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International Journal of Engineering Research and Development
e-ISSN: 2278-067X, p-ISSN: 2278-800X, www.ijerd.com
Volume 8, Issue 3 (August 2013), PP. 07-13
7
Empirical Research on TQM Practices of Organizations –
Development and Validation of Critical Factors &
Comparison of Manufacturing and Service Organizations
Anu P.Anil1
, Dr.Satish K.P2
1
M Tech student, 2
Associate Professor, 1,2,
Department of Production Engineering, Government Engineering
College Thrissur, Thrissur, India-680 009
Abstract:- Total Quality Management (TQM) is an integrative management philosophy aimed at continuously
improving the quality of products and processes to achieve customer satisfaction. The objective of this paper is
to describe an empirical research on the development of a tool to measure the quality management in different
organizations. It provides empirical evidence on top management’s awareness and understanding of the quality
management and its role towards business survival and competitiveness. Through a detailed analysis of
literature, this paper identifies thirteen critical factors of quality management .Using a survey of twenty
organizations, the critical factors are empirically tested and validated. SPSS is used for this purpose. This
provides reliable and valid critical factors of total quality management and develops a measurement instrument
for evaluating the TQM implementation process and to target improvement areas. In this paper, we compare the
quality management practices between Indian manufacturing and service organizations based on the survey of
104 organizations by using non parametric test. The results presented here are focused on thirteen critical factors
of quality management. The study shows significant differences between manufacturing and service
organizations with manufacturing organizations performing better in quality management practices.
Opportunities for improving quality management practices in Indian service organizations were identified.
Keywords:- Total quality management (TQM), Reliability,Validity,Internal consistency method, Factor
analysis, Multitrait multimethod matrix (MTMM),Mann Whitney U Test,Non parametric test .
I. INTRODUCTION
Total quality management (TQM) allows firms to obtain, on the one hand, a high degree of
differentiation, satisfying customer’s needs and strengthening brand image, and on the other, to reduce costs by
preventing mistakes and waste of time and by making improvements in the corporation's processes. In this
respect, both researchers and managers have been interested in studying quality management, and identified a
number of elements for a successful implementation. Thus, various studies have been carried out for the
identification of those critical factors ensuring its success, as a way to develop a theory of quality management
from three different areas: contributions from quality leaders (Crosby, 1979; Deming, 1982;
Ishikawa,1985;Juran, 1988; Feigenbaum, 1991), formal evaluation models (European Quality Award, Malcolm
Baldrige National Quality Award, The Deming Award) and empirical research (Saraph, Benson and Schroeder,
1989; Flynn, Schroeder and Sakakibaru, 1994; Badri, Davis and Davis, 1995; Ahire, Golhar and Waller, 1996;
Black and Porter, 1996; Grandzol and Gershon, 1998; Quazi et al., 1998) [2].
Thus, managers need to understand what elements are necessary in order to change a firm’s culture
towards a quality culture. Starting from a review of these studies, the purpose of this paper is to contribute to:
a) identify critical factors of total quality management b) developing measures for change towards a quality
culture c) testing these measures for reliability and validity using data collected from different organizations by
using a suitable questionnaire and d) evaluate the performance of manufacturing and service organizations.
Global competition and increasingly sophisticated and demanding customers are two important factors
that are driving organizations around the world to create, develop and sustain higher levels of quality. In this
study the similarities and differences of quality management practices of manufacturing and service sectors
were analyzed. The experience and strength in the quality management of the manufacturing sector can prove to
be valuable to improve quality management in the service sector.
II. CRITICAL FACTORS OF QUALITY MANAGEMENT
The companies should develop a number of TQM constructs in an integrated way for successful quality
management implementation. The theory of quality management has been studied from different areas: quality
leaders' ideas, empirical research and formal evaluation models. This has helped to identify a set of critical
factors for a successful implementation, as a way to improve customer satisfaction and performance. Through a
Empirical Research on TQM Practices of Organizations
8
detailed analysis of literature, this paper identifies thirteen critical factors with eighty five items for the
successful implementation of TQM.
Table I: Critical Factors of Quality Management
Critical
Factors
Significance of Critical Factors
Leadership and
top
management
commitment
Management’s commitment to quality through communication and motivation of
employees. The behavioural patterns which show senior management’s personal
involvement in the quality improvement process, acceptance of responsibility for
quality performance, visibility in developing and maintaining an environment of
organizational quality excellence and sharing the vision and quality goals with the
entire company.
Customer focus Increasing contacts between the organization and customers, identifying their
requirements, assessing their satisfaction and supporting activities improving
customer satisfaction.
Supplier quality
management
Relation with suppliers in order to find the quality specifications demanded by the
firm.
Continuous
improvement
Indicates whether the firm has created an organizational structure (quality committee,
a person in charge of quality and work teams) responsible for this improvement by
identifying actions through information management.
