AN INTEGRATED KPI FRAMEWORK FOR ORGANISATIONAL INFORMATION SYSTEMS: MAPPING SEVEN GOVERNANCE - LEVEL METRICS TO ISO/IEC 25010:2023 ATTRIBUTES

Abstract

Information systems have become strategic organizational assets, but classical success literature in the field of information systems offers qualitative models without predetermining which measurement attributes implement each dimension. This article proposes an integrated framework of key performance indicators (KPIs) that bridges this gap by mapping seven new government - level indicators to a vocabulary of measurement attributes taken from the ISO/IEC 25010:2023 standard. The subject of the study is an integrated framework of key performance indicators (KPIs) for evaluating organizational information systems at the government level. The purpose of the study is the group of organizational information systems along with their dimensions of quality, success, and risk in private and public sector deployments. The aim of the paper is to formulate, justify and formulate an integrated framework that maps seven governance - level metrics: Organization - Wide Effectiveness (OWE), Decision Lag (DL), Artificial Intelligence Adoption (AIA), Management Attention Index (MAI), Executive Engagement Score (EES), Risk Response Compliance (RRC) and Risk Mitigation Response Rate (RMAR) – to 25 measurable quality attributes taken from the ISO/IEC 25010:2023 standard. Mapping or suggesting dependencies is done using 37 literature - based dependency links. To achieve this goal, the paper addresses the following tasks:

• To organize classical information systems success theory, technology acceptance models and contemporary key performance indicator (KPI) hierarchies into a single conceptual vocabulary.
• To define the seven governance - level metrics in a form that is ready to be measured using variables observable from organizational data.
• Build an explicit dependency mapping between the seven metrics and the 25 characteristics of ISO/IEC 25010:2023.
• Formulate sector - specific weighting profiles for private and public sector deployments; and specify a three - stage empirical validation plan.

As a result of the study, a literature - based framework is presented that combines classical information systems success theory with contemporary constructs of AI adoption, management engagement, and project risk governance. The framework is implemented using a three - tier architecture, produced for both private and public sector deployments. The framework is illustrated using a use case diagram and a customer journey map, and is based on a life cycle interpretation of risk metrics based on a defect profile. A three - stage empirical validation plan (Delphi panel, case implementation, and cross - sector Partial Least Squares Structural Equation Modeling: PLS - SEM survey) is proposed for further research.