Description
Knowledge management (KM) comprises a range of strategies and practices used in an organisation to identify, create, represent, distribute, and enable adoption of insights and experiences
Scientific Papers (www.scientificpapers.org) Journal of Knowledge Management, Economics and Information Technology
Issue 6 October 2011
Analysis of Knowledge Management within Five Key Areas
Authors:
Alireza ANVARI, Gholam-Abbas ALIPOURIAN, Rohollah MOGHIMI, Leila BAKTASH, Department of Industrial Management, Gachsaran Branch, I.A.U., Gachsaran, Iran, [email protected]; [email protected]; [email protected]; [email protected]
Knowledge Management as a crucial factor impacts on organizational performance. It seems to be a lack of empirical studies that measure knowledge in high educational environments, especially in universities. The main purpose of this study was to identify and assess five pointers that contribute towards knowledge management in a university in Iran. The methodology involved both qualitative and quantitative research to evaluate knowledge management based on literature and personnel viewpoints in the university. Data from 101 participants were analyzed by using KruskalWallis, and Mann-Whitney test. The instrument used was a structured research questionnaire on knowledge management. The analysis showed that all five parameters had an effect on knowledge management. The results imply that the university is following a trend towards knowledge-orientation. Furthermore, there was a significant difference between two groups (lecturer and staff) perception. Its implication can also be beneficial to other universities that plan to highlight knowledgeoriented management. Keywords: Knowledge Management, Information Management, Evaluation Method, Five-Indicators
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Analysis of Knowledge Management Within Five Key Areas
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Introduction
A review of current business literature reveals that knowledge management (KM) has become a crucial factor in competitive environments. According to Bhatt [1], business and academic communities believe that the process of leveraging knowledge can provide an organization with long-term competitive advantages. Obviously, universities are no exception; they are centers for production and leveraging of knowledge. Islamic Azad University – Gachsaran Branch (IAU-G.B.), as a center of knowledge, wants to implement KM so that it can develop the potentialities and commitment of skilled employees through identifying methods for creating, recognizing, implementing, leveraging and distributing organizational knowledge. This would mean a KM emphasis on the creation, utilization and development of their collective intelligence [2]. This research initially focused on identifying assessment measures of KM and their strengths and weaknesses. This study then investigated the relationship between KM in the field of management and infrastructure of IAU-GB, its variables including the general management, the leadership style, strategic vision, internal processes, and human resources, as well as factors such as the type of the groups (lecturers and other staff), job levels, and gender (Figure 1). At the same time, the study aimed to clarify whether it is possible to provide strategies for making KM more effective. The research methodology used qualitative and quantitative methods. The aim of this research, using qualitative methods, was to address the following questions in a literature review: ? What measures are used to evaluate KM? ? What are the variables in KM evaluation? And, qualitative methods based on a case study addressed two questions: ? What is the level of KM from the perspective of employees? ? Are there any significant differences between the two groups (lecturer and staff)? The structure of the paper is as follows: Section 2 presents an outline of the literature review in the form of a table (Table 1) that lists the researchers of KM. moreover in this section, a general evaluation of KM and the categorization of their metrics and variables. The methodology and the case study are described in Section 3. Finally, Sections 2
Analysis of Knowledge Management Within Five Key Areas
Issue 6 October 2011
4 and 5 present a discussion, some concluding remarks and suggestions for universities regarding the implementation of KM.
Figure 1: A Conceptual Diagram of Five-Parameter Modeling of KM
A Review Study of Knowledge management
In recent years, researchers have focused on KM and have attempted to support organizational knowledge, such as: Sommerville and Dalziel [3], Goffee and Jones [4], Hwang [5], Albers and Brewer [6], Goh [7], Fernandez et al. [8], Gumus [9], Kayakutlu and Buyukozkan [10], Wen [11], and so on. Hence, KM has been categorized according to the authors’ different approaches (see Table 1).
