Grassini Laura, Magrini Alessandro, Conti Enrico
Department of Statistics, Computer Science, Applications, University of Florence, Florence, Italy.
Regional Institute for Economic Planning of Tuscany (IRPET), Florence, Italy.
Qual Quant. 2022 Sep 8:1-26. doi: 10.1007/s11135-022-01519-1.
In this article, we propose a formative-reflective scheme for the assessment of Tourism Destination Competitiveness (TDC) based on a combined use of Partial Least Squares-Path Modelling (PLS-PM) and the method recently proposed by Fattore, Pelagatti, and Vittadini (FPV). TDC is conceived as a construct reflecting the tourism performance of a destination, and several determinants are considered, including endowed resources, created resources, and supporting factors. The proposed scheme is applied to a case study on 1575 Italian municipalities for which the Italian National Institute of Statistics released data on tourist flows. Our contribution is innovative for three aspects: (i) the consistency of the formative-reflective scheme for TDC assessment is discussed on a theoretical basis; (ii) an empirical comparison between PLS-PM and the FPV method is performed; (iii) data with higher granularity than most studies on TDC assessment are employed. Our findings highlight that endowed resources are the primary driver of TDC, followed by created resources and supporting factors, and emphasize that the best ranked destinations are big cities with a multifaceted tourism alongside sea and mountain destinations with cultural attractions.
在本文中，我们基于偏最小二乘路径建模（PLS-PM）与法托雷、佩拉加蒂和维塔迪尼（FPV）最近提出的方法的结合使用，提出了一种用于评估旅游目的地竞争力（TDC）的形成性-反思性方案。TDC被视为反映一个目的地旅游表现的一个结构，并且考虑了几个决定因素，包括禀赋资源、创造资源和支持因素。所提出的方案应用于对1575个意大利市镇的案例研究，意大利国家统计局公布了这些市镇的游客流量数据。我们的贡献在三个方面具有创新性：（i）在理论基础上讨论了用于TDC评估的形成性-反思性方案的一致性；（ii）对PLS-PM和FPV方法进行了实证比较；（iii）使用了比大多数TDC评估研究粒度更高的数据。我们的研究结果突出表明，禀赋资源是TDC的主要驱动因素，其次是创造资源和支持因素，并强调排名靠前的目的地是具有多元旅游的大城市以及拥有文化景点的海滨和山区目的地。
