HOW INTERNAL AND EXTERNAL CIRCUMSTANCES INFLUENCE
THE EFFECTIVENSS OF UNCERTAINTY MANAGEMENT
STRATEGIES ON NEW TECHNOLOGY VENTURES PERFORMANCE.
by Arianne Plugboer1 University of Groningen Faculty of Economics and Business
Nettelbosje 2 9747 AE Groningen
06 304 961 74 a.g.plugboer@student.rug.nl
Date; August 2012
Master of Science, Business Administration Specialization Business Development
1st supervisor: Dr. J. D. (Hans) van der Bij 2nd supervisor: Dr. C. (Cees) Reezigt
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PREFACE
It is my pleasure to present to you my master thesis. This master thesis is the final product of the MSc program Business Administration, specialization Business Development, at the University of Groningen. It has been produced in the period between March 2012 and August 2012.
I was fortunate to have the opportunity to do research and consequently write my thesis at the University of Groningen. Since at the University of Groningen the Faculty of Economics and Business is one of the best business schools worldwide, confirmed by the recently obtained business accreditation from AACSB International, I could think of no better place to study than here.
With this thesis as a result, I hope to verify my expanded academic research skills. Furthermore, I hope to show that I’m able to formalize and test hypotheses in a sound methodological approach, and interpret the successive results by logical reasoning and with some resourcefulness. Regarding the process of this project, I did not only learn more about performing academic research and practicing academic writing, I also learned about the field of management strategies, business development and new technology ventures.
I would like to show my sincere thanks to Dr. J. D. (Hans) van der Bij, my first supervisor from the University of Groningen, for without his guidance this thesis would have never come to stand. He guided me throughout the entire process and with his, critique and support he raised the bar for achievement. In addition, I would like to thank Dr. Song, Mrs. Podoynitsyna and Dr. van der Bij for sharing their database with me. I also would like to thank Dr. C. (Cees) Reezigt, my second supervisor, for his supervision and comments.
Finally, I want to thank all my close friends and family for their support throughout the whole trajectory, especially Boris van Oostveen for sharing his academic knowledge and helping me with the academic writing.
ABSTRACT
This study examines how NTVs deal with environmental uncertainty and how strategies mitigate these uncertainties. Based on Miller’s (1992) five uncertainty management strategies we show how internal and external circumstances affect the relationship between uncertainty management strategies and new technology ventures’ performance. By using a sample of 385 NTVs from the USA, adopted from Song, Podoynitsyna and van der Bij (2012) we examined how pro-active customer orientation and entry barriers influence the uncertainty management strategies relationship with NTVs performance. Findings show that the internal and external circumstances significantly affect the uncertainty management strategies. We find that both proactive customer orientation and entry barriers positively interact with the relationship between strategic avoidance and strategic cooperation, on the one hand, and NTV performance on the other hand. We also find entry barriers to positively interact with the relationship between strategic imitation and NTV performance as measured by market share. We also find a positive interaction between proactive customer orientation and the relationship between strategic imitation and NTV performance for the return on investment performance measure, which contrasts our hypothesis. Finally, our results show that proactive customer orientation negatively interacts with the relationship between the real option to NPD approach and NTV performance.
Keywords; uncertainty management strategies; new technology ventures; real options; pro-active customer orientation; entry barriers
CONTENT
1. INTRODUCTION ... 2
2. LITERATURE REVIEW ... 4
2.1 Environmental uncertainties and new ventures ... 4
2.2 Uncertainty management strategies and new technology ventures performance ... 5
2.3 Proactive customer orientation and NTVs ... 7
2.4 Entry barriers and NTVs ... 8
3. CONCEPTUAL MODEL... 11 4. HYPOTHESES ... 12 4.1 Strategic avoidance ... 12 4.2 Strategic imitation ... 13 4.3 Strategic cooperation ... 14 4.4 Strategic control ... 15 4.5 Real options in NPD... 16 5. METHODOLOGY ... 17
5.1 Sample and data collection ... 17
5.2 Measures ... 18
5.3 Analysis ... 19
6. RESULTS... 23
7. DISCUSSION AND LIMITATIONS ... 26
7.1 Discussion ... 26
7.2. Managerial Implications ... 28
7.3 Limitations ... 29
HOW INTERNAL AND EXTERNAL CIRCUMSTANCES INFLUENCE
THE EFFECTIVENSS OF UNCERTAINTY MANAGEMENT
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1. INTRODUCTION
This study focuses on the five main strategies of Miller (1992) to manage environmental uncertainty and to improve new technology ventures (NTV) performance: strategic avoidance, strategic imitation, strategic cooperation, strategic control, and strategic flexibility. Based on resource dependence theory (Pfeffer & Salancik, 1978), Miller (1992) develops a framework for categorizing the uncertainties faced by firms operating internationally, and outlines both financial and strategic corporate risk management responses. All five strategies have different aims and affect NTV performance in a different way. However, it is not clear that each strategy works best under similar conditions faced by different NTVs. Literature scarcely discusses these circumstances. It is unclear under which circumstances these strategies work best and are effective for NTVs.
Present literature is focused mainly on product differentiation strategy and its interactions with different environmental characteristics, such as competition intensity and environmental dynamism (Li, 2001; Li & Atuahene-Gima, 2001). Additionally, scholars examine the success factors and failures of NTVs (Song et al., 2008), or discuss the risks entrepreneurs are subject to (Shrader, Oviatt & McDougall, 2000: Antoncic, 2003; Zahra, 2005). However, few examine the consequences of uncertainty management strategies on the performance of NTVs and how internal and external circumstances affect them. Ventures are faced with different internal and external circumstances that might affect their strategies in different ways.
These days, NTVs need to survive in a fast changing and competitive environment and new products are launched in a fast range (Nieto & Santamaría, 2010). The existence of barriers to entry and exit affects the competitive behavior of incumbent firms (Karakaya & Yannopoulos, 2011). While these new products open up new opportunities for ventures, the risks associated with them should not be neglected (Ernst, 2002). Launching new products on the market in the right moment is important for NTVs’ success. High entry barriers discourage NTVs to enter a new market (Robinson & McDougall, 2001) by which it limits competition for the incumbents (Karakaya, 2002). Entry barriers possibly affect ventures’ operations and thus the degree of competition on the market is an important factor for the success of a NTV.
In addition, NTVs do not only differ in their technical orientation, but are also differ in their market orientation. Being customer orientated to create customer value is important. Prior studies found that by being proactive customer orientated, NTVs are able to create superior value for their customers (Blocker, Flint, Myers & Slater, 2011). Proactive customer orientation refers to ventures capability to continuously search for customers’ latent needs and uncover future needs (Blocker, Flint, Myers & Slater, 2011), to
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achieve high quality products that meets customer (futures) needs. NTVs employ the uncertainty management strategies but deal with different circumstances and operate in different conditions.
