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phd hec paris - indepth knowledge - Britta Delhay

Our PhD Students Got Talent

This special issue aims to show the excellence and diversity of the research conducted by HEC Paris PhD candidates and alumni. You will find a selection of cutting-edge findings, answering crucial questions such as: Is AI a threat to human creativity? Should we listen to the Wall Street gurus? How to better manage one’s promotion? How much do we value our private data? What are ambiguity and risk attitudes? How bad is the mere presence of a phone? HEC Paris PhD Program, headed by finance professor Johan Hombert, supports its students throughout their thesis writing and job placement in the best universities and business schools, such as the MIT, Wharton and Harvard Business School. Most PhD alumni continue to collaborate with professors at HEC, thanks to the strong relationships they have developed during their journey.

Structure

Part 1
In Quest for Career Advancement: To Diversify or to Specialize?
Should I take this job? Will this new experience help me to get a promotion in future, or will I waste my time trying to master something that I am not good at? Those are questions that one would ask if proposed a job in another functional unit. Cross-functional transitions (moves between different functional units within an organization) may seem useful to boost one’s career, but what is better for long-term career advancement: to specialize or to diversify?
Part 2
A New Definition of Comparative Ambiguity Attitude
HEC Paris Ph.D. student Fan Wang unveiled a new definition of ambiguity attitude during the latest D-TEA conference on decision making, organized by HEC Paris Professor Itzhak Gilboa. This was acknowledged and congratulated by decision-theory expert Peter Wakker. In this interview, Mr Wang explains what does he brings both to the field of decision sciences and to practice.
Part 3
Understanding AI-Human Interactions to Foster Creative Effort
What comes out of our collaborations with artificial intelligence? What happens in the minds of humans who are involved in interactions with smart non-humans? Does AI change how we come up with new ideas and work together on bringing them into life? Daria Morozova, Ph.D. student at HEC Paris’s Management and Human Resources department, explains how her research on AI-human interactions can help establish best practices for creative work involving artificial intelligence. 
Part 4
How Much Consumers Value Data Privacy: Evidence from Online Borrowers
HEC Paris Ph.D. student Huan Tang was rewarded the 2020 AQR Top Finance Graduate Award. This prize rewards the six best finance Ph.D. graduates in the world. Huan works on the value that consumers place on the privacy of information in online bank lending platforms, under the supervision of Johan Hombert, HEC Paris professor of finance. In this interview, Huan explains what her latest research brings to the field of data privacy in online banking and FinTechs.
Part 5
Improving Consumer Welfare With Marketing Interventions
Fei Gao holds a Ph.D. from HEC Paris and has joined Bentley University in the U.S. as an Assistant Professor in 2020. Fei Gao’s dissertation consists of developing marketing interventions to influence consumers judgment, choice, and behaviors. He was awarded the HEC Foundation prize for the best 2020 doctorate thesis at HEC Paris. In this interview, Fei Gao explains the different interventions he studied and developed for various goals, such as altering consumers’ taste judgments of indulgent drinks and foods, reducing consumers’ portion size choices, or motivating consumers to referring products and services with a prosocial incentive scheme.
Part 6
Should You Listen to the Wall Street Gurus?
During the Covid-19 pandemic, many households started to invest in the stock market expecting to pick the winning stocks and to take advantage of the high volatility. This phenomenon has been possible thanks to the development of trading applications such as Robinhood, which provides individual investors with the opportunity to buy and sell stocks easily. Because most individual investors do not have sufficient time and financial skills, they need to find relevant information to pick stocks. While some of them use social networks such as Twitter, Stocktwits or the WallStreetBets discussions on Reddit, other investors rely on the Wall Street gurus. Is that really a good idea to listen to them?
Part 7
The Smartphone: Not the Behemoth Feared by Business and Researchers
“How bad is the mere presence of a phone?” That's the title of the research paper co-authored by Claire Linares and Anne Laure Sellier and published by the review PLoS ONE. This is the product of two years of research, involving the replication of a paper that was written eight years ago by two British psychologists Andrew K. Przybylski and Netta Weinstein. In 2013, they presented data suggesting the physical presence of a cellphone in a meeting was harmful in terms of social interaction between strangers. A conclusion now disputed by the two HEC research academics.
Part 8
Why Student Debt Relief May Fall Short of Its Good Intentions
As the U.S. staggers beneath the weight of its education debt – a crushing $1.6 trillion in 2020 – there are increasing calls for loan forgiveness. But debt forgiveness plans need to be crafted carefully or they might actually disproportionately favor high-income individuals or specific ethnic groups. A duo of Finance researchers, Sylvain Catherine of Wharton School and Constantine Yannelis of Chicago Booth School of Business, explains how to tailor such policies to better redistribute their benefits. Sylvain Catherine is a HEC Paris PhD alumnus.    

Part 1

In Quest for Career Advancement: To Diversify or to Specialize?

Human Resources
Published on:
Updated on:
October 13th, 2021

Should I take this job? Will this new experience help me to get a promotion in future, or will I waste my time trying to master something that I am not good at? Those are questions that one would ask if proposed a job in another functional unit. Cross-functional transitions (moves between different functional units within an organization) may seem useful to boost one’s career, but what is better for long-term career advancement: to specialize or to diversify?

Ivanova article - adobe

Photo Credits: Gajus on Adobe Stock

Handling new tasks in a different function* is attractive because it brings broader knowledge and better understanding of the business. Cross-functional transitions force us to deal with unusual situations and new audiences and train us to see a problem from multiple perspectives, so that we can make better decisions in future. But at the same time, they pose a significant challenge because skills that make us successful in the current job might not be relevant in a new function. Broadly speaking, experience in multiple functions may make us well-rounded individuals but also leave us dilettantes in every field that we have tried.

Should we specialize or diversify to boost our career?

To answer this question, we need to understand what knowledge and skills one acquires and loses by engaging in cross-functional rotations and what knowledge and skills are needed to perform high level jobs. Importantly, managerial skills are multidimensional: some of them depend on the function, such as domain expertise, while others are universal, such as negotiation skills or strategic thinking. To disentangle those different components, we look at two dimensions of the managerial experience: in different functions and in different managerial roles.

 

Experience in multiple functions improves one’s chances to reach higher organizational levels but might be not as beneficial earlier in one’s career.

