In this thesis, we study different Internet pricing schemes and how they can be applied to a multiple ISP environment. We first take a look at the current Internet architecture. Then the different classes that make up the Internet hierarchy are discussed. We also take a look at peering among Internet Service Providers (ISPs) and when it is a good idea for an ISP to consider peering. Moreover, advantages and disadvantages of peering are discussed along with speculations of the evolution of the Internet peering ecosystem. We then consider different pricing schemes that have been proposed and study the factors that make up a good pricing plan. Finally, we apply some game theoretical concepts to discuss how different ISPs could interact together. We choose a pricing model based on a Stackelberg game that takes into consideration the effect of the traffic variation among different customers in a multiple ISP environment. It allows customers to specify their desired QoS in terms of maximum allowable end-to-end delay. Customers only pay for the portion of traffic that meet this delay bound. Moreover, we show the effectiveness of adopting this model through a comparison with a model that does not take traffic variation into account. We also develop a naïve case and compare it to our more sophisticated approach.

In this thesis, we study different Internet pricing schemes and how they can be applied to a multiple ISP environment. We first take a look at the current Internet architecture. Then the different classes that make up the Internet hierarchy are discussed. We also take a look at peering among Internet Service Providers (ISPs) and when it is a good idea for an ISP to consider peering. Moreover, advantages and disadvantages of peering are discussed along with speculations of the evolution of the Internet peering ecosystem. We then consider different pricing schemes that have been proposed and study the factors that make up a good pricing plan. Finally, we apply some game theoretical concepts to discuss how different ISPs could interact together. We choose a pricing model based on a Stackelberg game that takes into consideration the effect of the traffic variation among different customers in a multiple ISP environment. It allows customers to specify their desired QoS in terms of maximum allowable end-to-end delay. Customers only pay for the portion of traffic that meet this delay bound. Moreover, we show the effectiveness of adopting this model through a comparison with a model that does not take traffic variation into account. We also develop a naïve case and compare it to our more sophisticated approach.

This dissertation is a compilation of three essays that analyze price dispersion in an online retail marketplace. Price dispersion is a measure of the variation in prices that sellers charge for products. Online price dispersion has been thoroughly analyzed in the past decade as it has numerous implications for firm pricing strategy as well as consumer welfare. Chapter 1 of this dissertation offers a literature review of price dispersion research, and discusses key explanations as to why this phenomenon exists on the web. Also, a literature review of shop-bots is presented as they are similar to online marketplaces and form the basis of the three studies. Chapter 2 is the first study, and it establishes the existence of price dispersion in online marketplaces and offers a comparison with price dispersion in shop-bots. It is determined that online marketplaces may have less variation than on shop-bots, yet the price dispersion is still high. Chapter 3 is the second study and it explains much of the dispersion found in the online marketplace through differences in seller service quality and seller reputation. A seller's reputation was found to be the key contributor to variation in the online marketplace hence, study 3, which is chapter 4 of this dissertation, employs an experimental approach designed to offer a perspective of buyers and sellers to determine why price varies with reputation and if consumers value the reputation score. It was determined that buyers prefer sellers with strong long run reputation scores more than sellers with strong short-term reputation scores. Based on these reputation scores sellers want to try to offer a higher price than consumers are willing to pay, and sellers think that a strong score conveys higher levels of trust than buyers believe. This mismatch between how sellers think consumers respond, and how the consumers actually respond could be another driver of price dispersion online. A discussion of the implications of these research studies is offered in Chapter 5. / Business Administration

因服務商品的天然特性，使服務業者即使在均衡時仍常存在結構性的剩餘產能而造成了社會資源的浪費。 　　本論文旨在研究以類似經濟學中的差別訂價（Price-Discrimination）概念，配合網際網路的載體平台，業者使用多種不同的價格方案銷售同一服務商品的策略。 　　多種不同的價格方案因為滿足了多種不同需求強度的消費者，而能擴大交易量，並增加了業者的收益。然而這些價格方案中所附加的條件與限制，透過預期及學習，最後可能改變了消費者的偏好與行為模式，而出現業者原本計算以外的結果。 　　本論文首先歸納各種現有的多重訂價方式，以此為基礎發展一個具有訂購時間順序及典型供需關係的市場模型，邀請受測者扮演消費者在其中模擬消費，而由實驗者扮演業者，在市場模型中實施不同的多重訂價策略，藉此觀察消費者實際採購的結果與實驗者預期的異同，記錄並採討其中的現象與發現。 　　實驗的最終總結：（一）各種以訂購時間進行差別訂價的策略對消費者行為及業者收益產生的影響；（二）如何改善多重訂價實際應用的效果；（三）對多重訂價策略擬定流程的建議；及（四）在網路平台上實施多重訂價策略的展望。

