Rethinking organizational learning orientation on radical and incremental innovation in high-tech firms

JBR-08782; No of Pages 7 Journal of Business Research xxx (2015) xxx–xxx

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Journal of Business Research

Rethinking organizational learning orientation on radical and incremental innovation in high-tech firms☆ Margaret L. Sheng ⁎, Iting Chien National Taiwan University of Science and Technology, School of Management, 43 Keelung Road, Section 4, Taipei 106, Taiwan

a r t i c l e

i n f o

Article history: Received 1 September 2015 Received in revised form 1 October 2015 Accepted 1 November 2015 Available online xxxx Keywords: Absorptive capacity Entrepreneurs High-tech firm Incremental innovation Organizational learning orientation Radical innovation

a b s t r a c t Does organizational learning orientation impede radical innovation? The results show that a high level learning orientation promotes myopic learning and incremental innovation, but constrains experimentation and radical innovation in emerging domains. The study tests hypotheses using two separate data analyses, comparing traditional PLS-SEM with fsQCA. The empirical results show that fsQCA captures better predictive outcomes than PLSSEM. Entrepreneurs and high-tech firms should interpret the findings with some cautions because of their prosperity based on competency and learning orientation in specific fields. For the high-tech industry and entrepreneurial ventures, superior capability in a particular area leads to exploitative learning and cultivate incremental innovation. © 2015 Elsevier Inc. All rights reserved.

1. Introduction Numerous studies emphasize the importance of a firm's learning orientation and its impact on innovation (Chung, Yang, & Huang, 2015; Rhee, Park, & Lee, 2010; Tho & Trang, 2015). Examining the integration of knowledge in firms is particularly useful in elucidating customer needs and market responses to product innovation (e.g., Li & Calantone, 1998). Few studies dispute the effect of organizational learning orientation on innovation, primarily because firms benefit from responding extensively to marketplace conditions. However, the myopia caused by focusing too closely on a firm's dominant markets can mean that new knowledge emerging beyond the scope of view may be undetected. Also, as firms accumulate experience and knowledge, they become increasingly competent at assimilating external knowledge from similar fields. Because of the positive feedback between experience and learning, the self-reinforcing nature of learning leads firms to efficiently use new knowledge into existing knowledge bases (Montgomery & Lieberman, 1998). However, core competencies can fall into competency traps and become core rigidities (Leonard-Barton, 1998). Therefore, a strong learning orientation ☆ This article was presented at the Global Entrepreneurship and Innovation in Management Conference, July 30–31, 2015, National Chung Hsing University, Taiwan. The authors are grateful for the support by the “Academic Exchange and Cooperation Project” between the Top University Strategic Alliance (Taiwan) and the University of California, Berkeley (USA). The authors thank the reviewers of GEIM Conference for their careful reading and suggestions. ⁎ Corresponding author. Tel.: +886 227373285. E-mail address: [email protected] (M.L. Sheng).

in a particular area encourages exploitative activities in the advance of incremental innovation but hinders the exploratory behaviors that lead to radical innovation (Levinthal & March, 1993; Zhou & Wu, 2010). To preclude organizations' learning orientation from dropping into competency traps, the present study explores the relationship between learning orientation and innovation within a broader learninginnovation framework. Absorptive capacity (Cohen & Levinthal, 1990) is a broader learning perspective that has received considerable attention in organizational literature (Huang, Lin, Wu, & Yu, 2015; Lane, Koka, & Pathak, 2006; Leal-Rodriguez, Ariza-Montes, Roldan, & Leal-Millan, 2014; Roberts, 2015). Rosenkopf and Nerkar (2001) also posit that absorptive capacity may enhance exploration and prevent firms from focusing on the development of core rigidities. According to absorptive capacity theory, the ability to evaluate and use external knowledge depends on the level of prior related knowledge. One common business norm mandates that firms scan the external environment and collect market knowledge from all possible sources (Laursen & Salter, 2006). New external knowledge through learning orientation requires systematic processing and represents a firm's internal cognitive map in answering the needs of customers and markets. Therefore, absorptive capacity can serve as an internal filtering mechanism to assist firms in the processing of new external knowledge (Lichtenthaler, 2009). Consequently, the market knowledge process partially generates the joint effect of learning orientation and absorptive capacity on innovation. Most previous research has concentrated on the relationship between learning orientation and innovation by lumping all forms of innovation into a single category (Akgün, Keskin, Byrne, & Aren, 2007;

http://dx.doi.org/10.1016/j.jbusres.2015.12.046 0148-2963/© 2015 Elsevier Inc. All rights reserved.