 

From functional perspective, we found that experience in multiple functions improves one’s chances to reach higher organizational levels but might be not as beneficial earlier in one’s career. Because job complexity increases with hierarchal level, domain expertise becomes less useful at more senior levels, while the need for broader knowledge and more general skills increases. Accumulating various work experiences stimulates integrative complexity, the ability to consider and combine multiple perspectives, and improves strategic thinking, a critical competence for senior managers. However, for lower-level managers, who mostly engage in operational rather than strategic tasks, it makes more sense to specialize to deepen domain expertise, which helps managers to faster identify task-specific problems and find better solutions within their area of expertise.

 

“We look at two dimensions of the managerial experience: in different functions and in different managerial roles.” (Photo Credits: Rawpixel on Adobe Stock

 

The question is even trickier for managerial roles

First, let’s define what is a managerial role. A managerial role is a predictable set of behaviors one can observe in daily activities and associated with a particular managerial position in an organization. In other words, it is a way of managing. A manager has three major ways of managing related to action, people, and information. Let me explain.

1)    Action:

In the first way, the necessary action is performed by the direct involvement of a manager. It represents a “doer” role, which includes supervising projects, solving problems, making decisions, and negotiating deals.

2)    People:

The second way implies managing indirectly by encouraging people to take necessary action. It is a “leader” role, which involves motivating and developing people, building teams, maintaining culture, and creating useful connections. 

3)    Information:

The third way is even less direct: a manager collects, processes, and shares information, but also controls information flows to influence people and ensure that they take necessary action. It is an “administrator” role, which might be exercised by creating systems, designing structures, implementing procedures, or imposing directives. 

Although managers might have a large repertoire of roles, they tend to gravitate towards one of these types. Notably, dominant managerial roles vary across functions and hierarchical levels. Therefore, by moving cross-functionally, one may acquire experiences in either similar or different managerial roles, and these experiences may be either beneficial or harmful for potential promotion. 

We found that at the lower managerial levels, dominant managerial roles are people focused. At the higher levels, the focus shifts from managing people to direct action, while information processing is useful at all levels. These findings suggest that managers with “doer” profiles are more likely to achieve higher organizational ranks than those whose experience is concentrated in interpersonal interactions.

 

Managers with “doer” profiles are more likely to achieve higher organizational ranks than those whose experience is concentrated in interpersonal interactions.


 

Methodology


We studied organizational career histories of 422 managers in a large pharmaceutical company. We collected data on all their job transitions within the company and studied job descriptions to better understand their roles in every appointment. We classify each job in three dimensions: the functional affiliation, the managerial role, and the hierarchical grade. While functional affiliation and hierarchical grade are clearly stated in the company’s HR records and aligned with its job catalogue, managerial roles are more subtle. So we had to carefully study the job descriptions to determine what types of activities a manager performs in a particular job and to infer what role(s) he or she plays. Based on this data we calculated the level of functional specialization of each manager and statistically tested how it influences one’s chances to be promoted from lower to middle management and from middle to senior management. We also looked at managers’ experience in different types of managerial roles and identified what roles are most valuable at different managerial levels.

 

Interview with Knowledge@HEC

Based on these results, what do you recommend to someone developing a managerial career and interested in achieving higher organizational ranks?

First, build a solid foundation in one function, but when you reach the middle management rank, think about expanding your experience outside of your areas of expertise. 

When planning a cross-functional move, think about what the dominant managerial role in a new function would be. It might sound counter-intuitive, but the more your experience is concentrated in “doer” and “administrator” roles and less in “leader” roles, the more skills necessary for higher-level jobs you will develop.

What do these results mean for organizations that think about developing their future leaders through cross-functional job rotations?

Not every cross-functional move is beneficial. The best leaders grow out of specializing generalists, those who develop broad knowledge and cognitive complexity though experience in multiple functions but keep concentrating in managerial roles most valuable at higher organizational levels. Therefore, paying close attention to managerial roles when developing a job rotation program is an essential condition for its success.

 

The best leaders grow out of specializing generalists.

 

*Function means functional unit in an organization: Sales, Marketing, Finance, IT, etc. Each function is associated with different tasks and requires different skillsets. Diverse experience means experience that spans multiple functional units.

"Specializing Generalists: Job Rotations, Managerial Learning, and Promotions", by Olga Ivanova and Roxana Barbulescu, published in the Academy of Management (AoM) proceedings in 2020. Olga Ivanova and Roxana Barbulescu have received the Arnon Reichers Best Student Paper Award from the Academy of Management’s Careers Division. The paper was also finalist of the prestigious SMS Strategic Human Capital Best Interdisciplinary Paper Award.
Related topics:
Human Resources
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Part 2

A New Definition of Comparative Ambiguity Attitude

Decision Sciences
Published on:
Updated on:
June 09th, 2020

HEC Paris Ph.D. student Fan Wang unveiled a new definition of ambiguity attitude during the latest D-TEA conference on decision making, organized by HEC Paris Professor Itzhak Gilboa. This was acknowledged and congratulated by decision-theory expert Peter Wakker. In this interview, Mr Wang explains what does he brings both to the field of decision sciences and to practice.

a man and a woman question themselves - deagreez

©deagreez on AdobeStock

Can you explain your field of research?

Recently, I work in the theoretical side of decision under uncertainty, focusing on building formal frameworks and proposing elicitation methods that I think are useful for people to gain a deeper understanding of the topic. The other side of the field tries to empirically uncover patterns of behaviors that people exhibit under uncertainty.

 

External content from platform.twitter.com has been blocked.


How do you define ambiguity attitude and risk attitude?

Risk is the type of uncertainty that is precisely quantifiable, like the chance of heads when tossing a fair coin (which is 50%). In comparison, ambiguity is un-quantifiable uncertainty, like the chance of success of a truly novel business idea. Risk attitude and ambiguity attitude are usually measured in terms of how much the decision maker evaluates risky bets and ambiguity bets, respectively. The decision maker with lower evaluations is deemed more risk (and ambiguity) averse. 

 

Risk is the type of uncertainty that is precisely quantifiable, like the chance of heads when tossing a fair coin, while ambiguity is un-quantifiable uncertainty, like the chance of success of a truly novel business idea.

