Competence Ambidexterity and New Product Performance for Small Firms

Abdul Ali*

*Abdul Ali is Associate Professor of Marketing and Entrepreneurship, Malloy Hall, Room 217, Babson College, Babson Park, MA 02457. Phone: (781) 239-5584, FAX: (781) 239-5020, Email: [email protected]. The author gratefully acknowledges the support provided by the Board of Research at Babson College.

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Competence ambidexterity and New Product Performance for Small Firms ABSTRACT As firms increasingly rely on new product development for competitive advantage, managers understand the need to build appropriate competencies to develop more new products. Past research, however, offers conflicting recommendations on building competencies for small firms. While some scholars suggest specialization for a firm with a technical competency to develop pioneering products and another firm with a marketing competency to develop incremental improvements, other scholars call for a better fit between marketing and technical competencies in order for firms to improve their new product success rates. This study aims to reconcile the conflicting recommendation about technical and marketing competency by suggesting that firms cannot afford to specialize in either technical or marketing competency but need to develop varying levels of ambidexterity in both competencies for different types of new product developments. More specifically, this paper explores how product innovativeness moderates the relationship between competence ambidexterity and new product performance. Based on the concept of “organizational ambidexterity” researched in the organizational science area, this paper has empirically observed that building a synergistic (high-high) combination of technical and marketing competency helps small firms improve performance of radical innovations while developing a balance (high-low or low-high) combination of the two competencies assists firms enhance performance of incremental innovations. This study contributes to existing research on ambidexterity by examining the impact of competence ambidexterity across three different measures of new product performance at the individual project levels for small firms.

Introduction The important role innovation plays in improving performances of small and medium-sized enterprises (SMEs) is well documented in the literature (Verhees and Meulenberg 2004; Qian and Li 2003). Liao, Kickul, and Ma (2009) suggest that an entrepreneurial firm's need for constant innovation to survive and create its own competitive advantage depends on its ability to mobilize its resources and capabilities, and align them dynamically with the changing opportunities in the environment. While previous research recommends that in order to excel in innovation, a firm should simultaneously be market-oriented, entrepreneurial, and have access to superior technological assets and capabilities. Renko, Carsrud, and Brannback (2009), however, have found that when firms are attempting to develop radical, disruptive innovations, only technological capability, and neither market orientation nor entrepreneurial orientation, has a significant relationship with product innovativeness. In contrast, Huang, Soutar, and Brown (2002) earlier observed in a sample of 276 SMEs that firms undertook marketing-related activities less frequently and executed them less well than technical activities, even though marketing-related activities were important in distinguishing between successful and unsuccessful new products. Danneels (2002), however, asserts that marketing and technological capabilities must be present for effective new product development. It seems, then, that a firm needs to be ambidextrous in both technical and marketing competencies to successfully develop new products. This paper plans to explore the impact of such competence ambidexterity on new product performance for small firms. The notion of ambidexterity in technical and marketing competencies studied here is similar to past research on organizational ambidexterity (for an integrative review, see Raisch and Birkinshaw 2008). Since March’s (1991) argument, in a seminal article, that successful firms were pursuing both exploitation and exploration activities, researchers have emphasized the need for firms to achieve balance between exploiting existing competency in bringing incremental innovations and exploring new competency in developing radical new products (Gupta, Smith, and Shalley 2006), further suggesting that such ambidextrous firms are more likely to achieve a superior performance than firms emphasizing one at the expense of the other (Tushman and O’Reilly 1996). The extant literature on organizational ambidexterity

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barring a few (for example, Lubatkin, Simsek, Ling, and Veiga 2006), however, has focused on larger firms. It is not obvious how such ambidexterity will play out for SMEs and how competence ambidexterity will help small firms to improve their new product performances. Given the fact that small firms play an important role in developing breakthrough innovations (Baumol 2005), this paper studies small firms (mostly less than 100 employees), and hopes to contribute to the existing research on ambidexterity by examining two specific research questions: How does a small firm balance technical and marketing competencies that place conflicting demand on its limited resources? Will the same level of competency be uniformly successful for small firms in improving market performances across all types of new products? This paper addresses the above two questions. First, this paper explores the nature of balancing technical and marketing competency in two different ways. The firm can achieve ambidexterity through (i) combining a high level of technical competency with a high level of marketing competency or (ii) balancing a high (low) level of technical competency with a low (high) level of marketing competency. These two different notions of ambidexterity in technical and marketing competencies studied here is similar to past research on organizational ambidexterity (Cao, Gedajlovic, and Zhang 2009; He and Wong 2004), but unlike past work which has operationalized exploiting and exploratory competencies in terms of incremental and radical innovations, this paper defines technical and marketing competencies exclusively in narrower terms of skills and experiences pertaining to technical and marketing functional areas. Furthermore, while past research has found mixed results for both “balanced” and “combined” dimensions of organizational ambidexterity (Cao, Gedajlovic, and Zhang 2009), this paper has found consistently positive impacts of the combined dimensions of competence ambidexterity for radical innovations. Second, this paper investigates the moderating role of product innovativeness in the relationship between ambidexterity and new product performance. Past research has investigated how environmental (Jansen, Van Den Bosch, and Volbreda 2006), and organizational (Auh and Menguc 2005; Atuahene-Gima 2005) factors moderate the relationship between ambidexterity and new product performance. Such research, however, has focused on

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the impact of exploiting and exploratory competency at the firm performance level, whereas this paper investigates the impact of competence ambidexterity on new product performances at the individual project level. Based on a survey of 110 small manufacturing firms in the computer-related industry, this paper observes that product innovativeness moderates the relationship between both types of ambidexterity and initial market performance. The significant relationship is found to be mostly robust across three different measures of initial market performance – revenue, profit, and cycle time. This is important given the caution raised by Raisch and Birkinshaw (2008) that studies deploying one-dimensional indicators of firm performances may “run the risk of producing biased estimations of organizational ambidexterity’s contribution to the firm’s overall success.” Figure 1 displays the conceptual model of the relationship between competence ambidexterity and new product performance. Product innovativeness will moderate the relationship between ambidexterity and new product performance. Theory and Hypothesis The notion of ambidexterity in technical and marketing competencies is the main focus of research in this paper. The concept of competence ambidexterity is similar to the organizational ambidexterity concept researched in the organizational science area (see Raisch and Birkinshaw 2008). In the organizational literature, ambidexterity refers broadly to a firm’s ability to simultaneously pursue two disparate things, such as an organization achieving alignment in its current operations while also adapting to changing environment (Gibson and Birkinshaw 2004), or, effectively developing both incremental and discontinuous innovation (Tushman and O’Reilly 1996), to name a few. Product innovation, thus, is one way of achieving organizational renewal. Researchers have (i) identified various organizational dimensions that can be instrumental in finding a balance between incremental and radical innovation (O’Reilly and Tushman 2004), (ii) investigated the environmental and organizations antecedents of organizational ambidexterity (Gibson and Birkinshaw 2004), (iii) looked into the impact of ambidexterity on firm performance (Lubatkin, Simsek, Ling, and Veiga 2006; He and Wong 2004), as well as (iv) studied how environmental dynamism (Jansen, Van Den Bosch, and

