Pub Date : 2025-12-18DOI: 10.1177/00222429251412261
Katrijn Gielens, Jan-Benedict E.M. Steenkamp
This study investigates how the effectiveness of three core marketing-mix instruments—price, assortment, and distribution—evolves over time across brands, categories, and countries, using the Empirics-First approach to generate relevant knowledge. The authors analyze household panel data covering over 16,000 brands in 85 consumer packaged goods categories for on average 10 years across 34 countries in Asia, Europe, North America and South America. They adopt a rolling-window estimation approach to derive time-varying elasticities, followed by a moderator analysis to identify systematic drivers of change. Averaged across time, brand price elasticity is -.640, assortment elasticity is .311, and distribution elasticity is .213. However, time-invariant averages have limited meaning given that 98.5% of brands exhibit significant evolution in at least one instrument’s elasticity. Substantial heterogeneity in trends emerges, moderated by brand, category, and country factors. The single most important predictor is the brand’s baseline (mean) elasticity. The stronger the elasticity, the larger its downward trend. Brand power and whether the brand is a local brand emerge as other key factors. Consumer purchase frequency and share-of-wallet are stronger category predictors of elasticity trajectories than retailer factors. Findings underscore the need for dynamic, elasticity-based resource allocation in brand management.
{"title":"EXPRESS: An Investigation into the Evolution of Marketing Mix Effectiveness: An Empirics-First Approach","authors":"Katrijn Gielens, Jan-Benedict E.M. Steenkamp","doi":"10.1177/00222429251412261","DOIUrl":"https://doi.org/10.1177/00222429251412261","url":null,"abstract":"This study investigates how the effectiveness of three core marketing-mix instruments—price, assortment, and distribution—evolves over time across brands, categories, and countries, using the Empirics-First approach to generate relevant knowledge. The authors analyze household panel data covering over 16,000 brands in 85 consumer packaged goods categories for on average 10 years across 34 countries in Asia, Europe, North America and South America. They adopt a rolling-window estimation approach to derive time-varying elasticities, followed by a moderator analysis to identify systematic drivers of change. Averaged across time, brand price elasticity is -.640, assortment elasticity is .311, and distribution elasticity is .213. However, time-invariant averages have limited meaning given that 98.5% of brands exhibit significant evolution in at least one instrument’s elasticity. Substantial heterogeneity in trends emerges, moderated by brand, category, and country factors. The single most important predictor is the brand’s baseline (mean) elasticity. The stronger the elasticity, the larger its downward trend. Brand power and whether the brand is a local brand emerge as other key factors. Consumer purchase frequency and share-of-wallet are stronger category predictors of elasticity trajectories than retailer factors. Findings underscore the need for dynamic, elasticity-based resource allocation in brand management.","PeriodicalId":16152,"journal":{"name":"Journal of Marketing","volume":"6 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145770622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1177/00222429251410844
Yi Qian, Anthony Koschmann, Hui Xie
Causal inference is of central interest in many empirical applications, yet often challenging because of the presence of endogenous regressors. The classical approach to the problem requires using instrumental variables that must satisfy the stringent condition of exclusion restriction. In recent research, instrument-free copula methods have been increasingly used to handle endogenous regressors. This article aims to provide a practical guide for how to handle endogeneity using copulas. The authors give an overview of copula endogeneity correction, outlining its theoretical rationales, advantages, and limitations for empirical research. They also discuss recent advances that enhance the understanding, applicability, and robustness of copula correction, and address implementation aspects of copula correction such as constructing copula control functions and handling higher-order terms of endogenous regressors. To facilitate the appropriate usage of copula correction in order to realize its full potential, the authors detail a process of checking data requirements and identification assumptions to determine when and how to use copula correction methods, and illustrate its usage using empirical examples.