Employee
involvement
Employees, if they fully participate in quality improvement activities, will acquire
new knowledge; realize the benefits of the quality disciplines; and obtain a sense of
accomplishment by solving quality problems. Cross-functional quality improvement
teams and quality circles, along with an appropriate evaluation and reward system for
quality improvement projects, are helpful for improving quality Employees should be
encouraged to submit suggestions and ideas for quality improvement.
Rewards and
recognition
Companies must develop formal systems to encourage, track, evaluate, reward and
recognize the individual or team effort for quality enhancement and improved
customer satisfaction. Employees should be made aware of the reward and penalty
system.
Education and
training
Measures whether the firm shows an interest in employees learning about all the basic
aspects of the firm and its business by encouraging continuous learning. It should also
include training in problem-solving and teamwork.
Strategic quality
planning
The integration of quality management and customer satisfaction in the organizational
strategic and operational plans, the organization’s long-term quality vision, and the
deployment and understanding of quality goals and policy within the organization
Process
management
Reflects how the organization controls and improves its processes by setting quality
measures (level of customer satisfaction, quality cost).
Product
innovation
Customer requirements should be thoroughly considered for product innovation.
Approaches such as quality function deployment, and experimental design help
companies translate customer requirements into action by cross functional product
innovation teams.
Quality
information and
analysis
The availability of quality-related data, timeliness of quality-related data, and the
usage of quality-related data at all levels in the organization
Quality
assurance
Sound procedures for design and introduction of new or improved products and
services. Design of process that meets and exceeds product/service quality
requirements. Error and failure prevention activities along the value-added chain.
Quality
citizenship
Consideration for public health, safety, and environmental issues as company’s
responsibility. Extension of company’s quality leadership to the external community.
Empirical Research on TQM Practices of Organizations
9
III. DEVELOPMENT AND VALIDATION OF CRITICAL FACTOR USING PILOT
STUDY
Based on a review of TQM literature and expert opinions, thirteen TQM critical factors were identified.
A detailed questionnaire was developed with the items for thirteen TQM factors along with the questions on
quality performance and information about the respondents. The questionnaire was then sent to randomly
selected manufacturing and service organizations in India. Based on the data from the survey, reliability and
validity of the questionnaire was determined. Internal consistency analysis was done to ensure the reliability of
the constructs. Content validity and construct validity were evaluated statistically to ensure that the set of
measures correctly represents the constructs, and the degree to which they are free from any systematic or non-
random error.
A. Data Collection
In order to achieve the objective different manufacturing and service organizations working in India
was considered as the population. While the database was being selected, a questionnaire was designed meeting
the objectives that had been set. Based on the review of literature thirteen critical factors were identified, but it
can’t measure directly. So to measure how the TQM is implemented in organizations indirectly a questionnaire
was developed with 101 items covering different factors. Following the methodology adopted in similar studies
(Ahire et al., 1996), a seven-point likert scale was used for all items to ensure higher statistical variability among
survey responses. Items of all the constructs were measured as: 1 – strongly disagree, 2 – disagree, 3 –
somewhat disagree, 4 – neutral, 5 – somewhat agree, 6 – agree, 7 – strongly agree [3]. Experts on the subject
were consulted, to ensure that the questions were properly phrased, and the suitability of the questionnaire was
tested on a sample of firms. The process of developing the questionnaire finished with a pilot survey, which was
used to modify and eliminate a number of variables, until the final questionnaire was designed. Finally the
questionnaire was developed with eighty five items covering domains of each factor. The data collected from
twenty different organizations were used to test the reliability and validity of tool developed. The data were
collected by means of personnel interview and based on a closed questionnaire plus a set of open questions to
clarify certain points. The questionnaire was answered by employees who have thorough knowledge about the
quality practices implemented in the organization.
B. Reliability
Reliability is the ability of the instrument to measure consistently. As the internal consistency method
is the most general form of reliability estimation (Nunnally, 1978), it has been used in this study. The internal
consistency method assesses the equivalence, homogeneity and inter-correlation of the items used in a measure.
The most popular test within the internal consistency method is the Cronbach’s coefficient α (Nunnally, 1978;
Cronbach, 1951). Cronbach’s α computes internal consistency reliability among a group of items combined to
form a single scale. It can also be computed for any subset of items. Nunnally (1978) advocates that new
developed measures can be accepted with Cronbach’s α of more than 0.60, otherwise 0.70 should be the
threshold. The measure with Cronbach’s α 0.80 or more is significant and reliable [3]. For this purpose, the
reliability for each set of items of the thirteen critical factors of TQM is calculated by using SPSS.Table 2
summarizes the Cronbach’s α for individual critical factors. The Cronbach’s α for the thirteen critical factors
ranged from 0.9511 to 0.9908 indicating a high reliability of the instrument.
