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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.18 No.3 pp.383-394

The Impact of Strategic Orientation on Performance of Retail SMEs by Structural Equation Model Evaluations

Mohd Noor Mohd Shariff*, Jauriyah Shamsuddin, Mohd Nizam Abdul Kadir
School of Business Management, Universiti Utara Malaysia, Malaysia
OYA Graduate Business School, Universiti Utara Malaysia, Malaysia
Corresponding Author, E-mail:
May 28, 2019 June 14, 2019 June 18, 2019


Overcoming challenging circumstances in a dynamic environment requires markets to have superior performance compared to their rivals. In order to achieve superior performance, this study analyzed two strategic orientation variables which might influence a retail firm performance - market orientation (MO) and entrepreneurial orientation (EO). It also examined the effect of Volatile Environment (VE) as a moderator for both direct affiliations towards the performance. Quantitative data were gathered from the 152 owner-managers of retail firms within the scope of Small and medium-sized enterprises (SMEs) in Malaysia. Dataset were processed for validity and reliability using SPSS and the multivariate regression performed using Smart PLS software. Four hypotheses were postulated and tested through structural equation model evaluations. The results indicated VE strongly moderated the relationship between MO and firm performance (FP). However, there was no significant moderating effect on the relationship between EO and performance. For direct effect relationship, the results revealed that MO had positive significant influence on FP. In contrast, EO had no significant effect on the retail firm performance.



    One of the most important SMEs’ subsectors is retail. Despite of its major contribution to a nation’s economy in terms of absorbing huge jobs offering and gross national income, the scope of this subsector is lacking in determining factors that contribute to its performance (Hamister, 2012;Kajalo and Lindblom, 2015). There are extensive studies highlighting SMEs performance as the centrestage, however they are mostly highlighting major sectors such as manufacturing or services (Grimmer et al., 2015;Martin and Rialp, 2013). As this subsector significantly contributes about USD20 trillion to the global SMEs GDP income, studies on determinants and comprehensive framework of retail firms performance are deemed crucial and sought after (Research and Markets, 2017;Kajalo and Lindblom, 2015;Sears, 2018).

    Market orientation (MO) and entrepreneurial orientation (EO) are two strategic orientation constructs that have been widely discussed in several SME sectors various perspectives. While MO is focusing on market activities by creating superior value of product or services in order to attract and retain customers (Narver and Slater, 1990;Kazakov, 2016), EO is most widely-accepted determinant of firm-level performance which denotes the strategic process used by organizations in order to implement entrepreneurial actions and identify new opportunities (Lumpkin and Dess, 1996;Gupta and Batra, 2015;Abishov et al., 2018).

    However, the external environment surrounding the retail businesses may posit different implications to the firms. The firms may operate in different environment volatility namely benign, moderate and high volatile, the determinants and capability in adapting to the environments may vary from one sector (or subsector) to another (Asad et al., 2018;Wiklund and Sherperd, 2005).

    This study focused on two strategic orientation variables used in several SME sectors, attempting to determine their influence towards retail firm performance. The impact of VE was also investigated in order to identify its role in moderating both affiliations. Hence, this paper aimed to determine the effect of market orientation and entrepreneurial orientation towards retail firm performance with moderating effect of VE; which is anticipated to enrich body of knowledge in entrepreneurship.


    2.1 Literature Review

    Global retail subsector has seen highly volatile trend in the past three years (2015 till 2017) but it was not exhibiting variation from one country to another. 2015 to 2017 were considered the worst pitfall of global retail sector but economic activity was projected to pick up pace by end of 2018, especially in emerging market and developing economies. Except China, the large economies such as the United States, India, Brazil and Mexico expect the margin would worsen whereby financial conditions are generally tight for business operations (World Economic Outlook, 2017). A phenomenon known as “retailpocalypse” resulted ordinarily due to global recession and worsen by several factors such as low spending power, changing of customer preferences, competition by ecommerce providers, higher rental faced by retailers, low exchange rate, staff cost increment, higher fuel and merchandize prices (Peterson, 2017;, 2017;Peres et al., 2018).

