Competitive Strategy - Technology research

Business orientations and innovation in small and medium sized enterprises

Elisabeth Zortea-Johnston & Jenny Darroch & Sheelagh Matear

Published online: 8 March 2011 # Springer Science+Business Media, LLC 2011

Abstract The capability of Small and Medium Enterprises (SMEs) to drive and shape markets is one path to competitive advantage. Firms that drive markets do so by leveraging radical and disruptive innovation to shape the needs of current and future customers, thereby altering market structure. In the current study, we find that firms with an entrepreneurial orientation are more likely to develop both driving markets and market driven innovations, while firms with a market orientation are more likely to develop market driven innovations.

Keywords Marketorientation . Entrepreneurialorientation . Drivingmarkets . Market driven . Innovation

Introduction

While Drucker (1954) argues that creating and keeping customers is the only valid purpose of a business—for “it is the customer who determines what a business is”, customer creation is often omitted from research agendas (Berthon et al. 2004). Instead, Drucker’s (1954, p. 37) work is generally interpreted as encouraging firms to focus more closely on their customers (Berthon et al. 2004). As Kumar et al. (2000, p. 129) note, “current practice dictates that success starts with careful market

Int Entrep Manag J (2012) 8:145–164 DOI 10.1007/s11365-011-0170-7

E. Zortea-Johnston Department of Marketing, University of Otago, PO Box 56, Dunedin, New Zealand e-mail: [email protected]

J. Darroch (*) Peter F. Drucker and Masatoshi Ito Graduate School of Management, Claremont Graduate University, 1021 North Dartmouth Avenue, Claremont, CA 91711, USA e-mail: [email protected]

S. Matear Lincoln University, PO Box 84, Lincoln, 7647 Christchurch, New Zealand e-mail: [email protected]

research, investigating the customers’ needs, and developing differentiated products or services for a well-defined segment.” In the current study, we argue that such customer focused firms are more likely to develop market driven innovations because they are strategically and tightly aligned with the market in such a way that they put their customers’ expressed needs first before creating appropriate products to meet these explicit needs (Deshpandé et al. 1993). We propose that market driven innovations are likely to be more incremental in nature (Kumar et al. 2000) because firms developing market driven innovations work within the confines of the existing market structure and behaviors (Jaworski et al. 2000).

We suggest that market driven innovations, which are characteristically customer focused, are unlikely to embrace radical ideas because (1) customers’ perceptions of their needs are restricted to items that they are both familiar with and could relate to; (2) customers’ abilities to express needs and wants are limited; and (3) the dynamic nature of customers’ expressed needs means that these needs might well change by the time new products are commercialised (Bennett and Cooper 1981). Thus, firms with a strong customer focus, and a bias toward market driven innovations, are likely to jeopardize their competitive advantage and long-term survival simply because they do not produce ground breaking innovations (Bennett and Cooper 1979; Hayes and Abernathy 1980; Christensen and Bower 1996; Kumar et al. 2000; Vázquez et al. 2001).

Increasingly, researchers are questioning whether being intimately close to the customer is appropriate for all firms operating in all contexts (see for example, Hamel and Prahalad 1991; Sheth and Sisodia 1999; Jaworski et al. 2000; Kumar et al. 2000). In the current paper, the ability to produce innovations that drive the market (that is, driving markets innovations) is presented as an alternative to market driven innovations. Driving markets innovations are defined as those innovations that create new customers, lead existing customers, meet latent needs, and reshape product/market spaces (Jaworski et al. 2000; Kumar et al. 2000; Harris and Cai 2002; Carrillat et al. 2004). Consequently, we suggest that driving markets innovations are more likely to be radical or breakthrough in nature and create new product market spaces in order to renew their competitive position and delay eventual firm decline (Rice et al. 1998; Jaworski et al. 2000; Kumar et al. 2000).

In acknowledging driving markets innovations as one path to competitive advantage, questions then include: Where do such innovations come from? What causes a firm to intentionally and proactively shape customer and competitor behavior? While scholars call for more firms to adopt behaviors and practices that lead to more driving markets innovations (Jaworski et al. 2000), a comprehensive framework to explain how firms can achieve this outcome has yet to be developed. In order to address this apparent gap and answer these questions, we call upon literature describing both an entrepreneurial orientation (EO) and a market orientation (MO). In the current study, we link an MO with market driven innovations and an EO with driving markets innovations. This is done within an SME context. This paper is organised as follows. First, we provide a theoretical justification for our research and then discuss the constructs and propose likely relationships between an EO, an MO and types of innovation. We then outline our methodology and report our results before concluding with a discussion of our findings and future areas for research.

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Theoretical background and constructs

Previous research

To date, no reported studies specifically examine the impact of both an EO and an MO on types of innovation; however, studies have explored the relationship between an EO and an MO and outcomes such as performance or general measures of innovation, such as an overall predisposition toward innovation or the success of an innovation. For example, Miles and Arnold (1991) found that an EO and an MO were correlated, although an EO and MO did not appear to represent the same underlying business philosophy. Becherer and Maurer (1997) investigated the EO-MO relationship and how an EO-MO affects performance. As with Miles and Arnold (1991), Becherer and Maurer (1997) identified a correlation between both an EO and an MO. Furthermore, they found that an EO, but not a MO, was significantly related to profitability. Conversely, Slater and Narver (2000) found a clear positive relationship between an MO and profitability but not between an EO and profitability. Bhuian et al. (2005) also focused on the MO- performance relationship, and assumed an EO to have a moderating effect on this link. Their results suggested a high level of an MO, combined with a moderate level of an EO, led to an optimum level of firm performance.

