Abstract
Běihuá Bank, a mid‑sized regional lender in China's Heilongjiang Province, is under competitive pressure from fintech disruptors and foreign banks offering advanced digital services. The back has already lost 12 percent of its 18 to 25 year old clients to a popular local super-app. In response, Bēihuá plans a digital overhaul anchored by a province-wide customer survey. The survey design and vendor selection must balance cost, data quality, reputation, geographic coverage, and timing. The customer survey would ensure that before committing tens of millions of yuan to new digital features, the bank understands granular nuances in customer priorities and expectations. This case invites students to (i) formulate and solve linear‑programming models that minimise survey cost while satisfying stringent demographic and regional quotas, and (ii) apply multi‑criteria decision analysis to choose among competing research vendors to address other constraint criteria such as data quality, reputation, and time. The dual quantitative frameworks foster discussion of trade‑offs, managerial judgement, and strategy execution in digital banking.