Dynamiques de conception, de mise en oeuvre et de création de la valeur publique des projets de smart territoires - Etude qualitative dans 37 territoires français.
Bibliographic record
Abstract
Faced with growing global instability, local and regional authorities are looking for solutions to reconcile economic growth and regional development, while meeting the challenges of energy transition and social inclusion. Smart cities are emerging as a strategic response, using digital technologies and infrastructures to optimize urban and regional management and citizens’ quality of life. These initiatives aim to make the management of communities more efficient, transparent and responsive, but also raise questions about the measurement of the tangible and intangible benefits they generate. This thesis examines how smart city projects contribute to the creation of public value, by assessing their impact on operational efficiency, citizen participation and environmental sustainability. It explores the conditions under which these projects contribute to the creation of public value. Focusing on the integration of digital technologies and infrastructures in territorial management, this study is structured around three main questions. The first aims to draw up a profile of the types of smart city projects that are emerging in the field. It also explores the role of contingency factors in the design and implementation of smart city projects. The second question examines the role of the main players involved, particularly citizens, and their integration into these projects, and identifies the factors that act as levers and/or barriers to the involvement of citizens-residents-users. Finally, the third question focuses on the practices of public organizations that make a significant contribution to the creation of this value, drawing on public value theory and work on open governance and e-government. The methodology adopted combines a bibliometric literature review and a systematic review, which have enabled us to deepen our understanding of the smart city concept in the literature and in practice in the territories adopting these initiatives. An empirical study was also undertaken through 46 interviews with managers from 37 French territories, analyzed using NVIVO 14 software. This research makes significant contributions to understanding the complex dynamics of smart cities, highlighting how these integrated urban initiatives use digital technologies and infrastructures to transform territories. This research enriches the theory of public value and proposes concrete practices for public managers. These results offer practical perspectives that can help create public value in territories developing these initiatives in the French context.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".