Atuahene-Gima and Ko (2001) investigated how an MO and an EO can be effectively integrated to drive new product performance and innovation. Hult et al. (2004) explored the impact of an EO, an MO, and a learning orientation on innovativeness (that is, the capacity to introduce a new process, product, or idea within an organization) which, in turn, was assumed to drive firm performance. In their study, an EO was identified as an important antecedent to innovativeness. Finally, Hult et al. (2003) investigated the role of an EO in building cultural competitiveness in organizations. Cultural competitiveness was conceptualized as the collective result of interactions among an EO, an MO, innovativeness, and organizational learning. Hult et al. (2003) found that an EO is the most influential and proactive means of developing a market-based culture, although it is contingent upon the type of organization under examination (for example, large vs. small, young vs. old firms). It, therefore, appears that there is equivocality in the scant existing research in this area.

In this study, we specifically attempt to resolve this equivocality by offering a comprehensive framework to examine the impact of both an EO and an MO on different types of innovation—in particular, market driven and driving markets innovations. We examine these relationships within a small business context because small businesses are positioned as a significant source of innovation and are also more likely to possess the level of strategic flexibility that allows responsiveness to market changes and, therefore, the ability to produce market driven innovations. Figure 1 presents the conceptual model that frames the current paper. The four constructs identified in the model and their relationships are discussed below.

An entrepreneurial orientation and its consequences

In this section, we propose that a firm with an EO is likely to produce driving markets innovations. The EO construct is widely used to represent the “entrepre- neurial activity of the firm” (Miller 1983, p. 770). Innovation, risk taking,

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proactiveness, competitive aggressiveness, and autonomy have all been acknowl- edged as components of an EO (for example, Miller 1983; Covin and Slevin 1989, 1991; Lumpkin and Dess 1996; Lyon et al. 2000). Zortea (2005) augmented Covin and Slevin’s (1989) seminal operationalisation of the EO construct by adding opportunity recognition, growth orientation and organizational learning.

We suggest that the characteristics attributed to entrepreneurial firms are antecedents of driving markets innovations. The proactive creation of products before competitors, along with the recognition of customer needs, is regarded as a fundamental activity of an entrepreneurial firm (Slater and Narver 1995). Other characteristics of EO firms include an involvement in emerging industries and the recognition and pursuit of opportunities (Miles and Snow 1978; Venkataraman 1989; Lumpkin and Dess 1996). In addition, Lumpkin and Dess (1996) note that by seizing initiatives and opportunistically shaping the environment, entrepreneurial firms influence trends and maybe even create demand. Thus, SMEs that adopt an EO create new products or services, expand into new markets, and identify new sources of growth. Furthermore, those within EO firms question current practices and policies as well as examine existing beliefs and values. This enables entrepreneurial firms to move quickly to identify product or service ideas that might provide a competitive advantage over competitors. Thus, we argue that

H1: SMEs with an entrepreneurial orientation will develop driving markets innovations.

A market orientation and its consequences

The second hypothesis argues that a market oriented firm is likely to develop market driven innovations. Kohli and Jaworski (1990) suggest that a market oriented firm generates, disseminates, and responds to information about market forces and market conditions. Narver and Slater (1990) describe a market oriented firm as one that

Fig. 1 Proposed model describing the relationships between an EO, a MO and driving markets vs. market driven innovations

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exhibits a customer and competitor orientation along with interfunctional coordina- tion. These firm behaviors are further complemented by a firm’s long-term focus and profitability. In general, an MO means learning what customers want, implementing processes to deliver what customers desire and adapting processes in response to market changes. Furthermore, an MO firm is often described as a market driven organization (for example, Day 1994; Vorhies et al. 1999).

The evidence suggests that an MO does not tend to produce radical innovations (see for example, Bennett and Cooper 1981; Hamel 1998; Rice et al. 1998). As a result, there have been attempts to broaden the meaning of a MO. For example, Jaworski et al. (2000) suggest that a MO represents both market driven and driving markets behaviors and consequences (this view is also supported by Tuominen et al. (2004)). However, the widely-used MO constructs do not include any of Jaworski et al. (2000) recommendations for capturing driving markets behaviors and consequences. Jaworski et al. (2000, p. 47) state that the driving markets approach is “in sharp contrast to a market driven approach” that “entails shaping the market structure and/or behavior of players in the market.” In the current paper, we argue that a MO focuses too much on explicit customer needs, resulting in incremental or imitative products rather than radically different innovations that disrupt customer behavior. In fact, the evidence is that an MO may negatively affect radical innovations and act as a deterrent to the development of breakthrough innovations (for example, Hayes and Abernathy 1980; Lawton and Parasuraman 1980; Bennett and Cooper 1981; Atuahene-Gima 1996). Therefore, in the current paper we argue that:

H2: SMEs with a market orientation will develop market driven innovations.

