R&D CAPITAL, ENVIRONMENTAL UNCERTAINTY AND PRODUCT INNOVATION. A CASE OF POLAND

Author Magdalena Pichlak, Chair in Management, University of Silesia, Poland E-mail: [email protected]

Co-author Mariusz Bratnicki, Head of Chair, Chair in Entrepreneurship University of Economics in Katowice, Poland

SUMMARY

In the paper an analysis of the relationship between R&D-related resources and product innovation under different contextual conditions is presented. By application both the resource-based theory and the contingency perspective to the study, it was found that the impact of R&D-related human-, R&D-related relational capital and their interaction on product innovation varies across the levels of environmental uncertainty. The study of the sample of 219 Polish companies from the Silesian Region indicates that aggressive strategic posture lies at the core of this debate being an important but underestimated moderating variable. More pointedly, as emerges from the study, the effects of R&D-related human-, R&D-related relational capital and their interaction on product innovation under conditions of high environmental uncertainty are strengthened as aggressive strategic posture increases. The study contributes to the emerging literature on innovation by moving beyond the direct effects to explore a moderated model. Implications for future research are also discussed.

Keywords: product innovation, human capital, relational capital, environmental uncertainty, aggressive strategic posture.

INTRODUCTION Innovation is widely recognized as a key driver of a company’s success that is closely linked to a company’s R&D resources (Xu, Sirmon & Gao, 2010). Several types of resources related to innovation have been identified in the previous studies (Subramaniam & Youndt, 2005), especially those involved in R&D efforts. These studies have strongly supported the traditional view that human capital (Helfat & Raubitschek, 2000) and relational capital (Ahuja, Lampert & Tandon, 2008) induce a company’s innovative performance, being the resources most important for R&D activities.

As stated in the innovation and management literature, R&D-related human- and R&Drelated relational capital have a strong and positive impact on product innovation (e.g. Dierickx & Cool, 1989; Rao & Drazin, 2002; Ahuja, Lampert & Tandon, 2008; Xu, Sirmon & Gao, 2010). However, there is no empirical research reported examining whether this relationship depends on the various contextual conditions. The presented study aims to fill this research gap by considering and empirically testing how environmental uncertainty and a company’s aggressive strategic posture affect the relationship between the two different kinds of R&D-related resources as well as their interaction and product innovation, which have not been explored in previous research. Consequently, applying both the resource-based theory and the contingency perspective to the presented study appears to be advantageous for understanding how these kinds of R&D-related resources affect product innovation, through direct and indirect ways. Environmental uncertainty describes the unpredictability of change in a company’s external environment (Liu & Huang, 2009). It is often caused by rapid and unexpected changes in markets or technologies (Bstieler, 2005) and offers an increased range and frequency of potential innovation (Russel & Russel, 1992; Freel, 2005). Under such conditions, companies have to be more innovative by gaining new valuable and rare knowledge, technology skills and abilities from the internal as well as the external sources (Ahuja, Lampert & Tandon, 2008) in order to cope with the challenges related to the intensified market and technological competition. In other words, companies need to flexibly adapt to their environmental changes and renew their resource bases (Tseng & Lai, 2011) to attain flexibility and novelty in product innovation. Additionally, because the effective patterns of “the renewing process” that manipulates resources into new value-creating strategies change with environmental 2

dynamism (Eisenhardt & Martin, 2000), the main effects of R&D-related resources and product innovation may vary according to different strategic actions taken up by CEO or other high-ranking executives in order to maximize the probability of exploiting the potential market and technology opportunities (Joshi & Das, 2009). Thus, a more specific evaluation of the effects of R&D-related resources on product innovation turns out to be particularly important, especially in the context of uncertain environment and such aggressive, bold and wide-ranging actions.

The study is the first to consider a multi-dimensional model of R&D-related resources and product innovation. It contributes to the innovation and management literature in a few ways, which have not been explored before. Firstly, the primary objective of the presented study is to examine the antecedents of product innovation, in the context of environmental uncertainty that may better explain the relationship between R&D-related resources and product innovation. The purpose of the study is to further delineate and empirically verify the relationship between the two significant R&D-related resources (human- and relational capital) as well as their interaction and product innovation through the environmental evaluations. Secondly, in order to examine these linkages more extensively, the study considers an additional internal contingent factor (e.g. aggressive strategic posture) by indicating that the innovation effects of R&D-related resources in uncertain environment are stronger when aggressive strategic posture is high. Furthermore, the joint utilization of these R&D-related resources facilitates product innovation, especially under the conditions of environmental uncertainty, and this effect becomes more evident after controlling the influence of aggressive strategic posture. Therefore, looking from the resource and the contingency perspectives, the study may shed some light on whether or not a company can benefit more from developing R&D-related resources and simultaneously adopting aggressive strategic posture in the context of uncertain environments.

