Adoption Of Business Intelligence Systems Research Articles

Bibliometric analysis of the literature on business Intelligence systems adoption and acceptance, trends and perspectives

In today's economic landscape, marked by a rapid surge in data, information has grown in volume, speed, and volatility. This has led to heightened competitive pressures within the business environment. As a result, organizations must adopt improved techniques and tools for information management. Business Intelligence is one of these tools, seen as a crucial technological advancement for improving the decision-making process, then Business Intelligence Systems (BIS) assist companies and organizations in making well-informed strategic decisions. Despite of the importance of these tools, literature shows that most BI projects do not deliver the expected results and BIS’s full benefits have largely been missed by organizations. In this respect, this work aims to analyze papers published between 2000 and 2022 that have focused on the adoption of BI. It presents bibliometric data, including high-frequency words, disciplinary distribution, lexical fields, approaches, trends, and evolution of research in this area. The study also presents some factors influencing the Business Intelligence Adoption (BIA).

Business intelligence adoption among small apparel retailers in KwaZulu-Natal

Business intelligence (BI) can assist businesses with the analysis of information to make better decisions to improve business performance; however, a lack of research with respect to the adoption of BI tools specifically in the SMME apparel sector has been observed. Developments in information technology (IT) have led to an increase in competitiveness among providers, resulting in a plethora of offerings for customers to choose from. As such, businesses are operating in evolving and complex environments where business intelligence systems (BIS) have become essential. The aim of this study was to establish the factors that influence the adoption of BI by micro-small apparel retailers in KwaZulu-Natal. The study was a cross-sectional survey that sampled 132 apparel business owners who were selected using purposive sampling. A survey questionnaire was used to collect the data. The data was analyzed using the Statistical Package for Social Sciences (SPSS) Version 13.0. This study found that the main inhibitors to the adoption of BI systems among small apparel retailers are cost-related. However, an interesting finding was that although cost had a negative relationship to adoption in the results, most of the respondents still indicated that they were able to make financial plans to adopt BI. The study recommends that small apparel business owners prioritize the adoption of BI as a tool for business operations. The adoption of such tools would have a net positive effect on the operations of such businesses.

Business Intelligence Adoption for Small and Medium Enterprises: Conceptual Framework

All businesses have many issues, especially small and medium enterprises trying to survive with traditional technology. Therefore, enterprises need to adopt business intelligence by using the management of information technology systems to overcome the issues. This study proposes a conceptual framework that identifies the potential factors that influence the adoption of business intelligence systems in the SME industry in Libya. Therefore, this study was established based on two main theories: the technology acceptance model (TAM) and the unified theory of adopting and using technology (UTAUT). In line with the previous studies that investigated this type of influence, this study recommended a conceptual framework containing several factors: change management, knowledge sharing, information quality, IT project management, the perceived usefulness of a BIS, and the perceived ease of adoption of a BIS. This study did not consider the environmental factors’ effect on adopting a BIS (business intelligence system); this is due to the different characteristics of each small and medium enterprise in terms of the sector or industry type.

Critical success factors for business intelligence and bank performance

This research attempts to investigate the technological, organizational, and environmental aspects that impact the banking industry's use of business intelligence (BI). In addition, the present research aims to quantify the effect of business intelligence adoption on bank performance to contribute to the current understanding of business intelligence adoption. Upon the completion of the sample verification procedure, 232 samples are collected. Throughout the research investigation, the SEM software is used to process all the acquired data. The study's findings indicate that TOE had a direct and beneficial effect on the adoption of BI systems by banks. Based on the results of the study, the researchers believe that decision-maker and managers would define all activities, responsibilities, and work processes using business intelligence platforms in order to increase their organization's versatility and performance.

Justifying Business Intelligence Systems Adoption: A Literature Review on Healthcare Supply Chain Perspective

Business Intelligence (BI) systems have played an essential position in facilitating information sharing, strategic cost-cutting, and improvement in business process management through data-driven decision-making analytics. The technological enablers of Industry 4.0 have empowered the clinician to attain accurate information in formulating predictive and data-driven diagnoses based on artificial intelligence-enabled medical devices resulting in an efficient and quality clinical pathway for patients. However, there is a noticeable distinction between the hospital's technological aptitude between clinician and non-clinician. The current technological capability of the hospital information system is to digitize daily business processes that could not offer intelligence reports for predicting, forecasting, and data-driven decision-making support. The compilation of past works of literature is expected to justify the need for the healthcare supply chain to adopt BI solutions that produce near real-time data in making efficient inventory management and procurement to support the clinician in delivering efficient and quality clinical pathways for patients by bringing the supplies at the right moment. Hence, a study of BI solutions in healthcare supply chain operation is achieved through a narrative overview of existing literature from papers published online. The results show that appropriate technological tools, resource competencies, and supplier management platform as the essential dimensions to support the business intelligence adoption effort. The study, therefore, not only identified the critical dimensions in facilitating BI adoption but also offer practical awareness to the healthcare policymakers to better understand the strategic need for BI systems in managing the entire hospital operations to gain a competitive advantage.

