E-commerce Research Articles

Characterization and insights of fig sales on e-commerce platforms – taking Taobao and Tmall as an example

Characterization and insights of fig sales on e-commerce platforms – taking Taobao and Tmall as an example

Digital Immigrants Versus Digital Natives: Decoding Their E-commerce Adoption Behavior

It is easier to assume that educated older adults will find digital gadgets or the Internet as simple to use as the young generation does. However, it is not as simple as that. The generation that was not born into the digital world but has had to make an effort to learn to use digital technologies during their middle or late middle age is referred to as Digital Immigrants (DIs). Most of these individuals were forced to adapt to information technologies due to environmental pressure to survive and thrive at their workplace. The objective of this study is to investigate if the proposed “digital divide” that differentiates digital immigrants from digital natives (DNs) exists among e-commerce users in India, and if so, are digital immigrants less likely to adopt and use e-commerce services? Data was collected through a self-administered survey questionnaire from 432 Indian Internet users aged 19 to 65. Multigroup structural equation modeling analysis (M-SEM) of data revealed that DIs and DNs perceive e-commerce services differently. Though digital immigrants find e-commerce services challenging to use, their higher perception of its usefulness propels them to adopt and use e-commerce. This study contributes to the existing body of literature by extending our understanding of the technology adoption behavior of digital immigrants. The study’s implications and the scope for future research are discussed at the end of the article.

Is there a direct benefit of using electronic commerce and electronic banking in mitigating climate change?

The main objective of the study is to highlight the impact that the use of electronic commerce (e-commerce), electronic banking (e-banking) services have on climate change in European Union (EU) countries. Thus, we built a panel model to evaluate the correlations between e-commerce, e–banking, electronic sales channels, and climate change mitigation during 2011–2022 period for the EU countries. Furthermore, we applied the Fully Modified Ordinary Least Squares (FMOLS) method including three independent variables that evaluate the use of digital commerce applications and the dependent variable for climate change. A significant revelation of the study is the positive contribution of e-commerce activities to climate change mitigation. Furthermore, the study emphasizes the role of e-banking in decreasing the consequences of climate change. However, the study also uncovers a more complex aspect regarding electronic sales channels. It finds that not all forms of electronic sales are effective in reducing climate change impacts. Thus, the study highlights the potential benefits of e-commerce and e-banking in the context of climate change mitigation, while also warning against a one-size-fits-all approach to the adoption of digital commerce models. These findings have important implications for policymakers, businesses, and researchers aiming to align digital transformation with sustainable development goals.

Fake It Till You Make It—A Statistical Assessment of the Proportion of Fake Reviews in Closed Reputation Systems

ABSTRACT Fake reviews have become an increasingly relevant issue in electronic commerce. Regulators and platform operators have begun to take action against fake reviews through regulation and litigation. While there has emerged an ample body of research on fake reviews in open reputation systems (i.e. where everyone can write reviews), little is known about the frequency and nature of fake reviews in closed reputation systems (i.e. where the completion of a transaction is a necessary precondition for reviewing). This article assesses the frequency of fake reviews in this particular domain of the platform economy. To do so, we draw on data from Airbnb and investigate systematic differences between first and second rating score distributions, estimating the proportion of potentially fake five-star ratings using KL-divergence. In doing so, we advance the understanding of fake reviews in closed reputation systems, offering theoretical insights into review dynamics and practical strategies for detecting fraudulent behavior using score distributions and user attributes. This shows that early-on reputation is crucial for complementors to overcome the cold-start problem, and platform operators will have to think of ways to allow them to do so (e.g. reputation imports) in order not to jeopardize the overall credibility of their reputation systems.

Decision-making Optimization of Cross-border E-commerce Supply Chain based on Genetic Simulated Annealing Algorithm

This paper mainly studies the collaborative operation of a cross-border e-commerce supply chain composed of manufacturers, e-commerce platforms and foreign warehouses. Firstly, the decision models of transnational e-commerce enterprises based on decentralized, centralized, and hybrid modes are established. The sensitivity of the contract and each determining variable is analyzed using the simulation method. Through the joint contract of ”revenue sharing + volume discount,” the production efficiency of the enterprise and the logistics service of the international warehouse can be improved. The genetic algorithm combined with simulated annealing was adopted. Finally, a concrete example is given to verify the feasibility of the proposed method. The results show that the member departments can work together better under centralized decision-making compared to the decentralized management mode. Manufacturers to increase production capacity and improve the level of logistics services in overseas warehouses will help improve the profitability of cross-border e-commerce.

