Internally Versus Externally Developed ... - Wiley Online Library

European Management Review, Vol. 11, 173–186 (2014) DOI: 10.1111/emre.12029

Internally Versus Externally Developed Technology and Market Acceptance of Innovations: The Complementary Role of Branding Chirag Patel and Christophe Haon Grenoble Ecole de Management, Grenoble, France

Empirical studies that relate internally versus externally developed technology to market acceptance of innovation during emergent stages provide contradictory findings. We contend that these conflicting findings might be the result of a theoretical misspecification in existing models that fail to consider the effect of synergy between a firm’s technology development choice and its branding choice. We use the concepts of value creation and value appropriation to develop our hypotheses relating different combinations of technology development and branding choices to market acceptance. With data on the early history of Internet banking in the United States, we show that internally developed technology leads to greater market acceptance than externally developed technology, but this effect changes with the choice of a brand extension versus a new brand. Specifically, firms that combine internally developed technology with a new brand achieve greater market acceptance for their innovation during emergent stages. Keywords: technology development; branding; innovation; value creation; value appropriation

Introduction Greater market acceptance of innovations requires firms to develop the underlying technology better than others (see Abernathy and Utterback, 1978). This supplyside view of the technology life cycle has spurred an impressive number of academic studies that compare the direct effect of the firm-level technology development choice between internally and externally developed technology on market acceptance of the innovation (e.g., Chesbrough, 2003; von Hippel, 2005; Boudreau, 2010). However, theoretical reasoning and empirical findings related to market performance of technology development choices are different, contradictory, and inconclusive for technologies in their emergent stages.1 Correspondence: Chirag Patel, Grenoble Ecole de Management, 12 rue Pierre Semard-BP 127, 38 003 Grenoble, France. Email: chirag.patel@ grenoble-em.com 1

Regardless of the differences in nomenclature, the notion of extreme technological and market uncertainty during the emergent stages appears consistently in economics, organizational ecology, and strategy literature. This period of evolution has been referred to as the entrepreneurial technology regime (Nelson and Winter, 1982), era of ferment (Tushman and Anderson, 1986), and growth phase (Agarwal et al., 2002).

© 2014 European Academy of Management

Two separate streams of studies exist. The first stream of empirical research based on transaction cost economics seeks to predict the best technology development option under varying environments. Few empirical studies in this line have explicitly compared the performance between internally and externally developed technology. In addition, no clear choice between these options has been predicted for conditions of extreme technological and market uncertainty (see Rindfleisch and Heide, 1997; Geyskens et al., 2006). The second stream of literature uses the knowledge-based perspective to argue for the superior performance of combined internally and externally developed technology, as opposed to using a single technology development option (Cusumano et al., 1992; von Burg, 2001; Chesbrough, 2003; von Hippel, 2005; Boudreau, 2010. However, these arguments do not find uniform empirical support when different environmental factors such as type of technology sourced (Rothaermel and Alexandre, 2009; Weigelt, 2009), degree of perceived product complexity (Almirall and Casadesus-Masanell, 2010; Boudreau, 2010, and type of partnerships (Almirall and Casadesus-Masanell, 2010) are included in the model. Thus, despite extensive research into the performance implications of technology development choice, it

174 remains unclear whether firms should use internally or externally developed technology to achieve greater market acceptance in the emergent stage. This paper seeks to fill this research gap by identifying and correcting possible theoretical misspecifications in existing models of market acceptance of new technologies. Existing models’ assumptions that technology development choices serve as a firm’s value creation mechanism and affect the number of consumer benefits delivered by an innovation are supported empirically (see Rivadeneyra et al., 2010). Moreover, value creation alone might not be sufficient to achieve greater market acceptance (Capon et al., 1990; Leiponen, 2000; Mizik and Jacobson, 2003). We identify branding choice (i.e., new brand creation versus extension of an existing brand), which is part of a firm’s value appropriation mechanism,2 as a key moderating variable for inclusion in these models. This serves to correct the existing models of market acceptance. Inclusion of branding in these models is based on a key theoretical insight from the demand-based view of the technology life cycle, which posits that market performance of new technologies is a function of the degree of synergistic interaction between the consumer benefits delivered and the evaluation of these benefits by consumers (Adner, 2004). For this paper, we study the effect of synergy between a firm’s technology development choice (i.e., internally versus externally developed technology) and branding choice (i.e., new brand versus brand extension) on market acceptance of innovation in the emergent stage. We find that internally developed technology combined with a new brand leads to greater market acceptance of emergent innovations than other combinations of technology development and branding. Moreover, considering that prior comparable product/service offerings may affect a firm’s ability to create and capture value, we also address the following question: does prior offer relatedness moderate the synergistic effects of technology and branding decisions on the market acceptance of an innovation? We find that firms with high prior offer relatedness that use an internal technology–new brand combination will likely gain greater market for their innovation than firms with low offer relatedness that use a similar set of options. Thus, our research contributes to a more complete, coherent, theoretical, and empirical explanation of the market acceptance of an innovation. Specifically, we 2

A firm’s value appropriation mechanism (e.g., branding) dictates consumer evaluation of value created by an innovation. The distinction between value creation and value appropriation mechanisms has been made previously, particularly in studies that consider both concepts together. For example, Mizik and Jacobson (2003) categorized new consumer benefits delivered by an innovation as value creation but designated value appropriation as the use of reputation, brand, advertising, and network externalities to extract profits.

