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Competitiveness Review: An International Business Journal
Comparative analyses of competitive advantage using Porter diamond model (the
case of MSMEs in Himachal Pradesh)
Manjeet Kharub Rajiv Sharma
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Manjeet Kharub Rajiv Sharma , (2017),"Comparative analyses of competitive advantage using
Porter diamond model (the case of MSMEs in Himachal Pradesh) ", Competitiveness Review: An
International Business Journal, Vol. 27 Iss 2 pp. 132 - 160
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Comparative analyses of
competitive advantage using
Porter diamond model (the case
of MSMEs in Himachal Pradesh)
Manjeet Kharub
Mechanical Engineering Department,
National Institute of Technology Hamirpur, Himachal, India, and
Rajiv Sharma
National Institute of Technology Hamirpur, Hamirpur,
Himachal Pradesh, India
Abstract
Purpose –The purpose of this paper is to measure and analyze the competitive advantage of micro, small
and medium enterprises (MSMEs) based upon the Porter’s diamond framework. The major objective is to
contribute toward better understanding of various determinants of the diamond model in context within
Indian MSMEs.
Design/methodology/approach –Extent review of the literature has been done to identify various
critical factors contributing to developing a competitive advantage. Exploratory factor analysis and
internal consistency tests were performed to verify scales validity and reliability of measuring
instrument (questionnaire). In research design, a case study approach has been used, in which MSMEs
operating in the pharmaceutical, electrical and electronics, automobile, food and textile sectors were
considered.
Findings –Study ndings indicate that the pharmaceutical sector is more competitive followed by food
(112.491) as revealed by the high value of surface area i.e. 150.931. The competitiveness among
MSME sectors is mostly affected by demand conditions followed by rm strategy, structure and rivalry.
Moreover, the score of diamond axes indicates signicant difference with respect to determinants. For
instance, in the textile sector, the determinants such as factor conditions and related and supporting
industries scored low, for example, 4.710 and 4.280, respectively, which indicates it needs to be
strengthened as this sector stands at last position with minimum surface area, for example, 67.398.
Research limitations/implications –Owing to the time and resource constraints, this study was
conducted in MSMEs situated in the state of Himachal Pradesh, India, and thus generalizations of results are
rather limited.
Practical implications –This study is one of the original being undertaken by authors which helps to
underline the importance of various determinants which may help the MSME units to improve
competitiveness by implementing effective competitive strategies. The study could be extended to other
regions of the country.
Originality/value –This study is a result of extended research on competitiveness and provides an
instrument to measure rm ability to be competitive. CEO’s, managers and policy makers from industries as
The authors would like to thank the Editor in Chief and anonymous reviewers for their valuable
comments and suggestions to improve the quality of the paper. The nancial support received from
Department of Science and Technology, Ministry of Science and Technology, Govt of India vide letter
No 100/FD/4232/20127–13 under the project grant is highly acknowledged.
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1059-5422.htm
CR
27,2
132
Received 8 February 2016
Revised 1 April 2016
Accepted 6 April 2016
Competitiveness Review
Vol. 27 No. 2, 2017
pp. 132-160
© Emerald Publishing Limited
1059-5422
DOI 10.1108/CR-02-2016-0007
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well as government will be able to use this to evaluate their competitive positioning and identify key problem
areas which required improvements.
Keywords Business strategy, Competitive advantage, MSMEs, Factor and demand conditions,
Porter diamond
Paper type Research paper
1. Introduction
In modern global market, because of globalization and rapid technology changes, rms need
to compete not only with national rivals but also with international rms (Ickis, 2006;Brenes
et al., 2011). This immense global pressure continues to alter the environment in which rms
operate, the traditional industrial strategies are becoming less effective. For survival,
companies have to build “core competencies” via implementing quality practices, cost
effective competitive pricing policy, internet marketing, sound strategy basis, product
innovation and predicting buyer behavior for high customer satisfaction (Lynch and Ariely,
2000;Chobanyan and Leigh, 2006;Gupta and Nanda, 2015). Whenever the strategies used are
successful in leveraging the rm’s performance, the rm is likely to gain an advantage over
its competitors in the marketplace and thus earn a higher return. The strategies build on
particular resources that are rare, valuable and difcult to imitate are proving more efcient
than others and are being considered as main drivers of creating sustainable competitive
advantages. In this unpredictable business environment, a variation in regional economic
performance has become a common feature in nation’s economy both in developing as well as
developed countries. Numerous studies have been conducted to explain why some regions
achieve signicantly higher growth rate than others (Delgado et al., 2014;Singla and Jain,
2014;Chandamoyo and Dumbu, 2012;Baptista and Preto, 2010). Researchers from various
countries focused considerable attention on regions, clusters and industrials sectors which
appear to have achieved comparatively strong economic performance, for instance, Combes
(2000) in France, Oz (2002) in Turkey, Porter and Emmons (2003);Bresnahan and
Gambardella (2004);Ellison et al. (2010) in USA, Kao et al. (2008) in Southeast Asian
countries, Lattuch et al. (2013);Bonte (2004) in Germany, with particular emphasis on one or
very few dimensions (namely, start-up resources, potential for innovation, technological
upgradation, knowledge management and the composition of economic activities etc.) of
performance at a time.
According to Ketels (2006), in the presence of highly competitive related and supporting
industries, growth increases at a level of economic activity (activity that creates value by
providing products and services at a price above their cost of production). Firm’s competitive
advantage, economic performance and prosperity arises through interdependencies across
complementary activities; it includes availability of initial resources, sharing of common
technology, specic knowledge, input and output across industrial sectors (Petrakis et al.,
2015). In literature, a long list of individual factors is found which affect the rm’s
competitiveness. These factors differ in their current impact on potential productivity based
upon the specic set of local conditions presents (Porter, 2000). Policy makers are thus facing
problem to identify which factors are critical for improving competitiveness in the given
situation and what strategic actions need to be taken to address these priority factors? Thus,
the aim of this paper is, rst, to identify the various critical factors for rm’s competitiveness
and, second, to present the sector wise competitive advantage of various micro, small and
medium enterprises (MSMEs). To this effect, a case of MSMEs situated in the state of
Himachal Pradesh has been undertaken, and the most popular approach to measuring
competitiveness among various sectors, the framework developed by Michael Porter has
been used, as this framework is provides broad-based integrative tool, particularly which
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helps to identify most prominent issues for competitiveness in a given location (Rugman and
D’cruz, 1993;Ketels, 2006;Kao et al., 2008;Dobbs, 2014).
