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系統識別號 U0026-0812200915091656
論文名稱(中文) 新產品開發團隊知識來源對產品知識創新及產品績效之影響─以團隊成員對新知識共識程度為干擾變項
論文名稱(英文) The Influence of Knowledge Source of NPD Team Members on Product Knowledge Innovation and Project's Performance - Interpretation Consensus as a Moderator.
校院名稱 成功大學
系所名稱(中) 國際企業研究所碩博士班
系所名稱(英) Institute of International Business
學年度 97
學期 2
出版年 98
研究生(中文) 李世音
研究生(英文) Shih-Yin Li
學號 R6696104
學位類別 碩士
語文別 英文
論文頁數 78頁
口試委員 口試委員-李國瑋
指導教授-蔡明田
口試委員-莊立民
中文關鍵字 共識程度  知識來源  團隊凝聚力  創新程度  新產品開發專案績效 
英文關鍵字 Cohesiveness  Interpretation Consensus  Knowledge Source  Innovativeness  NPD project performance 
學科別分類
中文摘要   新產品開發除了是企業重要的價值創造活動,亦能幫助企業維持持久性競爭優勢。現今競爭激烈、變化快速的環境縮短了產品生命週期,也促使企業更加重視新產品開發之相關課題。
  許多學者指出新產品開發屬於知識密集的活動,過去一些文獻中探討了組織既有知識對資訊創新、新產品創造力以及新產品績效之影響,但實證結果無法證實組織既有知識與資訊創新間存在顯著之關聯。故本研究根據之前文獻之建議從內、外部知識獲得切入,加入新產品開發團隊成員對新知識解釋之共識程度為干擾變數,希望能找到與新產品創新存在顯著關係之前置變項;另外並從過去學者所提出的理論整理出有關新產品創新程度對專案效率、效果造成之影響,並配合實證方式來驗證這些假設。
  本研究以台灣高科技產業上市公司為研究對象,採取分層抽樣選取250間公司,以專案為單位就每一間公司發放3份問卷,共發放750份問卷,問卷詢問對象為公司新產品開發團隊成員及專案負責人或主管,實際回收131份有效問卷,回收率為17.47%。
  實證結果發現,內部知識獲得與產品知識創新間存在顯著之正向關係、干擾變數對兩者間之關係存在顯著的負向影響,外部知識獲得可能受到not invented here (NIH) syndrome影響,與產品知識創新之間無顯著關係;此外,由於研究對象特別之產業特性,使得產品創新程度與新產品開發效率、效果間分別皆存在顯著之正向關係;團隊凝聚力和團隊成員對新知識解釋之共識程度間則存在顯著的正向關係。
英文摘要   The continuous development and market introduction of new products is an important determinant of sustained company. A combination of intense competition, fragmenting markets, and technical diversity has brought the effective management of product development to the top of the competitive agenda in many industries. Some scholars described NPD as a knowledge-intensive activity considering knowledge as the source of innovation and creativity. However, the results of previous studies can not tell a significant relationship between organization existing knowledge and innovative information. For the reason, we try to find some factors which may significantly affect product knowledge innovation. In addition, we made some hypotheses according to the prior research. Hoping that through the empirical test, we can have a further understanding on how new product innovativeness affect the effectiveness and efficiency of new product respectively.
  A random stratified sampling method was used to choose 250 Taiwan’s high technology public firms, listed in the TEJ database. For the 750 mailed questionnaires, 131 were completed yielding a response rate of 17.47%.
  The results display the positive relationships between (1) cohesiveness and interpretation consensus, (2) internal knowledge acquisition and product knowledge innovation, (3) product knowledge innovation and new product innovativeness, and (4) product innovativeness and NPD effectiveness and efficiency. Furthermore, the moderating effect of interpretation consensus weakens the relationship between internal knowledge acquisition and product knowledge innovation.
論文目次 摘 要 I
Abstract II
誌 謝 III
Table of Contents IV
List of Tables VI
List of Figures VII

Chapter 1 Introduction 1
1.1 Research Background and Motivations 1
1.2 Research Objectives 5
1.3 Structure of the Research 5
1.4 Research Procedure 6
Chapter 2 Literature review and Hypotheses 8
2.1 NPD Project Performance 8
2.1.1 NPD Effectiveness 8
2.1.2 NPD Efficiency 9
2.2 Knowledge Source 10
2.2.1 Internal Knowledge Acquisition and Product Knowledge Innovation 11
2.2.2 External Knowledge Acquisition and Product Knowledge Innovation 13
2.3 Product Knowledge Innovation and New Product Innovativeness 15
2.4 New Product Innovativeness and NPD Performance 16
2.5 Cohesiveness and Interpretation Consensus 18
2.6 The Moderating Effect of Interpretation Consensus 19
Chapter 3 Research Design and Methodology 21
3.1 Research Framework 21
3.2 Research Hypotheses 22
3.3 Construct Measurement 23
3.3.1 Internal Knowledge Acquisition 23
3.3.2 External Knowledge Acquisition 24
3.3.3 Product Knowledge Innovation 25
3.3.4 New Product Innovativeness 26
3.3.5 Cohesiveness 28
3.3.6 Interpretation Consensus 29
3.3.7 NPD Performance 30
3.3.8 Control Variables 33
3.4 Data Collection and Sampling 33
3.5 Characteristics of Respondents 34
3.6 Data Analysis Procedure 36
3.6.1 Descriptive Statistic Analysis 36
3.6.2 Factor Analysis 36
3.6.3 Item-to-total Correlation 37
3.6.4 Internal Consistency Analysis (Cronbach’s alpha) 37
3.6.5 Multiple Regression Analysis and Moderated Hierarchical Regression Analysis 37
Chapter 4 Analysis and Results 39
4.1 Factor Analysis and Reliability Test 39
4.2 Regression Results 45
4.2.1 Hierarchical regression analyses for the Relationship between Knowledge Sources and Product Knowledge Innovation 46
4.2.2 The Moderating Effect of Interpretation Consensus between Knowledge Sources and Product Knowledge Innovation 46
4.2.3 Regression Analysis for the Relationship between Cohesiveness and Interpretation Consensus 48
4.2.4 Regression Analysis for the Relationship between Product Knowledge Innovation and New Product Innovativeness 49
4.2.5 Regression Analysis for the Relationship between New Product Innovativeness and NPD Performance 50
Chapter 5 Conclusions and Suggestions 52
5.1 Research Result 52
5.2 Discussion and Implications 54
5.3 Limitation and Future Research 56
References 58
Appendix Questionnaire 70
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