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Nov -2011/ Volume-1/Issue-4/Article No-8/63-77 ISSN: 2249-7196

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INTERNATIONAL JOURNAL OF MANAGEMENT RESEARCH

AND REVIEW

IMPACT OF QUALITY MANAGEMENT PRACTICES ON THE ORGANISATIONAL

PERFORMANCE OF SMALL AND MEDIUM SCALE MANUFACTURING

INDUSTRIES

Shivakumar B. Burli *1 , B. B. Kotturshettar 1, Priyanka Kalghatgi 1

1 Department of Industrial & Production Engineering, BVB College of Engineering &

Technology, Hubli, Karnataka, India

ABSTRACT

This paper investigates the relationships between quality management practices and multiple

performance measures in SMEs. Based on extensive literature survey six determinants of TQM

practices were identified, and their impact was measured on overall performance of ISO certified

and Non-ISO manufacturing SME’s in Karnataka and Maharashtra. The investigated constructs

included Management Support, People Management, Training, Continuous Improvement,

Customer Focus, and Supplier Relationship. Sample of this study comprised of 133 ISO certified

manufacturing industries of Karnataka and Maharashtra and 40 Non-ISO firms. A set of

questionnaires was sent to some conveniently selected ISO certified and Non ISO manufacturing

industries of Karnataka and Maharashtra. The data set resulted from the questionnaire survey

were analysed using statistical software SPSS. The focus of analysis was to produce results that

reinforce the belief of senior management in quality management practices. The findings of this

study bring out the significant benefits of ISO 9001:2000 in SMES and, encourage the Non-ISO

firms to begin quality initiatives via ISO.

Keywords: TQM practices, ISO certification, Organisational Performance, SMEs

INTRODUCTION

Small and medium scale enterprises (SMEs) provide development abilities to the complete world

economy. Economic growth is accelerated by the SMEs, as SMEs are productive and vibrant

contributors to the economy. SMEs output grew with higher speed than the large industrial

sector. Employment generation in SMEs is swifter, 0.5 million jobs annually. Importance of

SME sector is vital for the industrial development of a country. Taking into consideration the

tremendous contribution of SMEs in industrial upbringing and development of economic

condition, this sector has been chosen so that effective solutions could be suggested for the

improvement in performance measures.

With the advent of planned economy from 1951 and the subsequent industrial policy followed by

Government of India, both planners and Government earmarked a special role for small-scale

industries and medium scale industries in the Indian economy. Due protection was accorded to

both sectors, and particularly for small-scale industries from 1951 to 1991, till the nation adopted


Copyright © 2011 Published by IJMRR. All rights reserved 64

a policy of liberalisation and globalisation. Certain products were reserved for small-scale units

for a long time, though this list of products is decreasing due to change in industrial policies and

climate. SMEs form the backbone of the Indian manufacturing sector and have become engine of

economic growth in India. It is estimated that SMEs account for almost 90% of industrial units in

India, and 40% of value addition in the manufacturing sector.

The ISO 9001 family of standards relate to quality management systems, and are designed to

help organisations ensure they meet the needs of customers and other stakeholders. The global

adoption of ISO 9001 may be attributable to a number of factors. A number of major purchasers

require their suppliers to hold ISO 9001 certification. ISO does not itself certify organisations.

Many countries have formed accreditation bodies to authorise certification bodies, which audit

organisations applying for ISO 9001 compliance certification. An ISO certificate is not a once-

and-for-all award, but must be renewed at regular intervals recommended by the certification

body, usually around three years. There are no grades of competence within ISO 9001, either a

company is certified (meaning that it is committed to the method and model of quality

management described in the standard), or it is not.

Quality Management System (QMS) can be expressed as the organisational structure,

procedures, processes and resources needed to implement quality management. Successfully

establishing Quality Management System according to ISO 9001:2000 means that all workflow,

from the beginning up to the manufacturing and test procedures, is done to the highest, precisely

defined quality standard. The ISO 9001 family of standards relate to quality management

systems and are designed to help organisations ensure they meet the needs of customers and

other stakeholders.

