Factores Críticos de TQM

1. An instrument for measuring the critical
factors of TQM in Turkish higher
education
Erkan Bayraktara
, Ekrem TatoglubÃ
and Selim Zaimc
a
Faculty of Engineering, Bahcesehir University, Besiktas, Istanbul, Turkey; b
Faculty of Business Administration,
Bahcesehir University, Besiktas, Istanbul, Turkey; c
Faculty of Economics and Administrative Sciences, Fatih
University, Buyukcekmece, Istanbul, Turkey
Driven by increasing competition and intensifying market forces, higher education institutes (HEIs)
find total quality management (TQM) as one of the indispensable tools to adapt to the evolving new
educational environment and to fulfil the expectations of their stakeholders. Based on a thorough
review and synthesis of the quality management literature, this paper identifies 11 critical areas of
TQM in an HEI. Operational measures of the critical factors are developed that can be used
individually or in concert to produce a profile of institution-wide quality management. These
measures are tested for reliability and validity using perceptual data collected from a sample of
144 academics from 22 HEIs in Istanbul, Turkey. Decision makers will be able to use this
instrument to identify the extent of TQM implementation in their institutions, while researchers
will be able to use it for furthering TQM research in HEIs.
Keywords: TQM; implementation; higher education; measurement; Turkey
Introduction
Drawing largely on the ideas of quality gurus including Juran, Feigenbaum, Deming and Crosby,
total quality management (TQM) has been widely recognised as a management philosophy.
TQM encompasses organisation-wide efforts towards customer satisfaction through continu-
ously increasing the performances of the goods, services and employees. The most attractive
features of TQM are continuous learning, leadership and flexibility in the creation of an environ-
ment where organisation-wide goals are shared by everyone, and an organisation’s processes are
focused directly on customers.
TQM is the culture of an organisation committed to customer satisfaction through continuous
improvement. This culture varies from one country to another and between different industries,
but has certain essential principles, which can be implemented to secure greater market share,
increased profits and reduced costs (Kanji & Wallace, 2000). Management awareness of the
Total Quality Management
Vol. 19, No. 6, June 2008, 551–574
Ã
Corresponding author. Email: ekremt@bahcesehir.edu.tr
1478-3363 print/1478-3371 online
# 2008 Taylor & Francis
DOI: 10.1080/14783360802023921
http://www.informaworld.com

2. importance of TQM, alongside business process re-engineering and other continuous improve-
ment techniques was stimulated by the benchmarking movement to seek, study, implement and
improve on best practices (Zairi & Ahmed, 1999). A review of extant literature on TQM and
continuous improvement programs identifies 12 common aspects: committed leadership,
adoption of TQM, communication of TQM, closer customer relationships, benchmarking,
increased training, open organisation, employee empowerment, zero defects mentality, flexible
manufacturing, process improvement and measurement.
Furthermore, to determine critical factors of TQM, various studies were undertaken and differ-
ent instruments were developed by individual researchers and institutions, such as the Malcolm
Baldrige Award, EFQM (European Foundation for Quality Management) and the Deming
Prize Criteria. Based on these studies, a wide range of management issues, techniques, approaches
and systematic empirical investigations have been generated.
Saraph et al. (1989) developed 78 items related to TQM practices, which were classified into
eight critical factors to measure the performance of TQM in an organisation. They labelled these
critical factors as: role of divisional top management and quality policy, role of the quality
department, training, product and service design, supplier quality management, process manage-
ment, quality data and reporting and employee relations.
Flynn et al. (1994) developed another instrument in which they identified seven quality factors
of TQM. These are top management support, quality information, process management, product
design, workforce management, supplier involvement and customer involvement. This instru-
ment is in close resemblance to the preceding instrument developed by Saraph et al. (1989).
In a later study, Flynn et al. (1995) measured the impact of TQM practices on quality perform-
ance and competitive advantage.
On the other hand, Anderson et al. (1994) developed the theoretical foundation of quality
management practice by examining Deming’s 14 points. They reduced the number of factors
from 37 to seven using the Delphi Method, which consists of visionary leadership, internal
and external cooperation, learning, process management, continuous improvement, employee
fulfilment and customer satisfaction.
In a similar vein, using the Malcolm Baldrige Award criteria, Black and Porter (1996) ident-
ified ten empirically validated critical TQM factors, which include corporate quality culture,
strategic quality management, quality improvement measurement systems, people and customer
management, operational quality planning, external interface management, supplier partner-
ships, teamwork structures, customer satisfaction orientation and communication of improve-
ment information. In addition to Black and Porter (1996), various authors also assessed the
validity of Malcolm Baldrige Award Criteria (Wilson & Collier, 2000; Flynn & Saladin, 2001).
Ahire et al. (1996) developed 12 integrated quality management constructs, which were
labelled as: supplier quality management, supplier performance, customer focus, statistical
process control usage, benchmarking, internal quality information usage, employee involve-
ment, employee training, design quality management, employee empowerment, product
quality and top management commitment.
While TQM has been used in the manufacturing area for a long time, service applications of
TQM are relatively new. Implementation of TQM principles is also applicable to higher edu-
cation (Owlia & Aspinwall, 1997). As a standalone process, TQM has the potential of improving
quality in educational institutions and achieves continuous improvement (Kanji et al., 1999).
The initial attempts to implement TQM in US higher education institutions (HEIs) date back
to the early 1980s (Kanji et al., 1999). TQM was practised in 78 universities in 1991 where it
was later expanded to 216 universities in 1996 (Klaus, 1996). According to Burkhalter (1996),
552 E. Bayraktar et al.

