Table 1: Variable Selection and Classification ............................................................................................................. 4

Table 2: Means of Variables ........................................................................................................................................ 6

INDIAN

INFRASTRUCTURE

FIRMS A Strategic Group Analysis

ABSTRACT The objective of this paper is to identify the possible

strategic groups that exist within the Indian

infrastructure industry by using statistical cluster

analysis techniques. Three clusters have been identified

with significant differences between the performances

of firms in each cluster. Findings of strategic group

analysis can be used to understand the current

strategic position of a firm within the competitive

environment and formulate strategies to shift to a

better performing cluster.

Group 3, Section B Strategic Management

BATCH 2014-16

1 | P a g e

Contents Introduction ................................................................................................................................................................. 2

Literature Review ......................................................................................................................................................... 2

Methodology ............................................................................................................................................................... 4

Research Findings ........................................................................................................................................................ 5

Means of Variables of each cluster .......................................................................................................................... 6

CLUSTER ANALYSIS ....................................................................................................................................................... 6

Cluster 1- Toddler Closet ......................................................................................................................................... 6

Cluster 2- ‘I’m-all-right-Jack’ .................................................................................................................................... 7

Cluster 3- Big Daddies .............................................................................................................................................. 7

CONLCUSION ............................................................................................................................................................... 8

REFERENCES ................................................................................................................................................................. 8

EXHIBITS …….. .. ………………………………………………………………………….………………………………….………………………………….11

List of Tables Table 1: Variable Selection and Classification ............................................................................................................. 4

Table 2: Means of Variables ........................................................................................................................................ 6

2 | P a g e

Introduction All firms need to have a clear strategic perspective to achieve competitive advantage. The selected strategies should remain in accordance with objectives, competencies, and competitive rules prevailing in the market. It is clear that a number of companies that compete in the same industry may have similar resources/competencies and develop similar strategic perspectives. The question is whether these companies show similar performance or not. This project attempts to address the questions about the clustering of firms by conducting a strategic group

analysis of a set of firms from the infrastructure industry in India. This paper analyzes a set of fifty firms from

the Indian infrastructure industry and finds evidence of the existence of strategic groups, each underlying a

distinct competitive strategy. Two important characteristics of the Indian infrastructure industry is that

infrastructure is highly responsible for propelling India’s overall development. Also, India's enormous unmet

infrastructure needs, combined with the public private partnership approach, offer an unprecedented

investment opportunity for the private players. The government estimates that $1 trillion of investments will

be required for developing India's infrastructure in the 12th plan period. Therefore, there seems to be a high

demand for services and products offered by infrastructure companies.

The report reviews the relevant literature on the competitive strategies and strategic groups with a specific

focus on infrastructure firms. It is followed by a description of the infrastructure industry in India and its

appropriateness as a research setting for the study of the different strategies of firms. A section on

methodology then outlines the research method of strategic group analysis, the sample and data collection

and selection of strategic variables. We then report the results and through an in-depth analysis of

representative firms of the strategic groups and assimilate the information to theorize the concept.

Literature Review The basic premise of strategic groups is in fact that performance can be attributed to strategic groups and

not only to the idiosyncratic character of the individual firm. Hunt (1972), who was the first to formulate this

concept, observed significant differences in the strategies followed by firms in the U.S. home appliance

industry, even though many of them were pursuing similar strategies. Business combinations can therefore

facilitate the identification of different types of generic strategies followed. Hunt therefore defined a

strategic group as a group of companies within a sector, which are very similar in terms of cost structure,

degree of product diversification, formal organization, control systems and perceptions and preferences of

individuals.

Subsequently, many other definitions of strategic groups have been proposed. According to Porter (1979):

"An industry can be considered as composed of groups of firms, each group consisting of firms pursuing

similar strategies regarding key decision variables". The definition of Porter (1980) is certainly the most

commonly used: "A strategic group is a group of firms in an industry following a similar or identical strategy

regarding relevant dimensions. An industry may have a single strategic group if all firms follow essentially the

same strategy. At another extreme, each firm could be a different strategic group. However, there are

usually a small number of strategic groups, summarizing the essential strategic differences among firms in an

industry."