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Volbreda 2006), competitive intensity (Auh and Menguc 2005), and market orientation (Atuahene-Gima 2005) moderate the relationship between elements of ambidexterity (exploitation and exploratory) and firm performance. These studies in organizational literature, however, have described the exploitation and exploratory competency in terms of incremental and radical innovation respectively (Tushman and Smith 2002) and further conceptualized the ambidexterity construct at the organization or business unit level (Raisch, Birkinshaw, Probst, and Tushman 2009). It is not clear how a firm, especially a small one, can be ambidextrous at the individual project level and whether such ambidexterity will equally be effective for different types of new product development projects. Ambidexterity and New Product Performance: The Moderating Role of Product Innovativeness Past research suggests that market pioneers, early followers, and late entrants tend to have different skills and resource profiles (Robinson, Fornell, and Sullivan, 1992). Liberman and Montgomery (1988) suggest that if one firm has unique R&D capabilities while the other has strong marketing skills, it is in the interest of the first firm to pioneer and the second firm to enter at a later stage. However, such research mainly focuses on the conceptual discussion of order of entry (Golder and Tellis, 1993) and empirical demonstration of pioneering advantages (Robinson and Fornell, 1985). Implicit in this body of research is that technical competencies help a firm to develop pioneering products, while marketing competencies will be beneficial for incremental innovations. There is no suggestion in this type of research that a firm needs both technical and marketing competencies to successfully develop a new product. In new product literature, however, researchers recommend closer interaction between R&D and marketing activities (Hise, O’Neal, Parasuraman, and McNeal 1990). Souder (1988) observes that “to successfully develop many types of new product innovations, R&D and marketing must work together.” Calantone, di Benedetto and Divine (1993) observe that “technical activities and marketing skills appear to have a greater direct effect on new product development than product quality.” Similarly, Song and Parry (1997) conclude that “increases in a project’s fit with the firm’s existing base of marketing and technical skills and resources lead to an increase in the quality of implementation during the NPD process.” Based on a meta-

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analysis of the new product performance literature, Henard and Szymanski (2001)1 suggest that marketing and technological task proficiency are among the ten most significant drivers of new product performance. Nerkar and Roberts (2004), likewise, argue that a firm will be more successful with its new product development when it “possesses the appropriate stocks of technological and product market experience.” It seems then a firm requires both technical and marketing competency in order to succeed in new product development. In other words, competence ambidexterity helps firms to successfully develop new products. However, it is not clear from this literature how a firm combines these two competencies. Further, this paper questions whether such competence ambidexterity will be a panacea for all types of new products. Highly innovative products may require more time, efforts, and resources to be developed successfully (de Brentani 2001). Olson, Walker, and Ruekert (1995) suggest that product innovativeness moderates the relationship between cross-functional team structures and the effectiveness and timeliness of the development process. They observe that new product teams encounter greater difficulty and take more time when developing products with a high degree of newness. In the case of developing a highly innovative product, a firm may have limited knowledge or expertise in identifying or understanding evolving customer needs and/or emerging technological development. Consequently, a firm needs both technical and marketing competency not only to understand customers and technology, but also to act quickly to take advantage of this knowledge. In other words, competence ambidexterity will help firms to improve their new product performance when they develop highly innovative products. In the case of an incremental innovation, a firm’s investment on building ambidexterity may be counter-productive as it might create the need to justify the investment made on building technical and marketing capability by conducting unnecessary research and development activities that would make cross-functional coordination more difficult and often result in “analysis paralysis.” Further, well endowed resources and capability may prompt firms to spend 1

Henard and Szymanski (2001) identified ten dominant antecedents of new product performance. Marketing and technological proficiency, being the focus of this paper, are only mentioned here. Most of the remaining eight drivers are considered as control variables for the purpose of this research.

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unnecessary time on development tasks and may result in products that may be overengineered or have too many features that customers may not want to pay for. Therefore, this paper suggests that in case of a major product innovation, a firm’s ambidexterity in technical and marketing competency will lead to a superior initial market performance; however, when there is a minor product innovation, competence ambidexterity will not necessarily lead to improved initial market performance. More formally, this paper proposes that: H1:

Product innovativeness moderates the relationship between competence ambidexterity and new product market performance.

Research Method Research Setting: The sampling frame selected for this study consisted of a cross-section (4 different 4-digit SIC groups) of small (mostly less than 100 employees) firms involving in manufacturing computers, computer peripherals, prepackaged software or semiconductor devices2. These firms were chosen to represent an industry where firms are actively engaged in product development, and as a result it was possible to investigate broad patterns of new product development activities that firms are pursuing in this industry. The unit of analysis was the firm's most recently completed new product development project. Entrepreneurs (e.g., president or owner) were used as single key informants on the basis of their vested interest and presumed intimate knowledge of their firms' new product development processes. Data collection: The data collection phase proceeded in several stages. First, unstructured personal interviews were undertaken with several entrepreneurs and industry experts to identify the most important issues facing the key decision-maker. Second, a questionnaire was developed based on personal interviews and the literature review, and pre-tested with a small group of firms. Next, 1000 invitations to participate in the study were sent out. Of these, 107 letters were found to have wrong mailing addresses. This is quite common in this industry because of a high failure rate in the rapidly changing technology. Of the remaining 893 firms, 626 firms responded, but only 543 firms agreed to participate in the survey and fit the criteria

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The sampling frame was constructed from a highly regarded commercial mailing list provider.

