Search

The purpose of this paper is to improve understanding of Tourism Innovation by using a Uses and Gratification Theory model to investigate tourist intention to visit a city after reading other users' valuations of the destination on Mobile Applications.The Uses and Gratification Theory (U&G) model was adapted to investigate the factors which influence tourist intention to visit a city. Satisfaction and Tourism Experience were added as external variables to the U&G model. The original Convenience construct for mobile tourism applications was changed to Mobile Convenience for this study.A survey was carried out to investigate the factors which influence tourist intention to visit a City. 261 users with different nationalities were asked about their experiences and feelings when using Runnin'City, which was the mobile tourism application used in this study. The results were analyzed with Partial Least Squares Structural Equation Modeling (PLS-SEM). All the relationships of U&G were supported, except for Information for Tourism Experience.Self-Expression was found to be especially relevant and was moderated by Entertainment, Information and Mobile Convenience which in turn influence Satisfaction, Tourism Experience and Intention to visit a City.The Gender and Running frequency variables were also investigated using multi-group analysis. The influence of Mobile Convenience on Satisfaction was seen to be moderated by Gender, and the relationships of Information and Entertainment on satisfaction are moderated by Running Frequency.The results obtained with the proposed changes in the U&G model will be very useful for academics and also for designers and developers of mobile tourism apps as they show the special role played by Self-Expression and Entertainment as relevant factors for the success of a mobile tourism app.

In this work, we try to answer a key question: what are the more efficient units in franchising: owned or franchised? The literature on this specific field is very limited. To compare the efficiency of owned and franchised units we use the following variables: average sales per unit, average sales per employee and the average number of employees per unit for owned and franchised establishments. The analyses are carried out using the population of franchise chains, a database with the 1232 franchise chains existing in Spain at the end of 2015 has been created for this purpose. The results show the higher efficiency of owned regarding franchised units.