Beyond ERP Adoption: Does System Choice Associate With Firm Performance?

Sammanfattning

This thesis examines the association between Enterprise Resource Planning vendor type, generation, complexity, and firm performance among Fortune 100 companies in the United States in 2025. Moreover, whether differences in ERP characteristics have a statistical relationship with firm performance, measured by Return on Assets, is investigated. While prior researchers studied Enterprise Resource Planning adoption and implementation, this study examines a broader perspective. Accordingly, the study addresses the research question: “Is the choice of Enterprise Resource Planning (ERP) systems associated with the firm performance of Fortune 100 companies?” Consequently, a quantitative, positivist, and deductive methodological approach is applied. To examine this relationship, several statistical models are estimated. Ordinary Least Squares is applied as a baseline model, Random Effects as a main model, and a Generalized Linear Mixed Model and a Bootstrapping are used as robustness tests. The results indicate consistency and robustness across all statistical models. All ERP vendor types exhibited a significant relationship, although varying in direction. Enterprise Resource Planning generation predominantly indicated a significant and positive association with firm performance, while Enterprise Resource Planning complexity displayed a statistically significant and negative association. Overall, the results indicate a statistically significant relationship between Enterprise Resource Planning characteristics and firm performance, highlighting the importance for large companies to take Enterprise Resource Planning characteristics into consideration at implementation. The findings partially support theoretical frameworks and prior empirical research. Accordingly, the study concludes that variation in Enterprise Resource Planning system characteristics indicates a statistically significant association with firm performance among Fortune 100 companies, while simultaneously underlining the importance of efficient implementation of Enterprise Resource Planning systems. The study is based on a relatively short time period (2023-2025), which may limit the possibility of capturing long term associations and time lags. Future research should therefore apply a longer sample period, and enhance generalizability by including smaller firms and more diverse geographical regions.