Intellectual Capital and Innovation Capability

Organizational knowledge assetsand innovation capability

Evidence from Spanish manufacturing firms

Miriam Delgado-Verde, Gregorio Martn-de Castro andJose Emilio Navas-Lopez

Departamento de Organizacion de Empresas,Facultad de Ciencias Economicas y Empresariales,

Universidad Complutense de Madrid, Madrid, Spain

Abstract

Purpose Organizational knowledge assets are key organizational factors responsible for firminnovation, as well as effective management. Traditionally, a good piece of research takes theinnovation processes from an external perspective, leaving aside the internal complexity thatcharacterizes innovation dynamics. Nevertheless, the innovation capability of a certain firm dependsvery closely on the intellectual assets and organizational knowledge that it possesses, as well as on itsability to deploy them. In this sense, this paper aims to test empirically the relationships betweenorganizational knowledge assets and the innovation capability of the firm.

Design/methodology/approach The data collection was carried out through a questionnaire on asample of 251 Spanish high and medium-high manufacturing firms. Exploratory and confirmatoryfactor analyses and multiple linear regressions were also used.

Findings Based on the literature review, this work explores the nature and measurement oforganizational capital as well as its role on innovation performance in high and medium-highmanufacturing firms.

Practical implications This paper proposes a theoretical and empirical model of technologicalinnovation that, based on organizational knowledge assets, highlights the importance of culture andCEO commitment towards innovation, as well as the role played by communication and informationtechnologies (CITs) applied to management on product innovation capability within high andmedium-high manufacturing firms.

Originality/value The scarcity of empirical works analyzing the innovation phenomena from aninternal point of view adds value to the current academic literature, specifically from an intellectualcapital-based view.

Keywords Organizations, Knowledge management, Assets, Intellectual capital, Product innovation

Paper type Research paper

1. IntroductionDuring the last years, research about the role of knowledge in firm activities and valuecreation has been one of the most fruitful topics within the business management field.The knowledge-based view has highlighted the relevance of knowledge as a keyorganizational factor (Zack, 1999; Darroch, 2005), considering it as one of the maindeterminants for the existence of the firm.

Nevertheless, previous approaches such as the resource-based view (Wernerfelt,1984; Barney, 1991, 2001; Peteraf, 1993) or parallel research streams as the dynamiccapabilities approach (Teece et al., 1997) have also emphasized the role that intangible

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Knowledgeassets andinnovation

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Journal of Intellectual CapitalVol. 12 No. 1, 2011

pp. 5-19q Emerald Group Publishing Limited

1469-1930DOI 10.1108/14691931111097890

resources and organizational capabilities, which are based on knowledge, play inbuilding robust competitive advantages.

As Galende and De la Fuente (2003) point out, a good piece of research takes theinnovation processes from an external perspective, leaving aside the internalcomplexity that characterizes innovation dynamics (Du Plessis, 2007). Besides, it canbe said that the innovative capability of the firm depends very closely on theintellectual assets and knowledge that it possesses, as well as on its ability to deploythem (Alegre and Lapiedra, 2005; Chang and Lee, 2008; Subramaniam and Youndt,2005).

Nevertheless, these approaches pose certain problems (Priem and Butler, 2001) likethe lack of a clear definition for the notion of competitive advantage, or the challengesand difficulties for the identification and measurement of resources and capabilitiesthat become critical for that competitive advantage. This kind of problems hindersempirical testing, making difficult to advance towards a consolidated theory. In thissense, and following the recommendations outlined by Reed et al. (2006), a feasible andpragmatic solution is to use the so-called intellectual capital-based view.