The presented study goes beyond the common approach to conceptualizing the resourceinnovation relationship and highlights the benefit of applying a moderated model. Additionally, the use of Polish data provides a fresh look at the probable innovation effects of R&D-related resources, especially in emerging economies. Increasing technological and market uncertainty in Poland, resulting from the rapid, major economic, social, and political changes that the country has been undergoing since 1989, made companies to be more innovative to grasp the opportunities and cope with the challenges of the environment. 3

Therefore, a more specific evaluation of the relationships between the two significant R&Drelated resources (human- and relational capital) as well as their interaction and product innovation turns out to be particularly important, especially in such a context.

The paper is organized as follows: first a review of the relevant literature is presented and the hypotheses are developed. This is followed by a brief discussion of the research methodology and the survey. Next, the research findings obtained from the empirical analysis and their implications are considered. A concluding section summarizes the paper and outlines issues for further research.

THEORETICAL BACKGROUND

R&D-Related Resources and Product Innovation The presented study is based on the resource-based view of the company (Barney, 1991; Rumelt, 1984; Wernerfelt, 1984), according to which a company’s characteristic resources and abilities may be the source of its innovative advantage. RBV reflects the internal characteristics of companies through two kinds of capital. These are: human capital, which represents a creation of the new, internal knowledge through identifying essential problems by employees and next discovering valuable, new solutions, which lead to a development of new products (Shih, Yang & Chiang, 2009), and relational capital, consisting in e.g. an access to a range of the complementary external, valuable and rare knowledge (Ahuja, Lampert & Tandon, 2008).

As it has been reported in the existing literature, human capital represents the knowledge, experience, and attributes of employees (Harris & Helfat, 1997), as they constitute a strategic intangible resource, enabling creation of a company’s competitive advantage (Eddleston, Kellermanns & Sarathy 2008). Human capital plays an essential role in stimulating product innovation, since it personifies the creativity and intelligence of skilled, qualified employees with expertise in specific domains (Xu, Sirmon & Gao, 2010). Qualified employees constitute the main source of new ideas and knowledge, which lead to a development of new products (Rao & Drazin, 2002). Moreover, as much of a company’s knowledge resides in its human capital, employees’ tacit and codified knowledge creates an effect of complementarity, which positively influences product innovation (Helfat & Raubitschek, 2000). 4

Although R&D-related human capital constitutes a strategic resource, enabling creation of a company’s competitive advantage (Eddleston, Kellermanns & Sarathy, 2008), it is often criticized because it is easily lost when the key employees leave the company. Moreover, a company’s ability to stimulate innovation through purely internal knowledge may be exhausted because of the complexity of a technological transition (Hagedoorn, 1993). The aforementioned reasoning is consistent with the assertion of Ahuja, Lampert and Tandon (2008) and other scholars who have argued that the probability of advancing new products requires various solutions that absorb knowledge from a myriad of external sources, such as customers, suppliers, competitors, experts, consultants, and universities (Teece, 1986; Jorde & Teece, 1990; Kogut & Zander, 1992; Helfat & Raubitschek, 2000; Luo, 2007; Ahuja, Lampert & Tandon, 2008).

The knowledge and technological assets, being indispensable for the efficient generation and implementation of product innovation (with a high level of novelty), are very rarely accessible within a single company. Hence, generation and implementation of this type of innovation require an access to a range of the complementary external knowledge. Integration, coordination and reconfiguration of one’s own abilities, result in creation of new combinations of possessed capabilities (Kogut & Zander, 1992). Moreover, some disembodied assets (e.g. know-how or reputation) are often extremely expensive. Since an independent development is impossible because of the costs of the transactions and legal limitations, the only real alternative consists in undertaking cooperation (Teece, 1986). R&Drelated relational capital increases the pool of knowledge. The resultant knowledge is available to all partners, given the public good nature of knowledge (Jorde & Teece, 1990). R&D-related relational capital helps to collect various competences – all partners can benefit from the so-called complementarity effect in the context of knowledge sharing (Ahuja, Lampert & Tandon, 2008). Moreover, an access to a range of the complementary external knowledge of suppliers and customers (Helfat & Raubitschek, 2000) as well as industry members (Luo, 2007) helps to widen a company’s knowledge base.

