Gadjah Mada International Journal of Business - January-April, Vol. 25, No.

1, 2023

Gadjah Mada International Journal of Business

Vol. 25, No. 1 (January-April 2023): 28-49

The Relationship Between Export Market Orientation

and Firm Performance: A Meta-Analysis of Main and
Moderator Effects

Asmat-Nizam Abdul-Taliba, Siti Norhasmaedayu Mohd Zamania, Ili Salsabila Abd Razaka
a
Universiti Utara Malaysia, Malaysia

Abstract: Despite various studies into the relationship between performance and the ex-
port market orientation, researchers still argue that the current findings remain mixed
and inconclusive. In this study, the authors use meta-analytic techniques to examine the
relationship between the export market orientation and performance, and the impact of
firm-level, industry-level and country-level moderators using a total sample of 10,758
firms in 51 manuscripts from 19 countries. In particular, this study focuses on the nature
of incongruent findings across studies conducted in different contexts around the globe.
The results reveal that market orientation has a positive overall relationship with export-
ers’ revenue-based and profit-based performance. Moreover, the moderated regression
analysis results indicate that the type of construct (general versus export-specific) and
firm size moderate the relationship between the export market orientation and perfor-
mance. The results also reveal that market turbulence, competitive intensity, and techno-
logical turbulence are significant industry-level moderators of the relationship between
the market orientation and performance. This study contributes to the body of knowledge
by aggregating the empirical evidence from the past literature and providing conclusive
results that are beneficial for practitioners and researchers.

Keywords: export market orientation, performance outcomes, meta-analysis, environ-

ment, moderator
JEL Classification: L21, M31

28 *Corresponding author’s e-mail: asmat@uum.edu.my

ISSN: PRINT 1411-1128 | ONLINE 2338-7238
http://journal.ugm.ac.id/gamaijb
 Abdul-Talib et al

Introduction
Market orientation has always been considered to be an inevitable source of firms’
competitive advantage because it allows them to take efficient responsive action to cus-
tomers and market requirements (Kohli, Jaworski & Kumar, 1993; Slater & Narver, 1995).
Several studies using meta-analysis techniques affirm the significant contribution market
orientation makes in influencing various performance measures and these studies also
suggest that firms should enhance their market-oriented activities to achieve superior out-
comes (Cano, Carrillat, & Jaramillo, 2004; Ellis, 2007; Grinstein, 2008).
In the exporting context, export-specific market-oriented behavior offers a val-
uable perspective to explain the firms’ success with their export operations (Miocevic &
Crnjak-Karanovic, 2011). As a result, many scholars have focused on research investi-
gating the export market orientation (EMO, hereafter) and its performance outcomes.
Collectively, research indicates that the EMO is a critical factor for success in exporting
(Cadogan, Diamantopoulos, & Siguaw 2002; Murray, Gao, & Kotabe 2011).
The purpose of this study is to make conclusive findings based on previous studies
into the export market orientation and performance through a meta-analytic procedure
by responding to the following research questions:

RQ1: What is the relationship between market orientation and performance in the
export setting? RQ2: Are the firm-level moderators (types of measurement
and firm size) influencing the relationships between the market orientation
and performance?
RQ3: Are the industry-level moderators influencing the relationships between
market orientation and performance?
RQ4: Are the country-level moderators influencing the relationships between
market orientation and performance?

More specifically, our primary objective is to summarize and consolidate the no-
table findings and unique insights accumulated from a pool of studies in the export mar-
keting domain, to provide a comprehensive understanding of the relationship between
the EMO and performance. Moreover, our study expands the conceptual boundaries of
the EMO literature as we investigate several firm, industry, and country-level factors that
strengthen or weaken the relationship between the EMO and performance. Despite var-
ious studies into the relationship between the EMO and performance, researchers still
argue that the current findings remain mixed and inconclusive (Boso, Cadogan, & Story,
2012; Chung, 2012; Chung, Wang, & Huang, 2012). This study aims to explain some of
these contradictory and inconclusive results and advance our theoretical and empirical
understanding in this area. We structured this paper as follows: a theoretical framework
for the EMO and its consequences on performance, our methodology, results, discussion,
and implications.

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Conceptual Framework and Hypotheses

Conceptual Framework
The conceptual framework that drives our empirical approach is presented in Fig-
ure 1. Our primary objective is to quantitatively summarize and consolidate the extant
research on the relationship between the EMO and performance, and we only provide the
key arguments about the relationships that are shown in Figure 1. As these relationships
have already been explained in detail elsewhere (e.g., Cadogan, Diamantopoulos and De
Mortanges, 1999; Murray et al., 2011), we first briefly describe the foundation for the main
effects of EMO on various performance outcomes below. Then, we focus on our mod-
erator arguments following the prior meta-analytic reviews that investigated the market
orientation and performance relationship (e.g., Ellis 2007; Grinstein, 2008).