The Gross Domestic Product or GDP is the indicator of the performance of an economy. India is

a vast country, so the sectors contributing to the country's GDP are also big in number. Various

sectors falling under the India GDP composition includes food processing, transportation

equipment, petroleum, textiles, software, agriculture, mining, machinery, chemicals, steel,

cement and many others. Agriculture is the pre dominant occupation in India, employing more

than 50% of the population. The service sector accounts for employing more than 25% while the

industrial sector accounts for more than 10%. According to the estimates of 2008, India's GDP is

$1.209 trillion, and this is slated to make improvement in the coming times. In 2008 the country's

GDP growth rate was 9% (Figure 1). The slowdown that has been witnessed this year in the

estimates is largely due to the slowdown witnessed by the agriculture and the industrial sectors.

A look at the India GDP composition sector wise throws up some interesting figures. The

agriculture sector contributed 17.2%; industry contributed 29.1% while the service sector had a

contribution of 52.7% according to 2008 estimates (see Figure1). The reasons for the increase of

industry growth rate in Indian GDP are that huge amounts of investments are being made in this

sector, and this has helped the industries to grow. The structural transformation of the Indian

economy over the last three decades has been spectacular growth of the services sector, which

now accounts for about 50 per cent of the GDP.



Figure 1: Indian GDP growth rate

About four million industrial undertakings in India are under small and medium-sized enterprises

(SME’s) category and their contribution to the gross domestic product (GDP) of the nation is

very much significant. For survival and growth of SMEs, it has become highly imperative for

them to adapt cost effective manufacturing strategies by eliminating defects from every one of

the company’s products, process, and business transactions. It can be observed that by and large,

SMEs in India met the expectations of the Government in this respect. SMEs developed in a

manner, which made it possible for them to achieve the following objectives:

� High contribution to domestic production

� Significant export earnings

� Technology oriented industries

At the same time one has to understand the limitations of SMEs, which are:

� Low Capital base

� Lack of professionalism

In spite of these limitations, the SMEs have made significant contribution towards technological

development and exports.

SMEs have been established in almost all-major sectors in the Indian industry such as food

processing, agricultural inputs, engineering, electrical, electronics, textiles and garments, and

computer software, etc. Those SMEs who have strong technological base, international business

outlook, competitive spirit, and willingness to restructure themselves shall withstand the present

challenges, and come out with shining colours to make their own contribution to the Indian

economy.

LITERATURE REVIEW

This research was carried out to get an understanding of the impact of TQM on the performance

of SMEs. In order to get complete understanding of the theory and practice, extensive literature



study was made and various studies were analysed and reviewed. The literature review starts

with a description of ISO, TQM and its practices. According to some authors, these areas have

often been considered the critical factors of TQM (e.g., Sila and Ebrahimpour, 2003; Conca et

al., 2004; Claver et al., 2003). Brief explanation of these factors is given in the following

sections:

ISO

It is a measure of whether the company has been certified by the ISO 9000 specifying which

version is being applied. Since ISO 9000 series of standards first emerged in 1987, many authors

found that ISO offered a reasonable first step toward implementing quality (Bradley, 1994;

Claver et al., 2002; Escanciano et al., 2001; Gotzamani and Tsiotras, 2002; Skrabec, 1999;

Stephens, 1997; Sun, 2000; Taylor, 1995; Tummala and Tang, 1996; Withers and Ebrahimpour,

2001; Yusof and Aspinwall, 2000). This initial version of ISO addressed quality issues in

categories such as quality policy, quality documentation and quality planning.

Total Quality Management

TQM is defined as the art of managing the whole to achieve excellence (Besterfield et al., 2008).

This definition emphasises the need to focus on all the functions of an organisation in an

integrated manner to achieve customer satisfaction. The author expands the meaning of TQM as

both, ‘a philosophy, and a set of guiding principles’, that represent the foundation of a

continuously improving organisation. Flynn et al, (1994) defined and empirically tested a scale

for measuring TQM. The same authors for evaluation of TQM in the company performance later

used this scale. This scale was chosen for the current study in order to measure TQM

implementation. This is appropriate for manufacturing companies, and also has been validated

and accepted as a good measurement of TQM in the literature. Lee and Kelce, (1973)

investigated the existing status of TQM practices in 112 SMEs (manufacturing firms) of China

and its impact on their performance. It was found that manufacturing process of these small firms

was not an obstacle to the implementation of TQM; instead it was the size of firm, which posed

as a threat for implementation. Research showed that majority of the firms were new to TQM

practices and that it was initiated by their top management. A positive influence of TQM was

observed on performance as waste, inventory and costs was reduced, and an increase in sales was

observed.

