Rebecca Hamilton, Editor in Chief

Recently appointed Journal of Marketing Research editor designate Rebecca Hamilton is pleased to announce the selection of four coeditors to serve during her editorship, which begins July 2023: Brett R. Gordon, Raghuram Iyengar, Kapil Tuli, and Karen Page Winterich.

Brett R. Gordon, Coeditor

Brett R. Gordon is Professor of Marketing at the Kellogg School of Management at Northwestern University. His research interests include pricing, advertising, promotions, new products, and competitive strategy, often with applications in retail or digital markets. Professor Gordon studies these topics by drawing on methods from empirical industrial organization, econometrics, and machine learning. His research has appeared in scholarly journals such as American Economic Review, Journal of Political Economy, Marketing Science, Journal of Marketing Research, Management Science, Quantitative Marketing and Economics, and Journal of Marketing. He has twice won the ISMS John D. C. Little Award at Marketing Science for best paper, and he won the Robert D. Buzzell Best Paper Award from the Marketing Science Institute for contributions to marketing practice. Currently, he is an Associate Editor at Journal of Marketing Research, Management Science and Quantitative Marketing and Economics, and serves on the Editorial Review Board at Marketing Science. He is a co-founder of the Quantitative Marketing and Structural Econometrics Workshop, which helps educate graduate students on state-of-the-art empirical techniques. He previously held a faculty position at Columbia Business School and has held visiting positions at University of Chicago’s Booth School of Business and Stanford GSB. He earned his PhD in Economics from Carnegie Mellon.

Raghuram Iyengar, Coeditor

Raghuram Iyengar is the Miers-Busch W’1885 Professor and Professor of Marketing at the Wharton School, University of Pennsylvania. He serves as the faculty co-director of Wharton AI & Analytics in Business, the world’s preeminent academic research center focusing on the practice of data-driven business decision making. Professor Iyengar has an undergraduate degree in engineering from I.I.T. Kanpur, India, and a PhD in marketing from Columbia University. His research has been published in Journal of Marketing Research, Journal of Consumer Research and Marketing Science. Professor Iyengar serves on the Editorial Review Boards of Journal of Marketing, Marketing Science, and International Journal of Research in Marketing. He also serves as an Associate Editor at Journal of Marketing Research and Area Editor at Management Science and International Journal of Research in Marketing.

Kapil Tuli, Coeditor

Kapil Tuli is the Lee Kong Chian Professor of Marketing, Lee Kong Chian School of Business, Singapore Management University, where he recently served as Director, Retail Centre of Excellence. Professor Tuli received his PhD in Marketing from Goizueta Business School, Emory University. His research interests include marketing strategy, customer relationships, customer solutions, and financial impact of marketing strategy. His research has been published in Journal of Marketing, Journal of Marketing Research, Journal of the Academy of Marketing Science, Management Science, and International Journal of Research in Marketing, among others. He serves as Associate Editor for Journal of Marketing Research and International Journal of Research in Marketing, where he recently served as coeditor for the Contemporary Marketing Strategy Research: New Perspectives for the Digital Economy special issue. He also serves on the Editorial Review Board at Journal of Marketing. 

Karen Page Winterich, Coeditor

Karen Page Winterich is Gerald I. Susman Professor in Sustainability and professor of marketing at Smeal College of Business, Pennsylvania State University. She has served as an Associate Editor for the Journal of Marketing Research and the Journal of Marketing as well as the Journal of Consumer Psychology and on the Editorial Review Board at the Journal of Consumer Research, among others. Winterich has also co-edited special issues for the Journal of Consumer Psychology and the Journal of the Association for Consumer Research.  Winterich conducts research in the area of consumer behavior, with specific interests in consumers’ sustainable behaviors. Her primary research includes: investigating the effect of consumer identities on product preference and donations, strategies for increasing sustainable behavior particularly regarding disposition, recycling, and repair, and understanding the role of morality in the marketplace.  Her research is published in the Journal of Marketing Research, Journal of Marketing, and Journal of Consumer Research, among others.  Her research has received the MSI/H. Paul Root Award and the ÂÜŔňÉçąŮÍř-EBSCO Responsible Research in Marketing Award. She was named an MSI Young Scholar in 2013 as well as an MSI Scholar in 2020. Winterich is incoming President of the ÂÜŔňÉçąŮÍř’s Academic Council. She received her PhD from the University of Pittsburgh in 2007.

