The interface between organizational learning capability, entrepreneurial orientation, and SME growth Article 

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Altinay, L., Madanoglu, M., De Vita, G., Arasli, H. and Ekinci, Y. (2016) The interface between organizational learning capability, entrepreneurial orientation, and SME growth. Journal of Small Business Management, 54 (3). pp. 871­891. ISSN 1540­627X doi: https://doi.org/10.1111/jsbm.12219 Available at http://centaur.reading.ac.uk/47957/ 

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The Interface between Organizational LearningCapability, Entrepreneurial Orientation, and SMEGrowthby Levent Altinay, Melih Madanoglu, Glauco De Vita, Huseyin Arasli, andYuksel Ekinci

This paper investigates the interface between organizational learning capability, entrepreneur-ial orientation (EO), and small business performance. It reports on the findings from 350 smalland medium enterprises (SMEs) in North Cyprus operating in the services and retailing sectors.The findings indicate a positive relationship between EO and sales and market share growth, butnot between EO and employment growth. There is also a positive relationship between organiza-tional learning capability and EO. This paper contributes to the small business management liter-ature by providing a holistic analysis of the interface between organizational learning capability,EO, and growth.

IntroductionThe contemporary dynamism of the business

environment has been forcing businesses toremain competitive by exploring new opportuni-ties (Hitt et al. 2001). Strategic orientation hasbeen defined as the principles that direct andinfluence the activities of businesses and thatinform the behaviors aimed at exploiting oppor-tunities so as to gain and sustain competitiveadvantage (Hakala 2011). A strategic orientation,therefore, steers the direction of businessesand assists them in the process of identifying cus-tomer needs and wants proactively by introduc-ing new products and services ahead ofcompetitors. This pattern, in turn, influences theindustry at large through the establishment of

new standards (Escriba-Esteve, Sanchez-Peinado,and Sanchez-Peinado 2008).

The strategic orientation of businesses hasattracted widespread attention from entrepre-neurship scholars. According to the entrepre-neurship literature, businesses create value andgrowth through engaging in entrepreneurialactivities (Spicer and Sadler-Smith 2006). Suchactivities include the identification and exploita-tion of business opportunities through inno-vation, proactive behaviors, and risk-takingdecisions (Covin and Slevin 1989, 1991; Spicerand Sadler-Smith 2006). However, such anentrepreneurial approach can only offer tempo-rary competitive advantages. Businesses alsohave to think creatively about how to sustain

Levent Altinay is Professor of Strategy and Entrepreneurship and Research Area Leader at Faculty of Business,Oxford Brookes University, Oxford, United Kingdom.

Melih Madanoglu is Associate Professor at College of Business, Florida Atlantic University, Boca Raton, Florida.Glauco De Vita is Professor of International Business Economics at Centre for Business in Society (CBiS), Cov-

entry University, Coventry, United Kingdom.Huseyin Arasli is Professor of Management, Eastern Mediterranean University Faculty of Tourism, Famagusta,

TRNC, Mersin 10 Turkey.Yuksel Ekinci is Professor of Marketing and Reputation, Henley Business School, Reading University, Reading,

United Kingdom.Address correspondence to: Levent Altinay, Oxford Brookes University, Gipsy Lane Campus, Headington,

Oxford, OX3 0BP, UK. Tel: 144 (0)1865 483832; Fax: (0)1865 483878; E-mail: laltinay@brookes.ac.uk.

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Journal of Small Business Management 2015 00(00), pp. 00–00

doi: 10.1111/jsbm.12219

competitive advantages by adopting a long-termorientation and taking strategic actions includ-ing strategic planning and the acquisition andanalysis of information to improve decision-making (Cohen and Sproull 1996; Morgan andStrong 2003). Therefore, entrepreneurial andstrategic management perspectives need to becombined in order to be able to develop thestrategic orientation needed to achieve and sus-tain competitive advantages (Escriba-Esteve,Sanchez-Peinado, and Sanchez-Peinado 2008;Hakala 2011).

Entrepreneurial orientation (EO) is one of themost popular constructs explaining value creationactivities and business growth. It encompassesfirm-level behaviors, in particular, entrepreneur-ial processes, practices, and decision-makingactivities (Lumpkin and Dess 1996). EO reflectsthe propensity of small and medium enterprises(SMEs) to engage in the “pursuit of new marketopportunities and the renewal of existing areas ofoperation” (Hult and Ketchen 2001, p. 901). Inspite of its importance in explaining how firmsdevelop and exploit business opportunitiesthrough engaging in entrepreneurial activities,extant research on EO has been criticized forneglecting organizational learning capability andknowledge creation, thereby falling short ofexplaining the processes through which growthis achieved (Covin and Lumpkin 2011). Thisclearly suggests the adoption of a combinedapproach to explaining performance, reiteratingthe point made earlier that, besides the imple-mentation of entrepreneurial processes and prac-tices, businesses need to develop internal systemsand procedures to enhance knowledge buildingcapacity and enable organizational learning(Cohen and Sproull 1996; Floyd and Wooldridge1999). In particular, entrepreneurial activitiescould be sustained through developing learningcapability processes and knowledge creation,leading to continuous and proactive entrepre-neurial engagement and sustainable growth(Floyd and Wooldridge 1999). Organizationallearning capability (hereafter OLC) can bedefined as the ability of an organization to create,transfer, and integrate knowledge and modify itsbehavior with a view to improving its perform-ance (Jerez-Gomez, Cespedes-Lorente, and Valle-Cabrera 2005). It encompasses organizationaland managerial factors including managerialcommitment, openness, a sense of belonging tothe organization, experimentation, knowledgetransfer, and integration, all of which facilitate thelearning process (Goh and Richards 1997).

The relationship between OLC, EO, and per-formance has been studied individually (Covinand Lumpkin 2011; Grinstein 2008). However,very few studies have adopted a strategicmanagement perspective to understanding thecombined and simultaneous effects of strategicorientations on growth in a small business con-text. The notable exception is the excellent con-tribution by Alegre and Chiva (2013) who usingstructural equation modeling on a data set fromItalian and Spanish ceramic tile producers, findthat OLC (alongside innovation) significantlyinfluence the EO-performance relationship.

More importantly, although the analysis oflearning has become an increasingly significantstudy area in recent years, there is a dearth ofstudies investigating the role of organizationallearning in the survival and growth of small busi-nesses (Hakala and Kohtamaki 2011; Wales,Gupta, and Mousa 2013; Wang 2008). In particu-lar, OLC has been identified as a missing link inthe examination of the relationship between EOand growth (Jerez-Gomez, Cespedes-Lorente,and Valle-Cabrera 2005; Zhao et al. 2011). Thispaper aims to fill this glaring gap by investigatingthe interface between OLC, EO, and small busi-ness growth. By doing so, our study offers newinsights into how SMEs exploit their learningcapabilities to stimulate EO and thus improveperformance. In particular, the paper contributesto the small business management literature bydemonstrating that OLC of small firms facilitatesEO, which in turn, influences sales and marketshare growth positively.

The study also investigates the mediatingrole of EO between OLC and performance, aresearch avenue that has not been exploredbefore. Investigation of this issue is particularlyimportant because although the empirical evi-dence supporting this argument is still limited, itis through entrepreneurial ventures that a firmmaximizes the impact of OLC on firm perform-ance (Ar and Baki 2011; Hakala and Kohtamaki2011). In this respect, a further contribution ofthe study to the small business management lit-erature lies in providing empirical evidence thatEO broadens the scope of small firms for learn-ing and thus maximizes the impact of OLC onsmall firm’s sales and market share growth.

