COMPETITIVENESS OF TOURISM INDUSTRY IN KAZAKHSTAN - Tourism in Central Asia: Cultural Potential and Challenges - page 28

of the fifth pillar—Prioritization of Travel & Tourism—increased due to
increased government expenditure on the sector, hosting and participating
in key international tourism fairs (the 50th rank), and increased compre-
hensiveness of the annual T&T data (the 28th rank).
The results of the analysis of the T&T business environment and infra-
structure sub index of the Travel & Tourism Competitiveness Index indi-
cate positive trends for the percentile ranks of three pillars. There is great
potential for further progress by improving a) the quality of air transport
infrastructure and expanding the international air transport network (the
6th pillar: Air transport infrastructure), b) the quality of port infrastructure
and the quality and density of roads (the 7th pillar: Ground transport in-
frastructure), c) the competitiveness of hotel prices—providing value for
money (the 10th pillar: Price competitiveness in the T&T industry).
The results of the analysis of the T&T human, cultural and natural re-
sources sub index of the Travel & Tourism Competitiveness Index do not
reveal improvements for the ranks of its four pillars. There is great space
for the development of T&T human resources (the 11th pillar) and the
affinity of travel and tourism (the 12th pillar). A significant focus should
be placed on the natural resources (the 13th pillar): the protected areas
(ranked 114th) and the quality of the natural environment (ranked 126th).
Cultural resources (the 14th pillar) also have low T&T competitiveness in
terms of the number of World Heritage cultural sites, creative industries,
international fairs and exhibitions held in the country, and sports stadiums
capacities.
RESULTS OF THE LONGITUDINAL STUDY: HYPOTHESIS
TESTING
Hypothesis 1: There is a positive relationship between competitiveness of
the firm, its age, the propensity of the firm to innovate and the number of
cluster actors in its network. To define the underlying determinants of firm
competitiveness factor analysis was used. The eigenvalue-greater-than-
one criterion was used in identifying four factors. The principal component
solution using the Varimax with Kaiser Normalization rotation method re-
sulted in the rotated component matrix (rotation converged in five itera-
tions) where the first three factors have high loadings (greater than 0.7) on
the number of employees, their education and language skills. The fourth
factor has high loadings on the firm age (0.653), the total number of the