1
 
ENTREPRENEURIAL ORIENTATION, MARKET ORIENTATION, AND
PERFORMANCE IN MANUFACTURING SMES

Ricardo Gouveia Rodrigues (rgrodrigues@ubi.pt)
University of Beira Interior, Department of Business and Economics, Research Unit NECE
Estrada do Sineiro, 6200-209 COVILHÃ, PORTUGAL

ABSTRACT
Marketing and entrepreneurship are two different disciplines in the business research areas.
In the marketing field, for long years it was not possible to study the link between the firms using
marketing and their performance. But the works of Kohli, Jaworski and Kumar (1993) and
Narver and Slater (1990) came up with alternative scales to measure market orientation, thus
allowing quantifying the level of the firms’ orientation towards marketing.
On the other way, authors like Covin and Morgan (1999), Covin and Slevin (1991) or Miller and
Friesen (1983) searched for the link between corporate entrepreneurship and business
performance, proposing the concept of entrepreneurial orientation and a scale to measure it.
Since the proposal of both concepts, several studies looked for the link between market
orientation and performance, and for the link between entrepreneurial orientation and
performance.
But little has been done to connect the concepts of market orientation, entrepreneurial orientation
and performance.
The aim of this paper is to propose and test a structural equations model which includes the
relationship among market orientation, entrepreneurial orientation and business performance.
The results show no direct relationship between either entrepreneurial orientation or market
orientation and economic results. Entrepreneurial orientation has a direct positive effect on
market share, but market orientation doesn’t. Both entrepreneurial and market orientation have a
direct effect on new product success. New product development is both an entrepreneurial
activity and a marketing activity, so this result strengths the relationship between marketing and
entrepreneurship.
Moreover, entrepreneurship has a positive direct impact on market orientation. This suggests that
entrepreneurship is an antecedent of marketing, and that being entrepreneur make firms pay more
attention to their markets.

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INTRODUCTION
Marketing and entrepreneurship are two different disciplines in the business research areas.
In the marketing field, for long years it was not possible to study the link between the firms using
marketing and their performance. But the works of Kohli, Jaworski and Kumar (1993) and
Narver and Slater (1990) came up with alternative scales to measure market orientation, thus
allowing to quantify the level of the firms’ orientation towards marketing.
On the other way, authors like Covin and Morgan (1999), Covin and Slevin (1991) or Miller and
Friesen (1983) searched for the link between corporate entrepreneurship and business
performance, proposing the concept of entrepreneurial orientation and a scale to measure it.
Since the proposal of both concepts, several studies looked for the link between market
orientation and performance, and for the link between entrepreneurial orientation and
performance.
But little has been done to connect the concepts of market orientation, entrepreneurial orientation
and performance.
The aim of this paper is to propose and test a structural equations model which includes the
relationship among market orientation, entrepreneurial orientation and business performance.
Both marketing and entrepreneurship have innovation as one of their cornerstones. In spite of
this obvious common element, little research has been done to explore the joint effect of both
marketing and entrepreneurship on business performance. This paper contributes to fill this gap.
LITERATURE REVIEW
Lafferty and Hult (2001), in their work of theoretical synthesis of Market Orientation, identify
two main theoretical approaches: cultural focus and managerial focus. The first being identified
with the works of Deshpandé et al. (1993) and Narver and Slater (1990), and the other with the
works of Kohli e Jaworski (1990), Shapiro (1988) and Ruekert (1992).
The proposal of Narver and Slater (1990) is the most adopted in later researches using cultural
focus. They defend that the Market Orientation construct comprehends three dimensions –
Customer Orientation, Competitor Orientation, and Interfunctional Coordination (Figure 1).

