Pay or not to pay. Moonseo Park Advanced Construction Technology. Professor, PhD

Transcription

1 Pay or not to pay Moonseo Park Professor, PhD 9 동 4 Phone , Fax mspark@snu.ac.kr Department of Architecture College of Engineering Seoul National University 1

2 Model Quantification Is it always required with S&F? The Little Prince by Antoine de SaintExupéry the grownups who are no longer interested in anything but numbers Useful to determine loops magnitude Requiring a lot of relevant data

3 Lecture Outline Ø Typical Modeling Method Ø Background of the Case Project Ø Dynamic Modeling Process

4 Modeling Process Ø Learning can happen across ALL stages of modeling. Ø Involving continuous iterations among the modeling steps. System Understanding Conceptualization Policy Analysis Model Formation Model Test & Validation 4

5 Ø System Understanding: the process of deepening the modeler s understanding of the system with relevant information, usually including problem statement, list of variables, and reference modes Ø Conceptualization: conceptual model structures are described in the form of a causal loop diagram to show the dynamics of variables involved in the system (also, called dynamic hypotheses) 5

6 Examples of Causal Loop Diagram Uncertainties Assumptions in Design Owners' Requests on Changes Uncertainties Assumptions in Design Owners' Requests on Changes Oversizing Project Costs Overlapping between Design and Construction Time Pressure Construction Processes Overlapping Project Duration. Estimated Project Duration R1 Increase in Workforce Delay R Productivity Potential Design Change Impact on Construction Construction Work Done before Upstream Completed R Construction Changes Design Changes Oversizing Project Costs Project Duration. Overlapping between Design and Construction Time Pressure Construction Processes Overlapping Increase in Workforce Estimated Project Duration R1 Productivity Delay Potential Design Change Impact on Construction Design Changes Construction Work Done before Upstream Completed R R Construction Changes DesignDriven Feedbacks ConstructionDriven Feedbacks 6

7 Ø Model Formation: having a causal loop constructed, variables in the model structures come to have quantitative attributes through building mathematical equations for variables. This step also includes the identification of stock and flow structures, which characterize the state of the system and generate the information, upon which decisions and actions are based, by giving the system inertia and memory [Sterman, 000] 7

8 Ø Model Validation: tested and validated in accordance with the purpose of the modeling Ø Policy Analysis: the validated model is applied to solving the given problems 8

9 One Typical Modeling Method is Establishing a Problem Statement Listing Important Variables Making Reference Modes System Understanding Conceptualization Policy Analysis Establishing Dynamic Hypotheses, using Causal Loop Diagrams Model Formation Model Test & Validation 9

10 Lecture Outline ü Typical Modeling Method Ø Background of the Case Project Ø Dynamic Modeling Process 10

11 Background of the Case Project Strategic Decisions for Highway Operation A construction company has recently completed their highway construction project, which has been awarded with a BOT contract. Highway City A Old Road City B The highway runs from City A to City B in a more direct way than the existing road, and has service facilities for drivers. 11

12 A discounted cash flow analysis shows some numbers for toll charges that can return their investment within the operation period. However, the top management of the company won t believe the numbers, thinking that highway operation might not be a simple mathematics. 1

13 According to their experience, drivers choose a drive road depending on costconvenience tradeoffs, having the following two options: A highway with a lot of services and toll An old road without services Because of such a recognition, the top management wants to understand dynamics caused by drivers tendency in choosing a drive road and to know how to maximize their profits, while keeping an acceptable level of service. 1

14 Lecture Outline ü Typical Modeling Method ü Background of the Case Project Ø Dynamic Modeling Process 14

15 Problem Statements Ø Figuring out the dynamics involved in highway operations including tradeoffs among toll charges, service level, volume of traffic, and congestion level. Ø Finding an optimal level of toll charges and maintenance costs, which can maximize their profits, keeping an acceptable level of service. 15

16 List of Variables Toll Charges Highway Capacity Travel Time Traffic Volume Service Quality Trip Frequency Road Attractiveness Degree of Congestion Time Reduction through Highway GDP* Population* Price of Gasoline per Mile* *Exogenous Variables 16

17 Reference Mode HOPE Traffic Volume on Highway FEAR Maintenance Costs HOPE Profits FEAR 0 Operation Starts Now TIME End of Concession 17

18 Dynamic Hypotheses The Spaghetti Capacity TrafficOn Highway Congestion Service Capacity Deteriorate Service Capacity ServiceLevel AvgTravelTime Perceived Attactiveness OfHighway AttactivenessOf Highway ServiceLevel OfOldRoad GapOfServiceLevel TollPerCar InvestmentOn Maintenance Revenue FractionOfRevTo Invest For the first stage of the development, one needs to analyze feedback loops that have the most significant impacts on the system and established dynamic hypotheses of them. 18

