Jimk.17.2.00

The Trade-Off Between Customer
and Technology Orientations:
Impact on Innovation Capabilities
and Export Performance
Paula Hortinha, Carmen Lages, and Luis Filipe Lages Technological exporters are constantly challenged by the trade-off between two types of strategic orientations: customerand technology. Nonetheless, research directly addressing this topic is scarce, and few recommendations exist about thebest orientation to emphasize. Using two respondents in the same firm, the export manager and the research-and-development manager, the authors find that customer orientation is as important as technological orientation in thedevelopment of exploratory innovation capabilities. However, when past performance is poor, customer orientation hasa greater role. Exporters with poor past performance may achieve higher export performance levels by focusing moreon customers than on technology. Conversely, firms performing well may risk export performance if they ignore tech-nology orientation. These firms also need to maintain high levels of customer orientation. Keywords: exporters, innovation, customer orientation, technology orientation, past performance
Researchers agree that firms need to pursue cus- and Tse 2005). However, despite the many and broadly tomer and technological competences simultane- recognized benefits of a customer orientation (Jaworski ously because both provide a foundation for inno- and Kohli 1993; Narver and Slater 1990), firms may vation (Danneels 2002; Gatignon and Xuereb 1997; lose their innovation competences if they are too cus- Yalcinkaya, Calantone, and Griffith 2007; Zhou, Yim, tomer focused (Christensen and Bower 1996; Hameland Prahalad 1994; Im and Workman 2004). Becausecustomers are not completely knowledgeable about thelatest market or technological trends, exporters that Paula Hortinha is Marketing Director at Jerónimo Mar-
overly rely on customers may overlook technological tins, Portugal, and is affiliated with Nova School of opportunities and therefore become stuck developing Business and Economics, Faculdade de Economia, Lis- incremental innovations. Conversely, an excessive tech- bon, Portugal (e-mail: phortinha@novasbe.pt). Carmen
nology orientation may lead to unsuccessful innovation Lages is Assistant Professor, ISCTE Business School,
(Gatignon and Xuereb 1997; Kleinschmidt and Cooper Lisbon University Institute, Portugal. Part of this research was conducted while she was a VisitingScholar at the Massachusetts Institute of Technology’s The trade-off between customer orientation and tech- Deshpande Center for Technological Innovation (e- nology orientation is of utmost importance and presents mail: carmen.lages@iscte.pt). Luis Filipe Lages is Asso-
ciate Professor, Nova School of Business and Econom-
ics, Faculdade de Economia, Lisbon, Portugal. Part of
Journal of International Marketing
this research was conducted while he was an Inter-national Faculty Fellow in the Massachusetts Institute 2011, American Marketing Association
of Technology Sloan School of Management (e-mail: lflages@novasbe.pt; www.lflages.com).
ISSN 1069-0031X (print) 1547-7215 (electronic) a key challenge to exporters because it is intrinsically and Rajiv 1999; Mohr and Sarin 2009; Mohr, Sengupta, linked to innovation. Nevertheless, resources are limited, and Slater 2010). In addition, the notion that a technology and firms must make choices in their allocation and orientation is inherent to technological firms is no guaran- determine the extent to which they will emphasize one strategic orientation over another (Danneels 2007; Lant,Milliken, and Batra 1992). Although the individual roles Finally, we extend our research by examining the trade- of customer and technology orientations on innovation off between customer orientation and technology orien- and performance have attracted considerable attention tation under the contingency effect of the past perfor- (e.g., Gao, Zhou, and Yim 2007; Gatignon and Xuereb mance of the firm. Organizational learning literature 1997; Jeong, Pae, and Zhou 2006; Zhou, Yim, and Tse demonstrates that firms tend to rely on their past experi- 2005), few studies have assessed their relative impact— ence and performance in decision making (Cyert and that is, the difference in the strengths of the relationships March 1963; Lages, Jap, and Griffith 2008; Lant and between customer orientation and innovation and Mezias 1992; Levinthal and March 1981). More specifi- between technology orientation and innovation.
cally, past performance affects innovation-related deci-sions because of limited resources (Durmus,og˘lu et al.
Drawing on organizational learning literature, we examine 2008). We follow a different perspective from that of how customer and technology orientations relate to inno- researchers exploring the impact of past performance on vation capabilities to contribute to exporters’ performance.
strategy; that is, we use past performance as a modera- Thus, we consider the mediating role of two distinct capa- tor rather than an antecedent of firm strategy, investi- bilities—exploratory innovation and exploitative innova- gating whether technological exporters respond differ- tion—on the relationships between strategic orientations ently under different scenarios of past performance.
and performance. Exploratory innovation includes activi-ties aimed to enter new product-market domains, whileexploitative innovation activities improve existing product-market domains (He and Wong 2004). High- performing firms go beyond gathering and understandingmarket and technological information to also translate Organizational learning represents the development of that knowledge into learning (Noble, Sinha, and Kumar knowledge that influences behavioral changes and leads 2002). Research supports the view that firm capabilities, to enhanced performance (Crossan, Lane, and White such as strategic orientations, do not directly lead to better 1999; Fiol and Lyles 1985). Product innovation is a tool performance; instead, organizational learning behaviors for organizational learning and, thus, a primary means act as mediators (Atuahene-Gima 2005; Baker and Sinkula of achieving its strategic renewal (Danneels 2002; 2007; Zhou, Yim, and Tse 2005). In this study, we advance Dougherty 1992). Renewal demands that firms explore the literature by allowing for a mediating role of and assimilate new knowledge while exploiting what exploratory and exploitative innovations while also con- has already been learned. These two learning capabili- sidering customer and technology orientations. Moreover, ties are known as exploration and exploitation (March we provide insights into how choices about emphasizing 1991). Exploration pertains more to new knowledge— one strategic orientation over another affects the balance such as the search for new products, ideas, markets, or between exploration and exploitation.
relationships; experimentation; risk taking; and discov-ery—while exploitation pertains more to using the exist- Research typically addresses these trade-offs in a domestic ing knowledge and refining what already exists; it context. This is surprising, given that innovation and inter- includes adaptation, efficiency, and execution (March nationalization are critical drivers of today’s businesses 1991). Exploration and exploitation compete for the and economies. Firms can leverage their innovations by same resources and efforts in the firm. With a focus on acting on business opportunities in international markets exploring potentially valuable future opportunities, the (Knight and Cavusgil 2004). In this study, we explore the firm decreases activities linked to improving existing topic in the context of technological exporters. Though competences (Levinthal and March 1993; March 1991).
valid for any organization, our topic is particularly impor- In contrast, with a focus on exploiting existing products tant for technological exporters. Because such firms oper- and processes, the firm reduces development of new ate in international markets with highly complex environ- opportunities. However, firms must develop both ments and high technological and demand uncertainties, exploratory and exploitative capabilities because they require sophisticated marketing (Dutta, Narasimhan, returns from exploration are uncertain, often negative, The Trade-Off Between Customer and Technology Orientations 37 and attained over the long run, while exploitation gen- cle for renewing other firm capabilities, such as strategic erates more positive, proximate, and predictable returns orientations, and achieving superior performance. We (Levinthal and March 1993; March 1991; Özsomer and theorize that strategic orientations affect performance Gençtürk 2003). Researchers have shown that both through exploratory and exploitative innovation. We types of learning are essential to enhancing firm perfor- specifically address the performance of technological mance (Leonard-Barton 1992; March 1991). In this exporters. International markets are turbulent and study, we use exploration and exploitation to describe diverse with respect to customer needs, cultures, and two innovation-related capabilities that a firm must competitiveness; therefore, innovation assumes a pri- develop to attain superior performance.
mary role (Kleinschmidt, De Brentani, and Salomo2007). Firms can leverage their innovations by securing Strategic orientations are capabilities that reflect the business opportunities in those markets and thus strategic directions a firm takes to create the appropri- increase their innovative capabilities (Knight and Cavus- ate behaviors for continuous superior performance gil 2004). Through exploratory innovation, firms (Day 1994; Narver and Slater 1990). These behaviors develop new competences and thus achieve superior assume the generation and dissemination of informa- export performance by attaining positions of market tion (Gatignon and Xuereb 1997; Jaworski and Kohli and technological leadership (Teece, Pisano, and Shuen 1993; Narver and Slater 1990). Because this informa-
1997). Exploitation activities are also important to tion must be transformed into knowledge, strategic ori- exporters because they facilitate the lower-risk exten- entations are linked to learning behaviors and therefore sion of export operations. Furthermore, by searching for to innovation capabilities (Atuahene-Gima 2005; Baker solutions in the existent competence base, exploitative and Sinkula 2007; Noble, Sinha, and Kumar 2002; innovation increases efficiency and productivity.
