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The impact of strategic learning orientation, entrepreneurial orientation and reconfiguring capabilities on export performance of SMEs in Nigeria

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International Journal of Management Science and Business Administration
Volume 2, Issue 3, February 2016, Pages 33-42


The Impact of Strategic Learning Orientation, Entrepreneurial Orientation and Reconfiguring Capabilities on Export Performance of SMEs in Nigeria

DOI: 10.18775/ijmsba.1849-5664-5419.2014.23.1004
URL: http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.23.1004

¹Tope Samson Abiodun, ²Muhammed Isa KIDA

¹ ² Graduate School of Business, Universiti Utara Malaysia, 06010UUM Sintok, Kedah, Malaysia

Abstract: The  objectives of this study are to investigate the relationship between learning orientation (LO), entrepreneurial orientation (EO), reconfiguring capability (RC)  and export performance (EP) as well as determine the mediating effect of entrepreneurial orientation on the relationship between LO, RC and EP of SMEs in Nigeria. Having employed PLS-SEM on 201 data from SMEs in Nigeria, the findings of the study revealed significant relationship between LO and EP, between RC and EP, and between EO and EP, while the mediating effect of EO on the relationship between LO and EP, and between RC and EP are less statistically significant

Keywords: Entrepreneurial orientation, Reconfiguring capability, Learning orientation, Small and medium enterprises, Export performance

The impact of strategic learning orientation, entrepreneurial orientation and reconfiguring capabilities on export performance of SMEs in Nigeria

1. Introduction

The need for economic growth has made SMEs’ significant roles to be recognized in many nations. Their values, such as power of expansion, Job creations at relatively low capital cost, means of livelihood, provision and development of trained and untrained labor for potential industrial growth and the breeding ground for managerial and entrepreneurial talents have shown SMEs as indispensible sector in any economy (Ayanda & Laraba, 2011). However, SMEs in Nigeria face monumental challenges such as weak strategic orientations, poor infrastructure, inadequate capabilities, poor management and inadequate technological skills’ development and lack of export market knowledge/experience (Adegbite, Ilori, Irefin, Abereijo, & Aderemi, 2007).

A study carried out by Manufacturing Association of Nigeria (MAN) showed that just about 10 percent of industries run by its members are completely in operation. The vast majority of SMEs die before their first to five year of operation, while some disappear within sixth and tenth year of existence and the remaining ones that grow to maturity are less than five to ten percent (Onugu, 2005). Economic and industrial growth as development goals can only be attained by promoting export development of Small and Medium Enterprises (Kazem & van der Heijden, 2006). SMEs account for 25-35 percent of world’s manufactured export and their contribution to GDP is between four and six percent (Ibeh, 2004). In spite of the importance of export development and SMEs’ relationship with economic development, scholarly interest  has neglected how an emerging firms should decide what resources to amass and how to configure them to create customer value in a context of uncertainty in international arena (Santos & Eisenhardt, 2009). The bulk of researches on strategic orientations and reconfiguring capabilities in export performance focus on large established firm (Corner & Wu, 2012).

Many of these researches focus on firms operating in western developed market and little is known about Reconfiguring capability and strategic orientations and their relationship with export performance in transition economies.  As such, little is known about export development of SMEs (Sapienza, Autio, George, & Zahra, 2006). Wang and Ahmed (2007) Suggested that researchers should develop more refine measure of adaptive capabilities by considering specific aspects of dynamic capabilities such as resources reconfiguration and examine it in a systematic network and provide a better understanding of what circumstances and how firms should direct their resources and capabilities in search of competitive advantage. Hence, the basic objectives of this study are to explain and predict export performance of SMEs with strategic learning orientation, entrepreneurial orientation and reconfiguring capability through the lens of dynamic capability view and resource based view (RBV).

2. Underpinning Theories

  1. Resources Based View
  2. Dynamic Capability View

This study considers entrepreneurial orientation as a sufficient tool to mediate between learning orientation and export performance of SMEs based on the premises that firms are proactive organization and manager makes decision on structural change in order to learn, find new opportunity and be profitable (Karim, 2006). Entrepreneurial orientation would give explanation on why the managers of smaller organization need to learn, since he plays the significant roles in shaping the firm’s future. For export firm in today’s dynamic environment to achieve competitive advantage depends on its capacity to learn, knowing how to store and how to recover a good memory bank and apply it. Hence, this study hypothesizes that:

H5: Entrepreneurial orientation mediates the relationship between learning orientation and export performance.