Please cite this article as: Sheng, M.L., & Chien, I., Rethinking organizational learning orientation on radical and incremental innovation in high-tech firms, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.12.046

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M.L. Sheng, I. Chien / Journal of Business Research xxx (2015) xxx–xxx

Jiménez-Jiménez & Sanz-Valle, 2011). Recognizing the inherent multidimensionality of innovation, the first contribution in this study is to conceptualize the construct at a fined level by discriminating between radical and incremental innovation. Second, the study explores the respective linkages between learning orientation, absorptive capacity, and incremental and radical innovation. Third, the study investigates the possible differential effect of learning orientation on radical and incremental innovation, thereby providing a comprehensive understanding of the influence of learning orientation on organizations. Finally, although prior research indicates that absorptive capacity can enhance innovation (Datta, 2011a), the study discovers that the relative effects of potential and realized absorptive capacity complement learning orientation on radical and incremental innovation. Next, the present study introduces a theoretical framework by first reviewing learning orientation, absorptive capacity, radical and incremental innovation. Subsequently, the study develops a set of hypotheses that examine the direct effect of learning orientation and the complementary effect of absorptive capacity on radical and incremental innovation. After testing the hypotheses by using data collected from 70 high-tech firms in Taiwan, the study presents the results and discusses managerial implications. 2. Conceptual framework and hypothesis development The foundation of the theoretical framework comprises two elements: organizational learning orientation and the effect of absorptive capacity. Learning orientation has proven highly effective in determining how external forces influence innovative processes. However, even powerful external forces cannot affect the outcome without first addressing the effect of absorptive capacity within the organization. This study conceptualizes organizational learning orientation to be the market knowledge process in an organization: acquisition, dissemination, shared interpretation, and responsive action (e.g., Sinkula, 1994; Slater & Narver, 1995). Absorptive capacity highlights learning, the process by which a firm derives and absorbs knowledge from its experiences (Lane & Lubatkin, 1998; Zahra & George, 2002), and an organization's risk-taking action. The two processes are interdependent: to learn from risk-taking action, the organization must acquire market knowledge and undertake responsive action. The two processes are complementary because absorptive capacity is a firm's ability to recognize new external knowledge through learning orientation and then assimilate and apply external knowledge. Therefore, the study examines the complementary effect of learning orientation and absorptive capacity on both incremental and radical innovation. 2.1. Radical innovation and incremental innovation Radical innovation involves the acquisition of new knowledge and the development of new products for new customers or emerging markets while incremental innovation is to enhance the firm's existing knowledge and improve existing products (Benner & Tushman, 2003). Incremental innovation improves existing product-market domains by responding to the needs of existing customers and markets (Lin, McDonough, Lin, & Lin, 2013). Radical innovation commonly destroys existing market positions and broadens new market opportunities (Aboulnasr, Narasimhan, Blair, & Chandy, 2008). Pursuing radical innovation requires the development of unique features and benefits superior to those found in existing products and markets. 2.2. Organizational learning orientation Organizational learning orientation relates to organization-wide activities associated with the creation and use of knowledge for the enhancement of innovation. However, we argue that learning orientation has a more pronounced effect on incremental than on radical innovation through the application of knowledge in the refinement

