1. David vs. Goliath in Developer Decision Making & Performance Keelan Cunningham – Msc Real Estate

2. Building Decision Making

3. Research Hypothesis Distinct Developer Types adopt Different Strategies to formulate Profit Expectations which in turn Impacts Developer Performance.

4. Research Drivers 1.Full-time Student, Recovering Property Investor! 2.Some Barely Survived…Others Thrived…Why? 3.Dissatisfaction – Where’s My Developer!? 4.Distinct Developer Types – Homogenous!?

5. Research Rationale & Genesis “Leaving aside the impact of market dynamics and property cycles, is there an approach to decision-making, a veritable “secret sauce”, that determines performance outcomes which doesn’t solely rely on some econometric, tightly- sprung financial modelling?”

6. Research Objectives 1.To evaluate the start/stop development decision-making factors by developer type. 2.To analyse the decision-making behaviour of distinct developer types. 3.To critically examine the main influences and influencers on property developers‘ decision-making. 4.To develop a critical understanding of development performance as measured by developer type.

7. Parameters – Distinct Developer Types Small, Independent Developers Mid-Size Developers Large, plc Developers  <50 Direct Employees  Privately- owned  Turnover:>£25 m  Net Assets: >£25m-£100m  >50-99 Direct Employees  Public or Privately Owned  Turnover >£100m- £749m  Net Assets:  >100 Direct Employees  Publically- owned  Turnover: >£750m  Net Assets: >£1bn

8. Research Strategy & Method Quantitative - Statistical Analysis of Planning Applications. Reason Why: Proxy for developer intentions Qualitative - Semi-Structured Interviews Reason Why: Deeper, exploratory & higher-response.

9. Interviews – Participant Selection

10. Qualitative Data Analysis – Theme Matrix Theme Matrix: Key Themes Identified Impacting Decision-Making Start/StopID1ID2ID3ID4LD1LD2LD3CAB1CAB2CAB3F1F2 Interest & Background -XXX---XXXXX Equity XXXXXXX-XXXX Available Land XXXX----X--X Overseas Investors ---X-X-X--X- Cycle Watching ----XX-X--XX BehaviourID1ID2ID3ID4LD1LD2LD3CAB1CAB2CAB3F1F2 Returns Incr Over Dev. ----XXX-XX-- Trader/Exit Fast -XXX-XX--XXX No ROT XXXXXXXXXXXX Intuitive XXXX-X-XXX-- Low-Med Risk XXXXXXXX--XX

11. Qualitative Data Analysis – Theme Matrix Themes Identified Impacting Decision-Making (Cont.) Influence& Influencers ID1ID2ID3ID4LD1LD2LD3CAB1CAB2CAB3F1F2 Planning/ Consultant XXXXXXXXXX-- Professionals XXXX-X-XXXXX Internal Loans X---XX------ Sustainability = Planning XXXXXXXXXXXX Constr Costs XX-X-XX----X Dev. Perform. ID1ID2ID3ID4LD1LD2LD3CAB1CAB2CAB3F1F2 Stability -XXX-------- Profit and/or ROCE XXXX-XX-XXXX Short Timeline XXXX------XX Constr Costs XX-X-XX---XX Internal Loans X---XXX-----

12. Key Finding – Distinct Developer Profit Developer Profits Quoted ID1ID2ID3ID4LD1LD2LD3CAB1CAB2CAB3F1F2 25%+20%+ -25%+25%-20% 20 - 25% >10% 15- 16% Independent Developers vs. Large plc Developers

13. Key Finding – Evolving Profit Expectations Large plc Developers: Appraisal Stages Acquisition Appraisal Purchase Appraisal Planning Appraisal 2% Increase

14. Key Finding – Relationships Identified Available Land Debt Finance Professional Input Equity Develop & Exit Initial Capital

15. In Conclusion… Do Larger plc Developers approach decision-making differently than Smaller, Independent Developers?....or is it merely that they have the equity to participate in the property cycle at the most opportune time thereby maximising profits?