International Journal of Business & Economics (IJBE)
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Macroeconomic Factors and Stock Market Indices
Get PDFThis paper explores macroeconomic factors and their effect on the stock market. Our analysis covers the stock market indices, the Dow Jones, the S&P 500, and the NASDAQ, over the period of 10 years starting in 2011 and ending in 2021, compared against macroeconomic factors, such as gross domestic product, effective funds rate, oil prices, money supply, consumer price index, unemployment rate, and producer price index. In our analysis, NASDAQ is the best indicator to predict macroeconomic factors
A Note on Economic Impact of Refugees in Host Countries
Get PDFRefugee issue has been debated mostly in the political and humanitarian arena and less in the economic impact in the host countries. Furthermore, even if refugee issues were discussed from economic perspectives, most studies use macro-emotionally charged tools rather than economic theory-based argument. In addition, discussions have been limited to short-term economic impact on host countries and ignore a long-term economic implication. Although inflation and labor displacement in host countries by the refugees are expected, this study reveals that the host countries benefit greatly from refugees in the long-run in almost every aspect of life. If refugees decide to settle permanently in the host countries, a structural change in economic area occurs in the host countries.
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IMPACT OF CORONAVIRUS ON INDIAN AVIATION INDUSTRY
Get PDFThe world is facing its biggest ever fear which initially seemed to be an outbreak and within days it engulfed many countries globally and World Health Organization (WHO) announced it a PANDEMIC on 11th of March, 2020.The Coronavirus or COVID-19, term given by WHO, starting in the Wuhan province of China in November 2019, has witnessed 808,716 deaths, 24 August 2020. Over the years, tourism has grown into an industry and has become a major source of revenue for many nations. The economy of many countries rests largely on foreign currency earned through tourism. Further, due to economic growth and rise in per capita incomes, people have a higher disposable income and the urge to travel and see different places is now more easily satisfied. The tourism is one of the industries which has been badly effected due to the pandemic. The nationwide lockdown, restrictions on movement has added to the woes with leaving many jobless. This study, calculates the effect of COVID-19 on aviation industry which is complement to tourism industry. The outcomes of this study will help the bureaucrat’s and industry practitioners to form a strategy to minimize the economic effect and to bring back on track the industry. This will help the industry to recover post lockdown and to bring back its lost glory
CONSISTENCY OF BENCHMARKING PERFORMANCE MEASURES: AN EMPHASIS ON COMPANY SIZE
Get PDFThis article investigates consistency of organizational strategy and potential links between the company size and the alignments of benchmarking performance measures. Six hypotheses were used to examine the consistency of the benchmarking performance measures and the impact of company size on selection of strategic and tactical benchmarking performance measures. Statistical results show evidence of misalignment between strategic goals and objectives, competitive dimensions, and proactive development of organizational core competencies. The results also indicate that managers from larger companies placed more emphasis on strategic measures while managers from smaller organizations emphasized more on tactical performance measures
Introducing Students to Business Analytics: A Case Study
Get PDFEmployer demand for business analytics skills is strong, yet most universities provide an inadequate amount of business analytics education. This paper describes and evaluates an introductory business analytics course required for undergraduate business management majors. It examines not only students' perceptions of teaching effectiveness and learning satisfaction from end-of-semester surveys but also student learning outcomes measured by the instruments for the program assurance of learning. Student evaluations were not generally favourable, which is unsurprising for the courses like this that require statistical analysis and quantitative skills. However, the measures of learning showed positive results as over three-quarters of the students’ demonstrated satisfactory performance in using analytical tools and applying spreadsheet and optimization models. Perceptions were enhanced for students who held more positive impressions of the instructor and of the team-based assignments, who expected higher grades, and who were more interested in the subject of business analytics. The study suggests that measures of learning may provide a more accurate picture of the effectiveness of business analytics coursework than measures of reactions
Emerging Bond Markets in Asia: Credit Spread Dynamics
