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It is widely argued that money laundering (ML) is not a new phenomenon and the pervasiveness of ML is associated with some severe economic, social and political costs. Due to the lack of studies on the ML’s issue in the UAE, this study aims to examine the determinants of ML in the country between 1975 and 2020.

The autoregressive distributed lag bounds testing results demonstrate the presence of long-run relationship between ML and the selected macroeconomics variables. The analysis is validated by the dynamic ordinary least squares, the fully modified ordinary least squares and the canonical co-integration regression estimators.

The estimation result reveals that while the real estate market, outflow of money, arms procurement and size of the underground economy influences the size of ML positively, gold trade, the level of financial development and the size of economic activities are negatively associated with ML, both in the short- and long-run.

Up to date from a country-level analysis, no study has been devoted to the ML in UAE, except for Aljassmi et al. (2023). To the best of the authors’ knowledge, this study is the first to investigate the determinants of laundered money in the UAE economy. Based on these outcomes, strategies and measures which will deter the laundering of illicit funds through the real estate and gold market, remittance system, financial system and arms procurement contracts in the UAE are recommended.

The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.