Publikační činnost Katedry podnikové ekonomiky a práva / Publications of Department of Business Administration (152)

Permanent URI for this collectionhttp://hdl.handle.net/10084/70911

Kolekce obsahuje bibliografické záznamy publikační činnosti (článků) akademických pracovníků Katedry podnikové ekonomiky a práva (152) v časopisech registrovaných ve Web of Science od roku 2003 po současnost.
Do kolekce jsou zařazeny:
a) publikace, u nichž je v originálních dokumentech jako působiště autora (adresa) uvedena Vysoká škola báňská-Technická univerzita Ostrava (VŠB-TUO),
b) publikace, u nichž v originálních dokumentech není v adrese VŠB-TUO uvedena, ale autoři prokazatelně v době jejich zpracování a uveřejnění působili na VŠB-TUO.

Bibliografické záznamy byly původně vytvořeny v kolekci Publikační činnost akademických pracovníků VŠB-TUO, která sleduje publikování akademických pracovníků od roku 1990.

V ak. roce 2024/2025 sloučeno s katedrou 119, název změněn z Katedra podnikohospodářská na Katedra podnikové ekonomiky a práva.

Browse

Now showing 1 - 20 out of 52 results

Work engagement and burnout syndrome of civil servants during and after the covid-19 pandemic
(Czestochowa University of Technology, Faculty of Management, 2023) Mokrá, Kateřina; Poláková, Gabriela; Horváthová, Petra; Štverková, Hana
There have been a number of changes in organizations in the context of anti-epidemic measures, so the authors aim to examine the level of engagement of civil servants before the pandemic and now and to examine the correlation between engagement and burnout syndrome. Based on a review and analysis of the available Czech and foreign literature, a questionnaire survey was prepared, and a survey was conducted on a sample of 984 respondents (civil servants) in the Czech Republic. The Utrecht Work Engagement Scale and a questionnaire assessing burnout syndrome were used. The data were processed using statistical methods. In addition, parametric paired t-test and one-way ANOVA were used. This study provides insight into the current state of the issue and possible changes caused by the covid-19 pandemic. For the observed sample of respondents, it was found that burnout syndrome had no impact on the engagement of civil servants; age had no impact on the burnout syndrome of civil servants, and the level of engagement of civil servants was higher in 2022 than before the pandemic. The novelty of the study is the focus on the measurements mentioned above, as similar research has not been conducted in the Czech Republic yet. The findings from this research may be useful for practitioners and the management of public institutions if a similar situation arises in the future.
The moderating role of a corporate life cycle with the impact of economic value-added on corporate social responsibility: Evidence from China's listed companies
(Elsevier, 2023) Wu, Xiaojuan; Dluhošová, Dana; Zmeškal, Zdeněk
The moderating role of corporate life cycle stages with the impact of relative economic value added (EVA) indicator on corporate social responsibility participation index (CSRPI). Chinese Ashare listed companies are investigated. The CSRPI weights are calculated by Analytic Network Process. Fractional regression with interaction is used. The corporate life cycle stages moderate the relationship between relative EVA measure and CSRPI. Surprisingly, this impact is confirmed for companies at non-mature stages, but not for mature companies. Model type, weights and corporate life cycle robustness were confirmed. The findings have implications for stakeholders in understanding companies' social behaviour in the Chinese market.
Hybrid demand forecasting models: pre-pandemic and pandemic use studies
(Polskie Towarzystwo Ekonomiczne Oddział w Toruniu, Instytut Badań Gospodarczych, 2022) Kolková, Andrea; Rozehnal, Petr
Research background: In business practice and academic sphere, the question of which of the prognostic models is the most accurate is constantly present. The accuracy of models based on artificial intelligence and statistical models has long been discussed. By combining the advantages of both groups, hybrid models have emerged. These models show high accuracy. Moreover, the question remains whether data in a dynamically changing economy (for example, in a pandemic period) have changed the possibilities of using these models. The changing economy will contin-ue to be an important element in demand forecasting in the years to come. In business, where the concept of just in time already proves to be insufficient, it is necessary to open new research questions in the field of demand forecasting.Purpose of the article: The aim of the article is to apply hybrid models to bicycle sales e-shop data with a comparison of accuracy models in the pre-pandemic period and in the pandemic period. The paper examines the hypothesis that the pandemic period has changed the accuracy of hybrid models in comparison with statistical models and models based on artificial neural net-works.Models: In this study, hybrid models will be used, namely the Theta model and the new fore-castHybrid, compared to the statistical models ETS, ARIMA, and models based on artificial neural networks. They will be applied to the data of the e-shop with the cycle assortment in the period from 1.1. 2019 to 5.10 2021. Whereas the period will be divided into two parts, pre -pandemic, i.e. until 1 March 2020 and pandemic after that date. The accuracy evaluation will be based on the RMSE, MAE, and ACF1 indicators.Findings & value added: In this study, we have concluded that the prediction of the Hybrid model was the most accurate in both periods. The study can thus provide a scientific basis for any other dynamic changes that may occur in demand forecasting in the future. In other periods when there will be volatile demand, it is essential to choose models in which accuracy will decrease the least. Therefore, this study provides guidance for the use of methods in future periods as well. The stated results are likely to be valid even in an international comparison.
