Description
The literature on quality contains numerous case studies of successful companies and descriptions of quality concepts and quality improvement programs. The purpose of this study is to determine the critical factors of total quality management.
Problems and Perspectives in Management, 4/2005 220
Critical Factors of Total Quality Management and Its Effect on
Performance in Health Care Industry: A Turkish Experience
Mustafa Dilber, Nizamettin Bayyurt, Selim Zaim, Mehves Tarim
Abstract
The literature on quality contains numerous case studies of successful companies and de-
scriptions of quality concepts and quality improvement programs. The purpose of this study is to
determine the critical factors of total quality management in the healthcare sector and to measure the
effect of critical factors of total quality management on business performance in small and medium
size hospitals in Turkey. The instrument used in this study was developed to identify critical factors
(areas) of total quality management in the hospital industry. The technique of canonical correlation
analysis is employed to investigate this relationship. To measure the eight dimensions of total quality
management, thirty items were measured by using a five point Likert scale, ranging from “very low”
to “very high”. Performance of the hospital was measured using by subjective measures based on
hospital administrators’ perception of how their organization performed relative to the competition.
Data analysis indicated a positive correlation between the performance of the hospital and the four
critical factors of quality management in Turkish healthcare industry.
Key words: Total quality management, Canonical correlation, Business performance.
Introduction
In today’s changing and developing global world, both service and manufacturing com-
panies are confronted with a challenging and increasingly competitive environment. This competi-
tion focuses on before and after sales services rather than products’ attributes and manufacturing
(Sivadas & Baker-Prewitt, 2000).
Today, service industries are dominant in developed countries and are among the fastest
growing sector even in the emerging countries. The service sector also approximately accounts for
60 or 70 percentage of the total worldwide GNP (Franklin, 1997). Due to the phenomenal growth
of the service sector in modern society, the importance of service management and marketing is
also expected to increase (Yavas, Bilgin & Shemwell, 1997), (Camison, 1996), (Bates, Bates,
Johnston, 2003). Since its emergence, the basic concept of service management has continued to
change. Two major changes in the concept include: (a) a shift from an interest in the internal con-
sequences of performance (e.g., internal efficiency – productivity of labor and profits) to an inter-
est in the external consequences (e.g., consumer behavior- customer satisfaction, loyalty), and (b)
a shift from focus on structure to a focus on process. Thus, marketers and managers now focus on
the process of service production and consumption as it governs consumer behavior in the service
industry where services are produced and consumed simultaneously with active participation of
the consumer.
The change in the conceptual paradigm within service marketing and management has
motivated many scholars to research the issues of service quality. Providing quality service is not
only the most important factor for consumer satisfaction, it is also the principal criterion that
measures the competitiveness of a service organization. Whereas the marketing textbooks stress
the four P’s of marketing, namely, product, place, promotion, and price, in a service business none
of these work very well without a Q for quality (Youssef & Bovaird, 1996).
Quality has become one of the most important factors in global competition today. Inten-
sifying global competition and increasing demand by customers for better quality have caused
more and more companies to realize that they will have to provide quality product and /or services
in order to successfully compete in the marketplace. To meet the challenge of this global revolu-
tion, many businesses have invested substantial resources in adapting and implementing total qual-
© Mustafa Dilber, Nizamettin Bayyurt, Selim Zaim, Mehves Tarim, 2005
Problems and Perspectives in Management, 4/2005 221
ity management (TQM) strategies. TQM is defined as an action plan to produce and deliver com-
modities or services, which are consistent with customers’ needs or requirements by better,
cheaper, faster, safer, easier processing than competitors with the participation of all employees
under top management leadership.
The role of total quality management is widely recognized as being a critical determinant
in the success and survival of an organization in today’s competitive environment. Any decline in
customer satisfaction due to poor service quality would be a matter of concern. Consumers are
becoming increasingly aware of rising standards in service quality, prompted by competitive
trends which have developed higher expectations (Yavas & Shemwell, 2001).
In recent years, one of the fastest growing industries in the service sector is the healthcare
industry. In the healthcare industry, all hospitals provide the same type of service, but they do not
provide the same quality of service. To achieve service excellence, hospitals must strive for zero
defects, retaining every customer that the company can profitably serve. Zero defects require con-
tinuous efforts to improve the quality of the service delivery system (Lim & Tang, 2000).
The purpose of this study is to determine the critical factors of total quality management
in the healthcare sector and to measure the effect of critical factors of total quality management on
business performance in small and medium size hospitals in Turkey.
Literature Review of Total Quality Management
Although the literature on total quality management includes a rich spectrum of research,
there is no consensus on the definition of quality. The notion of quality has been defined in differ-
ent ways by different authors. Gurus of the total quality management disciplines such as Garvin,
Juran, Crosby, Deming, Ishikawa and Feigenbaum defined the concept of quality and total quality
management in different ways. Garvin proposed a definition of quality in terms of the transcen-
dent, product based, user based, manufacturing based and value based approaches. Garvin also
identified eight attributes to measure product quality (Garvin, 1987). Juran defined quality as “fit-
ness for use”. Juran focused on a trilogy of quality planning, quality control, and quality improve-
ment (Mitra, 1987). Crosby defined quality as “conformance to requirements or specifications”
(Crosby, 1996). According to Crosby, requirements are based on customer needs. Crosby identi-
fied 14 steps for a zero defect quality improvement plan to achieve performance improvement.
According to Deming, quality is a predictable degree of uniformity and dependability, at low cost
and suited to the market. Deming also identified 14 principles of quality management to improve
productivity and performance of the organization (Deming, 1986). Ishikawa also emphasized im-
portance of total quality control to improve organizations’ performance. He contributed to this area
by using a cause and effect diagram (Ishikawa diagram) to diagnose quality problems (Mitra,
1987). Feigenbaum described the concept of organization- wide total quality control. Feigenbaum
was the first user of total quality control concept in the quality literature. He defined quality as
“the total composite product and service characteristics of marketing, engineering, manufacturing
and maintenance through which the product and service in use will meet the expectations by the
customer” (Mitra, 1987). Major common denominators of these quality improvement plans in-
clude management commitment, strategic approach to a quality system, quality measurement,
process improvement, education and training, and eliminating the causes of problems.
Total quality management is the culture of an organization committed to customer satis-
faction through continuous improvement. This culture varies both from one country to another and
between different industries, but has certain essential principles which can be implemented to se-
cure greater market share, increased profits, and reduced costs (Kanji & Wallace, 2000). Manage-
ment awareness of the importance of total quality management, alongside business process reengi-
neering and other continuous improvement techniques was stimulated by the benchmarking
movement to seek, study, implement and improve on best practices (Zairi & Youssef, 1995). The
commitment to continuous improvement historically originated in manufacturing firms; but spread
quickly to the service sector (e.g. teller transactions in banks, order processing in catalog firms,
etc.). Surveys point at the widespread interest and application of TQM:
Problems and Perspectives in Management, 4/2005 222
95% of manufacturing companies and 70% of service companies have used one form
or other of quality improvement programs and 55% of American executives and 70%
of Japanese executives use quality improvement information at least monthly (Olion
& Rynes, 1991), (Rigby, 1998).
An international survey of over 4000 managers in 15 countries indicated TQM usage
by approximately 60% in 1997 (Rigby, 1998). A Survey of TQM and continuous im-
provement programs indicates 12 common aspects: Committed leadership, adoption
and communication of TQM, closer customer relationships, benchmarking, increased
training, open organization, employee empowerment, zero defects mentality, flexible
manufacturing, process improvement, and measurement (Powel, 1995).
Furthermore, to determine critical factors of total quality management, various studies
have been carried out and different instruments were developed by individual researchers and in-
stitutions such as Malcolm Baldrige Award, EFQM (European Foundation For Quality Manage-
ment), and the Deming Prize Criteria. Based on these studies, a wide range of management issue,
techniques, approaches, and systematic empirical investigation have been generated.
Accordingly, Saraph, Benson & Schroder, (1989) developed 78 items, which were classi-
fied into eight critical factors to measure the performance of total quality management in an or-
ganization. These critical factors are: Role of divisional top management and quality policy, role
of the quality department, training, product and service design, supplier quality management,
process management, quality data and reporting, and employee relations.
Flynn, Schroeder & Sakakibara, (1994) developed another instrument to determine criti-
cal factors of total quality management. Flynn et al. identified seven quality factors. These are top
management support, quality information, process management, product design, workforce man-
agement, supplier involvement, and customer involvement. As it is seen, this instrument is very
similar to the preceding instrument that was developed by Saraph et al. (1989). Flynn, Schroder &
Sakakibara, (1995) measured the impact of total quality practices on quality performance and
competitive advantage.
