Christophe Van den Bulte

Jing Peng and Christophe Van den Bulte (2024), Participation vs. Effectiveness in Sponsored Tweet Campaigns: A Quality-Quantity Conundrum, Management Science (in press).

Abstract: We investigate the participation and effectiveness of paid endorsers in sponsored tweet campaigns. We manipulate the financial pay rate offered to endorsers on the Chinese paid endorsement platform weituitui.com, where payouts are contingent on participation rather than engagement outcomes. Hence, our design can distinguish between variation in participation and variation in outcomes, even if people self-select to endorse only specific tweets. The main finding is that endorsers exhibited adverse selection: Several observed and unobserved endorser characteristics associated with a higher propensity to participate had a negative association with being an effective endorser given participation. This adverse selection results in a conundrum when trying to recruit a sizable number of high-quality endorsers. Only 9% to 17% of the endorsers were above the median in both the propensity to participate and the propensity to be effective, compared to a benchmark of 25% in the absence of any association. A simulation analysis of various targeting approaches that leverages our data of actual endorsements and outcomes shows that targeting candidate endorsers by scoring and ranking them using models taking into account adverse selection on observables improves campaign outcomes by 12% to 40% compared to models ignoring adverse selection.

Kathleen T. Li and Christophe Van den Bulte (2023), Augmented Difference-in-Differences, Marketing Science, 42 (4), pp. 746-767.

Ron Berman and Christophe Van den Bulte (2022), False Discovery in A/B Testing, Management Science, 68 (9), pp. 6762-6782. 10.1287/mnsc.2021.4207

Abstract: We investigate what fraction of all significant results in website A/B testing is actually null effects (i.e., the false discovery rate (FDR)). Our data consist of 4,964 effects from 2,766 experiments conducted on a commercial A/B testing platform. Using three different methods, we find that the FDR ranges between 28% and 37% for tests conducted at 10% significance and between 18% and 25% for tests at 5% significance (two sided). These high FDRs stem mostly from the high fraction of true null effects, about 70%, rather than from low power. Using our estimates, we also assess the potential of various A/B test designs to reduce the FDR. The two main implications are that decision makers should expect one in five interventions achieving significance at 5% confidence to be ineffective when deployed in the field and that analysts should consider using two-stage designs with multiple variations rather than basic A/B tests.

Stefan Wuyts and Christophe Van den Bulte, “Control and Coordination in B2B Networks”. In Handbook of Business-to-Business Marketing, 2nd Ed,, edited by Gay L. Lilien, J. Andrew Petersen, and Stefan Wuyts, (Cheltenham, UK: Edward Elgar, 2022)

Gila E. Fruchter, Ashutosh Prasad, Christophe Van den Bulte (2022), Too Popular, Too Fast: Optimal Advertising and Entry Timing in Markets with Peer Influence, Management Science, 68 (6), pp. 4725-4741. 10.1287/mnsc.2021.4105

Abstract: We study optimal advertising and entry timing decisions for a new product being sold in two-segment markets in which followers are positively influenced by elites, whereas elites are either unaffected or repulsed by product popularity among followers. Key decisions in such markets are not only how much to advertise in each segment over time but also when to enter the follower segment. We develop a continuous-time optimal control model to examine these issues. Analysis yields two sets of two-point boundary value problems where one set has an unknown boundary value condition that satisfies an algebraic equation. A fast solution methodology is proposed. Two main insights emerge. First, the optimal advertising strategy can be U-shaped, that is, decreasing at first to free-ride peer influence but increasing later on to thwart the repulsion influence of overpopularity causing disadoption. Second, in markets where cross-segment repulsion triggers disadoption, advertising is only moderately effective, and entry costs are high, managing both advertising and entry timing can result in significantly higher profits than managing only one of these levers. In markets without disadoption, with high advertising effectiveness or with low entry costs, in contrast, delaying entry may add little value if one already manages advertising optimally. This implies that purveyors of prestige or cool products need not deny followers access to their products in order to protect their profits, and can use advertising to speed up the democratization of consumption profitably.