C. Patel and C. Haon show that the effect of technology development choice on market acceptance is contingent upon branding choice and prior offer relatedness. Moreover, we provide an explanation for contradictory findings in extant literature and more accurate recommendations for practice. In the next section, we develop the framework that guides our research and present a series of hypotheses about the implications of technology development and branding choice for market acceptance of an innovation. Then, we test our hypotheses using data on development of Internet banking from 1995 to 1999 in the US retail banking industry, drawing on archival sources to develop our database. Finally, we present the results, which offer key implications for both research and practice.

Theory and hypotheses Definitions Technology development choice refers to whether a firm develops technology internally or relies on external sources. Branding choice indicates whether a firm creates a new brand or extends an existing brand to a new product or service. Market acceptance is the mere purchase, experience or ownership of a new product or service (see Bass, 1969; Wilton and Pessemier, 1981; Dekimpe et al., 2000). Theoretical framework Our theoretical framework draws upon the resourcebased view, organizational boundary, innovation and branding literature to explain how different combinations of technology development and branding lead to varying levels of value creation and value appropriation during the emergent stage of innovation. In developing our arguments, we focus on the key characteristics of the emergent stage, namely the dynamics of technological and market uncertainty. The emergent stage commences with the emergence of an innovation – that incorporates substantially new technology as compared to existing products in the industry – thus, initiating a period of extreme technological and market uncertainty (Abernathy and Utterback, 1978). At the onset, the technology underlying innovation is relatively untested resulting in substantial uncertainty about the technological superiority of the innovation as compared to existing products in the industry. This is accompanied by considerable market uncertainty about the usefulness of the innovation in relation to existing products. During the emergent stage, the nascent technology underlying innovation undergoes dynamic and continuous change that improves the functionality delivered by the innovation (Abernathy and Utterback, 1978; Afuah, 2001). On the demand side, consumer needs and © 2014 European Academy of Management

The Complementary Role of Branding evaluations regarding the innovation also undergo dynamic continuous change throughout the emergent stage (Weigelt and Sarkar, 2012). For some emergent innovations, the technological changes and consumer evaluations co-evolve in a synergistic fashion resulting in continuous reduction in technological uncertainty about the superiority of the innovation along with reduced market uncertainty about the usefulness of the innovation. These changes ultimately result in the emergence of a dominant design of the innovation that is commonly accepted by all stakeholders in the industry and that marks the end of the period of technological and market uncertainty (Tushman and Anderson, 1986). Moreover, firms that introduce innovations during the emergent stage face substantial market acceptance challenges and might even eventually exit the market (Klepper, 1996). In this paper, we consider the market performance implications of firm-level technology development and branding choices during the emergent stage. We use these arguments to develop hypotheses that link four possible configurations of technology development and branding to market acceptance during the emergent stage. We start development of our theoretical framework below by considering the link between firm-level technology development choices during the emergent stage and market acceptance of the innovation. Internally versus externally developed technology and market acceptance of innovation Processes underlying internally and externally developed technology differ in terms of their value creation ability during the emergent stage for three reasons. First, internal development processes are designed to solve the type of technical problems that arise during the emergent stage. From a problem-solving perspective (Nickerson and Zenger, 2004), firms face illstructured and complex technical problems during this stage. Such problems have poorly defined knowledge sets that are highly interdependent and interact in unexpected ways (Levinthal, 1997), making a technical solution search difficult. To solve such problems, knowledge-intensive and closely coordinated experiential learning activities are required (Azoulay, 2004; Macher, 2006). Processes used to develop technology internally allow for coordination, sharing of tacit knowledge, frequent interactions, and ambiguous problem solving (Afuah, 2001) that correspond to ill-structured and complex problems (Macher and Boerner, 2012). In contrast, firms that use externally developed technology depend on external technology developers who have formalized processes that efficiently solve well-structured problems (Macher and Boerner, 2012). This implies that processes for internally developed technology corresponds better to © 2014 European Academy of Management

175 problem-solving demands of innovation during the emergent stage as compared to externally developed technology (see Kapoor and Adner, 2012). Second, internal development processes have the flexibility required to respond to the ever-changing consumer needs during the emergent stage. Internal development routines involve experimentation and search for novel approaches that increase variance and support adaptability to changing environments (Smith and Tushman, 2005; Rivkin and Siggelkow, 2003). In contrast, external developers have routines that are mapped and documented in order to replicate them with minimum variance. Such routines are designed to solve efficiency problems but do not support adaptation to changing environments, which constitutes an illstructured and complex problem (Weigelt and Sarkar, 2012). Recent empirical research has shown that internal development during the emergent stage reduces the efficiency but increases the adaptability of a firm (Weigelt and Sarkar, 2012). Thus, firms that rely on internally developed technologies are likely to be apt at adapting them to changing market conditions, resulting in innovation with greater consumer benefits than innovation developed externally. Third, firms that develop the technology internally also have the flexibility to develop technology solutions that correspond specifically to the needs of their customer base. On the other hand, since the processes of external developers are designed to be replicated with minimum variance, they are unable to respond to the heterogenous needs of client firms (Weigelt and Sarkar, 2012). Thus, internally developed technology tends to be more customized than externally developed technology and offers greater opportunities for a competitive advantage to those firms that develop them. In summary, firms that develop new technology internally should create greater consumer value through superior innovation compared to firms that acquire the new technology from external sources (Rivadeneyra et al., 2010; Sirmon et al., 2007). Moreover, greater consumer value is likely to increase market acceptance of the innovation (Abernathy and Utterback, 1978). Based on these arguments, we hypothesize: Hypothesis 1: Internally developed technology leads to greater market acceptance of an innovation with emerging technology than externally developed technology. Moderating effect of branding Firms that develop technology internally are similar in their ability to create consumer value through superior innovations but might differ in their ability to appropriate this value. Value appropriation, or the ability to improve consumer evaluations of the benefits delivered

