E-commerce Sales Research Articles

The Effect of Retail E-Commerce Sales and Domestic Direct Investment on the RCA Value of the Indonesian Medium High Technology Sector: RLS and FMOLS Approach

The Effect of Retail E-Commerce Sales and Domestic Direct Investment on the RCA Value of the Indonesian Medium High Technology Sector: RLS and FMOLS Approach

Investigating Methods for Increasing Sales in E-Commerce

In this detailed exploration of e-commerce strategies, we delve into the intricacies of enhancing customer experience, leveraging social media and marketing, employing data analytics and market research, integrating advanced technology, ensuring trust and reliability, and optimizing logistics and delivery. These facets are crucial for understanding and responding to consumer behavior, predicting market trends, and maintaining competitive pricing strategies. The synthesis underscores the necessity of continuous innovation and adaptability in the fast-evolving digital marketplace. E-commerce businesses are encouraged to embrace these strategies to meet consumer demands effectively, drive sales, and ensure sustainable growth. This comprehensive overview serves as a guide for e-commerce entities aiming to thrive in this dynamic sector.

A Review on Sustainable Marketing Strategy for Crocs

Crocs is an American shoe brand. This study talking about how brand marketing and brand decisions have made Crocs' success, decline, and return to the masses a popular trend again. Nowadays the social economy rapid develop. various products advent more faster, the new things with creativity could always attract peoples attention. However, the society trend changed quickly, then all brands need to think about how they could expand their customer base in addition to consolidating their existing customers same as Crocs. To make a sustainable marketing strategy crocs needs to combine their brand history, the market requirement, their brand positioning, and their consumer buying behavior. Therefore, the purpose of this study is to provide a sustainable development plan for Crocs from the author's point of view through the several items of information above. The sustainable development suggestions in this paper include, but are not limited to, clarifying brand positioning and target customer groups, developing e-commerce sales channels, etc.

Boosting e-commerce sales with live streaming: the power of barrages

Boosting e-commerce sales with live streaming: the power of barrages

The Impact of Artificial Intelligence Marketing on E-Commerce Sales

This review explores the influence of AI marketing on e-commerce sales, examining how AI-driven strategies affect key metrics such as customer acquisition and conversion rates. Given the growing importance of AI in online retail, this paper employs a critical review methodology, analyzing 50 documents from the Scopus database. The analysis reveals that AI tools like chatbots, personalization engines, and predictive analytics significantly enhance e-commerce performance. The study provides practical and theoretical contributions, offering recommendations for businesses and suggesting future research directions.

The Relevance of Ibnu Khaldun's Price Concept to the Prohibition of Sales in E-Commerce

The background of the problem in this study suggests that the impact of the internet, one of which is technological advances, has opened up new business opportunities. As one of the urgencies of digital business progress in Indonesia today is e-commerce through the encouragement of advanced technology. The focus of this research explains that the relationship between Ibnu Khaldun's theory and the concept of e-commerce. This research uses a qualitative method with a description approach. The data collection is through literature articles, books and newsletter. As for the results of the research that the regulation of the Minister of Trade Number 31 of 2023 officially prohibits the merger of e-commerce and social commerce through e-commerce platforms, they are only allowed to promote products or services. This is called political dumping; the practice of dumping is expressly prohibited in Islam. In Ibnu Khaldun's price theory: the Islamic principle of determining the seller's price of a good tends to use the concept of average, because the demands of justice must be linked to effort.

DIGITALISATION IN ACCOMMODATION AND FOOD SERVICE ACTIVITIES IN ROMANIA AND EUROPEAN UNION

The purpose of this paper is to evaluate the levels regarding the digitalisation and e-commerce footprint of enterprises in accommodation and food service activities for Romania and the European Union (EU). The goal of this research relating to the status of digitalisation and electronic commerce in accommodation and food service activities, is to better understand the magnitude (in Romania and EU) of the aforementioned from the viewpoint of specific indicators. And through those indicators to retrieve some answers regarding to: the degree of digitalisation, the level of enterprises where persons employed have access to the internet and also that have access to the internet for business purposes, the use of social media, the degree of enterprises with a website, the extent of difficulties for web sales of enterprises, what is the situation regarding the enterprises with e-commerce sales and enterprises total turnover from e-commerce sales. The research methodology included collecting information from recognized data bases (Google Scholar for theoretical part and Eurostat for the empirical approach).

