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Journal of Manufacturing Technology Management
A comparative evaluation of manufacturing flexibility adoption in SMEs and large
firms in India
Ruchi Mishra
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large firms in India", Journal of Manufacturing Technology Management, Vol. 27 Iss 5 pp. 730 - 762
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A comparative evaluation of
manufacturing flexibility
adoption in SMEs and large
firms in India
Ruchi Mishra
Department of Operation Management,
National Institute of Industrial Engineering, Mumbai, India
Abstract
Purpose –The purpose of this paper is to analyse and compare the status of manufacturing flexibility
adoption, its barriers and adoption practices in small and medium-sized enterprises (SMEs) and large
firms in India.
Design/methodology/approach –Using mixed methods sequential explanatory design, this study
employs survey responses from 121 firms, followed by 16 semi-structured interviews to investigate
and explain the status of manufacturing flexibility adoption, barriers to adoption and practices
adopted to achieve flexibility in SMEs and large firms in India.
Findings –The study suggests that awareness of manufacturing flexibility concept in SMEs is
considerably low and application of manufacturing flexibility is still at embryonic stage. It was found
that both SMEs and large firms employ manufacturing flexibility, but they differ with respect to their
emphasis on adoption practices used to achieve flexibility. SMEs emphasize entrepreneurial
orientation and flexible human resource practices to achieve flexibility, whereas large firms emphasize
practices such as technological capability, sourcing practices and integration practices to achieve
flexibility. The study also illustrates barriers that hinder manufacturing flexibility adoption at plant
level in India.
Research limitations/implications –The study is cross-sectional in nature and is limited to
specific regions of India. The use of subjective measures in survey questionnaire is another limitation
of the study.
Practical implications –Practitioners should consider combinations of adoption practices to
achieve the desired level of manufacturing flexibility. It is also important to give due consideration to
barriers before considering manufacturing flexibility adoption.
Originality/value –The findings contribute to the manufacturing flexibility and SMEs research by
providing insights into manufacturing flexibility adoption from the developing economy perspective
and by widening the scope of existing research into SMEs.
Keywords Manufacturing performance, Implementation, Strategy,
Small and medium-sized enterprises, Manufacturing flexibility
Paper type Research paper
1. Introduction
Business environment has considerably changed from “mass production”to “lean
manufacturing”and “mass customization”over the years. Several authors have
recognized manufacturing flexibility as an important strategic competitive capability
helping firms achieve mass customization. The strategic importance of manufacturing
flexibility has motivated this study, which concerns status of manufacturing flexibility
adoption, its barriers and adoption practices in small and medium-sized enterprises
(SMEs) and large firms in India. Since, SMEs differ from large firms in terms of
business model, organizational design, operating conditions and management style,
Journal of Manufacturing
Technology Management
Vol. 27 No. 5, 2016
pp. 730-762
© Emerald Group PublishingLimited
1741-038X
DOI 10.1108/JMTM-11-2015-0105
Received 26 November 2015
Revised 17 May 2016
Accepted 20 May 2016
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1741-038X.htm
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this study offers an opportunity to understand the underlying differences between
SMEs and well-established large firms with respect to manufacturing flexibility
adoption. Further, from an operational point of view, this study explores validity of
manufacturing flexibility concepts in the context of a developing economy.
The motivation of this study is based mainly on the following research gaps
identified from existing literature on manufacturing flexibility and SMEs:
(1) Manufacturing flexibility has widely been considered as a competitive
capability in the manufacturing strategy literature, but there is a little empirical
evidence to suggest so in the context of developing economies like India.
(2) Majority of the manufacturing flexibility studies has focused on definition,
measurement and the relationship between manufacturing flexibility and its
drivers and enablers. However, there are very few studies available on various
manufacturing flexibility adoption concerns such as flexibility awareness, its
adoption rate, barriers to its adoption, and practices applied for achieving
manufacturing flexibility.
(3) Studies done in SMEs context have focused on a wide range of topics such as
marketing (Poolton et al., 2006), strategy (Raymond and Bergeron, 2008;
Galbraith et al., 2008; Hilmola et al., 2015), supply chain (Thakkar et al., 2011,
2012; Lenny Koh et al., 2007; Awais et al., 2014), performance (Hilmola et al.,
2015) innovation (Laforet, 2011; Rujirawanich et al., 2011), quality management
(QM) practices/six sigma (Temtime, 2003; Thomas and Barton, 2006; Kumar
et al., 2014), lean implementation (Dora et al., 2014; Panwar et al., 2015),
enterprise resource planning (ERP) implementation (Lenny Koh and Simpson,
2005), advanced manufacturing technologies (Raymond, 2005; Raymond and
St-Pierre, 2005; Dangayach and Deshmukh, 2005). However, very few SMEs
studies deals with the flexibility-related concept. Also, differences between
SMEs and large firms with respect to flexibility adoption practices have not
been much explored.
This study fills these gaps by investigating current status of manufacturing flexibility
adoption, barriers to adoption and differences in manufacturing flexibility adoption
practices in SMEs and large firms. More specifically, the objectives of this study are
presented as follows:
(1) to explore familiarity of Indian manufacturing firms with respect to
manufacturing flexibility concepts, usefulness of these concepts and any
initiative being taken to achieve flexibility;
(2) to explore barriers to adoption of manufacturing flexibility in Indian firms; and
(3) to explore and compare extent of manufacturing flexibility adoption in SMEs
and large firms and also investigate ranking of these adoption practices.
This study contributes to the manufacturing flexibility literature by advancing
academic knowledge on flexibility adoption. The contribution of present study is
manifold. First, this study provides a comparative evaluation of SMEs and large firms
with respect to their familiarity with manufacturing flexibility concepts and usefulness
of these concepts in achieving competitive advantage. Second, the study
ranks flexibility adoption practices with respect to their importance for SMEs and
large firms. Third, the study highlights barriers to manufacturing flexibility adoption
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in Indian firms. The knowledge of these barriers will assist practitioners in
manufacturing flexibility adoption.
The rest of the paper is organized as follows: Section 2 briefly describes studies
conducted in the context of SMEs. Section 3 provides theoretical background of this
study. Section 4 describes research methodology and Section 5 presents results and
findings of this study. Discussion on findings of the study is given in Section 6.
Conclusion, limitations and future works are presented in Section 7.
2. The studies done in SMEs context
SMEs segment has recently received wide attention by several authors and
practitioners. A large number of studies have been done in the context of SMEs to
investigate the different aspects, such as manufacturing practices, technology,
workforce, financing, marketing, supply chain (Thakkar et al., 2012; Awais et al., 2014;
Kafetzopoulos et al., 2015; Hilmola et al., 2015). Temtime (2003) reported that majority of
SMEs is aware of the importance of TQM and planning activities. The study found that
size of the SMEs and the level of planning positively influence TQM practices. Various
studies examined the implementation of several manufacturing practices, such as lean,
QM practices –TQM, six sigma, ISO 9000, 9001 in SMEs. In a comparative study of
Australian and UK SMEs, Kumar et al. (2014) observed that low level of six sigma
adoption in manufacturing SMEs. They concluded that ISO 9000 is the most popular
among QM initiatives. The study further suggests that leadership is critical to the
success of any QM practices. Similar to this, Dora et al. (2014) examined the status of
lean manufacturing practices, their benefits and barriers among European food
processing SMEs. In a recent study, Kafetzopoulos et al. (2015) found that ISO 9001
directly affects quality of products and operational performance and indirectly affects
business performance of firms through moderating influence of operational
performance. Several studies have examined different technological aspects, such as
its present status, antecedents, relationship with performance, evaluation and
prioritization, in SMEs. Dangayach and Deshmukh (2005) conducted an exploratory
study on advanced manufacturing technology (AMT) in Indian SMEs. The various
aspects of AMT, i.e. status, preferred AMT, competitive criteria, implementation
criteria and degree of investments in AMTs were explored. The study reported that
Indian SMEs give highest priority to quality aspect of whereas flexibility aspect is
given least priority while implementing AMT. Further, more attention is given to
indirect AMT and administrative AMT than direct AMT. Similar to this, Raymond and
St-Pierre (2005) investigated antecedents and performance outcomes of advanced
manufacturing system (AMS) sophistication in the context of SMEs. The antecedents
of AMS involve strategic orientation of firms, education and experience of owner
manager and type of production and commercial dependency of firms. The study also
concluded that AMS sophistication affects both operational and business performance
of Canadian SMEs. Raymond (2005) concluded that increased critical success factors
(CSF) and AMT assimilation level directly improve performance level, whereas
mismatch between CSF and AMT negatively affects performance. Further, Lenny Koh
and Simpson (2005) found that ERP can improve agility and responsiveness to change
in SMEs but due to stochastic and unpredictable nature of uncertainty, ERP cannot
always ensure responsiveness to uncertainties.
