Social and Cultural Challenges in ERP Implementation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper studies the differential practices of change management in organizations of western origin and compares it with the best practices prevalent in Indian organizations, with special emphasis on social and cultural challenges faced in these countries. Since Enterprise Resource Planning (ERP), as part of an information and communication technology (ICT) initiative, is frequently associated with organization change and transformation in relation to its adaptation, it has been used as the context in this study. The impact of social factors and cultural challenges on change management processes and elements are compared and contrasted using multiple case studies from USA, Canada, European (Western/Eastern) and Indian organizations who have adopted ERP technologies. The conceptual framework highlights cultural and social factors that affect ERP implementation, and offers suggestions to researchers to empirically test these influences using sophisticated analytical methods and develop change strategies and practices in response to these challenges. Further, it also draws attention to the need for a contemporary, result-oriented, quantitatively measurable framework of change management at the individual and enterprise levels. It is expected that such an approach would result in better buy-in from all stakeholders in terms of increased accountability.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it