Demand forecasting: AI-based, statistical and hybrid models vs practice-based models - the case of SMEs and large enterprises
(Centre of Sociological Research, 2022) Kolková, Andrea; Ključnikov, Aleksandr
Demand forecasting is one of the biggest challenges of post-pandemic logistics. It appears that logistics management based on demand prediction can be a suitable alternative to the just-in-time concept. This study aims to identify the effectiveness of AI-based and statistical forecasting models versus practice-based models for SMEs and large enterprises in practice. The study compares the effectiveness of the practice-based Prophet model with the statistical forecasting models, models based on artificial intelligence, and hybrid models developed in the academic environment. Since most of the hybrid models, and the ones based on artificial intelligence, were developed within the last ten years, the study also answers the question of whether the new models have better accuracy than the older ones. The models are evaluated using a multicriteria approach with different weight settings for SMEs and large enterprises. The results show that the Prophet model has higher accuracy than the other models on most time series. At the same time, the Prophet model is slightly less computationally demanding than hybrid models and models based on artificial neural networks. On the other hand, the results of the multicriteria evaluation show that while statistical methods are more suitable for SMEs, the prophet forecasting method is very effective in the case of large enterprises with sufficient computing power and trained predictive analysts.
Modified PROMETHEE V method for supplier portfolio selection
(4S go, s.r.o., 2022) Zapletal, František; Trumic, Rijad; Lenort, Radim
This paper focuses on the problem of supplier portfolio selection where a company has to choose the best possible set of suppliers with respect to various constraints. An intuitive heuristic can suggest to use any of the methods for suppliers ranking and then to put the first one into the portfolio. If some required constraint is not met, then the second supplier according to the ranking is added, and so on, until all the constraints are satisfied. However, such approach can result in a non-optimal decision. The constraints can cause that a combination of the alternatives with lower rankings can be better, than some higher-ranked alternative from the perspective of feasibility. To build the optimization model, the authors of this paper use the PROMETHEE V method: a popular combination of multi-criteria decision making method PROMETHEE and mixed integer programming. However, it is shown that the original PROMETHEE V method, namely the logic under which an objective function is set, is not suitable here and leads to discrimination of suppliers with worse ranking. Therefore, a modification, which brings more reasonable results, is proposed in this paper. A numerical example is used to show the suitability of the proposed approach and compare the results with the original algorithm and also with one prior modification introduced by by other authors in the past. The analysis is further supported by a thorough sensitivity analysis using flexible and parametric programming.
Innovation ecosystem in selected regions of the Czech Republic and Poland: Specifics of infrastructure supporting innovative entrepreneurship
(Univerzita Pardubice, Fakulta ekonomicko-správní, 2022) Peterková, Jindra; Czerná, Katarzyna; Zimmermannová, Jarmila
There are no official statistics in the Czech Republic and Poland mapping the number of start-ups, spin-offs, and organizations supporting innovative businesses. The paper defines the specifics of innovation ecosystem in selected regions of the CZ Moravian-Silesian Region and PL Silesian Voivodeship. Similar economic and socio-cultural developments characterize chosen regions. Hypotheses are defined whose statistical significance is evaluated through the Pearson Chi-Square test. The results are estimated separately for the Moravian-Silesian Region and Silesian Voivodeship and focus on identifying the ownership of organizations, the nature of services provided, and the average annual occupancy of clients in the business phase financing business support programs and possible cooperation between organization. Using the hierarchical cluster analysis with the Ward method, the authors described four clusters. Based on the results obtained from the solution, a general model of the innovation ecosystem supporting innovative entrepreneurship is defined.
