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Firm
Entrepreneurial orientation and performance:
firm performance: an updated an updated
meta-analysis
meta-analysis
Mauren do Couto Soares 143
Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre, Brazil and
Escola Superior de Propaganda e Marketing – Campus ESPM Sul, Received 26 January 2019
Accepted 26 June 2019
Porto Alegre, Brazil, and
Marcelo Gattermann Perin
Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre, Brazil

Abstract
Purpose – The purpose of this paper is to analyze the relationship between entrepreneurial orientation (EO)
and organizational performance through an updated and extended meta-analytic review that includes EO,
mediators, moderators and performance results.
Design/methodology/approach – Using Pearson correlations as effect size statistics, and based on 80
independent samples from 78 studies, with a total sample size of 19,514 cases, the meta-analysis consolidates
the empirical findings of this field of research.
Findings – The results reveal that there is a direct and positive impact of EO on organizational
performance, and this effect is stronger for multi-item measures of performance and for revenue-based
performance measures. In addition, the authors found partial mediation effects of learning orientation and
innovativeness on the relationship between EO and firm performance.
Originality/value – The work contributes to the literature by demonstrating the importance of EO to
organizational performance with a meta-analysis, reporting the partially mediating variables in this
relationship and seeking to explain the observed inconsistencies in preceding results, also examining
methodological moderating variables. Hence, the research extends previous meta-analytic studies done in the
area.
Keywords Organizational performance, Entrepreneurial orientation, Meta-analysis, Mediators,
Moderators
Paper type Research paper

© Mauren do Couto Soares and Marcelo Gattermann Perin. Published in RAUSP Management
Journal. Published by Emerald Publishing Limited. This article is published under the Creative
Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and
create derivative works of this article (for both commercial and non-commercial purposes),
subject to full attribution to the original publication and authors. The full terms of this licence
may be seen at http://creativecommons.org/licences/by/4.0/legalcode
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível
Superior – Brasil (CAPES) – Finance Code 001. Mauren do Couto Soares lead on data curation, formal
analysis, writing the original draft and reviewing and editing the paper. Mauren do Couto Soares RAUSP Management Journal
Vol. 55 No. 2, 2020
contributed equally to the conceptualization of the paper. Marcelo Gattermann Perin contributed pp. 143-159
equally to the conceptualization of the paper and supported in the data curation, formal analysis, Emerald Publishing Limited
2531-0488
writing the original draft and reviewing and editing the paper. DOI 10.1108/RAUSP-01-2019-0014
RAUSP 1. Introduction
55,2 Since the 1980s, entrepreneurial orientation (EO) has received growing conceptual and
empirical attention in the literature on strategic management and entrepreneurship (Rauch,
Wiklund, Lumpkin, & Frese, 2009; Shan, Song, & Ju, 2016). The relationship between EO
and performance is one of the most researched topics in this field (Saeed, Yousafzai, &
Engelen, 2014). Despite the impressive collection about EO-performance relationship, the
144 results remain inconclusive and contradictory (Su, Xie, and Wang, 2015). Some researchers
from the predominant view argue that EO is positively linked to performance (Wiklund &
Shepherd, 2003). Others claim that the effects of this relationship are either negative or not
significant (Renko, Carsrud, & Brännback, 2009; Slater & Narver, 2000). As such, there is no
unanimous conclusion or consensus on this matter.
This inconsistency has led researchers to investigate the role of mediators and
moderators that may influence the relationship between EO and performance (Schepers,
Voordeckers, Steijvers, & Laveren, 2014). The mediating factors most frequently studied
were learning orientation (Hakala, 2013; Wang, 2008) and innovativeness (Hult, Hurley, &
Knight, 2004). The disparate results may also be due to methodological moderators
associated with measurement and sample characteristics that could affect the relationship
between EO and organizational performance (Song, Podoynitsyna, Van der Bij, & Halman,
2008). For example, differences in the operationalization of EO were found (Wales, Gupta, &
Mousa, 2013). While some authors conceptualized the phenomenon based on Miller (1983),
others supported the definition of Lumpkin and Dess (1996).
To address the inconsistencies in previous research, we applied a meta-analytical review
about the empirical findings on the EO-organizational performance relationship in the field.
We also assessed potential mediating and moderating effects in this relationship.
Past efforts to consolidate research results in the EO literature were the studies
conducted by Rauch et al. (2009) and Wales et al. (2013). The first explored the existing
knowledge on the relationship between EO and performance, without analyzing certain
moderations and mediations (Rauch et al., 2009). Wales et al. (2013) developed a
comprehensive qualitative review to identify the most frequently examined antecedents,
moderators, mediators and consequences of EO.
Therefore, the main goal of the present study is to provide an updated and extended
meta-analytic investigation to evaluate a conceptual framework that includes EO,
mediators, methodological moderators, and performance results. It contributes to literature
by analyzing the sources of inconsistencies in the findings and by providing a better
understanding of the role of EO in organizations.
The article is structured as follows. Section 2 develops the theoretical framework and the
hypotheses. Section 3 describes the study identification process, coding and
operationalization of variables, as well as the meta-analytical procedures used. Section 4
reports the main results. The last section presents the article’s conclusions, academic and
managerial implications, limitations and suggestions for future studies.