Figure 1: Conceptual Framework for Meta-Analysis

Previous literature on export market orientation suggests that market orientation

in an international context, has a direct effect on the exporters’ overall performance (e.g.,
Boso, Cadogan, & Story 2013; Chung, 2012; Murray et al., 2011), which is consistent with
studies conducted in the domestic context (Cadogan et al., 2001). Specifically, research
indicates that market orientation enhances the overall performance of exporters because
it enables firms to generate intelligence on the export markets’ needs and wants, thus al-
lowing them to respond appropriately (Cadogan et al., 2003; Kwon & Hu 2000; Murray et
al., 2011). By focusing on international customers’ needs, firms can deliver superior prod-
ucts and services and achieve superior performance by maintaining a global market-ori-
ented business culture (Knight, & Kim, 2009). Murray et al. (2011) posit that applying a
market-oriented focus in an export market enhances a firm’s performance by fulfilling its
customers’ requirements. This helps firms reduce foreign market uncertainty and address
the psychic distance between their home and export markets. This, in turn, allows them
to customize their marketing strategy rather than copying the marketing strategy used at

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home, which leads to better performance (Navarro-Garcia, Peris-Oritz, & Barrera-Barre-

ra, 2016).
Our study adopts a multifaceted character of performance constructs, consistent
with the strategic marketing literature (see Katsikeas, Morgan, Leonidou, & Hult (2016)
for a summary of performance assessment in marketing). Thus, our meta-analytic inves-
tigation develops specific hypotheses relating to the effects of EMO on financial and profit
performance. Specifically, our focus is on how EMO affects firms’ profitability and reve-
nue-based performance. We believe in the positive effect of market orientation on a firm’s
revenue-based and profit-based performance (cf. Rubera & Kirca 2012). Katsikeas et al.
(2016) found that the marketing literature’s most extensively used marketing performance
measures are what that study termed accounting indicators, comprising of profit and sales
revenue. The study revealed that out of 998 studies conducted between 1981 and 2014,
53.3% used profit-related performance measures, and 41.3% adopted revenue-related
measures. Taking this study into account, we focus on how EMO affects profitability and
revenue-based performance.
Many previous studies examined exporters’ general performance without look-
ing at any specific aspects (Katsikeas et al., 2016). However, more recent studies have of-
ten used a combination of separate indicators to investigate export performance, such as
through sales revenue-related, profit-related, new product development, new market en-
try, and market share indicators, among others. A combination of these indicators would
then be translated into the overall performance. For example, Cadogan et al. (2001) used
profit, market share, sales volume, and new market entry to assess export performance. So
did Tantong, Karande, Nair, and Singhapakdi (2010), who relied on profitability, export
growth, and sales volume to measure export performance. However, Cadogan, Sundqvist,
Puumalainen, and Salminen (2012) used only one aspect: the sales indicator.
The findings from these studies, including Cadogan et al. (2012), and Tantong et
al. (2010), in general, indicate that market orientation positively relates to export firms’
performance (e.g., Akyol & Akehurst, 2003; Murray, Gao, Kotabe, & Zhou 2007), because
firms practising market orientation activities are better positioned to understand their
market (Cadogan & Chui, 2004). However, Sousa, Martinez-Lopez and Coelho (2008)
argue that sales and profitability would have an opposite and detrimental effect on firms’
performance. Exporters may have increased their revenue but decreased profitability
when implementing market orientation activities, as they often require more resources.
While we have realized the possibility of this occurrence emerging in our study,
we believe that market-oriented firms would positively affect both profit-based and rev-
enue-based performance compared to non-market-oriented firms, because these firms
are better able to understand their global customers’ base to enhance their performance.
We believe in the positive impact of market orientation on a firm’s profit-based and reve-
nue-based performances. Therefore, we hypothesize that:
H1: Market orientation has a positive effect on the overall performance of export-
ers.

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H1 (a): Market orientation has a positive effect on revenue-based performance.

H1 (b): Market orientation has a positive effect on profit-based performance.

Moderators of EMO-Performance Relationship

Analysis of the research into this area reveals that most prior studies added mod-
erating variables to understand the impact of EMO and performance; in fact they added
so many that they outnumbered those assessing the direct relationship of the two. It is also
found that the EMO-performance link is not always positive and/or significant, depend-
ing on the type of moderators used in testing the relationship. These moderators can be
classified into firm-level moderators, country-level moderators, and industry-level mod-
erators. Based on the existing studies, it would be essential to verify any differences that
these moderators in question may have on the EMO-performance relationship.

