Relationship between Total Quality Management, Knowledge
Management, and Innovation in the Construction Sector in Indonesia
Maureen Theodora and Yusuf Latief
Department of Civil Engineering, Universitas Indonesia, Depok, West Java, Indonesia
Keywords: Construction, Innovation, Knowledge Management, Partial Least Square, Total Quality Management.
Abstract: The construction sector in Indonesia plays a very important role in global competitiveness. One of the main
factors that promote national economic growth is innovation. Unfortunately, innovation performance in
Indonesia, including the construction sector, is regarded as low. It is believed that the two main causes of low
innovation are lack of knowledge and poor quality management. In light of that issue, this study examined
the relationship of Total Quality Management (TQM), Knowledge Management (KM), and innovation in the
construction sector in Indonesia. PLS-SEM approach was used to analyze the data obtained from 75
respondents, ranging from staff to managerial positions from 6 property developers in Indonesia. Property
developers, who are the clients, are believed to be the most influential actors in increasing innovation in the
construction sector. The results showed that TQM practices give a significant influence on KM processes
through customer focus, people management, and process management. KM processes then give a significant
influence on innovation through knowledge sharing and knowledge application.
1 INTRODUCTION
Indonesia’s active role in global competitiveness,
especially in the construction sector cannot be denied
(Soeparto and Trigunarsyah, 2014). According to
Badan Pusat Statistik (2017), as a non-departmental
government institute of Indonesia that is responsible
for conducting statistical surveys, the construction
sector occupies the third position as a driver of
economic growth in Indonesia throughout 2017. It is
also believed that innovation helps the construction
sector to support national economic growth (Blayse
& Manley, 2004). Unfortunately, innovation in the
construction sector still faces difficulty (Davidson,
2013).
Innovation itself plays a very important role in an
organization, by providing a competitive advantage
and superior performance (Antunes, Quirós &
Justino, 2016). Based on the assessment of Global
Innovation Index (2017), Indonesia is ranked 87
th
out
of 147 countries, with a value of 30.01 out of 100.
This is certainly very concerning and needs special
attention, considering that innovation is a very
important element in global competitiveness.
There are two main things that are believed to have
a major influence on innovation. The availability of
knowledge (Du Plessis, 2007) and the application of
quality management practices (Kim, Kumar &
Kumar, 2012).
Based on the previous studies, it can be said that
the two factors that give significant influences on
innovation are Knowledge Management (KM) and
Total Quality Management (TQM). Recent studies
examined the relationship between KM and TQM,
and concluded that TQM practices support KM
processes (Rajeshwaran & Aktharsha, 2017;
Qasrawi, Almahamid & Qasrawi, 2017). It was also
found that the relationship between KM and TQM
positively influences innovation (Honarpour, Jusoh &
Nor, 2017; Yusr et al., 2017).
In the construction sector, the client has a very
important role in determining the performance of
innovation (Bengtsson, 2017). Besides that, the
championing characteristics of a client are believed to
have a positive impact on innovative activities in the
construction sector (Kulatunga et al., 2011). Based on
these findings, this study was evaluated on property
developers in Indonesia, as the clients in the
construction sector. Property developers also have the
requirement to meet customer needs and
expectations, which pushes them to innovate
constantly.
Theodora, M. and Latief, Y.
Relationship between Total Quality Management, Knowledge Management, and Innovation in the Construction Sector in Indonesia.
DOI: 10.5220/0008428301290135
In Proceedings of the 2nd International Conference on Inclusive Business in the Changing World (ICIB 2019), pages 129-135
ISBN: 978-989-758-408-4
Copyright
c
2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
129
2 LITERATURE REVIEW
2.1 Innovation in the Construction
Sector
Construction refers to the process of fulfilling
customer needs through a temporary production
system (Bertelsen & Emmit, 2005). Characteristics of
the client, such as competence, assessment of
innovation, a vision of innovation, self-development,
and openness to change, give influence on various
aspects of innovation (Kulatunga et al., 2011).
According to Dulaimi, Nepal, and Park (2005),
innovation in the construction sector develops when
companies are faced with challenges, opportunities,
and problems, in order to achieve project goals. But,
because the development of innovation in the
construction sector is still at a very early stage, its
development still depends on other sectors (Sexton &
Barrett, 2003).
2.2 Knowledge Management
In the course and development of KM, most experts
divide KM into 3 stages of the process, namely
knowledge creation, knowledge sharing, and
knowledge application (the use of terms for each
process may be different).
