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This study aims to examine the association of employee resilience and agility with innovative performance and subjective well-being. Moreover, it tests job crafting as the underlying mechanism through which resilient and agile employees perform innovatively and experience higher subjective well-being.

The study used a survey-based research design and structural equation modeling technique to examine the proposed hypotheses. Data was collected from a sample of 380 employees working in the Indian information technology sector using survey questionnaires.

The results show that highly resilient and agile employees participate in job crafting that positively influences their innovative performance and subjective well-being. Job crafting fully mediates the association of resilience with work and well-being outcomes and partially mediates agility and outcomes.

There is a value in promoting the development of employee resilience and agility to foster ways in which employees can craft their jobs and, thus, maximize their innovative performance and subjective well-being.

This study makes an important contribution by underscoring the importance of personal resources (resilience and agility) as drivers of job crafting for higher innovative performance and subjective well-being.

Access to good menstrual products is a human rights issue. Yet, there are rising health concerns of women regarding traditional–plastic sanitary napkins. The usage of these products has raised apprehensions towards the environmental pollution due to the plastic content. The solution for both these issues lies in the sustainable menstrual products. As menstruation is a public health issue, this study aims to identify the role of health beliefs on attitude of women towards sustainable menstrual products.

A survey was conducted for the purpose of data collection. The study uses questionnaire as a research instrument to gain an insight on women health beliefs towards sustainable menstrual products. Data was collected from 527 women respondents through convenience sampling. SPSS and Smart-PLS 4 were used for analysing the data.

Results of the study indicate that all the health belief perceptions had a significant impact on attitude. Women with more positive health belief and less negative health beliefs are the potential consumers for sustainable menstrual products.

To the best of the authors’ knowledge, this the first study that uses health belief model to explore and add to the menstruation literature especially sustainable menstrual hygiene.

This all-inclusive bibliometric study aims to highlight the importance and shift of the researchers and the society towards the sustainable menstrual products (SMPs). This study also provides insights for this taboo topic which needs to be addressed for improving the menstrual hygiene of women.

This study adopts a trio of systematic literature review, bibliometric analysis and content analysis of the research articles taken from the SCOPUS database. The influential journals, authors and countries were established with the bibliometric analysis. Most prestigious research articles were identified based on the page-rank analysis. The intellectual structure was established with bibliographic coupling through which various themes were identified. For the content analysis, thematic mapping and author keyword analysis was performed to gain deeper understanding of themes.

It was established that the taboo yet novel research domain of SMPs is a necessary step towards the improvement of hygiene of women as well as the economy. The products are here to stay making them a Classic; hence, more research normalizing their usage is necessary. From this analysis, research gaps providing directions to the researchers were identified.

To the best knowledge of the authors, this is the first study that provides a comprehensive review of the SMPs. The research methodology applied in this review involves the triad of systematic literature review, bibliometric and content analyses study that establishes an intellectual structure and provides an all-inclusive overview of this taboo research area.

The novel Coronavirus (COVID-19) pandemic, which started in late December 2019, has spread to more than 200 countries. As no vaccine is yet available for this pandemic, government and health agencies are taking draconian steps to contain it. This pandemic is also trending on social media, particularly on Twitter. The purpose of this study is to explore and analyze the general public reactions to the COVID-19 outbreak on Twitter.

This study conducts a thematic analysis of COVID-19 tweets through VOSviewer to examine people’s reactions related to the COVID-19 outbreak in the world. Moreover, sequential pattern mining (SPM) techniques are used to find frequent words/patterns and their relationship in tweets.

Seven clusters (themes) were found through VOSviewer: Cluster 1 (green): public sentiments about COVID-19 in the USA. Cluster 2 (red): public sentiments about COVID-19 in Italy and Iran and a vaccine, Cluster 3 (purple): public sentiments about doomsday and science credibility. Cluster 4 (blue): public sentiments about COVID-19 in India. Cluster 5 (yellow): public sentiments about COVID-19’s emergence. Cluster 6 (light blue): public sentiments about COVID-19 in the Philippines. Cluster 7 (orange): Public sentiments about COVID-19 US Intelligence Report. The most frequent words/patterns discovered with SPM were “COVID-19,” “Coronavirus,” “Chinese virus” and the most frequent and high confidence sequential rules were related to “Coronavirus, testing, lockdown, China and Wuhan.”

The methodology can be used to analyze the opinions/thoughts of the general public on Twitter and to categorize them accordingly. Moreover, the categories (generated by VOSviewer) can be correlated with the results obtained with pattern mining techniques.

This study has a significant socio-economic impact as Twitter offers content posting and sharing to billions of users worldwide.

According to the authors’ best knowledge, this may be the first study to carry out a thematic analysis of COVID-19 tweets at a glance and mining the tweets with SPM to investigate how people reacted to the COVID-19 outbreak on Twitter.