A recent drive on an express lane showed tolls as high as $9 to Broadway and $10 to I-380, depending on real-time conditions. What makes this interesting is that the price for using the same road is not predetermined; it is decided on the spot.
Dynamic toll pricing may adjust based on traffic volume, creating an anchor for drivers to evaluate the value of the express lane. If traffic is heavy, the higher toll can feel worth it when compared to the frustration of sitting in congestion. This shifting price serves as a real-time incentive or deterrent, depending on how drivers value their time at that moment.
Mental accounting, the tendency to categorize resources such as money and time, is a key principle at work. The price is not just about the toll but about the potential loss of time stuck in traffic. For many, the higher toll feels like a small price to pay to avoid the larger loss of wasted time, especially during busy hours.
Dynamic pricing taps into our varying perceptions of time. During a stressful commute, paying $10 to save several minutes is more appealing than when traffic is light. The system uses behavioral cues to nudge drivers into seeing the express lane as a valuable, time-saving option.
In essence, dynamic toll pricing leverages human psychology to adjust behavior in real time, making the express lane more than just a road—it is a reflection of what happens when we convert time into money.
The sunk-cost effect, an irrational attention to non-recoverable past costs while making current decisions, has been documented widely in the domain of monetary costs. In this paper, I study the effect of past time investments on current decisions. In three experiments using choice situations, I demonstrate that the sunk-cost effect is not observed for past investments of time, but the effect reappears when the investments are expressed as monetary quantities. I further propose that this ‘pseudo-rationality’ is due to the fact that individuals lack the ability to account for time in the same way as they account for money. In two additional experiments, I facilitate the accounting of time and show that the irrational sunk-cost effect reappears. In a final experiment, I test my propositions in a setting where subjects make real investments of time and subsequently make real choices.
Recently, while applying for my driver license in California, I encountered a section about organ donation. The DMV’s (Department of Motor Vehicles) approach is an example of default.
First, they primed me with two statements:
“One person can save up to 8 lives, and heal over 75, through organ and tissue donation for transplantation. You can register regardless of age or health.”
“Organ donation happens after death, and your decision will not impact medical treatment.”
The first statement emphasizes the positive impact, while the second addresses potential concerns. This balanced approach put me at ease and highlighted benefits.
Then comes the question: “Would you like to register?” with two options: “Yes” or “Not at this time.” This is where default comes into play. By framing the question this way, they make saying “yes” feel like the natural choice.
Interestingly, even if I chose “Not at this time,” I was informed that I am still in the registry but without the pink dot on my license that indicates donor status. This opt-out process requires additional steps, making it more likely for people to remain registered.
This example resonates the findings of Johnson & Goldstein’s 2003 study on how defaults influence decision-making. By designing the process this way, the California DMV is likely increasing organ donation rates without forcing anyone’s hand.
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Reference
Johnson, E. J., & Goldstein, D. (2003). Do defaults save lives? Science, 302(5649), 1338–1339.
“If preferences concerning organ donation are strong, we would expect defaults to have little or no effect. However, as can be seen in the figure, defaults appear to make a large difference: the four opt-in countries (gold) had the lower rates than the six opt-out countries (blue)… One reason these results appear to be greater than those in our laboratory study is that the cost of changing from the default is higher; it involves filling out forms, making phone calls, and sending mail.” (pg. 1339)
Salon de Jungui Lee is a cafe in Jeju island. With minimal construction and a commitment to preserving its essence, the owner of the old house transformed it into a cafe that embodies her philosophy of refined simplicity.
This cafe is a popular destination among Korean coffee lovers. Coffee is excellent, but its desserts are not overly sweet, not sticky, nor heavy treats. To me, each bite was a carefully orchestrated symphony of taste and texture.
Beyond taste, its atmosphere was unique. The pinnacle was the air conditioner vent. Instead of a tasteless plastic vent, a repurposed traditional Korean window frame was hanging on the ceiling. It was functional, beautiful, and deeply rooted in cultural heritage.
While enjoying coffee, dessert, and unique air conditioner vent, I naturally assumed that the vintage speaker pumped out the tunes. However, it was actually a cleverly disguised modern Bose system connected to an iPhone.
Salon de Jungui Lee taught me a valuable lesson about experience. It is not just about the individual components – the coffee, the desserts, or the décor. It is about how these elements come together to create something greater than the sum of its parts.
