The nexus between green intellectual capital, blockchain technology, green manufacturing, and sustainable performance.

Enterprises across the globe are facing increasing pressure to effectively utilize resources and reduce costs through green supply chain practices. Emerging technology, such as blockchain technology which enables green practices, has become a contemporary industrial paradigm. However, enterprises need to build green intellectual capital to implement blockchain technology, which can be key to realizing green supply chain practices.

Greening the manufacturing firms: do green supply chain management and organizational citizenship behavior influence firm performance?

The spontaneous organizational citizenship behavior towards environment (OCBE) of employees in the workplace is crucial to businesses' green development and low-carbon transition. However, it was not considered how such behavior could be encouraged for enhanced firm performance. From the natural resource-based view theory perspective, this study tests a model that investigates how green supply chain management practices, green culture, top management commitment, and OCBE, and influences firm performance.

Striving towards sustainable development: how environmental degradation and energy efficiency interact with health expenditures in SAARC countries.

The previous studies focused on environmental issues, identifying their root causes, urging prompt action to reduce environmental degradation. In this context, the current article extends the literature by incorporating the ecological impacts on the health sector and the role of sustainable development. The present study adds to the body of knowledge by examining the relationship between CO emissions, sustainable development, energy efficiency, energy intensity, and health expenditures for SAARC countries from 2000 to 2020.

Assessment and prediction of environmental sustainability: novel grey models comparative analysis of China vs. the USA.

Emission forecasting is vital for policy-making and emission reduction goals globally. This research aimed to perform an accurate model for forecasting and assessing CO emissions and the production of renewable electricity for the top two countries contributing to these emissions, the USA and China. In this study, we employed three novel advanced mathematical grey models: optimized discrete grey model (ODGM), nonhomogeneous discrete grey model (NDGM), and variable speed and adaptive structure grey model (VSSGM) to estimate the future trends of CO emissions and renewable electricity production.