E-commerce Research Articles

Optimization of the cooperative electronic commerce model for sustainable development in the context of ecological environment conservation

AbstractThis study aims to explore how to optimize the cooperative electronic commerce model in a sustainable ecological environment to meet the needs of consumers while maximizing social and economic benefits. The empirical research method is adopted, which mainly includes a literature review, case analysis, and questionnaire. Firstly, through a literature review, this study introduces and analyses the concept of sustainable ecological environment and the development and optimization direction of cooperative electronic commerce model in detail, providing a theoretical basis and thought guidance for subsequent research. Secondly, this study selects several representative cooperative electronic commerce platforms for case analysis. It explores their operation mode, product characteristics, service quality, and social benefits to summarize the experience and lessons of optimizing cooperative electronic commerce model. Finally, a questionnaire is designed to sample the consumers of cooperative electronic commerce. By analysing the results of questionnaire, the following conclusions are drawn. (1) 54.3% of respondents said they had used the cooperative electronic commerce model, with agricultural products purchasing (23.5%) and community service (18.9%) using it more frequently. (2) The cognition level of sustainable development was high overall, with 62.6% believing that it was essential for the future. (3) A multiple linear regression model explored the relationship between using the cooperative electronic commerce model and sustainable development cognition. The results reveal that adopting cooperative electronic commerce model has a significant positive impact on the cognition of sustainable development, which indicates that the promotion and use of this model can promote cognition and practice of sustainable development.

TPAAS: Trustworthy privacy-preserving anonymous authentication scheme for online trading environment

In recent years with the improvement of information communication technology (ICT) and wireless communication, Online Trading Environment (OTE) has become a popular E-commerce platform to connect sellers and buyers in an efficient way. As, OTE’s are increasing in a wider range, the authentication and verification of entities in OTE network becomes a challenging task. Although, some authentication schemes exist in OTE’s, they have flaws such as account creation delays, authentication delays, communication cost and user privacy. In this work, a trustworthy and secure anonymous authentication scheme is proposed to prevent malicious users to enter into the OTE network. In addition, our proposed scheme provides conditional privacy to users until they maintain a genuine relationship with other entities without compromising. If any dispute occurs, then the system will revoke the access of that particular entity. Moreover, the security and performance analysis in this work concludes that our scheme ensures a secure interface to provide sustainable trading experience to users by taking less computation cost and communication delay when compared to other existing authentication schemes.

Enhancing Fraud Detection Systems through Advanced Data Engineering Techniques

Aims: Fraud remains a persistent issue in various industries, particularly in finance, e-commerce, and healthcare, where traditional rule-based systems have struggled to keep pace with the evolving complexity of fraudulent activities. This study aims to develop an enhanced fraud detection framework by addressing the limitations of traditional rule-based systems, particularly in industries where sophisticated fraud schemes prevail. Study Design: The research utilizes advanced data engineering techniques, including big data analytics, machine learning, and real-time processing, to improve the accuracy and efficiency of fraud detection systems. Place and Duration of Study: The study was conducted over two years across industries with high fraud susceptibility, including financial services, e-commerce platforms, and healthcare organizations. Methodology: The framework integrates various data sources, including transaction logs, user behavior, and external fraud indicators. These datasets were pre-processed through data cleaning, feature engineering, and integration. Supervised and unsupervised machine learning models, such as Random Forest and Gradient Boosting, were applied to detect fraud patterns. Real-time data processing enabled immediate detection and response. The system continuously learned from historical data, adapting to new fraud tactics and improving detection over time. Results: The proposed framework demonstrated a significant improvement in fraud detection accuracy, with machine learning models achieving over 90% accuracy rates. There was also a 30% reduction in false positives compared to traditional methods, and detection times were shortened by 40%, enabling faster identification and mitigation of emerging fraud schemes. Conclusion: This study concludes that integrating advanced data engineering techniques with machine learning significantly enhances fraud detection systems' accuracy, scalability, and adaptability. While promising, further improvements are needed, particularly in addressing the evolving nature of fraud schemes and ensuring the scalability of real-time data processing. These areas present opportunities for future research and development.

