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International Journal of Mechanical Engineering and Technology (IJMET)

Volume 9, Issue 9, September 2018, pp. 631–646 Article ID: IJMET_09_09_068

Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=9&IType=9

ISSN Print: 0976-6340 and ISSN Online: 0976-6359

© IAEME Publication Scopus Indexed

STUDIES ON QUALITY PRACTICES IN SMALL

& MEDIUM SCALE INDUSTRIES USING

STATISTICAL TOOLS

Lakshmi Kumari

Department of Mechanical Engineering, Ballari Institute of Tech. & Management,

Bellary, Karnataka, India

Dr. Y Vijay Kumar

Department of Mechanical Engineering, Sri Sairam College of Engineering,

Anekal, Bengaluru, Karnataka, India

ABSTRACT

In the era of globalization and privatization, the challenges of current market

trends can be competed using total quality management (TQM) principle. More

particularly, the small and medium scale enterprises (SME’s) play a vital role in

providing employment and boosting the economy of the developing country like India.

However, to fulfill the customer satisfaction, the quality of the product plays a vital

role in the products being manufactured in SME’s. Focusing on satisfaction of

customers, increase in profit and minimizing losses to a lower level are quality

improvement parameters. These parameters can be met through the application of

advanced quality philosophies and TQM principles. The paper discusses the

identification of critical success factors that contribute to the performance of quality

practices in SME’s. The study planned to establish a guideline that the management

can take care itself to improve the productivity of the firms. The work includes a

questionnaire survey to implement TQM practices in the structure of governance in

SME’s. Based on priority, the critical factors are arranged from the collected data.

Employee satisfaction, customer satisfaction and operational effectiveness are the

three hypothesis formulated. Statistical test is carried out for formulated hypothesis

separately using T-test, one-way ANOVA and MANOVA tests. It is summarized that

the TQM implemented SME’s are more effective in fulfilling the needs of employees,

customers and in operation as well.

Keywords: TQM, SME’s, Quality, Hypothesis, T-test, one-way ANOVA, MANOVA

test.

Cite this Article: Lakshmi Kumari and Dr. Y Vijay Kumar, Studies on Quality

Practices in Small & Medium Scale Industries using Statistical Tools, International

Journal of Mechanical Engineering and Technology, 9(9), 2018, pp. 631–646.

http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=9&IType=9

Studies on Quality Practices in Small & Medium Scale Industries using Statistical Tools


1. INTRODUCTION

Economic intensification of a nation is truthfully associated to the level of industrial growth.

The expansion of industrial sector leads to a greater utilization of natural resources,

production of goods and services, creation of employment opportunities and improvement in

the general standard of living. All countries, more particularly the India has been striving to

develop the country’s industrial base since independence. Though the large scale industries

have contributed a lot, the small and medium scale enterprises play a key role in our planned

development towards the fulfillment of the socio economic objectives particularly in

achieving equitable growth. Since decades, the concept of TQM has been dominated the

management scene irrespective of type and size of industry. It has been tickled around basic

principles such as consumer focus; continuous improvement and human resource

management are significant in the implementation of quality practices irrespective of type and

size like small, medium and heavy industries [1, 2, 3, 4, 5, 6, and 7]. TQM is one of the most

multifaceted activities that any company can involve as it requires implementing a new way

of managing business and a new working culture which not only affects the whole

organizational process and all employees but also demand the allocation of significant

organizational resources [8, 9, 10]. More particularly, the customer satisfaction is one of the

noteworthy constraints for the success of organization as the growth of any business depends

on the same. To conquer the total satisfaction from the consumers with respect to product

quality, delivery, after sales service, the organizations particularly small-scale industries does

not have any option other than implementing TQM concepts in holistic manner. Many

researchers have been carried out extensive research in different industries to implement the

quality practices using TQM. Management awareness of the importance of total quality

management including business process re-engineering and other continuous improvement

techniques has been studied using bench-marking movement for improving best practices

[11]. TQM principles and practices in the service firms as well as in the manufacturing

organizations have been described in [12]. They have concluded that there is no significant

difference in the level of most of TQM practices and quality performance between the two

sectors. Improvement in business performance and received considerable attention in recent

researches has been proposed [13] using TQM. This study empirically examines the extent to

which TQM and business performance are correlated and how TQM impacts various levels of

business performance. Simulations have been carried out [14] that TQM has been clearly

conceptualized around basic principles such as consumer focus, continuous Improvement and

human resource management. Necessary resources [15] required to produce one unit from the

total production has been discussed. The productivity has been measured by taking Total

