Personality types in learning enterprise resource planning (ERP) systems
BR Lea, D Mirchandani, M Sumner… - Journal of Computer …, 2022 - Taylor & Francis
BR Lea, D Mirchandani, M Sumner, K Yu
Journal of Computer Information Systems, 2022•Taylor & FrancisThis research explores the influence of personality types on ERP system learning
performance in a university setting. Four personality types (labeled Type 1 to 4) were
identified using cluster analysis of 176 survey respondents' Big Five personality traits, ie,
conscientiousness, neuroticism, extraversion, openness, and agreeableness. These four
personality types were found to be significantly associated with ERP system learning
performance. Additionally, prior knowledge, user affect, demographic factors (such as …
performance in a university setting. Four personality types (labeled Type 1 to 4) were
identified using cluster analysis of 176 survey respondents' Big Five personality traits, ie,
conscientiousness, neuroticism, extraversion, openness, and agreeableness. These four
personality types were found to be significantly associated with ERP system learning
performance. Additionally, prior knowledge, user affect, demographic factors (such as …
Abstract
This research explores the influence of personality types on ERP system learning performance in a university setting. Four personality types (labeled Type 1 to 4) were identified using cluster analysis of 176 survey respondents’ Big Five personality traits, i.e., conscientiousness, neuroticism, extraversion, openness, and agreeableness. These four personality types were found to be significantly associated with ERP system learning performance. Additionally, prior knowledge, user affect, demographic factors (such as gender, age, year in school), and environmental factors (such as ethnicity, location, English proficiency) were found to moderate the relationships between the four personality types and ERP learning performance. These findings can provide valuable insights into the organizational success of ERP systems by helping to identify which users may effectively learn to utilize these systems.
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