Mitesh Patel, Katherine L. Milkman, Linnea Gandhi, Heather N. Graci, Dena Gromet, Hung Ho, Joseph S. Kay, Timothy W. Lee, Jake Rothschild, Modupe Akinola, John Beshears, Jonathan E. Bogard, Alison Buttenheim, Christopher F. Chabris, Gretchen B. Chapman, James J. Choi, Hengchen Dai, Craig R. Fox, Amir Goren, Matthew D. Hilchey, Jillian Hmurovic, Leslie K. John, Dean Karlan, Melanie Kim, David Laibson, Cait Lamberton, Brigitte C. Madrian, M. Meyer, Maria Modanu, Jimin Nam, Todd Rogers, Renante Rondina, Silvia Saccardo, Maheen Shermohammed, Dilip Soman, Jehan Sparks, Caleb Warren, Megan Weber, Ron Berman, Chalanda N. Evans, Seung Hyeong Lee, Christopher K. Snider, Eli Tsukayama, Christophe Van den Bulte, Kevin Volpp, Angela Duckworth (2022), A Randomized Trial of Behavioral Nudges Delivered through Text Messages to Increase Influenza Vaccination Among Patients with an Upcoming Primary Care Visit, American Journal of Health Promotion, 37 (3), pp. 324-332.

Abstract: Purpose: To evaluate if nudges delivered by text message prior to an upcoming primary care visit can increase influenza vaccination rates. Design: Randomized, controlled trial. Setting: Two health systems in the Northeastern US between September 2020 and March 2021. Subjects: 74,811 adults. Interventions: Patients in the 19 intervention arms received 1-2 text messages in the 3 days preceding their appointment that varied in their format, interactivity, and content. Measures: Influenza vaccination. Analysis: Intention-to-treat. Results: Participants had a mean (SD) age of 50.7 (16.2) years; 55.8% (41,771) were female, 70.6% (52,826) were White, and 19.0% (14,222) were Black. Among the interventions, 5 of 19 (26.3%) had a significantly greater vaccination rate than control. On average, the 19 interventions increased vaccination relative to control by 1.8 percentage points or 6.1% (P = .005). The top performing text message described the vaccine to the patient as “reserved for you” and led to a 3.1 percentage point increase (95% CI, 1.3 to 4.9; P < .001) in vaccination relative to control. Three of the top five performing messages described the vaccine as “reserved for you.” None of the interventions performed worse than control. Conclusions: Text messages encouraging vaccination and delivered prior to an upcoming appointment significantly increased influenza vaccination rates and could be a scalable approach to increase vaccination more broadly.

Katherine L. Milkman, Linnea Gandhi, Mitesh Patel, Heather N. Graci, Dena Gromet, Hung Ho, Joseph S. Kay, Timothy W. Lee, Jake Rothschild, Jonathan E. Bogard, Ilana Brody, Christopher F. Chabris, Edward Chang, Gretchen B. Chapman, Jennifer E. Dannals, Noah J. Goldstein, Amir Goren, Hal E. Hershfield, Alexander Hirsch, Jillian Hmurovic, Samantha Horn, Dean Karlan, Ariella Kristal, Cait Lamberton, M. Meyer, Allison H. Oakes, Maurice Schweitzer, Maheen Shermohammed, Joachim H. Talloen, Caleb Warren, Ashley Whillans, Kuldeep N. Yadav, Julian J. Zlatev, Ron Berman, Chalanda N. Evans, Rahul Ladhania, Jens Ludwig, Nina Mazar, Sendhil Mullainathan, Christopher K. Snider, Jann Spiess, Eli Tsukayama, Lyle Ungar, Christophe Van den Bulte, Kevin Volpp, Angela Duckworth (2022), A 680,000-Person Megastudy of Nudges to Encourage Vaccination in Pharmacies, Proceedings of the National Academy of Sciences, 119 (6). 10.1073/pnas.211512611

