Examining the effects of contextual factors on TQM and ...isila.gau.edu.tr/article/1445341397-jom_publication.pdf · Examining the effects of contextual factors on TQM and performance

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Journal of Operations Management 25 (2007) 83–109

Examining the effects of contextual factors on TQM and

performance through the lens of organizational theories:

An empirical study

Ismail Sila *

Department of Finance and Management Science, College of Commerce, University of Saskatchewan,

25 Campus Drive, Saskatoon, Sask., Canada SK S7N 5A7

Received 20 April 2005; received in revised form 25 October 2005; accepted 13 January 2006

Available online 20 March 2006

Abstract

Although much has been written about TQM, little attention has been paid to the potential effects of contextual factors on TQM

and TQM–performance relationships. The use of organizational theory to formulate propositions regarding the effects of such

factors is especially scarce in the TQM literature. This study uses institutional theory and contingency theory as the basis to test a

number of such propositions. First, a model of TQM and organizational performance is developed. Then using survey data, the

effects of five contextual factors – three institutional factors and two contingency factors – on the implementation of TQM practices

and on the impact of TQM on key organizational performance measures are analyzed within a TQM–performance relationships

model framework. The three institutional factors include TQM implementation, ISO 9000 registration, and country of origin, and

the two contingency factors include company size and scope of operations. The results show that the implementation of all TQM

practices is similar across subgroups of companies within each contextual factor. In addition, the effects of TQM on four

performance measures, as well as the relationships among these measures, are generally similar across subgroup companies. Thus,

for the five contextual factors analyzed, the overall findings do not provide support for the argument that TQM and TQM–

performance relationships are context-dependent. The implications of the study for managers and researchers, as well as study

limitations, are also discussed.

# 2006 Elsevier B.V. All rights reserved.

Keywords: Quality management; Organizational behavior; Interdisciplinary; Empirical research methods; Questionnaires/surveys/interviews

1. Introduction

In general, previous studies obtained mixed results

about the success and failure rates of total quality

management (TQM). Some of these studies reported

estimates of TQM failure rates as high as 60–67%

(Dooyoung et al., 1998). However, other studies yielded

more optimistic results. For instance, according to a

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E-mail address: [email protected].

0272-6963/$ – see front matter # 2006 Elsevier B.V. All rights reserved.

doi:10.1016/j.jom.2006.02.003

study conducted by Mohrman et al. (1995), 83% of the

surveyed companies had a ‘‘positive or very positive’’

experience with TQM, and 79% planned to ‘‘increase

or greatly increase’’ their TQM initiatives in the next

3 years.

One likely reason for some of the unsuccessful

TQM implementations is the possibility that TQM is

context-dependent. That is, contextual factors such

as company size and scope of operations might play a

role in the implementation of TQM practices and out-

comes. However, this issue has largely been ignored in

the literature. Thus, one of the objectives of this study

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http://dx.doi.org/10.1016/j.jom.2006.02.003

I. Sila / Journal of Operations Management 25 (2007) 83–10984

is to empirically analyze and compare TQM practices

across companies with different characteristics using

several contextual factors. The study will also examine

how these factors affect the relationships among TQM

and key organizational performance measures. These

analyses are intended to shed light on whether the

universal or the context-dependent approach to TQM

is warranted. The use of organizational theory to test

the validity of these two approaches has been scarce in

the TQM literature. To fill this void, this study uses

two organizational theories, institutional theory and

contingency theory, as the basis to formulate proposi-

tions regarding the effects of contextual factors on

TQM practices and TQM–performance relationships.

There are differing views on whether a context-

dependent or universal approach to TQM implementa-

tion is appropriate. However, despite a lack of empi-

rical evidence, the assumption of universal applicability

has permeated the literature with little attention being

given to the context-dependent argument. Several

recent studies (e.g., Sousa and Voss, 2002; Sila and

Ebrahimpour, 2002, 2003) also emphasized the need

to conduct contingency studies in the field of TQM.

One of the earlier empirical studies in the quality

management area that analyzed the effects of several

contextual factors on the implementation of TQM

practices was conducted by Benson et al. (1991). This

study obtained mixed results in that although company

type explained the variation in the ‘‘actual quality

management practices’’ implemented, other factors

including company size and manager type did not. It can

be argued that this study did not have a big following

since very few similar studies were published in

subsequent years. For instance, a study by Martinez-

Lorente et al. (1998) used data from Spanish industrial

companies to analyze the effects of several company

characteristics such as size, nationality, conviction

about the benefits of TQM, and perceived product value

on the application of TQM. Most of the other empirical

studies in this area mainly focused on cross-country

comparisons of TQM practices (e.g., Adam et al., 1997;

Solis et al., 2000; Rungtusanatham et al., 2005) or the

effect of company size on these practices (e.g., Ahire

and Golhar, 1996). In addition, Sousa and Voss (2001)

analyzed manufacturing strategy as a contextual factor

and found evidence that TQM practices were contingent

on manufacturing strategy.

In these previous studies that analyzed contextual

factors, either no performance measures or a limited

number of measures were used, or the relationships

among TQM and performance measures were not

analyzed within a TQM–performance relationships

model. Overall, a limited number of such empirical

studies did not provide conclusive evidence for the

validity of either the universal or context-dependent

approach to TQM. This study develops a structural

equation modeling (SEM) model, where the combined

effects of seven TQM practices on four measures of

organizational performance, as well as the effects of

these performance measures on each other, are tested

using survey data. This model is also tested using five

contextual factors by conducting multiple group

analysis to determine whether the model relationships

are invariant (i.e., equivalent) across subgroups of

companies within each contextual factor.

2. Model and hypotheses

An extensive review of the TQM literature showed

that the TQM construct could be measured by seven

general categories of practices including leadership,

strategic planning, customer focus, information and

analysis, human resource management (HRM), process

management, and supplier management. A description

of these practices and the supporting literature for them

are provided in Table 1. These practices are also

consistent with the Malcolm Baldrige National Quality

Award (MBNQA) criteria as suggested by Sila and

Ebrahimpour (2003), who analyzed the TQM practices

extracted by 76 empirical TQM studies and categorized

them under the 2002 MBNQA framework. The results

of an empirical study by Curkovic et al. (2000a) also

showed that using the MBNQA framework, companies

could achieve the implementation of TQM, which also

indicated that the MBNQA was compatible with TQM

practices. However, in contrast to the MBNQA frame-

work, supplier management was used as a separate

practice in the current study since supplier management

has been very critical for many organizations in recent

years as a result of the growing importance of supply

chain management. In addition, as shown in Table 1,

this practice has been extracted as a separate TQM

factor by a number of previous empirical studies. Using

it as a separate practice in the proposed model would

also make it possible to assess its significance for the

TQM construct, as well as compare its implementation

across companies with different characteristics.

The four performance variables used to measure

organizational performance in four key business areas

include human resource results, customer results,

organizational effectiveness, and financial and market

results. The items constituting each measure and the

supporting literature for these items are listed in Table 1.

Fig. 1 shows an SEM model of the nine hypotheses

I. Sila / Journal of Operations Management 25 (2007) 83–109 85

Fig. 1. A model of the relationships among TQM and key organizational performance measures and structural path analysis results for the full

sample (*p < 0.001).

Table 1

TQM practices and performance measures used in the model

TQM practices and

performance measures

Description of TQM practices and


Supporting literature for TQM practices and


Leadership Top management and supervisory commitment

and leadership; public responsibility

and citizenship

Flynn et al. (1994), Powell (1995), Anderson et al. (1998),

Wilson and Collier (2000), Sun and Cheng (2002)

Strategic planning Quality mission, goals and policy; strategy

development and deployment

Mohrman et al. (1995), Black and Porter (1996),

Raghunathan et al. (1997), Dow et al. (1999),

Solis et al. (2000), Sun and Cheng (2002)

Customer focus Customer and market knowledge; attention

to customer satisfaction; management

of customer relationships

Powell (1995), Ahire et al. (1996b),

Adam et al. (1997), Anderson et al. (1998),


Information and

analysis

Performance measurement and analysis;

information management; use of information

technology; quality tools; benchmarking

Powell (1995), Samson and Terziovski (1999),

Anderson and Sohal (1999), Wilson and Collier (2000),


Human resource

management

Employee involvement; employee empowerment;

teamwork; rewards, recognition and performance

appraisal; employee training

Flynn et al. (1994), Black and Porter (1996),

Rao et al. (1997a), Anderson and Sohal (1999),

Samson and Terziovski (1999), Wilson and Collier (2000),

Sun and Cheng (2002)

Process management Product and service design; process control;

innovation and continuous improvement of

processes, products and services

Saraph et al. (1989), Flynn et al. (1994), Powell (1995),

Anderson et al. (1995), Samson and Terziovski (1999),

Wilson and Collier (2000), Sun and Cheng (2002)

Supplier management Supplier quality; supplier involvement;

supplier relationships

Saraph et al. (1989), Powell (1995), Ahire et al. (1996b),

Rao et al. (1999), Solis et al. (2000), Curkovic et al. (2000b),

Sun and Cheng (2002)

Human resource

results

Employee turnover rate; employee absenteeism;

number of employee suggestions received;

employee job performance

GAO (1991), Adam et al. (1997),

Paauwe and Richardson (1997),

McAdam and Bannister (2001), NIST (2002)

Customer results Customer retention; reliability and timely delivery

of products and services; personalized service;

value for the money spent

GAO (1991), Dean and Bowen (1994),

Hendricks and Singhal (1997),

Atkins et al. (2002), NIST (2002)

