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博碩士論文 etd-0723110-024701 詳細資訊
Title page for etd-0723110-024701
論文名稱
Title
智慧資本、運籌能耐與運籌績效關係之研究
The Relationships among Intellectual Capital, Logistics Capabilities and Logistics Performance
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
109
研究生
Author
指導教授
Advisor
召集委員
Convenor
黃良志
none
口試委員
Advisory Committee
葉榮椿, 溫金豐, 陳世哲
none; none; none
口試日期
Date of Exam
2010-07-21
繳交日期
Date of Submission
2010-07-23
關鍵字
Keywords
人力資本、結構資本、關係資本、運籌能耐、運籌績效
Structural capital, Human capital, Relational capital, Logistics performance, Logistics capabilities
統計
Statistics
本論文已被瀏覽 5625 次,被下載 0
The thesis/dissertation has been browsed 5625 times, has been downloaded 0 times.
中文摘要
中文摘要
隨著企業對運籌服務之需求增加,統籌企業物流配送作業的運籌服務業者地位也越趨重要,因此如何增強運籌能耐及提升運籌績效,成為一個重要的課題。此外,傳統偏重有形的實質資產為公司基礎的觀念已逐漸式微,無形的智慧資本對於績效的優劣正逐漸扮演著舉足輕重的地位。根據資源基礎觀點,智慧資本是組織競爭優勢的主要來源,而且也會影響組織績效。然而智慧資本領域的學者與專家鮮少對靜態的智慧資本與動態的運用智慧資本能力進行區辨,而本研究認為這是兩種不相同的概念,希望瞭解運籌服務業者運用智慧資本對其運籌績效的影響。因此,本研究結合資源基礎與動態能耐觀點,以運籌服務公司之高階主管為調查對象,採用結構方程式的統計分析方法,來探索智慧資本、運籌能耐、及運籌績效間彼此的關係。
過去學者比較側重有形資源、能耐與績效的研究,較少從無形資源的角度來研究此議題,因此本研究首先藉由文獻探討歸納出人力資本、結構資本與結構資本做為無形資源--智慧資本的構面。其次,本研究依據學者的實證結果,認為運籌能耐除了直接影響運籌績效之外,也是其運用智慧資本的關鍵因素。而且由於運籌能耐是一複雜的概念,若要對其進行衡量,應該要進一步釐清該構念,甚至建構適合的衡量指標,提出較為完整的、且符合信度與效度的衡量量表,方能正確地加以衡量,因此運籌能耐包括服務能耐、創新能耐、與彈性能耐。最後在釐清各個學者對各變項的定義,再經由各項假設推演後,提出本研究之研究架構。
本研究以台灣運籌服務業者做為研究樣本,共寄發放出1,033份問卷,回收有效問卷109 份,整體的有效問卷回收率為10.6 %。最後利用結構方程模式(Structural Equation Modeling, SEM)分析,研究結果發現:運籌服務業者的結構資本、關係資本與運籌能耐會正向影響運籌績效;人力資本、結構資本與關係資本也會正向影響運籌服務業者的運籌能耐。雖然人力資本對運籌績效沒有顯著關係存在,然由分析結果發現人力資本可透過運籌能耐之中介效果間接影響運籌績效。因此,本研究建議運籌服務業者欲提升運籌績效時,應積極強化其智慧資本,進而提升運籌能耐,以提升運籌績效。
Abstract
ABSTRACT
As enterprises have increased the demand for logistics services, the role of logistics service providers (LSPs) as home bases for merchandise transportation and distribution has consequently become increasingly important. Therefore, how to strengthen the logistics capability and promote the logistics performance has become an important topic. In addition, traditionally the perspective of treating tangible assets as the location of firm’s value has been gradually diminished. The intangible intellectual capital is increasingly playing a pivotal position for the firm’s performance. Researchers studied the field of intellectual capital argued that intellectual capital was the main source of organizational competitive advantages. Besides, they thought that the better the intellectual capital a company has, the better the business can have the ability to generate performance. However, researchers seldom distinguished static intellectual capital from dynamic capability for utilizing intellectual capital. Whereas, this study proposed that these two constructs were different concepts, and would like to explore the impact of utilizing intellectual capital on logistics performance. Consequently, this study integrated the concept of RBT and dynamic capability to offer a conceptual model, a survey of LSPs was undertaken in order to examine the relationships among intellectual capital, logistics capabilities and firm performance, using the structural equation modeling technique (SEM) analysis method.
Previous researches had concerned the tangible resources, capabilities and firm performance, however, less from the perspective of intangible resources to study this subject. Hence, after reviewing the relevant literature, we conclude human capital, structural capital, and relational capital as dimensions of intellectual capital. Furthermore, from the empirical results of related scholars’ researches, this study argues that it has a directly significant effect of logistics capabilities on logistics performance, and logistics capabilities are the critical factors for utilizing intellectual capital. Moreover, this research proposes that logistics capabilities are complex constructs. Therefore, we should clarify these constructs and provide an appropriate measurement tool with reliability and validity if we would like to measure them. Consequently, logistics capabilities were identified: service capability, innovation capability, and flexibility capability. Finally, after clarifying the definition and extracting the components of each variable from the literature review, this research deduced several hypotheses and formed the research framework.
In this study, we take logistics service providers in Taiwan as the study sample. A total of 1,033 questionnaires were hand delivered and the remaining 109, valid and complete, were used for quantitative analysis. The useable response rate was 10.6%. A structural equation modeling (SEM) approach was employed to test the research hypotheses. Results indicated that structural capital, relational capital, and logistics capabilities had a significant positive effect on logistics performance. Results also indicated that human capital, structural capital, and relational capital had a positive effect on LSPs’ logistics capabilities. While human capital was not found to have a direct positive effect on LSPs’ logistics performance, it was found to have an indirect effect on logistics performance mediated by logistics capability. According to the results, LSPs should enhance the intangible resource - intellectual capital, further heighten their understanding of logistics capabilities and identify how such capabilities may affect logistics performance, therefore develop effective logistics strategies.
目次 Table of Contents
TABLE OF CONTENTS
Chapter 1 INTRODUCTION 1
1-1 Research Background and Motives 1
1-2 Research Objectives and Scope 6
Chapter 2 LITERATURE REVIEW 9
2-1 Logistics Capabilities 9
2-2 Logistics Capabilities and Logistics Performance 20
2-3 Intellectual Capital 22
2-4 Intellectual Capital and Logistics Capabilities 34
2-5 The Mediating Effect of Logistics Capability 36
Chapter 3 METHODOLOGY 40
3-1 Research Framework 40
3-2 Hypotheses 40
3-3 Variable Definition and Measurement 41
3-4 Sampling and Data Collection 48
3-5 Common Method Variance 51
3-6 Data Analysis 52
Chapter 4 RESULTS AND ANALYSIS 56
4-1 Exploratory Factor Analysis 56
4-2 Confirmatory Factor Analysis 61
4-3 Empirical Results 69
Chapter 5 CONCLUSIONS AND IMPLICATIONS 77
5-1 Conclusions and Contributions 77
5-2 Implications 78
5-3 Limitations 80
5-4 Future Research Suggestions 81
REFERENCES 84
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