of products in a manner that is consistent with current organizational processes and routines. Christiansen (1997) also suggests that high-tech firms which have superior capability in a particular field are more likely to search and use their existing knowledge to foster incremental innovation. In contrast, we do not expect to see an equally strong relationship between learning orientation and radical innovation. Radical innovation depends on a firm encouraging questions related to current theoriesin-use (Argyris & Schön, 1997), mental models, dominant logics (Bettis & Prahalad, 1995), and behavioral norms, thereby challenging traditional goals and activities in the organization (Baker & Sinkula, 1999). Radical innovation requires that a firm be able to recognize the value of new knowledge, which in turn provides insights into current knowledge (Cheng & Chen, 2013). Therefore, a high level of learning orientation may be locked in with similar areas, thereby hampering radical innovation. H1. Organizational learning orientation has a stronger effect on incremental innovation than on radical innovation. 2.3. Absorptive capacity Absorptive capacity is the ability to recognize new external knowledge, assimilate, and apply it to commercial ends (Cohen & Levinthal, 1990). Absorptive capacity advances the unique resource and capability of a firm is a key to driving the firm's performance, leading organizational renewal (Datta, 2011b; Narasimhan, Rajiv, & Dutta, 2006), and promoting product innovation (Robertson, Casali, & Jacobson, 2012). Zahra and George (2002) suggest that absorptive capacity has two dimensions: potential and realized absorptive capacity. 2.3.1. Potential absorptive capacity Potential absorptive capacity, which includes knowledge acquisition and assimilation, captures efforts in acquiring and assimilating new knowledge obtained from external sources (Zahra & George, 2002). Enkel and Heil (2014) suggest that potential absorptive capacity can make a firm better to value new external knowledge, thereby averting a firm from being fixed in a special sphere of expertise. Potential absorptive capacity is critical in the development of radical innovation through the recognition of new external knowledge, thereby renewing the stock of knowledge and developing new products that are radically different from existing ones (Jansen, Van Den Bosch, & Volberda, 2005). Therefore, the more new external knowledge is, the more likely the firm achieves radical innovation. Studies also show that the acquisition and assimilation of heterogeneous knowledge has a more pronounced effect on radical innovation than on incremental innovation (Fang, 2008). H2. Potential absorptive capacity has a stronger effect on radical innovation than on incremental innovation. 2.3.2. Realized absorptive capacity Realized absorptive capacity, which includes knowledge transformation and application, encompasses new insights and the consequences associated with the combination of existing and newly acquired knowledge, as well as the incorporation of transformed knowledge into operations (Zahra & George, 2002). Realized absorptive capacity also encourages the development of new products without undercutting existing product lines (Datta, 2011a). Prior research indicates that sustainable competitive advantage relies heavily on a firm's ability to transform and reconfigure knowledge (Rosenkopf & Nerkar, 2001). Realized absorptive capacity can deepen existing knowledge through transformation processes to improve efficiency and aid in the application of knowledge in pursuing product innovation (Jansen et al., 2005). When a firm reconfigures new and

Please cite this article as: Sheng, M.L., & Chien, I., Rethinking organizational learning orientation on radical and incremental innovation in high-tech firms, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.12.046

M.L. Sheng, I. Chien / Journal of Business Research xxx (2015) xxx–xxx

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1996). Realized absorptive capacity increases a firm's capacity to apply new external knowledge, thus enabling the firm to understand and adopt the knowledge for commercial ends. Levinthal and March (1993) posit that firms with exceptional abilities in distinct disciplines are more likely to access existing knowledge for achieving an immediate advantage. Benner and Tushman (2003) claim that process management techniques enhances exploitative learning and facilitates incremental innovation. The following causes result in learning orientation and realized absorptive capacity positively affecting incremental innovation. First, applying similar knowledge in existing domains for the refinement of products fits densely with current organizational systems. Accordingly, strong realized absorptive capacity may help deeper exploitation of existing knowledge. Second, realized absorptive capacity involves transforming and applying valuable knowledge as well as storing new knowledge to warrant knowledge permanence within an organization, thus fostering easy accessibility for knowledge exploitation (Cepeda-Carrion, Cegarra-Navarro, & Jimenez-Jimenez, 2012) and the nurturing of incremental innovation. Third, upgrading knowledge bases and increasing the control of knowledge processes may enhance the ability of firms to assess commercial returns in terms of the time and resources dedicated to achieving incremental innovation.