Data-Driven Personalized Marketing in E-commerce: Practical Applications

Data-driven personalized marketing is crucial for enhancing user experience and increasing sales in e-commerce. This paper explores the practical applications of personalized marketing, focusing on algorithms, user behavior analysis, and associated risks. Also, the paper illustrates how data-driven personalized marketing is implemented and its impact on user engagement and sales. The collection and processing of large amounts of user data are essential for personalized marketing strategies. Various algorithms, including collaborative filtering and deep learning, are employed for personalized recommendation systems. Real-time data analysis techniques enable e-commerce companies to adjust marketing strategies rapidly. Combining information from several platforms, including social media, mobile apps, and websites helps in creating comprehensive user profiles for effective personalized marketing. Analyzing user behavior is essential to comprehending user requirements and preferences. However, there are risks and challenges associated with data-driven personalized marketing, including data privacy and compliance issues, over-personalization risks, and data quality concerns.

The Influence of User-Generated Content on E-Commerce Sales: A Meta-Analysis

User-generated content (UGC) has become a common element of e-commerce platforms, with customers increasingly depending on reviews, ratings, and other kinds of UGC to make purchase choices. While the effect of user-generated content (UGC) on e-commerce sales is generally acknowledged, its quantity and consistency are still debated. This meta-analysis combines data from previous research studies to give a full knowledge of the link between user-generated content and e-commerce sales. Using a variety of empirical research and theoretical frameworks, we investigate the implications of UGC qualities, platform features, and contextual variables on e-commerce revenue success. Our findings provide useful insights into the elements that influence the effect of user-generated content on sales, such as product category, brand reputation, and customer characteristics. Furthermore, we highlight gaps in the current literature and offer future study directions to help us better understand the complicated interaction between user-generated content and e-commerce purchases.

Сегментация пользователей мобильных приложений в омниканальном ритейле

A prominent issue now facing the retail industry is the process of digitization. The proportion of e-commerce sales in overall retail trade is expanding, and consumers are progressively emphasizing digital services. The prevalence of mobile applications and smart phones is likewise steadily rising. Several merchants provide smartphone applications that integrate online and brick-and-mortar purchasing. While there has been study on the adoption of mobile apps, there is a dearth of evidence about the categorization of users. This study used cluster analysis to categorize mobile app users in the multichannel retail industry. The catego rization is based on a survey conducted with a sample size of 300 consumers. The discovered results have potential utility in the advancement of forthcoming mobile applications for retail.

Research on influencing factors of pharmaceutical e-commerce sales based on web crawler and support vector machine

Research on influencing factors of pharmaceutical e-commerce sales based on web crawler and support vector machine

IMPACT OF BNPL SERVICE ON CONSUMERS PURCHASING BEHAVIOUR

The impact of Buy Now, Pay Later (BNPL) services on consumers' retail purchase behavior is examined in this study. The study uses a mixed-methods approach to investigate the attitudes, behaviors, and motives behind BNPL adoption. Quantitative analysis of survey data from many participants is combined with qualitative insights. This research aims to fill this gap by examining how Flipkart's BNPL service influences consumer behavior, cart abandonment rates, and overall e-commerce sales. Additionally, it seeks to explore the implications for both consumers and businesses and assess the role of regulatory factors in this context. The objective of the study is to examine the influence of BNPL services on consumer decision-making processes, investigate the effects of BNPL on consumer spending habits and financial behaviors, explore the relationship between BNPL services and consumer loyalty in the e-commerce sector and to assess the impact of BNPL on impulse buying and its implications for consumer financial well-being. And we have gathered primary data through questionnaire, and these questionnaire contain 12 questions which was filled by 225 respondents, we have circulated the questionnaire on social media. Among every 100 active customers 75 are using BNPL. the research underscores the transformative influence of Buy Now, Pay Later (BNPL) services on online consumer transactions. The advent of BNPL has, indeed, raided the online purchase realm, altering the traditional dynamics of how consumers engage with e-commerce. As we witness this paradigm shift, it is imperative for stakeholders to recognize the far-reaching consequences, adapt to the changing landscape, and formulate strategies that balance the allure of BNPL with responsible financial practices for sustained and healthy growth in the digital shopping sphere.

