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Country indicators moderating the relationship between phubbing and psychological distress : A Study in 20 Countries
Agata Blachnio, Nenad Čuš Babič, Bojan Musil, 2021, original scientific article

Abstract: Problematic mobile phone use can be related to negative mental states. Some studies indicate that behavioural dependency is related to variables associated with the country of origin. The aim of our study was to investigate if country indicators moderated the relationship between phubbing and psychological distress. Our sample consisted of 7,315 individuals from 20 countries, who completed the Phubbing Scale and the Kessler Psychological Distress Scale (K6). The analyses also included country indicators: the Gender Gap Index (GGI), the Human Development Index (HDI), the Social Progress Index (SPI), Hofstede’s dimensions of culture, and the World Happiness Index (WHI). Our results showed that psychological distress was related to at least one dimension of phubbing (i. e., to communication disturbance or phone obsession) in all countries, which means this relationship is culturally universal. The results of the study demonstrate the importance of testing measurement invariance to determine what type of analysis and what type of conclusion are valid in a given study or comparison. Moreover, the increasing or decreasing correlation between phubbing and distress is related to some culture-level indices.
Keywords: country indicators, culture, phubbing, mobile phone addiction, distress
Published in DKUM: 07.08.2024; Views: 88; Downloads: 17
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Financial distress prediction of Iranian companies using data minig techniques
Mahdi Moradi, Mahdi Salehi, Mohammad Ebrahim Ghorgani, Hadi Sadoghi Yazdi, 2013, original scientific article

Abstract: Decision-making problems in the area of financial status evaluation are considered very important. Making incorrect decisions in firms is very likely to cause financial crises and distress. Predicting financial distress of factories and manufacturing companies is the desire of managers and investors, auditors, financial analysts, governmental officials, employees. Therefore, the current study aims to predict financial distress of Iranian Companies. The current study applies support vector data description (SVDD) to the financial distress prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use a grid-search technique using 3-fold cross-validation to find out the optimal parameter values of kernel function of SVDD. To evaluate the prediction accuracy of SVDD, we compare its performance with fuzzy c-means (FCM).The experiment results show that SVDD outperforms the other method in years before financial distress occurrence. The data used in this research were obtained from Iran Stock Market and Accounting Research Database. According to the data between 2000 and 2009, 70 pairs of companies listed in Tehran Stock Exchange are selected as initial data set.
Keywords: financial distress prediction, Support vector data description, Fuzzy c-mean
Published in DKUM: 30.11.2017; Views: 959; Downloads: 201
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