E-commerce Business Research Articles

Leveraging Transformer Model for Data-Driven Requirement Engineering: A Case Study of NLP4RE E-Commerce Business Apps in Malaysia and Indonesia

Leveraging Transformer Model for Data-Driven Requirement Engineering: A Case Study of NLP4RE E-Commerce Business Apps in Malaysia and Indonesia

Transformation of e-commerce business models in the digital economy

Purpose. Research on the transformation of e-commerce business models in the conditions of the digital economy, analysis of the main directions of changes in business processes, as well as the determination of key differences between Internet commerce, e-commerce and online commerce, substantiation of the difference in the sources of generation of added value and identification of the factors that facilitate the transition from traditional e-commerce business models to digital ones. Methodology. When conducting the research, the trends of the development of electronic commerce and the factors contributing to their transformation in the conditions of the digital economy were revealed by the method of formal analysis. Findings. This study presents an analysis of trends and factors affecting the development of digital commerce and the transformation of digital commerce business models. The directions of integration of digital technologies into business processes and strategic aspects of the implementation of digital solutions into business practice are substantiated. The key factors that contribute to the transformation of e-commerce business models into digital commerce business models are identified, in particular, in the creation and implementation of new business models that allow for effective adaptation to the conditions of the digital economy. It is found that the economic basis of transformations of business models is the sources of creation of added value. It has been proven that digital technologies, which form the basis of e-business, are carriers and main sources of added value creation, which is reflected in business monetization models. The impact of artificial intelligence on the prospects and further development of digital commerce business models is analyzed. Originality. The scientific novelty obtained as a result of this research consists in the definition and substantiation of a new factor – added value, which is the main factor influencing the transformation of e-commerce business models into a digital commerce business model, which takes place under the influence of the digital economy. The novelty of the obtained research results in terms of substantiation of added value as a factor of transformation is proven by confirming the hypothesis that the formation of e-commerce business models and their transformation into digital commerce models take place under the influence of digital sources of added value creation.

Elevating logistics performance: harnessing the power of artificial intelligence in e-commerce

PurposeArtificial intelligence (AI) usage improves e-commerce logistics efficiency. However, many actors can play significant roles, such as supply chain consistency (SCC), last-mile logistics (LML) performance and collaboration and coordination among logistics firms. This study aims to assess how SCC and LML performance mediate and collaboration and coordination moderate the relationship between AI usage and logistics efficiency.Design/methodology/approachA structured questionnaire was used to collect the data. A total of 245 valid responses were received from Indian e-commerce businesses. The data were then analysed using AMOS v25 and structural equational modelling using SPSS for regression, PROCESS macro for mediation and moderated mediation analysis.FindingsThe findings show that AI usage independently impacts logistics efficiency, with SCC and last-mile delivery performance as mediating variables. Collaboration and coordination among logistic firms are also critical moderators in enhancing AI’s efficacy in logistic operations. The study findings suggest the integration of AI into logistic operations and provide implications to managers on the urgency of fostering a collaborative and synchronised environment to utilise the full potential of AI in e-commerce businesses.Originality/valueThis study not only contributes to the field of logistics theory by presenting empirical data on the various ramifications of AI but also offers practical guidance for logistics firms, particularly those operating in developing economies, on how to strategically employ AI to enhance operational efficiency and attain a competitive advantage in the era of e-commerce logistics in the digital age.

Leveraging Artificial Intelligence in Supply Chain Execution in E-commerce

Modern perspective of consumer satisfaction has changed due to the proliferation of online businesses. E-commerce has opened up a whole new world to the consumers. The consumers can now get what they want, when they want, delivered at their doorstep. While the ease of online shopping has increased consumerism and consumer demand, it poses significant challenges for the e-commerce players as the consumers are seldom willing to shell out money for availing the convenience of doorstep deliveries. Under such circumstances, the e-commerce players are left with little choices but to significantly enhance their supply chain efficiencies through the improvement of logistics and the delivery services they offer to their customers. Artificial Intelligence or AI, as it is popularly known, is altering the ways and means of these e-commerce businesses. It is changing the manner in which supply chains are managed. Through the use of smart algorithms, data analysis, and automation, it is possible for businesses to employ AI effectively for the optimization of their supply chain management involving inventory and logistics management, demand forecasting, and customer service. This article focuses on logistics management and the application of AI to optimize costs and efficiency in first mile, middle mile and last mile delivery.

