Case Study

Validity and reliability of lean enterprise frameworks in Indian manufacturing industry

Proc IMechE Part B: J Engineering Manufacture 2016, Vol. 230(2) 354–363 Ó IMechE 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0954405414555736 pib.sagepub.com

Naga Vamsi Krishna Jasti1 and Rambabu Kodali2

Abstract Lean principles are useful to achieve excellence in all aspects of business processes. In the present global scenario, the implementation of lean principles in Indian manufacturing is essential to compete globally. The purpose of this study is to conduct validity and reliability analysis on existing lean enterprise frameworks while applied to Indian manufacturing organizations. The study used survey questionnaire method to collect data from manufacturing industries. The data were collected against 31 lean enterprise frameworks from 180 middle and top management personnel belonging to 180 Indian manufacturing firms. The survey instrument was developed with a team of 12 members, that is, 6 experts each from academic and industry background and also performed pilot study to improve understanding of the respondents. Reliability and factor analysis has been carried out to measure each framework’s Cronbach’s alpha (a reliability coefficient) and unidimensionality with respect to the constructs, that is, the lean enterprise it measures. Finally, frequency distribution analysis was performed on the selected framework to identify familiar elements of lean enterprise. This research has brought out that a majority of the frameworks exhibit a high level of reliability. When the study has investigated further about unidimensionality with respect to the construct, that is, the lean enterprise it measures, it showed that a few of the frameworks were exhibiting unidimensionality. A frequency distribution analysis illustrates that the majority of the constructs have a high mean score and mode. Finally, the study concludes that there is a need for a new framework to fulfill the requirement of Indian manufacturing industry.

Keywords Lean manufacturing, empirical research, lean enterprise, reliability analysis, validity

Date received: 2 December 2013; accepted: 22 September 2014

Introduction From the early 1980s, Japanese firms have dominated the manufacturing sector with low-cost, superior quality products and on-time delivery systems. All these achievements were possible by implementing just-intime (JIT) manufacturing, continuous improvement and best quality methods. Later, the US manufacturing firms understood the secrecy of the success of Japanese manufacturing firms. The US firms started adapting these technologies, processes and practices, which in turn helped them to face challenges, in some cases even exceeding their Japanese competitors in terms of fulfilling the customer requirements. With this, manufacturing became one of the key strategic activities to continue in the global markets.1 Most of the Indian manufacturing industries benefited from a protectionist regime until the early 1990s. Since the start of economic liberalization in the early 1990s, Indian manufacturing

industries are facing heightened challenges from global competition in aspects of low cost, better quality, improved product performance and better services.2 Now there is no doubt that Indian manufacturers can accept the challenges from global competitors. However, they have to focus on improvements in their key activities or processes to fulfill customer requirements and stay in global competition.3 In recent times, China and Southeast Asian countries have become the manufacturing hubs of the world. 1

Department of Mechanical Engineering, Birla Institute of Technology and Science (BITS), Pilani, Pilani, India 2 National Institute of Technology, Jamshedpur, Jamshedpur, India Corresponding author: Rambabu Kodali, National Institute of Technology, Jamshedpur, Jamshedpur 831014, India. Email: [email protected]; [email protected].

