Research

ECMI – Research

Gear Manufacturers as Contestants in Sports Competitions: Breeding and Branding Effects

Several manufacturers make substantial investments to compete in sports contests, using the gear they develop and market. However, no systematic analysis of the breeding (i.e., innovation) and branding (i.e., marketing) returns from such investments exists. In this study, the authors conceptualize and empirically estimate the breeding and branding returns that such manufacturers obtain. The authors gather data for 30 car brands of 16 manufacturers over the period 2000–2015 regarding their participation, spending, and performance in Formula One championships, annual patent citations, and research-and-development (R

Yvonne van Everdingen, Vijay Ganesh Hariharan, Stefan Stremersch

Several manufacturers make substantial investments to compete in sports contests, using the gear they develop and market. However, no systematic analysis of the breeding (i.e., innovation) and branding (i.e., marketing) returns from such investments exists. In this study, the authors conceptualize and empirically estimate the breeding and branding returns that such manufacturers obtain. The authors gather data for 30 car brands of 16 manufacturers over the period 2000–2015 regarding their participation, spending, and performance in Formula One championships, annual patent citations, and research-and-development (R&D) budgets as well as monthly vehicle registrations, advertising expenditures, and Formula One TV viewership. The authors find that only gear manufacturers with relatively high levels of R&D spending obtain a positive and significant breeding return from competing in sports contests. While most brands obtain positive branding returns, the lower the level of advertising spending for the brand, the greater the branding returns they obtain from competing in these contests. Thus, research-intense (compared with advertising-intense) gear manufacturers have more to gain from competing in sports contests. These findings can help guide manufacturers in budget allocation decisions on sports competitions, R&D, and advertising.

Tournaments to Crowdsource Innovation: The Role of Moderator Feedback and Participation Intensity

Firms increasingly use innovation tournaments to crowdsource innovation ideas from customers. This article uncovers antecedents and consequences of customers’ participation intensity over the course of a tournament. More specifically, the authors theorize on the effects that the type and timing of moderating feedback have on tournament participants’ participation intensity, as well as the effect of the latter on idea quality. Through two longitudinal experiments using a commercial innovation tournament platform, the authors show that moderating feedback stimulates ideators’ participation intensity. They find that negative feedback increases participation intensity, as compared to no feedback and positive feedback. Moreover, negative feedback, either provided in isolation or together with positive feedback, is more effective during the early stages than in the later stages of a tournament. Using a large-scale managerial survey, the authors show that higher participation intensity leads to higher idea quality and better business performance. The effect of participation intensity on idea quality is stronger than the effect of number of ideas and as strong as the effect of number of participants on idea quality.

Nuno Camacho, Hyoryung Nam, P.K. Kannan, and Stefan Stremersch

Firms increasingly use innovation tournaments to crowdsource innovation ideas from customers. This article uncovers antecedents and consequences of customers’ participation intensity over the course of a tournament. More specifically, the authors theorize on the effects that the type and timing of moderating feedback have on tournament participants’ participation intensity, as well as the effect of the latter on idea quality. Through two longitudinal experiments using a commercial innovation tournament platform, the authors show that moderating feedback stimulates ideators’ participation intensity. They find that negative feedback increases participation intensity, as compared to no feedback and positive feedback. Moreover, negative feedback, either provided in isolation or together with positive feedback, is more effective during the early stages than in the later stages of a tournament. Using a large-scale managerial survey, the authors show that higher participation intensity leads to higher idea quality and better business performance. The effect of participation intensity on idea quality is stronger than the effect of number of ideas and as strong as the effect of number of participants on idea quality.

Advertising non-premium products as if they were premium: The impact of advertising up on advertising elasticity and brand equity

Non-premium brands occasionally emulate their premium counterparts by using ads that emphasize premium characteristics such as superior performance and exclusivity. We define this practice as “advertising up” and develop hypotheses about its short- and long-term impact on advertising elasticity and brand equity respectively. We test the hypotheses in two large-scale empirical studies using a comprehensive dataset from the automotive industry that includes, among others, the content of 2317 television ads broadcast over a period of 45 months. The results indicate that advertising up increases (decreases) short-term advertising elasticity for non-premium products with a low (high) market share. The results also show that an intensive use of advertising up over time leads to long-term improvements (reductions) in brand equity for expensive (cheap) non-premium products. Furthermore, an inconsistent use of advertising up leads to reductions in brand equity. The results imply that managers of non-premium products with a low market share can use advertising up to increase advertising effectiveness in the short run. However, advertising up will only generate long-term improvements in brand equity for expensive non-premium products. Finally, to avoid long-term reductions in brand equity, advertising up should be consistently used over time.