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of recent product development3. Finally, questionnaires were mailed to these 543 firms. Of the 543 questionnaires mailed, 110 (20.2%) were returned. The median respondent firm had a total staff size of 14.5 people with $1.5 million annual revenue. The median product development time was 10 months. Non-response: No significant differences between the full sample of 543 firms and the 110 responding firms were found with respect to sales, total employees and geographic location for these firms. As suggested by Armstrong and Overton (1977), responses from early versus late respondents were compared to further assess non-response bias. The time between when the questionnaire was mailed and when it was returned was used to form early (67%) and late (33%) respondent groups. Subsequent t-tests revealed that no significant differences existed between the groups regarding company size, locations, types of new products being developed, and other constructs used in the study. Therefore, non-response does not appear to be a significant issue4. Measures Competence ambidexterity: Researchers have operationalized the organizational ambidexterity construct in a variety of ways. The “balance view” of ambidexterity is defined as: the absolute difference between exploitation and exploration when a firm places relatively equal emphasis on both dimensions (He and Wong, 2004; Cao, Gedajlovic, and Zhang 2009). The “combined view” is characterized as the product of the two dimensions (He and Wong, 2004; Gibson and Birkinshaw 2004; Cao, Gedajlovic, and Zhang 2009) when a firm wants to score “high on both explorative and exploitative innovations strategies.” Given these two different notions of the ambidexterity construct researched in the past, this paper explores 3

Two reasons motivated this approach: First, new product development is an infrequent activity in many small firms; thus, at any one time many firms are not likely to have recently completed a project. This was evidenced by several responses indicating the firm had not recently developed a new product. Second, the complexity of the new product development task was felt to be such that the quality of the response was likely to decay rapidly with time. Therefore, managers were asked to respond only if they could report on a recently developed project. 4

Some non-respondents were also contacted by telephone in order to determine the reason for nonparticipation. The majority reported that they had not recently developed any new products.

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both the “balanced” (absolute difference) and “combined” (multiplicative) dimension of ambidexterity. This paper defines competence ambidexterity in terms of technical and marketing competencies5. A marketing competence refers to the skills and experience (knowledge) associated with the marketing functional area that a firm needs to develop a new product. Two 5-point Likert rating scales are used to measure the skill and experience (knowledge) assessment of the organization. A comparable construct is developed for technical competence. The “balance view” of the competence ambidexterity is then operationalized as the absolute difference between marketing and technical competence. The absolute difference is reverse coded so that a higher value of this construct indicates a greater balance or match between technical and marketing competencies. Next, the “combined dimension” is developed as the product of the two scores on two competencies. Product Innovativeness: In this paper, a categorical variable as well as a Likert scale was developed to measure the product innovativeness. Following Booz, Allen, and Hamilton’s (1982) taxonomy of new product types and a classification scheme discussed by Wheelwright and Clark (1992), this study considered five categories of new product(s). These categories are: similar to available (me-too) products (6.4% of the survey respondents indicated developing this type of new product), improved versions of existing product(s) (34.9%), line extensions (20.2%), next generation new-to-the market products (25.7%), and radical or breakthrough products that create new industries or markets (12.8%). As can be seen from the descriptions of the five categories, one can assume that the level of innovativeness increases as one moves from developing a me-too product to line extension to next-generation to radical product. Further, a 5-point Likert scale was used to assess the respondent’s agreement with a statement about the innovativeness of a product in a separate section of the survey questionnaire (so as not to influence the two responses). A product is classified as innovative when a survey respondent categorizes it as a new-to-the market or breakthrough product (38.2%) and either agrees or strongly agrees with the statement that the product is highly innovative (70%). 5

Following Atuahene-Gima (2005), and Danneels (2002), the word “competence” is used interchangeably with “capability.”

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Consequently, a new binary variable is created for the product innovativeness construct and only 32.7% of the products in the survey are characterized as innovative products. Initial Market Performance: One can measure initial market performance in many ways. Following Raisch and Birkinshaw’s (2008) suggestion of using multiple dimensions of a firm’s performance to reduce the risk of producing a biased estimate, three different performance measures have been included in this study. All three market performance measures used in this study, however, have a short-term perspective because several environmental and market variables, which are beyond the control of managers, influence long-run market performance, making it difficult to isolate the effect of innovativeness and competence ambidexterity on longer term market performance. Since firms are often reluctant to reveal actual performance data, 5-point Likert rating scales or ratio scales were used to measure the performance assessment of the key informant. Revenue: The revenue construct was measured in terms of sales, revenue growth, and market share using 5-point Likert scales. Profit: The profit construct was measured in terms of profit, break-even time, and return on investment using 5-point Likert scales. Development time: Two ratio-scale items were used to measure development time. The first ratio scale defines the development time from a firm’s perspective. It measures the total project time from the date when a firm first discussed the product idea to the date when the first production for sales from the manufacturing facility began (see Griffin 1993). The second ratio scale, defined from market perspective, measures the total time from when the marketplace or technological development first revealed an opportunity to when a firm’s new product was installed and working for the first time in a customer’s facility. Model Specification This paper considered other factors that may impact the relationship between competence ambidexterity and new product performance. The marketing strategy literature suggests that the performance of a new entry depends on (1) the competitive environment facing the entry,

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(2) the capabilities of the entrant, and (3) the market entry strategy (Gatignon, Weitz, and Bansal 1990). New Product researchers have observed that technical and market uncertainties influence some aspects of NPD effectiveness (Souder, Sherman and Davies-Cooper 1998). Bstieler (2005) suggests that “under condition of uncertainty [new product] project managers are likely to put more emphasis on development proficiency for a lack of sufficient information.” Further, Henard and Szymanski (2001) suggest that market potential and product advantage are among the ten most significant drivers of new product performance. In organizational learning literature, strategic intent (profit versus breakthroughs) was considered to be one of the important tensions firms experience in balancing exploitative and exploratory innovation (Andriopoulos and Lewis 2009). Cao, Gedajlovic, and Zhang (2009) suggest that a firm's ability to benefit from organizational ambidexterity is critically dependent on the internal and external resources available to it. Further, Auh and Menguc (2005) found competitive intensity moderates the relationship between organizational learning (exploitation and exploration) and the firm’s performance. Consequently, the model included the following variables to reduce specification error: Environmental:

market attractiveness, competitive intensity, uncertainty

Strategic Intent:

product development strategy, market entry timing

Project/Product:

product advantage

Organizational:

resources

Functional Form: This paper proposes that product innovativeness influences the relationship between competence ambidexterity and new product performance. As discussed earlier, both “balance” and “combined” dimensions of ambidexterity have been explored here. Consequently, the two equations (Equations 1 and 2), shown below, are used to test the hypothesis concerning the moderating effect of product innovativeness in the relationship between competence ambidexterity and initial market performance. Further, each of the two equations is tested for three different dependent variables: revenue, profit, or development time. Both equations also include an interaction term as this study investigates the moderating effect of product innovativeness. To establish moderation, one needs to show that the

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parameter for the interaction term is significant. The equations also include specification variables and the components (dimensions) of ambidexterity construct (technical and marketing competency).