Organizational

effectiveness

Cost; quality; productivity; cycle times;

number of errors or defects;

supplier performance

Deming (1986), GAO (1991),


Kim et al. (2002), Rust et al. (2002)

Financial and

market results

Market share; profit; return on total assets

(ROA); overall competitive position;

number of successful new product

and service introductions

Shetty (1987), GAO (1991), Juran (1992),


Gunasekaran (2002), NIST (2002)

I.S

ila/Jo

urn

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of

Op

eratio

ns

Ma

na

gem

ent

25

(20

07

)8

3–

10

98

6

Table 2

Comparison of TQM practices across different studies

Saraph et al. (1989) Flynn et al. (1994) Ahire et al. (1996b) Dow et al. (1999) Rao et al. (1999) Wilson and Collier (2000) The current study

The role of top

management

leadership

Top management

support

Top management

commitment

Top management commitment Leadership Leadership

Quality citizenship

Shared vision Strategic quality planning Strategic planning Strategic planning

The role of the quality

department

Customer

involvement

Customer focus Customer focus Customer orientation Customer focus

Quality data and

reporting

Quality

information

Internal quality

information usage

Use of

benchmarking

Quality information availability Information and analysis Information and

analysis

Benchmarking Quality information usage

Benchmarking

Training Workforce

management

Employee training Workforce

commitment

Employee training Human resource

development and

management

Human resource

management

Employee relations Employee empowerment Use of teams Employee involvement

Employee involvement Personnel training

Product/service design Product design Design quality management Product/process design

Process management Process

management

Statistical process

control usage

Process management Process management

Supplier quality

management

Supplier

involvement

Supplier quality

management

Cooperative

supplier relations

Supplier quality Supplier management

Product quality Internal quality results Customer focus

and satisfaction

Organizational

effectiveness

Supplier performance External quality results Financial results Customer results

Financial and market results

Human resource results


developed using literature support. Table 2 suggests

that the TQM practices included in this study are

consistent with those used by previous studies.

However, the items measuring each TQM practice

is more comprehensive compared to these studies.

This study also incorporates a greater number of

performance measures and tests the relationships

among them. Previous studies that integrated perfor-

mance measures into their models mostly included

one or two measures, each of which was operationa-

lized by a single item. In addition, these measures

were generally used as dependent variables. In this

study, three of the four performance measures serve as

both independent and dependent variables, each of

which is measured by at least four items. Although

this study incorporates most major TQM practices and

a large number of key performance measures, no

claim is made that they are exhaustive, if indeed such a

claim is possible. The nine hypotheses formulated are

discussed below.

2.1. The effect of TQM on human resource results

The implementation of TQM is one of the most

complex undertakings for a company, as it entails

changes in organizational culture and affects employees

(Kanji and Barker, 1990). It is important to analyze how

organizational changes brought about by TQM will

affect employees simply because employees are key

organizational stakeholders (Mohrman et al., 1995).

However, research analyzing TQM’s effect on human

results has been scarce (Guimaraes, 1996).

Many TQM elements are people-oriented and

include such practices as teamwork, employee empow-

erment and involvement in decision-making (Guimar-

aes, 1996). Making such practices part of TQM

contributes positively to employee results such as

employee satisfaction. This is because the new

processes put in place as a result of TQM are more

likely to be embraced by employees if they are actively

involved in developing these processes (Mohrman et al.,

1995).

A case study conducted by McAdam and Bannister

(2001) suggested that the implementation of TQM in

a company contributed to a positive working environ-

ment, in both physical and psychological sense, and

resulted in reductions in employee absenteeism.

Mohrman et al. (1995) reported that a composite of

several core TQM practices such as quality improve-

ment teams and cross-functional planning had a

significant association with employee satisfaction

and quality of work life. Other studies also showed

that TQM practices had a positive correlation with

employee satisfaction (Grandzol, 1998) and annual

employee turnover rate (Adam et al., 1997). Consistent

with these studies, a study by Boselie and van der Wiele

(2002) indicated that employee perceptions of TQM

concepts led to a higher level of satisfaction and less

intention to leave the organization. In addition,

according to a study conducted by Guimaraes

(1996), employees had higher job satisfaction, job

involvement, commitment to the organization, and

intentions to stay with the company as a result of TQM.

Thus we have the following hypothesis.

H1. TQM has a direct, positive effect on human

resource results.

2.2. The effect of TQM on customer results

A company’s success in the long term depends on

how effectively it satisfies its customers’ needs on a

constant basis (Brah et al., 2002). Therefore, TQM’s

success is determined by how willing the organization

is to change and whether it uses customer satisfaction

as a measure in assessing the success of its decisions

and actions (Madu and Kuei, 1993). Although many

companies may realize the significance of being

customer-oriented, they usually face a challenge in

monitoring and measuring their customers’ expecta-

tions, experience, and satisfaction with their products

(Sebastianelli and Tamimi, 2002). Many companies

implementing TQM attempted to meet this challenge

by encouraging their employees to get actively involved

in achieving customer satisfaction. For instance, they

tied their employees’ performance evaluations to cus-

tomer care indicators (Wilkinson et al., 1993).

Deming (1982) argued that customer satisfaction

was the most important outcome of TQM practices.

Most quality award models also recognize customer

results as a significant TQM outcome. In fact, the

customer results measure is assigned 20% of the overall

scores in the European Foundation for Quality Manage-

ment (EFQM) model (EFQM, 2004), the highest

percentage for any criterion in the model. Several

researchers including Filiatrault et al. (1996), Grandzol

(1998) and Parzinger and Nath (2000) found a positive

relationship between TQM practices and customer

results. A study by Das et al. (2000) reported a positive

relationship between TQM practices and customer

satisfaction performance. Timeliness of delivery was

also found to be a significant outcome of TQM practices

by Anderson and Sohal (1999). Hence we have the

following hypothesis.


H2. TQM has a direct, positive effect on customer

results.

2.3. The effect of TQM on organizational

effectiveness

A commitment to quality over cost and schedule

results in improvements in cost and delivery perfor-

mance in the long run (Ferdows and Demeyer, 1990).

TQM practices not only help to improve the quality of

products but also reduce scrap, rework, and the need for

buffer stock by establishing a stable production process.

These in turn minimize production costs and throughput

time. Consequently, reduction in throughput time

enables a company to improve delivery performance.

TQM practices can also help improve flexibility. For

instance, workforce flexibility, where employees are

trained in multiple skills and are empowered to make

decisions, can enable a company to make changes in

production volume without having any negative effects

on production cost (Ahmad and Schroeder, 2002).

Through continuous improvement, not only errors and

defects can be prevented but also product cycle times

can be reduced, thereby improving productivity (Huang

and Lin, 2002). Improvements in manufacturing cycle

times have been well documented in one company that

implemented TQM. These improvements were partly

attributed to teams’ focus on their internal customers

and their knowledge of these customers’ requirements.

These teams’ active involvement equipped them with

the knowledge of what the production priorities were

and how each process fit into the overall production

process (McAdam and Bannister, 2001).

A study by the US Government Accounting Office

(GAO, 1991) examined the effect of TQM practices on

the performance of 20 US companies that won the

MBNQA. The study found that these practices had a

strong relationship with quality and productivity,

among others. Similarly, Carter and Narasimhan

(1994) argued that TQM’s emphasis on process

improvement contributed to productivity increases

through effective utilization of people and processes.

Deming (1986) also suggested that TQM could be

effective in achieving organizational effectiveness. That

is, TQM could minimize total costs through sole

sourcing. By concentrating on a small number of

suppliers, providing them with the needed training and

technology, and monitoring their performance, varia-

bility in suppliers’ products could be reduced, improv-

ing product quality; costs of delay and rework could

also be minimized. Thus, TQM practices could be

implemented to achieve superior supplier performance.

According to Anderson et al. (1998), several TQM

practices including training, information, and supplier

management had positive relationships with ‘‘opera-

tional results’’ measured by logistics cost performance,

effectiveness and efficiency of transaction processes,

and order cycle time. These findings were supported

by Tata et al. (2000), who found that the effect of

TQM practices on operational results were positive.

Thus we have the following hypothesis.

H3. TQM has a direct, positive effect on organizational

effectiveness.

2.4. The effect of TQM on financial and market

results

According to Buzzell and Gale (1987), financial

performance is an important measure of TQM out-

comes. This is consistent with Deming’s (1986)

argument that quality improvement leads to elimination

of waste, reduction of costs, and improved financial

performance. Juran (1992) contended that market share

was the ultimate test of the results of TQM

implementation since TQM led to higher sales.

Anectodal evidence also suggests that investments in

quality can lead to improvements in sales, return on

assets (ROA), and market share (Sankar, 1995).

However, some of the previous studies found no

relationship between TQM and financial and market

results measures. For instance, Curkovic et al. (2000b)

found no relationship between leadership, employee

empowerment, cross-functional quality teams and

performance measures such as ROA, return on

investment (ROI), and market share growth. Some

of the other studies that reported no linkages between

TQM and financial results included those by Cunning-

ham and Ho (1996) and Davis (1997). However, the

literature review conducted for this study indicated

that most of the studies found a positive relationship

between TQM practices and measures of financial and

market results. For instance, Curkovic et al. (2000b)

and Wilson and Collier (2000) did report a number of

such positive relationships. Mohrman et al. (1995) also

found that TQM practices had a positive effect on

profitability and competitiveness. Similarly, the find-

ings of a study by Anderson and Sohal (1999)

suggested that the effect of TQM practices on overall

competitiveness, sales, and market share was positive.