    For Malaysia scenario, the introduction of GST in April 2015 has softened retailers’ sales and dampened consumer spending confidence. Industry players have considered the retail subsectors in Malaysia facing the vibrant, uncertain and highly VE since then and years ahead (Mahalingam, 2017). As a consequence, few retailers have exercised job cuts especially the supermarket chains and small retailers have closed down their underperforming outlets (Davies and Butler, 2018). The future of retailers may depend on their internal strategic skills such as EO and MO, and their capability to adapt to unfriendly and rapid changes environment (Leung and Chan, 2016;Al-Nuiami et al., 2014).

    There are two approaches of MO. Slater and Narver (1995) argued that both approaches, behavioral by Kohli and Jaworski (1990) and cultural by Narver and Slater (1990) are market-driven with the intention of creating superior value for firms. Both models emphasize the developing needs of customers and responsiveness through innovating services or products based on market feedback and information (Matikainen et al., 2016). Previous studies indicated that MO influences the objective of achieving high organizational performance in various SMEs and businesses (Rogo et al., 2017;Troung, 2014;Gruber-Muecke and Hofer, 2015;Chin et al., 2013;Fang et al., 2014;Kazemian et al., 2016;Kamboj and Rahman, 2017;Mahmoud et al., 2016;Newman et al., 2016;Green et al., 2015).

    Additionally, interests on the EO and performance studies have been increasing. Previous studies have examined direct relationship and inclusive role of indirect variables (mediator or moderator) (Martin and Rialp, 2013;Ahmad and Ghani, 2013;Aliyu et al., 2015;Kurtulmuş and Warner, 2015;Amin et al., 2016). From a different perspective, Morgan et al. (2015) analysed 206 mid-sized Swedish manufacturing firms and found that the EO has positive effect on performance, but when the firms implemented MO simultaneously, the effect has reduced compared to the direct link of EO-performance.

    An underpinning theory utilized for this study is Dynamic Capabilities View (DCV), an extension of Resource Based View (RBV) theory. It is a contemporary theory highlighting strategic management literature for the past decade (Vogel and Güttel, 2013). DCV is a “firmbased performance-focuses theory” (Arend and Bromley, 2009) and has acquired mainstream attention since Teece et al.’s (1997) article publication. This theory addresses the capacity of firms to create, integrate and reconfigure internal and external resources, competencies and capabilities to adapt to rapid changes of environment. Hence, the capability of firms’ management in redeploying their resources may differentiate the performance of one firm compared to others (Eisenhardt and Martin, 2000;Morgan et al., 2009).

    This study also utilized VE as its moderator. According to Sekaran (2004), a moderator might modify the pattern of an affiliation between a predictor and dependent variable. The moderator of the independent-dependent relationship might trigger two effects namely it may strengthen the relationship, or it may weaken the form of relationship (Rana et al., 2016). Various type of environmental volatility is summarized as follows: Table 1


    3.1 Research Method

    Quantitative method was applied for this study in which data collected through mail questionnaires which were edited, coded and categorized before being entered into software for analysis. The study utilized Statistical Package for the Social Sciences (SPSS) version 23.0 and Smart PLS version 3.2.6 for data analysis. SPSS was used for “data screening and cleaning” until data were useable for analysis; as well as for checking the normality of data, multicollinearity and measurement error tests. The checking of data was necessary due to the sensitivity of input data in SEM and in ensuring the effectiveness of the multivariate regression analysis later (Hair Jr et al., 2014). After that, path modelling using Partial Least Square- Structural Equation Model (PLS-SEM) was executed for the remaining analysis process.