This theoretical-pragmatic approach is a narrowly focused or specialization of theresource-based view around those resources or factors with intangible nature that maybecome the main responsible for firm success. Starting from practitionerscontributions in the 1990s (Brooking, 1996; Edvinsson and Malone, 1997; CIC, 2003)distinguishes different blocks of intellectual capital or types of organizationalknowledge stocks. There is some general agreement when depicting the followingmain kinds of intellectual capital:

. human capital, or the knowledge, abilities, experiences and attitudes possessedby the organizational members (CIC, 2003; Subramaniam and Youndt, 2005);

. structural capital, which includes those pieces of knowledge that providecoherence and guidance for the whole organization (Edvinsson and Malone,1997); and

. relational capital, emphasizing relationship processes that the firm maintainswith the external agents that surround it (CIC, 2003; Reed et al., 2006).

This work tries to bring some more light on the relations between organizationalknowledge stocks and the processes of firm innovation. To carry out this task, in a firstsection a review of some of the main works that have tried to link intellectual capital orknowledge and technological innovation is carried out, taking into account that in thisresearch technological innovation is understood as the successful development of newproducts. Later on, based on the literature review, the research hypotheses arediscussed, addressing their empirical test in the results section. Conclusions,limitations and future research suggestions complete the structure of the paper.

2. Organizational knowledge assets and intellectual and organizationalcapitals of the firmSeveral definitions of intellectual capital can be found in the literature, but while tosome extent there is certain convergence among these definitions, we can also findsubstantial differences (Hayton, 2005). In general, intellectual capital is a broad-basedterm considered synonymous with firm knowledge assets (Tseng and Goo, 2005).Nevertheless, taking into account that intangible resources and firm capabilities have a

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common essence because they are based on knowledge, or they are simply a form ofknowledge, intellectual capital constitutes a representation of the endowment, domainor stocks of firm knowledge.

Therefore, if according to the resource-based view these are the ultimate responsiblefor the competitive advantage of the firm, analyzing knowledge stocks or intellectualcapital should allow us to determine the possibilities of the organization to generate asustainable competitive advantage.

Both academics and practitioners have embraced the intellectual capital perspectiveas a useful framework for describing knowledge stocks, and its relation with valuecreation. The intellectual capital perspective focuses on how to obtain the maximumvalue from intangible assets endowment, so this perspective provides an interestingbridge between resources and corporate value (Tseng and Goo, 2005), which makesoperative the resource-based view for the case of intangible assets.

To be able to better cope with the challenge of measuring and valuing intellectualcapital, the most comprehensive approaches are models based on a structureddifferentiation (Leitner, 2005). Although several taxonomies of intangibles have beensuggested over the past decade, considering the internationally proposed metrics forintellectual capital, we have found some consensus in the use of intangible assetsclassifications based on the social character of knowledge (Brown and Duguid, 1991).This way, intellectual capital is usually classified in three basic components (Hermansand Kauranen, 2005): human capital, organizational or structural capital, and relationalcapital, which represent the most commonly, accepted categories of intangibles (Pikeet al., 2005).

The knowledge tied to the people within the firm is critical for business activities. Infact, people are hired and fired according to the assessment of their knowledge and itsusefulness for the firm tasks. The main characteristic of human capital is theimpossibility of separating this kind of intangible assets from the people that developthem. When speaking about human capital we are considering an individual capitalthat comes to the firm and remains at it by means of employment contracts, which linkthe employees with the organization.

The second block of intangible elements presented in the general classification ofintellectual capital is named organizational capital. Most organizations form aconglomerate of different communities of practice or overlapped and interdependentwork groups (Brown and Duguid, 1991). The relationships among these groups thatintegrate the organization make possible the development, starting from independentand partial contributions, of a series of knowledge based assets or intangible elementsthat present an outstanding systemic, integrative, synthetic and synergistic character.This way, structural capital knits jointly the technical dexterity of the organizationalmembers (Edvinsson and Malone, 1997), and it includes all the intangible assets thatshape the real firm structure, culture, as well as its internal organizing principles. Thiskind of intellectual capital fosters the knowledge flow, and it brings a relevantimprovement in organizational effectiveness through coordination, because itintegrates, in an appropriate way, the different functions of the firm.

