Role Of Business Intelligence Research Articles

The Role of Business Intelligence in Developing Tax Performance: An Applied Research in The General Taxing Authority

Objective: The present research aims at examining the role of business intelligence in developing tax performance in the General Tax Authority of a developing county. Theoretical Framework: To enlighten the main concepts of this study and underpin their theoretical foundations, the business intelligence tools and applications were presented. Their characteristics, dimensions, virtues, as well as the reasons behind their implementation were also detailed. Therefore, the role of business intelligence in improving tax performance was justified, providing a solid basis for understanding the context of our investigation carried out in the taxing authority of the Iraqi capital. Method: To conduct our investigation, a questionnaire was administrated to the target respondents, i.e. 97 employees of the General Tax Authority, located in Baghdad. Following the data collection process, descriptive, then regression analyses were undertaken. Results and Discussion: The obtained findings support that business intelligence exerts a positive influence on tax performance of the general tax authority. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into the awareness of the importance of business intelligence and software applications at the workplace. Departments’ directors of the general taxing authority are invited to cooperate with the corresponding authority whose work could be better performed electronically. Decisions regarding citizens could also be taken more wisely. Originality/Value: The relevance of the present research is essentially evidenced by its main practical implications regarding the improvement of tax performance of taxing authorities of developing countries, as well as the betterment of tax services dedicated to citizens.

Balancing data-driven insights and human judgment in supply chain management: The role of business intelligence, big data analytics, and artificial intelligence

Balancing data-driven insights and human judgment in supply chain management: The role of business intelligence, big data analytics, and artificial intelligence

Developing a goal-driven data integration framework for effective data analytics

Data integration plays a crucial role in business intelligence, aiding decision-makers by consolidating data from heterogeneous sources to provide deep insights into business operations and performance. In the big data era, automated data integration solutions need to process high volumes of disparate data robustly and seamlessly for various analytical needs or operational actions. Existing data integration solutions exhibit limited capabilities for capturing and modeling users' needs to execute on-demand data integration. This study, underpinned by affordance theory and the goal definition principles from the Goal-Question-Metric approach, designs and instantiates a goal-driven data integration framework for data analytics. The proposed innovative design automates data integration for non-technical data users. Specifically, it demonstrates how to elicit and ontologize users' data-analytic goals and addresses semantic heterogeneity, thereby recognizing goal-relevant datasets. In a structured evaluation using the context of counter-terrorism analytics, our design artifact shows promising performance in capturing diverse and dynamic user goals for data analytics and in generating integrated data tailored to these goals. Our research establishes a theoretical framework to guide future scholars and practitioners in building smart, goal-driven data integration.

A Model for Enhancing Unstructured Big Data Warehouse Execution Time

Traditional data warehouses (DWs) have played a key role in business intelligence and decision support systems. However, the rapid growth of the data generated by the current applications requires new data warehousing systems. In big data, it is important to adapt the existing warehouse systems to overcome new issues and limitations. The main drawbacks of traditional Extract–Transform–Load (ETL) are that a huge amount of data cannot be processed over ETL and that the execution time is very high when the data are unstructured. This paper focuses on a new model consisting of four layers: Extract–Clean–Load–Transform (ECLT), designed for processing unstructured big data, with specific emphasis on text. The model aims to reduce execution time through experimental procedures. ECLT is applied and tested using Spark, which is a framework employed in Python. Finally, this paper compares the execution time of ECLT with different models by applying two datasets. Experimental results showed that for a data size of 1 TB, the execution time of ECLT is 41.8 s. When the data size increases to 1 million articles, the execution time is 119.6 s. These findings demonstrate that ECLT outperforms ETL, ELT, DELT, ELTL, and ELTA in terms of execution time.