Slater and Narver 1995). With their focus on informa-tion processing, strategic orientations greatly enhance We further theorize about the influence of past perfor- the firm’s learning capabilities. Without the ability to mance of the firm on the strategic orientation– use and act on information (learning), strategic orienta- innovation relationship. Past performance influences tions would not affect performance. Two critical strate- available resources, and these determine the innovation gic orientations linked to innovation are customer ori- focus toward more or less exploratory activities (Cyert entation and technology orientation (Gatignon and and March 1963; Singh 1986). Figure 1 depicts the Xuereb 1997; Zhou, Yim, and Tse 2005). Research hypotheses in this research framework.
emphasizes that innovation requires that firms havecapabilities related to technology and customers (Dan- neels 2002; Dougherty 1992). Customer orientation is the understanding and monitoring of customers andtheir needs (for a review, see Kirca, Jayachandran, and Firms with a strong customer orientation have a Bearden 2005). It includes gathering knowledge about competitive advantage because they consider the crea- current and future customers and disseminating that tion and maintenance of customer value a top priority knowledge in the firm (Jaworski and Kohli 1993).
(Narver and Slater 1990; Olson, Slater, and Hult 2005).
Technology orientation is “the ability and the will to Thus, customer orientation is broadly recognized as a acquire a substantial technological background and use driver of business performance (Han, Kim, and Srivas- it in the development of new products” (Gatignon and tava 1998; Hult and Ketchen 2001; Hurley and Hult Xuereb 1997, p. 78). A technology-oriented firm is 1998; Jaworski and Kohli 1993; Narver and Slater committed to research and development (R&D) and is 1990). Performance benefits from technology orienta- proactive in acquiring and integrating new and sophis- tion have also been demonstrated, particularly in export- ticated technologies in the new product development ing and technological contexts (Dutta, Narasimhan, process (Slater, Hult, and Olson 2007; Zhou, Yim, and and Rajiv 1999; Filatotchev et al. 2008; Gao, Zhou, Tse 2005). The technology orientation also promotes and Yim 2007; Workman 1993; Zou, Fang, and Zhao openness to ideas that use state-of-the art technologies, 2003). However, research supports the view that strate- in contrast to a customer orientation, which favors gic orientations as firm capabilities do not directly lead ideas that better satisfy customer needs.
to better performance; instead, organizational learningcompetences mediate the relationship (Atuahene-Gima In this article, we use organizational learning theory to 2005; Baker and Sinkula 2007; Zhou, Yim, and Tse support the idea that innovation capabilities are a vehi- Figure 1. Proposed Theoretical Framework
Control Variables
Performance
Strategic
Innovation
Orientations
Capabilities
Customer-oriented firms can effectively combine explo- Thomas 1992). For example, firms introduce more radi- ration and exploitation (Kyriakopoulos and Moorman cal innovations by focusing on future customers 2004). These firms are committed to understanding and (Chandy and Tellis 1998). Moreover, for innovation to serving the needs of current customers; therefore, they be successful, customers must be aware of the product excel in searching for and using market information for adoption to accelerate (Sorescu, Chandy, and Prabhu (Day 1994). By leveraging their customer knowledge, 2003). Another example of the importance of customer they can become aware of market opportunities and orientation in the development of exploratory innova- improve their existing processes and resources (Yal- tion capabilities is when exporters develop new tech- cinkaya, Calantone, and Griffith 2007). An exporting nologies; firms must identify which customers are firm might fine-tune products and services to better sat- appropriate for the products developed with those tech- isfy existing customer needs. For example, a firm might nologies to ensure their success (Yalcinkaya, Calantone, strengthen relationships with its customers in existing export markets (Lages, Lages, and Lages 2005). Thus, acustomer orientation directly benefits an exploitative H1b: Exploratory innovation mediates the rela- tionship between customer orientation andexport performance.
H1a: Exploitative innovation mediates the rela- tionship between customer orientation and Empirical evidence suggests that technology orientation has a positive relationship to innovation (Gatignon andXuereb 1997; Li and Calantone 1998; Song and Parry A customer-oriented firm not only responds to existing 1997). Technology-oriented firms are technically profi- customer needs but also uncovers latent needs and cient and flexible, which facilitates the refinement of anticipates future needs (Chandy and Tellis 1998; Day existing technologies either to cope with existing mar- 1994; Slater and Narver 1995). Thus, such firms must kets or to leverage market research efforts and try new build on new capabilities (exploration), as existing ones markets (Danneels 2007). A technology-oriented firm is (exploitation) become inadequate (Huff, Huff, and technologically diverse because of its commitment to The Trade-Off Between Customer and Technology Orientations 39 enrich its technological knowledge base (Katila and In general, a customer orientation is more important Ahuja 2002). Quintana-Garcia and Benavides-Velasco than a technology orientation when developing (2008) find that technological diversity (i.e., scope of a exploitative innovation capabilities (Baker and Sinkula firm’s technological knowledge) is positively related to 2007; Yalcinkaya, Calantone, and Griffith 2007). In exploratory and exploitative innovation competences.
exploitation, the firm develops new products by refining Firms with technology diversity have more expertise in and recombining existing technological and customer similar technologies, thus increasing the possibilities of competences (Danneels 2002; March 1991). As such, technological combinations. The resultant technologies exploitative learning increases efficiency through the may improve products and services, resulting in discovery and use of solutions from the firm’s current exploitative innovations. Moreover, existing customers experience. Customer-oriented firms are knowledgeable are often offered new products that incorporate new about their customers and excel in finding solutions to technologies that incrementally enhance existing prod- meet their needs (Day 1994; Jaworski and Kohli 1993).
ucts (Yalcinkaya, Calantone, and Griffith 2007). Thus: Exploitative learning generally leads to incrementalinnovations, which consist of product improvements H2a: Exploitative innovation mediates the rela- and line extensions that aim to serve existing customers tionship between technology orientation and (Atuahene-Gima 2005; Baker and Sinkula 2007). To develop incremental innovations, firms use existingtechnologies (Chandy and Tellis 1998). According to A technological ability also favors experimentation with Yalcinkaya, Calantone, and Griffith (2007), because new alternatives to meet emerging technological trends exploitation involves leveraging existing knowledge and (March 1991). Exporters with more diverse technologi- capitalizing on existing opportunities, a deep under- cal knowledge capture more opportunities and tend to standing of current market needs is more beneficial to develop more radical innovations (Quintana-Garcia and those activities than the firm’s technological resources.
Benavides-Velasco 2008). Researchers acknowledge that Moreover, the more incremental the innovations are, the to develop truly new innovations, firms need strong lower are the levels of technology orientation needed to technological capabilities (Gatignon and Xuereb 1997; deploy those innovations (Gatignon and Xuereb 1997).
Workman 1993). Therefore, a technology orientation is important for exploratory innovation.
