Self-service business intelligence systems in production domains: Introducing data democratization and mass customizable mashups

Arabic Abstract: هدفت الدراسة إلى التعرف على واقع استخدام أنظمة ذكاء الأعمال وأثرها على التوجهات الريادية لبنك فلسطين-المحافظات الجنوبية، واعتمدت الدراسة على المنهج الوصفي التحليلي، وتم جمع البيانات الأولية للدراسة من خلال تطوير استبانة مكونة من ستة مجالات رئيسية تضمنت 39 فقرة، وتشكل مجتمع الدراسة من العاملين في الوظائف الإدارية المتقدمة في بنك فلسطين (مدير إدارة، مدير دائرة، مدير فرع) والبالغ عددهم 55 موظفا، واعتمد الباحثان على أسلوب الحصر الشامل، حيث تم توزيع (55) استبانة استرد منها (46) بنسبة (83%)، وتم تحليل الاستبانة واختبار فرضيات الدراسة بواسطة برنامج الحزم الإحصائية (SPSS)، وقد اظهرت النتائج أن واقع استخدام أنظمة ذكاء الأعمال بأبعادها (جمع وتحليل البيانات، إدارة أداء الأعمال، دعم الموقف التنافسي) قد حصل على تقدير مرتفع بمتوسط حسابي (3.85)، ووزن نسبي (77.0%). وقد اظهرت النتائج مستوى تحقق التوجهات الريادية بأبعادها مجتمعة (الاستباقية، المغامرة التنافسية، المخاطرة) قد حصل على تقدير مرتفع وبمتوسط حسابي (3.98) ووزن نسبي(79.6%). كما بينت النتائج وجود تأثير ذو دلالة إحصائية عند مستوى (α ≤ 0.05) لواقع استخدام أنظمة ذكاء الأعمال في مستوى تحقق التوجهات الريادية، حيث بلغت قيمة معامل التفسيرR2 (44.4%). وتوصي الدارسة الإدارة العامة للبنك بتطوير أنظمة ذكاء الأعمال بحيث تساهم بشكل أكبر في رصد قدرات وإمكانيات المنافسين واستراتيجياتهم التنافسية، وطرح خدمات مصرفية مبتكرة، ومزيد من خفض أسعار الخدمات وتخصيص الأموال الكافية للبحث والتطوير. English Abstract: The study aimed at identifying the reality of using business intelligence (BI) systems and its impact on entrepreneurial orientations of the bank of Palestine in southern governorates. To achieve the objectives of the study, the descriptive analytical approach was used , The Primary data collection achieved by developing a questionnaire consisting of six main areas, which included (39) paragraphs, The study population consisted of (55) employees working in senior management positions in the bank of Palestine includes director of administration, Director, and bank’s Branch Manager. The researchers adopted the complete census, Where (55) questionnaires were distributed, of which (46) were retrieved at a rate of (83%). The questionnaire was analyzed and the study hypotheses tested by the statistical package program (SPSS). Findings of the study showed that the reality of using business intelligence (BI) systems with its dimensions of (data collection and analysis, business performance management, and competitive position support) scored a high level, where its mean reached (3.85) with a relative weight of (77.0%). Also showed that the level of realizing the entrepreneurial orientations with its combined dimensions (proactive, competitive adventure, risk) scored a high level, where its mean reached (3.98) with a relative weight of (79.6%). The study also showed that there was a statistically significant effect at the level of (α ≤ 0.05) for the reality of using the business intelligence (BI) systems in the level of achieving entrepreneurial orientations, where the determination coefficient R2 scored (44.4%). The study recommends that the general administration of the bank should develop business intelligence (BI) systems to contribute more in monitoring competitors’ abilities, capacities and competitive strategies, furthermore, to offer innovation-baking service, and to reduce service prices and allocating sufficient funds for research and development.

Purpose – The purpose of this study was to identify the influence of organizational strategy, structure, process and culture on organizational effectiveness and the possible mediating role of business intelligence (BI) systems among them. Design/methodology/approach – Sample data for this study were collected from 225 organizational units in Bangladesh and analyzed using the partial least squares method, a statistical analysis technique based on the structural equation modeling. Findings – The results revealed that organizational factors, such as organizational strategy, structure, process, and culture positively affect both BI systems’ effectiveness and organizational effectiveness. Furthermore, BI systems’ effectiveness partially mediates the impact of organizational strategy, structure, process and culture on organizational effectiveness. Originality/value – BI systems are context-specific and can influence organizational effectiveness. Dearth in research on the influence of organizational factors to B...

