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

Eastern Michigan University Department of Marketing

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Linkages between Relationship Norms and Export Marketing Performance:

Theory and Empirical Model

Harash J. Sachdev, Ph.D. G. Russell Merz, Ph.D

Eastern Michigan University


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Presentation Agenda

•  Background •  Literature •  Research questions

and hypotheses •  Methodology •  Findings •  Discussion •  Conclusions and

limitations 2


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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

Monitoring

Flexibility

Dependence

Info Sharing

Commitment

Export Marketing

Performance

Behavioral Norms

Long-Term/ Signaling Norms

Performance Outcomes


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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

Monitoring

Flexibility

Dependence

Info Sharing

Commitment

Export Marketing

Performance

H4a(+)

H2(+)

H3a (+)

H4b(+)

H1(+)

H4c(+) H3b(+) H5a(+)

H5b(+)

H4d(+)

Behavioral Norms




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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

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Descriptive Variable N MeanTotal firm sales last year 243 $162,382,913.72Export dollars 243 $5,014,276.50% Change in export sales 247 18.66% total firm sales from exporting 245 19.25% Change in export profits 247 13.19% Worldwide sales from this product 243 28.21Years of firm export activity 248 23.19Number of employees 248 418.59Number of employees FT in exporting 248 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.

Variable 1 2 3 4 5 Mean Stdev nInfoshare2 0.838 0.214 0.145 0.013 0.042 4.74 1.65 248Infoshare3 0.795 0.29 0.07 0.072 0.052 4.12 1.79 248Infoshare1 0.756 0.192 0.117 0.084 0.022 4.76 1.72 248Infoshare5 0.69 0.085 0.249 -0.034 0.104 4.90 1.65 248Infoshare4 0.674 -0.085 -0.026 0.042 0.084 5.11 1.66 248Monitoring1 0.143 0.823 -0.002 0.067 -0.016 4.07 2.00 248Monitoring2 0.073 0.778 0.071 -0.028 -0.172 2.98 1.86 248Monitoring4 0.157 0.775 0.035 -0.058 0.013 3.83 1.89 248Monitoring3 0.127 0.678 -0.025 -0.053 0.247 4.96 1.76 248Commit3 0.129 -0.017 0.852 0.235 0.099 5.69 1.45 248Commit2 0.094 -0.022 0.84 0.162 0.049 5.63 1.50 248Commit1 0.221 0.119 0.798 0.122 0.091 6.04 1.24 248Dependence3 0.013 -0.032 0.179 0.828 0.015 5.16 1.68 248Dependence4 -0.001 -0.013 0.148 0.756 0.087 4.53 1.82 248Dependence1 0.028 0.031 0.382 0.74 0.053 4.77 1.86 248Dependence2 0.103 -0.038 -0.05 0.703 0.048 4.44 1.74 248Flexible1 0.095 -0.037 -0.054 0 0.808 5.7 1.35 248Flexible2 -0.02 0.033 0.067 0.162 0.731 5.06 1.44 248Flexible3 0.204 0.042 0.288 0.019 0.665 5.13 1.40 248Eigen Values 3.04 2.546 2.468 2.449 1.777% of Variance 16.000 13.401 12.991 12.890 9.351Total Variance

0.79Bartlett's Test of Sphericity Approx. Chi-Square = 1790.735

df = 171 Sig.= 0.000

ComponentsExploratory Factor Analysis Rotated Component Matrix

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.64.633

VariableDescriptives

Scree Plot

Component Number

19181716151413121110987654321

Eig

enva

lue

5

4

3

2

1

0


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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 cross-loadings.

•  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.

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Monitoring Flexible InfoShare Commit Dependence PerformMonitoring1 0.841 0.017 0.290 0.029 -0.004 0.211Monitoring2 0.747 -0.048 0.187 -0.012 -0.064 0.155Monitoring3 0.712 0.159 0.242 0.021 -0.030 0.218Monitoring4 0.843 0.098 0.282 -0.005 -0.040 0.290Flexible1 0.047 0.659 0.144 0.044 0.073 0.175Flexible2 0.060 0.651 0.088 0.203 0.210 0.135Flexible3 0.072 0.894 0.288 0.353 0.169 0.234InfoShare1 0.258 0.218 0.821 0.254 0.121 0.366InfoShare2 0.309 0.239 0.877 0.325 0.064 0.356InfoShare3 0.390 0.186 0.851 0.250 0.111 0.346InfoShare4 0.095 0.137 0.614 0.170 0.094 0.188InfoShare5 0.153 0.240 0.747 0.351 0.103 0.301 Commit1 0.092 0.258 0.370 0.835 0.343 0.345 Commit2 -0.039 0.233 0.238 0.840 0.348 0.261 Commit3 -0.027 0.323 0.286 0.903 0.433 0.404Dependence1 0.002 0.242 0.154 0.478 0.893 0.391Dependence2 -0.027 0.077 0.103 0.200 0.618 0.209Dependence3 -0.090 0.128 0.059 0.324 0.838 0.217Dependence4 -0.036 0.138 0.043 0.287 0.748 0.241Perform1 0.219 0.182 0.216 0.293 0.281 0.732Perform2 0.253 0.238 0.291 0.298 0.268 0.762Perform3 0.151 0.216 0.256 0.301 0.246 0.776Perform4 0.147 0.203 0.297 0.204 0.193 0.715Perform5 0.256 0.119 0.375 0.353 0.381 0.799Perform6 0.286 0.222 0.361 0.293 0.299 0.813Perform7 0.180 0.184 0.350 0.372 0.206 0.760

Loadings and Cross Loadings


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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.

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Monitoring InfoShare Flexible Commit Dependence PerformMonitoring 0.788 0.324 0.081 0.012 -0.041 0.285Info Share 0.324 0.788 0.263 0.349 0.123 0.405Flexible 0.081 0.263 0.743 0.319 0.205 0.250Commitment 0.012 0.349 0.319 0.860 0.439 0.399Dependence -0.041 0.123 0.205 0.439 0.781 0.357Performance 0.285 0.405 0.250 0.399 0.357 0.766Composite Reliability 0.867 0.890 0.783 0.895 0.860 0.908Cronbachs Alpha 0.796 0.845 0.631 0.824 0.786 0.883Average Variance Extracted (AVE) 0.621 0.620 0.552 0.740 0.610 0.587R-square 0.161 0.309 0.330Redundancy 0.042 0.138 0.068Diagonal 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.

Constructs


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Findings: Structural Model Results

Monitoring

Flexibility

Dependence

Info Sharing R2=.161

Commitment R2=.309

Export Marketing

Performance R2=.330

0.192 (1.5631) 0.305

(2.5963)

0.238 (2.4343)

0.222 (1.9852)

0.257 (2.6163)

0.064 (.297ns) 0.176

(1.9122) 0.371 (4.3363)

0.241 (2.2652)

0.216 (2.2682)

Behavioral Norms



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


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