Jasti and Kodali Many global organizations have established and are also interested to establish manufacturing firms in China and Southeast Asian countries due to low labor cost and raw material availability, which is resulting in low manufacturing cost. Hence, China has become one of the leading global economies and has achieved high employment rate.4 Consequently, China’s gross domestic product (GDP) has grown around 9.5%–11.0% per annum on the domestic front and has also recorded a growth rate of 35% on the international front.5 Is such a high level of manufacturing growth possible in India? It is not a secret that India is an upcoming manufacturing hub to the global investing firms. India’s manufacturing sector is currently contributing to 16% of the total economy and also anticipates bright future contributions of around 25% of the total economy by the end of the next decade.6 The growth has been possible through focus on manufacturing excellence, which is evident from the number of Deming awards given to a country, based on which Indian manufacturing firms have been placed second only to their Japanese counterparts.1 India is moving in the direction of becoming one of the prime manufacturing investment locations for multinationals. Indian manufacturing companies have seen significant growth internationally as well as within the country over the last two decades. All these achievements have been possible due to the following reasons: First, the substantial reduction in trade barriers in India and across the world, particularly with respect to manufacturing products. Second, the implementation of advanced technology that is taking place, which is resulting in productivity improvement and cost reduction of the product. The third is the emergence of China and other Southeast Asian countries as low-cost manufacturing hubs. All these have contributed to the fact that the Indian economy, and in particular the manufacturing sector, has had to change to meet the challenges. India’s economy has situated itself positively as a center of competitive supply, technology innovation, design and business activities. However, when the availability of vast natural resources, human resources, economy and manufacturing potentials in India is considered, it can be easily seen that India is still unexploited with regard to the resources. It indicates that the prospects for India are immense, but various constraints also exist like aspects of culture and organizational thinking.1 Indian manufacturing industries are struggling to achieve better productivity rate due to various constraints. The following numbers are clear indication of how much Indian manufacturing industry is lagging compared with other Asian countries. The average growth rate in terms of productivity in manufacturing in India is 4.95% in comparison to 7.31% of China, 9.45% of Singapore and 8.65% of Pakistan.7 Thus, the government and industries have to take responsibility to overcome the various challenges that are faced by the Indian manufacturing industry. To compete in the global marketplace, Indian firms have to implement advanced manufacturing systems

355 and practices. It is an integrated combination of processes, people, machine systems, communication, organization structures and computers. The final objectives are to achieve economic products, competitive performance, responsiveness, flexibility in the system, quality products and services.8 Some of the most extensively practiced and implemented advanced manufacturing techniques/philosophies for change are lean manufacturing (LM) system, JIT production system, total quality management system and business process reengineering.9 But looking at the other side of the coin, according to Strozniak,10 less than 20% of Indian industries are practicing advanced manufacturing systems like lean principles in their organization. It is a very clear indication of the extent to which the Indian manufacturing industry is struggling in implementation of advanced manufacturing systems. Very few Indian companies, including Hero Group, Maruti and their ancillaries, Kalyani Group, Bajaj automobile and Mahindra & Mahindra are implementing the advanced manufacturing philosophies in their companies to achieve the required objectives of the organizations. The Indian manufacturing sector has to think of ways to achieve excellence in all aspects of business activities. To meet these objectives of Indian manufacturing industries, a systematic approach needs to be developed that not only fits the Indian manufacturing industry but also incorporates the best practices established by other countries. Instead of developing a new lean enterprise (LE) framework from ground level, any research needs to check usefulness of the existing LE frameworks in Indian environment. This study conducted a nationwide survey to find out suitable frameworks to implement in the Indian manufacturing industry. The results obtained have been analyzed and are being presented in this article. The present study covers the following areas: first, finding the existing LE frameworks from the literature and performing their validity analysis for Indian environment; second, carrying out reliability analysis on selected LE frameworks to check the reliability of the frameworks; and third, performing frequency analysis to identify significant elements/ constructs. Sharma and Kodali1 conducted a similar kind of study on manufacturing excellence frameworks. The article is arranged as follows. Section ‘‘Literature review in LE’’ reviews the literature about LE and explains its pertinence in this study. Section ‘‘Research methodology’’ gives research methodology applied for this study. Section ‘‘Results’’ implies that validity and reliability analysis results are discussed. Finally, section ‘‘Conclusion’’ is about conclusions of this study.

Literature review in LE In the mid-1980s, Japanese automobile industry was dominating the world with the implementation of Toyota Production System (TPS).11 The main objective