H3: Customer orientation relates more strongly H2b: Exploratory innovation mediates the rela- than technology orientation to exploitative tionship between technology orientation and Although prior findings related to the relationship The Relative Impact of Strategic Orientations between strategic orientations and exploitation seem to on Exploratory and Exploitative Innovations be consensual, in the case of exploration they seem to beless so. Some studies find that a customer focus prevails In recent years, innovation research has shifted from a over technology; other studies find the opposite. Earlier dichotomous view of customer-led or technology-led research has used the term “exploration” to include dif- to an interaction view (Gatignon and Xuereb 1997; ferent types of exploratory innovations; thus, it is not Slater and Narver 1995; Zhou, Yim, and Tse 2005).
surprising that the findings are contradictory. Danneels Researchers agree that firms need to develop technolog- (2002) argues that three scenarios of exploration exist.
ical and customer knowledge simultaneously for suc- In the first, pure exploration, firms build new products cessful innovation. Technology-driven firms have the on new customer and technological competences. The most to gain from combining their technological skills other two scenarios are not pure because they combine with a customer orientation (Atuahene-Gima, Slater, exploitation; that is, they leverage existing competences and Olson 2005; Dutta, Narasimhan, and Rajiv 1999; (technological or customer related) and explore new Lukas and Ferrel 2000; Zhou, Yim, and Tse 2005).
ones (technological or customer related). Prior research However, because resources are limited, firms must has found that a technology orientation is more impor- make choices in their allocation and determine the tant than a customer orientation when exploratory extent to which they will emphasize one strategic orien- innovations are based on new technologies aimed to tation over another (Danneels 2007; Lant, Milliken, and serve existing customers (Gatignon and Xuereb 1997; Zhou, Yim, and Tse 2005). However, when exploratory innovation is developed using existing technologies, a exploitation activities (Singh 1986; Voss, Sirdeshmukh, technology orientation might not be beneficial. In this and Voss 2008). Consequently, the balance between scenario, a customer orientation may be as important as exploration and exploitation shifts depending on the a technology orientation. Exploring new customers firm’s past performance. From the previous arguments, implies a proactive approach in understanding the needs we hypothesize that past performance moderates the of customers that are not yet identified as well as build- relationship between strategic orientations and innova- ing knowledge on how to address those customers and tion. Our focus is not on understanding the effects of developing a relationship with them (Slater and Narver past performance on the innovation activities of the firm but rather on understanding how past performanceaffects the trade-off between the two strategic orienta- H4: Customer orientation and technology orienta- tions when leading to innovation, either through explo- tion are similarly important to exploratory Although we acknowledge that firms with poor past The Moderating Effect of Past Performance performance will favor exploitation and thus need a cus-tomer orientation more than a technological orienta- Organizational learning literature demonstrates that tion, we posit that the level of past performance will not firms tend to rely on their past experience and past alter the relative impact of the two strategic orientations performance for decision making (Cyert and March on exploitative innovation (in line with H3). As we indi- 1963; Lant and Mezias 1992; Lant, Milliken, and Batra cated previously, exploitative innovation means refining 1992; Levinthal and March 1981). Poor past export existing technological and customer competences (Dan- performance is associated with strategic reorientation of neels 2002). While a customer orientation helps exporting firms (Lages, Jap, and Griffith 2008; Lages, improve current customer competences (Atuahene- Lages, and Lages 2006; Lages and Montgomery 2004).
Gima 2005; Baker and Sinkula 2007), by definition, a Managers facing poor past performance are pressured technology orientation does not compromise the refine- to make more precise decisions because they have less ment of existing technological competences (Gatignon margin for error than managers in well-performing firms. Organization theory researchers often use theconcept of “slack” when discussing the impact of H5: (a) For exporters with poor past performance, performance on organizations (Bourgeois 1981). Slack customer orientation relates more strongly refers to the resources that are readily available to than technology orientation to exploitative finance organizational activities. Organizations per- innovation, and (b) for exporters with supe- forming poorly show lower levels of slack than those rior past performance, customer orientation relates more strongly than technology orienta-tion to exploitative innovation.
Slack catalyzes the innovation process (Cyert andMarch 1963). First, slack protects organizations from With regard to exploration, exporters with poor past uncertainties linked to innovation projects, thus foster- performance cannot afford to explore new opportuni- ing search behavior (Bourgeois 1981; Nohria and Gulati ties and ideas through the use of new technologies.
1996). Second, slack enables the firm to follow high- Developing innovations by leveraging customer compe- potential innovation projects that are visionary but not tences or pure exploration implies technology acquisi- justifiable according to standard internal criteria tion, which represents higher innovation costs (Levinthal and March 1981). Profitable organizations (Gatignon and Xuereb 1997). If, on the one hand, firms can commit resources to innovation, particularly to the with a technology orientation have higher innovation renewal of technological knowledge through explo- costs, on the other hand, a customer orientation has no ration activities (Garcia, Calantone, and Levine 2003).
significant impact on innovation cost. Innovations However, unprofitable firms are unlikely to have slack incorporating state-of-the-art technology (e.g., those or to invest in renewing firm competences. Low levels of that technology-oriented firms develop) are extremely slack are detrimental to innovation (Nohria and Gulati expensive and require significant investments (Sorescu, 1996). Firms with greater slack engage in more explo- Chandy, and Prabhu 2003; Wind and Mahajan 1997).
ration activities, while firms with less slack must con- Furthermore, the fewer slack resources a firm has, the serve it for organizational ongoing activities, that is, for lower is its exploratory R&D competence (Danneels The Trade-Off Between Customer and Technology Orientations 41 2008). Thus, it is logical that exporters facing poor past Yim, and Tse 2005). In such a case, a technology orien- performance address exploratory innovation mainly by tation is essential because firms need greater technolog- leveraging existing technology competences. Although ical competences (Slater, Hult, and Olson 2007).
these competences may provide access to unserved mar-kets (Prahalad and Hamel 1990), that potential often With pure exploration, firms must develop new tech- remains untapped because of the lack of customer- nologies to appeal to unserved markets (Danneels related competences (Danneels 2007). Therefore, a cus- 2002). A technology orientation is broadly recognized tomer orientation might serve poor-performing exporters as a critical driver of radical innovations (Chandy and better. Thus, exporters must engage in the pursuit of new Tellis 2000; Gatignon and Xuereb 1997; Zhou, Yim, and radical market information, far beyond the cur- and Tse 2005). Nonetheless, even firms that have strong rent customer knowledge domains (Levinthal and patents cannot increase sales of radical products if cus- March 1993; March 1991). A firm’s customer knowl- tomers are not aware of the product or if adoption is not edge base becomes more diversified, thus increasing accelerated (Sorescu, Chandy, and Prabhu 2003). For chances for greater experimentation and innovation.
example, Apple was able to steal Sony’s market for Therefore, for exporters with poor past performance, a mobile music with less than ten times the number of customer orientation is more critical than a technology Sony’s patents (Tellis, Prabhu, and Chandy 2009).