Mascarenhas (1989) highlights the importance of mobility barriers and argues that strategic groups may

exist only if significant mobility barriers exist between groups. Leask (2004) defines strategic groups as stable

intra-industry structures separated by mobility barriers in pursuit of different strategies that may be

expected to yield significant performance differences.

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Hatten and Hatten (1987) argue that strategic groups are more than an analytical convenience only if true

group-level effects exist. Dranove et al. (1998) state that true effects (strategic group level) and spurious

effects (industry level) should be distinguished. They argue that “a strategic group exists if the performance

of a firm in the group is a function of group characteristics.” McNamara et al. (2003) argue that rivalry rather

than collusion may also exist within strategic groups.

Porter (1980) defines strategic group analysis as the first step in structural analysis of industries to

understand the strategies of all significant competitors. It is used to determine the different strategic

positions that rival firms occupy, intensity of competitive rivalry within and between industry groups, the

profit potential of the various strategic groups in an industry, and implications for the competitive position of

the firm under analysis.

Two research streams studied largely independently the strategic group concept, the first being derived

specifically from the industrial economy and the second from the cognitive approach to strategy. These two

approaches could be reconciled in order to achieve more conclusive results regarding the link between

strategic group and performance.

There is no universally accepted technique for carrying out strategic group analysis. The most common

method for identifying strategic group structures is through cluster analysis. Major challenges of cluster

analysis are: choosing the clustering variables, algorithms, number of clusters, and validating clusters. Cluster

analysis is criticized as it relies heavily on researcher judgment and it does not offer a test statistic that

supports results (Ketchen and Shook 1996).

There are a limited number of studies within construction management literature about strategic grouping

and its performance implications. Kale and Arditi (2002) argue that research on competitive positioning in

the construction industry appears to be unbalanced in favour of anecdotal or descriptive approaches. Only a

few construction management researchers (such as Jennings and Betts 1996) have conducted empirical

research studies in this area and explored performance implications (Akintoye and Skitmore 1991; El-

Mashaleh et al. 2006; Hampson and Tatum 1997).

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Methodology The first step entails selection of sample space. Screening of companies was done from the

Bloomberg terminal. The companies selected have a minimum market capitalisation of INR 100

crores, from the heavy construction sector registered in India.

The market capitalization, revenue, operating expenses, profit, current ratio, sales revenue in

construction sector and sales revenue in India are the data fields chosen. (see Exhibit1)

The project and client information was obtained from secondary sources. The major types of

projects included were infrastructure, buildings and factories, industrial and others. The clients are

primarily of two types, namely government and private.

Variables chosen for the cluster analysis and the parameters that measure the variables are as

under: (see Exhibit1)

Table 1: Variable Selection and Classification

Sr. No Variable Category Criteria for choosing the variable

1 Differentiation strategy:

Category 1: price differentiation Category 2: quality differentiation

Calculate profit/COGS ratio to find if the company is a price differentiator of quality differentiator

2 Diversification strategy

Category 1: only construction/construction-related sectors Category 2: diversified in sectors unrelated to construction

This measures the market-level diversification of the companies

3 Internationalization

Category 1: Internationalized Category 2: not internationalized

This measures geographical diversification

4 Type of projects

Category 1: infrastructure Category 2: Housing + building Category 3: industrial

Project type that has the highest percentage in total number of projects. Measures project diversification.

5 Type of client Category 1: government Category 2: private sector

client type that has the highest percentage in total number of projects Defines target segment of the company

6 Financial capability

Working capital ratio The decision to bid for a project will depend on whether the company has enough funds. Working capital management ensures a company has sufficient cash flow in order to meet its short-term debt obligations and operating expenses.

7 Managerial Capability

Return on capital employed for 2010 and 2014

This measure the way the available capital is put to use at the level at which strategic decision are taken.

The statistical tool used for cluster analysis is R. We use the data mining package “Rattle” of R. Each

field is Rescales using "transform" function such that the mean is 0 and standard deviation is 1.

The Name field was taken as "target". Hierarchical clustering was done with Euclidian distance and

Ward's method for agglomeration. A dendogram with 3 clusters was predefined and the cluster

data plot matrix of each factor with the other and the discriminant was plotted. This was done for

the data for the year 2014 and 2010.

5 | P a g e

The cluster wise average table of each field was drawn.

