Globalizing SMEs

MODELING AND ANALYSIS OF

GLOBALIZING MANUFACTURING SMES

IN DEVELOPING ECONOMIES

Author

Rafi Javed Qureshi

05-UET/PhD-ME-20

Supervisor

Prof Dr Iftikhar Hussain

Department of Mechanical Engineering

Faculty of Mechanical and Aeronautical Engineering

University of Engineering & Technology,(UET) Taxila

Pakistan

2012

[email protected]@uettaxila.edu.pk

ii

MODELING AND ANALYSIS

OF GLOBALIZING MANUFACTURING SMES

IN DEVELOPING ECONOMIES

Rafi Javed Qureshi 05-UET/PhD-ME-20

A dissertation submitted in partial fulfillment of

the requirement for the

degree of

Doctor of Philosophy

in

Industrial Engineering and Management

Research Monitoring Committee

Prof Dr Iftikhar Hussain Supervisor

Dr Khalid Akhtar Member

Prof Dr Sahar Noor Member

Prof Dr Shahab Khushnood Dean (FME&AE)

[email protected]@uettaxila.edu.pk

[email protected]

iii

Acknowledgements

All praises to ALLAH who bestow on us His mercy and kindness. It is indeed a time

of reckoning to remember all those who have given me thrust and support in my

endeavor to work on this topic.

I start with my supervisor Prof Dr Iftikhar Hussain who has endured with me over a

period exceeding six years showing his patience with my intellectual follies and

posing confidence in me to think always positive.

My special thanks go to Dean Dr Shahab Khushnood who always provided the

supporting environment to creatively induce and test new ideas keeping resilience

intact. His push always worked wonders when thinking batteries seemed to be drying.

It is time to pay homage to other members of my research monitoring committee to

spare time and provide me conciliatory support. In this regard my gratitude goes to

Prof Dr Khalid Akhtar and Prof Dr Sahar Noor for their thoughtful and constructive

suggestions.

At this moment, I would pay respect to Engr Aamir Hussain, CEO TESLA whose

wonderful achievement for Pakistan as an entrepreneur inspired me to select SMEs as

an area of research. I specifically want to thank him for my six months stay at his

facility and experience the dynamics of entrepreneurship in a real time environment.

My special thanks go to Mr Imtiaz Rastgar whose efforts for promoting the cause of

entrepreneurship and SMEs in Pakistan as former Chairman EDB are laudable. I must

also thank Prof Sarfraz Mian of State University of NewYork and Dr Arif Rana of

LUMS for providing me support in the form of literature and SME Pulse in early days

of research.

There are a lot of entrepreneurs and academia persons who have helped my thoughts

to grow and mature regarding entrepreneurship and SMEs in Pakistan. In this regard, I

iv

pay thanks to Dr Shahid Qureshi (Associate Director Entrepreneurship at IBA

Karachi), Dr Ali Sajid (Founder Director of IB & M, UET Lahore), Engr Asif Ali

Shah (Director, Technology Incubation Center, UET Peshawar), Dr Ali Rizwan (UET

Taxila), Engr Tallat Mahmood (CEO, Global Engg Services) and Engr Shoaib Qadri.

I should avail this opportunity to pay homage to the individuals and institutions that

have contributed vehemently to make ICT as an open source of information exchange

and strengthened the cause of promoting knowledge sharing among the under-

privileged educational communities of the globalized world. I have benefited a lot by

online video lectures of Professor Andrew NG of Stanford University on Machine

Learning through the courtesy of Professional Development Centre and, Professor

David Mease of San Jose State University related to Statistical Aspects of Data

Mining through the courtesy of Google®

Techtalk. I am also indeed thankful to global

institutions like World Bank, Global Entrepreneurship Monitor (GEM), International

Finance Corporation (IFC), World Economic Forum (WEF) and Global Edge of

Michigan State University for sharing their datasets.

There are so many other people and institutions who have aided me in this creative

process. I pay my thanks to all of them. In this regard, efforts of HEC Pakistan are

laudable to launch the Digital Library project thereby facilitating researcher’s access

to international knowledge repositories. The websites of SMEDA and EDB have

come a long way to infer knowledge about SMEs and state of Entrepreneurship in

Pakistan.

I like to thank officers and staff of ASRTD at the University of Engineering and

Technology Taxila for helping and guiding me in procedural matters.

Finally, my heart goes to my family for their astounding support during all these

years.

v

Declaration

It is certified that PhD research work titled “Modeling and Analysis of Globalizing

Manufacturing SMEs in Developing Economies” is my own work. This work has not

been presented elsewhere for assessment. The material used from any other source

has been properly acknowledged.

