Collective Behaviour
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Herd Behavior and the Quality of Opinions
Journal of Socio-Economics 32 (2003) 661–673 Herd behavior and the quality of opinions Shinji Teraji Department of Economics, Yamaguchi University, 1677-1 Yoshida, Yamaguchi 753-8514, Japan Accepted 14 October 2003 Abstract This paper analyzes a decentralized decision model by adding some inertia in the social leaning process. Before making a decision, an agent can observe the group opinion in a society. Social learning can result in a variety of equilibrium behavioral patterns. For insufficient ranges of quality (precision) of opinions, the chosen stationary state is unique and globally accessible, in which all agents adopt the superior action. Sufficient quality of opinions gives rise to multiple stationary states. One of them will be characterized by inefficient herding. The confidence in the majority opinion then has serious welfare consequences. © 2003 Elsevier Inc. All rights reserved. JEL classification: D83 Keywords: Herd behavior; Social learning; Opinions; Equilibrium selection 1. Introduction Missing information is ubiquitous in our society. Product alternatives at the store, in catalogs, and on the Internet are seldom fully described, and detailed specifications are often hidden in manuals that are not easily accessible. In fact, which product a person decides to buy will depend on the experience of other purchasers. Learning from others is a central feature of most cognitive and choice activities, through which a group of interacting agents deals with environmental uncertainty. The effect of observing the consumption of others is described as the socialization effect. The pieces of information are processed by agents to update their assessments. Here people may change their preferences as a result of E-mail address: [email protected] (S. -
A Complex Adaptive Systems Perspective to Appreciative Inquiry: a Theoretical Analysis Payam Saadat George Fox University
http://journals.sfu.ca/abr ADVANCES IN BUSINESS RESEARCH 2015, Volume 6, pages 1-13 A Complex Adaptive Systems Perspective to Appreciative Inquiry: A Theoretical Analysis Payam Saadat George Fox University Appreciate inquiry is utilized to facilitate organizational change by encouraging stakeholders to explore positives and generative capacities within their organization. In the literature, analysis of the effectiveness of AI is confined to psychological and managerial explanations such as highlighting the promotion of positive mindset and collective organizational planning. This paper will discuss a complex adaptive systems (CAS) perspective and present a new model for understanding the functionality of AI. The emphasis of this paper is placed on exploring the effects of AI on the behavior and interactions of agents/employees related to how they cope with change. An analysis of AI’s functionality through the lens of CAS reveals two critical insights: a) AI enhances adaptability to change by strengthening communication among agents, which in turn fosters the emergence of effective team arrangements and a more rapid collective response to change and b) AI possesses the potential to generate a collective memory for social systems within an organization. Furthermore, a systematic analysis of AI indicates a close connection between this method and CAS-based styles of management. This paper concludes by suggesting that AI might represent a potential method with the capacity to place organizational teams at the edge of chaos. Keywords: appreciative inquiry, organizational change, management, complex adaptive systems, edge of chaos Introduction In today’s fast-paced world where the fluctuating preferences of consumers, the growth in the global web of interdependence, and technological advancements guide the co-evolving relationship between the dominant business environment and the social systems within its domain, an organization’s capacity to cope with change in a timely manner determines its survival (Hesselbein & Goldsmith, 2006; Macready & Meyer, 1999; Senge, 2006). -
A Behavioural and Neuroeconomic Analysis of Individual Differences
