Use Of Business Intelligence Systems Research Articles

Strategies for success: A theoretical model for implementing business intelligence systems to enhance organizational performance

The use of Business Intelligence Systems (BIS) has seen a significant rise worldwide in recent years, aiming to support organizations in navigating the competitive business environment. Despite this, many organizations struggle to fully benefit from BIS due to challenges in its implementation. A key reason identified for these challenges is the lack of effective measurement strategies. This paper seeks to provide a clear overview of business intelligence and the key factors that influence its successful implementation in organizations. Through a review of existing literature, the study identifies the most critical components necessary for the effective use of a business intelligence system. It proposes a theoretical model for evaluating BIS performance at the organizational level inspired by the Information System Performance Model. This model suggests that system quality, information quality, service quality, relationship quality, and process quality all play a vital role in enhancing perceived usefulness and user satisfaction, thereby leading to organizational benefits. By integrating insights from relevant literature, this paper offers a detailed understanding of how to assess the success of BIS within an organization. The findings highlight the positive impact of business intelligence systems on organizational performance and decision-making processes, aiding organizations in making informed decisions. This research is unique in that it presents a theoretical model for evaluating the success of BIS in organizations based on an extensive review of the literature. Additionally, it extends the application of the Information System Success Model to the domain of BIS for analyzing performance at the management level.

On the Impact of a Business Intelligence System on Analysis Effort

Background: Business intelligence provides decision support to decision-makers in public administrations. So far, researchers have studied the use of business intelligence systems concerning, for example, efficiency gains of the organization. However, based on our literature study, researchers have yet to focus on the impact of business intelligence systems on the efficiency of analytical processes in the public administration context. Objective: This study's objective is to investigate the impact of introducing a business intelligence system in public administration. Method: A case study was conducted to investigate the impact. We studied four departments at Flensburg Municipality in Germany. We used interviews and analyzed documentation to describe the analytical processes and to estimate efficiency gains.Results: The BI system led to efficiency gains across departments. The gains varied from 1.77% to 47%. Losses were observed regarding media changes.Conclusions: The impact on efficiency varies with the attributes of the analytical process (e.g., repetitions in the process). Hence, further investigations are needed to build theories regarding the relationship between efficiency and the use of BI systems in public administrations.

Impact of Business Intelligence Systems on Profitability - Empirical Study

There is a research gap regarding the impact of Business Intelligence (BI) implementation on banks' profitability ratios. In particular, this relates to the financial profitability ratios of banks operating under the conditions of the Polish economy after 2015. The main research problem addressed in this study is whether the implementation of Business Intelligence systems has a positive impact on the profitability indicators of commercial banks. The main hypothesis formulated is that the use of a Business Intelligence management system between 2009 and 2020 improves the profitability of Polish commercial banks. The First Differences Generalized Method of Moments (FDGMM) panel dynamic model estimation method was used to evaluate this impact. The parameters of the models based on financial indicators were calculated for each of the selected indicators, and the analysis used those models for which the lagged BI variable, related to the timing of system implementation, proved statistically significant. Based on the obtained parameters of the models, long-term multipliers were calculated. The study determined the probability of the impact of using the business intelligence system on the selected indicators. The study was conducted on a group of the five largest out of the thirteen commercial banks listed on the Warsaw Stock Exchange in 2020. The assets of the surveyed banks comprise 50% of the assets of commercial banks in Poland. The study identified the impact of BI system use on selected profitability indicators of commercial banks. The generalized results of the study enable us to identify causal relationships between the use of the BI system in commercial banks and profitability, as measured by ROE and ROA. The research implications of this study may suggest to top management that implementing business intelligence systems can benefit the organization.