Competitiveness Strategy of South Korean Cosmetic Brands: Current Practices and Opportunities for Russian Cosmetic Brands

This study analyzes place, trends and competitiveness of the South Korean cosmetics brands to identify opportunities for the Russian cosmetics brands, whose country has suffered from a large trade deficit in the cosmetics industry despite the government’s vigorous attempts in implementing import substitution policies. We constructed the econometric models (with ordinary least square, weighted least square and robust least square estimators) of the cosmetics brands’ competitiveness by employing the endogenous factors of Porter’s diamond model, which are comprised of firm factor conditions, demand conditions, related and supporting industries, and strategy, structure and rivalry. From the regression analysis, it is revealed that the brand diversification, expansion of e-commerce sales and improvement of governance quality are factors that drive up sales revenues of a cosmetic company. The follow-up comparative analysis between Russian and South Korean companies allowed us to substantiate that the main factors causing the gap between Russian and South Korean cosmetic brands are e-commerce strategies and the efficiency of the governmental system. Russian cosmetic companies should construct stable global and domestic supply chain and expand contact points with foreign customers through big data analysis and development of customized product portfolio. Furthermore, the government is recommended to implement digital services and construct a data-sharing ecosystem to enhance efficiencies of the business process.

Toward a Sustainable Development of E-Commerce in EU: The Role of Education, Internet Infrastructure, Income, and Economic Freedom on E-Commerce Growth

The emergence of e-commerce reshaped the traditional trade models, also playing a significant role in meeting the UN sustainable development goals. According to the UN, sustained growth and social development must include resilient infrastructure, foster innovation, allow for better access to information and communications technology, and universal and affordable internet infrastructure. This study explores a multidimensional analysis of e-commerce development in the EU generated by the following factors: education, internet infrastructure, income, and economic freedom. We use an ARDL econometric model and Eurostat data. Additionally, we analyze the time responsiveness of e-commerce growth to changes in these factors. In the long run, our findings identify a stable and positive relationship between e-commerce and all these factors. However, in the short run, our results illustrate significant dynamics between two variables and e-commerce. Specifically, the level of internet access and the percentage of individuals who use the internet daily exhibit a positive short-run impact on e-commerce sales, with the system absorbing shocks within a short period. This research advocates for targeted policies that support innovation, fair competition, and consumer protection in the digital economy. This research provides valuable guidance for policymakers and stakeholders in improving the institutional framework to promote a sustainable development of e-commerce in the EU.

Developing urban infrastructure constructions for increasing e-commerce sales: the moderating roles of aging population

PurposeThe aging population, a higher proportion of older adults (aged 65+), is considered a global and severe problem, while the information systems (IS) literature on detecting the relationship between the aging population and the development of electronic commerce (e-commerce) is limited and insufficient. Hence, the main objective of this paper is to examine whether an aging population can moderate the effect of infrastructure constructions on e-commerce sales and whether an aging population can affect e-commerce sales.Design/methodology/approachTo investigate the relationship between the aging population and e-commerce sales, this study proposes two potential influential mechanisms: moderating the effects of infrastructure development on e-commerce sales and direct influence. Subsequently, a sample of 31 Chinese provinces from 2013 to 2019 is utilized to conduct regression analyses in order to examine these hypotheses.FindingsThe findings suggest that the development of urban transportation infrastructure and network constructions can significantly contribute to the enhancement of e-commerce sales, and the influence cannot be affected by aging population. Furthermore, it is noteworthy that an aging population can have a positive effect on e-commerce sales.Practical implicationsThe findings can inform future infrastructure constructions by assessing the potential of infrastructure projects to boost e-commerce sales and examining whether this effect varies in an aging population context.Originality/valueThe findings substantiate the pivotal role of older adults in the e-commerce industry. Moreover, the obtained results establish a positive relationship between an aging population and e-commerce sales, thereby offering diverse perspectives on existing theories.

