Advanced techniques for quantifying data-driven heritage: a cross study of statistical methods in heritage research
DOI:
https://doi.org/10.18537/est.v016.n031.a01Keywords:
heritage valuation, statistical methods, cultural heritage, meta analysis, spatial modellingAbstract
The quantification of cultural heritage value is increasingly supported by advanced statistical models, moving beyond traditional qualitative narratives. This paper presents a meta-analysis of 45 empirical studies (2010-2024) that applied statistical methods such as EFA, CFA, SEM and other multivariate methods to assess heritage value, perception and policy relevance. Studies were analysed for methodological transparency, model rigor and adaptability across contexts. Findings show significant variation in method selection, with SEM and CFA common in urban heritage research in Asia and Europe while PCA, cluster analysis and GWR are more prevalent in studies on landscapes and intangible heritage. The study reveals increasing use of spatial and perceptual models but also highlights underuse of spatial SEM and latent class modelling particularly in the Global South. This paper offers a comparative synthesis and practical guidance for selecting appropriate statistical methods in heritage research supporting more robust policy and Conservation strategies.
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