3. Methodology

The data collection for this study took place in Nigeria, because of the call for the development of non-oil sector and low performance of Nigeria’s SMEs in export venture. Each of the manufacturing SMEs identified in the directory Manufacturing Association of Nigeria (MAN) were contacted by telephones to identify an appropriate key informant for the study and inform the firm about the research project (Morgan, Kaleka, & Katsikeas, 2004). About 2200 firms were identified as qualified because they met the criteria specified. To select a sample size for the population of 2200, Krejcie and Morgan (1970) sample sizes determination’s table was used. The table showed that 331 sample sizes would be required for the population of 2200 and additional 40% of 331 were added to make provision for response bias, making 457 sample sizes.

Having employed proportional stratified and systematic sampling, the distribution of the questionnaires was based on the proportion of population of SMEs’ export manager in each geographical area and systematic selection of the respondents from the list of SMEs’ exporter in order to ensure representative distribution. About twenty five days after the questionnaire have been emailed to the respondents, 118 completed questionnaires were received through e-mail and these 118 questionnaires were regarded as early responses which (after non useable ones have been removed) were further used to assess non response bias on the actual variables.  In order to improve the response rate, a follow-up phone calls and series of Short Message Service (SMS) were sent to remind the exporting managers who were yet to return their questionnaires. This effort yielded the largest numbers of response compared to the first response. About 120 questionnaires were returned. It was tagged as late responses which (after non useable ones have been removed) were later used to assess non-response bias.

Out of 457 questionnaires that were emailed to the selected respondents, a total of 238 were returned, 156 questionnaires were returned from Lagos, 58 from Kano and 24 from Aba respectively out of these 238 questionnaires 2 were not usable due to excessive missing data, 2 were completely eliminated due to their selection of option ‘services/government’ and not ‘manufacturing’ as primary area of business, 2 were also removed for selection of option ‘total cost of business that above #200,000,000 Naira specified as a criteria for SMEs and 2 were also eliminated due to low level of knowledge on the topic of interest, remaining 230 useable questionnaire. Hence, the response rate was calculated as 50% which is sufficient for the study (Sekaran & Bougie, 2013).

4. Measures

Learning Orientation (LO) was measured with Baker and Sinkula (1999).  The items in the scale really suit the purpose of this study because Learning orientation is a set of values that affect the satisfaction of a firm (Argyris & Schon, 1978). The degree to which firms are likely to promote generative learning as competency is influenced by its culture of learning orientation (Sinkula, Baker, & Noordewier, 1997) Learning orientation is reflected when old assumptions are challenged and set of knowledge-questioning values that have been held in the organization (Bettis & Prahalad, 1995; Sinkula et al., 1997). All values that are routinely associated with organizational learning capabilities revolved around its commitment to learning, open-mindedness and shared vision (Baker & Sinkula, 1999).

The reconfiguring capabilities in this study were examined from two different perspectives: the amount of reconfiguring activity over the past three years and the perceived success in implementing the activities. Jantunen et al. (2005) used the success of renewal activities carried out in the community innovation survey of the European Union. This list comprises seven renewal types (organization structure, business strategy and manufacturing process). Some of the activities performed ranged from zero to seven. This study employed the seven items to measure reconfiguring capability.

Entrepreneurial orientation was measured with nine items of Covin and Slevin (1989). The vast majority of studies related to EO used only reactiveness, risk taking and innovativeness (George & Marino, 2011) which are version of the scale suggested by Covin and Slevin (1989). Moreover, Jantunen et al. (2005) realized that the three dimensions are closely related through the composite measure constructed as an average of all nine items which resulted in reliability coefficient of .74. The guidelines regarding composite reliability considered this satisfactory (Nunnally, 1978).  Hence, this study adapted the nine items’ measure of Covin and Slevin 1989 for parsimony and credibility

The measurement of export performance has not been universally suggested among the scholars of export’s researchers, however, Zou, Taylor, and Osland (1998) addressed the three critical issues in determining export performance, their scale EXPERF was multidimensional and really centered on performance of exporting ventures. It was built on Cavusgil and Zou (1994) and comprises three basic dimensions that are rooted in export performance’s literatures; financial, strategic and satisfaction’s export performance measure. The nine items adapted from Zou et al., (1998) are used to measure export performance in this study because they reflect economic and non-economic factor that could easily show the performance of SMEs.

5. Analysis

The present study employed a two-step process to calculate and report the result of PLS-SEM path as suggested by (Henseler, Ringle, & Sinkovics, 2009). Having run   PLS-SEM algorithm, the indicators with outer loading were between 0.4299 and 0.8702, and this shows individual items reliability (Hair, Hult, Ringle,Sarstedt, & 2013). The composite reliability of the study ranged between  0.7970 and 0.8702 which is considered satisfactory for internal consistency validity (Bernstein & Nunnally, 1994). The average variance extracted range between 0.521 and 0.7948, which are all above the cut off .50. Table 1 shows the items loadings, average Variance Exracted and the composite reliability of the study.