In the same manner, performance of SMEs was observed in (Malaysia by Sohail and Hoong,

2003; in India by Mahadevappa et al., 2004; in Portugal by Sousa et al., 2005; in Spain by Bou

and Beltrain, 2005; and in Turkey by Demirbag and Zaim, 2006). All researchers were of the

view that ISO certification should be acquired by the SMEs, and, ISO quality management

systems should be integrated with TQM for continuous improvement of the overall business

performance.

In Pakistan, Alam and YeZhuang, (2005), studied the trend, status and scope of ISO certification

in Pakistani industry and made comparative analyses with Spanish industry and Chinese industry



Alam to highlight the differences in approaches and the hurdles encountered in implementation.

Earlier Moosa, (1999) observed that maximum practice of quality management practices in ISO

certified firms was in the production department, there was unawareness from usage of different

quality tools for performance measurement and that TQM was properly practiced in only 5%

firms among total. Khan (2000) proposed that for successful implementation of TQM in

Pakistani organizations commitment of both top and middle level management is compulsory,

that a right approach towards TQM implementation should be made, that TQM tools should be

used step by step and that workers fears should be removed and a reward system should be

introduced for better performance. Hayat M. Awan, (2007) studied the impact of ISO registration

in sports industry of Pakistan. Benefits gained by these organizations were increase in sales

(exports), increased customer satisfaction, better utilization of human and material resources and

reduction in costs and wastage. The results validated the previous studies in which it was

concluded that performance has positive relationship with TQM practices.

Most of the above-mentioned studies were carried out in developed countries with few

exceptions and, in India there is scarcity of research on TQM except few examples cited above.

This research will therefore fill a gap in the existing literature by investigating plausible

relationship between TQM practices and Organisational Performance.

RESEARCH METHODOLOGY

Figure 2 , gives the stepwise methodology adopted for the current study.

Figure 2: Research Process

Define the research objectives

Identify the data sources

Choosing appropriate design and data collection methods

Designing of the form or research instrument

Identifying the sample

Collecting the data

Analyzing and interpreting the data

Presenting the findings



Research Design and Analysis

For this study, three objectives were identified to explore the impact of total quality management

practices on organisational performance of SMEs.

(i) To investigate the relationships between TQM practices and multiple performance measures

(ii) To prepare and test a model showing the relationship between various TQM practices and

Organisational performances

(iii) To determine the difference between the performances of ISO certified and Non-ISO

certified small and medium scale industries.

Based on similar studies, the sample size of 150 was chosen. Primary data was collected through

self-administered questionnaire. Total 150 questionnaires were sent to quality managers and

owners of SMEs located in states of Karnataka and Maharashtra. Responses received were 133

from ISO certified SMEs. Using the same instrument responses were collected from 40 Non ISO

firms that included electrical, tools, and machinery segments from two States i.e. Karnataka and

Maharashtra. The six TQM constructs i.e. Management Support, People Management, Training,

Continuous Improvement, Supplier Relationship, and Customer Focus were chosen from the

studies of Richard Yu Yuan hung et al., (2010) and Esin et al., (2010). Likert’s five-point scale

was used for collecting the responses in which ‘5=Strongly Agree’, ‘4= Agree’,

‘3=Neutral’,’4=Disagree’, and ‘1=Strongly Disagree’. Questionnaires were distributed to

managers and supervisors of the SMEs.

The dataset from questionnaires survey was fed in to SPSS 17.0 for initial descriptive analysis.

The correlation and regression analysis was carried out and the results, graphs, tables were

extracted. In the first stage, applying Cronbach’s alpha, which measures internal consistency or

average correlation of items in a survey instrument to gauge its reliability, has checked reliability

of the data. In the second stage, Pearson correlation analysis was carried out to assess the

strength of relationship between dependent and independent variables. In the third stage, multiple

regression analysis is applied to check association of variables with each other and also the

extent of variance, which is determined by co-efficient of determination (R-square) in dependent

variable. Finally Z-Test was used, to analyse the diffrences in mean values obtained in ISO and

Non ISO firms.

