<div>We consider the models of sequential games over supply chain networks and production chain networks. In the supply chain model, we show that in particular, for series-parallel networks, there is a unique equilibrium. </div><div>We provide a polynomial time algorithm to compute the equilibrium and study the impact of the network structure to the total trade flow at equilibrium. Our results shed light on the trade-off between competition, production cost, and double marginalization. </div><div><br></div><div>In the production chain model, we investigated sequential decisions and delegation options over three agents, chain, and tree networks. Our main contribution is showing the value of delegation and how to maximumly leverage the middleman's aligned interests with the principal. In particular, we provide a polynomial time algorithm to find the optimal delegation structure and the corresponding necessary contract payments for the principal. Furthermore, we analyzed the trade-off of the delegation and gave a deeper insight into the value of delegation in different conditions. Several questions are left for future research such as what's the optimal delegation structures in general tree and how to build the model that agents can try multiple times until the task is successful. </div>

<p dir="ltr">The rise of digital media has allowed for unprecedented access to information. In particular, people are able to form beliefs based on information sources that span the full spectrum of reputation, information quality, and motivated biases. Such access is a double-edged sword because “with great power, comes great responsibility” (“Spider-Man”, 2002). Heterogeneity in information quality may be due to a variety of factors, and it is often up to the consumer to consider quality signals when evaluating the quality of information. My research explores this complicated process, and contributes to the understanding of how people demand and utilize information in different environments. I do so over three chapters. The first studies how people respond to signals of information quality in a sequential prediction game. In the second chapter, biased incentives are introduced in a prediction game experiment to test how intrinsic and extrinsic biases affect demand and utilization of information. The third chapter contains a survey in which subjects report their valuations of an X account that varies on political affiliation, occupation credentials, and number of followers.</p><p dir="ltr">My first chapter focuses on how subjects respond to signals of information quality. In it, subjects predict which of two urns was randomly chosen in each of 30 rounds. They observe a private ball drawn from the selected urn each round to help them make their prediction. The color of the ball signals the urn it came from. The subjects then sequentially broadcast their belief about which urn was selected for the session without revealing the color of the observed ball. Future subjects can use the previous broadcasts to infer additional information that may help them accurately predict the urn.</p><p dir="ltr">In the control, subjects exhibit very low utilization of previous predictions when informing their own behavior. While consistent with prior research, behaving in such a manner is suboptimal. To experiment on the malleability of subjects’ beliefs about the rationality of others, I implement two novel treatments. In the first, the subjects’ prediction order in the last 15 rounds is determined by their accrued earnings in the first 15 rounds, with highest earners predicting first. The prediction order is similarly determined in the second treatment, except a quiz on conditional updating ability is used. Subjects who score the highest on the quiz predict first. In both cases, the sorting mechanism is explained to the subjects.</p><p dir="ltr">Sorting on earnings yields a modest increase in valuations of previous subjects’ predictions. A much more significant increase is observed when sorting on ability. Additionally, the subjects who make the fewest irrational predictions (ones against the color of the ball when they do not have additional information to suggest otherwise) are the ones who score the best in the ability sort. Placing them at the beginning of rounds increases the entire round’s average earnings.</p><p dir="ltr">My second chapter uses a similar environment to study the role that bias plays in demanding and utilizing information. In it, participants predict which of two states (red or blue) each of 30 rounds was assigned. To aid them, participants observe two predictions from ‘experts,’ who are informed by a private signal with a known precision. Participants can bid to receive additional information about the state from two sources: a private signal and another independent expert’s prediction. Both sources’ precision is known. This method is the first of its kind, and allows for direct comparison between information types. The bid results are revealed once this process is complete. Participants then predict the state.</p><p dir="ltr">Two innovative treatments are implemented to implement bias into the basic environment exogenously. In the first, participants receive a small bonus each time they predict the state is blue. In the second, experts receive the same bonus each time they predict the state is blue instead of the participants. Surprisingly, participants value the private signal and additional expert’s prediction similarly, except when the experts are biased. This is a departure from most research using similar environments, which assume that some sub-optimal behavior can be attributed to mistrust in others’ ability to understand the environment. That assumption may warrant further and more careful evaluation. The most striking valuation behavior is when participants are biased. Their bids are higher when their existing information set already favors their bias, relative to when it is against it. Doing so is antithetical to the rational equilibrium and inconsistent with prior research on confirmation bias.</p><p dir="ltr">Participants generally utilize information obtained from a successful bid at a lower rate when it is against the initial experts than with it. No difference is detected between information sources. This is expected, albeit inconsistent with rational decision-making. One exception is noted. When participants are biased, they use the newly obtained information at a much higher rate when it is consistent with their bias than against it. Doing so is at odds with bidding behavior, as it implies participants bid more to receive information that they utilize less. Participants generally do a much better job of rationalizing and responding to the experts’ bias than their own in the experiment.