Recent research has highlighted the notion that people can make judgments and choices by means of two systems that are labeled here tacit (or intuitive) and deliberate (or analytic). Whereas most decisions typically involve both systems, this chapter examines the conditions under which each system is liable to be more effective. This aims to illuminate the age-old issue of whether and when people should trust “intuition” or “analysis.” To do this, a framework is presented to understand how the tacit and deliberate systems work in tandem. Distinctions are also made between the types of information typically used by both systems as well as the characteristics of environments that facilitate or hinder accurate learning by the tacit system. Next, several experiments that have contrasted “intuitive” and “analytic” modes on the same tasks are reviewed. Together, the theoretical framework and experimental evidence leads to specifying the trade-off that characterizes their relative effectiveness. Tacit system responses can be subject to biases. In making deliberate system responses, however, people might not be aware of the “correct rule” to deal with the task they are facing and/or make errors in executing it. Whether tacit or deliberate responses are more valid in particular circumstances requires assessing this trade-off. In this, the probability of making errors in deliberate thought is postulated to be a function of the analytical complexity of the task as perceived by the person. Thus the trade-off is one of bias (in implicit responses) versus analytical complexity (when tasks are handled in deliberate mode). Finally, it is noted that whereas much attention has been paid in the past to helping people make decisions in deliberate mode, efforts should also be directed toward improving ability to make decisions in tacit mode since the effectiveness of decisions clearly depends on both. This therefore represents an important frontier for research.
The broken windows theory, introduced by James Q. Wilson and George L. Kelling in 1982, suggests that visible signs of disorder and misbehavior in an environment encourage further disorder and misbehavior, leading to serious crimes. A classic example is a building with a few broken windows. If left unrepaired, vandals are likely to break more windows, potentially leading to more serious property damage.
During a recent trip to Istanbul, Turkiye, I observed this theory in action through a series of urban landscapes. The following image illustrates the problem. An outside trash and garbage collection area was exposed in a busy commercial district.
In contrast, the following three images demonstrate clever solutions, showcasing how to apply the broken windows theory in urban planning. In the first two images, the trash and garbage collection area was enclosed by an artificial ivy hedge to minimize its visibility from pedestrians. In the last image, the back side of a series of market stalls was enclosed by the decorative wall.
Hiding trash and garbage collection areas may not be a permanent solution. However, doing so will motivate citizens to keep their cities clean. By investing in public spaces, urban planners create environments that naturally deter crime and foster community well-being.
***
Reference
Kelling, G. L., & Wilson, J. Q. (1982). Broken windows. Atlantic monthly, 249(3), 29-38.
In the mid-1970s The State of New Jersey announced a “Safe and Clean Neighborhoods Program,” designed to improve the quality of community life in twenty-eight cities. As part of that program, the state provided money to help cities take police officers out of their patrol cars and assign them to walking beats. The governor and other state officials were enthusiastic about using foot patrol as a way of cutting crime, but many police chiefs were skeptical. Foot patrol, in their eyes, had been pretty much discredited. It reduced the mobility of the police, who thus had difficulty responding to citizen calls for service, and it weakened headquarters control over patrol officers…
Design Fixation refers to the tendency to adhere to pre-existing ideas, which hinders innovative design solutions. This research explores the potential of LLM-powered Creativity Support Tools, the ’Behaviorally Informed Creativity Support Tool (BI-CST),’ to facilitate ideation and combat Design Fixation using ’Behavioral Science Theory.’ BI-CST assists in redefning problems and generating new ideas by presenting experimental fndings from Behavioral Sciences that challenge users’ initial concepts, thus providing a deeper understanding of real human behaviors. We will assign three groups to diferent conditions: one designing without generative AI support, one with open-ended generative AI (e.g., ChatGPT), and one using a model trained in behavioral science. We aim to compare the originality, practicality, and general quality of the designs to assess design fxation. This study addresses design fxation through an interdisciplinary approach combining design and behavioral science, aiming to expand users’ perspectives.
Keywords
creativity support tool, human AI collaboration, behavioral science, design fixation, generative AI
… Behavioral science, a sub field of psychology, aims to understand and predict people’s behaviors through scientific methods ranging from casual observation of daily life to systematic observation to minimize the effects of biases [22, 29]. Its research includes behavioral decision theory, which shows people’s heuristics and biases in judgment [9], and builds nudges that gently alter people’s decision making processes [27]. As this field targets problem-solving by understanding people’s psychology, efforts have been made to apply theories of behavioral science in the HCI field to change users’ behavior [13, 14, 19]. However, there has been limited research on incorporating behavioral science into Creativity Support to aid design processes. We assume that the scientific causal and systematic observational results about human behavior from behavioral science can serve as a ’nudge’ to assist users in gaining more diverse perspectives. (pg. 117)
… We hypothesize that participants using a non-behaviorally informed Creativity Support Tool (CST) in Condition B are likely to reinforce their existing heuristics, which could increase their design fixation. In contrast, participants in Condition C, who will be provided with behaviorally informed guidance, are expected to adopt new heuristics that help reduce their fixation on initial ideas. Specifically, we anticipate that the outputs in Condition A and Condition B will likely exhibit medium to high originality but may have low practicality. Conversely, outputs from Condition C are expected to show medium originality but high practicality, due to the application of evidence-based creative support derived from behavioral science research. (pg. 119)
Through the years, the Duncan Anderson Design Lecture Series has invited top professionals to share their knowledge and experience with design students at CSULB. This coming year marks the expansion of that series to a bi-monthly event. Thanks to Cecelia Anderson-Malcolm and the Duncan Anderson Endowment, CSULB now has an ongoing design lecture series to rival those at private design schools. The CSULB Industrial Design Program is working closely with IDSA-LA, and its student chapters, to schedule an exciting line-up of speakers. Please let your chapter officers know of professionals you want to meet and hear at future events.