3. 50% of universities in the US had some sort of quality councils. In the UK, the first TQM
initiatives in HEIs were experienced in the late 1980s and early 1990s (Kanji & Malek,
1999). In contrast to the US, the impetus to introduce TQM in the UK stemmed from the gov-
ernment (Owlia & Aspinwall, 1997). A 1998 survey on HEIs in the UK indicated that the UK
HEIs were hardly involved in TQM and had a lack of interest in adopting it in the future (Kanji &
Malek, 1999).
Jaraiedi and Ritz (1994) noted that university revenue shortfalls and expenditure pressures in
the US were increasing, while total university enrolment was declining. Given the imperatives of
globalisation, classical education systems have been far from fulfilling the needs of the individ-
uals and societies (Vazzana & Winter, 1997). Higher education has also been driven by increas-
ing commercial competition imposed by economic forces, namely market orientation (Owlia &
Aspinwall, 1997). In addition, improving student/staff morale, increasing productivity and deli-
vering higher quality services to both internal and external customers are emerging as absolute
necessities. TQM may integrate and improve inputs, processes and outputs in contrast to accred-
itation and assessment at universities (Owlia & Aspinwall, 1997).
Vazzana et al. (2000) identify three main areas to implement TQM in higher education: cur-
riculum, non-academic functions and academic administration. Even though a relatively high
use of TQM was reported by administrative, support and academic departments, only a small
number of institutions (17% in 1995 and 15% in 1998) employed a complete TQM model
(Vazzana et al., 1997, 2000). Koch and Fisher (1998) also express that TQM is only marginally
useful in the rapidly changing environment that HEIs inhabit today. In their empirical study,
Elmuti et al. (1996) assessed the status of TQM practices in HEIs in the US. Almost one
third of respondents failed to achieve their targets on improving quality of teaching and
research. Major reasons for failure were due to implementation of TQM programs without a
full grasp of their nature, tenure system in the US and autonomous role of the professors in
academia. In the implementation of TQM in HEIs, there are number of difficulties such as
preparation of curriculum, teaching continuous improvement process and increasing research
activities (Mergen et al., 2000). The other barriers for TQM in HEIs are lack of agreement
on the meaning of quality and academic freedom, unwillingness to change, compartmentalisa-
tion, lack of competition and conformance to minimum requirements (Owlia & Aspinwall,
1997).
Measurement is also an important issue for TQM applications. Many TQM concepts such as
customer satisfaction and employee involvement are difficult to be systematically measured. The
purpose of this study is to develop an instrument to measure and evaluate TQM practices in
Turkish HEIs. To date, there has been no systematic attempt in the extant literature to organise
and synthesise the various sets of critical factors in HEIs identified by different authors, nor have
measures of overall organisational quality management or of any individual critical factor been
proposed. Based on a thorough review and synthesis of the quality literature, this paper identifies
11 critical areas of TQM in a HEI. Operational measures of the critical factors are developed that
can be used individually or in concert to produce a profile of institution-wide quality manage-
ment. These measures are tested for reliability and validity using perceptual data collected
from a sample of 144 academics from 22 HEIs in Istanbul.
The remainder of the paper is organised as follows. The next section briefly reviews the TQM
practices in Turkish HEIs. The section after provides an explanation of the critical factors of
TQM in HEIs. The process of developing the measurement instrument is then described.
Reliability and validity tests of the instrument are performed. Conclusions are provided in the
final section.
Total Quality Management 553

4. TQM practices in Turkish HEIs
Turkish higher education has been characterised by a highly centralised and mechanistic struc-
ture in which the Turkish Higher Education Council (Yu¨kseko¨g˘retim Kurulu – YOK) is the only
authority for the regulation of higher education. Since there is a strong demand for higher edu-
cation in Turkey, there is a nationwide university entrance exam for placement held annually.
The number of applicants as of 2005 was 1,851,674, while, in 2004, only 532,273 were able
to register onto a program and nearly 5% of them were enrolled at privately held universities
(YOK, 2005). These numbers clearly demonstrate how challenging access is to higher education
in Turkey where only one-third of the applicants are admitted each year. According to a YOK
strategy report (YOK, 2006), the number of students has increased 3.8 times in post-secondary
programs, 1.7 times in undergraduate programs, 2.6 times in graduate programs and 2.1 times in
total over the last 12 years.
Since the early 1980s, the number of Turkish HEIs has also increased dramatically. In 1981,
there were only 27 state-owned universities. This number has more than tripled, reaching at
present 93, of which 25 are privately held universities (YOK, 2006). The average number of stu-
dents per instructor is 59 for post-secondary programs and 29 for undergraduate programs. Over
two-thirds of lecturers are overloaded with heavy course loads and 60% of them have problems
with using a foreign language effectively (YOK, 2006). These figures are in fact much higher
than those in most western countries and lead to serious quality problems in education. In
addition, the heterogeneous structure of higher education has been further inflated due to
regional differences of educational opportunities and the distribution of resources (Mizikaci,
2003).
Quality assurance and standardisation among Turkish HEIs have emerged as a result of the
need to eliminate worries about the quality of this fairly fast introduction of newly established
HEIs, and have gained popularity especially after the Sorbonne and Bologna declarations (YOK,
2006; Mizikaci, 2003). Some of these efforts date back to the early 1990s, and some engineering
programs of leading universities such as METU, Bosporus, Marmara and ITU are accredited by
ABET (Accreditation Board for Engineering and Technology) to be recognised internationally
as a measure of quality assurance (YOK, 2006; TUSIAD, 2003). Recently, seven Turkish uni-
versities have participated in the European Universities Association (EUA), which aims to
spread and promote the quality culture among the participants (YOK, 2006).
TQM applications have been popular among Turkish HEIs since the late 1990s. This has been
an era of massive introduction of privately held universities into Turkish higher education.
Although there has been a huge demand for higher education in Turkey, it was a real challenge
for these new HEIs to attract students who were not used to paying their tuition fees. The pro-
vision of a new teaching environment and better quality services to the students was the main
challenge faced by many of these institutions. TQM was treated as a new promising tool. The
following factors have further contributed to the increasing popularity of TQM among
Turkish HEIs:
. increasing competition among the newly founded HEIs (Mizikaci, 2003) and the growing
need for market orientation;
. creating job opportunities for graduates and promoting the applied research and knowledge
production (YOK, 2006);
. better fulfilment of the needs and expectations of stakeholders from an academic program;
. increasing the visibility and accountability of management (YOK, 2006);
554 E. Bayraktar et al.

