Impact of the internal business environment on knowledge management within construction...

Impact of the internal businessenvironment on knowledge

management withinconstruction organisations

Le Chen and Sherif MohamedGriffith School of Engineering, Griffith University, Gold Coast, Australia

Abstract

Purpose – Recent knowledge management (KM) literature suggests that KM activities are influencedby the elements of the internal business environment (BE) of organisations. This paper attempts toprovide some unique insights into the contextual input of the KM process through empiricallyidentifying the major factors (i.e. “forces”) within the internal BE of construction organisationsoperating in Hong Kong, and investigating their impact on the intensity of KM activities.

Design/methodology/approach – A questionnaire survey was administered to a sample ofconstruction contractors operating in Hong Kong to elicit opinions on the internal BE and intensityof KM activities as executed by targeted organisations. A total of 149 usable responses were receivedfrom 99 organisations representing about 38 percent of the research population. In parallel, to thesurvey, a total of 15 semi-structured interviews were undertaken to provide more insights intothe phenomenon under investigation.

Findings – Supported by the empirical and qualitative evidence, this study established that firstly,both organisational and technical environments have the capacity to either positively or negativelyimpact the intensity of KM activities, and both environments serve as stimuli in increasing eachother’s dynamism; secondly, certain types of KM activities are stronger “energy receivers” and easilyto be “powered up” by manipulating factors representing these two environments. Then, throughinteractions between KM activities, the intensity of the whole strategic KM cycle will be increased thushelping to strengthen organisational competitive advantage.

Originality/value – The impact of internal BE on KM activities was both empirically andqualitatively investigated, from a strategic perspective, within the construction business context.

Keywords Knowledge management, Business environment, Organizational culture, Hong Kong,Construction industry

Paper type Research paper

IntroductionFrom a strategic perspective, knowledge management (KM) activities within businessorganisations interact with each other to form a process that receives input from itscontext (i.e. business environments (BEs)), and produces valid knowledge that can bejustified by desired business performance (Diakoulakis et al., 2004; Kalling, 2003;Mouritsen, 2004). Core values of collaboration, innovation and trust; organisationalstructure, systems and process; and interactions between staff are considered asknowledge enablers, within the internal BE, which operate over various organisationallevels and facilitate KM implementations (Debowski, 2006, pp. 86-7; Pillania, 2006). Thesetheoretical arguments imply that through manipulating certain “forces” within theinternal BE, business organisations are able to “power up” the intensity of KM activities,which, in theory, will ultimately improve business performance. Despite recent efforts in

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KM withinconstruction

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Received 16 May 2006Accepted 5 March 2007

Construction InnovationVol. 8 No. 1, 2008

pp. 61-81q Emerald Group Publishing Limited

1471-4175DOI 10.1108/14714170810846521

conceptual model proposition and exploratory studies, the number of empirical studiesinto KM within construction organisations is limited (Egbu et al., 2003a). The studyreported herein, therefore, attempts to provide some unique insights into the contextualinput of the KM process within construction organisations, through empiricallyidentifying the major factors (i.e. the “forces”) within the internal BE, and investigatingtheir impact on the intensity of KM activities.

Background and motivation for the studyThe construction industry is characterised as an highly turbulent, rapidly changing,very complex, and extremely competitive environment (Price and Newson, 2003).In such a volatile BE, new issues attributed to the changes caused by technology,communication, and market advances are emerging (Chinowsky and Meredith, 2000).To illustrate, the boundaries of historically defined markets have been blurred to thepoint where any organisation can theoretically participate in a construction projectduring any phase of its life cycle and at any geographical location (Chan et al., 2001). Inthe mean time, information technology instigates an evolution from hierarchicalinformation transfer to the concept of hierarchical information access and transfer,which bring project participants together through virtual reality environment(Becerik, 2005; Waly and Thabet, 2003). The move toward more integratedprocurement systems and changes in technology increasingly demand collaborativepractice cross traditional professional boundaries (Chan et al., 2001). In sum, theindustry is witnessing the emergence of knowledge-based tasks as a central focus oforganisational operations, particularly in managing knowledge and innovation(Ankrah and Langford, 2005).

Notwithstanding the above facts, the fragmented and hierarchical nature of theindustry illustrates difficulties for it to operate in a co-ordinated and homogeneous waywhen dealing with knowledge-related issues such as research and development,training and innovation (Barthorpe et al., 2000). The functional segregation andseparated risks allocation/management frameworks discourage innovation in design,construction and even managerial methods (Kumaraswamy et al., 2004). The level ofinnovation within the construction industry compared with other industries has beenmodest at best (Barthorpe et al., 2000) due to its nature and structures, as well as thearrangements for delivering its projects (McCaffer and Edum-Fotwe, 2006). Thetraditional procurement systems place a premium on speed or on competition that islargely on the basis of price; establish rigid role responsibilities, and promoteadversarial and self-protective behaviour (Blayse and Manley, 2004). The cultureposture of construction reflects three key characteristics, i.e. the over-reliance onproduct rather than performance standardisation, a reflection of risk aversionthroughout at both company and industry level, and continuous erosion ofinnovativeness through systematic unlearning, which inadvertently militates againstthe adoption of innovation (McCaffer and Edum-Fotwe, 2006).

It can be expected that the culture and climate of the organisations operating withinthe construction industry are profoundly shaped by the long-establishedcharacteristics of the industry, whilst also being affected by the changes in thesector as well (Ankrah and Langford, 2005). It is suggested that enterprise culturesmust see capacity to change internal structures and system as critical success factorsin the effective exploitation of their knowledge resource (Sutton, 2001). It has also been

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theoretically proposed that the elements of organisational culture and climate such asstructure, strategy, policy, motivation within a project-based environment (as that ofconstruction organisations), affect the main KM factors including people, process andtechnology that carry out the KM activities and influence an organisation’s knowledgecontent (Egbu, 2004). However, to date, apart from recent exploratory studies(Egbu et al., 2003a; Fong, 2005b), understanding the impact of contextual factors onKM activities within the single firm environment of construction organisations is stilllimited, and remain empirically unidentified.

In an effort to fill the above-research gap, this paper sets to examine how theinternal BE affects KM activities within construction organisations operating inHong Kong. In doing so, the next section briefly introduces a theoretical framework,which postulates that two main elements of BE, i.e. organisational environment (OE)and technical environment (TE) interact with each other, and influence KM activities.

Theoretical frameworkThis study was built on the premise that some factors (i.e. “forces”) within the internalBE of organisations could be manipulated to better facilitate (i.e. “power up”) KMactivities (Alavi and Leidner, 2001; Egbu, 2004; Pillania, 2006), which in theory help toachieve long-term organisational objectives (Sveiby, 1997). Therefore, this study isstrategic in nature and aims to identify:

. environmental factors that have greater impact on KM activities; and

. categories of KM activities that are more sensitive to variations within theinternal BE.

