Study of the Tourism Competitiveness Model of the World Economic Forum Using Rasch’s Mathematical Model: The Case of Portugal

Abstract

In this paper, the potential of the World Economic Forum (WEF) model to analyze tourism competitiveness is studied. The study aims to analyze the WEF model’s validity, reliability and dimensionality. It attempts to determine the WEF model’s potential for studying tourism destinations’ competitiveness in an integrated context. Finally, using the WEF model, Portugal’s competitiveness is analyzed in an integrated and benchmarking context. The methodology used in this study is the Rasch mathematical model, a methodology that has been effectively demonstrated in social sciences. Competitiveness data from the latest available WEF Travel and Tourism Competitiveness Report (TTCR-2019) has been used. The results show that the WEF model is statistically valid and reliable for studying competitiveness in tourism. Likewise, the WEF model’s high potential for the joint study of competitiveness and individual countries in an integrated and benchmarking context is confirmed. The study facilitates the development of policies to improve tourism competitiveness.

Exploring Personal and Contextual Variables of the Global Entrepreneurship Monitor through the Rasch Mathematical Model

“…Due to the one-dimensional principle of RM, the variables must be measuring a single latent dimension [133,134]. RM proposes that the observed data can be explained based on the ease of countries in valuing the entrepreneurship variables (β) highly, and the difficulty of the entrepreneurship variables to be highly valued by the countries (δ) [135][136][137]. The β and δ values refer to the logit scale and can vary from minus to plus infinity, usually being in the range from −5.00 to +5.00.…”

“…Conventionally, point 0 corresponds to the mean of the variables [138,139]. The calculations of the logit measurements β and δ are carried out by the maximum likelihood method through the PROX and JMLE algorithms [135,140,141]. Figure 1 represents, on a linear continuum, the parameters β and δ.…”

“…Figure 1 represents, on a linear continuum, the parameters β and δ. Due to the interval properties of the logit scale, the interpretation of the differences in the scale is the same in all the measured attributes [135,142]. Therefore, equal differences between a country and a variable correspond to identical probabilities of a correct answer [47,135,143].…”

“…Due to the interval properties of the logit scale, the interpretation of the differences in the scale is the same in all the measured attributes [135,142]. Therefore, equal differences between a country and a variable correspond to identical probabilities of a correct answer [47,135,143]. In the RM context, the probability of a certain category of variable "i" by country "n" would be [47,135,144]:…”

“…Therefore, equal differences between a country and a variable correspond to identical probabilities of a correct answer [47,135,143]. In the RM context, the probability of a certain category of variable "i" by country "n" would be [47,135,144]:…”