Original Research

Factors affecting Mobile Business Intelligence readiness in the South African telecom sector

Marothi P. Lemekwane, Nkqubela Ruxwana, Tendani J. Lavhengwa, Sunday O. Ojo
South African Journal of Information Management | Vol 28, No 1 | a2097 | DOI: https://doi.org/10.4102/sajim.v28i1.2097 | © 2026 Marothi P. Lemekwane, Nkqubela Ruxwana, Tendani J. Lavhengwa, Sunday O. Ojo | This work is licensed under CC Attribution 4.0
Submitted: 25 September 2025 | Published: 24 February 2026

About the author(s)

Marothi P. Lemekwane, Department of Informatics, Faculty of Information and Communication, Tshwane University of Technology, Pretoria, South Africa
Nkqubela Ruxwana, Department of Digital Transformation, School of Computer Science, University of Wollongong, Dubai, United Arab Emirates
Tendani J. Lavhengwa, Department of Informatics, Faculty of Information and Communication, Tshwane University of Technology, Pretoria, South Africa
Sunday O. Ojo, Department of Information Technology, Faculty of Accounting and Informatics, Durban University of Technology, Durban, South Africa

Abstract

Background: The rapid adoption and accelerated integration of mobile technology into organisational processes have significantly transformed the landscape of data collection and analysis, establishing Mobile Business Intelligence (MBI) as a critical enabler of real time, data-driven decision-making. Mobile Business Intelligence has emerged as a pivotal tool for enhancing the speed and accuracy of strategic business decisions.
Objectives: The study investigated and established factors affecting MBI readiness within the South African telecommunications sector.
Method: Quantitative research methodology and probability sampling were used to select participants, and closed-ended questionnaires were used. One hundred and twenty-eight responses were received and tested. The factors affecting MBI readiness were validated using quantitative analysis.
Results: Fourteen factors affecting MBI readiness were identified, namely: organisational culture, organisational capability, policies and people, infrastructure, security, skills, training, enterprise mobility support, need for change, inhibitors, motivators, and change enablers.
Conclusion: The findings of this study may encourage success in leveraging mobility and developing better strategies and approaches for MBI adoption, enabling organisations to realise expected benefits, make well-informed decisions and conserve costs, time and resources. These organisations could achieve a higher success rate with MBI investments.
Contribution: This study contributed methodologically, theoretically and practically by identifying critical success factors affecting MBI readiness. Methodologically, the identified factors inform the MBI readiness model and provide guidelines for the successful implementation of MBI solutions.


Keywords

Mobile Business Intelligence; Mobile Business Intelligence readiness; technology readiness; telecommunications; Business Intelligence; mobile technology

JEL Codes

M15: IT Management

Sustainable Development Goal

Goal 4: Quality education

Metrics

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