Assessing Knowledge Management
According to the literature, there are nine perspectives for KM measurement (Table 2). Mostafa Jafari et al. [55] identified 33 measurement methods of knowledge and intellectual capital. They classified them into four groups: direct intellectual capital, score card, marketing cost methods, and return on assets. Khadivar et al. [74] classified the studied measurement methods into three approaches (from an area-based perspective): knowledge
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Analysis of Knowledge Management Within Five Key Areas
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measurement in products and processes, measurement of knowledge value in internal organization, and measurement of organizational conditions based on KM processes. Moreover, Chang and Wang [59] classified the measurement methods into seven approaches (from a factors-based perspective): employee traits, strategy factors, superintendent traits, audit and assessment, organizational culture, operating procedures, and information technology. In addition, Adli [76] proposed 4 key indicators (context, input, process and output indicators); Vlok [82] stated 14 dimensions in 3 processbased areas: background/structural factors, knowledge production and knowledge integration; and Wen [11] offered 5 criteria for KM: data, information, knowledge, wisdom, and Staff; and so on. As a result of the literature review of KM performance evaluation, we can classify some of these review findings into several perspectives (see Table 2). Table 1: Different Approaches to KM Resources [12- 36] [1, 37- 45] [1, 2, 23, 25, 26, 33 [29, 40, 61 -75] 59]
No 1 2 3 4
Issues
Study on theory and fundamentalsbetween KM Relationship and IT Competitive advantages of KM Categorization of KM
Knowledge Management in High Education
Knowledge systems are core elements of a manager’s requirements for organizing, controlling, participating, and combining systems of structures, processes, and people [35]. For this reason, many authors have studied the different facets of knowledge [33, 34, 36, 59, 83], but it seems that the creation and utilization of knowledge is the most important challenge. Universities are the main centers for producing and leveraging knowledge [56]. Through the use of KM, universities will be able to perform more effectively by spreading knowledge among cultures, and expanding the process of learning and teaching to overseas universities [53].
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Analysis of Knowledge Management Within Five Key Areas
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Therefore, we need to establish what KM is and organize it into categories so that we can gain a conceptual understanding, and prepare the appropriate context for the creation of software concepts. Due to the appearance of new knowledge producers in the education sector, more and more universities are looking into the possibility of applying corporate KM systems [2]. In this case, there are some factors which affect the success of KM in a university: leadership, the nature of academic other staff, evidence of the benefits, the taxonomy for the application of KM within the university, management structure, and the history of the university [83]. Hijazi and Kelly [42] claim that KM can help to solve problems between industry and a university, such as: align IT with social networks and dealings, encourage and support the use of KM, allow knowledge transfer across different tasks, apply knowledge to workers’ management and practice tacit knowledge within their surroundings. Abdullah et al. [81] proposed a framework for a KM system: psychological – motivation, awareness, reward, strategy; culture – truth, beliefs, value, experience; process – acquisition, store, disseminate, use; functionality – agent, email, video conferencing, chats; architecture – application, technology, infrastructure, repositories.
Evaluating KM at Universities
Regarding KM in universities, Sar karani [53] focused on the challenges of Japan and the prerequisites for the internationalization of universities as well as their duties of producing knowledge and KM. Jamshidi and Nemati worked on ‘knowledge share and experience’ in social capital development within IT units in universities, and their results showed that there was a significant difference between the knowledge share process and social capital experience [84]. In this study, the indexes to evaluate the success of a KM system have been provided by a questionnaire. In this case, a combination of indexes was introduced in the questionnaire as suggested by Rampersad [85].
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Table 2: KM perspectives and metrics Perspective Analysisbased
?
Indicators / Metrics
Qualitative analysis, quantitative analysis, nonfinancial indicator analysis, financial indicator
N
Res
8
[36]
analysis, internal performance analysis, external performance analysis, project-orientated analysis, organization-orientated analysis
Area-based
?
Knowledge measurement in products and processes, measurement organization, of knowledge value of in internal
3
[74]
measurement
organizational
conditions based on KM processes
Factorsbased
?
Employee traits, strategy factors, superintendent traits, audit and assessment, organizational culture, operating procedures, information technology
6
[59]
Indicatorbased
?
Context indicator, input indicator, process indicator, output indicator
5
[76]
?
Knowledge
or
information
quality,
perceived
4
[43]
knowledge management system (KMS) benefits, user satisfaction, and system use were used as dependent variables in evaluating KMS success
Methodbased
?
Marketing cost methods, return on assets, direct intellectual capital, score card
4
[77]
?
The balanced score card, economic value-added, Skandia Business Navigator
3 4
[78]
?
Direct intellectual capital, score card, marketing cost methods, return on assets
[73]
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Analysis of Knowledge Management Within Five Key Areas
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Metricsbased Modelbased
?
Benchmarking focus, performance measurement focus, Skandia Business Navigator, value focus
4
[79]
?
Cognitive model, network model, community model, quantum model, philosophy-based model, general intellectual capital (IC) measurement model
6
[57, 71]
Parametersbased
?
General management, leadership style, strategic vision, internal process, human resources
5 5 3 3
[80]
?
Psychological, architecture
culture,
process,
functionality,
[81]
? ?
Technology, process, people
[57]
People, structures and processes
[35]
Processbased
?
