knowledge-sharing motivations affecting r&d employees' acceptance of electronic knowledge...
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Knowledge-sharing motivations affecting R&Demployees' acceptance of electronic knowledgerepositoryShin-Yuan Hung a , Hui-Min Lai a b & Wen-Wen Chang aa Department of Information Management , National Chung Cheng University , Minhsiung,Chia-Yi, 62100, Taiwanb Department of Information Management , Chienkuo Technology University , Chang-Hua,Chang-Hua, 50094, TaiwanPublished online: 18 Feb 2011.
To cite this article: Shin-Yuan Hung , Hui-Min Lai & Wen-Wen Chang (2011) Knowledge-sharing motivations affecting R&Demployees' acceptance of electronic knowledge repository, Behaviour & Information Technology, 30:2, 213-230, DOI:10.1080/0144929X.2010.545146
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Knowledge-sharing motivations affecting R&D employees’ acceptance
of electronic knowledge repository
Shin-Yuan Hunga*, Hui-Min Laia,b and Wen-Wen Changa
aDepartment of Information Management, National Chung Cheng University, Minhsiung, Chia-Yi, 62100, Taiwan; bDepartment ofInformation Management, Chienkuo Technology University, Chang-Hua, Chang-Hua, 50094, Taiwan
(Received 7 December 2009; final version received 30 November 2010)
Why would R&D employees be willing to use an electronic knowledge repository (EKR) for knowledge-sharing?This study integrates a technology acceptance model (TAM) to investigate the influence of extrinsic and intrinsicmotivations on R&D employees’ acceptance of an EKR for knowledge-sharing. Empirical data were collectedthrough a survey, which gathered data from 225 employees working in 10 organisations in Taiwan. The resultsindicated that (1) reputation and reciprocity were found to be two important antecedents to perceived usefulnessand perceived ease of use; (2) altruism was also found to be an important antecedent to perceived ease of use;(3) reputation was the most influential factor of perceived usefulness, and another influential factor of perceivedusefulness was reciprocity. Three knowledge-sharing motivations that significantly affect the perceived ease ofuse were listed as reciprocity, altruism, and reputation, according to the relative importance; (4) altruism playsan important role in explaining the EKR usage intentions for knowledge-sharing both directly and indirectly;and (5) the results were consistent with the propositions of TAM. This study contributes theoretically andempirically to the body of EKR usage research and also has practical implications.
Keywords: knowledge sharing; knowledge-sharing motivations; electronic knowledge repositories; knowledgemanagement; information system acceptance
1. Introduction
Issues regarding knowledge management (KM) havecaptured the interest and attention of many organi-sations in general, the R&D departments in parti-cular (Miller and Morris 1999, Benabou and Tirole2003, Berends et al. 2006, Park and Kim 2006),because it has recently become dependent upon adepartment’s demands and can be developed for theneeds of a single, specific department. An organisa-tion’s R&D employees always need to develop newproducts, re-engineer old products, acquire newtechnology and share know-how knowledge. TheKM system (KMS) can contribute to those tasks(Lee et al. 2009). Thus, their need for a KMS ismuch stronger than that of other employees in theorganisation. KMS categories can be divided intoelectronic knowledge repositories (EKRs) and com-munities of practice. The EKR corresponds to thecodification approach and communities of practicecorrespond with the personalisation approach(Hansen et al. 1999). The EKR is one of the mostcommon forms of KMS in organisations (He andWei 2009). However, what are the major motiva-tional factors that influence R&D employees to
accept the EKR in their organisations? Daviset al.’s. (1989) technology acceptance model (TAM)emphasises perceived ease of use and perceivedusefulness as the major factors in the acceptance ofan information technology (IT). The influence factorsaffecting the acceptance of a new IT are likely tovary with the technology, target users and context(Moon and Kim 2001). A large number of externalvariables influencing the core elements of TAM wereexplored and hypothesised: for example, individualcharacteristics (Igbaria et al. 1996, Hong et al. 2001,Pijpers et al. 2001, Ong et al. 2004, Saade andBahli 2005, Lu et al. 2008), organisational character-istics (Igbaria et al. 1996, Pijpers et al. 2001), task-related characteristics (Pijpers et al. 2001, Kamis et al.2008), IT characteristics (Hong et al. 2001, Pijperset al. 2001, Fu et al. 2006, Kamis et al. 2008, Lu et al.2008) and so on.
Why would R&D employees be willing to use anEKR for knowledge-sharing? Recent EKR studieshave shown that the use of the EKR for knowledge-sharing is determined by knowledge-sharing motiva-tions, such as reputation (Kankanhalli et al. 2005a,He and Wei 2009), reciprocity (Kankanhalli et al.2005a, He and Wei 2009), enjoyment in helping others
*Corresponding author. Email: [email protected]
Behaviour & Information Technology
Vol. 30, No. 2, March–April 2011, 213–230
ISSN 0144-929X print/ISSN 1362-3001 online
� 2011 Taylor & Francis
DOI: 10.1080/0144929X.2010.545146
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(Kankanhalli et al. 2005a, Lin 2008, He and Wei 2009),knowledge self-efficacy (Kankanhalli et al. 2005a),organisational rewards (Kankanhalli et al. 2005a, Heand Wei 2009) and so on. This motivation can beextrinsic or intrinsic in nature (Ryan and Deci 2000,Benabou and Tirole 2003). However, an effective EKRtypically requires an appropriate combination oftechnological and human elements (Davenport et al.1998, Wu and Wang 2006). Thus, if the user hasknowledge-sharing motivations, will he or she thenaccept the use of the EKR, either directly or indirectlythrough perceived usefulness and perceived ease ofuse? In addition, how are they related?
In the past, many organisations encountered atremendous bottleneck when they implemented anEKR, because they believed that, as long as theknowledge platform was well built, employees wouldshare it voluntarily. However, EKR benefit comesfrom effective knowledge-sharing (Wu and Wang2006). Sharing knowledge may cause a diffusion ofknowledge and may eliminate the uniqueness of theknowledge workers (Davenport and Prusak 1998,Kankanhalli et al. 2005a). No matter how well thesystem is designed, if it could not tally with users’motivations, users might refuse to accept it and furtheraffect organisational performance (Malhotra andGalletta 2004). Thus, what individual sharing motiva-tions can explain how a user comes to believe that asystem is useful? In addition, what individual sharingmotivations could be a probable antecedent to thebelief that a system is simple or difficult to use?Therefore, studying individual sharing motivation isespecially important in understanding the users’acceptance of EKR for knowledge-sharing. Althoughthe individual’s primary use of the EKR is forknowledge-sharing and knowledge-seeking (Bocket al. 2006, Kulkarni et al. 2006, Bock et al. 2008), inthis study, we only focus on one side – knowledgesharing. Because it is often seen that R&D employeesmove from one project to another or experience a fastturnover, much essential and professional knowledge islost, and then knowledge cannot be shared and passeddown. Thus, studying the EKR usage for knowledge-sharing is of paramount importance.
Prior research has investigated various knowledge-sharing motivations, and it was believed that theywould facilitate EKR usage for knowledge-sharing(Kankanhalli et al. 2005a, Bock et al. 2008, He andWei 2009). According to Davenport and Prusak (1998,p.31), within organisations, the medium of exchange isseldom money, but there are agreed-upon currenciesthat drive the knowledge market. Knowledge sharerslike to share their knowledge because they can obtainthe benefits of reputation, reciprocity and altruism.Based on their perspectives, this study emphasises the
knowledge-sharing motivations, including reputation,reciprocity and altruism, which are derived from thesocial exchange theory (SET). Reputation and reci-procity are examples of extrinsic motivation, whereasaltruism is an example of intrinsic motivation.Reputation is recognised as an example of extrinsicmotivation, because it is defined as ‘ReputationDesign’, which is one kind of system characteristic.This research aims to understand (1) the relativeimportance of these motivational factors for sharing(reputation, reciprocity and altruism) and (2) thecausal relationships among variables on the acceptanceof the EKR.
2. Theoretical background
2.1. R&D employees and electronicknowledge repository
Today, the fourth generation of R&D is coming andKM becomes an indispensable requisite for R&D(Miller and Morris 1999, Park and Kim 2006). R&Dwork is usually perceived as a group of activitiesinvolving interaction and knowledge exchange betweenpeople. R&D work produces a number of documentsand requires mutual sharing among team members(Barthes and Tacla 2002). EKRs constitute the mostcommon form of IT supporting KM (Bock et al. 2006).The R&D employees who use the EKR will improvetheir R&D effectiveness (Lee et al. 2009).
Some problems that may exist during the process ofR&D can be resolved efficiently and effectively by theEKR. For example:
. knowledge should be transferred and sharedrapidly among R&D employees (Cummingsand Teng 2003), and the EKR can make thishappen more easily and faster;
. lack of knowledge and an overly long time toacquire it because of the fact that some R&Demployees may need a longer time to learn (Rusand Lindvall 2002). In the EKR, documentedknowledge can provide the basis for self-trainingmaterial. The EKR can help employees learnfrom others (Gray and Durcikova 2005) andthrough self-study any time;
. R&D employees constantly repeat mistakesbecause they forget what they learnt from theprevious projects (Rus and Lindvall 2002). TheEKR avoids the same mistakes and enables theproject to succeed more easily (Davenport et al.1998);
. R&D employees change their tasks from oneproject to another and, therefore, much experi-ence is usually lost (Barthes and Tacla 2002).EKR can effectively store valuable experiences
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and successful solutions from the past (Gray andDurcikova 2005); and
. most lessons relating to projects are memorisedby project team members. The EKR clearlyclassifies which member possesses what kind ofknowledge (Davenport and Prusak 1998).
Park and Kim (2006) suggest that KMS comprisessix functions, namely knowledge portal, informationretrieval, document management, workflow manage-ment, collaboration and analysis. Table 1 shows the listof KMS functions and related sub-functions. Asmentioned above, all of the KMS functions are definedto support the R&D process.
2.2. Technology acceptance model
Studies of IT usage often use TAM to predict andexplain behavioural intention and system usage. TAMwas proposed by Davis et al. (1989) and assumes thatbeliefs in the information system will influenceattitudes, which will in turn lead to the intentions,which will then influence usage behaviour. The beliefsinclude two variables, namely perceived usefulness andperceived ease of use. Perceived usefulness is definedas ‘the degree to which a person believes that usinga particular system would enhance his or her jobperformance’ (Davis 1989, p.320). Perceived ease ofuse is defined as ‘the degree to which a person believesthat using a particular system would be free of effort’(Davis 1989, p.320).
TAM is believed to be a useful, parsimonious,predicative and robust model compared with othermodels (Venkatesh 2000), although it lacks variablesrelated to both human and social factors (Legris et al.2003). Prior studies (Chau 1996, Hong et al. 2001, Onget al. 2004, Saade and Bahli 2005, Wu and Wang 2005)on TAM adopted a simple model by removing the‘attitude’ construct, because this was believed to act as
a weak mediator. Ignoring the ‘attitude’ construct canhelp people to understand the influence of perceivedease of use and perceived usefulness constructs ondependent variables (Davis 1989, Davis et al. 1992,Venkatesh 2000). In this study, the ‘attitude’ constructis dropped in order to simplify the TAM model.
2.3. Social exchange theory (SET) andknowledge-sharing motivations
SET posits ‘benefit maximisation and cost minimisa-tion’, and this common aphorism sums up much of thewisdom embedded in the social exchange process, inwhich the individual motivations can be classified intointrinsic and extrinsic benefits (Deci and Ryan 1980,Benabou and Tirole 2003), crucial for knowledgetransfer (Osterloh and Frey 2000). Extrinsic motiva-tion refers to the fact that, when a person isextrinsically motivated, he or she is acting to gainsome tangible reward or valuable outcome (Deci andRyan 1980), such as (1) organisational rewards, like abonus or money for contributing knowledge (Hall2001a, Hall 2001b, Kankanhalli et al. 2005a, He andWei 2009), (2) reputation benefits to enhance his or herimage and social status in the organisation (Ba et al.2001, Kankanhalli et al. 2005a, He and Wei 2009), (3)knowledge which is shared due to the reciprocitypeople obtain from each other (Wasko and Faraj 2000,Wasko and Faraj 2005, Kankanhalli et al. 2005a, Lin2007, He and Wei 2009). Intrinsic motivation refers tothe fact that, when a person is intrinsically motivated,he or she will engage in an action primarily for thepleasure or satisfaction gained from performing theactivity (Deci and Ryan 1980). Examples of intrinsicmotivation are (1) people enjoy and derive pleasurefrom knowledge-sharing because they enjoy helpingothers (Kollock 1999, Fehr and Gachter 2000, Lin2007), (2) the belief that people with knowledge self-efficacy have that they are capable of providingvaluable knowledge and are willing to share it withothers (Kankanhalli et al. 2005a, Lin 2007), and (3) theself-worth that is obtained through knowledge-sharing(Bock et al. 2005). The three motivational factorsunderlying this study are reputation, reciprocity andaltruism.
There is a growing body of academic research thatexamines the influencing factors of EKR usage, assummarised in Table 2. Their research contexts arecategorised in terms of sharing only, seeking only orthe combination of both. In summary, there is arelative lack of attention to (1) the relative importanceof these sharing motivational factors and (2) thecausal relationships among variables on the accep-tance of the EKR. This study contributes to filling inthis gap.
Table 1. KMS functions.
KMS functions Sub-functions
Knowledgeportal
Integrated interface, link management,annotations
Informationretrieval
Search agents, user profiling,visualisation, finding experts
Documentmanagement
Finding documents, version control,metadata management, permissionsmanagement
Workflowmanagement
Process definition, task assignment,authority, management
Collaboration Community of practice, chatting,conferencing, mailing
Analysis User analysis, market analysis,knowledge analysis
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Table 2. Summary of influencing factors of EKR usage.
