Summary: The Entrepreneurial Individual
Course logic:
● Entrepreneurship is about acting under uncertainty — combining cognition, behaviour, and
learning to create value despite limited resources.
● Across six weeks, the course progresses from the individual entrepreneur → to teams → to
cognitive mechanisms, showing how entrepreneurial success depends on how people think,
learn, act, and collaborate.
Week Theme Core insight Key theories/models
1 Introduction & Entrepreneurs “fail forward” — ● Real Options Reasoning (McGrath, 1999) – stages, portfolio
Background they treat ventures as real logic, “falling forward” concept.
options, learn through ● Entrepreneurial Learning Framework (Wang & Chugh,
experimentation, and embrace 2014) – dual knowledge types (propositional vs practical), dual
uncertainty. learning modes (explore ↔ exploit ; sense ↔ intuition).
2 Positive Success driven by self-belief, ● Social Cognitive Theory (Bandura) → basis of
Psychology of passion, and autonomy. Entrepreneurial Self-Efficacy (Newman et al., 2019).
Entrepreneurship Well-being and motivation ● Entrepreneurial Passion Theory (Newman et al., 2021) –
sustain performance. harmonious vs obsessive passion.
● Job Demands–Resources theory – explains engagement ↔
burnout balance.
3 AI-Augmented AI amplifies entrepreneurial ● AI–Entrepreneurship Nexus (Shepherd & Majchrzak, 2022)
Entrepreneurs ability — automates analysis, – augmentation logic.
enhances creativity, but needs ● Generative vs Predictive AI Framework (Obschonka et al.,
human judgment and ethics. 2025) – creativity vs risk reduction
● Generative vs Predictive AI Framework (Obschonka et al.,
2025) – creativity vs risk reduction.
● Human-AI Complementarity Model (Shay et al., 2025) –
“minimum viable AI” adoption stages.
4 Entrepreneurial Entrepreneurs use flexible ● Effectuation Theory (Sarasvathy, 2001) – 5 principles
Skills & logics — Effectuation, (bird-in-hand, affordable loss, lemonade, crazy quilt,
Strategies Bricolage, Hustle, Balanced pilot-in-plane).
Skills — to control what can’t ● Bricolage Theory (Baker & Nelson, 2005) – “making do” with
be predicted. available resources.
● Entrepreneurial Hustle (Fisher et al., 2020) – urgent,
unorthodox, useful action.
● Balanced Skills (Stuetzer et al., 2013) – skill breadth > depth.
5 Entrepreneurial Teams outperform individuals ● Transactive Memory System Theory (Lazar et al., 2022) –
Teams when composition, trust, and “who knows what” coordination.
complementarity align. ● Sharedness of Competence Framework (Reese et al., 2021) –
Performance evolves over time. shared entrepreneurial vs centralised managerial skills.
● Team–Venture Life-Cycle Model (Patzelt et al., 2021) –
alignment across stages.
6 Cognitive Biases Entrepreneurs think differently ● Cognitive Bias Framework (Baron, 1998) – counterfactual
& Heuristics — biases and heuristics drive thinking, affect infusion, self-justification.
action but can distort judgment. ● Prospect Theory (Kahneman & Tversky) – foundation of loss
Manage them consciously. aversion.
, 2
🧠 Thematic integration
1. Uncertainty as a constant
● Entrepreneurs cannot predict the future; they control through action and learning (Weeks 1
& 4).
● Uncertainty reframed as opportunity — variance = value.
2. The adaptive mind
● Learning, reflection, and self-efficacy (Weeks 1–2) underpin resilience.
● Biases (Week 6) and emotions both hinder and energise entrepreneurial judgement.
3. From individual to system
● Starts with individual cognition and behaviour → extends to AI collaboration (Week 3) and
team dynamics (Week 5).
● Modern entrepreneurship = augmented human agency — empowered by tech and teamwork.
4. Resourcefulness and control
● Whether through effectuation, bricolage, or hustle, entrepreneurs focus on what they can
influence, not what they can predict (Week 4).
● Portfolio logic (Week 1) + adaptive execution (Week 4) form the course’s central mindset.
5. The human factor
● Motivation (Week 2), collaboration (Week 5), and cognition (Week 6) make entrepreneurship
a deeply psychological and social process.
● Autonomy, trust, and reflection link performance and well-being.
💡 Cross-cutting takeaways
● Fail forward: treat every initiative as an experiment; learn, adapt, repeat.
● Self-belief fuels action: self-efficacy and passion sustain effort under pressure.
● AI & humans: best outcomes emerge when machines handle data, humans add creativity and
ethics.
● No one-size-fits-all strategy: blend effectuation, bricolage, and causation based on context.
● Team success = design + trust + diversity: combine friendship and complementarity,
manage conflict, ensure psychological safety.