Since entry barriers and proactive customer orientation are important external and internal circumstances, we examine their interaction with the uncertainty management strategies. This study proposes to address this gap in the literature by studying NTVs characteristics and their effect on performance. Therefore, we will answer the research question: “What are the consequences of the uncertainty management strategies and how do internal and external circumstances affect them?”
This study makes three main contributions to the literature. First, we contribute to prior studies in the field of uncertainty management strategies (Miller, 1992; Song, Podoynitsyna & van der Bij, 2012). Second, by studying the interaction effects of entry barriers and proactive customer orientation on the uncertainty management strategies and NTV performance, we contribute to prior studies elaborating on entry barriers and proactive customer orientation functioning as moderators. Finally, our study contributes to the existing literature of entrepreneurship, new technology ventures and their functioning and performance (Li, 2001; Li & Atuahene-Gima, 2001; Song et al., 2008).
In the next section a literature review will be provided. First, the environmental uncertainty will be discussed since it forms an important driver or the limitation to survival for NTVs. Subsequently, uncertainty management strategies and NTV’s performance will be discussed. These strategies provide the pillars of this study and we will elaborate on their effect on NTV performance. After this, the proactive customer orientation and entry barriers will be discussed, for this study tries to clarify the interaction of these internal and external circumstances with uncertainty management strategies on NTV performance. In this section, hypotheses will be developed and a conceptual model is showed to visualize the hypotheses. In the third section, the data set and methodology will be discussed. This followed by the results and a discussion of the study outcomes in the fourth section. Finally, in section five we conclude with a discussion of our results, suggestions for further research and some limitations on our work.
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2. LITERATURE REVIEW
2.1 Environmental uncertainties and new ventures
“An entrepreneurial culture is one in which new ideas and creativity are expected, risk taking is encouraged, failure is tolerated, learning is promoted, product, process and administrative innovations are championed, and continuous change is viewed as a conveyor of opportunities” (Hitt et al., 2011). Risk taking is an important property of entrepreneurship (Antonicic, 2003). Risk taking appears to be influenced by threats to survival (March & Shapira, 1992) and is associated with uncertainty. According to Song, Podoynitsyna and van der Bij (2012), before products are launched on the market, NTVs distinguish themselves from other entrepreneurial firms. This because they do in-depth research and development of new products and in addition they have to deal with substantial uncertainty; the unpredictability of the venture payoffs. However, few studies discuss how, new ventures, NTVs in particular, deal with environmental uncertainties. Song et al. (2008) discuss the factors of success and failure of NTVs and a study of Li (2001) discuss the roles of strategy in the relationship between environment and performance in new ventures
Competitive effects play an important role in the strategy of ventures (Porter 1980) and more specifically in the innovation strategy and the performance of ventures (Gatignon & Xuereb, 2007). An uncertain and competitive environment presents increased performance risk for NTVs (Li & Atuahene-Gima, 2002; Li, 2001). New venture creation is a complex phenomenon, which is affected by the environment and the situation around the organization (Gartner, 1985). Additionally, the ability to operate under conditions of uncertainty may depend on an individual’s motivation and risk propensity (Hitt, et al, 2011). While two ventures may have the same characteristics and resources, environmental variation may lead only one of the two to identify and exploit a particular opportunity (Hitt et al., 2011). Whereas, institutional support and environmental turbulence enhances the effectiveness of NTVs product innovation strategies (Li & Atuahene-Gima, 2002), many new ventures might have a high propensity to fail characterized by “liability of newness”. Most new ventures have limited resources (Li, 2001). Hence, strategies must match with the organizational and environmental variables to achieve superior performance (Robinson & McDougall, 2001).
Environmental uncertainty, defined as the degree of uncertainty in terms of products, markets, and competitive behavior perceived by management of the firm, affects decision making (Li & Atuahene-Gima, 2002). Prior literature argues that managers of small firms must examine the external environment before they can select an appropriate strategy. Parnell, Lester, Long and Koseoglu (2011) mention that in order to understand the environment, firms need to scan, gather and analyze the information and trends which take place in the environment. And thus, firms must develop structures and processes appropriate
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for the imperatives of their external environment (Liang, Ndofor, Priem & Picken, 2010; Zahra & Bogner, 1999). However, since NTVs often deal with limited resources and a lack of market power, many struggle to develop basic business skills and many have not enough time and energy to focus on the management of external uncertainties (Shrader, Oviatt & McDougall, 2000). In addition, they not only face the pressures that accompany all young ventures (e.g. shortages of capital and resources), they also have to keep up with a rapid pace of technological change (Zahra & Bogner, 1999). Consequently, the choices ventures make regarding how to develop and exploit its technological resources, can strongly affect a venture’s performance and survival. To conclude, in particular NTVs need to deal with many internal and external uncertainties, whereas they often lack to do so.
Literature discusses different characteristics of a ventures environment. Song et al. (2008) mention the competition intensity, which refers to the strength of interfirm competition within the ventures’ industry, an environmental characteristic. In addition, Zahra and Bogner (1999) discuss the major characteristics of the firms’ external environment and mention the dynamism and heterogeneity of the environment. Environmental dynamism occurs when there is a high rate and unpredictability of changes in the firm’s external environment (Song et al., 2008). Those changes result from the entry or exit of competitors, changes in customers’ needs, and shifts in technological conditions. These changes create opportunities and threats for new ventures and require ventures to act by building and leveraging technological resources (Zahra & Bogner, 1999). While environmental heterogeneity refers to the perceived diversity and complexity of the firm’s external environment (Song et al., 2008). This diversity results from the industry’s natural conditions and from the choices the ventures themselves make (Zahra & Bogner, 1999). Those environmental dimensions are hard to predict and might be perceived as external uncertainties for the venture. However, the results of the meta-analysis of Song et al. (2008) show that none of these factors has a significant effect on NTV performance. And thus, aligning ventures’ strategy and internal capabilities with the external environment is important, but overall environmental uncertainties do not directly affect NTV performance.