A more recent study by Hansson and Eriksson (2002)

showed that a sample of quality award-winning

Swedish companies that implemented TQM success-

fully had better financial performance than other


companies of comparable size and their biggest

competitors. Several other studies that indicated a

positive relationship between TQM and financial

results included those by Hendricks and Singhal

(1997), Handfield et al. (1998) and Tena et al. (2001).

Therefore we have the following hypothesis.

H4. TQM has a direct, positive effect on financial and

market results.

2.5. The effect of human resource results on

customer results

The effect of employee fulfillment on customer

satisfaction is implicit in the Deming management

method, which views customer satisfaction as a natural

consequence of pride of workmanship. Pride of

workmanship is determined by how capable the

employees feel of delivering quality products and

services to customers (Anderson et al., 1994a).

Many service companies have also realized that

there is a strong relationship between employee per-

formance and customer satisfaction (Hartline and

Ferrell, 1996). As a result, the potential role of job

satisfaction in improving various work-related out-

comes (Hellman, 1997), and especially customer

satisfaction (e.g., Schneider and Bowen, 1985; Hallo-

well et al., 1996; Hartline and Ferrell, 1996), has drawn

many researchers’ interest. Hoffman and Ingram

(1992) found a positive relationship between job

satisfaction and customer-related behaviors. Other

studies reported both direct (e.g., Testa et al., 1998)

and indirect (e.g., Hallowell et al., 1996) relationships

between job satisfaction and customer satisfaction.

A number of studies (e.g., Heskett et al., 1994;

Rucci et al., 1998; Harrison and Freeman, 1999)

related employee results to customer satisfaction and

loyalty, and business performance. This cause–effect

relationship has been described as the ‘‘service-profit’’

chain by these studies and has been ascribed to

successful human resource practices, which are an

integral part of the TQM philosophy. A similar cause–

effect relationship can also be seen in the model

presented in Fig. 1, where human results directly affect

customer results, which in turn directly affect financial

and market results.

Retford (1998) emphasized the importance of

integrating customer results with employee results.

She argued that if employee satisfaction measures

and customer measures were designed in unison so that

they accounted for the interaction of customers and

employees, customer defections could be prevented.

For instance, employee retention, one of the measures

of employee results, could affect customer results

because experienced employees are more knowledge-

able about their organizations’ goals and the customers’

requirements (Schneider and Bowen, 1985). Hence, the

next hypothesis is as follows.

H5. Human resource results have a direct, positive

effect on customer results.

2.6. The effect of human resource results on

organizational effectiveness

The HRM and TQM literature have become

increasingly interlinked. This is partly due to the use

of similar theoretical concepts and assumptions such as

leadership, employee involvement and motivation,

teamwork, and training, and partly because both

HRM and TQM are being linked to business

performance in theory and practice (Boselie and van

der Wiele, 2002). Most of the previous studies (e.g.,

Huselid, 1995; Delaney and Huselid, 1996; Tsui et al.,

1997) focused on the relationship between human

resource practices and performance outcomes and

paid little attention to the effects of human resource

results on other performance measures. Some of these

studies (e.g., U.S. Department of Labor, 1993; Youndt

et al., 1996) found that human resource practices such

as selection and training contributed to productivity

and company performance. Ryan et al. (1996) also

argued that if the employees in a unit shared positive

attitudes and valued cooperation and collaboration,

productivity could be improved.

Although there is no extensive empirical evidence on

the effect of human resource results on various

performance outcomes, several studies did examine

such relationships. For instance, Paauwe and Richard-

son (1997) hypothesized that human resource activities

affected human resource results such as turnover and

absenteeism, which in turn contributed to productivity

and product or service quality. In addition, a report

prepared for the Canadian Policy Research Networks

suggested that workplace practices such as job design,

employee involvement, and training, which are strongly

emphasized by TQM, had a favorable impact on

employee satisfaction, absenteeism, tardiness, commit-

ment, motivation, effort, and performance, which in

turn had a positive effect on company performance, as

well as productivity and competitiveness (Anonymous,

2002). In addition, an empirical study by Grandzol

(1998) found that employee fulfillment had a positive

impact on ‘‘operational results’’ measured by produc-


tivity, cycle time, scrap/waste, energy/efficiency, and

material usage. Koys (2001) suggested that employee

retention would improve organizational effectiveness

in terms of lower costs, because a low turnover would

result in less hiring and training activities. Arthur (1994)

found that employee retention could also help improve

productivity. Thus we have the following hypothesis.

H6. Human resource results have a direct, positive

effect on organizational effectiveness.

2.7. The effect of organizational effectiveness on

customer results

TQM is generally viewed as a process-oriented

approach to improving customer satisfaction by

offering goods and services of high quality (Mehra

et al., 2001). The production of high quality products

and services at a reasonable price has a direct effect on

how external customers perceive their purchase-

consumption experience (Gustafsson and Johnson,

2002). This level of quality can be attained through

improved business processes that reduce defects, costs

(Rust et al., 2002; Napolitano, 2003), as well as cycle

times and inventories (Napolitano, 2003), which

eventually improve customers’ perception of quality

and increase customer satisfaction (Rust et al., 2002;

Napolitano, 2003). Atkins et al. (2002) also argued that

customer value was created through lowest cost,

highest quality, fastest cycle time, and highest overall

customer satisfaction.

The impact of TQM implementation on various

performance outcomes has been documented in many

companies. Among these outcomes, organizational

effectiveness measures such as reduced cycle times,

higher quality, and increased productivity were reported

as contributing factors to increased customer satisfac-

tion (Tan et al., 1999). A simulation study by Lai et al.

(2001) also found a positive relationship between

shorter cycle times and customer satisfaction. However,

not many empirical studies examined the effect of

organizational effectiveness measures on customer

results. One such study was conducted by Anderson

et al. (1998) who found that the effect of operational

results on customer satisfaction was positive. Agus et al.

(2000) reported that product quality had a major effect

on customer satisfaction. In addition, Voss and Black-

mon (1994) found a significant link between quality-in-

use and customer satisfaction. Hence we have the

following hypothesis.

H7. Organizational effectiveness has a direct, positive

effect on customer results.

2.8. The effect of organizational effectiveness on

financial and market results

Internal quality can directly affect costs and revenues.

Making improvements to internal quality can result in

higher productivity, reduce internal costs and thus have a

direct, positive impact on profits (Gustafsson and

Johnson, 2002; Shetty, 1987). Even though some quality

improvements may concurrently lead to higher revenues

and lower costs, improvements focused on affecting

customer perception of quality usually increase profits

through revenue expansion and those focused on

streamlining internal processes increase profits through

cost reduction (Rust et al., 2002). Shetty (1987) found

that companies that improved the quality of their

products realized increases in market share by five or six

times faster than those companies that saw the quality of

their products decline. In addition, the market share of

these companies grew three times faster than the market

share of companies that had product quality levels

similar to those of their competitors.

Research conducted by Rogers et al. (1982) showed

that adjustment of organizational effectiveness mea-

sures such as order cycle time, variability of delivery

time, and communication time could help increase

profits. Other studies (e.g., Kim et al., 2002; Gunase-

karan, 2002) suggested that cycle time had a positive

effect on competitiveness. In addition, reduction of

cycle times and manufacturing costs, as well as

elimination of waste, could help improve productivity

and ROA (Omachonu and Ross, 1994).

Some of the previous empirical studies also examined

the relationship between measures of organizational

effectiveness and financial and market results. Studies on

the profit impact of marketing strategies (PIMS), where

the effects of various marketing strategies on financial

performance at over 500 corporations were analyzed,

revealed that there was a strong relationship between

product or service quality and financial indicators

(Buzzell and Gale, 1987). Curkovic et al. (2000c) also

found that quality had a positive effect on financial

and market performance measures such as market share,

ROI, and ROA. Thus we have the following hypothesis.

H8. Organizational effectiveness has a direct, positive

effect on financial and market results.

2.9. The effect of customer results on financial and

market results

Most of the previous studies that examined the

relationship between customer-related performance and


financial and market results chose customer satisfaction

as the main measure of customer-related performance.

However, some researchers (e.g., Crosby and Johnson,

2002; Wright and Snell, 2002) argued that it was not

only customer satisfaction that led to positive financial

results but customer retention as well. Although

marketing theory and practice suggest that companies

can improve their performance by satisfying their

customers, this relationship is still being debated

(Yeung et al., 2002). The general argument is that

customer satisfaction creates customer loyalty and

retention, which results in repeat purchases, growth in

sales, a reduction in operating costs, and an increase in

profits (Das et al., 2000; Yeung and Ennew, 2001).

Increased retention rates can increase profits (Fornell

and Wernerfelt, 1988; Reichheld and Sasser, 1990),

because the selling costs to existing customers are much

lower (Peters, 1987).

The PIMS studies also found a positive relationship

between customer satisfaction and market share

(Buzzell and Weirsema, 1981; Craig and Douglas,

1982). Other studies reported a significant positive

relationship between customer satisfaction and reven-

ues (e.g., Zeithaml et al., 1996; Rucci et al., 1998) and

profitability (e.g., Anderson et al., 1994b; Hallowell,

1996; Bernhardt et al., 2000). Filiatrault et al. (1996)

and Agus et al. (2000) also found a positive relationship

between customer satisfaction and financial results.

Therefore we have the following hypothesis.

H9. Customer results have a direct, positive effect on

financial and market results.

3. Contextual factors

The pioneers of quality such as Deming, Crosby

and Juran suggested that the quality management

principles were universally applicable. However, more

recently, other quality researchers (e.g., Dean and

Bowen, 1994; Sitkin et al., 1994) questioned this

argument suggesting that these principles could in fact

be context-dependent, which could render certain

TQM practices and tools inappropriate. Watson and

Korukonda (1995) also stated that there was no

empirical evidence to support the universal applic-

ability of TQM practices.

