Prof. Haiyang Yang Associate Professor of Marketing Johns Hopkins Carey Business School Johns Hopkins University
ABSTRACT
How can brands make quantity discounts more attractive to consumers? This research proposes that, instead of providing only a target quantity discount (e.g., regular price: $6.99 each; buy two: $5.59 each), offering it along with an additional tier of discount (e.g., buy one: $6.79 each) can increase the likelihood that consumers take up the target quantity discount. This pattern occurs because the inclusion of the additional discount tier can lead consumers to perceive the target discount price as lower. Through a series of studies involving different consumption contexts, product categories, price points and discount levels, this research demonstrates the proposed effect, an underlying mechanism and key boundary conditions.
Prof. Dmitri Kuksov Ashbel Smith Professor Professor of Marketing Naveen Jindal School of Management The University of Texas at Dallas
ABSTRACT
More intense consumer search across firms may lead to both stronger price competition and a better match between customers and products. We show that the net result of these forces may lead to the optimality of either shorter or longer product lines, and higher or lower prices and profits depending on the distribution of the product valuations across consumers, even if lower search costs do not lead to total demand increase. We derive a general condition on the distribution under which lower search costs lead to longer product lines in the absence of the market expansion effect. In particular, when consumer search costs decrease, product lines become longer if the distribution is Exponential or Log-Normal, become shorter if the distribution is Normal, Logistic, or Gumbel-Minimum, and do not change if the distribution is Gumbel-Maximum. With uniformly distributed product values, equilibrium prices and product lines are inverted-U shaped in the search costs. If lower search costs expand the market, firms have an additional incentive to increase product line length when search costs decrease.
Prof. P.K. Kannan Associate Dean for Strategic Initiatives Dean’s Chair in Marketing Science Robert H. Smith School of Business University of Maryland
ABSTRACT
When observing a sequence of customer interactions, it is important for a firm to understand how these interactions relate to key objectives – qualified customer leads, customer conversion events, or churn. Inspired by recent development in Large Language Models (LLM), this research proposes a transformer-based framework that models the sequence of customer interactions in a way that resembles modeling a sequence of words in a sentence. Our proposed model accounts for the varying effects of an interaction when it occurs at different times and the complex interactions between the various touchpoints on other touchpoints and events. We present an application in the multi-channel marketing context where the firm observes sequences of customer-firm encounters across multiple touchpoints. We show that our model successfully predicts the next touchpoint and the evolution of conversion rate over time at the individual level, as well as the contribution of each touchpoint to the conversion event. By unraveling the patterns within rich customer interaction data, our model provides a useful tool to help managers better understand and manage the customer journey. In addition, our model has wide applicability in other areas, such as patient journeys in healthcare.
Prof. Yann Cornil Associate Professor of Marketing & Behavioural Sciences Sauder School of Business University of British Columbia
ABSTRACT
Although food marketing is often accused of increasing population obesity, the relationship between individual responsiveness to marketing and obesity has yet to be established: Are people with obesity more responsive to food marketing and, if so, is it a stable trait or can it be reversed by bariatric surgery? In our research (part of it is published, another part is in review), we studied the responses to common marketing tactics in a group of women with obesity before, 3 months, and 12 months after bariatric surgery, as well as in two control groups (lean women, and women with obesity who were not seeking any treatment). People with obesity were initially more responsive to food marketing, but bariatric surgery reduced their responsiveness down to the level of lean people. We propose that this decreased responsiveness to marketing (i.e., external influences on food choices) may be due to increased internal preferences (or decreased indifference) for various food options after surgery. Our findings provide novel insights into the role of marketing in obesity, and suggest that developing sensory and hedonic discrimination can be a pathway to decreasing the influence of marketing on food choices.
Prof. Praveen Kopalle Signal Companies’ Professor of Management & Professor of Marketing Area Chair, Marketing Tuck School of Business at Dartmouth Dartmouth College
ABSTRACT
The first part of this study examines how electric utilities and regulators can encourage residential consumers to conserve electricity during the hottest summer days and shift electricity load from the day to off-peak, nighttime hours. We analyze a two-year field experiment involving 280 Texas households that explores approaches to conservation and load-shifting to enable emission reductions and reduce generation costs. Our critical peak pricing intervention reduces electricity consumption by 14% on the peak hours of the hottest days, leading to greenhouse gas emission reductions of about 16%. A key contribution of this study is the use of high-frequency appliance-level data. We show that 74% of the critical peak response is from reducing air conditioning. In a complementary nighttime pilot program, consumers respond strongly to lower prices by programming the timing of electric vehicle charging. Our work highlights how automation can influence the consumer tradeoffs relating to effort costs, discomfort, monetary incentives, and warm glow.
In a second part, we develop a marketing-centric framework for delivering affordable, clean energy to consumers by leveraging the marketing mix to encourage a bi-directional flow of information between firms and consumers. Using our field experiment results and a decarbonization simulation, our findings point to the need for a “system-wide” solution. Specifically, we showcase the real effects of a combination of an automated solution and dynamic electricity pricing on behavior, and examine the role of dynamic prices and automation in transitioning to 100% clean electricity.