Knowledge
creation,
knowledge
validation,
6
[1]
knowledge presentation, knowledge distribution, and knowledge application activities, knowledge capitalization, knowledge balancing ? Background/structural factors, knowledge
3 4
[82]
production, knowledge integration ? Knowledge knowledge creation, sharing, knowledge knowledge accumulation, utilization, [75]
knowledge internalization ? KM process (knowledge acquisition, knowledge conversion, knowledge application and knowledge protection), KM effectiveness (individual-level and organizational-level KM effectiveness) and sociotechnical support (organizational support and
3
[30]
information technology previous literature
diffusion) based on the
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Analysis of Knowledge Management Within Five Key Areas
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The Specific Research Questions
The research questions of the study were as follows: ? What is the level of KM based on the main parameters at this university? ? Is there a significant difference between demographic factors such as: groups of the study (lecturer and other staff), job levels, and KM? ? How can KM be practiced at this university? ? How should the strategies be provided for enhancing effectiveness of KM in IAU-GB?
The Research Methodology
This study was based on a survey that involved all the lecturers and other staff of IAU-GB. The population was 135 and the Kokaran model of sampling was used. Data obtained from the sample 101 participants were analyzed. In this study, descriptive statistics methods such as percentage, mean and so on were used, and depending on the type of variable, KruskalWallis test, Mann-Whitney and correlation coefficient tests were applied for investigating the correlation. Research Hypotheses: 1. There is a relationship between an adequate ‘general status of management’ and KM. 2. There is a relationship between leadership style at IAU-GB and KM. 3. The more a university follows proper strategic outlooks, the more easily KM is achieved. 4. The internal management procedures at IAU-GB help establishes KM. 5. There is a relationship between the status of human resources and KM. To test these hypotheses, KM was defined on 5 parameters. Then, due to the fact that the data were of ordinal scale, non-parametric KruskalWallis Test was applied to obtain the mean of the 4 groups in every 5 variables of KM. All the hypotheses were tested and are summarized in 8
Analysis of Knowledge Management Within Five Key Areas
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Table 8. Of course, with regard to the ordinal mean in each of the 4 groups in all 5 management parameters, it can be concluded that the more the means of the parameters are, the more easily KM is achieved.
Participants
Questionnaires were sent to employees with positions of significant responsibility to measure the level of KM. 120 lecturers and other staff were selected through stratified random sampling and investigated through a standardized instrument designed by the researchers for management of knowledge. The collected data was analyzed using SPSS. The KruskalWallis test, Mann-Whitney test and Spearman correlation tests were also applied. From 120 questionnaires distributed, 101 employees completed and returned their questionnaires, resulting in 101 (47 other staff and 54 lecturers) usable responses (see Table 3). Table 3: A Demographics Frequency of Participants
Gender Ma le Fe ma le Field study Hu man scien ces M S Ph Dstu N o % 67. 3 32. 7 61.4 13.9 24.8 46. 5 53.5 14.9 31.7 24 .8 9.9 18. 8 68 33 62 14 25 47 54 15 32 25 10 19 Ph D Basic scien ces Enginee ring Job groups Sta ff Lectu rer Job levels Mana ger Exp ert Lecturer
Demographics
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Sampling Design
Five sets of measures were adopted and used to measure each of the five constructs, namely, general management, leadership style, strategic vision, internal process and human resources. These measures were made by integrating Rampersad test [85], and were subjected to a formal pre-test by some managers and experts. An internal consistency analysis was performed separately for each variable in the theorized model by calculating the Cronbach’s alpha. The results in Table 4 show that the Cronbach-a s for all the variables in the model were above the critical value of 0.7 [86]. Hence, the authors concluded that all the items had been appropriately assigned to each variable. The instrument developed also had content validity, because the selection of measurement items was based on an exhaustive review of the literature and a detailed evaluation by academics and practitioners. Content validity depends on how well the researchers created the measurement items to cover the content domain of the variable being measured [86]. The study used a five-point rating scale, i.e. from 1 (strongly disagree) to 5 (strongly agree). The reliability alphas (a) of different variables and sample items for each variable are discussed as follows. Table 4: Statistical Information
Parameter No Items General Management Leadership Style Strategic Vision Internal Process Human Resources KM Total 7 5 7 7 39 .77 .79 .77 .83 .90 22.3335 15.3665 19.9206 19.7428 23.1635 .728** .736** .745** .785** .000 .021 .025 .001 13 of Cronbach's Alpha .77 38.454 .710** .000 Mean Correlations Sig
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Findings of the Study
Correlation and validity of the instrument’s statements were achieved through the Cronbach method, the correlation for all the subscales of KM were high and significant at 0.01, but note the correlation for the indicators of human resources in the first rank (r=0.785), and general management (r= 0.710) is last rank (see Table 4). Also, the maximum Cronbach belongs to human resources (.83) and among the indicators, general management, leadership, and internal process are least (0.77), and strategic vision is .79. Fortunately, the reliability alphas of Total KM (0.90) were very strong, and the alpha value of 90% indicates that the research instrument has a high validity.
