## 2 Materials and Methods
### Data Analysis  
The exploratory analysis of the data was achieved through basic statistical tools. The survey was prepared in Greek and divided into six parts:  
Part I. Sociodemographic data (see Table 1)  
Part II. Motivation and consumer behavior for food purchase  
Part III. Consumer's perception for the traditional food of Epirus  
Part IV. Consumer's perception for the marketing of Epirus' traditional foods  
Part V. Consumer access to the traditional food of Epirus  
Part VI. Consumer's evaluation for traditional products of Epirus  
The sociodemographic characteristics (six questions) were collected in the first part of the questionnaire (two dichotomous, one ordinal variable, and three nominal variables). According to the objectives of the present study, the second section of the questionnaire recorded the motivations and consumer behavior toward food purchases (five ordinal variables). The third (four ordinal variables, one dichotomous and one multiple choice question with each response considered as dichotomous variable) and the fourth (one categorical and two ordinal variables) parts were designed to explore the degree of consumers' awareness for the traditional products of Epirus and to reveal their opinion on the level of marketing of these products, respectively. The fifth (one dichotomous variable and one multiple choice question with each response considered as dichotomous variable) and sixth (four ordinal variables and one multiple choice question with each response considered as dichotomous variable) parts of the questionnaire aimed to collect the consumer's buying habits and the quality perception of traditional products of Epirus region.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Variable** & **Groups** & **\%** \\ \hline \multirow{3}{*}{Sex} & Male & 41.3 \\  & Female & 58.7 \\  & 18–25 & 25.3 \\  & 26–35 & 21.1 \\ \multirow{3}{*}{Age} & 36–45 & 18.4 \\  & 46–55 & 23.1 \\ \multirow{6}{*}{Level of education} & 55+ & 12.1 \\  & None/Primary school & 0.4 \\  & Secondary school & 0.2 \\ \multirow{3}{*}{Level of education} & High school & 10.5 \\  & University & 88.9 \\ \multirow{6}{*}{Civil state} & Single & 50.1 \\  & Married & 43 \\ \cline{1-1}  & Divorced & 5.9 \\ \cline{1-1}  & Widow & 1 \\ \cline{1-1}  & Employed & 72.4 \\ \cline{1-1}  & Unemployed & 5.6 \\ \cline{1-1}  & Student & 22 \\ \cline{1-1}  & Yes & 43.4 \\ \cline{1-1}  & No & 56.6 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Sociodemographic characterization of the sample.  
The statistical processing of the data was performed using IBM SPSS Statistics for Windows (Version 25.0, IBM Corp. Armonk, NY, USA). The normality test was performed on the data before proceeding with the other statistical tests. Data obtained from the Likert scale were considered as ordinal values.  
The nonparametric tests were used. A nonparametric chi-square test was performed to test the distribution of variables of each group and response based on the hypothesized equal proportions for each variable. The chi-square independence test was used to determine whether there is an association between variables. Post-hoc tests for the chi-square independence test were used. The pairwise comparisons (z-tests) for independent proportions followed by a Bonferroni correction were applied to the data. In order to measure the strength of association (when it is present between two variables), the Phi, Cramer's V, or Kendall's tau-b test. The Cramer's V coefficient was used to analyze the strength of the significant relations found between some of the variables at study. This coefficient ranged from 0 to 1 and can be interpreted as follows: V \(\approx\) 0.1 the association is considered weak, V \(\approx\) 0.3 the association is moderate, and V \(\approx\) 0.5 or over, the association is strong. Sociodemographic characteristics were considered as predictor variables that could affect the other responses of the questionnaire. In all the tests performed, the level of significance considered was 5% (\(p<\) 0.05).