This study explores the potential of business intelligence (BI) systems in facilitating digital healthcare marketing. The healthcare industry has undergone a digital transformation in recent years, with increasing use of digital channels for marketing and customer engagement. BI systems have emerged as a promising technology that can enable healthcare organizations to gain valuable insights into customer behavior, preferences, and trends. Despite the potential benefits of BI systems in healthcare marketing, there is a notable research gap in understanding the role and impact of these systems. This study aims to fill this gap by conducting a qualitative investigation into the experiences and perceptions of marketing professionals in the healthcare sector regarding the use of BI systems for marketing. The study employs a qualitative research design and collects data through in-depth interviews with marketing professionals in the healthcare industry. The analysis of the data reveals that BI systems can provide valuable insights for healthcare marketing, including customer segmentation, personalized marketing, and performance monitoring. However, the study also highlights challenges associated with the implementation and use of BI systems, including data privacy concerns and the need for specialized technical expertise. The findings of this study contribute to the existing literature on BI systems and digital healthcare marketing. The study suggests that BI systems can enable healthcare organizations to make informed decisions about marketing strategies and customer engagement. Furthermore, the study highlights the importance of careful planning and implementation of BI systems to overcome potential challenges and ensure successful adoption in the healthcare sector.

In today's data-driven business landscape, robust metadata and data documentation practices are essential for enterprises aiming to maximize their data assets. When integrated with Business Intelligence (BI) systems, this architecture empowers data democratization, allowing widespread utilization by stakeholders across the organization. This research explores the critical role of metadata in shaping Business Intelligence (BI) systems and organizational effectiveness within today's data-driven business landscape. Through a systematic literature review, a preliminary study, a quantitative survey with 318 responses, and a focus group discussion, the study identifies key metadata components influencing BI systems effectiveness and organizational outcomes. Findings indicate a direct and positive impact of BI systems effectiveness on organizational effectiveness. Certain metadata components exhibit direct positive effects on both BI systems and organizational effectiveness. The research underscores the importance of strategic metadata implementation for enterprises seeking to optimize data-driven decision-making processes. Overall, the study provides practical implications for organizations and contributes valuable insights to the understanding of metadata's role in enhancing enterprise effectiveness. Doi: 10.28991/HIJ-2025-06-01-02 Full Text: PDF

Business intelligence and corresponding intelligent components and tools have been one of those instruments that receive significant attention from health community. In order to raise more awareness on the potentials of business intelligence and intelligent systems, this paper aims to provide an overview of business intelligence in healthcare context by specifically focusing on the applications of intelligent systems. This study reviewed the current applications into three main categories and presented some important findings of that research in a systematic manner. The literature is wide with respect to the applications of business intelligence covering the issues from health management and policy related topics to more operational and tactical ones such as disease treatment, diagnostics, and hospital management. The discussions made in this article can also facilitate the researchers in that area to generate a research agenda for future work in applied health science, particularly within the context of health management and policy and health analytics.

Business intelligence and corresponding intelligent components and tools have been one of those instruments that receive significant attention from health community. In order to raise more awareness on the potentials of business intelligence and intelligent systems, this paper aims to provide an overview of business intelligence in healthcare context by specifically focusing on the applications of intelligent systems. This study reviewed the current applications into three main categories and presented some important findings of that research in a systematic manner. The literature is wide with respect to the applications of business intelligence covering the issues from health management and policy related topics to more operational and tactical ones such as disease treatment, diagnostics, and hospital management. The discussions made in this article can also facilitate the researchers in that area to generate a research agenda for future work in applied health science, particularly within the context of health management and policy and health analytics.

Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems: An empirical study of Taiwan's electronics industry

Business Intelligence (BI) Systems are today considered as a major strategic tool of many well-established companies like Lufthansa, TDC Telecom and AT&T. Of course, the knowledge derived from the experience of those companies could be helpful guide in building efficient BI Systems. Thus, this study highlights the main points arisen from the worldwide practice of building successful BI Systems. The managers usually expect from BI Systems the acceleration of their decision-making process while keeping the quality of each decision, the enhancement of their product development cycle, the maximization of the profit from existing product lines and the discovery of new opportunities, the establishment of better marketing with robust CRM. However, more than 50% of BI projects fail to meet these requirements. So this study investigates the critical mistakes commonly made by BI System developers and suggests profound solutions from the best BI practices.

Building scalable Business Intelligence (BI) systems in the cloud has become a crucial strategy for modern enterprises aiming to harness the power of data analytics for informed decision-making. Cloud-based BI systems offer unprecedented scalability, flexibility, and cost-effectiveness compared to traditional on-premises solutions. This paper delves into the technical approach to designing and implementing scalable BI systems in the cloud. It covers essential aspects such as cloud architecture, data integration, security considerations, and real-time analytics. By leveraging services from leading cloud providers like AWS, Azure, and Google Cloud Platform, organizations can address the challenges of growing data volumes and ensure seamless scalability. The paper also examines best practices for data pipeline optimization, storage management, and the integration of advanced technologies like machine learning and artificial intelligence. Furthermore, the discussion highlights how a well-architected BI system can align with organizational goals, driving efficiency and innovation. This technical guide aims to provide IT professionals and business stakeholders with actionable insights into adopting and optimizing BI systems in the cloud.