Lastly, relational capital gathers those intangible assets that the firm obtains whenit maintains successful relationships with agents of its environment as clients,suppliers or allies.


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It is widely recognized, in particular from the Resource-based view, that intellectualcapital affects organizational performance and competitive advantage (Wu et al., 2006).Nonetheless, whereas in management literature, firm value is often explained byintellectual capital, empirical contributions on these matters are scarce (Hermans andKauranen, 2005). Thus, an improved understanding of how intellectual capitalprovides sustained competitive advantage is required, deepen into the black boxbetween intellectual capital, and especially organizational capital, and corporate value(Tseng and Goo, 2005).

Specifically, within organizational capital, this research will be focused in thoseintangible factors that could play an important role in achieving innovations. In thissense, we pay attention to culture and CEO commitment towards innovation as well asCITs applied to management.

3. Innovation capabilityAlthough the value of tangible assets is generally recognized, managers need to knowhow their investments in intangible assets are associated to firm returns (Wu et al.,2006). The challenge for the users of intellectual capital, whatever it will be managersor investors, is to make this kind of assets meaningful, connecting them to corporategoals in order to understand their impacts on financial returns (Leitner, 2005). Here iswhere our model tries to provide the missing link between intellectual capital and valuecreation, taking into account firm innovation.

This way, the second part of the model is referred to innovation, which has been afrequently addressed topic for specialized scientific literature, due to its relevance forfirm survival and success. However, the analysis and understanding of thisphenomenon continues raising debates (Subramaniam and Youndt, 2005). Accordingto these authors, innovation can be defined as the identification and seizure ofopportunities to create new products, services or processes.

Although the literature (Tushman and Nadler, 1986; Van de Ven, 1986; Hill andRothaermel, 2003; Stieglitz and Heine, 2007, among others) recognizes a wide range ofinnovation types within the firm (product/process, radical/incremental,technological/managerial, market pull/technology push, or competence-enhancing/competence-destroying), most of the empirical works use the product-process typologyof innovation. This research will also employ this kind of typology that classifiesinnovation types according to the results or outputs of the innovation process, focusingspecifically on product innovation, since is one of the most promising areas in the fieldof knowledge management (Corso et al., 2001). This way, according to Nieto (2001),when new technological knowledge is materialized in the development of new productsor in the improvement of those already existent we are talking about a productinnovation.

4. HypothesesThe role that organizational knowledge stocks play on the firm capabilities to innovatethrough its products constitutes the main argument of this paper. In this sense, oncethe theoretical background has been presented, it is necessary to move towards aspecific model. This model is shaped by three basic hypotheses to be tested that will becommented along this section. Later on, the variables and measurement tools employedare included, as well as the research resume of the empirical research.

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As has been pointed out previously, from a theoretical point of view there is a veryclose relation between knowledge stocks and flows, and the innovation process (Nonakaand Takeuchi, 1995; Daz et al., 2006). Nevertheless, from an empirical point of view, andexcepting pieces of research like that of Subramaniam and Youndt (2005), Darroch (2005)or Smith and Sharif (2007), the works that have addressed this topic from theknowledge-based view and the intellectual capital-based view are quite scarce.

Having a brilliant, motivated and experienced human capital should be the base ofall innovation process in the company. Thus, this kind of intellectual capital providesthe main source for developing new ideas and knowledge (Snell and Dean, 1992).Highly motivated and trained employees workers may question the alreadyestablished organizational routines, so this kind of human capital become critical topush the firm into its technological limits, constituting the best incentive towardsobtaining new knowledge and innovations (Nonaka and Takeuchi, 1995; Hill andRothaermel, 2003).