In recent studies, authors have focused on innovation aspects in SMEs. A range of
business-related factors govern innovation in SMEs. Using a grounded theory
approach, Laforet (2011) explored the drivers and outcomes of innovation in SMEs
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from firms’perspective. The drivers of innovation include market-, business- and
customer-related factors, such as technological change, competitive pressure in
domestic and international markets, uncertainty in the market place, business growth,
profit margin, desire for quality of products and CEOs desire for success and improve
working condition. Once implemented, innovation has mixed influences on operations
of SMEs. Some of the positive results of innovation include operational excellence,
improved image and reputation, better working conditions, satisfied customers and job
fulfilment. On the other hand, adverse outcomes of innovation involve higher chances
of failure, employee dissatisfaction, and high turnover of work force. In a more
recent study, Liao and Barnes (2015) examined the link between knowledge acquisition
and innovation performance in SMEs. The study found that acquiring knowledge
from outside firms, such as suppliers’involvement in joint problem solving, new
product development process, planning and continuous improvement programs
significantly influence product innovation flexibility in SMEs. The study further adds
that knowledge acquisition acts a relationship mediator between information
capability, relationship quality and product innovation flexibility. Several other
studies in SMEs literature also focused on applications, implementation and impact of
new concepts, different strategies, tools and the influence of firms’specific variables.
Table I presents some of the manufacturing and supply chain-related studies
conducted in SMEs context.
Despite, a wide range of studies in SMEs context, the manufacturing flexibility
concept has not been much explored in SMEs. In detailed review, Singh et al. (2008)
suggested several gaps in the literature, including “need to compare SMEs and large-
scale enterprise in terms of operations management issues”. In this regard, this study
addresses various concerns, such as familiarity, usefulness and barriers to adoption
and compares manufacturing flexibility adoption practices in SMEs and large firms.
3. Theoretical background
The study employs purposive search strategy using keywords, “manufacturing
flexibility”,“implementation”,“adoption”,“antecedents”,“enablers”to confine the
search results. Highly cited papers and book chapters were incorporated. To provide a
better understanding of manufacturing flexibility adoption, this section briefly outlines
manufacturing flexibility concepts and describes various adoption practices applied by
firms to achieve flexibility.
3.1 Manufacturing flexibility
The strategic importance of manufacturing flexibility is well-recognized (Hayes and
Wheelwright, 1984; Gerwin, 1987; Slack, 1988). A broad range of studies have highlighted
the significance of manufacturing flexibility in an uncertain environment. Manufacturing
flexibility refers to the ability of a manufacturing firm to respond to environmental
changes. Extensive literature review on manufacturing flexibility described various
types of flexibility. Upton (1994) suggested 15 general types of flexibility and broadly
classified these flexibilities into internal and external flexibility. Internal flexibility is not
directly related to market except its effect provides customer benefits. On the other hand,
external flexibility improves competitive position of firms within an industry. Customers
directly recognize external flexibility. Out of several types of manufacturing flexibility,
volume flexibility and product mix flexibility are the two most widely used
manufacturing flexibility types (Oke, 2005; Mishra et al., 2014a, b). Volume flexibility is
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Author(s) Methodology Purpose of the study
Kafetzopoulos et al. (2015) Survey, 287 SMEs, Greece Measured the impact of ISO 9001 effectiveness on three dimensions of a firm’s performance,
namely, product quality, operational performance and business performance
Hilmola et al. (2015) Survey, 244 SMEs Finland Examined manufacturing strategy priorities and their performance implications
Panwar et al. (2015) Survey, 120 SMEs India Investigated the current status, reasons and challenges of lean manufacturing in all Indian
process industries including SMEs and large firms
Lechner and Gudmundsson
(2014)
Survey, 335 firms, Iceland Investigated relationship between entrepreneurial orientation and competitive strategy and
the effect of competitive strategy on firm performance
Kumar et al. (2014) Survey, 92 Australian+64 UK
firms
Assessed and compared the status of quality management practices in the manufacturing
SMEs in Australia and the UK
Guo and Cao (2014) Survey, 166 SMEs, China Proposed a contingency framework to address conditions impact of strategic flexibility on
firm performance in emerging economies context
Zeinalnezhad et al. (2014) Interview, 20 Malaysian SMEs
and large firms
Explored the present status, benefits and difficulties of lead benchmarking implementation
and lead performance indicators between Malaysian SMEs and
large firms
Dora et al. (2014) Survey, 35 SMEs, Europe Explored the status of the lean manufacturing practices and their benefits and barriers
among European food processing SMEs
Urban and Mothusiwa (2014) Survey, 133 SMEs, South
Africa
Measured the relationship between planning flexibility, entrepreneurial orientation and
firm performance
Awais et al. (2014) Survey, 170 SMEs Canada and
Pakistan
Compared supply chain strategy, flexibility and performance relationships between
Canada and Pakistan
Chiarini (2012) Case study, Italy Purpose was to investigate whether activity-based costing (ABC) and value stream
accounting are suitable for lean production
Thakkar et al. (2012) Case study, India Investigated supply chain issues in SMEs
Laforet (2011) Grounded theory, interviews,
UK
Examined innovation in SMEs and their impact on financial performance
Rundh (2011) Survey, 212 SMEs, Sweden Examined how small and medium-sized firms (SMEs) meet market needs in their export
marketing strategy (EMS)
Gaur et al. (2011) Survey, 315 SMEs India Examined the relationship between market orientation and manufacturing performance
in SMEs
(continued )
Table I.
Manufacturing and
Supply chain-related
empirical studies in
SME context
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Author(s) Methodology Purpose of the study
Rujirawanich et al.(2011) Case study, single Thailand Investigated understanding of innovation concept, process and examined how five factors
associated with innovation interact with each other
Thakkar et al. (2011) Multiple case study, India Developed a mapping framework for evaluating supply chain learning potential for the
context of SMEs
Bahri et al. (2011) Survey, 108 SMEs, Canada Developed performance measurement and management system for small- and medium-
sized enterprises
Raymond and Bergeron (2008) Survey, 107 SMEs, Canada Investigated relationship between of e-business capabilities and business strategy
Galbraith et al. (2008) Survey, 44 SMEs, Scotland Explored the relationship between firms’location-related decision and competitive strategy
in high-tech manufacturing firms
Lenny Koh et al. (2007) Survey, 203 SMEs, Turkey Identified relationships among SCM practices, operational performance and SCM-related
organizational performance
Poolton et al. (2006) Case study, UK Applied agile manufacturing concept into marketing strategy, planning and management,
in the context
Thomas and Barton (2006) Case study, UK Developed a strategic framework for widespread use of six sigma in SMEs
Dangayach and Deshmukh (2005) Survey, 122 SMEs, India Assessed the status competitive priorities, degree of investment, implementation steps of
AMT
Raymond and St-Pierre (2005) Survey, 248 SMEs, Canada Explored the level of AMS sophistication, relationship of SMEs characteristics with AMS
sophistication and impact of AMS sophistication on operational and business performance
Raymond (2005) Survey, 118 SMEs, Canada Examined the relationship among environmental uncertainty, operations management,
critical success factors, AMT and operational performance
Lenny Koh and Simpson (2005) Mixed methodology survey
and interviews 108 SMEs
Examined the responsiveness and agility of ERP systems to change and uncertainly and
identified the nature of change and uncertainty
Walker and Brown (2004) Survey, 290 small business
owners, Australia
Examined success factors for small business owners
Temtime (2003) Survey, 54 SMEs Botswana Investigated relationship between TQM, planning behaviour and firm size
Gunasekaran et al. (2000) Case study, England Identified potential areas for cost savings from productivity gain and implementation
issues associated with productivity improvement strategies in a small company
Table I.
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required to deal with variations in demand caused due to changes in quantity
demanded whereas product mix flexibility is required to cope up with the
variations in demand caused due to changes in nature of products demanded
(Camisón and López, 2010). This study is concerned with the volume and product mix
aspects of manufacturing flexibility. The study defines manufacturing flexibility as
“the ability to deploy and redeploy resource efficiently to deal with variability in demand
caused due to variations in quantity demanded and nature of products demanded”
(Duguay et al., 1997). The proposed definition is adopted from the definition given by
Camisón and López (2010).
3.2 Manufacturing flexibility adoption practices in firms
The concept of mass customization emerged in the late 1980 as the market demand for
product varieties increased substantially (Pine, 1993). Mass customization can be
viewed as a system that delivers a wide variety of products and services to meet the
specific demand of consumers using process agility, flexibility and integration (Davis,
1989). Lean manufacturing is considered as a transitional step for achieving mass
customization, as some aspects of lean manufacturing are directly transferable to mass
customization (Da Silveira et al., 2001; Stump and Badurdeen, 2012). The positive
association of lean manufacturing with mass customization and flexibility has also
been discussed in literature (Da Silveira et al., 2001; Zhang et al., 2006). One of the CSF
for successful mass customization is the flexibility of a manufacturing system (Moser,
2007); a firm cannot achieve mass customization without being a flexible firm.
Therefore, it is essential to explore the means that help in developing manufacturing
flexibility in a firm.
Early work of Gerwin (1987) identified flexibility as one of the competitive
performance criteria in manufacturing strategy. Thereafter numerous studies have
been done on different antecedents and contingents of manufacturing flexibility
(Vokurka and O’Leary-Kelly, 2000; Chang et al., 2005; Mishra et al., 2014a, 2016).
Early studies have described the significant role of intrinsic factors that influence
manufacturing flexibility. Technological capability is central to the most of the
manufacturing flexibility studies. Along this line, conceptual and empirical
studies have described the positive association of different technologies and
manufacturing flexibility (Vokurka and O’Leary-Kelly, 2000). The practices of
employing manufacturing flexibility are widely discussed in the literature.
