Research6.pdf

Influence of human factors on
organisational performance

Quality improvement practices
as a mediator variable

Nasser Habtoor
Department of Human Resource Management,

Islamic Science University of Malaysia, Nilai, Malaysia and
Faculty of Business Administration, University of Aden, Aden, Yemen

Abstract
Purpose – The purpose of this paper is to explore the influence of human factors in quality
management on quality improvement practices and organisational performance in the Yemeni
industrial sector.
Design/methodology/approach – Data were collected via a quantitative survey with a
questionnaire distributed to 261 managers from 87 industrial companies. Replies from
210 managers give a response rate of 80 per cent. Data were analysed with Statistical Package for
the Social Sciences 16.0, including factor analysis, reliability analysis, descriptive statistics, and
correlation analysis. Structural equation modelling was carried out using Amos to evaluate the model
and hypotheses.
Findings – Human factors influence positively quality improvement practices and organisational
performance. Quality improvement practices positively influence organisational performance. Human
factors indirectly and significantly influence organisational performance via the mediator of quality
improvement practices.
Research limitations/implications – The findings will be useful to both researchers and
managers, especially those in Yemeni industrial companies. For further work, this study can be
expanded to cover companies in other Middle East countries, and it may include more human factors.
Originality/value – The study is one of a few that investigate the influence of human factors on
quality management. Additionally, this study is the first to carry out such research in the Yemen and
the Middle East region.
Keywords Total quality management, Human resource management, Organizational performance
Paper type Research paper

Introduction
Human factors in quality management play a central role in the implementation of
quality improvement practices and organisational performance. Literature on quality
management suggests that the implementation of a total quality management
programme will not be successful unless great attention is paid to the human factors
(Lewis et al., 2006b; Motwani et al., 1994; Wilkinson et al., 1994).

Literature on quality management divides the total quality management practices
into two groups; the first group is called technical factors and the second group is
human factors. Technical-factors group focuses on tools and work processes such as
product design, process and statistics, benchmarking, just-in-time, continuous
improvement, and control/feedback. On the other hand, human-factors group
includes the human or behaviour side of quality management such as leadership,
employee involvement, training and education, customer focus, teamwork,
communication, supplier relations, and rewards and recognition.

International Journal of
Productivity and Performance
Management
Vol. 65 No. 4, 2016
pp. 460-484
© Emerald Group Publishing Limited
1741-0401
DOI 10.1108/IJPPM-02-2014-0016

Received 3 February 2014
Revised 17 July 2014
14 October 2014
8 January 2015
15 April 2015
27 July 2015
13 August 2015
Accepted 17 August 2015

The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1741-0401.htm

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Literature suggests that there is a lack of studies emphasising the human side of
total quality management; too many of them were carried out to investigate only the
technical aspect. The situation is due to the technical orientation of total quality
management leaders who emphasise technical factors rather than human factors (Lau
and Idris, 2001; Wilkinson, 1992). According to Edwards and Sohal (2003), the lack of
attention to the human factors in total quality management may lead to limiting the
success of total quality management implementation.

Moreover, literature of quality management suggests that when companies
implement total quality management in their processes, there is more emphasis on the
technical factors in quality management rather than the human factors (Yang, 2006;
Lewis et al., 2006b; Wilkinson et al., 1994). Hill (1991) noted that although the solution to
the technical issues of designing appropriate systems and procedures is fully specified,
there are lacunae in the treatment of social factors. Therefore, as a result of the
significant influence of human factors in quality management on organisational
performance and their contribution to the implementation of total quality management,
the human factors need more attention when an organisation reengineers its processes
to implement total quality management.

There are insufficient empirical studies which have examined the influence of
human factors in quality management on organisational performance. There is no
study which had examined the influence of human factors on quality improvement
practice except some studies which had examined the influence of human factors on
technical factors in quality improvement practices. However, they provide evidence
showing the existence of both direct significant influence of human factors on technical
factors in quality improvement practices and organisational performance, and indirect
significant influence of human factors on organisational performance through their
influence on technical factors in quality improvement practices (Flynn et al., 1995;
Rahman and Bullock, 2005; Abdullah et al., 2008; Gadenne and Sharma, 2009).

In Yemen, there is a growing governmental interest in the industrial sector because
of its important role in leading economic changes, in addition to its role in supporting
the Yemeni economy. Furthermore, Yemeni industrial companies have adopted total
quality management programme as a way to enhance their competitive advantage in
to face new challenges in the business environment. However, the
implementation of total quality management is way below the expected level
(Nashwan, 2008; Abdullatef, 2006).