Firm-level moderators
Oliveira et al. (2012) suggested four different levels at which export performance
could be measured in a firm: The general export function, export cohort, intra-firm ex-
port venture, and single export venture of the firm. They argued that the right perfor-
mance measure should be determined by the level at which the theory is tested. Some
studies employed general business performance to assess exporters’ success, whereas oth-
ers employed specific export performance in measuring exporters’ success. Chung (2012)
evaluated the relationship between EMO and performance by measuring the exporter’s
strategic (business) performance. Other studies employing general performance measures
include Ellis (2005; 2007; 2010), and Murray et al. (2011). There are also studies utilizing
specific export performance in assessing the relationship between EMO and performance
among exporters, including Dodd (2005), Lee (2008), Ngansathil (2001), and Sorensen
and Madsen (2012).
Studies have also shown that EMO is positively linked with performance when us-
ing general and specific performance measures. However, we are interested in finding out
if there is a moderating effect between the two measurements. Cavusgil and Zou (1994)
asserted that the effectiveness of a strategic marketing tactic would best be measured with-
in a specific business venture rather than assessed generally in a firm. As EMO is a type
of strategic marketing, we believe that it is stronger when measured using specific export
ventures yielding an export-specific type of performance measurement. Therefore;
H2: Market orientation has a stronger effect on the performance of exporters
when it is measured by an export-specific type of performance measurement.

Firm size can be used to turn firms’ capabilities and competencies into the pri-
mary source of their competitive advantage (Abdul-Talib and Abd-Razak, 2012, 2020;
Bodlaj and Čater, 2022; Wernerfelt, 1984). Firm size can be measured by different proxies:
number of employees, sales volume, sales to employees’ ratio, assets, investment level in
R&D. Thus, a firm’s size has a direct association with performance (Bonaccorsi, 1992). In

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research into the impact of offshore outsourcing on performance, Bertrand (2011) assert-
ed that firm size positively moderates export performance due to the more extensive base
of resources owned by larger firms. This is in line with Wolff and Pett’s (2000) finding that
bigger firms appear to be highly competitive in export markets because of the broadly
developed resource base that they own. Nonetheless, some studies such as Stoian, Rialp
and Rialp (2011) did not find that firm size positively influences export performance,
but rather it is the export commitment of the firm, which is aligned with Cadogan et al.
(2000), who found that the commitment to export is positively linked with the market
orientation. We believe that larger firms are endowed with wide resources that they can
tap into when venturing into a foreign market. Vast resources may allow a firm to commit
to an export market and to implement more market orientation activities that would en-
able it to perform better than the smaller firms with limited resources. Consequently, we
hypothesize that:
H3: The relationship between market orientation and export performance is
stronger in larger firms compared to smaller firms.

Industry-level moderators
The influence of moderators, such as market turbulence, competitive intensity, and
technological turbulence on the relationship between EMO and performance has often
been examined in the literature. In the context of market orientation literature, a common
approach to the external environment is related to the origin of environmental pressure
such as customer, competitor and technological pressures (Kohli and Jaworski 1993). The
customer environment includes all individuals or organizations that purchase an organ-
ization’s products. The competitor environment includes the organizations and products
that compete with the firm, and the competitive tactics used by the firm and its competi-
tors. The technological environment includes the development of new production meth-
ods or materials which lead to cost advantages or innovative products (Ashari, Yahanis,
Mohd-Zamani and Abdul-Talib 2018).
Within the sphere of EMO, studies into market turbulence show inconsistent re-
sults. Some early studies of the subject did not find any moderating effect of environmen-
tal turbulence (market turbulence, competitive intensity and technological turbulence) on
performance, including studies by Cadogan and Chui (2004) and Kirca et al. (2005).
Nevertheless, in recent studies, these moderators are found to have significant
moderating effects on EMO and the performance of exporters. In a different study, Cado-
gan, Cui, and Li (2003), for example, found that market dynamism strengthens the EMO
and export performance relationship up to a point before reversing the impact on the re-
lationship, while Boso et al. (2012) found that competitive intensity strengthens the EMO
and performance relationship. In a dynamic market, exporters tend to increase their EMO
activities to achieve the desired performance outcome.
Grinstein (2008), however, found that the relationship between market orientation
and innovation are strongly linked in a low technology turbulent environment. We argue

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that in low technology turbulent markets, market orientation activities are less significant
than in markets experiencing higher technology turbulence; this is due to the decreasing
need to continuously adapt to the changing technology in the market, resulting in a weak-
er association between EMO and performance (c.f. Yayla, Yeniyurt, Uslay and Cavusgil,
2018). Thus, we hypothesize that:
H4: Market turbulence, competitive intensity, and technological turbulence are
significant moderators of the relationship between market orientation and
the performance of exporters.