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Figure 1 - Market Orientation - Cultural Approach

Source: Narver and Slater (1990:23)
On the other hand, Kohli, Jaworski and colleagues, state that Market Orientation includes three
dimensions – Intelligence Generation, Intelligence Dissemination and Responsiveness, as shown
in Figure 2.
Figure 2 - Market Orientation - Managerial Approach
 
Source: Own, based on Kohli and Jaworski (1990)
Despite the presence of these two different approaches in the literature, Rodrigues (2004) stands
that they are convergent and complement each other, and there have been studies to integrate

Intelligence
Dissemination

Intelligence
Generation

Responsiveness
Market
Orientation
Customer
orientation
Interfunctional
Coordination
Competitor
Orientation
Long-Term
Profit
Focus
Target market

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together in the same study (Cadogan and Diamantopoulos, 1995; Küster, 1999; Lafferty and
Hult, 2001).
The links between the two approaches are emphasized by Narver and Slater (1990), when they
state that the three behavioural components of Market Orientation include the activities of
generating market intelligence, disseminating intelligence, and co-ordinately creating customer
value (see Figure 2). In a later work, Slater and Narver (1994) suggest a view of Market
Orientation combining the two focuses, as shown in Figure 3.

Figure 3 – Market Orientation – Integration of Approaches
 
Source: Adapted from Slater e Narver (1994b:23)
In this paper Market Orientation is considered as being market intelligence generation, its
dissemination throughout the organisation, and the response of the entire organisation.

According to Kreiser, Marino and Weaver (2002), the theoretical foundation of entrepreneurial
orientation lays on that firms with that orientation are different from the others. Miller and
Friesen (1982) defend that entrepreneurial firms have a will to innovate regularly and boldly,
taking considerable risks in their market and product strategies. They also say (Miller e Friesen,
1978), as well as other authors (Mintzberg, 1973; Khandwalla, 1977), that entrepreneurial firms
seek new opportunities in a proactive way. These contributes were integrated to form the
construct Entrepreneurial Orientation, encompassing three dimensions – Innovativeness,
Proctivity and Risk-taking (Figure 4).


Customer
Intelligence
Competitor
Intelligence
Other market
intelligence
Shared
diagnosis and
coordinated
action Superior
customer
value
Intelligence
Acquisition
Interfunctional
assessment

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Figure 4 – Entrepreneurial Orientation

Source: Own, based on Miller (1983)
Recent studies focused on the impact of the two constructs, Market Orientation and
Entrepreneurial Orientation, on Business Performance.
Jones, Knotts and Udell (2008) conclude that Market Orientation is crucial for the success of
small manufacturers.
Moreno and Casillas (2008) studied the effect of Entrepreneurial Orientation on the growth of
SMEs using a PLS model. Green, Covin and Slevin (2008) defend that Entrepreneurial
Orientation combined with a strategic reactiveness posture enhances business performance.
Wang (2008) found that Entrepreneurial Orientation combined with Learning Orientation have a
strong impact on Business Performance.
Li, Zhao, Tan and Liu (2008) found that Market Orientation, when combined with some
dimensions of Entrepreneurial Orientation, has a positive impact on Business Performance.
Todorovic and Ma (2008) report how a cultural variable, individualism/collectivism, influences
Market Orientation, Entrepreneurial Orientation and Performance.
Other authors studied the relationship between Market Orientation and Innovation, which is a
component of Entrepreneurial Intention, concluding that there is a positive relationship
(Grinstein, 2008; Hsieh, Tsai and Wang, 2008; Jimenez-Jimenez, Valle and Hernández-
Espallardo, 2008; Laforet, 2008; Paladino, 2008).
 
Proactivity

Innovativeness

Risk-taking
 
Entrepreneurial
Orientation

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RESEARCH MODEL AND HYPOTHESIS
The research model proposed relates Market Orientation, entrepreneurial Orientation and
Performance, as shown in

Figure 5 – Proposed Research Model

MO – Market Orientation, EO – Entrepreneurial Orientation; BP – Business Performance
The research hypotheses that come from the proposed model are as follow:
H1: The higher the Market Orientation, the higher the Business Performance.
H2: The higher the Entrepreneurial Orientation, the higher the Market Orientation.
H3: The higher the Entrepreneurial Orientation, the higher the Business Performance.

METHODOLOGY
This paper adopts a quantitative methodology, based on a hypothetical/deductive method. From
the literature several research hypothesis are drawn concerning the relationships among market
orientation, entrepreneurial orientation, and business performance. These hypotheses are used to
build a model which is tested with the structural equations modelling (SEM) technique.
H3
MO BP
 
EO
H1
H2

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The population studied is constituted by manufacturing SMEs located in Portugal. Data was
collect with a postal questionnaire on a random sample of 1530 firms, resulting in 212 valid
responses (15% response rate).
As non response rate was very high, Armstrong and Overton’s (1977) procedures to evaluate
non-response bias were carried on. Using the extrapolation method (Ferber, 1948-1949)1, we
came into the conclusion that non-respondent did not differ from respondents, thus minimising
the risk of non-response bias.
To measure Market Orientation, MARKOR scale was used, combined with the MO scale
(Matsuno et al. 2000), resulting in a total of 35 indicators.
Covin and Slevin’s (1989) scale for Entrepreneurial Orientation was used, which has a total of
nine indicators.
Performance was measured on three aspects – Economic Results, Relative Market Share and
New Product Success (Moorman, 1995), in a total of 21 indicators.
RESULTS
In order to test the research hypothesis, data was analysed with the Structural Equation
Modelling (SEM) technique, using the statistical software Amos 4.0.
The two-step approach recommended by Anderson and Gerbing (1988), being the first step the
evaluation of the measurement model, and the second step the structural model analysis.
The initial measurement models (one for each construct) were composed of 65 indicators, 35 to
measure Market Orientation, 9 to measure Entrepreneurial Orientation, and 21 to measure
Business Performance.
The measurement models were assessed using Incremental Fit Measures (NFI, RFI, IFI, NNFI
and CFI). All the models showed poor measures, so, as recommended by Garson (2003),
measurement models had to purified, deleting indicators with poor performance.
Indicators were evaluated according to their significance of regression coefficients, standardised
residuals (not higher than 2.58), and explained variances (Hair et al., 1998).
After the purifying process, the measurement models included 32 indicators (MO – 13, EO -6,
BP, 13).
Fit measures (Table 1) show that the measurement models are acceptable, so the first step of the
analysis is completed.
                                                            
1 Ferber, Robert (1948-1949) “The problem of Bias in Mail Returns: A Solution”, Public Opinion Quarterly, 40
(Winter), 669-676, quoted by Armstrong and Overton (1977).

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Table 1 - Fit Measures – Measurement Models
MO EO
Absolute Fit Measures
Chi-Square χ2 120.787 10.317
Degrees of Freedom GL 62 7
Bollen-Stine bootstrap p 0.729 0.199
Root Mean Square Residual RMSR (RMR) 0.214 0.091
Goodness-of-Fit Index GFI 0.935 0.980
Root Mean Square Error of Approximation RMSEA 0.067 0.047
Incremental Fit Measures
Adjusted Goodness-of-Fit Index AGFI 0.905 0.941
Relative Adjusted Goodness-of-Fit Index RAGFI 0.946 0.951
Normed Fit Index NFI 0.768 0.941
The second step of the analysis is the test of the structural model, which allows to test the
research hypotheses.
Because the data doesn’t follow a multi-normal distribution2, the estimation method used was
ADF (Asymptotically distribution-free). This is a very demanding estimation method in what
regards sample size3. In this case, with 32 indicators, sample size should be bigger than 528. As
the sample has only 212 observations, the measurement models had to be parcelled. Catanzaro
(1997) defines parcels as indicators that are computed by summing up or averaging other
indicators. This way, first order constructs become indicators, and second order constructs
become first order constructs. After computing parcels using means, instead of 32 indicators, the
model stays with 11 indicators, making it possible to use ADF estimation.
The structural model to be analysed is presented on Figure 6. Ellipses represent the constructs,
and rectangles represent the indicators, which were first order constructs before parcelling.
After estimating the model, coefficients are analysed for their significance. The ones non
significant are excluded from the model.
In Table 2 the structural model coefficients are presented. Three of them are non significant and
are to be excluded from the model. The paths MO → MS, EO → ER, and MO → ER aren’t
statistically different from zero (α = 0.05). Market Orientation doesn’t have a direct effect on
Market Share nor on Economic Results, and Entrepreneurial Orientation does not have a direct
effect on Economic Results.
The next step is to analyse a modified structural model without the non significant paths – model
B.
                                                            
2 Mardia coefficient with a t statistic of 9,501, bigger than the critical value t0,025;∞= 1,96.
3 Sample size must be bigger than
2
)1p(*p + , where p is the number of indicators.