Moderating the Synergies between Business Intelligence and Strategic Foresight: Navigating Uncertainty for Future Success through Knowledge Management

The role of business intelligence in driving strategic planning in organizations have received considerable attention from many scholars. Nonetheless, there remains a promising area for further research, especially when considering moderating variables on effects such as knowledge management, which has contributed to businesses’ appreciation of the importance of business intelligence. To this end, in this study, the researchers constructed a conceptual model based on existing literature by incorporating relevant research variables. A questionnaire survey was conducted among a random sample of 307 employees selected from three telecom companies in Jordan. The researchers then utilized structural equation modeling with AMOS 21.0 to validate and test the model. The findings of the study revealed that business intelligence has a significant positive influence on strategic foresight. Furthermore, the analysis indicated that knowledge management mediates the relationship between business intelligence and strategic foresight. The implications and recommendations of academic research are also discussed.

Assessing the effect of business intelligence on supply chain agility. A perspective from the Jordanian manufacturing sector

This study aimed to examine the effect of integrating Business Intelligence (BI) into the supply chain on supply chain agility, within the Jordanian manufacturing sector. Based on the resource-based view of the firm, this study developed and examined a research model, to achieve its goal. The impact of three dimensions of BI including managerial, technical, and cultural competencies was examined. Using an electronic questionnaire, data was gathered from 462 administrative personnel and employees. Structural equation modeling techniques were employed to analyze the data. Results revealed that the three dimensions of BI have statistically significant positive direct effects on supply chain agility. In addition to that, the results revealed that BI cultural competence has statistically significant positive direct effects on BI technical and managerial competencies. This study contributes to the literature on the role of BI in promoting supply chain agility, from the perspective of a developing country. The findings of this study are expected to help organizations' administrations in making better decisions regarding employing BI to achieve an agile supply chain.

Role of Business Intelligence and Knowledge Management in Solving Business Problems

The term “Business intelligence” is described as a plan or a strategy where the operations like reporting, data analysis, data mining, event processing are performed to improve the production and growth of a business enterprise or a business entity. And on the other hand, the “Knowledge management” is explained as well-organized management of resources and information within a commercial organization it can be a business too. Almost all business will have limitations and challenges which can be also known as the business problems. One of the main business problem is demand, the business plans must work according to the demand of the consumers. Analyzing the demand would provide the solutions for queries like what is the business trend? What is the need of the users? What should be the improvement make in the production? Where is the current position of the enterprise? And who all will be the competitors? For the predictive analysis a dataset of bitcoin is taken. The major aim of the study is to implement the strategies to overcome the business problems mainly the demand prediction. And the objective is to find out the relevant issues and the remedies by using knowledge management and business intelligence to the common business problems. The dataset has columns called lowest price, highest price, open price, close price, trading volume and market capital. The research methodology used is predictive analysis using PCA and K-means clustering algorithm. By this dataset predictive plots are developed as achieved results for easy analysis by using research methodology. PCA and K-means are the algorithm used for accurate prediction. The importance of study is to predict the future sale, as it is very essential for a business enterprise to find future demand so that the organization can improve production.

The Role of Business Intelligence in Promoting Decision-Making in Humanitarian Organizations Operating in Turkey, Orange Organization as a Sample

This study aimed to identify the relationship between business intelligence systems and the decision-making process of humanitarian organizations operating in Turkey. In this study, the non-experimental quantitative descriptive research method was preferred, which is one of the types of scientific research suitable for the aim of the current research. The number of community members surveyed as a whole was (105) and represent the number of employees in the orange organization for this, data were collected and analyzed, and hypotheses were tested using SPSS. Several tests were conducted suitable for research, including noting the correlations between the variables, in addition to looking at the averages and proving the hypotheses. After conducting the process of analyzing the study data and its hypotheses, the study reached several results, the most prominent of which are first: There is a strong correlation between business intelligence systems and the decision-making process in humanitarian organizations operating in Turkey at the level of significance α ≤ 0.05. Second: There is a positive correlation between the quality of information and the quality of systems used in business intelligence systems and both user satisfaction and perceived value and its use in humanitarian organizations operating in Turkey at the level of significance α ≤ 0.05. Third: There is a positive correlation between the satisfaction of users of business intelligence systems with regard to decision-making in humanitarian organizations operating in Turkey at the specified significance level α ≤ 0.05.