Knowledge creation can be interpreted as a
process of turning data into knowledge through
various stages of learning (García-Fernández, 2015),
while knowledge sharing is the process of transferring
knowledge before the knowledge is exploited,
through the stages of distribution (Bhatt, 2001).
Lastly, knowledge application is a process of
transforming existing knowledge into new
knowledge by applying and using it, exploiting
resources, and developing learning processes
(García-Fernández, 2015).
2.3 Total Quality Management
TQM implementation and the development of
innovation in organizations provide many benefits for
companies, by helping companies to improve quality
and facilitating the innovation process (Martínez-
Costa & Martínez-Lorente, 2008). Recently, Yusr et
al. (2017) conducted a study to examine the
relationship between KM, TQM, and innovation in
manufacturing companies. They used 6 TQM
practices, namely top management commitment,
customer focus, supplier management, people
management, process management, and quality data
reporting.
According to Ahire and O’Shaughnessy (1998),
companies that implement top management
commitments well will be able to encourage other
TQM practices. Customer focus is also one of the
main principles in the TQM system, where the
relationship between customer focus and innovation
that can be created by the company is positive
(Mustafa & Bon, 2012). People management means
providing support for each individual who works
within the company, such as employee
empowerment, employee involvement, and training
(Ahire, Golhar, & Waller, 1996). Palmberg (2009)
summarizes the results of research from experts and
explains that process management is a structured
systematic approach that continually improves the
performance of certain processes which integrates the
entire process that occurs within an organization.
Lastly, quality data reporting is about providing
information related to existing processes to the right
party and at the right time to assist in decision-making
activities (Yusr et al., 2017)
2.4 Research Model and Hypotheses
TQM practices and the research model used in this
study were adopted from Yusr et al. (2017) who
conducted a similar study in the manufacturing sector
in Malaysia. But one of the practices, supplier
management, was not use in this study because, based
on the study of previous researches, supplier
management was mostly evaluated in manufacturing
companies. According to Malcolm Baldrige National
Quality Award (MBNQA) criteria, which was
developed to assess the application and
implementation of quality in both manufacturing and
service organizations (Bon & Mustafa, 2013), there
was also no supplier management practice. The use of
terms for some KM processes was also adjusted due
to the consideration for further development of this
study.
Based on the discussion, the research model used
in this study is shown in Figure 1 below. This study
examined the TQM effect on KM and the KM effect
on innovation in the construction sector in Indonesia,
evaluated in property developers.
ICIB 2019 - The 2nd International Conference on Inclusive Business in the Changing World
130
Figure 1: Research Model.
(Adopted from Yusr et al. (2017), with adjustment).
This study proposes the following main
hypotheses:
▪ H1: TQM practices have a significant effect on
KM processes.
▪ H2: KM processes have a significant effect on
innovation.
The following sub-hypotheses have also been
developed:
▪ H1a: Top Management commitment practice has
a significant effect on KM processes.
▪ H1b: Customer focus practice has a significant
effect on KM processes.
▪ H1c: People management practice has a
significant effect on KM processes.
▪ H1d: Process management practice has a
significant effect on KM processes.
▪ H1e: Quality data reporting practice has a
significant effect on KM processes.
▪ H2a: Knowledge creation process has a significant
effect on innovation.
▪ H2b: Knowledge sharing process has a significant
effect on innovation.
▪ H2c: Knowledge application process has a
significant effect on innovation.
3 RESEARCH METHODOLOGY
3.1 Data Collection
This study used a survey and questionnaire to collect
the data needed. With respondents ranging from staff
to managers, 90 questionnaires were sent to 6
property developers in Indonesia. There were 78
questionnaires returned, which formed a response rate
of 86.67%. It was found that 3 of them were not valid.
Therefore, there were 75 questionnaires used in this
study.
3.2 Survey Instrument
The instrument used in this study consists of three
major parts. The first part contains 28 indicators,
adopted from García-Fernández (2015), which were
used to assess KM processes. The second part
contains 22 indicators to assess TQM practices,
adopted from Yusr et al. (2017) and Honarpour, Jusoh
& Nor (2017). The third part, which assessed
innovation performance, contains 16 indicators
adopted from Julison (2014). All items were rated on
a five-point Likert scale from 1 (strongly disagree) to
5 (strongly agree). The instrument was validated by
experts and went through a pilot survey before being
used in this study.