In another noteworthy study, Anderson, Rungtusanatham & Schroeder, (1994) developed
the theoretical foundation of quality management practice by examining Deming’s 14 points. They
reduced the number of concepts from 37 to 7 using the Delphi Method. These are visionary leader-
ship, internal and external cooperation, learning, process management, continuous improvement,
employee fulfillment, and customer satisfaction.
Black & Porter (1996) also identified critical factors of the total quality management us-
ing the Malcolm Baldrige Award criteria and investigated their validity by empirical means. They
developed 32 items, which were classified into ten critical factors. These factors are: Corporate
quality culture, strategic quality management, quality improvement measurement systems, people
and customer management, operational quality planning, external interface management, supplier
partnerships, teamwork structures, customer satisfaction orientation, and communication of im-
provement information. Various authors have also assessed the validity of Malcolm Baldrige
Award Criteria (Wilson & Collier, 2000), (Flynn & Saladin, 2001).
Ahire, Golhar, & Waller (1996) developed twelve integrated quality management con-
structs through detailed analysis of literature to determine critical factors of quality management of
organizations. Ahire et al. identified twelve factors. These are supplier quality management, sup-
plier performance, customer focus, statistical process control usage, benchmarking, internal quality
information usage, employee involvement, employee training, design quality management, em-
ployee empowerment, product quality, and top management commitment.
Measuring Performance Through TQM Criteria
Performance measurement is very important for the optimum management of an organi-
zation. According to Deming, without measuring something, it is impossible to improve it. There-
fore, to improve organizational performance, one needs to determine the total quality management
criteria and measure their effect on business performance ( Madu, Kuei, Jacob, 1996), (Gadenne,
Sharma, 2002).
Problems and Perspectives in Management, 4/2005 223
Traditionally, success of business performance has been measured financially. Profit,
market share, earnings, and growth have been regarded as critical indicators of business perform-
ance. Kaplan & Norton (1996) emphasized that financial indicators measure past performance
only. Therefore, in order to overcome shortcomings of traditional business performance systems,
they added non-financial categories to the traditional performance measurement system.
Both manufacturing and service sector literature contain a considerable number of studies
that measure business performance through total quality management criteria (Samson and
Terziovski, 1998), (Flynn, Schroeder & Sakakibara, 1995), (Wilson & Collier, 2000), (Fynes &
Voss, 2001), (Flynn & Saladin, 2001), (Azaranga, Gonzalez & Reavill,1998), (Montes, Jover &
Fernandez, 2003), (Benson, Saraph, Schroeder, 1991), (Stein, 1998), (Choi, Eboch, 1989). While
these works explore a variety of theoretical and empirical issues, the general conclusion is that if
TQM plan is implemented properly, it produces a variety of benefits such as understanding cus-
tomers’ needs, improved customer satisfaction, improved internal communication, better problem
solving, fewer errors, and so on.
While many firms all over the world have invested substantial resources in adapting and
implementing TQM programs to improve their performance, many of them did not achieve any im-
provement and some only a little. Specifically, due to the presence of a multitude of barriers, many
healthcare organizations utilize only a partial implementation of TQM, and hence are unable to
achieve continuous and systematic improvement (Nwabueze & Kanji, 1997), (Zabada, Asubonteng,
Munchus, 1998). In these studies, two main culprits were identified. The first was the uncertain defi-
nition of TQM. The second was the inappropriate implementation of TQM (Hansson & Ericsson,
2002). Despite this lack of success, many researchers found that TQM is still a very important source
for improving the organizational performance of hospitals. Particularly, quality management has be-
come an important issue in the healthcare sector after 1980 (Kunst & Lemming, 2000), ( McAlexan-
der, Keldenberg, Koenig, 1994), (Kenagy, Berwick, Shore, 1999), (Andaleeb, 2001), (Eggli, Halfon,
2003), (Butler, Leong, 2000), (Yasin, Meacham, Alavi, 1998), (Li, 1997), (Yang, 2003), (Meyer,
Collier, 2001), (Ovretveit, 2001), (Brashier, Sower, Motwani, Savoie, 1996).
As explained above, total quality management focuses on processes rather than results.
Therefore, after determining the improvement area in the organization and taking the corrective
actions, the results will be high quality products or services.
The Model
We will employ a model that is based on the relationships between the critical factors of
total quality management and their effect on business performance in health care sector. This
model is shown in Figure 1 below.
Methodology
The Sample
For the empirical research, we selected as our universe the private and state hospitals in
Turkey. Data for this study were collected by using a questionnaire that was distributed to 150 chief
administrative officers of healthcare institutions in Turkey. 50 useable questionnaires were returned
giving a response rate of 33 percent, which was considered satisfactory for subsequent analysis.
The research instrument
The instrument used in this study was developed by Jayant V. Saraph, P. George Benson,
and Roger G. Schroeder with the purpose of identifying critical factors (areas) of total quality
management in a business unit adapted by Raju, Lonial for use in the hospital industry (Raju &
Lonial, 2002).
However, in the present questionnaire, the eight critical factors were reduced to four. The
basic justification for this lies in the researchers’ impression (derived from the pilot study) that the
hospital sector is in the “awakening” stage described by Crosby (Crosby, 1996). Our interviews
corroborated that management “recognized that quality management may be of value but was not
willing to provide money or time to make it all happen, teams were set up to attack major prob-
Problems and Perspectives in Management, 4/2005 224
lems instead of soliciting long range solutions”, and that company quality posture could be sum-
marized as “is it absolutely necessary to always have problems with quality?”. These signified a
very close alignment with the “awakening” stage of Crosby’s stages of maturity.
As is typical of this stage, none of the hospitals in the sample reported an established
quality department or relevant training programs. Consequently, three critical factors, namely role
of quality department, training, and product and service design were excluded from the question-
naire. A fourth critical factor, supplier quality management, was also omitted since the Turkish
Ministry of Health requires hospitals to award contracts to vendors who are the lowest bidders as
long as they satisfy certain specifications. As Deming points out, this practice overrules any con-
cern on the part of companies to review the bidders’ approaches to quality control (Deming, 1986).
A second section in the questionnaire measures business performance criteria.
Fig. 1. The Model
The original version of the questionnaire was in English. This questionnaire was trans-
lated into the local language (Turkish). The local version was retranslated until a panel of experts
agreed that the two versions were matched (Albaum, Strandskov & Duerr, 2002). Each item was
rated on a five-point Likert scale, ranging from “very low” to “very high”. The questionnaire was
pre-tested several times to ensure that the wording, format, and sequencing of questions were ap-
propriate. Occasional missing data on variables were handled by replacing them with the mean
value. The percentage of missing data across all data was calculated to be relatively small. The
questionnaire is given in Appendices A and B.
Analysis and Results
The analysis of the data is conducted at three steps:
1. Performing an exploratory factor analysis with varimax rotation to determine the
critical factors of the total quality management.
2. Performing an exploratory factor analysis with varimax rotation to determine the fac-
tors of business performance criteria.
3. Using canonical correlation analysis measuring the effect of critical factors of total
quality management on business performance. These steps are discussed in greater
detail in the next section.
Determining critical factors of total quality management using Exploratory Factor Analysis
Exploratory factor analysis with varimax rotation was performed on the total quality
management criteria in order to extract the dimensions underlying the construct. The factor analy-
sis of the 30 variables yielded four factors explaining 83.953% of total variance. Only eleven of
the thirty items loaded on these four factors and, based on the items loading on each factor, the
factors were labeled "Role of divisional top management and quality policy” (Factor 1), “Process
Problems and Perspectives in Management, 4/2005 225
management” (Factor 2), “Quality data and reporting” (Factor 3), “Employee relations (Factor
4). These eleven items are shown in Table 1.
Table 1
Factor analysis of total quality management criteria
Factors Variables
1 2 3 4
Extent to which top executives assume responsibility for quality
performance
0.910
Extent to which top management has objectives for quality
performance
0.888
Extent to which top management has developed and communicated a
vision for quality as part of a strategic vision of the organization
0.569
Amount of preventive equipment maintenance 0.762
Amount of inspection, review, or checking of work 0.902
Clarity of work or process instructions given to employees 0.752
Availability of quality data (mortality, morbidity) 0.892
Extent to which quality data are used as tools to manage quality 0.868
Scope of the quality data includes clinical performance 0.700
Extent to which quality awareness building among employees is on-
going
0.844
Extent to which employees are recognized for superior quality
performance
0.859
These items were factor analyzed to see if they were structurally related. Factor analysis
is a multivariate technique which links the three variables in the Factors 1, 2 and 3 and two vari-
ables in the Factor 4 in such a way that only the unique contribution each of the eleven variables is
considered for each factor. Thus factor analysis avoids potential problems of multicollinearity
(Hair, Anderson, Tatham & Black, 1998).