In another words, the study attempts to identify the most influential BE “forces” thatinfluence KM, and the major “KM receivers” of the “energy” created throughmanipulating these “forces.” In order to achieve these research objectives, a theoreticalframework was designed to examine how the two major “forces” (represented by OEand TE) within the internal BE of construction organisations influence four differentcategories of KM activities as explained below.

Within the construction context, the KM process has been perceived as a combinationof a series of sub-processes of identifying, capturing, sharing and measuring knowledge(Palmer and Platt, 2005). More specifically, organisations first recognise and identify theknowledge to be captured; then examine the needs of, and implement tools (techniquesand technologies) for, acquiring the knowledge; the captured knowledge is subsequentlyfiltered, refined, analysed, stored and shared; once the knowledge is disseminated newknowledge would be created through a new production process and organisationalknowledge would be updated, based on which a new circle of the KM process begins(Hari et al., 2005). It is clear that KM activities interact with each other forming a strategicKM cycle, which contributes to organisational long-term objectives (Dalkir, 2005,pp. 26-46). Therefore, KM activities are classified herein into four strategic dimensions,i.e. responsiveness to knowledge (KR) within the BE; knowledge acquisition (KA);knowledge dissemination (KD) and knowledge utilisation (KU) (Abou-Zeid, 2002;McCann and Buckner, 2004; Salisbury, 2003) – which all constitute the four KMconstructs of the theoretical framework, and are defined as follows:

(1) KR. Responding to the various types of knowledge an organisation has accessto, in its external as well as internal environments (Darroch, 2003).


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(2) KA. Seeking and acquiring knowledge from the external environment andcreating new knowledge based on existing knowledge within the organisation(Darroch, 2003; Gold et al., 2001).

(3) KD. Creating and maintaining structures, systems and processes for sharingknowledge, and for retaining knowledge within the organisation (McCann andBuckner, 2004).

(4) KU. Applying newly developed knowledge (Gold et al., 2001).

Recent empirical studies (Darroch, 2003; Gold et al., 2001) provide basic measurableitems for operationally defining the above four KM constructs. These items were usedin this study, however, a limited number of these items were modified in light of thefindings of recent construction-specific studies (Egbu et al., 2003b; Kululanga et al.,2002). In order to finalise the operational definitions of the four constructs, a pilotquestionnaire survey was administered to a sample of 43 managerial and professionalstaff members from contracting organisations operating within Hong Kong. Based onits findings, items with very low-implementation levels were excluded leaving a total of41 items to operationally define the above four constructs (Chen and Mohamed, 2005;Chen et al., 2005).

Organisational environmentOE covers organisational culture (value and principles) and organisational climate(rules, policies, procedures, structure, incentive systems, etc.). Functioning in thebackground of an organisation, culture is the collection of overt and covert rules,values and principles that ensure and guide organisational behaviour (Burke andLitwin, 1992). Whereas more in the foreground, climate is a summary of perception ofhow an organisation deals with its members and environment (Ostroff and Schmitt,1993). Both concepts have been identified as major catalysts to knowledge creation andsharing (Alavi and Leidner, 2001; Gold et al., 2001).

KM is a value-driven process, which relies on shared knowledge, collaboration andtrust, and requires a long term and integrated approach to changing employeeattitudes, gain employee acceptance and sustain knowledge sharing in the work place(Debowski, 2006). Implementations of KM almost always require a cultural change, inthe mean time, trigger a change that will in turn trigger a maturing or evolutionaryprocess (Dalkir, 2005, p. 185). Therefore, organisational culture has been identified as amajor catalyst (or alternatively a major hindrance) to knowledge creation and sharing(Alavi and Leidner, 2001; Dalkir, 2005, p. 177; Pillania, 2006). Furthermore, the capacityof organisational culture in enabling changes of internal structure and system isrecognised as a critical success factor for effective exploitation of organisationalknowledge resources (Sutton, 2001).

In addition to the previously described culture challenges confronted by constructionorganisations, the special project-based structure of these organisations constitutesanother difficulty facing KM implementation. For both the organisation and individuals,project environments are constantly changing with project delivery cycles, hence thisdynamic structure limits the organisation’s capacity to facilitate knowledge flowsthrough interactions and transactions between individuals and the organisation,consequently inhibits their ability to form a “cognitive structure” favourable to learning(Blayse and Manley, 2004; Fong, 2005b). Under project time constraints, and due to the

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tacit and context-specific nature of significant portion of project-related knowledge,innovations developed within a particular project are often ineffectively “codified” evenwhen a post-project review is undertaken (Hartmann, 2006; Kamara et al., 2002), hencethese innovations and learning are easily lost to future projects.

A recent exploratory study (Egbu et al., 2003a) based on the UK construction industryrevealed that “encouraging innovation to deliver better value” “willingness to embracetechnological development” and “awareness of the importance of KM” are the three mostfrequently-cited culture promoters to KM; whilst “time pressure” “inward lookingsilo-mentality” and “reluctance to change” are the three most frequently-cited obstacles.In the meantime, recent Hong Kong-based studies found that “top management support”“employee participation” and “trust between employees/employer” are the three mostcritical factors that drive KM success (Fong, 2005b). The above discussion gives rise tothe first hypothesis:

H1. OE is positively related to the intensity of the different categories of KMactivities.

Technical environmentInformation systems are designed to support and to augment organisational KM needs(Alavi and Leidner, 2001). TE therefore refers to the technological infrastructure and itsability to respond to the increasingly dynamic work environment.

The nature of knowledge is of particular complexity within the construction industrycharacterised by temporary “virtual” organisations formed for the completion ofprojects (Al-Ghassani et al., 2002). Construction projects requires a large flow ofdocumentary information between project participants (Peansupap and Walker, 2005),and extensive human interactions between professionals from diverse disciplines (Fong,2005a). Effectively using information and web technologies in the project-deliveryprocess enables knowledge to be captured and managed to the benefit of future projects,and effective experience and knowledge sharing can lead to knowledge reutilisation,which can minimise the cost of problem solving, reduce the probability of repeatingproblems, and increase innovation ability (Tserng and Lin, 2004). Hence:

H2. TE is positively related to the intensity of the different categories of KMactivities.

It has been argued in the literature streams of IT and organisational culture (Gallivanand Srite, 2005) that organisational culture factors have impact on IT implementation,whilst adoption of IT to support knowledge sharing could also bring about a culturalchange within organisations. This argument is also supported by recentconstruction-related studies (Egbu et al., 2003b; Peansupap and Walker, 2005; Stewartet al., 2004). The contribution of IT implementation towards building a knowledgesharing and innovation encouraging culture was also reported (Egbu et al., 2003a).Furthermore, IT implementation could be improved by developing an IT strategic planwith full support of senior management; encouraging employees to embrace IT-relatedapplications; and seeking ways to adopt IT with a view to change traditional businessprocesses (Stewart et al., 2004). The foregoing gives rise to the proposition that both OEand TE do somehow affect each other, thus leading to the third hypothesis:

H3. OE and TE are positively related to each other in a recursive manner.


