Modeling Complex Networks For (Electronic) Commerce

NYU, Stern School of Business, IOMS Department, Center for Digital Economy Researc

Modeling Complex Networks For (Electronic) Commerce

NYU, Stern School of Business, IOMS Department, Center for Digital Economy Researc

Contribución del comercio electrónico al desempeño de las PyMEs industriales: un modelo estructural

El rol que juegan las Tecnologías de la Información y comunicación (TIC) para lograr un mejor desempeño organizacional aún requiere de un análisis más profundo entre las pequeñas y medianas empresas (PyMEs) de los países en desarrollo. Este estudio pretende ampliar la literatura empírica sobre la relación entre TIC, comercio electrónico y desempeño de las PyMEs en países en desarrollo. Para alcanzar este objetivo, utilizamos una muestra de 87 empresas manufactureras de la ciudad de Bahia Blanca, Argentina correspondiente al año 2015. Mediante la estimación de un Modelo de ecuación estructura, se obtiene que la adopción del comercio electrónico posee una influencia positiva y significativa en las ventas de las PyMEs la cual es potenciada por el nivel de uso de las TIC. Otros factores organizacionales tales como el tamaño de la empresa y los programas públicos explican el desempeño, pero no son predictores significativos de la adopción del comercio electrónico.The role Information and Communication Technologies (ICT) play in achieving a better organizational performance still needs further analysis among small and medium sized enterprises (SME) from developing countries. This study aims to extend the empirical literature on the relationship between ICT, electronic commerce and SME performance in developing countries. To achieve this goal, we employ a sample of 87 manufacturing firms from the city of Bahía Blanca, Argentina in the year 2015. By estimating a structural equation model, we obtain that electronic commerce adoption has a positive and significant influence on SME sales which is reinforced by the level of ICT use. Other organizational factors such as firm size and public programs explain performance, but are not significant predictors of the electronic commerce adoption.Fil: Alderete, Maria Veronica. Universidad Nacional del Sur. Departamento de Economía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentin

Business model requirements and challenges in the mobile telecommunication sector

The telecommunications business is undergoing a critical revolution, driven by innovative technologies, globalization, and deregulation. Cellular networks and telecommunications bring radical changes to the way telecom businesses are conducted. Globalization, on the other hand, is tearing down legacy barriers and forcing monopolistic national carriers to compete internationally. Moreover, the noticeable progress of many countries towards deregulation coupled with liberalization is significantly increasing telecom market power and allowing severe competition. The implications of this transition have changed the business rules of the telecom industry. In addition, entrants into the cellular industry have had severe difficulties due to inexistent or weak Business Models (BMs). Designing a BM for a mobile network operator is complex and requires multiple actors to balance different and often conflicting design requirements. Hence, there is a need to enhance operators’ ability in determining what constitutes the most viable business model to meet their strategic objectives within this turbulent environment. In this paper, the authors identify the main mobile BM dimensions along with their interdependencies and further analysis provides mobile network operators with insights to improve their business models in this new ‘boundary-less’ landscape

Customer purchase behavior prediction in E-commerce: a conceptual framework and research agenda

Digital retailers are experiencing an increasing number of transactions coming from their consumers online, a consequence of the convenience in buying goods via E-commerce platforms. Such interactions compose complex behavioral patterns which can be analyzed through predictive analytics to enable businesses to understand consumer needs. In this abundance of big data and possible tools to analyze them, a systematic review of the literature is missing. Therefore, this paper presents a systematic literature review of recent research dealing with customer purchase prediction in the E-commerce context. The main contributions are a novel analytical framework and a research agenda in the field. The framework reveals three main tasks in this review, namely, the prediction of customer intents, buying sessions, and purchase decisions. Those are followed by their employed predictive methodologies and are analyzed from three perspectives. Finally, the research agenda provides major existing issues for further research in the field of purchase behavior prediction online

An e-Business Model Ontology for Modeling e-Business

After explaining why business executives and academics should consider thinking about a rigorous approach to e-business models, we introduce a new e-Business Model Ontology. Using the concept of business models can help companies understand, communicate and share, change, measure, simulate and learn more about the different aspects of e-business in their firm. The generic e-Business Model Ontology (a rigorous definition of the e-business issues and their interdependencies in a company’s business model), which we outline in this paper is the foundation for the development of various useful tools for e-business management and IS Requirements Engineering. The e-Business Model Ontology is based on an extensive literature review and describes the logic of a “business system” for creating value in the Internet era. It is composed of four main pillars, which are Product Innovation, Infrastructure Management, Customer Relationship and Financial Aspects. These elements are then further decomposed.e-business models, ontology, e-business, strategy