(2012) BJM

From Entrepreneurial Orientation andLearning Orientation to Business

Performance: Analysing the MediatingRole of Organizational Learning and the

Moderating Effects of Organizational Size

Juan C. Real, José L. Roldán1 and Antonio Leal1

Department of Business Management and Marketing, Pablo de Olavide University, Ctra. de Utrera, Km. 1,41013 Seville, Spain, and 1Department of Business Administration and Marketing, University of Seville,

Avda. Ramón y Cajal, 1, 41018 Seville, SpainCorresponding author email: [email protected]

Following the organizational learning theory and the knowledge-based view approach,this contribution aims to study the influence of entrepreneurial orientation and learningorientation on organizational learning, considering the latter as a mediating variable inthe relationships between both antecedent cultural values and business performance. Wealso analyse the moderating role of organizational size on these previous relationships.The hypotheses proposed in our research model are tested on a sample of 140 Spanishindustrial companies, applying variance-based structural equation modelling: partialleast squares. In order to assess the moderating effects of organizational size, we adopta multi-group approach using two subsamples with large firms and small and medium-sized enterprises (SMEs). Our findings indicate that organizational learning partiallymediates the relationship between entrepreneurial orientation and performance and fullymediates the link between learning orientation and performance. Likewise, the resultsreveal that the relationship established between entrepreneurial orientation and organi-zational learning is more intense for the group of large firms than for the group of SMEs.Moreover, the influence of learning orientation on organizational learning is greater inSMEs than in large firms.

Introduction

The implications of the knowledge-based view inthe learning and knowledge creation in organiza-tions have not been extensively addressed in theexisting literature. Argote (2011) argues thatknowledge creation is a research area that wouldespecially benefit from more theorizing andempirical research. In this respect, a particular

investigation field is linked to managerial atti-tudes and cultural values that would play an ante-cedent role. This would be the case of theentrepreneurial orientation and learning orienta-tion. Entrepreneurial orientation is associatedwith methods, practices and decision-makingstyles that managers use to act entrepreneurially(Covin and Slevin, 1989). This leads companies todevelop product-market innovations, take risksand behave proactively (Miller, 1983). Learningorientation is conceptualized as a basic attitudetowards learning, i.e. the organizational andmanagerial characteristics that facilitate the

This research was supported by the Junta de Andalucía(Consejería de Economía, Innovación y Ciencia), Spain(Proyecto de investigación de excelencia SEJ-6081).

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British Journal of Management, Vol. ••, ••–•• (2012)DOI: 10.1111/j.1467-8551.2012.00848.x

© 2012 The Author(s)British Journal of Management © 2012 British Academy of Management. Published by Blackwell Publishing Ltd,9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA, 02148, USA.

organizational learning process (Chiva andAlegre, 2009).

Both cultural values are drivers of organiza-tional learning, i.e. the process through whichorganizations change or modify their mentalmodels, processes or knowledge, maintaining orimproving their performance (DiBella, Nevis andGould, 1996). On the one hand, the organization’sentrepreneurial orientation encourages the firm’sadoption of an innovating proactive behaviourthat will promote the organizational learning andthe knowing process (Dess et al., 2003). On theother hand, the learning orientation will influencethe firm’s likelihood of creating and using knowl-edge (Sinkula, Baker and Noordewier, 1997).

Organizational learning allows the combina-tion of the firm’s existing resources and cap-abilities, transforming them into distinctivecompetences – a source of sustainable competitiveadvantage (Lado, Boyd and Wright, 1992).Therefore, organizational learning becomes afundamental strategic factor according to theresource-based view approach and its extension,the knowledge-based view approach. Both theo-retical frameworks suggest that competitiveadvantage stems from the firm’s capabilities andskills. Consequently, organizational learning willimprove the company performance, reinforcingits competitive advantage.

Moreover, the relationship between entrepre-neurial orientation and business performance hasreceived substantial attention in the literature(Covin and Slevin, 1986; Wiklund and Shepherd,2003). Although entrepreneurial orientation isusually considered to have a positive impact onfirm performance (Rauch et al., 2009), this rela-tionship requires a wider analysis of the interme-diate steps between entrepreneurial orientationand firm performance. Similarly, other studieshave demonstrated the influence of learning ori-entation on business performance (Baker andSinkula, 1999; Calantone, Cavusgil and Zhao,2002; Vijande et al., 2005). Hult, Hurley andKnight (2004) state that learning orientationoccurs especially at the level of corporate cultureand the relationship between learning orientationand firm performance can be mediated by othervariables that would impact directly on businessresults. In addition, the literature provides somecontroversial results concerning the link betweenorganizational learning and business performance(Pérez López, Montes Peón and Vázquez Ordás,

2005). Nonetheless, there are no previous studiesthat test the joint impact of entrepreneurial orien-tation and learning orientation on organizationallearning, the latter being considered as a mediat-ing variable in the relationships between anteced-ent cultural values and business performance.

In order to understand the conditions underwhich an entrepreneurial orientation and learningorientation enhance firm performance, we suggestthat it is necessary to take intermediate variablesinto account, such as organizational learning. Indoing so, our first objective will be to test the roleof organizational learning as a mediator of therelationship between entrepreneurial orientationand learning orientation in business performance.

This paper also makes another contribution tothe literature: organizational size may exert a mod-erating effect on the direct relationships previouslydisclosed. The majority of organizational learningstudies have concentrated on large organizations(Leonard-Barton, 1992). These are based on casestudies of organizations that are successful in theirlearning. Notwithstanding, the empirical evidenceis limited (Easterby-Smith, 1997). This is particu-larly so in the case of small companies (Sadler-Smith, Spicer and Chaston, 2001). Organizationallearning research has neglected this organizationtype for too long (Hendry, Arthur and Jones,1995). Contrariwise, the literature also indicatesthat organizational size could be a key impedimentto organizational learning (Marquardt and Rey-nolds, 1994). Given that situation, as a secondobjective we explore the role of organizational sizeas a potential moderator variable.

To achieve the objectives proposed, the struc-ture of the paper is as follows. First, there is adescription of the theoretical framework appliedin this research. This leads to a series of hypoth-eses describing the research model. Next, wepresent the sample selection, the questionnairedesign and the planning of the fieldwork. Then,we report our findings and discuss their implica-tions based on an analysis of data collected from140 manufacturing firms. Finally, we state thelimitations and guidelines for future research, aswell as the conclusions of our study.

Theory and hypothesisOrganizational learning and knowledge creation

This paper defines organizational learning as adynamic process of knowledge creation generated

2 J. C. Real, J. L. Roldán and A. Leal

© 2012 The Author(s)British Journal of Management © 2012 British Academy of Management.

at the heart of the organization via its individualsand groups. It drives the generation and develop-ment of capabilities that enable the organizationto improve its performance and results (Real, Lealand Roldán, 2006).

Based on this definition, the work takes a socialprocess approach to organizational learning(Chiva and Alegre, 2005). Here individuals aresocial beings who, together, construct an under-standing of what they have around them. Learn-ing can only be achieved through activeparticipation. This can occur at the individual,group or organizational level (Crossan, Lane andWhite, 1999). This is thanks to the existence oftwo types of basic activities for learning in theorganization: exploration or feedforward, andexploitation or feedback (March, 1991). Explora-tion learning consists of experimenting with newpossibilities, and its results are uncertain, longterm and often negative (March, 1991). Exploita-tive learning describes learning activity focused onacquiring existing knowledge to be used with theunderstanding that it already has a known valueand outcome (Hughes, Hughes and Morgan,

2007). Organizational learning is a dynamicprocess through levels that create a tensionbetween incremental or amplifying logic – involv-ing exploration or the assimilation of new learn-ing (feedforward) – and reductive logic, whichexploits or uses what has been learned (feedback)(Vera and Crossan, 2004).

