## 4 Model Data
### Input-Output Data for SM-DEA (Social Media-DEA) Layer  
The present boom of social media in almost all consumption areas and habits is unquestionable. Social networks contribute to strengthening relationships among and between airline organizations and individuals. To do so, interaction and engagement are the most important functions of social media regarding the management of airlines. Social media had an important effect on companies' performance through a sustainable brand [38; 42]. Given the increasing importance of social media in airlines, the necessary next step has to do with the integration of related indicators to assess the efficiency and performance of airlines.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Business Management**} & \multicolumn{2}{c}{**Network Management**} & \multicolumn{2}{c}{**Social Media Network Management**} & \multicolumn{2}{c}{**Total**} \\  & \multicolumn{2}{c}{**(Bus-DEA)**} & \multicolumn{2}{c}{**(Net-DEA)**} & \multicolumn{2}{c}{**(SM-DEA)**} & \multicolumn{2}{c}{**(Overall Model)**} \\ \cline{2-10}  & **Step 1** & **Step 2** & **Step 3** & **Step 4** & **Step 5** & **Step 6** & **Step 7** & **Step 8** & **Step 9** \\ \cline{2-10}  & **(Basic)** & **(Airline Basic)** & **(Degree Net)** & **(Eigenc. Net)** & **(Total Net)** & **(Fib)** & **(Twitter)** & **(OwTube)** & **(Overall)** \\ \hline \hline Number of & & & & & & & & & \\ employees & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ Total assets & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ Destinations & & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ Degree & & & \(\surd\) & \(\surd\) & \(\surd\) & & & & & \\ Eigencentralty & & & & \(\surd\) & \(\surd\) & & & & \(\surd\) \\ Tweet/day & & & & & & & & \(\surd\) & & \\ Publication/day & & & & & & & \(\surd\) & & & \(\surd\) \\ Number of & & & & & & & & & & \\ videos & & & & & & & & & \\ \hline \hline Sales & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ Millions of & & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ passengers 2/144 & & & & & & & & & \(\surd\) & \\ Lites Twitter & & & & & & & & \(\surd\) & & \\ Likes Facebook & & & & & & & & & \(\surd\) \\ Views & & & & & & & & & \(\surd\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Variables selected for each DEA layer model.  
We add to previous DEA layer inputs-outputs data that represent support for and acceptance of a company in social networks for the SM-DEA layer.  
As [PERSON] and [PERSON] [56] assert, Web 2.0 technologies are features with two types of variables--firstly, response levels: number of fans, followers, hits, comments, and tweets received; and secondly, company activity levels: comments, tweets, followings, responses, publications/posts, applications, events, surveys. We incorporate different features to the SM-DEA model as inputs: tweets/days, publication/days, and number of released videos as measure of activity level in social networks [56; 64; 65]. As outputs we use Twitter likes, Facebook likes, and views in YouTube channels as the user response.  
The information on practice of Web 2.0 technologies is based on indicators of social media activity in 2014; the data were obtained directly from the Web 2.0 tools themselves.