 

 

stick drawing of someone tossing a coin - Zdenek Sasek on AdobeStock

 

What do you bring to the field of decision sciences?

Let’s go back to the example of a novel business idea, and suppose that we want to compare the ambiguity attitudes of two venture capitalists (VC) who are interested in financing the idea. Again, the standard method suggests comparing their monetary evaluations of the idea. This is reasonable, but it has been shown that this makes sense only if the two VCs have the same risk attitude, that is, if the chance of success of the idea were precisely quantifiable, the two VCs must have the same evaluation. This strong requirement renders comparing ambiguity attitudes practically impossible.

 

I propose a method which in our example amounts to comparing the two VCs’ subjective estimates of the idea's chance of success.

 

In my research, I propose a method which in our example amounts to comparing the two VCs’ subjective estimates of the idea's chance of success. And I formally show that this method does not require a common risk attitude. Therefore, my paper establishes a separation between ambiguity attitude and risk attitude, which provides decision-theoretic support to many applications and empirical tests.

 

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Part 3

Understanding AI-Human Interactions to Foster Creative Effort

Human Resources
Published on:
Updated on:
March 11th, 2021
10 minutes

What comes out of our collaborations with artificial intelligence? What happens in the minds of humans who are involved in interactions with smart non-humans? Does AI change how we come up with new ideas and work together on bringing them into life? Daria Morozova, Ph.D. student at HEC Paris’s Management and Human Resources department, explains how her research on AI-human interactions can help establish best practices for creative work involving artificial intelligence. 

human - robot - phonlamaiphoto

©phonlamaiphoto on Adobe Stock

While many may think creativity will be a key human capacity as work processes get increasingly automated, AI-applications get more creative as well: for example, AI-painted portraits sell at exorbitant prices, pop hits feature AI-generated music, and mainstream media ‘hire’ AI-journalists to publish thousands of articles a week. How workplace AI-application will impact creative processes, crucial for innovation and organizational development, is an important question that needs rigorous scientific attention. 

portrait peint Edmond de Belamy - wikipedia

Portrait d'Edmond de Belamy by an Artificial intelligence software (Source: Christie's)

What can research bring to the field of creativity with AI?

Research can help find ways to foster creative work and innovation augmented by the numerous AI-provided capacities. We need research that explains how we can create and adapt artificial agents and arrange working processes such that employees do not have to be defensive against AI and be more creative.

By now, we have learned that many people believe that artificial agents – these are, for instance, AI-run apps like Siri or Alexa, or social robots you may see at an airport - are not suited for creative work or work that requires diplomacy and judgement skills. So, normally people would not care much about AI trying to compose a symphony or write a novel as long as they believe that humans are creatively superior. But we also know that when AI is involved in creative work – for example, generating image suggestions, or even creating logotypes at a design studio, people often reject its results and evaluate them lower even if the AI objectively performs just as well as a human. 

This is a problem because when employees believe that AI should not be creative and it turns out to be exactly that, they may feel threatened by it, fearing it might substitute them, and these feelings are normally not very conducive to creativity. In addition, when threatened, employees will try to protect themselves – after all, we want to feel that we, humans, the creative species, are unique. This hence may also hinder creative work.

How can your research help manage creative human-AI interactions?

Together with my advisor Professor Mathis Schulte, we investigate the differences in how people work on creative and non-creative tasks when they collaborate with AI, compete with it, or use results of its work as a benchmark for their own performance. We also investigate how these interactions are different from same situations in which a human counterpart is involved instead of an AI agent. 

Creative interactions with AI is a nascent area of managerial knowledge, and we are excited to be making first contributions to it. We show, for instance, that people use the same psychological mechanisms in comparing themselves to AI agents, even when they believe these agents can’t really compete with people creatively. We also show that what we believe about ourselves and about AI matters, and while some beliefs can make employees work harder on creative tasks, other may demotivate them. Knowing what these configurations are will help managers set up collaborations such that AI is used to its full capacity, and people blossom in creative work.

We show, for instance, that people use the same psychological mechanisms in comparing themselves to AI agents, even when they believe these agents can’t really compete with people creatively.

So, what main differences do you find between human-human and human-AI creative interactions?

First of all, we saw that people did not take as much time to work on a creative task – that is, they were not as effortful - when they collaborated with an AI as when they collaborated with a colleague. This was not the case for a non-creative task, in which people worked on average for the same time both with an AI and a human collaborator. To illustrate, in one of our experiments, the creative task was to come up with recycling ideas for a medical mask (this task could be, for example, a challenge in an engineering competition, or a topic for an entertaining article, which was the setting in our experiment). The non-creative task was to find recycling-related words in a word matrix that needed to be tested as a game for publishing online. 

word search matrix - HEC
Word search matrix

 

 

People were not as effortful to work on a creative task when they collaborated with an AI as when they collaborated with a colleague.

 

We also found that an AI’s performance did not matter for such a decrease in effort. In a different experiment, we asked the participants to propose ideas on how to motivate their colleagues to move more or to eat better. We then showed them either a list of nonsense ideas (which really was a text generated by an algorithm!) or a list of sensible ideas. We told the participants that the list they see was either created by an AI or by someone else who also participated in the experiment. As a result, some people saw a nonsense list of ideas and thought it was proposed by an AI, and others thought that same list was suggested by a human. Regarding the list of sensible ideas, a third group saw a sensible list that was ostensibly AI-written, and the last group thought it was a human suggestion. Then, we again asked the participants to propose ideas on one of the topics. We found that no matter whether the ideas made sense or not, participants who looked at ideas that were introduced as suggested by other people took almost half a minute longer on the second task than those who thought the ideas were AI-generated. 

Interestingly, this was also the case in the non-creative task, in which participants looked for a specific character on an old-Russian birch bark, looked at the results of work of an AI or a human, and looked for another character again. Although we did not expect them to, participants who saw the results of AI’s work, both done well and failed, took less time to work on the task in the second round. 
 

bark - HEC
“Participants looked for a specific character on an old-Russian birch bark”. (Original birch bark from “Histrf” website here.)

 

bark 1 - HEC
Birch bark in which the counterpart did the task well.

 

bark 2 - HEC
Birch bark in which the counterpart failed the task.

