Purchase intentions for cultural heritage products in E-commerce live streaming: An ABC attitude theory analysis.

With the increasing popularity of e-commerce live streaming, understanding purchase intentions for cultural heritage products in this context is crucial, prompting the analysis based on the ABC attitude theory. This study investigates how creative products of intangible cultural heritage influence consumers' purchase intentions within the framework of e-commerce live streaming. It further explores the mediating influence of consumer satisfaction in this association, utilizing the ABC attitude theory. The research design encompasses dimensions related to creative products of intangible cultural heritage, e-customer satisfaction, and purchase intention. Confirmatory factor analysis and Structural Equation Modeling (SEM) are utilized to examine the research hypotheses. The study reveals that perceived product quality, perceived interactivity, and professionalism among streamer factors, as well as perceived entertainment among scene factors, positively influence consumer satisfaction. Additionally, intangible cultural heritage has a positive effect on consumers' purchase intention toward creative products of intangible cultural heritage. Furthermore, consumer satisfaction serves as a mediating factor in the relationship between perceived product quality, perceived professionalism and interactivity, perceived entertainment, and consumers' purchase intention. This study is limited to creative products of intangible cultural heritage and involved a relatively small sample size. Moreover, certain perceptual dimensions of e-commerce live streaming were excluded from the analysis. Originality/value - This study contributes to the existing literature on the ABC theory by developing a model that examines consumer satisfaction and purchase intention. The model employed in this study integrates perceptual dimensions pertaining to creative products of intangible cultural heritage within the framework of e-commerce live streaming, utilizing the ABC theory. Additionally, this research contributes to addressing a gap in the existing literature by specifically focusing on the category of creative products of intangible cultural heritage within the broader discourse on dimensions in e-commerce live streaming. Thus, this study presents numerous diverse perspectives that can serve as a basis for further research into the integration of e-commerce live streaming and cultural and creative products associated with intangible cultural heritage.

Dataset of concerns for privacy information practices and consumer behavior in online market: A survey in Vietnam.

This dataset presents survey results on concerns for consumer privacy information practises in business, online trust; and purchase intention in the online marketplace in Vietnam. The raw data was collected via an online questionnaire of 467 respondents aged 18 and over recruited randomly. The survey included questions on demographic attributes as well as ratings and rankings for various statements related to privacy information concerns, such as Collection, Unauthorized secondary use (internal), Improper Access, Error; consumer online trust; and purchase intention when shopping online. The de-identified dataset is available in CSV format, including the question/statement text, collection method details, and coded response values. This novel dataset further investigates the impact of privacy information concerns on consumer behaviors in an emergent Southeast Asian e-commerce market. As one of the first collections of empirical data focused distinctly on perspectives within Vietnam, this dataset has high reuse potential for research on information privacy attitudes, responses, and needs within the country and in comparison to regional/global trends.

New marketing strategy model of E-commerce enterprises in the era of digital economy.

With the continuous development of technology, traditional marketing methods no longer meet the needs of the main forces of social consumption, and people urgently need more innovative and personalized marketing strategies. E-commerce companies must develop a comprehensive customer-oriented marketing strategy based on big data and multi-channel to achieve their long-term healthy development. This paper first investigated the impact of the digital economy on e-commerce enterprises, focused on the transformation of the digital economy on the marketing model, expounded the development analysis of e-commerce in the digital economy era, and described the development trend of e-commerce marketing in the digital economy era. Then, this paper expounded the current problems faced by e-commerce enterprises, and discussed the lack of integrity, homogeneity, large-scale marketing strategies, and the lack of analysis and application of big data. After that, this paper put forward the marketing strategy of e-commerce enterprises in the digital economy era, and studied it from three aspects, namely, building a reasonable product management structure, marketing strategy based on customized marketing content, and social media marketing strategy based on information sharing. Then this paper proposed to use genetic algorithm to strengthen the marketing strategy of e-commerce enterprises. Finally, based on experiments and surveys, this paper used genetic algorithms to strengthen the construction of e-commerce enterprise marketing strategy in the digital economy, and concluded that the new e-commerce enterprise marketing strategy was 21% more satisfactory than the traditional new e-commerce enterprise marketing strategy. Through comparison, it can see that the integrity of the marketing plan of the new e-commerce enterprise's marketing strategy was 0.33 higher than that of the traditional e-commerce enterprise's marketing strategy, and the integrity of the promotion strategy was 0.34 higher than that of the traditional e-commerce enterprise's marketing strategy. After using the new e-commerce enterprise marketing strategy, the improved management structure was 0.29 higher than that of the traditional monitoring system, and the high quality of products was 0.18 higher than that of the traditional system.

