Hsi-kong Chin Wang, Da-yeh University Shi-ching Sha, Da-yeh University ABSTRACT RESEARCH BACKGROUND AND MOTIVE RESEARCH SUBJECTS AND OBJECTIVES

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1 The Study of Structure Factors, Relationship Factors and Knowledge Sharing for their Influences on Organizational Performances Taking the 202nd Plant, Materiel Production Center, M.N.D. as Example Hsi-kong Chin Wang, Da-yeh University Shi-ching Sha, Da-yeh University ABSTRACT Knowledge is the resource of competition advantage of the enterprise in the era of knowledge economy. The innovation of knowledge and technique will change the way of wealth creation on individual, enterprise and nation in the future. The development foundation of future economy is going to be based on the creative capability of knowledge. However, the innovation of knowledge and capital should start by knowledge sharing. The key point of knowledge sharing depends on human being not on the technique. According to the results of former studies, the main factor of how employees effectively exploit the wisdom and experiences is decided by the relationship between the boss and subordinate. Seeing that, the study starts from knowledge sharing of employees that is the angle of view of human being. Moreover, the structure factor and relationship factor are used to assist in investigating the connection between human being and organization. By the demonstration in the units of MND, the study compares variables to show whether the differences exist or not. This study adopts the method of questionnaire survey. The structure factor and relationship factor are investigated to reach the objective of knowledge sharing among employees. Furthermore, knowledge sharing is used to promote achievements of individual and organization. Analyses of statement statistics, factor, variable, and typical correlation are calculated by SPSS statistical software to demonstrate the hypotheses of this study. The results of this study show: 1. Structure factor and relationship factor are obviously positive relationship with knowledge sharing. 2. Structure factor, relationship factor and knowledge sharing are obviously positive relationship with organization achievement. Keywords: knowledge sharing, structure factor, relationship factor, organization achievement RESEARCH BACKGROUND AND MOTIVE How fast is the world changing in the 21 st century? Perhaps, we are not able to sense it immediately. However, we are sure that the world is changing at an unprecedented speed due to technological advancement. Technological development upgrades life quality and promotes economic and social prosperity. In the era of knowledge and value, the role of knowledge has changed in society. In the new economic system, the three traditional production elements, land, labor and capital have become the secondary resources. Only the knowledge is the primary resource for individual and overall economy (Drucker, 1993). In the past studies on knowledge sharing, many scholars conducted analysis in different aspects, such as study on the behavior and intention for organization members to share knowledge(hendriks, 1999; Monika & Takeuchi, 1995). This study started with structure factors and relationship factors to achieve the objective of sharing knowledge among employees and improving individual and organizational performance. RESEARCH SUBJECTS AND OBJECTIVES According to the background and motives for the study, the subjects and objectives are divided to the following points:

2 1. Study the theories for structure factors, relationship factors, knowledge sharing, and organizational performance. 2. Study the influences of structure factors, relationship factors and knowledge sharing intention on organizational performance. 3. Study different demographic variables in structure factors, relationship factors and knowledge sharing for organizational performance. 4.Make suggestions based on research results for management references. RESEARCH PROCESS The research is conducted with the following process: Step 1: research motives and objectives describe the motive and objective for the research Step 2: determine research subjects determine the issues and the objectives Step 3: literature review collect and study theories and data relevant to the issues Step 4: research method establish research assumption and framework, and design questionnaire to conduct survey Step 5: result analysis and discussion select the proper statistical method and conduct analysis for returned questionnaire Step 6: conclusions and suggestions make suggestions based on the results and conclusions for the research RESEARCH FRAMEWORK According to the research motives and objectives and with consideration in four aspects, structure factor, relationship factor, knowledge sharing and organizational performance, the research framework is established with references to related theories as in Figure 1. Figure 1: Research Framework h5: 結構性因素對組織績效有顯著影響 結構性因素誘因機制資訊科技關係性因素非正式互動關係信任 h3: 結構性因素對知識分享有顯著影響知識分享 知識擁有者角度組織層面 h2: 關係性因素對知角度識分享有顯著影響 h4: 知識分享對組織績效有顯著影響組織績效 累積知識資產增加結合能力 h6: 關係性因素對組織績效有顯著影響 RESEARCH ASSUMPTIONS Based on the above research framework and subjects, the study lists the following assumptions to investigate the relationship among all aspects: Assumption 1: demographic characteristics (gender, education background, age, years of employment, rank, position) vary significantly with structure factors, relationship factors, knowledge sharing and organizational performance.

