(2002). Valuing time in make-to-stock manufacturing: Calculating the limits of time-based competition. In Klose

Speranza

Van Wassenhove

(Eds.), Quantitative approaches to distribution logistics and supply chain management (pp. 19-35). Berlin, Germany: Springer.

13.

Burgelman

R. A.

(1994). Fading memories: A process theory of strategic business exit in dynamic environments. Administrative Science Quarterly, 39, 24-56.

14.

Cantwell

Mudambi

(2000). The location of MNE R&D activity: The role of investment incentives. Management International Review, 40(1), 127-148.

15.

Cantwell

Mudambi

(2005). MNE competence-creating subsidiary mandates. Strategic Management Journal, 26, 1109-1128.

16.

Cao

Gedajlovic

Zhang

(2009). Unpacking organizational ambidexterity: Dimensions, contingencies, and synergistic effects. Organization Science, 20, 781-796.

17.

Chaney

P. K.

Devinney

T. M.

Winer

R. S.

(1991). The impact of new product introductions on the market value of firms. Journal of Business, 1, 573-610.

18.

Chang

S. J.

van Witteloostuijn

Eden

(2010). From the editors: Common method variance in international business research. Journal of International Business Studies, 41, 178-184.

19.

Child

Rodrigues

S. B.

(2005). The internationalization of Chinese firms: A case for theoretical extension? Management and Organization Review, 1, 381-410.

20.

Clark

K. B.

(1989). Project scope and project performance: The effect of parts strategy and supplier involvement on product development. Management Science, 35, 1247-1263.

21.

Coombs

Narandren

Richards

(1996). A literature-based innovation output indicator. Research Policy, 25, 403-413.

22.

Cousins

P. D.

Lawson

Petersen

K. J.

Handfield

R. B.

(2011). Breakthrough scanning, supplier knowledge exchange, and new product development performance. Journal of Product Innovation Management, 28, 930-942.

23.

Dunlap

Marion

Friar

(2014). The role of cross-national knowledge on organizational ambidexterity: A case of the global pharmaceutical industry. Management Learning, 45, 458-476.

24.

Dunlap-Hinkler

Kotabe

Mudambi

(2010). A story of breakthrough versus incremental innovation: Corporate entrepreneurship in the global pharmaceutical industry. Strategic Entrepreneurship Journal, 4, 106-127.

25.

Durisin

Todorova

(2012). A study of the performativity of the “ambidextrous organizations” theory: Neither lost in nor lost before translation. Journal of Product Innovation Management, 29(Suppl. 1), 53-75.

26.

Duysters

Lokshin

(2011). Determinants of alliance portfolio complexity and its effect on innovative performance of companies. Journal of Product Innovation Management, 28, 570-585.

27.

Dyer

J. H.

Hatch

N. W.

(2006). Relation-specific capabilities and barriers to knowledge transfers: Creating advantage through network relationships. Strategic Management Journal, 27, 701-719.

28.

Dyer

J. H.

Singh

(1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23, 660-679.

29.

Eisenhardt

K. M.

Santos

F. M.

(2002). Knowledge-based view: A new theory of strategy. In Pettigrew

Thomas

Whittington

(Eds.), Handbook of strategy and management (pp. 139-164). Thousand Oaks, CA: Sage.

30.

Faems

Van Looy

Debackere

(2005). Interorganizational collaboration and innovation: Toward a portfolio approach. Journal of Product Innovation Management, 22, 238-250.

31.

Figueiredo

P. N.

Brito

K. N.

(2012). MNE-subsidiaries’ innovation capability building and learning in emerging economies: Firm level evidence from the ICT industry in Brazil. International Journal of Innovation and Learning, 11, 12-43.

32.

Frost

T. S.

(2001). The geographic sources of foreign subsidiaries’ innovations. Strategic Management Journal, 22, 101-123.

33.

Gaze

Roderick

(2012). The grown up BRIC: Innovation and brand expansion in Brazil. New York, NY: Thomson Reuters.

34.