2.2 Uncertainty management strategies and new technology ventures performance
As mentioned before, this study is based on the five strategies of Miller (1992). These strategies aim to mitigate the sensitivity of NTV performance to environmental uncertainty (Song, Podoynitsyna & van der Bij, 2012). The four common strategic responses of firms to environmental uncertainty are 1) avoidance, 2) imitation, 3) control and 4) cooperation (Song, Podoynitsyna & van der Bij, 2012). Strategic avoidance refers to decision makers within a firm believing that operating in a particular geographic area is considered to be too uncertain, and thus will not be commenced (Miller, 1992). By entering a new market, uncertainty avoidance involves slowing down the process of entering the market until (industry)
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uncertainties are decreased to an acceptable level. In addition firms may try to reduce the uncertainties by strategic imitation. This involves copying rivals’ products, technologies or strategies (Miller, 1992). According to Lieberman and Asaba (2006) imitation can occur for a variety of reasons leading to dramatically different implications. Imitation processes are most interesting in environments characterized by uncertainty or ambiguity, since environmental uncertainty raises the likelihood of undesirable out comes and in general promotes certain types of imitation. Therefore, Lieberman and Asaba (2006) argue that firms may imitate each other to avoid falling behind their rivals and probably strengthen competition. Next to imitation, ventures may aim to increase the predictability of important environmental contingencies, in order to control them, with strategic cooperation and strategic control. Strategic cooperation is also used by firms to reduce the uncertainty by long term contractual agreement with suppliers and customers (Miller, 1992). Shrader, Oviatt and McDougall (2000) argue that ventures that do not use alliances may sense risk in losing unilateral control. As a radical innovation strategy could be perceived as being too risky for independent ventures, they might decide to share this risk by taking on partnerships (Song, Podoynitsyna, van der Bij & Halman, 2008). Additionally, the use of external sources can sometimes reduce the profits earned on a given product, due to royalties or profit sharing with partners (Zahra & Bogner, 1999). Thus, cooperation has some advantages and disadvantages. In short, the main aim of the first four strategies is to increase the NTV’s control over the environment and to decrease uncertainty.
The last strategy of uncertainty management identified by Miller (1992) relates to strategic flexibility. According to Song, Podoynitsyna and van der Bij (2012) strategic flexibility is expressed by using the real options strategies, which refers to ‘real options to NPD’ (Huchzermeier & Loch, 2001). In contrast to strategic cooperation and the strategic control, flexibility responses increase internal responsiveness by keeping the predictability of external factors unchanged (Miller, 1992). These days, in this rapidly changing environment, flexibility of action will be a requirement for successful competition by NTVs experiencing accelerated internationalization (Shrader, Oviatt & McDougall, 2000). Much of the value of highly uncertain projects lies in the future. It is hard to know for an NTV when or whether the projects are going to pay off (MacMillan & McGrath, 2002). The ‘real options to NPD’ enable NTVs to invest relatively small amounts in R&D projects, until the benefits of the project are clear and uncertainty is diminished. This flexible decision structure of options is valid in an R&D context: after the initial investment, management can collect more information, based on the information, about project progress and market characteristics, they can change its course of action (Huchzermeier & Loch, 2001). If investments are staged so that expenditures end under poor conditions, losses can be contained. The cost of failure, in other words, is limited to the cost of creating the real option, less any remaining option value (McGrath, 1997).
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After outlining the five important management strategies and discussing NTVs in general and the different environmental uncertainties, this research will continue with elaborating on the internal and external circumstances of the NTVs. In order to study the internal and external circumstances, we elaborate on the strengths of the proactive customer orientation and the entry barriers NTVs are faced with. In the next section, both topics will be discussed.
2.3 Proactive customer orientation and NTVs
A competitive advantage grows out of a ventures ability to create value for its customers (Blocker, Flint, Myers & Slater, 2011; Hortinha, Lages & Lages 2011). As pointed out by Porter (1985) a “competitive advantage grows fundamentally out of the value a firm is able to create for customers.” In-depth understanding of customer needs ensures effective product innovation for a firm and thus contributes to a firm’s competitive advantage (Atuahene-Gima, Slater & Olson, 2005). Market orientation urges ventures to stay close to their customers and put them on the top of the organization chart (Zhou, Yim & Tse, 2005). Literature argues that there is a positive relation between market orientation and ventures performance (Atuahene-Gima, Slater & Olson, 2005; Zhou, Yim & Tse, 2005).
In existing literature market orientation not only refers to customer orientation, but also to the concept of competitive orientation. Gatingnon and Xuereb (2007) define three major strategic orientations of a venture, which are important determinants of the success or failure of new products. A strong competitor orientation is necessary to track and anticipate competitive activities. This because, competitors are particularly attentive to each other’s moves in high-growth markets, in which strong competitive rivalry has been observed (Gatingnon & Xuereb, 2007). Additionally, competitive effects affect the strategy of the venture (Porter, 1980).
Of all concepts of market orientation, most research is focused on customer orientation. Customer orientation is defined as the component of market orientation (Lukas & Ferrell, 2000), that is based on commitment to customer needs during the innovation project (De Luca, Verona & Vicari, 2010). It includes generating information about current and future customers and using it within the firm (De Luca, Verona & Vicari, 2010). Ventures generate and share intelligence about customer needs and take coordinated action to satisfy those needs (Blocker, Flint, Myers & Slater, 2011). Gatingnon and Xuereb (2007) define a customer-oriented firm as a firm with the ability and the will to identify, analyze, understand, and answer user needs. A customer orientation also helps a firm to learn a lot about the market's technical issues and provides an evaluation of possible segments, the importance of the market, and its growth rate. Customer orientation is considered to be of importance because acquiring information from (potential) customers about their preferences, requirements, and needs, is routinely stressed as a prerequisite for successful new product development (Piller & Walcher, 2006; Stanley, Slater & Narver,
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1994; Dowling & McGee, 1994). Despite its importance, research argues that many ventures underestimate, misunderstand, or overlook these customer expectations (Blocker, Flint, Myers & Slater, 2011).
These days’ customers expect providers not only to respond effectively to their expressed needs, but also to proactively address their latent and future needs. Existing literature based on customer orientation makes a distinction between reactive customer orientation and proactive customer orientation. Reactive customer orientation refers to the process of responding effectively to customers current and expressed needs (Blocker, Flint, Myers & Slater, 2011). While Blocker, Flint, Myers and Slater (2011) define proactive customer orientation as a provider’s capability to continuously search customers’ latent needs and uncover future needs, possibly offering ideas even before customers realize they had such a need; from the customer’s perspective, it reflects customers’ perceptions that providers have proactive processes and skills to successfully anticipate their latent and future needs. Through observation of customers’ behavior in the context of uncovered new market opportunities, information is gathered and prospects are made (Atuahene-Gima, Slater & Olson, 2005). Blocker, Flint, Myers and Slater (2011) found that a strong proactive customer orientation is beneficial to new product success and contributes to the creation of superior customer value. Furthermore, Beverland, Farrelly and Woodhatch (2004) argue that a lack of provider proactivity can undermine customer loyalty and lead to feelings of provider complacency. Additionally, quality can give customers pleasure and thus optimize ventures profitability, competitive position and market share in the long term (Haro-Domınguez, Ortega-Egea & Tamayo-Torres, 2010). In the light of this theoretical background, some research published already provides evidence that proactive customer orientation is a cross-culturally valid and strategically important capability for value creation in global markets (Blocker, Flint, Myers, & Slater 2011).