Table 1: Items Loadings, Average Variance Extracted and Composite Reliability for the constructs

Latent Variable Items Loadings          AVE     Composite  Reliability
     Commitment to Learning CLO01 0.8359 0.5871 0.8471
CLO02 0.8073
CLO03 0.8376
CLO04 0.5444
            Open-mindedness SLO01       0.797
SLO02 0.7955
SLO03 0.7422
SL005 0.5246
Entrepreneurial Orientation  EOO01 0.6968 0.5479 0.858
 EOO04 0.7122
 EOO05 0.7987
EOO06 0.7098
EOO07 0.7654
EOO08 0.7768
EOO09 0.7778
Reconfiguring Capability RCD01 0.5816 0.6568 0.9296
RCD02 0.8483
RCD03 0.8816
RCD04 0.8619
RCD05 0.769
RCD06 0.8581
RCD07 0.8318
               Satisfaction SAT01 0.9382 0.7948 0.9207
SAT02 0.869
SAT03 0.8654
                   Strategy STG01 0.6995 0.6883 0.8675
STG02 0.8998
STG03 0.8752
                  financial FIN01 0.6995 0.6924 0.8702
FIN02 0.8998
FIN03 0.8752

The square root of the average variance extracted ranged between 0.7218 and 0.8915 which were all greater than the correlation among the latent constructs, signifying sufficient discriminant validity (Chin, 1998; Fornell & Larcker, 1981). Table 2 shows the square root of the variance extracted and correlations of the latent variables.

Table 2: Square Root of Average Variance Extracted and Correlations of the latent Variables

  Latent Constructs         1 2 3 4 5 6 7 8
 Commitment to L 0.7662
Entrepreneurial O 0.3074 0.7402
 Open-mindedness 0.5819 0.3268 0.7218
Reconfiguring C 0.061 0.3008 0.0083 0.8104
 Satisfaction 0.0634 0.3131 -0.0729 0.5355 0.8915
Shared Vision 0.3836 0.3983 0.2998 0.0546 0.2954 0.7076
Strategy 0.1314 0.289 -0.0557 0.5661 0.6482 0.205 0.8296
 financial 0.3061 0.2987 0.1893 0.4955 0.5833 0.2156 0.6976

Note: Diagonal elements (figures in bold) are the square root of the variance shared the constructs and their measures while off diagonal elements are the correlations among constructs.

The effect size of each of the constructs on endogenous construct, large with F squared of 0.5043 and small with F. squared of 0.0223. The cross validated redundancy for endogenous variables are 0.2247 and 0.135 which are greater than zero and considered to have predictive relevance (Henseler et al., 2009). Standard bootstrapping procedure was used with a number of 5000 bootstrap samples and 201 cases to assess the significance of the paths (Henseler et al., 2009; Hair et al., 2013). Figure 3.1 depicts the use of boostrapping to assess the significance of the path coefficients and Table 3.1 shows the result of the structural model.

Table 3: The Result of the structural Model and Mediator

 H Relationship βeta Standard Error T. Value P. value
H1 Learning Orientation -> Export P. 0.1262 0.0626 2.0146 0.02
H2 Reconfiguring C. ->Export P. 0.5713 0.0811 7.0453 0.00
H3 Entrepreneurial O.-> Export P. 0.1221 0.0823 1.4831 0.06
H4  Reconfiguring C->Entrepreneurial O.->Export P. 0.2874 0.0713 1.3589 0.09
H5 

