Testing the Effects of Peak, End, and Linear Trend on Evaluations of Online Video Quality of Experience

Abstract

While previous research has shown that the sequencing of good and bad experience is an important predictor of overall evaluations of a set of experiences, the impact of sequencing effects on the experience of viewing online video has yet to be established. The aim of this study was to determine whether different sequences of good (G), mediocre (M), and bad (B) quality videos in different blocks would influence overall ratings after viewing those blocks. Thirty-two participants each watched 10 blocks of 4 videos and provided ratings of technical quality (TQ), satisfaction, and frustration for each video in the block, as well as overall ratings for each block (as a whole). Sequences of G, M, and B videos were designed to test whether block characteristics (features), like the peak-end effect and effect of linear trend, influenced summary evaluations of the block service. The results of the experiment show that overall block TQ, satisfaction, and frustration ratings differed significantly by sequencing feature. Difference scores were used to determine whether the features had an effect on overall evaluations beyond what could be explained by the total number of bad videos in the block or the average ratings of the videos in the block. Results showed a significant end effect for negative ends of a block, and an effect of linear trend (both increasing and decreasing). There was no evidence of a peak effect or an end effect for positive ends. The presence of a negative end effect and effect of linear trend indicate that where possible service providers should avoid service sessions with poor service quality at the end, or sessions that have decreasing quality as the session progresses.