Analysis of one industry from each of the clusters was done based on our secondary research findings.

Research Findings The following results were obtained from our analysis. The analysis was carried for both 2010 and 2014. We

found that some firms migrated from one cluster to another. It indicates that some firms have overcome the

mobility barriers. This can be understood from the following plots.

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Correlation data.csv using Pearson

The correlation matrix in above figure gave the variables that were redundant. Our analysis gave satisfactory

correlations which shows that the factors are consistent with the motives they were taken – (a) are subject

to influence of top managers (b) collectively capture the strategy (c) reflects strategic choice more than

industry norms (4) allow for consistency of measurement across all firms in the sample.

Means of Variables of each cluster Table 2: Means of Variables

2010 2014

Variables Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3

Differentiation 0.67 0.12 0.15 0.13 0.03 0.13

Diversification 1.00 0.95 0.79 0.99 0.94 0.81

Internationalization 1.00 1.00 0.80 0.98 1.00 0.85

Working Capital 2.72 1.72 2.05 1.36 0.84 1.34

Type of Projects 2.58 1.00 1.67 2.61 1.07 1.48

Type of Clients 1.79 1.00 1.53 1.83 1.07 1.33

Managerial Capability 11.99 16.45 17.51 3.83 10.39 16.31

The clusters – 1, 2 & 3 formed for both the years 2010 and 2014 are listed in Exhibit2.

CLUSTER ANALYSIS

Cluster 1- Toddler Closet This cluster has firms that are non-diversified, non-internationalized, dealing with industrial and real estate

with private companies as major clients.

One company that characterizes this cluster well is Jaypee Infratech Limited. Jaypee Infratech Limited (JIL) is

a infrastructure development company engaged in the development of the Yamuna Expressway and related

real estate projects. The Yamuna Expressway is a 165-kilometre access-controlled six-lane concrete

pavement expressway along the river Yamuna, with the potential to be widened to an eight-lane

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Correlation data.csv using Pearson

7 | P a g e

expressway. The company also has the right to develop 25 million square metres (approximately 6,175 acres)

of land along the Yamuna Expressway at five locations for residential, commercial, amusement, industrial

and institutional purposes.

JIL has not yet forayed into the international arena. It remains a company dedicated to one sector of the

infrastructure domain and even to a single geographic location within the country. It is imperative to note

that the scope of the projects undertaken is limited in this group. The main projects cater to the

housing/building sector and most of the clients are private players.

This in effect is the least profitable group and constantly companies are shifting out by crossing the mobility

barriers. The mobility barriers range from huge investment to entrenched players. But increasingly,

companies are jumping across to join more profitable groups.

Cluster 2- ‘I’m-all-right-Jack’ It houses all the big domestic companies in the infrastructure industry that have yet to explore and exploit

the international market. These include firms whose clientele is mainly the government. Consequently, they

account for the large construction or construction-related projects in our country.

The company in this group that we have chosen for analysis is Gammon India Limited. Founded in the year

1922, it is India’s largest civil engineering construction company. It has executed notable projects for the

Delhi Metro Rail Corporation and boasts of an expertise in building bridges and flyovers. The main problem

with firms in this cluster is that they have become complacent and do not want to move out of their comfort

zone.

It should be noted that most companies in this strategic group have had some international exposure, but

major section of their business still focuses only on the domestic market. It is interesting to note the

movement of companies from one strategic group to another. We know that every company would like to

move into a more profitable segment by crossing the mobility barriers. In our analysis, we deduced that

cluster 3 is the most profitable and likewise, we see companies like KEC, Ashoka Buildcon, Atlanta and GPT

move from cluster 2 to 3.

The firms in this cluster have the required to resources to expand and internationalize and slowly, we’re

observing a shift towards this phenomenon.

Cluster 3- Big Daddies This group is characterized by large companies with diversified international operations dealing in various

types of projects with both private and government clients.

A good example of such a company is Larsen and Toubro. The company provides a wide range of advanced

solutions, products and services in the technology, engineering, construction and manufacturing sectors.

L&T’s businesses are supported by a wide marketing and distribution network. L&T has manufacturing

facilities in India, China, Oman and Saudi Arabia, with a global supply network in 10 locations across the

world including Houston, London, Milan, Shanghai and Seoul. The company’s customers include major

players in more than 30 countries. It operates principally in Asia, the US, the UK, Europe and the Middle East.

