Homo Economicus vs. Behavioral Public Policy

• Policymakers often have a rational view on human behavior
• Policymakers often come from economics or law backgrounds

Homo Economicus

• A model that describes humans as rational and self-interested
• Humans make decisions to maximize their utility
• Operates on the assumption that individuals have perfect information
• Operates on the assumption that individuals have unlimited cognitive capacity
• Operates on the assumption that individuals have stable preferences

Behavioral Public Policy (BPP)

• An established strand in public policy research and policymaking
• Influenced by cognitive and social psychology, anthropology, behavioral economics, and sociology
• Recognizes that real-world decision-making is influenced by cognitive biases, heuristics, social norms, and emotions

Linear K-A-B Model

• Assumes human behavior follows a straightforward progression
• Knowledge (K): Individuals first acquire information about an issue
• Attitude (A): Knowledge shapes or changes their attitude toward the issue
• Behavior (B): Attitude directly influences behavior, leading to rational action
• Aligns with homo economicus, suggesting providing accurate information drives behavioral change
• Cognitive biases, emotions, and external factors can disrupt or reverse the relationship between knowledge, attitude, and behavior
• Knowledge alone is deemed unhelpful
• Awareness of risks may not change behavior due to habits, social norms, or present bias
• Positive attitudes may not translate to behavior due to status quo bias, inertia, or lack of incentives
• Cognitive dissonance effect means behavior can shape attitude

Policy Approaches

• Nudges are often more effective than simply providing knowledge
• Framing and timing of information influence decision-making
• Social norms and peer effects: Policies leveraging social influence are more persuasive than factual arguments

Behaviourally-Aligned Policy

• Effectiveness of a measure is explained in hindsight with behavioral insights
• Initiatives aligned with behavioral evidence a posteriori such as penalty point systems for driving licenses

Behaviourally-Informed Policy

• Behavioral insights are used when developing the measure
• Initiatives designed explicitly on previously existing behavioural evidence such as ban of pre-checked boxes in EU

Behaviourally-Tested Policy

• Measure is tested and proofed for effectiveness using behavioural insights
• Initiatives tested or scaled after an ad-hoc experiment such as self-commitment strategies to address gamblers' overconfidence and myopia in online gambling

Social Psychology Perspective

• Emphasizes well-defined constructs and how they influence behavior
• Conceptual models or path diagrams are usually used to explain behavior

Agent-Based Modeling Perspective

• Focuses on how individual agents with attributes/behaviors interact in a simulated environment
• Agent interactions produce emergent outcomes at the group or societal level

Contrasting Social-Psychological Modelling vs ABM

• Social-psychological modelling is more aggregated/conceptual
• ABM is more bottom-up/computational
• Social psychology offers detailed theories of human behaviour
• ABM can test how those theories play out at scale in a simulated society

EU Policy Cycle

• Policy Design and Preparation -> Adoption
• Impact Assessment (IA)
• Implementation -> Application
• Monitoring and Evaluation
• Better Regulation guidelines integrate behavioral evidence into every step of policy formulation and evaluation
• ABM is a complementary tool within the Better Regulation framework
• ABM leverages behavioral parameters simulate complex interactions to enrich impact assessment

Agent-Based Modelling

• Many agent-based models use ad hoc implementations of decision-making processes
• Modelers may be unfamiliar or lack expertise to represent explanatory theories
• Challenges include selection of theories, finding/navigating relevant theories and formalization of theories
• Behavioral analyses should be implemented at the design stages by defining agent behaviors/interactions and establishing data requirements

Lecture 2: Behavioural Change

• Behaviours are observable and measurable actions of one or more actors towards one or more objects
• Transitions include changes in behaviour
• Current behavior (CB) to status quo and/or unwanted behaviour
• Future behaviour to define wanted behaviour

Optimising Policy Intervention with CB and FB Analysis

• If current and future behaviour is identified, behaviour change can be determined
• Formulation of behavior change helps design policy intervention
• Information about actors, objects, micro/meso/macro-level factors influencing behavior is needed
• The CLIMACS Framework defines interventions based on what part of the model is being targeted

CLIMACS Framework

• Continue, Learn, Increase: Applies to beneficial behaviors that already exist or need knowledge support
• Mitigate, Adapt: Addresses contexts where the existing behavior must be fine-tuned or adjusted
• Change, Stop: Relevant for undesirable behaviors that need to be replaced or halted
• Policymakers choose interventions based on which part of CLIMACS they're targeting
• Actors: Agents and their behaviours are actions and interactions
• Objects: Resources when the object is something the agent uses such as money

Lecture 3: Behavioural Drivers

• Kurt Lewin's CATS (Change as Three Steps) Model determines behaviour is driven by the psychological and contextual factors

CATS Model

• Unfreeze: Prepare people for change by disrupting their current equilibrium to overcome inertia
• Change: Actual behavior shifts occur via training, incentives, altered social norms, interventions, and clear communication
• Freeze: Stabilize the new behaviour, making it part of everyday practice
• B = f(P, E): Behavior (B) is a function of the person (P) and their environment (E)

