Bounded Rationality and Beyond
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Behavioral Economics has Never Been Hotter

Behavioral Economics has Never Been Hotter | Bounded Rationality and Beyond | Scoop.it

Behavioral economics is a perfect example of interdisciplinary thinking, as ideas first developed by psychologists have come to inspire all sorts of microeconomic models. This trendy economics theory shows how emotions, instincts and biases shape our behavior. .

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Bounded Rationality and Beyond
News on the effects of bounded rationality in economics and business, relationships and politics
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The Seneca Effect: The Seneca Effect: why decline is faster than growth

The Seneca Effect: The Seneca Effect: why decline is faster than growth | Bounded Rationality and Beyond | Scoop.it

Don't you stumble, sometimes, into something that seems to make a lot of sense, but you can't say exactly why? For a long time, I had in mind the idea that when things start going bad, they tend to go bad fast. We might call this tendency the "Seneca effect" or the "Seneca cliff," from Lucius Annaeus Seneca who wrote that "increases are of sluggish growth, but the way to ruin is rapid." Could it be that the Seneca cliff is what we are facing, right now? If that is the case, then we are in trouble. With oil production peaking or set to peak soon, it is hard to think that we are going to see a gentle downward slope of the economy. Rather, we may see a decline so fast that we can only call it "collapse." The symptoms are all there, but how to prove that it is what is really in store for us? It is not enough to quote a Roman philosopher who lived two thousand years ago. We need to understand what factors might lead us to fall much faster than we have been growing so far. For that, we need to make a model and see how the various elements of the economic system may interact with each other to generate collapse. I have been working on this idea for quite a while and now I think I can make such a model. This is what the rest of this post will be about. We'll see that a Seneca cliff may indeed be part of our future if we keep acting as we have been acting so far (and as we probably will). But let's go into the details.

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Selective Maintenance of Value Information Helps Resolve the Exploration/Exploitation Dilemma

Laboratory studies of value-based decision-making often involve choosing among a few discrete actions. Yet in natural environments, we encounter a multitude of options whose values may be unknown or poorly estimated. Given that our cognitive capacity is bounded, in complex environments, it becomes hard to solve the challenge of whether to exploit an action with known value or search for even better alternatives. In reinforcement learning, the intractable exploration/exploitation tradeoff is typically handled by controlling the temperature parameter of the softmax stochastic exploration policy or by encouraging the selection of uncertain options. We describe how selectively maintaining high-value actions in a manner that reduces their information content helps to resolve the exploration/exploitation dilemma during a reinforcement-based timing task. By definition of the softmax policy, the information content (i.e., Shannon's entropy) of the value representation controls the shift from exploration to exploitation. When subjective values for different response times are similar, the entropy is high, inducing exploration. Under selective maintenance, entropy declines as the agent preferentially maps the most valuable parts of the environment and forgets the rest, facilitating exploitation. We demonstrate in silico that this memory-constrained algorithm performs as well as cognitively demanding uncertainty-driven exploration, even though the latter yields a more accurate representation of the contingency. We found that human behavior was best characterized by a selective maintenance model. Information dynamics consistent with selective maintenance were most pronounced in better-performing subjects, in those with higher non-verbal intelligence, and in learnable vs. unlearnable contingencies. Entropy of value traces shaped human exploration behavior (response time swings), whereas uncertainty-driven exploration was not supported by Bayesian model comparison. In summary, when the action space is large, strategic maintenance of value information reduces cognitive load and facilitates the resolution of the exploration/exploitation dilemma.