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As previously mentioned, an empirical study (Moffett et al., 2003) provided basicmeasurable items for operationally defining the OE and TE constructs. Whilst many ofthese items were adopted in this study, others had been either modified or dropped inview of the findings of relevant construction-related studies (Bossink, 2004; Egbu et al.,2003a, b; Kululanga et al., 2002; Stewart et al., 2002, 2004).

In summary, the theoretical framework proposes that the two BE constructs(i.e. “OE” and “TE”) are positively related to each other, and both could be used topredict the intensity of the KM process. In addition to these two constructs, four moredistinct constructs are adequately model the KM process which is, as explained earlier,perceived as a series of sub-processes of identifying, acquiring, disseminating andutilising knowledge. The graphical illustration of the theoretical framework, shown inFigure 1, contains all these six constructs (i.e. OE, TE, KR, KA, KD and KU); and thehypothetical relationships between them.

MethodologyThis study follows a deductive approach, which begins with an abstract and logicalrelationships among concepts (i.e. theoretical framework), then moves toward concreteempirical evidence (Neuman, 2003, p. 51). In order to provide an additional perspectiveon the KM process and assumed relationships between different four KM activities, aqualitative approach was also used to complement the empirical evidence.

A cross-sectional study design was used to provide a snap-shot of the BE and KMactivities within construction contracting organisations operating in Hong Kong.Data were gathered over a period of several months via a mail-questionnaire survey to

Figure 1.Theoretical framework

KR: Responsivenessto Knowledge

KA: KnowledgeAcquisition

KU: KnowledgeUtilisation

KD: KnowledgeDissemination

OE: OrganisationalEnvironment

TE: TechnicalEnvironment

: Proposed links to be empirically tested

Contextual Input Process

Internal Business Environment (BE)

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elicit opinions on the BE and intensity of KM activities as executed by targetedorganisations. In the questionnaire, five-point Likert scales were used to measure theoperationally defined items of the constructs within the proposed theoreticalframework. The detailed survey questions and measurement scales are reported withfactor analysis findings and presented below. The questionnaire was pre-tested withten local contractors. The data-collection process began after the questionnaire hadbeen finalised, based on the pre-test feedback.

The sample population comprising 260 contractors was randomly drawn from twotrade directories, i.e. the “List of Approved Contractors for Public Works” (ETWB,2005), and the “Members List” of the Hong Kong Construction Association (HKCA,2005). Large- and medium-sized organisations represented the theoretical populationbecause they provide a relatively better environment for KM compared to smallorganisations (Ng, 2003; Robinson et al., 2005). Self-administered questionnaires weremailed or delivered in person to the managerial/professional staff member(s) withintargeted organisations. A total of 149 usable responses were received from 99organisations representing about 38 percent of the research population. No more thanfive usable (containing no missing data) feedback questionnaires were chosen fromeach organisation to avoid bias in the data. The responses were considered a goodrepresentation of the opinions of the population, since the majority of the respondentswere middle-aged, educated, at peak of their career, experienced, and knowledgeableabout KM operations within their organisations. The demographical information of thesurvey respondents is summarised in Table I.

In order to provide more insights into the phenomenon under investigation, inparallel to the survey, a total of 15 semi-structured interviews were undertaken withmanagerial staff members representing 12 large- to medium-sized contractorsoperating in Hong Kong. The demographical information of the interviewees are

Demographical information of the respondents Percent

AgeMore than 40 years 78.5Educational backgroundA bachelor degree or higher 82.6PositionTop management 32.2Senior professional staff members 47.0Professional industry experienceMore than ten years 89.9Years working for the companyMore than five years 67.8Company categoriesLocal contractors 71.1Branches or subsidiary companies of overseas corporations 22.8Branches of state-owned enterprises of the People’s Republic of China 4.7Company turnoverLess than HK$100 million 23.5HK$100-500 million 22.8HK$ 501-1,000 million 12.1HK$ 1,001-5,000 million 22.1

Table I.Demographical

information of surveyrespondents


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summarised in Table II. The interviewees were asked to describe KM activities andrelated systems being implemented within their organisations, and the policies thatfacilitate KM implementation.

Quantitative data analysisFactor analysisGathered data were analysed using the Statistical Package for Social Sciences Software(SPSS Version 12.0). Six cases (containing missing values) were deleted from the datafile keeping 143 usable responses. Data screening techniques were applied to allvariables to assess their distribution to ensure that normality and linearity arereasonably upheld (Tabachinick and Fidell, 2001). Factor analysis (Varimax method)was adopted for identifying the structure among the set of measurement variables foreach construct in the theoretical framework, and also for data reduction. The 143cases exceed the minimum requirement for factor analysis (Hair et al., 1998, p. 98).Checks were undertaken to ensure factorability is upheld for all factor analysisscenarios (Coakes, 2005). Tables III and IV report the results of the factor analyses.With the sample of 143, a factor loading of 0.50 and above is considered significant atthe 0.05 level to obtain a power level of 80 percent (Hair et al., 1998, p. 112), thusvariables with a factor loading less than 0.50 were eliminated. The cumulativepercentage of total variance extracted by successive factors of the six factors analysesrange from 52.1 to 68.3 percent, and are therefore considered satisfactory solutions(Hair et al., 1998, p. 104). Also, the reliability coefficient values of all scales are abovethe low-acceptable limit of 0.70, indicating satisfactory internal consistency (Hair et al.,1998, p. 118).

Since, the constructs were conceptually defined based on a combination of the literaturereview and previous empirical studies, the scales were considered to have face validity(Hair et al., 1998, p. 117). In view of the foregoing, the developed theoretical constructs areconsidered to comprise reliable and valid items for their operationalisation.

Demographical information Number of interviewees

PositionChairman 1Managing director 1Director 6Regional branch managers 2Project managers 3Department managers 3Company categoriesGeographical location origin

Local contractors 5Branches or subsidiary companies of overseas corporations 6Branches of state-owned enterprise of the People’s Republic of China 1

Qualification for public works (ETWB, 2005)Group C contractors (contract values exceeding $50 million) 7Group B contractors (contract values of up to $50 million) 5

SpecialtyGeneral contractors 6Specialist contractors 6

Table II.Demographicalinformation ofinterviewees

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As presented in Table III, the analysis identified two factors for the OE construct:“OE1: organisational creative environment” representing innovation policies and“OE2: organisational supportive environment” representing strategic guidance to KMand communication style; and a single factor (TE) for the TE construct representingthe technological infrastructure and its ability to respond to the increasingly dynamicwork environment. The four KM constructs were also subjected to factor analysis forbetter understanding of their inherent properties. A total of nine underlying KM factorswere extracted and are presented in Table IV. The following names were assigned tothese factors to reflect their common and latent properties. These are: “KM1: responseto market knowledge” “KM2: response to clients’ needs” “KM3: business KA” “KM4:market KA” “KM5: financial KA” “KM6: training-based KA” “KM7: tacit KD”“KM8: explicit KD” and “KM9: knowledge utilisation.”

