Multi-attribute consumer choice and decision conflict: A process tracing study

Abstract

Decision making has been studied throughout decades and even centuries, and along that journey, also the research methods to study it have been developing. A few of the current popular methods include eye-tracking and mouse movement tracking. However, both of these entail some limitations or impracticalities that make the method inflexible and/or expensive. Therefore, room for new methods exist. Especially tracing scrolling movements instead of mouse movements, as was tested in this research, could be an interesting direction for process tracing in order for the field to stay current in today’s age of mobile online shopping.

In this thesis, a quantitative empirical study was done with an open-source platform oTree that was used to create a browser-based survey that utilizes the same idea behind it as eye- and mouse-tracking methods do. The survey used shoes as an example of a consumer good and asked the respondent to state their preferences towards each shoe and then make binary choices between them. Multi-Attribute Utility Theory was used as a foundation to the study as the research aims to measure the effect of the chosen attributes (style, price and category) and the level of decision conflict. However, the main goal of the study was to test how well the chosen research method performs in this context of consumer decision process tracing. That being said, the current research should be considered as a pilot for the used research method and its results as exploratory in nature.

In the data analysis, the interest was especially on decision conflict and how that can be measured and visualized, for example, through response time and motor responses. The data collected from the survey was able to show that whenever the options differed more on the respondent’s subjective preference, the response time decreased, suggesting that there was less conflict in the decision process. Similarly, a Polygon area variable that measured the respondent’s scrolling movement between the options, decreased during decision tasks where the preference difference was bigger. It was also found that preference difference rating affected the proportion of responses that chose the shoe that was preferred more. The method was also found applicable for the current research setting and could definitely provide great possibilities for future research.