The final two hypotheses allow for a comparison of an EO and an MO in generating market driven innovations and driving markets innovations. So far, we have proposed that an EO results in driving markets innovations while an MO results in market driven innovations. Our final tests allow us to conclude that an EO is in fact superior to an MO for generating driving markets innovations; while an MO is superior to an EO for generating market driven innovations. Accordingly, our final hypotheses are that

H3: An entrepreneurial orientation leads to more driving markets innovations than an MO. H4: A market orientation leads to more market driven innovations than an EO.

Methodology

Sample and data collection procedure

We carried out a mail survey using a sampling frame purchased from Kompass NZ (www.kompass.co.nz), a database of New Zealand business-to-business firms. Two selection criteria were used: organizations were required to have 11 or more employees; and organizations needed to have been in business for at least five years. Using these criteria allowed us to omit micro-sized and start-up firms from the sample. By using more established companies, we included companies that had not only survived the start up phase but also had business practices typical of more

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established firms (Pickle and Abrahamson 1976). Our sampling frame comprised 3,871 organizations, representing a cross-section of industries. We employed a self- administered survey, which was addressed to the senior executive. In line with the principles of Dillman (2000), the mail survey was administered in two phases. A cover letter together with the questionnaire and a self-addressed envelope were mailed out first. A reminder letter followed a week later. We received 836 (21.6%) usable responses. Non-response bias was checked using Bonferroni’s corrected t-tests (see Armstrong and Overton 1977) and did not reveal any difference between the mean scores of the first 20% of respondents (“early”) and the last 20 percent of respondents (“late”). Furthermore, our sample reflected the nature of New Zealand’s small business environment in which just over 3,000 firms have 50 or more employees. In the current study, our sample was dominated by SMEs with fewer than 500 employees (94.7% of the sample).

Measure development and assessment

We followed Churchill’s (1979) and Gerbing and Anderson’s (1988) scale development procedures. We reviewed the literature for construct definitions and existing scales. All scale items were extensively pre-tested by academics and a judgement sample of CEOs of entrepreneurial companies. We used a five-point rating scale (does not describe our organization at all to describes our organization exactly) against each item in the questionnaire.

Entrepreneurial orientation We adopted Zortea’s (2005) expanded EO scale to measure: innovative firm behavior, R&D, risk taking, proactiveness, competitive aggressiveness, autonomy, opportunity recognition, growth orientation, single loop, and double loop learning (in total 66 items). This augmented EO scale was based on previous work describing the dimensions and items of an EO (Covin and Slevin 1989; Lumpkin and Dess 1996; Lyon et al. 2000).

Market orientation We adapted Kohli et al. (1993) MARKOR scale to measure an MO (in total 20 items). Extensive pre-testing revealed that the scale might be biased toward larger firms. Several executives also pointed out that some items used complicated wording (in a New Zealand context), making the items difficult to understand. Based on their feedback, we adjusted the wording of each item to minimize bias and potential misunderstandings.

Driving markets (DMI) and market driven innovations (MDI) Due to the lack of scales to assess driving markets innovations and market driven innovations, we developed new scales for this study. Our new scales were grounded on the ideas of Jaworski et al. (2000), Schiffman and Kanuk (2000), and Kumar et al. (2000) and informed by nine interviews with entrepreneurs and senior executives.

In the current paper, we argue that market driven firms try to enhance customer value within the confines of a given market structure and/or existing behaviors of market players (Jaworski et al. 2000). Therefore, market driven innovations will result in no, or at most very little, disruptive effects on customer usage patterns—that is, most innovations will be either incremental or dynamically continuous

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innovations—that is, new or modified products that affect but do not substantially alter consumer behavior (Schiffman and Kanuk (2000). Therefore, we suggest that incremental innovations and dynamically continuous innovations are examples of market driven innovations.

We measured incremental innovation with several items from Booz Allen and Hamilton’s (1982) innovation typology (additions to existing product lines, improvements or revisions to exiting product lines, cost reductions to existing products, or repositioning of existing products). Such extensions or product/service improvements do not require serious modifications to customers’ behavior nor do they lead to dramatic changes in the market (Heany 1983; Garcia and Calantone 2002). Additionally, two items from Cooper (1981) and Zahra and Covin (1995) were adapted to assess whether (1) the products or services developed met customer needs better than those offered by competitors; and (2) to inquire about the number of products or services introduced over the last 5 years.

Following Schiffman and Kanuk’s (2000) typology of innovation, we developed items to capture dynamically continuous innovations, which have a more disruptive effect on customer usage patterns but do not inflict significant change to behavior (for example, products or services that offer benefits to existing products or services not recognized by consumers before; products or services that address latent needs within existing or new market segments).

In direct contrast to market driven innovations, driving markets innovations are seen as those that proactively shape customers’ and competitors’ behaviors (Jaworski et al. (2000). Kumar et al. (2000, p. 130) argue that “the key to the success of these market driving firms is that they create and deliver a leap in benefits, while reducing the sacrifices and compromises that customers make to receive those benefits.” Furthermore, competitive advantage is achieved through “radical innovations on two dimensions—a discontinuous leap in the value proposition and the implementation of a unique business system” (Kumar et al. 2000, p. 130). Accordingly, we argue that radical innovation and changes to consumer behavior or market structures are examples of driving markets innovations.