Manufacturing firms tend to use and develop a variety of practices, such as
flexible working practices, integration practices, manufacturing practices that aid in
developing flexibility. Manufacturing firms employ advanced manufacturing
technologies for several purposes, such design, manufacturing, planning and
control and integration (Dangayach and Deshmukh, 2005) that ultimately help firms
in achieving manufacturing flexibility (Zhang et al.,2006).Differenttypesof
technologies and automation facilitate in daily operations, such as gathering,
analysing and interpreting data and day-to-day control of shop floor activities
(Chiarini and Vagnoni, 2015). Use of FMS, CAD, CAM, CNC, AGV, ERP are some of
theexamplesofAMTthatarecitedintheliterature(Zhanget al., 2006; Mishra
et al., 2016). FMS allows switching from one product configuration to another thereby,
facilitates in manufacturing several products variants in a short period of time ( Jack
and Raturi, 2002). The implementation of FMS provides a range of benefits to the
manufacturing firms. However, it is important for a firm to consider different
enablers of FMS before considering its implementation (Raj et al., 2008).
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Similarly, studies have examined the role of workforce-related factors in achieving
manufacturing flexibility (Suarez et al., 1995; Jack and Raturi, 2002; Oke, 2005, Mishra
et al., 2016). Flexible working practices, such as temporary workforce, over timing,
multi-skilling are considered important for manufacturing flexibility ( Jack and Raturi,
2002, Oke, 2005; Salvador et al., 2007; Mishra et al., 2016). Multi-skilled workforce is
better able to deal with demand variations caused due to changes in demand of
quantity and varieties of products (Suarez et al., 1995). Similarly, temporary workers
and flexible wage system positively increase firms’ability to deal with volume
fluctuations (Suarez et al., 1996). The application of manufacturing practices in
enabling manufacturing flexibility is emphasized by the several studies (Suarez et al.,
1996; Zhang et al., 2006; Hallgren and Olhager, 2009). Set-up time reduction is
considered one of the essential requirements for manufacturing flexibility (Hallgren
and Olhager, 2009). The application of FMS and multi-skilled workforce considerably
reduce set-up time and facilitates in developing products with multiple configurations.
Design for manufacture and assembly facilitates in designing and assembling fewer
components that can be used for developing multiple products (Suarez et al., 1996).
These components can serve different purposes when these components are utilized in
diverse products (Zhang et al., 2006). Modular product design enhances external
diversity while minimizes internal diversity. Firms can develop varieties of products by
using combinations of new or existing modular products (Suarez et al., 1996; Jack and
Raturi, 2002; Hallgren and Olhager, 2009). Similarly, inventory buffer ensures product
availability when dealing with the changes in product demand. Slack capacity absorbs
variations in product demand. It aids in flexibility adoption by allowing larger orders to
be processed without affecting on-time delivery performance ( Jack and Raturi, 2002).
Further, just-in-time supply was regarded as a generic factor that provides
manufacturing flexibility in a firm (Oke, 2005; Mistry, 2006). Grounded on the pull
system strategy, it provides flexibility to the system by ensuring product availability
as and when required. Just-in-supply and outsourcing practices absorb any demand
variations that arises due to change in volume and variety of products (Lenny Koh
et al., 2007). Several authors also highlighted the strategic contribution of sourcing in
manufacturing performance (Narasimhan and Das, 1999). Flexibility of suppliers
significantly influences manufacturing flexibility of firms (Lau, 1999; Avittathur and
Swamidass, 2007; Mishra et al., 2016). Firm maintains multiple suppliers and
encourages flexible sourcing practices to develop manufacturing flexibility (Lau, 1999;
Jack and Raturi, 2002; Lenny Koh et al., 2007). A fit between plant flexibility and
suppliers flexibility is essential in order to achieve the desired business objectives.
Avittathur and Swamidass (2007) examined the importance of fit between a factory
and its suppliers. Their study found that firms achieve above average level of
profitability when flexible plant utilize flexible small suppliers. On the other hand,
mismatch between plant flexibility with supplier flexibility leads to below average
level of profitability.
Few studies have suggested important links between entrepreneurial orientation
and manufacturing flexibility (Barringer and Bluedorn, 1999; Chang et al., 2007).
Entrepreneurial orientation refers to the “firm’s willingness to involve in new market
opportunities and the revival of existing areas of operations”(Hult and Ketchen, 2001).
The dimensions of entrepreneurial orientations are autonomy, innovativeness, risk
taking, proactivness and competitive aggressiveness (Chang et al., 2007). Autonomy
encourages free thinking, open communication, information exchange and provides
opportunity to handle problems during development of modified products and new
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products (Muthusamy et al., 2005). In the same way, innovativeness leads to development
of new products. An entrepreneurial firm offers various product options and develop new
products by efficiently using advanced manufacturing (Chen et al., 1992). Further,
risk taking practices, proactivness and competitive aggressiveness induce
manufacturing flexibility in a firm (Chang et al., 2007). Studies also place high degree
of importance on supplier integration practices. High degree of supplier integration
practices, such as joint problem solving, involvement in new product development and
continuous improvement programs significantly influence flexibility (Liao and Barnes,
2015). It is essential for firms that they should well integrate with their suppliers to
successfully implement any new initiatives (Chiarini and Vagnoni, 2015). In a recent
study, Mishra et al. (2016) proposed that integration among different functions positively
influences manufacturing flexibility adoption. Integration includes demand variability in
the production process by incorporating required changes in design, making adjustment
in production schedule and providing real time information.
Based on existing manufacturing flexibility literature, different means to achieve
manufacturing flexibility can be broadly grouped into six key areas including flexible
working practices, integration Practices, technological capability, entrepreneurial
orientation, sourcing practices and manufacturing practices. It is evident that
combinations of different practices lead to manufacturing flexibility at plant level.
Successful firms incorporate and develop these practices to achieve flexibility. Based
on the literature, a conceptual framework has been developed to empirically investigate
implementation of these practices in SMEs and large firms (see Figure 1).
4. Research design and methodology
This study compares and evaluates status of manufacturing flexibility, their
usefulness, barriers to adoption and practices applied to achieve manufacturing
flexibility in SMEs and large firms in India. Consistent with the objective, this study
Flexible working practices
Sourcing Practices
Integration Practices
Entrepreneurial Orientation
Technological Capabilities
Manufacturing Practices
Manufacturing
Flexibility Adoption
Figure 1.
Conceptual
framework for
manufacturing
flexibility adoption
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adopts sequential explanatory research design (Creswell and Clark, 2007), in which
qualitative interviews follow survey methodology to explain the status of
manufacturing flexibility adoption, barriers to adoption and practices applied
for manufacturing flexibility adoption in Indian firms. The research framework is
shown in Figure 2.
4.1 Scale development
Systematic literature review was carried out to explore the related concepts and
variables used in this study. Since, the majority of manufacturing flexibility studies has
been done in large firms of developed economies, it was considered essential to explore
the feasibility of doing studies in SMEs and large firms in India. Consequently, eight
unstructured interviews (DiCicco Bloom and Crabtree, 2006) were conducted with the
experts (three academicians+five practitioners) to assist in the preparation of a
questionnaire on flexibility adoption. Findings of interviews were reconciled with
existing literature to prepare a survey questionnaire. Table II shows the questionnaire
items and their related supports from literature and unstructured interviews.
The self-administered questionnaire using mail survey was preferred over online
survey ( Jenkins and Dillman, 1997). The questionnaire comprised of four sub-sections
and each of the questions aimed at assessing manufacturing flexibility adoption in
SMEs and large firms of India. Each of the sections is described as follows.
4.1.1 Section A. Familiarity about manufacturing flexibility: this section provides
an understanding about the awareness of manufacturing flexibility concept in firms.
To investigate adoption rate, challenges and
practices applied for manufacturing flexibility in
SMEs and large firms
Literature Review
on Manufacturing
Flexibility and SMEs
Open ended,
unstructured interview
(n=8)
Questionnaire Survey
(n= 121)
Semi-Structured,
Follow up Interviews
(n= 16)
Integration of Survey
and Interview results
Interview data Analysis
Questionnaire Survey
Data Analysis
Research
Outcome
Figure 2.