Author

vi

Acronyms

ABM Agent based Modeling

APS Adult Population Survey

ANN Artificial Neural Networks

ANOVA Analysis of Variance

AUC Area under curve

BLR Binary Logistic Regression

CHAID Chi-Square Automated Interaction Detection

CR Categorical Regression

C&R Classification and Regression

CART Classification and Regression Tree

DM Data Mining

ECI Entrepreneurial Climate Index

EDA Exploratory Data Analysis

EDB Engineering Development Board

ES Enterprise Survey

FDI Foreign Direct Investment

GCI Global Competitiveness Index

GDF Global Development Finance

GDP Gross Domestic Produce

GEM Global Entrepreneurship Monitor

GLM Generalized Linear Modeling

GNI Gross National Income

vii

GOSME Globally Oriented Small and Medium Enterprises

GS Globalization Score

GEDI Global Entrepreneurship and Development Index

GETI Global Enabling Trade Index

GUI Graphical User Interface

HCA Hierarchial Cluster Analysis

H&L Hosmer and Lemeshow

ICT Information and Communication Technologies

IFC International Finance Corporation

KDD Knowledge Discovery from Databases

K-W Kruskal-Wallis

LIC Lower Income Countries

LMC Lower Middle Income Countries

LPI Logistic Performance Index

MAE Mean Absolute Error

MLR Multiple Linear Regression

MNCs Multi National Corporations

MSME Micro, Small and Medium Enterprises

NOC Non-OECD Member Countries

NRI Network Readiness Index

OEC OECD Member Countries

OECD Organization for Economic Cooperation and Development

PCA Principal Component Analysis

viii

QUEST Quick, unbiased and efficient statistical technique

RE Relative Error

ROC Receiver Operating Characteristics

ROSE Rough Set Data Explorer

SME Small and Medium Enterprises

SMEDA Small and Medium Enterprise Authority

SVM Support Vector Machine

UMC Upper Middle Income

UNCTAD United Nations Conference on Trade and Development

VAM Value added manufacturing

WDI World Development Indicators

WEF World Economic Forum

ijEE % of firms engaged in exporting in i

th economy and j

th type of

firm

ETE(E) Ratio of engineering sector exports and total exports

ijHSIO % of high tech firms bearing strong international orientation in

ith

economy and jth

type of firm

ijHMEE % of high tech firms engaged in manufacturing as well as

exporting in ith

economy and jth

type of firm

ijHME % of high tech firms engaged in manufacturing in i

th economy

and jth

type of firm

ijHWIO % of firms bearing weak international orientation in i

th

economy and jth

type of firm

ix

ITI(E) Ratio of engineering sector exports and total exports

ijIIO % of firms bearing intensive international orientation in i

th

economy and jth

type of firm

ijIIO % of firms bearing intensive international orientation at

th

export intensity range in ith

economy and jth

type of firm

ijLSIO % of low tech firms bearing strong international orientation in

ith

economy and jth

type of firm

ijLWIO % of low tech firms bearing weak international orientation in i

th

economy and jth

type of firm

ijLME % of low tech firms engaged in manufacturing in i

th economy

and jth

type of firm

ijLMEE % of low tech firms engaged in manufacturing as well as

exporting in ith

economy and jth

type of firm

ijME % of firms engaged in manufacturing in i

th economy and j

th

type of firm

ijMEE % of firms engaged in manufacturing as well as exporting in i

th

economy and jth

type of firm

ijSIO % of firms bearing strong international orientation in i

th

economy and jth

type of firm

ijWIO % of firms bearing weak international orientation in i

th

economy and jth

type of firm

χ2

Chi-Square

i Rank of ith

economy for world manufacturing export share

ci

Average manufacturing exports per capita for the ith

economy

x

j,i % of total manufacturing exports between ith

and jth

economy

blocks

jk Volume of manufacturing items exported to j

th economy by k

th

economy

k Export intensity ratio of kth

economy

ij % of i

th economy countries with j

th level of VAM contribution

to GDP

% of countries in ith

economy at jth

contribution level of

manufactures export to GDP

'j ratio of foreign to direct sales

i

j

xi

Abstract

The work undertaken in the dissertation is of pioneering nature integrating world

databases to accrue knowledge about economies and enterprises around the globe. It

is an endeavor to demonstrate the adequacy of applying data mining techniques in

global databases concealing heaps of knowledge about enterprises engaged in

manufacturing and exporting in the global context. A cohesive and coherent

exploration of databases from repositories of World Bank, GEM, WEF and IFC’s

Enterprise Survey elucidates the patterns of internationalization of enterprises through

manufacturing exports in developed and developing economies. We have followed

inductive reasoning methodology using symbiosis of statistical modeling and data

mining coupled with extensive data visualizations.

The exploratory research has asserted the fitness of manufacturing exports as the core

engine for economic health of a country. Both Kruskal-Wallis and Chi-square tests

affirm that manufacturing export share level is not independent of economy type and,

developed economy block shares 77% of world manufacturing exports matching to

their share in world GDP. Manufacturing exports per capita for world five economies

ranks them exactly analogous to their income-group ranks. The predictive MLR

modeling reveals a positive relationship between GDP and manufacturing exports for

LMC and UMC economies. LMC economy countries have the prospects of 14%

increase in GDP share by unit increase in manufacturing export share.

The findings from the global databases regarding economies and enterprises in these

economies are in unison. The enterprises of the developing economies (LIC, LMC

and UMC) have more inclination towards manufacturing than economies and

enterprises of developed (NOC, OEC) block. However, the enterprises of developed

economy block lead by a significant margin in terms of exporting and manufacturing

exports. The enterprises of LIC economy block portrays an exorbitant despondency in

all spheres of activities ranging from manufacturing to exporting with pathetic state of

entrepreneurial climate culminating in extreme level of poverty.

Enterprises in Pakistan portray a posture identical to other countries of LMC

economy. K-means and HCA clustering identify LFE (Large, Foreign and Exporter)

enterprises in Pakistan to form one group and align their practices benefiting from

information and communication technologies (ICT) to boost and spearhead the

internationalization through exports. Both statistical and data mining methodologies

work in unison to identify characteristics of a Pakistani SME to be exportable.

Registration with original equipment manufacturer (OEM) is a significant key

determinant for an enterprise to acquire the exporting status.