Fundamental Attribution Error

• Tendency to underestimate contextual factors and overestimate individual factors
• Contextual Factors (S-frame): system, macro- and meso level
• Psychological Factors (I-frame): individual, micro level
• Motives: Driving force behind a person's actions (short-time)
• Values: Lifegoals or ideals that define what is important to people (long-time)

Key Elements of behaviour change

• Trust: Accepting vulnerability based upon positive expectations and/or context
• Attitudes: Evaluation of object/person/concept based on beliefs, emotions, and past behaviours
• Wellbeing: Personal and subjective 'contextual' factors

PESTEL Framework

• Structured analysis of meso- and macro-environment identifies threats and opportunities for behaviour change
• Political: government activity, taxes, trading, warfare, conflicts
• Economic: GDP, employment rate, inflation, welfare, prices of products
• Social: demographics, religion, education level, culture, cohesion
• Technological: access level, research, location of technology, quality
• Environmental: geography, trends, natural risks, facilities, health
• Legal: wages, rights, regulations

Social Factors for behaviour change

• Social factors relate to others, while psychological factors are individual
• Social perception can be norm-based (i.e. perceived norm) or observable (i.e. friends' relation)
• Social Norms: People compare themselves to those they identify with, adapting behaviour based on how they think those peers behave
• Social norms can be implicit or explicit

Descriptice Social Norms

• Implicit: inferring from subtle cues or observation
• Explicit: openly stated or communicated

Injunctive Social Norms

• Implicit: implied through subtle cues or social "rules of thumb"
• Explicit: stated outright through formal rules, policies, or direct statements

Lecture 4: Behavioural Theory and Application

• Behavioural theory: Scientifically validated idea explaining behaviour by psychological and contextual drivers/barriers

Ethical Nudging

• Considerations for ethical nudging include transparency, opt-in/out options, and wellbeing of affected individuals
• Select behavioural theory considering what behavioural change that was identified and the scientific domain

Key questions for behavioral analysis

• What is the level of analysis for the identified change and what data do you need/have?
• Data-driven theory uses an existing dataset or data collected to fit a theory
• Theory-driven uses a behavioural theory as a starting point and check to see if a data-set exists

Evaluating Behavioural Theory

• Search articles relevant to behavioral aspects, including domain, level, and data
• Evaluate empirical support, familiarity, and available analytical/measurement tools
• Social Identity Theory defines an influences on one's identity as a combination of interpersonal and intergroup interaction

Social Identity Theory

• Individuals compare themselves to the in-group and adapts behavior accordingly
• Pro: Helps explain different responses to different people (e.g. biases, stereotyping, favoritism, polarisation)

Values Beliefs Norms Theory

• Describes technology choices explained as a chain of effects
• Argues that decisions are not based solely on reasoned action, but it is rather linear
• Framework for pro-social or pro-environmental behaviors.
• Values shape information interpretation, influencing which issues they find important and their beliefs on environmental degradation

Asch Conformity Experiment

• Agreement to the majority position through the desire to 'fit in' or be liked (normative) or correct with identification
• Response to real (physical/imagined) or imagined group pressure

Unified Theory of Acceptance and Use of Technology

• Introduced to explain new technology adoption in the workplace; predominantly in management science/information studies
• Theory is narrowed to new technologies and behavior

Technology Acceptance Model (TAM)

• Designed to predict how users accept and use technology.
• According to TAM, Perceived Usefulness and Perceived Ease of Use directly influence a user's Attitude toward the technology.
• Attitudes then shape behavioral intention, which in turn leads to actual use
• External variables such as training, system characteristics, and user support can influence PU and PEOU

Innovation Diffusion Model

• Focuses on how an innovation spreads over time among members of a social system.

Key Points of Innovation Diffusion Model

• Relative Advantage: Is it better than what came before?
• Compatibility does it fit with existing characteristics
• Innovation: Is it difficult to understand and test
• Community: Can people test
• Observability: Are the results of the innovation visible to others?

Stage of Adoption

• Steps from communities to become part of the culture
• Knowledge: Awareness of community
• Persuasion: A favorable community
• D ecision: to adopt to new innovations or reject
• Implementation: individual to use
• Theory of Planned Behavior: Predicts and explains human behavior in specific contexts and is motivational

Key Factors of Planned Behaviour

• Attitude Toward the Behavior: An individual's overall evaluation of the community
• Subjective Norm: the performance of an individual
• Perceived Behavioral Control: An individual's perception, in there ability to perform the behaviour
• Behavioral Intention: Motivational factors that influence a behavior

Core Predictors of Behavioural Intention

• Performance Expectancy : Belief that using the technology will improve the outcomes for people
• Effort: Expected use
• Social: Others in the community contribute the the tecnology
• Facilitating Conditions: Support the community
• Addiction: the pleasure or fun from the use of tech
• Price: cost benifit assesssment
• Habit: the one will automatically have behaviour

Factors of behaviour

• Behaviour intent: to continue behaviour
• Use: adoption