Crossan and Berdrow (2003) and Crossan,Lane and White (1999) present a theoreticalframework (Figure 1) according to the epistemo-logical dimension (types of knowledge) and theontological dimension (learning levels of knowl-edge). This framework adds value by clarifyingand expanding upon the theory of organizationallearning. This adds a previously absent focus onlevels and types of learning to the existing litera-ture (Crossan, Maurer and White, 2011).

Therefore, Crossan, Lane and White’s (1999) 4Imodel of organizational learning helps us tounderstand how the organization’s existing learn-ing process is seen as a combination of stocks andflows of knowledge. As individuals, groups andthe organization act as repositories of knowledge,learning flows across these levels through the 4I

Feedback

Feedforward

Output

Individual Group Organization

Intuition Interpretation Integration Institutionali-zation

Inpu

t

Indi

vidu

al

Intu

itio

n

Inte

rpre

tati

on

Gro

up

Inte

grat

ion

Org

aniz

atio

n

Inst

itut

iona

li-za

tion

Figure 1. The 4I model of organizational learning as a knowledge-creation process

Entrepreneurial and Learning Orientation and Performance 3


sub-processes. These sub-processes are intuition,interpretation, integration and institutionaliza-tion (see the matrix diagonal in Figure 1), in theform of feedback and feedforward linkages.

Organizational learning takes place throughlevels which create a tension between incrementalor amplifying logic. This involves two aspects:first, the exploration or assimilation of new learn-ing (feedforward: cells in the upper part of thematrix diagonal in Figure 1); second, a reductivelogic which exploits or uses what has been learned(feedback: cells in the lower part of the matrix).Learning that originates with individuals and isthen transferred to groups and the organization isknown as feedforward learning. On the otherhand, learning is also transferred from the organi-zation to individuals and groups through a feed-back process. Integration unites the two types oflearning. It facilitates the institutionalization ofthe results of exploration and the interpretationby individuals and groups of institutionalizedlearning (Crossan, Lane and White, 1999).

The Strategic Learning Assessment Map(SLAM) proposed by Bontis, Crossan andHulland (2002) was applied to the 4I model(Crossan and Berdrow, 2003; Crossan, Lane andWhite, 1999) used in this research to analyseorganizational learning. The SLAM matrixincludes three key dimensions of the organiza-tional learning literature: first, an analysis per-spective with multiple levels; second, a conceptualoperative framework; third, the integration oflearning into stock and flow magnitudes. Theseare three stock learning constructs related to thelearning exploration process (individual, groupand organization) and two flow learning con-structs corresponding to the exploration andexploitation process (feedforward and feedback).The definition of the SLAM constructs is given inTable 1.

Entrepreneurial orientation andorganizational learning

According to Covin and Slevin (1989), entrepre-neurial orientation relates to the methods, prac-tices and decision-making styles that managersuse to act entrepreneurially. Entrepreneurial ori-entation has been characterized by three dimen-sions (Miller, 1983). These are innovativeness,proactiveness and the propensity to risk invest-ments in new businesses.

Innovativeness refers to the pursuit of creativeor novel solutions or challenges (Knight, 1997).Proactiveness is thus closely allied to competitiveaggressiveness (Lumpkin and Dess, 1996). This isdefined as how firms respond to trends anddemands that already exist in the marketplace.Risk-taking is the willingness to commit largeamounts of resources to projects whose results areunknown and where the cost of failure may behigh (Miller and Friesen, 1978).

Entrepreneurial orientation encourages thefirm’s adoption of an innovating and proactivebehaviour that enables it to create a new knowl-edge that is required to achieve novel distinctivecapabilities. Entrepreneurial orientation couldbe an important measure of how organizationsuse knowledge-based resources to discover andexploit fresh opportunities (Wiklund and Shep-herd, 2003). Zahra, Nielsen and Bogner (1999)suggest a model in which the influence of entre-preneurial orientation on organizational learningprovides a mechanism to create new knowledge.This lays the foundation for novel competences orthe revitalizing of existing ones. Liu, Luo and Shi(2002) show that entrepreneurial orientationrelates positively to organizational learning.

Learning orientation and organizational learning

Learning orientation is defined as a basic atti-tude towards learning. This exogenous variablesynthesizes the critical components of learningorganizations (Chiva and Alegre, 2009) – a pre-scriptive approach concerned with the question

Table 1. Definition of SLAM constructs

Individual-levellearning stocks

Individual competency, capability andmotivation to learn the required tasks

Group-levellearning stocks

Group knowledge or knowledgeincorporated into social interactions, aproduct of shared understanding

Organizational-levellearning stocks

Knowledge or skills internalized innon-human aspects of the organization,including systems, structures, proceduresand strategy

Feedforwardlearning flows

Transfer of learning from the individual tothe collective sphere

Feedbacklearning flows

The use made of learning which hasbecome institutionalized (learning whichis embedded in the organization, in itssystems, structures, strategy etc.)

Source: Adapted from Bontis, Crossan and Hulland (2002).



‘how should an organization learn?’ (Tsang,1997).

This study views learning orientation as agroup of organizational values which influencethe firm’s tendency to create and use knowledge(Sinkula, Baker and Noordewier, 1997). Bakerand Sinkula (1999) state that one of these values isthe commitment to learning. This closely relatesto the management’s commitment to support aculture that fosters learning orientation as oneof its main values (Garvin, 1993). Bapuji andCrossan (2004) stress the role of managerialsupport in learning and what managers can spe-cifically do to broaden support for learning. Thegeneral rules for organizational learning allowmanagers to guide it efficiently. Such norms are ofparticular importance because in the future theywill create a way of leading people that will stimu-late organizational learning at both the individualand the team level (Michna, 2009).

Another value is open-mindedness. This is con-nected with the mental models that dominate thefirm (Day, 1994) and with unlearning as a drivingforce for organizational change. Shared vision(Senge, 1990) is a knowledge vision which givesmeaning to the firm’s everyday tasks and definesthe type of knowledge it must seek and create.

Learning orientation, as a cultural value, is anantecedent to the organizational learning andknowledge-creation process that facilitates inven-tiveness (Cohen and Levinthal, 1990). Authorssuch as DiBella, Nevis and Gould (1996) considerthat learning orientation determines where learn-ing will take place and the nature of what is learnt.It defines how organizations acquire, share anduse knowledge, and it affects the spiral processand knowledge conversion (Kim, 1998).

Organizational learning and business performance

In this study, perceived business performanceencompasses issues such as corporate success,group performance and employee satisfaction(Bontis, Crossan and Hulland, 2002).

There is great controversy in the field of busi-ness administration regarding the relationshipbetween organizational learning and perceivedbusiness performance (Inkpen and Crossan,1995). Several authors attribute an improvementin company results to organizational learning,although there are significant differences in theirdefinition of company results. In this respect,

organizational learning demonstrates the abilityto positively influence results. These are results atthe financial level (Lei, Slocum and Pitts, 1999).There are also those affecting the organizationalstakeholders (Goh and Richards, 1997) andoperational outcomes, such as innovation capa-bility and productivity improvement (Leonard-Barton, 1992).

March (1991) considers that learning is a prin-cipal component of any effort to improve per-ceived business performance and reinforcecompetitive advantage. Even so, the increase inknowledge associated with the learning processmay reduce rather than increase the variability ofperformance.

According to Mintzberg (1990), performanceprovides important feedback of the efficiency andeffectiveness of the learning process. Similarly,Inkpen and Crossan (1995) believe that organiza-tions which learn more efficiently have a betterlong-term performance than their competitors.

The mediating role of organizational learning

The literature has so far found evidence thatentrepreneurial orientation has a positive associa-tion with business performance (cf. Wiklund,1999; Wiklund and Shepherd, 2003, 2005; Zahra,1991; Zahra and Covin, 1995). Along the samelines, some contributions have shown that learn-ing orientation positively influences organiza-tional performance (cf. Baker and Sinkula, 1999;Tippins and Sohi, 2003).

Although most research considers that entre-preneurial orientation has a positive impact onfirm performance this direct relationship does notseem to be empirically conclusive (Rauch et al.,2009). Similarly, Suliyanto and Rahab (2012)demonstrate that the learning organizationcannot directly improve the organization’s per-formance but rather that it must pass throughother variables that may intervene betweenorganizational learning and business perform-ance, as stated by Hult, Hurley and Knight(2004). They affirmed that learning orientationoccurs especially at the level of corporate cultureand the possibilities to be mediated by factors thatimpact directly on business performance. There-fore, we consider that it is necessary to identify thepotential mediators in such links. Hence, our pre-vious theoretical analysis leads us to propose the



organizational learning variable as a mediatingvariable in the two aforementioned relationships.

On the one hand, in accordance with ourearlier presentation, we consider that entrepre-neurial orientation positively impacts on organi-zational learning and, in turn, the latter has a pluseffect on business performance. Consequently, anincrease of entrepreneurial orientation can inten-sify the organizational learning capability andraise the likelihood of the company performanceimproving. Thus, we put forward the followinghypothesis.

H1: Organizational learning mediates the rela-tion between entrepreneurial orientation andperceived business performance.

On the other hand, given the theory and empiri-cal evidence above, learning orientation will berelated to business performance through organi-zational learning. We expect that the more anorganization presents a learning orientation, themore likely the entity will develop its organiza-tional learning ability and, subsequently, willenhance its business performance. Based on thislogic and previous research, we hypothesize thefollowing.

H2: Organizational learning mediates the rela-tion between learning orientation and perceivedbusiness performance.

The moderating role of organizational size

Most studies on organizational learning focus onlarge organizations (cf. Garvin, 1993; Leonard-Barton, 1992; Ulrich, Jick and von Glinow,1993) and on case studies of organizationsthat claim to be successful in learning. Yetthese provide little empirical evidence (Chaston,Badger and Sadler-Smith, 1999a; Easterby-Smith, 1997). This is especially so with respect tosmall firms (Sadler-Smith, Spicer and Chaston,2001) – a sector long neglected in organizationallearning research (Hendry, Arthur and Jones,1995). In turn, the literature also indicates thatorganizational size may weaken the influence ofantecedent variables on organizational learning(Marquardt and Reynolds, 1994). Our contribu-tion aims to verify, from an exploratory perspec-tive, the moderating effects of firm size on therelationships that emerge in our research model(Figure 2).

According to Lumpkin and Dess (1996), therelationship between entrepreneurial orientationand other contingent variables, such as organiza-tional size, opens up a path for future research.Several empirical studies explore the relationshipbetween firm size and entrepreneurial behaviour(Acs and Audretsch, 1987). There has been afocus on start-ups and small organizations (Dav-idsson and Wiklund, 2001).

H1 = EO OL PBP = a*c

Entrepreneurialorientation

(EO) a

H1 ‡ ‡ a cH2 = LO ‡ OL ‡ PBP = b*c

Organizationallearning

(OL)

Perceived businessperformance

(PBP)

a

c

b( )

Learningorientation

b

(LO)

H4

5H3H

Organizational size

Figure 2. Research model and hypotheses



Camisón (2001) states that small and medium-sized enterprises (SMEs) are in general morehostile to activity. This is because they have aheightened perception of the inherent risks. Forthis reason they show an outstanding capabilityfor seeking out new resources on which to basetheir increase in sales.

The statement that as organizations grow insize they tend to be less entrepreneurial-oriented iscommon in the literature (McMillan, Block andSubba Narasimha, 1986). Entrialgo, Fernándezand Vázquez (2001) examine the flexibility andmarket orientation of SMEs. These aspectsencourage them to learn from the environmentalcontext and to demonstrate a more entrepre-neurial behaviour. Hence, an entrepreneurial ori-entation has become an increasingly importantsurvival condition. When SMEs compete inhostile or turbulent environments, they tend toadopt entrepreneurial postures (Bouchard andBasso, 2011). The explanation is to be found inthe fact that SMEs are flexible and market-oriented and this encourages them to have a moreentrepreneurial behaviour. Large organizations,however, probably because their size enables themto take a more pioneering, innovating and risk-assuming approach, are more formal and stand-ardized. These are characteristics that areinversely related to innovation and creativity(Bahadir, Bharadwaj and Parzen, 2009). Siro-nopolis (1994) argues that larger firms tend to bemore bureaucratic than smaller firms. Bureauc-racy, however, prevents organizations from actingon opportunities for learning. In short, keeping inmind the above arguments, we propose the fol-lowing hypothesis.

H3: Organizational size moderates the positiverelationship between entrepreneurial orienta-tion and organizational learning.

The findings of Goh and Richards (1997)confirm that SMEs have many attributes of learn-ing organizations. Thus, according to Deakinsand Freel (1998), the concept of the learningorganization relates to small entrepreneurialfirms. It also emphasizes the organization’s abilityto learn from experience. On the other hand, thelearning environment of SMEs contains the enter-prise’s relationships within the network of interestgroups (Gibb, 1997). In addition, a large organi-zation size is typically accompanied by a greaterstructural complexity, such as a large number of

hierarchical levels (Blau, 1970). Since coordina-tion costs increase with the number of interfacesthat a particular piece of data has to cross, toomany levels of hierarchy tend to increase the coor-dination costs associated with learning flow.Compared with large firms, small firms may alsomore effectively leverage their own firm experi-ence thanks to the advantages of attracting andhiring talented employees. It has long beenaccepted that small firms have distinct advantagesin the hiring process (Leiblein and Madsen, 2009).Based on the above contributions, we propose thefollowing hypothesis.

H4: Organizational size moderates the positiverelationship between learning orientation andorganizational learning.

There is no theory of organizational learningwhich also takes into consideration the manage-ment specificity of SMEs in connection with theirperformance. Since not enough attention has beenpaid to the specificity of these processes in SMEsin association with their performance, the ques-tion of how organizational learning takes place inSMEs and how it affects their performance is bothhighly topical and very important (Michna, 2009).Bigger companies usually have more resources toinvest in organizational learning. Therefore, theymay depend on organizational learning processesless than smaller firms (Jiménez-Jiménez andSanz-Valle, 2011). Marquardt and Reynolds(1994) uphold that, in theory, size is a key impedi-ment to organizational learning development andto results. Simonin (1997) finds that size has anegative effect on the relationships establishedwithin a cross-organizational learning process.Chaston, Badger and Sadler-Smith (1999b)observe significant differences within a group ofSMEs when testing the relationship betweenorganizational learning and organizational per-formance. In light of the above, we put forwardthe following hypothesis:

H5: Organizational size moderates the positiverelationship between organizational learningand perceived business performance.

MethodSample selection

In this research we chose sectors classified as inno-vative for the population of the empirical study.



This is because the companies in these sectorsinnovate through a continuous learning process.In doing so, they generate new technologicalknowledge (Nonaka and Takeuchi, 1995).

To determine the population’s size, we initiallyselected Spanish industrial sectors in which tech-nological competences are central (Hendersonand Clark, 1990). In addition to this classification,we draw on information from the survey by theSpanish National Institute of Statistics (InstitutoNacional de Estadística, 2008) of innovativesectors regarding technological innovation incompanies. The sectors finally included in thepopulation are listed in Table 2.

