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At the outbreak of the COVID-19 pandemic, the absence of pharmaceutical agents meant that policy institutions had to intervene by providing nonpharmaceutical interventions (NPIs). To satisfy this need, the World Health Organization (WHO) issued policy guidelines, such as NPIs, and the government of Pakistan released its own policy document that included social distancing (SD) as a containment measure. This study explores the policy actors and their role in implementing SD as an NPI in the context of the COVID-19 pandemic.

The study adopted the constructs of Normalization Process Theory (NPT) to explore the implementation of SD as a complex and novel healthcare intervention under a qualitative study design. Data were collected through document analysis and interviews, and analysed under framework analysis protocols.

The intervention actors (IAs), including healthcare providers, district management agents, and staff from other departments, were active in implementation in the local context. It was observed that healthcare providers integrated SD into their professional lives through a higher level of collective action and reflexive monitoring. However, the results suggest that more coherence and cognitive participation are required for integration.

This novel research offers original and exclusive scenario narratives that satisfy the recent calls of the neo-implementation paradigm, and provides suggestions for managing the implementation impediments during the pandemic. The paper fills the implementation literature gap by exploring the normalisation process and designing a contextual framework for developing countries to implement guidelines for pandemics and healthcare crises.

This study aims to analyse 508 financially distressed firm-year observations for the period 2010–2018 of Pakistan Stock Exchange (PSX) listed firms to examine the magnitude of indirect financial distress costs (IFDC) and to investigate which firm-specific variable is relatively important in explaining these indirect costs. This will not only enrich empirical literature but also helpful in cross-country comparison.

Optimal model selection along with panel data analysis technique is used to select the most optimal model to observe the findings. Financial distress is measure through Altman’s Z-score and firm-specific variables cover leverage, level of intangible assets, investment policy, tangible assets, firm’s size, level of liquid assets and Tobin’s Q of sample firms.

The findings of this study show that the average size of IFDC for the sample observations is 6.70%. In addition to this, finding further suggest that leverage, the level of intangible assets and changes in investment policy have positive while the size of the firm and Tobin’s Q have a significant negative impact on IFDC. Further, this paper argues that the level of tangible assets and liquid assets are statistically unimportant in observing the IFDC for PSX financially distressed firm-year observations.

The findings of this study provide more insight to corporate managers and investors about the association between firm-specific financial characteristics and IFDC concerning Pakistani firms. Furthermore, this study contributes to the existing literature by adding new evidence from developing countries such as Pakistan which are helpful for regulatory bodies and policymakers in the formulation of long-term strategies to manage the financial distress costs.

The study extends the body of existing literature on IFDC regarding Pakistan. The results suggest that policymakers may pay special attention to the quality of a firm’s capital structure strategies while predicting corporate financial distress costs.