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Subscription-based digital services have become a central business model across software, streaming, membership platforms, curated commerce, replenishment services, and digitally mediated retail. Their appeal rests on replacing irregular transactions with continuing customer relationships that generate recurring revenue, richer behavioural data, and stronger possibilities for long-term engagement. Despite this growth, the literature on digital subscriptions remains fragmented. Studies often examine subscription architecture, customer lifetime value, churn prediction, or engagement separately, which limits understanding of how revenue generation, retention management, and value renewal interact as a connected system. The review shows that subscription performance cannot be understood through acquisition growth or churn reduction alone. Sustainable subscription management depends on aligning revenue metrics, customer experience, predictive retention systems, and ongoing value creation across the subscriber lifecycle. The article argues for an integrated view of digital subscription strategy. Future research must connect financial logic with behavioural retention and value renewal, while managers must move beyond reactive churn control toward proactive lifecycle governance.

Digital firms increasingly operate through more than one revenue logic. Freemium tiers, subscriptions, transaction fees, marketplace commissions, advertising, and data-enabled monetization often coexist within the same business model. This multiplicity has become central to business model innovation in digital environments. Despite this practical reality, the literature on digital revenue models remains fragmented. Freemium research often focuses on conversion, subscription research on retention, marketplace research on platform transactions, and data monetization research on privacy and value extraction. As a result, the combined strategic role of these revenue logics remains insufficiently integrated. The review identifies four major revenue logics: freemium and subscription logic, marketplace and transaction-based logic, data-enabled revenue logic, and portfolio-level diversification logic. It shows that these logics can complement one another by linking acquisition, retention, transaction volume, personalization, and customer lifetime value. However, it also finds tensions involving cannibalization, privacy risk, platform governance, customer fairness, and strategic complexity. The review concludes that digital revenue diversification should not be treated as the simple addition of revenue streams. It is a deliberate process of designing, aligning, and governing multiple monetization mechanisms within a coherent business model. Future research should examine how firms configure, evolve, and govern multi-logic revenue portfolios over time.

Digital business has expanded the number and variety of revenue models through which firms capture value from software, platforms, data, digital services, and online ecosystems. Subscription, freemium, marketplace, pay-per-use, licensing, and data-enabled models are now widely used across sectors, but their conceptual boundaries are often blurred. This makes it difficult for researchers and managers to compare models systematically. The problem addressed in this article is the lack of a clear taxonomy for distinguishing digital revenue models in business management. Existing terminology often mixes pricing mechanisms, business model architectures, customer access rights, platform intermediation, and data monetization under overlapping labels. As a result, revenue model analysis may become imprecise, fragmented, or overly case-specific. The objective of this article is to develop a rigorous taxonomy of digital revenue models based on explicit classification criteria. The taxonomy classifies digital revenue models into six categories: subscription, freemium, marketplace, pay-per-use, licensing, and data-enabled models. These categories are differentiated according to revenue generation logic, payment structure, value unit, customer relationship, scalability mechanism, and governance requirement. The resulting taxonomy provides definitions, sub-types, comparative criteria, and governance implications for each model. It contributes a shared vocabulary for studying digital revenue strategies and offers managers a practical tool for designing, combining, and governing revenue portfolios. The article concludes that digital revenue model selection should be treated not only as a monetization choice but also as a strategic governance decision.