176 by an innovation, is crucial for market acceptance of an innovation. The demand-side view of the technology life cycle further posits that market acceptance of an innovation is a function of the synergistic co-evolution of consumer benefits delivered by an innovation and the perceived usefulness of these benefits to the consumer (Adner, 2004). Firms that develop technology internally but make different value appropriation choices should develop different synergies between the consumer evaluations of benefits and the actual benefits delivered by the innovation. This difference creates heterogeneity in market acceptance of innovations among firms that develop technology internally but make different value appropriation choices. We focus on branding decisions as a value appropriation strategy. Firms that introduce innovations based on new technologies have the option to create a new brand or extend an existing brand. We argue that brand extension differs from new brand creation in the degree to which it allows firms to create coherent, co-evolving consumer perceptions about the benefits delivered by the innovation. The motivation to use a brand extension for an innovation is to leverage the equity of an existing brand, thus saving promotion expenses (Smith and Park, 1992; Sullivan, 1992). In particular, using an existing brand is a way to provide potential customers with references they can rely on to infer the quality of an innovation (Aaker and Keller, 1990; Erdem and Swait, 2004). Therefore, extending a strong parent brand is commonly considered an efficient way to signal quality and trustworthiness to potential adopters of an innovation. However, it does not necessarily create coherence between consumer perceptions and actual benefits delivered by the innovation for two reasons. First, a major condition for brand extension success is the perceived fit between the innovation and the parent brand (Boush et al., 1987; see Keller, 2002 for a review). This compels the firm to adopt a positioning close to that of the existing products or services and limits its freedom in communicating the distinctive characteristics of its new offer (Wernerfelt and Karnani, 1987; Sullivan, 1992). Such an impediment can compromise the chances that targeted customers really perceive the unique benefits offered by the innovation. Olshavsky and Spreng (1996) empirically showed that when customers exposed to an innovative concept cannot easily categorize it – which is likely when the innovation is in the emergent stage – they tend to adopt a detailed, attribute-based judgmental approach. Communicating the innovation attributes while trying to comply with the constraints imposed by the parent brand’s positioning may thus be difficult. In this regard, choosing a brand extension for an innovation may prevent providing potential early adopters the detailed, specific, and accurate information they need.

C. Patel and C. Haon Second, a brand extension might signal that the innovation is not novel. Knowledge of the reputation might reduce the attention and the interest of innovative customers, who are vital to the takeoff of innovations with emerging technologies. In their classification of innovation adoption behaviors, Wood and Swait (2002) hypothesized and observed two segments within the most innovative customers who were studied. When confronted with an innovation, highly innovative customers with a low need for cognition will rely on novelty cues that they can process without effort. A new brand is such a cue. As for highly innovative customers with a high need for cognition, they will consider a significantly greater amount of attributes and will especially focus on attributes that are substantially different from current alternatives. A firm can thus use an abundance of details to communicate the unique benefits of an innovation to such customers. This tends to mitigate the importance of brand associations – which are the purpose of brand extensions – for really new innovations. This might also explain the observation that early market entry tends to be less successful when firms use brand extensions than when they create a new brand (Sullivan, 1992; DeGraba and Sullivan, 1995). On the other hand, the creation of a new brand grants the firm substantial flexibility in selecting the appropriate positioning for the innovation. However, the potential advantages in this opportunity require relatively more effort to be realized. In particular, the firm needs to allocate more resources to market research, exploitation of customer insights, and innovation launch support. Henard and Szymanski (2001) showed that marketing task proficiency, market orientation, and launch proficiency, among other factors, are significantly and positively related to new product performance. If executed properly, the creation of a new brand should consequently involve resource allocation in a set of different activities that makes success more likely. In particular, investments in market research are likely to allow firms that create a new brand to monitor the ever-changing consumer needs and evaluations of benefits delivered by their innovation throughout the emergent stage (Weigelt and Sarkar, 2012). This knowledge about the dynamics of market perception of their innovation is likely to allow these firms to match their technology development with the changing consumer expectations. Such a match will allow the technology to be co-created with the consumer’s help. In summary, using a new brand strategy (vs. an existing brand extension) maximizes the synergy between the actual consumer benefits embedded in the innovation and the consumer perception of innovation superiority. It then follows that the combination of internally developed technology and new brand will allow firms to develop innovations with greater consumer benefits and © 2014 European Academy of Management