We have chosen Andalusia, the largest region inSpain, as the geographical area for our researchstudy. The sample of firms was randomly selectedfrom the Dun & Bradstreet 2001 database, whichincludes the 50,000 biggest companies operatingin Spain. This information is supplemented by thelist of companies that make up the AndalusiaInnovation Network. In the case of there being

affiliates in the database, the sample only includesthe parent company. These combined databasesgive a population made up of 492 firms.

With regard to the sample unit, since the levelof analysis in this study is the organization, therespondent to the questionnaire is a single personfrom each company. This must be the ChiefExecutive Officer or the highest ranking official,as their cognitive maps represent the essentialaspects of all the members of the organization(Lyles and Schwenk, 1992). In order to maximizethe data accuracy and reliability, this contribu-tion follows Huber and Power’s (1985) guidelineson how to obtain quality data from singleinformants.

The population’s 492 companies received thequestionnaire. A total of 152 forms were returned,of which 140 were usable. This represents a replyrate of 28.45%. The companies in the sample havean average sales revenue of !11.5 million and amean age of 34.13 years (Table 2).

The study classifies firms by size according tothe number of employees, the annual turnoveror the annual financial statements in keepingwith Recommendation 2003/361/EC of the Com-mission of the European Communities (2003)regarding the definition of micro, small andmedium-sized enterprises. Most firms are SMEs,compared with a smaller number of large firms(n = 39, 27.86%).

The research applies several tests for potentialsources of bias in the collected data (Armstrongand Overton, 1977). Hence, in order to guaranteethe statistical representation of the companieswhich had agreed to take part, we measured thenon-response bias. These tests show no significantdifferences in average size (in terms of salesvolume).

Measures

Since the analysis uses already validated scales,efforts in this section focused on making the rel-evant adjustments to the setting and language inwhich the researchers were working. The meas-ures used in this study are given in Appendix 1.All the variables were Likert 1–7 measurementscales, except in the case of learning orientation inwhich the range of responses was 1, strongly disa-gree, to 5, strongly agree.

We measure entrepreneurial orientation usingKnight’s (1997) scale (ENTRESCALE). Accord-

Table 2. Respondent characteristics

Number of firms Percentage

(a) Industry typeFood and drinks 27 19.29Cardboard and paper 4 2.86Chemical sector 23 16.43Rubber and plastic materials 12 8.57Non-metallic minerals 17 12.14Metallurgy and manufacturing of

metal products11 7.86

Machinery and mechanicalequipment

9 6.43

Electrical, electronic and opticalmaterial and equipment

18 12.86

Manufacturing of transportmaterial

19 13.57

Total 140 100.00

(b) Total sales revenue (millions)Range!2 million to !10 million 42 30.00More than !10 million to !50

million59 42.14

More than !50 million 39 27.86Total 140 100.00

(c) Total number of employeesRange10 to less than 50 42 30.0050 to less than 250 59 42.14250 to less than 500 24 17.14500 and above 15 10.72Total 140 100.00



ing to ENTRESCALE, entrepreneurial orienta-tion consists of eight items divided into two criticaldimensions: entrepreneurial orientation and pio-neering behaviour or proactiveness. Nevertheless,the research included a confirmatory factorialanalysis (c2 = 20, p = 0.11, goodness-of-fit index(GFI) = 0.94, root mean squared error of approxi-mation (RMSEA) = 0.05, comparative fit index(CFI) = 0.95) and an analysis of the correlationsbetween the dimensions. As a result, we find threefactors. The correlation between these dimensionswas higher than 0.5. Therefore, the three dimen-sions co-varied. They appear in Covin and Slevin’s(1989) scale: innovativeness, proactiveness andrisk-taking.

We measure learning orientation by applyingthe scale used in Sinkula, Baker and Noordewier’s(1997) empirical research. According to theseauthors, learning orientation is made up of 11items grouped into three dimensions. These reflectthe organization’s commitment to learning,shared vision and open-mindedness.

All of the scales used to measure organizationallearning dimensions have their origin in theresearch developed by Bontis, Crossan andHulland (2002). This is defined by 50 items dis-tributed over five dimensions (SLAM variables):individual, group and organizational learningstocks, and feedforward and feedback learningflows.

To measure perceived business performance, weuse the scale worked out by Bontis, Crossan andHulland (2002). This is made up of 10 items. Thisperceptual measure of performance at the indi-vidual, group and organizational level can be areasonable substitute for objective measures ofbusiness performance. It can also have a significantcorrelation with objective measures of financialperformance (Venkatraman and Ramanujam,1986). The application of a confirmatory factoranalysis (c2 = 20, p = 0.11, GFI = 0.94, RMSEA= 0.05, CFI = 0.95) shows that the items load ontothree factors: the individual, group and organiza-tional performance dimensions.

Concerning organizational size, in this paperwe adopt the definition of the Commission of theEuropean Communities (2003) of SMEs and largeenterprises. This has been used in several studies(e.g. Delgado-Hernández, Benites-Thomas andAspinwall, 2007; Martin-Tapia, Aragon-Correaand Senise-Barrio, 2008; Ngugi, Johnsen andErdélyi, 2010). Two categories have been consist-

ently considered. On the one hand, large enter-prises are defined as enterprises which employmore than 250 people and whose annual turnoverexceeds !50 million or whose annual balance sheettotal exceeds !43 million. On the other hand, thegroup of SMEs consists of enterprises whichemploy more than 10 people and whose annualturnover or annual balance sheet total surpasses!2 million.

To assist in the preparation of the question-naire, we validated the content through a series ofinterviews with experts on its different sections.Their suggestions and contributions were incor-porated into a second version of the question-naire. The research therefore included a pre-testusing 14 companies, one for each of the sectorsbeing studied. The final questionnaire contains 79items.

Data analysis and resultsStatistical method

The data analysis method used in this paper is thepartial least squares (PLS) technique of analysingstructural equations. PLS has been chosenbecause this study focuses on the prediction ofdependent variables (Roldán and Sánchez-Franco, 2012), and the research has an incremen-tal character. That is, the study is based on priormodels but introduces new measures and struc-tural paths (Chin, 2010). For this work, the PLSmethod appears to be the most suitable, particu-larly because the technique is effective with smallsamples (Chin and Newsted, 1999; Reinartz,Haenlein and Henseler, 2009). We used the PLS-Graph software version 3.00 Build 1130 (Chin,2003).

Because all the data on the four latent variableswere self-reported from a single questionnaire, thepossibility of common variance exists. Followingthe advice of Podsakoff et al. (2003) and Huberand Power (1985), and bearing in mind that theinformation could not be obtained from differentsources, we followed all the procedural steps relat-ing to questionnaire design. We psychologicallyseparate the measurement of predictor and crite-rion variables, and guarantee response anonym-ity. A single-common-method factor is applied.The possibility of common influence across allresponses is first assessed by applying Harman’s(1967) one-factor test. Using a factor analysis, no



single factor that explains variance across all theitems is identified. This suggests that a mono-method bias is unlikely. Of the 14 factors that areidentified, the main factor explains 41.84% of thevariance. Because no single factor is found toexplain more than 50% of the variance, the study’sdata can be accepted as valid (Podsakoff andOrgan, 1986). Moreover, confirmatory analyses(covariance structure analysis based on maximumlikelihood) using VisualGSCA (Hwang, 2009,2008) are performed to identify and isolate anypossible method effects (Barroso, Villegas andCasillas, 2008). Each of the 75 items underlyingthe latent factors is also represented as one indi-cator of a large common variance factor. Theanalyses show that the fit of the last model isimproved by the proposed multifactor measure-ment model. We based our conclusions on fourmeasures for non-nested structural equation mod-elling comparisons: Akaike’s information crite-rion (AIC) (the smaller the better), the Bayesianinformation criterion (BIC) (the smaller thebetter), the GFI and the adjusted goodness-of-fitindex (AGFI) (the closer GFI and AGFI are to1.00, the better is the fit). Following a non-nestedmodel comparison, the fit indices for the modelwith a single method factor (c2(2700) = 6801.606)are AIC = 6501.606, BIC = 6060.359, AGFI =0.355 and GFI = 0.389, while the fit statistics forthe multifactor measurement model (c2(74) =225.776) are AIC = 163.776, BIC = 72.585,AGFI = 0.669 and GFI = 0.767.

