During the Covid-19 pandemic, some government restrictions to curb the spread of corona virus rendered print media obsolete. Social media became a convenient channel of communication. However, social media was awash with false and alarming information about the pandemic and government initiatives. This led to infodemic as consumers accessed misrepresented information on social media. As a result of social media infodemic, some consumers engaged in panic banking through withdrawal rush due to uncertain future expectation. This study aimed to examine the effect of social media infodemic during the Covid-19 pandemic on consumers’ panic intention behaviour in the banking industry. Data for the study was collected from 230 consumers of the baking industry in Oman using a questionnaire. A social media infodemic model was developed using a deductive approach. The study found out that social media infodemic was responsible for panic banking intention behaviour in Oman. The four determinants of social media panic behaviour were all statistically significantly impacting on panic banking behaviour. The study concluded that social media infodemic is a key determinant of panic banking in the banking sector. In light of the above findings, the banking industry should monitor social media so as to dilute misinformation with factual corporate communications so as to minimise panic banking behaviour.
There has been a dominance of e-learning Quality Assurance (QA) discourse since the adoption and increased usage of e-learning by HEIs. Research has shown that majority of graduates from HEIs were failing to meet industry expectation due to explicit mismatch between industry expectation and HEIs offering. This study aims to establish how e learning QA can act as a symbolic control in HEIs. The study used systematic literature review research methodology to understand the how e-learning quality assurance can be guaranteed in HEIs. The results of the study proposed a framework to be adopted and used by HEIs for e-learning QA. Of interest to note in the framework is the -e-learning QA was difficulty in HEIs due to the following aspects financial resources, culture, technological advancement, IT skills, leadership, staff retention, resistance to change and employee involvement. This study recommends that HEIs need to put the much-needed infrastructure, financial resources, develop the IT skills and benchmark their practices with international standards to effectively ensure e-learning QA.
This study examines the extent to which nation branding antecedents can be leveraged to create a strong nation brand for emerging economies. The Anholt (2002) nation branding model was quantitatively applied to develop a hexagon of factors which can affect developing economies. The Republic of Zimbabwe was targeted for analysis due to its national brand challenges and the negative brand equity. Data for the study was collected using structured questionnaires. Structural equation modelling (SEM) using Amos Graphics was the main tool for analysis. Findings suggest that government regulatory framework is the single most important key nation brand element which influences emerging economies’ brands today. This is followed by tourism, natural resources, sport and entertainment, diasporic citizenry, and religion. The study concluded that if these affordances are capitalised, nation branding for emerging economies can be greatly improved by 58%. The study recommends government and private sector stakeholders to take active roles in capitalising these affordances in order to achieve the nation brand equity
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