existing knowledge, the transformation and application process assists the firm in reinterpreting existing knowledge, adding new knowledge, and deleting outdated knowledge (Cegarra-Navarro, Eldridge, & Wensley, 2014), thereby developing alternatives for radical innovation. The diversity of the knowledge determines its influence on radical innovation (Carnabuci & Operti, 2013). Thus, realized absorptive capacity is more likely to reconfigure existing knowledge and change existing routines, both of which have a greater effect on radical innovation rather than on incremental innovation. H3. Realized absorptive capacity has a stronger effect on radical innovation than on incremental innovation. Potential absorptive capacity makes a firm receptive to the acquisition and assimilation of new external knowledge (Lane & Lubatkin, 1998). Ideas and discoveries that occur beyond a firm's search zone are easily overlooked because the firm is unable to comprehend them (Liebeskind, 1996). Although broadening knowledge acquisition and assimilation, potential absorptive capacity does not guarantee exploiting this knowledge to enhance incremental innovation. Potential absorptive capacity requires an open-to-change culture characterized by qualities such as creativity and flexibility (Leal-Rodriguez et al., 2014). Organizational inertia strongly discourages innovative behaviors in firms that have a well-established base. Innovative behaviors often violate existing systems of organizational routines and require the support of a new set of processes that may be incompatible with existing ones. Consequently, organizations strongly resist incremental innovation. Furthermore, assimilating new knowledge into an existing knowledge base can be difficult for firms that have already gained substantial experience in a certain domain. Completely new knowledge from another domain may require a different processing mindset; therefore, the firm may need to unlearn old processes to assimilate the new knowledge (Levinthal & March, 1993). The cost associated with learning new knowledge and restructuring existing knowledge prompts firms to reduce their exploitative behaviors (March, 2006).

H5. Realized absorptive capacity positively moderates the relationship between learning orientation and incremental innovation.

3. Method 3.1. Sample and data collection The sampling frame consists of the top 1000 companies in Taiwan listed in Fortune Magazine in 2014. We receive 200 usable questionnaires from 70 Taiwan-based companies. These responses represent firms operating in the high-tech industry. Consistent with past studies, the study classifies the electricity and electronic appliance manufacturing industry as a high-tech industry (Bregman, Fuss, & Regev, 1991). An independent t-test comparing the mean revenue of responding and nonresponding companies, using data from secondary sources, reveals no significant differences (p N .05), suggesting that nonresponse bias is not a substantive concern. To enhance the ability to reach informants participated in new product development, the study uses a list that identifies senior managers serving in marketing, research-and-development, and/or manufacturing roles. Our interviewers contact each firm on the

H4. Potential absorptive capacity negatively moderates the relationship between learning orientation and incremental innovation. Realized absorptive capacity is a function of transforming and applying new external knowledge (Zahra & George, 2002). Transformation processes expand new external knowledge and improve the efficiency of knowledge absorption (Jansen et al., 2005). Application processes go further by converting knowledge into new products (Liebeskind,

Table 1 Means, standard deviations, and bivariate correlations. Variable

Mean

S.D.

1

2

1. Firm size 2. Firm age

3.4

2.7 .5

1 .28⁎⁎

1

.4

.47⁎⁎

.8

.02

-.01

.12

(.84)

.8

.13

.04

.18⁎

.73⁎⁎

(.81)

.8

.14⁎

.12

.19⁎⁎

.74⁎⁎

.65⁎⁎

(.86)

.8

.10

.06

.11

.67⁎⁎

.60⁎⁎

.76⁎⁎

(.87)

.8

.11

.09

.14⁎

.64⁎⁎

.65⁎⁎

.68⁎⁎

.66⁎⁎

(.86)

.89 .92

.87 .91

.91 .93

.89 .93

.91 .93

1.7 3. Knowledge type

3

.20⁎⁎

4

5

6

7

8

1

.2 4. Incremental innovation 5.3 5. Radical innovation 5.2 6. Potential absorptive capacity (PAC) 5.2 7. Realized absorptive capacity (RAC) 5.2 8. Organizational learning orientation 5.3 Cronbach alpha Composite reliability Note: Numbers in parentheses in the diagonal are the square root of AVE. ⁎ p b .05. ⁎⁎ p b .01.

