Modern E-commerce Research Articles

Security aspects in modern service component-oriented application logic for social e-commerce systems

Modern practices in social commerce are a subset of e-Commerce focusing on security framework protocols such as secure transactional protocols, cryptographic schemes, and sanitization criteria. It is assumed that these practices will ensure stable social media-based e-Commerce applications. The main concern in utilizing these practices focus on software component composition, and integration flaws, which are often overlooked in their business application logic. These problems can render the effect of modern information security concepts null and void. The weakest link in social media-based e-Commerce applications is the component’s logic subversion on its server side, which is caused by developers overlooking the design process. This paper addresses a unique issue in aspects of information security in application logic vulnerability called subversion attack, which can be classified as a design flaw. This kind of security flaw cannot be prevented by many traditional security mechanisms commonly used in modern e-Commerce systems. To address this issue, we propose the use of security assurance methodologies in service component-oriented applications to be utilized through threat modeling and a novel technique component fault detection model. This idea is further extended to the modeling component and its applications using a UML secure design approach. To validate the technique, the methods applied in this paper are verification and validation for security by design testing to avoid the business logic design flaw problem in rapidly built component-based social media e-Commerce applications.

Hybrid ecommerce recommendation model incorporating product taxonomy and folksonomy

In modern ecommerce platforms, product content information may have two origins: one is tree-structured taxonomy attributes, and the other is free-form folksonomy tags. This paper proposes a hybrid model to incorporate taxonomy and folksonomy information to enhance ecommerce recommendations. It first develops a tree matching algorithm to establish the overall similarity between items, where tag information is integrated for semantic analysis for taxonomy attributes. Next, it proposes a unique random walk model on a heterogeneous graph constructed by user nodes and item nodes and different types of relations — user–item preference and item–item similarity relations. The random walk model is designed to be effective to identify the nearest item nodes for a particular user node, which are seen as the best-fit items for recommendations. Empirical experiments demonstrate that the proposed model improves performance in terms of both recommendation coverage and accuracy, especially for sparse data.

Електронна комерція в контексті розвитку міжнародного рекламного менеджменту

The paper is devoted to the analysis of the scientific approaches to e-commerce concept understanding; it was made the analysis of the trends of modern e-commerce market development and there were given the practical tips concerning the own business development in this sphere. There were structured the main features of e-commerce, particularly: electronic payment systems using as the analogue of real money; making agreement thank to ICT; operations uniformity and possibility to do audit by provider or another organization; property rights and assets are kept as in the traditional form and electronic one. The barriers to the development of electronic commerce in Ukraine were structured: limit access to the Internet, especially villagers; Internet-shops oversaturation by extra information what provokes potential customers loosing; low level of education of staff who work in the Internet (in particular, the lack of special knowledge required for this sphere). It was calculated the prognosis of the dynamics of e-commerce international market to 2030, which presents the stable growth. There were presented practical tips how to do business in the sphere of e-commerce.

E-Commerce Models suited to the Micro, Small and Medium Enterprises in India

Micro, Small and Medium Enterprise (MSME) sector in India has been blooming significantly in respect of the number of units and in generating new employment, annually. The MSMEs are looking forward to an enhanced customer base and increased profits by using modern e-commerce technology. The Budget 2020 contains a long list of proposals to boost investment cycle, infrastructure development and growth of MSME sector. Of this, the most vital proposal is the provision for additional channel to promote marketing. It is made clear that the Government plans to start an e-commerce platform on the lines of other private e-commerce giants to sell products from MSMEs. Future of e-commerce in India, thus, is bright with the mobile platforms, personalization, social media analytics, and omni-channel services. In this backdrop, an attempt is made in this paper to identify the befitting e-commerce models for the MSMEs in line with the Budget proposals..

Перспективы развития иммерсивных технологий как современных инструментов электронной коммерции

Перспективы развития иммерсивных технологий как современных инструментов электронной коммерции

Loyalty of young female Arabic customers towards recommendation agents: A new model for B2C E-commerce

E-commerce is becoming a major contributor to the worldwide economic system, owing to its adaptability and ease of use for both customers and service providers. Recommender systems are embedded in most modern e-commerce websites, as efficient tools for guiding users to view additional items provided by e-commerce portals. These items are matched with customers' interests depending on their current activities, or on preferences stated in their profiles. As service providers are more concerned with the long-term behavior of customers, and specifically customer loyalty (which bears directly on the long-term success of e-commerce websites), most recommender systems have been developed to consider that aspect. This study investigates the major factors in the loyalty formation of female online shoppers through an e-commerce recommender agent. A new model is introduced, developed, and analyzed for helping to improve e-commerce customer loyalty via the recommender systems. Based on the implications of the results, we can understand research constructs and highlight research outcomes to help in managing recommender systems more effectively.

