Consumer E-commerce Research Articles

Platform supply chain pricing and financing: Who benefits from e-commerce consumer credit?

E-commerce (EC) consumer credit has stimulated consumption vitality which fuels regional economic growth. Platforms that provide credit services can adjust their charge, however, the impact of such behavior on all participants remains unexplored. Thus, we construct a game model for the platform supply chain (PSC) consisting of third-party seller—EC platform—strategic consumers, to analyze the pricing strategies and examine who ultimately benefits from the credit. We find the credit increases the product price but not necessarily the platform charge. Whether the participants can benefit from the credit is contingent upon parameter conditions. For the transaction of mid-to low-end products, the seller, the consumers and the whole PSC can profit from the credit, but it is ambiguous for the platform. When the dishonesty aversion coefficient of consumers is high, the platform has more incentives to provide credit; for the seller and the consumers, they are more willing to participate in credit services when this coefficient is moderate. Social welfare is higher for the consumers with higher dishonesty aversion. Our extensive analyses show that, for one thing, the heterogeneity in dishonesty aversion can expand the profit range of consumer credit for both the consumers and the seller, nevertheless, it weakens the platform's motivation to supply credit; for another, the diversity of consumer payments has a non-monotonic effect on the utilities or profits of participants, but a lower credit payment ratio discourages the credit supply for low-end product transactions, while the seller and the consumers can benefit from mid-to low-end product transactions due to payment diversity.

온라인 의류 쇼핑몰에서의 반품에 영향을 미치는 요인에 관한 연구

Currently, the e-commerce market has continued to grow significantly for more than 10 years, and the transaction volume is further increasing in the face of the special situation of COVID-19. Fashion(28.2%) accounted for the highest percentage of online shopping transaction amount by product group in 2020. Also, as a result of analyzing the cases of consumer damage received in 2016, among the 26 product groups, ‘clothes and textile personal items’ with 2,442 cases(28%) were the most damaging to domestic e-commerce consumers. Return rate management is an important performance management indicators in the e-commerce industry because the entire process, including a decrease in satisfaction for consumers, return consultation by a customer center agent, and the cost handling process for receiving and collecting returns through a courier company are all counted as expenses. regarded as one of the indicators.<BR> In this paper, the factors affecting returns were studied by targeting customers who have purchased and returned clothing products from online fashion shopping malls. A survey was conducted on 184 online shopping mall users, and 5 factors(difference between picture and reality, change of mind, defective delivery, defective quality and defective service) influencing the return of clothing products through exploratory factor analysis were found that reliability and validity were secured through the confirmatory factor analysis process. It is judged that more data collection and research on the relationship between returns and customer satisfaction are needed in the future.

Exploring energy-saving refrigerators through online e-commerce reviews: an augmented mining model based on machine learning methods

PurposeBased on climate issues and carbon emissions, this study aims to promote low-carbon consumption and compel consumers to actively shift to energy-saving appliances. In this big data era, online reviews in social and electronic commerce (e-commerce) websites contain valuable product information, which can facilitate firm business strategies and consumer comparison shopping. This study is designed to advance existing research on energy-saving refrigerators by incorporating machine learning models in the analysis of online reviews to provide valuable suggestions to e-commerce platform managers and manufacturers to effectively understand the psychological cognition of consumers.Design/methodology/approachThis study proposes an online e-commerce review mining and management strategy model based on “data acquisition and cleaning, data mining and analysis and strategy formation” through multiple machine learning methods, namely, Bayes networks, support vector machine (SVM), latent Dirichlet allocation (LDA) and importance–performance analysis (IPA), to help managers.FindingsBased on a case study of one of the largest e-commerce platforms in China, this study linguistically analyzes 29,216 online reviews of energy-saving refrigerators. Results indicate that the energy-saving refrigerator features that consumers are generally satisfied with are, in sequential order, logistics, function, price, outlook, after-sales service, brand, quality and space. This study also identifies ten topics with 100 keywords by analyzing 18 different refrigerator models. Finally, based on the IPA, this study allocates different priorities to the features and provides suggestions from the perspective of consumers, the government and manufacturers.Research limitations/implicationsIn terms of limitations, future research may focus on the following points. First, the topics identified in this study derive from specific points in time and reviews; thus, the topics may change with the text data. A machine learning-based online review analysis platform could be developed in the future to dynamically improve consumer satisfaction. Moreover, given that consumers' needs may change over time, e-commerce platform types and consumer characteristics, such as user profiles, can be incorporated into the model to effectively analyze trends in consumers' perceived dimensions.Originality/valueThis study fills the gap in previous research in this field, which uses small-sample data for qualitative analysis, while integrating management ideas and proposes an online e-commerce review mining and management strategy model based on machine learning methods. Moreover, this study considers how consumers' emotional and thematic preferences for products affect their purchase decision-making from the perspective of their psychological perception and linguistically analyzes online reviews of energy-saving refrigerators using the proposed mining model. Through the improved IPA model, this study provides optimizing strategies to help e-commerce platform managers and manufacturers.