Radical innovation was measured using the “new to the world” item from the Booz Allen and Hamilton (1982) typology of innovation. A new to the world innovation is likely to shape the market and change consumers’ behavior. To emphasise the radical aspect of these innovations, an additional item was adapted from Chandy and Tellis (1998) to cover the introduction of products or services that are radically different from existing market offerings. By definition, a firm that introduces radical innovations is the first to do so. Hence, items from Deshpandé et al. (1993) were adapted to capture this pioneering aspect of radical innovation. New items were developed to reflect consumer disruption (Cooper 1985; Atuahene-Gima 1995; Schiffman and Kanuk 2000). Kumar et al. (2000), for instance, stress the importance of customer education as part of driving markets innovations.

New items were developed to reflect changes to consumers’ behavior such as changing their usage patterns and/or learning new things as part of the product adoption process (Cooper 1985; Atuahene-Gima 1995; Schiffman and Kanuk 2000). Kumar et al. (2000), for instance, stress the importance of customer education as part of driving markets behaviors.

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We assessed changes to market structure with newly developed items designed to capture the creation of new markets and the re-arrangement of existing markets following the introduction of a new product or service (Kumar et al. 2000; Song and Xie 2000). Additionally, markets can be changed by dramatically altering the distribution of products or services (Jaworski et al. 2000; Kumar et al. 2000), investing in technological opportunities that do not contribute to the needs of one’s main customers (Christensen and Bower 1996), using innovative business models (for example, joint ventures, partnerships) to lead markets with new products and acquiring competitors (Jaworski et al. 2000).

In order to develop and test our measurement models, we used Anderson and Gerbing’s (1982) approach, in which we applied confirmatory factor analysis (CFA) using AMOS 5.0. All of the initial measurement models required modifications to improve model fit. These modifications were based on theory and CFA (high modification indices, large residuals, and low standardized regression weights). Two samples were collected; Sample 1 was used for the development of the measurement model and Sample 2 for validation of the model. This allowed greater confidence that our models would perform well when run with a different sample (Bagozzi and Yi 1988). We followed Hu and Bentler’s (1999) and Schumacker and Lomax’s (1996) recommendations to determine the cut-off criteria for good/adequate fit statistics. The CFA results for all final measurement models (an EO, an MO, driving markets and market driven innovations) are presented in Table 1; we elaborate upon our procedure below.

We first tested each scale dimension for unidimensionality and then tested the dimensions together to allow for a more rigorous assessment of unidimensionality of each construct. Having established unidimensional measurement models for the EO, MO, driving markets innovations, and market driven innovations constructs, we then put all models together into one single measurement model. This very stringent test is aimed at detecting high intercorrelations among the items in these models (for example, Hult et al. 2003). Such rigorous testing occurred because potential correlations may have produced too much noise, thereby reducing the effects and explanatory power of the constructs examined in the full structural model. As before, we tested this final measurement model on Sample 1 and cross-validated it on Sample 2 and, eventually, on the full data set (see Table 1). The combination of both samples was particularly important because this single measurement model has a very high number of parameters to be estimated (the use of split samples explains the less adequate fit statistics for the final measurement model when tested with Sample 2).

We ran a multi-group invariance analysis (thus allowing for a comparison of Sample 1 and Sample 2) to ensure that all components of the measurement model were invariant across both samples. Results confirmed the invariance of this final measurement model across both samples. All measurement models were then bootstrapped to ensure model stability (Yung and Bentler 1996) and were found to be stable.

Convergent and discriminant validity of all measurement models were evaluated by following Anderson and Gerbing’s (1988) approach. The scale items for EO, MO, market driven innovations, and driving markets innovations are presented in the Appendix. To assess convergent validity, the standardized factor loadings for all indicators were examined. Their values ranged from 0.50 to 0.90 and are greater than twice their standard errors. Furthermore, all indicators were significant with their t scores ranging from 12.48 to 26.08. These findings support convergent validity of all

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indicators. We examined discriminant validity by performing pairwise χ2 difference tests. Correlations between each factor pair were constrained to 1.0. The χ2 values obtained for the constrained and unconstrained models were then compared. The results show discriminant validity between all pairs of constructs. Composite reliabilities for all constructs were greater than the recommended minimum threshold value of 0.60 (Nunnally 1978; Bagozzi and Yi 1988) as described in the Appendix. The summary statistics and correlations among the constructs are reported in Table 2.

Due to the rigorous scale development process we undertook, combined with very strict cut-off values for all goodness-of-fit indices, Zortea’s (2005) EO scale was reduced to 24 items to reflect eight dimensions and Kohli et al. (1993) MARKOR scale was reduced to 10 items to reflect three dimensions. DMI and MDI were measured with a total of 14 items. Although a larger number of items per dimension is desirable, only two items per factor are necessary to sufficiently capture a dimension (Gerbing and Anderson 1988). Also, Marsh et al. (1998) state that large samples (N>200) compensate, to some extent, for fewer items per factor.

In the current study, we aggressively reduced the responsiveness dimension from nine to only three items. Farrell and Oczkowski (1997) encountered similar problems when testing the MARKOR scale and also reduced the responsiveness component to three items. Similarly, Siguaw et al. (1998) removed seven items from the responsiveness component and Gray et al. (1998) measured responsiveness with only two items.