Please cite this article as: Sheng, M.L., & Chien, I., Rethinking organizational learning orientation on radical and incremental innovation in high-tech firms, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.12.046

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M.L. Sheng, I. Chien / Journal of Business Research xxx (2015) xxx–xxx

Table 2 PLS results. Variables

Radical innovation Model 1

Control variables Firm size Firm age Knowledge type

Incremental innovation Model 2

Model 4

Model 5

Model 6

Coefficient

t-value

Coefficient

t-value

Coefficient

t-value

Coefficient

t-value

Coefficient

t-value

Coefficient

t-value

-.026 -.028 .194**

-.391 -.546 2.631

-.077 -.076 .038

-1.440 -1.555 .987

-.075 -.075 .041

-1.424 -1.711 .980

.084 -.014 .150*

1.154 -.299 1.973

.030 -.052 .054

.800 -1.317 1.180

.030 -.057 .031

.908 -1.444 .748

Independent variables Learning Orientation (LO) Moderator variables Potential AC (PAC) Realized AC (RAC)

.217**

3.203

.227**

3.230

.357***

4.941

.349***

4.842

.473*** .175**

5.949 2.630

.461*** .172**

6.220 2.603

.300** .144

3.215 1.919

.283** .156*

3.083 1.965

Interaction effect LOxPAC LOxRAC Model statistics R2 R2 change

Model 3

.033 .027

.032

.613 .581

.616 .003

.678 .602

-.117* .137*

.040

.535 .495

-1.978 2.131

.561 .026

list by telephone to identify two or three additional key informants knowledgeable about their firm's product innovation process. The firm contacts give the questionnaire in person to the most senior managers able to respond.

terms, the highest VIF in the PLS analysis is less than 4, suggesting that multicollinearity is not a substantive concern (De Vaus, 2002).

3.2. Construct measures

To assess the extent of CMB, the study performs Harman's singlefactor test. Harman's single-factor test produces a five-factor solution, with the first factor accounting for less than 50% of the variance (17.01% of 73.43%), suggesting that CMB is not a substantive issue. The study then performs the partial correlation procedure, comparing the zero-order correlations of the study's variables with their partial correlations, after controlling for a marker variable (Lindell & Whitney, 2001). Because the zero-order and partial correlations are similar after controlling for our marker variable and no correlations significantly differ, the study concludes that CMB is not a substantive concern.

The study measures incremental and radical innovation adopted from Jansen et al., 2005. The study assesses learning orientation using five items modified on the basis of Sinkula (1994) and Slater and Narver (1995). The study assesses potential and realized absorptive capacity adopted from Cohen and Levinthal (1990). Seven-point Likert-type scales, ranging from “strongly disagree” to “strongly agree,” rate the aforementioned constructs in Appendix A.

3.5. Common method bias (CMB)

3.3. Control variables

4. Analyses and results

The study includes firm size, knowledge type, and firm age as control variables. The study controls for firm size given that large firms generally have greater resources than do small firms and those resources contribute to innovation. The study also controls for knowledge type: tacit and explicit knowledge. Firms with different type of knowledge may affect the type of innovation. Tacit knowledge is hard to articulate and difficult to transfer whereas explicit knowledge can be transmitted without loss of integrity. Finally, the study controls for firm age. The firm's industry experience, indicated by its age, may increase learning capability, thereby influencing innovation.

