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The purpose of this study is to examine whether companies with high audit quality (AQ) are expected to use trade credit (TC) as a financing source. Traditionally, vendors are most likely to extend TC to creditworthy customers.

The author uses the data from 134,099 firm-year observations of nine Asian emerging markets from 2001 to 2017. Further, to check the impact of AQ on trade credit, the authors employ ordinary least square (OLS) with fixed effects, cluster effect regression and random effect.

The findings indicate that vendors extend more TC to the companies audited by the BIG4 auditors as, these independent practitioners have greater competencies, expert intellectual capital, global networking connections, and high investment in information technology. The authors, therefore, conjecture that the company's use of TC increases with their improved AQ, especially audited by BIG4. The results are found consistent with this prediction and robust to the alternative measures of trade credit. Similarly, this positive association is more pronounced with the BIG4 partner's unqualified audit opinion.

This study uses the sample of Asian Emerging countries but the researchers cannot generalize the results to developed countries or other regions.

This paper's findings have significant implications for the management, board of directors, shareholders and suppliers. Further, results are in favor of appointing BIG4 auditors to gain the trust of suppliers.

Despite the wide-ranging literature that discusses the importance of quality audits in enhancing the firms' financial disclosures that leads to better access to finance through investors and lenders. But the TC as a financing source is ignored in relation to AQ. The study’s results extend the literature associating companies' AQ with financial decisions.

This article investigates the dynamic implication of healthcare expenditure on economic growth in the selected ten Sub-Saharan African countries over the period 2000–2018.

The study methodology included dynamic heterogenous panel, using mean group and pooled mean group estimators. The investigation of the healthcare expenditure and economic growth nexus was achieved while controlling the effects of investment, savings, labor force and life expectancy via interaction terms.

The results from linear healthcare expenditure have a significant positive impact on economic growth, while the nonlinear estimates through the interaction terms between healthcare expenditure and investment have a negative statistically significant impact on growth. The marginal effect of healthcare expenditure evaluated at the minimum and maximum level of investment is positive, suggesting the impact of health expenditure on growth does not vary with the level of investments. This result responds to the primary objective of the article.

In policy terms, the impact of investment on healthcare is essential to addressing future health crises. The impact of coronavirus disease 2019 (COVID-19) can never be separated from the shortages or low prioritization of health against other sectors of the economy. The article also provides an insight to policymakers on the demand for policy reform that will boost and make the health sector attractive to both domestic and foreign direct investment.

Given the vulnerability of SSA to the health crisis, there are limited studies to examine this phenomenon and first to address the needed investment priorities to the health sector infrastructure in SSA.

This bibliometric study aims to analyze publication trends, active countries, collaborations, influential citations and thematic evolution in learning analytics (LA) research focused on higher education (HE) during and after the COVID-19 lockdown period.

From the Scopus database, this bibliometric analysis extracts and evaluates 609 scholarly articles on LA in HE starting in 2019. The multidimensional process identifies the scope impacts, advancing the understanding of LA in HE. An analysis of co-citation data uncovers the key influences that have shaped the literature. This study uses the stimulus-organism-response (SOR) theory to suggest future research directions and organizational adaptations to new LA technologies and learner responses to LA-enabled personalized interventions.

Learning analytics are becoming important in the HE environment during and after the COVID-19 lockout. Institutions have used LA to collect socio-technical data from digital platforms, giving them important insights into learning processes and systems. The data gathered through LA has assisted in identifying areas for development, opening the path for improved student success and academic performance evaluation and helping students transition to the workforce.

The study’s concentration on the post-COVID-19 timeframe may lead to paying attention to potential pandemic developments. Nonetheless, the findings provide a thorough picture of LA’s contributions to HE and valuable ideas for future study initiatives. Future research with the SOR framework suggests areas for additional study to maximize LA’s potential in diverse HE situations.

This study adds to the growing corpus of knowledge on learning analytics in HE, especially in light of the COVID-19 lockdown and its aftermath. By using bibliometric analysis, the study provides a complete and evidence-based understanding of how LA has been used to address challenges related to HE. This study uses bibliometric analysis and SOR theory to appraise and map HE learning analytics research. The selected study themes can help scholars, educators and institutions shape their future efforts to improve teaching, learning and support mechanisms through learning analytics.