The company follows these below initiatives on a regular basis- Widening new geographical areas for

augmenting its exports, exploring inorganic growth opportunities for the acquisition of specialized

engineering outfits abroad and bringing in high caliber resources in the areas of front-end marketing,

engineering, project management, risk management, contract administration, etc., to strengthen the

overseas operations.

8 | P a g e

There is an increase in the number of companies in this strategic group from 2010 to 2014. This group has an

average market capitalization of around seventy billion INR. Also, from Table 2, we can see that this group

has the best average return on capital invested. Due to high profitability and greater opportunities,

companies want to join this group.

CONLCUSION Through the research and findings, we have tried to establish groupings in the Indian infrastructure industry

through a strategic group analysis. It was noted that firms belonging to one group follow a similar strategy

and are exposed to similar resources. By in-depth analysis of representative firms in each cluster, we have

identified the strategy adopted by them and this in turn could be used to gauge a comprehensive

understanding of the industry and a new entrant could choose a given cluster based on its competencies and

position itself in the market accordingly.

For the firms already established, it could serve as a review tool by which the companies could analyse their

current strategy and review it in light of the changing scenario. With globalization penetrating every sector,

it is imperative for the companies to remain on their toes and continuously evolve in order to remain

profitable. From our analysis, we have found out that firms do shift from one cluster to another as time

progresses.

The report aims to identify critical factors in the success of firms operating in the infrastructure industry.

These drivers could be further exploited and exclusively addressed to alleviate specific problems, if any.

REFERENCES 1. Dikmen, Birgonui and Budayan, 2009. Strategic Group Analysis in the Construction Industry.

2. Ravendra Chittoor and Sougata Ray, 2007. Internationalization paths of Indian pharmaceutical firms.

Journal of International Management 13 (2007) 338–355.

3. Raphaël Dornier, Noureddine Selmi and Thierry Delécolle. Strategic Groups Structure, Positioning of

the Firm and Performance: A Review of Literature. ISC Paris School of Management

doi:10.5539/ibr.v5n2p27

4. Databases used – Bloomberg

5. Web tools to learn R : Quick R Cluster analysis tutorial – www.statmethods.com ,

http://tryr.codeschool.com, https://www.coursera.org/ , http://www.r-project.org/