3 Assumption 2: structure factors are significantly related to knowledge sharing. Assumption 3: relationship factors are significantly related to knowledge sharing. Assumption 4: knowledge sharing is significantly related to organizational performance. Assumption 5: structure factors are significantly related to organizational performance. Assumption 6: relationship factors are significantly related to organizational performance. Assumption 7: structure factors, relationship factors and knowledge sharing are significantly related to organizational performance. Assumption8: structure factors, relationship factors and knowledge sharing have significantly influences to organizational performance. RESEARCH SCOPE The study used questionnaire as sample collection method. But the study was limited by overly large military organization, broad unit distribution, numerous officers and insufficient research time, so the study cannot extend to extensive survey. The research scope is limited officers, petty officers, and employees of the 202nd Plant, Materiel Production Center, and M.N.D as the population, which sample number is 716. Table 1: Overall Sample Item Number of People Colonel 16 Lieutenant colonel, major 77 Company officer(including petty officer) 461 Employees 162 Data source: the Research ASSESSMENT OF RESEARCH VARIABLES The study uses questionnaire as assessment tool and includes four parts: the first is structure factor scale;the second is relationship factor scale;the third is knowledge sharing scale;the fourth is organizational performance scale. The questionnaire contains 38 questions. The following describes the major part of the questionnaire. 1. Structure Factor Scale (6 questions in total) Incentive mechanism question 1 to 3; information technology question 4 to Relationship Factor Scale (6 questions in total) Informal interactive relationship question 1 to 3; trust question 4 to Knowledge Sharing Scale (16 questions in total) Knowledge owner question 1 to 10; organization aspect question 11 to Organizational performance scale (10 questions in total) Accumulated knowledge asset, question 1 to 7; enhanced associative ability, question 8 to 10. Assessment method: the above questions are all single-choice, adopting five point Liker-type scales and ranking by semantic differential scale. The choices include agree very much 5 points, agree 4 points, no opinion 3 points, disagree 2 points, disagree very much 1 point. The higher the score is, the stronger the agreement is by the questionnaire taker. DATA ANALYSIS METHOD Based on the above research motives and research assumption, after questionnaires returned, those with incomplete answers were first deleted. Then, statistical software SPSS was used for data analysis. The statistical method adopted in the research is as follows: 1. Descriptive statistical analysis

4 2. Factor analysis: 3. Reliability analysis 4. t-test 5. One-Way ANOVA 6. Pearson Product-Moment Correlation Analysis 7. Regression Analysis RESEARCH LIMIT Although the study is scheduled to be completed with valuable conclusions in a time frame, it still encountered some difficulties and limit in the process as follows: 1. Variable: Presently, there are many studies in the industry or academia regarding knowledge sharing. But in the military system, it lacks study on individual organization. The study hopes to investigate the structure factors and relationship factors through the perspectives of employees of the 202nd Plant, Materiel Production Center, and M.N.D. 2. Sample: Since the study scope is limited to all the employees of the 202nd Plant, Materiel Production Center, M.N.D., excluding other units under Material Production Center, whether the results and inferences can apply to all military units is limited. 3. Scale: The scale in every aspect of the study is adopted as much as possible from revision of domestic high-reliability and high-validity scale. Through testing and expert correction in the research, most scales are adopted in the civilian society, which differentiates from military units in culture and perspectives. Thus, the validity test still cannot establish accuracy and applicability. PILOT TEST AND FACTOR ANALYSIS To effectively develop the research tool, after pilot test of the scale, it was the 401st Plant, Materiel Production Center to conduct the test, which distributed 100 copies of questionnaire and received 90 copies in return, with return rate 90%. They are all valid and subject to statistical analysis to test the validity and reliability of the scale. Validity analysis: The research uses factor analysis method to establish scale validity. It set up files for pilot test samples and conducted factor analysis with statistical software SPSS 10.0 version. Each scale is analyzed as