Home Uncategorized Help with Definition Essay about " What is Trust"

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Help with Definition Essay about ” What is Trust”

*** You must provide and elaborate on a 3-content pages minimum (not including Cited Works page) and you will follow the Gordon rules policies and procedures reviewed in class and available in Blackboard. Even though, the Gordon rules and procedures does not necessary include the terminology on the different writing essays, they will guide you as to inform you about the college-level research writing expectations, information on the writing structure and standard as well as the correct MLA format and reliable sources to be utilized in your essay.

Chapter Six Outline

Definition: Establishing Meaning

I. What is Definition?

Definitions limit or explain the meaning of a term or concept. Although the term definition leads most people to think of a dictionary, definitions are not always precise or universally accepted (Connelly 181).

II. Different types of definitions exist:

Standard definitions
Regulatory definitions
Evolving definitions
Qualifying definitions
Cultural definitions
Personal definitions
Invented definitions

III. Methods of Definition – Definitions can be established using a number of techniques:

Defining through synonyms – use a word with similar meaning to define a term; this is the simplest method of providing meaning for a word.
Defining by description – uses details about a word or subject to define a term; this method gives readers a sense of what a term might look, feel, taste, smell, or sound like.
Defining by example – uses specific illustrations to establish meaning. Examples can establish meaning through identification. Complex or abstract concepts are easier to comprehend if defined by example.
Defining by comparison – uses analogies readers can understand to provide meaning to something less familiar.
Extended definition – this method is necessary when defining highly complex words (love; racism; justice) or concepts. A full description of abstract, disputed, or complex terms requires several paragraphs (even whole essays).

Your Definition Essay

For your definition essay assignment, you will need to apply most, if not all, of the methods listed above to develop and support the term you choose to explain and illustrate (since you are writing an essay to define a selected term, you are already defining through extended definition. Your goal as the author of a definition piece is to establish the meaning of a term, using the methods of definition, for the purpose of sharing a common understanding of that term with your reader.

Article

The Origins of Trust Asymmetr

in International Relationships:
An Institutional View

Mengyang Wang, Qiyuan Zhang, and Kevin Zheng Zhou

Abstrac

Trust is key to relationship marketing. Although trust is bilateral, studies on the dispersion of trust among exchange partie

remain limited, leaving the antecedents and outcomes of trust asymmetry largely underexplored. To fill the gaps, this study
empirically examines the effects of different types of trust asymmetry on exchange performance and then investigates the
institutional origins of trust asymmetry in international interfirm exchanges. Drawing on a survey of 134 international buyer–
supplier relationships in China, the study finds that both calculative trust asymmetry and relational trust asymmetry have negative
influences on exchange performance. The study also finds that formal institutional distance constrains calculative trust asymmetry
and informal institutional distance increases relational trust asymmetry. Moreover, prior interactions and expectations of con-
tinuity significantly moderate the effects of formal and informal institutional distance. This study advances trust studies in cross-
border settings

Keywords
trust asymmetry, formal institutional distance, informal institutional distance, international buyer–supplier relationships

Trust is central to interorganizational relationship marketing

(Aulakh, Kotabe, and Sahay 1996; Katsikeas, Skarmeas, and

Bello 2009; Leonidou et al. 2014). When trust exists,

exchange parties are willing to cooperate, share information,

and make adaptations (Griffith, Myers, and Harvey 2006;

Gulati and Nickerson 2008). In an international marketing

relationship characterized by high unpredictability and com-

plexity, cross-border players usually face more challenges in

effectively dealing with their exchange partners and achieving

satisfactory outcomes, making the role of trust even more

pivotal (Katsikeas, Skarmeas, and Bello 2009; Leonidou

et al. 2014). For instance, Robson, Katsikeas, and Bello

(2008) show that in cross-border relationships, trust is critical

for increasing transaction value and reducing transaction

costs, which in turn result in better performance. Katsikeas,

Skarmeas, and Bello (2009) also reveal that importer trust

enhances performance in international exchange relationships

by motivating participants to contribute resources and share

sensitive information. Although many studies have validated

the importance of trust in an international marketing context,

several aspects of this issue remain unexplored.

First, the extant studies on interorganizational trust mainly

investigate the topic from a single perspective (Aulakh,

Kotabe, and Sahay 1996; Poppo and Zenger 2002; Zaheer,

McEvily, and Perrone 1998), and few have studied trust dis-

persion (McEvily, Zaheer, and Kamel 2017). Trust asymmetry,

which refers to the difference in trust between exchange part-

ners, adds significant uncertainty to cross-border exchanges

and generates uncertain performance implications (Graebner

2009; Zaheer and Zaheer 2006). For example, despite a 20-

year partnership, Ford Motor and China’s Changan Automobile

Co. Ltd still have high trust asymmetry, which not only hinde

team cooperation but also generates lackluster global perfor-

mance. And not until recently did Ford Motor commit itself to

the partnership with Changan by localizing its management

team and offering more tested talents to product R&D, manu-

facturing, and marketing areas (Li 2018). In studying the fail-

ures of interorganizational relationships, Oliveira and

Lumineau (2019) suggest that trust may backfire, and the

Mengyang Wang is Associate Professor, Huazhong University of Science and

Technology, China (email: wangmengyang@hust.edu.cn). Qiyuan Zhang is

Associate Professor, Zhejiang University, China (email: bessieqy@zju.edu.

cn). Kevin Zheng Zhou is Chang-Jiang Scholar Chair Professor and Professor

of Management and Strategy, The University of Hong Kong, Hong Kong (email:

kevinzhou@business.hku.hk).

Journal of International Marketing
2020, Vol. 28(2) 81-101

ª American Marketing Association 2020
Article reuse guidelines:

sagepub.com/journals-permissions
DOI: 10.1177/1069031X1989

journals.sagepub.com/home/jig

mailto:wangmengyang@hust.edu.cn

mailto:bessieqy@zju.edu.cn

mailto:kevinzhou@business.hku.hk

https://sagepub.com/journals-permissions

https://doi.org/10.1177/1069031X19898492

http://journals.sagepub.com/home/jig

extant literature mainly focuses on the inverted curvilinear

effect of trust without a multiparty consideration of the effects

of trust. By adopting a dyadic view to examine trust asymme-

try, our study attempts to enrich the understanding of the dark

side of trust. Furthermore, distinct types of trust exist. Poppo,

Zhou, and Li (2016) argue that calculative trust and relational

trust coexist and characterize most business relationships. By

examining alternative forms of trust asymmetry, our study dee-

pens our understanding of the performance implications of

trust.

Second, despite abundant attention on the origins of trust,

few studies explicitly consider how institutional factors influ-

ence trust asymmetry (for a review, see Table 1). Oliveira and

Lumineau (2019) posit that a topic less studied in interorgani-

zational relationships is how country-related antecedents influ-

ence interaction outcomes. For international exchange

relationships, the distinct institutional backgrounds of interfirm

partners may shape their attitudes and behaviors toward eco-

nomic transactions and thus drive the level of

trust asymmetry.

However, related studies mainly focus on the informal aspects

of institutions (i.e., culture) and argue that cultural distance

leads to a lower level of trust (Homburg et al. 2009; Leonidou

et al. 2014). Whereas informal institutions influence relational

trust by emphasizing business participants’ internal interpreta-

tions and knowledge obtained from repeated social interactions

(Kostova and Roth 2002; Yang, Su, and Fam 2012), formal

institutions mainly influence calculative trust by providing a

basis for exchange parties to calculate the benefits and costs of

their actions (Cai, Jun, and Yang 2010). Given this dissimilar-

ity, a collective consideration of both formal and informal

institutional distance to understand different types of trust

asymmetry is critical but lacking in the current literature.

Third, past studies on the origins of trust imply that histor-

ical interactions and future expectations matter (Poppo and

Zenger 2002; Poppo, Zhou, and Ryu 2008). According to the

relational view, prior interactions breed familiarity and mutual

understanding, which in turn promote trust (Gulati 1995).

According to game theory, expectations of continuity instill a

forward-looking calculus of costs and benefits that drives trust

perception (Parkhe 1993; Poppo, Zhou, and Ryu 2008).

Although institutional distance demonstrates a macro-level

institutional force exerted by the external environment, the

exchange parties themselves intentionally determine the ways

in which they assess their relationships and shape their attitudes

and actions. When parties hold dissimilar perceptions regard-

ing the transaction, they may react differently in dealing with

institutional challenges when forming their trust perception

However, few studies have developed an interdependence per-

spective in studying trust asymmetry. Thus, researchers have

not resolved how the factors involved with the institutional

view, the relational view, and game theory jointly account for

the emergence of trust asymmetry.

Accordingly, the following three important questions

remain unanswered: (1) How do calculative/relational trust

asymmetry (TA) affect exchange performance? (2) What are

the effects of institutional distances on the formation of

calculative/relational trust asymmetry? and (3) How do past

perceptions and future expectations held by the exchange par-

ties moderate the relationships between institutional distance

and calculative/relational trust asymmetry? To answer these

research questions, we first explore the different performance

logics associated with calculative and relational trust asymme-

try. Second, we show that different forms of institutional dis-

tance (i.e., formal and informal institutional distance) have

divergent effects on the formation of calculative and relational

trust asymmetry. Third, we examine the moderating roles of

prior interactions and expectations of continuity to examine

when institutional distance matters more under various

conditions.

By conducting an empirical study with 134 international

buyer–supplier dyads, this article contributes to the extant

international marketing studies in several ways. First, by

empirically examining the roles of trust asymmetry in reducing

exchange performance in international buyer–supplier relation-

ships, our study enriches the understanding of performance

implications and the dark side of trust (Korsgaard, Brower, and

Lester 2015; Scheer 2012). Second, by integrating an institu-

tional view in understanding how formal and informal institu-

tional distance influence calculative and relational trust

asymmetry in international marketing relationships, we

enhance the understanding of the institutional origins of trust

asymmetry in an international context with empirical evidence

(Zaheer and Kamal 2011; Zaheer and Zaheer 2006). Third, by

incorporating prior interactions and expectations of continuity

as moderators, we apply an interdependence perspective to

understanding the influences of institutional distance on trust

asymmetry in international markets. Figure 1 displays our con-

ceptual framework.

Theory

Calculative Versus Relational Trust

Trust is the confidence that a partner will act in a reliable,

predictable, and fair manner (Zaheer, McEvily, and Perrone

1998). With the belief that their partners will not pursue self-

interest, business participants show a “willingness to be

vulnerable” (Mayer, Davis, and Schoorman 1995, p. 712).

Trust is not unitary but multidimensional. As a multifaceted

concept, trust has distinct implications with different bases

(Dyer and Chu 2000; Rousseau et al. 1998). The extant

research mainly defines interorganizational trust from the fol-

lowing two perspectives: economic and social (Gulati 1995;

Rousseau et al. 1998; Williamson 1993). The economic per-

spective (e.g., transaction cost economics, game theory) empha-

sizes calculative trust, in which the trustor uses rational

reasoning to recognize that the calculated benefits of cooperative

behaviors are greater than those of opportunism (Rousseau et al.

1998; Williamson 1993). As a rational choice based on calcu-

lated gains and losses in economic exchanges, calculative trust

requires economic incentives, such as credible commitments, to

make deliberate calculations (Williamson 1993). It relies on a

82 Journal of International Marketing 28(2)

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co
m

p
u
te

r
e
x
e
cu

ti
ve

s
R

E
T
(R
e
la
ti
o
n
al

)

E
x
ch

an
ge

h
az

ar
d
s,

p
re

vi
o
u
s

re
la

ti
o

n
s

R
e
la
ti
o
n
al

go
ve

rn
an

ce
an

d
co
n
tr

ac
ts

fu
n
ct

io
n

as
co

p
le

m
e
n
ts

in
e
x
p
la

in
in

g
e
x
ch

an
ge
p
e
rf
o
rm
an
ce

.
M

u
tu
al
tr
u
st
D
ye
r
an
d
C
h
u

(2
0
0
3
)

3
4

su
p
p
lie
r–
au
to
m
ak
e
r
re
la
ti
o
n
sh
ip
s
In
st
it
u
ti
o
n
al
th
e
o
ry
(I
n
st
it
u
ti
o
n
al
)
N
.A
.
T
ru

st
lo

w
e
rs

tr
an

sa
ct

io
n

co
st

s,
p
ro

m
o
te
s
in
fo
rm
at
io
n
sh

ar
in

g,
an

d
is
an
im
p
o
rt
an
t

so
u
rc

e
o
f

p
e
rf

o
rm
an
ce
.
U
n
ila
te
ra
l
tr
u
st

K
ri

sh
n
an

,
M

ar
ti

n
,
an

d
N

o
o
rd

e
rh

av
e
n

(2
0
0
6
)

1
2
6

In
d
ia

n
fi
rm

s
w
it
h
in
te

n
at

io
n
al

al
lia

n
ce
s
R
E
T
(R
e
la
ti
o
n
al
)
N
.A
.
T
h
e

p
o
si

ti
ve
re
la
ti
o
n
sh

ip
b
e
tw

e
e
n

tr
u
st
an
d
p
e
rf
o
rm
an
ce

is
st

ro
n
ge

n
d
e
r

h
ig

b
e
h
av

io
ra

u
n
ce

rt
ai

n
ty

an
d

w
e
ak

e
r
u
n
d
e
r
h
ig

h
e
n
vi

ro
n
m
e
n
ta
l
u
n
ce
rt
ai
n
ty
.
M
u
tu
al
tr
u
st
Z
ah

e
e
r

an
d
Z
ah
e
e
r
(2
0
0
6
)

C
o
n
ce

p
tu

al
st

u
d
y

In
st
it
u
ti
o
n
al
th
e
o
ry
(I
n
st
it
u
ti
o
n
al

)
D

if
fe

re
n
ce

s
in
in
st
it
u
ti
o
n
al
e
n
vi
ro
n
m
e
n
ts
T
ru

st
as

ym
m

e
tr

y
ar

is
e
s

fr
o
m

d
if
fe

re
n
ce
s
in
in
st
it
u
ti
o
n
al
e
n
vi
ro
n
m
e
n
ts
an
d
h
as

gr
e
at

e
r

n
e
ga

ti
ve

e
ff
e
ct

s
o
n

o
lla

b
o
ra

ti
o
n
p
e
rf
o
rm
an
ce
w
it
h
h
ig

h
in

te
rd
e
p
e
n
d
e
n
ce
.
T
ru
st
as
ym
m
e
tr
y

B
st

ie
le

r
an
d
H

e
m

m
e
rt

0
0
8
)

1
0
0

p
ro

d
u
ct

d
e
ve
lo
p
m
e
n
t
p
ar

tn
e
rs

h
ip
s
In
st
it
u
ti
o
n
al
th
e
o
ry
(I
n
st
it
u
ti
o
n
al
)
C
o
m
m
u
n
ic
at
io

n
,
fa

n
e
ss

,
co
n
fl
ic

ts
,
n
at

io
n
al

cu
lt
u
re

R
e
la
ti
o
n
al
b
e
h
av

io
rs

im
p
ac

t
tr

u
st
fo
rm
at
io
n
,a
n
d
n
at
io
n
al
cu
lt
u
re
h
as

a
d
ir

e
ct
an
d

a
m

o
d
e
ra

ti
n
g
e
ff
e
ct
o
n
tr
u
st
d
e
ve
lo
p
m

e
n
t.

U
n
ila
te
ra
l
tr
u
st

G
u
la

ti
an

d
N

ic
k
e
rs

o
n

(2
0
0
8
)

2
2
2

co
m

p
o
n
e
n
t–

so
u
rc
in
g

ar
ra

n
ge
m
e
n
ts

o
f
tw

o
as

se
m

b
le

rs
T
C

E
(E

co
n
o
m

ic
)

N
.A

.
T
ru
st
co
m
p
le
m
e
n
ts

b
u
y

an
d

al
ly

go
ve
rn
an

ce
ch

o
ic

e
s

b
y

lo
w

e
ri
n
g

co
n
fl
ic

t
an

e
n
h
an

ci
n
g

p
e
rf
o
rm
an
ce
.
M
u
tu
al
tr
u
st

(c
o
n
ti
n
u
ed

)

T
a
b
le
1
.

(c
o
n
ti
n
u
e
d
)

S
tu
d
y
C
o
n
te
x
t

T
h
e
o
re

ti
ca

l
P
e
rs

p
e
ct
iv
e
A
n
te
c
e
d
e
n
ts
M
a
jo
r
F
in
d

in
g
s

T
r
u
st
C
o
n
c
e
p
t

P
o
p
p
o

,
Z

h
o
u
,
an

d
R

yu
(2

0
0
8
)

1
3
7

m
an
u
fa
ct
u
re

rs
T

C
E

(E
co
n
o
m
ic
)

A
ss

e
t

sp
e
ci

fi
ci

ty
,
u
n
ce

rt
ai
n
ty

p
ri

o
r
e
x
ch
an
ge

h
is

to
ry

,
e
x
p
e
ct

at
io

o
f
co

n
ti
n
u
it
y

T
h
e
re
la
ti
o
n
sh
ip
b
e
tw
e
e
n

as
se

t
sp

e
ci
fi
ci

ty
/u

n
ce
rt
ai
n
ty

/p
ri

o
r
h
is
to
ry
an
d
tr
u
st

is
m

e
d
ia
te
d
b
y
e
x
p
e
ct
at
io
n
s
o
f
co

n
ti
n
u
it
y.

M
u
tu
al
tr
u
st

R
o
b
so

n
,
K

at
si

k
e
as

,
an

d
B
e
llo

(2
0
0
8
)

1
7
7

in
te

rn
at

io
n
al

st
ra

te
gi

c
al

lia
n
ce

s
R
E
T
(R
e
la
ti
o
n
al
)
D

is
tr

u
ti
ve

fa
ir

n
e
ss

,
p
ar

tn
e
r

si
m
ila
ri

y
B
o
th

d
is
tr
ib
u
ti
ve
fa
ir
n
e
ss
an
d
p
ar
tn
e
r
si
m
ila
ri

ty
ar

e
p
o
si

ti
ve

ly
as

so
ci

at
e

w
it
h
in
te

rp
ar

tn
e
r
tr
u
st
,
w

h
ic

h
is
p
o
si
ti
ve
ly
as
so
ci
at
e
d
w
it
h
al
lia
n
ce
p
e
rf
o
rm
an
ce
.
M
u
tu
al
tr
u
st

G
ra

e
b
n
e
r

0
0
9
)

C
as

e
st

u
d
y

o
f
1
2

e
n
tr

e
p
re

n
e
u
ri

al
fi
rm

s
an

d
e
ig

h
t

ac
q
u
ir

e
rs
T
C
E
(E
co
n
o
m
ic
)

In
fo

rm
at
io
n
as
ym
m
e
tr
y
B
o
th
b
u
ye

rs
’
an

d
se

lle
rs

’
as

se
ss

m
e
n
ts

o
f
th

e
ir

co
u
n
te

rp
ar

ts
’

tr
u
st
w
e
re

o
ft

e
n

m
is

ta
k
e
n
,
an

d
th

e
se

im
b
al

an
ce

s
fo

st
e
r

se
lle

r
vu

ln
e
ra

b
ili

ty
an

d
b
u
ye

r
d
e
ce

it
.

T
ru
st
as
ym
m
e
tr
y

H
o
m

b
u
rg

e
t

al
.
(2

0
0
9
)

1
1

b
u
ye
r–
su
p
p
lie
r
re
la
ti
o
n
sh
ip
s
In
st
it
u
ti
o
n
al
th
e
o
ry
(I
n
st
it
u
ti
o
n
al

)
T

n
sn

at
io
n
al
it
y

o
f
b
u
ye

r–
su
p
p
lie
r
re
la
ti
o
n
sh

ip
,
n
at

io
n
al
cu
lt
u
re
o
f
b
u
ye

r
fi
rm

T
ra
n
sn
at
io
n
al
it
y
an
d
cu
lt
u
re

b
o
th

af
fe

ct
th

e
b
u
ye

r’
s

ch
o
ic

e
o
f
go
ve
rn
an

ce
m

o
d
e
s.

U
n
ila
te
ra
l
tr
u
st

K
at

si
k
e
as

,
S
k
ar

m
e
as

,
an
d
B
e
llo

(2
0
0
9
)

1
4

im
p
o
rt

in
g
d
is
tr
ib
u
to

s
In

st
it
u
ti
o
n
al
th
e
o
ry
(I
n
st
it
u
ti
o
n
al

)
In

te
rn

al
u
n
ce

rt
ai
n
ty

,
e
x
te

rn
al

u
n
ce
rt
ai
n
ty
,
in

te
rf

ir
m

p
sy

ch
ic

d
is

ta
n
ce

,
tr

an
sa

ct
io

n
sp

e
ci
fi
c
as
se

ts
,
o

p
p
o
rt

u
n
is

m
In

te
rf
ir
m
p
sy
ch
ic
d
is
ta
n
ce
,
in
te
rn
al
u
n
ce
rt
ai
n
ty
,
an

d
e
x
p
o
rt

e
r
tr
an
sa
ct

io
n
-s

p
e
ci
fi
c
as
se

ts
an

d
o
p
p
o
rt

u
n
is

m
ar

e
re
la
te
d
to
im
p
o
rt
e
r
tr
u
st
.
U
n
ila
te
ra
l
tr
u
st

C
ai

,
Ju

n
,
an

d
Y

an
g

0
1
0
)

3
9
8

C
h
in

e
se
m
an
u
fa
ct
u
re
rs
In
st
it
u
ti
o
n
al
th
e
o
ry
(I
n
st
it
u
ti
o
n
al

)
L
e
ga

l
p
ro

te
ct

io
n
,
go

ve
rn

m
e
n
t

su
p
p
o
rt

,
im

p
o
rt
an
ce

o
f
gu

an
x
i

G
o
ve

rn
m

e
n
t
su
p
p
o
rt
an
d
im
p
o
rt
an
ce
o
f
gu

an
x
i
si

gn
if
ic
an
tl
y
af
fe

ct
tr

u
st
,
w
h
ic

h
su

b
se

q
u
e
n
tl
y

in
fl
u
e
n
ce
s
in
fo
rm
at
io
n
sh
ar
in

g
an

d
co

lla
b
o
ra

ti
ve
p
la

n
n
in

g.
U
n
ila
te
ra
l
tr
u
st

N
ya

ga
,
W

h
ip
p
le
,
an

d
L
yn

ch
(2

0
1
0
)

3
7
0

b
u
ye

rs
an

d
2
5
5

su
p
p
lie

rs
R

E
T
(R
e
la
ti
o
n
al
)
C
o
lla
b
o
ra
ti
ve

ti
vi

ti
e
s

(i
n
fo
rm
at
io
n
sh
ar
in
g,

jo
in

t
re

la
ti
o
n
sh

ip
e
ff
o
rt

,
an

d
d
e

d
ic

at
e
d
in
ve
st
m
e
n
ts
)
C
o
lla
b
o
ra
ti
ve
ac
ti
vi
ti
e
s

le
ad

to
tr

u
st
an
d
co
m

m
it
m

e
n
t.
T
ru
st
an
d
co
m
m
it
m

e
n
t,

in
tu

rn
,
le

ad
to

im
p
ro

ve
d

sa
ti
sf
ac
ti
o
n
an
d
p
e
rf
o
rm
an
ce
.
M
u
tu
al
tr
u
st

Ji
an

g
e
t

al
.
(2

0
1
1
)

1
0
8

C
h
in
e
se

se
n
io

r
e
x
e
cu
ti
ve
s
In
st
it
u
ti
o
n
al
th
e
o
ry
(I
n
st
it
u
ti
o
n
al
)
C

lt
u
ra

l
si

m
ila

ri
ty

O
ve

rs
e
as

p
ar
tn
e
rs

o
f
cu

lt
u
ra

l
e
th

n
ic

it
ie

s
d
if
fe

re
n
t

fr
o
m

h
o
st

–
co

u
n
tr

y
e
x
e
cu

ti
ve

s
ar

e
d
is

ad
va

n
ta

ge
d

in
th
e
tr
u
st

d
o
m

ai
n

w
h
e
n

co
m
p
ar
e
d
w
it
h
p
ar
tn
e
rs

w
h
o

sh
ar

e
si

m
ila

r
cu

lt
u
ra
l
e
th
n
ic
it
ie
s.
U
n
ila
te
ra
l
tr
u
st
Z
ah
e
e
r
an
d

K
am

al
(2

0
1
1
)
C
o
n
ce
p
tu
al
st
u
d
y
In
st
it
u
ti
o
n
al
th
e
o
ry
(I
n
st
it
u
ti
o
n
al

)
H

o
m
e
co
u
n
tr

y,
h
o
st

co
u
n
tr

y
B
o
th
th
e

h
o
m

e
an

d
h
o
st

co
u
n
tr

y
o
f
th

e
e
x
ch

an
ge
p
ar
tn
e
rs
in
fl
u
e
n
ce
th
e
n
at
u
re
an
d

o
u
tc

o
m
e
s

o
f
d
ya

d
ic
tr
u
st
.
M
u
tu
al
tr
u
st

A
lt
in

ay
e
t

al
.
(2

0
1
4
)

2
0
0

m
u
lt
is

e
ct
o
r

fr
an

ch
is

e
e
s

In
st
it
u
ti
o
n
al
th
e
o
ry
(I
n
st
it
u
ti
o
n
al

)
R

o
le
p
e
rf
o
rm
an
ce

,
cu

lt
u
ra

l
se

n
si
ti
vi

ty
T

h
e
re

is
a

p
o
si
ti
ve
re
la
ti
o
n
sh
ip
b
e
tw
e
e
n
fr
an
ch
is

e
r’

s
ro

le
p
e
rf

o
rm
an
ce

/c
u
lt
u
ra

l
se
n
si
ti
vi
ty
an

d
fr

an
ch

is
e
e
’s

tr
u
st
.
T
ru
st
p
o
si
ti
ve

ly
af

fe
ct

s
th

e
fr

an
ch
is
e
e
’s
sa
ti
sf

ac
ti
o
n
.

U
n
ila
te
ra
l
tr
u
st

L
e
o
n
id

o
u
e
t
al
.
(2
0
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84

forward-looking decision rule, in which business participants

must envision the future situation and make decisions with an

assumption of self-interest calculations (Rousseau et al. 1998).

During the conscious process, calculative trust forms rational

expectations and motivates the exchange parties’ behaviors to

maximize their economic interests within the exchange (Poppo,

Zhou, and Li 2016; Rousseau et al. 1998).

The social perspective (e.g., social exchange theory), how-

ever, challenges this rational basis of trust and instead posits

that trust arises from social interactions (Blau 1964; Morgan

and Hunt 1994; Uzzi 1997). Relational trust refers to the trust-

ing party’s positive beliefs about the shared understanding and

common identity regarding the specific relationship (Rousseau

et al. 1998). In contrast to rational reasoning, relational trust is

more comparable to relational beliefs, which generally arise

from intrinsic values, social interactions, and understanding

of goodwill (Schilke and Cook 2015; Uzzi 1997). Distinct from

the forward-looking logic of calculative trust, relational trust

relies on repeated interactions to guide the parties’ decisions

and transactional actions. With an emphasis on the noneco-

nomic aspects of exchange relationships, business participants

with high relational trust would follow the norm of mutuality to

behave and consider the relationship as a whole (Rousseau

et al. 1998; Schilke and Cook 2015).

As different facets of trust, calculative and relational trust

coexist and characterize most business relationships (Poppo,

Zhou, and Li 2016). Trust studies can lead to misattributions if

they fail to account for the various types of trust (Poppo, Zhou,

and Li 2016; Schilke and Cook 2015). Therefore, we distinguish

between calculative and relational trust and explore their distinct

bases and decision logics in studying the origins, boundary con-

ditions, and performance outcomes of trust asymmetry.

