An Exploration of Personal Factors Influencing Disposition towards Knowledge Sharing in a South African Context

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1、An Exploration of Personal Factors Influencing Disposition towards Knowledge Sharing in a South African Context.Valentine Brink & Jean-Paul Van BelleDepartment of Information Systems, University of Cape TownSummaryThe aim of this research was to develop an understanding of the personal factors influ

2、encing an individuals attitude towards knowledge sharing behaviour in the context of South African larger organisations. The following personal factors were considered: gender, age, experience, education and level within organization. This research objective was explored using an empirical survey. F

3、rom our survey, we found that, although knowledge sharing is perceived to be the most essential process for knowledge management, only one factor, i.e. the age of respondent, was shown to be statistically significant in affecting an individuals attitude towards sharing knowledge. Moreover, the assoc

4、iation was not a linear one. However, the lack of the influence of various specific personal factors on knowledge sharing attitude can be construed as positive. It suggests that there is no discernable deterministic individual barrier against knowledge sharing attitudes based on gender, experience o

5、r education and gives hope to organisations willing to pursue a knowledge management adoption process.IntroductionAs the 21st century unfolds, knowledge has become the most important product in most organisations. Employers are hiring minds, not hands, and knowledge is seen as a company asset. Globa

6、lisation, information technology, communications systems and the exponential growth of knowledge all contribute to an increasingly complex environment in which information is abundant and volatile. To keep pace with the environment, business managers must learn as quickly as it changes. To be more c

7、ompetitive within a given industry, they need to access the necessary knowledge in more efficient ways than others do (Bourdreau & Couillard, 1999). According to Tiwana (2000), survival depends on the best possible response to a multitude of challenges. Managing knowledge means adding or creating va

8、lue by actively leveraging know-how, judgment, intuition and experience within and outside the company. Consequently, organisations are seeking to create systematic ways to identify and convert individual expertise, skills and experience into organisational knowledge. The strategic management of kno

9、wledge resources is regarded as one of the key factors for sustainable competitive advantage. A survey of 423 organisations in the UK, mainland Europe and the USA conducted by KPMG Consulting (1999), showed that 81% of respondents had undertaken, or were considering implementing a knowledge manageme

10、nt programme.What is knowledge management? Kanter (1999) states that knowledge management can be viewed as turning data (raw material) into information (finished goods) and from there into knowledge (actionable finished goods). The implication is that managing knowledge gives one the power to act, t

11、o make decisions that are value producing to the individual and to the company as a whole. According to Wiig (1999) the “the goal of Knowledge Management is to build and exploit intellectual capital effectively and gainfully.” Bock & Kim (2002, 14) and Tiwana (2000, 4) agree that the management of o

12、rganisational knowledge can be extended to creating business value and sustainable competitive advantage.Leveraging knowledge is possible only when people value building on each others ideas and sharing their own insights. Bock & Kim (2002, 14) and Mayo (2001, 36) emphasise that, in particular, know

13、ledge sharing is perceived to be the most essential process for knowledge management.In trying to answer the question whether the organisation is ready to become a knowledge organisation (Stevens, 2000), it should be acknowledged that this knowledge management readiness is shaped by the culture of t

14、he organisation (McDermott, 1999). However, knowledge sharing is perceived to be the most essential process for knowledge management. In a survey of 260 CEOs and directors in European multinational organisations conducted by the Financial Times in 1999, 94% of respondents answered that people should

15、 share what they know with others in the organisation (Bock & Kim, 2002, 14). However, Davenport (1998) argues that sharing of knowledge is often an unnatural act. People will not share their knowledge as they think their knowledge is important and valuable to them. A 1997 survey by the Ernst & Youn

16、g Centre for Business Innovation, cited by Ruggles (1999, 86), showed that the biggest difficulty in managing knowledge was changing peoples behaviour. Therefore, organisations need to examine peoples attitudes towards and habits concerning knowledge sharing in the company and learn with whom the em