Conditional Potential User Mining framework via explainable surrogate models

User prediction aims to identify the user who show potential value in e-commerce platforms. Existing user prediction algorithms primarily focus on distinguishing between potential user, those likely to purchase a specific product in the future, and non-potential user, those unlikely to do so. However, these algorithms often overlook a valuable group named conditional potential user in non-potential group. Conditional potential user, initially categorized as non-potential, can convert into potential user under specific converted condition (e.g., product trial, coupon receipt, or certification attainment). Additionally, conventional user prediction models do not offer insights into the associated converted condition and provide classification results only. Furthermore, the lack of explainability in user prediction methods limits their practical utility. To tackle these challenges, this paper proposes a definitive concept for conditional potential users and introduces an innovative user prediction framework, the Conditional Potential User Mining (CPUM). Addressing the challenge of predicting conditional potential users, CPUM employs a Gold Standard Classifier to ascertain users’ intentions, thereby identifying their interest in target products under converted conditions and enabling the prediction of conditional potential users. Moreover, CPUM adopts an explainable surrogate model with an attention mechanism to boost explainability. This model is designed to mirror the decision-making capacity of the Gold Standard Classifier and provides importance explanations for different user interactions. This enables precise identification of converted conditions in conditional potential users, thus enhancing explainability. The effectiveness of this method is substantiated by experimental results derived from extensive e-commerce datasets from Alibaba and Amazon, demonstrating its cutting-edge performance and applicability.

Penerapan Algoritma Clustering untuk Segmentasi Pelanggan E-commerce berdasarkan Data Pembelian dan Aktivitas

In the current digital era, e-commerce has become one of the main pillars of global trade. With the ever-increasing amount of transaction and user activity data, e-commerce companies are faced with the challenge of understanding and managing diverse customer segments more effectively. This paper discusses the application of clustering algorithms for e-commerce customer segmentation based on purchasing data and user activity. The aim of this research is to identify homogeneous customer groups to support more targeted marketing strategies and increase customer retention. The problem faced is how to process big data originating from user transactions and activities on e-commerce platforms, as well as how to identify patterns that are useful for customer segmentation. The data used in this research includes purchase history, frequency of visits, length of time spent on the site, and interactions with certain products. The solution method applied in this research is the clustering algorithm, especially K-Means and DBSCAN. K-Means is used to group data into a predetermined number of clusters based on the Euclidean distance between data points. Meanwhile, DBSCAN is used to identify clusters with high density and separate data that is considered noise or outliers. Data preprocessing is carried out to clean and normalize the data before being applied to the clustering algorithm. Validation of clustering results is carried out using metrics such as Silhouette Score and Davies-Bouldin Index. The research results show that by applying the clustering algorithm, customers can be grouped into several segments that have similar characteristics. For example, we found groups of customers with high purchase frequency but low transaction value, as well as other groups with high transaction value but low purchase frequency. This information is very useful for companies to design more effective marketing strategies, such as special offers for customers with high transaction values ​​or loyalty programs for customers with high purchasing frequency. The conclusion of this research is that clustering algorithms can be a very effective tool in e-commerce customer segmentation, allowing companies to understand customer behavior patterns and develop more targeted and effective marketing strategies. Thus, implementing this method is expected to improve business performance and overall customer satisfaction.

The development of electronic commerce in the Republic of Moldova

The formulation of proposals for the development of e-commerce were carried out based on the research of this process on the internal and external markets of the Republic of Moldova. In the article, general scientific methods of research were used: the analysis, economic-statistical methods of research. The list of the used references is presented in the end of the work. E-commerce is a sector of the economy that includes commercial and financial transactions, business processes and other actions: advertising, sales, payment for goods. The main advantages of e-commerce are: the reduction of costs, the expansion of the target audience and the reduction of the number of intermediaries. The commercialization of goods through e-commerce platforms on the market of the Republic of Moldova registers significant increases. The article will explore the examination of the e-Commerce process in the international and local market, the studying and elaboration of proposals for the improvement of e-Commerce in the republic.

