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期刊影響力之研究
No full textWhile conducting journal ranking, selecting measure is crucial. Different measures will lead to different ranking results. Generally speaking, these measures could be classified in three categories. The first category is the Author-Based measures which ranks journals by the publishing preference of the authors. The second category is the Citation-Based measures which ranks journals based on the number of citations. The last category is the Perception-Based measures which ranks journals by active scholars' opinions. Many journal ranking methods are thus defined in terms of the measure(s) in either one of these categories. While many measures have been proposed in the literature, little has been done on the relations amongst measures. Nevertheless, not much work has been done on ranking journals by combining measures from different categories. Therefore, this thesis presents the results on (1) the relations between publishing intensity and publishing breath, (2) the relations between Eigenfactor and raw citations, and (3) a new ranking method called Knowledge Transfer Impact.
Given a set of active scholars and a period of time, publishing intensity (PI) of a journal is defined as the total number of publications appear in the journal that are co-written by the active scholars. Publishing breadth (PB) is defined as the total number of active scholars who have publications in that journal. On the other hand, the definition of Eignefactor is intricate. Suppose an article is randomly picked from any journal. The reader reads the article and then randomly picks another article in the references and reads it. The process repeats until no article can be picked again. The Eigenfactor of Journal-J is the proportion of times that the articles being picked in the process that are from Journal-J. Raw citation is the total number of times a journal has been cited by the published articles. While PI and PB have been applied in journal ranking, their dependency has not been investigated. So do the Eigenfactor and the raw citations, little has been done to investigate if there is any relation between them. In this regard, this thesis presents empirical analyses on the relation between different measures, with focus on six fields namely Artificial Intelligence, Information Science and Library Science, Management, Anthropology, Geography, and Nursing.
To investigate the relation between publishing intensity and publishing breadth, we first extract the list of journals from the JCR 2012 edition. The list of active scholars of a field is compiled based on three rules: (1) an active scholar must currently be an editorial member of a journal which is in our journal list (published more than 15 years), (2) an active scholar must be affiliated with one of the Top 25 US universities compiled by US News, and (3) an active scholar must have publications in the field during 1999 to 2003. The last rule ensures that an active scholar has been active in the field for more than ten years. Based on the lists of journals and active scholars, PI and PB for each journal were counted from the Thomas Reuter WoK Database. Finally, we analyze the log-log relation between PI and PB of the journals in the list. Results show that log PI and log PB have log-linear relation. The same result appears in all six fields. As the six fields have quite diverse natures, we argue that this log-linear relation is a common behavior across other research fields.
To investigate the relation between Eigenfactor and raw citations, we also extract the list of journals from the JCR 2012 Version and screen out those journals which have life time less than 15 years. The Eigenfactors are thus simply retrieved from the JCR 2012 database. For the raw citations, we count for each journal the total number of citations in between the years 2006 to 2010. Finally, we analyze the log-log relation between the Eigenfactors and the raw citations of the journals in the list. Results show that Eigenfactors and the raw citations have log-linear relation. The same result appears in all six fields. As the six fields have quite diverse natures, we argue that this log-linear relation is a common behavior across other research fields.