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Gil Kalai’s Argument Against Quantum Computers

Gil Kalai’s Argument Against Quantum Computers | Bounded Rationality and Beyond | Scoop.it

Sixteen years ago, on a cold February day at Yale University, a poster caught Gil Kalai’s eye. It advertised a series of lectures by Michel Devoret, a well-known expert on experimental efforts in quantum computing. The talks promised to explore the question “Quantum Computer: Miracle or Mirage?” Kalai expected a vigorous discussion of the pros and cons of quantum computing. Instead, he recalled, “the skeptical direction was a little bit neglected.” He set out to explore that skeptical view himself. Today, Kalai, a mathematician at Hebrew University in Jerusalem, is one of the most prominent of a loose group of mathematicians, physicists and computer scientists arguing that quantum computing, for all its theoretical promise, is something of a mirage. Some argue that there exist good theoretical reasons why the innards of a quantum computer — the “qubits” — will never be able to consistently perform the complex choreography asked of them. Others say that the machines will never work in practice, or that if they are built, their advantages won’t be great enough to make up for the expense.

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An interview based study of pioneering experiences in teaching and learning Complex Systems in Higher Education

Due to the interdisciplinary nature of complex systems as a field, students studying complex systems at University level have diverse disciplinary backgrounds. This brings challenges (e.g. wide range of computer programming skills) but also opportunities (e.g. facilitating interdisciplinary interactions and projects) for the classroom. However, there is little published regarding how these challenges and opportunities are handled in teaching and learning Complex Systems as an explicit subject in higher education, and how this differs in comparison to other subject areas. We seek to explore these particular challenges and opportunities via an interview-based study of pioneering teachers and learners (conducted amongst the authors) regarding their experiences. We compare and contrast those experiences, and analyse them with respect to the educational literature. Our discussions explored: approaches to curriculum design, how theories/models/frameworks of teaching and learning informed decisions and experience, how diversity in student backgrounds was addressed, and assessment task design. We found a striking level of commonality in the issues expressed as well as the strategies to handle them, for example a significant focus on problem-based learning, and the use of major student-led creative projects for both achieving and assessing learning outcomes.

 

J.T. Lizier, M.S. Harré, M. Mitchell, S. DeDeo, C. Finn, K. Lindgren, A.L. Lizier, H. Sayama

"An interview based study of pioneering experiences in teaching and learning Complex Systems in Higher Education"

arXiv:1802.02707, 2018


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How Coca-Cola, Netflix, and Amazon Learn from Failure

How Coca-Cola, Netflix, and Amazon Learn from Failure | Bounded Rationality and Beyond | Scoop.it

Encourage your team to embrace mistakes.

Why, all of a sudden, are so many successful business leaders urging their companies and colleagues to make more mistakes and embrace more failures? In May, right after he became CEO of Coca-Cola Co., James Quincey called upon rank-and-file managers to get beyond the fear of failure that had dogged the company since the “New Coke” fiasco of so many years ago. “If we’re not making mistakes,” he insisted, “we’re not trying hard enough.” In June, even as his company was enjoying unparalleled success with its subscribers, Netflix CEO Reed Hastings worried that his fabulously valuable streaming service had too many hit shows and was canceling too few new shows. “Our hit ratio is too high right now,” he told a technology conference. “We have to take more risk…to try more crazy things…we should have a higher cancel rate overall.”

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Controllability and Observability of Complex Systems - Yang-Yu Liu

OVERVIEW: The ultimate proof of our understanding of complex systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered systems towards a desired state, a framework to control complex systems is lacking. In this talk I will show that many dynamic properties of complex systems can studied be quantitatively, via a combination of tools from control theory, network science and statistical physics. In particular, I will focus on two dual concepts, i.e. controllability and observability, of general complex systems. Controllability concerns our ability to drive the system from any initial state to any final state within finite time, while observability concerns the possibility of deducing the system's internal state from observing its input-output behavior. I will show that by exploring the underlying network structure of complex systems one can determine the driver (or sensor) nodes that with time-dependent inputs (or measurements) will enable us to fully control (or observe) the whole system.Summer School in cognitive Science: Web Science and the Mind Institut des sciences cognitives, UQAM, Montréal, Canada http://www.summer14.isc.uqam.ca

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Identifying and modeling the structural discontinuities of human interactions