Study
Use category
Influencing factors SampleSharingonly
Seekingonly Both
He et al.(2009)
. Perceived trust, perceivedseeking effort, perceivedusefulness, seekingcontinuance intention
186 usable responsesfrom a leading ITcorporation in China
Bock et al.(2008)
. KRSsuccess
Extrinsic rewards, intrinsicrewards, organisationaltrust, KRS output quality,KRS searchability, perceivedusefulness, user satisfaction
141 usable responses (39responses fromSingapore 102responses from China)
He and Wei(2009)
. User’s contribution intention,user’s seeking intention,facilitating conditions, userhabit, contribution belief,seeking belief, contributionattitude, seeking attitude,user satisfaction, users’extent of confirmation
161 usable responsesregarding knowledgecontribution behaviorand 201 usableresponses regardingknowledge seekingbehavior
King andMarks(2008)
. Supervisory control,organisational support, easeof use, usefulness, sharingfrequency, sharing effort
169 usable responses in alarge US federalagency
Lin andHuang(2008)
. Task interdependence, tasktacitness, KMScharacteristics, perceivedtask technology fit, KMSself-efficacy, personaloutcome expectations,performance-relatedoutcome expectations
192 usable responses inTaiwanese companies
Bock et al.(2006)
. Perceived usefulness, perceivedease of use, future obligation,seeker knowledge growth,collaborative norms, self-efficacy, resource facilitatingconditions
134 workingprofessionals inknowledge-intensiveorganisations
Watson andHewett(2006)
. Ease of knowledge access,training in knowledge reuse,computer self-efficacy, trustin knowledge source, valueof knowledge, frequency ofknowledge reuse, projectperformance, organisationaltenure, advancement withinthe organisation, frequencyof knowledge contribution.
430 usable responses inorganisations
Gray andDurcikova(2005)
. Learning orientation,intellectual demands, timepressure, risk aversion,sourcing from colleagues,sourcing from documents,sourcing from repository
110 usable responsesfrom 7 organisations
Money andTurner(2005)
. Usage ingeneral
Perceived usefulness, perceivedease of use, behavioralintention to use
35 usable responses in2 major NortheasternU.S. metropolitanareas with systemaccess
Kankanhalliet al.(2005a)
. Loss of knowledge power,codification effort,organisational reward,image, reciprocity,
150 usable responsesfrom 10 organisations
(continued)
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3. Research model and hypotheses
Figure 1 presents the model of our hypotheses.
3.1. Hypotheses regarding TAM
R&D work focuses mainly on innovation and speed,and thus R&D employees must bear severe pressures interms of product development time and marketresponse when trying to chase business opportunities.Thus, it is increasingly necessary to study EKR incomplex R&D settings. Previous studies on informa-tion system usage point out that individual behaviouris to minimise the effort and support the relation-ship between ease of use and behavioural intention(Venkatesh 2000). If a new system is time-consumingor difficult to learn, then there is a natural tendency for
people to avoid using it (Venkatesh 1999, Malhotraand Galletta 2004). Thus, accessible EKR will promoteEKR usage intentions for knowledge-sharing. Hence,we hypothesise:
H1. Perceived ease of use will have a positive effecton behavioural intention to use EKR for knowl-edge-sharing.
Since R&D work requires more expertise, EKRcan provide R&D employees with complete knowl-edge storage, to maintain precise experience fromprior employees and hence provide R&D employeeswith a smoother operation. Therefore, when theEKR can facilitate R&D tasks, the behaviouralintention of using EKR for knowledge-sharing isalso enhanced. Thus, the greater the usefulness of the
Table 2. (Continued).
Study
Use category
Influencing factors SampleSharingonly
Seekingonly Both
knowledge self-efficacy,enjoyment in helping others,pro-sharing norms,identification, generalisedtrust
Kankanhalliet al.(2005b)
. Perceived output quality,perceived ease of use,knowledge sharing norms,resource availability,incentive availability, tasktacitness, taskinterdependence
160 respondents from 8public-sectororganisations inSingapore
Note: KRS, knowledge repository systems; EKR, electronic knowledge repository.
Figure 1. Research model.
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EKR in enabling R&D employees to accomplishtheir tasks, the more frequently it will be used,further influencing usage intention. Therefore, wehypothesise:
H2. Perceived usefulness will have a positive effecton behavioural intention to use EKR for knowl-edge-sharing.
TAM suggests that perceived ease of use has anindirect effect on behavioural intention throughperceived usefulness. Here, perceived ease of userepresents the belief that an EKR can be appliedwithout effort. Previous studies (Davis et al. 1989, Leeet al. 2005) have also shown that perceived ease of usedetermines perceived usefulness. System ease of usedecreases the cost of system usage, facilitating thereallocation of the user to other activities. The userthus can accomplish more tasks with the same effort.Easier systems also enhance employee work perfor-mance. Additionally, EKR was designed to supportR&D work such as content management tools, knowl-edge-sharing tools, knowledge search and retrievalsystems. For example, a more user-friendly interfacemakes it easier for R&D employees to use the EKR topropose and retrieve knowledge and, thus, be per-ceived as more ‘useful’ in their tasks. We thushypothesise:
H3. Perceived ease of use will have a positive effecton perceived usefulness of the EKR.
3.2. Hypotheses regarding extrinsic and intrinsicmotivations for knowledge sharing
3.2.1. Reputation
Individuals can be motivated by either extrinsic orintrinsic factors, and reputation is an example ofextrinsic motivation for sharing, and is defined assystem characteristic. Through the reputation designof the EKR, the system records the number of usagesand the number of contributions. The credits then goto knowledge contributors. Therefore, individualswho share more knowledge receive a higher reputa-tion (Davenport and Prusak 1998). Previous studiessuggest that individuals participate in KM practices toimprove or establish a reputation (Constant et al.1996, Donath 1999, Wasko and Faraj 2005) or toearn peer recognition (Carrillo et al. 2004). Previousstudies have shown that building a reputation is astrong motivator for knowledge-sharing (Davenportand Prusak 1998, Kankanhalli et al. 2005a). There-fore, when R&D employees see that EKR forknowledge-sharing can enhance their reputation, their
inclination to use this EKR will increase. Thus, wehypothesise:
H4. Reputation will have a positive effect onbehavioural intention to use EKR for knowledge-sharing.
System characteristics are recognised as one cate-gory of external variable that affect both perceived easeof use and perceived usefulness (Davis et al. 1989, Honget al. 2001). System features can also be considered anexternal variable of TAM, and significant relationshipshave been found between the system variables andTAM constructs (Venkatesh and Davis 2000). Addi-tionally, Venkatesh and Davis (2000) propose thatperceived usefulness is affected by image, which meanssocial status, upgraded by the use of innovativetechnologies. Venkatesh and Davis (2000, p.189) arguethat ‘the increased power and influence resulting fromelevated status provides a general basis for greaterproductivity.’ Therefore, an individual may perceivethat using the system will improve their job perfor-mance. An individual may thus believe that the systemis useful because it improves their image and reputation(Yi et al. 2006).
Individuals could expend effort because of bothextrinsic and intrinsic motivations (Deci and Ryan1985). Skinner (1953), the representative scholar inBehaviour Science related to Educational Psychol-ogy, proposes that, when a teacher utilises a positivereinforcer to appropriately apply stimulation, specificbehavioural patterns are automatically established;for example, giving gifts on the completion ofhomework; giving a higher score to students whoare proactive in speaking during class; etc. Thesegifts or scores are all classified as extrinsic motiva-tion but can assist students in enhancing theirconfidence and hence overcoming their learningdifficulties. Previous research indicates that reputa-tion building is a strong motivator for activeparticipation in electronic networks of practice(Donath 1999). The reputation mechanism used inthis study is revealed by ‘Knowledge ContributionCharts’, which show reputation-related messages,such as ranking. Therefore, while motivation forsharing relies on the acquisition of extrinsic reputa-tion, individuals will be willing to contribute effortsand load their burden on psychology. They thusperceive the system as becoming easier to use. Wetherefore hypothesise:
H5. Reputation will have a positive effect onperceived usefulness of the EKR.H6. Reputation will have a positive effect onperceived ease of use of the EKR.
