Economics of Organizational Change Adoption: Diffusion-Curve Estimation and Forecasting for Digital Programs

Organizational change initiatives, particularly those involving digital transformation, continue to suffer from inconsistent adoption rates, leading to sunk costs and unrealized strategic value. While technology diffusion theories provide explanatory frameworks, limited research explicitly connects adoption curves to economic models of organizational investment, risk, and return. This paper investigates the economics of change adoption by integrating diffusion-curve estimation techniques with forecasting models tailored for digital program implementation. Drawing upon archival case data, simulation modeling, and survey insights from multinational organizations, the study demonstrates how logistic, Gompertz, and Bass diffusion models can be adapted to predict adoption trajectories under varying structural, cultural, and financial conditions. Key contributions include the identification of economic inflection points where investment in change initiatives yields positive returns, and the development of hybrid forecasting frameworks that combine behavioral data with financial modeling. The findings advance both theory and practice by aligning adoption curve estimation with economic decision-making, providing managers with actionable tools to optimize digital program rollouts.