International Choice Modelling Conference, International Choice Modelling Conference 2015

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The influence of time of day on decision fatigue in stated choice experiments
Søren Bøye Olsen

Last modified: 11 May 2015


It is well-known from social and consumer psychology that making choices requires a cognitive effort. Since cognitive capacity is limited, making choices may thus lead to decision fatigue. More specifically, Baumeister (1998) relates decision making to self-control[1] since both involve the use of a limited resource, namely the human body’s mental energy. Along these lines, Muraven and Baumeister (2000) suggest that self-control is a renewable limited resource, analogous to a muscle; when depleted of energy it becomes tired and needs to relax and replenish itself. However, the depletion of energy can be reversed as suggested by Gailliot et al. (2007) and Masicampo and Baumeister (2008), by replenishing glucose in the blood, i.e. the main source of energy for the brain. In the SCE literature, decision fatigue has mainly been linked to the design dimensions of the SCE itself and particularly to the number of choice tasks presented to a respondent. Applying the relation between decision making and self-control put forth by Baumeister (1998), we hypothesize that decision fatigue in SCE can also be caused by depletion of mental energy and low levels of blood glucose (Baumeister and Tierney 2011) and not only confined to the SCE context itself, but also as a consequence of the time of day that respondents answer the SCE questionnaire. In this case, the time of day when the questionnaire is answered might be crucial to consider, since respondents could be in a situation with either low or high mental energy, i.e. blood sugar levels, depending on how many other cognitively demanding decisions they have already been required to make since they woke up in the morning and how long it has been since their last meal. Ultimately, this could affect the decision making process of the individual and thus the elicited preferences in a SCE survey.

The potential impact of time of day would seem particularly relevant when using survey modes that leave it up to the respondents to decide what time of day to answer the questionnaire. When interviewing respondents using postal paper-and-pen questionnaires or web-based online questionnaires, it is essentially up to the individual respondent to decide when to answer. Compared to face-to-face and telephone survey modes where the analyst (at least to a much greater extent) can decide when to conduct interviews, this represents a loss of control to the analyst. This would be important if responses are indeed affected by the time of day they are obtained. Particularly in the light of the recent years’ surge of online surveys (Olsen 2011), this would seem to warrant an investigation. While this loss of control may be inevitable when using postal paper-and-pen questionnaires, online surveys offer an opportunity to at least control for the time of day. When conducting interviews online, client-side paradata such as timestamps, keystrokes, mouse clicks and answer-changes can be easily and unobtrusively collected with no additional effort required of the respondent (Olson and Parkhurst 2013). Timestamps indicating the time of day that each survey response is obtained are typically collected, and such data offer an opportunity to test and control for time of day related decision fatigue.

It is against this backdrop that we suspect effects of decision fatigue in responses obtained in SCE surveys to be affected by the time of day that an interview takes place, and maybe more importantly, that responses could be affected by the level of glucose in the respondent’s blood during the interview. This raises a question concerning how depletion of mental energy could affect peoples’ response behavior in SCEs? Drawing on findings by Baumeister and Tierney (2011) we expect four different types of response behavior when respondents are relatively more fatigued. Firstly, they might not answer at all. Secondly, they might drop out of the survey before completing it - particularly in demanding sections such as the choice tasks. Thirdly, they might try to simplify their choices by, among other strategies, opting more frequently or always for the status quo option or ignoring certain attributes. Lastly, they may make more random choices when decision fatigued and low on blood sugar.

While a range of different behavioral observations might explain the above mentioned response behavior, we specifically examine the latter three types of response behavior in relation to non-parametric analyses of dropout rates, status quo choice and attribute non-attendance, as well as parametric analyses of impacts on error variance, Willingness-To-Pay (WTP) and market share predictions. We investigate this by using data from an online SCE survey concerning Danish consumers’ preferences for cheese. Paradata on recorded time of day of response are linked with typical eating patterns as identified in the food sociology literature, constructing a proxy variable for the expected level of glucose in the blood at the time of response.

While we find no strong evidence of a pure time of day effect, we do find that individuals with relatively low blood sugar levels exhibit significantly larger error variance, indicating that their choices are less consistent. We also find that respondents who are low on blood sugar tend to drop out more, choose the opt-out alternative more frequently, and state higher levels of attribute non-attendance. Finally, when controlling for different individual blood sugar levels we find significant impacts on some of the attribute marginal WTP estimates which translates into fairly large effects on predicted market shares. This could have important implications for the decision support and advice that decision-makers may obtain from stated choice experiments.


Baumeister, R.F. 1998. The self. In D. T. Gilbert, S. T. Fiske, and G. Lindzey, eds. Handbook of social psychology. New York: McGraw-Hill, pp. 680-740.

Baumeister, R.F., and J. Tierney. 2011. Willpower: Rediscovering the greatest human strength. New York: The Penguin Press.

Gailliot, M. T., R. F. Baumeister, C. N. DeWall, J. K. Maner, E. A. Plant, D. M. Tice, L. E. Brewer, and B. J. Schmeichel. 2007. Self-control relies on glucose as a limited energy source: Willpower is more than a metaphor. Journal of Personality and Social Psychology 92: 325-336

Masicampo, E.J. and R.F. Baumeister. 2008. Toward a Physiology of Dual-Process Reasoning and Judgment: Lemonade, Willpower, and Expensive Rule-Based Analysis. Psychol Science 19: 255-260

Muraven, M., and R.F. Baumeister. 2000. Self-regulation and depletion of limited resources: Does self-control resemble a muscle? Psychological Bulletin 126:247-259

Olsen, S. 2009. Choosing between internet and mail surveys modes for choice experiment surveys considering non-market goods. Environmental and Resource Economics 44: 591-610.

Olson, K., and B. Parkhurst. 2013. Collecting Paradata for Measurement Error Evaluations. Chapter 3 in Improving Surveys with Paradata: Analytic Uses of Process Information. Edited by Kreuter F., John Wiley & Sons, 2013, pp. 43–72.

[1] In the psychology literature there is a strong linkage between "self-control", "free will", and "willpower", terms that are often used interchangeably.

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