Business intelligence, as a decision support tool in many organisations, has offered the ability to gather, store, access and analyse huge amounts of data so that better decisions can be made regarding customers, suppliers, employees, logistics and infrastructure Prior empirical studies of business intelligence and decision support applications (BIDSA) focus on technological and operational aspects and there is very little research to consider managerial and strategic factors The factors that affect the adoption of BIDSA have, however, not yet been fully investigated Differences in the use of information technology (IT) have been distinguished in different countries and so it is necessary to conduct a comprehensive study about the facilitating and inhibiting factors in the adoption and diffusion of BIDSA in Australia The aim of this study was thus to fill the gap by investigating factors affecting the successful adoption of BIDSA in Australian ERP user organisations by applying Rogers’ theory of Diffusion of Innovations (DOI), and to develop a conceptual model for the successful adoption of BIDSA

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The determinants of the adoption and application of business intelligence : an ERP perspective

With the start of current century, Business Intelligence (BI) has become an important and emerging tool, technique and technology in business world Organizations of all types across the globe are adopting BI for promoting business and getting advantage over competitors Business Intelligence is the processes, technologies, and tools that help organizations to change the data into information, information into knowledge and knowledge into plans that guide for better and effective decision making A Business Intelligence Competency Center (BICC) is an eternal legal unit with an organization, which encompasses dedicated members from both IT and business divisions The major reasons behind establishment of BICC are to ensure the adoption of BI at different levels of the organization by all stakeholders and to provide a platform to maintain and standardized the overall BI application Responsibilities of BICC include defining and managing the execution of the organization's BI strategy Moreover success of BI application within an organization can also be ensured through BICC In this paper, we have reviewed and analyzed BI implementations having BICC versus BI executions having no concept of BICC This study can also be used for future works like building Business Intelligence Competency Centers and/or measuring impact of Business Intelligence Competency Centers in success/failure of BI applications

Impact of business intelligence competency center in success/ failure of B.I. applications

A Business Intelligence (BI) system provides users with multi-dimensional information (a so-called 'BI product') to support decision-making. However, existing BI systems overlook the lineage metadata which supports individual data quality dimensions such as data believability and ease of understanding. Using a design science research paradigm, this paper proposes and develops an integrated framework (known as BI Product and Metacontent Map-'BIP-Map') to facilitate the traceability and accountability of BI products. Specifically, the business workflow layer of the integrated framework is modelled using business process modelling notation, and an information product map is used to model the second layer's information manufacturing process, whilst the third layer represents the metacontent detail of the data validation stage, from source system through to ETL, to the data warehousing stage. Also, the authors develop a BIP-Map informed prototype in collaboration with an online job advertising firm, the framework then being validated by key BI stakeholders of the firm. The integrated framework addresses individual-related data quality issues and builds user confidence by enhancing the traceability and accountability of a BI product.

http://dro.deakin.edu.au/eserv/DU:30068057/yeoh-improvingbusiness-2014.pdf

Improving Business Intelligence Traceability and Accountability: An Integrated Framework of BI Product and Metacontent Map

Business environment has become increasingly complex, along with the rapid development of economic globalization and information technology. organizations have to understand business intelligence (BI) system by showing information system success factors such as: system quality, information quality and service quality. Many organizations implemented BI system since there are a set of factors which influenced the success of the information system. The aim of this study is to investigate the relationship between information system success and BI system effectiveness in Jordanian banks. The study aims to promote better understanding of the benefits of the BI system that would be contributed toward enhancing BI system effectiveness. This paper used a quantitative methodological approach. 500 questionnaires were distributed to bank employees in Jordan with BI system in place. The returned and valid questionnaires were 386. data analysis showed there is a positive and significant relationship between information system success and BI system effectiveness.

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The impact of information system success on business intelligence system effectiveness

Acquiring useful Business Intelligence (BI) for highqualitative decision making is a challenging task in today’s dynamic business environment. Powerful tools are available such as ETL, data-warehouse, OLAP, data-mining and visualization. However, companies are lack of standardization of procedures in cultivating BI for improving the performance of the organization at all levels. In this paper, we developed a model that link dimensions of BI and processes together, for providing a good decision support, for disaster management organization in Pakistan as a case study. The model is implemented and validated using Oracle BI tools and techniques. The significance of this research work is the BI model proposed which provides exploratory abilities on the data, and linkages among BI processes from the conceptual BI dimensions.

Business Intelligence Modeling: A Case Study of Disaster Management Organization in Pakistan

As a kind of data-driven decision support systems, business intelligence tools focus too much on data and have low efficiency of decision making. Companies in today are more process-oriented than in the past and process-driven decision support system is emerging to help enterprises improve the speed and effectiveness of business operations. In order to provide the business intelligence system with the ability of process-driven decision making, we introduce the concept of business process management to the current business intelligence system. We add the process model component in our business intelligence model base. With the implementation of case-based reasoning and rule-based reasoning technology, the process models can be built and managed efficiently. In this paper we also provide a strategy for knowledge management in business intelligence system.

Hong Peng

Papers

Knowledge and Process Based Decision Support in Business Intelligence System