KM 101 Dr. Nick Bontis Associate Professor of Strategic Management , McMaster U.

KM 101Dr. Nick Bontis

Associate Professor of Strategic Management, McMaster U.Director, Institute for Intellectual Capital Research

Associate Editor, Journal of Intellectual CapitalChief Knowledge Officer, Knexa Solutions

www.NickBontis.com [email protected]

Seminar Agenda• Phase 1: Knowledge Era

– understanding the context of the information age• Phase 2: IC Multi Perspectives

– What is IC? Depends on who you ask.• Phase 3: IC Models

– levels of analysis, types of knowledge, stocks & flows• Phase 4: SLAM Measures

– alignment of stocks and flows with performance• Phase 5: Causal Mapping

– Structural equation methodology and measures• Phase 6: National IC Index

– Country level measurement and modeling• Phase 7: Software Demonstration

– TangoNet and Tribute

MindLand

Machine

Knowledge Era

Industrial Era

Entering A New Era ?

Agriculture Era

Tobin’s q

GroupWare

Internet

AccountingMetrics

Tech

http://www.johnfoxx.com/content/articles/picture/info.cfm?pictureID=12817












Internet users:30 million - 1999

817 million - 2005 WTO

In 1997 home PCs passed TVs in units sold

Retail Week

Canadian Internet Usage:1995 4%, 1998 25%, 2005 75%

Nielsen

Internet trafficdoubling every

70 daysDept. of Commerce

KM Research Highlights

• IDC reports FORTUNE 500 wasted $12 billion duplicating work

• Ford reports $914 million cost savings due to KM from 1997 - 2000• Chevron saves $650 million since 1991 due to KM• Texas Instruments saves $1 billion cumulatively since

KM program launched in mid 1990s

• Gartner Group reports– 90% of FORTUNE 500 working on KM– 33% of FORTUNE 1000 had begun KM programs by 1999– will rise to over 50% by 2003

• World Economic Forum– 95% of CEOs feel that KM is critical to success





Myths of Measuring KM

1. The reality is that when you finally do it, you are never satisfied

2. The few who are doing it are probably not doing it well

3. Those who say they are doing it are probably lying4. No one is sure what it is, but they hear that it is

great5. Everyone thinks everyone else is doing it

KM Research Highlights

• Stats Canada (348 organizations surveyed)– 93% have KM initiatives, 25% dedicated budget– Why have KM?

• Competitive advantage, human capital, intellectual capital retention

• Fortune 500– 80% have KM initiative(s) in place, 25% have CKOs

53% have KM staff, all #s expected to grow – 6% have KM initiatives company-wide, 60% < 5 years

KM is owned 32% Sr.Mgt., 25% HR, 16% IT

• Government - all levels• Institute for Intellectual Capital Research

– CKOs from 40% HR, 40% IT, plus other (hired within)





Multi - Perspectives

Accounting

Training &Development

Economics

HumanResources

OrganizationalBehaviour

Strategy

Finance

TechnologicalSystems

Marketing

Sales

Aoccdrnig to rscheearch at Cmabrigde Uinervtisy, it deosn't mttaer in waht oredr the ltteers in a wrod are, the olny iprmoetnt tihng is taht the frist and lsat ltteer be at the rghit pclae. The rset can be a total mses and you can sitll raed it wouthit a porbelm. Tihs is bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the wrod as a wlohe.

Volunteer for a Reading test

Volunteer for a Reading test

Where are we Where are we going?going?

• Lester Thurow - MIT“The dominant competitive weapon of the 21st century will be the

education and skills of the workforce.”• Jac Fitz-enz - Saratoga Institute

“The contingent workforce will become the dominant model.”• President Clinton - U.S. White House

“By having the chance to work while you learn ... You embody the growing unity between experience and education.”

• Steve Maharey - NZ Labour Spokesperson on Education“Maori and Pacific Island peoples in particular remain under

represented in tertiary education.”

Importance of Importance of phenomenonphenomenon

Choo and Bontis (2002), Bontis (2002) Fitz-enz (2000) Max Boisot (1998) & Choo (1998)

Knowledge Assets, Knowing in Organizations Sveiby (1997) & Stewart (1997) & Roos (1997)

Organizational Wealth Nonaka and Takeuchi (1995)

The Knowledge Creating Company Drucker (1993)

arrival of the “knowledge society” Toffler (1990), Handy (1989)

ultimate resource, intellectual assets 3 or 4 times BV

Tracing KM’s History

Egyptians, Greeks, Monks, Knights Taylor (1911)

Evidence of codification of knowledge Simon (1945)

Cognitive capacity “bounded rationality” Schumpeter (1952)

Innovation from new combinations of knowledge

Penrose (1959) Organization is a knowledge repository

IASC, CICA, FASB & SEC … Help!

Cash

Receivables

Fixed Assets

IntellectualCapital

Liabilities

Shareholder’sEquity

Market ValueAdded

Visible (Explicit) Accounting

Invisible (Implicit) Accounting





Distinguishing the Terms

Stock Stock Flow

Behaviour 1 Behaviour 2 Behaviour 3

IntellectualCapital

KnowledgeManagement

IntellectualCapital

Organizational Learning System 123

Devil’s Advocate

KnowledgeManagement

The Danger of KM

Achievement Driven

Paternalistic

Balance Organizational Slack

OrganizationalPerformance

Level of Analysis: Individual

recruitment building competencies assessing weaknesses retention compensation satisfaction





Level of Analysis: Group

• concerted team action

• collectively aligned mind sets

• synergy

• cohesion

• shared perception of thebusiness environment

http://photo.net/photo/pcd3559/hoc-4.tcl

Level of Analysis: Organization

StrategyContinuous Improvement

Systems

Culture

Leadership

Structure

Trust

Technology

IC Conceptualization

2nd order multi-dimensional 3 sub-domains drivers

trust, culture leadership

HumanCapital

StructuralCapital

RelationalCapital

Customer Capital

Organizational Capital

Innovation Capital

Process Capital

Structural Capital

Human Capital

Intellectual Capital

Financial Capital

Market Value

Conceptual Model - Firm

House Metaphor

Financial Wealth

Human Capital

Marke

tC

apita

l

Renewal Capital

Pro

cess

Cap

ital

Past

Present

Future

Financial Wealth

Human Capital

Marke

tC

apita

l

Renewal Capital

Pro

cess

Cap

ital

Past

Present

Future





IC Perceptual Model

Nonaka (SECI Model)

Tacit

Explicit

Socialization

Internalization

Externalizaton

Combination

Tacit Explicit

From

To

Metaphors and Analogies

• stocks and flows– production system– capacity utilization, bottlenecks, throughput– ties-in stocks of knowledge and flow of learning

• bathtub analogy– tap in and leak (knowledge flow)– water level (intellectual capital)– the whole water system (organizational learning)

We need an integrative We need an integrative framework!framework!

Strategic Learning Assessment Map

H R S

H R S

H R S

H R S

Individual Group Organization Cross-organization

Individual

Group

Organization

Cross-organization

Flow Output

Flow Input

Feed-forward

Feed-back

Legend: H

(human), R

(relation

al), S (structural) =

IC)

Measure, Test and Evaluate

• multi-method approach (quantitative and qualitative) – IICR Knowledge AuditIICR Knowledge Audit: survey design (Likert-type)

• objective proxies (www.Saratoga-Institute.comwww.Saratoga-Institute.com)– benchmarking of HR metrics (turnover and training & dev.turnover and training & dev.)– e-mail direction (IICR e-Flow AuditIICR e-Flow Audit)– knowledge sweeping (dynamic corporate yellow pages)

• Some tools to check out ...Some tools to check out ...– Knexa.com, BrassRing.com, OpenText.com– Monster.com, eLance.com, Talent websites

• Tango SimulationTango Simulation– www.TangoNow.net

• IC DisclosureIC Disclosure– www.Celemi.se– www.Skandia.se– www.Carlbro.dk


KM Continuum

IICR KM Diagnostic

Tribute Technology

KM Seminars

KM Diagnostic Audit

ManagerialLeadership

ValueAlignment

Retention of Key People

Human CapitalDepletion

BusinessPerformance

EmployeeSatisfaction

EmployeeCommitment

EmployeeMotivation


HumanCapital

RelationalCapital

Human CapitalEffectiveness

StructuralCapital

ProcessExecution

KnowledgeIntegration

KnowledgeGeneration

KnowledgeSharing

0.751

0.506

0.475

0.530 0.326 0.360

0.358

0.734

0.456 0.429

0.430

0.285 - 0.233

- 0.372

- 0.337

0.327

0.439

0.543

0.491

0.3940.262

0.307

0.442

R2 = 28.5%

R2 = 28.5%

R2 = 68.2%

R2 = 44.1%

Age

Obesity

HeartAttack

Correlation between Age and Risk of Heart Attack+ 0.36 (p < 0.01)

