The Application of Personalized Recommendation Algorithms in TikTok E-commerce: Advantages, Risks, and Development Trends

The digital age, e-commerce platforms can accurately capture users' consumption habits, browsing history, geographic location, and other personal information through big data, artificial intelligence and other technical means, thereby providing users with a personalized shopping experience. However, behind this convenience, there are also huge privacy risks. Once a user's personal information is improperly used or leaked, it will not only lead to the infringement of personal privacy rights but may also lead to serious consequences such as identity theft and financial fraud, causing huge economic losses and psychological pressure on users. This paper deeply explores the current status of user privacy protection on e-commerce platforms and the main problems it faces and proposes multi-dimensional solutions, including improving laws and regulations, strengthening technical means, enhancing user privacy protection awareness, and optimizing rights protection channels. Only through the multi-party collaboration and continuous improvement of e-commerce platforms, users, and regulatory agencies can a solid privacy protection system be built to effectively deal with the risk of privacy leakage and promote the healthy development of the e-commerce industry.

As the online retail market expands and brand competition intensifies, e-commerce platforms and retailers are facing increasing service and operational costs. The emergence of artificial intelligence (AI) technology has transformed the consumer shopping experience while simultaneously reducing retailers' operational costs. However, platforms must judiciously balance the operational efficiency improvements enabled by AI technology with the potential risks stemming from intensified competition and rising technology adoption costs. This study constructs a two-stage supply chain model involving a retailer and a platform, who are selling national brand products and substitutable private label brand, respectively. The platform strategically adopts and shares AI technology with retailer to optimise sales performance. We systematically analyze the viability of AI adoption and its impact on brand competition. The findings suggest that under moderate cost conditions, the platform's AI adoption may result in a lose–lose situation for both firms. When AI R&D costs are low, sharing AI technology, despite potentially weakening the platform's private-label competitiveness and reducing overall market demand, can still lead to a win-win situation for both parties. Additionally, extended analysis indicates that changes in consumer preferences have a limited effect on AI investment decisions, although different AI applications may introduce more complex supply chain dynamics.

The fundamental provisions of the Food Security Doctrine to ensure physical availability of food to the population are implemented through the development of various forms of retail. The general tendencies in economic development, digitalization, changes in consumer preferences, external factors affect the forms of retail in the forms of food retail in accordance with general trends in economic development, and the possibility of purchasing food products by different groups of the population depending on consumer habits regarding purchasing methods. As a result of retrospective and structural analysis of statistical data and aggregation of public opinion survey results, a shift in consumer preferences was revealed, expressed in a significant decrease in the share of market and fair trade. It should be noted the growth of retail chains and online food trading. Penetration of digitalization processes into the agricultural sector, including cooperation of agricultural producers through agro-aggregators. Despite the change in consumer habits, there remains a significant portion of the population that prefers traditional ways of purchasing goods in markets and fairs. In order to ensure physical availability of food for all groups of the population, support for market and fair trade, mobile commercial outlets continues despite their small share in the turnover. The Kaliningrad region is characterized by cooperation of local producers, the increase in the share of online trading in food products at a higher rate than the Russian average. In general, it can be concluded that the development of retail in the Kaliningrad region is in accordance with all-Russian trends with the features due to the exclave position of the region and limited market capacity.

The rapid development of artificial intelligence (AI) has brought tremendous changes to various industries, ecommerce and education are two of the most affected sectors. In this paper, we tackle the task of deploying AI agents as bespoke assistants for revolutionizing digital product marketing in educational e-commerce markets. These AI agents use sophisticated machine learning, deep natural language processing and user behavior analytics to deliver hyper-personalized marketing experiences to students, faculty and administrative staff. We provide a detailed design of an AI agent architecture with user profiling, recommendation system, conversational interface, and RT AM modules. It also digs deeper into how this AI-personal assistant will drive higher levels of user engagement and conversion and will optimize marketing effectiveness, as it addresses the weighty questions of data privacy, bias and how to use AI ethically. Finally, future trends are discussed including the use of immersive technology and explainable AI to evolve educational and ecommerce marketing strategies.