● Bias awareness = decision edge: recognise overconfidence and loss aversion; use reflection
and feedback to recalibrate.
🧾 TL;DR – The Entrepreneurial Individual in one line
Entrepreneurship = learning under uncertainty — combining adaptive thinking, motivated action, and
collaborative intelligence to turn risk into opportunity.
, 3
Week 1: Introduction
🧠 Core idea(s)
● Entrepreneurship = to act under uncertainty, manage risk + learn through experiments.
● Success = few big upsides + many cheap failures → portfolio logic.
📄 Key paper insights
McGrath (1999) – Falling Forward
● Main premise: Failure = integral to wealth creation under uncertainty.
● Core arguments:
○ Entrepreneurial initiatives = real options → low initial cost, large potential upside.
○ Stage investments → observe → decide to continue or quit.
○ Antifailure bias suppresses experimentation + learning.
○ Portfolio of independent options > single big bet.
○ Bounded downside & strong upside rewards → active ecosystems.
● Take-home: Fail forward by running cheap experiments; contain losses, amplify learning.
Wang & Chugh (2014) – Entrepreneurial Learning
● Main premise: Entrepreneurial success = adaptive learning mixing theory + practice.
● Core arguments:
○ EL research fragmented → paper offers
integrated framework.
○ Distinguishes formal (propositional) vs tacit
(practical) knowledge.
○ Highlights social learning (peers, mentors).
○ Identifies dualities: explore ↔ exploit & sense
↔ intuition.
○ Effective entrepreneurs shift between modes
depending on stage + context.
● Take-home: Learn continuously via doing + reflecting;
stay agile across learning modes.
📘 Key lecture insights
Entrepreneur defined
● Agent of change (role in society); creates and destroys (old → new industries).
● Focus on opportunity recognition, evaluation, and exploitation.
● Operates mainly in start-ups → speed + fewer barriers.
Core forces
● Uncertainty (known as variance) | Failure | Opportunity | Risk | Success
● Variance drives innovation → accept high risk of failure.
● Failure ≠ bad, high income (new ventures, projects, initiatives), high outcome (failures and
exits); also known as churn.
● Goal = max upside while bounding downside.
● In essence, entrepreneurship as consistent, goal-oriented behavior is about leveraging
existing (often limited) resources in a smart way. And, creating and realizing upsides (while
keeping downsides manageable), dealing with uncertainty and risk in proactive ways.
Course logic:
● Entrepreneurship is about acting under uncertainty — combining cognition, behaviour, and
learning to create value despite limited resources.
● Across six weeks, the course progresses from the individual entrepreneur → to teams → to
cognitive mechanisms, showing how entrepreneurial success depends on how people think,
learn, act, and collaborate.
Week Theme Core insight Key theories/models
1 Introduction & Entrepreneurs “fail forward” — ● Real Options Reasoning (McGrath, 1999) – stages, portfolio
Background they treat ventures as real logic, “falling forward” concept.
options, learn through ● Entrepreneurial Learning Framework (Wang & Chugh,
experimentation, and embrace 2014) – dual knowledge types (propositional vs practical), dual
uncertainty. learning modes (explore ↔ exploit ; sense ↔ intuition).
2 Positive Success driven by self-belief, ● Social Cognitive Theory (Bandura) → basis of
Psychology of passion, and autonomy. Entrepreneurial Self-Efficacy (Newman et al., 2019).
Entrepreneurship Well-being and motivation ● Entrepreneurial Passion Theory (Newman et al., 2021) –
sustain performance. harmonious vs obsessive passion.
● Job Demands–Resources theory – explains engagement ↔
burnout balance.
3 AI-Augmented AI amplifies entrepreneurial ● AI–Entrepreneurship Nexus (Shepherd & Majchrzak, 2022)
Entrepreneurs ability — automates analysis, – augmentation logic.
enhances creativity, but needs ● Generative vs Predictive AI Framework (Obschonka et al.,
human judgment and ethics. 2025) – creativity vs risk reduction
● Generative vs Predictive AI Framework (Obschonka et al.,
2025) – creativity vs risk reduction.
● Human-AI Complementarity Model (Shay et al., 2025) –
“minimum viable AI” adoption stages.
4 Entrepreneurial Entrepreneurs use flexible ● Effectuation Theory (Sarasvathy, 2001) – 5 principles
Skills & logics — Effectuation, (bird-in-hand, affordable loss, lemonade, crazy quilt,
Strategies Bricolage, Hustle, Balanced pilot-in-plane).
Skills — to control what can’t ● Bricolage Theory (Baker & Nelson, 2005) – “making do” with
be predicted. available resources.
● Entrepreneurial Hustle (Fisher et al., 2020) – urgent,
unorthodox, useful action.