Ivan Guitart, Jorge Gonzalez, and Stefan Stremersch

Non-premium brands occasionally emulate their premium counterparts by using ads that emphasize premium characteristics such as superior performance and exclusivity. We define this practice as “advertising up” and develop hypotheses about its short- and long-term impact on advertising elasticity and brand equity respectively. We test the hypotheses in two large-scale empirical studies using a comprehensive dataset from the automotive industry that includes, among others, the content of 2317 television ads broadcast over a period of 45 months. The results indicate that advertising up increases (decreases) short-term advertising elasticity for non-premium products with a low (high) market share. The results also show that an intensive use of advertising up over time leads to long-term improvements (reductions) in brand equity for expensive (cheap) non-premium products. Furthermore, an inconsistent use of advertising up leads to reductions in brand equity. The results imply that managers of non-premium products with a low market share can use advertising up to increase advertising effectiveness in the short run. However, advertising up will only generate long-term improvements in brand equity for expensive non-premium products. Finally, to avoid long-term reductions in brand equity, advertising up should be consistently used over time.

Predicting the consequences of marketing policy changes: A new data enrichment method with competitive reactions

Eelco Kappe, Sriram Venkataraman, and Stefan Stremersch

This article introduces a new data enrichment method that combines revealed data on consumer demand and competitive reactions with stated data on competitive reactions to yet-to-be-enacted, unprecedented marketing policy changes. The authors extend the data enrichment literature to include stated competitive reactions, collected from subject-matter experts through a conjoint experiment. The authors apply their method to investigate hypothetical and unprecedented sales force policy changes of pharmaceutical companies. The results from the data enrichment method have high face validity and lead to various unique insights compared with using revealed data only. The authors find that only a very large sales force decrease initiated by the market leader triggers all competitors to decrease their sales force as well, leading to substantial profit increases for each firm. With respect to sales force allocation, when competitors decrease their sales force, they mainly decrease the reach of detailing across doctors, rather than decreasing the number of details to the most-visited doctors. The proposed data enrichment method provides managers with a powerful tool to, ex ante, predict the consequences of unprecedented marketing policy changes.

 

What to Stress, to Whom and Where? A Cross-Country Investigation of the Effects of Perceived Brand Benefits on Buying Intentions.

Ralf van der Lans, Yvonne van Everdingen and Valentyna Melnyk

This paper investigates cross-country differences in the importance of four brand benefits that are commonly stressed in international positioning strategies—quality, uniqueness, leading position,
and growing popularity—in determining brand purchase intentions. It also investigates how these effects are moderated by country characteristics, consumer characteristics, and perceptions about competing brands’ benefits, as well as whether they are stable across product categories. To achieve this, we developed a hierarchical Bayesian model that recognizes the ordinal nature of the measurement of purchase intentions and captures scale usage differences in a parsimonious way. The model is estimated using a unique multi-continent, multi-category data set across 19,682 respondents from 25 countries. In total 337 brands across six product categories (fast food, beer, designer brands, athletic shoes and apparel, mobile phones, photography) and two service categories (airlines, credit cards) were assessed. The results show that on average intrinsic benefits (i.e., quality and uniqueness), are most important in determining purchase intentions. The strengths of these effects are significantly influenced by culture and become weaker if more competing brands are perceived to possess these benefits. Companies are therefore advised to trade-off between positioning their brand along a brand benefit that appeals to a country, while ensuring that this positioning is distinct from the positioning of competing brands. If a multinational company prefers using one global strategy, then focusing on quality is recommended.

Drug Detailing and Doctors’ Prescription Decisions: The Role of Information Content in the Face of Competitive Entry

Eelco Kappe and Stefan Stremersch

We study the effects of information content in 59,814 pharmaceutical sales calls on doctors’ prescription decisions for statins, in the face of entry of competing brands and generics, using a hierarchical Bayesian distributed lag model. We conclude that adding information content to the prescription response model improves the in- and out-of-sample performance of the model. In the first six months following generic entry, it is more effective for incumbent brands to detail on drug contraindications and indications, compared to other periods, to positively differentiate from generics. In the first six months following branded entry, it is less effective for incumbent brands to detail on drug indications and costs, given increased competitive clutter. We also document substantial heterogeneity among doctors in their response to information content. Our model is helpful for analysts to more accurately assess the effectiveness of detailing. Our empirical results are also informative for drug manufacturers as they set or change their messaging policies in response to entry and help firms to tailor their message content at the doctor level.