Literature considers human factors as a vital player in the success of total quality
management implementation through their direct contribution to the practices of
quality improvement and company performance, besides indirect contribution to
organisation performance via creating a suitable environment for the implementation
of quality improvement practices (Rahman and Bullock, 2005; Abdullah et al., 2008;
Gadenne and Sharma, 2009). Thus, the current study investigates the human factors
in quality management in Yemeni industrial companies through examining the direct
influence of human factors on quality improvement practices and organisational
performance; the study also examines the direct influence of quality improvement
practice on organisational performance. Furthermore, this study evaluates the
indirect influence of human factors in quality management on organisation
performance through their direct influence on quality improvement practices. Thus,
this study can contribute to the efforts of the Yemeni Government and companies,
and enhance the industrial sector through improving the implementation of total
quality management.

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Finally, the framework of this study consists of six factors representing the human
side of quality management; they are leadership, customer focus, supplier relation,
employee involvement, training and education, as well as reward and recognition. The
scope also covers quality improvement practices (involve both human and technical
factors in quality management), and organisational performance represented by five
dimensions. Therefore, the research question is:

RQ1. What are the direct and indirect influences of human factors on quality
improvement practices and organisational performance?

The structure of this paper is constructed to investigate the aims of the study. The next
section examines the human factors and discusses the critical factors in total quality
management implementation identified by a set of empirical studies. It also touches on
human factors in total quality management and their importance to total quality
management implementation. Then, it is followed by the outline of the methodology,
which includes framework, population and sampling, measurement and statistical
analysis. Furthermore, an analysis of the results of the study is carried out, followed by
a discussion and conclusion.

Literature review
Through a literature review of total quality management, a set of total quality
management practices was identified as critical factors for the successful implementation
of total quality management. Oakland (2000) provided a general definition of critical
factors in quality management that influence the organisational or a management system
in the business environment. He defined critical factors as the critical areas an
organisation should carefully examine; and it should categorise their impacts on the
system as well as on the whole organisation. This is necessary to successfully manage
them and achieve the effective implementation of the system and the organisation’s
mission. Saraph et al. (1989) pioneered an empirical approach to identify and measure the
critical factors in total quality management implementation in the USA. They argued
that no systematic attempt had been made in the literature to organise and synthesise the
various sets of critical factors, the measures of overall organisational management or of
any individual critical factors identified by different quality gurus. Later, some authors
developed a similar approach to identify and investigate the critical success factors for
total quality management implementation (such as Alok and Sushil, 2013; Kaur et al.,
2013; Oprime et al., 2012; Sanjiv et al., 2012; Psomas and Fotopoulos, 2010; Guion, 2010;
Fotopoulos et al., 2009; Salaheldin, 2009; Wahid and Corner, 2009; Sharma and Kodali,
2008; Antony et al., 2002; Zhang, 2000; Black and Porter, 1996; Vinzant and Vinzant, 1996;
Flynn et al., 1994).

Based on the message of quality, that quality is every one’s responsibility,
Wilkinson (1992) emphasised the human factors in quality management. He divided
quality management into two aspects, soft and hard, which correspond to the human
side of quality management and work process, respectively. He claimed that the hard
aspect (technical side) involves the arrangement of production techniques, including
statistical process control, quality function deployment, changes in the layout, design
procedures of the organisation, and just-in-time inventory, while the human side is
concerned with creating customer awareness within an organisation and as such, may
be seen as a form of internal marketing or employee communication.

According to Louise (1996), culture change is a major reason for the reorientation of
total quality towards the human factors in quality management. The culture change

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becomes a stumbling block to many companies involved in total quality management
implementation (Louise, 1996). Lau and Idris (2001) suggested that it is necessary to
study the critical soft factors (human factors) of quality management due to their
importance to total quality management implementations, which contribute to a
change in the thinking of managers and employees, and in turn permeates the total
quality management throughout the whole organisation. Yasuo (1980) claimed that to
make good use of personnel is difficult, but it is an issue that is required and must be
overcome. According to Tamimi and Sebastianelli (1998), 48 per cent of organisations
identified human factors as barriers to total quality management.

Recently, researchers pay more attention to the dimension of human factors in
quality management, and their influences and relations with the hard factors and
organisational performance (e.g. Assadej, 2012; Gadenne and Sharma, 2009; Fotopoulos
and Psomas, 2009; Abdullah et al., 2008; Lewis et al., 2006a, b; Rahman and Bullock,
2005; Boon and Arumugam, 2005; Sila and Ebrahimpour, 2002; Lau and Idris, 2001;
Louise, 1996; Motwani et al., 1994; Wilkinson, 1992; Hill, 1991).