PERAN HUKUM DALAM PLATFORM E-COMMERCE DALAM ERA TRANSFORMASI DIGITAL DI DESA BATUNUNGGAL KECAMATAN CIBADAK KABUPATEN SUKABUMI

This community service aims to improve the understanding and implementation of legal aspects in e-commerce platforms in the era of digital transformation in Batununggal Village, Cibadak District, Sukabumi Regency. The program was implemented through a workshop method with a participatory approach, involving 20 MSME players. The result was 30% who have utilized the e-commerce platform and 85% admitted to have a limited understanding of the legal aspects of electronic transactions. The program also resulted in the establishment of a digital business community and a digital legal consultation center at the village level. The sustainability of the program is supported through an ongoing mentoring system and the development of an online learning module

Application of Fuzzy - AHP - Topsis Model Integration to Select Green C2C Websites in Online Shopping

In today's digital age, online shopping has become an indispensable part of daily life. The strong development of e-commerce platforms helps consumers easily search and choose products from around the world with just a few clicks. Making purchasing decisions is not simple when buyers have to consider many factors such as price, quality, brand and many other factors. To support smart consumers in shopping, the study applied the Fuzzy - AHP - Topsis integrated model to evaluate purchasing criteria on 4 popular C2C websites: Shopee, Tiki, Lazada and Sendo.

Optimized AI-Driven Semantic Web Approach for Enhancing Phishing Detection in E-Commerce Platforms

For e-commerce systems, phishing attempts remain a major threat, so sophisticated detection techniques using Semantic Web and artificial intelligence are very necessary. An efficient AI-driven Semantic Web method for phishing detection enhancement is presented in this work. The approach uses the Chi-square feature selection approach along with the Adaptive Differential Evolution with Optional External Archive (JADE) algorithm to optimize the hyperparameters of a Convolutional Neural Network (CNN) model. Having grown up on a large collection of more than 11,000 webpages, the model attained 93% accuracy. Although alternative models sometimes exceeded it in accuracy, the suggested method always showed the lowest loss values throughout all epochs, therefore stressing its stability and efficiency. Comparative study using conventional models confirms its resilience against phishing attacks for protecting e-commerce systems.

Tanggung Jawab Pelaku UMKM Sebagai Merchant Dalam E-commerce

Introduction: The dynamics of globalization and technological advances have changed the business world significantly, especially with rapid developments in the field of electronic commerce (e-commerce). Significant growth in this field is expected to make a positive contribution to the development of Micro, Small and Medium Enterprises (MSMEs) by expanding market access.Purposes of the Research: To find out and analyze the responsibilities of MSME actors as merchants in e-commerce.Methods of the Research: The legal research method used in studying this problem is normative juridical, which is based on primary, secondary and tertiary legal materials, and uses a statutory approach and a conceptual approach.Results of the Research: The results of this research show that quite a few business actors do not fulfill their obligations, namely being responsible for fulfilling consumer rights. The form of consumer rights that is violated by business actors in a food product for consumption by consumers is stated in Article 4 point (3) regarding the provision of correct and clear information about a product, goods and/or services. Therefore, business actors are obliged to follow food production standards and maintain product quality in order to meet consumer needs and satisfaction. To protect consumers from business actors whose rights are not fulfilled, the Consumer Protection Law provides protection to consumers in two forms, namely preventatively and repressively. By using strict liability, the application of absolute responsibility solves problems faced by consumers without the need to prove fault, so that consumer rights based on this responsibility can provide legal protection

Smart moves: Flipkart’s name-personalized nudging techniques to combat cart abandonment

Flipkart, a leading e-commerce platform, has made significant global strides by offering a diverse range of products, including electronics, fashion, and groceries. Flipkart has a significant problem with high cart abandonment rates, particularly on mobile devices, despite its success. This problem is severe because it damages marketing efforts, impacts customer retention, and causes a large loss of revenue. Complicated checkout procedures and unforeseen expenses are major contributors. Flipkart uses name-based personalized nudges to address this, giving customers a sense of familiarity and customization that makes them feel appreciated. Purchase completion is encouraged by these nudges, which include recovery emails that use the customer’s name and provide customized incentives. Challenges in putting these nudges into practice include protecting customer privacy and guaranteeing data accuracy. Nonetheless, the possible advantages of lowering abandonment rates and strengthening allegiance make it valuable. Flipkart also improves the shopping experience by strategically nudging customers. Transparent pricing, streamlined checkout procedures, guest checkout, a variety of payment methods, and conspicuous security badges are a few of them. To further promote transaction completion and reduce abandonment rates, several interventions are used, such as mobile optimization, exit-intent popups, and cart recovery emails. Flipkart’s dedication to establishing a smooth shopping experience and tackling the serious problem of cart abandonment is demonstrated by these initiatives. All things considered, even though putting these nudges into practice can be difficult, Flipkart’s creative strategy for addressing cart abandonment through personalization and name-based personalized nudges demonstrates its commitment to improving customer satisfaction and increasing conversion rates.

