E-commerce Companies Research Articles

Exploring the Role of Digital Technologies in Enhancing Supply Chain Efficiency: A Case Study of E-Commerce Companies

This study examines the role of digital technologies in improving supply chain efficiency in e-commerce companies. It investigates how technologies such as AI, IoT, blockchain, and big data analytics optimize logistics, inventory, and order fulfillment. The study shows that these technologies enhance operational performance, reduce costs, and improve customer satisfaction by increasing supply chain transparency and enabling real-time tracking. The qualitative method is used in the research. The data is collected through the application of interviews, focus groups and document analysis and the results are presented in the form of prominent themes. The findings reveal that digital technologies like AI, IoT, automation, and blockchain, have greatly improved supply chain effectiveness in e-commerce companies. These technologies resulted in advancements like cost reduction, satisfaction of customers and delivery speed.

User avoidance behavior in pharmaceutical e-commerce intelligent customer service: a stressor-strain-outcome perspective

IntroductionThis study explores the implementation of Intelligent Customer Service (ICS) in pharmaceutical e-commerce, aiming to enhance user acceptance and service efficiency while addressing the psychological factors influencing user behavior. It expands the boundaries of technology acceptance research by focusing on ICS use and avoidance in high-risk environments.MethodA total of 418 valid questionnaires were collected from participants, ensuring data quality through rigorous screening. The study employed SPSS for data normality tests and SmartPLS for structural equation modeling to analyze the relationships between emotional stress, system overload, and user avoidance behavior.ResultsThe findings indicate that system overload, information overload, and service overload significantly contribute to user emotional stress, which in turn drives avoidance behavior. The analysis revealed strong explanatory power (R2 values ranging from 0.450 to 0.586) and confirmed the mediating role of emotional stress in the relationship between overload factors and user avoidance.DiscussionThis research highlights the critical role of emotional stress in user interactions with ICS, suggesting that pharmaceutical e-commerce companies must refine their ICS design to meet diverse user needs and reduce cognitive burdens. By leveraging big data and establishing robust feedback mechanisms, companies can enhance user experience and loyalty. The study also identifies limitations in demographic representation and suggests future research should incorporate qualitative methods for a deeper understanding of user behavior.

AN EMPIRICAL RESEARCH OF CONSUMER EXPERIENCES OF FRESH-PRODUCT E-COMMERCE PLATFORMS: BASED ON TIME, CONVENIENCE AND PERCEIVED PRICE, EXEMPLIFIED BY COMMUNITY GROUP SHOPPING

This paper examines the consumer experiences of representative E-commerce platforms for fresh products and groceries in mainland China using the framework of the nine factors of business activities. The paper breaks down the analysis into three major attributes of consumer experiences: waiting time, convenience and perceived price level, which isolate the specific factors that affect consumer behaviour and, hence, the channels in which E-commerce managers could engage to improve their performances. This paper summarises the consumer experience by conducting anonymised large-scale online questionnaires and analyses the empirical data using descriptive statistics. The paper has spotted the shortcomings and inefficiencies in the operation of these e-commerce platforms and proposed targeted optimisation strategies to improve consumer experiences based on the empirical evidence and justified their feasibility. This paper aims to benefit both sides of the online grocery market by delivering more affordable prices and greater satisfaction to consumers and improved brand loyalty and core competitiveness to the E-commerce companies.

Akulaku E-Commerce Company's Public Relations Marketing Strategy in Building Brand Awareness

Akulaku E-Commerce Company's Public Relations Marketing Strategy in Building Brand Awareness

URGENSI E-SERVICE QUALITY UNTUK PENGUATAN KEPERCAYAAN DALAM KEPUTUSAN PEMBELIAN

This study analyzes the role of e-service quality in building consumer trust in purchasing decisions on Shopee. Using a causal associative approach and explanatory research method, this study examines the relationship between variables using Structural Equation Modeling (SEM) through SmartPLS 3.0. The study population was the people of Kendari City who had made purchases on Shopee, with a sample size of 160 respondents selected by purposive sampling. The results of the study indicate that e-service quality has a positive effect on customer trust. This trust mediates the relationship between e-service quality and purchasing decisions. The theoretical implications of this study indicate the importance of digital service quality in strengthening the relationship between e-commerce platforms and consumers. Managerially, the results of this study suggest that e-commerce companies such as Shopee need to continue to improve service quality to build trust, maintain information transparency, and ensure a safe and comfortable shopping experience to attract and retain customers. Success in managing service quality drives repeat purchasing decisions, which contributes to business growth and sustainability.