KM constructs and factors Factor loadingsa

OE (two factors)Survey question: “Please indicate your opinions about the current internal OE inyour company. In our company . . . ”OE1: organisational creative environment

O8 formal and informal innovation activities are integrated 0.782O7 innovation are rewarded 0.782O6 innovations to deliver better cost-effectiveness are encourage 0.772O9 divisions, departments, construction sites often work jointly on innovations 0.701O11 interdisciplinary team work is encouraged 0.627

OE2: organisational supportive environmentO1 we have shared vision for managing organisational knowledge 0.679O2 we have committed leadership to manage organisational knowledge 0.666O3 problems/errors are discussed openly 0.647O13 lateral communication structure between construction sites is adopted 0.765O14 teams look to see how they can contribute more to the company 0.611O12 lateral communication structure between construction sites and functional

departments is adopted 0.678TE (one factor)Survey question: “Please indicate your opinions about the current internal TE inyour company. In our company . . . ”

T3 senior management support IT development 0.787T5 IT applications are designed to share information across the whole

organisation 0.777T11 employees are trained to use IT 0.770T6 IT is adopted with a view to change traditional business processes 0.756T10 interaction is established between end-users and IT professionals 0.740T1 IT and its applications are developed with a clear vision of business needs 0.727T4 IT is designed to aid efficient decision-making 0.697T2 IT and its applications are developed based on a strategic plan 0.669T7 IT is used to minimize geographical/time barriers 0.659T8 IT is a means of enhancing collaboration 0.616

Notes: Scale: 1 – strongly disagree; 2 – disagree; 3 – neither agree nor disagree; 4 – agree; 5 –strongly agree. aExtraction method: principal component analysis. Rotation method: Varimax withKaiser normalization; factor loadings: significant at the 0.05 and of a power level of 80 percent. Totalvariance explained (percent) of the four factor analyses: OE: 55.5 percent, TE: 52.1 percent. Reliability(Cronbach’s a) of the scales of the four KM constructs: OE: 0.865, TE: 0.897

Table III.Factor analysis of OE and

TE constructs


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Survey question: “Please indicate your opinions about the intensity of KMactivities in your company. Our company. . .”KR (two factors)KM1: response to market knowledge

Periodically reviews the likely effect of technological changes on clients 0.839Effectively implements marketing plans 0.829Keeps up to date with technological developments that could affect business 0.813Endeavours to improve the cost effectiveness of marketing service 0.761Responds quickly if a major competitor offers similar service to clients at a verycompetitive price 0.596

KM2: response to clients’ needsResponds quickly to any complaint raised by clients 0.866Promptly acts if clients are unsatisfied with the quality of service 0.813Makes a concerted effort to act on the clients’ identified needs 0.785Responds positively to changes in clients’ product or service needs 0.748

KA (four factors)KM3: business KA

Undertakes structured and meaningful market research 0.739Surveys clients to assess the quality of our projects or services 0.704Holds regular meetings with employees to generate business ideas 0.641Undertakes staff appraisals to facilitate their input in our operations 0.620Frequently acquires new business ideas through working with others 0.613

KM4: market KAQuickly detects changes in market needs (e.g. preference of clients) 0.835Drives business direction according to the changes in market needs 0.818Actively and timely collects information about our competitors 0.682Occasionally meets with major clients to find out their future needs 0.541

KM5: financial KAAnalyses regularly the financial contribution of our projects or services 0.843Has good financial information about our business operations 0.827Knows how much each of our projects costs us 0.743

KM6: training-based KAEncourages employees to undertake formal university courses 0.801Encourages employees to attend training seminars and conferences 0.782

KD (two factors)KM7: tacit KD

Encourages open communication 0.821Actively encourages staff mentoring or coaching 0.740Records internal best practices on a regular basis 0.730Frequently steps back and review all aspects of our business 0.685Market needs/trends are frequently discussed by managerial and technical staff 0.574

KM8: explicit KDDocuments (e.g. reports and newsletters) about our business achievements areperiodically circulated to external stakeholders 0.799Groupware (e.g. Lotus Notes) is frequently used to share information 0.731Policy and procedure manuals are frequently updated 0.698Written reports are circulated to disseminate knowledge 0.665

KU (one factor)KM9 knowledge utilisation

Uses accumulated knowledge to solve new problems 0.833Is able to apply knowledge to changing competitive conditions 0.825

(continued )

Table IV.Factor analysis of KMconstructs

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Correlation and regression analysesCorrelation analysis was employed to investigate both the existence and strength ofrelationships between the constructs of the theoretical framework. The analysisshowed that all six constructs are positively associated with one another, as are theirfactors. Pearson correlation r (coefficient of correlation) values between the constructsrange from 0.389 to 0.700, and those between the factors range from 0.240 to 0.575. Allof these r-values are significant at the 0.01 level (two-tailed).

Stepwise regression analysis was undertaken to depict how a specific KM constructbeing predicted by the two BE constructs (working as independent variables); and tomeasure the degree of influence of each BE factor on the nine KM factors. To pursue thestepwise analysis, a specific dependent variable (e.g. KR) was hypothesized as beinginfluenced by a set of independent variables (e.g. OE and TE). The independent variables,which had strong correlations with a specific dependent variable, were entered step bystep in its regression model. The significant model selected to predict this dependentvariable has the largest adjusted R 2 (the multiple coefficient of determination) of a powerof 0.80 significant at 0.01 level (Jaccard and Becker, 1997); and both F-ratio for the overallmodel, and t-statistics for the regression coefficients are significant at the 0.01 level(Bowerman et al., 1986). This suggests that the variables included in the final significantmodels are correct as evidenced by their largest and significant predicting power. Checkswere carried out to ensure the absence of multi-collinearity and multi-variate outliersamong the independent variables. All assumptions of linearity, homoscedasticity andindependence of residuals have been met.