Research
framework
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Adoption practices Related Studies
Interview
supports
Hiring of temporary workforce Suarez et al. (1995), Slack (1988) and
Oke (2005)
Yes
Regular information-sharing communication Urtasun-Alonso et al. (2014) Yes
Provision for over timing/extra working hour Slack (1988), Suarez et al. (1996) and
Oke (2005)
Yes
Multi-skill training and workforce
capabilities (also referred as cross-skill)
Suarez et al. (1995), Oke (2005) and
Jack and Raturi (2002)
Yes
Opportunities for employee participation Suarez et al. (1995) and Urtasun-Alonso
et al. (2014)
Yes
Marketing and manufacturing integration Chang et al. (2005) Yes
Manufacturing and design integration Chang et al. (2005) Yes
Supplier integration Chiarini and Vagnoni (2015) Yes
Advanced manufacturing technologies for
manufacturing,
Vokurka and O’Leary-Kelly (2000),
Zhang et al. (2006), Mishra et al. (2014a, b)
and Chiarini and Vagnoni (2015)
Yes
Advanced manufacturing technologies for
planning and control
Vokurka and O’Leary-Kelly (2000),
Zhang et al. (2006), Mishra et al. (2014a, b)
and Chiarini and Vagnoni (2015)
Yes
Advanced manufacturing technologies for
integration
Vokurka and O’Leary-Kelly (2000),
Zhang et al. (2006), Mishra et al. (2014a, b)
and Chiarini and Vagnoni (2015)
Yes
Advanced manufacturing technologies for
product and process design
Slack, (1988), Vokurka and O’Leary-Kelly
(2000), Zhang et al. (2006) and Chiarini and
Vagnoni (2015)
Yes
Innovative ability Chang et al. (2007), Camisón and López
(2010) and Mishra et al. (2014a, b)
Yes
Entrepreneurial proactivness Chang et al. (2007) Yes
Autonomy Chang et al. (2007) and Chiarini and
Vagnoni (2015)
Yes
Competitive aggressiveness Chang et al. (2007) Yes
Risk taking ability Chang et al. (2007) Yes
Outsourcing Jack and Raturi (2002) and Lenny Koh
et al. (2007)
Yes
Multiple sourcing Salvador et al. (2007) Yes
Flexible sourcing (referred as suppliers’
responsiveness/suppliers’flexibility)
Lau (1999), Suarez et al. (1996),
Narasimhan et al. (2004) and Salvador
et al. (2007)
Yes
Short set-up time(also referred as set-up time
reduction)
Zhang et al. (2006) and Hallgren and
Olhager (2009)
Yes
Design for manufacturing and assembly Suarez et al. (1995, 1996) and Salvador
et al. (2007)
Yes
Just-in-time supply Narasimhan et al. (2004), Oke (2005)
and Lenny Koh et al. (2007)
Yes
Total preventive maintenance Zhang et al. (2006) and Hallgren
andOlhager (2009)
Yes
Modular product designs Suarez et al. (1995), Salvador et al. (2007)
and Hallgren and Olhager (2009)
Yes
Buffer stock Jack and Raturi (2002) Yes
Slack capacity Suarez et al. (1996) and Hallgren and
Olhager (2009)
Yes
Table II.
Questionnaire items
related to practice
applied for
manufacturing
flexibility adoption
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All the firms irrespective of their involvement in manufacturing flexibility adoption
answered this part of the questionnaire.
4.1.2 Section B. Barriers to manufacturing flexibility adoption: the main purpose of
this section is to explore barriers to manufacturing flexibility adoption in Indian firms.
This section of questionnaire was filled-up by those firms, who understood the
importance of manufacturing flexibility, but were not able to employ any
manufacturing flexibility.
4.1.3 Section C. Practices applied for manufacturing flexibility adoption: this
section of questionnaire includes information about the various practices that are
required for manufacturing flexibility adoption in firms. Firms, who employed
manufacturing flexibility at plant level, responded this section of the questionnaire.
4.1.4 Section D. Respondents and their organizational background: this section of
questionnaire seeks information about the respondents and their organizational
background, such as, job experience in existing firm, job-profile, age of the
organization, number of employee, nature of industry.
Section A includes dichotomous questions; therefore, nominal scale (Yes/No) was used
to assess the familiarity of manufacturing flexibility concepts in Indian firms. Seven-point
Likert scale (strongly disagree to strongly agree) was used to measure questions related to
section B and section C of the questionnaire. Likert scales have an advantage over other
scales is that parametric statistical methods can be easily used on its data point (Hair et al.,
2006). Section D consists of demographic questions that aimed at identifying respondents’
profile and firms’characteristics. The survey questionnaire included information related
to various aspects of firms –designation of respondents, work-experience in existing
firms, age of the firms, nature of industry, industry types. The proposed questionnaire
was given to ten experts, i.e. practitioners (four) and academicians (six) having experience
in operations domain of more than ten years, to assess the face and content validity of the
proposed instrument. Content validity was established by using representative items from
an extensive review of literature and a formal assessment by ten experts (DeVon et al.,
2007). Further, clarity, wordings and overall style, layout and formatting of the
questionnaire was examined to ensure face validity.
4.2 Pilot study
A pilot study was carried out to ensure that proposed questionnaire is unambiguous
and unbiased to target audiences (Oppenheim, 2000). As the study includes a target
sample of both SMEs and large firms, it was essential to evaluate whether both types of
respondents can understand and fill the survey questionnaire. Therefore, a pilot survey
was carried out in the month of March 2015. For the pilot study, questionnaires were
given to six SMEs and three large firms. The findings of pilot study highlighted that
some respondents were using the term “flexible manufacturing system”and
“manufacturing flexibility”interchangeably. Therefore, in order to avoid ambiguity,
a supplementary sheet was included with a survey questionnaire to describe the
meaning, types and possible benefits of manufacturing flexibility concept and
definitions of other technical terms.
4.3 Survey administration
The study has a target population of SMEs and large firms located in the northern and
western parts of India. The sampling process comprised of two steps: first step
established qualifying criteria for selection of manufacturing firms. Manufacturing
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firms were selected based on the two qualifying criteria: firms should manufacture
multiple products in terms of attributes, functionality or benefits; firms should operate
in a competing environments, which drives fluctuation in the quantity demanded.
Uncertainty in demand is one of the major reasons for firms to develop manufacturing
flexibility (Zhang et al., 2006; Pundir et al., 2013; Mishra et al., 2016, 2017). Therefore, it
is essential for manufacturing firms to operate in uncertain environments. Once the
manufacturing firms were selected, the next task was to select the sample firms from
northern and western parts of India. These regions were selected particularly due to
factors like availability of a large number of manufacturing firms, ease of accessibility
of reliable data and researcher’s familiarity with these regions. The survey was
targeted to the top and middle management (founder, director, VP-operations, plant
head, plant manager, supply chain manager) of manufacturing firms from different
industries. The name of the potential respondents was identified using personal
connection and business-oriented social networking site (Linkedin). Initially, total 217
manufacturing firms (130 SMEs+87 large firms) were chosen. The respondents were
initially contacted via telephonic calls and/or personal visits. Then questionnaire was
e-mailed to all the 217 target respondents in the first week of April 2015. Only 12
responses were received by the end of April 2015. Due to delay in response, follow-up e-
mails and telephonic calls were made to request respondents to participate in the
survey. Since e-mail was preferred mode of communication, few small firms might face
the problem in communication. The possibility of exclusion of few small firms in
survey research can bring coverage bias in the findings (Klassen and Jacobs, 2001).
To eliminate coverage bias, small firms were contacted and a copy of questionnaire was
mailed to their addresses. A total 175 responses were returned and these responses
were further used for data analysis.
4.4 Follow-up interviews
This study aimed at exploring differences in manufacturing flexibility adoption in
Indian SMEs and large firms. Follow-up semi-structured interviews with
manufacturing and operations management professionals were done to develop
insights and get better explanations of survey findings. It facilitated in understanding
various cause and effect relationships. Selection of plants and potential respondents
were done using purposive, snowball and convenience sampling. A total 16
semi-structured interviews with employees of SMEs (eight) and large firms (eight) were
conducted by asking open-ended questions in the month of October 2015.
Sample characteristics of all these firms are presented in Table III. All of these firms
were earlier participated in survey research. A sample size of 16 was considered
appropriate as majority of studies conducted 15-30 personal in-depth interviews as a
mean for exploring research questions (Mariampolski, 2001).
4.5 Data analysis methodology
This study applied both descriptive and inferential statistical data analysis techniques
using SPSS software (version 21) to address research objectives. Descriptive statistical
techniques such as mean score and standard deviations were used to better understand
the barriers to manufacturing flexibility adoption. Higher mean score implies higher
intensity of the corresponding barrier. The theoretical model given in Figure 1 and
Wilcoxon-Mann Whitney U-test was used to compare the level of manufacturing
flexibility adoption in SMEs with the level of manufacturing flexibility adoption in
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large firms. Further, mean implementation level of manufacturing flexibility adoption
practices in SMEs and large firms was calculated. Lastly, Friedman test was performed
to determine the priority ranking of six types of manufacturing flexibility adoption
practices in SMEs and large firms.
Follow-up interviews were conducted to recombine evidences so as to reconfirm
survey results. As participants hesitated to record their conversation in audio recording
device, the note-based analysis was purposively chosen. As recommended by Casey and
Krueger (1994), notes were reviewed subjectively to identify common themes.
5. Data analysis and empirical results
The study investigates various aspects of manufacturing flexibility adoption in SMEs and
large firms. Along these lines, respondents firms were divided into two groups, i.e. SMEs
and large firms, to evaluate and compare familiarity and usefulness of manufacturing
flexibility adoption, barriers to adoption and practices applied for adoption. This section
provides response analysis, data screening and results of the data analysis.