The Complementary Role of Branding to create stronger perceptions of innovation superiority among consumers. Consequently, we hypothesize: Hypothesis 2: The positive effect of internally developed technology on market acceptance of an innovation with emerging technology is greater for firms that create new brands than for those that extend an existing brand. Moderating effect of prior offer relatedness on technology-branding synergy Firms that use an internal technology–new brand combination might differ from each other in terms of their ability to create maximum synergy between value delivered and value appropriated. As mentioned, the opportunity to select an appropriate synergistic positioning depends on the firm’s ability to understand the new market, exploit customer insights, and support innovation launch. Firms with higher relatedness between prior product or service offerings and the emerging innovation have relevant technological and market knowledge that increases their understanding of the new market (Larsson and Finkelstein, 1999; Cattani, 2005). For example, when banks introduced personal computer (PC) banking to provide anytime, anywhere banking services, they addressed a market that had high relatedness with the market relevant to Internet banking. This discussion implies that when an innovation is introduced, some firms in the industry might have higher prior offer relatedness with the innovation. These firms may be more proficient at using the internal technology–new brand combination to create a positioning that maximizes synergy between the actual consumer benefits delivered by the innovation and the perceived usefulness of these benefits. Prior related offerings also ensure that consumers have previous experience with a technology that addresses similar consumer benefits as those delivered by the emerging innovation. For example, consumers that used PC banking had the opportunity to experience anytime anywhere banking services through a computer interface.

Figure 1 Conceptual model


177 Since previous experience increases consumer readiness to use an innovation (Saaksjarvi, 2003; Meuter et al., 2005;), it follows that prior related offerings increase consumer propensity to adopt an innovation during the emergent stage. Based on the above arguments, we predict that: Hypothesis 3: The positive effect of internally developed technology and new brand creation on market acceptance of an innovation with emerging technology is greater for firms that offer a related product or service prior to the innovation introduction. Overall, our hypotheses seek to better understand market acceptance of innovation during the emergent stage. Our conceptual model proposes a direct effect of a firm’s choice of internally versus externally developed technology on market acceptance of innovation during the emergent stage. This effect is moderated by a firm’s choice of branding – new brand versus brand extension. Further, prior offer relatedness moderates the synergistic effect of technology and branding decisions on market acceptance of innovation (see Figure 1).

Method Empirical context We test our hypotheses with data from the early history of Internet banking in the US retail banking industry. Specifically, we examine the effect of US retail banks’ technology and brand decisions about Internet banking over a five-year period, starting in early 1995, on market acceptance of the Internet banking offer by the end of 2001. Recent research on Internet banking cites 1995–1999 as the emergent period of development for this innovation (Weigelt and Sarkar, 2012). During this time, considerable technological and market uncertainty surrounded Internet banking, largely because nascent Internet banking technology did not support reliable financial

178 transactions. Technical issues linked to Internet banking negatively influenced consumer perceptions about the usefulness of the technology and led to security, privacy, and loss concerns among consumers. The technology evolved continuously from 1995 to 1999, leading to an increase in the actual consumer value delivered by Internet banking. Furthermore, market acceptance of Internet banking evolved with a slow but steady increase from 2.4 million households banking online in 1995 to 5 million households in 1999 (Furst et al., 2002). During this emergent period, there was considerable heterogeneity among banks in terms of choice of technology development and branding combination for Internet banking. For example, Bank of America developed the emerging online banking platform internally and created a new brand for the online transactional service. On the other hand, Northern Trust Bank also developed the emerging technology internally but chose to extend the existing brand name to the Internet banking service. Other possible combinations of technology development and branding were also used. Bancorp South Bank licensed the technology from an external technology developer but created a new brand, while Bank One licensed and extended the existing brand (www.onlinebankingreport.com). Among these four banks, Bank of America’s choice resulted in registration for the Internet banking service by 2.5 million consumers, while other banks lagged behind. Even Northern Trust bank with its internally developed technology and brand extension decision had only 17,000 online banking registrations by end of 2001. Sample. Our sample consists of Federal Deposit Insurance (FDIC) insured banks that introduced Internet banking between 1995 and 1999 (initial n = 161). We obtained our sample from the Thomson Directory of Internet Banks (2001 edition) published by Thompson Financial Publishing. We included every bank that offered a basic transactional website3 by the end of 1999 and had assets greater than $100 million to ensure the banks in our sample had sufficient resources to consider alternative technology and branding choices. The Thomson Directory includes all banks that made detailed information available about their Internet banking services at the time of data collection. All these banks were also part of the Office of the Comptroller of the Currency4 database, which lists all banks that have a transactional Internet banking website, whether or not they have released any information about it. We checked 3

A basic transactional website offers customers banking and financial services, such as accessing accounts, transferring funds, and conducting electronic bill payments (Furst et al., 2002). 4 We thank Daniel Nolle (Office of the Comptroller of the Currency) for making the list of banks used in Furst et al. (2002) available.

