SPEAKER

Prof. Xu Zhang
Assistant Professor of Marketing
London Business School

ABSTRACT

Many digital platforms with large product assortments endorse a select group of items to facilitate user choice. However, while it seems intuitive that such endorsement may increase the sales of endorsed items, little is known about its effect on unendorsed items, and on the platform. Using data from a field experiment conducted by an online freelance platform, we examine the effect of exposure to platform endorsement on user search and purchase behavior. We find that exposure to platform endorsement increases user search and purchases not only for endorsed services, but also for unendorsed services. We link the increase in search and purchases to an increase in the perception of the quality of services offered on the platform. We further explore heterogeneity in the effect of platform endorsement and find that the effect of exposure to platform endorsement on purchase is more pronounced for users with a higher propensity to purchase. We discuss implications for platforms, merchants, and regulators.

The Conference on Behavioural Science in the Age of Smart Technology 2023 was successfully held on July 3, 2023, at the brand new HKU event venue at the heart of the city, HKU-iCube. The conference was sponsored by the HKU Business School’s Institute of Behavioural and Decision Science (IBDS) and Institute of Digital Economy and Innovation (IDEI). The objective of the conference is to create a forum for researchers from multiple disciplinaries to discuss the behavioural impact of the smart technology.

Event Highlights

Event Programme at a Glance

Opening Remarks by Professor Heshan Sun, The University of Oklahoma “When Herding Cues Backfire: Examining Contrarian Behavior in Online Service Marketplaces” Chair: Professor Yulin Fang, IDEI Director

Opening Remarks by Professor Soo Hong Chew, Southwestern University of Finance & Economics “The Role of Top-down Attention and Bottom-Up Salience in Context Sensitive Choice” Chair: Professor Echo Wan, IBDS Director

Alison Xu, Minnesota University “Order Matters: Rating Service Professionals Reduces Tipping Amount on Digital Platforms” Chair: Dr Michael Jia, IBDS Associate Director

Adelle Xue Yang, National University of Singapore “Malleable AI Aversion: A Moral Intuition Perspective”  Chair: Dr Michael Jia, IBDS Associate Director

Yang You, The University of Hong Kong “Cyber Income Inequality” Chair: Professor Yulin Fang, IDEI Director

Keynote Speech by Professor Andrew Burton-Jones, The University of Queensland “Behavioural Science in the Age of Smart Technology: Perspectives from MIS Quarterly” Chair: Professor Jack Jiang, Area Head, Innovation and Information Management

Yanli Jia, Xiamen University “How Product Display Orientation Affects Customers’ Product Satisfaction in Online Purchase: A Choice Closure Perspective” Chair: Professor Yulin Fang, IDEI Director

Hailiang Chen, The University of Hong Kong “ChatGPT vs. Google: A Comparative Study of User Behaviors and Search Performance” Chair: Professor Echo Wan, IBDS Director

Miaozhe Han, The Chinese University of Hong Kong “An Empirical Study of Algorithm-Induced Online Information Misallocation” Chair: Professor Echo Wan, IBDS Director

Organising Committee

Professor Echo WAN

Director, Institute of Behavioural and Decision Science

HKU Business School

Professor Yulin FANG

Director, Institute of Digital Economy and Innovation

HKU Business School

Professor Zhenghui Jack JIANG

Academic Area Head, Innovation and Information Management

HKU Business School

Dr Michael JIA

Associate Director, Institute of Behavioural and Decision Science

HKU Business School

Dr Yiwen ZHANG

Associate Director, Institute of Behavioural and Decision Science

HKU Business School

Event Photo Gallery

SPEAKER

SISU BMIB Research Team

ABSTRACT

Neuroscience approaches have extensive applications across various business disciplines, such as consumer behavior, organizational behavior, information systems, behavioral economics, and behavioral finance.