PERFi =  0 + 1PIi +  2 COMBIAMBIi +  3 PIi .COMBIAMBIi    i X i    J YJ i

(1)

J

PERFi =  0 + 1PIi +  2 BALANCEAMBIi + 3PIi .BALANCEAMBIi   i Xi    J YJ (2) i

Where,

J

PERF

=

initial market performance (revenue, profit, or development time)

COMBIAMBI

=

combined dimension of competence ambidexterity

BALANCEAMBI

=

balance dimension of competence ambidexterity

PI

=

product innovativeness

Xi

=

technical or marketing competency

YJ

=

specification variable (e.g., market attractiveness)

Analysis and Results Reliability and Validity of Measures: Fifteen constructs were developed for the research. All but two constructs were based on multiple item measures. These items, item to total correlation, reliability of measures (coefficient alpha), and the means and standard deviations of the constructs are shown in Table 1. --------------------------------Table 1 about here ---------------------------------Exploratory factor analysis was used to confirm the underlying factor structures of the main constructs. Each multi-item construct was subjected to a varimax rotated principal components factor analysis. Each of these factor analyses produced only one factor with an Eigen value greater than one. The content validities of some measures were checked by examining the relationship between these measures and other measures asked in the questionnaire. For example, the relationship between the product innovativeness measure and development strategy suggested that firms which were developing next generation or radical products were

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also following a “great-leap-forward” strategy, whereas firms that were developing minor improvement or line extension products were following an “incremental” strategy (Chi -square = 23.20, p = .000). Method variance: Use of self-report data in a cross-sectional survey, like the one used in this study, is very prevalent in management research. Such use of a single source or instrument like a survey questionnaire, however, may lead to a “common method variance” (CMV) problem (Podsakoff, MacKenzie, and Podsakoff 2003). As Ganesan, Malter, and Rindfleisch (2005) observed, it is difficult to locate multiple respondents in small organizations in which an owner/entrepreneur is in charge of most decisions. Furthermore, the units of analysis, here, are new product development projects and multiple sources of data (e.g., secondary data) may not be available for confidential new product development projects or for small or privately held organizations as noted by Voss, Montoya-Weiss, and Voss (2006). This study, however, deployed multiple measurement formats and scales (Likert, ratio, and category) in order to reduce the influence of measurement procedure as recommended by Lindell and Whitney (2001). Further, the new product performance studied here is a “less emotionally laden subject” and Chen, Reilly, and Lynn (2005) claims that self-reports of new product performance is less likely to be distorted by a common method variance problem than those self-report studies that investigate topics which generate strong sentiments like attitudes. This study conducted the Harman’s single factor test, a widely used statistical technique, to address the common method variance problem. If the CMV problem exists in the dataset, all 17 variables studied here are hypothesized to load on a single factor. The results of the un-rotated factor solution of the 17 items resulted in the first factor accounting for only 23.2% of the variances and a clear indication of seven total factors, which suggests a relative lack of common method variance (Podsakoff and Organ 1986). However, as Podsakoff, MacKenzie, and Podsakoff (2003) noted, Harman’s test is a diagnostic technique for assessing the extent to which common method variance may be a problem and does nothing to statistically control for method effects. As Rindfleisch, Malter, Ganesan, and Moorman (2008) recommended, this

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study examined concrete and externally oriented constructs, sampled highly educated respondents, employed multiple measurement formats and scales, and developed constructs that are strongly rooted in theory. Further, the result of Harman’s test, as well as findings from other researchers would indicate that the common method variance problem may not be a significant issue in the current study. Model Estimation: The ordinary least squares (OLS) procedure was used to estimate regression coefficients. No evidence of heteroskedasticity was found in the analyses. The focus on only computer-related industries in the study may have alleviated the heteroskedasticity problem. Hierarchical regression analyses were used to test for the moderating effects of uncertainty and product innovativeness. Further, following Cronbach's (1987) recommendation, all competency variables (prior to forming the multiplicative term) were mean-centered in the two equations as a means of addressing a multicollinearity problem. Results: Hypotheses Regarding Moderating Effect of Product Innovativeness This paper investigates the moderating effect of product innovativeness in relationship between two types of ambidexterity and three different measures of initial market performance. Consequently, the results from six different cases are reported here. Tables 2 and 2

3 present the standardized coefficient estimates, their t values and the adj. R from the ordinary least square estimation of the revenue model for “combined” and “balance” dimensions of competence ambidexterity respectively (see Equations 1 and 2). Similar results for profit and development time are reported in Tables 4 to 7. The main findings from these tables confirm earlier discussions of the moderating role of product innovativeness in explaining the relationship between two types of competence ambidexterity and initial market performances. -----------------------------------Tables 2 and 3 about here -----------------------------------Model 1A in Table 2 presents the regression results from a base model that comprises of only control variables including the two variables used in developing the competence

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ambidexterity construct -- technical and marketing competency. Results from Model 1A indicate that the control variables explain 29.6% of the variance in revenue performance. Next, the combined ambidexterity variable is entered into the model (Model1B). Adding this independent variable into the model increased R2 by only 0.7% (F = 0.647, not significant). The same non-significance results are observed when product innovativeness, the other independent variable, is introduced into the model (Model 1C). Finally, Model 1D includes all variables mentioned earlier as well as the hypothesized interaction term between product innovativeness and combined ambidexterity resulting in significant improvement of R2 by 6.8% (F = 7.154, p < 0.01). The results from Model 1D confirms the presence of a significant interaction effect between product innovativeness and combined competence ambidexterity in explaining revenue performance (estimated 3 = 0.386, p < 0.01). Marketing attractiveness, a control variable, is found to be significantly related to revenue. Table 3 presents the results for revenue model for balance dimension of competence ambidexterity. As shown in Model 2D, the interaction term for the balance dimension of competence ambidexterity and product innovativeness is also found to be significant (estimated 3 = 0.565, p < 0.01) for the revenue model. Tables 4 and 5 present the results for the profit model. Again, the significant interaction effect between product innovativeness and competence ambidexterity in explaining profit performance has been observed for both combined (estimated 3 = 0.358, p < 0.05; in Table 4), and balance (estimated 3 = 0.509, p < 0.01; in Table 5) dimensions of competence ambidexterity. -----------------------------------Tables 4 to 7 about here -----------------------------------The regression analyses for the development time model, however, show the mixed results for our hypothesis. While the interaction between product innovativeness and competence ambidexterity is found to be highly significant (estimated 3 = -0.350, p < 0.01; in Table 6), no such significant result has been observed (estimated 3 = 0.021 in Table 7) for the balance dimension case. Given that five out of six cases support the hypothesis, a claim may be made