Table II: Internal Consistency Method (Cronbach's Alpha (α)) Using SPSS
Factor No: of Items Cronbach's
Alpha (α)
Leadership and top management commitment 7 .9707
Customer focus 7 .9917
Supplier quality management 5 .9511
Continuous improvement 7 .9609
Employees involvement 8 .9777
Rewards and recognition 4 .9700
Education and training 9 .9908
Strategic quality management 7 .9633
Process management 7 .9693
Product innovation 5 .9612
Quality information and analysis 6 .9674
Quality assurance 7 .9807
Quality citizenship 6 .9646
Empirical Research on TQM Practices of Organizations
10
C. Validity
The validity of a measure is defined as the extent to which a construct or a set of measures correctly
represents the concept of study, and the degree to which it is free from any systematic or non-random error.
Validity is concerned with how well the concept is defined by the measure(s), whereas reliability relates to the
consistency of the measure(s).
Content validity: A measure has content validity if there is a general agreement among the subjects and
researchers that the instrument has measurement items that cover all aspects of the variable being measured. The
thirteen critical factors for measuring TQM implementation should have content validity, as the measurement
items were developed based on both an extensive review of the literature and detailed evaluations by
academicians and practicing managers. Moreover, the pre-test subjects indicated that the content of each critical
factor was well represented by the measurement items employed.
Construct validity. A measure has construct validity, if it measures the theoretical constructs that it was
intended to measure. Factor analysis can be used for evaluating construct validity. Factor analysis helps to
analyse the interrelationships among a large number of variables and explains these variables in terms of their
common underlying dimensions (constructs). It also helps reduce data that do not correlate with any of the
underlying dimensions. This measurement is calculated through a factor analysis for each of the thirteen factors.
In this analysis, each factor must be one dimensional. Hence the developed tool is found to be valid. The
summary of factor analysis of each measure is shown in Table III.
Table III: Summary of Factor Analysis for Each Measure
Construct KMO
Item
Loading
Range for
Factor 1
Eigen
Value
Percentage
Variance
Explained by
Factor 1
Leadership and top management commitment .617 .82-.97 6.037 86.239
Customer focus .799 .95-.99 6.670 95.288
Supplier quality management .805 .89-.96 4.189 83.786
Continuous improvement .766 .80-.95 5.706 81.518
Employee involvement .796 86-.97 6.969 87.107
Rewards and recognition .853 .93-.97 3.677 91.924
Education and training .784 .95-.97 8.394 93.271
Strategic quality planning .909 .69-.97 5.992 85.605
Process management .767 .81-.98 6.059 86.559
Product innovation .722 .89-.97 4.350 86.999
Quality information and analysis .704 .89-.97 5.220 87.002
Quality assurance .715 .91-.97 6.289 89.838
Quality citizenship .668 .85-.96 5.131 85.516
The construct validity is also determined by using multitrait multimethod matrix (MTMM). Multitrait
multimethod matrix analysis allows us to detangle correlations between instruments due to similarity of test
methods form and similarities due to tapping the same attribute. The MTMM is simply a matrix or table of
correlations arranged to facilitate the interpretation of the assessment of construct validity. The basic principle
of MTMM matrix is coefficients in the reliability diagonal should consistently be the highest in the matrix. The
intra attribute correlation (correlation between the items of same attributes) are to be higher than the inter
attribute correlation (correlation between the items of different attributes). The average inter attribute and intra
attribute correlations are given in Table IV.
Table IV: Average Inter Attribute and Intra Attribute Correlations
Critical Factor Intra Attribute
Correlation
Inter
Attribute
Correlation
Leadership and top management commitment 0.843 0.697
Customer focus 0.922 0.700
Supplier quality management 0.866 0.586
Continuous improvement 0.831 0.640
Employee involvement 0.892 0.729
Empirical Research on TQM Practices of Organizations
11
Rewards and recognition 0.926 0.703
Education and training 0.929 0.581
Strategic quality planning 0.869 0.593
Process management 0.876 0.704
Product innovation 0.891 0.460
Quality information and analysis 0.887 0.689
Quality assurance 0.908 0.734
Quality citizenship 0.873 0.671
IV. ANALYSIS OF QUALITY MANAGEMENT PRACTICES OF MANUFACTURING
AND SERVICE ORGANIZATIONS
The final reliable and valid questionnaire was used to collect data from different organizations in India
to analyze the quality management practices. Based on the survey of 104 organizations, the quality management
practices were evaluated using non parametric test.
Fig.1: Manufacturing and Service Organizations
A. Non parametric test
A non-parametric statistical test is a test whose model does NOT specify conditions about the
parameters of the population from which the sample was drawn. It does not require measurement so strong as
that required for the parametric tests. Most non-parametric tests apply to data in an ordinal scale, and some
apply to data in nominal scale. In this study, we compare the quality performance of manufacturing and service
sectors. The Mann-Whitney U test or Mann-Whitney-Wilcoxon rank sum test is used to evaluate the significant
differences between two independent groups. The Mann-Whitney U test or Mann-Whitney-Wilcoxon evaluates
whether the medians on a test variable differ significantly between two groups. To conduct the Mann-Whitney
U test, each case must have scores on two variables, the grouping variable (independent or categorical variable)
and the test variable (dependent or quantitative variable). The grouping variable divides cases into two groups or
categories, and the test variable assesses individuals on a variable with at least an ordinal scale. Unlike its
parametric counterpart, the t test for two samples, this method does not assume that the differences between the
samples have normality distributed, or that the variances of the two populations are equal. In this study the null
hypothesis of Mann Whitney U test is that both manufacturing and service sectors have same quality
management practices. If the asymptotic significance is less than or equal to the significance level, then there is
significant differences between quality management practices of manufacturing and service organizations. The
result of this test is shown in Table V.