From the early homogeneity test, 7 indicators and
7 respondents were removed from the study. An early
validity test then showed that all remaining indicators
were valid. The result of the early reliability test gave
a reliability value of 0.979 that showed a very high
reliability level.
3.3 Method of Analysis
To analyze the relationship between variables, the
PLS-SEM method was used through SmartPLS
software. PLS-SEM is used to estimate the partial
least squares of regression models, by combining
features from the main component analysis and
multiple regression (Sarwono & Narimawati, 2015).
The stages in processing data with the PLS-SEM
method include outer model analysis, inner model
analysis, and hypotheses testing.
4 DATA ANALYSIS AND
RESULTS
4.1 Outer Model Analysis
The first step in the outer model analysis is to
determine the number of iteration needed to process
the data. Five iterations (out of 300 as the maximum
number of iteration) showed that there were no data
abnormalities, such as sample sizes that were too
small or the existence of data with extreme values.
The next step is to test the reliability for each
indicator. After several steps, 12 indicators were
Relationship between Total Quality Management, Knowledge Management, and Innovation in the Construction Sector in Indonesia
131
removed, in order to achieve the permitted value of
the outer loadings, which is above 0.7. Then, all
indicators were found to be valid, through a
discriminant validity test that analyzes cross loadings
value of each indicator.
Besides indicators, constructs also need to be
tested for reliability and validity. Constructs are
counted reliable if they have composite reliability
values above 0.7 and Cronbach’s α above 0.6. To test
the ability of a construct to represent the indicators
associated with it, constructs need to be examined for
convergent validity. If the construct has an AVE
value above 0.5, it can be said that the construct
adequately represents the indicators associated with
it. From table 1 below, we can see that all constructs
are reliable and valid.
Table 1: Constructs’ Reliability and Validity.
Constructs
Composite
Reliability
Cronbach’s α
AVE
KC
0.863
0.762
0.678
KS
0.900
0.832
0.752
KA
0.909
0.880
0.625
TMC
0.897
0.857
0.637
CF
0.890
0.835
0.671
PEM
0.912
0.881
0.676
PRM
0.908
0.864
0.711
QDR
0.934
0.894
0.825
IN
0.967
0.964
0.665
KC: Knowledge Creation, KS: Knowledge Sharing,
KA: Knowledge Application, TMC: Top
Management Commitment, CF: Customer Focus,
PEM: People Management, PRM: Process
Management, QDR: Quality Data Reporting, IN:
Innovation
4.2 Inner Model Analysis
The inner model analysis starts with R
2
analysis,
which describes the relationship between one
construct and another construct that are connected to
it. The R
2
value of ±0.25 indicates a weak effect. The
R
2
value of ±0.50 indicates a moderate effect and R
2
value of ±0.75 indicates a substantial effect. For
Knowledge Creation (KC), the R
2
value was 0.398. It
indicated that the five TQM constructs that affected it
explained 39.8% of the construct variance. The value
of 39.8% showed that the five TQM practices had a
moderate effect on Knowledge Creation (KC). For
Knowledge Sharing (KS), the R
2
value was 0.564,
and for Knowledge Application (KA), the R
2
value
was 0.776. For Innovation (IN), the R
2
value was
0.642. The value of 64.2% showed that the three KM
processes had a substantial effect on Innovation (IN).
Table 2: Result of the Relationship between Constructs.
Constructs
t-
value
Decisions
KC → IN
0.195
Not Supported
KS → IN
1.914
Supported
KA → IN
4.703
Supported
TMC → IN
0.841
Not Supported
TMC → KC
0.995
Not Supported
TMC → KS
0.735
Not Supported
TMC → KA
0.795
Not Supported
CF → IN
1.458
Not Supported
CF → KC
0.196
1.048
Not Supported
CF → KS
3.253
Supported
CF → KA
0.635
Not Supported
PEM → IN
N/A
2.525
Supported
PEM → KC
0.725
Not Supported
PEM → KS
0.041
Not Supported
PEM → KA
4.112
Supported
PRM → IN
N/A
2.875
Supported
PRM → KC
0.961
Not Supported
PRM → KS
0.344
2.099
Supported
PRM → KA
2.733
Supported
QDR → IN
0.071
Not Supported
QDR → KC
1.342
Not Supported
QDR → KS
0.020
Not Supported
QDR → KA
0.162
Not Supported
The value of the path coefficient illustrates the
influence of one construct on other constructs. The
influence can be said to be significant if the value of
the path coefficient is greater than 0.1. The greater the
value of the path coefficient, the greater the influence
is given. As we can see from Table 2, from the results
of path coefficients, it can be concluded that all TQM
practices have a significant effect on at least one KM
process. Knowledge Creation (KC) does not support
innovation, but Knowledge Sharing (KS) and
Knowledge Application (KA) have significant
influences on innovation.