Combating fraud in online commerce: challenges of today

Combating fraud in online commerce: challenges of today

An Ensemble Approach for Speaker Identification from Audio Files in Noisy Environments

Automatic noise-robust speaker identification is essential in various applications, including forensic analysis, e-commerce, smartphones, and security systems. Audio files containing suspect speech often include background noise, as they are typically not recorded in soundproof environments. To this end, we address the challenges of noise robustness and accuracy in speaker identification systems. An ensemble approach is proposed combining two different neural network architectures including an RNN and DNN using softmax. This approach enhances the system’s ability to identify speakers even in noisy environments accurately. Using softmax, we combine voice activity detection (VAD) with a multilayer perceptron (MLP). The VAD component aims to remove noisy frames from the recording. The softmax function addresses these residual traces by assigning a higher probability to the speaker’s voice compared to the noise. We tested our proposed solution on the Kaggle speaker recognition dataset and compared it to two baseline systems. Experimental results show that our approach outperforms the baseline systems, achieving a 3.6% and 5.8% increase in test accuracy. Additionally, we compared the proposed MLP system with Long Short-Term Memory (LSTM) and Bidirectional LSTM (BiLSTM) classifiers. The results demonstrate that the MLP with VAD and softmax outperforms the LSTM by 23.2% and the BiLSTM by 6.6% in test accuracy.

Benefits of Developing E-Commerce Platform for Informatics Students as Additional Income

The article in this journal will bring readers more specifically to university students to see easier access to money for additional living expenses. A new perspective when students are more specifically informatics students who are taught and nurtured so that they have skills and knowledge about program development not only live with money given by parents, but with money from the creation and development of their own programs or platforms. Access and dissemination of this journal will be expanded to make it more accessible and useful to all readers not only for informatics students but for prospective students and former students who have dived into the sea of computer code more specifically on the creation and development of programs or platforms.

Persuasive Speech Act Strategies of Online Fashion Sellers in Live E-Commerce: A Cyberpragmatics Approach

Through cyberpragmatics outlook, this study explores the persuasive speech act techniques utilized by online fashion vendors during live e-commerce sessions. The study investigates how sellers utilize persuasive strategies in digital communication to influence consumer behavior and increase revenue. A mixed-methods approach is employed so that the research combines qualitative content analysis of live selling sessions with quantitative measures of engagement and conversion rates. Important discoveries show that sellers frequently use a combination of assertive, expressive, directive, commissive, and phatic speech acts, which are adapted to the dynamic and interactive nature of real-time e-commerce platforms. The implications for both sellers and digital marketing strategists underscore the importance of adaptive communication techniques in enhancing consumer engagement and optimizing sales outcomes. Furthermore, the persuasive strategies emphasize the importance of using visual aids, real-time client engagement, and personalized marketing tactics. This research contributes to the understanding of digital persuasion in e-commerce and offers insights into the evolving landscape of online retail communication.

Shopee E-Commerce Website Quality Analysis Based on User Perception Using the Webqual Method

This study aims to analyze the quality of Shopee's e-commerce site using the WebQual method approach. Three main dimensions, namely usability, information quality, and service interaction, are used to evaluate the quality of the Shopee website from the user's point of view. This method measures users' perception of the main aspects that determine their experience in using the Shopee website. The results of the study show that although Shopee has succeeded in providing a responsive and informative platform, several areas need improvement, especially related to aspects of service interaction and the security of users' personal information. In conclusion, Shopee needs to optimize several important aspects to improve the user experience and strengthen its position as a leading e-commerce platform in Southeast Asia. Improved design and navigation of a more modern and intuitive interface can make it easier for users to navigate the platform. In addition, real-time updates of product information regarding stock and prices will help prevent user dissatisfaction. Shopee also needs to improve customer service, both with the addition of staff and technology such as advanced chatbots, to answer customer needs faster. Finally, increased security and transparency regarding transactions and protection of personal data will strengthen user trust in this platform. Through these efforts, Shopee is expected to be able to provide a better shopping experience and maintain the loyalty of its users in the midst of fierce e-commerce competition.