Deposits at The End of Year / Total Number of Employees. Total Quality Management is a

management technique [16] adopted by the most manufacturing organizations has been

discussed. It helps to manufacture products at lowest cost by the following various

management techniques through continuous improvement. Total Quality Management has

been widely considered [17] as the strategic, tactical and operational tool in the quality

management research field. Computational tests such as t-test and MANOVA test using the

data collected 222 manufacturing and service companies discussed by [18] to implement the

quality practices. The tests showed a clear difference in TQM practices by company size,

industry type, and degree of innovation. TQM concept cannot be applied to any industry other

than Manufacturing has been discussed in [19]. One of the main principles of the TQM

concept is to achieve customer Satisfaction and this is an important objective for any

organization, including Construction firms. Quality aspect has become one of the most

important factors in global competition today has been discussed [20]. Increasing demand by

customers for better quality of product in market place has encouraged many companies to

provide quality product and services to compete in the marketplace successfully. TQM

Lakshmi Kumari and Dr. Y Vijay Kumar


practices, activities, critical success factors through t-test and ANOVA barriers and business

outcomes in electric fan manufacturing industry of Pakistan has been analyzed [21].

Descriptive statistics in terms of Measures of Central Tendency and Measures of Dispersion

has been carried out to study TQM [22]. Inferential Statistics were performed in terms of

Measures of Pearson Correlation, Tests of Hypotheses, Analysis of Variance, Step-wise

Regression One Sample T-test, F-test, Chie-Square, and Significance Levels as a part of

implementing quality practices in manufacturing and service industries located in Riyadh city.

With this, the objective of the paper is to attempt the implementation of quality principles in

small and medium scale industries in and around Bellary city by carrying out statistical tests.

2. METHODOLOGY

The proposed plan of implementing the quality practices in small and medium enterprises

carried out comprises three activities namely method of data collection, population and

sample size, and method of data analysis. The potential problems arises due to difficulty in

understanding the questions by respondents in all visited industries are resolved using pilot

study. Questionnaire is mainly intended to prepare without harming the emotions of the

respondents in addition to other various considerations. The final questionnaire is built after

little iterative reconsideration, with reformatting and consecutive improvisation in the

questionnaire. Through survey, a questionnaire about industry, employee and customer

satisfaction, quality practices effectiveness and interviews were conducted to collect the data.

Questionnaire associated to employee and customer satisfaction, a range of 1 to 5 is chosen.

Table 1 List of factors considered in the formulation of questionnaire.

Topics Number of Questions

Content

General Information

Personal details 4 Shows name, designation , educational

qualification, experience etc

Organizational details 5 Firm name, workforce size, type of industry

etc Influencing Factors

Leadership and vision 5 Indicates management view on quality

improvement policy & plans.

Quality commitment 5 Shows quality in product design, review and

feedback from experts.

Employee involvement 5 Meetings and encouragement of employees,

quality circles

Costumer focus 5 Customer feedback, programs to implement

customer service etc Continuous improvement 5 labels and signboards, ,waste elimination, etc Process monitoring and

control 5 Includes periodic audits, review of targets etc

Incentive and recognition system

4 Company certification, employees incentives

etc

Fact based management 3 Quantitative techniques in process, training

etc

The survey is conducted in all small and medium scale industries across the different parts

of Bellary city considering all influencing factors of total quality management. A total of 71

(40 Small and 31 Medium) SME does have come voluntarily to give valuable opinion by

participating in survey to implement the concept of TQM. Different sectors namely steel, agro

food, cotton, garments, MRF tyres and treads in and around Bellary city has been covered as a

part of survey. Questionnaire comprises details of personnel, organizational and factors

influencing quality management practices in small and medium scale industries. The



personnel, organizational and other influencing factors considered in the preparation of

questionnaire are tabulated in Table 1.1.

2.1. HYPOTHESIS FORMULATION

The data collected through questionnaire has been analyzed using different tests namely

Hypothesis test, Significance test and Statistical descriptive statistics. The difference in the

means of two categories of SME’s has been verified using Hypothesis test in SPSS software.