2. Theoretical background and hypotheses

2.1 Entrepreneurial orientation and performance
According to Miller (2011), the performance implications of EO are the largest stream of
research within the field of entrepreneurship. The predominant argument is that EO plays
an important role in enhancing a firm’s performance (Rauch et al., 2009). Li, Liu, and Zhao
(2006) found that EO motivates companies to aggressively launch product innovations,
exploring opportunities and favoring new product development activities. Wong (2014)
noted that EO contributes to the success of new products by allowing firms to identify and Firm
proactively take advantage of new business opportunities. performance:
Although these theoretical considerations delineate the positive effects of EO, it must be
pointed that the literature also mentions negative effects that could result from EO. Naldi,
an updated
Nordqvist, Sjöberg, and Wiklund (2007) revealed the negative implications to performance meta-analysis
caused by the risk-taking dimension of EO. Such dimension shows a negative effect on
financial performance in family organizations (Naldi et al., 2007). Yet, Renko et al. (2009) 145
found that the EO construct is not a significant predictor of product innovation. These
findings revealed that EO is not necessarily beneficial and viable (Renko et al., 2009).
Regardless the contradictories results, the main stream in literature sustains that the
relationship between EO and organizational performance tend to be positive (Li et al., 2006;
Wong, 2014). Thus:

H1. The EO-organizational performance relationship is direct and positive.

2.2 Mediators of the entrepreneurial orientation-performance relationship

2.2.1 Learning orientation. Sinkula, Baker, and Noordewier (1997, p. 309) conceptualize
learning orientation as a “set of organizational values (commitment to learning, open-
mindedness, and shared vision) that influence the propensity of the firm to create and use
knowledge”. Learning orientation is proposed as a mediator in the relationship between EO
and organizational performance (Hakala, 2013; Liu, Luo, & Shi, 2002; Wang, 2008). In this
regard, Liu et al. (2002) noted that an entrepreneurial culture encourages values related to
learning that ultimately enhance an organization’s performance. Based on these arguments,
it is suggested that learning orientation is a mechanism through which a company can
maximize the impact of EO on performance (Wang, 2008). Entrepreneurial firms that seek to
generate effects on performance are more prone to investing in open-mindedness,
commitment to learning and shared vision (Wang, 2008).
Therefore, and considering the direct link between the constructs (H1), it is expected that
the relationship between EO and performance is partially mediated by learning orientation.
Thus:

H2. The EO-organizational performance relationship is partially mediated by learning

orientation.
2.2.2 Innovativeness. Innovativeness, according to Hurley and Hult (1998), is the notion of
openness to innovative ideas as an aspect of a firm’s culture. It is interesting to note that
there is a difference between innovativeness and EO. While EO is an attitude-based
construct toward certain behaviors, such as proactiveness, innovativeness is a behavior-
based construct designed to achieve results (Hult et al., 2004; Rhee, Park, & Lee, 2010).
In this sense, the literature establishes that EO can be considered an antecedent of
innovativeness (Rhee et al., 2010). Hult et al. (2004) argue that innovativeness acts as a
partial mediator in the EO-business performance relationship. When EO incorporates
proactiveness and initiative, it may increase the creation of innovation projects to improve
performance (Hult et al., 2004). Therefore, it is expected that innovativeness is a partial
mediating variable in the EO-performance relationship. Thus:

H3. The EO-organizational performance relationship is partially mediated by

innovativeness.
RAUSP 2.3 Methodological moderators of the entrepreneurial orientation-performance relationship
55,2 2.3.1 Manufacturing vs service firms. In literature, it is argued that services are less
tangible, less separable in production and consumption, more heterogeneous, and more
perishable (Zeithaml, Parasuraman, & Berry, 1985). In this regard, Kraus (2013) points that
EO can provide greater flexibility and more opportunities for adapting services to the
preferences of customers. However, higher levels of customization in services can result in
146 higher costs that can ultimately reduce a firm’s performance (Kirca, Jayachandran, &
Bearden, 2005). Therefore, it can be suggested that in manufacturing companies there is a
higher positive impact of EO on performance, since the organization’s efforts in the market
can be less costly than in the services sector, where constant revisions are required to ensure
performance and quality standards. Thus:

H4. The EO-organizational performance relationship is stronger in manufacturing

firms than in service firms.
2.3.2 Country: Western vs Asian countries. Hofstede (1983) describes national culture in
four dimensions: power distance, uncertainty avoidance, individualism and masculinity.
The first dimension, power distance, is based on the idea that “all societies are unequal, but
some are more unequal than others” (Hofstede, 1983, p. 81). Power distance, within
organizations, is associated with the degree of autocratic leadership. Uncertainty avoidance
is related to the way in which societies deal with unknown aspects of the future. Low
uncertainty avoidance societies tend to be more open and receptive to new ideas (Efrat,
2014). Individualism refers to the degree to which individual interests prevails over those of
the group (Calantone, Harmancioglu, & Droge, 2010; Efrat, 2014). In high individualistic
countries, each individual is expected to take care of him/herself and his/her immediate
family (Efrat, 2014). Masculinity involves the division of roles in society according to gender
(Hofstede, 1983). Masculine societies emphasize achievement, wealth, mission, and
performance (Calantone et al., 2010).
According to Mueller and Thomas (2000), EO might be strongly encouraged in an
individualistic country, with low uncertainty avoidance. This would be a typical
characteristic of Western countries according to Hofstede’s (1983) approach. Therefore, it is
proposed that EO leads to better performance in Western countries, where high
individualism and low uncertainty avoidance prevail. Thus:

H5. The EO-organizational performance relationship is stronger in Western than Asian

countries.
2.3.3 Objective vs subjective performance measures. Previous investigations in literature
reports that different performance measures (objective vs subjective) can produce different
correlations with dependent variables (Evanschitzky, Eisend, Calantone, & Jiang, 2012;
Kirca et al., 2005). Objective performance measures, as sales data or return on assets, are
impartially quantified (González-Benito & González-Benito, 2005). Subjective measures of
performance, made by judgmental assessment of respondents, as brand equity or customer
satisfaction, appear to be more flexible and reliable than objective ones, facilitating
comparisons between firms (González-Benito & González-Benito, 2005). Therefore, it can be
hypothesized that the strength of the relationship between EO and performance is greater
when subjective performance criteria are evaluated. Thus:

H6. The EO-organizational performance relationship is stronger for subjective

measures of performance than for objective measures of performance.
2.3.4 Single vs multi-item performance measures. Past research demonstrated the Firm
importance of multi-item measures of performance. It is claimed that the constructs’ performance:
measurement tends to be better and more precise when more than one indicator is used
(Murphy, Trailer, & Hill, 1996; Venkatraman & Ramanujam, 1986). Based on this
an updated
assumption, it is expected that stronger correlations between EO and business performance meta-analysis
are associated with the use of multi-item measures of performance. Thus:

H7. The EO-organizational performance relationship is stronger for multi-item 147

measures of performance than for single item measures of performance.
2.3.5 Cost-based vs revenue-based performance measures. Performance can also be
evaluated based on costs vs revenue measures (e.g. profitability vs sales and market share)
(Kirca et al., 2005; Song et al., 2008). In this sense, Covin, Green, & Slevin (2006) noted that
EO is more consistent with performance criteria that emphasize the effectiveness and
success of an organization, since they examine the translation of entrepreneurial activities
into a firm’s trajectory of growth and expansion. Therefore, it can be proposed that the
impact of EO on revenue-based performance measures is stronger. Thus:

H8. The EO-organizational performance relationship is stronger for revenue-based

performance measures than for cost-based performance measures.
2.3.6 Entrepreneurial orientation scales. The approach introduced by Miller (1983) and
developed by Covin and Slevin (1989) states that the three components of EO –
innovativeness, risk-taking and proactiveness – must be present for a firm to be considered
entrepreneurial (Miller, 1983). Lumpkin and Dess (1996) identified another two dimensions –
competitive aggressiveness and autonomy. For Lumpkin and Dess (1996), organizations
with EO can manifest traits from the five characteristics, but the presence of only one may
be sufficient for a new entry into the market to be successful.
Several recent publications applied Miller/Covin and Slevin (1989) scale. The scale is in
congruence with the definition of EO that recognizes the construct as a business attribute
identified through sustainable standards of entrepreneurial behavior (Miller, 2011).
Therefore, it is suggested that, when EO is linked to the Miller/Covin and Slevin (1989) scale,
the effect of EO on performance is greater than when the Lumpkin and Dess (1996) scale is
used. Thus:

H9. The EO-organizational performance relationship is stronger for EO measures based

on the Miller/Covin and Slevin (1989) scale than for the Lumpkin and Dess (1996)
scale.
Figure 1 shows the conceptual framework of this meta-analysis.