Fusing SVR with PSO Improves E-commerce Sales Prediction with 8.98% MAPE

This study explores the integration of Support Vector Regression (SVR) with Particle Swarm Optimization (PSO) to forecast clothing product sales at Nara Gallery Collection Boutique, addressing the challenge of achieving high forecast accuracy in e-commerce. Through literature review, direct observation, and interviews with a textile SME owner, SVR parameters are optimized using PSO. Results indicate a Mean Absolute Percentage Error (MAPE) value of 8.98% with optimized parameters (C = 34.3642, ε = 0.0110, σ = 0.3677, cLR = 0.1062, λ = 0.0117), enhancing decision-making in inventory management and strategic planning for e-commerce businesses. This research highlights the potential of integrating SVR with PSO for accurate sales forecasting and suggests avenues for further exploration in alternative forecasting methods and optimization techniques. Highlight: Enhanced Forecasting Accuracy: SVR and PSO integration improves e-commerce sales predictions. Parameter Optimization: PSO optimizes SVR parameters, reducing Mean Absolute Percentage Error. Strategic Inventory Management: Accurate forecasts aid in effective e-commerce inventory control. Keywoard: Support Vector Regression, Particle Swarm Optimization, Sales Forecasting, E-commerce, Inventory Management

Research on sales forecasting in e-commerce industry for imbalanced classification data

The background of this study is that with the advent of the big data era, e-commerce sales forecasting has become a key factor in improving the market competitiveness and economic benefits of enterprises. To solve this problem, we used machine learning technology to build a comprehensive sales forecasting system. By processing massive sales data, including data cleaning, label encoding, outlier processing and other steps, we established a complete data set. In terms of model selection, we tried multiple regression models, such as RandomForestRegressor [1], ExtraTreesRegressor, etc., and evaluated their performance through cross-validation. In order to solve the problem of data imbalance, a combination of oversampling technology (RandomOverSampler)[2] and normalization processing is used. Finally, we selected ExtraTreesRegressor as the best model and evaluated it on the training set. The research results show that the accuracy and reliability of sales forecasts can be improved by comprehensively processing sales data and selecting appropriate machine learning models. The contribution of this study in the field of e-commerce sales forecasting is to provide a comprehensive and practical solution, which provides important decision-making support for enterprises in market competition. Combining machine learning technology and data processing methods, we provide e-commerce companies with an effective sales forecasting strategy that is expected to have a positive impact in improving market competitiveness, reducing risk costs, and accelerating revenue growth [3]. Future research directions can be carried out in deeply exploring the characteristics of sales data, optimizing model parameter adjustment, and combining professional knowledge in more fields. Introducing more emerging machine learning algorithms and technologies to adapt to the changing market demands in the e-commerce field is expected to further improve the performance and adaptability of the sales forecasting system.

