Číslo 3

Permanent URI for this collection


Recent Submissions

Now showing 1 - 5 of 13
  • Item
    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.
  • Item
    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.
  • Item
    DEA Approach for Performance Assessment of Call Centre Agents
    (Technická Univerzita v Liberci, ) Mendelová, Viera; Strnádová, Petra; Ekonomická fakulta
    The paper focuses on a relatively new and prospective application of the data envelopment analysis (DEA) in the employee performance assessment. In the paper, a novel DEA approach is proposed for evaluating the performance of call centre agents, based on their relative efficiency. Since call centres handle a majority of customer-company interactions, performance of call centre agents largely influences the future success or failure of a company. To ensure the quality of customer service, permanent evaluation of call centre agents’ performance is essential. The proposed DEA model consisting of two input variables (wage and working time) and five output variables (quick-answer calls proportion, customer satisfaction, net first contact resolution, call quality and inbound contact handle time) has been tested on 55 call centre agents working at the call centre of one of the largest telecommunications operators in the Slovak Republic. After measuring the performance of each agent, based on the DEA models, the call centre agents’ performance was evaluated in the DEA matrix format. As a result, the call centre agents were divided into four groups: Stars, Cash Cows, Question Marks and Poor Dogs. Finally, based on the proposed approach, recommendations for call centre managers on how to improve or maintain the performance of each of these groups were drawn. The proposed approach provides a practical framework for call centre managers to assess the performance of the agents, and to plan and take steps to improve the quality of call centre services.
  • Item
    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.
  • Item
    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.