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A new model for two-sided platforms is presented, incorporating both the original business and an expanded (new) business. Previous studies have neglected the impact of technology R & D on the new business aspect of two-sided platforms. This study addresses this gap by examining the technology R & D effect on the new business while also considering the congestion effect on the original business. It investigates the optimal pricing and user scales for both the original and new businesses. Additionally, the profits of the original business, the new business, and the overall two-sided platform are analyzed.

Previous studies have overlooked the technology R & D effect on the new business aspect of two-sided platforms. Therefore, this study focuses on examining the technology R & D effect on the new business. Additionally, the congestion effect on the original business is considered. To determine the optimal prices for both sides of the original and new businesses, a game sequence model is introduced.

The optimal price on the service buyers (defined b side) of new business increases only with regard to technology R & D effect on b side of new business increasing. The optimal price on b side of new business is equal to half of the b-side R & D effect. The optimal profit of original business decreases with regard to the technology R & D effect of new business and cross-market network effect on the services provider (defined s side) between original business and new business increasing, respectively. To gain optimal profit of two-sided platform, the two-sided platform adopts some strategies to improve the congestion.

A new two-sided platform model is stated, in which the technology R & D effect is embraced. The expanded business scenario of two-sided platform is considered, that is, the two-sided platform has one business firstly and a new business is developed or improved of two-sided platform. To solve the prices strategy of original business and new business, a game sequence of the original business and new business is presented.

The research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the framework of the carbon peaking and carbon neutrality (dual carbon) goals, while also identifying the driving factors through an exponential decomposition of ACTFP, aiming to provide policy recommendations to enhance financial support for low-carbon agricultural development.

In this paper, the Global Malmquist Luenberger (GML) Index method was employed to analyze and decompose the ACTFP, while the direct and spillover effects of China’s green finance pilot policy (GFPP) on ACTFP were assessed using the difference-in-differences (DID) method and the spatial differences-in-differences (SDID) method, respectively.

After the implementation of the GFPP, the ACTFP in the pilot area has experienced significant improvement, with the enhancement of technical efficiency serving as the main driving force. In addition, the GFPP exhibits a positive low-carbon spatial spillover effect, indicating it benefits ACTFP in both the pilot and adjacent areas.

Within the framework of the dual carbon goals, the paper highlights agriculture as a significant carbon emitter. ACTFP is assessed by considering the agricultural carbon emission factor as the sole non-desired output, and the impact of the GFPP on ACTFP is investigated through the DID method, thereby providing substantial validation of the hypotheses inferred from the mathematical model. Subsequently, the spillover effects of GFPP on ACTFP are analyzed in conjunction with the spatial econometric model.

The purpose of this paper is to explore China’s online wine market segmentation on the basis of the wine-related lifestyle (WRL). Moreover, this study can provide further understanding and reference about China’s wine market segmentation research, which is limited at present. This work can be helpful for those who want to do further research in the Chinese wine market. It is good for wine importers wanting to import wine to China to understand the Chinese wine consumers.

Survey data were obtained from a sample of 3,369 participants through cooperation between the College of Enology and the Yesmywine.com website. Questionnaire items included gender, age, area distribution, unit price, bottles consumed, drinking frequency, drinking time, wine-related knowledge, etc. Combined with the influence factors of the WRL, a structural equation model was developed. The data analysis, particularly employing principal component analysis, enabled the identification of five market segments.

Five distinct segments were identified within the wine market and designated as follows: wine official consumption type enthusiastic fancier; enjoyment consumption; fashionable consumption; and new, young wine drinkers.

The research data were derived from Yesmywine, one of the largest online wine sale platforms. However, the impact of yesmywine is much smaller compared with Tmall and Taobao and Jingdong. In this paper, we can see that WRL is increasingly becoming a part of Chinese people’s daily lives, especially for the enthusiastic and fancier wine consumers, which is the official type of wine consumer. Next, an analysis of time series under the data of the near future years should be conducted to find the online wine segmentation market variation trend. Moreover, it is important to conduct cross-culture comparison between the Chinese and Australians. Brand positioning can be improved by better understanding China’s online wine market segmentation.

WRL segmentation is valuable for the wine importers and producers in west France, Italian, Germany and so on, as they want to develop China’s wine market and understand the mindset of Chinese wine consumers. The wine importers in China should focus more on consumers that enjoy wine along with newer and younger wine drinkers.

This paper analyzes a large sample (3,369) and therefore is useful for understanding online wine market segmentation and wine consumption behavior in China owing to China’s limited wine market segmentation literature. This paper is the first to use WRL tool to segment China’s online wine market. Moreover, the research data have reference value for those who want to learn more about China’s online wine market, as yesmywine is one of the largest online wine-sale platforms. It also gives some managerial implications for wineries and wine marketers that will be helpful to wine companies in understanding the emerging Chinese wine market and in enacting wine marketing strategies more effectively.