Main Article Content

Abstract

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


JEL Code: M15.

Keywords

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

Article Details

Author Biographies

Hasan Alhanatleh, Education Ministry of Jordan (Jordan)

PhD

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

Associate Peofessor
Academic profiles: Scopus

How to Cite
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
Cited by

References

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  68. Chang, M. K., & Chung, W. (2001). Determinants of the intention to use Internet/WWW at work: A confirmatory study. Information & Management, 39(1), 1–14
  69. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19(2), 189-211
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  77. Hsu, C. L., & Lin, C. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45, 65-74.
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  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
  87. Lee, D. H., Lee, S. M., Olson, D. L., & Chung, S. H., (2010). The effect of organizational support on ERP implementation, Industrial Management & Data Systems, 110 (1-2), 269-283.
  88. MacGregor, R., & Vrazalic, L. (2005). A basic model of electronic commerce adoption barriers: a study of regional small businesses in Sweden and Australia. Journal of Small Business and Enterprise Development, 12(4), 510-527.
  89. Morris, M. G., & Dillon, A. (1997). How user perceptions influence software use. IEEE Software, 14(4), 58–65.
  90. Martins, C., Oliveira, T., & Popovič, A. (2014).Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1-13, http://dx.doi.org/10.1016/j.ijinfomgt.2013.06.002
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  92. Oliveira, T, Thomas, M., & Espadanal, M. (2014). Assessing the determinants of cloudcomputing adoption: An analysis of the manufacturing and services sectors, Information & Management,51, 497–510.
  93. Olhager, J., & Selldin, E. (2003). Enterprise resource planning survey of Swedish manufacturing firms. European Journal of Operational Research, 146, 365-73.
  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.
  95. Podsakoff, P. M, MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and/recommended remedies.Journal of Applied Psychology, 88, 879-903.
  96. Preacher, K. J., & Hayes, A. F., (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods Instruments Computer, 36(4), 717–731
  97. Ruivo, P., Oliveira, T., & Neto, M. (2012). ERP use and value: Portuguese and Spanish SMEs. Industrial Management & Data Systems, 112(7), 1008-1025.
  98. Rajan, C. A., & Baral, R. (2015). Adoption of ERP system: An empirical study of factors influencing the usage of ERP and its impact on end user, IIMB Management Review,27(2),105-117. http://dx.doi.org/10.1016/j.iimb.2015.04.008
  99. Saini, S.L., Saini, D.K., Yousif, J.H. and Khandage, S.V. (2011).Cloud computing and enterpriseresource planning systems. Proceedings of the world Congress on Engineering, London, U.K, 1,681-684.
  100. Santamaría-Sánchez, L., Núnez-Nickel, M., & Gago-Rodríguez, S. (2010). The role played by interdependences in ERP implementations: An empirical analysis of critical factors that minimize elapsed time. Information and Management, 47(2), 87-95.
  101. Slevin, D. P., & Pinto, J. K. (1987). Balancing strategy and tactics in project implementation. Sloan Management Review,29, 33-44.
  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.