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of TPS is removing all types of waste and abnormality in the manufacturing operations. In early stage of TPS, few investigators12,13 termed it as ‘‘JIT production.’’ The reason might be the perception that the aim of TPS strategy is to minimize in-process stock. Another important feature of TPS is producing the required product, at the right time, in right quantity and should take away the redundant stock.14 The term LM had appeared in the book The Machine That Changed the World by Womack et al.15 in the year 1990. LM principles were spread across the world due to its impact on manufacturing operations. Later, after seeing the response from manufacturing operations, the same investigators expanded LM principles across business activities of the organization and proposed a new strategy called LE.16 An LE, by definition, delivers utmost value to its consumers in all aspects of product, with modest utilization of resources (materials, individual, funds, time, machinery, information, energy, etc.). To demonstrate this, Womack and Jones17 reported a case study of Lantech, a wrapping machine producer. They discussed about the application of the five tenets of LM across business activities, which led to unimaginable results in every aspect of its business. After that, publications dealing with application of LM in other functional areas of the organization such as product development,18 purchasing19 and distribution20 slowly came out. However, the number of articles dealing with the application of lean principles in manufacturing operations predominantly dominated over other functional areas. However, the articles published on the issue of LE strategy were very minimal due to the lack of clarity on LE concept. Later, Karlsson and A˚hlstro¨m21 reported LE as a combination of lean development, lean procurement, LM and lean distribution. According to Womack and Jones,16 LE is a system which can be used to integrate all operations within the organization, whereas Karlsson and A˚hlstro¨m21 reported that LE across the boundaries of the organization and business partners have to be included for identification of the waste in the system. The ultimate target of the LE is to find waste procedures across business activities of the organization and eliminate these waste procedures from the system. Waste can be any activity that does not create any value for the customer. Lean principles deal not only with the removal of waste and but also ensure that the production flow is smooth and well-organized.22 The waste concept consists of all possible defective activities, not only faulty products. Waste can be categorized into eight areas as follows: 1. 2. 3.

Motion: the unnecessary movement of employee, which leads zero value addition to the process. Waiting: the idle time created while goods, information, employee or machinery is not ready. Correction: the final products that contain faults and reworks

4. 5. 6. 7. 8.

Over-processing: the processes that cannot add any value from the customer’s perspective. Over-production: manufacturing more products than the consumer needs right now. Transportation: the movement of goods that will not give any value to the system. Inventory: storage of more resources, parts or goods than the customer requirements. Knowledge: lack of confidence of employees about the best way to carry out responsibilities.

The journey of lean philosophy started with the development of TPS. It is rapidly progressing toward ‘‘LM’’ and finally it is configured in the form of LE. There are two approaches to eliminate these seven wastes. First approach is to implement various kinds of lean tools and techniques to eliminate waste from the processes. There is a second approach to eliminate these seven wastes, which is implemented by Toyota Motor Company: in the second approach, the main focus is to improve the flow of work, which resulted in steady elimination of unevenness from the system and not upon waste reduction. Generally, lean techniques used to enhance the flow include production leveling, pull production and heijunka box. This is a fundamentally different approach to most improvement methodologies which may partially account for its lack of popularity.23 The main distinction between these two approaches is not the objective but the methodology to attaining it. The main objective of implementation of smooth flow is to expose quality problems, which already exist in the system. Then the waste reduction naturally happens as a consequence. The main advantage for this methodology is a system-wide perception. Some of the Toyota employees were surprised after seeing the tool-based approach, as they see the tools as essential work-a rounds, where the flow could not be fully implemented and not as aims in themselves. Many researchers have suggested that organizations implement the most suitable methodology as per their requirement, instead of simply following the Toyota system. However, many organizations preferred to implement a similar kind of approach followed by Toyota without understanding their system and requirements. The Toyota employees have argued that any organization works in dynamic working conditions and problems. Hence, other organizations require appropriate methodology to resolve the problem and should not implement practices that Toyota is practicing. Both lean principles and TPS can be seen as a loosely associated set of principles. The objective of these strategies is cost reduction by the elimination of waste.12 After the huge success rate of lean principles in manufacturing operations, many researchers have started to implement supply chain management and product development activities as well. According to Womack and Jones,16 the philosophy of LM principles can be implemented not only in manufacturing operations but also across the enterprise. Finally, the researchers proposed the philosophy

