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研究生:陳威榮
研究生(外文):Wei-Ron Chen
論文名稱:網路外部性透明度對產品擴散之影響
論文名稱(外文):The Impact of Network Externality''s Transparency on Diffusion of Product
指導教授:呂德財呂德財引用關係
指導教授(外文):TE-TSAI LU
學位類別:碩士
校院名稱:崑山科技大學
系所名稱:企業管理研究所
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:中文
論文頁數:45
中文關鍵詞:網路外部性擴散透明度系統模擬
外文關鍵詞:Network ExternalityDiffusionTransparencySystem Simulation
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產品擴散(diffusion)是行銷領域中重要的研究議題之一。早期的產品擴散研究,很少將「網路外部性(network externalities)」納入產品擴散探討,且過去研究偏重將「Bass模型」加入各種變數來進行解析性研究。本研究則是應用系統模擬的研究方法,以「網路外部性透明度(network externality''s transparency)」之 不同分別進行實驗。其中網路外部性透明度,本研究將其分為「連續式(continuous)透明」及「間斷式(discrete)透明」兩種。所謂連續透明度為外部性資訊可立即同步傳達給潛在消費者;間斷式透明則是累積一段期間才提供給潛在消費者。
本研究結果顯示,相較於不具網路外部性之產品擴散,具網路外部性產品的擴散過程,每消費週期之首購數量會產生上下震盪起伏的現象,且該產品的擴散成長期起點亦較提前。另外,在兩種不同透明度的實驗中,具連續式透明網路外部性之產品擴散過程,其上下震盪之幅度較間斷式透明小,且網路外部性擴散進入成長期(growth)之時間點較早。

Product diffusion is the important research subject in marketing for a long time, and Bass model always play as reference basis for the diffusion research. However the past researches focus on how to embed different variables in Bass model by analytic method. The purpose of this research is the first attempt to simulate the behavior of individual consumer through their mouth of word and then evolve the phenomenon of diffusion. The main goal is, using dynamic simulation, to explore the difference of diffusion process among products with different transparency of network externality, which we classify them “continue transparency” and “discrete transparency”, the former, we mean it as the externality information is deliver to consumer immediately as it change, where as the latter we mean it as the externality information is disclosed to consumer only for a period of time.
This research results show that, the diffusion process rise and fall several times when compare to the product with no externality and its take off time is earlier. On the other hand the diffusion process of product with discrete externality rise and fall largely than the product with continuous externality, its take off time is earlier too .

目錄
中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1 研究背景 1
1.2研究動機與目的 2
1.3研究方法與流程 3
1.4論文章節之結構 4
第二章 文獻回顧 6
2.1產品擴散理論 6
2.1.1新產品成長模型 6
2.1.2擴散理論之修正 8
2.2網路外部性 12
2.2.1網路外部性定義 12
2.2.2網路外部性的來源 13
2.2.3網路外部性的效果 13
2.3網路外部性對產品擴散的影響 15
2.4網路外部性透明度 15
2.5蟻族理論 16
2.6不連續事件模擬 17
第三章 模型架構與各模組設定 18
3.1模型架構 18
3.1.1模型架構說明 18
3.1.2大眾傳播與口碑傳播 20
3.1.3消費者滿意度 21
3.1.4網路外部性與透明度 22
3.1.5費洛蒙與購買機率 24
3.2非探討變數之調整與模型測試 26
3.2.1大眾傳播與口碑傳播之變數 26
3.2.2網路外部性之變數 27
第四章 網路外部性及其透明度實驗 29
4.1連續式透明 30
4.1.1連續式透明網路外部性實驗 30
4.2間斷式透明 31
4.2.1間斷式透明網路外部性實驗 32
4.3實驗結果分析 34
第五章 結論與建議 37
5.1研究結論 37
5.2研究貢獻 38
5.2.1學術貢獻 38
5.2.2管理實務貢獻 39
5.3研究限制 40
5.4後續研究建議 40
參考文獻 41
一、中文文獻 41
二、英文文獻 41

