## 5 Discussion  
The present work has investigated the connections between continuance intention of playing Pokemon Go and a set of constructs: enjoyment, fantasy, escapism, social interaction, social presence, achievement and self-presentation. The U&G perspective was adopted.  
The findings indicate that U&G theory comprises an appropriate framework, because (1) it broadly explains the voluntary use of ICT for hedonic purposes and (2), specifically, it has enough potential to examine motivations for the continuous use of augmented reality mobile games, such as Pokemon Go. Based on these U&G principles, people will consume augmented reality mobile games to gratify a wide set of needs.  
According to [50; 51], U&G is a useful framework to identify social and psychological needs, and in this way to answer to key questions in the motivational field. In fact, the U&G approach considers that continuance intention of ICT use depends largely on cognition-oriented behaviour [30; 31; 32]. From a theoretical point of view, this study makes a number of contributions. First, it has improved understanding of the essential dimensions that incentive the use of online games. The results confirm the variables that determine continuance intention of online games. Second, results contribute to the  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Fit Index** & **Results** & **Recommended Value** \\ \hline \(\chi\) 2/grade of freedom & 0.295 & \(\leq\)3.00 \\ Normed Fit Index (NFI) & 0.960 & \(\geq\)0.90 \\ Non-normed Fit Index (NNFI) & 0.964 & \(\geq\)0.90 \\ Comparative Fit Index (CFI) & 0.970 & \(\geq\)0.90 \\ Adjusted Goodness-of-Fit Index (AGFI) & 0.915 & \(\geq\)0.80 \\ Root Mean Square Error of & 0.050 & \(\leq\)0.05 \\ Approximation (RMSEA) & 0.934 & \(\geq\)0.90 \\ Goodness-of-Fit Index (GFI) & 0.970 & \(\geq\)0.90 \\ Incremental Fit Index (IFI) & 0.970 & \(\geq\)0.90 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Overall fits of the models  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Hypothesis (Path)** & **Path Coefficient** & **t-Value 2** & **Supported** \\ \hline H1: ENJ\(\rightarrow\)CI & 0.484 & 12.065 *** & Yes \\ H2: FAN\(\rightarrow\)CI & \(-\)0.0145 & \(-\)0.442 & No \\ H3: ESC\(\rightarrow\)CI & 0.0647 & 1.975 ** & Yes \\ H4: SINT\(\rightarrow\)CI & 0.0627 & 1.968 ** & Yes \\ H5: SPRE\(\rightarrow\)CI & 0.155 & 3.166 ** & Yes \\ H6: ACH\(\rightarrow\)CI & 0.0814 & 2.515 ** & Yes \\ H7: SELFP\(\rightarrow\)CI & \(-\)0.0284 & \(-\)0.848 & No \\ \hline \hline \end{tabular}
\end{table}
Table 5: Results of hypothesis testing.  
existing literature by highlighting the impact of gratifications on online game use. In this respect, the structural model, based on prior literature [49; 53; 59], received strong support from the dataset.  
Overall, the model supports almost all relationships as expected. In this respect, the dataset indicates that the proposed model offers an appropriate fit for the defined connections, as the positive influence of enjoyment, escapism, social interaction, social presence and achievement on the CI of playing Pokemon Go are clearly confirmed. These results share some similarities with the previous literature [53; 57; 58; 59]. However, contrary to what was expected, the hypotheses relating to fantasy and self-presentation were not supported, and so do not seem to be relevant to Pokemon Go. Overall, however, it can be concluded that users achieve gratification when they use augmented reality mobile games.  
Finally, this is one of the first studies to examine the intentions of people using an online game with three basic features: it is (1) free-to-play (players do not need to pay to use it), (2) location-based (the progress of the game depend on the player's location) and (3) an augmented reality game.