Beyond human capital, or individual knowledge, an important part of theknowledge, abilities, experiences and behaviors required for the successfuldevelopment of new products and services lie inside the own organization. As Vande Ven (1986) points out, the innovation process in general terms is a collectiveachievement of the organizational members, where organizational support becomes akey element. Institutionalization acts as a mean for preserving organizationalknowledge and routines, which in turn fosters the accumulation, preservation andimprovement of collective knowledge.

Following Tseng and Goo (2005), good organizational capital or organizationalknowledge assets will translate the human dimension innovation into companyproperty (Pitt and MacVaugh, 2008). For doing so, firms must support and nurture thebrightest individuals to share their innovation, knowledge, and abilities throughorganization learning. Tacit issues like managerial commitment, a common identityand shared vision or a climate of openness and experimentation compose the learningcapability of the firm (Akgun et al., 2007). Nevertheless, although organizedinformation cannot substitute tacit knowledge, it can significantly enhance it to fillexisting knowledge gaps, so information technologies can support the transformationof information into organizational knowledge (Adamides and Karacapilidis, 2006). Inthis vein, an effective knowledge management towards product innovation needs takeinto account the elicitation and exchange of tacit knowledge as well as explicit andcodified information. Thus, operational processes, information systems, organizationculture, internal organization structure and administrative systems, will have apositive influence on the innovative capabilities of the firm. Thus, having databases,proceeding manuals, effective information systems, or cultural values devoted toinnovation promotion can constitute important sources for innovative success. Thisrelation appears in the following hypotheses:

H1. The higher organizational capital endowment in the firm, the stronger will beits product innovation capability.

H1a. Culture and CEO commitment towards innovation within the firm results inhigher product innovation capability.

H1b. The higher utilization of CITs applied to management within the firm, thehigher will be the product innovation capability.


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5. Research design5.1 Measuring variablesBearing in mind the purpose of identifying and measuring the different issues oforganizational capital, as well as capturing technological innovation, a literaturereview was carried out. As a result, a series of items were designed, and they were usedas the basis for the elaboration of a questionnaire with Likert 1-7 scale, which wereemployed for gathering primary data.

This way, organizational capital is the platform or supporting knowledge structurethat allows the coordinated execution of tasks inside the firm. From the literaturereview, and taking into account that this study is focused on technological innovation,we paid attention to two dimensions: on the one hand, culture and CEO commitmenttowards innovation (Carmeli and Tishler, 2004; Chen et al., 2004; Subramaniam andYoundt, 2005; Prajogo and Ahmed, 2006; Akgun et al., 2007; Egbetokun et al., 2009;among others), and, on the other hand, CITs applied to management (Smith et al., 1994;Chen et al., 2004; Subramaniam and Youndt, 2005; Akgun et al., 2007; among others).

Innovation outcomes were measured through three items. The first was devoted tothe number of product innovations implemented by a firm in a certain time (Tsai andGhosal, 1998; Souitaris, 2002; among others) because this was the most direct way ofknowing the success of the innovation efforts carried out by the firm. The second itemwas based on the percentage of sales with respect to new products against total sales(Chandy and Tellis, 1998; Souitaris, 2002; Chen et al., 2004; among others). The thirditem is related to the number of new products with respect to the firm product portfolio,with the aim of assessing the product innovation capability of a firm.

Finally, due to the fact that firm size and age, as well as the industry may influencefirm innovation development, size, age and industry are considered as control variables(based on Subramaniam and Youndt, 2005; Reed et al., 2006; among others). Size wasmeasured by means of employees who belong to the firm; age was measured from thefirms establishment; and regarding industry, they were taken into account, on the onehand, high technology manufacturing firms, and, on the other and, medium-hightechnology manufacturing firms.