The purpose of this study is to integrate the method of chance discovery with visualization tools (KeyGraph) for presenting important and latent research topics in the e-commerce (EC) field. This study collects keywords and abstracts from 995 articles in four primary EC journals. To establish the professional terms of EC, this work divides EC development into three periods: the development of the Internet, the growth of information technology, and the extension of commerce applications. For exploring significant and latent EC topics, this study analyzes the differences and similarities between international and Taiwanese sources. Pursuing this approach yields three findings. First, this paper determines that the KeyGraph as a computing process and a visualization tool is an effective method for exploring future research topics. Second, international EC topics have different thematic characteristics at different phases and they are more diverse and extensive than Taiwanese sources. Third, a professional thesaurus is very helpful in identifying EC research topics. All these findings suggest Taiwanese scholars should pay more attention to research issues from international journals when studying EC.

The integration of artificial intelligence (AI) into media production workflows has revolutionized the industry, addressing traditional challenges and driving unprecedented efficiencies. This paper explores AI's transformative role in streamlining post-production, editing, and distribution processes. In post-production, AI technologies such as machine learning and computer vision automate complex tasks like video stitching, color grading, and sound design, reducing costs and timelines while enhancing creativity. In editing, intelligent systems enable precise scene detection, facial recognition, and subtitle generation, improving accessibility and minimizing manual intervention. The paper also examines how automation optimizes media distribution through personalized recommendation algorithms, automated metadata generation, and adaptive streaming, ensuring a seamless audience experience. While the benefits of AI are undeniable, the paper emphasizes the importance of ethical integration, advocating for transparency, data privacy, and the augmentation of human creativity. By responsibly leveraging AI, the media industry can continue to innovate while maintaining its commitment to inclusivity and artistic integrity.

The integration of Artificial Intelligence (AI) in e-commerce platforms has significantly revolutionized how businesses optimize product performance and customer experiences. One of the most impactful applications of AI is in A/B testing, a method used to compare two versions of a webpage or product feature to determine which one performs better. AI-enabled A/B testing enhances this process by automating the experimentation, analyzing vast amounts of data in real-time, and providing actionable insights faster and more accurately than traditional methods. This review explores the impact of AI-enabled A/B testing on product performance in e-commerce platforms. AI-driven A/B testing algorithms can dynamically adapt tests based on user behavior, allowing for more personalized and effective product offerings. This leads to an increase in conversion rates, customer satisfaction, and ultimately, revenue. Furthermore, AI enables the testing of multiple variables simultaneously, which reduces the time required to identify optimal configurations and strategies. By leveraging machine learning models, e-commerce platforms can predict outcomes more accurately, ensuring that product changes are more likely to result in positive performance metrics. The review also discusses the challenges associated with implementing AI-enabled A/B testing, such as the need for large datasets, the risk of overfitting models to specific data segments, and the potential for bias in AI algorithms. Additionally, it highlights the importance of human oversight in interpreting AI-generated results to avoid misalignment with broader business goals. In conclusion, AI-enabled A/B testing represents a powerful tool for enhancing product performance in e-commerce platforms. It offers the ability to optimize user experiences in real-time, leading to more effective product strategies and higher customer engagement. As AI technology continues to advance, its role in A/B testing will likely expand, offering even greater opportunities for innovation in the e-commerce industry.. Keywords: Artificial Intelligence, A/B Testing, E-commerce, Product Performance, Conversion Rates, Machine Learning, Customer Engagement.

With the development of the Internet, science, and technology, the Internet has penetrated all aspects of the national economy. The amazing sales of "Double Eleven" in 2012 tell the world that in the era of e-commerce, every day is a shopping carnival. E-commerce giants rely on e-commerce platforms to launch an impact on banks, banks in the opposite direction but also started e-commerce. Research methods Single case study method was used. Taking the e-commerce platforms Shanrong Commerce and Global E-Trade Service built by China Construction Bank and Industrial and Commercial Bank of China as examples, this paper analyzes the marketing strategies of their e-commerce platforms, online and offline user transformation, customer relationship platform construction, and other marketing links. And evaluate its marketing model, and analyze its advantages and disadvantages. Through the case analysis of Shanrong commerce and Global E-Trade Service, the paper gives suggestions on the network marketing mode of the bank e-commerce platform, which has certain reference significance for the current bank e-commerce network marketing.