Trust Asymmetry Across Borders

Although trust is multidimensional, it is also important to note

that trust is bidirectional, which involves both a trustor (the

trusting party) and a trustee (the trusted party) (Korsgaard,

Brower, and Lester 2015). When examining trust asymmetry,

we take both parties’ perceptions into consideration to capture

the bilateral nature of trust. To achieve relational benefits, it

usually requires the mutual consent of dyadic parties to make

adaptations and provide information, and a shared value of trust

between exchange partners is, therefore, essential (Heide and

John 1992). However, in practice, the perceptions of the parties

often vary across the dyad, especially in an international con-

text, making trust asymmetry in such contexts more prevalent

(Zaheer and Zaheer 2006).

Zucker (1986) highlights the importance of institutions in

determining trust. As “the rules of the game,” institutions

define what is institutionally appropriate for social actors and

shape the firms’ perceptions through formal and informal

forces (DiMaggio and Powell 1983; Scott 1995). In interna-

tional exchanges, cross-border partners’ expectations and per-

ceptions are likely to vary across the dyad given their different

institutional backgrounds (Zucker 1986). Institutional distance,

which is defined as the differences in the institutional environ-

ments of the exchange parties, can be characterized into two

types: formal institutional distance and informal institutional

distance (Xu and Shenkar 2002; Yang, Su, and Fam 2012). For

Expectation of continuity

Prior interaction

Formal institutional distance

Informal institutional distance

Exchange performance

Calculative trust asymmetry

Relational trust asymmetry

H2a: (−**)

H2b: (+*)

H1a: (−**)

H1b: (−*)

H3a: (n.s.) H3b: (−*)

H4a: (−**) H4b: (−*)
Control Variables

Shared calculative trust
Shared relational trust

Shared asset specificity
Asset specificity asymmetry
Supply market uncertainty

Guanxi importance
Buyer age

Supplier age
Buyer size

Supplier size
Mechanics

Heavy
Electronics

Figure 1. Conceptual model.
Notes: n.s. ¼ not significant, *p < .05, **p < .01.

Wang et al. 85

formal institutional distance, we examine the differences in the

legal and regulatory institutions of the home and host countries

(Kaufmann, Kraay, and Mastruzzi 2009). For informal institu-

tional distance, we focus on the national culture differences in a

cross-border context (Salomon and Wu 2012). By doing so, we

attempt to offer a clear picture of how institutional distance

influences different types of trust asymmetry in international

relationships.

According to Scott’s schema (Scott 1995), we suggest that

formal institutions mainly apply to calculative trust, whereas

informal institutions mainly explain relational trust given their

different emphases and implications. Formal institutions

mainly refer to the regulatory and political bodies of a nation,

such as regulatory policies, constitutions, and property rights

(Scott 1995). Using legal deterrence, formal institutions sanc-

tion deviant behaviors according to written regulations and

laws, thereby shaping business participants’ recognitions about

rewards or punishments for specific behaviors (Scott 1995). In

addition, since formal institutions are generally characterized

as objective and formalized frameworks, it is easy for business

participants to obtain explicit information (Gaur and Lu 2007;

Scott 1995), which provides a basis for exchange parties to

make economic calculations of their actions, thereby applying

to the formation of calculative trust (Cai, Jun, and Yang 2010).

Informal institutions include social beliefs, values, beha-

vioral norms, and conventions (Scott 1995). Informal institu-

tions can be manifested in terms of individualism versus

collectivism, masculinity versus femininity, power distance,

uncertainty avoidance, and long-term orientation (Hofstede

2001). When operating in China, guanxi is a key informal

institution that shapes exchange parties’ interpretation and

behaviors. Literally, guanxi means social connections and rela-

tionships (Xin and Pearce 1996). Because Chinese society is

heavily structured according to social relations, guanxi affects

not only personal interactions but also business practices (Peng

and Luo 2000). Guanxi influences interfirm exchanges through

the operating rules of reciprocal obligation and face saving

(i.e., the idea of maintaining one’s prestige; Park and Luo

2001). Considering that guanxi mainly originated from a col-

lective mindset, which correlates with the collectivism–indivi-

dualism dimension of the tradition distinction of informal

institutions, we focus on a more generalized form of informal

institutions (i.e., national culture) to develop our hypotheses

(Hofstede 2001; Salomon and Wu 2012). Informal institutions

emphasize the knowledge and perceptions developed from

repeated social interactions, which constitute the basis of rela-

tional trust (Kostova and Roth 2002; Yang, Su, and Fam 2012).

In this regard, the logics underpinning informal institutions are

more in line with the formation of relational trust.

Hypotheses

Effects of Trust Asymmetry

We first posit that both calculative and relational TA show

negative influences on exchange performance. First, high

calculative TA implies that the exchange parties attach differ-

ent importance to the economic reasoning of gains and losses.

Thus, when allocating jobs to fulfill performance goals, high

calculative TA would motivate exchange parties to understand

their roles and obligations in different ways (Rousseau et al.

1998). Whereas the exchange party who emphasizes a calcula-

tion of gains and losses in building trust would pay more atten-

tion to actions that are related to high rewards and low

punishments (Poppo, Zhou, and Li 2016), the other would

understand their roles with less calculation. This inconsistency

would generate conflicts when interpreting each other’s expec-

tations, leading to additional transaction costs and, thus, lower

performance satisfaction.

Second, according to economic evaluations, calculative

trust relies on a forward-looking decision rule to guide how

the exchange parties would work (Bromiley and Harris 2006;

Poppo, Zhou, and Li 2016). In this regard, when interfirm

partners have asymmetric levels of calculative trust, they show

inconsistent reliance on this forward-looking logic. We argue

that such an inconsistency indicates divergent time horizon

expectations regarding the specific exchange relationship and

drives different behavioral patterns of international partners.

To be specific, the international partner with relatively lower

calculative trust tends to adopt a short-term perspective about

the transaction relationship and pursue interests in the short run

(Bromiley and Harris 2006), whereas its partner is more likely

to show less concern about short-term benefits and be long-

term oriented. The misalignment of motivations between

international exchange parties leads to inconsistent and even

contradictory transactional behaviors, thus decreasing overall

satisfaction regarding the exchange.

H1a: Calculative trust asymmetry is negatively associated

with exchange

performance.

We further argue that relational TA decreases exchange

performance for two reasons. First, relational TA indicates

that the exchange parties rely differently on past interactions

to interpret the partner’s intentions and obligations (Gulati

1995). In this situation, interfirm partners are likely to have

divergent understandings about the roles and responsibilities

of each of the parties. To be specific, the partner who has

higher relational trust tends to show higher learning capabil-

ity in understanding roles and more inertia in linking their

expectations to prior interactions (Gulati 1995), whereas its

partner relies less on the past to consider each other’s roles

and obligations. This generates misunderstandings between

transaction parties and, thus, increases conflicts in the inter-

national exchange relationship, resulting in lower exchange

performance.

Second, exchange parties with relational TA tend to place

inconsistent emphases on mutuality when carrying out roles

and jobs. Such divergence causes interfirm partners to behave

in very different ways. Specifically, the party who attaches

more importance to mutuality is more likely to care about its

partner’s welfare and act beneficially because it is in its

86 Journal of International Marketing 28(2)

partner’s interest (Lewicki and Bunker 1996), whereas its part-

ner shows less care regarding the other’s benefits and has a

higher tendency to pursue self-interest. Such a misalignment

fails to support business partners to work well together and

proceed smoothly to achieve joint goals, thereby increasing

transaction costs and curtailing exchange performance. Thus,

we propose

the following

hypothesis:

H1b: Relational trust asymmetry is negatively associated

with exchange performance.

Institutional Distance and Trust Asymmetry

We argue that formal institutional distance decreases calcula-

tive trust asymmetry. First, high formal institutional distance

implies high dissimilarity between two nations’ regulations,

rules, and sanctions that influence business practices (Salomon

and Wu 2012; Scott 1995). International parties become more

concerned about the aspects of the foreign legal rules and

practices that are unfamiliar to them to avoid any misbehaviors

that would invite legal sanctions (Yang, Su, and Fam 2012).

Due to the perceived high risk within the relationship, both

sides tend to be more cautious and sensitive about their invest-

ments and rewards, which in turn fortifies their calculative

mindsets. In this regard, both sides continually assess the gains

and losses for cooperation and noncompliance, attempting to

use this as an internal remedy to curtail external hazards. Dur-

ing the process, exchange partners align their calculative trust

perceptions and thereby lower their cal

culative TA.

Second, given that formal institutions contain rules and

practices that are objective and explicit (Scott 1995), interna-

tional business participants can easily recognize the specific

differences between the two nations. For instance, formal insti-

tutions constrain business participants’ behaviors through

explicit rules and observable sanctions such that international

exchange parties can still obtain specific information despite

distance (Gaur and Lu 2007; Scott 1995). The observable

nature of those codes and practices enables international inter-

firm partners to make comparable assessments of the costs and

benefits of compliance and noncompliance, thus allowing them

to better build similar forward-looking decision rules between

them. As a result, the exchange parties are more likely to

develop similar levels of calculative trust. Thus, we propose

the following hypothesis:

H2a: Formal institutional distance is negatively associ-

ated with calculative trust asymmetry.

We argue that informal institutional distance increases rela-

tional TA for two reasons. First, informal institutional distance

reflects differences in national cultures in terms of the attitudes,

beliefs, values, and norms of business participants (Yang, Su,

and Fam 2012). For example, whereas Western relationships

usually emphasize a fair and even relationship, guanxi does not

demand an equal level of reciprocity but may request a sacri-

fice of self-interest in the anticipation of future favors (Gu,

Hung, and Tse 2008). This divergence adds complexity and

difficulty to interactions within the international dyads and

increases the perceived risk for international exchanges (Leo-

nidou et al. 2014). Facing such risk, it is likely that international

interfirm partners with dissimilar cultural backgrounds will

have different views regarding mutuality (Eden and Miller

2004). Specifically, one may show more goodwill and care

regarding mutuality, whereas the other may be more likely to

show willingness to pursue self-interest. Therefore, we argue

that international exchange parties are more likely to develop

different levels of relational trust toward each other because of

such dissimilar behavior patterns, thus resulting in higher rela-

tional TA.

Second, in the forms of values, beliefs, cognitions, and

norms of conduct, informal institutions are imprinted in parti-

cipants’ mindsets and are characterized as implicit and tacit

(Scott 1995; Yang, Su, and Fam 2012). Informal institutions

are, therefore, difficult for outsiders to understand and interpret

(Johnston et al. 2012; Leonidou et al. 2014). Reciprocal obli-

gation and face saving, which are two operating norms of

guanxi, can be difficult to understand even in other collectivist

cultures such as Russia’s and Japan’s (Guthrie 1998). Given the

implicit nature of informal institutions, exchange parties tend

to organize their perceptions and develop norms with reference

to their cultural backgrounds (Scott 1995). Because informal

backgrounds influence the way that firms understand and inter-

pret situations (Samaha, Beck, and Palmatier 2014), exchange

parties with high informal institutional distance also tend to

interpret previous interactions within the specific exchange

through different perspectives, allowing more opportunity for

relational TA to arise. Thus, we propose the following

hypothesis:

H2b: Informal institutional distance is positively associ-

ated with relational trust asymmetry.

Moderating Effects of Prior Interactions and Expectations
of Continuity

We also explore how prior interactions and expectations of

continuity moderate the effects of formal and informal institu-

tional distance. Prior interactions are essential in interorganiza-

tional relationships (Poppo, Zhou, and Ryu 2008; Rindfleisch

and Heide 1997). With a longer transacting history and more

frequent interactions, interfirm partners learn about each other

and gain familiarity (Lee 2013). Expectations of continuity

capture business parties’ prospects for their future exchange

relationships (Lusch and Brown 1996). When exchange parties

anticipate continued relationships, they generally attach more

importance to the relationships (Poppo, Zhou, and Ryu 2008).

As key characteristics capturing the past and the future of inter-

firm relationships, both factors play roles in the trust-building

process that cannot be ignored (Ganesan 1994; Lusch and

Brown 1996; Poppo, Zhou, and Ryu 2008). Whereas institu-

tional distance serves as an external force that shapes the par-

ties’ behaviors, prior interactions and expectations of

continuity serve as two internal forces that jointly influence

Wang et al. 87

the participants’ perceptions and behaviors in the formation of

trust asymmetry.

We contend that a high prior interaction level intensifies the

effect of formal institutional distance on constraining calcula-

tive TA. First, with high levels of repeated interactions,

exchange parties accumulate knowledge and specific informa-

tion about each other (Kwon, Haleblian, and Hagedoorn

2016). Such prior learning enables international parties to

develop a better understanding of their partners’ expectations

and decision rules. Whereas high formal institutional distance

motivates participants to adopt more calculative decision

rules and behavior patterns, prior interactions facilitate parti-

cipants’ calculations by offering unified and precise informa-

tion (Gulati 1995; Poppo, Zhou, and Ryu 2008) and thus

provide a common ground for exchange parties to better align

their assessments of gains and losses, further lowering calcu-

lative TA. Conversely, when levels of prior interaction are

low, international parties cannot predict their potential gains

and losses on the basis of historical interactions. Even though

great formal institutional distance fortifies their calculative

perspectives, the lack of sufficient historical information pro-

hibits their ability to form a consistent level of calculative

trust toward each other.

Second, prior interactions facilitate the establishment of a

standardized approach (Poppo, Zhou, and Ryu 2008; Reuer and

Ariño 2007). With collaborative histories, both parties gain a

better mutual understanding of how the transaction can be

organized to achieve greater benefits and how the routinized

process based on prior history can reduce costs (Reuer and

Ariño 2007). Whereas formal institutional distance exerts

influence through dissimilar codes and practices and motivates

firms to adopt more calculative thinking, a standardized

approach developed on the basis of prior interactions would

enable participants to assess the costs and benefits in the same

way, thereby strengthening the effect on constraining the

potential calculative TA. In contrast, a low prior interaction

level fails to support exchange parties with different formal

institutions to effectively build a standardized process, thereby

increasing the possibility of a divergence in calculative trust.

Thus, we propose the following hypothesis:

H3a: The negative relationship between formal institu-

tional distance and calculative trust asymmetry is stronger

when the prior interaction level is high than when it is

low.

We further posit that high levels of prior interaction weaken

the link between informal institutional distance and relational

TA. As international parties repeatedly interact, they tend to

rely more on prior experience than cultural stereotypes to form

perceptions about their partners (Kwon, Haleblian, and Hage-

doorn 2016). Whereas informal institutional distance would

enlarge relational TA given the dissimilar cultural imprints of

international partners, prior interactions build a collective

experience that narrows the perception gap between the two.

Through repeated interactions, exchange parties gain specific

knowledge about each other and develop a greater understand-

ing of their partners’ idiosyncrasies (Reuer and Ariño 2007).

Buckley, Clegg, and Tan (2006) echo that active guanxi build-

ing in China facilitates the development of a common under-

standing of the aspects of ongoing interactions. This provides a

relational basis for exchange parties to bridge their original

divergence in cultural values and align their methods of inter-

pretation with mutual experience during the interaction pro-

cess. Progressing from distinct cultural backgrounds to

shared experiences helps to mitigate the initial effect of diver-

gent informal institutions. Conversely, when prior interaction is

low, with limited shared experiences, international exchange

parties would rely more on their dissimilar cultural back-

grounds to form perceptions and trust, thus allowing a higher

degree of relational TA to emerge from informal institutional

distance. Therefore, we propose the following hypothesis:

H3b: The positive relationship between informal institu-

tional distance and relational trust asymmetry is weaker

when the prior interaction level is high than when it is
low.

We also propose that a high expectation of continuity level

amplifies the influence of formal institutional distance in

reducing calculative TA. First, in the presence of a high expec-

tation of continuity, exchange parties recognize that it is impor-

tant to maintain a long-term relationship with their partners

(Ganesan 1994). Under this condition, international interfirm

partners tend to exert more effort to make plans and show more

concern about potential risks arising from formal institutional

distance (Yang, Su, and Fam 2012). For instance, they need to

pay more attention to the possibility of a government transition

occurring when requiring government support to deal with sud-

den issues. As a result, when the expectation of continuity level

is high, exchange parties with distant formal institutions are

more likely to show similar sensitivity and make coordinated

assessments to constrain external risks, leading to a lower level

of calculative TA. By contrast, when expectation of continuity

is low, it is less possible that international interfirm partners

will show comparable levels of sensitivity in response to per-

ceived risks.

Second, when the expectation of continuity level is high, the

transaction partners are more willing to regularly share useful

and confidential information with each other (Dyer and Singh

1998; Poppo, Zhou, and Ryu 2008). The provision of contin-

uous and unified knowledge to formally distant exchange par-

ties facilitates their calculating efforts to clearly specify their

responsibilities and rights to deal with the divergence in expli-

cit formal institutions (Gaur and Lu 2007), thereby enabling

them to make more aligned evaluations about benefits and

costs, resulting in an even lower degree of calculative TA. In

contrast, when the expectation of continuity is low, exchange

parties who view their relationships as short-lived tend to with-

hold specific information. This fails to help international inter-

firm partners with formal institutional distance work well

together to make consistent assessments of gains and losses,

88 Journal of International Marketing 28(2)

thereby weakening the effectiveness of efforts to constrain cal-

culative TA.

H4a: The negative relationship between formal institu-

tional distance and calculative trust asymmetry is stronger

when the expectation of continuity level is high than

when it is low.

We further hypothesize that a high expectation of continuity

mitigates the influence of informal institutional distance on

relational TA. When the expectation of continuity is high, both

exchange parties show more willingness to signal goodwill

through actively sharing information and making commitments

within the relationship (Dyer and Singh 1998; Parkhe 1993).

While dissimilar cultural backgrounds increase relational

through the occurrence of divergent understandings and inter-

pretations, high expectations about the relationship continuity

align the perceptions of cross-border exchange dyads and

encourage mutual engagement (Poppo, Zhou, and Ryu 2008).

Such joint efforts weaken the role of divergent informal back-

grounds in shaping exchange parties’ perceptions and trust,

thereby mitigating the effect of informal institutional distance

on relational TA. In contrast, under the condition of a low

expectation of continuity, the implicit character of informal

institutions can still be a concern for cross-border transaction

parties with different informal backgrounds, allowing rela-

tional TA to emerge. Therefore, we propose the following

hypothesis:

H4b: The positive relationship between informal institu-

tional distance and relational trust asymmetry is weaker
when the expectation of continuity level is high than
when it is low.

Method

Sampling and Data Collection

For the empirical research setting, we focused on international

buyer–supplier relationships within various manufacturing

industries in China. China engages heavily in international

business. In 2017, the amount of international trade of goods

and services with China was $4.63 trillion USD, which

accounts for 10.16% of all world trade (World Bank
2017). Despite this achievement, China also faces increasing

challenges to effectively manage its cross-border exchange

relationships due to the complexity of transition economies

and the recent global rise in protectionism. Moreover, China

is characterized by an underdeveloped legal framework and

a traditional culture (Armstrong and Yee 2001). Its distinct

institutional environment not only places an emphasis on

trust for relationship management but also underlines the

necessity for firms to better understand the role of institu-

tional distance when dealing with cross-border players

(Armstrong and Yee 2001). All these aspects make China

a suitable context for our study.

We collected data at both the interorganizational level and

institutional level. For the interorganizational-level data, we

approached both buyers and suppliers to retrieve dyadic data.

By randomly selecting firms using a list from the National

Bureau of Statistics of China, we identified an initial sample

of 1,200 manufacturing firms located in more developed areas

in China (Beijing, Shanghai, and Guangdong) and in the sur-

rounding less developed areas, such as Hebei, Anhui, and

Jiangxi. These firms operated within the four-digit Chinese

Industrial Classification codes 1311–4290, covering industry

sectors such as medicine, electronics, telecommunication,

mechanics, automobiles, chemicals, apparel, food, textiles, and

furniture. As such, this sample provides significant variations

in China’s institutional environments.

We conducted a questionnaire survey to collect the interor-

ganizational data. Drawing on a thorough review of the related

literature and in-depth discussions with experienced research-

ers in the area, we developed an initial version of the question-

naire in English. Two independent translators then translated it

into Chinese (i.e., Chinese Mandarin). We then conducted

back-translation and compared the different versions to ensure

conceptual equivalence and accurate calibration. To verify the

validity and clarity of our questionnaire content, we invited 20

senior managers with practical experience to pretest the survey.

The respondents not only answered the survey questions but

also provided suggestions about the questionnaire content.

With their feedback, we made minor changes to refine the

questionnaire.

To guarantee survey quality, we ensured that our inter-

viewers were well-trained before sending them to conduct

onsite interviews (Hoskisson et al. 2000; Ju, Jin, and Zhou

2018). Before they gave the survey, the interviewers explained

the objectives and importance of the study to participants and

offered to provide a report with the findings and conclusions to

encourage their participation. For the main data collection, we

contacted senior managers from matched buyers and suppliers

to gather dyadic data. We first contacted the senior purchasing

managers who are mainly and directly responsible for dealing

with major suppliers, as they are the key respondents. We asked

them to identify a major supplier and then answer the distrib-

uted survey questions referring to the specific relationship with

the supplier. With their responses and information, we

approached the corresponding supplier managers and collected

matched assessments regarding the specific relationship with

the buyer.

After excluding 17 responses with missing values on the key

variables of interest, we obtained a sample of 433 matched

buyer–supplier relationships, yielding a response rate of

36.08%. Of the 433 dyads, there were 134 international
buyer–supplier relationships, which constitute the final sample

for this study. The sample size is comparable to prior interna-

tional marketing studies (Ju, Jin, and Zhou 2018). To avoid

potential nonresponse bias, we adopted t-tests to compare the

samples of respondents and nonrespondents in terms of firm

size (t ¼ .68, p ¼ .50) and firm age (t ¼ .90, p ¼ .38) (Lambert
and Harrington 1990). According to the results, there was no

statistically significant difference between the groups, indicat-

ing limited risk of nonresponse bias for this study.

Wang et al. 89

Among the final sample, 74 of the dyads were local buyer–

foreign supplier relationships and 60 were foreign buyer–local

supplier relationships. Appendix A shows the details of the

sampling characteristics. On average, as senior managers, the

participants had 7.52 years of experience within the firm and

12.89 years within the industry. Moreover, we included a

qualification question to measure the respondents’ familiarity

with the survey content (Cannon and Perreault 1999), and the

average score was 5.40 (seven-point scale). These statistics

offered support to the assertion that our informants were

knowledgeable about our research questions and qualified to

offer reliable assessments about their ongoing exchange rela-

tionships, thereby enhancing the validity of our study (John

and Reve 1982).

The final sample covered 19 economies, including mainland

China, the United States, the U.K., France, Japan, Singapore,

Australia, Germany, Denmark, India, South Korea, the Nether-

lands, Luxembourg, Norway, Philippines, Sweden, Switzer-

land, Hong Kong, and Taiwan. On the basis of this sample,

we collected corresponding institutional-level data. To evalu-

ate the lagged effect of institutions, we obtained data regarding

the formal institutions and informal institutions one year before

the survey data was collected. For the effect of trust asymmetry

on exchange performance, although we considered a time-

lagged data collection, it was difficult to collect adequate sam-

ples given the dyadic relationship context of our research

design. Because the major focus of our study is institutional

origins of trust asymmetry, we ultimately decided to save the

lagged effect of trust asymmetry as an empirical challenge for

future research.

Measures

Appendix B shows the measurement details of the multi-item

constructs from the survey. To examine calculative trust, we

adapted three items from Lewicki and Bunker (1996) and

Rousseau et al. (1998) to capture the degree of the participants’

perception of calculative confidence regarding the relationship.

For relational trust, we followed Lewicki and Bunker (1996) to

adopt a three-item scale to assess the extent of the exchange

parties’ relational beliefs about the business relationship in

terms of shared understanding and common identity. We then

calculated the absolute value of the buyer calculative/relational

trust minus the supplier calculative/relational trust within the

relationship to examine calculative TA and relational TA. For

exchange performance, we relied on a four-item scale adapted

from Bercovitz, Jap, and Nickerson (2006) to assess relation-

ship performance. We computed the average value of the buyer

and supplier evaluations to indicate the exchange performance.

We examined two main aspects of institutional distance—

formal and informal institutional distance—to gain a more

comprehensive picture of the cross-border business relation-

ships. To compute formal institutional distance, we first fol-

lowed Kaufmann, Kraay, and Mastruzzi (2009) and adopted

the following six dimensions to measure the quality of formal

institutions: voice and accountability, political stability, control

of corruption, government effectiveness, regulatory quality,

and rule of law. All these are critical indicators of legal and

regulatory institutions (Kaufmann, Kraay, and Mastruzzi

2009). Using data from the World Bank Governance Indicators

database (World Bank 2014), we created the composite vari-

able of formal institutional distance (FD) with the deviation

along each of the dimensions, as follows:

FD j ¼
X6
i¼1

ðD ij � D iChinaÞ2 =V i
n o

= 6

FD j stands for the formal institutional distance of country j

from China. D ij is the index for country j on the ith formal

dimension. D iChina indicates the index for China on the ith

formal dimension. V i is the variance of the index of the ith

dimension across countries.

For informal institutional distance, we focused on the

national culture, which broadly captures both cognitive and

normative institutions (Salomon and Wu 2012). Hofstede

(2001) classified culture into five separate dimensions (indivi-

dualism vs. collectivism, masculinity vs. femininity, power

distance, uncertainty avoidance, and long-term orientation),

which have been widely used in prior studies (Salomon and

Wu 2012). Because relationship marketing literature has well

recognized the representation of the five dimensions (Samaha,

Beck, and Palmatier 2014), we ultimately focused on them to

measure informal institutions. We used the differences across

the five cultural dimensions to measure informal institutional

distance and obtained available data from Hofstede’s database

(www.geerthofstede.nl). Similarly, we constructed informal

institutional distance (ID) as follows (Kogut and Singh 1988;

Shenkar 2001):

ID j ¼
X5
i¼1

ðD ij � D iChinaÞ2 = V i
n o

= 5

ID j refers to the informal institutional distance of country j

from China; D ij represents the index for country j for the ith

informal dimension; D iChina is the index for China for the ith

informal dimension; and V i is the variance of the index of the

ith informal dimension.

We computed prior interaction with the product term of

exchange duration and exchange frequency. Exchange duration

is the number of years that the exchange parties have been

doing business together. Exchange frequency examines the

frequency that the buyer places orders with the supplier as

follows: (1) more than once a day, (2) once a day, (3) one to

five times a week, (4) two to three times a month, (5) once a

month, (6) five to ten times a year, (7) two to four times a year,

and (8) once a year. We reverse-coded the exchange frequency

to align with the concept of prior interaction as follows: the

higher the exchange frequency, the higher the degree of prior

interaction. The data was identical for buyers and suppliers. For

expectation of continuity, we adapted three items from Gane-

san (1994) and Lusch and Brown (1996) to evaluate the degree

of the participants’ belief about the continuity of their

90 Journal of International Marketing 28(2)

http://www.geerthofstede.nl

relationships. The items were adjusted according to interviews

with participants. We calculated the average value of the buyer

and supplier data to capture the shared level of expectations of

continuity.

To eliminate alternative explanations, we also included sev-

eral control variables that potentially influenced the dependent

variables in the analysis. First, considering the unignorable

correlations between shared values and asymmetric values,

we controlled shared calculative trust (the average value of

buyer calculative trust and supplier calculative trust) when

examining calculative TA and shared relational trust (the aver-

age value of buyer relational trust and supplier relational trust)

for analysis of relational TA.