Controversial claims have been suggested by researchers regarding the most
effective factors for implementing total quality management; for example, Black and
Porter claimed that hard factors concerned with tools and systems lend support to the
implementation of human factors, while Samson and Terziovski (1999) found that
human factors in quality management such as executive commitment, employee
empowerment, and an open culture can strengthen competitive advantage more than
the technical factors such as process improvement, benchmarking, and information
and analysis do. Wilkinson (1992) suggested that the whole total quality management
process will be much enhanced if these issues are brought to the fore, adding positive
effects such as the breaking down of department barriers and increasing employee
involvement. Thus, it is difficult for quality tools to contribute in terms of quality
improvement, customer satisfaction, and consolidation of its market position without
the support and guidance from the human factors in quality management such as top
management commitment and employee and supplier cooperation (Fotopoulos and
Psomas, 2009). Lewis et al. (2006b) found that hard criteria implementation attracts
more attention than soft criteria (human factors) in small and medium enterprises. He
defined the human factors in quality management as criteria which are largely
related to the behavioural aspects of working life such as leadership, human resource
management, supplier’s relations and customer focus. Hill (1991) also suggested that
there are lacunae in the implementation of social factors when organisations
reengineer their systems and procedures. Lau and Idris (2001) found that human
factors such as culture and trust as well as teamwork have a strong influence on
quality management. The importance of human factors in quality is based on their
important role in the implementation of total quality management, as a programme
needs significant and continuous changes in the culture of an organisation. Motwani
et al. (1994) considered the human factors in quality management such as leadership,
organisational skills, and culture as a key player that acts to achieve quality
performance. It is easy to quantify the hard criteria (Lewis et al., 2006a; Oakland,
2000; Louise, 1996), while the soft criteria are more open to interpretation; thus, it is
more difficult to measure them (Lewis et al., 2006a; Gotzamani and Tsiotras, 2001;
Samson and Terziovski, 1999).

Lewis et al. (2006a) identified 13 soft factors (human factors) and 12 hard factors as
critical factors in quality management based on the Sila and Ebrahimpour (2002) study
that identified 25 criteria factors in quality management. Sila and Ebrahimpour (2002)

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conducted a large-scale study to investigate total quality management practices based
on the survey studies conducted between 1989 and 2000 in different countries and
published in different journals within that period. Sila and Ebrahimpour (2002) found
out in their survey four out of seven practices that received the highest coverage are
related to the human side of total quality management; these are customer focus and
satisfaction, teamwork, training, and employee involvement.

More specifically, Abdullah et al. (2008), Rahman and Bullock (2005), Ho et al. (2001),
and Flynn et al. (1995) attempted to explore and investigate the relationship between
hard and soft factors and their impact on organisational performance. They divided
quality management practices into two groups; the first group, named the hard factors
(technical factors), includes process flow management, product design process and
statistics, control/feedback, JIT principles, and continuous improvement. The second
group, named the soft factors (human factors), includes customer relationship, supplier
relationship, training and education, workforce commitment, teamwork, and top
management support. They found a positive relationship between hard and soft factors
and also a positive relationship between these factors and organisation performance;
both hard and soft factors have significant impact on organisational performance.
They also found that the hard factors act as a mediator factor for the relationship
between the soft factors and organisational performance. This finding supports the
purpose of the present study.

Methodology
Framework
The framework of the current study connects the variables of human factors in quality
management, the variables of quality improvement practices and the dimensions of
organisational performance. The framework shown in Figure 1 includes independent
variables represented by six human factors in quality management; they are
leadership, customer focus, supplier relations, employee involvement, training and
education, and finally reward and recognition. Moreover, two dependent variables are
also included in this framework. The first is quality improvement practices as a
mediator variable for the relationship of human factors and organisational
performance. It includes six elements; they are top management support, teamwork,
customer involvement, process control and improvement, product design, and quality
system improvement. However, the quality improvement practices include both
technical and human side of quality management. The second is organisational
performance represented by five dimensions; they are customer satisfaction, employee
morale, productivity, defects, and delivery in full.

QUALITY
IMPROVEMENT

PRACTICES

HUMAN FACTORS ORGANISATIONAL
PERFORMANCE

Figure 1.
Framework of study

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Population and sample
The target population of this study consists of Yemeni industrial companies, which had
received local and international quality certificates due to their interest in total quality
management implementation, with implication of international and local quality
criteria reflected in their operations. In fact, 87 Yemeni industrial companies had
already possessed local quality certificates, which were awarded by Yemen
Standardization Metrology and Quality Control Organization, and international
quality certificates (such as European Business Excellence Model, ISO 9000, and other
international quality awards). These companies are located in five industrial cities;
namely, Sana’a, Aden, Alhudaidah, Hadramout, and Taiz as shown in Table I.

