Ramayya Krishnan

A hybrid approach to supplier selection for the maintenance of a competitive supply chain

This article outlines a hybrid method, incorporating multiple techniques into an evaluation process, in order to select competitive suppliers in a supply chain. It enables a purchaser to do single sourcing and multiple sourcing by calculating a combined supplier score (CSS), which accounts for both qualitative and quantitative factors that impact on supply chain performance. By performing a cluster analysis, it draws a supplier map (SM) so as to position suppliers within the qualitative and quantitative dimensions of performance efficiency, and to select a portfolio of suppliers from supplier segments, which are different in performance with regard to key factors.

Retail Strategies on the Web: Price and Non-price Competition in the Online Book Industry

Two conflicting predictions have emerged regarding the effect of low-cost information on price. The first states that all Internet retailers will charge the same low price for mass produced goods. The second states that Internet retailers will differentiate to avoid intense price competition. Using data collected in April 1999 on the prices of 107 books in thirteen online and two physical bookstores, we find similar average prices online and in physical stores and substantial price dispersion online. Analysis of product differentiation yields no clear results. The substantial premium charged by Amazon provides indirect evidence of product differentiation. Copyright 2002 by Blackwell Publishing Ltd

Scheduling a Major College Basketball Conference

The nine universities in the Atlantic Coast Conference (ACC) have a basketball competition in which each school plays home and away games against each other over a nine-week period. The creation of a suitable schedule is a very difficult problem with a myriad of conflicting requirements and preferences. We develop an approach to scheduling problems that uses a combination of integer programming and enumerative techniques. Our approach yields reasonable schedules very quickly and gave a schedule that was accepted by the ACC for play in 1997–1998.

An Empirical Analysis of Network Externalities in Peer-to-Peer Music-Sharing Networks

Peer-to-peer (P2P) file sharing networks are an important medium for the distribution of information goods. However, there is little empirical research into the optimal design of these networks under real-world conditions. Early speculation about the behavior of P2P networks has focused on the role that positive network externalities play in improving performance as the network grows. However, negative network externalities also arise in P2P networks because of the consumption of scarce network resources or an increased propensity of users to free ride in larger networks, and the impact of these negative network externalities--while potentially important--has received far less attention.Our research addresses this gap in understanding by measuring the impact of both positive and negative network externalities on the optimal size of P2P networks. Our research uses a unique dataset collected from the six most popular OpenNap P2P networks between December 19, 2000, and April 22, 2001. We find that users contribute additional value to the network at a decreasing rate and impose costs on the network at an increasing rate, while the network increases in size. Our results also suggest that users are less likely to contribute resources to the network as the network size increases. Together, these results suggest that the optimal size of these centralized P2P networks is bounded--At some point the costs that a marginal user imposes on the network will exceed the value they provide to the network. This finding is in contrast to early predictions that larger P2P networks would always provide more value to users than smaller networks. Finally, these results also highlight the importance of considering user incentives--an important determinant of resource sharing in P2P networks--in network design.

Decision support on demand : Emerging electronic markets for decision technologies

Abstract For the individual or organization wishing to employ a scientific approach in solving decision problems, there is a plethora of relevant concepts, methods, models, and software. Yet, relative to their potential or to peer software such as database technologies, decision technologies are little used in real-world decision making. We argue that at least some of the problems that restrict the use of decision technologies are rooted in the use of conventional market mechanisms to distribute them. We propose the development of electronic markets for decision technologies, and explain how features of modem information networks offer a solution to these problems. We present a framework for comparing alternative electronic markets for decision technologies, survey and analyze several such emerging markets, and present some details on our own research initiative — DecisionNet. A distinctive feature of DecisionNet is that it consists of software agents that perform — at the market level —; functions (such as user accounting, billing and setting up the interface to a decision technology) that would otherwise need to be developed for each consumer, provider, or technology.

Designing a Better Shopbot

A primary tool that consumers have for comparative shopping is the shopbot, which is short for shopping robot. These shopbots automatically search a large number of vendors for price and availability. Typically a shopbot searches a predefined set of vendors and reports all results, which can result in time-consuming searches that provide redundant or dominated alternatives. Our research demonstrates analytically how shopbot designs can be improved by developing a utility model of consumer purchasing behavior. This utility model considers the intrinsic value of the product and its attributes, the disutility from waiting, and the cognitive costs associated with evaluating the offers retrieved. We focus on the operational decisions made by the shopbot: which stores to search, how long to wait, and which offers to present to the user. To illustrate our model we calibrate the model to price and response time data collected at online bookstores over a six-month period. Using prior expectations about price and response time, we show how shopbots can substantially increase consumer utility by searching more intelligently and then selectively presenting offers.

The Economics of Peer-to-Peer Networks

Peer-to-Peer (P2P) networks have emerged as a significant social phenomenon for the distribution of information goods and may become an important alternative to traditional client-server network architectures for knowledge sharing within enterprises. This paper reviews and synthesizes the relevant computer science and economics literatures as they relate to P2P networks, and raises important questions for researchers interested in studying the behavior of these networks from the perspective of the economics of information technology.

Incremental hierarchical clustering of text documents

Incremental hierarchical text document clustering algorithms are important in organizing documents generated from streaming on-line sources, such as, Newswire and Blogs. However, this is a relatively unexplored area in the text document clustering literature. Popular incremental hierarchical clustering algorithms, namely Cobweb and Classit, have not been widely used with text document data. We discuss why, in the current form, these algorithms are not suitable for text clustering and propose an alternative formulation that includes changes to the underlying distributional assumption of the algorithm in order to conform with the data. Both the original Classit algorithm and our proposed algorithm are evaluated using Reuters newswire articles and Ohsumed dataset.

Prospects for Operations Research in the E-Business Era

The digital economy is creating abundant opportunities for operations research (OR) applications. Several factions of the profession are beginning to respond aggressively, leading to notable successes in such areas as financial services, electronic markets, network infrastructure, packaged OR-software tools, supply-chain management, and travel-related services. Because OR is well matched to the needs of the digital economy in certain ways and because certain enabling conditions are coming to pass, prospects are good for OR to team with related analytic technologies and join information technology as a vital engine of further development for the digital economy. OR professionals should prepare for a future in which most businesses will be e-businesses.

The impact of free-riding on peer-to-peer networks

Peer-to-peer networking is gaining popularity as a architecture for sharing information goods and other computing resources. However, these networks suffer from a high level of free-riding, whereby some users consume network resources without providing any network resources. The high levels of free-riding observed by several recent studies have led some to suggest the imminent collapse of these communities as a viable information sharing mechanism. Our research develops analytic models to analyze the behavior of P2P networks in the presence of free-riding. In contrast to previous predictions, we find that P2P networks can operate effectively in the presence of significant free-riding. However, we also show that without external incentives, the level of free-riding in P2P networks is higher than socially optimal. Our research also explores the implications of these findings for entrepreneurs, network designers, and copyright holders.