The impact of non-stereotypical gender role endorsement in live broadcasting on consumers' purchase intention.

Introduction: Non-stereotypical gender role endorsement is becoming more common in e-commerce live broadcasting. However, there is relatively little research on this topic, and the mechanism of its impact on purchase intention is not yet clear. Based on schema theory and experimental methods, this study explores the impact of non-stereotypical gender role endorsement (compared to stereotypical gender role endorsement) on purchase intention in e-commerce live broadcasting. Besides, we take traditional gender ideology as the moderating variable. Methods: We first selected experimental materials available for formal experiments through two pre-experiments. Secondly, this study conducted experiments on male/female product groups, respectively. Participants were recruited through the Credamo platform for both experiments. Results: Experiment 1 indicates that for female product, stereotypical gender role endorsement triggers higher consumer purchase intention compared to non-stereotypical gender role endorsement. The subsequent moderating effect test results manifest that traditional gender ideology plays a moderating role in this effect. Experiment 2 shows that for male product, there is no significant difference in the impact of the two types of endorsement on consumers' purchase intention. In other words, non-stereotypical gender role endorsement does affect consumers' purchase intention, but this effect exists only in female product, and is more significant for consumers with a high level of traditional gender ideology. Discussion: This study not only has certain theoretical significance for expanding the application boundaries of schema theory and congruence between celebrities and products endorsed, but also has practical significance for brand owners and streamers to effectively adopt non-stereotypical gender role endorsement to enhance purchase intention.

Impacts of Behavioral, Organizational, and Spatial Factors on the Carbon Footprint of Traditional Retail and E-commerce in the Paris Region.

Carbon footprint assessment of retail is necessary to optimize procurement strategies and adopt sustainable shopping habits. However, estimating carbon footprints is a complex task, given the diversity of existing distribution channels. Average values for carbon emissions of "conventional" retail (i.e., purchasing and receiving the product directly at the physical point of sale) found in most studies mask a heterogeneous reality: different retail strategies entail diverse shopping behavior for consumers, as well as varied procurement processes for outlets. In this paper, we propose a methodology to assess greenhouse gas (GHG) impacts of different distribution systems related to the consumption of goods in the Paris Region by coupling traditional transport modeling with a life-cycle assessment (LCA) approach. We model and compare six distribution systems, including five traditional retail formats (hypermarkets, supermarkets, small generalist retail, small food retail, and small nonfood retail) and E-commerce home deliveries. Our model includes warehouse activity, shop and home delivery, shop energy consumption, consumer mobility, and goods packaging. Overall, we conclude that E-commerce emits fewer GHG emissions than retail outlets per kilogram of product purchased. This result is in line with the existing literature on the topic. However, the carbon footprint varies greatly within the case study depending on the characteristics of the logistics procurement processes of outlets, the behavior of shoppers, and spatial characteristics.

Computer security technology in E-commerce platform business model construction.

The global e-commerce market is expanding rapidly as the big data era advances and the e-commerce industry thrives. This paper aims to discuss the application of computer security technology in constructing an e-commerce platform business model. The research aims to find effective security technology solutions to strengthen the security of e-commerce platforms, protect user information and rights, and enhance the sustainable development of business models. Big Data-assisted E-Commerce Business Model (BD-ECBM) construction is discussed to overcome the e-commerce platform issues and positively impact marketing strategy decision-makers by raising their level of awareness. The business decision-making process is a series of steps that help businesses overcome obstacles by collecting relevant data, analyzing all relevant alternatives, and settling on a course of action. Big data analytics can improve business management with data fusion technology in many ways. The system's framework of the information service layer, the application-level layer, and the client session layer was developed using the Business model paradigm for accounting for e-past, commerce's capabilities of the platform, and an analysis of supply and demand. It can monitor its rivals in near real-time, adjusting prices, offering more attractive deals, and analyzing negative customer comments to see if it can outperform its rivals. The trial results demonstrate the effectiveness of this method of making marketing decisions and formulating a strategy. Hence, the BD-ECBM technique improves customers' overall satisfaction and experience with the brand while raising the latter's profile.

Decoding the trends and the emerging research directions of E-commerce and tourism in the light of Resource Dependence Theory: A bibliometric analysis.