Optimal targeting of advertisement for new products with multiple consumer segments

Armed with improved targeting technology, firms are increasingly interested in optimizing their advertising dollars through consumer segment-specific targeting, particularly while introducing new products. That task becomes especially important in markets with distinct consumer segments—the early market and the main market—that affect each other’s adoption behavior. In this study, in contrast to prior normative studies that assume a single-segment market structure, we derive dynamic optimal advertising and segment-specific targeting strategies for firms facing a two-segment market structure. We allow for mutual demand interactions between the two segments, and for the diffusion parameters, advertising sensitivity, and cost of targeting to differ across the segments. We model the effect of advertising as a logarithmic function that accounts for diminishing marginal returns. Among our key findings: From profit optimization perspective, our two-segment model outperforms the single-segment model under multiple diffusion dynamics contexts—especially for the ‘bimodal chasm’ and the ‘early dip followed by bell-shaped’ type diffusion patterns—even when the cost of targeting the early market is relatively high. Our numerical analyses indicate that the optimal share of advertisement targeted to the early market segment at launch needs to be much higher than the share of the early market segment in the population. Advertising sensitivity, relative cost of targeting the early market, and the proportion of early market consumers in the population have the greatest effects on the optimal time to transition the targeted advertising spending from the early to the main market segment.

Vijay Ganesh Hariharan, Debabrata Talukdar, Changhyun Kwon

Armed with improved targeting technology, firms are increasingly interested in optimizing their advertising dollars through consumer segment-specific targeting, particularly while introducing new products. That task becomes especially important in markets with distinct consumer segments—the early market and the main market—that affect each other’s adoption behavior. In this study, in contrast to prior normative studies that assume a single-segment market structure, we derive dynamic optimal advertising and segment-specific targeting strategies for firms facing a two-segment market structure. We allow for mutual demand interactions between the two segments, and for the diffusion parameters, advertising sensitivity, and cost of targeting to differ across the segments. We model the effect of advertising as a logarithmic function that accounts for diminishing marginal returns. Among our key findings: From profit optimization perspective, our two-segment model outperforms the single-segment model under multiple diffusion dynamics contexts—especially for the ‘bimodal chasm’ and the ‘early dip followed by bell-shaped’ type diffusion patterns—even when the cost of targeting the early market is relatively high. Our numerical analyses indicate that the optimal share of advertisement targeted to the early market segment at launch needs to be much higher than the share of the early market segment in the population. Advertising sensitivity, relative cost of targeting the early market, and the proportion of early market consumers in the population have the greatest effects on the optimal time to transition the targeted advertising spending from the early to the main market segment.

Introduction to the IJRM Special Issue on Marketing and Innovation

Gui Liberali, Eitan Muller, Roland T. Rust and Stefan Stremersch

This special issue of the International Journal of Research in Marketing results from the inaugural edition of bi-annual joint symposia of the American Marketing Association (AMA) and the European Marketing Academy (EMAC). The Erasmus School of Economics (Erasmus Center for Marketing and Innovation, ECMI) organized this inaugural symposium on May 27th and 28th, 2014, in the context of its Centennial
celebrations. The future organizers are the Wharton School (for the 2016 edition) and INSEAD (for the 2018 edition). These symposia are meant to address a topic of high relevance to the marketing community, thus changing over future meetings.

For the Erasmus inaugural meeting we chose Innovation and Marketing as a topic for the symposium. Keynote speakers on the practitioner side included among others, Paul Polman (CEO of Unilever), Jean Francois Van Boxmeer (CEO of Heineken), Jacques Van den Broek (CEO of Randstad), and Frans Muller
(CEO of Delhaize). Academically, keynotes were given by Jan Peter Balkenende (Erasmus University and former prime minister of the Netherlands), Eric Bradlow (Wharton), Glen Urban (MIT), Nirmalya Kumar (LBS and Tata), and Jagdish Sheth (Emory).

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Unraveling scientific impact: Citation types in marketing journals

The number of citations a paper receives is the most commonly used measure of scientific impact. In this paper, we study not only the number but also the type of citations that 659 marketing articles generated. We discern five citation types: application, affirmation, negation, review and perfunctory mention (i.e., citing an article only indirectly without really using it). Prior literature in scientometrics recognizes that the former three types, on average, signal a higher level of scientific indebtedness than the latter two types. In our sample, these three types of citation represent only 15% of all citations. We also find different determinants of citation behavior across citation types. Across the 49 determinants we included, only 13 have the same effect across all citation types, of which only 5 are statistically significant across all citation types. For instance, we find a significant inverted U-effect of challenging commonly held beliefs on citation counts, but only for three of the citation types: affirmation, review and perfunctory mention. Our results encourage scientific stakeholders to move beyond mere citation counts to assess a paper's or a scholar's scientific contribution, as well as to devote greater attention to the citation process itself.

