{"title":"基于近似动态规划算法的生命周期阶段、BCG矩阵类、竞争者反应和预算约束的多产品媒体广告策划","authors":"Majid Khalilzadeh, Hossein Neghabi","doi":"10.24200/J65.2020.54496.2054","DOIUrl":null,"url":null,"abstract":"In the new competitive world, companies several types of tools and strategies are used to differentiate their products with competitors' product, one of which is promotional. Companies spend a large amount of their promotional budget on advertising. For increase the effectiveness of advertising budgeting, media planning must be properly developed and determine the manner allocation advertising over a company's programming horizon. In this paper, investigates advertising media planning and budgeting for several products. Important aspects including life cycle stage, BCG matrix class, price, competitors’ reaction and budget constraint is considered in our model given uncertainty and with the aim of maximizing profits at the end of the time horizon. We formulate this problem as a stochastic dynamic program and utilized approximate dynamic programming (ADP) algorithm to overcome the huge dimensionality and considerable uncertainties existed in our problem. approximate Dynamic Planning (ADP) is a powerful technique for solving discrete time problems under multistage stochastic control processes. \n A numerical example was carried out on two products over the course of one year (12 monthly periods) with five different advertising packages. The results showed that 5 million iterations would be suitable to converging. Remaining budget analysis shows the percentage of selective offensive packages in higher budgets for product 2 and the more often selection of such packages in midterms for product 1. The process of the life cycle shows that product 1 does not most likely complete its life stages, but product 2 completes its life cycle stages. Moreover, the BCG matrix confirms the results and product 2 is in the final stages of dogs, while product 1 is more likely in Cash Cows. Also, the total budget was examined in different quantities, which showed that as the amount of the budget increased, the target amount increased slowly. The presented model offers the opportunity to managers by which they are able to compare different media for making advertising decisions for various products in an uncertain environment with different budgets.","PeriodicalId":45245,"journal":{"name":"Industrial Engineering and Management Systems","volume":"94 1","pages":"0-0"},"PeriodicalIF":0.6000,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi Product Media Advertising Planning Considering Life Cycle Stage, BCG Matrix Class, Competitors’ Reaction and Budget Constraint using Approximate Dynamic Programming Algorithm\",\"authors\":\"Majid Khalilzadeh, Hossein Neghabi\",\"doi\":\"10.24200/J65.2020.54496.2054\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the new competitive world, companies several types of tools and strategies are used to differentiate their products with competitors' product, one of which is promotional. Companies spend a large amount of their promotional budget on advertising. For increase the effectiveness of advertising budgeting, media planning must be properly developed and determine the manner allocation advertising over a company's programming horizon. In this paper, investigates advertising media planning and budgeting for several products. Important aspects including life cycle stage, BCG matrix class, price, competitors’ reaction and budget constraint is considered in our model given uncertainty and with the aim of maximizing profits at the end of the time horizon. We formulate this problem as a stochastic dynamic program and utilized approximate dynamic programming (ADP) algorithm to overcome the huge dimensionality and considerable uncertainties existed in our problem. approximate Dynamic Planning (ADP) is a powerful technique for solving discrete time problems under multistage stochastic control processes. \\n A numerical example was carried out on two products over the course of one year (12 monthly periods) with five different advertising packages. The results showed that 5 million iterations would be suitable to converging. Remaining budget analysis shows the percentage of selective offensive packages in higher budgets for product 2 and the more often selection of such packages in midterms for product 1. The process of the life cycle shows that product 1 does not most likely complete its life stages, but product 2 completes its life cycle stages. Moreover, the BCG matrix confirms the results and product 2 is in the final stages of dogs, while product 1 is more likely in Cash Cows. Also, the total budget was examined in different quantities, which showed that as the amount of the budget increased, the target amount increased slowly. The presented model offers the opportunity to managers by which they are able to compare different media for making advertising decisions for various products in an uncertain environment with different budgets.\",\"PeriodicalId\":45245,\"journal\":{\"name\":\"Industrial Engineering and Management Systems\",\"volume\":\"94 1\",\"pages\":\"0-0\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Industrial Engineering and Management Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24200/J65.2020.54496.2054\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial Engineering and Management Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24200/J65.2020.54496.2054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Multi Product Media Advertising Planning Considering Life Cycle Stage, BCG Matrix Class, Competitors’ Reaction and Budget Constraint using Approximate Dynamic Programming Algorithm
In the new competitive world, companies several types of tools and strategies are used to differentiate their products with competitors' product, one of which is promotional. Companies spend a large amount of their promotional budget on advertising. For increase the effectiveness of advertising budgeting, media planning must be properly developed and determine the manner allocation advertising over a company's programming horizon. In this paper, investigates advertising media planning and budgeting for several products. Important aspects including life cycle stage, BCG matrix class, price, competitors’ reaction and budget constraint is considered in our model given uncertainty and with the aim of maximizing profits at the end of the time horizon. We formulate this problem as a stochastic dynamic program and utilized approximate dynamic programming (ADP) algorithm to overcome the huge dimensionality and considerable uncertainties existed in our problem. approximate Dynamic Planning (ADP) is a powerful technique for solving discrete time problems under multistage stochastic control processes.
A numerical example was carried out on two products over the course of one year (12 monthly periods) with five different advertising packages. The results showed that 5 million iterations would be suitable to converging. Remaining budget analysis shows the percentage of selective offensive packages in higher budgets for product 2 and the more often selection of such packages in midterms for product 1. The process of the life cycle shows that product 1 does not most likely complete its life stages, but product 2 completes its life cycle stages. Moreover, the BCG matrix confirms the results and product 2 is in the final stages of dogs, while product 1 is more likely in Cash Cows. Also, the total budget was examined in different quantities, which showed that as the amount of the budget increased, the target amount increased slowly. The presented model offers the opportunity to managers by which they are able to compare different media for making advertising decisions for various products in an uncertain environment with different budgets.
期刊介绍:
Industrial Engineering and Management Systems (IEMS) covers all areas of industrial engineering and management sciences including but not limited to, applied statistics & data mining, business & information systems, computational intelligence & optimization, environment & energy, ergonomics & human factors, logistics & transportation, manufacturing systems, planning & scheduling, quality & reliability, supply chain management & inventory systems.