Moreover, when engaging in exploratory market learn-ing, a firm achieves greater product differentiation (Kim H6a: For exporters with poor past performance, and Atuahene-Gima 2010). A truly customer-oriented customer orientation relates more strongly firm explores unserved markets and understands the than technology orientation to exploratory latent and unexpressed needs of those customers (Slater and Narver 1998). By focusing on future customers,firms introduce more radical innovations (Chandy and With superior past performance, firms can afford to Tellis 1998). Therefore, a customer orientation is also explore new ideas and opportunities by pursuing new important for pure exploration. We conclude that both and sophisticated technologies (Garcia, Calantone, and customer and technology orientations are important to Levine 2003). Slack helps firms ensure continuous exploration-related innovations for exporters with supe- investments in R&D and fund the launch of new prod- ucts (O’Brien 2003). In addition to exploration throughthe leverage of technology competences, the other two H6b: For exporters with superior past performance, cus- exploration-related innovation activities (leverage of tomer orientation and technology orientation are customer competences with new technologies and pure similarly important to exploratory innovation.
exploration) are available options to such firms. Whenfirms develop innovations by leveraging customer com-petences, they must incorporate new technologies into new products to serve the existing customer base (Dan- neels 2002). In this case, exploitative market learningactivities (i.e., the use of knowledge pertaining to cur- We tested our hypotheses with a random sample of rent customers) help refine exporters’ capabilities to 1031 manufacturer exporters in technological indus- serve those customers (March 1991). For example, they tries, listed in the 2007 AICEP Portugal Global, a data- enhance cost efficiency in developing innovations by base of the Portuguese business development agency.
better using the available market information (Kim and For Portuguese companies, exporting is a condition of Atuahene-Gima 2010). Market knowledge is particu- survival, not only because of the current economic crisis larly important for innovations in most high-tech indus- but also because of the country’s small market. For a tries, and earlier research has argued that technology- small economy such as Portugal’s, integration in the based firms must be customer oriented (Mohr and Sarin world economy is particularly important because of the 2009). Innovations developed by leveraging customer access to opportunities for scale economies, specializa- competences require substantial technological capabili- tion, and advanced technology (Organisation for Eco- ties and resources because they adopt new and advanced nomic Co-operation and Development 2008). From the technologies (Danneels 2002). Firms that invest more in database, we considered manufacturing exporters in R&D and are more technically proficient and flexible multiple industries to increase variance and generaliza- are better positioned to deploy those innovations (Zhou, bility of the results (Morgan, Kaleka, and Katsikeas 2004). However, we selected only the firms operating in them with multi-item scales, except for the moderator medium to highly technological industries according to and control variables. Unless specified, we used Likert- the Eurostat (2009) classification, which is based on type scales ranging from 1 (“strongly disagree”) to 7 technological intensity (R&D expenditure). We used (“strongly agree”). Scale items appear in Appendix A.
firms in those industries to provide a similar context torespondents while being broad enough to ensure the Strategic Orientations. We adapted the customer orien- generalizability of the results. Our research question tation construct from Narver and Slater’s (1990) scale of addresses the trade-off between customer and tech- market orientation to capture the degree to which firms’ nology orientation. Because a technology orientation is export activities are oriented toward understanding and intrinsically related to strong investments in R&D, we monitoring customers and their needs. Respondents excluded firms with low R&D expenditures.
rated their level of agreement with statements regardingbehaviors of their firms’ export activities toward cus- Data collection took place in 2009 through an online tomers. This scale has six items. We adapted the meas- survey. The database included the company’s name, tele- ure of technology orientation from the work of Zhou, phone number, address, industry, products, and number Yim, and Tse (2005) to assess the orientation of firms’ of employees. We contacted all the exporters to confirm export operations toward using sophisticated technolo- eligibility for participating in the study—that is, if firms gies in new product development. This scale has four had exported in the previous year and if their export operations were regular. For eligible firms, we estab-lished contact with the export manager (preferably), Exploratory and Exploitative Innovation. We adopted introduced him or her to the project, and asked for an exploratory and exploitative innovation scales from e-mail address and the name and e-mail of the second Lubatkin et al. (2006) to capture two innovation compe- respondent, the R&D manager. We also asked the tences in firms’ export markets. Exploitative innovation export manager to brief the second respondent about pertains to activities close to firms’ current customers the survey. We used this method and followed managers’ and technological trajectory, and exploratory innovation suggestions that we gathered during preliminary inter- includes activities aimed to enter new product-market views. We then sent an e-mail invitation to respondents domains. Each of the scales has six items.
to explain the academic purpose of the project, toensure confidentiality of the responses, and to send the Export Perceived Performance. Export performance is respective link to the survey. The e-mail offered incen- the extent to which the firm achieves its exporting- tives, including a report with the main findings after related objectives (Cavusgil and Zou 1994). We used completion of the study and a significant discount for a three items (profit, sales, and sales growth) from Zou, course about the topic to be held at the end of the year.
Taylor, and Osland (1998), which are indicators of We sent an e-mail reminder three weeks later to non- financial export performance. We did not measure respondents and a final reminder four weeks after that.
export performance in relation to that of competitors, as Of the 1031 firms, 191 were not eligible and 94 were not some researchers (Morgan, Kaleka, and Katsikeas 2004) available to answer the questionnaire, resulting in 746 suggest, because of the outcome from preliminary inter- questionnaires mailed. We obtained 193 usable question- views, in which managers expressed the difficulty of naires, for a response rate of 26%. From those, 170 acknowledging results from competitors at the export remained after missing data analysis and cleaning. To level. We added the word “perceived” to “export assess nonresponse bias, we compared late (last 25%) performance” to make it easier for respondents to dif- and early (first 75%) respondents regarding the means of ferentiate that type of performance from the past perfor- all the variables (Armstrong and Overton 1977). We found no significant differences between the two groupsand therefore concluded that there were no meaningful Past Performance. We selected past return on assets problems in this study regarding response bias.
(ROA), that is, the ratio of net operating profit to thefirm’s start-of-year assets recorded on its balance sheet, as the moderator for the exporter’s financial situation.
Most measures of financial performance fall into two We sourced measures from the literature and adapted broad categories: accounting returns and investor them to the current research context (see Churchill returns. Return on assets is an accounting-based indica- 1979). Constructs were first order, and we measured tor and is the most common and readily available The Trade-Off Between Customer and Technology Orientations 43 means of assessing firm performance (Richard et al.
[1996] recommendation.) These data reflect the Por- 2009). The validity of this type of measure is grounded tuguese exporting industry, in which most firms are in extensive evidence showing the relationship between small to midsize. The average age of firms participating accounting and economic returns. Among accounting in the study was 32 years (SD = 22; range = 2–100), with measures, ROA is popular because it captures a firm’s average exporting experience of 19 years (SD = 19; efficiency (Cochran and Wood 1984) and reflects inter- range = 1–100). The firms are present, on average, in 11 nal decision making on capabilities and performance.
countries (SD = 13; range = 1–75). The average annual We took ROA data from the 2009 Bureau van Dijk sales of the firms ranged from 1.5 million to 5 mil- database and calculated them as the average of the lion, and 8% of firms had sales less than .35 million, ROA of the firm (in percentage) in the three years pre- 23% had from .35 million to 1.5 million, 22% had ceding data collection. Note that we use the past from 1.5 million to 3.5 million, 9% had from 3.5 performance at the firm level, not the export level, million to 5 million, 31% had from 5 million to 35 because it better reflects the total available resources to million, and 7% had more than 35 million. Exporting the firm operation (including export operation).
operations contributed 0%–9% of sales to 9% of firms,with 10%–29% to 14% of firms, 30%–59% to 29% of Control Variables. We controlled for firm size (total firms, 60%–84% to 25% of firms, and more than 85% firm sales), export experience (number of countries with export operations), and export intensity (percentage oftotal firm sales from export operations) following previ- ous exporting literature (Lages, Jap, and Griffith 2008).