Video Generative AI in Digital Marketing: A SWOT Analysis on E-Commerce

Artificial Intelligence (AI) is reshaping the way various business processes are performed, most rapidly in digital marketing, due to its advanced computational capabilities. ECommerce companies are in advantageous position to adopt and reap the benefits of AI for many reasons including the readily available computational infrastructure and big data related to their users and processes. Meanwhile, big tech companies and startups are competing to create and improve generative AI models, that create high-definition videos based on inputs in the form of text, image or videos. The current research specifically aims to analyse the video outputs of various video generating AI models available for digital marketing purposes in ecommerce businesses and to rationally analyse how those video generative AI models benefit or affect e-commerce companies. To meet the research objectives, mixed methodologies of experimentation and content analysis were deployed. It was observed that the video outputs from the tested models were not yet suitable for digital marketing and appeared underdeveloped. Additionally, the SWOT analysis revealed advantages like low costs, alongside concerns such as intellectual property issues.

Conceptualizing the Implications of Artificial Intelligence (AI) Tools and Personalization Marketing on Consumer Purchase Intention: Insights from the Malaysian E-Commerce Market

Artificial intelligence (AI) has emerged as a powerful tool, enabling online retailers to offer highly personalized shopping experiences tailored to individual preferences and behaviors. As e-commerce continues to grow in Malaysia, understanding the influence of AI and personalization marketing on consumer purchase intentions has become increasingly important for businesses seeking to remain competitive. However, the rapid adoption of AI also raises concerns about data privacy, ethical AI usage, and compliance with emerging data protection regulations, such as Malaysia’s Personal Data Protection Act (PDPA). This study aims to explore the potential impact of artificial intelligence (AI) and personalization marketing on consumer purchase intention within the Malaysian e-commerce market. By reviewing previous literature and theoretical frameworks, the study explores how the use of AI tools including predictive analytics automation, and personalization experiences might influence consumer behavior in online shopping environments. The study adopts a quantitative approach, in which quota sampling will be used for the participant selection. A self-administered questionnaire with a five-point Likert scale will be employed to gather data from e-commerce users in Malaysia. The findings from this study have important implications for both e-commerce businesses and policymakers in Malaysia. For businesses, understanding which aspects of AI and personalization most influence consumer purchase intentions can help them strategically implement these technologies to enhance customer engagement and drive sales. For policymakers, the study highlights the need to consider ethical and legal issues, such as data privacy and policy issues, in the growing use of AI in the e-commerce market.

Intelligent E-commerce under the Trend of Integration of Artificial Intelligence and E-commerce: A Case Study of Alibaba International Station

Abstract: China has fully entered the era of digital economy, and undoubtedly, the e-commerce industry needs to keep pace with the times and evolve into a new stage of development: integrating artificial intelligence with e-commerce. Nowadays, an abundance of new productivity tools have unveiled new opportunities for the e-commerce industry. This study focuses on Alibaba International, a premier global digital trading platform, to illustrate the applications of artificial intelligence tools in e-commerce, examine both the positive and negative impacts of these tools on e-commerce, and suggest strategies for enhancing e-commerce Operation Management. The aim is to offer enlightenments for small and medium-sized cross-border e-commerce businesses. Through this case analysis, it can be understood that intelligent e-commerce has provided many conveniences for the e-commerce industry, but also faces a series of challenges, such as AI generated false or infringing content, and increased operational management difficulties. In this situation, e-commerce companies should take strengthening the cultivation of intelligent talents as a guarantee, focusing on customer experience and valuing personalized product needs as advantages, and improving operational management efficiency through the reasonable use of favorable policies to bring profits to the enterprise.

The Role of Insecurity in Shaping Consumer Purchase Intentions: Mediating Effects of Perceived Usefulness and Ease of Use in Live Commerce

Live commerce platforms facilitate real-time interactions between sellers and buyers, but challenges related to consumer uncertainty can negatively impact their intention to purchase. This study examines how uncertainty affects perceptions of usefulness, ease of use, and the intention to purchase. Additionally, it investigates whether perceived usefulness and ease of use serve as mediators in these relationships. The research adopts a quantitative methodology, collecting data from 150 respondents in Banjarmasin using a questionnaire based on a 5-point Likert scale. The analysis employed Structural Equation Modeling with Partial Least Squares (PLS-SEM) to understand the interrelations among the variables. The findings reveal that insecurity does not significantly impact perceived usefulness, ease of use, or purchase intention, and these perceptions do not act as mediators in the relationship. However, both perceived ease of use and perceived usefulness have a strong and positive effect on purchase intention. These results underscore the need to focus on technology's ease of use and functionality to encourage purchasing behaviour, even when insecurity is present. This suggests that e-commerce businesses should improve their platforms' functional aspects and user-friendliness to enhance consumer engagement. Furthermore, the study encourages future research to delve into more profound psychological aspects and beliefs surrounding consumer insecurity that may influence decision-making in live commerce environments.

