Bass-modeling for fast fashion lady's shoes based on consumer behavior

Fast fashion is prevalent in the retail industry, however, plotting its life cycle becomes problematic as that feedback from sales record is even considered to be late for them. So, variables in the process of consumer behavior are potential ones for life cycle assessment of fast fashion products. Currently, most studies of Bass model chose the sales data, but whether the Bass model can also be applied for those in consuming process has not been evaluated; meanwhile, if the modeling based on consumer behaviors such as attention and fitting are available, we can project forward in time and make predictions much earlier than those based only on sales. Therefore, we developed a special system and it was used to collect the attention and fitting records. Our results show that only moderate Bass-fitting results were found for individual-level data; while, good to excellent results could be obtained for the accumulated data. Further, a moderate to good correlation was found between the sales and attention on one hand, and sale and fitting on the other. Regression models including Bass Model equations could be applied to predict the sales by either the attention or the fitting data. Overall, variables of consumer behavior, such as attention and fitting, were found to be suitable for Bass Modeling; further they were found to be good indicators to predict sales. These efforts advanced the time required to predict the sales trend of fast fashion sandals and make the predictive protocols more reliable.