19 Congestion Capacity TrafficOn Highway <Service Capacity> ServiceLevel AttactivenessOf Congestion Highway Congestion TollPerCar AvgTravelTime Perceived Attactiveness OfHighway ServiceLevel OfOldRoad GapOfServiceLevel If toll becomes cheaper, traffic goes up, congestion becomes more, and drivers have a higher average travel time. That affects negatively on the Attractiveness of Highway with the consequent reduction in traffic. The following hypotheses on the system s behaviors are established when toll is decreased. Traffic on Highway Profits Will be stabilized at a certain point that is determined by other conditions Will be determined by Traffic Volume 0 Toll decrease Operation End 19

20 Service Capacity TrafficOn Highway <Service Capacity> ServiceLevel AttactivenessOf Highway Congestion TollPerCar AvgTravelTime ServiceLevel OfOldRoad GapOfServiceLevel ServiceDeteriorate Perceived Attactiveness OfHighway The attractiveness of the Highway with respect to the service level depends on both the service on highway and in the alternative route. As an increase in traffic deteriorate the Highway s service level and in turn its attractiveness. The same hypotheses on the system s behaviors as Congestion Loop are established when toll is decreased. 0

21 Investment Capacity TrafficOn Highway Service Capacity Deteriorate Service Capacity ServiceLevel AttactivenessOf Highway Congestion AvgTravelTime ServiceLevel OfOldRoad GapOfServiceLevel Perceived Attactiveness OfHighway Investment TollPerCar InvestmentOn Maintenance Revenue FractionOfRevTo Invest Traffic on Highway Profits As traffic goes up, the company can spend more money on services. And better services increase the attractiveness of the highway. The following hypotheses on the system s behaviors are established when fraction of revenue for investment on the service capacity is increased. 1

22 Model Formation Fraction OfInitial TrafficOn Highway <TotalTraffic> Coef for Init Service Traffic On Highway <Time> Init Service ChangesInTraffic Traffic On Old Roads Total Traffic Time to Service Improvement TimeToPerceive Attractiveness Effect of Marketing on Time to Perceive Attractiveness f Regional Growth Highway Capacity Time To Change Trans Congestion Improve Service Congestion on Old Roads Table for congestion <Traffic On Highway> TravelTimeOn OldRoads ServiceLevel Service ChangesIn Attractiveness Old Road Capacity MaxService Advantage Coef for Mkt Investment Investment on Marketing TableFor TimeEffect MaxTime Reductionon OldRoad Coef for Congestion TravelTime OnHighway Service Deterioration Perceived Relative Attractiveness Relative Attractiveness GapOfTravelTime MaxTime Reduction EffectOfTravel TimeOn Attractiveness Service Lifecycle EffectOf ServiceOn Attractiveness Gap Of Service Level EffectOfTollOn Attractiveness stepsize Table for Toll effect Service Level Of Old Roads Operation Costs InitialToll Toll Maximum Toll allowable TableFor Service Effect <Traffic On Old Roads> <TotalTraffic> <FractionOfInitial TrafficOn Highway> <Investment on Marketing> Service coef Net Profits Revenue Annual Budget For Changes in Service Fraction Of Revenue For changes in Service Time to change Budget

23 Model Analysis Toll Impact 1.41 Graph for PerceivedRelativeAttractiveness Time (Year) PerceivedRelativeAttractiveness : toll7$ PerceivedRelativeAttractiveness : toll$ PerceivedRelativeAttractiveness : toll4$ PerceivedRelativeAttractiveness : base dimensionless dimensionless dimensionless dimensionless

24 Model Analysis Toll Impact.89 M Graph for Traffic On Highway.40 M.964 M.57 M M Time (Year) Traffic On Highway : toll7$ Traffic On Highway : toll$ Traffic On Highway : toll4$ Traffic On Highway : base car/year car/year car/year car/year 4

25 Model Analysis Toll Impact M 1 Graph for Net Profits 7.95 M M 1.54 M M Time (Year) Net Profits : toll7$ Net Profits : toll$ Net Profits : toll4$ Net Profits : base dollar/year dollar/year dollar/year dollar/year 5

26 Policy Implications Ø While the relative attractiveness always becomes stabilized at the initial equilibrium point, the traffic volume becomes stabilized at the point where there are no more changes in the attractiveness. Ø Net profit from the highway operation may not be proportional either to toll amount or to traffic volume. 6

27 Model Analysis Investment on Service Graph for PerceivedRelativeAttractiveness Time (Year) PerceivedRelativeAttractiveness : base PerceivedRelativeAttractiveness : Service50%increase PerceivedRelativeAttractiveness : Service50%decrease dimensionless dimensionless dimensionless 7

28 Model Analysis Investment on Service Graph for Traffic On Highway.919 M.77 M.68 M.48 M.6 M Time (Year) Traffic On Highway : base Traffic On Highway : Service50%increase Traffic On Highway : Service50%decrease car/year car/year car/year 8

29 Model Analysis Investment on Service M Graph for Net Profits 8.9 M M M 7.04 M Time (Year) Net Profits : base Net Profits : Service50%increase Net Profits : Service50%decrease dollar/year dollar/year dollar/year 9

30 Policy Implications Ø Investment on the service capacity can increase traffic volume and lowers annual net profits. Ø However, the system also becomes stabilized, which implies that the long run, we can get almost same annual net profits regardless of the investment amount on service. 0

31 Policy Recommendations Ø Set initial toll price a little bit higher than that of equilibrium case (say 7$ per car) Ø Set the investment amount on service lower than that of equilibrium case (say 50% decrease) Ø Invest on marketing for the initial period of operation (say the first 1.5 years) 1

32 81 Housing Policy Supply Demand Price 공급위축 수익성악화로인한공급축소 투기수요증가 분양프리미엄의형성은투기수요 가격상승억제 신규공급가격조절로전체주택가격조절가능 영향無 공공주택의공급 중소기업이틈새시장을메꿈 실수요위주로개편 청약가점제, 전매제한으로투기수요진입어려움 프리미엄형성 분양완료후프리미엄형성, 이는주택매매가에그대로영향

33 Tug war

34 Development Cost Sales Unit Cost per Square Meter Housing Attractiveness Expected Trading Profit of Sales Housing Potential Value of Existing Housing Expected Trading Profit of Existing Housing Potential Investment Demand Expected Sales Profit Available Residential Area Newly Built Housing B1a Expected Sales Rate Housing Price B1b Home Ownership Ratio Potential Actual Demand Existing Housing on Sale Supply Difference between Demand and Supply Demand Funding Capability Total Potential Demand Chonsei Price 4

35 Development Cost Sales Unit Cost per Square Meter Expected Sales Profit Available Residential Area Newly Built Housing Expected Sales Rate Housing Attractiveness Expected Trading Profit of Sales Housing Potential Value of Existing Housing Housing Price Ba Expected Trading Profit of Existing Housing Potential Investment Demand Bb Home Ownership Ratio Potential Actual Demand Existing Housing on Sale Supply Difference between Demand and Supply Demand Funding Capability Total Potential Demand Chonsei Price 5

36 Development Cost Sales Unit Cost per Square Meter Expected Sales Profit Available Residential Area Newly Built Housing Expected Sales Rate Housing Attractiveness Expected Trading Profit of Sales Housing Potential Value of Existing Housing Housing Price Expected Trading Profit of Existing Housing Potential Investment Demand R1a Home Ownership Ratio Potential Actual Demand Existing Housing on Sale Supply Difference between Demand and Supply Demand Funding Capability Total Potential Demand Chonsei Price 6

37 Development Cost Sales Unit Cost per Square Meter Expected Sales Profit Available Residential Area Newly Built Housing Expected Sales Rate Housing Attractiveness Expected Trading Profit of Sales Housing Potential Value of Existing Housing Housing Price R1b Expected Trading Profit of Existing Housing Potential Investment Demand B Home Ownership Ratio Potential Actual Demand Existing Housing on Sale Supply Difference between Demand and Supply Demand Funding Capability Total Potential Demand Chonsei Price 7

38 References Ø Avraham Shtub, Jonathan F. Bard, Shlomo Globerson, Project management : engineering, technology, and implementation, Englewood Cliffs, NJ, Prentice Hall, 1994 Ø Ø Ø Ø Ø Ø Frederick E. Gould, Nancy Joyce, Chapter 8, Construction project management, Upper Saddle River, NJ, Prentice Hall, 1999 James M. Lyneis *, Kenneth G. Cooper, Sharon A. Els, Strategic management of complex projects: a case study using system dynamics, System Dynamics Review, Vol. 17, No., 001 Christopher M. Gordon, Choosing appropriate construction contracting method, J. of Construction Engineering & Management, Vol. 10, No. 1, 1994 Feniosky PenaMora, Jim Lyneis, Project control and management, MIT 1.4J Lecture Material, 1998 Barrie, D.S., and Paulson, B.C., Professional Construction Management, McGraw Hill, 199 Halpin, D.W., Financial and Cost concepts for construction management, John Wiley & Sons, 1995 Ø Yehiel Rosenfeld, Project Management, MIT 1.401J Course Material, 000 Ø Sarah Slaughter, Innovation in construction, MIT 1.40 Course Material, 1999 Ø Chan, Albert P. C.; Ho, Danny C. K.; Tam, C. M, Design and Build Project Success Factors: Multivariate Analysis, J. of Construction Engineering & Management, Vol. 17, Issue, 001 8

39 Term Project Towards the world best consulting firm 9

40 Criteria for Consulting topics Ø Problem System understating: who are (Main) players? At which level (industry, corporate, individual etc)? To whom? To be specific Avoid physical or financial systems (this can be feasible only with a quantitative model) 40

41 Ø Tradeoff Unexpected behaviors (sometimes side effects) caused by remedial actions, together with expected behaviors. What did client do for solving the problem? This can be hints for finding tradeoffs If feedbacks are involved, it would be super. Problems and tradeoffs should have the same dimensions (to whom, at which level, type of behaviors) e.g., In S s call taxi model, government s policy to easy people s inconvenience worsened people s inconvenience. 41