EXPLORING “TECHNOLOGY-BASED” FIRMS: RISK-SEEKING BEHAVIOR AND FIRM CONTEXT

AS ANTECEDENTS OF A FIRM’S TECHNOLOGICAL LEVEL

Erno T. Tornikoski, Grenoble Ecole de Management (France) Heikki Rannikko, Aalto University (Finland) Tomi Heimonen, Aalto University (Finland)

Abstract: In this empirical study, our objective is to explore the factors that contribute to the technological level of young firms to understand better the origins of technology-based competitive advantages. To our understanding little is known about what makes some firms to emphasize technologies while other firms compete with less emphasis on these. We claim that a firm’s technological level is partly the result of entrepreneurs and their choices (managerial choice perspective). In certain contexts, however, firms do not have any other choice than to invest in their technology base (environmental pressure perspective). Finally, besides these direct effects, we further claim that these two perspectives interact, and, therefore, provide an original explanation and understanding of the technological level of young firms. Our empirical observations among young Finnish firms give support to our main hypotheses.

Key-words: Young firms; Technology-level; Competitive advantage; Risk-seeking attitudes; Environmental pressure; Finnish startups; Growth potential

INTRODUCTION A firm’s competitive advantage derives from scarce, valuable, and durable resources, competencies and capabilities (Wernefelt, 1984; Bamey, 1991). Indeed, according to the resource-based approach, firms should develop and posses distinctive resources –physical, human, organizational–to achieve competitive advantage over other actors. To this end, technology –the sum of a firm’s knowledge and skills (Zahra & Bogner, 1999) – provides one mean for firms to build idiosyncratic resources. As a part of a firm’s physical capital (Barney, 1991), a firm’s technology becomes an essential ingredient in its overall competitive strategy if it has a role in determining relative cost position or differentiation, or changing the other drivers of cost or uniqueness (Porter, 2007). In essence, technology “determines the ability of new ventures to offer the products (services), gain market acceptance, survive, and achieve financial success” (Zahra & Bogner, 1999: 136). While the previous insights on the role of technology for the prosperity of firms are not new, to our understanding, however, surprisingly little is known about what makes some firms to emphasize technology as a source of competitive advantage while other firms choose to leverage other means (such as human and organizational capital resources, or relational capital) to pursue similar ends. In addition, while the concept “technology-based” firm is part of our standard vocabulary, there seems to be a tendency to take the level of technology in a firm as a given. At least, the technological level of a firm generally appears as an independent variable (or as a control variable) in our inquiries about new and young firms and their diverse performance outcomes, rather than the object for theorizing efforts. In this study, we take a new look into the concept of technology-based firm. Our objective is to explore the factors that contribute to the technological level of young firms to understand better the origins of technology-based competitive advantages.

In our theorizing efforts, we look into two different theoretical perspectives. First, according to the managerial choice perspective, entrepreneurs have a distinctive impact on the orientations and operations of their firms. Entrepreneurs are expected to make things happen, to take risks. Leaning on this perspective, we claim that a firm’s technological level is partly the result of entrepreneurs and their choices. Second, we integrate environmental perspective to this picture, according to which firms do not have any other choice, in certain contexts, but to invest in their technology base. Finally, besides these direct effects, we end our theorizing efforts by demonstrating how these two perspectives interact, and, therefore, provide an original explanation for the technological level of young firms. Our paper is structured as follows. In the next section we develop the theoretical arguments about the mechanism, which explains the technological level of a firm. Thereafter we detail our methodological choices, the sampling procedure, and our measures. The third section will present the result. Finally, we discuss our observations in the light of existing literature, highlight the contribution of this study, and discuss the implications and draw the main conclusions.