In this lecture, I introduced why designers have to adopt behavioral science to understand customer experience deeply. For instance, prospect theory neatly elucidates why once people have a single extraordinary experience, they can no longer revert to previously satisfactory mundane experiences. It is because the extraordinary experience can become a reference point, while the mundane experiences transform into sources of negative affect. Since loss looms larger than gain, people avoid mundane experiences.
This paper presents a critique of expected utility theory as a descriptive model of decision making under risk, and develops an alternative model, called prospect theory. Choices among risky prospects exhibit several pervasive effects that are inconsistent with the basic tenets of utility theory. In particular, people underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty. This tendency, called the certainty effect, contributes to risk aversion in choices involving sure gains and to risk seeking in choices involving sure losses. In addition, people generally discard components that are shared by all prospects under consideration. This tendency, called the isolation effect, leads to inconsistent preferences when the same choice is presented in different forms. An alternative theory of choice is developed, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights. The value function is normally concave for gains, commonly convex for losses, and is generally steeper for losses than for gains. Decision weights are generally lower than the corresponding probabilities, except in the range of low probabilities. Overweighting of low probabilities may contribute to the attractiveness of both insurance and gambling.
Many design practitioners aim to enhance the beauty of an existing product or develop novel products and services. However, market does not always pay off their effort. Carefully designed products often fail to attract consumers. What should designers do to enhance sales?
One solution is to borrow insights from behavioral economics. Studies show that behavioral economics can increase the adoption rate of newly designed products because it overcomes consumer resistance.
I was once invited by Palermo University in Argentina to share findings about the commercial impact of behavioral economics in the context of design. I shared my experimental findings about three Korean companies.
(1) Samsung’s printer would sell more if its ugly version is placed next to it because joint evaluation helps consumers consider aesthetics importantly,
(2) LG’s Styler would sell more if the clock in the store presents time in analog not in digital because doing so encourages consumers to think abstractly and creatively to appreciate the value of something new, and
(3) SK Telecom’s AI speaker would be used more often if it has a human feature and viewed as a foreigner or child because people become more tolerant about the mistakes of the AI speaker.
Coming January 3rd to 6th of 2022, EBS Business Review will broadcast “Behavioral Economics for Dummies.”
The world-renowned bestseller book, Nudge, by Richard H. Thaler, winner of the 2017 Nobel Prize in Economics, is well known for its coverage of behavioral economics. The term nudge which has an idiomatic meaning of nudging with an elbow refers to guiding people’s choices through gentle intervention instead of compulsion or coercion. Different from normative economics and descriptive psychology, prescriptive behavioral economics intervenes and guides people’s choices by closing the gap between behavior and mind.
What is the hidden key of behavioral economics? You will learn its various cases which show the power that moves the world.
The secret of 99% adoption of organ donation (January 3rd)
As medical dramas suggest, hospitals need more organ doners. In order to solve the supply-demand problem of organ donation in Korea, a policy was implemented in 2007 which inserts a statement regarding donation into the driver’s license upon issuance or renewal. However, the survey result in 2018 showed that the actual number of those who wish to donate is only about 3%.
What about other countries? If we look into the organ donation rate in European countries in the early 2000s, Denmark had a rate of about 5%, Germany had a rate of about 12%. However, there are many other countries boasting a rate of 99%, such as Portugal and France. What is the secret behind these countries with a high donation rate? We will explore successful uses of behavioral economics that change people’s behavior.
Public institutions can be smarter (January 4th)
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In 2020, an experiment was conducted in US to find out how to increase the vaccination rate for the flu. As a result of sending 20 messages that encouraged people to get vaccinated, the most effective one was the combination of messages sent three days before vaccination saying “a flu vaccine is available for you” and one day before vaccination saying “a flu vaccine has been reserved for your appointment.” For those who received these messages, they made a promise to themselves to get vaccinated, resulting in an increased vaccination rate of about 5%.
Since behavioral economics brings great results with little cost, it is actively applied in many public institutions. Let’s listen to other cases of public policy which solve tough social problems.
