Organizational Learning Capability andJob Satisfaction: an Empirical Assessment

in the Ceramic Tile Industry

Ricardo Chiva and Joaquın Alegre1

Universitat Jaume I, Avda Sos Baynat s/n, Dep. d’Administracio d’Empreses i Marketing,

12071 Castello, Spain, and 1Universitat de Valencia, Avda Tarongers s/n, Dep. de Direccio d’Empreses

‘Juan Jose Renau Piqueras’, 46022 Valencia, Spain

Corresponding author email: rchiva@emp.uji.es

Organizational learning capability has been considered an essential issue of an

organization’s effectiveness and potential to innovate and grow. Although its positiveeffects on organizations and employees are generally assumed, there is no empirical

evidence of its positive association with employee attitudes such as job satisfaction. This

paper aims to investigate the relationship between organizational learning capabilityand job satisfaction through the questionnaire responses of 157 employees from eight

companies in the Spanish ceramic tile industry. Results suggest that organizational

learning capability and job satisfaction are strongly linked.

Introduction

During the past years, learning has become animportant subject in organizational contexts.Among the main reasons for this growingimportance are the rapidly changing environ-ment, the need for innovation and the relevanceof human resources for organizations. Thecapacity to learn has been considered a key indexof an organization’s effectiveness and potential toinnovate and grow (Jerez-Gomez, Cespedes-Lorente and Valle-Cabrera, 2005, p. 279). Con-sequently, organizations and academics haveincreasingly focused on enhancing organizationallearning capability (OLC) and building a learningorganization.OLC (Dibella, Nevis and Gould, 1996; Goh

and Richards, 1997; Hult and Ferrell, 1997;

Jerez-Gomez, Cespedes-Lorente and Valle-Cab-rera, 2005; Yeung et al., 1999) emphasizes theimportance of the facilitating factors for organi-zational learning or the organizational propensityto learn. We consider OLC as the organizationaland managerial characteristics that facilitate theorganizational learning process or allow anorganization to learn and thus develop a learningorganization. Organizational learning is generallydefined as a process (Sun, 2003, p. 160) and alearning organization is defined via the existenceof organizational conditions that favour learningper se (Lahteenmaki, Toivonen and Mattila,2001, p. 114). Consequently, the analysis of thefactors that facilitate organizational learning hastraditionally been dealt with in the learningorganization literature. However, research fromboth organizational learning and the learningorganization literatures have suggested factorsthat facilitate learning (Chiva, 2004).Job satisfaction, the degree to which people

like their jobs (Spector, 1997), is an extensivelyexplored research topic, due to its significantassociations with several variables such as

The authors would like to thank the Bancaja-UJIProgramme (Ref. P1-1A2002-18 and P1-1A2004-05) andthe Conselleria d’Empresa, Universitat i Ciencia Pro-gramme of the Generalitat Valenciana (Ref. GV05/082and GV06/082) for the financial support of this research.

British Journal of Management, Vol. 20, 323–340 (2009)DOI: 10.1111/j.1467-8551.2008.00586.x

r 2008 British Academy of Management. Published by Blackwell Publishing Ltd, 9600 Garsington Road, OxfordOX4 2DQ, UK and 350 Main Street, Malden, MA, 02148, USA.

organizational commitment (Fletcher andWilliams, 1996), job performance (Babin andBoles, 1996) and turnover intentions (Van Dicket al., 2004). Job satisfaction is an essentialindependent variable that can lead to employeebehaviours that affect organizational functioningand performance (Rowden, 2002), but also adependent variable, mainly influenced by work-ing and organizational conditions (e.g. Hackmanand Oldman, 1980; Herzberg, 1966). Some of themost relevant conditions, for instance participa-tive management (Kim, 2002) or continuousimprovement (Victor, Boynton and Stephens-Jahng, 2000), form the basis for a learningorganization (Ulrich, Jick and Von Glinow,1993).Although some studies assume the important

positive outcomes of the learning organization ordescribe its positive effect on firm performance(Ellinger et al., 2002), no research has providedempirical evidence of its positive links withemployee attitudes such as job satisfaction. Thispaper aims to investigate the relationship be-tween OLC and job satisfaction.In this paper OLC will be explained by five

dimensions: experimentation, risk taking, inter-action with the external environment, dialogueand participative decision making. Our identifi-cation of the five dimensions of OLC will bebased on complex adaptive systems and on acomprehensive and heterogeneous analysis of theliterature. As OLC is a complex multidimensionalconstruct, defined by several dimensions orcharacteristics (Dibella, Nevis and Gould, 1996;Jerez-Gomez, Cespedes-Lorente and Valle-Cab-rera, 2005), it is essential to understand therelationship of each of these dimensions with jobsatisfaction. Consequently, we provide an in-depth analysis of the relationship between thespecific characteristics we put forward as learningfacilitators and job satisfaction.In general, there is a relative shortage of

empirical research in the field of learning inorganizations. This research addresses this short-coming. Understanding whether OLC influencesjob satisfaction will help to determine its poten-tial relationship with employees’ job performanceor attitudes like commitment. Awareness ofwhether efforts to support OLC have a positiverelationship with employees’ performance willconstitute valuable information for the organiza-tion.

The purpose of our paper is to analyse therelationship of the different dimensions of OLCwith job satisfaction and to provide empiricalevidence that will clarify this association. To thisend, we analyse the relationship between OLCand job satisfaction through the responses of 157employees from eight companies in the Spanishceramic tile industry.

Literature review and hypotheses

OLC

Thought on learning in organizations has tradi-tionally been divided into two literatures: theorganizational learning literature and the learn-ing organization literature. The former hasfocused on the learning process of an organiza-tion and the latter on the factors that facilitatethis process or the guidelines to becoming alearning organization (Argyris and Schon, 1996;Chiva, 2004; Tsang, 1997).The organizational learning literature attempts

to analyse and determine whether and how acertain process of learning is being accomplishedin organizations (e.g. Crossan, Lane and White,1999). Organizational learning thinking has un-folded over time and many perspectives haveappeared. However, two main explanations seemto be put forward for how organizations learn(Chiva, 2004; Chiva and Alegre, 2005; Cook andYanow, 1996; Easterby-Smith, Snell and Gher-ardi, 1998): the individual and the social views.As Chiva (2004) explains, the individual viewconsiders learning as an individual phenomenonand consequently understands that organizationslearn through individuals (e.g. Huber, 1991); thesocial view considers learning as a social phe-nomenon and consequently understands thatorganizations learn through communities andgroups (e.g. Brown and Duguid, 1991). Never-theless, recent papers have begun to develop athird approach or perspective that attempts toencompass the two and/or rethink organizationallearning (e.g. Clegg, Kornberger and Rhodes,2005; Elkjaer, 2004; Ortenblad, 2002).The learning organization literature aims to

describe and analyse organizations, and thepeople in them, that learn constantly. Pedler,Burgoyne and Boydell (1997) define a learningorganization as an organization that facilitateslearning of all its members and continuously