R&D-Related Resources, Product Innovation and Environmental Uncertainty The concept of environmental uncertainty has been defined in a variety of ways in the previous innovation and management literature (for a review see Duncan, 1972). It generally refers to the rate of change and the degree of unpredictability and instability of the 5

environment (Liu & Huang, 2009). According to the previous innovation and management literature, the more complex and changing the environment, the higher the level of environmental uncertainty (Russel & Russel, 1992; Damanpour, 1996; Bstieler, 2005; Freel, 2005; Wei, Wu & Yang, 2009). According to Henderson (1993), the organizational outcomes are often affected by inadequate or delayed responses to the environmental change. Therefore, companies need to act quickly to manage environmental uncertainty as well as to predict future conditions (Gao, Gao, Shu & Wang, 2010) in order to survive in such environment.

A high level of environmental uncertainty increases the importance of generation and implementation of product innovation. Moreover, under such conditions, companies face a greater risk that their existing resources and capabilities become obsolete more rapidly. Gaining the competitive advantage via new products in relatively stable or mature markets might be provided through efficient, effective and comprehensive understanding of customers’ needs (Bstieler, 2005). According to Bstieler (2005), when the environment gets increasingly uncertain, the search for the competitive advantage via new products may be critically linked to the accumulation of variety of resources within a company. Thus, R&Drelated resources would be expected to be of a considerable importance for product innovation because there is a greater need to gather market- and technology-related information under conditions of high uncertainty.

Increasing technological and market uncertainty forces managers to make decisions based on complex and imprecise information (Ben-Menahem, Jansen & Van den Bosch, 2011). As such, CEO and other high-ranking executives usually encounter serious challenges to conduct business in such circumstances (Gao, Gao, Shu & Wang, 2010). This provides a framework for CEO to carry out strategic actions that rely mainly on the internal knowledge possessed by employees, especially those with certain cognitive capabilities, expertise and technical knowledge. This statement is based on the belief that intangible resources, such as human capital, constitute the most critical, competitive assets possessed by a company (Grant, 1996). If properly motivated human capital is not only more likely to produce a short-term competitive advantage, but also may ensure the long-term survival of a company, especially in uncertain environment (Parzefall & Karna, 2011).

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Additionally, as Bstieler states “managers who are uncertain about the state of their environment will spend a greater amount of resources on environmental scanning and forecasting than those who are more confident that they understand the environment” (2005:273). Consequently, developing higher levels of R&D-related relational capital (that provides the information of customers, suppliers, competitors, consultants, universities and other research institutes) is more effective for creating new products by recognizing and assimilating the external emerging knowledge. Moreover, it constitutes an important support factor in a company’s innovation process because it allows the exchange of tacit knowledge through personal face-to-face interactions (Parzefall & Karna, 2011).

Accordingly, it is argued that R&D-related human- and R&D-related relational capital operate in distinct but interrelated ways as they can cover each other’s limitations and deficiencies. Developing solely R&D-related human capital, especially under the conditions of environmental uncertainty, may result in “lock-in” effect which limits the external sharing of information and knowledge. Additionally, as Xu, Sirmon and Gao state “relying on internal knowledge increases path dependence in learning and knowledge accumulation, thereby increasing myopic learning and knowledge traps, which inhibit product innovation” (2010:8). Similarly, developing only R&D-related relational capital may inhibit product innovation by leading to unprofitable strategic behavior. For instance, companies may send only relatively inefficient researchers, providing qualitatively poor inputs even when meeting the quantitative requirements of the R&D-related projects (Ahuja, Lampert & Tandon 2008). Such behavior is of critical importance in environments in which future evolutions in markets or technologies are hard to predict. Therefore, environmental uncertainty originating in markets and technologies may impact R&D-related resources and ultimately, their interaction, due to the complementary effects.

