Between Acquiescence and Manipulation: IS Project Managers Responses to Institutionalized Practices
Bibliographic record
Abstract
A number of information systems (IS) project management practices can now be considered institutionalized. While traditional institutional approaches assume that actors – in search of legitimacy - passively adopt such practices, others posit that there is a broad range of responses to institutional pressures. These responses vary from acquiescence to manipulation, including compromise and defiance. Our study adopted this perspective to examine IS project managers’ responses to institutionalized practices. The study addressed the following questions: Are IS project managers institutional actors who unquestioningly adopt institutionalized practices or do they consciously comply? Or else, do they adopt avoidance or defiance strategies? We conducted a multi-method study to address these questions. First we conducted a field study during which we interviewed 46 IS project managers after which we conducted two case studies. We offer the following contributions. From an empirical point of view, the study reveals how IS project managers may apprehend project management practices that they are presented as being norms. The study also has a theoretical contribution, in that it combines and enriches extant frameworks pertaining to actors’ responses to institutional pressures; these strategies are contrasted with the notion of mindfulness. From a practical point of view, our results can help organizations better understand how IS project managers may apprehend institutionalized practices. The originality of our approach consists in the operationalization of Oliver’s (1991) famous framework in an IS context.
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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 | 0.021 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".