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about the existence of the moderating role of product innovativeness in explaining the relationship between competence ambidexterity and initial market performance of new products. To examine the nature of the interaction effect, the paper now focuses on product innovativeness as the moderator variable. The value of the estimated parameter 3 indicates how the relationship between competence ambidexterity and initial market performance varies across the two levels of product innovativeness (this construct has been developed as a binary variable). Following Aiken and West (1991), a slope difference test has been conducted by splitting the moderator (product innovativeness) into a high group and a low group and then reestimating the relationship between initial market performance and competence ambidexterity. The plot in Figure 2, Panel A, shows that when product innovativeness is high, the relationship between combined dimension of competence ambidexterity and revenue is positive and statistically significant (b = 0.724, t = 2.810, p < 0.01), but the relationship is not significant (b = -0.015, t = -0.188) when product innovativeness is low. Figure 2, Panel B similarly shows the significant positive relationship between balance dimension of competence ambidexterity and revenue (b = 0.520, t = 2.510, p < 0.02) for the high product innovativeness case, whereas the relationship is negative and less significant (b = -0.347, t = -1.795, p < 0.10) when product innovativeness is low. Thus, the results suggest that achieving combined or balanced competence ambidexterity helps firms improve revenue performance of new products when product innovativeness is high, but may have no impact or a negative impact on revenue performance when developing low innovative products. The Panel A in Figure 3, shows that when product innovativeness is high, a combined dimension of competence ambidexterity has a significantly positive relationship with profit (b = 0.573, t = 2.058, p < 0.05), whereas the relationship is negative and significant (b = -0.166, t = 1.952, p < 0.055) when innovativeness is low. In contrast, the plot in Figure 3, Panel B, shows no impact of balance ambidexterity on profit performance of new products when product innovativeness is high (b = 0.234, t = 1.083) but it has a significantly negative effect on profit when product innovativeness is low (b = -0.606, t = -3.191, p < 0.01). Similar computations for

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the third measure of initial market performance (development time) can be carried out only for the combined dimension of the competence ambidexterity case since the interaction term between competence ambidexterity and product innovativeness is significant only for that situation (see Tables 6 and 7). The results (see the Panel A in Figure 4) make it clear that when product innovativeness is high, the relationship between combined dimension of competence ambidexterity and development time is statistically significant and negative (b = -10.291, t = 2.494, p < 0.02), but the relationship is not significant when product innovativeness is low (b 1.357, t = 1.087). In other words, achieving combined competence ambidexterity helps a firm reduce its product development time or improve profit performance only when it develops a highly innovative product, but no such improvement on new product performance has been observed in the case of achieving balance ambidexterity. The results from the slope difference tests, thus, make it clear that the effect of competence ambidexterity on initial market performance depends on the level of product innovativeness. Discussion and Implications This paper studied how product innovativeness moderates the relationship between competence ambidexterity and new product performance by building on past research in various streams and disciplines. Research in organizational science have studied exploitation and exploratory competency in terms of incremental and radical innovation and investigated the impact of these competencies at the overall firm performance level. This paper studied competence ambidexterity in terms of technical and marketing skills/experiences at the individual new product development project level. This study aimed to reconcile conflicting recommendations about technical and marketing competency in literature on first-mover advantages by suggesting that a firm needs to be ambidextrous with both types of competencies to improve its chance of new product success, but unlike new product researchers who recommend closer interaction between marketing and technical activities, this paper observed that building such ambidexterity pays off only when firms are developing highly innovative products. This study further contributed to existing research on ambidexterity by being one of the few to focus on small firms -- the main source of breakthrough innovations in many industries.

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Researchers are in consensus about the importance of competence ambidexterity in improving firm performances but remain unclear about how firms should achieve such ambidexterity. This lack of clarity has led to past scholars operationalizing a competence ambidexterity construct by “balancing” or “combining” exploratory and exploitation competency and not surprisingly, researchers found mixed results of such competence ambidexterity on firms’ performances. This paper explored both the balanced and combined dimension of competence ambidexterity and has found significant results for both types of competence ambidexterity. Further, this paper studied the impact of competence ambidexterity on three different measures of new product performance, thereby heeding to Raisch and Birkinsahw's (2008) suggestion that future research on ambidexterity should consider multiple dimensions as a one-dimensional indicator of firm performance may run the risk of producing a biased estimate of the impact of ambidexterity on performance. Combining both technical and marketing competencies is found to help firms improve new product performances when they are developing highly innovative products. The finding of the synergistic effect of technical and marketing competencies that enhances new product performances relates to earlier empirical evidence that the interaction between exploration and exploitation will have a positive impact on new product development (Katila and Ahuja 2002). In order for a firm to see the potential value of its radical innovation and to execute the associated product development project successfully, it requires a strong product-market orientation that is implied by high levels of marketing competency (Nerkar and Roberts 2004). A strong market orientation helps firms to move innovation priority toward more radical innovation activities (Baker and Sinkula 2007). A high level of marketing competency enables a firm to acquire knowledge about its customers and competitors, and such market knowledge helps the firm in deciding the types of customer problems it likes to solve, determining early on the design parameters of probable new products and then selecting appropriate technical expertise and knowledge to develop new products. Balancing or matching both technical and marketing competencies is found to improve revenue performances of highly innovative products but worsens profit and revenue

18

performances of less innovative products. Since the balance ambidexterity construct is defined here in a way that a higher value of this variable indicates a greater match between two competencies, the negative impact of balance competence ambidexterity on new product performances suggests that instead of matching a high (low) technical competency with a high (low) marketing competency, a firm would be better off in developing incremental innovations by balancing a high (low) technical competency with a low (high) marketing competency. In other words, effective balancing of technical and marketing competency for incremental innovations requires a high-low matching rather than a high-high matching. This finding echoes Nerkar's (2003) observation that the effective balancing of exploitation and exploration requires a high-low matching rather than a high-high matching. Since time is of the essence to gain a competitive advantage for an incremental innovation, too much of technical and marketing competency may result in time-consuming coordination between two high-powered functional areas resulting in over-engineered and over-featured products that may be “toomuch, or too little, too late” for customers. From the results, this paper then suggests: .