Description of Data
Table 5 shows Mean, SD, Skewness and Kurtosis of 5 parameters: general management, leadership style, strategic vision, internal process, human resources and total of KM. Table 5: Descriptive Statistics
Five Parameters Statis tic General Management Leadership Style Strategic Vision Internal Processes 101 2.8458 .51968 .031 .240 -.388 .476 101 3.0733 .59513 .082 .240 -.444 .476 101 3.1905 .61714 -.289 .240 -.949 .476 101 2.9580 .42427 -.032 Statistic N Mean Std. Deviation Statistic Statistic Std. Error .240 -.935 Statistic Std. Error .476 Skewness Kurtosis
HUMAN RESOURCES
101
2.8204
.71419
-.213
.240
-.871
.476
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The total KM scores of the participants are illustrated in the form of a histogram and a normality distribution in Figure 2. In fact, the normality distribution of the assessed variables was based on Kurtosis and Skewness (Table 5), the result of exploratory analysis showed an excellent normality KM scale.
Figure 2: Normal Distribution
The Score of Parameters
As can be seen in Table 6, the means of the parameters of other staff, lecturers, and total participants, are different. They are discussed below: ? Staff – The total mean of the 5 parameters that were indicative of KM was 2.73, and the highest mean belonged to strategic vision (2.93) and the lowest mean was 2.40 for human resources. ? Lecturers – The total mean for the 5 parameters measuring KM was 3.19, which is more than the average score. The highest mean was 3.46 and belonged to leadership style, and the lowest mean (3.04), belonged to internal process. ? Other staff and lecturers – The total mean of 5 parameters was 2.98. The parameter for leadership style had a high mean of 3.19. The mean for the parameter of internal process was lower than average (2.82). In general, the respondents level of leadership style and strategic vision is more than average, in other words, they are satisfied with the system aspect of leadership style and strategic vision. However responses to 12
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the other parameters (general management, internal process, and human resources) are less than average. Table 6: An Analytical Survey of parameters
Parameter General manage ment mean staff Lectu rer 2.8156 3.0820 2.8845 3.4568 Leader ship style Strate gic Vision 2.9277 3.2000 Inter nal process 2.6201 3.0423 Human resour ces 2.4012 3.1852 2.73 3.19 Total mean
Total mean
2.9580
3.1905
3.0733
2.8458
2.8204
2.976
Data Analysis
The main objective of this research was to identify and investigate the pattern for establishing a KM at university. In the other words, this research sought the answer whether there are any signs observed at the University of knowledge-based Management and how can this new and efficient pattern be implemented or strengthened at the university? The minor objectives of the study included studying the demographic features of gender, age, education, and the groups of the study (lecturer and staff) as well as studying the parameters of knowledge-based management such as the general style of management at university, the leadership style, the strategic vision, the internal processes of management, and investigating the status of human resources at university. According to the results shown in Table 7, there are significant differences between the approach of other staff and lecturers to KM parameters. In addition, the ranges of SD in measures show differences between the two groups. It seems the approach of lecturers were concentrated. So, it was assessed that lecturers had a more positive approach because they have more information and deeper/wider vision.