The Cronbach’s alpha measures of reliability for the four factors were 0.8349 for
Factor 1, 0.8787 for Factor 2, 0.8399 for Factor 3, 0.8209 for Factor 4. Since Cronbach’s alpha
measures for each factor are above the traditionally acceptable value of 0.70, all of the factors
were accepted as being reliable for the research.
Determining business performance criteria
Exploratory factor analysis with varimax rotation was performed on the performance
measurement criteria of the hospital in order to extract the dimensions underlying the construct.
Performance of the hospitals was measured by using financial and non-financial indicators. Finan-
cial criteria include subjective measures such as revenue growth over the last three years, net prof-
its, return on investment, profit to revenue ratio, cash flow from operations. On the other hand,
non-financial criteria contain subjective measures such as reputation among major customer seg-
ments, capacity to develop a unique competitive profile, new product/ service development and
market development. Non-financial criteria are based on executive’s perception of how the organi-
zation is performing relative to the competition.
The factor analysis of the 19 variables yielded two factors explaining 77.901% of total
variance. Only nine of the nineteen items loaded on these two factors and, based on the items load-
ing on each factor, the factors were labeled" Financial factor” (Factor 1), “Non-financial factor”
(Factor 2). Factor loadings of these nine items are shown in Table 2.
Problems and Perspectives in Management, 4/2005 226
Table 2
Factor analysis for performance criteria
Factors Variables
1 2
Revenue growth over the last three years 0.760
Net profits 0.890
Return on investment 0.663
Profit to revenue ratio 0.896
Cash flow from operations 0.761
Reputation among major customer segments 0.888
Capacity to develop a unique competitive profile 0.803
New product / service development 0.836
Market development 0.852
The Cronbach’s alpha measures of reliability for the two factors were 0.9092 for Factor 1,
0.9206 for Factor 2. Since Cronbach’s alpha measures for each factor are above the traditionally
acceptable value of 0.70, all of the factors were accepted as being reliable for the research.
Canonical Correlation Analysis
Canonical correlation analysis is a more general case of usual multiple regression. In mul-
tiple regression analysis, the aim is to find a linear combination of the independent (or predictor)
variables such that the composite has the maximum correlation with the dependent (or criterion)
variable. Canonical correlation analysis seeks to identify and quantify the associations between
two sets of variables. It focuses on the correlation between a linear combination of the variables in
one set and a linear combination of the variables in another set (Johnson, 2002). It can be used for
both metric and nonmetric data for either the dependent or independent variables (Hair, Anderson,
Tatham & Black,1998). Canonical correlation analysis maximizes the correlation between variates.
q
i
i i
p
i
i i
y b V x a U
1 1
The correlation between the two sets of variables is called canonical correlation. The co-
efficients are determined such that a linear combination of variables from the first set has the high-
est possible correlation with a linear combination of variables from the second set. These coeffi-
cients are called canonical coefficients. Standardized coefficients are used when the variables are
not measured in the same units. A variable which has a high-standardized coefficient is loading
heavily on its canonical variable and therefore is significant. If a variable is highly correlated with
its canonical variable, its movement will be closely related to that canonical variable. Therefore,
either a high-standardized canonical coefficient or a high correlation with its canonical variable
signifies the importance of that variable. In general, the researcher faces the choice of interpreting
the functions using canonical coefficients or correlations. It is suggested that correlations are supe-
rior to canonical coefficients (Hair, Anderson, Tatham & Black, 1998). Interpreting coefficients is
sometimes misleading and dangerous, because intercorrelated predictors imply that the confidence
intervals around the coefficients will be broad and that one variable may hide or suppress the im-
portance of another variable correlated with the first (Levine, 1977).
Results of Analysis
In this study, canonical correlation was used to investigate the interrelationships between
two sets of variables: the criterion set includes performance factors (financial and nonfinancial
performance variables) while the predictor set consists of variables reflecting TQM factors (proc-
ess management, quality data and reporting, employee relations, role of divisional top management
Problems and Perspectives in Management, 4/2005 227
and quality policy). All the variables (except quality data and reporting) satisfy normality of
Shapiro-Wilk, Anderson-Darling, Martinez-Iglewicz, Kolmogorov-Smirnov, D'Agostino Skew-
ness, D'Agostino Kurtosis, D'Agostino Omnibus tests (quality data and reporting accepts normality
of all the tests mentioned above except Shapiro-Wilk test).
Pearson correlations between performance and TQM variables are shown in Table 3.
These correlations indicate that financial performance is positively correlated with quality data and
reporting (at 1% significance level) and role of divisional top management and quality policy (at
10% significance level). Non-financial performance of hospitals is positively correlated with em-
ployee relations (significant at 1% level). Other correlations are not significant at 10 % signifi-
cance level.
Table 4 displays the test statistics of canonical correlation. The first canonical correlation
(R=0.56) indicates a strong relationship between performance and TQM variables. Both canonical
functions were found to be significant at an alpha level of .05 using Bartlett’s chi-square test. Be-
cause the canonical correlations do not give the variance shared between the performance and
TQM variables, Stewart and Love’s redundancy index is obtained. The redundancy index is the
mean variance of the dependent (or independent) set of variables that is explained by a particular
canonical variate of the independent (or dependent) set. The proportion of variance in the perform-
ance variables predictable from or shared with the TQM variables is 24.8% and the proportion of
variance in the TQM variables shared with the performance variables is 12.4% by the two canoni-
cal variates.
Table 3
Pearson Correlations between Performance and TQM Variables
prcman qualdata emprel role fin nonfin
prcman 1,00
qualdata 0,00 1,00
emprel 0,00 -0,00 1,00
role 0,00 0,00 -0,00 1,00
fin -0,11 0,46* 0,02 0,26** 1,00
nonfin 0,18 0,02 0,37* 0,17 0,00 1,00
* Significant at 1% level, ** Significant at 5% level
Abbreviation :
Performance Variables
Fin: Financial Performance
Nonfin: Nonfinancial Performance
TQM Variables
Prcman: process management
Qualdata: quality data and reporting
Emprel: employee relations
Role: role of divisional top management and quality policy
Table 4
Canonical Correlations
Variate Canonical Num Den Prob Wilks'
Number Correlation F-Value DF DF Level Lambda
1 0,554438 3,67 8 88 0,000974 0,561980
2 0,434271 3,49 3 45 0,023268 0,811409
Problems and Perspectives in Management, 4/2005 228
Table 4 (continuous)
Redundancy Index
Canonical Variation Explained Individual Cumulative Canonical
Variate in these by these Percent Percent Correlation
Number Variables Variates Explained Explained Squared
1 TQM PERF 7,7 7,7 0,3074
2 TQM PERF 4,7 12,4 0,1886
1 PERF TQM 15,4 15,4 0,3074
2 PERF TQM 9,4 24,8 0,1886
Since there is no multicollinearity within the sets of performance and TQM variables,
standardized canonical coefficients and loadings were found equal to each other. Therefore, inter-
pretation of those would be the same. The canonical loadings are shown in Table 5. Canonical
variable for the criterion set is a linear combination of the two performance variables (financial
and non-financial). Canonical variable I shows that financial performance has the highest correla-
tion (0.94) with its variable and therefore is the most important variable. Non-financial variable is
also important and load onto the canonical variable. In the predictor set among the TQM variables
the most important variable is the most heavily loaded variable, which is quality data and report-
ing; loading of 0.80 to its canonical variate indicates its importance. The role of divisional top
management and quality policy is also highly correlated with its canonical variate (0.54). Financial
performance on the dependent side is related to quality data and reporting and role of divisional
top management and quality policy on independent side. Canonical variate II shows the strong
association between non-financial performance measurement and employee relations.
Table 5
Canonical Loadings
U1 U2
prcman -0,082930 -0,489085
qualdata 0,795663 0,322383
emprel 0,255362 -0,791371
role 0,542984 -0,174923
V1 V2
fin 0,941988 0,335646
nonfin 0,335646 -0,941988
Discussion
In this study, as it is mentioned above, implementation of TQM in healthcare industry in
Turkey is found to have a strong correlation with business performance (R=0.56). TQM model
contains only four main factors: data reporting, role of top management, process management, and
employee relations. Performance of hospitals consists of two dimensions: financial and non-
financial factors.