5.1 Response analysis
Out of 217 contacted firms, 42 firms did not participate in the survey even after
sending a couple of reminder e-mails; total 175 (217 −42) complete survey questionnaires
Participants’
designation Industry Nature of products
Size of
firm
Respondents’experience in
existing firm
General manager Food processing Starch manufacturing
firm
SME W10 years
VP-operations Packaging Aluminium packaging SME 5-10 years
GM-operations Electrical Wire and cable
manufacturing
SME W10 years
Owner Fashion apparel Ladies apparel SME 5 years
Owner Fashion apparel Ladies apparel and
fashion jewellery
SME 10 years
Owner Machine and
machinery
Machine tools SME 5-10 years
Owner Chemical Detergent SME 5-10 years
Director Apparel Sports wear SME 2-5 years
Senior engineer Automotive Two-wheeler Large
firm
2-5 years
Senior engineer Heavy
equipment
Health care systems Large
firm
2-5 years
GM-operations Auto-ancillary Air-conditioning systems Large
firm
5-10 years
Plant head Capital
equipment
Diesel engines and related
technology
Large
firm
5-10 years
Plant head Automobile Passenger vehicle cars Large
firm
5-10 years
GM-operations Auto-ancillary Batteries Large
firm
3 years
Head-operations Fashion apparel Sports wear Large
firm
5-10 years
Project manager Machine and
machinery
Pump manufacturing Large
firm
5-10 years
Table III.
Sample
characteristics
of interview
participants
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were received. During the initial screening of filled questionnaires, 11 responses were
found not suitable for inclusion as standard deviation between responses of each of the
questions was minimal, leaving us with the sample size of 164 (175 −11) and effective
response rate of 76 per cent, which are consistent with other studies in manufacturing
flexibility domain. The responses were classified into two categories –SMEs and large
firms. The basis for classifying the size of a firm varies from country to country.
SMEs classification as per the definition of the European Commission (2003) is based on
number of employees and either turnover or balance sheet total (see Table IV).
In India, definition of SMEs is based on the total amount of investment in plants
and machineries. As per Small and Medium Enterprises Development Act, 2006, a
manufacturing enterprise having investment of more than 25 lakh rupees but not more
than five crore rupees is considered small enterprise. Similarly, a manufacturing enterprise
having investment of more than five crore rupees but not more than ten crore rupees is
considered medium enterprise. An enterprise having investment of more than ten crore
rupees is considered large enterprise. Since the sample comprised of Indian manufacturing
firms, the study classified these firms based on their investment in plant and machinery.
5.2 Data preparation
Before doing the data analysis, responses were analysed to ensure the validity of some
key assumptions, such as normality, non-response bias and common method bias.
5.2.1 Normality assessment. There are various tests for assessing normality of the
data set. Among several test, Shapiro-Wilk test is considered the best choice for testing
normality of data (Ghasemi and Zahediasl, 2012). Using Shapiro-Wilk test, Null
hypothesis, i.e. population is normally distributed was rejected for all items (see Table V).
Therefore, condition of normality was not satisfied for any parametric method. Due to
non-normal distributions of data and unequal comparison group sizes, non-parametric
test was applied for data analysis (Hair et al.,2006).
5.2.2 Non-response bias and common method bias. Non-response bias was assessed
to examine the differences in characteristics of respondents and non-respondents.
Using exploration method, non-response bias was assessed to understand the
difference in early and late respondents (Armstrong and Overton, 1977). In this study,
non-response bias was not found. Common method bias was controlled by maintaining
respondents’profile anonymous and minimizing apprehension in questionnaire
evaluation (Podsakoff et al., 2003).
The findings of this study are presented in three different sections, namely, status
of manufacturing flexibility adoption, barriers to manufacturing flexibility adoption
and manufacturing flexibility adoption practices.
5.3 Status of manufacturing flexibility adoption
To investigate manufacturing flexibility adoption, the first step is to ensure the
familiarity of manufacturing flexibility concept in Indian firms. Out of 164 effective
Company category Staff headcount Turnover/balance sheet total
Micro o10 ⩽€2m/⩽€2m
Small o50 ⩽€10 m/⩽€10 m
Medium sized o250 ⩽€50 m/⩽€43 m
Table IV.
SME definition
as per EU
recommendation
2003/361
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responses, 43 (26 per cent) firms’representative stated their unawareness about
manufacturing flexibility concept. The majority of these contacted firms were
SMEs (39), where practitioners were not familiar with this concept at all. Even after
providing details about each of the key terms in the cover page, these firms indicated
that they were not familiar with the concept. Only four firms belonged to large firms,
which suggest that familiarity about the manufacturing flexibility concept is
considerably higher in large firms, whereas concept is relatively new and rate of
awareness is low in SMEs. Table VI presents sample characteristics of firms, which are
aware about the manufacturing flexibility concepts and its importance. Out of
121-collected response, 11 firms (six SMEs and five large firms) indicated that they do
not find manufacturing flexibility beneficial to their production process; therefore,
these firms do not employ manufacturing flexibility in its operating environment.
5.3.1 Level and types of adoption. To assess firms’initiatives, participants were
asked to mention if their firms have taken any initiatives or employed any polices
regarding manufacturing flexibility. Out of 46 large firms, 41 large firms confirmed
that their firms have implemented policies related to manufacturing flexibility. On the
other hand, out of 75 SMEs, only 45 SMEs confirmed that their firms have taken some
SMEs (df ¼45) Large firms (df ¼41)
Manufacturing flexibility adoption practices Statistics p-value Statistics p-value
Hiring of temporary workforce 0.896 0.001 0.941 0.033
Regular information-sharing communication 0.915 0.003 0.920 0.007
Provision for over timing/extra working hour 0.876 0.000 0.938 0.027
Multi-skill training and workforce capabilities 0.891 0.001 0.912 0.004
Opportunities for employee participation 0.906 0.001 0.894 0.001
Marketing and manufacturing integration 0.930 0.010 0.903 0.002
Manufacturing and design integration 0.914 0.003 0.897 0.001
Supplier integration 0.920 0.004 0.912 0.004
Advanced manufacturing technologies for
manufacturing 0.905 0.001 0.895 0.001
Advanced manufacturing technologies for planning
and control 0.908 0.002 0.895 0.001
Advanced manufacturing technologies for integration 0.928 0.008 0.873 0.000
Advanced manufacturing technologies for product and
process design 0.900 0.001 0.855 0.000
Innovative ability 0.932 0.011 0.909 0.003
Risk taking ability 0.907 0.002 0.904 0.002
Autonomy 0.896 0.001 0.916 0.005
Competitive aggressiveness 0.911 0.002 0.901 0.002
Entrepreneurial proactivness 0.891 0.000 0.905 0.002
Flexible sourcing 0.878 0 0.910 0.003
Multiple sourcing 0.897 0.001 0.868 0.000
Outsourcing 0.891 0.001 0.911 0.003
Total preventive maintenance 0.923 0.005 0.885 0.001
Design for manufacturing 0.912 0.002 0.859 0.000
Just-in-time supply 0.908 0.002 0.909 0.003
Short set-up time 0.902 0.001 0.879 0.000
Modular product design 0.900 0.001 0.905 0.002
Buffer stock 0.872 0.000 0.907 0.003
Slack capacity 0.851 0.000 0.879 0.000
Table V.
Results of the
Shapiro-Wilk test
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initiatives to adopt flexibility. The findings suggest a higher level of involvement of
large firms in manufacturing flexibility adoption compared to SMEs.
Further, the study investigated the most commonly used flexibility types in Indian
firms Among three types of external manufacturing flexibility, i.e. volume flexibility,
product mix flexibility, new product flexibility, volume flexibility was found commonly
used in Indian firms. Interestingly, it was found that the majority of SMEs and large
firms adopt volume flexibility in their production environment. Adoption of product
mix flexibility was observed significantly lower than volume flexibility in Indian firms.
Out of 41 large firms, 27 firms adopt product mix flexibility, whereas out of 45 SMEs,
only 12 SMEs reported the application of product mix flexibility in their firms.
Surprisingly, only 13 of firms (five large-scale firms, eight SMEs) reported that they have
developed new product flexibility in their plants. Participants from these firms stated
that new products are developed in their firms mainly through strategic alliances or
outsourcing with MNC players. Therefore, new product flexibility was found to be a
less-practised flexibility type among Indian manufacturing firms. Table VII summarizes
the responses related to status of manufacturing flexibility adoption.
5.4 Barriers to manufacturing flexibility adoption
The second research question pertaining to barriers to manufacturing flexibility
adoption was investigated using a questionnaire. The questionnaire included a set of
15 barriers that hinders manufacturing flexibility adoption. Out of remaining
SMEs Large firms
1. Respondents experience in existing firms
2-5 years 40 25
6-9 years 32 13
More than 10 years 3 8
2. Respondents designation
Plant manager 5 14
Plant head 14 8
Supply chain manager na 7
Operations manager na 13
Director 19 na
VP-operations 20 4
Founder 17 na
3. Firms’age
0-2 years 3 na
3-5 years 27 na
5-10 years 39 na
More than 10 years 6 46
4. Industry
Textile and fashion apparel 16 2
Automobile and automotive 8 5
Electrical 12 7
Machine tools and machinery 9 8
Food processing 14 5
Packaging industry 4 na
Others (chemical, paper, plastic, etc.) 12 19
Table VI.
Sample
characteristics
of firms
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110 responses, a total of 24 firms (all SMEs) indicated their failure to adopt
manufacturing flexibility despite knowing its strategic importance in firms.
Table VIII provides descriptive statistics of barriers to adoption to manufacturing
flexibility adoption. The findings of the study suggest that major barriers to adoption
are lack of adequate knowledge and commitments for manufacturing flexibility, low
technology adoption and lack of access of modern technology, lack of suppliers’
support in enhancement of manufacturing flexibility capability, lack of long-term
relationship with target customers and lack of innovative capabilities.
