20.500.12556/DKUM-89418 Enhancing PLS-SEM-Enabled research with ANN and IPMA research study of enterprise resource planning (ERP) systems’ acceptance based on the technology acceptance model (TAM) PLS-SEM has been used recently more and more often in studies researching critical factors influencing the acceptance and use of information systems, especially when the technology acceptance model (TAM) is implemented. TAM has proved to be the most promising model for researching different viewpoints regarding information technologies, tools/applications, and the acceptance and use of information systems by the employees who act as the end-users in companies. However, the use of advanced PLS-SEM techniques for testing the extended TAM research models for the acceptance of enterprise resource planning (ERP) systems is scarce. The present research aims to fill this gap and aims to show how PLS-SEM results can be enhanced by advanced techniques: artificial neural network analysis (ANN) and Importance–Performance Matrix Analysis (IPMA). ANN was used in this research study to overcome the limitations of PLS-SEM regarding the linear relationships in the model. IPMA was used in evaluating the importance and performance of factors/drivers in the SEM. From the methodological point of view, results show that the research approach with ANN artificial intelligence complements the results of PLS-SEM while allowing the capture of nonlinear relationships between the variables of the model and the determination of the relative importance of each factor studied. On other hand, IPMA enables the identification of factors with relatively low performance but relatively high importance in shaping dependent variables. traditional PLS-SEM artificial neural network (ANN) analysis Importance–Performance Matrix Analysis (IPMA) ERP system acceptance TAM model umetna nevronska omrežja analiza matrike pomembnosti in učinkovitosti ERP sistemi model tehnološke sprejemljivosti true false true MDPI Angleški jezik Slovenski jezik Znanstveno delo 2024-07-09 09:12:06 2024-07-09 09:37:55 2024-07-10 04:36:42 0000-00-00 00:00:00 2022 0 0 Str. 1-28 Št. 9, št. članka 1379 Letn. 10 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2022-03-16 2022-04-18 2022-04-20 659.2 105683203 10.3390/math10091379 2227-7390 Zabukovsek-2022-Enhancing_PLS-SEM-Enabled_Rese.pdf Zabukovsek-2022-Enhancing_PLS-SEM-Enabled_Rese.pdf 1 61A8155150BE869B71329E5EA057E55C c54dedfed4bf3bb3913c03d2928d2042056a114fc7925933d54e3c8ac47895ce f5f9e51f-3dc5-11ef-9361-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=181261 https://doi.org/10.3390/math10091379 0 10e6d439-3dc6-11ef-9361-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=181262 Ekonomsko-poslovna fakulteta 0 0 0