It is easier for ventures to acquire and retain customers and earn profits when the market demand is growing (Cooper, 1984). These growing markets are at the early stages of the product life cycle. However, little information is available on these markets at the same time as consumers are developing preferences (Carpenter & Nakamoto, 1989). For this reason, a strong proactive customer orientation is necessary to understand these newly created markets. To conclude, literature discusses different concepts of customer orientation and in this study we will research the effects of proactive customer orientation.
2.4 Entry barriers and NTVs
For a new venture, it might be critical to break into an established market or to create a new market, and to develop a product that highly differentiates from existing products and one that creates substantial value for the customers (Hitt et al., 2011). However, when new ventures start to serve their primary market, they struggle with incumbent barriers, which provoke researchers to examine these barriers
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(Robinson & McDougall, 2001; Parker, Don & McLoughlin 2010; Weizsacker, 1980; Karakaya, 2002; Karakaya & Kerin, 2007). According to McAfee, Mialon and Williams (2004) “an entry barrier is a cost that must be incurred by a new entrant and that incumbents do not or have not had to incur”. In addition Gilbert (1989) defines barriers to enter as a rent that is derived from incumbency.
Barriers to enter are considered an important structural characteristic of an industry and therefore could vary per industry or consumer market (Karakaya, 2002; McAfee, Mialon & Williams, 2004). In the past decade, due to the evolution of the electronic commerce many of the barriers to enter markets have decreased in some industries (Karakaya & Kerin, 2007). Porter (1980) argues that new entrants to an industry bring new capacity, the desire to gain market share and, often, substantial resources. Prior research on entry barriers and new venture performance shows that high entry barriers discourage new ventures to enter the market, although there is some disagreement of which specific barriers limits the most (Robinson & McDougall, 2001). Weizsacker (1980) argues that there are three sources of entry barriers: absolute cost advantages of incumbent firms, economies of scale, and product differentiation advantages of incumbent firms. In addition, Bain (1956) argues that barriers to enter markets are also created by the degree of firm concentration and Porter (1980) and Karakaya (2002) elaborate on the capital requirements, customer switching costs, access to distribution channels, and government policy as barriers to enter the market. Subsequently, research of Karakaya and Kerin (2007) found that the capital requirement to enter a market and the amount of sunk costs involved in entering a market have the highest ratings in terms of importance for deterring market entry. Karakaya and Stahl (1989) argue that cost advantage, customer switching costs, and government policy are considered to be more important in industrial good markets than markets of consumer goods. In the later market, switching from one product or brand to another is associated with implicit and explicit costs, in a financial (e.g. sunk costs) or psychological (e.g. the perceived risk in switching to another product of brand) form. The government can limit or even foreclose entry to industries with controls like license requirements and limits on access to raw materials. In sum, although researchers disagree, some entry barriers are perceived to be more important than others.
Gotz (2002) indicates that the number of potential entrants is limited in each period of the product life cycle and increases over time. Constantly market introduction of new and improved products occurs; especially NTVs will be faced with important changes of the product’s market potential due to technological obsolescence (Tailan & Liu, 2001). Those fast changing technologies might create barriers to enter the market for NTV’s. While shorter product life cycles, means that the firms can enter markets earlier and faster than their competitors and thus more likely to be successful (Karakaya & Kerin, 2007). Entering markets fast and early means overcoming barriers to enter. However, this process requires often adequate resources and market experience as well as an innovative product that will be perceived by
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customers as a better product than the ones that already exist in the market. This process could be hard for NTV’s because they often have a lack of resources.
Entry barriers retain firms to enter a market, however there are some conditions that encourage ventures and make it attractive to enter markets (Karakaya, 2002). Baldwin (1995) stresses that expected growth and the size of the market have been found to be significant determinants of entry. While larger firms are more likely to respond to a new entry than smaller firms because they have greater human, financial, facilities and other resources than smaller firms (Karakaya & Yannopoulos 2011). Because those entry barriers require extra effort of ventures, they might use different entry strategies to handle with those barriers. Karakaya and Stahl (1989) define the three major entry strategies which firms often use. The first is the entry through internal development; this involves the creation of a new business entity in an industry. The second is entry through acquisition and the third is entry by sequence. The latter entails initial entry into one group and subsequent mobility from group to group. Although these strategies help ventures to cope with entering a market, entry barriers remain to play a significant role for new technology ventures.
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3. CONCEPTUAL MODEL
In this paper we examine the consequences of five uncertainty management strategies on NTVs performance, based on Miller (1992) and McGrath (1997; 1999), under different internal and external circumstances. Figure 1 shows the conceptual model of the hypotheses that we will discuss in the next section.
FIGURE 1 CONCEPTUAL MODEL
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4. HYPOTHESES
4.1 Strategic avoidance
Strategic avoidance occurs when new ventures consider to operate in a given product or geographic market, but which is consequently perceived to be too risky (Miller, 1992; Song, Podoynitsyna & van der Bij, 2012). New ventures may try to avoid uncertainty by only entering low uncertainty markets or through a niche strategy (Miller, 1992). When a market is yet unknown and perceived to be too risky, it may include postponement of market entry until the industry uncertainties decrease to acceptable levels (Miller, 1992). This implies that the first product introduction will only be for small, predictable market niches or growth from a small scale when entering a new market (Shane, 2003; Song, Podoynitsyna & van der Bij, 2012). Consequently, the market in which the venture operates becomes smaller and thus may constrain the number of new products sold. Therefore, strategic avoidance has a negative effect on NTV performance (Song, Podoynitsyna & van der Bij, 2012). Proactive customer orientated ventures have more information about customers needs and thus know more about their customer’s future preference. Because of this information, a larger predictable market arises in which the venture can operate and thus more customers can be reached. While strategic avoidance leads to a smaller operating market, knowing customers future needs, leads to a larger operating market. And thus, strategic avoidance will have less of a negative impact on NTVs performance when ventures are high proactive customer orientated. Therefore, we expect that being proactive customer oriented will be positively interacting with strategic avoidance. We hypothesize;
H1a: There is a positive interaction between strategic avoidance and pro-active customer orientation on NTV performance.
High entry barriers discourage other ventures to enter the market (Karakaya & Kerin, 2007). When the incumbent ventures have specific advantages, or product differentiation advantages, the potential for the new entrants may not be attractive unless the new entrants are willing to take a risk or are able to exceed those advantages (Karakaya, 2002). In this case, rivals might decide to postpone product launch because of the high entry barriers. This leads to benefits for the incumbent ventures, because they are faced with less competition. Consequently, an increase in potential market share for incumbent ventures and a larger operating area arises for the venture. Since strategic avoidance is negatively related to NTV performance, which depends on the size of the operating market area, a larger operating area leads to a stronger negative effect of strategic avoidance on NTV performance. Therefore, we expect that employing the
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avoidance strategy will have a stronger negative impact on NTV performance in a market with high entry barriers. For this reason, we hypothesize;
H1b: There is a positive interaction between strategic avoidance and entry barriers on NTV performance.