Stefan Stremersch, Nuno Camacho, Sofie Vanneste, Isabel Verniers

The number of citations a paper receives is the most commonly used measure of scientific impact. In this paper, we study not only the number but also the type of citations that 659 marketing articles generated. We discern five citation types: application, affirmation, negation, review and perfunctory mention (i.e., citing an article only indirectly without really using it). Prior literature in scientometrics recognizes that the former three types, on average, signal a higher level of scientific indebtedness than the latter two types. In our sample, these three types of citation represent only 15% of all citations. We also find different determinants of citation behavior across citation types. Across the 49 determinants we included, only 13 have the same effect across all citation types, of which only 5 are statistically significant across all citation types. For instance, we find a significant inverted U-effect of challenging commonly held beliefs on citation counts, but only for three of the citation types: affirmation, review and perfunctory mention. Our results encourage scientific stakeholders to move beyond mere citation counts to assess a paper’s or a scholar’s scientific contribution, as well as to devote greater attention to the citation process itself.

The relationship between DTCA, drug requests, and prescriptions: Uncovering variation in specialty and space

Patients increasingly request their physicians to prescribe specific brands of pharmaceutical drugs. A popular belief is that requests are triggered by direct-to-consumer advertising (DTCA). We examine the relationship between DTCA, patient requests, and prescriptions for statins. We find that although the effect of requests on prescriptions is significantly positive, the mean effect of DTCA on patient requests is negative, yet very small. More interestingly, both effects show substantial heterogeneity across physicians, which we uncover using a hierarchical Bayes estimation procedure. We find that specialists receive more requests than primary care physicians but translate them less into prescriptions. In addition, we find that the sociodemographic profile of the area a physician practices in moderates the effects of DTCA on requests and of requests on prescriptions. For instance, physicians from areas with a higher proportion of minorities (i.e., blacks and Hispanics) receive more requests that are less triggered by DTCA and are accomodated less frequently than physicians from areas with a lower proportion of minorities. Our results challenge managers to revisit the role of DTCA in stimulating patient requests. At the same time, they may trigger public policy concerns regarding physicians' accommodation of patient requests and the inequalities they may induce.

Stefan Stremersch, Vardit Schwartz-Landsman, Sriram Venkataraman

Patients increasingly request their physicians to prescribe specific brands of pharmaceutical drugs. A popular belief is that requests are triggered by direct-to-consumer advertising (DTCA). We examine the relationship between DTCA, patient requests, and prescriptions for statins. We find that although the effect of requests on prescriptions is significantly positive, the mean effect of DTCA on patient requests is negative, yet very small. More interestingly, both effects show substantial heterogeneity across physicians, which we uncover using a hierarchical Bayes estimation procedure. We find that specialists receive more requests than primary care physicians but translate them less into prescriptions. In addition, we find that the sociodemographic profile of the area a physician practices in moderates the effects of DTCA on requests and of requests on prescriptions. For instance, physicians from areas with a higher proportion of minorities (i.e., blacks and Hispanics) receive more requests that are less triggered by DTCA and are accomodated less frequently than physicians from areas with a lower proportion of minorities. Our results challenge managers to revisit the role of DTCA in stimulating patient requests. At the same time, they may trigger public policy concerns regarding physicians’ accommodation of patient requests and the inequalities they may induce.

Variable selection in international diffusion models

Prior research comes to different conclusions as to what country characteristics drive diffusion patterns. One prime difficulty that may partially explain this divergence between studies is the sparseness of the data, in terms of the periodicity as well as the number of products and countries, in combination with the large number of potentially influential country characteristics. In face of such sparse data, scholars have used nested models, bivariate models and factor models to explore the role of country covariates. This paper uses Bayesian Lasso and Bayesian Elastic Net variable selection procedures as powerful approaches to identify the most important drivers of differences in Bass diffusion parameters across countries. We find that socio-economic and demographic country covariates (most pronouncedly so, economic wealth and education) have the strongest effect on all diffusion metrics we study. Our findings are a call for marketing scientists to devote greater attention to country covariate selection in international diffusion models, as well as to variable selection in marketing models at large.

Stefan Stremersch, Sarah Gelper

Prior research comes to different conclusions as to what country characteristics drive diffusion patterns. One prime difficulty that may partially explain this divergence between studies is the sparseness of the data, in terms of the periodicity as well as the number of products and countries, in combination with the large number of potentially influential country characteristics. In face of such sparse data, scholars have used nested models, bivariate models and factor models to explore the role of country covariates. This paper uses Bayesian Lasso and Bayesian Elastic Net variable selection procedures as powerful approaches to identify the most important drivers of differences in Bass diffusion parameters across countries. We find that socio-economic and demographic country covariates (most pronouncedly so, economic wealth and education) have the strongest effect on all diffusion metrics we study. Our findings are a call for marketing scientists to devote greater attention to country covariate selection in international diffusion models, as well as to variable selection in marketing models at large.

