Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Business
An Empirical Application Of Delone And Mclean Model In Evaluating Decision Support System In The Banking Sector Of Oman, Anu Manchanda, Saurabh Mukherjee
An Empirical Application Of Delone And Mclean Model In Evaluating Decision Support System In The Banking Sector Of Oman, Anu Manchanda, Saurabh Mukherjee
Journal of International Technology and Information Management
Banks are investing a huge amount on information systems to provide fast services to their customers and to stay competitive. Therefore it becomes necessary to measure the success of these systems. The main objective of this study is to assess the applicability of DeLone and McLean model of information systems in evaluating decision support system in the banking sector of Oman and to check the relationship among variables of the model. In order to achieve the objectives, data was collected from the managers and assistant managers using decision support system in the banks of Oman. Hypotheses were tested using correlation …
The Classification Performance Of Multiple Methods And Datasets: Cases From The Loan Credit Scoring Domain, Jozef Zurada, Niki Kunene, Jian Guan
The Classification Performance Of Multiple Methods And Datasets: Cases From The Loan Credit Scoring Domain, Jozef Zurada, Niki Kunene, Jian Guan
Journal of International Technology and Information Management
Decisions to extend credit to potential customers are complex, risky and even potentially catastrophic for the credit granting institution and the broader economy as underscored by credit failures in the late 2000s. Thus, the ability to accurately assess the likelihood of default is an important issue. In this paper the authors contrast the classification accuracy of multiple computational intelligence methods using five datasets obtained from five different decision contexts in the real world. The methods considered are: logistic regression (LR), neural network (NN), radial basis function neural network (RBFNN), support vector machine (SVM), k-nearest neighbor (kNN), and decision tree (DT). …
Improving Credit Card Operations With Data Mining Techniques, Malini Krishnamurthi
Improving Credit Card Operations With Data Mining Techniques, Malini Krishnamurthi
Journal of International Technology and Information Management
Consumer credit is ubiquitous and lending poses credit risk – the risk of economic loss due to the failure of a borrower to repay according to the terms of his or her contract with the lender. And so, managing credit risk entails estimating the potential ability of borrowers to repay their debts. Researchers have sought to identify factors that contribute to consumer risk, by using quantitative models. However, the presence of data mining techniques to identify credit risk cannot be ignored. There is a paucity of research to demonstrate the use of data mining techniques in this context, and such …
A New Approach For Evaluating The Order Fulfillment Process Options Of B2c Horizontal Portals Using Dea (Data Envelopment Analysis), Tapati Bandopadhyay, Pradeep Kumar
A New Approach For Evaluating The Order Fulfillment Process Options Of B2c Horizontal Portals Using Dea (Data Envelopment Analysis), Tapati Bandopadhyay, Pradeep Kumar
Journal of International Technology and Information Management
By using the traditional statistical or operations research methods for deciding the product-delivery logistics, the portal companies are not using their competitive advantages on being more e-enabled, informed and computationally able than their traditional counterparts. In this paper, we show some typical characteristics of the portals like their handling of a huge range of goods in terms of transactional values or volumes. Subsequently, we have identified three types of generic product-delivery logistics of the portals with various intermediate entities or trading partners. Then, a completely different approach using an extreme point method rather than the traditional central-tendency-based statistical methods has …