5. . the need for a high quality education system that continuously evolves and adapts to recent
developments;
. the desire to contribute to the regional and national developments through better public
cooperation (YOK, 2006);
. cost effectiveness (YOK, 2006).
The TQM model has been taught in several universities at both undergraduate and graduate
levels in Turkey. Most TQM principles are found easy to apply to teaching environments
(Sisman, 1997). At the school of foreign languages of the Middle East Technical University,
some of the TQM principles have been implemented since 1991 for the solution of employee
problems through quality circles, and for process improvement (Peker, 1998). Marmara Univer-
sity Engineering School, in 1993, was one of the first universities implementing TQM principles
(Koksal, 1998; Mizikaci, 2003) and also one of the finalists for the EFQM award in 2000.
Bas¸kent University founded a TQM Centre in 1996 (Aksit, 1998; Mizikaci, 2003). It started
to work on the quality systems for educational institutes in 1995 and was certified with ISO
9001 in 1998. Several other universities also have similar efforts for TQM implementation in
their educational processes.
While most of the universities in Turkey have been involved in TQM or other quality-related
programs, a large number were not persistent enough to pursue a complete TQM program. Many
applications were confined to a particular school or a department of a university and depended
heavily on the administrators. Mizikaci (2003) reports that TQM implementation at Bas¸kent
University was successful in documentation systems and procedures, but not at a desired
level in terms of educational impact, academic improvement and customer satisfaction.
Based on a recent YOK regulation, accepted in September 2005, all HEIs in Turkey are
required to establish an ‘Academic Evaluation and Quality Improvement Committee’ in order
to monitor the educational, training and research activities of HEIs along with their administra-
tive services, to improve their quality and to get approval and recognition of their quality levels
from independent ‘external examiners’. This clearly emphasises the concerns for quality in
HEIs. Mizikaci (2003) states that the adaptation process of TQM implementation mainly fails
on questioning the effectiveness of the process, and measuring the impact of the implementation
on the system. These issues are related to evaluation and assessment of the implementation
process based on the country specific culture, policies and objectives.
Critical factors of TQM implementation in HEIs
Institution-wide implementation of quality management requires developing instruments to
measure multidimensional features of quality management practices. Without a proper measure-
ment system, shortcomings of the current implementation and areas of further improvements
may not be easy to identify (Mizikaci, 2003; Grant et al., 2002). This study, therefore, aims
at developing an instrument for measuring quality management practices in Turkish HEIs. To
achieve this objective, a number of items for measuring the underlying constructs of quality
management implementation were developed based on an extensive review of quality manage-
ment literature, expert guidance and views of colleagues.
The scales developed here for HEIs are largely an adaptation of the relevant constructs
initially developed for manufacturing companies (Black & Porter, 1996; Saraph et al., 1989;
Flynn et al., 1994; Anderson et al., 1994; Ahire et al., 1996; Zhang et al., 2000; Demirbag
et al., 2006). Owlia and Aspinwall (1997) also express that the type of activities carried out
Total Quality Management 555

6. in manufacturing is not so different from those in HEIs, and suggest a checklist with ten factors
for TQM implementation on HEIs. Tang and Zairi (1998) apply five factors to benchmark higher
education with financial services. Kanji et al. (1999) and Kanji and Malek (1999) identify nine
critical success factors to compare the state of the art of TQM implementations in the UK, the US
and Malaysia. These factors are summarised in Table 1. TQM implementation scales considered
in this study are as follows: leadership, vision, measurement and evaluation, process control and
improvement, program design, quality system improvement, employee involvement, recog-
nition and reward, education and training, student focus and other stakeholders focus. A brief
explanation of these scales is presented in the following subsections.
Leadership
As a well-accepted TQM implementation presumption, the European Quality Award and
Malcolm Baldrige Quality Award emphasise the role of top management commitment to the
TQM efforts. The authors, including Owlia and Aspinwall (1997), Tang and Zairi (1998),
Kanji et al. (1999) and Kanji and Malek (1999), incorporate leadership as a primary construct
in their instruments and comparisons. Similarly, some authors (Sirvanci, 2004; Lomas, 2004)
have also emphasised the importance of appropriate leadership on the success of the TQM
implementations. Top management of HEIs should be aware of the needs of TQM: understand
the importance of employee involvement; and concentrate on long-term stable performance
measures while actively showing their support to TQM practices through their actions.
Vision
A vision of HEI serves its public declaration of what kind of organisation to become in the
future. Organisational values, beliefs and business practices are good indicators of the vision
statement communicated and practised throughout the organisation. Different vision statements,
obviously, may lead to different policies on TQM implementations and require different per-
formance measures (Bayraktar, 2006).
Measurement and evaluation
In any implementation, the measurement of degree of success is an absolute necessity to identify
the area of improvements. Measurement and then evaluation are nearly impossible without
clearly defined performance measures, even though it is difficult to identify the ones universally
accepted for all HEIs (Bayraktar, 2006). While measurement of the administrative processes of a
HEI is relatively simple, it is much more difficult to measure the level of success on many aca-
demic processes such as student learning, performance of instructors and institutions. The
attempts to identify the performance measures and evaluations of these measures are important
indicators of TQM efforts. To this end, Owlia and Aspinwall (1996), and Lagrosen et al. (2004)
investigated the performance metrics and quality dimensions for HEIs. Gozacan-Borahan and
Ziarati (2002) proposed a quality criteria checklist for Dogus University in Turkey. This check-
list includes the following sections: program management and operation; curriculum design and
structure; teaching, learning and assessment; student support and guidance; learning resources;
quality assurance and enhancement; student progression and achievement.
556 E. Bayraktar et al.

7. Table 1. Comparison of TQM dimensions in higher education.
Our instrument
Checklist of Owlia and
Aspinwall (1997)
Benchmarking items of
Tang and Zairi (1998)
Critical success factors
of Kanji et al. (1999)
† Leadership
† Vision
† Measurement and evaluation
† Process control and improvement
† Program design
† Quality system improvement
† Employee involvement
† Recognition and reward
† Education and training
† Student focus
† Other stakeholders’ focus
†Top management commitment
†Strategic planning
†Organisation for quality
†Employee involvement and team working
†Training for quality
†Design management
†Process management
†Supplier quality management
†Information and analysis
†Customer focus and satisfaction
†Leadership
†Policy and strategy
†People management
†Resource management
†Process management
†Leadership
†Continuous improvement
†Prevention
†Measurement of resources
†Process improvement
†Internal customer satisfaction
†External customer satisfaction
†People management
†Teamwork
TotalQualityManagement557

8. Process control and improvement
This is a natural consequence of measurement and evaluation. As HEIs are considered as service
organisations, comprising several processes, they may require a different type of organisational
structure (Sahney et al., 2004a; Bayraktar, 2006). This new way of looking into HEIs may help
reduce the tension on TQM applications. Administrative and academic processes for HEIs
should be measured, evaluated, controlled and improved regularly. Facility maintenance such
as cleaning of the overall building, functionality of classrooms, laboratories and A/C system,
and ‘fool proof’ process maintenance such as student enrolments and course registrations are
a few areas to control and improve through comprehensive statistical data collection.
Program design
Academic programs are the main products of HEIs to attract and satisfy the needs of the stake-
holders such as students, industry, academy and community at large. These programs should be
reviewed regularly considering the needs of the stakeholders and technological advances, and
should be updated if necessary. Interdisciplinary study areas as well as necessary facilities to
conduct such types of study should be considered on the development of curriculum and pro-
grams. SERVQUAL and Quality Function Deployment (QFD) approaches may be utilised in
the program design as tools to penetrate TQM into the program development stage (Sahney
et al., 2004b).
Quality system improvement
A well-documented quality assurance system is needed in order to guarantee the consistency of
the quality related issues in HEIs. ISO 9000 based standardisation with all the critiques may help
to create a solid basis for quality discussions (Mizikaci, 2003; Sakthivel et al., 2005). Clearly
stated process flow charts and documents may increase the consistency and traceability of the
processes in case of error. Gozacan-Borahan and Ziarati (2002) reported that the quality criteria
checklist has helped lead to the development of an ISO-based TQM implementation.
Employee involvement
Without the clear support and contributions of the employees, a successful TQM implementation
will not be accomplished. TQM is an organisation-wide effort to generate a quality culture. With
active participation, negative attitudes of the employees towards TQM implementation may be
eliminated. Cross-functional team formations, collaboration among employees, voluntary
employee participation to TQM studies, and acceptance of employee suggestions regarding
the system are some indicators of employee involvement in HEIs.
Recognition and reward
The recognition of excellence on TQM-related efforts by any employee, department or school
should be rewarded as a means of supporting a particular performance level. In order to stimulate
employee commitment to TQM implementation, performance measures for HEIs may need to be
modified to take the quality efforts into consideration.
558 E. Bayraktar et al.

