Siva Sankaran

A Framework for Designing a Global Information Network for Multinational Humanitarian Assistance/Disaster Relief

Large-scale Humanitarian Assistance/Disaster Relief (HA/DR) operations, particularly in developing countries, require the intervention and aid of various agencies from all over the world in a concerted and timely manner. As a result, HA/DR operations involve dynamic information exchange, planning, coordination and above all negotiation. Although a number of studies have reported the benefits of using information and communication technologies to support negotiation activities, it remains unclear how such technologies could be adapted to large-scale HA/DR operations. This paper examines negotiational issues involved in a multinational HA/DR environment and presents a framework that would help in developing a Global Information Network (GIN). The proposed framework can be used to assess and characterize individual disaster situations so that the GIN functional and design requirements can be accurately identified early. Future implications to GIN architecture are also discussed.

A Multi-Attribute Negotiation Support System with Market Signaling for Electronic Markets

Despite the rapid growth of technology and Internet-based markets, many of the current systems limit themselves to price as the single dimension variable and offer, if at all, only minimal negotiation support to the consumer. In the real world, commercial transactions take into account many other parameters both quantitative and qualitative such as product quality, speed, reputation, after sales service, etc. This paper discusses how these multiple attributes can be captured to augment standard negotiation processes in order to support electronic market transactions. Using a combination of utility theory and multicriteria decision-making, we propose heuristic algorithms to discover potential trades. In addition, the approach is included within a larger framework that incorporates market-signaling mechanisms. This not only allows for the systematic evolution of negotiation positions among buyers and sellers but can ultimately lead towards improving both market transparency and efficiency. To illustrate the multiple criteria model coupled with the dynamic market signaling framework, we report in this paper the implementation of a Web-based clearinghouse that serves the real estate market.

Group decision and negotiation support in telemedicine: an application of intelligent mobile agents as non-human teleworkers

Rapid advances of the Internet, multimedia technology and virtual reality have opened new opportunities for organizations to re-design their traditional functional units often separated by vast distances into a virtually cohesive and cost effective enterprise. This paper proposes an Internet-based framework for supporting collaborative work among human and non-human teleworkers. The proposed framework enables the geographically dispersed organization to distribute work across the Internet and embed intelligent software agents, as teleworkers, capable of supporting decision and negotiation to facilitate implementation of complex distributed decision making. The proposed framework is being simulated on a telemedicine project.

A Web-based correctional telemedicine system with distributed expertise

Due to increasingly tougher and mandatory sentencing laws, the U.S. has experienced a sharp increase in the prison population during the last decade. Correctional facilities face unique challenges in providing health care to a population that has a history of physical, mental and psychological abuse. Telemedicine is an innovative way to bring health care to prisons in a safe and cost-effective manner. The steady proliferation of the Internet, its versatility and low cost are ushering in new possibilities for providing telemedicine through such a cyberspace medium. This paper discusses the workflows involved in correctional health care environments and develops an object-oriented architecture for a Web-centric telemedicine system. The prototype uses relational tables to represent expert knowledge and ActiveX programming for initiating and coordinating the consultation sessions over the Internet. The prototype has the ability to deal with single physician consultations as well as with distributed multiple experts in more complex diagnostic sessions.

Improving Online Course Performance Through Customization: An Empirical Study Using Business Analytics

The number of educational courses offered online is growing, with students often having no choice for alternative formats. However, personal characteristics may affect online academic performance. In this study, the authors apply two business analytics methods multiple linear/polynomial regression and generalized additive modeling (GAM) to predict online student performance based on six personal characteristics. These characteristics are: communication aptitude, desire to learn, escapism, hours studied, gender, and English as a Second Language. Survey data from 168 students were partitioned into training/validation sets and the best fit models from the training data were tested on the validation data. While the regression method outdid the GAM at predicting student performance overall, the GAM explained the performance behavior better over various predictor intervals using natural splines. The study confirms the usefulness of business analytics methods and presents implications for college administrators and faculty to optimize individual student online learning. KEywORdS Generalized Additive Modeling, Online Learning, Online Performance, Personal Factors, Predictive Analytics, Regression