The aim of the work is to examine the issue of pricing network resources so as to ensure fair and efficient resource-sharing among users. The basic question we address is: Do there exist simple pricing schemes such that fair and efficient resource-sharing is ensured, even though (i) individ-ual users are concerned with maximizing their own net benefits, and (ii) a user alternates between data-limited and infinite-data phases? The Internet provides congestion control through the Transport Control Protocol TCP). TCP congestion control is dependent on voluntary participation of cooperative end users. If everyone uses TCP, congestion could be managed. However, it can be mathematically shown that it is economically more favorable for users to violate TCP rules. The published literature suggests pricing as a mechanism to control congestion. The context of operation is as follows. Each user is assumed to have a utility function which is a concave in-creasing function of the rate at which she sends data through the network. The problem is to find the vector of users' rates such that the sum of all users' utility functions is maximized, subject to resource capacity constraints. This constrained optimization problem can be solved in a central-ized manner if all the utility functions are known. In practice, however, the utility functions are not known and there is no central authority. In the literature this optimization problem has been decomposed into two sub-problems such that the knowledge of utility functions is not required. These problems are solved independently by the network and the users. It has been shown that at system optimum, the network computed vec-tor of rates and users’ choice of prices are in equilibrium and they also solve the system optimi-zation problem of maximizing sum of utilities of all users. But in all related work, the authors as-sume that users have infinite amount of data to sustain the system-optimal data rates indefinitely. In practice, however, users may run out of data at times. We propose a pricing scheme in which, under certain conditions, the following is possible. If some users run out of data, and hence are not able to inject traffic at their respective system op-timal data rates, it is possible for others with plenty of data to transmit above their system opti-mal rates. This allows efficient utilization of the resource at all times. Further, it is possible to compel users above optimal rates to back down when, at a later point of time, data-limited users are back with enough data. This ensures that fairness is maintained.

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Multicast has long been considered an attractive service for the Internet for the provision of multiparty applications. For over a decade now multicast has been a proposed IETF standard. Though there is a strong industry push towards deploying multicast, there has been little multicast deployment by commercial Internet Service Providers (ISPs) and more importantly most end-users still lack multicast capabilities. Depending on the underlying network infrastructure, the ISP has several options of implementing his multicast capabilities. With significantly faster and more sophisticated protocols being designed and prototyped, it is expected that a whole new gamut of applications that are delay sensitive will come into being. However, the incentives to resolve the conflicting interests of the ISPs and the end-users have to be provided for successful implementation of these protocols. Thus we arrive at the following economic questions: What is the strategy that will enable the ISP recover his costs ? How can the end-user be made aware of the cost of his actions ? Naturally, the strategies of the ISP and the end-user depend on each other and form an economic game. The research problems addressed in this thesis are: A pricing model that is independent of the underlying transmission protocols is prefered. We have proposed such a pricing scheme for multicast independent of the underlying protocols, by introducing the concept of pricing points* These pricing points provide a range of prices that the users can expect during a particular time period and tune their usage accordingly. Our pricing scheme makes both the sender and receiver accountable. Our scheme also provides for catering to heterogeneous users and gives incentive for differential pricing. We explore a number of formulations of resource allocation problems arising in communication networks as optimization models. Optimization-based methods were only employed for unicast congestion control. We have extended this method for single rate multicast. We have also devised an optimization-based approach for multicast congestion control that finds an allocation rate to maximize the social welfare. Finally we also show that the session-splitting problem can also be cast as an optimization problem. The commonly used "max-min" fairness criteria suffers from serious limitations like discriminating sessions that traverse large number of links and poor network utilization. We provide an allocation scheme that reduces discrimination towards multicast sessions that traverse many links and also improves network utilization.