表目錄
表2-1 Bass模型假設1之歷年研究 9
表2-2 Bass模型假設2之歷年研究 9
表2-3 Bass模型假設3之歷年研究 10
表2-3 Bass模型假設4之歷年研究 10
表2-4 Bass模型假設5之歷年研究 10
表2-5 Bass模型假設6之歷年研究 11
表2-6 Bass模型假設7之歷年研究 11
表2-7 Bass模型假設8之歷年研究 11
表2-8 Bass模型假設9之歷年研究 12
表2-9 商管領域之透明度定義分類 16
表3-1 滿意度與傳播人數關係表 21

圖目錄
圖1-1 研究流程圖 5
圖2-1 Bass模型之架構 7
圖3-1 模型架構圖 19
圖3-2 標準化商品在不同消費者市場的滿意度 22
圖3-3 網路外部性與累積消費人數的關係 23
圖3-4 累計費洛蒙與購買機率的關係圖 24
圖3-5 無網路外部性產品當期首購量之五次獨立實驗圖 26
圖3-6 無網路外部性產品累積首購量之五次獨立實驗圖 27
圖3-7 網路外部性的飽和點差異比較圖 27
圖4-1 連續式透明網路外部性實驗結果之當期產品首購量比較圖 30
圖4-2 連續式透明網路外部性實驗結果之累積首購量比較圖 31
圖4-3 間斷式透明網路外部性實驗結果之當期產品首購量比較圖 32
圖4-4 間斷式透明網路外部性實驗結果之累積首購量比較圖 33
圖5-1 透明度實驗之當期產品首購量比較圖 34
圖5-2 透明度實驗之累積產品首購量比較圖 35

中文文獻
1.孫中璽(民92)。具網路外部性產品之擴散模型研究。花蓮:國立東華大學國際企業研究所碩士論文。

2.周建宏(民91)。提高資訊透明度以因應全球化的資本市場。會計研究月刊,200。

英文文獻
3.Asvanund, A., Clay, K., Krishnan, R., & Smith, M. D. (2004). An Empirical Analysis of Network Externalities in Peer-to-Peer Music Sharing Networks. Information Systems Research, 15(2), 155-174.

4.Bass, F. M. (1969). A New Product Growth Model
for Consumer Durable. Management Science, 15, 215-227.

5.Bayus, B. L. (1987). Forecasting Sales of New Contingent Products: An Application to the Compact Disc Market. Journal of Product Innovation Management, 4, 243-255.

6.Blackwell, R. D., Miniard, P. D., & Engel, J. F. (10th ed). (2006). Consumer Behavior. Thomson South-Western.

7.Bloomfield, R., O''Hara, M., (1999). Market Transparency: Who Wins and Who Loses. The Review of Financial Studies, 12(1), 5-35.

8.Bonaccorsi, A., Rossi, C. (2003). Why Open Source software can succeed. Research Policy, 32(7), 1243.

9.Cabral, L. M. B. (2000). Introduction to Industrial Organization. Cambridge: MIT Press.

10.Chen, J. C., Lin, T. L., & Kuo, M. H. (2002). Artificial Worlds Modeling of Human Resource Management Systems. IEEE Transactions on Evolutionary Computation, 6(6), 542-556.

11.Chun, S. Y., Hahn, M. (2008). A diffusion model for products with indirect network externalities. Journal of Forecasting, 27(4), 357-370.

12.Conrad, M., Rizki, M. M. (1989). The Artificial Worlds Approach to Emergent Evolution. BioSystems, 23, 247-260.

13.Dodson, J. A. Jr., Muller, E. (1978). Models of new Product Diffusion through Advertising and Word-of-Mouth. Management Science, 24(15), 1568.

14.Dolnicar, S., Freitag, R., & Randle, M. (2005). To Segment or Not to Segment? An Investigation of Segmentation Strategy Success Under Varying Market Conditions. Australasian Marketing Journal, 13(1), 20-35.