4.2 Strategic imitation
Strategic imitation occurs when ventures experience uncertainty and might try to manage this by coping other firm’s products or process technologies (Miller, 1992). Ventures might follow other firms by moving into new markets. Strategic imitation reduces the control of competitors over the venture’s customer groups (Pfeffer & Salancik, 1978: Song, Podoynitsyna & van der Bij, 2012). When ventures imitate the strategic behavior of others, they occupy in the same strategic niche (Lieberman & Asaba, 2006). Imitation processes are mostly occurring in environments characterized by uncertainty or ambiguity (Lieberman & Asaba, 2006). Imitation results in a decrease in R&D costs and often leads to market share which needs to be shared by the competitor imitated. By imitating others’ products or a part of it, ventures perceive a larger predictability of the market. This because, they know that what they have imitated was already a success on the market. When ventures are proactive customer orientated, they know customer future needs and thus perceive a market as more predictable. In this case, strategic imitation is less effective for NTVs performance, because the market is already perceived as more predictable. Therefore, the higher the proactive customer orientation, the less important strategic imitation will be for NTV performance. For this reason, we expect a negative interaction of proactive customer orientation on strategic imitation. We hypothesize:
H2a: There is a negative interaction between strategic imitation and pro-active customer orientation on NTV performance.
Ventures imitate others by trying to manage the uncertainty, to increase their performance. As argued by Karakaya (2002) entry barriers retain other firms to enter a market and thus potential rivals might postpone entering the market. High entry barriers limit competition by preventing market entry of new ventures and often increase the profit of incumbent firms in the marketplace, because incumbents could set higher margins and do have higher market share (Karakaya & Kevrin, 2007). So, when the entry barriers are high, competition is limited and thus a larger potential market arises for incumbent ventures and thus more customers can be reached. However, by imitation the market has to be shared for both, the copier and copied venture, but still the potential market share increases. It simply is more easy to share a
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market which is less competitive and thus in those markets the benefits of strategic imitation will be larger (more potent). And thus, strategic imitation will have a stronger influence on NTV performance in a market with high entry barriers. We therefore expect that the higher the entry barriers in the market, the more important strategic imitation is for successful NTVs performance. For this reason, we hypothesize;
H2b: There is a positive interaction between strategic imitation and entry barriers on NTV performance.
4.3 Strategic cooperation
Strategic cooperation occurs when ventures decide to cooperate with other ventures (Li & Atuahene-Gima, 2001; Miller, 1992). Ventures often do this by long-term contractual agreements with suppliers or buyers. Voluntary restraint of competition, alliances or joint ventures, franchising agreements, technology licensing agreements and participation in consortia and personnel flows can facilitate interfirm coordination (Miller, 1992). By strategic cooperation ventures could save costs by sharing risks and using each other’s expertise (Un, Cuervo-Cazurra & Asakawa, 2010). By following a cooperation strategy, ventures may find improvements in a product’s quality, availability, or promotion; this could result in a higher quality product (Song, Podoynitsyna & van der Bij, 2012). Ventures can benefit from this, by setting higher prices and generating more customer value. By being proactive customer orientated and thus customer focused, ventures have more information about customer preference and can predict the future market better. By having this information, ventures can collect and specifically choose their partners which are connected with their customers. And thus, ventures can align their cooperation strategy with the gained information about the predictability of the market. Consequently, proactive customer orientation strengthens the positive relationship between strategic cooperation and NTV performance. We therefore expect that, employing the cooperation strategy will have a more positive impact on NTV performance when ventures are highly proactive customer orientated. We hypothesize;
H3a: There is a positive interaction between strategic cooperation and pro-active customer orientation on NTV performance.
Collaboration enables NTVs to share and use expertise and resources of others to create successful innovations (Un, Cuervo-Cazurra & Asakawa, 2010). Additionally, ventures could speed up the product life cycle process, by outsourcing a part of the product development process (Un, Cuervo-Cazurra & Asakawa, 2010) which result in a faster product launch. High entry barriers limit competition in the market, which is a big advantage for the incumbent ventures because they have a larger potential market
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share. The established sellers in the market can raise their prices and set higher margins (Mcafee, Mialon & Williams, 2004). Incumbent ventures can cooperate to make price agreements mutually. Moreover, other ventures would like to cooperate with the incumbent ventures, because they have a larger potential market share. Additionally, ventures could launch products faster through cooperation with suppliers. Because of this, potential market share can be converted into actual market share. And thus, giving these arguments, we expect that the positive impact of strategic cooperation on NTV performance will be higher in case of markets with high entry barriers. Therefore, we hypothesize;
H3b: There is a positive interaction between strategic cooperation and entry barriers on NTV performance.
4.4 Strategic control
When ventures perform strategic control they may seek to control important environmental contingencies to reduce uncertainty (Miller, 1992). Examples of this strategy are political activities, like lobbying for or against laws or regulations, or gaining market power and undertaking strategic moves that threaten competitors into more predictable behavior patterns. Another example of reducing environmental uncertainty includes influencing consumers by advertising or promotion (Miller, 1992; Song, Podoynitsyna & van der Bij, 2012). Advertising or promotion will promote the product, and thereby reach more customers which could lead to an increase in NTV performance. And thus strategic control positively affects NTV performance. Proactive customer orientation leads to gathering new information by which prospects can be made by the venture (Atuahene-Gima, Slater & Olson, 2005). Because a venture knows his customers future preferences, promotion and advertisements can meet those preferences more accurately. Additionally, a venture can fit their agreements with suppliers to the prospects. And thus, the positive influence of strategic control on NTV performance will be strengthened when ventures have a high proactive customer orientation. Giving these arguments, we expect a positive interaction between proactive customer orientation and strategic control. We hypothesize;
H4a: There is a positive interaction between strategic control and pro-active customer orientation on NTV performance.
The more the NTV follows the control strategy, the more customers it will acquire for its products and thus performance will increase (Song, Podoynitsyna & van der Bij, 2012). Strategic control includes promotion of advertising to reach customers in the market. High entry barriers limit competition, and thus ventures might need to reach customers by less promotion and ads. In addition, this limited competition
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leads to a larger potential market share for the incumbent ventures. Consequently, a larger market with more customers and can be reached by those advertisement and promotion, which result in an increase in performance. And thus, the potential market share could be converted into an actual market share. For this reason, we expect that compared to markets with low entry barriers, strategic control will have a stronger effect on NTV performance when a venture operates in a market with high entry barriers. Entry barriers will positively interact with strategic control. Therefore, we hypothesize;
H4b: There is a positive interaction between strategic control and entry barriers on NTV performance.
