scholarly journals EFFECT OF BUSINESS INTELLIGENCE SYSTEM ON ORGANIZATIONAL AGILITY: EVIDENCE FROM SYRIA

2021 ◽  
Vol 56 (4) ◽  
pp. 288-299
Author(s):  
Hayan Hamdan ◽  
Abdul Aziz Abdul Rahman
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Primary Data ◽  
Organizational Agility ◽  
Intelligence System ◽  
Spss Software ◽  
Analyze Data

This study aims to identify the effect of the business intelligence (BI) system on organizational agility. A questionnaire has been used with Twenty-Three (23) questions to collect the primary data from Seventy-Five (75) people to achieve the objectives of this study. The study depends on SPSS software to analyze data collected by the questionnaire. The results prove a significant effect directly correlates between the business intelligence system, sensor agility, and application agility. The results also prove a significant effect with a strong direct correlation between the business intelligence system and the decision-making and organizational agility.

Implementation System of Business Intelligence System In The Company

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdul Hamid Arribathi ◽  
Maimunah Maimunah ◽  
Devi Nurfitriani
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Research Library ◽  
Decision Making Process ◽  
Intelligence System ◽  
Business Intelligence Systems

This study aims to determine the stages that must be implemented in building a Business Intelligence System structured and appropriate in building Business Intelligence Systems in an organization, and understand the important aspects that must be considered for investment development Business Intelligence System is increasing. Business must be based on the conditions and needs of the organization in achieving the desired goals. If these conditions occur, then the decision-making process will be better and more accurate. The purpose of this study is to determine the important aspects that must be understood and prepared in using the Business Intelligence System in an organization. The method used is the explanation as well as the research library of several books, articles and other literature.

scholarly journals Business Intelligence System via Group Decision Making

2016 ◽  
Vol 16 (3) ◽  
pp. 219-229 ◽  
Author(s):  
Daniela Borissova ◽  
Ivan Mustakerov ◽  
Dilian Korsemov
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Business Intelligence ◽  
Optimization Model ◽  
Web Application ◽  
Group Decision ◽  
Evaluation Criteria ◽  
Decision Makers ◽  
Intelligence System ◽  
Three Layer Architecture

Abstract In the paper a business intelligence tool based on group decision making is proposed. The group decision making uses a combinatorial optimization modeling technique. It takes into account weighted coefficients for evaluation criteria assigned by decision makers together with their scores for the alternatives in respect of these criteria. The proposed optimization model for group decision making considers also the knowledge level of the group members involved as decision makers. This optimization model is implemented in three-layer architecture of Web application for business intelligence by group decision making. Developed Web application is numerically tested for a representative problem for software choice considering six decision makers, three alternatives and 19 evaluation criteria. The obtained results show the practical applicability and effectiveness of the proposed approach.

Business Intelligence System Design and its Consequences for Knowledge Sharing, Collaboration, and Decision-Making

2020 ◽  
pp. 382-402
Author(s):  
Lapo Mola ◽  
Cecilia Rossignoli ◽  
Andrea Carugati ◽  
Antonio Giangreco
Keyword(s):  
Decision Making ◽  
Knowledge Sharing ◽  
Business Intelligence ◽  
Two Phase ◽  
Intelligence System ◽  
Business Intelligence Systems ◽  
Managerial Implications ◽  
Decision Making Processes

This exploratory study analyses the effects of the technical and organisational characteristics of business intelligence systems (BIS) on knowledge sharing, collaboration, and decision-making processes. The authors conducted a two-phase multi-method investigation. First, we surveyed 30 enterprises using BIS on a regular basis; then, we engaged in an in-depth case study with one of the respondent companies. Our results show that, on average, the technical and organisational characteristics of the BIS are positively associated with an increase in knowledge sharing, leading to an improvement in internal collaboration that subsequently brings improvement in the quality of decision-making. This case study adds that the way the BIS is designed and appropriated in organisations is important in obtaining such results is. A BIS being designed so that it can be appropriated by the general employee base is key in obtaining the desired organizational impacts. This suggests some requirements for BIS design that we will discuss in terms of theoretical and managerial implications.

scholarly journals Identification of k-Most Promising Features to Set Blue Ocean Strategy in Decision Making

2019 ◽  
Vol 4 (4) ◽  
pp. 367-384 ◽  
Author(s):  
Ritesh Kumar ◽  
Partha Sarathi Bishnu
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Similar Type ◽  
Multiple Features ◽  
Intelligence System ◽  
Typical Type

Abstract Customers demand typical type of products with multiple features. We want to develop a business intelligence system which helps the company to set the blue ocean strategy by discovering k-most promising features (k-MPF) from the customers’ query and a set of existing products of the similar type. In this paper, we have formulated k-MPF to set the blue ocean strategy with compatible features. We have experimented with our proposed algorithms using different synthetic and real datasets, and the results showed the effectiveness of our proposed algorithms.

Data Profiling and Data Quality Metric Measurement as a Proactive Input into the Operation of Business Intelligence Systems

2014 ◽  
pp. 253-270
Author(s):  
Scott Delaney
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Business Intelligence ◽  
Intelligence System ◽  
Use Of Data ◽  
Data Profiling ◽  
Business Intelligence Systems ◽  
Profiling Techniques ◽  
System Data ◽  
Taking Action

Business intelligence systems have reached business critical status within many companies. It is not uncommon for such systems to be central to the decision-making effectiveness of these enterprises. However, the processes used to load data into these systems often do not exhibit a level of robustness in line with their criticality to the organisation. The processes of loading business intelligence systems with data are subject to compromised execution, delays, or failures as a result of changes in the source system data. These ETL processes are not designed to recognise nor deal with such shifts in data shape. This chapter proposes the use of data profiling techniques as a means of early discovery of issues and changes within the source system data and examines how this knowledge can be applied to guard against reductions in the decision making capability and effectiveness of an organisation caused by interruptions to business intelligence system availability or compromised data quality. It does so by examining issues such as where profiling can be best be applied to get appropriate benefit and value, the techniques of establishing profiling, and the types of actions that may be taken once the results of profiling are available. The chapter describes components able to be drawn together to provide a system of control that can be applied around a business intelligence system to enhance the quality of organisational decision making through monitoring the characteristics of arriving data and taking action when values are materially different than those expected.

Business Intelligence System Design and its Consequences for Knowledge Sharing, Collaboration, and Decision-Making

2015 ◽  
Vol 11 (4) ◽  
pp. 1-25 ◽  
Author(s):  
Lapo Mola ◽  
Cecilia Rossignoli ◽  
Andrea Carugati ◽  
Antonio Giangreco
Keyword(s):  
Decision Making ◽  
Knowledge Sharing ◽  
Business Intelligence ◽  
Two Phase ◽  
Intelligence System ◽  
Business Intelligence Systems ◽  
Managerial Implications ◽  
Decision Making Processes

This exploratory study analyses the effects of the technical and organisational characteristics of business intelligence systems (BIS) on knowledge sharing, collaboration, and decision-making processes. The authors conducted a two-phase multi-method investigation. First, we surveyed 30 enterprises using BIS on a regular basis; then, we engaged in an in-depth case study with one of the respondent companies. Our results show that, on average, the technical and organisational characteristics of the BIS are positively associated with an increase in knowledge sharing, leading to an improvement in internal collaboration that subsequently brings improvement in the quality of decision-making. This case study adds that the way the BIS is designed and appropriated in organisations is important in obtaining such results is. A BIS being designed so that it can be appropriated by the general employee base is key in obtaining the desired organizational impacts. This suggests some requirements for BIS design that we will discuss in terms of theoretical and managerial implications.

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