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Figure 6 – Structural Model

MO – Market Orientation; EO – Entrepreneurial Orientation; NP – New Product Success; ER – Economic Results; MS – Market Share;
IG – Intelligence Generation; ID – Intelligence Dissemination; R – Responsiveness; IN– Innovativeness; PR – Proactivity;
RT- Risk-Taking; NPT – New Product Timing; NPC – New Product Creativity; NPP – New Product Performance.

Table 2 – Structural Model Coefficients
Coefficient Standard deviation t p
Standardised
coefficient
EO → MO 0.510 0.132 3.865 0.000 0.452
MO → NP 0.346 0.094 3.681 0.000 0.346
EO → NP 0.595 0.131 4.539 0.000 0.526
EO → MS 0.633 0.260 2.435 0.015 0.378
MO → MS 0.049 0.149 0.332 0.740 0.033
NP → MS 0.531 0.183 2.902 0.004 0.359
EO → ER 0.180 0.187 0.964 0.335 0.113
MO → ER 0.043 0.089 0.487 0.627 0.031
NP → ER 0.295 0.145 2.036 0.042 0.210
MS → ER 0.373 0.093 4.020 0.000 0.393
Table 3 shows that Model B’s coefficients are all significant. Next step of the analysis is to
assess fit measures.
Table 4 shows that fit is acceptable for model B.

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Table 3 – Structural Model B Coefficients
Coefficient Standard deviation t p
Standardised
coefficient
EO → MO 0.497 0.120 4.150 0.000 0.454
MO → NP 0.336 0.092 3.653 0.000 0.334
EO → NP 0.609 0.128 4.741 0.000 0.554
EO → MS 0.567 0.243 2.334 0.020 0.359
NP → MS 0.538 0.186 2.892 0.004 0.376
NP → ER 0.434 0.101 4.286 0.000 0.314
MS → ER 0.390 0.075 5.194 0.000 0.404

Table 4 - Fit Measures – Structural Model B
Absolute Fit Measures
Chi-Square χ2 99.598
Degrees of Freedom GL 39
Bollen-Stine bootstrap p 0.045
Root Mean Square Residual RMSR (RMR) 0.166
Goodness-of-Fit Index GFI 0.904
Root Mean Square Error of Approximation RMSEA 0.086
Incremental Fit Measures
Adjusted Goodness-of-Fit Index AGFI 0.837
Relative Adjusted Goodness-of-Fit Index RAGFI 0.865
Normed Fit Index NFI 0.670
Being model B accepted as final, results of the coefficients were used to compute total effects of
the constructs, and thus test the research hypotheses.

Figure 7 – Final Structural Model with Structural Coefficients

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Based on direct effects and on path analysis, indirect and total effects can be computed, and are
shown on

of EO MO NP MS
in Directos Indirectos Totais Directos Indirectos Totais Directos Indirectos Totais Directos Indirectos Totais
MO 0.454 - 0.454 - - - - - - - - -
NP 0.554 0.152 0.705 0.334 - 0.334 - - - - - -
MS 0.359 0.265 0.624 - 0.126 0.126 0.376 - 0.376 - - -
ER - 0.474 0.474 - 0.156 0.156 0.314 0.152 0.466 0.404 - 0.404
Total effects allow to test the research hypothesis. Entrepreneurial Orientation has positive effect
on MO, NP, MS, and ER. Market Orientation has positive effect on MS NP, and ER. New
Product Success has positive effect on MS and ER. Market Share has a positive effect on ER.
H1: The higher the Market Orientation, the higher the Business Performance.
Supported.
H2: The higher the Entrepreneurial Orientation, the higher the Market Orientation.
Supported.
H3: The higher the Entrepreneurial Orientation, the higher the Business Performance.
Supported.
CONCLUSIONS
The results suggest that there is a relationship between the two apparently independent concepts
of marketing and entrepreneurship. Being so, further research is needed to deepen the knowledge
of the relationship and of its impact on business performance.
Besides, from the study’s results looks like innovation could be the connection factor between
the two concepts.
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