Jasti and Kodali of ‘‘LE.’’ They defined ‘‘LE’’ as a group of individual functions legally divided but operationally synchronized in organization.24 Karlsson and A˚hlstro¨m21 reported the LE as a combination of lean product development, lean procurement, LM and lean distribution. Among the elements of the LE suggested by them, the concept of lean supply chain management deals with both lean procurement and lean distribution. There are too many contradictions about implementation of lean principles that helps to improve the productivity and quality. Coffey and Thornley25 have argued that there is no evidence in terms of productivity and quality rise due to implementation of lean principles since the last 20 years in the United Kingdom. McLaughlin26 has conducted surveys across globe and concluded that many organizations have struggled to implement lean principles in their organizations. The same study also revealed the productivity rate in the United Kingdom is very low (21% lower than G7 countries) as compared with other developed countries such as the United States, Japan, Sweden and Germany. The study has also analyzed the main reasons for these results, which are as follows: UK organizations’ lack of commitment in implementation of management practices27 and their relatively low skill levels. According to Zhu and Meredith,28 training and education play very important roles in implementation of lean principles in any organization. But the education level of management of UK organizations is lower than other development organizations.27 McLaughlin26 has suggested to improve employee education qualification, which will help to improve effective implementation of advance manufacturing systems. In fact, the basic lean principles that can help to achieve excellence in manufacturing operations can be adapted for use in any business processes. When the lean philosophy was implemented across all business processes, it leads to the most efficient use of resources, competent use of time and finally fulfilled the customer requirements. Rubrich and Watson29 reported that world-class manufacturing is usually understood as ‘‘sophisticated manufacturing method that can be adapted and used to elevate a facility’s manufacturing performance to world-class levels.’’ A phrase for quantifying ‘‘world class’’ was given by the definition of lean production by Womack et al.:15 uses less of everything—half the human effort in the factory, half the manufacturing space, half the investment in tools, half the engineering hours to develop a new product in half the time. Also, it requires keeping far less than half the inventory on site, results in many fewer defects, and produces a greater and ever growing variety of products.

When the study investigated the implementation status of LM principles in Indian manufacturing industry, it clearly indicated that most of the industries are not able to sustain it.30 The main reason for failure to

357 implement LM is improper sequence of implementation of LM elements in their system. In the present global scenario, to compete with global players, Indian manufacturing industry should achieve effective business activities across the organization instead of just in manufacturing operations. Hence, the study concluded that there is a need of identification of the suitable LE framework to implement lean principles in the Indian manufacturing industry.

Identification of existing LE frameworks The term framework does not have a clear-cut definition from the research world. However, it is a very popular term in the LE literature. Many researchers are using the model in the place of framework or vice versa. It is all happening due to the lack of clarity about what is framework or model. This study investigated what is indeed a framework. Few researchers tried to give proper definition of the framework and model. Yusuf and Aspinwall31 reported that ‘‘a model can answer to the question of ‘what is’ with the overall perception or elements put down together, whereas a framework attempts to answer ‘‘how to’’ questions and presents an overall relationships and method forward.’’ According to Anand and Kodali,32 a framework can be useful to the managers of the organization as a guiding torch, which can assist and show the required path during implementation of the new advance manufacturing philosophy in an organization. Gunjan and Kodali33 reviewed entire existing literature on the framework and concluded that the framework should fulfill the following conditions: 





A framework is not only just recommended bunch of elements to be considered in that system. It should give information about the complete relationships among elements of system under study. A framework should discuss the important steps and stages of activities and how these are vital for the required purpose. A framework should give information about all the activities that are involved and connection of various elements of frameworks with those activities.

To achieve LE excellence in any industry, many researchers, professionals and experts have proposed different frameworks. These frameworks can give the direction to attain LE excellence in their organizational activities and fulfill the customer requirements. The study found 31 LE frameworks by conducting literature survey in various portals. The complete list of frameworks considered in this study is given in Appendix 1 (available online). The complete coverage of all frameworks may not be viable due to various constraints regarding resource accessibility. Hence, the study is considering only widely acceptable and used frameworks to conduct analysis in Indian manufacturing industry environment. The study is projecting the

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Table 1. Taxonomy of lean enterprise excellence frameworks. Taxonomy