Country-level moderators
The discussion of country-level moderators within the EMO and performance
among exporters is regarded as important due to the nature of the existing studies on the
subject. While the number of such studies is increasing, these studies were conducted
using different backgrounds of country and economy. Some previous studies have been
undertaken in developing nations such as Croatia, Korea, New Zealand, and Thailand,
whereas others were conducted in advanced economies, including the US, the UK, the
Netherlands, and Finland. It is interesting to explore whether this country-level modera-
tor affects the relationship between EMO and performance among the exporters.
Developing countries are generally characterized by rapid economic development,
high growth rates, and strong market demand. As opposed to a more developed market,
competition is minimal due to the increased uncertainty in doing business. Given such
circumstances, firms could choose not to focus on being market-oriented (Kohli & Jawor-
ski 1990) as the return from their investment in market-oriented activities may be limited.
On the other hand, in a developed market, competition is intense, and the market is rel-
atively stable; hence, firms are more likely to focus on customers rather than competitors
(Ellis, 2006) and manage their resources to enhance their performance. Ellis (2005) sug-
gested that the relationship between market orientation and performance was stronger in
research conducted in advanced nations compared to developing economies, and in large-
sized markets compared to small-sized ones. That study asserted that as a market matures,
market orientation activities become more significant with less market turbulence and
increasing competitive intensity. This is also possible as mature economies, as opposed
to developing economies, often provide firms with ample resources and infrastructure
to become more market-oriented. Consequently, a stronger relationship between market
orientation and the performance of exporters is more visible within mature economies
than in developing ones. Thus:
H5: Market orientation has a stronger effect on the performance of exporters when
it is measured in advanced economies, rather than in developing economies.

Methodology
Eligibility Criteria
The results obtained from identified independent studies were generated to meas-

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ure the association among the constructs and to correct the measurement and sampling
errors (Cano et al., 2004; Kirca & Yaprak, 2010). Each study comprised independent ob-
servations’ effect sizes. Meta-analysis offers a powerful technique to make empirical gener-
alizations within marketing fields (Ellis 2007). Meta-analysis also offers superior analysis
than other conventional synthesis analyses, such as a systematic literature review because
it includes statistical analyses to measure the relationships that are unavailable through
other methods. Additionally, through meta-analysis, study outcomes can be compared
across different contextual characteristics (Ellis 2006). Our study comprised papers that
included correlations between the constructs of interests (r—Pearson’s coefficient) (or r—
transformed from t, F, or χ2), the constructs’ reliability, and the sample size (Hunter &
Schmidt 1990).
The inclusion samples in this research were built on two criteria. First, we only
included studies that reported a correlation (r—Pearson’s coefficient or equivalent r—
transformed from t, F, or χ2), reliabilities, and a sample size for each of the constructs
(King et al., 2004). Second, only articles that measured (i) export market orientation or
(ii) market orientation in the export setting at the organizational level were included in the
study. Studies that had divergent objectives were excluded (King et al., 2004). Published
and unpublished studies ranging from 1996 to 2019, available in English that reported an
effect size between the export market orientation and export performance (and market
orientation to performance in an export setting) satisfied the criteria and were eligible for
inclusion.

Literature Search
A comprehensive search was performed that included manually searched online
databases, which included ABI/Inform, LEXIS/NEXIS, EMERALD, JSTOR, and IDEAL.
We used the following keywords: export market orientation, marketing concept, export
performance, MARKOR, and MKTOR. Wildcard (e.g., *, ?) was used in the search to tap
for multiple variations of possible key terms. Since Cadogan’s (1996) manuscript was the
first one published on the export market orientation, we also searched for papers that cited
this study. We examined all the references in articles about the export market orientation
for additional studies.
Dissertations published in the English language were located using various on-
line databases. Google Scholar was used to identify manuscripts on the internet. Lastly, a
manual search of key marketing journals was performed, including Journal of Marketing,
Journal of Marketing Research, Journal of the Academy of Marketing Science, Interna-
tional Marketing Review, and Journal of International Marketing. To assure mutual exclu-
sivity, author(s) with multiple papers were analyzed. When duplicate samples were found,
the article that reported the richer statistical information was selected, while the other
samples were excluded. Several studies were excluded due to at least one of the following
reasons: (1) Their results did not provide the direct link between (export) market ori-
entation and performance, and (2) the relationships under investigations were uniquely

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different from the present study and thus may not be related to this study.

