Eurasian Journal of Higher Education https://londonic.uk/js/index.php/ljis <h2><span style="font-size: 14px;">EJHE is a refereed academic journal. The journal publishes research articles in social sciences and interdisciplinary sciences. Articles are thus expected to be proactively interdisciplinary. The main objective of the Journal is to provide an intellectual platform for scholars, a platform in which research in alternative paradigms for interdisciplinary studies could be presented and debated.</span></h2> en-US <p><a title="License Terms" href="https://creativecommons.org/licenses/by-nc-nd/4.0/" target="_blank" rel="noopener">CC Attribution-NonCommercial-NoDerivatives 4.0</a></p> editor@londonic.uk (Omer Farooq) editor@londonic.uk (Omer Farooq) Thu, 31 Mar 2022 00:00:00 +0000 OJS 3.2.1.2 http://blogs.law.harvard.edu/tech/rss 60 Learning from fast & slow fashion supply chains https://londonic.uk/js/index.php/ljis/article/view/68 <p>Slow and fast fashion companies and their supply chains can learn a lot from each other. The fast fashion business model is often associated with short lead times, while the slow fashion business model is deemed to be more sustainable in nature. Therefore, many people believe that fast fashion companies do not have enough time to be concerned with the sustainability of their practices. This study seeks to determine whether fast fashion companies should be more concerned about the sustainability of their production. The findings show, among other things, that these fast fashion companies are also getting better in terms of building their business sustainability. This becomes clear when a total of 20 slow and 20 fast fashion companies are analyzed using the triple bottom line approach. As a result, it is safe to say that fashion companies' business models do not define whether or not they are concerned about the sustainability of their practices. Rather, it is each company's awareness of the environment that motivates them to implement sustainable, eco-friendly practices in their operations.</p> Christina Schabasser Copyright (c) 2022 Christina Schabasser https://creativecommons.org/licenses/by-nc-nd/4.0 https://londonic.uk/js/index.php/ljis/article/view/68 Wed, 23 Mar 2022 00:00:00 +0000 Education with AI & Machine Learning in a Post-Pandemic World https://londonic.uk/js/index.php/ljis/article/view/67 <p>The shift from the 20th to the 21st century has brought about a multitude of technological developments, particularly in the education sector. However, the recent COVID-19 pandemic has created substantial obstacles for students, not limited to but including economic difficulties, the digital divide, and lack of resources. Nevertheless, the pandemic also allowed for the flourishing of artificial intelligence (AI) &amp; machine learning technologies, which can be utilized to mitigate these issues in education. This paper explores how AI &amp; machine learning have been used to innovate current education institutions — including programs such as Educational Data Mining, Intelligent Tutoring Systems, and Adult Learning Systems among others — as well as the drawbacks to this approach and potential future applications for these technologies. Naturally, as a developing field there are many objections surrounding these technologies due to concerns such as data privacy, loss of soft skills, barriers to implementation, and more. But in spite of this resistance, many AI-driven educational initiatives have thrived. By analyzing past successes and failures, we hope to provide guidance for better employing these technologies in education in the future.</p> Jazhiel Segura-Monroy, Hugo Hernandez-Ordonez, Oscar Catemaxa Cardoza, Sergio Sanchez-Sarellano, Yetkin Yildirim Copyright (c) 2022 Jazhiel Segura-Monroy, Hugo Hernandez-Ordonez, Oscar Catemaxa Cardoza, Sergio Sanchez-Sarellano, Yetkin Yildirim https://creativecommons.org/licenses/by-nc-nd/4.0 https://londonic.uk/js/index.php/ljis/article/view/67 Wed, 23 Mar 2022 00:00:00 +0000 An In-depth analysis of government debt to GDP of the three selected African countries and its effects on their Economy https://londonic.uk/js/index.php/ljis/article/view/69 <p>This study investigated the effects of Government debt to the GDP of the 3 selected African Countries and the negativity on their economy using data from 2012-2020. The provable/empirical results showed that debt effects enhanced growth only on a short term and hindered growth in the long term. Debt servicing has negative impacts on the borrower country’s economy because It takes a large benefit from the domestic economy to transfer to the foreign economy. Therefore, the country foregoes some spectacular multiplier accelerator effects. Debt servicing, including interest payments and repayments, may also be a real leakage from an indebted country. The study suggested that government should channel the borrowed funds on both infrastructural development and the productive base of the economy, that will improve long-term economic growth, expand the revenue base, and strengthen the capacity to repay outstanding debts when due. Government should put in place a debt management mechanism that will prevent the government from default.</p> Benedict Ebenezer Alechenu Copyright (c) 2022 Benedict Ebenezer Alechenu https://creativecommons.org/licenses/by-nc-nd/4.0 https://londonic.uk/js/index.php/ljis/article/view/69 Wed, 23 Mar 2022 00:00:00 +0000 The impact of COVID-19 on stock market returns: Empirical evidence from Nigeria https://londonic.uk/js/index.php/ljis/article/view/70 <p>The study investigates the causal relationship between COVID-19 and changes in the prices and volume of stocks in the Nigerian stock market, to identify whether there is a short and or long-run relationship between changes in the Nigerian Stock Exchange All Share Index 30 (NSE ASI 30) and NSE 30 traceable to the outbreak and continued presence of the coronavirus-19 diseases (COVID-19) during the period 31 December 2019 to June 30, 2020.</p> <p>The paper seeks to estimate the effect of the COVID-19 shocks on the volatilities of returns in the NSE30 and ASI 30 stocks. After a property check on the times series data, a correlation matrix was drawn to understand the relationship between stock returns in NSE30 and ASI30 with total cases, test units, new cases, female and male smokers, and COVID-9 deaths. The ADF results helped us in selecting what the use in the representative model.</p> <p>We then applied the Lagrange Multiplier (LM) test on the residuals of both the mean and the variance equations of the NSE30 and the Generalized Autoregressive Conditional Heteroscedastic (GARCH) to estimate the short and long-run return spillovers and conditional correlations between the shock from COVID-19 and stock market returns.</p> <p>Generally, the results indicated a weak impact of COVID-19 on the returns and volume of both the NSE30 and NSE ASI 30 stocks. This is so because of some data issues and issues relating to empirics. More data will be sought, and a proper review of the paper undertaken, to ascertain its usefulness for policy.</p> <p>The study concludes that to spur economic growth in COVID-19, Nigeria’s economic managers, particularly, the monetary, fiscal, and capital market regulators must learn to work as a team, to ensure complementary in their policies and thus, propel the economy out of a likely recession.</p> Mela Yila Dogo, Osman Nuri Aras Copyright (c) 2022 Mela Yila Dogo, Osman Nuri Aras https://creativecommons.org/licenses/by-nc-nd/4.0 https://londonic.uk/js/index.php/ljis/article/view/70 Thu, 24 Mar 2022 00:00:00 +0000