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Wyświetlanie 1-3 z 3
Tytuł:
Gender-generation characteristic in relation to the customer behavior and purchasing process in terms of mobile marketing
Autorzy:
Stefko, Robert
Bacik, Radovan
Fedorko, Richard
Olearova, Maria
Powiązania:
https://bibliotekanauki.pl/articles/19322532.pdf
Data publikacji:
2022
Wydawca:
Instytut Badań Gospodarczych
Tematy:
online shopping
e-commerce
customer insight
online consumer behavior
Opis:
Research background: Today, it is an m-commerce platform that provides brands with the opportunity to foster their sustainable image and communicate with environmentally and socially conscious consumers. Proper communication that respects the customer's interests, conducted through mobile marketing tools, can be a key to creating a competitive advantage. Therefore, it is essential, at the level of scientific research, to broaden the knowledge base in the field of consumer behavior. Purpose of the article: The research was aimed at assessing ten purchasing behavior constructs in terms of gender and generation characteristics, as well as inferring impact on and assessing the difference between generations (Generation X and Y) and gender in terms of purchasing behavior. Methods: The sample consisted of 765 Slovak respondents. The Wilcoxon Test was used for differences testing. Partial Least Squares - Path Modeling (PLS-PM) was used to determine the general impact and the permutations-based method was used to assess the difference in impact between gender and generation characteristics. Findings & value added: The difference in purchasing behavior patterns between the categories of gender and generation was significant in most cases, with the most significant difference being seen in the Visual Appeal of an e-shop. The most striking general influences were recorded between Hedonic Browsing and Urge to Buy, also the impact of Portability on Hedonic Browsing and Utilitarian Browsing. These findings indicate the potential of retailers to communicate effectively with their customers not only about products, but also about sustainable practices and values while engaging consumers in purchasing processes. Proper optimization of marketing processes, in terms of impulsive and thought-through purchases too, positively influences the user experience and the satisfaction with the purchase process. These facts may positively influence the sale and, in a broader perspective, increase the competitiveness and overall value of the e-commerce entity. It is also worth emphasizing the long-term value for the customer, as the application of the model leads to better satisfaction of customer needs, thus to a stable growth not only of the organizations, but ultimately of the economy as a whole.
Źródło:
Oeconomia Copernicana; 2022, 13, 1; 181-223
2083-1277
Pojawia się w:
Oeconomia Copernicana
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Effect of service quality assessment on perception of TOP hotels in terms of sentiment polarity in the Visegrad group countries
Autorzy:
Stefko, Robert
Fedorko, Richard
Bacik, Radovan
Rigelsky, Martin
Olearova, Maria
Powiązania:
https://bibliotekanauki.pl/articles/19233601.pdf
Data publikacji:
2020
Wydawca:
Instytut Badań Gospodarczych
Tematy:
sentiment polarity
customer satisfaction
hotel
Visegrad group
Opis:
Research background: In the developed countries, the services sector, which also includes the accommodation services, is a significant source of the gross national product. Tourism can be perceived as an important determinant of countries' economies, so attention paid to the needs of clients is at least necessary and beneficial. Purpose of the article: The aim of the study is to assess the quality of services provided and the perception of the hotel from the point of view of the accommodated clients. This objective was fulfilled by determining the effect of selected indicators of perception of the quality of provided services (location, personnel evaluation, cleanliness, equipment, comfort, price/quality ratio of provided services, free Wi-Fi connection) on the indicator determining the perception of the hotel (polarity of sentiment). Methods: In the analysis of the above, 22,000 text-reviews of 117 five-star hotels of the Visegrad Group countries were evaluated. The hotel reviews were obtained from Tripadvisor.com and indicator rankings from Booking.com. The analysis made use of the regression analysis methods - influence (regulatory models - Ridge, Lasso, Elastic net, and multiple linear regression - OLS). Findings & Value added: It has been found out that hotel equipment and cleanliness have the greatest effect on the polarity of sentiment. As could be expected, the trend has an upward tendency - that is, as quality increases, so does the sentiment polarity - the perception of hotel facilities. Overall, the analysed sentiment variables can be considered positive, as was confirmed by the positive coefficients of the coherence analysis (Spearman-ρ; Pearson-r), as well as the upward trend in the predictions under the regression analysis. Hotels should be strategically customer-oriented and, as the analyses show, pay the greatest attention to equipment and cleanliness. The services of accommodation facilities are dominant in terms of satisfaction with the destination in general, so in the long run, they should be given due attention. These findings are particularly beneficial for hotel services provided in the Visegrad Group countries, as no research studies have yet been carried out on customer evaluation of the quality of accommodation facilities using the presented methods.
Źródło:
Oeconomia Copernicana; 2020, 11, 4; 721-742
2083-1277
Pojawia się w:
Oeconomia Copernicana
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial intelligence in predicting the bankruptcy of non-financial corporations
Autorzy:
Gavurova, Beata
Jencova, Sylvia
Bacik, Radovan
Miskufova, Marta
Letkovsky, Stanislav
Powiązania:
https://bibliotekanauki.pl/articles/19322666.pdf
Data publikacji:
2022
Wydawca:
Instytut Badań Gospodarczych
Tematy:
engineering industry
automotive industry
bankruptcy prediction
Logistic regression
artificial intelligence
neural network
Opis:
Research background: In a modern economy, full of complexities, ensuring a business' financial stability, and increasing its financial performance and competitiveness, has become especially difficult. Then, monitoring the company's financial situation and predicting its future development becomes important. Assessing the financial health of business entities using various models is an important area in not only scientific research, but also business practice. Purpose of the article: This study aims to predict the bankruptcy of companies in the engineering and automotive industries of the Slovak Republic using a multilayer neural network and logistic regression. Importantly, we develop a novel an early warning model for the Slovak engineering and automotive industries, which can be applied in countries with undeveloped capital markets. Methods: Data on the financial ratios of 2,384 companies were used. We used a logistic regression to analyse the data for the year 2019 and designed a logistic model. Meanwhile, the data for the years 2018 and 2019 were analysed using the neural network. In the prediction model, we analysed the predictive performance of several combinations of factors based on the industry sector, use of the scaling technique, activation function, and ratio of the sample distribution to the test and training parts. Findings & value added: The financial indicators ROS, QR, NWC/A, and PC/S reduce the likelihood of bankruptcy. Regarding the value of this work, we constructed an optimal network for the automotive and engineering industries using nine financial indicators on the input layer in combination with one hidden layer. Moreover, we developed a novel prediction model for bankruptcy using six of these indicators. Almost all sampled industries are privatised, and most companies are foreign owned. Hence, international companies as well as researchers can apply our models to understand their financial health and sustainability. Moreover, they can conduct comparative analyses of their own model with ours to reveal areas of model improvements.
Źródło:
Oeconomia Copernicana; 2022, 13, 4; 1215-1251
2083-1277
Pojawia się w:
Oeconomia Copernicana
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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