Daozhi Zhao

Exemplified by EcoStruxure from Schneider and CASICloud, production-capacity-sharing platforms typically operate as two-sided platforms. These platforms contribute to carbon emission reductions while generating revenue through uniform membership fees, fixed service charges, or commission fees applied to one or both sides of the platform. As B2B platforms, however, they must determine whether to offer online payment options to participants on both sides of the market. We employ the theory of two-sided markets and the method of comparative analysis, developing a two-sided market model to investigate: (1) the platform’s optimal payment method selection strategies and (2) how same-side network externalities and user online search costs affect platform performance. We examine two payment modes: M mode (offline payments only) and F mode (combined offline/online payments). The F mode comprises two sub-modes—FF (two-sided users choose to pay offline) and FN (two-sided users choose to pay online)—determined by users’ payment preferences on each side. We conduct pairwise comparisons of the platform’s membership fee, fixed service fee, and online service level between: (i) FF and M modes and (ii) FN and M modes. Our results indicate that the optimal payment method selection varies across market conditions, with each mode demonstrating superior performance under specific market characteristics. The FF mode consistently yields higher profits compared to the M mode. When suppliers’ expected revenues fall below a certain threshold, the FN mode outperforms the M mode in terms of profit generation. Conversely, the M mode becomes preferable above this threshold. Furthermore, the effects of same-side network externalities and search costs vary significantly across different payment modes. Under the M mode and the FF₁ mode, the effects of the same-side network externality on the platform’s membership fee are associated with two-sided users’ online search costs, which are more monotonous. Under the FN₁ and FN₂ modes, both the same-side network externality and two-sided users’ online search costs impact the platform’s optimal strategies monotonously, but they are not always the same in these two modes.

High economic growth is accompanied by substantial consumption of fossil energy and significant negative externalities on the ecological environment. The global warming effect resulting from environmental pollution caused by energy has brought energy carbon emissions into the forefront of social attention. Establishing a carbon trading market is an essential measure to achieve the “double carbon” goal, with individual and household carbon emissions accounting for 70% of China’s total emissions. Constructing an individual-level carbon trading market will facilitate the efficient realization of this goal. However, addressing the challenge of handling vast amounts of data and network congestion in relation to frequent but small-scale individual carbon trading has become an urgent issue that needs to be resolved. In light of this, the present study designs a digital technology-based framework for the carbon market trading system and proposes an individual carbon asset price-based model for carbon market trading, aiming to establish a research framework for the carbon quota market. Furthermore, blockchain technology is employed as the underlying technology in the proposed carbon trading market model to cater to individual-level carbon trading services and achieve optimal matching between carbon quota suppliers, thereby enhancing profitability of the carbon trading platform. The numerical results obtained from the model demonstrate that in absence of government subsidy mechanisms, individual-level carbon trading can effectively reduce total consumer emissions. The present study successfully overcomes the carbon lock-in effect of consumer groups and achieves the generation and trading of individual carbon assets despite capital constraints. This study facilitates accumulation and trade of individual carbon resources, reduces overall consumer emissions, enhances environmental benefits at societal level, and provides a foundation for governmental decision-making.