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Items
Table 7: Mann-Whitney Test – Group Statistics Position N Mean SD staff Lecturer staff Lecturer staff Lecturer staff Lecturer staff Lecturer 47 54 47 54 47 54 47 54 47 54 40.84 59.84 36.54 63.58 43.67 57.38 37.65 62.62 33.85 65.93 .34881 .44765 .56646 .53368 .52985 .62405 .45788 .49302 .61599 .58451
General management Leadership style Strategic vision Internal process Human resources
According to the results of the Kruskal-Wallis Test in which the significance value is less than 0.05, the null hypothesis that there is no relationship between these 5 parameters and KM is rejected and all 5 parameters are proved to have a direct positive relationship with KM (Table 8). Table 8: Kruskal-Wallis Test
Human Leadership General Chi-Square df Asymp. Sig. 88.982 3 .000 Style 21.100 3 .000 Strategic Vision 9.758 3 .021 Internal Processes 9.329 3 .025 16.320 3 .001 Resources
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Hypothesis Test
H-1, There is a relationship between gender and KM To test this hypothesis, a non-parametric Mann-Whitney Test, needs to be conducted for two independent male and female groups: Table 9 shows the results of tests and allows comparison of the means for female and male groups in 5 management parameters. Because the significance is
Knowledge management (KM) comprises a range of strategies and practices used in an organisation to identify, create, represent, distribute, and enable adoption of insights and experiences
Scientific Papers (www.scientificpapers.org) Journal of Knowledge Management, Economics and Information Technology
Issue 6 October 2011
Analysis of Knowledge Management within Five Key Areas
Authors:
Alireza ANVARI, Gholam-Abbas ALIPOURIAN, Rohollah MOGHIMI, Leila BAKTASH, Department of Industrial Management, Gachsaran Branch, I.A.U., Gachsaran, Iran, [email protected]; [email protected]; [email protected]; [email protected]
Knowledge Management as a crucial factor impacts on organizational performance. It seems to be a lack of empirical studies that measure knowledge in high educational environments, especially in universities. The main purpose of this study was to identify and assess five pointers that contribute towards knowledge management in a university in Iran. The methodology involved both qualitative and quantitative research to evaluate knowledge management based on literature and personnel viewpoints in the university. Data from 101 participants were analyzed by using KruskalWallis, and Mann-Whitney test. The instrument used was a structured research questionnaire on knowledge management. The analysis showed that all five parameters had an effect on knowledge management. The results imply that the university is following a trend towards knowledge-orientation. Furthermore, there was a significant difference between two groups (lecturer and staff) perception. Its implication can also be beneficial to other universities that plan to highlight knowledgeoriented management. Keywords: Knowledge Management, Information Management, Evaluation Method, Five-Indicators
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Analysis of Knowledge Management Within Five Key Areas
Issue 6 October 2011
Introduction
A review of current business literature reveals that knowledge management (KM) has become a crucial factor in competitive environments. According to Bhatt [1], business and academic communities believe that the process of leveraging knowledge can provide an organization with long-term competitive advantages. Obviously, universities are no exception; they are centers for production and leveraging of knowledge. Islamic Azad University – Gachsaran Branch (IAU-G.B.), as a center of knowledge, wants to implement KM so that it can develop the potentialities and commitment of skilled employees through identifying methods for creating, recognizing, implementing, leveraging and distributing organizational knowledge. This would mean a KM emphasis on the creation, utilization and development of their collective intelligence [2]. This research initially focused on identifying assessment measures of KM and their strengths and weaknesses. This study then investigated the relationship between KM in the field of management and infrastructure of IAU-GB, its variables including the general management, the leadership style, strategic vision, internal processes, and human resources, as well as factors such as the type of the groups (lecturers and other staff), job levels, and gender (Figure 1). At the same time, the study aimed to clarify whether it is possible to provide strategies for making KM more effective. The research methodology used qualitative and quantitative methods. The aim of this research, using qualitative methods, was to address the following questions in a literature review: ? What measures are used to evaluate KM? ? What are the variables in KM evaluation? And, qualitative methods based on a case study addressed two questions: ? What is the level of KM from the perspective of employees? ? Are there any significant differences between the two groups (lecturer and staff)? The structure of the paper is as follows: Section 2 presents an outline of the literature review in the form of a table (Table 1) that lists the researchers of KM. moreover in this section, a general evaluation of KM and the categorization of their metrics and variables. The methodology and the case study are described in Section 3. Finally, Sections 2
Analysis of Knowledge Management Within Five Key Areas
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4 and 5 present a discussion, some concluding remarks and suggestions for universities regarding the implementation of KM.
Figure 1: A Conceptual Diagram of Five-Parameter Modeling of KM
A Review Study of Knowledge management
In recent years, researchers have focused on KM and have attempted to support organizational knowledge, such as: Sommerville and Dalziel [3], Goffee and Jones [4], Hwang [5], Albers and Brewer [6], Goh [7], Fernandez et al. [8], Gumus [9], Kayakutlu and Buyukozkan [10], Wen [11], and so on. Hence, KM has been categorized according to the authors’ different approaches (see Table 1).