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Apollo Herding in Financial Behaviour: A Behavioural and Neuroeconomic Analysis of Individual Differences M. Baddeley, C. Burke, W. Schultz and P. Tobler May 2012 CWPE 1225 1 HERDING IN FINANCIAL BEHAVIOR: A BEHAVIOURAL AND NEUROECONOMIC ANALYSIS OF INDIVIDUAL DIFFERENCES1,2 ABSTRACT Experimental analyses have identified significant tendencies for individuals to follow herd decisions, a finding which has been explained using Bayesian principles. This paper outlines the results from a herding task designed to extend these analyses using evidence from a functional magnetic resonance imaging (fMRI) study. Empirically, we estimate logistic functions using panel estimation techniques to quantify the impact of herd decisions on individuals' financial decisions. We confirm that there are statistically significant propensities to herd and that social information about others' decisions has an impact on individuals' decisions. We extend these findings by identifying associations between herding propensities and individual characteristics including gender, age and various personality traits. In addition fMRI evidence shows that individual differences correlate strongly with activations in the amygdala – an area of the brain commonly associated with social decision-making. Individual differences also correlate strongly with amygdala activations during herding decisions. These findings are used to construct a two stage least squares model of financial herding which confirms that individual differences and neural responses play a role in modulating the propensity to herd. Keywords: herding; social influence; individual differences; neuroeconomics; fMRI; amygdala JEL codes: D03, D53, D70, D83, D87, G11 1. Introduction Herding occurs when individuals‘ private information is overwhelmed by the influence of public information about the decisions of a herd or group. -
Herd Behavior by Commonlit Staff 2014
Name: Class: Herd Behavior By CommonLit Staff 2014 “Herd behavior” is a term used to describe the tendency of individuals to think and act as a group. As you read, take notes on the causes of herd behavior. Background [1] The term “herd behavior” comes from the behavior of animals in herds, particularly when they are in a dangerous situation such as escaping a predator. All of the animals band closely together in a group and, in panic mode, move together as a unit. It is very unusual for a member of the herd to stray from the movement of the unit. The term also applies to human behavior, and it usually describes large numbers of people acting the same way at the same time. It often has a "Herd of Goats" by Unknown is in the public domain. connotation1 of irrationality, as people’s actions are driven by emotion rather than by thinking through a situation. Human herd behavior can be observed at large-scale demonstrations, riots, strikes, religious gatherings, sports events, and outbreaks of mob violence. When herd behavior sets in, an individual person’s judgment and opinion- forming process shut down as he or she automatically follows the group’s movement and behavior. Examples of Herd Behavior Herd behavior in humans is frequently observed at times of danger and panic; for example, a fire in a building often causes herd behavior, with people often suspending their individual reasoning and fleeing together in a pack. People in a crisis that requires escape will attempt to move faster than normal, copy the actions of others, interact physically with each other, and ignore alternative strategies in favor of following the mass escape trend. -
Changing People's Preferences by the State and the Law
CHANGING PEOPLE'S PREFERENCES BY THE STATE AND THE LAW Ariel Porat* In standard economic models, two basic assumptions are made: the first, that actors are rational and, the second, that actors' preferences are a given and exogenously determined. Behavioral economics—followed by behavioral law and economics—has questioned the first assumption. This article challenges the second one, arguing that in many instances, social welfare should be enhanced not by maximizing satisfaction of existing preferences but by changing the preferences themselves. The article identifies seven categories of cases where the traditional objections to intentional preferences change by the state and the law lose force and argues that in these cases, such a change warrants serious consideration. The article then proposes four different modes of intervention in people's preferences, varying in intensity, on the one hand, and the identity of their addressees, on the other, and explains the relative advantages and disadvantages of each form of intervention. * Alain Poher Professor of Law