The paper draws upon data collected from350 SMEs in North Cyprus where firms con-stantly confront a complex and turbulent exter-nal environment caused by political andeconomic instability on the island. North Cyprusis not an internationally recognized State. It is

JOURNAL OF SMALL BUSINESS MANAGEMENT2

known as a de facto State, segregated and iso-lated from the southern Republic of Cyprus andheavily dependent upon Turkey, the sole coun-try to recognize North Cyprus, both politicallyand economically (Howells and Krivokapic-Skoko 2010). The economy of North Cyprus hasthe characteristics of a typical island economywith limited resources and imports exceedingexports. There is no heavy industry such asmanufacturing, and the economy is dependentupon the services sector, primarily tourism, andhigher education, and continuing economic aidfrom Turkey (Katircioglu 2010; Mehmet 2010).Due to economic and political embargoes onNorth Cyprus, the country cannot export itsagricultural and textile products. Significantly,the continuing economic sanctions have made itimpossible for aid agencies or internationalcompanies to operate in the region (Howellsand Krivokapic-Skoko 2010).

Despite international economic and politicalsanctions, North Cyprus has developed adynamic economy. More than 95 percent ofsmall and medium sized firms are private sectororganizations contributing to the public sectordominated economy (Mehmet 2010; Tanova2003). There is a strong public sector involve-ment in the economy, with the public sectorbeing the largest customer of SMEs, offering taxreductions and exemptions as well as providingincentives and subsidies to stimulate the start-upand growth of SMEs (Tanova 2003). A recentsurvey noted that small businesses operating inthe “protective environment” in North Cyprusare economically productive despite the eco-nomic sanctions (Howells and Krivokapic-Skoko 2010). Such an environment is believedto be fertile for new information and knowl-edge, characteristics which align to those seenas core features of entrepreneurial firms.Indeed, as pointed out by Wang (2008) andZhao et al. (2011), the more entrepreneurial afirm is, the more it engages in information andknowledge acquisition in order to respond togrowth opportunities.

Theoretical ReviewPrevious research investigating the interface

between strategic behavior and firm performancehas focused on large firms in large economiesleaving a glaring research gap in strategicbehavior-performance relationship in SMEs insmall and dependent economies (Parnell 2013).In particular, understanding the strategic orienta-

tions of SMEs is crucial as the strategic orientationadopted by SMEs determines the extent of SMEsrun demand and competitor analysis, and theway they acquire and exploit knowledge aboutmarket opportunities and engage in product-market innovations leading to growth (Aragon-Sanchez and Sanchez-Marin 2005; Escriba-Esteve, Sanchez-Peinado, and Sanchez-Peinado2009). It is now well documented in the literaturethat relying solely on an entrepreneurial mind-setprovides an incomplete understanding of SMEs’performance (Wiklund and Shepherd 2005). EOcan create temporary competitive advantagesthat cannot be sustained long term (Ireland, Hitt,and Sirmon 2003). Understanding the reasons fordifferentials among SMEs’ sustainable competi-tive advantage therefore requires analyzing theirlearning and knowledge creation capability andhow this can lead to continuous and proactiveentrepreneurial engagements and sustainablegrowth (Floyd and Wooldridge 1999; Jerez-Gomez, Cespedes-Lorente, and Valle-Cabrera2005). In fact, Baker and Sinkula (2009) state thatEO is a learning construct. SMEs that learn moreeffectively than their competitors improve fasterand more effectively than their competitors andachieve superior new product and service devel-opment. Effective analysis and integration ofmarket knowledge facilitates innovation, risk tak-ing and proactiveness leading to product andservice success, increased market share, profit-ability, and sustainable competitive advantage(Baker and Sinkula 2009). Likewise, SMEs adopt-ing a strong EO engage in proactive and exten-sive environmental scanning, serving as astimulus for information acquisition and exploita-tion and opening up scope for learning aboutmarket opportunities and growth (Wang 2008).Based on this reasoning, we take a more holisticview of investigating SME growth through ana-lyzing the combined effects of EO and OLC onperformance.

This paper aims to evaluate the relationshipbetween different orientation constructs, namelyOLC, EO, and SME growth holistically. It isinternational in scope, collecting and articulatinginformation about the market conditions of adeveloping country characterized by an uncer-tain environment, both politically and economi-cally. The conceptual framework (Figures 1and 2) and research hypotheses are based ontheories of EO, learning capability, and firmgrowth. Model development is based on theapproach of Baker and Sinkula (2009). Theframework consists of two competing models

ALTINAY ET AL. 3

where OLC is first an exogenous construct(Model 1) and then employed as a mediator(Model 2).

EO has emerged as a multidimensional firm-level construct within the strategic managementand entrepreneurship literatures over the years.Originally proposed by Miller (1983) and latermodified by Covin and Slevin (1991), EOdescribes certain firm-level outcomes andmanagement-related preferences and beliefs withregard to an organization’s overall business oper-ations, its response to customers’ needs and prod-uct offerings and interactions with competitors(Covin, Green, and Slevin 2006). It consists offour main factors, namely innovativeness, proac-tiveness, risk taking, and autonomy (Lumpkinand Dess 1996). Innovativeness is connected withseeking creative solutions to problems and needs(Covin and Slevin 1989). It involves promotingand supporting novel ideas, and experimentationand creative processes that may lead to new prod-ucts. Proactiveness involves shaping the environ-ment by introducing new products, technologies,

and administrative techniques rather than merelyreacting to market change (Lumpkin and Dess1996). Risk taking involves the willingness tocommit significant resources to opportunitieswhich have a reasonable chance of costly failure(Lumpkin and Dess 1996; Miller and Friesen1983). Autonomy refers to the organization’s will-ingness to delegate responsibility to individualsor a team to take independent action in bringingforth an idea or a vision and carrying it through tocompletion (Lumpkin and Dess 1996). As a strate-gic choice, these dimensions of EO are embeddedin an organization’s philosophy, which drivesdecision-making and behavior toward creatingnew goods, pursuing new methods of productionor of offering services, and entering into newmarkets (Stevenson and Jarillo 1990). EO, there-fore, could be an important indicator of the wayin which an organization is structured and itsability to outperform competitors. As such, EO isparamount for improving a firm’s competitiveadvantage and performance. It contributes toorganizational transformation and strategic

Figure 2Conceptual Model 2

OLC

EO GROWTH

H3b(+)

OLC, organizational learning capability; EO, entrepreneurial orientation; GROWTH, SME growth.

Figure 1Conceptual Model 1

EO

OLC GROWTH

H3a(+)

H2(+)

H1

OLC, organizational learning capability; EO, entrepreneurial orientation, GROWTH, SME growth.

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renewal through the creation and combination oforganizational resources and competences(Wales, Gupta, and Mousa 2013; Zahra, Kuratko,and Jennings 1999). An entrepreneurially ori-ented firm engages in product innovation, under-takes risky ventures, and possesses proactiveness(Lumpkin and Dess 1996; Miller 1983). By search-ing for product/service-market prospects, entre-preneurial firms tend to concentrate on customerneeds and competitors’ offerings, thereby becom-ing more market oriented (Miles and Arnold1991; Morris and Paul 1987).

The analysis of learning has become anincreasingly important aspect of entrepreneur-ship research (Hakala 2011; Wang 2008). Morerecently, learning has been considered from astrategic perspective, as a strategic resource anda key contributor to the competitive advantageof small firms (Covin and Lumpkin 2011; Zhaoet al. 2011). Both learning orientation, concep-tualized as a firm’s values which influence itspropensity to create and use knowledge (Sin-kula, Baker and Noordewier 1997), and OLC,conceptualized as enablers of creation, acquisi-tion, transfer, and integration of knowledge(Jerez-Gomez, Cespedes-Lorente, and Valle-Cabrera 2005), influence a firm’s capability toengage in entrepreneurial activities. Learningorientation reflects values and norms repre-sented in a firm’s behaviors and processeswhereas OLC is seen as the ability of a firm tocreate an enabling platform to generate, trans-fer, and integrate knowledge and modify itsbehavior with a view to improving its perform-ance (DiBella, Nevis, and Gould 1996).