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3.2.2. Reciprocity
Why would R&D employees expend any effort in theabsence of extrinsic incentives, such as monetaryreward and enhanced reputation? One answer may bethat they are motivated to establish reciprocal relation-ships with others. According to Davenport and Prusak(1998), people suffer from limited time, energy andknowledge, and thus are usually unwilling to sharescarce resources unless it is profitable for them.Reciprocity is a form of conditional gain, meaningthat people expect future benefits from their presentactions. People reciprocate previous friendly actions(Fehr and Gachter 2000), which they believe are likelyto lead to mutual benefits (Lin 2007, Hsu and Lin2008) or knowledge feedback in the future (Kankan-halli et al. 2005a) and thus they have strongerknowledge-sharing intentions (Lin 2007). When R&Demployees feel that EKR for knowledge-sharing canlead to future requests for knowledge being met, theywill be more inclined to use EKR for knowledge-sharing. Thus, we hypothesise:
H7. Reciprocity will have a positive effect onbehavioural intention to use EKR for knowledge-sharing.
If individual sharing motivation is based onextrinsic reciprocity, namely the expectation of afuture relationship based on cooperation and a beliefthat necessary knowledge will be provided (Davenportand Prusak 1998), leading to confidence that jobperformance will improve, then users with reciprocalmotivation will believe that the system can improveknowledge-sharing speed and efficiency, fostering theperception that the system is useful. Consequently, anindividual’s higher norm of reciprocity would lead togreater perceived usefulness due to greater confidencein the belief that the necessary knowledge will befavourably returned.
When expectations of reciprocal benefits arestrong, individuals are willing to expend time andeffort on studying, and thus see the system as moreaccessible. Malhotra and Galletta (2004) proposed thatuser motivations can positively affect perceived useful-ness, perceived ease of use, intention on initial use andsustained use. Therefore, these suggest that the benefitsassociated with expected reciprocity significantly andpositively affect perceived ease of use and usefulness ofthe EKR. Therefore, we hypothesise:
H8. Reciprocity will have a positive effect onperceived usefulness of the EKR.H9. Reciprocity will have a positive effect onperceived ease of use of the EKR.
3.2.3. Altruism
Altruism is an example of intrinsic motivation forsharing, which contrasts with reciprocity, and can beconsidered a form of unconditional kindness withoutexpecting anything being provided in return (Krebs1975, Smith 1981, Fehr and Gachter 2000). Altruisticpeople simply provide help and enjoy doing it(Kollock 1999, Lin 2007). People having a desire tohelp others stems from relative altruism (Constantet al. 1996, Davenport and Prusak 1998, Lin 2007).Hoffman (1975) also proposed a concept of empathy,a kind of emotional response that closely resemblesthe feelings of others. Therefore, the more empathic aknowledge sharer acts the more altruistic he willbehave (Krebs 1975), for instance, recognition of‘doing the same justice and rationality to everyone’; itwill enhance the usage intention of the EKR forknowledge-sharing. Hence, the following hypothesis isproposed:
H10. Altruism will have a positive effect onbehavioural intention to use EKR for knowl-edge-sharing.
This study defines altruism as perceived pleasureobtained from helping others by sharing knowledgethrough EKR (Wasko and Faraj 2000). Altruisticpeople would like to share their knowledge with othersvia EKR (Kankanhalli et al. 2005a). They also perceivehigher satisfaction, and such satisfaction is stemmingfrom their intrinsic enjoyment in helping others (Krebs1975, Smith 1981, Constant et al. 1996, Ba et al. 2001).According to Bock et al. (2008, p.542), ‘intrinsicallymotivated people may be able to locate better knowl-edge than others, and thus may perceive output qualityas higher’. In contrast, an individual who is notintrinsically motivated to help others will only useEKR for their own purposes, and hence, the overallsystem will be perceived less useful by such person(Bock et al. 2008).
A higher intrinsic motivation will lead to anincreased willingness to spend much more time andenergy (Deci 1975, Deci and Ryan 1985), facilitatingthe perception about the perceived ease of use.According to Hsu and Lin (2008, p. 66), ‘people withhigher altruism are willing to enhance the welfare ofothers’. Most of the time, R&D is a collective action,requiring the collaboration of many individuals. If anindividual has higher altruism due to his or her passionand enjoying in helping others by sharing knowledgevia EKR, he or she will be able to expend the effortneeded to overcome any difficulty while using theEKR. Thus, the EKR will become much easier to use.Thus, we hypothesise:
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H11. Altruism will have a positive effect onperceived usefulness of the EKR.H12. Altruism will have a positive effect onperceived ease of use of the EKR.
In order to test the proposed hypotheses, our dataanalysis was conducted using SPSS 12.0 and AMOS5.0. The data analysis consisted of two parts, the firstof which tested internal consistency reliability, con-vergent validity and discriminant validity of themeasurement model. The second used a structuralmodel to investigate the path coefficients (the strengthsof the relationship between independent and depen-dent variables) and the R2 value (the amount ofvariance explained by independent variables).
4. Research method
4.1. Measures
There were six constructs in the research model, andthe items which were used to measure each constructwere developed based on previous studies whereverpossible. All items were measured by a five-pointLikert scale (ranging from 1 ¼ strongly disagree to5 ¼ strongly agree). There are six items for perceivedusefulness according to TAM, developed by Daviset al. (1989), and it is defined as the degree to which aperson believes that an EKR can enhance his or herwork performance. Six items for ease of use are alsoadopted from Davis et al. (1989), and it is defined asthe degree to which a person believes that using anEKR will be free of effort. Three items which measurereputation are modified from Wasko and Faraj (2005),and it is defined as the belief that sharing knowledgethrough the EKR will appear in the reputationmechanism and enhance the sharer’s reputation andstatus. Four items that measure reciprocity are derivedfrom Kankanhalli et al. (2005a) and focus on thebelief that current sharing through the EKR will leadto future requests for knowledge being met. Fouritems that measure altruism are taken from Kankan-halli et al. (2005a) and focus on the perception ofpleasure obtained by helping others by sharingknowledge through the EKR. Two items that measurebehavioural intention are adapted from Venkateshand Davis (2000), and this is defined as the strength ofintention to use an EKR for knowledge-sharing. Acomplete list of questionnaire items can be found inAppendix 1.
To ensure the content validity, a pretest of thequestionnaire was performed and four professors andpractitioners reviewed it. Several minor modificationswere made to the questionnaire in the wording anditem sequence. Furthermore, we conducted a pilotstudy from 16 users. Some minor errors were corrected
and small changes were made in the questionnaire as aresult of the pilot test.
