International Journal of Information Technology & Decision Making

Although verbal and numerical scales are commonly used in the Analytic Hierarchy Process for pairwise comparisons, new experiments with computer-based visual tools confirm that ratio preferences can be effectively and efficiently elicited using adjustable visual tools and simultaneous comparisons, as well. Such an improved approach shows promise in the design of a new class of multi-criteria decision support system both for individual and group decisions.

This research focuses on developing a model that can be used to assess the performance of Small to Medium-Sized Manufacturing Enterprises (SMEs). The model will result from the integration of a decision tool called the Analytical Hierarchy Process (AHP) and a data analysis model called Data Envelopment Analysis (DEA). This research demonstrates that by eliminating flaws and taking advantage of each methodology's specific characteristics in identifying and solving problems, the new integrated AHP/DEA model appears to be a logical and sensible solution in multi-criteria decision-making problem.

This paper develops a new model for evaluating and selecting the vendor using an integrated approach of Grey Relational Analysis (GRA) along with an Analytical Hierarchy Process (AHP) in a Forward Supply Chain Model (FSCM). The paper aims to demonstrate how the model can help in solving such decisions in practice. It also examines the structure of the decision hierarchy, whether it can represent vendor selection decisions in reality and whether it covers all key factors affecting vendor selection choices. The effectiveness of the GRA model is illustrated with an Original Equipment Manufacturing (OEM) industry in southern part of India and the results of GRA were validated using the result obtained from AHP. The proposed model helps the industry to effectively select the vendor.

Although several previous studies have investigated the success factors and implementations of data warehouses, only few of them have explored the end-users' perceptions of data warehouses. Moreover, none of these previous studies were conducted in a company outside North America. Thus, this study was conducted to identify the data warehousing system characteristics affecting end-users' usage and perceived impact of using data warehouses in Korean financial companies. A research model for end-users' usage and perceived impact of using data warehouses was developed based on the Technology Acceptance Model and the IS Success Model. Then, a survey questionnaire was design to collect data from the data warehousing users in four leading Korean financial companies. We analyzed these data to test the proposed hypotheses by using Structural Equation Modeling. Results of this study suggest that Data Quality and End-user Support and Training are significant system characteristics affecting end-users' usage of data warehouses and perceived impact of data warehouses.

For the past few years, a steady growth has been observed in the Internet-based commerce activities in Singapore and Asia-Pacific region. However, there has been very limited study that empirically investigates the socio-economic factors and their influence on the adoption of electronic commerce (e-commerce) by consumers in Singapore. This study seeks to fill some of the gaps in this area. Viewing such a medium as a form of new innovation, the five socio-economic characters namely gender, age, income level, education level and the exposure to the Internet were hypothesized to see whether there was any relationship between these five factors and the consumer's willingness to adopt e-commerce. The results indicate that income level; education level and exposure to the Internet were significant predictors in explaining the rate of adoption of e-commerce. However, contrary to general beliefs, this study showed that the gender and the age of consumers are not important factors for the adoption of e-commerce in Singapore. This study may help the e-merchants and policy makers to better understand consumer behavior and attitude towards e-commerce so that suitable changes can be made to make e-commerce more attractive and popular in Singapore and the Asia-Pacific region.

E-commerce over the Internet has become an attractive means of conducting business in today's world. However, the principles of classical economics demand a fresh insight before they can be adapted to the market structure presented by the Internet. Here, we investigate markets for goods that are characterized by an experience-limited supply curve. We propose an algorithm that maximizes the welfare in the e-market by maximizing the combined profit of the buyers and sellers. For this, the buyers and sellers must reveal their value and cost curves to a trusted intermediary who can determine the transaction that maximizes their joint welfare. We show that accurate revelation of hidden profits offers better incentives, both to the buyers and the sellers, than inaccurate or incomplete revelation.

Wavelet Shrinkage using DWT has been widely used in de-noising although DWT has a translation variance problem. In this study, we solve this problem by using the translation invariant DWT. For this purpose, we propose a new complex wavelet, the Real-Imaginary Spline Wavelet (RI-Spline wavelet). We also propose the Coherent Dual-Tree algorithm for the RI-Spline wavelet and extend it to the 2-Dimensional. Then we apply this translation invariant RI-Spline wavelet for translation invariant de-noising. Experimental results show that our method, when applied to ECG data, the medical image and the textile surface inspection can obtain better de-noising results than that of conventional Wavelet Shrinkage.

This paper considers how best to sequence the acquisition of new locations (e.g. office park buildings, multi-tenant units, etc.) to expand the coverage area or fill in the geographic footprint of a network service provider or other business-service activities. Consider several locations, candidates for acquisition, on the plane. Each location will generate a certain revenue stream for the service provider if it is acquired. In addition, once a location has been acquired (i.e. served), it may be less expensive to acquire other nearby locations. The problem addressed in this paper is: Given a finite budget for acquisitions and a model for the acquisition costs, how to sequence the acquisitions to maximize the total new revenue from the locations acquired? A specific cost model is proposed, an integer programming formulation of the problem and its transformations presented. Properties of the models and of the optimal solution are discussed. Finally, an effective heuristic method intended for applications is developed. Features of the solutions are demonstrated by a numerical study.

The program package for identification of river water excessive pollution sources located between two controlled cross-sections of the river is described in this paper. The software has been developed by the authors on the basis of mathematical models of pollutant transport in the rivers and statistical hypotheses checking methods. The identification algorithms were elaborated with the supposition that the pollution sources discharge different compositions of pollutants or (at the identical composition) different proportions of pollutants into the rivers.