Relational Theory of Active Systems Development (RTDAS v1.1): Structural Retention vs. Saturation in the Global B2B SaaS Market (2020–2026)

Abstract

Purpose:
To diagnose whether the volatility of the global horizontal B2B SaaS platform field (2020–2026) reflects saturation regimes or structural retention, using RTDAS v1.1 and the S-Screen operator.

Background:
The global market for horizontal B2B SaaS platforms (CRM, ERP, ITSM, HR, collaboration tools) experienced significant turbulence between 2020 and 2026, characterized by pandemic-driven growth, a sharp correction in 2022–2023, and the rapid integration of artificial intelligence. Academic and industry discourse often misinterprets this volatility as a sign of structural instability or market saturation, leading to ambiguous diagnoses. This article addresses this gap by applying the Relational Theory of the Development of Active Systems (RTDAS) v1.1, incorporating the S-Screen operator, to empirical data. Based on 31 open signals across two time slices (2020–2022 and 2023–2026), it demonstrates that the SaaS field is organized as an Unsustainable Problematic Configuration (UPC). This constitutes a self-reproducing structure where key actors (vendors, integrators, clients) derive distributed benefits from persistent complexity, high Total Cost of Ownership (TCO), and the mutation of innovations (AI, new pricing models) into additional lock-in mechanisms.

Materials and Methods:
Field-level case study using 31 open signals across two time slices (2020–2022; 2023–2026), processed through the RTDAS v1.1 diagnostic sequence with the S-Screen operator, R* formulation, and a stress test with falsification conditions.

Results:
The S-Screen operator systematically excludes the dominance of resource, procedural, and legitimation saturation, identifying the complexity dimension as an internal mechanism of the UPC rather than an external limit. The article formulates the configuration's minimal core (R*), conducts a stress test, and proposes early indicators and conditions for falsification. This work contributes to the Theory of Saturation (Manafi, 2025) and the Saturation–Collapse (SEA) model by offering an operational diagnostic tool that positions saturation as one regime among others within the development of an active system. A reproducible protocol for regime diagnosis is presented, applicable to other complex systems.

Conclusion:
The diagnosis supports structural retention (UPC) rather than a dominant saturation regime, and provides a reproducible protocol for regime diagnosis applicable to other complex systems.