The context-dependent approach to administrative

innovations has also been discussed in the organiza-

tional theory literature. Administrative innovations are

concerned with either changing the structure of an

organization or its administrative processes and are

mainly related to the management of the organization

rather than its basic work activities (Damanpour, 1987).

Damanpour (1987) conducted a comparative analysis of

the relationships between six organizational factors

(functional differentiation, specialization, profession-

alism, administrative intensity, organizational size,

organizational slack) and several types of innovations

using data from public libraries located in northeastern

United States (US). His findings showed that these

factors had a significant effect on the adoption of admi-

nistrative innovations, although their effect on the adop-

tion of technological innovations was much greater.

In another study, Damanpour (1991) conducted a

meta-analysis of the relationships between 13 organiza-

tional attributes (mainly structural, process, resource,

and cultural variables) and organizational innovation.

An analysis of the effects of moderating variables on

these relationships showed that differences in organiza-

tional types such as industry, sector, structure, and

strategy could have different effects on the degree of

innovativeness. This was mainly attributed to different

environmental opportunities and threats that these

companies faced, providing support for a contingency

theory of organizational innovation.

Westphal et al. (1997) explored TQM in hospitals as

an administrative innovation that is open to various

interpretations and that can exhibit differences in

adoption across organizations. The authors suggested

that empirical evidence for the effects of TQM on

overall performance and knowledge of ideal form or

content of TQM programs were limited. Therefore, the

question of whether the institutionalization of TQM in

organizations should conform to normative forms of

adoption, or whether TQM should be customized to the

unique needs and capabilities of these organizations,

remained unanswered. According to institutional theory,

norms emerge based on the organizational performance

motives of early adopters exerting pressure on later

adopters to conform. Hence, Westphal et al. (1997)

argued that later adopters of TQM would imitate the early

adopters’ quality practices rather than customizing them

to their unique needs and capabilities. In addition, the

early adopters’ customization of these quality practices

would be expected to yield superior organizational

performance gains, whereas the later adopters’ con-

formity to normative TQM adoption would be negatively

associated with organizational performance benefits

(Westphal et al., 1997). These hypotheses were

empirically supported by the analysis conducted by

the authors. Thus, these studies provided evidence that

the implementation of administrative innovation such as

TQM and their effects on organizational performance

could be affected by contextual factors.


In the next section, we present a discussion of the

five contextual factors – three institutional factors and

two contingency factors – that will be used to test the

proposed model by drawing on institutional theory and

contingency theory. The propositions related to

institutional theory will be called institutional factors

and those related to contingency theory will be called

contingency factors.

3.1. Institutional factors

According to institutional theory, organizations

create structures to look legitimate to important

stakeholders. This is due in part to regulations,

procedures, and structures imposed on them by

environmental institutions. Organizations may be

forced to change their structures due to governmental

pressures, imitate the structures of other organizations

as a result of competitive pressures, or conform to

normative standards developed by such organizations

as accreditation companies and consumer organiza-

tions (Wagner et al., 2001). ISO registration, which is

one of the institutional factors in the current study, is

an accreditation process that seeks to standardize

systems for quality around the world. Thus, companies

need to conform to a number of normative standards to

obtain registration. However, since there is no

certification for TQM, there are no official guidelines

for implementation. In spite of this, companies

implementing TQM may imitate early adopters to

improve the quality of their products, services, and

processes in response to competitive pressures. As

suggested by Westphal et al. (1997), this imitation

would be expected to lead to similar TQM practices

across TQM implementers. As a result, TQM

implementers would differentiate themselves from

nonimplementers.

The last institutional factor analyzed, country of

origin, represents a cultural factor that may become

institutionalized at the country level (Homburg et al.,

1999). Different societies have different traits at the

regional or national level such as a ‘‘normative

institutional order’’, as well as unique cultural

characteristics and economic and industrial structures.

Therefore, the organizational practices of companies

that originate from different countries or regions may

diverge (Harzing and Sorge, 2003). This divergence

might also be witnessed in these companies’ approaches

toward the implementation of TQM practices.

Institutional theory also suggests that organizations

that conform to norms of acceptable practice can

achieve high levels of production efficiency and

effectiveness (DiMaggio and Powell, 1983; Carruthers

and Espeland, 1995). Hence, companies, for instance,

that implement TQM and are registered to ISO 9000

would be expected to have superior performance

compared to those companies that do not implement

TQM or are not ISO-registered.

3.2. Contingency factors

Contingency theory suggests that successful orga-

nizations choose structures and process characteristics

that ‘‘fit’’ to the degree of uncertainty in their

environment (Duncan, 1972; Miller, 1992). Contin-

gency factors that may affect the establishment of this

fit include both internal and external factors. Theorists

have used various constructs to operationalize internal

contingency factors, but these factors generally had

three dimensions in common: task variability, task

difficulty, and task interdependence (Gupta et al.,

1994). In the marketing literature, Homburg et al.

(1999) used differentiation and cost-leadership strat-

egy, and distribution and customer base as internal

contingency factors, and market growth, market-

related uncertainty, and technological turbulence as

external contingency factors. In health care quality

management area, Wagner et al. (2001) used con-

tingency factors such as centralization of decision-

making, formalization of regulations, and organiza-

tional size. Organizational size, used as an external

contingency factor by Gupta et al. (1994), is one of the

factors analyzed in the current study. The other

contingency factor included in this study is scope of

operations (i.e., domestic operating versus interna-

tional operating companies), which affects the degree

to which companies are exposed to uncertainty as a

result of the different environments they operate in.

Structural contingency theory is an extension of

contingency theory and attempts to explain context–

structure–performance relationships (Melan, 1998).

The theory suggests that organizations that can

establish a fit between organizational structure and

environmental uncertainty will achieve higher organi-

zational performance results (Schlevogt and Donald-

son, 1999; Ellis et al., 2002), while a misfit would have

a negative effect on organizational performance

(Donaldson, 2001). Within the context of contingency

propositions, using the practice of Reed et al. (1996),

this study assumes that it is fit that determines

organizational performance, and not the independent

effects of environmental uncertainty and TQM. The

propositions for each of the institutional and con-

tingency factors are discussed below.


3.3. Institutional propositions

3.3.1. TQM implementation

TQM has become a recognized philosophy in the US

since the 1980s as a result of the success of Japanese

companies with the implementation of TQM practices,

as well as the early success of several US companies

such as Motorola and Ford with this philosophy.

Consequently, many US companies increasingly imple-

mented TQM programs (Ahire et al., 1996a). As

previously mentioned, the literature is not in agreement

with the benefits of implementing TQM. In this study,

however, approximately 70% of the companies that

implemented TQM stated that their program was

successful whereas 14% stated that it was unsuccessful.

The other 16% did not respond, while the 3% did not

know the results of their program. Thus, a big

percentage of TQM implementers (TQM companies)

rated their programs as being successful.

One of the objectives of this study is to compare

TQM companies with companies that never imple-

mented a TQM program (non-TQM companies) using

the proposed model. The companies were classified

into two groups as TQM companies and non-TQM

companies based on their response to a question

included in the survey asking them whether they

implemented TQM. If they did implement TQM, the

companies were also asked to state the duration of their

implementation and whether they considered their

TQM program as being successful. However, since

non-TQM companies may still be implementing TQM

practices either as part of another continuous improve-

ment program or as part of their regular business

operations, the term ‘‘non-TQM company’’ only

suggests that these companies never implemented a

TQM program.

The implementation of TQM practices is expected

to be more rigorous in TQM companies than in non-

TQM companies, because TQM companies allocate

more resources for the implementation of these

practices and focus their efforts on their effective

implementation (Lascelles and Dale, 1990; Ahire et al.,

1996a; Brah et al., 2002). In addition, TQM companies

are generally expected to achieve better business

performance than non-TQM companies as a result of

implementing these TQM practices more rigorously

(Powell, 1995; Ahire et al., 1996a; Brah et al., 2002). In

fact, Hendricks and Singhal (1997) found that

companies that effectively implemented TQM

achieved better performance results than non-TQM

companies in terms of profitability, revenues, costs,

capital expenditure, and total assets. In addition to such

financial performance measures, this study will use a

broader range of business performance measures to

compare the two groups within the proposed TQM–

performance relationships model framework.

Proposition 1. TQM practices are different across

TQM companies and non-TQM companies.

Proposition 2. The structural model relationships are

different across TQM and non-TQM companies.

3.3.2. ISO 9000 registration

ISO 9000 can be considered to be a subset of TQM.

ISO 9000 mainly deals with quality management systems

for the design, development, purchasing, production,

installation, and servicing of products and services.

However, the eight TQM practices added to the 2000

version of ISO 9000 brought ISO 9000 and TQM closer

together than ever before (Goetsch and Davis, 2003).

Overall, the literature suggests that many ISO-registered

companies view the registration process as a prerequisite

to TQM implementation (Escanciano et al., 2001). Yusof

and Aspinwall (2000) argued that ISO registration

contributed to a company’s achievement of the ‘‘total

system’’ associated with TQM. Thus, ISO-registered

companies would be expected to have more effective

TQM practices in place than non-ISO-registered

companies as a result of their ISO 9000 efforts.

