PRIORITIZING PERFORMANCE EVALUATION FACTORS OF EVENT-BASED INFORMATION SYSTEMS USING INTERPRETIVE STRUCTURAL MODELING

This paper is aimed at the application of Interpretive Structural Modeling (ISM) for prioritizing the factors associated with the performance evaluation of event-based information management system (EBIMS). The study identified thirteen such critical factors deciding the performance of Event-Based Information Systems. Literature review along with experts' opinions were collected to arrive at the final thirteen factors. In this paper, the authors have used Interpretive Structural Modeling (ISM) approach to interpret the interdependency among the selected factors. In addition, MICMAC (cross-impact matrix multiplication applied to classification) analysis is also performed to illustrate the relative driving and dependence power among the selected factors. This paper infers that event processing algorithm, data volume and quality, and hardware and software along with query complexity are the most dominating factors which have the highest driving power and the minimum dependence power as they drive other factors and sit at the top of the interpretive structure model.