Data monetization capability: from the systematic literature review to the proposition of a multidimensional model

Abstract

Purpose: This study explores the underexplored field of data monetization and value creation within Information Systems (IS). Despite the growing interest in leveraging data for financial and operational gains, a literature gap exists in systematically examining the interplay between data-related terms such as monetization, value, capabilities, insights, and performance.Design/Methodology/Approach: Conducted as a Systematic Literature Review (SLR), the study analyzed 148 articles from the Scopus database using PRISMA guidelines and the Bibliometrix package. Synthesizing existing knowledge sheds light on trends in major IS journals and challenges faced by organizations in extracting value from their data.Findings: The study reveals influential trends in IS literature on data monetization and uncovers challenges faced by organizations in this domain. Proposing a multidimensional theoretical model, the research integrates information management and data monetization capabilities, contributing to advancing scientific knowledge in IS research.Practical Implications: The study offers actionable strategies for organizations to monetize data effectively, enhance business agility, and improve performance, guiding them toward becoming data-driven.Originality/Value: Contributing to the Theory of Administration within IS research, this study conducts a comprehensive analysis of data monetization, synthesizes literature trends, and proposes an innovative theoretical model integrating information management and data monetization capabilities.