标题： 将智能调查与传统调查相结合 显示英文标题

标题： Integrating smart surveys with traditional surveys

摘要： 智能调查是利用传感器和机器智能来减少受访者负担并提高数据质量的调查。 智能调查已被测试作为一种改进官方统计中的日记调查的方法，其中数据是在诸如出行、时间使用和家庭支出等主题上收集的。 智能调查与传统日记之间在测量和表示方面往往存在固有差异，这使得在生成统计数据时难以整合这两种数据源，或者在混合或多源环境中整合。 本文区分了两种不同的整合方法：混合模式方法，它优先考虑结果对齐，并最小化测量差异以便于数据直接合并；多源方法，它保持固有的模式差异，并在建模阶段整合数据，从而利用每个来源的优势。 以出行调查为例，我们探讨了每种方法的优缺点，并提出了一个决策框架，以指导研究人员选择适当的整合策略。 显示英文摘要

摘要： Smart surveys are surveys that make use of sensors and machine intelligence to reduce respondent burden and increase data quality. Smart surveys have been tests as a way to improve diary surveys in official statistics, where data are collected on topics such as travel, time use and household expenditures. There are often inherent differences both in measurement and representation between smart surveys and traditional diaries, which makes it difficult to integrate both data sources in producing statistics over time, or within a mixed- or multi-source context. This paper distinguishes two different approaches to integration: the mixed-mode approach, which prioritizes outcome alignment and minimizes measurement differences for straightforward data merging, and the multisource approach, which maintains inherent mode differences and integrates data at the modeling stage, allowing exploitation of the strengths of each source. Using travel surveys as an illustrative example, we explore the benefits and drawbacks of each approach, and propose a decision framework to guide researchers in selecting the appropriate integration strategy.