17、ployees collaborate, how they get the information they need, whether and when they document their own knowledge and how they store and distribute knowledge. Hence, the aim of this research is to develop an understanding of the personal factors influencing an individuals attitude towards knowledge sh

18、aring behaviour in an organisational context.Factors Influencing Knowledge SharingPersonal factors influencing knowledge sharingSharing knowledge is an unnatural act. People question why they have to share knowledge as this is a valuable resource, and sharing it may put their jobs at risk if other p

19、eople use their knowledge. Therefore the natural tendency is to hoard knowledge (Davenport, 1998; Probst et al., 2000, 193; Tiwana, 2000, 37). According to Harris (1998), employees perform their work and advance their careers by keeping their knowledge to themselves for their own benefit, rather tha

20、n sharing it with others. Knowledge management demands a shift to a culture where collaboration, knowledge sharing and team achievement are valued equally with competition and individual achievement. Frick (1998) further states that the key to a successful knowledge management implementation is the

21、shift to a belief that knowledge sharing is power.Education and trainingAccording to Mayo (2001, 27) visionary companies, with an average lifespan of nearly 100 years, demonstrate a continuing focus on intellectual capital by focusing on employee development. Sveiby (1997, 169) argues that in knowle

22、dge companies, which depend heavily on the knowledge and competence of their employees, competence development ought to be an item in which the company invests heavily, and it usually does. Sveiby (1997, 168) also found that the educational level of the professionals employed affects the assessment

23、of their competence and thus the companys ability to achieve future success. Probst et al. (2000, 175) emphasise that it is important to keep employees competencies at a constant high level, especially in dynamic, knowledge-intensive industries.Experience and skillsAccording to Davenport & Prusak (1

24、998, 7), Mayo (2001, 36) and Tiwana (2000, 68), knowledge is largely derived from experience, which leads to sound judgement and wisdom the knowledge that is used in making future decisions. Being able to transfer knowledge implies that experiential knowledge also gets transferred to the recipient.

25、The benefit of experience lies in the fact that it provides a historical perspective that helps people better understand present situations. Experienced people are usually valued in a company (and are often paid more) because they possess this historical perspective from which they can view current

26、situations something that a typical newcomer will almost never have.Attitudes, values and trustAttitudes are closely related to values, and are about how people view their world. They are shaped by education, by the environment and its demands, and by the culture to which people belong. Values and a

27、ttitudes shape many of the ways a person behaves. Values reflect a persons ethos about their work and their interaction with the people connected with it. They rarely change. Attitudes can change where people see that it is necessary (Mayo, 2001, 104).Probst et al. (2000, vii) suggest that the easie

28、st way to approach the subject of knowledge management is for individuals to make themselves aware of how they deal with their own knowledge and emphasise that an atmosphere of trust is essential for the sharing of knowledge, but add that it is difficult to create.Organisational factors influencing

29、knowledge sharingSize and structureOrganisations need to know what they know and use that knowledge effectively. Size and geographic dispersion can make it difficult to locate existing knowledge and get it to where it is needed. In small-localised organisations, a manager probably knows who has expe

30、rience in a particular aspect of the business, and can walk across the passage and talk to him or her. Alternatively, managers in large organisations know how common it is to reinvent the wheel, solving the same problem from scratch, duplicating effort because knowledge already developed has not bee

31、n shared within the company (Davenport & Prusak, 1998, 17).According to Bourdreau & Couillard (1999), traditional top-down hierarchies are not conducive to the development of knowledge organisations. They typically discourage individual thinking, creativity and initiative. New organisational structu

32、res designed around teamwork, self-managed teams, and overlapping responsibilities facilitate knowledge sharing and development. However, Stewart (1997, 130) warns against these new organisational structures creating their own difficulties, where the non-management of intellectual capital could lead

33、 to over-investing in knowledge. Passion for the value of intellectual capital should not come at the expense of a basic principle of management, i.e. using assets more efficiently. Organisational CultureOrganisational culture refers to the shared values and attitudes of the members of an organisati