Results

In this section, we report our results in which we had to take a fairly iterative, rigorous approach in order to finally test our hypotheses. As this section shows, we had to make several modifications to the proposed model due to the behavior of several constructs. We initially ran the model as proposed and found that the

Table 1 CFA results for EO and innovation measurement model

Model χ2 Df p-value χ2 /df GFI AGFI TLI CFI RMSEA SRMR

EO (final) 349.74 207 .000 1.690 0.95 0.93. 0.96 0.97 0.036 0.0333

EO (final)—sample 2 383.97 207 .000 1.855 0.90 0.86 0.91 0.93 0.054 0.0467

Full data set 491.30 207 .000 2.737 0.95 0.93 0.95 0.96 0.041 0.0331

MO (final) 82.05 32 .000 2.564 0.97 0.95 0.96 0.97 0.054 0.0344

MO (final)—sample 2 79.024 32 .000 2.470 0.095 0.91 0.92 0.94 0.071 0.0445

Full data set 121.96 32 .000 3.811 0.97 0.95 0.95 0.96 0.058 0.0328

Driving markets (final) 32.17 11 .001 2.924 0.98 0.96 0.98 0.99 0.060 0.0262

Driving markets (final)—sample 2 29.16 11 .002 2.651 0.97 0.93 0.96 0.98 0.075 0.0379

Full data set 44.28 11 .000 4.025 0.98 0.96 0.87 0.99 0.060 0.0276

Market driven (final) 19.91 8 .011 2.488 0.99 0.97 0.98 0.99 0.052 0.0247

Market driven (final)—sample 2 16.15 8 .040 2.018 0.98 0.95 0.97 0.99 0.059 0.0292

