進階搜尋


   電子論文尚未授權公開,紙本請查館藏目錄
(※如查詢不到或館藏狀況顯示「閉架不公開」,表示該本論文不在書庫,無法取用。)
系統識別號 U0026-0307201416510100
論文名稱(中文) 網路外部性對於創新產品之擴散研究
論文名稱(英文) A study of diffusion model for innovation product with network externality
校院名稱 成功大學
系所名稱(中) 工業與資訊管理學系
系所名稱(英) Department of Industrial and Information Management
學年度 102
學期 2
出版年 103
研究生(中文) 潘聖雯
研究生(英文) Sheng-Wen Pan
學號 R36011199
學位類別 碩士
語文別 中文
論文頁數 50頁
口試委員 指導教授-耿伯文
口試委員-李昇暾
口試委員-林清河
中文關鍵字 擴散模型  互補品  直接網路外部性模型  間接外部性模型 
英文關鍵字 Diffusion model  Complement  Direct network externalities  Indirect network externalities 
學科別分類
中文摘要 現今科技環境變化迅速,消費者對於滿意的標準也愈來愈高,使得企業不斷在追求創新以滿足消費者的期望,近年來智慧型手機逐漸趨向多樣化功能,其中在手機應用程式快速發展下也促進了消費者對智慧型手機的選用。在競爭的市場中,了解產品擴散形態才能掌握未來市場的需求,往往企業成功的因素在於產品網路外部性的使用人數連結價值,為了對網路外部性有更深入之了解,使企業可透過適當的分析工具進行市場預測。本研究將探討在網路外部性影響下創新產品之擴散模型,除了在模型中考慮網路外部性外,並考慮載具之加入套用至模型中以進行模型之預測及分析,驗證載具的加入會提升模型的預測能力且具有較佳的適配能力,以APP軟體LINE的下載量做為本研究的實證對象,並利用模型分析網路外部性在不同產品生命週期中對擴散之影響,以提出相關建議。
本研究發現模型加入了網路外部性、互補品因素的考量後,其模型無論在配適性或預測能力上皆優於Bass模型。其模型主要考量了網路外部性相關因素應用於創新產品中,使得模型能夠更準確預測到未來的趨勢,而本研究也針對具有互補品性質之產品比較直接網路外部性模型與間接網路外部性模型的差異,其結果發現直接網路外部性模型不適用於具有互補品之產品,其原因在於直接網路外部性為單純由產品使用人數增加所引起的變化,而LINE的下載量除了產品本身的力量外,其中在使用此App軟體所搭配的載具佔了重要的角色,故了解當分析App軟體LINE下載量趨勢時,除了考慮產品本身的網路力量外,加入智慧型手機銷售量及互補品採用率後之模型更能提升準確度。
英文摘要 In the competitive market, realizing the diffusion patterns of products can help enterprise to estimate the market demand accurately and utilizing the effects of product externalities can connect with external functional activity to increase the added value.

For achieving the purpose that enterprise can use appropriate analysis tool to evaluate product market, this study propose a modified innovation product diffusion model that combined network externality and complement to illustrate the diffusion of smart phone and the contribution of App software toward the adoption of smart phone. We utilizes mobile application of Line as case to demonstrate the factor of machine device considered in the modified model that lead to better model fit and raise the explanation ability toward real case as well. In addition, the network externality effects are considered in the model, and further to discuss the influence on the growth of App Line in life cycle.

