Linkages between Relationship Norms and Export Marketing Performance: Theory and Empirical Model

Eastern Michigan University
Department of Marketing

Linkages between Relationship Norms
and Export Marketing Performance:
Theory and Empirical Model
Harash J. Sachdev, Ph.D.
G. Russell Merz, Ph.D

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Presentation Agenda
•  Background
•  Literature
•  Research questions
and hypotheses
•  Methodology
•  Findings
•  Discussion
•  Conclusions and
limitations
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2


Introduction
Manufacturers using intermediaries to export are reluctant
to fully commit to the export market because they feel loss
of control. Why?
•  Fear of becoming dependent
•  Proprietary information about the firm and product may
be shared
•  Time and effort needed to train and motivate the
intermediaries which may be lost if exchange terminated

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Options
Vertically Integrate (Why not?)
•  Lack of resources
•  Lack of foreign market skills, etc.
Intermediate modes of Governance (close, on-going
relationship) How?
•  Signaling Norms
- Dependence
- Commitment
•  Behavioral Action Norms
- Monitoring
- Flexibility
- Information Sharing
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Benefits
•  Better manage business (e.g., Noordewier, John, and Nevin
1990; Bello, Zhang, and Sachdev 1996).
•  Help reduce cost and improve performance (Cannon and
Homburg 2001;Palmatire, Dant, and Grewal 2007).
•  Using such norms make non-integrated firms operate as if
they are integrated plus maintain the advantage of economies
of scale, low overhead, and flexibility of an exchange (e.g.,
Grossman and Hart 1986; Dwyer et al. 1987; Zsididin et al.
2007).
•  The long run benefit of relational exchanges (close
relationships) is that they create barriers to entry for other
firms.
•  The synergy effect created by such exchanges that is greater
than the sum of parts.

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Purpose
•  Although understanding the types and degree of
relationship norms is important, few studies have been
conducted to study the cause and effect relationship
between these norms and how changes in one norm
affects changes in the other.
•  What is the performance consequence resulting thereof?
•  Once these cause and effect linkages are understood,
export manufacturers may better manage their channel
members and assist them in promoting the viability of the
channel and improving overall export performance.

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Transaction Cost Economics (TCE)
Conceptual Framework

•  TCE framework initiated by Williamson (1975; 1985) has
been modified to better fit into channel settings (e.g.,
Heide and John 1988;1990).
•  The purpose of TCE is to assess the efficiency of
hierarchical (vertically integrated) exchanges over
market-based (e.g., two independent parties) in the
presence and absence of transaction cost properties.
•  Assumptions:
–  Bounded Rationality (limited cognitive ability of the human mind)
–  Information Asymmetry (difference in information levels existing
between two parties)
–  Opportunistic behavior

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What is Transaction Cost?
Ex-ante - the cost associated with setting up (e.g., selection
of a distributor) and safeguarding the agreement
between parties.
Ex-post - the cost of monitoring and enforcing policies and
obtaining some form of secured commitment.

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TCE and Dependence
•  TCE theorists suggest that forced dependence is the key to
understanding and developing long-term relationships (e.g.,
Heide and John 1988). This is because perceptions about the
nature of this dependence may lead to high transaction cost.
•  Channel partners are presumed to have high levels of
interdependence and transaction cost (e.g., Anderson and
Weitz 1989).
•  The establishment of appropriately developed relationship
norms is a major way to manage the transaction costs of an
exchange (Macneil 1978).
•  Most channel transactions have some element of relationship
norms that may assist in coordinating channel activities (Weitz
and Jap 1995).

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Relationship Norms: Linkages
•  Each relationship norm may
be placed along a continuum,
proportional to the degree of
transaction cost, up to and
including simulating a
vertically integrated firm but
falling short of total ownership
(e.g., Grossman and Hart
1986; Dwyer et al. 1987;
Zsididin et al. 2007).
•  These relationship norms are
related through linkages.

