Smart Survey Implementation Workpackage 2: Research Methodology Deliverable M6: review stage

Abstract

Smart surveys combine traditional survey questions with sensor-based data from smartphones, wearables, and other devices. By leveraging modern technology, these surveys can improve data quality, reduce participant burden, and yield more timely and granular insights. This deliverable reports on the first stage of the Smart Survey Implementation (SSI) project, whose overarching aim is to develop an end-to-end research methodology for smart surveys. Focusing on European Time Use Surveys (TUS) and Household Budget Surveys (HBS), it identifies knowledge gaps in the existing literature and outlines how the project will address them in subsequent stages. The deliverable centers on four key challenges that hinder large-scale adoption of smart surveys: (1) recruiting and retaining diverse participants (including difficult-to-reach groups), (2) using machine learning to enhance human-computer interaction, (3) ensuring strong usability and user experience, and (4) integrating smart survey data with conventional surveys while controlling for mode effects. Drawing on previous ESSNET projects and broader international research, each chapter examines these challenges in detail and describes planned field tests and randomized controlled trials. The ultimate goal is to evaluate best practices and design trade-offs across multiple countries, thereby providing a robust methodology and concrete recommendations for implementing smart surveys in official European statistics.