In this interdisciplinary seminar, the research team from the Key Laboratory of Brain-Machine Intelligence for Information Behavior (BMIB, Ministry of Education and Shanghai) at Shanghai International Studies University (SISU) will (1) introduce various cutting-edge equipment and devices including a research-dedicated 3T Siemens MRI scanner, EEG, fNIRS, TMS/tDCS, eye trackers, inter alia available in the BMIB lab that are open for business researchers to use (for measuring mental process, information processing, visual attention, etc.), (2) illustrate the applications of neuroscience approaches to business studies, and (3) discuss with HKUBS colleagues and students how neuroscience approaches can be facilitated by the BMIB lab to provide complementary evidence for existing and potential projects.

Rundown

(1) A brief introduction of the Key Laboratory of Brain-Machine Intelligence for Information Behavior at SISU by Dean Yu PAN & Prof. Fenghua WANG

(2) Flash talks on applications of neuroscience in business studies

> “Motivated Information Processing and Belief Updating: Evidences from Behavioral Experiment, Computational Modelling, and Neuroscience” by Prof. Qiang SHEN

> “Adapting Sense of Presence to Product Uncertainties in Crafting Augmented Reality Enhanced Experiences” by Prof. Hua FAN

(3) Idea exchanges between the SISU BMIB research team and HKUBS colleagues and students on leveraging neural measures to augment research projects across various business disciplines

SPEAKER

Mr. Heiman Ng

ABSTRACT

Art Prince Advisory Limited is a fine art consultancy specialising in Art and Tech exhibition curation, education programming and project management. Mr. Heiman Ng will share with us his insights on Digital Arts and engaged in an interactive discussion with the audience.

SPEAKER

Prof. Thomas Allard
Associate Professor of Marketing
Lee Kong Chian School of Business
Singapore Management University

ABSTRACT

This research documents how creating redemption tasks requiring a token (i.e., minimal) amount of effort—for instance, by asking the consumer to enter a promo code or solve a CAPTCHA to receive a discount—increases price promotion effectiveness compared to equivalent straight discounts (i.e., applied automatically). Nine studies, including two field experiments, provide robust evidence for the beneficial effect of token effort requirements on redemption rates. This counterintuitive effect occurs because the easy-to-attain redemption task induces a positive effort-based transaction utility. As such, this effect only occurs when the redemption task requires token-type effort but not when it is effortful. Our results also show that a token redemption effort can boost the promotional effectiveness of small discounts—which prior research often finds ineffective. This research offers costless and easy-to-implement managerial recommendations for effective price promotion management.

SPEAKER

Prof. Soheil Ghili
Assistant Professor of Marketing
Yale School of Management
Yale University

ABSTRACT

This paper analyzes sequential screening, a selling mechanism in which a firm price-discriminates across buyers based on how their uncertainty about their willingnesses to pay (WTP) evolve over time. We design an economical-yet-informative experiment, which was run on the pricing of flight ancillaries in collaboration with a Low-Cost Carrier (LCC) internatinal airline in India. Leveraging the experiment results, we estimate a random-effects demand model with heterogeneous uncertainty resolution. We use the model to simulate the optimal pricing policy and find that the airline should optimally commit to a 10% early-purchase discount on seat selection. More broadly, we find that early-purchase discounts (i.e., sequential screening) is optimal when customers with lower ex-ante WTP face larger uncertainty about their ex-post WTP. Further counterfactual analysis examines the impact of marginal costs, the role of commitment in the design of the pricing scheme, and a more general menu of “prices and refunds.” Our framework (i.e., experiment design and demand model) may be used to study optimal pricing and welfare for any other product that has a set consumption date and requires booking, such as flights, accommodation, and events.