Correlation vs Path Analysis

Correlation between Obesity and Risk of Heart Attack+ 0.32 (p < 0.01)

+ 0.36

+ 0.32

Age

Obesity

HeartAttack

Path between Age and Obesity+ 0.26 (p < 0.01)

Correlation vs Path Analysis

Path between Obesity and Risk of Heart Attack+ 0.43 (p < 0.01)

X+ 0.26

+ 0.43


ValueAlignment


EmployeeCommitment

EmployeeMotivation

TrainingHumanCapital

RelationalCapital



BusinessPerformance


StructuralCapital

ProcessExecution


KnowledgeGeneration

KnowledgeSharing

0.751

0.506

0.475

0.530 0.326 0.360

0.358

0.734

0.456 0.429

0.430

0.285 - 0.233

- 0.372

- 0.337

0.327

0.439

0.543

0.491

0.3940.262

0.307

0.442

R2 = 28.5%

R2 = 28.5%

R2 = 68.2%

R2 = 44.1%

Outcome Constructs

Participating Participating OrganizationsOrganizations

ABN AMRO North America Inc. Allstate Insurance CompanyAMP Australia AMP UK Andersen Consulting Aon AXA Client Solutions Blue Cross Blue Shield of Florida Blue Cross Blue Shield of Illinois / Texas Blue Cross Blue Shield of North Carolina CNA Commercial Insurance EquitaxFarmers Insurance Group

Hartford Financial ServicesHewitt Associates, LLCIntermountain Health Care International Monetary Fund Merrill LynchNational City Corp. Northwestern Mutual LifePenn National InsurancePNC BankSavings Bank of UticaUnited Health Group Zurich U.S.

Quantitative Quantitative Metric ModelMetric Model


Human CapitalValuation


Human CapitalInvestment

+

+

_






+

+

_

• Revenue Factor• Income Factor

HC Effectiveness - HC Effectiveness - Income FactorIncome Factor

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

$80,000

$90,000

Income Factor $36,514 $42,037 $64,612 $18,107 $61,373 $78,379 $64,112

HCV Sample

Banks Insurance -

All Insurance -

H&L Insurance -

PCP Non-Bank Financials

All Industries






+

+

_


• Compensation Expense Factor• Compensation Factor

HC Valuation - HC Valuation - Compensation Compensation

FactorFactor

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

Comp Fac $54,024 $32,509 $41,046 $37,588 $40,900 $46,531 $44,445

HCV Sample Banks Insurance -

All Insurance -

H&L Insurance -


All Industries






+

+

_



• Development Rate• Training Investment

HC Investment - HC Investment - Development RateDevelopment Rate

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

Develop Rate 82.2% 56.9% 74.2% 87.9% 61.1% 59.1% 66.3%

HCV Sample

Banks Insurance -

All Insurance -

H&L Insurance -


All Industries






+

+

_



• Development Rate• Training Investment

• Voluntary Turnover• Involuntary Turnover

HC Depletion - HC Depletion - Voluntary TurnoverVoluntary Turnover

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

20.0%

Voluntary 13.1% 18.8% 12.6% 12.6% 11.9% 18.6% 14.7%

HCV Sample

Banks Insurance -

All Insurance -

H&L Insurance -


All Industries

Areas of Areas of ConcernConcern

2

5

5

6

7

9

10

11

12

13

17

23

29

30

31

0 5 10 15 20 25 30 35

Relational Capital

Structural Capital

Know ledge Generation

Education

Value Alignment

Motivation

Know ledge Sharing

Human Capital

Know ledge Integration

Employee Satisfaction

Employee Commitment

Process Execution


Business Performance

Management Leadership


BusinessPerformance


EmployeeCommitment

EmployeeMotivation


RelationalCapital


StructuralCapital

ProcessExecution


KnowledgeGeneration

0.475

0.530 0.326 0.360

0.358

0.734

0.456 0.429

0.430


ValueAlignment


KnowledgeSharing

0.751

0.506

0.285 - 0.233

- 0.372

- 0.337

0.327

0.439

0.543

0.491

0.3940.262

0.307

0.442

R2 = 28.5%

R2 = 28.5%

R2 = 68.2%

R2 = 44.1%

Research Research Implication IImplication I


ValueAlignment



BusinessPerformance


EmployeeCommitment

EmployeeMotivation

Training

ProcessExecution


KnowledgeGeneration

KnowledgeSharing

0.751

0.506

0.475

0.530

0.358

0.734

0.456 0.429

0.430

0.285 - 0.233

- 0.372

- 0.337

0.327

0.439

0.543

0.491

0.3940.262

0.442

R2 = 28.5%

HumanCapital

RelationalCapital


StructuralCapital

0.326 0.360

0.307 R2 = 28.5%

R2 = 68.2%

R2 = 44.1%

Research Research Implication IIImplication II


ValueAlignment




RelationalCapital


StructuralCapital

ProcessExecution


KnowledgeGeneration

0.751

0.506

0.475

0.530 0.326 0.360

0.285 - 0.233

- 0.372

- 0.337

0.3270.543

0.3940.262

0.307

0.442

R2 = 28.5%

R2 = 28.5%

R2 = 68.2%

0.430Knowledge

Sharing

BusinessPerformance


EmployeeCommitment

EmployeeMotivation

0.358

0.734

0.456 0.4290.439

0.491

R2 = 44.1%

Research Research Implication IIIImplication III


ValueAlignment



EmployeeCommitment

EmployeeMotivation


RelationalCapital


StructuralCapital

0.751

0.506

0.475

0.530 0.326 0.360

0.358

0.734

0.456 0.429

0.430

0.285

- 0.372

- 0.337

0.439

0.543

0.491

0.307

0.442

R2 = 28.5%

R2 = 68.2%

BusinessPerformance


ProcessExecution


KnowledgeGeneration

KnowledgeSharing

- 0.233

0.327

0.3940.262

R2 = 28.5%

R2 = 44.1%

Research Research Implication IVImplication IV


ValueAlignment



EmployeeCommitment

EmployeeMotivation


RelationalCapital

StructuralCapital

ProcessExecution


KnowledgeGeneration

KnowledgeSharing

0.751

0.506

0.475

0.530 0.326 0.360

0.358

0.734

0.456 0.429

0.430

0.285 - 0.233

0.327

0.439

0.543

0.491

0.3940.262

0.307

0.442

R2 = 68.2%


BusinessPerformance


- 0.372

- 0.337

R2 = 28.5%

R2 = 28.5%

R2 = 44.1%

Research Research Implication VImplication V

KRA Health KRA Health CanadaCanada

ManagementLeadership

ValueAlignment


Turnover

PerformanceEmployeeSatisfaction

EmployeeCommitment

EmployeeMotivation

FeedbackLearning

HumanCapital

RelationalCapital

StructuralCapital

ProcessExecution

KnowledgeIntegrationKnowledge

Generation

KnowledgeSharing

0.598

0.326

0.424

0.135

0.235

-0.161

0.139

0.182

0.380

0.442

0.328

0.809

0.295

- 0.352

0.282

-0.266

0.454

0.522

0.257

0.376

0.196

R2 = 20.0%

R2 = 61.1%

R2 = 54.1%


0.730

0.603

0.570

0.567

0.3560.3980.651

0.446 - 0.1570.167

Elements of KM Elements of KM ProgramsPrograms

KMKM Applications Applications MatrixMatrix

Individual Group Organization Extended

Arsenal of KM Arsenal of KM ToolsTools

Simulate Scenario planning

Expert systemsVirtual organization

KM Laboratories

Disseminate Distributed e-learning

Communities of practiceKnowledge portals

IC reporting / disclosure

Communicate Apprenticeships

Job rotationOrganizational slack

Ba design/implementation

MapWorkflow analysisKnowledge maps

Statistical flow timing eFlow Audits

Categorize Taxonomy development

Intranet groupwareText mining

Organizational libraries

ContextualizeExpertise locators

Intranet yellow pagesDocument managementVideo teleconferencing

HypothesizeMathematical models

Neural networksKnowledge discovery

Longitudinal forecasting

GatherData warehousing

Information navigationCompetitive IntelligenceEnvironmental scanning

DiagnoseAwareness / storytelling

KM audit / survey Values assessment

Customer focus groups

TACIT EXPLICIT EMBEDDED

Background Background InformationInformation

• United Nations– Nationalize IC concept– Leverage for public policy– Isolate a target area for study

• McMaster University– World Congress on IC– 1st MBA with KM minor– Develop methodology– Research and collect metrics– Design a structural model