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The Paul E. Green Award recognizes the article in JMR that demonstrates the greatest potential to contribute to the theory, methods, and practice of marketing.  It honors the S.S. Kresge Professor Emeritus of Marketing at the Wharton School at the University of Pennsylvania. On behalf of the ÂÜŔňÉçąŮÍř, this year’s Green Award selection process was managed by Professor Michel Wedel, Distinguished University Professor at the Robert H. Smith School of Business at the University of Maryland. The committee overseeing the selection process consisted of Russ Winer (New York University), Kusum Ailawadi (Dartmouth College), and Mary Frances Luce (Duke University). ​In recognizing the winning paper, the committee made the following comment:

In their paper, “Bayesian Synthetic Control Methods,” Kim et al. significantly improve the application of synthetic control methods (SCMs) to marketing and other social science problems where the lack of a randomized control group inhibits the ability to estimate the treatment effect.  SCMs are very useful tools for such quasi-experimental research that creates a “synthetic” control unit as a weighted average of a set of controls where the weights are determined by getting as close as possible to the pre-treatment outcome in the treatment unit.  It has three limitations: restrictive constraints on the weights, no formal theory for statistical inference, and what is called the “large p, small n” sparsity problem, in which there are more parameters than observations.

The significant contribution of this paper is the use of Bayesian methods to address these three limitations. It relaxes the constraints on the weights, provides exact statistical inference, and uses shrinkage priors to solve the sparsity problem.  In addition, the authors’ methods incorporate analogs of the frequentist SCM variants used in prior research.  The authors provide computer code for their SCM approach so that it can be implemented by practitioners and other academics.  With respect to the practical applications, the example in the paper of the impact of a soda tax imposed on Washington State consumers in 2010 illustrates how their method can be applied in the real world.  Thus, the paper makes important advances both methodologically and substantively as it gives analysts a new tool to improve the measurement of the causal effects of a variety of marketing, policy, and other interventions where randomized controlled tests are either infeasible or expensive.

In addition to the winning paper, the three other excellent finalists for the award were as follows:

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Don’t text while driving.

Source: Does it matter? yes.

In 2017, the California Department of Transportation enacted a law to fine drivers who use their phones while driving. The law prohibits drivers from even having their phones in places that might block their view of the road. This regulation was put in place for people’s protection: using mobile phones while driving is the cause of 9% percent of deaths resulting from car accidents in the United States. Similarly, the U.S. government and states have responded to high rates of obesity (almost 40% percent of adult Americans are considered obese) and the dangers of smoking (around 15% of the U.S. adult population are smokers) by implementing a variety of laws to curb unhealthy eating and limiting smoking to nonpublic places. Various agencies and company have enacted many rules and regulations to ensure that people are safe and healthy. But do they work? A recent Journal of Marketing Research investigates how these regulations aimed at consumption can affect consumers’ reactions by considering their political ideology.

 Authors Caglar Irmak, Mitchel Murdak, and Vamsi Kanuri performed four studies that show that regulations enacted by governments and companies can be counterintuitive; that is, in some situations, people react to regulations differently than expected. It is essential to consider political ideology because, typically, the sources of such regulations are government agencies, and political ideology is a vital aspect of an individual’s relationship with and understanding of the government. The authors find that political conservatives are more likely to act against the new regulations when the regulations prohibit a typical behavior, like talking on a cell phone. Conservatives are also more likely to act against a warning label when its source is a governmental agency. However, liberals did not show reactance to these types of regulations.

The authors believe that the underlying reason behind these backfire effects is psychological reactance, a perceived threat to freedom. Conservatives believe in the free market and few government regulations, so when the source of the regulation is the government, they react negatively. The “implication principle” suggests that when individuals perceive a threat to their freedom, they also identify (consciously or nonconsciously) other implied threats. So, conservatives might draw implications from the government interventions that more restrictions will follow similarly in the future. Hence, when the source is highly authoritative, consumption regulations lead to high reactance.

In contrast, political liberals believe that government regulations, even though they might restrict their freedom, can be a mechanism to protect equality and increase people’s well-being. Thus, liberals are more likely to adhere to government regulations and make trade-offs between freedom and equality when evaluating government regulations. Liberals are supporters of social and economic equality devised to improve people’s safety and health. An earlier study provides a telling example: Gromet, Kunreuther, and Larrick (2013) demonstrate that liberals are more likely than conservatives to purchase high-cost energy-efficient lamps with “Protect the Environment” stickers than conservatives.

