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Impact of asymmetric trust on
construction project management
performance: the mediating role
of knowledge sharing
Xiaolin Li and Huimin Li
North China University of Water Resources and Electric Power, Zhengzhou, China
Ruirui Zhang
The First Institute of Resources and Environment Investigation of Henan Province,
Zhengzhou, China
Yilin Yin
Tianjin University of Technology, Tianjin, China
Shaonan Sun
North China University of Water Resources and Electric Power, Zhengzhou, China
Juan Bai
Anhui University of Technology, Maanshan, China, and
Ruihua Liu
North China University of Water Resources and Electric Power, Zhengzhou, China
Abstract
Purpose –The purpose of this study is to explore the impact of asymmetric trust on construction project
management performance in China’s construction industry. Moreover, the authors explore the mediating role
of two types of knowledge sharing (explicit knowledge sharing and tacit knowledge sharing) in explaining the
association between asymmetric trust and project management performance.
Design/methodology/approach –A theoretical model based on the research hypotheses proposed in this
study was developed and a questionnaire survey was conducted with 271 professionals. The data collected was
analyzed by the structural equation modeling (SEM) technique.
Findings –The results of this study indicate that there is a significant and negative association between
asymmetric trust and project management performance. Moreover, two types of knowledge sharing (explicit
knowledge sharing and tacit knowledge sharing) have different degrees of impact on improving project
management performance. In addition, tacit knowledge sharing is a mediator between asymmetric trust and
project management performance.
Research limitations/implications –The data used in this study is from Chinese scenarios, so the research
conclusions and application effects based on this are bound to have certain regional limitations. Besides, there
are many factors that affect project management performance improving, and the relationships among them
are so complex. The theoretical model proposed in this study may not be fully considered. Therefore, follow-up
researchers can consider bringing more suitable variables into their researches, so that the theoretical
researches can be more in line with the actual project management practice, and the specific mechanism for
improving project management performance can be explained more deeply.
Originality/value –This research’s value is as follows: Firstly, this paper contributes to the trust and
relational governance literature by expanding the research perspective of mutual trust to asymmetric trust.
Specially, this research designs a measurement scale for asymmetric trust and then reveals the impact
mechanism of it on project management performance, which will certainly promote research paradigm change
Impact
of asymmetric
trust
The authors acknowledge with gratitude the Key Science and Technology Projects of Henan Province
(No. 222102320174); the National Social Science Foundation of China (No. 21BGL029); and the National
Natural Science Foundation of China (No. 72271091; No. 71974056). This study would not have been
possible without their financial support.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0969-9988.htm
Received 6 May 2022
Revised 31 October 2022
16 March 2023
Accepted 2 April 2023
Engineering, Construction and
Architectural Management
© Emerald Publishing Limited
0969-9988
DOI 10.1108/ECAM-05-2022-0400
of trust. Secondly, this research is beneficial to knowledge sharing literature in the construction management
field by expanding the research scope of knowledge sharing from a cross-organizational perspective.
Keywords Asymmetric trust, Project management performance, Explicit knowledge sharing,
Tacit knowledge sharing, Project governance
Paper type Research paper
1. Introduction
The continuous improvement of construction project management performance has always
been the goal pursued by project management researchers and practitioners (Li et al., 2022). The
reason for it is that, as special products, construction projects have the characteristics of strong
technicality, large one-time investment (Kong et al., 2012), high rework cost (Eze and Idiake,
2018), implementation irreversible (Ibbs and Chih, 2011), etc., which makes construction projects
more rigorous in achieving management performance improving. Since the 21st century, the
world construction industry is moving towards a new stage, which makes construction projects
larger in scale, more intelligent and more diversified in attribute. According to a latest survey by
Ribeirinho et al. (2020), the world construction industry is undergoing nine major changes
(i.e. product-based approach, specialization, value-chain control and integration with industrial-
grade supply chains, consolidation, customer-centricity and branding, investment in technology
and facilities, investment in human resources, internationalization, sustainability), which will
push the construction industry to the next new normal-more standardization, unification and
integration. Similarly, China has been accelerating its construction industry into a new stage of
high-quality growth. As the Report of the 19th National Congress of the Communist Party of
China pointed out, the focus of economic development should be on the real economy. The
construction project, as one of the pillars of the real economy, has become one of the most
important driving forces for the real economy in China. So, under the transformation
background of construction industry all over the world, the functional attributes of construction
projects are becoming more and more complicated, making the pursuit for project management
performance more and more obvious. Thus, the goal of continuous improvement of project
management performance has become more urgent compared with other periods.
Research on the methods to improving project management performance have thus
attracted much attention in recent years. To date, researchers mainly discuss this issue from
four different perspectives: technical perspective (e.g. Ali, 2020;Jin and Zhang, 2011),
organizational perspective (e.g. Jia et al., 2021;Anyanwu, 2013), contractual governance
perspective (e.g. Wu et al., 2017;Lu et al., 2015) and relational governance perspective (e.g. Liu
et al., 2020;Benitezavila et al., 2018). And it has been pointed out that relational governance
has become more and more important (Li et al., 2022), especially in restricting opportunism
(Lu et al., 2015), as well as in strengthening the interfirm partnership and facilitating
knowledge transfer between alliance partners (Lee and Cavusgil, 2006). Here, relational
governance, also named informal governance (Helmke and Levitsky, 2004) or relational
mechanism (Jayaraman et al., 2013), refers to the extent to which one exchange relationship is
governed by social relations and shared norms (Cao and Lumineau, 2015;Poppo et al., 2008).
Many researchers regard trust as the core element of relational governance (e.g. Roehrich and
Lewis, 2010;Zhang et al., 2021), and most researchers have proven that trust plays a positive
role in improving project management performance (Cheung et al., 2013;Li et al., 2022).
However, some scholars have found the different conclusions, and even found that trust can
lead to project failure (Langfred, 2004). The reason is that the existing researches have
focused primarily on trust in the context of inter-organization relationships basing on the
implicit assumption that trust between partners in the negotiation process is symmetric
(Gulati and Sytch, 2008), neglecting another distribution state of trust among the contracting
parties, namely asymmetric trust (Graebner, 2009;De Jong and Dirks, 2012).
