A three-pronged approach to social business: a Brazilian multi-case analysis

Social businesses present a new paradigm to capitalism, in which private companies, non-profit organizations and civil society create a new type of business with the main objective of solving social problems with financial sustainability and efficiency through market mechanisms. As any new phenomenon, different authors conceptualize social businesses with distinct views. This article aims to present and characterize three different perspectives of social business definitions: the European, the American and that of the emerging countries. Each one of these views was illustrated by a different Brazilian case. We conclude with the idea that all the cases have similar characteristics, but also relevant differences that are more than merely geographical. The perspectives analyzed in this paper provide an analytical framework for understanding the field of social businesses. Moreover, the cases demonstrate that in the Brazilian context the field of social business is under construction and that as such it draws on different conceptual influences to deal with a complex and challenging reality.

Metodi e strumenti di business intelligence per i processi di ciclo attivo: un caso di studio in un?azienda di servizi

Relazione tecnica e funzionale, con rimandi teorici disciplinari, riguardo la realizzazione di un sistema informatico su piattaforma Microsoft per l'organizzazione e la fruizione delle informazioni di Ciclo attivo in un'azienda di servizi di grandi dimensioni.

Pervasive Business Intelligence

In the last few years, a new generation of Business Intelligence (BI) tools called BI 2.0 has emerged to meet the new and ambitious requirements of business users. BI 2.0 not only introduces brand new topics, but in some cases it re-examines past challenges according to new perspectives depending on the market changes and needs. In this context, the term pervasive BI has gained increasing interest as an innovative and forward-looking perspective. This thesis investigates three different aspects of pervasive BI: personalization, timeliness, and integration. Personalization refers to the capacity of BI tools to customize the query result according to the user who takes advantage of it, facilitating the fruition of BI information by different type of users (e.g., front-line employees, suppliers, customers, or business partners). In this direction, the thesis proposes a model for On-Line Analytical Process (OLAP) query personalization to reduce the query result to the most relevant information for the specific user. Timeliness refers to the timely provision of business information for decision-making. In this direction, this thesis defines a new Data Warehuose (DW) methodology, Four-Wheel-Drive (4WD), that combines traditional development approaches with agile methods; the aim is to accelerate the project development and reduce the software costs, so as to decrease the number of DW project failures and favour the BI tool penetration even in small and medium companies. Integration refers to the ability of BI tools to allow users to access information anywhere it can be found, by using the device they prefer. To this end, this thesis proposes Business Intelligence Network (BIN), a peer-to-peer data warehousing architecture, where a user can formulate an OLAP query on its own system and retrieve relevant information from both its local system and the DWs of the net, preserving its autonomy and independency.

Studio e implementazione di una soluzione di business intelligence a supporto dell'analisi economico finanziaria

Progetto di tesi svolto in azienda. Studio dei principali concetti di Business Intelligence (BI) e degli strumenti per la BI. Confronto tra i principali vendor nel mercato dell'analisi dei dati e della Business Intelligence. Studio e reigegnerizzazione di un modello per l'analisi economico finanziaria dei fornitori/clienti di un'azienda. Realizzazione di un prototipo del modello utilizzando un nuovo strumento per la reportistica: Tableau. Il prototipo si basa su dati economici finanziari estratti da banche dati online e forniti dall'azienda cliente. Implementazione finale del database e di un flusso automatico per la riclassificazione dei dati di bilancio.

Integrating structured and unstructured data in a business-intelligence-system

The recent liberalization of the German energy market has forced the energy industry to develop and install new information systems to support agents on the energy trading floors in their analytical tasks. Besides classical approaches of building a data warehouse giving insight into the time series to understand market and pricing mechanisms, it is crucial to provide a variety of external data from the web. Weather information as well as political news or market rumors are relevant to give the appropriate interpretation to the variables of a volatile energy market. Starting from a multidimensional data model and a collection of buy and sell transactions a data warehouse is built that gives analytical support to the agents. Following the idea of web farming we harvest the web, match the external information sources after a filtering and evaluation process to the data warehouse objects, and present this qualified information on a user interface where market values are correlated with those external sources over the time axis.