To begin, the three major hypotheses is formulated and verified to know how the selected

sample will answer the queries framed in the questionnaire. Figure 1 shows the hypothesis

formulated from dissertation model that is divided into three parts namely employee

satisfaction, effective operations and customer satisfaction. Hypothesis 1 implies a higher

degree of employee’s satisfaction in TQM SME’s than NON TQM SME’s. Quality

improvement activities are too excelled with a committed and skilled work force for a

successful TQM environment. It is imparted by reward, reorganization, sponsoring higher

education and training of employees supports the drive for quality. Employees will encourage

taking more responsibility, communicating more effectively, acting creatively, and

innovatively. Hypothesis-2 implies a greater customer satisfaction in TQM SME’s compared

to non-TQM SME’s as it is evident from Fig. 2 according to Jordan, 2002.Company involved

TQM is perceptive to customer requisite and responds to them quickly.

Figure 1 Dissertation Model (Researchers, 2008).

TQM accentuates customer focus as shown in Fig. 2 to progress the quality of service

provided to consumers by accepting the needs and problems of customers. SME’s have to be

aware of their customer’s needs and compare it with managerial performance in meeting the

needs and as well to preserve a level of customer satisfaction. Customer requirements will be

satisfied according to Muffatto and Panizzolo (1995) by providing services or products within

the stipulated time and of quality as well. Hypothesis 3 implies a greater operational

performance in TQM SME’s compared to non-TQM SME’s in small and medium scale

enterprises. Organizational performance will be effective by adopting TQM. Sila (2007)

proven that the Suppliers involvement in the overall process of quality improvement have a



major role to play in the overall effectiveness of operations. Continuous improvement is also

another major tenet of TQM as it leads to efficient operation.

Figure 2 Model of TQM Process (Jordan, 2002).

3. RESULTS AND DISCUSSION

This section discusses the in-detail analysis of data collected through questionnaire. Further,

the tests such as descriptive analysis, T-test, one-way ANOVA and MANOVA carried out for

all visited small and medium scale industries. Statistics and other allied things namely as

mean, standard deviation, and mean performance based on mean difference has been

calculated for employee satisfaction, customer satisfaction and operational effectiveness. To

begin, the probability value reflects the strength of the evidence against the null hypothesis as

told by Fisher. Data presents well-built evidence and the null hypothesis is false if the

probability is under 0.01. Null hypothesis is normally rejected if the probability value is

below 0.05 and bigger than 0.01. Probability values between 0.05 and 0.10 provide pathetic

evidence against the null hypothesis and, are not considered low enough to justify rejecting it.

Higher probabilities provide less evidence that the null hypothesis is false. At the end T-test,

one-way ANOVA and MANOVA tests have been carried out to give comprehensive

conclusion using SPSS software.

3.1. EMPLOYEE SATISFACTION

3.1.1. DESCRIPTIVE ANALYSIS

Table 2 shows the descriptive statistics for the variables defined in customer satisfaction of a

total 71 small and medium scale industries. The test has been conducted for side by side

comparison of the descriptive statistics of the six numeric variables. Highest mean of 3.4366

was obtained for standard quality in service and 2.9437 of lowest was found for company

giving warrantee to customer. The mean for all numeric variables is almost above 3 except for

company giving warrantee to customer. The reason may be that the customers are not satisfied

with the warranty period offered for the product being delivered. The standard deviation for

quick response to customer is less compared to other variables with respect to customer

satisfaction. This indicates that the customers are satisfied with the response shown by all the

small and medium scale enterprises instead of other defined numeric variables. Table 3 shows

the descriptive statistics for the variables defined in employee satisfaction of a total 71 small

and medium scale industries. Highest mean of 3.5321 was obtained for individual effort and

3.1127 of lowest was found for continuous improvement. The mean for all numeric variables

is almost above 3.2 except for individual effort. The reason may be that the employee’s

individual effort is not being recognized.



Table 2 Descriptive statistics for customer satisfaction

Descriptive Statistics

Type of industry

Mean Std.