1.1 Theoretical development
The MSME sector in India draws signicant importance because of its considerable
contribution in employment, production and export. It contributes almost 40 per cent of gross
industrial value, 45 per cent of the export and is the second largest employer of the human
resources. The employment potential in this sector has increased to 106.152 million in
2012-2013 from 80.523 million in 2006-2007 (Annual Report MSME, 2013/2014). MSMEs in
India now provide more employment and business turnover than large and public
organizations together. The MSMEs continue to dominate in production of over 6,000
products ranging from traditional to high-tech in its leading industrial sectors, namely,
fabrication, metalwork, food processing, papermaking, printing, garments tannery, plastic
molding, wood and furniture industries. The demand from buyer organizations is expected
to grow dramatically in coming years as evident from Electronics Industries Report (2013)
and study conducted by Singh et al. (2010);Brown (2011) and Fisheries (2011). Thus, the
MSME sector is considered as backbone of economy growth in all countries; the research
pertaining to this sector has grown remarkably since the past decade, as is evident from the
quality of research ndings such as Zhang (2000),Bhattacharya (2002),Arinaitwe (2006),
Chikan (2008),Rugman and Oh (2008),Quer et al. (2010),Bhavani (2011) and Gupta and
Nanda (2015). Though MSMEs play a critical role in the economy of India, they have received
far less research attention than large rms (Gunasekaran et al., 2011;Sharma and Kharub,
2014). However, it is observed that sickness in MSMEs is increasing at a rapid rate, especially
in developing countries (Sabharwal, 2000;Snowdon and Stonehouse, 2006;Wang et al., 2007;
Sharma and Kharub, 2015). It has been noted that MSMEs focus only on certain aspects of
their functioning, works in isolation and are not able to sustain their competitiveness in the
global market (Singh et al., 2008). So, there is a need to conduct more research particularly in
rapid emerging economies such as Brazil, Russia, India, China and South Africa.
This background raises interesting questions about the competitiveness of emerging
nations and their ability to compete in the current global economy:
RQ1. Can the competitiveness of MSMEs sector be measured?
RQ2. If yes, what are the critical factors/features that contribute to their ability to
compete?
RQ3. What is the competitive positioning of various Indian MSMEs sectors with respect
to each other?
RQ4. Which MSME sector is more competitive than other and why?
This necessitates the authors to investigate the factors affecting competitiveness among
MSMEs and to develop a framework to analyze the competitive positioning among MSMEs.
As a case study, MSMEs operating in the pharmaceutical, electrical and electronics,
automobiles, food and textile manufacturing sectors were considered, and their
competitiveness is analyzed by using the diamond model. A well-designed questionnaire
was administered among the industry respondents to gather the information pertaining to
various determinants of competitiveness. Figure 1 presents the research framework
developed by authors to measure competitive positioning among various MSME sectors.
Stage 1 of the framework presents a brief introduction to Indian MSMEs, the role of
competitiveness and theoretical development. Stage 2 presents research instrument design
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and sample size determination. Stage 3 presents the case study design, exploratory factor
analyzes, reliability check and calculation of diamond surface areas.
2. Theoretical background
2.1 National and international studies on competitiveness strategy
During recent years, globalization has opened numerous opportunities as well as the huge
pressure of building competitive advantage by designing sustainable strategies to support
and improve economic prosperity. That is why research on competitiveness has become an
interesting topic for theorist and practitioners and considered as a key issue for policy
makers in many countries or specic regions (Cetindamar and Kilitcioglu, 2013). Policy
makers are facing challenges without clear guidance on how to address this current nature of
global competitions. There are important reports (i.e. Global Competitiveness Report
published by World Economic Forum; World Competitiveness Yearbook published by
International Institute for Management Development) and case studies by various authors
which present empirical assessments of competitiveness of national and regional economies.
They differ widely in terms of their scope, drivers of competitiveness they took at, industrial
sectors and in their geographic coverage. For instance, Oz (2002) sought to identify the source
of international competitiveness in Turkish industrial sectors – namely, glass, construction,
leather clothes, automobiles and steel industries. Ajitabh and Momaya (2004) conducted a
detailed review of the competitiveness of rms and summarized that increasing productivity
via effective capacity utilization and quality management is the actually way which makes
industrial growth possible. In an another study, Hamalainen (2003) found productive
resources, socio-economic infrastructure, capacity utilization and technological
infrastructure, as the strategic issues of competitive advantage for manufacturing rms.
Furthermore, cost, exibility, quality, delivery lead time, product and market characteristics,
government policies and innovations are common factors discussed by various authors in
the literature which helps rms to remain competitive. The most recent national and
international studies on competitiveness are reviewed by the authors, and the details are
Figure 1.
Framework for
measuring competitive
positioning among
MSME sectors
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summarized in Table I. Most of the studies found supportive with Porter’s approach to
competitiveness. Section 2.2 presents brief description about Porter’s idea of
competitiveness, its critiques and extension of the original Porter’s diamond framework.
2.2 Michael porter’s competitive approach
Michael E. Porter has been regarded as a leading authority on competitive strategy in a
nation and, more recently, the application of competitive analysis on social and environment
aspect of business activities. Porter (1990) provided a model which was widely accepted and
is used to measure Competitive Advantage of Nation. This section highlights the critical
features of Porter’s concept of competitiveness and based on it proposes a conceptual model
for this study.
2.2.1 The denition of competitiveness. Porter denes the competitiveness of a location as
the productivity that companies located there can achieve (Cairncross, 2001). He believed
that measuring competitiveness is a mapping of competitive environment of an organization
which helps the nation to form a sound basis for business strategies and developments. His
work forms the centerpiece of the competitive positioning via presenting the dominant
strategy paradigm of 1980 and has become extremely popular with management, theories
and practitioners in recent years (Naserbakht et al., 2008;Li et al., 2009;Smit, 2010;Deniz
et al., 2013). His two books competitive strategy (1980) and competitive advantage (1985)
marked a revolution in thinking and increased the awareness of the subject of competitive
strategy by developing three linked concepts, namely: ve forces, genetic strategy and value
chain frameworks.
The “ve forces” Porter’s diamond model has been regarded as the major analytical
framework of competitive positioning paradigm. This framework allows a rm to assess its
competitive positioning through an evaluation of:
• the strength of the threat of new entrants and substitute products;
• the power of buyers and suppliers; and
• the degree and nature of rivalry among businesses.
In literature (Table I), various authors adopted Porter’s diamond model with the clear
intention to assess competitive environment with respect to various industrial sectors,
operating in various countries. Results from most of the studies found supportive with
Porter’s idea, that competitive advantage of the nation is determined by the strength of their
factor endowments, their demand conditions and the competitiveness of rm strategy,
structure and rivalries in major industries (Porter, 2003).
The following paragraphs briey describe the various determinants of porter’s diamond
framework.
2.2.1.1 Factor conditions. These conditions contribute to the productivity of an
organization, act as the key determinants of the level of prosperity of an organization can
sustain over time. Two implications from this focus on factors conditions have been
highlighted in recent literature:
(1) basic factors or tangible resources; and
(2) advance factors or intangible resources (Porter, 1998;Nilsson and Peterson, 2002;Li
et al., 2009;Deniz et al., 2013).
The rst category has its root in history, and it is possessively inherited, such as climate,
location, available minerals, national resources, agriculture advancements, forest resources,
skilled and unskilled labor, etc. (Oz, 2002;Jin and Moon, 2006;Lin and Wu, 2014). Strong
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Table I.