R&D-Related Resources, Product Innovation, Environmental Uncertainty and Company’s Aggressive Strategic Posture Companies are likely to pursue more aggressive strategies as environmental uncertainty increases (Ozsomer, Calantone & Di Benedetto, 1997; Freel, 2005). Following Joshi and Das: “an aggressive posture may be characterized by bold and wide-ranging actions by top managers to achieve their objectives, allowing the organization to maximize the probability of exploiting potential market opportunities” (2009:9). Aggressiveness allows a company to keep its rivals at bay (Joshi & Das, 2009) and thus it is considered to be critical for improving 7

a company’s performance (Davies & Walters, 2004). In such circumstances managers may follow different strategies (Miles & Snow, 1978) due to a company’s entering the market with innovative products. Being the first-mover or pioneer in the market, in order to meet the changing market opportunities, may require an access to the new, valuable, internal as well as the external knowledge. Such strategy enables to pursue radical ideas, introduce products which have not been thought of before and lead in the innovation race (Puri & Srivastava, 2009).

The previous studies have shown that following the pioneering companies and companies of more aggressive strategy may result in playing more active role in generating and implementing of valuable product innovation (Puri & Srivastava, 2009), whereas the innovation output of followers and late movers may depend on individual changes in the industry as they follow the original innovators (Miller & Friesen, 1982). Thus, it may be hypothesized that aggressive strategic posture positively stimulates the relationship between R&D-related resources and product innovation in companies that have to face a strong environmental uncertainty. In the light of the above, it is suggested that:

Hypothesis 1: The innovation effects of R&D-related human capital in uncertain environment are stronger when aggressive strategic posture is high.

Hypothesis 2: The innovation effects of R&D-related relational capital in uncertain environment are stronger when aggressive strategic posture is high. Hypothesis 3: The innovation effects of the interaction between a company’s R&D-related human- and R&D-related relational capital in uncertain environment are stronger when aggressive strategic posture is high.

METHODOLOGY

Sample. Data for the study were collected by using a questionnaire survey, a part of a wide questionnaire survey conducted within the research grant No. N N115 257434, entitled “Determinants of the enterprises innovation in the industrial area – by example of the Silesian Voivodeship”. Two surveying methods were adopted: Computer Assisted Telephone Interview (CATI) and Paper And Pencil Interview (PAPI). All data were collected from 8

January to June 2010. Complete data sets were received from 219 Silesian companies, which makes 4% of 5177 companies contacted and asked to fill in the questionnaire.

The sample of 219 Polish companies from the Silesian Region (with at least 20 full time employees) was used in order to empirically test the above mentioned hypotheses. The data set consists of Silesian companies active in one of the following industry sectors: biotechnology, power industry, environmental protection, ICT, materials processing and production, transport infrastructure and medical technologies. The survey was directed to CEO or other high-ranking executives (i.e. presidents, vice-presidents, directors, or general managers), who are the appropriate informants to provide resource related information. Respondents were ensured of the confidentiality and offered a summary of the results (Pichlak & Bratnicki, 2011). A non-response bias was tested in order to validate the sample’s representativeness. In particularly, differences between respondents and non-respondents were examined. T-tests indicated that there were no significant differences based on the number of full-time employees. Thus, a non-response bias did not seem to pose a problem to the study.

Measures. Three steps were taken to appropriately measure the constructs of the presented study. In order to find relevant indicators, the review of the existing literature was made. All items in the questionnaire stemmed from the empirical studies cited earlier. Thus the questionnaire developed on the basis of a thorough literature review seems to be validated and reasonable. In the next step, the items were translated into Polish and then independently back into English. This resulted in minor changes in the idiomatic or colloquial wording of a few items. Multi-item scales were used to operationalize all the constructs.

Dependent Variable. The dependent variable in the study was product innovation. It was measured as the number of new products launched in the last three years. The criteria for new innovative products mentioned in the survey were adopted from the study by Puri and Srivastrava (2009). Some researches (Griliches, 1990; Choi & Lee, 2008) use an alternative measure of innovation, such as the number of patents granted. However, the use of patent data is considered to be imperfect. First, award of the patent does not necessarily lead to a commercial application of the patented inventions (Basberg, 1987). Second, the patented inventions differ considerably in respect to quality features (Griliches, 1990). Third, there are extremely innovative inventions which have never been patented (Kamien & Schwarz, 1975). 9

Hence, the number of new products launched seems to be an appropriate measure of product innovations, and therefore it was used in the presented study. The use of this measure allowed also for a across sectors comparison. The mean was 12.53 with a standard deviation of 8.66.