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Mente & computazione

Mente & computazione | Bounded Rationality and Beyond | Scoop.it

Si propone un’analisi comparata dei modelli simbolici e sub-simbolici dellamente, in relazione alla nozioni di Turing-computabilità, di amplicazioned’informazione e di sistema dissipativo. Si mostra che una contrapposizionetra le due classi di modelli costituisce un errore epistemologico. Si introduceil concetto di computazione naturale e se ne discutono le caratteristiche. Unarelazione tra i modelli dell’attività cognitiva può essere delineata utilizzandola nozione di emergenza nei sistemi logicamente aperti. Si discute il ruoloche possono giocare i modelli quantistici per la costruzione di uno scenarioteorico unitario nella scienza della mente, con particolare riguardo agli aspetti computazionali

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Diversity of meso-scale architecture in human and non-human connectomes | Nature Communications

Brain function is reflected in connectome community structure. The dominant view is thatcommunities are assortative and segregated from one another, supporting specializedinformation processing. However, this view precludes the possibility of non-assortativecommunities whose complex inter-community interactions could engender a richer functionalrepertoire. We use weighted stochastic blockmodels to uncover the meso-scale architectureofDrosophila, mouse, rat, macaque, and human connectomes. Wefind that most commu-nities are assortative, though others form core-periphery and disassortative structures, whichbetter recapitulate observed patterns of functional connectivity and gene co-expression inhuman and mouse connectomes compared to standard community detection techniques. Wedefine measures for quantifying the diversity of communities in which brain regions parti-cipate, showing that this measure is peaked in control and subcortical systems in humans,and that inter-individual differences are correlated with cognitive performance. Our reportpaints a more diverse portrait of connectome communities and demonstrates their cognitiverelevance
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A Conceptual Model Exploring the Dynamics of Government–Nonprofit Service Delivery Sungsook Cho, David F. Gillespie

Abstract This article explores the dynamics between government and human service nonprofits for service delivery in the United States. The authors initiate the development of a dynamic resource theory to explain the process of government–nonprofit interdependence for human service delivery. The theory is conceived from the application of system dynamics to dependencies arising through the process of resource exchange. They explain how government regulations can help to improve or to lower the quality of service and how the balance of power between government and nonprofits shifts over time. Elaboration, refinement, and testing of dynamic resource theory will improve our ability to manage and benefit from the government–nonprofit partnership.
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How biases, politics and egos derail business decisions | Strategy & Corporate Finance | McKinsey & Company

How biases, politics and egos derail business decisions | Strategy & Corporate Finance | McKinsey & Company | Bounded Rationality and Beyond | Scoop.it

When creating a strategy for your organization there are many obstacles. It's important to know what they are and how to get around them.

Peter Drucker famously said that “culture eats strategy for breakfast.” Nowhere is that more evident than in meetings to decide corporate strategies. In those rooms, egos and competing agendas, biases and social games reign. That’s because strategy isn’t the only thing at stake. Jobs - even careers - are on the line. How biases politics and egos derail business decisions The budget process intrudes, too. You may be discussing a five-year strategy, but everyone knows that what really matters is getting a “yes” to the first-year budget. The outcome of all these dynamics is the Hockey stick projection, confidently showing future success after a dip to account for first-year spending—a bold forecast that, more often than not, fails to materialize.

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6 Creepy Brainwashing Techniques You Can Use Today

6 Creepy Brainwashing Techniques You Can Use Today | Bounded Rationality and Beyond | Scoop.it

The human brain is an odd, glitchy machine that is influenced in all sorts of weird ways you never thought of. The world is full of shady self-help gurus and workplace seminars telling us how we can turn our lives around just by using the right words ("Don't say the cheese is 'spoiled' -- say it's 'aged'!"), as if language is a form of magic that can alter reality. But here's the thing: The human brain is an odd, glitchy machine that is influenced in all sorts of weird ways you never thought of. This is why politicians and salespeople can trick you into going along with them, just by toying with the words they use. Science is just now catching up to them, and has found that ...