Green Behaviors Among Employees in Chinese E-Commerce Companies: Impact of Environmental, Social, and Governance (ESG) Performance

Perceived ESG performance refers to stakeholders’ assessment of a company’s efficacy in implementing and maintaining ESG initiatives. This perception is crucial as it influences stakeholders’ trust and engagement with the company. The present study aims to test the relationships between the perceived performance of Chinese e-commerce firms and their employees’ green behaviors, with the mediating role of green psychological climate and the moderating role of ESG actions: substantive vs. symbolic. Employees’ green behavior is defined as any measurable individual behavior that contributes to environmental sustainability goals in the work context. Green psychological climate is defined as employees’ perceptions and interpretations of their organization’s policies, procedures, and practices regarding environmental sustainability. The sample includes 1285 employees from various Chinese e-commerce firms. Participants ranged in age from 19 to 66 years, with a mean age of 37.27 years (SD = 10.35). This study examines the impact of environmental, social, and governance (ESG) performance on green behaviors among employees in Chinese e-commerce companies. Leveraging data from organizational surveys, the findings reveal that perceived ESG performance significantly influences green behaviors, both directly and indirectly, through the mediating role of green psychological climate. Mediation analysis underscores the pivotal role of green psychological climate in bridging ESG performance and individual green behaviors, with the strength of this relationship varying significantly across levels of substantive ESG actions. Furthermore, while the moderating effects of ESG substantive and symbolic actions on the relationships between ESG performance, green psychological climate, and green behaviors did not achieve conventional statistical significance, observed trends suggest a nuanced interplay worthy of further exploration. These findings highlight the complexity of translating organizational ESG commitments into employee actions, emphasizing the importance of both substantive and symbolic ESG initiatives in fostering a green psychological climate. This study contributes novel insights into the mechanisms driving green behaviors in organizational contexts, offering implications for both academic research and managerial practice.

Efficient Personalization in E-Commerce: Leveraging Universal Customer Representations with Embeddings

E-commerce has grown into a billion-dollar industry in recent times with an ever-increasing number of individuals using it regularly. Thus, e-commerce companies can gather interaction data from their customers and analyze it to create focused and personalized marketing campaigns. For large companies, it is possible to tap into these data for personalization using deep learning-based methods that require enormous computing resources. Small companies, on the other hand, cannot afford this. Furthermore, this level of tailor-made addressing necessitates an accurate customer representation. Nevertheless, the exploration of universal representations applicable across various tasks has been limited despite the advantages they offer. We propose a universal customer representation learned only from customer interaction data. We demonstrate that self-supervised trained embeddings of the customer interaction context are a suitable universal customer representation for various e-commerce tasks. To demonstrate the effectiveness of our approach, we conducted experiments comparing four different state-of-the-art approaches and their capabilities in different prediction tasks. Not only do we show that our method outperforms others in most cases, but it also meets other important criteria for real-world applications. It is particularly important to emphasize that our approach does not require a significant amount of resources, and furthermore, is data protection compliant by not using personal information.

Machine Learning Models for Predicting Order Returns in Cross-Border E-Commerce

This study investigates the application of machine learning models to address after-sales service issues in cross-border e-commerce, focusing on predicting order returns to reduce return costs and optimize customer experience. Using H cross-border e-commerce company as a case study, the research employs Random Forest and XGBoost models to identify high-risk return orders. By comparing the performance of these two models, the study highlights their respective strengths and weaknesses and proposes optimization strategies. The findings provide a valuable reference for e-commerce companies to refine their business models, reduce return rates, improve operational efficiency, and enhance customer satisfaction.