Prof. Sha Yang Ernest Hahn Professor of Marketing Professor of Marketing Marshall School of Business University of Southern California
ABSTRACT
A multi-product ad (MPA) allows an ad platform to show multiple product ads within a single ad unit. Compared to single-product ads, MPA delivers multiple ads simultaneously and thus proposes new challenges for researchers to capture consumers’ ad consumption behavior. First, ads of similar products from the same category are likely to attract more consumer attention but induce satiation. Second, there is interdependence among different ad categories. Our research is the first to comprehensively examine both within-category satiation and cross-category preference interdependence within MPA, and explores implications for advertisers and ad platforms. We use an extended multiple discrete-continuous model that accommodates substitutability/complementarity, combined with a multi-choice model to study consumer responses to MPA. Additionally, we model the platform’s ad allocation and advertisers’ bidding decisions. Our findings reveal two consumer segments with varying satiation levels in the MPA context, with complementarity existing between different categories for these segments. Through two counterfactuals, enabled by the modeling of both demand and supply, we demonstrate the value of our proposed framework in designing ad variety amidst consumer within-category satiation and cross-category interdependence. The results uncover a misalignment of welfare implications of ad variety for consumers, advertisers, and the ad platform in multi-product display advertising, offering profound insights into when ad variety benefits or hinders one or multiple stakeholders.
Prof. Jerry Jisang Han Assistant Professor of Marketing SKK Business School Sungkyunkwan University
ABSTRACT
Consumers can make consequential inferences about service providers based on subtle communication cues. The current paper proposes that relatively high (vs. low) pitched voices in marketing communications can increase perceptions of service provider warmth when warmth is an important attribute for evaluation (e.g. for warmth-related services or for consumers who value warmth in services). In turn, increased perceptions of warmth enhance consumers’ evaluation of and preference for these services. Eight studies provide support for these predictions. First, in three lab studies, the authors find that relatively higher pitched voice improves consumer response towards service providers when warmth is relevant to the category (Study 1), when consumers personally value warmth (Study 2), and when consumers subscribe to communal (vs. exchange) relationship norms (Study 3). Next, field data involving podcast evaluations (Study 4) and Kickstarter pledge data (Study 5) provide further support for this effect. The results of three Web Appendix Studies (2 lab studies, 1 field study) show consistent support. The findings contribute needed nuance to the literature on nonverbal cues in sensory marketing and provide actionable guidelines for marketing managers.
Prof. Anthony Dukes Robert E. Brooker Chair in Marketing Professor of Marketing Co-Director Initiative on Digital Competition Marshall School of Business University of Southern California
ABSTRACT
An implicit product claim is one that is suggested by the marketer, but is not overtly asserted. For example, a package may employ a minimalist design and images of nature, which the consumer uses to infer that the product is environmentally friendlier than alternatives. We build an economic framework that incorporates motivated beliefs to show how implicit product claims arise in equilibrium because of the consumer’s desire to feel positive about their choice. Our framework is then used to ask how the use of an implicit product claim affects the firm’s incentive to make tangible product improvements. For example, does an implicit product claim of environmental friendliness raise or suppress actual investment in making the product more sustainable? We locate conditions for which implicit product claims and actual product investments are either substitutable or complementary marketing tools.
Associate Professor, Department of Economics, Tsinghua University
BIO
Prof. Tracy Xiao Liu is an Associate Professor at the Department of Economics, School of Economics and Management, Tsinghua University. She studies behavioral market design and behavioral game theory, such as the design of innovative markets and transfer of learning between repeated games.
Recently, she is working on the intersection between computer science and economics. This involves collaboration with leading high-tech companies in China such as XuetangX and Tencent.
ABSTRACT
As large language models (LLMs) like GPT become increasingly prevalent, it is essential that we assess their capabilities beyond language processing. This paper examines the economic rationality of GPT by instructing it to make budgetary decisions in four domains: risk, time, social, and food preferences. We measure economic rationality by assessing the consistency of GPT decisions with utility maximization in classic revealed preference theory. We find that GPT decisions are largely rational in each domain and demonstrate higher rationality scores than those of humans reported in the literature. We also find that the rationality scores are robust to the degree of randomness and demographic settings such as age and gender, but are sensitive to contexts based on the language frames of the choice situations. These results suggest the potential of LLMs to make good decisions and the need to further understand their capabilities, limitations, and underlying mechanisms.
The China India Insights Program (CIIP) at the Yale School of Management and HKU Business School are co-organizing the 14th annual China India Insights Conference on June 20–22, 2024 (a reception on Thursday evening, June 20 and end late afternoon on Saturday, June 22). The conference will be hosted at the University of Hong Kong by Junhong Chu, in collaboration with the China India Insights Program at the Yale School of Management.
This annual conference serves as a forum for academic scholars and research practitioners from diverse disciplines to share the best available research on both consumer and firm behavior related to China and India – two of the world’s largest and fastest growing emerging markets. Research on other emerging markets is also welcome.
Researchers interested in presenting a paper should submit abstracts — one to two pages in length and double-spaced in pdf format with the pdf labeled with the last name of the presenting author. Please include the title of the paper, name, affiliation, mailing and email addresses of the authors. Please specify who will be the presenting author. Abstracts should be sent to ciip@yale.edu by February 7, 2024. Chosen presenters will be notified by February 20, 2024.
Abstracts will be reviewed by a program committee comprised of Sha Yang (University of Southern California), Hui Li (University of Hong Kong), S. Sriram (University of Michigan), Pranav Jindal (Indian School of Business), Ralf Van Der Lans (HKUST), and Shreya Kankanhalli (Cornell University).