xii

Table of Contents

Chapter Description

Page

Title Page i

Title Page 2 ii

Acknowledgements iii

Declaration v

Acronyms vi

Abstract xi

Table of Contents xii

List of Figures xix

List of Tables xxvi

1 Introduction

1.1 Globalization 1

1.2 Large Scale Manufacturing 1

1.3 Small Firms 2

1.4 Research Theme 3

1.5 Aims and Objectives of Research 4

1.6 Thesis Organization 5

2 Literature Survey and Research Methodology

2.1 Literature Review

2.1.1 Employment Generation and SMEs 8

2.1.2 Globalization 9

xiii

2.1.3 SMEs and Globalization 11

2.1.4 Internationalization of Firms 13

2.1.5 SMEs Exporting 15

2.1.6 SMEs and Pakistan 16

2.1.7 Entrepreneurship in Pakistan 17

2.1.8 Five World Economies 20

2.2 Research Methodology

2.2.1 Introduction 20

2.2.2 Research Analytics 20

2.2.3 Comparing Statistics and DM 21

2.2.4 The Old and New Data Paradigms 22

2.2.5 Inductive Reasoning Methodology 23

2.2.6 Hypothesis-Driven Analysis 24

2.2.7 Data-Driven Discovery Paradigm 24

2.2.8 The Symbiosis of Statistics and DM 25

2.3 Analytical Methods Overview 27

2.3.1 Parametric Statistics 27

2.3.1.1 χ2 Test of Independence 27

2.3.1.2 ANOVA 28

2.3.2 Nonparametric Tests 29

2.3.2.1 Mann-Whitney Test 29

2.3.2.2 Kruskal Wallis (K-W) Test 29

2.3.3 Categorical Data Analysis 30

2.3.3.1 Binary Logistic Regression 30

2.3.3.2 Categorical Regression 31

2.3.4 Machine Learning Techniques 31

2.3.4.1 Decision Trees 32

2.3.4.2 Support Vector Machines 33

2.3.4.3 Principal Component Analysis 33

2.3.4.4 Clustering Techniques 34

2.3.4.5 Performance Measures 35

xiv

2.4 Data Pools and Filters 36

2.4.1 World Development Indicators 36

2.4.2 Globalization Indicators 37

2.4.3 Doing Business Indicators 38

2.4.4 GEM Entrepreneurial Indicators 39

2.4.5 Enterprise Survey Indicators

2.4.5.1 SMEs Obstacles 40

2.4.5.2 Trade Parameters 41

2.4.5.3 Innovation/Technology Parameters 42

2.5 Choosing a Statistical Processor 42

2.6 Research Issues and Ensuing Chapters 43

3 Manufacturing Exports and World Economies 45

3.1 Manufacturing Exports Share 48

3.1.1 Exports Share Levels 51

3.1.2 Statistical Significance Tests 52

3.2 Manufacturing Exports per Capita 54


3.2.2 Share of Manufacturing Exports per Capita 59

3.3 Inter and Intra Economy Block Exports 59

3.3.1 Establishing Statistical Significance 61

3.3.2 Exporting Intensity Ratio 64

3.4 Value added Manufacturing and GDP 66

3.4.1 Levels of VAM Contribution to GDP 67

3.4.2 Dynamics of VAM Contribution Levels 69


xv

3.5 Manufacturing Exports & GDP 73

3.5.1 Testing Statistical Significance 77

3.5.2 Dynamics of Manufactures Exports 80

3.6 GDP Correlation with Manufacturing Exports 83

3.7 Globalization and World Economies 87

3.7.1 Exploring Globalization Parameters 88

3.7.2 Kruskal-Walis Pairwise Tests 91

3.7.3 Globalization and Manufacturing Exports 92

3.7.4 Predictive Modeling 92

3.7.5 Dealing with Multicollinearity 95

3.7.6 z-Transformations & MLR Modeling 98

3.7.7 Residual Analysis 99

3.8 Chapter Summary 102

4 Internationalization and

Enterprises around the Globe 106

4.1 International Orientation in Economy Blocks 107

4.1.1 Exporting Intensity 111

4.1.2 Technology Scales 114

4.1.3 Manufacturing and Exporting 116

4.1.4 Manufacturing and Technology Scales 120

4.2 Internationalization and World Economies 122

4.2.1 IO and Technology Scales 124

4.2.2 Manufacturing Enterprises 126

4.2.3 Manufacturing and Exports 128

4.2.4 Nonparametric Tests 132

4.3 Entrepreneurial Climate 134

4.3.1 Business Parameters 135

4.3.2 Importing and Exporting 136

xvi

4.3.3 Taxation 138

4.3.4 Contracting and Legal Aspects 140

4.3.5 Entrepreneurial Climate (EC) and K-W Tests 141

4.4 Pathology of Enterprises 145

4.4.1 Obstacles in Entrepreneurship 145

4.4.2 Economy specific Obstacles 147

4.4.3 Internationalization and Obstacles 150

4.5 Trading Practices 154

4.5.1 Economy specific Trade Practices 155

4.5.2 Internationalization and Trade Practices 159

4.6 Innovation and Technology 162

4.6.1 Economy specific Parameters 164

4.6.2 Internationalization and Innovation 166


5 Internationalizing SMEs in Pakistan

5.1 Pakistan and Asian Economies 178

5.1.1 SMEs and Selected Asian Economies 179

5.1.2 SMEs and Manufacturing Sector 180

5.1.3 Exporting Trends 183

5.1.4 Analysis of Export Indicators 186

5.1.5 Entrepreneurial Climate 189

5.2 Analyzing Enterprises in Pakistan

5.2.1 Import/Export Scenario 191

5.2.2 Pathology of Enterprises 192

5.2.2.1 Statistical Analysis 195

5.2.2.2 Causality Analysis: Electricity

And Corruption 197

5.2.3 Innovation in SMEs 198

5.2.3.1 Innovation and Enterprise Sectors 200

5.2.3.2 Significant of Innovation Parameters 202

5.2.4 Trading Practices 204

5.2.4.1 Sales in Domestic Markets 204

xvii

5.2.4.2 Sales through Exporting 205

5.2.4.3 K-W Tests of Significance 207

5.2.4.4 Direct Exporting Correlation 207

5.2.4.5 Supervised Learning Approach 209

5.2.4.6 Enterprise Comparisons 210

5.2.4.7 Enterprise Clustering 212

5.3 Characterizing Exporting SMEs 215

5.3.1 Pilot Study 215

5.3.2 Reducing Dimensionality 216

5.3.3 Association Analysis: Two-way Table 218

5.3.4 Association Analysis: Three-way Tables 219

5.3.5 BLR Analysis 222

5.3.6 CR Analysis 224

5.3.7 CR Outputs Adequacy 226

5.3.8 Supervised Learning Methodologies 228

5.3.9 Analyzing DM-based Solutions 232


6 Research Findings and Recommendations

6.1 Research Findings 244

6.1.1 Manufacturing Exports in World Economies 245

6.1.2 GEM Databases 247

6.1.3 Entrepreneurial Climate 249

6.1.4 IFC’s ES Indicators 249

6.1.5 Enterprises in Pakistan 251

6.1.6 Concluding Remarks 254

6.2 Recommendations

6.2.1 Time Series Analysis 256

6.2.2 Evolutionary Classification 256

6.2.3 Rough Set Theory 257

6.2.4 Graphical Taxonomy 258

6.2.5 ABM and SMEs 258

xviii

6.2.6 GEDI Ranking and SMEs 259

6.2.7 Special SMEs 259

6.2.8 Extending Scope of ES Indicators 260

References 261

Appendices

A0 Globalization Parameters and Manufacturing Exports 274

A Appendix A – GEM Data Mining 281

B Doing Business attributes 287

C IFC Enterprise Survey: Obstacles Dataset 292

D Data Mining Streams for Internationalization & Obstacles 294

E IFC Enterprise Survey: Trading Practices 297

F Data Mining Streams for Internationalization &

Trading Parameters 302

H MSME, SMEs and Pakistan’s Databases 305

I Outputs of Stepwise Categorical Regression 315

