The scientific paper deals with a part of the business sector, which is made up of family businesses. The paper presents the current status of such businesses from the perspective of positive and negative factors which will be linked to the problem areas. In this article, we have focused our attention on some aspects of family business, especially the managerial aspects, because the management of a family business has various differences and specifics compared to other types of businesses. In the theoretical part, we present the current state of the issue, while the empirical part of the article is based on a survey conducted among family businesses using a questionnaire. This article does not aim to highlight the contentious areas of family business. However, it brings valuable findings of business practice. More than 400 enterprises were approached, the resulting sample consisted of 185 family enterprises. Therefore, we understand the results as a case study from Slovakia. Our findings were subject to statistical analysis using several quantitative methods (t-test, regression models) and we present them in the empirical part. Based on our results, we bring the most valuable findings and ideas for further research.
The overall effectiveness of a website as an e-commerce platform is influenced by how usable it is. This study aimed to find out if advanced web metrics, derived from Google Analytics software, could be used to evaluate the overall usability of e-commerce sites and identify potential usability issues. It is simple to gather web indicators, but processing and interpretation take time. This data is produced through several digital channels, including mobile. Big data has proven to be very helpful in a variety of online platforms, including social networking and e-commerce websites, etc. The sheer amount of data that needs to be processed and assessed to be useful is one of the main issues with e-commerce today as a result of the digital revolution. Additionally, on social media a crucial growth strategy for e-commerce is the usage of BDA capabilities as a guideline to boost sales and draw clients for suppliers. In this paper, we have used the KMP algorithm-based multivariate pruning method for web-based web index searching and different web analytics algorithm with machine learning classifiers to achieve patterns from transactional data gathered from e-commerce websites. Moreover, through the use of log-based transactional data, the research presented in this paper suggests a new machine learning-based evaluation method for evaluating the usability of e-commerce websites. To identify the underlying relationship between the overall usability of the eLearning system and its predictor factors, three machine learning techniques and multiple linear regressions are used to create prediction models. This strategy will lead the e-commerce industry to an economically profitable stage. This capability can assist a vendor in keeping track of customers and items they have viewed, as well as categorizing how customers use their e-commerce emporium so the vendor can cater to their specific needs. It has been proposed that machine learning models, by offering trustworthy prognoses, can aid in excellent usability. Such models might be incorporated into an online prognostic calculator or tool to help with treatment selection and possibly increase visibility. However, none of these models have been recommended for use in reusability because of concerns about the deployment of machine learning in e-commerce and technical issues. One problem with machine learning science that needs to be solved is explainability. For instance, let us say B is 10 and all the people in our population are even. The hash function’s behavior is not random since only buckets 0, 2, 4, 6, and 8 can be the value of h(x). However, if B = 11, we would find that 1/11th of the even integers is transmitted to each of the 11 buckets. The hash function would work well in this situation.
The global environment of organizations requires from management to respond promptly to the demands of a changing environment, both external and internal, requiring managers to continually develop their skills, especially in the area of soft skills. The current management of organizations, in an effort to make the most of their employees’ potential, seeks to promote an individual approach to their motivation, expresses an increased interest in employee satisfaction and loyalty, encourages employee involvement in achieving organization goals, seeks to apply W-L-B and more. This requires managers to have a high level of social skills and an appropriate leadership style that considers both the needs of the individual and his cultural background. Highly productive employees are the key to success for all organizations, they are the key to a competitive advantage in the global business world. At present, there is a strong pressure on organizations to behave in the spirit of corporate social responsibility both by senior staff and by the general public. Highly required is a style of leadership that honors basic ethical principles in any country. It should be stressed that there are still organizations that do not respect, for example, the need for ethical leadership, ethical decision-making at all levels of management and all employees. The aim of the paper is to point to preferred leadership styles especially in the younger generation, helping to increase their job satisfaction and productivity, as well as those of managers who will support this effort in a culturally diverse environment. In the submitted analysis of the topic selected scientific methods were applied such as e.g. a critical analysis and synthesis, comparison and deduction.
Nowadays, we are living in the modern era of technological revolution and globalization, where people are giving more priority to proper education to compete among the top countries and to achieve something in their lives. Education improves a person’s abilities and creativity, which in turn have a positive effect on the development of a nation’s or an individual’s economy and also play a productive role in it. The traditional approaches are based only on statistical measures and are not capable of figuring out the most significant socioeconomic factors affecting the performance of a student. Keeping in mind the significance of socioeconomic status (SES) in improving the performance of a student, this study analyzes the important socioeconomic factors that affect the performance of a student in Khyber Pakhtunkhwa, Pakistan. We developed our own dataset by collecting data from 100 different schools (both government and private) in Khyber Pakhtunkhwa, Pakistan, consisting of more than 5550 students who were given a proper questionnaire survey. The created dataset consists of a total of 18 features and a target class. In this research, we used different statistical and machine learning (ML) methodologies to identify the most crucial elements that significantly affect the academic achievements of a student and have a strong correlation with the target class. To select the most prominent features from the dataset, we used two different feature selectors (FCBF and relief) and measured their performances along with ML models. To measure the significance rate of each ML algorithm using the full and selected feature space, we used different performance measures such as accuracy, precision, recall, sensitivity, specificity, etc. The experimental outcomes show that the feature selection algorithms significantly improve the performance of the classification models by providing more relevant features that have a strong association with the target class. This study also offered some advice for decision-makers, particularly in the respective education sector and other authorities, to develop specific solution strategies, plans, and initiatives to address the issue. It is envisioned that the suggested scheme will help the residents of Khyber Pakhtunkhwa province, in particular, obtain a high-quality education that can help pave the way for an educated and developed Pakistan.
Governments are increasingly utilizing digital technologies to deliver advanced electronic and mobile services aimed at bringing benefits to all people. All sectors have seen an increase in the provision of such services, albeit to varying degrees. A major trend is the increase in mobile technologies and applications. It entails new development opportunities for the poorest and the most vulnerable, and it is driving initiatives to promote sustainable development and new ways of providing services. As is the case for other aspects of e-government, the major challenge for the future will be to bridge the digital divides between countries and people. This requires policies in the social and economic areas, mobilizing technologies and providing services to the poorest and most vulnerable; while ensuring adequate attention to environmental aspects. The right mix of technological features and the settings marketing strategy makes possible for government to have a strong place on the market. The management orientation to the IT segment will show meaningful further orientation, which would be included on site for ideal effectiveness for all users.
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