    The seven-point Likert scale was used to measure dichotomous responses ranging from strongly disagree to strongly agree for independent, moderator and dependent variables. All the measures were adapted from the previous studies. The measures of FP were derived from the subjective tangible and intangible elements namely satisfaction with financial and nonfinancial success which includes profitability, market share, sales growth, customer satisfaction and customer growth. These elements were chosen because they are main reflective of performance in the mainstream studies (Suliyanto and Rahab, 2012;Gruber-Muecke and Hofer, 2015). The high VE reflects competitive intensity, predictability and rapid market changes (Prajogo, 2016).

    The database of the SME Corp. of Malaysia was used to extract the list of SME retail firms as the respondents. The SME firms were selected from the distributive trade category. The population from central region of Malaysia in 2015 database consists of 13,685 registered firms. Applying statistical formula of Dillman (2007), the identified sample sizes of the respondents were 373. Stratified random sampling technique was applied in order to ensure that all states in the central region were being fairly represented. The study applied cross-sectional method in which a structured questionnaire was emailed to the owner-managers. The respondents were given 90 days to respond with two interval written reminders issued for certain retail firms. Out of 154 surveys returned, 152 are useable for analysis and regression was equal to 40.7 percent valid response rate.

    Path modelling analysis using Partial Least Square- Structural Equation Model (PLS-SEM) was executed in regressing the data and testing the hypotheses. Variancebased SEM (PLS-SEM) is suggested for exploratory variables especially when the new independent, moderator or mediator variables are being introduced to a common accepted framework. It caters for both low and high number of respondents (Hair et al., 2014).

    3.2 Hypothesis Development

    This study proposed four hypotheses that envisaged two direct relationship between EO, MO and SME retail firm performance. It also emphasized on the moderating effect of VE on the both linkages. This research framework is depicted as per Figure 1.

    There are continuous extensive studies on MO related to performance of various business models. Many studies have proven that MO provides significant positive effect towards performance either directly and indirectly (Mahmoud et al., 2016;Kazakov, 2016;Kazemian et al., 2016;Beneke et al., 2016;Amin et al., 2016;Kamboj and Rahman, 2017). With exception of different moderators or performance dimensions, the direct effect of MO towards performance is also positively aligned with other scholars’ findings such as Narver and Slater (1990) and Matikainen et al. (2016). Therefore, from the discussion above a hypothesis is formed as follows:

    • Hypothesis 1: There is a significant positive relationship between market orientation and FP of retail firms in Malaysia

    Evidently, EO is an important determinant of firm’s performance for over 30 years since its popularity in literature. For example, Kajalo and Lindblom (2015) focused on the direct effect of EO and MO towards performance (financial and non-financial) of small retailers in Finland. From the analysis of 202 samples from small retailers of non-food segment, they found that the EO has positive effect for both direct and indirect relationship with performance. Another study by Kantur (2016) on 324 top managers from 118 companies in Turkey also shows positive effect of EO on firm performance, with the mediating role of strategic entrepreneurship. Locally, studies by Ahmad and Ghani (2013) and Amin et al. (2016) also supported the roles of three EO dimensions toward the business performance. Hence, this study postulated that:

    • Hypothesis 2: There is a significant positive relationship between entrepreneurial orientation and FP of retail firms in Malaysia

    There are inconsistent findings on the role of MO towards performance. Few studies failed to find significant direct relationship like studies by Kajalo and Lindblom (2015) and Morgan et al. (2009). In addition, Najafi-Tavani et al. (2016) found that a combination of MO with other marketing capacities does not prove any significant relationship towards performance of new products. Therefore, the mixed findings of previous studies provide avenue for researchers to explore and investigate the role of VE in determining the moderating effect of MO-performance relationship. Therefore, this study proposes the below hypothesis.

    • Hypothesis 3: VE moderates the relationship between MO and FP

    From previous studies, the effect of environment volatility especially on the high VE (VE) is worth studying in order to better understand the relationship between EO and FP. Currently, there are two contradicting views of the role of environment volatility in the relationship between EO and firm performance. First view suggests that high VE significantly moderates the relationship between the EO and FP, signifying the requirement of firms to adapt with uncertain environments to maintain their competitiveness (Kurtulmuş and Warner, 2015;Al-Nuiami et al., 2014). The second view proposes that external environment volatility has no moderating effect on EO and FP (Pratono and Mahmood, 2016;Grimmer et al., 2015;Aminu and Shariff, 2015). Instead, the performance is characterized by internal environment such as by firm characteristics, human resources and financial availability (Kurtulmuş and Warner, 2015;Grimmer et al., 2015). Therefore, this study proposed the following hypothesis.