EXHIBITS

EXHIBIT 1 – DATA FOR CLUSTER ANALYSIS

Name Differenti

ation-2014

Differentiation-2010

Diversification - 2014

Diversification - 2010

Internationalization

- 2014

Internationalization

- 2010

Working Capital -

2014

Working Capital -

2010

Type of Project

Type of Client

Managerial Capability-

2014

Managerial Capability-

2010

LARSEN & TOUBRO 2 2 2 2 2 1 1.25 1.03 1 1 22.49 17

JAIPRAKASH ASSOC 2 2 2 2 2 2 0.75 0.61 1 1 8.61 7

GMR INFRA-SLB 2 2 1 1 1 1 0.50 0.42 1 2 0.81 2

ENGINEERS INDIA 1 2 2 2 2 2 2.57 2.12 3 1 59.16 28

IRB INFRASTRUCTU 1 1 1 1 2 2 0.97 0.80 1 1 2.63 15

JAYPEE INFRATECH 1 1 1 1 2 2 1.50 1.24 2 2 7.62 9

SKIL INFRASTRUCT 2 2 1 1 2 2 0.58 0.48 1 1 6.25 0

VA TECH WABAG LT 1 2 1 1 1 2 1.49 1.23 3 2 34.23 21

NATIONAL BUILDIN 2 2 2 1 2 2 1.37 1.13 2 2 32.70 32

KEC INTL LTD 2 2 2 1 1 2 1.03 0.85 1 1 27.12 17

GLOBUSCONSTRUCT 2 2 1 1 2 2 0.33 0.27 2 2 -5.06 1

SADBHAV ENGINEER 2 2 1 1 2 2 1.06 0.87 1 1 16.27 13

KALPATARU POWER 2 2 2 2 1 1 1.26 1.04 2 2 20.83 14

ASHOKA BUILDCON 2 2 2 1 2 2 1.03 0.85 1 1 17.60 18

HINDUSTAN CONST 2 2 1 1 1 1 1.11 0.92 1 1 9.24 12

PUNJ LLOYD LTD 2 2 2 1 1 1 1.01 0.84 1 1 9.19 12

NCC LTD 2 2 2 1 1 2 1.15 0.95 1 1 9.71 16

GAMMON INFRA 2 2 1 1 2 2 0.47 0.38 1 1 1.87 8

KOLTE-PATIL 1 1 1 2 2 1 2.40 1.98 2 2 8.53 5

ITD CEMENTATION 2 2 1 1 2 2 1.04 0.86 1 1 11.57 14

SRS REAL INFRA 2 2 1 1 2 2 1.64 1.36 2 2 7.20 5

DREDGING CORP 2 2 1 1 2 2 2.05 1.69 4 1 4.85 10

TECHNO ELE & ENG 1 2 2 1 2 2 1.91 1.57 1 1 11.37 27

SIMPLEX INFRASTR 2 2 1 1 1 1 1.08 0.89 1 1 9.75 16

J.KUMAR INFRAPRO 2 2 1 1 2 2 1.08 0.89 1 1 17.61 33

PATEL ENGINEER 2 1 1 1 2 2 1.24 1.03 2 2 9.49 13

SUPREME INFRASTR 2 2 1 1 2 2 0.94 0.77 1 1 18.14 17

MAN INFRACONSTRU 2 2 1 1 2 2 3.56 2.94 2 2 7.11 26

IVRCL LTD 2 2 1 1 2 2 0.80 0.66 1 1 2.34 19

IL&FS ENGINEERIN 2 2 1 1 2 2 0.93 0.76 2 2 9.97 -33

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ATLANTA LTD 1 1 1 1 2 2 1.22 1.01 1 1 14.14 20

GAMMON INDIA LTD 2 2 1 1 2 2 0.90 0.75 1 1 9.08 13

PRATIBHA INDUSTR 2 1 2 1 2 2 1.06 0.88 1 1 13.68 19

GANESH HOUSING 1 1 1 1 2 2 1.95 1.61 2 2 13.73 11

JYOTI STRUCTURES 2 2 1 1 1 2 1.23 1.01 3 2 14.93 28

AHLUWALIA CONTRA 2 2 1 2 2 1 0.92 0.76 2 1 9.71 45

ERA INFRA LTD 2 2 2 2 2 2 1.65 1.36 1 1 2.52 16

RAMKY INFRASTRUC 2 2 2 1 2 1 1.07 0.88 3 2 -22.98 23

KNR CONSTRUCTION 2 2 1 1 2 2 1.18 0.97 1 1 14.71 24

JMC PROJECTS 2 2 1 1 2 2 1.14 0.94 3 2 10.49 19

MBL INFRASTRUCT 2 2 1 2 2 2 1.44 1.18 2 2 18.43 21

MSR INDIA LTD 2 2 1 1 2 2 1.35 1.11 4 1 -0.62 0

VASCON ENGINEERS 2 2 1 2 2 1 1.39 1.15 2 2 -0.96 11

GPT INFRAPROJETC 2 2 2 1 1 2 1.06 0.87 1 1 10.22 24

GAYATRI PROJECT 2 2 1 1 2 2 0.54 0.45 1 2 12.22 15

UNITY INFRAPROJE 2 2 1 1 2 2 0.99 0.82 2 2 9.90 17

SPML INFRA LTD 2 2 2 1 1 2 0.77 0.63 3 1 16.35 19

SHRIRAM EPC LTD 2 2 1 1 2 2 0.51 0.42 3 2 -12.82 13

RPP INFRA PROJ 2 2 1 1 2 2 1.85 1.53 3 1 15.18 28

COROMANDEL ENG 2 2 1 1 2 2 1.04 0.85 4 2 0.34 6

BL KASHYAP&SONS 2 2 1 1 2 2 1.15 0.95 2 2 -4.10 12

C & C CONSTRUCTI 2 2 1 1 1 1 1.28 1.06 1 2 -0.81 15

MADHUCON PROJEC 2 2 1 1 2 2 0.48 0.40 1 1 14.45 9

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EXHIBIT 2A – CLUSTERS OF 2010