Demo of QueryBooster: Supporting Middleware-Based SQL Query Rewriting as a Service

Query rewriting is an important technique to optimize SQL performance in databases. With the prevalent use of business intelligence systems and object-relational mapping frameworks, existing rewriting capabilities inside databases are insufficient to optimize machine-generated queries. In this paper, we propose a novel system called "QueryBooster," to support SQL query rewriting as a cloud service. It provides a powerful and easy-to-use Web interface for users to formulate rewriting rules via a language or express rewriting intentions by providing example query pairs. It allows multiple users to share rewriting knowledge and automatically suggests shared rewriting rules for users. It requires no modifications or plugin installations to applications or databases. In this demonstration, we use real-world applications and datasets to show the user experience of QueryBooster to rewrite their application queries and share rewriting knowledge.

Exploring the Role of Business Intelligence Systems in Digital Healthcare Marketing:

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.

EVALUATION OF THE IMPACT OF CREATIVE USE OF BUSINESS INTELLIGENCE SYSTEMS ON THE PERFORMANCE OF THE ELECTRICITY INDUSTRY IN IRAN

Nowadays, the use of creative ideas in companies' business intelligence systems is significant and leads to improving their performance. This study aims to evaluate the impact of the creative use of business intelligence systems on the performance of the Electricity industry in Iran. The data collection tool was a questionnaire, and the data collection was done in 2022. Data analysis was done using the structural equation model of the data. The data shows that creative ideas affect the business intelligence of the electricity industry with a probability of 99%. Also, sales marketing, internal operations management, and procurement affect the performance of the electricity industry with a probability of 99%. The results show that creative ideas for business intelligence systems lead to improved performance in the electricity industry.

Towards an understanding of actual business intelligence technology use: an individual user perspective

PurposeAlthough much is understood about Business Intelligence (BI) technology adoption, less is known about the complementary organisational resources that drive the actual use of BI systems and the impacts of BI systems at an individual employee level. This study aims to develop and test a model of the impact of key complementary organisational resources on employees' actual BI systems’ use behaviours and their decision-making performance.Design/methodology/approachTo test the research model, a cross-sectional survey of 437 North American employees, who described themselves as using a BI system to make decisions, was conducted. The partial least square (PLS), a structural equational modelling (SEM) technique, was employed to analyse the survey data.FindingsThe survey findings attest to the influence of key complementary organisational resources (i.e. data-based culture (DBC), quality of data in source systems and decision-making autonomy) on employees' actual BI use (comprising BI system dependence and BI system infusion) and on their decision-making performance. Specifically, a DBC and the quality of data in source systems are found to significantly enhance BI system dependence and BI system infusion. Decision-making autonomy, DBC, BI system dependence and BI system infusion are significant contributors to achieving decision-making performance.Originality/valueThis study proposes a theoretical model of actual BI systems’ use from an individual user perspective that increases our understanding of both the complexity of BI usage and the complementary organisational resources that drive both actual BI systems’ use and the impacts of BI systems.

Capabilities of business intelligence for improving the efficiency of economic analysis in stressful economic conditions caused by pandemic

From the perspective of economic analysis, the phenomenon of business intelligence (BI), which is the main subject of this research, is described as a version of artificial intelligence oriented towards comprehensive analysis of high data volume and its transformation into applied knowledge on the economic activity of organizations. Emphasis is placed on the feasibility and peculiarity of implementation of business intelligence systems in stressful economic conditions caused by pandemic on the global and national scale. The empirical part of research lies in the development and testing of the intelligent solution in the area of information and analytical support for economic analysis. The acquired conclusions prove that the current situation on the global economic market promotes further development of methodology for implementing information technologies, and business intelligence in particular, in the economic analysis of business activity. In order to meet the specific needs of end-users of business intelligence systems, was developed the tool for calculating the economic efficiency of medical insurance for health improvement of the personnel. It is substantiate that innovative BI- technologies help to integrate and successfully apply the solutions of business analysis at any level of corporate management. The authors outline the leading parameters of the ideal version of business intelligence, as well as justify that the use of business intelligence systems in the area of information support for economic analysis gives a multiplicative effect: - contributes to the improvement of economic analysis, efficiency of implementation and accuracy of data; - ensures the effectiveness of economic analysis for achieving  best result with relatively low cost and maximum utilization time; - provides acceptable relevance of the data that underlie the management decisions, leaving out subjectivism.