Learning O->Entrepreneurial O.->Export P

0.4051 0.0636 1.4316 0.08

***P<0.00;**P>0.05: *P<0.01

1

Figure 1: The full Structural Model

6. Discussion

The result (β=0.1262, t=2.0146, p<0.02) of the relationship between learning orientation and export performance in the study is consistent with the previous studies (Akyol & Akehurst, 2003; Cadogan, Cui, & Li, 2003; Day, 1992; Song, Joo, & Chermack, 2009; Souchon et al., 2012). Ability to learn and apply this knowledge to turbulent environment and challenge export market is the major key to achieve and sustained competitive advantage (Day, 1992). Secondly, the outcome of PLS model’s estimate (β=0.5713, t=7.0453, p<0.00) on the relationship between reconfiguring capability and export performance returned statistically significance result to support the hypothesis. This finding is consistent with prior study (Abiodun & Rosli, 2014), and the findings of this study provide empirical support for dynamic capability theory which lays emphasis on the ability to orchestrate change and reconfigure the asset base in order to take the advantage of new opportunity (Jantunen, et al., 2005). Thirdly, the result (β=0.1221, t=1.4831, p<0.06) is also consistent with  earlier studies   (Baker & Sinkula, 2009; Balabanis & Katsikea, 2003; Boso, Cadogan, & Story, 2012; Calantone, Kim, Schmidt, & Cavusgil, 2006; Cavusgil, 1984; Lechner & Gudmundsson, 2014; Wiklund & Shepherd, 2003; Zahra & Covin, 1995) which suggested relationship exists between entrepreneurial orientation and firm/export performance. Fourthly, the mediating effect calculated through the spreadsheet of coefficient generated by war PLS (Kock, 2014), indicates that (β=0.2874, t=1.3589, p<0.09) entrepreneurial orientation mediate between reconfiguring capability and export performance. The ownership perception of opportunities is used to underpin changes in existing routines or resources configuration, their willingness to undertake such changes and their ability to implement the change. (Woldesenbet, Ram, & Jones, 2012). Fifthly, the mediating effect calculated through the spreadsheet of coefficient generated by war PLS (Kock, 2011), the result (β=0.4051), t=1.4316, p<0.08) shows that entrepreneurial orientation mediate the relationship between learning orientation and export performance. This is consistent with the view that Entrepreneurial orientation would give explanation on why the managers of smaller organization need to learn, since he plays the significant roles in shaping the firm’s future (Souchon et al., 2012). However, p. value; 0.08 at one Tale significant level for mediation of EO relationship between LO and EP did not reflect good significant mediating effect. The same thing applicable to P Value; 0.09 and P Value; 0.06 respectively, which means there is no strong mediating effect and each of the variable could directly have impact on export performance without EO. Nevertheless, this study has been able to show the level of the significance that could be attained when EO is used as mediator between these constructs.

7. Conclusion

 This study makes contribution to the literature of entrepreneurship and strategic management research by investigating the impact of reconfiguring capabilities and strategic learning and entrepreneurial orientation on export performance of SMEs. To the best of the knowledge of this study, these effects have not been empirically investigated in previous study in this approach. Even though there have been studies on strategic orientations and export performance (Cadogan, 2012; Knight & Cavusgil, 2004).This study in particular complements the existing study and the result suggests that it is not only the ability to learn and apply this knowledge and challenge export market old assumptions to achieve and sustain competitive advantage (Day, 1992), but also the ability of firm to create new asset configuration that have strategic impact on export performance. The findings of this study provide empirical support for dynamic capability view which lays emphasis on the ability to orchestrate change and reconfigure the asset base in order to take the advantage of new opportunity (Jantunen, et al., 2005). Reconfiguring capability significantly related to export performance, shows that reconfiguring capabilities are learned and stable blueprint of combined activities through which the organization steadily generates and transform its operating routines in order to improve efficiency and effectiveness (Zollo & Winter, 2002). This finding has also joined the host of prior studies on learning orientation to subscribe that learning orientation -export performance implication represents area of building a cumulative body of relevant knowledge about entrepreneurship  and  stresses the fact that exporting  SMEs are likely to benefit from pursuing learning orientation.

Entrepreneurial orientation mediates the relationship between reconfiguring capability, learning orientation and export performance, which denotes that reconfiguring capability and learning orientation possessed by an exporting entrepreneur  would identify new combination of productive resources within the firm and extend the frontiers of capability, and connecting several ventures with different resources and enhance the ongoing adaptation of exporting since the linkage improves overall innovation management that would enable the firm to reconfigure its resources and provide way to experiment new idea (Borch & Madsen, 2007; Dougherty & Hardy, 1996).

Therefore, Manager who put relatively more emphasis on profitability could invest more in reconfiguring their assets Such SMEs’ manager could emphasize capability development and market penetration in their exporting activities as such effort would enhance processes needed to learn from disappointment, recognition of failure, interpretation of result into exporting model that can be tested and better action taking routine in export arena. Firms should also be proactive, innovative, and strategic and take measure of calculated risk to improve their export performance. Managers should recognize that their ability to adapt to external environmental changes is only the key driver to sustainable export performance.

Hence, skills should be honed to spot growth options from other development initiatives, executing  reconfiguring option required different operating capabilities that have to be reconfigured, coordinated and integrated for maximum competitive advantage in export arena (Newey & Zahra, 2009). The managerial implication of learning orientation impact on export performance implies that export growth is optimal at very high levels of response to export information which is promoted by commitment to learning, open-mindedness, shared vision, acquisition and distribution of export information and management of mental model.

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