9. Education and training
Even for HEIs, educating and training employees on TQM implementation and its related con-
sequences are crucial for the success of the program. The training needs of academic and non-
academic staff should be identified separately and considered as a quality awareness workshop.
Missing skill sets should be determined and new training should be scheduled to fulfil these gaps.
Necessary financial resources should be available for such efforts.
Student focus
While creating a bit of controversy, students are the main customers of HEIs as suggested by
TQM terminology (Kanji & Malek, 1999; Sirvanci, 2004; Sahney et al., 2004b). A close
relationship with students within the academic ethics is a key to recognising their needs. Collec-
tion and evaluation of student complaints, careful consideration of course-evaluations, the
support of student club activities, and the follow-ups of the alumni are some of the key concerns
of a successful TQM program to be considered as being student-focused.
Other stakeholders’ focus
Apart from students, there are many other stakeholders for HEIs (Kanji & Malek, 1999;
Bayraktar, 2006) such as families, businesses/industry, society and employees of HEIs. The
needs and expectations of a particular business or industry as well as society in general
should be systematically observed and be considered as a feedback to the HEIs’ academic
and continuous education programs. Employees of HEIs are also highly important in delivering
the actual services to the customers of HEIs. The success of a TQM implementation program
really hinges on to what extent the employees are able to understand the whole process and
vision of the institution.
Research methodology
Survey instrument
A questionnaire for this survey was carefully designed to be easy to complete and restricted to
five-point scales ranging from 1 ‘strongly disagree’ to 5 ‘strongly agree’. The preliminary ques-
tionnaire was also discussed with a number of academicians involved in senior administrative
posts in higher education institutions, who also had experience in quality management appli-
cations in HEIs. A pilot study based on a series of semi-structured interviews was conducted
in two different schools (schools of business and engineering) of a privately held university
in Istanbul in order to confirm that the items of the questionnaire were clear and unambiguous.
Based on their comments, the draft questionnaire was subjected to a series of tests and revisions
to arrive at the final form.
The final version of the questionnaire is composed of two main parts. The first part included 61
items that are related to 11 critical success factors of TQM implementation in higher education
institutions. The second part attempts to capture the demographic characteristics of the respon-
dents. The Appendix lists the English version of all 11 constructs with their constituent items.
Total Quality Management 559

10. Sample and data collection
A postal survey was considered to be the most appropriate method for collecting primary data for
empirically testing and validating the instrument. The sampling frame of this survey was com-
posed of the Turkish universities in Istanbul. For centuries, being the largest city of Turkey,
Istanbul has been undisputedly the main business and cultural centre, generating nearly 23%
of Turkish GNP. As of March 2006, there are 93 universities (68 state and 25 private) in
Turkey (www.yok.gov.tr) where 22 of them (7 state and 15 private) are located in Istanbul
alone. Similarly, in terms of the number of total academics in Turkish HEIs, over 17% of
them were employed by HEIs in Istanbul (YOK, 2005). The potential respondents for the
survey were identified as academics who were familiar with the university’s quality manage-
ment practices. Each university administration was contacted to identify the names and
addresses of appropriate academics who are most knowledgeable about the university’s
quality management applications. Generally, people from business schools, industrial engineer-
ing departments and administrative bodies constituted potential respondents due to their famili-
arity with the subject. Eventually, the survey questionnaire was mailed to a total of 225
academics identified as potential respondents from 22 HEIs in Istanbul.
A total of 155 questionnaires were returned of which 11 were eliminated owing to largely
incomplete or unanswered questions. As a whole, the response rate was 0.64 (144/225),
which is satisfactory given the nature of respondents. The key characteristics of respondents
are summarised in Table 2.
Table 2. Characteristics of respondents.
Characteristics n %
Ownership
State 73 50.7
Private 71 49.3
Academic rank
Professor 31 21.5
Associate Professor 41 28.5
Assistant Professor 72 50
Length of employment
Less than a year 29 20.1
1–3 years 47 32.6
4–6 years 27 18.8
More than 6 years 41 28.5
Administrative position
Rector/Deputy Rector 3 2.1
Dean/Deputy Dean 24 16.6
Department Chair/Deputy Chair 22 15.4
Other 26 18
No administrative duty 69 47.9
Age
30 and younger 39 27.1
31–40 57 39.6
41–50 23 15.9
51 and older 25 17.4
N 144 100
560 E. Bayraktar et al.

