Official controls on the distance sale of dairy products in the territory of the Modena Local Competent Authority: an analysis of websites.

The internet and digital technologies pose new, specific challenges to competent authorities, whose activity fields are limited to their own jurisdictions. Consequently, these authorities must operate a system of controls adapted to online sites and e-sales, and official control must be strengthened. To address these challenges and protect consumers from misleading practices that can lead to the consumption of unsafe food, it is necessary to adapt official controls to new distance-selling techniques. The food inspection scheme as conceived in the European legal system cannot be easily applied to online food sales. To this purpose, the competent authorities need to equip themselves to guarantee effective control and compliance with the European Union laws regarding food sold online. It emerged that there are different levels of non-compliance with online food: the non-registration of the food business operator (registrant) and the non-compliance with the obligations as the law prescribes (obligations on food hygiene, electronic commerce, and information to consumers about the food). The focus of this survey on the distance sale of dairy products in the Modena Local Competent Authority territory is on the pattern suggested by the Food Standards Agency in 2016. This analysis is based on two different phases. The first one is the study of the websites, and the second one is the physical visit to the address of the online food business. This survey shows how to collect the first phase's data and organize the official controls.

The effect of new e-commerce platform's OSC promotion on consumer cognition: from cognitive legitimacy and cognitive psychology perspective.

Introduction: In the realm of emerging e-commerce platforms, the influence of online shopping events, specifically online carnival promotions (OSC), on consumer behavior is a significant area of interest.This paper delves into the effects of such promotions on consumer perceptions, a topic that has not been extensively explored in academic research. Methods: To investigate this phenomenon, two distinct studies were conducted. The first study employed a questionnaire-based experiment involving 220 participants, divided into two groups. The first study examined the mediating role of cognitive legitimacy in the relationship between OSC events organized by new e-commerce platforms and the perceptions of consumers. The second study utilized an event-related potentials (ERPs) experiment with 33 participants to explore the differences in consumer perceptions between OSC promotions and general promotions by new e-commerce platforms. This study measured the brain's response to promotional stimuli to gain insights into the cognitive processes involved. Results: The first study yielded results that suggest OSC activities can facilitate the establishment of cognitive legitimacy for new e-commerce platforms. This, in turn, was found to be associated with an increase in positive purchase intentions among consumers. In the second study, the ERPs data indicated that exposure to OSC promotional materials elicited larger P2 and N2 ERP components when participants were presented with the logo of a new e-commerce platform. This was in contrast to the response to general promotional materials, suggesting a heightened cognitive and perceptual engagement with OSC promotions. Discussion: The findings from both studies collectively imply that OSC promotions have a distinct impact on consumer perceptions and cognitive processes. The implicit memory triggered by these promotions appears to influence the identification of new platforms and the mechanisms of cognitive control during online shopping. This, in turn, may have implications for explicit consumer behavior, suggesting that OSC promotions could be a powerful tool for shaping consumer attitudes and behaviors in the e-commerce space. The results underscore the importance of understanding the nuances of consumer engagement with new e-commerce platforms and the role of promotional strategies in fostering a positive brand image and consumer loyalty.

Optimization of cross-border E-commerce (CBEC) supply chain management based on fuzzy logic and auction theory.

People have benefited enormously from e-commerce's explosive expansion in recent years. E-commerce, in contrast to the traditional business environment, is dynamic and complicated, which poses a number of challenges. The prediction market can create mixed intelligence for sales forecasting, which is essential for e-commerce enterprises, to handle this difficulty. Combining the usage of human analysts and machine learning algorithms can accomplish this. To accurately anticipate retailer volume and allot resources, a novel methodology for optimizing supply chain management at CBEC is proposed in this paper. The framework improves efficiency and profitability by using fuzzy logic and auction theory to make strategic decisions. Thanks to this creative strategy, managers can now make more informed decisions, ultimately enhancing the efficiency of CBEC's supply chain. The results of this paper reveal that our proposed method is superior to previous comparable methods, with RMSE and MAE values of 22.31 and 18.76, respectively. This approach offers a promising solution to the challenges faced by e-commerce businesses, and can help them achieve greater success in the dynamic and complex world of online commerce.

How information and communication overload affect consumers' platform switching behavior in social commerce.

In social commerce, users are increasingly resorting to social media platforms to search for information, purchase goods, and share shopping experiences. However, social media use may also affect users' emotions negatively, causing them to switch platforms. Therefore, this study aims to investigate how negative factors (i.e., information and communication overload) affect consumers' platform-switching behavior in social commerce. Drawing on the stimulus-organism-response (SOR) model, this study established a research framework and conducted an online survey in China. A purposive sampling technique was used to collect the data, generating 477 valid responses. Data analysis, based on structural equation modeling, indicates that information and communication overload, and online fatigue positively affect platform-switching intention. The effect of the intention to switch on behavior is moderated by switching costs. Mediation analysis shows that information and communication overload can indirectly influence switching behavior through online fatigue and switching intention. This study incorporates the novel aspects of switching costs in examining the driving forces behind platform-switching in social commerce, thereby theoretically adding value to the existing body of knowledge. Apart from this, our findings also bear significant practical implications and are valuable for social commerce platforms and sellers to improve their user experience and retain existing customers.