LITERATURE REVIEW

According to the resource-based approach, firms gain competitive advantages by possessing scarce, valuable, and durable resources, competencies and capabilities (Wernefelt, 1984; Barney, 1991). For young firms, one of the central means to competitive advantage is represented by technology. The methods by which organizations utilize technology is regarded the technology basis of competitive advantage (Schumann, et al., 1994). When a firm competes through technological means, it translates, for example, into investments in R&D activities and promotion of novel products. Inspired by these premises, we put forward three different hypotheses to explain the level of technology in a firm. Managerial perspective and technological level of a firm We start our theorizing efforts by arguing that the technological level of a firm depends largely upon entrepreneurs and their choices. We base this overall argument on the managerial choice perspective (e.g. Andrews, 1971; Child, 1972). More specifically, we focus on the risk-seeking attitudes of entrepreneurs. Indeed, entrepreneurs have been associated with risk-taking in uncertain environments (Cantillon, 1931; Knight, 1921). In management literature, risk taking is treated generally as essential to innovation and success (March & Shapira, 1987). In our approach, we go a bit further and claim that those entrepreneurs, who exhibit higher level of risk-seeking attitudes, develop their firm’s technological base as the key competitive advantage of their firm. To see this association it is first reminded that entrepreneurship may be conceptualized as the creation of new products or processes, entry into new markets or as the creation of new ventures. Common for all conceptualizations is uncertainty and risk involved with the action (McMullen & Shepherd, 2006). While entering new markets with old products involves less uncertainty (market risk only), developing new products for new markets involves more uncertainty (technology risk in addition to market risk). For explaining how uncertainty discriminates those who decide to act entrepreneurially from those who do not, there are two streams of thought (McMullen & Shepherd, 2006). The first focuses on the amount of uncertainty perceived due to differences in knowledge. The other, directly related to this paper, focuses on the willingness to bear uncertainty due to differences in risk-propensity (risk-seeking attitudes) (McMullen & Shepherd, 2006). High risk-seeking attitude contributes to willingness to bear uncertainty in the process of making judgments about business opportunities. Therefore, from two entrepreneurs that perceive uncertainty

similarly one with higher risk acceptance is more likely to engage in entrepreneurial act such as developing technology in order to take advantage of emergent technological opportunity. More specifically, uncertainty in the context of action contributes to the sense of doubt that blocks or delays action differently because it is subjective (Lipshitz & Strauss,1997). There is variance in how it blocks action because of individual differences in e.g. attitudes towards risk (Khilstrom & Laffont, 1979). In specific doubt prevents action by undermining prospective actor’s beliefs regarding (1) whether an environmental stimulus presents an opportunity for someone in the market place, (2) whether this opportunity could feasibly be enacted by the actor and (3) whether successful exploitation of the opportunity would adequately fulfill some personal desire (McMullen & Shepherd, 2006). Thus, entrepreneurs, who have higher risk-seeking attitudes, are able to make the necessary investments in technologies even though the returns are uncertain, not immediate, and often negative (e.g. March, 1991). And vice versa: entrepreneurs, who exhibit low level of risk-seeking attitudes, will prefer to keep the technological level of their firm low or modest. They prefer to compete with less novel products and low or moderate level of technological investments, i.e. refinement and extension of existing technologies where the return are positive, proximate, and predictable (March, 1991). These arguments lead to the following hypothesis:

Hypothesis 1: Risk-seeking attitude of entrepreneurs contributes positively to the Technological Level of a firm.

Environmental perspective and the technological level of a firm We continue our theorizing efforts by pointing out that the context of a firm also dictates, or sets conditions over, whether the firm has to invest in technologies or not. Along this line of reasoning, we argue that environmental factors influence, to certain extent, the choices entrepreneurs have in regards of building competitive advantages for their young firms. To start with, it is well acknowledged that there is no best way to manage a firm, and that the possible managerial actions of a firm are dependent upon internal and external situations of the firm (Scott, 1981; Lawrence & Lorsch, 1967; Thompson, 1967). Young ventures in particular are usually more vulnerable to the external conditions than their established rivals (Zahra & Bogner, 1999). Furthermore, according to economies of agglomeration, especially in certain environments where firms are grouped together geographically may provide a firm multiple means to achieve competitive advantages, than just focusing on their internal resources such as technology. For example, relational view (Dyer & Singh, 1998) posits that firms can achieve competitive advantage through close relationships with other actors in the industry value chain. In those kind of situations entrepreneurs can choose not to develop internal resources but to rely on those of their partner firms/suppliers through outsourcing and therefore divide technological risks. Economies of agglomeration also provide firms improved access to labor, other specialized human resources, knowledge stocks and spillovers (Acs, et al., 1994; Saxenian, 1994), all which can be used as a bases for competition. The situation of firms is different, on the contrary, in rural areas (areas of non-agglomeration/non-favorable context). Rural areas are by definitions characterized by the lack of opportunities related to access to labor or other specialized human resources, proximity with other actors, and the like. Therefore, locational agglomeration is bound to influence the choices entrepreneurs have over means to achieve competitive advantages. As a sum, the external context and market conditions set conditions for firms and their organizational forms (Carroll, 1985). If a firm is located in non-favorable context (i.e. there are little extra resources in the immediate environment of the firm), the firm has to develop its internal technological competencies and distinctiveness to compensate contextual deficiencies, and to build resistance against environmental selection pressures. As such, when firms are located in non-favorable context, one central mean to

