A Prelaunch Diffusion Model for Evaluating Market Defense Strategies
This paper describes the development and application of a marketing model to help set an incumbent's defensive marketing strategy prior to a new competitor's launch. The management problem addressed is to assess the market share impact of a new entrant in the residential Australian long di...
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Veröffentlicht in: | Marketing science (Providence, R.I.) R.I.), 2005-01, Vol.24 (1), p.150-164 |
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creator | Roberts, John H Nelson, Charles J Morrison, Pamela D |
description | This paper describes the development and application of a marketing model to help set an incumbent's defensive marketing strategy prior to a new competitor's launch. The management problem addressed is to assess the market share impact of a new entrant in the residential Australian long distance telephone call market and determine the factors that would influence its dynamics and ultimate market appeal.
The paper uses probability flow models to provide a framework to generate forecasts and assess the determinants of share loss. We develop models at two levels of complexity to give both simple, robust forecasts and more detailed diagnostic analysis of the effect of marketing actions. The models are calibrated prior to the new entrant's launch, enabling preemptive marketing strategies to be put in place by the defending company. The equilibrium level of consideration of the new entrant was driven by respondents' strength of relationship with the defender and inertia, while trial was more price-based. Continued use of the defender depends on both service factors and price. The rate at which share loss eventuates is negatively related to the defender's perceived responsiveness, saving money being the only reason to switch, and risk aversion.
Prelaunch model forecasts, validated six months after launch using both aggregate monthly sales data and detailed tracking surveys, are shown to closely follow the actual evolution of the market. The paper provides a closed-form multistate model of the new entrant's diffusion, a methodology for the prelaunch calibration of dynamic models in practice, and insights into defensive strategies for existing companies facing new entrants. |
doi_str_mv | 10.1287/mksc.1040.0086 |
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The paper uses probability flow models to provide a framework to generate forecasts and assess the determinants of share loss. We develop models at two levels of complexity to give both simple, robust forecasts and more detailed diagnostic analysis of the effect of marketing actions. The models are calibrated prior to the new entrant's launch, enabling preemptive marketing strategies to be put in place by the defending company. The equilibrium level of consideration of the new entrant was driven by respondents' strength of relationship with the defender and inertia, while trial was more price-based. Continued use of the defender depends on both service factors and price. The rate at which share loss eventuates is negatively related to the defender's perceived responsiveness, saving money being the only reason to switch, and risk aversion.
Prelaunch model forecasts, validated six months after launch using both aggregate monthly sales data and detailed tracking surveys, are shown to closely follow the actual evolution of the market. The paper provides a closed-form multistate model of the new entrant's diffusion, a methodology for the prelaunch calibration of dynamic models in practice, and insights into defensive strategies for existing companies facing new entrants.</description><identifier>ISSN: 0732-2399</identifier><identifier>EISSN: 1526-548X</identifier><identifier>DOI: 10.1287/mksc.1040.0086</identifier><identifier>CODEN: MARSE5</identifier><language>eng</language><publisher>Linthicum: INFORMS</publisher><subject>Analysis ; Australia ; brand choice ; Business forecasts ; Calibration ; Case studies ; Communications industry ; Competition ; Decision making ; Defense ; defensive strategy ; diffusion ; Dynamic modeling ; Econometrics ; Empirical research ; Flow velocity ; forecasting ; Forecasting models ; Forecasts ; Game theory ; Incumbency ; Incumbents ; Industrial economics ; Inertia ; Market entry ; Market prices ; Market share ; Market shares ; Market strategy ; Marketing ; Marketing management ; Modeling ; Modelling ; Monopolies ; Optus ; Parametric models ; Product development ; Strategic planning ; Studies ; Telecommunications services industry ; Telstra</subject><ispartof>Marketing science (Providence, R.I.), 2005-01, Vol.24 (1), p.150-164</ispartof><rights>Copyright 2005 INFORMS</rights><rights>COPYRIGHT 2005 Institute for Operations Research and the Management Sciences</rights><rights>Copyright Institute for Operations Research and the Management Sciences Winter 2005</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c621t-3376edc4f340f540da1b533f9e816bb7e39d53f546b945c71b38dc7e4c8a72a13</citedby><cites>FETCH-LOGICAL-c621t-3376edc4f340f540da1b533f9e816bb7e39d53f546b945c71b38dc7e4c8a72a13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/40056945$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://pubsonline.informs.org/doi/full/10.1287/mksc.1040.0086$$EHTML$$P50$$Ginforms$$H</linktohtml><link.rule.ids>314,780,784,803,3692,4008,27924,27925,58017,58250,62616</link.rule.ids><backlink>$$Uhttp://econpapers.repec.org/article/inmormksc/v_3a24_3ay_3a2005_3ai_3a1_3ap_3a150-164.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Roberts, John H</creatorcontrib><creatorcontrib>Nelson, Charles J</creatorcontrib><creatorcontrib>Morrison, Pamela D</creatorcontrib><title>A Prelaunch Diffusion Model for Evaluating Market Defense Strategies</title><title>Marketing science (Providence, R.I.)</title><description>This paper describes the development and application of a marketing model to help set an incumbent's defensive marketing strategy prior to a new competitor's launch. The management problem addressed is to assess the market share impact of a new entrant in the residential Australian long distance telephone call market and determine the factors that would influence its dynamics and ultimate market appeal.