The impact of business intelligence systems on profitability and risks of firms

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.

The anchoring effect in business intelligence supported decision-making

ABSTRACTThis article reports on a study that is part of a larger project on how Business intelligence (BI) can effectively support a range of decisions made by different decision-makers through the lens of behavioural economics. This study examines one cognitive bias, the anchoring effect. A laboratory experiment was conducted where participants used a BI system to make a forecast. Two anchors with the same value were presented; a spurious anchor and a plausible anchor. We were interested if the use of a BI system would mitigate the negative consequences of the anchoring effect. Our results show BI system use mitigates the effect of a spurious anchor, but not a plausible anchor. That is, despite the significant expenditure on BI, decision-makers can still be subject to major biases and make less rational decisions. This study indicates that cognitive bias is an important topic for BI supported decision makingresearch and practice.

Determinants of business intelligence system acceptance in an emerging country

In today’s highly competitive and cumulative uncertainty in the business domain, access to organizations’ business intelligence (BI) can mean not only the difference between profit and loss but also the difference between survival and bankruptcy. The use of Business intelligence systems has become an inevitable requirement for profitability, competitiveness and organisational survival. This study objective is to determine factors that influence users’ acceptance of BI systems in the South African energy sector and develop a conceptual model to explain factors that influence users’ acceptance of BI systems. A survey research strategy was used for the study to empirically test a conceptualised model using collected data. The results of the study found that habit, affect and perceived consequences have a significant influence on users’ acceptance of BI systems. Furthermore, the study discovered that habit influences affect in respect of users’ acceptance of BI systems. The study contributed to literature and body of knowledge on factors that influence users’ acceptance of BI systems in organisations.

BI4BI: A continuous evaluation system for Business Intelligence systems

Business Intelligence (BI) allows supporting decision making by providing methods and tools to easily access and manage business information. Indeed, it is crucial to maintain BI systems and make them evolve in order to fit business and users’ needs. For this purpose, applying BI for BI is suggested. It helps to analyze the current BI environment and to make decisions about its use and evolution. Then, the main contribution of this paper consists in developing a novel system called BI4BI which is based on both BI systems’ data and BI users’ feedbacks.As a result, based on a user centered approach, an automated system for BI evaluation is developed helping its continuous evolution. To this end, system-based and user-based solutions provide two complementary data sources, required to effectively gather insights on the use of BI systems and the way they should evolve. A case study in a semiconductor manufacturer company demonstrates the impact of our solution on the evaluation and evolution of BI systems. Hence, thanks to the involvement of the company’s BI users during the solution design, a set of evaluation criteria responding to their objectives for evaluating the BI system are identified and validated. Furthermore, the results of this case study show that our proposed solution is better than existing ones, in terms of level of focus of its BI evaluation criteria, its level of automation, and its continuous processing.

Business Intelligence System Use as Levers of Control and Organizational Capabilities: Effects on Internal and Competitive Benefits

This study investigates the organizational benefits of business intelligence (BI) systems. BI systems are management control systems (MCS) that leverage operational and market data. We draw upon levers of control and capability theory, and distinguish among three aspects of BI systems (intelligence, benchmarking, and integration) and two types of organizational benefits: internal (inward-facing) and competitive (outward-facing). We propose that intelligence use of BI (diagnostic use and an inside-out capability) provides internal benefits, whereas benchmarking use of BI, (interactive use and an outside-in capability) provides competitive benefits. We propose that BI integration with other technologies, a spanning capability, contributes to both internal and competitive benefits. Finally, we investigate the effects of information culture, a clan control, on these aspects of BI. We test our model using structural equation modeling with survey data collected from 175 global organizations, and find our hypotheses to be largely supported. Research and practice implications are discussed.