THE IMPACT OF E-COMMERCE ON SMALL BUSINESS

The article provides a review of scientific literature in order to generalize the methodology for defining the concept of "electronic commerce". The main trends in the field of e-commerce in small business are characterized. The data on the development of the e-commerce market are analyzed and the following is emphasized: in the number of purchases from mobile devices has increased; creation and widespread use of social media pages is a key factor in the development of e-commerce by entrepreneurs. The advantages and disadvantages of using electronic commerce by small businesses are systematized. In given article authors shine a problem an analysis he shift toward online transactions and digital platforms has been accelerated to adapt to the changing business landscape. Through the review of scientific literature, a comprehensive understanding of e-commerce's impact on small businesses has been highlighted. The article has delved into the main trends shaping the e-commerce landscape for small businesses, emphasizing the significant increase in purchases made through mobile devices. This trend underscores the importance of having a mobile-friendly online presence for entrepreneurs to effectively reach their target audience. E-commerce is a tool through which firms can attain competitive advantage. Therefore it is interesting to further explore how firms exactly go about implementing e-commerce systems, and which path firms take from e-commerce idea generation up to realization of e-commerce success.To comprehensively understand the impact of e-commerce on small businesses, it is crucial to conduct a multiple case studies analysis using a qualitative research design. Small businesses experience challenges before, when, and after integrating e-commerce into their operational structures internally and externally, such as perceiving the technology as an unnecessary business cost, lack of resources to fund e-commerce infrastructure, and absence of managerial support to adopting a radical approach to innovation and growth of the business. The analysis of the impacts of e-commerce on small businesses helps to determine the opportunities and challenges in the business operation process.

IMPACT OF ARTIFICIAL INTELLIGENCE ON E-COMMERCE:"A STUDY OF CONSUMER BEHAVIOR"

Artificial Intelligence (AI) has transformed the e-commerce landscape, influencing consumer behavior significantly. This study aims to explore the various ways AI impacts e-commerce, utilizing numerical data to analyze consumer preferences, purchasing patterns, and overall shopping experiences. The findings reveal both advantages and disadvantages, providing a comprehensive overview of AI's role in shaping modern consumer behavior. This study examines the transformative effects of artificial intelligence on E-commerce and consumer preferences and purchasing patterns have evolved. this paper analyzes various numerical data, identifies key trends, and discusses the advantages and disadvantages of AI in E-commerce. In online shopping enterprises, AI technology has been widely used to provide accurate and fast personalized consumer services. This research demonstrates the use of AI technology in the e-commerce business, specifically online enterprises, to determine different effects. The study was conducted in Jordan and involved about 230 participants. The study evaluated different impacts of AI, such as e-payment and stimulating consumers' sentiments. The study used the Stimulus–Organism–Response model (SOR) empirical model, which states that the examination of human processes differs from that of the machine assessment. The model classified the AI technology experienced by the customers' when they visit online to do purchasing. Online purchasing behaviors can be influenced by insight, accuracy, and interaction experience. Also, the perceived value was used as a mediating variable from the prospects of perceived hedonic and utility value. The research integrated empirical research models such as SEM and SPSS to analyze the data on the effects of three-dimension. The results indicated that the AI technology accuracy, interactive experience, and insight significantly affected customers' perceived hedonic and utilitarian values. KEYWORDS: AI in consumer behavior, Artificial Intelligence etc

Enhancing Customer Experience through Sentiment Analysis and Natural Language Processing in E-commerce

The research explores the use of sentimental analysis and natural language processing (NLP) in e-commerce applications to enhance customer experience. It identifies a positive correlation between customer reviews and products, overcoming previous limitations in language training and customer loyalty. The study aims to increase e-commerce business sales by 15.4%, resulting in a 15% increase in business profit and a 1% increase in positive recommendations. The study underscores the potential of these technologies in enhancing consumer satisfaction, brand loyalty, and e-commerce performance.

The Influence of Social Media Strategy, Customer Interaction, and Word of Mouth on E-commerce Purchase Intention

This study investigates the effects of social media strategy, customer interaction, and word of mouth on e-commerce purchase intention. Utilizing a quantitative approach, data were collected from 360 respondents using a structured questionnaire with a Likert scale ranging from 1 to 5. The analysis employed Structural Equation Modeling with Partial Least Squares (SEM-PLS 3) to assess the relationships among the variables. The findings reveal that a well-implemented social media strategy significantly enhances customer interaction and positively influences word of mouth, which in turn drives purchase intention in the e-commerce sector. These results underscore the importance of strategic social media engagement and effective customer communication in fostering consumer intent to purchase online. The study provides valuable insights for e-commerce businesses seeking to optimize their marketing strategies and enhance customer engagement.