As shown in Table V and Figure 2, the analysis reveals that firstly, theindependent variables OE and TE have significant ( p ¼ 0.001) and moderate level ofmutual explanatory power, as the adjusted R 2 ¼ 0.284; thus, lending support to H3.Secondly, both these two variables are significant predictors of KM constructs; theircombination can explain 35.2, 44.6, 46.8 and 51.7 percent of the variability of KU, KR, KAand KD, respectively. This finding endorses H1 and H2 which state that bothorganisational and TEs are positively related to the intensity of the different categories ofKM activities. The findings presented in Table V and Figure 2 also reveal that compared toTE, OE has stronger predicting power over the intensity of KM activities. This impliesthat OE is a stronger “force” to influence KM. Meanwhile, the findings identified that


Uses shared knowledge to improve efficiency 0.825Matches sources of knowledge to problems and challenges 0.783Applies knowledge learned from mistakes 0.779

Notes: Scale: 1 – strongly disagree; 2 – disagree; 3 – neither agree nor disagree; 4 – agree;5 – strongly agree. aExtraction method: principal component analysis. Rotation method: Varimax withKaiser normalization; Factor loadings: significant at the 0.05 and of a power level of 80 percent. Totalvariance explained (percent) of the four factor analyses: KR: 68.3 percent, KA: 65.8 percent, KD: 60.2percent, KU: 65.5 percent. Reliability (Cronbach’s a) of the scales of the four KM constructs: KR: 0.886,KA: 0.877, KD: 0.862, KU: 0.868 Table IV.


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among the four categories of KM activities, KD is predicted and explained by the BEfactors to the largest degree, thus suggesting KD as the strongest “energy receiver.”

The findings shown in Table VI identifies the “organisational supportiveenvironment” factor (OE2) as the most powerful “force” among all BE factors (OE1,OE2 and TE), since it not only predicts and explains the variance of seven KM factors,but also functions as the major predictor that explains larger proportion of thevariance of four KM factors. The “organisational creative environment” factor (OE1)is the major predictor to the variance of “response to market knowledge” (KM1),and “explicit KD” (KM8). The results also indicate that the TE factor TE is only

Independent variablesUnstandardised coefficients b/standardised

coefficient b a (t-statistic) Model summaryDependent variables OE TE R R 2 Adj. R 2 F

KR 0.435/0.537 (7.203 *) 0.169/0.211 (2.824 * *) 0.674 0.454 0.446 57.443 *

KA 0.489/0.420 (5.750 *) 0.421/0.366 (5.005 *) 0.690 0.476 0.468 62.600 *

KD 0.541/0.582 (8.241 *) 0.202/0.220 (3.112 * *) 0.724 0.525 0.517 73.927 *

KU 0.291/0.597 (8.784 *) – 0.597 0.357 0.352 77.162 *

OE – 0.532/0.537 (7.512 *) 0.537 0.289 0.284 56.428 *

TE 0.542/0.537 (7.512 *) – 0.537 0.289 0.284 56.428 *

Notes: *Significant at 0.001 level; * *significant at 0.01 level. aStandardised regression coefficients b(beta coefficient); predictor of larger predicting power represented by larger b coefficient value of thespecific model is bold, with b coefficient italicised

Table V.Stepwise regressionanalysis on BE and KMconstructs

Figure 2.Relationships between BEand KM constructs

KA: Knowledgeacquisition

KD: Knowledgedissemination

KU: Knowledgeutilisation

KR: Responsivenessto knowledge

TE: Technicalenvironment

OE: Organisationalenvironment

0.468*

0.517*

0.352*

0.491*

: more influential internal businessenvironment construct

Independent Variable


: KM activity construct most sensitive to theinternal business environment constructs

Note: *Adj. R2: Adjusted multiple coefficient of determination

0.284*

Dependent Variable

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/0.373

(4.677

* )0.

293/

0.33

5(4

.200

* )0.

623

0.38

90.380

43.8

50*

KM

2:re

spon

seto

clie

nts

’n

eed

s0.

198/

0.27

0(3

.056

** )

0.191

/0.296

(3.354

* )0.

499

0.24

90.

238

22.8

64*

KM

3:b

usi

nes

sK

A0.

298/

0.35

5(4

.762

* )0.187

/0.3724.995

* )0.

615

0.37

90.370

42.0

56*

KM

4:m

ark

etK

A0.

203/

0.26

2(2

.999

** )

0.219

/0.321

(3.668

* )0.

514

0.26

40.

254

24.7

85*

KM

5:fi

nan

cial

KA

0.13

0/0.

238

(2.9

09*

* )0.113

/0.348

(4.252

* )0.

500

0.25

00.

239

22.9

68*

KM

6:tr

ain

ing

-bas

edK

A0.

105/0.439

(5.7

53* )

0.43

90.

192

0.18

733

.097

*

KM

7:ta

cit

KD

s0.

272/

0.26

9(3

.694

* )0.460

/0.516

(7.084

* )0.

702

0.49

20.485

66.4

49*

KM

8:ex

pli

cit

KD

0.355

/0.379

(4.621

* )0.

136/

0.27

6(3

.362

* )0.

573

0.32

90.

319

33.2

81*

KM

9:k

now

led

ge

uti

lisa

tion

0.20

4/0.

223

(2.7

42*

* )0.365

/0.452

(5.565

* )0.

604

0.36

50.356

39.6

56*

Notes:

* Sig

nifi

can

tat

0.00

1le

vel

;*

* sig

nifi

can

tat

0.01

lev

el.

aS

tan

dar

dis

edre

gre

ssio

nco

effi

cien

tsb

(bet

aco

effi

cien

t);

pre

dic

tor

ofla

rger

pre

dic

tin

gp

ower

rep

rese

nte

db

yla

rger

bco

effi

cien

tv

alu

eof

the

spec

ific

mod

elis

bol

d,

wit

hb

coef

fici

ent

ital

icis

ed

Table VI.Step-wise regression

analysis on BE and KMfactors


organisations

73

a predictor of KA activities (i.e. KM3, KM5 and KM6), and surprisingly has nopredicting power when it comes to KR (i.e. KM1 and KM2) or “knowledge utilisation”(i.e. the KU construct with a single factor KM9). In addition, TE’s predicting powerover KD only limited to explicit knowledge (indicated by KM8). These findings notonly dispel the myth that IT infrastructure is an absolute necessity for KD, but alsoreveal that organisational creative and supportive environments are the major driving“forces” for KD, especially in dealing with tacit knowledge – the important source ofcompetitive advantage (Subramaniam and Venkatraman, 2001).

A comparison of the obtained adjusted R 2 values indicates that the variance of fourKM factors (i.e. “KM1: response to market knowledge” “KM3: business KA” “KM7:tacit KD” and “KM9: knowledge utilisation”) are predicted and explained to a largerdegree by the combination of BE factors. This suggests that within each broadcategory of KM activity (represented by a construct), there is a certain type of practices(represented by KM factors) that is more sensitive to changes in the BE factors, thusfunction as major “energy receivers.” The relationships between the BE and KMfactors are graphically shown in Figure 3.