The study uses PLS to evaluate the hypothesized relationships and tests the hypotheses using 500 bootstrapped samples in Visual PLS (version 1.04b1). As shown in Table 2, the coefficients for learning orientation in model 2 and model 5 are significant and positive on radical (β = .217, p b .01) and incremental innovation (β = .357, p b .001). Learning orientation has a stronger effect on incremental innovation than on radical innovation, which supports Hypothesis 1. The coefficients for potential absorptive capacity in model 2 and model 5 are significant and positive on radical innovation (β = .473, p b .001) and

3.4. Reliability and validity Table 1 displays variable means, standard deviations, and bivariate correlations. Cronbach's reliabilities, composite reliabilities, and average variance extracted (AVE) estimates exceed recommended thresholds (Hair, Black, Babin, Anderson, & Anderson, 2010). Partial Least Squares (PLS) indicator loadings are considerably higher for their hypothesized factors than for other factors, and the square root of the AVE for each construct is greater than its correlation with any other construct (Fornell & Larcker, 1981). Overall, these results suggest that the measures possess convergent and discriminant validity. Several of the independent and control variables are moderately correlated. To assess whether multicollinearity is a substantive concern, the study examines the variation inflation factors (VIFs). Even including two interaction

Fig. 1. The moderating effect of potential absorptive capacity on the relationship between learning orientation and incremental innovation.

Please cite this article as: Sheng, M.L., & Chien, I., Rethinking organizational learning orientation on radical and incremental innovation in high-tech firms, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.12.046

M.L. Sheng, I. Chien / Journal of Business Research xxx (2015) xxx–xxx

Fig. 2. The moderating effect of realized absorptive capacity on the relationship between learning orientation and incremental innovation.

incremental innovation (β = .300, p b .01). Potential absorptive capacity has a stronger effect on radical innovation than on incremental innovation, which supports Hypothesis 2. The coefficients for realized absorptive capacity in model 2 and model 5 are significant and positive on radical (β = .175, p b .01) and incremental innovation (β = .144, p N .1). Realized absorptive capacity has a stronger effect on radical innovation than on incremental innovation, which supports Hypothesis 3. Hypothesis 4 proposes that potential absorptive capacity negatively moderates the relationship between learning orientation and incremental innovation. Table 2 shows a significant negatively interaction between learning orientation and potential absorptive capacity on incremental innovation (β = −.117, p b .05), in support of Hypothesis 4. Fig. 1 plots the moderating effect of potential absorptive capacity on the relationship between learning orientation and incremental innovation, which weakens to a greater degree under stronger potential absorptive capacity than under weaker potential absorptive capacity. Hypothesis 5 proposes that realized absorptive capacity positively moderates the relationship between learning orientation and incremental innovation. Table 2 shows that the interaction between learning orientation and realized absorptive capacity has a positive influence on incremental innovation (β = .137, p b .05), in support of Hypothesis 5. Fig. 2 plots the moderating effect of realized absorptive capacity on the relationship between learning orientation and incremental innovation, which strengthens to a greater degree under stronger realized absorptive capacity than under weaker realized absorptive capacity. 4.1. FsQCA Two perspectives guide theory advancement and the analysis of survey data in the present study. “Scientists' tools are not neutral” (Gigerenzer, 1991, p. 19). “Relationships between variables can be nonlinear with abrupt switches occurring, so the same “cause” can, in specific circumstances, produce different effects” (Urry, 2005, p.4). Gigerenzer's (1991) perspective stresses that method, including the tools used to analyze data (e.g., symmetric analysis), influences the researchers' theoretical stance; we advance the view that the symmetric stance to data analysis and theory development has severe limitations; these limitations can be