follows: (1). Structure factors scale: Use principal factor extraction to extract common factors. Select common factors with Eigen value larger than 1.0. Then use varimax method to conduct the orthogonal rotation. After factor analysis, two common factors are named incentive mechanism, including subject 2, 4 and 6, with explained variance %; information technology, including subject 1, 3 and 5, with explained variance %;total accumulated explained variance %, which communality validity and factor loading are both above 0.5, indicating the scale has good construct validity. (2). Relationship factors scale: Use principal factor extraction to extract common factors. Select common factors with Eigen value larger than 1.0. Then use varimax method to conduct the orthogonal rotation. After factor analysis, two common factors are named informal interactive relationship, including subject 3, 4, 5 and 6, with explained variance %; trust, including subject 1 and 2, with explained variance %;total accumulated explained variance %, which communality validity and factor loading are both above 0.5, indicating the scale has good construct validity. (3). Knowledge sharing scale: Use principal factor extraction to extract common factors. Select common factors with Eigen value larger than 1.0. Then use varimax method to conduct the orthogonal rotation. After factor analysis three times, delete subject 11, 13, 14,

5 15 and 16 with insufficient representation. Two common factors are named knowledge owner, including subject 1, 2, 3, 7, 8, 9 and 10, with explained variance %; organizational aspect, including subject 4, 5, 6 and 12, with explained variance %;total accumulated explained variance %, which communality validity and factor loading are both above 0.5, indicating the scale has good construct validity. (4). Organizational performance scale: Use principal factor extraction to extract common factors. Select common factors with Eigen value larger than 1.0. Then use varimax method to conduct the orthogonal rotation. After factor analysis three times, delete subjects 3, with insufficient representation. Two common factors are named accumulated knowledge asset, including subject 4, 7, 8, 9 and 10, with explained variance %; enhanced associative ability, including subject 1, 2, 5 and 6, with explained variance %;total accumulated explained variance %, which communality validity and factor loading are both above 0.5, indicating the scale has good construct validity. Reliability analysis: (1). Structure factor scale: The establishment of scale reliability in the study uses Cronbach s Alpha to test its internal consistency and adopts Item to Total Correlation to test correlation among all dimensions. Each sub-dimension s Cronbach s Alpha coefficients are incentive mechanism , information technology Every dimension is above 0.6, indicating the scale has good internal consistency and homogeneity after establishment. (2). Relationship factors scale: The establishment of scale reliability in the study uses Cronbach s Alpha to test its internal consistency and adopts Item to Total Correlation to test correlation among all dimensions. Each sub-dimension s Cronbach s Alpha coefficient is informal interactive relationship , trust Every dimension is above 0.6, indicating the scale has good internal consistency and homogeneity after establishment. (3). Knowledge sharing scale: The establishment of scale reliability in the study uses Cronbach s Alpha to test its internal consistency and adopts Item to Total Correlation to test correlation among all dimensions. Each sub-dimension s Cronbach s Alpha coefficient is knowledge owner , organization level Every dimension is above 0.6, indicating the scale has good internal consistency and homogeneity after establishment. (4). Organizational performance scale: The establishment of scale reliability in the study uses Cronbach s Alpha to test its internal consistency and adopts Item to Total Correlation to test correlation among all dimensions. Each sub-dimension s Cronbach s Alpha coefficient is accumulated knowledge asset , enhanced associative ability Every dimension is above 0.6, indicating the scale has good internal consistency and homogeneity after establishment. The result from the study to forecast scales in terms of validity and reliability found good validity and reliability and they could be used by military units to assess effects of knowledge sharing, structure factors, and relationship factors on organizational performance. They are effective tools to be referenced and adopted. RESULT ANALYSIS Characteristic Analysis for Returned Samples (1)Status of Sample Return The research scope is on the employees of the officers, petty officers and employees for the 202nd Plant, Materiel Production Center, and M.N.D. The status of sample return is as shown in Table 2. Table 2: Status of Sample Return Issued Returns Return rate Invalid returns Valid returns Valid return rate % % Data Source:the Research