5.2 Population, sample and information sourcesTaking into account the hypotheses arose from the literature review, they wereempirically tested in a set of firms where the intangible resources represent animportant determinant of business competitiveness. In this sense, high andmedium-high technology manufacturing firms of Spain found on the SABI databasewere chosen for the fieldwork, following the classification system provided byCNAE-93 codes[1]. This kind of firms has a strong dependence on intellectual capital,since they are based on knowledge (Johnson et al., 2002; Leitner, 2005), and they belongto a homogeneous industry to avoid different effects derived to environmentalcharacteristics (Rouse and Daellenbach, 1999; King and Zeithaml, 2003). Finally, onlythose firms with at least 50 employees were selected to assure the existence of thedifferent types of intellectual capital, due to the fact that for very small businesses thedifferent capitals may not clearly be distinguished.

With the aim of collecting data, we designed a questionnaire (seven-point Likertscale) because secondary sources do not provide enough information about thevaluable and unique competences of a firm, being probably irrelevant (Penrose, 1959).

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Therefore, starting from a literature review related to intangible factors andinnovation, we followed the next steps:

(1) Different questions were collected from several works that used questionnaire(see section 5.1).

(2) The selected questions were presented to academic experts of our topics inorder to improve them.

(3) A pre-test of 20 firms was carried out to identify mistakes, which did notappear.

(4) We contacted with top managers by telephone, because they have a widervision of their firms, to obtain data.

Thus, at June 2009, we obtained a sample of 251 firms, 43 high technologymanufacturing firms and 208 medium-high technology manufacturing firms, with aresponse rate of 17.07 percent and a sampling error of /2 5.5 percent for a 95 percentof confidence level (see Table I).

6. ResultsThe gathered information was processed through two stages. In the first one,exploratory and confirmatory factor analyses were carried out in order to determinethe basic components that can be found in the firms sample regarding organizationalcapital and product innovation capability. Next, on a second stage, a multipleregression model was designed to test the effects of the different assets oforganizational capital on the firm product innovation capabilities.

With the aim of testing the main dimensions included in organizational capital, anexploratory factor analysis was carried out, using SPSS 17.0. This technique allows usto synthesize the information contained in wide data set into a limited number ofcomponents that will represent the original variables with a minimum informationloss; finding two factors referred to the two dimensions theoretically considered andobtaining a 70.109 percent of accumulated variance (see Table II). These results wereobtained by means of varimax orthogonal rotation.

Before carrying out this exploratory factor analysis for organizational capital scale,the preliminary tests were run: determinant of the matrix, KMO test, and Bartlett test.

Research aim Intellectual capital and innovation

Criteria defining firm population High and medium-high technology manufacturing firms: Included in the SABI database Located in Spain Within 24, 29, 30, 31, 32, 33, 34, 35 CNAE-93 codes With at least 50 employees

Population 1,270 firms

Sample and response rate 251 firms (17.07 percent)

Method for gathering data Survey (questionnaire)Answered by top managers

Used statistical software SPSS 13.0 and AMOS 7.0Table I.

Research resume


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The results of these diagnostic tests can be found in Table II, and they advice to carryout the factor analysis according to Hair et al. (2004).

This way, the first component of organizational capital includes six questionnaireitems regarding culture and CEO commitment towards innovation (CCI), which werequite coherent among them; because they address the way of working andunderstanding within the organization with respect to achieve innovations, as well asits core values. In this sense, issues like the efforts of the employees and managers forsolving problems, the incentives designed for innovative employees, or the sense ofcommitment and adhesion to the core values of the firm, explain a 43.710 percent of thevariance.

The second component of organizational capital is focused around CITs applied tomanagement (CIT) of the firm; including a set of three items referred to ITcompetences, which are show through the frequent use of information technologies,and the level that the firm has reached in its use. This component represents 26.399percent of the explained variance.

Then, reliability tests for the components of the organizational capital scale areperformed through the Cronbachs alpha coefficients, showing 0.908 and 0.804 for CCIand CIT, respectively. So, they fulfill the reliability analysis of the measurement scale(Hair et al., 2004).