Despite the general consensus around theseuncontroversial notions, it needs to be acknowl-edged that there are still different views regard-ing the nature of learning at the organizationlevel. Some theorists view the organization as acollection of individuals (human perspective),while others view it as the systems, structures,and procedures of the organization (nonhumanperspective). These two different perspectivesmark different viewpoints in addressing the linkbetween learning and organizational perform-ance, with some scholars focusing on the capa-bilities of individual members (e.g., Guzzo,Jette, and Katzell 1985), others in terms of teams(e.g., Edmondson 2002), and others still on thecapacity of the organization as a whole toacquire, disseminate, utilize, and embed newknowledge (e.g., DiBella, Nevis, and Gould1996). Recently, Jerez-Gomez, Cespedes-Lorente, and Valle-Cabrera (2005) developed a

four-dimensional OLC framework which under-lines how the learning process stems from theknowledge acquisition of the individuals andthen progresses with the exchange and integra-tion of this knowledge until a corpus of collec-tive, organizational knowledge is created,including knowledge on mechanisms (routines,systems, etc.) by which the exchange of knowl-edge can be better fostered and embedded. Inso doing, the framework transcends the criticalissue about the level at which learning can takeplace and the connections between the individ-ual, teams, and the organization. Drawing onthis perspective, our intent is to present a holis-tic perspective of OLC as it relates to the phe-nomenon of EO. The view of OLC presentedhere, therefore, can be distinguished from otherperspectives that have focused on specific ele-ments of organizational learning as exemplifiedby Cohen and Sproull’s (1996) collection ofarticles on the wide range of approachesemployed in relevant literature.

Jerez-Gomez, Cespedes-Lorente, and Valle-Cabrera’s (2005) OLC framework hinges on theprinciple that the effective development of OLCrequires four dimensions, namely, managerialcommitment, systems perspective, opennessand experimentation, and knowledge transferand integration. Managerial commitmentinvolves the support of leadership for organiza-tional learning. People in managerial positionsshould acknowledge the importance of learningand actively promote the acquisition, creation,and transfer of knowledge (Nonaka and Takeu-chi 1995). Management should place learning atthe heart of strategy formulation and implemen-tation (Hult and Ferrell 1997; Ulrich, Jick, andGlinow 1993). Likewise, managers should con-vey and communicate the importance of learn-ing to the employees (Senge 1990; Slater andNarver 1995). Finally, management should playan instrumental role in initiating and managingchange through encouraging learning amongthe employees (Nonaka 1994; Nonaka andTakeuchi 1995). A systems perspective entailscreating a sense of identity and belonging to anorganization (Senge 1990; Sinkula 1994). Theorganization should be considered as a systemof shared mental models through which infor-mation is acquired, disseminated, and shared(Miller 1996; Senge 1990). This implies thatorganizational learning goes beyond individuallearning and acquires a collective nature (Jerez-Gomez, Cespedes-Lorente, and Valle-Cabrera2005). Therefore, the presence of a common

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language is seen as a crucial facilitator of knowl-edge sharing and integration (Grant 1996).Openness involves welcoming the arrival ofnew ideas both from internal and external envi-ronments allowing the generation and acquisi-tion of new knowledge (Leonard-Barton 1992;Sinkula 1994). Openness to new ideas and per-spectives also favors experimentation, an essen-tial aspect of generative learning (Jerez-Gomez,Cespedes-Lorente, and Valle-Cabrera 2005).Experimentation entails coming up with innova-tive solutions to current and future problems(Garvin 1993; Leonard-Barton 1992) and itrequires a culture stimulating creativity andlearning through making mistakes (Naman andSlevin 1993; Slater and Narver 1995). Knowl-edge transfer and integration refer to internaltransfer and integration of knowledge (Jerez-Gomez, Cespedes-Lorente, and Valle-Cabrera2005). These two interrelated processes shouldfacilitate the transfer of knowledge among indi-viduals without any internal barriers (Kofmanand Senge 1993; Nicolini and Menzar 1995).This requires transparent and abundant commu-nication through various platforms includingpersonnel meetings, forums, and workshops(Nonaka 1994; Slater and Narver 1995). Theknowledge transfer and integration taking placethrough these processes is, in turn, expected tolead to “collective ownership learning” and“organizational memory” (Chiva, Alegre, andLapiedra 2007).

The multidimensional nature of the OLCframework described above appears to us to beparticularly suited in application to SMEs. Ofcourse much work has already been conductedon learning in SMEs (see, inter alia, Cope 2005;Deakins and Freel 1998; Gibb 1997). This bodyof literature has highlighted that small firms arenot scaled-down versions of larger firms (uponwhich most of the research has focused) assmaller firms face different challenges (due toscale, resources, expertise, etc.) which may wellimpact EO (for instance, the four main factors ofEO identified by Lumpkin and Dess 1996). Suchwork has also brought to the fore how SMEentrepreneurs learn by doing, learn from trial-and-error, from peers, and from customers.However, much of this research has focused onthe entrepreneur as a unit of analysis ratherthan intrafirm level OLC, which constitutes ourfocus.

The measurement of the performance andgrowth of small businesses is a complex area,with different approaches proposed in the litera-

ture. Dobbs and Hamilton (2007) identified sixapproaches adopted by previous research tostudying small firm growth, namely: stochastic,descriptive, evolutionary, resource-based, learn-ing, and deterministic approaches. The stochas-tic approach to growth argues that there arenumerous factors that affect growth and/ordecline. While recognizing this, those studiesfollowing a descriptive approach are concernedwith how a small firm adapts internally in orderto grow. The evolutionary perspective to growthadvocates that small firm growth is contingentupon the interaction between internal and exter-nal factors. The resource-based view postulatesthat growth is primarily the result of idio-syncratic configurations and management ofresources. The learning approach emphasizesthe importance of knowledge acquisition andlearning by the employees and firm, positingthat learning created by the individuals and thefirm facilitates business growth. The determinis-tic approach to small firm growth argues thatvariations in growth can be explained by differ-ent variables related to people, the firm, and thebusiness environment. Studies exploiting theseapproaches contribute to our understanding ofsmall business growth through explaininggrowth promoted by managerial strategies(employee recruitment and development, prod-uct and market development, internationaliza-tion and collaboration), characteristics of theentrepreneur, environmental/industry specificfactors and characteristics of the firm (Reijonenet al. 2012). Though the research on the influ-ence of firm and the firm’s resources on growthis fairly robust, little research has been done onthe influence of strategic orientations on SMEgrowth. In particular, the combined effects ofEO and OLC have been neglected by previoussmall business management research.