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From Maps to Multi-dimensional Network Mechanisms of Mental Disorders

From Maps to Multi-dimensional Network Mechanisms of Mental Disorders | Bounded Rationality and Beyond | Scoop.it

The development of advanced neuroimaging techniques and their deployment in large cohorts has enabled an assessment of functional and structural brain network architecture at an unprecedented level of detail. Across many temporal and spatial scales, network neuroscience has emerged as a central focus of intellectual efforts, seeking meaningful descriptions of brain networks and explanatory sets of network features that underlie circuit function in health and dysfunction in disease. However, the tools of network science commonly deployed provide insight into brain function at a fundamentally descriptive level, often failing to identify (patho-)physiological mechanisms that link system-level phenomena to the multiple hierarchies of brain function. Here we describe recently developed techniques stemming from advances in complex systems and network science that have the potential to overcome this limitation, thereby contributing mechanistic insights into neuroanatomy, functional dynamics, and pathology. Finally, we build on the Research Domain Criteria framework, highlighting the notion that mental illnesses can be conceptualized as dysfunctions of neural circuitry present across conventional diagnostic boundaries, to sketch how network-based methods can be combined with pharmacological, intermediate phenotype, genetic, and magnetic stimulation studies to probe mechanisms of psychopathology.

 

From Maps to Multi-dimensional Network Mechanisms of Mental Disorders
Urs Braun, Axel Schaefer, Richard F. Betzel, Heike Tost, Andreas Meyer-Lindenberg, Danielle S. Bassett

Neuron
Volume 97, Issue 1, 3 January 2018, Pages 14-31


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COMPLEXITY, PROBLEM SOLVING, AND SUSTAINABLE SOCIETIES, by Joseph A. Tainter, 1996

OVERVIEW Historical knowledge is essential to practical applications of ecological economics. Systems of problem solving develop greater complexity and higher costs over long periods. In time such systems either require increasing energy subsidies or they collapse. Diminishing returns to complexity in problem solving limited the abilities of earlier societies to respond sustainably to challenges, and will shape contemporary responses to global change. To confront this dilemma we must understand both the role of energy in sustaining problem solving, and our historical position in systems of increasing complexity.
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AI’s Deep Problem

AI’s Deep Problem | Bounded Rationality and Beyond | Scoop.it

Artificial intelligence is modeled to some extent on the human brain; and there’s a deep problem with this approach. Machine learning is a subset of artificial intelligence (AI) where computer programs automatically learn from data without explicit programming. Inspired in part by the human biology, deep learning is a machine learning method that deploys layers of artificial neurons, called nodes, in an artificial brain called a neural network. Neuroscientists and psychologists have yet to fully understand how the human brain works. Similarly, there’s a big problem with deep learning; scientists do not really know exactly how deep learning reaches its decisions. In both cases, complexity is at the root of the lack of transparency. The human brain is complex; researchers estimate an adult male human brain to have 86 billion neurons on average [1]. Human neuroanatomy textbooks commonly gauge the number to be closer to 100 billion neurons. Similar to the human brain, deep learning consists of densely interconnected processing neurons, or nodes, arranged in multiple layers. Deep learning does not require explicit programming because it is designed to learn from vast amounts of input data. For example, Google’s deep learning program learned to recognize images of cats after being fed 10 million YouTube video thumbnails without hard coding or labeling the images [2].

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How disinformation spreads in a network

How disinformation spreads in a network | Bounded Rationality and Beyond | Scoop.it

Disinformation is kind of a problem these days, yeah? Fatih Erikli uses a simulation that works like a disaster spread model applied to social networks to give an idea of how disinformation spreads. I tried to visualize how a disinformation becomes a post-truth by the people who subscribed in a network. We can think this network as a social media such as Facebook or Twitter. The nodes (points) in the map represent individuals and the edges (lines) shows the relationships between them in the community. The disinformation will be forwarded to their audience by the unconscious internet (community) members. Set the “consciousness” parameter and select a node to run.

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An interview based study of pioneering experiences in teaching and learning Complex Systems in Higher Education –

An interview based study of pioneering experiences in teaching and learning Complex Systems in Higher Education – | Bounded Rationality and Beyond | Scoop.it
Due to the interdisciplinary nature of complex systems as a field, students studying complex systems at University level have diverse disciplinary backgrounds. This brings challenges (e.g. wide range of computer programming skills) but also opportunities (e.g. facilitating interdisciplinary interactions and projects) for the classroom. However, there is little published regarding how these challenges and opportunities…
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Talking Complex Systems Economics to people who understand complex systems | Prof Steve Keen on

Talking Complex Systems Economics to people who understand complex systems | Prof Steve Keen on | Bounded Rationality and Beyond | Scoop.it

Official Post from Prof Steve Keen: This talk was a pleasure to give, because for once I was talking to an audience which completely understands Complex Systems (unlike the vast majority of economists). In the case of "EASY"--the "Evolutionary and Adaptive Systems Research Group"(http://www.sussex.ac.uk/easy/)--they apply this methodo

This talk was a pleasure to give, because for once I was talking to an audience which completely understands Complex Systems (unlike the vast majority of economists). In the case of "EASY"--the "Evolutionary and Adaptive Systems Research Group"(http://www.sussex.ac.uk/easy/)--they apply this methodology to analysing the brain and consciousness, rather than economics. In this talk I: Outline Minsky (downloadable from https://sourceforge.net/projects/minsky/), the system dynamics platform I designed for economics to enable banks, debt and money to be easily incorporated into dynamic models of the economy, explain why mainstream economists believe that you don't have to include banks, debt and money in macroeconomic models and why they are profoundly wrong, discuss the attempt by some Neoclassical economists to get back to that Olde Religion now that the global economy is reviving somewhat, ten years after the Global Financial Crisis, and conclude by showing that macroeconomics does not have to be derived from microeconomics (which is impossible in the first place, because of emergent properties in complex evolutionary systems, which the economy manifestly is), but can instead be derived directly from macroeconomic definitions in a Complex Systems manner.

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Big Data 2017 | Albert László Barabási

Title: "Taming Complexity: From Network Science to Controlling Networks" Abstract: The ultimate proof of our understanding of biological or technologica
Abstract: The ultimate proof of our understanding of biological or technological systems is reflected in our ability to control them. While control theory offers mathematical tools to steer engineered and natural systems towards a desired state, we lack a framework to control complex self-organized systems. Here we explore the controllability of an arbitrary complex network, identifying the set of driver nodes whose time-dependent control can guide the system’s entire dynamics. We apply these tools to several real networks, unveiling how the network topology determines its controllability. Virtually all technological and biological networks must be able to control their internal processes. Given that, issues related to control deeply shape the topology and the vulnerability of real systems. Consequently unveiling the control principles of real networks, the goal of our research, forces us to address series of fundamental questions pertaining to our understanding of complex systems

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Nassim Nicholas Taleb Home & Professional Page

Nassim Nicholas Taleb Home & Professional Page | Bounded Rationality and Beyond | Scoop.it
author of the INCERTO a philosophical and practical essay on uncertainty (Antifragile , The Black Swan, Fooled by Randomness, and The Bed of Procrustes), a (so far) 4-volume "investigation of opacity, luck, uncertainty, probability, human error, risk,and decision making when we don’t understand the world, expressed in the form of a personal essay with autobiographical sections, stories, parables, and philosophical, historical, and scientific discussions in nonoverlapping volumes that can be accessed in any order." Amazon and B&N
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How to be Rational about Rationality – INCERTO – Medium