ECAM
As the “theory of gap”and “a promising missing link”in trust research (Gulati and Sytch,
2008), asymmetric trust has gradually attracted scholars’attention since the influential work
of Graebner (2009). Current research perspectives focusing on asymmetric trust can be
divided into two groups, namely information preference perspective and mutual trust degree
perspective, of which the latter is the more accepted viewpoint. From the viewpoint of the
latter, asymmetric trust refers to the difference of trust degree among individuals (Graebner,
2009). In fact, it is quite rare that the trust level is distributed symmetrically among
transaction partners. On the contrary, trust distributing asymmetrically is closer to the real
world (Korsgaard, 2014). Take owner-contractor relationships in construction projects as an
example. Considering the differences in market position, resource demand and risk
management ability, the trust between the owner and the contractor is usually asymmetric (Li
et al., 2019a,b). Specifically, the construction market in China is so competitive. According to
CCIA (China Construction Industry Association), there were 128,746 biding contractors in
2021, with an increase rate of 10.31% over the previous year. So, owners have more choices,
while contractors have to face fierce competition in project bidding stage. This could usually
cause an asymmetric trust relationship between owners and contractors. That is, owners tend
to give contractors a lower degree of trust. For example, to understand the trust level among
EPC project stakeholders in China, Shen et al. (2017) did an investigation by responding on a
five-point Likert scale (1 5very low and 5 5very high). They found the trust of contractors
on owners scored 4.02, ranking the first. However, according a recent survey based on 173
construction projects in China by Li et al. (2022), owners’trust on contractors scored pretty
low, indicating a significant difference with the former result of 4.02. Several factors can cause
lower trust in this case. The first one is the unpleasant cooperation experience in the past. To
be specific, if one contractor does not meet the expectation of an owner, the owner tends to
think that all contractors are likely to disappoint, and then the owner may distrust
contractors in general (Busch and Hantusch, 2000), causing their trust level toward
contractors to decrease. The subsequent one is about the market factor. The typical buyer’s
market means that contractors have to do more to win owners’trust. In such situation, owners
have advantages in many aspects. So, to guarantee their interests and rights, owners are
more willing to adopt excessively controlling and monitoring behaviors, such as over-control,
over-monitoring and excessive self-defense, leading to the decrease of trust (Li et al., 2019a,b).
Finally, as a developing country, China’s laws and regulations system is not so sound, so the
cost for contractors to safeguard their own rights and interests is still relatively high. If
owners refuse or deliberately delay the payment obligation due to dissatisfaction with the
cooperative relationships, contractors will suffer huge losses. So, in order to establish and
maintain good trust relationships with owners, contractors with low bargaining power
(Ryciuk, 2017) often have to resort to flattery, social dinners, gift giving or even bribery (Li
et al., 2019a,b). Though there have been attempts to look into the area of asymmetric trust in
other research fields (Graebner, 2009;De Jong and Dirks, 2012;Wang et al., 2015;Gulati and
Sytch, 2008;Malaquias and Hwang, 2016), limited research has taken the initiative to
specifically discuss asymmetric trust in the construction management field, and there are no
clear studies showing that asymmetric trust is universally related to construction project
management performance. So, there is a significant gap between thinking from academic
research of asymmetric trust and project management practice that needs to be bridged.
Given the huge differences in cognition, culture, organizational structure of enterprises and
development degree of local system, asymmetric trust may be more prominent and serious in
China (Krishnan et al., 2006).
Besides, with construction technology development and project requirements becoming
more and more complicated, construction industry’s knowledge-intensive degree is getting
higher and higher (Deng et al., 2022). According to a survey administered to CEOs of
construction enterprises, knowledge is regarded as the most critical strategic asset (Sik-wah
Impact
of asymmetric
trust
Fong and Chu, 2006). To observe project management from a knowledge management
perspective is not really a new research direction in the construction industry (Li et al., 2017),
and many researchers have been lured to explore this concept from an intra-organizational
perspective (e.g. Zhang and Sun, 2020;Li et al., 2019b;Zhang and Ng, 2013;Ding et al., 2013;
Bhatti et al., 2021;Kucharska and Erickson, 2019), ignoring the interaction of knowledge
sharing among enterprises in the construction industry (Hao et al., 2019). However, inter-
organizational knowledge sharing has an important impact on project management
performance. In reality, the knowledge capability that organizations develop from
collaborating with external partners is believed to help them minimize disruption to
normal operations and prevent mistakes (Blome et al., 2014;Li et al., 2017). Consequently,
identifying and evaluating the types of knowledge sharing that affect project management
performance during project implementation is a critical task for researchers and
practitioners. Besides, the role of trust in promoting knowledge sharing has been generally
recognized (Phong et al., 2018;Buvik and Rolfsen, 2015;Park and Lee, 2014), and the positive
correlation between interpersonal distrust and knowledge hiding can also provide evidence
for the former researches (Connelly et al., 2012). So, it can be seen that knowledge sharing can
be used as the key to open the black box of the relationship between asymmetric trust and
project management performance.
In a word, there are two gaps that need to be addressed: Firstly, there is a significant gap
between thinking from the academic research of asymmetric trust and project management
practice that needs to be bridged. In other words, the impact of asymmetric trust on
construction project management performance needs to be explored. Secondly, previous
researches ignore the interaction of knowledge sharing among enterprises in the
construction industry. To address such gaps, this research establishes a theoretical model
of “asymmetric trust-knowledge sharing-project management performance”from the
perspective of asymmetric trust and knowledge-based view. Subsequently, the empirical
test designed for the theoretical model was conducted. The purpose of this study is to
explore the impact of asymmetric trust on construction project management performance
in China’s construction industry. Moreover, this research aims to explore the mediating
role of two types of knowledge sharing (explicit knowledge sharing and tacit knowledge
sharing) in explaining the association between asymmetric trust and project management
performance.
2. Theoretical background and hypotheses development
2.1 Asymmetric trust
That asymmetric trust exists and is an important phenomenon initself has been acknowledged
in the management literature (Korsgaard et al., 2015). Furthermore, Korsgaard et al. (2015)
distinguished different types of trust: reciprocal trust, mutual trust and asymmetric trust. In
contrast to mutual trust, asymmetric trust allows that partners in a dyad may have
substantively different levels oftrust (Tomlinson and Mryer, 2009). Asymmetric trust can take
on a variety offorms, depending on its degree and direction (Tomlinson and Mryer, 2009). With
regard to the degree, asymmetric trust can be conceptualized as varying along a continuum
from complete asymmetry to complete congruence. As for the direction, it describes the
difference between two partners who trusteach other. The direction of asymmetry is likely to be
important when partners occupy unique roles in relation to one another, such as the leader and
the follower (Korsgaard et al., 2015). Unlike the positive role of mutual trust in improving
cooperation performance (Kim et al., 2018;Padma et al., 2017;Susilo and Diharto, 2018), scholars
posit that asymmetric trust is disruptive to joint outcomes of the dyad (Tomlinson and Mryer,
2009;Call and Korsgaard, 2013). They explained the reason: mutual trust, even at low levels of
trust, has its virtue. In mutual trust relationships, partners are more apt to share mental models,
ECAM
and individual actions are more predictable, even if predictably untrustworthy. On the
contrary, asymmetric trust can result in lower joint outcomes than moderate levels of
mutual trust.
