The logistics industry around the world has proliferated over recent years as a large number of business organizations have come to recognize the importance of logistics. Cost control used to be emphasized to remain competitive, but recently green logistics has gained attention with the awareness of the integration of economy and society as a whole. Nowadays, green logistics is a useful concept to improve the sustainability of logistics operations, and its related policies and theoretical research have been investigated and explored. However, the practical applications of green logistics are impeded by real-time data sharing, which is common in the logistics industry. Blockchain technology is adopted to address this challenge and enable data sharing among related stakeholders. This paper presents a reference framework for green logistics based on blockchain to reach the sustainable operations of logistics, with the integration of the Internet of Things and big data. Finally, potential benefits and limitations are analyzed when implementing this framework.

Although researchers have stressed the effects of scientific, geographical and economic factors on patent collaboration at a global or national scale, few studies explored the evolutionary mechanism of collaboration in cross-border megalopolitan areas. In this context, the article investigates the spatial patterns and provides a dynamic evaluation of different types of determinants on the intercity co-invention network of the Greater Pearl River Delta in China. Using the patent application data over the period of 2008–2016, social network analysis results confirm that the co-invention network has become more cohesive and more decentralised, and the ‘core-periphery’ structure remains stable. The empirical results from Exponential Random Graph Model show that the establishment of high-speed railway network is gaining importance in collaboration with time. While regional, linguistic borders impede the collaborations at first, the effect is diminishing. Besides, cognitive proximity, R&D input intensity, educational level and triadic closure contribute positively to the co-invention network, and their relevance remain nearly the same over time.