Frameworks

Researcher/ academic based

Cook and Graser Karlsson and A˚hlstro¨m Sayer and Williams Czarnecki and Loyd Czabke CTRM Aero Composites Lean Breakthru Consulting Group J.E. Boyer Company, Inc. Beason Conner Unlimited Possibilities Consulting LLC Fraunhofer IPA Slovakia The MIT Lean Aerospace Initiative Crawford Scrimshire Columbus Unisa Strategic Partnerships Industrial Solutions, Inc. Lucansky et al. Wyrick Enterprises Karen Martin & Associates Zayko Archfield Consulting Group Productivity Inc. Bohan and Accorti Moffitt Associates Consultants Lean Enterprise LLC Broadsight Analysis Lean Enterprise Canford Consultants Just-in-Time Enterprise Institute Howardell

Consultants/ experts based

present list of LE frameworks as representative of total LE framework existing in the literature. The frameworks can be categorized under two broad areas, namely (1) researcher/academic based and (2) consultants/experts based. Table 1 shows the taxonomy of LE excellence frameworks.

Research methodology A cross-sectional study by using survey research design was conducted on chosen multi-sectional industries of manufacturing sector. A survey questionnaire was prepared to collect data for this study. In order to achieve the objectives of this research, the study focused on different multi-sectional industries in manufacturing industrial sectors, that is, the automobile industry, process industry, machinery equipment, electrical and electronics and the textiles industry.1 The Confederation of Indian Industry’s (CII) database directory for the year 2011 was referred to collect the addresses of manufacturing industries. The employees involved in the survey are from various levels like managing directors/CEOs, production managers, maintenance managers, logistics managers, human resource managers, product managers and quality managers.

A structured questionnaire was developed using the 5-point Likert scale. The scale ranged from 1 to 5, where 1 means not important, 2 means less important, 3 means important, 4 means more important and 5 means most important. The complete details of questionnaire are given in Appendix 2 (available online). The study requested the respondents to consider each framework as an independent entity and as part of a path toward achieving LE excellence. The questionnaire consisted of two parts: Sections A and B. ‘‘A’’ is the background information of the organization and the respondent information and ‘‘B’’ is a structured questionnaire of all considered frameworks in this study. The objective of the present study and instructions to fill out the survey were discussed in the covering letter. The covering letter was also helpful to the organizations to gather information regarding email communication of the present study authors. In early stage of questionnaire development process, the study consulted the experts from industries and academics. The comments and feedback of the experts were considered and a few minor enhancements were made especially in questionnaire format. Most of the experts gave the feedback on questionnaire format and finally declared that it was suitable for data collection. To make sure, the study performed a pilot study to reinforce the experts’ feedback. The study expected that the respondents have basic idea about the lean principles and practices. The language used in each LE excellence framework is simple for easy understanding to the respondents. However, the authors gave their contact details in the covering letter to the participants, in case of any ambiguity on the questionnaire elements. A final version of the questionnaire was sent to a sample of 753 manufacturers, which were selected from a population of Indian manufacturing organizations. Four weeks later, the authors sent 182 postal reminders and 423 emails to non-responding organizations and also communicated personally over telephone. The authors received 186 replies from various industries of Indian manufacturing sector, which puts the response rate at 24.70%. However, the authors did not consider six incomplete questionnaire responses to final analysis, whereas the remaining 180 manufacturer responses were considered, which make the response rate 23.90%. According to Sharma and Kodali,1 a response rate of 18% is considered to be adequate in Indian manufacturing industry conditions. The statistics of the individual sector responses are shown in Table 2. Part A of the questionnaire revealed that the average amount of respondent experience is 12 years, which clearly suggests the respondents had enough experience to respond to the questionnaire. The study has considered responses from the organizations who are practicing some kind of advanced manufacturing systems. The respondent organizations comprised around 61.66% of large-scale organizations and the remaining organizations were small- and medium-scale industries. The study also observed that around 48% of the

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Table 2. The statistics of the individual sector responses. Industry

No. of responses received by post

No. of responses received by email

Total No. of responses received

Sample size

Response rate (%)

Automobile Machinery equipment Electrical and electronics Process Textile Total

25 17 12 13 5 72

30 25 20 18 15 108

55 42 32 31 20 180

202 152 190 150 59 753

27.23 27.63 16.84 20.67 33.90 23.90

organizations have practiced lean principles for less than 2 years. The study also observed that 82% of the organizations have implemented lean principles in manufacturing operations areas only.