The next step was to carry out a confirmatory factor analysis using AMOS 7.0, andthe results suggested that the organizational capital model provided a good fit for the

Questionnaire items F1 F2

OC2: A common system of values, beliefs and objectives exists in my company,directed towards innovation 0.864

OC3: My company promotes experimentation and innovation as ways toenhance processes 0.831

OC5: In my company, managers support and lead the innovation process 0.804

OC1: My company encourages creativity, innovation and/or the development ofnew ideas 0.778

OC4: Often, managers involve employees in important decision-makingprocesses 0.730

OC6: Managers share similar beliefs about the future management of this firm 0.715

OC9: My company prefers to use CIT for communication, co-ordination andinformation diffusion 0.910

OC8: My company uses CIT, which allows it to learn from past situations, thusimproving employees learning and experience 0.857

OC7: Much of the firms knowledge of processes, systems and structures iscontained in databases, the intranet, electronic files, etc. 0.632

% of standard deviation 43.710 26.399Accumulated % 43.710 70.109

Notes: Determinant of the correlation matrix 0.003; Kaiser-Meyer-Olkin index 0.865; Bartlett test(Chi-squared, gf) 1,441.438 (36); Signification level 0.000

Table II.Exploratory factoranalysis of organizationalcapital

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data, since chi-squares/degrees of freedom ratio was less than 3 (x2=df 2:600);Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Incremental FitIndex (IFI), as well as Comparative Fit Index (CFI) were close to 0.95 (Hu and Bentler,2000), obtaining GFI 0:950; AGFI 0:906; IFI 0:973; and CFI 0:973; and RootMean Square Error of Approximation (RMSEA) was less than 0.08 (Browne andCudeck, 1993), obtaining RMSEA 0:075.

Finally, the dependent variable of the model was measured through the scaledevoted to innovation outcomes, which included three items. From another exploratoryfactor analysis we can argue the existence of a sole component which was labeled it asproduct innovation capability (PIC). The determinant of the matrix, KMO test, andBartlett test showed that the exploratory factor analysis was pertinent, and a 91.009percent of accumulated variance was obtained (see Table III). Also, it shows aCronbachs Alpha of 0.951, demonstrating the reliability of the measurement tool.

Once the different dimensions of firm organizational capital have been obtained,and trying to answer the second question that guides this research, multiple linealregressions are carried out in order to analyze the influence of organizational capital, aswell as its dimensions, on the innovative capabilities of the firm (see Table IV).

As can be seen in the regression model resume and in the variance analysis, bothDurbin-Watson coefficient and Snedecors F show values above the critical values, sowe can conclude that the proposed models are statistically significant as a whole.

In a more detailed comment, the empirical test of H1a (model 2) shows that CCI(b 0:486, p , 0:01) has a positive and significant influence on product innovationcapability, so such hypothesis is supported. In addition, this model presents anadjusted R 2 coefficient of 0.229, explaining an important portion of variance invariable PIC. In the same way, the model 3 shows that H1b is supported, since TICs(b 0:276, p , 0:01) positively and significantly influences product innovationcapability, but obtaining a lower adjusted R 2 coefficient (0.067) than the one of CCI.

With respect to organizational capital as a whole, the model 4, in which areconsidered both dimensions of organizational capital, shows that this capital has apositive and significant influence on product innovation capability as well; explaininga 30.1 percent of the dependent variable variance. Moreover, as it can be seen, thedimension CCI (b 0:486, p , 0:01) is more important than dimension TICs(b 0:275, p , 0:01).

Questionnaire items F1

PIC1: In the last three years, the number of product innovations developed by mycompany is higher than my competitors 0.958

PIC2: The percentage of sales with respect to new products, against total sales, ishigher than my competitors 0.954

PIC3: In the last three years, the number of new products with respect to my productportfolio is higher than that of my competitors 0.950

% of standard deviation 91.009

Notes: Signification level 0.000; Determinant of the correlation matrix 0.049; Kaiser-Meyer-Olkinindex 0.775; Bartlett test (Chi-squared, gf) 747.101 (3)

Table III.Exploratory factoranalysis of product

innovation capability


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Regarding control variables, they do not have significant effects on PIC, only age of thefirm within models 2 and 4.

