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This study investigates the impact of temporary employment on various forms of financial distress for firms during the COVID-19 pandemic.

The authors apply a logit model to evaluate the differences in the probabilities of experiencing financial distress for firms with or without temporary reemployment and for firms with different intensities of temporary workers. As an additional test, an ordinal logistic model is applied to reflect different degrees of financial distress.

Our main results indicate that firms with temporary employment are more likely to experience financial distress than firms without temporary employment, regardless of the severity of financial distress. Among firms with temporary employment, our analysis suggests that a firm’s likelihood of experiencing financial distress depends on its relative share (quantile) of temporary workers.

Our findings provide valuable insights for evaluating the impact of temporary employment on firms’ vulnerability during the COVID-19 crisis and suggest strategies for firms to enhance resilience to similar future crises.

Our study is the first one that explores the relationship between temporary employment and financial distress. Firms around the world have been pursuing flexible labor to improve resilience and firm performance. The pandemic may further ramify this trend, creating a future “new normal” regarding employment relationships, job segmentation and gender equality in the job market. This article adds a new dimension to the evaluation of the new normal, which may help firms evaluate the consequences of temporary employment, especially in times of crisis.

This study aims to examine the impact of COVID-19 on tourism and hospitality small and medium-sized enterprises (SMEs) in an emerging country located in Latin America and identifies service innovation strategies adopted by these firms to survive a prolonged crisis.

A qualitative investigation was conducted drawing on a framework of imposed service innovation. Data were obtained from in-depth interviews with owners/managers of 20 SMEs in the hospitality and tourism sector in Chile.

Findings show that the effect of COVID-19 on SMEs includes a decline in demand due to lockdowns and restrictions, with minimal government support. Tourism and hospitality SMEs developed different service innovation strategies to confront the crisis, and several businesses were even able to exploit new opportunities for future growth.

The effect of COVID-19 and SMEs' service innovation strategies to confront a prolonged crisis is a topic that is largely unexplored, particularly in the tourism and hospitality sector. The findings contribute to the literature on emerging markets, crisis management and SME innovation in tourism and hospitality. The findings provide managerial implications for SME managers, governments and policymakers.

This study aims to conduct a systematic literature review and bibliometric analysis on the topic of digital labour. The study also identifies the future research directions for the topic.

In total, 118 research papers were identified and reviewed from 11 established research databases and A*, A and B category journals from the ABDC journal list. The papers covered a timespan between 2006 and 2023. Bibliometric analysis was conducted to identify key research hotspots.

The emergent themes and associated sub-themes related to digital labour were identified from the literature. The paper found three significant themes that include digital labour platform, gig economy and productivity. This study also acts as a platform to initiate further research in this field for academicians, scholars, industry practitioners and policymakers. The future research scope in the topic is also presented.

The present study is unique in its nature as it approaches the topic of digital labour from all relevant perspectives.

The current research elucidates the role of empathy in design of artificial intelligence (AI) systems in healthcare context, through a structured literature review, analysis and synthesis of academic literature published between 1990 and 2024.

This study aims to advance the domain of empathy in AI by adopting theory constructs context method approach using the PRISMA 2020 framework.

The study presents a current state-of-the-art literature to review the connections between empathy and AI and identifying four clusters showing the emerging trajectories in the field of AI and empathy in healthcare setting.

Despite a rise in empirical research, the potential pathways enhancing AI accountability by incorporation of empathy is unclear. The research aims to contribute to the existing literature on AI and empathy in the healthcare sector by carving out four distinct clusters depicting the future research avenues.