J MSMEs Databases of Seven Asian Developing Economies 318

xix

List of Figures Figure 2.1 A sample of Research articles about SMEs and

Entrepreneurship till 2010 19

Figure 2.2 A Schematic Framework based on Platonic Idealism

for Knowledge Discovery using Logic and Mathematics 25 Figure 2.3 A Schematic Framework for Symbiosis of Hypothesis-Driven and Discovery-Driven Research reinforcing inductive reasoning approach 26 Figure 3.1 Exporting Patterns of five classes of Exports in World five Economies. 46 Figure 3.2 Share of Manufacturing Exports (%) of World Economies 49 Figure 3.3 Levels of Manufacturing Export Share (%) among

World Economies 51

Figure 3.4 K-W Rank Test of Manufacturing Export Share for World Economies 53 Figure 3.5 Difference Network Chart of World Manufacturing Export Share 53

Figure 3.6 Distribution of Manufacturing Exports per Capita for Five

Economies over 2006-2009 period 56

Figure 3.7 Difference network chart showing ranks of Economies

related to manufacturing exports per share 58

Figure 3.8 Share of Manufacturing Exports per Capita over 2006-2009 period 59

Figure 3.9 Box Plot for Inter and Intra Economy Manufacturing Exports 62

Figure 3.10 K-W Test Statistics For Inter and Intra Economy

Block Manufacturing Exports 62

Figure 3.11 Distance Network Chart showing Ranks of Inter and

Intra Economy block Manufacturing Exports 63

Figure 3.12 Distribution of Exporting Intensity Ratio For

World Five Economies 65

Figure 3.13 Value added Manufacturing (VAM) contribution to GDP at

Low, Moderate and High Levels 66

Figure 3.14 Levels of VAM Contribution to GDP in World Economies 67

xx

Figure 3.15 Distribution of levels of VAM Contribution to GDP in World 68

Figure 3.16 Levels of VAM Contribution to GDP over 2006-2009 periods 70

Figure 3.17 Difference Network Chart for VAM Contribution to GDP 73 Figure 3.18 Levels of Manufacturing Export Intensity

across World Five Economies 77

Figure 3.19 Difference Network Chart showing Ranks and Significant

Relationships for Manufacturing Export Contribution to GDP 80

Figure 3.20 Distribution of Manufacturing Exports Contribution to GDP across

World Economies over the Years 2006-2009 81

Figure 3.21(a) The K-W Test statistics for Manufacturing Export (as % of GDP)

over the period 2006-2009 82

Figure 3.21(b) The K-W Test results affirming that Manufacturing Export

(as % of GDP) over the period 2006-2009 is statistically similar 82

Figure 3.22 Scatter Plot of World Shares of Manufacturing Exports and

GDP for year 84

Figure 3.23 Revised Scatter Plot of World Shares of Manufacturing Exports

and GDP for year 2009 excluding USA, Germany and China 85

Figure 3.24 Boxplots of Globalization Parameters for World Economies 90

Figure 3.25 Network Difference Charts and Globalization Parameters

For World Economies 91

Figure 3.26 Distribution of Manufacturing Exports, (a) Raw data,

(b) Log-Transform 7 95

Figure 3.27 Standardized Residual Plot showing outliers on Left Tail 100

Figure 3.28 Normal P-P Plot showing the accuracy of Predictive Modeling 101

Figure 3.29 Regression Plot showing a genuine predictive modeling

for Globalization Parameters 101

Figure 4.1(a) Ranks of Economy Blocks for Weak International Orientation 109

Figure 4.1(b) Nonparametric Tests output for Weak International Orientation 109

Figure 4.2 Weak and Strong International Orientation among TEA type

Low and High Technology Manufacturing Enterprises 114

xxi

Figure 4.3 Percentage of TEA and EB type enterprises engaged in Manufacturing,

Exporting and Manufacturing Enterprises engaged in Exporting related

to Manufacture in Developing and Developed Economies 117

Figure4.4 Distribution of Low and High Technology Manufacturing Enterprises in Developing and Developed Economy blocks 120

Figure 4.5 Box Plot of Weak International Orientation of World Five Economies 122 Figure 4.6 Results of Krukal-Wallis Test to validate the Null Hypothesis

regarding Weak International Orientation of World Economies 123 Figure 4.7 Distribution of Enterprises bearing weak internationalization (WIO) 123

Figure 4.8 Distribution of Weak and Strong International Orientation in Low

and High Technology Manufacturing Enterprises of World Economies 124

Figure 4.9 Percentage of TEA and EB type Manufacturing Enterprises using

Low and High Technology in World Economies 127

Figure 4.10 Percentages of TEA and EB type Manufacturing Enterprises engaged

in Exporting using Low and High Technology in World Economies 129

Figure 4.11 Deviation of Business Entry Rate from World Averages 135 Figure 4.12 Deviation of Business Startup Cost from World Averages 135

Figure 4.13 Deviation of Export/Import Characteristics in World Economies 137

Figure 4.14 Deviation of Taxation Characteristics in World Economies 139

Figure 4.15 Deviation of Legal Aspects in World Economies 140

Figure 4.16 Frequency charts showing ranks of economies for 17 EC attributes 143

Figure 4.17 Ranking of Entrepreneurial Obstacles in Percentages across

Developing Economies 146

Figure 4.18 Territorial Map of Developing Economies f

for Critical Inhibiting Factors 149

Figure 4.19 Distribution of Impact of Obstacles on

Internationalization in LIC Economy 151


Internationalization in LMC Economy 152


xxii

Internationalization in UMC Economy 153

Figure 4.22 Distribution of Enterprises engaged in

trade related activities in Developing Economies 155

Figure 4.23 Territorial Map for Three economies with regard to significant

Export related activities (1=LIC, 2=LMC, 3=UMC) 158

Figure 4.24 Territorial Map for Three economies with regard to significant

Innovation and Technology related activities

(1=LIC, 2=LMC, 3=UMC) 165

Figure 4.25 A Schematic of Data Mining Stream for Internationalization &

Innovation/Technology Policies 167

Figure 5.1 Sector wise distributions of SMEs in Eight Asian Economies 181

Figure 5.2 Sector wise distributions of Micro Enterprises in Four

Asian Economies 181

Figure 5.3 Micro Enterprises, SMEs and MSMEs (Millions)

in Manufacturing sector of selected Asian economies 183

Figure 5.4 Domestic Sales as % of Total Sales in seven Asian economies 184

Figure 5.5 Ratio of Export and Domestic Sales in seven Asian economies 185

Figure 5.6 Exporting Characteristics of seven Asian economies 185

Figure 5.7 Entrepreneurial Climate in Pakistan and other Top Economies in Asia 190

Figure 5.8.Exports and imports from Engineering sector as a % of total exports

and imports, (EDB, 2009) 191

Figure 5.9.Total Export/Imports Ratio vs Engineering Sector Exports/ Imports

Ratio (EDB, 2009) 192

Figure 5.10 Average Severity Perception of Problems by Enterprise

Owners in Pakistan 193

Figure 5.11 Electricity vs Corruption perception among Nine Enterprise Sectors 194

Figure 5.12 Summary Distribution of Enterprises with regard to Six Obstacles 195

Figure 5.13 K-W Test to ascertain that Obstacles are affecting Enterprises

with different severity 196

Figure 5.14 Difference Network Chart with average sample ranks of obstacles 196

xxiii

Figure 5.15 Severity Levels of Corruption and Electricity Shortage:

Biplot Correspondence Map 198

Figure 5.16 Innovation and Enterprise Sectors of Pakistan 199

Figure 5.17 (a) Kruskal Wallis Test ascertaining that Enterprise size

is significant to effect Innovation activities 200

Figure 5.17 (b) Pairwise Comparison and difference network chart 200

Figure 5.18 Summary Statistics (Boxplot) of Innovation Related 202

Figure 5.19 Kruskal-Wallis Test for Significant Innovation Related Parameters 202

Figure 5.20 Average Sample Ranks of Innovation Related Parameters 203

Figure 5.21 Comparison of Acquisition of Technology License in and around 203

Figure 5.22 Strong positive correlation between Domestic Sales &

Domestic Inputs 205

Figure 5.23 Domestic and Export Sales in nine Sectors of

Enterprises in Pakistan 206

Figure 5.24 K-W Test for Trade Characteristics of Large, Exporter

and Foreign type 207

Figure 5.25 K-W Test for Trade Characteristics of Small, Non-Exporter,

Domestic, Manufacturing and Service type enterprises 207

Figure 5.26 Correlation graphs between Exporting Firms and Export 208

Figure 5.27 A data mining stream for predictive modeling of

Sales through direct Exports 209

Figure 5.28 Importance of Trade Related Parameters and

Categories of Enterprises 210

Figure 5.29 Segmentation of Enterprises using Hierarchical

Cluster Analysis (HCA) 212

Figure 5.30 Graphical Output for Cluster Formation using K-Means. 214

Figure 5.31 Conditional Associations between XPT and XREG 220

Figure 5.32 Step wise procedure of Categorical Regression model 225

xxiv

Figure 5.33 Variation of Adj-R2 and Prediction Error in Categorical

Regression Model Development 227

Figure 5.34 Distribution of Variance Inflation Factor in Categorical

Regression Model Development 227

Figure 5.35 Distribution of Importance of Predictor Variables

during Categorical Regression Model Development 228

Figure 5.36 A Data Mining Stream for Modeling Export Behavior of SMEs 229

Figure 5.37 ROC Curve of Machine-Learning based Models for

SMEs Exporting. 231

Figure 5.38 Rule Sets For Classifying Exporting and Non-Exporting SMEs 234

Figure A0-1 Globalization Score and Manufacturing Exports in

Five Economies 275

Figure A0-2 Global Enabling Trade Index & Manufacturing Exports in

Five Economies 276

Figure A0-3 Logistic Performance Index & Manufacturing Exports in

Five Economies 277

Figure A0-4 Networked Readiness Index & Manufacturing Exports in

Five Economies 278

Figure A0-5 Inward Foreign Direct Investment and Manufacturing Exports

in Five Economies 279

Figure A0-6 Global Competitiveness Index and Manufacturing Exports in

Five Economies 280

Figure D4.1 Data Mining Streams for Internationalization

& Obstacles in LIC Countries 294


& Obstacles in LMC Countries 295


& Obstacles in UMC Countries 296

Figure F4.1 Data Mining Stream for Internationalization

& Trade Policies in LIC Countries 302


& Trade Policies in LMC Countries 302

xxv


& Trade Policies in UMC Countries 303

Figure-H.5.6.2 Entrepreneur’s Perception about Second Most

Serious Obstacle with Electricity Shortage as Prime Obstacle 312

Figure-H.5.6.3Entrepreneur’s Perception about Second Most Serious

Obstacle with Corruption as Prime Obstacle 312

Figure-H.5.6.4 Correspondences of Levels of Severity between

Corruption and Electricity Shortage 313

Figure H5.7(A): Foreign Sales and Inputs as Percent of Domestic Sales 314

xxvi

List of Tables Table 2.1 Jobs Creation Capacity of SMEs 9 Table 2.2 Manufacturing Exports as % of Total Exports in selected Countries 16 Table 2.3 Basic Indictors and Filters for Global Manufacturing Exports 36 Table 2.4 Derived Indicators for Global Manufacturing along with Source Filters from World Bank Data 37 Table 2.5 Globalization Parameters and Data Sources 37 Table 2.6 Indicators of Doing Business along with Filters [83] 38 Table 2.7 Basic Indicators for Entrepreneurial firms engaged in

Manufacturing and Exporting [84]. 39 Table 2.8 Derivation of Indicators pertaining to Manufacturing and Exporting of Enterprises in GEM data pool. 40 Table 2.9 Obstacles in promoting the cause of Entrepreneurship [85] 41 Table 2.10 Attributes related to Trade Practices [85] 42 Table 2.11 Attributes related to innovation/technology parameter in Enterprise Survey [85] 42 Table 3.1 Average Manufacturing Exports 48