Reliability analysis Reliability analysis was used to find whether the survey instrument is producing the repetitive results at any time it is administered to the same respondent under same settings regardless of who administers them.34 Walsh and Betz35 discussed four types of reliabilities: test–retest reliability, alternate forms reliability, splithalf reliability and internal consistency reliability. Many researchers preferred to use internal consistency methods due to its various advantages such as consistency and the fact that it only requires a single application to get required results.36 Cronbach’s alpha coefficient is the most commonly used to measure internal consistency of any framework.37 It can be calculated using standard commercial package SPSS, which is a user-friendly software package.34

Validity Validity is defined as the extent to which any measuring instrument measures what it is intended to measure.38,39 Initially, few researchers proposed four types of validity analysis. Over a period of time, many researchers like Creswell40 and Muijs41 amalgamated both concurrent validity and predictive validity. Finally, the researchers proposed three different types of validity analysis. Those are as follows: (1) content validity, (2) criterion-related validity and (3) construct validity. Reliability is a necessary condition for validity, but reliability is not sufficient to determine validity alone.42 In this study, validity analysis was carried out by using three measures: 1.

2.

Content validity is determined by qualitative approach and a judgment made by panel of experts. The main objective of content validity is used to check whether all aspects of the attributes are considered in the survey instrument.39 It can be determined by expert opinions and cannot be determined by statistical methodologies.43 Criterion validity was used to determine how well the result obtained from one data-gathering

3.

instrument is supported by other surveys or questionnaires. It can be determined by comparing the results of the various data gathering instruments. It gives information about the extent of observations of two different surveys differentiating from each other. The criterion-related validity is validating by simple correlation, for testing a scale of constructs for a single outcome. Construct validity provides the researcher with confidence that a survey actually measures what it is anticipated to measure. It can be measured through empirical survey and cannot be directly evaluated. Factor analysis is the most reliable method to perform construct validity. Factor analysis is conducted to check whether all elements are loading on to a single factor, that is, unidimensionality of the scales toward a single construct. In this study, the factor analysis has been used to check unidimensionality of each framework.1

Results The validity analysis was performed on each LE excellence framework to find eligible LE excellence frameworks that could be used for further investigation. The content validity of the questionnaire items was performed by two stages: initial stage, the questionnaire was administered to six practitioners in industry and six academicians from Birla Institute of Technology and Science, Pilani. The feedback given by them was incorporated in the questionnaire. Final stage, the questionnaires were also sent to academicians in other prestigious institutions and also pilot study was conducted in a reputed automotive industry. The sample size of the pilot study is 30 comprising people in the middle- and top-level management, who have complete knowledge about lean principles. The comments and feedback of the experts were taken into consideration and a few minor enhancements were made especially in questionnaire draft format. Finally, the questionnaires were sent to various Indian manufacturing organizations. Criterion-related validity has been used to check whether the frameworks’ measure positively related to the level of LE excellence in an organization. This study did not evaluate criterion-related validity of the frameworks because the level of LE excellence was not

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Table 3. Factors extracted from each framework. Name of the framework Cook and Graser CTRM Aero Composites Lean Breakthru Consulting Group J.E. Boyer Company, Inc. Beason Conner Karlsson and A˚hlstro¨m Unlimited Possibilities Consulting LLC Fraunhofer IPA Slovakia The MIT Lean Aerospace Initiative Crawford Sayer and Williams Czarnecki and Loyd Scrimshire Columbus Unisa Strategic Partnerships Industrial Solutions, Inc. Lucansky et al. Wyrick Enterprises Karen Martin & Associates Zayko Archfield Consulting Group Productivity Inc. Bohan and Accorti Moffitt Associates Consultants Czabke Lean Enterprise LLC Broadsight Analysis Lean Enterprise Canford Consultants Just-in-Time Enterprise Institute Howardell

