کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
998049 1481437 2016 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multi-period-ahead forecasting with residual extrapolation and information sharing — Utilizing a multitude of retail series
ترجمه فارسی عنوان
پیش بینی چند دوره جلوتر با برون یابی باقی مانده و به اشتراک گذاری اطلاعات - استفاده از بسیاری از سری‌های خرده فروشی
کلمات کلیدی
سری های زمانی چند متغیره؛ پیش بینی فروش؛ پنل اطلاعات؛ داده کاوی؛ پسرفت؛ خرده فروشی؛ پیش بینی چند دوره جلوتر
موضوعات مرتبط
علوم انسانی و اجتماعی مدیریت، کسب و کار و حسابداری کسب و کار و مدیریت بین المللی
چکیده انگلیسی

Multi-period sales forecasts are important inputs for operations at retail chains with hundreds of stores, and many different formats, customer segments and categories. In addition to the effects of seasonality, holidays and marketing, correlated random disturbances also affect sales across stores that share common characteristics.We propose a novel method, Two-Stage Information Sharing that takes advantage of this challenging complexity. In this method, segment-specific panel regressions with seasonality and marketing variables pool the data, in order to provide better parameter estimates. The residuals are then extrapolated non-parametrically using features that are constructed from the last twelve months of observations from the focal and related category-store time series. The final forecast combines the extrapolated residuals with the forecasts from the first stage.Working with the extensive dataset of a leading Turkish retailer, we show that this method significantly outperforms both panel regression models (mixed model) with an AR(1) error structure and the autoregressive distributed lags (ADL) model, as well as the univariate exponential smoothing (Winters’) method. The further out the prediction, the greater the improvement.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Forecasting - Volume 32, Issue 2, April–June 2016, Pages 502–517
نویسندگان
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