Intellectual Capital: More Than the


Interaction of Competence x Commitment



Abstract:



Ulrich (1998) has suggested that intellectual capital is a product of competence and


commitment. This broad proposition, though intuitively appealing, does not identify


theoretical links between these variables, and has little empirical foundation. This


paper draws on organisational behaviour theory to propose a model that specifies


mechanisms, intermediate linkages and boundary conditions that predict intellectual


capital. In doing so, we respond to a recent call for research that is specific about


human resource management–firm effectiveness relationships. Moderated


relationships between competence, commitment and control are proposed as


predictors of intellectual capital. Implications for future theory and practice are


highlighted.



Keywords:



INTELLECTUAL CAPITAL; COMPETENCE; COMMITMENT; CONTROL.



1. Introduction


The advance  resource-based view of the firm suggests that intellectual capital and the


potential to transform it into skilled action provides firms with competitive


advantage (Drucker 1999; Prahalad & Hamel 1998). Ulrich (1998) has proposed an


innovative formula based on Human Resource Management (HRM) principles:


intellectual capital = competence x commitment. Ulrich however, does not offer


theoretical or empirical causal links between the variables in the formula (Burr &


Girardi 2001), nor does he include situational influences that may have an impact


on intellectual capital.


Ferris, Hochwarter, Buckley, Harrell-Cook & Frink (1999) suggest that our


discipline has numerous under-developed or specified constructs, leading to the


criticism that the ‘black-box’ phenomenon prevails in our understanding of HRM


effectiveness. Ferris et al. (1999) suggest some new directions for HRM research,


which could heighten the impact of Ulrich’s formula in terms of both HRM


research and practice. First, they recommend that HRM research should be specific


about what HRM effectiveness criterion is being measured. There is very little in


the literature at present that clearly evaluates the impact of HR practices on the


firm’s holdings of intellectual capital. There is a need therefore for research that


specifically links HR practices from an organisational behaviour perspective with


the value of a firm’s intellectual capital. Ulrich’s formula provides a useful


conceptual basis for measuring intellectual capital as the outcome of effective HR


practices. It also avoids the use of accounting principles, which are currently used


to calculate intellectual capital (Flamholz 1999), but omit individual and


psychological factors.


Second, Ferris and his colleagues highlight the need for research that unpacks


the ‘black-box’ by specifying psychological mechanisms: the intermediate linkages


among these mechanisms and the boundary conditions that underpin HRM—firm


outcome linkages. Ulrich’s formula (1998) does indeed draw on psychologically


based, cognitive explanations for predicting a company’s intellectual capital.


However, it is not specific about the psychological mechanisms associated with


competence and commitment (both of which are multi-faceted), and their impact on


intellectual capital. Nor does it take into account boundary conditions that can


activate, appreciate or depreciate stocks of intellectual capital as a result of high


competence and commitment. In this paper, we extend Ulrich’s model based on


organisational behaviour research and theory to suggest that intellectual capital is


determined by factors in addition to specific facets of competence and commitment


and discuss implications for future research and practice.



2. Intellectual Capital Defined


Current definitions of intellectual capital are ambiguous. At present it is no one


particular entity, but a rather broad and vague concept that needs to be supported


by and composed of a variety of interrelated elements (Bukh, Larsen & Mouritsen


2001). A widely used definition describes intellectual capital as the knowledge,


information, intellectual property and experience that can be put to use to create


wealth (Stewart 1997). It is the future earning potential from a combination of


human capital (brains, skills, insights), and the potential of an organisation’s people


(Edvinsson 2000). Intellectual capital, which is a sub-set of an organisation’s


market capital, is generally categorised into two elements (see figure 1): human


capital and structural capital (Edvinsson 1997; Stewart 1997; Sveiby 1997). Human


capital has been described as being made up of four facets: ability, behaviour,


effort and time (Davenport 1999), all of which are owned and controlled by


workers. It is at the worker’s discretion to use personal initiative at work (Frese,


Kring, Soose & Zempel 1996) and decide when, what, where and how they will


use the skills they possess to add value to the firm’s operations. Structural capital


on the other hand has been described as ‘the backbone of the organisation’, and


includes not only intellectual property but also infrastructure consisting of an


organisation’s strategies, processes and policies (Dzinkowski 2000).


Ulrich’s definition of intellectual capital focuses solely on human capital and


does not take into account any of its structural dimensions. Edvinsson, Kitts and


Beding (2000) specifically state that intellectual capital is about a fit between


essential state variables (market and customer value) and free parameters (e.g.


competence and commitment in Ulrich’s formula and organisational processes,


systems and structures), which are adjustable variables that can be changed through


managerial intervention. Like Ulrich, Edvinsson, Kitts and Beding (2000) believe


that the systematic transformation of human capital into value requires structural


capital as a multiplier, to realize sustainable earnings potential for the organisation.