The Performance Effects of Using Business Intelligence Systems for Exploitation and Exploration Learning

ABSTRACTAccounting researchers are becoming increasingly interested in the performance effects of business intelligence (BI) systems in their role as management control systems. Extant research focuses on the performance effects of adopting and implementing such systems. However, there is less known about how organizations use the information in BI systems for management control once implemented, and whether the use of this information translates into organizational performance. We utilize the theoretical connection between information systems and organizational learning to explain the performance effects of BI system use through organizational learning. Evidence from recent literature indicates the need for organizations to engage in exploitation and exploration learning in pursuit of organizational ambidexterity. Our study draws on agenda setting and framing theories to provide insights that will enable organizations to strategically use the information in two fundamental BI systems to emphasize either or both modes of learning. Subsequently, we examine whether the two modes of learning translate into performance.

Factors influencing business intelligence system use in decision making and organisational performance

This research examined the factors that contributed to use of information from a business intelligence system (BIS) in management decision making and the relationship to organisation and business process performance. Business intelligence (BI) is a timely topic, as organisations continue to invest in systems to leverage big data and gain sustainable competitive advantage. Few studies have examined whether organisational performance benefits result from management use of information from the BIS in decision-making processes. This research surveyed 259 managers with access to a BIS for use in their decision-making processes. A partial least squares structural equation modelling (PLS-SEM) approach was used to analyse the results. The global model indicated that use of information from the BIS in management decision making contributed to organisational performance benefits. Information content quality, information access quality, and analytical decision-making culture contributed to use of information in the global model.

Business intelligence in magazine distribution

This case discusses the use of business intelligence systems in the running and optimisation of magazine distribution by a UK company. The company collects a wide range of data to help it monitor and optimise a supply chain involving subcontractors. The case study raises a number of issues which are discussed. It illustrates the variety of forces which are driving companies to adopt business intelligence systems. It demonstrates how business intelligence systems can help run business processes. It explores the problems and issues with sourcing, collecting and cleaning data. Issues around anonymisation and the concept of a ‘single version of the truth’ are discussed and ethical issues highlighted. It concludes that an understanding of the role of interpretation in data collection, collation and subsequent decision making is critical to business intelligence and calls for more research in this area.

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

The advent of new information technology has radically changed the end-user computing environment over the past decade. To enhance their management decision-making capability, many organizations have made significant investments in business intelligence (BI) systems. The realization of business benefits from BI investments depends on supporting effective use of BI systems and satisfying their end user requirements. Even though a lot of attention has been paid to the decision-making benefits of BI systems in practice, there is still a limited amount of empirical research that explores the nature of end-user satisfaction with BI systems. End-user satisfaction and system usage have been recognized by many researchers as critical determinants of the success of information systems (IS). As an increasing number of companies have adopted BI systems, there is a need to understand their impact on an individual end-user's performance. In recent years, researchers have considered assessing individual performance effects from IS use as a key area of concern. Therefore, this study aims to empirically test a framework identifying the relationships between end-user computing satisfaction (EUCS), system usage, and individual performance. Data gathered from 330 end users of BI systems in the Taiwanese electronics industry were used to test the relationships proposed in the framework using the structural equation modeling approach. The results provide strong support for our model. Our results indicate that higher levels of EUCS can lead to increased BI system usage and improved individual performance, and that higher levels of BI system usage will lead to higher levels of individual performance. In addition, this study's findings, consistent with DeLone and McLean's IS success model, confirm that there exists a significant positive relationship between EUCS and system usage. Theoretical and practical implications of the findings are discussed.

Real time business intelligence in supply chain analytics

PurposeRapid innovation and globalization have generated tremendous opportunities and choices in the marketplace for firms and customers. Competitive pressures have led to sourcing and manufacturing on a global scale resulting in a significant increase in products. The paper tries to identify the need for real time business intelligence (BI) in supply chain analytics.Design/methodology/approachThe paper provides argument and analysis of the advantages and hurdles in BI.FindingsThe paper focuses on the necessity to revisit the traditional BI concept that integrates and consolidates information in an organization in order to support firms that are service oriented and seeking customer loyalty and retention. Enhancing effectiveness and efficiency of supply chain analytics using a BI approach is a critical component in a company's ability to achieve its competitive advantage.Originality/valueThis paper furthers understanding of the issues surrounding the use of BI systems in supply chains.