Deviation N

Standard quality in service

small scale 3.2250 .89120 40

medium scale 3.7097 .78288 31

Total 3.4366 .87395 71

Listen to customer complains

small scale 2.5750 .98417 40

medium scale 3.8387 .82044 31

Total 3.1268 1.10750 71

Repeat of customer

small scale 2.8000 1.09075 40

medium scale 3.6774 .79108 31

Total 3.1831 1.05978 71

Product recommendation by customer

small scale 2.9000 .87119 40

medium scale 3.7097 .78288 31

Total 3.2535 .92146 71

Quick response to customer

small scale 2.9750 .76753 40

medium scale 3.7742 .76200 31

Total 3.3239 .85815 71

Company giving warrantee to customer

small scale 2.2500 1.35401 40

medium scale 3.8387 .89803 31

Total 2.9437 1.41307 71

3.1.2. T- TEST

Table 4 shows the results of T-test conducted for the parameters defined in customer

satisfaction. It is observed that the equality of variances has been violated which we either

consider or not considered the assumption of T-test. The significance is less than 0.05 for a

company giving warrantee to customer compared to all other parameters and it is evident that

there is no violation of equality of variances. On the other hand, remaining all parameters

whose significance is greater than 0.05 and implies there is a violence of equality of

variances. However, the SPSS software makes corrections automatically during test. Similarly

from the table, also it has been observed that the value of sig. 2 tailed differs between small

and medium scale enterprises. There should not be less than a 1% (0.01) chance of error if

there is a difference. Alternately, it is evident that there is 99 % difference in industries based

on chosen sample. Table 5 shows the results of T-test conducted for the parameters defined in

employee satisfaction. The significance is less than 0.05 for all defined numerical variables

and it is evident that there is no violation of equality of variances. Table 6 shows the results of

T-test conducted for the parameters defined in operational effective of the organization. It has

been observed that the significance for all parameters is greater than 0.05 and implies there is

a violence of equality of variances.



Table 3 Descriptive statistics for employee satisfaction

Descriptive Statistics

Type of industry Mean Std.

Deviation N

Satisfaction with authority

small scale 2.9744 .95936 39

medium scale 3.6562 .86544 32

Total 3.2817 .97370 71

Training for workers

small scale 2.7179 .94448 39

medium scale 3.7813 .79248 32

Total 3.1972 1.02288 71

Encouragement of team effort

small scale 2.9487 .91619 39

medium scale 3.5938 .83702 32

Total 3.2394 .93296 71

Continuous improvement

small scale 2.7179 .91619 39

medium scale 3.5938 .97912 32

Total 3.1127 1.03578 71

Management recognizes individual effort

small scale 2.9487 .94448 39

medium scale 3.5625 .91361 32

Total 3.2254 .97390 71

Mistakes made while responding to customer

small scale 3.0000 .91766 39

medium scale 3.6250 .83280 32

Total 3.2817 .92864 71

Flexibility of job

small scale 2.8974 1.07103 39

medium scale 3.7188 .88843 32

Total 3.2676 1.06848 71

employee involvement in decision making

small scale 2.7949 1.05580 39

medium scale 3.7500 .76200 32

Total 3.2254 1.04468 71

Individual effort is recognized in delivering quality service

small scale 2.7179 .97194 39

medium scale 3.6563 .70066 32

Total 3.1408 .97535 71

Individual effort

small scale 3.0256 .93153 39

medium scale 3.7500 .84242 32

Total 3.3521 .95765 71

3.1.3. One-way ANOVA test

Table 7 shows the ANOVA test results conducted for a customer satisfaction. One-way

between groups analysis of variance was conducted to explore the impact of different

parameters defined in customer satisfaction. Respondents were divided into groups according

to the knowledge of TQM. It has been observed that there was a statistically significant

difference of 0.019 for standard quality in service and it is zero for all other defined

parameters. Table 8 shows the ANOVA test results conducted for an employee satisfaction. It

has been observed that there was a statistically maximum significant difference of 0.007 for

Management recognizes individual effort. Table 9 shows the ANOVA test results conducted

for operational effectiveness of an organization. It has been observed that there was a

statistically significant difference of 0.889 for the query related to ISO certification of all the

visited SME’s.