The COVID outbreak caused governments worldwide to put social distancing regulations, ban physical contact, and close physical enterprises, which changed how multitudinous businesses operated. Due to the epidemic, businesses were impelled to modify their business plans by incorporating the current electronic system of operation, or electronic commerce. Electronic commerce, ore- commerce, enhanced businesses' external connections with their stakeholders. multitudinous businesses stopped operating their physical stores and started up, or bolstered, their online presence by moving toper- existing- commerce platforms (Chengeta, 2022). The United Nations Conference on Trade and Development (UNCTAD) 2021 report states that, in distinction to 2018, there was an unexpected 4 rise in global- commerce in 2020. demonstrating the significant increase in e- commerce, which includes business- to- business (B2B) and business- to- consumer (B2C) deals, and the growing significance of online exertion (UNCTAD, 2021). Indeed, while demand shifted from physical stores to online retailers, certain- commerce companies outperformed others in terms of digital addition. predicated on gross wares value (GMV), e-commerce companies like Alibaba, Amazon, JD.com, and Pendulous ranked as the top four B2Ce- commerce enterprises in 2020 (UNCTAD, 2021). Businesses with significant drops in their 2020 GMV compared to 2019 were Expedia, Booking goods, and Airbnb (UNCTAD, 2021). Because of their proficiency with Artificial Intelligence (AI), the top- ranked e- commerce companies demonstrated strong performance in digital addition (Micallef and Gupta, 2021). Thanks to large data, artificial intelligence (AI) has come a technical priority. for multitudinous online retailers in recent times (Davenport Tal, 2018). The use of AI has increased by over 300 in the last numerous times and has the implicit to be profitable for businesses. exploration and examination of the use of AI one- commerce platforms are long overdue. To increase the perceived demands of guests being satisfied, the commerce effectiveness of AI operations one- commerce platforms is a vital concern. E-commerce platforms produce a competitive edge by virtue of their distinct and delicate to replicate characteristics, as demonstrated by the IS literature (Schreyer, 2012). Former studies on AI operations emphasize that to give AI capacity value, organizational and mortal resources are demanded the factory of Ramsbotham teal. ultimate of the disquisition on AI operations in e- commerce has concentrated on handover and operation oddities (Khari, 2020). Consumer- AI operation commerce effectiveness has entered lower attention, and as a result, the benefits of AI operation Ine- commerce have not been fully appreciated. The operation's end stoners, or consumers, anticipate a positive hassle with slice- edge technical apps one- commerce platforms. To close this gap, the current study examines the unique advanced technologies and platform structures one- commerce platforms as AI capabilities that elicit favourable sentiments about consumer participation. It does this by erecting on earlier disquisition from the viewpoint of the consumers (Howard and Roswell- Jones, 2019). This study specifically assesses chatbots, image quest, recommendation machines, and post- purchase backing as AI factors in an online store, and how well they communicate with guests to draw in favourable observed(behavioural) and unobserved(cerebral) engagement stations. Using the instigations- organism- response (S- O- R) model, this study investigates how consumers' behavioural engagement stations(R) are sparked by AI rudiments(S) in response to their cerebral engagement(O) and attention to social comparison (Congeal, 2019). When a consumer interacts with the AI features on and- commerce platform, they witness a happy, fulfilling state of mind known as cerebral engagement. This state is characterized by devotion, absorption, and vitality. The response, which was behavioural the term" engagement" describes the ongoing, visible relations that stoners have with thee- commerce platform because of their positive perceptions of the platform and their relations with the AI rudiments that are there (Luetta., 2019). Literature on AI operations and IT capabilities in information system disquisition is consulted in this study. Also, by using the scale, we created a check instrument to measure guests' satisfaction with AI capabilities and their stations about consumer engagement. development morals set up in the literature on operation information systems (Mackenzie Tal., 2011). This is how the rest of the composition is structured. The literature on the S- OR model, customer involvement, and the history of thee- commerce platforms used for the study is curtly introduced in the following section. Next, the study's abstract frame, hypotheticals, and explanations for the AI constructs are established. The process is also described, and initially, the analysis's outgrowth and interpretation. In conclusion, we go over the results and point out the implications, constraints, and future disquisition directions of the work.