324 R. Chiva and J. Alegre

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transforms itself. This literature focuses on thefacilitating factors for organizational learning oron the characteristics that define a learningorganization, in short, the contextual variablesthat facilitate learning (Jerez-Gomez, Cespedes-Lorente and Valle-Cabrera, 2005). Consequently,most of the studies that propose facilitatingfactors for organizational learning do so fromthe learning organization literature perspective(e.g. Goh and Richards, 1997; Pedler, Burgoyneand Boydell, 1997; Ulrich, Jick and Von Glinow,1993). However, the facilitating factors fororganizational learning have also been analysedby the organizational learning literature (Chiva,2004). As Chiva (2004) maintains, essentialproposals have been made by the social view(e.g. Brown and Duguid, 1991; Weick andWestley, 1996) and the individual view (e.g.Hedberg, 1981; Popper and Lipshitz, 2000).Consequently, any analysis of the literature onthe facilitating factors for organizational learningshould take both the organizational learning andthe learning organization literatures intoaccount.As previously stated, the concept of OLC has

already been used to emphasize the importance ofthe facilitating factors for organizational learningor the organizational propensity to learn (Dibel-la, Nevis and Gould, 1996; Goh and Richards,1997; Hult and Ferrell, 1997; Jerez-Gomez,Cespedes-Lorente and Valle-Cabrera, 2005;Yeung et al., 1999). OLC is defined as theorganizational and managerial characteristicsthat facilitate the organizational learning processor allow an organization to learn and thusdevelop a learning organization. It is assumedthat learning can be promoted when certainconditions are in place (Jerez-Gomez, Cespedes-Lorente and Valle-Cabrera, 2005).In order to determine which factors facilitate

organizational learning and to develop an OLCmeasurement scale, most papers have analysedpart of the literature, mainly the learningorganization literature (e.g. Goh and Richards,1997; Jerez-Gomez, Cespedes-Lorente and Valle-Cabrera, 2005). Although there are some veryinteresting tools that could have been considered,our aim was to develop a new and comprehensiveproposal, based on a process that has embracedthree analytical activities.First, we analysed complex adaptive systems,

steeped in complexity theory. Complex adaptive

systems are defined as systems composed ofinteracting agents following rules, exchanginginfluence with their local and global environ-ments and altering the very environment they areresponding to by virtue of their simple actions(Sherman and Schultz, 1998, p. 17). Duringrecent years, numerous researchers and practi-tioners have started to use complexity theory tobetter understand organizations (Dooley et al.,2003). As a consequence, theoretical models andproposals based on complex adaptive systemshave emerged on organizational and managerialissues. The main reasons for proposing the use ofthese systems are, first, that organizations areconsidered to be complex adaptive systems(Anderson, 1999; Axelrod and Cohen, 1999;Gell-Mann, 1994; Stacey, 1996) and, second, thatone of the most important characteristics of thesesystems is their capacity to learn (Gell-Mann,1994; Sherman and Schultz, 1998; Stacey, 1995,1996). One of the most significant findings ofcomplexity theorists is that learning happensthrough a process of self-organization, which isa consequence of agents’ interactions and con-nections. Interactions are therefore the essentialfacilitating factor for learning in complex adap-tive systems. However, interaction is too generala concept, and is better understood through itsinteracting agents (relationships) and its contex-tual characteristics. As an organization is com-posed of the social interactions among actors (asocial actor can be an individual or a collectivesuch as a group), objects and norms (Casey,2005), we understand there are two main types ofinteractions: actor–artefact (objects, norms, va-lues etc.) and actor–actor. The actor–artefactinteraction is mainly considered as experimenta-tion, as it involves questioning how things workor inquiring into processes or norms. This impliestrying out new ideas and suggestions, which issupported by risk taking acceptance. The actor–actor interaction could be divided into two: theinteractions between actors within the organiza-tions (dialogue) and the interactions betweenactors of the organization and actors fromoutside the organization (interaction with theexternal environment). Furthermore, these inter-actions will be supported by participative deci-sion making (Ashmos et al., 2002). According tothese authors, participative decision makingenhances connectivity in organizations which, inturn, gives the opportunity to learn. In sum, five

Organizational Learning Capability and Job Satisfaction 325

r 2008 British Academy of Management.

organizational learning facilitating factors areproposed: experimentation, risk taking, dialogue,interaction with the external environment andparticipative decision making.Figure 1 shows the OLC conceptual model.

The figure includes the dimensions of the model.The second analytical activity involved an

analysis of certain authors from several perspec-tives or literatures. In his review of the facilitatingfactors for learning, Chiva (2004) took intoaccount authors from both organizational learn-ing and learning organization literatures. Wetook the same comprehensive approach andanalysed the same authors. Table 1 shows thekey conditions for learning as identified by theseworks and also describes how the key conditionsin the literature were related to our five under-lying dimensions: experimentation, risk taking,interaction with the external environment, dialo-gue and participative decision making.The five underlying dimensions integrated the