The results of these two experiments suggest that in many cases, especially when we think AI has no place in creative work, we might be less motivated to exert effort on it than we do when working together with another human.

 

In many cases, we might be less motivated to exert effort on creative work when there is AI participation, than we do when working together with another human.

 

So what are the conditions in which AI can motivate us try harder on a creative task? 

This we tackled in a further experiment. In it, we again had participants think about creative ideas for the use of a medical mask or medical gloves. But, unlike in the first experiment, we first subtly made half of the participants remember that creativity is what makes humans unique, while the other half did not see such a reminder. We also told the participants that either an AI or a person came up either with many creative ideas, or with only a few. The results of these manipulations were astounding: while people who were reminded that creativity is a uniquely human trait and saw that AI came up with 20 ideas worked on average for almost full five minutes, those who were also reminded of creativity uniqueness but saw that it was a person that thought of 20 ideas took only 3.5 minutes to work on the task. We also saw that when high creative performance of AI was unexpected, people were much more threatened by that AI. 

What are the implications of these findings for practice?

These findings have very important implications for practice: what should we tell employees about AI-applications that can be used in creative work to not have them disengage as they have nothing to prove against supposedly non-creative AI? How do we motivate them to perform creatively without scaring them with AI? These are the questions that I am looking forward to solving in my future work.

You’re using some unusual online services to conduct your research. Can you describe how you recruit your participants and why these services are so attractive?

People who participated in these experiments were recruited either on Prolific, which is a rather popular British service for academic research, or on Yandex.Toloka, which is a Russian service for recruitment of individual workers on mini-tasks like data markup. 

Using both platforms is a great advantage. First, I can test whether the effects I hypothesize are universal across different cultures and nationalities. Second, as specialized platforms have recently been criticized for data quality, people that I recruit at Yandex.Toloka, which is primarily used by businesses for crowdsourcing, are naïve to experimental studies and, as the majority of these tasks are quite mechanical and dull, they are intrinsically motivated to participate in my experiments – I have received quite a few messages from participants saying that they enjoyed the “task” and would be willing to do it again. Although, unfortunately for these participants, that will not be possible to not compromise the integrity of the research, I think it says much about how people are unlikely to sabotage participation.

 

I can test whether the effects I hypothesize are universal across different cultures and nationalities.

 

Finally, Yandex.Toloka offers a great gender balance in the sample (51% of participants I randomly recruit there are women), people come from different walks of life and mostly have had quite a lot of working experience – their average age is almost 36 years. These factors make the use of both services a great strength of my research design, and I thank GREGHEC Laboratory for enabling me to use them by providing research support in the form of funding that got me almost 1200 participants.

Related topics:
Human Resources
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Part 4

How Much Consumers Value Data Privacy: Evidence from Online Borrowers

Finance
Published on:
Updated on:
August 31st, 2020

HEC Paris Ph.D. student Huan Tang was rewarded the 2020 AQR Top Finance Graduate Award. This prize rewards the six best finance Ph.D. graduates in the world. Huan works on the value that consumers place on the privacy of information in online bank lending platforms, under the supervision of Johan Hombert, HEC Paris professor of finance. In this interview, Huan explains what her latest research brings to the field of data privacy in online banking and FinTechs.

mosaique of people - fizkes-AdobeStock

 ©fizkes on Adobe Stock

Can you explain your recent research about the value of privacy in online bank loaning?

My recent research paper, “The Value of Privacy: Evidence from Online Borrowers”, studies the monetary value consumers attach to the privacy of their personal data. Whether and how much consumers value data privacy are not obvious questions. For example, previous studies based on lab experiments and survey data often find small to zero value for privacy. This is commonly referred to as the “privacy paradox”, i.e., the claimed intentions to protect privacy divert from how people actually behave online. 

 

I investigate this question in a real life context, where online borrowers have to relinquish personal data in exchange for consumer loans.

 

I investigate this question in a real life context, where online borrowers have to relinquish personal data in exchange for consumer loans. Because there is no official credit score in China, online lending platforms commonly require applicants to disclose extensive amount of information, in order to assess their creditworthiness. This implies that individuals borrowing from such platforms face a clear tradeoff between data privacy and credit access. In this context, their preferences for privacy can be truthfully revealed by their actual choices.

How do you quantify the monetary value of privacy?

To quantify the monetary value of privacy, I exploit large-scale field experiments, which involve around 320,000 participants, on a major Chinese peer-to-peer lending platform. These experiments randomly vary the amount of information required from applicants and the cost of borrowing. Applicants’ decision to disclose or not then truthfully reveals their preferences for privacy. In particular, the experiments allow me to measure applicants’ sensitivities to disclosure requirements and to cost of borrowing. By contrasting these two sensitivities, I back out the monetary value of privacy. The $33 value in the headline result can be interpreted as the fee reduction required to exactly offset the drop in loan demand cased by additional data questions in the application procedure.

What have you found? 

The headline result is that online borrowers in China are willing to share their social network ID and employer contact in exchange for a $33 reduction in loan origination fees. This is a non-trial amount considering that it represents 70% of the average daily salary in China. 

In addition, the platform makes 10% less in expected revenue by requiring applicants to disclose these additional data. This is because such data policy discourages a significant fraction of applicants from completing the applications.

These results suggest that maybe there is no “privacy paradox” after all. When we measure the value of privacy in a real-life context, the number can be far above zero. This paper also contributes to the ongoing debates about whether the recent privacy protection regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), benefit consumers or not.

california consumer privacy act
The California Consumer Privacy Act of 2018 (CCPA) gives consumers more control over the personal information that businesses collect about them. (Photo Credit: ©hafakot on Adobe Stock)

What are the implications for FinTech companies and for customer’s privacy? 

A key innovative aspect of the FinTech business model is to use customer data to generate revenue, either by using the data to improve the risk model, by profiling customers and sending them targeted advertising, or by selling the data to third parties. The overall impact of data collection on firm profit depends on how much consumers value data privacy and how useful the data is for generating revenue.


The overall impact of data collection on firm profit depends on how much consumers value data privacy and how useful the data is for generating revenue.


My paper shows that there are cases where collecting more data is socially inefficient. This is when the data items are valued to a large extent by consumers but have little economic benefit for the platforms. Therefore, it is a win-win situation if FinTech firms can identify such data items. The framework provided in this paper can be easily generalized and exploited by firms to conduct this type of analysis.
 

