The influence of product involvement and emotion on short-term product demand forecasting

Abstract

a b s t r a c tSales forecasters in industries like fast-fashion face challenges posed by short and highly volatile sales time series. Computers can produce statistical forecasts, but these are often adjusted judgmentally to take into account factors such as market intelligence. We explore the effects of two potential influences on these adjustments: the forecaster's involvement with the product category and their emotional reactions to particular products. Two forecasting experiments were conducted using data from a major Italian leather fashion goods producer. The participants' judgmental adjustments tended to lower the forecast accuracy, but especially when the participants had strong preferences for particular products. This appeared to result from a false consensus effect. The most accurate forecasts were made when the participants had no knowledge of the product and only received time series information, though a high level of involvement with the product category also led to a greater accuracy.

The Influencing Mechanism of Interaction Quality of UGC on Consumers’ Purchase Intention – An Empirical Analysis

“…Product involvement affects the evaluation and actual purchase of a product by consumers. Product involvement is an important factor for consumer product choice ( Belvedere and Goodwin, 2017 ). When consumers perceive usefulness and trust through UGC interaction, they are involved in the product, and will consider the uncertain consequences of the product, resulting in perceived risk ( Rahman, 2017 ; Habib et al, 2021 ).…”

“…Therefore, we should consider the characteristics of information receivers when analyzing the impact of UGC on consumers. Product involvement in the communication effect has helped explain consumer behavior in advertising, promotion stimulation, information search, and processing ( Zaichkowsky, 1985 ; Belvedere and Goodwin, 2017 ). Therefore, this study introduces consumer product involvement as the moderating variable.…”

Predictive competitive intelligence with prerelease online search traffic

“…This is further amplified by the judgmental processes used for new products (Kahn & Chase, 2018). We see an interesting avenue of future research in how this new kind of marketing intelligence can integrate into decision‐making processes, hopefully mitigating biases involved with new products (Belvedere & Goodwin, 2017; Markovitch et al., 2014).…”

Interventions as experiments: Connecting the dots in forecasting and overcoming pandemics, global warming, corruption, civil rights violations, misogyny, income inequality, and guns

“…Research on adjusting forecasts from statistical models found that adjustments often increase errors (e.g. Belvedere & Goodwin, 2017;Fildes & Goodwin, 2007) or have mixed results (e.g. Franses, 2014;Lin, Goodwin, & Song, 2014)" (Armstrong & Green, 2018a, 2018b.…”