Strategic Transformation of Ford Motor Company
Bibliographic record
Abstract
Executive Summary New Mobility is a relatively new term used to represent an exciting and imminent reality. Our individual and societal transportation needs are complex and rapidly-evolving, while being shaped, constrained, transformed, and defined by a host of global pressures and trends. Within this context, New Mobility offers a fresh understanding of how we can meet transportation needs for both people and goods through an integrated network of products, services, and information technology. As the concept of New Mobility begins to take root, certain human-induced trends are putting unprecedented pressures on our global society. “Megatrends” such as climate change, increasing social disparity, shifting demographics, urbanization, and congestion are affecting the rate and degree to which populations, regions, and economies can grow and prosper. This project builds on the work of previous groups, including the Canadian think-tank Moving the Economyi and a group of three University of Michigan graduate students who, in 2005, produced a report for Ford Motor Company entitled New Mobility: Future Opportunities for Ford as a Mobility Integrator. Our team consists of eight MS students at the School of Natural Resources and Environment at the University of Michigan. Through a combination of primary and secondary research, we surveyed the current and future potential for New Mobility products, services, and technologies in five global cities, vis-à-vis the growing urgency of addressing the aforementioned megatrends. Our results from each city combined a conventional Market Attractiveness Analysis with a progressive New Mobility Market Analysis. We then overlaid these results with Ford’s specific strengths, core competencies, and leadership potential in each of the five cities. In so doing, we have created a novel new approach to business project evaluation. Our results indicate that Bangalore, India is the most attractive New Mobility market, due not only to the overall market size, but also to the transportation infrastructure gap which is rapidly emerging as Megatrend pressures intensify. However, our Discussion & Analysis section identifies a number of other key factors for Ford to consider when selecting how, when, and why to assume a leadership role in the New Mobility Market.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.000 |
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".