In the empirical literature, a variety ofmeasures have been utilized to evaluate smallbusiness growth: sales volume (Basu and Gos-wami 1999; Fischer and Reuber 2002; Rue andIbrahim 1998); profit levels (Birley and West-head 1990); number of employees (Birley andWesthead 1990); and number of customersand increases in market share (Baldwin et al.1994). However, there are practical limitationswith respect to gathering reliable data aboutthese measures as small business owners areoften unwilling to provide and share thisinformation. Barkham et al. (1996) emphasizethat the least problematic growth measure-ment is sales turnover, which is always

JOURNAL OF SMALL BUSINESS MANAGEMENT6

recorded and can act as a reliable indicator ofsize and growth. This study, therefore, utilizessales growth as one of the indicators forgrowth. This is average annual sales growthfrom the business start-up to the present(Basu and Goswami 1999). However, in theirresearch into ethnic minority entrepreneur-ship, Fadahunsi, Smallbone, and Supri (2000)state that Pakistani and Indian Sikh respond-ents declined to answer questions about theirsales turnover because of tax reasons. Takingthis into consideration, it is thought that utiliz-ing sales turnover alone as an indicator ofbusiness growth may be insufficient forextracting growth-related information. Ireland,Reutzel, and Webb (2005) emphasize thatalthough there is little evidence of the impactof EO on job creation, job creation has beenan important target of government support forsmall business growth. In view of this, Ire-land, Reutzel, and Webb (2005) call for furtherresearch examining the role of firms’ entrepre-neurship on job creation. Given that the firmscomprising our sample include gift shops andcafes, it is more likely that increased marketshare or sales might be more desirable orindeed achievable than an increase in thenumber of employees (given the size of theworking population in what is a constrainedeconomy). However, for the sake of compre-hensiveness we also use employment growthas one of our performance measures. Asunderlined in previous studies (Altinay andAltinay 2006; Barkham et al. 1996; Naman andSlevin 1993), measuring growth of SMEs is achallenging, complex, and difficult issue, withpractical limitations with respect to gatheringreliable data as small business owners areoften reluctant to provide and share financialinformation. This study therefore relies onmore than one measure to quantify the per-formance of firms. The measurement ofgrowth consists of sales growth, market sharegrowth, and employment growth.

Hypotheses DevelopmentThe Effects of EO on SME Growth

EO is crucial in improving an SME’s competi-tive advantage and performance. Empirical stud-ies have largely found that firms with a moreEO perform better (Baker and Sinkula 1999;Wales, Gupta, and Mousa 2013; Wiklund 1999).EO contributes to organizational transformationand strategic renewal through creation and

combination of organizational resources andcompetences (Zahra, Nielsen, and Bogner1999). An entrepreneurially oriented firmactively innovates through new products andservices, acts proactively in order to identifychanging consumer needs, responds to competi-tors moves, undertakes risky ventures, and dele-gates responsibility to their employees foreffective decision-making (Lumpkin and Dess1996). Entrepreneurship scholars have alsoattempted to explain the performance of SMEsby investigating their EOs. EO is a firm-levelconstruct that encourages certain SME-level out-comes and management-related preferenceswith regard to an organization’s overall businessoperations, product offerings, interactions withcompetitors, risk taking, and management struc-ture (Covin, Green, and Slevin 2006; Lumpkinand Dess 1996). As a strategic choice, it is anembedded organizational philosophy that drivesdecision-making and behavior toward creatingnew goods, new methods of production andnew geographical and/or product markets (Ste-venson and Jarillo 1990).

Recent years have raised interest toward a bet-ter understanding of the relationship between EOand growth. High growth has been linked to afirm’s entrepreneurial behavior including innova-tiveness, proactiveness, and risk taking behavior(Casillas, Moreno, and Barbero 2010; Covin,Green, and Slevin 2006; Dess and Lumpkin 2005;Madsen 2007; Wang and Altinay 2012). In theirstudy of family, small and medium sized compa-nies in Spain, Casillas, Moreno, and Barbero(2010) found a positive relationship between EOand growth, in particular, the positive influenceof innovativeness and proactiveness on profitabil-ity. Confirming the positive relationship betweenEO and growth, Covin, Green, and Slevin (2006)found that the relationship between EO and salesgrowth was positive among manufacturing firmsthat employ autocratic decision-making andexhibit an emergent strategy formation process.Similarly, Dess and Lumpkin (2005) state thatfirms grow through new venture opportunitiesand strategic renewal. Madsen (2007) who under-took a longitudinal analysis to understanding thegrowth of Norwegian SMEs also found that thereis a positive relationship between EO andemployment growth. They contributed to the lit-erature by identifying that resources that may beinimitable also have some influence on perform-ance compared to competitors. Perks (2006) alsofound a positive relationship between EO andgrowth of SMEs in France and Germany and

ALTINAY ET AL. 7

explained it with reference to the characteristicsof these firms, in particular their managementstyles. Given these arguments, we have set ourhypothesis as:

H1: EO has a positive effect on SME growth (salesgrowth, market share growth, and employ-ment growth).

The Effects of OLC on SME GrowthThere is no consensus in the literature about

the link between OLC and business perform-ance (Popper and Liphitz 2000; Prieto andRevilla 2006). The divergence of views is due tothe fact that cause-and-effect relationships arenot necessarily straightforward and can hardlybe defined clearly (Yeo 2003). One of the rea-sons is that the effects of OLC on performancemay occur step-by-step and creating the mecha-nisms to develop the capacity to learn may becomplex. Another reason is that many factorsaffect organizational outcomes including theorganization’s environment, leadership, andorganizational culture (Prieto and Revilla 2006).In spite of conflicting perspectives, there is clearevidence that OLC may improve business per-formance. Senge (1990) argues that, over a longperiod, superior performance depends on OLC.Other scholars also recognize the importance ofOLC as crucial to overall performance (Nahapietand Ghoshal 1998; Soo, Devinney and Midgley,2004). Recent empirical studies also give sup-port to the impact of OLC and different forms ofknowledge on performance (Palacios-Marques,Ribeiro-Soriano and Gil-Pechuan 2011; Prietoand Revilla 2006; Theriou and Chatzoglou2009). Organizations with a greater capacity tolearn are able to identify changing consumerneeds and wants more easily than their competi-tors, leading to better organizational perform-ance (Bontis, Crossan, and Hulland 2002; Prietoand Revilla 2006; Tippins and Sohi 2003). Con-sequently we propose the following hypothesis:

H2: There is a positive relationship between OLCand SME growth (sales growth, market sharegrowth, and employment growth).

The Effects of OLC and EOThere is convincing evidence for both the

view (Bell, Whitwell, and Lukas 2002) that learn-ing may have a two-way interaction with EO, andthe view (Hakala and Kohtamaki 2011) that

learning capability enables companies to success-fully combine different orientations to generateperformance enhancing behaviors. Most previ-ous research agrees that OLC influences EO posi-tively. Floyd and Wooldridge (1999) propose thatknowledge creation in corporate entrepreneur-ship contributes to the renewal of OLC leading tonovel entrepreneurial ideas and behaviors. Weer-awardena (2003) and Weerawardena and O’Cass(2004) state that a market-focused learning capa-bility leads to higher degrees of entrepreneur-ship, as market driven firms are superior inmarket sensing and customer-orientated capabil-ities. Confirming these claims, Garcia-Morales,Llorens-Montes, and Verdu-Jover (2007) find thatthe most innovative and entrepreneurial firmshave effective learning mechanisms. Similarly,investment in employee training, education, andskill development is a precursor of entrepreneur-ial activities (de Jong and Vermuelen 2006).Siguaw, Simpson, and Enz (2006) advocate thatan organization should have a strong learningphilosophy in order to be entrepreneurial.

It is also well documented that EO contrib-utes to the learning capability of a firm (Sinkula,1994). Entrepreneurial firms operate in com-plex, uncertain, and turbulent environments thattend to push firms toward knowledge acquisi-tion and exploitation (Wang 2008). Such firmsare more proactive and, by and large, exten-sively engage in environmental scanning activ-ities involving information acquisition anddissemination (Huber 1991). They are innova-tive and risk tolerant, constantly exploring andexperimenting new business ideas through cre-ating mechanisms for knowledge acquisitionand exploitation (Slater and Narver 1995). Usingdata from 213 medium-to-large U.K. firms,Wang (2008) found that EO positively influen-ces learning and broadens scope for learningthrough stimulating firms to challenge the statusquo and introduce flexibility and change in theirway of doing things. Given all this, we formu-late our hypotheses as:

H3a: OLC influences EO positively.H3b: EO influences OLC positively.