Abstract: Encouraging vaccination is a pressing policy problem. To assess whether text-based reminders can encourage pharmacy vaccination and what kinds of messages work best, we conducted a megastudy. We randomly assigned 689,693 Walmart pharmacy patients to receive one of 22 different text reminders using a variety of different behavioral science principles to nudge flu vaccination or to a business-as-usual control condition that received no messages. We found that the reminder texts that we tested increased pharmacy vaccination rates by an average of 2.0 percentage points, or 6.8%, over a 3-mo follow-up period. The most effective messages reminded patients that a flu shot was waiting for them and delivered reminders on multiple days. The top performing intervention included two texts delivered 3 d apart and communicated to patients that a vaccine was “waiting for you.” Neither experts nor lay people anticipated that this would be the best-performing treatment, underscoring the value of simultaneously testing many different nudges in a highly powered megastudy.

Katherine L. Milkman, Mitesh Patel, Linnea Gandhi, Heather N. Graci, Dena Gromet, Hung Ho, Joseph S. Kay, Timothy W. Lee, Modupe Akinola, John Beshears, Jonathan E. Bogard, Alison Buttenheim, Christopher F. Chabris, Gretchen B. Chapman, James J. Choi, Hengchen Dai, Craig R. Fox, Amir Goren, Matthew D. Hilchey, Jillian Hmurovic, Leslie K. John, Dean Karlan, Melanie Kim, David Laibson, Cait Lamberton, Brigitte C. Madrian, M. Meyer, Maria Modanu, Jimin Nam, Todd Rogers, Renante Rondina, Silvia Saccardo, Maheen Shermohammed, Dilip Soman, Jehan Sparks, Caleb Warren, Megan Weber, Ron Berman, Chalanda N. Evans, Christopher K. Snider, Eli Tsukayama, Christophe Van den Bulte, Kevin Volpp, Angela Duckworth (2021), A Megastudy of Text-Based Nudges Encouraging Patients to Get Vaccinated at an Upcoming Doctor’s Appointment, Proceedings of the National Academy of Sciences, 118 (20). 10.1073/pnas.2101165118

Abstract: Many Americans fail to get life-saving vaccines each year, and the availability of a vaccine for COVID-19 makes the challenge of encouraging vaccination more urgent than ever. We present a large field experiment (N = 47,306) testing 19 nudges delivered to patients via text message and designed to boost adoption of the influenza vaccine. Our findings suggest that text messages sent prior to a primary care visit can boost vaccination rates by an average of 5%. Overall, interventions performed better when they were 1) framed as reminders to get flu shots that were already reserved for the patient and 2) congruent with the sort of communications patients expected to receive from their healthcare provider (i.e., not surprising, casual, or interactive). The best-performing intervention in our study reminded patients twice to get their flu shot at their upcoming doctor’s appointment and indicated it was reserved for them. This successful script could be used as a template for campaigns to encourage the adoption of life-saving vaccines, including against COVID-19.

Pinar Yildirim, Yanhao Wei, Christophe Van den Bulte, Joy Lu (2020), Social Network Design for Inducing Effort, Quantitative Marketing and Economics, 18 (), pp. 381-417.

Abstract: Many companies create and manage communities where consumers observe and exchange information about the effort exerted by other consumers. Such communities are especially popular in the areas of fitness, education, dieting, and financial savings. We study how to optimally structure such consumer communities when the objective is to maximize the total or average amount of effort expended. Using network modeling and assuming peer influence through conformity, we find that the optimal community design consists of a set of disconnected or very loosely connected sub-communities, each of which is very densely connected within. Also, each sub-community in the optimal design consists of consumers selected such that their “standalone” propensity to exert effort correlates negatively with their propensity to conform and correlates positively with their propensity to influence others.

Ron Berman, Leonid Pekelis, Aisling Scott, Christophe Van den Bulte, p-Hacking and False Discovery in A/B Testing.