商业与经济杂志

Although COVID-19 was declared a global pandemic by the World Health Organization on March 11, 2020, its effects are still being seen today. Governments all around the world implemented stringent measures in an effort to limiting cases and slow the virus' rate of spread because of the illnesses' Chinese origins and quick worldwide spread. However, these strategies have shattered the key pillars supporting modern world economies when nationalist concentration and struggle over scarce resources eclipsed global commerce and collaboration. The covid outbreak had major economic effects on every country in the world, and it doesn't seem to appear that any nation will be exempted. This has an adverse effect not only on the economy but also on society as a whole, which has drastically altered how both firms and customers conduct themselves. Interestingly, most governments in the African continent especially see this mire as good news and a necessary evil by putting the blame on the epidemic for their failure in government and subsequently failing the citizens. The status quo has created an atmosphere of terror and insecurity in individuals so much so that, people are now timid to complain or go to the hospital of normal headaches, fever, stomachaches, malaria and even the common cold we all know of. Once you cough in public, you will not only be lucky for people around running away from you but will draw the attention of the police on you in addition. When will?

One of the widely discussed issues in the financial literature is the daily seasonality in asset prices. In this study, we shed fresh lights and explore the evolution of weekday seasonality in the US capital market. For this sake, we utilize daily data for the period January 1990 to August 2022. We compare between cross-section portfolios including, for example, size-based profitability-based as well as risk-based portfolios. We find that Monday effect does not exist in both small and large cap firms. Yet, Fridays are associated with positive returns mainly for small size firms. Different subsamples and moving-sample window tests reveal mixed findings. Overall, our results indicate high degree of financial efficiency in information. Scholars and market participants may find our results useful.

This paper examines the structural breaks dates for capital base, interest rates, exchange rates, corporate governance and economic growth in Nigeria using annual banking reform variables data spanning from 1970 through 2015. The theory used in the research was Balance growth theory. The study applied conventional unit root test of Augmented Dicker Fuller (ADF). Time series properties of the data are analyzed using Chow test approach to examine the more likely time of structural breaks in banking reform variables of the Nigerian economy. The study has established that structural breaks exist in all banking reform variables employed in the study. We therefore, conclude that structural change is pervasive in banking sector reform and it can be quite dangerous to ignore. It was recommended that given that structural breaks are associated with regime changes, there is need for the potential use of regime switching models in Nigeria.

Customer Engagement Value (CEV) is a crucial concept for measuring the comprehensive value of a customer without overvaluation or undervaluation. CEV consists of four main components that comprehensively capture the transactional and non-transactional behavior of a customer within a firm. Traditional models contributed to measuring the value of each CEV’s component separately. Only a few researchers contributed to constructing a comprehensive framework for CEV to combine its components altogether. Meanwhile, these previous models either were theoretical or utilized gamification concepts for describing the relationship between a firm and its customers. The objective of this paper is to design a more realistic and comprehensive framework that captures CEV’s components’ relationships using a non-linear model. The elasticity parameters the determine the effect of each component in this non-linear model are determined using an online survey. These parameters are plugged in a system dynamics model that its relationships are formulated based on that non-linear model. The proposed CEV’s system dynamics model is applied only using imperial data. It proved the significance of both purchasing and non-purchasing components in CEV. It is recommended to be applied to real-life data to confirm its effectiveness.