Second, to account for the potentially significant roles of

exchange hazards in influencing exchange performance and

trust, we controlled two transactional characteristics—asset

specificity and supply market uncertainty—which have been

highlighted in prior studies (McEvily, Zaheer, and Kamel

2017; Poppo and Zenger 2002). For asset specificity, we

adapted three items following Cannon and Perreault (1999) and

Jap and Ganesan (2000) to assess the degree to which the

exchange parties had made specific and non-redeployable

investments within the relationship. With the dyadic data, we

computed both the shared asset specificity (the average value

of buyer asset specificity and supplier asset specificity) and

asset specificity asymmetry (the absolute value of buyer asset

specificity minus supplier asset specificity). For supply market

uncertainty, we followed Cannon and Perreault (1999) to adopt

a three-item scale that examined the extent to which the supply

market changes in terms of pricing, product features and spec-

ifications, and product supply and demand.

Regarding transactions in Chinese society, guanxi is an

important force that affects a firm’s business decisions and

actions, especially regarding trust (Cai, Jun, and Yang 2010;

Lee and Dawes 2005). Therefore, guanxi serves as a valuable

control for our analysis given the Chinese context. Using three

items developed by Child, Chung, and Davies (2003) that cap-

ture the respondents’ awareness of the significance of guanxi

when doing business in the market, we measured the guanxi

importance (the average value of buyer evaluation and supplier

evaluation) and incorporated it as a control.

Moreover, to further account for firm-level effects, we con-

trolled for the buyer/supplier age (i.e., the number years the

buyer/supplier has been in operation) and buyer/supplier size

(i.e., the number of people the buyer/supplier employs), which

have been shown to have important implications for firm deci-

sions and performance. For these variables, we applied natural

logarithms given the positive skewness. In addition, because

industries play a significant role in explaining performance, we

included buyer industry types to control for the potential

effects. With three dummy variables, we respectively coded

1 for mechanics, heavy (e.g., materials, automobile, chemicals)

and electronics, and 0 for all other industries.

Construct validity. We first conducted exploratory factor analysis
for the multidimensional measures and did not observe high

cross-loadings between them. Using confirmatory factor anal-

ysis for the constructs, Appendix B reports the results of the fit

statistics of the measures, suggesting an acceptable model fit

for the study (w2 / df ¼ 1.94, CFI ¼ .96, IFI ¼ .96, RMSEA ¼
.075). All the loadings on the factors were statistically signif-

icant (p < .01). For all constructs, the composite reliability (CR) values fell into the range between .85 and .95, and the

average variance extracted (AVE) ranged from .66 to .87.

These results provided support for adequate convergent valid-

ity. Moreover, for every possible pair of multidimensional con-

structs, we constrained the correlation for one model to 1.0 and

freely estimated the correlation for another model. Then, we

ran chi-square difference tests to show that the difference

between them was significant, displaying discriminant validity

(Anderson and Gerbing 1988).

Common method bias. By collecting data from different sources
(formal/informal institutional distance from the secondary data

and other variables from the survey data), we can safely state

that common method variance was not a significant threat for

our study (Podsakoff et al. 2003). In addition, for the subjective

responses to the survey, we took measures to ensure that

respondents clearly understood the survey content. By guaran-

teeing informants that we protected their confidentiality, we

also constrained the common method variance (Podsakoff

et al. 2003).

To further control for common method variance, we adopted

the marker variable technique, following Lindell and Whitney

(2001). We used the firm tenure of supplier respondent (i.e., the

number of years the supplier respondent had been working at

the company) as the marker variable because it was not theo-

retically related to at least one of the focal constructs in the

study, and the correlation between the firm tenure of supplier

respondent and the exchange performance variable was .01.

After conducting a partial correlation adjustment for all bivari-

ate correlations between the constructs, the significance of the

correlations remained consistent. The results indicate that com-

mon method variance was not a serious problem in this study.

Analysis and Results

Hypothesis Testing

Our study first examined the impacts of calculative and rela-

tional TA on exchange performance and then analyzed the

influences of formal/informal institutional distance on calcula-

tive/relational TA with the moderating roles of prior interac-

tions and expectations of continuity. For interaction effects, we

mean centered formal institutional distance, informal institu-

tional distance, prior interactions, and expectations of continu-

ity to constrain the potential multicollinearity between the

variables and their interaction terms (Aiken

and West 1991).

Among all the variables, the maximum variance inflation factor

was 1.78, suggesting that multicollinearity was not likely to be

a significant issue. Table 2 reports the descriptive statistics and

correlations among all the variables.

Wang et al. 91

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In Table 3, Model 2 shows the regression results of calcu-

lative TA on exchange performance, and Model 4 examines the

effect of relational TA. For the model analyses of H2a and H2b,

we followed McEvily, Zaheer, and Kamal (2017) and adopted

seemingly unrelated regression, which is a regression in which

two or more unrelated dependent variables are predicted by sets

of independent variables, to deal with potential correlations

between the error terms of the variables (Zellner 1962). Table 4

displays the seemingly unrelated regression results of the insti-

tutional origins of calculative TA and relational TA. In Table 4,

Models 1 and 4 report the influences of the controls on the

dependent variables, Models 2 and 5 test the main effects of

formal and informal institutional distance, and Models 3 and 6

represent the results of the full model with the product terms of

formal/informal institutional distance and the moderators.

As we can observe from Table 3, Model 2, calculative TA

shows a significantly negative influence on exchange perfor-

mance (b ¼�.21, p < .01), which supports the prediction that the increasing divergence in calculative trust between

exchange parties is detrimental for business relationships.

According to Table 3, Model 4, relational TA also significantly

reduces exchange performance (b ¼�.16, p < .05). Thus, both H1a and H1b are well supported.

As shown in Table 4, Model 2, the hypothesized relationship

between formal institutional distance and calculative TA is sig-

nificantly negative (b ¼ �.31, p < .01), which confirms H2a (that formal institutional distance has a negative effect on calcu-

lative TA). For H2b, Model 5 in Table 4 reveals that informal

institutional distance leads to a significant increase in relational

TA (b ¼ .22, p < .05), which supports the prediction that rela- tional TA becomes higher when the informal institutional dis-

tance between international exchange parties increases.

We then tested the moderating effects of prior interactions

and expectations of continuity. For significant interactions, we

employed a simple slope analysis and plotted graphs to better

explain the interaction coefficients following Aiken and West

(1991). With the mean value and standard deviation (SD) of

each moderator, we computed its high levels (one SD above

the sample mean) and low levels (one SD below the sample

mean) to illustrate the interaction effect in Figure 2 (Aiken

and West 1991).

H3a predicted that prior interactions negatively moderate the

association between formal institutional distance and calcula-

tive TA. However, the result in Table 4, Model 3, does not

show a significant moderating effect of prior interactions, fail-

ing to support H3a. A possible reason for this is that despite the

specific knowledge gained from experience, prior interactions

also breed relational inertia, which may weaken the interna-

tional exchange parties’ sensitivities to external risks and thus

inhibit their active calculations as a response (Lee 2013).

H3b posited that the influence of informal institutional dis-

tance on increasing relational TA becomes weaker when the

level of prior interactions is high. The significant and negative

interaction between prior interactions and informal institutional

distance provides support to H3b (b ¼ �.21, p < .05). As Figure 2, Panel A, shows, the positive association between

informal institutional distance and relational TA is much stron-

ger at low (simple slope: b ¼ .11, t ¼ 3.12, p < .01) rather than

Table 3. Regression Results: Exchange Performance.

Dependent Variable: Exchange Performance

Model 1 Model 2 Model 3 Model 4

Independent Variables b t b t b t b t

Shared calculative trust .15* 2.01 .14* 1.98
Shared relational trust .16* 2.01 .17* 2.22
Shared asset specificity �.26** �3.57 �.29** �4.05 �.20* �2.47 �.22** �2.78
Asset specificity asymmetry �.10 �1.49 �.03 �.44 �.13y �1.81 �.10 �1.38
Supply market uncertainty .20** 2.83 .24** 3.40 .17* 2.31 .14

y
1.82

Guanxi importance .29** 3.88 .30** 4.08 .32** 4.33 .33** 4.54
Buyer age .02 .28 .01 .11 .01 .09 .02 .30
Supplier age �.05 �.72 �.06 �.84 �.05 �.62 �.05 �.67
Buyer size .22** 3.00 .23** 3.34 .19** 2.64 .17* 2.36
Supplier size �.03 �.35 �.00 �.05 .01 .07 .02 .33
Mechanics .37* 2.27 .30

y
1.84 .37* 2.26 .33* 2.01

Heavy .54** 2.71 .44* 2.22 .57** 2.87 .52** 2.62
Electronics .44* 2.40 .37* 2.05 .45* 2.45 .42* 2.31
H1a: Calculative TA �.21** �2.95
H1b: Relational TA �.16* �2.16
R2 .31 .33 .30 .32
F-value 9.04** 9.76** 9.24** 9.14**

yp < .10. *p < .05. **p < .01. Notes: Standardized coefficients are reported for b.

Wang et al. 93

high levels of prior interaction (simple slope: b ¼ .01, t ¼ .16,
p > .10).

For calculative TA, the interaction between formal institu-

tional distance and expectations of continuity is significantly

negative (b ¼ �.23, p < .01), which supports H4a. As shown in Figure 2, Panel B, the role of formal institutional distance in

reducing calculative TA is significantly negative when the

expectation of continuity is high (simple slope: b ¼ �.04, t ¼
�7.36, p < .01) and less significant when it is low (simple slope: b ¼�.01, t ¼�1.83, p < .10). H4b predicted that the influence of informal institutional distance on relational TA becomes

weaker at high levels of expectation of continuity. Our results

demonstrate that the interaction term of informal institutional

dis

tance and expectations of continuity is significantly negative

(b ¼ �.20, p < .05), which supports H4b. Figure 2, Panel C, reveals that the impact of informal institutional distance on rela-

tional TA is insignificant for relationships with high expectation

of continuity levels (simple slope: b ¼ .00, t ¼ .00, p > .10) and
is significantly positive for those with low expectation of con-

tinuity levels (simple slope: b ¼ .12, t ¼ 3.23, p < .01).

Additional Analysis

Because the final sample of our study consists of both local

buyer–foreign supplier and foreign buyer–local supplier rela-

tionships, we conducted an additional test to complement our

analysis. Since the sizes of the two types of relationships are

comparable, we split the whole sample into the following two

groups: the local buyer–foreign supplier group and the foreign

buyer–local supplier group. We then reran the analysis for the

two groups individually to examine whether there is any dif-

ference. Although the regression results of the two groups show

lower significance levels with smaller sample sizes, the results

of this analysis were highly consistent with the results of the

whole sample.

To be specific, for the local buyer–foreign supplier group,

both calculative TA (b ¼�.16, p < .05) and relational TA (b ¼ �.13, p < .05) relate negatively to exchange performance. In addition, formal institutional distance negatively influences

calculative TA (b ¼�.33, p < .05), and informal institutional distance positively influences relational TA (b ¼ .16, p < .10). With calculative TA as the dependent variable, the interaction

Table 4. Seemingly Unrelated Regression Results: Calculative and Relational Trust Asymmetry.

Dependent Variable: Calculative TA Dependent Variable: Relational TA

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6

Independent Variables b t b t b t b t b t b t

Shared calculative trust �.17y �1.86 �.13 �1.37 �.18y �1.84
Shared relational trust .12 1.19 .16 1.51 .12 1.17
Shared asset specificity �.13 �1.41 �.09 �.90 �.09 �.92 �.18y �1.74 �.15 �1.36 �.17 �1.57
Asset specificity asymmetry .30** 3.42 .30** 3.48 .27** 3.15 .09 .98 .08 .87 .10 1.08
Supply market uncertainty .18* 1.97 .20* 2.26 .19* 2.24 �.19* �1.96 �.19* �2.01 �.18* �1.97
Guanxi importance .03 .36 .02 .21 .01 .11 .06 .60 .09 .94 .06 .59
Buyer age �.06 �.60 .03 .31 .05 .48 .13 1.35 .09 .90 .13 1.31
Supplier age �.04 �.45 �.06 �.58 �.06 �.64 �.06 �.64 �.05 �.45 �.09 �.86
Buyer size .08 .84 .07 .71 .07 .78 �.14 �1.45 �.17y �1.71 �.18y �1.86
Supplier size .11 1.13 .07 .70 .06 .58 .18y 1.90 .16* 1.67 .20* 2.09
Mechanics �.39 �1.60 �.36 �1.56 �.42y �1.81 �.42y �1.69 �.43y �1.75 �.32 �1.32
Heavy �.51y �1.74 �.47y �1.65 �.50y �1.77 �.52y �1.73 �.50y �1.66 �.36 �1.24
Electronics �.36 �1.34 �.32 �1.24 �.36 �1.43 �.38 �1.39 �.39 �1.43 �.39 �1.47
H2a: Formal institutional distance (FD) !

calculative TA
�.31** �3.60 �.33** �3.85 .00 .01 �.04 �.39

H2b: Informal institutional distance (ID) !
relational TA

.02 .25 .03 .36 .22* 2.40 .19* 2.16

Prior interaction �.06 �.63 �.05 �.45 .05 .45 �.01 �.14
Expectation of continuity �.03 �.25 .04 .41 .02 .14 �.01 �.11
H3a: FD � prior interaction ! calculative TA .02 .29 .08 .87
H3b: ID � prior interaction ! relational TA �.04 �.47 �.21* �2.29
H4a: FD � expectation of continuity !

calculative TA
�.23** �2.59 .10 1.11

H4b: ID � expectation of continuity !
relational TA

.02 .25 �.20* �2.15

R2 .20 .28 .33 .15 .19 .28
F-value 2.36* 2.77** 2.65** 1.69y 1.98* 2.12**

yp < .10. *p < .05. *p < .01. Notes: Standardized coefficients are reported for b.

94 Journal of International Marketing 28(2)

of formal institutional distance and prior interactions remains

insignificant, and the interaction of formal institutional dis-

tance and expectations of continuity is significantly negative

(b ¼�.47, p < .05). For the effects on relational TA, both the interaction terms of informal institutional distance and prior

interactions (b ¼ �.35, p < .05) and informal institutional distance and expectations of continuity (b ¼ �.16, p < .10) are negative and significant.

For the foreign buyer–local supplier group, both calculative

TA (b ¼�.17, p < .05) and relational TA (b ¼�.15, p < .10) negatively influence exchange performance. Moreover, we

found a negative relationship between formal institutional dis-

tance and calculative TA (b ¼ �.37, p < .01) and a positive relationship between informal institutional distance and rela-

tional TA (b ¼ .17, p < .10). With calculative TA as the depen- dent variable, the interaction of formal institutional distance and

prior interactions is insignificant, and there is a significantly

negative interaction between formal institutional distance and

expectations of continuity (b ¼ �.39, p < .01). For the influ- ences on relational TA, both the interaction terms of informal

institutional distance and prior interactions (b ¼�.27, p < .10) and informal institutional distance and expectations of continuity

(b ¼ �.18, p < .05) are significantly negative.

Discussion

Our research examines how formal and informal institutional

distance influence the formation of calculative trust asymmetry

and relational trust asymmetry in international marketing rela-

tionships. With 134 dyads of international buyer–supplier

relationships, our results first show that both calculative and

relational TA negatively influence exchange performance and

that formal institutional distance constrains calculative TA

whereas informal institutional distance leads to a higher degree

of relational TA. Moreover, exchanges with high prior interac-

tion levels show weaker links between informal institutional

distance and relational TA. A high expectation of continuity

level strengthens the role of formal institutional distance in

reducing calculative TA and mitigates the impact of informal

institutional distance on relational TA.

Research Implications

Our study contributes to international marketing research in

three ways. First, the study contributes to trust research by

empirically examining the role of trust asymmetry in interna-

tional buyer–supplier relationships, answering calls for further

exploration of trust in dyadic relationships (McEvily, Zaheer,

and Kamal 2017). Although prior studies view trust as an

important factor in interfirm interactions, there have been

mixed findings about the influence of trust on exchange per-

formance (Aulakh, Kotabe, and Sahay 1996; Gulati and Nick-

erson 2008; Katsikeas, Skarmeas, and Bello 2009). By

adopting an asymmetrical perspective and empirically examin-

ing the influences of calculative and relational TA on exchange

performance, our study offers an explanation for the inconsis-

tent results of previous studies and enriches the understanding

of the performance implications of trust. Moreover, in contrast

to mutual trust, trust asymmetry indicates a divergence in

understanding, motivation, and emphasis across the exchange

Low

High

R
el

at
io

na
l T

Informal Institutional Distance

High prior interaction

Low prior interaction

High

A: H3b. Informal Institutional Distance and Prior Interaction: Relational TA.

Low High

C
al

cu
la

tiv
e

Formal Institutional Distance

High expectation of continuity

Low expectation of continuity

High

B: H4a. Formal Institutional Distance and Expectation of Continuity: Calculative TA

Low High
R
el
at
io
na
l T
A
Informal Institutional Distance
High expectation of continuity
Low expectation of continuity
High

C: H4b. Informal Institutional Distance and Expectation of Continuity: Relational TA.

Figure 2. Interaction effects.

Wang et al. 95

dyad, thereby increasing conflicts and transaction costs and

resulting in lower exchange performance. This explains the

failure of some seemingly strong relationships and further con-

tributes to research on the dark side of trust (McEvily, Zaheer,

and Kamal 2017; Scheer 2012).

Second, this article integrates an institutional view in under-

standing how formal and informal institutional distance influ-

ence different forms of trust asymmetry in cross-border

relationships. Due to the high complexity of developing trust

with counterparties from divergent institutional backgrounds, it

is urgent for international exchange parties to understand under

what circumstances trust asymmetry can emerge (Korsgaard,

Brower, and Lester 2015; Zaheer and Kamal 2011). We suggest

that a formal institutional distance urges international channel

partners to make continual assessments of gains and losses to

constrain external risk and makes them build similar forward-

looking decision rules given the objective and explicit charac-

teristics of formal institutions, thereby constraining calculative

TA. In contrast, informal institutional distance enlarges rela-

tional TA due to international exchange parties’ dissimilar

behavior patterns and different reliance on cultural back-

grounds to develop understandings and interpretations about

previous relations. The empirical results confirm our argu-

ments. By explaining the distinct implications of formal and

informal institutional distance, we extend the understanding of

institutional origins of trust asymmetry in the international

context (Zaheer and Kamal 2011).

Third, we introduce an interdependence perspective to

investigate the moderating roles of prior interactions and

expectations of continuity in understanding the institutional dis-

tance–trust asymmetry relationship. The empirical findings show

that prior interactions weaken the link between informal institu-

tional distance and relational TA by providing shared experiences

to mitigate the initial effect of different cultural backgrounds.

Moreover, an expectation of continuity strengthens the impact

of formal institutional distance on constraining calculative TA

by highlighting the importance of making continued assessments

and motivating international interfirm partners to share detailed

information. An expectation of continuity also lessens the influ-

ence of informal institutional distance on increasing relational TA

by encouraging cross-border exchange parties to share informa-

tion and make commitments to signal goodwill. The findings

underscore the importance of developing a contingent view of

the effects of institutional distance on trust asymmetry.

Managerial Implications

Our study provides important practical implications for inter-

national marketing relationships. First, managers often empha-

size the building of trust but ignore the potential trust

asymmetry. Representing the divergence in trust across the

dyad, trust asymmetry increases conflicts and transaction costs

and is disruptive to joint outcomes, thereby reflecting the dark

side of trust. By investigating the negative implications of both

types of trust asymmetry in international relationships, our

study cautions managers to also take their partners’ trust into

consideration and avoid relying too heavily on trust to manage

the exchange relationship lest their partners do not trust in the

same way.

Furthermore, managers should understand that their institu-

tional backgrounds play a nontrivial role in shaping trusting

relationships. Specifically, for culturally distant marketing

relationships, firm managers should be more cautious about

relying on relational trust to manage their exchange relation-

ships because their dissimilar cultural backgrounds could breed

higher levels of divergence in relational trust, indicating

increasingly negative consequences. For international relation-

ships with high formal institutional distance, firm managers

can worry less about the potential negative impacts of calcula-

tive trust asymmetry since both sides are motivated to make

continual assessments and are able to achieve consistency.

Third, by examining whether the parties hold a shadow of

past or a shadow of future perception, our study provides guide-

lines for international channel partners with originally diver-

gent institutional backgrounds to operate more effectively. For

exchanges with high prior interaction levels, relational TA is

less likely to be an issue for culturally distant partners because

they are able to learn about each other and develop a better

understanding during the interaction process. When the expecta-

tion of continuity is low, managers need to be more concerned

with calculative trust asymmetry when dealing with their for-

mally distant partners because their evaluation efforts become

less effective. In addition, managers should be particularly alert

to the more serious issue of relational trust asymmetry arising

from informal institutional distance because interfirm partners

are more likely to have divergent views regarding engagement.

Limitations and Future Research

The limitations of our study leave several issues up for future

investigation. First, we adopted the measures of the united

index of formal and informal dimensions with the assumption

that all dimensions have equal weight (Kogut and Singh 1988).

This method, however, has limitations because the dimensions

might vary in their effect sizes (Shenkar 2001). Future studies

might extend this by adopting specific data that allows more

solid measurements, thereby making contributions to interna-

tional marketing research.

Second, the study focuses on the generality of international

marketing parties, but it does not discuss the potentially diver-

gent characteristics of buyers and suppliers. With different posi-

tions within relationships, buyers and suppliers might have

divergent perceptions and operations concerning the role of trust

(Nyaga, Whipple, and Lynch 2010). Taking this into consider-

ation, it would be fruitful for researchers to advance the literature

in this area by comparing the potentially different roles of buyers

and suppliers in influencing the effect of trust asymmetry.

Third, our study examines exchange performance using

overall satisfaction, which is a focal consequence of transaction

relationships and has been widely used in prior research (Gulati

and Nickerson 2008; Poppo and Zenger 2002). However, it has

limitations, and future research could examine the different

96 Journal of International Marketing 28(2)

aspects of performance to investigate the performance trade-

offs of trust asymmetry in international marketing relationships

(Katsikeas et al. 2016). In addition, it is also meaningful to

adopt objective performance indicators, such as accounting

performance, to provide the validity of the findings (Katsikeas

et al. 2016).

Fourth, as trust asymmetry is still a nascent topic, future

research can investigate other possible contingencies, such as

transactional attributes for the effects of formal and informal

institutional distance, to offer a more nuanced understanding.

In addition, an extension of this study might include the use of

longitudinal data to provide a dynamic view of how the roles of

trust asymmetry evolve as exchange relationships proceed over

a longer time period. Specifically, it would be beneficial for

future research to collect time-lagged data to examine the effect

of trust asymmetry on exchange performance.

Finally, although we consider guanxi an important informal

institution regulating business interactions in China, we fail to

test it directly. Given the uniqueness of guanxi, it would be

meaningful for further research to extend our proposed model

by investigating the roles of guanxi in the links between insti-

tutional distance and trust asymmetry in a Chinese context.

Appendix A. Characteristics of sample firms.

Category Buyer Firms (%) Supplier Firms (%)

1. Number of employees
Less than 100 14.93 24.63
100–499 45.52 47.76
500–999 17.16 13.43
1,000 and above 22.39 14.18

2. Annual revenue (in millions of renminbi)
Less than five 63.43 68.66
5–9 9.7 13.43
10–49 14.93 13.43
50 and above 11.94 4.48

3. Industry Type
Medicine 5.97 1.49
Electronics, telecommunication 27.61 27.61
Mechanics 23.88 19.40
Chemical 9.70 14.93
Metal, automobiles/parts 20.37 25.58
Others (food, shoes/clothing, furniture, print, textiles, etc.) 12.47 10.99

Appendix B. Measurement items and validity assessment.

Items
Standardized

Factor Loading

Exchange performance (reported by buyers/suppliers: CR ¼ .91/.91; AVE ¼ .71/.73) Buyer Supplier
In dealing with this supplier/client, to what degree do you agree (1 ¼ “very low,” and 7 ¼ “very high”):
1. The partner’s performance leaves a lot to be desired from an overall standpoint. .80 .81
2. We are satisfied with the outcomes from this buyer–supplier relationship. .88 .87
3. Our relationship with this partner has been a successful one. .85 .86
4. Our relationship with this partner has more than fulfilled our expectations. .84 .87

Calculative trust (reported by buyers/suppliers: CR ¼ .87/.88; AVE ¼ .70/.72) Buyer Supplier
In dealing with this supplier/client, to what degree do you agree (1 ¼ “very low,” and 7 ¼ “very high”):
1. Considering the costs and benefits involved in the relationship, both parties act as expected. .97 .96
2. Considering rewards and punishments, both parties behave honestly in dealing with each other. .76 .85
3. The behaviors of both parties are trustworthy because the costs and punishments of misconduct are very high. .76 .72

Relational trust (reported by buyers/suppliers: CR ¼ .93/.94; AVE ¼ .83/.84) Buyer Supplier
In dealing with this supplier/client, to what degree do you agree (1 ¼ “very low,” and 7 ¼ “very high”):
1. Both parties allow the other make decisions because we think like one another. .95 .95
2. Both parties can effectively act for the other because both share the same understanding of what matters. .95 .96
3. Both parties are confident that their interests will be fully protected because both parties share the common identity. .82 .84

Expectation of continuity (reported by buyers/suppliers: CR ¼ .86/.85; AVE ¼ .67/.66) Buyer Supplier
In dealing with this supplier/client, to what degree do you agree (1 ¼ “very low,” and 7 ¼ “very high”):
1. Our company expects the relationship with this supplier/client to continue for a long time. .86 .88

(continued)

Wang et al. 97

Associate Editor

Kelly Hewett

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to

the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for

the research, authorship, and/or publication of this article: This study

was supported by the China National Natural Science Foundation

(Project nos.71602173, 71821002) and the Fundamental Research

Funds for the Central Universities (Project nos. 2019kfyXJJS042,

2019WKYXQN052).

References

Aiken, Leona S. and Stephen G. West (1991), Multiple Regression:

Testing and Interpreting Interactions. Newbury Park, CA: SAGE

Publications.

Altinay, Levent, Maureen Brookes, Melih Madanoglu, and Gurhan

Aktas (2014), “Franchisees’ Trust in and Satisfaction with Fran-

chise Partnerships,” Journal of Business Research, 67 (5), 722–28.

Anderson, James C. and David W. Gerbing (1988), “Structural Equa-

tion Modeling in Practice: A Review and Recommended Two-Step

Approach,” Psychological Bulletin, 103 (3), 411–23.

Anderson, James C. and James A. Narus (1990), “A Model of Dis-

tributor Firm and Manufacturer Firm Working Partnerships,” Jour-

nal of Marketing, 54 (1), 42–58.

Armstrong, Robert W. and Siew Min Yee (2001), “Do Chinese Trust

Chinese? A Study of Chinese Buyers and Sellers in Malaysia,”

Journal of International Marketing, 9 (3), 63–86.

Aulakh, Preet S., Masaaki Kotabe, and Arvind Sahay (1996), “Trust

and Performance in Cross-Border Marketing Partnerships: A Beha-

vioral Approach,” Journal of International Business Studies, 27

(5), 1005–32.

Bercovitz, Janet, Sandy D. Jap, and Jack A. Nickerson (2006), “The

Antecedents and Performance Implications of Cooperative

Exchange Norms,” Organization Science, 17 (6), 724–40.