The Mediating Effects of EO and OLCon SME Growth

Starting with Floyd and Wooldridge (1999),there is a stream of research that claims thatOLC has a positive relationship with EO. Thereis also evidence in the literature suggesting that

JOURNAL OF SMALL BUSINESS MANAGEMENT8

OLC has a positive impact on EO, which inturn, has a positive impact on firm performance.These studies generally view EO as an exoge-nous construct which influences organizationalperformance through knowledge creation (Li,Huang, and Tsai 2009) and market information(Keh, Nguyen, and Ng 2007). Reporting onthe results of a survey, McAdam, Armstrong,and Kelly (1998) concluded that continuouslearning and improvement leads to increasedentrepreneurial activities and ultimately to betterorganizational performance. In a study of ITcompanies, Koc (2007) emphasized that organi-zational learning creates a strong innovationcapacity and performance through acquisition,integration, and exploitation of new knowledge.In their studies of SMEs in Turkish Science andTechnology parks, Ar and Baki (2011) alsofound that OLC has a positive impact on processinnovation and ultimately on performance.Thus, learning mechanisms established inter-nally enable firms to question the status quo ona regular basis and push for continuousimprovement, leading to a more flexible andadaptable way of doing things. Such anapproach increases both the productivity andefficiency of firms. Aragon-Correa, Garciamor-ales, and Cordonpozo’s (2007) survey resultsalso showed that firms’ ability to engage inentrepreneurial activities and innovate success-fully is influenced by their OLC. The learningcapability of firms enables them to experimentwith new ideas and deliver superior new serv-ices and products leading to business growth.On this basis, we have set our hypothesis as:

H4a: The OLC-performance relationship is medi-ated by EO; OLC has a positive impact on EO,which, in turn, has a positive impact on SMEgrowth (sales growth, market share growth,and employment growth).

Although the literature supporting this view islimited, it is also argued that EO has a positiveimpact on OLC which, in turn, has a positiveimpact on firm performance (Wang 2008).Covin, Green, and Slevin (2006) state that OLCis a crucial dimension of firms’ strategic activ-ities. How firms choose to develop their learn-ing mechanisms, use different sources forlearning and inform and refine their strategicdecisions and activities influences the effect ofEO on performance. Recognizing this, in herstudy of 213 medium-to-large U.K. firms, Wang(2008) investigated the EO-performance rela-

tionship by incorporating learning as a media-tor. It became apparent that OLC mediates theEO-performance relationship. EO leads to thestimulation of new ideas and transformation ofroutine business practices, creating a responsiveorganizational environment to market opportu-nities. Wang (2008, p. 649) therefore concludedthat EO has a positive impact on learning orien-tation which, in turn is conducive to firm per-formance. In line with this, Slater and Narver(1995) also argued that OLC underpins firms’self-renewal ability and creates a platform thatdrives continuous improvement in entrepre-neurial activities and performance. We thereforeset our hypothesis as:

H4b: The EO-performance relationship is medi-ated by OLC; EO has a positive impact onOLC which, in turn, has a positive impact onSME growth (sales growth, market sharegrowth, and employment growth).

MethodSetting and Sample

The research hypotheses were tested usingdata collected from SME owners in NorthernCyprus services and retail organizations includ-ing hotels, restaurants, rent-a-car, gift shops,retail shops, cafes, and travel agencies. Retail andtourism are the two primary industries repre-sented in this study. SMEs in this sample havebetween 2 and 50 employees. We selected 500SMEs from the Business Directories of Trade andCommerce Associations and other publishedbusiness directories in the country with the aimof achieving a minimum of 250 responses inorder to test our model via the Structural Equa-tion Modeling approach (J€oreskog and S€orbom1996).

The first step in conducting the survey was dis-tributing the questionnaires to the owners andexplaining to them the aim of our study. A totalnumber of 400 questionnaires were personallydistributed to the owners of the small andmedium sized touristic organizations by ourresearch team. The participants were kindlyrequested to fill out the questionnaires in a self-administered manner. The managers were alsogiven an assurance about confidentiality. Approx-imately 40 questionnaires were not returnedalthough the owners were reminded severaltimes via telephone and e-mail. About 10 ques-tionnaires were biased and thus excluded from

ALTINAY ET AL. 9

the data evaluation process. By the cutoff date fordata collection, a total number of 350 question-naires were personally retrieved, yielding aresponse rate of 87.5 percent. More than half ofresponding companies (57 percent) were familyfirms. The mean of number of employees was10.7. As mentioned before, a large majority ofsample firms (83 percent) had fewer than 10employees. The oldest firm in our sample was 40years old while the mean organizational age forthe sample was 10 years.

This study thus collected self-reported datafrom single informants, which introduces thepotential for common method variance bias.First, to alleviate concerns about commonmethod bias, we ensured the anonymity of therespondents to reduce evaluation apprehension.Next, we conducted the Harman’s one-factortest (Podsakoff and Organ 1986) to rule out anypossibility for common method variance. Weentered all variables into an exploratory factoranalysis (EFA) which showed that more thanone factor emerged from this analysis. In addi-tion, no factor accounted for the majority of var-iance in these variables. The highest variancewas 28.9 percent. As a result, we concluded thatthe variance in this study can be attributed tothe constructs of interest rather than to the mea-surement method.

MeasuresAs the knowledge accumulation around the

construct of EO has been substantial and stud-ies mainly used the measure initially devel-oped by Miller (1983) and later modified byCovin and Slevin (1989). The present studyalso adopts this widely used measure, whichis sometimes referred to as the “Miller/Covinand Slevin scale” (Brown, Davidsson, andWiklund 2001). In addition, following the sug-gestions of previous studies (see Wang 2008),this study adapted two items from Miller andFriesen (1983) and one item from HurtJoseph, and Cook (1977) in order to be ableto measure a firm’s overall propensity forinnovative behavior. In total, 12 items wereincluded in the interview questionnaire tomeasure the EO construct using seven-pointLikert scales.

Consistent with our previous discussion onthe different perspectives on OLC and its multi-dimensional nature, it should not come as a sur-prise that the OLC construct has been captureddifferently in different studies. Although varioustheoretical studies have identified different

dimensions (Crossan, Lane, and White 1999;Crossan et al. 1995; Senge 1990; Slater andNarver 1995), most of the measurement scalesadopted in the empirical literature to captureOLC do not adequately reflect the many dimen-sions identified nor how learning (as a processof which knowledge is an outcome) can betranslated between levels. As discussed earlierin our theoretical review section, Jerez-Gomez,Cespedes-Lorente, and Valle-Cabrera (2005) isone of the few studies that proposed a viablesolution to this issue by considering OLC to be alatent multidimensional construct inasmuch asits full significance lies beneath the variousdimensions that go toward its makeup. It is forthis reason that we adopt the scale of Jerez-Gomez, Cespedes-Lorente, and Valle-Cabrera(2005), where the OLC construct consists of 16variables (measured on a seven-point Likertscale). According to Jerez-Gomez, Cespedes-Lor-ente, and Valle-Cabrera (2005), an organizationshould show a high degree of learning in eachand every one of the dimensions defined, to beable to state that its OLC is high. These dimen-sions (managerial commitment, systems per-spective, openness and experimentation, andknowledge transfer and integration) sum up theaspects seen as the core elements needed for anorganization to develop a learning capability,and constitute the organizational learning struc-ture of their conceptual model. Significantly,such a model recognizes the role of individuallearning and its influence, direct and indirect,on the way in which organizations “learn” whilealso accounting for the fact that although OLChas its roots in individual learning (Senge 1990),the dynamic process that leads to OLC develop-ment goes beyond the individual learning of theorganization’s different members, implyingmoving among the different levels of learning inaction and knowledge outcomes; going fromthe individual to the team level, and then to theorganizational level and back again (Argyris andSch€on 1978).