4.2. Data collection
Empirical data were collected by conducting a surveyof R&D employees in Taiwan. In order to control thedifference of research results resulting from varioussystems, this study referred to the results of the votingobtained by the 10th MIS Best Choice held by theInstitute for Information Industry, Taiwan in 2005.1
This study focuses on R&D employees in companiesthat have used an EKR for a period of more than 3months. Nominated employees of 20 organisationsoperating in Taiwan were contacted by phone, thepurpose of the study was explained and they wereinvited to participate in the study and the administra-tion of the survey. The nominated person wasresponsible for distributing and collecting the ques-tionnaires within his or her organisation. Out of the 20organisations contacted, 10 organisations (covering 9industries) agreed to participate in the survey, andamong the 650 questionnaires distributed to theseorganisations, 231 responses were recycled, with aresponse rate of 36% (Table 3). Out of those 231responses, 6 were eliminated from the study, due tomissing data. The 225 usable responses resulted in anoverall usable response rate of 39%. Demographics ofthe sample are shown in Table 4.
5. Results
5.1. Reliability and validity
Internal consistency reliability (shown in Table 5)reflects the extent to which items of a constructmeasure various aspects of the same characteristic. It
Table 3. Profile of industries and organisations.
Industry(No. of company)
No. ofrelease
No. ofresponse
Percent ofresponse
Bio-tech pharmaceuticaland chemical industry (1)
100 40 17.8
Electro-optical industry (1) 50 25 11.1General commodity,manufacturing anddistribution industry (1)
50 20 8.9
Machinery and automobileindustry (2)
150 47 20.9
Telecommunicationindustry (1)
50 27 12
Electronic and electricalindustry (1)
50 18 8
Steel-related industry (1) 50 16 7.1Petrol chemical industry (1) 50 14 6.2Semi-conductor industry (1) 100 18 8Total 650 225 100
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was assessed by computing Cronbach’s alpha, in whichthe coefficients for six constructs are obtained, rangingfrom 0.817 to 0.957, revealing an adequate level of
reliability (40.7) for each construct, as suggested byNunnally (1978).
A confirmatory factor analysis was conducted withrelated data in order to acquire evidence of convergentand discriminant validity. Convergent validity isdemonstrated when item loading exceeded the accep-table value of 0.5 recommended by Hair et al. (2006)on their corresponding constructs, and average var-iance extracted (AVE) of the construct is larger than0.5, exceeding the threshold value suggested by Fornelland Larcker (1981). A principal components analysiswith a varimax rotation was conducted and Table 5illustrates that all of the factors exceeded the thresholdvalue of 0.5, and the AVE for all constructs exceededthe threshold value of 0.5. Discriminant validity isdemonstrated when the square root of the AVE fromthe construct is greater than the inter-constructcorrelations, as suggested by Fornell and Larcker(1981). Table 6 shows the square root of AVE valuesand inter-correlations among the variables.
5.2. Model fitness
To assess structural model fit, the results show thatnormed x2 (the ratio between x2 and the degree offreedom) was 1.56 (x2 ¼ 396.6, df ¼ 255), which issmaller than the recommended value of 3 suggested byHair et al. (2006). The goodness-of-fit index (GFI) is0.88, which exceeds the recommended cutoff value of 0.8
Table 4. Demographic information.
Measure Items Frequency Percent
Gender Male 153 68Female 72 32
Age 21–30 70 3131–40 101 4541–50 40 1851–60 12 560þ 2 1
Workexperience(in years)
0–1 10 42–3 35 164–5 32 146–7 31 148þ 117 52
Education High school 12 6College (2 years) 28 12University(4 years)
88 39
Graduate degree 97 43Position Researcher 13 6
Engineer 178 79Chief of section/team
9 4
Chief of division 19 8Departmentmanager/vicemanager
6 3
Table 5. Factor loadings and internal consistency reliability.
Construct Item Factor loading Cronbach’s alpha AVE
Reputation REPU1 0.780 0.890 0.736REPU2 0.765REPU3 0.800
Reciprocity RECP1 0.705 0.817 0.530RECP2 0.794RECP3 0.723RECP4 0.621
Altruism ALTR1 0.853 0.949 0.823ALTR2 0.858ALTR3 0.848ALTR4 0.842
Perceived usefulness PU1 0.753 0.932 0.701PU2 0.772PU3 0.824PU4 0.830PU5 0.780PU6 0.761
Perceived ease of use PEOU1 0.781 0.915 0.647PEOU2 0.696PEOU3 0.776PEOU4 0.660PEOU5 0.809PEOU6 0.841
EKR usage intention forknowledge-sharing
BI1 0.840 0.957 0.917BI2 0.857
Note: See Appendix 1 for abbreviations used in Tables 5, 8 and 9.
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Table 6. Descriptive statistics and discriminant validity.
Mean SD 1 2 3 4 5 6
Reputation 3.54 0.76 0.86Reciprocity 3.66 0.66 0.50a 0.73Altruism 4.00 0.78 0.49a 0.52a 0.91Perceived usefulness 3.42 0.65 0.61a 0.50a 0.45a 0.84Perceived ease of use 3.55 0.65 0.48a 0.54a 0.50a 0.54a 0.80Usage intention 3.96 0.75 0.46a 0.44a 0.49a 0.50a 0.49a 0.96
aCorrelation is significant at the 0.01 level (two-tailed)
Note: The diagonals represent the square roots of the AVE, these values should exceed the inter-construct correlations.
Table 7. Goodness of fit of the structural model.
Fit indicators Results Recommended value Suggested by authors
Chi-square/d.f. 1.56 53 Hair et al. 2006GFI 0.88 40.8 Browne and Cudeck 1993AGFI 0.85 40.8 Browne and Cudeck 1993RMSEA 0.05 50.08 Hair et al. 2006RMSR 0.03 50.08 Hair et al. 2006NFI 0.92 40.9 Hair et al. 2006CFI 0.97 40.9 Hair et al. 2006
Figure 2. Result of the proposed research model.
suggested by Browne and Cudeck (1993). The adjustedGFI (AGFI) is 0.85, which exceeds the recommendedcutoff value of 0.8 suggested by Browne and Cudeck(1993). The root-mean-square error of approximation(RMSEA) is 0.05, which is below the cutoff value of0.08 suggested by Hair et al. (2006). The root-mean-square residual (RMSR) is 0.03, which is below thecutoff value of 0.08 suggested by Hair et al. (2006). Thenormed fit index (NFI) is 0.92, which is greater than therecommended value of 0.9 suggested by Hair et al.(2006). The comparative fit index (CFI) is 0.97, which isgreater than the recommended value of 0.9 suggested byHair et al. (2006). All of the model-fit indices of thestructural model exceeded their respective commonacceptance levels (see Table 7).
5.3. Hypothesis testing
The data support the proposed model and 9 of the 12hypotheses. Figure 2 illustrates the path coefficientsand their significance in the structural model. Support-ing H1, ease of use has a positive effect on the EKRusage intention for knowledge-sharing (b ¼ 0.19,p 5 0.05). Supporting H2, usefulness has a significanteffect on the EKR usage intention for knowledge-sharing (b ¼ 0.17, p 5 0.05). Supporting H3, ease ofuse has a significant effect on usefulness (b ¼ 0.23,p 5 0.05). Inconsistent with H4, extrinsic reputationhas no significant effect on the EKR usage intentionfor knowledge-sharing (b ¼ 0.11, p ¼ 0.20). Support-ing H5, extrinsic reputation has a significant effecton usefulness of the EKR (b ¼ 0.45, p ¼ 0.00).