Table V: Mann Whitney U Test
Critical factor Mann Whitney U Asymptotic
Significance
Leadership and top management commitment 1305.0 0.918
Customer focus 918.0 0.004
Supplier quality management 846.0 0.001
Continuous improvement 1030.5 0.036
Employee involvement 1280.5 0.783
Rewards and recognition 1181.0 0.342
Education and training 1221.0 0.485
Strategic quality planning 1252.5 0.633
Empirical Research on TQM Practices of Organizations
12
Process management 1206.0 0.436
Product innovation 1117.5 0.169
Quality information and analysis 1275.5 0.761
Quality assurance 1236.5 0.564
Quality citizenship 978.5 0.019
According to Mann Whitney test, obtained a result that manufacturing organizations have better quality
practices in the following constructs.
a) Customer focus
The result show that manufacturing organizations excel over service organizations in the following
customer orientation features:
 Building and maintaining relationship with customers to retain the customers and building their market
share.
 Meeting the requirements and trying to exceed the expectations of customers in every life cycle of
product.
 Determining satisfaction level of customer and compare it with the competitor and bench markers.
 Following up with customers on the quality of product, customer support, after sales service to receive
immediate feedback.
 Effectively making use of the voice of the customer data and information (including complaints) to
develop operational and strategic quality plan and for product innovation.
 Adopting new strategies to improve company responsiveness to customer’s complaints
So the service companies need to adopt new strategies to improve company responsiveness to
customer’s complaints. One of the success factors in service sector is the ability to meet the customer
expectations and respond faster to customer complaints and concerns.
b) Supplier quality management
 Manufacturing organizations ensure that supplier selected are qualified and positioned to enhance
performance and customer satisfaction and
 Continuously evaluate supplier performance and discard poorly performing suppliers.
c) Continuous improvement
 Manufacturing organizations identifies the importance of continuous improvement of all of its products,
processes and services.
 By self assessment activities and creating an organizational structure, they identified areas and actions
for improvement through information management.
d) Quality citizenship
 Manufacturing companies exhibiting higher levels of community involvement through quality, and
higher levels of responsibility for different social concerns than service companies.
 They concerned about the impact on society due to the current and future product and process.
 Pay attention to the workforce environment ,their safety
 Government rules and regulations and certain safety standards are followed by manufacturing sectors.
 Sustainable environment is also considered as factor in making their quality policies (including
optimum use of natural resources).
Service companies need to extend their quality leadership to their surrounding community. Companies
that are socially responsible for the impact they have in the community reinforce their quality image and build a
path for customer’s loyalty.
V. CONCLUSIONS
The research develops an empirically based instrument for measuring the TQM implementation in
different organizations in India. This study provides thirteen critical factors of TQM as a model allowing
managers to have a better understanding of quality management practices. By periodically using this model, it
may serve to evaluate a firm’s quality standards, finding those areas where improvement is necessary and,
therefore, planifying the quality management effort.
From the detailed analysis of comparison of individual items of the quality practices, we find that
service organizations can learn from the experience of top quality performers in the manufacturing sector. In this
study we found that manufacturing companies outperform service companies in almost all quality factors. That
manufacturing companies excel service organization shows that it takes time to develop both a strong quality
and a customer orientation culture successfully. However, service companies in India can accelerate their
quality implementation process and learning by benchmarking the quality practices of top quality manufacturing
companies.
Empirical Research on TQM Practices of Organizations
13
ACKNOWLEDGMENT
Gratitude goes to the employees of different organizations for their immense contribution towards this research.
REFERENCES
[1]. Ahire, S.L., Golhar, D.Y., Waller, M.A., 1996,” Development and validation of TQM implementation
constructs, Decision Sciences 27 (1) 23-56.
[2]. F.J. Conca et al. / European Journal of Operational Research 156 (2004) 683–697, Development of a
measure to assess quality management in certified firms.
[3]. Anupam Das, Himangshu Paul and Fredric W. Swierczek, Developing and validating total quality
management (TQM)constructs in the context of Thailand’s manufacturing
industry./www.emeraldinsight.com/1463-5771.htm
[4]. Luis E. Solis, S. Subba Rao, T.S. Raghu-Nathan, Cho-Young Chen and Shih-Chun Pan, Quality
management practices and quality results: a comparison of manufacturing and service sectors in
Taiwan, Managing Service Quality .Volume 8 · Number 1 · 1998 · pp. 46–54.
