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 digital transformation of the logistics industry is the current trend of development. In order to promote the integrated development of the logistics industry (LI) and the digital economy (DE), we propose a data-driven method which can be used to measure, evaluate, and identify the coupled and coordinated development (CCD) of the LI and DE. On the basis of data collection, we use the entropy weight method to measure the comprehensive development level of the LI and DE. A coordination model is then used to evaluate their CCD level. Finally, an obstacle degree model (ODM) is used to identify the key factors inhibiting the coordinated development (CD) of the two. This method is then applied to gauge the integration development of the LI and DE in Anhui Province. The results show that energy consumption and the lack of logistics employees are the main obstacles to the development of the LI in Anhui Province. The main obstacles to the development of the DE are the low development level of the electronic communications equipment manufacturing industry and the limited digitization of enterprises. Accordingly, this study puts forward corresponding countermeasures and suggestions to provide decision support for the CCD of the LI and DE.

The Chinese economy has undergone high-speed, high-quality growth, and the concept of low-carbon technology has gained popular support. Businesses and consumers must jointly endeavor to achieve low-carbon economic development. Moreover, it is important to investigate whether enterprises' low-carbon behavior is correlated with consumers' green consumption behavior. We built a theoretical model to depict the relationship between corporate public welfare low-carbon behavior, consumers' green purchase intention, and green purchase behavior. We then divided corporate public welfare low-carbon behavior into three dimensions. We proposed hypotheses, collected data through a questionnaire survey, and analyzed the data using statistical analysis software of SPSS 26.0 and AMOS 24.0. Public welfare low-carbon behavior was significantly correlated with consumers’ green purchase intention, and public welfare low-carbon participation and public welfare low-carbon motivation were significantly correlated with green purchase intention. Finally, we proposed suggestions from three perspectives: the public welfare low-carbon mechanism, public welfare low-carbon participation, and public welfare low-carbon motivation. The results provide theoretical support for research methods related to the low-carbon growth of enterprises and green consumption, as well as guidance and decision-making support for enterprises in carrying out cause marketing.

Evaluating the degree of coordination among regional carbon emission systems is key to achieving an earlier carbon peak and carbon neutrality. However, quantifying the co-evolution of carbon emissions among regions is challenging. Therefore, we propose a data-driven method for evaluating the synergetic development of the regional carbon emission composite system. First, the proposed method employs relevant data to calculate the carbon emissions and carbon emission intensity of each subsystem within the region to describe the temporal trends. The inverse entropy weight method is then used to assign weight to each order parameter of the subsystem for data processing. Then, we perform synergetic development assessment of the composite system to measure the order degree of each subsystem, the degree of synergy among subsystems, and the overall synergetic degree of the temporal evolution of carbon emissions between regions. Finally, the evaluation results can be used to suggest measures for the regional coordinated reduction of carbon emissions. In this study, we used data from the Yangtze River Delta (YRD) region from 2010 to 2019 to demonstrate the feasibility and effectiveness of the method. The results show that there is still a long way to go to reduce carbon emissions in the Yangtze River Delta region. Economic development still relies heavily on fossil energy consumption, and the regional carbon emission reduction synergy is not high. This study provides theoretical and methodological support for regional carbon emission reduction. Moreover, the proposed method can be applied to other regions to explore low-carbon and sustainable development options.

To delve into the interrelationship between the green transformation of industry and the economy’s high-quality development, to promote the coordinated development of industrial carbon emission efficiency and digital economy, to expand the scope and research ideas related to economic and social sustainable development, and to provide scientific reference for the low-carbon sustainable development of regional economy, this article introduced a data-centric methodology for evaluating the collaborative advancement of both industrial enterprises’ carbon emission efficiency and the digital economy. To accurately gauge the carbon footprint of industrial enterprises, models focusing on carbon emissions as well as carbon emission intensity were employed. To enhance the precision of evaluation outcomes and mitigate biases stemming from subjective weighting factors, we employed the entropy weight method to objectively assign weights to each indicator. Furthermore, the super-efficient slack-based model (SBM) can solve the problem that the conclusions are biased, due to the different radial. Subsequently, a carbon-emission efficiency slack-based measure model, and models for coupling degree and coupling-coordination degree were formulated. Anhui, as a central province in China, is also an important province in the Yangtze River Delta integration development. Coordinated development of its carbon emission efficiency and digital economy has important implications for the sustainable economy advancements of other regions in China, and even other countries or regions in the world. Therefore, Anhui was selected to be the empirical research sample. The results showed that the comprehensive levels of these two systems followed an increasing trend, while the digital economy lagged. Their coupling degree fluctuated and reached its highest point in 2021, whereas their coupling-coordination degree increased, showing high coupling and low coordination overall. This study proposes specific countermeasures and suggestions for the relevant decision-makers.