The Effectiveness of 2020 E-Commerce Rules in Protecting Consumer Rights

This paper critically evaluates the effectiveness of India’s Consumer Protection (E-Commerce) Rules, 2020 in safeguarding consumer rights within the rapidly growing digital marketplace. The 2020 rules, introduced under the Consumer Protection Act of 2019, were designed to address challenges arising from the proliferation of e-commerce platforms, including issues related to transparency, grievance redressal, counterfeit products, and data protection. The paper examines how these rules have enhanced consumer protection by mandating clear product information, establishing robust grievance mechanisms, and promoting accountability among e-commerce platforms. However, the implementation of the rules faces several challenges, such as uneven enforcement across platforms, limited consumer awareness, and difficulties in regulating cross-border transactions. Additionally, the paper explores the gaps in data privacy protections and the ongoing issues of counterfeit goods within online marketplaces. While the rules represent a significant step forward in regulating the e-commerce sector, this analysis highlights the need for continued regulatory oversight, technological innovation, and consumer education to ensure that the rules are effectively implemented and enforced. The paper concludes that although the 2020 E-Commerce Rules have made strides in protecting consumer rights, further reforms are necessary to address emerging challenges and ensure equitable consumer protection in India’s expanding e-commerce ecosystem.

Navigating The Digital Shift: Challenges And Opportunities For Traditional Retailers In India's Evolving Marketplace

The retail industry in India is experiencing a monumental shift driven by the rapid adoption of digital technologies. As e-commerce platforms, digital payment systems, and data analytics become increasingly integrated into the retail landscape, traditional brick-and-mortar stores find themselves at a crossroads. This digital transformation is not merely a technological upgrade but a fundamental change that reshapes business models, consumer interactions, and market dynamics. India, with its burgeoning internet penetration and widespread smartphone usage, presents a unique environment where digital innovation meets a diverse consumer base. The proliferation of global and local e-commerce giants such as Amazon, Flipkart, and JioMart has set new standards for customer expectations and operational efficiency, compelling traditional retailers to reevaluate their strategies (Invest India). However, the transition to digital is fraught with challenges. High costs of technology adoption, lack of digital expertise, and resistance to change are significant barriers that traditional retailers must overcome to remain competitive in the digital age

Home is best: Review source and cross-border online shopping

Electronic word of mouth (eWOM) has attracted considerable research interest in the past two decades. This paper revisits the impact of eWOM in the context of international business. Using review data scraped from AliExpress, a cross-border e-commerce platform, we show that the impact of online reviews is related to the identity of reviewers. Consumers are most affected by reviews from their home country, followed by reviews from neighboring countries, while they are not affected by reviews from strangers. This confirms the existence of home bias in the consumption of review information. In addition, the bias is more profound among consumers from countries with higher levels of uncertainty avoidance and trust. Our study is among the first to investigate eWOM in digitized international business. By discovering and reporting how consumers react to reviews with different identities, we offer actionable implications for digital platforms to improve the effectiveness of online reviews.

Intelligent Recommendation Algorithm for Product Information on E-commerce Platforms Based on Robot Customer Service Automatic Q&A

In order to enhance the shopping experience of customers and retain them, thereby increasing sales volume, the author proposes the research topic of an intelligent recommendation system for product information on e-commerce platforms based on robot customer service automatic question answering. Firstly, starting directly from the question itself, the system can provide feedback to customers by simply segmenting the questions submitted by customers and matching them with semantic templates; Secondly, the system automatically builds and updates the user’s personalized knowledge base, using this to predict user purchasing tendencies and achieve the function of recommending products to customers. The implementation of the intelligent shopping robot system has passed 365 question and answer tests on 5G mobile phone sales terms, and is feasible in the professional field. The experimental results indicate that, when the number of training corpora increased to 300, the accuracy of the system was 0.85, 0.90, and 0.98 using 100, 2003, and 300 tests respectively. Such a system is perfect for natural language processing, so we can improve the system by expanding and improving the knowledge base. The intelligent shopping robot recommendation system studied by the author is still in the analysis and demonstration stage, sincerely hope that the processing method used in this project can have reference significance for similar recommendation systems in the near future.

