Although studies are conducted on economical gains due to BI system adoption, limited knowledge is available on factors which influence BI system usage. Identifying these factors is necessary for organisations because this may enable the design of effective BI systems, thus increasing the chance of firms adopting them to realise the actual value inherent in the exploitation of BI systems. The purpose of this study is, therefore, to investigate factors which influence BI system usage. The investigation employed constructs derived from three theoretical frameworks, namely technology acceptance model (TAM), task-technology fit (TTF) and social cognitive theory (SCT) as follows: intention to use, perceived usefulness, perceived ease use, task characteristics, technology characteristics, task-technology fit and computer self-efficacy. To test the hypotheses, data was collected by administering the study to 682 BI system users in a South African financial institution, SA-Bank, wherein 193 usable responses were received. The findings of the study with partial least squares (PLS) analysis indicated support for the joint use of constructs from the three theoretical frameworks, explaining 65% of BI system usage variance. Furthermore, the perceived usefulness of a BI system reflected a stronger influence as a factor of BI system usage over the beliefs that the system was easy to use, and the belief that it was aligned to the performance of business tasks. An unusual outcome in this study was the lack of influence of computer self-efficacy on BI system usage. Nonetheless, the study extended validation of the use of constructs derived from the three theoretical frameworks for a BI technology in the context of SA-Bank, thereby contributing to theory. Finally, the results of hypothesis testing suggested a starting point for practitioners towards designing BI systems, and recommendations and suggestions are included in this report.

In the modern competitive business activity, information collection becomes very important to support enterprises management groups to make decision. Many enterprises consider knowledge management and application are very important issues in the Knowledge Economy era. Therefore, Business Intelligence System becomes more popular and adopted by many enterprises like the flames added by the fuel in Knowledge Economy era. Enterprise management with Balanced Scorecard is also introduced by well-known scholars as well at this stage. The combination of Business Intelligence System and Balanced Scorecard becomes more efficient for enterprise management and pushes the modern enterprises forward to the Open Knowledge Economy era. The main purpose of this research is to adopt architecture theory to construct the Architecture Oriented Business Intelligence system with Balanced Scorecard Model(AOBIBSCM). This model provides an efficient construction method for the constructors to control the system with the whole system overview. The constructors can easily find out the Structure elements, Services of structure elements, Relationship of structure elements, Structure Behavior Coalescence, in order to compare with the real world behaviors and allow constructors validate and realize the sequence of behaviors. The tight combination of structure point of view, behavior point of view and other points of view integrates structure and behavior neatly, making it far superior than Non-Architecture designed method which separates structure and behavior. Non-Architecture construction method is easy to lead the structure and behavior to different routes and wastes time to re-design and adjust the system. This research adopts logical theorem to construct AOBIBSCM. It constructs (1)AOBIBSCM¡Aand describes (2)Non-AOBIBSCM(NAOBIBSCM) construction method, then (3)Compare AOBIBSCM and NAOBIBSCM, then show the benefit of AOBIBSCM. The contribution of this research is to construct AOBIBSCM which includes Structure element diagrams, Hierarchy of structure element diagrams, Service of structure element diagrams, Relationship of structure element diagrams, Structure and behavior coalescence diagram, Sequence diagrams. Our research furnishes an efficient construction method for enterprises to install AOBIBSC, and reduces the construction risk and cost, and provides more discussion space of the system real implementation, testing, construction and performance tuning.

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It happens quite often that most Business Intelligence System (BIS) projects are never near to their completion. While there are many reasons for such high failure rate, the major unsuccessful factors of BIS result in ¡§Member¡¨, ¡§Organization¡¨, and ¡§Technique¡¨. Especially, it seems there is not yet a model and methodology gluing together the interrelationship among people, source of information, and BIS. This thesis aims to assist the enterprise by defining a model of Architecture-Oriented Analysis of Business Intelligence Systems¡¦ Requirement which helps analyze the system with ease. The model emphasizes on the structure behavior coalescence. Using this approach of structure behavior coalescence, developers would devise and adjust the BIS more flexible and adaptable. Architecture-Oriented Analysis-Model is a model which includes many viewpoints, which help analyze several problems caused by mixed BIS products. The main purpose of this research is to achieve Business Intelligence Systems¡¦Requirement through the establishment of the model, and raise the strike-rate and efficiency on the construction of any BIS.