C. Patel and C. Haon the representativeness of our sample; the percentages of small, medium, and large banks in our sample and in the population were virtually the same (about 60%, 25%, and 11%, respectively). Measures We collected data from archival sources about the variables to measure the technology development choice, branding choice, prior offer relatedness, and market acceptance of Internet banking. Innovation market acceptance depends on many other variables such as time of entry into the Internet banking market and other bank specific characteristics like size, profitability, market share, charter type, and type of business. We collected data on appropriate measures of these variables and control for them. Table 1 presents an overview of the operational measures and data sources for each variable. Details for the measures of the variables are provided below. Innovation market acceptance. We used the number of registered online users of the transactional website in 2001 as a measure of market acceptance of Internet banking for the banks in our sample. These data came from the 2001 edition of the Thomson Directory of Internet Banks. Technology development choice. We operationalized technology development choice as a two-level measure of the use of in-house technology resources, namely, whether the Internet banking platform at entry was completely licensed from an outside vendor (n = 119) or at least partially developed in-house (n = 28). This Internet banking platform is essential for providing basic online transactional banking services since it supports transactional processes between end user interface and banks legacy systems. We first obtained data on in-house or licensed Internet banking platform for banks in our sample from Online Banking Report (www.onlinebankingreport.com). We cross-checked this data with archival information from Factiva (global. factiva.com) and the Internet Archive’s Wayback Machine (archive.org). Unfortunately, this information could not be retrieved for 14 banks in our sample. Branding choice. To operationalize branding choice, we categorized banks’ decisions as either the creation of a new brand (n = 52) or a brand extension (n = 100). A new brand uses a completely different brand name than the brand for the bricks-and-mortar banking arm. In the case of brand extension, the brand name of the Internet banking service either includes or is identical to the bricks-and-mortar brand name (e.g., Milberg et al., 1997). We illustrate these branding choices in the Internet banking context in Table 2. For these comparisons, © 2014 European Academy of Management

The Complementary Role of Branding

179

Table 1 Summary of measures and data sources Variable

Operational measure

Data source

Innovation Market Acceptance Technology Development

Number of registered online users in 2001 Degree of integration of Internet banking platform at entry: licensed from an external vendor (0) vs. partly or completely developed internally (1) Brand name for online banking service at entry: new brand (0) vs. existing brand (1)

Thomson Directory of Internet Banks Online Banking Report Factiva Internet Archive Internet Archive Thomson Directory of Online Banking U.S. Patent and Trademark Office Thomson Directory of Internet Banks FDIC FDIC FDIC Internet Archive Thomson Directory of Internet Banks Online Banking Report, Factiva, Google News Archives, and news archives on bank and vendor websites FDIC FDIC

Branding

Prior Offer Relatedness Control Variables

PC banking offered in 1994 (1) or not (0) Firm size: Assets in 1994 Market share: Deposits in 1994 Profitability (return on assets) in 1994 Entry time

Bank charter in 1994: national (0) or state (1) Type of business in 1994: B-to-B (0) vs. B-to-C (1)

Table 2 Examples of branding in a banking context Branding Strategy

Operational Definition

Examples

New Brand

Exclusion of bricks- and-mortar brand name

Brand Extension

Inclusion of new words in bricks-and-mortar brand name or use of bricks-and-mortar brand name only

Citizens Bank Tri-Cities → Bank-By-Net Bank One → Wingspanbank Wells Fargo → Wells Fargo Online or Wells Fargo.com Fleet National Bank → Fleet Home Link Universal Bank → Universal Bank

we considered the brand name of the transactional Internet banking service, not web addresses of banks. In addition to comparing the brand name of the transactional Internet banking service with the brand name of the bank to identify the branding choice, we compiled data from the Thomson Directory of Internet Banks, the Internet Archive, and the US Patent and Trademark Office to ensure that at least two sources corroborated the initial name of the transactional Internet banking service. When we found only one source of data provided the brand name at entry, we cross-checked that name with archival information from Factiva. This information could not be retrieved for nine banks that were consequently excluded from our sample. Prior offer relatedness. We used the availability of PC banking prior to the introduction of Internet banking as an indicator of prior offer relatedness because PC banking incorporates precursor technology and addresses similar customer needs. We coded prior offer relatedness depending on whether the bank offered PC banking at the end of 1994 (n = 50) or not (n = 107). We obtained this data from the Thomson Directory of Internet Banks. This information could not be retrieved for four banks in our sample. © 2014 European Academy of Management

Controls First, we measured profitability as return on assets in 1994. Profitability is a measure of the availability of resources for investment (Borenstein, 1991), which is important for innovation (Sorescu et al., 2003) because a firm’s profitability can have an important influence on innovation outcomes. We collected archival data about the return on assets as of December 1994 from the Institutional Directory of the FDIC. Second, the entry time that banks in our sample introduced transactional Internet banking occurred during various points in time between 1995 and 1999, and this likely had an effect on the market acceptance that was measured in 2001. To control for this variation, we collected and verified information on the month and year of introduction of transactional Internet banking from several sources: Internet Archives, Thomson Directory of Internet Banks, Online Banking Report, Factiva, and news archives on bank and vendor websites. Third, depending on their charter, US banks are regulated by either the state or the federal government. Banks regulated by the federal government tend to have greater geographic reach and thus larger customer bases. We coded each bank depending on whether it had a federal or state charter; this data was obtained from the FDIC. Fourth, we used the asset

180 concentration (specialization) of a bank as an indicator of its main type of business. Banks with different specializations have different types of customers, which could determine consumer acceptance of a banks’ innovation. Specifically, we coded whether a bank conducts the majority of its business in commercial and industrial (B-to-B) or consumer lending (B-to-C) from data obtained from the FDIC. Finally, we collected data from1994 on assets and deposits as measures of firm size and market share from the Institutional Directory of the FDIC. Data analysis Modeling the effect of the technology development and branding choices on the market acceptance of innovation raises some important issues because firms might selfselect in their decisions to internally (/externally) develop the technology according to unobserved firm-specific factors, such as their internal capabilities. Such selfselection may also occur for branding choices. Therefore, any model that relates technology development and branding to firm performance makes the independent technology and branding variables potentially endogenous and correlated with the error term. The ordinary least squares (OLS) estimation of such a model would result in biased estimates (Hamilton and Nickerson, 2003). We assessed whether the technology development and branding variables are endogenous using an instrumental variables estimator (Stock and Watson, 2003). Specifically, we used instrumental variables in place of the potentially endogenous variables to estimate the effect on market acceptance. The two main criteria for the selection of valid instrumental variables are instrument relevance (i.e., the instrument should be correlated with the covariates) and instrument exogeneity (i.e., the instrument should not be correlated with the error term; Stock and Watson, 2003). We constructed four instrumental variables from the predicted values of technology development choice (idv1) and branding choice (bi1), which were obtained through Probit estimates of the following models:

