A System Dynamics Framework for Market Share Forecasting in the Telecommunications Market

Abstract

Highlights: What are the main findings? The paper introduces a data-lean system dynamics framework that represents competing providers’ market shares as interacting subscriber stocks driven by bounded churn and attraction flows, coupled with a stochastic diffusion process. Monte Carlo simulation and variance-based sensitivity analysis generate coherent probabilistic forecasts and quantify how each behavioral mechanism contributes to forecast uncertainty using only aggregate data. Applied to the Greek mobile telecommunications market (2006–2022), the framework reproduces the observed evolution of market shares and delivers accurate 5-year out-of-sample forecasts that outperform a reconciled ARIMA benchmark and provide well-calibrated prediction intervals. The analysis shows that outgoing churn parameters are the primary drivers of market-share variability in this mature, near-saturated oligopoly, while volatility-related parameters and exogenous noise play only a minor role. What are the implications of the main findings? Operators should prioritize churn-reduction and targeted acquisition strategies, because outflow parameters account for most of the forecast uncertainty in future market shares. The model’s risk-informed forecasts and sensitivity results can be used to stress-test pricing, retention and marketing policies under alternative churn and attraction scenarios, helping firms balance growth against volatility in a disciplined way. Policymakers and planners can apply the framework to evaluate how regulatory changes, competitive shocks or entry/exit events would reallocate subscribers in an already saturated market, even when only aggregate data are available. By combining probabilistic forecasts with an explicit decomposition of behavioral drivers, the approach supports evidence-based decisions that sustain healthy competition, protect consumers and inform infrastructure investment. This paper presents a novel system dynamics-based framework for forecasting market share evolution in the telecommunications sector. The framework conceptualizes market share as flows of subscribers—driven by churn, attraction, and market growth—between interconnected compartments representing providers. It is designed to operate with limited available market data and incorporates stochastic processes to capture market uncertainty, enabling risk-informed forecasts. The framework is applied to the Greek mobile telecommunications market using historical data (2006–2022), with a 5-year hold-back period for validation. Results highlight the dominant role of churn management in market share variability, particularly for the incumbent provider Cosmote, while subscriber attraction parameters show moderate influence for alternative providers Vodafone and Wind Hellas. Sensitivity analysis confirms the model’s robustness and identifies key drivers of forecast variability. The proposed framework provides actionable insights for strategic decision-making, making it a valuable tool for providers and policymakers to address churn, optimize attraction strategies, and ensure long-term competitiveness in dynamic markets.