CLUSTER 1 - Companies (2010) Differentiation 2010 Diversification 2010 Internationalization 2010 Working

Capital 2010 Type of Projects

Type of Clients

Managerial Capability 2010

JAYPEE INFRATECH 10.04 1.00 1.00 1.18 2.00 2.00 9.35

VA TECH WABAG LT 0.17 1.00 1.00 1.47 3.00 2.00 20.89

NATIONAL BUILDIN 0.04 1.00 1.00 1.11 2.00 2.00 31.57

GLOBUS CONSTRUCT 0.00 1.00 1.00 15.31 2.00 2.00 0.52

SRS REAL INFRA 0.02 1.00 1.00 1.40 2.00 2.00 4.81

DREDGING CORP 0.11 1.00 1.00 4.14 4.00 1.00 10.09

PATEL ENGINEER 0.53 1.00 1.00 3.51 2.00 2.00 13.30

IL&FS ENGINEERIN 0.00 1.00 1.00 1.11 2.00 2.00 -32.89

GANESH HOUSING 1.45 1.00 1.00 8.06 2.00 2.00 11.33

JYOTI STRUCTURES 0.04 1.00 0.99 1.48 3.00 2.00 28.08

JMC PROJECTS 0.03 1.00 1.00 1.21 3.00 2.00 19.12

MSR INDIA LTD 0.03 1.00 1.00 0.98 4.00 1.00 0.00

GAYATRI PROJECT 0.04 1.00 1.00 1.50 1.00 2.00 15.34

UNITY INFRAPROJE 0.06 1.00 1.00 1.75 2.00 2.00 17.08

SPML INFRA LTD 0.03 1.00 1.00 1.79 3.00 1.00 19.45

SHRIRAM EPC LTD 0.04 1.00 1.00 1.83 3.00 2.00 13.35

RPP INFRA PROJ 0.06 1.00 1.00 0.82 3.00 1.00 27.86

COROMANDEL ENGIN 0.03 1.00 1.00 1.34 4.00 2.00 6.23

BL KASHYAP&SONS 0.04 1.00 1.00 1.64 2.00 2.00 12.41

Mean Cluster 1 0.67 1.00 1.00 2.72 2.58 1.79 11.99

CLUSTER 2 - Companies (2010) Differentiation 2010 Diversification 2010 Internationalization 2010 Working

Capital 2010 Type of Projects

Type of Clients

Managerial Capability 2010

JAIPRAKASH ASSOC 0.24 0.00 1.00 2.18 1.00 1.00 7.29

IRB INFRASTRUCTU 0.36 1.00 1.00 2.36 1.00 1.00 14.73

SKIL INFRASTRUCT 0.04 1.00 1.00 4.16 1.00 1.00 0.21

KEC INTL LTD 0.05 1.00 1.00 1.46 1.00 1.00 17.05

SADBHAV ENGINEER 0.03 1.00 1.00 1.33 1.00 1.00 13.09

ASHOKA BUILDCON 0.13 0.99 1.00 1.17 1.00 1.00 18.02

NCC LTD 0.05 1.00 1.00 1.35 1.00 1.00 16.36

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GAMMON INFRASTRU 0.11 1.00 1.00 1.48 1.00 1.00 7.83

ITD CEMENTATION 0.01 1.00 1.00 2.29 1.00 1.00 13.61

TECHNO ELE & ENG 0.20 1.00 1.00 1.70 1.00 1.00 26.87

J.KUMAR INFRAPRO 0.11 1.00 1.00 1.83 1.00 1.00 32.74

SUPREME INFRASTR 0.09 1.00 1.00 1.67 1.00 1.00 17.04

IVRCL LTD 0.01 1.00 1.00 1.56 1.00 1.00 18.64

ATLANTA LTD 0.33 1.00 1.00 0.95 1.00 1.00 19.55

GAMMON INDIA LTD 0.01 1.00 1.00 1.12 1.00 1.00 12.80

PRATIBHA INDUSTR 0.35 1.00 1.00 1.64 1.00 1.00 19.23

KNR CONSTRUCTION 0.08 1.00 1.00 1.41 1.00 1.00 24.01

GPT INFRAPROJETC 0.06 1.00 1.00 1.73 1.00 1.00 24.05

MADHUCON PROJECT 0.03 1.00 1.00 1.31 1.00 1.00 9.42

Mean Cluster 2 0.12 0.95 1.00 1.72 1.00 1.00 16.45

CLUSTER 3 - Companies (2010) Differentiation 2010 Diversification 2010 Internationalization 2010 Working