The adoption of business intelligence systems in small and medium enterprises in the healthcare sector: A systematic literature review

In this era of industrial revolution (IR 4.0), coupled with the emergence of the deadly global pandemic of COVID-19, healthcare organizations are compelled to embrace new technologies for their routine decision-making. The Business Intelligence System (BIS) is one of the emphasized innovations, and due to its potential to provide more intellectual information for decision-making processes, has attracted the interest of industry analysts and policymakers. Literature suggests that the BIS is integrated by organizations in different sectors, but most BIS initiatives struggle to produce the anticipated outcomes. Moreover, the adoption of BIS in SMEs generally and healthcare specifically is rather insignificant. This is due to numerous factors. It is therefore necessary to discover and analyze the essential determinants affecting the adoption of BIS in healthcare SMEs. Therefore, this study tries to tackle this gap by exploring the relevant factors for BIS adoption using a systematic literature review (SLR) and an expert-ranking survey of 63 studies that were published in Scopus and WoS databases from 2011 to 2020. A total of 22 determinants are identified and sent to 15 experts. The data that were gathered from these experts were analyzed using SPSS. The results of the analysis indicated 15 determinants were significant, and one determinant was added by an expert. Consequently, a theoretical structure has been developed based on technology, organization, environment, and CEOs determinants and theories. The results of the current study will deepen the current BIS literature and advance the understanding of the significant elements of BIS adoption decision.

Statistical Assessment of Business Intelligence System Adoption Model for Sustainable Textile and Apparel Industry

The textile and apparel industry is one of the biggest competitive industries in the world. Nowadays, industry 4.0 concepts put pressures on textile and apparel companies to integrate advanced technologies. Consequently, Business Intelligence (BI) systems are diffusing rapidly to process large data sets to harness the true value of smart technologies. Regardless of its potentials, most textile and apparel companies are lagging and hesitating to adopt this credible innovation in the presence of a high failure rate (70%-80%) especially in developing countries. To achieve the successful adoption of BI systems, statistical assessment is required to better understand this complex phenomenon. Therefore, a BI system model based on Technology-Organization-Environment (TOE) is developed to evaluate the role of potential determinants pertaining to the users, technology, organization, and environment. Data were collected using a survey with self-administered questionnaires from decision-makers with authoritative designations in the textile and apparel industry, academia, and software companies. Influential relationships among critical determinants were assessed and validated by using Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach. The results of this study would contribute to the success of costly BI system projects and will motivate the industry experts to potentially assign investments for the BI projects in the developing countries to sustain in the competitive markets.

Business intelligence systems and operational capability: an empirical analysis of high-tech sectors

PurposeIn this research, we empirically examine the impact of Business Intelligence (BI) systems on operational capability in high-tech sectors. We also seek to understand the contextual factors that facilitate the adoption of BI systems.Design/methodology/approachWe adopt Propensity Score Matching (PSM) and event study methodology, and analyze the financial data for a sample of 144 US firms which adopted BI systems from 2005–2014, and compare them to control firms without BI systems.FindingsWe find that the implementation of BI systems leads to higher operational capability, particularly for large high-tech firms with high technology intensity. We further show that technology intensity and firm size are important contextual factors for firms to reap the benefits of BI systems.Practical implicationsWe demonstrate how benefits from the adoption of BI systems are likely to be strengthened. The benefits of BI systems depend on firms' technology intensity and firm size of high-tech firms. Accessing relevant and timely reports for decision-making is particularly important in the highly dynamic, volatile and competitive high-tech sectors.Originality/valueWe contribute to the literature by providing empirical evidence that the adoption of BI systems can improve firms' operational capability and show that technology intensity and firm size are important contextual factors for firms to reap the benefits of BI systems. We advance the understanding regarding the contextual factors in which firms are more likely to gain additional benefits from their adoptions of BI systems.