Optimalisasi Penjualan dan Pengelolaan Keuangan UMKM Pedagang Melalui Pengenalan Fintech dan Pemanfaatan Facebook Market Place

This service aims to assist Micro, Small and Medium Enterprises (MSME) traders in increasing sales and managing their finances through the introduction of financial technology (fintech) and the utilization of the Facebook Marketplace e-commerce platform. This service was carried out in response to the challenges faced by MSMEs in the digital era, especially in the aspects of increasing sales and efficiency of financial management. This service activity involves direct training and assistance to MSME players in Wanayasa District, Banjarnegara Regency. The stages of training activities include 1) survey 2) training and mentoring 3) results and evaluation. This training activity is an introduction to the basics of fintech, how to access and utilize fintech services for financial management, as well as marketing and sales strategies through Facebook Marketplace. The results of this activity show an increase in the ability of MSME traders to use fintech to better manage their finances, including in terms of transaction recording, cash flow management, and access to digital financial services. In addition, the merchants also succeeded in increasing the visibility and sales of their products through Facebook Marketplace.Thus, the introduction of fintech and the utilization of Facebook Marketplace are proven to support the optimization of sales and financial management of MSMEs.

IMPACT OF BLOCKCHAIN TECHNOLOGY IN THE E-COMMERCE SECTOR

Blockchain technology is considered as a significant development after the invention of the internet. Blockchain technology records the transactions on database which are encrypted and distributed over many computer networks like a digital ledger of online transactions. This technology can be utilized in the e-commerce industry to develop a decentralized online buying and selling platform. E-commerce industry presently facing many unique challenges like security measures of the e-commerce system, transparency, and trust, efficiency, etc. These challenges can be answered by the implementation of blockchain technology in the e-commerce industry. This paper discussed opportunities for using blockchain technology in the e-commerce industry. Blockchain applications and opportunities are discussed for various aspects of e-commerce like Payment, Security, Supply chain, Work automation with Smart contract, Ethical practices for transparency in e-commerce transactions. The paper seeks to explore the possible uses of blockchain technology within the e-commerce sector.

E-commerce market entry strategy, adoption and market performance: Basis for e-commerce industry synergy framework

E-commerce market entry strategy, adoption and market performance: Basis for e-commerce industry synergy framework

Christian Ethical Response to The Challenges of Digital Financial Borrowing in Nigeria

Digital financial borrowing is the money borrowed online through digital mobile applications, platforms or phones that are offered by financial lenders using the Internet. Due to the advancement in financial technology, banking and financial services and operations have been digitalized. The emergence of digital finance has rebranded banking and financial borrowing access and opportunities. People can now borrow money online, digitally and seamlessly. This development is applaudable because it eases traditional banking operations burdens and removes bottlenecks in borrowing and lending to finance business and personal needs. However, the attendant experiences from digital financial borrowing are worrisome and pose challenges to human well-being in developing economies, especially among Christians in Nigeria. Some of the experiences of digital financial borrowers are poor loan repayment, which may be due to high interest, breach of personal data policy and social shaming of defaulted borrowers by lending companies’ employees. The unvirtuous motives and characters of some borrowers, professionally unethical attitudes and loan recovery strategies are responsible for these challenges. This paper gives an overview of digital financial borrowing in Nigeria and discusses digital financial borrowing, which is characterized with features such as instant, automation, remote, consumer loans and short maturity. The paper argues that digital financial borrowing has assisted financial inclusion and contributed to Nigeria’s digital economy, it has however negatively impacted on borrowers’ personal, emotional, mental, marital, business, spiritual and moral well-being due to poor repayment or inability to repay, high interest, and social shaming of customers by digital loan officers. The paper concludes that Christians should act virtuously and ethically according to biblical instructions when dealing in financial borrowing, wisdom, honesty, godliness, discretion, patience and mutual respect are among Christian virtues to display in financial borrowing decisions, actions and relationships. It recommends that churches and church leaders should encourage financial education and literacy that enhance credit understanding and boost Christians’ financial wellness. It also recommends that Chartered Institute of Bankers of Nigeria, with other financial regulatory bodies in Nigeria should regulate the operations of lending companies and enforce acceptable professional work ethics and attitudes of digital lending companies’ employees to enhance friendly relationships with customers.