There are many purposes for gathering data in quality management. Data can be collected
to determine mortality and morbidity rate in hospitals to understand current processes. Moreover,
data provide inspection, various test results and verification records. Data are also used to analyze
the process using various types of statistical process control tools such as control charts, Pareto
charts, cause and effect diagrams, check sheet, histograms, scatter diagram, and so on. These tradi-
tional quality tools are very useful in monitoring and measuring progress and performance. Man-
agement by facts requires that management decisions are based on relevant data and reports. In
Problems and Perspectives in Management, 4/2005 229
this model, data and reporting have a very strong correlation with TQM and financial performance
of the hospital.
In healthcare industry, successes of TQM applications depend on a strong leadership that
must be initiated by the top management. Quality improvement plans proposed by several gurus
emphasize primarily the commitment of top management. In this study, role of top management
and quality policy has the second highest correlation with TQM plan. Top management of the hos-
pitals determines an appropriate organization culture, vision, and quality policy. Managers of
healthcare organizations should determine objectives, and set specific measurable goals to satisfy
customer expectations and improve their organizations’ performance. On the other hand, the top
management must provide adequate resources to the implementation of quality efforts. This model
implies that the managers’ role has a direct impact on the financial performance of the hospitals. In
order to increase net profit and revenue, and to reduce cost of quality, hospital managers must
convey their priorities and expectations to their employees.
Employee relations, the third factor, have a sufficient correlation with TQM. In this model,
employee relations have two variables. The first variable is building quality awareness among em-
ployees; the second one is recognition of employees for superior quality performance. Hospitals must
develop formal reward and recognition systems to encourage employee involvement, and support
teamwork. In this model, employee relations have a strong correlation with non-financial perform-
ance factor. Non-financial measures contain reputation, capacity of hospital, new service design, and
new market development. Non-financial performance measures are better indicators of management
effort and reflect the reasons for future financial performance (Hoque, 2003). Therefore, non-
financial measures supplement financial measures in providing support for TQM. Hence, employee
relations have also indirect impact on the financial performance of hospitals.
Fourth factor, process management, which includes such sub-factors as process monitor-
ing, supervision, and preventive equipment maintenance, did not have sufficiently strong influence
on TQM in this model. A possible reason for this might be the high level of personnel compliance
with the implicit and explicit norms and rules of the workplace. Under such circumtances the mar-
ginal contribution to total quality of the inputs used for process management (inspection, supervi-
sion etc.) purposes would be expected to be low. This could explain the low value of the process
management-coefficient in the model.
Limitation and further research:
Sample size must be increased.
Data should be gathered from more than one city in Turkey.
Objective performance indicators should be employed in the analysis. In this study,
data were collected from top managers of hospitals on the basis of their subjective
evaluations.
Structural equation modeling (SEM) or neural network model could be used in the fu-
ture studies to utilize the additional insights they might provide.
After using exploratory factor analysis, confirmatory factor analysis could be used.
Conclusion
TQM primarily focuses on the production of quality goods and services and the delivery
of excellent customer service; however, its success increases when it is extended to the entire
company. This enables the reformation of the corporate culture and the permeation of the new
business philosophy into every facet of organization. The philosophy of doing things right must be
implemented with enthusiasm and commitment throughout the organization – from top to bottom
and the little steps forward (called “Kaizen” by the Japanese) must be viewed as “a race without a
finish”. Consequently, effective use of TQM is a valuable asset in a company’s resource portfolio
– one that can produce important competitive capabilities and be a source of competitive advan-
tage.
Problems and Perspectives in Management, 4/2005 230
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Problems and Perspectives in Management, 4/2005 233
Appendix A
1. Role of Top Management and Quality Policy
1. Extent to which top executives assume responsibility for quality performance.
2. Acceptance of responsibility for quality by major department heads.
3. Degree to which top management (top executive and major department heads) is
evaluated for quality performance.
4. Extent to which top management supports a long term quality improvement process.
5. Extent to which the top management has objectives (Management By Objectives) for
quality performance.
6. Importance attached to quality by top management in relation to cost/revenue objec-
tives.
7. Degree to which top management considers quality improvement as a way to in-
crease profits.
8. Degree of comprehensiveness of the quality plan.
9. Extent to which top management has developed and communicated a Vision for
Quality as part of a Strategic Vision of the Organization.
2. Process Management/Operating Procedures
1. Use of statistical control charts to control processes.
2. Amount of preventive equipment maintenance.
3. Amount of inspection, review or checking of work.
4. Importance of inspection, review or checking of work.
5. Stability of work schedules.
6. Clarity of work or process instructions given to employees.
3. Quality Data and Reporting
1. Availability of cost of quality data in the hospital.
2. Availability of quality data (mortality and morbidity, etc.).
3. Timeliness of quality data.
4. Extent to which quality data (cost of quality, mortality and morbidity, errors, etc.) are
used as tools to manage quality.
5. Extent to which quality data are available to managers and supervisors.
6. Extent to which quality data are used to evaluate supervisor and managerial perform-
ance.
7. Extent to which quality data, control charts, etc. are displayed in work areas.
8. Scope of the quality data includes clinical performance and service/process perform-
ance.
4.Employee Relations
1. Extent to which employee involvement type programs are implemented in the hospi-
tal.
2. Effectiveness of quality teams or employee involvement type programs in the hospi-
tal.
3. Extent to which the employees are held responsible for error free output.
4. Amount of feedback provided to the employees on their quality performance.
5. Degree of participation in quality decisions by hourly/non-supervisory employees.
6. Extent to which quality awareness-building among employees is on-going.
7. Extent to which employees are recognized for superior quality performance.
Problems and Perspectives in Management, 4/2005 234
Appendix B
1. Performance
1. Revenue growth over the last three years.
2. Service quality as perceived by customers.
3. Market share gain over the last three years.
4. Investments in R&D aimed at new innovations.
5. Net profits.
6. Return on investment.
7. Reputation among major customer segments.
8. Capacity to develop a unique competitive profile.
9. Profit to revenue ratio.
10. Cash flow from operations.
11. New product/service development.
12. Market development.
13. Cost per adjusted discharge.
14. Mortality and Morbidity rate.
15. Return on Assets.
16. Employee Turnover.
17. Number of Admissions.
18. Share of net patient revenue.
19. Market Orientation.
Problems and Perspectives in Management, 4/2005 235
AUTHORS OF THE ISSUE
Yoser Gadhoum Ph.D., Département des stratégies des affaires, University of
Quebec in Montreal, Canada
Salih Katircioglu Ph.D., Assistant Professor of Economics, Department of Banking
and Finance, Eastern Mediterranean University, Turkey
Bilge Oney Ph.D., Assistant Professor of Economics, Department of Banking
and Finance, Eastern Mediterranean University, Turkey
Michael Colin Cant School of Business Management, University of South Africa
Cindy Erdis School of Business Management, University of South Africa
Abdul Jumaat bin
Mahajar
Ph.D., Universiti Utara Malaysia, Faculty Business Management,
West Malaysia
Jasmani Binti Mohd
Yunus
Universiti Utara Malaysia, Faculty Business Management, West
Malaysia
Vlado Dimovski Ph.D., Associate Professor, Department of Management and
Organization, Faculty of Economics, University of Ljubljana,
Slovenia
Miha Škerlavaj M.Sc., Assistant, Department of Management and Organization,
Faculty of Economics, University of Ljubljana, Slovenia
Jens Gammelgaard Ph.D., Associate Professor, Department of International
Economics and Management, Copenhagen Business School,
Denmark
Tatiana Zalan PhD, AFAIM, Lecturer, Department of Management, University
of Melbourne, Australia
Geoffrey Lewis PhD, Professorial Fellow, Melbourne Business School, Australia
Rasoava
Rijamampianina
DSSC, DECSA, MBA, DBA, Associate Professor, Graduate
School of Business Administration, University of the
Witwatersrand, South Africa
Teresa Carmichael BSc (Hons), MM(HR), Lecturer, Graduate School of Business
Administration, University of the Witwatersrand, South Africa
Kok Leong Choo Senior Lecturer in Strategic Management and holds an MBA,
University of Wales Institute, Cardiff, UK
Louise van Scheers School of Business Management, University of South Africa
doc_676083778.pdf
The literature on quality contains numerous case studies of successful companies and descriptions of quality concepts and quality improvement programs. The purpose of this study is to determine the critical factors of total quality management.
