Abstract:
The growing dependence on mobile applications has revolutionized global business operations, offering
substantial advantages, including enhanced customer engagement, streamlined workflows, and expanded market
access. Micro, Small, and Medium Enterprises (MSMEs), particularly in developing economies, can significantly
benefit from harnessing mobile technology. However, many MSMEs in Kampala Capital City Authority (KCCA)
face challenges in designing and delivering mobile applications that meet user needs, resulting in low adoption
rates and disappointing business outcomes. This study developed a user centric model for guiding the development
of mobile applications for Micro, Small, and Medium Enterprises; a case study of Kampala Capital City Authority.
To achieve this, the study explored the user-centric factors that influence the development of mobile applications
for MSMEs, formulated a conceptual model, and validated the user centric model for mobile application
development. The identification of user centric variables was achieved through a review of the literature on
technology adoption models, software development models, the use of mobile applications in MSMEs, challenges
experienced in developing user-centric mobile applications for MSMEs, and a pilot study. The study also
examined Human-Computer Interaction (HCI) and Human-Centered Computing (HCC) models. These models,
which informed the identification of key user-centric constructs including interface consistency, intuitiveness,
usability, and interaction quality, emphasize usability, interaction design, cognitive fit, accessibility, and
continuous user involvement throughout the system lifecycle. This reinforces the importance of designing mobile
applications that align with users’ cognitive capabilities, behavioral patterns, and contextual usage environments.
This study draws from four complementary theoretical frameworks: - The Technology Acceptance Model for
Mobile Services (TAMM) focuses on user perceptions of usefulness and ease-of-use in mobile contexts, while
Task-Technology Fit Theory (TTF) emphasizes the alignment between technology capabilities and task
requirements for optimal performance. Diffusion of Innovation Theory (DOI) explains how technological
innovations spread through social systems based on perceived attributes and communication channels. The
Technology-Organization-Environment (TOE) framework examines use through technological readiness,
organizational characteristics, and environmental pressures, providing a comprehensive lens for understanding
the multi-level factors that influence the acceptance and diffusion of technology. The conceptual model was
developed based on existing literature that explores the causal relationships between independent variables
identified, which are factors that drive design and development, and the dependent variable, which is the user
centric development (UCD). In this model, the independent variables represent key technological, organizational,
individual, and contextual drivers, while user-centric development serves as the dependent outcome. This study
investigated the relationship between these factors and their impact on the development of mobile apps designed
to meet the needs of MSMEs. The study employed an exploratory research design informed by the paucity of
literature on user centric development models. The study integrated both quantitative and qualitative data
collection techniques; the quantitative data enabled the extraction and analysis of descriptive and demographic
statistics and statistical validation of the model, while qualitative techniques enabled triangulation of the
quantitative findings. The adequacy of demographic compositions was confirmed through chi-square and t-test
analysis. The Model analysis and validation utilized the Partial Least Squares-Structured Equation Modelling
(PLS-SEM), a variance based tool found in SmartPLS software. The PLS-SEM analysis divides the model into
measurement and structural components and confirmed several factors that significantly influence user-centric
mobile application development for MSMEs across all four development phases. The most impactful predictors
were User Training (β = .21), Updates (β = .20), and Cross-Platform Capability (β = .19), alongside other factors
such as stakeholder input, compliance, functional features, interface consistency, intuitiveness, design flexibility,
quality assurance, and task-fit. The model accounted for 59.7% of the variance (R² = .597), indicating moderate
to substantial explanatory power. Predictive relevance was also strong, with Q² = .411, reflecting the model’s
robustness in predicting user centric mobile application development outcomes. The development of this model
constitutes a fundamental contribution to the foundational knowledge on user centric development of mobile
technology applications for MSMEs.