WaterHealth International in India: crafting sustainable solutions for potable water
Bibliographic record
Abstract
Synopsis The case features WaterHealth International India (WHIN) – a subsidiary of WaterHealth International (WHI) Inc. WHIN was launched in 2006 with the vision to “be the leader in providing scalable, safe, and affordable water solutions to underserved populations through an innovative business model.” The company incorporated a Build-Operate-Transfer model with decentralized production and distribution. Following a successful pilot project, WHIN installed its WaterHealth Centers in 175 sites throughout rural India by 2009, and attracted a $15 million investment from the International Finance Corporation to further expand its operations in India. Mr Vikas Shah, the Chief Operating Officer of the company, is faced with the issue of assessing scalability and sustainability of the company's business model. He needs to examine and evaluate the company's value proposition, resources and capabilities, and decide how to generate economic value while maintaining a focus on its social vision. The latter entails an ability to create shared value for stakeholders as an important contributor toward the company's sustainability. Additionally, Mr Shah is evaluating alternative public-private partnerships in terms of their suitability for the Indian context and viability to drive profitability. Research methodology The case uses primary and secondary data, i.e. interviews with company representatives, company reports, presentations, and consulting papers. Relevant courses and levels The case is written for graduate (and advanced undergraduate) students that enroll in classes with a focus on emerging markets, sustainability, innovation, and entrepreneurship. Examples are courses in Entrepreneurship and Innovation (especially those that include one or more sessions on the social dimensions) as well as those in Inclusive Growth and Sustainable Development.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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 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".