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EN
The focus of this research is on assessing the perception of public service quality through a customer-centred approach. Public service quality comprises multiple factors that are prioritised differently by customers. Therefore, the study aims to conduct a literature review to identify the primary quality dimensions of public services and evaluate the heterogeneity of their perception within the context of Lithuania. The research measures the user perceptions of public service quality. The literature review allowed for identifying service quality indicators and grouping them into dimensions based on unifying characteristics. Such identification of service quality dimensions grounded the research methodology. An adapted SERVQUAL model was used to analyse data collected by a survey to interview customers of Lithuanian public service organisations. Logit and probit models were applied to examine the effect of sociodemographic characteristics and the type of service on customer perceptions of different quality aspects of the provided public services. Explored heterogeneity of attitudes and detailed analysis of socio-demographic factors revealed that women with higher education are the most satisfied users of public services, while less educated men usually have a negative attitude towards the quality of public services. The study confirmed that marital status and income level are not related to customer satisfaction with service quality. Although gender, age, family size, education level, and employment status explain heterogeneity in customer satisfaction, they still account for only a small amount of variance compared to the place of residence and type of service. The study is a significant contribution to the field of service engineering as it introduces a systematic approach to the development of service quality, incorporating models and methods that enable the assessment of service quality and efficiency. The literature review has identified several research gaps related to public service quality, including a lack of research on general public services and areas such as tourism, real estate management, fire protection and rescue.
PL
W pracy rozpatrzono modele prawdopodobieństwa stosowane do analizy zmiennej dychotomicznej:liniowy (MLIN), logitowy (MLOG) oraz probitowy (MPRO). Szczególną uwagę zwrócono na ocenę jakości modelu wynikającą z wartości błędów: MSE (wzór (26)), MAE (wzór (27)), ważoną sumę kwadratów (wzór (28)) oraz zaproponowaną w pracy ważoną sumę wartości bezwzględnych (wzór (37)) . W tym celu wykonano symulacje komputerowe z wykorzystaniem generatora liczb losowych o rozkładzie Bernoulliego.
EN
The study examined probability models used to analyze the dichotomous variable: linear (MLIN), logit (MLOG) and probit (MPRO). Particular attention was paid to the assessment of the quality of the model resulting from the errors: MSE (formula (26)), MAE (formula (27)), the weighted sum of the squares (formula (28)) and the work proposed in the weighted sum of the absolute values (formula (37) ). To this end, computer simulations were performed using a random number generator distributed Bernoulli
PL
Celem artykułu jest prezentacja modeli zmiennych dychotomicznych: logitowego i probilowego oraz zwrócenie uwagi na ich szerokie zastosowanie w różnych dziedzinach nauk. W artykule wykorzystano model regresji probitowej do wyznaczenia prawdopodobieństwa przyjęcia kandydata na Wydział Ekonomii, specjalność Handel i spółdzielczość, Uniwersytetu Rzeszowskiego.
EN
The aim of this article is presentation of logit and probit models and their wide application in many nt science. Logit and probit regression arę used for analyzing the relationship between one or morę ent yariables with categorical dependent yariable. There arę a lot of advantages of logit (probit) fels over linear multiple regression. These methods imply that the dependent yariable is actually the t of a transformation of an underlying yariable, which is not restricted in range. For example, the bit model assumes that the actual underlying depedent yariable is measured in terms of values for curve; if one transforms those values for probabilities then the predictions for the dependent ble will always fali between O ond 1. Thus, we arę actually predicting probabilities from the inde-nt yariables The probit model was used to calculate the probability of admissions in Rzeszów zUniwersity, speciality Handel i spółdzielczość.
4
Content available remote Modele logitowe iprobitowe w ekonometrii
PL
Artykuł omawia stosowanie symulacji komputerowej jako narzędzia do analizy rzeczywistości ekonomicznej. W szczególności omówiono modele logitowe i probitowe oraz ich bezpośrednie zastosowanie w modelu POLIMOD (Cambridge)
EN
This paper describe using computer simulation as a tool for analysing economical reality. The main ideas of the paper is describing probit and logit models and practically using in model POLIMOD (Cambridge).
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