Arab RegionArab Region

AlgeriaBahrain

ComorosDjiboutiEgyptIraq

SomaliaSudanSyria

TunisiaUAE

Yemen

JordanKuwait

Lebanon Libya

Mauritania

MoroccoOman

PalestineQatar

Saudi Arabia






Customer Capital


Innovation Capital

Process Capital

Structural Capital

Human Capital


Financial Capital

Market Value


Market Capital


Renewal Capital

Process Capital

Structural Capital

Human Capital


Financial Wealth

National Wealth

Conceptual Conceptual Model - NationModel - Nation

House House MetaphorMetaphor

Financial Wealth

Human Capital

Marke

tC

apita

l

Renewal Capital

Pro

cess

Cap

ital

Past

Present

Future

Financial Wealth

Human Capital

Marke

tC

apita

l

Renewal Capital

Pro

cess

Cap

ital

Past

Present

Future

Descriptive Descriptive StatisticsStatistics

Total Projected Gender Health Poverty Gender

Total Total Growth Age 0-14 Poplution GEM HDI HPI-1 GDI

(millions) (millions) (%) (%) (millions) (index) (index) (index) (index)2000 1950 1950-2000 2000 2015 2001 2001 2001 2001

DES01 DES02 DES03 DES04 DES05 DES06 DES07 DES08 DES09Algeria 30.31 8.75 246.4 34.8 37.85 0.693 23.5 0.673Bahrain 0.64 0.11 481.8 28.2 0.78 0.824 0.814Comoros 0.71 0.17 310.4 43.0 0.98 0.510 29.9 0.503Djibouti 0.63 0.06 916.1 43.2 0.85 0.447 34.7Egypt 67.89 21.83 210.9 35.4 84.51 0.258 0.635 31.7 0.620Iraq 22.95 5.16 344.9 41.6 32.53Jordan 4.91 0.47 940.3 40.0 6.97 0.714 8.5 0.698Kuwait 1.91 0.15 1,156.6 31.3 2.36 0.818 0.815Lebanon 3.50 1.44 142.6 31.1 4.31 0.758 10.2 0.741Libya 5.29 1.03 414.1 33.9 6.84 0.770 16.7 0.748Mauritania 2.66 0.83 222.4 44.1 3.84 0.437 47.2 0.428Morocco 29.88 8.95 233.7 34.7 37.90 0.596 36.4 0.579Oman 2.54 0.46 457.0 44.1 3.92 0.747 32.2 0.715PalestineDjibouti 0.56 0.03 2,140.0 26.7 0.68 0.801 0.788Saudi Arabia 20.35 3.20 535.7 42.9 31.06 0.754 17 0.719Somalia 8.78 2.26 287.8 48.0 13.66Sudan 31.10 9.19 238.4 40.1 41.36 0.439 34.8 0.413Syria 16.19 3.50 363.2 40.8 21.95 0.700 19.8 0.677Tunisia 9.46 3.53 168.0 29.7 11.52 0.714 0.700UAE 2.61 0.07 3,628.6 26.0 3.09 0.809 0.798Yemen 18.35 4.32 325.2 50.1 33.16 0.470 42.5

Arab States 281.22 75.51 272.4 35.9 380.12 0.258 0.665 27.5 0.672

SOURCE UN, 2001 UN, 2001 Calculated UNESCO UN, 2001 HDR, 2001 HDR, 2001 HDR, 2001 HDR, 2001

Population World Bank Indices

Financial Financial CapitalCapital

Trade

Per Capita Trade as % Barriers to Market ListedPer Capita Growth of Goods GDP Entry Cap. Companies

($PPP) (%) (%) ($ millions)1999 90-99 1999 2001 2000 2000FC01 FC02 FC03 FC04 FC05 FC06

Algeria 5,063 -0.4 69.90 4.0Bahrain 13,688 0.8 3.0Comoros 1,429 -3.1Djibouti 2,377 -5.1Egypt 3,420 2.4 42.10 5.0 28,741 1,076Iraq 5.0Jordan 3,955 0.4 171.60 4.0 4,943 163Kuwait 17,289 132.70 2.0 18,814 76Lebanon 4,705 3.0Libya 7,570 5.0Mauritania 1,609 1.3 138.20Morocco 3,419 0.4 108.20 4.0 10,899 53Oman 13,356 2.8 126.10 2.0 3,463 131PalestineQatar 18,789 3.0Saudi Arabia 10,815 -2.2 109.60 4.0 67,171 75SomaliaSudan 664Syria 4,454 0.8 108.50 5.0Tunisia 5,957 1.9 126.70 5.0 2,828 44UAE 18,162 -1.6 159.30 2.0 28,211 53Yemen 806 -0.4 116.20 4.0

Arab States 7,238 -0.14 117.43 3.75 165,070 1,671

SOURCE HDR, 2001 HDR, 2001 WDI 2001

Gross Domestic Product Stock Markets

Human Capital Human Capital (1 of 4)(1 of 4)

Pre- Pre- Primary Primary Tertiary Primary Primary Secondary Tertiary

1980 2000 LYA LYA 1998 LYA LYA LYA LYAHC01 HC02 HC03 HC04 HC05 HC06 HC07 HC08 HC09

Algeria 40.10 63.30 15,426 13 1,333 170,956 145,160 19,910Bahrain 71.40 87.60 90 2 655Comoros 48.30 56.20 327 600 1,508 591Djibouti 31.40 51.40 2 72 1 1,096 403Egypt 39.30 55.30 2,367 18 12,050 310,116 259,618Iraq 570 8,145 12 4,841 145,455 52,393 8,818Jordan 68.40 89.80 932 2,623 17 3,346 45,367 5,275Kuwait 67.60 82.30 215 286 1 3,525 10,798 20,867 1,691Lebanon 72.40 86.10 1,938 2,160 10 10,444Libya 52.90 79.80 78 11 1,051Mauritania 29.00 39.90 36 2,392 1 108 6,225 1,865 270Morocco 28.60 48.90 33,617 5,806 14 39,469 114,406 80,817Oman 36.80 71.90 5 411 1 347 12,052 12,251 1,307Palestine 86.10 1,118 9 15,903 7,634 2,443Qatar 69.80 81.30 64 174 1 321 864 3,946 643Saudi Arabia 52.30 77.00 893 11,506 8 7,703 175,458 115,907 15,868Somalia 16 1,224 1 133 10,338 2,149 324Sudan 33.00 57.10 7,541 11,158 26 8,897 102,987 14,743 2,043Syria 53.30 74.40 1,096 10,783 4 4,427 114,689 2,182 4,733Tunisia 46.80 70.80 1,115 4,417 6 59,708 36,528 6,641UAE 65.60 76.50 4 3,110 16,148 9,832Yemen 20.20 46.20 62 15 680 90,478 13,787

Arab States 48.80 69.10 50,637 78,028 175 91,941 1,404,552 635,513 81,065

SOURCE UNESCO UNESCO UNESCO HES, 1998 UNESCO UNESCO UNESCO UNESCO

Literacy Rate Number of StaffNumber of Schools


Labour

Total Required Certified Pre- Force Qual. to Teach Primary Primary Secondary Tertiary

(millions) (%) (%)1999 LYA LYA LYA LYA LYA LYAHC10 HC11 HC12 HC13 HC14 HC15 HC16

Algeria 0.23 92.96 92.96 33,503 4,674,947 2,480,168 347,410Bahrain 65.00 100.00 12,308 72,876 49,897 7,676Comoros 17,778 78,527 21,192 348Djibouti 24.00 100.00 66.10 247 36,896 11,367 161Egypt 6.00 99.75 85.50 289,995 7,499,303 4,835,938 850,051Iraq 1.00 21.10 78.90 85,024 2,903,923 1,037,482 169,665Jordan 1.00 46.70 100.00 69,425 1,121,866 115,307 112,959Kuwait 1.00 100.00 100.00 54,572 142,308 222,079 29,509Lebanon 2.00 56.00 164,397 382,309 292,002 81,588Libya 1.00 97.40 15,028 1,357,040 189,202 72,899Mauritania 11.00 94.70 800 312,671 49,221 8,496Morocco 1.00 91.00 91.00 829,384 3,160,907 1,315,342 311,743Oman 99.00 6,989 313,516 215,673 16,032Palestine 0.25 97.10 45.40 656,353 5,469 49,599Qatar 7.00 33.20 68.50 7,018 53,631 37,924 8,475Saudi Arabia 100.00 100.00 85,484 2,256,185 1,500,072 273,992Somalia 12.00 1,558 196,496 39,753 2,040Sudan 5.00 61.10 59.70 343,767 3,000,048 379,162 59,824Syria 4.00 89.92 10.80 98,151 2,690,205 865,042 167,186Tunisia 1.00 93.30 99.20 68,108 140,479 833,372 121,787UAE 5.00 78.90 55,624 259,509 121,736 16,213Yemen HC 74.30 90.90 11,999 2,699,788 286,405 65,675

Arab States 97.00 79.57 79.26 2,251,159 34,009,783 14,903,805 2,773,328

SOURCE

Primary Teachers Number of Pupils


Pre- Pre- Population Cumulative TotalPrimary Primary Tertiary Primary Primary w/ Tertiary Graduates Tertiary Grad.

(%) (/100k people) (/100k people)LYA LYA LYA LYA LYA 1980-1995 1996HC17 HC18 HC19 HC20 HC21 HC22 HC23 HC24

Algeria 303 26,724 11 1,129 184Bahrain 137 3,838 10.3 2,090 272Comoros 240 5Djibouti 124 512 161 15 678 91Egypt ` 47,225 5 4.6 2,435 213Iraq 149 357 14,139 8 18 4.1 1,553 274Jordan 74 428 6,645 4 17 3,069 657Kuwait 254 498 29,509 16 38 16.4 2,833 571Lebanon 85 177 8,159 4,738 486Libya 193 6,627 13 2.7 2,105 209Mauritania 22 131 8,496 3 3 1.3 743 107Morocco 25 544 22,267 1 20 1,147 128Oman 1,398 763 16,032 69 29 414 101Palestine 587 5,511 14 2,126 345Qatar 110 308 8,475 5 5 13.3 1,715 244Saudi Arabia 96 196 34,249 9 15 944 163Somalia 97 161 2,040 8 8 169 9Sudan 46 269 2,301 1 9 0.8 530 42Syria 90 249 41,797 4 11 1,391 200Tunisia 61 32 20,298 14 2.8 1,320 209UAE 4,053 640 120Yemen 194 4,378 11 337 74

Arab States 185 338 14,901 11 14 6.3 1,529 224

SOURCE Calculated Calculated Calculated Calculated Calculated UNESCO HES, 1998 HES, 1998

Staff to Schools Higher EducationPupils to Schools


ArabicMale Female Male Female Language Math(%) (%) (%) (%) (%) (%)

1994-1999 1994-1999 1997 1997 LYA LYAHC25 HC26 HC27 HC28 HC29 HC30

Algeria 82.0 79.0 96.0 94.0Bahrain 98.4 99.1ComorosDjiboutiEgypt 88.0 85.0Iraq 99.0 98.0 82.0 87.0Jordan 63.0 63.0 97.5 97.7 63.1 26.7Kuwait 63.0 62.0 95.2 98.1 57.0 43.5Lebanon 71.4 60.6LibyaMauritania 30.0 30.0 65.4 66.1 36.8 26.0Morocco 55.0 51.0 73.1 76.6Oman 75.0 75.0 95.6 94.5 57.3 54.3Palestine 98.0 98.3 32.0 16.7Qatar 82.3 92.5 98.5 98.8Saudi Arabia 87.0 75.0 97.0 95.7SomaliaSudan 46.0 41.0 74.6 77.9 76.3 27.7Syria 91.0 88.0 93.2 90.0 82.5 84.5Tunisia 87.0 85.0 90.0 92.0 71.3 28.8UAE 96.0 98.0 94.7 96.1 53.5 51.5Yemen 83.0 51.0 77.2 69.2

Arab States 74.6 70.1 88.1 89.1 63.6 47.2

SOURCE WDI, 2001 WDI, 2001

Pupils with Basic SkillsGrade 5 CohortGrade 1 Net Intake

Process Capital Process Capital (1 of 2)(1 of 2)

Total PC-1 in Waiting Waiting Cost of Cost of Int. Intn'l Internet Securelargest city List Time Local Call Call (3min) Mins/User PC's Hosts Users Servers

(/1000 p.) (/1000 p.) (000's) (years) ($) ($) (minutes) (/1000 p.) (/10K p.) ('000's)1999 1999 1999 1999 1999 1999 1999 2000 1999 2000PC01 PC02 PC03 PC04 PC05 PC06 PC07 PC08 PC09 PC10 PC11

Algeria 52 55 640.0 6.0 0.02 8.278 90 5.8 0.01 20BahrainComorosDjiboutiEgypt 75 151 1290.0 2.3 0.03 7.849 32 12.0 0.85 200 12Iraq 30 75 19 0.00Jordan 87 232 29.7 0.4 0.03 258 13.9 1.45 12 2Kuwait 240 47 0.0 0.0 0.02 8.011 394 121.3 23.15 100 3Lebanon 201 96 0.07 8.372 124 46.4 11.89 200 16Libya 101 94 80.0 1.4 0.03 78 0.01 7Mauritania 6 17 47.8 >10.0 0.09 489 27.2 0.20 13Morocco 53 115 17.9 0.2 0.08 8.353 40 10.8 0.33 50 4Oman 90 165 3.9 0.5 0.07 463 26.4 3.00 50 1PalestineQatarSaudi Arabia 129 253 927.0 3.1 0.02 7.634 305 57.4 1.53 300 9SomaliaSudan 9 45 355.0 7.0 0.02 99 2.9 0.00 5Syria 99 140 2820.0 >10.0 0.01 76 14.3 0.00 20 1Tunisia 90 90 83.7 0.9 0.03 7.612 165 15.3 0.10 30 4UAE 332 373 0.6 0.0 0.02 8.627 988 102.1 92.13 400 24Yemen 17 77 131.0 4.5 0.02 109 107.0 0.06 10

Arab States 87 127 6314.0 1.4 0.03 8.092 124 25.4 0.67 1153 72

SOURCE WDI, 2001 WDI, 2001 WDI, 2001 WDI, 2001 WDI, 2001 WDI, 2001 WDI, 2001 WDI, 2001 WDI, 2001 WDI, 2001 WDI, 2001

Computer and InternetTelephone Mainlines

Process Capital Process Capital (2 of 2)(2 of 2)

Mobile Newspaper

Phones Radio TV TV Cable FaxReceivers Sets Subscribers Machines Circulation

(/ 1000 p.) (/1000 p.) (/1000 p.) (/1000 p.) (/1000 p.) (/1000 p.)1999 1999 1999 1999 1999 LYAPC12 PC13 PC14 PC15 PC16 PC17

Algeria 2 242 105 0.2 38Bahrain 580 472 117Comoros 141 1.9Djibouti 84 45Egypt 8 317 119 0.5 38Iraq 0 229 83 20Jordan 18 271 82 0.1 8.4 42Kuwait 158 678 505 31.6 377Lebanon 194 907 375 1.4 141Libya 4 259 140 14Mauritania 0 146 24 1.3 1Morocco 13 247 115 0.7 27Oman 49 607 694 2.7 28PalestineQatar 450 404 161Saudi Arabia 40 321 262 59Somalia 53 15 1Sudan 0 272 86 0.0 0.9 27Syria 0 278 70 1.4 20Tunisia 6 224 100 3.4 31UAE 283 355 134 21.0 170Yemen 2 64 29 15

Arab States 12 320 184 0.5 6.6 70

SOURCE WDI, 2001 UNESCO UNESCO UNESCO UNESCO UNESCO

Radio, Television, & Fax Machines

Market Capital Market Capital (1 of 2)(1 of 2)

% of Mfg. % of Mfg. Domestic Granted

Total (A) (B) Receipts Payments Apps. by USPTO Books Periodicals

($ millions) (%) (%) ($ millions) ($ millions) (/M people) ($) ($)1999 1999 1999 1999 1999 1998 2000 LYA LYA

MC01 MC02 MC03 MC04 MC05 MC06 MC07 MC08 MC09Algeria 16 4 0.656 42 0.000 17 1,410Bahrain 1.183 23 1ComorosDjiboutiEgypt 3 0 0 47 329 494 0.079 4,588 2,266Iraq 68Jordan 15 2 0.328 0 0.311 15,137Kuwait 35 1 0.164 2.747 699 138Lebanon 1.183LibyaMauritania 0 0Morocco 10 0 0 6 201 90 0.118 860 8Oman 118 10 1.639 0.000 446 115PalestineQatar 0.000Saudi Arabia 18 0 0 0 0 45 1.140 1,032 34SomaliaSudan 0 0 0 0 6 2 8Syria 0.381 560Tunisia 125 3 0.492 10 3 46 0.000 1,364 381UAE 2Yemen 0 0.000 20

Arab States 1336 2 0.410 63 548 926 0.549 24,748 4,363

SOURCE WDI, 2001 HDR, 2001 WDI, 2001 HDR, 2001 HDR, 2001 WDI, 2001 USPTO UNESCO UNESCO

High-Technology Exports Royalty & License Fees $000's Spent on ExportsPatents

Market Capital Market Capital (2 of 2)(2 of 2)

Citations Meetings Study Abroad

Number vs. studying

Hosted domestically

(%)93-97 2000 LYAMC10 MC11 MC12

Algeria 1,814 18 7.4Bahrain 9Comoros 0Djibouti 1Egypt 9,730 143 0.9Iraq 327 5Jordan 1,018 17 15.4Kuwait 1,576 6Lebanon 715 20 12.9Libya 5Mauritania 3Morocco 3,031 74 11.9Oman 4Palestine 0Qatar 7Saudi Arabia 7,826 4 2.8Somalia 1Sudan 852 8Syria 11 6.8Tunisia 2,148 46 9.4UAE 1,352 19Yemen 3

Arab States 29,050 404 8.4

SOURCE IBRD (2000) ICCA (2000)

Renewal Renewal Capital (1 of 3)Capital (1 of 3)

National Public Institution Technical Sci & Tech ISI Social Sci. Book PeriodicalLibraries Libraries Libraries Papers Articles Publications Papers Imports Imports

('000's) ('000's) ('000's) (/M people) ($000's) ($000's)LYA LYA LYA 1997 1997 1995 - 2001 1995 LYA LYARC01 RC02 RC03 RC04 RC05 RC06 RC07 RC08 RC09

Algeria 623 2.063 139 2,480 291 9,717 584Bahrain 35 522 4,301 1,038Comoros 9Djibouti 16 1,305 163Egypt 1,154 1,500 35,790 3.925 1,108 16,349 2,091 13,358 3,387Iraq 35 500 84Jordan 706 1,227 4.973 177 3,563 278 6,734 320Kuwait 272 6.341 173 3,711 324 8,767 6,023Lebanon 2,075 4.134 81 4,828 110Libya 352 28,958 64Mauritania 2 72Morocco 3.061 271 5,939 554 21,542 13,943Oman 4 101 4.536 53 1,229 3,703 2,442Palestine 349 89Qatar 228 138 329 368 368Saudi Arabia 4,844 4.755 613 11,260 1,409 61,373 769Somalia 15Sudan 43 681 101 432 726Syria 150 10 0.361 57 760 889Tunisia 2,493 4.180 188 3,400 300 14,642 5,923UAE 13 5.245 127 2,216 224 289Yemen 0.125 10 221 827 570

Arab States 2,865 4,403 44,773 3.642 3,123 58,580 5,555 176,548 36,609

SOURCE UNESCO UNESCO UNESCO WDI, 2001 HDR, 2001 ISI, 2001 IBRD, 2000 UNESCO UNESCO

Number of Books Publications Importing Information


Students in # in # of # of # in # in # inTotal % of GNI Tertiary R&D Technicians Researchers Ministry Universities Private Sect.

($000's) (%) (%) (/M people) (/M people) (/Million) (/M people) (/M people) (/M people)1996 87-97 1987-1997 1987-1997 1987-1997 LYA 1996 1996 1996RC10 RC11 RC12 RC13 RC14 RC15 RC16 RC17 RC18

Algeria 33,561 58 529 475 0Bahrain 3,736 39 27 59 0ComorosDjiboutiEgypt 227,499 0.22 15 459 341 459 8,074 2,384 286Iraq 27,573 41 729 662 0Jordan 20,615 0.26 28 94 10 94 215 140 46Kuwait 67,113 0.16 29 230 71 230 334 83 23Lebanon 7,453 30 93 112 0Libya 16,921 8 362 130 105 0Mauritania 4,304 41 76 40 0Morocco 74,871 41 824 750 52Oman 10,755 13 56 26 0PalestineQatar 5,461 594 4 30 0Saudi Arabia 196,094 17 308 538 0SomaliaSudan 10,044 16 500 143 0Syria 24,184 0.20 23 30 25 30 210 146 0Tunisia 28,901 0.30 33 125 57 125 267 218 0UAE 10,886 24 56 51 0Yemen 10,297 5 204 66 0

Arab States 780,268 0.23 29 188 101 271 702 335 23

SOURCE WDI, 2001 WDI, 2001 UNESCO

Scientists and Engineers Research and DevelopmentR&D Expenditures


Patents

GNP Govn't Tertiary Pre- ForeignExpenditure Expenditure Primary Primary Secondary Tertiary Apps.

(%) (%) (% of RC20)1995-1997 1995-1997 LYA LYA LYA LYA LYA 1998

RC19 RC20 RC21 RC22 RC23 RC24 RC25 RC26Algeria 5.10 16.40 73.40 25.13 27.35 17.09 17.45 264 Bahrain 4.40 12.00 31.26 11.72Comoros 29.63 52.07 35.86Djibouti 65.90 33.66 28.21Egypt 4.80 14.90 14.10 24.07 24.18 18.63 1,139 Iraq 40.60 17.56 19.96 19.80 19.24 18 Jordan 7.90 19.80 53.00 20.75 24.73 21.41Kuwait 5.00 14.00 30.50 15.48 13.18 10.64 17.45Lebanon 2.50 8.20 32.69 7.81Libya 14.30Mauritania 5.10 16.20 49.60 7.41 50.23 26.39 31.47Morocco 24.90 40.30 21.01 27.63 16.28 237 Oman 4.50 16.40 31.60 20.14 26.01 17.60 12.27Palestine 85.00 41.27 0.72 20.30Qatar 3.40 53.70 21.86 62.07 9.61 13.18Saudi Arabia 7.50 22.80 43.80 11.10 12.86 12.94 17.27 1,286 Somalia 11.71 19.01 18.50 6.30Sudan 1.40 43.30 38.64 29.13 25.72 29.28 67,713 Syria 4.20 13.60 43.10 22.17 23.46 396.44 35.32Tunisia 7.70 19.90 43.40 2.35 22.81 18.34 128 UAE 1.70 20.30 38.70 17.89 16.07 12.38 8 Yemen 7.00 21.60 80.00 17.65 29.84 20.77

Arab States 4.81 17.21 47.05 19.79 28.16 39.47 18.59 70,793

SOURCE HDR, 2001 HDR, 2001

Public Expenditure on Education Staff to Pupil Ratio

Sampling for Sampling for the NICIthe NICI

Total Population Total GDP (millions) ($ U.S. billions) 2000 1999 Algeria 30.31 47.872 Egypt 67.89 89.148 Jordan 4.91 8.073 Kuwait 1.91 29.572 Morocco 29.88 34.998 Oman 2.54 14.962 Saudi Arabia 20.35 139.383 Sudan 31.10 9.718 Tunisia 9.46 20.944 Yemen 18.35 6.825 Sample Arab States 216.70 401.500

10 of 22 countries representing 77% of the population

Development of Development of the NHCIthe NHCI

Index H1 H2 H3 H4 H5 H6 H7 Metric HC02 HC05 HC11 HC16 HC23 HC25 HC26

NHCITM

Algeria 0.633 0.124 0.930 0.498 0.368 0.82 0.79 0.586 Egypt 0.553 0.077 0.998 0.544 0.793 0.88 0.85 0.647 Jordan 0.898 1.000 0.467 1.000 1.000 0.63 0.63 0.842 Kuwait 0.823 0.151 1.000 0.672 0.923 0.63 0.62 0.726 Morocco 0.489 0.135 0.910 0.453 0.374 0.55 0.51 0.481 Oman 0.719 0.114 0.990 0.274 0.135 0.75 0.75 0.537 S. Arabia 0.770 0.114 1.000 0.585 0.308 0.87 0.75 0.638 Sudan 0.571 0.241 0.611 0.084 0.173 0.46 0.41 0.382 Tunisia 0.708 0.183 0.933 0.560 0.430 0.87 0.85 0.644 Yemen 0.462 0.236 0.743 0.156 0.110 0.83 0.51 0.410 Weighting 30% 10% 10% 15% 15% 10% 10% H1 HC02 literacy rate H2 HC05 number of tertiary schools per capita relative to highest value H3 HC11 percentage of primary teachers with required qualifications H4 HC16 number of tertiary students per capita relative to highest value H5 HC23 cumulative tertiary graduates per capita relative to highest value H6 HC25 percentage of male grade 1 net intake H7 HC26 percentage of female grade 1 net intake

Development of Development of the NPCIthe NPCI

Index P1 P2 P3 P4 P5 P6 P7 P8 Metric PC01 PC08 PC09 PC10 PC12 PC13 PC14 PC17

NPCITM

Algeria 0.217 0.048 0.000 0.013 0.013 0.357 0.151 0.101 0.117 Egypt 0.313 0.099 0.037 0.056 0.051 0.468 0.171 0.101 0.168 Jordan 0.363 0.115 0.063 0.047 0.114 0.400 0.118 0.111 0.178 Kuwait 1.000 1.000 1.000 1.000 1.000 1.000 0.728 1.000 0.973 Morocco 0.221 0.089 0.014 0.032 0.082 0.364 0.166 0.072 0.130 Oman 0.375 0.218 0.130 0.376 0.310 0.895 1.000 0.074 0.385 S. Arabia 0.538 0.473 0.066 0.282 0.253 0.473 0.378 0.156 0.327 Sudan 0.038 0.024 0.000 0.003 0.000 0.401 0.124 0.072 0.073 Tunisia 0.375 0.126 0.004 0.061 0.038 0.330 0.144 0.082 0.158 Yemen 0.071 0.882 0.003 0.010 0.013 0.094 0.042 0.040 0.125 Weighting 20% 10% 15% 10% 10% 10% 10% 15% P1 PC01 telephone mainlines per capita relative to highest value P2 PC08 personal computers per capita relative to highest value P3 PC09 Internet hosts per capita relative to highest value P4 PC10 Internet users per capita relative to highest value P5 PC12 mobile phones per capita relative to highest value P6 PC13 radio receivers per capita relative to highest value P7 PC14 television sets per capita relative to highest value P8 PC17 newspaper circulation per capita relative to highest value

Development of Development of the NMCIthe NMCI

Index M1 M2 M3 Metric MC01 MC08 MC11

NMCITM

Algeria 0.042 0.000 0.122 0.062 Egypt 0.004 0.027 0.433 0.183 Jordan 0.236 1.000 0.712 0.655 Kuwait 0.150 0.013 0.646 0.307 Morocco 0.036 0.013 0.509 0.219 Oman 1.000 0.016 0.324 0.434 S. Arabia 0.016 0.004 0.040 0.022 Sudan 0.000 0.000 0.053 0.021 Tunisia 0.757 0.035 1.000 0.637 Yemen 0.000 0.002 0.034 0.014 Weighting 30% 30% 40%

M1 MC01 high-technology exports as a percentage of GDP relative to highest value M2 MC08 number of patents granted by USPTO per capita relative to highest value M3 MC11 number of meetings hosted per capita relative to highest value

Development of Development of the NRCIthe NRCI

Index R1 R2 R3 R4 R5 R6 R7 Metric RC08 RC09 RC10 RC12 RC16 RC17 RC21

NRCITM

Algeria 0.243 0.031 0.275 0.580 0.066 0.199 0.734 0.254 Egypt 0.180 0.095 0.999 0.150 1.000 1.000 0.141 0.699 Jordan 1.000 0.099 1.000 0.280 0.027 0.059 0.530 0.480 Kuwait 0.355 0.511 0.889 0.290 0.041 0.035 0.305 0.411 Morocco 0.738 1.000 0.838 0.410 0.102 0.315 0.403 0.564 Oman 0.297 0.410 0.281 0.130 0.007 0.011 0.316 0.187 S. Arabia 0.528 0.014 0.551 0.170 0.038 0.226 0.438 0.309 Sudan 0.053 0.188 0.405 0.160 0.062 0.060 0.433 0.204 Tunisia 0.838 0.710 0.540 0.330 0.033 0.091 0.434 0.395 Yemen 0.145 0.210 0.591 0.050 0.025 0.028 0.800 0.267 Weighting 10% 10% 30% 10% 15% 20% 5% R1 RC08 book imports as a percentage of GDP relative to highest value R2 RC09 periodical imports as a percentage of GDP relative to highest value R3 RC10 total R&D expenditures as a percentage of GDP relative to highest value R5 RC16 number of ministry employees in R&D per capita relative to highest value R6 RC17 number of university employees in R&D per capita relative to highest value R7 RC21 tertiary expenditure as a percentage of public education funding

Countries Countries Ranked by NICIRanked by NICI

NHCITM NMCITM NPCITM NRCITM NICITM FC

Kuwait 0.726 0.307 0.973 0.411 0.604 1.000 Jordan 0.842 0.655 0.178 0.480 0.539 0.229 Tunisia 0.644 0.637 0.158 0.395 0.459 0.345 Egypt 0.647 0.183 0.168 0.699 0.424 0.198 Oman 0.537 0.434 0.385 0.187 0.386 0.773 Morocco 0.481 0.219 0.130 0.564 0.349 0.198 S. Arabia 0.638 0.022 0.327 0.309 0.324 0.626 Algeria 0.586 0.062 0.117 0.254 0.255 0.293 Yemen 0.410 0.014 0.125 0.267 0.204 0.047 Sudan 0.382 0.021 0.073 0.204 0.170 0.038

FC FC01 national financial capital, GDP per capita relative to highest value

Is the NICI a good predictor of a nation’s wealth?

Structural Structural Model of NICIModel of NICI

Hypothesis H1 H2 H3 H4 H5 H6 coefficient 0.450 0.106 0.775 0.279 0.273 0.277

National Human Capital

National Process Capital

National Market Capital

National Renewal Capital

National Financial Capital

H3

H1

H4

H2

H5

H6

R2 = 20.9%

Clustering Clustering by by NICINICI and GDP and GDP

Relative FCGDP / capita

NICITM

1.0

0.5

0.00.0 0.5 1.0

Kuwait

JordanTunisia

Egypt

Morocco

Yemen

Algeria

Oman

S. Arabia

Sudan


R2 = 20.9%

ConclusionsConclusionsNational intellectual capital accounts for nearly one-fifth of the explanatory power of the financial wealth of an Arab country.

Human capital is the pre-eminent antecedent for the intellectual wealth of a nation. As a nation’s citizens codify their knowledge into the systems and processes of a country (H1), those structural capital assets can then be renewed for the future (H2) by investing in research and development. A feedback loop further develops a nation’s human capital (H3). Eventually, the codified knowledge base of a nation can be marketed (H4) within the global and domestic economies. As the human capital continually develops (H5), a nation’s ability to market its intellectual wealth will result in a higher financial well-being (H6).

Future Future ResearchResearch

• Larger sample across many more nations (allows for bench-marking).

• Longitudinal nature of impacts (i.e., time lag effects of constructs and measures).

• Alternative financial capital measures • In-depth intra-national analysis (i.e.,

within industrial sectors or sub-geographies)

• Intermediating effects (i.e., poverty, gender empowerment, health)

Background Information

http://www.undp.org/

Customer Capital


Innovation Capital

Process Capital

Structural Capital

Human Capital


Financial Capital

Market Value


Conceptual Model - Nation

Market Capital


Renewal Capital

Process Capital

Structural Capital

Human Capital


Financial Wealth

National Wealth

Developed Nations

NorwayRussia

Singapore

ItalyJapan

New Zealand

SwedenUK

USA

AustraliaCanadaChina

FinlandFrance

Germany













Descriptive Statistics (1 of 2)

GDP/Cap PPP 2000 Pop 2015 Pop 2015 - 2000$ Millions Millions % Change

Australia 25,693 19 21.9 14%Canada 27,840 31 34.4 12%China 3,976 1,263 1410.2 12%Finland 24,996 5 5.2 0%France 24,223 59 61.9 5%Germany 25,103 82 80.7 -2%Italy 23,626 58 55.2 -4%Japan 26,755 127 127.5 0%New Zealand 20,070 4 4.1 7%Norway 29,918 4 4.7 5%Russia 8,377 146 133.3 -8%Singapore 23,356 4 4.8 19%Sweden 24,277 9 8.6 -3%United Kingdom 23,509 60 60.6 1%United States 34,142 282 321.2 14%





Descriptive Statistics (2 of 2)

Unemploy Youth Unemp Urban Pop Svc Empt Life ExpRate % Rate % % of total % of total Years

Australia 6.3 14 85 73.6 78.9Canada 6.8 14 77 74.1 78.9China 3.1 3 32 12.9 70.3Finland 9.8 22 67 66.0 77.5France 9.5 27 76 74.0 78.9Germany 7.5 8 88 62.6 77.4Italy 10.7 33 67 62.2 78.7Japan 4.7 9 79 63.1 80.7New Zealand 6.0 14 87 67.6 78.2Norway 3.4 10 76 73.8 78.6Russia 13.3 7 73 58.8 65.3Singapore 3.2 8 100 71.1 77.7Sweden 4.7 14 83 72.2 79.6United Kingdom 5.5 12 90 72.8 77.3United States 4.0 10 77 74.5 77.1

Prime Minister’s Report

Category Canada's Performance Top Performer

Economy Average U.S.

Labour markets Top U.S.

Innovation Poor Sweden

Environment Poor Sweden

Education Average U.S.

Health Average Japan

Financial Capital

GDP/Cap PPP GDP, PPP Market Cap (listed)$ $ billions % of GDP

Australia 25,693 493 95.6Canada 27,840 856 122.3China 3,976 5,019 53.8Finland 24,996 129 241.7France 24,223 1,427 111.8Germany 25,103 2,062 67.8Italy 23,626 1,363 71.5Japan 26,755 3,394 65.2New Zealand 20,070 77 37.3Norway 29,918 134 40.2Russia 8,377 1,219 15.5Singapore 23,356 94 165.7Sweden 24,277 215 144.4United Kingdom 23,509 1,404 182.2United States 34,142 9,613 153.5

Human Capital (1 of 2)

Adult literacy Secondary Public $ on Educ. Pupil:Teacher% age > 15 enrolment % % of GDP Ratio

Australia 99.9 79 4.8 4.8Canada 99.9 94 5.6 5.6China 84.1 50 2.3 23.7Finland 99.9 95 7.1 17.8France 99.9 94 5.9 5.9Germany 99.9 88 4.6 4.6Italy 98.4 88 4.7 4.7Japan 99.9 97 3.5 3.5New Zealand 99.9 84 7.2 7.2Norway 99.9 96 7.7 7.7Russia 99.6 78Singapore 92.3 75 25.4Sweden 99.9 100 8.0 8.0United Kingdom 99.9 94 4.7 4.7United States 99.9 90 5.0 5.0

Human Capital (2 of 2)

Teachers' comp Educ exp Edu Exp% of Educ Exp as % of GNP as % of Gov Exp

Australia 5.5 13.5Canada 18.0 6.9 12.9China 21.5 2.3 12.2Finland 17.3 7.5 12.2France 18.9 6.0 10.9Germany 17.0 4.8 9.6Italy 11.3 4.9 9.1Japan 21.0 3.6 9.9New Zealand 7.3 17.1Norway 7.7 16.8Russia 17.6 3.5 9.6Singapore 25.3 3.0 23.3Sweden 12.3 8.3 12.2United Kingdom 19.1 5.3 11.6United States 15.4 5.4 14.4

Process Capital (1 of 2)

Telephones Moblies TV sets Cable TV PCs Radios Internet hosts per 1,000 per 1,000 per 1,000 per 1,000 per 1,000 per 1,000 per 1,000

Australia 525 447 738 68 465 1,376 85.7Canada 677 285 715 259 390 1,047 77.4China 112 66 293 61 16 339 0.1Finland 550 720 692 184 396 1,564 102.3France 579 493 628 45 304 950 19.1Germany 611 586 586 247 336 948 24.8Italy 474 737 494 1 180 878 17.8Japan 586 526 725 147 315 956 36.5New Zealand 500 563 522 4 360 997 90.6Norway 532 751 669 184 491 915 101.1Russian Federation 218 22 421 78 43 418 2.2Singapore 484 684 304 63 483 672 45.2Sweden 682 717 574 199 507 932 67.3United Kingdom 589 727 653 57 338 1,432 28.2United States 700 398 854 252 585 2,118 295.2

Process Capital (2 of 2)

Electricity consumption IT exp. IT Exp. / capita Internet users (active)kwh per capita % of GDP US$ % of population

Australia 8,884 9.7 1,922 34%Canada 15,260 8.4 1,911 41%China 758 5.4 46 2%Finland 14,366 7.8 1,835 37%France 6,392 8.7 1,916 14%Germany 5,690 7.9 1,798 29%Italy 4,535 5.7 1,068 23%Japan 7,443 8.3 3,118 37%New Zealand 8,426 13.6 1,771 22%Norway 24,248 6.9 2,445 49%Russian Federation 4,050 3.7 63 2%Singapore 6,641 9.7 2,104 30%Sweden 14,138 10.4 2,674 46%United Kingdom 5,384 9.1 2,187 30%United States 11,994 8.1 2,926 34%

Market Capital (1 of 1)High-tech exports License fees receipts Outgoing Int. telecom Daily newspapers % of Mfg. exports US$ per person mins / subscriber per 1,000

Australia 15.22 17.9 136 293Canada 18.60 44.7 347 159China 18.58 0.1 11Finland 27.33 219.9 164 455France 24.26 39 129 201Germany 17.71 34.4 184 305Italy 9.19 9.8 101 104Japan 28.35 80.5 35 578New Zealand 10.16 12.9 340 207Norway 17.13 29.3 234 581Russia 13.53 0.6 29 105Singapore 63.00 538 298Sweden 22.00 144.2 209 432United Kingdom 32.00 123.9 227 329United States 34.00 134.3 153 213

Renewal Capital (1 of 2)

R&D Exp. R&D Scientists Science students% of GDP per million % of tertiary

Australia 1.7 3,320 24.2Canada 1.7 3,009 15.7China 0.1 459 53.0Finland 2,668 36.6France 2.2 2,686 48.0Germany 2.3 2,873 39.2Italy 1.0 1,322 30.8Japan 2.8 4,960 26.7New Zealand 1.2 2,197 19.9Norway 1.7 4,095 26.1Russia 1.1 3,397 48.0Singapore 1.1 2,182 18.5Sweden 3.8 4,507 37.6United Kingdom 1.8 2,678 29.0United States 2.5 4,103 36.5





Renewal Capital (2 of 2)

License fees paymt. Trademarks filed Patents grantedUS$ per person per million per million

Australia 52 3,065 75Canada 106 1,313 31China 1 131 1Finland 106 1,828 187France 35 1,708 205Germany 66 1,044 235Italy 21 778 13Japan 87 961 994New Zealand 80 4,327 103Norway 87 3,026 103Russia 0 199 131Singapore 0 3,921 8Sweden 101 1,755 271United Kingdom 103 1,186 82United States 57 926 289

Development of the NFCI

GDP/Cap PPP GDP, PPP Market Cap (listed) NFCI$ $ billions % of GDP

United States 34,142 9,613 153.5 3.64Finland 24,996 129 241.7 3.02United Kingdom 23,509 1,404 182.2 1.64Singapore 23,356 94 165.7 1.16Canada 27,840 856 122.3 1.11Sweden 24,277 215 144.4 .89France 24,223 1,427 111.8 .32Australia 25,693 493 95.6 .15Japan 26,755 3,394 65.2 -.03Norway 29,918 134 40.2 -.29Germany 25,103 2,062 67.8 -.38Italy 23,626 1,363 71.5 -.63New Zealand 20,070 77 37.3 -2.07China 3,976 5,019 53.8 -4.09Russia 8,377 1,219 15.5 -4.45

Development of the NHCI

H1 H2 H3 H4 H5 H6 H7 NHCISweden 99.9 100 8.0 8.0 12.3 8.3 12.2 1.27Norway 99.9 96 7.7 7.7 7.7 16.8 .71Canada 99.9 94 5.6 5.6 18.0 6.9 12.9 .49Finland 99.9 95 7.1 17.8 17.3 7.5 12.2 .46Italy 98.4 88 4.7 4.7 11.3 4.9 9.1 .44France 99.9 94 5.9 5.9 18.9 6 10.9 .40New Zealand 99.9 84 7.2 7.2 7.3 17.1 .40United States 99.9 90 5.0 5.0 15.4 5.4 14.4 .31United Kingdom 99.9 94 4.7 4.7 19.1 5.3 11.6 .20Germany 99.9 88 4.6 4.6 17.0 4.8 9.6 .19Australia 99.9 79 4.8 4.8 5.5 13.5 -.01Japan 99.9 97 3.5 3.5 21.0 3.6 9.9 -.10Russia 99.6 78 17.6 3.5 9.6 -.22Singapore 92.3 75 25.4 25.3 3 23.3 -1.86China 84.1 50 2.3 23.7 21.5 2.3 12.2 -2.69

Development of the NPCI

PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 NPCIUnited States 700 398 854 252 585 2,118 295.2 11,994 8.1 2,926 34% 1.53Norway 532 751 669 184 491 915 101.1 24,248 6.9 2,445 49% .88Sweden 682 717 574 199 507 932 67.3 14,138 10.4 2,674 46% .85Finland 550 720 692 184 396 1,564 102.3 14,366 7.8 1,835 37% .64Canada 677 285 715 259 390 1,047 77.4 15,260 8.4 1,911 41% .58Australia 525 447 738 68 465 1,376 85.7 8,884 9.7 1,922 34% .36Japan 586 526 725 147 315 956 36.5 7,443 8.3 3,118 37% .34United Kingdom 589 727 653 57 338 1,432 28.2 5,384 9.1 2,187 30% .18Germany 611 586 586 247 336 948 24.8 5,690 7.9 1,798 29% .05New Zealand 500 563 522 4 360 997 90.6 8,426 13.6 1,771 22% -.05Singapore 484 684 304 63 483 672 45.2 6,641 9.7 2,104 30% -.20France 579 493 628 45 304 950 19.1 6,392 8.7 1,916 14% -.30Italy 474 737 494 1 180 878 17.8 4,535 5.7 1,068 23% -.76Russia 218 22 421 78 43 418 2.2 4,050 3.7 63 2% -1.92China 112 66 293 61 16 339 0.1 758 5.4 46 2% -2.17

Development of the NRCI

RC1 RC2 RC3 RC4 RC5 RC6 NRCIJapan 2.8 4,960 26.7 87 961 994 1.97449Sweden 3.8 4,507 37.6 101 1,755 271 1.45856United States 2.5 4,103 36.5 57 926 289 .59575Norway 1.7 4,095 26.1 87 3,026 103 .47169Canada 1.7 3,009 15.7 106 1,313 31 .28614Finland 2,668 36.6 106 1,828 187 .18849Germany 2.3 2,873 39.2 66 1,044 235 .17207United Kingdom 1.8 2,678 29.0 103 1,186 82 .12403Australia 1.7 3,320 24.2 52 3,065 75 .02155New Zealand 1.2 2,197 19.9 80 4,327 103 -.16539France 2.2 2,686 48.0 35 1,708 205 -.22504Russia 1.1 3,397 48.0 0 199 131 -.77830Singapore 1.1 2,182 18.5 0 3,921 8 -.83511Italy 1.0 1,322 30.8 21 778 13 -1.17329China 0.1 459 53.0 1 131 1 -2.11564

Development of the NMCI

MC1 MC2 MC3 MC4 NMCISingapore 63.00 538 298 2.11881Finland 27.33 219.9 164 455 1.30552United Kingdom 32.00 123.9 227 329 .78730Sweden 22.00 144.2 209 432 .72343United States 34.00 134.3 153 213 .53448Japan 28.35 80.5 35 578 .43603Norway 17.13 29.3 234 581 .19953Canada 18.60 44.7 347 159 -.19449Germany 17.71 34.4 184 305 -.38188France 24.26 39 129 201 -.45042New Zealand 10.16 12.9 340 207 -.60013Australia 15.22 17.9 136 293 -.69522China 18.58 0.1 11 -.95016Italy 9.19 9.8 101 104 -1.38288Russia 13.53 0.6 29 105 -1.44992

Countries Ranked by NICI

Is the NICI a good predictor of a nation’s wealth?

