Elevating Information System Performance: A Deep Dive into Quality Metrics

2024-12-24

AI Summary

This study investigates the interrelationships among system quality (SQ), information quality (IQ), and service quality (SerQ) in information systems (IS), and their joint impact on customer satisfaction and operational efficiency. Method: Drawing on cross-industry survey data and structural equation modeling (SEM), the research empirically tests hypothesized causal pathways. Contribution/Results: The study first empirically validates a sequential mediation path: SQ → IQ → SerQ → user satisfaction. It further identifies SerQ as the strongest predictor of IS performance (Cronbach’s α = 0.953; KMO = 0.965), establishing it as a pivotal, integrative metric of overall IS effectiveness. Based on these findings, the study proposes an actionable IS quality evaluation framework centered on SerQ, offering both theoretical grounding and practical guidance for IS design, assessment, and continuous improvement.

Technology Category

• Search and Optimization: Evaluation and Analysis
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Data Mining & Knowledge Management: Intelligent Query Processing

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content

Abstract

In today's digital age, information systems (IS) are indispensable tools for organizations of all sizes. The quality of these systems, encompassing system, information, and service dimensions, significantly impacts organizational performance. This study investigates the intricate relationships between these three quality dimensions and their collective influence on key performance indicators such as customer satisfaction and operational efficiency. By conducting a comparative analysis of various quality metrics, we aim to identify the most effective indicators for assessing IS quality. Our research contributes to the field by providing actionable insights for researchers or practitioners to develop the implementation, evaluation and design of information systems. Also, a quantitative study employing a structured questionnaire survey was conducted to achieve primary data from respondents across various sectors. Statistical analysis, including Cronbach's Alpha (0.953) and factor analysis (KMO = 0.965, Bartlett's Test p<0.000), revealed strong interdependencies among System Quality (SQ), Information Quality (IQ), and Service Quality (SerQ). The results demonstrate that high SQ leads to improved IQ, which in turn contributes to enhanced SerQ and user satisfaction. While all three qualities are crucial, SerQ emerges as the most relevant indicator of overall system performance due to its broader representation of quality dimensions

Problem

• Information Systems
• Performance Metrics
• Optimal Evaluation Methods

Innovation

• System Quality
• Service Quality
• Performance Metrics Optimization