Business Intelligence Adoption Research Articles

Factors driving business intelligence adoption: an extended technology-organization-environment framework

Business intelligence (BI) is a vital component for businesses of all scales, offering actionable insights crucial for timely decision-making. This technology has become integral across diverse enterprises. Recognizing the factors influencing BI adoption is imperative, and this article employs the organization, complexity, knowledge, technology, user perception and experience, economic, environmental, and social (OCKTUEES) framework to identify key aspects. Building upon the TOE framework, it pinpoints significant variables, emphasizing the importance of factors like user perception and experience, technology, social, economical, and environmental. Employing structural equation modelling on primary data yields actionable insights to address BI adoption challenges. Analysis reveals the user perception and experience, technology, social, economic, and environmental as the top factors. However, the organization appears vulnerable, necessitating a mitigation strategy for successful BI adoption. The study predicts insignificant variables requiring mitigation, such as high costs, inadequate resources, organizational size, security and privacy concerns, risk of open-source adoption, and perception of analytics impacting jobs. This research aids those navigating the BI implementation journey.

Delivering data analytics: A step‐by‐step guide to driving adoption of business intelligence from planning to launchLondon, UK: Kogan Page2022

Delivering data analytics: A step‐by‐step guide to driving adoption of business intelligence from planning to launchLondon, UK: Kogan Page2022

Driving Business Growth from Research to Innovation in The Deployment of Business Intelligence

This research evaluates a company's development and performance based on its intelligence and BI utilization. A study using quantitative poll data from numerous firms examines the relationship between leveraging business knowledge, promoting innovation, and important performance metrics. The findings demonstrate that BI adoption and receptivity to new ideas improve corporate development. Companies that invest heavily in business intelligence (BI) programmes and foster innovation generally outperform their rivals in sales, earnings, and market share. Creative thinking and business knowledge are crucial to corporate success, according to the findings. These gives workers’ suggestions on how to work faster and more creatively. More research, sector-specific analysis, and continuing studies are needed to determine how innovation culture and BI adoption effect firm performance. Finally, this research adds to what is already known about how BI adoption and innovation culture effect firm performance in today's competitive business environment.

Understanding the Nexus: Business Intelligence and its Impact on Customer Experience Across Diverse Work Sectors

In the 21st-century hyper-competitive business landscape, comprehending and improving customer experience (CX) is highly quintessential for sustainable success across diverse industry sectors. Customers today hold more options in pursuing a luxurious lifestyle compared to their predecessors, yet their expectations continue to be on a constant surge. To meet these rising expectations, today's organisations strongly emphasize incorporating the best industry practices to ensure a high-end customer experience [1]. One such practice that has been included in recent times is integrating business intelligence and analytics. By leveraging advanced analytics tools and techniques, businesses can extract valuable insights from vast datasets, enabling informed decision-making and proactive strategies [2]. Business intelligence and analytics play a vital role in this practice by providing real-time data analysis, predictive modelling, and actionable recommendations, empowering organizations to optimize operations, enhance customer experiences, and stay ahead in today's dynamic marketplace [3]. The following paper aims to explore the vital role Business Intelligence (BI) plays in enhancing customer experience across various sectors. By applying a comprehensive review and analysis methodology, the study will seek to investigate how BI tools, strategies, and analytics influence user experience metrics, organizational performance, and competitive advantage in disparate sectors. Moreover, it further aims to determine the significance of leveraging data-driven insights garnered through business intelligence processes to comprehend customer behaviours, preferences, and sentiments across diverse sectors, ranging from retail and hospitality to finance and healthcare. The paper will bolster the aforementioned analysis by synthesising empirical case analysis, diving into the multifaceted impacts of Business Intelligence and Analytics on Customer Experience. Furthermore, the paper aims to examine the role of BI in optimizing operational efficiencies, streamlining processes, and fostering innovation to meet evolving customer expectations and market demands. Alongside this, it will dive deeper into issues such as data privacy concerns, and underscore the importance of organizational culture, leadership support, and cross-functional collaboration in fostering a BI-driven CX-centric mindset within diverse work environments. Through empirical evidence and industry case studies, the paper will seek to demonstrate how Business Intelligence adoption correlates with improved customer satisfaction scores and profitability metrics across diverse sectors. Towards the end, the paper will present a concluding argument by highlighting key insights, implications, and the imperative of investing in robust data infrastructure, analytics capabilities, and talent development initiatives to unlock the full transformative power of Business Intelligence in driving superior customer experiences. It will eventually underscore the need for continuous evaluation, adaptation, and innovation in Business Intelligence strategies to stay abreast of evolving customer preferences, technological advancements, and competitive dynamics. By illuminating the transformative impact of Business Intelligence on Customer Experience metrics, organizational performance, and competitive advantage, the study aims to provide valuable insights and guidelines for leveraging data-driven strategies to drive customer-centric innovation and sustainable growth in an increasingly dynamic business landscape.

