Abstract

Management reporting is a complex activity that requires multiple systems and information resources created for other purposes in the course of daily work. When companies have to write their management reports, they often suffer the problems of an inadequate information management system. Technological solutions by themselves do not respond to the needs, unless they are embedded in an information governance framework.  

Abstract

Different authors have pointed out the importance of applying competitive intelligence (CI) to non-business sectors (public administration, universities, non-governmental organizations, etc.). Besides, universities increasingly apply management tools and techniques coming from the business field. On the other hand, in recent years universities have perceived an environmental pressure as a consequence of a) their implication in regional development where they are located, and b) their need to reform their program offerings according to the needs of society and the requirements of the labour market, as well as a result of the process of adapting their degrees to the European Higher Education Area (Bologna process). This paper describes and characterises CI practices in the universities and analyses the CI contribution to the design of degree courses. The research is based on qualitative methods, and data were collected through interviews. Results suggest that the use of CI in universities is mainly reactive, and addressed only to organisational tactics.

Abstract

New internet-based technologies are transforming the business model around the world. The use of new competitive watch and intelligence platforms is discussed. We review the information sources used in combination with other data (e.g., financial and technological data) to create intelligence. Analytical tools allow the detection of connections between data so that the company can identify changes, adapt products to new customers, or anticipate market movements. Three practical cases are presented using the VicuboCloud solution to collect and analyze information for decision-making.

Abstract

Big data has become an enormous asset for on-demand content distribution services, helping information supply and decision- making, regarding both the content of the database and suscribers to the database. In this article we describe and define big data and data management in a media company devoted to on-demand audiovisual content distribution: Netflix. This article suggests that big data is a prime strategy in media business and outlines the upcoming challenges that follow its global expansion.

Abstract

Big data has become an enormous asset for on-demand content distribution services, helping information supply and decision- making, regarding both the content of the database and suscribers to the database. In this article we describe and define big data and data management in a media company devoted to on-demand audiovisual content distribution: Netflix. This article suggests that big data is a prime strategy in media business and outlines the upcoming challenges that follow its global expansion.

Abstract

Providing support for users during their search sessions has\\ud been hailed as a major challenge in interactive information retrieval\\ud (IIR). Providing such support requires considering the context of the\\ud search and facilitating the work task at hand. In this paper, we consider\\ud the work tasks associated with air traffic analysts, who perform numerous\\ud searches using a multifaceted search interface in order to acquire business\\ud intelligence regarding particular events and situations. In particular, we\\ud develop a novel task completion engine and seamlessly incorporated it\\ud within a current air traffic search system to facilitate the comparison\\ud of information objects found. In a study with 24 participants, we found\\ud that they completed the complex work task faster using the comparison\\ud feature, but for simple work tasks, participants were slower. However,\\ud participants reported (statistically) significantly higher satisfaction and\\ud had (statistically) significantly higher accuracy using the search system\\ud equipped with task completion engine. These findings help to steer systems to provide a better support to users in their search process. Document type: Part of book or chapter of book

Abstract

This study analyzes Twitter’s contribution to green energy. More than 200,000 global tweets sent during 2020 containing the terms “green energy” OR “greenenergy” were analyzed. The tweets were captured by web scraping and processed using algorithms and techniques for the analysis of massive datasets from social networks. In particular, relationships between users (through mentions) were determined according to the Louvain multilevel algorithm to identify communities and analyze global (density and centralization) and node-level (centrality) metrics. Subsequently, the content of the conversation was subject to semantic analysis (co-occurrence of the most relevant words), hashtag analysis (frequency analysis), and sentiment analysis (using the Vader model). The results reveal nine main communities and their leaders, as well as three main topics of conversation and the emotional state of the digital discussion. The main communities revolve around politics, socioeconomic issues, and environmental activism, while the conversations, which have developed mostly in positive terms, focus on green energy sources and storage, being aligned with the main communities identified, i.e., on political, socioeconomic, and climate change issues. Although most of the conversations have been about socioeconomic issues, the presence of leading company accounts was minor. The main aim of this work is to take the first steps toward an innovative competitive intelligence methodology to study and determine trends within different scientific fields or technologies in society that will enable strategic decisions to be made.

Abstract

The radio broadcasting industry is facing a process of profound digital transformation throughout which, over the last 20 years, the strategies to preserve the traditional business model have prevailed. The consolidation of platformization and datafication in the economic management of the media requires adaptation of the radio broadcasting sector’s structures, management models, and corporate culture. Through an exhaustive bibliographic review, nonparticipant observation, and in-depth interviews conducted with heads of the systems, sales and marketing, content, and digital and innovation departments of the three leading Spanish companies (Prisa Radio, Grupo COPE, and Atresmedia Radio) and the state public broadcaster (RNE), we seek to identify the functional areas of the radio broadcasting company in which big data (BD) has a greater potential for application, trying to establish the differences in its utilization in the analogue and digital business model. The results revealed that the degree of BD implementation in the Spanish radio broadcasting industry was significantly different between the private sector –which within the last 2 or 3 years has begun to introduce, very incipiently, big data management, applied primarily to the analysis of digital audiences, these users’ consumer behavior, and business management– and the public sector, which so far has not adopted these technologies on a systematic basis.

Abstract

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence Intelligent traffic planning, the promotion of public transport and the improved interconnectedness of all road users in a city-wide communication infrastructure comprise the mobility characteristics of a smart city. Living in an era of Smart Cities emerging, we can make use of all the data available nowadays to better serve our lives with the best services. All the data generated every day by the Vehicles can be used to get a better insights to improve the quality of the available service as the creation of new routes, increase supervision on problematic areas, among others. This document intends to detail the project carried out at Carris, a public transportation company which operates Lisbon's buses, trams, and funiculars. The master thesis project aims to create a Business Intelligence solution to support planning decisions though the use of a Dashboard by presenting information about all relevant data collected on a bus daily route by the driver in order to get a better understating of a public transportation service and how can the organization improve them to rebuild schedules, create or eliminate routes, do some inspection on tickets validations inside the vehicles, etc. This project is supported by a Microsoft tool called Power BI that enables all the extraction, transformation and loading of data processes, based on an Azure SQL Data Warehouse based on Cloud services. The Business Dashboards are divided in 4 main areas inside the organization and will support Onboard Sales, Ticket validations, Route Planning and Onboard issues reported by the driver.

Abstract

Pilot briefings, in their traditional form, drown pilots in a sea of information. Rather than unfocused swathes of air traffic management (ATM) information,pilots require only the information for their specific flight. In this paper, we introduce the notion of ATM information cubes. We propose a conceptual framework with merge and abstraction operations for the combination and summarization of the information that is organized in ATM information cubes. A merge operation combines ATM information from individual cells of an ATM information cube. An abstraction operation summarizes the data items within a cell, replacing individual data items by more abstract data items with summary information. The result is a managementsummary of relevant information