NHCI NPCI NRCI NMCI NICI NFCISweden 1.27062 .84501 1.45856 .72343 1.07440 .89213United States .30747 1.53446 .59575 .53448 .74304 3.63611Japan -.10460 .33760 1.97449 .43603 .66088 -.02992Finland .46333 .63571 .18849 1.30552 .64827 3.02013Norway .71069 .88401 .47169 .19953 .56648 -.28583United Kingdom.20407 .18041 .12403 .78730 .32395 1.64398Canada .49292 .58380 .28614 -.19449 .29209 1.11303Germany .18696 .04741 .17207 -.38188 .00614 -.38255Australia -.01249 .36316 .02155 -.69522 -.08075 .15366New Zealand .40285 -.04699 -.16539 -.60013 -.10241 -2.06696France .40326 -.30324 -.22504 -.45042 -.14386 .31559Singapore -1.85927 -.20475 -.83511 2.11881 -.19508 1.15927Italy .44235 -.76415 -1.17329 -1.38288 -.71949 -.62521Russia -.22235 -1.92334 -.77830 -1.44992 -1.09348 -4.45314China -2.68582 -2.16912 -2.11564 -.95016 -1.98019 -4.09029

Structural Model of NICI

Path H1 H2 H3 H4 H5 H6 Arab Region coefficient 0.450 0.106 0.775 0.279 0.273 0.277






H3

H1

H4

H2

H5

H6

R2 = 20.9%

G8 + coefficient 0.742 0.868 0.771 0.645 -0.418 -0.670






H3

H1

H4

H2

H5

H6

R2 = 20.9%

0.9130.2080.454-0.544-0.578-0.4180.6450.7710.8680.742 coefficientG8 +

-0.670-0.4180.6450.7710.8680.742 coefficientG8 +

0.2770.2730.2790.7750.1060.450 coefficientArab Region

H10H9H8H7H6H5H4H3H2H1Path

0.9130.2080.454-0.544-0.578-0.4180.6450.7710.8680.742 coefficientG8 +

-0.670-0.4180.6450.7710.8680.742 coefficientG8 +



Modified NICI ?

0.993-0.6700.2080.454-0.544-0.4180.6450.7710.8680.742 coefficientG8 +

-0.670-0.4180.6450.7710.8680.742 coefficientG8 +



0.993-0.6700.2080.454-0.544-0.4180.6450.7710.8680.742 coefficientG8 +

-0.670-0.4180.6450.7710.8680.742 coefficientG8 +



Poverty

GenderEmpowerment

Health

H7

H8

H9

H10

R2 = 83.3%

0.913-0.6700.578

Poverty

UN Human Poverty Probability not People lacking Population below PovertyIndex @ surviving to 60 functional skills poverty line

United States 15.8 12.8 20.7 16.9 1.61749Russian Federation 30.1 20.1 1.25961United Kingdom 15.1 9.9 21.8 13.4 1.23980Australia 12.9 9.1 17.0 14.3 .56012Canada 12.3 9.5 16.6 12.8 .32925Italy 12.2 9.1 14.2 .28208New Zealand 10.7 18.4 .26560China .00000Singapore .00000Japan 11.2 8.2 11.8 -.08392France 11.1 11.4 8.0 -.31247Germany 10.5 10.6 14.4 7.5 -.51778Finland 8.8 11.3 10.4 5.1 -1.28109Norway 7.5 9.1 8.5 6.9 -1.55023Sweden 6.7 8.0 7.5 6.6 -1.80848

Health

Life Expectancy Baby measles Physicians Health Exp. HealthYears % immunized per 100,000 per Capita PPP

Italy 78.7 90 554 1,676 2.18991Germany 77.4 95 350 2,697 1.33894Norway 78.6 93 413 3,182 .93127United States 77.1 92 279 4,271 .71905France 78.9 84 303 2,288 .57583Sweden 79.6 96 311 2,145 -.02859Australia 78.9 89 240 1,714 -.18666New Zealand 78.2 83 218 1,163 -.22436Japan 80.7 94 193 2,243 -.35919Finland 77.5 96 299 1,704 -.37005Russia 65.3 97 421 -.42537Canada 78.9 96 229 1,939 -.51542United Kingdom 77.3 91 164 1,675 -.73388Singapore 77.7 93 163 678 -1.21061China 70.3 90 162 40 -1.70086

Gender Empowerment

UN GEM % Seats in Female pros Income Gender EmpowerValue parliament % of total ratio

Finland 0.803 36.5 27 0.70 1.51276Sweden 0.824 42.7 49 0.68 1.40361Norway 0.837 36.4 49 0.64 1.08853New Zealand 0.765 30.8 54 0.67 .70486Australia 0.759 26.5 48 0.69 .70061Canada 0.777 23.6 53 0.62 .33363Germany 0.765 31.0 50 0.50 .13904China 21.8 -.00311United States 0.757 13.8 54 0.62 -.07301United Kingdom 0.684 17.1 45 0.61 -.11351France 10.9 -.36633Singapore 0.592 11.8 42 0.50 -.95806Russia 0.450 6.4 64 0.64 -1.39917Italy 0.539 9.1 44 0.44 -1.47306Japan 0.527 10.0 45 0.44 -1.49677

Clustering by NICI and GDP

RelativeGDP / capita

NICI

1.0

0.5

0.00.0 0.5 1.0

Sudan

Kuwait

JordanTunisia

Egypt

Morocco

Yemen

Algeria

Oman

S. Arabia ?

G8 + by NICI and NCFI

RelativeNFCI

Relative NICI

4.0

0.0

-4.0-2.0 -1.0 0.0 1.0 2.0

United States

CanadaSweden

Russia

Japan

Finland

Norway

United Kingdom

Germany

Australia

New Zealand

FranceSingapore

Italy

China

Further Developments ...

• IICR KM Diagnostic Tool (business and government)– Health, financial services, software, chemical, hospital

• IICR KM Seminars (business and government) - certification• Education (McMaster University, Tangonow.net)• eFlow Audit (codified proxy of e-mail flow)• World Congress (http://worldcongress.mcmaster.ca) Jan 19-21, 2005• Journal of Intellectual Capital (http://www.emeraldinsight.com/jic.htm)• 1 text Oxford U. Press with Choo, 1 books with BH KMCI Press• Knexa.com (Tribute incentive methodology, ICUs, rewards)• NICI (National Intellectual Capital Index) for United Nations• Longitudinal causal mapping with integration (RBC project)• Citation impact (literature and cases)• Knowledge auction experiments

Knexa Knexa SolutionsSolutions

• New knowledge assets with old value measures• Market mechanism “the invisible hand of the

market”• Exchanges

– what’s next? … talent markets … total markets

• Internet Auction Model– E-bay, Yahoo, Bid.com, etc. … stickiness, bid-ask

• Cost / benefit micro calculation• ICUs – electronic tokens and the reward of

redemption

5 To Do’s 5 To Do’s ImmediatelyImmediately

1. Raise awareness about knowledge era challengesAction: Fully engage employees about KM

2. Don’t throw training dollars down the toiletAction: Benchmark your T&D / FTE investment

3. Attempt to recoup talent that leaves the firmAction: Implement universal exit (entry) interviews

4. Accelerate your knowledge absorption rateAction: speed reading test (www.bontis.com/speedread)

5. Be mindful of technology investmentsAction: Test that search costs are reduced

Dr. Nick Bontis Ph.D.

DeGroote Business SchoolMcMaster UniversityTel: (905) 525-9140 x23918Fax: (905) 304-7734Director, Institute for Intellectual Capital ResearchChief Knowledge Officer (CKO), Knexa SolutionsAssociate Editor, Journal of Intellectual Capital

[email protected] www.NickBontis.com

Thank Thank you!you!

Speaking, training Keynotes, seminars Consulting, surveys www.NickBontis.com




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KM 101 Dr. Nick Bontis Associate Professor of Strategic Management , McMaster U.

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