Examining the Drivers and Performance Impact of Business Intelligence Adoption in Healthcare Organizations: Evidence from Jordan

Examining the Drivers and Performance Impact of Business Intelligence Adoption in Healthcare Organizations: Evidence from Jordan

Healthcare Value Chain and the Impact of Analytics & BI

This study aims to investigate how the existing healthcare value chain system has significantly been impacted as a result of the increasing adoption and implementation of analytics and business intelligence (A&BI) capabilities. Given the increasing interest and investment in A&BI, it is important to have a good understanding of what A&BI capabilities healthcare organizations are utilizing to enhance value. Based on extensive search of the literature and a follow-up case study of a large regional hospital, it was found that the existing healthcare value chain (HCVC) framework is outdated and no longer effective. We therefore revised and updated the existing framework to meet the current needs of modern healthcare practices. Moreover, A&BI applications currently being deployed in healthcare organizations were identified and mapped onto the revised framework. The study contributes by illustrating how healthcare organizations currently utilize or should be using A&BI capabilities to enable them close the quality gaps.

The Interplay of Human, Organizational, Environmental, and Technological Factors in Business Intelligence Adoption: a Systematic Literature Review

Purpose: The objective of this research is to identify the most common factors in the literature influencing Business Intelligence Adoption (BIA) and present the main approaches, analysis methods and frameworks with model recently used in the study of BIA. Theoretical framework: Business intelligence (BI) has become a significant subject of study for both practitioners and researchers, due to its capabilities to apply data analytics and produce key information to support business decision-making. The literature indicates that most organizations have not succeeded in fully leveraging the benefits of BI, Furthermore, there is a limited availability of studies that investigate the human aspect. We also notice the absence of a relevant review of previous literature on the methods and approaches to analyse the BIA context, as well as the determination of adoption factors with a particular emphasis on human axis. The review aims to identify the most common factors in the literature for Business Intelligence Adoption (BIA) and present the main approaches, analysis methods and frameworks with model recently used in the study of BIA. Methods: This study adopts a systematic literature review by selecting and analysing 32 relevant studies published between 2012 and 2022 from two reputable databases, Science Direct and Web of Science. Content analysis was employed to scrutinize the selected article and identify the factors and characteristics that influence the adoption of Business Intelligence. Findings: The research unveiled over seventy TOE factors and twenty-four distinct human factors relevant to Business Intelligence Adoption. These findings help elucidate the multifaceted nature of BIA and the key elements that drive its adoption. Practical implications: This study enhances the existing body of knowledge by providing a thorough analysis of methodologies and approaches used in BIA research, while also advancing the understanding of adoption factors, especially those related to the human dimension. Originality/Value: The originality lies in its emphasis on the main approaches, analysis methods, and recently used models in the study of BIA. Furthermore, it enhances the field's originality and value by categorizing adoption factors within the TOE framework and giving special attention to human factors.

The Influence of Business Intelligence to Maintain Customer Relationships in Small and Medium Enterprises in Indonesia

The adoption of Business intelligence (BI) has become increasingly prominent among organizations for attracting customers and gaining a competitive edge. This becomes even more important for small and medium enterprises (SMEs) which face immense pressure to retain existing customers and attract more customers for survival. This study presents a systematic literature review of studies investigating the impact of BI on customer relations with exclusive focus on Indonesia, which has a growing number of SMEs (also called ‘UMKMs’). By examining 15 papers published between 2013 to 2024, the findings of the study highlight that BI contributes to building better connections with customers and making them feel more engaged and satisfied. This study provides valuable insights for SMEs in Indonesia to adopt BI to attract more customers. The findings of the study also lay the foundation for future research, especially those wanting to perform an empirical investigation.