Capital 2010 Type of Projects

Type of Clients

Managerial Capability 2010

LARSEN & TOUBRO 0.14 0.42 0.75 1.44 1.00 1.00 17.18

GMR INFRA-SLB 0.04 1.00 0.80 1.82 1.00 2.00 2.07

ENGINEERS INDIA 0.29 0.53 1.00 1.54 3.00 1.00 28.46

KALPATARU POWER 0.05 0.44 0.71 1.30 2.00 2.00 13.76

HINDUSTAN CONST 0.00 1.00 0.98 1.64 1.00 1.00 12.03

PUNJ LLOYD LTD 0.00 0.99 0.32 2.30 1.00 1.00 11.75

KOLTE-PATIL 1.08 0.55 0.55 3.49 2.00 2.00 5.49

SIMPLEX INFRASTR 0.03 1.00 0.75 1.13 1.00 1.00 16.40

MAN INFRACONSTRU 0.21 1.00 1.00 2.78 2.00 2.00 25.61

AHLUWALIA CONTRA 0.06 0.70 0.70 1.31 2.00 1.00 45.29

ERA INFRA LTD 0.10 0.85 1.00 5.24 1.00 1.00 16.11

RAMKY INFRASTRUC 0.07 0.98 0.98 1.22 3.00 2.00 22.61

MBL INFRASTRUCT 0.07 0.84 1.00 1.63 2.00 2.00 20.54

VASCON ENGINEERS 0.08 0.57 0.57 2.64 2.00 2.00 10.82

C & C CONSTRUCTI 0.06 1.00 0.93 1.29 1.00 2.00 14.58

Mean Cluster 3 0.15 0.79 0.80 2.05 1.67 1.53 17.51

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EXHIBIT 2B – CLUSTERS OF 2014

CLUSTER 1 - Companies (2014) Differentiation 2014 Diversification 2014 Internationalization 2014 Working

Capital 2014 Type of Projects

Type of Clients

Managerial Capability 2014

JAYPEE INFRATECH 2.09 1.00 1.00 1.50 2.00 2.00 7.62

GLOBUS CONSTRUCT 0.00 1.00 1.00 0.33 2.00 2.00 -5.06

SRS REAL INFRA 0.01 1.00 1.00 1.64 2.00 2.00 7.20

DREDGING CORP 0.05 1.00 1.00 2.05 4.00 1.00 4.85

PATEL ENGINEER 0.00 1.00 1.00 1.24 2.00 2.00 9.49

MAN INFRACONSTRU 0.07 1.00 1.00 3.56 2.00 2.00 7.11

IL&FS ENGINEERIN 0.00 1.00 1.00 0.93 2.00 2.00 9.97

JYOTI STRUCTURES 0.00 1.00 0.65 1.23 3.00 2.00 14.93

RAMKY INFRASTRUC 0.00 0.80 1.00 1.07 3.00 2.00 -22.98

JMC PROJECTS 0.00 1.00 1.00 1.14 3.00 2.00 10.49

MBL INFRASTRUCT 0.05 1.00 1.00 1.44 2.00 2.00 18.43

MSR INDIA LTD 0.00 1.00 1.00 1.35 4.00 1.00 -0.62

VASCON ENGINEERS 0.00 1.00 1.00 1.39 2.00 2.00 -0.96

UNITY INFRAPROJE 0.00 1.00 1.00 0.99 2.00 2.00 9.90

SHRIRAM EPC LTD 0.00 1.00 1.00 0.51 3.00 2.00 -12.82

RPP INFRA PROJ 0.06 1.00 1.00 1.85 3.00 1.00 15.18

COROMANDEL ENGIN 0.00 1.00 1.00 1.04 4.00 2.00 0.34

BL KASHYAP&SONS 0.00 1.00 1.00 1.15 2.00 2.00 -4.10

Mean Cluster 1 0.13 0.99 0.98 1.36 2.61 1.83 3.83

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CLUSTER 2 - Companies (2014) Differentiation 2014 Diversification 2014 Internationalization 2014 Working