The paper uses probability flow models to provide a framework to generate forecasts and assess the determinants of share loss. We develop models at two levels of complexity to give both simple, robust forecasts and more detailed diagnostic analysis of the effect of marketing actions. The models are calibrated prior to the new entrant's launch, enabling preemptive marketing strategies to be put in place by the defending company. The equilibrium level of consideration of the new entrant was driven by respondents' strength of relationship with the defender and inertia, while trial was more price-based. Continued use of the defender depends on both service factors and price. The rate at which share loss eventuates is negatively related to the defender's perceived responsiveness, saving money being the only reason to switch, and risk aversion.
Prelaunch model forecasts, validated six months after launch using both aggregate monthly sales data and detailed tracking surveys, are shown to closely follow the actual evolution of the market. The paper provides a closed-form multistate model of the new entrant's diffusion, a methodology for the prelaunch calibration of dynamic models in practice, and insights into defensive strategies for existing companies facing new entrants.</description><subject>Analysis</subject><subject>Australia</subject><subject>brand choice</subject><subject>Business forecasts</subject><subject>Calibration</subject><subject>Case studies</subject><subject>Communications industry</subject><subject>Competition</subject><subject>Decision making</subject><subject>Defense</subject><subject>defensive strategy</subject><subject>diffusion</subject><subject>Dynamic modeling</subject><subject>Econometrics</subject><subject>Empirical research</subject><subject>Flow velocity</subject><subject>forecasting</subject><subject>Forecasting models</subject><subject>Forecasts</subject><subject>Game theory</subject><subject>Incumbency</subject><subject>Incumbents</subject><subject>Industrial economics</subject><subject>Inertia</subject><subject>Market entry</subject><subject>Market prices</subject><subject>Market share</subject><subject>Market shares</subject><subject>Market strategy</subject><subject>Marketing</subject><subject>Marketing management</subject><subject>Modeling</subject><subject>Modelling</subject><subject>Monopolies</subject><subject>Optus</subject><subject>Parametric models</subject><subject>Product development</subject><subject>Strategic planning</subject><subject>Studies</subject><subject>Telecommunications services industry</subject><subject>Telstra</subject><issn>0732-2399</issn><issn>1526-548X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkt9r1TAUx4soeJ2--iYUH3wQes2vNunjZXc6ZUPBCb6FND3pzV2b3CXtZP_90nVMkOEIyQnJ5_vlnJxk2VuM1pgI_mm4jHqNEUNrhET1LFvhklRFycTv59kKcUoKQuv6ZfYqxj1CiBMkVtl2k_8I0KvJ6V2-tcZM0XqXn_sW-tz4kJ9cq35So3Vdfq7CJYz5Fgy4CPnPMagROgvxdfbCqD7Cm_t4lP36fHJxfFqcff_y9XhzVuiK4LGglFfQamYoQ6ZkqFW4KSk1NQhcNQ0HWrclTTdVU7NSc9xQ0WoOTAvFicL0KPuw-B6Cv5ogjnKwUUPfKwd-ipIKjAmjM_j-H3Dvp-BSbpJgQlhdizJBxQJ1qgdpnfGpIN2Bg6B678DYdLzBFHFeMc4Sv36ET6OFwer_CXTwMQYw8hDsoMKNxEjOLZNzy-TcMjm3LAm-LYIAB9APtHWDD3fotaSKsLTczBuEyhRsmjjNwxzLZFwxuRuHZPZuMdvH0YcHM5ZUVXrev-XPlYQhPp3cx4Xf2W73x4blCWbhcPcvorYy5YZlSoLeAkKZyKc</recordid><startdate>20050101</startdate><enddate>20050101</enddate><creator>Roberts, John H</creator><creator>Nelson, Charles J</creator><creator>Morrison, Pamela D</creator><general>INFORMS</general><general>Institute for Operations Research and the Management Sciences (INFORMS)</general><general>Institute for Operations Research and the Management Sciences</general><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88G</scope><scope>8AO</scope><scope>8BJ</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FQK</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>JBE</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L.0</scope><scope>M0C</scope><scope>M2M</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>PYYUZ</scope><scope>Q9U</scope></search><sort><creationdate>20050101</creationdate><title>A Prelaunch Diffusion Model for Evaluating Market Defense Strategies</title><author>Roberts, John H ; Nelson, Charles J ; Morrison, Pamela D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c621t-3376edc4f340f540da1b533f9e816bb7e39d53f546b945c71b38dc7e4c8a72a13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Analysis</topic><topic>Australia</topic><topic>brand choice</topic><topic>Business forecasts</topic><topic>Calibration</topic><topic>Case studies</topic><topic>Communications industry</topic><topic>Competition</topic><topic>Decision