Independent Variables. The first independent variable was R&D-related human capital. For the purpose of the study it was measured as the ratio of R&D employees to the total number of employees. The mean was 0.22 with a standard deviation of 0.49. The second independent variable, R&D-related relational capital was operationalized using 5 items, which were measured on a 7-point Likert scale, from 1 – “strongly disagree” to 7 – “strongly agree” and took into account a company’s relationship with customers, suppliers, competitors, consultants, and universities. An exemplary question on a company’s R&D-related relational capital is “Our company has a close relationship with customers”. In the previous studies by Subramaniam and Youndt (2005) and Xu, Sirmon and Gao (2010) similar operationalization of a company’s R&D-related relational capital was applied. The mean was 4.79 with a standard deviation of 1.57. The reliability of this construct is acceptable (Cronbach’s alpha for this scale was 0.86). Moderator Variable. The moderator variable in the study is a company’s aggressive strategic posture which reflects bold and wide-ranging actions taken up by CEO or other high-ranking executives in order to achieve their strategic goals and objectives. It was captured by two items, rated on a 7-point Likert scale, from 1 – “strongly disagree” to 7 – “strongly agree” used by Joshi and Das (2009). Respondents were asked to comment on the following items: “My company typically adopts a bold, aggressive strategic posture in order to maximize the probability of exploiting potential market opportunities” and “My company has top management, who believe that bold wide-ranging acts are necessary to achieve their objectives”. The mean was 4.26 with a standard deviation of 1.28. This variable’s Cronbach’s alpha was 0.91. Control Variables. Four control variables (the sector dummy variable, the respondents’ age and their organizational tenure as well as a company’s size) were used in the study to account for other factors that could influence resource based activities and product innovation. Firstly, a dummy variable for companies active in manufacturing, and service sector was included to account for innovation heterogeneity across sectors. Secondly, it has been suggested in the innovation and management literature that the age of CEO or other high-ranking executives 10

positively affects their motivations to invest in innovation (Bantel & Jackson, 1989; Ahuja, Lampert & Tandon, 2008). Therefore, the natural logarithm of the respondents’ age was included in the statistical analyses reported below. The mean was 3.26 with a standard deviation of 0.77. Thirdly, according to the relevant literature, also organizational tenure of CEO or other high-ranking executives affects their ability to implement strategic changes. Longer tenure reduces their willingness to implement innovation (Ahuja, Lampert & Tandon, 2008; Hambrick & Mason, 1984). Therefore, the natural logarithm of the number of years of the respondent’s activity within a company was included in the statistical analyses (Vaccaro, Van den Bosch, Jansen & Volberda, 2009). The mean was 2.18 with a standard deviation of 0.59. Finally, it is commonly accepted in the previous studies that a company’s size seems to be a “mandatory covariate” in empirical and theoretical analyses, regarded to be the key driver of R&D productivity in studies of innovation (Lejarraga & Martinez-Ros, 2009). Therefore, the natural logarithm of full time employees as the last control variable was included. The mean was 3.82 with a standard deviation of 0.85.

ANALYSIS AND RESULTS

The analysis consists in a hierarchical multiple regression for which product innovation was considered as the dependent variable. First of all, in order to investigate the specific direction and strength of the moderation effect between companies facing high and low levels of environmental uncertainty, the total sample of 219 companies was divided into the two subgroups using the median split. 74 companies were classified as facing high level of environmental uncertainty, whereas 145 companies were classified as facing low level of environmental uncertainty.

After demonstrating the distinctiveness of the major variables used in the study a three-step hierarchical moderated multiple regression analysis was conducted (separately for companies facing high and low levels of environmental uncertainty). This hierarchical regression analysis provides several interesting insights for theory and practical implications. In the first step of the regression analysis, the control variables (sector dummy variable, respondents’ age, their organizational tenure and a company’s size) were entered into the equation. It was followed by the main independent variables (R&D-related human-, R&D-related relational capital and their interaction) in the second step. Moderating variable (aggressive strategic posture) was entered into the equation in the third step. The final models (Model 3 for 11

companies facing high level of environmental uncertainty and Model 6 for companies facing low level of environmental uncertainty) test the above mentioned hypotheses. Following Aiken and West (1991), the variables were centered to reduce the potential problem of multicollinearity.

Descriptive statistics. The descriptive statistics of all major variables used in the analysis is presented in Table 1 and correlations between all variables examined in the study are given in Table 2. ---------------------------------Insert Table 1 about here ----------------------------------

As expected, product innovation is positively correlated with R&D-related human- and R&Drelated relational capital with correlation coefficients of 0.74 and 0.63 respectively.