Literature review on
international and
national
competitiveness
Author(s) Scope
Determinants of competitive
positioning Method and ndings
Oz (2002) National Basic Porter diamond framework Study identied the source of international competitive advantage in Turkey and emphasized on
strengthening of factors like product innovation and technology upgradation to survive in the current
global competitive environment
Hamalainen (2003) National Productive resources
Socio-economic infrastructure
Technological infrastructure
Productive capacity
Econometric model of empirical data has been implemented and the study concluded that there is a need
to introduce automation and optimization of production cost and productivity
Ajitabh and Momaya
(2004)
International Capacity utilization
Relative unit labor costs
Productivity
Authors concluded that increasing productivity via effective capacity utilization and implementing
quality management is the actually mean which makes industrial growth possible
Chobanyan and Leigh
(2006)
International Socio-economic infrastructure
Product market characteristics
Human resources
Qualitative and quantitative methods have been used to nd a relationship between the drivers of
competitiveness and organizational performance
Jin and Moon (2006) National Double diamond model This study used two competitiveness models: Porter’s diamond model and generalized double diamond
model, as a theoretical framework to assess competitiveness
Nair (2006) National Knowledge management
Organizing abilities
Flexibility
Strategic behavior
The results obtained from this study help to predict the MSMEs behavior for implementing strategy for
competitive advancement. Introducing new product, carefully managing customer delivery, skillful
handling changes in product mix, etc. all of these items is conrmed as important to MSMEs
Loader (2007) International Economic-policy
Cost superiority
Knowledge transfer
The study presents the evolutionary views in term of economic strategic, empirical research and policy
implementations through appropriate knowledge transfer
Chikan (2008) International Porter’s diamond model Author provides a conceptual model to connect competitiveness at macro and micro level of the economy
Rugman and Oh
(2008)
International Special advantage and regional
matrix framework
It is a conventional study of international competitiveness based on country-level data from 500 Asian
rms. It is found that most of the Asian rms do not operate globally but focus on their home region,
only a few Japanese and Korean rms found having a signicant sale outside of Asia
Singh et al. (2008) International Strategy development
Organizational culture
Vendor development
Innovation and knowledge
Authors presented a general review of 134 papers and presented a research agenda and concluded that
small rms face many problems because of lack of resources and poor innovative capabilities and
suggested that to sustain their competitiveness they have to benchmark their assets, processes and
performances
Wang and Wu (2012) International Team member commitment
Start-up commitment
Based upon empirical study, the authors found that competitiveness is positively associated with start-
up team member’s trust on the entrepreneurs
(continued)
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Table I.
Author(s) Scope
Determinants of competitive
positioning Method and ndings
Brown et al. (2010) International Product market characteristics
International business activities
Entrepreneur’s education and
practical experience
Government policies
A survey-based study was conducted, and interviews were asked regarding recent development in their
rms. Investment in new equipment, broadening of products spectrum or portfolio, implementation new
PPC system and quality improvement were observed as important determinants for competitiveness
Dogl et al., 2012 International Basic Porter’s diamond model This study presents a case study based upon Porter’s diamond model to investigate the demand for
renewable energies in India, China and German rms. Continuous investment in R&D activities has been
found main competitive priority for small manufacturing rms
Esen and Uyar (2012) International Porter’s diamond model Authors presented a descriptive study based upon data collected from secondary source pertaining to
key issues regarding the competitive advantage of rms
Deniz et al. (2013) National Five forces of Porter’s framework Authors conducted a descriptive and quantitative research and concluded that majority of MSMEs in
Turkey are at very low competitive level
Herciu (2013) International Basic Porter diamond model Base upon Porter’s diamond model, the authors calculated competitive advantage and disadvantage of Romania
Thurer et al. (2013) National New equipment
Product innovation
New PPC system
Market share
Stated outsourcing
New infrastructure
An exploratory study based on semi-structured telephone interviews is conducted to examine the
competitive priorities based on the recent development opportunities and challenges
Vijande et al. (2013) International Brand management system
Brand orientation
Internal branding
Strategic brand management
Authors concluded that brand management system (BMS) is crucial for sustainable competitive
advantage. Based upon the view point of 115 knowledge-intensive business services study show that the
BMS effectively helps rms to perform better than their competitor
Dobbs, 2014 International Porter ve forces The study provides an industry analysis template for applying Porter’s ve-force framework for
measuring competitiveness
Lin and Wu (2014) International Dynamic capacity This study analyzes the viewpoints of 10,000 employees from Taiwanese companies and explore the
relationship between dynamic capabilities and rm performance
Sharma and Kharub
(2014)
National Quality management
Reduction in defects rate
Productivity
A conceptual framework with a straightforward application of SPC to attain competitive positioning in
MSMEs is presented. It is concluded that management support and knowledge attained through proper
training helps SMEs to establish their market position
Rojaka (2015) National Exchange rate
Sale growth
Market share
Marketing
Author used data envelopment technique of survey and concluded that product and process innovation
must link to increase rm’s market share
Petrakis et al. (2015) Organization structure
Innovation
Social learning
Authors conducted an empirical study and found innovation, competitive capacities, social learning and
organizational structure extremely important dimensions to help in attaining competitive positioning
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basic factors mainly help in providing competitiveness on the long-term basis and attract
new investors in the region. According to Ajitabh and Momaya (2004), better availability of
labor, their educational level and technical skills have a direct impact on quality and delivery
of manufacturing goods and leads toward higher customer’s satisfaction.
The second category consists of advance factors which are mainly affected by human
efforts or are created to generate competitive advantages. For instant, competitive human
resource includes abilities, skills and satisfaction level of employees (Saru, 2007;Nanda and
Singh, 2009), comparatively low cost of staff (Hamalainen, 2003;Nair, 2006); physical
resources include raw materials, its quality and quantity, effective utilizations of limited
available resources, knowledge resource consist of the state’s stock of scientic, technical
and market knowledge (Loader, 2007;Rojaka, 2015;Petrakis et al., 2015); and information
resources include universities, government research institutes, government statistical
agencies, business and scientic literature, reports and database, etc. (Shee and Momaya,
2001;Brown et al., 2010).
Porter’s concept of competitiveness focuses on the prosperity “created” from the economic
activities rather than “inherited” prosperity, i.e. the exploitation of national resources. He
believed that only depending on inherited prosperity often becomes a powerful barrier
against upgrading true underlining competitiveness. The organization’s prosperity depends
upon the economic-wide productivity generated from each factor unit available for economic
activity (Cairncross, 2001).
2.2.1.2 Demand conditions. This determinant refers to the nature of home-market and is
the second broad determinant of national competitive advantage (Nilsson and Peterson,
2002). Porter viewed demand conditions in terms of size of the home market, sophistication
and demanding buyers (either industrial buyers or consumers). That is, if the size of home
demand is large, rms will invest to reap economies of scale which contribute toward
building competitive edge. In countries where the domestic buyers are the world’s most
sophisticated and demanding, the companies are forced to meet high standards and upgrade
to respond to tough challenges (Beise and Cleff, 2004). As per Stonehouse and Snowdon
(2007),Ahn et al. (2012), the more rigorous demands lead the rms to meet higher standards,
force them to upgrade technology, quality improvement, product features with the high
performance followed by better services. According to Nair (2006),Woodside and Walser
(2007) and Thurer et al. (2013), reducing delivery lead time, ability to meet exibility in
demands and having better brand image are noted as vital features in increasing market
share and creating competitive advantage particularly for small businesses.
