Search results

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.

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).