3. Method
3.1 Study identification process
To ensure the representativeness of the empirical studies selected, a search was first
performed in the electronic databases of ABI/INFORM Global (ProQuest), Electronic
Journals (EBSCO), Emerald Journals, JSTOR, ScienceDirect, SCOPUS and Web of Science.
Previous meta-analytic studies (Evanschitzky et al., 2012; Rubera & Kirca, 2012) searched
some of these databases, but we investigated all the above-mentioned in order to identify
and comprehend the most relevant studies. The keywords examined were “entrepreneurial
orientation”, “entrepreneurial proclivity”, “entrepreneurial posture”, “entrepreneurial
disposition” and “entrepreneurial intensity”. These terms, chosen as variations of the EO
RAUSP Mediators H2 ~ H3
55,2 - Learning orientation
- Innovativeness

Entrepreneurial H1 Organizational
orientation performance

148
H4 ~ H9
Methodological Moderators
- Manufacturing vs service firms
Figure 1. - Country: Western vs Asian countries
Conceptual - Objective vs subjective performance measures
framework for meta- - Single vs multi -item performance measures
- Cost-based vs revenue -based performance measures
analysis - EO scales

expressions commonly used in literature, were searched in the titles, abstracts and
keywords of papers published from 1983 to 2014.
In order to supplement the electronic search, we conducted an issue-by-issue search in
the most important journals, according to the ISI Web of Knowledge (2014) – Journal
Citation Reports, in management, strategy, innovation, marketing and entrepreneurship:
Journal of Management, Academy of Management Journal, Administrative Science
Quarterly, Journal of Marketing, Strategic Management Journal, Organization Science,
Journal of International Business Studies, Journal of Business Venturing, Journal of the
Academy of Marketing Science, Journal of Marketing Research, Entrepreneurship Theory
and Practice, Industrial Marketing Management, Management Science, International Journal
of Research in Marketing, Journal of Product Innovation Management, Journal of Business
Research and Journal of Small Business Management.
Next, we examined references and citations from relevant publications to locate
additional studies (Evanschitzky et al., 2012; Rauch et al., 2009). To obtain unpublished
work, we used Google Scholar and databases of theses and dissertations (e.g. The DART-
Europe E-theses Portal, ProQuest Dissertations and Theses, Open Access Theses and
Dissertations – OATD) (Matos, 2009; Moher, Liberati, Tetzlaff, & Altman, 2009).
After that, following the common approach of previous meta-analytic reviews to evaluate
the appropriateness of each study identified (Rosenbusch, Brinckmann, & Bausch, 2011;
Rubera & Kirca, 2012), we developed a few guiding rules to determine the studies that would
be retained for the meta-analysis. The studies needed to:

address the EO-performance relationship as a major topic of investigation;

measure both EO and performance at the organizational level; and

provide the Pearson’s correlation coefficient (or variants that can be converted) for
the EO-performance relationship.

Some potentially relevant manuscripts were not included in the meta-analysis because they
measured EO and/or performance at another level of analysis (ten studies); they did not
report the statistics needed to calculate the effect size (six studies); they investigated specific
relationships that could not be integrated with other studies (five studies); and, their results
were based on samples used in other publications from the data set (six studies). In this
regard, it was decided to use the sample only once in the calculations to avoid excessive
representation of specific samples (Rosenbusch et al., 2011).
These procedures resulted in 78 studies, with 80 independent samples and 149 effect sizes, Firm
with 137 of these for the EO-organizational performance relationship and 12 for the performance:
relationship between EO and the mediators. an updated
meta-analysis
3.2 Coding and operationalization of variables
A coding scheme was prepared with the information to be extracted from each paper. To
facilitate the analysis, the following data was coded: author(s), title, journal, publication date, 149
country and industry of the sample, sample size, descriptions of the respondents, scales and
dimensions used in the constructs from the model and statistical information of the
relationships studied.
About the EO measurement, it is worth noting that most articles operationalized the
construct with the Miller/Covin and Slevin (1989) scale (63 studies). The sub-dimensions
most commonly used were: innovativeness, risk-taking and proactiveness (60 studies);
innovativeness, risk-taking, proactiveness, competitive aggressiveness, and autonomy (8
studies); risk-taking and proactiveness (2 studies); and, other variations (8 studies)
(Calantone et al., 2010; Saeed et al., 2014).
The overall profile of the 78 studies selected according to their year of publication
can be seen in Figure 2. In fact, it is possible to infer that there is a greater
concentration of studies from 2013 (16 studies) and 2014 (9 studies). This demonstrates
a predominance of work conducted on the theme of EO and organizational
performance in a more recent period, reflecting the growing importance of the topic for
researchers.
Regarding the country factor, the database shows that the country most frequently
represented in the studies was the USA (20.0 per cent). Subsequently, approximately
12.5 per cent of the analyzed samples used China as background. The UK (6.3 per
cent), Holland (5.0 per cent) and Sweden (5.0 per cent) were also configurations
observed in a representative volume of cases. Considering the classifications of
Western vs Asian countries, a concentration of 75.0 per cent was found in Western
cultures.

Figure 2.
Evolution of scientific
production by year
RAUSP 3.3 Meta-analytic procedures
55,2 First, the statistics from the studies were converted into r correlation coefficients. 16 studies,
representing 28 effect sizes (out of a total of 78 and 149 respectively), did not provide the
metrics, producing standardized regression (beta) coefficients. Then, following Peterson and
Brown’s (2005) suggestions, the correlations were estimated from the beta coefficients, using
the formula: r = 0.98 b þ 0.05 g , where g is a variable equal to 1 when b is non-negative
150 and 0 when b is negative. No significant difference was found between studies that had
correlation coefficients and those where the coefficients were derived from the beta (mean
r = 0.249; mean converted r = 0.288; F = 0.976; p > 0.10).
Subsequently, the correlations were corrected for measurement error by dividing the
correlation coefficients by the product of the square root of the reliabilities of the two
constructs (e.g. EO and organizational performance) (Hunter & Schmidt, 2004). When a
study did not indicate its reliability, we computed the average reliability for that construct
across the sample and used it for correction purposes (Kirca et al., 2005; Saeed et al., 2014).
With Comprehensive Meta-Analysis®, the corrected correlations were transformed into
Fisher’s z-coefficients (Rubera & Kirca, 2012). To show the direct effect and confidence
intervals results, for example, these Fisher’s z-estimates were reconverted into revised
correlation coefficients, as proposed by Borenstein, Hedges, Higgins, and Rothstein (2009).
The correlations were then weighted by the sample size of each study for correction of
sampling error (Rosenbusch et al., 2011).
A 95 per cent confidence interval was calculated to examine the significance of the
relationship among the variables (the interval cannot include zero) (Borenstein et al., 2009;
Lipsey & Wilson, 2001). Once the significance was determined, the publication bias was
evaluated by calculating the fail-safe number (FSN), to indicate the number of studies with
non-significant results needed to reduce the cumulative effect size to a level of
nonsignificance (Lipsey & Wilson, 2001).
Homogeneity of the effect size distribution was tested by the Q statistics (Borenstein
et al., 2009; Lipsey & Wilson, 2001). If there was a result that contradicted the null
hypothesis of homogeneity of the relationship (e.g. EO and organizational performance), the
correlations would be considered heterogeneous, and this variation could be attributed to
potential moderators (Hunter & Schmidt, 2004).
To verify the existence of mediators, a multivariate analysis was conducted with
structural equations modeling (Hair, Black, Babin, Anderson, & Tatham, 2009). To examine
possible methodological moderations, a multiple regression model was developed (Card,
2012).
We performed the meta-analysis with the random-effects perspective. This approach,
unlike the fixed-effects model, does not assume that the studies included in the meta-
analysis are identical, i.e. present the same effect size (Borenstein et al., 2009). Therefore, the
random-effects approach for calculating the mean values is more reasonable, because it
produces more realistic estimates and indicates the real variability of the effect sizes
between studies (Borenstein et al., 2009; Saeed et al., 2014).

4. Results
4.1 Entrepreneurial orientation-performance relationship
Table I summarizes the meta-analytical results for the relationship between EO and
organizational performance.
A total of 137 effect sizes were considered, taken from 78 studies, with an accumulated
sample of 19,514 participants. The correlations recovered ranged from 0.330 to 0.690, with
a mean of 0.240. The results revealed a positive association between EO and organizational
performance (r = 0.299), which is consistent with the findings of Rauch et al. (2009). Table I Firm
also shows that there is a significant relationship among the constructs, since the 95 per cent performance:
confidence interval did not include zero.
The Q statistic produced a significant result (Q = 1,592.06; df = 136; p < 0.001). It
an updated
indicates a heterogeneous distribution of effect sizes and suggests that this variability may meta-analysis
be due to the existence of moderating variables. The fail-safe number was 684.
Consequently, new or unpublished studies not included in the meta-analysis did not threaten
the validity of the findings (Lipsey & Wilson, 2001). Therefore, H1 is supported.
151

4.2 Mediation analysis

Following Iacobucci (2010), structural equations modeling was used to test the mediations.
First, the model was estimated to verify the mediation of learning orientation. Then, a new
analysis with innovativeness was processed. It was decided to assess the two mediating
factors separately due to insufficient studies using the constructs at the same time. To
address these mediations in AMOS®, a correlation matrix was developed and used as input
(Kirca et al., 2005).
Table II shows the correlation matrix designed to investigate the direct and indirect
effects (through learning orientation) of EO on organizational performance. To generate the
matrix, the mean correlations among constructs were calculated, adjusted by sample size for
each pair of factors of the model (Viswesvaran & Ones, 1995).
The model was based on the Maximum Likelihood approach, with the use of
bootstrapping (Byrne, 2010). Bootstrapping enables the correction of problems associated
with non-normal data, and may increase the statistical power for identification of mediation
effects (Wood, Goodman, Beckmann, & Cook, 2008). The results of the mediation of learning
orientation are shown in Figure 3.
The results reveal a direct, positive and significant effect of EO on learning orientation
( b = 0.55, p < 0.01) and of learning orientation on performance ( b = 0.29, p < 0.01). As
predicted, there is a direct and positive impact of EO on performance ( b = 0.33, p < 0.01). In
addition, there is a significant indirect effect of EO on organizational performance through
learning orientation ( b = 0.16, p < 0.01). These findings provide support for H2.