[5]. Calculating, Interpreting, and Reporting Cronbach’s Alpha Reliability Coefficient for Likert-Type
Scales. Joseph A. Gliem ,Rosemary R. Gliem
[6]. Statistics with STATA (updated for version 9)/ Hamilton, Lawrence C. Thomson Books/Cole, 2006.
[7]. Non-Parametric Tests in SPSS,Dr Daniel Boduszek ,d.boduszek@hud.ac.uk

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International Journal of Engineering Research and Development (IJERD)

  • 1. International Journal of Engineering Research and Development e-ISSN: 2278-067X, p-ISSN: 2278-800X, www.ijerd.com Volume 8, Issue 3 (August 2013), PP. 07-13 7 Empirical Research on TQM Practices of Organizations – Development and Validation of Critical Factors & Comparison of Manufacturing and Service Organizations Anu P.Anil1 , Dr.Satish K.P2 1 M Tech student, 2 Associate Professor, 1,2, Department of Production Engineering, Government Engineering College Thrissur, Thrissur, India-680 009 Abstract:- Total Quality Management (TQM) is an integrative management philosophy aimed at continuously improving the quality of products and processes to achieve customer satisfaction. The objective of this paper is to describe an empirical research on the development of a tool to measure the quality management in different organizations. It provides empirical evidence on top management’s awareness and understanding of the quality management and its role towards business survival and competitiveness. Through a detailed analysis of literature, this paper identifies thirteen critical factors of quality management .Using a survey of twenty organizations, the critical factors are empirically tested and validated. SPSS is used for this purpose. This provides reliable and valid critical factors of total quality management and develops a measurement instrument for evaluating the TQM implementation process and to target improvement areas. In this paper, we compare the quality management practices between Indian manufacturing and service organizations based on the survey of 104 organizations by using non parametric test. The results presented here are focused on thirteen critical factors of quality management. The study shows significant differences between manufacturing and service organizations with manufacturing organizations performing better in quality management practices. Opportunities for improving quality management practices in Indian service organizations were identified. Keywords:- Total quality management (TQM), Reliability,Validity,Internal consistency method, Factor analysis, Multitrait multimethod matrix (MTMM),Mann Whitney U Test,Non parametric test . I. INTRODUCTION Total quality management (TQM) allows firms to obtain, on the one hand, a high degree of differentiation, satisfying customer’s needs and strengthening brand image, and on the other, to reduce costs by preventing mistakes and waste of time and by making improvements in the corporation's processes. In this respect, both researchers and managers have been interested in studying quality management, and identified a number of elements for a successful implementation. Thus, various studies have been carried out for the identification of those critical factors ensuring its success, as a way to develop a theory of quality management from three different areas: contributions from quality leaders (Crosby, 1979; Deming, 1982; Ishikawa,1985;Juran, 1988; Feigenbaum, 1991), formal evaluation models (European Quality Award, Malcolm Baldrige National Quality Award, The Deming Award) and empirical research (Saraph, Benson and Schroeder, 1989; Flynn, Schroeder and Sakakibaru, 1994; Badri, Davis and Davis, 1995; Ahire, Golhar and Waller, 1996; Black and Porter, 1996; Grandzol and Gershon, 1998; Quazi et al., 1998) [2]. Thus, managers need to understand what elements are necessary in order to change a firm’s culture towards a quality culture. Starting from a review of these studies, the purpose of this paper is to contribute to: a) identify critical factors of total quality management b) developing measures for change towards a quality culture c) testing these measures for reliability and validity using data collected from different organizations by using a suitable questionnaire and d) evaluate the performance of manufacturing and service organizations. Global competition and increasingly sophisticated and demanding customers are two important factors that are driving organizations around the world to create, develop and sustain higher levels of quality. In this study the similarities and differences of quality management practices of manufacturing and service sectors were analyzed. The experience and strength in the quality management of the manufacturing sector can prove to be valuable to improve quality management in the service sector. II. CRITICAL FACTORS OF QUALITY MANAGEMENT The companies should develop a number of TQM constructs in an integrated way for successful quality management implementation. The theory of quality management has been studied from different areas: quality leaders' ideas, empirical research and formal evaluation models. This has helped to identify a set of critical factors for a successful implementation, as a way to improve customer satisfaction and performance. Through a
  • 2. Empirical Research on TQM Practices of Organizations 8 detailed analysis of literature, this paper identifies thirteen critical factors with eighty five items for the successful implementation of TQM. Table I: Critical Factors of Quality Management Critical Factors Significance of Critical Factors Leadership and top management commitment Management’s commitment to quality through communication and motivation of employees. The behavioural patterns which show senior management’s personal involvement in the quality improvement process, acceptance of responsibility for quality performance, visibility in developing and maintaining an environment of organizational quality excellence and sharing the vision and quality goals with the entire company. Customer focus Increasing contacts between the organization and customers, identifying their requirements, assessing their satisfaction and supporting activities improving customer satisfaction. Supplier quality management Relation with suppliers in