Building competence ambidexterity synergistically to develop new products seems to improve the chance of meeting initial market performance targets for highly innovative products. In contrast, balancing and not synergistic build up of competence ambidexterity may help firms to meet the initial market performance goals of me-too products or minor improvements.

Although the theory of competence ambidexterity and its impact on new product performance is of academic interest, it is also important to managers as firms increasingly rely on new product development to grow and gain a competitive advantage in today’s increasingly competitive world. A recent article by Barczak, Griffin and Kahn (2009), however, suggests that companies have become “slightly more conservative” in selecting more product improvement projects and fewer new-to-the world products with a consequent decline in the percent of sales and profits accounted for by new products. One way firms need to develop more innovative products is to build an appropriate capability to nurture risky product development projects. Since the competency required for radical and incremental innovations are so fundamentally different from each other, pursuing both innovations places conflicting resource and organization demands on the firm and may tempt managers to make a trade-off in pursuing

19

one innovation at the expense of another. Consequently, managers may hope to build either technical competency in developing radical innovations, or marketing competency for incremental innovations. This study suggests, however, that a firm cannot afford to be too specialized with one set of competency and hope to compensate for over-competency in one area with a lack of competency in another. The old argument of a firm being either “technology driven” or “market driven” no longer holds true with the increased level of global competition and accelerated technological development. While “Jack of all trades, master of none” is definitely a bad idea, “master of one” is probably not a good idea either, especially when a firm wants to develop new products in an ever-changing marketplace. This paper recommends companies to build capability in both technical and marketing competencies in order to be successful with their new product development projects. It is, however, not advisable that they need to excel in both competencies for all types of new product development projects. This paper suggests that companies need to build a high level of technical competency coupled with a high level of marketing competency to improve the performance of their radical innovations, since the development of new-to-the-world products requires companies to act quickly in identifying and seizing evolving customer needs as well as emerging technological development. In the case of incremental innovations, companies will be better off by balancing a high (low) level of technical competency with a low (high) level of marketing competency because the cost of building a high level of both competencies does not justify relatively lower returns from minor improvements. Limitations and Future Research Directions This study has several limitations. First, the research findings, here, are based on four computer-related industries. Although such a focus on a major industry group may reduce cross-sectional bias, the idiosyncratic nature of the industry may put more of an emphasis on certain types of development processes rather than some other types. Second, the static nature of cross-sectional analysis precludes the investigation of the full effect of competence ambidexterity on market performances of a new product that occurs over time. To generalize these findings, one needs to test the hypotheses across different industries and also over time.

20

Third, the paper included many explanatory variables to reduce the specification error problem. However, there is a chance that product innovativeness may be correlated with the error terms in the product performance equations. Unfortunately, the Hausman (1978) test cannot be done as the data collected for this study does not have a variable that fits the property of an instrument variable which is related to the product innovativeness variable, but not with new product performances. Finally, the paper uses results from a survey that may be subject to the common method bias (CMB) problem which is very prevalent in many survey-based researches. Though the use of multiple measurement formats and scales in this study may alleviate the problem to some extent, the CMB cannot be eliminated completely. Clearly, there is an opportunity for further work in this area to address some of these limitations. There are ample scopes for further research besides reducing these limitations. First, the organizational competencies in managing and coordinating new product development projects will definitely have an impact on new product performances. It will be interesting to examine how organizational competency variables interact with technical and marketing competencies in influencing the success rates of new products. Second, researchers have looked into the antecedents and mediating factors on small firm innovation (Baker and Sinkula 2009). Similar research on the impact of the antecedents like market or entrepreneurial orientation, and environmental dynamism may be carried out for functional competency at the individual project level. Third, this study suggests a synergistic (high-high) perspective of technical and marketing competency for the successful development of radical innovation and a balancing (high-low or low-high) view of the two functional competencies in improving the performance of incremental innovations. Past research, however, has found a significant impact on radical innovation performance for both a high-high (Katila and Ahuja 2002) and a high-low or a lowhigh (Atuahene-Gima 2005) combination of exploitation and exploratory competency. It seems further research is necessary to resolve these inconsistent findings. Clearly, there is an opportunity for further work in this area to improve our understanding of competence ambidexterity.

21

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24 Raisch, S. and J. Birkinshaw (2008). "Organizational Ambidexterity: Antecedents, Outcomes, and Moderators," Journal of Management, 34(3), 375-409 (June). Raisch S., J. Birkinshaw, G. Probst, and M.L. Tushman (2009). "Organizational Ambidexterity: Balancing Exploitation and Exploration for Sustained Performance," Organization Science 20(4), 685-695 (JulyAugust). Renko, Maija, Alan Carsrud, and Malin Brannback (2009). "The Effect of a Market Orientation, Entrepreneurial Orientation, and Technological Capability on Innovativeness: A Study of Young Biotechnology Ventures in the United States and in Scandinavia," Journal of Small Business Management, 47(3), 331 - 369. Rindfleisch, A., A.M. Malter, S. Ganesan, and C. Moorman (2008). "Cross-Sectional Versus Longitudinal Survey Research: Concepts, Findings, and Guidelines," Journal of Marketing Research 45, 261-279 (June). Robinson, William T., and Claes Fornell, (1985). "Sources of Market Pioneer Advantages in Consumer Goods Industries," Journal of Marketing Research 22(2), 305-327 (August). Robinson, William T., Claes Fornell, and Mary Sullivan (1992). "Are Market Pioneers Intrinsically Stronger than Later Entrants?" Strategic Management Journal 13, 609 - 624. Song, Michael X. and Mark E. Parry (1997). "A Cross-National Comparative Study of New Product Development Processes: Japan and the United States," Journal of Marketing 61, 1-18 (April). Souder, William E. (1988). "Managing Relations between R&D and Marketing in New Product Development Projects," Journal of Product Innovation Management 5, 6-19. Souder, William E., Daniel J. Sherman, and Rachel Davies-Cooper (1998). "Environmental uncertainty, Organizational Integration, and New Product Development Effectiveness: a Test of Contingency Theory," Journal of Product Innovation Management 15(6), 520-533 (November). Tushman, Michael L., and Charles A O’Reilly III (1996). "Ambidextrous Organizations: Managing Evolutionary and Revolutionary Change," California Management Review 38(4), 8 – 30 (Summer). Tushman, M.L. and W.K. Smith (2002). Organization Technology. In Companion to Organization, J. Baum (ed.). Malden, MA: Blackwell, 386-414. Verhees, Frans J. H. M., and Mathew T.G. Meulenberg (2004). "Market Orientation, Innovativeness, Product Innovation, and Performance in Small Firms," Journal of Small Business Management, 42(2), 134 - 154. Voss, G.B., M. Montoya-Weiss, , and Z.G. Voss (2006). "Aligning Innovation with Market Characteristics in the Nonprofit Professional Theater Industry," Journal of Marketing Research 43, 296-303 (May). Wheelwright, Steven C. and Kim B. Clark, (1992). Revolutionalizing Product Development: Quantum Leaps in Speed, Efficiency, and Quality, New York, NY, 237.