Blau, Peter Michael (1964), Exchange and Power in Social Life. New

York: Wiley.

Bromiley, Philip and Jared Harris (2006), “Trust, Transaction Cost

Economics, and Mechanisms,” in Handbook of Trust Research,

Akbar Zaheer and Reinhard Bachmann, eds. Cheltenham, UK:

Edward Elgar Publishing, 124–43.

Bstieler, Ludwig and Martin Hemmert (2008), “Developing Trust in

Vertical Product Development Partnerships: A Comparison of

South Korea and Austria,” Journal of World Business, 43 (1),

35–46.

Buckley, Peter J., Jeremy Clegg, and Hui Tan (2006), “Cultural

Awareness in Knowledge Transfer to China—The Role of Guanxi

and Mianzi,” Journal of World Business, 41 (3), 275–88.

Cai, Shaohan, Minjoon Jun, and Zhilin Yang (2010), “Implementing

Supply Chain Information Integration in China: The Role of Insti-

tutional Forces and Trust,” Journal of Operations Management, 28

(3), 257–68.

Cannon, Joseph P. and William D. Perreault Jr. (1999), “Buyer–Seller

Relationships in Business Markets,” Journal of Marketing

Research, 36 (4), 439–60.

Child, John, Leanne Chung, and Howard Davies (2003), “The Perfor-

mance of Cross-Border Units in China: A Test of Natural Selec-

tion, Strategic Choice, and Contingency Theories,” Journal of

International Business Studies, 34 (2), 242–54.

Appendix B. (continued)

Items
Standardized
Factor Loading

2. Maintaining a long-term relationship with this supplier/client is important to us. .81 .77
3. We expect this supplier/client to continue working with us for a long time. .78 .79

Asset specificity (reported by buyers/suppliers: CR ¼ .94/.93; AVE ¼ .84/.81) Buyer Supplier
You may have made investments in time, energy, and/or money specifically to accommodate this supplier/client and its

products. These investments would be lost if your firm switched to another supplier/client. Please indicate the extent to
which your firm has made investments or changes specifically to accommodate this supplier/client (1 ¼ “none,” and 7 ¼ “a
great deal”). Just for the supplier/client, we have changed our (1 ¼ “none,” and 7 ¼ “a great deal”):
1. Product features .88 .88
2. Personnel .94 .92
3. Inventory and distribution procedures .93 .90

Supply market uncertainty (reported by suppliers: CR ¼ .95; AVE ¼ .87)
For this supply market, the following factors are changing (1 ¼ “very infrequent,” and 7 ¼ “very frequently”): Supplier
1. Pricing .88
2. Product features and specifications .96
3. Product supply and demand .95

Guanxi importance (reported by buyers/suppliers: CR ¼ .93/.92; AVE ¼ .81/.79) Buyer Supplier
1. In this market, business depends on good connections with friends and family. .94 .91
2. In this market, guanxi is still very important. .99 .94
3. In this market, guanxi is a requirement for success. .76 .82

Notes: Sample size ¼ 134. Model fit: w2 (401) ¼ 776.44, p < .01; CFI ¼ .96, IFI ¼ .96; RMSEA ¼ .075. CR ¼ composite reliability; AVE ¼ average variance extracted.

98 Journal of International Marketing 28(2)

DiMaggio, Paul J. and Walter W. Powell (1983), “The Iron Cage

Revisited: Institutional Isomorphism and Collective Rationality

in Organizational Fields,” American Sociological Review, 48 (2),

147–60.

Doney, Patricia M. and Joseph P. Cannon (1997), “An Examination of

the Nature of Trust in Buyer–Seller Relationships,” Journal of

Marketing, 61 (2), 35–51.

Dyer, Jeffrey H. and Wujin Chu (2000), “The Determinants of Trust

in Supplier–Automaker Relationships in the U.S., Japan, and

Korea,” Journal of International Business Studies, 31 (2),

259–85.

Dyer, Jeffrey H. and Wujin Chu (2003), “The Role of Trustworthiness

in Reducing Transaction Costs and Improving Performance:

Empirical Evidence from the United States, Japan, and Korea,”

Organization Science, 14 (1), 57–68.

Dyer, Jeffrey H. and Harbir Singh (1998), “The Relational View:

Cooperative Strategy and Sources of Interorganizational Compet-

itive Advantage,” Academy of Management Review, 23 (4),

660–79.

Eden, Lorraine and Stewart R. Miller (2004), “Distance Matters: Lia-

bility of Foreignness, Institutional Distance and Ownership

Strategy,” in Theories of the Multinational Enterprise: Diversity,

Complexity, and Relevance. Advances in International Manage-

ment, Vol. 16, Michael A. Hitt and Joseph L.C. Cheng, eds. Bing-

ley, UK: Emerald Group Publishing Limited, 187–221.

Ganesan, Shankar (1994), “Determinants of Long-Term Orientation in

Buyer–Seller Relationships,” Journal of Marketing, 58 (2), 1–19.

Gaur, Ajai S. and Jane W. Lu (2007), “Ownership Strategies and

Survival of Foreign Subsidiaries: Impacts of Institutional Distance

and Experience,” Journal of Management, 33 (1), 84–110.

Graebner, Melissa E. (2009), “Caveat Venditor: Trust Asymmetries in

Acquisitions of Entrepreneurial Firms,” Academy of Management

Journal, 52 (3), 435–72.

Griffith, David A., Matthew B. Myers, and Michael G. Harvey (2006),

“An Investigation of National Culture’s Influence on Relationship

and Knowledge Resources in Interorganizational Relationships

Between Japan and the United States,” Journal of International

Marketing, 14 (3), 1–32.

Gu, Flora F., Kineta Hung, and David K. Tse (2008), “When Does

Guanxi Matter? Issues of Capitalization and Its Dark Sides,” Jour-

nal of Marketing, 72 (4), 12–28.

Gulati, Ranjay (1995), “Does Familiarity Breed Trust? The Implica-

tions of Repeated Ties for Contractual Choice in Alliances,” Acad-

emy of Management Journal, 38 (1), 85–112.

Gulati, Ranjay and Jack A. Nickerson (2008), “Interorganizational

Trust, Governance Choice, and Exchange Performance,” Organi-

zation Science, 19 (5), 688–708.

Guthrie, Douglas (1998), “The Declining Significance of Guanxi in

China’s Economic Transition,” China Quarterly, 154, 254–82.

Heide, Jan B. and George John (1992), “Do Norms Matter in Market-

ing Relationships?” Journal of Marketing, 56 (2), 32–44.

Hofstede, Geert Jan (2001), Culture’s Consequences, 2nd ed. Thou-

sand

Oaks, CA: SAGE Publications.

Homburg, Christian, Joseph P. Cannon, Harley Krohmer, and Ingo

Kiedaisch (2009), “Governance of International Business

Relationships: A Cross-Cultural Study on Alternative Governance

Modes,” Journal of International Marketing, 17 (3), 1–20.

Hoskisson, Robert E., Lorraine Eden, Chung Ming Lau, and Mike

Wright (2000), “Strategy in Emerging Economies,” Academy of

Management Journal, 43 (3), 249–67.

Jap, Sandy D. and Shankar Ganesan (2000), “Control Mechanisms and

the Relationship Life Cycle: Implications for Safeguarding Spe-

cific Investments and Developing Commitment,” Journal of Mar-

keting Research, 37 (2), 227–45.

Jiang, Crystal X., Roy Y.J. Chua, Masaaki Kotabe, and Janet Y.

Murray (2011), “Effects of Cultural Ethnicity, Firm Size, and Firm

Age on Senior Executives’ Trust in Their Overseas Business Part-

ners: Evidence from China,” Journal of International Business

Studies, 42 (9), 1150–73.

John, George and Torger Reve (1982), “The Reliability and Validity

of Key Informant Data from Dyadic Relationships in Marketing

Channels,” Journal of Marketing Research, 19 (4), 517–24.

Johnston, Wesley J., Shadab Khalil, Megha Jain, and Julian Ming-

Sung Cheng (2012), “Determinants of Joint Action in Interna-

tional Channels of Distribution: The Moderating Role of

Psychic Distance,” Journal of International Marketing, 20 (3),

34–49.

Ju, Min, Jason Lu Jin, and Kevin Zheng Zhou (2018), “How Can

International Ventures Utilize Marketing Capability in Emerging

Markets? Its Contingent Effect on New Product Development,”

Journal of International Marketing, 26 (4), 1–17.

Katsikeas, Constantine S., Neil A. Morgan, Leonidas C. Leonidou,

and G. Tomas M. Hult (2016), “Assessing Performance Outcomes

in Marketing,” Journal of Marketing, 80 (2), 1–20.

Katsikeas, Constantine S., Dionysis Skarmeas, and Daniel C. Bello

(2009), “Developing Successful Trust-Based International

Exchange Relationships,” Journal of International Business Stud-

ies, 40 (1), 132–55.

Kaufmann, Daniel, Aart Kraay, and Massimo Mastruzzi (2009),

“Governance Matters VIII: Aggregate and Individual Governance

Indicators, 1996–2008,” Working Paper No. 4978, World Bank

Policy Research.

Kogut, Bruce and Harbir Singh (1988), “The Effect of National Cul-

ture on the Choice of Entry Mode,” Journal of International Busi-

ness Studies, 19 (3), 411–32.

Korsgaard, M. Audrey, Holly H. Brower, and Scott W. Lester (2015),

“It Isn’t Always Mutual: A Critical Review of Dyadic Trust,”

Journal of Management, 41 (1), 47–70.

Kostova, Tatiana and Kendall Roth (2002), “Adoption of an Organi-

zational Practice by Subsidiaries of Multinational Corporations:

Institutional and Relational Effects,” Academy of Management

Journal, 45 (1), 215–33.

Krishnan, Rekha, Xavier Martin, and Niels G. Noorderhaven (2006),

“When Does Trust Matter to Alliance Performance?” Academy of

Management Journal, 49 (5), 894–917.

Kumar, Nirmalya, Lisa K. Scheer, and Jan-Benedict E.M. Steenkamp

(1995), “The Effects of Perceived Interdependence on Dealer

Attitudes,” Journal of Marketing Research, 32 (3), 348–56.

Kwon, Seok-Woo, Jerayr Haleblian, and John Hagedoorn (2016), “In

Country We Trust? National Trust and the Governance of

Wang et al. 99

International R&D Alliances,” Journal of International Business

Studies, 47 (7), 807–29.

Lambert, Douglas M. and Thomas C. Harrington (1990), “Measuring

Nonresponse Bias in Customer Mail Surveys,” Journal of Business

Logistics, 11 (2), 44–59.

Lee, Don Y. and Philip L. Dawes (2005), “Guanxi, Trust, and Long-

Term Orientation in Chinese Business Markets,” Journal of Inter-

national Marketing, 13 (2), 28–56.

Lee, Jeongsik (2013), “Dancing with the Enemy? Relational Hazards

and the Contingent Value of Repeat Exchanges in M&A Markets,”

Organization Science, 24 (4), 1237–56.

Leonidou, Leonidas C., Saeed Samiee, Bilge Aykol, and Michael A.

Talias (2014), “Antecedents and Outcomes of Exporter–Importer

Relationship Quality: Synthesis, Meta-Analysis, and Directions for

Further Research,” Journal of International Marketing, 22 (2),

21–46.

Lewicki, Roy J. and Barbara B. Bunker (1996), “Developing and

Maintaining Trust in Work Relationships,” in Trust in Organiza-

tions: Frontiers of Theory and Research, Roderick Kramer and

Tom Tyler, eds. Thousand Oaks, CA: SAGE Publications, 114–39.

Li, Fusheng (2018), “Ford Pushes Localization Strategy, Streamlines

Sales Units in China,” China Daily (June 11), https://www.china

daily.com.cn/cndy/2018-06/11/content_36363081.htm.

Lindell, Michael K. and David J. Whitney (2001), “Accounting for

Common Method Variance in Cross-Sectional Research Designs,”

Journal of Applied Psychology, 86 (1), 114–21.

Lusch, Robert F. and James R. Brown (1996), “Interdependency, Con-

tracting, and Relational Behavior in Marketing Channels,” Journal

of Marketing, 60 (4), 19–38.

Mayer, Roger C., James H. Davis, and F. David Schoorman (1995),

“An Integrative Model of Organizational Trust,” Academy of Man-

agement Review, 20 (3), 709–34.

McEvily, Bill, Akbar Zaheer, and Darcy K. Fudge Kamal (2017),

“Mutual and Exclusive: Dyadic Sources of Trust in Interorganiza-

tional Exchange,” Organization Science, 28 (1), 74–92.

Morgan, Robert M. and Shelby D. Hunt (1994), “The Commitment–

Trust Theory of Relationship Marketing,” Journal of Marketing,

58 (3), 20–38.

Nyaga, Gilbert N., Judith M. Whipple, and Daniel F. Lynch (2010),

“Examining Supply Chain Relationships: Do Buyer and Supplier

Perspectives on Collaborative Relationships Differ?” Journal of

Operations Management, 28 (2), 101–14.

Oliveira, Nuno and Fabrice Lumineau (2019), “The Dark Side of

Interorganizational Relationships: An Integrative Review and

Research Agenda,” Journal of Management, 45 (1), 231–61.

Park, Seung Ho and Yadong Luo (2001), “Guanxi and Organizational

Dynamics: Organizational Networking in Chinese Firms,” Strate-

gic Management Journal, 22 (5), 455–77.

Parkhe, Arvind (1993), “Strategic Alliance Structuring: A Game The-

oretic and Transaction Cost Examination of Interfirm Coop-

eration,” Academy of Management Journal, 36 (4), 794–829.

Peng, Mike W. and Yadong Luo (2000), “Managerial Ties and Firm

Performance in a Transition Economy: The Nature of a Micro–

Macro Link,” Academy of Management Journal, 43 (3), 486–501.

Podsakoff, Philip M., Scott B. MacKenzie, Jeong-Yeon Lee, and

Nathan P. Podsakoff (2003), “Common Method Biases in

Behavioral Research: A Critical Review of the Literature and Rec-

ommended Remedies,” Journal of Applied Psychology, 88 (5),

879–903.

Poppo, Laura and Todd Zenger (2002), “Do Formal Contracts and

Relational Governance Function as Substitutes or Comple-

ments?” Strategic Management Journal, 23 (8), 707–25.

Poppo, Laura, Kevin Zheng Zhou, and Julie J. Li (2016), “When Can

You Trust ‘Trust?’ Calculative Trust, Relational Trust, and Sup-

plier Performance,” Strategic Management Journal, 37 (4),

724–41.

Poppo, Laura, Kevin Zheng Zhou, and Sungmin Ryu (2008),

“Alternative Origins to Interorganizational Trust: An Interdepen-

dence Perspective on the Shadow of the Past and the Shadow of the

Future,” Organization Science, 19 (1), 39–55.

Reuer, Jeffrey J. and Africa Ariño (2007), “Strategic Alliance Con-

tracts: Dimensions and Determinants of Contractual Complexity,”

Strategic Management Journal, 28 (3), 313–30.

Rindfleisch, Aric and Jan B. Heide (1997), “Transaction Cost Analy-

sis: Past, Present, and Future Applications,” Journal of Marketing,

61 (4), 30–54.

Robson, Matthew J., Constantine S. Katsikeas, and Daniel C. Bello

(2008), “Drivers and Performance Outcomes of Trust in Interna-

tional Strategic Alliances: The Role of Organizational Complex-

ity,” Organization Science, 19 (4), 647–65.

Rousseau, Denise M., Sim B. Sitkin, Ronald S. Burt, and Colin

Camerer (1998), “Not So Different After All: A Cross-

Discipline View of Trust,” Academy of Management Review,

23 (3), 393–404.

Salomon, Robert and Zheying Wu (2012), “Institutional Distance and

Local Isomorphism Strategy,” Journal of International Business

Studies, 43 (4), 343–67.

Samaha, Stephen A., Joshua T. Beck, and Robert W. Palmatier (2014),

“The Role of Culture in International Relationship Marketing,”

Journal of Marketing, 78 (5), 78–98.

Scheer, Lisa K. (2012), “Trust, Distrust, and Confidence in B2B

Relationships,” in Handbook on Business to Business Marketing,

Chap. 18, Gary L. Lilien and Rajdeep Grewal, eds. Cheltenham,

UK: Edward Elgar Publishing, 332–48.

Schilke, Oliver and Karen S. Cook (2015), “Sources of Alliance Part-

ner Trustworthiness: Integrating Calculative and Relational

Perspectives,” Strategic Management Journal, 36 (2), 276–97.

Scott, W. Richard. (1995), Institutions and Organizations. Thousand

Oaks, CA: SAGE Publications.

Shen Lu, Chenting Su, Zheng Xu, and Guijun Zhuang (2019),

“Contract Design Capability as a Trust Enabler in the Preformation

Phase of Interfirm Relationships,” Journal of Business Research,

95, 103–15.

Shenkar, Oded (2001), “Cultural Distance Revisited: Towards a More

Rigorous Conceptualization and Measurement of Cultural

Differences,” Journal of International Business Studies, 32 (3),

519–35.

Uzzi, Brian (1997), “Social Structure and Competition in Interfirm

Networks: The Paradox of Embeddedness,” Administrative Sci-

ence Quarterly, 42 (1), 35–67.

Williamson, Oliver E. (1993), “Calculativeness, Trust, and Economic

Organization,” The Journal of Law and Economics, 36 (1), 453–86.

100 Journal of International Marketing 28(2)

https://www.chinadaily.com.cn/cndy/2018-06/11/content_36363081.htm

World Bank (2014), “Worldwide Governance Indicators Project,

1996–2013,” (accessed July 19, 2017), http://www.govindicators.

org.

World Bank (2017), “World Development Indicators,” (accessed Jan-

uary 3, 2019), https://datacatalog.worldbank.org/dataset/world-

development-indicators.

Xin, Katherine R. and Jone L. Pearce (1996), “Guanxi: Connections as

Substitutes for Formal Institutional Support,” Academy of Manage-

ment Journal, 39 (6), 1641–58.

Xu, Dean and Oded Shenkar (2002), “Institutional Distance and the

Multinational Enterprise,” Academy of Management Review, 27

(4), 608–18.

Yang, Zhilin, Chenting Su, and Kim-Shyan Fam (2012), “Dealing

with Institutional Distances in International Marketing Channels:

Governance Strategies That Engender Legitimacy and Efficiency

Firms,” Journal of Marketing, 76 (3), 41–55.

Zaheer, Akbar, Bill McEvily, and Vincenzo Perrone (1998), “Does

Trust Matter? Exploring the Effects of Interorganizational and

Interpersonal Trust on Performance,” Organization Science, 9

(2), 141–59.

Zaheer, Akbar and Darcy Fudge Kamal (2011), “Creating Trust in

Piranha-Infested Waters: The Confluence of Buyer, Supplier, and

Host Country Contexts,” Journal of International Business Studies,

42 (1), 48–55.

Zaheer, Srilata and Akbar Zaheer (2006), “Trust Across Borders,”

Journal of International Business Studies, 37 (1), 21–29.

Zellner, Arnold (1962), “An Efficient Method of Estimating See-

mingly Unrelated Regressions and Tests for Aggregation Bias,”

Journal of the American Statistical Association, 57 (298), 348–68.

Zucker, Lynne G. (1986), “Production of Trust: Institutional Sources

of Economic Structure, 1840 to 1920,” Research in Organizational

Behavior, 8, 53–111.

Wang et al. 101

http://www.govindicators.org

https://datacatalog.worldbank.org/dataset/world-development-indicators

Copyright of Journal of International Marketing is the property of American Marketing
Association and its content may not be copied or emailed to multiple sites or posted to a
listserv without the copyright holder’s express written permission. However, users may print,
download, or email articles for individual use.

On the Relation Between Felt Trust and Actual Trust: Examining Pathways
to and

Implications of Leader Trust Meta-Accuracy

Rachel L. Campagna
University of New Hampshire

Kurt T. Dirks and Andrew P. Knight
Washington University in St. Louis

Craig Crossley
University of Central Florida

Sandra L. Robinson
University of British Columbia

Research has long emphasized that being trusted is a central concern for leaders (Dirks & Ferrin, 2002),
but an interesting and important question left unexplored is whether leaders feel trusted by each
employee, and whether their felt trust is accurate. Across 2 field studies, we examined the factors that
shape the accuracy of leaders’ felt trust— or, their trust meta-accuracy—and the implications of trust
meta-accuracy for the degree of relationship conflict between leaders and their employees. By integrating
research on trust and interpersonal perception, we developed and tested hypotheses based on 2 theoretical
mechanisms—an external signaling mechanism and an internal presumed reciprocity mechanism—that
theory suggests shape leaders’ trust meta-accuracy. In contrast to the existing literature on felt trust, our
results reveal that leader trust meta-accuracy is shaped by an internal mechanism and the presumed
reciprocity of trust relationships. We further find that whether trust meta-accuracy is associated with
positive relational outcomes for leaders depends upon the level of an employee’s actual trust in the leader.
Our research contributes to burgeoning interest in felt trust by elucidating the mechanisms underlying
trust meta-accuracy and suggesting practical directions for leaders who seek to accurately understand
how much their employees trust them.

Keywords: trust, felt trust, meta-accuracy, metaperception, leader

“One of the hardest things for leaders to do is to understand how other
people see them . . .” Bill George, Former CEO of Medtronic (George,
2016).

Trust has become a central concept in organizational research
and, across time, researchers’ efforts have progressed through a
logical series of questions regarding trust. After defining the con-
struct and delineating its theoretical bases, researchers focused on
assessing the importance of trust in the workplace, finding that
trust is associated with a range of important outcomes, including
teamwork and leadership effectiveness (e.g., Colquitt, Scott, &
LePine, 2007; Dirks & Ferrin, 2002; Mayer, Davis, & Schoorman,
1995; McAllister, 1995). Recognizing its significance, researchers
then turned attention to understanding how trust is established

within relationships, identifying key drivers of trust formation and
the psychological processes that underlie it (e.g., Lewicki, Tom-
linson, & Gillespie, 2006).

Having established that being trusted by others is valuable for
employees and leaders, and with an improved understanding of its
antecedents, researchers have recently begun to explore the phe-
nomenon of feeling trusted by others (e.g., Baer et al., 2015; Lau,
Lam, & Wen, 2014; Salamon & Robinson, 2008). Feeling trusted,
or felt trust, reflects the degree to which one person believes that
another person trusts them. Existing research suggests that felt
trust can motivate organizational members to perform at a high
level (Baer et al., 2015; Lau et al., 2014; Salamon & Robinson,
2008) and be more likely to incur personal costs to maintain that
felt trust (Campagna, Mislin, & Bottom, 2019). Thus, evidence
suggests that individuals act upon and respond to felt trust.

An interesting and important question, however, is whether felt
trust reflects the actual trust that exists in the relationship. Are
organizational members able to accurately assess whether they are
trusted? An untested assumption underlying research on felt trust
is that one person’s felt trust is shaped by the actual trust held by
a counterpart and expressed through the counterpart’s behavior.
For example, Baer et al. (2015) suggested that an employee’s felt
trust develops in response to behavioral manifestations of a super-
visors’ actual trust, such as the delegation of critical tasks or
disclosure of sensitive information. Lau et al. (2014, p. 112)
asserted that, although they are different concepts, “trust and felt

This article was published Online First December 19, 2019.
X Rachel L. Campagna, Peter T. Paul College of Business and Eco-

nomics, University of New Hampshire; Kurt T. Dirks and Andrew P.
Knight, Olin Business School, Washington University in St. Louis; Craig
Crossley, Department of Management, University of Central Florida; San-
dra L. Robinson, Sauder School of Business, University of British Colum-
bia.

Correspondence concerning this article should be addressed to Rachel L.
Campagna, Peter T. Paul College of Business and Economics, University
of New Hampshire, 10 Garrison Road, Durham, NH 03824. E-mail:
rachel.campagna@unh.edu

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ISSN: 0021-9010 http://dx.doi.org/10.1037/apl000047

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https://orcid.org/0000-0001-5189-4655

mailto:rachel.campagna@unh.edu

http://dx.doi.org/10.1037/apl0000474

trust are very often related” and are “two sides of the same coin”
(p. 114). As a result, employees and leaders would presumably
want their felt trust to be accurate—to know who trusts them and
who does not—so that they can act appropriately. Likewise, while
leaders are advised to demonstrate their trust so that employees
will know they are trusted, this advice is only useful if employees
assess those signals accurately (e.g., Baer et al., 2015; Nerstad et
al., 2018; Salamon & Robinson, 2008). Recognizing this issue,
researchers have suggested that a logical next step in investigations
of felt trust is to examine the relationship between actual trust and
felt trust (Lau et al., 2014; Salamon & Robinson, 2008).

The current article addresses this issue by integrating theoretical
insights from literatures on trust and interpersonal perception to
critically examine the degree to which a leader’s felt trust corre-
sponds to actual employee trust and why the two may diverge. To
do so, we offer a conceptualization of the relation between felt and
actual trust that is rooted in the more general social psychology
literature on interpersonal perception (e.g., Carlson & Kenny,
2012; Kenny & DePaulo, 1993). Viewed from this perspective, felt
trust is the outcome of one person’s error-prone attempt to accu-
rately understand the perception held by another person (i.e., the
other person’s actual trust). Drawing from this literature, we de-
velop and test predictions about factors that may increase or
decrease the accuracy with which one person (i.e., a leader) un-
derstands another person’s (i.e., an employee’s) trust and examine
why this matters for the relationship between the two.

This article makes several contributions to the literature on trust.
First, our findings challenge two presumptions of existing work on
felt trust—that felt trust is inherently linked to a counterpart’s
actual trust and that observed interpersonal behavior creates a
linkage between the two. Grounded in the more general literature
on interpersonal perception (e.g., Carlson & Kenny, 2012; Kenny
& DePaulo, 1993), we consider how two different psychological
mechanisms might shape how accurate people are in understand-
ing how much others trust them. Rather than accurately interpret-
ing another person’s observable behavior as signals of their true
underlying trust—the presumed mechanism in existing theory and
research on felt trust (e.g., Baer et al., 2015; Lau et al., 2014;
Nerstad et al., 2018; Salamon & Robinson, 2008)— our findings
suggest that an accurate sense of felt trust instead emerges when
someone uses their own trust as the basis for assessing how much
another person trusts them by presuming that trust relationships are
reciprocal. Thus, the findings underscore an important point re-
garding how leaders develop an accurate assessment of trust and
the limitations of relying on the behavioral signals they observe.

Second, our findings extend existing research on felt trust within
organizations in two ways. In contrast to existing research that has
focused on employees feeling trusted by leaders, we consider the
implications of leaders feeling trusted by employees. Felt trust
should be important to leaders, and we argue that the accuracy of
their felt trust may be particularly valuable. Whereas prior research
on felt trust has considered its implications for individual out-
comes like job performance and emotional exhaustion (e.g., Baer
et al., 2015), our theoretical development and empirical findings
suggest that felt trust also has important implications for interper-
sonal outcomes, such as the degree of relationship conflict between
two people. Understanding how felt trust accuracy relates to con-
flict is important, given the adverse effects of conflict with em-
ployees for leaders (de Dreu, Van Dierendonck, & Dijkstra, 2004;

Thomas, 1992). By relaxing the assumption that felt trust is nec-
essarily an accurate reflection of actual trust, we suggest that the
interpersonal implications of felt trust depend upon the degree to
which felt trust and actual trust are aligned (Brion, Lount, &
Doyle, 2015). In addition to cultivating and managing the level of
felt trust that someone feels in an organization, our findings point
to the importance of cultivating and managing the accuracy of
someone’s felt trust.