{"title":"EXPRESS: A Practical Guide to Endogeneity Correction Using Copulas","authors":"Yi Qian, Anthony Koschmann, Hui Xie","doi":"10.1177/00222429251410844","DOIUrl":"https://doi.org/10.1177/00222429251410844","url":null,"abstract":"Causal inference is of central interest in many empirical applications, yet often challenging because of the presence of endogenous regressors. The classical approach to the problem requires using instrumental variables that must satisfy the stringent condition of exclusion restriction. In recent research, instrument-free copula methods have been increasingly used to handle endogenous regressors. This article aims to provide a practical guide for how to handle endogeneity using copulas. The authors give an overview of copula endogeneity correction, outlining its theoretical rationales, advantages, and limitations for empirical research. They also discuss recent advances that enhance the understanding, applicability, and robustness of copula correction, and address implementation aspects of copula correction such as constructing copula control functions and handling higher-order terms of endogenous regressors. To facilitate the appropriate usage of copula correction in order to realize its full potential, the authors detail a process of checking data requirements and identification assumptions to determine when and how to use copula correction methods, and illustrate its usage using empirical examples.","PeriodicalId":16152,"journal":{"name":"Journal of Marketing","volume":"4217 1 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145752982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-11DOI: 10.1177/00222429251409673
Elisa Montaguti, Scott Neslin, Sara Valentini
Returning products has become standard practice for consumers, and a significant "pain point" for retailers. The authors contend that returns can be harnessed to increase profits. This requires retailers to manage the interweaving dynamics of product returns and purchase. The strategy is to co-manage a virtuous cycle whereby current returns increase future purchases, and a vicious cycle whereby current returns increase future returns. Marketing executes the strategy. It generates purchases. The returns that follow impose a direct cost due to the vicious cycle. However, the virtuous cycle of returns can offset this, enabling the retailer to “free-ride” returns by optimizing its marketing. The approach follows the Decision Support System (DSS) paradigm by combining a conceptual model, a statistical model, data, and optimization. A core construct is a stock variable tracking consumers’ memory of return experiences. This drives both the virtuous and vicious cycles. The authors optimize marketing spend accounting for Return Stock. The best results are when dynamics are included in both the statistical and optimization models. Results suggests managers should avoid strict return policies aimed at eliminating returns. Instead, they should design policies that optimally balance the long-term benefits and costs of returns.
{"title":"EXPRESS: Free-Riding Product Returns to Drive Profits","authors":"Elisa Montaguti, Scott Neslin, Sara Valentini","doi":"10.1177/00222429251409673","DOIUrl":"https://doi.org/10.1177/00222429251409673","url":null,"abstract":"Returning products has become standard practice for consumers, and a significant \"pain point\" for retailers. The authors contend that returns can be harnessed to increase profits. This requires retailers to manage the interweaving dynamics of product returns and purchase. The strategy is to co-manage a virtuous cycle whereby current returns increase future purchases, and a vicious cycle whereby current returns increase future returns. Marketing executes the strategy. It generates purchases. The returns that follow impose a direct cost due to the vicious cycle. However, the virtuous cycle of returns can offset this, enabling the retailer to “free-ride” returns by optimizing its marketing. The approach follows the Decision Support System (DSS) paradigm by combining a conceptual model, a statistical model, data, and optimization. A core construct is a stock variable tracking consumers’ memory of return experiences. This drives both the virtuous and vicious cycles. The authors optimize marketing spend accounting for Return Stock. The best results are when dynamics are included in both the statistical and optimization models. Results suggests managers should avoid strict return policies aimed at eliminating returns. Instead, they should design policies that optimally balance the long-term benefits and costs of returns.","PeriodicalId":16152,"journal":{"name":"Journal of Marketing","volume":"113 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145717536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-09DOI: 10.1177/00222429251409065
Divya Anand, Vamsi K. Kanuri, Lisa K. Scheer
Channel restructuring is a firm’s redesign and optimization of its channel system to serve markets more effectively. Restructuring demands significant investments of time, capital, and managerial attention, as firms must reconfigure processes, renegotiate agreements with channel partners, and manage the operational disruptions that inevitably accompany structural change. As even the most rigorously planned restructuring efforts can falter if partners do not buy in, it is paramount that firms secure the compliance of partners they seek to retain in the revised channel system. Prior research lacks a comprehensive and integrated conceptualization of channel restructuring, the available restructuring options, and the implications of restructuring for the firm’s downstream channel partners. We offer a channel restructuring typology comprising six restructuring types and delineate the functional role, status, and financial implications of each type for the firm’s partners. We provide theoretically grounded, testable propositions regarding the impact of restructuring on partner compliance. This paper offers scholars guidance for empirical investigation. It also highlights factors that practitioners should consider when designing and implementing channel restructuring to achieve both operational efficiencies and sustain partner relationships.