15 facilitating factors proposed by Chiva (2004),which were obtained through a literature reviewand by conducting 60 interviews in four compa-nies in the Spanish ceramic sector. These facil-itating factors were grouped together or includedin several dimensions with the aim of simplifyingthe Chiva (2004) proposal and developing ameasurement scale. In ‘experimentation’, we haveincluded concepts like support for new ideas,continuous training or workers that want to learnand improve. In ‘dialogue’, we considered ideassuch as communication, diversity, teamwork, orcollaboration. In ‘participative decision making’,we incorporated delegation, flexible organiza-tional structure, or knowledge of the organiza-

tion. Several factors were considered to beimplicit in all five underlying dimensions: com-mitment to learning, involved leadership andlearning as an essential element in the strategy.The third analytical activity consisted of

analysing the five facilitating factors throughthe literature in order to improve our under-standing of them and to confirm their importancein several heterogeneous papers and perspectives.We now describe our proposal of the five OLCdimensions through the literature.Experimentation can be defined as the degree

to which new ideas and suggestions are attendedto and dealt with sympathetically. Experimenta-tion seems to be the most heavily supporteddimension in the organizational learning litera-ture (Goh and Richards, 1997; Hedberg, 1981;Nevis, DiBella and Gould, 1995; Pedler, Bur-goyne and Boydell, 1997; Tannenbaum, 1997;Ulrich, Jick and Von Glinow, 1993; Weick andWestley, 1996). Nevis, DiBella and Gould (1995)consider that experimentation involves trying outnew ideas, being curious about how things work,or carrying out changes in work processes. Itincludes the search for innovative solutions toproblems, based on the possible use of distinctmethods and procedures (Garvin, 1993).Risk taking can be understood as the tolerance

of ambiguity, uncertainty and errors. Sitkin(1996, p. 541) goes as far as to state that failureis an essential requirement for effective organiza-tional learning, and to this end examines theadvantages and disadvantages of success anderror. If the organization aims to promote short-term stability and performance, then success isrecommended, since it tends to encourage main-tenance of the status quo. According to Sitkin(1996, p. 547), the benefits brought about byerror are risk tolerance, prompting of attention toproblems and the search for solutions, ease ofproblem recognition and interpretation, andvariety in organizational responses. Since theappearance of this work, many authors haveunderlined the importance of risk taking andaccepting mistakes, thus enabling organizationsto learn (Popper and Lipshitz, 2000; Ulrich, Jickand Von Glinow, 1993).Interaction with the external environment can

be defined as the scope of relationships with theexternal environment. Environmental character-istics play an important role in learning, and theirinfluence on organizational learning has been

Experimentation

Interaction with theexternal environment

Dialogue

Participative decisionmaking

OrganizationalLearning

Capability

Risk taking

InteractionActor–Artefact

InteractionActor–Actor

Figure 1. OLC dimensions

326 R. Chiva and J. Alegre

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Table1.Key

conditionsforOLC

Author/s

Key

conditions

Experim

ent

Risk

taking

Interactionwith

theexternal

environment

Dialogue

Participative

decisionmaking

Ulrich,Jick

and

VonGlinow

(1993)

U1.Buildacommitmentforlearning(m

akeitstrategic,

investin

learning,talk

aboutlearning,measure

it...)

��

��

�

U2.Work

togenerate

ideaswithim

pact

(continuousim

provem

ent,

competence

acquisition,experim

entation,boundary–

environmentspanning)

��

U3.Work

togeneralize

ideaswithim

pact

(sharedmindset,

welcominginquiry,supportingfailures,dialogue...),leadership

��

��

Nevis,DiBella

and

Gould

(1995)

N1.Scanningim

perative(environmentalanalysis)

�N2.Perform

ance

gap

��

��

�N3.Concern

formeasurement

��

��

�N4.Experim

entalmindset

�N5.Climate

foropenness(interaction,dialogue,

communication...)

�N6.Continuouseducation

�N7.Operationalvariety(diversity)

�N8.Multiple

advocates(experim

entationandparticipation)

��

N9.Involved

leadership

��

��

�N10.System

sperspective(connections)

��

GohandRichards(1997)

G1.Clarity

ofpurpose

andmission(readyaccessto

inform

ation)

�G2.Leadership

commitmentandem

powerment(toexperim

ent,

takerisks,communicate

etc.)

��

��

�

G3.Experim

entation

�G4.Transfer

ofknowledge(internalandexternal;communication

andfailuresdiscussion)

��

��

G5.Teamwork

andgroupproblem

solving

��

Pedler,Burgoyneand

Boydell(1997)

P1.A

learningapproach

tostrategy

��

��

�P2.Participativepolicy

making

�P3.Inform

ing

�P4.Form

ativeaccountingandcontrol

�P5.Internalexchange

�P6.Rew

ard

flexibility

�P7.Enablingstructures

�P8.Boundary

workersasenvironmentalscanners

��

3P9.Inter-companylearning

��

P10.A

learningclim

ate

��

�P11.Self-developmentopportunitiesforall

��

�Hedberg(1981)

H1.Promotingexperim

entation

��

�H2.Regulatingawareness

��

H3.Redesigningenvironments

��

H4.Achievingdynamic

balances

��

Tannenbaum

(1997)

T1.Assignsto

provideopportunityto

learn

�3T2.Toleratesmistakes

aspart

oflearning

�

Organizational Learning Capability and Job Satisfaction 327

r 2008 British Academy of Management.

studied by a number of researchers (Bapuji andCrossan, 2004, p. 407). Relations and connec-tions with the environment are crucial, since theorganization attempts to evolve simultaneouslywith its changing environment. According toNevis, DiBella and Gould (1995), in recent yearsresearchers have stressed the importance ofobserving, opening up to and interacting withthe environment (e.g. Goh and Richards, 1997;Ulrich, Jick and Von Glinow, 1993).In particular, authors from the social view

(Brown and Duguid, 1991; Weick and Westley,1996) highlight the importance of dialogue andcommunication for organizational learning. Dia-logue is defined as a sustained collective inquiryinto the processes, assumptions and certaintiesthat make up everyday experience (Isaacs, 1993,p. 25). Schein (1993, p. 47) considers dialogue asa basic process for building common under-standing in that it allows one to see the hiddenmeanings of words, first by revealing these hiddenmeanings in our own communication. Someauthors (Dixon, 1997; Isaacs, 1993; Schein,1993) understand dialogue to be vitally importantto organizational learning.Participative decision making refers to the level

of influence employees have in the decision-making process (Cotton et al., 1988). Organiza-tions implement participative decision making tobenefit from the motivational effects of increasedemployee involvement, job satisfaction and orga-nizational commitment (Daniels and Bailey,1999; Latham, Winters and Locke, 1994; Scott-Ladd and Chan, 2004; Witt, Andrews andKacmar, 2000). Scott-Ladd and Chan (2004)provide evidence to suggest that participativedecision making gives better access to informa-tion and improves the quality and ownership ofdecision outcomes. Parnell and Crandall (2000)also maintain that divulging information is arequirement for participative decision making.Subordinates are assumed to be informed inorder to participate efficiently. Bapuji and Cross-an (2004), Goh and Richards (1997), Nevis,DiBella and Gould (1995), Pedler, Burgoyneand Boydell (1997) and Scott-Ladd and Chan(2004) consider participative decision making tobe one of the aspects that can facilitate learning.In sum, we propose these five facilitating

factors or OLC dimensions as essential for anorganization to be considered as a learningorganization. As they are dimensions for OLC,

