Aug 2026· Veredas do Direito· 0 citations· 41 references
TL;DR
This study investigates the adoption of BI practices in small and medium-sized enterprises (SMEs) to examine the extent of BI integration and its impact on decision-making, competitiveness, and the critical success factors influencing effective BI implementation.
Abstract
Background: The adoption of Business Intelligence (BI) practices has gained attention across enterprises as rapid advances in digital technologies enable the automation of business processes and enhance organisational competitiveness. BI tools offer SMEs the ability to generate insights that support informed decision-making. Despite these benefits, SMEs often encounter challenges in adopting and implementing BI, particularly in relation to financial constraints, limited staff skills, and organisational culture. Objectives: This study investigates the adoption of BI practices in small and medium-sized enterprises (SMEs) to examine the extent of BI integration and its impact on decision-making, competitiveness, and the critical success factors influencing effective BI implementation. Method: A qualitative research approach aligned with an interpretivist paradigm was employed. The Technology Acceptance Model (TAM) was adopted as the lens to guide the study. Data were collected through in-depth interviews with nine (9) participants, including owners, a director and co-founder, and employees from three purposively selected SMEs. Participants were chosen to reflect diverse organisational roles and experiences with BI tools. The interview data were analysed thematically to identify patterns related to BI adoption, utilisation, and effectiveness. Results: The findings indicate that BI adoption among South African SMEs remains limited, with many enterprises relying primarily on basic BI tools. Nevertheless, SMEs that have adopted BI reported improvements in decision-making speed and overall competitiveness. Key challenges identified include data integration issues, financial limitations, and a lack of technical skills. Successful BI adoption was found to depend on leadership support, appropriate training, strategic alignment, and the use of tailored, cloud-based BI solutions. Conclusion: The study concludes that while BI adoption offers notable performance benefits for South African SMEs, its success is contingent upon addressing financial, skills-related, and cultural barriers. Enhanced funding support, practical training initiatives, and effective change management are essential. The study contributes practical insights into the enablers and challenges of BI adoption in a developing economy context and extends the discourse on BI adoption in emerging economies, offering guidance for policymakers, SME owners, and technology providers seeking to enhance SME competitiveness through data-driven decision-making.
This study investigates the factors influencing the adoption of business intelligence (BI) systems among small and medium enterprises (SMEs). By integrating the Technology Acceptance Model (TAM) with the Technology-Organization-Environment (TOE) framework, this research proposes a comprehensive model that was empirically tested using data collected from 312 SME managers across multiple industries in Indonesia. A quantitative approach was employed using an online survey instrument, and the data were analyzed using Structural Equation Modeling with Partial Least Squares (PLS-SEM). The results indicate that perceived usefulness, organizational readiness, and competitive pressure are the strongest predictors of BI adoption intention among SMEs. Interestingly, perceived ease of use has a weaker effect than expected, suggesting that SME managers prioritize strategic value over usability when considering BI adoption. Furthermore, top management support positively moderates the relationship between organizational readiness and BI adoption intention. This study extends the theoretical understanding of technology adoption in resource-constrained settings and provides practical recommendations for BI vendors and policymakers targeting the SME market.
Dorris Yadewani, Hendrik Permana, Marjohan et al.· International Journal of Dig...· 0 citations
Aim/Purpose: This study aims to identify the key factors influencing the adoption of integrated enterprise resource planning and business intelligence systems (ERPBI) in small and medium-sized enterprises (SMEs). Using the technology-organization-environment (TOE) framework, the study develops a conceptual framework explaining how technological, organizational, and environmental determinants shape ERPBI adoption.
Background: ERP and BI systems are increasingly interdependent: ERP systems integrate operational data, while BI systems convert that data into decision-support insights. In SMEs, adopting integrated ERPBI systems is especially challenging because of limited resources, technical expertise, and managerial capacity. Since existing studies often examine ERP and BI separately, an integrated, SME-focused framework is needed to better explain the combined adoption of operational and analytical capabilities.