An Analysis of Cash Management Strategies in E-Commerce Companies

This paper investigates the vital role of cash management in e-commerce companies, focusing on three major players: Pinduoduo, Jing Dong, and Amazon. The study delves into the strategies these firms use to optimize cash flows, emphasizing how technological advancements and social factors unique to the e-commerce industry influence their cash management practices. By exploring the advanced systems implemented by these companies, this research provides valuable insights into the techniques that drive financial efficiency. In addition to analyzing existing cash management methods, the study incorporates a comparative analysis of financial models and statistical data to highlight the best practices in the sector. The findings underscore the importance of cash management in sustaining operational success and long-term growth in the e-commerce industry. Furthermore, the paper offers predictions on future trends, identifying potential challenges and opportunities for innovation in cash management. This research aims to contribute to the broader understanding of financial optimization in online retail, offering actionable insights for both academics and practitioners in the field.

Enhancing E-commerce Security through Fake News Detection Using Natural Language Processing and Advanced Feature Engineering Technique

E-commerce has simplified customers' lives and offered a range of items, but it has also made them vulnerable to frauds. Fake news on e-commerce platforms threatens trust, brand image, and economic stability. Researchers have shown that contemporary Natural Language Processing (NLP) and machine learning can stop bogus news. However, e-commerce companies still struggle to distinguish phony news from real information. Fast knowledge diffusion can cause financial loss, reputation damage, and customer distrust. Thus, e-commerce false news identification requires robust and trustworthy methods. This investigation will successfully recognize and discriminate fake news. High Feature Extraction uses Word2vec and Term Frequency-Inverse Document Frequency (TF-IDF) to extract features. The optimum feature subset is determined via feature selection utilizing the least absolute shrinkage and selector operator (LASSO). The study involves four phases: Extraction, selection, classification, and data processing are the four steps. To remove raw data, data preparation utilizes stemming, lemmatization, and stop word removal. The suggested method averages model outputs to reduce overfitting and improve prediction stability. DIstilBERT with multi-stacked LSTM is tested on WELFake and ranked by F1 score, sensitivity, accuracy, and specificity. The multi-stacked LSTM distiller has 99.77% accuracy, far greater than the others do. We can use it to detect bogus news. It boosts customer confidence and Internet commerce legitimacy by improving accuracy and consistency.

Eksplorasi Model Bisnis E-Commerce dan Penerapannya pada Industri Pariwisata

Successful e-commerce companies have business models that leverage the uniqueness of the web, providing real value to customers. Understanding and awareness of the importance of e-commerce business with its various models among business actors is still low. Implementation, especially in the tourism industry, is also not optimal, so it cannot improve company performance. The purpose of the study was to comprehensively explore e-commerce business models and their application to the tourism industry, which has never been done before. The method used is library research, using critical analysis techniques. This study found 36 e-commerce business models: B2B, B2C, C2C, C2B, B2B2C, B2G, G2B, C2G, G2C, G2E, G2G, B2A, C2A, O2O, B2P, C2P, G2P, P2C, P2G, P2B, P2P, Mobile Commerce (M-Commerce), Social Commerce, Influencer Commerce, Video Commerce, Direct-to-Consumer (D2C), Dropshipping Model, Wholesaling & Warehousing Model, Private Label & White Label, Subscription E-Commerce, Marketplace E-Commerce Model, Niche E-Commerce, Digital Products & Downloads, Brick-and-Click, Business Process Reengineering (BPR), and Canvas in E-Commerce. The use of e-commerce in the tourism industry is known as electronic tourism (e-tourism) and tourism e-commerce. In its implementation, there are 22 e-commerce business models, including: B2B, B2C, C2C, C2B, B2G, B2B2C, G2G, G2B, G2C, G2E, M-Commerce, B2E, G2B2C, G2N, G2V, and there is a new model based on tourism supermarket & adaptable workflow mechanism-M-TSAW. Each of these models has its own characteristics, and there are several impacts of e-commerce on the tourism industry.

