Geography and Strategy in Developing Countries
Bibliographic record
Abstract
Geography plays a central role in firms’ strategic choices. Deciding where to locate operations and employees, as well as whether to move or not, can have critical performance implications. At the same time, a growing literature in strategy shows that conditions in developing economies often necessitate different firm strategies. This raises an important question at the intersection of these literatures: how do choices about geography shape firm strategy in developing economies? In this symposium, we explore this new area of research through a set of cutting edge studies, each of which examines a different way in which geography and firm strategy interact in developing economies. Our discussant, Professor Lamar Pierce, will build on these presentations and his own expertise on firm strategy in Africa to synthesize and critique the studies. Following this, the host will encourage a lively debate about how geography matters for strategy and organization theory in developing economies. Location, Gendered Constraints and Business Performance Presenter: Solene Delecourt; Haas School of Business, UC Berkeley Employee Work Novelty and Communication in a Hybrid Remote Workplace Presenter: Tarun Khanna; Harvard U. Presenter: Kyle Schirmann; Harvard Business School Presenter: Christos Makridis; MIT Sloan School of Management The Impact of Capital Constraints on Strategic Misconduct Presenter: Fulton C. Eaglin; Harvard Business School Won’t you be my neighbor? Geography, networking, and entrepreneur performance in Togo Presenter: Stefan Dimitriadis; U. of Toronto, Rotman School of Management Presenter: Rembrand Michael Koning; Harvard Business School
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 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".