A growing body of literature spanning the social, psychological, and neurological sciences is studying the influence of affect (emotions, feelings and moods) within a variety of decision-making contexts. Accounting Information Systems (AIS) researchers interested in capturing affect within such contexts ought to consider methods that are designed to capture affect close to its realization. One such approach is the experience sampling method (ESM), developed as a way to collect individuals' subjective perceptions of their cognitions, motivations and affect as they become manifest. In short, ESM involves capturing brief responses from individuals throughout the day over the course of weeks or even months. By doing so, researchers can strengthen internal validity weaknesses associated with surveys and interviews, and increase ecological validity beyond laboratory experiments. ESM data is rich with possibilities for within- and between-participant comparisons. However, conducting an ESM study is much more intense and time-consuming than a one-time survey. In this paper, we discuss the concept of ESM, explain how and it can be used for studying affect, explore various theoretical considerations, and mention some key implementation issues. Our objective is to highlight the ESM and offer directions for AIS researchers interested in evaluating the suitability of the ESM method for their research programs.
Prompted by a growing body of evidence from psychology and neuroscience (Damasio, 1994, Russell, 2003, Lerner and Keltner, 2000, Clore and Huntsinger, 2007 and Sanfey et al., 2003), the role of emotions, feelings and moods (herein collectively referred to as affect) in understanding and predicting human behavior appears to be quite powerful. Interest in this burgeoning area of inquiry is also spilling over into information systems (IS) and accounting research. IS scholars are recognizing the need to better understand technology acceptance, adaptation and continuance models through the incorporation of affect related variables ( Zhang, 2009, Ortiz de Guinea and Markus, 2009, Kim et al., 2007 and Sun and Zhang, 2006). In accounting, research has begun to focus on the influence of affect within relevant decision-making contexts ( Bhattacharjee and Moreno, 2002, Moreno et al., 2002 and Chung et al., 2008). This expanding stream of research should be on the radar scope of accounting information systems (AIS) researchers who sit at the intersection of both disciplines, as gaining deeper insight into how and why affect influences the behavior of system developers, users and evaluators can lead to richer development of AIS theory.
The major problem with conducting research in this area is the difficulty in capturing affect coincident with related behavior. This is particularly thorny because affect is ephemeral and, for the most part, unobservable outside the mind of the beholder. Aside from neuroimaging, one of the most reliable methods of measuring affect is known as the experience sampling method (ESM) (Csikszentmihalyi and Larson, 1987 and Csikszentmihalyi et al., 1977). However, the benefits of ESM must be tempered with potential challenges involved with implementing the method. This research note describes the ESM as a potentially effective way of capturing affect data for AIS researchers.
The remainder of this paper is organized as follows: First, we provide an overview of the ESM procedure and explain why it can be beneficial for studying affect; next, we direct our attention to some theoretical considerations associated with using ESM; subsequently, we examine data collection challenges; finally, we mention some potential research topics in AIS for which ESM might be helpful.
“Affect and emotion are pervasive influences on human judgment and thought,” (Clore and Huntsinger, 2007, p. 397) and “feelings are an indispensable part of people's individual and organizational lives” (Seo and Barrett, 2007, p. 936). Given the rising interest in affect research in psychology, neuroscience, and other business related social sciences (e.g., marketing and information systems), we expect to see further development of research models and future conduct of empirical studies within IS, accounting, and AIS that draw upon this line of thinking. The challenge we have raised in this research note is that traditional methods of capturing the affect of research participants can be fraught with distortion and biases. ESM provides a mechanism to tap into the everyday lives of participants in a way that holds stronger internal validity than retrospective surveys, interviews or real-time observation, and greater external validity than laboratory experiments or fMRI studies. At the same time, we agree with Hektner et al. that, “ESM research requires a substantial investment of time and resources on the part of researchers and participants, and we urge those who consider the method to carefully determine the utility of the method for your particular research question” (2007, p. 32).