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Supporting H6, extrinsic reputation has a significanteffect on ease of use (b ¼ 0.19, p 5 0.05). Inconsistentwith H7, extrinsic reciprocity has no significant effecton the EKR usage intention for knowledge-sharing(b ¼ 0.11, p ¼ 0.24). Supporting H8, extrinsic recipro-city has a significant effect on usefulness (b ¼ 0.16,p 5 0.1). Supporting H9, extrinsic reciprocity has asignificant effect on ease of use (b ¼ 0.36, p ¼ 0.00).Supporting H10, intrinsic altruism has a significanteffect on the EKR usage intention for knowledge-sharing (b ¼ 0.20, p 5 0.05). Inconsistent with H11,intrinsic altruism has no significant effect on usefulness(b ¼ 0.02, p ¼ 0.78). Supporting H12, intrinsic altru-ism has a significant effect on ease of use (b ¼ 0.24,p 5 0.05). Table 8 provides the results of thesehypotheses tests.
The structural model explains 53% of the variancein usefulness, 44% of the variance in ease of use, and40% of the variance in behavioural intention. Accord-ing to the path coefficients, ease of use, except forshowing a slightly stronger direct effect than usefulnesson intentions, exhibited a stronger total effect onintentions. The total effect of perceived ease of use onintentions was 0.23. Intrinsic altruism emerged as thecentral aspect of the EKR for knowledge-sharing,since it has both direct effects on intended use, andindirect effects through perceived ease of use. The totaleffect of intrinsic altruism on intentions was 0.26.Table 9 summarises the significant direct/indirect
effects between variables in the proposed researchmodel.
6. Discussion
The goal of this study was to attempt to understandhow knowledge-sharing motivations affect the accep-tance of EKR. Specifically, we argued that knowledge-sharing motivations can indirectly affect EKR usageintentions for knowledge-sharing by developing per-ceived usefulness and ease of use.
The results of the empirical analysis provide anumber of interesting insights. Reputation and reci-procity were found to be two important antecedents toperceived usefulness and perceived ease of use; altru-ism was also found to be an important antecedent toperceived ease of use. Reputation was the mostinfluential factor to perceived usefulness and anotherinfluential factor to perceived usefulness was recipro-city. In addition, three knowledge-sharing motivationsthat can significantly affect perceived ease of use werelisted as reciprocity, altruism and reputation, accord-ing to their relative importance. Altruism played animportant role in explaining EKR usage intentions forknowledge-sharing both directly and indirectly. Theresults were consistent with the propositions of TAM.This study contributes theoretically and empirically tothe body of EKR usage research and has practicalimplications for R&D employees.
Table 9. The direct, indirect, and total effect on behavioural intention.
Direct effect Indirect effect Total effect
PU PEOU BI PU PEOU BI PU PEOU BI
REPU 0.45 0.19 0.11 0.04 0.12 0.49 0.19 0.23RECP 0.16 0.36 0.11 0.08 0.11 0.24 0.36 0.22ALTR 0.02 0.24 0.20 0.06 0.06 0.08 0.24 0.26PU 0.17 0.17PEOU 0.23 0.19 0.04 0.23 0.23
Table 8. Results of hypotheses tests.
Hypothesis Effects Standardised coefficient t-value p-value Supported
H1 PEOU!BI 0.187 2.265 0.024 YesH2 PU!BI 0.172 1.967 0.049 YesH3 PEOU!PU 0.226 2.969 0.003 YesH4 REPU!BI 0.113 1.279 0.201 NoH5 REPU!PU 0.452 5.659 0.000 YesH6 REPU!PEOU 0.186 2.393 0.017 YesH7 RECP!BI 0.112 1.171 0.242 NoH8 RECP!PU 0.159 1.774 0.076 MarginalH9 RECP!PEOU 0.361 3.783 0.000 YesH10 ALTR!BI 0.204 2.738 0.006 YesH11 ALTR!PU 0.020 0.281 0.779 NoH12 ALTR!PEOU 0.237 3.080 0.002 Yes
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6.1. Influence of extrinsic reputation
Extrinsic reputation was shown to be an importantinfluential factor to perceived usefulness and perceivedease of use. However, contrary to expectations, theresults indicate that extrinsic reputation does notdirectly affect behavioural intention to use EKR forknowledge-sharing, but it directly affects both per-ceived usefulness and ease of use. Reputation as usedin this study means ‘reputation mechanism in anEKR’, which represents knowledge-sharing perfor-mance, such as ranking. The results of this studyindicate that there is no intention to use the EKR forknowledge-sharing, even if an extrinsic reputationexists, unless such a system can facilitate R&Demployees’ work and is easy to use. We infer that,due to the reputation of expertise, it can be establishedthrough various methods (e.g. speech in a routinemeeting) and does not need to be established via EKR.However, if an EKR with a well-designed reputationmechanism can convince employees to perceive it asbeing more useful and easier to use, this will contributeto higher usage intention.
6.2. Influence of extrinsic reciprocity
Extrinsic reciprocity was shown to be an importantinfluential factor to perceived usefulness and perceivedease of use. However, contrary to expectations, theresults indicate that extrinsic reciprocity does notdirectly affect behavioural intention to use EKR forknowledge-sharing, but it directly affects both per-ceived usefulness and perceived ease of use. In terms ofreciprocity and knowledge-sharing, the result wasequivocal, and some prior research (Wasko and Faraj2000, Kankanhalli et al. 2005a) suggest a positiverelationship, but different results were found by others(Wasko and Faraj 2005, Hsu and Lin 2008). We inferthat a probable explanation of this may lie in theperceived uncertainty of knowledge quality, sinceknowledge quality is one of the critical factors forthe success of the KMS (Kulkarni et al. 2006). R&Demployees are asked to focus on completing theircurrent project on time. However, under rapidlychanging technical circumstances, while they are tryingto get help for the next project, the knowledgeprovided may be irrelevant or irrelative. Furtherresearch can extend this study to include more under-standing of the relationship between knowledge qualityand employees’ behavioural intentions. Another pos-sible explanation is that the EKR is a network-basedinteraction, which contrasts with a face-to-face setting.Face-to-face communication is helpful to achieve thegoal of dyadic reciprocity (Wasko and Faraj 2005).For instance, A first helps B and B assists A the next
time. The reciprocity of EKR is generalised reciprocity,which involves an exchange between closely relatedindividuals, with the contributor’s giving needing noimmediate return or conscious thought of return(Polanyi 1968). Thus, this could also be a reason forthe equivocation of reciprocity on the EKR usageintentions for sharing their knowledge. However, ourfindings also indicate that reciprocity can directly affectthe perceived ease of use and perceived usefulness.Therefore, an organisation should continue to build upa strong norm of reciprocity, so that employees willtrust that their knowledge-sharing efforts will bereciprocated. This will lead to employees expendingtheir efforts voluntarily, facilitating easier usage andperceiving more usefulness in their R&D tasks.