Predicting sales and cross-border e-commerce supply chain management using artificial neural networks and the Capuchin search algorithm.

E-commerce provides a large selection of goods for sale and purchase, which promotes regular transactions and commodity flows. Efficient distribution of goods and precise estimation of customer wants are essential for cost reduction. In order to improve supply chain efficiency in the context of cross-border e-commerce, this article combines machine learning approaches with the Internet of Things. The suggested approach consists of two main stages. Order prediction is done in the first step to determine how many orders each merchant is expected to get in the future. In the second phase, allocation operations are conducted and resources required for each retailer are supplied depending on their needs and inventory, taking into account each store's inventory as well as the anticipated sales level. This suggested approach makes use of a weighted mixture of neural networks to anticipate sales orders. The Capuchin Search Algorithm (CapSA) is used in this weighted combination to concurrently enhance the learning and ensemble performance of models. This indicates that an effort is made to reduce the local error of the learning model at the model level via model weight adjustments and neural network configuration. To guarantee more accurate output from the ensemble model, the best weight for each individual component is found at the ensemble model level using the CapSA method. This method yields the ensemble model's final output in the form of weighted averages by choosing suitable weight values. With a Root Mean Squared Error of 2.27, the suggested technique has successfully predicted sales based on the acquired findings, showing a minimum decrease of 2.4 in comparison to the comparing methodologies. Additionally, the suggested method's strong performance is shown by the fact that it was able to minimize the Mean Absolute Percentage Error by 14.67 when compared to other comparison approaches.

The Effects of Live Streamer's Facial Attractiveness and Product Type on Consumer Purchase Intention: An Exploratory Study with Eye Tracking Technology.

As a booming branch of online retailing, live-streaming e-commerce can present abundant information dimensions and diverse forms of expression. Live-streaming e-commerce has enabled online retailers to interact with customers face-to-face, resulting in widespread instances of emotional and impulse buying behavior. Prior research in live-streaming e-commerce has suggested that live streamers' characteristics, especially the live streamer's face, can affect customers' purchase intentions. The present research used questionnaire surveys and an eye tracking experiment to investigate the impact of live streamer's facial attractiveness on consumer purchase intention for search-based and experience-based products. The questionnaire survey analyzed 309 valid questionnaires and revealed that attractive faces are the key influencing factor driving consumers' impulse purchase intentions. Moreover, consumers' emotional experience plays a partial mediating role in the process of live streamers' faces influencing purchase intention. The eye tracking experiment further explored the mechanism of a live streamer's facial attractiveness on consumers' purchase intentions of search-based products and experience-based products from the perspective of visual attention by analyzing 64 valid sets of data. The results showed that attractive faces attract more consumers' attention and, therefore, increase their purchase intention. Furthermore, there is a significant interaction between product type, the live streamer's facial attractiveness, and consumers' purchase intentions. In the case of unattractive live streamers, consumers are more likely to buy search-based products than experience-based products, while the purchase intention does not vary between search-based products and experience-based products in the case of attractive live streamers. The present study provides evidence for 'beauty premium' in live-streaming e-commerce and sheds light on the design of the match between live streamers and different types of products.

Enhancing resilience in transnational E-commerce supply chains: Critical factors, perspectives and strategic action plan.

This study develops a hybrid model to investigate the factors affecting transnational e-commerce supply chain resilience (TNSCRE) by integrating the Entropy Weight Method (EWM), Simple Additive Weighting (SAW), and Interpretive Structural Modeling (ISM). The study identifies 36 critical factors categorized under supply chain adaptability, supply chain efficiency, and supply chain evolution, and five criteria are used to rank these factors. The EWM is used to calculate the relative weights of the criteria, and the SAW method is used to rank the factors based on their weighted scores. The ISM is then used to evaluate the interrelationships among the key factors. The research highlights the significance of several factors, such as the speed of supply chain disruption recovery, interactive collaboration, and response time to supply chain disruption. Sensitivity analysis was performed to assess the robustness of the findings. Finally, a SWOT analysis is conducted to develop a strategic action plan for addressing these significant factors. The study provides a comprehensive understanding of the factors that impact TNSCRE from the perspective of multiple stakeholders. The findings can help e-commerce business owners improve their existing supply chain resilience and achieve sustainable growth in the context of globalization.

How social and media cues induce live streaming impulse buying? SOR model perspective.