order to find the quality specifications demanded by the firm. Continuous improvement Indicates whether the firm has created an organizational structure (quality committee, a person in charge of quality and work teams) responsible for this improvement by identifying actions through information management. Employee involvement Employees, if they fully participate in quality improvement activities, will acquire new knowledge; realize the benefits of the quality disciplines; and obtain a sense of accomplishment by solving quality problems. Cross-functional quality improvement teams and quality circles, along with an appropriate evaluation and reward system for quality improvement projects, are helpful for improving quality Employees should be encouraged to submit suggestions and ideas for quality improvement. Rewards and recognition Companies must develop formal systems to encourage, track, evaluate, reward and recognize the individual or team effort for quality enhancement and improved customer satisfaction. Employees should be made aware of the reward and penalty system. Education and training Measures whether the firm shows an interest in employees learning about all the basic aspects of the firm and its business by encouraging continuous learning. It should also include training in problem-solving and teamwork. Strategic quality planning The integration of quality management and customer satisfaction in the organizational strategic and operational plans, the organization’s long-term quality vision, and the deployment and understanding of quality goals and policy within the organization Process management Reflects how the organization controls and improves its processes by setting quality measures (level of customer satisfaction, quality cost). Product innovation Customer requirements should be thoroughly considered for product innovation. Approaches such as quality function deployment, and experimental design help companies translate customer requirements into action by cross functional product innovation teams. Quality information and analysis The availability of quality-related data, timeliness of quality-related data, and the usage of quality-related data at all levels in the organization Quality assurance Sound procedures for design and introduction of new or improved products and services. Design of process that meets and exceeds product/service quality requirements. Error and failure prevention activities along the value-added chain. Quality citizenship Consideration for public health, safety, and environmental issues as company’s responsibility. Extension of company’s quality leadership to the external community.
  • 3. Empirical Research on TQM Practices of Organizations 9 III. DEVELOPMENT AND VALIDATION OF CRITICAL FACTOR USING PILOT STUDY Based on a review of TQM literature and expert opinions, thirteen TQM critical factors were identified. A detailed questionnaire was developed with the items for thirteen TQM factors along with the questions on quality performance and information about the respondents. The questionnaire was then sent to randomly selected manufacturing and service organizations in India. Based on the data from the survey, reliability and validity of the questionnaire was determined. Internal consistency analysis was done to ensure the reliability of the constructs. Content validity and construct validity were evaluated statistically to ensure that the set of measures correctly represents the constructs, and the degree to which they are free from any systematic or non- random error. A. Data Collection In order to achieve the objective different manufacturing and service organizations working in India was considered as the population. While the database was being selected, a questionnaire was designed meeting the objectives that had been set. Based on the review of literature thirteen critical factors were identified, but it can’t measure directly. So to measure how the TQM is implemented in organizations indirectly a questionnaire was developed with 101 items covering different factors. Following the methodology adopted in similar studies (Ahire et al., 1996), a seven-point likert scale was used for all items to ensure higher statistical variability among survey responses. Items of all the constructs were measured as: 1 – strongly disagree, 2 – disagree, 3 – somewhat disagree, 4 – neutral, 5 – somewhat agree, 6 – agree, 7 – strongly agree [3]. Experts on the subject were consulted, to ensure that the questions were properly phrased, and the suitability of the questionnaire was tested on a sample of firms. The process of developing the questionnaire finished with a pilot survey, which was used to modify and eliminate a number of variables, until the final questionnaire was designed. Finally the questionnaire was developed with eighty five items covering domains of each factor. The data collected from twenty different organizations were used to test the reliability and validity of tool developed. The data were collected by means of personnel interview and based on a closed questionnaire plus a set of open questions to clarify certain points. The questionnaire was answered by employees who have thorough knowledge about the quality practices implemented in the organization. B. Reliability Reliability is the ability of the instrument to measure consistently. As the internal consistency method is the most general form of reliability estimation (Nunnally, 1978), it has been used in this study. The internal consistency method assesses the equivalence, homogeneity and inter-correlation of the items used in a measure. The most popular test within the internal consistency method is the Cronbach’s coefficient α (Nunnally, 1978; Cronbach, 1951). Cronbach’s α computes internal consistency reliability among a group of items combined to form a single scale. It can also be computed for any subset of items. Nunnally (1978) advocates that new developed measures can be accepted with Cronbach’s α of more than 0.60, otherwise 0.70 should be the threshold. The measure with Cronbach’s α 0.80 or more is significant and reliable [3]. For this purpose, the reliability for each set of items of the thirteen critical factors of TQM is calculated by using SPSS.Table 2 summarizes the Cronbach’s α for individual critical factors. The Cronbach’s α for the thirteen critical factors ranged from 0.9511 to 0.9908 indicating a high reliability of the instrument. Table II: Internal Consistency Method (Cronbach's Alpha (α)) Using SPSS Factor No: of Items Cronbach's Alpha (α) Leadership and top management commitment 7 .9707 Customer focus 7 .9917 Supplier quality management 5 .9511 Continuous improvement 7 .9609 Employees involvement 8 .9777 Rewards and recognition 4 .9700 Education and training 9 .9908 Strategic quality management 7 .9633 Process management 7 .9693 Product innovation 5 .9612 Quality information and analysis 6 .9674 Quality assurance 7 .9807 Quality citizenship 6 .9646
