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COVID-19 pandemic has overturned the work and family life challenging the world in unpredictable ways that were previously unimaginable. With universities shutting down and emergence of online classes, this phenomenon is prevalent among academicians as well. With this background, the current study aims to investigate the direct relationships between workplace isolation (WPI) during COVID-19 and work–family conflict (WFC) with psychological stress (PS) mediating and organizational identification (OI) moderating the relationship between the two.

The authors employed time lagged survey and collected data at three different time intervals (T1, T2, T3) from 203 academicians working across various universities and colleges in India. The data were analyzed quantitatively using SPSS PROCESS Macro and AMOS.

The results indicated that WPI during COVID-19 has a significant positive relationship with PS and WFC . It was also found that PS partially mediated the relationship between WPI during COVID-19 and WFC. Further, OI emerged as a potential moderator.

Based on the current empirical studies, it remains unclear if WPI during COVID-19 is associated with WFC. Therefore, drawing upon stress–strain–outcome (SSO) model and the conservation of resource theory, this study makes a significant contribution to the existing body of literature by exploring the unexplored associations. To the best of the authors’ knowledge, such an association has not received much scholarly attention before.

This study aims to examine the reaction of anchor investors (AIs) to pre-IPO earnings management (EM). The authors use the unique detailed bid data from the Indian anchor experiment. The authors also study the reputed AIs’ EM detection ability and pricing behavior in response to pre-IPO EM.

The authors use unique AI bid data for 169 Indian IPO firms. Utilizing the logistic regression and Tobit regression models with industry and year-fixed effects, the authors examine the relationship between various measures of AI participation and proxies of short-term and long-term discretionary accruals.

The authors document that pre-IPO EM is positively associated with the likelihood of anchor backing but negatively related to the likelihood of reputed anchor backing. The findings indicate that AIs are misled by pre-IPO EM, but reputed AIs are not. The authors also observe that reputed AIs, compared to the non-reputed, pay less than the upper band with increasing EM. The findings are robust to using various AI measures and EM proxies.

The findings have significant implications for regulators in the implementation of AI concept in non-anchor markets and better implementation of policies in existing anchor settings. Findings can also be relevant for non-institutional investors in the IPO domain.

This is one of the few studies on institutional investors' IPO bidding behavior in response to pre-IPO EM. However, this is the first study to analyze AIs' IPO bidding behavior in response to pre-IPO EM.