Technology Development i = ξ0 + ξ1Assetsi + ξ2 Deposits + ξ3 Profitability i + ξ4 Prior Offer Relatednessi + ξ5 Type of Businessi + ξ6 Charteri + ε ′′′i , (1) And

Branding i = ξ0 + ξ1Assetsi + ξ2 Deposits + ξ3 Profitability i + ξ4 Prior Offer Relatednessi + ξ5 Type of Businessi + ξ6 Charteri + ε ′′′i , (2) where i indicates the bank. The four instrumental variables we used can be coded bi1, t1_b, t1_d, and q. They

C. Patel and C. Haon were constructed from the predicted values of technology development (idv1) and branding choice (bi1) as shown: ti1_b = idv1 × Branding; ti1_d = Technology Development × bi1; and q = idv1 × bi1. We performed instrumental variable estimations of the following model (see Equation 3) using these four instruments, and then conducted the test of endogeneity for the regressors (i.e., technology development and branding choice).

Innovation Market Acceptance i = ξ0 + ξ1Technology Development i + ξ2 Branding + ξ3 Profitability i + ξ4 Prior Offer Relatednessi + ξ5 Type of Businessi + ξ6 Charteri + ξ7 Entry Timei (3) + ξ8 Assetsi + ε ′′′′i , where i is the bank offering Internet banking. The endogeneity test statistic was not significant though (χ2 = 2.42, p = 0.29), so these variables are not endogenous. Because this test result is sensitive to the reliability and validity of the instruments used, we also conducted several further tests. To check for the validity of the instruments, we conducted the Sargan-Hansen test of overidentifying restrictions. The Hansen’s J statistic was 2.10 (p = 0.34), which indicated that the instruments were valid and uncorrelated with the error term (Hayashi, 2000). To check for the reliability of the instruments, we conducted an underidentification test; the Kleibergen-Paap rank LM statistic was 22.89 (p = 0.00). Therefore, the equation was not underidentified, and the excluded instruments were relevant and correlated with the potentially endogenous regressors (Hall, Rudebusch and Wilcox, 1996). Finally, we conducted a test of weak identification or correlation of the instruments with the potential endogenous regressors. To assess the strength of identification (or predictive power) of the excluded instruments, we estimated the Kleibergen-Paap rank Wald F statistic, which we then used to infer the degree to which the instrumental variable estimate is biased and the degree of the size distortion relative to the OLS estimate. We found that the Kleibergen-Paap rank Wald F statistic for our instruments was 13.10. To infer the strength of identification of the four excluded instruments for the two endogenous variables, we referred to Stock and Yogo (2005), who asserted that the rule-of-thumb critical value of 11.04 limits the bias to 5% of OLS, and the critical value of 9.93 limits the size distortion to 15%. Our Kleibergen-Paap statistic equaled 13.10, so the bias resulting from the use of these instruments was relatively small (less than 5% of OLS), as was the size distortion (less than 15% of OLS), at a p-value of 0.05. This implies that the instruments are not weakly identified. In the absence of endogeneity, we estimated an analysis of covariance (ANCOVA) model to test our © 2014 European Academy of Management


181

Table 3 Means and correlations Mean (SD) Technology Development (TD) Branding (B) Prior Offer Relatedness (POR) Innovation Market Acceptance (IMA)

0.15 (0.35) 0.66 (0.47) 0.32 (0.46) 92 552.84 (333 026.1)

Minimum

Maximum

TD

0

1

1.0

0

1

–0.02

0

1

0.23***

82

2 500 000

0.43***

B

POR

IMA

1.0 0.067 –0.06

1.0 0.33***

1.0

*p < 0.1. **p < 0.05. ***p < 0.01. Pearson correlations have been reported.

hypotheses. The analysis featured a 2 (external vs. internal technology) × 2 (existing vs. new brand) × 2 (related vs. unrelated offer prior to introduction) ANCOVA design with eight main effects (factors, covariates, and controls), 2 two-way interactions (technology development × branding and technology development × prior offer relatedness), and a three-way interaction (technology development × branding × prior offer relatedness) with innovation market acceptance as the dependent variable. The final sample consists of 98 banks for which all the required measures were available in our data set. We performed a multicollinearity diagnostic for covariates (Tabachnick and Fidell, 2007). The Variance Inflation Factor (VIF) for both entry time and profitability is 1.1. This value is below every recommended cut-offs (2, 5, or 10), showing that there is no multicollinearity issue to be suspected in our estimation. The unbalanced cell sizes reflected real-world differences; in our analysis, we accordingly used the Type II sums of squares (SS Type II), the preferred approach in such situations (Langsrud, 2003; Page et al., 2003). Moreover, according to Levene’s test, the assumption of the homogeneity of variance is violated, which could lead to positively biased F tests in the analysis. To avoid this risk, we followed Keppel and Wickens’s (2004) recommendation to use a more stringent significance level by halving the significance level, thus setting α = 0.025.