Assessing Knowledge Management
According to the literature, there are nine perspectives for KM measurement (Table 2). Mostafa Jafari et al. [55] identified 33 measurement methods of knowledge and intellectual capital. They classified them into four groups: direct intellectual capital, score card, marketing cost methods, and return on assets. Khadivar et al. [74] classified the studied measurement methods into three approaches (from an area-based perspective): knowledge
3
Analysis of Knowledge Management Within Five Key Areas
Issue 6 October 2011
measurement in products and processes, measurement of knowledge value in internal organization, and measurement of organizational conditions based on KM processes. Moreover, Chang and Wang [59] classified the measurement methods into seven approaches (from a factors-based perspective): employee traits, strategy factors, superintendent traits, audit and assessment, organizational culture, operating procedures, and information technology. In addition, Adli [76] proposed 4 key indicators (context, input, process and output indicators); Vlok [82] stated 14 dimensions in 3 processbased areas: background/structural factors, knowledge production and knowledge integration; and Wen [11] offered 5 criteria for KM: data, information, knowledge, wisdom, and Staff; and so on. As a result of the literature review of KM performance evaluation, we can classify some of these review findings into several perspectives (see Table 2). Table 1: Different Approaches to KM Resources [12- 36] [1, 37- 45] [1, 2, 23, 25, 26, 33 [29, 40, 61 -75] 59]
No 1 2 3 4
Issues
Study on theory and fundamentalsbetween KM Relationship and IT Competitive advantages of KM Categorization of KM
Knowledge Management in High Education
Knowledge systems are core elements of a manager’s requirements for organizing, controlling, participating, and combining systems of structures, processes, and people [35]. For this reason, many authors have studied the different facets of knowledge [33, 34, 36, 59, 83], but it seems that the creation and utilization of knowledge is the most important challenge. Universities are the main centers for producing and leveraging knowledge [56]. Through the use of KM, universities will be able to perform more effectively by spreading knowledge among cultures, and expanding the process of learning and teaching to overseas universities [53].
4
Analysis of Knowledge Management Within Five Key Areas
Issue 6 October 2011
Therefore, we need to establish what KM is and organize it into categories so that we can gain a conceptual understanding, and prepare the appropriate context for the creation of software concepts. Due to the appearance of new knowledge producers in the education sector, more and more universities are looking into the possibility of applying corporate KM systems [2]. In this case, there are some factors which affect the success of KM in a university: leadership, the nature of academic other staff, evidence of the benefits, the taxonomy for the application of KM within the university, management structure, and the history of the university [83]. Hijazi and Kelly [42] claim that KM can help to solve problems between industry and a university, such as: align IT with social networks and dealings, encourage and support the use of KM, allow knowledge transfer across different tasks, apply knowledge to workers’ management and practice tacit knowledge within their surroundings. Abdullah et al. [81] proposed a framework for a KM system: psychological – motivation, awareness, reward, strategy; culture – truth, beliefs, value, experience; process – acquisition, store, disseminate, use; functionality – agent, email, video conferencing, chats; architecture – application, technology, infrastructure, repositories.
Evaluating KM at Universities
Regarding KM in universities, Sar karani [53] focused on the challenges of Japan and the prerequisites for the internationalization of universities as well as their duties of producing knowledge and KM. Jamshidi and Nemati worked on ‘knowledge share and experience’ in social capital development within IT units in universities, and their results showed that there was a significant difference between the knowledge share process and social capital experience [84]. In this study, the indexes to evaluate the success of a KM system have been provided by a questionnaire. In this case, a combination of indexes was introduced in the questionnaire as suggested by Rampersad [85].
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Analysis of Knowledge Management Within Five Key Areas
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Table 2: KM perspectives and metrics Perspective Analysisbased
?
Indicators / Metrics
Qualitative analysis, quantitative analysis, nonfinancial indicator analysis, financial indicator
N
Res
8
[36]
analysis, internal performance analysis, external performance analysis, project-orientated analysis, organization-orientated analysis
Area-based
?
Knowledge measurement in products and processes, measurement organization, of knowledge value of in internal
3
[74]
measurement
organizational
conditions based on KM processes
Factorsbased
?
Employee traits, strategy factors, superintendent traits, audit and assessment, organizational culture, operating procedures, information technology
6
[59]
Indicatorbased
?
Context indicator, input indicator, process indicator, output indicator
5
[76]
?
Knowledge
or
information
quality,
perceived
4
[43]
knowledge management system (KMS) benefits, user satisfaction, and system use were used as dependent variables in evaluating KMS success
Methodbased
?
Marketing cost methods, return on assets, direct intellectual capital, score card
4
[77]
?
The balanced score card, economic value-added, Skandia Business Navigator
3 4
[78]
?
Direct intellectual capital, score card, marketing cost methods, return on assets
[73]
6
Analysis of Knowledge Management Within Five Key Areas
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Metricsbased Modelbased
?
Benchmarking focus, performance measurement focus, Skandia Business Navigator, value focus
4
[79]
?
Cognitive model, network model, community model, quantum model, philosophy-based model, general intellectual capital (IC) measurement model
6
[57, 71]
Parametersbased
?
General management, leadership style, strategic vision, internal process, human resources
5 5 3 3
[80]
?
Psychological, architecture
culture,
process,
functionality,
[81]
? ?
Technology, process, people
[57]
People, structures and processes
[35]
Processbased
?