achieve competitive advantage is to invest in its own technologies. To put it bluntly, in non-favorable contexts firms have to have higher technological level than in favorable contexts. As such, we hypothesize the following:

Hypothesis 2: Context contributes to the Technological Level of a firm.

Managerial and environmental interaction and the technological level of a firm Rather than juxtaposing the two previous perspectives –in reality things always seem to end up being connected to each other in multiple ways –and echoing Hrebiniak and Joyce (1985), we propose that managerial and environmental perspectives interact to the extent that context moderates the impact of risk-seeking behavior on technological level. In contexts, which provide entrepreneurs multiple means to achieve competitive advantages, the risk-seeking attitude contributes to the technological level of the firm, as hypothesized in the first hypothesis. In highly constraints environments (e.g. non-favorable context), the managerial control over and selection of the means by which competitive advantages can be achieved still exist (e.g. Hrebiniak & Joyce, 1985), but is severely limited. In other words, the number of means to achieve competitive advantage is very limited in non-favorable contexts. We argue that in non-favorable contexts, firms need to follow “resource-based strategy” of accumulating valuable technology assets (e.g. Teese & Pisano, 1994) as their only real choice for achieving competitive advantage. As a consequence of the limited managerial choices in non-favorable contexts, the risk-seeking attitude have no, or minimal, effects on the technological level of a firm due to its nature as a necessity rather than one available mean among several others. As such, we claim that context moderates the relationship between managerial risk-seeking attitude and technology level of a firm. In non-favorable context, risk-seeking attitude of entrepreneurs does not impact the technology level of firms. This is because it is a necessity for firms to invest in technologies to compensate contextual deficiencies in the first place. Risk-seeking attitude, on the contrary, impacts technological level of firms in favorable contexts. That is, firms will not have high technological level in favorable contexts if risk-seeking attitude of entrepreneurs is low. As such, we hypothesize the following:

Hypothesis 3: The direct effects of Risk-seeking attitude on the Technology Level of a firm are moderated by the Context.

METHODOLOGY Sample In our empirical study, we draw on a unique longitudinal dataset of over 2000 technology-based young firms in Finland. Our research data-base is retrieved through the customer database of the Finnish Funding Agency for Technology and Innovation (Tekes) and it represents a sub-group of the population of innovative new manufacturing and knowledge-intensive service firms in Finland. Construction of our research database started by receiving a list of firm names and identification codes from Tekes on 545 firms that ended their Tekes-supported research and development projects in 2002; 1061 firms that ended their Tekes-supported research and development projects in 2004; and 1180 firms that ended their Tekes-supported research and development projects in 2007. Additionally, firms that apply for the Young Innovative Firms programme (NIY firms) are added continuously into the database. By the time this research was completed, the number of NIY firms was over 300. After the firm