Aggregate Impact of Different Brand Development Strategies

Current branding literature investigates the spillover effects and extension effects due to the introduction of product extensions. However, no study so far has evaluated the aggregate market impact of these effects across different brand development strategies or accounted for the strategic decision to introduce the extension. It is important to examine the above given the significant investments and the high failure rates associated with the introduction of new product extensions. In this study, we develop an analytical framework that derives revenue outcome due to an extension introduction as a function of spillover and extension effects. We empirically estimate the above effects through a Bayesian endogenous switching model that jointly models market shares of the extension and its parent brand along with the strategic decision to introduce the extension and the endogeneity in prices. By using a data set that covers 155 extensions introduced across 20 U.S. geographic markets, we obtain several new generalizable empirical insights. Our results show that spillover effects are higher for brand extensions, whereas line extensions benefit through larger extension effects. We find that vertically differentiating a line extension in terms of increased quality mitigates its negative spillover effects. The addition of a new brand name (i.e., sub-branding) lowers spillover effects for line extensions, whereas it increases the market performance for brand extensions. Our findings provide several strategic implications for manufacturers to successfully introduce and manage product extensions.

Vijay Ganesh Hariharan, Ram Bezawada, Debabrata Talukdar

Current branding literature investigates the spillover effects and extension effects due to the introduction of product extensions. However, no study so far has evaluated the aggregate market impact of these effects across different brand development strategies or accounted for the strategic decision to introduce the extension. It is important to examine the above given the significant investments and the high failure rates associated with the introduction of new product extensions. In this study, we develop an analytical framework that derives revenue outcome due to an extension introduction as a function of spillover and extension effects. We empirically estimate the above effects through a Bayesian endogenous switching model that jointly models market shares of the extension and its parent brand along with the strategic decision to introduce the extension and the endogeneity in prices. By using a data set that covers 155 extensions introduced across 20 U.S. geographic markets, we obtain several new generalizable empirical insights. Our results show that spillover effects are higher for brand extensions, whereas line extensions benefit through larger extension effects. We find that vertically differentiating a line extension in terms of increased quality mitigates its negative spillover effects. The addition of a new brand name (i.e., sub-branding) lowers spillover effects for line extensions, whereas it increases the market performance for brand extensions. Our findings provide several strategic implications for manufacturers to successfully introduce and manage product extensions.

Incorporating Mental Representations in Discrete Choice Models of Travel Behaviour: Modelling Approach and Empirical Application

We introduce an extension of the discrete choice model to take into account individuals' mental representation of a choice problem. We argue that, especially in daily activity and travel choices, the needs of an individual have an influence on the benefits he or she pursues in the choice of an alternative. Activated benefits and mental costs determine which attributes are considered in evaluating alternatives. The extended model considers the formation of a mental representation of a choice problem as an integral part of the choice process. We show how formation of a mental representation and making a choice can be modeled jointly in an integrated random utility maximization framework. We further show how the integrated model can be estimated based on combined observations of mental representations and choice outcomes using maximum likelihood estimation. A comparative analysis shows that observations of the mental representations may significantly improve predictions and enhance insights into situation-dependent motivations underlying preferences. We illustrate the approach using a data set that involves measurements of mental representations and choice behavior in the area of transport mode choice.

Benedict Dellaert, Theo Arentze, Casper Chorus

We introduce an extension of the discrete choice model to take into account individuals’ mental representation of a choice problem. We argue that, especially in daily activity and travel choices, the needs of an individual have an influence on the benefits he or she pursues in the choice of an alternative. Activated benefits and mental costs determine which attributes are considered in evaluating alternatives. The extended model considers the formation of a mental representation of a choice problem as an integral part of the choice process. We show how formation of a mental representation and making a choice can be modeled jointly in an integrated random utility maximization framework. We further show how the integrated model can be estimated based on combined observations of mental representations and choice outcomes using maximum likelihood estimation. A comparative analysis shows that observations of the mental representations may significantly improve predictions and enhance insights into situation-dependent motivations underlying preferences. We illustrate the approach using a data set that involves measurements of mental representations and choice behavior in the area of transport mode choice.

The effect of customer empowerment on adherence to expert advice

Customers often receive expert advice related to their health, finances, taxes or legal procedures, to name just a few. A noble stance taken by some is that experts should empower customers to make their own decisions. In this article, we distinguish informational from decisional empowerment and study whether empowerment leads customers to adhere more or less to expert advice. We empirically test our model by using a unique dataset involving 11,735 respondents in 17 countries on four continents. In the context of consumer adherence to doctors' therapy advice (patient non-adherence to doctor advice may cost about $564 billion globally to the pharmaceutical industry every year), we find that decisional empowerment lowers adherence to expert advice. The effect of informational empowerment varies predictably across cultures and is only universally beneficial when initiated by the customer. These findings have important implications for professional service providers.