34、on (Jarvenpaa & Staples, 2001, 156). Every organisation and subgroup within it has developed it own culture, which is not easily changed. This can be a significant barrier to any aspirations, blocking vital change (Gold et al., 2001, 189; Mayo, 2001, 159; Schein, 1992, 5; Shields, 1999).Harris (1998

35、) reports that cultural changes require 50 % to 70 % of the overall knowledge management implementation effort, and failure to change culture accounts for at least 50% of knowledge management failures. Similar arguments were given by Kluge et al. (2001, 25) and Tiwana (2000, 94).LeadershipSchein (19

36、92, 15) points out that culture and leadership are two sides of the same coin in that leaders create initial cultures when they first create groups and organisations. If an organisation has strong values, leaders will be expected to be role models for those values. In many organisations the chief ex

37、ecutive has a pivotal role as the final decision-maker and as a model of behaviour. Davenport et al. (1998, 55) found that executives who championed knowledge initiatives were usually themselves well read and well educated; they set the tone for a knowledge-oriented culture. However, in organisation

38、s and cultures where hierarchy has less influence, collective leadership and decision-making are common (Mayo, 2001, 161).Theoretical Framework.As the underlying theoretical model to determine personal influences affecting knowledge sharing attitudes, it is proposed that the Theory of Reasoned Actio

39、n (TRA) be used. Davis, Bagozzi and Warshaw, cited by Bock & Kim (2002, 15), state that a particularly useful aspect of the Theory of Reasoned Action is that it assumes all other factors influence behaviour only indirectly, by influencing attitude. Because it has this explanatory power, the Theory o

40、f Reasoned Action can be a useful model for explaining knowledge sharing behaviour in organisations. The Theory of Reasoned Action is a widely accepted model in social psychology, used to explain virtually any human behaviour (see Figure 1). According to this theory, a persons performance of a speci

41、fic behaviour is determined by his or her behavioural intention (I) to perform the behaviour (B = f (I). Next, the intention is jointly determined by the persons attitude (A) and subjective norm (SN) concerning the behaviour in question, with relative weights typically estimated by the regression co

42、efficients (I = Aw1 + SNw2). And then, a persons attitude toward a behaviour is determined by his or her salient beliefs (bi) about the consequences of performing the behaviour, multiplied by the evaluation (ei) of those consequences (A= Sbiei). Figure 1: Theory of Reasoned ActionSource: Adapted fro

43、m Bock & Kim (2002, 15)Finally, an individuals subjective norm (SN) is determined by a multiplicative function of his or her normative beliefs (nbi) and motivation to comply (mci) (SN = Snbimci) (Bock & Kim, 2002, 15).Research Hypothesis and Methodology.The objective of this research is to explore t

44、he personal factors influencing attitudes towards knowledge sharing. The purpose of this study is explanatory. The following main hypothesis can be formulated:H1: There is a relationship between personal factors and an individuals attitude towards knowledge sharing.Various sub-hypothesis can be stat

45、ed by substituting the generic “personal factors” with specific factors under consideration, namely: Gender, Age, Education, Experience and Level within organisation.The research strategy will adopt a quantitative survey-based approach to test the corresponding null-hypotheses. The survey was admini

46、stered to participants via e-mail and hand delivery. The companies chosen had implemented, or were in the process of implementing, knowledge management programmes. The purpose of this study is explanatory as it seeks to establish whether attitude towards knowledge sharing is determined by such varia

47、bles as gender, age, education, experience and level within organisation. Survey InstrumentThe questionnaire administered was developed by Bock & Kim (2002). Items to measure attitude towards knowledge sharing were modified by Bock and Kim from Fishbein and Ajzens works, to make them relevant to the

48、 knowledge sharing context. As described in Bock & Kim (2002), before conducting the main survey, a pre-test was performed to test internal consistency and discriminant validity of the measurement instrument. The main survey was conducted in four large public organisations in Korea. The instrument m

49、easures respondents attitude towards knowledge sharing. Attitude towards knowledge sharing was defined as the degree of ones positive feelings about sharing ones knowledge. Variables were measured on a Likert-scale ranging from1 (very rarely) through 5 (very frequently). The questionnaire captured a