Research Hypotheses

Hypothesis is a tentative conjecture explaining an observation, phenomenon or scientific

problem that can be tested by further observation, investigation and/or experimentation. In this

study hypotheses were formulated so as to capture the relation between six independent variables

(Management Support, People Management, Training, Continuous Improvement, Supplier

Relationship, Customer Focus) and, one composite dependent variable (Organisational

Performance which include Internal Customer Satisfaction, External Customer Satisfaction,



Financial Performance, Societal Impact). Summated scales of each construct were used for

testing the hypotheses. The following regression equation has been formulated here for the study:

OR = B0 + B1MS + B2PM + B3TR + B4CI + B5SR + B6CF + error

Where,

OR = Organisational Performance

B0 = Constant of proportionality

MS = Management Support

PM= People Management

TR = Training

CI= Continuos Improvement

SR = Supplier Relationship

CF = Customer Focus

e = error term

B1, B2…….B6 : Un standardised regression coefficients of predictors viz, Management Support

(MS), People Management (PM), Training (TR), Continuous Improvement (CI), Supplier

Relationship(SR), Customer Focus (CF) respectively.

A total of six hypotheses were formulated related to six TQM practices and their impact was

measured on Organisational Performance. The research model is shown in Figure3.

H1 = Management Support influences Organisational Performance of Manufacturing industries.

H2 = People Management influences Organisational Performance of Manufacturing industries.

H3 = Training influences Organisational Performance of Manufacturing industries.

H4 = Continuous Improvement influences Organisational Performance of Manufacturing

industries.

H5 = Supplier Relationship influences Organisational Performance of Manufacturing industries.

H6 = Customer focus influences Organisational Performance of Manufacturing industries.

.

Figure 3: Research Model



RESULTS AND DISCUSSIONS

The data set was subjected to reliability analysis prior to correlation and regression analysis in

SPSS. Summated scales of individual constructs were used for analysis.

RELIABILITY ANALYSIS

To check the consistency of the variables reliability analysis was carried out using Cronbach’s

Alpha, which is a coefficient of reliability and, is commonly used as a measure of the internal

consistency or reliability of a data set. Table 1 gives the test results.

Table 1: Reliability of scale of ISO certified manufacturing industries

Variable No. of items Cronbach’s Alpha.

Management Support 5 0.95

People Management 4 0.90

Training 4 0.87

Continuous Improvement 4 0.91

Supplier Relationship 4 0.82

Customer Focus 4 0.81

Internal Customer

Satisfaction 6 0.91

External Customer

Satisfaction 4 0.95

Financial Performance 3 0.96

Societal Impact 2 0.92

By referring Table 1, it is evident that all the values of Cronbach’s alpha for independent

variables i.e. Management Support, People Management, Training, Continuous Improvement,

Supplier Relationship, Customer Focus, Supplier Relationship, Customer Focus respectively are

above the suggested cut-off value of 0.7 or higher (Nunnally and Bernstein, 1994) which means

that the constructs were reliable to measure the Organisational Performance. Whereas alpha

values of dependent variable i.e. Internal Customer Satisfaction, External Customer Satisfaction,

Financial Performance, Societal Impact respectively are also above 0.7 which is in acceptable

range and means that individual constructs were reliable to measure the parameters of

Organisational Performance



Table 2: Reliability of scale of Non ISO certified manufacturing industries

Variable No. of

items Cronbach’s alpha.

Management support 5 0.78

People management 4 0.78

Training 4 0.73

Continuous improvement 4 0.70

Supplier relationship 4 0.71

Customer focus 4 0.74

Internal customer satisfaction 6 0.85

External customer satisfaction 4 0.81

Financial performance 3 0.94

Societal impact 2 0.82

With reference to Table 2, it is evident that the overall values of Cronbach’s alpha for

independent variables are above the suggested cut-off value of 0.7 or higher (Nunnally and

Bernstein, 1994) which means that the constructs were reliable to measure the Organisational

Performance. Whereas alpha values of dependent variable i.e. Internal Customer Satisfaction,

External Customer Satisfaction, Financial Performance, Societal Impact respectively are also

above 0.7, which is in acceptable range.