In the era of network, B2B electronic commerce (EC) has become new bright spot and trend of future business development gradually. B2B EC has huge development potential in China. But there is lack of research on coordinate control among enterprises of B2B EC. That is disadvantage to the running of B2B EC smoothly in china. Therefore, the paper analyses B2B EC types and coordinate control influencing factors among enterprises of B2B EC. Then the paper constructs research model about identification on coordinate control influencing factors among enterprises of B2B EC, and shows how to use this research model by a calculative example. That provides gist for the coordinate control among enterprises of B2B EC.

Generation Z, digitally proficient and progressive in their stance on social and environmental issues (Gomes et al., 2023), are emerging as influential consumers. In the Philippines, 77.2 % of them made online purchases (Kemp, 2021), spending an average of 246 US dollars annually (PCMI, 2024). Notably, 7 in 10 online shoppers fall within the 18 to 24 demographic (Pan, 2023). Despite their awareness, studies reveal an attitude–behavior gap, where Gen Zs’ concern for the environment does not consistently reflect in their purchasing choices (Islam et al., 2023). Fashion items are the most purchased products by Filipino Gen Z on e-commerce platforms, contributing to 92 million tonnes of textile waste annually, much of which ends up in landfills (Crumbie, 2024). This is just one of the leading product types purchased online by this generation. As the Philippines, a climate-vulnerable developing nation (World Risk Report, 2017), faces mounting environmental and economic challenges, Gen Z’s consumption habits have serious implications for sustainability. This study examined factors affecting their intention to purchase sustainable products using Structural Equation Modeling in WarpPLS. Findings showed that Price Sensitivity (0.02), Social Influence (0.01), Marketing and Communication (0.01), and Availability (0.01) significantly impact purchasing intentions. To foster sustainable consumption, businesses should improve affordability, accessibility, and marketing, ensure clear labeling, and leverage technology and policy support. Public education and further research on cultural and digital trends are also essential. These strategies support market sustainability and contribute to achieving UN Sustainable Development Goal 12: Responsible Consumption and Production by 2030. Keywords: Filipino Gen Zs, E-commerce platforms, Sustainable Products, SEM-WarpPLS, SDG 12

Purpose Considering the emergence of e-commerce platforms and their integration into marketing channels, this paper aims to investigate how artificial intelligence (AI) resources – both technological and human – possessed by e-commerce platforms can enhance their channel power by acquiring market-based assets (relational and intellectual). Design/methodology/approach Based on resource-based theory and resource orchestration theory, the authors developed a framework tested using survey data gathered from the sellers, which incorporated six key variables: the e-commerce platform’s AI technology resources and human resources, rational and intellectual market-based assets, intraplatform competition and channel power. The analyses are performed using the regression analysis technique. Findings The empirical findings indicate that both technological and human AI resources are crucial in building channel power. In addition, market-based assets serve as a mediator in this relationship, while intraplatform competition moderates the effect of intellectual market-based assets on channel power negatively. Originality/value This study contributes to the existing literature by exploring how e-commerce platforms’ AI resources affect their channel power. The results offer valuable guidance to managers and researchers on optimizing AI resources to improve channel power.

