Search

This study addresses the "projectification of society" and its alignment with the VUCA framework (Volatility, Uncertainty, Complexity, Ambiguity). Four widely used international project management standards—PMI, IPMA, PRINCE2, and PM2—are evaluated for their suitability in the VUCA environment. The research employs a multicriteria approach, specifically the Weighted Sum Approach method, considering factors like volatility, uncertainty, complexity, and ambiguity. The selected standards are scrutinized based on their adaptability to VUCA challenges, with a focus on PMBOK, IPMA, PRINCE2, and PM2. The seventh edition of the PMBOK has been evaluated on the first position. The study emphasizes the crucial role of selecting an appropriate project management standard for success in navigating the dynamic VUCA world. The results confirmed this and brought a number of recommendations for managing projects in a VUCA environment.

Presented systematic review is analyzing cyber risk management, more specifically economic aspect of the measures resulting from the risk analysis, through search of Web of Science and Scopus databases. The article questions the current scientific knowledge in the field of applicability of quantitative methods on measuring of the negative impact of successful cyberattacks. The purpose of the article is to define how these shall be improved for real application in the environment of healthcare, being specific not only by operating with sensitive patient data, but also by the urgency with which system malfunctions must be dealt with in order to prevent threatening the health and lives of patients (the fact that is providing the attacker with a unique position of privilege). While it is apparently necessary to invest more resources into the cybersecurity in healthcare, it is at the same time essential to ensure that these measures are profitable and the resources for them are spent economically. While cost of human life cannot easily be quantified, it is now time to search for methods on how to define an appropriate cybersecurity investment as opposed to the costs of a potential cyberattack.

Support from European structural and investment funds has a large impact and significantly contributes to the reduction of differences between regions within the European Union. In the case of the Czech Republic the European Union helped from 2004 to 2021 to development of the country with amount of 1,700 billion CZK. This support is mainly offered in the form of subsidies by which individual projects have been supported. 164,537 projects have been implemented in the period from 2004 to the end of the year 2021. In such case of large number of projects financed from public resources is appropriate to manage them effectively and finished successfully. International standards of project management recommend the useful methods, tools and procedures leading to higher efficiency and success. The main goal of the article is to evaluate the knowledge and usage of project management international standards in the organizations implementing the projects financed or co-financed from European structural and investment funds. 171 respondents mainly project managers of this type of projects answer in questionnaire survey. They hardly know international project management standards, and if they do know them, they hardly use them in practice, with the exception of the PRINCE2 methodology, in which they have some certified employees.

The article deals with the issue of assessment of the green growth in context of the Green Deal in the European Union Countries. Because this issue leads to the decision problem which has typical the properties of multi-criteria decision making (MCDM), the Analytical Hierarchy Process (AHP) method, including the sensitivity analysis, was used as a suitable method for solving this issue. The main aim of the paper is to propose a new and suitable approach for a complex and systematically assessed Green Growth in countries of the European Union. The public OECD Green Growth database was used for the analysis. The multicriteria assessment model employs four criteria, indicators for monitoring progress towards green growth (1. Production-based CO2 productivity; 2. Annual surface temperature; 3. The mean exposure of the population exposure to PM2.5; 4. Environmentally related tax). Thanks to the new approach to the Green Growth assessment based on multicriteria evaluation, it is possible to automate this process and it is repeatedly applied. This ultimately provides management authorities with a tool to measure the maturity of the Green Deal not only in EU countries. Based on the proposed multi-criteria model, Ireland is evaluated as the land with the highest level of Green Growth and Latvia as the country with the lowest level in the analyzed year 2020.