To analyse the relationships between the differ-ent constructs and their indicators, we adopt thelatent model perspective (MacKenzie, Podsakoffand Jarvis, 2005). With regard to second-orderfactors, the study follows a two-step approach(Calvo-Mora, Leal and Roldán, 2005). Thismethod creates latent variable scores by optimallyweighing and combining items for each dimensionusing the PLS algorithm. As a result, the dimen-sions or first-order factors become the observedindicators of second-order factors.

Measurement model

With regard to the measurement model, we beginby assessing individual item reliability (Table 3).Loadings are generally above the accepted thresh-old of 0.7 (Carmines and Zeller, 1979), both forindicators and first-order factors (dimensions)related to reflective higher-order constructs

(common latent constructs). Those individualitems that had loadings with their respective con-structs under the accepted threshold were excludedfrom the analysis. We do not include loadingsof the indicators in Table 3 due to limitations onthe length of the paper. Thus, only data about thetotal sample are included in Tables 3 and 4.

The assessment of the construct reliability ismeasured by the composite reliability (rc) (Werts,Linn and Jöreskog, 1974). The four main con-structs meet the requirement of construct reliabil-ity since their composite reliabilities (rc) aregreater than 0.7 (Nunnally, 1978) (Table 3). Inaddition, all constructs and dimensions achieveconvergent validity because their average varianceextracted (AVE) rates surpass the 0.5 level(Fornell and Larcker, 1981) (Table 3).

For discriminant validity, we compare thesquare root of AVE (i.e. the diagonal in Table 4)with the correlations between constructs (i.e. theoff-diagonal elements in Table 4). On average,each construct relates more strongly to its ownmeasures than to others.

Structural model

In the structural model assessment, we estimatedthe path coefficients, their significance via boot-strap tests, the R2 values and the Q2 tests for

Table 3. Total sample measurement model: individual reliability,composite reliability and average variance extracted for the first-order factors and second-order factors

Construct/dimension Loading Compositereliability

(rc)

AVE

Entrepreneurial orientation 0.81 0.60Innovativeness 0.84 0.83 0.62Proactiveness 0.73 0.62 0.53Risk-taking 0.75 0.89 0.73Learning orientation 0.88 0.71Commitment to learning 0.84 0.93 0.76Shared vision 0.88 0.89 0.67Open-mindedness 0.80 0.84 0.73Organizational learning 0.95 0.81Individual-level learning stocks 0.88 0.93 0.60Group-level learning stocks 0.86 0.94 0.64Organizational-level learning stocks 0.92 0.94 0.64Feedforward learning flows 0.91 0.94 0.61Feedback learning flows 0.91 0.92 0.58Perceived business performance 0.90 0.75Individual-level performance 0.85 0.92 0.80Group-level performance 0.91 0.91 0.78Organizational-level performance 0.84 0.90 0.70



predictive relevance. This analysis was carried outboth for the total sample and for the two subsam-ples (Figure 3). The three main paths are signifi-cant. Furthermore, our dependent variablesachieve R2 values higher than 0.6. This can beconsidered near to substantial according to Chin(1998). The examination of the cross-validatedredundancy indices (Q2) (Geisser, 1975; Stone,1974) confirms that the three structural models(Figure 3) have satisfactory predictive relevance

for the two endogenous variables (organizationallearning and perceived business performance).

With the aim of testing the mediation hypoth-eses, we applied the analytical approach describedby Preacher and Hayes (2008). Figure 4(A)describes the total effects of the entrepreneurialorientation (d) and the learning orientation (e) onthe perceived business performance. These totaleffects may be arrived at via a variety of direct andindirect forces (Hayes, 2009). Specifically, in

Table 4. Averages, typical deviations and discriminant validity coefficients for the total sample

Construct Mean SD 1 2 3 4

1. Entrepreneurial orientation 4.30 0.24 0.77a

2. Learning orientation 3.59 0.43 0.36b 0.84a

3. Organizational learning 4.88 0.53 0.50b 0.77b 0.90a

4. Perceived business performance 5.33 0.34 0.50b 0.67b 0.83b 0.87a

aDiagonal elements (bold) are the square root of the variance shared between the constructs and their measures. Off-diagonal elementsare the correlations between constructs. For discriminant validity, diagonal elements should be larger than off-diagonal.bAll of the correlations are significant at the p < 0.01 level.


(bold) E = Entire sample(normal) L = Large firmsNote

orientation

s

.84

.85

.81

E1: .26***L1: .49***S1: .21***

R2 65 Q2 49

(italic) S = Small and medium-sized enterprises

R2 68 Q2 49

.73

.77

.72

.75

.71

.77

Organizationall i

Inno

vativ

enes

s

Proa

ctiv

enes

s

Ris

k ta

king

E2: .68***

!E3: .83***!L3: .85***!S3: .82***

E: . ; E: .R2

L: .77 ; Q2L: .62

R2S: .61 ; Q2

S: .43

2E: . ; E: .

R2L: .72 ; Q2

L: .56R2

S: .67 ; Q2S: .43

learning

Learningi t ti

Perceived businessperformance

L2: .39*S2: .73***

.88

.92.92.9691

.91

.96.91.94

.85

.87.91.95

.84

.90

orientation

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*** p < 0.001, ** p < 0.01, * p < 0.05 (based on t(499), one-tailed test)

Figure 3. Structural model results (entire sample, large firms and SME samples)



Figure 4(B) the total effect of the entrepreneurialorientation on the perceived business perform-ance can be expressed as the sum of the direct (d")and indirect effects (a*c). Thus, d = d" + a*c(Taylor, MacKinnon and Tein, 2008). Thisapproach has the advantage of being able toisolate the indirect effect (a*c) described inHypothesis 1. The relationships d and d", althoughnon-hypothesized, are included in our analysis inorder to test the presence of either full or partialmediation (Baron and Kenny, 1986). The sameprocedure is applicable to the total effect of learn-ing orientation on the perceived business perform-ance, e = e" + b*c where b*c is the indirect effectpostulated by Hypothesis 2.

Furthermore, we follow a bootstrappingprocess, i.e. a non-parametric resampling proce-dure that does not impose the assumption of nor-mality on the sampling distribution. MacKinnon,Lockwood and Williams (2004) show via simula-tions that the performance of bootstrapping is

better than the traditional Sobel test (Sobel,1982). Using latent variables scores obtained fromthe PLS analysis, we have applied the SPSSroutine developed by Preacher and Hayes (2008)to calculate total, direct and indirect effects, aswell as the 95% confidence interval (CI) for themediator variable (Table 5, Figure 4). In accord-ance with Hayes (2009), we have done 5000 resa-mples. In addition, we have applied threeprocedures to obtain three different bootstrapconfidence intervals: percentile, bias-corrected(BC) and bias-corrected and accelerated (BCa)(Hayes, 2009). When an interval for a mediatingeffect does not contain zero, this means that theindirect effect is significantly different from zerowith a 95% confidence level.