E-commerce and tourism have all seen a lot of growth and development recently in both business and academia. The tourism sector has significantly changed because of the growth of e-commerce platforms, as more and more consumers buy their rooms and tickets online. The academics conducted further research to understand the impact of e-commerce platforms on the tourism industry, leading to the development of these two specific fields' body of literature. A bibliometric review was carried out to draw the trends of the research conducted to date in the field of e-commerce and tourism. Thus, it is possible to have a general overview of the literature for academics to intent to conducting future research. Employing bibliometric analysis with Biblimetrix software on 456 publications from the Web of Science database covering the years from 2000 to 2022, this study identifies predominant themes and research trends in the field. The terms "e-commerce" and "tourism" were used as keywords. During the analysis, six research questions were answered and results were combined with Resource Dependence Theory. Australia and China which are the first two countries in terms of citations. China is the outstanding country for author collaborations. Co-citation network analysis identified four clusters, namely management, model, satisfaction, and quality. Publications with keyword "communication", "enterprises", "application" and "rural" are in a decrease after 2015. Finally, future research directions were proposed.

E-commerce readiness and training needs of small-scale dairy processors in Serbia: Understanding barriers and knowledge gaps.

The objective of this study was to identify the requirements needed for selling dairy products through e-commerce, as well as current gaps and challenges that exist for small scale dairy processors (SSDPs), and need to be addressed in order to comply with those requirements. A mixed method research design was used for training needs assessment. Qualitative (in-depth interview with 7 online platform representatives (OPRs)) and quantitative approach (survey questionnaire with 58 SSDPs) were conducted. Interview transcripts were coded and codes were grouped into seven themes. Hierarchical cluster analysis was applied to 146 answers from 58 SSDPs. They were divided into 4 clusters. Mean sums of responses between clusters were compared by Mann-Whitney U test. OPRs suggested that SSDPs should be provided with tools and resources to help them achieve food safety and quality targets, as well as practical knowledge and skills. They reported that it is crucial to find a solution for the cold chain transportation, for maintaining consistent product quality. Survey results showed that SSDPs use kitchen equipment (79.3%) and kitchen cleaning products (81.0%) for dairy processing. In total, 43.1% process raw milk and only 24.1% have product label on the package. Only members of cluster 3 and 4 sell their products online (73.7% and 90.0%, respectively), mostly using their own social media platforms (57.9% and 60.0%, respectively), transporting products to end buyers by themselves in hand refrigerators (47.4% and 70.0%, respectively). By analyzing the differences among clusters of SSDPs, trainings can be tailored to the characteristics and knowledge gaps of each group.

Research on Determinants Affecting Users' Impulsive Purchase Intention in Live Streaming from the Perspective of Perceived Live Streamers' Ability.

As an innovative marketing pattern, live-streaming e-commerce supplies advantages over traditional e-commerce in stimulating impulsive purchases. This study developed a theoretical model that examines how perceived live streamers' abilities (perceived live interaction ability and perceived linguistic persuasion ability) affect impulsive purchase intention based on interaction theory, affective distance theory, trust theory, and Aristotle's rhetorical appeals. We conducted empirical research through a survey questionnaire to verify the effectiveness of the model. A total of 330 valid samples were gathered from live-streaming users, and partial least squares-structural equation modeling (PLS-SEM) was employed for data analysis. The results indicate that perceived live interaction ability, encompassing responsiveness, entertainment, and personalization, significantly impacts affective distance. Among the four dimensions of perceived linguistic persuasion ability, emotional contagion significantly influences affective distance, whereas expertise, logic, and morality significantly affect cognitive trust. Both affective distance and cognitive trust promote consumers' impulsive purchases through affective trust. Our research findings provide theoretical and practical recommendations for live-streaming platforms and merchants engaged in live marketing.

Enhancing environmental sustainability in transferred farmlands through rural e-commerce: insights from China.

