The present study attempted to assess the impact of fundamental ratios on the share prices of selected telecommunication companies in India. India has dramatically expanded over the past ten years to become the second-biggest telecoms market worldwide, with 1.17 billion users. The Indian telecom industry has proliferated thanks in part to the government of India’s liberal and reformist policies and strong customer demand. It has become a lucrative investment sector for investors due to its recent and prospective growth. Data on 13 telecom firms indexed in the S&P BSE telecommunication index from 2013 to 2022 were taken from companies’ annual reports, the BSE website (Bombay Stock Exchange), and other secondary sources. Six firm-specific fundamental factors viz. Debt to Equity ratio (D/E), Current ratio (CR), Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to earnings ratio (P/E), Return on equity (ROE), and three country-specific fundamental factors viz. Gross Domestic Product, Inflation rate, and S&P BSE Sensex return were considered. Fixed effect panel regression through Generalized Least Square (GLS) model was performed to find inferences. Debt Equity ratio and Inflation rate were found to impact share price negatively. Conversely, the Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to Earnings ratio (P/E), and Return on Equity (ROE) positively impacted selected companies’ share prices. The study results will benefit individual & institutional investors in formulating their investment and portfolio diversification strategies for gaining a high effective rate of return on their investments.
Since entering the new era, in the face of the changing international situation, China is faced with both development opportunities and challenges. How to cultivate English talents to meet the needs of national development and national rejuvenation in the new era has become an urgent problem to be solved in English education in China. The application of applied linguistics to English teaching in colleges and universities plays a positive role in promoting the innovation of English teaching concept and teaching mode in colleges and universities and the improvement of teaching efficiency and quality. This requires college English teachers to master the relevant concepts and connotations of applied linguistics, and clarify the content scope of applied linguistics and the value of practical application. This paper will focus on the analysis of the current situation of English teaching in colleges and universities, and on the basis of the concept and scope of applied linguistics, put forward some practical application strategies, hoping to provide a reference for the innovation of teaching mode and teaching methods of English curriculum in colleges and universities.
MXenes are one of the most important classes of materials discussed worldwide by many researchers of diverse fields for diverse applications in recent years. It is a nanomaterial with a wide range of applications due to its multiple forms and structures with fascinating properties, for example, high surface area and porosity, biocompatibility, ease of fictionalizing with various active chemical moieties, benefit of high metallic conductivity, activated metallic hydroxide sites, and sensitivity to moisture. MXenes have great chances for potential applications in environmental issues, water purification, biological applications, and energy storage devices and sensors. MXenes show great selectivity towards the absorption of heavy metals and a good capability to reduce chemical and biological pollutants present in the water. The present review article critically analyzed advancements in water purification using the adsorption and reduction abilities of MXenes and their composites. The mechanism of various procedures, important challenges, and associated problems using MXene and their composites are discussed in detail. The future research directions can be extracted from this article efficiently and comprehensively. The energy storage issues of rechargeable lithium-ion batteries, batteries other than lithium-ion batteries, and electrochemical capacitors are also discussed in detail.
Although various actors have examined the user acceptance of e-government developments, less attention has so far devoted to the relationship between attitudes of certain commuter groups against digital technologies and their intention to engage in productive time-use by mobile devices. This paper aims to fill this gap by establishing an overall framework which focuses on Hungarian commuters’ attitudes toward e-government applications as well as their possible demands of developing them. Relying on a representative questionnaire survey conducted in Hungary in March and April 2020, the data were examined by a machine learning and correlations to identify the factors, attitudes and demands that influence the use of mobile devices during frequent commuting. The paper argues that the regularity of commuting in rural areas, as well as the higher levels of qualification and employment status in cities show a more positive, technophile attitude to new ICT and mobile technologies that strengthen the demands for digital development, with special regard to optimising e-government applications for certain types of commuting groups. One of the main limitations of this study is that results suggest a picture of the commuters in a narrow timeframe. The findings suggest that developing e-government applications is necessary and desirable from both of the supply and demand sides. Based on prior scholarly knowledge, no research has ever analysed these correlations in Hungary where commuters are among the European citizens who spend extensive time with commuting.
This research presents a novel approach utilizing a self-enhanced chimp optimization algorithm (COA) for feature selection in crowdfunding success prediction models, which offers significant improvements over existing methods. By focusing on reducing feature redundancy and improving prediction accuracy, this study introduces an innovative technique that enhances the efficiency of machine learning models used in crowdfunding. The results from this study could have a meaningful impact on how crowdfunding campaigns are designed and evaluated, offering new strategies for creators and investors to increase the likelihood of campaign success in a rapidly evolving digital funding landscape.
Adult obesity is a significant health problem, with nearly a quarter of Hungarian citizens aged 15 years and older being obese in 2019 (KSH, 2019a). The use of mobile devices for health purposes is increasing, and many m-health apps target weight-related behaviours. This study uniquely examines the effectiveness and user satisfaction of health-oriented apps among Hungarian adults, with a focus on health improvement. Using a mixed-methods approach, the study identifies six key determinants of health improvement and refines measurement tools by modifying existing parameters and introducing new constructs. The principal objective was to develop a measurement instrument for the usability of nutrition, relaxation and health promotion applications. The research comprised three phases: (1) qualitative content analysis of 13 app reviews conducted in June 2022; (2) focus group interviews involving 32 students from the fields of business, economics and health management; and (3) an online survey (n = 348 users) conducted in December 2023 that included Strava (105 users), Yazio (109 users) and Calm (134 users). Six factors were identified as determinants of health improvement: physical activity, diet, weight loss, general well-being, progress, and body knowledge. The LAUQ (Lifestyle Application Usability Questionnaire) scale was validated, including 'ease of use' (5 items), 'interface and satisfaction' (7 items) and 'modified usefulness and effectiveness' (9 items), with modifications based on qualitative findings. This research offers valuable insights into the factors influencing health improvement and user satisfaction with healthy lifestyle-oriented applications. It also contributes to the refinement of measurement tools such as the LAUQ, which will inform future studies in health psychology, digital health, and behavioural economics.
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