Montreal Living Lab / CIRANO

Towards Open Economics

Who we are

• Open innovation & co-design center

• Smart cities, urban mobility, virtual identity, gamification, etc.

• Online collaborative platform• Citizen, public, private &

academic partners

• Interuniversity research center on organization analysis

• Public policies, risk analysis, finance, sustainable development, etc.

• Experimental economics lab• 180+ researchers

The application of gamemechanics and game-thinking

in non-game environmentsto increase participation and

engagement.

What is Gamification?

Massively Multiplayer Online Games

Online games (MMOs) reach millions of players in large-scale collaborative environments.

Can millions of people play games for science and profit?

Hermione

Nemo_12

X-manTODZ

wizKidSnowBall

The GOLDCORP Challenge

Open innovation contest• In 2000, GoldCorp put 000’s of pages of

complex geological data online.• To help discover new veins of gold

at its Red Lake mine, Ontario, Canada.

US $500,000 in prize money• Over 1,400 corporations, consultants and

universities from 50 countries entered the contest.

• More than 8 million ounces of gold found.

Company’s value rocketed

from $100M to $9B

Serious Games for Science

Foldit

3D puzzle for protein

pattern identification

• 234,000 users

• 600 protein puzzles solved

GalaxyZoo

Visual classification

of Hubble space photos

• 400,000 users

• 1 million galaxies

Biotech Astronomy

Is there any data issuetoo big to handle?

The Big Data Tsunami

Fact:

Geolocation, smartphone & transactional data are piling up.

Issue:

How to identify, measure & understand behavioral patterns?

Experimental Economics

Understanding fundamentals of individual & group behaviors

Beyond Risk Analysis

Trust

Collaboration

Coordination

Patience

Ambiguity

Fairness

Uncertainty

Measuring people’s preferences for...

From the Labto In-field & Online Research

Open EconomicsCitizens for economic development

Center for Open Economics

What is it needed for?To apply experimental economics to emergent fields of applications:

• Open Data Analysis

• Serious Game Design

• Dynamic Pricing

• Collaborative Forecasting

• Open Finance

• Impact Investment

• Clean Tech

• Change Management, etc.

What is it?

• International, multidisciplinary collaboration network

• Bridging the gap between experts and citizens worldwide

• Montreal-based

• Opening: 2012

Montreal Living Lab / CIRANO

Towards Self-optimized Cities

Bike-sharing Worldwide MarketOperation Dilemma: System scalability vs Closed business model

A Self-optimization Gamefor Bike-sharing Systems

Station A

Involve users into a “mission”

Hi!Hi!

Station B

Get rewards and cash rebates

Near Full

Near Empty

$$$

Ride to empty bike stations

9

1

Game Play

• Social game:– To rebalance bike stations for the benefit of both riders and operator.– Invest riders with a mission, and provide tools for them to reach it.

• Each mission is a ‘micro contract’ from which you will gain something.

– Merchants offering rewards to riders according to nearest stations imbalance state.– Actual rewards must meet designated station balancing requirements.

• Based on a dynamic pricing platform opened to all stakeholders.– Multi-constraint, collaborative negotiation modelling.– Google Places promoted as the incentive platform of choice.

• By repeating this synchronized pattern on high-scale online system, this game will engage its players.

– By promising both a personal reward and a global one.– By tracking and visualizing in real time data generated by the game.

• This game massively integrates in the social aspect of people’s life.– Provides suggestions of places to go / buy / dream / share with friends.– Opt-in-based.– Users are in control of how things work for them.– Merchants & participating bikers grow reputation together.

Incentive Program

Self-optimization Platform

Bike NetworkSimulation Model

Optimization Engine

Optimization GoalsDynamic Pricing

Engine

Incentive Plan Design

Google Places

APIs

Mobile App

User Profile

Mission Selector

Scoreboard

Rewards Earned

Bike Network Data Stream

System Co-design

• Optimizing complex open systems is improved...

– By providing an open collaborative platform.

• Get people from outside organizations to collaborate for...

– Identifying relations and parameters describing user needs, material constraints, stakeholder interests, system resources, etc.

• Simulation models created cooperatively are...

– More accurate as their complexity increases.

• Dynamic pricing and optimization algorithms...

– Provide real-time feedback to all participants.

– Help them to further improve their incentive plans.

• London• Paris• Montreal

• Mexico City

• Tel Aviv • Nagoya• San Francisco

• Buenos Aires

Revenue Model

How do we make money?

• Mobile application licensing to bike system operators is just a beginning:

– Already 1900+ bike-sharing systems worldwide.

• Two options:

– Performance-based licenses

(% of operator’s net savings)

– Traffic-based licenses

(Monthly fees)

Growth Potential

There’s more!

• Dynamic pricing models apply to several more urban resources:

– Parking, transit, energy, telcos, entertainment, etc.

Investors’ perspective

• Increasing urban density profits to all investment sectors.

– Freeing market liquidity is key.

Freeing New Market LiquidityWith Alternate Transportation

Liquidity per HouseholdAverage Canadian Household Size = 2.5

Car per Household = 1.55

Liquidity per 1M PeopleCars per 1M people = 620,000

Households = 400,000

(Based on an average car annual cost of ownership of $11,000 CDN. Alternate transportation fares available in Montreal from Communauto, STM and Bixi.)

D) Available Liquidity (B-C):

B) Saved Cost on Car Ownership:

C) Alternate Transportation Fares:

A) Annual Car Ownership Cost:(per 1M People)

$1.57B

– $1.16B

$2.73B

$6.82B

Assuming a 40% conversion rate

C) Available Liquidity (A-B): $9,808

B) Alternate Transportation Fares: (Car-sharing + Transit + Bike-sharing)

– $7,242

A) Annual Car Ownership Cost:(per Household)

$17,050

New Liquidities by City

$7.4BToronto

$5.2BMontreal

$3.1BVancouver

City

TorontoMontrealVancouver

Total:

Pop.

4.8M3.3M1.9M

10.0M

Liquidity

$7.4B$5.2B$3.1B

$15.7B

Thank you!

Louise Guaylouiseguay11@gmail.com

Claude Faribaultclaude.faribault@gmail.com