SPEAKER

Prof. Yan ZHANG
Associate Professor
NUS Business School
National University of Singapore

ABSTRACT

Marketers often set prices for products with varying numerical attributes by considering the price of a base model. It is crucial to anticipate how consumers will determine their willingness-to-pay (WTP) based on these variations in numerical attributes accordingly to maximize profit. We conduct seven studies to investigate the differential sensitivity of buyers and sellers to product’s numerical information. We find that the gap between buyers’ willingness-to-pay and sellers’ willingness-to-sell (WTS) not only widens but also accelerates as the numerical attribute deviates from the base model. Furthermore, we demonstrate that this differential sensitivity is driven by buyers’ pain of paying. When individuals are evaluating values based on unit price rather than personal feelings, when they are setting prices as agents rather than for themselves, and when they set prices for products separately rather than comparing multiple products, the observed widening and accelerating gap diminishes.

SPEAKER

Prof. Kapil Tuli
Professor of Marketing
Lee Kong Chian School of Business
Singapore Management University

ABSTRACT

Exploiting the staggered state-wide adoption of the Inevitable Disclosure Doctrine (IDD), this study examines how the protection of trade secrets is likely to have a significant impact on the advertising spending of firms. The adoption of IDD offers greater protection for a firm’s trade secrets because it restricts the ability of a firm’s current employees to work for its competitors. However, at the same time it also restricts the firm’s ability to hire employees from competitors. Building on these key aspects, we argue that firms exposed to IDD legislation are likely to increase their advertising spending as they seek to raise the profile of the firm. Utilizing a staggered difference-in-differences model, we find that firms that are treated to IDD are significantly more likely to increase their advertising spending as compared to firms in the control group. Importantly, the observed effects are robust across specification choices and the use of alternative estimation methods. In addition, we find significant heterogeneity in the firm response to this exogenous shock in their legislative environment.

SPEAKER

Dr. Robert Sanders
Assistant Professor
Marketing group
UC San Diego’s Rady School of Management

ABSTRACT

We present experimental evidence that suggest that the observational price variation found in typical supermarket scanner data is insufficient to recover true price elasticities. Our field experiment generated 174,076 random, in-store price changes over the course of 11 weeks, across 736 products at 82 “treated” stores of a Midwestern supermarket chain. We compare the demand elasticity estimates derived with these experimental price changes against the elasticity estimates derived with the observational (non-experimental) price changes at 34 “control” stores from the same chain. The resulting control-store estimates are systematically more negative than the treated-store estimates: the control-store estimate exceeds the corresponding treated-store estimate by more than a factor of 4.3 for half of our specifications. The gap is even wider in the difference in differences, and we cannot reconcile it by controlling for promotions, instrumenting with the chain price or lagged prices, focusing on a short time window around each price change, focusing on base-price changes, or accounting for longer-term price effects. Our results suggest that all meaningful variation in grocery prices is tainted by endogeneity.

This is a joint seminar organized by the Institute of Digital Economy & Innovation and HKU Business School’s academic area of Marketing.

SPEAKER

Prof. Yuxin Chen
Distinguished Global Professor of Business
Dean of Business
NYU Shanghai an affiliated appointment in the Department of Marketing
NYU Leonard N. Stern School of Business

ABSTRACT

Data on individual consumers are a critical asset for online retail platforms, which enable them to use personalized query-based search algorithms to help consumers find the products they are looking for. Yet data privacy regulations have been scaling up to protect customers’ personal data, which may result in the de-personalization in search algorithms. To understand its impacts on consumer search and purchase behavior, we design and exploit a high-stake large-scale field experiment involving 4,189,498 customers with the collaboration of a world-leading online retail platform. We find decreases in customer search efficiency and market transactions due to the de-personalization of the search algorithm. Compared with the control group with personalization, customers in the de-personalized treatment group on average browse more products in the product listing returned by the search algorithm but make fewer clicks and purchases. Meanwhile, the clicks and purchases from the sponsored ads increase in the treatment group. Finally, we find evidence that customers adapt their expectations of the search results and accordingly adjust their search behaviors almost immediately upon the de-personalization of the search algorithm. The findings offer insights for platforms and regulators to understand the implications of de-personalization in search algorithms arising from the evolving privacy regulations.

MODERATOR

Prof. Jinzhao DU
Assistant Professor of Marketing,
HKU Business School