This study emphasises the industrial sector due to its importance to the Yemeni
economy, and the government’s effort to enhance this sector via improving total quality
management implementation. Essentially, the researcher chose this type of company
because they are interested in the implementation of total quality management and
using international and local factors in their operations. Hence, these companies are
familiar with the issues this study attempts to address (Curry and Kadasah, 2002).

Choosing the appropriate sample is the most important element to answer the
research questions and investigate the objectives of any study (Sekaran, 2000). Based
on this logic, the participants of this study are managers, who are familiar with the
implementation of total quality management in their organisations and at the same
time have knowledge about the performance.

Therefore, the respondents of this study consist of one top management manager
and two quality managers of each selected Yemeni company. Thus, a total of 261
managers from 87 Yemeni industrial companies were listed as respondents of this
study, and a questionnaire was sent to each of the 87 industrial companies in Yemen.
A total of 210 completed survey forms were returned out of 261 survey questionnaire
distributed; this works out to a response rate of 80 per cent, which is considered good
(Roth and BeVier, 1998).

Measurement
A questionnaire was designed to determine and clarify the relationship between the
human factors, quality improvement practices, and organisational performance. To
measure the human factors, the instrument developed by Zhang (2000) was used. This
instrument had 40 items which included six factors: leadership, customer focus,
employee involvement, supplier relations, training and education, as well as reward
and recognition. To examine quality improvement practices, this study adopted the
instrument of Flynn et al. (1994) to evaluate the human side of quality improvement
practices (top management support, teamwork, customer involvement). To examine the

Industrial cities Number of companies

Alhudaidah 21
Hadramout 20
Sana’a 18
Taiz 17
Aden 11
Total 87
Source: Yemen Standardization Metrology and Quality Control Organization

Table I.
Population of study

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technical side of quality improvement practices (process control and improvement,
product design and quality system improvement), this study used Zhang’s (2000)
instrument, which included 38 items. To measure organisational performance, the
instrument developed by Samson and Terziovski (1999) was used. Prior to conducting
the main study, a preliminary study was carried out among 30 quality managers of
Yemen industrial companies, in to test the clarity, comprehensiveness and
acceptability of the questionnaire.

Factor analysis was carried out to evaluate the assignment of items to scale in
developing the instrument of this study. According to Hair et al. (1998), the main purpose
of factor analysis is to find a way of condensing or summarising the information into a
smaller set of new composite dimensions (factors) with a minimum loss of information.
In fact, factor analysis is a way of testing how well measured variables represent the
constructs. Moreover, factor analysis results can provide evidence for the convergent and
discriminant validities of theoretical constructs (Brown, 2006). Indeed, factor analysis can
help to identify whether the selected items cluster on one or more than one factor. Factor
loadings are used to present these relations. Hair et al. (1998) regarded factor loadings
greater than 0.30 as significant factors; loadings of 0.40 as more important; and if the
loadings are 0.50 or greater, they are considered very significant. The previous studies in
the field of total quality management such as Saraph et al. (1989), Flynn et al. (1994),
and Zhang (2000) used factor analysis and they claimed that a factor loading of 0.50
is acceptable in their studies. Therefore, in the current study, a factor loading of
0.50 or greater is considered significant.

The results shown in the Appendix present factor loadings of human factors,
quality improvement practices and organisational performance, after removing the
items with low-factor loading or double loading. Regarding the variables of human
factors, four out of 40 items were removed after factor analysis; one of which belonged
to leadership factor; thus, seven items of leadership factor remained. Another two items
were removed from employee involvement factors; thus, only six items of employee
involvement remained. The fourth item was removed from the group of six items of
reward and recognition factor. The findings of this technique show that the loadings of
remaining items range from 0.510 to 0.904. The relative explanatory power (Eigen
values) for each factor of human factors is 3.550 for leadership, 3.210 for customer
focus, 3.193 for supplier relationship, 3.234 for employee involvement, 3.586 for training
and education, and 3.266 for reward and recognition. The value of KMO for each factor
of human factors in quality management is 0.814 for leadership, 0.822 for customer
focus, 0.685 for supplier relationship, 0.707 for employee involvement, 0.799 for training
and education, and 0.817 for reward and recognition. Actually, these results indicated
that sampling adequacy for factor analysis was appropriate. Bartlett’s test of sphericity
for each variable significantly supports the factorability of correlation matrix.