11. Empirical analysis of the instrument
In this research, we followed the updated measure development paradigm proposed by Anderson
and Gerbing (1988) as well as the traditional procedure suggested by Churchill (1979) to develop
better measures of TQM constructs. To operationalise the constructs, the following properties of
the measures are considered (Bagozzi & Phillips, 1982; Venkatraman, 1989): reliability (internal
consistency of operationalisation) and validity (content, construct, convergent and discriminant
validity).
The instrument that will be developed in this study consists of 11 scales (61 items). Table 3 pre-
sents the descriptive statistics for the scales that have to be empirically tested and validated. The
following subsections will detail how the reliability and validity of these scales are evaluated.
Item analysis
This is a method to check the appropriateness of the items assigned to the scales and it considers
the correlation of each item with each scale. This method has been generally used to evaluate the
assignment of items to scales for developing an instrument (Saraph et al., 1989; Zhang et al.,
2000). So, we decided to conduct this analysis in order to ascertain whether items had been
appropriately assigned. Table 4 presents the correlation matrix for the 11 scales and their
measurement items. As is readily apparent from Table 4, the items were highly correlated
with the scales they intend to measure. Any correlation score of less than 0.5 indicates that
the associated item can not explain adequately the variance with the rest of the items in that scale.
Table 3. Descriptive statistics.
Item No.
Scales 1 2 3 4 5 6 7 8 9
1. Leadership Mean 3.08 3.06 3.06 3.20 2.90 3.29 3.19 3.01 3.24
SD 1.17 1.19 1.10 1.15 1.08 1.08 1.05 1.17 1.26
2. Vision Mean 3.57 2.84 3.40 2.92 2.68 2.89
SD 1.17 1.19 1.09 1.05 1.06 1.10
3. Measurement and evaluation Mean 2.83 3.22 3.27 2.81 3.24 3.08 3.42
SD 1.04 1.08 1.11 1.07 1.05 1.08 1.06
4. Process control and improvement Mean 3.60 3.06 3.67 3.44 2.83 2.83
SD 1.12 0.99 1.01 1.04 0.94 1.14
5. Program design Mean 2.87 3.47 2.94 3.39 3.70
SD 1.15 1.15 1.04 1.17 1.04
6. Quality system improvement Mean 2.98 2.93 2.50
SD 1.12 1.16 0.98
7. Employee involvement Mean 3.03 2.79 2.73 2.91 3.03 3.01
SD 1.12 1.00 1.03 1.04 1.08 1.17
8. Recognition and reward Mean 2.49 2.53 2.46 3.23
SD 1.14 1.07 1.07 1.19
9. Education and training Mean 3.33 2.86 2.63 2.83 2.95
SD 1.10 1.01 1.17 1.03 1.18
10. Student focus Mean 3.53 3.61 3.98 3.29
SD 0.99 1.32 0.96 1.00
11. Other stakeholders’ focus Mean 2.97 3.22 2.42 3.17 2.91 3.02
SD 1.11 1.08 1.19 1.02 1.15 1.03
Note: SD ¼ Standard Deviation.
Total Quality Management 561

12. With the exception of one item (item 4 of scale 8), all of the correlation values in Table 4 were
greater than 0.5, indicating that all items were appropriately assigned to scales. The items with
correlation scores of lower than 0.5 do not share adequate variance with the rest of the items in
that scale, which in turn should be omitted from the scale. Hence, the mentioned item with a
correlation value of less than 0.5 (0.461) was deleted from the scale.
Reliability
The reliability of the scales is related to the homogeneity of their items. It is a measure of the
ability to produce the same results on repeated trials. Cronbach’s alpha is commonly used to
measure internal consistency of the scales. It is based on the average correlation between
items within a test. In order initially to assess the internal consistency of the scales, an item inter-
correlation matrix is constructed for each scale. Those items that have a relatively low corre-
lation with the other items in their scale are deleted, prior to further analysis. Cronbach’s
alpha is then calculated for each scale (Cronbach, 1951). Although an alpha value of 0.70
and higher is often considered the criterion for internally consistent established scales (Hair
et al., 1998), Nunnally (1978) suggests the alpha value of 0.50 and 0.60 is acceptable in the
early stages of research. Table 5 lists Cronbach’s alpha values of the scales developed. All
the scale measures of TQM implementation are over 0.80, thus exhibiting a satisfactory level
of construct reliability. This establishes the internal consistency of the dimensions being
studied and is reliable for this research. Typically, we employ the Cronbach alpha coefficient
as a measure of reliability; however, this coefficient is based on a restricted assumption assigning
equal importance to all indicators. Werts et al. (1974) suggested an alternative measure (rc)
which represents the ratio of trait variance to the sum of the trait and error variances. Table 5
shows that all rho (rc) indices are greater than 0.5, denoting a satisfactory level of internal
consistency of the dimensions being studied.
Validity
Validity is defined as the extent to which the instrument measures what it intends to measure. In
this survey, the validity of the instrument was assessed by investigating its content, construct,
Table 4. Item to scale correlation matrix.Ã
Item No.
Scales 1 2 3 4 5 6 7 8 9
1 0.814 0.839 0.868 0.776 0.791 0.700 0.720 0.746 0.767
2 0.771 0.845 0.837 0.803 0.835 0.737 – – –
3 0.786 0.735 0.780 0.810 0.862 0.829 0.785 – –
4 0.761 0.755 0.692 0.765 0.834 0.714 – – –
5 0.817 0.771 0.757 0.844 0.752 – – – –
6 0.963 0.965 0.707 – – – – – –
7 0.818 0.838 0.752 0.866 0.846 0.714 – – –
8 0.923 0.868 0.908 0.461ÃÃ
– – – – –
9 0.813 0.852 0.743 0.774 0.784 – – – –
10 0.788 0.806 0.736 0.752 – – – – –
11 0.839 0.735 0.832 0.830 0.770 0.802 – – –
Note: Ã
Significant at the 0.01 level (2-tailed); ÃÃ
low correlation value (,0.5).
562 E. Bayraktar et al.

13. convergent and discriminant validity. Churchill (1987) notes that the validity of a measuring
instrument can be assessed by seeking evidence of its pragmatic content and construct validity.
Content validity refers to the agreement among professionals that a scale logically appears to
reflect accurately what it intends to measure (Zikmund, 1991), although its determination is sub-
jective and judgemental (Emory, 1980). The content validity of the survey instrument was estab-
lished in several steps. First, an extensive review of quality management literature was
undertaken to develop the questionnaire items. Next, preliminary questionnaire items were dis-
cussed with a number of academicians and administrators working for Turkish universities, who
were closely familiar with TQM practices in HEIs. Finally, a pilot study based on a series of
semi-structured interviews was conducted in two different schools of a privately held university
in Istanbul in order to give the final shape to the survey instrument.
Construct validity is performed to check whether there exist any subscales within the same
construct. The construct validity can be assessed by factor analysis. The primary purpose of
factor analysis is to produce a parsimonious set of new composite dimensions from a large
number of variables with a minimum loss of information (Hair et al., 1998). There are two
forms of factor analysis, namely explanatory factor analysis (EFA) and confirmatory factor
analysis (CFA). EFA is designed for a situation where links between the observed and latent
variables are unknown or uncertain. The analysis helps determine how and to what extent the
observed variables are linked to their underlying factors. Factor loadings are used to delineate
these relations. The general purpose of CFA, however, is to confirm a pre-specified relationship
between indicators and latent variables. Given the nature of this study, both EFA and CFA would
have to be employed to assess construct validity.
First, EFA was performed and each scale was subjected to factor analysis separately. The
results of EFA are shown in Table 6, and indicate that all of the items constituting each
factor had factor loadings that were greater than 0.50. The scales with factor loadings of 0.50
or greater are considered very significant (Hair et al., 1998). In this study, a factor loading of
0.50 was used as the threshold value. The EFA showed that the items in all of the 11 scales
formed a single factor.
The second stage is also known as testing the measurement model where TQM scales were
tested using the first-order confirmatory factor model to assess construct validity using the
maximum likelihood method. The results consistently supported the factor structure for TQM
that was initially shown by the EFA. Table 7 shows the measurement model for TQM practices
Table 5. Internal consistency of the scales.
Scales
Number of
items
Number of
deleted items Cronbach’s alpha Rho (rc)
1. Leadership 9 No 0.921 0.935
2. Vision 6 No 0.872 0.907
3. Measurement and evaluation 7 No 0.892 0.920
4. Process control and improvement 6 No 0.839 0.888
5. Program design 5 No 0.845 0.894
6. Quality system improvement 3 No 0.892 0.940
7. Employee involvement 6 No 0.880 0.920
8. Recognition and reward 4 1 0.870 0.898
9. Education and training 5 No 0.848 0.897
10. Stakeholder focus 4 No 0.774 0.841
11. Other stakeholders’ focus 6 No 0.888 0.918
Total Quality Management 563