Table 3.2 Manufacturing Exports Share of Top 10 countries in the World 50

Table 3.3 Manufacturing Exports share of lowest 9 countries in the World 50

Table 3.4 Tests of Independence between Manufacturing Export

Share Level and Type of Economy 52

Table 3.5 Manufacturing Exports per capita: Top 10 Countries 54

Table 3.6 Manufacturing Exports per capita: Lowest 10 Countries 55

Table 3.8 Grand Average of Manufacturing Exports per Capita for

Five Economies 57

Table 3.9 Inter and Intra Economy Manufacturing Exports for year 2006-2009 60

Table 3.10 Pearson Correlation between Manufacturing Exports and

Economy Block 61

Table 3.11 K-W Tests of VAM Contribution to GDP for

Pairwise Comparison of Economies 72

xxvii

Table 3.12 Distribution of Levels of Manufacturing Export

Contribution Intensity to GDP 74

Table 3.13 Mean aggregate values of Manufacturing Export (as % of GDP) 77

Table 3.14 ANOVA Test Results for the Significance of Contribution 78

Table 3.15 K-W Tests of Manufacturing Exports Contribution to

GDP for Pairwise 79

Table 3.16 Year Wise Mean values of Manufacturing Export (as % of GDP) 80

Table 3.17 List of Top 50 Countries with GDP Share along with

Share of Manufacturing Exports 83

Table 3.18 Linear Regression Model Parameters for World

Shares of Manufacturing Exports and GDP among Five Economies 86

Table 3.19 Statistical Characteristics of Globalization Parameters in

World Economies 89

Table 3.20 Correlation between Manufacturing Exports and Globalization

Parameters 93

Table 3.21 Features of Regression Models for Globalization Parameters 93

Table 3.22 Correlation Matrix for Globalization Parameters 95

Table 3.23 Correlation of z-Transform of Globalization Parameters 96

Table 3.24 Factor Analysis outputs: (a) Anti-image correlations,

(b) Sphericity Test output 96

Table 3.25 Variance Distribution of Component Loadings in PCA 97

Table 3.26 Loading of Globalization Parameters on Components 97

Table 3.27 Statistical Outputs From ANOVA 99

Table 3.28 3-Sigma Outlier Countries in Globalization Studies 100

Table 4.1 Statistical Significance of Strong International Orientation

among TEA type Enterprises in Developing and Developed

Economy blocks on yearly basis. 110

Table 4.2 Distribution of Intensive International Orientation of Economy

Blocks 111

xxviii

Table 4.3 Statistical significance of export intensity of TEA type enterprises in

Developing and Developed economy blocks on yearly basis. 112

Table 4.4 Statistical significance of export intensity of EB type enterprises in

Developing and Developed economy blocks on yearly basis. 113

Table 4.6 Mean Sample Ranks of World Economies and Kruskal-Wallis Test 132

Table 4.7 Kruskal Wallis Tests for Average Sample Ranks of

Entrepreneurial Parameters of World Economies 142

Table 4.8 Relative Frequency for rankings in EC attributes of five

world economies 144

Table 4.9 Entrepreneurial Climate Index For World Economies 144

Table 4.10 ANOVA Tests on Obstacles in Three Developing Economies 147

Table 4.11 Structure Matrix for Inhibiting Factors (Obstacles)

for Developing Economies 148

Table 4.12 Models for Investigating Impact of Obstacles on Internationalization

of an Economy 150

Table 4.13 Average Sample Ranks of economies with Chi-Square

Significance Tests 156

Table 4.14 Tests of Equality of Group Means For Trading Practices 157

Table 4.15 Structure Matrix showing Correlations between discriminating variables

and Discriminant functions F1 and F2 157

Table 4.16 Significant Correlations between Trading parameters and

Exporting Levels 159

Table 4.17 Predictor Models for Exporting Level relative to Trading Parameters 160

Table 4.18 Significant Trading parameters and Data Mining methodologies 161

Table 4.19 Group statistics related to Technology parameters in three

developing economies 163

Table 4.20 Group means test for significance of technology related parameters 164

Table 4.21 Structure matrix for Technology related parameters in

Developing Economies 164

Table 4.22 Significant Correlations between Innovation parameters

and Exporting Levels 166

xxix

Table 4.23 Predictor Models for Exporting Level relative to Trading Parameters 167

Table 4.24 Significant Innovation parameters and Data Mining methodologies 168 Table 5.1 A Two-way Difference Test for Pakistan and Top Economies in Pakistan 178 Table 5.2 Manufacturing Export Leverage of j

th Country over Pakistan 179

Table 5.3 The cluster centers for export characteristics, (a) Initial Cluster,

(b) Final Cluster 187 Table 5.4 Allocation of seven Asian economies to Two clusters 187 Table 5.5 Kruskal Wallis Test output for testing the significance of exporting

characteristics. 188

Table 5.6 A Two-way Difference Test for Pakistan and Top Economies

in Pakistan 189 Table 5.7 Data on Obstacles in nine enterprises of Pakistan 192 Table 5.8 Chi-Square Test of Independence between Corruption and

Electricity Shortage 197

Table 5.9 Significance Test and Distribution of Inertia (Variance) 197 Table 5.10 Innovation Related Parameters in Nine Enterprise Sectors of Pakistan 199 Table 5.11 Innovation related nonparametric Tests for Four Categories of Enterprises 201 Table 5.11 Trade Parameters across nine sectors of Enterprises in Pakistan 204 Table 5.12 Significant Correlations between Direct Sales Exports and input Factors 208 Table 5.13 Adequacy of Supervised Learning algorithms for Modeling Sales

through Direct Exports 208 Table 5.14 Importance of Trade Related Predictor Variables when

target variable is Sales through direct export 209 Table 5.15 K-W Tests for Pairwise Comparison of Enterprises for Trade related attributes 211 Table 5.16 Segmentation of Enterprises using K-Means Analysis 212 Table 5.17 Anti-image Correlation Matrix 215

Table 5.18 MO and Bartlett's Test 215

xxx

Table 5.18 Extraction Sum of Squared Loadings on Three Components 214 Table 5.19 Rotated Component Matrix

