A technology acceptance model extension of ERP use in Sri Lanka’s pharmaceutical industry
TL;DR
It is highlighted that in regulated contexts, ERP value depends more on real-time data, compliance and system usefulness than on customization, positioning ERP as a strategic decision-support system.
Abstract
This study aims to examine how enterprise resource planning (ERP) system characteristics influence the effectiveness of decision-making (EDM) in Sri Lanka’s pharmaceutical industry, a highly regulated sector that demands strong compliance, operational efficiency and real-time information. Grounded in the technology acceptance model (TAM), the study extends prior research by linking ERP usability and functional capabilities directly to decision-making outcomes rather than focusing solely on technology adoption. A quantitative, cross-sectional design was adopted, with data collected via a structured questionnaire from 274 ERP users in Sri Lanka’s pharmaceutical firms. The study examined the effects of two TAM constructs jointly – perceived ease of use (PEOU) and perceived usefulness (PU) – and ERP characteristics: ease of use of ERP (EUE), industry-specific requirements (ISR), user requirements and preferences (URP), real-time reporting capabilities (RRC) and regulatory compliance (RGC) on decision-making effectiveness (EDM). Hierarchical multiple regression was used to assess relationships and to assess the incremental explanatory power. Results indicate that two TAM elements, RRC and RGC, are the strongest positive predictors of EDM. EUE also has a significant but smaller positive effect. ISR shows a negative effect, while URP is not significant. The final model explains 82.5% of the variance (R2 = 0.825), with ERP factors accounting for a significant increase in R2 (ΔR2 = 0.138). Cross-sectional design limits analysis of changes in ERP use and decision-making over time; future studies should adopt longitudinal approaches. Reliance on quantitative survey data restricts deeper insights into user experiences; mixed-method studies are recommended. Focus on Sri Lanka’s pharmaceutical industry limits generalizability; cross-industry and cross-country studies are needed. Emphasis on system variables overlooks factors like culture, leadership and digital skills; future research should include these. Limited focus on emerging technologies; future work should explore ERP integration with artificial intelligence (AI), analytics and decision-support systems. Policymakers should strengthen digital infrastructure and promote ERP adoption through governance frameworks, compliance standards and industry guidelines. Organizations should prioritize user-friendly ERP systems with real-time data access and strong compliance features. Firms must align ERP capabilities with user needs, ensuring intuitive interfaces and actionable insights. Vendors should develop simplified systems with advanced reporting and embedded compliance functions. Strong ERP systems enable business intelligence, analytics and AI-driven tools, enhancing decision quality and supporting timely, transparent and compliant decision-making. This study extends TAM by focusing on EDM rather than adoption. It highlights that in regulated contexts, ERP value depends more on real-time data, compliance and system usefulness than on customization, positioning ERP as a strategic decision-support system.