Converting knowledge into something that has value creates intellectual


capital (Drucker 1999; Dzinkowski 2000). This implies that knowledge is only


useful for what it does, how it is used and acted upon. In order to sustain the value


of knowledge as an internal good, it has to be put to use or activated through


opportunities provided by the work system and the individual’s willingness to


apply their abilities and skills (Roselander 2000). Therefore, value creation results


from the interaction of the human and structural components of intellectual capital.


The conclusions to be drawn from the definition of intellectual capital is that


it is a product of:


• Capacity which is the knowledge, skills, abilities, information and experience


of people;


• Willingness of people to apply capacity; and


• Opportunity provided by the work system to activate stocks of intellectual


capital.


Capacity reflects the competence component of the Ulrich (1998) formula, and


willingness mirrors commitment. The opportunity element however, is missing in


Ulrich’s conception of intellectual capital. Our aim is to extend the Ulrich model to


include this missing element. Our discussion proceeds in three steps. The first step


specifies psychological mechanisms and their intermediate linkages which


underpin the components of human capital covered in Ulrich’s model. The second


step identifies boundary conditions (or structural capital) in the form of job control


as an additional element in the model. The third step draws together a model that


presents intellectual capital as the outcome of the interaction of competence and


commitment with job control.



Figure 1


Components of Market Capital



Intellectual Property Intangible Assets


Innovation Capital Process Capital


Customer Capital Organisation Capital


Human Capital Structural Capital


Financial Capital Intellectual Capital


Market Capital



3. Unpacking Ulrich’s Formula


Competence is a multi-dimensional construct. The rationalist approach couches


competence in terms of the personal attributes of workers such as education level,


which is often used as an objective measure of intellectual capital (Dzinkowski


2000). This approach is fairly narrow. A broader and more common definition of


competence in organisational settings is that it includes an individual’s


demonstrated knowledge, skills and abilities (Ulrich, Brockbank, Yeung & Lake


1995).


Sandberg (2000) expressed concerns that the rationalist approach defines


competence in indirect terms, as these descriptions do not indicate whether the


worker uses these attributes. Sandberg advocates the use of an interpretative


approach to discover the workers’ definition and understanding of their jobs. In


Sandberg’s view, this interpretation determines the workers’ definition of job


competence and therefore the range of skills they utilise at work.


Bandura (1986) also suggested that knowledge and skills possessed are not


enough. One must also consider a worker’s efficacy beliefs about being able to


mobilise these skills for successful performance. Self-efficacy is described as the


‘beliefs in one’s capabilities to mobilise the motivation, cognitive resources and


courses of action to meet given situational demands’ (Bandura & Wood 1989,


p. 408). Efficacy beliefs are strongly linked to learning and organisational


performance (Stajkovic & Luthans 1998), through their motivational properties.


The conception of competence therefore needs to extend beyond capacity


defined as knowledge, skills and abilities (KSAs) to include more dynamic


elements such as skill utilisation and efficacy beliefs, which convert KSAs into true


intellectual capital. This leads to our first proposition:


Proposition 1: In valuing intellectual capital, competence needs to be measured as


a function of rationalist measures of capacity (KSAs),


interpretative measures (skill utilisation, determined by the


worker’s understanding of job requirements) and cognitions of


capability (efficacy beliefs).


Commitment is also a multi-faceted construct. It has been defined as a job attitude


or belief that reflects ‘the relative strength of an individual’s identification and


involvement in a particular organisation’ (Steers 1977, p. 46). A frequently used


operationalisation of organisational commitment is the three-factor model


developed by Meyer and Allen (1992). The factors are continuance commitment,


normative commitment, and affective commitment. Ulrich not only fails to


discriminate between these facets of commitment but also does not take into


consideration the differential impact of the three facets on intellectual capital as


discussed below.


Affective commitment is the most studied dimension (Dunham, Grube &


Castaneda 1994). Affective commitment is often described as loyalty to the


organisation, demonstrated by emotional attachment and identification with


organisational goals (Meyer & Allen 1984). This type of commitment therefore


reflects the willingness of people to provide discretionary effort. Continuance


commitment is attachment to the organisation induced by recognition of the costs


of leaving the firm. Continuance commitment is therefore essential for retention of


intellectual capital. The final component of organisational commitment is


normative commitment, which reflects the employees’ feelings of obligation to


remain with the organisation. These obligations are compiled through identification


with the organisation’s values and culture. This facet of commitment ties in with


elements of structural capital, which are the organisation-based sources of


intellectual capital such as organisational processes, systems, culture, values and


management philosophy (Dzinkowski 2000). This leads to our second proposition:


Proposition 2: Affective, continuance and normative commitment should all be


included when valuing intellectual capital.