---------------------------------Insert Table 2 about here ----------------------------------

Test of Hypothesis. Table 3 presents the results of the hierarchical regression analysis performed for the sub-group of companies facing high (Model 1, Model 2 and Model 3) and low (Model 4, Model 5 and Model 6) levels of environmental uncertainty.

---------------------------------Insert Table 3 about here ----------------------------------

Based on the results obtained, it is worth noting that for the sub-group of companies facing high level of environmental uncertainty, their size was found to be significant in all models (β = .013, p < .1, in Model 1; β = .043, p < .1, in Model 2 and β = .031, p < .1, in Model 3). Such results emphasize an innovative advantage of the large-sized companies under conditions of high environmental uncertainty.

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The results from Model 2 indicate a statistically significant and positive relationship between R&D-related human capital (β = .201, p < .1) and R&D-related relational capital (β = .112, p < .05) as well as their interaction (β = 1.063, p < .05) and product innovation under the conditions of high environmental uncertainty. The adjusted R2 value increased significantly from Model 1 to Model 2, indicating significant main effects. Next, the moderating variable (aggressive strategic posture) was entered into the equation (Model 3), and the overall model was significant (F value = 9.621, p ˂ .05), whereas the adjusted R2 value increased from previous models, indicating the significant moderation effects. Hypothesis 1 states that the innovation effects of R&D-related human capital in uncertain environment are stronger when aggressive strategic posture is high. The empirical results support this Hypothesis as the interaction term between R&D-related human capital and aggressive strategic posture is positive and significant (β = .231, p < .1, in Model 3). Hypothesis 2, which tests the positive moderating effect of aggressive strategic posture on the relationship between R&D-related relational capital and product innovation under the conditions of high environmental uncertainty, is supported as well. The interaction term between R&D-related relational capital and aggressive strategic posture is also positive and significant (β = .097, p < .1, in Model 3). Additionally, the results from Model 3 indicate a statistically significant and positive correlation between the interaction of R&D-related human- and R&D-related relational capital and product innovation (β = 1.142, p < .05), which supports Hypothesis 3.

Similarly, in the analogous analysis for the sub-group of companies facing low environmental uncertainty (Model 5) both independent variables were found to be significant (β = .152, p < .1 for R&D-related human capital and β = .501, p < .1 for R&D-related relational capital). Accordingly, for the second sub-group of companies the interaction term between these kinds of R&D-related resources is also positive and significant (β = .208, p < .1, in Model 5). Surprisingly, for the sub-group of companies facing low environmental uncertainty the interaction terms between R&D-related resources (solely and in the interaction) and aggressive strategic posture are not statistically significant (Model 6).

DISCUSSION

It has been suggested in the previous studies that product innovation requires considerable resources (Galende & de la Fuente, 2003; Rosenbusch, Brinckmann & Bausch, 2009). In the resource-based perspective, companies differ fundamentally in respect to possessed 13

resources, utilization of which affects their performance (Barney, 1991; Wernerfelt, 1984). The results of the study confirmed the previous ones (e.g. Xu, Sirmon & Gao, 2010), by indicating that the relation between each of the analysed resources and product innovation is positive and statistically significant. Product innovation is greater in case of developing valuable and rare knowledge embedded in R&D-related human capital (Rao & Drazin, 2002). Also relational capital has a positive effect on product innovation, as it allows for important exchange of information and knowledge through which companies may improve their innovation outputs (Ahuja, Lampert & Tandon, 2008).

Surprisingly, it was found that under the conditions of high environmental uncertainty this is the human capital which plays a crucial role, whereas for companies facing low environmental uncertainty R&D-related relational capital seems to be more important. As emerges from the study, for companies operating in less uncertain environment the benefits of the external knowledge acquisition for product innovation are more likely to be relatively significant. R&D-related relational capital offers useful information for conducting innovation projects properly and therefore improves a company’s strategic position in relatively stable or mature markets. However, for companies operating in highly uncertain environment, R&D-related relational capital secures access to information and knowledge as well, but it might undermine a company’s innovative output, because under such conditions, companies may be at greater risk of unintended flow of rare and valuable knowledge (Wadhwa, Freitas & Sarkar, 2011). Therefore, in such circumstances, the qualified employees constitute the essential source of new ideas and knowledge which, when used properly, leads to a development of new products (Rao & Drazin, 2002).