Number of factors extracted 1 3 1 2 1 1 1 1 3 4 2 2 3 2 3 5 1 2 4 3 1 1 3 1 7 3 3 2 2 1 2

incorporated. The study assumed that the respondents carried out a validity analysis on their respective frameworks in their manufacturing environment. The similar kind of approach was followed by Sharma and Kodali1 in their research on manufacturing excellence framework. Finally, the construct validity of each framework was conducted. The objective of the construct validity is to check whether it measures the concept or the theoretical construct it was anticipated or designed to measure. The validity analysis can be performed on any scale, but the scale should satisfy two conditions: One is unidimensionality of the scale.44 Unidimensionality is used to check whether all elements are concentrated toward the main target of the measurement.44,45 Unidimensionality is used to find a set of elements or constructs forming an instrument to measure one thing in common. Second, the scale should fulfill the reliability conditions as well.46 Hence, on all the considered frameworks, the unidimensionality checks as well as the reliability analyses were conducted. The factor analysis was used to conduct construct validity on all 31 LE excellence frameworks. The factors extracted from each framework are listed in Table 3. The analysis shows that only 11 frameworks displayed unidimensionality with respect to LE excellence. Table 4 shows an example of a component matrix for the framework of

Table 4. Component matrix for the framework of Archfield Consulting Group. Elements

Component 1

5S Visual management Pull production Waste elimination Standard work Zero defects Workforce empowerment Continuous improvements (Kaizen)

0.724 0.763 0.609 0.741 0.807 0.861 0.796 0.800

Extraction method: principal component analysis.

Archfield Consulting Group, which is result of the principal component analysis for the factor extraction. The frameworks displaying unidimensionality are as follows: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.

Cook and Graser Lean Breakthru Consulting Group Beason Conner Karlsson and A˚hlstro¨m Unlimited Possibilities Consulting LLC Industrial Solutions, Inc. Zayko Archfield Consulting Group Bohan and Accorti Just-in-Time Enterprise Institute

Internal consistency or reliability of the frameworks can be checked by inter-item analysis. One of the most commonly used indicator of internal consistency is Cronbach’s alpha coefficient. Internal consistency is used to find the extent to which constructs or elements on the test or instrument are measuring the same thing. For instance, if any researcher has developed a survey to measure organizational commitment, the researcher should verify the reliability of each item. The individual constructs or elements are highly associated with each other. The possible outcome of the test is higher reliability of the entire scale. The advantage of internal consistency is that it is estimated after only one test administration. Preferably, the framework’s Cronbach’s alpha coefficient of a scale should be above 0.7, which is considered to be good.47,48 Cronbach’s alpha coefficients of the 11 selected frameworks were more than 0.7 and a mean of more than 3.5. Table 5 shows the mean and reliability analysis results for the selected frameworks. Tables 6–8 show the reliability analysis for the framework of Archfield Consulting Group. From these selected frameworks, the most important elements were recognized by applying frequency distribution. A value of mode of 4 or more was used as the criterion for choosing elements (i.e. most frequently occurring value). The sample frequency analysis statistics performed on the framework of Archfield Consulting Group is shown in Table 9. Majority of the elements in

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Table 5. Mean and reliability analysis results for the selected frameworks. Framework name

Cook and Graser

Lean Breakthru Consulting Group

Beason

Conner

Karlsson and A˚hlstro¨m

Unlimited Possibilities Consulting LLC

Industrial Solutions, Inc.

Zayko

Archfield Consulting Group

Bohan and Accorti

Justin-Time Enterprise Institute

Overall mean Cronbach’s alpha

4.263 0.789

3.65 0.789

4.106 0.87

4.033 0.865

3.967 0.726

4.112 0.794

3.739 0.85

3.778 0.901

3.89 0.895

3.848 0.86

3.708 0.877

Table 6. Reliability analysis for the framework of Archfield Consulting Group: summary item statistics. Number of cases: 180

Mean

Minimum

Maximum

Range

Maximum/minimum

Variance

No. of items

Item means Inter-item correlations

3.890 0.522

3.650 0.338

4.083 0.714

9.433 9.376

1.119 2.109

0.023 0.012

8 8

Table 7. Reliability analysis for the framework of Archfield Consulting Group: item-total statistics.

F22.1 F22.2 F22.3 F22.4 F22.5 F22.6 F22.7 F22.8

Scale mean if item deleted

Scale variance if item deleted

Corrected item-total correlation

Squared multiple correlation

Cronbach’s alpha if item deleted

27.2333 27.3333 27.4667 27.1000 27.2667 27.0333 27.3167 27.0667

21.130 20.939 22.172 21.208 20.945 21.016 20.631 21.817

0.635 0.697 0.517 0.652 0.721 0.793 .707 .715

0.499 0.598 0.351 0.570 0.641 0.684 .645 .625

0.886 0.880 0.897 0.884 0.877 0.872 .878 .879

Table 8. Reliability analysis for the framework of Archfield Consulting Group: reliability statistics. Cronbach’s alpha

Cronbach’s alpha based on standardized items

No. of items

0.895

0.897

8

Table 9. Statistics of the frequency analysis carried out for the framework of Archfield Consulting Group.

N

Valid Missing

Mean Median Mode

5S

Visual management

Pull production

Waste elimination

Standard work

Zero defects

Workforce empowerment

Continuous improvement (Kaizen)

180 0 3.8833 4.0000 4.00

180 0 3.7833 4.0000 4.00

180 0 3.6500 3.5000 3.00

180 0 4.0167 4.0000 4.00

180 0 3.8500 4.0000 3.00

180 0 4.0833 4.0000 4.00

180 0 3.8000 4.0000 3.00

180 0 4.0500 4.0000 4.00

each framework were recognized as critical elements from the selected eleven frameworks. Finally, a total of 44 elements were selected from the 11 frameworks.

Conclusion The objective of this article is to conduct validity and reliability analysis on existing LE excellence

frameworks applied to Indian manufacturing environment through questionnaire survey methodology. This study reported that most of the frameworks exhibited high level of reliability and few frameworks displayed unidimensionality with respect to the construct, that is, the LE excellence it measures. Most of the constructs have a high mean and mode score, which was examined through the frequency analysis. Finally, the frameworks

362 displayed different constructs with a certain amount of overlap between them. When the study investigated validated 11 frameworks, many important constructs were not found such as knowledge management, customer relationship management and total productive maintenance (except Bohan and Accorti framework). Very few frameworks reported importance of top management commitment in their frameworks. The Bohan and Accorti framework did not consider important elements such as total quality management and continuous improvement. Hence, it clearly shows that none of the existing frameworks can be used in their present form due to various limitations. Interestingly, even a single framework was not reported from the Indian manufacturing organizations. It clearly shows that there is a need of development of new frameworks, which can be more useful to fulfill the present vacuum and for Indian manufacturing environment. In the present global scenario, LE excellence is an important alternative for Indian manufacturing sector to battle successfully with the global companies. Hence, Indian manufacturing industry needs a novel framework to compete with global manufacturing players, which needs to be developed considering all the present aspects of the Indian manufacturing industry. However, a complete development of a novel LE excellence framework is beyond the scope of this study. It can be carried out as a part of future research. The limitation of this article is that the survey is restricted to only the Indian manufacturing sector with the sample size of 180 only. In the end, the authors would like to suggest future researchers to validate various LE frameworks not only from manufacturing sectors but also from service, infrastructure and various other sectors across the globe instead of only limiting to India. Declaration of conflicting interests The authors declare that there is no conflict of interest. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. References 1. Sharma M and Kodali R. Validity and reliability of applying manufacturing excellence frameworks to Indian industries. Proc IMechE, Part B: J Engineering Manufacture 2008; 222(6): 723–739. 2. Dangayach GS and Deshmukh SG. Manufacturing strategy: experiences from Indian manufacturing companies. Prod Plan Control 2001; 12(8): 775–786. 3. Chandra P and Sastry T. Competitiveness of Indian manufacturing: findings of the 1997 manufacturing future survey. Vikalpa 1998; 23(3): 25–35. 4. Norman JR. The oil card: global economic warfare in the 21st century. Walterville, OR: Trine Day, 2008.

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