Results Table 3 presents the means and correlations for key variables. The positive and significant correlations of technology development and prior offer relatedness with innovation market acceptance provide face validity for the hypotheses. The basic motivation for our study is to establish a potential model specification error of prior research, namely, the omission of the interactions described in our hypotheses. In order to prove the benefit from modeling these interactions we introduced them successively. In © 2014 European Academy of Management

Model 0, only the main effects of the independent variables and of the controls5 are specified. Next, we added the interaction of technology development choice and branding choice (Model 1), then the interaction of technology development and prior offer relatedness (Model 2), and finally, the three-way interaction of technology development, branding, and prior offer relatedness (Model 3). From the estimation of Model 1 onwards, we verified that results remained consistent with those of the previous step and that the practical significance (adjusted R2) was significantly greater. As shown in Table 4, the conclusions regarding the significance of variables remained consistent across estimations. Moreover, the F changes were all significant, supporting the hypothesis of an increase of the practical significance across successive models. Hypotheses tests Effect of technology development choice. The main effect of choosing between externally and internally developed technology is significant, F (1, 86) = 21.756, p = 0.000. The estimated marginal means displayed in Figure 2 show a greater market acceptance for banks that chose internal development rather than external development, thus supporting Hypothesis 1. Moderating effect of branding choice. The interaction of technology and branding decisions exerted a significant effect on innovation market acceptance, F (1, 86) = 15.706, p = 0.000. We display the estimated marginal means of market acceptance in Figure 3. Among banks that developed their technology internally, market acceptance was significantly greater for those also choosing to create a new brand rather than extend their existing brand. In contrast, among banks that used externally developed technology, market acceptance did 5

Among the controls used, we cannot use firm size as well as market share together due to multi-collinearity. Results presented in Table 4 uses firm size. Note that we also estimated all models after replacing firm size by market share. We obtained similar results as those obtained with firm size.

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Table 4 Hierarchical ANCOVA Model 0 Source Main effects and controls Technology Development (TD) Prior offer relatedness (POR) Branding (B) Type of business Charter Profitability Entry time Firm size Interaction effects TS x BS TS x POR TS x BS x POR Error Total Adjusted R2 Δ R2 ΔF Sig.

d.f. 1 1 1 1 1 1 1 1

Model 1

F

Sig.

21.756 0.009 0.024 0.145 2.597 0.650 10.627 51.358

0.000 0.923 0.879 0.704 0.111 0.422 0.002 0.000

87 96 0.574

d.f.

Model 2

F

Sig.

1 1 1 1 1 1 1 1

27.083 0.239 0.144 0.013 1.760 0.364 6.891 47.007

0.000 6.26 0.706 0.911 0.188 0.548 0.010 0.000

1 1

15.706 14.523

0.000 0.000

85 96 0.658 0.084 11.650 0.000

d.f.

F

Sig.

1 1 1 1 1 1 1 1

29.374 0.259 0.156 0.170 1.507 0.127 7.035 37.453

0.000 0.612 0.694 0.681 0.223 0.722 0.010 0.000

1 1 2

17.035 15.752 4.596

0.000 0.000 0.013

83 96 0.685 0.029 8.919 0.004

Figure 2 Main effect of technology development choice on innovation market acceptance

Figure 3 Moderation of technology development effects by branding choice

not differ significantly for those choosing to create a new brand or extend their existing brand, supporting Hypothesis 2.

introduction of Internet banking. To test for different technology–brand synergies (two-way interactions) across levels of prior offer relatedness (PC banking), we removed prior offer relatedness from our original model and estimated it using (1) only banks with no PC banking and (2) only banks with PC banking prior to Internet banking. The mean square value of the two-way interaction for each level of PC banking, divided by the mean square error from the original model revealed the F ratio. These tests show that the two-way interaction was significant for banks that offered PC banking prior to the introduction of Internet banking,

Moderating effect of prior offer relatedness. The threeway interaction of technology development, branding, and prior offer relatedness was statistically significant, F (2, 86) = 4.596, p = 0.013, and the estimated marginal means of innovation market acceptance is displayed in Figure 4. As that figure reveals, the synergy of internally developed technology and new brand creation was greater for banks that offered PC banking prior to the



183

Figure 4 Moderation of technology development and branding combined effect by prior offer relatedness

F (1, 86) = 22.303, p = 0.000, but it was not for banks that did not offer PC banking, F (1, 86) = 0.346, p = 0.558. We thus confirmed Hypothesis 3. Among control variables, we find that firm size and entry time have positive and significant effects on innovation market acceptance across all three models. To understand the implications of these results on technology development and branding choice, we conducted some additional analysis. Specifically, we conducted analysis of variance (ANOVA) tests to check for differences in entry time and firm size among firms that made different technology development and branding choices. We found that there are no significant differences, in terms of entry time and firm size among firms that choose internally versus externally developed technology and among those that choose new brand versus brand externsion.