215

Table 5.20 Logistic Regression for Sub Problems using H&L Criteria 218

Table 5.21 Testing the Adequacy of Machine Learning Algorithms 226

Table 5.22 Results of applying All- variant Machine Learning

Algorithms approach 227

Table 5.23 Influencing Effect of Predictor Variables on target variable XPT 228

Table 5.24 Comparison of Classification Accuracy Level of Methodologies 229

Table A4.1 Strong and Weak International Orientation and Technology Scales 281

Table A4.2 % of TEA and EB Type Enterprises engaged in Manufacturing,

Exporting and Exporting related to Manufacture 282

Table A4.3 Percentage of Low and High Tech Manufacturing Enterprises

In Developing and Developed Economy blocks 283

Table A4.4 Weak and Strong Levels of International Orientation in Low

Technology and High Technology Enterprises 284

Table A4.4 Distribution of Manufacturing Enterprises of TEA and EB type

Engaged in Exporting in World Economies 285

Table A4.6 Percentage of TEA and EB type Enterprises engaged in Low

And High Technology Manufacturing in World Economies 286

Table B4.1 Business Entry Rate (% of Total Enterprises) 287

Table B4.2 Cost of Business Start-Up Procedures (% of GNI per Capita) 287

Table B4.3 Cost to Export (US $ per Container) 287

Table B4.4 Cost to Import (US$ per Container) 287

Table B4.5 Average Number of Export Documents 288

Table B4.5 Average Number of Import Documents 288

Table B4.7 Average Lead Time to Exports (Days) 288

Table B4.8 Average Lead Time to Import (Days) 289

xxxi

Table B4.9 Average Number of Tax Returns 289

Table B4.10 Total Tax Rate as a percent of Profit 289

Table B4.11 Time to prepare returns and pay taxes 290

Table B4.12 Time to resolve insolvency in years 290

Table B4.13 Time to enforce a contract in days 290

Table B4.14 Average Number of Procedures to enforce a contract in days 290

Table B4.15 Strength of Legal Right Index ( 0 = weak, 10=strong) 291

Table C4.1 Percentage of Enterprises considers ith

parameter as

Biggest obstacle 292

Table H5.1 Distribution of Large Scale and SMEs in seven economies

Of Asia 304

Table H5.2 MSME sizes, Distribution, Density and Employment in Nine

Economies of Asia 305

Table H5.3 (a) Sector wise SMEs Density in Eight Asian Economies 306

Table H5.3 (b) Sector wise Micro Enterprise Density in Four Asian Economies 306

Table H5.4 Distribution of Micro Enterprises and SMEs (in Millions) in

Prominent Asian Economies 307

Table H5.5 (a) Home market Sales Features in seven Asian Economies 308

Table H5.5 (b) Exporting Features of seven Asian Economies 309

Table H5.6 Doing Business Indicators for Nine Economies of Asia 310

Table H5.7 (A) Foreign Sales and Inputs as percent of Domestic Sales 311

Table H5.7 (B) ANOVA tests for Foreign Sales and Inputs as percentage

of Domestic Sales 315

1

Chapter 1

Introduction

1.1 Globalization

Globalization is a process that connotes the ever increasing interdependence and closer

integration of national economies. From social perspective, it is the instant interaction of

people and societies in the background of virtual world made possible through internet

and social networking. On the political front, it is more and more homogenization of

governing systems with democratization of societies. In its ideal form, globalization

process aims to remove physical and psychic barriers between nationalities and transform

the world into one country; the united states of the planet earth. However, it is the

manufacturing activity that has been profoundly affected by the globalization. Prior to

globalization era, manufacturers were trying to accomplish all their functions within the

confines of the organization. The distribution function was constrained to local and

domestic market. All that changed with the arrival of ICT inspired technologies coupled

with loosening of restrictions on trade. Manufacturing strategies drastically changed by

relocating production facilities near to emerging markets. Manufacturing enterprises are

now executing core competency tasks in-house, and awarding the support tasks to the

efficient vendors around the globe in terms of cost, quality and competency. This

globalization of production and distribution functions is manifested by the huge trade

volumes between economies.

1.2 Large Scale Manufacturing

Since the start of manufacturing as a segment of economy to create wealth of a nation,

large scale production organizations have been in the lime light. This large size factor has

been important because of mass production capability facilitating all important

2

economies of scale. The large size of manufacturing organizations has been a competitive

advantage by default. The huge resource base of these organization equip them to indulge

in strategic management, securing consultancy services, carry out market intelligence,

launch R&D activities and execute logistic operations. The large structure has drawbacks

also. The responsiveness to adapt to a changing environment is slow and often lethargic.

The lengthy administrative channels make these organizations highly inflexible.

Entrepreneurial spirit dies down as the age of the organization prolongs. The biggest

question on the viability of the large organizations is their inability to create new jobs

over a period of time. During last thirty years or so, size factor of an organization has

been critically reviewed and small size firms have been successful to attract the attention

of academia because of astounding success of these organizations. Microsoft Corporation

and Dell Computers are one of those glaring examples that have turned the world.

1.3 Small Firms

Is small size a stigma for an organization? The answer is dependent on the mindset of the

owner. If owner has entrepreneurial mindset, there are few solid arguments in favor of

being a small size firm. Small size firms have highly coherent structure like a spider-web

enabling the organization to react and adapt to the changing environment. The instant

responsiveness capability of these organizations makes them ideal for customized

solutions. These organizations are highly flexible because of the absence of non-

bureaucratic working.

Small firms have traditionally survived in ‘isolation’ prior to the emergence of internet

enabled e-commerce and e-business era. These firms were operating in restricted business

sphere often confined to their home markets. The protections implanted by national

governments created an environment of safe home markets where routine and

standardized products were offered in a low intensity competitive backdrop. However, all

that has changed drastically during the start of second decade of 21st century.

Protectionism has been replaced by liberalism where every organization views the entire

3

world as one market. Reaching unexplored markets with competitive advantage is a

thorny challenge to every enterprise be it a large or small. However, this challenge is

particularly daunting for small enterprises in developing economies where the firms have

acutely feeble resources with scant support from their governments and live under the

fear of extinction every day.