6 (2)Reliability Test After each scale of the research was implemented, Cronbach s Alpha was used to test the reliability of the total correlation coefficient. The coefficient for test result by structure factor scale is The coefficient for test result by relationship factor scale is The coefficient for test result by knowledge sharing scale is The coefficient for test result by organizational performance scale is Every scale dimension is above 0.7, higher than Nunnally(1978) suggested standard 0.7, indicating the scale has good internal consistency and homogeneity after establishment. (3)Individual Characteristic Data Analysis Among the returns, the rank distribution shows 31 employees or under (including others) at 12.4%, 174 company officers or under(including petty officer)at 69.6%, 41 officers at 16.4%, 4 colonels and above at 1.6%, indicating the returns have the majority from company officers or above (including petty officers);the position classification shows 22 supervisors of basic management level at 8.8%, 67 administration staffs at 26.8%, 161 technicians at 64.4%;gender distribution shows 211 males at 84.4% and 39 females at 15.6%;the education degree distribution shows 3 middle school or under at 1.2%, 20 high school at 8%, 210 colleges or above at 84%, 17 graduate or above at 6.8%;the age distribution shows 127 people between 26~35 at 50.8%, 113 people between 36~45 at 45.2%, 10 people of 45 at 4%;the service year distribution shows 1 people under 1 year at 0.4%, 2 people between one and three years at 0.8%, 121 people between three years and ten years at 48.4% and 126 people more than ten years at 50.4%. Descriptive Analysis of Scale Status (1)Descriptive Analysis for Knowledge Sharing In a general view, the perception of knowledge sharing by all the employees of the 202nd Plant, Materiel Production Center, M.N.D. based on their answers has average between and in Likert scale, indicating most questionnaire respondents agree the military is a knowledge-sharing organization. Especially, question 06, it is an accomplishment if you can teach others methods of handling cases or working, (average ), has received the most recognition; on the other hand, question 10, it will weaken individual s strength if you candidly teach colleagues professional knowledge or working experiences (average ),received the least recognition. (2)Descriptive Analysis of Structure Factors For structure factors, based on the answers, the questionnaire respondents have the average between and in the Likert scale for the effect of structure factors on knowledge sharing. For issues on structure factors, their average is larger than 3, indicating these issues have received consensus among employees in military. Especially question 01, employees providing knowledge or technological sharing would receive compliments or credits (average ), received the most recognition. (3)Descriptive Analysis of Relationship Factors For relationship factors, based on the answers, the questionnaire respondents have the average between and in the Likert scale for the effect of relationship factors on knowledge sharing. Their average is larger than 3, indicating these issues have received consensus among employees in military. Especially question 06, employees usually communicate/ talk in an informal occasion (break room, restroom) (average ), received the most recognition. (4)Descriptive Analysis of Organizational Performance For organizational performance, based on the answers, the questionnaire respondents have the average between and in the Likert scale for the effect of organizational performance on knowledge sharing. Their average is larger than 3, indicating these issues have received consensus among employees in military. Especially question 06, the unit has significant improvement on management of new knowledge and concepts (average ), received the most recognition. One Way ANOVA on structure factors relationship factors knowledge sharing, organizational performance by Demographic Statistical Characteristics(gender, education degree, age, years of work, rank, position)

