Explaining tourism competitiveness in small and medium destinations: the Italian case

Abstract

The aim of the paper is to provide evidence of causal relationships between attributes of competitiveness and tourism destination competitiveness (TDC) in small and medium destinations (SMDs). A model of destination competitiveness has been developed and integrated with attributes of competitiveness, and then applied to a unique dataset of 370 outstanding Italian SMDs. A principal component analysis and a partial least square regression have been performed to test the model. The use of economic and financial measures as dependent variables, in addition to standard measures of destination performance, allows to investigate the concept of TDC from a wider economic point of view. Empirical evidence reveals that the multidimensionality and relativity of the concept of TDC influence the relationships among predictors and dependent variables. Managerial capabilities, quality of services, and policies aimed at fostering local empowerment are found to be key determinants of the competitiveness of Italian outstanding SMDs.

Keywords:

• competitiveness determinants
• small and medium destinations
• Italy
• tourism policy and planning
• destination management

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Gianluca Goffi http://orcid.org/0000-0002-9332-1123

Notes

1 http://ec.europa.eu/regional_policy/sources/docgener/focus/2012_01_city.pdf.

2 The effects of shocks on destination competitiveness are not neutral, and negative effects are more persistent in highly intensive economic crisis, due to the reduction of internal and external tourism demand and falling investments (Perles-Ribes, Ramón-Rodríguez, Rubia-Serrano, & Moreno-Izquierdo, 2017).

3 The AIDA – Bureau van Dijk DATABASE is an authoritative and reliable source of information on Italian companies. Additional information from http://www.bvdinfo.com.

4 $GOR=(Overnight\mathrm{\_}Stays÷Bed\mathrm{\_}Places\times 365)\times 100$

5 The sum of the number of respondents in the first row (628) is greater than the total number of respondents (550) because 54 municipalities have been awarded with both “Blue Flag” and “Blue Sails”, 20 municipalities have received both “Orange Flag” and “Beautiful Village”, whereas 2 municipalities have been awarded with “Blue Flag” and “Beautiful Village”; finally, 10 municipalities have been awarded with “Blue Sail” and “Beautiful Village”, and 4 municipalities received “Blue Flag”, “Blue Sail” and “Beautiful Village”. In few cases, there is an inland historic centre but the territory extends to the sea, and this explains why were awarded with both Blue Flag/Blue Sail and Orange Flag/Beautiful Village.

6 The loss of significance of F12 when we consider the dependent variable “hotels’ employment growth” is probably due to the fact that the quantity of accommodations seems to have a decisive importance: in F.12 quantity is only represented by a single indicator out of three. The loss of significance of F5 when we consider the dependent variable “GOR” could mean that occupation rate is more determined by other variables related to the internal organization and marketing strategies of the firms.

7 F.8 gastronomy is significant only when considering the dependent variable “GOR”. This is probably due to the formula offered, as most of the hotels offer an all-inclusive or a half-board formula. When the quality of the food is high, and at the same time the formula is convenient, it can induce tourists to stay longer, hence having an impact on the occupancy rate (in this case the dependent variable has a major impact).