{"title":"EXPRESS: Deconstructing Channel Restructuring","authors":"Divya Anand, Vamsi K. Kanuri, Lisa K. Scheer","doi":"10.1177/00222429251409065","DOIUrl":"https://doi.org/10.1177/00222429251409065","url":null,"abstract":"Channel restructuring is a firm’s redesign and optimization of its channel system to serve markets more effectively. Restructuring demands significant investments of time, capital, and managerial attention, as firms must reconfigure processes, renegotiate agreements with channel partners, and manage the operational disruptions that inevitably accompany structural change. As even the most rigorously planned restructuring efforts can falter if partners do not buy in, it is paramount that firms secure the compliance of partners they seek to retain in the revised channel system. Prior research lacks a comprehensive and integrated conceptualization of channel restructuring, the available restructuring options, and the implications of restructuring for the firm’s downstream channel partners. We offer a channel restructuring typology comprising six restructuring types and delineate the functional role, status, and financial implications of each type for the firm’s partners. We provide theoretically grounded, testable propositions regarding the impact of restructuring on partner compliance. This paper offers scholars guidance for empirical investigation. It also highlights factors that practitioners should consider when designing and implementing channel restructuring to achieve both operational efficiencies and sustain partner relationships.","PeriodicalId":16152,"journal":{"name":"Journal of Marketing","volume":"29 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145704138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1177/00222429251408341
Christine Moorman, Ajay K. Kohli, Bernard J. Jaworski
Knowledge is a key resource in marketing and an assumption across literatures is that a firm must prevent valuable knowledge from leaking to competitors. This research develops a theoretical framework that calls for rethinking this view by offering a fresh perspective on when and how a firm should protect marketing knowledge to minimize the likelihood harm to the firm. This framework integrates research across disciplines and interviews with executives to provide a more accurate analysis of the payoffs of knowledge protection. This is accomplished, first, by introducing a set of unintended hidden costs of the most commonly used knowledge-protection strategy—leakage prevention—that harm a firm’s competitive advantage. Firm and industry moderators that influence the magnitude and consequences of these hidden costs are outlined. Second, the framework suggests that the benefits of knowledge protection may be more limited than previously recognized. It does so by delineating the knowledge “leakage-to-harm” process and identifying competitor and industry moderators that can impede the process. Third, the framework offers a typology of alternative protection strategies firms can use to preserve their knowledge-based competitive advantage. Across these contributions, the framework calls for substantial rethinking marketing knowledge protection with important implications for marketing practice and future research.
{"title":"EXPRESS: Rethinking Marketing Knowledge Protection: Hidden Costs and Uncertain Benefits","authors":"Christine Moorman, Ajay K. Kohli, Bernard J. Jaworski","doi":"10.1177/00222429251408341","DOIUrl":"https://doi.org/10.1177/00222429251408341","url":null,"abstract":"Knowledge is a key resource in marketing and an assumption across literatures is that a firm must prevent valuable knowledge from leaking to competitors. This research develops a theoretical framework that calls for rethinking this view by offering a fresh perspective on <jats:italic toggle=\"yes\">when</jats:italic> and <jats:italic toggle=\"yes\">how</jats:italic> a firm should protect marketing knowledge to minimize the likelihood harm to the firm. This framework integrates research across disciplines and interviews with executives to provide a more accurate analysis of the payoffs of knowledge protection. This is accomplished, first, by introducing a set of unintended hidden costs of the most commonly used knowledge-protection strategy—leakage prevention—that harm a firm’s competitive advantage. Firm and industry moderators that influence the magnitude and consequences of these hidden costs are outlined. Second, the framework suggests that the benefits of knowledge protection may be more limited than previously recognized. It does so by delineating the knowledge “leakage-to-harm” process and identifying competitor and industry moderators that can impede the process. Third, the framework offers a typology of alternative protection strategies firms can use to preserve their knowledge-based competitive advantage. Across these contributions, the framework calls for substantial rethinking marketing knowledge protection with important implications for marketing practice and future research.","PeriodicalId":16152,"journal":{"name":"Journal of Marketing","volume":"40 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145673568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1177/00222429251408344
Martin Eisend, Anna Rößer, Erik Hermann
Although research on ethnic diversity in advertising is extensive, its findings remain fragmented and often inconclusive. This limits practical guidance for marketers. Beyond marketing- and consumer-specific factors, differences between ethnic minority groups within a country and cross-national socioeconomic and cultural factors can play a role in shaping responses to ethnic diversity advertising of consumers belonging to either ethnic majority or minority groups. This study develops and empirically tests a theoretical framework to examine the impact of ethnic diversity in advertising along with the factors that moderate this impact. We conduct a meta-analysis based on 1,276 effect sizes derived from 106 studies published between 1969 and 2024, encompassing 155 unique datasets from 21 countries. The findings reveal that ethnic diversity effects are small, but are moderated by country-level variables such as migration rates and rule of law, in addition to product, advertising, and consumer characteristics and that some of these moderator effects work differently for ethnic minority compared to majority consumers. Furthermore, within the U.S. context, the sociopolitical power position of ethnic minorities enhances advertising effectiveness among majority consumers. These insights offer implications for both researchers and practitioners.