The literature is not in unanimous agreement with

the effects of ISO 9000 registration on organizational

performance. Some of the previous studies (e.g.,

Terziovski et al., 1997; Simmons and White, 1999;

Lima et al., 2000) found that ISO registration did not

necessarily improve companies’ performance. On the

other hand, according to the International Organization

for Standardization, ISO 9000 can increase customer

satisfaction, provide cost and risk-management bene-

fits, and result in improved competitiveness (Goetsch

and Davis, 2003). In fact, Rao et al. (1997a) found that

ISO-registered companies had better quality manage-

ment practices and quality results than those companies

that were neither ISO-registered nor interested in

obtaining registration. Ismail and Hashmi (1999) also

reported better performance for ISO-registered compa-

nies compared to non-ISO-registered companies. A

study by McAdam and McKeown (1999) found that

37% of the surveyed companies reported improve-

ments, such as increases in productivity and sales and

reductions in costs and customer complaints. Overall,

77% of the companies reported being pleased or very

pleased with ISO. Lee and Palmer (1999) also reported

improvements in performance as a result of ISO

registration. Thus we have the following proposition.


Proposition 3. TQM practices are different across

ISO-registered and non-ISO-registered companies.


different across ISO-registered and non-ISO-registered

companies.

3.3.3. Country of origin

Although several cross-country studies were con-

ducted, where the similarities and differences in TQM

practices and performance measures across countries

were analyzed, this is still an area of research in quality

management that needs to be explored further. The

results of these studies were inconsistent. For instance,

some of the studies found that TQM practices were

similar across the compared countries (e.g., Adam

et al., 1997; Rao et al., 1997b), whereas others reported

differences (e.g., Raghunathan et al., 1997; Tata et al.,

2000). Most of these empirical studies used data

collected from companies operating in different

countries. However, the data in the current study were

collected from local and foreign companies operating

in the same country (i.e., the US). In fact, studies

comparing the TQM practices and performance of local

and foreign companies operating in the host country

using organizational theory and a TQM–performance

relationships model are nearly non-existent.

The issue of convergence versus divergence of

various practices across companies with different

countries of origin has not yet been resolved in the

international management literature, regardless of

whether the companies compared were located in the

same country or in different countries. Researchers

supporting the convergence hypothesis (e.g., Tung,

1981; Mendenhall and Oddou, 1985) argued that global,

industrial, and economic pressures would outweigh

cultural factors, resulting in convergence of structures,

processes, and practices across companies with

different countries of origin. On the other hand,

researchers supporting the divergence hypothesis

contended that cultural differences played an important

role in shaping these structures and practices differently

(e.g., Whitley and England, 1977; Hofstede, 1983).

However, Child (1981) argued that there was evidence

in support of both the convergence and divergence

hypothesis, where convergence mostly applied to

macrolevel variables such as structure and technology,

and divergence applied more to microlevel variables

such as human behavior within companies.

The convergence hypothesis and institutional theory

are congruent in that they both suggest that external

forces will compel companies to adopt similar

practices. Chung et al. (2000) analyzed the control

practices of multinational companies (MNCs) operating

in Australia related to knowledge flows, product flows,

and capital flows. The authors reported that these

control practices were similar across MNCs, indicating

that they converged due to normative and mimetic

pressures as suggested by institutional theory. Rungtu-

sanatham et al. (2005) also found evidence for the

convergence hypothesis by comparing Deming man-

agement principles across companies located in several

different countries. This study also takes the position

that US companies and foreign companies operating in

the US will mimic each other’s TQM practices and

create similar structures to look legitimate to important

stakeholders. As a result, these companies will also be

expected to have similar business performance. Thus we

have the following proposition.

Proposition 5. TQM practices are similar across US-

owned and foreign-owned companies operating in the

US.


similar across US-owned and foreign-owned companies

operating in the US.

3.4. Contingency propositions

3.4.1. Company size

TQM was first developed by large Japanese

companies and subsequently adopted by large US

companies (Powell, 1995). As a result, much of the

literature focused on the implementation of TQM in

large companies (Ghobadian and Gallear, 1997).

However, companies with different sizes have distin-

guishing characteristics that may have different effects

on how TQM is implemented and how TQM contributes

to organizational performance. For instance, small and

medium-sized companies (SMCs) have flatter manage-

ment structures and higher flexibility than large

companies (McAdam and McKeown, 1999), more

customer orientation, less complexity and better

communication due to informal relationships (Cagliano

et al., 2001) and are more likely to use innovative work

practices (Osterman, 1994; Walley, 2000), which may

make the implementation of TQM easier. On the other

hand, large companies are more formalized, specia-

lized, and decentralized (Germain and Spears, 1999)

and have more abundant resources than SMCs that

allow them to undertake TQM activities (Ghobadian

and Gallear, 1997; van der Wiele and Brown, 1998).

However, since it is difficult to achieve major change in

large companies, these companies may be less willing


to undertake such change or may even give up on TQM

if problems arise early during implementation (Mohr-

man et al., 1995).

Large companies and SMCs also differ in terms of

the reasons why they implement TQM practices.

Although large companies implement these practices

due to corporate decision, company survival, and to

reduce costs, SMCs’ main goal is to meet customer

requirements. Accordingly, large companies emphasize

structural and organizational components of TQM,

such as training, feedback, and supplier management,

whereas SMCs focus on the soft sides of TQM such as

leadership and employee involvement (Sun and Cheng,

2002). A detailed analysis of the differences between

SMCs and large companies as they pertain to the design

and implementation of TQM is provided by Ghobadian

and Gallear (1997). These differences range from

structure, procedures and behavior to processes,

people, and contact.

There is also some evidence in the literature that

there are differences among large companies and SMCs

in terms of the benefits they obtain from TQM. For

instance, according to Hendricks and Singhal (2001),

small companies are more likely to realize greater

improvements in operating income and sales as a result

of implementing TQM practices. In addition, some

practices, such as employee participation, can be

implemented more successfully in smaller companies,

resulting in greater employee satisfaction (Manoo-

chehri, 1988). Overall, the literature suggests that the fit

of TQM practices and the TQM results achieved are

different in large companies and SMCs. Thus we have

the following proposition.

Proposition 7. The fit of TQM practices is similar

across small and medium-sized companies and differs

from the fit for large companies.


similar across small and medium-sized companies and

differ from those in large companies.

Note that, in this study, small companies were those

companies with less than 100 employees, medium-sized

companies included those with 101–500 employees,

and large companies had more than 500 employees.

3.4.2. Scope of operations

The extent to which companies operate in the global

marketplace (i.e., domestic versus international) may

have an effect on their TQM practices. However, no

studies were found that examined the effect of this

contingency factor on TQM practices and TQM–

performance relationships. Nonetheless, a somewhat

comparable study conducted by Das et al. (2000) used

international competition as a contingency factor.

Their study compared high involvement work prac-

tices and quality practices across three groups of North

American companies that faced low, medium, and high

levels of competition from Japanese companies, as well

as these practices’ effects on company performance and

customer satisfaction. The study found differences in

high involvement practices and quality practices across

these three groups. It also found differences across the

three groups in terms of the effect of quality practices on

customer satisfaction. However, the effect of customer

satisfaction on company performance was similar across

these groups. Even though the effect of high involvement

work practices on company performance was similar

across low and high competition conditions, this

relationship was nonsignificant for companies facing

medium level competition.

The current study is different from the Das et al.

(2000) study in that it compares companies that have

only domestic customers (domestic operating compa-

nies) to those that have customers worldwide (interna-

tional operating companies). International operating

companies are generally more exposed to new ideas and

practices than domestic operating companies and are

therefore in a better position to learn from the experiences

of similar plants and adopt new management techniques

more rapidly. This learning also comes as a result of the

intense competitive pressures that these companies face

from their foreign competitors to implement these

techniques (Osterman, 1994). For instance, a study

conducted by Gonzalez-Benito and Spring (2000) found

that international companies were more likely to

implement just-in-time purchasing practices. Bayo-

Moriones and Merino-Diaz de Cerio (2003) argued that

companies that belonged to a multinational group gene-

rally positioned their quality departments at a higher level

in the organizational structure, which suggested that the

level of implementation of TQM practices at these

companies was probably greater.

The HRM literature also suggests that companies

that have international presence have superior manage-

ment practices such as employee relations, recruitment,

and the use of innovative human resource practices

compared to domestic operating companies (Chambers

et al., 1998; Holbeche, 1999; Hiltrop, 2002). There are a

number of reasons for the differences in human resource

practices across these companies. For instance, inter-

national companies have to deal with a greater range of

complex issues such as the coordination of interna-

tional training activities, relocation of expatriates, and


adjustment of pay policies to the regulations of

different countries (Hiltrop, 2002). Data collected

from Chinese and Slovakian domestic and global

companies also showed that companies that had global

presence were more market-oriented in their emphasis

on training and allocated more resources for sales

training (Honeycutt et al., 1999). Since international

operating companies allocate more resources for the

effective implementation of their various TQM

practices, these investments in quality would be

expected to lead to higher levels of performance in

these companies (Das et al., 2000).

Proposition 9. The fit of TQM practices is different

across domestic operating and international operating

companies.


different across domestic operating and international

operating companies.

4. Methodology

4.1. Measurement instrument

The initial measurement instrument was created

using an extensive review of the literature. Most of the

items were adopted from the measurement instruments

of previous TQM studies such as Saraph et al. (1989),

Flynn et al. (1994) and Samson and Terziovski (1999)

Table 3

A profile of the respondents

Industries (SIC codes) Chemicals a

Fabricated m

Industrial an

Electronic a

Transportati

Measure, an

Wholesale t

Wholesale t

Business se

Engineering

Job titles Vice preside

manager: 8,

Site’s sales (in millions of dollars) 0–1: 5, 2–1

101–500: 50

Unspecified

Number of employees at the site 0–20: 17, 2

1001–2500:

Number of hours of continuous

improvement-related training received

by an average employee

0–10: 173,

Over 50: 4,

and supplemented by the general quality management

literature. Some items that were not covered sufficiently

in the literature were also added using the 2002

MBNQA criteria (NIST, 2002). A similar practice was

also used by Black and Porter (1996) who supplemented

the 1992 MBNQA items with issues in the TQM

literature that were not adequately covered in the

MBNQA. The measurement instrument was then tested

and refined based on the feedback of several companies’

general managers, quality experts, and Executive MBA

students at a major public university. The final

instrument had 114 items measuring the TQM construct

and 19 items measuring the four performance variables.