2.2 Knowledge sharing
In the 21st century, known as the era of knowledge economy, various organizations must
undertake effective knowledge management work to improve organizational performance
and core competitiveness continuously (Ni et al., 2018). As “temporary organizations”,
construction projects (Brookes et al., 2017) are no exception. In recent years, construction
projects have become more complex, dynamic and interactive situations (Ni et al., 2018).
According to a survey administered to CEOs of construction companies, knowledge is
regarded as the most critical strategic asset (Sik-wah Fong and Chu, 2006) because that
knowledge sharing and professional skills sharing among employees of construction
companies inside and outside the team can help overcome the challenges and adverse effects
caused by project complexity (Ribeiro, 2009;Cooke, 2013). Construction projects involve
many knowledge resources, such as ideas in management, technology, economy, law,
computer, psychology, sociology, organizational behavior and so forth (Ni et al., 2018).
Scholars divided knowledge into tacit knowledge and explicit knowledge (Jain and Moreno,
2015). General speaking, both tacit knowledge sharing and explicit knowledge sharing can
extenuate the influence of construction project complexity (Cooke, 2013). And to cope with
complex tasks, employees in construction firms need to share knowledge and expertise
within and between groups (Ribeiro, 2009). Therefore, project management organizations
need to be aware of the advantages of knowledge-sharing initiatives and practices (Chen and
Mohamed, 2010;Ribeiro, 2009).
2.3 Project management performance
Performance measurement is at the heart of ceaseless improvement (Kim and Huynh, 2008),
and the primary dimensions for measuring project management performance are cost,
schedule and quality. This study measures project management performance by learning
from previous researches focusing on project management performance theme (e.g.
Demirkesen and Ozorhon, 2017;Ma et al., 2021;Naji et al., 2020;Bjorvatn and Wald, 2018). To
be specific, majority of the researches measure project ma nagement performance with timely
completion (Bjorvatn and Wald, 2018;Demirkesen and Ozorhon, 2017;Zidane and Andersen,
2018), under budget completion (Papke-Shields et al., 2010;Berssaneti and Carvalho, 2015;
Bjorvatn and Wald, 2018;Demirkesen and Ozorhon, 2017) and meeting quality criteria (Tam
et al., 2011;Chang et al., 2013;Chou et al., 2013;Demirkesen and Ozorhon, 2017). Moreover, it
is believed that the evaluating on project management performance should not only consider
the result determinants such as the above ones, but also take the process determinants such
as client satisfaction with projects into account (Davis, 2016;Gayatri and Saurabh, 2013;
Cserh
ati and Szab
o, 2014;Nassar and Abourizk, 2014;Demirkesen and Ozorhon, 2017). This
is important because most stakeholder groups occasionally attempt to influence
project implementation in line with their expectations (Olander and Landin, 2008). In the
light of previous studies, this study also utilizes those mostly cited indicators to measure
construction project management performance.
2.4 Asymmetric trust and knowledge sharing
As mentioned previously, asymmetric trust allows that partners in a dyad may have
substantively different levels of trust (Tomlinson and Mryer, 2009). In short, asymmetric
trust is the divergence between firm A’s trust on firm B and the latter’s trust on the former.
Impact
of asymmetric
trust
So, it can be described in forms of direction and degree. For the degree, asymmetric trust can
be conceptualized as varying along a continuum from complete asymmetry to complete
congruence. Asymmetric trust also varies in terms of the direction, that is, which member of
the partner trusts more and to what degree (Korsgaard, 2014). Scholars believe that
asymmetric trust is not beneficial to establish positive partnerships, and will lead to low
cooperation performance (Tomlinson and Mryer, 2009). This is because within asymmetric
trust context, the initial action of the partner with higher trust is cooperation. However, if this
partner has not received positive trust feedback from the other partner for a long time, it will
give up cooperation (Call and Korsgaard, 2013). Current empirical researches also suggest
that cooperation is crucial to knowledge sharing (e.g. Levin and Cross, 2004;Lucas, 2005). So,
it can be seen that asymmetric trust leads to low cooperation level, which will subsequently
have a negative impact on knowledge sharing. In addition, it has pointed out that knowledge
sharing and learning are more likely to occur in trusting relationships (Qureshi et al., 2018).
This is because when trust exists, people are more willing to seek and absorb one another’s
knowledge (Levin and Cross, 2004) and are themselves more willing to provide insights and
useful knowledge. On the contrary, asymmetric trust weakens the positive relationship
between mean trust and cooperative behaviors such as knowledge sharing (Thomas and
Skinner, 2010;Korsgaard, 2014). Based on the above analysis, the research hypothesis H1 is
proposed:
H1. Asymmetric trust between project partners has a negative impact on knowledge
sharing.
H1a. Asymmetric trust between project partners has a negative impact on explicit
knowledge sharing.
H1b. Asymmetric trust between project partners has a negative impact on tacit
knowledge sharing.
2.5 Asymmetric trust and project management performance
Many scholars have pointed out that asymmetric trust will compromise cooperative
performance in dyadic relationships (Call and Korsgaard, 2013). This is because that
asymmetric trust can restrain performance improving brought by mutual trust, which is very
unfavorable for the partner with higher trust level (Korsgaard, 2014). Similarly, Thomas and
Skinner (2010) believed that asymmetric trust can weaken the positive links between total
trust and collaborative behaviors (e.g. knowledge sharing routines, relationship specific
assets and complementary task execution) in inter-organizational relationships. This
attenuating effect may occur because the higher trust partner may consider diminishing its
collaboration in the asymmetric trust relationship in order to match the other partner’s trust
level of involvement. De Jong and Dirks (2012) found that asymmetry in dyadic trust
moderated the relationship between mean trust within groups and team performance such
that this relationship was weaker when trust asymmetry was high. In a word, asymmetric
trust limits the benefits of mean trust (Korsgaard et al., 2015). Besides, as Tomlinson and
Mryer (2009) pointed out, symmetric trust in dyadic relationships will bring benefits to
cooperation performance, while asymmetric trust will lead to lower cooperation performance.