Článek se zabývá využitím fuzzy logiky, jakožto vhodného nástroje pro podporu hodnocení rizik v procesu řízení rizik. Nejprve jsou stručně představeny tradiční přístupy k hodnocení rizik, stejně jako základní teoretická východiska související s procesem fuzzy modelování, tj. fuzzy množina, fuzzy číslo, fuzzy logika. Formou případové studie je následně prezentován fuzzy model hodnocení rizik, což je jeho hlavním cílem. K vytvoření, ověření a implementaci fuzzy modelu byl použit Fuzzy Logic Toolbox v softwaru MATLAB., The article deals with the use of the fuzzy logic as a suitable tool to support risk evaluation in the risk management process. First, the current approaches to risk assessment are briefly introduced, as well as the basic theoretical background related to the process of fuzzy modelling, i.e. fuzzy set, fuzzy number, fuzzy logic. The fuzzy model of risk assessment is then presented in the form of a case study, which is its main goal. The Fuzzy Logic Toolbox in MATLAB software was used to create, verify and implement the fuzzy model.

Článek připomíná historii existence metody RIPRAN (RIsk PRoject ANalysis) v průběhu více než 20 let jejího používání, což je současně jeho hlavním cílem. V jednotlivých kapitolách článek představuje historii metody, její ocenění, principy, přednosti, uživatele a nástin možného dalšího vývoje.+, The article recalls the history of the existence of the RIPRAN method (RIsk PRoject ANalysis) during more than 20 years of its use. It is also the main goal of the article. In individual chapters, the article presents the history of the method, its award, principles, advantages, users and an outline of possible further development.

This paper is focused on the root cause analysis of post project phases. The research has been linked to the identification of the 21 most common reasons for not executing post project phases. The main aim of this paper is to identify the root causes of not executing selected post project phases. The empirical research was performed as qualitative research employing the observation and inquiry methods in the form of a controlled semi-structured interview. The research was realised in the Czech Republic in 2017 and 2018. The key performances for ensuring a functional, effective and systematic post project process are based on the principles of knowledge management. The identified causes were used as inputs for the proposed measures with the aim to make the post project process more effective. The main contribution of the paper is the overview of techniques that may be recommended for post project analysis. These techniques are demonstrated in detail on particular examples of the analysis of the most common reasons for failure to implement post project phases. The described examples demonstrate the procedure to be followed in order to identify the root cause of the analysed phenomenon. At the same time, the paper also describes proposals of recommended measures that should minimize the root causes resulting in negative outcomes. The paper explicitly emphasizes and shows the connection between knowledge management and post project phase effectiveness., Příspěvek je zaměřen na analýzu kořenových příčin neprovádění poprojektových fází. Výzkum navazuje na dříve identifikovaných 21 důvodů neprovádění poprojektových fází. Hlavním cílem je identifikovat kořenové příčiny neprovádění vybraných poprojektových fází. Empirický výzkum byl realizován jako kvalitativní výzkum s využitím metody pozorování a dotazování v podobě techniky polostrukturovaného rozhovoru. Výzkum byl realizován v České republice v letech 2017 a 2018. Klíčové ukazatele zajištění funkčního, efektivního a systematického procesu poprojektových fází vychází z principů řízení znalostí. Identifikované příčiny byly použity jako vstupy pro navrhovaná opatření s cílem zefektivnit proces realizace poprojektových fází. Hlavním přínosem článku je přehled technik, které mohou být doporučeny pro analýzu poprojektových fází. Tyto techniky jsou podrobně demonstrovány na konkrétních příkladech nejčastějších důvodů neprovedení fází projektu. Popsané příklady prezentují postup, který je třeba, pro identifikaci kořenových příčin zkoumaného jevu, dodržet. Příspěvek dále popisuje opatření, formou návrhů a doporučení, která by měla minimalizovat příčiny, vedoucí k negativním výsledkům. Příspěvek explicitně zdůrazňuje a ukazuje na souvislost mezi znalostním management a efektivitou poprojektových fází.