Examining the Moderating Effects of Time-Since-Adoption on the Nexus Between Business Intelligence Systems and Organisational Performance

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.

Justifying business intelligence systems adoption in SMEs

PurposeThe purpose of this paper is to provide a better understanding of how post-adoption use of business intelligence system (BIS) affects firm performance. It develops and empirically tests a conceptual model for assessing the impact of BIS routine and innovative usage on firm performance the context of small and medium enterprises (SMEs).Design/methodology/approachDrawing on the data collected from 181 SMEs we analyzed how BIS usage influences firm performance using the PLS-SEM method.FindingsThe paper provides empirical insights about how BIS routine and innovative usage affect firm performance.Practical implicationsThe results provide instrumental insights for managers and solution providers to help them understand the influence of various determinants to more effectively conclude the post-adoption process in SMEs.Originality/valueThis study represents important progress in the authors’ theoretical understanding of the role of BIS routine and innovative usage across different BIS partial impacts on firm performance dimensions.

Investigating the Factors Affecting Business Intelligence Systems Adoption

This study explores the factors influencing the adoption of Business Intelligence Systems (BIS) in Higher Educational Institutions (HEIs), and also evaluate the extent of adoption in the universities. A research framework was developed based on the Technology-Organization-Environment (TOE) framework and the Diffusion of Innovations (DOI) theory, comprising of ten factors which were hypothesized and tested for the adoption of BIS in HEIs. Data was collected through a paper survey questionnaire from a sample of 120 managers and academicians in twelve private universities in Selangor State, Malaysia which were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings revealed that Absorptive Capacity, Competitive Pressure, Complexity, IT Infrastructure, Presence of Champion, Top Management Support, and Vendor Selection, are the factors influencing BIS adoption in the universities. The results also indicate that most private universities in Malaysia are currently involved in level 2 of BIS adoption. Other implications are also discussed.

Business intelligence systems and bank performance in Ghana: The balanced scorecard approach

Business intelligence (BI) systems has been widely publicised as providing immense benefits to organisations that have implemented it. Yet, very few studies have empirically evaluated these assertions theoretically. The main aim of this study is to empirically evaluate the impacts of adopting BI systems on organisational performance of banks. A conceptual model was developed using the balanced scorecard. Data were collected through hand-administered survey questionnaires from the universal banks in Ghana where 130 samples from executives were analysed through partial least squares structural equation modelling (PLS-SEM). The results indicate that BI Systems indeed have a positive significant effect on the learning and growth, internal process and customer performances of the banks. However, the findings proved that the adoption of BI systems does not directly lead to the financial performance of the banks, but rather through the indirect effects of learning and growth, internal process and customer performances thus confirming the core premise of the balanced scorecard. A major practical implication from the study is that vendors can capitalise on the findings to promote their BI products.

Using the balanced scorecard in assessing the impact of BI system usage on organizational performance

There is currently a trend towards the integration of business intelligence (BI) systems with existing information systems in order to improve decision-making capabilities in organizations. Even though much attention has been paid to the factors influencing the adoption of BI systems, in practice there is still limited research investigating the business value of BI systems in a post-adoption environment. The motivation for this study is to examine the impact of BI system usage on organizational performance. This study develops a multidimensional measurement for assessing organizational performance, based on the balanced scorecard (BSC) approach developed by Kaplan and Norton. Data for the study were collected from 139 companies in the semiconductor industry in Taiwan and the relationships proposed in the framework were tested using Partial Least Squares method. The results indicate that higher levels of BI system usage will lead to improved financial performance indirectly through enhanced internal process, learning and growth and customer performance (non-financial performance). Moreover, higher levels of BI system usage can also lead to improved internal process, customer, and learning and growth performance in organizations. The results also show that internal process and customer performance have positive significant impact on financial performance. While learning and growth does not directly lead to the improvement of financial performance, it indirectly influences financial performance through the mediating effect of internal process performance. The findings of this study provide initial evidence that the adoption of BI systems leads to increased financial performance. The results indicate that these four BSC performance measures for BI system usage are interrelated, supporting the core premise of the BSC.