Summary and discussion Our results have several implications for firms involved in innovation activity during the emergent stage. First, our results suggests that firms involved in developing emergent innovation should create technology and branding resources that are adaptable and synergistic. We find in this study that firms with greater synergy between their choice of internally versus externally developed technology and choice of new brand versus brand extension likely enjoy greater market acceptance of their innovation than firms with lower synergy. The implication being that resource allocation during the emergent stage of innovation development should be guided by the need to make combined technology development and brand choices that lead to the greatest adaptability and synergy between these resources. However, firms pursuing innovation during a period of uncertainty often seek to simply balance their risk-resources portfolio. For example, Bank One decided to create a separate brand name (Wingspanbank.com) and use externally developed technology for its Internet banking initiative © 2014 European Academy of Management

(Sucher and McManus, 2002). These choices balanced the bank’s risk-resource portfolio because the choice to create a new brand is risky and resource intensive, whereas the choice to license Internet banking technology involves fewer resources and reduces the risk of technological failure. Yet, the results of our study suggest that Bank One – and other firms confronted with the same decisions – would have better benefited from focusing on adaptability and synergy between their technology development and branding choices. Recognizing that these decisions are complementary and synergistic and that different combinations of technology development and branding have differing effects has important consequences for firms involved in developing innovation during the emergent stages. Second, our results encourage firms to invest in emerging technologies. Although the market for emerging technologies is fraught with uncertainty, our study indicates that firms that introduce emerging innovations stand to benefit in the long term. For example, PC banking was an early effort by US banks to provide home-based retail banking services by allowing customers to connect directly with banks’ servers using a modem. Although financial transactions using PC banking were more secure than transacting on a public network like the Internet, it was not widely accepted, and banks ultimately replaced this service by introducing Internet banking on their websites. Our study shows that though the PC banking innovation failed, banks that provided PC banking before the advent of Internet banking benefited from their technological and market knowledge relatedness. That is, PC banking positively moderated the market acceptance of Internet banking for certain combinations of technology development and branding choices. Our study thus provides empirical evidence that investment in products incorporating emerging technologies can lead to greater market success for the related innovations. Our study also makes several theoretical contributions to research on innovation. Prior research has shown that firms choose their firm boundary in accordance

184 to technological and market conditions (Kapoor and Adner, 2012; Macher and Boerner, 2012). For example, Kapoor and Adner (2012) find that internally developed technology is preferable when an industry undergoes architectural technological changes. Similarly, Macher and Boerner (2012) demonstrate that the nature of technological problem that firms face impacts the optimal firm boundary choice. We contribute to this growing literature stream by examining, in contrast, the moderating effect of branding decisions on performance of firm technology boundary. We suggest that firms that create a new brand for their innovation with emerging technology are able to realize benefits of internally developed technology. We develop a theoretical framework to support our arguments and in doing so, uncover the following implications for research. First, our theoretical framework builds on the demand-based view of the technology life cycle to point out that a complete and coherent theoretical explanation of market acceptance of innovations during the emergent stages requires consideration of the market performance effects of synergy (or lack thereof) between a firm’s value creation mechanism and its value appropriation mechanism. Our approach thus differs from previous studies that build on the supplyside view of the technology life cycle and that assume that value creation mechanisms alone explain differences in innovation performance. This assumption does not hold; greater insight into firm differences in terms of the market success of their innovations can come from studying the synergy between value creation and value appropriation mechanisms. Second, our theoretical framework also reveals the mechanism by which different combinations of value creation and value appropriation mechanisms affect market acceptance of innovations. In contrast to existing research that focuses on firm resources alone as the source of competitive advantage, we argue that greater value creation and value appropriation results from the alignment, adaptation, and integration of complementary firm resources (technology and brand) with the external environment. Specifically, the choice of internally developed technology allows firms to align and adapt their technology resources to the changing environment during a period of technological uncertainty. Thus, internally developed technology leads to greater value creation. But aligning and adapting technology resources alone is insufficient for market acceptance. To increase innovation market acceptance, firms must also align and integrate their technology resources with complementary brand resources used for innovation. Therefore, firms should combine internally developed technology with a new brand for the innovation. Third, our theoretical arguments take into account the role of different types of resources and the nature of resources in influencing innovation performance. We

C. Patel and C. Haon explain the mechanism by which the interplay between internal versus external and new versus existing brand and technology resources leads to greater value creation and value appropriation during the emergent stages of innovation, thus affecting its market acceptance. This approach sets our study apart from previous studies that focus on internal versus external technology resources to explain innovation performance. Despite the contributions, our research has several limitations. First, the empirical context of this study is limited to a single industry in the United States. Future studies might want to test generalizability of the results across different industries and across nations. Second, the empirical context of Internet banking is in the services sector, and the generalizability to products might be questioned. Yet, we believe that the results are generalizable to product as well as service innovations that incorporate emerging technologies, and the conceptual arguments and concerns regarding consumer perceptions about usefulness of the innovation are relevant to both product and service innovations during the emergent stage. Third, we have a single measure of value appropriation mechanism, namely, branding choice. Other marketing strategies such as advertising or network externalities are also relevant measures of value appropriation. Similarly, we also have a single measure of innovation market acceptance, one that does not consider ‘depth’ or ‘the amount of usage by consumers’. Despite this limitation, note that our operational measure of number of registered online banking users captures purchase or ownership aspect, which is crucial for take off of an innovation to occur. Finally, the final sample size is rather small. Yet, our dataset is composed of every available bank that met the selection criteria in the period studied; we could not increase the number of observations. For this reason, in order to make our conclusions more robust, we adapted our estimation strategy to the type of data we have (i.e., Type II sums of squares). In addition, our hierarchical model estimation approach demonstrates that our results are stable across models and are thus not dependent on the model specification.

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