LATENT PROFILES OF PERCEIVED SYSTEMIC E-GOVERNMENT BARRIERS IN SUDANESE HIGHER EDUCATION: A PERSON-CENTRED ANALYSIS OF EMPLOYEE SURVEY DATA

Abstract

Studies of e-government barriers in developing settings often report average scores or variable-centred dimensions, implicitly treating employees as a single response population. This paper applies latent profile analysis to employee survey data from Sudanese higher education to examine whether perceived systemic e-government barriers cluster into hidden response groups. The dataset includes 275 valid responses and 35 five-point barrier items. A three-profile solution was retained because it provided the most defensible balance between statistical fit, class size, entropy, and substantive interpretability. The retained profiles are best understood as low-, moderate-, and high-systemic barrier groups rather than as sharply specialized domain types. The high-systemic profile reported elevated scores across governance, leadership, capability, digital inclusion, financing, and utilities. Qualification, job role, and years of experience were associated with profile membership. Robustness checks using alternative covariance structures and split-half estimation recovered the same substantive ordering. The study contributes to person-centred barrier modelling by showing that employee heterogeneity in this setting lies primarily in the intensity of system-wide constraints, with practical implications for more differentiated reform design.