Irmak, Murdak, and Kanuri investigate the effect of message framing on products by examining two label types (warning vs. notification) in advertisements from the Food and Drug Administration (FDA) to determine if message framing affects conservatives’ reactions to the regulations. This study suggests that if the FDA displays information on products less forcefully, conservative consumers are more likely to comply with regulations.

The origination of this idea

I asked the authors how their idea for this research emerged. Their response revealed their interesting viewpoints on public initiative effectiveness. The authors realized that public initiatives were often not as effective as intended, so they wanted to see if there were simple ways to increase regulation effectiveness and positively impact people’s lives. They also added that since the dominant political ideology of different communities is widely known, it has a distinct advantage over other individual differences that are hard to measure. Messages that consider their audiences’ political ideology should perform better than generic messages, this has become more accurate as political polarization has increased, which it has done since this research project was first started in 2012.

Some insights from their methodologies

The authors of this paper used firsthand and secondary data sets in their studies. To demonstrate both internal and external validity of the empirical research findings, they used two types of studies. They have done experimental studies to illustrate internal validity (i.e., consistently observing similar results and understanding why the effect occurs). Additionally, to demonstrate external validity (i.e., that the effect occurs in real-life situations), they leveraged field data from a telecommunications firm that one of the authors was collaborating with at the time.

Study 1 tests whether consumers’ behavior is influenced by a regulation that gives law enforcement officials the authority to issue fines. The authors used three secondary data sources: hourly website traffic data, U.S. Census data, and electoral data. They extracted the number of hourly visits for every county 31 days before the regulation and 31 days after it. They were also able learn which devices were used for each visit occurred. The authors used electoral data to understand the degree of conservatism in every county by differentiating between Donald J. Trump and Hillary R. Clinton voters. By comparing consumers’ behavior before and after regulations, they found statistically significant differences in mobile usage while driving before and after the regulation among conservatives.

Various exogenous factors could affect the traffic to the firm’s webpages. Therefore, with long windows, the risk of capturing such exogenous events and the effect of interest increases, which makes the identification of the focal effect difficult. Therefore, the authors contacted the executives at the telecommunications firm and determined that the website’s traffic could not have been impacted by any exogenous events at the firm (e.g., a promotional campaign).

The first study results were validated by a following experimental study, for which almost 200 participants were hired. The participants filled out measurements for their political ideology and the perceived threat to freedom. Some people saw a regulation from state agencies, and some others saw a regulation from a federal agency. They were asked how likely they are to text or make a phone call while driving next week after seeing a regulation.

In another study, 164 participants were informed that either “the company that makes the pizza…” or “the Food and Drug Administration (FDA), which is a government-run organization, is considering new warning labels that highlight unhealthy ingredients.” They varied these sources between subjects, and they were successful in showing that intention of purchasing unhealthy food increases among more conservative participants.

In the final study, to find the difference between negative perceptions and quitting intention of electronic cigarettes while using a warning versus a notification in message framings in an advertisement by the FDA, the authors performed a study with 200 participants. Each participant was assigned to one of the conditions (i.e., one with an ad containing “warning” and the other one with an ad containing “notification” from the FDA). After seeing each ad, participants answered questions regarding their perception and quitting intentions of electronic cigarettes.

Implications for public policy makers

The research findings are useful for government agencies to be more effective in their communications while informing people about new regulations. In the United States, a significant percentage of the population is conservative, so it is of paramount salience to know how to communicate. For instance, the Centers for Disease Control and Prevention launched an awareness campaign against the opioid epidemic, and the U.S. FDA has launched a campaign to reduce tobacco-related disease using “every try counts” as its slogan. The findings of this research suggest that these two regulatory agencies should keep the sources of their messages nebulous or frame their messages as notifications rather than warnings to increase their campaigns’ effectiveness. The results demonstrate that any signal related to a warning label or a government regulation might bring unexpected and unwanted responses from politically conservative consumers.

