Statističko modeliranje ekstrema

U različitim područjima, od hidrologije, seizmologije, telekomunikacija i biomedicine pa do ekonomije i aktuarstva, postoji potreba za analizom ekstremnih događaja – događaja čija je vjerojatnost pojavljivanja vrlo mala, a čije posljedice, nasuprot tome, mogu biti vrlo velike. Teorija ekstremnih vrijednosti je grana statistike koja proučava upravo takve događaje. U članku su opisane osnove statističke analize ekstremnih podataka

Stabla odlučivanja ne lažu: Zanimljivosti o sklonostima hrvatskih online potrošača

Understanding consumers’ preferences has always been important for economic theory and for business practitioners in operations management, supply chain management, marketing, etc. While preferences are often considered stable in simplified theoretical modelling, this is not the case in real-world decision-making. Therefore, it is crucial to understand consumers’ preferences when a market disruption occurs. This research aims to recognise consumers’ preferences with respect to online shopping after the COVID-19 outbreak hit markets. To this purpose, we conducted an empirical study among Croatian consumers with prior experience in online shopping using an online questionnaire. The questionnaire was completed by 350 respondents who met the criteria. We selected decision-tree models using the J48 algorithm to determine the influences of the found shopping factors and demographic characteristics on a consumer’s preference indicator. The main components of our indicators that influence consumer behaviour are the stimulators and destimulators of online shopping and the importance of social incidence. Our results show significant differences between men and women, with men tending to use fewer variables to make decisions. In addition, the analysis revealed that four product groups and a range of shopping mode-specific influencing factors are required to evaluate consumers’ purchase points when constructing the consumers’ preference indicator.Razumijevanje preferencija potrošača uvijek je bilo važno kako za ekonomsku teoriju, tako i za operacijski menadžment, upravljanje lancem opskrbe, marketing i druge poslovne aktivnosti. Iako se preferencije u teorijskom modeliranju često smatraju stabilnima, to nije slučaj u donošenju odluka u stvarnom svijetu. Zbog toga je preferencije potrošača potrebno dobro razumjeti, a to posebno vrijedi u okolnostima kada dolazi do poremećaja na tržištu. Cilj ovog istraživanja bolje je razumijevanje preferencija potrošača u internet kupovini nakon što su tržišta bila pogođena pandemijom COVID-19. U tu svrhu, provedeno je anketno istraživanje među hrvatskim potrošačima s prethodnim iskustvom u internet kupovini. Upitnik je bio aktivan od svibnja do rujna 2022. godine, a ispunilo ga je 350 ispitanika. S ciljem ustanovljavanja utjecaja analiziranih čimbenika kupovine i demografskih karakteristika potrošača na ponašanje potrošača, korišteni su modeli stabla odlučivanja uz pomoć tri klasifikacijska algoritma. Od tri odabrana algoritma, algoritam J48 je na testnim podacima pokazao najveću stopu točnosti u klasifikaciji. Glavne komponente pokazatelja koji utječu na ponašanje potrošača u ovom istraživanju su stimulatori i destimulatori internet kupovine, a zatim i važnost društvene incidencije. Rezultati istraživanja upućuju na značajne razlike u potrošačkim navikama između muškaraca i žena, pri čemu muškarci koriste manje varijabli pri donošenju odluka. Osim toga, analiza donošenja odluka pokazala je razlike i prema nizu drugih demografskih čimbenika te razlike kod kupnje različitih grupa proizvoda

Statistical modelling of extreme values

U ovom radu predstavljeni su osnovni pojmovi i rezultati teorije ekstremnih vrijednosti te su opisane statističke procedure koje se koriste za prilagodbu modela podacima. Naveden je osnovni teorem teorije ekstremnih vrijednosti (prvi teorem teorije ekstremnih vrijednosti) koji je potkrijepljen simulacijama, a zatim i drugi teorem teorije ekstremnih vrijednosti. Opisano je nekoliko neparametarskih metoda za vizualizaciju podataka te različite metode za procjenu parametara. Istaknuto je nekoliko statističkih testova koji se najčešće koriste u teoriji ekstremnih vrijednosti, od kojih je detaljnije opisan test omjera vjerodostojnosti. Postupci su objašnjeni na primjerima iz različitih područja (hidrologija, klimatologija, financije i drugo)

