The Role of Social Entrepreneurship in Shaping Architects’ Behavioral Response toward AI-Based Taxation and Sustainable Hospitality Construction: A Serial Mediation Analysis

Abstract

The integration of Artificial Intelligence (AI) into taxation systems has emerged as a critical mechanism for enhancing transparency, efficiency, and economic sustainability, particularly within the hospitality construction sector of emerging economies. However, architects’ behavioural responses toward AI-based taxation remain inconsistent due to underlying socio-entrepreneurial and technological factors. This study examines the role of social entrepreneurship in shaping architects’ behavioural responses toward AI-based taxation and its subsequent impact on sustainable hospitality construction through a serial mediation framework. A quantitative, cross-sectional research design was employed, and data were collected from architects involved in hospitality construction projects using a structured questionnaire. The proposed model was analysed using SmartPLS software (Partial Least Squares Structural Equation Modeling). The findings reveal that social entrepreneurship significantly and positively influences both perceived ease of use and perceived usefulness of AI-based taxation systems. Perceived ease of use further enhances perceived usefulness, which in turn strengthens trust in the system. Trust was found to have a strong positive effect on behavioural response, which significantly contributes to sustainable hospitality construction. Moreover, the results confirm a statistically significant serial mediation effect, demonstrating that social entrepreneurship indirectly influences sustainability outcomes through the sequential pathway of perceived ease of use, perceived usefulness, trust, and behavioural response. The model exhibits substantial explanatory power with significant path coefficients. This study contributes to technology adoption and sustainability literature by integrating social entrepreneurship into the TAM framework and offers practical insights for policymakers and industry stakeholders to promote AI-driven sustainable development in emerging economies.