Problems and Perspectives in Management, 4/2005 220
Critical Factors of Total Quality Management and Its Effect on
Performance in Health Care Industry: A Turkish Experience
Mustafa Dilber, Nizamettin Bayyurt, Selim Zaim, Mehves Tarim
Abstract
The literature on quality contains numerous case studies of successful companies and de-
scriptions of quality concepts and quality improvement programs. The purpose of this study is to
determine the critical factors of total quality management in the healthcare sector and to measure the
effect of critical factors of total quality management on business performance in small and medium
size hospitals in Turkey. The instrument used in this study was developed to identify critical factors
(areas) of total quality management in the hospital industry. The technique of canonical correlation
analysis is employed to investigate this relationship. To measure the eight dimensions of total quality
management, thirty items were measured by using a five point Likert scale, ranging from “very low”
to “very high”. Performance of the hospital was measured using by subjective measures based on
hospital administrators’ perception of how their organization performed relative to the competition.
Data analysis indicated a positive correlation between the performance of the hospital and the four
critical factors of quality management in Turkish healthcare industry.
Key words: Total quality management, Canonical correlation, Business performance.
Introduction
In today’s changing and developing global world, both service and manufacturing com-
panies are confronted with a challenging and increasingly competitive environment. This competi-
tion focuses on before and after sales services rather than products’ attributes and manufacturing
(Sivadas & Baker-Prewitt, 2000).
Today, service industries are dominant in developed countries and are among the fastest
growing sector even in the emerging countries. The service sector also approximately accounts for
60 or 70 percentage of the total worldwide GNP (Franklin, 1997). Due to the phenomenal growth
of the service sector in modern society, the importance of service management and marketing is
also expected to increase (Yavas, Bilgin & Shemwell, 1997), (Camison, 1996), (Bates, Bates,
Johnston, 2003). Since its emergence, the basic concept of service management has continued to
change. Two major changes in the concept include: (a) a shift from an interest in the internal con-
sequences of performance (e.g., internal efficiency – productivity of labor and profits) to an inter-
est in the external consequences (e.g., consumer behavior- customer satisfaction, loyalty), and (b)
a shift from focus on structure to a focus on process. Thus, marketers and managers now focus on
the process of service production and consumption as it governs consumer behavior in the service
industry where services are produced and consumed simultaneously with active participation of
the consumer.
The change in the conceptual paradigm within service marketing and management has
motivated many scholars to research the issues of service quality. Providing quality service is not
only the most important factor for consumer satisfaction, it is also the principal criterion that
measures the competitiveness of a service organization. Whereas the marketing textbooks stress
the four P’s of marketing, namely, product, place, promotion, and price, in a service business none
of these work very well without a Q for quality (Youssef & Bovaird, 1996).
Quality has become one of the most important factors in global competition today. Inten-
sifying global competition and increasing demand by customers for better quality have caused
more and more companies to realize that they will have to provide quality product and /or services
in order to successfully compete in the marketplace. To meet the challenge of this global revolu-
tion, many businesses have invested substantial resources in adapting and implementing total qual-
© Mustafa Dilber, Nizamettin Bayyurt, Selim Zaim, Mehves Tarim, 2005
Problems and Perspectives in Management, 4/2005 221
ity management (TQM) strategies. TQM is defined as an action plan to produce and deliver com-
modities or services, which are consistent with customers’ needs or requirements by better,
cheaper, faster, safer, easier processing than competitors with the participation of all employees
under top management leadership.
The role of total quality management is widely recognized as being a critical determinant
in the success and survival of an organization in today’s competitive environment. Any decline in
customer satisfaction due to poor service quality would be a matter of concern. Consumers are
becoming increasingly aware of rising standards in service quality, prompted by competitive
trends which have developed higher expectations (Yavas & Shemwell, 2001).
In recent years, one of the fastest growing industries in the service sector is the healthcare
industry. In the healthcare industry, all hospitals provide the same type of service, but they do not
provide the same quality of service. To achieve service excellence, hospitals must strive for zero
defects, retaining every customer that the company can profitably serve. Zero defects require con-
tinuous efforts to improve the quality of the service delivery system (Lim & Tang, 2000).
The purpose of this study is to determine the critical factors of total quality management
in the healthcare sector and to measure the effect of critical factors of total quality management on
business performance in small and medium size hospitals in Turkey.
Literature Review of Total Quality Management
Although the literature on total quality management includes a rich spectrum of research,
there is no consensus on the definition of quality. The notion of quality has been defined in differ-
ent ways by different authors. Gurus of the total quality management disciplines such as Garvin,
Juran, Crosby, Deming, Ishikawa and Feigenbaum defined the concept of quality and total quality
management in different ways. Garvin proposed a definition of quality in terms of the transcen-
dent, product based, user based, manufacturing based and value based approaches. Garvin also
identified eight attributes to measure product quality (Garvin, 1987). Juran defined quality as “fit-
ness for use”. Juran focused on a trilogy of quality planning, quality control, and quality improve-
ment (Mitra, 1987). Crosby defined quality as “conformance to requirements or specifications”
(Crosby, 1996). According to Crosby, requirements are based on customer needs. Crosby identi-
fied 14 steps for a zero defect quality improvement plan to achieve performance improvement.
According to Deming, quality is a predictable degree of uniformity and dependability, at low cost
and suited to the market. Deming also identified 14 principles of quality management to improve
productivity and performance of the organization (Deming, 1986). Ishikawa also emphasized im-
portance of total quality control to improve organizations’ performance. He contributed to this area
by using a cause and effect diagram (Ishikawa diagram) to diagnose quality problems (Mitra,
1987). Feigenbaum described the concept of organization- wide total quality control. Feigenbaum
was the first user of total quality control concept in the quality literature. He defined quality as
“the total composite product and service characteristics of marketing, engineering, manufacturing
and maintenance through which the product and service in use will meet the expectations by the
customer” (Mitra, 1987). Major common denominators of these quality improvement plans in-
clude management commitment, strategic approach to a quality system, quality measurement,
process improvement, education and training, and eliminating the causes of problems.
Total quality management is the culture of an organization committed to customer satis-
faction through continuous improvement. This culture varies both from one country to another and
between different industries, but has certain essential principles which can be implemented to se-
cure greater market share, increased profits, and reduced costs (Kanji & Wallace, 2000). Manage-
ment awareness of the importance of total quality management, alongside business process reengi-
neering and other continuous improvement techniques was stimulated by the benchmarking
movement to seek, study, implement and improve on best practices (Zairi & Youssef, 1995). The
commitment to continuous improvement historically originated in manufacturing firms; but spread
quickly to the service sector (e.g. teller transactions in banks, order processing in catalog firms,
etc.). Surveys point at the widespread interest and application of TQM:
Problems and Perspectives in Management, 4/2005 222
95% of manufacturing companies and 70% of service companies have used one form
or other of quality improvement programs and 55% of American executives and 70%
of Japanese executives use quality improvement information at least monthly (Olion
& Rynes, 1991), (Rigby, 1998).
An international survey of over 4000 managers in 15 countries indicated TQM usage
by approximately 60% in 1997 (Rigby, 1998). A Survey of TQM and continuous im-
provement programs indicates 12 common aspects: Committed leadership, adoption
and communication of TQM, closer customer relationships, benchmarking, increased
training, open organization, employee empowerment, zero defects mentality, flexible
manufacturing, process improvement, and measurement (Powel, 1995).
Furthermore, to determine critical factors of total quality management, various studies
have been carried out and different instruments were developed by individual researchers and in-
stitutions such as Malcolm Baldrige Award, EFQM (European Foundation For Quality Manage-
ment), and the Deming Prize Criteria. Based on these studies, a wide range of management issue,
techniques, approaches, and systematic empirical investigation have been generated.
Accordingly, Saraph, Benson & Schroder, (1989) developed 78 items, which were classi-
fied into eight critical factors to measure the performance of total quality management in an or-
ganization. These critical factors are: Role of divisional top management and quality policy, role
of the quality department, training, product and service design, supplier quality management,
process management, quality data and reporting, and employee relations.
Flynn, Schroeder & Sakakibara, (1994) developed another instrument to determine criti-
cal factors of total quality management. Flynn et al. identified seven quality factors. These are top
management support, quality information, process management, product design, workforce man-
agement, supplier involvement, and customer involvement. As it is seen, this instrument is very
similar to the preceding instrument that was developed by Saraph et al. (1989). Flynn, Schroder &
Sakakibara, (1995) measured the impact of total quality practices on quality performance and
competitive advantage.