With the development of ecological economics, energy-saving green energy chain management has been a wide concern of academia and industries. However, the relatively high cost of green investment makes manufacturers face the problem of financial constraints. On this basis, because the green level information of products is proprietary to manufacturers, manufacturers will lie about the green level of products in order to improve their profits out of the principle of profit maximization. As a result, banks cannot obtain the true green level of products, reducing the benefits of the green energy-efficient supply chain system and making the market of green products volatile. In view of this, blockchain technology is introduced in this paper to improve customer’s product green level sensitivity and obtain lower green credit interest rates from banks. In this paper, a green supply chain financing model based on blockchain technology was constructed under the condition of green information misreporting, and it is compared with the benchmark without blockchain technology. Research shows that the adoption of blockchain can achieve Pareto improvement of green supply chain members. In addition, manufacturers have an incentive to adopt blockchain if the cost of blockchain investment falls below a certain threshold, and consumer green sensitivity increases below that threshold. We compared the profits of green manufacturers with those of retailers and the total emissions of manufacturers. The results show that: (1) When the financing intensity exceeds a certain value, there is an optimal coverage of green financing to ensure that the profit target of manufacturers, the profit target of retailers and the emission reduction target are achieved simultaneously. (2) The adoption of blockchain can achieve Pareto improvement of green energy supply chain members. The actual data of green transformation of Jinyuan New Technology Company were cited. Through calculation, it was found that green transformation can reduce the emissions of enterprises. When the financing intensity is in a certain range, the profits of manufacturers and retailers can be maximized, and the emission reduction degree is the highest. Thus, the practicability and reliability of this model were proved. (3) Manufacturers have an incentive to adopt blockchain if the cost of blockchain investment falls below a certain threshold, and consumer green sensitivity increases below that threshold. The research results of this paper provide solutions for enterprises with limited funds for green transformation and provide a theoretical basis for the government to formulate emission reduction incentive mechanism.

Ride‐sharing platforms, such as Uber and Didi Chuxing, widely use differential pricing strategies to encourage platform participation. However, it remains unclear whether differential pricing strategies in ride sharing are reasonable when users care about price fairness. Moreover, platforms face a unique dilemma when considering differential pricing: should it be used for customers, drivers, or both? On the demand side, platforms must deal with taxi competition, while the supply side contends with government regulation; it is this dilemma that motivates our work. Using a stylized model that includes price fairness, market conditions, and government policies, we consider four ride‐sharing platform pricing strategies: uniform pricing, differential customer pricing, differential driver pricing, and bilateral differential pricing. We present results from three perspectives. For platforms, we obtain feasible regions in all four pricing strategies. If the maximal number of potential drivers is below certain thresholds, a platform will use differential driver pricing. Conversely, differential customer pricing is optimal when the maximal number of potential drivers is sufficiently large. Moreover, when customers have stronger fairness concerns, platforms tend to use differential driver pricing to reduce competition. From the government perspective, when a platform charges customers differently, the government can achieve a win‐win solution for sustainable development and market stability by setting a proper taxi rate. Interestingly, we find that, for the demand and supply sides, an increase in fairness concerns may hurt customers and drivers under certain conditions.

In the manufacturing capacity sharing platform, considering the manufacturing capacity provider’s cost misreporting behavior and the collusion behavior of the platform operator, this paper built a supply chain consisting of a platform operator, a capacity provider with surplus capacity, and a manufacturer with insufficient capacity. This paper studied the influence of the cost misreporting behavior on the supply chain members’ decisions and profits. By use of the game theory, in the scenarios including the supplier misreporting to other supply chain members and the supplier colluding with the platform, the paper analyzed the optimal pricing decision, misreporting coefficient decision, and platform’s service fee decision and further compared the profits of the supply chain and its members. The results show that the capacity provider tends to overstate the production cost for gaining more profits, which exerts negative effects on profits of other members and the supply chain. Compared with the case of misreporting to both the manufacturer with insufficient capacity and the platform, the case of colluding with platform is more favorable to the profits of the manufacturer, the platform, and the supply chain, while the supplier prefers to choose the former situation. When the sales revenue-sharing proportion, cost-sharing proportion, and service fee satisfy certain conditions, the sales revenue-sharing and cost-sharing contract can avoid the capacity provider’s cost misreporting behavior and coordinate the supply chain.