Results of interviewsThe interviews revealed that both organisational and TEs vary significantly amongorganisations. Reasons for such variation are many, including but are not limited tomanagement style, national culture, market position, nature of marketing strategies,and performance history in the local market. The interviews reflect varied intensity ofKM activities as perceived by interviewees representing different OEs, hence offerssome insights of the associations between the internal BE and intensity of KMactivities in different settings. The interviews also highlight that strategic guidanceand innovation policies are perceived as “driving force” being of strong influence onKM activities, which is in line with the statistical findings.

The interviewees indicated that “strategic guidance to KM” was critical to theimplementation of KM activities. Meanwhile, management leadership is seen as beingparamount to the promotion of KM and the conveyance of KM-related vision to variousorganisational levels. The interviews reflect that during the recent economic down turnin Hong Kong (2001-2003) (Chan et al., 2005), the contractors were challenged by fiercecompetition, declining demand and low-profit margins. The companies, which hadclear strategic guidance such as competitive strategies with “Innovation” focus andstrong management leadership, experienced higher intensity in a wide range of KMactivities and ultimately strengthened the companies’ competitive position. On thecontrary, if long-term development needs failed to be clearly addressed during alteringmarket strategy, for example shifting target markets, the intensity of KM activitieswas significantly weakened when KM-related programmes lost direction. As aninterviewee commented:

At the beginning of the past financial year, a business review forum was instigated to coverthe KM related areas on a three-monthly schedule. Unfortunately after the second forum, thepractice was not continued due to staff changes and having a new management direction.

Another interviewee succinctly stated: “With no sustainable support fromlarge profitable projects, our proposed IT-based solutions to disseminate projectknowledge were significantly hindered.” The interviews provide qualitative insights

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74

for the statistical predicting power of “organisational supportive environment” uponthe intensity of most KM activity categories.

The majority of interviewees asserted that innovation is a major KM practice whichcombines activities such as acquiring, disseminating, and utilising knowledge. Aninterviewee indicated:

Construction, in principle, is a creative industry, because each of our projects is unique.Therefore, innovation is naturally an essential part of our operations. All the company needsto do is to encourage the innovative practices.

As commented by interviewees, and reported in a number of professional contractors’publications, innovation is being rewarded through both monetary and non-monetarymeans. Innovation has been adopted by companies for different reasons includingincreasing productivity, controlling cost, gaining technological advantage through

Figure 3.Relationships between

BE and KM factors

KM3

KM4

KM5

KM6

KM7

KM8

KM1

KM2

KM9

0.380*

Notes: *Adj. R2: adjusted multiple coefficient of determination; KM1: response to market knowledge; KM2: response to clients’ needs; KM3: business knowledge acquisition; KM4: market knowledgeacquisition; KM5: financial knowledge acquisition; KM6: training-based knowledge acquisition; KM7: tacit knowledge dissemination; KM8: explicit knowledge dissemination; KM9: knowledge utilisation

OE1:Organisational

CreativeEnvironment

OE2:Organisational

SupportiveEnvironment

TE:Technical

Environment

0.238*

0.356*

0.370*

0.254*

0.239*

0.187*

0.485*

0.319*

: KM activity factors relatively more sensitive to the variance of internal business environmentfactors

: most influential internal business environment factor to KM activities

: KM activity factor most sensitive to the variance of internal business environment factors


Independent VariableDependent Variable


organisations

75

creative design, and applying new technology. For example, innovation was said to bea strategy, especially in bidding for large-scale projects where low-profit margin andhigh-technical requirement mean alternative designs are essential for success.The tendering team is generally formed jointly by functional departments responsiblefor tendering and cost control, and project teams with experience in works of similarnature required by the tender documents. This interdisciplinary team work enablesthe transfer of knowledge acquired from previous project operations into innovativedesigns and construction methods. In the case of joint-venture tendering, knowledgecan be acquired and transferred between venture partners, and is reflected inthe creative designs and methods. These findings provide qualitative support to thepredicting power of “organisational creative environment” upon the intensity of“responsiveness to market” and its strong association with most of the KM factors.

As for the TE, the interviewees identified a plethora of information systems (e.g.project management systems, quality documentation systems, cost and financialcontrol systems, technical information archives, though varies in degree oftechnological sophistication), have already been widely adopted for KA. Thisreflects what has been empirically supported by the predictive power of the TE factor,which was found to focus solely on KA activities.

The interviews also revealed that although the high cost of IT systems was believedto be a concern for contractors, particularly during the economic down-turn (Chan et al.,2005), the IT system integration process within these companies has been ongoing, eventhough their scopes and approaches are varying. In order for integration to besuccessful, top management support and collaboration across the boundaries of variousprofessions were said to be the key. The most difficult task was found not to produce ITtechnical solutions, but to motivate the different functional units such as finance,procurement and project management working together to generate new procedures andinterfaces to enable previously isolated systems to communicate with each other, andparticularly when taking a more radical approach to creating a new system. Risk-averseattitudes and the organisational boundaries were said to be the primary barriers for bothsystem development and implementation. The cases presented in the interviews suggestthat under the circumstances where strong top management leadership and clearstrategic plans are presented, the system development is usually smooth. This findingsupports the statistically identified strong correlation between organisational and TEs.

Concluding remarksThe study reported herein reveals that the impact of internal BE factors on KMactivities, within contracting organisations operating in Hong Kong, is in line withtheoretical propositions derived from the literature. Supported by the empirical andqualitative evidences, this study established that firstly, both organisational and TEshave the capacity to make either positively or negatively impact on the intensity of KMactivities; secondly, the organisational and TEs affect each other in a recursive manner,and both environments serve as stimuli in increasing each other’s dynamism andcapacity. These findings imply that the more conducive these two environments are,the higher the intensity of KM activities becomes, in addition, OE has much strongerimpact on the intensity of KM activities, hence it is the major “force” to facilitate KM.This is in line with the findings of the recent exploratory studies (Egbu et al., 2003a;Fong, 2005b).

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76

Among the three internal BE factors, “organisational supportive environment”appear to have the strongest impact on KM activities particularly “tacit KD” and“knowledge utilisation.” This finding indicates that strategic guidance is an essential“driving force” for KM implementation, and especially for dissemination of tacitknowledge, which is considered as the important source of competitive advantage(Subramaniam and Venkatraman, 2001); and for knowledge utilisation, which in theoryproduces new knowledge (Nonaka and Takeuchi, 2004). In addition, “organisationalcreative environment” strongly affects “responsiveness to market knowledge” and“explicit KD.” The influence of the TE appears to focus exclusively on KA activities.

The empirical study also identified that the intensity level of KD is influenced by thevariances in both organisational and TEs to a largest degree; furthermore, the intensitylevel of “business KA” “response to market knowledge” “knowledge utilisation” and“tacit KD” are most sensitive to changes in the internal BE. These findings suggestthat within the strategic KM cycle, these four types of KM activities are stronger“energy receivers” and easily to be “powered up” through manipulating differentenvironment “forces” in particular by strengthening strategic guidance, encouraginginnovation, and improving IT infrastructure. In doing so, through the interactionsbetween the KM activities (Chen and Mohamed, 2006), the intensity of whole strategicKM cycle will be increased which helps to strengthens organisational competitiveadvantage (Sveiby, 1997).