Capital 2014 Type of Projects

Type of Clients

Managerial Capability 2014

JAIPRAKASH ASSOC 0.00 0.17 1.00 0.75 1.00 1.00 8.61

IRB INFRASTRUCTU 0.19 1.00 1.00 0.97 1.00 1.00 2.63

SKIL INFRASTRUCT 0.00 1.00 1.00 0.58 1.00 1.00 6.25

SADBHAV ENGINEER 0.02 1.00 1.00 1.06 1.00 1.00 16.27

GAMMON INFRASTRU 0.04 1.00 1.00 0.47 1.00 1.00 1.87

ITD CEMENTATION 0.01 1.00 1.00 1.04 1.00 1.00 11.57

J.KUMAR INFRAPRO 0.08 1.00 1.00 1.08 1.00 1.00 17.61

SUPREME INFRASTR 0.04 1.00 1.00 0.94 1.00 1.00 18.14

IVRCL LTD 0.00 0.98 1.00 0.80 1.00 1.00 2.34

GAMMON INDIA LTD 0.00 1.00 1.00 0.90 1.00 1.00 9.08

AHLUWALIA CONTRA 0.02 0.98 1.00 0.92 2.00 1.00 9.71

KNR CONSTRUCTION 0.07 1.00 1.00 1.18 1.00 1.00 14.71

GAYATRI PROJECT 0.00 1.00 1.00 0.54 1.00 2.00 12.22

MADHUCON PROJECT 0.00 1.00 1.00 0.48 1.00 1.00 14.45

Mean Cluster 2 0.03 0.94 1.00 0.84 1.07 1.07 10.39

CLUSTER 3 - Companies (2014)

Differentiation 2014 Diversification 2014 Internationalization 2014 Working

Capital 2014 Type of Projects

Type of Clients

Managerial Capability 2014

LARSEN & TOUBRO 0.06 0.45 1.00 1.25 1.00 1.00 22.49

GMR INFRA-SLB 0.00 1.00 0.87 0.50 1.00 2.00 0.81

ENGINEERS INDIA 0.33 0.61 1.00 2.57 3.00 1.00 59.16

VA TECH WABAG LT 0.32 1.00 0.37 1.49 3.00 2.00 34.23

NATIONAL BUILDIN 0.07 0.02 1.00 1.37 2.00 2.00 32.70

KEC INTL LTD 0.01 0.90 0.90 1.03 1.00 1.00 27.12

KALPATARU POWER 0.02 0.48 0.74 1.26 2.00 2.00 20.83

ASHOKA BUILDCON 0.06 0.79 1.00 1.03 1.00 1.00 17.60

HINDUSTAN CONST 0.00 1.00 0.45 1.11 1.00 1.00 9.24

PUNJ LLOYD LTD 0.00 0.92 0.38 1.01 1.00 1.00 9.19

NCC LTD 0.00 0.93 0.93 1.15 1.00 1.00 9.71

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KOLTE-PATIL 1.04 1.00 1.00 2.40 2.00 2.00 8.53

TECHNO ELE & ENG 0.15 0.82 1.00 1.91 1.00 1.00 11.37

SIMPLEX INFRASTR 0.01 0.99 0.84 1.08 1.00 1.00 9.75

ATLANTA LTD 0.21 1.00 1.00 1.22 1.00 1.00 14.14

PRATIBHA INDUSTR 0.01 0.94 1.00 1.06 1.00 1.00 13.68

GANESH HOUSING 0.32 1.00 1.00 1.95 2.00 2.00 13.73

ERA INFRA LTD 0.00 0.79 1.00 1.65 1.00 1.00 2.52

GPT INFRAPROJETC 0.01 0.69 0.69 1.06 1.00 1.00 10.22

SPML INFRA LTD 0.00 0.70 0.70 0.77 3.00 1.00 16.35

C & C CONSTRUCTI 0.00 1.00 0.89 1.28 1.00 2.00 -0.81

Mean Cluster 3 0.13 0.81 0.85 1.34 1.48 1.33 16.31