Employee perception of CSR and its effects on the company's image
(De Gruyter, 2022) Rosak-Szyrocka, Joanna; Żywiołek, Justyna; Shengelia, Natia; Štverková, Hana; Santo, Pedro Espírito; Pilař, Ladislav
Understanding and promoting the CSR is an important societal issue, and circumstances force modern-minded management to abandon the classical model of only the necessary fulfilment of legally set obligations. There has been a lot of study done on employee perceptions of CSR in the workplace, but very little has been done on how employees comprehend CSR and how they received it at their workplace in chosen countries. Research was carried out based on a questionnaire survey with data collection from September 2020 to March 2021, with a total of 1103 respondents. The aim of the article is to describe the CSR concept among employees meaning in selected countries: Zimbwabwe, Czech Republic, Poland. The measuring instrument used in the study was the questionnaire method, in which the research tool is a questionnaire CAWI - Computer Assisted Web Interview. It was shown that enterprises apply CSR activities, but they are not fully aware of the CSR benefits.
Competency gaps of employees in the construction sector in terms of the requirements of a low-carbon economy. Polish and Czech case
(MDPI, 2021) Howaniec, Honorata; Wróblewski, Łukasz Krzysztof; Štverková, Hana
Environmental policy obliges modern society to transition to a low-carbon economy. After entering to life, the Paris Agreement obligated the signatories to prepare the first nationally determined contributions (NDCs). The NDCs aim first to reduce greenhouse gas emission targets under the UNFCCC and they apply equally to both developed and developing countries. Countries voluntarily indicate what actions will be taken to achieve the declared goals. The construction sector is an industry that is under scrutiny due to its negative impact on the environment, but it also has the potential to reduce it. Activities that can reduce greenhouse gas emissions can be carried out at various levels in the construction industry. One of them is the appropriate preparation of the staff, including equipping them with the so-called green skills. This research aimed to determine the competency gaps of people employed in the construction industry, including competencies in the field of low-emission economy. For the purposes of the study, a questionnaire survey was carried out in Poland and the Czech Republic and based on the results obtained the appropriate competencies were determined that should be possessed by people employed in the construction sector, including competencies related to a low-emission economy. Competency profiles for people employed in the construction sector were built and competency gaps of these people were determined. In both countries, no competencies have been identified in any of checked areas that meet or exceed the requirements of managers according to specific competency profiles.
Demand forecasting: An alternative approach based on technical indicator Pbands
(Instytut Badań Gospodarczych, 2021) Kolková, Andrea; Ključnikov, Aleksandr
Research background: Demand forecasting helps companies to anticipate purchases and plan the delivery or production. In order to face this complex problem, many statistical methods, artificial intelligence-based methods, and hybrid methods are currently being developed. However, all these methods have similar problematic issues, including the complexity, long computing time, and the need for high computing performance of the IT infrastructure. Purpose of the article: This study aims to verify and evaluate the possibility of using Google Trends data for poetry book demand forecasting and compare the results of the application of the statistical methods, neural networks, and a hybrid model versus the alternative possibility of using technical analysis methods to achieve immediate and accessible forecasting. Specifically, it aims to verify the possibility of immediate demand forecasting based on an alternative approach using Pbands technical indicator for poetry books in the European Quartet countries. Methods: The study performs the demand forecasting based on the technical analysis of the Google Trends data search in case of the keyword poetry in the European Quartet countries by several statistical methods, including the commonly used ETS statistical methods, ARIMA method, ARFIMA method, BATS method based on the combination of the Cox-Box transformation model and ARMA, artificial neural networks, the Theta model, a hybrid model, and an alternative approach of forecasting using Pbands indicator. The study uses MAPE and RMSE approaches to measure the accuracy. Findings & value added: Although most currently available demand prediction models are either slow or complex, the entrepreneurial practice requires fast, simple, and accurate ones. The study results show that the alternative Pbands approach is easily applicable and can predict short-term demand changes. Due to its simplicity, the Pbands method is suitable and convenient to monitor short-term data describing the demand. Demand prediction methods based on technical indicators represent a new approach for demand forecasting. The application of these technical indicators could be a further forecasting models research direction. The future of theoretical research in forecasting should be devoted mainly to simplifying and speeding up. Creating an automated model based on primary data parameters and easily interpretable results is a challenge for further research.