at Tel Aviv University, Fischel-Neil Distinguished Visiting Professor of Law at the University of Chicago Law School, Visiting Professor of Law at Stanford Law School (Fall 2016) and Visiting Professor of Law at Berkeley Law School (Spring 2017). For their very helpful comments, I thank Ronen Avraham, Oren Bar-Gill, Yitzhak Benbaji, Hanoch Dagan, Yuval Feldman, Talia Fisher, Haim Ganz, Jacob Goldin, Sharon Hannes, David Heyd, Amir Khoury, Roy Kreitner, Tami Kricheli-Katz, Shai Lavi, Daphna Lewinsohn- Zamir, Nira Liberman, Amir Licht, Haggai Porat, Eric Posner, Ariel Rubinstein, Uzi Segal, and the participants in workshops at the Interdisciplinary Center in Herzliya and the Tel Aviv University Faculty of Law. -
Conformity, Gender and the Sex Composition of the Group
Stockholm School of Economics Department of Economics Bachelor’s Thesis Spring 2010 Conformity, Gender and the Sex Composition of the Group Abstract In light of the current debate of the sex distribution in Swedish company boards we study how a proportional increase of women would affect conformity behavior. We compare conformity levels between men and women as well as conformity levels between same-sex and mixed-sex groups. The results suggest that same-sex groups conform significantly more than mixed-sex groups due to higher levels of normative social influence. No differences are found in the levels of informational or normative social influence between men and women. These finding possibly suggest lower levels of normative social influence in company boards with more equal sex distribution. Key Words: Conformity, Gender Differences, Group Composition Authors: Makan Amini* Fredrik Strömsten** Tutor: Tore Ellingsen Examiner: Örjan Sjöberg *E-mail: [email protected] **E-mail: [email protected] Acknowledgements We would like to thank our tutor Tore Ellingsen for his guidance and inspiration during the thesis work. We would also like to express our gratitude to Magnus Johannesson and Per-Henrik Hedberg who have devoted their time to support our work through very important and helpful comments. Finally we are impressed by the large number of students from the Stockholm School of Economics who participated in the experiments. This study would of course never have been possible without you. Table of Contents 1. Introduction............................................................................................................................................ -
Chapter 17: Social Change and Collective Behavior
CHAPTER 17 SocialSocial ChangeChange andand CollectiveCollective BehaviorBehavior 566 U S Your Sections I Sociological N Imagination 1. Social Change G 2. Theoretical Perspectives on Social Change hen you see photos or films showing the Plains Indians of the 3. Collective Behavior WOld West—Sioux, Crow, and so forth—what do you think about the culture 4. Social Movements of those Native Americans? If you’re like most of us, you may assume that it had re- mained unchanged for many centuries—that these people dressed and acted in exactly Learning Objectives the same way as their ancestors. We often assume that nonindustrial soci- eties such as these stand still over time. After reading this chapter, you will be able to Actually, though, sociology teaches us that change comes to all societies. Whether by ❖ illustrate the three social processes that borrowing from other cultures, discovering contribute to social change. new ways of doing things, or creating inven- ❖ discuss how technology, population, nat- tions that ripple through society, all peoples ural environment, revolution, and war experience social change. cause cultures to change. Let’s return to the example of the Plains Indians. You may picture these tribes as ❖ describe social change as viewed by the fierce, buffalo-hunting warriors. Perhaps im- functionalist and conflict perspectives. ages of Sitting Bull and Crazy Horse astride ❖ discuss rumors, fads, and fashions. fast horses attacking Custer come to mind, ❖ compare and contrast theories of crowd leading you to think that their ancestors for centuries had also ridden horses. In fact, behavior. horses were a relatively recent introduction ❖ compare and contrast theories of social to Plains Indian culture in the 1800s. -
The Emergence of Animal Social Complexity
The Emergence of Animal Social Complexity: theoretical and biobehavioral evidence Bradly Alicea Orthogonal Research (http://orthogonal-research.tumblr.com) Keywords: Social Complexity, Sociogenomics, Neuroendocrinology, Metastability AbstractAbstract ThisThis paper paper will will introduce introduce a a theorytheory ofof emergentemergent animalanimal socialsocial complexitycomplexity usingusing variousvarious results results from from computational computational models models andand empiricalempirical resultsresults.. TheseThese resultsresults willwill bebe organizedorganized into into a avertical vertical model model of of socialsocial complexity.complexity. ThisThis willwill supportsupport thethe perspperspectiveective thatthat social social complexity complexity is isin in essence essence an an emergent emergent phenomenon phenomenon while while helping helping to answerto answer of analysistwo interrelated larger than questions. the individual The first organism.of these involves The second how behavior involves is placingintegrated aggregate at units socialof analysis events larger into thethan context the individual of processes organism. occurring The secondwithin involvesindividual placing organi aggregatesms over timesocial (e.g. events genomic into the and context physiological of processes processes) occurring. withinBy using individual a complex organisms systems over perspective,time (e.g. fivegenomic principles and physiologicalof social complexity processes). can Bybe identified.using a complexThese principles systems -
Cyberbullying Ullying Has His- Cyberbullying
SPRING 2009 VOL. 36 NO. 108 TIInterEDInterEDHE JOURNALnter OF THE ASSOCIATIONION FOR THE ADVANCEMENEDT OF IINTERNATIONALIONAL EDUCATIONION AAIE IN THIS ISSUE Cyberbullying ullying has his- cyberbullying. Chib- President's Message --------------------------- 2 torically been re- By Barrie Jo Price, Anna C. baro (2007) states that portedB to be the most McFadden and Juanita McMath cyberbullying is one Executive Director's Message --------------- 3 common form of vic- of the most preva- Editor's Desk ------------------------------------- 4 timization in schools with over 5 million lent forms of harassment among Grade 6 students reporting being threatened physi- through Grade 8 students. Superintendent of the Year: Ladd ----------- 7 cally, verbally or indirectly every year, with that number on the rise as cyberbullying Though it may begin in elementary schools, Memo to the Board ----------------------------- 8 becomes part of a computer-mediated research indicates that Middle School stu- Recruiting & Retaining Staff -----------------11 culture (Harris, Petrie & Willoughby, dents appear to be the most frequent tar- 2002; Willard, 2006; Anderson & Sturm, gets or at least those for whom this activity Treasurer's Report ---------------------------- 12 2007). is most reported (Beale & Hall, 2007; Hin- duja & Patchin 2009). This finding, coupled Research is the Key -------------------------- 14 How frequently does cyberbullying occur? with a recent report from the Pew Research Superintendent of the Year Program ----- 17 Tonn (2006) reported on a study in which Center, shows half of all youth (in the U.S.) one third of United States (U.S.) youths online between the ages of 12 and 17 have GovNet ------------------------------------------ 19 surveyed (ages 12-17) reported experienc- a social networking account of some kind ing cyberbullying in the past 12 months, (Facebook, MySpace, etc.). -
Threshold Models of Collective Behavior!
Threshold Models of Collective Behavior! Mark Granovetter State University of New York at Stony Brook Models of collective behavior are developed for situations where actors have two alternatives and the costs and/or benefits of each depend on how many other actors choose which alternative. The key concept is that of "threshold": the number or proportion of others who must make one decision before a given actor does so; this is the point where net benefits begin to exceed net costs for that particular actor. Beginning with a frequency distribution of thresholds, the models allow calculation of the ultimate or "equilibrium" number making each decision. The stability of equilibrium results against various possible changes in threshold distributions is considered. Stress is placed on the importance of exact distributions for outcomes. Groups with similar average preferences may generate very different results; hence it is hazardous to infer individual dispositions from aggregate outcomes or to assume that behavior was directed by ultimately agreed-upon norms. Suggested