5.5 Manufacturing flexibility adoption practices
The study compares manufacturing flexibility adoption practices between SMEs and
large firms in India. The null hypothesis of this study is that, SMEs population is
identical to the large firms’population on various manufacturing flexibility adoption
practices. Wilcoxon-Mann Whitney U-test was applied to compare the various
manufacturing flexibility adoption practices in SMEs and large firms. The results
suggest that practices applied for developing manufacturing flexibility vary
Barriers Mean SD
Strategic concerns
Lack of leadership support and commitment for manufacturing flexibility adoption 4.75 1.51
Inadequate knowledge regarding implementation of manufacturing flexibility 5.67 1.09
Lack of top management support for innovation 5.42 1.38
Operational concerns
Fear of increasing overall cost 5.46 1.22
Fear of compromising with efficiency 5.17 1.17
Fear of compromising with quality 3.04 1.33
Internal resource concerns
Low level of technology adoption levels and lack of access to modern technology 5.83 1.05
Shortage of multi-trained human resource to develop manufacturing flexibility 4.50 1.06
Inadequate operational improvement practices to facilitate flexibility 4.25 1.45
Lack of employee motivation 4.21 1.14
External supports
Absence of suppliers’support in enhancement of manufacturing flexibility capabilities 5.29 1.08
Inability to procure raw materials at competitive cost 4.96 1.52
Lack of long-term relationship with target customers 4.58 1.44
High cost of credit 4.71 1.73
Inadequate infrastructure, i.e. road, power, water, etc. 3.92 0.97
Table VIII.
Barriers to
manufacturing
flexibility adoption
Items for study SMEs Large firms Total
Awareness about the manufacturing flexibility concept 75 46 121
Usefulness of manufacturing flexibility concept 69 41 110
Policy related to manufacturing flexibility adoption 45 41 86
Types of implementation Volume flexibility 24 38 62
Product mix flexibility 12 27 39
New product flexibility 8 5 13
Table VII.
Status of
manufacturing
flexibility adoption
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significantly between SMEs and large firms. It was found that SMEs achieve flexibility
by emphasizing on flexible working practices, entrepreneurial orientation. On the other
hand, large firms develop manufacturing flexibility by using integration practices,
sourcing practices, technological capability. The results of the study indicate that there
are statistically significant differences in average adoption score of SMEs and large
firms (Table IX). Descriptive statistics on questions related to practices applied for
manufacturing flexibility adoption are presented in Table X.
In order to assess the priority rank of various manufacturing flexibility adoption
practices in SMEs and large firms, Friedman test was conducted. Friedman’s
non-parametric test was applied to validate the observed differences
in different manufacturing flexibility adoption practices in SMEs and large firms.
Table XI presents priority ranks of manufacturing flexibility adoption practices in
SMEs and large firms. The result of a Friedman test (n¼45, χ
2
¼18.37, p¼0.003,
df ¼5) suggests that in SMEs difference in manufacturing flexibility adoption practices
are statistically significant. The findings indicates that the null hypothesis of this
test (H
0
), which refers to the assumption that in SMEs, all the considered
manufacturing flexibility adoption practices have same priorities is rejected.
The possible explanation of these variations in priority ranks is that some practices,
such as entrepreneurial orientations and flexible work practices are relatively easy to
employ in SMEs whereas other practices, such as technological capabilities, sourcing
practices are difficult to implement in SMEs. Similarly, for large firms, the results of
Friedman test (n¼41, χ
2
¼24.49, p¼0.00, df ¼5) suggests that there are statistically
significant differences between manufacturing flexibility adoption practices, thereby,
rejecting the null hypothesis (H
0
) about equal priority of all the manufacturing
practices in large firms.
6. Discussion
The study compares and evaluates familiarity of manufacturing flexibility concept, its
usefulness and barriers to manufacturing flexibility adoption in SMEs and large firms
in India. The study also ranks importance level of flexibility adoption practices for
SMEs and large firms. The follow-up interviews was used to explain and build upon
cross-sectional survey results. This section presents discussion on integrated findings
of cross-sectional survey and follow-up semi-structured interviews.
The findings of study illustrate that majority of SMEs and large firms were aware
of manufacturing flexibility concepts and found these concepts useful, but the
adoption of manufacturing flexibility was significantly lower in SMEs than adoption
Average adoption score Total sample (n¼86)Manufacturing flexibility
adoption practices SMEs (n¼45) Large firms (n¼41) p-value Average score SD
Flexible working practices 5.23 4.86 0.098 5.05 1.00
Integration practices 4.82 5.19 0.085 5 0.89
Technological capabilities 4.54 5.61 0.000 5.05 0.89
Entrepreneurial orientation 5.15 4.69 0.003 4.93 0.71
Sourcing practices 4.85 5.24 0.011 5.03 0.73
Manufacturing practices 5.24 5.38 0.156 5.31 0.61
Note: Responses were taken on seven-point Likert-type scale, ranging from 1 (strongly disagree) to 7
(strongly agree)
Table IX.
Average adoption
score of SME and
large firms
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in large firms. At the same time, majority of large firms not only recognized
benefits of manufacturing flexibility but have also initiated several practices to
achieve flexibility.
Among 121 firms (75 SMEs and 46 large firms) who were aware of manufacturing
flexibility concepts, a total 110 firms (69 SMEs and 41 large firms) consider
manufacturing flexibility beneficial to their organization. Total 11 firms reported that
they do not find manufacturing flexibility beneficial to their production process and
therefore, these firms did not employ manufacturing flexibility in their operating
environment. The possible reasons for not finding manufacturing flexibility beneficial
could be product characteristics and uncertainties avoidance strategies adopted by
firms. These firms offer few product varieties, maintain strong customer relationship
SMEs Large firms Total firms
Key areas
Manufacturing flexibility adoption
practices
Mean
(n¼45) SD
Mean
(n¼41) SD
Mean
(n¼86) SD
Flexible
working
practices
Hiring of temporary workforce 5.36 1.26 4.56 1.23 4.98 1.30
Multi-skill training and workforce
capabilities 5.02 1.41 4.90 1.50 4.97 1.44
Provision for over timing/extra
working hour 5.51 1.31 4.78 1.39 5.16 1.39
Regular information-sharing
communication 5.04 1.31 5.05 1.34 5.05 1.32
Opportunities for employee
participation 5.20 1.27 5 1.40 5.10 1.33
Integration
practices
Marketing and manufacturing
integration 4.93 1.27 4.88 1.10 4.91 1.18
Manufacturing and design integration 5.00 1.21 5.37 1.26 5.17 1.24
Supplier integration 4.53 1.42 5.32 1.17 4.91 1.36
Technological
capabilities
Advanced manufacturing technologies
for manufacturing 3.69 1.16 5.49 1.29 4.55 1.52
Advanced manufacturing technologies
for planning and control 4.73 1.47 5.51 1.12 5.10 1.36
Advanced manufacturing technologies
for integration 4.33 1.51 5.63 1.04 4.95 1.45
Advanced manufacturing technologies
for product and process design 5.40 1.23 5.80 1.19 5.59 1.22
Entrepreneurial
orientation
Innovative ability 4.98 1.32 4.95 1.20 4.97 1.26
Risk taking ability 4.91 1.22 4.15 1.01 4.55 1.18
Autonomy 5.49 1.12 4.78 1.11 5.15 1.16
Competitive aggressiveness 4.87 1.18 4.66 1.20 4.77 1.18
Entrepreneurial proactivness 5.49 1.25 4.90 1.34 5.21 1.32
Sourcing
Practices
Flexible sourcing 4.98 1.06 5.05 1.30 5.01 1.17
Multiple sourcing 5.42 1.18 5.66 1.06 5.53 1.12
Outsourcing 4.16 1.48 5.00 1.40 4.56 1.49
Manufacturing
practices
Total preventive maintenance 4.98 1.37 5.54 1.27 5.24 1.35
Design for manufacturing 5.04 1.26 5.44 1.12 5.23 1.20
Just-in-time supply 4.67 1.19 5.34 1.17 4.99 1.22
Short set-up time 5.42 1.03 5.51 0.95 5.47 0.99
Modular product designs 5.36 1.17 5.46 1.07 5.41 1.12
Buffer stock 5.42 1.34 5.34 1.02 5.38 1.19
Slack capacity 5.58 1.12 5.56 1.18 5.57 1.14
Table X.
Use of
manufacturing
flexibility adoption
practices in firms
749
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large firms
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and operate in a market with relatively stable demand conditions. Despite familiarity
about manufacturing flexibility concept and finding it beneficial, only 86 firms
(45 SMEs and 41 large) have taken initiatives in developing manufacturing flexibility
capability. Thus, it can be said that manufacturing flexibility is still at very nascent
stage in Indian firms as far as its implementation is concerned. The possible reason for
non-adoption of manufacturing flexibility by SMEs can be that SMEs engaged in
contract manufacturing find manufacturing flexibility practices such as lean
manufacturing practices, cellular manufacturing, just-in-time practices and design
for manufacturing bringing in additional cost with very marginal benefits (Doolen and
Hacker, 2005). Due to these reasons, these SMEs do not adopt manufacturing
flexibility despite being aware of manufacturing flexibility concepts and finding these
concepts useful.