Examining the relationship between business intelligence adoption and marketing effectiveness: The mediating role of customer satisfaction

Examining the relationship between business intelligence adoption and marketing effectiveness: The mediating role of customer satisfaction

The Influence of Strategic Planning and Analytical Maturity on Organizational Performance in Implementing Business Intelligence in Indonesia

This research delves into the dynamics of intricate Business Intelligence (BI) deployments in Indonesian startups, emphasizing the interplay of organizational performance, analytical maturity, and strategic planning. Structural Equation Modeling with Partial Least Squares (SEM-PLS) was utilized in the study, which had 187 individuals from several industries, to examine the linkages and extract significant findings. The results showed three strong positive relationships: organizational performance is positively impacted by strategic planning, analytic maturity has a considerable impact on organizational performance, and strategic planning influences analytic maturity. Large impact sizes and statistical robustness characterize these practically meaningful associations. This study adds to our understanding of BI adoption in the particular setting of startups by highlighting the crucial roles that mature analytics and strategic planning play in fostering organizational success.

BUSINESS INTELLIGENCE IMPLEMENTATION ROADMAP FOR HOSPITALITY AND TOURISM INDUSTRY: EXPLORATY WORK

Hospitality and tourism are sectors that generate a large amount of data, from hotel bookings, flights and customer information to data on tourist destinations and tourist preferences. The use of business intelligence in the hospitality and tourism industry enables companies to intelligently analyse this data and make informed decisions to improve their services, optimise operational efficiency, and enhance the customer experience. This research addresses the adoption of business intelligence in hospitality and tourism companies and, in the first phase, aims to identify and characterise the strategic objectives underlying decision-making in hospitality and tourism companies. After reviewing the literature, it was found that there are some studies on the use of business intelligence in companies in the hospitality and tourism sectors, although there is no roadmap to serve as a reference for the implementation of a business intelligence system in companies in these sectors. The objective of this research is to present the methodology of a roadmap proposal for the implementation of business intelligence systems in companies in the hospitality and tourism sectors, which will allow them to improve their ability to analyse and evaluate the data and information available in the different systems and platforms.

Analyzing the Influence of Cloud Business Intelligence on Small and Medium Enterprises A Case Study of Morocco

Business intelligence (BI) has long been a crucial factor in bolstering organizational competitiveness, offering strategic insights that shape decision-making and propel business expansion. The advent of cloud computing has further amplified data sharing and collaboration. This study advocates for the adoption of Cloud BI as an innovative tool to bolster the economic growth of small- and medium-sized enterprises (SMEs) in Morocco. We emphasize the interconnectedness of these businesses' performance with the overall well-being of the Moroccan economy, underscoring the need for regulatory bodies to prioritize not only financial support but also a keen focus on technological advancements. We explore how technological integration can enhance the competitive edge of SMEs. Finally, we conclude by presenting a framework that incorporates the migration of BI to the cloud within the realm of Cloud BI. Drawing inspiration from prior research, we propose modifications tailored to address the specific concerns of SMEs in embracing cloud BI technology.

The Interplay of Human, Organizational, Environmental, and Technological Factors in Business Intelligence Adoption: A Systematic Literature Review

Finalidade: O objetivo desta pesquisa é identificar os fatores mais comuns na literatura que influenciam a Adoção de Inteligência Empresarial (BIA) e apresentar as principais abordagens, métodos de análise e estruturas com modelo recentemente usado no estudo da BIA. Purpose: The objective of this research is to identify the most common factors in the literature influencing Business Intelligence Adoption (BIA) and present the main approaches, analysis methods and frameworks with model recently used in the study of BIA. Theoretical framework: Business intelligence (BI) has become a significant subject of study for both practitioners and researchers, due to its capabilities to apply data analytics and produce key information to support business decision-making. The literature indicates that most organizations have not succeeded in fully leveraging the benefits of BI, Furthermore, there is a limited availability of studies that investigate the human aspect. We also notice the absence of a relevant review of previous literature on the methods and approaches to analyse the BIA context, as well as the determination of adoption factors with a particular emphasis on human axis. The review aims to identify the most common factors in the literature for Business Intelligence Adoption (BIA) and present the main approaches, analysis methods and frameworks with model recently used in the study of BIA. Methods: This study adopts a systematic literature review by selecting and analysing 32 relevant studies published between 2012 and 2022 from two reputable databases, Science Direct and Web of Science. Content analysis was employed to scrutinize the selected article and identify the factors and characteristics that influence the adoption of Business Intelligence. Findings: The research unveiled over seventy TOE factors and twenty-four distinct human factors relevant to Business Intelligence Adoption. These findings help elucidate the multifaceted nature of BIA and the key elements that drive its adoption. Practical implications: This study enhances the existing body of knowledge by providing a thorough analysis of methodologies and approaches used in BIA research, while also advancing the understanding of adoption factors, especially those related to the human dimension. Originality/Value The originality lies in its emphasis on the main approaches, analysis methods, and recently used models in the study of BIA. Furthermore, it enhances the field's originality and value by categorizing adoption factors within the TOE framework and giving special attention to human factors.