identification information was received financial information (sales and number of employees) on firms was collected mainly through the Voitto+ -register, which is a privately held source of financial information that is maintained by Asiakastieto Oy. Occasionally, missing values were found from the National Patent and Registry Office or from the firms themselves by emailing or by telephone. The second step in data collection has been to conduct surveys in such a way that all groups (2002 firms, 2004 firms, 2007 firms and NIY firms) first received the base survey and then follow-up surveys each year. All surveys were conducted on-line through the Webropol Internet-based research tool. Base surveys and follow-up surveys differ from each other. New questions were added to later surveys and not all questions have been used in all surveys. There are 182 items across the questions, with each item used at least once by the time of this research. Questions can be broadly classified into the following areas: (1) the firm and its products and services; (2) the firm’s resources, organisation and competences; (3) strategic goals and growth strategies; (4) internationalisation, (5) product features and operating environment; and (6) Tekes services. For the purposes of this study our sample was narrowed down to 37 firms in which the independent variables of our interest were measured before the dependent variable. These firms were founded between 1991 and 2010, and they operate in various industries largest representation being from software business. The data was collected through questionnaires in 2007, 2008, 2009, 2010 and the last round 2012. Variables Our dependent variable, Technological level, is made of four items. It captures the extent to which a firm’s products are based on high technology, the firm invests in R&D, the products are unique in the markets, and the firm aims to grow through new customers. The variable has good reliability (Cronbach’s alpha of 0.76). The independent variable of Context is operationalized through a firm’s location. Large cities represent favorable context in which resources are closely available whereas rural areas and small cities represent somewhat unfavorable contexts that do not have the same benefits as big cities. If a firm is located in one of the five largest cities in Finland, value one is attributed and zero otherwise. The second independent variable, Risk-seeking attitude is measured using three items: Entrepreneur’s preferences towards risk-taking; Need for bold actions; and Pro-activeness. The variable has good reliability (Cronbach’s alpha of 0.85). In order to control for effects that might otherwise influence the technological level of young firms, we control for firm size, firm age, firm industry, and number of lags in the measure of risk-seeking behavior. Firm size is measured as the average number of employees in firms from years they have been in operation and natural logarithm is taken from that. Because opportunities for firms to build businesses around novel technologies is likely to differ across industries (Eckhardt & Shane, 2011), industry is controlled by a dummy variable of whether a firm operates in an information technology industry (value 1) or other industries (value 0). Number of lags in the measure of risk-seeking behavior relates to the distance between the years when risk-seeking behavior and technological level were measured (one to five years). Method As statistical analysis, we use regression analysis. Our methodological design allows us to measure the independent variables before the outcome variable. This temporal separation between the measurement of

the independent and outcome variables allows us to make inferences about the potential causal relationships between them. Common Method Variance To evaluate the possibility of common method bias the Harman’s single-factor test has been suggested. In this test both the measures for independent variables and dependent variables are loaded into an exploratory factor analysis and unrotated factor solution is used to determine the number of factors that are necessary to account for the variance in the variables (Podsakoff, et al., 2003). Harman’s test assumes that if a significant amount of common method variance is present one factor will come out of the factor analysis (or one factor accounts for the majority of the variance among measures). Loading four items of the dependent variable ‘technological level’ and three items of the independent variable ‘risk seeking behaviour’ into a factor analysis results in two factors with eigenvalue over one. The result that two factors emerge suggests that common method variance should not be a major problem. One should bear in mind, though, that this procedure does nothing to statistically control for the common method effect; it is merely a diagnostic technique (Podsakoff, et al. 2003: 889). As a result, the presence of common method bias cannot be fully discounted.

RESULTS

The Table 1 presents the results of the regression analysis: Model 1 presents the control model, Model 2 adds the independent variables, and Model 3 adds the interaction term. The increase in the explained variance between the models (from 10% to 38%) is statistically significant indicating that our model seems to be well specified. ----Place the Table 1 about here ---- Regarding the control variables, Firm size is statistically significantly (p < .01) associated with Technological level across the three models. Our three hypotheses receive support from our empirical observations. First, Risk-seeking attitude has statistically significant (p < 0.01) positive impact on Technological level (see Model 2). This observation suggests that the more an entrepreneur manifests risk-seeking behavior, the higher will the technology level of the firm become. As such, Hypothesis 1 is confirmed. Second, Context has statistically significant (p < .05) negative impact on Technological level (see Model 2). This observation suggests that locating outside big cities leads to higher technological level. As such, Hypothesis 2 is confirmed. Third, the interaction term Context x Risk-seeking attitude has statistically significant (p < .05) positive impact on Technological level (see Model 3). In order to confirm this interaction, we plotted the interaction effects. As can be seen from the Figure 1, Context moderates the relationship between Risk-seeking attitude and Technological level. This observation suggests that the impact of risk-seeking behavior on technological level depends on the context, i.e. locating in big cities leads to stronger association between risk acceptance and technological level than outside big cities. As such, Hypothesis 3 is confirmed.

Figure 1: Interaction effects of Context * Risk-seeking attitude.