The findings derived from the empirical study and the interviews suggest thatfirstly, KM implementation will be much more effective if its related practices areformulated as core components of corporate strategy, thereby ensuring accessibility ofmanagement support and resource allocation to enable implementation. Secondly, KUand tacit KD are crucial for building an organisational knowledge asset, whilstparticularly sensitive to changes in the OE. Hence, incentive systems should be used tomotivate tacit knowledge externalisation; meanwhile open, flexible and efficientcommunication styles should be encouraged. Thirdly, empowering policies to promoteautonomous work are important to increasing the sense of responsibility, and hence thewillingness to produce new knowledge through innovative activities. Finally, ITsystem development should be guided by a strategic plan and supported by topmanagement; meanwhile facilitating tacit knowledge sharing and externalisationshould be incorporated as a major function of IT system.

This study was limited only to one type of construction organisations in a specificregion, i.e. Hong Kong. To reach better generalisability, future research would benefitfrom a larger sample size, as well as greater sample diversity in terms of size andcategory of organisations and cultural context as well. Further, qualitative studies suchas in-depth case studies would be also desired to detail the impact of internal BE onKM activities.

References

Abou-Zeid, E.S. (2002), “A knowledge management reference model”, Journal of KnowledgeManagement, Vol. 6 No. 5, pp. 486-99.

Alavi, M. and Leidner, D.E. (2001), “Review: knowledge management and knowledgemanagement systems: conceptual foundation and research issues”, MIS Quarterly, Vol. 25No. 1, pp. 107-34.


organisations

77

Al-Ghassani, A.M., Kamara, J.M., Anumba, C.J. and Carrillo, P.M. (2002), “A tool for developingknowledge management strategies”, available at: www.itcon.org/2002/5/paper.pdf

Ankrah, N.A. and Langford, D.A. (2005), “Architects and contractors: a comparative study oforganizational cultures”, Construction Management & Economics, Vol. 23 No. 6,pp. 595-607.

Barthorpe, S., Duncan, R. and Miller, C. (2000), “The pluralistic facets of culture and its impact onconstruction”, Property Management, Vol. 18 No. 5, pp. 335-51.

Becerik, B. (2005), “Usage of online collaboration and project management technology to achievesuccess and gain competitive advantage in virtual teams: a case study”, Proceedings of theCIB W102-2005 Meeting and International Conference: Information and KnowledgeManagement in a Global Economy: Challenges and Opportunities for ConstructionOrganizations, Lisbon, Portugal, pp. 87-96.

Blayse, A.M. and Manley, K. (2004), “Key influences on construction innovation”, ConstructionInnovation, Vol. 4 No. 3, pp. 143-54.

Bossink, B.A.G. (2004), “Managing drivers of innovation in construction network”, Journal ofConstruction Engineering and Management, Vol. 130 No. 3, pp. 337-45.

Bowerman, B.L., O’Connell, R.T. and Dickey, D.A. (1986), Linear Statistical Models, DuxburyPress, Boston, MA.

Burke, W.W. and Litwin, G.H. (1992), “A causal model of organisational performance andchange”, Journal of Management, Vol. 18 No. 3, pp. 523-45.

Chan, E.H.W., Chan, M.W. and Chan, A.T.S. (2001), “Disintegrating professional boundaries:a case with the building professions in Hong Kong”, International Journal of ProjectManagement, Vol. 19 No. 2, pp. 127-35.

Chan, J.K.W., Tam, C.M. and Cheung, R.K.C. (2005), “Construction firms at the crossroads inHong Kong: going insolvency or seeking opportunity”, Engineering, Construction andArchitectural Management, Vol. 12 No. 2, pp. 111-24.

Chen, L. and Mohamed, S. (2005), “A self-assessment tool for knowledge managementimplementation in the construction industry”, Proceedings of the Third InternationalConference on Construction in the 21st Century, Advancing Engineering, Management andTechnology, Athens, Greece, pp. 688-93.

Chen, L. and Mohamed, S. (2006), “Empirical analysis of knowledge management activities inconstruction organisations”, Proceedings of the Joint International Conference onComputing and Decision Making in Civil and Building Engineering, Montreal, Canada,pp. 1564-73.

Chen, L., Mohamed, S. and Chan, E.M.Y. (2005), “Knowledge management practices inconstruction: evidence from Hong Kong”, Proceedings of the CIB W102-2005 Meeting andInternational Conference: Information and Knowledge Management in a Global Economy:Challenges and Opportunities for Construction Organizations, Lisbon, Portugal, pp. 435-43.

Chinowsky, P.S. and Meredith, J.E. (2000), “Strategic management in construction”, Journal ofConstruction Engineering and Management, Vol. 126 No. 1, pp. 1-9.

Coakes, S.J. (2005), SPSS: Analysis without Anguish: Version 12.0 for Windows, Wiley Australia,Ltd, Milton.

Dalkir, K. (2005),KnowledgeManagement inTheory andPractice, Elsevier Butterworth-Heinemann,London.

Darroch, J. (2003), “Developing a measure of knowledge management behaviours and practices”,Journal of Knowledge Management, Vol. 7 No. 5, pp. 41-54.

Debowski, S. (2006), Knowledge Management, Wiley Australia, Ltd, Sydney.

CI8,1

78

Diakoulakis, I.E., Georgopoulos, N.B., Koulouriotis, D.E. and Emiris, D.M. (2004), “Towards aholistic knowledge management model”, Journal of Knowledge Management, Vol. 8 No. 1,pp. 32-46.

Egbu, C. (2004), “Managing knowledge and intellectual capital for improved organisationalinnovations in the construction industry: an examination of critical success factors”,Engineering, Construction and Architectural Management, Vol. 11 No. 5, pp. 301-15.

Egbu, C., Anumba, C., Quintas, P., Hutchinson, V., Hayles, C. and Ruikar, K. (2003a), “Knowledgeproduction, sources & capabilities in the construction industry”, available at: www.knowledgemanagement.uk.net

Egbu, C., Anumba, C., Quintas, P., Hutchinson, V., Hayles, C. and Ruikar, K. (2003b), “Techniques& technologies for knowledge management”, available at: www.knowledgemanagement.uk.net

ETWB (2005), “List of approved contractors for public works”, The Environment, Transport andWorks Bureau (ETWB) of the Government of the Hong Kong Special AdministrativeRegion (HKSAR), available at: www.etwb.gov.hk/consultants_and_contractors/contractors

Fong, P.S.W. (2005a), “Co-creation of knowledge by multidisciplinary project teams”, in Love,P.E.D., Fong, P.S.W. and Irani, Z. (Eds), Management of Knowledge in ProjectEnvironments, Elsevier Butterworth-Heinemann, London.