4.5 Real options in NPD
Managers of R&D projects might be faced with many uncertainties, not only in payoffs, but also from other sources (Huchzermeier & Loch, 2001) and need to make decisions of unpredictable future actions. The core idea of a real option can be defined as a limited commitment that creates future decision rights (McGrath et al., 2004; Song, Podoynitsyna & van der Bij, 2012). Options initiated under this strategy require relatively small R&D investments until their benefits become clear. This flexible decision structure of options is valuable for R&D projects. After the first investment, more information can be gained and based on that information further decisions and actions can be completed (Huchzermeier & Loch, 2001). As time passes, uncertainty surrounding particular options resolves, facilitating the decision to invest further in the most beneficial ones and leading to higher revenue (MacMillan & McGrath, 2002). The advantages of this strategy emerge when real options can be worked out (or not) after resolving the uncertainty (McGrath, 1999; McGrath et al., 2004). By proactive customer orientation, ventures have more information of the customers and the future market by which prospects can make and thus a larger predictable market arises. The real options in NPD strategy is outperformed based on new information about the market. When a venture is highly proactive customer orientated, it perceives a more predictable market, and thus less real options are needed. Because of the predictability, the added value of the extra options are less required. Therefore, we expect that the positive impact of real options in NPD on NTV performance will be less than when a venture is high proactive customer orientated. And thus, we hypothesize:
H5a: There is a negative interaction between Real options in NPD and pro-active customer orientation on NTV performance.
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When the entry barriers are high, incumbent firms may prevent the entry of new firms by investing intensively in R&D, which increases technological scale economies and forces the ongoing industry context to evolve in a way that would make subsequent attempts to enter even more ineffective (Karakaya & Stakl, 1989). Consequently, competition will be limited and potential market share will grow for the incumbent ventures. The real options to NPD enable NTVs to invest relatively small amounts in R&D projects, until the benefits of the project are clearer. Because a larger potential market arises, more customers can be reached and thus a venture can increase his performance with focusing on the right options. We thus expect that the positive impact of real options in NPD on NTV performance will be stronger, when a venture operates in a market with high entry barriers. Therefore, we hypothesize;
H5b: There is a positive interaction between Real options in NPD and entry barriers on NTV performance.
5. METHODOLOGY
5.1 Sample and data collection
This study empirically examines the effect of uncertainty management strategies on NTV performance and the interacting effects of entry barriers and proactive customer orientation. For this, existing data from a prior study by Song, Podoynitsyna and van der Bij (2012) is used. This dataset consists of 420 NTVs drawn from the VentureOne 2001 database and the 1995–2000 Inc. 500 list. This list includes the fastest-growing private ventures in the United States, which are selected by Inc. magazine. By using the VentureOne 2001 and the Dun & Bradstreet Market Identifiers database, the name of the contact person and all other contact information is collected.
The survey is administered by using the total design method for survey research as described by Dillman (1987). For the survey, Song, Podoynitsyna and van der Bij (2012) randomly selected two thousand NTVs. The first package they mailed included a personalized letter, a project fact sheet, the survey, a priority postage-paid envelope with an individually typed return-address label and a list of research reports available to participants. The package was sent by priority mail to all 2,000 NTVs. From all packages, 569 packages were returned because of undeliverable addresses or names. Therefore, the adjusted sample consisted of 1,431 NTV’s.
To increase the response rate, Song, Podoynitsyna and van der Bij (2012) sent four follow-up mails to the ventures. One week after the first mailing, a follow-up letters was sent. After two weeks, a second package with the same original package was sent to all non-responding ventures. This resulted in
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completed questionnaires from the founders or their chief executive officer successors of 420 ventures and consequently a response rate of 29% (420/1,431).
These 420 ventures operate in different industry segments; electronic and electrical equipment (25%); pharmaceutical, drugs, and medicines (12%); industrial machinery and equipment (9%); telecommunications equipment (9%); semiconductors and computer-related products (29%); instruments and related products (6%); and others (10%). In addition from those 420 ventures (25%) is mainly operating in a business-to-business markets, 67% in a business-to-consumer market, and 8% in a business-to-government market. For the ventures in this sample the average annual R&D expenditures were about $37 million and the R&D/revenues ratio was 20% and above, with the indication that these ventures are highly R&D intensive. Respondents that had missing values of the R&D expenditures and the number of employees were excluded from the analysis (35 of 420) and 385 remained. By using the extrapolation method of Armstrong and Overton (1977) we test for possible non-response bias. We compare early responses (between the initial mailing and the mailing after three weeks) with late responses on ROI and market share. The results indicated no significant differences at a 5% significance level.
5.2 Measures
In this study, NTV performance will be regressed on the five uncertainty management variables, and the interacting variables proactive customer orientation and entry barriers using the OLS method. To measure NTV performance we will use two objective measures, the market share growth and the return of investment (ROI) of the NTVs. The market share refers to the market share of the NTV in their primary market. The firm’s ROI refers to their last fiscal year.
Similar to Song, Podoynitsyna and van der Bij (2012) we draw scales from the literature that are used to measure the variables. However, for some items no scales were available. Consequently, those items were deduced from current definitions, examples and ideas in the existing literature. Since Song, Podoynitsyna and van der Bij (2012) created new scales, they needed to pretest the survey and they interviewed 11 entrepreneurs. To get a better understanding of the entrepreneurs and the NTVs, different topics were discussed. Consequently, entrepreneurs elaborated on the background of the venture, how the venture was started and how they discovered the opportunity, and how the whole business was developed over time. Furthermore, in the last part of the interview the protocol method was used and the entrepreneurs were asked to ‘think aloud’ during filling out the questionnaire (Hunt, Sparkman & Wilcox, 1982). The interviews were recorded and notes of the verbalizations and the thinking process of the entrepreneurs were made by two researchers. Based on the analysis of these interviews, changes were made in the wording of the instructions and items.
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Dependent variables. This study uses one dependent variable, NTV performance. This variable is
measured by two objective measures. One the one hand, the ROI of the last fiscal year of the NTVs and on the other hand, the market share of the NTVs’ primary market.
Independent variables. The five main uncertainty management strategies are measured by drawn
scales used from existing literature. For strategic avoidance a three-item scale (α = 0.79) is used, which is based on the work of Miller (1992) and Shane (2003). Strategic imitation (α = 0.81) is also based on a three-item scale, but originates from Miller (1992) and Gatignon and Xuereb (1997). Strategic cooperation (α = 0.65) is measured by a three-item scale used by Li and Atuahene-Gima (2001). For strategic control (α = 0.86) a three-item scale is used similar to Miller (1992). Finally, real options in NPD is based on a three-item scale (α = 0.86) similar to McGrath, Ferrier and Mendelow (2004) and Huchzermeier and Loch (2001). By using the approach of Churchill (1979) this three-item scale measures the three basic sources of strategic flexibility, the core of the real options in NPD. To make this criterion validity check, the number of projects paused and the number of project stopped are measured.