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1 2 3 4 5 6 7Risk acceptance

Rural area (context dummy=0) Large city (context dummy=1)

DISCUSSION In this study we have made an attempt to understand what determines the technological level of a young firm. Our theorizing efforts lead us to propose a model where managerial choice and environmental perspectives together explain the level of technology is a young firm. We found empirical support for these ideas. The main result of our study is that the impact of entrepreneurs’ risk-seeking attitude on the technological level of their firms is much stronger in big cities than outside big cities. This observation is similar to our existing understanding of the moderating role of environment between risk attitudes and implementation of diverse strategies (Covin & Slevin, 1998; Covin, et al., 1999). Implications to theory and practice We believe that our empirical observations can inform both theory and practice in important ways. From a theoretical perspective, the results of our study contribute to the scant literature about the determinants of technological-base of firms. While we acknowledge the benefits of technology to the competitive posture of firms, we still have little understanding how firms choose to compete with technology. Our study offers one potential explanation for such behavior. Our empirical observations give support to open system view of organization theory: possible managerial actions concerning the development of a firm depend both on internal (decision making and level of firm technology) and external context of the firm (Scott, 1981; Lawrence & Lorsch, 1967; Thompson, 1967). From a practical perspective, our observation that young firms operating outside big cities must to have higher technological level, to start with, than their counterparts in big cities ought to be of great interest to young firms seeking for competitive advantage. This requirement to have a higher technological level outside big cities, regardless of the level of risk-seeking attitude, may be born out from the necessity for

firms outside big cities to compensate the relatively poor context in which these firms choose to operate. Young firms located in big cities, on the contrary, have multiple choices: they can either put emphasis on technologies or seek competitive advantages through other means, such as closeness to customers or internationalization channels. Our study demonstrates that in big cities where firms have the choice among multiple means, it is the risk-seeking attitude of entrepreneurs that leads to higher technological level. Limitations and conclusions While we believe that our study may contribute to what is known about the factors affecting the technological level of young firms, we identify the following limitations of our study and offer advice for scholars interested in this line of inquiry to improve upon it in future studies. Regarding our operationalization of a favorable context, which was measured as a firm being located in one of the five largest cities in Finland, the operationalization is rather rudimentary, rather than a precise measure of favorable or non-favorable context for entrepreneurial activities. We used this measure because it is relatively objective compared to an entrepreneur’s perception of the environmental munificence. We encourage future studies to verify our observations using more fine-tuned measured to operationalize favorable and non-favorable contexts. Regarding our sampling strategy, we have purposefully used the database of TEKES. While the TEKES database does not represent all the potential innovative startups and young firms in Finland, it is nevertheless the best source of such firms in Finland. Future studies are encouraged to use complementary sampling strategies to confirm our observations, and to generalize them beyond the Finnish startups and young firms. As Markman and his colleagues (2001) emphasized, firm performance is not so much based on technological breakthroughs or getting technology to market, but on succeeding in the competitive market place. Our study did not, however, shed light on any performance implications of having higher technological level. For example, do young firms performance better because of higher technological level? Do young firms perform better when the technological level is high as a result of necessity or managerial choice? We encourage further scholarly work to focus on these kinds of questions. Notwithstanding the previous limitations, we believe that our findings can inform the collective understanding of the factors affecting the technological level of young firms. At the very least, we hope to have added richness to the ongoing discussion regarding the importance of technology as a source of competitive advantage in the context of young growth potential firms.

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APPENDIX Table 1: Regression table.

Model 1 Model 2 Model 3

Coeff. Std. Error

Coeff. Std. Error

Coeff. Std. Error

Number of lags in risk acceptance .060 .065 .073 .056 .074 .054

Firm age (years) .010 .020 .002 .018 .003 .017

Firm industry (software = 1) .610+ .317 .541+ .279 .624* .268

Firms size (number of employees) .188+ .099 .263** .089 .279** .085

Context (big city = 1) -.512* .206 -2.35* .929

Risk-seeking behavior .288** .089 .165 .104

Context * Risk-seeking behavior .340* .167

Constant -14.80 41.11 -1.31 36.13 -1.53 34.38

Adj. R-sq 0.10 0.32 0.38

Prob>F 0.1160 0.0058 0.0025 Number of observations 37 37 37 ***p=0,001 ** p=0,01, * p=0,05 (two-tailed testing)