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This study analyses the organizational consequences of work–family conflict (WFC) among female nurses in health care sector. Moreover, this study focuses on the moderating effect of intrinsic motivation on the association between WFC dimensions with different organizational outcomes.

Data are collected from 347 female nurses working in health care sector at Islamabad, Rawalpindi, Lahore, Multan and Bahawalpur regions of Pakistan, using random sampling technique. Regression analysis is used to test the hypotheses of this study.

The findings demonstrate that WFC conflict lowers job satisfaction, affective commitment and organizational citizenship behaviour. Contrary, WFC reduces job satisfaction, affective commitment and organizational citizenship behaviour and increases turnover intentions among female nurses. Moreover, intrinsic motivation moderates the association between WFC and certain organizational outcomes.

The study offers valuable insights for female nurses at health care sector about WFC and finally leads to theoretical contributions and practical implications for the healthcare sector of Pakistan.

Drawing on the conservation of resources theory, the present study aims to design and explore the influence of abusive supervision and coworker incivility on turnover intention among frontline employees (FLEs). Besides the mediating effects of work stress between abusive supervision and turnover intention, coworker incivility and turnover intention also be explored.

Data from 311 FLEs are collected by a self-administered structured questionnaire and analyzed by confirmatory factor analysis and structural equation model.

The empirical results established that abusive supervision and coworker incivility significantly predicts work stress and work stress significantly predicts turnover intention. Abusive supervision significantly predicts a positive relationship with turnover intention, whereas coworker incivility with turnover intention is vis-à-vis. Besides, abusive supervision and coworker incivility significantly predict turnover intention via work stress. The study further illustrated the control variables, e.g. education, experience, and proactive personality of FLEs.

The study finds abusive supervision and coworker incivility as stressors in the emerging economy for FLEs. However, coworker incivility on turnover intention cannot predict as expected because the roles of the supervisor and coworker are different in this context.

The continuous support of supervisors and coworkers can reduce the stress and consequences of reducing the intention of turnover of FLEs. The concerns can enhance their support by using respect and credit for work, maintaining privacy, providing proper feedback, being sensible to the performance, and entitlement to any achievement. They also suggest ensuring a work environment of privacy, fair treatment, importance to suggestions, and ascertaining punishment for any colleague's mistreatment.

The frontliners always contribute a large pie of output for any organization. Supervisors and coworkers impact the day-to-day life of FLEs.

As a study on FLEs in the context of evolving economy, the investigation fulfills the inconsistencies of the previous result with the mediating role of work stress with a strong theoretical base.

The main purpose of this study is to develop an environmental mitigation behavior model (EMBM) for predicting waste reduction behaviors among young coastal tourists in Bangladesh by modifying and extending the theory of planned behavior (TPB).

The research has been administered by applying mixed method (both qualitative and quantitative), where study-1(qualitative) identifies factors, study-2 (quantitative) verifies factors by employing exploratory factor analysis (EFA) approach, and study-3 confirms factors influencing waste reduction behaviors among young coastal tourists by employing confirmatory factor analysis (CFA). Study-2 collects 385 valid responses and analyzes by applying the principal component analysis (PCA) technique with the Varimax rotation method by using SPSS-v25, and Study-3 collects 501 valid responses and analyzes by partial least structural equation modeling (PLS-SEM) technique, using Smart PLS3.3.3.

The study findings have revealed that waste reduction intention and perceived ecological balance significantly influence waste reduction behaviors among young coastal tourists in Bangladesh. Further, waste reduction intention is significantly predicted by mitigation attitude, resource conservation norms and environmental perceptions. Furthermore, environmental ethics significantly affects mitigation attitudes and resource conservation norms.

The study offers several insightful implications (e.g. incentives, charging fines, environmental awareness-related knowledge-based campaign, etc.) for policymakers and industry operators, which may be a dynamic cost-effective mechanism for reducing waste at coastal tourism destinations in Bangladesh as well as in the world.

This study addresses the need for developing a model that can explain waste reduction behaviors among young coastal tourists in Bangladesh, and thus, the study uniquely postulates the theory of environmental mitigation behavior for predicting waste reduction behaviors by modifying and extending the TPB.

This study aimed to examine how knowledge sharing, knowledge management, supply chain efficiency and integration collectively impacted firm performance. Additionally, it investigated the moderating influence of reverse logistics on these relationships, seeking to enhance understanding of the complex dynamics within organizations.

A comprehensive method was used in the research design, combining a thorough evaluation of the body of literature with organized questionnaire data collection. Random sampling was used to collect data from Pakistani manufacturing companies, and PLS-SEM was used to analyze the collected data.

The findings demonstrated the strong positive relationships between knowledge management, integration, supply chain effectiveness, and information sharing and business performance. The study also showed that reverse logistics improved and moderated these correlations, highlighting the significance of managing reverse logistics well for the best possible company performance.

In terms of practical implications, the study offered organizations looking to improve performance useful information. Making informed strategic decisions was made possible by realizing the benefits of knowledge management, integration, supply chain efficiency, and sharing. The relevance of using successful tactics to maximize company outcomes was highlighted by highlighting the moderating effects of reverse logistics.

By thoroughly analyzing the connections between knowledge management, supply chain effectiveness, integration, and firm performance—while taking into account the moderating influence of reverse logistics—this study enhanced the body of existing literature. The discoveries significantly added value to this research topic by enhancing our understanding of how these elements collectively influence business performance, especially in the sometimes disregarded field of reverse logistics.

Despite the current progress in realizing how Big Data Analytics can considerably enhance the Sustainable Manufacturing Supply Chain (SMSC), there is a major gap in the storyline relating factors of Big Data operations in managing information and trust among several operations of SMSC. This study attempts to fill this gap by studying the key enablers of using Big Data in SMSC operations obtained from the internet of Things (IoT) devices, group behavior parameters, social networks and ecosystem framework.

Adaptive Prospects (Improving SC performance, combating counterfeits, Productivity, Transparency, Security and Safety, Asset Management and Communication) are the constructs that this research first conceptualizes, defines and then evaluates in studying Big Data Analytics based operations in SMSC considering best worst method (BWM) technique.

To begin, two situations are explored one with Big Data Analytics and the other without are addressed using empirical studies. Second, Big Data deployment in addressing MSC barriers and synergistic role in achieving the goals of SMSC is analyzed. The study identifies lesser encounters of barriers and higher benefits of big data analytics in the SMSC scenario.

The research outcome revealed that to handle operations efficiently a 360-degree view of suppliers, distributors and logistics providers' information and trust is essential.

In the Post-COVID scenario, the supply chain practitioners may use the supply chain partner's data to develop resiliency and achieve sustainability.

The unique value that this study adds to the research is, it links the data, trust and sustainability aspects of the Manufacturing Supply Chain (MSC).