In another noteworthy study, Anderson, Rungtusanatham & Schroeder, (1994) developed
the theoretical foundation of quality management practice by examining Deming’s 14 points. They
reduced the number of concepts from 37 to 7 using the Delphi Method. These are visionary leader-
ship, internal and external cooperation, learning, process management, continuous improvement,
employee fulfillment, and customer satisfaction.
Black & Porter (1996) also identified critical factors of the total quality management us-
ing the Malcolm Baldrige Award criteria and investigated their validity by empirical means. They
developed 32 items, which were classified into ten critical factors. These factors are: Corporate
quality culture, strategic quality management, quality improvement measurement systems, people
and customer management, operational quality planning, external interface management, supplier
partnerships, teamwork structures, customer satisfaction orientation, and communication of im-
provement information. Various authors have also assessed the validity of Malcolm Baldrige
Award Criteria (Wilson & Collier, 2000), (Flynn & Saladin, 2001).
Ahire, Golhar, & Waller (1996) developed twelve integrated quality management con-
structs through detailed analysis of literature to determine critical factors of quality management of
organizations. Ahire et al. identified twelve factors. These are supplier quality management, sup-
plier performance, customer focus, statistical process control usage, benchmarking, internal quality
information usage, employee involvement, employee training, design quality management, em-
ployee empowerment, product quality, and top management commitment.
Measuring Performance Through TQM Criteria
Performance measurement is very important for the optimum management of an organi-
zation. According to Deming, without measuring something, it is impossible to improve it. There-
fore, to improve organizational performance, one needs to determine the total quality management
criteria and measure their effect on business performance ( Madu, Kuei, Jacob, 1996), (Gadenne,
Sharma, 2002).
Problems and Perspectives in Management, 4/2005 223
Traditionally, success of business performance has been measured financially. Profit,
market share, earnings, and growth have been regarded as critical indicators of business perform-
ance. Kaplan & Norton (1996) emphasized that financial indicators measure past performance
only. Therefore, in order to overcome shortcomings of traditional business performance systems,
they added non-financial categories to the traditional performance measurement system.
Both manufacturing and service sector literature contain a considerable number of studies
that measure business performance through total quality management criteria (Samson and
Terziovski, 1998), (Flynn, Schroeder & Sakakibara, 1995), (Wilson & Collier, 2000), (Fynes &
Voss, 2001), (Flynn & Saladin, 2001), (Azaranga, Gonzalez & Reavill,1998), (Montes, Jover &
Fernandez, 2003), (Benson, Saraph, Schroeder, 1991), (Stein, 1998), (Choi, Eboch, 1989). While
these works explore a variety of theoretical and empirical issues, the general conclusion is that if
TQM plan is implemented properly, it produces a variety of benefits such as understanding cus-
tomers’ needs, improved customer satisfaction, improved internal communication, better problem
solving, fewer errors, and so on.
While many firms all over the world have invested substantial resources in adapting and
implementing TQM programs to improve their performance, many of them did not achieve any im-
provement and some only a little. Specifically, due to the presence of a multitude of barriers, many
healthcare organizations utilize only a partial implementation of TQM, and hence are unable to
achieve continuous and systematic improvement (Nwabueze & Kanji, 1997), (Zabada, Asubonteng,
Munchus, 1998). In these studies, two main culprits were identified. The first was the uncertain defi-
nition of TQM. The second was the inappropriate implementation of TQM (Hansson & Ericsson,
2002). Despite this lack of success, many researchers found that TQM is still a very important source
for improving the organizational performance of hospitals. Particularly, quality management has be-
come an important issue in the healthcare sector after 1980 (Kunst & Lemming, 2000), ( McAlexan-
der, Keldenberg, Koenig, 1994), (Kenagy, Berwick, Shore, 1999), (Andaleeb, 2001), (Eggli, Halfon,
2003), (Butler, Leong, 2000), (Yasin, Meacham, Alavi, 1998), (Li, 1997), (Yang, 2003), (Meyer,
Collier, 2001), (Ovretveit, 2001), (Brashier, Sower, Motwani, Savoie, 1996).
As explained above, total quality management focuses on processes rather than results.
Therefore, after determining the improvement area in the organization and taking the corrective
actions, the results will be high quality products or services.
The Model
We will employ a model that is based on the relationships between the critical factors of
total quality management and their effect on business performance in health care sector. This
model is shown in Figure 1 below.
Methodology
The Sample
For the empirical research, we selected as our universe the private and state hospitals in
Turkey. Data for this study were collected by using a questionnaire that was distributed to 150 chief
administrative officers of healthcare institutions in Turkey. 50 useable questionnaires were returned
giving a response rate of 33 percent, which was considered satisfactory for subsequent analysis.
The research instrument
The instrument used in this study was developed by Jayant V. Saraph, P. George Benson,
and Roger G. Schroeder with the purpose of identifying critical factors (areas) of total quality
management in a business unit adapted by Raju, Lonial for use in the hospital industry (Raju &
Lonial, 2002).
However, in the present questionnaire, the eight critical factors were reduced to four. The
basic justification for this lies in the researchers’ impression (derived from the pilot study) that the
hospital sector is in the “awakening” stage described by Crosby (Crosby, 1996). Our interviews
corroborated that management “recognized that quality management may be of value but was not
willing to provide money or time to make it all happen, teams were set up to attack major prob-
Problems and Perspectives in Management, 4/2005 224
lems instead of soliciting long range solutions”, and that company quality posture could be sum-
marized as “is it absolutely necessary to always have problems with quality?”. These signified a
very close alignment with the “awakening” stage of Crosby’s stages of maturity.
As is typical of this stage, none of the hospitals in the sample reported an established
quality department or relevant training programs. Consequently, three critical factors, namely role
of quality department, training, and product and service design were excluded from the question-
naire. A fourth critical factor, supplier quality management, was also omitted since the Turkish
Ministry of Health requires hospitals to award contracts to vendors who are the lowest bidders as
long as they satisfy certain specifications. As Deming points out, this practice overrules any con-
cern on the part of companies to review the bidders’ approaches to quality control (Deming, 1986).
A second section in the questionnaire measures business performance criteria.
Fig. 1. The Model
The original version of the questionnaire was in English. This questionnaire was trans-
lated into the local language (Turkish). The local version was retranslated until a panel of experts
agreed that the two versions were matched (Albaum, Strandskov & Duerr, 2002). Each item was
rated on a five-point Likert scale, ranging from “very low” to “very high”. The questionnaire was
pre-tested several times to ensure that the wording, format, and sequencing of questions were ap-
propriate. Occasional missing data on variables were handled by replacing them with the mean
value. The percentage of missing data across all data was calculated to be relatively small. The
questionnaire is given in Appendices A and B.
Analysis and Results
The analysis of the data is conducted at three steps:
1. Performing an exploratory factor analysis with varimax rotation to determine the
critical factors of the total quality management.
2. Performing an exploratory factor analysis with varimax rotation to determine the fac-
tors of business performance criteria.
3. Using canonical correlation analysis measuring the effect of critical factors of total
quality management on business performance. These steps are discussed in greater
detail in the next section.
Determining critical factors of total quality management using Exploratory Factor Analysis
Exploratory factor analysis with varimax rotation was performed on the total quality
management criteria in order to extract the dimensions underlying the construct. The factor analy-
sis of the 30 variables yielded four factors explaining 83.953% of total variance. Only eleven of
the thirty items loaded on these four factors and, based on the items loading on each factor, the
factors were labeled "Role of divisional top management and quality policy” (Factor 1), “Process
Problems and Perspectives in Management, 4/2005 225
management” (Factor 2), “Quality data and reporting” (Factor 3), “Employee relations (Factor
4). These eleven items are shown in Table 1.
Table 1
Factor analysis of total quality management criteria
Factors Variables
1 2 3 4
Extent to which top executives assume responsibility for quality
performance
0.910
Extent to which top management has objectives for quality
performance
0.888
Extent to which top management has developed and communicated a
vision for quality as part of a strategic vision of the organization
0.569
Amount of preventive equipment maintenance 0.762
Amount of inspection, review, or checking of work 0.902
Clarity of work or process instructions given to employees 0.752
Availability of quality data (mortality, morbidity) 0.892
Extent to which quality data are used as tools to manage quality 0.868
Scope of the quality data includes clinical performance 0.700
Extent to which quality awareness building among employees is on-
going
0.844
Extent to which employees are recognized for superior quality
performance
0.859
These items were factor analyzed to see if they were structurally related. Factor analysis
is a multivariate technique which links the three variables in the Factors 1, 2 and 3 and two vari-
ables in the Factor 4 in such a way that only the unique contribution each of the eleven variables is
considered for each factor. Thus factor analysis avoids potential problems of multicollinearity
(Hair, Anderson, Tatham & Black, 1998).