The parameter estimations show that the product diffusion with consideration of complement is not explained well by direct network externality diffusion model, because this model only illustrates the externality effect caused by the increase of users. However, the factors affect the adoption of mobile application don’t only include the value generated by the product but also the contribution of operation system embedded in machine devices. According to the case study we indicate that the modified model have better performance than Bass model in forecasting accuracy with consideration both sales of smart phone and complement adoption rate when analyzing the diffusion process of Line.
論文目次 摘要 I
ABSTRACT II
誌謝 VI
目錄 VII
表目錄 VIII
圖目錄 IX
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 2
第三節 研究流程 3
第二章 文獻探討 5
第一節 網路外部性 5
第二節 擴散模型 8
第三節 網路外部性擴散模型 17
第四節 擴散模型之參數估計 19
第三章 研究方法 22
第一節 研究架構 22
第二節 研究模式 24
第三節 參數估計與模型評估準則 27
第四章 實證分析與預測 30
第一節 應用程式軟體LINE之背景介紹 30
第二節 資料來源 33
第三節 模型之參數估計及配適能力 34
第四節 模型之預測能力 41
第五章 結論與建議 45
第一節 研究結論 45
第二節 研究限制 47
參考文獻 48
參考文獻 林瑞芸 (2012) 《消費者採用智慧型手機行動應用軟體影響因素之研究》,龍華科技大學資訊管理研究所碩士論文。
孫中璽 (2003) 《具網路外部性產品之擴散模型研究》,東華大學國際企業研究所碩士論文。
黃凱民 (2007) 《具網路外部性產業之研究-以電視遊戲機產業為例》,中山大學經濟研究所碩士論文。
陳品仁 (2006) 《創新擴散模型之改良與應用-以MP3 Player為例》,中正大學企業管理研究所碩士論文。
Bass, F. M. (1969). A new product growth model for consumer durables. Management Science, 15(5), 215-227.
Bayus, B. L. (1987). Forecasting sales of new contingent products: An application to the compact disc market. Journal of Product Innovation Management, 4(4), 243-255.
Bucklin, L. P., & Senqupta, S. (1993). The co-diffusion of complementary innovations: supermarket scanners and UPC symbols. The Journal of Product Innovation Management, 10(2), 148-160.
Casey, T. R., & Töyli, J. (2012). Mobile voice diffusion and service competition: A system dynamic analysis of regulatory policy. Telecommunications Policy, 36(3), 162-174.
Cheng, H. K., & Liu, Y. (2012). Optimal software free trial strategy: The impact of network externalities and consumer uncertainty. Information Systems Research, 23(2), 488-504.
Chou, C. F., & Shy, O. (1990). Network Effects without Network Externalities. International Journal of Industrial Organization, 8(2), 259-270.
Chun, S. Y., & Hahn, M. (2008). A diffusion model for products with indirect network externalities. Journal of Forecasting, 27(4), 357-370.
Dewenter, R., Haucap, J., & Wenzel, T. (2012). On sharing with indirect network effects between concert ticket sales and music recordings. Journal of Media Economics, 25(3), 168-178.
Economides, N. (1996). The economics of networks. International Journal of Industrial Organization,14(6), 673-699
Farrell, J., & Saloner, G. (1985). Standardization, Compatibility, and Innovation Rand Journal of Economics, 16(1),70-83
Gatignon, H., Eliashberg J., & Robertson T.S. (1989). Modeling multinational diffusion patterns: An efficient metodology. Marketing Science, 8(3), 231-247
Goolsbee, A., & Klenow, Peter J. (2002). Evidence on Learning and Network Externalities in the Diffusion of Home Computers. Jounal of Law and Economics, 45(2), 317-343.
Jain, D. C. & Rao, R. C. (1990). Effect of Price on the Demand for Durables: Modeling, Estimation, ad Findings. Journal of Business & Economic Statistics, 8(2), 163-170.
Jones, J. M., & Ritz, C. J. (1991). Incorporating distribution into new product diffusion models. International Journal of Research in Marketing, 8(2), 91-112.
Kalish, S. (1985). A new Product Adoption Model with Price, Advertising, and Uncertaint. Management Science, 31(12), 1569-1585
Kalish, S., & Lilien G. (1986), A market entry timing model for new technologiew. Management Science, 32( 2), 194-205
Katz, M., & Shapiro, C. (1985). Network externality, competition, and compatibility. American Economic Review, 75(3), 424-440.
Kim, N., Chang, D. R., & Shocker, A. D. (2000). Modeling intercategory and generational dynamics for a growing information technology industry. Management science, 46(4),496-512.
Lewis, C. (1982). Industrial and business forecasting methods: Butterworth Scientific, London.
Liebowitz, S. J., & Margolis, S. E. (1995). Path Dependence, Lock-in, and History. Journal of Law Economics & Organization, 11(1), 205-226.
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.
Mahajan, V., Muller, E., & Bass, F. M. (1990). New product diffusion models in marketing: a review and direction for research. Journal of Marketing, 54(1), 1-26.
Peterson, R. A., & Mahajan, V. (1978). Multi-product growth models. Research in marketing, 1, 201-231.
Rogers, E. M. (1962). Diffusion of Innovation. New York, NY: The Free Press.
Rogers, E. M. (1995). Diffusion of innovation (Vol. 4): New York: Free Press.
Rohlfs, J. (1974). A theory of interdependent demand for a communications service. The Bell Journal of Economics and Management Science, 5(1), 16-37.
Schmittlein, D. C., & Mahajan, V. (1982). Maximum likelihood estimation for an innovation diffusion model of new product acceptance. Marketing Science, 1(1), 57-78.
Shankar, V., & Bayus, B. L. (2003). Network effects and competition: An empirical analysis of the home video game industry. Strategic Management Journal, 24(4), 375-384.
Sharif, M. N., & Ramanathan, K. (1981). Binomial Innovation Diffusion-Models with Dynamic Potential Adopter Population. Technological Forecasting and Social Change, 20(1), 63-87.
Shapiro, C., & Varian, H.R. (1998), Information Rules: A strategic Guide to The Network Economy. Boston:Harvard Busness School Press
Shurmer, M. (1993). An investigation into sources of network externalities in the packaged pc software market. Information economics and policy, 5(3), 231-251.
Srinivasan, V., & Mason, C. H. (1986). Nonlinear least squares estimation of new product diffusion models. Marketing Science, 5(2), 169-178.
Theil, H. (1965). The analysis of disturbances in regression analysis. Journal of the American Statistical Association, 60(312), 1067-1079.
Westbrook, R. A. (1987). Product/consumption-based affective responses and postpurchase processes. Journal of Marketing Research, 24(3), 258-270.
Wu, F. S., & Chu, W. L. (2010). Diffusion models of mobile telephony. Journal of Business Research, 63(5), 497-501.
論文全文使用權限
  • 同意授權校內瀏覽/列印電子全文服務,於2024-12-31起公開。


  • 如您有疑問,請聯絡圖書館
    聯絡電話:(06)2757575#65773
    聯絡E-mail:etds@email.ncku.edu.tw