Privacy Preferences of Consumer and Lender: A Case of Digital Credit Systems in India

Digital credit services are rapidly evolving in the Internet commerce environment. As such, this study aims to identify and prioritize the key factors influencing the views of digital credit users (DCU) and digital credit providers (DCP) on privacy practices. The study begins with a comprehensive literature review to identify an extensive set of factors and inputs from an expert panel. Next, the study applies the well-established “multi-criteria decision-making method,” which allows assigning weights to each of the four criteria and 13 sub-criterions to reveal DCU and DCP preferences for digital credit protection. Results indicated that the “Concerns about Personal Information” criteria are prioritized highly by DCU and DCP. This study marks the first attempt to reveal the preferences of DCU and DCP digital data privacy policies in a growing economy (India) and help policymakers and regulators align their digital privacy policies, enhancing the overall user experience.

Blockchain in Luxury Resale: The Impact of Blockchain Technology Through Regulatory Focus and Uncertainty Reduction Theories

ABSTRACTThe exponential growth of the online luxury resale market has spurred a notable shift toward a circular economy, reflecting the increasing consumer preference for pre‐owned luxury items. Nevertheless, this growth presents challenges related to product authenticity and seller credibility. In response to these concerns, blockchain technology (BT) emerges as a promising solution, leveraging a decentralized ledger to enhance transparency and reduce information asymmetry. This allows for the traceability of pre‐owned luxury goods, addressing issues of provenance and authenticity in the online resale space. By incorporating regulatory focus theory into the uncertainty reduction theory, this study examines how approach and avoidance motivations impact evaluations of BT‐enabled platforms to effectively mitigate consumer uncertainties and influence trust. The collected data (N= 511) was analyzed through partial least squares structural equation modeling (PLS‐SEM; study 1), and a complementary qualitative study (study 2) was additionally conducted. Results reveal that distinct motivations coexist, each following separate pathways to build consumer trust. Findings indicate that an approach orientation mindset highly values the reliability of BT‐enabled information, while an avoidance orientation focuses on risk mitigation and expresses heightened uncertainty in online transactions. Consequently, BT is found to be instrumental in reducing consumer concerns about purchasing pre‐owned luxury products. The study contributes to the existing literature by shedding light on the psychological dynamics influencing consumer trust in BT‐enabled platforms, has implications for luxury retailers contemplating BT integration, and offers insights into consumer behavior that can inform strategies to enhance perceived trust in online luxury resale.

Enhancing Customer Satisfaction

Customer satisfaction is crucial for the sustained success of e-commerce platforms, necessitating effective Customer Relationship Management (CRM) strategies to bolster relationships and overall performance. While existing research provides insights into factors like payment methods, shipping times, and customer demographics that influence satisfaction, significant gaps remain in fully understanding these dynamics, particularly within specific contexts such as Olist, a prominent Brazilian online marketplace. This study aims to address these gaps by leveraging advanced machine learning techniques on a comprehensive dataset comprising 100,000 orders spanning 2016 to 2018. Through meticulous analysis, which includes rigorous feature selection and the application of predictive models like logistic regression, decision trees, and random forests, we pinpoint crucial determinants of customer satisfaction. Our findings underscore the pivotal role of operational efficiencies in shaping customer experiences and offer actionable recommendations for enhancing e-commerce performance. By bridging these research gaps, this study not only contributes to the existing body of knowledge but also informs practical strategies for optimizing customer satisfaction and guides future research endeavors in the realm of e-commerce and CRM.