The study was aimed at answering the question whether possessing solely the R&D-related resources (R&D-related human- and R&D-related relational capital) is sufficient to implement effectively product innovation, especially in the context of environments in which future evolutions in markets or technologies are hardly to predict. As such, the presented study provides substantive theoretical and practical insights for academics and practitioners. The results of the research conducted indicate that under the conditions of high environmental uncertainty this is the aggressive strategic posture which is of critical importance along with high quality R&D-related resources. Therefore, the most important implication that comes from the presented study is the notion that under conditions of high environmental uncertainty, companies need to be more aggressively oriented in order to 14

create more innovative products, so as to achieve market and technology competitiveness. More specifically, the results indicate that the interaction terms between R&D-related resources (human- and relational capital) as well as their interaction and aggressive strategic posture are positive and significant. Aggressive strategic posture exerts influences on the relationship between R&D-related resources and product innovation. For companies adopting aggressive strategic posture, the positive effect of R&D-related resources on product innovation is stronger. If a company pays attention to its resources and engages in implementing effective and aggressive strategy, it is more likely to obtain grater innovative output, especially in uncertain environment. Consequently, the findings confirmed the hypothesis that the effects of these R&D-related resources on product innovation in uncertain environment are strengthened as aggressive strategic posture increases. The strengthening effect, however, does not exist for companies operating in stable and mature environments.

Research Contributions. The presented study advances the existing literature by empirically testing a moderated model to highlight that a company’s innovation output is conditional. First of all, the study contributes to the existing literature by confirming the role of R&Drelated resources in promoting product innovation. Secondly, it extends the previous research on the emerging environmental contingency perspective on the R&D-related resources framework. As such, the findings indicate that R&D-related human- and R&D-related relational capital as well as their interaction insufficiently explain product innovation under conditions of high uncertainty. As emerges from the study, companies facing a high degree of environmental uncertainty need to be more aggressively oriented in order to gain more benefits from directing resources to product innovation in such a context. Moreover, by using the sub-group analysis based on high and low levels of environmental uncertainty, the findings indicate that while companies’ age is not significant, their size plays an important role. Such results emphasize an innovative advantage of the large-sized companies under conditions of high environmental uncertainty.

Implication for Practice. The findings of the study also contribute to the managerial practice in a few important aspects. Firstly, the presented study emphasizes the significance of R&Drelated resources and stresses that the accumulation of R&D-related human- and R&Drelated relational capital enables the full development and generation of product innovation on a level higher than the competitors’ (Subramaniam & Youndt, 2005). Secondly, it was found that under the conditions of high environmental uncertainty, possessing a greater 15

number of R&D employees enables to discover and recognize the latent market and technological opportunities. Under such conditions, companies need to create valuable product innovation through the development of R&D-related human capital in the pursuit of a temporary competitive advantage. Finally, the positive influence of aggressive strategic posture on the relationship between R&D-related resources and product innovation also calls managers’ attentions to examine their ability to cope with changing environment. As emerges from the study the positive effect of R&D-related resources on product innovation is stronger for companies adopting aggressive strategic posture. Thus, the study implies that developing R&D-related resources as well as implementing aggressive strategy provide greater innovative output especially in uncertain environments.

Limitations of the Study and Directions for Future Research. This first effort towards revealing the role of both internal (aggressive strategic posture) and external (environmental uncertainty) contingent factors on the relationship between the two key R&D-related resources as well as their interaction and product innovation is constrained by several inherent limitations, which also represent a broader perspective for further research in this area. First of all, although the findings indicate that R&D-related human- and R&D-related relational capital impact product innovation, other potential kinds of resources that may also promote product innovation are not systematically examined in the study. Thus, another types of R&D-related resources might be included in further analysis. Moreover, the findings call for further research on other potentially moderating effects of additional contingency factors that affect the relationship between R&D-related resources and product innovation (e.g. organizational culture, structure and proactiveness). Another limitation of the study derives from the cross-sectional design, which means that causality cannot be established. Undoubtedly, R&D-related resources need to be created, extended, and modified (Hung, 2010) in order to be a key source of a company’s competitive advantage via developing new products. It seems to be a dynamic process. Therefore, the cross-sectional data set used in the study does not allow for investigating the changing relationship between analyzed variables. Thus, longitudinal data can be used in future research. Fourthly, since the role of environmental uncertainty was examined in the study, future research focusing on other types of environmental characteristics such as environmental munificence and environmental hostility is needed. Such analysis may offer further understanding of the influence of different external environmental elements on a company’s innovative efforts. Fifthly, the sample of companies ranged from different sectors, but in some cases the sample size was too small 16