CORRELATION ANALYSIS

Correlation analysis was carried out between the independent variables i.e. Management

Support, People Management, Training, Continuous Improvement, Supplier Relationship,

Customer Focus, and dependent variable i.e. Organisational Performance.

Table 3: Corrélation Matrix

Variable MS PM TR CI SR CF OR

MS 1.00 * * * * * *

PM 0.14 1.00 * * * * *

TR 0.16 0.16 1.00 * * * *

CI 0.12 -0.07 0.02 1.00 * * *

SR 0.09 0.07 -0.03 0.28 1.00 * *

CF 0.05 0.02 -0.02 0.10 0.16 1.00 *

OR 0.15 0.06 0.16 0.09 0.05 0.13 1.00

Keys: MS-Management Support, PM-People Management, TR-Training, CI-Continuous

Improvement, SR- Supplier Relationship, CF- Customer Focus, OR- Organisational

Performance.

Table 3 illustrates that the value of the correlation coefficient (r) of dependent Variable i.e.

Organisational Performance (OR) with independent variable i.e. Management Support (MS) is

0.15 which means that both the variables have weak positive correlation. The correlation

coefficient (r) of independent Variable i.e. Continuous Improvement (CI) with independent



variable i.e. Supplier Relationship (SR) is 0.28, this indicates that there is a weak positive

correlation between them. In the same manner a weak positive correlation has been found

between dependent variable i.e. Organisational Performance (OR) and independent variables i.e.

People Management (PM), Training (TR), Continuous Improvement (CI), Supplier Relationship

(SR), Customer Focus (CF) whose values of correlation coefficient (r) are 0.06, 0.16, 0.09, 0.05,

0.13 respectively.

REGRESSION ANALYSIS

In statistics, regression analysis includes the techniques for modelling and analysing the

relationship between several independent variables and a dependent variable. More specifically,

regression analysis helps one understand how the typical value of the dependent variable changes

when any one of the independent variables is varied, while the other independent variables are

held fixed. For the current study, multiple regression was carried out taking organisational

performance as dependent composite variable and six quality practices as independent variables.

The analysis produces ANOVA (Table 4) and coefficients (Table5). The F value 1.755 with p

value of 0.114 indicate that the regression model is not adequate. Table 5, give the both

standardised and unstandardised coefficients, and their p values. The collinerity statistics revel

the VIF (variance inflation factor) values for all parameters are much below 5 and hence, the

problems of multicollinerity can be ignored.

Table 4: ANOVA

Model Sum of Squares Df Mean Square F Sig

1 Regression 268.272 6 44.712 1.755 .114a

Residual 3209.819 126 25.475

Total 3478.090 132

a. Predictors: (Constant), CF, CI, PM, MS, SR, TR

b. Dependent Variable: OR

Table 5: Coefficients

Unstandardised coefficients T Sig Collinearity statistics

B Tolerance VIF

(Constant) 34.72 2.74 0.01

MS 0.79 1.82 0.02 .93 1.08

PM -0.25 -0.80 0.43 .97 1.03

TR 0.40 1.14 0.04 .47 2.15

CI 0.36 1.30 0.20 .92 1.09

SR -0.13 -0.51 0.61 .89 1.13

CF 0.32 0.29 0.77 .45 2.20



It is evident from Table 5 that the values of unstandardised coefficients of Management Support

(MS), Training (TR), Continuous Improvement (CI), and Customer Focus (CF) are significant

which supports hypotheses regarding these four variables. Values of unstandardised coefficients

of People Management (PM) and Supplier Relationship (SR) are not statistically significant as

their p value exceeds 0.05 level.

As the p value (illustrated in table 4) is not significant (p > 0.05) the weak criteria i.e. People

Management (PM) and Supplier Relationship (SR) with least unstandardised co-efficient values

were discarded and again the regression analysis was re-run with only four variables i.e.