Gibson

C. B.

Birkinshaw

(2004). The antecedents, consequences, and mediating role of organizational ambidexterity. Academy of Management Journal, 47, 209-226.

35.

Gottfredson

Puryear

Phillips

(2005). Strategic sourcing. Harvard Business Review, 83(2), 132-139.

36.

Govindarajan

Ramamurti

(2011). Reverse innovation, emerging markets, and global strategy. Global Strategy Journal, 1, 191-205.

37.

Grant

R. M.

(1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17(Suppl. 2), 109-122.

38.

Harry

M. J.

Schroeder

R. R.

(2005). Six sigma: The breakthrough management strategy revolutionizing the world’s top corporations. New York, NY: Broadway Business.

39.

Z. L.

Wong

P. K.

(2004). Exploration vs. exploitation: An empirical test of the ambidexterity hypothesis. Organization Science, 15, 481-494.

40.

Humphrey

Memedovic

(2003). The global automotive industry value chain: What prospects for upgrading by developing countries (UNIDO Sectorial Studies Series). Retrieved from https://www.unido.org/fileadmin/user_media/Publications/Pub_free/Global_automotive_industry_value_chain.pdf

41.

Jaccard

Wan

C. K.

Turrisi

(1990). The detection and interpretation of interaction effects between continuous variables in multiple regression. Multivariate Behavioral Research, 25, 467-478.

42.

Jansen

J. J.

Van Den Bosch

F. A.

Volberda

H. W.

(2006). Exploratory innovation, exploitative innovation, and performance: Effects of organizational antecedents and environmental moderators. Management Science, 52, 1661-1674.

43.

Johnsen

T. E.

(2009). Supplier involvement in new product development and innovation: Taking stock and looking to the future. Journal of Purchasing and Supply Management, 15, 187-197.

44.

Kasper

Lehrer

Mühlbacher

Müller

(2009). Integration-responsiveness and knowledge-management perspectives on the MNC: A typology and field study of cross-site knowledge-sharing practices. Journal of Leadership & Organizational Studies, 15, 287-303.

45.

Kaufman

Wood

C. H.

Theyel

(2000). Collaboration and technology linkages: A strategic supplier typology. Strategic Management Journal, 21, 649-663.

46.

Keen

(2011). An ambidextrous learning model for the internationalization of firms from emerging economies. Journal of International Entrepreneurship, 9, 316-339.

47.

Khurana

Rosenthal

S. R.

(1998). Towards holistic “front ends” in new product development. Journal of Product Innovation Management, 15, 57-74.

48.

Kleinbaum

D. G.

Kupper

L. L.

Muller

K. E.

(1988). Applied regression analysis and other multivariate analysis methods. Boston, MA: PWS-Kent.

49.

Kogut

Zander

(1993). Knowledge of the firm and the evolutionary theory of the multinational corporation. Journal of International Business Studies, 24, 625-645.

50.

Kotabe

Parente

Murray

J. Y.

(2007). Antecedents and outcomes of modular production in the Brazilian automobile industry: A grounded theory approach. Journal of International Business Studies, 38, 84-106.

51.

Lakshman

Parente

R. C.

(2008). Supplier-focused knowledge management in the automobile industry and its implications for product performance. Journal of Management Studies, 45, 317-342.

52.

Lamin

Dunlap

(2011). Complex technological capabilities in emerging economy firms: The role of organizational relationships. Journal of International Management, 17, 211-228.

53.

Lau

A. K.

Tang

Yam

(2010). Effects of supplier and customer integration on product innovation and performance: Empirical evidence in Hong Kong manufacturers. Journal of Product Innovation Management, 27, 761-777.

54.

Lavie

Rosenkopf

(2006). Balancing exploration and exploitation in alliance formation. Academy of Management Journal, 49, 797-818.

55.

Lazzarini

S. G.

Claro

D. P.

Mesquita

L. F.

(2008). Buyer–supplier and supplier–supplier alliances: Do they reinforce or undermine one another? Journal of Management Studies, 45, 561-584.

