Implementation of Configurable Information Systems: Negotiations between Global Principles and Local Contexts
Bibliographic record
Abstract
Among the new forms of technology that overwhelm information systems research and practice, configurable information systems refers to technologies that are built up from a range of components to meet the very specific requirements of a particular client organization. Software packages like enterprise resources planning (ERP) are good illustrations of configurable IS because they typically provide hundreds, or even thousands, of discrete features and data items that can be combined in multiple ways. They cannot be seen independently from their representations through external intermediaries (mediators), who “speak” for the technology by providing images, descriptions, policies, templates and, very often, solutions. From a critical-interpretive view, this paper proposes a new way of understanding the implementation of configurable solutions. Using seven retrospective case studies, we investigate the relationship built by clients and consultants during the configurational process, where visions of how the technology should operate are negotiated. Different degrees of dependencies are mutually constructed, maintained, and transformed in the long run, influencing the global- local negotiation and the project results. The main contribution of this research is (1) to recognize different patterns of mediation, i.e., different types of client-consultant relationships, and the different types of trajectories in terms of global-local negotiation these patterns are likely to produce; (2) to address how initial organizational decisions in terms of power and knowledge distribution between clients and consultants influence the negotiation between global principles and local contexts; and (3) to identify mediating strategies that may help organizations improve global-local negotiations and, hopefully, improve the benefit of embarking on such costly and risky projects.
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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 | 0.022 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.018 | 0.016 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".