Search Results (40)

This study examines how digital transformation (DT) affects sustainable marketing performance (SMP) in the green consumer-goods sector, focusing on new energy vehicle (NEV) enterprises. It explores the mediating role of responsive market orientation (RMO) in this relationship. A structural path model integrating DT, RMO, and SMP is developed to analyze the impact of digital-technology adoption and market responsiveness to green marketing outcomes. This research conducts an empirical analysis using structural equation modeling based on the data of 86 Chinese A-share listed new-energy companies from 2018 to 2022. The results indicate that DT directly improves SMP and also indirectly enhances it by reinforcing RMO. RMO is found to play a significant mediating role. This study may contribute to the theoretical and methodological understanding of how digital strategies drive marketing performance in the context of green consumption and offers empirical support for advancing corporate green marketing practices. Full article

With the rising urgency of global environmental challenges, understanding the mechanisms behind green consumption has become increasingly vital. This study investigates how green product information disclosure influences consumers’ green consumption intention, focusing on new energy vehicle (NEV) consumers in China. Grounded in the Theory of Planned Behavior (TPB), the study introduces environmental concern as a mediator and brand reputation as a moderator to enhance the explanatory power of the model. A total of 527 valid questionnaires were collected on-site from NEV exhibitions in Beijing. Structural equation modeling and PROCESS macro analysis were employed to test the research hypotheses. The results indicate that environmental information disclosure significantly promotes green consumption intention, both directly and indirectly, through the mediating effects of green consumption attitude, subjective norms, and environmental concern. However, the direct effect of information communication channels was not statistically significant. Moreover, brand reputation positively moderates the relationship between environmental information disclosure and green consumption intention. These findings provide new theoretical insights by extending TPB with contextual and psychological variables and offer practical implications for NEV manufacturers and marketers. Specifically, companies are encouraged to prioritize transparent and credible environmental information disclosure, strengthen brand reputation, and consider consumers’ attitudes and social norms when designing green marketing strategies. Full article

New energy vehicles (NEVs) have gained increasing favor among NEV consumers due to their dual advantages of “low cost” and “environmental friendliness.” In recent years, the share of NEVs in the global automotive market has been steadily rising. For instance, in the Chinese market, the sales of new energy vehicles in 2024 increased by 35.5% year-on-year, accounting for 70.5% of global NEV sales. However, as the diversity of NEV brands and models expands, selecting the most suitable model from a vast amount of information has become the primary challenge for NEV consumers. Although online service platforms offer extensive user reviews and rating data, the uncertainty, inconsistent quality, and sheer volume of this information pose significant challenges to decision-making for NEV consumers. Against this backdrop, leveraging the strengths of the quasi OWA (QOWA) operator in information aggregation and interval basic uncertain linguistic information (IBULI) information aggregation and two-dimensional information representation of “information + quality”, this study proposes a large-scale group data aggregation method for decision support based on the IBULIQOWA operator. This approach aims to assist consumers of new energy vehicles in making informed decisions from the perspective of information quality. Firstly, the quasi ordered weighted averaging (QOWA) operator on the unit interval is extended to the closed interval $\left[0,\tau \right]$, and the extended basic uncertain information quasi ordered weighted averaging (EBUIQOWA) operator is defined. Secondly, in order to aggregate groups of IBULI, based on the EBUIQOWA operator, the basic uncertain linguistic information QOWA (BULIQOWA) operator and the IBULIQOWA operator are proposed, and the monotonicity and degeneracy of the proposed operators are discussed. Finally, for the problem of product decision making in online service platforms, considering the credibility of information, a product decision-making method based on the IBULIQOWA operator is proposed, and its effectiveness and applicability are verified through a case study of NEV product decision making in a car online service platform, providing a reference for decision support in product ranking of online service platforms. Full article

This study combines text mining and binary logit model to analyze the main influencing factors of consumers’ purchase intention for new energy vehicles (NEVs) in Urumqi. Through the analysis of 34,561 consumer reviews and 400 valid questionnaire data, the study found that battery technology, sales price, and policy support have a significant impact on purchase intention. Based on the differences in consumers’ price sensitivity, technology preference, and policy support, this paper segments consumers into six groups. Based on these findings, we propose policy recommendations to optimize subsidy policies, promote battery technology upgrades, and improve charging infrastructure, in order to drive the development of the NEV market. Full article