The issue of farmers neglecting environmental concerns in transferred farmlands poses a serious challenge, contradicting the long-term ecological goals of establishing resource-efficient and environment-friendly agriculture. Amidst the pivotal trend of moderately scaled agricultural operations, rural e-commerce holds promise as a catalyst and driving force for enhancing long-term environmental governance of transferred lands. The effectiveness and mechanisms of this potential, however, remain to be empirically examined. This study gathers panel data on environmental positive and negative externalities from six provinces in China, spanning the period from 2013 to 2022, encompassing 6372 farmers. A quasi-natural experiment of farmers' e-commerce participation is designed using difference-in-differences methodology (DID), propensity score matching (PSM), and moderating models. The primary findings are as follows: E-commerce participation increases farmers' positive environmental inputs on transferred lands, such as water-saving irrigation, adoption of social services, and preservation of traditional varieties. Simultaneously, it decreases negative environmental inputs, such as the consumption of fertilizers, pesticides, and agricultural films. The environmental sustainability effects of e-commerce vary across the eastern, central, and western regions of China. E-commerce has a more pronounced impact on agricultural social services and chemical pollutants in the eastern and central regions, while its influence is more significant on water-saving irrigation and variety preservation in the western region. Land transfer forms and supply order contracts do not directly promote farmers' environmentally friendly cultivation practices. Instead, they catalyze the environmental effects of e-commerce through a significant positive interaction term. These conclusions hold after matching for e-commerce participation propensity, while passing sensitivity tests, parallel trend tests, and placebo tests. Consequently, rural e-commerce, without compromising farmers' income, enhances the proactiveness of farmers in environmental conservation, transforms agricultural management practices, and effectively reduces rural non-point source pollution. Policy recommendations include reducing institutional barriers to rural e-commerce participation at the national level, encouraging the establishment of region-specific agricultural environmental sustainability goals, and leveraging the rural e-commerce industry chain to establish a nationwide environmental credit database and incentive mechanism.

Multi-angle perception and convolutional neural network for service quality evaluation of cross-border e-commerce logistics enterprise.

The development of cross-border e-commerce logistics services has injected new vitality into the development of international trade, and therefore has become a new hot spot in theoretical research. In order to ensure the healthy development of cross-border e-commerce, it is urgent to build a set of scientific and effective evaluation mechanisms to scientifically evaluate the logistics service quality of cross-border e-commerce. Multi-angle perceptual convolutional neural network is a framework for service scene identification of cross-border e-commerce logistics enterprises based on deep convolutional neural network and multi-angle perceptual width learning. In this article, both shallow features and deep features were input into the deep perception model (DPM) to obtain a set of distinguishable features with causal structure, which was used to completely describe the high-level semantic information of cross-border e-commerce logistics enterprise services. Among them, DPM mainly adopts the fusion strategy of shallow feature and deep feature. Meanwhile, the feature representation is input into the width learning pattern recognition system for training and classification, so as to evaluate the service quality of cross-border e-commerce logistics enterprises. The multi-angle perceptual convolutional neural network can effectively solve the problems of high similarity between service classes of cross-border e-commerce logistics enterprises and large differences within the class, and achieve better generalization performance and algorithm complexity than support vector machine, random forest and convolutional neural network.

Time-aware forecasting of search volume categories and actual purchase.

The new e-commerce field has attracted businesses of all sizes, retailers, and individuals. Consequently, there is an ongoing necessity for applications that can offer predictions on trending products and optimal selling time. This research suggests aiding businesses in forecasting demand for various product categories by employing data mining algorithms on multivariate time series data. To ensure the most recent information, real-time data was gathered through APIs to build the first block in this research. While search volume was derived from the Keywords Everywhere tool, Amazon's search volume was derived from the Helium 10 tool and external features about actual purchased data. The harvested raw datasets went through multiple processes to generate the dataset and were validated. The models XGBoost, Linear Regression, Random Forest, long-short-term memory, and K-nearest neighbor were employed to predict the trends, and the performance is demonstrated using evaluation metrics, namely Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R2). Overall, Linear Regression outperformed, especially at a correlation coefficient of 0.9, with R2 = 90.688, MAE = 0.038, MSE = 0.003, and RMSE = 0.057. KNN outperformed on correlation coefficient of 0.7, R2 = 85.129, MAE = 0.045, MSE = 0.005, and RMSE = 0.068. XGBoost produced the best results with a correlation coefficient of 0.9, yielding R2 = 85.89, MAE = 0.042, MSE = 0.004, and RMSE = 0.062. Random Forest, on the other hand, achieves peak metrics with a correlation coefficient of 0.6, R2 = 84.854, MAE = 0.041, MSE = 0.004, and RMSE = 0.066.

Investigating the acceptance intentions of online shopping assistants in E-commerce interactions: Mediating role of trust and effects of consumer demographics.