39 million people in the world are blind and approximately 15 million of them live in India. Aravind Eye Care System is the biggest provider of eye care in India and the world and it continues to expand and spread medical understanding and best practice to improve ophthalmological care. Aravind Hospitals measure data of performance indicators for management and identify best practice. Currently, each department handles data of these parameters in locally stored excel sheets which limiting benchmarking in real-time. The main objective of this project has been to develop a user-friendly web platform that enables real time benchmarking across all of Aravind’s hospitals. A prototype of a web based business intelligence system has been developed as a proof of concept. The aim of this prototype has been to enable benchmarking across Aravind’s hospitals. The impact has been studied to analyse the extents to which the organization can become more efficient through continuous benchmarking. Initially, a database was developed containing data from the glaucoma clinics in Coimbatore, Madurai, Pondicherry and Tirunelveli. Subsequent was a web platform developed which presents the data dynamically with Google Charts. Interviews and analyses support the implementation of a business intelligence system at Aravind’s Hospitals. Testing and analysis have proven that a business intelligence system can improve value, create innovation and spread best practice at Aravind’s Hospitals. / 39 miljoner personer i världen är blinda och uppskattningsvis 15 miljoner av dem bor i Indien. Aravind Eye Care System är de största leverantörerna av ögonsjukvård i Indien och i världen. De fortsätter att växa och sprida medicinsk kunskap och best practice för att förbättra ögonsjukvården. Aravinds sjukhus mäter data på nyckelparametrar av verksamheten för management och för att identifiera best practice. För närvarande så hanterar varje avdelning data av dessa parametrar i lokalt lagrade Excel dokument vilket begränsar benchmarking i realtid. Det huvudsakliga syftet med detta projekt har varit att utveckla en användarvänlig web plattform som möjliggör benchmarking mellan Aravinds sjukhus i realtid. En prototyp av ett web baserat business intelligence system har utvecklats i form av ett proof of concept. Syftet med denna prototyp har varit att möjliggöra benchmarking mellan Aravinds sjukhus. Dess påverkan har utvärderats och analyserats för att studera till vilken utsträckning organisationen kan bli mer effektiv genom kontinuerlig benchmarking. Till en början har en databas utvecklats för att hantera data från glaukom klinikerna i Coimbatore, Madurai, Pondicherry and Tirunelveli. Där efter har en web plattform utvecklats som presenterar dynamisk data med Google Charts. Intervjuer och analyser stödjer implementationen av ett business intelligence system på Aravinds sjukhus. Denna rapport har bevisat att det är genomförbart att utveckla en skalbar open-source webbplattform som möjliggör benchmarking i realtid. Tester och analyser har även visat att ett business intelligence kan vara värdeskapande, innovation skapande samt sprida kunskap på Aravinds sjukhus.

By using systems, organizations can increase the flow of information by getting the right information, in the right place and with the right person, at the right time. A system that has become more common today are Business Intelligence systems, which aims to support the decision-making process within organizations. Over the last decade, cloud systems have also become more common. Cloud systems are provided on cloud platforms over the Internet and are delivered like services. The adoption and use of such cloud services differs from the implementation and the use of traditional systems, which are implemented on premise by the customer. The system supplier has huge control over the cloud system, which leaves the customer with less control. The purpose of this study is to identify challenges that can arise when adopting and using a cloud- based Business Intelligence system, from a customer perspective. By using a case study design, we want to identify the different challenges that the customer may face when adopting and using such a system. This study is based on several literature reviews on topics such as Business Intelligence systems, cloud services, information security and user resistance etcetera. This study is also based on four qualitative interviews, from two respondents that sell the current cloud-based Business Intelligence system, as well as from two respondents who have chosen to use the system in their organizations. The study results in a conclusion that presents four overall themes that include a variety of challenges. The challenges relate to themes such as time to get started, information security requirements, needs of education and support and lastly, understanding the systems and its user interface. Several of the challenges can be specifically associated with the nature of systems and how the system is delivered, the customers’ knowledge has also been shown to be a significant aspect. Keywords: System adoption, System usage, Cloud service, Business Intelligence systems

An information society under constant development enables organizations to have access to a growing supply of information. Handled in an efficient manner, information can be a valuable, competitive resource. This can be achieved by investing in a Business Intelligence system (BI system). BI system's main function is to manage large amounts of unstructured data, convert it into useful information, which in turn will be used as a basis for performance management. The purpose of this study is that, through qualitative, semi-structured, in-depth interviews, to examine the perceived benefit of using BI systems to support business governance. This benefit is analyzed using theories such as traditional, bounded and flexible-bounded rationality, cognitive bias and theories of man's ability to think intuitively and reflective. The benefits of BI systems will also be analyzed using the theories of the communication process, conflicts in decision making and DIKW pyramid describing the process data, information, knowledge, wisdom. It also analyzes the benefits of BI systems using agency theory. The results show that users of BI systems are experiencing the benefits as follow: BI systems provide increased access to information in the organization, increasing the ability to handle large amounts of information, creating more fact-based decisions, freeing up time for analysis, reducing opportunistic behavior and facilitates internal communication. This creates flexibility in the bounded rationality, a more reflective decision-making process that improves the prospects to make rational decisions. Users go higher up in DIKW pyramid. BI systems reduce the information asymmetry between principal and agent. BI systems reduce uncertainty in decision reducing the risk of conflict. Training and practice are essential for BI systems to generate benefits. Unlike previous research, this study shows that BI systems are well integrated into organizations as well as live up to expectations. A new aspect of BI systems is that they reduce the risk of opportunistic behavior.