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Conceptual Model of Export Marketing Performance
Behavioral
Norms

Long-Term/
Signaling Norms

Performance
Outcomes

Monitoring
Commitment
Export
Marketing
Performance

Info
Sharing
Dependence

Flexibility

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Hypotheses
Since communication can be described as the glue that
holds together a channel of distribution (Mohr and Nevin
1990, p. 36), it is expected that:
–  Information sharing will be the central relational norm through
which parties signal longevity of the relationship commitment
(Goffin et al. 2005) [H1].
–  The relational norms of monitoring and flexibility will directly
affect the degree of information sharing communication between
parties [H2,H3a],
–  In addition, flexibility is also presumed to independently
positively effect commitment to a relationship (e.g., Ford 1984)
[H3b].
–  Collectively all of the relationship norms guide manufacturers to
curtail opportunism and will positively affect export marketing
performance (Klein 1989; Bello et al. 1996) [H4a,b,c,d].

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Hypotheses
–  Perception of dependence increases transaction cost and forces
the dependent party to forge a committed relationship (Sriram et
al. 1992) [H5a].
–  A source s dependence on its target firm is positively related to
the agreement about the developed marketing strategy for the
source and also satisfaction with the role performance of the
target firm (Frazier 1983). Thus, it is expected that dependence
in a relationship positively influences the level of adaptability in
the relationship and have positive performance consequences
(e.g., Hallen et al. 1991; Hibbard et al. 2001) [H5b].

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Summary of Model Hypotheses
Behavioral
Norms

Long-Term/
Signaling Norms

H1(+)

Commitment

H3b(+)

H5a(+)

Flexibility

H4c(+)

H5b(+)
Dependence

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H4d(+)

H4b(+)

Info
Sharing

H3a (+)

Performance
Outcomes

H4a(+)

Monitoring

H2(+)


Export
Marketing
Performance


Operational Definitions
All measured on a 7 point Likert Agree/Disagree Scale
Flexibility is the degree to which manufacturers have room
to make adjustments for unforeseen needs not specified
in contracts.
Information sharing is measured as the extent to which
manufacturers provide their intermediaries with detailed
explanations of future plans.
Monitoring refers to the extent to which manufacturers
evaluate intermediaries' progress in foreign markets
through operating control or performance criteria.
Relationship commitment refers to the anticipated
longevity of a working relationship.
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Operational Definitions
Dependency is the manufacturer s perceptions about the
difficulty of replacing its intermediary.
Export Marketing Performance is measured on a 6 point
semantic scale (poor, adequate, somewhat good,
moderately good, very good, and extremely good).
Respondents are asked to judge how effectively their
intermediaries perform basic export marketing activities.
These activities pertain to issues concerning developing
and servicing an export market and marketing strategy
for a manufacturer.

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Methodology: Sample, Data Collection,
Analysis

•  Systematic sample of 600 manufacturers was selected
from the export manufacturers' directory:
–  Key informants were identified through telephone calls.
–  400 participants who qualified for the study were mailed the
questionnaire.
–  Three weeks after the initial mailing, respondents were reminded
via telephone calls to fill out the survey.
–  A total of 248 completely answered questionnaires resulted in a
62% response rate.

•  Analysis was conducted in three stages:
–  Descriptive and summary characteristics of sample.
–  Exploratory factor analysis (PCA) with varimax rotation.
–  Structural equations modeling with latent variable partial least
squares (LV-PLS).

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Findings: Sample Descriptives

Descriptive Variable
Total firm sales last year
Export dollars
% Change in export sales
% total firm sales from exporting
% Change in export profits
% Worldwide sales from this product
Years of firm export activity
Number of employees
Number of employees FT in exporting

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N

Mean

243
243
247
245
247
243
248
248
248

$162,382,913.72
$5,014,276.50
18.66
19.25
13.19
28.21
23.19
418.59
13.38

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Findings: Factor Analysis Results
• 

• 

• 

The EFA results showed
strong support for the
proposed separate
treatment of the composite
variables.
All of the variables have
loadings greater than 0.6,
each factor exceeds the
minimum acceptable
Eigenvalue score of 1.0
and collectively the percent
of variance explained is
64.6%.
The KMO of sampling
adequacy (.79) and the
Bartlett s test statistic also
exceed minimums.

