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    Assessment of Logistics Platform Efficiency Using an Integrated Delphi Analytic Hierarchy Process-data Envelopment Analysis Approach: A Novel Methodological Approach Including a Case Study in Slovenia
    (Technická Univerzita v Liberci, ) Bajec, Patricija; Kontelj, Monika; Groznik, Aleš; Ekonomická fakulta
    The objective of this study is to propose a trustworthy, valid and consistent methodological approach for measuring the efficiency of a logistics platform, where an entire country constitutes a logistic platform. Traditional Data Envelopment Analysis (DEA) is found to be an appropriate tool – if its weaknesses are eliminated. DEA results are highly influenced by the choice of appropriate inputs and outputs variables, but the method itself does not provide guidance for their identification. The authors therefore propose to integrate traditional DEA by combining the Delphi technique with the Analytical Hierarchy Process (AHP) method, which will assist in identifying proper, consistent input/output variables, evaluated by their relevance. The proposed framework allows the performance evaluation of the selected platform’s element or elements. It is thus a useful decision support tool for enterprises (private, public, both) that are managing logistics platforms and trying to improve their productivity in order to sustain or improve their position on the competitive market. This methodology allows comparative efficiency analyses to be estimated for similar countries. The presented methodology on one hand enables tailor-made solutions, but on the other hand is very general, and, with minor adjustments, can be applied by a variety of firms and industries. It can be applied in private sector firms in production and service industries, to analyse the relative performance of diverse logistics and non-logistics services, and in public profit or non-profit organisations.
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    Prospective MADM and Sensitivity Analysis of the Experts Based on Causal Layered Analysis (CLA)
    (Technická Univerzita v Liberci, ) Hashemkhani Zolfani, Sarfaraz; Yazdani, Morteza; Zavadskas, Edmundas Kazimieras; Hasheminasab, Hamidreza; Ekonomická fakulta
    “Multiple Attribute Decision Making (MADM)” is an expert based field which is working based on real data and experts’ opinions. So many studies have been doing based on MADM methods which they usually use qualitative data based on experts’ ideas. Decisions based on the experts’ opinion shall be carefully designed to cope the real problems uncertainty. This uncertainty will be even more intricate if combining the problem with the ambiguity of the future study. Prospective MADM is a future based type of MADM field which is concentrating on decision making and policy making about the future. Prospective MADM (PMADM) can have both explorative and descriptive paradigms in the studies but it will more useful to be applied for strategic planning. In this regard, experts’ role would be even more challenging because one/some possible future/futures will be partially designed based on their opinions. Future and prediction always complicates the decision environment, especially methodologies founded on experts’ judgement. Considering experts’ preferences, attitude, and background, they may be a major source of inaccurate results. Causal Layered Analysis (CLA) is well-known “Futures Studies” method which is qualitative and usually is supporting other methods such as “Backcasting” and “Scenario Planning”. CLA has a deep point of view to the subjects to support a future with all those changes which are necessary for the main goal/goals. In this study, this idea will be proposed that CLA can be added to PMADM outline to decrease the risk of unsuitable decisions for the future and for this aim a case study about energy and CO2 consumption in policy making level proposed and a hybrid MADM method based on BWM-CoCoSo applied in the PMADM outline for the procedure.
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    Methodology of Industry Statistics: Averages, Quantiles and Responses to Atypical Value
    (Technická Univerzita v Liberci, ) Boďa, Martin; Úradníček, Vladimír; Ekonomická fakulta
    The paper notices troublesome aspects of compiling industry statistics for the purpose of inter-enterprise comparison in corporate financial analysis. Whilst making a caveat that this issue is unbeknownst to practitioners and underrated by theorists, the goal of the paper is two-fold. For one thing, the paper demonstrates that financial ratios are inclined to frequency distributions characteristic of power-law (fat) tails and their typical shape precludes a simple treatment. For the other, the paper explores different approaches to compiling industry statistics by considering trimming and winsorizing cleansing protocols, and by confronting trimmed, winsorized as well as quantile measures of central tendency. The issues are empirically illustrated on data for a great number of Slovak construction enterprises for two years, 2009 and 2018. The empirical distribution of eight financial ratios is studied for troublesome features such as asymmetry and power-law (fat) tails that hamper usefulness of traditional descriptive measures of location without considering different possibilities of handling atypical values (such as infinite and outlying values). The confrontation of diverse approaches suggests a plausible route to compiling industry statistics that consists in reporting a 25% trimmed mean alongside 25% and 75% quantiles, all applied to trimmed data (i.e. data after discarding infinite values). The paper also highlights the sorely unnoticed fact that the key ratio of financial analysis, return on equity, may easily attain non-sense values and these should be removed prior to compiling financial analysis; otherwise, industry statistics is biased upward regardless of what measure of central tendency is made use of.
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    Face-to-face and Electronic Communication with Customers in Retailing and Company Performance: A Case Study in the Electronics and Communication Equipment Retail Industry in the Czech Republic
    (Technická Univerzita v Liberci, ) Eger, Ludvík; Suchánek, Petr; Ekonomická fakulta
    Customers today can find the same assortments in a number of retail stores and through the Internet, thus effective store management has become a critical basis for developing strategic advantages. The aim of this research is to identify whether customer satisfaction measured by means of mystery shopping and the results of communication with the public on a company’s Facebook profile assessed by quantitative analysis influence the performance of the selected companies. The evaluation of customer satisfaction and loyalty follows the older pilot study and is newly supplemented by an analysis of communication with customers using social media such as Facebook. The company’s performance is evaluated through the financial ratios (ROA, ROE and ATO) based on accounting data available in the Magnusweb database. The research is focused on selected companies from the electronics and communication equipment retail industry in the Czech Republic and is unique from that point of view because it analyses communication with customers not only in retail shops but concurrently on their profiles for Facebook. The findings show how it is possible to assess the level of customer-oriented communication in retail shops and also the level of communication with customers on the social network. Retailers are increasing their focus on customers’ experience in their shops and on social media sites. The research contributes to a better understanding of marketing in retail and on social media in the selected industry.
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    Impact of Stock Markets on the Economy in V4 Countries
    (Technická Univerzita v Liberci, ) Krkošková, Radmila; Ekonomická fakulta
    The performance of the economy should generally reflect the performance of stock markets. Production increases, prices rise, and companies’ profits increase if the economy grows. And the shares should naturally make the profits (which means among other things, higher dividends) even more attractive. But is that really true? The aim of the article is to find out the relationship between the development of stock markets and the economic growth in Visegrad Group countries (V4). The subject of the survey is both the long-term relationship and the short-term relationship in the course of economic cycles. The article uses the tools of time series econometrics, especially VECMs, including corresponding diagnostics, Granger causality and block erogeneity. The relationships between the variables examined vary from country to country. The long-term relationship between the development of stock markets and the economic growth was confirmed in Slovakia and Hungary. It was confirmed that the GDP growth rate influenced the growth rate of stock indices in all V4 countries. The opposite relationship (the stock index growth rate influences the GDP growth rate) was not confirmed only in the Czech Republic. Quarterly data for the period from 2005/Q1 to 2018/Q4 was used for the analysis. This period was selected because all of the V4 countries have been members of the European Union since 2004. The EViews software version 9 was used for the calculations. Variables used in this research are: the GDP, the stock exchange index of the country and stock trading volume. The PX, SAX, BUX and WIG20 stock indices are considered to be the crucial representatives of individual stock markets in this work.