Deployment factors for mobile business intelligence in developing countries small and medium enterprises

• Published in: African journal of science, technology, innovation and development Vol. 10; no. 6; pp. 715 - 723
• Main Authors: Adeyelure, Tope Samuel, Kalema, Billy Mathias, Bwalya, Kelvin J.
• Format: Journal Article
• Language: English
• Published: Routledge 19.09.2018; Taylor & Francis
• Subjects: Advance impact analysis; Mobile business intelligence; Principal component analysis; Small and medium enterprises; Textual analysis
• ISSN: 2042-1338; 2042-1346
• DOI: 10.1080/20421338.2018.1491137

Data are more rapidly generated than they can be digested and consumed in real time due to the increased mobility and automation of activities of small and medium enterprises (SMEs). These challenges could be avoided if SMEs in developing countries deployed Mobile Business Intelligence (MBI) within their settings. Though the deployment of MBI in SMEs in developed countries has been noticeable, its success in the developing countries is still far from reach. Few to no studies have been conducted to investigate the direct and indirect factors influencing the deployment of MBI within SMEs in developing countries. This study sought to investigate and determine factors that influence the deployment of MBI in developing countries' SMEs. Relevant literature was reviewed to determine factors that previous researchers have identified as essential in MBI deployment. Textual analysis was used to verify each factor, remove repetitions and determine the frequencies of their appearance in the literature. Principal Component Analysis (PCA) was then used as reduction method for the many factors that had been identified in the literature. This also helped in the factor categorization. Lastly, a multi-criteria decision-making method of Advance Impact Analysis (ADVIAN ® ) was carried out to determine the direct and indirect impacts that exist between the factors and the overall system of MBI deployment. Based on the ADVIAN ® results, impacting factors were classified into four categories namely: active (for example, user privacy), reactive (for example, changing trends), critical (for example, top management support) and inert (for example, technician's location). The findings of this study are expected to be integrated into SMEs in developing countries to prioritize those factors that need additional attention during the deployment of MBI.