T3.Assignsto

avoid

errors

��

T4.Highperform

ance

expectations/accountability

�T5.Open

tonew

ideas/change

�T6.Policies

andpractices

support

training

�T7.Supervisors

support

training

�T8.Co-w

orkerssupport

new

ideas

�T9.Awarenessofbig

picture

�Popper

andLipshitz(2000)

L1.Environmentaluncertainty

�L2.Costly

potentialerrors

�L3.Highlevel

ofmem

bers’professionalism

��

L4.Strongleadership

commitmentto

learning

�BrownandDuguid

(1991)

B1.Narration

�B2.Collaboration

�B3.Socialconstruction

�Weick

andWestley

(1996)

W1.Humour

��

W2.Im

provisation

��

W3.Smallwins

�

Table1.(continued)

Author/s

Key

conditions

Experim

ent

Risk

taking

Interactionwith

theexternal

environment

Dialogue

Participative

decisionmaking

328 R. Chiva and J. Alegre

r 2008 British Academy of Management.

the stronger they are, the higher the learningpotential will be.

Linking OLC and job satisfaction

Job satisfaction is considered to be a centralconcept in organizations, as it mediates therelation between working conditions on the onehand and organizational and individual out-comes on the other (Dormann and Zapf, 2001).The situational approach to job satisfaction (e.g.Hackman and Oldman, 1980; Herzberg, 1966)considers this issue to be primarily determined bythe characteristics of the job. Working conditionssuch as communication, task variety or respon-sibility are believed to be highly responsible forjob satisfaction.Job satisfaction can be considered either as a

related constellation of attitudes about variousaspects or facets of the job or as an overallperception of the job (Spector, 1997). The first,the facet approach, is used to find out whatelements of the job produce satisfaction ordissatisfaction. This can be particularly usefulfor organizations that wish to identify areas ofdissatisfaction that they want to improve. As amultifaceted construct, job satisfaction includesboth intrinsic and extrinsic elements of the job(Howard and Frick, 1996; Warr, Cook and Wall,1979). The second, the global approach, is usedto assess overall job satisfaction in relation toother variables of interest, for instance OLC. Asingle item measure is generally used to assessoverall job satisfaction (Wanous, Reichers andHudy, 1997). Although the use of a single itemmeasure is often questioned, empirically novalidity or reliability appears to be lost (Ganzach,1998; Wanous and Reichers, 1996; Wanous,Reichers and Hudy, 1997).Perception of job satisfaction is influenced by

two aspects: the pleasant mood or state affect andthe job beliefs or cognition on job satisfaction(Ilies and Judge, 2004; Weiss, 2002). A single itemsurvey is better positioned to capture cognitiveassessments of the job than affective experiencesof the job (Ilies and Judge, 2002). Consequently,a single item measure seems to be appropriate toassess job satisfaction and relate it to certainworking conditions that facilitate organizationallearning.Research suggests that job satisfaction, as a

work-related outcome, is influenced by certain

organizational and managerial characteristics.Below we analyse the linkage between ourproposal of the underlying dimensions of OLCand job satisfaction.

Experimentation and risk taking. Victor, Boyn-ton and Stephens-Jahng (2000) presented evi-dence that continuous improvement at workgenerates job satisfaction. When experimentingand working on continuous improvement tasksRohlen (1989) observed a diffusion of responsi-bility, horizontal communication patterns, andan expectation by managers for worker partici-pation and thoughtful contribution from allmembers of the organization. The freedomemployees have to do their jobs as they see fit,to experiment, to improve processes etc. willincrease their motivation and satisfaction (Hack-man and Oldman, 1976). As previously stated,experimenting also implies making mistakesand taking risks. An organization that allowsor even supports risks and mistakes willfacilitate experimentation and task autonomy.In light of the above, we propose the followinghypotheses.

H1: Experimentation is positively related tojob satisfaction.

H2: Risk taking is positively related to jobsatisfaction.

Interaction with the external environment, dialo-gue, and participative decision making. Accord-ing to Pincus and Rayfield’s (1989) meta-researchon communication and job satisfaction, there is apositive but complex relationship between em-ployees’ perception of various types of organiza-tional communication and their perceived jobsatisfaction. Further research (Pincus, Knipp andRayfield, 1990) confirmed this positive relation-ship. Similarly, Monge et al. (1985) claimedthat the proximity among people in anorganization exerts considerable influence on avariety of organizational outcomes such as jobsatisfaction.

Gaertner (2000) states that leadership beha-viours related to inspiring teamwork, challengingtradition, or enabling others have been shownto have significant effects on job satisfaction.

Organizational Learning Capability and Job Satisfaction 329

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Griffin, Patterson and West (2001) found that theextent of teamwork is positively related toperceptions of job autonomy, which in turnaffects job satisfaction. Valle and Witt (2001)consider teamwork as a relevant aspect toimprove job satisfaction.Communication, dialogue, teamwork, interac-

tion with the external environment and colla-boration represent trust and proximity, which inturn motivate and increase commitment, andfinally satisfy employees.Bussing et al. (1999) detected a connection

between job satisfaction and employee engage-ment. According to Kim (2002), participativemanagement that incorporates effective super-visory communication can increase job satisfac-tion. Wagner and LePine (1999) conducted ameta-analysis and revealed significant impacts ofjob participation and work performance on jobsatisfaction. Daniels and Bailey (1999) concludedthat participative decision making increases thelevel of job satisfaction. Eylon and Bamberger(2000) reported that empowerment had a signifi-cant impact on job satisfaction. Johnson andMcIntye (1998) found that the measures of culturemost strongly related to job satisfaction wereempowerment, involvement and recognition.Given the potential relationship between inter-

action with the external environment, dialogueand participative decision making and job satis-faction, the following hypotheses are proposed.

H3: Interaction with the external environmentis positively related to job satisfaction.

H4: Dialogue is positively related to jobsatisfaction.

H5: Participative decision making is positivelyrelated to job satisfaction.

