A new model to support the personalised management of a quality e-commerce service

The paper presents an aiding model to support the management of a high quality e-commerce service. The approach focuses on the service quality aspects related to customer relationship management (CRM). Knowing the individual characteristics of a customer, it is possible to supply a personalised and high quality service. A segmentation model, based on the "relationship evolution" between users and Web site, is developed. The method permits the provision of a specific service management for each user segment. Finally, some preliminary experimental results for a sport-clothing industry application are described

A Study of the Research Hot Topics and Visualization Analysis of Cross-border Ecommerce in China

With many incentive policies recently released, cross-border e-commerce has been highly concerned by all sectors of society. As an emerging research field, it has great research value. Applying SATI to the keywords in CSSCI papers relevant to CBEC from the CNKI periodical database, we undergo bibliometric and visualization study in terms of word frequency analysis. The visualization analysis reveals that: (1) hot topics in CBEC research fall into 4 areas: e-commerce and international business, government policy and supervision, cross-border logistics and cross-border e-commerce finance; (2) prospective research will focus on talent training, synergy, big data, import , customs supervision, etc

Intelligent Agent-Based Data Mining in Electronic Markets

The advent of web-based electronic commerce has brought a tremendous increase in the volume of “collectable data” that can be mined for valuable managerial knowledge. Utilizing intelligent agents can enhance the data mining procedures that are employed in this process. We focus on the role of data mining and intelligent agent technology in the B2C and B2B e- commerce models. By identifying the complex nature of information flows between the vast numbers of economic entities, we identify opportunities for applying data mining that can lead ultimately to knowledge discovery

Barriers To B2C Segment Of E-Business

The purpose of this paper is to identify several barriers affecting B2C segment growth and to project technological advances that may soften or eliminate these barriers.  Included in the paper is an analysis of the interrelationship between barriers and products.  Finally, the paper presents the impact of technology-controlled and human-controlled factors on Internet sale.  &nbsp

Trust in Electronic Commerce: A New Model for Building Online Trust in B2C

The rapid growth in the electronic commerce over the internet has fuelled predictions and speculations about what makes a business to consumer (B2C) web site effective. Increasing use of the World Wide Web as a B2C commercial tool raises interest in understanding the key issues in building relationships with customers on the internet. Trust is believed to be the key to these relationships. In this paper, an overall model has presented for building online trust in this context. This model outlines some of the key factors that are related in this area and suggests a framework based on these factors. With respect to the position and importance of the trust in online commerce, this model helps businesses in order to capture, sustain and construct long-term relationships with their consumers.               Keywords: E-Trust, Reverse engineering, Business-consumer web sites, online shopping, Web desig

Digital Echelons and Interfaces within Value Chains: End-to-End Marketing and Logistics Integration

[EN] The goals of real business in the context of the digital transformation of international logistics networks and marketing channels have necessitated the application of a scientifically based theoretical approach to the development of a formalized description acceptable for predictive planning based on leading indicators. In the context of globalization and interstate and regional economic unions, this will lead to achieving the maximum end-to-end integration of digital platforms. Based on the analysis, the article presents the integration of digital logistics and marketing approaches with the mathematical models of the ecosystem organization of economic relations. The features of the organization of economic relations between contractors involved in the execution of virtual transactions and the material movement of resources were analyzed. The researchers considered prerequisites for the analytical description of interconnections between the participants of digital platforms in cross border e-commerce. The authors' approach is based on the idea of both a sales funnel in marketing and a conversion funnel in digital transformation. Considering the integration of logistics and marketing, authors offer the definition of business echelons as stages of the consumer value creation. The theoretical contribution of this article consists in constructing a mathematical description of business echelons along the entire value chain. The developed analytical description of business echelons is acceptable both for embedding a digital management support system into various software products, and for conducting in-depth analysis and finding optimal solutions.The research of S.E.B., S.M.S. and I.V.K. is partially funded by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership program Priority 2030 (Agreement 075-15-2021-1333 dated 30 September 2021).Barykin, SE.; Smirnova, EA.; Chzhao, D.; Kapustina, IV.; Sergeev, SM.; Mikhalchevsky, YY.; Gubenko, AV.... (2021). Digital Echelons and Interfaces within Value Chains: End-to-End Marketing and Logistics Integration. Sustainability. 13(24):1-18. https://doi.org/10.3390/su132413929S118132

Recruitment Market Trend Analysis with Sequential Latent Variable Models

Recruitment market analysis provides valuable understanding of industry-specific economic growth and plays an important role for both employers and job seekers. With the rapid development of online recruitment services, massive recruitment data have been accumulated and enable a new paradigm for recruitment market analysis. However, traditional methods for recruitment market analysis largely rely on the knowledge of domain experts and classic statistical models, which are usually too general to model large-scale dynamic recruitment data, and have difficulties to capture the fine-grained market trends. To this end, in this paper, we propose a new research paradigm for recruitment market analysis by leveraging unsupervised learning techniques for automatically discovering recruitment market trends based on large-scale recruitment data. Specifically, we develop a novel sequential latent variable model, named MTLVM, which is designed for capturing the sequential dependencies of corporate recruitment states and is able to automatically learn the latent recruitment topics within a Bayesian generative framework. In particular, to capture the variability of recruitment topics over time, we design hierarchical dirichlet processes for MTLVM. These processes allow to dynamically generate the evolving recruitment topics. Finally, we implement a prototype system to empirically evaluate our approach based on real-world recruitment data in China. Indeed, by visualizing the results from MTLVM, we can successfully reveal many interesting findings, such as the popularity of LBS related jobs reached the peak in the 2nd half of 2014, and decreased in 2015.Comment: 11 pages, 30 figure, SIGKDD 201