Ulrich (1998) suggested that commitment is gained by engaging employees’


emotional energy, avoiding burnout and stress through high involvement work


practices based on high levels of employee autonomy, and self-regulation (job


control). Ulrich therefore acknowledges that structural variables have an impact on


commitment, but does not include them in his model. Similarly, there is a growing


body of research that highlights that competence can be influenced by structural


factors, specifically job control (Burr & Cordery 2001; Parker & Wall 1998). The


next part of the discussion therefore examines job control as a major boundary


condition that influences both the capacity and willingness elements of the Ulrich


formula.



4. Job Control as a Boundary Condition


Empirical and theoretical research supports the proposition that job design (a


structural capital variable) and in particular job control or work autonomy


(Hackman & Oldham 1976), has the potential to activate value-creating intellectual


capital mechanisms. Within the dominant job design paradigms, job control is


viewed as allowing individuals to act directly on the environment so as to produce


desired outcomes or avoid negative ones (behavioural control) and/or allowing a


choice among several possible actions, outcomes, or tasks (cognitive control)


(Wall, Corbett, Martin, Clegg & Jackson 1990).


A series of job redesign studies within advanced manufacturing systems by


Wall and colleagues (Jackson & Wall 1991; Wall et al. 1990; Wall, Jackson &


Davids 1992), has provided evidence that significant performance improvements


within high control job designs arose not due to employees working harder, but


rather as a result of the development of new knowledge, which enabled the


prevention of errors. These findings closely approximate the propositions of the


demand-control model of job design that mastery outcomes are engendered by


active, high control jobs (Karasek & Theorell 1990). Evidence substantiating this


‘active learning’ finding is emerging in other work environments. For example, job


control has been found to influence skill utilisation (Girardi 1999), job related


efficacy beliefs (Burr & Cordery 2001; Parker 1998; Speier & Frese 1997), and job


crafting (Wrzesniewski & Dutton 2001) in work settings as diverse as process


control, the knowledge work environment and in the service industry.


High Performance Work Systems (HPWS) (Huselid 1995; Lawler, Mohrman


& Ledford 1995), predicated on high control-based job design, have also been


shown to contribute to the development of intellectual capital. Emerging evidence


shows that HPWS are instrumental in creating committed, long-term employee


relationships, which have an impact on firm performance (see Lawler et al. 1995;


Pfeffer 1998). Broad justifications for these outcomes are based on principles of


worker empowerment ( Spreitzer 1995; Thomas & Velthouse 1990).


However, HPWS have been demonstrated to be effective only when three


pre-conditions exist (Macduffie 1995). First, employees must be competent and


possess knowledge and skills valued by the firm. Second, employees must be


willing and motivated to apply these skills through voluntary effort. Third,


employees must have the opportunity to contribute to the firm’s business or


production strategy through discretionary effort. It is evident therefore that an


interaction of individual competence, willingness (commitment) and opportunity


(via job control) is needed if positive outcomes are to be recognised from systems


that were designed to enhance intellectual capital (Huselid 1995). This leads to our


third proposition:


Proposition 3: Job control will moderate the impact of competence and


commitment on intellectual capital.



5. The Extended Model


The discussion so far has highlighted two issues. First, there is a need to


decompose the broad elements of Ulrich’s existing formula for valuing intellectual


capital to include specific psychological mechanisms. Second, the formula needs to


be expanded to include job control as a boundary condition. An expanded formula


for valuing intellectual capital is therefore proposed:


Proposition 4: Intellectual Capital = Competence x Commitment x Control


In which:


Competence = Rationalist measures of capacity (KSAs), interpretative measures


(skill utilisation) and cognitions of capability (efficacy beliefs);


Commitment = Affective, continuance and normative commitment; and


Control = Work autonomy.


There are a number of organisational behaviour models that support this three-way


interaction. For example, Amabile’s (1988) multiplicative componential model of


creativity and innovation in organisations includes organisational components


similar to control (resources, motivation to innovate, management practices) and


individual components similar to competence and commitment (skills in creative


thinking and the task domain, motivation). Another example is Wrzesniewski and


Dutton’s (2001) job crafting model that proposes that interactive relationships


between ability, motivation and opportunities provided by job control determines


job crafting or role redefinition in response to dynamic job requirements. Similarly,


Blumberg and Pringle (1982) proposed a simple model in which job performance is


the outcome of the moderated relationships between the willingness and capacity of


individuals and the opportunity provided by the organisation to perform.



6. Implications for Future Research and Practice


The debate about valuing intellectual capital has been dominated by practitioners to


date (Bukh et al. 2001; Larsen, Bukh & Mouritsen 1999). It is fitting therefore to


draw out the practical implications of the proposed model first and then the agenda


for future research.