The authors further discussed the application of this research for COVID-19 regulations. They noted that reactive behavior (e.g., rallies, business openings) against COVID-19 regulations has been common in the United States. One way to decrease this behavior is to use an ambiguous source rather than a specific government source. Messages regarding proper COVID-19 actions come from various sources (e.g., influencers, celebrities, politicians, scientists), and it is clear that messages from different sources produce better results in individual states. They also mentioned that based on this research, the fact that COVID-19 strategies and their accompanying marketing/warning efforts have been primarily driven by states and municipalities rather than the federal government (e.g., the United States has no federal mask mandate) should result in less reactance and more compliance with government initiatives if done correctly. This is because each local area can present the regulations that best meet the needs and perspectives of their unique populations. Messaging can and should be different based on the dominant political ideology of the region and other dimensions (e.g., culture). Throughout 2020, several creative solutions and partnerships have been established better to match the local community (e.g., testutah.com).

Some points for future researchers

To add to this article’s insight into how to manipulate government messages’ effectiveness by changing the framing, additional research is needed to see the effect of morally matched messages from the government to conservative consumers. Conservatively identified people are receptive to messages that favor the moral values, so the question that might arise is that what if the message from the regulatory agency is in line with their moral foundations?

Furthermore, this research used a single bipolar measure of political ideology, which considers liberalism versus conservatism. However, conservatives and liberals can differ with regard to social and economic ideologies, which are important to consider. Future research could examine how conservatives versus liberals react to government regulations regarding health issues such as abortion rights and stem-cell research.

Read the full article:

Irmak Caglar, Mitchel R. Murdock, and Vamsi K. Kanuri (2020), “,”ĚýJournal of Marketing Research, 57 (5):966–84.

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With the digital evolution, privacy and perception are becoming more prominent concerns for consumers. Our images are everywhere, thanks to the internet and social media. As a result, consumers are now facing the “face dilemma”—a trade-off between the informative and beneficial use of facial images and the harmful effect of these images being misused or used for discriminatory purposes. Previous research has shown that face perceptions significantly impact many aspects of business, including dating, social networking, employee allocation, and services. As such, using facial images can lead to concerns about privacy and discrimination. To address these concerns, (2020) have developed the contour-as-face (CaF) framework, and they highlight its effectiveness in their recent article in the Journal of Marketing Research.

Can contours help combat the face dilemma?

Yes! The authors find that using the novel CaF framework to show images of contours allows researchers and practitioners to predict how people react when they see someone’s face, without revealing the face itself (i.e., when they see a contour). When we asked the authors about the greatest strength of their research, they emphasized that their research is the first to apply the Fourier transformation technique to resolve the face dilemma. This new method enables privacy protection, combats discrimination, and allows firms to quantify the effects of holistic contour information of facial parts on various face perceptions.

Highlights from the Article

• Facial information is used by consumers and marketers to make inferences in many contexts; meanwhile, consumers are increasingly concerned about privacy and discrimination, resulting in a privacy-perception trade-off.

• The authors provide a comprehensive literature review on face perceptions in business-related contexts.

• They compare facial contour imaging with visual face images for the first time in the academic or practitioner domain.

• The authors introduce the contour-as-face (CaF) framework using novel methodology.

• Three robust empirical studies test the effectiveness of the CaF framework and demonstrate its effectiveness in a real-world context (i.e., online dating). 

Generating the Research Question

The idea for this research initially came from the authors’ observation of the face dilemma in the online dating industry: users’ dating decisions are largely determined by profile photos; however, some users are reluctant to post any facial photos due to privacy and discrimination concerns. This observation led the authors to formulate a research question to resolve the trade-off between the value of face perceptions and facial privacy protection. To identify a valid solution to the face dilemma, the authors used the principle of reduction. They sought to determine how much information could be reduced from a photographed face to inhibit recognizability while still preserving enough information for perception. After considering different options, the authors decided to remove all facial information except for the facial contours, which allowed for a rigorous modeling method using the Fourier transformation.

The Method

The authors first developed the CaF representation, which presents the contour of a facial image beside the actual face image as the visual stimulus. Then, they performed modeling on the contour-as-face image in two steps: (1) extraction of the features for the contour and (2) quantifying the effects of those facial features through machine learning techniques. To extract the features, the authors use the CD-FD (centroid distance–Fourier descriptor) method, which has been widely used in computer vision applications like image retrieval and object recognition. This technique uses the discrete Fourier transformation, which converts the contours to mathematically precise Fourier coefficients.

Next, the authors tested the effectiveness of this framework in three empirical studies. Study 1 assessed whether humans would have similar perceptions of contours versus facial images. The authors found that the CaF framework was indeed effective as a stimulus and as a modeling method. Specifically, their findings show that humans make inferences on contours consistent with those made with the corresponding face images. They also found that using the contours masked the ability to identify gender or age, thereby enhancing privacy and reducing discrimination.

