Bibliographic record
Abstract
Project-based working forms a major component of information technology (IT) activity in most companies, especially in relation to the design and implementation of new IT systems. Yet evidence suggests that many IT projects do not meet cost, schedule and functionality targets. This has significant negative implications for individual companies and for national economies. For example, Johnson [1] estimated that $81 billion was spent in the USA on IT projects that were abandoned before they were completed. Moreover, IT tools and techniques are seen to be central to the management of projects of all types across the diverse range of industrial sectors. Given this context, this minitrack will provide a forum for discussing advanced concepts, tools and techniques for managing projects (both IT and non-IT projects) in today’s dynamic business environments. We will explore the latest techniques for tracking and controlling projects, compressing time-to-market cycles, managing innovation under cost/ time pressures, managing diverse project teams in decentralized organizations, capturing and transferring knowledge and learning across projects, and dealing with interruptions, risks, conflict and commitment. We hope that the six papers in this minitrack will encourage and stimulate debate around this increasingly important topic of managing projects and contribute to both our conceptual and practical understanding. The six papers that will be presented at this session are as follows: Controlling Iterative Software Development Projects: The Challenge of Stakeholder and Technical Integration by Bendik Bygstad, from Norway. Reducing the Technical Complexity and Business Risk of Major System Upgrades, by Alan Thorogood and Philip Yetton, from, Australia. SMP: A Process-Driven Approach to Project Management by Marc Frappier, and Mario Richard, from Canada. Managing the tension in IS projects: balancing alignment, engagement, perspective and imagination, by Kevin Gallagher , Robert M. Mason, and Betty Vandenbosch , from the USA. Criteria for Project Assignments in Multiple-Project Environments by Peerasit Patanakul, Dragan Z. Milosevic and Timothy R. Anderson, from the USA. And finally, Process Ownership Challenges in IT-Enabled Transformation of Interorganizational Business Processes, by Michael Holm Larsen and Ralf Klischewski, from Denmark and Germany. We hope that this very international mix of papers will promote some really interesting discussion over the two sessions.
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 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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 teacher head, 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".