The accounting profession has long been interested in assigning monetary


value for intellectual capital, in spite of its intangible nature. However, it is


recognised that existing assessments such as the difference between the firm’s


market and financial or book value, the Tobin’s q ratio, and the calculated


intangible value (CIV) measure are not useful indicators of intellectual capital


(Dzinkowski 2000; Larsen et al. 1999). It has been suggested as a result, that


intellectual capital has to be defined on its own terms (Larsen et al., 1999). In this


paper we have proposed an organisational behaviour theory-based formula to do


this.


While it may be difficult to assign financial value to intellectual capital using


the proposed formula, we believe that it adds structure to efforts towards the


development of intellectual capital statements (Bukh et al. 2001; Larsen et al.


1999) elsewhere. Such statements describe activities that management might apply


in order to mobilise intellectual capital and specify how it is drawn upon to produce


organisational benefits. In keeping with the proposed formula, intellectual capital


statements make connections between intellectual resources, the motivation


directed towards use of these resources, and activities that draw upon them (Bukh


et al. 2001).


HPWS are one set of management activities that can enable the utilisation of


capabilities based on employee commitment and empowerment (Tomer 2001). The


message therefore for organisations interested in increasing their intellectual


capital, is that they need to pay attention to all the different facets of competence,


commitment and control and put into place complementary ‘bundles’ of HRM


practices. In doing so, the visible consequences of how these three intellectual


capital elements interact can be observed and can collectively provide a clearer


definition of intellectual capital. This responds to Ferris et al.’s (1999) suggestion


that HRM research should be specific about what HRM effectiveness is being


measured for—in this case valuing intellectual capital.


The research agenda is determined by Ferris et al.’s second suggestion, which


highlights the need for research that unpacks the ‘black-box’ by specifying


psychological mechanisms, intermediate linkages between them and boundary


conditions that underpin HRM—firm outcome linkages. This paper has sought to


address this suggestion in the development of an expanded interactive model for


valuing intellectual capital, which serves as a framework for future research.


There is a need for empirical research, to test the intermediate linkages both


between and within the elements of the expanded intellectual capital formula. It is


expected that when levels of job control are high, and competence and commitment


are high, intellectual capital will be maximised. However, how do the various


facets of control, commitment and competence influence this maximisation? In


order to answer this question, two avenues need to be explored.


The first is to deal with the validation and/or development of measures for the


constituents of competence, commitment and control. Whilst psychometrically


sound measures of job control (e.g. Jackson & Wall 1991) and commitment (Meyer


& Allen 1992) are available, measures of competence need further refinement


(Sandberg 2000).


The second is to empirically test for an interaction effect. Although


methodological limitations regarding interaction analysis exist (Jaccard, Turrisi &


Wan 1990), and must be acknowledged, the theoretical and practical importance of


moderated relationships exceed these concerns (Baron & Kenny 1986; Karasek &


Theorell 1990). Some of the main methodological obstacles are: the issue of


multicollinearity between the formula variables; the impact of measurement error


which can result in biased estimates and lead to statistical power problems thereby


undermining significance tests; and that effects sizes reported in interaction studies


in industrial and organisational psychology tend to be small (Jaccard & Wan 1996).


However recent developments in testing interaction effects with structural equation


modelling (Schumacker & Marcoulides 1998) provide avenues to overcome some


of these difficulties.


A preliminary empirical test of Ulrich’s formula (Burr & Girardi 2001) has


found support for the two-way interaction between competence and commitment in


predicting intellectual capital. The agenda for future research to test the three-way


interaction includes the development of innovative methodologies in addition to


conventional statistical methods. One suggestion is to follow the methodology


adopted by the Danish Intellectual Capital Project (Bukh et al. 2001). This project


is testing the use of a combination of quantitative and qualitative measures such as


statistical information, internal ratios, measurement of effects and improvements,


knowledge narratives, stakeholder reports and gap analysis to identify optimum


stocks of intellectual capital and its firm-specific components of intellectual capital


and management challenges. The field of accounting for intangible assets (Lev


1997), and development of measures such as the intellectual capital multiplier


(Åberg & Edvinsson 2001), also provides opportunities for cross-disciplinary


research for quantifying the human and structural components of the intellectual


capital formula. Other approaches such as Mayo’s (2001) Human Capital Monitor


and Sveiby’s (1997) Intangible Assets Monitor measure intellectual capital as a


metric that incorporates human asset value, human resource costs and revenue.


Future research will benefit from using such objective measures of intellectual


capital as the dependent variable. Empirical tests of the predictive validity of our


expanded formula against each of these measures of intellectual capital will be


challenging. However it is an area worthy of research efforts if it highlights the


contribution of organisational behaviour and HRM in the valuation of a firm’s


intellectual capital.



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