We begin by integrating the general literature on interpersonal
perception with the literature on felt trust to outline two theoretical
mechanisms that might underlie the accuracy of a leader’s felt
trust. We develop and test predictions that logically flow from
these mechanisms in Study 1—an investigation of leaders and
employees working within a state corrections department who are
entrusted with supervising convicted felons. We conceptually rep-
licate and extend the findings of Study 1 in Study 2—an exami-
nation of leaders and employees working in a nonprofit caregiving
organization who are charged with supporting individuals with
neurological and cognitive impairments. In addition, Study 2 tests
predictions about the implications of accuracy for relationship
conflict.

Theoretical Framework

Trust—“a psychological state comprising the intention to accept
vulnerability based upon positive expectations of the intentions or
behavior of another” (Rousseau, Sitkin, Burt, & Camerer, 1998, p.
395)— has a long history in the organizational literature. The
concept of felt trust is, however, newer. Felt trust refers to the
degree to which a person believes he or she is trusted by another
person (Baer et al., 2015; Salamon & Robinson, 2008). Just as the
concept of trust is relational, such that trust inherently requires a
target (e.g., John trusts Mary), so too is the concept of felt trust
relational (e.g., Mary feels trusted by John). The target for felt trust
can be a group (e.g., Salamon & Robinson, 2008) or an individual
employee (e.g., Lau et al., 2014). In this article, we focus specif-
ically on a leader’s felt trust at the dyad-level, such that felt trust
is a leader’s belief that a given employee is willing to make herself
vulnerable to the leader.

To advance our understanding of felt trust, we draw from the
general literature on interpersonal perception (e.g., Carlson &
Kenny, 2012; DePaulo, Kenny, Hoover, Webb, & Oliver, 1987;
Kenny, 1994; Kenny & DePaulo, 1993). This literature has long
sought to understand how accurately people understand others’
perceptions of them. The concept of felt trust reflects what the
more general interpersonal perception literature refers to as a
dyadic metaperception— one person’s belief about the thought,
attitude, or perception held by another person (Kenny, 1994).
Importantly, and unlike existing theory and research on felt trust,
the more general literature on interpersonal perception does not
presume that a metaperception is an accurate reflection of the other
person’s true thought, attitude, or perception. Instead, a derivative
concept that is the focus of significant research in the literature on
interpersonal perception is the concept of dyadic meta-accuracy—
the degree of alignment between one person’s metaperception and
the actual thought, attitude, or perception held by another person
(Kenny & DePaulo, 1993).

Grounded in the literature on interpersonal perception, the de-
gree of alignment between one person’s felt trust and a counter-

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995LEADER TRUST META-ACCURACY

part’s actual trust is dyadic trust meta-accuracy (i.e., How much
does Mary’s felt trust match John’s actual trust of Mary?; Brion et
al., 2015). Like any form of accuracy, the degree of trust meta-
accuracy can be described in either absolute or directional terms.
In absolute terms, accuracy reflects the separation, or distance,
between one person’s felt trust and another person’s actual trust. In
directional terms, accuracy reflects the degree to which one per-
son’s felt trust over- or underestimates another person’s actual
trust. Theoretically, when leaders accurately understand an em-
ployee’s trust in them—that is, when there is a minimal gap
between felt trust and actual trust—they are equipped to behave in
ways that build or restore weak or broken trust, as well as meet the
employee’s expectations and ensure smooth interpersonal interac-
tions (Brion et al., 2015). But what might enable a leader to
develop an accurate understanding of an employee’s trust? An-
swering this question—and developing predictions about the an-
tecedents of trust meta-accuracy—requires an account of how
leaders’ felt trust forms in the first place.

Theory and research (e.g., DePaulo et al., 1987; Eisenkraft,
Elfenbein, & Kopelman, 2017; Kenny & DePaulo, 1993) describe
two different theoretical pathways through which people form
metaperceptions. These pathways have historical roots in different
literature streams and, consequently, provide different explana-
tions for why leaders may be relatively accurate or inaccurate in
their understanding of how much an employee trusts them. In
particular, these two pathways highlight different sources of infor-
mation that people use when forming their understanding of what
another person thinks. The first—an external pathway— has roots
in an interpersonal relations tradition that describes people as
looking outward, using others’ observable behavior to understand
their perceptions and attitudes (e.g., Funder, 1987; Kenny & Al-
bright, 1987). The second—an internal pathway— has roots in a
cognitive tradition that portrays people as turning inward, relying
on their own perceptions and feelings, in conjunction with cogni-
tive heuristics, to form their beliefs about other people’s percep-
tions and attitudes (e.g., Carlson & Kenny, 2012; De Soto &
Kuethe, 1958, 1959; Heider, 1958). These pathways are not mu-
tually exclusive; rather, each represents a different channel of
information that people can use when forming a metaperception
(Eisenkraft et al., 2017; Kenny & DePaulo, 1993); or, in the
context of our article, a leader’s felt trust.

The External Pathway: Trust Meta-Accuracy Is
Shaped by One’s Interpretation of Another’s Behavior

The external pathway for trust meta-accuracy suggests that
leaders develop felt trust by directly observing and interpreting an
employee’s verbal and nonverbal behaviors as cues or signals of
the employee’s trust (Kenny & DePaulo, 1993). Longstanding
theories of trust are steeped in observation and interpretation of
others’ behavior as a foundation of trust and vulnerability. For
instance, Lewicki and Bunker (1996) suggested early stages of
trust are formed as a “calculus” or expectation based on another’s
prior behavioral cues. To the extent that researchers studying felt
trust have commented on its origins, they have also presumed it to
form through this external mechanism. For example, Nerstad et al.
(2018) stated that employee felt trust stems from cues and signals
sent by one person that convey trust in another. This is consistent
with Baer et al. (2015, p. 1639), who concluded from a series of

interviews that employees use observable behavior “. . . as signals
of their supervisors’ trust in them.” Similarly, Lau, Liu, and Fu
(2007) suggested that employees interpret a leader’s delegation or
monitoring behavior as signals of how much their leader trusts
them.

Developing predictions for this external pathway to trust meta-
accuracy requires considering attributes of both the person sending
social information (i.e., in our case, the employee) and the person
receiving and interpreting this social information (i.e., in our case,
the leader). The logic underlying the external pathway implies that
a leader’s trust meta-accuracy is likely to be high when (a) the
employee’s observable behavior is a true representation of his or
her actual trust in the leader, and/or (b) the leader is a skilled
interpreter of the underlying meaning of the employee’s behavior.
Conversely, a leader is likely to develop an inaccurate understand-
ing of an employee’s trust when (a) the employee’s observable
behavior diverges from his or her actual trust, and/or (b) the leader
misinterprets the meaning of the signals that an employee sends.
We consider each of these two factors in postulating whether a
leader’s felt trust aligns with an employee’s actual trust.

With respect to employees and the signal-sending component,
any attribute that disconnects an employee’s observable behavior
from his or her true feelings of trust would curtail leader trust
meta-accuracy. An attribute that likely distorts the veracity of
social signals is employee self-monitoring—an individual tendency
to monitor situations and to control or modify one’s expressed
behavior to be socially appropriate (Snyder, 1974). Self-monitoring is
likely associated with an employee’s tendency to express a false
sense of trust for the leader (Caldwell & O’Reilly, 1982), which
would reduce a leader’s trust meta-accuracy. Those who are high
in self-monitoring are often referred to as social chameleons be-
cause they alter their external self-presentation to match the norms
and expectations of others in different situations in order to be
viewed positively by others (DePaulo et al., 1987; Kilduff & Day,
1994). In contrast, the observable behaviors of those low in self-
monitoring are driven more by their own internal feelings and
attitudes (Snyder, 1979). Self-monitoring is thus akin to a filter
through which an employee’s true internal feelings and beliefs
must pass before they are expressed as external signals to a leader.
Within the context of a leader– employee relationship, self-
monitoring likely filters out behavior that would signal a lack of
trust in a leader, with employees high in self-monitoring behaving
in ways that signal to their leader a sense of trust and withholding
behaviors that would indicate feelings of distrust. This would
upwardly bias the cues of trust available for the leader to interpret
when forming a sense of felt trust and contribute to an overesti-
mation of an employee’s trust.

Hypothesis 1a: Employee self-monitoring is negatively re-
lated to dyadic leader trust meta-accuracy, such that higher
employee self-monitoring results in a leader overestimating an
employee’s trust.

With respect to leaders and the signal-receiving component of
the external pathway, any attribute that enhances a leader’s effec-
tiveness in interpreting the underlying intentions and feelings that
drive others’ behavior likely improves leader trust meta-accuracy.
Perspective taking—a cognitive process in which one intentionally
adopts and considers the view of another person to understand his

996 CAMPAGNA, DIRKS, KNIGHT, CROSSLEY, AND ROBINSON

or her intentions, beliefs, and attitudes (Parker & Axtell, 2001)—is
an attribute that may make some leaders more fine-tuned receivers
and interpreters of the social signals that are diagnostic of an
employee’s trust. Leaders high in perspective taking may have
superior decoding abilities, which may allow them to process
interactions with, and behaviors of, a given employee and use them
to discern the employee’s true perceptions and feelings (Davis,
1983). Because they more frequently consider others’ internal
motives and beliefs when attempting to make sense of their exter-
nal behavior, leaders high in perspective taking likely interpret an
employee’s behavior in ways that more closely align with the
employee’s actual trust. Thus, perspective taking should enhance a
leader’s ability to attain trust meta-accuracy.

Hypothesis 1b: Leader perspective taking is positively related
to dyadic leader trust meta-accuracy, such that higher leader
perspective taking results in a smaller discrepancy (i.e., abso-
lute difference) between a leader’s felt trust and employee’s
trust.

The Internal Pathway: Trust Meta-Accuracy Is
Shaped by One’s Own Trust in Another and the

Presumption of Reciprocity

In addition to using external information when seeking to un-
derstand another person’s perception, leaders’ meta-accuracy may
also be shaped by an internal mechanism. This internal pathway
reflects the lay theories people hold to help them make sense of
ambiguous information in their social worlds (Bargh & Chartrand,
1999). Classic research in social psychology and interpersonal
perception has highlighted that one cognitive heuristic that people
use when assessing others’ feelings is presumed reciprocity (some-
times called symmetry or balance; e.g., Burnstein, 1967; Heider,
1958; Kenny, 1994)—the assumption that one’s own feelings are
reciprocated by another (Carlson & Kenny, 2012; De Soto, 1960;
De Soto & Kuethe, 1959; Eisenkraft et al., 2017; Kenny & De-
Paulo, 1993; Kenny & Nasby, 1980; Zajonc & Burnstein, 1965).
Although research has found support for the presumption of rec-
iprocity, in that it decreases accuracy by introducing bias into the
perception process, other research on interpersonal perception has
provided empirical support for this pathway in shaping the accu-
racy with which people understand how others view them gener-
ally (e.g., Carlson & Kenny, 2012; Eisenkraft et al., 2017; Elfen-
bein, Eisenkraft, & Ding, 2009; Kenny, Bond, Mohr, & Horn,
1996; Shectman & Kenny, 1994). Yet, notwithstanding this evi-
dence, trust scholars have not—to our knowledge— considered
how this internal mechanism might shape felt trust and, thus, trust
meta-accuracy.

An internal pathway to trust meta-accuracy would suggest that
when trying to determine how much an employee trusts them, a
leader would consider their own feeling of trust for an employee in
conjunction with their cognitive representation of the nature of
trust relationships or their implicit assumption of how trust-based
relationships generally function between a leader and employee.
To illustrate, in their classic research on how people cognitively
represent interpersonal relations, De Soto and Kuethe (1959)
prompted participants with a statement about a relationship, such
as “Jane trusts John.” Then, they asked participants whether John
also trusts Jane, finding that participants expected, at a 73%

probability, a trust-based relationship to be reciprocated by the
other party. This example demonstrates that individuals’ cognitive
representation of trust guides their expectation for reciprocity in
interpersonal relationships. Thus, rather than only drawing from
external observable signals, a leader’s felt trust may be shaped by
their assumption of reciprocity in the relationship with their em-
ployee. Whereas an employee’s trust in a leader may not be
immediately evident to the leader, a leader’s own trust for the
employee is readily accessible and can be used to infer how much
the employee trusts him or her.

Using their own view of an employee and a cognitive heuristic
that trust relationships are reciprocal can yield a relatively accurate
sense of felt trust because trust relationships are, in general, truly
reciprocated (Bacharach, Guerra, & Zizzo, 2007; Kenny, 1994;
Kenny & Nasby, 1980; Pillutla, Malhotra, & Murnighan, 2003).
When people turn inward, consulting their own feelings about a
positive interpersonal relationship with another person, the pre-
sumption of reciprocity tends to be a useful heuristic for inferring
the other person’s trust in them. Thus, we posit that a leader may
achieve trust meta-accuracy through the internal pathway involv-
ing a valid presumed reciprocity mechanism, where a leader’s trust
for his or her employee is positively related to the leader’s felt
trust, which is in actuality reciprocated by the employee.

Hypothesis 2: Dyadic leader trust meta-accuracy is a function
of presumed reciprocity, such that an employee’s trust in a
leader is positively related to a leader’s felt trust indirectly
through a leader’s trust in the employee.

Study

Method

Procedure and sample. We collected survey data from lead-
ers and employees of a large state corrections department in the
United States. Participants represented several common roles in
the department, including corrections officers, caseworkers, and
probation officers. These employees noted in informal interviews
that accurately understanding their relationships with others is
critical in this context. One leader’s comments, for example,
reflected the importance of having an accurate felt trust perception:
“You realize the need to trust others and know they trust you on
day one of the job. When the gates open and you are outnumbered
by inmates, you have to know your people have your back.”

The corrections department provided a roster of leaders and
their employees. Needing to constrain the length of the leader
survey— because leaders would be asked to respond to several
items for each of their employees—we drew a sample from this
roster of all leaders and a maximum of five (randomly selected)
employees per leader. Our personalized e-mail invitations yielded
a total participation of 147 leaders (98% response rate) and 37

employees (78% response rate). Because our hypotheses focused
on the leader– employee pair, our final sample for conducting
analyses comprised the 213 dyadic observations (213 employees
nested within 90 unique leaders) for which we received matched
leader and employee responses.

Leaders were 36% female, 92% White, with an average age of
47.57 years old (SD � 9.21) and average department tenure of
11.57 years (SD � 8.01). Employees were 43% female, 82%

997LEADER TRUST META-ACCURACY

White, with an average age of 42.59 years (SD � 11.82) and
department tenure of 5.72 years (SD � 5.45).1

Measures. Interitem reliability (i.e., Cronbach’s alpha) for
multiitem survey measures is included along the diagonal in
Table 1.

Employee and leader trust. We used three items from Kim,
Ferrin, Cooper, and Dirks (2004), which was based on Mayer and
Davis (1999), using a 5-point Likert-type scale ranging from 1 �
strongly disagree to 5 � strongly agree. Employees responded to
these items for their sole leader; leaders completed the items for
each of their employees, identified by name. A sample item is “I
feel secure in having make decisions that critically affect me.”

Leader felt trust. Leaders responded to the same root items
that we used to measure trust, altered to solicit their beliefs about
how much a given employee trusted them. A sample item that
parallels the item given above is, “[Employee nam] feels secure in
having me make decisions that critically affect him/her.”

Leader trust meta-accuracy. As we explain in greater detail
below, we assessed leader trust meta-accuracy using a multivariate
approach (Edwards, 1995). This entailed considering (a) the alge-
braic difference between a leader’s felt trust and the employee’s
trust (i.e., leader felt trust minus employee trust); (b) the absolute
value of the algebraic difference; and, (c) each of the components
of these difference scores (i.e., leader’s felt trust, employee’s
trust). We explain this approach in greater detail below.

Employee self-monitoring. Employees completed Lennox
and Wolfe’s (1984) 13-item Revised Self-Monitoring scale using a
7-point Likert-type scale (1 � certainly always false to 7 �
certainly always true). A sample item is “In social situations, I
have the ability to alter my behavior if I feel that something else is
called for.”

Leader perspective taking. Leaders completed the 7-item per-
spective taking subscale from the Interpersonal Reactivity Index
(Davis, 1983), responding with a 6-point Likert-type scale (1 �
does NOT describe me well to 6 � describes me well). A sample
item is “Before criticizing somebody, I try to imagine how I would
feel if I were in his/her place.”

Analyses. Predicting leader trust meta-accuracy—the congru-
ence between a leader’s felt trust and an employee’s actual trust—
presents several analytical challenges. Edwards (1995) detailed
how using a difference score (either algebraic or absolute) as a
criterion variable in regression analyses entails making several
untested, and often invalid, assumptions about the relationship
between a predictor variable and concepts like congruence, align-
ment, and accuracy. To appropriately test our hypotheses about
leader trust meta-accuracy we thus used the multistep approach
that Edwards (1995) developed for predicting congruence.

We made three different kinds of predictions regarding the
antecedents of leader trust meta-accuracy. First, our prediction in
Hypothesis 1b involves expectations about how a predictor vari-
able—perspective taking—relates to trust meta-accuracy irrespec-
tive of direction, such that perspective taking is negatively related
to the absolute discrepancy between a leader’s felt trust and an
employee’s trust. To test this hypothesis, following Edwards
(1995), we first computed the absolute difference between the
leader’s felt trust and the employee’s trust for the leader (i.e.,
leader felt trust � employee trust|) and then regressed this onto
predictors of meta-accuracy. We included this analysis because
this is a common way of thinking about accuracy; however, we did

not rely on it for testing our hypotheses because it suffers from
serious disadvantages that can lead to misinterpretation. Specifi-
cally, the use of an absolute difference score for testing a pure
accuracy effect—irrespective of the direction of the difference—
requires making the untested assumption that (a) the relationship
between the predictor and accuracy is positive when a leader’s felt
trust was below an employee’s actual trust (i.e., underestimators);
but, (b) negative when a leader’s felt trust was above an employ-
ee’s actual trust (i.e., overestimators). As Edwards (1995) noted,
using the absolute difference score as an outcome variable would
require assuming that a given predictor “exhibited equal but op-
posite relationships for managers who overestimated their ratings
and managers who underestimated their ratings” (p. 315).

To test this hypothesis, we thus adopted the multistep approach
that Edwards (1995) proposed. We first examined the results of a
univariate model with the algebraic difference score (leader felt
trust � employee trust) as the criterion variable. However, we
created a dummy variable (w) to indicate whether the algebraic
difference score is positive or negative—that is, to indicate
whether a leader has overestimated (w � 0) or underestimated
(w � 1) an employee’s trust.2 We included this dummy variable
and interaction terms between this dummy and each of the focal
variables in our hypotheses as predictors in the model. As Edwards
(1995) showed, regressing the algebraic difference score on the
main effects and interactions is mathematically equivalent to using
the absolute difference as the criterion variable; however, the use
of the dummy variable and interaction terms results in an uncon-
strained equation that enables testing key assumptions underlying
the absolute difference score as a measure of accuracy. In this
equation, the main effect of a predictor indicates the simple slope
of the relationship between the predictor and accuracy for overes-
timators, while the interaction term plus the main effect estimates
the simple slope for underestimators. The strongest statistical
evidence of a true and uniform relationship between a predictor
variable and absolute accuracy is found when the two simple
slopes are equal in magnitude, but opposite in sign.

Following up on this univariate analysis, we examined the
results of a multivariate path analysis in which the two components
of the difference score—the leader’s felt trust and the employee’s
actual trust—were endogenous variables (i.e., Edwards, 1995;
McKee, Lee, Atwater, & Antonakis, 2018). As with the univariate
analysis, we included the dummy variable and interaction terms to
separately model the effect of a given predictor for underestima-
tors and overestimators. Examining the relations between a pre-
dictor and each of the components provides insight into whether a
relation with one component or the other, or both, is responsible
for an observed congruence effect.

1 Study 1 was approved by Washington University in St. Louis’s
Institutional Review Board. Title: Workplace Relationships, Protocol
number 201107015; Study 2 was approved by University of New
Hampshire’s Institutional Review Board. Title: Workplace Relation-
ships, Protocol Number 6483.

2 We followed Edwards’ (1995) guidance for handling cases of perfect
accuracy. Specifically, we examined the impact on parameter estimates of
coding instances of perfect accuracy as either 0 or 1. Because our results
were equivalent across these different coding approaches, we do not report
results below using an additional indicator for instances where the leader’s
metaperception perfectly equals the employee’s trust.

998 CAMPAGNA, DIRKS, KNIGHT, CROSSLEY, AND ROBINSON

We also made a second and slightly different type of prediction in
Hypothesis 1a, regarding employee self-monitoring. Rather than pre-
dicting a relationship with the absolute discrepancy between leader
felt trust and employee trust, here we argued that employee self-
monitoring is related to a specific form of inaccuracy— overestima-
tion of an employee’s trust by a leader. Much like an absolute
difference score is flawed for testing overall accuracy effects, so
too is the algebraic difference score flawed for testing the specific
form of an inaccuracy effect (i.e., overestimation or underestima-
tion). As a simple example, consider an observed correlation
between a predictor variable (e.g., self-monitoring) and an alge-
braic difference score (e.g., leader felt trust � employee trust). A
significant positive correlation could indicate that self-monitoring
is associated with increasing accuracy (i.e., moving from negative
values toward zero) or with increasing overestimation (i.e., moving
from zero to increasingly positive values). To test this hypothesis,
we therefore used an extension of the approach described above
(e.g., Cable, Aiman-Smith, Mulvey, & Edwards, 2000; Cable &
Yu, 2006; Edwards, 1995). Specifically, we examined the coeffi-
cient of the path between a given predictor and a leader’s felt trust
in our multivariate path analysis. Then, we examined whether the
estimated simple effects were above or below the sample values
for an employee’s actual trust (Cable et al., 2000). The strongest
evidence that a given predictor is positively associated with over-
estimation is found when (a) there is a significant positive rela-
tionship between the predictor and the algebraic difference score
and (b) the predicted values at high levels of the predictor variable
in this second regression equation are significantly greater than the
sample values of actual trust.

Finally, to test Hypothesis 2, regarding presumed reciprocity as
a mechanism for dyadic trust meta-accuracy, we interpreted the
coefficients from the multivariate path model used in prior re-
search for assessing presumed reciprocity (i.e., Eisenkraft et al.,
2017; Elfenbein et al., 2009). This model specifies that a leader’s
felt trust is linked to an employee’s actual trust through the
leader’s trust in the employee. Empirical evidence for a presumed
reciprocity effect is thus provided by a significant indirect rela-
tionship between an employee’s actual trust and a leader’s felt trust
via a leader’s trust for an employee.

Also important to consider in our analyses is the potential for
nonindependence in our data. Our focus is dyadic meta-accuracy
and, as such, our focal level of analysis is the leader– employee

dyad. Because some of the leaders in our dataset are matched to
multiple employees, however, it is possible that analyses focusing
on the dyadic level of analysis would violate the assumption of
nonindependence intrinsic to the calculation of standard errors in
Ordinary Least Squares regression. To address this concern and
take into account any clustering of dyads within leaders, we used
clustered robust standard errors, which adjusts standard errors for
possible bias due to nonindependence (McNeish, Stapleton, &
Silverman, 2017).

Following recent guidance regarding the use of control variables
in organizational research (e.g., Carlson & Wu, 2012), we selected
variables to include based on theory. First, we included as controls
variables indicating whether leaders and employees were of the
same gender and ethnicity. Theory and research (e.g., Elfenbein &
Ambady, 2002) suggest that individuals may be better able to
detect and interpret the social signals of those who are of a similar
demographic group. Second, we included as a control variable the
number of years that a leader and an employee had worked
together. Research indicates that trust develops over time and,
further, increasing tenure provides opportunities for leaders to
observe and interpret employee signals of trust (Jones & Shah,
2016). Our results are substantively identical—in significance,
direction, and approximate magnitude—if control variables are
omitted from the models.

Results

Table 1 presents the descriptive statistics for and intercorrela-
tions among Study 1 variables. The negative mean value for the
algebraic difference score (M � �0.15, SD � 0.94) indicates that
there was a slight average tendency for leaders to underestimate
how much an employee trusts them. However, note that the me-
dian value for this variable was zero, suggesting that—at least on
average—this tendency was slight. More relevant for our focus on
the potential for misalignment between felt trust and actual trust,
we observed meaningful variability in accuracy (i.e., SD � 0.94).
Further illustrating the fact that felt trust and actual trust are
imperfectly aligned, the bivariate correlation between the two was
0.32.

Table 2 presents the results of regression models used to test our
hypotheses regarding the predictors of leader trust meta-accuracy.
Following Edwards (1995), we considered several parameters to

Table 1
Study 1: Descriptive Statistics and Correlations

Variable name M SD 1 2 3 4 5 6 7 8 9

1. Same gender .53 .50
2. Same ethnicity .86 .35 .01
3. Employee–leader relationship tenure 2.55 2.71 .13 .13
4. Employee self monitoring 4.14 .64 .03 �.15 .04 (.87)
5. Leader perspective taking 3.64 .53 �.12 �.12 �.08 �.16 (.76)
6. Employee trust in leader (ET) 3.56 .93 .05 .05 �.03 .01 .08 (.76)
7. Leader trust in employee 3.50 .94 .01 �.01 .13 .02 .05 .37 (.84)
8. Leader felt trust (FT) 3.73 .67 .08 .06 .05 .05 .03 .32 .49 (.73)
9. Algebraic difference (FT � ET) �.15 .94 .01 .02 �.07 �.02 .02 .74 �.01 �.40

10. Absolute difference (|FT � ET|) .74 .61 �.09 .12 �.04 �.06 �.01 �.38 �.15 .13 �.46

Note. N � 213 employees nested within 90 leaders. FT � leader’s felt trust; ET � employee’s trust in leader. Cronbach’s alpha is provided for multi-item
scales in parentheses along the diagonal. Denotations of statistical significance are excluded due to nested data structure.

999LEADER TRUST META-ACCURACY

determine the degree of support for Hypotheses 1 and 2. First, we
examined the coefficient relating a given predictor to the absolute
difference of leader and employee ratings (Model 1 of Table 2).
Although this coefficient potentially masks the form of the true
relationship— because it constrains the effect for overestimators
and underestimators to be equal, thus ignoring the direction of
inaccuracy—it provides an initial and coarse estimate of the rela-
tionship. Second, we examined the main effect and interaction of
a given variable with the dummy variable (w) in predicting the
algebraic difference of leader and employee ratings (Model 2 of
Table 2). Third, we examined these same parameters for a given
variable in predicting, separately, leader and employee ratings in a
multivariate path analysis (Model 3 of Table 2). This final step
allows us to break down the component parts (leader felt trust and
employee trust) to provide additional insight into how each pre-
dictor relates to leader felt trust and employee trust in order to
more clearly discern the drivers of congruence (Edwards, 1995).
Fourth, for evaluating Hypothesis 2, we examined the indirect
relationship between a leader’s felt trust and an employee’s actual
trust through the leader’s trust for the employee.

Hypothesis 1, examining the external pathway, predicted that (a)
employee self-monitoring would be negatively related (i.e., over-
estimated); and (b) leader perspective taking would be positively
related to leader trust meta-accuracy (i.e., greater accuracy). As
Table 2 shows, neither employee self-monitoring nor leader per-
spective taking was significantly related to the absolute difference
score (Model 1), the algebraic difference score with interaction
terms (Model 2), or either of the components of these difference
scores (Model 3). Accordingly, Hypotheses 1a and 1b were not
supported.