Full data set 27.38 8 .001 3.422 0.99 0.97 0.98 0.99 0.054 0.0235

All models 1548.49 881 .000 1.758 0.89 0.86 0.93 0.94 0.037 0.0389

All models (sample2) 1433.83 881 .000 1.628 0.83 0.79 0.88 0.90 0.046 0.0506

Full data set 2008.13 881 .000 2.279 0.91 0.88 0.92 0.93 0.039 0.0374

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T a b le

2 C o rr el at io n m at ri x an d d es cr ip ti v e st at is ti cs

o f m ea su re s

D im

en si o n s

C o rr el at io n s

1 2

3 4

5 6

7 8

9 1 0

11 1 2

1 3

1 4

1 5

1 6

1 7

1 8

1 . In n o v at iv e fi rm

b eh av io r

1 .0 0

2 . R & D

0 .4 2 * *

1 .0 0

3 . R is k ta k in g

0 .3 6 * *

0 .3 9 * *

1 .0 0

4 . P ro ac ti v en es s

0 .5 0 * *

0 .4 3 * *

0 .4 6 * *

1 .0 0

5 . C o m p et it iv e ag g re ss iv en es s

0 .3 7 * *

0 .2 6 * *

0 .2 7 * *

0 .5 3 * *

1 .0 0

6 . A u to n o m y

0 .3 4 * *

0 .2 6 * *

0 .3 1 * *

0 .2 9 * *

0 .2 7 * *

1 .0 0

7 . O p p o rt u n it y re co g n it io n

0 .4 3 * *

0 .4 3 * *

0 .3 4 * *

0 .4 7 * *

0 .3 4 * *

0 .2 1 * *

1 .0 0

8 . G ro w th

o ri en ta ti o n

0 .3 9 * *

0 .3 5 * *

0 .4 6 * *

0 .5 4 * *

0 .4 0 * *

0 .3 3 * *

0 .3 5 * *

1 .0 0

9 . S in g le

lo o p le ar n in g

0 .3 5 * *

0 .2 2 * *

0 .1 8 * *

0 .3 2 * *

0 .3 0 * *

0 .1 3 * *

0 .3 1 * *

0 .2 6 * *

1 .0 0

1 0 . D o u b le

lo o p le ar n in g

0 .4 3 * *

0 .2 9 * *

0 .2 4 * *

0 .3 9 * *

0 .3 3 * *

0 .2 1 * *

0 .2 9 * *

0 .3 2 * *

0 .4 7 * *

1 .0 0

11 . In te ll ig en ce

g en er at io n

0 .4 5 * *

0 .3 5 * *

0 .2 2 * *

0 .4 7 * *

0 .3 9 * *

0 .2 8 * *

0 .4 7 * *

0 .3 2 * *

0 .4 4 * *

0 .4 0 * *

1 .0 0

1 2 . In te ll ig en ce

d is se m in at io n

0 .4 8 * *

0 .2 6 * *

0 .2 0 * *

0 .4 3 * *

0 .4 1 * *

0 .2 9 * *

0 .3 8 * *

0 .2 9 * *

0 .3 5 * *

0 .3 7 * *

0 .6 2 * *

1 .0 0

1 3 . R es p o n si v en es s

0 .3 6 * *

0 .1 6 * *

0 .1 3 * *

0 .3 4 * *

0 .3 9 * *

0 .1 8 * *

0 .2 5 * *

0 .2 2 * *

0 .3 3 * *

0 .3 3 * *

0 .5 3 * *

0 .5 8 * *

1 .0 0

1 4 . D M I—

R ad ic al

in n o v at io n

0 .3 6 * *

0 .4 9 * *

0 .4 0 * *

0 .5 9 * *

0 .3 5 * *

0 .2 3 * *

0 .4 0 * *

0 .4 3 * *

0 .1 6 * *

0 .2 5 * *

0 .3 3 * *

0 .3 1 * *

0 .2 1 * *

1 .0 0

1 5 . D M I—

B eh av io ra l ch an g e

0 .3 2 * *

0 .3 7 * *

0 .3 2 * *

0 .3 9 * *

0 .3 0 * *

0 .2 5 * *

0 .3 2 * *

0 .3 5 * *

0 .1 8 * *

0 .2 5 * *

0 .3 1 * *

0 .3 1 * *

0 .1 3 * *

0 .4 8 * *

1 .0 0

1 6 . D M I—

S tr u ct u ra l ch an g e

0 .3 4 * *

0 .4 1 * *

0 .4 3 * *

0 .5 2 * *

0 .3 8 * *

0 .3 4 * *

0 .3 4 * *

0 .5 1 * *

0 .2 0 * *

0 .2 8 * *

0 .3 4 * *

0 .3 3 * *

0 .1 8 * *

0 .6 0 * *

0 .6 1 * *

1 .0 0

1 7 . M D I—

In cr em

en ta l in n o v at io n

0 .4 1 * *

0 .3 5 * *

0 .3 5 * *

0 .5 6 * *

0 .4 7 * *

0 .3 4 * *

0 .3 6 * *

0 .4 9 * *

0 .3 0 * *

0 .3 5 * *

0 .4 2 * *

0 .4 5 * *

0 .3 4 * *

0 .5 2 * *

0 .4 4 * *

0 .5 7 * *

1 .0 0

1 8 . M D I—

D y n am

ic al ly

co n ti n u o u s

in n o v at io n

0 .4 0 * *

0 .3 8 * *

0 .3 4 * *

0 .5 0 * *

0 .3 4 * *

0 .3 5 * *

0 .3 1 * *

0 .4 3 * *

0 .2 3 * *

0 .2 9 * *

0 .4 2 * *

0 .3 6 * *

0 .2 8 * *

0 .5 0 * *

0 .5 7 * *

0 .5 5 * *

0 .4 9 * *

1 .0 0

S u m m ar y st at is ti cs

N u m b er

o f it em

s 2

2 3

3 3

2 2

2 2

3 4

3 3

2 2

3 3

3

M ea n

3 .3 7

2 .5 2

2 .4 0

3 .6 5

3 .1 8

2 .5 3

3 .5 7

3 .1 7

3 .5 8

3 .1 1

3 .5 6

3 .6 0

3 .8 5

2 .9 4

2 .5 5

2 .5 3

3 .3 6

3 .1 8

S ta n d ar d d ev ia ti o n

0 .8 7

1 .2 3

0 .9 1

0 .8 2

0 .8 5

1 .0 2

0 .8 9

0 .8 9

0 .8 1

0 .8 3

0 .7 4

0 .7 9

0 .6 3

1 .1 3

1 .0 2

0 .9 2

0 .8 5

0 .8 9

* p < 0 .0 5 , * * p < 0 .0 0 1

154 Int Entrep Manag J (2012) 8:145–164

responsiveness dimension, a component of the MO construct, had a negative impact on innovations that change market structures and consumers’ behavior (two types of driving markets innovations). While not anticipated in the current study, these suppressive paths are not entirely unexpected because being responsive, as defined by the existing MO construct, is less likely to result in driving markets innovations since its emphasis is on encouraging meeting existing customers’ needs and generating a positive customer response. We also found that only four components of an EO were significant—R&D, proactiveness, autonomy and growth orientation. Therefore, we reran the model and deleted all non significant paths and dimensions. Fit statistics were good with the χ2/df=3.43, GFI=0.90 and CFI=0.90. The final results are provided in Fig. 2 and summarized in Table 3.

In the current study, we find that an EO has a significant and positive effect on all five types of innovation, with radical innovation and structural change being influenced the most. Therefore, we find evidence to support H1 and conclude that an EO leads to driving markets innovations. We also find evidence for H2 that an MO leads to market driven innovations; however, when we compared the two orientations, we found that an MO does not lead to driving markets innovations. Therefore, we find no support for H3 that an EO leads to more driving markets innovations than an MO; however, the results for H4 were unexpected. We hypothesized that an MO would lead to more market driven innovations than an EO. In this research, the opposite was true. While both orientations led to market

R&D

DMIBC

MDIINC

MDIDYC

EO

ResEO

MOIG

MOID

RESP.

DMISC

PRO

AUT

DMIRAD

MO

0.230.40

0.09

0.58

0.28 0.43

0.89

0.75

0.90

0.75

0.74

0.85

0.99

0.91

0.32

0.16

GRO

0.37

0.33

0.75

0.47

0.70

Fig. 2 Final EO-MO model

Int Entrep Manag J (2012) 8:145–164 155

driven innovations, the effect of an EO on market driven innovations was significantly greater than the effect of an MO. Therefore H4 is not supported in the current study.

Discussion and managerial implications

Our results show that firms drive markets by adopting an EO. That is, firms with an entrepreneurial orientation not only create new markets or re-arrange existing ones by launching new products or services but also cause customers to alter their usage behavior. Such firms offer superior customer value while requiring the customers who buy their products or services to learn new things.

