With a renewed global scientific and technological revolution and industrial reform, the digital economy, with data resources as the key element, has rapidly developed. This study proposes a data-driven measurement and evaluation method to promote the coordinated development of the digital economy and logistics industry. An evaluation index system is constructed, which comprehensively considers the index dimensions that reflect the development level of the digital economy and logistics industry. A Z-score standardisation method is applied to data processing, to carry out dimensionless standardisation processing of the original index data. A collaborative degree model is constructed to evaluate the collaborative development level of the digital economy and logistics industry composite system. We demonstrate the implementation process of these models using data from Anhui province from 2013 to 2020. The results verify the feasibility of the research method and emphasise that the development level of the composite system of the digital economy and logistics industry in Anhui province shows a fluctuating growth trend, with variations between the types and degrees of collaboration policy; suggestions are made accordingly. This study provides theoretical and methodological support for the coordinated development of the regional digital economy and logistics industry.

The resources and environmental carrying capacity (RECC) of a region are considered the key and the foundation for achieving sustainable development and the benchmark of environmental protection and pollution control. However, to improve the regional RECC, we need to comprehensively consider the data information and correlation of the economy, society, resources, and the environment. Therefore, we propose a data-driven method for RECC measurement and evaluation of the regional RECC. Based on data collection and the application of the pressure-state-response (PSR) framework to reflect RECC, an evaluation index system for the regional RECC is constructed. The technique for order of preference by similarity to the ideal solution (TOPSIS) model with the entropy weight method is used to measure and evaluate the regional RECC. The obstacle degree model is adopted to select and identify the key factors affecting the regional RECC and to propose targeted policy suggestions for data application. The results indicate that the RECC level in three provinces and one city of the Yangtze River Delta region fluctuated slightly from 2010 to 2019, with an overall upward trend. Anhui Province has a relatively weak carrying capacity, and the main obstacles to RECC improvement in the region are the proportion of wetland area and the ownership of water resources. This study provides theoretical and methodological support for regional RECC research and management as well as a basis for formulating policies related to environmental protection and pollution control.