Hypothesis 2, examining the internal pathway, predicted that a
leader’s meta-accuracy would be a function of presumed reciproc-
ity, such that the employee’s actual trust and the leader’s felt trust
would be influenced by the leader’s own trust in the employee. The
pattern of coefficients in Table 2 suggests support for Hypothesis
2. In Model 2, there was a significant interaction between a
leader’s trust in an employee and the dummy variable marking
over- and underestimators (B � 0.29, p � .01). Simple slopes
analysis indicated that the interactive relationship was such that
leader trust was significantly related to meta-accuracy particularly
for leaders who underestimated how much an employee trusted
them (B � 0.24, SE � 0.06, p � .01). For those who overestimated
how much an employee trusted them, the relationship was not
significant (B � �0.05, p � .42). As Model 3 shows, a leader’s
trust in an employee was significantly and positively related both
to the leader’s felt trust (B � 0.41, p � .01) and to an employee’s
actual trust (B � 0.37, p � .01) and there were no significant
differences between over- and underestimators. Accordingly, we
examined the presumed reciprocity path model delineated by
Eisenkraft et al. (2017) without these interaction terms to directly
test this mechanism. The indirect effect of the relation between a
leader’s felt trust and an employee’s actual trust through the
leader’s trust in the employee was positive and significant (B �
0.12, SE � 0.03, p � .01). Hypothesis 2 was thus supported.

Discussion

The findings of Study 1 did not provide evidence in support of
an external pathway to leader trust meta-accuracy. According to an
external model, a leader’s felt trust is shaped by (a) the verbal and

Table 2
Study 1: Results of Analyses Testing Predictors of Leader Trust Meta-Accuracy

Model 1 Model 2

Model 3: Multivariate

path

analysis

DV � |FT � ET| DV � FT � ET DV � FT DV � ET
Variable name B SE B SE B SE B SE

Intercept .58 (.09) .26 (.10) 3.46 (.22) 3.72 (.25)
W �1.04 (.18)�� .31 (.33) �.73 (.32)��

Same gender �.12 (.11) �.07 (.11) .17 (.10) .10 (.12)
Same ethnicity .23 (.09)� .31 (.08)�� .01 (.22) .30 (.26)
Employee–leader relationship

tenure .01 (.02) �.02 (.01) .00 (.02) �.02 (.02)
Employee self-monitoring �.05 (.07) �.04 (.06) .06 (.08) .02 (.08)
Leader perspective taking .03 (.08) �.04 (.08) .06 (.11) .03 (.08)
Leader trust in employee �.10 (.06) �.05 (.06) .41 (.07)�� .37 (.08)��

W � Same Gender .14 (.20) �.08 (.16) .06 (.20)
W � Same Ethnicity �.61 (.19)�� .26 (.33) �.35 (.33)
W � Employee–Leader

Relationship Tenure �.01 (.03) �.01 (.02) �.01 (.03)
W � Employee Self-Monitoring .09 (.12) �.01 (.14) .08 (.16)
W � Leader Perspective Taking �.25 (.17) .10 (.19) �.15 (.21)
W � Leader Trust in Employee .29 (.11)�� .19 (.10) .10 (.14)
R2 .06 .70 .39 .47
F 1.83 32.06��

Note. N � 213 employees nested within 90 leaders. Entries are unstandardized parameter estimates. All
continuous predictors are grand mean centered. DV � dependent variable; FT � leader’s felt trust; ET �
employee’s trust in leader; W � dummy variable to indicate whether an observation represented overestimation
or underestimation (W � 0 when FT � E and W � 1 when FT � E). Standard errors are cluster robust standard
errors.
� p � .05. �� p � .01 two-tailed.

1000 CAMPAGNA, DIRKS, KNIGHT, CROSSLEY, AND ROBINSON

nonverbal signals of trust that an employee sends and (b) a leader’s
perception and interpretation of those signals. Our results sug-
gested that employee self-monitoring, which was posited to ob-
scure an employee’s true feelings of trust and result in the leader
overestimating trust, was not significantly related to leader trust
meta-accuracy. Our findings also indicated that leader perspective
taking, which we posited would enhance a leader’s ability to
accurately interpret subtle interpersonal signals of trust and thus
yield higher accuracy, was unrelated to meta-accuracy.

The results of Study 1 did provide support, however, for an
internal pathway to leader trust meta-accuracy. According to this
model, a leader’s beliefs about whether an employee trusts them is
shaped by their own feelings about an employee and a cognitive
heuristic of presumed reciprocity in trust relationships. This ex-
planation suggests that a leader’s felt trust is informed by how
much they trust a given employee because a leader’s own view of
the relationship is readily accessible and most proximal. Because
humans’ cognitive representation of trust comprises reciprocity
between two people (De Soto, 1960; Kenny & DePaulo, 1993),
this internal information informs a leader’s assessment of an
employee’s actual trust because they presume that their own feel-
ings of trust for an employee are likely reciprocated. When reci-
procity does exist and employees trust those leaders who trust
them, the presumption of reciprocity increases trust meta-accuracy. In
line with this perspective, we found that (a) a leader’s trust in an
employee was positively related to that leader’s felt trust, (b) a
leader’s trust in an employee was positively related to the employ-
ee’s actual trust, and, consequently, (c) a leader’s trust in an
employee served as a mechanism aligning a leader’s felt trust with
an employee’s actual trust.

Study 2

We sought to accomplish two objectives in Study 2. The first
objective was to conceptually replicate Study 1 to increase confi-
dence in our results. The purpose of a conceptual replication, also
called a systematic replication (e.g., Aronson, Carlsmith, Ells-
worth, & Gonzales, 1990), is to test the robustness of empirical
findings by varying the context, participants, and specific opera-
tionalizations of a set of underlying theoretical variables (Lynch,
Bradlow, Huber, & Lehmann, 2015). Before drawing conclusive
interpretations from Study 1 findings, we sought to examine the
two pathways a second time using a broader set of theoretically
relevant constructs for the external pathway. We also sought to
replicate our findings for Hypothesis 2, regarding the internal
pathway, in a new context to determine if these findings general-
ize. The second objective was to examine an important implication
of leader trust meta-accuracy; namely, its association with subse-
quent relationship conflict between leaders and employees, which
most readily represents the consequence of inaccurate perceptions.

Further Examining the Mechanisms Underlying
Leader Trust Meta-Accuracy

In replicating and extending the findings from Study 1 regarding
the external pathway, we considered whether conceptually similar
variables might drive leader trust meta-accuracy. As with Study 1,
we identified and considered factors that would logically enhance
or mitigate (a) a leader’s ability to accurately receive and interpret

any interpersonal signals that an employee sends regarding trust
and (b) the extent to which an employee sends veridical signals of
trust.

We first considered the opportunity that a leader has to observe
and interpret an employee’s behavioral signals of trust. Research
suggests that increasing the frequency of available social signals
might decrease the degree to which leaders rely on cognitive
heuristics to judge their interpersonal relationship with an em-
ployee (e.g., Freeman, 1992). As such, more frequent interactions
between a leader and an employee should provide the leader with
a larger set of social cues on how much an employee trusts him or
her. If a leader and an employee rarely interact, the leader has few
signals to interpret in forming a sense of felt trust. A basic prediction
in line with the external model is thus that more frequent interactions
between a leader and an employee— because they increase the avail-
ability of interpersonal information— engender greater trust meta-
accuracy.

Hypothesis 1c: The frequency of leader-employee interaction
is positively related to dyadic leader trust meta-accuracy, such
that a greater frequency of interaction results in a smaller
discrepancy (i.e., absolute difference) between a leader’s felt
trust and employee’s trust.

In Study 1 we considered leader perspective taking as an individual
attribute that would enhance a leader’s ability to interpret the social
signals of an employee’s trust. Within a workplace context, a con-
ceptually related characteristic is social astuteness—a dimension of
political skill that reflects the ability to understand social interac-
tions and accurately interpret the meaning of others’ behavior
(Ferris et al., 2007). Much like perspective taking, leaders higher
in social astuteness should be more skilled in ascertaining the true,
underlying perceptions of others in the workplace, due to their
ability to read people and situations (Ferris et al., 2007). Thus,
social astuteness should enhance a leader’s ability to attain trust
meta-accuracy.

Hypothesis 1d: Leader social astuteness is positively related to
dyadic leader trust meta-accuracy, such that greater leader
social astuteness results in a smaller discrepancy (i.e., absolute
difference) between a leader’s felt trust and employee’s trust.

In addition to characteristics that could enhance their ability to
interpret social signals, leaders also could possess attributes that
prompt them to systematically misinterpret an employee’s behav-
ior. One such attribute is narcissism—an individual characteristic
that comprises a grandiose and inflated view of the self (Farwell &
Wohlwend-Lloyd, 1998). Those high in narcissism perceive them-
selves more positively than others actually perceive them (e.g.,
Gabriel, Critelli, & Ee, 1994; John & Robins, 1994; Robins &
John, 1997). Highly narcissistic leaders may be more likely to
systematically misread social signals in a way that is self-
enhancing, by discounting negative feedback and augmenting pos-
itive feedback. By compromising their ability to interpret social
signals, leader narcissism may thus detract from trust meta-
accuracy, contributing to an overestimation of an employee’s
actual trust.

Hypothesis 1e: Leader narcissism is negatively related to
dyadic leader trust meta-accuracy, such that higher leader

1001LEADER TRUST META-ACCURACY

narcissism results in a leader overestimating an employee’s
trust.

In Study 1 we considered employee self-monitoring as an indi-
vidual attribute that could influence the veracity of the behavioral
signals that an employee sends regarding trust and, in particular,
upwardly bias those signals. A conceptually related characteristic
is the use of impression management tactics by an employee.
Impression management tactics are behaviors used to induce a
favorable reaction or perception from another person (Bolino,
1999). Research suggests that employees often direct these behav-
iors specifically toward leaders in the workplace because leaders
control resources (e.g., promotions, performance evaluations) that
employees value (Wayne & Ferris, 1990). Rather than communi-
cating their true feelings of trust to a leader, employees may
instead carefully use impression management tactics, such as in-
gratiation or other-enhancement, to mislead their leader and imply
that their trust is higher than it actually is. Similar to the logic of
employee self-monitoring, the use of these tactics would distort the
signals sent by an employee to a leader, upwardly biasing them,
and inhibit the leader from forming an accurate perception of the
employee’s trust for him or her.

Hypothesis 1f: Employee impression management is nega-
tively related to dyadic leader trust meta-accuracy, such that
higher employee impression management results in a leader
overestimating an employee’s trust.

In addition to examining these alternative conceptualizations
reflecting the external pathway, we replicate our test of Hypothesis
2 and the internal pathway. Recall that this pathway specified that
a leader’s trust in an employee influences dyadic leader trust
meta-accuracy through the use of a presumed reciprocity heuristic.
As with Study 1, we test the association between a leader’s trust in
an employee and trust meta-accuracy by considering the compo-
nents of a presumed reciprocity heuristic—a positive relation
between a leader’s felt trust and a leader’s trust in an employee, a
positive relation between a leader’s trust in an employee and an
employee’s actual trust, and the indirect relationship between a
leader’s felt trust and an employee’s actual trust via the leader’s
trust in the employee.

Implications of Leader Trust Meta-Accuracy

Existing research on felt trust has, to date, largely focused on the
implications of employees feeling that they are trusted by their
managers. Studies have shown, for example, that employees per-
form at a higher level and engage in greater citizenship behavior
when they believe that management or their supervisors trust them
(Lau et al., 2014; Salamon & Robinson, 2008). Moreover, when
employees feel trusted by their supervisors, they are prone to
engage in knowledge sharing behavior toward their supervisor
(Nerstad et al., 2018) and incur personal costs to maintain felt trust
(Baer et al., 2015).

We build upon and extend these findings in three ways. First, in
contrast to existing research that has focused on employees’ feel-
ing trusted by leaders, we consider the implications of leaders
feeling trusted by employees. Felt trust should be important to
leaders, and as we describe below, the accuracy of their felt trust
may be particularly valuable. Second, whereas prior research on

the implications of felt trust has focused on individual-level out-
comes, we consider an important relational outcome—the degree
of relationship conflict between leaders and employees. Relation-
ship conflict, the presence of personal tension and incompatibility
between individuals, typically has a negative impact on individuals
by adversely impacting their well-being (Jehn & Bendersky,
2003), performance, and interpersonal relationships due to the
increase in hostility and tension (Janssen, Van de Vliert, & Veen-
stra, 1999; Peterson, 1999; Spector & Jex, 1998). As a result,
individuals spend more time and energy on each other (Jehn &
Mannix, 2001) instead of work tasks, which can lead to lower
decision quality (Simons & Peterson, 2000) and performance (de
Dreu & Weingart, 2003). Leaders are particularly vulnerable be-
cause they spend a significant amount of time managing personal
conflicts (de Dreu et al., 2004; Thomas, 1992). By decreasing
relationship conflict, the leader could improve the relationship
with their employees (Römer, Rispens, Giebels, & Euwema, 2012)
and with their work unit more broadly (Gelfand, Leslie, Keller, &
de Dreu, 2012). Third, we consider how the implications of felt
trust might depend on how accurately leaders understand the
degree to which an employee trusts them, given that theory and
research on interpersonal perception suggest that the working
relationship between two people might inherently depend on how
much it aligns with the other person’s belief (e.g., Carlson, 2016;
Elfenbein et al., 2009). Underlying this general prediction that
accuracy improves relational outcomes is the idea that when one
person accurately understands another person’s perspective, there
are fewer expectation violations between the two, resulting in
smoother interpersonal interactions (Heider, 1958; Malinowski,
1932). Conversely, when someone has an inaccurate understand-
ing of another person’s perspective, they may act on that inaccu-
rate understanding in ways that violate expectations and produce
frustrating interpersonal interactions.

Notwithstanding the intuitive appeal of this prediction that
greater meta-accuracy is beneficial within relationships, research
on trust meta-accuracy in teams suggests that it is important to
consider both meta-accuracy and the level of an employee’s actual
trust (Brion et al., 2015). To illustrate the importance of both,
consider two cases in which a leader’s felt trust accurately aligns
with an employee’s actual trust— one in which an employee’s
actual trust is high and a second in which an employee’s actual
trust is low. In the first case, if the employee has high trust for the
leader and the leader accurately perceives this trust, both parties
would behave in ways that correctly reflect a strong and positive
relationship, with open communication and support that should
yield benefits for the leader and the employee. In particular, the
leader will likely be more effective in understanding and fulfilling
the employee’s needs and expectations, leading to lower relation-
ship conflict. In the second case, if the employee has low trust for
the leader and the leader accurately perceives this low trust, the
result is likely quite different. When a leader accurately under-
stands that an employee does not trust her, both parties may behave
in ways that correctly substantiate a negative relationship, resulting
in guarded communication and decreased support. Whereas accu-
racy about a high level of employee trust is likely associated with
lower relationship conflict, accuracy about a low level of employee
trust is likely associated with higher relationship conflict.

1002 CAMPAGNA, DIRKS, KNIGHT, CROSSLEY, AND ROBINSON

Hypothesis 3: Dyadic leader trust meta-accuracy is negatively
related to relationship conflict when employee trust is high,
but positively related to relationship conflict when employee
trust is low.

In addition to considering aligned cases, in which leaders are
accurate in their felt trust perceptions, our arguments above sug-
gest that it is important to consider the directionality of potential
misalignment (Brion et al., 2015). That is, whether a leader over-
estimates or underestimates an employee’s trust may be conse-
quential for relationship conflict. When a leader overestimates an
employee’s trust, believing that the employee trusts him or her
more than the employee actually does, the leader may behave in
ways that the employee perceives as presumptuous and as over-
stepping the boundaries that the employee sees in their relation-
ship. For example, thinking that an employee trusts them at a high
level, a leader might ask the employee to disclose private or
sensitive information that the employee, who actually does not
trust the leader at a high level, is reticent to share. In contrast, when
a leader underestimates an employee’s trust, believing that the
employee trusts him or her less than the employee actually does,
the leader likely behaves with greater caution. Although this leader
might be reluctant to share information with the employee, the
employee would not be privy to the leader’s inaction. Whereas
overestimating trust likely results in errors of commission on the
part of the leader, underestimating trust likely results in errors of
omission on the part of the leader. Errors of commission, which are
evident to the employee, likely contribute to the kinds of frustrat-
ing interactions that engender relationship conflict with the leader
and the employee.

Hypothesis 4: A leader’s overestimation of an employee’s
trust produces increased relationship conflict compared to a
leader’s underestimation of an employee’s trust.

Method

Procedure and sample. We collected survey data at two
points in time, 6 weeks apart, from leaders and employees of a
not-for-profit caregiving organization based in the southeastern
United States. The organization provides a range of services (e.g.,
residential, vocational, and educational programs) for people with
mild to severe cognitive impairments. This setting complemented
the corrections department setting used in Study 1. The caregiving
organization was located in a different region of the United States,
involved a different type of work, and comprised a different set of
professional roles and norms regarding the leader– employee rela-
tionship. Nevertheless, accurately predicting trust was important
given the vulnerability and at times unpredictable nature of the
clients. For instance, one worker remarked about how an adult
client physically assaulted her and another employee stepped in to
help without hesitation.

The Time 1 survey for leaders, sent via work e-mails, assessed
demographic characteristics, social astuteness, and narcissism. The
Time 1 employee survey assessed demographic characteristics,
impression management, interaction frequency, and trust in the
leader. We received 108 leader responses (67% response rate) and
334 employee responses (72% response rate) to the Time 1 survey.

We distributed the Time 2 survey 6 weeks following the Time
1 survey. The Time 2 survey for leaders assessed their perceptions

of specific employees, including their felt trust with respect to each
employee, their trust in each employee, how frequently they in-
teracted with each employee, and their perception of relationship
conflict with each employee. To reduce survey fatigue, given that
leaders would have to complete several measures for each of their
employees, we randomly sampled up to five of a leader’s employ-
ees from the pool of completed responses to the Time 1 survey.
The Time 2 survey for employees assessed their perceptions of
relationship conflict with their leader. We received 91 leader
responses (56% response rate) and 280 employee responses (60%
response rate) to the Time 2 survey. We conducted our analyses on
142 matched leader– employee pairs (51 unique leaders) for which
we received a response from the leader at Times 1 and 2 and a
response from the employee at least at Time 1.3

Leaders were on average 26.30 years old (SD � 10.68) and had
worked at the nonprofit organization for 6.62 years (SD � 6.02) on
average. They were 85% female and ethnically diverse (46%
White, 32% Black or African American, 6% Hispanic). Employees
were on average 24.18 years old (SD � 13.38), 76% female, and
ethnically diverse (57% Black or African American, 20% White,
10% Hispanic).

Measures. Unless otherwise indicated below, participants re-
sponded to survey measures using a Likert-type scale ranging from
1 � strongly disagree to 7 � strongly agree. Interitem reliability
values for multiitem survey measures are included along the di-
agonal in Table 3.

Employee trust in the leader. We used the same three items in
Study 1, adapted from Kim et al. (2004) to assess employees’ trust
in their leader. Employees responded to the items at Time 1 using
a 5-point Likert-type scale (1 � strongly disagree to 5 � strongly
agree).

Leader felt trust. As with Study 1, at Time 2 leaders re-
sponded to the root items that we used to measure employee trust,
but adapted to target the leader’s perceptions of how much each of
their employees trust in them.

Leader trust meta-accuracy. As with Study 1, we used Ed-
wards’ (1995) multivariate approach to assess meta-accuracy. The
inputs into this procedure were again the absolute and algebraic
differences of leader felt trust minus employee trust, as well as
these individual components of the difference scores.

Employee impression management. At Time 1, employees
completed a six-item measure (Bolino, Varela, Bande, & Turnley,
2006), adapted to focus specifically on their behavior toward their
leader. Using a 7-point Likert scale (1 � never to 7 � always),
employees responded to items such as “How often do you do and
say things that make [leader name] believe you think highly of
him/her?”

Employee–leader interaction frequency. We adapted three
items from McAllister (1995). A sample item is “[Leader/em-
ployee name] and I interact often in the course of our work.”
Employees completed this measure at Time 1, while leaders com-
pleted this measure at Time 2. We included the interaction fre-
quency measure in the Time 2 leader survey, rather than at Time

3 We conducted a sensitivity power analysis using G�Power (Faul,
Erdfelder, Lang, & Buchner, 2007) with � � .80 and � � .05 (two-tailed)
with four predictors for a linear regression model. Our analysis revealed a
sample of 85 is needed to detect a small effect size of .15. With our current
sample size of 142, our expected effect size is .09.

1003LEADER TRUST META-ACCURACY

1 as we did with employees, simply because we needed the roster
of completed Time 1 surveys to populate the Time 2 leader survey.
There was high within-dyad agreement in leader and employee
ratings of interaction frequency (median rwg(j) � 0.92). We thus
operationalized employee–leader interaction frequency using the
mean of employee and leader ratings.

Leader social astuteness. At Time 1, leaders completed the
four-item social astuteness dimension of political skill from Ferris
et al.’s (2005) measure. A sample item is “I am particularly good
at sensing the motivations and hidden agendas of others.”

Leader narcissism. Leaders responded to Ames, Rose, and
Anderson’s (2006) 16-item measure of narcissism at Time 1.
Notwithstanding the large number of items, interitem reliability
analysis indicated that the measure had poor psychometric quali-
ties (� � .56). We thus used exploratory factor analysis to identify
a subset of items that (a) assessed the egocentric aspect of narcis-
sism and (b) had acceptable psychometric properties. This ap-
proach led us to create a five-item scale that captured a single
factor and had acceptable interitem reliability (� � .70). A sample
item is “Everybody likes to hear my stories.”

Leader trust in employee. We measured a leader’s trust in
each of his or her employees at Time 2 using a single item: “I trust
[employee name].” Leaders responded to this item using a 5-point
Likert-type scale ranging from 1 � strongly disagree to 5 �
strongly agree. We chose to use a single item for three reasons.
First, our goal in Study 2 was to conduct a conceptual replication
of our Study 1 findings regarding leader trust. Second, it was a
practical necessity to minimize the number of items that leaders
needed to respond to for each of their employees, particularly
given that we asked leaders to complete several multiitem scales
for each of their (up to five) employees in Study 2 (i.e., felt trust,
frequency of interaction, relationship conflict). Third, prior trust
research (e.g., Jones & Shah, 2016) suggests that single-item
measures can adequately capture elements of trust and serve as
useful measures in dyadic research. To ensure that our single-item
measure possessed favorable psychometric characteristics, we fol-
lowed the approach of prior researchers (e.g., Jones & Shah, 2016;
Joshi & Knight, 2015) and collected data from an online sample of
187 adults residing in the United States. We asked respondents to
think of a work relationship they held and respond to a set of

survey items that included (a) our single-item measure and (b) the
three-item measure of trust described above (e.g., Kim et al.,
2004). The results of a confirmatory factor analysis showed that a
single factor model fit the data well ( 22 � 0.74, p � .69; CFI �
1.00; RMSEA � 0.00, SRMR � 0.01). All four items had high
standardized loadings (i.e., all loadings �0.70) on the single latent
factor, supporting the validity of the single item that we used. The
correlation between the single item we used and the three-item
scale score used in Study 1 was 0.82 (p � .01).

Relationship conflict. At Time 2, both leaders and employees
completed items measuring relationship conflict (Jehn & Mannix,
2001). Employees responded to three items that asked about con-
flict with their leader (e.g., “How much tension is there between
you and [leader name]?”) and leaders responded to the same three
items asking about conflict with each of their employees (e.g.,
“How much tension is there between you and [employee name]?”).
Respondents used a 7-point Likert-type scale ranging from 1 �
never to 7 � always. There was high within-dyad agreement
between employees and leaders in their ratings of relationship
conflict (median rwg(j) � 0.97). Accordingly, we operationalized
relationship conflict using the mean of employee and leader rat-
ings.

Analyses. To test Hypotheses 1 and 2, which address the
antecedents of leader trust meta-accuracy, we followed the same
approach described above and used in Study 1. Hypotheses 3 and
4 consider dyadic leader trust meta-accuracy as a predictor of
relationship conflict. Using meta-accuracy as a predictor of leader
and employee outcomes presents a number of analytical chal-
lenges. Edwards and colleagues (Edwards, 1994, 1995, 2001;
Edwards & Parry, 1993) have described in depth the potential
problems and untested assumptions inherent in using difference
scores as predictors in regression models. To circumvent these
problems, we used polynomial regression and response surface
analysis (Barranti, Carlson, & Côté, 2017; Edwards & Parry,
1993). Whereas using a difference score requires making several
untested assumptions about how the alignment of two variables
(i.e., leader felt trust and employee trust) relates to a criterion
variable, polynomial regression models these assumptions in an
unconstrained way. Furthermore, polynomial regression and re-
sponse surface analysis enables examining how the relationship

Table 3
Study 2: Descriptive Statistics and Correlations

Variable name M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1. Same gender .69 .46
2. Same ethnicity .43 .50 .18
3. Employee–leader relationship tenure 1.67 2.81 �.01 .05
4. Employee impression management 2.99 1.34 �.01 .00 .27 (.78)
5. Employee–leader interaction frequency 5.69 .63 �.07 .06 �.05 �.10 (.82)
6. Leader social astuteness 5.44 1.05 .25 .16 .05 .41 �.11 (.88)
7. Leader narcissism 3.68 .94 .05 .05 �.02 �.05 .14 .02 (.70)
8. Employee trust in leader (ET) 5.81 1.43 .19 .32 .06 .31 .08 .38 .07 (.90)
9. Leader trust in employee 5.96 1.00 .20 �.03 �.09 .03 .12 .27 .05 .28

10. Leader felt trust (FT) 5.92 .91 .14 �.05 �.11 .03 .14 .19 .00 .29 .62 (.84)
11. Algebraic difference (FT � ET) .12 1.46 �.10 �.35 �.13 �.28 .02 �.25 �.06 �.80 .11 .34
12. Absolute difference (|FT � ET|) 1.05 1.02 �.17 �.16 �.07 �.23 �.06 �.16 �.09 �.61 �.21 �.25 .45
13. Relationship conflict 1.33 .56 �.19 �.05 .07 .04 �.06 �.20 .04 �.34 �.58 �.43 .07 .04 (.92)
14. Leader effectiveness 5.82 1.35 .19 .09 .09 .27 �.10 .28 �.08 .60 .36 .08 �.54 �.42 �.33 (.98)

Note. N � 142 employees nested within 51 leaders. FT � leader’s felt trust; ET � employee’s trust in leader. Cronbach’s alpha for is provided for
multi-item scales in parentheses along the diagonal. Denotations of statistical significance are excluded due to nested data structure.

1004 CAMPAGNA, DIRKS, KNIGHT, CROSSLEY, AND ROBINSON

between meta-accuracy and a given outcome might vary across
different levels of employee trust. A number of published articles
provide detailed tutorials of this method (e.g., Barranti et al.,
2017), which we describe in greater depth below when presenting
our results.

As in Study 1, we controlled in our analyses for the similarity of
employees and leaders with respect to gender and ethnicity, as well
as the tenure of the leader– employee relationship. We include
these control variables both in predicting leader trust meta-
accuracy and in using leader trust meta-accuracy to predict rela-
tionship conflict. The results of our hypothesis tests are the same
if control variables are excluded from our models.

Results

Table 3 presents the descriptive statistics for and intercorrela-
tions among Study 2 variables. In contrast to Study 1, there was a
very slight tendency for leaders to overestimate how much their
employees trusted them, as reflected in the positive mean value for
the algebraic difference of leader metaperception and employee
trust (M � 0.12, SD � 1.46). As with Study 1, however, this
tendency was slight—the median value was zero. Further, and as
with Study 1, we observed meaningful variance (SD � 1.46) in the
alignment between a leader’s felt trust and an employee’s actual
trust. Similar to our Study 1 findings, a leader’s felt trust and an
employee’s actual trust were positively related (r � .29).

