Research-Grade XLSForms, Ready for Deployment.

'- Multi-member tracking allows member-level HFIAS scoring - Frequency-based responses provide more granular data - Household HFIAS score is automatically calculated for analysis - Ready for comparisons across households, schools, and restaurants

'- Actor classification: Identifies respondent category (importer/exporter/economist/trader) - Years of experience: Supports correlation between experience and hedging literacy - Self-scored literacy: Respondents evaluate their own market understanding - Multi-commodity repeat group: Allows per-commodity knowledge and hedging analysis - Hedging tool selection: Captures futures, options, swaps, and forwards - Usage frequency: Measures how often hedging is practiced

'- Multiple barriers per exporter using repeat group - Severity rating and frequency captured per barrier - Conditional subtype details for certification and customs barriers - Optional additional comments for qualitative context - Aggregated structure ready for basic analytics and reporting

'- Target users: Government Agencies, Hospital Administrators, Procurement Officers - Simple design: Minimal fields for rapid data collection - Road coverage: Focus on last-mile feeder roads during rainy season - Key checks: Road condition, passability, maintenance needs - Global applicability: Includes international country and region options - Notes field: Allows qualitative observations per road

- Target Users Included: Importers, Exporters, Economists, Commodity Traders - Purpose: Assess fairness and transparency of grower-buyer contract dispute mechanisms - Key Focus Areas: Dispute types, resolution mechanisms, fairness perceptions - Analysis Capability: Supports comparisons by user category and satisfaction scoring - Sensitivity Level: Medium — includes business practices but no personal data - Optional Logic: Dispute questions become relevant once engaged_contracts = yes

- Target users: Veterinarians, Quality Auditors, Lab Technicians - Multi-batch repeat group: Allows multiple batches per supplier - Fraud risk scoring: Each detected issue contributes 1 point (0-3) - Conditional follow-ups: Triggered if risk score ‚> 2 - Product metadata: Tracks product type, batch ID, inspection date, testing conducted - Key checks: Adulteration, dilution, mislabeling, lab testing

- 1. Declared Preference vs Blind Preference - Compare perceived vs actual favorite brand - Useful for bias detection - 2. Attribute Scoring - Numeric (1-5) scores for: - Taste

'- Farmer and Field Identification: Captures farmer details, GPS location, field ID, size, and crop type to link labor data to specific fields. - Seasonal Labor Tracking: Records labor details by season or crop activity, allowing comparison across different periods. - Labor Type and Workforce Size Monitoring: Collects type of labor used and number of workers to understand labor composition and availability. - Wage and Payment Structure Documentation: Tracks daily wage rates and payment types to analyze labor costs and compensation practices. - Labor Shortage Reporting: Identifies whether labor shortages occurred and captures reasons when shortages are reported. - Automatic Labor Severity Classification: Calculates labor shortage severity (Low, Medium, High) based on workforce size and reported shortages to support decision-making.

'- Survey Metadata: Captures survey start/end times, device ID, and enumerator name for audit tracking - Farmer Registration: Records farmer identification, name, and GPS coordinates for comprehensive farmer profiling - Production Tracking: Documents crop type, field size in hectares, planting date, and total production in kilograms - Cost Breakdown: Itemizes all production costs including seeds, fertilizer, chemicals, labor, machinery, transport, and other expenses - Revenue Calculation: Automatically computes total revenue based on selling price per kg and total production volume - Profitability Analysis: Calculates profit, profit margin percentage, and classifies into Loss, Low, Medium, or High Profit categories

'- Target users: Veterinarians, Quality Auditors, Lab Technicians - Simple design: Minimal fields for rapid data collection - Farm coverage: Poultry, Livestock, Mixed farms - Key protocols: Visitor restrictions, sanitation baths, protective clothing - Global applicability: Includes international country options - Analysis-ready: Structured for basic frequency tables and pivot analysis

'- Captures waste/by-product generation across the supply chain - Identifies opportunities to reuse or transform waste - Allows qualitative notes for potential circular economy initiatives

'- Input Validation: Strict constraints on age (6-59m), height, and weight to prevent data entry errors in the field. - Anthropometric Repeat: Dynamic repeat group allows for multiple children per household to be recorded efficiently. - Recall Logic: Structured mortality section designed to capture crude death rate (CDR) baseline data. - Optimized Analysis: Standardized snake_case naming conventions and numeric coding for sex/symptoms to facilitate direct import into ENA for SMART software. - Skip Patterns: Relevance logic ensures morbidity symptoms are only asked if the child was reported sick.