6.3. Influence of intrinsic altruism
Intrinsic altruism was shown to be an importantinfluential factor to perceived ease of use. Also, therelationship between intrinsic altruism and intention touse the EKR for knowledge-sharing is significant.Perhaps intrinsic altruism motivation could be theexplanation of why people share their time andknowledge with others freely. This seems to supportand explain the success of Amazon.com book commen-taries, the content contribution in Wikipedia andopinions expressed in weblogs, forums, etc. Altruismis one of the primary dimensions of organisationalcitizenship behaviour (OCB), and the organisationalculture of OCB can encourage employees to enhancethe well-being of their co-workers and also to be morewilling to share their knowledge (Lin 2008). When anemployee exhibits intrinsic altruism, he or she willshare knowledge voluntarily, be willing to create apositive mood and want to spend more time andenergy, thus facilitating the perceptions of ease of use.
6.4. Influence of TAM constructs
The results were consistent with the propositions ofTAM. As expected, both the perceived usefulness andperceived ease of use would significantly affect theintention to use the EKR to share knowledge. Again,perceived ease of use could significantly impact theperceived usefulness of the EKR. As hypothesised,when an easier system is being used, it becomes moreuseful. All of these three findings are consistent withprevious TAM-related studies, highlighting the ease ofuse and usefulness as the two main determinants ofuser acceptance of a new technology. Thus, it isessential to design a smooth system interface whereR&D employees may choose the EKR in knowledge-sharing. On the other hand, the EKR must providerich knowledge and combine knowledge retrieval tools,
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thereby leading to perceived usefulness in facilitatingtasks.
7. Implications
7.1. Implications for theory
Prior research (Kankanhalli et al. 2005a) has wellshown the direct effects of knowledge-sharing motiva-tions on EKR usage for knowledge-sharing. In thisstudy, by adding perceived usefulness and perceivedease of use as the mediators, we have demonstrated aclear understanding of how knowledge-sharing moti-vations may affect their acceptance of the EKR.
This study makes several important contributionsto the research literature. First, based on the evidencefrom the literature, the effect of knowledge-sharingmotivations on knowledge-sharing is still controver-sial. We compared our findings with the four recentlypublished studies on knowledge-sharing (see Table 10).By incorporating TAM with knowledge-sharing moti-vations, this study finds that perceived usefulness is akey intervening variable linking the antecedent vari-ables, namely reputation and reciprocity, with usageintentions for knowledge-sharing. The results alsoindicate that perceived ease of use is a key interveningvariable linking the antecedent variables, namelyreputation, reciprocity and altruism, with usage inten-tions for knowledge-sharing. Karahanna and Straub(1999) investigate how and why perceived ease of useand perceived usefulness develop. In their study,integrated social presence theory, social influencetheory, and Triandis’ modifications to the theory ofreasoned actions, the causal relationships between theproposed antecedents and perceived usefulness andperceived ease of use are examined. Our study offers amotivational perspective by proposing knowledge-sharing motivations as original antecedents for theconstructs of usefulness and ease of use on the EKR.
Second, we contribute to EKR research by reveal-ing the influences of knowledge-sharing motivations onthe acceptance of the EKR. In particular, based onSET, we propose the existence of three motivations,namely reputation, reciprocity and altruism. These arealso theorised by Davenport and Prusak (1998), asexisting in the knowledge market. We believe that thelinks between TAM and users’ sharing motivationsneed to be further elaborated. In particular, investiga-tion of other sharing motivations has been omitted.Further studies are also required to examine whetheror not other knowledge-sharing motivators (e.g.knowledge growth, knowledge self-efficacy, and re-wards) would influence TAM. Prior research adopts adivision of intrinsic and extrinsic motivations for usewhich correspond to psychology and economics(Osterloh and Frey 2000). Monetary reward has been
omitted because most of the R&D departments in thisstudy did not use money to encourage knowledge-sharing, since employees of an R&D department arerequired to share knowledge to create a commonunderstanding of the problems at hand (Hong et al.2001, Berends et al. 2006). However, the result showsthat reputation is not a significant extrinsic motivationfor the intention to use the EKR to share knowledge,thus we suggest that future research should exploretangible economic incentives (e.g., salary, bonus,promotion), and should also examine whether or notthe usage behaviour relates to direct economicincentives and if so, how.
Third, in previous studies of TAM, perceivedusefulness was a comparatively strong determinant ofusage intentions, such as mobile commerce acceptance(Wu and Wang 2005), on-line learning acceptance(Saade and Bahli 2005) and electronic tax filingacceptance (Fu et al. 2006). However, the results inthis study indicate that R&D employees use the EKRmainly because they perceive that it is easy to use andsecondarily, because it is more useful for their R&Dtasks. This result is consistent with prior research (Laiet al. 2008), where ease of use has stronger significanteffects than that of perceived usefulness with KMS.This study suggests that all researchers, practitioners,and policy makers should emphasise a user-friendlyEKR interface in order to facilitate the usage of theEKR in knowledge-sharing, so that people will sharetheir knowledge easily. In addition, according to Wuand Wang (2005), mature innovation technology hasdecreased user interface problems because users nowhave the necessary skill and confidence. Thus, as usersgain familiarity over time, the effect of ease of use willreduce (Chau 1996). Further research is also needed toexamine the implementation time of the EKR.
Fourth, knowledge-sharing and knowledge-seekingare two distinct types of behaviours (He and Wei2009). We argue that, in order to further understandthe behavioural intention to use the EKR, futureresearch could investigate employees’ knowledge-seek-ing motivations on their acceptance of the EKR forknowledge-seeking.
7.2. Implications for practice
This study also makes several important contributionsto practice. First, the findings demonstrate thatextrinsic reputation, extrinsic reciprocity and intrinsicaltruism are three antecedents to the perceived ease ofuse. Therefore, before the implementation of the EKR,organisations should establish the culture of knowl-edge-sharing in advance, in order to arouse altruismand reciprocity. Those who believe in reciprocityexpect that they will receive other people’s favour in
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Table
10.
Acomparisonwithfourpriorstudies.
KMS
Sample
Dependent
variable
Reputation
Reciprocity
Altruism/enjoyment
inhelpingothers
HeandWei
(2009)
Electronic
knowledge
repository
161responsesansw
ered
the
questionnaireregarding
knowledge-contribution
behaviourand201answ
ered
regardingknowledge-seeking
behaviour.Thesample
isfrom
aninternationalIT
companyin
China
Contributionbeliefs
Insignificant
Insignificant
Significant
Kankanhalli
etal.(2005a)
Electronic
knowledge
repository
150respondents
from
10
organisationsin
Singapore
EKR
usageby
knowledge
contributors
N/A
N/A
Significant
Waskoand
Faraj(2005)
Electronic
network
of
practice
173responsesfrom
anational
legalprofessionalassociation
inUS
Helpfulnessof
contribution
Significant
Insignificant
Significant(p50.1)
Volumeof
contribution
Significant
Significant
Insignificant
Bock
etal.
(2005)
NospecificKMS.