    • Hypothesis 4: VE moderates the relationship between EO and FP

    3.3 Data Analysis Procedure

    PLS-SEM was chosen as a platform for multiplevariation regressions to evaluate the framework and defined hypotheses. PLS-SEM has increasingly gained interest in research for its user-friendliness, applicability and versatility in analysing and interpreting data (Hair et al., 2014). Structural equation modelling (SEM) has been a preferred tool for survey-based research since three decades ago (Dijkstra and Henseler, 2015). Researchers utilize SEM abilities, for example, modelling the latent variables and adjusting measurement error. Another advantage of PLS-SEM application is an ability to regress the multiple variables (independent, moderator, mediator and dependent variables) simultaneously compared to SPSS which is limited to regression of a relationship with a dependent variable once for every linkage.

    The PLS-SEM regression resulted in two sets of linear equations for path modelling, namely measurement model (outer model) and structural model (inner model). The outer model assessment consists of ascertaining individual item reliability, determining internal consistency reliability, and examining convergent and discriminant validity of the constructs (Hair et al., 2017;Imam and Hengky, 2015). Furthermore, an inner model focuses on hypotheses testing which applies a standard bootstrapping procedure by regressing large subsamples (5000), one tailed test type and 0.05 significant level to determine significance of the path coefficients (Hair et al., 2017).

    Moderating effect was analyzed using three procedures proposed by Hair et al. (2017). Three procedures comprise (i) a model of direct interaction (ii) a model with the moderating effect and (iii) the change in R2 evaluation. These three procedures were applied to identify the interacting effect of high VE (VE). In this study, the moderating interaction effect evaluation was applied through a product indicator approach (Hair et al., 2017;Henseler and Chin, 2010) in order to determine and assess the strength of the moderating effect of high VE (VE) on the relationships between MO as well as EO and the Firm Performance (FP).

    Interaction term of product indicator is deemed appropriate if a moderating variable is continuous (Rigdon et al., 1998). Hence, to ascertain the interaction effect using the product indicator, the product terms (calculation method) between the indicators of the latent variable and the indicators of the latent moderator variable must be accounted for. Moderating effect exists if the interaction term is significant (Hair et al., 2017;Imam and Hengky, 2015).

    3.4 Non Bias Test

    In this study, 10 demographic variables were used to measure the early and late respondents as they were available and significant to the survey assessment (McFarlane et al., 2006). Late respondents were categorised based on the returned questionnaire after second follow up was done by reminder notice. Late respondents should be assessed since they could lead to poor data quality and seen as less reliable (Chandhok, 2008). They can also be categorized as unwilling respondents which is related to nonrespondents (Draugalis and Plaza, 2009).

    Table 2 depicts the results of the non-response bias test. From the table, the p-values revealed no statistical significance (p > 0.005) between the late and early respondents, hence, the late and early analysis was accomplished on all the 152 respondents.

    Besides the chi-square test, an independent sample ttest can also be used to outline whether significant differences occur in the mean scores for the selected variables among the early and late respondents. According to Table 3, the early and late respondents did not differ in terms of their responses to the study variables (p >.005). Therefore, all the useable questionnaires from 152 respondents can be used in the analysis.


    SEM-PLS is a robust tool to determine the individual reliability for all constructs (Duarte and Raposo, 2010). It is important that each measurement item achieves the value above 0.708 for individual outer loading (Hair et al., 2017) since it will lead to 0.50 AVE value (0.7082 is slightly equal to 0.500). For specific case, Hair et al. (2017) suggested that outer loading of 0.40 to 0.70 is still acceptable as long as the same construct delivers AVE of 0.50 and above. Three items out of 37 were removed and with that this study has met all the specification of reliability (outer loadings & AVE).