A 1–7 Likert scale was used for the items that measured

the TQM construct, where 1 was strongly disagree and 7

was strongly agree. Regarding the performance items,

the respondents were asked to rate the level of their

site’s performance during the past 3 years compared that

of their major industry competitors. A 1–7 Likert scale

was used for these items, where 1 was below average

and 7 was above average.

4.2. Sample

The instrument was administered to 2000 manufac-

turing and service companies (SIC codes 28, 34–38,

50, 51, 73, 87) randomly selected from the American

Society for Quality mailing list. One key informant

from each organization who was deemed to be

nd allied products (28): 18

etal products (34): 86

d commercial machinery and computer equipment (35): 15

nd other electric equipment (36): 75

on equipment (37): 12

alyze and construction industries (38): 14

rade—durable goods (50): 19

rade—non-durable goods (51): 16

rvices (73): 15

, accounting, research management and related services (87): 16

nt: 20, general manager: 5, quality manager: 143, other type of

engineer: 41, coordinator: 14, director: 32, supervisor: 7, others: 16

0: 57, 11–20: 39, 21–50: 50, 51–100: 36

, 501–1000: 16, over 1000: 18

: 15

1–100: 85, 101–500: 102, 501–1000: 49

19, 2501–5000: 7, over 5000: 7

11–20: 45, 21–30: 15, 31–40: 22, 41–50: 4

do not know: 13, unspecified: 10


knowledgeable about the issues discussed in the survey

was identified. These informants included the vice

president, general manager, quality manager, engineer,

coordinator, director, and supervisor. Six of the surveys

were returned as undeliverable, and within 1 month of

mailing, 302 completed surveys were returned. After

eliminating those surveys with missing data, 286 usable

surveys remained.

To test for nonresponse bias, the data were split into

two groups, where the surveys received late (90)

represented the nonrespondents and those received

early (196) represented the respondents. Then t-tests

were conducted on the two groups’ mean responses to

ten randomly selected questions (Armstrong and

Overton, 1977), and the results showed that the two

groups were identical. The two groups were also not

significantly different in terms of demographic vari-

ables such as sales, number of employees, unionization

Table 4

Summary of goodness-of-fit statistics for CFA of model constructs

Model constructs and their indicators x2 d.f

TQM 57.58 14

Leadership

Strategic planning

Customer focus

Information and analysis

Human resource management

Process management

Supplier management

Human resource results 8.20 2

Employee turnover

Employee absenteeism

Number of employee suggestions

Employee job performance

Customer results 2.87 2

Customer retention

Reliability and timely delivery of products/services

Personalized service

Value for the money spent

Organizational effectiveness 32.38 9

Cost

Product/service quality

Productivity

Cycle times

Number of errors or defects

Supplier performance

Financial and market results 15.40 5

Market share

Profit

Return on total assets

Overall competitive position

Number of successful new product/service introductions

* This factor loading was significant at p < 0.01. All other factor loading

(Ahire and Dreyfus, 2000), and ISO 9000 registration.

In addition, a multiple group analysis was conducted,

which showed that that the proposed model was

equivalent across respondents and nonrespondents

(Curkovic et al., 2000a). These tests showed that there

was no nonresponse bias in the data. Table 3 provides

a descriptive summary of the respondents.

4.3. Scale reliability and validity

The corresponding items of each of the seven TQM

practices and those of the four performance measures

were parceled to reduce them to a manageable level and

to meet sample size requirements for multiple group

analysis (Hall et al., 1999). A parcel is simply the

average of responses on items corresponding to an

indicator. However, before the items constituting each

TQM practice were parceled, they were screened by

. x2/d.f. p-Value CFI SRMR Factor

loading

Cronbach’s

alpha

4.11 0.0000 0.95 0.035 0.94

0.81 0.78

0.88 0.90

0.88 0.85

0.87 0.88

0.81 0.76

0.83 0.86

0.80 0.77

4.10 0.0646 0.93 0.075 0.72

0.75

0.84

0.29

0.29

1.44 0.2377 1.00 0.018 0.82

0.72

0.75

0.54

0.70

3.60 0.0000 0.92 0.074 0.75

0.31

0.75

0.87

0.69

0.28*

0.62

3.08 0.12 0.93 0.059 0.87

0.75

0.88

0.89

0.80

0.45

s were significant at p < 0.001.


conducting a confirmatory factor analysis (CFA) for

each TQM practice to determine whether they indeed

measured their assigned practices. All the items had

statistically significant factor loadings on their assigned

TQM practices and were therefore retained in the

model. Then the unidimensionality and reliability of the

scales were analyzed before their convergent validity,

discriminant validity, and criterion-related validity were

assessed (Anderson and Gerbing, 1982). EQS 6.1 for

Windows was used for the following analyses.

4.3.1. Unidimensionality analysis

The unidimensionality of the TQM construct and the

four performance measures was analyzed using CFA. In

the SEM literature, a comparative fit index (CFI) cutoff

value of 0.90 (e.g., Bentler and Bonnet, 1980; Kline,

1998) or ‘‘close to’’ 0.95 (Hu and Bentler, 1999), and a

standardized root mean square residual (SRMR) value

of less than 0.08 (Hu and Bentler, 1998, 1999) have

been recommended for adequate model fit. Table 4

indicates that the CFI values ranged from 0.92 to 1.00,

and the SRMR values ranged from 0.018 to 0.075,

suggesting that all the constructs were unidimensional.

4.3.2. Reliability analysis

The reliability of the constructs was assessed using

Cronbach’s alpha (Cronbach, 1951). Alpha values equal

to or greater than 0.70 indicate high construct reliability

(O’Leary-Kelly and Vokurka, 1998). The alpha values

Table 5

Discriminant validity analysis

Construct scale pairs Unconstrained

x2 d.f.

TQM

Human resource results 295.66 43




Human resource results




Customer results



Organizational effectiveness


* p < 0.001.** p < 0.005.

*** p < 0.01.

for the seven TQM practices ranged from 0.76 to 0.90

(see Table 4), yielding an overall reliability of 0.94 for

the TQM construct, and the alpha values for the four

performance measures ranged from 0.72 to 0.87. These

results suggested that all constructs were highly

reliable. In no case would any of these constructs’

reliabilities increase substantially if items were to be

deleted from them.

4.3.3. Convergent validity analysis

Convergent validity is defined as ‘‘the degree to

which two or more attempts to measure the same

concept ... are in agreement’’ (Bagozzi and Phillips,

1982, p. 468). According to Bagozzi et al. (1991), CFA

can be used to assess convergent validity. The authors

suggested that if all the factor loadings of indicators on

their constructs were significant, convergent validity

was attained. Table 4 shows that the factor loadings

ranged from 0.28 to 0.89 and were all statistically

significant, indicating strong convergent validity.

4.3.4. Discriminant validity analysis

Discriminant validity measures the degree to which

a construct and its indicators are different from

another construct and its indicators. Discriminant

validity can be assessed by conducting a series of x2

difference tests between nested CFA models for all

pairs of constructs. CFA is run on each pair of

constructs, where the two constructs are allowed to

Constrained Dx2

x2 d.f.

315.91 44 20.25*

201.52 44 11.98*

333.39 65 56.05*

293.82 54 58.44*

155.24 20 9.17**

313.63 35 47.86*

309.91 27 48.88*

193.99 35 68.89*

179.55 27 24.09*

204.77 44 7.63***


correlate freely (called the unconstrained model). The

x2 obtained from this model is subtracted from the x2

obtained from another CFA run, where the correlation

between the two constructs is constrained to 1 (the

constrained model) (Bagozzi et al., 1991). Table 5 lists

the x2 for the constrained and unconstrained models.

The table shows that the x2 difference tests between

all pairs of constructs are significant, suggesting

strong discriminant validity (Bagozzi et al., 1991).

4.3.5. Criterion-related validity analysis

Criterion-related validity evaluates the extent to

which items in a construct scale are correlated with an

external criterion (Nunnally, 1978). In this study, the

TQM construct is the predictor and the four perfor-

mance measures are the relevant criteria. The bivariate

correlations between TQM and human resource results,

customer results, organizational effectiveness, and

financial and market results were 0.49, 0.61, 0.60,

and 0.50, respectively. These correlations were statis-

tically significant at p < 0.001, indicating strong

criterion-related validity.

Based on the above analyses, the reliability and

validity of all scales were established. In addition, the

assumptions of multivariate analysis including normal-

ity, linearity, multicollinearity, and singularity were

tested for the variables used in the proposed model. The

results showed that there were no statistically significant

violations of these assumptions.