Get PDFWe present a comprehensive analysis of the credit spread determinants in five Asian bond markets over a sample period of 10 years, from January 2010 to December 2019. Consistent with the western literature, we find that the structural models are broadly valid even in emerging countries with developing bond markets. Empirical results unveiled that bond-specific liquidity is the most important driver that reduces the credit spread, followed by the slope of the term structure and industrial growth in the economy. In Emerging Asia, inflation is the key driver that aggravates credit spread for business firms, followed by financial market volatility. Cross-country data reveals that the Chinese corporate bond market is the largest in Asia. Indian markets offer higher yield rates, while credit spread is noted to be highest in China. The empirical findings of our study would provide important insights for the policy makers while developing the most sought-after liquid bond markets. Effective liquid bond markets would reduce the cost of capital for firms and price credit risks efficiently
HOW SOCIAL CAPITAL IMPACTS THE SUSTAINABILITY OF GROUP LENDING PROGRAMMES - A GROUNDED THEORY APPROACH
Get PDFThis research study aims at generating a Grounded Theory on how social capital enables the Self-help groups linked to banks to attain financial sustainability. Globally, 1.7 billion people are below the poverty line, and these people do not have physical collateral. The banks and financial institutions are wary of lending to the poor. Group lending with bank linkages is a social innovation that, through social capital, ensures access to finance to the people at the bottom of the pyramid. The extant literature is available in the domain of social capital, but how it is operationalized and the factors impacting the efficacy of the social capital to generate financial sustainability have not been explored. This study has developed a theoretical model of how social capital impacts the sustainability of group lending interventions viz—self-help group bank linkage. The study establishes that network structure and form of network ties have a profound impact on the success of this initiative
BOARD COMPOSITION, BOARD DIVERSITY AND STOCK PERFORMANCE
Get PDFThe study investigates the relationship between six board compositions and stock returns. The results indicate a significant association between various board compositions and stock returns. Specifically, board size and executive directors have a negative impact, whereas independent directors enhance stock returns. Busy directors positively impact the abnormal stock returns for the companies in the non-financial industry, which implies that busy directors who serve on more boards tend to be well connected. More importantly, the results indicate a significant positive relationship between board tenure and stock returns. Board service time is perceived as the board quality of knowledge and experience from the investors’ point of view
An Enquiry into the Purchase Intention of AI – based Virtual Personal Voice Assistants in India
Get PDFThis paper attempts to analyze the Indian consumers’ intention to purchase AI – based virtual personal assistants (VPAs). The various AI beliefs of the Indian consumers were initially captured using forty-four statements via the questionnaire survey method using snowball and convenience sampling techniques. Principal Component factor analysis followed by Varimax rotation was adopted to reduce these statements into nine factors namely: Trust in AI, Knowledge about AI, Personalization Preference, Current usage of AI, Awareness of AI, Positive outlook on Current AI Performance, Future Dangers of AI, Negative outlook on Current AI Performance and Desired Applications of AI. The survey which was conducted across India resulted in a sample size of 637 respondents who did not own a VPA and had either an intention/no intention to purchase a VPA. By employing Independent sample ttests, the purchase intention was analyzed with respect to the nine reduced factors and the tests were repeated for various demographic profiles like gender, age, annual income and AI knowledge level for a better understanding. The results show that different factors significantly influence the purchase intention for different profiles. A complete understanding of the purchase intention of VPAs with respect to the various dimensions of the consumers’ AI beliefs and various demographic profiles is important for both businesses selling VPAs and also for the retail industry as voice shopping via VPAs is the future of e-commerce
LINKAGES BETWEEN BRENT OIL PRICE AND IRAN STOCK MARKET: NEW EVIDENCE FROM THE CORONA PANDEMIC
Get PDFThis article reviews the relationship between the oil market and the stock market during the Corona outbreak. The hypothesis of this paper is whether while oil prices shocks happen due to business cycle fluctuations and some other reasons like political reasons occur; the correlations between changes in Brent oil prices and stock market indices tend to be affected by named corona indexes. Forecasting the stock market in each period has been difficult and the value of stock index has been affected by various factors. Among these factors has been the oil and gas sector, especially in countries dependent on the revenue from their sales. This study examines relationship between Brent oil price and Iran stock market Index during the outbreak of corona pandemic. Research method is, vector autoregression model (VAR) which using daily data covering the period from February 20, 2020 to August 21, 2020. The findings of this study suggest that a negative causal effect from Brent oil price changes to the Iran stock market Index. Also, the results of impulse response functions and variance decompositions showed that some corona pandemic indicators have significant effects on the stock index