Live streaming is revolutionizing the landscape of e-commerce, creating new opportunities for platforms and e-tailers to improve their performance. However, little is known about the underlying mechanisms that shape consumer behavior in this burgeoning business phenomenon. This study aims to shed light on the relationships between environmental cues generated by live streaming and online impulse buying. Drawing upon the Stimulus-Organism-Response framework, a comprehensive model was formulated to explore how social cues (streamer interaction, peer interaction) and media cues (vividness, realness) impact pleasure, arousal, perceived uncertainty, and subsequently induce consumers' urge to buy impulsively. The model was tested by survey data from 403 consumers. SPSS and PLS are employed to verify the model. The findings revealed that realness and streamer interaction can reduce perceived uncertainty and foster a pleasant consumer experience, while vividness and peer interaction serve to awaken and delight consumers. Pleasure, arousal, and perceived uncertainty mediate antecedent variables' effects on urge to buy impulsively in a parallel and reverse way, and emotions exert a more powerful influence. This study enriched the research on the influence mechanisms of impulse buying driven by live streaming and provided suggestions for platforms and streamers to optimize product display and guide interaction, which is conducive to leveraging the advantages of live streaming and creating greater commercial value.

Superior medical resources or geographic proximity? The joint effects of regional medical resource disparity, geographic distance, and cultural differences on online medical consultation.

Online medical consultation platforms enable patients to seek health advice from physicians across geographic regions. In this study, we analyze patterns of online consultation between patients and physicians. We examine the joint effects of regional medical resource disparity, geographic distance, and cultural differences between patients and physicians on patients' decisions about which physicians they consult online. Using a unique dataset of city-to-city tuples based on 813,684 online consultation records and combining it with region-level data from multiple external sources, we find that while regional medical resource disparity drives patients from medically disadvantaged regions to seek online consultations with physicians from medically advantaged regions, geographic distance and cultural differences tend to constrain these consultations. We also find that cultural differences can amplify the impact of regional medical resource disparity, whereas geographic distance may lessen this effect. Further, we discover that the constraining effect of geographic distance is partly due to the online-to-offline nature of online medical consultations. Moreover, additional analyses suggest that physicians' online reputation and information about physicians' participation on the platform can help alleviate the negative effects of geographic distance and cultural differences. These findings hold significant implications for the allocation of medical resources and the formulation of healthcare policies.

Green Consumer Profiling and Online Shopping of Imperfect Foods: Extending UTAUT with Web-Based Label Quality for Misshapen Organic Produce.

Misshapen organic vegetables in the food supply chain can easily be discarded in the market if they do not meet aesthetic standards. E-commerce technology enables the distribution of imperfect organic produce from farmers to potential customers, mitigating agri-food waste issues. Green consumers are prospective customers of imperfect produce because their purchasing decisions are made based on sustainability and environmental considerations. However, each individual's degree of green consumption differs, impacting their preferences and behaviors toward green buying activity. Considering the gap between the varying levels of green consumers and their intention to purchase imperfect organic produce through e-commerce, this study aimed to profile three distinct green consumers and explore factors affecting their Online Green Purchase Intention (OGPI) for imperfect organic vegetables. The Unified Theory of Acceptance and Use of Technology (UTAUT) was applied in this study, and Web-Based Label Quality (WLQ) was introduced as an extended construct to describe green consumers' perceptions of the credibility and reliability of labels or product-related information displayed on e-commerce platforms. This study involved 668 internet users from environmental platforms and online communities of organic food enthusiasts. First, the consumers were classified into dark-green, semi/light green, and non-green using a cluster analysis approach. Then, Structural Equation Modeling (SEM) and Multi-Group Analysis (MGA) were employed to determine the factors affecting OGPI among green consumer groups. This research found that Performance Expectancy (PE), Social Influence (SI), and WLQ positively influenced dark-green consumers' online green purchase intention. Only Performance Expectancy (PE) positively affected semi/light-green consumers' OGPI. Meanwhile, the Facilitating Condition (FC) positively affected non-green consumers' online green purchase intentions. This research revealed dark-green consumers as the target segment, broadening customers' perspectives on accepting imperfect organic products, including e-commerce technology. Moreover, the research results can be utilized for marketing and business purposes and contribute to food policy.

E-commerce recommender system based on improved K-means commodity information management model.

