Social Business Intelligence: a Literature Review and Research Agenda

The domains of Business Intelligence (BI) and social media have meanwhile become significant research fields. While BI aims at supporting an organization’s decisions by providing relevant analytical data, social media is an emerging source of personal and individual knowledge, opinion, and attitudes of stakeholders. For a while, a convergence of the two domains can be observed in real-world implementations and research, resulting in concepts like social BI. Many research questions still remain open – or even worse – are not yet formulated. Therefore, the paper aims at articulating a research agenda for social BI. By means of a literature review we systematically explored previous work and developed a framework. It contrasts social media characteristics with BI design areas and is used to derive the social BI research agenda. Our results show that the integration of social media (data) into a BI system has impact on almost all BI design objects

Development and validation of an instrument to measure the concern of smartphone users on the privacy invasion

O uso de smartphones cresceu de forma consistente ao longo dos últimos anos. Na medida que os aparelhos adquiriram novas funções, aumentou a sua capacidade de suportar serviços e aplicações. Preocupações sobre a privacidade durante o uso dos equipamentos como: coleta e armazenamento de dados, localização e uso de informações por terceiros sem autorização passaram a ser comuns entre os usuários. O presente artigo apresenta um questionário composto por cinco dimensões e dezesseis itens e tem como objetivo iniciar o processo de desenvolvimento e validação de uma escala para mensurar os fatores que influenciam a preocupação dos usuários sobre invasão de privacidade durante o uso de smartphones. Dentre as conclusões, verificou-se que a inclusão de duas dimensões que mensuram percepções positivas relacionadas ao uso dos aparelhos (Auto Eficácia e Benefício Percebido), pode contribuir para a mensuração de como os usuários avaliam as ameaças e benefícios ao usar os smartphones.The use of smartphones grew consistently over the past few years. To the extent that the appliances acquired new functions and increased its ability to support services and applications. Concerns about privacy during its use such as collection and storage of data, location, and use of information by third parties without authorization rose among users. This article presents a questionnaire composed of five dimensions and 16 items and aims to start the process of development and validation of a scale to measure the factors that influence users' concerns about invasion of privacy during the use of smartphones. Among the findings, we found that the inclusion of two dimensions that measure positive perceptions regarding the use of the equipment (Self-efficacy and perceived benefit), can contribute to the measurement of how the users assess the threats and benefits when using smartphones.El uso de smartphones creció de forma consistente a lo largo de los últimos años. A medida que los aparatos adquirieron nuevas funciones, aumentó su capacidad para soportar servicios y aplicaciones. Preocupaciones sobre la privacidad durante el uso de equipos como: recolección y almacenamiento de datos, ubicación y uso de informaciones por terceros desautorizados se volvieron comunes entre los usuarios. El presente artículo presenta una encuesta compuesta por cinco dimensiones y dieciséis ítems y tiene como objetivo iniciar el proceso de desarrollo y validación de una escala para medir los factores que influencian la preocupación de los usuarios sobre invasión de privacidad durante el uso de smartphones. Entre las conclusiones, se verificó que la inclusión de dos dimensiones que miden percepciones positivas relacionadas con el uso de los aparatos (Auto Eficacia y Benefício Percibido), puede contribuir a la medición de cómo los usuarios evalúan las amenazas y beneficios al usarlos

An Effective Method of Discovering Target Groups on Social Networking Sites

With the tremendous popularity of social networking sites in this era of Web 2.0, increasingly more users are contributing their comments and opinions about products, people, organizations, and many other entities. These online comments often have direct influence on consumers’ buying decisions and the public’s impressions of enterprises. As a result, enterprises have begun to explore the feasibility of using social networking sites as platforms to conduct targeted marking and enterprise reputation management for e-commerce and e-business. As indicated from recent marketing research, the joint influence power of a small group of active users could have considerable impact on a large number of consumers’ buying decisions and the public’s perception of the enterprises. To help enterprises conduct cost-effective targeted marketing and reputation management, this paper illustrates a novel methodology that can effectively discover the most influential users from social networking sites (SNS). In particular, the general methodology of mining the influence network from SNS and the computational models of mathematical programming for discovering the user groups with the maximal joint influence power are proposed. The empirical evaluation with real data extracted from social networking sites shows that the proposed method can effectively identify the most influential groups when compared to the benchmark methods. This study opens the door to effectively conducting targeted marketing and enterprise reputation management on social networking sites