Improved Marine Predators Algorithm and Extreme Gradient Boosting (XGBoost) for shipment status time prediction

Shipment Status Time Prediction (STP) is a complex problem requiring expertise in many disciplines, including Machine Learning (ML) and logistics management, to develop effective solutions. Estimating every possible shipment step before creation plays a vital role in e-commerce sale channels. In this point of view, a novel STP approach was proposed to predict shipment status times. The proposed approach involves two phases. The first leg of the novel STP approach is to build an ML model for estimating shipment statuses using a dataset acquired from a real-world application. The Extreme Gradient Boosting (XGB) and popular ML algorithms were compared for the classification of shipment status prediction first. The XGB algorithm performed best among the compared algorithms, with 99.92% and 96.16% accuracy for training and test sets. Moreover, the ML algorithms were run on the public New York City taxi trip dataset. The XGB algorithm exhibited the best performance. The accuracy for training and test sets are 97.40% and 97.33%, respectively. The second phase of the proposed approach is shipment status time estimation, designed as an optimization problem. The Marine Predators Algorithm (MPA) is a recently proposed optimization algorithm for numerical function optimization. An improved MPA algorithm for STP (STPMPA) was proposed in this study. The performance of the STPMPA algorithm was scrutinized on numerical benchmark problems first. The STPMPA algorithm outperformed all the algorithms in the experiment. Then, the most feasible shipment status times are searched by optimizers using the XGB model. The proposed STPMPA algorithm put forth a superior performance for the STP problem than the compared optimization algorithms. Consequently, experimental studies reveal that the proposed STP approach is able to generate efficient estimations in reasonable times for real-time systems.

The Influence of Digital Literacy on the Phenomenon of Deviation between Farmers’ E-Commerce Sales Willingness and Behavior: Evidence from Rural China

E-commerce, as a prominent feature of the digital economy era, is highly expected to promote economic growth and sustainable development. Based on the 2020 “China Rural Revitalization Survey” data, this study empirically analyzed the impact and mechanism of digital literacy on the discrepancy between the willingness and behavior of farmers in e-commerce sales. Eleven indicator items were selected, and factor analysis was used to obtain the comprehensive score of digital literacy. Firstly, benchmark regression was performed using the probit model, and then potential endogeneity issues were addressed using the IV probit method and endogenous conversion probit model. The following main conclusions were drawn: Digital literacy has a suppressive effect on the deviation between the willingness and behavior of farmers in e-commerce sales. Farmers with media operation literacy, information acquisition literacy, digital transaction literacy, e-commerce cognitive literacy, and digital social literacy have a 12.3%, 18.3%, 26.2%, 37.5%, and 21.9% reduction in the probability of deviation between the willingness and behavior of farmers in e-commerce sales compared to those without these literacy counterfactual assumptions. Digital literacy helps curb the deviation between farmers’ willingness and behavior in e-commerce sales by facilitating their access to financial resources and agricultural production services. This study demonstrates that enhancing the digital literacy of farmers will promote their willingness to convert e-commerce sales into behavior, help promote sustainable agricultural products more efficiently, and make important contributions to economic growth and sustainable development.

A transition to sustainable marine living resources: Why does digital transformation matter?

This paper empirically examines how digital transformation in both the public and private sectors impacts the performance of marine living resources to demonstrate its importance for promoting a sustainable blue economy. Our approach captures the sustainable performance of countries within the European blue economy using three different measures: value added at the factor cost of capture fisheries, shellfish aquaculture, and marine aquaculture. In the context of digitalization, four different aspects are measured, namely online selling, e-commerce sales, e-commerce turnover, e-commerce, and customer relationship management, while digital public services are measured based on digital literacies, business mobility, and key enablers. By using various empirical techniques, namely a panel-corrected standard error (PCSE) model, FGLS models, and a pooled mean group estimation (PMG) in an autoregressive distributed lag estimation method (ARDL), we provide many remarkable findings. During the 2011–2019 period, we estimate that digitalization will have a significant impact on improving the sustainability of the blue economy in Europe. Nevertheless, long-term effects are more likely to be noticeable. Further, in the shape of a U curve, we also find that digitalization has nonlinear effects on marine living resources in the private and public sectors. In this study, results indicate that digitalization affects marine living resources only to a certain extent once they have reached a certain maturity level. Our findings suggest that European countries should accelerate the digital economy, strengthen the establishment of digital infrastructure, and promote digital implementation on the path toward sustainable marine living resources.