Knowledge
creation,
knowledge
validation,
6
[1]
knowledge presentation, knowledge distribution, and knowledge application activities, knowledge capitalization, knowledge balancing ? Background/structural factors, knowledge
3 4
[82]
production, knowledge integration ? Knowledge knowledge creation, sharing, knowledge knowledge accumulation, utilization, [75]
knowledge internalization ? KM process (knowledge acquisition, knowledge conversion, knowledge application and knowledge protection), KM effectiveness (individual-level and organizational-level KM effectiveness) and sociotechnical support (organizational support and
3
[30]
information technology previous literature
diffusion) based on the
7
Analysis of Knowledge Management Within Five Key Areas
Issue 6 October 2011
The Specific Research Questions
The research questions of the study were as follows: ? What is the level of KM based on the main parameters at this university? ? Is there a significant difference between demographic factors such as: groups of the study (lecturer and other staff), job levels, and KM? ? How can KM be practiced at this university? ? How should the strategies be provided for enhancing effectiveness of KM in IAU-GB?
The Research Methodology
This study was based on a survey that involved all the lecturers and other staff of IAU-GB. The population was 135 and the Kokaran model of sampling was used. Data obtained from the sample 101 participants were analyzed. In this study, descriptive statistics methods such as percentage, mean and so on were used, and depending on the type of variable, KruskalWallis test, Mann-Whitney and correlation coefficient tests were applied for investigating the correlation. Research Hypotheses: 1. There is a relationship between an adequate ‘general status of management’ and KM. 2. There is a relationship between leadership style at IAU-GB and KM. 3. The more a university follows proper strategic outlooks, the more easily KM is achieved. 4. The internal management procedures at IAU-GB help establishes KM. 5. There is a relationship between the status of human resources and KM. To test these hypotheses, KM was defined on 5 parameters. Then, due to the fact that the data were of ordinal scale, non-parametric KruskalWallis Test was applied to obtain the mean of the 4 groups in every 5 variables of KM. All the hypotheses were tested and are summarized in 8
Analysis of Knowledge Management Within Five Key Areas
Issue 6 October 2011
Table 8. Of course, with regard to the ordinal mean in each of the 4 groups in all 5 management parameters, it can be concluded that the more the means of the parameters are, the more easily KM is achieved.
Participants
Questionnaires were sent to employees with positions of significant responsibility to measure the level of KM. 120 lecturers and other staff were selected through stratified random sampling and investigated through a standardized instrument designed by the researchers for management of knowledge. The collected data was analyzed using SPSS. The KruskalWallis test, Mann-Whitney test and Spearman correlation tests were also applied. From 120 questionnaires distributed, 101 employees completed and returned their questionnaires, resulting in 101 (47 other staff and 54 lecturers) usable responses (see Table 3). Table 3: A Demographics Frequency of Participants
Gender Ma le Fe ma le Field study Hu man scien ces M S Ph Dstu N o % 67. 3 32. 7 61.4 13.9 24.8 46. 5 53.5 14.9 31.7 24 .8 9.9 18. 8 68 33 62 14 25 47 54 15 32 25 10 19 Ph D Basic scien ces Enginee ring Job groups Sta ff Lectu rer Job levels Mana ger Exp ert Lecturer
Demographics
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Sampling Design
Five sets of measures were adopted and used to measure each of the five constructs, namely, general management, leadership style, strategic vision, internal process and human resources. These measures were made by integrating Rampersad test [85], and were subjected to a formal pre-test by some managers and experts. An internal consistency analysis was performed separately for each variable in the theorized model by calculating the Cronbach’s alpha. The results in Table 4 show that the Cronbach-a s for all the variables in the model were above the critical value of 0.7 [86]. Hence, the authors concluded that all the items had been appropriately assigned to each variable. The instrument developed also had content validity, because the selection of measurement items was based on an exhaustive review of the literature and a detailed evaluation by academics and practitioners. Content validity depends on how well the researchers created the measurement items to cover the content domain of the variable being measured [86]. The study used a five-point rating scale, i.e. from 1 (strongly disagree) to 5 (strongly agree). The reliability alphas (a) of different variables and sample items for each variable are discussed as follows. Table 4: Statistical Information
Parameter No Items General Management Leadership Style Strategic Vision Internal Process Human Resources KM Total 7 5 7 7 39 .77 .79 .77 .83 .90 22.3335 15.3665 19.9206 19.7428 23.1635 .728** .736** .745** .785** .000 .021 .025 .001 13 of Cronbach's Alpha .77 38.454 .710** .000 Mean Correlations Sig
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Findings of the Study
Correlation and validity of the instrument’s statements were achieved through the Cronbach method, the correlation for all the subscales of KM were high and significant at 0.01, but note the correlation for the indicators of human resources in the first rank (r=0.785), and general management (r= 0.710) is last rank (see Table 4). Also, the maximum Cronbach belongs to human resources (.83) and among the indicators, general management, leadership, and internal process are least (0.77), and strategic vision is .79. Fortunately, the reliability alphas of Total KM (0.90) were very strong, and the alpha value of 90% indicates that the research instrument has a high validity.