15.Dorigo, M., Maniezzo, V., & Colorni, A. (1996). Ant system: optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man and Cybernetics Part B, 26(1), 29-41.

16.Ethiraj, S. K., Levinthal, D. (2004). Modularity and Innovation in Complex Systems. Management Science, 50(2), 159-173.

17.Fagiolo, G. (2005). Endogenous Neighborhood Formation in a Local Coordination Model with Negative Network Externalities. Journal of Economic Dynamics and Control, 29(1-2), 297-319.

18.Farrell, J., Saloner, G. (1985). Standardization, Compatibility, and Innovation. Rand Journal of Economics, 16, 70-83.

19.Fornell, C. (1992). A National Customer Satisfaction Baromere: The Swedish Experiment. Journal of Marketing, 56, 6-21.

20.Fourt, L. A., Woodlock, J. W. (1960). Early prediction of market success for grocery products. Journal of Marketing, 24(5), 31-38.

21.Gatignon, H., Eliashberg, J., & Robertson, T. S. (1989). Model Multinational Diffusion Patterns: An Efficient Methodology. Marketing Science, 8(3), 231-247.

22.Goldenberg, J., Libai, B., & Muller, E. (2001). Using Complex Systems Analysis to Advance Marketing Theory Development: Modeling Heterogeneity Effects on New Product Growth through Stochastic Cellular Automata. Academy of Marketing Science Review, 2001, 1-19.

23.Goldenberg, J., Libai, B., & Muller, E. (2010). The Chilling Effects of Network Externalities. International Journal of Research in Marketing, 27, 4-15.

24.Hellofs, L. L., Jacobson, R. (1999). Market Share And Customers’ Perceptions of Quality: When Can Firms Grow Their Way to Higher Versus Lower Quality. Journal of marketing, 63, January, 16-25.

25.Jain, D. C., Mahajan, V. & Muller, E. (1991). Innovation Diffusion in The Presence of Supply Restriction. Marketing Science, 10(1), 83-90.

26.Jain, D., Rao, R. C. (1990). Effect of Price on Demand for Durable: Modeling, Estimation, and Finding. Journal of Business and Economic Statistics, 8, 163-170

27.Jang, S. L., Dai, S. C., & Sung, S. (2005). The pattern and externality effect of diffusion of mobile telecommunications: the case of the OECD and Taiwan. Information Economics & Policy, 17(2), 133-148.

28.Jones, J. M., Ritz, C. J. (1991), Incorporating Distribution into New Product Diffusion Models. International Journal of Research in Marketing, 8, 91-112.

29.Kalish, S. (1985). A New Product Adoption Model with Pricing, Advertising and Uncertainty. Management Scienec, 31, 1569-1585.

30.Kalish, S., Lilien, G. L. (1986). A Market Entry Timing Model for New Technologies, Management Scienec, 32(2), 194-205.

31.Kapur, P. K., Singh, V. B., Sameer, A. & Yadavalli, V. S. S. (2007). An Innovation Diffusion Model Incorporating change in Adoption Rate. Management Dynamics, 16(1), 33-40.

32.Katz, M. L., Shapiro, C. (1985). Network Externalities, Competition and Compatibility. American Economic Review, 75(3).

33.Kim, M. S., Kim, H. (2004). Innovation diffusion of telecommunications : General patterns, diffusion clusters and differences by technological attribute. International Journal of Innovation Management, 8(2), 233-241.

34.Kotler, P. (8th ed). (1994). Marketing Management: Analysis, Planning, Implementation and Control. New York: Prentice-Hall Inc.

35.Levy, D., (1994). Chaos Theory and Strategy: Theory, Application, and Managerial Implications. Strategic Management Journal, 15, 167-178.

36.Liebowitz, S. J., Margolis, S. E. (1994). Network Externality: An Uncommon Tragedy. Journal of Economic Perspectives, 8(2), 133-150.

37.Lim, B. L., Choi, M., & Park, M. C. (2003). The late take-off phenomenon in the diffusion of telecommunication services: network effect and the critical mass. Information Economics and Policy, 15(4), 537-557.