Table 6

Goodness-of-fit indices for structural path model analyses using the full sa

Contextual factor Subgroup n x2 d

All data 286 139.90 3

TQM implementation TQM 151 83.81 3

Non-TQM 135 112.27 3

ISO registration ISO 165 104.22 3

Non-ISO 121 79.44 3

Country of originb US 183 91.18 3

Non-US 101 81.07 3

Company size Small (<100 employees) 102 82.07 3

Medium (101–500 employees) 102 86.38 3

Large (>500 employees) 82 55.05 3

Scope of operationsb International operating 190 100.45 3

Domestic operating 94 67.64 3

a The number of free parameters to be estimated was 27.b The sum of the sample sizes for subgroups within these contextual factor

one or more demographic questions and were thus excluded from the analc The computed power for these subgroups was equal to or greater than 0

subgroups, power was greater than 0.80 at a = 0.05 and RMSEA null hypoth

model fit as suggested by Browne and Cudeck (1993) and MacCallum et a

5. Results

5.1. Structural path model analyses for the full

sample and subgroup samples

Before testing the proposed model in Fig. 1 using the

full sample and each of the subgroup samples, two of

the recommended approaches in the SEM literature

were used to test whether sample size requirements

were met. These included the number of cases (n) per

free parameter (t) (i.e., the n:t ratio) rule and power

analysis. When the number of cases per free parameter

rule is used, Bentler (1989) recommends a 5:1 ratio as

an ‘‘over-simplified guideline’’, and Bollen (1989)

argues that using ‘‘at least several cases per free

parameter’’ would be a useful suggestion since there is

‘‘no hard and fast rule’’ (Marsh et al., 1998). Table 6

shows that there are indeed several cases for each of the

27 free parameters estimated in the model. The ratios

ranged from 3.04 to 10.59, and most of them were either

close to or greater than 5. In addition, power analysis

was conducted for each of the structural path models

shown in Table 6 using the framework presented by

MacCallum et al. (1996). First, a test of not-close fit was

carried out for each model. The root-mean square error

of approximation (RMSEA), a measure of model

residuals, is used in conducting this test. Since the upper

bound of the RMSEA confidence interval for all of the

models was below 0.10, the hypothesis of not-close

mple and subgroup samples

.f. x2/d.f. p-Value CFI SRMR RMSEA n:t ratioa Power

9 3.59 0.00000 0.95 0.031 0.039 10.59 1.00

9 2.15 0.00004 0.95 0.038 0.040 5.59 0.97

9 2.88 0.00000 0.92 0.047 0.050 5.00 0.87

9 2.67 0.00000 0.95 0.031 0.043 6.11 0.97

9 2.04 0.00014 0.94 0.047 0.049 4.48 0.83

9 2.34 0.00000 0.95 0.035 0.039 6.78 0.99

9 2.08 0.00009 0.92 0.044 0.041 3.74 0.81

9 2.10 0.00007 0.93 0.049 0.041 3.78 0.82

9 2.21 0.00002 0.95 0.037 0.040 3.78 0.83

9 1.41 0.04569 0.96 0.036 0.042 3.04 0.80c

9 2.58 0.00000 0.95 0.035 0.043 7.04 0.99

9 1.73 0.00300 0.92 0.042 0.047 3.48 0.83c

s did not add up to 286 since some of the respondents did not respond to

ysis.

.80 at a = 0.10 and RMSEA null hypothesis value = 0.10. For all other

esis value = 0.10 (values above 0.10 for RMSEA would indicate a poor

l. (1996)).


fit could be rejected (MacCallum et al., 1996). Thus, it

could be inferred that none of the models had a poor

fit. The power value for the test of not-close fit for

each model was computed using the SAS program

created by MacCallum et al. (1996) and has been listed

in Table 6. Since all the values were equal to or greater

than 0.80 (MacCallum et al., 1996), all models had

adequate power.

Furthermore, to minimize the effect of sample size

in assessing model adequacy, CFI and SRMR were

used to assess model fit in addition to the x2 signi-

ficance test, because CFI and SRMR are relatively

unaffected by sample size (Hu and Bentler, 1998).

Table 6 shows that the CFI values for subgroups

ranged from 0.92 to 0.96, and the SRMR values ranged

from 0.031 to 0.049, indicating adequate model fits.

To save space, parameter estimates including the factor

loadings of TQM practices on the TQM construct, path

coefficients for the structural paths, and the amount

of explained variance (R2 values) for the dependent

variables are shown only for the full sample in Fig. 1.

All the hypotheses except H4 and H5 were statistically

significant at p < 0.001. The R2 values for the four

performance measures (23.7%, 47.5%, 40.5% 43.2%)

were either greater than or comparable to those

reported by other quality management studies (e.g., see

Flynn et al. (1995) and Pannirselvam and Ferguson

(2001)).

5.2. Multiple group analyses to test the propositions

In Section 5.1, the testing of the proposed model

involved the use of single samples. When the researcher’s

goal is to determine whether the components of the

measurement model and the structural model are inva-

riant across multiple samples, multiple group analysis is

used. Multiple group analysis is needed for direct

comparisons of particular model parameters across sub-

groups. In multiple group analysis, the sets of parameters

analyzed to determine subgroup invariance depend on

Table 7

Goodness-of-fit indices for multiple group analyses

Contextual factor x2 d.f. x2/d.f. p-Value

TQM implementation 232.41 93 2.50 0.00000

ISO registration 226.31 93 2.43 0.00000

Country of origin 188.81 93 2.03 0.00000

Company size 279.89 147 1.90 0.00000

Scope of operations 171.04 93 1.84 0.00000

a The number of free parameters to be estimated for the multiple group anal

the other four analyses was 38.b a = 0.05 and the null hypothesis value for RMSEA = 0.10 for all powe

the model and hypotheses to be tested and typically

include factor loadings, structural paths, factor variances/

covariances, factor residuals, and error variances/

covariances (Byrne, 1994). In the current analysis, factor

loadings, and structural paths were of interest based on

the proposed model and hypotheses and therefore

equality constraints were imposed only on these

parameters. EQS estimates these parameters simulta-

neously to get ‘‘efficient estimates’’. Since EQS tests

equality constraints multivariately rather than univari-

ately based on the Lagrange multiplier (LM) test, there is

no need to compare a series of restrictive versus

nonrestrictive models to detect where noninvariance lies

in the model. As a result, it is not required to test for the

measurement model’s equality first before testing the

structural model (Byrne, 1994).

Invariance testing for the subgroups of each

contextual factor was conducted separately. EQS was

run for the subgroups of each contextual factor by setting

the parameters for factor loadings and structural paths

equal across subgroups. The EQS output provides a

LM x2 associated with each constraint. The probability

value for each LM x2 can be checked to find out whether

any of the tests are statistically significant. A probability

value greater than 0.05 indicates that the hypothesized

equality of factor loadings and structural paths holds

(Byrne, 1994).

The results are shown in Tables 7 and 8. Table 7

indicates that the n:t ratios (ranging from 4.40 to 7.53)

and power values (ranging from 0.96 to 0.99) were high,

suggesting that sample size requirements were met. It

also shows that the CFI values ranged from 0.93 to 0.95,

and the SRMR values ranged from 0.040 to 0.055,

suggesting adequate model fits. The results of factor

loading invariance tests were used to determine whether

the seven TQM practices were invariant across

subgroups (addressing the odd-numbered propositions).

These results showed that the probability value

associated with each LM x2 exceeded 0.05, indicating

that all of the seven practices were invariant across the

CFI SRMR RMSEA n n:t ratioa Powerb

0.93 0.044 0.055 286 7.53 0.99

0.94 0.054 0.060 286 7.53 0.98

0.94 0.055 0.063 284 7.47 0.96

0.94 0.051 0.050 286 4.40 0.99

0.95 0.040 0.061 284 7.47 0.97

ysis of the three subgroups of company size was 65 and that for each of

r analyses.


Tab

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subgroups of each contextual factor. Table 8 shows

the results of structural path invariance tests that were

used to evaluate whether the structural model relation-

ships were invariant across subgroups (addressing the

even-numbered propositions). These results provided

support for the invariance of most of the constrained

model parameters across subgroups within each

institutional and contingency factor. As can be seen

from Table 8, all the structural paths were invariant

across the subgroups of both TQM implementation and

ISO registration. The country of origin factor had two

noninvariant paths (although one of the paths was

nonsignificant); company size and scope of operations

each had one noninvariant path.

5.3. Summary of results

The results of structural path model analyses using

each sample showed that the data had a good fit to the

proposed model and thus provided support for the

system of relationships among TQM and business

performance measures. The seven TQM practices and

all the hypotheses except H4 and H5 were statistically

significant. TQM had a significant direct effect on all

measures except financial and market results. However,

TQM did have a significant indirect effect on financial

and market results through the mediating effects of the

other three measures.

The multiple group analyses results showed that there

were not many statistically significant differences across

the subgroups of each institutional and contingency

factor. This provided more support for the universal

applicability of the TQM practices and their effects on

performance rather than the context-dependent argu-

ment. This support was valid at least for the contextual

factors analyzed in this study. Propositions 1–4 were not

supported in that all the TQM practices and structural

model relationships were similar across TQM and non-

TQM companies, as well as across ISO-registered and

non-ISO-registered companies.

The study’s results largely supported Propositions 5

and 6 indicating that US and non-US companies did not

have statistically significant differences except H5 and

H8. In partial support of Proposition 7, all the TQM

practices were found to be similar across small and

medium-sized companies. However, contrary to this

proposition, these practices were also found to be similar

across SMCs and large companies. Proposition 8 was

partly supported, because all the structural model

relationships except the effect of TQM on financial

and market results were similar across small and

medium-sized companies. However, since most of these


relationships were also similar across SMCs and large

companies, this proposition was partly not supported.

Overall, the results showed that large companies and

SMCs were similar in terms of the fit of their TQM

practices and the structural model relationships. Finally,

the fit of all the TQM practices was similar across

domestic and international operating companies, which

did not provide support for Proposition 9. Only H3 was

different across these companies, providing minimal

support for Proposition 10.