Nos últimos trinta anos a conjuntura na qual as organizações atuam passou por profundas transformações, criando um contexto complexo, altamente competitivo e instável. No intuito de se manterem competitivas, é imperativo que as organizações criem mecanismos para responderem às pressões externas. Tais respostas podem ser obtidas por meio de estratégias de aumento na produtividade nas operações; aumento na agilidade para atuar em novos mercados; melhoria no processo de tomada de decisão e melhoria na Qualidade da Informação (QI). A TI vem desde a década de 70 evoluindo na construção de sistemas de inteligência de negócios (BI - Business Intelligence) para apoiar e melhorar o processo de tomada de decisão. Um dos principais objetivos do sistema de BI é disponibilizar informações com qualidade para os seus usuários. Na literatura científica ainda não há uma convergência de opiniões dos autores na definição de quais dimensões da QI devem ser utilizadas no contexto de sistema de BI sob a perspectiva do usuário. A identificação de quais dimensões da QI são relevantes no contexto de sistema de BI na percepção do usuário é o problema desta pesquisa. Foi realizada uma revisão da literatura, a qual identificou trinta dimensões da qualidade da informação para o contexto de sistema de BI. A metodologia para resolver esse problema é de natureza exploratória, utilizando a estratégia de levantamento para coleta de dados, estudo de caso e método quantitativo para as análises. O estudo de caso único ocorreu em uma empresa de grande porte do setor financeiro brasileiro, a qual possui uma grande quantidade de sistemas de BI e de usuários. Um questionário web foi utilizado para coleta dos dados. Foram coletadas 170 observações válidas. Para análise dos resultados, foram empregadas análises descritivas e técnicas de análise multivariada de dados, como a Regressão Múltipla, a Análise Fatorial Exploratória e a Análise de Correspondência (Homals). Nos resultados foram identificadas vinte dimensões da QI relevantes para o contexto de sistema de BI na perspectiva do usuário, que formam quatro categorias: \"Qualidade de Conteúdo\", \"Qualidade Intrínseca e da Acessibilidade\", \"Valor Agregado\" e \"Qualidade Contextual\". Também foi possível identificar que as características dos usuários interferem nas suas percepções em relação à QI do sistema de BI. Os resultados ajudam a guiar pesquisas futuras sobre a QI no contexto de BI e possui aplicações práticas para as empresas que desejam avaliar a percepção dos seus usuários em relação à QI presente no sistema de BI. / In the past thirty years the conjuncture in which organizations operate faced deep transformations, creating a complex context, highly competitive and instable environment. In order to keep competitive, it is imperative that companies generate mechanisms to respond these external pressures. These answers can be created by productivity increasing strategies; increasing the agility to function in new markets; improvement of decision making-processes and enhancing Information Quality (IQ). Since the 1970 decade, IT has been evolving in Business Intelligence (BI) systems construction to support and improve the decision-making process. One of the main goals of BI system is to provide IQ for users. On the scientific literature there is still no convergence between the authors regarding the definition of which IQ dimensions must be used in context of BI system from a user perspective. The identification of which IQ dimension is relevant in context of BI system from the user perspective is the research problem. Thirty information quality dimensions were identified on the literature review for BI context. The research method of this study is exploratory, based on online survey strategy for data collection and quantitative methods for analysis. A single case study was conducted in a big financial company in Brazil, which has a great amount of BI systems and users. A total of 170 responses were considered valid. Descriptive statistics and multivariate data techniques as Multiple Regression, Exploratory Factor Analysis and Multiple Correspondence Analysis (Homals) were used for analysis. Results highlight twenty IQ dimensions which are important in context of BI system from a user perspective, which forming four categories: \"Content Quality\", \"Intrinsic and Accessibility Quality\", \"Aggregated Value\" and \"Contextual Quality\". Also, the results suggest that the characteristics of the users leverage their perceptions on IQ in context of BI. These findings guide future researches about IQ in context of BI and may also have practice contributions for companies that want to evaluate IQ from user perspective.