Bennett and Cooper (1979, p. 77) argue that great product innovations are a result of technological breakthroughs, laboratory discoveries, or inventions “with only a vague notion of a market need in mind.” They claim that such innovations are often produced in a way that is far removed from customers, market needs and wants, and even from the industry itself. Moreover, customers restrict perceptions of their own needs to familiar things (Bennett and Cooper 1981). The same applies to customers’

Table 3 Effects of an EO and a MO on driving markets\market driven innovations

SEM results

SRWs Total effects

EO ➔ DMI—Radical innovation 0.89**

EO ➔ DMI—Behavioral change 0.75**

EO ➔ DMI—Structural change 0.90**

EO ➔ MDI—Incremental innovation 0.75**

EO ➔ MDI—Dynamically continuous innovation 0.74**

MO ➔ DMI—Radical innovation Path not significant

MO ➔ DMI—Behavioral change Path not estimated

MO ➔ DMI—structural change Path not estimated

MO ➔ MDI—Incremental innovation 0.32**

MO ➔ MDI—Dynamically continuous innovation 0.16**

SMCs

EO 0.70

MO Intelligence generation 0.72

MO Intelligence dissemination 0.99

MO Responsiveness 0.83

DMI—Radical innovation 0.79

DMI—Behavioral change 0.56

DMI—Structural change 0.81

MDI—Incremental innovation 0.67

MDI—Dynamically continuous innovation 0.58

Sample size 836

*p<0.05, **p<0.001

156 Int Entrep Manag J (2012) 8:145–164

ability to verbalize their needs. Kerby (1972) also points out that countless products have been invented that customers do not even know they want. Lynn et al. (1996) further stress that being customer-driven is not at all effective when the market has never seen any of the features offered by radical product innovations and potential customers are unknown; getting close to customers can discourage innovation rather than promote it (Macdonald 1995). The findings of this study demonstrate the limitations of an MO for generating radical innovation, altering the market structure and/or customer usage patterns (see for example, McGee and Spiro 1988; Kumar et al. 2000). Rather, adopting an MO tends to lead to incremental and dynamically continuous innovations—that is, market driven innovations.

Although we did find that an MO led to market driven innovations (that is, incremental and dynamically continuous innovations), we found that an EO performed better in its ability to support market driven innovations. Therefore, we suggest that an EO offers a more balanced approach than an MO because it promotes both driving markets and market driven innovations. Consequently, an EO is presented as an essential and, above all, comprehensive business philosophy for generating radically different products or services, shaping the market and the behavior of its players, and modifying and revising products or services in order to enhance customer satisfaction. Hence, organizations wishing to create a competitive advantage and shape the market will find adopting an EO useful.

The findings of our research recommend that SME managers adopt an EO if they want their firms to engage in driving markets innovations while also keeping in touch with current customers. EO firms actively search for and pursue new opportunities, focus on long-term R&D, empower employees to contribute to the innovative process of the firm, acquire new resources, and expand into new markets to grow. Our study shows that an MO (1) does not lead to driving markets innovations and (2) affects market driven innovations but less than an EO. This implies that managers should exercise caution when deciding on how intimately to strategically align their firms with their markets. In particular, when the generation of radically different market offerings lies at the core of the business, managers might want to reconsider an approach that focuses too closely on customers and their explicit needs.

Finally, with robust scales to measure MO, EO, and driving markets and market driven innovations, managers can identify and develop effective behaviors and practices. At the same time, managers are able to check whether their company drives markets. This is an important contribution in itself, since, so far, no metric had been available to specifically assess these driving markets outcomes; however, the simple use of these scales to undertake an independent audit of behaviors within a firm is limited. Making comparisons between SMEs in similar or different industries can derive more value to the firm. Without such comparisons, managers do not know how well their businesses are performing in these areas.

Limitations and future research

This study is subject to several limitations. First, as with other studies on EO and MO (for example, Miller 1983; Greenley 1995; Li and Calantone 1998; Kreiser et al.

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2002) we collected data from only one respondent in any organization. The CEO or managing director of a firm may not accurately perceive how a firm operates in its environment (Sharfman 1998), although given the small business profile of our sample we believe the CEO is in a good position to comment on the behaviors and practices within his or her firm. Furthermore, Hambrick’s (1981) research findings show that CEOs’ perceptions of overall strategies of the firm are closer to a set of objective measures of the same phenomena than are other managers’ perceptions. Since an EO and an MO represent overall firm orientations, we consider the single informant adequate for this study, but note that using single informants may limit validity. Second, the study was administered by mail, relying on the self-reporting of respondents. For example, we acknowledge that firms that have consciously adopted an EO may be more aware of issues surrounding entrepreneurial behavior and possible outcomes (such as radical innovations) than firms that have not. Consequently, it is likely that firms conscious of an EO might exhibit higher scores.

Our study offers several possible areas for future research. The investigation of the relationship between an EO and driving markets/market driven innovations makes a significant contribution to the entrepreneurship literature as well as the marketing literature. By introducing an MO to this framework, the predictive validity of an EO is confirmed and valuable research is added to both streams of literature. No known studies investigate both orientations and their impact on driving markets innovations and market driven innovations. We recommend further research is conducted to further explore the ability of an EO to drive markets compared with an MO. This also includes longitudinal research to assess the impact of an EO over time. The conflicting nature of the responsiveness dimension of an MO represents an unprecedented phenomenon that also needs further examination. Having established a positive link between an EO and driving market innovations, we recommend more research to establish how this relationship influences firm performance. This is of importance because driving markets innovations can be viewed as a means of achieving better firm performance.