From Grapes to Clicks : A Cloud-Based Wine-Selling Solution for Single Vendors

This document outlines the design and creation of a robust wine vending application for a single vendor, which combines a web platform, an Android mobile app, and a cloud-based framework. This solution addresses the increasing demand for online wine sales while delivering a smooth, secure, and adaptable shopping experience. Essential features of the system include an intuitive web interface and an application focused on effective product searching, ordering, and payment processing. Cloud infrastructure is implemented to guarantee high availability, scalability, and secure data management. The paper discusses various architectural alternatives, such as utilizing cloud services for load balancing, data handling, and disaster recovery. It also emphasizes the necessity of strong security protocols, including encryption, user authentication, and adherence to industry standards for online transactions. Additionally, the document addresses challenges related to regulatory compliance, including age verification mandates and data protection laws. Lastly, it explores strategies for performance enhancement, improvements to user experience, and potential avenues for future expansion. The proposed solution aims to deliver a dependable, secure, and scalable platform tailored to the requirements of individual wine retailers while accommodating future growth.

Production of a Wood–Plastic Composite with Wastes from Disposable Masks and Corrugated Cardboard: A Sustainable Post-Pandemic Approach

The increasing demand for disposable textile products, personal care items, and electronic commerce has led to a substantial rise in waste generation, particularly from nonwoven fabric masks (wNWFs) and corrugated cardboard (wCC). This study assessed the feasibility of utilizing these waste materials, which were produced in significant amounts during the COVID-19 pandemic, as both a matrix and reinforcement filler in wood–plastic composites (WPCs). The WPC was fabricated using either two extrusion cycles or thermokinetic homogenization, with both processes being followed by hot pressing. The formulations consisted of virgin polypropylene (vPP), wNWF, and wCC in proportions of 45, 45, and 10 wt %, respectively. The results demonstrated that the composites produced via two extrusion cycles exhibited a tensile strength that was 85% higher and three-point flexural strength three times greater than those produced through thermokinetic homogenization. These findings contribute to advancements in scientific and technological knowledge and offer an efficient solution for managing these types of waste, which continue to be generated post-pandemic.

Brand Loyalty through Consumer Protection of Selected E-Commerce Firms

Ensuring consumer rights and addressing their various concerns has been identified as a crucial step in securing customer loyalty. However, the e-commerce sector in Nigeria has struggled to retain its customers due to its failure to adequately protect consumer rights. This lack of consumer rights protection has resulted in poor customer loyalty, with users frequently abandoning e-commerce platforms. This study examines the effect of consumer protection on brand loyalty within selected e-commerce firms. The research surveyed 497 active users of these e-commerce platforms with a 90.3% return rate and employed multiple regression analysis to assess the results. The findings revealed that consumer protection has a significant effect on purchase decisions (Adj.R² = 0.660, F(3, 445) = 290.639, p < 0.05), customer trust (Adj.R² = 0.580, F(3, 445) = 207.126, p < 0.05) and customer satisfaction (Adj.R² = 0.590, F(3, 445) = 215.819, p < 0.05) of listed e-commerce firms in Lagos State, Nigeria. Consequently, the study concludes that consumer brand protection significantly influences the brand loyalty of selected e-commerce firms, recommending that e-commerce management prioritize the recognition and protection of consumer rights to enhance brand loyalty

Limited Practical Effect of APEC ODR: A Comparative Analysis of Platform ODR and APEC ODR

Abstract: The actual demand and effect of the ODR (Online Dispute Resolution) mechanism in the field of cross-border e-commerce dispute resolution are relatively limited, and the protection of the ODR mechanism within small and medium-sized cross-border e-commerce platforms is insufficient. The reasons why the ODR mechanism cannot be fully applied to such platform disputes include the complexity of cross-border, diverse types of disputes, cost of time and money, and limited scope of application of the ODR mechanism. In addition, the lack of neutrality and standardized operating rules of the ODR mechanism within the e-commerce platform directly affects the fairness of dispute resolution. Although APEC (Asia-Pacific Economic Cooperation) ODR mechanism has shown significant advantages in improving efficiency and ensuring information security, it fails to effectively balance efficiency and fairness in terms of application scope and practical effect. Based on this, there are insufficient fairness problems in the automatic process mechanism, evidence collection procedure, and process deadline setting in the APEC ODR process. In the future, the APEC ODR and other international dispute resolution mechanisms will continue to be more internationalized and standardized. In addition, we have to be alert to the anti-globalization risks reflected in the APEC ODR, avoid geopolitical interferences as much as possible, and prevent the emergence of trade protectionism.