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Register a new userLaws governing development of institutionalization of e-commerce
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Added by
Mikhail Kaluzhsky L.
Publication date
2015
fields
Informatics Engineering
and research's language is
English
Authors
Mikhail Kaluzhsky
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Article about objective laws of formation of social and economic institutes in system of electronic commerce. Rapid development of Internet technologies became the reason of deep institutional transformation of economic relations. The author analyzes value transaction costs as motive power of formation of new economic institutes in network economy.
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Web 3.0 promises to have a significant effect in users and businesses. It will change how people work and play, how companies use information to market and sell their products, as well as operate their businesses. The basic shift occurring in Web 3.0 is from information-centric to knowledge-centric patterns of computing. Web 3.0 will enable people and machines to connect, evolve, share and use knowledge on an unprecedented scale and in new ways that make our experience of the Internet better. Additionally, semantic technologies have the potential to drive significant improvements in capabilities and life cycle economics through cost reductions, improved efficiencies, enhanced effectiveness, and new functionalities that were not possible or economically feasible before. In this paper we look to the semantic web and Web 3.0 technologies as enablers for the creation of value and appearance of new business models. For that, we analyze the role and impact of Web 3.0 in business and we identify nine potential business models, based in direct and undirected revenue sources, which have emerged with the appearance of semantic web technologies.
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Customers trust in vendors reputation is a key factor that facilitates economic transactions in e-commerce platforms. Although the trust-sales relationship is assumed robust and consistent, its empirical evidence remains neglected for Latin American countries. This work aims to provide a data-driven comprehensive framework for extracting valuable knowledge from public data available in the leading Latin American e-commerce platform with commercial operations in 18 countries. Only Argentina, Brasil, Chile, Colombia, Ecuador, Mexico, Uruguay, and Venezuela showed the highest trust indexes among all nations analyzed. The trust-sales relationship was statistically inconsistent across nations but worked as the most important predictor of sales, followed by purchase intention and price.
The rich body of Bandit literature not only offers a diverse toolbox of algorithms, but also makes it hard for a practitioner to find the right solution to solve the problem at hand. Typical textbooks on Bandits focus on designing and analyzing algorithms, and surveys on applications often present a list of individual applications. While these are valuable resources, there exists a gap in mapping applications to appropriate Bandit algorithms. In this paper, we aim to reduce this gap with a structured map of Bandits to help practitioners navigate to find relevant and practical Bandit algorithms. Instead of providing a comprehensive overview, we focus on a small number of key decision points related to reward, action, and features, which often affect how Bandit algorithms are chosen in practice.
In recent years, many new and interesting models of successful online business have been developed, including competitive models such as auctions, where the product price tends to rise, and group-buying, where users cooperate obtaining a dynamic price that tends to go down. We propose the e-fair as a business model for social commerce, where both sellers and buyers are grouped to maximize benefits. e-Fairs extend the group-buying model aggregating demand and supply for price optimization as well as consolidating shipments and optimize withdrawals for guaranteeing additional savings. e-Fairs work upon multiple dimensions: time to aggregate buyers, their geographical distribution, price/quantity curves provided by sellers, and location of withdrawal points. We provide an analytical model for time and spatial optimization and simulate realistic scenarios using both real purchase data from an Italian marketplace and simulated ones. Experimental results demonstrate the potentials offered by e-fairs and show benefits for all the involved actors.
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