Since the start of the 21st century, there has been a rapid development of internet technology, causing electronic computers and smartphones to become increasingly popular. The e-commerce industry also experiences quick development. However, the recommendation technology of e-commerce progresses slowly, hindering it from keeping up with the changing times. To enhance the efficiency and accuracy of e-commerce recommender systems, this research introduces an e-commerce recommender system that utilizes an enhanced K-means clustering algorithm to manage commodity information. This method combines the K-means algorithm with a genetic algorithm by encoding the genetic algorithm, setting the initial population, defining the fitness function, and configuring other parameters. The results of the test indicated that the K-mean clustering algorithm and fuzzy C-mean algorithm had a recommendation accuracy of 87.9 % and 84.8 % respectively under the test dataset. The highest recommendation accuracy was observed from the improved K-mean clustering algorithm, which was 91.1 %. The convergence rate of the improved K-mean clustering algorithm was faster by 44 % compared to the traditional K-mean clustering algorithm and 73 % quicker than the fuzzy C-mean algorithm. The study's findings demonstrate that the refined K-means clustering algorithm greatly enhances the recommendation proficiency and precision of the e-commerce recommendation system, in comparison to other comparable algorithms. This research can potentially advance the e-commerce industry and stimulate its growth.

Is online shopping addiction still a depressive illness? -- the induced consumption and traffic trap in live E-commerce.

While immersive shopping has injected new vitality into China's e-commerce, it has also resulted in consumers' over-reliance on online shopping. Psychological studies have linked online shopping addiction with depression, but business practices challenge this conclusion. This study, grounded in addiction theory, developed a theoretical model, and conducted an online survey with 214 live-streaming shoppers using structural equation modeling for validation. The primary focus was on determining whether consumers truly become addicted to online shopping in the four stages of the addiction model. The study unveils the process of consumers becoming addicted to online shopping. It explores the moderating role of perceived risk in the relationship between utilitarian and hedonic purchases and online shopping addiction. The findings suggest that through tactics such as traffic promotion, traffic trapping, anchor feature utilization, and incorporation of consumer aesthetics, merchants may induce utilitarian and hedonic purchases, leading to addiction to live-streaming shopping among consumers. Furthermore, perceived risk significantly and negatively moderates the relationship between utilitarian purchases and online shopping addiction. Our research indicates that merchants intentionally create external stimuli, enticing consumers to indulge in online shopping, suggesting that online shopping addiction is not merely a simple psychological state but may be influenced by external factors. This study provides novel insights into the phenomenon of online shopping addiction while offering valuable recommendations for consumers seeking to avoid succumbing to its allure.

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.

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.

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.

Purchasing in the digital age: A meta-analytical perspective on trust, risk, security, and e-WOM in e-commerce.

This comprehensive meta-analysis investigates the significant factors influencing consumer decision-making in e-commerce. Predominantly focusing on the parameters of trust, perceived risk, perceived security, and electronic word-of-mouth (e-WOM), this study provides insightful revelations on their integral roles in shaping e-commerce purchasing decisions. The findings demonstrate that trust, perceived risk, perceived security, and e-WOM significantly influence consumers' e-commerce purchasing decisions. Perceived Risk plays a substantial moderating role in the relationship between Trust and e-commerce purchasing decisions, amplifying the importance of managing and minimizing risk in online transactions to cultivate consumer trust. Contrastingly, the roles of Perceived Security and e-WOM do not hold the same moderating effect on the trust-purchasing decision nexus, underscoring the direct yet unmoderated influence these factors have on e-commerce purchasing behaviors. Furthermore, The research reveals no significant size effect difference among respondents from high-income and low-income countries or between general internet users and online shoppers concerning the impact of trust on e-commerce purchasing decisions. This intriguing finding suggests the universal importance of trust in the digital purchasing landscape, irrespective of socio-economic status or the degree of e-commerce engagement. This study thus sheds new light on the complexities of e-commerce decision-making processes. It offers valuable insights for businesses aiming to enhance consumer trust and engagement in the expanding digital marketplace.

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.

The Impact of Interpersonal Interaction on Purchase Intention in Livestreaming E-Commerce: A Moderated Mediation Model.

Over the last few years, livestreaming e-commerce has shown rapid growth and has become an important form of e-commerce. However, the potential mechanisms of interpersonal interaction's influence on purchase intention in livestreaming e-commerce have yet to be fully investigated. Based on the SOR (Stimulus-Organism-Response) framework, this study reveals the association between interpersonal interaction (consumer-anchor interaction and consumer-consumer interaction), psychological distance, consumer purchase intention, and the positive role of brand identification and time pressure in this context of influential relationships. The results of analyzing 603 questionnaires show that psychological distance between consumers and products plays a mediating role in the effect of interpersonal interaction on purchase intention. Meanwhile, this study found that consumers' brand identification with the products in the live room was effective in enhancing the direct effect of interpersonal interaction in the model. Additionally, the time pressure associated with limited-time sales was also found to be effective in enhancing the effects of interpersonal interaction and psychological distance on purchase intention. The results of this study reveal the potential influence mechanisms of interpersonal interactions with various identities in livestreaming e-commerce, providing theoretical guidance and practical insights for practitioners in the field.

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.

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.