These studies have examined the associationsof some individual dimensions related to ourunderlying dimensions of OLC; however, thecorrelation of the full range of these dimensionswith job satisfaction is not known. Egan, Yangand Bartlett (2004) found that organizationallearning culture is associated with job satisfac-tion. Lyles and Easterby-Smith (2003, p. 644)state that clear empirical evidence exists to showhow organizational learning impacts on firmperformance. Several papers (Bontis, Crossanand Hulland, 2002; Ellinger et al., 2002) haveexamined the relationship between organizationallearning and firm financial performance, suggest-ing a positive association between the two. Insum, organizational learning and the learningorganization have been theoretically related topositive organizational performance. Moreover,Hwang and Chi (2005) have recently providedempirical evidence of the positive effects of jobsatisfaction on organizational performance. Con-sequently we can hypothesize:

.......................

V1 V2.......................V1 V2.......................

V3 V4.......................V3 V4.......................

V5 V7.......................V5 V7.......................

V8 V11.......................V8 V11.......................

V12 V14V12 V14

EX

RI

ENV

DI

EXP

RISK

ENV

DIALOG

OLCOLCJOB

SATISFACTION V17V17

EDUEDU AGEAGE

V15V15 V16V16

PARTICIP

Figure 2. OLC and job satisfaction

330 R. Chiva and J. Alegre

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H6: OLC is positively related to job satisfac-tion.

Figure 2 summarizes the proposed conceptualmodel.

Methods

Sample and data collection procedure

We tested our hypotheses in the Spanish ceramictile industry. Ceramic tile production is aglobalized industry whose features belong to thescale-intensive and science-based trajectories ofPavitt’s taxonomy (Alegre, Lapiedra and Chiva,2004). In the production of ceramic tiles,technological accumulation is mainly generatedby (1) the design, building and operation ofcomplex production systems (scale-intensive tra-jectory) and (2) knowledge, skills and techniquesemerging from academic chemistry research(science-based trajectory). Previous studies pro-vide compelling evidence of the significantinnovating behaviour of Spanish ceramic tileproducers (Alegre, Lapiedra and Chiva, 2004;Chiva, 2004). Innovation seems to be related toorganizational learning practices (Hurley andHult, 1998; McKee, 1992).The biggest ceramic tile producers are China

followed by Spain, Italy, Brazil and Turkey.However, Italian and Spanish firms are the firstand second world exporters, respectively. This ismainly due to their high quality value addedproducts, achieved through the emphasis oninnovation, design, technology and corporateimage (Valencia Chamber of Commerce, 2004).

Most of the Spanish firms in this sector are smalland medium-sized enterprises, as they do notexceed an average of 250 workers; they aregeographically concentrated in an industrialdistrict located in the province of Castellon. Asthis is a dynamic and innovating industry, weconjectured that some companies would bedeveloping organizational learning practices.The field work was carried out from January to

April 2004. In order to obtain more descriptivedata from the sector we purposefully selected,with the help of Technological Institute ofCeramics (ITC-ALICER) technicians, eight cera-mic tile manufacturers that are representative ofthe two main design strategies in the ceramic tileindustry (Chiva, 2004): firms 1–4 are designfollowers, while firms 5–8 are design innovatingcompanies. Design is an important competitiveissue in the ceramic tile industry and is closelyrelated to organizational learning.The questionnaire was addressed to the opera-

tions workers in each organization. We excludedmanagers in order to obtain a homogeneous setof respondents who expressed their perception ofOLC in their organization.We received a total of 157 valid questionnaires,

which represents 61% of the study population(see Table 2). Both the number of responses andthe response rate can be considered satisfactory(Janssen and Van Yperen, 2004).We asked workers, in company time, to answer

the overall job satisfaction and OLC question-naire with reference to their organization. Inorder to reinforce confidentiality no managerswere present when the questionnaire was being

Table 2. Response rates and descriptive statistics

Firm 1 Firm 2 Firm 3 Firm 4 Firm 5 Firm 6 Firm 7 Firm 8 Total

Total number of workers 50 40 20 20 25 30 35 35 255

Total number of cases 35 19 14 11 25 20 15 18 157

Response rate 70% 47% 70% 55% 100% 66% 42% 51% 61%

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Experimentation 3.54 1.15 3.00 1.08 2.86 0.97 3.05 1.12 4.88 1.08 3.63 1.09 3.73 1.03 4.14 1.03 3.69 1.54

Risk taking 3.33 0.94 2.37 1.10 2.61 1.16 2.73 1.04 4.18 0.79 3.78 1.14 2.93 0.84 3.39 1.01 3.26 1.47

Interaction with the

external environment

2.56 1.16 2.00 1.00 2.19 1.02 2.88 1.06 4.56 1.05 3.18 1.09 3.73 1.04 4.35 0.92 3.20 1.49

Dialogue 3.56 1.17 3.45 1.00 3.80 1.09 4.16 1.07 4.05 1.14 3.59 1.05 3.62 0.99 5.03 1.01 3.87 1.48

Participative decision

making

2.37 1.06 2.25 1.01 1.98 0.82 2.55 1.05 3.19 1.11 2.82 1.13 2.58 1.07 3.72 1.10 2.69 1.64

Organizational learning

capability

3.06 1.07 2.66 0.96 2.76 0.67 3.18 1.05 4.11 0.93 3.37 1.04 3.34 0.89 4.24 0.84 3.36 1.32

Job satisfaction 4.59 1.63 5.22 1.20 4.93 1.81 4.67 1.03 5.14 1.15 4.90 1.29 5.19 1.11 4.47 1.59 4.89 1.41

Calculations based on the means of each construct.

Organizational Learning Capability and Job Satisfaction 331

r 2008 British Academy of Management.

answered. However, a researcher was constantlyon hand to immediately solve any doubts. The setof responses for a particular organization enabledus to determine its OLC. Table 2 and Table 3show the descriptive statistics.

Measures

Overall job satisfaction. In this research weconsider job satisfaction as a global perceptionof the job (Spector, 1997), which is generally usedto assess overall job satisfaction in relation toother variables of interest such as OLC. A singleitem measure is regularly used to estimate overalljob satisfaction (Wanous, Reichers and Hudy,1997). The measure of overall job satisfactionwas derived from answers to the question ‘Howmuch do you like your job?’ expressed on aseven-level response scale ranging from ‘dislike itvery much’ to ‘like it very much’. A single item tomeasure job satisfaction is used in several studies(Ganzach, 1998; Gerhart, 1987; Staw and Ross,1985). Ganzach (1998) explains that, althoughreliance on a single item is often open to question,the construct validity of a single item measuremay be higher than that of a multiple itemmeasure and no loss of reliability is likely tooccur (Wanous and Reichers, 1996; Wanous,Reichers and Hudy, 1997).Perception of job satisfaction is influenced by

both emotional and cognitive facets (Ilies andJudge, 2004; Weiss, 2002). A single item surveyseems to capture the cognitive facets ofthe job more conveniently (Ilies and Judge,2002, 2004). We regard the use of a single itemmeasure of job satisfaction as appropriate since itis being considered as an overall perception of

the job that aims to capture mainly the cognitiveassessments of the job (Ilies and Judge, 2002).