To improve the robustness of our models,we included two (firm-level) control variables.First, we controlled for organizational age,which was measured as the difference betweensurvey year (2011) and the year in which thecompany was founded. The second control vari-able was a binary dummy taking the value ofone if the firm was family-owned, and the valueof zero otherwise.

As noted in our previous discussion, thepresent study employs three different measures

JOURNAL OF SMALL BUSINESS MANAGEMENT10

to quantify the performance of firms. The mea-surement of growth consists of sales growth,market share growth, and employment growth.Growth was measured as a percentage ofgrowth over the past two years.

Data AnalysisWe follow the approach of Baker and Sin-

kula (2009) by viewing OLC and EO constructsas unidimensional. First, to establish that OLCand EO are unidimensional and that their respec-tive variables do cross-load on each other, weconduct EFA. Next, based on EFA results andpotential construct refinements, we posit a mea-surement model that confirms the factor structureof latent variables. Last, we employ a structuralequation model (SEM) to test the relationshipsbetween two latent variables and three manifestvariables pertaining to growth (sales growth,market share growth, and employment growth).The posited model is tested using maximum like-lihood estimation which has been found to over-come the problems created by violations of thenormality assumption (Anderson and Gerbing1988; Bentler 1983). Both confirmatory factoranalysis and the SEM estimation are performedusing the Mplus 6.1 statistical program.

The mediation analysis in this study is basedon the recommendations of Zhao, Lynch, andChen (2010) who claim that the mediation spec-ifications of Baron and Kenny (1986) are coarseand misleading. That is, as the relationshipbetween OLC and three growth variables is notsignificant, based on Baron and Kenny (1986)one cannot test for partial or full mediationthrough EO. However, Zhao, Lynch, and Chen(2010) argue that even if there is no direct effectof the exogenous construct on the outcome,there is still a possibility for indirect-onlymediation.

ResultsModel Constructs

EFA with EO and OLC showed that when atwo-factor solution was entered, each variablewould load on its specified construct. That is, allEO variables loaded on the first factor and hadfactor loadings between 0.74 and 0.54. As forOLC, we removed three variables representingOLC due to low factor loadings (< 0.40) (Hair,Black, Babin, Anderson, and Tatham 2006).Using the same cutoff value (0.40), we deter-mined that no variables loaded on more thanfactor, which denotes that cross loading is not a

concern here. The refined OLC construct con-sisted of 13 variables whose loadings rangedbetween 0.74 and 0.48.

Next, we assessed the reliability and constructvalidity of manifest variables representing thetwo exogenous constructs (OLC and EO). First,we used Cronbach’s alpha to measure unidimen-sionality of the key constructs (OLC and EO).Both constructs had an acceptable internal consis-tency based on the 0.70 threshold value of Nun-nally (1978) (Table 1). That is, OLC and EO hadalpha values of 0.88 and 0.88, respectively, which

Table 1Measurement Scale Properties

(N 5 350)

Indicator

CompletelyStandardized

LoadingsError

Variance

EO AVE 5 0.52EO1 0.74* 0.54EO2 0.74* 0.59EO3 0.73* 0.60EO4 0.52* 0.75EO5 0.51* 0.66EO6 0.68* 0.52EO7 0.67* 0.59EO8 0.64* 0.62EO9 0.67* 0.59EO10 0.67* 0.58EO11 0.64* 0.60EO12 0.60* 0.63OLC AVE 5 0.54C1 0.60* 0.57OLC2 0.55* 0.61OLC3 0.70* 0.47OLC4 0.74* 0.45OLC5 0.68* 0.53OLC6 0.70* 0.52OLC7 0.65* 0.55OLC8 0.59* 0.59OLC9 0.67* 0.47OLC10 0.65* 0.52OLC11 0.52* 0.77OLC12 0.51* 0.53OLC13 0.62* 0.44

*Denotes significance at the .01 level.AVE, average variance extracted; OLC, organi-zational learning capability, EO, entrepreneur-ial orientation.

ALTINAY ET AL. 11

show that both constructs are unidimensional.We also checked for composite reliability (Fornelland Larcker 1981). Both constructs had accepta-ble composite reliability (EO 5 .89; OLC 5 .89).Next, we checked for construct validity which isdisclosed through convergent and discriminantvalidity. Convergent validity can be detected fromthe t value of each indicator (Anderson and Gerb-ing 1988; Bagozzi and Lynn 1982). As can be seenin Table 1, all indicator loadings had significant tvalues (p< .01). We used Average VarianceExtracted (AVE) as another measure to check forconvergent validity (Fornell and Larcker 1981).Both constructs had AVE values of over 0.50 (seeTable 1) which offered support for convergentvalidity. We also followed up by constraining thecorrelation parameter between the constructs at1.0 and then observing the Chi-square differencevalues for the unconstrained and constrainedmodels. Our results show that the Chi-squarevalue for unconstrained model (v2 5 419.55,df5 274) was significantly lower than that of theconstrained model (v2 5 1,206.72, df 5 386). Thesignificant Chi-square difference between the twomodels demonstrated that discriminant validityheld for the measurement model.

While the Chi-square value for the measure-ment model was significant (v2 5 419.55,df 5 274, p< .01), we followed J€oreskog andS€orbom’s (1993, p. 309) note that “since chi-square is N 2 1 times the minimum value of thefit function, the chi-square test tends to be largein large samples.” As a result, to evaluate ourmodel, we looked at commonly used incremen-tal goodness-of-fit indices: the Tucker-LewisIndex (TLI) and the comparative fit index (CFI).The TLI value of 0.95 for our model implies thatthe proposed measurement model demonstratesa good fit to data. The CFI value produced by

our measurement model (0.94) denotes a goodfit (Bentler 1992). Next, we checked residualmeasures of the model. The standardized rootmean square residual (SRMR) value for the mea-surement model was 0.05 which is indicativeof a well-fitting model as suggested by thethreshold value of 0.05 (Byrne 1998). The otherresidual measure, the root means error ofapproximation (RMSEA) value was 0.05 whichis considered satisfactory (Hair et al. 2006).

As can be seen in Table 2, EO and OLC hadsimilar means. The same can be said about salesgrowth and market share growth. Sales growthhad the highest mean and highest standarddeviation among three growth measures. Theresults also show that OLC and EO were highlycorrelated (0.60). EO was significantly correlatedwith sales growth and market share growth.However, OLC did not have significant correla-tions with the three performance measures.

Hypothesis TestingThis section investigates two structural mod-

els. The first model (Model 1) is based on thedepiction of the conceptual model in Figure 1and hypotheses which make up the empiricalside of this study. In Model 1, OLC is an exoge-nous construct, EO is a mediator and the threegrowth measures are dependent variables. Thisis our main model which we use to test Hypoth-eses 1, 2, 3a, and 4a. Model 2 is a competingstructural model where EO is an exogenousconstruct, whereas OLC is a mediator betweenEO and growth. Model 2 is employed to testHypotheses 3b and 4b. It should be noted thatorganizational age and firm type are used ascontrol variables in both models. As can be seenin Table 3, v2 value is significant, which could

Table 2Descriptive Statistics and Correlations

Variables Mean S.D. 1 2 3 4 5

1. EO 4.50 1.18 12. OLC 4.49 1.04 0.60* 13. Sales Growth 5.64 19.82 0.25* 0.15 14. Market Share Growth 5.14 15.03 0.11* 20.01 0.67* 15. Employment Growth 2.43 14.34 0.04 0.02 0.36* 0.37* 1

*Denotes significance at the .05 level.OLC, organizational learning capability; EO, entrepreneurial orientation; S.D., standard deviation.