This paper focuses on measures towards sustainable development of coal ports based on the economic, environmental, and social dimensions of the triple bottom line, and examines the integration and optimization roles of smart technologies on coal port sustainability in the era of the Internet of Things. By investigating the representative case of Huanghua Port, one of the largest coal transportation ports in China, this paper enables a better understanding of the coal port’s sustainable practices driven by smart technologies. This study provides measures on the intelligent renovation, coal dust pollution treatment, air pollution treatment and sewage treatment, the customer and employee satisfaction improvement, and community involvement as well as social reputation enhancement. The research investigates the effectiveness of measures on the coal port’s sustainability by examining changes in key performance indicators and further examines the integration and optimization roles of smart technologies. The findings show that the approach taken by the port can effectively promote the coal port’s sustainability. The intelligent operation control system linking the separate nodes in operation, the ecological intelligent control system integrating environmental protection functions, and the intelligent service platform linking supply chain members are interrelated and interact to achieve the continuous optimization of decisions towards coal port sustainability. This study offers managerial insights for the port operators and policymakers towards the sustainable and smart development of ports.

In the context of sharing economy, a manufacturer can source from two alternative channels: sharing and traditional, when facing production capacity constraints and sustainably conscious consumers. The aim of the paper is to analyze channel selection and pricing strategies of the manufacturer for achieving sustainable operations, to investigate the operations of the platform regarding charging modes, access requirements, and commission rates in different stages of development, and to discuss the interaction among all stakeholders for sustainability in the whole system. The game-theoretic approach is adopted. The results provide references for decisions of the manufacturer and surplus production capacity supplier to join in the sharing, as well as corresponding optimal pricing strategies, which guides platforms to keep a balance between profitability and attracting participants by relatively low access requirements and commission rates. Moreover, developing platforms prefer to charge suppliers and set low access requirements while relatively developed platforms tend to charge bilateral sides or manufacturers and set high access requirements. Charging the manufacturer encourages the bilateral participation of the platform most. In addition, as charging mode changes, the trend of changes in consumer surplus and social welfare is the same as that in the market share of products from the sharing channel.

With the maturity of mobile payments and internet technology, a new type of travel mode, shared bicycles, was brought out by China’s urban transport under the impetus of “the last mile” travel demand. Although convenient travel has been achieved by using shared bicycles, the resulting problems such as disorderly parking and the deposition of bicycles could severely influence urban traffic order and impede the sustainable development of shared bicycles. Based on the quasi-public goods property of shared bicycles, this article established a management system for the tripartite collaborative governance of disorderly bicycle parking by virtue of regulating the bicycle parking behavior of users, the promoting of multiple propaganda and macro-institutional controls of the government, and acquiring technique support of enterprise “entry settlement”. Furthermore, considering the influence on the governance effect of user conduct, a structural model for guiding users to regulate bicycle parking to guarantee the governance effect by adopting material incentive and spiritual motivation was established via the utilization of the theory of planned behavior and motivation theories, and multiple hypotheses were also proposed. In this article, users of shared bikes in Beijing, China were selected as the research objects, and a questionnaire survey was adopted as the empirical research method. In addition, the governance validity on disorderly parking of the collaborative governance model was tested via hierarchical regression analysis after the collection and analysis of the factors influencing bicycle parking behavior of users. The obtained results show that the tripartite collaborative governance model could enhance the regular parking consciousness of users and improve the governance effect of disorderly parking. The research conclusion of this article could provide feasible suggestions for the governance of bicycle disorderly parking and propel the sustainable development of shared bicycles.

In the era of the sharing economy, the rise of production capacity sharing has changed traditional manufacturing modes and broken the balance of original production systems. In addition to that environmental-friendly manufacturing enterprises are of great significance with regard to production capacity sharing and sustainable development of the ecology environment. To investigate the decision-making behaviors of the participants involved in low-carbon production capacity sharing, an evolutionary game model taking into account the platforms, manufacturing enterprises with idle production capacity, and those with demanding production capacity is constructed. Then, both evolutionary game theory and Lyapunov stability theorem are used to analyze the asymptotic stability of the equilibrium and evolutionary stability strategies of the system. Besides, the economic and managerial significance of the evolutionary stability strategy is given. Finally, the influence of low-carbon production capacity of enterprises on the stability of the dynamic system is discussed, such as the cost effect of low-carbon production capacity, the effect of transaction cost, and so on. Results indicate that they can provide theoretical reference for decision-making with respect to the platforms, manufacturing enterprises, and sustainable development of the dynamic system.