5

overcome by embracing an asymmetric stance. Urry's (2005) perspective extends and complements Gigerenzer's (1991) thought: the same antecedent conditions have a positive and negative relationship with an outcome condition – which depends on the particular complex configurations of antecedents under examination. This study selects fuzzy set Qualitative Comparative Analysis (fsQCA) for analyzing the data according to a set-theoretic approach. FsQCA facilitates the analysis of how casual conditions jointly (as configurations) link to an outcome of interest (Fiss, 2011; Ragin, 2000). Instead of treating variables as competing causes of an outcome, fsQCA analyzes how variables combine in configurations to generate an outcome (Woodside, 2013a). Consequently, set memberships enable the clearest understanding of the relationship between multiple conditions (Ganter & Hecker, 2014). Using fsQCA to analyze data requires translating the raw data, of both the causal conditions and the outcome, into fuzzy set values (Ragin, 2000) by transforming the data into set membership scores ranging from zero to one. Three anchors calibrate the data (Ragin, 2008): full nonmembership, full membership, and crossover point. FsQCA examines the consistency of complex antecedent conditions in explaining high scores related to an outcome condition (Woodside, 2014; Wu, Yeh, Huan, & Woodside, 2014). Woodside (2013a) stresses the importance of achieving high consistency over high coverage; therefore, this study compares conventional PLS with fsQCA in the empirical analysis. The study utilizes the same variables as those listed in Table 1. Table 3 shows the results from fsQCA. Ragin (2008) recommends that a consistency threshold should not be less than 0.75. The findings reveal that the three fsQCA solutions (complex, parsimonious, and standard) yield the same configurations and a consistency threshold is over 0.75. The empirical results show that fsQCA has better predictive outcomes than does PLS. 5. Discussion The results show that learning orientation has a stronger effect on incremental innovation than on radical innovation (H1) and potential and realized absorptive capacity have a stronger effect on radical than on incremental innovation (H2 and H3). Potential absorptive capacity negatively moderates the relationship between learning orientation and incremental innovation (H4) and realized absorptive capacity positively moderates the relationship between learning orientation and incremental innovation (H5). These findings make contributions to the literature. First, the findings provide a thorough understanding of the effect of learning orientation on incremental and radical innovation. Learning orientation bears an explicit emphasis on the utilization of knowledge that is potentially useful for the organization (Harrison & Leitch, 2005) and its role in refining existing knowledge and processes. The findings represent an important aspect of incremental innovation. Learning orientation underpins the process of internal self-renewal (Covin, Green, & Slevin, 2006), resulting in the self-reinforcement of learning centered on the refinement of existing knowledge, which leads to inflexibility stultifying radical innovation. Absorptive capacity can reduce the impact of

Table 3 fsQCA results. Subset analysis Outcome: incremental innovation — COMPLEX SOLUTION — Frequency cutoff: 1.000000 Consistency cutoff: 0.983401 Solution coverage: 0.964884 Solution consistency: 0.955405

Subset analysis Outcome: radical innovation — COMPLEX SOLUTION — Frequency cutoff: 1.000000 Consistency cutoff: 0.985529 solution coverage: 0.971351 Solution consistency: 0.954685

Potential absorptive capacity* learning orientation Realized absorptive capacity

Raw coverage

Unique coverage

Consistency

Raw coverage

Unique coverage

Consistency

0.937171 0.959824

0.011527 0.034180

0.979936 0.959504

0.927452 0.954236

0.010648 0.037431

0.977010 0.961036

Please cite this article as: Sheng, M.L., & Chien, I., Rethinking organizational learning orientation on radical and incremental innovation in high-tech firms, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.12.046

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M.L. Sheng, I. Chien / Journal of Business Research xxx (2015) xxx–xxx

