10087934
Comparative analysis of multi-item online auctions: evidence from the laboratory
Abstract The dynamics of customer relationship are being reshaped by price-setting processes such as online auctions. This paper analyzes price setting process in business-to-consumer (B2C) online auctions. Typically, these auctions involve multiple identical units and utilize a variant of the traditional English-auction mechanism. We describe an online laboratory experiment that compares the efficiency of such a mechanism with a multi-item version of Vickrey's [Journal of Finance 41 (1961) 8.] second-price auction with respect to both seller's revenue and allocative efficiency. Our results reject the revenue equivalence principle and indicate that English auctions may dominate the Vickrey auctions. However, we observe that the allocative efficiency of Vickrey auctions is higher than the English auctions.
11409534
Risk profile and consumer shopping behavior in electronic and traditional channels
This paper develops an economic model that captures consumer shopping channel choices based on shopping channel characteristics and consumer risk profiles--risk-neutral or risk-averse. Analyses of results show that after making purchases through one channel, electronic or traditional, risk-averse consumers tend to be more loyal customers than risk-neutral consumers. Further, the two types of consumers may exhibit split channel behavior--risk-neutral consumers prefer one channel and risk-averse consumers prefer the other. However, risk-neutral consumers are not always more likely to prefer electronic channel than risk-averse consumers. Implications for retailer pricing strategies are discussed.
166893960
Priority pricing of integrated services networks
30721210
Economic analysis of consumer purchase intentions in electronic and traditional retail channels: competitive and strategic implications
We develop a multiattribute economic model to analyze consumer behavior for traditional and electronic channels based on consumers' risk profiles and risk-neutral or risk-averse. We then conduct comparative analyses of consumer purchase decisions to derive strategies for different channels. We study the attitudinal and economic factors that lead to specific purchase decisions under different combinations of price, delivery time, and product customization. We develop theoretical propositions concerning consumer channel switching behavior, incentives to consumers, and pricing strategies for different channels. We also use simulations to gain insights for cases where analytical model becomes intractable.
62621279
Estimating Internet Users' Demand Characteristics
We investigate two parametric approaches and one non-parametric approach toestimating Internet users' value-of-time, an important characteristic ofdemand for Internet services. The advantages of these approaches are madeclear and their limitations discussed. The models are tested with datagenerated from our similation model of the Internet economy. Given thecharacteristics of the data, we investigate parametric count-data modelsfirst. While reasonably good results are obtained on all medium- andlarge-sized jobs, the method fails on small-sized ones. Second, we develop anonparametric quasi-Bayesian update algorithm for retrieving the underlyingdistribution function of Internet users' value-of-time purely fromobservations on their choices. Compared with the parametric count-data models,good results are obtained in every case.
57631
Insights and analyses of online auctions
3094106
LIPTUS: associating structured and unstructured information in a banking environment
Growing competition has made today's banks understand the value of knowing their customers better. In this paper, we describe a tool, LIPTUS, that associates the customer interactions (emails and transcribed phone calls) with customer and account profiles stored in an existing data warehouse. The associations discovered by LIPTUS enable analytics spanning the customer and account profiles on one hand and the meta-data associated or derived from the interaction (using text mining techniques) on the other. We illustrate the value derived from this consolidated analysis through specific customer intelligence applications. LIPTUS is today being extensively used in a large bank in India. A highlight of this paper is a discussion of the technical challenges encountered while building LIPTUS and deploying it on real-life customer data.
1276171
Using Lagrangean Relaxation for Service Location Planning with QoS Constraints in Large-Scale Networks
Current trends in computing indicate that there is a great potential for service oriented computing and similar technologies, such as Cisco's Application Oriented Networks, where services provide a higher-level of abstraction to traditional applications. In such cases, providing and consuming services and establishing a relationship between consumers (users of services) and producers (providers of services) are still challenging and vastly researched aspects. We define a service location planning problem (SLP) that is novel in the approach it takes to match consumers to producers, such that the cost of providing services is minimized while taking into account quality of service constraints of throughput and delay. In previous work, we presented an integer linear programming (ILP) model to formulate the service location planning problem. In this paper, we present Lagrangean Relaxation of the model for large-scale networks. We use the approach of Trick [3] to decrease computational overheads.
6190398
Time Representation in Prolog Circuit Modelling
This paper is an examination of some issues in domain ontology and of various knowledge representation techniques for the temporal modelling of digital electronic circuits in Prolog. It should serve as an example of the advantages of such analysis, an area of relative neglect within the logic programming community.
15213964
Performance Indicators in a 802.11 WLAN Deployment
Organizations and Institutions across the world are increasingly deploying 802.11 based WLAN (in short Wi-Fi) to have mobility benefits in their operations. However, due to the nature of 802.11 technology, there are more number of challenges for an administrator in ensuring the optimum performance levels for the deployed WLAN compared to a Wired Network. Degraded performance leads to connectivity problems and low data throughput for wireless clients using the Wi-Fi network. In the presented work, we have identified a set of indicators whose values at any point of time signals a possible degradation in WLAN performance. Each of the identified indicators is explained and the behavior of same is illustrated using an example with respect to presence or absence of performance anomalies in a WLAN deployment.
62172477
A unified framework for uncertainty propagation in automatic shape tracking
Uncertainty handling plays an important role during shape tracking. We have recently shown that the fusion of measurement information with system dynamics and shape priors greatly improves the tracking performance for very noisy images such as ultrasound sequences [22]. Nevertheless, this approach required user initialization of the tracking process. This paper solves the automatic initialization problem by performing boosted shape detection as a generic measurement process and integrating it in our tracking framework. We show how to propagate the local detection uncertainties of multiple shape candidates during shape alignment, fusion with the predicted shape prior, and fusion with subspace constraints. As a result, we treat all sources of information in a unified way and derive the posterior shape model as the shape with the maximum likelihood. Our framework is applied for the automatic tracking of endocardium in ultrasound sequences of the human heart. Reliable detection and robust tracking results are achieved when compared to existing approaches and inter-expert variations.