Browsing by Author "Táborecká-Petrovičová, Janka"
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- ItemModelling the Determinants of Festival Visitors’ Behavioural Intentions(Technická Univerzita v Liberci, ) Ďaďo, Jaroslav; Maráková, Vanda; Táborecká-Petrovičová, Janka; Rajić, Tamara; Ekonomická fakultaLimited efforts have been made to date to examine the determinants of visitors’ behavioural intentions in the context of cultural festivals in Central Europe. The present study aims to fi ll this void in literature by proposing a conceptual model incorporating the festival setting that has thus far scantly examined perspective of the fulfi lment of motives and a subjective well-being as a consequence of a festival experience. The application of structural equation modelling (SEM) on a sample of 770 festival visitors in Slovakia provided support for the concept of visitors’ motivation as a higher-order construct and its direct relatedness to perceived value of a festival experience and visitors’ satisfaction. Both satisfaction and visitors’ subjective well-being emerged as direct antecedents to visitors’ behavioural intentions and mediators of the impact of perceived value on visitors’ behavioural intentions. Implications of the study are provided and limitations and directions for future research are highlighted.
- ItemTargeting of Online Advertising Using Logistic Regression(Technická Univerzita v Liberci, ) Šoltés, Erik; Táborecká-Petrovičová, Janka; Šipoldová, Romana; Ekonomická fakultaRecently, the internet became the dominant medium in marketing and comparing the development of expenditures into advertising indicates the dominance of online advertising will be inevitably stronger. Internet advertising compared to traditional media advertising has plenty of advantages hence online marketing exhibits a huge expansion in recent era. To fully utilize the potential of online marketing, it is necessary to effectively target activities of relevant internet users with the real presumption they will purchase promoted products or services. The paper is focused on demographic targeting by the mean of logistic regression models. Explanatory variables in presented application are arising from affinities of internet webpages visited by particular users and areas of their interests that are identified from their online behaviour. Our paper provides binomial logistic mode whose role is to predict the gender of internet user and multinomial logistic model constructed for the estimation of age category the user may be assigned to. The only variables exploited in the model by the mean of stepwise regression are variables with significant influence. The impact of particular factors is quantified via odds ratios that are used for the identification of areas of interests typical for women, men and for considered age categories. The paper demonstrates how it is possible to utilise estimated logistic models for the estimation of probabilities that the internet user is from a target group – in our case, women aged 25–44 years old. Prediction quality of models is assessed by the set of classification measures arising from confusion matrix that is generally acceptable in machine learning. Presented analyses are conducted in statistical software SAS Enterprise Guide on data provided from the real advertising campaign. More than 160,000 statistical units enabled the confirm results gained on training dataset of a relatively huge validation dataset.