Совершенствование основных подходов к прямому и косвенному налогообложению при трансграничных операциях цифрового бизнеса (Improving the Basic Approaches to Direct and Indirect Taxation in Cross-Border Digital Business Operations)

Russian Abstract: Тема налогообложения трансграничных операций является ключевой для современной системы электронной торговли. В работе исследуются различные аспекты данной темы. На основании анализа позиций ведущих международных организаций установлены принципы налогообложения трансграничных операций. В связи с этим особое значение имеет подход ОЭСР, которая является главной международной площадкой, где государства согласовывают свои позиции по вопросам налогообложения. В настоящее время не достигнут консенсус государств по вопросам налогообложения трансграничных операций. В настоящее время есть несколько примеров законодательного введения нового «цифрового налога» (Франция и проект закона в Великобритании). Принимая во внимание международный опыт и практику государств в исследовании была проведена оценка готовности России к внедрению налогообложения трансграничных операций в части импорта и экспорта. По результатам такой оценки подготовлены соответствующие предложения. English Abstract: The issue of taxation of cross-border transactions is a key topic in the modern e-commerce system. The paper explores various aspects of this issue. Based on the analysis of the positions of leading international organizations, the principles of taxation of cross-border transactions are established. In this regard, the OECD approach, which is the main international platform where states coordinate their positions on taxation issues, is of particular importance. At present, no consensus has been reached on taxation of cross-border transactions. There are currently several examples of the legislative introduction of the new “digital tax” (France and the draft Act in the UK). Taking into account international experience and state practice, an assessment was made of Russia's readiness to introduce taxation on imports and exports. Based on the results of this assessment, we made relevant proposals.

Моделі формування рекомендацій у інтелектуальних системах електронної комерції

Результати роботи пошукових та фільтраційних механізмів сучасних систем електронної комерції не завжди задовольняють вимоги користувачів, що проявляється у неточних та неповних рекомендаціях товарів за пошуковим запитом. Удосконалення якості рекомендацій для покупців онлайн торгівельних платформ є актуальною задачею. Дана робота наводить моделі формування рекомендацій на основі методів кластерного аналізу, які дозволяють згрупувати схожі товари та схожих клієнтів за їхніми характеристиками. Наведені результати експерименту щодо формування рекомендацій придбання рюкзаків для покупців онлайн магазину спортивного обладнання.

ON PERFORMANCE FEASIBILITY AND SERVICE QUALITY OF E-COMMERCE MARKETING BASED ON FUZZY LOGIC

In the evolving era of digitization, the success of the modern e-commerce industry is measured by several key performance metrics. These performance indicators determine its efficiency and overall service quality in online business marketing. In this paper, we investigate the feasibility performance of e-commerce based on assessment of multiple qualitative parameters influencing the behaviour of online consumers. The attributes considered for evaluating the proficiency of e-commerce platforms and improving their service quality in the highly competitive global market include setup and operational cost, scalability, execution time, and resources accessibility. These multiple independent parameters with different units and range of values exhibit implicit imprecision and uncertainties, which can be effectively handled by multivariate fuzzy logic modeling. For a given dataset application of the presented fuzzy multi-criteria decision making framework, simulation results are used to compute the absolute error, root mean square error and normalized error in the estimation of fuzzy output variable of feasibility, thereby validating the proposed model. Furthermore, numerical results and analyses depict that our model offers substantial performance enhancement in terms of achieving higher accuracy than other estimation methodologies existing in literature with equivalent dataset size

The Impact of digital technology on e-commerce development in Russian Federation

The article is devoted to the problem of development and influence of digital technologies on e-Commerce enterprises. The types and forms of digital technologies used in this field are studied the characteristics and features of modern e-Commerce in the Russian Federation are considered. The modern Russian e-Commerce market still lags behind foreign ones in terms of the number of users and assortment, but it shows high annual growth rates. The article substantiates the point of view that the further development of e-Commerce is one of the key drivers of growth of all trade in the Russian Federation and the economy total. So, it is very important to assess not only the current state of the e-commerce market, but also to identify perspective trends in its development. E-commerce analysis of research if indicates that modern digital technologies can shape and control the way that a buyer goes from getting acquainted with a product to purchasing it. Digital technologies help to create new patterns of customer relationship. The article offers an overview of the main areas of use of digital technologies that are used in this field: Big Data and personalization, mobile Commerce, Blockchain technology, social networks. This overview can be useful to the scientific and business communities when conducting research in the field of digital economy, when building business plans and strategies taking into account the use of modern digital technologies in the development of the information society.

