Critical success factors in enterprise resource planning implementation
Bibliographic record
Abstract
Purpose – The purpose of this paper is to consolidate the critical success factors (CSFs) as published in enterprise resource planning (ERP) implementation case studies. The authors perform the analysis and propose the final CSFs based on the reported ERP implementation process stages. Design/methodology/approach – The paper follows the eight category coding steps proposed by Carley (1993) and utilizes only ERP implementation case studies to identify a distinct set of critical success factors. The 37 case studies used in this paper provide a reasonable sample from different countries and contexts. Two methodologies were followed, one for the literature review process and the other for the analysis and synthesis. Findings – Out of 64 reported CSFs that were extracted from the literature and subsequent detailed analysis and synthesis the authors found a total of 22 factors that are distinct. These factors which encompass change management, are proposed with five ERP implementation stages. Research limitations/implications – The final set of success factors proposed in this study gives a consolidated and unified view of the significant variables to be considered during all the stages of ERP implementation. The research is limited to case study literature and does not account for ERP implementation models and frameworks. Another limitation would be the scope of the literature searched which is that of the Management Information Community. Practical implications – The proposed CSFs can be used by practitioners in five ways: assess implementation of an ERP; ex-ante assessment; comparative analysis with other implementation experiences; utilize CSFs from model as part of key performance indicators; and utilize the model to establish a concise strategy to project management process for the ERP implementation. Social implications – ERP implementation is complex. The promise has not yet been fully realized. An ERP-enabled organization entails primarily strategy and change management. To that effect, all stakeholders are impacted by ERP implementation. This paper, identified CSFs extracted from cases of ERP implementation and proposes a model to support its project management, user satisfaction and sustainability. The results aim at reducing costs, maintaining timeline, reducing employee anxieties and with a successful implementation, better service to customer base. Originality/value – This paper is the first attempt to present a consolidated list of CSFs and mapping them to the stages of an ERP implementation as reported from the industry. It originality is its focus on utilizing rigorous published case studies with the hope that future case studies would utilize the work to report on the same factors. The value is that as the case studies are increased, comparison and differentiation between is enhanced.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".