Online shopping has various advantages, such as convenience, easy access to information, a greater variety of products or services, discounts, and lower prices. However, the absence of salespeople's personalized assistance decreases the online customer experience. Business-to-consumer e-commerce companies are increasingly implementing online shopping assistants (OSAs), interactive and automated tools used to assist customers without salespeople's assistance. However, no comprehensive model of OSA acceptance in e-commerce exists, including constructs from multiple information system disciplines, sociopsychology, and information security. This study aims to fill these gaps by empirically investigating consumers' intention to accept OSAs from a functional, social, relational, and security perspective. It identifies OSA acceptance factors in e-commerce through an extensive literature review and expert opinion. A research model is proposed after identifying structural relationships among the study's variables from the literature. The study employs partial least squares-structural equation modeling (PLS-SEM) to validate the proposed model empirically. The results indicate that anthropomorphism, attitude, ease of use, enjoyment, privacy, trust, and usefulness are crucial determinants of acceptance variables. There are significant moderating effects of respondents' gender and education on OSA acceptance. The study's results have substantial implications for academia, extending and validating the Technology Acceptance Model (TAM) for OSA acceptance in e-commerce. The study will help e-commerce marketers develop optimal adoption strategies when implementing OSAs on social media platforms.

Multistage Supply Chain Channel Principal-Agent Model in the Context of e-Commerce With Fairness Preference.

This research aims to investigate information asymmetry in e-commerce supply chain channels and the impact of the fair preference model on the behavior and returns of channel members. Therefore, by contrasting it with the model in the completely rational case, this research establishes a more realistic principal-agent model and incorporates the fair preference model into the e-commerce supply chain channel. According to the model's analysis, the effort level of the retailer at each stage is positively correlated with the e-commerce efficiency coefficient, and the incentive coefficient of manufacturers is positively correlated with the e-commerce efficiency coefficient in the case where all rationality is assumed. Manufacturing companies' anticipated profits are positively correlated with the e-commerce efficiency coefficient. According to the fair preference model, retailers will put forth more effort to sell products when their fixed income from manufacturers is higher and their optimal effort level is positively correlated with that income. When e-commerce's efficiency coefficient is higher than 1, the retailer's revenue and effort exceeded those of traditional channels. Manufacturers and retailers both experience Pareto improvements in their earnings after the fair preference model is introduced.

Sales to Apparently Intoxicated Customers in Three States with Different Histories of Responsible Beverage Service Training.

OBJECTIVE: Most states prohibit sales of alcohol to customers who are apparently intoxicated and many require training in responsible beverage service (RBS), with the aim of reducing driving while intoxicated (DWI) and other harms. Sales to apparently intoxicated patrons were assessed in on-site alcohol sales establishments and compared across three states. METHODS: A sample of 180 licensed on-site alcohol establishments was selected in California (n=60), New Mexico (n=60), and Washington state (n=60). States had different RBS training histories, content, and procedures. Research confederates, trained to feign cues of intoxication, visited each establishment twice. The pseudo-intoxicated patron (PP) ordered an alcoholic beverage while displaying intoxication cues. Sale of alcohol was the primary outcome. RESULTS: At 179 establishments assessed, PPs were served alcohol during 56.5% of 356 visits (35.6% of establishments served and 22.6% did not serve at both visits). Alcohol sales were less frequent in New Mexico (47.9% of visits; odds ratio [OR]=0.374, p=0.008) and Washington state (49.6%; OR=0.387, p=0.012) than in California (72.0%). Servers less consistently refused service at both visits (6.8%) in California than New Mexico (33.9%) or Washington (27.1%) (χ2(4, N=177)=16.72, p=0.002). Alcohol sales were higher when intoxication cues were less obvious (p<0.001). CONCLUSIONS: Over-service of alcohol to apparently intoxicated customers was frequent and likely elevated risk of DWI and other harms. The lower sales in New Mexico and Washington than California may show that a policy approach prohibiting sales to intoxicated customers combined with well-established RBS training can reduce over-service. Further efforts are needed to reduce over-service.

"In the Metaverse We (Mis)trust?" Third-Level Digital (In)equality, Social Phobia, Neo-Luddism, and Blockchain/Cryptocurrency Transparency in the Artificial Intelligence-Powered Metaverse.