Corrected 95% Confidence

E N Range of r Mean r Mean ra Interval Q Significance FSNb

Organizational
performance 137 19,514 0.330 0.690 0.240 0.299 0.262 0.335 1,592.06 0.000 684 Table I.
a b
Notes: Sample-size-weighted, reliability-corrected coefficient. Orwin’s method. The Rosenthal’s fail-safe Bivariate meta-
number was 87,187 analytical results

1 2 3

1. EO 0.828
2. Organizational performance 0.443 0.845
Table II.
3. Learning orientation 0.522 0.430 0.832
Meta-analytic
Notes: Italic values represent sample-size-weighted mean reliabilities. Other values reflect the average correlation matrix:
sample-size-weighted correlation coefficients learning orientation
RAUSP Based on the assumption that organizations oriented toward entrepreneurship are more
55,2 inclined to encourage a fertile learning atmosphere, as pointed out by Hakala (2013), it was
expected that this environment could have beneficial effects on performance. The EO-
performance link was also recapitulated herein, which corroborates the partial mediating of
learning orientation in this relationship.
Next, we created the correlation matrix summarized in Table III to examine the possible
152 mediation of innovativeness.
The results obtained are shown in Figure 4. The analysis reveals that the effects between
EO and innovativeness ( b = 0.55, p < 0.01), innovativeness and organizational performance
( b = 0.07, p < 0.01) and EO and performance ( b = 0.35, p < 0.01) are direct, positive and
significant. The indirect effect of EO on performance through innovativeness also had an
adequate level of significance ( b = 0.04, p < 0.01). Although it is worth noting the lower
magnitude of this effect.
Hence, H3 is supported. EO, through proactiveness and risk-taking, positively influences
innovativeness that, subsequently, has a positive impact on the development of advantages
that contribute to organizational performance (Rhee et al., 2010). Here, the partial mediation
of innovativeness can be seen, which coincides with Hult et al. (2004).

Learning orientation
0.55** 0.29**

Entrepreneurial 0.33 ** Organizational

orientation performance
Figure 3.
Indirect effect = 0.16**
Mediation results of
learning orientation
Note: **p < 0.01

1 2 3

1. EO 0.850
2. Organizational performance 0.429 0.846
Table III.
3. Innovativeness 0.583 0.300 0.858
Meta-analytic
correlation matrix: Notes: Italic values represent sample-size-weighted mean reliabilities. Other values reflect the average
innovativeness sample-size-weighted correlation coefficients

Innovativeness
0.55** 0.07**

Entrepreneurial 0.35** Organizational

orientation performance
Figure 4.
Indirect effect = 0.04**
Mediation results of
innovativeness
Note: **p < 0.01
4.3 Moderation analysis Firm
To examine the moderating effects of the sample and measurement characteristics of the performance:
studies, a multiple regression model was used. The moderators were coded and added into
the analysis as independent variables. The dependent variable was the z-score of the
an updated
reliability-corrected correlations between EO and organizational performance. The meta-analysis
regression model was processed with 100 effects from 63 studies, which provided
information on all the moderating and control variables (year of publication and journal
scope). Table IV reports the results. 153
The model was significant (F(8,91) = 6.067, p < 0.001) and the methodological moderators
are responsible for 34.8 per cent of the variation in the correlations between EO and
performance. The regression model is free of multicollinearity, since the maximum value of
the variance inflation factor (VIF) was 2.038, below the limit recommended by Hair et al.
(2009).
The results demonstrate that the strength of the EO-performance relationship does not
vary between manufacturing and service firms, not supporting H4 ( b = 0.082, p > 0.1).
This discovery has implications for the literature on strategic orientation because it goes
against the findings of Kirca et al. (2005), in which industry context (i.e. manufacturing and
service) is relevant when investigating the relationship between market orientation and
performance.
H5, which predicted that the impact of EO on performance would be stronger in a
Western country, was not supported ( b = 0.052, p > 0.1). Based on the Hofstede (1983)
classification, it is reasonable to suppose that the magnitude of the EO-performance
relationship can, in fact, be separately influenced by each dimension of the national culture
(power distance, uncertainty avoidance, individualism and masculinity).

