Coscia, C.; Pasquino, F. Demand Analysis Models to Support Cultural Tourism Strategy: Application of Conjoint Analysis in North Sardinia (Italy). Land2023, 12, 2150.
Coscia, C.; Pasquino, F. Demand Analysis Models to Support Cultural Tourism Strategy: Application of Conjoint Analysis in North Sardinia (Italy). Land 2023, 12, 2150.
Coscia, C.; Pasquino, F. Demand Analysis Models to Support Cultural Tourism Strategy: Application of Conjoint Analysis in North Sardinia (Italy). Land2023, 12, 2150.
Coscia, C.; Pasquino, F. Demand Analysis Models to Support Cultural Tourism Strategy: Application of Conjoint Analysis in North Sardinia (Italy). Land 2023, 12, 2150.
Abstract
This work focuses on an inland area of North Sardinia (Italy), which is currently subject to depopulation and economic crisis because it is not affected by the summer tourism typical of the region. Despite this, the area shows an interesting architectural and natural heritage, as of today insufficiently known and valued. Therefore, the purpose of this paper is to illustrate the application of the Conjoint Analysis methodology on this case study aimed at supporting processes of valorisation, diversification of the tourist offer and promotion of the through the detection of the preferences of a sample of residents and visitors on a set of 9 cards (itinerary profiles) which also promote the peculiarities of small rural centres. Thus, by valorising the material and immaterial heritage and their intrinsic characteristics, it is shown that inland areas can generate an economy by offering new types of tourism, not just the typically invasive summer and maritime tourism. The research, therefore, seeks to estimate the economic value of the area from a public point of view through the WTP measured by a questionnaire of 600 interviews between inhabitants (300) and tourists (299).
Keywords
conjoint analysis; inner territories; willingness to pay; consumer behaviour; Sardinia
Subject
Business, Economics and Management, Econometrics and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
