research study of enterprise resource planning (ERP) systems’ acceptance based on the technology acceptance model (TAM)
Simona Sternad (Author), Samo Bobek (Author), Uroš Zabukovšek (Author), Zoran Kalinić (Author), Polona Tominc (Author)

Abstract

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.

Keywords

traditional PLS-SEM;artificial neural network (ANN) analysis;Importance–Performance Matrix Analysis (IPMA);ERP system acceptance;TAM model;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UM EPF - Faculty of Economics and Business
Publisher: MDPI
UDC: 659.2
COBISS: 105683203 Link will open in a new window
ISSN: 2227-7390
Views: 13
Downloads: 0
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Other data

Secondary language: Slovenian
Secondary keywords: umetna nevronska omrežja;analiza matrike pomembnosti in učinkovitosti;ERP sistemi;model tehnološke sprejemljivosti;
Type (COBISS): Scientific work
Pages: 28 str.
Volume: ǂVol. ǂ10
Issue: ǂissue ǂ9
Chronology: 2022
DOI: 10.3390/math10091379
ID: 24492734
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