The paper is focused on the analysis of the key aspects of sustainability projects, namely advanced risk management and project knowledge. These aspects are recommended to the attention of institutions and project managers when designing and executing new projects simultaneously with quality and project status management. The aim of the paper is to point out the critical factors that have recently affected the success of sustainability projects, which is also its contribution. Empirical research focused on the identification of the application level of the post-project phases in project management in the Czech Republic in 2016 and 2017 was performed. The research was performed as qualitative research employing observation and inquiry methods in the form of a controlled semistructured interview. The research identified 21 most common reasons for not executing post-project phases. Ensuring good and efficient progress of post-project phases, in particular by the means of post-implementation system analysis and compilation of a set of improvement suggestions for subsequent project management, forms the practical background for application of knowledge management and project management principles. A case study focused on the application of fuzzy logic in project risk assessment has been elaborated. In practice, current project management requires the application of advanced risk analysis methods that will replace the simple risk values estimated by calculations of separate risk components., Článek se zaměřuje na analýzu klíčových aspektů projektů udržitelnosti. Jedná se o pokročilé řízení rizik a znalostí projektu. Tyto aspekty doporučují pozornosti institucím a projektovým manažerům při návrhu a realizaci nových projektů současně s řízením kvality a stavu projektu. Hlavním cílem článku je identifikovat kritické faktory úspěchu projektů udržitelnosti, což je současně jeho přínosem. Byl realizován empirický výzkum zaměřený na identifikaci úrovně aplikace po-projektových fází při řízení projektů v České republice v letech 2016 a 2017. Výzkum byl realizován formou kvalitativního výzkumu s využitím metody pozorování a metody dotazování v podobě techniky řízeného polo-strukturovaného rozhovoru. Výzkum identifikoval 21 nejčastějších důvodů, proč se po-projektové fáze nerealizují. Zajistit dobrý a efektivní průběh po-projektových fází, zejména prostřednictvím post-imlementační systémové analýzy a vypracováním souboru návrhů pro zlepšení řízení následných projektů, v praxi představuje východisko pro využívání zásad znalostního management v projektovém řízení. Byla zpracována případová studie zaměřená na aplikaci fuzzy logiky při hodnocení rizik projektu. Současný projektový management v praxi vyžaduje aplikovat pokročilé metody pro analýzu rizik, jež budou nahrazovat prostý odhad celkové hodnoty rizika výpočtem separovaných složek rizika.

