Finest business plan

Field lab: Entrepreneurial and business ventures

Ideation at Canon business services

Digitalisation, globalisation, and evolving customer demands are only a few of the factors that are bound to transform the business process services industry for CBS. By investigating new ways to address these imminent challenges, this thesis explores the feasibility of implementing a formal approach to ideation to complement CBS’ service innovation practice. Two workshops were therefore conducted to put theory into action by generating new service ideas in a multifunctional team. Applying both divergent and convergent ideation techniques revealed that the latter improved an idea’s novelty and creativity as opposed to the expected increase in workability and relevance. Additionally, further analysis sheds light into the potential influence of individual characteristics and group dynamics on creativity. The thesis concludes with a discussion on the organisational implications of the findings and recommendations for future research.

[An editorial to] Recent Advances on Knowledge Discovery and Business Intelligence

Special issue guest editorial, June, 2015.

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

From a NoSQL data source to a business intelligence solution: An experiment

We are living in the era of Big Data. A time which is characterized by the continuous creation of vast amounts of data, originated from different sources, and with different formats. First, with the rise of the social networks and, more recently, with the advent of the Internet of Things (IoT), in which everyone and (eventually) everything is linked to the Internet, data with enormous potential for organizations is being continuously generated. In order to be more competitive, organizations want to access and explore all the richness that is present in those data. Indeed, Big Data is only as valuable as the insights organizations gather from it to make better decisions, which is the main goal of Business Intelligence. In this paper we describe an experiment in which data obtained from a NoSQL data source (database technology explicitly developed to deal with the specificities of Big Data) is used to feed a Business Intelligence solution.

Improving selective collection of urban waste using a business intelligence system

Today recovering urban waste requires effective management services, which usually imply sophisticated monitoring and analysis mechanisms. This is essential for the smooth running of the entire recycling process as well as for planning and control urban waste recovering. In this paper we present a business intelligence system especially designed and im- plemented to support regular decision-making tasks on urban waste management processes. The system provides a set of domain-oriented analytical tools for studying and characterizing poten- tial scenarios of collection processes of urban waste, as well as for supporting waste manage- ment in urban areas, allowing for the organization and optimization of collection services. In or- der to clarify the way the system was developed and the how it operates, particularly in process visualization and data analysis, we also present the organization model of the system, the ser- vices it disposes, and the interface platforms for exploring data.

Step towards of a homemade business intelligence solution: A case study in textile industry

Nowadays, organizations are increasingly looking to invest in business intelligence solutions, mainly private companies in order to get advantage over its competitors, however they do not know what is necessary. Business intelligence allows an analysis of consolidated information in order to obtain more specific outlets and certain indications in order to support the decision making process. You can take the right decision based on the data collected from different information systems present in the organization and outside of them. The textile sector is a sector where concept of Business Intelligence it is not many explored yet. Actually there are few textile companies that have a BI platform. Thus, the article objective is present an architecture and show all the steps by which companies need to spend to implement a successful free homemade Business Intelligence system. As result the proposed approach it was validated using real data aiming assess the steps defined.

Pervasive business intelligence platform to improve the quality of decision process in primary and secondary education – A Portuguese case study

Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.

Effects of forest structure components on the occurence, group size and density of groups of bare-face tamarin (Saguinus bicolor - primates: Callitrichinae) in Central Amazonia

This study analyzed the influence of forest structural components on the occurence, size and density of groups of Bare-face Tamarin (Saguinus bicolor) - the most threatened species in the Amazon - and produced the first map of distribution of groups in large-scale spatial within the area of continuous forest. Population censuses were conducted between November 2002 and July 2003, covering 6400 hectares in the Ducke Reserve, Manaus-AM, Brazil. Groups of S. bicolor were recorded 41 times accordingly distributed in the environments: plateau (20); slopes (12); and lowlands (09). The mean group size was 4.8 indiv./group, and ranged from 2 to 11 individuals. In the sites where the groups were recorded, and in an equivalent number of sites where no tamarins were found located at least 500 m from those where they had been recorded, we placed 50 m x 50 m plots to record the following forest structural components: abundance of trees; abundance of lianas; abundance of fruiting trees and lianas; abundance of snags; abundance of logs; percentage of canopy opening; leaf litter depth; and altitude. Bare-face Tamarin more often uses areas with lower abundance of forest logs, smaller canopy opening and with higher abundance of snags, areas in the forest with smaller canopy opening present higher density of S. bicolor groups. Apparently this species does not use the forest in a random way, and may select areas for its daily activities depending on the micro-environmental heterogeneity produced by the forest structural components.

Grupos de facto enquanto fenómeno organizativo plurissocietário: (in)admissibilidade da aplicação analógica dos artigos 501º e 502º do CSC aos grupos de facto qualificados

Dissertação de mestrado em Direito dos Contratos e das Empresas

Using students’ learning style to create effective learning groups in MCSCL environments

Students have different ways for learning and processing information. Some students prefer learning through seeing while others prefer learning through listening; some students prefer doing activities while other prefer reflecting.Some students reason logically, while others reason intuitively, etc. Identifying the learning style of each student, and providing learning content based on these styles represents a good method to enhance the learning quality. However, there are no efforts onhow to detect the students’ learning styles in mobile computer supported collaborative learning (MCSCL) environments. We present in this paper new ways for automatically detecting the learning styles of students in MCSCL environments based on the learning style model of Felder-Silverman. The identified learning styles of students could be then stored and used at anytime toassign each one of them to his/her appropriate learning group.

Corporate Performance Management através da integração de Business Intelligence e Business Process Management

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Facilitadores e obstáculos do empreendedorismo: o caso das muambeiras de Lubango

Dissertação de mestrado em Estudos de Gestão

Business intelligence no suporte às autarquias locais e à sua gestão orçamental

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Exploração de dados para soluções de retalho em business intelligence

Dissertação de mestrado integrado em Engenharia de Gestão e Sistemas de Informação