Coding Schema
In developing the final database, we employed established meta-analysis proce-
dures used in marketing on the topic of the market orientation, such as by Cano et al.
(2004). First, a coding form was created to extract specific information from each study
(Grewal, Puccinelli, and Monroe, 2018; Lipsey and Wilson, 2001). The literature search-
es identified 51 potential studies, and three researchers coded all of these studies inde-
pendently. Whenever there were inconsistencies in the coding, they were fixed with fur-
ther analysis until a consensus was reached.

Effect Size: Correcting for Measurement Error and Sampling Errors

A correlation based on large studies provides higher precision because they have
smaller sampling errors (Hunter and Schmidt, 1990). Based on the protocols suggested by
Lipsey and Wilson (2001), the measurement error of the effect sizes was corrected before
converting it using Fisher’s Zr-transform. We corrected the measurement error by follow-
ing Hunter and Schmidt’s (1990) and Geyskens, Steenkamp, and Kumar’s (1998).

Confidence Intervals and Homogeneity Analysis

A confidence interval is present and significant when the effect size does not in-
clude zero. Whenever the mean effect size was significant, we calculated a fail-safe N. This
was done to estimate the number of non-significant and unavailable studies needed to
bring the cumulative effect size to a non-significant value, or as Rosenthal (1994) termed
it, the “file-drawer problem.” Similar to Grewel et al. (1997), we used a level of 0.05 as “just
significant.” The homogeneity of the effect size’s distribution was measured using Q-statis-
tics (Lipsey & Wilson (2001).

Control Variables
We included several study characteristics and contextual variables as control var-
iables because they had been shown to affect the relationship between market orientation
and performance in previous meta-analytic reviews (e.g., Cano et al., 2004; Ellis, 2006).
We examined the effects of market orientation measures (MARKOR vs. MKTOR), per-
formance measures (objective vs. subjective), and types of industry (multiple vs. single) as
control variables. The MARKOR scale was developed by Kohli et al. (1993) and consisted
of 32 items while MKTOR was advanced by Narver and Slater (1990), which comprised
21 items Gauzente (1999) reaffirmed that the use of any one of these scales would signif-
icantly illustrate a different theoretical orientation of the research. Thus, based on this
argument, the effects of the market orientation scale were controlled.
We also included subjective and objective performance measures as control var-
iables because prior research showed that they were critical variables that affected the
results in market orientation studies (Kirca et al., 2005). Subjective measures referred to a

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performance appraisal based on a respondent’s perception or self-reporting. In contrast,

objective measures referred to a firm’s financial data, such as return on investment ROI,
sales, profits, and market share (Ellis, 2006). Katsikeas et al. (2000) found that objective
assessments, although reliable, showed less feasibility for researchers because of the lim-
ited availability of companies’ data. Thus, many studies investigating market orientation
resorted to only using subjective measures across countries (Harris, 2001; Dawes, 1999).
Finally, we also included a control variable to account for industry-level effects, namely
samples from a single industry or multiple industries.

Results
We identified 51 manuscripts from 40 journal publications, five dissertations, one
book chapter, and five proceedings from the literature search. Eleven studies were elimi-
nated for not fulfilling the eligibility requirements and thus were removed. The final anal-
ysis left us with 40 studies consist of 33 manuscripts, three proceedings, and one book
chapter providing 70 useable effect sizes.
The total samples from 51 manuscripts in this study equalled 10,758 with a mean
sample size of 236 (sizes range from 48 to 783). There were 19 countries covered that
included Belgium, Croatia, the Netherlands, Finland, and Ghana. (Please refer to Table
1 for a complete list). The respondents were primarily senior executives, specifically the
managers responsible for export operations.

Table 1. Study-Level Coding

PERFORMANCE MEAS-
EMO MEASURE
URE

SAMPLE
STUDY COUNTRY IND. ES
SIZE EMO KJ (0) EP (0) Multi vs
(0) vs vs NS vs OP Scale Single
MO (1) (1) (1) item

Abdul-Talib and Cado- 225 UK M 0.256 0 9 1 X M

gan (2007)
Akyol and Akchurst 103 Turkey S 0.7516 0 9 0 X X
(2003)
Armario, Ruiz and 112 Spain M 0.74 1 0 0 S M
Armario (2008)
Asaad, Melewar and 63 UK S 0.6102 0 9 0 S M
Cohen (2015)
Beaujanot, Lockshin, 77 Australia S 0.452 1 1 1 S M
and Quester (2006)
Boso, Cadogan and 164 Ghana M 0.27 0 9 0 S M
Story (2012)
Boso, Cadogan and 212 UK M 0.29 0 9 0 S M
Story (2013)
Breman and Tevfik 105 Netherland M 0.42 1 0 1 S M
(2000)
Cadogan (1996) 198 UK M 0.3015 0 0 0 X M
Cadogan and Diaman- 48 UK M 0.486 1 0, 1 0 X M
topoulus (1998)