{"title":"EXPRESS: Ethnic Diversity in Advertising: A Meta-Analysis","authors":"Martin Eisend, Anna Rößer, Erik Hermann","doi":"10.1177/00222429251408344","DOIUrl":"https://doi.org/10.1177/00222429251408344","url":null,"abstract":"Although research on ethnic diversity in advertising is extensive, its findings remain fragmented and often inconclusive. This limits practical guidance for marketers. Beyond marketing- and consumer-specific factors, differences between ethnic minority groups within a country and cross-national socioeconomic and cultural factors can play a role in shaping responses to ethnic diversity advertising of consumers belonging to either ethnic majority or minority groups. This study develops and empirically tests a theoretical framework to examine the impact of ethnic diversity in advertising along with the factors that moderate this impact. We conduct a meta-analysis based on 1,276 effect sizes derived from 106 studies published between 1969 and 2024, encompassing 155 unique datasets from 21 countries. The findings reveal that ethnic diversity effects are small, but are moderated by country-level variables such as migration rates and rule of law, in addition to product, advertising, and consumer characteristics and that some of these moderator effects work differently for ethnic minority compared to majority consumers. Furthermore, within the U.S. context, the sociopolitical power position of ethnic minorities enhances advertising effectiveness among majority consumers. These insights offer implications for both researchers and practitioners.","PeriodicalId":16152,"journal":{"name":"Journal of Marketing","volume":"216 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145673549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Novice art pricing is an understudied domain. Novice artists operate as microenterprises, making crucial price-setting decisions. Research shows that newcomers often risk overpricing or underpricing their work, and existing online tools offer basic, cost-based pricing advice. Using a three-study framework, we examine novice art pricing on Etsy, where artwork listings include structured data, images, and textual descriptions. We first analyze how these inputs relate to final selling prices using a hedonic regression on structured data, followed by a multimodal fusion deep learning (MMF-DL) model that integrates structured, visual, and textual features. Our results show that features related to artist authenticity (e.g., certificates), customer service (e.g., shipping, returns, personalization), and art style (e.g., genre) are important price predictors. Thus, novice art sold on online platforms exhibits some features typical of mature art markets (e.g., authenticity and reputation) but emphasize customer-focused services. Finally, using a Cox proportional hazards model, we show that, while higher artist reputation is associated with faster sales, discounting correlates with longer time on market. These associations suggest the importance of price setting. From these insights, we develop a price recommender application that predicts both selling prices and time-to-sale, offering practical guidance for newcomer artists and online platforms.
