Číslo 4

Permanent URI for this collection


Recent Submissions

Now showing 1 - 5 of 12
  • Item
    (Technická Univerzita v Liberci, ) Su, Wunhong; Fan, Yi-Hao; Ekonomická fakulta
    This study explores the relationship between income tax preference and R&D investments of high-tech enterprises. This study selects listed high-tech enterprises in China from 2013 to 2018 as samples. The empirical results show that the effective income tax rate among high-tech enterprises in China differs widely. The findings suggest that high-tech enterprises in China have to take advantage of preferential income tax, pay more attention to R&D investments, and strive to improve R&D ability and market competitiveness. In addition, there is a significantly positive relationship between income tax preference and R&D investments of high-tech enterprises, indicating that the preferential tax rate policy and other tax incentives such as additional tax deduction increase R&D investments of high-tech enterprises effectively. State-owned enterprises (SOEs) are enterprises in which the state has ownership or control over its capital. The positive relation between income tax preference and R&D investments of hightech enterprises is more significant for non-SOEs. Non-SOEs have stronger governance efficiency. Therefore, SOEs should make better use of income tax preference and improve innovation enthusiasm. Moreover, this study finds a more positive relationship between income tax preference and R&D investments among high-tech enterprises in the introduction phase than in the growth and mature phases. However, the relation between income tax preference and R&D investments is insignificant for high-tech enterprises in the decline phase. The findings seem to provide a new perspective for the life cycle characteristics of enterprises and the theoretical guidance to enterprises in phases of growth, mature and decline to develop R&D investments better. Finally, loss enterprises or enterprises in geographical units with the innovative environment are eliminated in this study to avoid extra interference. The results remain robust, indicating that preferential income tax policies applied in high-tech enterprises are significantly and positively associated with R&D investments.
  • Item
    (Technická Univerzita v Liberci, ) Svoboda, Milan; Říhová, Pavla; Ekonomická fakulta
    The article describes empirical research that deals with short-term stock price prediction. The aim of this study is to use this prediction to create successful business models. A business model that outperforms the stock market, represented by the Buy and Hold strategy, is considered to be successful. A stochastic model based on Markov chains analysis with varying state space is used for short-term stock price prediction. The varying state spate is defined based on multiples of the moving standard deviation. A total of 80 state space models were calculated for the moving standard deviation with 5-step lengths from 10 to 30 in combination with the standard deviation multiples from 0.5 to 2.0 with the step of 0.1. The efficiency of the business models was verified for 3 long-term, liquid stocks of the Czech stock market, namely the stocks of KB, CEZ, and O2 within a 14-year period – from the beginning of 2006 to the end of 2019. Business models perform best when they use a state space defined on the length of a moving standard deviation between 15 and 30 in combination with multiples of the standard deviation between 1.1 and 1.2. Business models based on these parameters outperform the passive Buy and Hold strategy. In fact, they outperform the Buy and Hold strategy for both the entire period under review and the yielded five-year periods (including transaction fees). The only exception is the five-year periods covering 2015 for O2 stocks. After the end of the uncertainty period caused by unclear intentions of the new majority stockholder, the stock price rose sharply. These results are in conflict with the efficient markets theory and suggest that in the period under review, the Czech stock market was not effective in any form.
  • Item
    (Technická Univerzita v Liberci, ) Ray, Manidatta; Ray, Mamata; Muduli, Kamalakanta; Banaitis, Audrius; Kumar, Anil; Ekonomická fakulta
    This research work focuses on integrating the multi attribute decision making with data mining in a fuzzy decision environment for customer relationship management. The main objective is to analyse the relation between multi attribute decision making and data mining considering a complex problem of ordering customers segments, which is based on four criteria of customer’s life time value, viz. length (L), recency (R), frequency (F) and monetary value (M). The proposed integrated approach involves fuzzy C-means (FCM) cluster analysis as data mining tool. The experiment conducted using MATLAB 12.0 for identifying eight clusters of customers. The two multi attribute decision making tools i.e., fuzzy AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) are used for ranking these identified clusters. The applicability of the integrated decision making technique is also demonstrated in this paper considering the case of Indian retail sector. This research collected responses from nine experts from Indian retail industry regarding their perception of relative importance of four criteria of customer life value and evaluated weights of each criterion using fuzzy AHP. Transaction data of 18 months of the case retail store was analysed to segment 1,600 customers into eight clusters using fuzzy c-means clustering analysis technique. Finally, these eight clusters were ranked using fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The findings of this research could be helpful for firms in identifying the more valuable customers for them and allocate more resources to satisfy them. The findings will be also helpful in developing different loyalty program strategies for customers of different clusters.
  • Item
    (Technická Univerzita v Liberci, ) Matušínská, Kateřina; Stoklasa, Michal; Ekonomická fakulta
    The aims of the paper are: 1) to verify the validity of the traditional theoretical definition of the Foote, Cone & Belding (FCB) model based on the use of representative products concerning the age (generation) and gender of the selected target group in the conditions of the Czech Republic, and 2) to verify the validity of defined advertising strategies in the traditional theoretical conception of the Foote, Cone & Belding (FCB) model with the current level of acceptance and perception of advertising within the defined selected target group according to age (generation) and gender in the conditions of the Czech Republic. To meet both aims, both secondary and primary marketing research was implemented. The theoretical background of the paper is based on knowledge of marketing communication principles in general with emphasis on advertising theories. The greatest attention is focused on the traditional version of the FCB model which is based on a matrix of consumer thinking–feeling and high–low involvement behaviours and proposes four advertising strategies. Primary research data were obtained using a questionnaire, on the online panel of research agency Ipsos, on 1,100 Czech respondents. The methods used are positional maps for the FCB grid and chi-squared with a suitable post-hoc test. The outputs reveal the differences of the theoretical FCB model in comparison with its practical implementation. It is necessary to adapt (extend) the model according to specific conditions and identification features of different Czech generations and genders, then adjust recommendations for advertising strategies. In Czech conditions, the sextant grind should be used. There is a prevalence of representative product placement in quadrants 1 and 3, i.e., rational appeals even for products where this is not expected. The outcomes can be used for the choice of correct advertising strategy, advertising media, and types.
  • Item
    (Technická Univerzita v Liberci, ) Hossain, Saddam; Gavurová, Beáta; Yuan, Xianghui; Hasan, Morshadul; Oláh, Judit; Ekonomická fakulta
    This paper analyzes the statistical impact of COVID-19 on the S&P500 and the CSI300 intraday momentum. This study employs an empirical method, that is, the intraday momentum method used in this research. Also, the predictability of timing conditional strategies is also used here to predict the intraday momentum of stock returns. In addition, this study aims to estimate and forecast the coefficients in the stock market pandemic crisis through a robust standard error approach. The empirical findings indicate that the intraday market behavior an unusual balanced; the volatility and trading volume imbalance and the return trends are losing overwhelmingly. The consequence is that the first half-hour return will forecast the last half-hour return of the S&P500, but during the pandemic shock, the last half-hour of both stock markets will not have a significant impact on intraday momentum. Additionally, market timing strategy analysis is a significant factor in the stock market because it shows the perfect trading time, decides investment opportunities and which stocks will perform well on this day. Besides, we also found that when the volatility and volume of the S&P500 are both at a high level, the first half-hour has been a positive impact, while at the low level, the CSI300 has a negative impact on the last half-hour. In addition, this shows that the optimistic effect and positive outlook of the stockholders for the S&P500 is in the first half-hours after weekend on Monday morning because market open during the weekend holiday, and the mentality of every stockholder’s indicate the positive impression of the stock market.