Study 2 further investigated the effectiveness of the CaF framework in protecting privacy. They found that when participants were asked to pick out the faces of the corresponding contours, they were mostly unsuccessful (i.e., a success rate of 2.68%). Additionally, their findings show that it is quite difficult for humans to guess the age or gender of the contour image. Study 3 then applied the CaF framework to a real-world context using a field study methodology. The authors created an online dating site implementing their framework and found that consumers were willing to use contour images to make decisions in real life, and they appreciated the privacy that contours provided.

Managerial Implications

The CaF framework provides important implications for business practices. Specifically, it can help practitioners overcome the face dilemma by (1) protecting customers’ facial identity privacy while preserving the ability to infer useful information from the face and improving marketing effectiveness; (2) accommodating customers’ face-based preferences while masking sensitive information (e.g., age, gender) and avoiding discrimination; and (3) developing face-related recommendation systems.

The managerial implications of this research extend beyond the facial data related to areas such as dating, social networking, employee allocation, and service. The CD-FD method can also be used as a feature extraction method—a method widely used in computer vision applications such as image retrieval and object recognition. In addition to faces, it can also be used to analyze other types of contour information in business contexts, such as contours of brand logos, product designs, and package designs.

Academic Implications

The authors’ research has several substantial contributions to academic literature. First, the authors introduced a rigorous method to model face data that has never been employed in the marketing literature. Second, the authors used face contours to elicit perceptions from humans on 15 fundamental dimensions, providing a comprehensive understanding of the trade-offs between desirable (e.g., emotional state) and undesirable (e.g., age, gender) facial inferences. Finally, the authors’ CaF framework was shown to effectively address the privacy–perception trade-off associated with using facial data.

Future Research Opportunities

The authors lay the foundation for a fruitful future research stream, and in an effort to springboard upcoming work in the optimal direction, they note several promising extensions of their research:

• Exploring the use of more realistic-looking CaF representation, such as 3-D CaF representation or a representation that includes other facial parts (e.g., ears).

• Testing the CaF framework in larger-scale studies with more diverse faces/contours, which would explore the heterogeneity in how people respond to specific features in contour images of different faces using larger data sets.

• Extending the use of the CaF method to model other types of visual information in related marketing contexts, such as perceptions of brands’ visual representations (e.g., BMW’s iconic grill).

The authors hope their research stimulates further discussion regarding privacy-related problems associated with visual data in various marketing contexts and that their framework becomes a valuable tool for improving consumer welfare in business marketing. It will be exciting to see what insights will be discovered using the authors’ novel CaF framework.

Referenced article

Zhou, Yinghui, Shasha Lu, and Min Ding (2020), “,” Journal of Marketing Research, 57 (4), 1–23.

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Americans have consistently demonstrated generosity with regard to charitable donations. In fact, the United States ranks in the top five nations for giving to charities, collecting close to $300 billion in 2018. However, this constitutes around 2% of the United States’ disposable income, a rather small percentage that has been a consistent limit to U.S. donations for over 40 years. Why does this 2% giving cap exist? What factors are at play here? These questions are significant when we consider that not-for-profits are one of the most important agencies in solving social problems such as poverty, inequality, and pollution at a global level. Our society is rife with not-for-profits that are determined to make a difference in the world but are heavily reliant on their donors. Although not-for-profits take advantage of donation days and various other charitable drives that occur throughout the year, and see higher donations in times of natural disasters, they still struggle with the 2% giving cap. The impact of the current COVID situation on the global society underscores the importance of understanding the drivers of giving behavior and donations and breaking through this giving ceiling.

When someone gives to a good cause, their identity almost becomes tied to that mission. For instance, people donating to a clean water campaign might label themselves environmental activists, while people donating to an inequality campaign may consider themselves humanitarians. But in these two examples, does it matter whether a man or a woman donated to these campaigns? Does gender influence the dollar amounts donated? Shang and colleagues’ addresses these critical questions with regard to charitable donations by positioning their research between the pillars of moral identity, gender, and the role of giving behavior in reducing moral identity discrepancy (the gap between actual and ideal moral identity). The authors’ finding that women (but not men) who are primed with moral traits give approximately 20% more to charitable causes, suggesting gender differences in supporting a not-for-profit mission. Specifically, giving campaigns that shrink this gap between actual and ideal moral identity (in women) can receive more generous donations than campaigns that simply ask for donations.

