Enhancing Functional Fit with Continuous Training During the ERP Post-Implementation Phase
Abstract
Enterprise Resource Planning (ERP) systems, such as SAP, feature a rich set of integrated business applications. However, to maximize the long term benefits from ERP implementations, organizations need to careful manage the post-implementation phase and focus on supporting end users to achieve better fit between their business processes and the ERP system features. This study develops a research model based on the resource-based view (RBV) of the firm and finds support for a positive and complementary relationship between continuous training resources, functional fit capability and business process success. An increase in continuous training resources increases the functional fit capability for the organization and is seen to improve business process success. The results support the need to focus on continuous end user training throughout the post implementation phase as a key contributor to ERP systems success for any organization.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Existing ERP literature is skewed towards the selection and implementation phases and not the post-implementation phases.
“reviews of previous studies by Hietala and Päivärinta (2021), Harun and Mansor (2019), Ghosh et al. (2013), and Cao et al. (2013) suggested that the existing ERP literature is skewed towards the selection and implementation phases and not the post-implementation phases of the ERP research.”
From ERP Post-Implementation Phase: Deployment of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model on User Acceptance (2023) · cites this paper as Ghosh et al. (2013)
Cites
Firm Resources and Sustained Competitive Advantage
Barney, J. (1991) · Journal of Management · doi:10.1177/014920639101700108 · Cited by 48,334 · see citing works
Enterprise resource planning: cultural fits and misfits: is ERP a universal solution?
Soh, C., Kien, S. S., & Tay-Yap, J. (2000) · Communications of the ACM · doi:10.1145/332051.332070 · Cited by 686 · see citing works
A Multi-Project Model of Key Factors Affecting Organizational Benefits from Enterprise Systems1
Seddon, P. B., Calvert, C., & Yang, S. (2010) · MIS Quarterly · doi:10.2307/20721429 · Cited by 211 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Mohamad Zain, M. R., Tajul Urus, S., Trinh, T., Amirul, S. M., & Tuan Mat, T. Z. (2023) · Asia-Pacific Management Accounting Journal · doi:10.24191/apmaj.v18i1-05 · Cited by 6 · see citing works
- Authors
- Ghosh, B., Yoon, T., & Fustos, J.
- Affiliations
- Metropolitan State University of Denver (US)
- Metropolitan State College of Denver, Denver, CO, USA
- Venue
- International Journal of Information Systems in the Service Sector
- Publisher
- IGI Global Scientific Publishing
- Published
- 2013-04-01
- Volume
- 5
- Issue
- 2
- Pages
- 30-45
- ISSN
- 1935-5688 (ISSN-L)
- 1935-5696
- OpenAlex
- W2025069241
- Cited by
- 8
- References
- 3
- Citations by year
- 2023: 2 · 2022: 2 · 2019: 1 · 2018: 3
- FWCI
- 0.00
- Type
- journal article
- Language
- ng
- Open access
- closed
- Locations
- International Journal of Information Systems in the Service Sector (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › ERP Systems Implementation and Impact
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Strategy and Management › Corporate Governance and Management
- Keywords
- enterprise resource planning, continuous training, functional fit, end-user training, resource-based view, ERP implementation success, SAP
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review