The path coefficients results were then examined
further by the structural path significance in
bootstrapping method, where the relationship of
ICIB 2019 - The 2nd International Conference on Inclusive Business in the Changing World
132
influence between constructs was analyzed again.
Using the two-tailed t test with a significance level of
90%, the relationship between the two constructs was
counted significant if the t-value was greater than
1.668.
From the result of the t-value presented in Table
2, we can see that Knowledge Sharing (KS) and
Knowledge Application (KA) have a significant
effect on Innovation (IN), while Knowledge Creation
(KC) does not have a significant effect on Innovation
(IN). For TQM practices, it was found that Top
Management Commitment (TMC) does not have a
significant effect on any KM processes, but Customer
Focus (CF) supports Knowledge Sharing (KS) and
People Management (PEM) supports Knowledge
Application (KA). It was also found that Process
Management (PRM) supports both Knowledge
Sharing (KS) and Knowledge Application (KA)
processes. Lastly, Quality Data Reporting (QDR) was
found to not have a significant effect on any KM
processes.
5 DISCUSSION
Based on the results of the study, out of three KM
processes, only Knowledge Sharing (KS) and
Knowledge Application (KA) have an influence on
Innovation (IN). This finding is in line with the results
of the research conducted by Yusr et al. (2017), who
explained that if knowledge management process
only stops at knowledge creation, it will not have a
major influence on innovation, until the knowledge is
shared and applied.
The significant effect of Knowledge Sharing (KS)
on Innovation (IN) also supports the previous study
conducted by Yusr et al. (2017), Honarpour, Jusoh &
Nor (2017), and Lee et al. (2013). Based on the
discussion with experts from a property developer, it
was also explained that brainstorming and discussion
between employees lead to the creation of innovation.
And, if the knowledge sharing process is facilitated
properly, for example by the existence of a company
database where employees can store and access
information, repetition of the same mistakes can be
minimized. By the existence of the database,
employees will also be able to find new alternatives
that are better in terms of quality, time, and cost,
which of course leads to the emergence of innovation.
In line with the previous study conducted by Yusr
et al. (2017), it was also found that Knowledge
Application (KA) has a significant influence on
innovation (IN). Experts explain that teamwork
forces each individual to communicate with each
other, which then provides a great opportunity for
knowledge to be discussed and support the creation
of innovation. Training can also increase employees’
ability to innovate.
Top Management Commitment (TMC) was found
to not have a significant effect on KM. This finding
supported by previous studies conducted by Ooi
(2014) and Wickramasinghe & Widyaratne (2012).
Top management commitment talks about managers'
awareness of the importance of acquiring knowledge
to assist them in decision making (Yusr et al., 2017).
Then, it can be said that in property developers, the
managers' awareness of that important issue is still
relatively low.
In line with a previous study conducted by Ooi et
al. (2010) who said that customer needs and
expectations encourage employees to share
knowledge, it was found that Customer Focus (CF)
has a significant effect on Knowledge Sharing (KS)
process. Experts said that analysis of customer and
measurement of customer satisfaction need to be kept
and accessed as a consideration and standard in
various stages of a construction project. With this
explanation, it can be said that customer focus has a
very important influence on the knowledge sharing
process.
It was also found that People Management (PEM)
has a significant effect on Knowledge Application
(KA). According to García-Fernández (2015), the
knowledge application process consists of teamwork,
empowerment, and commitment to knowledge. From
the discussion with experts, aspects of people
management such as well-maintained bottom-up and
top-down communication, training, and a supportive
work environment are the things that strongly support
teamwork and give employees the opportunity to
provide advice and input for the company. Good
people management practices also help employees to
have an awareness to develop themselves. This thing
greatly affects the commitment to knowledge, where
the company provides guidance and training to
employees.