We reached out to the authors to understand their motivations behind this unique study and to explore their findings in greater detail. We were curious to understand how the authors pinpointed the moral identity between men and women as being the focal point behind the study. The authors, fundamentally, were inspired by classic evolutionary theories of social agency that suggest different motivational drivers for men vs. women to interact with the world around them. For instance, women in traditional “roles” have been socialized over time and rewarded as caretakers and nurturers in their family roles. Research has found that these roles create a tendency to be more “collective.” On the other hand, men tend to be rewarded for their social capital linked to power and wealth creation, and studies show that this relates to a tendency to be more “individualistic.”^[1] This led the authors to wonder whether these differences might potentially lead women and men to respond differently to external triggers and the possible impact on their giving behaviors. The authors were also interested in whether women and men would be differentially sensitive to a moral prime that would invoke thoughts related to kindness, compassion, caring, etc. Furthermore, they wondered if this difference would lead to different experiences among women vs. men with regard to their moral image vs. desired ideal moral image (moral discrepancy). Finally, the authors wanted to examine the impact of this moral discrepancy in terms of marketplace donation behavior and philanthropic giving.

We delved further into gender differences between the giving tendencies of men and women. In the experiments conducted by the authors, donors were thanked for their donation with words of affirmation, like “kind” and “caring.” We wondered whether men were subconsciously averse to this language when describing their actions, such that they might instinctively “swat the hand” that pats them on the head for doing a good job, whereas women view those words of affirmation as encouraging words that reaffirm their groundedness in society. The authors clarified that this “swatting away,” if you will, is not out of stigma, and it may just be that men are not “tuned” to that kind of feedback in the same way women are. Thus, women do not respond in the same way. While the authors do not claim that men do not give, or will not give under other circumstances, they simply explored the differences that may be invoked as a function of exposure to certain cues that may trigger thoughts about kindness, caring, compassion, etc. The authors wanted to see if the difference between how one sees one’s moral image compared to one’s ideal moral image may change as a function of giving, and how that giving may reinforce their identity differently as a function of gender.

When the authors began to uncover the reasons why men and women differ in their giving tendencies, we thought it was wise to discuss related questions for subsequent authors who are looking to research in this area. First, we wanted to know if there might be other underlying mechanisms (apart from encouragement and upliftment) of giving behavior, for instance, social image or social impressions. The authors stressed that additional mechanisms could have to do with personal pride, or what researchers might refer to as an emotion of morality that one may experience. The authors were particularly interested in the concept of “warm glow” (feeling good about yourself because you know that you did something good) and emphasized how giving may solidify one’s status in society. For instance, people may perceive strong philanthropic givers as “established” and there may be external praise heaped upon the giver. While these are just a few possible reasons that can be explored in future research, they may also reveal robust differences in how the genders experience differential giving as a function of external and internal cues.

Second, from a methodological perspective, we wondered how the authors approached the moral identity discrepancy scale development measures. Specifically, we were interested to understand the detailed process required to develop the moral identity discrepancy scale, as well as possible challenges that researchers might encounter in this regard. The authors emphasized that while they were proud of their article in taking baby steps towards a preliminary moral discrepancy measure, more psychometric work needs to be done to develop the scale and ascertain its statistical properties. Although, there is always concern with “social desirability” when asking a person to introspect on how they see themselves as a moral being, the authors believed that the idea of measuring any identity discrepancy (where there may be internal and external factors that shrink and expand such a gap) is indeed a logical next step in research on identity more generally, and more specifically, in research in the moral domain. At the end of the day, the authors felt that the development of a scale would become an empirical question. The authors believed that a scale having robust properties would predict things in a logical and systematic fashion, in much the same way that the moral identity scale by Aquino and Reed (2002) has proven to be able to do.

In the context of donation behavior and philanthropic giving, it was difficult not to touch on the COVID-19 situation, and how that affects businesses around the world, especially not-for-profits who rely on donations to function. The article indicated that a shift in marketing to potential donors was undoubtedly necessary, and we wanted the authors’ views on whether this 2% donation cap can be solved mainly through a shift in marketing tone, for instance, centered around benefiting society at large, benefiting the community in which we operate? Furthermore, it seemed to us like donations go through ups and downs, shifting depending on the world’s events, and time of year. But we wondered whether a mentality shift, where people in our society began to look at charity giving as another monthly budget item that benefited the community they reside in, might create a more significant positive effect for both men and women.