Similarly, Wicks and Berman (2004),Vanpoucke et al. (2021) argued that asymmetric trust
has a negative impact on organizational performance. In project management research field,
Wang et al. (2015) pointed out that asymmetric trust is easy to cause participants’speculative
behaviors. Specifically, considering contractors’tendency to reduce project quality and their
efforts involved during project implementation, owners may suspect that contractors will not
implement projects according to their signed contracts. For contractors, they may wonder
owners’ability to provider payments. Ultimately, these suspicious behaviors caused by
ECAM
asymmetric trust will not only affect project results, but also increase the unreasonable
project costs (Cheung et al., 2011;Li et al., 2019a,b). So, asymmetric trust behavior has a
negative impact on project management performance (Li et al., 2019a,b). Based on the above
analysis, the research hypothesis H2 is proposed:
H2. Asymmetric trust between project partners has a negative impact on project
management performance.
2.6 Knowledge sharing and project management performance
Empirical researches based on the data from contractors confirmed that knowledge sharing
within contractor organizations can actively improve project performance (e.g. Kivrak et al.,
2014). What’s more, it is found that the earlier knowledge sharing occurs, the more significant
improvement effect of project performance can achieve. Conversely, the lack of knowledge
sharing is the key factor leading to construction projects failure (Nahyan et al., 2019). For this
reason, knowledge sharing is also regarded as the key management processes affecting
project success (Nahyan et al., 2019;Tan, 2015). In addition, scholars also have found that
cross-organizational knowledge sharing can quickly promote the acquisition, using and
innovation of project knowledge and then greatly improve project construction efficiency.
Besides, as Juozas and Renatas (2012) pointed out, knowledge sharing can trigger the
synergy of team cooperation in construction projects, especially in the temporary and one-off
cooperative relationship between owners and multi-contractors. Lin and Wang (2019) also
pointed out that knowledge sharing between DBB project owners and contractors plays a
vital role in improving project cooperation quality, shortening construction period and
consolidating cooperation relationship. So, the research hypothesis H3 is put forward:
H3. Knowledge sharing between project partners has a positive impact on project
management performance.
H3a. Explicit knowledge sharing between project partners has a positive impact on
project management performance.
H3b. Tacit knowledge sharing between project partners has a positive impact on project
management performance.
2.7 Mediating effects
As Schoorman et al. (2007) had already pointed out, trust only provided confidence guarantee
of not being cheated for project partners, but there must be some mediating mechanisms for
its impact on project success. Similarly, the impact of asymmetric trust on project
management performance can also be achieved by mediator variables. Based on the
hypothesis 1 and hypothesis 3, we assume that the impact of asymmetric trust on project
management performance will also be indirectly achieved via mediator variable
(i.e. knowledge sharing).
H4. Knowledge sharing mediates the impact of asymmetric trust on project management
performance.
H4a. Explicit knowledge sharing mediates the impact of asymmetric trust on project
management performance.
H4b. Tacit knowledge sharing mediates the impact of asymmetric trust on project
management performance.
The theoretical model is drawled based on hypotheses H1∼H4, as shown in Figure 1.
Impact
of asymmetric
trust
3. Research method
3.1 Questionnaire design
Questionnaire survey is adopted to collect data for this study. And also, measurement items from
published literature are adopted for the variables in the research model. After designing the
questionnaire, experienced practitioners and professionals are invited to give their optimization
suggestions on the initial questionnaire, and then questionnaire items are modified or deleted
according to their feedbacks. Akin to Ahmad et al. (2019), the criteria for determining the
“experienced practitioners and professionals”invited to give their optimization on the
questionnaire is based on the following ones: Firstly, academic scholars focusing on project
management performance for a long time are invited to optimize the initial questionnaire. Secondly,
industry experts who have worked for more than ten years and are responsible for large-scale
construction projects are also invited to do the same thing. To be specific, a preliminary review of
the initial questionnaire was conducted by four academic scholars. Subsequently, six industry
experts were asked to comment on the content and scope of the initial questionnaire. Some minor
amendments related to some of the questions were suggested by the participants, based on which
the questionnaire was revised. In addition, a pretest on the questionnaire was carried out before the
formal questionnaire survey. The purpose of pretest before a formal survey is as follows: Firstly, to
determine whether the questions are properly framed and to determine whether the wording of the
questions will achieve the desired results. Secondly, to know if the questions have been placed in
the best order and if the questions are understood by all classes of respondents. Finally, to know
whether additional or specifying questions are needed or some need to be eliminated (Roopa and
Rani, 2012). Different from the large sample required for formal survey, the sample size of pretest
tends to range from two, three to over twenty (Grealish, 2004;DeMaio and Landreth, 2004;Olson,
2010;Ikart, 2019). In this research, 90 questionnaires were distributed to owners in Zhengzhou,
Henan province, China. As a result, 75 questionnaires were recovered and 60 valid ones were
obtained, which meets the requirement of pretest on sample size. Besides, pretest requires selecting
the sample similar in socioeconomic background and geographic location which is intended to be
used in the formal survey. In this study, we selected Zhengzhou as the location of the pretest, which
then was also used as one of the formal survey locations. In a word, the sample of the pretest has
good representativeness. Based on the data gathered from these questionnaires, a small sample
pretest was undertaken, and none of items of the questionnaire shall be deleted. After previous
steps have been met, the final questionnaire is obtained whose items are shown in Appendix.Each
measurement criterion adopted a 5-point Likert scale.
It is worth noting that this research designs an asymmetric trust scale for the present
research. Theoretically speaking, the measurement on asymmetric relationship generally needs
the help of reciprocal data (Graebner, 2009). However, some scholars also pointed out that in
order to ensure confidentiality and prevent subjective prejudice from respondents to the former
in the second interview and questionnaire survey, nonreciprocal data shall be adopted in dyadic
models. Nonreciprocal data was also widely used in previous researches (e.g. Li et al., 2022;
Figure 1.
Research model based
on the hypotheses
ECAM
Gulati and Sytch, 2008;Brinkhoff et al., 2015). Therefore, this research designs an asymmetric
trust scale based on the published research and aims to collect nonreciprocal data from China’s
construction industry.
3.2 Sampling and procedure
Owners are the overall integrators and organizers in construction projects. In particular,
owners have authorities to exclude anybody from working during project implementation
when dispute events occur (Besley and Ghatak, 2001). Moreover, plenty of researches
focusing on project management performance have collected empirical data just from owners
(i.e. Ke et al., 2015;Brinkhoff et al., 2015). Thus, the present research take owner as data
resource. The survey was limited to Jiangsu, Zhejiang, Henan, Guangdong, Sichuan and
Shandong provinces. These six provinces can be considered representative in the Chinese
construction industry because they completed 38.9% of the country’s total output value of
construction in 2020.
