Using q methodology to test perspectives and attitudes: Experiences from a study about content marketing

Abstract

This paper is intended to propose the use of Q methodology in more business and management studies to complement existing business methodologies and will explain the different steps of a typical Q study with examples from a study on content marketing. It will be argued that this methodology is best suited to clarify and depict the scope of different viewpoints about a topic and hence provides numerous opportunities to researchers. Q methodology was introduced more than 80 years ago by psychologist William Stephenson to study human subjectivity but presently researchers do not sufficiently adopt this methodology to study perceptions and attitudes about business and management topics. For example, this mixed method has not become a common business and management method yet despite mounting scholarly work in various disciplines over the years which could perhaps be ascribed to the complexity of this method. In addition to illustrating how Q methodology could be used to test perspectives and attitudes, it will be argued in this paper why and how Q methodology can be a valuable business and management research tool to reveal individuals' subjectivity about a topic. The adoption of Q methodology could enhance conventional research methods such as surveys, interviews and focus groups. Since Q methodology uses the strengths of both qualitative and quantitative methods to study the subjective perspectives of participants, it becomes possible to gain insight in a much richer way than with a survey or interviews because it combines a robust qualitative element with the quantitative tool. The qualitative part categorises the variety and span of subjective opinions on the topic, while the quantitative part objectively confirms and analyses similarities and differences in the subjective viewpoints of individuals by means of a Q factor analysis. It is thus an exploratory, inductive and deductive methodology suitable for small populations of participants; strengthened by the statistical operation of Q factor analysis. However, there are also several limitations to using Q methodology which are highlighted with examples.