To address common method bias, we followed Pod- sakoff et al.’s (2003) recommendations. First, we useddifferent sources of information for our constructs. We We developed the survey instrument by combining split the questions between the two respondents, export information from three sources: (1) field interviews, manager and R&D manager, according to the respective (2) a panel of academic researchers in international mar- area of knowledge of each. We also gathered objective keting and innovation, and (3) the literature. After select- data on profit (ROA, net income), sales, sales growth, ing the scales from the literature, we assessed face number of employees, and years of existence for the validity with a panel of academics (Hunt, Sparkman, and exporters in the sample from the Bureau van Dijk data- Wilcox 1982) who tried to identify potential problems in base, and we calculated the correlation between the their application to the research context. We then con- objective data and the answers obtained from question- ducted ten face-to-face structured interviews with both naires, a procedure other researchers have followed export and R&D managers from firms in different indus- (Morgan, Kaleka, and Katsikeas 2004). Respondents’ tries to evaluate the survey on clarity of instructions, answers to their firms’ total sales and employees are response formats, design, items, and respondents’ com- given by eight and four interval measures, respectively, petence. From the interviews, we confirmed the need for so we coded the objective sales and employment data a different set of questions for each type of respon- into the same intervals. For the measures of export per- dents—one for the export manager and another for the ceived performance—profit, sales, and sales growth— R&D manager—to ensure that they were knowledgeable because the objective measures refer to total company enough about the questions addressed. The next stage figures and the data collected are at the export opera- was a pretest with 15 exporters, which enabled us to fur- tion level, we performed correlation analysis for both ther refine the survey and administration method. The groups of firms: total firms and firms with export inten- final survey was administered online.
sity of more than 60%. All correlations were significant,in support of the validity of key informants’ answers.
Second, the questionnaire clearly assured respondents ofthe confidentiality of the results of this study and that With respect to size, measured by the number of full- there were no right or wrong answers—only that their time employees, exporters in the sample were distrib- opinion mattered. We also followed standard survey uted as follows: 6% with 1–9 employees, 45% with design and administration practices. Finally, to control 10–49 employees, 41% with 50–249 employees, and for common method bias, we used the Harman single- 8% with 250 employees or more. (This classification of factor test (Podsakoff et al. 2003). We extracted six fac- companies is in line with the European Commission tors with eigenvalues greater than 1.0, and the first fac- tor accounted for less than 50% of variance explained.
that items load higher in the respective construct than Thus, we conclude that common method bias is not a on any other construct, thus confirming discriminate We assessed overall model fit by examining both the We tested the hypotheses using partial least squares number of significant relationships among the con- (PLS) with Smart PLS 2.2 software (Ringle, Wende, and structs and R-square, that is, the explained variance of Will 2005). We selected PLS because of the sample size.
the endogenous latent variables (Cool, Dierickx, and When moderators are tested by subgroup analysis, sam- Jemison 1989). Table 1 shows the path coefficients for ples are smaller, which makes PLS more appropriate.
the PLS model. More than 50% of the tested relation- The problem with PLS-biased results is not a concern ships were significant in a model including the moderat- because we have 170 responses, which is ten times ing effects. Variances explained are 49%, 50%, and greater than the number of independent constructs 38% for exploratory innovation, exploitative innova- affecting the dependent variable (i.e., six) (Chin 1998).
tion, and export perceived performance, respectively.
Even when undertaking subgroup analysis, we met this The values satisfy the minimum of 10% for the R- rule. Following Hulland’s (1999) suggestion, we ana- square of the endogenous variables (Falk and Miller lyzed the reliability and validity of the measurement 1992). Export intensity was the only control variable model first and then the structural model.
with a significant coefficient (β = .27, t = 3.74). The sig-nificance of its relationship to export perceived perfor- mance is in line with results from prior research (Cavus-gil and Zou 1994).
To assess the adequacy of the measurement model, weexamined individual item reliabilities, convergent A t-test of the difference between β coefficients of the validity, and discriminant validity (see Appendix A; Hul- relationships of customer orientation and technology land 1999). We assessed item reliabilities by examining orientation to exploitative innovation (.54 and .22, the loadings of the individual items in the respective respectively) confirmed that they are statistically differ- constructs. We confirm that all loadings are greater than ent (β = .32, t = 2.60), with the former greater than the .7 (which is the minimum value for many researchers) latter, in support of H3. The t-test of the difference except for the first item of the customer orientation con- between β coefficients of the relationships of customer struct, which had a loading of .624. However, a factor orientation and technology orientation to exploratory loading less than .7 but greater than .5 may be accepted innovation (.44 and .35, respectively) confirmed that if other items in the same construct present high scores, they are not statistically different (β = .09, t = .74), in which is the case (Chin 1998). Thus, given the concep- support of H4. The results confirm that customer orien- tual importance of this item, we retained it in the model.
tation relates more strongly than technology orientation We assessed convergent validity by analyzing composite to exploitative innovation but is equally important to reliability (Bagozzi 1980). All constructs were reliable and met the minimum value of .7 (Nunnally and Bern-stein 1994). We also computed average variance Testing for Mediating Effects. We followed Baron and extracted (AVE) (Fornell and Larcker 1981) and con- Kenny’s (1986) approach to test for the mediating effect of firmed that all results were greater than the recom- exploratory and exploitative innovation. We ran four PLS mended value of .5, thus confirming convergent validity.
models: (1) with the effects of the independent and inter- We assessed discriminant validity by comparing the cor- action variables on the dependent variable without the relation between each pair of constructs with the root of mediating variables (Model 1); (2) with the effects of the AVE among those constructs (Fornell and Larcker 1981) independent and interaction variable on the mediating and by analyzing cross-loadings between items and con- variables (Models 2 and 3); and (3) with the effects of the structs (Chin 1998). By analyzing the values in Appen- independent and interaction variables on the dependent dix B, we confirmed that the square root of AVE variable, in the presence of the mediating variables (Model between any two constructs (diagonal) is greater than 4). Table 2 presents the results. For the interaction terms, the correlation between those constructs (off-diagonal), we mean-centered indicator values of the variables before thus indicating discriminant validity. The results show multiplication to reduce multicollinearity between main The Trade-Off Between Customer and Technology Orientations 45 Table 1. PLS Path Coefficients
Standardized
Coefficient
Two-Tailed Test
Export intensity → export perceived performance Export experience → export perceived performance Firm size → export perceived performance Customer orientation → exploratory innovation Technology orientation → exploratory innovation Customer orientation → exploitative innovation Technology orientation → exploitative innovation Exploratory innovation → export perceived performance Exploitative innovation → export perceived performance Customer orientation × past ROA → exploratory innovation Customer orientation × past ROA → exploitative innovation Technology orientation × past ROA → exploratory innovation Technology orientation × past ROA → exploitative innovation and interaction variables (Aiken and West 1991). The tests showed statistical significance, and therefore for all mediating variables are significant in Model 4. Customer the independent variables, the regression coefficients of orientation is significant in Models 1, 2, and 3, but in “high past ROA” and “low past ROA” differ.
Model 4, it becomes nonsignificant, which suggests a fullmediation from exploratory and exploitative innovation To understand the relative impact of the two orienta- of the customer orientation–export perceived performance tions, we ran a t-test for the differences in β coefficients relationship, in support of H1a and H1b. Technology ori- of customer orientation and technology orientation in entation barely affected export perceived performance, each subgroup and in relation to the same mediating but the strength of that relationship diminished with the variable. The results in the subgroup of low past ROA entry of the mediating variables in the model. Therefore, revealed that customer orientation relates more strongly than technology orientation to exploitativeinnovation (βdifference = .48, t = 2.30, p < .05) and to Testing for Moderating Effects. We examined moderat- exploratory innovation (βdifference = .39, t = 2.08, p < ing effects of ROA following Sharma, Durand, and Gur- .05), in support of H5a and H6a. In the subgroup of high Arie’s (1981) methodology. First, we created and past ROA, t-tests of the differences in β coefficients were regressed interaction terms between ROA and the pre- nonsignificant in both exploratory (βdifference = .03, n.s.) dictor variables in PLS (see Table 1). Only the inter- and exploitative (βdifference = .11, n.s.) innovation. H5b actions of technology orientation with past ROA were hypothesized that when past performance is superior, a significant (β = .17, t = 2.08). Second, we found no sig- customer orientation relates more strongly to exploita- nificant correlations between ROA and customer or tive innovation (improving existing capabilities) than a technology orientations. Thus, we tested ROA as a technology orientation, but our findings did not sup- homologizer moderator by performing a subgroup port this. However, H6b is fully supported; with supe- analysis. We divided the sample into a low group and a rior past performance, technology and customer orien- high group, excluding the middle 15% of cases to tations do not have differentiated effects on exploratory ensure enough contrast (see Table 3; Kohli 1989). All t- Table 2. PLS Results on the Mediating Effect of Innovation
Exploratory
Exploitative
Perceived Performance
Innovation
Innovation
Perceived Performance
Control Variables
Main Effects
Interaction Effects
Mediating Variables
*p < .10 (two-tailed).