In addition,the form of electronic survey was adopted in this study for the following reasons:
First of all, electronic survey holds the advantages of cost reduction (Fernando and Chukai,
2018), and the speed of data collection by electronic survey can be dramatically increased
compared with paper survey (Zhuang et al., 2021). Besides, electronic survey affords
respondents great flexibility in offering their responses at their convenience in time and place
(Adom et al., 2020). What’s more, the absence of the researcher’s presence aids in reducing all
forms of biases in responses, ensuring high objectivity (Minto et al.,2017). The main form of the
electronic survey used in this study is electronic questionnaire. To be specific, we use E-mail
and chatting software such as WeChat to distribute questionnaires to owner companies in the
six provinces and then recover the distributed questionnaires. In particular, to improve the
recovery rate, we contact the respondents who is in charge of the survey once a week. And
the survey lasted for six months from July 2021 to December 2021. A total of 400 electronic
questionnaires were distributed, and then 321 were recovered, with an effective recovery rateof
80.02%. By eliminating invalid questionnaires, 271 valid questionnaires were finally obtained
which meeting the needs of empirical analysis (Boomsma and Hoogland, 2001;Kline, 2015).
3.3 Common method bias
The data collected from respondents was self-reported in the present research. So, it is
imperative to prevent the issue of common method bias. For this reason, two methods were
adopted, namely ex ante control and ex-post control. In ex ante control, a brief explanation
consisting of investigation purpose and confidentiality measures dispels respondents’doubts
on the survey. With regard to ex-post control, we adopted Harman’s single-factor test and
confirmatory factor analysis. First of all, we conducted exploratory factor analysis to extract
common factors from all items (KMO 50.853; Bartlett spherical test is significant at the level
of 0.001). By this way, we got 4 factors, which was in line with the questionnaire structure.
And the variance accounted by the first factor before rotation is less than 40%. Moreover,
confirmatory factor analysis was carried out to load all the items on a common factor. The
results indicated that the model’s fit index was worse than that of the initial model.
Consequently, it can be believed that there is no common method bias in this study.
4. Results and analysis
The research model of this research is tested though a Partial Least Squares approach by means
of Smart-PLS 3.0 software. Smart-PLS 3.0 software has many obvious advantages. For instance,
neither large samples nor the normally distributed data is required in PLS analysis (Hair et al.,
2017). That’s to say, PLS has a higher statistical power (Hair et al., 2019). The research model was
Impact
of asymmetric
trust
tested via a two-step process. Firstly, we estimated the measurement model to identify
constructs’reliability and validity. Then, we tested the structural model to identify the
significance and the strength of the relationships between variables in the research model.
4.1 Descriptive analysis
Characteristics of 271 respondents and projects are presented in Table 1. As can be seen in Table 1,
college degree or above accounts for 94.10% of all the respondents, and 56.09% of the respondents
have worked in their positions for three years or more. With respect to current position, project
manager or above accounts for 38.38% of the respondents. All of these ensure that the respondents
were familiar with construction projects and can understand the survey items.
4.2 Measurement model
As stated previously, the first step estimating constructs’reliability and validity (i.e. testing
the measurement model) is adopted. Specially, an evaluation of the measurement model is
conducted to estimate reliability and validity following the recommendation provided by Hair
et al. (2017). Here, reliability consists of two aspects: the reliability of individual items and the
reliability of the constructs. The reliability of individual items is evaluated by factor loadings.
As shown in Table 2, factor loadings of all items are significantly exceeded 0.7, lending
Characteristic of respondents Frequency Characteristic of projects Frequency
Education Total investments
Doctor degree or above 30(11.1%) >500mn RMB ($72.1mn) 87(32.1%)
Master degree 91(33.6%) 100–500mn RMB ($14.4–72.1mn) 53(19.6%)
College degree 134(49.4%) 50–100mn RMB ($7.2–14.4mn) 86(37.1%)
Others 16(5.9%) <50mn RMB ($7.2mn) 45(16.6%)
Work experience Project type
＞10 years 94(34.7%) Office and residential construction 99(36.5%)
6–10 years 13(4.8%) Industrial construction 42(15.5%)
3–5 years 45(16.6%) Public construction 26(9.6%)
<3 years 119(43.9%) Infrastructural construction 55(20.3%)
Job position Commercial construction 29(10.7%)
Manager at the headquarters 51(18.8%) Others 20(7.4%)
Project manager 53(19.6%) Project delivery system
GMTP
Others
152(56.1%) DBB/DB 136(50%)
15(5.5%) EPC/PPP 135(50%)
Note(s): GMTP 5General management/technical personnel
Source(s): Author’s own creation
Variable Items LOA CR
α
AVE Variable Items LOA CR
α
AVE
AT AT1 0.87 0.93 0.91 0.78 TKS4 0.75
AT2 0.92 EKS EKS1 0.95 0.95 0.89 0.90
AT3 0.85 EKS2 0.95
AT4 0.89 PMP PMP1 0.86 0.89 0.82 0.66
TKS TKS1 0.89 0.87 0.80 0.63 PMP2 0.70
TKS2 0.79 PMP3 0.71
TKS3 0.73 PMP4 0.78
Note(s): LOA 5factor loadings; CR 5composite reliability;
α
5Cronbach’s alpha; AT 5asymmetric trust;
TKS 5tacit knowledge sharing; EKS 5explicit knowledge sharing; PMP 5project management performance
Source(s): Author’s own creation
Table 1.
Characteristics of
respondents and
projects
Table 2.
Reliability and validity
analysis
ECAM
support that there is an appropriate level of reliability (Hair et al., 2017). Moreover, the
reliability of construct measures is evaluated by composite reliability and Cronbach’s alpha.
The values of composite reliability and Cronbach’s alpha in Table 2 exceed 0.7 and 0.7,
respectively, both of which are threshold values (Hair et al., 2017). These results demonstrate
that all reliabilities are within acceptable ranges.
In addition, the constructs’validity is evaluated with convergent validity and
discriminant validity. Convergent validity is evaluated using average variance extracted
(AVE). As shown in Table 2, all constructs’AVE value exceeds 0.50 threshold level,
indicating their convergent validities are adequate and satisfactory (Hair et al., 2017). With
regard to discriminant validity, it is evaluated with three approaches as the following ones:
Firstly, cross-loadings of measurement items are adopted. In the present research, each item’s
loading on its own construct (the italic values) exceeds the cross-loadings on the other
constructs. Secondly, we conduct the analysis with Fornell–Larcker criterion. As shown in
Table 3, square roots of all constructs’AVEs (the diagonal elements) exceed the correlation
between the constructs, demonstrating adequate and appropriate discriminant validity
(Fornell and Larcker, 1981). Finally, the HTMT approach proposed by Henseler et al. (2015) is
adopted. Results in Table 3 indicate that none of the HTMT ratios exceed 0.90 threshold level.