The Metaverse, powered by a variety of key innovative technologies including 3D virtual reality (VR)/augmented reality (AR), artificial intelligence (AI), blockchain/cryptocurrency-based non-fungible tokens (NFTs), and the Internet of Things, has been proposed as the future of a virtual universe for education, work, business, and commerce. This research (∑ N = 954) presents the results of three cross-sectional surveys that examine the influence of third-level digital (in)equality and consumer (mis)trust on Metaverse adoption intention. Study 1, focusing on the Metaverse for hybrid education, reports the mediating effect of (mis)trust in the Metaverse on the relationship between the educational dimension of third-level digital (in)equality and behavioral intention to adopt the Metaverse for virtual learning as well as the moderating effect of social phobia. Study 2, focusing on the Metaverse for remote working, reports the mediating effect of (mis)trust in the Metaverse on the relationship between the economic labor dimension of third-level digital (in)equality and Metaverse adoption for virtual working as well as the moderating effect of neo-Luddism. Study 3, focusing on the Metaverse for business, reports the mediating effect of (mis)trust in the Metaverse on the relationship between the economic commerce dimension of third-level digital (in)equality and Metaverse adoption for virtual commerce as well as the moderating effect of blockchain/cryptocurrency transparency perception. This research can provide theoretical frameworks to examine people's hopes and fears about the Metaverse and consequential adoption versus non-adoption of the Metaverse for hybrid education, hybrid remote working, and omni-channel virtual commerce. Practical, managerial, and policy implications for the Metaverse and the NFT market are also discussed.

Understanding Trust Drivers of S-commerce.

Trust has emerged as a pillar in the acceptance and use of new technologies in the ever-changing digital landscape, notably in the booming field of social commerce. The importance of this study lies in the fact that it explores in-depth the aspects of customer trust in Instashopping using new constructs that have yet to be explored in s-commerce literature. Focusing on Instashopping, the research proposed a multi-dimensional model of trust to examine the dynamics of user trust in social commerce platforms and analyses the effects of various factors, including institution-based trust, disposition to trust, personal inventiveness, perceived page quality, and overall web experience. Structural equation modelling and confirmatory factor analysis were used to examine data from 267 responses in a survey of university students in the United Arab Emirates who have used Instagram for shopping. The analysis showed that user trust and trusting beliefs were significantly influenced by the disposition to trust, institution-based trust, and general web experience. Still, no significant association was found between perceived site quality and trusting beliefs. These findings highlight the crucial part that user trust plays in social commerce platform success and how important it is for online platforms to build and maintain user trust. The work also contributes theoretically to the knowledge body by comprehensively analysing trust dynamics in social commerce. In practice, the knowledge gained can help organisations plan their strategy for gaining and keeping client trust, which is essential for long-term success in the digital arena. To ensure long-term success, organisations must emphasise building and maintaining customer trust.

Is the commercial determinants conversation confined to the health sciences? Potentially, and that's a problem.

The commercial determinants of health (CDoH) are attracting increased interest and are of great importance when discussing how trade affects health. Through a citation analysis of recent foundational CDoH documents (a Lancet paper series and an Oxford University textbook), we find that fully 71% of all citations reference the health sciences. The health sciences may be well suited to documenting the specific pathways of how commercial (by)products and practices harm human health. However, to operationalize upstream solutions for mitigating these harms, our citation analysis suggests that the field can engage political scientists, economists, sociologists, the trade law and business, as well as advocates in civil society and journalism, more so than it currently does. With CDoH explicitly referring to the interaction between commerce and health, CDoH researchers might be uniquely positioned to get health on the agenda of others, which requires that CDoH methods, datasets, evidence reviews, and proposed interventions are drawn from the widest possible range of sources.

Cultivated alien plants with high invasion potential are more likely to be traded online in China.

Biological invasions have become a worldwide problem, and measures to efficiently prevent and control invasions are still in development. Like many other parts of the world, China is undergoing a dramatic increase in plant invasions. Most of the currently 933 established (i.e., naturalized) plant species, of which 214 are categorized as invasive, have been introduced into China for cultivation. It is likely that many of those species are still being traded, particularly online, by plant nurseries. However, studies assessing whether naturalized and invasive species are currently being traded more or less than nonnaturalized aliens are rare. We extracted online-trade information for 13,718 cultivated alien plant taxa on 1688.com, the largest website for domestic B2B in China. We analyzed how the presence in online-nursery catalogs, the number of online nurseries that offerred the species for sale, and the product type (i.e., seeds, live plants and vegetative organs) differed among nonnaturalized, naturalized noninvasive, and invasive species. Compared to nonnaturalized taxa, naturalized noninvasive and invasive taxa were 3.7-5.2 times more likely to be available for purchase. Naturalized noninvasive and invasive taxa were more frequently offered as seeds by online nurseries, whereas nonnaturalized taxa were more frequently offered as live plants. Based on these findings, we propose that, to reduce the further spread of invasive and potentially invasive plants, implementation of plant-trade regulations and a monitoring system of the online horticultural supply chain will be essential.

Toward a low carbon path: Do E-commerce reduce CO2 emissions? Evidence from China.

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality.