A Field Study of Social Learning

We present a field study of social learning. The setting is a pair of adjacent fast food restaurants serving very similar cuisine whose main clientele are the students at a nearby major university. We observed whether an uninformed customer's choice of restaurant depends on the relative queue lengths at the two restaurants. Observations were made at two separate observation periods, the start of the academic year, when a significant proportion of customers had little or no experience with either restaurant, and the middle of the year, when most customers already had previous experience with the restaurants. It is found, consistent with the social learning hypothesis, that relative queue length has a significant effect at the first period but not at the second.

Does Television Terrify Tourists? Effects of US Television News on Demand for Tourism in Israel

In this paper we analyze a time series measuring the monthly flow of US tourists to Israel over the period 1997-2006. We pay particular attention to the response of tourists to variations in the intensity the Israeli-Palestinian conflict, drawing a distinction between actual conflict intensity and the intensity with which the conflict is reported in the US television media. We find that different dimensions of the conflict affect tourists in different ways. For some (but not all) dimensions of the conflict, reported intensity matters more than actual intensity

Peer effects in risk taking: Envy or conformity?

We examine two explanations for peer effects in risk taking: relative payoff concerns and preferences that depend on peer choices. We vary experimentally whether individuals can condition a simple lottery choice on the lottery choice or the lottery allocation of a peer. We find that peer effects increase significantly, almost double, when peers make choices, relative to when they are allocated a lottery. In both situations, imitation is the most frequent form of peer effect. Hence, peer effects in our environment are explained by a combination of relative payoff concerns and preferences that depend on peer choices. Comparative statics analyses and structural estimation results suggest that a norm to conform to the peer may explain why peer choices matter. Our results suggest that peer choices are important in generating peer effects and hence have important implications for modeling as well as for policy

Beliefs and expertise in sequential decision making

This work explores a sequential decision making problem with agents having diverse expertise and mismatched beliefs. We consider an N-agent sequential binary hypothesis test in which each agent sequentially makes a decision based not only on a private observation, but also on previous agents’ decisions. In addition, the agents have their own beliefs instead of the true prior, and have varying expertise in terms of the noise variance in the private signal. We focus on the risk of the last-acting agent, where precedent agents are selfish. Thus, we call this advisor(s)-advisee sequential decision making. We first derive the optimal decision rule by recursive belief update and conclude, counterintuitively, that beliefs deviating from the true prior could be optimal in this setting. The impact of diverse noise levels (which means diverse expertise levels) in the two-agent case is also considered and the analytical properties of the optimal belief curves are given. These curves, for certain cases, resemble probability weighting functions from cumulative prospect theory, and so we also discuss the choice of Prelec weighting functions as an approximation for the optimal beliefs, and the possible psychophysical optimality of human beliefs. Next, we consider an advisor selection problem where in the advisee of a certain belief chooses an advisor from a set of candidates with varying beliefs. We characterize the decision region for choosing such an advisor and argue that an advisee with beliefs varying from the true prior often ends up selecting a suboptimal advisor, indicating the need for a social planner. We close with a discussion on the implications of the study toward designing artificial intelligence systems for augmenting human intelligence.https://arxiv.org/abs/1812.04419First author draf

When half the truth is better than the truth: A Theory of aggregate information cascades

We introduce a new model of aggregate information cascades where only one of two possible actions is observable to others. When called upon, agents (who decide in some random order that they do not know) are only informed about the total number of others who have chosen the observable action before them. This informational structure arises nat- urally in many applications. Our most important result is that only one type of cascade arises in equilibrium, the aggregate cascade on the observable action. A cascade on the unobservable action never arises. Our results may have important policy consequences. Central agencies, for example in the health sector, may optimally decide to withhold in- formation from the public.

Towards quality-aware predesign model

An approach to capturing the semantics of qualityrequirements into an intermediate predesign model is outlined. This approach combines Klagenfurt Conceptual Predesign and Aspectual Predesign techniques. Proposed extensions in corporate the hierarchy of quality characteristics into the predesign model and represent crosscutting relationships between the quality concerns and the main functionality of the system. Some directions of integration of the proposed model into quality-driven software process are discussed.У статті розглядаються основи підходу до збирання семантики вимог якості у проміжну предпроектну модель. Цей підхід є поєднанням технологій Клагенфуртського концептуального предпроектування та аспектного предпроектування. Запропоновані додатки дозволяють включити до моделі іерархію характеристик якості та подати наскрізні відношини між інтересами якості та основною функціональністю системи. Обговорені деякі напрямки інтеграції запропонованої моделі у процесс розробки програмного забезпечення, що керується якістю

Biased Social Learning

This paper examines social learning when only one of the two types of decisions is observable. Because agents arrive randomly over time, and only those who invest are observed, later agents face a more complicated inference problem than in the standard model, as the absence of investment might reflect either a choice not to invest, or a lack of arrivals. We show that, as in the standard model, learning is complete if and only if signals are unbounded. If signals are bounded, cascades may occur, and whether they are more or less likely than in the standard model depends on a property of the signal distribution. If the hazard ratio of the distributions increases in the signal, it is more likely that no one invests in the standard model than in this one, and welfare is higher. Conclusions are reversed if the hazard ratio is decreasing. The monotonicity of the hazard ratio is the condition that guarantees the presence or absence of informational cascades in the standard herding model.Informational herds, Cascades, Selection bias

Herding with and without Payoff Externalities - An Internet Experiment

Most real world situations that are susceptible to herding are also characterized by direct payoff externalities. Yet, the bulk of the theoretical and experimental literature on herding has focused on pure informational externalities. In this paper we experi- mentally investigate the effects of several different forms of payoff externalities (e.g., network effects, first-mover advantage, etc.) in a standard information-based herding model. Our results are based on an internet experiment with more than 6000 subjects, including a subsample of 267 consultants from an international consulting firm. We also replicate and review earlier cascade experiments. Finally, we study reputation e¤ects (i.e., the influence of success models) in the context of herding.information cascades, herding, network e¤ects, experiment, internet.

Spontaneous diffusion of information in online social networks

Online Social Networks (OSN) are new types of web services which provide online communities an environment to gather and meet virtually. The online users are connected to each other via links of trust and utilize the features of the OSN to interact and communicate in an easy socio-technical way. Hence these virtual networks of social relationships have a high potential for influential decision-making and the word of mouth spread of information, but also for spreading fads, rumors, and erroneous information. The power of these new forms of social networks is also recognized by service providers, marketers and vendors of consumer goods. They would all like to (mis) use these existing communication channels to spread product placements, advertising and promotions directly to the connected users. However, just like the old economy businesses, not all attempted marketing initiatives are successful. Most of them fail or do notreach the desired audience. This paper tries to explain why OSN are a good environment for spontaneous diffusion of information and what phases of development need to beaccomplished to reach the optimal spreading rate for one piece information. Therefore, we start with a look at the "Hype Cycle" model of Gartner to explain over-enthusiasm for new technology adoptions. Next we introduce the concept of "social contagion" and the infections spread of information. After a short introduction of OSN, we try to illustrate the phases of a social online contagion development process which can lead to spontaneous and uncontrolled diffusion of information, messages or ideas. The core statement of our approach is that online individuals tend to behave collectively if they observe the virtual behaviors and actions of others. This principle of "other-directedness" can generate a chain reaction of infectious imitation which can sometimes spread uncontrolled through the interconnected social network like an epidemic. This helps to explain why some online information waves can grow extraordinarily high and others fall.Онлайнові соціальні мережі (ОСМ) є новими типами веб-сервісів, які пропонують онлайновим суспільствам середовище для гуртування та віртуального спілкування. Як наслідок, такі віртуальні мережі соціальних зв'язків мають високий потенціал для впливового прийняття рішень та розповсюдження інформації "з вуст в уста", але, з іншого боку, вони також можуть розповсюджувати чутки, плітки та некоректну інформацію. Потенціал цих мереж також розпізнається сервіс-провайдерами, маркетологами та виробниками товарів. Вони усі бажають використовувати ці існуючі комунікаційні канали для розповсюдження реклами продуктів безпосередньо користувачам. Але не усі такі спроби є успішними. Ця робота робить спробу пояснити, чому ОСМ є добрим середовищем для спонтанного розповсюдження інформації, та які етапи повинні бути виконані для досягнення оптимального рівня розповсюдження для одного елемента інформації. Ми починаємо з розгляду моделі гіперциклів Гартнера, яка пояснює надмірний ентузіазм при впровадженні нових технологій. Далі ми вводимо концепцію "соціального забруднення" та інфекційного розповсюдження інформації. Базова ідея нашого підходу полягає в тому, що онлайнові індивідуали прихильні до колективної поведінки, тобто вони спрямовані на віртуальну поведінку та дії інших. Цей принцип "спрямованості на інших" може генерувати ланцюгову реакцію інфекційних імітацій які інколи можуть розповсюджуватись неконтрольовано через соціальні мережі, подібно до епідемії