Leveraging gamification to enhance persuasive behaviour and streamline online product returns: an approach grounded in multiple case studies

Purpose The study identifies barriers all stakeholders face in the returns management process. The pressing issue of online product returns significantly erodes the net profit margins, demanding urgent action. Existing returns management systems are often complex, time-consuming and costly, failing to address this issue effectively. In this regard, persuasive technologies like gamification can effectively influence behaviour and enhance motivation towards reducing return by striking a balance between psychological and behavioural factors. Therefore, the study proposes a framework that combines the theory of planned behaviour and Octalysis to identify intentions to reduce product return rates in the e-commerce business. Design/methodology/approach A qualitative exploratory research design using a multiple case study-based approach with in-depth interviews conducted with 96 varied stakeholders was used to provide insights into the behavioural aspects for reducing return rates in e-commerce. Findings The results reveal three facets of effective returns management in e-commerce. Customers and delivery partners prioritize return processes, policies and rewards, emphasizing efficiency. Meanwhile, mid- and strategic-level employees are optimistic about return process enhancements. Interdepartmental integration and cross-functional communication are found to be vital, suggesting the need for a gamified framework in returns management. Originality/value This research enriches the returns management literature on gamification solutions and responds to the need for theoretical anchoring by applying the theory of planned behaviour at the organizational level to improve efficiency and customer centricity in the return process.

Segmentasi Pelanggan E-Commerce Menggunakan Fitur Recency, Frequency, Monetary (RFM) dan Algoritma Klasterisasi K-Means

The rapid growth in the e-commerce industry demands the development of smarter and more focused marketing strategies. One approach that can be applied is customer segmentation using various features such as Recency, Frequency, and Monetary (RFM), along with machine learning-based clustering methods. The objective of this study is to design and develop a web-based e-commerce customer segmentation application using a combination of RFM features and clustering methods. The study proposes the K-Means algorithm and compares it with K-Medoids and Fuzzy C Means using publicly available e-commerce datasets. Experimental results showed that the K-Means algorithm outperformed K-Medoids and Fuzzy C Means (FCM) based on the Silhouette Score of 0.67305, Davies Bouldin Index of 0.51435, and Calinski Harabasz Index of 5647.89. Through analysis and testing, the designed application has proven effective in grouping customers into relevant segments. These segments are divided into three categories: Loyal, Need Attention, and Promising, visualized in a web-based application dashboard using Streamlit. The developed application allows e-commerce business owners and users from the business, management, and marketing divisions to categorize customers based on transaction data. The results of this study are expected to provide valuable insights to e-commerce management and marketing professionals who are facing increasingly fierce competition.

The Influence of The Big 5 Personality, Financial Perceptions, and External Factors on Impulsive Buying Tendencies in Live Streaming

The digital era has significantly transformed the behavior of Indonesian consumers, particularly with the emergence of shopping trends through live streaming on e-commerce platforms. This study investigates the influence of the Big Five personality traits, financial perception, and external factors on the tendency for impulsive buying during live streaming. By integrating theories from consumer behavior and psychology, this research explores how self-control, money availability, economic well-being, time pressure, and sales promotions affect the tendency for impulsive buying. Using an online survey distributed among Indonesian consumers, this study provides insights into how these factors interact in the context of digital shopping during live streaming purchases. The findings aim to help e-commerce businesses optimize their sales strategies and offer recommendations to enhance consumer satisfaction. The results show a negative influence between self-control and the tendency for impulsive buying, with conscientiousness and extraversion personality traits showing significant effects on impulsive buying. The perception of money availability has a positive influence on the tendency for impulsive buying. From an external factors perspective, sales promotions positively influence purchase intentions, while time pressure negatively affects buying intentions or the tendency for impulsive buying. These insights aim to assist digital marketers and e-commerce businesses in optimizing their sales strategies and improving consumer satisfaction.