Employee well-being evaluation and proposal of activities to increase the level of health's area - The Czech case
(MDPI, 2021) Horváthová, Petra; Kashi, Kateřina; Štverková, Hana; Mikušová, Marie
Well-being and its evaluation, is currently considered one of the key trends in the practice of companies in the world and in the Czech Republic. Research in the field of well-being confirms that there is a positive correlation between a company's well-being and the company's performance. Satisfied and healthy employees contribute to the prosperity of the company through their higher work productivity and efficiency, and indirectly, through reduced incapacity for work and presenteeism. The purpose of this paper is to evaluate the employees' well-being of a specific company in the Czech Republic and propose activities for increasing the level of the most problematic of five areas of employees' well-being. The authors formulated two research questions and two hypotheses. Research questions were answered on the basis of the evaluation of an online questionnaire survey among 463 production staff of the company, hypotheses were statistically confirmed. The main results of this article include the identification of the most problematic area of well-being-the area of health-as well as the proposal of specific activities to improve the level of this area, the introduction which should achieve higher level of employees work productivity. The benefits of well-being show that companies should pay attention to it.
Demand forecasting in Python: Deep learning model based on LSTM architecture versus statistical models
(Óbuda University, 2021) Kolková, Andrea; Navrátil, Miroslav
Demand forecasting for business practice is one of the biggest challenges of current business research. However, the discussion on the use of forecasting methods in business is still at the beginning. Forecasting methods are becoming more accurate. Accuracy is often the only criterion for forecasting. In the reality of business practice or management is also influenced by other factors such as runtime, computing demand, but also the knowledge of the manager. The goal of this article is to verify the possibilities demand forecasting using deep learning and statistical methods. Suitable methods are determined on based multi-criteria evaluation. Accuracy according to MSE and MAE, runtime and computing demand and knowledge requirements of the manager were chosen as the criteria. This study used univariate data from an e-commerce entity. It was realized 90-days and 365-days demand forecasting. Statistical methods Seasonal naive, TBATS, Facebook Prophet and SARIMA was used. These models will be compared with a deep learning model based on recurrent neural network with Long short-term memory (LSTM) layer architecture. The Python code used in all experiments and data is available on GitHub (https://github.com/mrnavrc/demand_forecasting). The results show that all selected methods surpassed the benchmark in their accuracy. However, the differences in the other criteria were large. Models based on deep learning have proven to be the worst on runtime and computing demand. Therefore, they cannot be recommended for business practice. As a best practice model has proven Prophet model developed at Facebook.
Trends in corporate social responsibility reporting. The case of Chinese listed companies
(MDPI, 2021) Wu, Xiaojuan; Hąbek, Patrycja
Compared with Western developed countries, corporate social responsibility (CSR) implementation in China started relatively late, but so far, its development has been going on for more than ten years. Therefore, the development process of CSR reporting as a vital tool to reflect the CSR related information of Chinese listed companies is worth studying. It has been asserted in a large amount of literature that the government of a country has an important influence on the development of CSR reporting. Thus, in this paper, we aim to study the trends in CSR reporting practices of Chinese listed companies through statistical analysis methods and then consider the role of the government in it. The results show that the number of CSR reports issued by Chinese listed companies has increased year by year; notably, the number of voluntary CSR disclosure and environmental information disclosure has increased significantly. However, the overall disclosure rate of CSR reports is low and shows no upward trend, the published CSR reports lack third-party certification, and the information disclosure level of most CSR reports is concentrated at a relatively low level. The findings provide some useful references for the future development of Chinese CSR related laws, regulations, and guidelines.
Territorial risk management in relation to country risk classification and export
(Czestochowa University of Technology, Faculty of Management, 2021) Petrová, Michaela; Krügerová, Martina; Kozieł, Michal; Štverková, Hana
The subject of research is focused on determining the dependence of exports and the level of territorial risk assessment. Companies assess and manage risks that may affect the course of their contracts. Information on business partners, territorial and commercial risks are an important tool of territorial risk management. For the exporter it is all the more important to focus on the risks associated with international reach, which may already be more difficult to assess, in terms of data acquisition and their proper evaluation. They must also decide on the appropriate way to hedge the risks. Various tools and specialized institutions can help exporters with risk assessment. The aim of the article is to evaluate the extent to which published assessments of territorial risks influence decision-making and management of territorial risks in connection with the resulting export. Based on the analysis of data from primary sources and OECD and EGAP data from 1999 to 2018, the relationship between risk assessment and export volume in selected countries was examined. The results of the analysis show that the riskiness of countries has an impact on the resulting exports.