A good journal should satisfy two conditions. First, it has to attract very high quality research from active scholars. Second, it should attract lots of readers to read the paper and then follow the research, which means having high dissemination power. Therefore, a better journal ranking method should consist of measures from both author-based and citation-based categories. It leads to the development of a new method called Knowledge Transfer Impact (KTI), which is defined as the multiplication of publishing intensity and Impact Factor. In essence, it measures the number of new knowledge which is inspired by the articles published in a journal. From the ranking results, it is found that KTI supplements the current journal ranking methods by trading off the biases from either citation-based or author-based journal ranking methods.目前在學術界有許多期刊排序因子，我們可以依照因子的定義將之分為三大類。分別是Author-Based：觀察作者偏好與出版習慣、Citation-Based：觀察引用次數，以及Perception-Based：詢問專家意見。而在Author-Based中，一項特別的排序方法Publication Power Approach採用了兩個因子，一為Publishing Intensity(出版密度)，二為Publishing Breadth(出版寬度)，給定一組活躍的學者(Active Scholars)以及一段特定的時間範圍，一本期刊的出版密度可被定義為該組學者在該本期刊出版篇數的總數量，而出版寬度則是該組學者中曾經在該本期刊中出版過一篇文章以上的總數量；雖然出版密度與出版寬度已經被套用在期刊排序方法上面，但兩者之間的關係並沒有深入討論。
有鑑於此，本論文提供實際的數據分析去探討出版密度與寬度的關係，焦點將放在六個不同的領域之上，該六領域包含人工智慧、資訊科學與圖書科學、管理學、護士學、人類學以及地理學。對每個領域，我們從Journal Citation Report (JCR)資料庫2012版本中取得該領域的期刊列表。接著，一組活躍的學者應該滿足以下三項條件：(1) 活躍的學者應要擔任該領域任一期刊現任編輯，(2) 活躍的學者應要在美國Top 25 公立大學內任教 (3) 該活躍的學者應該在1999-2003年間出版過一篇以上的文章。最後一項規則確保學者在該領域中活躍時間超過10年以上，接著，我們將選出來合格的期刊以及學者藉由Thomson-Reuter Web of Knowledge資料庫去計算出每本期刊之出版密度與寬度，最後，我們分析log-log在兩者之間的關係，結果顯示出版密度跟出版寬度有log的線性關係。在經過六個不同領域的檢驗之後，log-log關係也顯現出相同的結果，我們相信這個log線性關係在其他領域也能適用。得到上述的結果，我們很好奇此結果是否適用在相同分類中的排序因子之間，因此，我們一併探討了Eigenfactor與Raw citations之間的關係。
最後，回到期刊排序因子探討，現今有許多種期刊排序因子，但每一個都有相關的缺點，單獨使用其中一種因子無法完美呈現出最客觀的結果，許多缺點需藉由不同因子的結合才能克服，一本好的期刊應該能吸引高質量的研究文章，也應吸引更多的讀者來閱讀並做後續研究；我們提出新的排序方式：'Knowledge Transfer Impact(知識轉移因子)'，該方法結合了前文所提的出版密度以及目前普遍使用的Impact Factor，將出版者的偏好以及讀者的引用次數納入考量中，希望反應出最真實的排序結果。在文中，我們將知識轉移因子套用在AI的領域並列出其他排序方式之結果，提供讀者更多元的排序方案。TABLE OF CONTENTS
CHAPTER 1 INTRODUCTION………………………………......………………1
1.1 Problems………………………………………………………...……..……..1
1.2 Thesis Organization…………………………………………………….…….3
CHAPTER 2 MEASURES FOR JOURNAL INFLUENCE......…………….…….5
2.1 Author-Based Measures……………………….…………………….……..5
2.1.1 Publication Power Approach………….……………………….……...5
2.1.2 Author Affiliation Index……………….……………………….……..7
2.2 Citation-Based Measures…………………….………………………………7
2.2.1 Impact Factor……………………….….……………………………..8
2.2.2 Raw Citations………………………..…………….………………….9
2.2.3 Eigenfactor…………………………….…………….………………..9
2.2.4 H-index……………………..………….………….…………………10
2.2.5 C-index……………………..………….……………….……………10
2.2.6 G-index……………………..……….………………….……………11
2.2.7 SCImago Journal Rank………………………………..……………..11
2.3 Perception-Based Measures …………………………………..……………11
2.3.1 Expert Survey……………………………………………..…………12
2.3.2 Delphi Method……………………………………………………….12
CHAPTER 3 MEASURES RELATIONS: PRELIMINARY RESULTS.……… 14
3.1Fellow-Based Publishing Intensity/Breadth…………………………..……..14
3.1.1 Methodology………………………………………………….……..14
3.1.2 Log-Linear Relation…………………………………………………15
3.1.3 Journal Ranking…………………………………………………..…18
3.2 Eigen factor & Raw Citations……………………………………………....18
3.2.1 Methodology………………………………………………………...18
3.2.2 Log-Linear Relation…………………………………………………19
CHAPTER 4 MEASURES RELATIONS: COMPREHENSIVE RESULTS.......20
4.1 Publishing Intensity and Publishing Breadth………………………...……..20
4.1.1 Methodology……………………………………………...…………22
4.1.2 Results…………………………………………………….…………26
4.2 Eigenfactor and Raw Citations……………………….……………………..30
4.2.1 Methodology……………………………………………….………..31
4.2.2 Results……………………………………………………………….31
CHAPTER 5 KNOWLEDGE TRANSFER IMPACT……………………………36
5.1 Methodology…………………………………………….………………….36
5.2 Results………………………………………………………………………39
CHAPTER 6 CONCLUSION…...………………………………….…………….. 40
