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- ItemExploring travel agencies customers’ loyalty motives throught machine learning analysis(Technická Univerzita v Liberci, ) Dudek, Andrzej; Jaremen, Daria E.; Michalska-Dudek, Izabela; Pellesova, Pavlina; Ekonomická fakultaThis article focuses on identifying the directions of changes in the decision-making process of purchasing package travels and the motives determining this purchase, as well as the impact of these motives on the affective, behavioral and global loyalty of travel agency customers during the COVID-19 pandemic. To achieve the research goal, a literature review and field research were conducted. In the case of secondary sources, the content analysis method was used to examine them, while data from primary sources (N = 1,508) were collected using an indirect survey technique (CAWI). The data analysis was carried out using machine learning – the variable importance method and the random forest algorithm. The obtained results allowed us to conclude that during the period of threat of the COVID-19 virus pandemic, tourist packages had been purchased less frequently, and buyers either had limited their trips to domestic trips or had adapted their travel destinations to the changing pandemic situation. The most important motivators that determined the choice of a travel agency during the COVID-19 pandemic were an attractive offer, a wide selection of package travels, previous positive experiences and trust in the organiser. It was also confirmed that in the face of the pandemic threat, buyers of package travels had been loyal to travel agencies. The use of machine learning allowed for more in-depth analyses and identification of motives that had a key impact on the development of buyer loyalty during the pandemic. The factors identified in the study encouraging buyers of package travels to maintain long-term relationships with their suppliers are belief in the value of the travel agency’s offer, trust in the travel agency, individual approach travel agency employees, efficient service in the travel agency, and a wide selection of package travels.
- ItemDigital payments as an indicator of financial inclusion in Euro Area countries(Technická Univerzita v Liberci, ) Petrikova, Tamara; Kocisova, Kristina; Ekonomická fakultaThe process of digitisation in the financial sector is developing through the systematic introduction of computer systems, the establishment of Internet connectivity and the use and ownership of various information and communication devices. Information and communication technologies can increase the desired degree of financial inclusion in a country by increasing the availability of various financial services. This study examines the individual attributes that can affect financial inclusion in the Euro Area countries in 2021. Our analysis applies a probit model to data from the World Bank Global Findex database, focusing on digital payments as a proxy for financial inclusion. The main finding highlights that higher income, higher education, female gender, and younger age groups are associated with an increased propensity to engage in digital payments. Notably, our expectation of a non-linear relationship between age and digital payments is confirmed, as evidenced by the application of the Robin Hood algorithm. Specifically, we observe a positive correlation between age and digital payment usage. However, this trend reverses beyond a specific breakpoint, approximately around the age of 40, leading to a subsequent decline in digital payment activity. Furthermore, our research shows that individuals who utilised alternative payment methods alongside cash before the COVID-19 pandemic are likelier to engage in higher digital payments. Additionally, a tendency for higher adoption of digital payments coincides with countries that achieved a higher Digital Access Index (DAI), an indicator assessing the degree of digitalisation in a country. Furthermore, it is associated with countries among the Euro Area’s founding members.
- ItemInvestigating the determinants and effects of prestige sensitivity in fashion retailing(Technická Univerzita v Liberci, ) Anic, Ivan-Damir; Kursan Milakovic, Ivana; Mihic, Mirela; Ekonomická fakultaTargeting the prestige fashion segment enables fashion retailers to continue growing while facing a challenging environment. To attract prestige-sensitive consumers, it is important to understand their buying motivations and responses to retail actions. Thus, this paper examines the motivational predictors and effects of prestige sensitivity in fashion retailing, using the symbolic self-completion theory as a framework. It also explores the moderating role of fashion innovativeness. The data collected from shoppers of apparel products (N = 289) in Croatia were analyzed using structural equation modelling (SEM). The results show that recognition enhancement, sexual attraction, and recreation shopping motivations, which help enhance individuals’ self-identity in society, drive prestige sensitivity. At the same time, fashion innovativeness significantly moderates the relationship between recreation motive and prestige sensitivity. Prestige-seeking consumers positively respond to mannequin displays, spend more time shopping, and focus more on symbolic apparel attributes while shopping. This study contributes to the self-completion theory applied in fashion retailing by developing and testing the model that links prestige sensitivity with shopping motivations, fashion innovativeness, the selection of apparel attributes, response to visual merchandising, and time expenditure. The findings provide recommendations for marketers on how to develop fashion products/prestige brands in line with the expectations of prestige-seeking shoppers, target this market segment more efficiently, and increase the effectiveness of marketing efforts.
- ItemRegional COVID-19 cases and Bitcoin volatility: Assessment through the Markov switching prism(Technická Univerzita v Liberci, ) Phan, Dat Minh; Hoang, Sinh Duc; Duy Dao, Tung; Pham, Tien Phat; Ekonomická fakultaThe 21st century has become the century of technology, which has spread to the currency market, presenting the international economic system with a new challenge – the challenge created by digital currency, which has determined a change in the rules of operation in the market. The main property of cryptocurrencies in general, and Bitcoin in particular, is constant volatility and mutual sensitivity to each other. This article aims to analyze the cryptocurrency market landscape from both short-term and long-term perspectives. Additionally, the article seeks to quantitatively assess the contradictions, trends, and patterns of price volatility in Bitcoin by employing the framework of Markov switching during the period spanning from 2020 to 2022. The Markov switching model was used in the study. In this study, the factors influencing volatility on different modes of the Markov switch are the COVID-19 pandemic and the Pearson correlation statistical method. The Chisquared test was estimated to identify the connection between Bitcoin volatility switching modes and the COVID-19 pandemic spread. This analysis enables international investors to diversify with maximum efficiency and returns using available hedging tools. However, several open questions remain for future research. Future studies can analyze different cryptocurrencies’ volatility. This research helps to assess the nature of the relationship of cryptocurrencies in statistics (the correlation of cryptocurrencies as of December 1, 2021, when no significant events in the financial market and political upheavals were recorded) and dynamics (the Markov switching models for the postpandemic period of 2020–2022). The article contributes to understanding the interdependence and sensitivity of different cryptocurrencies in relation to each other.
- ItemAn attempt to resolve no-wait flow shop scheduling problems using hybrid ant colony and whale optimization algorithms(Technická Univerzita v Liberci, ) Rostamzadeh, Reza; Gholipour, Arezou; Komari Alaei, Mohammad Reza; Zavadskas, Edmundas Kazimieras; Saparauskas, Jonas; Ekonomická fakultaThe incentive for many developments and scientific progresses within the field of scheduling has emerged from industrial environments, and naturally, it could be utilized in expressing the scheduling concepts regarding terms used in the industry. Generally speaking, scheduling problems are known as limited optimization issues through which decisions related to the machines’ assignment and works processing sequence are probed. Thus, following a review of the related literature, the major goal of this research is to design a mathematical model and to solve it through a meta-heuristic for no-wait flow shop scheduling problem using different machines for the purpose of minimizing the time required to complete the work using whale and ant colony optimization (ACO) algorithms in Sanat-Gostar-e-Hamgam Shoe Company. The ACO and whale algorithm methods are used to compare and predict scheduling activities in manufacturing line of shoe industry. The results showed an ACO algorithm with two stages in mean ideal distance (MID) end amounting to 76.65 and 77.38, respectively. Also, regarding the amounts of standard error mean squares, it could be claimed that the model designed using the improved whale algorithm has a better prediction, and the minimum time required to complete works using the whale algorithm is estimated to be equal to 86.1071. This could lead to an optimal state in achieving the predetermined goals.
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