Modeling of prospects for the development of regional renewable energy
(MDPI, 2021) Drobyazko, Svetlana; Wijaya, Suparna; Blecharz, Pavel; Bogachov, Sergii; Pinskaya, Milyausha
It has been proven that to solve the problems that arise in the combinatorial modeling of the prospects for the development of regional renewable energy, an algorithmically simple general combinatorial approach is the most appropriate option. The conceptual express method and corresponding mechanisms of the economic estimation of the efficiency of variants of the formation of regional systems of renewable energy have been suggested. These variants take into account the inflationary factors which serve as a basis of the analysis of investment and innovative projects of renewable energy sources by means of combinatorial modeling methods. To qualitatively analyze the effectiveness of the compared options, the system of existing indicators of the economic efficiency of renewable energy sources at the meso-level has been studied. The system was supplemented by informal and environmental indicators, the need for which is due to the fact that they have a significant impact on renewable energy in the region. Factors that significantly determine the effectiveness of the investment and innovation project for the introduction of renewable energy sources into the regional economy have been substantiated.
Corporate social responsibility and profitability: The moderating role of firm type in Chinese appliance listed companies
(MDPI, 2021) Wu, Xiaojuan; Dluhošová, Dana; Zmeškal, Zdeněk
Corporate social responsibility (CSR) is among the dominant multi-attribute methods of comprehensively representing the competitiveness of a company. A large number of studies have commonly found that profitability can positively affect CSR. However, positivity depends on firm type and the economy, and there is little research in this area. The objective of this paper is to study and verify whether the profitability of different types of companies has a comparable impact on CSR measures in Chinese appliance listed companies. A specific multi-attribute AHP (analytic hierarchy process) model was proposed to determine the CSR for the conditions of Chines appliance listed companies. The interactive regression model serves to analyse the impact of a firm type. The specific multi-attribute AHP model was verified as a suitable tool for CSR evaluation of Chines appliance listed companies. The regression results show that for family firms, the impact of profitability on CSR is significant, while for non-family firms, the impact was not confirmed. Thus, evidence that family firms fulfil better CSR than non-family firms in the investigated Chinese sector is offered. The findings provide proof that it is essential to distinguish firm types, and the generalised findings are simplified and not valid.
Wellbeing as a core area of line managers' work in cross-border organizations
(Czestochowa University of Technology, Faculty of Management, 2020) Horváthová, Petra; Kashi, Kateřina; Štverková, Hana; Mikušová, Marie
According to a number of studies and experts, one of the most important aspects of current human resources management in the world and in the Czech and Polish Republic is wellbeing. Research in the field of wellbeing confirms that there is a positive mutual relationship between employees' wellbeing and organization business results. Employees with high level of wellbeing are more engaged, higher perform and then more contribute to the better organization performance through their higher work productivity and efficiency and lower turnover. How people are treated at work by organizations and their managers, especially line managers, strongly affect the level of their wellbeing. The aim of this study is to assess the wellbeing of employees of the selected cross-border organizations in the Czech and Polish Republic and propose measures for increasing the level of the worst rated area of employees' wellbeing. Two formulated research questions were answered on the basis of the evaluation of an online questionnaire survey. This study reveals the area of health as the worst evaluated area of wellbeing and proposes several measures to increase the level of this area, which can be considered as its main outputs. The implementation of these measures focused on the health area should bring higher level of employees' engagement and performance and better organizations' results of operation.