    Internal consistency reliability determining how well all items measure same construct, hence delivering consistent result (Bijttebier et al., 2000;Sun et al., 2007). There are two main approaches on measuring internal consistency reliability, Cronbach’s alpha and composite reliability. According to Imam and Hengky (2015) the composite reliability is more reliable instead of Cronbach’s alpha. Specifically, the Cronbach’s alpha considers all items as equally reliable and this may lead to reliability value miscalculation. On the contrary, the composite reliability considers every item as individual and values above 0.70 are recommendable (Hair et al., 2017;Imam and Hengky, 2015). From the SEM-PLS regression, the result indicated the values of composite reliability were between 0.834 and 0.927, verifying the internal consistency reliability of this study.

    Meanwhile, convergent validity can be evaluated by examining the outer loadings of the indicator (item loadings) (Duarte and Raposo, 2010;Hair et al., 2017) and the AVE (Fornell and Larcker, 1981;Hair et al., 2017). The outer loading shows to what extent the indicator has in common with the latent construct. The higher the outer loading, the higher the indicator has something in common with the construct (Hair et al., 2017), and in effect, the more valid the latent construct is. In this measurement model, the outer loadings were between 0.598 and 0.905. The accepted AVE value for convergent validity should be above 0.50 (Ramayah et al., 2018) and therefore, the results fulfilled the convergent requirement.

    By executing the three tests above, study has ad-hered to the necessary evaluations for determining relia-bility and validity of items and constructs. Table 4 sum-marizes the results for individual item reliability, internal consistency reliability and convergent validity tests.

    For structural model assessment or hypotheses test-ing, this study applies standard bootstrapping procedure by PLS with regression for large subsamples (5000), one tailed test type and 0.05 significant level to determine the significance of path coefficients suggested by Hair et al. (2017). Figure 2 depicts the estimates for the full structural model including the moderating effect (VE).

    Table 5 illustrates the results of the direct path be-tween exogenous constructs and the endogenous con-struct. Multivariate regression using PLS-SEM revealed the output p-values of 0.000, which below the threshold of 0.05. Therefore, the results supported the hypothesis 1 where MO positively influences retail firm performance. However, the regression result for p-value of 0.460, indicating that no significant relationship between EO and FP, and thus hypothesis 2 is not supported.

    Hypothesis 3 (H3) posits that the relationship be-tween MO and SMEs retail firms’ performance (FP) is moderated by (VE). The result of this hypothesis, as shown in Table 6 does support the hypothesis (ß =0.018, t=1.803, p < 0.05) and thus, support that the relationship between MO and FP. Yet, the result also indicated that there is no significant moderating effect (p-value 0.476) between EO and FP.

    Figure 3 demonstrates that the positive relationship of MO and FP was indeed stronger when VE is high. The firms that displayed low MO differed a bit lower in per-formance either in low VE. This indicates the capacity of MO was still beneficial during both environments, either during high or low volatility. However, there was no significant moderating effect found between relationship of EO and FP.


    The Structural Model Assessment has been under-taken to test the H3 in which hypothesizes that high VE moderates the relationship between MO and FP. The result demonstrates that VE moderates the relationship. The finding is in lieu with results from past studies performed by Mahmoud et al. (2016), Mahmoud (2011), Wang et al. (2012) and Tang and Hull (2012) that investigate the effect of high VE on the performance achievement.

    Contrary to the predicted hypothesis (H4), this study found that high VE does not moderate the EO-SMEs performance relationship. Therefore, during this type of environmental volatility, firms do not boost their EO activities and at the same time there is no linkage towards performance indication. This finding aligns with the findings of Pratono and Mahmood (2016), Emam and Shajari (2013) and Zellweger and Sieger (2012). They argued that during highly VE, greater EO posture does not bring positive effect towards FP. Rather, the EO may decrease due to high uncertainty and rapid changes.