OLC. In accordance with our research analysis,we propose five dimensions to represent theessential factors that determine OLC or OLCdimensions: experimentation, risk taking, inter-action with the external environment, dialogueand participative decision making. Based on ourproposal of five OLC dimensions explainedabove, we proceed to the development of ameasurement instrument comprising a set ofitems from scales that represent our five theore-tical dimensions or latent variables. Spector(1992) argues that the content of existing scalesmay help in the development of a new scale.Accordingly, we selected a brief number of itemsfrom other scales that could synthesize thecontent of each OLC dimension. For example,for experimentation, we reviewed the measure-ment scales in the literature that exist for thisconcept and we found that two items from theIsaksen, Lauer and Ekvall (1999) creative climatemeasurement scale could adequately representthe experimentation dimension we propose in thetheory section. Table 4 shows the literaturesource of each item of our proposed OLCmeasurement scale.The OLC measurement instrument was applied

using a seven-point Likert scale, where 1 repre-sented total disagreement and 7 total agreement.A pre-test was administered to four techniciansfrom ALICER to ensure (1) that the translationinto Spanish was fully understandable, and (2)that the items could be easily understood in thecontext of ceramic tile production. There is no

Table 3. Means, standard deviations, composite reliabilities, Cronbach alphas and correlations between the dimensions of the OLC

construct

Mean Standard

deviation

Composite

reliability

EXP RISK ENV DIALOG PARTICIP

EXP 3.69 1.54 0.78 (0.89)

RISK 3.27 1.31 0.65 0.488** (0.74)

ENV 3.20 1.57 0.76 0.561** 0.480** (0.84)

DIALOG 3.87 1.30 0.80 0.505** 0.344** 0.470** (0.86)

PARTICIP 2.69 1.40 0.78 0.533** 0.481** 0.593** 0.541** (0.85)

JOB SATISF 4.88 1.42 – 0.302** 0.158* 0.162* 0.381** 0.308**

All correlation coefficients are statistically significant (**po0.01; *p o0.05).Cronbach alphas are shown on the diagonal.To calculate the correlation coefficients we worked with the means of the items that make up each dimension.

332 R. Chiva and J. Alegre

r 2008 British Academy of Management.

general agreement about how large a pre-testsample should be. According to Hunt, Sparkmanand Wilcox (1982), the pre-test sample should bea function of the instrument and the targetpopulation. Although a four-respondent pre-testsample could seem small, we believe that, giventhe industry characteristics and the competenceof the pre-test respondents, it is satisfactory. TheSpanish ceramic tile industry is concentrated inan industrial district (with a diameter of around30 kilometres) and is fairly homogeneous. Inaddition, the ALICER technicians who partici-pated in the pre-test have a wide knowledge ofday-to-day issues affecting operations workers.

Control variables

Employee-based surveys addressing job satisfac-tion typically include individual control variablessuch as gender, age, ethnic origin, area ofresidence (rural/non-rural) and education (Gan-zach, 1998).The target population of our study consisted of

a particularly homogeneous set of individuals:operations workers. Respondents were Spanish

male blue-collar workers who had been workingfor their firm for at least two years. Gender andethnic origin was the same for all respondents.The eight participant firms were all located in theceramic industrial district of Castellon: the areaof residence of respondents is non-rural.We controlled purposefully for education and

age. We distinguished two levels of education:basic education and basic education plus occupa-tional training. We defined four age groups:below 26, from 26 to 35, from 36 to 45, and above45 years. Control variables were designed toprevent respondents’ identification and thusenhance the response rate.

Analyses

The initial analyses of the data set are based onstructural equations modelling. Structural equa-tions models have been developed in a number ofacademic disciplines to substantiate theory. Thisapproach involves developing measurement mod-els to define constructs and then establishingrelationships or structural equations among theconstructs. Maximum likelihood is an asymptotic

Table 4. Items and dimensions comprising the OLC scale

Dimension Item Literature source

Experimentation 1. People here receive support and encouragement

when presenting new ideas

Isaksen, Lauer and Ekvall (1999)

2. Initiative often receives a favourable response here

so people feel encouraged to generate new ideas

Isaksen, Lauer and Ekvall (1999)

Risk taking 3. People are encouraged to take risks in this

organization

Amabile et al. (1996)

4. People here often venture into unknown territory Isaksen, Lauer and Ekvall (1999)

Interaction with

the external

environment

5. It is part of the work of all staff to collect, bring

back and report information about what is going

on outside the company

Pedler, Burgoyne and Boydell (1997)

6. There are systems and procedures for receiving,

collating and sharing information from outside

the company

Pedler, Burgoyne and Boydell (1997)

7. People are encouraged to interact with the

environment: competitors, customers,

technological institutes, universities, suppliers etc.

Pedler, Burgoyne and Boydell (1997)

Dialogue 8. Employees are encouraged to communicate Templeton, Lewis and Snyder (2002)

9. There is a free and open communication within

my work group

Amabile et al. (1996)

10. Managers facilitate communication Pedler, Burgoyne and Boydell (1997)

11. Cross-functional teamwork is a common practice

here

Hult and Ferrell (1997)

Participative

decision making

12. Managers in this organization frequently involve

employees in important decisions

Goh and Richards (1997)

13. Policies are significantly influenced by the view of

employees

Pedler, Burgoyne and Boydell (1997)

14. People feel involved in main company decisions Pedler, Burgoyne and Boydell (1997)

Organizational Learning Capability and Job Satisfaction 333

r 2008 British Academy of Management.

estimator, which means large samples are requiredfor stable, consistent estimates. One common rule-of-thumb on the minimum threshold for imple-menting structural equations models and fortesting measurement scales’ psychometric proper-ties is that the sample should exceed 100 subjects(Spector, 1992; Williams, Gavin and Hartman,2004). Our sample satisfies this threshold.EQS 5.7 software was used to estimate the

models for our research hypotheses. Confirma-tory factor analysis was used to check thegoodness of the measurement scales; this methodalso provides the correlations between factors ordimensions and the construct of interest (Muel-ler, 1996, p. 125).