The HTMT
inference
criterion which is evaluated by complete bootstrapping, demonstrates
that the uppers of 97.5% confidence bounds are all less than 1. As a result, discriminant
validity problems are not a concern in the present research.
Though evaluation on constructs’reliability and validity, we conclude that the designed
scales are reliable and valid in measuring constructs included in the research model. So, they
could be used to the subsequent analysis on structural model.
4.3 PLSpredict and blindfolding for model assessment
Akin to Shiau et al. (2020), this research adoptedthe blindfolding technique to assessthe model’s
predictive relevance and explanatory power. By using blindfolding procedure, the results of Q
2
scores for asymmetric trust (Q
2
50.269), explicit knowledge sharing (Q
2
50.679), tacit
knowledge sharing (Q
2
50.527) and project management performance (Q
2
50.769) are all more
than 0, showing that the research model has predictive relevance. Besides, it is pointed out that
Q
2
is ad hoc metric that does not provide highly interpretable results in terms of prediction error
magnitude (Shmueli et al., 2016). Moreover, Q
2
is not true measure of out-of-sample prediction,
as blindfolding procedure does not omit entire observations, but only data points.
Addressing this concern, Shmueli et al. (2019) pointed out that it is necessary to adopt
PLSpredict procedure to assess a model’s out-of-sample predictive power. The PLSpredict
procedure, which was propose by Shmueli et al. (2016), generates holdout sample-based
predictions and executes k-fold cross-validation, proving a good method to calculate the
predictive power of the PLS-SEM model. So, the PLSpredict procedure was adopted to assess
the research model’s predictive relevance. To be specific, the PLS prediction procedure
separates training and holdout samples with the aim to estimate model parameters and
evaluate the model’s predictive power. For current research, RMSE and mean absolute error
(MAE) were used akin to Damberg (2022),Low and Spong (2022) and Shiau et al. (2020).
AT EKS PMP TKS
AT 0.88
EKS 0.00 0.95
PMP 0.40 0.17 0.82
TKS 0.17 0.13 0.37 0.79
Source(s): Author’s own creation
Table 3.
Correlation matrix
Impact
of asymmetric
trust
The results are presented in Table 4. The PLS-SEM is less that the linear regression model
(LM) value for all indicators, suggesting that the model has high predictive power.
4.4 Structural model
The second step testing the structural model is also adopted. To test hypotheses proposed in
this research, the full PLS-SEM structural model was created to estimate the path coefficients
between all constructs (hypotheses H1-H4). In order to assess the structural model, several
criteria are adopted. The standardized root mean square residual (SRMR) is the first one.
SRMR is recommended as the approximate criterion of model fit proposed by Henseler et al.
(2016). According to the instruction of Smart-PLS, a SRMR value less than 0.10 represents a
good fit. The SRMR value of the structural model is 0.05, meeting the threshold level. In
addition, according to the calculation formula of the GoF index (GoF ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
communality 3R2
q)
proposed by Amato et al. (2004), the goodness-of-fit index (GoF) of the research model was
tested. After calculation, GoF 50.403, which is greater than the maximum standard value of
0.36, indicating that the model has good goodness-of-fit index.
As is recommended by Hair et al. (2017), the significance of all path coefficients is assessed
through bootstrapping with 271 cases and 5,000 subsamples. The path coefficients of the
relationships proposed in the research model are presented in Table 5. As proposed in H1b,
asymmetric trust has a negative and significant effect on tacit knowledge sharing
(β50.175, p< 0.001). Similarly, as proposed in H2, asymmetric trust has a significant and
negative effect on project management performance (β50.345, p< 0.001). As hypothesized
in H3a and H3b, both explicit knowledge sharing and tacit knowledge sharing are positively
associated with project management performance, providing supports for H3a (β50.133,
p< 0.05) and H3b (β50.289, p< 0.001). However, asymmetric trust is found to have no
significant impact on explicit knowledge sharing, demonstrating that H1a is not supported.
PLS-SEM LM
Items Q
2predict
RMSE MAE RMSE MAE
ESK1 0.105 0.589 0.612 0.789 0.689
ESK2 0.212 0.449 0.551 0.748 0.647
PMP1 0.191 0.509 0.391 0.510 0.393
PMP2 0.217 0.260 0.258 0.459 0.350
PMP3 0.208 0.187 0.187 0.486 0.383
PMP4 0.272 0.162 0.251 0.461 0.334
TSK1 0.059 0.601 0.340 0.603 0.438
TSK2 0.068 0.617 0.262 0.618 0.454
TSK3 0.055 0.592 0.429 0.593 0.431
TSK4 0.052 0.595 0.432 0.596 0.436
Source(s): Author’s own creation
Hypothesis βtpSupport Hypothesis βtpSupport
H1a:AT→EKS 0.004 0.06 0.950 No H3a:EKS→PMP 0.133 2.69 0.010 Yes
H1b:AT→TKS 0.175 3.20 0.000 Yes H3b:TKS→PMP 0.289 5.58 0.000 Yes
H2:AT→PMP 0.345 7.33 0.000 Yes
Note(s): β5Path coefficient
Source(s): Author’s own creation
Table 4.
PLSpredict assessment
results
Table 5.
Estimates for the
research model
ECAM
To further test the mediating effect of H4, the bootstrap technique is used to test the
hypotheses. As H1a is rejected, H4a is not established. Take H4b as an example. The research
seeks to meet three requirements: (1) asymmetric trust should pose a significant effect on
project management performance, (2) asymmetric trust should pose a significant effect on
tacit knowledge sharing and (3) when tacit knowledge sharing is added to the asymmetric
trust and project management performance model, the standardized estimate of the path of
asymmetric trust to project management performance may become insignificant (whole
mediation) or may weaken before adding tacit knowledge sharing (partial mediation).
Besides, it must be noted that tacit knowledge sharing has a significant effect on project
management performance. In the present research, H2 satisfies the requirement of (1), and
H1b satisfies the requirement of (2). And also, the supported H3b indicates that tacit
knowledge sharing has a significant effect on project management performance. So, it is
possible to construct mediation model to confirm the mediation role of tacit knowledge
sharing. The results show that the direct effect of mediated asymmetric trust on project
management performance is significant (β50.345, t 57.33, p< 0.0001), while the indirect
effect through knowledge leadership is significant (a*b 50.055, t 53.183, p< 0.001).