The Cronbach’s alpha measures of reliability for the four factors were 0.8349 for
Factor 1, 0.8787 for Factor 2, 0.8399 for Factor 3, 0.8209 for Factor 4. Since Cronbach’s alpha
measures for each factor are above the traditionally acceptable value of 0.70, all of the factors
were accepted as being reliable for the research.
Determining business performance criteria
Exploratory factor analysis with varimax rotation was performed on the performance
measurement criteria of the hospital in order to extract the dimensions underlying the construct.
Performance of the hospitals was measured by using financial and non-financial indicators. Finan-
cial criteria include subjective measures such as revenue growth over the last three years, net prof-
its, return on investment, profit to revenue ratio, cash flow from operations. On the other hand,
non-financial criteria contain subjective measures such as reputation among major customer seg-
ments, capacity to develop a unique competitive profile, new product/ service development and
market development. Non-financial criteria are based on executive’s perception of how the organi-
zation is performing relative to the competition.
The factor analysis of the 19 variables yielded two factors explaining 77.901% of total
variance. Only nine of the nineteen items loaded on these two factors and, based on the items load-
ing on each factor, the factors were labeled" Financial factor” (Factor 1), “Non-financial factor”
(Factor 2). Factor loadings of these nine items are shown in Table 2.
Problems and Perspectives in Management, 4/2005 226
Table 2
Factor analysis for performance criteria
Factors Variables
1 2
Revenue growth over the last three years 0.760
Net profits 0.890
Return on investment 0.663
Profit to revenue ratio 0.896
Cash flow from operations 0.761
Reputation among major customer segments 0.888
Capacity to develop a unique competitive profile 0.803
New product / service development 0.836
Market development 0.852
The Cronbach’s alpha measures of reliability for the two factors were 0.9092 for Factor 1,
0.9206 for Factor 2. Since Cronbach’s alpha measures for each factor are above the traditionally
acceptable value of 0.70, all of the factors were accepted as being reliable for the research.
Canonical Correlation Analysis
Canonical correlation analysis is a more general case of usual multiple regression. In mul-
tiple regression analysis, the aim is to find a linear combination of the independent (or predictor)
variables such that the composite has the maximum correlation with the dependent (or criterion)
variable. Canonical correlation analysis seeks to identify and quantify the associations between
two sets of variables. It focuses on the correlation between a linear combination of the variables in
one set and a linear combination of the variables in another set (Johnson, 2002). It can be used for
both metric and nonmetric data for either the dependent or independent variables (Hair, Anderson,
Tatham & Black,1998). Canonical correlation analysis maximizes the correlation between variates.
q
i
i i
p
i
i i
y b V x a U
1 1
The correlation between the two sets of variables is called canonical correlation. The co-
efficients are determined such that a linear combination of variables from the first set has the high-
est possible correlation with a linear combination of variables from the second set. These coeffi-
cients are called canonical coefficients. Standardized coefficients are used when the variables are
not measured in the same units. A variable which has a high-standardized coefficient is loading
heavily on its canonical variable and therefore is significant. If a variable is highly correlated with
its canonical variable, its movement will be closely related to that canonical variable. Therefore,
either a high-standardized canonical coefficient or a high correlation with its canonical variable
signifies the importance of that variable. In general, the researcher faces the choice of interpreting
the functions using canonical coefficients or correlations. It is suggested that correlations are supe-
rior to canonical coefficients (Hair, Anderson, Tatham & Black, 1998). Interpreting coefficients is
sometimes misleading and dangerous, because intercorrelated predictors imply that the confidence
intervals around the coefficients will be broad and that one variable may hide or suppress the im-
portance of another variable correlated with the first (Levine, 1977).
Results of Analysis
In this study, canonical correlation was used to investigate the interrelationships between
two sets of variables: the criterion set includes performance factors (financial and nonfinancial
performance variables) while the predictor set consists of variables reflecting TQM factors (proc-
ess management, quality data and reporting, employee relations, role of divisional top management
Problems and Perspectives in Management, 4/2005 227
and quality policy). All the variables (except quality data and reporting) satisfy normality of
Shapiro-Wilk, Anderson-Darling, Martinez-Iglewicz, Kolmogorov-Smirnov, D'Agostino Skew-
ness, D'Agostino Kurtosis, D'Agostino Omnibus tests (quality data and reporting accepts normality
of all the tests mentioned above except Shapiro-Wilk test).
Pearson correlations between performance and TQM variables are shown in Table 3.
These correlations indicate that financial performance is positively correlated with quality data and
reporting (at 1% significance level) and role of divisional top management and quality policy (at
10% significance level). Non-financial performance of hospitals is positively correlated with em-
ployee relations (significant at 1% level). Other correlations are not significant at 10 % signifi-
cance level.
Table 4 displays the test statistics of canonical correlation. The first canonical correlation
(R=0.56) indicates a strong relationship between performance and TQM variables. Both canonical
functions were found to be significant at an alpha level of .05 using Bartlett’s chi-square test. Be-
cause the canonical correlations do not give the variance shared between the performance and
TQM variables, Stewart and Love’s redundancy index is obtained. The redundancy index is the
mean variance of the dependent (or independent) set of variables that is explained by a particular
canonical variate of the independent (or dependent) set. The proportion of variance in the perform-
ance variables predictable from or shared with the TQM variables is 24.8% and the proportion of
variance in the TQM variables shared with the performance variables is 12.4% by the two canoni-
cal variates.
Table 3
Pearson Correlations between Performance and TQM Variables
prcman qualdata emprel role fin nonfin
prcman 1,00
qualdata 0,00 1,00
emprel 0,00 -0,00 1,00
role 0,00 0,00 -0,00 1,00
fin -0,11 0,46* 0,02 0,26** 1,00
nonfin 0,18 0,02 0,37* 0,17 0,00 1,00
* Significant at 1% level, ** Significant at 5% level
Abbreviation :
Performance Variables
Fin: Financial Performance
Nonfin: Nonfinancial Performance
TQM Variables
Prcman: process management
Qualdata: quality data and reporting
Emprel: employee relations
Role: role of divisional top management and quality policy
Table 4
Canonical Correlations
Variate Canonical Num Den Prob Wilks'
Number Correlation F-Value DF DF Level Lambda
1 0,554438 3,67 8 88 0,000974 0,561980
2 0,434271 3,49 3 45 0,023268 0,811409
Problems and Perspectives in Management, 4/2005 228
Table 4 (continuous)
Redundancy Index
Canonical Variation Explained Individual Cumulative Canonical
Variate in these by these Percent Percent Correlation
Number Variables Variates Explained Explained Squared
1 TQM PERF 7,7 7,7 0,3074
2 TQM PERF 4,7 12,4 0,1886
1 PERF TQM 15,4 15,4 0,3074
2 PERF TQM 9,4 24,8 0,1886
Since there is no multicollinearity within the sets of performance and TQM variables,
standardized canonical coefficients and loadings were found equal to each other. Therefore, inter-
pretation of those would be the same. The canonical loadings are shown in Table 5. Canonical
variable for the criterion set is a linear combination of the two performance variables (financial
and non-financial). Canonical variable I shows that financial performance has the highest correla-
tion (0.94) with its variable and therefore is the most important variable. Non-financial variable is
also important and load onto the canonical variable. In the predictor set among the TQM variables
the most important variable is the most heavily loaded variable, which is quality data and report-
ing; loading of 0.80 to its canonical variate indicates its importance. The role of divisional top
management and quality policy is also highly correlated with its canonical variate (0.54). Financial
performance on the dependent side is related to quality data and reporting and role of divisional
top management and quality policy on independent side. Canonical variate II shows the strong
association between non-financial performance measurement and employee relations.