In general, the relationship between an EO and an MO represents another area of future research. Some researchers highlight the fact that managers incorporate more than one approach to business orientations in organizations (Fritz 1996; Greenley and Foxall 1997). Also, the combination of both an EO and a MO is regarded as beneficial to organizations, enabling them to outperform their competitors (Slater and Narver 1995; Atuahene-Gima and Ko 2001) however, overall theoretical and empirical support for the relationship between both approaches is scarce (for example, Murray 1981; Morris and Paul 1987; Morris and Sexton 1996; Miles and Arnold 1991; Hills and LaForge 1992; Becherer and Maurer 1997; Hultman 1999; Slater and Narver 2000; Matsuno et al. 2002; Bhuian et al. 2005). The development of a measurement tool to assess the several selected manifestations of driving markets and market driven innovations may provide the opportunity for additional research on the driving markets/market driven concept itself. This paper does not claim that the scales developed for the study capture all facets of driving markets and market driven innovations. In fact, we encourage researchers to undertake more research in this area, and broaden the sample beyond business-to-business firms, to overcome the obvious lack of empirical studies on the driving markets/market driven concept.

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Overall, we believe our research makes an important contribution to existing knowledge in both the entrepreneurship and marketing literatures. Given the importance of driving markets in order to achieve competitive advantage and long- term survival, it is hoped that a stream of research will emerge that further explores relationships discussed in this study and identifies other consequences as well as antecedents of an EO in the context of SMEs.

Appendix

Table 4 Scale items for construct measures (full data set)

Standardized factor loading

t value** Composite reliability/ Coefficient alpha

EO CONSTRUCT

Innovative firm behavior 0.65/0.66

Our organization rewards people for creativity and innovation. 0.66 16.12

We create and sustain cross-functional groups of energetic and opinionated people.

0.72 Path fixed to 1

R&D 0.74/0.74

Our organization employs highly skilled research and development (R&D) staff.

0.80 Path fixed to 1

Our organization focuses on long term (that is, more than 3 years) R&D.

0.74 17.23

Risk taking 0.78/0.78

We invest in high-risk projects, which have the chance of very high returns.

0.72 17.88

Despite the uncertainty of our environment, we take risks to achieve the organization’s objectives.

0.74 Path fixed to 1

We seize risky growth opportunities. 0.73 18.05

Proactiveness 0.72/0.72

We are constantly seeking new opportunities to exploit. 0.64 17.28

We invest in projects that will provide us with a future competitive edge.

0.73 Path fixed to 1

Our organization seeks to shape the market place with its products or services.

0.68 18.53

Competitive aggressiveness 0.79/0.79

Our organization usually responds forcefully to actions undertaken by our competitors.

0.74 19.88

In dealing with our competitors, we initiate actions that our competitors then respond to.

0.80 Path fixed to 1

In response to our competitors, we redefine our products or services on a regular basis.

0.70 18.78

Autonomy 0.83/0.82

In our organization, champions assist people working on an innovation to make decisions outside the decision approval system.

0.78 Path fixed to 1

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Table 4 (continued)

Standardized factor loading

t value** Composite reliability/ Coefficient alpha

In our organization, champions assist people working on an innovation to avoid the need to provide financial justification at every stage of the development process.

0.90 16.28

Opportunity recognition 0.63/0.63

We track technological changes in our industry. 0.64 14.61

We actively attempt to predict industry trends. 0.72 Path fixed to 1

Growth orientation 0.69/0.69

We constantly acquire new resources. 0.68 Path fixed to 1

Our organization expands into new markets or market segments. 0.77 16.82

Single loop learning 0.76/0.75

Our monitoring systems highlight gaps between achieved and expected performance.

0.70 Path fixed to 1

We correct gaps between achieved and expected performance by changing our strategy and tactics.

0.86 15.90

Double loop learning 0.81/0.80

We frequently re-evaluate and challenge our organizational objectives.

0.84 21.17

We frequently challenge values and beliefs underlying our organizational objectives.

0.76 Path fixed to 1

We carefully examine discrepancies between our explicit objectives and policies and what our policies and practices actually are.

0.69 18.56

MARKET ORIENTATION

Intelligence generation 0.77/0.76

We meet with customers to find out what products or services they will need in the future.

0.67 17.19

We are quick to detect changes in our customers’ product or service preferences.

0.74 18.94

We systematically assess customer perceptions about the quality of our products and services.

0.71 Path fixed to 1

We periodically review the likely effect of changes in our business environment (for example, regulations) on customers.

0.58 15.17

Intelligence dissemination 0.68/0.69

In our organization, employees often discuss customers’ future needs.

0.72 15.67

When something important happens to a major customer or market, the whole organization knows about it within a short period.

0.63 14.32

Data on customer satisfaction are disseminated to all levels in this organization on a regular basis.

0.59 Path fixed to 1

Responsiveness 0.61/0.61

We always respond to changes in our customers’ product or service needs.

0.53 13.31

When responding to the market, the activities of our employees are well coordinated.

0.71 Path fixed to 1

We always listen to customer complaints. 0.50 12.48

DRIVING MARKETS INNOVATIONS

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