Determining Factors of Purchase Intention in Personalized Website Context for Indonesian Consumers

Personalized services can increase customer satisfaction, encourage emotional consumers, help consumers choose a product, and build relationships between service providers and consumers. This study combines the variables embedded in Technology Acceptance Model (TAM), Theory Planned Behavior (TPB), shopping experience, enjoyment, and trust in a research framework model, to examine factors determiningindividual purchase intentions with personalization features on online shopping sites. This study uses primary data obtained by the online survey method. The number of samples analyzed in this study is 303 e-commerce consumers in Indonesia. This study proves that consumer purchase intentions on websites with personalization are positively and significantly related to three factors: the perceived ease of use, perceived enjoyment, and trust. Furthermore, the results also show that the utilitarian value is more influential on these factors than the hedonic value. Further implications of the research results are also discussed in this paper.

MODA ÜRÜNLERİNİN E-TİCARETİNDE KULLANILAN UZMAN SİSTEMLERİN MÜŞTERİLERDEN TOPLADIKLARI VERİLERİN ANALİZİ

In this research; It is aimed to determine what information the fashion expert systems, which offer suggestions to consumers in e-commerce, collect directly from the consumer in order to identify the consumers and determine their clothing and purchasing behavior. In addition, it is also among the aims of the research to reveal whether there are significant relationships between the various characteristics of businesses and the number of questions they ask customers. It is a survey model research. The surveys were made over the internet. 30 enterprises selected by judgmental sampling from the research universe constituted the sample of the research. Research data were collected using observation forms. Collected data are classified. The frequency and rates of data included in the classifications in the sample were determined. Significant differences were sought between the number of questions asked by e-commerce businesses and some other features. It was observed that the data requested by fashion expert systems directly from their customers were collected in 3 main classes. These are; data on describe personal characteristics, data on customer's purchasing behavior and data on determine the customer's dressing habits and style. However, it was concluded that the data for determining the purchasing behavior, dressing habits and styles of the customer were directly requested from the customer by a few expert systems.

Determinants of e-commerce satisfaction: a comparative study between Romania and Moldova