7. ConclusionsAs Hayton (2005) points out, there has been limited research into intellectual capitaland its outcomes. The main contribution of the empirical findings of this research isprecisely providing evidence that supports that organizational capital is one of themain sources for firm innovation. Although our results corroborate those of previousworks, there are also some differentiated and valuable characteristics.

First, the theoretical framework adopted is the intellectual capital-based view (Reedet al., 2006), which until the present date has little empirical support for its mainarguments. In this sense, as the intellectual capital-based view proposes intangibleassets as the source of sustainable competitive advantage, several specific kinds ofcompetitive advantage have been considered by the previous literature, as corporatevalue (Tseng and Goo, 2005), anticipated future sales (Hermans and Kauranen, 2005),corporate entrepreneurship (Hayton, 2005), or directly firm performance (Wu et al.,2006). In our case, the competitive advantage has been considered in the shape ofinnovation outcomes. Thus, we have tried to provide additional empirical evidence intesting this research stream, moving from resource-based view of the innovationprocess (Pike et al., 2005) towards an intellectual capital-based view of innovation.

Second, exploratory and confirmatory factor analyses show the existence ofdifferent dimensions of organizational knowledge assets or organizational capital. Thisissue has received some attention from scholars; however, this research is focused onthose intangible factors, within organizational capital, that could be considered of themost relevance in order to achieve innovations, considering them within high andmedium-high manufacturing industries.

Product innovation capabilityModel 1 Model 2 Model 3 Model 4

Variables (Control variables) (H1a) (H1b) (H1)

CCI 0.486 * * 0.486 * *

(8.708) (9.139)CITs 0.276 * * 0.275 * *

(4.448) (5.131)SizeLog 20.017 20.060 20.019 20.062

(20.268) (21.070) (20.314) (21.164)Age 0.065 0.094 * 0.065 0.093 *

(1.027) (1.682) (1.054) (1.754)Industry 0.059 0.063 0.013 0.017

(0.931) (1.134) (0.216) (0.325)

Model resumeAdjusted R 2 20.004 0.229 0.067 0.301T. mistake 1.0022 0.87797 0.96610 0.835599Durbin-Watson 2.075 2.019 2.074 2.013F 20.639 19.581 * * 5.463 * * 22.542 * *

Note: Significance level *p , 0:10 (t); * *p , 0:01

Table IV.Results of regressionanalyses on productinnovation capability

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Third, the regression analysis provides support for the main thesis of this researchfor the selected sample. Thus, as expected, findings show a statistically positive andsignificant influence of organizational capital assets on product innovation capability.

In this sense, taking into account the routines and processes of the teams belongingto a firm, and according to Leiponen (2006), team knowledge is an important source ofcompetitive advantage because individual competences, which are probablycomplementary, allow increasing their value, the achievement of new knowledgedue to their combination. In this way, and following arguments of Akgun et al. (2007),knowledge transfer among employees, considering communication, interactions,conversations or discussions, lead to attain product innovations. So, in order topromote those actions, which are related to CIT because nowadays employees areusually linked by these technologies, it is important the existence of innovative culturewithin the firm (Prajogo and Ahmed, 2006).

However, contrary to Prajogo and Ahmed (2006), who did not find that incentivestowards innovation results had a direct effect with product innovation, our findingsshow the importance of culture and CEO commitment towards innovation (CCI) inorder to attain product innovations. Therefore, according to Damanpour (1991), whopaid attention to the managerial attitude toward change, it seems necessary the firmencourages human resources with a proactive attitude to reach this innovation aim.