Table 5
Canonical Loadings
U1 U2
prcman -0,082930 -0,489085
qualdata 0,795663 0,322383
emprel 0,255362 -0,791371
role 0,542984 -0,174923
V1 V2
fin 0,941988 0,335646
nonfin 0,335646 -0,941988
Discussion
In this study, as it is mentioned above, implementation of TQM in healthcare industry in
Turkey is found to have a strong correlation with business performance (R=0.56). TQM model
contains only four main factors: data reporting, role of top management, process management, and
employee relations. Performance of hospitals consists of two dimensions: financial and non-
financial factors.
There are many purposes for gathering data in quality management. Data can be collected
to determine mortality and morbidity rate in hospitals to understand current processes. Moreover,
data provide inspection, various test results and verification records. Data are also used to analyze
the process using various types of statistical process control tools such as control charts, Pareto
charts, cause and effect diagrams, check sheet, histograms, scatter diagram, and so on. These tradi-
tional quality tools are very useful in monitoring and measuring progress and performance. Man-
agement by facts requires that management decisions are based on relevant data and reports. In
Problems and Perspectives in Management, 4/2005 229
this model, data and reporting have a very strong correlation with TQM and financial performance
of the hospital.
In healthcare industry, successes of TQM applications depend on a strong leadership that
must be initiated by the top management. Quality improvement plans proposed by several gurus
emphasize primarily the commitment of top management. In this study, role of top management
and quality policy has the second highest correlation with TQM plan. Top management of the hos-
pitals determines an appropriate organization culture, vision, and quality policy. Managers of
healthcare organizations should determine objectives, and set specific measurable goals to satisfy
customer expectations and improve their organizations’ performance. On the other hand, the top
management must provide adequate resources to the implementation of quality efforts. This model
implies that the managers’ role has a direct impact on the financial performance of the hospitals. In
order to increase net profit and revenue, and to reduce cost of quality, hospital managers must
convey their priorities and expectations to their employees.
Employee relations, the third factor, have a sufficient correlation with TQM. In this model,
employee relations have two variables. The first variable is building quality awareness among em-
ployees; the second one is recognition of employees for superior quality performance. Hospitals must
develop formal reward and recognition systems to encourage employee involvement, and support
teamwork. In this model, employee relations have a strong correlation with non-financial perform-
ance factor. Non-financial measures contain reputation, capacity of hospital, new service design, and
new market development. Non-financial performance measures are better indicators of management
effort and reflect the reasons for future financial performance (Hoque, 2003). Therefore, non-
financial measures supplement financial measures in providing support for TQM. Hence, employee
relations have also indirect impact on the financial performance of hospitals.
Fourth factor, process management, which includes such sub-factors as process monitor-
ing, supervision, and preventive equipment maintenance, did not have sufficiently strong influence
on TQM in this model. A possible reason for this might be the high level of personnel compliance
with the implicit and explicit norms and rules of the workplace. Under such circumtances the mar-
ginal contribution to total quality of the inputs used for process management (inspection, supervi-
sion etc.) purposes would be expected to be low. This could explain the low value of the process
management-coefficient in the model.
Limitation and further research:
Sample size must be increased.
Data should be gathered from more than one city in Turkey.
Objective performance indicators should be employed in the analysis. In this study,
data were collected from top managers of hospitals on the basis of their subjective
evaluations.
Structural equation modeling (SEM) or neural network model could be used in the fu-
ture studies to utilize the additional insights they might provide.
After using exploratory factor analysis, confirmatory factor analysis could be used.
Conclusion
TQM primarily focuses on the production of quality goods and services and the delivery
of excellent customer service; however, its success increases when it is extended to the entire
company. This enables the reformation of the corporate culture and the permeation of the new
business philosophy into every facet of organization. The philosophy of doing things right must be
implemented with enthusiasm and commitment throughout the organization – from top to bottom
and the little steps forward (called “Kaizen” by the Japanese) must be viewed as “a race without a
finish”. Consequently, effective use of TQM is a valuable asset in a company’s resource portfolio
– one that can produce important competitive capabilities and be a source of competitive advan-
tage.
Problems and Perspectives in Management, 4/2005 230
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Appendix A
1. Role of Top Management and Quality Policy
1. Extent to which top executives assume responsibility for quality performance.
2. Acceptance of responsibility for quality by major department heads.
3. Degree to which top management (top executive and major department heads) is
evaluated for quality performance.
4. Extent to which top management supports a long term quality improvement process.
5. Extent to which the top management has objectives (Management By Objectives) for
quality performance.
6. Importance attached to quality by top management in relation to cost/revenue objec-
tives.
7. Degree to which top management considers quality improvement as a way to in-
crease profits.
8. Degree of comprehensiveness of the quality plan.
9. Extent to which top management has developed and communicated a Vision for
Quality as part of a Strategic Vision of the Organization.
2. Process Management/Operating Procedures
1. Use of statistical control charts to control processes.
2. Amount of preventive equipment maintenance.
3. Amount of inspection, review or checking of work.
4. Importance of inspection, review or checking of work.
5. Stability of work schedules.
6. Clarity of work or process instructions given to employees.
3. Quality Data and Reporting
1. Availability of cost of quality data in the hospital.
2. Availability of quality data (mortality and morbidity, etc.).
3. Timeliness of quality data.
4. Extent to which quality data (cost of quality, mortality and morbidity, errors, etc.) are
used as tools to manage quality.
5. Extent to which quality data are available to managers and supervisors.
6. Extent to which quality data are used to evaluate supervisor and managerial perform-
ance.
7. Extent to which quality data, control charts, etc. are displayed in work areas.
8. Scope of the quality data includes clinical performance and service/process perform-
ance.
4.Employee Relations
1. Extent to which employee involvement type programs are implemented in the hospi-
tal.
2. Effectiveness of quality teams or employee involvement type programs in the hospi-
tal.
3. Extent to which the employees are held responsible for error free output.
4. Amount of feedback provided to the employees on their quality performance.
5. Degree of participation in quality decisions by hourly/non-supervisory employees.
6. Extent to which quality awareness-building among employees is on-going.
7. Extent to which employees are recognized for superior quality performance.
Problems and Perspectives in Management, 4/2005 234
Appendix B
1. Performance
1. Revenue growth over the last three years.
2. Service quality as perceived by customers.
3. Market share gain over the last three years.
4. Investments in R&D aimed at new innovations.
5. Net profits.
6. Return on investment.
7. Reputation among major customer segments.
8. Capacity to develop a unique competitive profile.
9. Profit to revenue ratio.
10. Cash flow from operations.
11. New product/service development.
12. Market development.
13. Cost per adjusted discharge.
14. Mortality and Morbidity rate.
15. Return on Assets.
16. Employee Turnover.
17. Number of Admissions.
18. Share of net patient revenue.
19. Market Orientation.
Problems and Perspectives in Management, 4/2005 235
AUTHORS OF THE ISSUE
Yoser Gadhoum Ph.D., Département des stratégies des affaires, University of
Quebec in Montreal, Canada
Salih Katircioglu Ph.D., Assistant Professor of Economics, Department of Banking
and Finance, Eastern Mediterranean University, Turkey
Bilge Oney Ph.D., Assistant Professor of Economics, Department of Banking
and Finance, Eastern Mediterranean University, Turkey
Michael Colin Cant School of Business Management, University of South Africa
Cindy Erdis School of Business Management, University of South Africa
Abdul Jumaat bin
Mahajar
Ph.D., Universiti Utara Malaysia, Faculty Business Management,
West Malaysia
Jasmani Binti Mohd
Yunus
Universiti Utara Malaysia, Faculty Business Management, West
Malaysia
Vlado Dimovski Ph.D., Associate Professor, Department of Management and
Organization, Faculty of Economics, University of Ljubljana,
Slovenia
Miha Škerlavaj M.Sc., Assistant, Department of Management and Organization,
Faculty of Economics, University of Ljubljana, Slovenia
Jens Gammelgaard Ph.D., Associate Professor, Department of International
Economics and Management, Copenhagen Business School,
Denmark
Tatiana Zalan PhD, AFAIM, Lecturer, Department of Management, University
of Melbourne, Australia
Geoffrey Lewis PhD, Professorial Fellow, Melbourne Business School, Australia
Rasoava
Rijamampianina
DSSC, DECSA, MBA, DBA, Associate Professor, Graduate
School of Business Administration, University of the
Witwatersrand, South Africa
Teresa Carmichael BSc (Hons), MM(HR), Lecturer, Graduate School of Business
Administration, University of the Witwatersrand, South Africa
Kok Leong Choo Senior Lecturer in Strategic Management and holds an MBA,
University of Wales Institute, Cardiff, UK
Louise van Scheers School of Business Management, University of South Africa
doc_676083778.pdf