Table 5 shows the results of this assessment.Entrepreneurial orientation has a significanttotal effect on perceived business performance(d = 0.30, t = 4.76) (Figure 4(A)). When organiza-tional learning is introduced as a mediator, entre-


(EO)

d = .30***

A. Model with total effects

Learning

Perceived businessperformance (PBP)

R2= .52e = .56***

Orientation(LO)

B. Model with mediated effects


(EO)

= .26***

d’ = .12*

Organizationallearning (OL)

R2= .65

Perceived businessperformance (PBP)

R2= .69

ac = .70***

b = .68***

Learningorientation

(LO)

e’ = .09ns

H1 = EO ‡ OL ‡ PBP = a*cH2 = LO‡ OL‡ PBP = b*c

*** p < 0.001, ** p < 0.01, * p < 0.05, ns = not significant(based on t(499), one-tailed test)Non-hypothesized relationship

Hypothesized relationship

Figure 4. Summary of mediating effect tests



preneurial orientation reduces its direct effecton perceived business performance althoughit remains significant (d" = 0.12, t = 2.20)(Figure 4(B)), whereas its indirect effect viaorganizational learning achieves a point estimateof 0.18 (a*c). Since all CIs do not contain zero,the indirect effect is significant. Consequently,Hypothesis 1 is supported. This means thatorganizational learning partially mediates theinfluence of entrepreneurial orientation on per-ceived business performance (Baron and Kenny,1986). Hypothesis 2 is also supported. The indi-rect effect through organizational learning (b*c)has a point effect of 0.47 while its CIs do notpresent any sign change (Table 5). In this respect,it can be observed that learning orientation hasa significant total effect on perceived businessperformance (e = 0.56, t = 8.87) (Figure 4(A)).However, when organizational learning isincluded in the model, playing a mediating role,learning orientation no longer has a significantdirect effect on perceived business performance(e" = 0.09, t = 1.21) (Figure 4(B)). Therefore,organizational learning fully mediates the influ-ence of learning orientation on perceived businessperformance (Baron and Kenny, 1986).

Multi-group analysis

Hypotheses 3–5 represent moderating effects.Taking into account that organizational size hasbeen considered as a categorical variable byapplying the recommendation of the Commis-sion of the European Communities (2003), we

have adopted a multi-group or multi-sampleanalysis, as suggested by Henseler and Fassott(2010). This approach allows the testing of themoderating role of organizational size on therelationships included in our research model.Examples of multi-group comparisons consider-ing organizational size as a moderator variablecan be consulted in Fink and Neumann (2009),Saenz, Aramburu and Rivera (2007) andSimonin (2004).

The multi-group comparison entails dividingthe sample into groups according to the modera-tor variable. Next, each group of observations inthe model proposed is estimated separately. Sta-tistically significant differences in path coefficientsbetween subsamples are interpreted as moderat-ing effects (Qureshi and Compeau, 2009). Con-sistent with the Commission of the EuropeanCommunities (2003), the sample was divided intotwo groups: large enterprises and SMEs. Toconfirm the significance of these differencesbetween the two categories, we use the multi-group analysis proposed by Chin (2000) andimplemented by Qureshi and Compeau (2009).The moderating effect is examined using a t testwith pooled standard errors (Table 6). Thismethod is described as the parametric approach(Henseler, 2007) (see Appendix 2).

The findings support Hypothesis 3. The influ-ence proposed is significantly more intensefor the group of large firms than for SMEs(PathLFs > PathSMEs, p < 0.05) and therefore anincrease in the organizational size appears toincrease the positive influence of entrepreneurial

Table 5. Path coefficients and indirect effects for mediation models

Total effect Direct effect to Indirect effects

OL PBP Estimate Bootstrapping 95% confidence intervals

Percentile BC BCa

Lower Upper Lower Upper Lower Upper

EO # PBP 0.30*** (4.76)LO # PBP 0.56*** (8.87)EO 0.26*** (4.77) 0.12* (2.20)LO 0.68*** (12.48) 0.09ns (1.21)OL 0.70*** (8.68)H1 = EO # OL # PBP = a*c 0.18 0.09 0.28 0.10 0.28 0.10 0.30H2 = LO # OL # PBP = b*c 0.47 0.32 0.63 0.33 0.64 0.33 0.64

Notes: EO, entrepreneurial orientation; LO, learning orientation; OL, organizational learning; PBP, perceived business performance.BC, bias corrected; BCa, bias corrected and accelerated. 5000 bootstrap samples.*p < 0.05; **p < 0.01; ***p < 0.001. nsNot significant; t values in parentheses.



orientation on organizational learning. On theother hand, the study verifies that the influenceof learning orientation on organizational learn-ing is greater in SMEs than in large firms(PathSMEs > PathLFs, p < 0.01). This is in agree-ment with Hypothesis 4. On the other hand,Hypothesis 5 is not supported in our study – theinfluence of organizational learning on perceivedbusiness performance is practically equal for thetwo groups.

Discussion

Our findings are an important contributionto the entrepreneurial orientation–performanceresearch stream focusing on the intermediate linksbetween entrepreneurial orientation and firm per-formance. This research could explain why somefirms might manifest a low performance whiletheir managers show a clear entrepreneurial ori-entation attitude. Specifically, our study explainsthis relationship by an indirect effect throughorganizational learning, whose magnitude is evengreater than the direct effect. Consequently, otherdependent variables more sensitive to entrepre-neurial orientation should be suggested and somecontingent variables ought to be considered inorder to understand the entrepreneurial orienta-tion and business performance relationship.Firms with a strong entrepreneurial orientationwill enter new product markets aggressively andincur greater risks. This will require them to copewith more complex and changing environmentsand will call for learning. The organizationallearning process may partially mediate the rela-tionship between entrepreneurial orientation andbusiness performance by extending this attitudeto the rest of the organization.

The results confirm the conclusions of Sadler-Smith, Spicer and Chaston (2001) and show how

entrepreneurial orientation induces organiza-tional learning in the creation of new knowledgethat lays the foundations for new competencebuilding (Zahra, Jennings and Kuratko, 1999).Therefore, according to Dess et al. (2003), organi-zational learning is one of the major consequencesof entrepreneurial orientation. Following Slaterand Narver (1995), market and entrepreneurialorientation provide the foundation for organiza-tional learning. Similarly, Zahra, Nielsen andBogner (1999) and Liu, Luo and Shi (2002) con-sider that entrepreneurial orientation promotesorganizational learning and learning values suchas teamwork, openness etc.

Several studies have indicated that there is adirect impact of learning orientation on businessperformance (Baker and Sinkula, 1999; Tippinsand Sohi, 2003). Nonetheless, these studies didnot pay attention to there being a mediator vari-able in such a link. Our results show that organi-zational learning fully mediates the relationshipbetween learning orientation and business per-formance. One of the reasons for this might bethat firm performance depends directly on manyvariables, both internal and external to theorganization (Thoumrungroje and Tansuhaj,2005). Our study innovatively contemplates sucha mediating role and finds evidence that there isnot a direct effect of learning orientation on busi-ness performance, but there is an indirect effectvia organizational learning. This finding supportsthe results of several authors. On the one hand,there are those who have measured organiza-tional behaviours that must be in place fororganizational learning to occur (Hult andFerrell, 1997). On the other hand, we find thosewho have done so according to the critical com-ponents of learning organizations (Jerez-Gómez,Céspedes-Lorente and Valle-Cabrera, 2005). Thispaper explains this result. It takes into accountthe fact that learning orientation stimulates the

Table 6. Multi-group analysis

Path coefficients PathSMEs – PathLFs t value Supported

SMEs Large firms

H3: EO # OL 0.21 0.49 -0.28* 2.03 YesH4: LO # OL 0.73 0.39 0.34* 2.48 YesH5: OL # PBP 0.82 0.85 -0.03 0.43 No

Notes: EO, entrepreneurial orientation; LO, learning orientation; OL, organizational learning; PBP, perceived business performance.Levels of significance based on a Student t(499) distribution with two tails.*p < 0.05, t(0.05,132) = 1.98; **p < 0.01, t(0.01,132) = 2.61; ***p < 0.001, t(0.001,132) = 3.37.



organization’s willingness to create and useknowledge.