The authors felt that these were interesting potential implications of their research, with the global COVID-19 pandemic possibly leading to very interesting shifts in market donations and giving patterns. The authors felt that this could work both ways. People viewing the global threat as a trigger might choose to give more and more often outside their close circle of moral regard. People could also view this situation in the opposite way, whereby this threat to the common good could trigger a need to protect those that are closest to them and that are most vulnerable in their inner circle. The authors believe that there are probably lots of different moderators at play, including many of the ones studied in their article. According to the authors, marketing tone will play a key role in influencing giving behavior, but so will the way in which the benefactor of the donation is framed to the potential donor.

^[1] We thought it important to clarify the authors’ position here: “We are not saying that men cannot be kind, caring, giving, nurturing, etc., but it is a matter of degree and the external things that trigger potential different amounts of giving for men vs. women might be different.”

Full Article

Shang, Jen, Americus Reed, Adrian Sargeant, and Kathryn Carpenter. “.” Journal of Marketing Research 57, no. 2 (April 2020): 375–93.

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The Weitz-Winer-O’Dell Award honors the JMR article published five years earlier that has made the most significant, long-term contribution to marketing theory, methodology, and/or practice. The award committee this year included Pradeep Chintagunta (University of Chicago), Rebecca Hamilton (Georgetown University), and Russ Winer (New York University). The committee provided the following statement about their choice of Anderson et al.’s paper for this award:

The “Harbingers of Failure” paper makes the novel prediction that the early success of a product among certain customers may have negative—rather than positive—implications for the long-term success of the product. As the authors of the paper point out, most models used to forecast the success of new products, such as the classic Bass (1969) model, assume that early sales of a product are positively correlated with its long-term success. Further, models that have given more weight to the responses of specific customer segments, such as lead users, have given more weight to positive responses among these segments. In contrast, Anderson et al. propose that retailers should interpret high sales to Harbinger customers as a negative signal for a product’s long-term (three years or more) success.

To test their predictions, the authors use both customer-level data, obtained from loyalty program members for a period of two years, and store-level transaction data, obtained from 111 individual convenience stores over a period of six years. The customer-level data identified over 8,800 new product purchases over the two years, 40% of which survived for at least three years, making them “successful new products.” By grouping customers according to the number of unsuccessful versus successful new products they purchased (their “Flop” affinity), the authors illustrate the usefulness of this classification for predicting the success of subsequent new product introductions. Tracking the purchases of customers who purchase more unsuccessful new products during an initial period allows retailers to identify other new products that are likely to fail in a subsequent period; Harbinger customers (those with high “Flop” affinity) are more likely to purchase both, even if the new products are as different as hair styling gel and cookies. 

Consistent with ´ł˛Ń¸é’s goal of publishing research that is relevant to practice, “Harbingers of Failure” has been presented at Marketing Science Institute conferences and webinars and featured in over 100 popular press articles in outlets including the New York Times, Financial Times, The Wall Street Journal, Forbes, NBC, BBC and NPR. Coverage has spanned geographic areas including the United State, the United Kingdom, Ireland, Italy, India, China, and South Africa. A follow-up paper, Simester, Tucker, and Yang’s “,” was published in the December 2019 issue (Vol. 56, No. 6) of JMR, and we look forward to more work on this topic.

Two other excellent papers were named finalists for the 2020 Weitz-Winer-O’Dell Award:

• Valeria Stourm, Eric T. Bradlow and Peter S. Fader (2015), “,” Journal of Marketing Research, 52. (2), 253–67.
• Simone Wies and Christine Moorman (2015), “,” Journal of Marketing Research, 52 (5), 694–709.

Congratulations to the authors of all three of these papers. The authors will receive the award during the awards luncheon at the ÂÜŔňÉçąŮÍř Summer Academic Conference in San Francisco (August 21-24, 2020). A special session will be devoted to the paper and other finalists at the conference as well.

References

Bass, Frank M. (1969), “A New Product Growth for Model Consumer Durables,” Management Science, 15 (5), Theory Series, 215–27.

Simester, Duncan, Catherine Tucker, and Clair Yang (2019), “,” Journal of Marketing Research, 56 (6), 1034–49.

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