{"title":"Should price cannibalization be avoided or embraced? A multi‐method investigation","authors":"Atabak Mehrdar, Ting Li","doi":"10.1111/poms.14063","DOIUrl":null,"url":null,"abstract":"This paper proposes price cannibalization as a growth strategy despite prior findings that suggests avoiding it. We focus on a multi‐class, capacity‐constrained pricing problem in which each of the product classes has a price range. Specifically, we examine the effects of price range overlaps and introduce it as a revenue‐maximizing pricing strategy. Price cannibalization happens when sales in some product classes decrease due to the existence of overlaps between the price ranges. We employ a multi‐method approach. First, we define a Markovian Decision Problem (MDP) to obtain the revenue‐maximizing strategy in a two‐class sales scenario. We show that price range overlaps are part of the optimal strategy. Second, we collect multichannel data from a European storage company to examine how price range overlaps impact a customer's purchase decisions. The results show that the existence of price range overlaps leads to cannibalization, but increases spending and improves conversion. Finally, we use simulations to compare several pricing strategies and demonstrate the long‐term effects of using price range overlaps in pricing algorithms in complex situations. Our findings suggest that using price range overlaps, though leads to cannibalization, actually helps companies avoid spoilage and early sellouts, leading to better capacity utilization and higher revenue.This article is protected by copyright. All rights reserved","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":" ","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Production and Operations Management","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1111/poms.14063","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes price cannibalization as a growth strategy despite prior findings that suggests avoiding it. We focus on a multi‐class, capacity‐constrained pricing problem in which each of the product classes has a price range. Specifically, we examine the effects of price range overlaps and introduce it as a revenue‐maximizing pricing strategy. Price cannibalization happens when sales in some product classes decrease due to the existence of overlaps between the price ranges. We employ a multi‐method approach. First, we define a Markovian Decision Problem (MDP) to obtain the revenue‐maximizing strategy in a two‐class sales scenario. We show that price range overlaps are part of the optimal strategy. Second, we collect multichannel data from a European storage company to examine how price range overlaps impact a customer's purchase decisions. The results show that the existence of price range overlaps leads to cannibalization, but increases spending and improves conversion. Finally, we use simulations to compare several pricing strategies and demonstrate the long‐term effects of using price range overlaps in pricing algorithms in complex situations. Our findings suggest that using price range overlaps, though leads to cannibalization, actually helps companies avoid spoilage and early sellouts, leading to better capacity utilization and higher revenue.This article is protected by copyright. All rights reserved
期刊介绍:
The mission of Production and Operations Management is to serve as the flagship research journal in operations management in manufacturing and services. The journal publishes scientific research into the problems, interest, and concerns of managers who manage product and process design, operations, and supply chains. It covers all topics in product and process design, operations, and supply chain management and welcomes papers using any research paradigm.