Nuno Camacho, Martijn de Jong, Stefan Stremersch

Customers often receive expert advice related to their health, finances, taxes or legal procedures, to name just a few. A noble stance taken by some is that experts should empower customers to make their own decisions. In this article, we distinguish informational from decisional empowerment and study whether empowerment leads customers to adhere more or less to expert advice. We empirically test our model by using a unique dataset involving 11,735 respondents in 17 countries on four continents. In the context of consumer adherence to doctors’ therapy advice (patient non-adherence to doctor advice may cost about $564 billion globally to the pharmaceutical industry every year), we find that decisional empowerment lowers adherence to expert advice. The effect of informational empowerment varies predictably across cultures and is only universally beneficial when initiated by the customer. These findings have important implications for professional service providers.

Does direct-to-consumer advertising of pharmaceutical drugs deliver results?

Does direct-to-consumer advertising (DTCA) of pharmaceutical drugs lead to an increase in the number of prescription requests of those drugs by patients? Considering that pharmaceutical manufacturers spent US$4.3 billion on DTCA in 2010, the answer is of great significance.

Stefan Stremersch, Vardit Landsman, Sriram Venkataraman

Does direct-to-consumer advertising (DTCA) of pharmaceutical drugs lead to an increase in the number of prescription requests of those drugs by patients? Considering that pharmaceutical manufacturers spent US$4.3 billion on DTCA in 2010, the answer is of great significance.

The commercial contribution of clinical studies for pharmaceutical drugs

Pharmaceutical drugs are rigorously evaluated through clinical studies. The commercial consequences of such clinical studies, both to the promotion for and sales of drugs, are largely under-researched. The present study answers the following research questions: 1) How does the evolution of clinical study outcomes affect product sales? 2) How does the evolution of clinical study outcomes affect a firm's promotion expenditures to physicians and consumers? 3) Is the assessment of the responsiveness of sales to promotion expenditures biased when the analyst omits the role of clinical studies? We summarize a comprehensive body of clinical studies in three metrics: valence, dispersion, and volume. We extend the literature with the following findings. A higher valence and volume of clinical studies (i.e., more positive and larger number of studies) increase sales. A higher valence of clinical studies increases spending on both direct-to-consumer advertising and direct-to-physician promotion. A higher dispersion among clinical studies decreases spending on direct-to-consumer advertising. A higher volume of clinical studies has no effect on direct-to-physician promotion, but decreases direct-to-consumer advertising. Furthermore, the results show that omitting these metrics from a market response model leads to an overestimation of the responsiveness of sales to promotion expenditures.

Stefan Stremersch, Ashish Sood, Eelco Kappe

Pharmaceutical drugs are rigorously evaluated through clinical studies. The commercial consequences of such clinical studies, both to the promotion for and sales of drugs, are largely under-researched. The present study answers the following research questions: 1) How does the evolution of clinical study outcomes affect product sales? 2) How does the evolution of clinical study outcomes affect a firm’s promotion expenditures to physicians and consumers? 3) Is the assessment of the responsiveness of sales to promotion expenditures biased when the analyst omits the role of clinical studies? We summarize a comprehensive body of clinical studies in three metrics: valence, dispersion, and volume. We extend the literature with the following findings. A higher valence and volume of clinical studies (i.e., more positive and larger number of studies) increase sales. A higher valence of clinical studies increases spending on both direct-to-consumer advertising and direct-to-physician promotion. A higher dispersion among clinical studies decreases spending on direct-to-consumer advertising. A higher volume of clinical studies has no effect on direct-to-physician promotion, but decreases direct-to-consumer advertising. Furthermore, the results show that omitting these metrics from a market response model leads to an overestimation of the responsiveness of sales to promotion expenditures.

The role of trust in consumers’ brand considerations

Gaining the trust of consumers is crucial to the success of many brands. Increased trust leads to greater brand consideration, which in turn should lead to more sales. Research suggests that one way of engendering trust is by providing consumers with competitive information in a way that is seen as altruistic by being geared towards customers’ needs. However, while much theory has been written on the subject, no field experiments have been conducted to support this belief – until now.

Gui Liberali, Glen L. Urban, John R. Hauser

Gaining the trust of consumers is crucial to the success of many brands. Increased trust leads to greater brand consideration, which in turn should lead to more sales. Research suggests that one way of engendering trust is by providing consumers with competitive information in a way that is seen as altruistic by being geared towards customers’ needs. However, while much theory has been written on the subject, no field experiments have been conducted to support this belief – until now.

Consumer informedness and firm information strategy

Consumer informedness plays a critical role in determining consumer choice in the presence of information technology deployed by competing firms in the marketplace. This paper develops a new theory of consumer informedness. Using data collected through a series of stated choice experiments in two different research contexts, we examine how consumer characteristics and observed behaviors moderate the influence of price and product informedness on consumer choice. The results indicate that different types of consumer informedness amplify different consumer behaviors in specific consumer segments. In particular, we found that price informedness is more influential among consumers in the commodity segment. They exhibit greater trading down behavior, which represents stronger preferences for choosing the products that provide the best price. In contrast, product informedness is more influential among consumers in the differentiated segment. This group exhibits greater trading out behavior, involving stronger preferences for choosing products that best suit their specific needs. These results suggest that firm information strategy should take into account consumers' characteristics, their past observed behaviors, and the impact of consumer informedness. We also discuss the theoretical contributions of this research and its broader implications for firm-level information strategy.

