臺灣博碩士論文加值系統

由於全球競爭壓力增加、產品生命週期縮短與容易被對手模仿等因素，使得廠商必須以持續性創新來維持他們的競爭力。對高科技廠商而言，技術創新已儼然成為改善生產力、提升銷售量與廠商競爭力最基本的方法。此外由不同的觀點來確認與評估技術創新，已是現今有效管理技術的重要任務。
傳統上，對技術創新的研究強調單一模式或變數對廠商生產力與績效之影響，然而，企業經營環境持續在變化，單一模式或變數已經不足以詮釋技術創新全面性之影響。技術創新績效衡量最困難的觀點就是確認出最合適的衡量工具與方法，並提供適當的資訊來衡量與技術創新有關的各種因素。本論文中，作者試圖由系統性的觀點發展一套涵蓋無形與有形因素之技術創新績效衡量模式。換句話說，本質上技術創新應該是多重構面與多重準則。因此，技術創新績效衡量應概念化為多重準則之複雜問題且同時考量定性與定量準則之要求。
本研究首先以德非法技術來建立高科技廠商技術創新績效評估之層級網絡決策模式，再以網絡決策方法決定相互影響之構面與其準則之權重。接著因層級網絡決策模式中之準則是相互依賴且相互影響之關係，透過非可加模糊積分方法進行資訊融合並獲得綜合績效值。本研究利用 模糊測度與非可加模糊積分方法來推導出每個構面與廠商之整體績效值。經由績效創新評估模式可以提供廠商檢視他們本身從事技術創新管理之整體強處與缺點。此外，研發經理與高階管理者也可以利用此評估模式來評估與檢視廠商之技術創新能力並改善其技術創新績效，更可以充分提供經營者有用資訊且降低整體技術創新之不確定性。

Due to increase global competitive pressure, shortened product life cycles and ease of imitation, firms must continue to innovate to maintain their competitiveness. Technological innovation has become the primary basis of productivity improvements, sales volume growth, and competitiveness of firms, especially for the high-tech companies. Thus, identification and evaluation of technologies from a variety of perspectives now play important roles in the effective technological sources management.
Traditionally, technological innovation studies stressed single model or variable having effects on firm productivity and performance. However, the challenge for business environment is continually changing; single model or variable is not good enough to explain the overall impact of technological innovation. The most difficult aspect of technological innovation performance measurement is the identification of appropriate metrics and approaches that provide information concerning these facets. In this study, the researcher tried to develop a technological innovation performance measurement model and determine tangible and intangible factors from the systematical perspective. That is, technological innovation in its nature is multi-dimensional and multi-criteria. Furthermore, technology innovation performance measurement can be conceptualized as multi-criteria a complex problem which involves the simultaneous consideration of multiple quantitative and qualitative requirements.
In this empirical study, the researcher firstly utilizes the Delphi technique to build a hierarchical network structure model for evaluating the technological innovation performance measurement of high tech firms. Secondly, analytic network process (ANP) was applied to determine the importance weights of each dimension and criterion while exists interdependencies among criteria within the same dimension. Thirdly, Non-additive fuzzy integral method was then applied for information fusion and calculates the synthetic performance on a hierarchical network model structure for which criteria are interdependent and interactive. This study applied fuzzy measure and non-additive fuzzy integral method to derive the synthetic performance values of each dimension and firm. Through the technological innovation performance evaluation model can provide firms with an overview of their strengths and weaknesses with regards to technological innovation management. Furthermore, R&D managers and senior managers can apply this model to evaluate and determine the technological innovation capabilities of a firm to improve its technological innovation performance. Finally, this model may provide the useful information for managers and to reduce the overall technological innovation uncertainty.

論文提要 i
中文摘要 ii
Abstract iii
Table of Contents v
List of Tables vii
List of Figures viii
Chapter 1 Introductions 1
1.1 Research Background and Motivation 1
1.2 Statements of Problems and Purpose of the Study 4
1.3 Organization and Overview of the Study 4
Chapter 2 Literature Review 7
2.1 Concept of Technological Innovation and Its development
2.2 Definition of Technological Innovation 10
2.3 Performance Measurement 12
2.4 Analytic Network Process 14
2.5 Fuzzy Set Theory and Linguistic Variables in Fuzzy Decision Environment 18
2.6 Fuzzy Multi-Criteria Decision Making Approach 22
2.7 -Fuzzy Measure and Fuzzy Integral23
Chapter 3 Fuzzy Analytic Network Process (FANP) for Evaluating Technological Innovation Performance 29
3.1 The Delphi Technique for Building Hierarchy Evaluation Model 29
3.2 ANP Network Model for Technological Innovation Performance 35
3.3 Weights Identification Using ANP 36
3.4 Fuzzy Performance-Grade Identification and Its Defuzzifying Values 38
3.5 Development FANP for Synthetic Evaluation 43
Chapter 4 Empirical Study on High Technology Industry 48
4.1 Problem Background and Description 48
4.2 Determining the Importance Weights Using ANP Approach49
4.3 Obtaining the Fuzzy Performance Score and Its Defuzzifying Values 60
4.4 FANP for Measuring Firm Synthetic Performance 61
4.5 Summary 65
Chapter 5 Findings and Conclusions 67
5. 1 Research Summary 67
5.2 Research Findings 68
5.3 Future Study 69
Reference 71
Appendix 1 77
Appendix 2 78
Appendix 3 91

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