Supported H4b indicates that tacit knowledge sharing plays a partial mediation role between
asymmetric trust and project management performance.
5. Discussions and implications
5.1 Discussions
5.1.1 Impact of asymmetric trust on explicit knowledge sharing and tacit knowledge sharing. In
the test about H1, it is found that the hypothesis H1b (asymmetric trust-tacit knowledge
sharing) is supported, that is, asymmetric trust has significant effect on tacit knowledge
sharing. Obviously, this is consistent with most existing research results (e.g. Wang et al.,
2015;Graebner, 2009), that is, asymmetric trust weakens the positive relationship between
mean trust and cooperative behaviors such as knowledge sharing. This may be because that
the dominant partners (i.e. owners) have comparative advantages in selecting their project
partners (i.e. contractors) within asymmetric trust relationships, and they can adopt
corresponding cooperation strategies based on their pre-judgment of performance abilities,
the possibility of fulfilling commitments, integrity and honesty to their partners. For example,
in order to protect their own interests, the dominant partners (i.e. owners) may strengthen
over-control, over-monitoring and excessive self-defense to their partners (i.e. contractors) (Li
et al., 2019a,b). The phenomenon that owners tend to be uncooperative in asymmetric trust
relationships can also be explained by the construction industry attribute of China, which is a
typical buyer’s market (Ryciuk, 2017).
In addition, it is found that the hypothesis H1a (asymmetric trust-explicit knowledge
sharing) is not supported, that is, asymmetric trust has no significant effect on explicit
knowledge sharing. Obviously, compared with tacit knowledge sharing which is another
type of knowledge sharing, asymmetric trust has little effect on it. As scholars have pointed
out, explicit knowledge sharing in owner-contractor relationships mainly relies on explicit
means such as written documents, work-related tools and software, operation specifications
and trainings (Bock et al., 2010). These means are characterized by regularity, systematicness
and objectivity (Skyrme and Amidon, 1997). And also, these explicit means are easy and
convenient to obtain and operate, and can be institutionalized by means of formal documents,
reports and models (Huang et al., 2014). Consequently, once the formal cooperation
relationship is established, even if there is a certain degree of asymmetric trust between
owners and contractors, they will not completely stop explicit knowledge sharing-it is a
necessary condition for cooperation. Different from this, tacit knowledge sharing is mainly
manifested in insights, judgment, know-how, mental models, intuition and beliefs
Impact
of asymmetric
trust
(Kalpi
c and Bernus, 2006;Yazici et al., 2020), which needs to be realized by direct
conversation, telling of stories and sharing common experiences (Kalpi
c and Bernus, 2006).
In a word, tacit knowledge sharing puts forward higher requirements for both partners. So,
the knowledge owner tends to hide tacit knowledge within asymmetric trust relationships.
On the contrary, for the convenience of explicit material acquisition, even within asymmetric
trust relationships, there is still a certain degree of explicit knowledge sharing.
5.1.2 Impact of tacit and explicit knowledge sharing on project management performance.
The supported H3a indicates that explicit knowledge sharing has a significant impact on
project management performance (β50.133; p< 0.05). Similarly, the supported H3b indicates
that tacit knowledge sharing also has a significant impact on project management
performance (β50.289; p< 0.001). Here, the βrepresents the path coefficient and indicates
the relative strength of relationships between all variables in the analysis (Michaels and
Spector, 1982). Since 0.289 > 0.133, it is obvious that tacit knowledge sharing has a stronger
impact on promoting project management performance than that of explicit knowledge
sharing, which is consistent with Schoenherr et al. (2014),Swink (2006) and Goffin and Koners
(2011). Several reasons can account for such phenomenon. Firstly, as the Knowledge-based
view’s view, resources are heterogeneous and imperfectly mobile, decreasing their tendency
to become redundant (Schoenherr et al., 2014). In construction projects, tacit knowledge is a
highly personalized and valuable asset as it has roots in human brain, relates to individual
experience and can hardly be transferred directly (Chinowsky and Carrillo, 2007;An and
Ahmad, 2010). So, compared with explicit knowledge sharing, it is the hard-to conceptualize
property of tacit knowledge that can generate greater project management performance.
Secondly, tacit knowledge in construction project organizations often refers to the knowledge
based on individuals’experience, expertise or practical know-how that cannot be explicitly
described (Karhu, 2002;Koskinen et al., 2003). So, tacit knowledge can provide a greater
application foundation for project management performance improving. As Maqsood et al.
(2006) said, project teams prefer to use tacit knowledge rather than explicit knowledge such
as textbooks and established analytical approaches. Thus, tacit-knowledge sharing is
therefore more critical for improving team collaboration and effectiveness in the construction
sector (An and Ahmad, 2010;Rezgui et al., 2010;Zhang and He, 2016). Finally, some scholars
have also pointed out that explicit knowledge sharing can enable enterprises to acquire
technical criteria and principle, while tacit knowledge sharing can help enterprises acquire
technical knowledge (e.g. know-how skills) and professional experience (Al-Zoubi et al., 2019).
These technical know-how and professional experience often spread rapidly by means of
informal methods, so that the corresponding effect can quickly emerge. Based on this
knowledge, individuals can effectively avoid repetitive work, which is more important to
improve project management performance.
5.1.3 Impact of asymmetric trust on project management performance. The supported H2
indicates that asymmetric trust has a significant and negative impact on project management
performance (β50.345; p< 0.001), which is consistent with the theoretical viewpoint of
Tomlinson and Mryer (2009),Call and Korsgaard (2013) and Korsgaard (2014). The possible
reason why asymmetric trust inhibits project management performance improving may be
that under the context of asymmetric trust, owners and contractors no longer share the
mental model (Tomlinson and Mryer, 2009), which then can lead to the increase in behavior
uncertainty from both partners. So, as their behaviors become unpredictable in advance, their
cooperation difficulty also increase, which creates obstacles to cooperation and ultimately
restrains project management performance improving. In addition, this research also found
that tacit knowledge sharing plays a partial mediation role between asymmetric trust and
project management performance. The calculation results of Bootstrapping method provide
support for H4b. That is to say, asymmetric trust in owner-contractor relationships can
reduce tacit knowledge sharing in cooperative relationships, so as to restrain project
ECAM
management performance improving. This provides support for Korsgaard (2014), who
believed that asymmetric trust will inhibit the effect of average trust on performance
improving, and this is very unfavorable to the party with higher trust level (i.e. the weaker
party in asymmetric trust relationships).
5.2 Implications
5.2.1 Theoretical implications. This paper contributes to the trust and relational governance
literature by expanding the research perspective of mutual trust to asymmetric trust.