A general model based on the DuPont system of financial analysis for identification, analysis and solution of a potential crisis in a business
(MDPI, 2020) Kašík, Josef; Šnapka, Petr
The purpose of this article is to create a general model using the data commonly available in the managerial accounting system for the signalization of a possible potential crisis. The critical level of the input variables influencing the return of equity (ROE) and return on sales (ROS) was theoretically determined based on the DuPont system of financial analysis. To determine actual amount of the input variables for the test of their critical amount in a real company, we considered their average amount based on a simple arithmetic mean. For the real analysis in a potentially threatened company, we considered one month as a time unit for the time interval in a range of 14 months. We determined the average actual amounts of the input variables using confidence intervals. Because of the relatively small sample, we used Student's t-distribution for the construction of confidence intervals of the input variables. An analytical model-based system approach based on analysis of the complex value chain was used. By the means of logical derivations and testing this analytical model-based system approach in a real company, we proved, that this model enables not only to determine the critical level of the input variables leading to a crisis in a business but also to calculate their new adjusted amount, which the business needs to reach so that a potential crisis can be solved. The presented theoretical model was successfully applied to solve a real potential crisis in a particular Czech company which supports the correctness and practical applicability of this general model. There are two main advantages of this model: 1) it can use the data commonly available in the managerial accounting system, 2) this model is generally valid, i.e., it can be used in any business producing goods or services.
The application of forecasting sales of services to increase business competitiveness
(Univerzita Tomáše Bati ve Zlíně, Fakulta managementu a ekonomiky, 2020) Kolková, Andrea
The accurate forecasting of business variables is a key element for a company's competitiveness which is becoming increasing necessary in this globalized and digitalized environment. Companies are responding to this need by intensifying accuracy requirements for forecasting economic variables. The objective of this article is to verify the correctness of the models predicting revenue in the service sector against 6 precision criteria to determine whether the use of certain criteria may lead to the adoption of particular models to improve competitive forecasting. This article seeks to determine the best accuracy predictors in 32 service areas broken down by NACE. Exponential smoothing models, ARIMA models, BATS models and artificial neural network models were selected for the assessment. Six criteria were chosen to measure accuracy using a group of scale-dependent errors and scaled errors. Services for which the result was ambiguous were subject to complete forecasting, both ex-post and ex-ante. Based on the analysis, the main result of the article is that only two types of services do not achieve the same accuracy results when using other measure criteria. It can therefore be said that for 93.75% of services, an assessment according to one precision parameter would suffice. Thus, a model's competitiveness is not affected by the choice of accuracy.
Analysis of types, intensity, methods and effects of process innovations
(Technická univerzita Košice, 2019) Macurová, Pavla; Peterková, Jindra; Czerná, Katarzyna
Purpose: The purpose is to provide knowledge about the intensity and types of process innovation in the business sphere, as well as the representation of entities involved in creating innovation, and about the effects of process innovation. Methodology/Approach: Data from the statistical survey on innovation activities carried out by the Czech Statistical Office according to the Eurostat methodology were used, supplemented by some results of the own questionnaire survey. Methods of sorting, size arrangement, structure analysis, comparison, context analysis were used. Findings: The large enterprises were significantly more active than SMEs in implementing process innovations, as well as foreign affiliates were more active than domestic enterprises. Besides typical competitive advantages of process innovation benefits the benefits in ecology, occupational safety and reduced labour demand have also proved to be numerous. Co-operation of enterprises with universities has proved to be low. The lack of skilled workers and financial resources were the main obstacles to the innovation activity of enterprises. Research Limitation/implication: The research is focused on companies in the Czech Republic. Originality/Value of paper: The actual contribution of the article lies in the purpose-oriented comparison of process innovations between fields of enterprise activities, especially in the area of logistics innovations, in some aspects the comparison of process-innovation activities according to the size of the company and the ownership of the company.
Decision making support for managers in innovation management: A PROMETHEE approach
(University Nove de Julho, 2018) Peterková, Jindra; Franek, Jiří
The purpose of this paper is to present a decision making model as a support for selection of innovation management concept using multiple criteria decision making methods. Based on the specific nature of innovation management concepts a novel decision making model was designed. Ten defined innovation management concepts are firstly evaluated using set of criteria, which priorities are expertly evaluated using Saaty method and then the PROMETHEE outranking method is used for evaluating and selecting of innovation management concepts. To apply this model in the practice the Visual PROMETHEE software tool is incorporated to the model. The model was applied on a large manufacturing company. Using our approach in this company, the concept of value analysis was selected as the best. This study is limited for decision making processes in large companies. The results of Saaty method are based on expert but subjective assessment and therefore relevant for this particular company at that particular time. In addition, we suggest that this model can help managers to solve similar decision making problems using combination of Saaty method or analytic hierarchy process together with Visual PROMETHEE software. The logic and process of the decision making model elaboration as well as the decision model itself can be used as a framework for managers facing decision making problems with similar nature as innovation management concepts i.e.: ERP systems, information systems, technologies, business models.

Browse

Recent Submissions