The study confirms the influence of organiza-tional learning on perceived business perform-ance. This is a topic addressed by several scholars(e.g. Pérez López, Montes Peón and VázquezOrdás, 2005), but which lacked a solid empiricalfoundation (Chaston, Badger and Sadler-Smith,1999c). This is due to the absence of simplicityand clarity of the cause and effect relationship,furthered by the fact that, as stated by Yeo (2003),organizational learning occurs throughout aseries of actions or stages that can make thislearning become rather complex. This relates tothe idea that organizational learning can be influ-enced by other variables that have an immediateeffect on the results (Huber, 1991).

Regarding the influence of organizational sizeas a moderating variable, entrepreneurial orienta-tion seems to have a greater impact on organiza-tional learning in the group of large firms. Inprinciple, according to the literature, the size ofSMEs allows them to learn with more flexibility,permitting them to quickly change and takeadvantage of new opportunities appearing in theenvironment. This implies that these companiesare less reluctant to take risks and will thereforebe more agile than larger entrepreneurial firmsand able to learn faster in order to capitalize onbusiness opportunities. However, entrepreneurialorientation encompasses the qualities of proactiv-ity, drive and initiative that can lead managers toengage in and commit themselves to new ideas,novelties, experimentation and creative processes(Hult, Hurley and Knight, 2004). Proactivenessrefers to how a firm relates to market opportuni-ties by seizing the initiative and acting opportun-istically to influence trends and even, perhaps,create demand (Jogaratnam, Tse and Olsen,1999). Consequently, it implies acting as a leader,not a follower. The basis of this idea is theassumption that, owing to their size, large firmshave a greater number of resources available tothem and are therefore more likely to be pioneer-ing, innovating and risk-assuming than their SMEcounterparts. This fact would enable them toincrease their organizational learning capability.

Concerning the moderator role of organiza-tional size, the relationship between learningorientation and organizational learning is signifi-cantly stronger for SMEs, as indicated in themulti-group analysis test. The explanation of this

finding is that small and medium-sized enterpriseshave low levels of formalization and bureaucrati-zation and this kind of firm has to learn continu-ously from the environment if it wishes to survivein the competitive market. SMEs are dominatedby informal work-based learning as well as by oraland informal communication. This is becauseflexibility and adaptability are preferred to formaljob descriptions and skills while the transmissionof tacit knowledge is through ad hoc training(Salim and Sulaiman, 2011). SMEs can encouragethe exploration of knowledge by implementingformal or informal meetings, or creating externalcommunities of practice, where customers andsellers interact and work together to achieve aparticular objective (Dewhurst and Cegarra,2004). These results support Goh and Richards’sconclusions (1997), derived from a study of fourorganizations, in which the firm classified as asmall enterprise achieved the highest rating in aquestionnaire that measured the attributes oflearning organizations. Finally, our outcomescontradict the idea that many authors uphold(McGill, Slocum and Lei, 1992). They describethe application of the organizational learning phi-losophy within the group of large firms, excludingSMEs (Chaston, Badger and Sadler-Smith,1999c). This is because they consider that largefirms have better organized learning processes.

As for the organizational learning basedhypothesis, this variable generates equivalent pathcoefficients on perceived business performance inboth samples. This equality relation, revealed bythe lack of a significant difference in the multi-group analysis test, shows that, although size doesprovide resources, these by themselves cannot gen-erate an organizational learning that yields betterperformance. This is because, although organiza-tional learning takes place through individuals, itwould be misleading to think that this learningis the cumulative result of the organization’smembers (Crossan, Lane and White, 1999).Organizational learning depends not only oninvestment efforts but also on the previously accu-mulated knowledge or experience. The learningprocess is intrinsically social and collective andoccurs through the collaboration and interactionof the individual, regardless of the company type.Dalley and Hamilton (2000) show that a greatnumber of SMEs do not devote any resources toimproving their organizational learning process.Furthermore, SMEs often fail to even effectively



use publicly subsidized offers of individual lifelonglearning programmes for their employees (Morri-son and Bergin-Seers, 2002).

Practical implications

The conclusions of this study suggest a series ofrecommendations aimed at fostering organiza-tional learning with a potential to improveperformance.

The first recommendation is to capitalize on thefirm’s learning capability by suggesting the impor-tance of managers and their attitudes and stancesin order to effectively implement the factors orlearning conditions within organizations. Thisquestion takes on an added importance becausemost managers do not view themselves as learningfacilitators and they believe that they lack therequired skills. These can be achieved by applyingthe attributes of a learning organization in such away that learning orientation becomes the maintrigger for learning.

With organizational learning configured as akey strategic resource, firms need to analyse otherfactors that might assist its development. Entre-preneurial orientation and learning orientationare a managerial attitude that must be supportedby certain organizational conditions that facilitatelearning and have positive implications for per-formance. We propose that entrepreneurial orien-tation and learning orientation, via organizationallearning, will have a positive effect on businessperformance. Practitioners should develop newmethods to respond to change through implicitlearning, improvisation learning, learning byaction and learning by trial and error.

Firms with entrepreneurial orientation charac-teristics would focus the attention of individualand departments on promoting mutual learningin which members would remove the ideologicalpackage and share knowledge with others.

Our findings could also explain why some firmsmight show a low performance while their man-agers show a clear learning orientation. Eventhough managers recognize the importance ofentrepreneurial orientation and learning orienta-tion, their implications and requirements in therest of the organization is often an unknownprocess for them to be successful. In this paper, wesuggest the implementation of an organizationallearning approach when an entrepreneurial orien-tation and learning orientation have been selected

by managers. Organizational learning is a keyconcept for organizations nowadays and repre-sents the essence of their competitive advantage.

Limitations and directions forfuture research

This study has certain limitations. These,however, pave the way for new lines of research.This is a cross-sectional research, looking particu-larly at the dynamic nature of the organizationallearning construct. Because organizational learn-ing occurs over time, studying organizationallearning requires time-series or longitudinal data.While there are conceptual arguments in favour oforganizational learning affecting performance,the other causal direction is also possible: betterperformance might also stimulate organizationallearning. A new line of research might conduct alongitudinal study that implements measures atdifferent times in order to confirm the relation-ships set out in the theoretical model proposed.

Given that this study does not consider the roleof the inter-organizational level in knowledgecreation, it may stimulate a future line of researchthat would examine the external knowledge pro-vided by the firm’s interest groups. These could beclients, suppliers and competitors – valuablesources of information and new ideas.

The data this study uses are largely the subjec-tive perceptions of the managers responding tothe survey. Although the subjective evaluationsobtained through multi-item scales are in generalfairly consistent with objective measures, differ-ences between perceptions and objective data mayexist. Future research might focus on this area,using objective indicators via case studies.

In order to be effective, organizational learningalso requires the organization to have a goodabsorption capacity. Thus, a future line ofresearch might be the study of the impact of theabsorption capacity on new knowledge creation,as an indirect effect of the interaction with theantecedent variables of the organizational learn-ing and knowledge-creation process.

Conclusions

This study examines the problem of the complex-ity of organizational learning as a knowledge-



creation process. It does so using the literature onorganizational learning and the knowledge-basedview as its theoretical frameworks.

Second, the paper contributes to the organiza-tional learning literature integrating learning ori-entation and entrepreneurial orientation into acomprehensive research model as variables thatstimulate the organizational learning processand the influence of this on perceived businessperformance.