My research paper shows that there are cases where collecting more data is socially inefficient.
 

A word by Professor Johan Hombert, Huan Tang’s thesis supervisor

Huan’s research on privacy is making an impact because it provides a methodology to put a number on how much individuals value privacy. For example, Huan has been able to quantify that borrowers on a Chinese peer-to-peer lending platform needs to be given more advantageous loan terms worth $33 in exchange for revealing their ID on Tencent QQ, the Chinese equivalent of WhatsApp. 

Researchers previously calculated such numbers using data from surveys and lab experiments. However, such data suffer from well-known methodological problems such that results derived from these data can only be taken with a grain of salt. Instead, Huan’s methodology rely on “field data”, that is, data from actual borrowers taking actual loans, which are considerably more reliable, especially for quantitative analysis. 

Huan’s methodology can be used by FinTech platforms and more generally by B2C internet platforms to assess how much business they could gain by optimizing the personal information they require from customers. 
 
The HEC Paris Finance Department is proud to see the impact Huan’s research is making. Huan is now joining the London School of Economics as an assistant professor of finance, thereby continuing the exceptional track record of placement of HEC finance Ph.D. graduates (in recent years, HEC finance Ph.D. graduates were hired by universities such as MIT, Harvard Business School, Princeton and Wharton). 

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Part 5

Improving Consumer Welfare With Marketing Interventions

Marketing
Published on:
Updated on:
May 18th, 2021

Fei Gao holds a Ph.D. from HEC Paris and has joined Bentley University in the U.S. as an Assistant Professor in 2020. Fei Gao’s dissertation consists of developing marketing interventions to influence consumers judgment, choice, and behaviors. He was awarded the HEC Foundation prize for the best 2020 doctorate thesis at HEC Paris. In this interview, Fei Gao explains the different interventions he studied and developed for various goals, such as altering consumers’ taste judgments of indulgent drinks and foods, reducing consumers’ portion size choices, or motivating consumers to referring products and services with a prosocial incentive scheme.

food delivery app - rido adobe stock

©rido on Adobe Stock

First, you find that shapes can alter taste judgments. How and when shape–taste correspondences can be applied in marketing designs?

In my first essay, I study whether, how, and when correspondences between marketing techniques and senses affect downstream judgments. Six experiments that investigated shape–taste correspondences show that whether the correspondences influence downstream taste judgments depends on the strength of association in memory between the shape and the taste. 

I find that the shape of a logo (angular vs. rounded) for a bottled water (sparkling, still) or the shape of the product itself (chocolate bar) influences judgments of the water’s carbonation and smoothness and the chocolate’s sweetness and bitterness. 

However, these effects occur only if the shape–taste associative strengths reach a sufficient threshold (application threshold), even if the correspondences have surpassed the activation threshold (statistical significance). The effects are not observable in very young children because they have not yet established shape–taste correspondences, but the associative strengths increase with age, and eventually affect downstream judgments. These processes are highly automatic, occurring even when visuospatial working memory is impaired. Marketers can apply these findings to design packaging that will influence consumers’ expectations and perceptions of product attributes.

marketing experiments
“Making sure the associative strengths of shape–taste correspondences reach the critical application threshold is the key for marketers to leverage product or logo shapes to alter consumer taste judgments.”

 

You also develop a technique to reduce consumers’ choices of food portion sizes. Can you explain what this technique is?

I develop a behavioral intervention aimed at reducing portion size choices based on a theory called “conceptual metaphor theory”. In six experiments, we show that the simple sequential presentation of two food images that move from partial to whole (e.g., a pizza with one vs. no missing pieces) makes people choose a smaller portion size, compared to all other possible sequences. This effect occurs because the partial-to-whole sequence activates the metaphorical concept of fullness, which transfers to judgments of appetitive fullness (called a “metaphor transfer effect”). In other words, seeing the food shape progressing from partial to whole makes people associate with the judgment’s feeling of satiety, and hence decrease the appetite. 

 

food delivery app - HEC PhD Fei Gao
“The simple sequential presentation of two food images that move from partial to whole reduces portion size choice.”

 

This reaction happens even when the sequential images are unrelated to food, and is robust across languages, age groups, food type, and hypothetical and actual food choice contexts. The effect of image sequence on portion size choice is mediated by reduced perceptions of hunger and is attenuated when people cannot capture the dynamic nature of food shape moving from partial to whole. This technique can be implemented by online food-ordering applications and is usable for both commercial and non-commercial situations (e.g., diet apps, school cafeteria apps).

And finally, you study whether, how, and when a prosocial incentive scheme can motivate consumers to participate in online referral programs. What did you find?

In marketing, it is challenging to make people refer products and services. So far, most online referral programs are based on promoting consumers’ self-interests, either by rewarding referrers only, or by rewarding both referrers and recipients. Very few of them employ a prosocial strategy which rewards recipients only (but not referrers). In this third and last paper of the dissertation, I focus on the effectiveness of a prosocial incentive scheme to motivate consumers’ referral behaviors, compared to the commonly used self-interested incentive scheme.

We present five behavioral experiments (including a large-scale randomized field experiment) in a variety of settings. We demonstrate the effectiveness of the prosocial strategy, or altruistic setting, in motivating, not only referrers to make referrals, but also recipients to adopt the referred products. We show that the prosocial strategy can be as effective as the double-sided strategy, which rewards both referrers and recipients, albeit the prosocial strategy only requires half of the marketing expenditure for online retailers. 

 

The prosocial strategy, or altruistic setting of a referral campaign, is effective in motivating not only referrers to make referrals, but also recipients to adopt the referred products.

 

We hence find that referrers’ prosocial tendencies in the prosocial strategy are driven by altruism, while offering extrinsic rewards crowds out referrers’ altruistic motives. Interestingly, we also find that referrers’ altruistic tendencies in the prosocial strategy are inhibited when there is a more costly action for the referral, but not when the social cost of referral behaviors (e.g., interpersonal risk of a potential poor referral for a product whose quality is of great uncertainty) is increased. This shows the asymmetrical moderating roles of action cost and social cost. 

 

marketing referral campaign

 
So what do you recommend for designing such effective prosocial reward strategies?

