Post-occupancy evaluation of former residences of celebrities in Yangzhou based on the comparison of online reviews and questionnaire data

Online review data and traditional questionnaire data are common data sources in the current field of cultural heritage research. The former features a large data volume yet suffers from obvious limitations such as incompleteness, algorithm interference, dirty data and sensitivity; the latter enjoys a high degree of quantification but is constrained by high costs and limited sample size. To explore the complementary mechanism of the two types of data, this study selects 9 national-level former residences of celebrities in Yangzhou as cases and adopts a sequential mixed-methods design. First, content analysis and thematic coding are conducted on online reviews to identify 5 major categories of negative evaluations, based on the coding results, an indicator system is constructed, and offline questionnaire data are collected for AHP-FCE quantitative analysis. The results show that the two types of data exhibit partial correspondence in diagnosing core shortcomings, which, to a certain extent, reflects the inherent logic of the sequential design in which the questionnaire indicators were derived from the online review coding. Cultural expression, interactive experience, accessibility, and signage facilities are jointly identified as the weakest dimensions. Online data provide detailed descriptions and situational characteristics, while questionnaire data reflect the weight and severity of existing problems. Meanwhile, discrepancies exist between the two datasets. Complaints about service attitude appear frequently in online reviews, while this item scores well in questionnaires, reflecting the difference between extreme individual cases and overall public perception. Overall, online review data can truly and centrally reflect systematic defects, possessing unique advantages in capturing specific details and users’ real emotional perceptions. Questionnaire survey data can reflect the severity of problems with strong pertinence through weight analysis. The integrated management and diagnosis framework combining the two approaches provides timely and insightful decision-making support for the targeted optimization of cultural heritage sites, in which the granularity differences between the two data types offer a unique perspective for understanding tourist experiences.