Model-based testing (MBT) has been an important methodology in software engineering, attracting extensive research attention for over four decades. However, despite its academic acclaim, studies examining the impact of MBT in industrial environments—particularly regarding its long-term effects—remain limited and yield unclear results. This gap may contribute to the challenges in establishing a study environment for implementing and applying MBT in production settings to evaluate its impact over time. To bridge this gap, we collaborated with an industrial partner to undertake a comprehensive, longitudinal empirical study employing mixed methods. Over two months, we implemented our MBT tool within the corporation, assessing the short- and long-term effectiveness and efficiency of MBT compared to script-writing-based testing. Through a mix of quantitative and qualitative methods—spanning experimental data, questionnaire surveys, and interviews—our study uncovers several insightful findings. These include differences in effectiveness and maintainability between short- and long-term MBT application, the evolving perceptions and expectations of engineers regarding MBT, and more. Leveraging these insights, we propose actionable implications for both the academic and industrial communities, aimed at bolstering confidence in MBT adoption and investment for software testing purposes.