From Readiness to Performance: Modelling AI-Enabled HR Analytics Adoption Capability as a Second-Order Formative Construct in Nigerian SMEs

Michael Raphael Onenyi (Department of Business Administration, Prince Abubakar Audu University, Anyigba, Nigeria)
Peter Ugbedeojo Nelson (Department of Business Administration, Federal University Lokoja, Nigeria)
Muhammed Idris Ogbike (Department of Business Administration, Prince Abubakar Audu University, Anyigba, Nigeria)

SEISENSE Journal of Management
Vol. 9 No. 1 (2026): SEISENSE Journal of Management

Objective: This study examines how AI-enabled HR Analytics Adoption Capability (AIHRA), a second-order formative construct, is associated with operational performance among Nigerian SMEs.Design: Drawing on UTAUT2, the Resource-Based View, and Socio-Technical Systems Theory, a survey was administered to 296 respondents across SMEs in Lagos, Abuja, Port Harcourt, and Kano. PLS-SEM via SmartPLS 4.0.9.9 was used for analysis.Findings: Technological Readiness (weight = 0.584, p<0.001) and Organisational Support (weight = 0.532, p<0.001) significantly form AIHRA. Perceived Value and Use is non-significant (0.119, p = 0.219) but shows absolute importance. AIHRA is positively associated with operational performance (β = 0.626, R2 = 0.392). Policy Implications: Managers and policymakers should prioritise digital infrastructure and organisational support before AI procurement. Originality: This study contributes an empirically tested higher-order formative model linking AI-HR analytics adoption capability to operational performance in Nigerian SMEs, extending prior technology-organisation-environment evidence by showing structural determinants dominate perceptual constructs within a multi-theory, capability-based specification.