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Exploratory Factor Analysis Rotated Component Matrix
Variable
Components
Descriptives
Variable
1
2
3
4
5 Mean Stdev
n
0.838
Infoshare2
0.214
0.145
0.013
0.042 4.74 1.65
248
0.795
Infoshare3
0.29
0.07
0.072
0.052 4.12 1.79
248
0.756
Infoshare1
0.192
0.117
0.084
0.022 4.76 1.72
248
0.69
Infoshare5
0.085
0.249
-0.034
0.104 4.90 1.65
248
0.674
Infoshare4
-0.085
-0.026
0.042
0.084 5.11 1.66
248
0.823
Monitoring1
0.143
-0.002
0.067
-0.016 4.07 2.00
248
0.778
Monitoring2
0.073
0.071
-0.028
-0.172 2.98 1.86
248
0.775
Monitoring4
0.157
0.035
-0.058
0.013 3.83 1.89
248
0.678
Monitoring3
0.127
-0.025
-0.053
0.247 4.96 1.76
248
0.852
Commit3
0.129
-0.017
0.235
0.099 5.69 1.45
248
0.84
Commit2
0.094
-0.022
0.162
0.049 5.63 1.50
248
0.798
Commit1
0.221
0.119
0.122
0.091 6.04 1.24
248
0.828
Dependence3
0.013
-0.032
0.179
0.015 5.16 1.68
248
0.756
Dependence4
-0.001
-0.013
0.148
0.087 4.53 1.82
248
0.74
Dependence1
0.028
0.031
0.382
0.053 4.77 1.86
248
0.703
Dependence2
0.103
-0.038
-0.05
0.048 4.44 1.74
248
0.808
Flexible1
0.095
-0.037
-0.054
0
5.7 1.35
248
0.731 5.06 1.44
Flexible2
-0.02
0.033
0.067
0.162
248
0.665 5.13 1.40
Flexible3
0.204
0.042
0.288
0.019
248
Eigen Values
3.04
2.546
2.468
2.449
1.777
% of Variance
16.000
13.401
12.991
12.890
9.351
Total Variance
64.633
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
0.79
Bartlett's Test of Sphericity
Approx. Chi-Square = 1790.735
df = 171
Sig.= 0.000


Findings: Structural Equations Modeling with
Latent Variable Partial Least Squares (LV-PLS)
• 

• 

• 

• 

• 

To test hypotheses a structural equations model (SEM) with latent variables
was estimated using a latent variable partial least squares (LV-PLS)
algorithm (Ringle, et al 2005).
The measurement model in PLS is assessed in terms of item loadings and
reliability coefficients (composite reliability), as well as the convergent and
discriminant validity.
Measures with loadings onto underlying latent variables of greater than 0.7
possess acceptable levels of association with a component (Fornell and
Larcker 1981).
Interpreted like a Cronbach s alpha for internal consistency reliability, a
composite reliability of 0.7 or greater is considered as an acceptable level of
reliability (Fornell and Larcker 1981).
The average variance extracted (AVE) measures the variance captured by
the indicators relative to the measurement error, and it should be greater
than 0.5 to justify using a construct (Barclay, Thompson and Higgins 1995).

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Findings: Measurement Model Quality
•  The construct validity
was assessed by
examination of
loadings and crossloadings.
•  Some component
loadings are < .7, but
if the cross loadings
are smaller and the
discriminant validity
test is met, then the
structure is
acceptable for
exploratory analysis.

Loadings and Cross Loadings
Monitoring
Monitoring1
Monitoring2
Monitoring3
Monitoring4
Flexible1
Flexible2
Flexible3
InfoShare1
InfoShare2
InfoShare3
InfoShare4
InfoShare5
Commit1
Commit2
Commit3
Dependence1
Dependence2
Dependence3
Dependence4
Perform1
Perform2
Perform3
Perform4
Perform5
Perform6
Perform7

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0.841
0.747
0.712
0.843
0.047
0.060
0.072
0.258
0.309
0.390
0.095
0.153
0.092
-0.039
-0.027
0.002
-0.027
-0.090
-0.036
0.219
0.253
0.151
0.147
0.256
0.286
0.180

Flexible

0.017
-0.048
0.159
0.098
0.659
0.651
0.894
0.218
0.239
0.186
0.137
0.240
0.258
0.233
0.323
0.242
0.077
0.128
0.138
0.182
0.238
0.216
0.203
0.119
0.222
0.184

InfoShare

0.290
0.187
0.242
0.282
0.144
0.088
0.288
0.821
0.877
0.851
0.614
0.747
0.370
0.238
0.286
0.154
0.103
0.059
0.043
0.216
0.291
0.256
0.297
0.375
0.361
0.350

Commit

0.029
-0.012
0.021
-0.005
0.044
0.203
0.353
0.254
0.325
0.250
0.170
0.351
0.835
0.840
0.903
0.478
0.200
0.324
0.287
0.293
0.298
0.301
0.204
0.353
0.293
0.372