REFERENCES…..……………….……………….……………………….………..42
APPENDIX…………………………………………………………………………44
Appendix A: AAAI fellows list…………………….………...…………………44
Appendix B: IEEE CIS fellows list……………………………………………..45
Appendix C: 2013 Top 25 Public Universities in US……...……………………48
Appendix D: Demonstration of the data collection processes (PI&PB)…..……51
Appendix E: Demonstration of the data collection processes (Eigenfactor & Raw
citations)…...……………………………………...……………...5
營運管理與服務管理之研究
No full textBy surveying on the history of operations and service management (OSM), it is found that the evolution of the principles in OSM is essentially governed by four major trends: (1) increasing complexity of production process, (2) expanding scope of quality, (3) increasing focus on services and (4) advancing development of technologies. Besides, two phenomena are observed. First, there is a persistent increasing demand on the product features and service contents. Customers expect products to have more additional features. Second, no suitable models have been developed for designing operations and organization. Without proper design models for operation design, a gap exists between the strategic level and the operations level. Based on the survey, the possible future trends of operations and service management can be deduced.此篇論文主要是研究在營運管理與服務管理領域中概念之演進。藉由研究後發現，它們的演進可分為以下四個趨勢：(1)生產過程越來越複雜；(2)品質的範圍不斷的擴大；(3)服務越來越受到重視；(4)科技的進步。在這四個趨勢之下，發現了兩個重要的現象。第一個現象是顧客對於產品和服務的要求增加，顧客希望產品要有更多附加的功能；第二個現象則是缺乏一套用於設計流程及組織的模型，而這些模型對企業策略實行是很重要的。缺乏這些模型，最終將會導致企業之策略層面決策與操作層面實行的落差，企業會不知道如何實行決策者所制定的策略。最後，透過研究營運管理與服務管理概念之演進，來推斷其未來之發展。1. INTRODUCTION -------------- 1
2. INCREASING COMPLEXITY OF PRODUCTION PROCESSES ------ 3
2.1 Division and Specialization of Labors ------ 3
2.2 Interchangeable Parts -------------- 4
2.3 Scientific Management -------------- 4
2.4 Assembly Line -------------- 5
2.5 Modular Production -------------- 6
2.6 Lean Manufacturing -------------- 6
2.7 Mass Customization -------------- 8
2.8 Global Outsourcing -------------- 9
3. EXPANDING SCOPE OF QUALITY -------------- 10
3.1 Quality Control -------------- 10
3.2 Total Quality Control -------------- 12
3.3 Total Quality Management -------------- 12
3.4 ISO 9000 Series -------------- 13
3.5 Six Sigma -------------- 15
4. INCREASING FOCUS ON SERVICES -------------- 17
4.1 First Self-service Store -------------- 17
4.2 Service Economy -------------- 17
4.3 Production Line Approach to Service ----------- 18
4.4 Service Blueprint -------------- 19
4.5 Service Quality Model -------------- 19
4.6 Servitization -------------- 20
4.7 Service Productization -------------- 21
4.8 Experience Economy -------------- 21
4.9 Service Outsourcing -------------- 22
4.10 Emerging Area of Research -------------- 23
4.11 The 2nd Generation of Servitization ----------- 24
5. ADVANCING DEVELOPMENT OF TECHNOLOGIES ------------- 26
5.1 Automation -------------- 26
5.2 Information Technologies -------------- 27
5.2.1 Personal Computer & Network -------------- 27
5.2.2 Internet -------------- 28
5.2.3 Mobile & Wireless Communications ------------- 30
6. FINDINGS AND FUTURE TRENDS -------------- 31
6.1 Increasing Complexity on Production Processes --32
6.2 Expanding Scope of Quality -------------- 32
6.3 Increasing Focus on Services -------------- 34
6.4 Advancing Development of Technologies ---------- 35
7. CONCLUSION -------------- 36
REFERENCES -------------- 3
服務系統模型設計