6. Discussion and study implications

The synergies among TQM and performance

measures in the tested model provide support for

Deming’s (1982) quality chain reaction theory, which

states that focus on quality will lead to outcomes such

as employee and customer satisfaction, efficiency, and

profitability. One of the contributions of this study is

that it uses institutional and contingency factors as

moderator variables providing extensions to this theory

and empirically tests the effects of these variables on

TQM–performance relationships using a model. Over-

all, the results suggest that the holistic implementation

of the seven TQM practices contributes to improved

performance similarly across subgroups of companies

within each institutional and contingency factor.

6.1. Managerial implications

By implementing these practices effectively,

managers can expect to realize improvements in all

of the four performance areas. However, improve-

ments in human resource results, customer results, and

organizational effectiveness would be more immedi-

ate than those in financial and market results. This

finding supports the argument that a long-term view

should be taken in implementing TQM and that TQM

initiatives should not be terminated if there are no

significant improvements in the bottom line in the

short-term. Managers can use the items constituting

TQM in this study to assess where their companies

stand with regard to the use of these TQM practices or

as a guideline in implementing them. In addition, they

can use the items constituting the four performance

measures as an audit tool to evaluate the results of

their TQM initiatives over time.

The similar model relationships between TQM

companies and non-TQM companies show that for a

company to be a TQM company, it does not have to

formally implement TQM. This result agrees with the

findings of Ahire et al. (1996a). There was also no

difference between ISO-registered companies and non-

ISO-registered companies. These results could be

explained by the fact that a large number of companies

responding to the survey had a number of other quality

initiatives such as kaizen, lean manufacturing, con-

straint management, Juran training, as well as other

quality initiatives with no formal name. Therefore, the

important question is how effectively these companies

are implementing the various components of TQM in

the absence of a TQM program. This finding has

managerial implications in that companies need to

decide whether significant resources and effort should

be allocated to the implementation of a TQM program

to achieve desired performance outcomes. Companies

that already have other quality initiatives in place have

to determine whether they will reap extra benefits by

implementing a separate TQM program. The results

suggest that similar performance outcomes can be

achieved by either undertaking other quality initiatives

or simply establishing organizational systems that

incorporate these TQM practices. Those companies

that already have quality initiatives other than TQM can

use the practices constituting TQM in this study as an

assessment tool to determine whether additional

practices could be incorporated into their existing

programs to cover the range of principles supported by

TQM. Such an assessment could significantly reduce

investment that would be required for a full-blown

TQM program. Thus, companies should align their

various quality initiatives to reduce spending, effort,

and duplication.

This study provides support for the convergence

hypothesis and indicates that the TQM practices of US

and non-US companies operating in the US are similar.

This finding should be useful to the managers of these

companies in planning and implementing the appro-

priate TQM practices. However, as suggested by the few

noninvariant structural model relationships across these

companies, they should expect to see different results in

some of the performance areas.

As far as the contingency propositions are con-

cerned, the results show that the fit of the TQM practices

and most of the structural model relationships produced

by this fit are similar across the subgroups of each

contingency factor. These results suggest that tailoring

that may be needed to implement TQM practices under

these contingencies is minimal. Although TQM

practices were first implemented in large companies,

this study shows that SMCs have come a long way in

employing the same practices and that they can benefit

similarly from the same concepts. Therefore, both large

companies and SMCs that already have these practices


in place would be a good benchmark for later

implementers. These findings support those of Ahire

and Golhar (1996) who reported that small companies

could implement TQM practices as effectively as large

companies and obtain high product quality.

Similarly, the fit of TQM practices and the structural

model relationships are similar across domestic and

international operating companies. This suggests that

domestic operating companies have developed com-

parable TQM practices. Even though learning and

adoption of new management techniques in interna-

tional companies may be faster, the fact that the TQM

philosophy has been in practice for a long time may

have narrowed the TQM knowledge gap between the

two subgroups.

6.2. Research implications

The results have implications for the applicability of

institutional theory and contingency theory to the

analyzed contexts. These results indicate that, to a great

extent, US and non-US companies are similar, which

provides support for the argument that institutional

theory is effectual in explaining the convergence of their

practices. However, as mentioned above, a few

structural model relationships were different across

these companies, suggesting different results in some of

the performance areas. Future studies should attempt to

identify the potential factors that may produce such

differences. The model used in this study can also be

tested by conducting cross-country studies. Such studies

would shed more light on whether the convergence

hypothesis also holds for the TQM practices and TQM–

performance relationships of companies operating across

different country boundaries.

The premise of the first two institutional propositions

was that TQM implementation and ISO registration

would distinguish companies from other companies in

terms of their TQM practices and the structural model

relationships. However, the fact that this premise has

not been supported suggests that the mimicry or

conformance involved in the implementation of TQM

practices transcends beyond TQM and ISO 9000

initiatives and should be explained by a more complex

set of regulations, procedures, and structures imposed

on companies by environmental institutions. Therefore,

future studies should incorporate other potential factors

as control variables into the analysis. Conducting case

studies would especially be useful in gathering the

extent of data needed for such an analysis.

In addition, the finding that the subgroups within the

two contingency factors, size and scope of operations,

do not have many differences indicates that these factors

are not significant for the implementation of TQM

practices. However, the fact that one structural relation-

ship for each of the two factors is noninvariant suggests

that not all the performance results can be expected to

be similar across subgroup companies within each

contingency factor. Therefore, companies should be

aware that some of the desired outcomes of TQM may

not be realized due to lack of fit and that a more

appropriate fit should be established based on compa-

nies’ unique characteristics. Overall, the results suggest

that the nature of TQM practices in companies with

different sizes and scopes of operations is not dictated

by their unique environments or characteristics as

suggested by contingency theory but rather by institu-

tional factors as suggested by institutional theory that

force them to imitate or conform. However, the analysis

does not show whether these different groups of

companies are achieving their potential performance

levels by adopting the same TQM practices. It could be

possible to attain higher levels of performance by

establishing practices with a more optimal fit. However,

this may be a difficult task since the pressure exerted by

institutional factors to conform and thus apply TQM

practices universally may deter companies from such

an undertaking.

6.3. Research limitations

This study also has some limitations. First, it relies

on the perceptions of the respondents to operationalize

the survey instrument. Although the survey participants

were asked to report their actual and not desired

responses, some of them may not have done so. This

may have introduced bias into the data, which could

bring up potential concerns regarding generalizability,

reliability, and validity. Therefore, it is important that

construct reliability and validity analyses be conducted

to see if such concerns are warranted. However,

although all the constructs were found to be reliable

and valid, the presence of bias in data might not be

completely ruled out.

In addition, the data on performance measures were

based on the respondents’ perceptions and not on hard

data. Objective measures of performance such as actual

financial performance could provide a better test of the

proposed hypotheses. Furthermore, the independent and

dependent constructs were measured using the same

survey instrument, which may have resulted in common

method variance and potential common method bias.

That is, the use of a single method results in the

confounding of method variance with trait variance,


which may bias the estimates of relationships among the

model constructs. However, this could be overcome

using multiple methods, which make it possible to

partition the observed variation between construct and

methods variance so that the correlations among the

constructs are not confounded. As a result, the accuracy

of population parameter estimates could be improved

(Doty and Glick, 1998). Thus, multiple methods should

be used in collecting data in future studies to make a

stronger case for the generalizability of findings.

Another potential limitation is the bias that may be

introduced into the data by the use of single informants.

Although the use of single informants is widespread in

operations management research, using multiple

informants produces better quality data (Hogarth,

1978; Hill, 1982) since it ‘‘reduces the correlation

between systematic error components, averages out

random error in individual responses, provides the

opportunity to analyze the impact of error sources, and

provides a method to correct for systematic error in

informants’ responses’’ (Bruggen et al., 2002, p. 471).

However, to alleviate the potential problems associated

with using single informants, accepted methodological

guidelines were followed. For instance, the measure-

ment scales and the survey instrument were created and

pre-tested to maximize the validity of the data to be

collected and the appropriate key informants were

identified by name and job title before the surveys were

sent out (Huber and Power, 1985).

Finally, this study does not establish causality

between the model variables, because it uses cross-

sectional data. One of the basic requirements of

establishing causality is temporal ordering (i.e., a cause

must be shown to unambiguously precede an effect),

which necessitates the use of longitudinal data (Bullock

et al., 1994).

7. Conclusions

Empirical evidence in this study suggests that a

context-dependent argument for TQM and its effects on

key organizational performance measures is not

warranted for the contextual factors analyzed. However,

findings suggest that although the same TQM practices

will mostly yield similar performance results across

subgroups of companies within each contextual factor,

some of these results can be different. Reasons for such

differences should be explored in future studies. The

model developed and tested in this study should also be

replicated using other contextual factors to make

stronger assertions about the effects of institutional

and contingency factors. This study’s findings on the

effects of company size are similar to the findings of

Benson et al. (1991) and Ahire and Golhar (1996) who

also reported that this contextual factor was insignif-

icant in explaining variation in TQM practices.

However, since the contextual factors and research

designs used were different across these studies,

replication studies should be conducted to shed more

light on the effects of contextual factors. In addition,

future research should examine theoretically plausible

moderating effects. For example, the relationship

between company size and TQM practices may be

moderated by unit level strategy.

Overall, this study contributes to the discussion in

the literature over whether a universal or a context-

dependent approach to TQM is needed by drawing on

institutional theory and contingency theory. So far, these

discussions have been scant and mainly prescriptive. The

use of organizational theory in this context has been

especially rare. This empirical study will hopefully lay

the groundwork for more such studies.

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