Traditionally, the demand conditions were thought of as the size of a local market. Porter
adds another perspective by focusing explicitly on the quality of local demand: specic
customer’s need at a given location can provide companies the unique ability to learn how to
serve these needs with targeted products and services (Cairncross, 2001). If local customers
need to foreshadow the deeds of customers in the other markets, rms that operated locally
are likely to have a competitive edge when they enter the new market. Furthermore, he
emphasized that the focus of local demand does not imply that global market access does not
matter (Porter, 2004;Delgado et al., 2014).
2.2.1.3 Related and supporting industries. The geographic concentration of companies
and other institutions active in a specic economic eld are important for competitiveness
because they are associated with higher level of productivity and innovation (Porter, 2003).
Related industries are those in which an organization can organize or allocate activities in the
value chain when competing or those, which produce component goods (Tasevska, 2006).
The existence of related or supporting industries in a nation is argued as the third dimension
of the diamond model (Tuna, 2006). According to Nair (2006), the existence of competitive
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downstream industries well contributes to the four traditionally primary applied competitive
priority dimensions, i.e. cost, exibility, quality and delivery. Furthermore, the presence of
suppliers and related industries within a nation that are internationally competitive provides
benets such as innovation, upgrading of information ow and shared technology
development through rm alliance to create an advantage in downstream industries (Woods
and Hecker, 2011;Gupta and Nanda, 2015). They provide access to specialized input factors
such as employees and risk capital to enable higher rm’s performance. Potential suppliers
not only reduce the delivery lead time but also invest in research, innovative activities and
create knowledge base as per upstream enterprises (Porter and Ketels, 2003). Good supplier
creates potential for high competitive advantage by providing new methodology and
opportunities to utilize new technology; on the other hand, if there is a shortage of input such
as labor and raw materials, there is not a concept of competitiveness or industrial
development in any manufacturing or service sector (Withers and Ebrahimpour, 2000).
Porter and Emmons (2003) and Ketels (2006) emphasized on the presence of quality of
institutions, distinct agencies and geographic units are important for the business
environment. They have especially noted the role of “institutions for collaborations” and
suggested that the institutes with private and public partnership must focus on industrial
sectors and regions for competitiveness.
2.2.1.4 Firm strategy, structure and rivalry. This determinant refers to the conditions
which determine how the rms were created, organized, structured and managed, as well as
the nature of the domestic rivalry. The feature that governs this determinant is specic to
countries, vary as to the lifestyle of people, their attitude individual as well as the group
toward authority which further constitute into organizational culture (Cho et al., 2008;Esen
and Uyar, 2012). The academic system, social and religious belief, history and family
structure directly affect the structure of business. For example, many Turkish rms are
relatively small- or medium-sized, privately owned and operate like extended families (Oz,
2002).
This determinant governs the uniqueness of company over the competitor (Chobanyan
and Leigh, 2006); in other words, it shows the rm’s competitive priority such as increased
productivity using new equipments (Hamalainen, 2003;Thurer et al., 2013), or unique
product and production capabilities (Lin and Wu, 2014), or production planning system and
implementation of quality improvement techniques, investment in R&D activities,
technology sharing and upgradations (Nanda and Singh, 2009) or using strategic
management and skills for integration of business activities (Crittenden and Woodside,
2006).
With respect to this determinant, Porter’s concept focuses on creating prosperity by
achieving a market price for their output in excess of the cost of providing this output (Porter
et al., 2004). According to him, the changes in economic policy will only affect prosperity if
organizations make changes in the nature and extent of activity undertaken by companies
(Ketels, 2006). On the other hand, the pressure from local rivals make intimate access to new
ideas and lower the cost associated with forming new products and cultivate higher
productivity growth (Porter, 2004).
2.2.1.5 Government and chance events. Governments establish an environment that
fosters a high standard of living for its citizens by making policies regarding health, safety,
environment, nancial structure, industrial trade and development (Brown et al., 2010;Dogl
et al., 2012,Deniz et al., 2013). The government consists of many distinct agencies and
geographic units with their own impact on the business environment at a given location.
Government policies directly or indirectly affect the competitive environment for enterprises
which may further yield into minimizing the external risk for economic activities. According
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to Loader (2007) and Sharma and Kharub (2015), a well-developed government infrastructure
support economic activities – it includes access to natural resources, functional business
systems, information technology, transportation and communication systems, educational
structure and protection of the environment. Even though the role of government and chance
events has been introduced as an additional variable, but they play a crucial role in the
diamond model (Tuna, 2006). The government policies and regulations have its impact on all
dimensions of the diamond. Further, Porter regards the chance events as matters that have
little to do with situations in the nation. Chance events are regarded by denition as beyond
the control of rms.
2.2.2 Critics and extensions to porter’s diamond framework. Porter’s diamond framework
faces a wave of criticism from researchers of international business, management theorists
who argued that the Porter has not articulated a theory of national competitive advantage;
rather, it is a theory about the competitive advantage of rms and industries within nations
(Yetton et al., 1992). This argument is further supported by Rugman and D’cruz (1993), where
authors emphasized that Porter underestimates the role of multinational enterprises in the
global economy. Porter fails to recognize the impact of national culture as a source of
competitive advantage and the role of technology in the development process (Oz, 2002).
Furthermore, the ve-force concept has been attacked on the basis that the principle unit of
analysis is the industry rather than the individual rm, possibilities of applicability in
MSMEs, the role of domestic rivalry in the small economy (Clancy et al., 2001). Beside these
criticisms, this model is regarded as the major analytical framework of the competitive
positioning paradigm of the 1980s and still remains at the heart of most business school
strategy courses to this day (Jin and Moon, 2006;Esen and Uyar, 2012).
For better reection of competitive advantages, several scholars provided extensions,
modications and corrections of Porter’s single diamond framework and share the idea of
double and multiple-linked diamonds (Liu and Hsu, 2009). For instance, Rugman, and D’cruz
(1993),Moon et al. (1998) and Jin and Moon (2006) incorporate the effect of international
activity. The international business scholars Rugman and Verbeke (1993) and Asmussen
et al. (2009) provided the basis for the development of a new framework to analyze the
different ways in which foreign subsidies and multinational strategic management can be
managed. As an applied framework, Porter’s competitive concept has been well experienced
from many individual case studies and used for systematically testing of various research
hypotheses.
The present study is inspired by these debates and outstanding attention in the literature
regarding Porter’s diamond model. Also, research on competitiveness is now increasingly
shifting toward systematically operationalization and testing of developed conceptual
frameworks. So, based on above descriptions and critical review of literature studies, authors
proposed a conceptual research model, as given in Figure 2, to investigate competitiveness
among MSMEs operating in different sectors. Table II presents the source of links used to
complete conceptual model.
3. Research methodology
3.1 Research objective
While much has been learned about competitiveness in the past few years, there are many
questions that remain unanswered as discussed in Section 1.1. Thus, current research is
focused mainly on three aspects:
(1) identifying the issues contributing to rm’s competitiveness;
(2) developing a conceptual model for a systematic measure of competitiveness; and
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(3) developing a comparative case study by calculating the overall surface areas of rms
operating in various key MSME sectors.