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.

Understanding the continuous use of business intelligence: the case of Jordan

ABSTRACT Business intelligence (BI) system has become a crucial cornerstone of decision support, providing valuable information for effective organisational decision-making. This study contributes to BI literature by offering valuable insights into technology adoption in developing countries. It highlights unexplored BI adoption aspects that warrant further investigation in developing economies. Therefore, drawing upon ECM, flow theory, and IS success theory, an integrated model is proposed to study BI's continuous use in Jordan. This study utilised a quantitative survey methodology to examine how the synthesized model impact users’ intentions to continue using BI tools. The survey was conducted with 241 participants from organisations in different sectors in Jordan. The results, as analysed using partial least squares structural equation modeling (PLS-SEM), indicated significant relationships between quality-related factors, flow-related factors, post adoption factors and the continuous intention to use BI tools. The study's findings hold vital implications for policymakers, highlighting influential factors in BI tools usage.

The Role of Business Intelligence adoption as a Mediator of Big Data Analytics in the Management of Outsourced Reverse Supply Chain Operations

The Role of Business Intelligence adoption as a Mediator of Big Data Analytics in the Management of Outsourced Reverse Supply Chain Operations

Factors influencing business intelligence adoption by higher education institutions

Business intelligence (BI) has become increasingly popular among executives in various industries owing to its potential to facilitate informed decision-making. Nevertheless, its adoption is not well explored in higher education institutions (HEIs), where a large volume of data is generated. Therefore, this study aims to investigate the key drivers that underlie BI adoption in HEIs, leveraging the conceptual lens of the Technology-Organization-Environment (TOE) framework. To do so, prominent factors in TOE contexts have been gleaned from related BI literature. The study used PLS-SEM modelling to analyze quantitative data collected from 387 individuals in various management roles within HEIs in Jordan. The results showed that top management support, information culture, compatibility, organizational readiness, relative advantages, perceived Complexity, information quality, and vendor selection are significant determinants of BA in HEIs—competitive pressure, which was statistically insignificant. The results further revealed that information culture emerges as the strongest predictor, while Complexity exerts a significant negative effect on BI, demonstrating that Complexity acts as a key hurdle in BI adoption. The outcomes of this study offer valuable guidance for HEIs executives concerning the antecedents to consider for successful BI implementation.

Data analytics impacts in the field of accounting

This research study has focused on the impact of business intelligence and data analytics in the field of accounting. Based on the information collected from scholarly sources, data analytics, and business intelligence is helpful for business organizations in the improvement of their accounting processes and enhancing accuracy in real-time data storing and analysis. The research paper has analyzed the possible impact of big data analytics and business intelligence regarding the transformation of accounting practices. This research paper has also highlighted three main benefits or advantages of data analytics and business intelligence adoptions in accounting systems which include: increasing accuracy, enhancing efficiency, and improvement in the decision-making processes. Based on the research findings we suggest a significant impact of data analytics on the accounting industry which has enabled accounting professionals to draw appropriate decisions based on real-time data. However, some challenges and issues are associated with the implementation and adoption of advanced analytics and business intelligence in accounting systems. These challenges and issues are required to be focused on by the business managers while implementing technological advancement plans in business organizations, especially accounting departments. This research paper has also highlighted the possible issues and challenges with those analytics in accounting systems. The overall objective of this research paper is to review existing literature containing secondary and primary research information on similar research topics.

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.

Factors of Organizational Agility Mediated by Competitive Performance in Online Fashion Retailers

An organization is the formation of human relations work behavior efficiently and effectively to obtain personal satisfaction in carrying out their duties and providing certain environmental conditions to achieve goals. This study aimed to determine the effect of system quality, adoption of business intelligence, and flexibility of IT infrastructure mediated by organizational agility mediated by competitive performance on online fashion retailers so that it can be used as a reference in the field of science. Quantitative techniques were used in this study. The analysis of this study is a structural approach to the Equation Model (SEM) with the help of smart PLS. The results of this study are to indicate that the adoption of business intelligence is not able to affect organizational agility, system quality affects organizational agility, IT infrastructure flexibility affects organizational agility, competitive performance affects organizational agility, system quality affects competitive performance, adoption of business intelligence affects competitive performance, IT infrastructure flexibility affects competitive performance. Competitive performance is able to mediate the effect of system quality on organizational agility and IT infrastructure flexibility on organizational agility. Competitive performance is not able to mediate the adoption of business intelligence on organizational agility. This research contributes literature for further research conducted by other researchers.