Results

Psychometric properties of the OLCmeasurement scale

The psychometric properties of the measurementscale were evaluated by following acceptedpractice in the literature (Anderson and Gerbing,1988) and included establishment of scale dimen-sionality, reliability, content validity, convergentvalidity and discriminant validity (Tippins andSohi, 2003). To confirm dimensionality of theOLC higher-order construct we ran second-orderconfirmatory factor analyses. The loadings of themeasurement items on the first-order factors andthe loadings of the first-order factors on thesecond-order factors were all significant. Thecomparative fit index exceeded the recommendedthreshold of 0.90 for the measurement model,indicating good model fit and confirmation ofscale dimensionality.We computed both Cronbach’s alpha coeffi-

cient and composite reliability to assess scalereliability. Table 3 shows the reliability evalua-tion for each dimension. The composite reliabilityvalues and the Cronbach’s alpha coefficients arehighly satisfactory, all above 0.7 (Hair et al.,1998; Nunnally, 1978).Content validity was established through the

following actions. First, the generation of thedimensions and the items was well grounded inthe literature, and the scale was created inaccordance with procedures accepted in theliterature (Churchill, 1979; DeVellis, 1991; Spec-tor, 1992). Second, personal interviews withknowledgeable industry experts (i.e. ALICER

technicians) were conducted to make sure thatthe items were easy to respond to (Bearden,Netemeyer and Mobley, 1999, p. 4).Discriminant and convergent validity were

assessed with confirmatory pairwise analyses.The discriminant validity of the OLC dimensionswas ascertained by comparing measurementmodels in which the correlation between theconstructs was estimated by a model with thecorrelation constrained to 1 (thereby assuming asingle-factor structure). The discriminant validitywas examined for each pair of constructs at atime (Table 5). Results show that the model inwhich the correlation is not equal to 1 improvesthe fit for all pairs of constructs, confirming thatthe two constructs are distinct from each other,although they may possibly be significantlycorrelated (Bagozzi, Yi and Phillips, 1991).Convergent validity of the OLC dimensions

was assessed by comparing a measurement modelin which the correlation between the twoconstructs was estimated by a model with thecorrelation constrained to 0. Results showsignificant improvements in the pairwise fits,indicating that the two constructs are indeedrelated, and confirming convergence validity(Table 5). Combining the two tests demonstratesthat the two constructs are different, thusevidencing discriminant validity, although theymay be related, evidencing convergent validity(Gatignon et al., 2002).

OLC and job satisfaction

Hypotheses 1–5 deal with the relationship be-tween each OLC dimension and job satisfaction.Previous theory led us to argue that positiverelationships were to be expected. Table 3 showsthe correlations between these six concepts. Jobsatisfaction has a significant and positive correla-tion with experimentation, risk taking, interac-tion with the external environment, dialogue, andparticipative decision making. This result pro-vides support for Hypotheses 1–5. OLC dimen-sions have a significant, positive and moderatelink with job satisfaction. Job satisfaction de-pends on a number of factors, but this researchoutlines that, if it is to be improved, OLCdimensions should be taken into account.Table 6 shows the results of the structural

equations modelling analysis. The chi-squaredstatistic for the model is not significant (p5 0.12);

334 R. Chiva and J. Alegre

r 2008 British Academy of Management.

therefore the null hypothesis of perfect fit cannotbe rejected. Additionally, other relevant fitindices suggest a good overall fit (Bollen, 1989).Results show a positive relationship betweenOLC and job satisfaction and lend support toHypothesis 6. Having tested the model satisfac-torily, we can claim that there is compellingevidence of a positive link between OLC and jobsatisfaction (a5 0.431, t5 4.984).Furthermore, the structural equations model

provides additional support for Hypotheses 1–5.The measurement model (first-order factors)indicates that there is an important, positiveand significant relationship between OLC and itsfive dimensions: experimentation (b15 0.790),risk taking (b25 0.711, t5 6.411), interactionwith the environment (b35 0.800, t5 6.721),dialogue (b45 0.731, t5 8.296) and participativedecision making (b55 0.834, t5 8.015). High (orlow) levels of the five dimensions reveal a high (orlow) level of OLC. Since there is also a positivelink between OLC and job satisfaction, we findsupport for Hypotheses 1–5. Results bear outthat the higher the level of experimentation, riskT

able5.Pairwiseconfirm

atory

analyses:

estimatesofcorrelations

Experim

entation

Risktaking

Interactionwithexternalenvironment

Dialogue

Participativedecisionmaking

fdf

w2Dw2

pf

df

w2Dw2

pf

df

w2Dw2

pf

df

w2Dw2

pf

df

w2Dw2

p

RISK

0.60*

10.73

0.39

12

11.18

10.45

0.00

02

7.29

6.56

0.02

ENV

0.64*

40.82

0.93

0.60*

410.22

0.04

15

10.71

9.89

0.05

15

15.82

5.60

0.00

05

25.69

24.87

0.00

05

41.18

30.96

0.00

DIA

LOG

0.60*

813.44

0.10

0.41*

86.18

0.63

0.56*

13

16.30

0.23

19

21.24

7.80

0.01

19

15.54

9.36

0.07

114

22.91

6.61

0.06

09

42.41

28.97

0.00

09

19.62

13.44

0.02

014

51.29

34.99

0.00

PARTIC

IP0.62*

44.83

0.30

0.60*

43.63

0.46

0.68*

89.44

0.30

0.63*

13

13.39

0.42

15

13.32

8.49

0.02

15

7.11

3.48

0.21

19

14.59

5.12

0.10

114

25.99

12.60

0.02

05

24.97

20.14

0.00

05

27.34

23.71

0.00

09

76.27

66.83

0.00

014

60.85

47.46

0.00

JOB

SATISF.

0.29*

10.05

0.82

0.121

10.33

0.56

0.16

23.30

0.19

0.39*

54.29

0.51

0.30*

24.80

0.09

12

83.98

83.93

0.00

12

25.59

25.26

0.00

13

43.58

40.28

0.00

16

46.17

41.88

0.00

13

46.17

41.37

0.00

02

13.71

13.66

0.00

02

2.52

2.19

0.28

03

6.51

3.21

0.09

06

25.81

21.52

0.00

03

25.81

21.01

0.00

*Factorloadingssignificantatthe5%

level.