</p><p dir="ltr">My third chapter is motivated partly by the findings in my first two chapters, using a more contextualized setting. In it, subjects are presented with a series of X account versions. The versions vary on political affiliation, occupation credentials, and number of followers. Subjects are asked to rate how much they would value information from each account version. Subjects value account versions with an unrevealed political party affiliation more than their analogs which report a party affiliation, regardless of the party or the subject’s beliefs.</p><p dir="ltr">A partisan penalty is uniformly implemented. Additionally, credentials are insufficient to overcome bias concerns. The penalty assessed to an account version aligning with a party is similar when the version has high credentials versus when it does not. Followers are also a valuable resource, regardless of political affiliation or credential levels. The marginal value that followers provide is similar for all account versions, meaning that even relative experts in a field should seek validation if they want to be valued by others.</p><p dir="ltr">Previous research would expect subjects to value versions more when they are congruent with their own beliefs, so these findings are surprising. Two groups are identified as the most likely to deviate and value same-typed account versions more: subjects who believe echo chambers are good and subjects who are concerned they have believed fake news in the past. The former group does not require a significant number of followers to highly value a politically congruent account version. The latter value politically unaffiliated accounts even more, but are more skeptical of opposition account versions and are even more sensitive to the number of followers they have.</p><p dir="ltr">These three chapters explore new avenues for researching how biases and expertise are evaluated and responded to. People are generally much better at considering the potential biases that others have than rationalizing their own biases. I also find good news in an era of heightened concern about eroding trust in experts. In each case, subjects respond to signals of expertise, and demonstrate efforts to exploit the information that experts provide.</p>

The general topic of our thesis is forward looking behavior in strategic situations. Mixing theoretical and experimental analysis, we document how strategic thinking is affected by the specific features of a dynamic interaction. The overarching result is that the information regarding decisions that are close to the current one, receive a qualitatively different consideration, with respect to distant ones. That is, the actual decisions are based on reasoning over a limited number of steps, close to actual decison node. We capture this feature of behavior both in a strategic (limited backward induction) and in a non-strategic (limited farsightedness) set up, and we identify relevant consequences on the outcome of the interaction, which powerfullly explain many observed experimental regularities.<p>In the first essay, we present a general out-of-equilibrium framework for strategic thinking in sequential games. It assumes the agents to take decisions on restricted game trees, according to their (limited) foresight level, following backward induction. Therefore we talk of limited backward induction (LBI). We test for LBI using a variant of the race game. Our design allows to identify restricted game trees and backward reasoning, thus properly disentangling LBI behavior. The results provide strong support in favor of LBI. Most players solve intermediate tasks - i.e. restricted games - without reasoning on the terminal histories. Only a small fraction of subjects play close to equilibrium, and (slow) convergence toward it appears, though only in the base game. An intermediate task keeps the subjects off the equilibrium path longer than in the base game. The results cannot be rationalized using the most popular models of strategic reasoning, let alone equilibrium analysis.<p>In the second essay, a subtle implication of the model is investigated: the sensitivity of the players’ foresight to the accessibility and completeness of the information they have, using a Centipede game. By manipulating the way in which information is provided to subjects, we show that reduced availability of information is sufficient to shift the distribution of take-nodes further from the equilibrium prediction. On the other hand, similar results are obtained in a treatment where reduced availability of information is combined with an attempt to elicit preferences for reciprocity, through the presentation of the centipede as a repeated trust game. Our results could be interpreted as cognitive limitations being more effective than preferences in determining (shifts in) behavior in our experimental centipede. Furthermore our results are at odds with the recent ones in Cox [2012], suggesting caution in generalizing their results. Reducing the availability of information may hamper backward induction or induce myopic behavior, depending on the strategic environment.<p>The third essay consists of an experimental investigation of farsighted versus myopic behavior in network formation. Pairwise stability Jackson and Wolinsky [1996] is the standard stability concept in network formation. It assumes myopic behavior of the agents in the sense that they do not forecast how others might react to their actions. Assuming that agents are perfectly farsighted, related stability concepts have been proposed. We design a simple network formation experiment to test these extreme theories, but find evidence against both of them: the subjects are consistent with an intermediate rule of behavior, which we interpret as a form of limited farsightedness. On aggregate, the selection among multiple pairwise stable networks (and the performance of farsighted stability) crucially depends on the level of farsightedness needed to sustain them, and not on efficiency or cooperative considerations. Individual behavior analysis corroborates this interpretation, and suggests, in general, a low level of farsightedness (around two steps) on the part of the agents. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished