Predicting consumer variety-seeking through weather data analytics

作者：

Highlights：

• Assess why and how weather conditions may influence consumers’ variety-seeking.

• Integrate public weather data and supermarket panel data to predict variety-seeking behavior.

• Low sunlight, high temperature and low air quality could lead to greater variety-seeking behavior.

摘要

•Assess why and how weather conditions may influence consumers’ variety-seeking.•Integrate public weather data and supermarket panel data to predict variety-seeking behavior.•Low sunlight, high temperature and low air quality could lead to greater variety-seeking behavior.

论文关键词：China big data,Data analytics,Marketing decision support system,Mehrabian-Russell model,Variety-seeking,Weather data

论文评审过程：Received 27 August 2017, Revised 2 February 2018, Accepted 2 February 2018, Available online 7 February 2018, Version of Record 24 February 2018.

论文官网地址：https://doi.org/10.1016/j.elerap.2018.02.001