Dependence

-0.004
-0.064
-0.030
-0.040
0.073
0.210
0.169
0.121
0.064
0.111
0.094
0.103
0.343
0.348
0.433
0.893
0.618
0.838
0.748
0.281
0.268
0.246
0.193
0.381
0.299
0.206

Perform

0.211
0.155
0.218
0.290
0.175
0.135
0.234
0.366
0.356
0.346
0.188
0.301
0.345
0.261
0.404
0.391
0.209
0.217
0.241
0.732
0.762
0.776
0.715
0.799
0.813
0.760

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Findings: Measurement Model Discriminant
Validity
•  The square roots of AVE values exceed inter-correlations of the
latent variables. All composite reliability values and most
Cronbach s Alphas are > 0.7. All AVEs exceed minimum of 0.5.
Constructs
Monitoring InfoShare
Flexible
Commit Dependence Perform
0.788
0.324
0.081
0.012
-0.041
0.285
Monitoring
0.788
Info Share
0.324
0.263
0.349
0.123
0.405
0.743
Flexible
0.081
0.263
0.319
0.205
0.250
0.860
Commitment
0.012
0.349
0.319
0.439
0.399
0.781
Dependence
-0.041
0.123
0.205
0.439
0.357
0.766
0.285
0.405
0.250
0.399
0.357
Performance
Composite Reliability
0.867
0.890
0.783
0.895
0.860
0.908
0.796
0.845
0.631
0.824
0.786
0.883
Cronbachs Alpha
0.621
0.620
0.552
0.740
0.610
0.587
Average Variance Extracted (AVE)
R-square
0.161
0.309
0.330
0.042
0.138
0.068
Redundancy
Diagonal elements are the square root of the variance shared between the constructs and their measurement (AVE).
Off diagonal elements are the correlations among the constructs.
Diagonal elements should be larger than off-diagonal elements in order to obtain the discriminant validity.

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Findings: Structural Model Results
Behavioral
Norms

Long-Term/
Signaling Norms

0.257
(2.6163)

Commitment
R2=.309

0.176
(1.9122)

0.371
(4.3363)

Flexibility
Dependence

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0.192
(1.5631)
0.222
(1.9852)

Info
Sharing
R2=.161

0.238
(2.4343)

Performance
Outcomes

0.216
(2.2682)

Monitoring

0.305
(2.5963)


0.064
(.297ns)

Export
Marketing
Performance
R2=.330

0.241
(2.2652)
Path coefficients are standardized β
(t-statistics in parentheses:1 p ≤ 0.1, 2 ≤ 0.05, 3 ≤ 0.01)


Conclusions
•  Manufacturers who refrain from exporting or fear a loss
of control while exporting because of being dependent
on their intermediary should use Dependence in a
positive light.
•  They should believe and be willing to use the different
relationship norms to their benefit and guide their
relationship toward positive performance outcomes.
•  Monitoring the other party should not be perceived
suspiciously but rather as a tool to increase Information
Sharing in the channel.

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Conclusions
•  Flexibility should be used, through information sharing,
as a source of leveraging ones core competency in the
marketplace rather than be considered a headache due
to last moment redeployment of resources and activities.
•  All these norms should be signaled through
Commitment of the relationship as a sign of maintaining
the channel partnership into the future.
•  All of these norms work in a synergetic manner to
improve the viability of the channel, sustain competitive
advantage ,and may be a major barrier to entry to
potential competitors.

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Limitations
•  TCE is a normative framework which
prescribes a solution for firms facing
high transaction cost.
•  Manufacturers may follow an entirely
different course of action for reasons
not associated with transaction cost
(e.g., inefficient practices; limited
choice of intermediary availability;
government regulations in maintaining
and dissolution of a relationship).
•  Manufacturers maybe in different
stages of relationship development.
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Limitations
•  Some potentially useful constructs not included (e.g.,
internationalization process, risk management, tacit
communication).
•  Dependence and Commitment are broader constructs
than the way they have been measured in this study.
•  There may be other signaling norms besides
Commitment (e.g., trust)
•  Flexibility, Information Sharing, Dependence, and
Commitment are bi-direction constructs. Dyadic studies
may shed better light into these constructs

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Any Questions?

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28

Linkages between Relationship Norms and Export Marketing Performance: Theory and Empirical Model

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