14. Table 6. Factor analysis of each scale.
Factor loadings
Scales
Number of
factors MSAÃ
Total
eigenvalues 1 2 3 4 5 6 7 8 9
%
variance
explained
1 1 0.910 5.544 0.830 0.850 0.876 0.781 0.794 0.685 0.704 0.751 0.771 61.599
2 1 0.838 3.685 0.753 0.840 0.830 0.810 0.795 0.659 – – – 61.423
3 1 0.875 4.272 0.775 0.698 0.754 0.803 0.870 0.828 0.728 – – 61.027
4 1 0.821 3.369 0.750 0.760 0.679 0.784 0.833 0.678 – – – 56.152
5 1 0.819 3.088 0.767 0.781 0.781 0.856 0.740 – – – – 61.769
6 1 0.718 2.471 0.925 0.934 0.863 – – – – – – 82.383
7 1 0.827 3.807 0.818 0.846 0.753 0.859 0.826 0.659 – – – 63.448
8 1 0.777 2.681 0.895 0.828 0.890 0.634 – – – – – 67.013
9 1 0.832 3.144 0.794 0.875 0.748 0.740 0.800 – – – – 62.886
10 1 0.773 2.387 0.811 0.763 0.757 0.758 – – – – – 59.672
11 1 0.872 3.864 0.842 0.727 0.830 0.837 0.762 0.809 – – – 64.401
Note: Ã
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
564E.Bayraktaretal.

15. and summarises the results of assessments for unidimensionality for 11 dimensions. It provides
the following model statistics for the assessment of goodness-of-fit: x 2
statistics, its associated
degrees of freedom, p-value of significance, GFI, AGFI, CFI, and Tucker–Lewis index. One can
conclude that each of the 11 dimensions achieves unidimensionality and convergent validity at
monomethod levels of analysis. To exemplify, nine items constituting the leadership dimension
were subjected to CFA using the AMOS computer program (Arbuckle & Wothke, 1999). The x 2
statistic was 21.641 (degrees of freedom ¼ 16, p . 0.05), with the x 2
/df ratio having a value of
1.35, which is less than 2.0 (it should be between 0 and 3 with lower values indicating a better
fit). The goodness-of-fit index (GFI) was 0.97 and the adjusted goodness-of-fit (AGFI) index was
0.915. These scores are very close to 1.0 (a value of 1.0 indicates perfect fit). The comparative fit
index (CFI) was 0.993, while the Tucker–Lewis coefficient (TLI) was 0.984. All indices are
close to a value of 1.0 in CFA indicating that the measurement models provide good support
for the factor structure determined through the EFA.
Convergent validity is the extent to which indicators of a TQM construct converge or share a
high proportion of variance in common (Hair et al., 1998). Table 7 also shows that most of the fit
indices are within the acceptable range as given by Bentler (1992) for each construct. This pro-
vides first-hand support for reliability and convergent validity of the scales. We further looked at
the significance of individual factor loadings of each constituent item. All the individual factor
loadings were found to be highly significant, giving support to convergent validity (Anderson &
Gerbing, 1988). We also calculated the average variance extracted (AVE) for each scale. These
values are shown in Table 7. The values of AVE were higher than the recommended value of
0.50, providing further support to convergent validity of scales.
The standardised regression weights for all variables constituting each dimension were also
found to be significant ( p , 0.01), as shown in Table 8.
Discriminant validity refers to the degree to which measures of different dimensions of TQM
are unique from each other. According to Venkatraman (1989, pp. 953–54), ‘this is achieved
when measures of each dimension converge on their corresponding true scores (which is
unique from other dimensions) and can be tested that the correlations between pairs of dimensions
are significantly different from unity.’ Table 9 reports the results of 55 pair-wise tests conducted
for discriminant validity. Fifty-three of the 55 tests indicated strong support for the discriminant
Table 7. Initial confirmatory factor analysis results.
Dimension
Number of
indicators x2
df p-value GFI AGFI CFI TLI AVE
Leadership 9 21.64 16 0.16 0.97 0.92 0.99 0.98 0.61
Vision 6 9.67 6 0.14 0.98 0.92 0.99 0.98 0.62
Measurement and evaluation 7 9.91 9 0.36 0.98 0.94 0.99 0.99 0.62
Process control and improvement 6 10.84 8 0.21 0.98 0.94 0.99 0.98 0.58
Program design 5 5.98 3 0.11 0.98 0.92 0.99 0.96 0.62
Quality system improvement 3 — — — — — — — 0.83
Employee involvement 6 4.55 5 0.47 0.99 0.96 1.00 1.00 0.67
Recognition and reward 4 0.38 2 0.83 0.99 0.99 1.00 1.00 0.69
Education and training 5 3.85 4 0.43 0.99 0.96 1.00 1.00 0.64
Student focus 4 1.79 2 0.41 0.99 0.97 1.00 1.00 0.62
Other stakeholders’ focus 6 11.41 7 0.12 0.98 0.92 0.99 0.98 0.58
Note: — CFA results cannot be obtained due to inadequate number of variables constituting this dimension.
Total Quality Management 565