3.2 Sample design
According to information retrieval from state industrial department, MSMEs operating in
the pharmaceutical, electrical and electronics, automobile, food and textile manufacturing
units were selected. After identifying the number of companies operating in these prime
sectors, the sample size is determined. According to the Director Industries, Industries
Department, Government of Himachal Pradesh, the total population of such MSMEs
working in various manufacturing sectors in the state was found about 39,512 units. The
next step was to determine sample size. Cochran’s (1977) formula is used for sample size
determination as discussed below in equations (1) and (2)(Kotrlik and Higgins, 2001;
Oerlemans et al., 2006):
n0⫽z2p·q
C2(1)
Figure 2.
Proposed research
model for measuring
competitive
positioning
Table II.
Links identied from
literature studies
Serial
no. Main ndings Authors Links
1 There are positive interactions between factor
conditions and rm’s competitiveness
Porter and Emmons (2003),
Bresnahan and Gambardella
(2004),Ketels (2006),Chikan
(2008),Kao et al. (2008),
Ellison et al. (2010),
Stonehouse and Snowdon
(2007),Gunasekaran et al.
(2011),Cetindamar and
Kilitcioglu (2013),Thurer
et al. (2013),Delgado et al.
(2014)
H1
2 There are positive interactions between demand
conditions and rm’s competitiveness
H2
3 There are positive interactions between related and
supporting industries and rm’s competitiveness
H3
4 There are positive interactions between rm strategy,
structure and rivalry with competitiveness
H4
5 The government has effect of each determinant of
diamond model
H5
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n⫽n0
1⫹n0⫺1
N
(2)
Where
Z⫽value of selected alpha of 0.025 in each tail ⫽1.96;
(the alpha level 0.05 indicates the level of risk);
(p)(q) ⫽estimate of variation ⫽0.25;
(p is the probability of selecting a particular observation ⫽0.5, and qcan be
calculated using equation q⫽1–p⫽0.5)
C⫽accepted margin of error ⫽0.05; and
N⫽the number of units or total population in state.
By equation (1), nois calculated as 384.16. Further using equation (2), the required sample size
(n) is calculated as 380.47 units. Thus, the accepted sample size (n) is taken as 381 units.
Further, the proportions of industries to be surveyed from each particular sector are
estimated as 381/39,512 ⫽0.0096. Further details with respect to respondents and company
prole are presented in survey administration section (Section 4.2.1).
3.3 Factor analysis and reliability check
In this study, the principal component analysis method of factor analysis followed by the
varimax orthogonal was adopted on SPSS 22.0. To assess the construct validity, factor
loadings were obtained for each item. The loadings reect the strength of the relationship
between items and particular factor. To measure sample adequacy, the Kaiser–Meyer–Olkin
(KMO) test was performed before factor analysis; its value, more than 0.60, indicates that the
variables are appropriate for further analysis (Öcal et al., 2007;Dubey et al., 2015).
3.4 Diamond axes length
To determine the competitive advantage of various industrial sectors, we calculated separate
diamond and compare them as per studies proposed by Rahman (2001),Herciu (2013) and
Dogl et al. (2012). Within the framework of Diamond Model, the competitiveness of the rms
were measured with scale to the scores obtained by various determinants such as factor
conditions (two casual variables, nine proxy variables); demand conditions (two casual
variables, nine proxy variables); related and supporting industries (two casual variables,
eight proxy variables); rm strategy, structure and rivalry (two casual variables, eight proxy
variables); government and culture (two casual variables, nine proxy variables) as shown in
Table III.
Thereby, each determinant was determined by a composite score of two causal variables,
which were itemized by different proxy variables for the competitive advantage of industry.
For the purpose of construction and interpreting the diamond with regard to the size of the
axes and the surface area, we added the two casual variables.
The following paragraphs will briey explain the results obtained with respect to various
industrial sectors. For the measurement of proxy variables, we computed an interval scale
with a minimum of zero and a maximum of ten. If a casual variable was determined by more
than one proxy variable, the arithmetic average was calculated. This results in one score with
values between 0 to 10. For government and chance, we adopted a three-point scale from
Cartwright (1993). For example, an interventionist policy with a negative impact on the
diamond was evaluated with ⫺4, a policy that has no inuence on the diamond with 0 and a
government that facilitates the diamond process with ⫹4. Therefore, every score point
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Table III.
Operationalization of
porter’s diamond to
nd competitive
advantage
Serial
no. Determinants Casual variables Interval scale Proxy variables No.
1 Factor conditions (maximum 10) Basic (1-10) F1, F2, F3, F4, F5, F6, F7, F8, F9 9
Advance
2 Demand conditions (maximum 10) Market volume (1-10) D1, D2, D3, D4, D5, D6, D7, D8, D9 9
Sophistication
3 Related and supporting industries
(maximum 10)
Related companies (1-10) RS1, RS2, RS3, RS4, RS5, RS6, RS7, RS8 8
Support
4 Firm strategy, structure and rivalry
(maximum 10)
Rivalry (1-10) FS1, FS2, FS3, FS4, FS5, FS6, FS7, FS8 8
Structure/strategy
5 Government and culture (maximum 4) Government support Culture (⫺4-4) GC1, GC2, GC3, GC4, GC5, GC6, GC7, GC8, GC9 9
Total 43
Notes: F1 ⫽Natural resources; F2 ⫽Physical resources; F3 ⫽Unskilled labor; F4 ⫽Skilled labor; F5 ⫽Production and process technology; F6 ⫽Scientic and
technological information; F7 ⫽Capacity utilization; F8 ⫽Communication infrastructure; F9 ⫽IPR and patents; D1 ⫽Size of domestic demand; D2 ⫽Pattern of
growth; D3 ⫽Export potential; D4 ⫽Periodically Increase in demand; D5 ⫽Brand value; D6 ⫽New investment in the region; D7 ⫽Distribution channel; D8 ⫽
Bureaucracy and control; D9 ⫽Service efciency level; RS1 ⫽Level of technology up- gradation; RS2 ⫽Quick information ow; RS3 ⫽Shared technology
development; RS4 ⫽Level of active work of relevant civil societies; RS5 ⫽R&D investment; RS6 ⫽Suppliers and distribution channel; RS7 ⫽Marketing support;
RS8 ⫽Relations with research and development institutes; FS1 ⫽Boost innovation; FS2 ⫽Level of marketing innovation; FS3 ⫽Level of quality management
practices; FS4 ⫽Information ow with rm; FS5 ⫽Quality awards; FS6 ⫽Internal structure; FS7 ⫽Geographic concentration; FS8 ⫽Quality of suppliers; GC1
⫽Financial support system; GC2 ⫽Environmental regulation; GC3 ⫽R&D support; GC4 ⫽Training facilities; GC5 ⫽Industrial land allocation; GC6 ⫽Labor
Laws; GC7 ⫽Impact of national culture; GC8 ⫽Business climate; GC9 ⫽Formal and informal rules
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represents 10 per cent. We added its effect into actual score obtained by an individual casual
variable of various determinants.