The article deals with the issue of a client´s creditworthiness assessment in the insurance industry. The article aims to identify new factors related to a client´s creditworthiness, and to create an assessment model. The factors which have relations to a client´s creditworthiness were identified in the first research stage. These factors represent the inputs into the model. The assessment model of the client´s creditworthiness was created in the second stage. In the third stage, the model was verified and implemented. The neuro-fuzzy method was used for creation, verification and implementation of the model. Five variables were selected as the inputs including damages, insurance length, insurance penetration, annual earnings and 2nd degree liquidity. These input variables were divided into two categories based on their nature (insurance indicators, accounting indicators). Research results show that the proposed model was verified above input data and can be used as a tool for supporting decisions concerning a client’s creditworthiness in the insurance industry. The main contribution of the paper is the identification of new factors which have relation to a client’s creditworthiness and the creation of the assessment model which works with these new factors transferred to fuzzy variables. The proposed model differs from the current approaches primarily thanks to its complex, systematic and hierarchical ability to evaluate the newly identified factors related to a client’s creditworthiness as fuzzy variables. Thanks to the model, it is possible to automate and accelerate the process of evaluation of a client’s creditworthiness in the insurance industry. The knowledge gained from the evaluation model is immediately possible to use in the strategic management of insurance companies e.g. in marketing activities., Článek se zabývá problematikou hodnocení bonity klienta v pojišťovnictví. Cílem článku je identifikovat nové faktory, které souvisí s bonitou klienta v pojišťovnictví a navrhnout model jeho hodnocení. Výzkum je rozdělen do tří fází. V první fázi jsou identifikovány klíčové faktory související s bonitou klienta v pojišťovnictví. Ve druhé fázi jsou tyto faktory využity jako vstupy pro tvorbu hodnotícího modelu. Ve třetí fázi je model verifikován a implementován. Pro vytvoření, ověření a implementaci modelu byla využita neuro-fuzzy metoda. Bylo identifikováno pět vstupních proměnných do modelu - škodní procento, délka pojištění, propojištěnost, hospodářský výsledek, likvidita 2. stupně. Tyto proměnné byly rozděleny do dvou kategorií (bloky pravidel v modelu) dle svého charakteru. První blok pravidel vyhodnocuje pojistné indikátory (škodní procento, délka pojištění, propojištěnost). Druhý blok pravidel vyhodnocuje účetní indikátory (hospodářský výsledek, likvidita 2. stupně). Navržený model byl ověřen s využitím vstupní dat a s případnými dalšími korekcemi dle konkrétní potřeby může byt použit jako nástroj pro podporu rozhodování při hodnocení bonity klienta v pojišťovnictví. Hlavní přínosem článku je identifikace nových faktorů souvisejících s bonitou klienta a vytvoření hodnotícího neuro-fuzzy modelu. Od současného přístupu k hodnocení bonity klienta se navrhnutý model liší díky své komplexní, systematické a hierarchické schopnosti vyhodnocovat identifikované proměnné jako fuzzy proměnné. S využitím modelu je možno proces hodnocení klienta v pojišťovnictví zautomatizovat a urychlit. Znalosti z modelu plynoucí je možno okamžitě uplatnit při strategickém řízení pojišťoven a to např. v oblasti marketingových činností. Navrhovaný model se liší od současných přístupů především díky své komplexní, systematické a hierarchické schopnost vyhodnocovat nově identifikované faktory týkající se bonity klienta jak chmýřovité proměnné. Díky modelu, je možné automatizovat a urychlit p

Sustainability project is an important part of project management and depends on many factors, such as financial resources, human resources, scheduling operations and especially potential risks. This paper presents a way to work with uncertain information processing project risk analysis with regard to its sustainability. Risk management is an important part of various disciplines, e.g. Project management, Crisis management, Change management, Information Security Management System, etc. Risk analysis is mostly based on expert estimates. However, this may be a problem with brand new tasks as identification of different threats and their numerical evaluations can be interpreted as a decision-making task which can be formalised as a decision tree. A decision-making task solution requires knowledge of all relevant input information items (III), such as probabilities, penalties and profits. If all those numerical values are known then the well-known methods of decision trees evaluations can be used. However, if complex project management problems are solved then a substantial set of relevant data items is missing or its accuracies are prohibitively low. The aim of this paper is to present easy approach how missing elements of the III set can be obtained and integrated into incomplete data sets. The paper contributes a common sense heuristics to obtain missing elements of the III set which can generate all numerical values, i.e. a problem under complete ignorance is solve, and a reconciliation mechanism based on linear programming which allows results of common sense heuristics simply integrate into incomplete data set, i.e. a problem under partial ignorance is solved. The results are therefore divided into two parts. In the first part solves a problem under total ignorance. The second part of the case study evaluates some unknown probabilities, therefore solves a problem under partial ignorance. Both tasks, i.e. partial and total ignorance are demonstrated using a quasi