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Cadogan, Diaman- 206 USA M 0.8319 0 9 1 X M

topoulus andSiguaw
(2002)a
Cadogan, Diaman- 198 UK M 0.4572 0 9 0 X M
topoulus and Siguaw
206 USA 0.2683
(1998)
Cadogan, Diaman- 198 UK M 0.27 0 9 0 X X
topolous and De
103 Netherland 0.348
Mortanges (1999)
Cadogan, Cui, and Li 137 Hong Kong M 0.0944 0 9 0 X X
(2003)
Cadogan and Cui 209 China M 0.4 0 9 0 X M
(2004)
Cadogan et al. (2002) 783 Finland M 0.33 0 9 0 S M
Cadogan et al. (2002)b 783 Finland M 0.4424 0 9 0 X M
Cadogan, Kuivalanen 783 Finland M 0.38 0 9 0 S M
and Sundqvist (2009)
Chung (2012) 100 New Zealand M 0.271 0 9 0 S M
Dodd (2005) 115 Australia M 0.238 0 9 1 X M
Ellis (2007) 345 Taiwan M 0.158 1 1 0 X X
Ellis (2005) 57 China M 0.245 1 1 1 S M
Ellis (2010) 155 Hong Kong M 0.2 1 1 1 S X
French (2006) 92 USA M 0.61 0 9 0 S M
French and Cadogan 292 New Zealand M 0.202 0 9 0 S M
(2012)
Julian et al. (2014) 109 Indonesia M 0.5177 1 1 0 n.a n.a
Lin et al. (2014) 232 Taiwan M 0.2743 0 9 0 n.a M
Kwon and Hu (2000) 341 Korea M 0.5454 1 0 0 O M
Lee (2008) 132 Taiwan S 0.831 0 9 1 S M
Miocevic and Crn- 125 Croatia M 0.407 0 9 0 S M
jak-Karanovic, (2011)
Murray, Gao, and 491 China M 0.0556 0 9 0 S M
Kotabe (2011)
Murray et al. (2007) 491 China M 0.3137 0 9 0 S M
Naidoo (2010) 407 UK S 0.261 0 9 0 S M
Navarro-García et al. 212 Spain M 0.1 0 9 0 M M
(2014)
Ngansathil (2001) 147 Thailand M 0.0583 0 1 0 X X
Rose and Shoham 124 Israel M 0.2155 1 0 1 X M
(2002)
135 Spain M -0.0217 1 0 1 S M
Ripolles et al. (2008)
72 Belgium -0.0491
Sørensen and Koed 249 Denmark M 0.287 1 1 0 S S
Madsen (2012)
Sundqvist et al. (2000) 783 Finland M 0.3308 0 9 0 X M
Tantong et al. (2010) 252 Thailand M 0.2788 1 0 0 S M
a
Industry: M= Multiple, S= Single
b
MO measure: 0= Export MO scale, 1= General MO scale
c
MO measure: 0= MARKOR , 1= MKTOR
d
Performance measure: 0= Export performance, 1= General performance
e
Performance measure: 0= Objective scale, X= Mixed scale, S= Subjective scale
f
Performance measure: S=Single item, M= Multiple item
g
n.r= not related, since the study used EMO scale by Cadogan (1996)
h
n.a= not available or not reported by the author

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EMO- Performance Relationship

The results in Table 2 show that the mean (corrected) effect size of the 70 correla-
tions was 0.23 (CI = 0.21 – 0.25). We could conclude that the mean effect size was statisti-
cally significant as the associated confidence level was positive. Therefore, we found sup-
port for H1 that market orientations had a positive influence on exporters’ performance.
The results also indicated a significant, positive relationship between market orientation
and revenue-based performance (r = 0.18, CL = 0.14-0.21) and the profit-based perfor-
mance of the exporters (r = 0.11, CL = 0.04-0.19). Thus, both H1(a) and H1(b) were also
significant. The findings suggested that the variation in firm performance that was directly
linked to market orientation was less than 7% (Ellis, 2006).

Table 2. Overview of Consequences of Export Market Orientation

Total Corrected
Standard Availability
Performance No of effects sample mean r (Mean Lower CI Upper CL
Error (SEzr) bias
size Eszrcorr)
Overall export
27 5,164 0.302359334 0.013919802 0.275411228 0.55372581 5.047186672
performance
Revenue-based
13 3,395 0.177906765 0.01717007 0.144104 0.21171 2.55813531
performance
Profit-based per-
4 677 0.111714253 0.03851856 0.035709 0.18772 1.23428507
formance

The Q-statistic was less than the 0.05 critical value for χ2 of 89.39 with 69 df, sug-
gesting that the hypothesis of homogeneity could not be rejected at α = 0.5. The result
indicated that the variance in the effect sizes from the sample size was not demonstrably
higher than what it could be as the result of a sampling error alone. Thus, we probed fur-
ther to check the impact of sampling and the construct moderators on the relationships
between the EMO and performance. The results showed that the availability bias was high;
suggesting that unpublished studies that were not identified in our study did not pose va-
lidity threats to our research findings (see Lipsey & Wilson, 2001).