7 (1)Variance Analysis on Gender Among the background variables in the study, the dimensional variance for structure factors, relationship factors, knowledge sharing and organizational performance was t tested. The result showed no significant difference among all dimensions. (2)Variance Analysis on Education Degree Among the background variables in the study, the test by One-Way ANOVA and Scheffe post-test showed no significant difference among all dimensions. (3)Variance Analysis on Age Among the background variables in the study, One-Way ANOVA and Scheffe post-test was to analyze results. In the aspect of structure factors, after multiple comparison of Scheff e post-test, respondents at 26~35 years old and 36 ~45 years old have more recognition on structure factors than those at 45 years old. Other dimensions showed no significant difference. (4)Variance Analysis on Years of Work Among the background variables in the study, One-Way ANOVA and Scheffe post-test was to analyze and found no difference among all dimensions. (5)Variance Analysis on Rank Among the background variables in the study, One-Way ANOVA and Scheffe post-test was to analyze results. In the aspect of structure factors, after multiple comparison of Scheffe post-test, officers and those under company officers (including petty officer) have more recognition on structure factors than employees (including others). Other dimensions showed no significant difference. (6)Variance Analysis on Position Among the background variables in the study, One-Way ANOVA and Scheffe post-test was to analyze results. In the aspect of structure factors and organizational performance, after multiple comparison of Scheffe post-test, supervisors in basic management level and administration (staff) personnel have more recognition on structure factors and organizational performance than technical personnel. Other dimensions showed no significant difference. Pearson Product-Moment Correlation Analysis for Structure Factors on Knowledge Sharing By Pearson correlation analysis, it was clearly found only knowledge owner in knowledge sharing and incentive mechanism in structure factors have significant correlation. Others have no correlation. (1). Pearson Product-Moment Correlation Analysis for Relationship Factors on Knowledge Sharing By Pearson correlation analysis, it was clearly found only knowledge owner in knowledge sharing and informal interactive relationship and trust in relationship factors have significant correlation. Others have no correlation. (2). Pearson Product-Moment Correlation Analysis for Knowledge Sharing on Organizational Performance By Pearson correlation analysis, it was clearly found accumulated knowledge asset, enhanced associative ability in organizational performance and knowledge owner in knowledge sharing, enhanced associative performance in organizational performance and organizational level in knowledge sharing have significant correlation. Others have no correlation. (3). Pearson Product-Moment Correlation Analysis for Structure Factors on Organizational Performance By Pearson correlation analysis, it was clearly found accumulated knowledge asset and enhanced associative ability in organizational performance and incentive mechanism and information technology in structure factors have significant correlation. (4). Pearson Product-Moment Correlation Analysis for Relationship Factors on Organizational Performance By Pearson correlation analysis, it was clearly found accumulated knowledge asset and enhanced associative ability in organizational performance and informal interactive relationship and trust in relationship factors have significant correlation. (5). Pearson Product-Moment Correlation Analysis for Structure Factors, Relationship Factors, Knowledge Sharing on Organizational Performance

8 By Pearson correlation analysis, it was clearly found only accumulated knowledge asset in organizational performance and organizational level in knowledge sharing has no correlation. Other dimensions have significant correlation. Regression Analysis on Structure Factors, Relationship Factors, Knowledge Sharing and Organizational Performance Use the three variables, structure factors, relationship factors and knowledge sharing as independent variables. Then, use multiple regression to study the effect of structure factors, relationship factors, knowledge sharing on organizational performance. The analytical results are as follows: (1)Multiple Regression for Structure Factors and Organizational Performance Regression equation reaches the significance level(f= F=49.007,P<0.001). The effect of structure factors on organization performance reaches significance level, indicating enhancing structure factors facilitates strengthening of organizational performance. (2)Multiple Regression Analysis for Relationship Factors and Organizational Performance Regression equation reaches the significance level(f= F=36.160,P<0.001). The effect of relationship factors on organizational performance reaches significance level, indicating enhancing relationship factors facilitates strengthening of organizational performance. (3)Multiple Regression Analysis for Knowledge Sharing and Organizational Performance Regression equation reaches the significance level (F= F=20.334,P<0.001). The effect of knowledge sharing on organizational performance reaches significance level, indicating enhancing knowledge sharing facilitates strengthening of organizational performance. In summary, the research investigates the effect of structure factors, relationship factors and knowledge sharing on organizational performance. The assumptions after verification are listed in Table 3. Table 3: Verification Table for Research Assumption Assumption Result Assumption 1: demographic characteristics (gender, educational degree, age, years of work, rank, position) shows significant difference in dimensions like structure factors, Partially valid relationship factors, knowledge sharing and organizational performance. Assumption 2: structure factors have significant correlations with knowledge sharing. Partially valid Assumption 3: relationship factors have significant correlation with knowledge sharing. Partially valid Assumption 4: knowledge sharing has significant correlation with organizational performance. Partially valid Assumption 5: structure factors have significant correlation with organizational performance. Valid Assumption 6: relationship factors have significant correlation with organizational performance. Valid Assumption 7: structure factors, relationship factors and knowledge sharing have significant correlation with organizational performance. Partially valid Assumption 8: structure factors, relationship factors and knowledge sharing have significant effect on organizational performance. Valid Data Source: the Research SUGGESTIONS Research Samples The research scope is limited to all employees of the 202nd Plant, Materiel Production Center, and M.N.D. The research suggests further research should focus on other military material production units to study the variance among structure factors, relationship factors, knowledge sharing and organizational performance. For instances, the comparison among Engineering Production Center, Procurement Center, Specification Verification Center, Chung-Shan Institute of Science and Technology. Research Scope The research scope lies in all the employees of the 202nd Plant, Materiel Production Center, M.N.D. and is only limited to plant personnel. It is suggested further research can involve employees from other units(such as staffs) and compare variances in structure factors, relationship factors, knowledge sharing and organizational performance.

9 Research Design (1). Although the scale adopted by each dimension in the research is from revisions of high-reliability and high-validity domestic scales, they were tested and expert-corrected in the research. Most scales have satisfactory reliability. However after revision scale might show linguistic difference. Most scales apply to civilian organizations and pose variance in culture and perception with military organization. Therefore, the validity test still cannot establish accuracy and applicability. (2). Any policy should have supervisor s support to achieve the goal. Thus, if the research could interview decision makers, the analysis in every dimension would be improved. (3). There are many factors to affect knowledge sharing. The research is only classified by structure factors and relationship factors. There are other factors, such as organizational culture, leadership style and nature; employee characteristics can also have different effect on knowledge sharing. They are worth further thorough study. REFERENCES Atualene-Gima K. & Haying Li.(2002)July. When does trust matter? Antecedents and Contingent Effects of Supervisee Trust on Performance in Selling New Products in China and the United States. Journal of Marketing, 66, Chang-Guei Li(1997), Performance Management and Performance Evaluation(1 st edition), Taipei: Huatai Cinye Management Consultant, translated by Jing-Wei Liu(1999), The First Book for Knowledge Management, Taipei: Shang-Jhou Publication. Cubit R. (2001). Tacit knowledge and knowledge management: The keys to sustainable competitive advantage. Organizational Dynamics, 29(4), Da-Chun Tan(1999), Knowledge Management Techniques, Accounting Research Monthly, Vol. 16,page Dixon, N. D.(2000). Common knowledge: How companies thrive by sharing what they know. Harvard Business School Press, Boston. Goth. S. C.(2002). Managing effective knowledge transfer: An integrative framework and some practice implications. Journal of knowledge Management, 6(1), Jones G. C. & Permute H. (2000). Learning and protection of proprietary assets in strategic alliances: Building relational capital. Strategic management Journal, 21, Shih-Jun Syu(1999), Management Science, Taipei:Donghua. Syao-Syun Jhang(2001), Research Methodology(revised), Taipei:Canghai Ying-Jhong Huang(1997), Human Resource Management, Taipei:Huatai.