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The logistics industry (LI) is a key pillar of the global economy, and its carbon emission efficiency (CEE) is crucial for achieving carbon neutrality. The rapid development of the digital economy (DE) has had a profound impact on the LI, but the spatial impact on its CEE is currently unclear and requires further research. Firstly, based on the collection of relevant data, we use the entropy weight method and linear weighted sum method to measure the level of development of the DE. Secondly, the SBM model is used to measure the CEE level of the LI. Using Moran's I index model and OLS and GWR models, we analyze the impact and spatial distribution characteristics of the DE on the CEE of the LI and propose development strategies. The article uses statistical data from 30 provinces in China from 2013 to 2022 as an example to demonstrate the implementation process of the method. The results show that the DE has a positive impact on the CEE of the LI, and there are spatial differences. Based on this, this article proposes policy recommendations for the development of green and low-carbon logistics and digital logistics that are tailored to local conditions, providing theoretical and methodological support for low-carbon research in the LI, and providing reference for other countries and regions to explore the path of green and low-carbon transformation. [ABSTRACT FROM AUTHOR]

The deep integration and innovative development of the logistics and manufacturing industries (LMDIIs) are crucial for reducing costs, increasing efficiency, and advancing manufacturing. To assess the development level and performance of the LMDIIs, we construct an evaluation index system, calculate the weights using the CRITIC method, and measure the comprehensive level of the LMDIIs using the TOPSIS method. We evaluate the coupling coordination of the LMDIIs and conduct a ridge regression analysis of their performance, using Anhui Province, China, as a case study. The results show that the comprehensive level of the LMDIIs in Anhui Province is low. The highest values for the logistics and manufacturing industries from 2013 to 2022 indicate great development potential. The coupling level is fluctuating upwards, and the coupling degree is growing slowly. The performance impact coefficients of the LMDIIs on the digital intelligence development of the manufacturing industry and the profit levels of the two industries indicate a significant promoting effect. However, the performance coefficient for the low-carbon transformation of the logistics industry is negative, indicating a restraining effect. Hence, we propose countermeasures and suggestions to further promote the LMDIIs and provide theoretical and methodological support for their research and management. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The receding globalization has reshaped the logistics industry, while the additional pressure of the COVID-19 pandemic has posed new difficulties and challenges as has the pressure towards sustainable development. Achieving the synergistic development of economic, social, and environmental benefits in the logistics industry is essential to achieving its high-quality development. Therefore, we propose a data-driven calculation, evaluation, and enhancement method for the synergistic development of the composite system of economic, social, and environmental benefits (ESE-B) of the logistics industry. Based on relevant data, the logistics industry ESE-B composite system sequential parametric index system is then constructed. The Z-score is applied to standardize the original index data without dimension, and a collaborative degree model of logistics industry ESE-B composite system is constructed to estimate the coordinated development among the subsystems of the logistics industry's ESE-B system. The method is then applied to the development of the logistics industry in Anhui Province, China from 2011 to 2020. The results provide policy recommendations for the coordinated development of the logistics industry. This study provides theoretical and methodological support for the sustainable development aspects of the logistics industry. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Improving the logistics industry's resource efficiency (LIRE) is one of the most significant measures for ensuring sustainable development. We offer a data-driven technique for analyzing and optimizing the LIRE to improve it and achieve sustainable development. A LIRE index system is built based on relevant data gathering and a complete examination of the economy, society, and environment. The Super-EBM-Undesirable model was used to calculate the LIRE; the Global Malmquist–Luenberger index model was used to calculate the LIRE's dynamic change characteristics, and ArcGIS and spatial autocorrelation models were used to analyze the LIRE's spatial evolution pattern. The LIRE in 30 Chinese provinces and cities from 2011 to 2019 is used to illustrate the method implementation process. The results indicate the following: (1) The overall LIRE is low, with an average value of 0.717, and there are regional variances with a decreasing gradient pattern of "East–Northeast–Central–West". (2) Changes in pure technical efficiency have a bigger impact in general; increasing technical efficiency is the LIRE's principal motivator. (3) Improving the LIRE should take spatial spillover and inhibitory effects into account. This study provides theoretical and methodological support for the evaluation and optimization of the LIRE and a theoretical foundation for the logistics industry's sustainable development (LISD). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study explores the spatial effect of infrastructure development on real estate prices in the Yangtze River Delta. It constructs an evaluation system of the infrastructure development level across five dimensions (i.e., transportation, water supply and drainage, energy and power, postal communication, and ecological environment), analyzes the development characteristics of urban infrastructure in the Yangtze River Delta, and uses a spatial panel model to explore how urban infrastructure development affects real estate prices. Results indicate that (1) the overall development level of urban infrastructure in the Yangtze River Delta region shows an upward trend. Significant regional differences exist as the development level of urban infrastructure in the eastern region is ahead of that in the central region; (2) Spatial autocorrelation and real estate prices in the Yangtze River Delta region in infrastructure development and overall levels, respectively, are high; (3) Infrastructure directly affects local real estate market demand and improves the vitality of the housing market in adjacent areas; and (4) Infrastructure construction can significantly promote the rise of urban real estate prices in the eastern region, while this driving effect is not significant in the central region. This research will help the government promote the coordinated development of urban infrastructure and formulate relevant policies for the macro-control of the real estate market in urban agglomerations. [ABSTRACT FROM AUTHOR]