25 Table 1 Constructs: Composition, Reliability Assessments, and Descriptive Statistics Construct Name and Measuresa Item - Total Coefficient Correlation Alpha Revenue: The product met revenue goals. 0.58 The revenue growth of the product was as planned. 0.71 0.81 The product met market share goals. 0.69 Profitability Goal: The product attained profitability goals. 0.63 The break-even time of the product since launch was as 0.73 0.85 planned. The product attained return on investment goals. 0.79 b Development Time : Total time from when the market/technological development first revealed an opportunity to when your new 0.78 product was installed and/or working for the first time in a customer’s facility. 0.88 Total time from the date when your company first discussed the idea to the date when first production for sales from the 0.78 manufacturing facility started. Technical Competency Our company had the technical skills to develop the product. 0.47 0.63 Our company had prior experience with technology used in the 0.47 product. Marketing Competency Our company had the marketing skills to develop the product. 0.49 0.65 Our company had prior experience with marketing similar 0.49 products. Balance Competence ambidexterity: Absolute difference between technical and marketing competency (reverse coded) = | technical competency – marketing competency| Combined Competence ambidexterity: Product of technical and marketing competency (mean centered) = technical competency * marketing competency Product Innovativenessc: The new product is next generation product that is new-tothe-market or breakthrough/radical new product that creates new industry/market, and The product is highly innovative to the market. Market Attractiveness: The current market size for our product is attractive. 0.66 The current market is growing at a rapid rate. 0.65 0.77 The product market offers potential for making profit. 0.51 There is a positive economic climate in the marketplace. 0.48

Mean

Standard Deviation

3.27

0.96

3.29

1.05

15.27

15.02

4.14

0.96

3.68

1.08

4.17

0.90

0.39

1.44

32.7%

3.84

0.82

26 Table 1 (Continued) Constructs: Composition, Reliability Assessments, and Descriptive Statistics Construct Name and Measures Item - Total Coefficien Correlation t Alpha Competitive Intensity: There is not much aggressive competitive activity 0.65 in the marketplace. 0.79 There are few or no competitors in the marketplace. 0.68 Competitors are relatively small or weak companies. 0.56 Uncertainty Our product development process was marked by 0.55 technological uncertainty. Our product development process was marked by 0.57 0.69 competitive uncertainty. Uncertainty about customers' preferences and taste plagued 0.40 about our project. Product Advantage: The product is easy to use by customers. 0.61 The product has all the features potential customers need. 0.62 The product expresses quality in its appearance, feel, and/or sound. 0.67 The product is easy to maintain and repair. The product used company resources well to satisfy customer 0.53 0.84 needs. 0.53 The product meets customer needs better than the existing products. 0.67 The product quality is higher than any competing product’s. 0.59 Market Entry Timing Strategy: Was your company the first into the product market with this Yes: 56.7% new product? No: 43.3% Product Development Strategy (Strategic Intent): How would you describe this new product with the overall product development strategy of your company? “Incremental” strategy – frequent development of products Incremental: with incremental changes in technology 68.4% “Great-leap-forward” strategy – infrequent development of Major: 31.6% products with major changes in technology Resource: Our company had the internal financial resources to develop 0.32 the product. Our company had the engineering resources to design the 0.40 0.60 product. Our company had the plants and facilities to manufacture the 0.54 product. a

Mean

Standard Deviation

2.46

1.09

2.68

0.93

3.97

0.68

3.97

0.83

Unless otherwise indicated, all items were measured on 5-point Likert scale with 5 being the most positive. Measured in months. c Combined two scales to create a new category scale. b

27

Table 2 Moderating Effect of Product Innovativeness on Combined Ambidexterity and Revenue

Dependent Variable: Revenue Standardized Coefficient Estimates† Model 1A Model 1B Model 1C Model 1D Combined Ambidexterity Product Innovativeness Combined Ambidexterity * Product Innovativeness

0.104

0.106 0.175

-0.025 0.032 0.386***

Technical Competency Marketing Competency Market Attractiveness Competitive Intensity Uncertainty Product Advantage Market Entry Timing Strategy Product Development Strategy

-0.119 0.273** 0.376*** 0.128 -0.014 -0.020 -0.028

-0.069 0.253* 0.391*** 0.130 0.000 0.009 -0.038

-0.072 0.280** 0.362*** 0.113 -0.019 -0.002 -0.048

0.094 0.065 0.311*** 0.086 -0.071 -0.042 0.061

-0.094

-0.092

-0.188

-0.151

Resources

0.171

0.173

0.172

0.111

R2 Adjusted R2 F-value R2 Change Partial F value Degrees of freedom

0.296 0.203 3.175*** -

0.303 0.199 2.908*** 0.007 0.647 10/67

0.319 0.206 2.811*** 0.016 1.589 11/66

0.387 0.273 3.414*** 0.068 7.154*** 12/65

9/68

† All tests are two-tailed with * = 10%, ** = 5%, and *** = 1% significance.

28

Table 3 Moderating Effect of Product Innovativeness on Balance Ambidexterity and Revenue

Dependent Variable: Revenue Standardized Coefficient Estimates† Model 2A Model 2B Model 2C Model 2D Balance Ambidexterity Product Innovativeness Balance Ambidexterity * Product Innovativeness

0.042

0.045 0.174

-0.326* 0.209 0.565***

Technical Competency Marketing Competency Market Attractiveness Competitive Intensity Uncertainty Product Advantage Market Entry Timing Strategy Product Development Strategy

-0.119 0.273** 0.376*** 0.128 -0.014 -0.020 -0.028

-0.102 0.233 0.379*** 0.123 -0.014 -0.013 -0.028

-0.105 0.258 0.350*** 0.106 -0.033 -0.025 -0.037

-0.012 0.197 0.216* 0.026 -0.163 0.007 0.039

-0.094

-0.093

-0.189

-0.185

Resources

0.171

0.179

0.179

0.042

R2 Adjusted R2 F-value R2 Change Partial F value Degrees of freedom

0.296 0.203 3.175*** -

0.297 0.192 2.826*** 0.001 0.069 10/67

0.313 0.198 2.732*** 0.016 1.559 11/66

0.422 0.315 3.950*** 0.109 12.234*** 12/65

9/68

† All tests are two-tailed with * = 10%, ** = 5%, and *** = 1% significance.