Table 4 T-test for customer satisfaction

Independent Samples Test

Levene's Test for

Equality of Variances

t-test for Equality of Means

F Sig. t df

Sig. (2-

tailed)

Mean Differenc

e

Std. Error

Difference

95% Confidence

Interval of the Difference

Lower Upper


Equal variance

s assumed

.065 .799

-2.39

5 69 .019 -.48468 .20239

-.88844

-.08092

Equal variance

s not assumed

-

2.435

67.864

.018 -.48468 .19906 -

.88192 -

.08744

Listen to customer complains

Equal variance

s assumed

1.048

.310

-5.76

2 69 .000 -1.26371 .21933

-1.7012

5

-.82617

Equal variance

s not assumed

-

5.897

68.597

.000 -1.26371 .21431 -

1.69129

-.83613

Repeate of customer

Equal variance

s assumed

1.898

.173

-3.77

3 69 .000 -.87742 .23256

-1.3413

6

-.41348

Equal variance

s not assumed

-

3.927

68.740

.000 -.87742 .22345 -

1.32322

-.43161

Product recommendati

on by customer

Equal variance

s assumed

.057 .812

-4.05

7 69 .000 -.80968 .19955

-1.2077

7

-.41158

Equal variance

s not assumed

-

4.113

67.436

.000 -.80968 .19684 -

1.20252

-.41683


Equal variance

s assumed

3.786

.056

-4.36

5 69 .000 -.79919 .18309

-1.1644

4

-.43395

Equal variance

s not assumed

-

4.369

64.873

.000 -.79919 .18292 -

1.16451

-.43387

Company giving

warrantee to customer

Equal variance

s assumed

6.091

.016

-5.63

8 69 .000 -1.58871 .28180

-2.1508

8

-1.0265

4

Equal variance

s not assumed

-

5.927

67.547

.000 -1.58871 .26804 -

2.12365

-1.0537

7



3.1.4. MANOVA test

Table 10 shows the multivariate test results implies one-way MANOVA test results for

customer satisfaction as a part of verifying quality practices in small and medium scale

enterprises. The statistical significance of one-way MANOVA can be verified from the

second row of Table 10. The significant value is 0 (zero) which is less than 0.05. It has been

evident that the there is statistical significance between small and medium scale enterprises.


employee satisfaction. The significant value is 0 (zero) which is less than 0.05. It has been

evident that the there is statistical significance between small and medium scale enterprises.


operational effectiveness of organization. The significant value is 0 (zero) which is less than

0.05. It has been evident that the there is statistical significance between small and medium

scale enterprises.

Table 5 T-test for employee satisfaction


Levene's Test for



F Sig. t df

Sig. (2-

tailed)