PurposeThe purpose of this article is to highlight the relevance of the factors that influence the satisfaction of e-commerce consumers in Romania and Moldova. The study aims to clearly define the main influence factors, so that the marketing managers of the online stores can adopt scientific well-founded decisions.Design/methodology/approachThe paper opted for a study including a large sample of 399 respondents from two countries. For the analysis of the factors influencing the e-commerce satisfaction, multiple linear regression analysis was implemented, and their differentiation within the two countries was highlighted by multivariate analysis of variance.FindingsThe research conducted and the results obtained show that there is a differentiation of the factors that influence the level of satisfaction of e-commerce users in Romania and Moldova.Research limitations/implicationsThe research is still limited in terms of population studied to only two countries: Romania and Moldova. Although the study is intended to be exhaustive by analyzing no less than 11 factors influencing the satisfaction generated by e-commerce, it is still limited to this group of representative factors. Another limitation has to do with the limited number of demographic variables the authors have included.Practical implicationsBased on the results, the managerial implications for e-commerce companies that want to uniquely address consumers in Romania and Moldova are related to the decisions of marketing and sales managers who must allocate budgets and resources to improve the eight aspects highlighted in the paper. Also, the e-commerce companies should not allocate resources for the implementation of functionalities such as in-app after sales services, the possibility to cancel an order or the live consultant support feature, because these aspects do not influence the satisfaction of e-commerce consumers in Romania and Moldova.Originality/valueThis paper is the first in the scientific literature that implements a comparative study on the influence factors regarding the e-commerce satisfaction in Romania and Moldova. Also, it is important to mention that the present study is an exhaustive one because it includes many influence factors that were analyzed separately in the previous research papers from literature review.

An Enhanced Cascading Model for E-Commerce Consumer Credit Default Prediction

As an important global policy guide to promote economic transformation and upgrading, the upsurge of E-Commerce has been continuously upgraded with continuous breakthroughs in information technology. In recent years, China’s e-commerce consumer credit has developed well, but due to its short time of production and insufficient experience for reference, credit risk, fraud risk, and regulatory risk continue to emerge. Aiming at the problem of E-Commerce Consumer Credit default analysis, this paper proposes a Fusion Enhanced Cascade Model (FECM). This model learns feature data of credit data by fusing multi-granularity modules, and incorporates random forest and GBDT trade-off variance and bias methods. The paper compares FECM and gcForest on multiple data sets, to prove the applicability of FECM in the field of E-commerce credit default prediction. The research results of this paper are helpful to the risk control of financial development, and to construct a relatively stable financial space for promoting the construction and development of E-Commerce.

Influencing Factors of Cross-Border E-Commerce Consumer Purchase Intention Based on Wireless Network and Machine Learning

In recent years, with the continuous development of Internet technology and the deepening of economic globalization, cross-border e-commerce has become a new international trade model and an important growth point of foreign trade. With the popularity of international trade, domestic consumers have a deeper understanding of foreign products and brands and willingness to purchase, but at this stage, cross-border e-commerce transactions are not as close to domestic online shopping, and a few have business opportunities. PortUnity is the first among overseas consumers and some avant-garde consumers with a sense of consumption. Most people have not yet reached real cross-border e-commerce, so cross-border e-commerce has broad development potential on a global scale. As a high-tech field, cross-border e-commerce has few relevant theories and literature. Therefore, this article aims to explore the influencing factors of consumer purchase intention of cross-border e-commerce based on a wireless network and machine learning and to provide decision support for the management and operation of e-commerce in order to promote the better development of cross-border e-commerce. This article analyzes the influencing factors of consumers' intention in cross-border e-commerce shopping by combining literature research and empirical research. With the support of wireless networks and machine learning, perceptual-based ease of use and perceived usefulness of the original TAM, the individual influencing factors of cross-border e-commerce consumers' purchase intention and e-commerce platform factors are summarized according to the characteristics and technology acceptance model of cross-border e-commerce. In this questionnaire survey, the author fully explored the survey value of each respondent, and all the 100 questionnaires were successfully recovered, with a 100% utilization rate of data. The research results of this article show that in addition to the originally perceived usefulness and perceived ease of use, consumers' income level, education level, age, gender, service, safety index and price of cross-border e-commerce platform, and other factors also affect the cross-border consumption frequency of consumers.

Understanding E-Commerce Consumers' Repeat Purchase Intention: The Role of Trust Transfer and the Moderating Effect of Neuroticism.

