網際網路本身是一項創新，有人創造新的應用和新的商業模式也看到了創業機會，也有公司視它為威脅，但不可否認地有大量的資本和人才投入到與網際網路相關的產業，這些網際網路的創新和創意在網路上傳遞著，被人們了解、接受和使用，然而以人為接受創新的單位來探討網際網路在個人間如何擴散的相關的研究並不多。本論文研究以傳統創新擴散理論和擴散數學模式之貝氏模式(Bass Model)和動態模式(Dynamic Model)來描述和解釋網際網路創新擴散現象的適配性，探討網際網路創新與傳統創新在個人之間擴散時的不同特性，提出兩個假說：1.網際網路創新擴散的潛在使用者數量是變量非常數；2.相較於傳統非網際網路創新，人們對網際網路創新的採納使用受到人際關係口碑影響的內部效應比受到廣告等的外部效應要強。研究中收集十二項網際網路創新的歷年會員成長數量，以非線性迴歸分析(Non-linear Regression Analysis)方式分別估計貝氏模式和動態模式之潛在使用者數量m、外部影響係數p和內部影響係數q。結果顯示動態模式的適配性優於貝式模式，由於動態模式的潛在使用者數量m為變量，因此支持網際網路創新擴散的潛在使用者數量是變量非常數之假說。將有效的估計結果之內部影響係數q和外部影響係數p比值q/p與過去傳統非網際網路創新擴散研究結果之內部影響係數q和外部影響係數p比值比較，結果顯示僅部分網際網路創新之q/p比值高於傳統非網路創新，因此假說二得到部分支持。依此網際網路創新之擴散特性，將網際網路區分為三大類型：非網站型創新(如：Internet、ADSL、Skype)、入口網站型創新(如：PChome、Yahoo!、AOL)和利基型網站創新(如：Amazon、eBay、PayPal)，其中利基型網站之口耳相傳效應高，非網站型之廣告效應高。對於經營者而言，應利用此不同特性選擇適合的推廣行銷策略，以達到事半功倍的效果。

The diffusion of the Internet is the interest of many firms or individuals who see the Internet as an opportunity, a threat, or both. Huge amount of intellectual and real capital are invested on Internet. The more people understand the dynamics of Internet diffusion, the better they will manage the efforts put on it. The purpose of this study is to explore the extent to which the diffusion of the Internet-related innovation could be adequately described by the diffusion models and the effect of internal influence versus external influence described in the models. Two hypotheses of the Internet innovation diffusion are proposed. First, the number of potential adopters of the Internet innovation diffusion is dynamic, not constant. Second, in contrast to the traditional innovations, the diffusion of Internet innovation has stronger interpersonal communication influence than the promotional activity effect. Twelve Internet innovations are estimated in both the Bass model and the Dynamic model. The first hypothesis is fully supported, and the second hypothesis is partially supported. Based on the evidence, Internet innovations can be categorized into web-based versus non-web. The non-web Internet innovation of connection and communication like Internet, ADSL, and Skype has no significant difference of the ratio of the internal influence and the external influence effects to the traditional innovations. The segment-focused niche website, such as Amazon, eBay, and PayPal, has the strong internal influence effect. Understanding the various effects of Internet innovation diffusion can provide advantages in terms of enhancing functions and planning marketing strategies and tactics.

LIST OF TABLES v
LIST OF FIGURES vii
ABSTRACT ix
CHAPTER I: INTRODUCTION 1
1. Statement of Purpose 1
2. Research Process 4
CHAPTER II: LITERATURE REVIEW 6
1. Diffusion Theory 6
The Innovation 7
Communication 8
Social System 8
Time 9
Diffusion Research 12
2. Mathematical models of diffusion 14
Diffusion Model of Single Innovation 14
Diffusion Model of Multi-Innovations 18
3. Internet Innovation 21
4. Diffusion and Adoption of IS/IT 24
CHAPTER III: THEORETICAL BACKGROUND AND HYPOTHESES 27
1. Bass Diffusion Model 27
2. Observation and Hypotheses Development 29
Dynamic Potential Adopters 29
Stronger Internal Influence than External Influence 30
CHAPTER IV: RESEARCH DESIGN 32
1. Research Method 32
2. Research Domain 32
Adopter 32
Innovations 33
Data Source 42
3. Hypotheses Test 43
CHAPTER V: RESULT AND ANALYSIS 47
1. Basic Analysis 47
2. Potential Adopter Analysis 51
3. Ratio of External and Internal Influence Effect - Comparison to Prior Studies 52
CHAPTER VI: CONCLUSION 60
REFERENCE 62
APPENDIX 68
A. Internet User in Taiwan 68
B. ADSL Users in Taiwan 73
C. PChome Users in Taiwan 77
D. American Online (AOL) Global Users 83
E. Yahoo! Global Users 87
F. Amazon Global Users 92
G. eBay Global Users and Active Users 95
H. Global Wikipedian 102
I. PayPal Global Users 108
J. Skype Global Users 112
K. Skype Users in Taiwan 117

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