Description of Data
Table 5 shows Mean, SD, Skewness and Kurtosis of 5 parameters: general management, leadership style, strategic vision, internal process, human resources and total of KM. Table 5: Descriptive Statistics
Five Parameters Statis tic General Management Leadership Style Strategic Vision Internal Processes 101 2.8458 .51968 .031 .240 -.388 .476 101 3.0733 .59513 .082 .240 -.444 .476 101 3.1905 .61714 -.289 .240 -.949 .476 101 2.9580 .42427 -.032 Statistic N Mean Std. Deviation Statistic Statistic Std. Error .240 -.935 Statistic Std. Error .476 Skewness Kurtosis
HUMAN RESOURCES
101
2.8204
.71419
-.213
.240
-.871
.476
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The total KM scores of the participants are illustrated in the form of a histogram and a normality distribution in Figure 2. In fact, the normality distribution of the assessed variables was based on Kurtosis and Skewness (Table 5), the result of exploratory analysis showed an excellent normality KM scale.
Figure 2: Normal Distribution
The Score of Parameters
As can be seen in Table 6, the means of the parameters of other staff, lecturers, and total participants, are different. They are discussed below: ? Staff – The total mean of the 5 parameters that were indicative of KM was 2.73, and the highest mean belonged to strategic vision (2.93) and the lowest mean was 2.40 for human resources. ? Lecturers – The total mean for the 5 parameters measuring KM was 3.19, which is more than the average score. The highest mean was 3.46 and belonged to leadership style, and the lowest mean (3.04), belonged to internal process. ? Other staff and lecturers – The total mean of 5 parameters was 2.98. The parameter for leadership style had a high mean of 3.19. The mean for the parameter of internal process was lower than average (2.82). In general, the respondents level of leadership style and strategic vision is more than average, in other words, they are satisfied with the system aspect of leadership style and strategic vision. However responses to 12
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the other parameters (general management, internal process, and human resources) are less than average. Table 6: An Analytical Survey of parameters
Parameter General manage ment mean staff Lectu rer 2.8156 3.0820 2.8845 3.4568 Leader ship style Strate gic Vision 2.9277 3.2000 Inter nal process 2.6201 3.0423 Human resour ces 2.4012 3.1852 2.73 3.19 Total mean
Total mean
2.9580
3.1905
3.0733
2.8458
2.8204
2.976
Data Analysis
The main objective of this research was to identify and investigate the pattern for establishing a KM at university. In the other words, this research sought the answer whether there are any signs observed at the University of knowledge-based Management and how can this new and efficient pattern be implemented or strengthened at the university? The minor objectives of the study included studying the demographic features of gender, age, education, and the groups of the study (lecturer and staff) as well as studying the parameters of knowledge-based management such as the general style of management at university, the leadership style, the strategic vision, the internal processes of management, and investigating the status of human resources at university. According to the results shown in Table 7, there are significant differences between the approach of other staff and lecturers to KM parameters. In addition, the ranges of SD in measures show differences between the two groups. It seems the approach of lecturers were concentrated. So, it was assessed that lecturers had a more positive approach because they have more information and deeper/wider vision.
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Items
Table 7: Mann-Whitney Test – Group Statistics Position N Mean SD staff Lecturer staff Lecturer staff Lecturer staff Lecturer staff Lecturer 47 54 47 54 47 54 47 54 47 54 40.84 59.84 36.54 63.58 43.67 57.38 37.65 62.62 33.85 65.93 .34881 .44765 .56646 .53368 .52985 .62405 .45788 .49302 .61599 .58451
General management Leadership style Strategic vision Internal process Human resources
According to the results of the Kruskal-Wallis Test in which the significance value is less than 0.05, the null hypothesis that there is no relationship between these 5 parameters and KM is rejected and all 5 parameters are proved to have a direct positive relationship with KM (Table 8). Table 8: Kruskal-Wallis Test
Human Leadership General Chi-Square df Asymp. Sig. 88.982 3 .000 Style 21.100 3 .000 Strategic Vision 9.758 3 .021 Internal Processes 9.329 3 .025 16.320 3 .001 Resources
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Hypothesis Test
H-1, There is a relationship between gender and KM To test this hypothesis, a non-parametric Mann-Whitney Test, needs to be conducted for two independent male and female groups: Table 9 shows the results of tests and allows comparison of the means for female and male groups in 5 management parameters. Because the significance is