Exploiting Visual Content of Book Front Cover to Aggrandize the Content Based Book Recommendation System

In modern e-commerce world Recommendation Systems are playing a key role in supporting customers to take a decision. With this kind of services customers can choose comfortably the products as per their preferences from a long list of available products. It’s not only a boon for the customers; it will boost the sales for the organization and generate better revenues. Due to diverse domain characteristics, each domain requires different kinds of recommendation models. Content based recommendation model is one of the recommendation models which purely rely on product features and the current user preferences. This model is more effective for the domains like news, micro-blogs, books, movie plots and scientific papers etc. In this paper we propose a content-based filtering model for book recommender system by utilizing its overall textual features as well as visual features of its front cover. Numerous surveys have demonstrated that book readers are highly inclined to its covers that are visually attractive1. Book front cover is the first representative candidate of the book that will reveal the overall sense of the book; hence we considered book front cover as one of the book contents along with the text. Our experiment shows that augmenting the visual features to the existing content-based recommender models performed well.

Multi-Order Attentive Ranking Model for Sequential Recommendation

In modern e-commerce, the temporal order behind users’ transactions implies the importance of exploiting the transition dependency among items for better inferring what a user prefers to interact in “near future”. The types of interaction among items are usually divided into individual-level interaction that can stand out the transition order between a pair of items, or union-level relation between a set of items and single one. However, most of existing work only captures one of them from a single view, especially on modeling the individual-level interaction. In this paper, we propose a Multi-order Attentive Ranking Model (MARank) to unify both individual- and union-level item interaction into preference inference model from multiple views. The idea is to represent user’s short-term preference by embedding user himself and a set of present items into multi-order features from intermedia hidden status of a deep neural network. With the help of attention mechanism, we can obtain a unified embedding to keep the individual-level interactions with a linear combination of mapped items’ features. Then, we feed the aggregated embedding to a designed residual neural network to capture union-level interaction. Thorough experiments are conducted to show the features of MARank under various component settings. Furthermore experimental results on several public datasets show that MARank significantly outperforms the state-of-the-art baselines on different evaluation metrics. The source code can be found at https://github.com/voladorlu/MARank.

Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System

Developing effective and efficient recommendation methods is very challenging for modern e-commerce platforms. Generally speaking, two essential modules named “ClickThrough Rate Prediction” (CTR) and “Conversion Rate Prediction” (CVR) are included, where CVR module is a crucial factor that affects the final purchasing volume directly. However, it is indeed very challenging due to its sparseness nature. In this paper, we tackle this problem by proposing multiLevel Deep Cascade Trees (ldcTree), which is a novel decision tree ensemble approach. It leverages deep cascade structures by stacking Gradient Boosting Decision Trees (GBDT) to effectively learn feature representation. In addition, we propose to utilize the cross-entropy in each tree of the preceding GBDT as the input feature representation for next level GBDT, which has a clear explanation, i.e., a traversal from root to leaf nodes in the next level GBDT corresponds to the combination of certain traversals in the preceding GBDT. The deep cascade structure and the combination rule enable the proposed ldcTree to have a stronger distributed feature representation ability. Moreover, inspired by ensemble learning, we propose an Ensemble ldcTree (E-ldcTree) to encourage the model’s diversity and enhance the representation ability further. Finally, we propose an improved Feature learning method based on EldcTree (F-EldcTree) for taking adequate use of weak and strong correlation features identified by pretrained GBDT models. Experimental results on off-line data set and online deployment demonstrate the effectiveness of the proposed methods.

A Fortune 14 company’s journey to delivering a modern e-commerce customer experience

Digital transformation in business-to-business (B2B) organisations tends to move very slowly. The expectations of B2B buyers have quickly changed over the last few years. They now demand the same user experience, ease of navigation, intuitive search, robust product content and basic self-service experienced as consumers. This paradigm shift is driven mostly by the retail e-commerce experience that has evolved greatly over the last couple of decades. The challenge for the B2B marketer or e-commerce leader is that the target audience is not willing to wait a decade or two. The gap in current state compared with expected state must be closed with greater speed and urgency. It is these customer demands that prompted Cardinal Health’s medical business to initiate a journey — four years ago — to create an expected e-commerce experience. This case study highlights the Cardinal Health journey to date with an emphasis on making the case for change, developing a roadmap and executing the initial site launch.