{"title":"EXPRESS: Neither a Picasso Nor a Da Vinci: An Examination of Novice Artwork Pricing with Multi-Modal Data","authors":"Sharmistha Sikdar, Ishita Chakraborty, Nika Dogonadze","doi":"10.1177/00222429251408346","DOIUrl":"https://doi.org/10.1177/00222429251408346","url":null,"abstract":"Novice art pricing is an understudied domain. Novice artists operate as microenterprises, making crucial price-setting decisions. Research shows that newcomers often risk overpricing or underpricing their work, and existing online tools offer basic, cost-based pricing advice. Using a three-study framework, we examine novice art pricing on Etsy, where artwork listings include structured data, images, and textual descriptions. We first analyze how these inputs relate to final selling prices using a hedonic regression on structured data, followed by a multimodal fusion deep learning (MMF-DL) model that integrates structured, visual, and textual features. Our results show that features related to artist authenticity (e.g., certificates), customer service (e.g., shipping, returns, personalization), and art style (e.g., genre) are important price predictors. Thus, novice art sold on online platforms exhibits some features typical of mature art markets (e.g., authenticity and reputation) but emphasize customer-focused services. Finally, using a Cox proportional hazards model, we show that, while higher artist reputation is associated with faster sales, discounting correlates with longer time on market. These associations suggest the importance of price setting. From these insights, we develop a price recommender application that predicts both selling prices and time-to-sale, offering practical guidance for newcomer artists and online platforms.","PeriodicalId":16152,"journal":{"name":"Journal of Marketing","volume":"202 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145673548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-02DOI: 10.1177/00222429251405841
Jeeva Somasundaram, Laura Zimmermann, Quang Duc Pham
The pervasive use of smartphones has raised concerns about their addictive and maladaptive nature. This paper introduces an intervention based on rational addiction theory to cost-effectively nudge consumers to reduce smartphone usage, promoting sustainable digital consumption. We examine whether pre-announcing future targets to reduce smartphone usage influences current consumption and behavioral change. We develop a mathematical model incorporating habit formation, satiation, and projection bias, and test its predictions in three pre-registered randomized control trials using objectively measured smartphone usage. When future incentives and targets are pre-announced, consumers reduce usage pre-emptively compared to their baseline, consistent with rational addiction. This occurs only when participants are given fixed daily reduction targets, not when incentivized proportionally for reductions over time, and seems to reflect forward-looking habit formation, as other explanations (e.g., goal priming or capability testing) were unlikely to drive results. Interestingly, pre-emptive reductions are stronger among heavy users and those with stronger beliefs in meeting their targets. We also find that pre-emptive reductions help consumers meet their targets during the incentivized period and might support post-treatment behavioral sustenance. Our model fitting results reveal considerable heterogeneity and offer insights into how digital detox experiences can be structured to promote sustainable behavior change.
{"title":"EXPRESS: Leveraging Rational Addiction Theory to Reduce Mobile Usage","authors":"Jeeva Somasundaram, Laura Zimmermann, Quang Duc Pham","doi":"10.1177/00222429251405841","DOIUrl":"https://doi.org/10.1177/00222429251405841","url":null,"abstract":"The pervasive use of smartphones has raised concerns about their addictive and maladaptive nature. This paper introduces an intervention based on rational addiction theory to cost-effectively nudge consumers to reduce smartphone usage, promoting sustainable digital consumption. We examine whether pre-announcing future targets to reduce smartphone usage influences current consumption and behavioral change. We develop a mathematical model incorporating habit formation, satiation, and projection bias, and test its predictions in three pre-registered randomized control trials using objectively measured smartphone usage. When future incentives and targets are pre-announced, consumers reduce usage pre-emptively compared to their baseline, consistent with rational addiction. This occurs only when participants are given fixed daily reduction targets, not when incentivized proportionally for reductions over time, and seems to reflect forward-looking habit formation, as other explanations (e.g., goal priming or capability testing) were unlikely to drive results. Interestingly, pre-emptive reductions are stronger among heavy users and those with stronger beliefs in meeting their targets. We also find that pre-emptive reductions help consumers meet their targets during the incentivized period and might support post-treatment behavioral sustenance. Our model fitting results reveal considerable heterogeneity and offer insights into how digital detox experiences can be structured to promote sustainable behavior change.","PeriodicalId":16152,"journal":{"name":"Journal of Marketing","volume":"9 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145651514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-03DOI: 10.1177/00222429251396114
Jianping Ye, Michel Wedel, Rik Pieters
Contextual advertising involves matching features of ads to features of the media context where they appear. We propose AdGazer, a new machine learning procedure to support contextual advertising. It comprises a theoretical framework organizing highand low-level features of ads and contexts, feature engineering models grounded in this framework, an XGBoost model predicting ad and brand attention, and an algorithm optimally assigning ads to contexts. AdGazer includes a Multimodal Large Language Model to extract high-level topics predicting the ad-context match. Our research uses a unique eye-tracking database containing 3531 digital display ads and their contexts, and aggregate ad and brand gaze times. We compare AdGazer’s predictive performance to two feature learning models, VGG16 and ResNet50. AdGazer predicts highly accurately with hold-out correlations of 0.83 for ad gaze and 0.80 for brand gaze, outperforming both feature learning models and generalizing better to out-of-distribution ads. Context features jointly contributed at least 33% to predicted ad gaze and about 20% to predicted brand gaze, good news for managers practicing or considering contextual advertising. We demonstrate that the theory-informed AdGazer effectively matches ads to advertising vehicles and their contexts, optimizing ad gaze more than current practice and alternatives like text-based and native contextual advertising.