Organizational performance
Methodological moderators b Sig.

Manufacturing vs service firms 0.082 0.393

Country: Western vs Asian countries 0.052 0.567
Objective vs subjective performance measures 0.013 0.906
Single vs multi-item performance measures 0.248 0.043
Cost-based vs revenue-based performance measures 0.221 0.040
EO scales 0.038 0.679
Year of publication 0.290 0.009
Journal scope 0.036 0.676
R2 0.348
F-statistic 6.067
Degrees of freedom 8, 91
Sig. 0.000
Max variance inflation factor (VIF) 2.038

Notes: The categorical moderator variables are coded as follows: manufacturing firm = 0, service
firm = 1, manufacturing and service firm = 2; Western countries = 0, Asian countries = 1; objective
performance measure = 0, subjective = 1, objective and subjective = 2; single item performance Table IV.
measure = 0, multi-item = 1; cost-based performance measure = 0, revenue-based = 1, cost and Meta-analytic
revenue-based measure = 2; EO measure based on the Miller/Covin and Slevin (1989) scale = 0, based
on the Lumpkin and Dess (1996) scale = 1. We control the effects of year of publication (1989- regression results on
1997 = 0, 1998-2006 = 1, 2007-2014 = 2) and journal scope (marketing = 0, management = 1, methodological
international business = 2). b = standardized beta coefficient; Sig. = significance moderators
RAUSP Likewise, the use of objective vs subjective performance measures did not affect the
55,2 relationship between EO and organizational performance ( b = 0.013, p > 0.1). Thus, H6 was
also not supported. This result corroborates previous strategic management papers that
found a positive and significant correlation between objective and subjective measures of
business performance (Perin & Sampaio, 1999; Venkatraman & Ramanujam, 1987).
Two methodological moderators, consistent with our expectations, demonstrated
154 significance. It was observed that the relationship between EO and performance is stronger
for multi-item performance measures ( b = 0.248, p < 0.05). This result provides support for
H7. It also strengthens Murphy et al. (1996) statement that measuring performance through
more than one item is more appropriate.
Additionally, the effect of EO on revenue-based performance measures is stronger than
those based on cost, which supports H8 ( b = 0.221, p <0.05). This finding confirms the
conclusions by Covin et al. (2006) that EO is a construct focused on the growth of the
company. Hence, it is more adequate using indicators that reflect this evolution, such as
sales growth and market share.
The results also reveal that the EO-performance relationship is not influenced by the EO
scale ( b = 0.038, p > 0.1). Therefore, we found no support for H9. This is consistent with
the meta-analysis by Rauch et al. (2009), which reported that the Covin and Slevin (1989)
scale produced a similar correlation to other EO scales for EO-performance relationship.
About the control variables, the model showed that only year of publication ( b = 0.290,
p < 0.01) significantly moderates the relationship between EO and performance. It was
identified that more recent publications present stronger effects.
In conclusion, the analysis from the multiple regression model demonstrate that the
variance in the EO-organizational performance relationship can be partially attributed to the
methodological differences associated with certain performance measurement
characteristics (number of items and revenue or cost-based). Table V includes an overview
of the findings.
In summary, the EO-performance relationship was supported (H1). The partial
mediations of learning orientation (H2) and innovativeness (H3) were also empirically

Hypotheses Findings

H1 The EO-organizational performance relationship is direct and positive Supported