making</topic><topic>Defense</topic><topic>defensive strategy</topic><topic>diffusion</topic><topic>Dynamic modeling</topic><topic>Econometrics</topic><topic>Empirical research</topic><topic>Flow velocity</topic><topic>forecasting</topic><topic>Forecasting models</topic><topic>Forecasts</topic><topic>Game theory</topic><topic>Incumbency</topic><topic>Incumbents</topic><topic>Industrial economics</topic><topic>Inertia</topic><topic>Market entry</topic><topic>Market prices</topic><topic>Market share</topic><topic>Market shares</topic><topic>Market strategy</topic><topic>Marketing</topic><topic>Marketing management</topic><topic>Modeling</topic><topic>Modelling</topic><topic>Monopolies</topic><topic>Optus</topic><topic>Parametric models</topic><topic>Product development</topic><topic>Strategic planning</topic><topic>Studies</topic><topic>Telecommunications services industry</topic><topic>Telstra</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Roberts, John H</creatorcontrib><creatorcontrib>Nelson, Charles J</creatorcontrib><creatorcontrib>Morrison, Pamela D</creatorcontrib><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>Access via ABI/INFORM (ProQuest)</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>International Bibliography of the Social Sciences</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ABI/INFORM Global</collection><collection>Psychology Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ABI/INFORM Collection China</collection><collection>ProQuest Central Basic</collection><jtitle>Marketing science (Providence, R.I.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Roberts, John H</au><au>Nelson, Charles J</au><au>Morrison, Pamela D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Prelaunch Diffusion Model for Evaluating Market Defense Strategies</atitle><jtitle>Marketing science (Providence, R.I.)</jtitle><date>2005-01-01</date><risdate>2005</risdate><volume>24</volume><issue>1</issue><spage>150</spage><epage>164</epage><pages>150-164</pages><issn>0732-2399</issn><eissn>1526-548X</eissn><coden>MARSE5</coden><abstract>This paper describes the development and application of a marketing model to help set an incumbent's defensive marketing strategy prior to a new competitor's launch. The management problem addressed is to assess the market share impact of a new entrant in the residential Australian long distance telephone call market and determine the factors that would influence its dynamics and ultimate market appeal.
The paper uses probability flow models to provide a framework to generate forecasts and assess the determinants of share loss. We develop models at two levels of complexity to give both simple, robust forecasts and more detailed diagnostic analysis of the effect of marketing actions. The models are calibrated prior to the new entrant's launch, enabling preemptive marketing strategies to be put in place by the defending company. The equilibrium level of consideration of the new entrant was driven by respondents' strength of relationship with the defender and inertia, while trial was more price-based. Continued use of the defender depends on both service factors and price. The rate at which share loss eventuates is negatively related to the defender's perceived responsiveness, saving money being the only reason to switch, and risk aversion.
Prelaunch model forecasts, validated six months after launch using both aggregate monthly sales data and detailed tracking surveys, are shown to closely follow the actual evolution of the market. The paper provides a closed-form multistate model of the new entrant's diffusion, a methodology for the prelaunch calibration of dynamic models in practice, and insights into defensive strategies for existing companies facing new entrants.</abstract><cop>Linthicum</cop><pub>INFORMS</pub><doi>10.1287/mksc.1040.0086</doi><tpages>15</tpages></addata></record> |
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subjects | Analysis Australia brand choice Business forecasts Calibration Case studies Communications industry Competition Decision making Defense defensive strategy diffusion Dynamic modeling Econometrics Empirical research Flow velocity forecasting Forecasting models Forecasts Game theory Incumbency Incumbents Industrial economics Inertia Market entry Market prices Market share Market shares Market strategy Marketing Marketing management Modeling Modelling Monopolies Optus Parametric models Product development Strategic planning Studies Telecommunications services industry Telstra |
title | A Prelaunch Diffusion Model for Evaluating Market Defense Strategies |
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