**p < .01 (two-tailed).
***p < .001 (two-tailed).
Table 3. Results of Subgroup Analysis With Past ROA
Relationship
Customer orientation–exploratory innovation Technology orientation–exploratory innovation Customer orientation–exploitative innovation Technology orientation–exploitative innovation The Trade-Off Between Customer and Technology Orientations 47 past ROA/high export perceived performance (HH). We The results presented so far provide insights into the then performed one-way analyses of variance tests on the strategic decisions that firms should make with respect latent variable scores for customer orientation, tech- to innovation when facing good or bad results. How- nology orientation, and export perceived performance.
ever, we cannot conclude from the analysis what causes We also conducted Tukey tests for multiple comparisons the difference between firms that faced poor perfor- of the four groups. Table 4 presents the results.
mance and still achieved good export performance andthose that faced poor performance and had poor export First, LL firms differ from LH firms on customer orien- results. It is also important to understand why firms tation scores. We conclude that firms with poor past with good past results are harmed in their export opera- performance may achieve higher performance levels by tions. We conduct some additional analysis to answer increasing their customer orientation. Second, HL firms differ from HH firms on technology orientation scores.
Firms with good past performance can maintain greater With the purpose of understanding the differences performance by increasing technology orientation.
between exporters with poor and superior past perfor- Finally, LH and HH firms have similar levels of both mance with respect to export perceived performance, we orientations, which suggests that poor past performance split each subgroup (i.e., high past ROA and low past does not affect future performance, as long as high lev- ROA) into two groups, for high and low values of the els of both customer and technology orientations are dependent variable. We took the latent variable scores for export perceived performance, ordered them in descend-ing order, and split them into two groups—one with firmsexhibiting positive scores and the other with firms show- ing negative scores. This yielded four groups: low pastROA/low export perceived performance (LL), low past Exporters face the challenge of allocating their limited ROA/high export perceived performance (LH), high past resources between their possible strategic orientations.
ROA/low export perceived performance (HL), and high However, international marketing research has paid lit- Table 4. Analysis of Variance (ANOVA) and Multiple Comparisons of Subgroups
Homogeneity
Multiple
Latent Variable
of Variance
Significance
Comparisonsa
aTukey test at p < .05.
Notes: LL = low past performance/low export perceived performance, LH = low past performance/high export perceived performance, HL = high pastperformance/low export perceived performance, and HH = high past performance/high export perceived performance.
tle attention to understanding the relative roles of cus- will emphasize one strategic orientation over another.
tomer and technology orientations on innovation and We found that customer orientation is as important as performance. In this study, we used organizational technology orientation for a firm pursuing exploratory learning literature to support our hypotheses with a innovation. This result complements and integrates model in which we used innovation (exploratory and prior research by considering that exploratory innova- exploitative) as a mediator variable between strategic tion aggregates three distinct innovation types: (1) pure orientations (customer and technology) and export per- exploration, (2) technology-leveraging/customer-based ceived performance. We also tested the relative impact innovations, and (3) customer-leveraging/technology- of the two orientations in conditions of poor and supe- based innovations (Danneels 2002). A technology orien- rior past performance, measured by past ROA.
tation is critical when firms need greater technologicalcompetences to develop either tech-based or exploratory This study contributes to the international marketing lit- innovations (Gatignon and Xuereb 1997; Yalcinkaya, erature in several ways. First, it confirms that the two Calantone, and Griffith 2007; Zhou, Yim, and Tse learning competences identified by organizational learn- 2005). A customer orientation provides the necessary ing theory—exploitative and explorative—are essential skills for identifying current and latent needs, uncover- to exporters because they mediate the effects of the ing new market opportunities, searching for unserved firm’s strategic orientation on performance. Organiza- markets, and establishing relationships with existing tional learning research has found that high-performing and new customers (Slater and Narver 1998). Although firms go beyond gathering knowledge to translate it into existing technological competences may provide access learning (Baker and Sinkula 2007; Noble, Sinha, and to unserved markets (Prahalad and Hamel 1990), this Kumar 2002). We provide further support to the sugges- potential often remains untapped because of the lack of tion that strategic orientations do not directly lead to customer-related competences (Danneels 2007). There- better performance (Atuahene-Gima 2005; Baker and fore, a customer-oriented firm is better positioned to Sinkula 2007; Yalcinkaya, Calantone, and Griffith develop either exploratory or customer-based innova- 2007; Zhou, Yim, and Tse 2005); rather, this link tions (Zhou, Yim, and Tse 2005). By demonstrating that depends on how the exporting firm learns—that is, how customer orientation is as important as technology ori- it develops innovation capabilities on the basis of new entation to exploration, we advance the literature by (exploration) and existing (exploitation) knowledge and integrating prior findings. Our results also support the whether that knowledge is technological (prevalent in literature in finding that customer orientation is more technological-oriented firms) or customer (prevalent in important than technology orientation in developing pure exploitative innovations. On the one hand, becauseexploitative innovations consist of product improve- Second, our findings support the view that customer and ments and line extensions that aim to serve existing cus- technology orientations have a key role in ensuring that tomers, firms use existing customer and technological investments in both exploratory and exploitative innova- knowledge when developing them (Atuahene-Gima tion capabilities achieve optimal performance. The find- 2005; Baker and Sinkula 2007; Chandy and Tellis ings are consistent with organizational learning research, 1998). On the other hand, for innovations that are more which posits the need for both types of innovation incremental in nature, firms do not need high levels of (March 1991) and for both marketing and technological technology orientation (Gatignon and Xuereb 1997).
competences to develop them (Danneels 2002; Gatignonand Xuereb 1997; Holmqvist 2004; Yalcinkaya, Calan- Finally, we provide evidence on the influence of past tone, and Griffith 2007). Earlier research using techno- performance of the exporter on how the choices between logical companies as a sample has also shown that a cus- strategic orientations affect exploration and exploita- tomer orientation is critical for innovation success in tion. We found that when exporters have a poor past those firms (Im and Workman 2004; Zhou, Yim, and Tse performance, a customer orientation has more impact on 2005) and must be coupled with a technology orienta- exploratory innovation than a technology orientation.
tion (Dutta, Narasimhan, and Rajiv 1999).
With fewer resources, technical competences are difficultto acquire because of the high costs (Gatignon and Third, this study provides insights into the relative role Xuereb 1997). In such situations, exploratory innova- of customer and technology orientations. Because tions are predominantly developed by entering new mar- resources are limited, exporters must make choices in kets and leveraging the existing technological base, that their allocation and in deciding the extent to which they is, by developing customer-based innovations (Danneels The Trade-Off Between Customer and Technology Orientations 49 2002). With superior past performance, firms can afford (as well as on exploratory innovation) are relative (i.e., to explore new ideas and opportunities by pursuing new they depend on the firm’s financial results). Thus, this and sophisticated technologies (Garcia, Calantone, and study advances the literature by considering the inter- Levine 2003). Innovations incorporating state-of-the-art action between two key trade-offs: strategic orientations technology (e.g., those developed by technology- (customer versus technology) and innovation capabilities oriented firms, such as tech-based and pure exploration innovations) are extremely expensive and require sig-nificant investments (Sorescu, Chandy, and Prabhu 2003; Wind and Mahajan 1997). Nonetheless, even infirms with a strong technology orientation, success is This research contributes theoretically to organizational not certain; customers must be aware of the product or learning theory and innovation literature in many ways.