Application Development Model E-Commerce in Traditional Markets Using the TOGAF Framework

The existence of traditional markets is increasingly being eroded by the presence of online market models that already utilize various e-commerce platforms. However, the TOGAF Framework provides a ray of hope. Even though the existence of traditional markets is unlikely to disappear, if traders in traditional markets do not try to adapt to using e-commerce, it will have an impact on losing customers, losing turnover, and will even affect the acceleration of their business. Architectural design for system development in traditional market activities can provide an important picture of how to advance traditional market industries that will not be out of competition with modern markets. TOGAF (The Open Group Architecture Framework) provides a detailed method of how patterns build, manage, and implement enterprise architecture and information systems called the Architecture Development Method. Analysis using the TOGAF Framework provides an overview of how to plan, design, develop and implement information system architectures for traditional markets. The results of this design analysis are an information technology architectural design which is the basis for traditional market managers, especially in Indonesia, in advancing the business processes of traders in the market so that they are not unable to compete with modern markets but with gap analysis constraints that must really be considered with regard to internet infrastructure problems in the market, sellers who are not fully able to use technology due to age and not all forms of goods on the market can be sold through e-commerce platforms. This gap analysis will make e-commerce implementation slow to implement.

Classification of Vietnamese Reviews on E-Commerce Platforms

The research team used machine learning models to classify Vietnamese reviews on products on the e-commerce platform as positive or negative. To classify and evaluate the effectiveness of Support Vector Machine (SVM), Random Forest, Logistic Regression machine learning models on different platforms, the authors have built their own training and test data sets as well as a set of stopwords to classify Vietnamese web reviews [9]. This can then be applied to building a webapp that allows entering a link of any online products and then categorizing its user reviews, helping sellers evaluate their products/services, understand consumer behavior and make changes, improvements to the products accordingly.

Analyzing The Impact of Online Marketing on Students' Purchase Decisions on Shopee E-Commerce in Tasikmalaya, Indonesia

The study was driven by the growing trend of online shopping among students and the need to understand how digital marketing strategies impact their purchasing decisions on e-commerce platforms like Shopee. This research aims to evaluate the influence of online marketing on the purchasing decisions of students at STIE Latifah Mubarokiyah Suryalaya, in Tasikmalaya, Indonesia, specifically using the Shopee platform. Online marketing facilitates the transaction of goods and services via the Internet, providing the convenience of shopping without time and space constraints and allowing consumers to select products based on their preferences. The study employs a descriptive quantitative approach, involving 77 respondents selected through purposive random sampling. Data collection includes both primary and secondary sources, which are analyzed using simple regression, correlation analysis, determination analysis, and hypothesis testing. The findings reveal that online marketing strategies significantly influence students' purchasing behaviour on e-commerce platforms, with a correlation coefficient of 0.694 and a determination coefficient of 48.1%. This indicates that nearly half of the variability in student purchase decisions can be attributed to online marketing strategies. Moreover, the study offers new insights into how specific online marketing tactics, such as targeted advertisements and social media promotions, uniquely influence student preferences and purchasing patterns. These findings highlight the importance of personalized marketing approaches in shaping consumer behaviour. The study also suggests that further research should explore additional factors influencing consumer behaviour in e-commerce to achieve a more comprehensive understanding.

한국의 e커머스 시장 전략방향 연구: Business Model Canvas, 5Force Model을 이용한 공급망 전략 측면

Purpose: This study derives a sustainable strategic direction for K-commerce companies to respond to a threatened entry of multinational companies, mainly Chinese (C-commerce) companies, into the Korean e-commerce market. Research design, data, and methodology: The methodology includes a market approach, the Business Model Canvas, and the 5Force Model for the study period from March to July 2024. Results: The direction of Korea's e-commerce market success strategy, classified into asset type and non-asset type, is that the first is One Strength, which has the competitiveness and entry power to lead existing competitors. The second is that One Medle has the bargaining power of suppliers that can protect existing customers from conversion due to consumer benefits and seller benefits. The third is Three Weakness, which is facing the threat of new entrants, the bargaining power of buyers, and the threat of alternative products, so there are always risks. Conclusions: The implications of the “One Strength, One Medle, and Three Weakness” sector derived from Korea's e-commerce market strategic direction study are summarized into three in terms of supply chain strategy and presented in the text.