The internet’s growth has opened doors for global sales, particularly in Malaysia, where a rising trend in online shopping is evident. Floriculture entrepreneurs are seizing this opportunity to boost ornamental plant sales online, driven by the increasing internet-savvy Malaysian customer base. Despite the overall surge in online commerce, ornamental plants face challenges in popularity compared to items like clothing or food. Various factors, including plant pricing, quality attributes, and reliable delivery services, influence consumer preferences for online ornamental plant purchases. This study aims to explore the factors influencing consumers toward purchasing ornamental plants online, assess consumer preferences, and understand how these patterns may impact future buying behavior. The conceptual framework includes five independent variables: price, quality, time-saving, convenience, and delivery service, with consumer preferences as the dependent variable. Data was collected from 154 respondents in Klang Valley, Malaysia, experienced in purchasing ornamental plants online, and analyzed using descriptive and mean ranking analysis. Findings show that the key platforms for purchases were Facebook, Shopee, and WhatsApp, with seedlings and adult plants priced under RM20 being the preferred choices. Respondents identified price, quality, time-saving, convenience, and delivery service as crucial factors in their online purchasing decisions. Notably, delivery service emerged as the most influential factor, earning 100% preference. Consumers expressed a strong willingness to buy ornamental plants online if informed about the seller’s quality and packaging methods, as highlighted by a mean score of 4.533. The study emphasizes that consumers prioritize “quality delivery service” when making online purchases. “Convenience” is another key factor, allowing consumers to compare prices before buying. Overall, consumers focus on price, quality, convenience, and time savings in their decision to buy ornamental plants online. Sellers are encouraged to go beyond these factors, employing diverse strategies to attract consumers to the online ornamental plant market.

Electronic commerce (e-commerce) refers to the transfer of the traditional concept of commerce to digital platforms due to the acceleration of technological developments and globalization. This transformation enables commercial transactions to be carried out over computer networks and internet infrastructure, thus offering important advantages such as time saving, low cost, wide market access and elimination of physical limitations. The most prominent feature of e-commerce is that transactions are carried out in a virtual environment instead of a physical store or office and are accessible 24/7. The purpose of this study is to examine the main features of e-commerce platforms, to analyze the usage patterns in the context of user experience and success factors. The scope of work, electronic trading systems; and its object is product and service buying and selling processes in digital environments. Literature review was used as a research method; national and international ecommerce definitions, models and practices are evaluated comparatively. Important institutions such as the World Trade Organization, OECD and Japan Electronic Commerce Center have developed definitions emphasizing different aspects of e-commerce. In general, it is defined as the implementation of production, promotion, sales and distribution processes of products and services through digital platforms and telecommunication technologies. E-commerce is not only limited to the private sector, but also public institutions are among the important stakeholders of this process. The relevance of e-commerce is due to both the need for businesses to integrate into the digitalization process and the growing online shopping habits of consumers. Various e-commerce models such as B2C (company-consumer), B2B (between companies), C2C (between consumers), B2G (company-state) and C2G (consumer-state) were introduced in the study. In addition, the role of the right product management, user-friendly web design, effective digital marketing strategies, customer satisfaction, innovation, patience and trust factors is emphasized for the success of these models. As a result, the development of e-commerce provides businesses with a competitive advantage; it offers versatile benefits to consumers such as quick information access, affordable shopping and time saving. In this way, the structure and operation of e-commerce platforms has become one of the most important issues of today, both academically and sectorally. In addition, the technologies used in the infrastructure of e-commerce directly affect the success in this field. Secure payment systems, mobile-friendly designs, fast cargo integration, stock tracking software and artificial intelligence-supported recommendation systems contribute to increasing sales by improving the user experience. Especially the increase of purchases made on mobile devices has made it necessary to support e-commerce platforms with mobile applications. In this regard, businesses that want to operate in digital marketplaces should prioritize not only product, but also service quality. These aspects of e-commerce will play a decisive role on future economic structures and consumption habits. Keywords: electronic commerce, digital economy, B2C and B2B models, advantages of e-commerce, information technologies and commerce

This article starts from the context of post-pandemic consumer overheating in the domestic market and explores the impact of e-commerce and short video live-streaming platforms on the consumption habits of student groups. Based on the theoretical perspective of behavioral economics, it conducts a psychological study of students' consumption characteristics. As a result, it concludes that the influence of e-commerce and short video live-streaming platforms on student consumption habits is primarily negative. Therefore, it is essential to pay attention to and educate students on cultivating their consumer attitudes and improving their understanding of consumption.