  • 4. Empirical Research on TQM Practices of Organizations 10 C. Validity The validity of a measure is defined as the extent to which a construct or a set of measures correctly represents the concept of study, and the degree to which it is free from any systematic or non-random error. Validity is concerned with how well the concept is defined by the measure(s), whereas reliability relates to the consistency of the measure(s). Content validity: A measure has content validity if there is a general agreement among the subjects and researchers that the instrument has measurement items that cover all aspects of the variable being measured. The thirteen critical factors for measuring TQM implementation should have content validity, as the measurement items were developed based on both an extensive review of the literature and detailed evaluations by academicians and practicing managers. Moreover, the pre-test subjects indicated that the content of each critical factor was well represented by the measurement items employed. Construct validity. A measure has construct validity, if it measures the theoretical constructs that it was intended to measure. Factor analysis can be used for evaluating construct validity. Factor analysis helps to analyse the interrelationships among a large number of variables and explains these variables in terms of their common underlying dimensions (constructs). It also helps reduce data that do not correlate with any of the underlying dimensions. This measurement is calculated through a factor analysis for each of the thirteen factors. In this analysis, each factor must be one dimensional. Hence the developed tool is found to be valid. The summary of factor analysis of each measure is shown in Table III. Table III: Summary of Factor Analysis for Each Measure Construct KMO Item Loading Range for Factor 1 Eigen Value Percentage Variance Explained by Factor 1 Leadership and top management commitment .617 .82-.97 6.037 86.239 Customer focus .799 .95-.99 6.670 95.288 Supplier quality management .805 .89-.96 4.189 83.786 Continuous improvement .766 .80-.95 5.706 81.518 Employee involvement .796 86-.97 6.969 87.107 Rewards and recognition .853 .93-.97 3.677 91.924 Education and training .784 .95-.97 8.394 93.271 Strategic quality planning .909 .69-.97 5.992 85.605 Process management .767 .81-.98 6.059 86.559 Product innovation .722 .89-.97 4.350 86.999 Quality information and analysis .704 .89-.97 5.220 87.002 Quality assurance .715 .91-.97 6.289 89.838 Quality citizenship .668 .85-.96 5.131 85.516 The construct validity is also determined by using multitrait multimethod matrix (MTMM). Multitrait multimethod matrix analysis allows us to detangle correlations between instruments due to similarity of test methods form and similarities due to tapping the same attribute. The MTMM is simply a matrix or table of correlations arranged to facilitate the interpretation of the assessment of construct validity. The basic principle of MTMM matrix is coefficients in the reliability diagonal should consistently be the highest in the matrix. The intra attribute correlation (correlation between the items of same attributes) are to be higher than the inter attribute correlation (correlation between the items of different attributes). The average inter attribute and intra attribute correlations are given in Table IV. Table IV: Average Inter Attribute and Intra Attribute Correlations Critical Factor Intra Attribute Correlation Inter Attribute Correlation Leadership and top management commitment 0.843 0.697 Customer focus 0.922 0.700 Supplier quality management 0.866 0.586 Continuous improvement 0.831 0.640 Employee involvement 0.892 0.729
  • 5. Empirical Research on TQM Practices of Organizations 11 Rewards and recognition 0.926 0.703 Education and training 0.929 0.581 Strategic quality planning 0.869 0.593 Process management 0.876 0.704 Product innovation 0.891 0.460 Quality information and analysis 0.887 0.689 Quality assurance 0.908 0.734 Quality citizenship 0.873 0.671 IV. ANALYSIS OF QUALITY MANAGEMENT PRACTICES OF MANUFACTURING AND SERVICE ORGANIZATIONS The final reliable and valid questionnaire was used to collect data from different organizations in India to analyze the quality management practices. Based on the survey of 104 organizations, the quality management practices were evaluated using non parametric test. Fig.1: Manufacturing and Service Organizations A. Non parametric test A non-parametric statistical test is a test whose model does NOT specify conditions about the parameters of the population from which the sample was drawn. It does not require measurement so strong as that required for the parametric tests. Most non-parametric tests apply to data in an ordinal scale, and some apply to data in nominal scale. In this study, we compare the quality performance of manufacturing and service sectors. The Mann-Whitney U test or Mann-Whitney-Wilcoxon rank sum test is used to evaluate the significant differences between two independent groups. The Mann-Whitney U test or Mann-Whitney-Wilcoxon evaluates whether the medians on a test variable differ significantly between two groups. To conduct the Mann-Whitney U test, each case must have scores on two variables, the grouping variable (independent or categorical variable) and the test variable (dependent or quantitative variable). The grouping variable divides cases into two groups or categories, and the test variable assesses individuals on a variable with at least an ordinal scale. Unlike its parametric counterpart, the t test