Mean Differenc

e

Std. Error

Difference

95% Confidence

Interval of the Difference

Lower Uppe

r


Equal variance

s assumed

.021 .884

-3.11

3 69 .003 -.68189 .21904

-1.1188

7

-.2449

1

Equal variance

s not assumed

-

3.145

68.346

.002 -.68189 .21681 -

1.11448

-.2493

0


Equal variance

s assumed

1.186

.280

-5.06

9 69 .000 -1.06330 .20976

-1.4817

7

-.6448

3

Equal variance

s not assumed

-

5.158

68.956

.000 -1.06330 .20615 -

1.47457

-.6520

4

Encouragement of team

effort

Equal variance

s assumed

.897 .347

-3.06

8 69 .003 -.64503 .21025

-1.0644

8

-.2255

9

Equal variance

s not assumed

-

3.096

68.167

.003 -.64503 .20837 -

1.06081

-.2292

6


Equal variance

s assumed

1.391

.242

-3.88

6 69 .000 -.87580 .22540

-1.3254

5

-.4261

5

Equal variance

s not assumed

-

3.860

64.419

.000 -.87580 .22690 -

1.32902

-.4225

8



Management recognizes individual

effort

Equal variance

s assumed

.024 .878

-2.76

5 69 .007 -.61378 .22200

-1.0566

5

-.1709

1

Equal variance

s not assumed

-

2.774

67.108

.007 -.61378 .22126 -

1.05541

-.1721

6

Flexibility of job

Equal variance

s assumed

1.075

.304

-3.46

7 69 .001 -.82131 .23689

-1.2938

9

-.3487

4

Equal variance

s not assumed

-

3.532

68.987

.001 -.82131 .23255 -

1.28524

-.3573

9

employee involvement in decision

making

Equal variance

s assumed

3.809

.055

-4.28

1 69 .000 -.95513 .22308

-1.4001

7

-.5100

9

Equal variance

s not assumed

-

4.419

67.979

.000 -.95513 .21617 -

1.38648

-.5237

7

Individual effort is

recognized in delivering

quality service

Equal variance

s assumed

2.434

.123

-4.57

1 69 .000 -.93830 .20529

-1.3478

5

-.5287

5

Equal variance

s not assumed

-

4.717

67.961

.000 -.93830 .19891 -

1.33522

-.5413

9

Table 6 T-test for operational effectiveness


Levine’s Test for



F Sig. t df Sig. (2-tailed)

Mean Differen

ce

Std. Error Difference

95% Confidence Interval of the

Difference

Lower Upper

Is your company

ISO certified

Equal variance

s assumed

.079 .780

-.140 69 .889 -.00561 .04003 -.08546 .0742

4

Equal variance

s not assumed

-.139 63.3

63

.890 -.00561 .04042 -.08638 .0751

6

Does organisatio

n applay TQM

Equal variance

s assumed

.533 .468

-2.92

0 69 .005 -.38542 .13201 -.64877

-.1220

7

Equal variance

s not assumed

-

2.840

56.567

.006 -.38542 .13571 -.65722 -

.11362

Does Equal 2.68 .10 1.19 69 .237 .14103 .11830 -.09498 .3770



organisation applay

SQP

variances

assumed

8 6 2 3

Equal variance

s not assumed

1.18

7 65.093

.240 .14103 .11883 -.09628 .3783

4

Use of consultant

during ISO/TQM

Equal variance

s assumed

.520 .473

-.532 69 .596 -.06410 .12043 -.30435 .1761

4

Equal variance

s not assumed

-.532 66.027

.597 -.06410 .12056 -.30481 .1766

1

Table 7 ANOVA-test results for customer satisfaction

ANOVA


Sum of Squares df Mean Square F Sig.

Between Groups 4.103 1 4.103 5.735 .019

Within Groups 49.362 69 .715

Total 53.465 70

Listen to customer complines


Between Groups 27.891 1 27.891 33.198 .000


Total 85.859 70

Repeate of customer


Between Groups 13.446 1 13.446 14.235 .000


Total 78.620 70

Product recommendation by customer


Between Groups 11.450 1 11.450 16.463 .000


Total 59.437 70



Between Groups 11.155 1 11.155 19.054 .000


Total 51.549 70

Company giving warrantee to customer


Between Groups 44.081 1 44.081 31.785 .000

Within Groups 95.694 69 1.387

Total 139.775 70

Table 8 ANOVA-test results for employee satisfaction

ANOVA



Between Groups

8.173 1 8.173 9.691 .003


Total 66.366 70





Between Groups

19.873 1 19.873 25.695 .000


Total 73.239 70

Encouragement of team effort


Between Groups

7.313 1 7.313 9.412 .003


Total 60.930 70



Between Groups

13.482 1 13.482 15.098 .000


Total 75.099 70

Management recognizes individual effort


Between Groups

6.622 1 6.622 7.644 .007


Total 66.394 70

Mistakes made while responding to customer


Between Groups

6.866 1 6.866 8.855 .004


Total 60.366 70

Flexibility of job


Between Groups

11.857 1 11.857 12.021 .001


Total 79.915 70

employee involvement in decision making


Between Groups

16.035 1 16.035 18.331 .000


Total 76.394 70

Individual effort is recognized in delivering quality service


Between Groups

15.475 1 15.475 20.890 .000


Total 66.592 70

Individual effort


Between Groups

9.223 1 9.223 11.576 .001


Total 64.197 70

Table 9 ANOVA-test results for operational effectiveness

ANOVA

Is your company ISO certified


Between Groups .001 1 .001 .020 .889


Total 1.944 70



Have you heard of TQM


Between Groups .000 1 .000 . .

Within Groups .000 69 .000

Total .000 70

Does organisation applay TQM


Between Groups 2.611 1 2.611 8.524 .005


Total 23.746 70

Does organisation applay SQP


Between Groups .350 1 .350 1.421 .237


Total 17.324 70

Use of consultant during ISO/TQM


Between Groups .072 1 .072 .283 .596


Total 17.662 70

Overall do you think TQM brings positive effects




Total .000 70

Focus on continuous improvement of product




Total .000 70

Focus on continuous improvement of process




Total .000 70

Table 10 MANOVA-test results for customer satisfaction

Multivariate Testsa

Effect Value F Hypothesi

s df Error

df Sig.