For the variables of quality improvement practices, three items related to product
design out of 38 items were removed after factor analysis; they were removed due to the
reason that two of them were double loaded and one was low loaded (0.443). Thus, the
findings of this technique show that the loading of the remaining items ranges from 0.543
to 0.922. The relative explanatory power (Eigen values) for each factor of quality
improvement practices is 3.127 for top management support, 3.967 for teamwork, 2.902
for customer involvement, 5.126 for process control and improvement, 2.771 for product
design, and 3.097 for quality system improvement. The values of KMO for each factor of
human factors in quality management are 0.784 for top management support, 0.811 for
teamwork, 0.731 for customer involvement, 0.828 for process control and improvement,

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0.768 for product design, and 0.791 for quality system improvement; these figures show
the appropriateness of sampling adequacy for factor analysis. Bartlett’s test of sphericity
for each variable significantly supports factorability of correlation matrix.

For organisational performance, two of seven items were removed after factor
analysis. The findings of this technique show that the loading of remaining items
ranges from 0.587 to 0.844. The relative explanatory power (Eigen values) for the factor
of organisational performance is 3.004. The value of KMO for organisational
performance is 0.781, which indicates that sampling adequacy for factor analysis was
appropriate. Bartlett’s test of sphericity for each variable significantly supports the
factorability of correlation matrix.

The reliability analysis was conducted to provide information about the relationship
between individual items in the scale and their internal consistency, in addition to
examining the properties of measurement scale and the questions that made it. Wuest
et al., however, considered the calculating estimates of reliability as an essential
prerequisite for the instrument’s validation. In this research, internal consistency was
adopted to estimate the reliability of instrument. Internal consistency was measured by
Cronbach’s coefficient α, and the higher the α value or the closer reliability coefficient to
1.0, was considered the higher of the measurement items. Therefore, in this study,
Cronbach’s α values exceeding 0.7 represent acceptable reliability, while any α values
over 0.8 are considered as entirely good (Nunnally, 1978; Cronbach, 1951).

The results of Cronbach’s coefficient α of the six human factors in quality
management are shown in Table II. Measures of human factors were carried out based on
five point Likert scale from 1 ¼ strongly disagree to 5 ¼ strongly agree. The instrument
has an acceptable reliability for human factors in quality management, the Cronbach α
ranges between 0.727 for employee involvement and 0.871 for reward and recognition.
Measures of the six quality improvement practices (top management support, teamwork,
customer involvement, process control and improvement, product design, and quality
system improvement) were carried out based on five point Likert scales from
1 ¼ strongly disagree to 5 ¼ strongly agree. The instrument has an acceptable reliability
for quality improvement practices, and the Cronbach α ranges between 0.700 for product
design and 0.860 for teamwork. Moreover, Table II shows Cronbach’s coefficient α of the

Factor No. of items α

Human factors
Leadership 7 0.824
Customer focus 6 0.817
Supplier relations 6 0.777
Employee involvement 6 0.727
Training and education 6 0.860
Reward and recognition 5 0.871

Quality improvement practices
Top management support 5 0.839
Teamwork 7 0.860
Customer involvement 5 0.793
Process control and improvement 8 0.702
Product design 5 0.700
Quality system improvement 5 0.829
Organisational performance 5 0.827

Table II.
Reliability analysis

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five dimensions of organisational performance (customer satisfaction, employee morale,
productivity, defects, delivery in full) of this study. The instrument has an acceptable
reliability for organisational performance, and the Cronbach α is 0.827.

Statistical analysis
All collected data were transferred into the data entry template using the Statistical
Package for the Social Sciences (SPSS) version 19. In addition, the Amos programme for
structural equation modelling (SEM) was also used to test and evaluate the theoretical
framework and its hypotheses due to their flexibility in this respect.

The SPSS statistical programme was used to test the reliability of the variables, and
correlation analysis was carried out by SPSS as well to test the relationship between
the variables of the study due to their flexibility in this respect. SEM was carried out by
using statistical programme, Amos version 16.0 to evaluate the theoretical framework
and its hypotheses, which examine the direct influence of human factors in quality
management on quality improvement practices and organisational performance;
furthermore, it also gauged the indirect influence of human factors in quality
management on organisational performance through their influence on quality
improvement practices. One of the advantages of using SEM is that if the researcher
has many items, which are representative of one factor in hypothesised model, she/he
can use the summated score approach or total score for …