adoption for sales to accelerate (Sorescu, Chandy, and Organizational learning theory asserts that firms inno- Prabhu 2003). Moreover, earlier research has found that vate by engaging in two forms of learning: exploratory by focusing on future customers, firms introduce more (developing new knowledge) and exploitative (using radical innovations (Chandy and Tellis 1998). Our find- existing knowledge) (March 1991). First, we found that ings support these arguments: Customer and technology both exploratory innovation and exploitative innova- orientations are similarly important when exporters tion are essential to the firm because they act as vehicles with superior past performance develop exploratory for renewing two key firm capabilities—customer and technology orientations—to achieve superior perfor-mance. Moreover, by considering customer and tech- The differential effects of customer and technology orien- nology orientations with exploration and exploitation tations on exploitative innovations are also noteworthy.
simultaneously, we present a new perspective of the For exporters with poor past performance, customer ori- roles of these orientations in the development of firms’ entation was more important than technology orientation innovation capabilities. Our results indicate that the to exploitative innovation. Being more incremental in trade-off between customer and technology orientations nature, such innovations do not require a technology ori- is pivotal in ensuring a proper balance between entation because they rely on a firm’s existing technolo- exploratory and exploitative innovations.
gies (Baker and Sinkula 2007; Gatignon and Xuereb1997). However, because a customer-oriented firm is Second, we advance the literature by examining the rela- knowledgeable about its customers, a customer orienta- tive role of strategic orientation on exploration and tion favors the development of those innovations. In con- exploitation. We show that for the development of trast with our expectations, in exporters with good prior exploratory innovations, customer and technology ori- performance, customer orientation does not have a entations are equally important. Although marketing stronger influence than technology orientation on scholars have theorized about the importance of both exploitative innovation. A possible explanation is that orientations to innovation capabilities (Danneels 2002; because technological firms are inherently technology ori- Gatignon and Xuereb 1997; Yalcinkaya, Calantone, and ented (Workman 1993), they prefer to invest in new tech- Griffith 2007; Zhou, Yim, and Tse 2005), no empirical nological competences when having good financial evidence exists on their relative role.
results. Technological competences may be developed, forexample, through the diversification of exporters’ existing Third, our study confirms that a firm’s emphasis on technological portfolio, enabling them to become more either customer orientation or technology orientation expert in their current domains of expertise (Katila and affects the balance between exploratory and exploitative Ahuja 2002; Quintana-Garcia and Benavides-Velasco innovation changes according to its past performance.
2008). As such, past positive financial results would be The organizational learning literature demonstrates that more readily applied through a technology orientation firms’ past performance influences their decision mak- than through a customer orientation. Our study con- ing (Cyert and March 1963; Lages, Jap, and Griffith tributes to previous research by confirming that exploita- 2008; Lant and Mezias 1992). Thus, we offer a new per- tive innovation benefits more from existing customer spective by considering the moderating effect of past competences than from technological ones (Gatignon and performance rather than using it as an antecedent. Fur- Xuereb 1997; Yalcinkaya, Calantone, and Griffith 2007).
thermore, we show that when past performance is poor, We also advance the literature by showing that the roles exporters tend to develop exploratory innovations that of customer and technology on exploitative innovation rely on their existing technological competences to explore new customers rather than to explore new tech- Salomo 2007; Mohr and Sarin 2009). Therefore, in nologies (customer orientation had a stronger effect on addition to a strong orientation toward the development exploratory innovation than technology orientation).
of innovations using state-of-the-art technologies, man- Prior research has argued that firms with fewer agers of these firms need a similarly strong focus on resources engage in more exploitation activities (Singh understanding and satisfying the needs of both current 1986; Voss, Sirdeshmukh, and Voss 2008). Nonetheless, and potential customers. By acknowledging the need for this study supports the view that firms with poor perfor- a trade-off between customer and technology orienta- mance must develop both exploratory and exploitative tions, managers can ensure a balanced mix of innova- innovation capabilities (He and Wong 2004; Levinthal tion competences. For example, Motorola faced a sig- and March 1993; March 1991); failing to recognize that nificant decline in performance following the success of such exporters also need to invest in exploration (devel- its cell phone model, the Razr (Verma, Momin, and Gir- opment of new knowledge) might risk their long-term ija 2008). Because Motorola focused primarily on extending the Razr product lines to please its customerbase, it failed to maintain itself at the forefront of the Fourth, although the export literature has more exten- technological trends in the industry. Conversely, Philips, sively covered customer orientation (e.g., Cadogan, Kuiv- a company with a long tradition as a technological inno- alainen, and Sundqvist 2009), few studies have addressed vator, underestimated customers’ needs for products to technology orientation (e.g., Filatotchev et al. 2008), and, make their lives easier (George and Govind 2007). This to our knowledge, none have examined both. Moreover, behavior was partly responsible for Philips’s financial few studies have considered innovation capabilities (e.g., downturn at the beginning of the twenty-first century.
Lages, Silva, and Styles 2009). This is surprising becauseinnovation and internationalization are highly related Second, our results suggest that managers in technologi- (Knight and Cavusgil 2004). We found that exploratory cal firms pressured by poor past performance should and exploitative innovation capabilities drive the conver- invest more in developing a customer orientation than a sion of firms’ strategic orientations to export perfor- technology orientation. Because these firms cannot afford mance. Finally, the findings reveal that as long as an strong investments in R&D, they engage less in the pur- appropriate trade-off between customer and technology suit of technology-based innovations. To ensure a bal- orientations is maintained, exporting technology-based anced mix of innovation capabilities, they should develop firms with a poor past performance may achieve a high their exploratory innovations by focusing on new cus- export performance in the future. Moreover, an equili- tomers rather than on sophisticated technologies. A cus- brated trade-off between customer and technology orien- tomer orientation enables the simultaneous fine-tuning of tations can lead to a balanced mix of exploitative and existing customer competences (leading to the develop- exploratory innovation capabilities. Exporters with a ment of incremental innovations) and the exploration of poor past performance would benefit from innovation new customers (e.g., new geographical markets).
based on new market exploration (e.g., entry into newgeographical markets) and exploitation of existing com- For firms with superior past performance, managers petences to satisfy existing customers.
may fail because of the lack of an adequate level of cus-tomer orientation. Technological firms naturally focus on acquiring sophisticated technologies and new tech-nological competences, but this is no guarantee of suc- This study provides several managerial implications.
cess. Managers of such firms need to maintain high lev- First, the findings underscore the need for managers to els of customer orientation. Resultant innovations invest in both customer and technological knowledge to should be balanced between radical and tech-based ensure the development of exploration and exploitation.
innovations on the one hand and incremental innova- Therefore, resource allocation decisions should, on the tions on the other hand. Exporters may then use new one hand, consider the firm’s needs for innovation capa- technologies to enter new markets or to develop the bilities and, on the other hand, be guided by the firm’s strategic orientations toward customer and technology.