When online retailers design a referral campaign in practice, they often explicitly highlight the benefits that consumers can receive to motivate them to participate in online referral programs. However, given that referrers’ altruism is an important motive that drives their referral behaviors in the prosocial strategy, framings that highlight extrinsic benefits, such as maximizing collective benefit, may crowd out referrers’ altruistic motives and thus decrease their referral likelihood. In addition, explicitly highlighting the reputational benefit in a referral campaign might crowd out the referrers’ altruistic motives and hence plausibly decrease the effectiveness of the prosocial strategy. 

Given that consumers appear to be more sensitive to action cost than social cost when referring in the prosocial strategy, online retailers probably should first consider the action cost. If the action cost is relatively low, they can consider choosing the prosocial strategy. Otherwise, if the action cost is relatively high, they should avoid using the prosocial strategy. 

To maximize the effectiveness of the prosocial strategy, online retailers should attempt to reduce the action cost incurred at the referral stage as much as possible. For example, online retailers should minimize the steps and simplify the procedure to send out referral messages. 

 

When using prosocial incentive scheme, online retailers should minimize the steps and simplify the procedure to send out referral messages, and consider designing user-friendly interfaces.

 

Online retailers should also consider designing user-friendly interfaces for consumers to participate in online referral programs. Finally, when online retailers are uncertain about whether the product referred can satisfy the recipients’ needs, the prosocial strategy could be the optimal choice relative to the other reward strategies, as long as the action cost is not overly high.

You have joined Bentley University in Massachusetts as an Assistant Professor. What are your new research projects?

Because my research interests lie in the healthcare domain, I have joined the Health Thought Leadership Network (Health TLN) at Bentley University after landing there. The Health TLN at Bentley supports health research through multidisciplinary collaboration.

In one of my recent papers appearing at Memory, collaborating with Prof. L. J. Shrum from the Marketing department of HEC Paris and a Psychology team from the University of Otago, I study the effect of social distancing during the COVID-19 pandemic on people’s mental health and cognition. I find that the relation between social distancing duration and both negative mood and memory errors followed the same U-shaped function: negative moods and memory errors initially decreased as social distancing duration increased, and then at approximately 30 days, they began to increase. Thus, short-term social distancing might benefit psychological well-being and memory performance, but extended social distancing has a negative impact on mood and memory.

 

Short-term social distancing might benefit psychological well-being and memory performance, but extended social distancing has a negative impact on mood and memory.

 

In addition, I am working on multiple projects related to medical crowdfunding. In one project, for example, collaborating with Prof. Xitong Li from the Information Systems and Operations Management department of HEC Paris and Prof. Cathy Yang from the Marketing department of HEC Paris, I find that when creating a medical crowdfunding campaign, compared to the prompt instructing fundraisers to use a photo that indicates the beneficiary under medical treatment, the prompt instructing to use a photo that conveys positive emotions via a smiling face of the beneficiary under medical treatment is more effective in soliciting donations, whereas the prompt instructing to use a photo that conveys positive emotions of the beneficiary in a healthy situation has no such effect.

In another project, collaborating with Prof. Xitong Li, I find that raising funds from the first-person narrative perspective is more effective in motivating donations for female-beneficiary fundraising campaigns, whereas the third-person narrative perspective is more effective for male-beneficiary campaigns. The findings of these projects generate important managerial implications not only for the beneficiaries in need of medical funds but also for the medical crowdfunding platforms and our society.

Interview with Fei Gao based on his current research, “Three Essays on Marketing Interventions to Influence Consumer Judgments, Choices, and Behaviors”, a thesis supervised by HEC Paris professors Tina M. Lowrey and L.J. Shrum. (Summary in French on Thèses.fr here.)  
Related topics:
Marketing
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Part 6

Should You Listen to the Wall Street Gurus?

Finance
Published on:
Updated on:
October 18th, 2021

During the Covid-19 pandemic, many households started to invest in the stock market expecting to pick the winning stocks and to take advantage of the high volatility. This phenomenon has been possible thanks to the development of trading applications such as Robinhood, which provides individual investors with the opportunity to buy and sell stocks easily. Because most individual investors do not have sufficient time and financial skills, they need to find relevant information to pick stocks. While some of them use social networks such as Twitter, Stocktwits or the WallStreetBets discussions on Reddit, other investors rely on the Wall Street gurus. Is that really a good idea to listen to them?

wall street - adobe

©losonsky on Adobe Stock

Who are the Wall Street gurus?

Wall Street gurus are famous investors who are considered as experts because they were able to get large profits in the past and / or currently manage several billion dollars with their funds. The most famous gurus include for example Warren Buffet, Bill Ackman, Jim Chanos, or Carl Icahn. While they are often invited by different media to give their opinion on the economy and various stocks, they have fascinated individual investors for a long time and many books and movies feature their career and investments. For these reasons, individual investors listen to them and intend to mimic their supposedly superior investments. 

In my research, I focus on one of Wall Street gurus’ communication tools, the investment conferences (for example, the Sohn Investment Conferences or the Robin Hood Investors Conferences). During these conferences, Wall Street gurus are invited to share their opinions on the economy (such as the consequences of unemployment), discuss public policies (such as the impact of a change in tariffs) and, notably, pitch their favorite long or short investment ideas that they are supposed to have implemented in their own fund. They also regularly take advantage of their exposure to highlight their success and increase their reputation. For instance, some of them review their previous ideas if they were profitable.

 

pitch crowd - adobe

 

The investment ideas and forecasts of the Wall Street gurus

I study about 100 investment conferences and more than 1,000 investment ideas between 2009 and 2018. I find that Wall Street gurus’ investment ideas are profitable and allow the investors to “beat the market” for about six months. In other words, the return of the investment ideas exceeds the performance of the Standard & Poor's 500 index during this period. While this is a good reason to listen to the Wall Street gurus, I also find that the profitability of their investment ideas decreased during the decade, implying that this is not necessarily a good strategy nowadays.

 

Wall Street gurus’ investment ideas are profitable and allow the investors to “beat the market” for about six months.

