Year: 2024
Type: article
Abstract: In the realm of web-based surveys, ensuring the quality of responses is a crucial yet challenging task. This study addresses the issue of detecting poor responses, particularly focusing on the phenomenon of ‘satisficing’ - a situation where respondents provide minimal effort responses. Traditional methods such as the Instructional Manipulation Check (IMC) and Directed Question Scale (DQS) have been commonly employed to tackle this issue. However, their effectiveness is often limited due to various constraints. This paper introduces a theoretical framework and a generalized model for the design of questionnaires. This framework aims to improve the detection of poor responses, thus enhancing the reliability and validity of survey data. Through numerical experiments, the paper demonstrates the applicability and effectiveness of the proposed model. The study’s approach is based on a thorough analysis of response patterns and the integration of quality control questions within the survey structure. The findings of this research have significant implications for the field of survey methodology, providing a more robust and systematic way of ensuring data integrity in web-based surveys.
Authors: Tota SUKO, Manabu KOBAYASHI
Institution: Waseda University
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: bronze
Awards: Development and Systematization of Data Analysis Methods Considering Data Quality Issues, データ駆動型企業システム実現のための大規模ログと実験データの活用分析基盤の構築, Development and empirical evaluation of next-generation experimental design technology for the foundation of data-driven society, Research on Data Analysis Platform for Business Value Creation and Time-Varying Collaborative Filtering, ビジネス施策を正しく評価するための潜在構造に基づく協調フィルタリングに関する研究
OpenAlex ID: W4401599234