Q or R Factor Analysis for Subjectiveness Measurement in Consumer Behavior? A Study Case on Durable Goods Buying Behavior in Romania

Abstract

The complexity of consumer behavior requires new research methods to overcome the limitations of conventional evident-based research. The aim of this paper is the comparison between two types of factor analyses, Q and R (PCA and cluster analysis) for subjectiveness measurement in the case of durable goods buying behavior in Romanian households with different levels of education and occupancy. Our study explores different subjective patterns of stimulus of 30 statements (Q-sample) by 30 Romanian households (P-sample) using the Q-sort method for collecting data. For the Q-sample inputs, results from the literature were used. Based on the 30 Q-sorts, we discovered four factors for both Q and R factor analysis, mostly different according to specific results from different methods. For the Q method, we used the labels “pragmatic”, “modern”, “traditionalist”, and “innovator. For R factor analysis and cluster, we used “traditional Romanian brands”, “real needs and power purchasing”, “sceptic versus optimistic subjectiveness”, and “negative subjectiveness”. This paper suggests the Q methodology as a structured and transparent approach to consumer behavior research by combining the in-depth subjectivity of qualitative methods and statistical rigor of factor analysis to identify groups in consumers. The research provides useful suggestions for selecting and approaching target consumer segments in the Romanian durable goods industry.

The Impact of Air Quality on the Tourism Industry: Measuring Stakeholder Subjectivity in Mures Country Using the Q Methodology

“…Q methodology is a relatively recent tool in this field but has been widely recognized for its profound applications in areas where the psychometric understanding of individuals has significant implications. The results provided by this methodology are considered superior to other much-known and easier-to-use methods (Gabor & Cristache, 2021).…”

Coach leadership in a crisis context: Investigating effective coach behaviors during the COVID-19 pandemic with a process view

“…All interviews were transcribed into 60 double-space pages of Microsoft Word files. Regarding the number of statements (Q samples), we were guided by Militello and Benham ’s ( 2010 ; Q sample = 33) published research in Leadership Quarterly and Gabor and Cristache (2021 ; Q sample = 30) published research in Mathematics . A total of 34 statements were extracted and categorized as pre, during and post-crisis themes.…”

“…An extensive person sample of 30–50 participants in the Q methodology is sufficient ( McKeown and Thomas, 2013 ; Gabor and Cristache, 2021 ). Under the condition that the diversity of opinions is ensured, the Q method perfectly achieves the goal using a small number of samples ( Militello and Benham, 2010 ; McKeown and Thomas, 2013 ; Gabor and Cristache, 2021 ). The selection of participants needs to be careful and to bring more subjectivity.…”

“…Q methodology used centroid analysis to find correlation matrixes among the 32 Q-sorts, and Varimax rotation was applied to maximize the variance of the extracted patterns ( Watts and Stenner, 2012 ; Gabor and Cristache, 2021 ). Six patterns with an eigenvalue greater than one ( Watts and Stenner, 2012 ; Gabor and Cristache, 2021 ) were extracted and rotated, which explained a total of 49% of the study variance. All patterns’ composite fidelity meets the cut-off of 0.8 for explaining purpose ( Gabor and Cristache, 2021 ).…”

“…Six patterns with an eigenvalue greater than one ( Watts and Stenner, 2012 ; Gabor and Cristache, 2021 ) were extracted and rotated, which explained a total of 49% of the study variance. All patterns’ composite fidelity meets the cut-off of 0.8 for explaining purpose ( Gabor and Cristache, 2021 ). Each patterns implied a group of participants who shared similar opinions about the topic ( Watts and Stenner, 2012 ).…”