applications are to riot behavior, innovation and rumor diffusion, strikes, voting, and migra tion. Issues of measurement, falsification, and verification are dis cussed. BACKGROUND AND DESCRIPTION OF THE MODELS Because sociological theory tends to explain behavior by institutionalized norms and values, the study of behavior inexplicable in this way occupies a peripheral position in systematic theory. Work in the subfields which embody this concern-deviance for individuals and collective behavior for groups-often consists of attempts to show what prevented the established patterns from exerting their usual sway. In the field of collective behavior, one such effort involves the assertion that new norms or beliefs "emerge" 1 This report is heavily indebted to three co-workers. -
Economic Forecasting. Experimental Evidence on Individual Biases
ECONOMIC FORECASTING EXPERIMENTAL EVIDENCE ON INDIVIDUAL BIASES, GROUP COOPERATION AND HERD BEHAVIOR Dissertation zur Erlangung des Doktorgrades der Wirtschaftswissenschaftlichen Fakultät der Georg-August-Universität Göttingen vorgelegt von Lukas Meub geboren in Lich Göttingen, 2014 Erstgutachter: Prof. Dr. Kilian Bizer Zweitgutachter: Prof. Dr. Markus Spiwoks Weiteres Mitglied der Prüfungskommission: Prof. Dr. Claudia Keser CONTENTS 1 INTRODUCTION AND SUMMARY 1 2 ANCHORING: A VALID EXPLANATION 21 FOR BIASED FORECASTS WHEN RATIONAL PREDICTIONS ARE EASILY ACCESSIBLE AND WELL INCENTIVIZED? (with Till Proeger and Kilian Bizer) 3 AN EXPERIMENTAL STUDY ON SOCIAL ANCHORING 49 (with Till Proeger) 4 ARE GROUPS LESS BEHAVIORAL? 75 THE CASE OF ANCHORING (with Till Proeger) 5 OVERCONFIDENCE AS A SOCIAL BIAS: 109 EXPERIMENTAL EVIDENCE (with Till Proeger) 6 STRATEGIC COORDINATION IN FORECASTING: 123 AN EXPERIMENTAL STUDY (with Kilian Bizer, Till Proeger and Markus Spiwoks) 7 A COMPARISON OF ENDOGENOUS AND EXOGENOUS 169 TIMING IN A SOCIAL LEARNING EXPERIMENT (with Till Proeger and Hendrik Hüning) 8 THE IMPACT OF COMMUNICATION REGIMES 201 ON GROUP RATIONALITY: EXPERIMENTAL EVIDENCE (with Till Proeger) V VI Chapter I INTRODUCTION AND SUMMARY - 1 - - 2 - “Much has been written about the doubtful accuracy of economists’ predictions. [...] They are better at predicting the direction than the actual magnitude of events. [...] This is disappointing, but it does not mean that economics is not a science.” (‘Economics’, Encyclopædia Britannica1) The forecasting of economic developments guides decisions in all areas of public interest, whether in governments, finance or corporations.2 Accurate predictions hold an essential role for private and public actors’ ability to enable the efficient planning and execution of their strategic objectives. -
Digital Interaction and Empathy. the Challenges and Opportunities of Combining Technology with Artificial Intelligence
Expert report Digital interaction and empathy. The challenges and opportunities of combining technology with artificial intelligence. 29 April 2019 PREFACE People are profoundly social creatures. Every day, we think together? At best, joint thinking can be compared to opment into an effectively interacting individual takes many wonder what other people think of us. Despite knowing that running a kilometer in just one minute, which sounds impos times as long as for other animals. It has been suggested that lying is wrong, we do so to make a better impression on oth sible. For individuals it is indeed impossible, but joint think this is because there is so much to learn in mutual interac ers. Some researchers believe that reason evolved so that we ing based on effective interaction makes things possible that tion. could make arguments for, and justify, solutions that we had seemed impossible at first. already chosen. In so far as our capabilities allow, we are all responsible We humans do not always use our opportunities construc for how we treat each other. Such a responsibility applies The latest technological developments challenge people tively. We intentionally offend one another, build threat sce even when we are not facetoface with the other person. to consider their own strengths, those abilities which are so narios and behave nastily and unpleasantly towards others. unique that a machine cannot be programmed to replicate Such behavior can have serious consequences. For a child, The new social media environments and the Internet in them. Such strengths involve creative, unpredictable solu it can result in lifelong trauma.