How to be Rational about Rationality [One of the more technical (and optional) chapters, at the end of Skin of the Game] Rory Sutherland claims that the real function for swimming pools is allowing the middle class to sit around in bathing suits without looking ridiculous. Same with New York restaurants: you think their mission is to feed people, but that’s not what they do. They are in the business of selling you overpriced liquor or Great Tuscan wines by the glass, yet get you into the door by serving you your low-carb (or low-something) dishes at breakeven cost. (This business model, of course, fails to work in Saudi Arabia). So when we look at religion and, to some extent ancestral superstitions, we should consider what purpose they serve, rather than focusing on the notion of “belief”, epistemic belief in its strict scientific definition. In science, belief is literal belief; it is right or wrong, never metaphorical. In real life, belief is an instrument to do things, not the end product. This is similar to vision: the purpose of your eyes is to orient you in the best possible way, and get you out of trouble when needed, or help you find a prey at distance. Your eyes are not sensors aimed at getting the electromagnetic spectrum of reality. Their job description is not to produce the most accurate scientific representation of reality; rather the most useful one for survival.

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Viable system model - Wikipedia

Viable system model - Wikipedia

The viable system model ( VSM) is a model of the organisational structure of any autonomous system capable of producing itself. A viable system is any system organised in such a way as to meet the demands of surviving in the changing environment. One of the prime features of systems that survive is that they are adaptable.

Empty The model was developed by operations research theorist and cybernetician Stafford Beer in his book Brain of the Firm (1972).[1] Together with Beer's earlier works on cybernetics applied to management, this book effectively founded management cybernetics. The first thing to note about the cybernetic theory of organizations encapsulated in the VSM is that viable systems are recursive; viable systems contain viable systems that can be modeled using an identical cybernetic description as the higher (and lower) level systems in the containment hierarchy (Beer expresses this property of viable systems as cybernetic isomorphism). A development of this model has originated the theoretical proposal called viable systems approach.
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How Brainwashing Works

How Brainwashing Works | Bounded Rationality and Beyond | Scoop.it

Dur­ing the Korean War, Korean and Chinese captors reportedly brainwashed American POWs held in prison camps. Several prisoners ultimately confessed to waging germ warfare -- which they hadn't -- and pledged allegiance to communism by th­e end of their captivity. At least 21 soldiers refused to come back to the United States when they were set free. ­It sounds impressive, but skeptics point ­out that it was 21 out of more than 20,000 prisoners in communist countries. Does brainwashing really work in any reliable way? In psychology, the study of brainwashing, often referred to as thought reform, falls into the sphere of "social influence." Social influence happens every minute of every day. It's the collection of ways in which people can change other people's attitudes, beliefs and behaviors. For instance, the compliance method aims to produce a change in a person's behavior and is not concerned with his attitudes or beliefs. It's the "Just do it" approach. Persuasion, on the other hand, aims for a change in attitude, or "Do it because it'll make you feel good/happy/healthy/successful." The education method (which is called the "propaganda method" when you don't believe in what's being taught) goes for the social-influence gold, trying to affect a change in the person's beliefs, along the lines of "Do it because you know it's the right thing to do." Brainwashing is a severe form of social influence that combine­s all of these approaches to cause changes in someone's way of thinking without that person's consent and often against his will.Brainwashing is the attempt to change the thoughts and beliefs of another person against their will. Learn about the science behind brainwashing.

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La notion de résilience

La notion de résilience | Bounded Rationality and Beyond | Scoop.it
Afin de traiter de la résilience des territoires face aux chocs à venir, je me base sur le livre "Petit traité de résilience locale", disponible en PDF ici, co-écrit par A. Sinaï, R. Stevens, H. Carton et P. Servigne. Je résume notamment deux des 4 grandes parties du livre ("Une résilience globale pour faire face…
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Don’t Persuade Customers — Just Change Their Behavior

Most businesses underestimate how hard it is to change people’s behavior. There is an assumption built into most marketing and advertising campaigns that if a business can just get your attention, give you a crucial piece of information about their brand, tell you about new features, or associate their brand with warm and fuzzy emotions, that they will be able to convince you to buy.

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