Moderating variables. This study includes two moderators to measure the internal and external
circumstances of the venture, pro-active customer orientation and entry barriers respectively. Pro-active customer orientation (α = 0.75), is based on a three-item scale and refers to the NTV’s ability to discover and satisfy the latent and unarticulated needs of the customers (Slater & Narver, 1998; Jaworski, Kohli & Sahay, 2000; Narver, Slater & MacLachlan, 2004). To measure the entry barriers (α = 0.65) a two-item scale is used. In this, an entry barrier refers to a cost that must be incurred by NTVs entering the primary market segment, but not by incumbent NTVs (Karakaya & Stahl, 1989; Karakaya, 2002).
Control variables. To add robustness to our model we incorporate four control variables. First, the
logarithms of total number of employees is included to control for firm size. Second, a dummy variable is included to account for the firms’ clients. The variable has the value 1 when the NTV operates in the B2B segment and has the value 0 when the NTV operates in the B2C or B2G segment. Third, to control for the innovative nature of NTVs, the logarithms of the R&D expenses of the NTV is included. Finally, to control for the quality of the founding team, the size of the founding team is added to the control variables, measured as the number of the founding team members (Eisenhardt & Schoonhoven, 1990).
5.3 Analysis
The descriptive statistics and correlation matrix for the variables used in the model are shown in Table 1. Table 1 shows that of all strategies, real options in NPD is most extensively used (5.07), followed by strategic imitation (4.88), strategic cooperation (4.75), strategic control (4.42) and strategic avoidance (3.53). Regarding the management strategies, the highest correlation (0.46) is between real options in NPD and strategic imitation. This one itself does not indicate multicollinearity. With the exception of the
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dependent variables ROI and market share, the highest correlation is between proactive customer orientation and strategic control (0.49), again showing no sign of multicollinearity.
Table 1. Descriptive statistics and correlation matrix
Variables Mean St.Dev. A B C D E F G H
ROI A 75.99 77.19 Market Share B 21.27 15.25 0.52 Avoidance C 3.53 1.80 -0.07 -0.14 Imitation D 4.88 1.16 0.16 0.34 -0.20 Control E 4.42 1.35 0.26 0.48 -0.03 0.37 Cooperation F 4.75 1.18 0.35 0.37 -0.02 0.15 0.18 Real Options G 5.07 1.34 0.31 0.51 0.00 0.46 0.41 0.27
Pro-active customer orientation H 4.27 1.60 0.19 0.31 0.17 0.30 0.49 0.23 0.28
Entry barriers I 4.16 1.55 0.04 0.18 0.01 0.18 0.14 0.10 0.13 0.24
Control variable Mean St.Dev. A B C
Log (R&D expenses) A 6.64 1.04
Served market (B2B) B 1.82 0.56 0.24
Log (number employees) C 1.60 0.46 0.81 0.05
Team size D 2.56 1.09 0.11 -0.09 0.23
To determine the measurement scales for the independent variables and the moderators, a confirmatory factor analysis (CFA) is performed by using Maximum Likelihood estimation in LISREL 8.8. The CFA is performed with a sample of 420 responses. By analyzing all responses, each construct, is reviewed and the items that loaded on multiple constructs or had low item-to-construct loadings were excluded. Table 2 shows the measurement model.
The results in Table 2 show that the Cronbach’s α values for each measure range from 0.65 (strategic cooperation and proactive customer orientation) to 0.86 (strategic control and real options in NPD. Literature argues that values show a good reliability when the Cronbach’s
α is near or above the 0.70
(Nunnally, 1987; Hair, Black, Babin & Anderson, 2009). In addition the model shows a χ2 / df = 405.51 / 149 = 2.72, with a root mean square error (RMSEA) of 0.064, a goodness of fit index (GFI) of 0.91, a comparative fit index (CFI) of 0.95 and a non-normed fit index (NFI) of 0.92. Thus the model demonstrates a good fit for each subset of the variables (Hair et al., 2009). In addition, the results in Table 2 show that the loadings on the respective constructs are highly significant (p < .001), although standardized loadings of each item were greater than 0.5 in all cases except two. Because of this, we argue that our scales show convergent validity (Fornell & Larcker, 1981). Additionally, no interfactor correlations had a confidence interval containing a value of one (p < .01) and the multivariate Lagrange multiplier test illustrates that all item-level correlations between constructs were insignificant (Kim, Cavusgil & Calantone, 2006). We thus observe that our scales contain sufficient discriminant validity.-21-
Table 2. Confirmatory Factor Analysis, Items, Cronbach's α and the T-value.
Construct
Item wording Factor loadings and T-value
Item Cronbach's α
Avoidance α = 0.79
AV1 We tend to introduce our products to low uncertainty market niches first. 0.77 18.04
AV2
When a market becomes too uncertain, we tend to divest the assets
specialized for this market. 0.64 14.51
AV3 We tend to grow from the small scale in a new market. 0.70 15.07
Imitation α = 0.81
IM1 Overall, our products are similar to our main competitors' products. 0.67 15.53
IM2
For our products, we imitate certain manufacturing techniques of other
firms. 0.72 19.94
IM3 We follow other firms in moving into new markets. 0.66 15.81
Control α = 0.86
CTR1
We try to make entry of new competitors to our primary served market
problematic. 0.81 22.43
CTR2 We try to influence consumers through advertising. 0.72 14.88
CTR3 We try to use contractual agreements with suppliers for our products. 0.83 21.81
Cooperation
α = 0.65
CO1
We have cooperative agreements with other firms to manufacture our
products. 0.65 13.57
CO2 We collaborate with other firms to promote our products. 0.71 11.19
CO3 We jointly distribute our products with other firms. 0.52 7.56
Real options α = 0.86
RO1
We invest in new products in stages to allow management, based on newest information available, to decide whether or not to proceed with the
projects.
0.71 19.61
RO2
When starting developing a new product, we always make sure that we can expand the scale of this project if market conditions turn out to be more favorable than expected.