50、 maximum of 65 data items from each respondent.PilotDue to the questionnaire having been previously administered in Korea, the direct translation by Bock and Kim caused problems with the semantics of some questions. We modified some questions so as not to lose their original intent. The questionnair

51、e was piloted on 12 employees in the insurance sector. Respondents were given the opportunity to make comments about specific questions and about the questionnaire in general.Sampling designA random sample of six large South African companies across different market sectors was chosen, all of which

52、had implemented or, were in the process of implementing, knowledge management programmes. The various sectors included Insurance, Professional Consulting, Banking and Information Technology (IT) Infrastructure (see Figure 2). Data collectionEach of the selected companies was initially contacted tele

53、phonically, and subsequent communication was via e-mail. The contact person was usually an individual responsible for a particular companys knowledge management programme. In all cases approval was required from the companys executive management before the distribution of questionnaires throughout t

54、he organisation. All participants executive managements requested confidentiality and anonymity as requirements for participating in the survey and in the reporting of findings.For the hand-delivered questionnaires correspondence was personalised, with 120 delivered to the insurance sector and 40 to

55、 the Information Technology infrastructure sector. From the insurance sector 110 (91.7%) questionnaires were returned, of which 94 (85.5%) were useable, and 28 (70.0%) was returned from the Information Technology infrastructure sector, of which 26 (92.9%) were useable. For questionnaires administere

56、d via e-mail repeated rounds of follow-ups were used to maintain participants interest. From the professional consulting sector 102 e-mail questionnaires were returned, of which 90 (88.2%) were useable, and 27 e-mail replies came from the banking sector, of which 21 (77.8%) were useable. In summary,

57、 from the initial six companies approached, four companies responded, one from each sector, with 267 questionnaires returned, of which 231 (86.5%) were useable. In order to preserve anonymity, the four companies have been labelled per sector and no inferences should be drawn about the sector assigne

58、d to a particular company (see Figure 2). Figure 2: Usable Responses by SectorData AnalysisTo test the empirical stated hypothesis, the numeric variables age and experience, captured in years, were transformed into categorical variables. The class intervals chosen allowed for even distribution acros

59、s the categories (see appendix). This permitted an analysis to be performed, namely using the Pearson chi-square test for the significance of association, which is more relevant to the objectives of the research. It must be acknowledged that there is significant correlation between age on the one ha

60、nd and experience and education on the other. These were investigated in detail but can not be reported on due to space constraints. The full findings are available on simple request from the authors.The main statistical test performed was the Pearson chi-square test. The main motivation for this is

61、 that it can deal with the type of categorical data which constitutes most of the sample. Furthermore, it is a robust, non-parametric test which does not assume anything about the distribution of any of the variables. In addition, it is able to detect non-linear dependencies. This is quite critical

62、to this research, as will be demonstrated with the variable “Age”. In addition, linear regression analysis and ANOVA was performed, though this is only reported on in the age analysis sub-section.Table 1: Frequency table for the construct attitude towards knowledge sharing.Frequency table: AttitudeD

63、escriptionFrequencyPercentageAttitude = 3 and Attitude = 3.5 and Attitude = 4High4218.2In order to perform chi-square analysis, a number of continuous variables had to be converted into categorical data. Although this process may introduce bias, it was found that the results were not particularly se

64、nsitive to the exact cut-off values used to group data. Table 1 above shows the 4 classes which were created for the “attitude” construct. Note that the “description” labels such as “low” and “high” should note be interpreted strictly: they are fairly arbitrary and very relative to the responses obt

65、ained. The use of these labels is purely intended to facilitate the reading of the statistical results and they should not be interpreted strictly.Attitude x GenderThe first personal factor to be investigated was the correlation between gender on attitude towards knowledge sharing.Table 2: Impact of Gender on Attitude.Attitude Gender: MaleGender: FemaleRow totalsLow171431Medium343165Medium High603393High241842