16. Table 8. Confirmatory factor analysis of TQM practices.
Description
Regression
weight t-valueÃ
Description
Regression
weight t-valueÃ
Scale 1: Leadership Item 4 0.670 7.009
Item 1 0.866 — Item 5 0.845 8.326
Item 2 0.840 12.015 Item 6 0.621 6.564
Item 3 0.868 14.301 Scale 5: Program design
Item 4 0.718 8.824 Item 1 0.670 —
Item 5 0.777 9.869 Item 2 0.721 7.072
Item 6 0.600 7.641 Item 3 0.654 6.669
Item 7 0.719 8.756 Item 4 0.849 8.251
Item 8 0.688 9.107 Item 5 0.714 7.163
Item 9 0.712 9.279 Scale 6: Quality
system improvement
Scale 2: Vision Item 1 0.899 —
Item 1 0.748 — Item 2 0.931 14.268
Item 2 0.792 9.260 Item 3 0.747 10.969
Item 3 0.832 9.486 Scale 7: Employee
involvement
Item 4 0.807 8.189 Item 1 0.657 —
Item 5 0.713 8.079 Item 2 0.738 11.564
Item 6 0.508 5.823 Item 3 0.750 7.487
Scale 3: Measurement
and evaluation
Item 4 0.864 8.061
Item 1 0.812 — Item 5 0.784 7.466
Item 2 0.590 7.016 Item 6 0.596 6.862
Item 3 0.653 7.783 Scale 8: Recognition
and reward
Item 4 0.762 9.110 Item 1 0.892 —
Item 5 0.901 9.419 Item 2 0.736 10.087
Item 6 0.800 8.557 Item 3 0.872 12.235
Item 7 0.679 8.007 Item 4 0.485 5.929
Scale 4: Process control
and involvement
Scale 9: Education
and training
Item 1 0.686 — Item 1 0.724 —
Item 2 0.718 7.451 Item 2 0.855 9.528
Item 3 0.521 5.546 Item 3 0.713 7.796
(Table continued)
566 E. Bayraktar et al.

17. validity criterion, while only two tests failed to satisfy the discriminant validity criterion. Venka-
traman (1989, p. 954) states that ‘since the conceptual domains of these dimensions do not overlap
significantly and they exhibit different patterns of relationships with other dimensions, it is poss-
ible to accept the distinctive characteristics of these dimensions’. As only two of the 55 tests do not
meet this criterion, we can conclude that the discriminant validity criterion is satisfied by these
dimensions.
Table 8. Continued.
Description
Regression
weight t-valueÃ
Description
Regression
weight t-valueÃ
Item 4 0.643 7.272 Scale 11: Other
stakeholders’ focus
Item 5 0.767 8.399 Item 1 0.835 —
Scale 10: Student focus Item 2 0.694 8.749
Item 1 0.892 — Item 3 0.795 10.844
Item 2 0.736 10.087 Item 4 0.587 7.233
Item 3 0.872 12.235 Item 5 0.770 10.378
Item 4 0.485 5.929 Item 6 0.781 10.360
Note: — Fixed for estimation; Ã
all values are significant at the 0.01 level.
Table 9. Assessment of discriminant validity.
Test # Description
Chi-squared
model
Chi-squared
unconstrained
model Difference
1 Leadership – Vision 254.85 262.01 7.12Ã
2 Leadership – Measurement 109.19 120.67 11.48Ã
3 Leadership – Process control 211.41 219.61 8.21Ã
4 Leadership – Program design 168.25 184.08 15.83Ã
5 Leadership – Quality 124.38 125.30 0.92
6 Leadership – Employee involvement 265.67 270.74 5.07Ã
7 Leadership – Recognition 159.69 166.52 6.83Ã
8 Leadership – Education 206.61 213.80 7.19Ã
9 Leadership – Student focus 155.10 177.22 22.12Ã
10 Leadership – Other stakeholders’ focus 210.36 210.40 0.04
11 Vision – Measurement 200.78 215.35 14.58Ã
12 Vision – Process control 165.39 180.54 15.14Ã
13 Vision – Program design 118.22 139.66 20.85Ã
14 Vision – Quality 61.18 77.16 15.98Ã
15 Vision – Employee involvement 202.67 212.09 9.41Ã
16 Vision – Recognition 89.86 102.14 12.29Ã
(Table continued)
Total Quality Management 567

18. Conclusions
This paper offers a set of 11 critical factors of TQM in higher education based on a thorough
review and synthesis of the quality management literature. The extant TQM literature provides
little guidance regarding how to measure any of the proposed critical factors of TQM in higher
education institutes. This paper has attempted to develop an instrument that can be utilised to
Table 8. Continued.
Test # Description
Chi-squared
model
Chi-squared
unconstrained
model Difference
17 Vision – Education 93.80 107.01 13.21Ã
18 Vision – Student focus 92.74 109.05 16.32Ã
19 Vision – Other stakeholders’ focus 13.50 147.35 10.85Ã
20 Measurement – Process control 170.44 187.01 16.58Ã
21 Measurement – Program design 139.20 164.42 25.22Ã
22 Measurement – Quality 107.60 116.81 9.21Ã
23 Measurement – Employee involvement 195.46 208.32 12.85Ã
24 Measurement – Recognition 127.82 139.02 11.20Ã
25 Measurement – Education 148.40 163.88 15.47Ã
26 Measurement – Student focus 126.09 149.42 23.33Ã
27 Measurement – Other stakeholders’ focus 170.38 183.97 13.59Ã
28 Process Control – Program design 119.58 134.98 15.39Ã
29 Process Control – Quality 64.86 72.17 7.30Ã
30 Process Control – Employee involvement 153.85 163.44 9.59Ã
31 Process Control – Recognition 92.01 103.27 11.26Ã
32 Process Control – Education 95.08 105.65 10.57Ã
33 Process Control – Student focus 88.34 105.47 17.13Ã
34 Process Control – Other stakeholders’ focus 120.02 128.69 8.67Ã
35 Program Design – Quality 33.23 44.95 11.72Ã
36 Program Design – Employee involvement 126.29 142.68 16.38Ã
37 Program Design – Recognition 86.25 115.01 28.76Ã
38 Program Design – Education 75.83 92.29 16.46Ã
39 Program Design – Student focus 54.21 66.26 12.05Ã
40 Program Design – Other stakeholders’ focus 107.54 118.73 11.19Ã
41 Quality – Employee involvement 122.24 126.11 3.87Ã
42 Quality – Recognition 35.96 41.22 5.26Ã
43 Quality – Education 72.04 76.78 4.74Ã
44 Quality – Student focus 24.09 39.28 15.15Ã
45 Quality – Other stakeholders’ focus 72.48 77.52 5.04Ã
46 Employee Involvement – Recognition 89.86 102.15 12.29Ã
47 Employee Involvement – Education 93.80 107.01 13.21Ã
48 Employee Involvement – Student focus 92.74 109.05 16.32Ã
49 Employee Involvement – Other stakeholders’ focus 132.50 147.35 14.85Ã
50 Recognition – Education 82.97 91.77 8.80Ã
51 Recognition – Student focus 35.99 52.97 16.99Ã
52 Recognition – Other stakeholders’ focus 105.52 111.75 6.22Ã
53 Education – Student focus 43.99 64.87 20.87Ã
54 Education – Other stakeholders’ focus 114.13 121.76 7.63Ã
55 Student Focus – Other stakeholders’ focus 71.16 81.46 10.30Ã
Note: Ã
p , 0.01
568 E. Bayraktar et al.