A Cloud Service Framework for Virtual Try-On of Footwear in Augmented Reality

This paper presents an experimental cloud service framework for design evaluation of personalized footwear in augmented reality (AR) via networks. The service allows users to ubiquitously perceive themselves trying on three-dimensional (3D) shoe models in a video stream. They upload a clip of feet motion recorded by a commercial depth camera to the cloud. A new clip is generated to display the try-on process and made available to specified receivers via video streaming on a mobile device. The framework design emphasizes making most use of open-source software and off-the-shelf technologies commercially available. A prototyping cloud system implementing the framework demonstrates the practical value of virtual footwear try-on as AR as a service (ARaaS). This experimental study realizes the idea of human-centric design evaluation in modern e-commerce. The cloud framework may provide a feasible example to improve the usability for real-time applications of AR.

Study on Information Security Issues of E-Commerce

The rise of e-commerce has injected a new force for China’s industrial upgrading and economic and social development. Although e-commerce has flourished greatly, a great many of security risks have been caused due to information security issues of cyber transaction which have not be powerfully guaranteed in the respect of legislation nor technology, thus weaken consumers’ confidence to cyber products directly, and then restrict further development of China’s e-commerce. Information security systems of e-commerce will be analyzed and studied from three perspectives that are technology, management and legislation in this paper, with the purpose of constructing a multi-layer and multi-platform modern e-commerce security guaranteeing system.

Modern E-commerce as the basis for the development of transport and logistics providers in Ukraine

The article examines the state of e-business and prospects for its further development. A number of problems that complicate the use of e-Commerce in Ukraine, namely legal problems, fraud, risks. It should be noted that the underdeveloped legal component contributes to the spread of fraudulent transactions carried out with the help of stolen card details; the appearance of the shops, completely disappearing from the market after a successfully executed fraud, the fictitious shops intended for gathering information about the cards, and thus the emergence of psychological factors - buyers appear to distrust the conduct of consumer transactions via the Internet. The role of e-Commerce in the activities of transport and logistics providers is also highlighted. For successful strategic management of the online store it is profitable to use the services of intermediaries: outsourcing companies with the necessary experience in receiving calls and orders; a professional courier service that will fulfill its obligations much better than others. The calculation of e-business contribution to the gross domestic product growth is proposed. The relationship between the components of the network readiness index and the contribution of e-economy to GDP growth is analyzed. Countries with the most developed infrastructure, high rates of individual use of network resources and developed regulatory environment loyal to market conditions have more efficient e-economy.

Leveraging Image Visual Features in Content-Based Recommender System

Content-based (CB) and collaborative filtering (CF) recommendation algorithms are widely used in modern e-commerce recommender systems (RSs) to improve user experience of personalized services. Item content features and user-item rating data are primarily used to train the recommendation model. However, sparse data would lead such systems unreliable. To solve the data sparsity problem, we consider that more latent information would be imported to catch users’ potential preferences. Therefore, hybrid features which include all kinds of item features are used to excavate users’ interests. In particular, we find that the image visual features can catch more potential preferences of users. In this paper, we leverage the combination of user-item rating data and item hybrid features to propose a novel CB recommendation model, which is suitable for rating-based recommender scenarios. The experimental results show that the proposed model has better recommendation performance in sparse data scenarios than conventional approaches. Besides, training offline and recommendation online make the model has higher efficiency on large datasets.

Generating inter-dependent data streams for recommender systems

Recommender systems are essential tools in modern e-commerce, streaming services, search engines, social networks and many other areas including the scientific community. However, lack of publicly available data hinders the development and evaluation of recommender algorithms. To address this problem, we propose a Generator of Inter-dependent Data Streams (GIDS), capable of generating multiple temporal and inter-dependent synthetic datasets of relational data. The generator is able to simulate a collection of time-changing data streams, helping to effectively evaluate a variety of recommender systems, data fusion algorithms and incremental algorithms. The evaluation using recommender and data fusion algorithms showed that our generator can successfully mimic real datasets in terms of statistical data properties, and achieved performance of recommender systems.

E-Commerce in Tourism: Practice, Problems, Perspectives

The article is devoted to the consideration of the problem in using modern e-commerce tools in the field of tourism. In order to disclose the topic, methods of objectivity and system are used to establish the main advantages and disadvantages of using e-commerce in the economic activity of a tourist enterprise. The purpose of the article is to determine the state and prospects for the development of e-commerce in the tourism services market, as well as the analysis of international experience in the field of e-commerce legislative regulation. Together with the rapid spread of electronic payment, the communication networks development and the growing number of potential Internet users, e-commerce has become one of the most important sales channels for tourism services, while increasing the profitability and competitiveness of enterprises. One of the important factors that hinders the rapid spread of e-tourism in Ukraine is the regulatory framework imperfection. After the introduction of existing mechanisms in interaction between the seller and the consumer in tourism services, electronic sales can be made one of the modern and effective ways to implement a tourism product.