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<h2 class="hd hd-2 unit-title">4.1.1 The intersection of behavior and transportation</h2>
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<p><strong>Welcome to the Behavior Module!</strong></p>
<p></p>
<p>Historically, policies and systems have been designed under an assumption of rationality: individuals are rational actors who are capable of making complex, calculated decisions based on a variety of information inputs in order to optimize their well-being. But research has shown that decision-making might not be as straightforward as one might think. In fact, individuals’ behavior is far from rational, which affects the decisions they make every day. We, as humans, are not very good at taking all options into account and weighing their implications. And this applies, of course, to the world of transportation.</p>
<p></p>
<p>In this module, we will look at transportation through the lens of behavioral economics. We explore what choices and behaviors affect the way we get around. And, significantly, how transportation and its infrastructure affect the way that we act. <span style="mso-spacerun: yes;"> </span></p>
<p></p>
<p>As you move through this week’s lectures, think about your own personal experience with transportation. Why do you choose the travel mode that you use most frequently? Which principles discussed throughout the lecture might apply to your own actions and activities?</p>
<p>Verified learners will have their first peer-to-peer graded assignment (more details will be provided at the end of the module).</p>
<p><strong>Lectures:</strong></p>
<p>Jinhua Zhao, Ph.D. (Professor at MIT)</p>
<p>Carlos Pardo, M.S. (Pilot Manager at NUMO)</p>
<p><strong>Guest interviews:</strong></p>
<p>Ben Plowden (Transport for London, <span style="color: #000000;"></span><span style="color: #000000;"><span dir="ltr">Visiting Professor, University College London</span></span>)</p>
<p></p>
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<h3 class="hd hd-2">Jinhua Zhao, Ph.D. (MIT)</h3>
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<h3 class="hd hd-2">Framing behavioral perspectives for new mobility</h3>
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<p>The Transportation Paradox states that the increase in GDP does not necessary carry along an improvement in transportation. Some aspects of transportation may improve (e.g. more comfortable vehicles) while others get worse (e.g. traffic, pollution).</p>
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<p>Consider the opportunities that are presented by understanding behavior and its effects on transportation. How should we approach shaping that behavior? And what values should we prioritize?</p>
<p>Recap! As mentioned in the above video, there are three ways to change behavior:</p>
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<p>Preferences and behavior must change to achieve a sustainable future.</p>
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<p>Technology itself does not have a purpose. We, the people, determine the purpose. Next, we will learn about how different instruments are used to change behavior. While watching the videos, try to think of technologies that have been used to change human behavior.</p>
<p>You will also learn about the difference between objective reality and people's perception of that reality.</p>
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<p>People's choice is a result of a process that takes perception and preference as two key inputs. Therefore, information could be used to manipulate perception without changing the reality.</p>
<p>Real dollar drives revenue collected but it is the <em>perceived dollar</em> that drives behavior change (the gap between them is determined by <em>salience</em>.) There is a difference between travel time and <em>perceived travel time,</em> as well as between policy fairness and <em>perceived policy fairness</em>.</p>
<p>The above examples lead us to recognize that there is a difference between reality and how we perceive it.</p>
<p>This brings us to other examples we discussed earlier: our willingness to pay for housing and transportation also depends on how we value different factors that go into our decision making process.</p>
<p>To learn about other examples of price, its salience and choices, please read 1-4 pages of this <a href="http://scholar.harvard.edu/files/shleifer/files/salience_consumer_revision_feb6_0.pdf" target="[object Object]">article.</a></p>
<p>Can you try to think how this phenomenon could be used in the new mobility context? Share your thoughts with your classmates in the discussion forum below.</p>
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<h2 class="hd hd-2 unit-title">4.1.2 How is travel behavior shaped?</h2>
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<p>The following videos explore some of the forces that help shape travel behavior and our perceptions of travel. Prof. Zhao introduces how time might not be as absolute as we might think, and discusses the role of social interactions and pressures on our transportation decisions.</p>
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<p>In the last two videos we challenged the "traditional" perception of time. The perception of time will be important to evaluate the value of different behaviors. While watching lectures in this module, try asking yourself how you perceive time. Does 15 minutes on a crowded subway feel the same as 15 minutes traveling alone in an air-conditioned vehicle?</p>
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<h2 class="hd hd-2 unit-title">4.1.3 Better interactions through new mobility?</h2>
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<p>Now let’s take a look at shared mobility. As a new way to get around, shared mobility also sparks different forms of social interactions. Here, we explore this from a behavioral perspective. What can we learn about the experience of the riders using forms of shared mobility?</p>
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<p>Interactions during ride sharing can embody both spontaneity (impromptu-ness) and intensity, which makes them a unique behavior to study.</p>
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<p>Here we add another layer to the analysis. Interactions during ride-sharing are not only spontaneous and intensive, which makes them a unique behavior to study, but also allow for intimacy.</p>
<p>Does new mobility not only provide a new way of moving people; has it also become a new mode of social interaction? If so, can we incorporate social interaction preferences in the principles and rules being used to match people?</p>
<p>Apple headquarters were designed to increase creativity via spontaneous, random, but intensive interactions. Take a minute and think about how we can benefit, as a society, if we modified the system to leverage these unique interactions in ride-sharing.</p>
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<p>Now that we have observed how shared mobility provides unique and potentially beneficial social interactions, let’s think about how we might be able to make ride sharing happen.</p>
<p>Below, Prof. Zhao explores how we might be able to optimize rider matching for shared mobility and what such an optimization process might look like.</p>
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<p>To satisfy the need for social interaction, we can use the maximum stable matching algorithm.</p>
<p>If you are interested in this methodology and how this research was designed check out the original <a href="https://mobility.mit.edu/sites/default/files/Zhang%20and%20Zhao_2018_Mobility%20Sharing%20as%20a%20Preference%20Matching%20Problem.pdf" target="[object Object]">article </a>via MIT.</p>
<p>Prof. Zhao will now explain some other factors to consider when thinking about matching algorithms.</p>
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<p>No matter how robust our rider matching algorithms, we must always account for the psychological factors at play in every individual while they choose their mode of transportation.</p>
<p>The next unit focuses on the challenges we face when we seek to make these types of changes in human behavior.</p>
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