Role of Business Intelligence in Developing Countries

Developed countries are constantly evolving their information systems by assessing the use of information and incorporating data analysis for decision making and forecasting. Like, developing countries are incorporate information technology standards and business intelligence technologies into their analysis of data to help them make some informed decisions. However, developing countries still have a long way to go to fully realize the potential of business intelligence. Although the spread of information technology in developing countries is rapid, the did not come with a large development benefit of it. Therefore, this study aims to identify factors influencing the adoption of business intelligence in developing countries, such technologies to raise overall socio-economic standards in developing countries. The purpose of this study is how well business intelligence have been adopted, how useful they have been, and the potential facing developing countries in adopting business intelligence and other information. Keywords: Business Intelligence, developing countries.

The role of business intelligence and knowledge management systems in marketing information services in academic libraries under the Coved 19 pandemic: an analytical study

The role of business intelligence and knowledge management systems in marketing information services in academic libraries under the Coved 19 pandemic: an analytical study

Developing railway supplier selection excellence using business intelligence knowledge management framework

AbstractIn a broad scope, the term Information System (IS) is a scientific field of research study that approaches the scope of managerial, strategic, and operational activities complex in the storing, processing, distributing, gathering, and utilizing of knowledge and its associated technologies in organizations and industry. The model of railway supplier selection using BI-KM framework is situated on a horizontal structure of the organization and its technology transformation to execute the organization goal, with technology as enabler and driver (technology adoption), organization as the principal environment (business process analysis), and Information Management (data modeling). This study is significant in supporting data scenarios by focusing on the heuristic view of an industry approach to problem-solving management issues. Furthermore, the research development was to identify integrated framework adoption that contributes to strategic performance diagnostics dashboard. By understanding the factors of theoretical framework adoption, these conceptual frameworks assure competitive advantage. Besides, this railway supplier selection excellence model analyzed the extent and provides a potential solution to strategic decision-making issues. The study directs to regulate the adoption of the theoretical framework towards conceptual framework by using the role of Business Intelligence (BI) to analyze the quality of data presented as the railway supplier selection criteria from operational management through data analytics. Moreover, this will be united to help the best cycles and instruments in essential execution by the executives of a railway supplier selection dashboard for simulating data as interactive supplier performance.

Role of Business Intelligence in Banking Sector for Achieving Competitive Advantage- An Empirical Analysis

With recent advancements in information technology, organizations’ capability to acquire and analyze data for efficient decision making has increased. Good strategies promote alignment among processes and technology in use, which may result in better firm performance. However, there has been little focus on how firm strategies and business intelligence (BI) systems might play their part in forming organizational information and getting a competitive edge. Therefore, the purpose of conducting this study is to investigate the impact of firm strategy on firm competitive advantage with mediating role of BI adoption and moderating role of BI capabilities. For this, a quantitative research methodology was used, and data was collected from 300 middle-level managers in Pakistan’s telecom sector. Statistical tests such as descriptive statistics, correlation, reliability analysis, one-way ANOVA, confirmatory factor analysis, and mediation analysis through Hayes process were performed using SPSS and AMOS. The findings revealed a positive link between firm strategy and competitive advantage, with business intelligence adoption serving as a mediating factor. Business intelligence capabilities positively moderate the relationship between BI adoption and competitive advantage. Hence, all proposed hypotheses (H1, H2, and H3) were approved. The contribution and Limitation of the study are also discussed.