Management Support (MS), Training (TR), Continuous Improvement (CI), Customer Focus

(CF). Table 6, Table 7, and Table 8 give the ANOVA results, model summary, and regression

coefficients respectively along with the p- values. The p value illustrated in Table 6 is less than

0.05, it can be concluded at 95% confidence level the regression model is valid and adequate.

The R2 value of 0.071 (Table 7) indicates the predictors explain only 7.1% of variance in

dependent variable. Further, Table 8 gives the values of significant and unstandarised

coefficients generated from multiple regression analysis.

Table 6: ANOVA

Model Sum of Squares Df Mean Square F Sig.

1 Regression 247.570 4 61.893 2.452 .049a

Residual 3230.520 128 25.238

Total 3478.090 132

a. Predictors: (Constant), CF,CI, MS, TR

b. Dependent Variable: OR

Table 7: Model summary

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .267a .071 .042 5.024

a. Predictors: (Constant), CF, CI, MS, TR

Table 8: Coefficients of regression

Co-efficients

Untandardised co-efficients T Sig Collinearity Statistics *

B Tolerance VIF

(Constant) 29.79 2.63 0.01 0.97 1.04 MS 0.73 1.71 0.02 0.47 2.13 TR 0.38 1.08 0.04 0.99 1.04 CI 0.34 1.26 0.04 0.46 2.17 CF 0.34 0.38 0.04 0.97 1.04



* acceptable values: Tolerance > 0, and VIF < 5

Thus in the current study, out of six hypotheses only four were supported. The collinearity

statistics indicates that all ‘Variance Inflation Factor (VIF)’are less than 5 and hence, the dataset

is free from multi-collinearity problems. Figure 4, depicts the regression model results.

Hence the regression equation is,

OR=29.79+0.73MS+0.38TR+0.34CI+0.34CF

Figure 4: Regression model results

COMPARATIVE ANALYSIS

The current study, considered two types of SMEs, in which 133 were ISO certified and 40 were

Non-ISO certified. In order to analyse the difference in mean values of quality practices between

these two groups, two sample Z- test was carried out. The z values and their corresponding p-

values indicate that there are significant differences in quality practices between ISO-certified

and non-ISO certified SMEs.

Table 9: Z-test results

TQM practice

Means score Z

Sig ISO Non ISO

Management Support 21.7 18.0 7.1 0.00 People Management 16.9 15.8 2.4 0.01

Training 17.1 13.1 9.2 0.00 Continuous Improvement 17.1 16.6 2.0 0.02 Supplier Relationship 17.2 16.5 2.8 0.01

Customer Focus 16.6 14.4 5.6 0.00 Organisational Performance 61.7 55.5 8.8 0.00

All z values are significant as p < 0.05



It is evident from Table 9, that as all the z values surpass critical value of 1.96, at 95%

confidence level. Therefore it can be concluded that level of TQM practices in ISO certified

manufacturing SME’s are significantly better than Non-ISO certified manufacturing SME’s. This

brings leads to an important implication of ISO that the manufacturing SME’s that are ISO

certified are much better in terms of adoption of quality practices and, are slowly moving

towards TQM culture.

CONCLUSION

SMEs act as a vital component of growing economy by contributing significantly for the

development of economy by creating employment for both urban and rural workforce and by

providing much needed flexibility and innovation in the economy as a whole. If TQM policies

and practices are applied in a positive manner in manufacturing SMEs, it will significantly

contribute in their performance in terms of quality and customer satisfaction. ISO has been

adapted in many SMEs but certain TQM practices observed to be weak and hence, need

management attention. The study brought out that the manufacturing SME’s must accept, and

practice TQM practices to enhance performance and customer satisfaction. The study also

revealed that ISO certified firms demonstrate higher level of TQM practices as compared to

Non-ISO SMEs. Hence the firms must initiate TQM implementation via ISO and then slows

expand to address soft dimensions like people management to achieve continuous improvement

of processes and increased level of customer satisfaction.

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INTERNATIONAL JOURNAL OF MANAGEMENT RESEARCH AND …ijmrr.com/admin/upload_data/journal_Shivakumar Burli 8.pdf · Keyword s: TQM practices, ISO certification, Organisational Performance,