No full textIn software engineering, several models are combined for system design and analysis. This concept is same in service science, service management, service engineering (SSME) for designing a service system. Though lots of service researchers have proposed models for designing a service delivery process, multi-model framework for holistic design of a service system has yet to be revealed. In the thesis, we have selected five models from the area of management and software engineering. These five models can provide a holistic design of a service system. Moreover, they are simple enough to be adopted by management professionals. People involved in a service system also can comprehend and utilize the models easily. These five models include business model, service blueprint, sequence diagram, actor network and organization structure. We will complete the holistic design in four steps, namely business modeling, service encounter design, core operation design and organization design. By giving an example of designing an America style restaurant, we elucidate the way of applying these models and how to use these models to analyze a service system.在軟體工程中，系統分析與設計需要用到多種模型。在服務科學中，設計一個服務系統同樣需要用到多種模型。雖然很多服務研究學者提出用來設計服務傳遞流程的模型，但是一個用來設計總體服務系統的多模型架構卻尚未被提出。有鑑於此，本論文從管理及軟體工程界中選出了五種模型，這五種模型不只可以組成一套用來設計總體服務系統的模型，它們也都夠簡單以至於可以被管理專業人員所採用。而且，所有包括在服務系統中的人都可以輕易地了解並使用這套模型。這五種模型分別是商業模式圖、服務藍圖、流程圖、行為者網路以及組織結構圖。我們將這套設計方法分為四個步驟，第一個步驟是商業模式設計，第二步驟是服務接觸設計，第三步驟是核心流程設計，最後一個步驟是組織結構設計。在本論文中，我們以一家美式餐廳的用餐服務為例來描繪這套模型的運作，以及它們如何用來分析服務系統。1.INTRODUCTION------------------------------------------1
2.SERVICE ENGINEERING-----------------------------------5
3.EXISTING DESIGN MODELS--------------------------------8
3.1.Service Blueprint-----------------------------------9
3.2.Process Chain Network------------------------------13
3.3.Sequence Diagram-----------------------------------16
3.4.Comparisons Among These Models---------------------18
3.4.1.Service Blueprint vs. Sequence Diagram-----------18
3.4.2.Service Blueprint vs. Process Chain Network------18
3.5.Other Models---------------------------------------19
3.5.1.Component Business Model-------------------------20
3.5.2.Agent Based Model--------------------------------20
3.5.3.Computational and Configurable Service System Model -------------------------------------------------------21
3.5.4.Service Systems Meta-Model-----------------------22
4.COMPLETE DESIGN MODELS-------------------------------23
4.1.Business Model-------------------------------------25
4.2.Service Encounter Design---------------------------26
4.3.Core Operation Design------------------------------27
4.3.1.Convert the Service Blueprint to Sequence Diagram---------------------------------------------------------29
4.3.2.Augment the Suppliers Interactions---------------29
4.3.3.Augment the Management Process-------------------29
4.3.4.Augment the Actions Aligning Strategies----------30
4.4.Organization Design--------------------------------36
5.FACILITATE ANALYSIS----------------------------------41
5.1.Qualitative Analysis-------------------------------41
5.2.Mathematical Analysis------------------------------41
5.3.Simulation Analysis--------------------------------42
5.4.Value Network Analysis-----------------------------42
5.5.Supply Chain Analysis------------------------------43
5.6.Information System Requirement Analysis------------43
5.7.Technology Requirement Analysis--------------------44
5.8.Other Analysis-------------------------------------45
5.8.1.Gap Analysis-------------------------------------45
5.8.2.Market Analysis----------------------------------45
6.DESIGN PRINCIPLE-MODULARITY--------------------------46
7.CONCLUSION-------------------------------------------48
REFERENCE----------------------------------------------49
APPENDIX-----------------------------------------------52
A.The receptionist stand, decoration, and equipment of the restaurant-----------------------------------------52
B.Specifying the jobs in a restaurant by pseudo code---5
Going Beyond Counting First Authors in Author Co-citation Analysis
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are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
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Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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