4. Case study design
4.1 Design of research instrument
The research data were obtained by using the questionnaire as the data collection method
(Appendix). The survey questionnaire was designed using extant review of literature which
consists of 49 items thus covering all inuencing factors which may affect competitiveness in
MSMEs. The draft instrument was sent to ve (three academics and two industrial)
practitioners working in this eld. Inputs from academicians, consultants and practitioners
from industries were used to modify it. Each participant was asked to evaluate the
instrument for the readability, bias, understanding ability, ambiguous items and
appropriateness of each item in relevance to the MSMEs. The feedback received was
incorporated to make the questionnaire more relevant for the purpose. Based upon their
suggestions, items were modied, and a total number of items reduced to 43. Further, a pilot
test of the instrument was accomplished, and suggestions from 15 recognized MSMEs were
incorporated. The instrument comprises a non-comparative-itemized rating scale utilizing a
ve-point Likert-scale.
4.2 Survey administration
4.2.1 Interviewee selection process, respondents and company proles. The interviewees were
selected from the companies working in four key industrial clusters (Kangra, Una, Sirmaur
and Solan) in the state of Himachal Pradesh. Before choosing the study respondents, we
ensured that the respondent has the necessary knowledge to respond. We targeted single
well-informed respondents from each sampled company. The respondents included the
quality managers, plant managers, engineering managers, CEOs or the personnel with
management responsibility. Because a rm’s specic competitive strategy maker requires a
company-wide focus, we assume that these informants had a good understanding of the
competitive strategies formation, implementation and its outcomes on their companies. The
proles of the respondents and companies embraced in this study are displayed in Table IV.
Table IV.
Details of respondents
and companies
proles
Demographic
information Work prole (%)
Working
experience (Years) Education prole (%)
Respondent
prole
Quality manager 30.54 10-15 PhD degree 5
Plant manager 32.24 20-40 Post-graduate 24
Production Manager 19.15 15-20 Graduate 43
Engineering Manager 18.07 10-15 Under-graduate 28
Total 100 Total 100
Category (%) Sectors of operation
Sector-wise unit
to be surveyed
No. of useful
responses
Company proles Micro 24 Automobile 94 60
Electrical and Electronics 86 60
Small 45 Food 64 34
Pharmaceutical 102 79
Medium 31 Textile 35 09
Total 100 Total 381 242
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Respondents were asked to evaluate their expectations on a ve-point scale ranging between
degrees of strong disadvantage and strongly advantage with a neutral point in the middle.
Although it was planned to access the whole sample population (n⫽381), only 242 of them
(180 face to face interviews, 39 online and 23 postal) were found appropriate, which yield the
response rate by 63.52 per cent; in authors opinion, this is a sufcient number for further
analysis (Fumo and Jabbour, 2011;Sharma and Kharub, 2015). The period of making
personal visits and collecting data took around one year for 242 responses. Each company
visit lasted on an average one hour for the interview.
4.3 Exploratory factor analysis
The result of KMO test was found adequate as 0.84 which is greater than 0.60, which
indicates sufcient inter-correlations and also the Barlett’s test of sphericity was found
signicant as
2
⫽63, 52.95; p⫽0.000 ⬍0.01 (Das et al., 2008). Table V summarizes the
results of factor analysis and Cronbach’s
␣
for various constructs of competitiveness, as the
factor analysis explains a large number of variable in terms of their common underlining
construct. Out of total 43 items, 2 were eliminated: item number 9 (i.e. IPR and patents) from
factor conditions and item number 8 (i.e. Relations with research and development institutes)
from related and supporting industries (Tables III and V), through exploratory factor
analysis, those with Eigen value ⬍1. For interpretation of the factor relation to sample size,
only those items which have factor loading greater than 0.5 was included (Hair et al., 1998).
Those values are shown in italic in Table V were found appropriate and proceeded (total 41
items) for further analysis.
4.3.1 Reliability check. It can be measured in several ways; in this study, the authors follow
the internal consistency method and calculate reliability coefcient Cronbach’s
␣
. This is
most widely used reliability estimate in the empirical research (Conca et al., 2004). Cronbach’s
␣
computes internal reliability among a group of items combined to form a single scale. In
this respect, Nunnally (1978) advocates that newly developed measures can be accepted with
a minimum recommended Cronbach’s
␣
value more than 0.6; otherwise, 0.7 should be the
threshold (Jitpaiboon and Subba Rao, 2007).
For this purpose, we calculate the reliability for each set of items under all ve
determinants of Porter model as presented in Table V. As a result of condence analysis, the
value of Cronbach’s
␣
is found as 0.715 ⬍
␣
⬎0.831, which indicates that the scale is
signicant and reliable (Das et al., 2008;Spasojevic Brkic et al., 2013).
4.4 Diamond axes
In the following paragraphs, the main ndings of the study are presented by comparing the
diamonds axes score obtained from four main determinants of Porter model. MSMEs
operating in the pharmaceutical, electrical and electronics, automobile, food and textile
sectors were considered and individual diamond’s axes dimensions related to various
determinants were calculated. Afterward, the diamond surface areas for different sectors
were calculated and analyzed.
The descriptive results are presented in Table VI, and Figure 3(a) to (e) present the details
about ndings related to diamond axes.
4.4.1 Pharmaceutical sector. With emerging competitiveness and entrepreneurial skills,
this MSME sector is conspicuous by the large presence of private sector and has captured a
substantial share of the domestic and external market. The sector’s score in factor conditions
is 8.155, which indicates its strength, especially in advance factors conditions such as high
technology, types of equipment, skilled human and knowledge resource. This sector
produces a wide range of drugs to meet high demands, from different segments of
consumers, including USA and European, as revealed by its high score (8.775) in demand
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Table V.
Related factor loading
and reliability check of
various casual
variables
Determinants Casual variables 123456789Cronbach’s
␣
Factor conditions Basic factors 0.914 0.936 0.738 0.820 0.038 0.010 0.446 0.449 0.491 0.831
Advance factors 0.093 0.146 0.158 0.151 0.917 0.912 0.662 0.917 0.093
Demand conditions Market value 0.888 0.825 0.834 0.586 0.544 0.091 0.070 0.243 0.333 0.812
Sophistications 0.033 0.177 0.217 0.213 0.159 0.785 0.762 0.732 0.579
Related and supporting industries Related companies 0.855 0.785 0.655 0.188 0.409 0.329 0.160 0.409 – 0.715
Support 0.058 0.181 0.169 0.755 0.673 0.624 0.605 0.259 –
Firm strategy, structure and rivalry Rivalry 0.764 0.744 0.708 0.678 0.663 0.134 0.178 0.089 – 0.771
Structure/strategy 0.042 0.164 0.066 0.242 0.118 0.850 0.837 0.708 –
Government and culture Government support 0.925 0.811 0.762 0.767 0.715 0.750 0.246 0.145 0.122 0.772
Culture 0.160 0.169 0.206 0.228 0.216 0.120 0.834 0.797 0.673
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conditions. Further, the very high score in third and fourth determinants (i.e. 9.125 and 8.705,
respectively) indicates high competitive advantage from supporting industries, strategies of
distributions of resources in downstream rms which manufacture pharmaceutical
machinery and types of equipment.
4.4.2 Electrical and electronics sector. In the recent years, the electronic industry is also
growing at a brisk pace. The high value of second determinant (8.275) shows the increasing
requirement of electronics goods in the Indian market. The sector shows average scores in
rst, third and fourth determinants 6.035, 5.980 and 6.820, respectively, which shows
challenges with respect to manpower with required skills, overall support from related
industries and understanding of rms regarding the importance of strategy making in
perspective of current market scenario.