Methodology: A two-phase research design was employed. First, a systematic literature review of peer-reviewed studies published between 2017 and 2025 was conducted to extract ERPBI adoption determinants. Second, ten domain specialists were selected through purposive sampling based on their experience in ERP, BI, SME digitalization, or information systems adoption. They evaluated the relevance and importance of the identified determinants, which were then ranked using aggregated mean expert scores.
Contribution: This study consolidates fragmented ERP and BI adoption research into an integrated ERPBI perspective and proposes a validated TOE-based conceptual framework specifically tailored to SMEs.
Findings: The findings suggest that ERPBI adoption in SMEs is influenced by twelve technological, organizational, and environmental determinants: top management support, training, competitive pressure, communication, firm size, compatibility, relative advantage, perceived usefulness, artificial intelligence tools, big data analytics ability, cloud computing facility, and pandemic recovery planning. Rather than presenting these factors as definitive predictors of adoption success, the study synthesizes prior evidence and expert feedback to propose a structured framework for further empirical investigation.
Recommendations for Practitioners: For practitioners, the proposed framework should be viewed as a decision-support guide rather than a prescriptive implementation model. SME managers may use the framework to assess key readiness areas, including technological compatibility, organizational resources, managerial support, employee capability, vendor support, and external pressures. However, the relevance and priority of these factors may vary across SME size, sector, digital maturity, and resource availability.
Recommendation for Researchers: Future research should empirically test the proposed framework across different SME sectors and regions and investigate post-adoption outcomes using longitudinal approaches.
Impact on Society: Effective ERPBI adoption can strengthen SME resilience, promote sustainable business practices, and contribute to economic stability through enhanced digital transformation.
Future Research: Further studies are encouraged to explore emerging factors such as cybersecurity readiness, data governance, and responsible AI practices in ERPBI adoption.
The findings indicate that e-commerce, cloud computing, customer relationship management, and digital marketing tools supported operational coordination, market reach, and customer engagement, but limited digital skills, implementation costs, cybersecurity risks, and infrastructure constraints restricted deeper adoption.
Sundeep Kumar, N. Kumar, Akash Singh· Journal of Global Entreprene...· 0 citations
These findings highlight the necessity of customized implementation strategies, focused capacity-building initiatives, encouraging legislative frameworks, and multi-stakeholder cooperation to promote inclusive, responsible AI integration in SMEs.
E. S. Hamid, Bhenu Artha· Archives of Business Researc...· 1 citation
The rapid development of the digital economy has encouraged businesses to adopt digital technologies such as digital payment systems, e-commerce platforms, cloud-based management systems, and digital marketing tools. However, many businesses, particularly small and medium-sized enterprises, still face adoption challenges due to limited resources, digital skills, and implementation costs. This study aims to explore how technology innovation adoption influences business performance by examining the experiences, strategies, and challenges of business actors. A descriptive qualitative approach was employed through interviews, observations, and documentation involving business owners, managers, and technology stakeholders. Data were analyzed using data reduction, data display, thematic analysis, and conclusion drawing. The novelty of this study lies in its integrated qualitative perspective that views technology adoption as a multidimensional transformation process. Unlike previous studies that often focus on individual technologies or quantitative relationships, this research examines the combined adoption of multiple digital technologies within a unified framework. The findings show that technology adoption improves operational efficiency, productivity, market expansion, customer engagement, and competitiveness, while organizational readiness and digital capability remain key challenges. The study concludes that successful digital transformation requires alignment between technological readiness, organizational capability, and strategic implementation, providing contextual insights into how integrated digital technologies create business value.
M. Mustam, Agung Rizky, John Edwards· Aptisi Transactions on Manag...· 0 citations
The findings emphasise that successful AI adoption depends more on organizational AI literacy for a firm than on technology investment, and suggest that policymakers should prioritise capability building initiatives, educators develop curricula on AI targeted towards specific job roles, and MSME leaders should focus on upskilling human resources before they consider acquiring any technologies.
Mohammad Falahat, Qi Yi Thong, Murali Raman et al.· Journal of Asian Scientific...· 0 citations
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