Partial Eta

Squared

Noncent. Paramete

r

Observed Power

c

Intercept

Pillai's Trace

.968 322.967

b

6.000 64.00

0 .000

.968 1937.805 1.000

Wilks' Lambda

.032 322.967

b

6.000 64.00

0 .000

.968 1937.805 1.000

Hotelling's Trace

30.278

322.967b

6.000 64.00

0 .000

.968 1937.805 1.000

Roy's Largest

Root

30.278

322.967b

6.000 64.00

0 .000

.968 1937.805 1.000

Type of industry

Pillai's Trace

.398 7.055b 6.000

64.000

.000

.398 42.328 .999

Wilks' Lambda

.602 7.055b 6.000

64.000

.000

.398 42.328 .999

Hotelling's Trace

.661 7.055b 6.000

64.000

.000

.398 42.328 .999

Roy's Largest

Root .661 7.055

b 6.000

64.000

.000

.398 42.328 .999



a. Design: Intercept + Type of industry

b. Exact statistic

c. Computed using alpha = .05

Table 11 MANOVA-test results for employee satisfaction

Multivariate Testsa


s df Error

df Sig.

Partial Eta

Squared

Noncent. Paramete

r

Observed Power

c

Intercept

Pillai's Trace

.963 157.209

b

10.000 60.00

0 .000

.963 1572.087 1.000

Wilks' Lambda

.037 157.209

b

10.000 60.00

0 .000

.963 1572.087 1.000

Hotelling's Trace

26.201

157.209b

10.000 60.00

0 .000

.963 1572.087 1.000

Roy's Largest

Root

26.201

157.209b

10.000 60.00

0 .000

.963 1572.087 1.000

Type of industry

Pillai's Trace

.351 3.242b 10.000

60.000

.002

.351 32.425 .975

Wilks' Lambda

.649 3.242b 10.000

60.000

.002

.351 32.425 .975

Hotelling's Trace

.540 3.242b 10.000

60.000

.002

.351 32.425 .975

Roy's Largest

Root .540 3.242

b 10.000

60.000

.002

.351 32.425 .975


b. Exact statistic


Table 12 MANOVA-test results for operational effectiveness

Multivariate Testsa


s df Error

df Sig.

Partial Eta

Squared

Noncent. Paramete

r

Observed Power

c

Intercept

Pillai's Trace

.983 962.244

b

4.000 66.00

0 .000

.983 962.244b 4.000

Wilks' Lambda

.017 962.244

b

4.000 66.00

0 .000

.017 962.244b 4.000

Hotelling's Trace

58.318

962.244b

4.000 66.00

0 .000

58.318 962.244b 4.000

Roy's Largest

Root

58.318

962.244b

4.000 66.00

0 .000

58.318 962.244b 4.000

Type of industry

Pillai's Trace

.118 2.215b 4.000

66.000

.077

.118 2.215b 4.000

Wilks' Lambda

.882 2.215b 4.000

66.000

.077

.882 2.215b 4.000

Hotelling's Trace

.134 2.215b 4.000

66.000

.077

.134 2.215b 4.000

Roy's Largest

Root .134 2.215

b 4.000

66.000

.077

.134 2.215b 4.000


b. Exact statistic




4. CONCLUSION

The critical factors were identified and their analysis has been carried out in the present work

for the implementation of quality practices in SME’s. It has been observed that the critical

factors have been played a major role to increase performance and sustainability of TQM in

small and medium scale enterprises from statistical test results. Also, it is evident that the

implementation of TQM enhanced quality and cost saving in both service and production in-

turn increases the productivity with faster job and less rejection. Product quality, quality

policy, management committement, planning, resource management, purchasing,

measurement analysis are input factors increase the performance of output parameters such as

employee satisfaction, customer satisfaction, product realization, quality results,

environmental factors and all these improved the quality management system. The significant

difference was high in case of operational effectiveness and customer satisfaction compared

to employee satisfaction has been found.

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