Analisis Model E-Bisnis B2C ada Perusahaan Teknologi di Indonesia

This study aims to analyze the B2C e-business model implemented by technology companies in Indonesia and identify the factors influencing its success and the challenges faced during its implementation. The B2C (Business-to-Consumer) e-business model has grown rapidly with internet penetration and smartphone usage in Indonesia. Additionally, government policies and the digitalization of SMEs have been key factors in the country's growth of the e-commerce industry. This research uses a literature review and descriptive analysis method, gathering secondary data from industry reports, journals, and data from leading e-commerce companies in Indonesia. The results show that the success of the B2C model in Indonesia is significantly influenced by consumer trust, intense competition between companies, and the logistical infrastructure that remains a challenge. Furthermore, technologies such as AI and blockchain can enhance the customer experience and improve data management systems. Large companies like Tokopedia and Bukalapak have demonstrated that the development of the right strategy can help them maintain their market share. Still, they also face challenges related to declining profit margins due to aggressive customer acquisition strategies. Looking ahead, global market expansion and the empowerment of SMEs will be crucial to ensuring sustainable growth for the B2C e-business model in Indonesia. This study is expected to provide insights for policymakers and industry players in formulating more effective strategies to optimize the potential of e-commerce in Indonesia.

Optimizing ICMS Strategies for E-Commerce in Brazil: Tax Benefits and Profitability Insight

This study aimed to analyze the ICMS in the interstate operations of e-commerce companies, targeting non-taxpayers. The objective was to identify more economically advantageous strategies that would remain compliant with the tax legislation. The economic implications are evident in the use of tax benefits by various states, seeking to attract large companies to their jurisdictions through these incentives. A case study was conducted at a medium-sized company that has experienced significant growth in recent years, driven by both operational expansion and the rise of e-commerce on digital platforms. To carry out this case study, information from the company's tax documents was used, including verification of files and tax ledgers, and calculation of taxes and other reports relevant to the study. The analysis revealed that ICMS has a significant effect on the company's operations, necessitating the implementation of strategies to efficiently and legally reduce the tax burden. To implement these strategies, this study analyzed the tax benefits offered by specific states within the federation to this particular industry segment. By comparing these benefits to the company's operational values, opportunities to reduce the tax burden and increase profitability can be identified. The study demonstrated the potential for substantial cost savings by considering the company's location as the primary focus. These savings could range from 41.9% to 72.5%.

Machine Learning Models for Predicting Order Returns in Cross-Border E-Commerce

This study investigates the application of machine learning models to address after-sales service issues in cross-border e-commerce, focusing on predicting order returns to reduce return costs and optimize customer experience. Using H cross-border e-commerce company as a case study, the research employs Random Forest and XGBoost models to identify high-risk return orders. By comparing the performance of these two models, the study highlights their respective strengths and weaknesses and proposes optimization strategies. The findings provide a valuable reference for e-commerce companies to refine their business models, reduce return rates, improve operational efficiency, and enhance customer satisfaction.

Action Research on Talent Recruitment of Guangzhou Zz Cross-Border E-Commerce Company

Action Research on Talent Recruitment of Guangzhou Zz Cross-Border E-Commerce Company

Strategic Management in Improving Company Competitiveness in Indonesia's E-commerce Industry

This study aims to analyze the management strategies implemented by companies in increasing competitiveness in the Indonesian e-commerce industry. By using a qualitative approach through literature study or library research, this research utilizes various sources such as scientific journals, books, industry reports, and reliable articles. The results of the analysis show that e-commerce companies in Indonesia are facing increasingly fierce competition challenges due to rapid market growth and the development of digital technology. To survive and excel, companies need to implement management strategies that focus on innovation, human resource management, technology development, and customer experience optimization. Product and service innovation strategies are one of the important keys in attracting and retaining customers. In addition, effective logistics management and the application of data-driven technologies such as artificial intelligence (AI) and big data analytics are supporting factors in improving operational efficiency. The research also finds the importance of strategic collaboration with business partners to create a competitive digital ecosystem. Based on these findings, the study recommends the application of adaptive and future-oriented approaches to ensure long-term competitiveness. This finding is expected to make a practical contribution to managers of e-commerce companies in Indonesia as well as an academic reference for further research.