4.4.3 Automobile sector. Followed by high population with medium income, demand in
this sector is constantly increasing from past few decades. Practicing of quality
management philosophies such as, 5S and Housekeeping, TPM, etc. in the automobile
sector have provided a boost to improve quality in this sector as evident from the
moderate score in all four determinants as given in Table VI and Figure 3(c). Availability
of required skilled and unskilled manpower (6.950) is one of the important variables
under factor conditions which need to be addressed to improve competitiveness of this
sector. Further, as Indian is a developing economy, study results indicates that the
demand for automotive is also steadily increasing (6.690). Strong supply chain network
and rm strategy to meet upcoming demands were found appreciable as indicated by
medium score 6.700 and 6.900, respectively.
4.4.4 Food sector. After pharmaceutical, the food sector shows high growth in India,
especially in this region. This sector establishes a vital linkage and synergy between the two
pillars of the Indian economy: industry and agriculture. The high demand condition (8.305)
shows the enormous growth potential of this sector. The high value of related and supporting
industries (8.110) shows the raising agriculture yield, enhancing productivity, creating
employment and raising life-standard of a large number of people across the country,
especially those in rural areas. Furthermore, Table VI shows the high (7.450) and moderate
(6.170) score obtained by the sector in remaining two determinants: factor conditions and
rm strategy, structure and rivalry, which shows the ability of this sector to be sustained
with high competitive advantage for a long period of time.
Table VI.
Descriptive results
Serial
no. Determinants Casual variables Pharmaceutical
Electrical
and
electronics Automobile Food Textile
1 Factor conditions
(maximum 10)
Basic 7.75 5.03 7.69 8.69 5.22
Advance 8.56 7.04 6.21 6.21 4.20
Sum 8.155 6.035 6.950 7.450 4.710
2 Demand conditions
(maximum 10)
Market value 8.79 8.90 6.34 8.79 7.12
Sophistication 8.76 7.65 7.04 7.82 8.25
Sum 8.775 8.275 6.690 8.305 7.685
3 Related and supporting
industries (maximum
10)
Related
companies
9.57 6.82 6.22 7.69 4.24
Support 8.68 5.14 7.18 8.53 4.32
Sum 9.125 5.980 6.700 8.110 4.280
4 Firm strategy, structure
and rivalry (maximum
10)
Rivalry 8.67 7.28 7.57 6.05 6.65
Structure/strategy 8.74 6.36 6.23 6.29 6.54
Sum 8.705 6.820 6.900 6.170 6.595
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Firm stategy, structure and rivalry (1-10)
(a) Pharmaceutical sector
Factor conditions
(1-10)
Demand conditions
(1-10)
Related and supporting industries (1-10)
Firm stategy, structure and rivalry (1-10)
(b) Electrical and Electronics sector
Factor conditions
(1-10)
Demand conditions
(1-10)
Related and supporting industries (1-10)
Firm stategy, structure and rivalry (1-10)
(c) Automobile sector
Factor conditions
(1-10)
Demand conditions
(1-10)
Related and supporting industries (1-10)
Firm stategy, structure and rivalry (1-10)
(d) Food sector
Factor conditions
(1-10)
Demand conditions
(1-10)
Related and supporting industries (1-10)
Firm stategy, structure and rivalry (1-10)
(e) Textile sector
Factor conditions
(1-10)
Demand conditions
(1-10)
Related and supporting industries (1-10)
Notes: (a) Pharmaceutical sector; (b) Electrical and electronics sector;
(c) Automobile sector; (d) Food sector; (e) Textile sector
Figure 3.
(a) to (e) Diamond axes
for various industrial
sectors
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4.4.5 Textile sector. This sector is facing competition in productivity, delivery schedule, the
reliability of products and other such intangible factors such as the image of the country/
company and brand quality. This sector shows low score in factor conditions and support
from related industries, i.e. 4.710 and 4.280, respectively, whereas, owing to high demand
conditions (7.685), this sector shows tremendous scope for new technology, brands and
quality products through new competitive strategy development. Overall, the study results
found competitively small diamond (see Figure 3) for textile sector.
4.5 Diamond surface areas
After reporting the main ndings for each dimension of the diamond separately, the authors
analyzed the diamond surface areas for all industrial sectors considered in the study. The
diamond surface area is calculated by summing up the individual areas of each quadrant’s
triangle as shown in Table VII.
Porter suggested that a large diamond represents high competitiveness and a small
diamond represents low competitiveness (Dogl et al., 2012). The overall surface area of the
pharmaceutical sector is very high as 150.931; it shows its high competitive positioning
among other sectors as shown in Figure 4. The high growth of the pharmaceutical sector has
attracted global players to the region, and leaders, such as Ranbaxy Laboratories Ltd., Dr
Reddy’s, Sun pharmaceutical, Cipla Ltd. and many more, have made large investments to
access the market. The overall surface area of electrical and electronics and automobile
sector is found moderate, i.e. 91.584 and 92.752, respectively. This is because of the
Table VII.
Diamond surface area
Quadrant triangle P E&E A F T
ASD ⫽rm strategy, structure and rivalry ⫻1/2
demand conditions 38.193 28.218 23.081 25.621 25.341
ARD ⫽related and supporting industries ⫻1/2
demand conditions 40.036 24.742 22.412 33.677 16.446
ARF ⫽related and supporting industries ⫻1/2
factor conditions 37.207 18.045 23.283 30.210 10.079
ASF ⫽rm strategy, structure and rivalry ⫻1/2
factor conditions 35.495 20.579 23.978 22.983 15.531
Sum (units) 150.931 91.584 92.752 112.491 67.398
Notes: ⬎P⫽pharmaceutical; E&E ⫽electrical and electronics; A ⫽automobile; F ⫽food; T ⫽textile
Figure 4.
Sector wise diamond
surface area MSMEs
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consequent effect of low score in the third determinant of the diamond model. The high
surface area in food sector, i.e. 112.491, shows potential scope for R&D, new food-technology
development, investments in new projects and indicates the environment for quicker
development in this sector. The food industry has started producing many new items such as
ready-to-eat food, beverages, processed and frozen fruits and vegetable products, marine and
meat products, etc. The Indian consumer is being fast introduced to newer high-quality food
products made by using the latest state-of-the-art technology, which is also giving the
industry a competitive edge. One big threat to this sector would be China because, from past
few decades, China has upgraded its technology faster than India and exporting appreciable
higher good as compared to India.
The low score of Porter’s diamond model surface area (67.398) in textile sector shows that
this sector required structural reforms. Indian textile and clothing sector have a tremendous
potential, only a portion of which has been exploited because of policy constraints. However,
there lies a considerable potential that has not been exploited primarily because of government
policy, limited nancial resources and lack of entrepreneurship skills in the region. Because
garment manufacturing is reserved for small-scale industries in India, catering to the small size,
they cannot create competitive products. In India, most of the textile mills are organized one, but
the demand for Indian garments overseas is fashion-driven.