Antecedents of trust meta-accuracy. Table 4 presents the
results of analyses that are parallel to those that we ran in Study 1
to test Hypotheses 1 and 2. Model 1 predicts the absolute differ-
ence score. Model 2 predicts the algebraic difference score, but
includes a dummy variable and interactions to separately model
relations for over- and underestimators. Model 3 provides the
results of a multivariate path analysis predicting the two compo-
nents of these different scores separately.

Replicating our Study 1 results, we again found no support for
Hypothesis 1 and the external pathway of leader trust meta-
accuracy. As Table 4 shows, there were no significant effects of
employee–leader interaction frequency (Hypothesis 1c), leader
social astuteness (Hypothesis 1d), or leader narcissism4 (Hypoth-
esis 1e) on meta-accuracy. Moreover, we observed an effect in-
consistent with what we predicted regarding employee impression
management, which we posited in Hypothesis 1f would be nega-
tively related to leader trust meta-accuracy and contribute to a
leader’s overestimation of the employee’s trust. The coefficients in
Table 4 show that employee impression management instead con-
tributed to a leader’s accuracy; impression management was neg-
atively related to the absolute difference of leader felt trust and
employee trust (B � �0.18, p � .02). Simple slopes analysis of
Model 2 showed that the relationship between employee impres-
sion management was significantly negative for overestimators
(B � �0.29, p � .04), but nonsignificant for underestimators (B �
0.07, p � .71). However, as Model 3 shows, this effect was driven
by a relationship between impression management and an employ-
ee’s actual trust (B � 0.29, p � .04), rather than by an association
with a leader’s felt trust, which is not what our theoretical devel-
opment would suggest.

Also replicating our Study 1 results, we found support for the
internal pathway and Hypothesis 2. In accordance with our find-
ings from Study 1, analysis of the significant interaction term in

Model 2 (B � 0.50, p � .01) indicated that the effect was driven
by overestimators (Model 2). Among overestimators, the relation-
ship between a leader’s trust in an employee and the algebraic
difference was positive (B � 0.28, p � .01). The relationship was
nonsignificant for overestimators (B � �0.22, p � .12). Model 3
shows, however, that a leader’s trust in an employee was signifi-
cantly and positively related to both components of this difference
score—to a leader’s felt trust (B � 0.38, p � .01) and to an
employee’s actual trust (B � 0.60, p � .01)—and that there was
no significant difference between under- and overestimators in
these relationships. We thus examined the path model implied by
a presumed reciprocity mechanism (Eisenkraft et al., 2017) with-
out these interaction terms and found that the indirect effect of the
relationship between a leader’s felt trust and an employee’s actual
trust through the leader’s trust in the employee was positive and
significant (B � 0.11, SE � 0.04, p � .01). This supports the idea
that a leader’s trust in an employee is positively related to meta-
accuracy because the presumption of a reciprocal relationship is
valid.

Consequences of trust meta-accuracy. Polynomial regres-
sion and response surface analysis enable researchers to under-
stand how the interplay of two variables (e.g., leader felt trust and
employee trust in a leader) relates to a third variable (e.g., rela-
tionship conflict). The parameters of a polynomial regression
equation, along with response surface plots, provide a means for
describing in a nuanced way how the congruence or incongruence
of two variables might relate to variance in the third. The equation
that we fit for relationship conflict, with the addition of control
variables, is as follows:

Y � bo � b1FT � b2ET � b3FT
2 � b4�FT � ET� � b5ET

2 � e

where Y is relational conflict, FT is a leader’s felt trust, and ET is
an employee’s actual trust in a leader.

To test Hypotheses 3 and 4, regarding the relationship between
under- and overestimation of leader trust meta-accuracy and rela-
tionship conflict, we followed the procedure outlined by Barranti
et al. (2017) for using polynomial regression and response surface
analysis. This entails first examining the overall significance of the
polynomial regression equation and second interpreting the com-
bination of parameters that describe the shape of the surface. The
first (a1 � b1
b2) is the slope of the line of congruence in the
response surface plot. This parameter indicates whether leader
trust meta-accuracy is related to an outcome differently at higher
or lower values of employee trust. Relevant for our hypotheses, a
negative value of a1 would mean that relationship conflict is higher
when a leader’s felt trust and an employee’s actual trust are aligned
at lower levels of employee trust than at higher levels of employee
trust. A positive value of a1 would mean that relationship conflict
is higher when a leader’s felt trust and an employee’s actual trust
are aligned at higher levels of employee trust than at lower levels
of employee trust.

The second parameter (a2 � b3
b4
b5) is the curvature of
the line of congruence. This parameter indicates whether leader

4 The 16-item measure of narcissism had low interim reliability (� �
0.56) and a multidimensional factor structure. Reflecting the decreased
power of using a measure with low reliability, our finding of a nonsignif-
icant relationship with trust meta-accuracy was the same when using the
16-item measure.

1005LEADER TRUST META-ACCURACY

trust meta-accuracy is related to an outcome differently at extreme
values compared with midrange values. A positive value of a2
would indicate, for example, that relationship conflict is higher
when a leader’s felt trust and an employee’s actual trust are aligned
at the extremes (i.e., either very low or very high employee trust)
than in the middle. A negative value of a2 would indicate that
relationship conflict is higher when a leader’s felt trust and an
employee’s actual trust are aligned in the middle than at the
extremes.

The third parameter (a3 � b1 � b2) is the slope along the line
of incongruence. This parameter indicates whether the outcome is
higher for underestimators or overestimators of an employee’s
actual trust. A positive value of a3 would indicate that relationship
conflict is higher when a leader overestimates than underestimates
an employee’s trust. A negative value of a3 would indicate that
relationship conflict is higher when a leader underestimates than
overestimates an employee’s trust.

The fourth parameter (a4 � b3 � b4
b5) is the curvature of the
line of incongruence. This parameter is used to determine whether
the outcome is related to accuracy, per se—that is, whether align-
ment of leader trust metaperceptions with an employee’s actual
trust relates to an outcome. A positive value of a4 would indicate
that relationship conflict is higher when a leader lacks meta-
accuracy; that is, when a leader’s felt trust is not aligned with an
employee’s actual trust. A negative value of a4 would indicate that
relationship conflict is higher when a leader is accurate; that is,
when a leader’s felt trust is aligned with an employee’s actual trust.

In addition to examining these individual parameters, response
surface plots enable discerning the overall shape of the relationship
between accuracy and an outcome variable.

Models 1 and 2 of Table 5, along with the response surface plot
depicted as Figure 1, present the results testing the relationship
between leader trust meta-accuracy and relationship conflict. Hy-
pothesis 3 predicted that leader trust meta-accuracy would be
negatively related to relationship conflict when employee trust is

Table 4
Study 2: Results of Regression Analyses Testing Predictors of Leader Trust Meta-Accuracy

Model 1 Model 2
Model 3: Multivariate path

analysis

DV � |FT � ET| DV � FT � ET DV � FT DV � ET
Parameter B SE B SE B SE B SE

Intercept 1.36 (.22) 2.17 (.38) 6.35 (.14) 4.18 (.37)
W �2.79 (.43) �.68 (.31) 2.11 (.43)
Same gender �.27 (.22) �.74 (.40)
�.39 (.16)� .35 (.45)
Same ethnicity �.29 (.17) �.80 (.25)�� .06 (.17) .86 (.30)��

Employee–leader relationship tenure .00 (.00) �.01 (.01) �.01 (.00) .00 (.00)
Employee impression management �.18 (.08)� �.29 (.14)� .00 (.07) .29 (.14)�

Employee–leader interaction frequency .04 (.13) .10 (.18) .12 (.10) .02 (.21)
Leader social astuteness �.08 (.17) .13 (.21) .19 (.09)� .06 (.22)
Leader narcissism �.08 (.10) �.19 (.14) �.02 (.08) .18 (.15)
Leader trust in employee �.19 (.10)� �.22 (.14) .38 (.11)�� .60 (.16)��

W � Same Gender .68 (.48) .68 (.28)� .00 (.49)
W � Same Ethnicity .70 (.30)� �.09(.25) �.79 (.36)�

W � Employee–Leader Relationship Tenure .01 (.01) .01 (.00) �.00 (.00)
W � Employee Impression Management .31 (.16)� .09 (.12) �.22 (.15)
W � Employee–Leader Interaction Frequency �.18 (.19) �.18 (.12) .01 (.20)
W � Leader Social Astuteness �.01 (.23) �.15 (.15) �.14 (.21)
W � Leader Narcissism .17 (.16) �.03 (.08) �.20 (.15)
W � Leader Trust in Employee .50 (.18)�� .21 (.12) �.29 (.20)
R2 .14 .70 .46 .67
F 2.28 .04 25.33��

Note. N � 142 employees nested within 51 leaders. Entries are unstandardized parameter estimates. All continuous predictors are grand mean centered.
DV � dependent variable; FT � leader’s felt trust; ET � employee’s trust in leader; W � dummy variable to indicate whether an observation represented
overestimation or underestimation. Specifically, W � 0 when FT � E and W � 1 when FT � E. Standard errors are cluster robust standard errors.
� p � .05. �� p � .01 two-tailed.

Table 5
Study 2: Results of Regression Analyses Predicting
Relationship Conflict

Model 1 Model 2

Parameter B SE B SE

Intercept 2.20 (.17)�� 2.32 (.19)��

Same gender �.21 (.09)�

Same ethnicity .05 (.09)
Employee–leader relationship tenure .00 (.00)
Leader felt trust (b1) �.21 (.14) �.19 (.13)
Employee trust in leader (b2) �.28 (.07)

�� .30 (.07)��

Leader felt trust2 (b3) �.07 (.04) �.08 (.04)
�

Leader felt Trust � Employee Trust
in Leader (b4) .13 (.04)

�� .15 (.04)��

Employee trust in leader2 (b5) �.03 (.02) �.03 (.02)
a1 � b1
b2 �.49 (.13)

�� .50 (.12)��

a2 � b3
b4
b5 .03 (.03) .04 (.03)
a3 � b1 � b2 .07 (.18) .11 (.17)
a4 � b3 � b4
b5 �.23 (.07)

�� .26 (.07)��

F 13.01�� 9.04��

R2 .32 .35

Note. N � 142 dyadic observations. Entries are unstandardized parameter
estimates, with cluster robust standard errors in parentheses.
� p � .05. �� p � .01 two-tailed.

1006 CAMPAGNA, DIRKS, KNIGHT, CROSSLEY, AND ROBINSON

high, but positively related to conflict when trust is low. As shown
in Model 2 of Table 5, Hypothesis 3 was partially supported. On
the one hand, the significant negative curvature of the line of
incongruence (a4 � �0.23, p � .001) indicated that relationship
conflict is higher when a leader’s felt trust accurately reflects an
employee’s actual trust—a result that runs counter to our expec-
tation that, in general, accuracy would be more beneficial than
inaccuracy. However, the significant negative slope of the line of
congruence (a1 � �0.50, p � .001) clarifies specifically why
accuracy resulted in higher relationship conflict. Specifically, and
in line with our expectations, there is higher relationship conflict
when a leader accurately perceives that an employee’s trust is low,
compared with when a leader accurately perceives that an employ-
ee’s trust is high. The highest levels of relationship conflict occur
when a leader is accurate about an employee’s low trust.

Hypothesis 4 predicted that, compared with underestimation,
overestimation would be positively related to relationship conflict.
Because the slope along the line of incongruence was not signif-
icant (a3 � 0.11, p � .50), Hypothesis 4 was not supported. The
amount of relationship conflict was similar between leaders who
overestimated and leaders who underestimated an employee’s ac-
tual trust.

Discussion

In Study 2 we sought to conceptually replicate and extend the
findings of Study 1. With respect to the antecedents of leader trust
meta-accuracy, we examined an expanded set of conceptually
similar characteristics that are implicated by the external pathway,
as well as again tested the presumed reciprocity mechanism im-
plicated by the internal pathway. Our findings largely corroborated
those of Study 1. We again did not find evidence in support of the
external perspective. Leader social astuteness, leader narcissism,

and the frequency of interactions between a leader and an em-
ployee were not related to leader trust meta-accuracy, and the role
of employee impression management behavior was the opposite of
our prediction. However, consistent with Study 1, we again found
support for an internal perspective. Specifically, our findings sug-
gested that to determine whether an employee trusts them, leaders
refer to their own feelings of trust toward the employee and use a
cognitive heuristic that trust relationships are reciprocal. Because
leader– employee trust relationships tend to be reciprocal in reality,
this heuristic yields an accurate metaperception.

We further extended Study 1 by considering how leader trust
meta-accuracy relates to an important aspect of the quality of a
leader– employee work relationship—the degree of relationship
conflict. Our findings also show the implications of leader trust
meta-accuracy; when leaders accurately detect that an employee
does not trust them, relationship conflict is higher. Contrary to our
predictions, we did not find that the leader’s overestimation of the
employee’s trust led to greater conflict, compared with when they
underestimated. By using response surface analysis, the findings of
Study 2 paint a nuanced picture of the interplay between leader
trust meta-accuracy and relationship conflict.

General Discussion

Research has begun exploring the idea that felt trust— how
much one person feels trusted by another— has important impli-
cations in organizations (Baer et al., 2015; Lau et al., 2014;
Salamon & Robinson, 2008). Felt trust relates to meaningful
individual outcomes, such as knowledge sharing (Nerstad et al.,
2018), task performance (Lau et al., 2014; Salamon & Robinson,
2008), and emotional exhaustion (Baer et al., 2015). Given these
findings, existing researchers have suggested that it is imperative
that trust be bestowed upon others and communicated effectively
to them. Underlying these recommendations, however, is the as-
sumption that one person’s felt trust is an accurate reflection of the
other person’s actual trust. Grounded in the more general literature
on interpersonal perception, our theoretical development and em-
pirical findings raise important questions about the validity of this
basic assumption and current thinking about the origins and effects
of felt trust in organizations.

Theoretical Implications

Our article makes several contributions to the trust literature.
Most importantly, our findings challenge two key assumptions in
the existing literature on felt trust. First, existing theory and
research on felt trust appears to have presumed that felt trust is
inherently aligned with a counterpart’s actual trust. Reflecting this
assumption, existing research on felt trust has examined the unitary
effects of felt trust on an individual’s affect and behavior without
considering the potential role of the actual trust held by a coun-
terpart. Our empirical findings clearly show that this apparent
presumption is untenable and misleading. Rather than observing a
uniform, one-to-one correspondence between a leader’s felt trust
and an employee’s actual trust, we observed substantial variance in
the degree of alignment in both studies—sometimes leaders were
accurate in understanding their employee’s actual trust and some-
times they were inaccurate. Our findings thus point to an important
concept for researchers studying felt trust—trust meta-accuracy.

-3

-2

-1
0

1
2

3
-3
-2
-1
0
1
2
3
1
2
3
4

Lead
er Fe

lt Tru
st

EmployeeTrust

R
el
at
io
ns
hi
p
C
on
fli
ct

Figure 1. Response surface plot depicting the implications of leader trust
meta-accuracy for relationship conflict. See the online article for the color
version of this figure.

1007LEADER TRUST META-ACCURACY

Trust meta-accuracy, which varies across dyads, reflects the de-
gree of alignment between one person’s felt trust and a counter-
part’s actual trust.

Second, and similar to the literature on how individuals seek to
determine whether someone is trustworthy (e.g., see Korsgaard,
Brodt, & Whitener, 2002; Lewicki & Bunker, 1995), the literature
on felt trust (Lau et al., 2007, 2014; Salamon & Robinson, 2008)
and conventional wisdom have to date presumed that individuals
are more likely to look for signals or cues gathered through direct
observation during interpersonal exchanges. We identified how
this thinking about the mechanism underlying felt trust is just one
of the explanations offered in the more general literature on
interpersonal perception to explain the origins of meta-accuracy. If
this external pathway to trust meta-accuracy were true, the vari-
ance in meta-accuracy that we observed would be explainable by
the nature of the social signaling process between a leader and his
or her employee. We examined several factors that would logically
enhance or impede a leader’s accurate reading of the signals of an
employee’s trust but found no evidence supportive of this external
pathway to meta-accuracy in either study. Instead, our findings
suggested that trust meta-accuracy emerges through a different
route—an internal pathway that theory and research on interper-
sonal perception suggest reliably shapes meta-accuracy for posi-
tive interpersonal relationships (e.g., Eisenkraft et al., 2017; Kenny
& DePaulo, 1993). Rather than turning outward, the internal path-
way suggests that individuals turn inward and rely on cognitive
heuristics when trying to make sense of what another person thinks
about their relationship. Consistent with this internal pathway, we
found that a leader’s trust meta-accuracy is a function of the
leader’s own trust for their employee. Because the cognitive rep-
resentation of trust is one of reciprocity (e.g., De Soto & Keuthe,
1960) and because trust relationships are generally reciprocal in
reality (Bacharach et al., 2007; Kenny, 1994; Kenny & Nasby,
1980; Pillutla et al., 2003), presuming reciprocity can yield meta-
accuracy. Our consistent findings across two studies raise impor-
tant questions about the validity of existing thinking in the litera-
ture on trust regarding the origins of felt trust.

Our findings also extend existing research on the implications of
felt trust within organizations. A prevailing assumption in the
literature on leader development—reflected in organizational pro-
grams and practices—is that leaders are best equipped to grow and
improve when they understand others’ idiosyncratic views of
them. One of the reasons for this is that they are able to more
effectively manage relationships with each employee, which is
critical in gaining employee support, increasing coordination, and
ultimately performance, for both parties. The most readily avail-
able indicator or symptom of understanding how others view them
is the degree of animosity, or relationship conflict, present within
the dyad. Relationship conflict can lower performance (de Dreu &
Weingart, 2003) due to the increased tension between the parties
(Spector & Jex, 1998) which distracts them from their work goals
(Jehn & Mannix, 2001). Consistent with this line of thinking, we
found that relationship conflict was low when the leader’s felt trust
and employee’s trust perceptions were positive and aligned, dem-
onstrating that the leader accurately detected that the employee
trusted him or her. Inversely, conflict was highest when the lead-
er’s felt trust and employee’s trust were negative and aligned, or
when they were accurate about the employee’s low trust. These
findings reflect that the magnitude of the difference between the

leader’s felt trust and the employee’s trust had more influence on
relationship conflict than the directional differences, or when the
leader’s felt trust was higher (i.e., overestimated) or lower (i.e.,
underestimated) than the employee’s trust.

Finally, this article has important implications for leaders and
trust. To date, existing empirical research on felt trust has focused
primarily on employees feeling trusted by their supervisors or by
management (e.g., Baer et al., 2015; Lau et al., 2014; Nerstad et
al., 2018). But, research has long underscored that being trusted is
a central concern for leaders (Dirks & Ferrin, 2002). Unfortu-
nately, little knowledge exists about leader felt trust, the factors
that might shape it, or whether leaders’ perceptions are even
accurate. In fact, to our knowledge, there are only a few relevant
articles that have provide some insight into the topic (e.g., Brower,
Lester, Korsgaard, & Dineen, 2009; Lau & Lam, 2008). Never-
theless, given the need to rely on their employees, and the impli-
cations for when they cannot, trust meta-accuracy may be partic-
ularly important for leaders. Academic and popular press articles
have underscored that it is important for leaders to accurately
know how their employees perceive—and relate to them— on key
factors (Day, Fleenor, Atwater, Sturm, & McKee, 2014). The
present study informs not only the trust literature, but also the
leadership literature, by focusing on the processes by which lead-
ers achieve accuracy, and the pathway which may mislead them
when determining how others view them.

Practical Implications

One of the practical insights raised by our results is how leader
trust meta-accuracy might be improved. As suggested above, one
reason why the external pathway may not yield accuracy is that
there are two components of this process that are vulnerable to bias
and distortion—the employee sending signals of trust, and the
leader interpreting signals of trust. Conceptually, a structured
process may help to increase the fidelity of the signals relative to
the sources of noise. For example, 360-degree feedback is a
structured process that addresses both parts of this model by (a)
providing a mechanism for employees’ feedback to a leader and
(b) delivering accumulated feedback to leaders in a structured way.
However, with respect to dyadic meta-accuracy, common 360-
degree feedback processes may not be suitable, because leaders
receive anonymous and aggregate feedback. In the absence of
information about the variance of raters’ views, the 360-degree
process primarily informs a leader’s generalized or collective felt
trust (i.e., the sense of how colleagues, in general, view him or
her).

The practical implications for increasing leaders’ meta-accuracy
through the internal pathway are less clear. Enhancing accuracy
through this model would require increasing leaders’ insight into
the reciprocity of trust in a given relationship. Some scholars (e.g.,
Brion et al., 2015) have suggested that mindfulness practices could
help enhance accuracy when individuals look inward to understand
how others perceive them. Research is needed, however, to pro-
vide evidence for the practical value of such practices.

In addition, to the extent that they recognize potential employee
tensions or lack of helpfulness, leaders may benefit from consid-
ering the possibility that there is a misalignment between how they
think they are judged, and how their employees actually view
them. In our study, we found that leaders who accurately assessed

1008 CAMPAGNA, DIRKS, KNIGHT, CROSSLEY, AND ROBINSON

an employee’s trust benefited by having a better relationship with
lower conflict. The presence of low relationship conflict can affect
both parties by increasing their well-being (Jehn & Bendersky,
2003), decision quality (Simons & Peterson, 2000), and perfor-
mance (de Dreu & Weingart, 2003). Monthly or bimonthly one-
on-one goal-setting or developmental sessions with their employ-
ees, which include an emphasis on how the employee also views
the leader to be performing, may help to increase a leader’s
accuracy. The regular, open exchange of information could be a
precursor to trust, and perhaps also an effective mechanism for
leaders to fine-tune their metaperceptions.

Limitations and Future Directions

One key advantage of our empirical approach was our investi-
gation of trust meta-accuracy in meaningful work relationships
among leaders from two separate organizations. The disadvantage
of our examination of ongoing relationships, however, is the
inability to make claims about the causal flow among leader felt
trust, employee trust, and various predictor variables. Although our
theoretical foundation suggests one causal direction, it is likely that
the interplay of these variables is complex with a number of
feedback loops. For example, the process implicated by the inter-
nal pathway may begin with a leader trusting an employee, the
employee returning the trust, and then the leader fine-tuning his or
her felt trust perceptions. This is largely consistent with research
showing that trust for a counterpart creates an upward spiral of
reciprocated trust and cooperation. This reciprocity cycle could be
due to the continuous exchange of positive behaviors reinforcing
that trust exists. Or, perhaps reciprocity is due to a trust respon-
siveness effect, in which a person who feels trusted is more likely
to also trust their counterpart (Bacharach et al., 2007). In either
case, this may then further reinforce the leader’s trust in the
employee, the leader’s felt trust, and so on. Thus, research is
needed to more precisely understand how the reciprocity-based
mechanism operates with respect to meta-accuracy. Disentangling
these dynamics of mutual influence requires not only laboratory
experiments that isolate and manipulate these variables, but more
importantly, longitudinal studies that assess meta-accuracy at the
start of a relationship and model change in trust, metaperceptions,
and behavior over time. Alternatively, computational modeling
may provide a useful way for future research to disentangle the
feedback loops that are almost certainly a part of this process
(Vancouver & Weinhardt, 2012).

A second potential limitation and direction for future research
involves the direct assessment of the behavioral markers impli-
cated by the external pathway. Accuracy for the external pathway
is based on (a) the employee engaging in observable behaviors
which are more or less a true representation of their actual trust in
the leader, and (b) the leader being able to correctly interpret the
underlying meaning of the employee’s behavior. We chose to
focus on attributes and characteristics of leaders and employees
that would impact the fidelity of the employee’s behavioral signals
or the ability of the leader to interpret the employee’s behavior. A
different approach—which would remain consistent with the the-
oretical logic of the external pathway—would be to focus directly
on behavioral acts that reveal trust and on the leader’s attempts to
assess those acts. For example, Gillespie (2003) suggested that
there are two forms of trusting behavior—reliance (e.g., allowing

a leader to have control over one’s career) and disclosure (e.g.,
sharing sensitive or incriminating information with the leader).
Research could measure the extent to which employees display
these types of behaviors and whether leaders correctly perceive
them. This more direct approach would be feasible in a research
context in which researchers could clearly identify and measure—
or, perhaps, control—the display of specific behaviors believed to
indicate trust.

Future research could examine the nature of other types of
workplace relationships. We focused on leader– employee rela-
tionships because of the critical role of trust in those relationships.
Meta-accuracy is also particularly interesting in the leader-
employee relationship because the power difference may increase
the likelihood of inaccurate metaperception. Meta-accuracy is also,
however, likely to be relevant for other types of relationships
frequently studied in the trust literature. For example, interpersonal
trust is an important factor in relationships between teammates (De
Jong, Dirks, & Gillespie, 2016), in negotiations (Kong, Dirks, &
Ferrin, 2014), and in interorganizational relationships (Zaheer,
McEvily, & Perrone, 1998). The framework provided in this article
can be extended to each of these contexts. Theory and research are
needed to determine whether the mechanisms that underlie trust
meta-accuracy are consistent across contexts with varied power
dynamics. The implications of accurate trust perceptions may also
vary across contexts. For example, in a negotiation setting it may
be particularly problematic to overestimate that one is trusted,
whereas an accurate perception of not being trusted may enable
more realistic, if not optimal, outcomes.

Conclusion

Understanding the factors that affect leaders’ ability to achieve
trust meta-accuracy can help reduce relationship conflict. Our
results suggest that leader trust meta-accuracy is shaped by an
internal mechanism based on the presumed reciprocity of trust
relationships. Whether meta-accuracy is associated with relation-
ship conflict depends upon how much an employee trusts the
leader and whether the leader accurately estimates the employee’s
trust. Our study highlights this intriguing, yet thus far overlooked,
angle on leadership and trust, and we hope encourages future
research on this issue.

References

Ames, D. R., Rose, P., & Anderson, C. P. (2006). The NPI-16 as a short
measure of narcissism. Journal of Research in Personality, 40, 440 –
450. http://dx.doi.org/10.1016/j.jrp.2005.03.002

Aronson, E., Carlsmith, J. M., Ellsworth, P. C., & Gonzales, M. (1990).
Methods of research in social psychology (2nd ed.). New York, NY:
McGraw-Hill.

Bacharach, M., Guerra, G., & Zizzo, D. J. (2007). The self-fulfilling
property of trust: An experimental study. Theory and Decision, 63,
349 –388. http://dx.doi.org/10.1007/s11238-007-9043-5

Baer, M. D., Dhensa-Kahlon, R. K., Colquitt, J. A., Rodell, J. B., Outlaw,
R., & Long, D. M. (2015). Uneasy lies the head that bears the trust: The
effects of feeling trusted on emotional exhaustion. Academy of Manage-
ment Journal, 58, 1637–1657. http://dx.doi.org/10.5465/amj.2014.0246

Bargh, J. A., & Chartrand, T. L. (1999). The unbearable automaticity of
being. American Psychologist, 54, 462– 479. http://dx.doi.org/10.1037/
0003-066X.54.7.462

1009LEADER TRUST META-ACCURACY

http://dx.doi.org/10.1016/j.jrp.2005.03.002

http://dx.doi.org/10.1007/s11238-007-9043-5

http://dx.doi.org/10.5465/amj.2014.0246

http://dx.doi.org/10.1037/0003-066X.54.7.462

Barranti, M., Carlson, E. N., & Côté, S. (2017). How to test questions about
similarity in personality and social psychology research: Description and
empirical demonstration of response surface analysis. Social Psycholog-
ical & Personality Science, 8, 465– 475. http://dx.doi.org/10.1177/
1948550617698204

Bolino, M. C. (1999). Citizenship and impression management: Good
soldiers or good actors. Academy of Management Review, 24, 82–98.
http://dx.doi.org/10.5465/amr.1999.1580442

Bolino, M. C., Varela, J. A., Bande, B., & Turnley, W. H. (2006). The
impact of impression-management tactics on supervisor ratings of orga-
nizational citizenship behavior. Journal of Organizational Behavior, 27,
281–297. http://dx.doi.org/10.1002/job.379

Brion, S., Lount, R. B., Jr., & Doyle, S. P. (2015). Knowing if you are
trusted: Does meta-accuracy promote trust development? Social Psycho-
logical & Personality Science, 6, 823– 830. http://dx.doi.org/10.1177/
1948550615590200

Brower, H. H., Lester, S. W., Korsgaard, M. A., & Dineen, B. R. (2009).
A closer look at trust between managers and subordinates: Understand-
ing the effects of both trusting and being trusted on subordinate out-
comes. Journal of Management, 35, 327–347. http://dx.doi.org/10.1177/
0149206307312511

Burnstein, E. (1967). Sources of cognitive bias in the representation of
simple social structures: Balance, minimal change, positivity, reciproc-
ity, and the respondent’s own attitude. Journal of Personality and Social
Psychology, 7, 36 – 48. http://dx.doi.org/10.1037/h0024926

Cable, D. M., Aiman-Smith, L., Mulvey, P. W., & Edwards, J. R. (2000).
The sources and accuracy of job applicants’ beliefs about organizational
culture. Academy of Management Journal, 43, 1076 –1085.

Cable, D. M., & Yu, K. Y. T. (2006). Managing job seekers’ organizational
image beliefs: The role of media richness and media credibility. Journal
of Applied Psychology, 91, 828 – 840.

Caldwell, D. F., & O’Reilly, C. A., III. (1982). Responses to failure: The
effects of choice and responsibility on impression management. Acad-
emy of Management Journal, 25, 121–136.

Campagna, R. L., Mislin, A. A., & Bottom, W. P. (2019). Motivated by
guilt and low felt trust: The impact of negotiators’ anger expressions on
the implementation of negotiated agreements. Journal of Behavioral
Decision Making, 32, 450 – 470.

Carlson, E. N. (2016). Meta-accuracy and relationship quality: Weighing
the costs and benefits of knowing what people really think about you.
Journal of Personality and Social Psychology, 111, 250 –264. http://dx
.doi.org/10.1037/pspp0000107

Carlson, E. N., & Kenny, D. A. (2012). Meta-accuracy: Do we know how
others see us? In S. Vazire & T. D. Wilson (Eds.), Handbook of
self-knowledge (pp. 242–257). New York, NY: The Guilford Press.

Carlson, K. D., & Wu, J. (2012). The illusion of statistical control: Control
variable practice in management research. Organizational Research
Methods, 15, 413– 435. http://dx.doi.org/10.1177/1094428111428817

Colquitt, J. A., Scott, B. A., & LePine, J. A. (2007). Trust, trustworthiness,
and trust propensity: A meta-analytic test of their unique relationships
with risk taking and job performance. Journal of Applied Psychology,
92, 909 –927. http://dx.doi.org/10.1037/0021-9010.92.4.909

Davis, M. H. (1983). Measuring individual differences in empathy: Evidence
for a multidimensional approach. Journal of Personality and Social Psy-
chology, 44, 113–126. http://dx.doi.org/10.1037/0022-3514.44.1.113

Day, D., Fleenor, J., Atwater, L., Sturm, R., & McKee, R. (2014). Ad-
vances in leader and leadership development: A review of 25 years of
research and theory. The Leadership Quarterly, 25, 63– 82. http://dx.doi
.org/10.1016/j.leaqua.2013.11.004

de Dreu, C. K., Van Dierendonck, D., & Dijkstra, M. T. (2004). Conflict
at work and individual well-being. International Journal of Conflict
Management, 15, 6 –26. http://dx.doi.org/10.1108/eb022905

de Dreu, C. K., & Weingart, L. R. (2003). Task versus relationship conflict:
A meta-analysis. Journal of Applied Psychology, 88, 741–749. http://dx
.doi.org/10.1037/0021-9010.88.4.741

De Jong, B. A., Dirks, K. T., & Gillespie, N. (2016). Trust and team
performance: A meta-analysis of main effects, moderators, and covari-
ates. Journal of Applied Psychology, 101, 1134 –1150. http://dx.doi.org/
10.1037/apl0000110

DePaulo, B. M., Kenny, D. A., Hoover, C. W., Webb, W., & Oliver, P. V.
(1987). Accuracy of person perception: Do people know what kinds of
impressions they convey? Journal of Personality and Social Psychology,
52, 303–315. http://dx.doi.org/10.1037/0022-3514.52.2.303

De Soto, C. B. (1960). Learning a social structure. Journal of Abnormal and
Social Psychology, 60, 417– 421. http://dx.doi.org/10.1037/h0047511

De Soto, C. B., & Kuethe, J. L. (1958). Perception of mathematical
properties of interpersonal relations. Perceptual and Motor Skills, 8,
279 –286. http://dx.doi.org/10.2466/pms.1958.8.3.279

De Soto, C. B., & Kuethe, J. L. (1959). Subjective probabilities of inter-
personal relationships. Journal of Abnormal and Social Psychology, 59,
290 –294. http://dx.doi.org/10.1037/h0045430

De Soto, C. B., & Kuethe, J. L. (1960). On the relation between two
variables. Educational and Psychological Measurement, 20, 743–749.

Dirks, K. T., & Ferrin, D. L. (2002). Trust in leadership: Meta-analytic
findings and implications for research and practice. Journal of Applied
Psychology, 87, 611– 628. http://dx.doi.org/10.1037/0021-9010.87.4.611

Edwards, J. R. (1994). The study of congruence in organizational behavior
research: Critique and a proposed alternative. Organizational Behavior
and Human Decision Processes, 58, 51–100. http://dx.doi.org/10.1006/
obhd.1994.1029

Edwards, J. R. (1995). Alternatives to difference scores as dependent
variables in the study of congruence in organizational research. Orga-
nizational Behavior and Human Decision Processes, 64, 307–324.
http://dx.doi.org/10.1006/obhd.1995.1108

Edwards, J. R. (2001). Ten difference score myths. Organizational Re-
search Methods, 4, 265–287. http://dx.doi.org/10.1177/1094428101
43005

Edwards, J. R., & Parry, M. E. (1993). On the use of polynomial regression
equations as an alternative to difference scores in organizational re-
search. Academy of Management Journal, 36, 1577–1613.

Eisenkraft, N., Elfenbein, H. A., & Kopelman, S. (2017). We know who
likes us, but not who competes against us: Dyadic meta-accuracy among
work colleagues. Psychological Science, 28, 233–241. http://dx.doi.org/
10.1177/0956797616679440

Elfenbein, H. A., & Ambady, N. (2002). On the universality and cultural
specificity of emotion recognition: A meta-analysis. Psychological Bul-
letin, 128, 203–235. http://dx.doi.org/10.1037/0033-2909.128.2.203

Elfenbein, H. A., Eisenkraft, N., & Ding, W. W. (2009). Do we know who
values us? Dyadic meta-accuracy in the perception of professional
relationships. Psychological Science, 20, 1081–1083. http://dx.doi.org/
10.1111/j.1467-9280.2009.02396.x

Farwell, L., & Wohlwend-Lloyd, R. (1998). Narcissistic processes: Opti-
mistic expectations, favorable self-evaluations, and self-enhancing attri-
butions. Journal of Personality, 66, 65– 83. http://dx.doi.org/10.1111/
1467-6494.00003

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G�Power 3: A
flexible statistical power analysis program for the social, behavioral, and
biomedical sciences. Behavior Research Methods, 39, 175–191. http://
dx.doi.org/10.3758/BF03193146

Ferris, G. R., Treadway, D. C., Kolodinsky, R. W., Hochwarter, W. A.,
Kacmar, C. J., Douglas, C., & Frink, D. D. (2005). Development and
validation of the political skill inventory. Journal of Management, 31,
126 –152. http://dx.doi.org/10.1177/0149206304271386

Ferris, G. R., Treadway, D. C., Perrewe, P. L., Brouer, R. L., Douglas, C.,
& Lux, S. (2007). Political skill in organizations. Journal of Manage-
ment, 33, 290 –320. http://dx.doi.org/10.1177/0149206307300813

1010 CAMPAGNA, DIRKS, KNIGHT, CROSSLEY, AND ROBINSON

http://dx.doi.org/10.1177/1948550617698204

http://dx.doi.org/10.5465/amr.1999.1580442

http://dx.doi.org/10.1002/job.379

http://dx.doi.org/10.1177/1948550615590200

http://dx.doi.org/10.1177/0149206307312511

http://dx.doi.org/10.1037/h0024926

http://dx.doi.org/10.1037/pspp0000107

http://dx.doi.org/10.1177/1094428111428817

http://dx.doi.org/10.1037/0021-9010.92.4.909

http://dx.doi.org/10.1037/0022-3514.44.1.113

http://dx.doi.org/10.1016/j.leaqua.2013.11.004

http://dx.doi.org/10.1108/eb022905

http://dx.doi.org/10.1037/0021-9010.88.4.741

http://dx.doi.org/10.1037/apl0000110

http://dx.doi.org/10.1037/0022-3514.52.2.303

http://dx.doi.org/10.1037/h0047511

http://dx.doi.org/10.2466/pms.1958.8.3.279

http://dx.doi.org/10.1037/h0045430

http://dx.doi.org/10.1037/0021-9010.87.4.611

http://dx.doi.org/10.1006/obhd.1994.1029

http://dx.doi.org/10.1006/obhd.1995.1108

http://dx.doi.org/10.1177/109442810143005

http://dx.doi.org/10.1177/0956797616679440

http://dx.doi.org/10.1037/0033-2909.128.2.203

http://dx.doi.org/10.1111/j.1467-9280.2009.02396.x

http://dx.doi.org/10.1111/1467-6494.00003

http://dx.doi.org/10.3758/BF03193146

http://dx.doi.org/10.1177/0149206304271386

http://dx.doi.org/10.1177/0149206307300813

Freeman, L. C. (1992). Filling in the blanks: A theory of cognitive
categories and the structure of social affiliation. Social Psychology
Quarterly, 55, 118 –127. http://dx.doi.org/10.2307/2786941

Funder, D. C. (1987). Errors and mistakes: Evaluating the accuracy of
social judgment. Psychological Bulletin, 101, 75–90. http://dx.doi.org/
10.1037/0033-2909.101.1.75

Gabriel, M. T., Critelli, J. W., & Ee, J. S. (1994). Narcissistic illusions in
self-evaluations of intelligence and attractiveness. Journal of Personal-
ity, 62, 143–155. http://dx.doi.org/10.1111/j.1467-6494.1994.tb00798.x

Gelfand, M. J., Leslie, L. M., Keller, K., & de Dreu, C. (2012). Conflict
cultures in organizations: How leaders shape conflict cultures and their
organizational-level consequences. Journal of Applied Psychology, 97,
1131–1147. http://dx.doi.org/10.1037/a0029993

George, B. (2016). The truth about authentic leaders. Boston, MA: Har-
vard Business School Working Knowledge. https://hbswk.hbs.edu/item/
the-truth-about-authentic-leaders

Gillespie, N. (2003, August). Measuring trust in working relationships:
The behavioural trust inventory. Paper presented at the Academy of
Management meeting, Seattle, WA.

Heider, F. (1958). The psychology of interpersonal relations. New York,
NY: Wiley. http://dx.doi.org/10.1037/10628-000

Janssen, O., Van de Vliert, E., & Veenstra, C. (1999). How task and person
conflict shape the role of positive interdependence in management
teams. Journal of Management, 25, 117–141. http://dx.doi.org/10.1177/
014920639902500201

Jehn, K. A., & Bendersky, C. (2003). Intragroup conflict in organizations:
A contingency perspective on the conflict-outcome relationship. Re-
search in Organizational Behavior, 25, 187–242. http://dx.doi.org/10
.1016/S0191-3085(03)25005-X

Jehn, K. A., & Mannix, E. A. (2001). The dynamic nature of conflict: A
longitudinal study of intragroup conflict and group performance. Acad-
emy of Management Journal, 44, 238 –251.

John, O. P., & Robins, R. W. (1994). Accuracy and bias in self-perception:
Individual differences in self-enhancement and the role of narcissism.
Journal of Personality and Social Psychology, 66, 206 –219. http://dx
.doi.org/10.1037/0022-3514.66.1.206

Jones, S. L., & Shah, P. P. (2016). Diagnosing the locus of trust: A
temporal perspective for trustor, trustee, and dyadic influences on per-
ceived trustworthiness. Journal of Applied Psychology, 101, 392– 414.
http://dx.doi.org/10.1037/apl0000041

Joshi, A., & Knight, A. P. (2015). Who defers to whom and why? Dual
pathways linking demographic differences and dyadic deference to team
effectiveness. Academy of Management Journal, 58, 59 – 84. http://dx
.doi.org/10.5465/amj.2013.0718

Kenny, D. A. (1994). Interpersonal perception: A social relations analysis.
New York, NY: Guilford Press.

Kenny, D. A., & Albright, L. (1987). Accuracy in interpersonal perception:
A social relations analysis. Psychological Bulletin, 102, 390 – 402. http://
dx.doi.org/10.1037/0033-2909.102.3.390

Kenny, D. A., Bond, C. F., Jr., Mohr, C. D., & Horn, E. M. (1996). Do we
know how much people like one another? Journal of Personality and
Social Psychology, 71, 928 –936. http://dx.doi.org/10.1037/0022-3514
.71.5.928

Kenny, D. A., & DePaulo, B. M. (1993). Do people know how others view
them? An empirical and theoretical account. Psychological Bulletin,
114, 145–161. http://dx.doi.org/10.1037/0033-2909.114.1.145

Kenny, D. A., & Nasby, W. (1980). Splitting the reciprocity correlation.
Journal of Personality and Social Psychology, 38, 249 –256. http://dx
.doi.org/10.1037/0022-3514.38.2.249

Kilduff, M., & Day, D. V. (1994). Do chameleons get ahead? The effects
of self-monitoring on managerial careers. Academy of Management
Journal, 37, 1047–1060.

Kim, P. H., Ferrin, D. L., Cooper, C. D., & Dirks, K. T. (2004). Removing
the shadow of suspicion: The effects of apology versus denial for

repairing competence- versus integrity-based trust violations. Journal of
Applied Psychology, 89, 104 –118. http://dx.doi.org/10.1037/0021-9010
.89.1.104

Kong, D. T., Dirks, K. T., & Ferrin, D. L. (2014). Interpersonal trust within
negotiations: Meta-analytic evidence, critical contingencies, and direc-
tions for future research. Academy of Management Journal, 57, 1235–
1255. http://dx.doi.org/10.5465/amj.2012.0461

Korsgaard, M. A., Brodt, S. E., & Whitener, E. M. (2002). Trust in the face
of conflict: The role of managerial trustworthy behavior and organiza-
tional context. Journal of Applied Psychology, 87, 312–319. http://dx
.doi.org/10.1037/0021-9010.87.2.312

Lau, D. C., & Lam, L. W. (2008). Effects of trusting and being trusted on team
citizenship behaviours in chain stores. Asian Journal of Social Psychology,
11, 141–149. http://dx.doi.org/10.1111/j.1467-839X.2008.00251.x

Lau, D. C., Lam, L. W., & Wen, S. S. (2014). Examining the effects of
feeling trusted by supervisors in the workplace: A self-evaluative per-
spective. Journal of Organizational Behavior, 35, 112–127. http://dx.doi
.org/10.1002/job.1861

Lau, D. C., Liu, J., & Fu, P. P. (2007). Feeling trusted by business leaders
in China: Antecedents and the mediating role of value congruence. Asia
Pacific Journal of Management, 24, 321–340. http://dx.doi.org/10.1007/
s10490-006-9026-z

Lennox, R. D., & Wolfe, R. N. (1984). Revision of the self-monitoring
scale. Journal of Personality and Social Psychology, 46, 1349 –1364.
http://dx.doi.org/10.1037/0022-3514.46.6.1349

Lewicki, R. J., & Bunker, B. B. (1995). Trust in relationships. Adminis-
trative Science Quarterly, 5, 583– 601.

Lewicki, R. J., & Bunker, B. B. (1996). Developing and maintaining trust
in work relationships. In R. Kramer & T. Tyler (Eds.), Trust in organi-
zations (pp. 114 –139). Thousand Oaks, CA: Sage.

Lewicki, R. J., Tomlinson, E. C., & Gillespie, N. (2006). Models of
interpersonal trust development: Theoretical approaches, empirical evi-
dence, and future directions. Journal of Management, 32, 991–1022.
http://dx.doi.org/10.1177/0149206306294405

Lynch, J. G., Jr., Bradlow, E. T., Huber, J. C., & Lehmann, D. R. (2015).
Reflections on the replication corner: In praise of conceptual replica-
tions. International Journal of Research in Marketing, 32, 333–342.
http://dx.doi.org/10.1016/j.ijresmar.2015.09.006

Malinowski, B. (1932). Crime and custom in savage society. New York,
NY: Harcourt, Brace.

Mayer, R. C., & Davis, J. H. (1999). The effect of the performance
appraisal system on trust for management: A field quasi-experiment.
Journal of Applied Psychology, 84, 123–136. http://dx.doi.org/10.1037/
0021-9010.84.1.123

Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative
model of organizational trust. Academy of Management Review, 20,
709 –734. http://dx.doi.org/10.5465/amr.1995.9508080335

McAllister, D. J. (1995). Affect- and cognition-based trust as foundations
for interpersonal cooperation in organizations. Academy of Management
Journal, 38, 24 –59.

McKee, R. A., Lee, Y., Atwater, L., & Antonakis, J. (2018). Effects of
personality and gender on self-other agreement in ratings of leadership.
Journal of Occupational and Organizational Psychology, 91, 285–315.
http://dx.doi.org/10.1111/joop.12209

McNeish, D., Stapleton, L. M., & Silverman, R. D. (2017). On the
unnecessary ubiquity of hierarchical linear modeling. Psychological
Methods, 22, 114 –140. http://dx.doi.org/10.1037/met0000078

Nerstad, C. G., Searle, R., Černe, M., Dysvik, A., Škerlavaj, M., & Scherer,
R. (2018). Perceived mastery climate, felt trust, and knowledge sharing.
Journal of Organizational Behavior, 39, 429 – 447. http://dx.doi.org/10
.1002/job.2241

Parker, S. K., & Axtell, C. M. (2001). Seeing another viewpoint: Ante-
cedents and outcomes of employee perspective taking. Academy of
Management Journal, 44, 1085–1100.

1011LEADER TRUST META-ACCURACY

http://dx.doi.org/10.2307/2786941

http://dx.doi.org/10.1037/0033-2909.101.1.75

http://dx.doi.org/10.1111/j.1467-6494.1994.tb00798.x

http://dx.doi.org/10.1037/a0029993

https://hbswk.hbs.edu/item/the-truth-about-authentic-leaders

http://dx.doi.org/10.1037/10628-000

http://dx.doi.org/10.1177/014920639902500201

http://dx.doi.org/10.1016/S0191-3085%2803%2925005-X

http://dx.doi.org/10.1037/0022-3514.66.1.206

http://dx.doi.org/10.1037/apl0000041

http://dx.doi.org/10.5465/amj.2013.0718

http://dx.doi.org/10.1037/0033-2909.102.3.390

http://dx.doi.org/10.1037/0022-3514.71.5.928

http://dx.doi.org/10.1037/0033-2909.114.1.145

http://dx.doi.org/10.1037/0022-3514.38.2.249

http://dx.doi.org/10.1037/0021-9010.89.1.104

http://dx.doi.org/10.5465/amj.2012.0461

http://dx.doi.org/10.1037/0021-9010.87.2.312

http://dx.doi.org/10.1111/j.1467-839X.2008.00251.x

http://dx.doi.org/10.1002/job.1861

http://dx.doi.org/10.1007/s10490-006-9026-z

http://dx.doi.org/10.1037/0022-3514.46.6.1349

http://dx.doi.org/10.1177/0149206306294405

http://dx.doi.org/10.1016/j.ijresmar.2015.09.006

http://dx.doi.org/10.1037/0021-9010.84.1.123

http://dx.doi.org/10.5465/amr.1995.9508080335

http://dx.doi.org/10.1111/joop.12209

http://dx.doi.org/10.1037/met0000078

http://dx.doi.org/10.1002/job.2241

Peterson, R. S. (1999). Can you have too much of a good thing? The limits
of voice for improving satisfaction with leaders. Personality and Social
Psychology Bulletin, 25, 313–324. http://dx.doi.org/10.1177/
0146167299025003004

Pillutla, M. M., Malhotra, D., & Murnighan, J. K. (2003). Attributions of trust
and the calculus of reciprocity. Journal of Experimental Social Psychology,
39, 448 – 455. http://dx.doi.org/10.1016/S0022-1031(03)00015-5

Robins, R. W., & John, O. P. (1997). Effects of visual perspective and
narcissism on self-perception: Is seeing believing? Psychological Sci-
ence, 8, 37– 42. http://dx.doi.org/10.1111/j.1467-9280.1997.tb00541.x

Römer, M., Rispens, S., Giebels, E., & Euwema, M. C. (2012). A helping
hand? The moderating role of leaders’ conflict management behavior on
the conflict–stress relationship of employees. Negotiation Journal, 28,
253–277. http://dx.doi.org/10.1111/j.1571-9979.2012.00340.x

Rousseau, D. M., Sitkin, S. B., Burt, R. S., & Camerer, C. (1998). Not so
different after all: A cross-discipline view of trust. Academy of Management
Review, 23, 393– 404. http://dx.doi.org/10.5465/amr.1998.926617

Salamon, S. D., & Robinson, S. L. (2008). Trust that binds: The impact of
collective felt trust on organizational performance. Journal of Applied
Psychology, 93, 593– 601. http://dx.doi.org/10.1037/0021-9010.93.3.593

Shectman, Z., & Kenny, D. A. (1994). Metaperception accuracy: An Israeli
study. Basic and Applied Social Psychology, 15, 451– 465. http://dx.doi
.org/10.1207/s15324834basp1504_4

Simons, T. L., & Peterson, R. S. (2000). Task conflict and relationship
conflict in top management teams: The pivotal role of intragroup trust.
Journal of Applied Psychology, 85, 102–111. http://dx.doi.org/10.1037/
0021-9010.85.1.102

Snyder, M. (1974). Self-monitoring of expressive behavior. Journal of
Personality and Social Psychology, 30, 526 –537. http://dx.doi.org/10
.1037/h0037039

Snyder, M. (1979). Self-monitoring processes. Advances in Experimental
Social Psychology, 12, 85–128. http://dx.doi.org/10.1016/S0065-2601
(08)60260-9

Spector, P. E., & Jex, S. M. (1998). Development of four self-report
measures of job stressors and strain: Interpersonal conflict at work scale,
organizational constraints scale, quantitative workload inventory, and
physical symptoms inventory. Journal of Occupational Health Psychol-
ogy, 3, 356 –367. http://dx.doi.org/10.1037/1076-8998.3.4.356

Thomas, K. W. (1992). Conflict and negotiation processes in organizations.
In M. D. Dunnette & L. M. Hough (Eds.), Handbook of industrial and
organizational psychology (2nd ed., pp. 651–717). Palo Alto, CA: Con-
sulting Psychologists Press.

Vancouver, J. B., & Weinhardt, J. M. (2012). Modeling the mind and the
milieu. Organizational Research Methods, 15, 602– 623. http://dx.doi
.org/10.1177/1094428112449655

Wayne, S. J., & Ferris, G. R. (1990). Influence tactics, affect, and exchange
quality in supervisor-subordinate interactions: A laboratory experiment
and field study. Journal of Applied Psychology, 75, 487– 499. http://dx
.doi.org/10.1037/0021-9010.75.5.487

Zaheer, A., McEvily, B., & Perrone, V. (1998). Does trust matter? Exploring
the effects of interorganizational and interpersonal trust on performance.
Organization Science, 9, 141–159. http://dx.doi.org/10.1287/orsc.9.2.141

Zajonc, R. B., & Burnstein, E. (1965). Structural balance, reciprocity, and
positivity as sources of cognitive bias. Journal of Personality, 33, 570 –583.
http://dx.doi.org/10.1111/j.1467-6494.1965.tb01403.x

Received May 31, 2016
Revision received October 21, 2019

Accepted October 28, 2019 �

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1012 CAMPAGNA, DIRKS, KNIGHT, CROSSLEY, AND ROBINSON

http://dx.doi.org/10.1177/0146167299025003004

http://dx.doi.org/10.1016/S0022-1031%2803%2900015-5

http://dx.doi.org/10.1111/j.1467-9280.1997.tb00541.x

http://dx.doi.org/10.1111/j.1571-9979.2012.00340.x

http://dx.doi.org/10.5465/amr.1998.926617

http://dx.doi.org/10.1037/0021-9010.93.3.593

http://dx.doi.org/10.1207/s15324834basp1504_4

http://dx.doi.org/10.1037/0021-9010.85.1.102

http://dx.doi.org/10.1037/h0037039

http://dx.doi.org/10.1016/S0065-2601%2808%2960260-9

http://dx.doi.org/10.1037/1076-8998.3.4.356

http://dx.doi.org/10.1177/1094428112449655

http://dx.doi.org/10.1037/0021-9010.75.5.487

http://dx.doi.org/10.1287/orsc.9.2.141

http://dx.doi.org/10.1111/j.1467-6494.1965.tb01403.x

On the Relation Between Felt Trust and Actual Trust: Examining Pathways to and Implications of L …

Theoretical Framework
The External Pathway: Trust Meta-Accuracy Is Shaped by One’s Interpretation of Another …
The Internal Pathway: Trust Meta-Accuracy Is Shaped by One’s Own Trust in Another and the …
Study 1
Method
Procedure and sample
Measures
Employee and leader trust
Leader felt trust
Leader trust meta-accuracy
Employee self-monitoring
Leader perspective taking
Analyses
Results
Discussion
Study 2
Further Examining the Mechanisms Underlying Leader Trust Meta-Accuracy
Implications of Leader Trust Meta-Accuracy
Method
Procedure and sample
Measures
Employee trust in the leader
Leader felt trust
Leader trust meta-accuracy
Employee impression management
Employee–leader interaction frequency
Leader social astuteness
Leader narcissism
Leader trust in employee
Relationship conflict
Analyses
Results
Antecedents of trust meta-accuracy
Consequences of trust meta-accuracy
Discussion
General Discussion
Theoretical Implications
Practical Implications
Limitations and Future Directions
Conclusion
References

References Citation

Article 2

Wang, Mengyang, et al. “The Origins of Trust Asymmetry in International Relationships: An Institutional View.” Journal of International Marketing, vol. 28, no. 2, June 2020, pp. 81–101. EBSCOhost, doi:10.1177/1069031X19898492.

Article 1

Campagna, Rachel L., et al. “On the Relation between Felt Trust and Actual Trust: Examining Pathways to and Implications of Leader Trust Meta-Accuracy.” Journal of Applied Psychology, vol. 105, no. 9, Sept. 2020, pp. 994–1012. EBSCOhost, doi:10.1037/apl0000474.

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