INFORMATION SECURITY AND THE CONTINUAL USAGE OF E-COMMERCE PLATFORMS: A CASE OF GHANA

Objective: This study investigates the impact of information security and trust on continued e-commerce usage in Ghana, where online commerce has become essential despite growing cyber threats. Theoretical Framework: Social exchange theory was used to explain how individuals form trust in social interactions. It helps to reveal how people weigh relationship rewards and costs, navigate power dynamics, and make choices. Method: Out of 117 collected responses, 100 were valid for analysis. Partial Least Squares-SEM (PLS-SEM) was used for structural equation modeling, following the "10-times rule" for minimum sample size. Results and Discussion: The research demonstrates that Information Security significantly enhances continual usage and directly impacts consumer trust. Also, we found that, trust serves as a mediator between information security and continual usage. Further, the study reveals that ICT skills play a key mediating role in the relationship between trust and continual usage. The findings highlight the importance of prioritizing information security, implementing user-friendly security measures, and offering training to improve users’ ICT skills. Research Implications: These insights have practical implications for e-commerce businesses, policymakers, and individuals. It emphasizes the necessity of robust information security measures to build trust and encourage continual usage among Ghanaians. Originality/Value: The study adds to existing literature by underscoring the essential role of Information Security in cultivating Ghanaian consumers trust and loyalty in the e-commerce environment.

An Evolutionary Game-Based Regulatory Path for Algorithmic Price Discrimination in E-Commerce Platforms

With the advent of big data, the swift advancement of diverse algorithmic technologies has enhanced the transaction efficiency of the e-commerce business. Nevertheless, it is crucial to acknowledge that e-commerce platforms might employ algorithmic technology to enforce differential pricing for various consumers with the aim of maximizing profits, thus infringing upon the lawful rights and interests of consumers. This paper focuses on the algorithmic price discrimination commonly observed on e-commerce platforms. To effectively regulate this behavior, the paper utilizes evolutionary game theory (EGT) to analyze the strategies employed by e-commerce platforms, consumers, and market regulators to achieve stability. This research employs a real-life situation and utilizes parametric simulation to visualize and analyze the process and outcomes of the three-party evolutionary game. The results demonstrate the credibility and feasibility of the article’s findings. Based on our research, we have reached the following findings: During the process of evolution, the strategic decisions made by the game participants from the three parties will mutually impact each other, and various elements exert varying degrees of influence on the strategic choices made by the game participants from each party. Collaborative governance can enable consumers and market regulators to regulate the discriminatory pricing behavior of e-commerce platforms effectively. This article offers valuable insights into the governance of violations in the e-commerce sector based on robust data and model research.

Predicting Consumer Behavior in E-Commerce Using Decision Tree: A Case Study in Malaysia

Understanding and predicting consumer behavior will help e-commerce businesses improve customer satisfaction and devise better marketing strategies. This study is intended to explore the use of decision tree algorithms in predictions of consumer purchase behavior in the e-commerce platform in Malaysia. Comparing the performances of J48, Random Tree, and REPTree decision tree models using an online shopper dataset collected by surveying 560 Malaysians, on various aspects like accuracy, precision, recall, and F1 score. Results indicate that the highest accuracy has been achieved with the Random Tree algorithm, outperforming J48 and REPTree. The results will, therefore, form the basis upon which e-commerce can restrategize its marketing programs for better customer engagement. This is an important study in that it shows the efficacy of applying a decision tree algorithm to understand customer behavior in the context of Malaysia and adds to the growing body of knowledge in predictive analytics in e-commerce.

E커머스 시장에서 중국 기업의 성공적 진출 요인 연구: 글로벌 공급사슬 전략 측면

This paper was conducted over a period of about three months from April to June 2024, and among Chinese C-commerce companies AliExpress, TEMU, and Shein that entered the global e-commerce market and the K-commerce market in Korea, in April 2024, a year later than April 2023, we analyzed the case of TEMU, which is rapidly encroaching on the K-commerce market by securing the highest number of users of 5.81 million. The purpose of this study is to derive the success factors of C-commerce companies in the global e-commerce market through case analysis. The research methodology used domestic and foreign reports related to the research target company, market research methods such as domestic and foreign Internet sites, and Brain Storming, Delphi Method, PESTLE Methodology, and SWOT Analysis verified in consulting and research. As a result of the study, 19 factors for C-commerce company TEMU’s successful entry into the global e-commerce market were derived, and they were simplified into 13 and grouped by ranking. The first priority grouped was the marketing sector, the second priority was the investment sector, the third priority was the minimum risk sector, and the fourth priority was the customer satisfaction sector. In addition, TEMU’s ultra-low-cost e-commerce business model, which can only be found in this paper, and the ranking model of factors for successful entry into the global e-commerce market based on the efficiency of execution based on corporate resources and capabilities and the urgency to determine the fullness of business advancement were another research achievement that added great reward.

Implementation of the Fuzzy C-Means Clustering Method in Grouping Provinces in Indonesia based on the Types of Goods Sold in E-commerce Businesses in 2022

Implementation of the Fuzzy C-Means Clustering Method in Grouping Provinces in Indonesia based on the Types of Goods Sold in E-commerce Businesses in 2022