The improvements and capabilities of Business Intelligence (BI) systems are making them highly required by organizations in many of the fields. Day by day, the demand is increasing on these systems. Figures show that billions of US dollars are spent annually on BI systems. However, half of these BI projects are ending with unrealized benefit, according to some studies. As a participation to reduce this failure rate, the authors have developed a conceptual model, based on the existing studies in the field, which may help organizations to assess their readiness toward BI systems. The conceptual model is tested empirically on the Context of Malaysian Organizations(CMOs) as they are emerging widely to BI systems and they lack for this kind of studies to be done them. The conceptual model is consisting of seven dimensions. Depending on the results of the conducted study, this paper will disclose the results of management dimension, which will help to know the degree of its importance for organizations' to be ready for such systems. A brief introduction on BI systems and the challenges of their implementation will be presented. In Addition, this paper will go through some important studies have been done in the field. The details of the study will be provided as well.

This article investigates the post-adoption impacts of business intelligence (BI) systems on organisational performance of Ghanaian banks through the lens of the balanced scorecard. It also examines if time-since-adoption moderates the hypothesized relationship between BI systems adoption and the banks' organizational performance. A survey data of 130 Ghanaian bank officials was analysed through a partial least square structural equation modelling (PLS-SEM) approach to examine the relationship among the study constructs. The results indicated that BI Systems indeed impacted significantly on Ghanaian banks' organisational performance by improving employee learning and growth, enhancing their internal business processes and improving their customer management performances. Nonetheless, BI Systems did not have a direct significant effect on the banks financial performance. Moreover, the findings show that there is no significant difference between early-adopters and late-adopters in terms of BI Systems impacts on the banks' organisational performance. Other implications are also discussed.

Researchers in the field of operations management (OM) have long advocated fact-based decision-making. The use of business intelligence (BI) systems represents a great opportunity for manufacturers to improve profitability and reduce firm risks. However, the actual business value of BI systems has remained highly controversial because integrating BI systems into production and manufacturing operations is difficult. In particular, the informational sources and operational use of BI systems require substantial internal support from employees and institutionalised incorporation of BI into operations. Using a sample of 278 manufacturing firms in the US that had used BI systems from 2005 to 2014, we examine the impact of BI systems on firms’ profitability and risks. We show that firms improve their profitability and reduce risks in profit returns directly after the operational use of BI systems. Firms with superior employee relationships and higher process institutionalisation (i.e. firms that are ISO 9000 certified) benefit more from the operational use of BI systems. We provide a resource orchestration perspective (ROP) of the resource-based view (RBV) of firms for the competitive advantage derived from the operational use of BI systems; and we ascertain the circumstances in which manufacturers are more likely to benefit from BI systems.

Recent advances in information technology (IT), such as the advent of business intelligence (BI) systems, have increased the ability of organisations to collect and analyse data to support decisions. There is little focus to date, however, on how BI systems might play a role in organisational knowledge creation – in organisational knowing. We develop a conceptual framework of organisational knowing based on a synthesis of the literature, and use this as a framework to investigate how BI systems facilitate knowing in a case organisation. We identify two practices triggered by BI systems that distinguish them from prior applications of IT: the ability to initiate problem articulation and dialogue, and that of data selection (e.g. to address information needs of organisational decision makers at different managerial levels). This study provides empirical evidence of the performative outcome of BI systems in relation to organisational knowing through the practices of articulation and data selection. It provides a practice perspective on BI and focuses on the role of BI systems in organisational knowing thereby opening up a new departure for BI research that considers the implications of BI systems in organisations with actual practice in mind.

There is currently a trend for companies to invest in business intelligence (BI) systems to enhance their management decision-making capability. Even though a great deal of attention has been paid to the practical decision-making benefits of BI system adoption, there is still a lack of research to investigate factors that affect users’ intention to continue using BI systems after they had already adopted the systems. Therefore, the aim of the study is to examine post-adoption cognitive beliefs and factors influencing users’ intention to continue using BI systems. This study compares three theoretical models, namely, the Expectation-Confirmation Model of IS Continuance (ECM), the Technology Acceptance Model (TAM), and a synthesized model combining ECM and TAM to examine which model can best explain users’ intentions to continue using BI systems. Survey data collected from 330 respondents in the Taiwanese electronics industry were examined using structural equation modeling. Our findings indicate that the synthesized model was the most parsimonious and had a greater explanatory power than the TAM and ECM models. The results suggest that users’ continuance intention is determined by perceived usefulness and satisfaction. Several implications and limitations of this study are discussed.

The impact of Business Intelligence systems on stock return volatility