The dominant position of e-commerce is especially being articulated in the retailing industry once again due to several constraints that the world faces in the COVID-19 pandemic era. In this regard, this study explores the significant role of trust transfer (from offline to online) and the moderating effect of consumers’ neurotic traits in the framework of trust-satisfaction-repurchase intention in the e-commerce context based on a survey with 406 Korean e-commerce consumers. Moreover, a prediction-oriented segmentation (POS) technique combined with structural equation models (SEM) was utilized to reveal consumers’ probable hidden heterogeneous characteristics. The outcomes of the global model SEM analysis indicate that offline-online trust transference occurs in e-commerce, and the conveyed trust significantly influences satisfaction and consumers’ repeat purchase intention through satisfaction. Neuroticism also has significant positive effects on trust transfer in the global model. However, results in three subgroups generated by POS show heterogeneous characteristics that considerably differed from the global model test results. The implications from this study will be beneficial to field practitioners in the e-commerce industry in addressing the importance of trust transfer, negative neurotic traits as well as heterogeneous aspects of consumers.

Perlindungan Konsumen Bagi Pembeli Dalam Transaksi Di Platform E-Commerce

The ease of access to the Internet has increased the number of e-commerce consumers for reasons including practicality, easy-to-use payment systems, time efficiency, and the many preferential prices of online businesses. This is for many reasons. However, considering the number of online companies, behind all the conveniences and benefits provided, there is another concern that online companies are responsible for e-commerce consumers. In the context of the current Indonesian consumer protection law (namely Law Number 8 of 1999 concerning Consumer Protection), the rights and obligations of consumers and business actors have been clearly and firmly regulated. The rights and obligations of consumers are regulated in Articles 4 and 5 of Law Number 8 of 1999, while the rights and obligations of commercial actors are regulated in Articles 6 and 7 of Law Number 8 of 1999.

Factors Affecting Chinese Consumers’ Impulse Buying Decision of Live Streaming E-Commerce

From the perspective of consumers, this research studied four factors including price promotion, time pressure, interpersonal interaction and visual appeal influencing the impulse buying decision of live streaming e-commerce consumers in China. This research used a quantitative design by developing questionnaires to collect data through the convenience sampling approach from 477 Chinese users who has live streaming shopping experience in social commerce platform Taobao.com. within the past 1 year in Kunming, City. Structural Equation Model (SEM) was used to analyze the data and the hypotheses accordingly. The results confirmed that price promotion, time pressure (promotional time limit, perceived opportunity cost), interpersonal interaction (consumer-streamer interaction, consumer-consumer interaction) and visual appeal these six factors have a significantly positive effect on consumer impulse buying decision. Meanwhile, perceived risk was found negatively related to consumer impulse buying decision. Besides, price promotion and visual appeal played the most important role in influencing consumer impulse buying decision of live streaming than any other factors. Additionally, the results also show that the promotion, the perception of opportunity cost, the interpersonal interaction (the interaction between consumers and streamers, the interaction between consumers), and the visual appeal all have a significant negative impact on consumers&amp;#39; perceived risk. However, for time limit of time pressure, our research hypothesis that promotion time limit has a significant negative effect on consumers&amp;#39; perceived risk has not been verified. Finally, perceived risk was found plays a mediating role in the relationship between price promotion, perceived opportunity cost, interpersonal interaction, visual appeal and impulse buying decision. However, it did not play a mediating role in the effect of promotion time limit on impulse buying decision. The findings suggest that managers and merchants of live streaming e-commerce should make a reasonable price promotion plan and provide good visual experience for consumers, at the meantime, strengthen interpersonal interaction and try to reduce the purchase risk of consumers.

