Article: Social network of confident attitudes with response time testing Journal: International Journal of Applied Management Science (IJAMS) 2024 Vol.16 No.5 pp.1 - 31 Abstract: Data constitutes the foundation of scientific research. The selected methodology of data collection defines its quality and research quality. In quantitative surveys and Social Network Analysis (SNA), data quality discussions strongly focus on declarative bias. Data quality would significantly improve if strong attitudes could be distinguished from the low ones since the former are more likely to be reliable and reflect individuals' social perceptions. The current paper measures attitudes with Response Time Testing (RTT). This methodology allows the identification of highly confident data by assessing the calibrated speed of a response. Simultaneously, RTT delivers in parallel classical declaration-based answers because, to the respondent, they are just like any other questionnaire. The difference between both approaches (classical and RTT) is analysed in two networks of similarity of attitudes towards COVID-19. The results show significant differences when only responses that show a high attitude accessibility are kept. Quadratic Assignment Procedure (QAP) and <em>T</em>-tests show that highly confident responses provide a significantly less cohesive network than when all the declaration-based answers are considered for analysis. Inderscience Publishers - linking academia, business and industry through research

Title: Social network of confident attitudes with response time testing

Authors: Guillaume P. Fernandez; Bart F. Norré; Dorota Reykowska; Kirti Dutta; Mai Nguyen-Phuong-Mai; Joaquin Fernandez; Rafal Ohme

Addresses: JFE Études de Marché and Marketing Intelligence, University of Geneva, Geneva, Switzerland ' School of Management Fribourg, University of Applied Sciences of Western Switzerland, Sierre, Switzerland ' NEUROHM, Warsaw, Poland ' Faculty of Commerce & Management, SGT University, Gurgaon, Haryana, India ' Organisational Neuroscience, Amsterdam School of International Business (AMSIB), Amsterdam, Netherlands ' JFE Études de Marché and Marketing Intelligence, Geneva, Switzerland ' WSB University, Torun, Poland

Abstract: Data constitutes the foundation of scientific research. The selected methodology of data collection defines its quality and research quality. In quantitative surveys and Social Network Analysis (SNA), data quality discussions strongly focus on declarative bias. Data quality would significantly improve if strong attitudes could be distinguished from the low ones since the former are more likely to be reliable and reflect individuals' social perceptions. The current paper measures attitudes with Response Time Testing (RTT). This methodology allows the identification of highly confident data by assessing the calibrated speed of a response. Simultaneously, RTT delivers in parallel classical declaration-based answers because, to the respondent, they are just like any other questionnaire. The difference between both approaches (classical and RTT) is analysed in two networks of similarity of attitudes towards COVID-19. The results show significant differences when only responses that show a high attitude accessibility are kept. Quadratic Assignment Procedure (QAP) and T-tests show that highly confident responses provide a significantly less cohesive network than when all the declaration-based answers are considered for analysis.

Keywords: response time testing; social network; declarative bias; attitude; confidence; data quality.

DOI: 10.1504/IJAMS.2024.144419

International Journal of Applied Management Science, 2024 Vol.16 No.5, pp.1 - 31

Received: 02 Jun 2024
Accepted: 11 Oct 2024
Published online: 12 Feb 2025 *

Title: Social network of confident attitudes with response time testing

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