Realizing the decoupling development between the economic expansion and carbon dioxide emissions of the transport sector is of great importance if the Yellow River basin is to achieve green and low-carbon development. In this paper, we adopt the Tapio decoupling index to examine the decoupling relationship within the transport sector in the Yellow River basin, and then introduce the standard deviational ellipse to dynamically analyze the spatial heterogeneity of carbon emissions and economic growth at the provincial level. Furthermore, based on the decoupling method, we expand the traditional logarithmic mean Divisia index decomposition (LMDI) model to decompose the decoupling index into eight sub-indices, and we identify the impact of each factor on the decoupling relationship. The results indicate that the carbon emissions of the transport sector in the Yellow River basin show the non-equilibrium characteristics of “upstream region < midstream region < downstream region”. The decoupling state of the transport sector shows obvious spatial differences. The less-developed regions are more likely to present non-ideal decoupling states. The growth rate of carbon emissions in Sichuan, Qinghai, and Shandong provinces is relatively fast, and the azimuth of the transport sector’s carbon emissions shows a clockwise trend. Moreover, the inhibitory effects of urbanization on decoupling in the Yellow River basin are much greater than the non-urbanization factors. In addition to the effect of urbanization, the transport structure has a major negative effect on decoupling development in the upstream and midstream regions, while energy intensity and energy structure are key to realizing a decoupled status in the downstream region. Finally, we propose some differentiated policy recommendations.

Cold chain logistics is an industry that generates high levels of carbon emissions. In the context of a low-carbon economy, it is crucial to recognize the low-carbon competitiveness of regional cold chain logistics and to implement effective measures to guide the development and improvement of their low-carbon competitiveness. This is essential for transitioning the economic development model and promoting low-carbon economic growth. This article proposes a low-carbon competitiveness evaluation model known as the Triangular Fuzzy–Gray Correlation Evaluation Model. This model is based on the Triangular Fuzzy Theory and Gray System Theory. According to the calculated logistics low-carbon competitiveness index, a scatter plot is used to rank and classify the evaluation objects. This method utilizes triangular fuzzy numbers as evaluation levels and further expands upon them by introducing the concept of gray correlation in group decision making. By constructing relative closeness based on curve similarity, the improved method possesses a strong ability to capture information and objectivity compared to traditional models. The selected critical indicators cover four significant aspects: low-carbon environment, low-carbon flow service capability, energy consumption in cold chain logistics, and low-carbon energy transition. Empirical research is being conducted using relevant data from Henan in 2022. The measured results are divided into four levels of competition. Using the diamond model, this study analyzes the development of low-carbon cold chain logistics at different levels in each city and provides corresponding recommendations.

Returnable transport items (RTIs) are widely used in multimodal transport systems. However, due to the lack of effective tracking methods, RTIs management efficiency is low and RTIs are easily lost, which directly and indirectly causes economic losses to enterprises. Internet of Things (IoT) technology is proved to be effective in realizing real-time tracking and tracing of various objects in diverse fields. However, an IoT-enabled RTIs management system in a multimodal transport system has not been widely accepted due to a lack of an effective cost decision model. To address these problems, this research first presents three typical schemes of RTIs management. through extensive field studies on collaborative logistics service providers in multimodal transport systems. Then, the cost–benefit analyses of these three schemes are conducted while the decision models on whether to adopt IoT technologies are built. Finally, based on the decision models, the main factors affecting the application of IoT-RTIs management systems are studied by numerical analysis, based on which several managerial implications are presented. These results can serve as a theoretical basis for enterprises interested in finding out whether IoT technology should be used in RTIs management.

A logistics service integrator (LSI) usually requires a logistics service provider (LSP) to carry out smart transformation in order to improve the level of logistics service. However, LSP’s smart transformation faces uncertainty in terms of investments and income, which seriously hinders LSP’s enthusiasm for logistics service innovation. In this paper, we construct a logistics service supply chain (LSSC) consisting of an LSI and an LSP to explore the incentive mechanism for LSPs to undergo smart transformation. As a benchmark for comparison, we first obtain the equilibrium results under centralized decision making and wholesale price (WP) contracts. Then, cost-sharing (CS), revenue-sharing (RS), and cost sharing–revenue sharing (CS-RS) hybrid contracts are proposed. It is found that when the CS coefficient is in a certain interval, the CS contract can increase the profit of LSI and the smart level of logistics service, but it will decrease the profit of LSP. With the exception that the wholesale price of logistics services will decrease, the equilibrium results under the RS contract and WP contract remain consistent. Only the CS-RS hybrid contract can achieve the perfect coordination of LSSC. In addition, by conducting numerical analysis, we find that the enhancement of the smart effect can encourage LSP to improve the smart level and increase the overall revenue of LSSC. To the best of our knowledge, this paper is the first study to explore the incentive mechanism between LSI and LSP in the context of logistics service smart transformation. Our findings guide the LSI in implementing an effective contract.

Persuasive information developed by smartphone applications is a potential tool that can be utilized in order to increase the effectiveness of the impact of pricing strategies on triggering sustainable travel mode choice behavior. In order to address the joint impacts of pricing strategies and persuasive information on habitual automobile commuters’ travel mode shift responses, a stated-preference survey was conducted in Beijing’s inner district, from which over 1000 responses were collected. Four separate multivariable multilevel logistic regression models were estimated for more and less habitual automobile commuters when subjected to congestion pricing and reward strategies. The model estimation results showed that the influence of persuasive information was more effective in promoting travel mode shifts among more habitual automobile commuters with regard to reward strategies compared to congestion pricing. The results also showed that the impact of sociodemographic characteristics, commuter travel characteristics, the amount of congestion pricing or monetary award, and types of persuasive information on travel mode shift decisions under these strategies were deemed to be significantly different between more and less habitual automobile commuters. These findings suggest that more effective reward strategies can be explored by providing personalized and differentiated travel feedback information (e.g., pollution emission information and physical activity information), particularly for less habitual automobile commuters. This study also provides some degree of insight regarding the question as to how to design future congestion pricing, i.e., with respect to formulating differentiated charge rates according to the travel characteristics of habitual automobile commuters, as well as in developing complementary persuasive information that focuses on addressing public acceptability and fairness rather than travel feedback information.