 

Additionally, I study the forecasts of future stock prices, also called target prices, disclosed by these gurus at investment conferences. When the gurus recommend the investors to buy a stock, they expect the stock price to increase by 85% on average. These forecasts are extreme as the Standard & Poor's 500 historical annual returns is only around 10%. After two years, I find the return of their investment ideas is only 25% on average. In other words, their forecasts are overwhelmingly biased. I find a similar extreme bias if I focus on their selling recommendations. In that case, they expect the stock price to decrease by around 60%.

 

When the gurus recommend that the investors buy a stock, they expect the stock price to increase by 85% on average.

 

Because they often share profitable investment ideas and can also provide guidance to analyze a stock, you should definitely listen to the Wall Street gurus. Nevertheless, their forecasts are extremely biased and should always be interpreted cautiously. Always keep in mind that they are supposed to pitch stocks that they own themselves. Therefore, if many investors buy the stock, the stock price will increase, and the gurus will directly benefit from this increase. They face an inherent conflict of interest.

At these investment conferences, the gurus also often claim that you should “do your own work”, that is, consider their ideas and then, decide by yourselves if the idea is worthwhile. 

 

“Do your own work.”

 

A compelling example is a discussion of David Einhorn - a hedge fund manager who predicted the subprime crisis - during one of his pitch. He notified the audience about his confusion when the stock price of a firm decreased instantaneously when people read the title of his presentation. The audience had not actually seen the slides or listened to his arguments but was already trading the stock. You should listen to the gurus but not blindly! This advice is not only worth for equity investments but apply to all assets, including the cryptocurrencies for which the manipulation through pump-and-dump schemes is frequent and substantial.

 

Article based on “Causes and consequences of firm value estimates” by Alexandre Madelaine (work in progress, temporary title).
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Part 7

The Smartphone: Not the Behemoth Feared by Business and Researchers

Marketing
Published on:
Updated on:
October 14th, 2021

“How bad is the mere presence of a phone?” That's the title of the research paper co-authored by Claire Linares and Anne Laure Sellier and published by the review PLoS ONE. This is the product of two years of research, involving the replication of a paper that was written eight years ago by two British psychologists Andrew K. Przybylski and Netta Weinstein. In 2013, they presented data suggesting the physical presence of a cellphone in a meeting was harmful in terms of social interaction between strangers. A conclusion now disputed by the two HEC research academics.

smartphone meeting - cover

Photo by CoWomen on Unsplash

Why did both of you want to tackle this issue?

Claire Linares: I think it began when we saw the 2013 finding being published in the mainstream media, books and academic papers. We found the cellphone’s physical impact interesting enough to want to replicate this effect. It was actually to be a starting point of our research which we sought to extend into the field of creativity. But as we were conducting the studies, we were unable to find the initial effect. So this is what motivated our research.

Anne Laure Sellier: The claim that the mere presence of a phone would affect social interaction and would be deleterious to high quality relationships is formidable. Just imagine the consequences of smartphones today in negotiation rooms, at the U.N., for example, where you have leaders talking about going to war or not. We wanted to capture its impact. For theoretical reasons, as Claire said, we thought if it's true, it may hurt creativity beyond social interaction. But Claire conducted several studies and found nothing. However, don’t get me wrong: the effect is not necessarily bogus. It may have been there in 2013 in those two studies. But it certainly required replication. You cannot extrapolate about an effect based on only two studies.

As you said, the 2013 findings were widely accepted and reported on. Do you think your conclusions will enjoy the same attention?

ALS: I was looking at some articles recently showing just how bad it is to have a smartphone in business meetings. So, this perception is still very present. I imagine we’re not going to make waves with our results. It should certainly get as much media attention as the 2013 paper. But it probably won’t because intrinsically a failed replication paper rarely gets cited as recent research empirically shows. Let’s hope things will change going forward. We’re very pleased that the journal PLoS ONE chose to publish this work out of academic rigor.

You know, this is nothing new in terms of the relationship of mankind to technology. Whenever a new technology appears, there are fanciful theories that the world is coming to an end. If you look at the introduction of television, for instance, you can find articles from the 40s and 50s in the United States where men were warned to protect women and children from TV screens. Any new technology has this kind of vampire clout to it. That's kind of scary. And, rightly or wrongly, it's even more the case for cell- and smartphones because we know of cases of addiction which are made worse because smartphones are constantly at our fingertips.

The paper did involve lots of interesting elements, such as measuring pleasantness, appreciation, motivation, autonomy, control. All this research involved giving people tasks like creating a toy or telling an interesting story. How do you measure these, Claire? 

Across our two studies, we had a total of 356 volunteers split into 136 groups working on what we call a toy task. They had to discuss between themselves and then design a toy for a child from five to 11 years old. After the sessions, we had independent curators judging their originality and the other criteria pertaining to the creativity of these toys. We compared the creative measures of the toys between groups who had been exposed to the mere presence of a smartphone versus the group that had been exposed to the presence of a notebook. And we conclude by saying that there is too much concern over the impact of the mere presence of smartphones and how it can affect interaction, be it personal or professional, in terms of the professional context. Unfortunately, one result of the all-negative view of smartphones in meetings is that there have been widespread bans on smartphones in meetings. We should conduct more research on the impact of the active presence of the smartphone rather than its mere presence. For instance, what is the influence of notifications ringing during meetings, what happens to the interaction when someone checks his or her phone for messages, etc.?

You're saying that, in light of the results of your research, these policies go over-the-top?

CL: Well, certainly the media has insisted that the mere presence of a smartphone can be dangerous. We didn't find this impact. However, as we mentioned before, there are probably other negative effects caused by smartphones being in meeting rooms.

 

The media has insisted that the mere presence of a smartphone can be dangerous. We didn't find this impact.

 

Did you want to add something, Anne Laure? 

ALS: Yes. Of course, you don't want a smartphone inside a criminal court at the time of debates because you don't want anything to be recorded and get out of the closed room. This is a valid concern. But that's not what we're talking about. We're talking about those companies who require people to leave their phone outside of the room, the way cowboys left their colts outside of the saloon, just putting your phone on airplane mode is enough! And more generally, I think it is simply time for the business world to devise an etiquette for smartphone use.

In your research paper, there are a few caveats that you mention when you compare your own research to that of Andrew K. Przybylski and Netta Weinstein. For example, people have evolved in their attitudes towards smartphones and simply gotten used to their presence.