{"title":"EXPRESS: AdGazer: Improving Contextual Advertising with Theory-Informed Machine Learning","authors":"Jianping Ye, Michel Wedel, Rik Pieters","doi":"10.1177/00222429251396114","DOIUrl":"https://doi.org/10.1177/00222429251396114","url":null,"abstract":"Contextual advertising involves matching features of ads to features of the media context where they appear. We propose AdGazer, a new machine learning procedure to support contextual advertising. It comprises a theoretical framework organizing highand low-level features of ads and contexts, feature engineering models grounded in this framework, an XGBoost model predicting ad and brand attention, and an algorithm optimally assigning ads to contexts. AdGazer includes a Multimodal Large Language Model to extract high-level topics predicting the ad-context match. Our research uses a unique eye-tracking database containing 3531 digital display ads and their contexts, and aggregate ad and brand gaze times. We compare AdGazer’s predictive performance to two feature learning models, VGG16 and ResNet50. AdGazer predicts highly accurately with hold-out correlations of 0.83 for ad gaze and 0.80 for brand gaze, outperforming both feature learning models and generalizing better to out-of-distribution ads. Context features jointly contributed at least 33% to predicted ad gaze and about 20% to predicted brand gaze, good news for managers practicing or considering contextual advertising. We demonstrate that the theory-informed AdGazer effectively matches ads to advertising vehicles and their contexts, optimizing ad gaze more than current practice and alternatives like text-based and native contextual advertising.","PeriodicalId":16152,"journal":{"name":"Journal of Marketing","volume":"156 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145427727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1177/00222429251395986
Nils Wlömert, Dominik Papies, Harald J. van Heerde
The shift from physical music consumption to online music streaming has fundamentally transformed the market for recorded music, giving consumers access to millions of songs on demand. Because streaming platforms pay artists and labels on a per-play basis, sustained listening and effective discovery have become essential for generating meaningful revenue. With traditional marketing losing relevance for recorded music, curated collections in the form of playlists have emerged as a potentially vital tool for labels to lift streaming demand. As a result, labels have started to deploy playlist marketing by either curating their own playlists or by targeting influential playlists curated by others. However, the success factors behind the impact of playlists on song demand remain insufficiently understood. An analysis of 200,455 quasi-experiments where songs are listed on playlists and later delisted shows an average listing effect of 8.5% more global streams and a carry-over effect of 4% after delisting. Although these effects are highly heterogeneous, they can be systematically explained by playlist design characteristics, including playlist popularity, the song’s prior playlist exposure, the fit between the song and playlist, curator identity, and the curation approach. These findings empower labels to deploy more informed playlist marketing to lift streaming revenue.
{"title":"EXPRESS: Driving Music Demand in the Age of Streaming: Understanding the Heterogeneity in Curated Playlist Effectiveness","authors":"Nils Wlömert, Dominik Papies, Harald J. van Heerde","doi":"10.1177/00222429251395986","DOIUrl":"https://doi.org/10.1177/00222429251395986","url":null,"abstract":"The shift from physical music consumption to online music streaming has fundamentally transformed the market for recorded music, giving consumers access to millions of songs on demand. Because streaming platforms pay artists and labels on a per-play basis, sustained listening and effective discovery have become essential for generating meaningful revenue. With traditional marketing losing relevance for recorded music, curated collections in the form of playlists have emerged as a potentially vital tool for labels to lift streaming demand. As a result, labels have started to deploy playlist marketing by either curating their own playlists or by targeting influential playlists curated by others. However, the success factors behind the impact of playlists on song demand remain insufficiently understood. An analysis of 200,455 quasi-experiments where songs are listed on playlists and later delisted shows an average listing effect of 8.5% more global streams and a carry-over effect of 4% after delisting. Although these effects are highly heterogeneous, they can be systematically explained by playlist design characteristics, including playlist popularity, the song’s prior playlist exposure, the fit between the song and playlist, curator identity, and the curation approach. These findings empower labels to deploy more informed playlist marketing to lift streaming revenue.","PeriodicalId":16152,"journal":{"name":"Journal of Marketing","volume":"167 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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