کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6892563 1445450 2018 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Coping with demand volatility in retail pharmacies with the aid of big data exploration
ترجمه فارسی عنوان
مقابله با نوسان تقاضا در داروخانه های خرده فروشی با کمک اکتشاف داده های بزرگ
کلمات کلیدی
داروخانه خرده فروشی، داده کاوی، سری زمانی، پیش بینی، اطلاعات بزرگ، عدم قطعیت تقاضا،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی
Data management tools and analytics have provided managers with the opportunity to contemplate inventory performance as an ongoing activity by no longer examining only data agglomerated from ERP systems, but also, considering internet information derived from customers' online buying behaviour. The realisation of this complex relationship has increased interest in business intelligence through data and text mining of structured, semi-structured and unstructured data, commonly referred to as “big data” to uncover underlying patterns which might explain customer behaviour and improve the response to demand volatility. This paper explores how sales structured data can be used in conjunction with non-structured customer data to improve inventory management either in terms of forecasting or treating some inventory as “top-selling” based on specific customer tendency to acquire more information through the internet. A medical condition is considered - namely pain - by examining 129 weeks of sales data regarding analgesics and information seeking data by customers through Google, online newspapers and YouTube. In order to facilitate our study we consider a VARX model with non-structured data as exogenous to obtain the best estimation and we perform tests against several univariate models in terms of best fit performance and forecasting.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Operations Research - Volume 98, October 2018, Pages 343-354
نویسندگان
, ,