Moderators of EMO- Performance Relationship

Although the result from the homogeneity test showed that the sample effect size
variance was not greater than from the derived sampling error, we decided to test for
moderating factors. We followed the procedures outlined by Hunter and Schmidt (1990)
to assess the influence of the hypothesized moderators; so a dummy-variable regression
was used. The regression model was as follows:
ZEMO,P = β₀ + β1X1 + β₂X2 + β3X3 + β4X4+ β5X5 + β6X6 +εI,
where ZEMO,P was the z-transformed value of the corrected correlation between the ex-
port orientation and performance, βs were parameter estimates, and Xi were the following
categorical
variables (with the reference level [the level dummy-coded “0”] presented first for each
Xi):

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Gadjah Mada International Journal of Business - January-April, Vol. 25, No. 1, 2023

X1 = Export specific versus general,

X2 = Small versus large firm,
X3 = Advanced versus developing economy,
X4 = MARKOR versus MKTOR,
X5 = Objective versus subjective performance measures,
X6 = Multiple versus single industry.

Regression result
The result is shown in Table 3, and the proposed model was significant (F(13, 69)
= 1.79, p <0.1) with both the hypothesized moderators and control variables providing
10.2% of the variance in the export market orientationperformance correlations. More-
over, the regression model was free of multicollinearity (max variance inflation factor =
8.71).

Table 3. Results of Regression Analysis

Moderator Variables Hypotheses β (t-value)
Specific vs. General Export Measure H2 0.114(1.818)**
Small vs Large firm H3 -0.223(-1.999)*
Developing vs Advanced economic H5 0.070(1.221)
Control Variables
MARKOR vs. MKTOR - 0.285 (2.752)*
Objective vs. Subjective performance - 0.187(2.402)*
Single vs. Multiple industries - -0.026(-.341)

F-Statistic 1.791**
Degree of Freedom 13. 69
R2 0.102
* Significant at 0.1
**Significant at 0.05

Firm-level Moderators
General versus Specific Export measure: Based on the results, the general versus ex-
port specific performance measures did influence the strength of the relationship between
market orientation and performance among the exporters. The market orientation had
a more substantial effect on the performance of exporters when it was measured by the
general type of performance measurement (β = 0.114, t-value = 1.818). Thus, the results
did not support H2.
Large versus Small firm: The results also revealed that firm size did affect the rela-
tionship between market orientation and performance. The link between market orien-
tation and the measurement of export performance was stronger in smaller firms than
larger firms. Thus, H3 was not supported.

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 Abdul-Talib et al

Industry-level Moderators
A number of effects did not include information of the substantive moderators;
thus, we used vote-counting procedures to categorize these studies based on the signifi-
cance of the results (see Bushman and Wang, 1994). Then we ran the “sign test” (Bushman
and Wang, 1994), which tested the hypothesis that the effect sizes from a collection of k
independent studies are all zero (null hypothesis, Ho: π = .5). This procedure investigates
the probability of obtaining results that confirm the proposed hypotheses greater than
.5 (alternative hypothesis, HA: π > .5). Then, we classified the studies to check for the
moderators, and they fell into three categories: “supportive,” “non-significant effects,” and
“opposite.” The result is shown in Table 4. Using the counted studies that confirmed the
hypotheses, we then measured an estimate of π from the binomial distribution.

Table 4. Industry-level Moderators and the Market

Orientation–Performance Relationship
Moderator Supportive Opposite Non-significant

Cadogan et al. (2009) Cadogan et al.(2002)

French Cadogan (2012) Kwon and Hu (2000)
Boso et al. (2012) Ngansathil (2001)
Market turbulence
Abdul-Talib and Cadogan Rose and Shoham (2002)
(2007)
Ngansathil (2001)
Rose and Shoham (2002)
Cadogan et al. (2003)
Competitive intensity Cadogan et al. (2002) Ngansathil (2001)
Sundqvist et al. (2000) Rose and Shoham (2002)
Cadogan et al. (2002b) Kwon and Hu (2000)
Cadogan et al. (2003) Ngansathil (2001)
Technological Rose and Shoham (2002)
turbulence Sundqvist et al. (2000)
Cadogan et al. (2002b)

Five out of the nine studies found that market turbulence moderated the market
orientation–performance relationship, and this relationship was strengthened in turbu-
lent market conditions. The sign test value of π was p = 0.56 and corresponded to 0.25
cumulative probability. Thus, the results suggested that there was evidence that market
turbulence moderated the relationship between market orientation and performance.
Furthermore, the sign tests also provided evidence about the competitive intensity and
technological turbulence moderators on the market orientation-performance link with a
cumulative probability of 0.36 and 0.03, respectively. Consequently, H4 was supported.