56.

Lee

Veloso

F. M.

(2008). Interfirm innovation under uncertainty: Empirical evidence for strategic knowledge partitioning. Journal of Product Innovation Management, 25, 418-435.

57.

Leonard-Barton

(1992). Core capabilities and core rigidities: A paradox in managing new product development. Strategic Management Journal, 13, 111-125.

58.

Levinthal

D. A.

March

J. G

. (1981). A model of adaptive organizational search. Journal of Economic Behavior & Organization, 2, 307-333.

59.

Levinthal

D. A.

March

J. G

. (1993). The myopia of learning. Strategic Management Journal, 14, 95-112.

60.

Lin

H.-E.

McDonough

E. F.

Lin

S.-J.

Lin

C. Y.-Y.

(2013). Managing the exploitation/exploration paradox: The role of a learning capability and innovation ambidexterity. Journal of Product Innovation Management, 30, 262-278.

61.

Lubatkin

M. H.

Simsek

Ling

Veiga

J. F.

(2006). Ambidexterity and performance in small- to medium-sized firms: The pivotal role of top management team behavioral integration. Journal of Management, 32, 646-672.

62.

Luo

(2003). Industrial dynamics and managerial networking in an emerging market: The case of China. Strategic Management Journal, 24, 1315-1327.

63.

Luo

Jayaraman

(2013). Entry strategies in business process offshoring. Journal of Leadership & Organizational Studies, 20, 448-464.

64.

Luo

Tung

R. L.

(2007). International expansion of emerging market enterprises: A springboard perspective. Journal of International Business Studies, 38, 481-498.

65.

MacDuffie

J. P.

Fujimoto

(2010). Why dinosaurs will keep ruling the auto industry. Harvard Business Review, 88(6), 23-25.

66.

March

J. G.

(1991). Exploration and exploitation in organizational learning. Organization Science, 2, 71-87.

67.

Mata

Freitas

(2012). Foreignness and exit over the life cycle of firms. Journal of International Business Studies, 43, 615-630.

68.

Mendelson

Pillai

R. R.

(1999). Industry intra-organizational learning: Measurement and operational implications. Manufacturing and Service Operations Management, 1(1), 1-20.

69.

Mezias

J. M.

(2002). How to identify liabilities of foreignness and assess their effects on multinational corporations. Journal of International Management, 8, 265-282.

70.

Muller

(2012). Why the world’s automakers love Brazil? Retrieved from http://www.forbes.com/sites/joannmuller/2012/10/05/why-the-worlds-automakers-are-loving-brazil/#45d36f7bc20f

71.

Narasimhan

Kim

S. W.

(2002). Effect of supply chain integration on the relationship between diversiﬁcation and performance: Evidence from Japanese and Korean ﬁrms. Journal of Operations Management, 20, 303-323.

72.

Narasimhan

Narayanan

(2013). Perspectives on supply network–enabled innovations. Journal of Supply Chain Management, 49(4), 27-42.

73.

Nunnally

J. C.

Bernstein

(1978). Psychometry theory. New York, NY: McGraw-Hill.

74.

Ó hUallacháin

Wasserman

. (1999). Vertical integration in a lean supply chain: Brazilian automobile component parts. Economic Geography, 75, 21-42.

75.

O’Reilly

C. A.

III Tushman

M. L.

(2008). Ambidexterity as a dynamic capability: Resolving the innovator’s dilemma. Research in Organizational Behavior, 28, 185-206.

76.

O’Reilly

C. A.

III Tushman

M. L.

(2013). Organizational ambidexterity: Past, present and future. Academy of Management Perspectives, 27, 324-338.

77.

Phene

Almeida

(2008). Innovation in multinational subsidiaries: The role of knowledge assimilation and subsidiary capabilities. Journal of International Business Studies, 39, 901-919.

78.

Podsakoff

P. M.

MacKenzie

S. B.

Lee

J. Y.

Podsakoff

N. P.

(2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879-903.