When tech giants meet behavioral economics (January 5th)
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Marketing is a key area in which behavioral economics is actively applied. Various mechanisms can be used to target customers, which can lead to an increase in revenue and market share. Lyft, a ride-sharing company once conducted an experiment to encourage users to drive during peak demand times, Friday nights, instead of quiet mornings on Wednesdays.
They divided drivers into two groups randomly. One group was given information that their income would increase if they worked on Friday night. The other group was given information that their income would decrease if they did not work on Friday night. More people in the latter group chose to drive Friday night because people tended to avoid loss, helping Lyft mobilize the drivers’ behavior. What are the other special secrets of behavioral economics that change peoples’ choices and help companies increase profits?
Nudge yourself (January 6th)
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Self control is a process of paying the small pain in the present to obtain a greater gain in the future. But when the pain in the present is overwhelming to bear, people lose their motivation to control themselves. To solve this problem, we have to go beyond the present bias and go back to the past self.
Imagine that alarm wakes you up in the early morning. If you want to overcome the thought of having sleep for one more hour, you need to go back to the ‘me’ last night who set the alarm. To make a rational decision, you have to remember your own attitude of yesterday when getting up early eventually leads to a greater benefit than oversleep. We will introduce the secret of behavioral economics that makes a better ‘me’ based on deep understanding of human.
Jaewoo Joo is a field researcher who applies academic insights to solve real world problems. He received a Ph.D. in Marketing from the University of Toronto after obtaining a Bachelor degree and a Master degree from Seoul National University. Jaewoo is interested in developing customer experience by utilizing empathic design thinking and counter-intuitive behavioral economics. He is an associate professor of marketing and participating professor of experience design at Kookmin University.
References
Johnson, E. J., & Goldstein, D. (2003). Do defaults save lives? Science, 302(5649), 1338–1339.
Milkman, K. L., Patel, M. S., Gandhi, L., Graci, H. N., Gromet, D. M., Ho, H., … Duckworth, A. L. (2021). A megastudy of text-based nudges encouraging patients to get vaccinated at an upcoming doctor’s appointment. Proceedings of the National Academy of Sciences of the United States of America (Vol. 118).
Scheiber, N. (2017). How Uber uses psychological tricks to push its drivers’ buttons, The New York Times, April 2, https://www.nytimes.com/interactive/2017/04/02/technology/uber-drivers-psychological-tricks.html.
Soman, D., & Shi, M. (2003). Virtual progress: The effect of path characteristics on perceptions of progress and choice. Management Science, 49(9), 1229–1250.
In previous research on in-app purchasing, one of the revenue sources for mobile games focuses on users’ unilateral relationships, such as their achievement, loyalty, and perception. However, little has been discussed about the commercial impact of the bilateral relationship. We extend discussions by examining an unprecedented issue, that is, the role of the bilateral relationships between users and mobile game companies in increasing in-app purchasing intention. We borrow from the business literature and psychology to hypothesize that when mobile game users co-create value with a mobile game company, their psychological ownership of the mobile game increases, which in turn increases their in-app purchasing intentions. To test this hypothesis, we conducted a carefully designed study by recruiting eighty-six Chinese game users. Half of the participants were exposed to an imaginary mobile game whose interface allowed them to co-create value with the mobile game company and the other half were exposed to an identical mobile game whose interface did not. We recruited participants from the two online platforms in which Chinese mobile game players gather—Weibo and WeChat Moment. Using SPSS 26, we conducted an independent samples test to test the effect of value co-creation and employed Hayes Model 4 to test whether psychological ownership mediated the relationship between value co-creation and in-app purchasing intention. We found that (1) when participants were allowed to co-create value, their in-app purchasing intentions increased, and (2) the relationship between value co-creation and in-app purchasing intention was mediated by psychological ownership. Our findings provide fresh insights for mobile game designers and marketers.
This research examines the effectiveness of traffic-boosting mobile coupons through a randomized field experiment of over half a million South Korean consumers. The research question analyzes the effectiveness of the content (six message types) and context (three days out of the week for coupon distribution) of mobile coupons on response-to-coupon, store visits, and purchase amount for a health and beauty retail chain. Big data on individual customers, gathered from a field experiment, was analyzed through bivariate probit, mediation analysis, and tobit regression. The results show that message content affects store visits, which was fully mediated through response-to-coupon. In particular, messages that “made the amount of discount salient” and “formed a personal connection” were more effective than other messages. In terms of context, messages sent during the weekdays were more effective in increasing store visit, than those sent during the weekend.
Keywords
Mobile promotion · Mobile coupon · Message content · Message context · Coupon distribution · Field experiment
Acknowledgements
We would like to express our deep gratitude to Hyojung Kim, Sul Namgoong, and Joongjae Lee at Shinhan Card for their assistance with the collection of our data.
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