Specifically, managers play an important role in adopting technological innovations,since they depend on support, leadership and coordination provided by those managers,being drivers of innovative culture. Thus, in the same way as our results, Llorens et al.(2005), Elenkov and Manev (2005) and Akgun et al. (2007), paying attention to these kindof attitudes, found a positive relationship with innovation results.

Moreover, and according to Akgun et al. (2007) and Hegde and Shapira (2007),shared vision, values or beliefs among employees mean the updating of individualknowledge, due to the existence of a new ideas and viewpoints acceptanceenvironment, achieving better product innovation results.

Regarding control variables, only the age of the firm takes importance whendimension CCI is studied, result that seems to be quite consistent with the nature ofculture and managerial procedures, because it is necessary a long enough period overwhich to fully develop.

Finally, it seems interesting that managers pay attention to possible sourcesthrough which can attain product innovations. In this sense, as managerialimplications, this study provides a measurement scale, focusing on the existingneeds (Kaplan and Norton, 2004), in order to make the assessment of organizationalknowledge assets easier. Furthermore, some guidelines are offered about issues relatedto organizational capital, which should be taken into account in order to carry outproduct innovations within high and medium-high technology manufacturing firms.

In spite of the contributions of this paper, it is necessary to point out its main limitation,which advice taking our findings with care, and consider them as tracks, directions orpartial evidence for the hypotheses tested. We must also take into account that theconducted empirical research has a cross-sectional nature and it has been designedspecially for a certain industry. This implies that our findings may not be generalized inindustrial or geographically without some caution. It makes sense to think that other kindof industries or different countries could show other critical elements of organizational orintellectual capitals as main determinants of the firm innovation activities.


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8. Future research directionsFurther research is needed in order to analyze other components of organizationalcapital, and in a wider framework, intellectual capital, in other industrial settings, andalso for determining their influence on product or service innovation. Besides,longitudinal studies about this topic would provide a better understanding of howorganizational learning takes place, and how it is related to the innovation process.This systematic evidence may be very useful for both academics and practitionersinterested in using an intellectual capital-based view of innovation. This way, there isa long way to be walk, because as Park and Kim (2006) suggest, firm knowledge assetsand innovation must be combined into new terms, demonstrating empirically thatmanaging knowledge, organizational capital, and intellectual capital is crucial forsucceeding in the implementation of innovation based strategies (Liu et al., 2005).

Note

1. CNAE-93 is a classification of Economic Activities elaborated according to the conditionscovered in the implementation regulation of the NACE Rev.1.1. Its objective is to establish ahierarchical set of economic activities, allowing identifying and classifying differentcompanies according their executed economic activities.

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About the authorsMiriam Delgado-Verde is Assistant Professor in the Business Administration Department atUniversidad Complutense de Madrid (Spain). She was Research Fellow at the ManchesterInstitute of Innovation Research-The University of Manchester during 2008-2009. She is authorand co-author of several papers and books concerning resource-based view, intellectual capitaland knowledge management. Miriam Delgado-Verde is the corresponding author and can becontacted at: [email protected]

Gregorio Martn-de Castro is Associate Professor in the Business Administration Departmentat Universidad Complutense de Madrid (Spain). He has several years of research experience atCIC Spanish Knowledge Society Research Centre, he holds an Expert Diploma in IntellectualCapital and Knowledge Management by INSEAD (France), and he was Post-Doctoral ResearchFellow at Harvard University during 2004-2005 and the University of Manchester (MI for IR)during 2009. He is author and co-author of several papers concerning resource-based view,intellectual capital and knowledge management.

Jose Emilio Navas-Lopez is Professor and Head of the Business Administration Departmentat Universidad Complutense de Madrid (Spain). He is author and co-author of several books andpapers concerning technology management, strategy and knowledge management. He has heldthe first Knowledge Management Chair in Spain at IU Eroforum Escorial.


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Intellectual Capital and Innovation Capability

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