Pengaruh Penggunaan Dan Respons Chatbot Terhadap Kepuasan Konsumen E-Commerce

The development of technology and innovation impacts the growth of e-commerce activities and continues to expand yearly. This growth has led to an increased demand for efficient customer service. One effort made by e-commerce companies is to implement chatbots in their customer service. This study aims to analyze the impact of chatbot usage and response on e-commerce customer satisfaction, with mediation by extrinsic and intrinsic values of the online consumer experience. Data were collected by distributing questionnaires, and 213 respondents from several cities in Indonesia were successfully gathered. The data were processed using Smart PLS 3 software. This study demonstrates that chatbot usage and response, mediated by extrinsic and intrinsic values, positively affect customer satisfaction.

The Impact of Free Trade Zones on the International Competitiveness of Cross-Border E-Commerce Companies

As international e-commerce expands so quickly, cross-border e-commerce (CBEC) is becoming more and more important to China's exports. This study attempts to investigate the effect of free trade zones (FTZs) on the global competitiveness based on the FTZ. A thorough analysis of the ideas surrounding FTZs and CBEC allows for the clarification of the fundamental research framework and the application of both qualitative and quantitative research methods. The development strategy of CBEC is finally presented. After a review of the advantages of FTZ policies (such as expediting the customs clearance process, lowering trade barriers, improving logistics efficiency, etc.) and the disadvantages of CBEC policies (such as increasing market competition, diversifying the international market), and unpredictable regulatory policies: formulate and improve the relevant policies, strengthen the construction of the CBEC service platform, expand the scope of the CBEC comprehensive pilot zone, improve the financial service system, and cultivate the interdisciplinary talents needed for CBEC.

Creating Impulse Buying Behavior in The Online Festival Atmosphere: A Gender-Based Evaluation

Impulsive buying behavior during online shopping festivals is shown by many consumers and e-commerce businesses benefit from it. However, the reasons for this behavior have not been revealed. Therefore, this study will investigate the antecedents underlying this behavior. It was also investigated whether the effect of these antecedents on the festival atmosphere differed according to gender. A total of 590 participants (294 men and 296 women) participated in the study. The analysis was conducted with PLS-SEM 4.0. As a result of the analysis, it was seen that the elements that make up the festival atmosphere differed for men and women. For women, low price, perceived novelty, perceived perishability, perceived limitation, category richness, time constraint, and perceived entertainment affected the festival atmosphere, while for men, low price, perceived perishability, perceived limitation, time constraint, and social benefits affected the atmosphere. In addition, festival atmosphere positively influenced impulse buying for both genders. Therefore, e-commerce companies should create a festival atmosphere by considering gender differences and use different variables.

Problems and Solution Suggestions Related to Logistics Processes in Cross-Border E-Commerce: Evaluations Towards E-Export in Bursa Province

Rapidly growing e-commerce, due to globalization and the impact of the Covid-19 epidemic, has significantly increased global demand, and cross-border e-commerce has become a frequently mentioned concept. Cross-border e-commerce, which also triggers the development of international trade, has begun to influence the economic policies of countries, especially with its e-export dimension. The most important factor behind the development and success of cross-border e-commerce can be expressed as being its logistics services. E-commerce processes achieve success with the effectiveness of these services. However, as in many countries, problems may occur in logistics processes in Türkiye, which may prevent cross-border e-commerce companies from using their potential. In this context, in the study, firstly, the concepts of e-commerce and cross-border e-commerce are discussed and the concept of e-export is clarified. Then, logistics services in cross-border e-commerce are explained. Finally, a qualitative research is conducted to reveal the logistics problems encountered in cross-border e-commerce, and the findings of in-depth interviews with companies engaged in e-export in Bursa are evaluated.