JOURNAL OF SMALL BUSINESS MANAGEMENT12

be attributed to large sample size (N 5 350). Theevaluation of fit indices reveals that the modelachieves a good fit (CFI 5 0.92, TLI 5 0.92,RMSEA 5 0.05, SRMR 5 0.05) (Table 3).

H1 predicted a significant positive relation-ship between EO and growth (sales growth, mar-ket share growth, and employment growth).This hypothesis is only partially supported. Theresults in Table 3 indicate that EO has a positiveand significant influence on sales growth aftercontrolling for organizational age and firm type(t 5 3.01, p< .003). Similarly, the relationshipbetween EO and market share is significant andpositive, which is also consistent with H1(t 5 1.99, p< .044). Last, we found that there is

no significant relationship between EO andemployment growth. In the meantime, organiza-tional age had a significant negative relationshipwith all three growth variables. Conversely, firmtype is not significantly related with growth vari-ables. The partial support for H1 is consistentwith previous studies which find a positive sig-nificant relationship between EO and growth(Casillas, Moreno, and Barbero 2010; Covin,Green, and Slevin 2006; Wang and Altinay 2012).

H2 predicted that there is a direct positiveeffect of OLC on growth (sales growth, marketshare growth, and employment growth). Resultsshow that the relationship between OLC andgrowth measures was not significant in all three

Table 3Structural Equation Results and Mediation Analysis

Model 1 Model 2

v2 5 422.73 v2 5 422.73

CFI 5 0.92 CFI 5 0.92

TLI 5 0.92 TLI 5 0.92

RMSEA 5 0.05 RMSEA 5 0.05

SRMR 5 0.05 SRMR 5 0.05

Hypothesized Path Direct Effect Indirect Effect Supported

Model 1H1: EO ! SALES GROWTH 0.24 (3.01)** — YESH1: EO ! MARKET SHARE GROWTH 0.16 (1.99)* — YESH1: EO ! EMPLOYMENT GROWTH 20.02 (0.78) — NOH2: OLC ! SALES GROWTH 20.01 (20.09) — NOH2: OLC ! MARKET SHARE GROWTH 20.13 (21.72) — NOH2: OLC ! EMPLOYMENT GROWTH 0.04 (0.53) — NOH3a: OLC ! EO 0.60 (14.66)** YESH4a: OLC ! EO ! SALES GROWTH — 0.14 (3.13)** YESH4a: OLC ! EO ! MARKET SHARE GROWTH — 0.10 (2.18)* YESH4a: OLC ! EO ! EMPLOYMENT GROWTH — 20.01 (20.28) NOModel 2H3b: EO ! OLC 0.49 (8.08)** — YESH4b: EO ! OLC ! SALES GROWTH — 20.00 (20.09) NOH4b: EO ! OLC ! MARKET SHARE GROWTH — 20.06 (21.70) NOH4b: EO ! OLC ! EMPLOYMENT GROWTH — 0.02 (0.52) NO

*p� .05**p� .01T-values are shown in parentheses.

ALTINAY ET AL. 13

cases. Consequently, H2 is not supported, whichcontradicts the findings of Aragon-Correa, Gar-ciamorales, and Cordonpozo (2007).

H3a predicted that OLC has a positive and sig-nificant influence on EO. The analysis supportsthis proposition (t 5 14.16, p< .000). In addition,we find that organizational age is negativelyrelated to EO. The second control, firm type, doesnot have significant effect on EO.

H4a predicted that EO mediates the relation-ship between OLC and the three growth meas-ures. As the relationship between OLC and threegrowth measures was not significant, we canonly test for indirect-only mediation (Zhao,Lynch, and Chen 2010). That is, we investigatethe paths from OLC to EO, and EO to growth toconfirm whether there is an indirect-only media-tion effect of OLC on growth. The mediationanalysis showed that the indirect effect ofOLC on sales growth was 0.14 (t 5 3.13,p< .003). This finding lends support for H4a.Similarly, EO mediates the relationship betweenOLC and market share growth (0.10, t 5 2.18,p< .047), which again is consistent with H4a. Asneither OLC nor EO had a significant relation-ship with employment growth, H4a was notsupported. We conclude that indirect-only medi-ation is present based on sales growth and mar-ket share growth. This finding sheds some lightinto the intriguing effect of OLC on organiza-tional performance, particularly in a singleindustry setting (i.e., services). That is, we reportthat firms with greater learning capability areable to identify the changing consumer needsand wants better than their competitors, leadingto better organizational performance. In otherwords, the identification of these needs is alearning capability matter. Conversely, the provi-sion of products and services that customersexpect is a fruit of EO which shows that OLCdrives business performance via EO. Our resultsare in concert with the study of Aragon-Correa,Garciamorales, and Cordonpozo (2007) whoshowed that innovation mediated the relation-ship between OLC and performance. In theirstudy, the indirect effect of OLC on performancewas higher than its direct effect (0.41 vs. 0.24).

We used a competing model (Model 2 in Fig-ure 2), where EO was an exogenous construct.First, we looked at the relationship between EOand OLC. Then, we investigated whether OLCmediates the relationship between EO andgrowth (sales growth, market share growth, andemployment growth). H3b predicted a positiverelationship between EO and OLC after control-

ling for organizational age and firm type. As canbe seen in Table 3, results show that EO is sig-nificantly and positively related with OLC(t 5 8.08, p< .000). This finding offers supportfor H3b. It should be noted that the path coeffi-cient in H3b (0.49) is lower than H3a (0.60),which denotes that OLC is a stronger determi-nant of EO after we account for the effects ofcontrol variables and outcome variables. H4bpredicted that OLC is a mediator between EOand growth. As can be seen in Table 2, the indi-rect effect of EO on three growth variables wasnot significant, which leads us to conclude thatOLC does not mediate the relationship betweenEO and growth measures.

DiscussionThe findings of this study offer interesting

insights into the management of SMEs. First,consistent with the findings of previous research(Casillas, Moreno, and Barbero 2010; Covin,Green, and Slevin 2006; Wang and Altinay2012), we find a positive relationship betweenthe EO and SME growth. Firms which activelyinnovate (new products and services), act proac-tively to grasp market opportunities, and under-take risks, tend to perform better. Interestingly,however, this positive relationship between EOand growth is evident between EO and marketshare and sales growth measures, but notbetween EO and employment growth. This find-ing contradicts the findings reported by Madsen(2007) who undertook a longitudinal analysis tounderstand the growth of Norwegian SMEs andfound that there is a positive relationshipbetween EO and employment growth. This con-flicting evidence could be due to the differencesof the contexts in which the SMEs of these twostudies operate. The sample of our study is pri-marily comprised of SMEs from labor intensiveindustries, namely, services and retailing. Itcould well be that the SMEs in these industrieskeep their labor force at the minimal level inorder to minimize the cost of their operations.In addition, in the case of small businesses onthe island, there is a tendency to employ familymembers or friends as voluntary workforcerather than officially increasing the number ofemployees, which would obviously increase thecost of operations. Moreover, the type of organi-zations in our sample alongside the lack ofexporting capability, inevitably constrain furtherthe capacity of such organizations to employmore staff. Finally, returning to the point made

JOURNAL OF SMALL BUSINESS MANAGEMENT14

by Ireland, Reutzel, and Webb (2005) about theimpact of EO on job creation, it needs to beemphasized that this tends to be a measureemployed by policymakers and not necessarilyby entrepreneurs/owner-managers.