(e.g. less than ten in medical technology). Therefore, it was difficult to capture the sectorspecific effects in the presented study. The last limitation also concerns the sample. Although the results undoubtedly contributed to the understanding of the role of R&D-related resources in promoting product innovation under the presence of both internal (aggressive strategic posture) and external (environmental uncertainty) contingencies, the sample was composed only of Polish companies. Therefore, as with most research, generalization beyond the sample frame is highly cautioned. Hence, future research should focus on comparative studies in different countries or market institutions, especially in other emerging economies. More research in this area could overcome the limitations of the presented study.

CONCLUSIONS

The study was focused on linkages between R&D-related resources (R&D-related humanand R&D-related relational capital) and product innovation under the different contextual conditions. By using the sub-group analysis based on high and low levels of environmental uncertainty the study empirically verifies the relationships between these vital kinds of resources as well as their interaction and product innovation through the environmental evaluations. Moreover, the findings of the study highlight the moderating effect of aggressive strategic posture, especially in the context of environments, in which future evolutions in markets or technologies are hardly to predict. Therefore, the study seems to be important for both organizational scholars and practitioners, because it shows that the innovation effects of R&D-related resources in uncertain environment are stronger when aggressive strategic posture is high. Further research on how environmental uncertainty affects the relationship between resources and innovation is needed, not only for a theory development but also to increase scholars’ attention in order to better understand the underlying mechanisms, through which R&D-related resources encourage product innovation.

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Table 1. Descriptive Statistics Mean 12.53 0.52 3.26 2.18 3.82 0.22 4.79 4.26

1. Product Innovation 2. Sector (dummy) 3. CEO age* 4. CEO tenure** 5. Company’s Size*** 6. R&D-related Human Capital 7. R&D-related Relational Capital 8. Aggressive Strategic Posture * Log age ** Log years of tenure *** Log number of full time employees

Std. 8.66 0.50 0.77 0.59 0.85 0.49 1.57 1.28

Table 2. Inter-correlations between Variables 1. 2. 3. 4. 5. 6. 7. 8.

Product Innovation Sector (dummy) CEO age CEO tenure Company’s Size R&D Human Capital R&D Relational Capital Aggressive Strategic Posture

1.

2.

3.

4.

5.

6.

7.

-0.04 0.01 -0.10 0.11 0.74 0.63 0.41

0.06 -0.09 -0.11 0.15 -0.07 0.08

0.31 0.07 -0.06 0.04 0.12

0.07 0.03 0.08 0.17

-0.06 0.07 0.02

0.51 0.46

0.18

All correlations above 0.19 are significant at the 0.05 level.

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Table 3. Results of the Hierarchical Regression Analysis. The Comparison of Standardized Regression Coefficient for Product Innovation with High and Low Levels of Environmental Uncertainty

Product Innovation Model 1 Control Variables Sector (dummy) CEO age CEO tenure Company’s Size

Model 2

Model 4

Model 5

Model 6

Low Environmental Uncertainty (n=145)

-0.033 0.012 0.017 0.013

0.016 0.006 -0.012 0.007

Independent Variables R&D-related Human Capital R&D-related Relational Capital

*

-0.018 0.013 0.021 0.043

Interaction Effects R&D Human Capital* R&D Relational Capital R&D Human Capital* Aggressive Strategic Posture R&D Relational Capital* Aggressive Strategic Posture R&D Human Capital* R&D Relational Capital* Aggressive Strategic Posture

6.563

0.022 0.011 -0.013 0.029

*

*

0.201

*

0.173

*

0.152

*

0.017

0.112

**

0.101

**

0.501

*

0.011

0.651

**

0.561

**

0.231

*

0.093

0.097

*

-0.052

1.142

**

0.154

0.665 0.128 9.621

** **

1.063

0.216

-0.012 0.019 0.016 0.012

-0.026 0.007 0.019 0.031

Moderating Variable Aggressive Strategic Posture

R2 ∆R2 F

Model 3

High Environmental Uncertainty (n=74)

0.537 0.321 8.806

**

** **

0.067

0.208

0.112 6.001

0.411 0.299 7.012

*

* *

0.056

0.268 0.143 6.001

* p < 0.1 ** p < 0.05 *** p < 0.001

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