CL: Yes, we considered how we could reconcile our results with the findings of Przybylski and Weinstein. And one explanation is that time simply has passed. They published the article in 2013. So they conducted their studies in 2012 or earlier. We conducted our studies in 2018. Six years of technological progress is a lot. Furthermore, the participants in our studies were people in their 20s, this generation of people grew up with phones that were always there. Returning to your earlier point, the 2013 results may have been genuine, it’s may just be that time has passed and the mere presence of mobile phones no longer has the same impact.

***


Learn more soon in an upcoming podcast.

An interview based on the research article, “How bad is the mere presence of a phone? A replication of Przybylski and Weinstein (2013) and an extension to creativity”, by Claire Linares (HEC Paris PhD student of Marketing) and Anne Laure Sellier (HEC Paris Professor of Marketing), published in PLoS ONE in June 2021.
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Part 8

Why Student Debt Relief May Fall Short of Its Good Intentions

Finance
Published on:
Updated on:
October 13th, 2021

As the U.S. staggers beneath the weight of its education debt – a crushing $1.6 trillion in 2020 – there are increasing calls for loan forgiveness. But debt forgiveness plans need to be crafted carefully or they might actually disproportionately favor high-income individuals or specific ethnic groups. A duo of Finance researchers, Sylvain Catherine of Wharton School and Constantine Yannelis of Chicago Booth School of Business, explains how to tailor such policies to better redistribute their benefits. Sylvain Catherine is a HEC Paris PhD alumnus.

 

 

student debt - adobe

Photo Credits: Rawpixel on Adobe Stock

Crushing student debt is almost a fact of life in the U.S., where the cost of education routinely runs in the tens of thousands of dollars. While investing in a college education brings undeniable benefits, it also imposes a hefty burden on young (and even not-so-young) adults, potentially lessening their ability to buy a home, start a family or invest in a business. Not to mention that the staggering amount of student loan debt – an unprecedented $1.6 trillion in 2020 – possibly also holds back economic growth. 

And the figure is rising, as are calls to alleviate the burden of debt. 

At a time when many individuals, especially those with low to moderate income, are struggling during a pandemic-induced recession, student loan forgiveness is viewed as both fair to individuals and important for economic vitality. But do good intentions actually translate into financial benefits for borrowers?

Not all debt plans are created equal

A duo of researchers examined the financial situation of indebted households under various debt-relief policies – universal or capped forgiveness, and income-driven plans, targeted to specific borrowers. The researchers, Sylvain Catherine of Wharton University (formerly Ph.D. student at HEC Paris) and Constantine Yannelis of Chicago Booth, carried out their analysis by looking beyond student loan balances (what’s left to repay – the variable usually examined), because they felt it wasn’t truly representative of the weight of loans on individuals’ budgets. 

“Instead, we compute present values based on what people are actually repaying, which depends very much on their earnings,” Sylvain Catherine told Knowledge@Wharton.

Their conclusion? Not all plans are created equal. They have different distributional effects. In other terms, their costs and benefits are not evenly redistributed among various population groups – which may challenge some proponents’ view of fairness.

Universal debt forgiveness favors high earners, offers unequal benefits by race

Many progressives have been demanding universal debt forgiveness – i.e., (more or less) wiping the slate clean for everyone after a certain number of years, regardless of an individual’s financial situation. Such plans may be capped, discharging only a certain amount. In essence, they disproportionately favor those with higher incomes. 

“Any policy that is a universal loan forgiveness policy or a capped forgiveness policy – say forgiving debt up to $50,000 – is going to give most of the dollars in forgiveness to upper-income individuals,” Constantine Yannelis told Knowledge@Wharton

Specifically, under a universal loan forgiveness policy, in present value terms, individuals among the highest 10 percent of earners would receive $6,267 in forgiveness, while those in the bottom 10 percent would receive $1,276 in forgiveness. In a way, it is hardly surprising that plans are (almost by default) geared toward higher earners: Many holders of high loan balances completed graduate and professional degrees, and thus earn higher incomes.

The benefits of student loan forgiveness are unevenly distributed also by race and ethnicity, the researchers found. The average loan balances are highest among blacks, at $10,630, while those for whites are $6,157 and for Hispanics and others $3,996. After adjusting for the present value of those loans, universal loan forgiveness would lead to roughly equal average benefits for whites and blacks, but would yield significantly lower average benefits for Hispanics and other groups.

Better targeting middle and lower-income groups

In contrast, an existing loan forgiveness plan known as Income-Driven Repayment (IDR) links payment to income and forgives remaining debt after a fixed time, often 20 or 25 years. Under current IDR plans, borrowers pay 10 or 15 percent of their “discretionary income,” the part of their earnings above 150 percent of the poverty line. 

The researchers devised a scenario in which they expanded the existing IDR plan and found that it was more progressive than universal forgiveness plans. 

 

The researchers found that the Income-Driven Repayment was more progressive than universal forgiveness plans.

 

“Expanding the generosity of income-driven repayment plans, or enrolling more people in these plans, leads to the benefits of forgiveness going to the lower middle and the middle class, rather than the top percentiles of income distribution,” Yannelis told the Wharton site. 

Individuals in the bottom half of the earnings distribution would receive three-fifths of dollars forgiven, and borrowers in the top 30 percent would receive one-fifth. In terms of the racial and ethnic effects, forgiveness amounts are twice as high for blacks relative to whites and the general population. Hispanics and others see lower loan forgiveness amounts relative to other groups, however.

Designing better policies

For policymakers, these findings embody a timely contribution as they review plans to apply resources to the pressing question of debt. Indeed, the vast majority of student debt in the U.S. is directly disbursed or guaranteed by the federal government. 

Policymakers must be careful in shaping policies to deal with student loans “because they might sound progressive on paper, but they are very regressive,” Catherine noted. 

Of course, so-called distributional effects are not the only factor driving the debate, and such issues as how student loans impact career choices, hinder entrepreneurship or whether debt relief has macroeconomic consequences also must be considered.

 

Based on “The Distributional Effects of Student Loan Forgiveness” by Assistant Professors of Finance Sylvain Catherine of Wharton School and Constantine Yannelis of Chicago Booth School of Business, 14 April 2021, BFI Working Paper no. 2020-169, Becker Friedman Institute for Economics at the University of Chicago. (pdf)

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