An integrated model for determining business intelligence systems adoption and post-adoption benefits in banking sector

Business Intelligence (BI) Systems have been theorized as providing immerse benefits to organizations that adopt them. These benefits include: improved customer satisfaction improved decision-making process, provision of faster and more accurate reporting, increased revenues and increased competitive advantage. However, there are limited studies on the factors affecting adoption and actual benefits accruing to organizations adopting the system. The main aim of this study is to develop an integrated model for determining BI System's adoption and post-adoption benefits in banking industry. The proposed model is an integration of the Diffusion of Innovations Theory (DOI), Technology-Organization-Environment (TOE) Framework, the Institutional Theory (INT), and Kaplan & Norton's Balance Scorecard (BSC). This model is different from other studies in the context of organizational adoption of BI Systems as it integrates the determinants, and evaluation of the benefits of the technology in one study. There is also a moderator Time since adoption which is used to moderate the impact of the extent of adoption to organizational performance.

Technology Acceptance Model for Business Intelligence Systems: Preliminary Research

Business intelligence systems refer to the set of software platforms that support organizations in retrieving valuable information and knowledge, with the purpose to increase efficiency of decision making. Goal of the paper is to discuss a framework for investigating the adoption of business intelligence systems in companies, from the technology acceptance model perspective. We propose a research framework based on the technology acceptance model that is expanded using the concepts of technology driven strategy, information quality and project management in companies. Based on the framework, we propose a model with research propositions and discuss scientific contributions.

Distinguishing the adoption of business intelligence systems from their implementation: the role of managers’ personality profiles

For decades, the marketing guidelines of enterprise software providers have focused on those managers who are likely to be more innovative in adopting new information systems. The current study argues that this approach demands improvements for two reasons: (1) this tactic may be biased, since past studies have only examined the single trait of innovativeness and its impact on an individual adoption intention and (2) the organisational implementation intention might be more important than the individual adoption intention, but the former has been largely ignored in the existing literature. Based on the case of business intelligence (BI) systems and data from 62 senior managers, this study is a pioneer in that it empirically reveals that managers’ individual adoption intention is distinct from their organisational implementation intention. Further, while managers’ innovativeness may be a significant determinant of their individual adoption intention towards BI systems, the issue of whether managers actually implement BI systems in their organisations is dominated by their involvement characteristics. Fruitful suggestions are proposed for practitioners and scholars.

Cost Effective Cloud based Business Intelligence Model for Small Scale Organizations

Business Intelligence (BI) is the ability for an organization to collect, maintain, and organize data and information to provide historical, current and predictive views of operations. Cloud Computing concepts promise new options for an internet based resourcing of hardware and software. Cloud BI Portal will provide a utility model of computing with lower entry and maintenance cost and multiple delivery models. It will result in better adoption of BI systems mainly in case of small scale organizations where cost factor is a major concern. The target market for Cloud-BI software is currently small scale companies or organizations with few IT resources, limited budget to spend on servers and software, and minimal to no BI expertise .BI Cloud portal can be accessed from anywhere through internet, thus providing BI services to the organization more efficiently. This contribution provides a solution to the BI related problems being faced by small scale organizations like an institute, by designing a model for the BI Cloud Portal which will provide all BI facilities within the economic boundaries.

Investigating factors influencing the adoption of business intelligence systems: an empirical examination of two competing models

Even though much attention has been paid to decision-making benefits of Business Intelligence (BI) systems adoption in practice, there is still a lack of empirical research to investigate factors that influence the adoption of BI systems. Therefore, it is important to understand why users of a BI system choose to accept and use the system. This study compares two competing theoretical models, namely, the Technology Acceptance Model (TAM) and the Decomposed TPB (DTPB) to examine which model can best explain user intentions to use BI systems. Survey data collected from 339 respondents in Taiwan’s electronics industry were examined using structural equation modelling. Our findings indicate that the DTPB model was the most parsimonious and provided better explanatory power than the TAM model. Additionally, the DTPB model helps improve understanding of subjective norms and perceived behavioural control as the determinants of behavioural intention. Several implications and limitations of this study are discussed.

Business Intelligence Systems and Fraud Opportunity

This paper explores how uncertainty reduction due to increased forecasting accuracy, which is one of main benefits associated with the adoption of Business Intelligence systems, will affect the beh...

Adoption of business intelligence systems in Indian fashion retail

Using a classical framework in innovation adoption, this study focussed on BI systems adoption in two Indian retail organisations belonging to two different segments. One case site belonged to a small scale fashion retail which was owned by a single individual with two outlets. The owner made most major decisions usually based on intuition. The use of software was usually limited to spreadsheets. The other type involved a retailer who had numerous outlets all over India. With a professional management and major investments in centralised information technology infrastructure and applications, business decisions were sometimes supported by business intelligence software developed solely for the purpose of assessing sales and managing stocks scientifically. However BI systems were not yet strategically deployed as an engine for competition.