Table 6. Structural equations model analysis

Parameter Direct effect model

Hypothesized path

OLC ! JS 0.431 (4.984)

Control measure

EDU ! JS 0.316 (4.009)

AGE ! JS 0.006 (0.075)

Measurement model and first-order factors

OLC ! EXP 0.790a

OLC ! RISK 0.711 (6.411)

OLC ! ENV 0.800 (6.721)

OLC ! DIALOG 0.731 (8.296)

OLC ! PARTICIP 0.834 (8.015)

Goodness-of-fitness statistics

w2 131.86 (p5 0.12)

df 114

Bentler–Bonnet normed fit

index (NFI)

0.885

Bentler–Bonnet non-normed fit

index (NNFI)

0.954

Comparative fit index (CFI) 0.962

Root mean square error of

approximation (RMSEA)

0.053

aThe parameter was put equal to 1 to fix the latent variable

scale.Parameter estimates are standardized with t values shown inparentheses.OLC is a second-order factor. For brevity, only the first-orderloadings are shown. The item loadings for these first-orderfactors were all significant at po0.01.

Organizational Learning Capability and Job Satisfaction 335

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taking, interaction with the environment, dialo-gue, and participative decision making, the high-er the level of job satisfaction will be.Regarding the model control variables, age has

a low and insignificant effect on job satisfaction.On the other hand, evidence has been found tosupport the links of education with job satisfac-tion. Previous research maintains that the higherthe level of education attained, the more satisfiedwith their jobs people are (Ganzach, 1998).However, this claim should be regarded withcaution as these employees usually carry outmore complex tasks that generally involveautonomy, skill variety or task significance, allof which are considered to increase job satisfac-tion (Hackman and Oldman, 1976, 1980).

Discussion

We have analysed the relationship between thefive dimensions that make up OLC and jobsatisfaction. Following similar studies (Jerez-Gomez, Cespedes-Lorente and Valle-Cabrera,2005), we have underlined the complex andmultidimensional nature of learning. The empiri-cal findings presented in this paper suggest thatOLC is explained by five dimensions: experimen-tation, risk taking, interaction with the externalenvironment, dialogue and participative decisionmaking. Our identification of the five dimensionsof OLC was based on complex adaptive systemsand on a comprehensive and heterogeneousanalysis of the literature.Our paper provides evidence to support the

relationship between OLC and job satisfaction.Although the literature usually assumes theimportant positive outcomes of the learningorganization, little research has analysed itsconnections empirically. Some researchers de-scribe its positive effect on firm performance (e.g.Ellinger et al., 2002), but no research hasprovided empirical evidence of its positiveassociations with employee-related issues suchas job satisfaction. Nevertheless, the link betweenorganizational learning and firm performanceinvolves a series of questions that should beprioritized in discussions on this topic (Baldwinand Danielson, 2002). One of the most relevantquestions is the use of overall financial perfor-mance as a dependent variable for assessing thesuccess of organizational learning. Financial

performance is influenced by many factors overtime: economic environment, accounting prac-tices, new product or technique launches etc.Ray, Barney and Muhanna (2004) explain thelimitations of studying capabilities or resourcesand then correlating them with particular mea-sures of firm performance. One of the explana-tions these authors give is that not everything hasan effect on business performance: for example acapability may increase competitive advantagebut certain stakeholders may appropriate theprofits before they can affect a firm’s overallperformance. As a result, other potential associa-tions of organizational learning with organiza-tional and employee-related issues need to beidentified.Although the literature stresses the importance

of OLC, there is no general agreement on howmanagers can enhance it. This paper suggests fivedimensions or areas that should be taken intoaccount by managers to improve their learningcapability and therefore become a learningorganization.Research that determines the dimensions of

OLC and analyses the relationship between OLCand job satisfaction is likely to prove particularlyvaluable at a practical level. Managers canintroduce the organizational and managerialcharacteristics that will enhance OLC in theknowledge that these will have implications forjob satisfaction. The latter might well increase jobperformance (Babin and Boles, 1996) or organi-zational performance (Hwang and Chi, 2005).Specific methodological limitations must be

recognized in the present study. First, weadministered the questionnaire to workers only,as an employee-based survey, in order to obtain ahomogeneous set of respondents. This mayconstitute a limitation, as we do not take intoaccount other stakeholders. Second, the ques-tionnaires were completed by the internal stafffrom a single industry to control for potentialindustry effects across organizations. However,this may limit external validity. To assess thegeneralizability of our findings, future researchshould test our hypotheses in other industries andwith several stakeholders. Third, the sample sizelimits our conclusions to Spanish ceramic tilecompanies. Even though the eight companieswere selected as representative of the Spanishceramic tile industry, the number of respondentsclearly limits our conclusions from being

336 R. Chiva and J. Alegre

r 2008 British Academy of Management.

extended beyond this sector. Fourth, the mea-surement of the variables might also representcertain limitations. The OLC measurement scaleshould be further validated in other companies,industries and sectors. Although the use of asingle item to measure overall job satisfactionappears to have been validated by previousresearch and its choice seems to be appropriate,job satisfaction is a multidimensional concept,the measurement of which should take intoaccount not only job beliefs about different facetsof the job but also emotional feelings about it(Weiss, 2002).Finally, we put forward some suggestions for

future lines of research that would complementthis study and go beyond some of its limitations.To better understand the relationship betweenOLC and organizational outcomes, new studiesshould take into account other constructs such asorganizational commitment, emotional intelli-gence, employee turnover and business perfor-mance. Additionally, this research should beundertaken in several contexts and with a varietyof respondents.The literature on learning organizations and

organizational learning has suggested possiblepositive outcomes; however, future work couldlink organizational practices in human resourcemanagement or innovation management withOLC. This research would provide a holisticand contingent view of OLC and the learningorganization.

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Ricardo Chiva is an Associate Professor at Universitat Jaume I (Castellon, Spain) where he teachessubjects related to human resource management. He holds a PhD in management from theUniversitat Jaume I and an International MBA from the European School of Management (ESCP-EAP). His areas of interest are organizational learning, design and innovation management,complexity theory and human resource management.

Joaquın Alegre is an Associate Professor at Universitat de Valencia (Spain) where he teachessubjects related to strategy and innovation management. He holds a PhD in management fromUniversitat Jaume I. In 2002, he was a visiting researcher at INSEAD (Fontainebleau, France). Hisresearch interest focuses on knowledge management and technological innovation from a strategicperspective. Dr Alegre has also collaborated in several research projects dealing with competitive-ness in local firms and with ceramic tile producers.

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