(Executives
enrolled
intheCKO
program
offer
byauniversity)
154responsesfrom
27
organisationsacross
16
industries
inKorea
Attitudetoward
knowledgesharing
N/A
Significant
N/A
Thisstudy
Electronic
knowledge
repository
231responsesfrom
10
organisationsacross
nine
industries
inTaiwan
Perceived
ease
ofuse
Significant
Significant
Significant
Perceived
usefulness
Significant
Significant
(p50.1)
Insignificant
Usageintentionfor
knowledgesharing
Insignificant
Insignificant
Significant
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the future, so they share knowledge for each other’sbenefits. We believe that the reciprocity motivation isimportant for continued knowledge-sharing. Knowl-edge altruism can be inspired, and a climate of altruismcould be encouraged, if organisations hire goodemployees and treat them well, whereas employeeswill be discouraged if the organisation imposes moreand more pressures on their energy and time (Daven-port and Prusak 1998). Additionally, designing anappropriate reputation mechanism for the EKR willhelp employees to form their expert identity. Undersuch circumstances, they can enhance their effort andself-confidence.
Second, the findings indicated extrinsic reputationas an antecedent to perceived usefulness. Whenacquiring extrinsic reputation, people are willing tobelieve that the EKR can enhance their task perfor-mance. Therefore, this will create an image of a ‘Personof Wisdom’ while a reputation mechanism is incorpo-rated into the system. For instance, Xerox companyhas designed a system of KMS-Eureka, when employ-ees logging onto the KMS, employees are able to easilyinput new solutions, or new problems, into Eureka byregistering their name on the system. Therefore, it isable to promote zealous behaviour for employees toprovide their knowledge. With implications for soft-ware vendors and system developers, users’ contribu-tion outcomes could be created in the development ofan EKR product. Reputation design incorporated intoEKR can lead employees who want to overcome thedifficulties of sharing knowledge and thus make themmore aware of the usefulness of the EKR. Our findingssuggest that it is essential to design a reputationmechanism into an EKR.
Third, the findings indicate that extrinsic recipro-city is another antecedent to perceived usefulness.When people anticipate a reciprocal relationship infuture cooperation, they tend to believe that the EKRcan enhance their task performance, because they willobtain a return after using the EKR. Reciprocity hasbeen highlighted as the most important benefit forindividuals in the knowledge exchange environment(Davenport and Prusak 1998). Our findings suggestthat organisations should establish the norm ofreciprocity, which is a common and powerful socialnorm, which dictates that we need to return favours tothose who have done something nice for us (Ellis andFisher 1994). Under this condition, the perceivedusefulness of the system can be enhanced, which isalso believed to improve task performance.
Fourth, our results show that perceived ease of use,perceived usefulness and intrinsic altruism are signifi-cant factors on the EKR usage intention for knowl-edge-sharing. Our results find that intrinsic altruism isthe most important factor in determining users’
intention to use the EKR for knowledge-sharing.Although altruism is innate, organisational cultureand friendly relationships among employees may alsoshape people’s willingness to contribute their knowl-edge. De Long and Fahey (2000) argue that cultureincludes three elements, values, norms and practices,and where values are manifested in norms, theyinfluence a specific practice. Therefore, it is importantthat the organisational culture enhances altruism anddrives people to willingly contribute their knowledgethrough the EKR. Perceived ease of use is anotherimportant factor in the EKR usage intention forknowledge-sharing. Thus, a successful EKR reliesupon the determination of how easy it is to use andhow accessible the knowledge is for people. Hence,while designing the EKR, it is essential to reduce thecomplexity of the interface in order to enable users tofind what they want conveniently and fast. For example,a knowledge map is a method that uses a simple, clearvisual presentation, which can help employees findquickly the knowledge they seek (Wexler 2001, Lai et al.2008). In addition, the implementation of the EKRmust be able to be easily combined with existingtechnology, and training must also be provided foremployees to facilitate the EKR usage.
8. Conclusion
This study incorporates a motivational perspective intothe acceptance of the EKR and examines extrinsic(reputation and reciprocity) and intrinsic (altruism)motivations as being key influences on perceivedusefulness, ease of use and EKR usage intention forknowledge-sharing. The purpose of this study is tounderstand how users’ intrinsic and extrinsic motiva-tions affect R&D employees’ acceptance of the EKRfor knowledge-sharing. A correct understanding ofintrinsic motivation is necessary to ensure appropriatemanagerial interventions and the formation of organi-sational culture. Another correct understanding ofextrinsic motivation is to ensure the balance betweenthe interface design and users’ needs.
There are three limitations to this study. First, thesubjects in this study are limited to R&D departmentsfrom 10 specific organisations in Taiwan. The culturaldifferences among organisations influence employees’perceptions regarding knowledge-sharing (Lin 2007).Therefore, we suggest that future research could beconducted in other organisations or other countries inorder to enhance the representativeness. Or perhaps,the research could only focus on the R&D departmentsof some specific industries, in order to gain a deeperunderstanding of that particular industry. Second,this study investigated behavioural intention only,and the behavioural intention used was measured by
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self-reporting, which is a type of subjective measure(Chau 1996). Except for subjective measures, it issuggested that future research should employ objectivemeasures (e.g. knowledge-sharing quality and quantityon the EKR usage). Finally, the R&D departmentsinvestigated in this study have all used EKR for at leastmore than 3 months. However, we have not investi-gated the time an individual has been using the EKR.Thus, there is a possibility that it may contain somebias, due to the learning-curve effects of novice users.
Note
1. The eLand Technologies was at the top position in thecategory of ‘KM’ in Taiwan.
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Appendix 1. Survey instrument
Reputation
REPU1 From the reputationmechanism of EKR, Ican earn respect from othersby participating in the EKR.
REPU2 From the reputationmechanism of EKR, Ifeel that participationimproves my status inthe profession.
REPU3 From the reputationmechanism of EKR, Iimprove my reputation in theprofession.
Reciprocity
RECP1 When I share myknowledge through EKR, Ibelieve that I will get ananswer for giving an answer.
RECP2 When I share myknowledge through EKR,I expect somebody torespond when I’m in need.
RECP3 When I contributeknowledge to EKR, Iexpect to get backknowledge when I need it.
RECP4 When I share myknowledge through EKR, Ibelieve that my queries forknowledge will be answered infuture.
Altruism
ALTR1 I enjoy sharing myknowledge with othersthrough EKR.
ALTR2 I enjoy helping others bysharing my knowledgethrough EKR.
ALTR3 It feels good to help someoneelse by sharing my knowledgethrough EKR.
ALTR4 Sharing my knowledge withothers through EKR gives mepleasure.
Perceived usefulness
PU1 Using an EKR in my jobwould enable me toaccomplish tasks morequickly.
PU2 Using an EKR wouldimprove my job performance.
PU3 Using an EKR in my jobwould increase myproductivity.
PU4 Using an EKR wouldenhance my effectiveness onthe job.
PU5 Using an EKR would make iteasier for me to do my job.
PU6 I would find an EKR useful inmy job.
Perceived ease of use
PEOU1 Learning to operate an EKRwould be easy for me.
PEOU2 I would find it easy to get anEKR to do what I want it todo.
PEOU3 My interaction with an EKRwould be clear andunderstandable.
PEOU4 I would find an EKR to beflexible to interact with.
PEOU5 It would be easy for me tobecome skillful at using anEKR.
PEOU6 I would find an EKR easy touse.
Behaviour intention
BI1 I intend to use EKR forknowledge-sharing shortly.
BI2 I predict that I will reuse EKRfor knowledge-sharing in theshort term.
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