38.Lu, T. T., Chen, J. C., & Liao, G. X. (2008). Aggressive or Conservative, General or Specific? A Study of Organizations Adopting Different Learning Strategies in An Artificial World. Expert Systems With Applications, 34(4).

39.Mahajan, V. E., Muller, & Bass, F. M. (1990). New Product Diffusion Models in Marketing: A review and Direction for Research. Journal of Marketing, 54(1), 1-26.

40.Mahajan, V. T., Wind, & Sharma, S. (1983). An Adoption to Repeat Purchase Diffusion Models, AMA Proceeding. American Marketing association, 49, 442-446.

41.Mahajan, V., Peterson, R. A. (1978). Innovation Diffusion in a Dynamic Potential Adopter Population. Management Science, 24(15), 1589-1597.

42.Mahajan, V., Peterson, R. A. (1979). Integrating Time and Space in Technological Substitution Models. Technological Forecasting and Social Change, 14, 231-241.

43.Mansfield, E. (1961). Technical change and the rate of imitation. Econometrica, 29, 741-766.

44.Meade, N., Isiam, T. (2006). Modelling and forecasting the diffusion of innovation - A 25-year review. International Journal of Forecasting, 22(3), 519-545.

45.Meagher, K., Teo, E. G. S. (2005). Two-part Tariffs in the Online Gaming Industry: The Role of Creative Destruction and Network Externalities. Information Economics and Policy, 17(4), 457-470.

46.Olson, J. A., Choi, S. (1985). A Product Diffusion Model Incorporating Repeat Purchase. Technological Forecasting and Social Change, 27, 385-397.

47.Ordeshook, P. C. (1986). Game Theory and Political Theory. Cambridge: Cambridge University Press.

48.Oren, S. S., Smith, S. A. (1981). Critical Mass and Tariff Structure in Electronic Communications Market. Bell Journal of Economics, 12(4), 467-487.

49.Rohlfs, J. (1974). A Theory of Interdependent Demand for a Communications Services. Bell Journal of Economics, 5, 16-37.

50.Schelling, T. C. (2006). Micromotives and Macrobehavior. New York: W. W. Norton & company, Inc.

51.Schmidt, G. M., Druehl, C. T. (2005). Changes in Product Attributes and Costs as Drivers of New Product Diffusion and Substitution. Production and Operations Management, 14(3), 272-285.

52.Shankar, V., Bayus, B. L. (2003). Network Effects and Competition An Empirical Analysis of Home Video Game Industry. Strategic Management Journal, 24(4), 375-419.

53.Shy, O. (2001). The Economics of Network Industries. Cambridge: Cambridge University Press.

54.Simon, H., Sebastin, K. H. (1987). Diffusion and advertising: The German telephone company. Management Science, 33, 451-466.

55.Steenkamp, J. B. E. M., & Baumgartner, H. (1992). The Role of Optimum Stimulation Level in Exploratory Consumer Behavior. Journal of Consumer Research, 19(12), 434-448.

56.Sterman, J. D. (1989). Misperceptions of Feedback in Dynamic Making. Organizational Behavior and Human Decision Processes, 43(3), 301-335.

57.Sterman, J. D. (1989). Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment. Management Science, 35(3), 321-339.

58.Terano, T. (2000). Analyzing Social Interaction in Electronic Communities Using an Artificial World Approach. Technological Forecasting and Social Change, 64(1), 13-21.

59.Tomochi, M., Murata, H., & Kono, M. (2005). A consumer-based model of competitive diffusion: the multiplicative effects of global and local network externalities. Journal of Evolutionary Economics.Heidelberg, 15(3), 273-295.

60.Weerahandi, S., Dalal, S. R. (1992). A Choice-Based Approach to the Diffusion of a Service: Forecasting Fax Penetration by Market Segments. Marketing Science, 11(1), 39-53.

61.Xie, J., Sirbu, M. (1995). Price Competition and Compatibility in the Presence of Positive Demand Externalities. Management Science, 41(5), 909-926.

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