Word-of-mouth and the forecasting of consumption enjoyment

The digital era has permitted rapid transfer of peer knowledge regarding products and services. In the present research, we explore the value of specific types of word-of-mouth information (numeric ratings and text commentary) for improving forecasts of consumption enjoyment. We present an anchoring-and-adjustment model in which the relative forecasting error associated with ratings and commentary depends on the extent to which consumer and reviewer have similar product-level preferences. To test our model, we present four experiments using a range of hedonic stimuli. Implications for the provision of consumer WOM are discussed.