Benedict Dellaert, Ting Li, Robert Kauffman , Eric van Heck, Peter Vervest

Consumer informedness plays a critical role in determining consumer choice in the presence of information technology deployed by competing firms in the marketplace. This paper develops a new theory of consumer informedness. Using data collected through a series of stated choice experiments in two different research contexts, we examine how consumer characteristics and observed behaviors moderate the influence of price and product informedness on consumer choice. The results indicate that different types of consumer informedness amplify different consumer behaviors in specific consumer segments. In particular, we found that price informedness is more influential among consumers in the commodity segment. They exhibit greater trading down behavior, which represents stronger preferences for choosing the products that provide the best price. In contrast, product informedness is more influential among consumers in the differentiated segment. This group exhibits greater trading out behavior, involving stronger preferences for choosing products that best suit their specific needs. These results suggest that firm information strategy should take into account consumers’ characteristics, their past observed behaviors, and the impact of consumer informedness. We also discuss the theoretical contributions of this research and its broader implications for firm-level information strategy.

Do Customers Learn from Experience?

New research suggests that a specific type of customer experience can systematically lead to worse, not better, choices by consumers. Most evidence from economic theory suggests that experienced consumers make better choices. Even when we display the behavioural biases that lead us to less optimal economic outcomes, studies show that experience can ameliorate these initial biases and steer us back towards better choices. But does this principle hold true of all experiences?

Vardit Landsman, Itai Ater

New research suggests that a specific type of customer experience can systematically lead to worse, not better, choices by consumers. Most evidence from economic theory suggests that experienced consumers make better choices. Even when we display the behavioural biases that lead us to less optimal economic outcomes, studies show that experience can ameliorate these initial biases and steer us back towards better choices. But does this principle hold true of all experiences?

Customer Designs Not in Vogue for Luxury Fashion Brands

Firms such as Muji, LEGO, Threadless, Oscar de la Renta and many others are harnessing the creative potential of their customers. In actively encouraging users to design new products companies seek to enhance their competitive advantage by reducing new product development costs, improving time-to-market, and offering user-inspired innovations that satisfy market needs.

Christoph Fuchs, Emanuela Prandelli, Martin Schreier, Darren W. Dahl

Firms such as Muji, LEGO, Threadless, Oscar de la Renta and many others are harnessing the creative potential of their customers. In actively encouraging users to design new products companies seek to enhance their competitive advantage by reducing new product development costs, improving time-to-market, and offering user-inspired innovations that satisfy market needs.

Using Preferred Outcome Distributions to Estimate Value and Probability Weighting Functions in Decisions under Risk

In this paper we propose the use of preferred outcome distributions as a new method to elicit individuals’ value and probability weighting functions in decisions under risk. Extant approaches for the elicitation of these two key ingredients of individuals’ risk attitude typically rely on a long, chained sequence of lottery choices. In contrast, preferred outcome distributions can be elicited through an intuitive graphical interface, and, as we show, the information contained in two preferred outcome distributions is sufficient to identify non-parametrically both the value function and the probability weighting function in rank-dependent utility models. To illustrate our method and its advantages, we run an incentive-compatible lab study in which participants use a simple graphical interface – the Distribution Builder (Goldstein et al. 2008) – to construct their preferred outcome distributions, subject to a budget constraint. Results show that estimates of the value function are in line with previous research but that probability weighting biases are diminished, thus favoring our proposed approach based on preferred outcome distributions.

Bas Donkers, Carlos Lourenço, Benedict Dellaert, Daniel Goldstein

In this paper we propose the use of preferred outcome distributions as a new method to elicit individuals’ value and probability weighting functions in decisions under risk. Extant approaches for the elicitation of these two key ingredients of individuals’ risk attitude typically rely on a long, chained sequence of lottery choices. In contrast, preferred outcome distributions can be elicited through an intuitive graphical interface, and, as we show, the information contained in two preferred outcome distributions is sufficient to identify non-parametrically both the value function and the probability weighting function in rank-dependent utility models. To illustrate our method and its advantages, we run an incentive-compatible lab study in which participants use a simple graphical interface – the Distribution Builder (Goldstein et al. 2008) – to construct their preferred outcome distributions, subject to a budget constraint. Results show that estimates of the value function are in line with previous research but that probability weighting biases are diminished, thus favoring our proposed approach based on preferred outcome distributions.

