Analysing the cost-effectiveness of heritage conservation interventions: a methodological proposal within Project STORM

Maria João Revez*, Paola Coghi, José Delgado Rodrigues, Inês Vaz Pinto

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

Cost-Effectiveness Analysis (CEA) is a decision-support tool that allows strategy comparisons without the need for monetising expected outcomes. Since benefits to be gained in heritage contexts are inherently difficult to price, a CEA may provide valuable support to the allocation of cultural heritage preservation resources. Nevertheless, its application in the heritage sector is still limited, arguably due to difficulties in ‘effectiveness’ appraisals. STORM (Safeguarding Cultural Heritage through Technical and Organisational Resources Management) is an H2020-funded project for the development of Disaster Risk Management solutions for heritage sites facing natural hazards and climate change. Within its scope, a methodology for the CEA of conservation interventions was developed and applied to the Roman Ruins of Tróia (Portugal) pilot site. This paper describes the CEA methodology, including cost and effectiveness indicators and discount rate; and reports its application for the assessment of five strategies addressing the risks of a sand dune weighing upon a Roman well. Using expert opinion to tackle the effectiveness appraisals, the CEA showed that ordinary maintenance options are costlier but more effective than extraordinary maintenance ones. The most cost-effective option was the less intrusive strategy, matching current perspectives on archaeological conservation, and seemingly indicating that the procedure is robust.
Original languageEnglish
Pages (from-to)985-999
Number of pages15
JournalInternational Journal of Architectural Heritage
Volume15
Issue number7
DOIs
Publication statusPublished - 2021
Externally publishedYes

Keywords

  • Archaeological heritage conservation
  • Cost-effectiveness analysis
  • Disaster risk management
  • Project STORM

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