0.74 19.08
RO3
When developing new products, we try to keep our technological design
options open until we have enough information to make a choice. 0.71 19.79
Pro-active customer orientation α = 0.75 PROC1
We continuously try to discover additional needs of our customers of
which they are unaware. 0.66 17.69
PROC2
We incorporate solutions to unarticulated customer needs in our new
products and service. 0.64 17.96
PROC3
We brainstorm on how customers use our products and services to discover
new customer needs. 0.54 10.33
Entry Barriers α = 0.65
EB1 The capital requirements to enter our primary served market segment are: 0.77 6.56
EB2
Customer loyalty advantage is held by incumbents in our primary served
market. 0.72 5.53
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After an extensive CFA for determining the scale items, the hypotheses will be tested by performing an OLS regression analysis in SPSS. We regress the independent variables, the moderating variables and control variables on our measures of NTV performance. Table 4 presents the results of the hierarchical regression analyses for the ROI (column 1) and market share (column 2). Firstly, we estimate the impact of the control variables on our performance measures ROI (model 1) and market share (model 5). Secondly, we estimate the impact of the independent variables together with the control variables (model 2 and model 6). Thirdly, we add the moderating effect and the interaction effects of proactive customer orientation as showing in model 3 and model 7. Finally, we estimate the moderating effect and the interaction effects of entry barriers, presented in model 4 and model 8. In these regression models all variables were mean-centered (Kenny & Judd, 1984; Aiken & West, 1991).
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6. RESULTS
Table 3 reports the results of our regression analyses by showing the test outcomes of the ten hypotheses. We find that the full models explain about 46% of the variance in return on investment and almost 67% of the variance in market share. The results largely support the hypotheses with a few intriguing exceptions.
Hypothesis 1 predicted a positive interaction effect of strategic avoidance and proactive customer orientation on NTV performance (H1a) and a positive interaction effect in case of entry barriers (H1b). The results support H1a for both the ROI and market share performance measures, at the 5% significance level with a β of 3.033 and 0.505 respectively. H1b with a β of 3.135 is also supported at the 5% significance level for ROI.
Hypothesis 2 predicted a negative interaction effect of strategic imitation and proactive customer orientation on NTV performance (H2a) and a positive interaction effect in case of entry barriers (H2b). The results support H2b at the 10% significance level with a β of 4,347 for market share. In contrast, H2a is not supported.
Hypothesis 3 predicted a positive interaction effect of strategic cooperation and both proactive customer orientation (H3a) and entry barriers (H3b) on NTV performance. The results support H3a at the 5% significance level with a β of 0.697 and H4b at the 5% significance level with a β of 0.678 for market share. The results regarding H3a and H3b for ROI were positive though insignificant.
Hypothesis 4 predicted a positive interaction effect of strategic control and both proactive customer orientation (H4a) and entry barriers (H4b) on NTV performance. As shown in Table 3, both hypotheses are not supported. H4a and H4b show an insignificant negative β, with the exception of the insignificant positive interaction between control and entry barriers on market share.
Hypothesis 5 predicted a negative interaction effect of real options in NPD and proactive customer orientation on NTV performance (H5a) and a positive interaction effect in case of entry barriers (H5b). The results support H5a at the 5% significance level for market share, with a β of -0.576. For ROI a negative coefficient was estimated, but resulted insignificant. In addition, no support was found for H5b. The results show a negative interaction effect between real options in NPD and entry barriers on NTV performance, but it remains insignificant.
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ROI Market Share
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
Intercept 8.71 -100.14** -28.59 -85.64** -0.307 -29.46*** 1.810 -20.66***
(0.268) (-2.923) (-0.842) (-2.374) (-0.049) (-5.176) (0.324) (-3.433)
Strategic Avoidance (AV) -2.701 -3.227 -2.000 -0.986** -0.978** -0.979***
(-1.314) (-1.523) (-0.964) (-2.888) (-2.806) (-2.827)
Strategic Imitation (IM) -1.938 -2.286 -1.173 0.338 0.202 0.314
(-0.550) (-0.625) (-0.328) (0.577) (0.336) (0.527)
Strategic Cooperation (CO) 17.495*** 18.511*** 17.758*** 2.737*** 2.922*** 2.717***
(5.652) (5.864) (5.674) (5.322) (5.630) (5.204)
Strategic Control (CTR) 7.720** 6.365** 6.388** 3.263*** 2.989*** 3.113***
(2.597) (1.974) (2.125) (6.607) (5.637) (6.207)
Real Options in NPD (RO) 10.455** 10.405** 10.989** 3.395*** 3.264*** 3.510***
(3.326) (3.289) (3.410) (6.502) (6.274) (6.529)
Pro customer orientation
(PCO) 2.914 0.882
(0.858) (1.579)
AV* PCO H1a (+) 3.033** 0.505**
(2.344) (2.375)
IM* PCO H2a (-) 3.366 0.567*
(1.639) (1.678) CO*PCO H4a (+) 0.422 0.697** (0.196) (1.968) CTR* PCO H3a (+) -1.233 -0.336 (-0.638) (-1.060) RO*PCO H5a (-) -2.193 -0.576* (-1.104) (-1.763)
Entry barriers (EB) -0.515 0.679
(-0.216) (1.707) AV*EB H1b (+) 3.135** 0.205 (2.515) (0.986) IM* EB H2b (+) 4.347* 0.060 -1.929 (0.159) CO* EB H4b (+) 0.620 0.678** (0.325) (2.130) CTR* EB H3b (+) -1.854 0.030 (-1.200) (0.188) RO* EB H5b (+) -2.508 -0.177 (-1.389) (-0.586)
Log (R&D expenses) 12.947** 7.731 7.196 8.153 4.950*** 3.203*** 2.960** 3.104***
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Served market (B2B) -1.596 -0.779 -2.725 -1.898 -1.358 -1.525 -2.000* -1.403
(-0.226) (-0.120) (-0.418) (-0.293) (-0.993) (-1.419) (-1.864) (-1.297)
Log (Employees number) -21.741 -9.603 -8.727 -10.396 -8.995** -4.829** -4.476* -4.504*
(-1.422) (-0.678) (-0.607) (-0.728) (-3.041) (-2.054) (-1.892) (-1.891) Size of FT 7.406** -0.103 -2.690 -0.809 2.170** -0.098 -0.954 -0.224 (1.977) (-0.029) (-0.573) (-0.220) (2.994) (-0.162) (-1.236) (-0.364) F 1.902 10.156 6,626 6,906 5.993 31.624 20.48 19.59 R2 0.140 0.443*** 0.461*** 0.468*** 0.244*** 0.657*** 0.674*** 0.666*** Δ R2 - 0.303 0.018 0.025 - 0.413 0.017 0.009 Adj. R2 0.009 0.177 0.180 0.187 0.049 0.418 0.432 0.421 *p<0.10; **p<0.05; ***p<0.01
Parameter estimates are reported, standard errors are in the parentheses
In addition to the results regarding our hypotheses, similar to Song, Podoynitsyna and van der Bij (2012), our results appear remarkable. Although not significant, in Table 3 we do find strategic control, strategic cooperation, and real options in NPD to affect NTV performance positively. Although we expect to find a similar relationship regarding strategic avoidance and strategic imitation, we find a negative (insignificant) estimate instead. Song, Podoynitsyna and van der Bij (2012) result similar findings by using ROI and customer retention rate as NTV performance measures. In a way, our study thus contributes to their findings by finding a possible negative relationship when using market share as a performance measurement.
