Main Article Content

Abstract

Enterprise resource planning (ERP) systems have been used by organizations for years, whereas Cloud ERP systems gained an audience a few years ago from practitioners and academicians. As such, there is a migration from the traditional ERP to the Cloud ERP system, and employees in most organizations are accustomed to the traditional ERP system. In order to improve the efficiency and effectiveness of the Cloud ERP system used in the operation stage. Organizations must research the factors that impact users' satisfaction and managerial decision-making. There are a lot of prior studies that measured users' adoption of ERP systems using a technological acceptance model (TAM). Thus, this study also utilized the TAM model to examine the factors influencing users' adoption of Cloud ERP systems. To get the maximum value of the validity and reliability of the findings, the study was conducted in two folds: pre-implementation and post-implementation. In addition, structural equation modelling was employed to reach the findings. Finally, the study identified the technology factor, employee factor, perceived usefulness and ease of use as important variables affecting Cloud ERP adoption; and as essential antecedents influencing managerial decision-making. This study is the first to employ the TAM model in the Cloud ERP area in two waves: pre-post implementation phases. Interestingly, the relationships between the pre-and post-implementation variables do not differ significantly.

Keywords

Cloud ERP Cloud E-lerrec TAM model Managerial decision support Technology factor Employee factor Perceived usefulness Perceived ease of use

References

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  82. Iivari, J., & Ervasti, I. (1994). User information satisfaction: IS implementability and effectiveness, Information and Management, 27(4), 205-220.
  83. Kwahk, K. Y., & Lee, J. N., (2008). The role of readiness for change in ERP implementation: Theoretical bases and empirical validation, Information & Management, 45(7), 474-481.
  84. Karahanna, E., & Straub, D. W. (1999). The psychological origins of perceived usefulness and ease-of-use. Information & Management, 35, 237–250.
  85. Krejcie, R.V. & Morgan, D.W. (1970). Determining sample size for research activities. Educational and psychological measurement,30, 607-610.
  86. Lin, H. (2010). An investigation into the effects of IS quality and top management support on ERP system usage, Total Quality Management & Business Excellence, 21(3), 335-349, http://dx.doi.org/10.1080/14783360903561761
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  94. Peng G. C., & Gala, G. J. (2014). Cloud ERP: A new dilemma to modern organizations?,Journal of Computer Information Systems, 54(4), 22-30.
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  102. Sumner, M., & Hostetler, D. (1999). Factors influence the adoption of technology in teaching. Journal of Computer Information Systems, 40(1), 81-87.
  103. Stockdale, R., & Standing, C. (2006). A classification model to support SME e-commerce adoption initiatives. Journal of Small Business and Enterprise Development, 13(3), 381-394.
  104. Saadé, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model. Information & Management,42(2), 317-327.
  105. Turel, O., Serenko, A., & Bontis, N. (2007). User acceptance of wireless short messaging services: Deconstructing perceived value. Information & Management, 44, 63-73.
  106. Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: toward a conceptual model of utilization. MIS Quarterly, 15(1), 125-143.
  107. Van der Heijden, H., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions: contributions from technology and trust perspectives. European Journal of Information Systems, 12, 41–48.
  108. Venkatesh, V. (2000). Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.
  109. Wixom, B.H., & Todd, P.A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16, 85–102.
  110. Weng, F., & Hung, M. C. (2014). Competition and Challenge on Adopting Cloud ERP.International Journal of Innovation, Management and Technology, 5(4), 309-313.
  111. Wang, T. L., Su, C. H., Tsai, P. Y., Liang, T. Y., & Wu, W. H. (2008). Development of a Grid ERP architecture: integration of grid computing and enterprise resources planning application, in: 4th International Conference on Wireless Communications, Networking and Mobile Computing, 1–4.
  112. Wang, I. S., Lin, H. H., & Luarn, P. (2006). Predicting consumer intention to use mobile service. Information Systems Journal, 16, 157–179
  113. Xu, X. (2012). From cloud computing to cloud manufacturing. Robotics and Computer-Integrated Manufacturing, 28(1), 75–86. http://dx.doi.org/10.1016/j.rcim.2011.07.002
  114. Z Zhu, K., & Kraemer, K.L. (2005). Post‐adoption variations in usage and value of e‐ business by organizations: cross‐country evidence from the retail industry. Information Systems Research, 16, 61‐84.

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Alhanatleh, H., & Akkaya, M. (2020). Factors Affecting the Cloud ERP: A Case Study of Learning Resources Department at Jordanian Education Ministry. Management & Economics Research Journal, 2(4), 101-122. https://doi.org/10.48100/merj.v2i4.128
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Author Biographies  
Hasan Alhanatleh, Education Ministry of Jordan (Jordan)

PhD

Murat Akkaya, Department of Management Information Systems, Girne American University, Kyrenia (Cyprus)

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Vol. 2 No. 4 (2020): September
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Submitted 20 August 2020
Accepted 21 September 2020
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