Technological exporters operate in highly complex envi- ronments, characterized by high levels of technologicaland market uncertainties and highly diverse and dis- Although this work provides useful theoretical and persed customers (Kleinschmidt, De Brentani, and managerial insights, it also has several limitations. The The Trade-Off Between Customer and Technology Orientations 51 use of a sample of Portuguese exporters limits the gen- ment harms performance. International marketing eralizability of the results both geographically and in research could also investigate the trade-off between the scope. Further research could examine the relationships two strategic orientations but linked to different types of between strategic orientations and innovation capabili- exploratory innovation. Danneels (2002) identifies three ties in other cultural contexts. In addition, the cross- types: pure exploration, customer competence leveraging, sectional design does not allow for establishment of and technology competence leveraging. Each type needs causal relationships. A longitudinal study would pro- different trade-offs between the strategic orientations vide additional insights into the tested model. The (Yalcinkaya, Calantone, and Griffith 2007; Zhou, Yim, effects of innovation capabilities on performance are and Tse 2005). With a clear understanding of which differentiated in the long and short run (March 1991).
trade-off of orientations leads to which specific type ofinnovation, managers would be able to make more pre- Other possible limitations also imply fertile avenues for cise decisions on resource allocations and strategic direc- further research. International marketing research should tions of the firm (Sorescu, Chandy, and Prabhu 2003). In investigate the interaction effects between customer and addition to differentiating between innovations, we technology orientations, as well as the nonlinear relation- encourage further research to develop measures for each ships between these orientations and innovation, by type, echoing Zhou, Yim, and Tse’s (2005) call.
addressing the question of a more balanced view of strate-gic orientations. The resource-based theory posits that Finally, the use of other moderators might also be a fer- complementary resources achieve synergistic effects on tile area for international marketing research. For exam- performance; however, leveraging every resource is not ple, previous research has shown that depending on the possible (Song et al. 2005). For managers, knowing which absorption and the rarity of resources, firms’ decisions resources to invest in is of extreme importance. For exam- balance more toward exploration or exploitation (Voss, ple, in studying exporters, Cadogan, Kuivalainen, and Sirdeshmukh, and Voss 2008). Following this line of Sundqvist (2009) find that managers should develop a research, additional research could typify customer and market orientation only to a certain point, which depends technology orientations to increase the understanding of on market dynamism, because thereafter more develop- Appendix A. Scale Items and Reliabilities
Standardized
Variance
Composite
Constructsa
Adapted From
Extracted
Reliability
Loadings
Export Perceived Performance
Question: With regard to your company’s exportingoperation, to what extent do you agree with the following sentences? • It has generated a high volume of sales.
Customer Orientation
Question: With regard to your company’s actions in the exporting markets, to what extent do you agree with the following sentences? • Our business objectives are driven primarily by • We constantly monitor our level of commitment and orientation to serving customers’ needs.
• Our strategy for competitive advantage is based on our understanding of customers’ needs.
Appendix A. Continued
Standardized
Variance
Composite
Constructsa
Adapted From
Extracted
Reliability
Loadings
• Our business strategies are driven by our beliefs about how we can create greater value for customers.
• We measure customer satisfaction systematically • We give close attention to after-sales service.
Technological Orientation
Question: With regard to your company’s actions in the exporting markets, to what extent do you agree with the following sentences? • We use sophisticated technologies in our new • Our new products always use state-of-the-art • Technological innovation based on research results is readily accepted in our organization.
• Technological innovation is readily accepted in Exploratory Innovation
Question: With regard to your company’s actions in the exporting markets, to what extent do you agree with the following sentences? • We look for novel technological ideas by thinking • We base our success on our ability to explore • We create products or services that are • We look for creative ways to satisfy our • We dynamically risk entering new market • We actively target new customer groups.
Exploitative Innovation
Question: With regard to your company’s actions in the exporting markets, to what extent do you agree with the following sentences? • We commit to improve quality and lower cost.
• We continuously improve the reliability of our • We increase the level of automation in our • We constantly survey existing customers’ The Trade-Off Between Customer and Technology Orientations 53 Appendix A. Continued
Standardized
Variance
Composite
Constructsa
Adapted From
Extracted
Reliability
Loadings
• We fine-tune what we offer to keep our current • We penetrate more deeply into existing aScale format: 1 = “completely disagree,” and 7 = “completely agree.” Appendix B. Means, Standard Deviations, and Correlations Between Constructs
Notes: The diagonal shows the square root of the average variance extracted.
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The Trade-Off Between Customer and Technology Orientations 57 Sorescu, Alina B., Rajesh K. Chandy, and Jaideep C. Prabhu Nova School of Business and Economics, Lisbon, Portu- (2003), “Sources and Financial Consequences of Radical gal. Paula has developed her managerial career at vari- Innovation: Insights from Pharmaceuticals,” Journal of Mar- ous multinational companies in Portugal and Spain, in keting, 67 (October), 82–102.
industries such as fast-moving consumer goods, foodretail, and apparel retail. She has performed jobs in mar- Teece, David J., Gary Pisano, and Amy Shuen (1997), “Dynamic Capabilities and Strategic Management,” Strategic keting, commercial, and sales management areas.
Management Journal, 18 (7), 509–533.
Paula’s research interests are related to the transfer oftechnological innovation to international markets. Her Tellis, Gerard, Jaideep C. Prabhu, and Rajesk K. Chandy PhD research was a finalist of the McKinsey Award at (2009), “Radical Innovation Across Nations: The Preemi- the 38th European Marketing Academy conference.
nence of Corporate Culture,” Journal of Marketing, 73 (Jan-uary), 3–23.
Carmen Lages (PhD, Warwick, United Kingdom) is
Verma, M., P. Momin, and P. Girija (2008), “Motorola: Losing Assistant Professor of Marketing in the ISCTE Business Its ‘Razr’s’ Edge,” Case Study, ICFAI Business School, Pune, School, Lisbon University Institute, Portugal. Part of this research was conducted while she was a VisitingScholar in the Deshpande Center for Technological Voss, Glenn B., Deepak Sirdeshmukh, and Zannie G. Voss Innovation at the Massachusetts Institute of Tech- (2008), “The Effects of Slack Resources and Environmental nology. Her current research interests include sustain- Threat on Product Exploration and Exploitation,” Academy ability/corporate social responsibility, relationship man- of Management Journal, 51 (1), 147–64.
agement, branding, and international marketing. Her Wind, Jerry and Vijay Mahajan (1997), “Issues and Opportuni- publications have appeared in Journal of International ties in New Product Development: An Introduction to the Spe- Marketing, Journal of Business Research, Industrial cial Issue,” Journal of Marketing Research, 34 (February), Marketing Management, European Journal of Market- Workman, John P., Jr. (1993), “Marketing’s Limited Role in Luis Filipe Lages (PhD, Warwick, United Kingdom) is
New Product Development in One Computer Systems Firm,” Associate Professor of Marketing and International Busi- Journal of Marketing Research, 30 (November), 405–421.
ness at Nova School of Business and Economics, Lisbon, Yalcinkaya, G.R., Roger J. Calantone, and David A. Griffith Portugal. Part of this research was conducted while he (2007), “An Examination of Exploration and Exploitation was an International Faculty Fellow in the Sloan School Capabilities: Implications for Product Innovation and Market of Management at the Massachusetts Institute of Tech- Performance,” Journal of International Marketing, 15 (4), nology. His research interests include international mar- keting, managerial reactions to past performance, meas-urement of intangibles, innovation/creativity, and Zhou, Kevin Zheng, Chi Kin Yim, and David K. Tse (2005), transfer of technology to the market. His publications “The Effects of Strategic Orientations on Technology- andMarket-Based Breakthrough Innovations,” Journal of Mar- have appeared in Journal of International Marketing, Journal of International Business Studies, Journal ofRetailing, Journal of Business Research, International Zou, Shaoming, Eric Fang, and Shuming Zhao (2003), “The Marketing Review, International Business Review, Effect of Export Marketing Capabilities on Export Perfor- Industrial Marketing Management, European Journal of mance: An Investigation of Chinese Exporters,” Journal of Marketing, among others. He sits on several editorial International Marketing, 11 (4), 32–55.
boards, including those of Journal of International Mar-keting and International Marketing Review.
———, Charles Taylor, and Gregory Osland (1998), “The EXPERF Scale: A Cross-National Generalized Export Perfor-mance Measure,” Journal of International Marketing, 6 (3),37–58.
The authors thank the five anonymous JIM reviewers for constructive feedback. This research was supported Paula Hortinha (PhD, ISCTE, Portugal) is Marketing
by Fundação para a Ciência e a Tecnologia, “Nova Director at Jerónimo Martins, SGPS and affiliated with Forum,” and UNIDE-Lisbon University Institute.
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