19. evaluate the extent of TQM implementation in HEIs. The measures proposed were empirically
based and shown to be reliable and valid.
Operational measures of TQM in HEIs in terms of certain critical factors would be useful
to both decision makers and researchers. Decision makers may need to be aware of quality man-
agement practices. They can use this instrument reported here to evaluate the perceptions of TQM
in their institutions. These measurements may help decision makers in HEIs identify potential
areas of TQM where improvements could be made. In addition, comparisons of different HEIs
or divisions can be undertaken to help prioritise critical success factors of TQM implementation.
Researchers can use the instrument to understand TQM practices better and to develop the-
ories and models that relate the critical factors of TQM in a HEI to its quality performance
and quality environment. A number of research hypotheses can also be examined that relate
TQM to the HEI’s contextual and environmental variables.
The data utilised for testing and validating this instrument only came from 22 HEIs in Istan-
bul, which makes the generalisation of findings somewhat limited. In order to improve external
validity of the instrument, further research would be definitely called for. Although this instru-
ment was empirically tested and validated using data from Turkish HEIs, researchers and prac-
titioners from other countries would be able to utilise it.
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Appendix
TQM implementation instrument
The respondents were asked to indicate their level of agreement on the following statements
based on five-point Likert scales (1 ¼ strongly disagree; 2 ¼ disagree; 3 ¼ neutral;
4 ¼ agree; 5 ¼ strongly agree).
Scale 1: Leadership
1. University top management (Board of regents, rector and associate rectors) is knowledgeable
about TQM and its implementation.
2. University top management actively participates in TQM and supports the improvement
process.
3. University top management is well aware of the quality related concepts, new work environ-
ment and new skills in the implementation of TQM.
4. University top management strongly encourages employee involvement in TQM.
5. University top management empowers employees to solve quality problems.
6. University top management allocates adequate resources for academic and administrative
employee education and training.
7. University top management discusses many quality-related issues on TQM in their manage-
ment meetings.
8. University top management focuses on how to improve the performance of students and
employees apart from relying on financial criteria.
9. University top management pursues long-term stable performance instead of short-term tem-
porary solutions.
Scale 2: Vision
1. Our university has a clear written vision statement.
2. Our university vision is widely known and shared by our staff.
Total Quality Management 571

22. 3. Our vision effectively encourages our staff to improve the performance of our students and
our institution.
4. Academic and administrative processes in our university are well aligned with our vision.
5. Our university has well defined academic and administrative processes and performance
measures as well as policies.
6. Employees from different levels are involved in developing our policies and plans.
Scale 3: Measurement and evaluation
1. Our university regularly audits practices according to policies and strategies.
2. Our university benchmarks our academic and administrative processes with other
institutions.
3. Our university has standard performance measures (e.g. number of publications, course
evaluations, absenteeism, job satisfaction) to evaluate the performance of the institution
and TQM implementation.
4. Standard performance measures are used to evaluate the performance of university’s top
management.
5. Standard performance measures are used to evaluate the performance of academic units such
as schools and departments.
6. Standard performance measures are used to evaluate the performance of staff.
7. The aim of the evaluation is for improvement not for criticism.
Scale 4: Process control and improvement
1. Our university is kept neat and clean at all times.
2. Our university meets the expectations of our students and employees.
3. Our university has modern facilities (e.g. laboratories, library, computers, internet, video
players) to enhance the effectiveness of education.
4. Facilities of our university (e.g. classrooms, laboratories, computers, heating systems and air
conditioners) are maintained in good condition according to periodic maintenance plans.
5. Our processes are designed to be ‘fool proof” to minimise the source of error.
6. Our university collects statistical data (e.g. error rates on student records, course attendances,
employee turnover rates) and evaluates them to control and improve the processes.
Scale 5: Program design
1. Students’ requirements are thoroughly considered in the design of curriculum.
2. The experienced academicians’ suggestions are thoroughly considered in the design of
curriculum.
3. The needs and suggestions from the business world are thoroughly considered in the design of
curriculum and new academic programs.
4. Curriculum and academic programs are evaluated and updated every year.
5. Our university facilities (e.g. laboratories, hardware, finance and human resources) are con-
sidered in the development and improvement of the curriculum and programs.
Scale 6: Quality system improvement
1. TQM in our university is continuously improved.
572 E. Bayraktar et al.

23. 2. Our university is committed to TQM to establish our quality system in a level to be certified
by ISO 9000.
3. Our university has a clear quality manual, quality system documents and working
instructions.
Scale 7: Employee involvement
1. Our university has cross-functional teams and supports team-work.
2. As a result of quality efforts in our university, coordination and collaboration among our
employees have been enhanced.
3. Our employees are actively involved in TQM-related activities.
4. Our university has an established suggestion system to improve the processes by the
employees.
5. Employees’ suggestions are carefully evaluated and implemented if accepted.
6. Employees are very committed to the success of our university and its quality.
Scale 8: Recognition and reward
1. Our university has a reward program to recognise employee TQM efforts and their partici-
pation to the activities related to the university’s mission.
2. Our university has clear procedures for employees’ rewards and penalties, and applies them
transparently.
3. Recognition and reward activities effectively stimulate employee commitment to TQM
efforts.
4. Appointments to the administrative and academic positions are based on the necessary skills
required by the positions.
Scale 9: Education and training
1. Our university encourages education and training activities of our employees for academic
excellence.
2. Special training for work-related skills is provided to all employees.
3. Our university organises training on TQM for employees and encourages employees to
participate.
4. Financial resources are available for employee education and training in our university.
5. Employees, as the organisation’s most valuable and long-term resources, are worthy of
receiving the necessary education and training in order to achieve the university’s vision.
Scale 10: Student focus
1. Our university collects student complaints and evaluates them carefully.
2. Our university conducts a course-evaluation survey for every course taught in each semester
regularly.
3. Our university supports the student clubs and their activities.
4. Our university has some organised efforts on continuous education of our students for their
business-life and personal development after graduation.
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24. Scale 11: Other stakeholders’ focus
1. Our university collects employee complaints and evaluates them carefully.
2. Our university takes into consideration the changing needs of the business world.
3. Our university regularly conducts surveys on job satisfaction of the employees.
4. Our university has some organised efforts to understand the expectation of industry regarding
our graduates.
5. Our university follows up the career path of our graduates.
6. Our university has some organised efforts to identify the academic and administrative needs
of our employees.
574 E. Bayraktar et al.