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Risk Analysis of Food Retail Companies in Hungary’s Northern Great Plain Region
539-550Views:347Based on the financial ratios of analyzed companies we were performed a risk analysis, highlighting the degree of operational and financial leverages and the degree of combined leverage combining preceding ratios. We introduced a new aspect of the risk concept which began to spread in recent times. In the interest of to be able to analyse together cross-sectional and time series data, panel regression model was used. The panel regression is an extension of the multivariate linear regression interpreted as a multi-level model. In our study, the panel regression was used for analysis of food retailer companies, in the Northern Great Plain region's counties, in the period 2009-2014.
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The Impact of Sales Promotion, User Interface and User Experience Design on Shopee App Users' Repurchase Intentions
90-104Views:1370By 2022, Gen Z and millennial consumers dominated Shopee usage in Indonesia. Similar e-commerce platforms are forced to constantly innovate to remain competitive in the market due to increasing competition. Therefore, the primary focus of e-commerce platform development should be on the user interface, user experience design, and promotions that are appealing and easy to access so that potential customers are inclined to repurchase. This research aims to determine the influence of UI design, UX design, and promotions on the repurchase intention of users of the Shopee application. The sampling method used was systematic sampling. Ninety-six respondents are included in the sample. This study uses descriptive analysis, classical assumption tests, multiple linear regression, and hypothesis testing for data analysis. SPSS Statistics 28.0 was used for data processing. The study found that user interface design, user experience design, and sales promotions statistically impact the repurchase intention of users of the Shopee application. The results demonstrate the effectiveness of repurchase intent in e-commerce.
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The Dunning–Kruger Effect in Knowledge Management Examination of BSc Level Business Students
14-21Views:231The Dunning-Kruger effect (DKE) in higher education evaluation is one of the current research areas of psychology, educational science, and management science (in our case). Its importance is that the less prepared one is, the less accurately one can judge what performance is expected of him. What is more, he will err more and will overestimate himself. The present study aims better to understand the phenomenon with new, small-sample empirical results. The study is part of a research series that has been ongoing at the University of Debrecen since 2015. It not only quantitatively expands the literature but also includes the course of Knowledge Management among those examined. During the research, students were asked both before the examination (N = 63) and after the examination (N = 76) to guess how many points they would achieve on a multiple-choice test. It supports the presence of DKE, both in the case of pre-examination and post-examination self-evaluations. Using four multivariate linear regression models, we examined whether the sign value or absolute value of the errors made during the guesses show a correlation - in addition to the available control variables - with the test score. Our results showed that the more accurate the pre-examination and post-examination estimations were, the higher the students' actual score was, while the less they tended to overestimate their preparation. This supports the presence of DKE, both in the case of pre-exam and post-exam self-evaluation.
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Testing the Sametest-effect in a BSc-level Business Communication Course Examination
10-15Views:86Using secondary data, we empirically examine two biasing effects that may arise in the written evaluation of large groups of students. Suppose the students take the examination in consecutive groups, and we wish to avoid the distortion caused by tests of different difficulty. In that case, we can decide to use the same examination questions. However, the danger of the "same test effect" arises, according to which the group writing later can perform better if it receives information from the examinees in the previous round. Using the same examination tests cannot be recommended if that effect is significant. Another related potential phenomenon is the "revealed sameness effect". Accordingly, if the examinees are aware of the repetition of the questions, it significantly increases the scores of the following group. We tested these phenomena using the data of a three-round written examination. A previously published analysis of a larger sample found that the "same test effect" can be expected if the students decide in which round they take the examination. Since it was possible to freely register for the examination rounds for the assessment analyzed in this study, we assume that the "same test effect" will be significant. Based on the literature, we also expected that the "revealed sameness effect" would occur in the third round. The performed linear regression analysis (N=77) only found some weak evidence for the 'revealed sameness effect' but not for the 'same test effect'.
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Present and Future of Industrial Robotisation
13-24Views:137The following paper analyzing the installation of industrial robotisation in sectors and regions, in addition carry out forcastings on historical data. In recent years, automation and the use of industrial robotics have increased exponentially in the manufacturing sector. Given that companies prioritize enhanced production efficiency, quality assurance, and safety, it is evident that substantial investment and implementation of automation continue to occur in manufacturing facilities worldwide. The number of industrial robots globally has been growing steadily since 2010. However, the rate of growth has slowed from 2020 onwards. The impact of the Covid-19 epidemic was still felt in 2020, but the deployment of industrial robots increased significantly in 2021. Global industrial robot deployment is projected to continue to grow in the coming years, although the rate of increase may vary between regions and countries. The analysis showed a number of differences between regions in the number and growth rate of industrial robot deployments. Asia and Australia are the largest markets for robots and the number of robots deployed is expected to continue to grow in the future. Europe is the second largest market and, although growing at a slower rate, industrial robot deployment is also increasing steadily. In the Americas, growth is slower than in other regions, but still increasing. Global growth trends suggest that there will be further growth in the coming years and that the deployment of industrial robots will become more widespread in different parts of the world.