1.4 Research Theme

The research work is aimed at exploring and discovering the patterns of economy-centric

manufacturing activity in small and medium enterprises (SMEs) of developing economic

block through a symbiosis of techniques from Database Management, Data visualization,

Statistics, Machine Learning and Data Mining. In the process, exploration of parameters

influencing manufacturing exports is pursued at global level. The work has been carried

out with a commitment to shed light on the manufacturing affairs in least developed

countries as these economies are largely untouched by research community in the

developed world. Whereas, research on manufacturing activity is highly documented in

OECD countries, a selective and narrow approach is followed by research community in

developing economies. This work aims to bring in spotlight the state of manufacturing

activity in developing economies in an exhaustive manner and contrast it with

manufacturing activity in developed economy block. The economic dividend of

manufacturing activity accruing from exporting levels is the prime target and occupies

the central place in this research.

Three levels of exploring manufacturing activity are specified for research purpose. At

the top and global level, the economic impact of manufacturing activity is viewed from

the perspective of developed and developing economy blocks. At the intermediate level,

enterprises are explored segmenting these firms among developed and developing

economy blocks. At the lowest level, enterprises are explored at country level. For the

purpose of this research, Pakistan is picked up for exploration.

4

1.5 Aims and Objectives of Research

The aim of this research is to explore the impact of manufacturing export activity on

small and medium enterprises in the developing economies. There are a number of vistas

to be addressed in this research work. What is the state of affairs related to manufacturing

activity in developing economies? How is developing economy block performing in

comparison to developed economy block with regard to manufacturing? Is manufacturing

activity beneficial and a ray of hope for creating wealth in developing economies? How

manufacturing export is helping to enhance the economy of developing economy

countries? Is there any space left by the developed economy block for the developing

economy block to reap fruits of development? How is globalization influencing the

manufacturing in developing and developed economy blocks?

At second stage, research focus is on manufacturing enterprises in developed and

developing economies. In particular, what is the pattern of manufacturing activities in

born global and established businesses in developed and developing economies? How

entrepreneurial activity with regard to manufacturing is distributed along the two types of

economy blocks? What is the pattern of exporting activities of the young and old

enterprises in the two blocks of economies? What are the attributes of enterprises that

influence the exporting capability of these economies? How pathology of enterprises in

developing economy hamper the exporting efforts? What is innovation and trade related

parameters and how do these help to enhance manufacturing exports in developing

economies?

At third stage, enterprises in Pakistan are explored. What are the severe obstacles

impeding enterprises in Pakistan? What are critical parameters related to obstacles,

innovation and trade in Pakistan? How entrepreneurial climate compares with

neighboring countries of Pakistan? What are contrast and similarities in nine enterprise

5

sectors? What are enterprise and entrepreneurial parameters that influence exporting

stature of a Pakistani SME?

Novelty of the intended research is to investigate and thus find the significance of

manufacturing exports on the economic growth of developed as well as developing

countries in the global context. In particular, the role of SMEs is probed by integrating

global databases in a cohesive manner from repositories of World Bank, GEM and IFC.

The investigations are conducted by grouping SMEs according to their significance in

world five economies. A myriad of inhibiting and enabling attributes of these SMEs are

selected for exploration. Causal linkages are established between SMEs propensity for

manufacturing exports and a host of factors surrounding SMEs. These include trade

patterns, scale of technology levels, entrepreneurial climate and ICT practices. Major

portion of this detailed analysis pertains to SMEs in the three developing economies that

include lower income, lower and upper middle income countries. Finally, strenuous

efforts are expended for analyzing exporting propensity of SMEs in Pakistan. The

research efforts are unique with an aim to enhance the potential of competitiveness of

Pakistani SMEs on global horizon.

Data mining has been conventionally employed in exploring databases aiming at business

intelligence and fraud detection. This is the first attempt to apply the concepts embedded

in data mining and machine learning techniques for modeling and analysis of

internationalizing SMEs in global context. In particular, the specificity of economy

blocks has been modeled and analyzed by a combination of supervised and unsupervised

learning techniques. Symbiosis of statistical inferential techniques and data mining

methodology is the prime characteristics of this work in exploring world databases to

discover patterns and structures in internationalizing SMEs of developing economy block

in global context.

6

1.6 Thesis Organization

This chapter introduces the research topic and allied intended objectives in brief. Chapter

2 provides an expanded literature review on SMEs. The chapter also includes impact of

globalization on SMEs and internationalization through exporting. An inductive

reasoning methodology based on a hybrid of techniques from Statistics and Machine

Learning is devised combining hypothesis and data-driven analysis. The chapter also lists

down the main global databases to be used as prime source. The pertinent filters are

indicated to extract reduced data set for pattern identification. In Chapter 3, the World-

Bank data set is explored and reduced data set is formed by applying relevant filters from

Chapter 2. The patterns of manufacturing and manufacturing-exports are identified using

data visualization and correlation techniques. The parametric and nonparametric

multinomial techniques are used to test the adequacy of relationships with regard to

manufacturing between developing and developed countries. Globalization parameters

are tested for veracity in the context of developing and developed economy.

In Chapter 4, the internationalization aspirations of manufacturing enterprises in

developing and developed economies are explored through extensive Data visualizations

and attested by confirmatory hypothesis. The classification of born-global and established

enterprises is investigated to seek knowledge about manufacturing and international

orientation. The specificity of attributes related to a particular economy blocks are

explored. Both supervised and unsupervised learning algorithms are applied to

investigate the adequacy of parameters in the context of manufacturing exports.

Chapter 5 is about role of SMEs in Pakistan to enhance the manufacturing led exports.

Pakistan being one of the most populous countries has sizable manufacturing SME

sector. However, these SMEs target domestic markets for acquiring input resources and

7

sales of their produce. The issues related to SME’s operating hindrances are probed by

combining the statistical and knowledge discovery techniques. The emphasis is on

explanatory and exploratory search to extract knowledge in totality.

Chapter 6 contains main findings related to patterns visualized in reduced data sets

obtained through mining global databases. The results of efforts expended in pattern

evaluation by formulating and testing hypothesis are summarized. The adequacy and

future applications of applying data mining approach to the realm of manufacturing as an

engine of economic growth are proposed.

The appendices accommodate a large number of reduced data sets particularly useful for

future research in manufacturing data mining integrally coupled with economy. A special

section in the end provides a detailed account of SMEs and micro enterprises (MEs) in

prominent economies of Asia.