Against the backdrop of increasingly severe global climate change, the automotive industry, as a carbon-intensive sector, has found its low-carbon transformation crucial for achieving the “double carbon” goals. This paper constructs manufacturer decision-making models under an oligopolistic market scenario for the single dual-credit policy and the “dual-credit + carbon cap-and-trade” policy, revealing the nonlinear impacts of new energy vehicle (NEV) credit trading prices, carbon trading prices, and credit ratio requirements on manufacturers’ pricing, emission reduction effort levels, and profits. The results indicate the following: (1) Under the “carbon cap-and-trade + dual-credit” policy, manufacturers can balance emission reduction costs and NEV production via the carbon trading market to maximize profits, with lower emission reduction effort levels than under the single dual-credit policy. (2) A rise in credit trading prices prompts hybrid manufacturers (producing both fuel vehicles and NEVs) to increase NEV production and reduce fuel vehicle output; higher NEV credit ratio requirements raise fuel vehicle production costs and prices, suppressing consumer demand. (3) An increase in carbon trading prices raises production costs for both fuel vehicles and NEVs, leading to decreased market demand; hybrid manufacturers reduce emission reduction efforts, while others transfer costs through price hikes to boost profits. (4) Hybrid manufacturers face high carbon emission costs due to excessive actual fuel consumption, driving them to enhance emission reduction efforts and promote low-carbon technological innovation. Full article

The rapid development of the new energy vehicle (NEV) industry has led to concerns about battery quality and the transparency of green recycling, causing uncertainty among consumers. Many firms adopt blockchain technology to solve this problem, but blockchain adoption will bring privacy leakage risk to consumers. A Stackelberg game model of a three stage NEV supply chain is constructed to examine the impact of adapting blockchain on strategic decisions of supply chain participants. We consider a setting in which a battery supplier provides batteries to a NEV manufacturer, and a third-party recycler recovers retired batteries for a NEV manufacturer. We explore the influence of consumers’ green recycling preferences on the decisions of NEV supply chain members in three scenarios: not adopting blockchain traceability (NB), adopting blockchain with forward traceability (FB), and adopting blockchain with forward–reverse traceability (DB). We find that NEV supply chain members are more likely to adopt forward–reverse traceability under certain conditions. Moreover, the adoption of blockchain drives the battery supplier and NEV manufacture to increase wholesale price and retail price, especially under forward–reverse traceability. In addition, when consumers exhibit strong preferences for green recycling, third-party recyclers are more willing to invest in blockchain-based recycling due to its ability to enhance the accuracy and credibility of recycling data. Full article

Fine-grained feature extraction and affective semantic mapping remain significant challenges in product form analysis. To address these issues, this study proposes a contrastive learning-based cross-modal fusion approach for product form imagery recognition, using the front-end design of new energy vehicles (NEVs) as a case study. The proposed method first employs the Biterm Topic Model (BTM) and Analytic Hierarchy Process (AHP) to extract thematic patterns and compute weight distributions from consumer review texts, thereby identifying key imagery style labels. These labels are then leveraged for image annotation, facilitating the construction of a multimodal dataset. Next, ResNet-50 and Transformer architectures serve as the image and text encoders, respectively, to extract and represent multimodal features. To ensure effective alignment and deep fusion of textual and visual representations in a shared embedding space, a contrastive learning mechanism is introduced, optimizing cosine similarity between positive and negative sample pairs. Finally, a fully connected multilayer network is integrated at the output of the Transformer and ResNet with Contrastive Learning (TRCL) model to enhance classification accuracy and reliability. Comparative experiments against various deep convolutional neural networks (DCNNs) demonstrate that the TRCL model effectively integrates semantic and visual information, significantly improving the accuracy and robustness of complex product form imagery recognition. These findings suggest that the proposed method holds substantial potential for large-scale product appearance evaluation and affective cognition research. Moreover, this data-driven fusion underpins sustainable product form design by streamlining evaluation and optimizing resource use. Full article