For Process Management (PRM), it was found to
have a significant effect on Knowledge Creation (KC)
and Knowledge Application (KA) process. This
finding was contradictory with the finding of Yusr et
al. (2017), where process management does not create
a significant effect on any KM processes in the
manufacturing sector. According to Yusr et al.
(2017), this is due to the characteristics of
manufacturing companies where the existing
operating activities tend to be short of achieving
certain goals during the production process, while the
KM process depends on the accumulation of a long
Relationship between Total Quality Management, Knowledge Management, and Innovation in the Construction Sector in Indonesia
133
process. But, in the construction sector, especially in
property developers, the existing processes have a
fairly long cycle, so it can be agreed that process
management has an influence on the KM process. In
this case, the process of knowledge sharing and
knowledge application.
Lastly, for Quality Data Reporting (QDR), it was
also found in this study that it does not have a
significant effect on any KM processes, which was
contradictory with the finding of Yusr et al. (2017).
Experts explained that in the construction sector, each
project is unique. The decisive aspect in decision
making in the construction sector is not only quality,
but also time, cost, security, comfort, aesthetics,
environmental factors, and risks that may be caused.
Therefore, in the construction sector, quality data
cannot be a single source in decision making, and the
finding that it did not provide a significant influence
in the KM processes was acceptable.
6 CONCLUSION
From this study, it can be concluded that several
TQM practices have a significant effect on KM
processes in the construction sector in Indonesia,
namely customer focus, people management, and
process management. In order to increase innovation,
knowledge sharing and knowledge application were
found to give positive support. Improving the
implementation of TQM and KM will increase
innovation in the construction sector in Indonesia.
Due to the limitations of this study, it is
recommended to evaluate the study in other sub-
sectors of the construction sector, such as contractors.
Developing a more complex relationship between
variables and adding more suitable TQM practices is
also recommended.
ACKNOWLEDGEMENTS
The Authors would like to thank the financial support
provided by Universitas Indonesia through PIT 9
funding scheme under Grant number
NKB-0087/UN2.R3.1/HKP.05.00/2019 managed by
the Directorate for Research and Public Services
(DRPM) Universitas Indonesia.
REFERENCES
Ahire, S. L., Golhar, D. Y., & Waller, M. A. (1996).
Development and validation of TQM implementation
constructs. Decision Sciences, 27(1), pp. 23-56.
Ahire, S. L., & O’Shaughnessy, K. C. (1998). The role of
top management commitment in quality management:
an empirical analysis of the auto parts industry.
International Journal of Quality Science, 3(1), pp. 5-
37.
Antunes, M. G., Quirós, J.T., & Justino, M. R. F. (2016).
The relationship between innovation and total quality
management and the innovation effects on
organizational performance. International Journal of
Quality & Reliability Management, 34(9), pp. 1474-
1492.
Badan Pusat Statistik (2017), https://www.bps.go.id/.
Bengtsson, S. H. (2017). Innovation in the construction
industry: factors, actors and the client's role. In P. W.
Chan and C. J Neilson (Eds). Proceeding of the 33rd
Annual ARCOM Conference, 4-6 September 2017,
Cambridge, UK, Association of Researchers in
Construction Management, pp. 104-113.
Bertelsen, S. & Emmitt, S. (2005). The client as a complex
system. 13th International Group for Lean
Construction Conference: Proceedings, International
Group on Lean Construction, Sydney, pp. 73-80.
Bhatt, G. D. (2001). Knowledge management in
organizations: examining the interaction between
technologies, techniques, and people. Journal of
Knowledge Management, 5(1), pp. 68-75.
Blayse, A. M., & Manley, K. (2004). Key influences on
construction innovation. Construction Innovation, 4(3),
pp. 143-154.
Bon, A. T., & Mustafa, E. M. A. (2013). Impact of total
quality management on innovation service
organizations: literature review and new conceptual
framework. Procedia Engineering, 53, pp. 516-529.
Davidson, C. (2013). Innovation in construction – before
the curtain goes up. Construction Innovation, 13(4), pp.
344-351.
Du Plessis, M. (2007). The role of knowledge management
in innovation. Journal of Knowledge Management,
11(4), pp. 20-29.
Dulaimi, M. F., Nepal, M. P., & Park, M. (2005). A
hierarchical structural model of assessing innovation
and project performance. Construction Management
and Economics, 23(6), pp. 565-577.
García-Fernández, M. (2015). How to measure knowledge
management: dimensions and model. VINE, 45(1), pp.
107-125.