Second, unlike previous research (Bontis,Crossan, and Hulland 2002; Prieto and Revilla2006; Tippins and Sohi 2003), this study showsthat there is no relationship between OLC andgrowth, irrespective of the growth measureused. This could be due to the fact that thecause-and-effect relationship between OLC andperformance is not necessarily straightforward;the influence of OLC on growth occurs overmany steps and is very difficult to define (Yeo2003). In addition, as Prieto and Revilla (2006)point out, organizational outcomes such as betterperformance can be influenced by many otherfactors such as an organization’s environment,leadership, and organizational culture. After all,as noted in the introduction, the North Cypruseconomy can be considered as a “closed” econ-omy. Its opportunities to market products andservices are limited to only two markets: Turkeyand North Cyprus. On one hand, this state ofaffairs protects the country’s economic environ-ment from the global economic crisis, therebyreducing turbulence and the degree of highercompetitiveness that follows. On the other hand,it creates demand uncertainty. In addition, thereis an “over protective” government and publicsector involvement in the economy. The positiverelationships between EO and growth could beexplained by the government and public sector’sinvolvement where they act as suppliers of sup-port (information, financial capital, tax exemp-tions and subsidies, etc.) for the production ofproducts and services and at the same time theyare the largest buyers of products and services(Katircioglu 2010; Mehmet 2010).

Third, the findings of this study provide sup-port to the view that there is a two way interac-tion between OLC and EO (see Bell, Whitwell,and Lukas 2002; Hakala and Kohtamaki 2011).However, it needs to be emphasized that in thisstudy the influence of OLC on EO stems fromthe latent dimensions underlying the frameworkwe adopted (Jerez-Gomez, Cespedes-Lorente,and Valle-Cabrera 2005), from which the OLCmeasurement scale was developed. In thisrespect, a fundamental contribution of our find-ings can be identified in the OLC conditions thatinfluence EO (which obviously differ from thoseof other studies which employ a different OLCconstruct, e.g., Alegre and Chiva 2013). These

conditions, linked to the framework’s dimen-sions, are exemplified by managerial commit-ment toward learning (leadership support), asystem approach that builds upon and tran-scends individual learning endeavors, an attitudewelcoming openness toward new ideas andexperimentation, and the establishment of“barrierless” processes of knowledge transferand integration. This suggests that EO and OLCneed to be related to the strategic goals of theSMEs and need to be aligned in order for theSMEs to take full advantage of market opportuni-ties. This view also adds to the arguments ofWiklund and Shepherd (2005) and Baker andSinkula (2009) who argue that SMEs need toadopt a combined approach to their strategicpostures, as relying only on one—OLC or EO—could create temporary advantages but not sus-tainable competitive advantages. This insight isparticularly relevant for SMEs often competing in“narrow markets,” such as North Cyprus wherepotential growth can be limited, but competitiveadvantage is essential. SMEs, therefore, need toadopt a more strategic approach to managementand develop strong and effective learning mech-anisms that could stimulate entrepreneurial activ-ities. EO can be developed over time throughconsistent investment in resources that couldenhance learning capability. Likewise, SMEsneed to engage in entrepreneurial activities andcreate platforms for exploration and experimen-tation of new ideas to broaden their scope forlearning and pursue new business endeavors.

Finally, and most importantly, this studytested the mediating effects of both the EO andOLC on SME growth. Unlike previous research(Covin, Green, and Slevin 2006; Wang 2008), thefindings of this study showed that the EO-SMEgrowth relationship is not mediated by OLC.While the lack of support for the mediation effectof OLC on performance may seem surprising, itshould be noted once again that our OLC con-struct differs from other studies that look at themediating effect of OLC on performance (e.g.,Wang 2008). However, we find that the OLC-SME growth relationship is mediated by EO; thatis, OLC has a positive impact on EO which, inturn, has a positive impact on SME growth. Thisfinding provides empirical support to the argu-ments of Aragon-Correa, Garciamorales, andCordonpozo (2007) and Ar and Baki (2011) whoidentified the mediating role of EO in the OLC-performance relationship. This finding also cor-roborates the views of Hakala and Kohtamaki(2011) and Wiklund and Shepherd (2005) who

ALTINAY ET AL. 15

argue that a holistic and strategic approach tounderstanding SME growth is crucial because theorientations complement each other leading toimproved SME growth. SMEs that combine EOand OLC are likely to perform even better thanfirms adopting only one. Therefore, SMEs needto align EO and OLC and achieve congruencebetween these orientations in order to generateperformance enhancing behaviors.

ConclusionsThis paper makes two distinct and timely

contributions to the small business managementliterature. First, this paper is one of those fewstudies adopting a strategic management per-spective to understanding the combined andsimultaneous effects of orientations on variousmeasures of growth in a small business context.Previous research has identified six distinctapproaches to studying SME growth (Dobbsand Hamilton 2007). However, recognizing thedeficiencies of each approach, researchers(Baker and Sinkula 2009; Wang 2008) called forthe adoption of a more strategic approach tounderstanding SME growth encouraging furtherresearch into the combined and simultaneouseffects of orientations on growth in a small busi-ness context. Responding to these calls, thisstudy investigated SME growth through analyz-ing the combined effects of EO and OLC onSME growth measures in terms of sales growth,market share growth, and employment growth.Reporting on 350 SMEs, this study developed amodel that uses a multiconstruct framework andsystematically examined the influence of EOand OLC on SME growth. Our results demon-strate that there is a positive relationshipbetween EO and growth when the latter ismeasured in terms of sales growth and marketshare growth, but not in terms of employmentgrowth. The findings of this study also demon-strated that there is a positive, bilateral relation-ship between OLC and EO in the context ofSMEs. In particular, this study’s findings suggestthat an aligned and congruent EO and OLC areessential for the SMEs to take advantage ofmarket opportunities. More specifically, OLCappears to be an important contributor to theproactive entrepreneurial engagements and sus-tainable growth of SMEs. This finding denotesthat EO and growth of SMEs could be stimu-lated and facilitated through acquiring andexploiting knowledge thorough various learningmechanisms and channels in SMEs.

Second, the study investigated the mediatingeffects of EO and OLC on SME growth, aresearch avenue where there is a dearth ofempirical studies. In contrast to the argumentsof Wang (2008) and Covin, Green, and Slevin(2006), this study found that the EO-Growthrelationship is not mediated by OLC in SMEs.However, when there are entrepreneurialengagements, OLC augments EO and thusaffects growth positively. Such a finding andcontribution is important because this studydemonstrates that EO facilitates OLC throughbroadening the scope of SMEs for learning anddeveloping an adaptable and flexible approachto the exploitation of market opportunities.Hence, it is through EO that SMEs maximize theimpact of OLC on firm performance.

While acknowledging some limitations of ourstudy, we also offer recommendations for fur-ther research. First, as in this study the surveydata are cross sectional in nature, it was not pos-sible to capture the dynamic interplay betweenOLC and growth. We recommend that futurework makes use of longitudinal data in order tobetter assess the relationship between OLC andvarious measures of growth. Second, othermeasures of organizational growth such as prof-itability and return on investment could be con-sidered. Third, although our study controlled forsome firm characteristics, another novelty that isacutely needed at the empirical level is the utili-zation of contextual and environmental variablesas moderators or control variables in measuringthe relationship between OLC and growth.While Wang (2008) considered the four strategicorientations of Miles and Snow (1978) moreresearch is needed to include various contingen-cies such as environmental uncertainty, environ-mental munificence, the state of the economy,and the life cycle of the industry(ies) underexamination. Finally, notwithstanding the gener-alizability of our results, it should also beacknowledged that the North Cyprus context,particularly in terms of cultural connotations,may bear some influence on the strategic andlearning orientations of the businesses in oursample, their business conduct and attendantbehaviors. This caveat calls for further researchacross different countries and cultural contexts.

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