Post by Lancaster Centre for Marketing Analytics and Forecasting

𝙉𝙚𝙬 𝙥𝙪𝙗𝙡𝙞𝙘𝙖𝙩𝙞𝙤𝙣 𝙖𝙡𝙚𝙧𝙩! Our colleague (Anna-Lena Sachs) at the Centre for Marketing Analytics and Forecasting (CMAF) with her colleagues Thomas Vogt, Ben Lowery and Ulrich Thonemann examine an often overlooked driver of retail performance: customer picking behaviour and its implications for inventory and food waste. 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 The paper is motivated by the substantial food waste in grocery retail and the preferences of customers to pick longer-lasting items, which can lead to unsold expiring products and higher waste. 𝗠𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝘆 The study integrates a behavioural online experiment with an inventory modelling framework. Specifically, the authors design a controlled experiment comparing baseline and sustainability message treatments with varying price discounts, and embed the behavioural insights into a periodic-review inventory model formulated as a Markov Decision Process. 𝗣𝗿𝗼𝗽𝗼𝘀𝗲𝗱 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 The paper proposes a novel integration of behavioural operations and inventory optimisation by modelling mixed first-in-first-out (FIFO) and last-in-first-out (LIFO) picking behaviour and analysing how sustainability messages and price discounts can nudge customers towards choosing earlier-expiring items. 𝗙𝗶𝗻𝗱𝗶𝗻𝗴𝘀 Results show that sustainability messages significantly increase the likelihood of customers selecting expiring items, and higher discounts further reinforce this effect if tailored to specific customer groups. The numerical study demonstrates that shifting behaviour towards FIFO can substantially reduce inventory costs and waste. 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 The paper offers an important contribution by linking behavioural interventions with operational decision making, providing actionable insights for retailers seeking more sustainable and cost-efficient inventory management. Link to the paper: https://lnkd.in/eZsZNX9J. #CMAF #BehaviouralOperations #RetailAnalytics #InventoryManagement #Sustainability #OperationsResearch #BusinessAnalytics #FoodWaste #DecisionMaking