79.

Podsakoff

P. M.

Organ

D. W.

(1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12, 531-544.

80.

Primo

M. A.

Amundson

S. D.

(2002). An exploratory study of the effects of supplier relationships on new product development outcomes. Journal of Operations Management, 20, 33-52.

81.

Raisch

Birkinshaw

(2008). Organizational ambidexterity: Antecedents, outcomes, and moderators. Journal of Management, 34, 375-409.

82.

Raisch

Birkinshaw

Probst

Tushman

M. L.

(2009). Organizational ambidexterity: Balancing exploitation and exploration for sustained performance. Organization Science, 20, 685-695.

83.

Rothaermel

F. T.

Alexandre

M. T.

(2009). Ambidexterity in technology sourcing: The moderating role of absorptive capacity. Organization Science, 20, 759-780.

84.

Rugman

A. M.

Verbeke

(2001). Subsidiary-specific advantages in multinational enterprises. Strategic Management Journal, 22, 237-250.

85.

Schmitt

Stults

D. M.

(1986). Methodology review: Analysis of multitrait-multimethod matrices. Applied Psychological Measurement, 10, 1-22.

86.

Simsek

(2009). Organizational ambidexterity: Towards a multilevel understanding. Journal of Management Studies, 46, 597-624.

87.

Snow

C. C.

(2015). Organizing in the age of competition, cooperation, and collaboration. Journal of Leadership & Organizational Studies, 22, 433-442.

88.

Song

Di Benedetto

C. A.

(2008). Supplier’s involvement and success of radical new product development in new ventures. Journal of Operations Management, 26, 1-22.

89.

Subramaniam

Venkatraman

(2001). Determinants of transnational new product development capability: Testing the influence of transferring and deploying tacit overseas knowledge. Strategic Management Journal, 22, 359-378.

90.

Takeishi

(2001). Bridging inter- and intra-ﬁrm boundaries: Management of supplier involvement in automobile product development. Strategic Management Journal, 22, 403-433.

91.

Takeuchi

Nonaka

(1986, January). The new new product development game. Harvard Business Review, 137-146.

92.

Tushman

O’Reilly

(1996). Evolution and revolution: Mastering the dynamics of innovation and change. California Management Review, 38(4), 8-30.

93.

C. A.

(2011). The advantage of foreignness in innovation. Strategic Management Journal, 32, 1232-1242.

94.

C. A.

Cuervo-Cazurra

Asakawa

(2010). R&D collaborations and product innovation. Journal of Product Innovation Management, 27, 673-689.

95.

Van Echtelt

F. E.

Wynstra

Van Weele

A. J.

Duysters

. (2008). Managing supplier involvement in new product development: A multiple-case study. Journal of Product Innovation Management, 25, 180-201.

96.

West

Bogers

(2013). Leveraging external sources of innovation: A review of research on open innovation. Journal of Product Innovation Management, 31, 814-831.

97.

Worren

Moore

Cardona

(2002). Modularity, strategic flexibility, and firm performance: A study of the home appliance industry. Strategic Management Journal, 23, 1123-1140.

98.

Wynstra

Von Corswant

Wetzels

(2010). In chains? An empirical study of antecedents of supplier product development activity in the automotive industry. Journal of Product Innovation Management, 27, 625-639.

99.

Yang

Lang

(2010, May). Ambidextrous capabilities and innovation performance—The moderating effect of entrepreneurial orientation. Paper presented at International Conference on IEEE, Guangzhou, China. doi:10.1109/ICEE.2010.279

100.

Zaheer

(1995). Overcoming the liability of foreignness. Academy of Management Journal, 38, 341-363.

101.

Zhao

Cavusgil

S. T.

(2014). An investigation of the black-box supplier integration in new product development. Journal of Business Research, 67, 1058-1064.

102.

Zilbovicius

Marx

Salerno

M. S.

(2002). A comprehensive study of the transformation of the Brazilian automotive industry. International Journal of Automotive Technology and Management, 2, 10-23.