A Parallel Mediation Analysis of Behavioral Constructs Linking Intention-to-Use Technology to Performance Outcomes Among Pharmaceutical Executives

Abstract

Managers in organizations are at crossroads in ascertaining the precise mechanisms by which behavioral intention-to-use tendency influences the technology-based performance outcomes of employees. In the Technology Acceptance Model, behavioral intention-to-use is a precursor factor of actual system use. However, there is inadequate information regarding the mechanism through which it indirectly impacts performance in pharmaceutical organizations. Behavioral mechanisms (job satisfaction, conscientiousness, self-efficacy, perceived relevance) transform technology use to desired outcomes and was proposed as explanatory links in the relationship between behavioral intention-to-use and performance. Using the theoretical lens of reasoned action and the technology acceptance model, this study explores the linkage between behavioral intention-to-use and performance among pharmaceutical executives. Using a web-based survey of a random sample of 282 pharmaceutical executives and responses were elicited using self-administered Google Forms questionnaire. Data was analyzed using variance-based structural equation modeling in ADANCO software while controlling for job-based demographics. All independent variables in the model substantially explained the variance in the dependent variable-Technology-based performance significantly. Perceived relevance was the only substantial linkage between behavioral intention and technology-based performance. The study affirms that employees with high perceived relevance of technology use were more inclined to have better performance outcomes. To enhance consistent performance, positive user perception of technology relevance to tasks should be cultivated by ensuring the appropriateness of technology deployed, inclusive of adequate enlightenment and training. The study adds to the existing literature by recommending the addition of perceived relevance to the technology acceptance model.