Application Analysis of Computer Technology in E-Commerce Network Consumption Interaction

As companies pay more attention to online marketing, e-commerce has emerged, and it has quickly become the fashion consumers want, and more and more consumers have joined the online market. This article aims to study the application and analysis of computer technology in e-commerce network consumption interaction. The premise of this article is to analyze the classification requirements of computer marketing data in the e-commerce sector, and introduce the application of computer technology in e-commerce consumption in detail, and analyze the interactive role of computer technology in e-commerce consumption. This article defines the behavior of online consumers, and puts forward an e-commerce service quality relationship model, cases, and mathematical statistics for application model experiments. The experimental results in this paper show that the correlation coefficients between the six measurement elements of e-commerce service quality and the attitudes of online consumers are all positive. Among them, security and online consumer attitudes are significantly correlated at the p-value of 0.05.

UTILITARIAN SHOPPING VALUE AND HEDONIC SHOPPING VALUE TO IMPROVE CUSTOMER SATISFACTION AND REPURCHASE INTENTION ON E-COMMERCE BUSINESS

This study aims to examine and analyze the relationships between motivation shopping value, repurchase intention, and customer satisfaction on Lazada Indonesia’s ecommerce consumers in Malang City. The population of this research is Lazada Indonesia consumers who are of productive age (19-34 years old) in Malang City and the number of samples obtained following the research criteria is 100 correspondents. Sample selection is done by the non-probability sampling technique with the purposive sampling method. The research instrument used was a questionnaire that was analyzed using smartPLS 2.0 software. The results of this study indicate that utilitarian shopping value and hedonic shopping value have a direct effect on customer satisfaction and repurchase intention. Meanwhile, indirectly hedonic shopping value did not affect repurchase intention through customer satisfaction.

Research on consumer trust measurement model for agricultural products e-commerce based on D-S evidence theory

ABSTRACT This paper designs a consumer trust measurement model of agricultural e-commerce based on D-S evidence theory for improving the accuracy of consumer trust measurement of agricultural products e-commerce. First of all, the index system of consumer trust of agricultural products e-commerce was constructed. Then, the two sides of the transaction were divided into direct and indirect trust models. Secondly, according to the calculation results of direct trust, combining with redistributive conflict evidence, weight coefficient, time decay and confidence, indirect trust was calculated. Eventually, the comprehensive trust degree of agricultural e-commerce consumers was calculated based on D-S evidence theory. The results show that the model designed in this paper has good application effect and accurately measure consumer trust.

Optimization algorithm and simulation of supply chain coordination based on cross-border E-commerce network platform

With the rapid development of cross-border e-commerce, the improvement of consumer satisfaction has become the focus of cross-border e-commerce platform optimization. Relying on advanced algorithm technology, it can realize the accurate and efficient matching between massive information and users, which is conducive to improving the user experience. Based on the consideration of consumer satisfaction, this paper constructs a dual channel supply chain composed of cross-border suppliers, cross-border e-commerce enterprises, retailers and consumers and studies the revenue and cost sharing contract of the supply chain under the conditions of centralized decision and decentralized decision. The research shows that cross-border e-commerce enterprises can choose to form revenue and expenditure sharing contracts through online and offline channels, optimize decentralized decision-making, and achieve win–win cooperation among supply chain entities.

Implementation of E-Commerce Crime Law Enforcement at the West Nusa Tenggara Regional Police

This study aims to analyze the implementation of e-commerce criminal law enforcement in the NTB police institution related to how the law enforcement of e-commerce crime in the NTB Regional Police agency and how the legal protection of e-commerce consumers in the NTB Regional Police agency. Through empirical legal research related to law enforcement of e-commerce crimes in the NTB Regional Police. Based on the statutory approach, conceptual approach, and sociological approach to law. The legal basis for law enforcement of the NTB police e-commerce crime is the Criminal Code and Law Number 19 of 2016 concerning Electronic Information and Transactions. Enforcement of criminal law against e-commerce in article 378 of the Criminal Code, the penalty is too light, so the police apparatus uses article 28 paragraph (1) and article 45A paragraph (1) of Law number 19 of 2016 concerning Electronic Information and Transactions. In e-commerce crime, the police have difficulties such as difficulty finding evidence, finding anonymous accounts and electronic identities. In addition, the NTB Police agency does not have the authority to intercept and block accounts used by e-commerce criminals. The NTB Regional Police's legal protection measures for consumers include conducting checks at internet cafes, collecting evidence related to crimes, tracking related crimes, confiscating electronic evidence, disclosing (blocking bank accounts) or detaining based on preliminary evidence or so-called evidence enough.