Further, majority of these firms, both SMEs and large firms, employed only one
form of flexibility, i.e. volume flexibility and did not employ flexibilities, such as
product mix and new product flexibility. The possible explanation for wider
application of volume flexibility is its increased effectiveness in managing demand
uncertainty in cases where a firm produces multiple products and demand for these
products are positively correlated (Goyal and Netessine, 2011) and industry’s
characteristics driven by the needs of flexibility in firms. Industry characteristics refer
to the demand uncertainty, demand variability, customer influence on the lead-time
determination, short product life cycle and short shelf life of products (Oke, 2003).
Follow-up interviews revealed that demand variability and demand uncertainty were
the major reasons for implementing volume flexibility in Indian manufacturing firms.
Short-life-cycle was also observed to be an important driver in fashion apparel firms
and food processing firms. Participants from apparel firm indicated that life cycle of
products varies considerably based on the nature of products. Life cycles of basic
products, such as jeans, t-shirt, formal shirts, are comparatively longer than life cycles
of fashion apparels and fad products. Consequently, need of volume flexibility is
determined by nature of products. Influence of consumers in lead-time determination
was also found as an important driver for volume flexibility in packaging, food
processing and fashion apparel firms. Further, short shelf life was found to be major
driver of volume flexibility in food processing firms dealing with perishable products.
SMEs Large firms
(n¼45, χ
2
¼18.37,
significance ¼0.003, overall
mean ¼4.97)
(n¼41, χ
2
¼24.49,
significance ¼0.00, overall
mean ¼5.16)
Manufacturing flexibility adoption
practices
Friedman’s
test Rank Mean SD
Friedman’s
test Rank Mean SD
Flexible working practices 3.94 2 5.23 0.92 3.13 5 4.86 1.06
Integration practices 3.33 4 4.82 0.97 3.39 4 5.19 0.78
Technological capabilities 2.66 6 4.54 0.74 4.30 1 5.61 0.67
Entrepreneurial orientation 3.79 3 5.15 0.63 2.50 6 4.69 0.71
Sourcing practices 3.22 5 4.85 0.64 3.71 3 5.24 0.78
Manufacturing practices 4.06 1 5.24 0.56 3.96 2 5.38 0.66
Note: Responses were taken on seven-point Likert-type scale, ranging from 1 (strongly disagree) to 7
(strongly agree)
Table XI.
Ranking the
importance of
manufacturing
flexibility adoption
practices in SMEs
and large firms using
Friedman’stest
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Perishable nature of these products influences these firms to adopt make-to-order
strategy and develop volume flexibility, finding similar to Oke (2003).
At the same time, findings of study also suggest that new product flexibility
adoption is significantly lower than other two external manufacturing flexibilities.
The significantly lower level of new product flexibility can be attributed to the nature
of business environment, which necessitates redefining product range over time rather
than introducing product innovation frequently (Petroni and Bevilacqua, 2002).
Further, majority of firms confirmed that new products are not frequently introduced
as whenever firms need to develop new products, they mostly go with strategic
alliances or joint venture for design and development activities.
With reference to reasons for non-adoption of manufacturing flexibility, the study
reveals that key barriers to manufacturing flexibility adoption in SMEs are inadequate
knowledge about manufacturing flexibility adoption, low level of technology adoption,
lack of access to latest technology and lack of top management support for innovation.
Lack of access to latest technologies impedes firms’ability to deal with volume
fluctuations, which further leads to non-adoption of manufacturing flexibility in SMEs.
Majority of the interview participants opined that SMEs need restructuring of its entire
operations and need to become innovative. Further, flexible sourcing was considered
one of the key criteria for manufacturing flexibility adoption. However, flexible
sourcing requires a well-integrated and continuously supported supply system, which
is often difficult to attain. Thus, flexible sourcing remains a daunting challenge for
SMEs as these firms source raw materials within their local territory due to financial
constraints and limited geographical reach. Further, procurements in SMEs are much
smaller in scale as compared to procurement in industry at large. The barriers
highlighted in the survey are inability to procure raw materials at competitive costs
and lack of human resources with appropriate skills. Although, India has an advantage
of a large pool of human resources, SMEs face difficulties in terms of attracting,
developing and retaining employees for various manufacturing and maintenance
activities and this limits flexibility adoption capability of SMEs.
Further, it was observed that large firms consider manufacturing flexibility as a
strategic decision and thus these firms focus on alignment of manufacturing flexibility
decisions with their overall business strategy. These large firms proactively and
reactively implement and monitor different flexibility enhancement strategies so as to
ensure long-term success of their business. On the other hand, SMEs employ flexibility
from short-term perspective and utilize manufacturing flexibility as a reactive tool to
compete in the market and satisfy customer needs.
On technological capability aspect, large firms obtained a statistically significantly
higher score compared to the SMEs ( po0.001). The findings of the study implied that
there is statistically significant difference between two groups with respect to
technological capability. Follow-up interviews with practitioners also revealed that
SMEs employ AMT mainly for design and planning and integration purposes.
The application of CAD, ERP and MRP was found most common among
SMEs. The findings of study is consistent with the previous research (Dangayach
and Deshmukh, 2005). Anecdotally, employment of advanced manufacturing
technologies, such as FMS involve significant amount of investment, technical
knowledge and favourable human resource policies. Large firms often know the
strategic benefits of flexibility that can be derived from investment in advanced
manufacturing technologies, whereas SMEs do not possess enough technical
knowledge, favourable labour conditions and technical skills, findings consistent
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with earlier studies (Thakkar et al., 2012). As a result, financing of AMT becomes major
concerns for SMEs due to complexity and risk involved in flexibility-related
investments. Further, SMEs face several challenges, such as lack of financial resources,
incompetent staffs, and time constraint to examine the benefits of new technologies.
Lastly, incompatibility of new technologies with existing facilities also inhibits
implementation of advanced manufacturing technologies in SMEs (Raymond and
St-Pierre, 2005).
Regarding sourcing decision, larger firms had a statistically significant higher score
compared to SMEs ( po0.05). This indicates that large firms implement their sourcing
decisions more effectively than SMEs do. The findings of follow-up interviews with
participants of SMEs and large firms revealed that large firms effectively employ
multiple sourcing practices due to close relationship with multiple suppliers and well
developed suppliers’network. Further, flexible sourcing is comparatively well achieved
in large firms than in SMEs. Large firms are well-integrated in their value chain leading
to a well-developed flexible sourcing practices. Further, flexible sourcing practices are
also strengthened by application of information technologies and mutual
understanding among members of value chain (Chang et al., 2005). Regarding
manufacturing practices, there was no statistically significant difference observed
between SMEs and large firms ( p¼0.156). Findings of follow-up interviews revealed
that both SMEs and large firms utilize certain manufacturing practices that improve
manufacturing flexibility at plant level. Holding safety stocks and maintaining slack
capacity minimize supply chain and demand chain-related uncertainties (Lenny Koh
et al., 2007). Further, just-in-time practices, such as total preventive maintenance, set-up
time reduction, modular product design and just-in-time supply, offer flexibility to
manufacturing firms in developing multiple products while keeping minimum stock of
differentiated products (Zhang et al., 2006). Just-in-time supply facilitates minimum
inventory holding and thereby minimizes warehousing requirements and need for
advance cash flow, which is one of the essential requirement for survival of SMEs
(Mistry, 2006). The findings of study also coincided with earlier studies, which
suggested that small firms may attain high levels of manufacturing flexibility by using
manufacturing practices (referred as operational improvement practices by Zhang
et al., 2006) while large firms develop flexibility through investment in advanced
manufacturing technologies.
With respect to flexible work practices, mean score of SMEs (5.23) was observed
significantly higher than mean score of large firms (4.86). The study found
statistically significant difference between SMEs and large firm on flexible work
practices ( po0.1), but did not find any significant difference between SMEs and
large firms on flexible work practices at 95 per cent confidence. SMEs have a number
of strategic advantages over large firms in terms of human resource flexibility,
informality and adaptability compared to large firms. Human resource practices in
SMEs are predominately ad hoc, informal and opportunistic that assists in changing
policies based on the requirements of firms (Cardon and Stevens, 2004). There is no
set of rules or policies in terms of hiring skilled workers, employing temporary
workers and overtime policies in SMEs. SMEs recruit contract workers (temporary
and/or seasonal workers) mostly through external agency, which lowers its overall
cost and enable them to respond quickly to changing market demands (Cardon, 2003;
Cardon and Stevens, 2004; Thakkar et al., 2012). Findings from follow-up
semi-structured interviews suggest that practices, such as over time, hiring of
seasonal workers are common practices applied to fulfil seasonal demand.
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Further, these SMEs provide cross-training to their permanent employees to perform
varieties of related tasks. Training is given top priority in SMEs and firms engage
their employees in skill-advancement programme, findings consistent with earlier
studies (Banks et al., 1987; Rollag, 2002). On the other hand, human resource practices
in large firms are highly structured. The significantly higher score of SMEs compared
to large firms on flexible working practices is consistent with the previous studies
(Marlow and Patton, 1993; Cardon and Stevens, 2004) that suggest that SMEs are
better adaptable to changing market demand through flexible working practices.
Study reported statistically significant difference between SMEs and large firms
on entrepreneurial orientation aspect ( po0.05). Higher average score of
entrepreneurial orientation in SMEs group indicates that small firms are more
entrepreneurial than large firms. The finding is consistent with previous studies
(Entrialgo et al.,2001;Elfenbeinet al., 2010) which suggest that small firms nurture
entrepreneurial orientation. Engagement in broad range of business-related activities
develop jacks-of-all-trades employees in SMEs, which do not happen in large firms.