Sturm and Ribaucour curves

Rad ne sadrži sažetak

Sturm and Ribaucour curves

Rad ne sadrži sažetak

Statistical modelling of extreme values

U ovom radu predstavljeni su osnovni pojmovi i rezultati teorije ekstremnih vrijednosti te su opisane statističke procedure koje se koriste za prilagodbu modela podacima. Naveden je osnovni teorem teorije ekstremnih vrijednosti (prvi teorem teorije ekstremnih vrijednosti) koji je potkrijepljen simulacijama, a zatim i drugi teorem teorije ekstremnih vrijednosti. Opisano je nekoliko neparametarskih metoda za vizualizaciju podataka te različite metode za procjenu parametara. Istaknuto je nekoliko statističkih testova koji se najčešće koriste u teoriji ekstremnih vrijednosti, od kojih je detaljnije opisan test omjera vjerodostojnosti. Postupci su objašnjeni na primjerima iz različitih područja (hidrologija, klimatologija, financije i drugo)

Business' Attitudes Towards Corruption in Selected Central European Countries

Purpose: Corruption is perceived as a widespread problem throughout the world, including in Central European countries. In terms of corruption , these countries still lag behind the leading EU countries (as indicated by the 2023 Worldwide Governance Indicators). As corruption itself is very difficult to measure, the perception of corruption is often used as a proxy. The aim of this paper is to analyse attitudes towards corruption in selected Central European countries and to draw conclusions on the factors influencing these perceptions. Based on the assumption that the difference between de jure and de facto transparency matters, we selected Czechia, Hungary, and Poland as countries with small differences between these two dimensions of transparency, and Croatia, Slovakia, and Slovenia as countries with large differences. Design/Methodology/Approach: Using Eurobarometer data, we applied logistic regression to analyse attitudes towards corruption in the two groups of countries distinguished by differences in de jure and de facto transparency. Each group, consisting of three Central European countries, was used to create a model, i.e., Model 1 and Model 2, with a total number of observations of 901 and 902, respectively. Both models displayed adequate fit indices and enabled predictions that allowed us to draw conclusions. All respondents were business representatives with decision-making responsibilities in their companies, ensuring that the results reflect company perceptions rather than those of the general public. Findings: Attitudes towards corruption in the countries studied are related to perceptions of patronage and nepotism in business, perceptions of corruption in public procurement, perceived links between politics and business, and attitudes towards tax rates. In the group where there is little difference between de jure and de facto transparency levels, business attitudes towards corruption are also associated with perceptions of adequacy of infrastructure and complexity of administrative procedures. In the countries where these differences are substantial, attitudes towards corruption are related to perceptions of problems arising from frequent changes in the law, problems with debt collection, and differences in views regarding the severity of bribery depending on the value of the bribe. Academic contribution to the field: This research provides a better understanding of the factors influencing the perception of corruption in Central European countries from a business perspective. In doing so, it introduces a methodology that is well-suited for the analysis of survey-collected data, especially since it allows the dependent variable to be categorical. Moreover , by using data from the Transparency Index to differentiate countries, the study has the potential to stimulate further theoretical and empirical research into the relationship between corruption and transparency. Lastly, by linking companies' perceived problems to overall perceptions of corruption, this paper helps to identify the areas within the studied countries where pockets of corruption are most likely to exist. Originality/Value: Previous research has found that corruption tends to occur when the gap between de facto and de jure transparency is larger. This research demonstrates that the size of this gap can also be successfully used to achieve a better understanding of the factors influencing attitudes towards corruption. Therefore, this paper employs the difference between de jure and de facto transparency as a categorisation criterion to analyse the factors influencing the perception of corruption. This categorisation approach enabled the development of two separate logistic regression models with high predictive power