Differentiation of E-commerce Consumer Approach by Product Categories

Differentiation of E-commerce Consumer Approach by Product Categories

The role of e-satisfaction, e-word of mouth and e-trust on repurchase intention of online shop

The purpose of this study was to analyze the relationship between E-Satisfaction, E-Word of Mouth and E-Trust on Repurchase Intention of Online Shop. The approach in the research used is a quantitative approach using PLS-SEM SmartPLS software as a data processing tool. In this study, the data collection technique was carried out using an online questionnaire which was distributed to 150 respondents’ consumers of online shops. Sampling system with snowball sampling method. Based on the results of hypothesis testing, it was found that this study found that satisfaction had a positive and insignificant effect on repurchase intention. This shows that the e-satisfaction of online shop consumers does not significantly affect the repurchase intention of these consumers towards e-commerce online shops. In addition, e-word of mouth has a positive and insignificant effect on repurchase intention. This shows that the higher the e-word of mouth perceived by e-commerce consumers, the less significant customers will repurchase online. E-trust has a positive and significant effect on repurchase intention. This shows that the higher the e-trust perceived by online shop e-commerce consumers, the more customers will repurchase online. The novelty of this research is the new correlation model of e-satisfaction, e-word of mouth and e-Trust on repurchase intention of online shops and the research can be a reference for further research to be applied in other places or countries.

Research on Guiding Consumer Behavior Based on App Information Management of Fresh Food E-commerce in the Post-epidemic Era

With the advent of the post-epidemic era, China's nascent fresh food e-commerce industry has given people a new way to buy fresh products, and through this novel marketing model, it has alleviated the unsalable and short shelf life of fresh products.Taking the Hema Xiansheng APP platform in Shenzhen as an example, the questionnaire survey method is used to analyze the consumption motives and consumption behaviors of consumers to analyze the consumption dilemma and reasons of the company, and propose improvement measures: formulate commodity price standards; improve product quality; strengthen corporate branding Optimization; optimize the links of the logistics chain; attach importance to the personal experience of customers. It is demonstrated that by analyzing the consumption motivation and consumption behavior research of consumers and giving proper guidance, the efficiency of business operation can be improved. At present, the research and exploration of the fresh food e-commerce industry outside China is at the basic stage. Based on the research on the relationship between the consumption motivation and consumption behavior of Chinese consumers in fresh food e-commerce, it effectively expands the long-term confusion of Chinese agricultural products. The "last mile" of the terminal market and the promotion of fresh food e-commerce enterprises have certain practical value and significance.

MCDM based e-commerce consumer decision support tool

E-commerce is currently one of the most rapidly growing branches of the economy. Increasing competition in the market for this field creates the need for continuous improvement of service quality and the need to stand out from others. More and more consumers are taking advantage of the opportunity to purchase products and services over the Internet. Many products on the market and the existence of many criteria to be taken into account create difficulties in making an objective decision when choosing the most appropriate product.Multi-criteria decision-making methods (MCDMs) are designed to help make the most appropriate decision in multi-criteria problems. Literature studies have proven that they are a widely used and suitable tool to assist choice when purchasing products and services. The possibility of their application in online sales as a consumer decision support tool seems promising both to meet customers’ growing needs and strengthen the position of online outlets in the market for these services.This paper presents an approach involving applying four MCDM methods TOPSIS, VIKOR, PROMETHEE II and COMET, in solving the multi-criteria problem of selecting the most favourable model of headphones. The obtained results confirm the usefulness and adequacy of the selected set of methods in choosing purchased products and devices and indicate the great potential of MCDM methods in the field of online commerce and services.