Cloud-Based ERP Construction Process Framework in the Customer's Perspective

Hyeong-Soo Kim1, Deuk-Soo Oh1 and Seung-Hee Kim2

  1. Master's Student, Department of IT Convergence Software Engineering, Korea University of Technology and Education
    1600 Chungjeol-ro, Dongnam-gu, Cheonan-si, Chungcheongnam-do (31253) Republic of Korea
    {kawa95, ts0070}@ koreatech.ac.kr
  2. Faculty, Department of IT Convergence Software Engineering, Korea University of Technology and Education
    1600 Chungjeol-ro, Dongnam-gu, Cheonan-si, Chungcheongnam-do (31253) Republic of Korea
    sh.kim@koreatech.ac.kr

Abstract

Process frameworks for the implementation of cloud enterprise resource planning (ERP) were derived and each process was examined through detailed comparisons with on-premise ERP construction processes, using process engineering characteristics. The process frameworks for implementing cloud ERP are classified into infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), content-as-a-service (CaaS), and software-as-a-service (SaaS), depending on the construction type, and are defined based on 6 derived processes, 21 activities, and numerous specific tasks. The process engineering characteristics of the final proposed process framework were further analyzed and examined in comparison to on-premise ERP construction processes with respect to differences and similarities. This study provides a theoretical foundation of standardized research on cloud ERP construction methods. As a practical guideline for stakeholders, it can be used in practice as a process tailoring tool, providing information on specific activities and tasks for each construction phase, contributing to the construction and spread of reliable cloud-based ERP systems from the customer's perspective.

Key words

Cloud ERP, ERP comparison, SaaS ERP, CaaS, PaaS, IaaS

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS211230045K

How to cite

Kim, H., Oh, D., Kim, S.: Cloud-Based ERP Construction Process Framework in the Customer's Perspective. Computer Science and Information Systems, https://doi.org/10.2298/CSIS211230045K