{"title":"Predictors of Perceived Learning Outcomes, Satisfaction, and Continued Use Intention in SAP ERP-Enabled Courses","authors":"Y. Zhao, K. Bandyopadhyay, C. Barnes","doi":"10.4018/ijeis.2020040104","DOIUrl":null,"url":null,"abstract":"Enterprise resource planning (ERP) systems allow businesses to achieve high performance through distinctive capabilities and are one of the fastest growing areas within information systems. Many universities have adopted ERP in their management information systems (MIS) curriculum to increase the marketability of their students. Drawing on the IS success model and several constructive learning theories, this study develops a model that is predictive of students' continued ERP software use intention, satisfaction, and perceived learning outcomes. SAP is the ERP system used in this study. Business students at four mid-sized state universities in the United States were surveyed. The universities are members of the SAP University Alliance. There were 373 usable responses. Partial least squares structural equation modeling (PLS-SEM) was used to empirically test the model. The findings indicate that student motivation, perceived instructor support, and ERP system quality are strong predictors of student satisfaction, and learning outcomes. Student motivation and ERP system quality, but not perceived instructor support, are also significant predictors of continued use intention.","PeriodicalId":44507,"journal":{"name":"International Journal of Enterprise Information Systems","volume":" ","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4018/ijeis.2020040104","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Enterprise Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijeis.2020040104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Enterprise resource planning (ERP) systems allow businesses to achieve high performance through distinctive capabilities and are one of the fastest growing areas within information systems. Many universities have adopted ERP in their management information systems (MIS) curriculum to increase the marketability of their students. Drawing on the IS success model and several constructive learning theories, this study develops a model that is predictive of students' continued ERP software use intention, satisfaction, and perceived learning outcomes. SAP is the ERP system used in this study. Business students at four mid-sized state universities in the United States were surveyed. The universities are members of the SAP University Alliance. There were 373 usable responses. Partial least squares structural equation modeling (PLS-SEM) was used to empirically test the model. The findings indicate that student motivation, perceived instructor support, and ERP system quality are strong predictors of student satisfaction, and learning outcomes. Student motivation and ERP system quality, but not perceived instructor support, are also significant predictors of continued use intention.
期刊介绍:
Global markets and competition have forced companies to operate in a physically distributed environment to take the advantage of benefits of strategic alliances between partnering firms. Earlier, information systems such as Material Requirements Planning (MRP), Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) have widely been used for functional integration within an organization. With global operations are in place, there is a need for suitable Enterprise Information Systems (EIS) such as Enterprise Resource Planning (ERP) and E-Commerce (EC) for the integration of extended enterprises along the supply chain with the objective of achieving flexibility and responsiveness.