Third, our study contributes to the literature onentrepreneurship and organizational learningby evidencing the importance of organizationallearning for entrepreneurial and learning orienta-tion. Although entrepreneurial orientation andlearning orientation might be considered asimportant determinants of firm performance, weobserve that these influences on business perform-ance might be mainly indirect – through themediation of organizational learning. In this vein,entrepreneurial orientation has a greater indirecteffect on perceived business performance viaorganizational learning than a direct effect on the

outcome variable (partial mediation), whereaslearning orientation influences perceived businessperformance through organizational learning (fullmediation).

Fourth, this paper analyses organizational sizeas a moderating variable and we note that entre-preneurial orientation seems to have a greaterimpact on organizational learning in the group oflarge firms. In the SME group, on the other hand,learning orientation is more important than entre-preneurial orientation in organizational learning.Finally, organizational size is neither an impedi-ment to nor a facilitator of organizational learn-ing with regard to the firm’s results.

Acknowledgements

This research was supported by the Junta deAndalucía (Consejería de Economía, Innovacióny Ciencia), Spain (Proyecto de investigación deexcelencia SEJ-6081).

Appendix 1Entrepreneurial orientation

InnovativenessNew lines of product or services Very many new lines of products or servicesChanges in product or service lines have been

mostly of a minor natureChanges in product or service lines have usually

been quite dramaticA strong emphasis on the marketing of tried and

true products or servicesA strong emphasis on R&D, technological

leadership and innovations

ProactivenessIs very seldom the first business to introduce new

products/services, administrative techniques,operating technologies etc.

Is very often the first business to introduce newproducts/services, administrative techniques,operating technologies etc.

Typically seeks to avoid competitive clashes,preferring a ‘live and let live’ posture

Typically adopts a very competitive ‘undo thecompetitors’ posture

Risk takingHas a strong proclivity for low-risk projects (with

normal and certain rates of return)Has a strong proclivity for high-risk projects (with

chances of very high returns)Believes that, owing to the nature of the

environment, it’s best to explore it gradually viacareful, incremental behaviour

Believes that, owing to the nature of theenvironment, bold, wide-ranging acts arenecessary to achieve the firm’s objectives

Typically adopts a cautious ‘wait and see’ posturein order to minimize the probability of makingcostly decisions

Typically adopts a bold, aggressive posture in orderto maximize the probability of exploitingpotential opportunities



Learning orientation

Commitment to learningManagers basically agree that our organization’sability to learn is the key to our competitiveadvantageThe basic values of this organization includelearning as a key to improvementThe sense around here is that employee learning isan investment, not an expenseLearning in my organization is seen as a key com-modity necessary to guarantee organizationalsurvival

Shared visionThere is a commonality of purpose in myorganizationThere is a total agreement on our organizationalvision across all levels, functions and divisionsAll employees are committed to the goals of thisorganizationEmployees view themselves as partners in chart-ing the direction of the organization

Open-mindednessWe are not afraid to reflect critically on the sharedassumptions we have made about our customersPersonnel in this enterprise realize that the waythey perceive the marketplace must be continuallyquestionedWe rarely collectively question our own biasesabout the way we interpret customer information(reverse-coded item)

Organizational learning

Individual-level learning stocksIndividuals are current and knowledgeable abouttheir workIndividuals are aware of the critical issues thataffect their workIndividuals feel a sense of accomplishment inwhat they doIndividuals generate many new insightsIndividuals feel confident in their workIndividuals feel a sense of pride in their workIndividuals have a high level of energy at workIndividuals are able to grow through their workIndividuals have a clear sense of direction in theirworkIndividuals are able to break out of traditionalmind-sets to see things in new and different ways

Group level learning stocksIn meetings, we seek to understand everyone’spoint of viewWe share our successes within the groupWe share our failures within the groupIdeas arise in meetings that did not occur to anyone individualWe have effective conflict resolution whenworking in groupsGroups in the organization are adaptableGroups have a common understanding of depart-mental issuesGroups have the right people involved in address-ing the issuesDifferent points of view are encouraged in groupworkGroups are prepared to rethink decisions whenpresented with new information

Organizational-level learning stocksWe have a strategy that positions us well for thefutureThe organizational structure supports our strate-gic directionThe organizational structure allows us to workeffectivelyOur operational procedures allow us to work effi-cientlyThe organization’s culture could be characterizedas innovativeWe have a realistic yet challenging vision for theorganizationWe have the necessary systems to implement ourstrategyOur organizational systems contain importantinformationWe have company files and databases that areup-to-dateWe have an organizational culture characterizedby a high degree of trust

Feedforward learning flowsLessons learned by one group are actively sharedwith othersIndividuals have input into the organization’sstrategyGroups propose innovative solutions toorganization-wide issuesRecommendations by groups are adopted by theorganizationWe do not ‘reinvent the wheel’



Individuals compile information for everyone touseIndividuals challenge the assumptions of thegroupThe company utilizes the intelligence of itsworkforceThe ‘left hand’ of the organization knows whatthe ‘right hand’ is doingResults of the group are used to improve prod-ucts, services and processes

Feedback learning flowsPolicies and procedures aid individual workReward systems recognize the contribution madeby groupsGroup decisions are supported by individualsCompany goals are communicated throughoutthe organizationOur recruiting practices enable us to attract thebest talentCompany files and databases provide the neces-sary information to do our workInformation systems make it easy for individualsto share informationTraining is readily available when it is needed toimprove knowledge and skillsCross-training, job rotation and special assign-ments are used to develop a more flexibleworkforceWhen making decisions for the future, we do notseem to have any memory of the past

Perceived business performance

Individual-level performanceIndividuals are satisfied working hereIndividuals are generally happy working hereIndividuals are satisfied with their ownperformance

Group-level performanceOur group makes a strong contribution to theorganizationOur group performs well as a teamOur group meets its performance targets

Organizational-level performanceOur organization is successfulOur organization meets its clients’ needsOur organization’s future performance is secureOur organization is well respected within theindustry

Appendix 2

tm n

t m n= $+

% + $( )Path PathSp

SMEs LFs

1 12

This is a one-tailed t Student distribution with (m+ n – 2) degrees of freedom, where Sp is the pooledestimator for the variance, m is the number ofcases in the sample of SMEs, n is the number ofcases in the sample of large firms, and SE is thestandard error for the path provided by the PLS-Graph in the bootstrap technique.

Sp SE SESMEs LFs= $( )+ $

+ $( )+ $

mm n

nm n

12

12

22

22

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Juan C. Real is Assistant Professor of Operations Management in the Department of BusinessManagement and Marketing, Pablo de Olavide University, Seville. Prior to that, he was Lecturer inthe Department of Business Administration and Marketing at the University of Seville from which hereceived a PhD in management. His current research interests are in the areas of organizationallearning, knowledge management and technological innovation management. He holds a Masters ininternational business from Pablo de Olavide University.

José L. Roldán, PhD, is Associate Professor of Management at the Faculty of Economics andBusiness Administration at the University of Seville, Spain. He is currently on the editorial board ofthe Data Base for Advances in Information Systems and Guest Editor of the European Journal ofInformation Systems (Special Issue on Quantitative Research Methodology). His current researchinterests include knowledge management and partial least squares methodology.

Antonio Leal, PhD, is currently Professor of Business Administration in the Department of BusinessAdministration and Marketing at the University of Seville, Spain. His recent publications haveappeared in OR Insight and Total Quality Management and Business Excellence. In addition, he has,besides, published several book chapters for Idea Group Publishing and Kluwer Academic Publish-ers. His research interests include knowledge management, total quality management, benchmarkingand organizational culture.



(2012) BJM

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