Nos últimos trinta anos a conjuntura na qual as organizações atuam passou por profundas transformações, criando um contexto complexo, altamente competitivo e instável. No intuito de se manterem competitivas, é imperativo que as organizações criem mecanismos para responderem às pressões externas. Tais respostas podem ser obtidas por meio de estratégias de aumento na produtividade nas operações; aumento na agilidade para atuar em novos mercados; melhoria no processo de tomada de decisão e melhoria na Qualidade da Informação (QI). A TI vem desde a década de 70 evoluindo na construção de sistemas de inteligência de negócios (BI - Business Intelligence) para apoiar e melhorar o processo de tomada de decisão. Um dos principais objetivos do sistema de BI é disponibilizar informações com qualidade para os seus usuários. Na literatura científica ainda não há uma convergência de opiniões dos autores na definição de quais dimensões da QI devem ser utilizadas no contexto de sistema de BI sob a perspectiva do usuário. A identificação de quais dimensões da QI são relevantes no contexto de sistema de BI na percepção do usuário é o problema desta pesquisa. Foi realizada uma revisão da literatura, a qual identificou trinta dimensões da qualidade da informação para o contexto de sistema de BI. A metodologia para resolver esse problema é de natureza exploratória, utilizando a estratégia de levantamento para coleta de dados, estudo de caso e método quantitativo para as análises. O estudo de caso único ocorreu em uma empresa de grande porte do setor financeiro brasileiro, a qual possui uma grande quantidade de sistemas de BI e de usuários. Um questionário web foi utilizado para coleta dos dados. Foram coletadas 170 observações válidas. Para análise dos resultados, foram empregadas análises descritivas e técnicas de análise multivariada de dados, como a Regressão Múltipla, a Análise Fatorial Exploratória e a Análise de Correspondência (Homals). Nos resultados foram identificadas vinte dimensões da QI relevantes para o contexto de sistema de BI na perspectiva do usuário, que formam quatro categorias: \"Qualidade de Conteúdo\", \"Qualidade Intrínseca e da Acessibilidade\", \"Valor Agregado\" e \"Qualidade Contextual\". Também foi possível identificar que as características dos usuários interferem nas suas percepções em relação à QI do sistema de BI. Os resultados ajudam a guiar pesquisas futuras sobre a QI no contexto de BI e possui aplicações práticas para as empresas que desejam avaliar a percepção dos seus usuários em relação à QI presente no sistema de BI. / In the past thirty years the conjuncture in which organizations operate faced deep transformations, creating a complex context, highly competitive and instable environment. In order to keep competitive, it is imperative that companies generate mechanisms to respond these external pressures. These answers can be created by productivity increasing strategies; increasing the agility to function in new markets; improvement of decision making-processes and enhancing Information Quality (IQ). Since the 1970 decade, IT has been evolving in Business Intelligence (BI) systems construction to support and improve the decision-making process. One of the main goals of BI system is to provide IQ for users. On the scientific literature there is still no convergence between the authors regarding the definition of which IQ dimensions must be used in context of BI system from a user perspective. The identification of which IQ dimension is relevant in context of BI system from the user perspective is the research problem. Thirty information quality dimensions were identified on the literature review for BI context. The research method of this study is exploratory, based on online survey strategy for data collection and quantitative methods for analysis. A single case study was conducted in a big financial company in Brazil, which has a great amount of BI systems and users. A total of 170 responses were considered valid. Descriptive statistics and multivariate data techniques as Multiple Regression, Exploratory Factor Analysis and Multiple Correspondence Analysis (Homals) were used for analysis. Results highlight twenty IQ dimensions which are important in context of BI system from a user perspective, which forming four categories: \"Content Quality\", \"Intrinsic and Accessibility Quality\", \"Aggregated Value\" and \"Contextual Quality\". Also, the results suggest that the characteristics of the users leverage their perceptions on IQ in context of BI. These findings guide future researches about IQ in context of BI and may also have practice contributions for companies that want to evaluate IQ from user perspective.

Am Lehrstuhl Wirtschaftsinformatik II der TU Chemnitz arbeitet die Nachwuchsforschergruppe Computer-Aided Warehouse Engineering (CAWE), die seit August 2010 besteht, an einem vollständig modellgetriebenen Vorgehen zur Unterstützung des Lebenszyklus von Business-Intelligence-Systemen (BI-Systemen). Neben der Durchführung von Grundlagenforschung hat die Nachwuchsforschergruppe die Erstellung eines Software-Prototyps zum Ziel. Eine wichtige Funktionalität ist die automatische Erzeugung von Systemdokumentationen für verschiedene BI-Systeme mit dem Schwerpunkt auf den Architekturkomponenten. Im Rahmen des Forschungsprojektes führte die CAWE Nachwuchsforschergruppe unter der Leitung von Prof. Dr. Peter Gluchowski in 2011 eine bundesweite Umfrage bei mittelständischen bis großen Unternehmen zu folgendem Thema durch: „Softwaregestütztes Lebenszyklusmanagement und aktuelles Dokumentationsgeschehen für Business Intelligence-Systeme“.