In recent years, as an important alternative to traditional gasoline-powered vehicles, new electric vehicles (NEVs) have gained widespread attention and rapid development globally. In the traditional automotive industry chain, downstream vehicle manufacturers need to master core technologies, such as engines, chassis, and transmissions. In contrast to the traditional automotive industry chain, where downstream vehicle manufacturers must master core technologies, like engines, chassis, and transmissions, the electric vehicle industry chain has evolved in a way that the development of core components is gradually separated from the vehicle manufacturers. Downstream vehicle manufacturers can now outsource key components, such as batteries, electric controls, and motors. Additionally, in terms of sales models, the electric vehicle industry chain can adopt either the traditional 4S dealership model or a direct-sales model. As the research and development of core components are increasingly separated from vehicle manufacturers, the downstream vehicle manufacturers can source components, like batteries, electric controls, and motors, externally. At the same time, they can choose to use either the traditional 4S dealership model or the direct-sales model. The underlying mechanisms and channel selection in this context require further exploration. Based on this, a mathematical model is established by incorporating terminal marketing input, product competitiveness, and after-sales service levels from the literature to solve for the optimal pricing under centralized and decentralized pricing strategies. Using numerical examples, the pricing and profit performance under different market structures are analyzed to systematically examine the impact of the electric vehicle supply chain on business operations, as well as the changes in various elements across different channels. We will focus on how after-sales services (including the spare part supply) influence the pricing strategy and profit distribution in the supply chain, aiming to provide insights into advanced manufacturing system management for manufacturing enterprises and improve the efficiency of intelligent logistics management. The research indicates that (1) The direct-sales model helps to improve the terminal marketing input, after-sales service quality, and product competitiveness for supply chain stakeholders; (2) It is noteworthy that the manufacturer’s direct-sales model also significantly contributes to lowering prices, highlighting that the direct-sales model has substantial impacts on both supply chain stakeholders and, importantly, consumers. Full article

With the booming development of the new energy vehicle (NEV) industry, the issue of power battery recycling has increasingly attracted attention. Standardized recycling of power batteries can reduce environmental pollution and promote sustainable resource utilization. This paper employs evolutionary game theory to construct two models of deposit systems for the recycling of new energy vehicle power batteries: one under market mechanisms and the other with government participation. The evolutionary stable strategies among vehicle manufacturers, consumers, and the government are examined, and the stable equilibrium points of the models are analyzed. Finally, Matlab is used to conduct a simulation analysis of the deposit system with government participation. The results indicate that the deposit system under market mechanisms is difficult to constrain consumer behavior, while the deposit system with government participation is conducive to promoting the achievement of long-term environmental protection goals. These findings provide valuable insights for policymakers in designing deposit–refund systems and contribute to advancing the sustainable development of the NEV industry. Full article

Under the low carbon goal, recycling power batteries (PBs) from new energy vehicles (NEVs) is a crucial measure to address resource shortages and reduce carbon emissions. This study examined the insufficient collaboration among the responsible entities and the imperfections in market mechanisms within the PB recycling system. We overcome the limitations of traditional tripartite evolutionary game models by developing a four-party evolutionary game model that incorporates the government, manufacturers, recyclers, and consumers to investigate the strategic interactions within the extended producer responsibility (EPR) framework. Using MATLAB 2023a numerical simulations and Lyapunov stability analysis, we found that the system’s stability and efficiency depend on stakeholder collaboration and effective government policy guidance. The system evolves toward a Pareto optimal state when all parties adopt proactive recycling strategies. Meanwhile, ensuring substantial profits for manufacturers and recyclers is critical for the feasibility and stable operation of compliant recycling channels. While manufacturers and recyclers are more sensitive to subsidies than consumers, consumer decision-making is key to market stability. Long-term excessive subsidies may lead to diminishing marginal benefits. Strategic recommendations are provided for policymakers and stakeholders to enhance the efficiency and sustainability of the PB recycling system. Full article

This paper aims to assess the impact of the New Energy Vehicle (NEV) mandate policy on the passenger vehicle market in China, with a focus on its effectiveness in promoting NEV adoption. In response to global climate goals and energy security concerns, China has implemented various NEV policies, including the phase-out of direct subsidies and the introduction of the NEV mandate policy (dual-credits policy). This policy, which combines NEV credits and Corporate Average Fuel Consumption (CAFC) credits, aims not only to promote NEV adoption but also to support industrial policy objectives by helping the auto industry leapfrog traditional internal combustion engines and become globally competitive. In this study, a System Dynamics (SD) model was developed using Vensim software (10.2.2) to simulate interactions between automakers, government policies, and consumer behaviors. The results show that the NEV mandate policy significantly boosts NEV sales, with projections indicating that NEV sales will reach 15 million units by 2030, accounting for 55% of the passenger vehicle market. Additionally, the study finds that tightening NEV credits standards and increasing the NEV credit proportion requirements can further enhance market growth, with stricter measures post-2023 being crucial to achieving a 50% market share. In contrast, under a scenario where the dual-credits policy ends in 2024, the NEV market share would still grow but would fall short of the 50% target by 2030. The findings suggest that stronger policy measures will be essential to maintain long-term market momentum. Full article