5. Conclusion and future direction
The erce competition arising out of globalization and liberalization is forcing companies
across the world to realize that it is a rm’s competitive advantage that allows it to
outperform its competitors. It is high time that MSMEs must wake up and identify the
drivers of competitiveness at respective locations and develop cutting edge strategies to
create a sustainable competitive advantage. Creating a sustainable competitive advantage
may be the most important goal of any organization and may be the most important single
attribute on which each rm must place its most focus. This study is undertaken among ve
leading sectors of MSMEs located in the state of Himachal Pradesh of India with an aim to
nd out factors which affect the competitiveness of these sectors using Porter’s diamond
framework. To achieve the aim of this study, a reliable and valid instrument has been used.
In response to RQ1 and RQ2, the study results found that there are total 41 critical factors
which inuence the competitive ability of a rm, and, by carefully investigating these
factors, current competitive positioning can be assessed. In response to RQ3 and RQ4, the
competitive position of various MSME sectors are found in the order as: pharmaceutical
sector, food sector, automobile sector, electrical and electronics sector and textile sector.
The results have implications for managers of the rms, both operating in these
mentioned sectors and also the ones who are planning to enter. By reviewing the results of
this study, it is observed that competitiveness among MSME sectors is mostly affected by
intangible resources which are difcult to imitate by competitors, the demand conditions
followed by rm strategy, structure and rivalry and supporting industries. Moreover, the
diamond axes indicate signicant difference with respect to determinants, within various
MSME sectors which can help the managers to perform strength, weakness, opportunities
and threats analysis and focus on those areas where they have strengths and to introduce
corrective measures to overcome potential weaknesses. For instance, in the textile sector, the
determinants such as factor conditions and related and supporting industries scored 4.710
and 4.280, respectively, which needs to be strengthened as this sector stands at last position
with a minimum surface area of 67.398. To ascertain competitive advantages, disadvantages
and opportunities thereof, with respect to various MSME sectors, the results of the study are
summarized in Table VIII.
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These results are consistent with the studies conducted by Oz (2002),Shee and Momaya
(2001),Ajitabh and Momaya (2004),Saru (2007),Rugman and Oh (2008),Singh et al. (2008),
Nanda and Singh (2009),Chandamoyo and Dumbu (2012) and Uddin and Bose (2013).
Thus, the major contribution of the study is not only to understand the factors on which
competitiveness of various MSME sectors depend upon but also to study the applicability of
Porter diamond model framework in general and to ascertain competitive advantages,
disadvantages and opportunities with respect to MSME sectors. Moreover, like most of the
previous research, this study is based on the assumptions that the scores for determinants
lead to competitive advantage (Dogl et al., 2012;Deniz et al., 2013), and, as such, the factors
which have low scores should be analyzed in detail to gain competitiveness. Also, further
research should focus on considering social and culture inuences, policy to address social
and environment objectives and effects of geographic locations of rms as key determinants
of company prosperity, which in author’s opinion are important factors to affect the business
climate. Additionally, work from other leading sectors such as telecommunications, mining,
Table VIII.
Current status of
porter’s diamond of
the Indian MSMEs
Diamond
determinants Competitive advantage
Competitive
disadvantage Opportunities
Factor conditions Skilled human resource
Availability of local labor
Production and process
technology
Low initial investment
Investor protection
Availability of nancial
service
Quality of overall
infrastructure
Contractual labor
Lack of funding for
in-house-research
initiative
Employment opportunities for
weaker section of society
Training opportunities at
several government institute
and big rms
Demand
conditions
Market size
Different segments of
buyer
Number of procedure to
start a business
Degree of customer
orientation
Poor investment in
R&D
Lack of marketing
knowledge
Increasing demand growth in
each sector
Increase curiosity toward new
products
Related and
supporting
industries
Presence of international
competitive front-end
industries that effectively
coordinate global supply
chain management
Effective communication
Rapid movement of ideas
Local supplier quality
Local supplier quantity
State of cluster
development
Have greater learning
opportunities by collaborating
with large scale units and
institutes such as IITs, IIMs
NITs, etc.
Firm strategy,
structure and
rivalry
Functional and exible
management
High level of commitment
High ownership feeling
Quality of math and
science educations
High specic return
Firm-level technology
absorption
Capacity for innovation
Little career planning
for employee
Little formal training
program
Participation by entrepreneurs
in international trade can lead
to diversication of markets
Implementation of advance
quality tools cum techniques
Government and
culture
Central excises exception
General government debt
Bureaucratic hurdle in
obtaining government
support
Not properly dene
nancial strategy and
corruption
Transparence in government
policies, Single window
Clarence system, Tax benets,
reservation of production for
MSMEs
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machinery, iron and steel manufacturing plants can be analyzed, and multiple case studies,
in this respect, should be considered.
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Appendix
SECTION-A
GENERAL INFORMATION
Q.I Name of the company.................................................................................................
Postal Address…………………………………………………………….......
Pin Code:
Phone Number (With STD Code)
Fax Number With Code
Website:
Q.II Details of the contact person filling questionnaire.
Name and Designation……………………………………………………...............
Phone Number (With STD Code)
Mobile Number
Email Address:
Q.III Company Type and Year of establishment Please tick (.√) appropriate Box.
Private Ltd. Government Joint Venture Others
Year of Establishment: ……………………………………...
Q.IV Category of firm
Micro Scale Unit Small Scale Unit Medium Scale Unit
Q.V Work Profile of respondent
(i) Name and Designation.....................................................................................
(ii) Educational Qualification................................................................................
(iii) Working experience ........................................................................................
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SECTION – B
INFORMATION ON COMPETITIVENESS
Please tick the appropriate boxes representing variables to measure competitive positioning in your company on 1- 5
scale with 1 - Strongly disadvantage, 2 - disadvantage, 3 - Neither advantage-Nor disadvantage, 4 - advantage and
5 - strongly advantage
avyxorPstnanimreteD 54321selbair
Factor conditions
Natural resources
Physical resources
Unskilled labor
Skilled Labor
Production and process technology
Scientific and technological information
Capacity utilization
Communication infrastructure
IPR and patents
Demand conditions
dnamedcitsemodfoeziS
htworgfonrettaP
laitnetoptropxE
dnamedniesaercniyllacidoireP
eulavdnarB
noigerehtnitnemtsevniweN
lennahcnoitubirtsiD
lortnocdnaycarcuaeruB
levelycneiciffeecivreS
Related and supporting
industries
noitadarg-puygolonhcetfoleveL
wolfnoitamrofnikciuQ
tnempolevedygolonhcetderahS
Level of active work of relevant civil societies
tnemtsevniD&R
lennahcnoitubirtsiddnasreilppuS
troppusgnitekraM
Relations with research and development institutes
Firm strategy,
structure,and rivalry
noitavonnitsooB
noitavonnignitekramfoleveL
secitcarptnemeganamytilauqfoleveL
mrifhtiwwolfnoitamrofnI
sdrawaytilauQ
erutcurtslanretnI
noitartnecnoccihpargoeG
reilppusfoytilauQ
Government
and culture
metsystroppuslaicnaniF
noitalugerlatnemnorivnE
troppusD&R
seitilicafgniniarT
noitacolladnallairtsudnI
swaLrobaL
erutluclanoitanfotcapmI
etamilcssenisuB
selurlamrofnidnalamroF
Corresponding author
Manjeet Kharub can be contacted at: manjeetkharub@gmail.com
For instructions on how to order reprints of this article, please visit our website:
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