Complexity effects in choice experiment-based models

Many firms rely on choice experiment-based models to evaluate future marketing actions under various market conditions. This research investigates choice complexity (i.e., number of alternatives, number of attributes, and utility similarity between the most attractive alternatives) and individual differences in decision time as key factors that affect the predictive performance of models based on choice experiments, both within and between complexity conditions. The results show that complexity and individual decision time not only affect the error in consumer choice models but also consumers' decision strategy and systematic utilities. The authors introduce a complexity-adjusted mixed logit (CAM logit) model to capture the various influences of complexity in choice experiment-based models. They illustrate the consequences of complexity on choice behavior with market share predictions of the CAM logit model for different complexity conditions.

Benedict Dellaert, Bas Donkers, Arthur van Soest

Many firms rely on choice experiment-based models to evaluate future marketing actions under various market conditions. This research investigates choice complexity (i.e., number of alternatives, number of attributes, and utility similarity between the most attractive alternatives) and individual differences in decision time as key factors that affect the predictive performance of models based on choice experiments, both within and between complexity conditions. The results show that complexity and individual decision time not only affect the error in consumer choice models but also consumers’ decision strategy and systematic utilities. The authors introduce a complexity-adjusted mixed logit (CAM logit) model to capture the various influences of complexity in choice experiment-based models. They illustrate the consequences of complexity on choice behavior with market share predictions of the CAM logit model for different complexity conditions.

Trial, repeat purchase and spillover effects of cobranded extensions

This study aims to examine the factors that drive consumers' trial and repeat purchases of cobranded extensions, and the amount of spillover effects on host and ingredient brands. Design/methodology/approach: The analysis uses a comprehensive consumer transaction dataset that includes the actual introduction of four cobranded extensions. The authors develop a conceptual framework and three empirical models to explain how consumers' prior experience with the parent brands affect their trial and repeat purchase behaviors, and how their experiences with the cobranded extensions further affect parent brand purchases. Findings: The results from the study indicate that repeat purchases are higher for consumers with more joint purchase incidences in both host and ingredient categories when they have complementary features. In contrast to existing research on single-brand based extensions, it is found that host brand loyalty has a positive effect on both trial and repeat purchases when the host brand is not a market-leader.

Vijay Ganesh Hariharan, Ram Bezawada, Debabrata Talukdar

This study aims to examine the factors that drive consumers’ trial and repeat purchases of cobranded extensions, and the amount of spillover effects on host and ingredient brands. Design/methodology/approach: The analysis uses a comprehensive consumer transaction dataset that includes the actual introduction of four cobranded extensions. The authors develop a conceptual framework and three empirical models to explain how consumers’ prior experience with the parent brands affect their trial and repeat purchase behaviors, and how their experiences with the cobranded extensions further affect parent brand purchases. Findings: The results from the study indicate that repeat purchases are higher for consumers with more joint purchase incidences in both host and ingredient categories when they have complementary features. In contrast to existing research on single-brand based extensions, it is found that host brand loyalty has a positive effect on both trial and repeat purchases when the host brand is not a market-leader.

Dynamics in the international market segmentation of new product growth

Prior international segmentation studies have been static in that they have identified segments that remain stable over time. This paper shows that country segments in new product growth are intrinsically dynamic. We propose a semiparametric hidden Markov model to dynamically segment countries based on the observed penetration pattern of new product categories. This methodology allows countries to switch between segments over the life cycle of the new product, with time-varying transition probabilities. Our approach is based on penalized splines and can thus be flexibly applied to any nonstationary phenomenon, beyond the new product growth context.For the penetration of six new product categories in 79 countries, we recover the dynamic membership of each country to segments over the life cycle. Our findings reveal substantial dynamics in international market segmentation, especially at the beginning of the product life. Finally, we exploit the dynamic segments to predict the national penetration patterns of a new product before its launch and show that our forecasts outperform forecasts derived from alternate parametric and/or static methods. Our results should encourage multinational corporations to adopt dynamic segmentation methods rather than static methods.

Stefan Stremersch, Aurélie Lemmens, Christophe Croux

Prior international segmentation studies have been static in that they have identified segments that remain stable over time. This paper shows that country segments in new product growth are intrinsically dynamic. We propose a semiparametric hidden Markov model to dynamically segment countries based on the observed penetration pattern of new product categories. This methodology allows countries to switch between segments over the life cycle of the new product, with time-varying transition probabilities. Our approach is based on penalized splines and can thus be flexibly applied to any nonstationary phenomenon, beyond the new product growth context.For the penetration of six new product categories in 79 countries, we recover the dynamic membership of each country to segments over the life cycle. Our findings reveal substantial dynamics in international market segmentation, especially at the beginning of the product life. Finally, we exploit the dynamic segments to predict the national penetration patterns of a new product before its launch and show that our forecasts outperform forecasts derived from alternate parametric and/or static methods. Our results should encourage multinational corporations to adopt dynamic segmentation methods rather than static methods.