for two samples, this method does not assume that the differences between the samples have normality distributed, or that the variances of the two populations are equal. In this study the null hypothesis of Mann Whitney U test is that both manufacturing and service sectors have same quality management practices. If the asymptotic significance is less than or equal to the significance level, then there is significant differences between quality management practices of manufacturing and service organizations. The result of this test is shown in Table V. Table V: Mann Whitney U Test Critical factor Mann Whitney U Asymptotic Significance Leadership and top management commitment 1305.0 0.918 Customer focus 918.0 0.004 Supplier quality management 846.0 0.001 Continuous improvement 1030.5 0.036 Employee involvement 1280.5 0.783 Rewards and recognition 1181.0 0.342 Education and training 1221.0 0.485 Strategic quality planning 1252.5 0.633
  • 6. Empirical Research on TQM Practices of Organizations 12 Process management 1206.0 0.436 Product innovation 1117.5 0.169 Quality information and analysis 1275.5 0.761 Quality assurance 1236.5 0.564 Quality citizenship 978.5 0.019 According to Mann Whitney test, obtained a result that manufacturing organizations have better quality practices in the following constructs. a) Customer focus The result show that manufacturing organizations excel over service organizations in the following customer orientation features:  Building and maintaining relationship with customers to retain the customers and building their market share.  Meeting the requirements and trying to exceed the expectations of customers in every life cycle of product.  Determining satisfaction level of customer and compare it with the competitor and bench markers.  Following up with customers on the quality of product, customer support, after sales service to receive immediate feedback.  Effectively making use of the voice of the customer data and information (including complaints) to develop operational and strategic quality plan and for product innovation.  Adopting new strategies to improve company responsiveness to customer’s complaints So the service companies need to adopt new strategies to improve company responsiveness to customer’s complaints. One of the success factors in service sector is the ability to meet the customer expectations and respond faster to customer complaints and concerns. b) Supplier quality management  Manufacturing organizations ensure that supplier selected are qualified and positioned to enhance performance and customer satisfaction and  Continuously evaluate supplier performance and discard poorly performing suppliers. c) Continuous improvement  Manufacturing organizations identifies the importance of continuous improvement of all of its products, processes and services.  By self assessment activities and creating an organizational structure, they identified areas and actions for improvement through information management. d) Quality citizenship  Manufacturing companies exhibiting higher levels of community involvement through quality, and higher levels of responsibility for different social concerns than service companies.  They concerned about the impact on society due to the current and future product and process.  Pay attention to the workforce environment ,their safety  Government rules and regulations and certain safety standards are followed by manufacturing sectors.  Sustainable environment is also considered as factor in making their quality policies (including optimum use of natural resources). Service companies need to extend their quality leadership to their surrounding community. Companies that are socially responsible for the impact they have in the community reinforce their quality image and build a path for customer’s loyalty. V. CONCLUSIONS The research develops an empirically based instrument for measuring the TQM implementation in different organizations in India. This study provides thirteen critical factors of TQM as a model allowing managers to have a better understanding of quality management practices. By periodically using this model, it may serve to evaluate a firm’s quality standards, finding those areas where improvement is necessary and, therefore, planifying the quality management effort. From the detailed analysis of comparison of individual items of the quality practices, we find that service organizations can learn from the experience of top quality performers in the manufacturing sector. In this study we found that manufacturing companies outperform service companies in almost all quality factors. That manufacturing companies excel service organization shows that it takes time to develop both a strong quality and a customer orientation culture successfully. However, service companies in India can accelerate their quality implementation process and learning by benchmarking the quality practices of top quality manufacturing companies.
  • 7. Empirical Research on TQM Practices of Organizations 13 ACKNOWLEDGMENT Gratitude goes to the employees of different organizations for their immense contribution towards this research. REFERENCES [1]. Ahire, S.L., Golhar, D.Y., Waller, M.A., 1996,” Development and validation of TQM implementation constructs, Decision Sciences 27 (1) 23-56. [2]. F.J. Conca et al. / European Journal of Operational Research 156 (2004) 683–697, Development of a measure to assess quality management in certified firms. [3]. Anupam Das, Himangshu Paul and Fredric W. Swierczek, Developing and validating total quality management (TQM)constructs in the context of Thailand’s manufacturing industry./www.emeraldinsight.com/1463-5771.htm [4]. Luis E. Solis, S. Subba Rao, T.S. Raghu-Nathan, Cho-Young Chen and Shih-Chun Pan, Quality management practices and quality results: a comparison of manufacturing and service sectors in Taiwan, Managing Service Quality .Volume 8 · Number 1 · 1998 · pp. 46–54. [5]. Calculating, Interpreting, and Reporting Cronbach’s Alpha Reliability Coefficient for Likert-Type Scales. Joseph A. Gliem ,Rosemary R. Gliem [6]. Statistics with STATA (updated for version 9)/ Hamilton, Lawrence C. Thomson Books/Cole, 2006. [7]. Non-Parametric Tests in SPSS,Dr Daniel Boduszek ,d.boduszek@hud.ac.uk