With the escalating environmental issues, the imperatives to mitigate greenhouse gas emissions and advance energy products through innovation, energy production, and consumption frequently result in environmental externalities. Conventional markets frequently struggle to address these external factors, resulting in market failures. Consumers are more aware of the environmental repercussions, regulatory mandates, and potential economic benefits of new energy vehicles (NEVs). Consequently, there has been a substantial surge in the demand for NEVs as alternatives to conventional vehicles. This study analyses the method by which innovative technology moves from the stage of purchase intention dissemination toward market adoption and explores strategies to expedite this process. Moreover, it examines how the intentions of customers to purchase ecologically friendly energy goods and their receptiveness to such products affect the expansion of the market. Further analysis indicates that the factors influencing consumers’ attitudes towards NEVs include the adoption of ecological innovation, awareness of environmental product knowledge, and perceived value of innovative, environmentally friendly energy products. The purpose of this study is to expand upon the existing literature on consumer demand, examining the influential factors that extend the Theory of Planned Behaviour (TPB) to enhance consumer intention through internal mechanisms. It explicitly focuses on these aspects, as well as perceived risk (PR) and perceived value (PV), to identify gaps in the literature and contribute to intentions to purchase NEVs in China. This study presents a thorough research framework for efficiently examining customer demand for comparable eco-friendly energy products. It investigates the potential influence of attitudes, subjective norms, perceived behavioural control, and environmental perceptions, specifically those concerning environmental knowledge and concerns. Moreover, personal factors such as attitude, normative beliefs, and perceived control beliefs were found to impact consumer attitudes towards NEVs. The key factor influencing purchasing intention was the attitude towards NEVs. Simultaneously, subjective norms did not have a direct effect on purchase intentions. However, social influence played a significant role in the decision-making process, with perceived behavioural control and subjective norms exerting considerable influence. Full article

This paper explores how to promote consumer identification and acceptance of green products in the field of sustainable consumption and green marketing. Specifically, this paper examines how green factors affect consumers’ willingness to purchase new energy vehicles (NEVs) and focuses on the mediating role played by perceived price equity in this process. It is found that consumers’ green self-identity, green product experience, and green product innovation have a significant positive impact on their willingness to purchase NEVs, while perceived price fairness plays an important mediating role in this process. When consumers perceive that the pricing of NEVs is fair, they are more inclined to purchase them. Through the analysis of China’s new energy vehicle market, this paper puts forward suggestions to optimize the promotion strategy of green products from the perspective of price fairness, with a view to providing theoretical support and practical guidance for relevant enterprises. As China is the world’s number one country in terms of NEV ownership, studying its market consumption willingness not only reveals the unique characteristics of the Chinese market but also provides lessons and references for the future development of the new energy vehicle market in other countries, which is of great exemplary significance. Full article

Under the current low-carbon background, new energy vehicles are the main force in the new energy industry to reduce traffic pollution. Based on improving energy conservation and environmental protection, and taking consumers’ purchase intention (PI) of new energy vehicles (NEV) as an example, this study explores the influence mechanism of consumers’ green perceived value (GPV) and green perceived risk (GPR) on consumers’ PI of new energy vehicles. This study found that the higher the GPV, the higher the consumers’ willingness to buy NEV. Moreover, the higher the GPR, the lower the consumers’ willingness to buy NEV. Green trust plays an important role in promoting the consumption behavior of NEV. Citizens’ environmental awareness (EA) has a significant moderating effect on customers’ GPV, GPR, GT, and PI. By collecting samples from the world’s largest market, we try to provide meaningful insights for new energy vehicle companies that have entered or plan to enter the Chinese market. Full article

Corporate social responsibility (CSR) is increasingly becoming a major concern for investors and consumers, prompting companies to devote more resources to community engagement to manage conflict and improve business performance. In this study, we conducted an empirical analysis with a sample of 385 listed companies in China’s new energy vehicle (NEV) industry to analyze the relationship between CSR performance and corporate value (CV). With the ordinary least squares (OLS) regression analysis, our study’s results show a positive relationship between the CSR performance of these companies and corporate value. In addition, our findings indicate a lagged effect in the relationship between CSR and CV. The mechanism analysis suggests that corporate CSR performance helps to improve corporate reputation, reduce financing constraints, and thus increase corporate value. Moreover, high analyst attention and information transparency can enhance the positive effects of corporate CSR. This study contributes to the existing literature and empirical evidence by exploring the correlation between CSR performance and firm value in the context of emerging countries and the NEV industry. Full article