Visual Storytelling with BI Tools: Enhancing Data Interpretation and Communication

As organizations grapple with increasingly complex datasets, the role of Business Intelligence (BI) tools in data storytelling has never been more critical. Visual storytelling allows decision-makers to extract and communicate insights quickly, efficiently, and in a manner accessible to both technical and non-technical stakeholders. By utilizing visual elements such as charts, graphs, and dashboards, tools like Power BI, Tableau, and Looker transform raw data into actionable insights. This paper delves into the mechanics of visual storytelling, using specific examples and pseudocode to demonstrate how BI tools enhance data interpretation and communication. This paper explores how visual storytelling can improve data interpretation and communication within organizations, highlighting tools like Power BI, Tableau, and Looker, along with best practices for using visuals to convey insights effectively.

The Role of Business Intelligence in Supporting the Entrepreneurial Culture of entrepreneurs in Bechar City

The Role of Business Intelligence in Supporting the Entrepreneurial Culture of entrepreneurs in Bechar City

The role of internal marketing orientation and organisational citizenship behaviour on performance: testing the moderating role of business intelligence

The role of internal marketing orientation and organisational citizenship behaviour on performance: testing the moderating role of business intelligence

The Role of Business Intelligence in Administrative Development at King Abdulaziz University

this study aimed at clarifying the concept of business intelligence and what is meant by administrative development, and to know the role of business intelligence in administrative development at King Abdulaziz University. Also, to explain the relationship between them, the extent of its application in the university, and providing solutions and proposals that contribute to that. The study adopted the descriptive approach and data was collected by reviewing the existing intellectual production in the field of study. Preparing a questionnaire as a tool and distributing it electronically, (46) who entered the study (administrative leaderships at King Abdulaziz University) responded to it. The most important result of this study is the existence of an interrelated relationship between business intelligence and administrative development. The perceptions of the study sample came to the extent of applying business intelligence in administrative development in an average way. Also, there is a great importance for training in business intelligence practices in administrative Development processes. This study recommends supporting and adopting senior management and making more effort to apply business intelligence in accomplishing administrative operations. As well as giving high importance to training on business intelligence and sending informational and awareness messages to leaders at the university. And the need to seek to keep abreast of developments of business intelligence techniques to carry out and update. Further experimental studies reflecting business intelligence applications in local organizations recommend this, to find out the level and constraints of applying business intelligence.

디지털 세계에서 경쟁우위를 지속하기 위한 실시간 기업으로의 디지털 트랜스포메이션: 비즈니스 인텔리전스와 통신시스템의 역할

디지털 세계에서 경쟁우위를 지속하기 위한 실시간 기업으로의 디지털 트랜스포메이션: 비즈니스 인텔리전스와 통신시스템의 역할

The role of business intelligence in a knowledge-based economy: the case of Saudi Arabia

The role of business intelligence in a knowledge-based economy: the case of Saudi Arabia

The Role of Using Big Data in Predicting Customer Behavior: The Intermediary Role of Business Intelligence in Jordanian Telecommunications Companies (A Field Study).

The Role of Using Big Data in Predicting Customer Behavior: The Intermediary Role of Business Intelligence in Jordanian Telecommunications Companies (A Field Study).

The Role of Business Intelligence in Crises Management: A Field Study on the Telecommunication Companies in Jordan

The field of business intelligence and crisis management currently became have become important issues that organization should be concerned about. The aims of the research is to identify the concepts of business intelligence (BI) and crisis management and review the importance of business intelligence in business organizations through the following independent variables (data source - data stores - specialized data - analytical processing- Data and data mining) and its impact on the crisis management stages ( pre-crisis phase, during the crisis phase and post-crisis phase) in the Jordanian telecommunications companies. The study population consisted of employees of the Jordanian telecommunications companies. A simple random sample was selected, to whom (130) questionnaires were distributed and 120 questionnaires were retrieved. The study relied on the descriptive analytical approach (SPSS as statistical analysis). The research concluded that there is a positive significant impact between business intelligence and management crisis in the Jordanian business organizations. This indicates to the interest of these organizations in the tools of business intelligence, especially with regard to the analytical processing of data based on a secure and integrated system in the work environment to manage organization crises.