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ABSTRACT
The inaction inertia effect describes situations in which a person rejects an opportunity after having forgone a relatively superior opportunity. This study explores whether product format (hedonic vs. utilitarian) affects the inaction inertia effect. The authors build on previous findings that show comparisons of utilitarian benefits are easier than hedonic benefits, and hedonic consumption (vs. utilitarian consumption) usually generates greater pleasure. The authors propose that people show higher inaction inertia after they have missed a superior utilitarian consumption opportunity than after they have missed a superior hedonic consumption opportunity. This prediction was tested and supported in three different experiments. Moreover, the authors found that differences in comparability between products, rather than the hedonic pleasure, explain differences in inaction inertia effects. These findings contribute to the inaction inertia literature and marketing practice.
Acknowledgement
The authors thank the anonymous reviewers for their constructive comments. The authors are grateful for helpful suggestions from Chia-Yu Kuo.
Notes
1. This paper focuses on the relative strength of inaction inertia under hedonic and utilitarian products and is not examining the existence of inaction inertia.
2. Each cell under all three experiments conditions was designed to include at least 20 valid samples. This follows previous studies of inaction inertia (e.g., Butler & Highhouse, Citation2000; Kumar, Citation2004; Liu et al., Citation2011; Zeelenberg et al., Citation2006). Geuens and De Pelsmacker (Citation2017, p. 5) suggest that a study must be of “adequate size” but not “too big” in order to avoid statistical anomalies due to excessive power. They suggest that 30–40 participants per experimental condition are enough to ensure sufficient statistical power. We ensured that each condition included more than 20 but less than 40 samples. According to G*Power calculation, the minimum sufficient sample sizes for an alpha of .05, power of .80, and a medium effect size of f = .25 are 128 for testing a 2 × 2 two-factor interaction and 158 for testing a 2 × 3 two-factor interaction by ANOVA. The sample sizes in the experiments satisfy these requirements.
3. Students in Taiwan frequently go Karaoke TV bars with friends and classmates in order to relax and enjoy themselves.
4. These tests were also applied to Experiments 2 and 3 and demonstrated our manipulations followed the anticipated direction. For brevity these details were not included in the text but information can be requested from the authors.
5. Similar results are found for the attractiveness of the target apartment and participants’ renting decisions. Detailed information can be requested from the authors.
6. We performed similar supplemental analyses for both Experiments 2 and 3. Detailed information can be requested from the authors.
7. When we include participants’ gender, it does not have any main effect or two- or three- way interaction effect with the other two factors. The product format × condition interaction effect is still marginally significant, β = −0.43, χ2(n = 134) = 3.25, p = 0.07. When we add participants’ ages as covariance into the above model, the results are similar. Participants’ ages have no impact on participants’ decision, β = −0.09, χ2(n = 134) = 0.34, p > 0.1. Again, the product format × condition interaction effect is marginally significant, β = −0.44, χ2(n = 134) = 3.32, p = 0.07.
8. In a seventh condition (the control condition), participants neither encountered another person or the previous sale price. They reported the possibility of buying the pair of shoes at the promotional price (US$ 90). We do not report the control condition as it is irrelevant to the proposition.