This study evaluates the carbon emission reduction potential of industrialized construction technologies—specifically robotic 3D printing and prefabrication—in lower-star hotels in Hangzhou, China, from 2018 to 2023. A multidimensional ternary spatiotemporal model is developed to quantify the interactions among temporal, spatial, and hotel classification dimensions, enabling a systematic comparison between conventional construction (CC) and prefabricated construction (PC). The results show that prefabricated construction consistently reduces embodied carbon emissions across hotel categories, with the most significant reduction observed in 2-star and 3-star hotels, where carbon emissions can be reduced by approximately 20–35% compared to conventional methods. The findings further indicate that carbon reduction effectiveness varies by hotel classification and spatial distribution, with lower-star hotels benefiting more from standardized modular construction, while high-star hotels exhibit relatively lower reduction efficiency due to structural complexity. Spatiotemporal analysis also reveals heterogeneous decoupling patterns across districts, suggesting that carbon–economic relationships are strongly influenced by regional development conditions and construction intensity. This study advances the integration of carbon accounting and construction technology assessment by providing a quantitative and scalable framework for evaluating embodied carbon reduction in the hospitality sector. The findings offer robust evidence to support targeted low-carbon construction strategies and contribute to carbon–economic decoupling pathways in resource-constrained urban environments, aligning with the scope of carbon balance and management.

How heritage tourism scenes evolve alongside digital mediation and how different forms of mediation are represented in visitor accounts remain insufficiently understood. This study examines the Liangzhu heritage site, centred on the Archaeological Ruins of Liangzhu City, using 7172 visitor-generated online records collected from six major Chinese social media and travel platforms between 2015 and July 2025. A stage-based comparison contrasts the natural tourism stage (2015–2020) with the digitally mediated tourism stage (2020–2025), with records assigned to the corresponding stage-specific corpora based on temporal scope and record-level content eligibility. Word-frequency analysis, grounded-theory coding, social-semantic network analysis, and exploratory lexicon-based polarity analysis are combined to trace the stage-related evolution of the heritage tourism scene as represented in online visitor discourse. The results show that discourse in the digitally mediated tourism stage reflected a reconfiguration, rather than a replacement, of the represented heritage tourism scene: physical heritage remained the experiential anchor, while interpretation, interaction, and reconstructed experience became more prominent. AR-related discourse was associated mainly with guidance, recognition, and site-based interpretation, whereas VR-related discourse was associated with immersion, reconstructed scenes, and presence. Lexicon-derived polarity patterns were uneven: facilities, access, and management showed higher positive-polarity shares, while history, landscape, and overall visitor experience showed more mixed label distributions; some stage contrasts in positive-polarity shares were sensitive to platform composition. The findings extend the application of Cultural Scene Theory to stage-based analysis of digitally mediated heritage tourism by showing how cultural-scene elements are represented and connected in platform-mediated visitor discourse. They also offer evidence-informed implications for sustainable heritage interpretation and integrated visitor management, particularly regarding coherence among physical evidence, digital interpretation, visitor access, and service provision.