Country-level Moderators
The results in Table 3 reveal that economic development had no significant effect

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on the relationship between market orientation and performance among exporters. Thus,
based on the study findings, H5 was rejected.

Control Variables
Further analysis and results (Table 3) showed that market orientation had a signif-
icantly different effect on exporters’ performance when measured by the different scales
of MARKOR or MKTOR (β = 0.285, t-value = 2.752). This conclusion might be against
the findings in Langerak (2003), Rojas-Méndez and Rod (2013), Shoham, Rose and Kropp
(2005), but it supports Cano et al. (2004) and Ellis (2006). Our findings also revealed the
significant impact of different types of subjective and objective performance measures (β
= 0.187, t-value = 2.402) on the market orientation-performance association. However,
results from the regression analysis showed that the relationship between the export mar-
ket’s orientation and performance was indifferent across industry types.

Discussion and Implications

In this study, we collected the findings from previous research about the EMO-per-
formance relationship among exporters and ran a meta-analysis focusing on the relation-
ship itself and a number of moderating variables, including firm-level moderators, in-
dustry-level moderators, and country-level moderators. Findings from the analysis had
substantial implications for the current body of knowledge and the managerial front, in
relation to the relationship between the EMO and performance.
Analysis of the impact of the construct, the sample, and substantive moderators
produced significant findings for discussion. This study can corroborate that market ori-
entation has a positive and significant effect on exporters’ financial, strategic, and prod-
uct performance. Our findings within the firm-level moderators confirm that the general
construct yields a stronger relationship between the EMO and exporters’ performance.
Contrary to expectations, this study revealed that the relationship between the market ori-
entation and export performance is stronger in smaller firms than larger firms. This might
be attributed to the higher export commitment found by Cadogan et al. (1999) and Stoian
et al. (2011), which could probably be found among smaller firms. Arguably, smaller firms
might have limited resources, but they might also have a higher export commitment that
warrants investment in their export activities. Hence, the stronger market orientation and
performance relationship was found among them, compared to their larger counterparts.
The industry-level moderators comprised of market turbulence, technological turbulence,
and competitive intensity yielded remarkable findings too. We found that market turbu-
lence, technological turbulence, and competitive intensity are significant moderators of
the relationship between the EMO and performance. A strong relationship is established
between market orientation and performance in a turbulent market, or environment, with
the presence of technological turbulence and competitive intensity. In other words, the
relationship between EMO and the performance of exporters is stronger in a highly tur-
bulent market environment, a highly turbulent technological environment, and a highly
competitive environment. Country-level moderators in the analysis of economic devel-
opment are found to have significant impacts on the relationship between the EMO and
performance.
The analysis of the control variables shows that the use of the MARKOR or MK-

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TOR scale to measure EMO has a significant impact on the relationship. The use of the
MKTOR scale yields a stronger relationship between the EMO and the performance of
the exporters. Additionally, the use of a subjective performance measure strengthens the
relationship between market orientation and performance. However, we found that the
type of industry has no significant difference in the relationship between EMO and the
performance of exporters. Therefore, future studies should consider the types of measures
for the EMO and performance so that the results will not lead to unnecessary bias in a
general/export setting.

Limitation and Futher Research

There are three limitations to this study. First, although the fail-safe N statistic
suggests there is no issue with file drawer cases, selection bias could still be a limitation of
the study. Although we followed the protocols offered by scholars to reduce selection bias,
potentially there may be cases where we might exclude relevant papers. Second, our re-
sults suggest market orientation only accounts for about 23% of the variance, thus leaving
a significant amount of the variance in business performance unaccounted for. Third, our
research was bound to a limited sample size due to limited coding ability. Therefore, de-
spite the large studies covered, this study may not be entirely representative of the stream.
We encourage further studies in the future, focusing on perhaps more specific variables
within the area of the relationships between EMO and performance among exporters.
We would also encourage studies focusing on the antecedents to EMO to be analyzed by
future research.

Acknowledgement
Authors acknowledge the Ministry of Higher Education (MOHE) for funding under the
Fundamental Research Grant Scheme (FRGS) #FRGS/1/2020/SS01/UUM/02/5

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