29

Table 4 Moderating Effect of Product Innovativeness on Combined Ambidexterity and Profit

Dependent Variable: Profit Standardized Coefficient Estimates† Model 1A Model 1B Model 1C Model 1D Combined Ambidexterity Product Innovativeness Combined Ambidexterity * Product Innovativeness

-0.128

-0.125 -0.069

-0.259* -0.199 0.358**

Technical Competency Marketing Competency Market Attractiveness Competitive Intensity Uncertainty Product Advantage Market Entry Timing Strategy

-0.023 0.249* 0.329*** 0.104 -0.047 -0.003 0.052

-0.073 0.263** 0.312** 0.097 -0.062 -0.029 0.067

-0.068 0.247* 0.323*** 0.102 -0.053 -0.019 0.071

0.080 0.055 0.278** 0.078 -0.106 -0.068 0.178

Product Development Strategy

-0.199*

-0.210*

-0.176

-0.137

Resources

0.143

0.138

0.138

0.076

R2 Adjusted R2 F-value R2 Change Partial F value Degrees of freedom

0.326 0.234 3.548*** -

0.337 .235 3.301*** 0.011 1.051 10/65

0.340 0.226 2.991*** 0.003 0.266 11/64

0.397 0.282 3.452*** 0.057 5.970** 12/63

9/66

† All tests are two-tailed with * = 10%, ** = 5%, and *** = 1% significance.

30

Table 5 Moderating Effect of Product Innovativeness on Balance Ambidexterity and Profit

Dependent Variable: Profit Standardized Coefficient Estimates† Model 2A Model 2B Model 2C Model 2D Balance Ambidexterity Product Innovativeness Balance Ambidexterity * Product Innovativeness

-0.223

-0.218 -0.060

-0.534*** -0.020 0.509***

Technical Competency Marketing Competency Market Attractiveness Competitive Intensity Uncertainty Product Advantage Market Entry Timing Strategy

-0.023 0.249* 0.329*** 0.104 -0.047 -0.003 0.052

-0.089 0.433** 0.313*** 0.119 -0.040 -0.018 0.048

-0.083 0.415** 0.322*** 0.123 -0.033 -0.010 0.052

0.016 0.331* 0.205* 0.043 -0.153 0.023 0.124

Product Development Strategy

-0.199*

-0.221*

-0.190

-0.193

Resources

0.143

0.103

0.104

-0.019

R2 Adjusted R2 F-value R2 Change Partial F value Degrees of freedom

0.326 0.234 3.548*** -

0.351 0.251 3.515*** 0.025 2.492 10/65

0.353 0.242 3.175*** 0.002 0.205 11/64

0.440 0.333 4.126*** 0.087 9.794*** 12/63

9/66

† All tests are two-tailed with * = 10%, ** = 5%, and *** = 1% significance.

31

Table 6 Moderating Effect of Product Innovativeness on Combined Ambidexterity and Development Time

Dependent Variable: Development Time Standardized Coefficient Estimates† Model 1A Combined Ambidexterity Product Innovativeness Combined Ambidexterity * Product Innovativeness

Model 1B 0.012

Model 1C 0.016 0.190

Model 1D 0.135 0.305** -0.350***

Technical Competency Marketing Competency Market Attractiveness Competitive Intensity Uncertainty Product Advantage Market Entry Timing Strategy

-0.076 0.107 -0.137 0.211* 0.124 0.135 0.078

-0.070 0.106 -0.136 0.211* 0.125 0.138 0.077

-0.075 0.132 -0.152 0.204* 0.110 0.128 0.062

-0.193 0.301** -0.067 0.232** 0.167 0.141 -0.049

Product Development Strategy

0.305***

0.307***

0.200

0.160

Resources

-0.327***

-0.327***

-0.332***

-0.285***

R2 Adjusted R2 F-value R2 Change Partial F value Degrees of freedom

0.260 0.172 2.935*** -

0.261 0.161 2.608*** 0.001 0.010 10/74

0.282 0.174 2.603*** 0.021 2.152 11/73

0.345 0.236 3.163*** 0.063 6.976*** 12/72

9/75

† All tests are two-tailed with * = 10%, ** = 5%, and *** = 1% significance.

32

Table 7 Moderating Effect of Product Innovativeness on Balance Ambidexterity and Development Time

Dependent Variable: Development Time Standardized Coefficient Estimates† Model 2A Balance Ambidexterity Product Innovativeness Balance Ambidexterity * Product Innovativeness

Model 2B

Model 2C

-0.127

-0.142 0.199

Model 2D -0.154 0.199 0.021

Technical Competency Marketing Competency Market Attractiveness Competitive Intensity Uncertainty Product Advantage Market Entry Timing Strategy

-0.076 0.107 -0.137 0.211* 0.124 0.135 0.078

-0.122 0.212 -0.148 0.218** 0.123 0.122 0.076

-0.135 0.253 -0.167 0.212* 0.107 0.110 0.060

-0.131 0.248 -0.172 0.209* 0.102 0.112 0.064

Product Development Strategy

0.305***

0.292***

0.179

0.179

Resources

-0.327***

-0.339***

-0.346***

-0.350***

R2 Adjusted R2 F-value R2 Change Partial F value Degrees of freedom

0.260 0.172 2.935*** -

0.268 0.169 2.714*** 0.008 0.794 10/74

0.291 0.185 2.729*** 0.023 2.375 11/73

0.292 0.174 2.470*** 0.001 0.020 12/72

9/75

† All tests are two-tailed with * = 10%, ** = 5%, and *** = 1% significance.

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Figure 1 The Hypothesized Model of Competence ambidexterity and New Product Performance

34

Figure 2 Interaction of Product Innovativeness and Competence ambidexterity on Revenue

35

Figure 3 Interaction of Product Innovativeness and Competence ambidexterity on Profit

36

Figure 4 Interaction of Product Innovativeness and Competence ambidexterity on Development Time