H2 The EO-organizational performance relationship is partially mediated by learning Supported
orientation
H3 The EO-organizational performance relationship is partially mediated by Supported
innovativeness
H4 The EO-organizational performance relationship is stronger in manufacturing firms Not supported
than in service firms
H5 The EO-organizational performance relationship is stronger in Western than Asian Not supported
countries
H6 The EO-organizational performance relationship is stronger for subjective measures Not supported
of performance than for objective measures of performance
H7 The EO-organizational performance relationship is stronger for multi-item measures Supported
of performance than for single item measures of performance
H8 The EO-organizational performance relationship is stronger for revenue-based Supported
performance measures than for cost-based performance measures
Table V. H9 The EO-organizational performance relationship is stronger for EO measures based Not supported
Overview of the on the Miller/Covin and Slevin (1989) scale than for the Lumpkin and Dess (1996)
findings scale
supported. Importantly, the moderation analysis supported the effect of multi-item Firm
performance measures (H7) and revenue-based performance measures (H8). performance:
an updated
5. Discussion and conclusion
This study contributes to literature in several ways. First, the meta-analysis enabled to
meta-analysis
summarize and assess the current state of EO research. The paper provided an updated and
extended meta-analytic investigation on the subject, since previous works did not include
quantitative data from moderating or mediating variables. The results benefit both practice
155
and research, establishing empirical generalizations and identifying sources of
inconsistencies in the findings of the EO-performance relationship.
Second, the meta-analysis reported the magnitude of the effect between EO and
organizational performance. It was found that the corrected mean r for the direct association
between the two constructs is moderate in intensity (r = 0.299). It was shown that this effect
is positive and significant, consistent with a representative percentage of studies that claim
that firms strongly oriented by entrepreneurship achieve better performance than firms that
do not adopt EO (Rauch et al., 2009; Wiklund & Shepherd, 2003). Consequently, we
recommend executives to encourage and stimulate their employees to participate in
activities that involve creativity, proactivity, experimentation and propensity to assume
risks.
Our study also produced evidences about the mediators in the EO-performance
relationship by testing and confirming the partial mediation of learning orientation and
innovativeness. Although the indirect paths showed significance, it is notable the small
magnitude of these effects ( b = 0.16 for learning orientation and b = 0.04 for
innovativeness). It is reasonable to argue the probable influence of the approaches used for
the performance construct, known for its complex and multidimensional nature.
In addition, it can be assumed that there is a moderating effect, where the mediated
relationship between EO and organizational performance may vary among the levels of a
moderator. Wang (2008), for example, studied the moderating role of strategy types
(prospectors, analyzers, defenders, and reactors) in the EO, learning orientation and
performance relationship. Lin, Peng, and Kao (2008), on the other hand, examined the
moderation of organizational structures (formalization and decentralization) in the
innovativeness-performance relationship. Hence, the small size of the path coefficients may
be due to multiple moderators.
The multiple regression analysis provided robust evidence that the link between EO and
organizational performance is stronger for multi-item (vs single-item) performance
measures. The results also demonstrated that the impact of EO on revenue-based
performance measures is stronger than on cost-based measures. These findings contribute
to literature, emphasizing the importance of the appropriate definition and measurement of
performance, since distinct aspects of the construct, such as the number and diversity of
items, can influence its relationship with EO.
The moderator hypotheses of industry context (manufacturing vs service firms), national
culture (Western vs Asian countries), performance measure (objective vs subjective) and EO
measure (based on Miller/ Covin & Slevin, 1989 vs Lumpkin & Dess, 1996) were not
supported. From a practical perspective, this result shows the importance of EO for
performance. It means that the strength of the association is sustained in companies from
different segments and in different national regions.
In sum, this meta-analysis certified that EO positively and directly affects performance,
providing concrete and updated evidence, obtained from numerous studies, with
transparency and rigor in the application method. The article uses a synthesized model that
RAUSP includes mediators (learning orientation and innovativeness) along with moderating
55,2 variables. Therefore, the major contribution of the current research is the recognition of the
constructs that truly affect the EO-performance relationship.
For managers and policymakers, this study provides some relevant implications. The
explication of the routes through which EO influences performance deserves a few
comments. Specifically, our findings suggest that learning orientation and innovativeness
156 are mechanisms partially intervening in the relationship between EO and organizational
performance. This suggests that managers should stimulate firm’s values as commitment to
learning, open-mindedness, and shared vision (Wang, 2008). Similarly, managers should
also encourage the development of a culture that fosters openness to innovation, new
process, product, or new ideas within the organization (Hult et al., 2004).
Based on the evidence from this meta-analysis, policy makers should invest in programs
that effectively implement and increase the level of EO in firms, emphasizing this strategy
as a critical element to achieve superior performance (Su et al., 2015). In particular, we
recommend that policy makers facilitate access to financial assistance for organizations
involved in introducing new business ideas, also providing support for training activities,
and motivating employees to innovate and carrying out risky initiatives.

5.1 Limitations and further research directions

As with all meta-analytic reviews, a few limitations must be addressed. First, we could not
include in the database all studies and constructs in the EO literature, especially because of
the determined inclusion criteria. This paper attempted to avoid a publication bias.
Unfortunately, we had difficulties in accessing the gray literature, even without restricting
the identification process to peer-reviewed journal articles.
Our research provides some directions for future research. It might be productive to
assess the individual effects of the Hofstede’s (1983) dimensions of national culture (power
distance, uncertainty avoidance, individualism, and masculinity) in the EO-performance
relationship, to determine if the results vary based on the distinct factors. While uncertainty
avoidance and individualism may influence the magnitude of the EO-performance link in
one way, power distance and masculinity may perform another kind of impact (Efrat, 2014).
In conclusion, the article contributes to literature by demonstrating the importance of EO
to organizational performance with a meta-analysis, reporting the partially mediating
variables in this relationship, and seeking to explain the observed inconsistencies, also
examining methodological moderating variables. Furthermore, the present research may
instigate academics and practitioners to advance the knowledge about the topic, by
producing new theoretical and empirical insights.

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Corresponding author
Mauren do Couto Soares can be contacted at: mauren_soares@hotmail.com

Associate Editor: Adriana Takahashi

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