This study aimed to design and validate a sustainable marketing model centered on digital transformation in Iran's automotive industry, using an exploratory mixed-methods approach. In the qualitative phase, semi-structured interviews were conducted with 15 academic experts and senior automotive managers, and data were analyzed using grounded theory and MAXQDA software. In the quantitative phase, a researcher-developed questionnaire based on qualitative findings, with a five-point Likert scale, was distributed among 200 managers and experts, and data were analyzed using partial least squares (PLS) via SMART PLS. Qualitative findings revealed causal conditions including institutional and regulatory pressures, changes in consumer behavior, technological competition, and sustainable development requirements. Technological and informational infrastructures, along with structural-industrial characteristics, were identified as contextual conditions, while structural and processual challenges in the sustainable digital transition path were recognized as intervening conditions. The core strategy involves implementing digital transformation through data-driven approaches, intelligent customer relationship management, marketing channel integration, improved decision-making, and sustainable value chain reinforcement, leading to economic, environmental, social, technological, and industrial outcomes. Quantitative validation confirmed statistically significant relationships and path coefficients, affirming the predictive role of model variables. R² values demonstrated adequate explanatory power, and fit indices confirmed measurement and structural model adequacy. The innovation lies in presenting an integrated paradigmatic framework that synthesizes sustainable marketing, digital capabilities, institutional requirements, emerging consumer behavior, and automotive structural contingencies, enabling empirical assessment of relationships among these dimensions.