Fong, P.S.W. (2005b), “Managing knowledge in project-based professional services firms:an international comparison”, in Love, P.E.D., Fong, P.S.W. and Irani, Z. (Eds),Managementof Knowledge in Project Environments, Elsevier Butterworth-Heinemann, London.

Gallivan, M. and Srite, M. (2005), “Information technology and culture: identifying fragmentaryand holistic perspectives of culture”, Information and Organization, Vol. 15 No. 4,pp. 295-338.

Gold, A.H., Malhotra, A. and Segars, A.H. (2001), “Knowledge management: an organizationalcapabilities perspective”, Journal of Management Information System, Vol. 18 No. 1,pp. 185-214.

Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis,Prentice-Hall, Englewood Cliffs, NJ.

Hari, S., Egbu, C. and Kumar, B. (2005), “A knowledge capture awareness tool: an empirical studyon small and medium enterprises in the construction industry”, Engineering, Constructionand Architectural Management, Vol. 12 No. 6, pp. 533-68.

Hartmann, A. (2006), “The context of innovation management in construction firms”,Construction Management & Economics, Vol. 24 No. 6, pp. 567-78.

HKCA (2005), “Hong Kong construction association members list”, Hong Kong ConstructionAssociation, available at: www.hkca.com.hk/new/pg_hkca_member.htm

Jaccard, J. and Becker, M.A. (1997), Statistics for the Behavioral Sciences, Brooks/Cole PublishingCompany, A Division of International Thomson Publishing Inc., London.

Kalling, T. (2003), “Knowledge management and the occasional links with performance”, Journalof Knowledge Management, Vol. 7 No. 3, pp. 67-81.

Kamara, J.M., Augenbroe, G., Anumba, C.J. and Carrillo, P.M. (2002), “Knowledge management inthe architecture, engineering and construction industry”, Construction Innovation, Vol. 2No. 3, pp. 53-67.

Kululanga, G.K., Price, A.D.F. and McCaffer, R. (2002), “Empirical investigation of constructioncontractors’ organizational learning”, Journal of Construction Engineering andManagement, Vol. 128 No. 5, pp. 385-91.


organisations

79

Kumaraswamy, M., Love, P.E.D., Dulaimi, M. and Rahman, M. (2004), “Integrating procurementand operational innovations for construction industry development”, Engineering,Construction and Architectural Management, Vol. 11 No. 5, pp. 323-34.

McCaffer, R. and Edum-Fotwe, F.T. (2006), “Improving construction: why innovation tarries”,paper presented at Joint International Conference on Construction Culture, Innovation, andManagement (CCIM), available at: www.buid.ac.ae/conf/KeynoteSpeeches

McCann, J.E. and Buckner, M. (2004), “Strategically integrating knowledge managementinitiatives”, Journal of Knowledge Management, Vol. 8 No. 1, pp. 47-63.

Moffett, S., McAdam, R. and Parkinson, S. (2003), “An empirical analysis of knowledgemanagement applications”, Journal of Knowledge Management, Vol. 7 No. 3, pp. 6-26.

Mouritsen, J. (2004), “Measuring and intervening: how do we theorise intellectual capitalmanagement?”, Journal of Intellectual Capital, Vol. 5 No. 2, pp. 257-67.

Neuman, W.L. (2003), Social Research Methods: Qualitative and Quantitative Approaches, Allynand Bacon, Boston, MA.

Ng, K.H. (2003), “Application of knowledge management in Hong Kong construction industry”,MSc thesis, Department of Building and Construction, City University of Hong Kong,Hong Kong.

Nonaka, I. and Takeuchi, H. (2004), “Theory of organisational knowledge creation”, inTakeuchi, H. and Nonaka, I. (Eds), Hitotsubashi on Knowledge Management, Wiley,New York, NY.

Ostroff, C. and Schmitt, N. (1993), “Configurations of organisational effectiveness and efficiency”,Academy of Management Journal, Vol. 36 No. 6, p. 1345.

Palmer, J. and Platt, S. (2005), Business Case for Knowledge Management in Construction, CIRIA,London.

Peansupap, V. and Walker, D. (2005), “Factors affecting ICT diffusion: a case study of three largeAustralian construction contractors”, Engineering, Construction and ArchitecturalManagement, Vol. 12 No. 1, pp. 21-37.

Pillania, R.K. (2006), “State of organisational culture for knowledge management in Indianindustry”, Global Business Review, Vol. 7 No. 1, pp. 119-35.

Price, A.D.F. and Newson, E. (2003), “Strategic management: consideration of paradoxesprocesses, and associated concepts as applied to construction”, Journal of Management inEngineering, Vol. 19 No. 4, pp. 183-92.

Robinson, H.S., Carrillo, P.M., Anumba, C.J. and Al-Ghassani, A.M. (2005), “Knowledgemanagement practices in large construction organisations”, Engineering, Constructionand Architectural Management, Vol. 12 No. 5, pp. 431-45.

Salisbury, M.W. (2003), “Putting theory into practice to build knowledge management systems”,Journal of Knowledge Management, Vol. 7 No. 2, pp. 128-41.

Stewart, R.A., Mohamed, S. and Daet, R. (2002), “Strategic implementation of IT/IS projects inconstruction: a case study”, Automation in Construction, Vol. 11 No. 6, pp. 681-94.

Stewart, R.A., Mohamed, S. and Marosszeky, M. (2004), “An empirical investigation into the linkbetween information technology implementation barriers and coping strategies in theAustralian construction industry”, Construction Innovation, Vol. 4 No. 3, pp. 155-71.

Subramaniam, M. and Venkatraman, N. (2001), “Determinants of transnational new productdevelopment capability: testing influence of transferring and deploying tacit overseasknowledge”, Strategic Management Journal, Vol. 22 No. 4, pp. 359-78.

Sutton, D. (2001), “What is knowledge and can it be managed?”, European Journal of InformationSystems, Vol. 10 No. 2, pp. 80-8.

CI8,1

80

Sveiby, K.E. (1997), The New Organisational Wealth: Managing andMeasuring Knowledge-basedAssets, Berrett Koehler, San Francisco, CA.

Tabachinick, B.G. and Fidell, L.S. (2001), Using Multivariate Statistics, Allyn and Bacon,Boston, MA.

Tserng, H.P. and Lin, Y.C. (2004), “Developing an activity-based knowledge management systemfor contractors”, Automation in Construction, Vol. 13 No. 6, pp. 781-802.

Waly, A.F. and Thabet, W.Y. (2003), “A virtual construction environment for preconstructionplanning”, Automation in Construction, Vol. 12 No. 2, pp. 139-54.

Corresponding authorSherif Mohamed can be contacted at: [email protected]


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