● Balanced Skills (Stuetzer et al., 2013) – skill breadth > depth.
5 Entrepreneurial Teams outperform individuals ● Transactive Memory System Theory (Lazar et al., 2022) –
Teams when composition, trust, and “who knows what” coordination.
complementarity align. ● Sharedness of Competence Framework (Reese et al., 2021) –
Performance evolves over time. shared entrepreneurial vs centralised managerial skills.
● Team–Venture Life-Cycle Model (Patzelt et al., 2021) –
alignment across stages.
6 Cognitive Biases Entrepreneurs think differently ● Cognitive Bias Framework (Baron, 1998) – counterfactual
& Heuristics — biases and heuristics drive thinking, affect infusion, self-justification.
action but can distort judgment. ● Prospect Theory (Kahneman & Tversky) – foundation of loss
Manage them consciously. aversion.
, 2
🧠 Thematic integration
1. Uncertainty as a constant
● Entrepreneurs cannot predict the future; they control through action and learning (Weeks 1
& 4).
● Uncertainty reframed as opportunity — variance = value.
2. The adaptive mind
● Learning, reflection, and self-efficacy (Weeks 1–2) underpin resilience.
● Biases (Week 6) and emotions both hinder and energise entrepreneurial judgement.
3. From individual to system
● Starts with individual cognition and behaviour → extends to AI collaboration (Week 3) and
team dynamics (Week 5).
● Modern entrepreneurship = augmented human agency — empowered by tech and teamwork.
4. Resourcefulness and control
● Whether through effectuation, bricolage, or hustle, entrepreneurs focus on what they can
influence, not what they can predict (Week 4).
● Portfolio logic (Week 1) + adaptive execution (Week 4) form the course’s central mindset.
5. The human factor
● Motivation (Week 2), collaboration (Week 5), and cognition (Week 6) make entrepreneurship
a deeply psychological and social process.
● Autonomy, trust, and reflection link performance and well-being.
💡 Cross-cutting takeaways
● Fail forward: treat every initiative as an experiment; learn, adapt, repeat.
● Self-belief fuels action: self-efficacy and passion sustain effort under pressure.
● AI & humans: best outcomes emerge when machines handle data, humans add creativity and
ethics.
● No one-size-fits-all strategy: blend effectuation, bricolage, and causation based on context.
● Team success = design + trust + diversity: combine friendship and complementarity,
manage conflict, ensure psychological safety.
● Bias awareness = decision edge: recognise overconfidence and loss aversion; use reflection
and feedback to recalibrate.
🧾 TL;DR – The Entrepreneurial Individual in one line
Entrepreneurship = learning under uncertainty — combining adaptive thinking, motivated action, and
collaborative intelligence to turn risk into opportunity.
, 3
Week 1: Introduction
🧠 Core idea(s)
● Entrepreneurship = to act under uncertainty, manage risk + learn through experiments.
● Success = few big upsides + many cheap failures → portfolio logic.
📄 Key paper insights
McGrath (1999) – Falling Forward
● Main premise: Failure = integral to wealth creation under uncertainty.
● Core arguments:
○ Entrepreneurial initiatives = real options → low initial cost, large potential upside.
○ Stage investments → observe → decide to continue or quit.
○ Antifailure bias suppresses experimentation + learning.
○ Portfolio of independent options > single big bet.
○ Bounded downside & strong upside rewards → active ecosystems.
● Take-home: Fail forward by running cheap experiments; contain losses, amplify learning.
Wang & Chugh (2014) – Entrepreneurial Learning
● Main premise: Entrepreneurial success = adaptive learning mixing theory + practice.
● Core arguments:
○ EL research fragmented → paper offers
integrated framework.
○ Distinguishes formal (propositional) vs tacit
(practical) knowledge.
○ Highlights social learning (peers, mentors).
○ Identifies dualities: explore ↔ exploit & sense
↔ intuition.
○ Effective entrepreneurs shift between modes
depending on stage + context.
● Take-home: Learn continuously via doing + reflecting;
stay agile across learning modes.
📘 Key lecture insights
Entrepreneur defined
● Agent of change (role in society); creates and destroys (old → new industries).
● Focus on opportunity recognition, evaluation, and exploitation.
● Operates mainly in start-ups → speed + fewer barriers.
Core forces
● Uncertainty (known as variance) | Failure | Opportunity | Risk | Success
● Variance drives innovation → accept high risk of failure.
● Failure ≠ bad, high income (new ventures, projects, initiatives), high outcome (failures and
exits); also known as churn.
● Goal = max upside while bounding downside.
● In essence, entrepreneurship as consistent, goal-oriented behavior is about leveraging
existing (often limited) resources in a smart way. And, creating and realizing upsides (while
keeping downsides manageable), dealing with uncertainty and risk in proactive ways.