self-reinforcing learning through the strengthening of newly acquired knowledge. Absorptive capacity is a dynamic capability that helps firms to break down existing operational routines, reconfigure resources, and adapt to changing environments (Eisenhardt & Martin, 2000; Teece, Pisano, & Shuen, 1997). The findings have implications in understanding of the role of absorptive capacity in a firm's adaptation to turbulent environments. The significant risks and uncertainties in a turbulent environment indicate that firms must confront the challenge of new competition, changing technologies, and new customer preferences. Learning orientation may not be adequate for attaining a competitive advantage. Absorptive capacity can track market changes and assess the firm's competency deficiencies, thus refining existing competencies and developing new ones required for the new environment. Absorptive capacity has potential for assisting researchers and organizations in understanding how firms adapt to complex and turbulent environments. A more important contribution is that learning orientation is not significantly related to radical innovation, even under the effect of absorptive capacity. Firms with strong learning orientation may become so entrenched in their accumulated knowledge that they tend to ignore emerging knowledge and/or become unwilling or unable to migrate to new knowledge platforms. Organizational inertia may further discourage radical departures from the status quo, which would require a different set of rules and processes and provide only distant and uncertain returns (Hannan & Freeman, 1984). Therefore, rich experience and expertise in the existing knowledge base may decrease a firm's intention to explore future opportunities arising from a new dominant design (Zhou & Wu, 2010). The findings provide important managerial implications. Firms with strong learning orientation should be aware that market knowledge greatly enhances product extension and refinement (i.e., incremental innovation); however, it may trap firms in existing product trajectories and prevent the exploration of new options (i.e., radical innovation). Learning orientation in high-tech firms occurs when core organizational competencies continually develop and refine, thereby maintaining the competitive advantage of a firm within the focal market. The process of learning orientation involves responding to market conditions, then distributes the resulting knowledge within the organization, and takes responsive actions internally and externally. However, devoting attention to the focal market limits the potential of a firm to pursue alternative strategies. Learning orientation in high-tech firms can thus cause them to fail to appreciate the wider context in which learning takes place, detracting from radical innovation and the ability to discover their current deficiencies. High-tech firms that are strongly learning oriented are likely to suffer from a lack of novel ideas and knowledge necessary for generating new visions and radical innovation. Thus, a strategic dilemma ensues when core competencies become core rigidities. To resolve this strategic dilemma and overcome the myopia of learning orientation, high-tech firms can implement exploratory learning, which involves learning and acquiring knowledge outside existing customer boundaries and often entails experimentation and risk-prone behavior. Enabling the programmatic discovery of resources and technologies, exploratory learning is a more active process than learning orientation and is more crucial than absorptive capacity in the transition from market knowledge to radical innovation. Several limitations to the present study warrant discussions. First, the study is unable to collect data from a random sample of high-tech companies, wherein the collection of data depends on the willingness of firms to participate. This limitation bounds the degree of generalizability. One interesting follow-up study will involve the collection of data from a random sample of firms. Second, the effect of learning orientation has a stronger effect on incremental innovation than on radical innovation. Future research can evaluate the possibility that learning orientation influences radical innovation. Potential studies can examine from the proactiveness perspective of “desire to learn” as opposed to reactive learning orientation may indeed make radical innovation possible.

Appendix A. Items and factor loadings

Construct/items Radical innovation We accept demands that go beyond existing products and services. We invent new products and services. We experiment with new products and services in local markets. We commercialize products and services that are completely new. We frequently search and approach new clients in new markets. Incremental innovation We frequently refine the provision of existing products and services. We regularly implement small adaptations to existing products and services. We introduce improved but existing products and services for local markets. We improve our provision’s efficiency of products and services. We increase economies of scales in existing markets. Absorptive capacity Potential absorptive capacity We have frequent interactions with clients and competitors to acquire new knowledge. We collect industry information through informal means (e.g. talks with trade partners and industry friends). We are quickly to recognize shifts in our markets (e.g. competition, regulation, demography). New opportunities to serve our clients are quickly understood. We quickly analyze and interpret changing market demands. Realized absorptive capacity We record and store newly acquired knowledge for future references. We quickly recognize the usefulness of newly external knowledge to existing knowledge. We constantly consider how to better exploit knowledge. We clearly known how to implement new products and services. Learning orientation We often attend all sorts of expert presentations to improve our knowledge of production, marketing, and management. We often exchange ideas on learned knowledge to improve our knowledge of production, marketing, and management. Our employees often share the learned knowledge with top managers. We encourage teamwork, team decision making, and internal communication. We have extensive knowledge and experience in developing new products.

Standardized Loadings

.712 .853 .866 .832 .803

.774 .819 .863 .883 .851

.823 .814 .898 .873 .891

.862 .891 .901 .818

.827

.819 .882 .889 .891

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Please cite this article as: Sheng, M.L., & Chien, I., Rethinking organizational learning orientation on radical and incremental innovation in high-tech firms, Journal of Business Research (2015), http://dx.doi.org/10.1016/j.jbusres.2015.12.046