Due to lean structure and less hierarchy, SMEs have noticeable advantage of quick
decision-making and adaptation. Compared to well-established large firms, SMEs
have less to lose therefore, these firms are comfortable with dealing ambiguity
(Geis, 1985; Entrialgo et al., 2001). Study further identified statistically significant
difference between large firms group and SMEs group ( po0.1) on integration aspect.
Interviews with participants in SMEs and large firms suggested that integration with
different elements of value chain requires technological capability and higher
technical knowledge. In large firms, integration prevails both within and outside the
firms using information technologies. On the other hand, SMEs lack integration due
to heavy cost involvement, financial constraints, high technological demand and lack
of technical knowledge.
In summary, the findings of the study suggest that there is a statistically significant
difference between SMEs and large firms with respect to manufacturing flexibility
adoption practices. The summary of hypotheses describing the differences in
manufacturing flexibility adoption practices is presented in Table XII.
Overall study suggests that firms rely on different practices to achieve
manufacturing flexibility. The level of manufacturing flexibility adoption practices is
lower in SMEs and these firms bank on other strategies, such as use of inventory
buffer, slack capacity, slack scheduling and modular product design, to restore
flexibility for future contingency uses. However, it is difficult to conclude from the
study that whether large investment of resources leads to higher level of flexibility or
whether efficient management, irrespective of size or resources leads to higher level of
flexibility in manufacturing firms (Petroni and Bevilacqua, 2002).
Mean score
Manufacturing flexibility adoption practices SMEs Large firms Hypotheses
Flexible working practices High Low Not supported
Integration practices Low High Not supported
Technological capabilities Low High Not supported
Entrepreneurial orientation High Low Not supported
Sourcing practices Low High Not supported
Manufacturing practices No statistically significant difference Supported
Table XII.
Summary of
hypotheses stating
the difference in
manufacturing
flexibility adoption
practices
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7. Conclusion and implications
The study provides comparative evaluation of familiarity of manufacturing flexibility
concepts, their usefulness and barriers to manufacturing flexibility adoption in SMEs and
large firms. In particular, the key adoption practices used for comparative evaluation are
flexible working practices, integration practices, technological capabilities, entrepreneurial
orientation, sourcing practices and manufacturing practices. The mixed method
sequential explanatory design was used to better interpret results. Quantitative
analysis using descriptive and inferential statistics was done to critically assess
differences between large firms and SMEs, whereas qualitative analysis using follow-up
semi-structured interviews was carried out to offer a better interpretation of results.
The study reveals that awareness about manufacturing flexibility and initiatives
taken to improve manufacturing adoption practices are significantly higher in large
firms than SMEs.
Due to resource constraints and comparatively less familiarity with benefits of
manufacturing flexibility, awareness about the manufacturing flexibility and its
associated benefits were found significantly lower in SMEs. Despite the acknowledged
contribution of SMEs in Indian economic growth, these firms are facing a wide range of
challenges that hinder adoption of manufacturing flexibility. These SMEs need to be
educated and informed about the strategic benefits of manufacturing flexibility that
will help achieve competitive advantage.
This study found statistically significant difference between SMEs and large firms
with respect to three types manufacturing flexibility adoption practices ( po0.05),
namely, technological capabilities, entrepreneurial orientation and sourcing practices.
The study observed no statistically significant difference between SMEs and large
firms with respect to level of implementation in manufacturing flexibility adoption
practices such as Flexible working practices and integration practices (at po0.05
level), but found statistically significant difference at po0.1 level. Further, the study
reported no statistically significant difference between SMEs and large firms with
respect to level of implementation of manufacturing practices (p¼0.156).
This suggests that manufacturing practices in SMEs is identical to manufacturing
practices in large firms. The results support the notion that large firms are better able
to utilize their integration practices, sourcing practices and technological capabilities
than SMEs. On the other hand, SMEs employ manufacturing flexibility by efficiently
using entrepreneurial orientation practices and flexible working practices.
7.1 Theoretical implications
The study extends existing knowledge on manufacturing flexibility adoption by doing
comparative evaluation of Indian SMEs and large firms. Many empirical studies have
been done to explore different aspects of manufacturing flexibility, such as taxonomy,
definition, classification, relationship with drivers and enablers in large firms
(Chang et al., 2005, 2007; Mishra et al.,2017).However,veryfewstudiesinvestigate
manufacturing flexibility concept in the context of SMEs. This study contributes to the
knowledge of manufacturing flexibility adoption by extending the scope of
manufacturing flexibility study to SMEs. First, this research attempts to provide
comparative evaluation of familiarity, usefulness, barriers and means of adopting
manufacturing flexibility in Indian SMEs and large firms. It also offers a fresh
perspective on manufacturing flexibility adoption by importing existing theories from the
manufacturing flexibility literature. Moreover, the study supports that some significant
differences exist in the practices applied by firms to adopt manufacturing flexibility.
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The need to compare operational management issues in SMEs and large firms is one of
the future research areas suggested by Singh et al. (2008). Along this line, the study
represents a novel attempt to compare and evaluate various aspects of manufacturing
flexibility adoption in SMEs and large firms in India. Second, the study provides a rich
perspective on barriers to manufacturing flexibility adoption in Indian firms. In this
regard, study addresses a gap highlighted by Upton (1995) and Chang
et al. (2005) that suggests “40% flexibility improvement efforts become unsuccessful
and claimed that one of the major causes of poor performance was the inability to
recognize which factors most affected it”.
7.2 Practical implications
Thestudyhassomeimplicationsforpractitionersasitexplainssomeoftheimportant
aspects of manufacturing flexibility adoption. The study provides evidence that Indian
SMEs lack knowledge and awareness about manufacturing flexibility as compared to
large firms. Flexibility is one of the essential capabilities for firms to survive in the
changing environment. In today’s fast changing market, it is essential for firms to develop
manufacturing flexibility to meet unpredictable market demand. Also, the complex nature
of manufacturing flexibility requires that firm should apply a combination of practices to
achieve flexibility at plant level. At the same time, educational intervention is crucial for
success of any manufacturing flexibility adoption effort. The SMEs need to understand
the role of these practices and adopt innovative techniques to improve process flows,
reduce engineering time and implement flexibility oriented production system.
Second, the study suggests that both SMEs and large firms consider flexibility as an
important manufacturing capability. However, the emphasis placed on adoption
practices vary between SMEs and large firms. It is important that a firm should focus
on all dimensions of adoption practices, namely, integration practices, sourcing
practices and technological capabilities, entrepreneurial orientation, flexible sourcing
and manufacturing practices to achieve the desired level of manufacturing flexibility.
Third, the study highlights a range of barriers that hinders manufacturing flexibility
adoption. These barriers are found more prevalent in SMEs than large firms. The study
suggests that there are barriers at different levels and these barriers are often
interlinked. The major barriers associated with manufacturing flexibility adoption are
inadequate knowledge regarding implementation of manufacturing flexibility, low
level of technology adoption, lack of top management supports, fear of increasing
overall cost and absence of suppliers’support. Therefore, the study provides ample
scope of improvement with respect to these barriers. Managers should give due
consideration to these issues before considering manufacturing flexibility adoption.
7.3 Limitations and future research directions
The study has certain limitations that should be taken into consideration when
interpreting its findings. First, cross-sectional survey used in this research is confined
to specific regions of India. Longitudinal survey with a geographically diversified
sample can bring better insights about the manufacturing flexibility adoption practices
in SMEs and large firms over time. Second, the questionnaire used in this study
includes subjective measures that may limit understanding of flexibility adoption at
plant level as inclusion of objective measures offers precision and lead to better
generalization of findings. In future research, in addition to qualitative measure,
quantitative measures can also be considered. Third, small sample size is another
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limitation that restricts the application of advanced statistical techniques in the
analysis. The application of advanced statistical techniques with large sample size can
assist in getting more valid and reliable results. However, studies done by Dora et al.
(2014) and Panwar et al. (2015) on implementation of lean practices in firms also applied
descriptive due to small sample size. Regardless of the aforementioned limitations, this
study attempts to compare and evaluate manufacturing flexibility adoption practices in
SMEs and large firms in India.
The study proposes several avenues for future research based on the limitations of
this study. The sample was drawn from northern and western part of India and thus
any future research should focus on more geographically diversified sample. Since the
status, adoption rate, and barriers can significantly vary across countries and
industries, future research can focus on finding the underlying differences across
countries and industries. Moreover, the barriers to manufacturing flexibility adoption
are not exhaustive and these barriers can differ from country to country. Therefore,
replication of this study in other countries can provide better insights about barriers to
manufacturing flexibility adoption in these countries. A useful extension of this work
can be to assess how the differences in adoption practices influence the other
performance aspects, such as cost, quality and delivery, of SMEs and large firms.
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Further reading
Berry, W.L. and Cooper, M.C. (1999), “Manufacturing flexibility: methods for measuring the
impact of product variety on performance in process industries”,Journal of Operations
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for manufacturing flexibility”,International Journal of Operations & Production
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Corresponding author
Ruchi Mishra can be contacted at: ruchi461@gmail.com
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