The paper deals with the issue of project modelling, specifically with the practical use of methods, techniques and tools of project management in relation to its success. The aim of this paper is to examine the level of use of methods, techniques and tools in the management of projects and their impact on project success. To fulfil the aim of the paper, a questionnaire survey was carried out in the form of a guided interview, and three statistical hypotheses defined (H1, H2 , H3). A population was identified and then a selective sample, on which the survey was conducted. The primary data acquired were statistically evaluated and the defined hypotheses statistically verified. Conclusions of the testing of hypotheses by statistical testing showed that there were dependencies between defined statistical variables of individual statistical hypotheses ( H1 , H2 , H3 ). On the basis of the results of the overall survey, it can be summarized that in the context of the application of selected project management methods, techniques and tools, companies make certain mistakes in the management of their projects, which have an impact on project success., Příspěvek se zabývá problematikou modelování projektů, respektive praktickým využíváním metod, technik a nástrojů projektového řízení ve vazbě na jeho úspěšnost. Cílem příspěvku je zjištění úrovně využívání metod, technik a nástrojů při řízení projektů a jejich vliv na úspěšnost projektů. Pro naplnění cíle příspěvku bylo realizováno dotazníkové šetření formou řízeného rozhovoru a definovány tři statistické hypotézy (H1, H2 , H3). Byl identifikován základní statistický soubor a následně výběrový statistický soubor, na kterém byl výzkum realizován. Získaná primární data byla statisticky vyhodnocena a stanovené hypotézy byly statisticky ověřeny. Ze závěrů ověřování hypotéz statistický testováním vyplynulo, že mezi definovanými statistickými znaky jednotlivých statistických hypotéz (H1, H2 , H3) existují závislosti. Z výsledků celkového výzkumu lze souhrnně konstatovat, že firmy se při řízení svých projektů v kontextu aplikace vybraných metod, technik a nástrojů řízení projektů dopouští jistých chyb, které mají vliv na úspěšnost projektů.

Complex decision making tasks of different natures, e.g. identifying of a profitability of a client in the insurance business, are based on vague, sparse, partially inconsistent and subjective knowledge of experts. One important problem related to realistic decision making tasks is uncertainty in input data / information. Decision-making under these conditions is difficult and can lead to incorrect results (decisions). The aim of this paper is to present an easy approach of how to identify profitability of the client in insurance business under the condition of input data uncertainty. The solution to the decision-making problem is based on the decision to extend or renew an insurance contract for next period (concretely two years). The solution of this problem is based on the decision-making task, which is graphically represented by a decision tree. This decision problem is solved for a fictitious client, but the required data sets are based on real data sets. The case study is represented by a tree with three lotteries, three decisions and seven terminals. The results arising from the paper serve mainly for needs of insurance companies. The main contribution of this paper is using a decision tree to provide managers with the tool to support decision-making and information about expected client profitability for the next period and its confidence interval.

The article deals with the use of fuzzy logic as a support of evaluation of total project risk. A brief description of actual project risk management, fuzzy set theory, fuzzy logic and the process of calculation is given. The major goal of this paper is to present am new expert decision-making fuzzy model for evaluating total project risk. This fuzzy model based on RIPRAN method. RIPRAN (RIsk PRoject ANalysis) method is an empirical method for the analysis of project risks. The Fuzzy Logic Toolbox in MATLAB software was used to create the decision-making fuzzy model. The advantage of the fuzzy model is the ability to transform the input variables The Number of Sub-Risks (NSR) and The Total Value of Sub-Risks (TVSR) to linguistic variables, as well as linguistic evaluation of the Total Value of Project Risk (TVPR) – output variable. With this approach it is possible to simulate the risk value and uncertainty that are always associated with real projects. The scheme of the model, rule block, attributes and their membership functions are mentioned in a case study. The use of fuzzy logic is a particular advantage in decision-making processes where description by algorithms is extremely difficult and criteria are multiplied., Článek se zabývá využitím fuzzy logiky jako podpory pro vyhodnocení celkového rizika projektu. Nejprve je uveden stručný vstup do problematiky řízení rizik projektů, fuzzy množin a fuzzy logiky. Hlavním cílem příspěvku je představit expertní rozhodovací fuzzy model hodnotící celkové riziko projeku. Fuzzy model vychází z metody RIPRAN. Metoda RIPRAN (Risk PRoject ANalysis) je empirická metoda pro analýzu rizik projektu. Rozhodovací fuzzy model byl vytvořen s využitím Fuzzy Logic Toolbox v aplikaci MATLAB. Výhodou fuzzy modelu je jeho schopnost transformovat vstupní proměnné: počet dílčích rizik (NSR) a celková hodnota dílčích rizik (TVSR) na jazykové proměnné, jakož i jazykově vyhodnocovat celkovou hodnotu rizika projektu (TVPR) - výstupní proměnná. S tímto přístupem je možné simulovat hodnotu rizika a nejistoty, které jsou vždy s řízením reálných projektů spojeny. Schéma modelu, fuzzy pravidla, funkce členství a jejich atributy jsou uvedeny v případové studii. Fuzzy logiku je vhodné aplikovat v rozhodovacích procesech, kde popis algoritmu je velmi obtížný.