Market, Management and Profession. Social Business in the Polder

In a recent policy document of the organized employers in the care and welfare sector in The Netherlands (the MO Group), directors and board members of care and welfare institutions present themselves as "social entrepreneurs", managing their institutions as look-a like commercial companies. They are hardly criticized and there is not any countervailing power of significance. The workers are focusing on their own specialized professional fields and divided as a whole. Many government officials are in favour or do not bother. The relatively small number of intellectual workers in Dutch care and welfare are fragmented and pragmatic. From a democratic point of view this is a worrying situation. From a professional point of view the purpose and functions of professional care and welfare work are at stake. The penetration of market mechanisms and the take-over by commercially orientated managers result from unquestioned adaptation of Anglo-Saxon policy in The Netherlands in the 1990's, following the crisis of the Welfare State in the late 1980's. The polder country is now confronted fully with the pressure and negative effects of unbalanced powers in the institutions, i.e. Managerialism. After years of silence, the two principal authentic critics of Dutch care and welfare, Harry Kunneman and Andries Baart, are no longer voices crying in the wilderness, but are getting a response from a growing number of worried workers and intellectuals. Kunneman and Baart warn against the restriction of professional space and the loss of normative values and standards in the profession. They are right. It is high time to make room for criticism and to start a debate about the future of the social professions in The Netherlands, better: in Europe. Research, discussion and action have to prove how worrying the everyday situation of professional workers is, what goals have to be set and what strategy to be chosen.

Open business intelligence: on the importance of data quality awareness in user-friendly data mining

Citizens demand more and more data for making decisions in their daily life. Therefore, mechanisms that allow citizens to understand and analyze linked open data (LOD) in a user-friendly manner are highly required. To this aim, the concept of Open Business Intelligence (OpenBI) is introduced in this position paper. OpenBI facilitates non-expert users to (i) analyze and visualize LOD, thus generating actionable information by means of reporting, OLAP analysis, dashboards or data mining; and to (ii) share the new acquired information as LOD to be reused by anyone. One of the most challenging issues of OpenBI is related to data mining, since non-experts (as citizens) need guidance during preprocessing and application of mining algorithms due to the complexity of the mining process and the low quality of the data sources. This is even worst when dealing with LOD, not only because of the different kind of links among data, but also because of its high dimensionality. As a consequence, in this position paper we advocate that data mining for OpenBI requires data quality-aware mechanisms for guiding non-expert users in obtaining and sharing the most reliable knowledge from the available LOD.

Empowering global software development with business intelligence

Context: Global Software Development (GSD) allows companies to take advantage of talent spread across the world. Most research has been focused on the development aspect. However, little if any attention has been paid to the management of GSD projects. Studies report a lack of adequate support for management’s decisions made during software development, further accentuated in GSD since information is scattered throughout multiple factories, stored in different formats and standards. Objective: This paper aims to improve GSD management by proposing a systematic method for adapting Business Intelligence techniques to software development environments. This would enhance the visibility of the development process and enable software managers to make informed decisions regarding how to proceed with GSD projects. Method: A combination of formal goal-modeling frameworks and data modeling techniques is used to elicitate the most relevant aspects to be measured by managers in GSD. The process is described in detail and applied to a real case study throughout the paper. A discussion regarding the generalisability of the method is presented afterwards. Results: The application of the approach generates an adapted BI framework tailored to software development according to the requirements posed by GSD managers. The resulting framework is capable of presenting previously inaccessible data through common and specific views and enabling data navigation according to the organization of software factories and projects in GSD. Conclusions: We can conclude that the proposed systematic approach allows us to successfully adapt Business Intelligence techniques to enhance GSD management beyond the information provided by traditional tools. The resulting framework is able to integrate and present the information in a single place, thereby enabling easy comparisons across multiple projects and factories and providing support for informed decisions in GSD management.

Design and development of agent-based procurement system to enhance business intelligence

The purpose of this research is to propose a procurement system across other disciplines and retrieved information with relevant parties so as to have a better co-ordination between supply and demand sides. This paper demonstrates how to analyze the data with an agent-based procurement system (APS) to re-engineer and improve the existing procurement process. The intelligence agents take the responsibility of searching the potential suppliers, negotiation with the short-listed suppliers and evaluating the performance of suppliers based on the selection criteria with mathematical model. Manufacturing firms and trading companies spend more than half of their sales dollar in the purchase of raw material and components. Efficient data collection with high accuracy is one of the key success factors to generate quality procurement which is to purchasing right material at right quality from right suppliers. In general, the enterprises spend a significant amount of resources on data collection and storage, but too little on facilitating data analysis and sharing. To validate the feasibility of the approach, a case study on a manufacturing small and medium-sized enterprise (SME) has been conducted. APS supports the data and information analyzing technique to facilitate the decision making such that the agent can enhance the negotiation and suppler evaluation efficiency by saving time and cost.