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A Model of Diffusion of Digital Info...
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Wang, Jue.
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A Model of Diffusion of Digital Information Goods: Roles of a Key Agent.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
A Model of Diffusion of Digital Information Goods: Roles of a Key Agent./
作者:
Wang, Jue.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:
340 p.
附註:
Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
Contained By:
Dissertation Abstracts International78-12B(E).
標題:
Information technology. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10277776
ISBN:
9780355266887
A Model of Diffusion of Digital Information Goods: Roles of a Key Agent.
Wang, Jue.
A Model of Diffusion of Digital Information Goods: Roles of a Key Agent.
- Ann Arbor : ProQuest Dissertations & Theses, 2017 - 340 p.
Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
Thesis (Ph.D.)--George Mason University, 2017.
This dissertation attempts to study and explore marketing strategies that enable providers to leverage the "key agent" in the diffusion of digital information goods. By a "key agent" I mean any individual of the type described in the literature under the names connector, maven, persuader, opinion leader, influencer, innovator, and early adopter. Additionally, a digital pirate has much in common with a key agent. My approach is to explicitly represent diffusion processes between individual consumers using social networks and agent-based models, and my approach determines effective marketing strategies for digital content providers via learning classifier systems.
ISBN: 9780355266887Subjects--Topical Terms:
532993
Information technology.
A Model of Diffusion of Digital Information Goods: Roles of a Key Agent.
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This dissertation attempts to study and explore marketing strategies that enable providers to leverage the "key agent" in the diffusion of digital information goods. By a "key agent" I mean any individual of the type described in the literature under the names connector, maven, persuader, opinion leader, influencer, innovator, and early adopter. Additionally, a digital pirate has much in common with a key agent. My approach is to explicitly represent diffusion processes between individual consumers using social networks and agent-based models, and my approach determines effective marketing strategies for digital content providers via learning classifier systems.
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In the existing research on the diffusion of innovations there are several areas that are not sufficiently studied and which this dissertation addresses. First, little extant work has been conducted on developing effective marketing strategies which actively manage how new products diffuse. Specifically, while a variety of promotion strategies, pricing strategies, and product feature choices have been investigated, these are typically looked at individually. My approach permits the synthesis of effective strategies in an integrated fashion that considers these several dimensions simultaneously.
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Second, while processes associated with the diffusion of generic innovations have been extensively studied, there has been much less focus on digital information goods. Digital information goods are unmaterialized, requires high cost in creation, distribution cost is variable, and most importantly, the near $0 marginal cost of duplication of such good gives them special properties, such as making them vulnerable to various kinds of illegal activities, including digital piracy. Although there exists some research on digital piracy, few of them pay attention to the impacts of piracy on the diffusion process. In this dissertation, I will focus exclusively on such goods.
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Third, although the agent-based diffusion model on generic products utilize various network topologies, the existing research on digital information goods does not use social networks explicitly. In this dissertation, I study diffusion processes in realistic social networks -- small-world networks which explicitly represent each potential adopter and their social connections.
520
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Fourth, most research in this area neglects the role of competition between digital content providers. My dissertation provides effective marketing strategies for providers competing in the same markets.
520
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Lastly, classical mathematical approaches hold the advantages of simplicity and tractability. However, their failure to consider non-linear interactions among individuals, social networks, as well as heterogeneity and adaptations of individuals, make them special cases of the more general computational formalism that I have adopted and prevents them from generating realistic results.
520
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In this dissertation, I build models to simulate the market of digital information goods as a complex adaptive system. The models develop dynamic and self-learning marketing strategies in the context of potential adopters connected via social networks. Those marketing strategies are able to dynamically adjust various marketing factors, including prices, promotion costs, and/or piracy detection costs through an entire diffusion process. The resulting strategies would enable digital content providers to leverage a key agent to speed up new product diffusion and increase profits in both monopoly and duopoly environments. Also, the models demonstrate that the profits and the diffusion speed are also influenced by the topologies of social networks and location of the key agent in networks.
520
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This dissertation attempts to answer the following research questions: What are the characteristics of successful marketing strategies? What is the impact of network topologies? Does the position of a key agent in a network matter? How do a monopoly and a duopoly marketing environment differ with respect to above questions?
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This is a rich area of research and I have used modern computational methodologies to investigate it broadly. I believe that my results are interesting and the methodology I have employed will be useful down the road as successive generations of scholars investigate problems of the type investigated here. (Abstract shortened by ProQuest.).
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