The paper deals with a comparison of two different approaches (PERT method and Monte Carlo method) for calculation of the probability of a project completion. The PERT method is commonly used in a project management; the Monte Carlo is used less. The base assumption of authors can be expressed: The difference between the results obtained by the Monte Carlo method and PERT method is not significant with increasing number of simulations (iterations). For this reason, the hypothesis was formulated: There is no statistically significant difference between the calculated probabilities, i.e. both approaches are identical from application’s point of view. The case study describes a model of a project, which is shown by a network chart. This chart contains 18 nodes and 18 real activities and 6 fiction’s activities. Each activity is expressed by three time estimates, i.e. pessimistic, most likely and optimistic time. The planned date of completion of the project was selected at 200 time units and it was calculating the probability of completion of the project by PERT method and Monte Carlo method. Time duration of each project activity by the Monte Carlo method is successively obtained for 10, 100, 300, 500, 1000, 5000 and 10000 simulations. The calculated probabilities of project completion were compared using statistical hypothesis testing. The hypothesis was rejected for all simulations. It follows that there is difference between the approaches from application’s point of view.

Purpose: The paper deals with the creation of an investment portfolio using a proactive approach and technical elements to investment and speculations. Our aim was to perform statistical analysis of selected financial instruments and to find connections between the input data. We used the software Adaptrade, which operates on the basis of genetic algorithms. Scientific aim: To solve such sophisticated statistical problems in real time standard algorithms methods cannot be used. That is why we used algorithms based on the principle of evolution. Methodology/methods: Creating an investment portfolio we used technical approach supported by statistical analysis. We excluded fundamental news (information). We used application Adaptrade from Adaptrade Software Company for statistical analysis. This application is based on genetic algorithms basis and is able to process this difficult task in real time. Findings: The connections between the input data found by sophisticated statistical analysis are suitable for decision making in the financial markets. Conclusions: The tasks with processing large quantities of inputs are very difficult. Using of genetic algorithms is one of possible solutions. The principle based on evolution provides an optimal solution by finding the crossing of two “weak” solutions or partial solutions mutation. We used the software Adaptrade which operates on the basis of genetic algorithms. A proactive approach and technical elements was used for the creation of an investment portfolio and speculations. The connections between the input data found by sophisticated statistical analysis are suitable for decision making in the financial markets. The analysis is performed for three world currencies (U.S. dollar, Euro and British pound).

Tato bakalářská práce se zabývá využitím nástrojů projektového managementu v praxi, konkrétně na příkladu vytvoření návrhu plánu projektu pro uvedení nového výrobku na trh společnosti TOPVET. V první části bakalářské práce jsou uvedeny teoretické poznatky projektového managementu. Další část se zaměřuje na analýzu současného stavu společnosti TOPVET a jejího okolí. V poslední části je popsán návrh řešení projektu a jeho přínosy., This bachelor thesis deals with the use of project management tools in practice, specifically on the example of creating a draft project plan for launching a new product on the market of TOPVET company. The first part of the bachelor thesis presents theoretical knowledge of project management. The next part deals with the analysis of the current state of company TOPVET and its surroundings. The last part describes the design of the project and its benefits.