    As predicted, SEM-PLS regression shows highly significant effect of MO-performance and is supported by the structural model path coefficient test. The significant positive effect confirms that MO is a critical determinant for the achievement of SMEs existence of retail firms and the intended superior performance. Hence, the result supports the H1 that the MO has positive effect on the performance. The finding is aligned with most results in previous studies on MO. For examples, studies by Narver and Slater (1990), Kajalo and Lindblom (2015), Tutar et al. (2015), Mahmoud et al. (2016), Kazemian et al. (2016), Kazakov (2016), Beneke et al. (2016) and Matikainen et al. (2016).

    However, unlike the predicted relationship outcome, the hypothesis 2 in the present study is not supported. It is found that no significant effect of relationship between EO and FP in this retail subsector. Even though many studies have been conducted worldwide such as by Martin and Rialp (2015), Arshad et al. (2014), Gupta and Batra (2015), and Ruiz-Ortega et al. (2013), to name a few, which support the positive linkage of EO towards performance, many others are unable to find significant relationship.

    Various past studies support the absence of signifi-cance influence of EO towards performance (such as, Grimmer et al., 2015;Aminu and Shariff, 2015). From a different perspective, certain scholars also argued that when EO and MO executed simultaneously, the effects of EO reduced drastically or become ineffective (Morgan et al., 2015;Frishammar and Hörte, 2007).

    5.1 Research Implication

    The results of this study have important practical contributions and managerial implications for policy makers and SMEs retail firms’ owner-managers. With regards to the implications, policy-makers generally and retail firm’s owners-managers specifically may take significantly important measures for the performance of retail firms in developing countries especially in Malaysia.

    Studies on the predictors of retail firms’ performance especially during challenging environment are scarce. Hence, this study provides scholarly and practical insights on whether market orientation and entrepreneurial orientation are influenced by high VE which can enhance the overall SMEs performance of retail firms

    Policy-makers may develop training programs that can expedite managers’ expertise as the key element of valuable intangible asset of a firm. SMEs or related gov-ernment agencies should frequently expose the managers through industry players’ experience-sharing sessions and workshops as mean to improve firms’ market proposition which consist of competitor orientation, customer orientation and inter-department coordination. This includes educating the managers on how to identify, learn and respond quickly to various type of environment faced by firms. These trainings can be conducted for retail practitioners or as an early exposure by creating modules for technical or higher institutions curriculum. This will inculcate awareness that leads to more effective work culture, higher firm performance and business environment readiness.


    In conclusion, the study on the effect of two strategic orientation constructs for the retail firms’ performance operating in Malaysia reveals that MO has significant positive direct-effect. In contrast, the effect of EO is not significant when executing simultaneously with MO during high VE. The study also reveals that high VE strongly moderates the relationship between MO and FP, but not for the EO-FP linkage. This study concludes that the MO is an important and valuable firm-level culture notwithstanding the volatility of environment, either benign or highly volatile. As such, it is crucial for retail firms to invest and strengthen this orientation in adapting any circumstances of changing environments.

    6.1 Suggestion

    There are few limitations when conducting this study. This study does not examine objective financial data due to time and resources constraints. The performance is measured based on the owner-managers’ subjective assessment on the given measures. The opinion of employees and other stakeholders are also not taken into consideration.

    Future study should screen or adding other variables into the current framework, such as learning orientation, technology orientation, management and technical competencies, entrepreneur attributes, and other external forces (macro and micro environment) that may affect the superior performance of retail or other industry. A longitudinal study by combining perceptions from employees and retail experts may broaden the knowledge in this aspect.



    Conceptual framework.


    Structural model with moderating effect (full model).


    The moderating effect of VE.


    Various level of business environment volatility

    Chi-square test for early and late responses

    Differences in major variables by early and late responses (independent t-test)

    Individual item reliability, internal consistent reliability and convergent validity

    Structural model assessment (hypotheses testing)

    Structural model assessment (moderating effect)


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