Specifically, although many scholars have paid attention to the trust differences in dyadic
relationships (Tomlinson and Mryer, 2009;Korsgaard, 2014), and some researchers even
constructed the conceptual framework for asymmetric trust. However, there are no clear studies
showing that asymmetric trust are universally related to construction project management
performance. In other words, there is a significant gap between thinking from academic
research of asymmetric trust and project management practice that needs to be bridged.
Drawing lessons from other fields focusing on asymmetric trust, this research designs a
measurement scale for asymmetric trust and then reveals the impact mechanism of asymmetric
trust on project management performance. So, this research enriches the trust and relational
governance literature in construction project management field, and will certainly promote
research paradigm change of trust. This research provides a reference and basis for follow-up
asymmetric trust research as well.
Besides, this research is also beneficial to knowledge sharing literature in construction
management field. With construction technology development and project requirements
becoming more and more complicated, construction industry’s knowledge-intensive degree is
getting higher and higher and inter-organizational knowledge sharing is important for
improving project management performance. However, previous researches have recognized
the significant influence of knowledge sharing within organizations on enterprise
performance in the construction industry, ignoring the interaction of knowledge sharing
among enterprises in the construction industry. So, cross-organizational knowledge sharing
is empirically tested in this research. It is verified that knowledge sharing between owners
and contractors can effectively improve project management performance in the Chinese
context. Existing researches support the role of knowledge sharing in promoting enterprise
performance (e.g. Kivrak et al., 2014;Juozas and Renatas, 2012). By evaluating its impact on
project management performance, this research contributes to the knowledge sharing
literature from a cross-organizational perspective. That’s to say, this research expands the
research scope of knowledge sharing and provides theoretical support for stakeholders to
utilize knowledge sharing to improve project management performance.
5.2.2 Practical implications. Both owners and contractors need to avoid establishing
asymmetric trust relationships. In view of the fact that asymmetric trust can directly and
indirectly avoid improving project management performance, potential project participants
should form alliances with potential partners with similar trust level. For owners, they can
evaluate their symmetry degree of trust with contractors basing on contractors’size,
qualification, performance and reputation through the prequalification. Moreover, as far as
the strong partners (i.e. owners) are concerned, they should choose more trust strategies and
do not hesitate to take cooperative actions during project implementation, such as involving
contractors in decision-making through joint meetings, and strengthening cross-
organizational communication and collaboration. By doing this, the negative impact of
asymmetric trust on project management performance can be reduced in some certain.
Subsequently, it is necessary to use various means to promote project knowledge sharing
among organizations. Specially, in order to speed up the process of sharing project knowledge
among organizations, a project knowledge sharing platform based on BIM technology can be
Impact
of asymmetric
trust
built to provide an efficient project knowledge sharing channel for project partners. Finally,
given that tacit knowledge can provide greater project management improvement, it is
important that tacit knowledge should be largely shared. Thus, beneficial measures and
incentives should be adopted, such as adopting apprenticeship system, holding key technical
exchange meeting and rewarding those who share their work and technical experience et al.
6. Conclusion
Asymmetric trust is a theory gap and a promising missing link in trust research, while
current researches in project management ignore its existence and importance. Besides,
knowledge sharing is of great importance for construction project performance continuous
improving. However, previous researches on knowledge sharing have been insufficient in the
construction management field. To address such gaps, this research integrates trust theory
and knowledge-based view, and then constructs an antecedent variable model about
asymmetric trust and knowledge sharing on project management performance.
Subsequently, data analyzing following empirical test provides supports for 5 of 7
hypotheses in the present research. Specifically, the test results of the research model
statistically support the following viewpoints: The results of this study indicate that there is a
significant and negative association between asymmetric trust and project management
performance. Moreover, two types of knowledge sharing (explicit knowledge sharing and
tacit knowledge sharing) have different degrees of impact on improving project management
performance. In addition, tacit knowledge sharing is a mediator between asymmetric trust
and project management performance.
In spite of the achievements of this study, there are still some limitations: the data used in
this study is from Chinese scenarios, so the research conclusions and application effects
based on this are bound to have certain regional limitations. This study developed scales of
variables such as asymmetric trust and knowledge sharing, and carried out empirical
analysis based on China’s construction industry. However, different countries pay different
attention to each variable, thus expanding the data of countries with different cultures and
obtaining comparative research conclusions is necessary. Besides, there are many factors
that affect project management performance improving, and the relationships among them
are so complex. The theoretical model proposed in this study may not be fully considered.
Therefore, follow-up researchers can consider bringing more suitable variables into their
researches, so that the theoretical researches can be more in line with the actual project
management practice, and the specific mechanism for improving project management
performance can be explained more deeply.
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(The Appendix follows overleaf)
Impact
of asymmetric
trust
Appendix
Corresponding author
Xiaolin Li can be contacted at: 13132516831@163.com
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Construct Code Items Source
AT OWN1 We are certain that our partner has the ability to perform their
tasks
Lu et al. (2016)
Pinto et al. (2009)
OWN2 We believe that our partner could meet the requirements of the
project in technology and management
OWN3 We believe the project engineers and other technical people are
competent at what they are doing
OWN4 We believe that our partner is able to fulfill contractual agreements
CON1 We are certain that our partner has the ability to pay for our work
CON2 We believe that our partner could provide necessary supports for
us to meet the requirements of the project in technology and
management
CON3 We believe our partner’s management and technical personnel are
competent at what they are doing
CON4 We believe that our partner is able to fulfill contractualagreements
KS EKS1 We frequently share existing reports and official documents with
our partner
Wang and
Wang (2012)
Bock et al. (2010)
Zhang and Ng
(2013)
ESK2 We frequently share existing work manuals, instructions, methods
and models with our partner
TKS1 We frequently share work experience or know-how in construction
methods with our partner
TKS2 We frequently share management experience or know-how on
schedule control with our partner
TKS3 We frequently share project knowledge such as site conditions and
project status with our partner
TKS4 We frequently share the lessons of past failed projects with our
partner when necessary
PMP PMP1 The project has achieved the expected time control objective Pocock et al.
(1996)PMP2 The project has achieved the expected cost control objective
PMP3 The project has achieved the expected quality control objective
PMP4 The project satisfied us and our clients
Note(s): OWN1∼OWN3 are used to evaluate the trust level of owners on contractors; CON1∼CON3 are used to
evaluate the trust level of contractors on owners. AT is the absolute value of the difference between owner’s
trust on contractor (OWN) and contractor’s trust on owner (CON), similarly with Kumar et al. (1995)
Source(s): Author’s own creation
Table A1.
Measurement scales
ECAM