Global Innovation Index (2017),
https://www.globalinnovationindex.org/.
Honarpour, A., Jusoh, A., & Nor, K. Md. (2017). Total
quality management, knowledge management, and
innovation: an empirical study in R&D units. Total
Quality Management & Business Excellence, 29(7-8),
pp. 1-19.
ICIB 2019 - The 2nd International Conference on Inclusive Business in the Changing World
134
Julison, B. (2014). Instrumen pengukuran kinerja inovasi
perusahaan kontraktor di Indonesia [Innovative
performance measurement instrument for contractor
companies in Indonesia]. Jurnal Ilmu dan Terapan
Bidang Teknik Sipil – Media Komunikasi Teknik Sipil,
20(1), pp. 19-31.
Kim, D. Y., Kumar, V., & Kumar, U. (2012). Relationship
between quality management practices and innovation.
Journal of Operations Management, 30(4), pp. 295-
315.
Kulatunga, K., Kulatunga, U., Amaratunga, D., & Haigh,
R. (2011). Client’s championing characteristics that
promote construction innovation. Construction
Innovation, 11(4), pp. 380-398.
Lee, V. H., Leong, L. Y., Hew, T. S., & Ooi, K. B. (2013).
Knowledge management: a key determinant in
advancing technological innovation?. Journal of
Knowledge Management, 17(6), pp. 848-872.
Martínez-Costa, M., & Martínez-Lorente, A. R. (2008).
Does quality management foster or hinder innovation?
An empirical study of Spanish companies. Total
Quality Management & Business Excellence, 19(3), pp.
209-221.
Mustafa, E. M. A. & Bon, A. T. (2012). Impact of customer
orientation on innovation: literature review.
Proceedings National Graduate Conference 2012, 8-10
November 2012. Putrajaya: Universiti Tenaga
Nasional.
Ooi, K. B. (2014). TQM: a facilitator to enhance knowledge
management? A structural analysis. Expert Systems
with Applications, 41(11), pp. 5167-5179.
Ooi, K. B., Cheah, W. C., Lin, B., & Teh, P. L. (2010).
TQM practices and knowledge sharing: an empirical
study of Malaysia’s manufacturing organizations. Asia
Pacific Journal of Management, 29(1), pp. 59-78.
Palmberg, K. (2009). Exploring process management: are
there any widespread models and definitions?. The
TQM Journal, 21(2), pp. 203-215.
Qasrawi, B. T., Almahamid, S. M., & Qasrawi, S. T. (2017).
The impact of TQM practices and KM processes on
organisational performance: an empirical investigation.
International Journal of Quality & Reliability
Management, 34(7), pp. 1034-1055.
Rajeshwaran, N. R. & Aktharsha, U. S. (2017).
Relationship between total quality management,
knowledge management and organizational
performance in IT organization. International Journal
of Business and Management Invention, 6(8), pp. 44-
54.
Sarwono, J., & Narimawati, U. (2015). Membuat Skripsi,
Tesis, dan Disertasi dengan Partial Least Square SEM
(PLS-SEM) [Making Undergraduate Thesis, Thesis,
and Dissertation with Partial Least Square SEM (PLS-
SEM)]. Yogyakarta: Penerbit ANDI.
Sexton, M., & Barrett, P. (2003). A literature synthesis of
innovation in small construction firms: insights,
ambiguities and questions. Construction Management
and Economics, 21(6), pp. 13-622.
Soeparto, H. G. & Trigunarsyah, B. (2014). Industri
konstruksi Indonesia: masa depan dan tantangannya
[Indonesia's construction industry: the future and its
challenges]. Konferensi Peringatan 25 Tahun
Pendidikan Manajemen & Rekayasa Konstruksi (MRK)
di Indonesia, Institut Teknologi Bandung, Department
of Civil Engineering.
Wickramasinghe, V., & Widyaratne, R. (2012). Effects of
interpersonal trust, team leader support, rewards, and
knowledge sharing mechanisms on knowledge sharing
in project teams. VINE, 42(2), pp. 214-236.
Yusr, M. M., Mokhtar, S. S. M., Othman, A. R., &
Sulaiman, Y. (2017). Does interaction between TQM
practices and knowledge management processes
enhance the innovation performance?. International
Journal of Quality & Reliability Management, 34(7),
pp. 955-974.
Relationship between Total Quality Management, Knowledge Management, and Innovation in the Construction Sector in Indonesia
135