Supply Chain Information and Relational Alignments ...

Supply Chain Information and Relational Alignments:

Mediators of EDI on Firm Performance

Keah Choon Tan

College of Business

University of Nevada Las Vegas

Las Vegas, NV 89154-6009

Tel/Fax: (702) 895-3873/4370

[email protected]

Vijay R. Kannan

Jon M. Huntsman School of Business

Utah State University

Logan, UT 84322-3510

Tel/Fax: (435) 797-7212/1091

[email protected]

Chin-Chun Hsu *

College of Business



Tel/Fax: (702) 895-3842/4370

[email protected]

G. Keong Leong

College of Business


4505 Maryland Parkway, Box 456009


(702) 895-1762

[email protected]

November 9, 2009

Submission to the International Journal of Physical Distribution and Logistics Management

(First Revision)

(*corresponding author)

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Keah-Choon Tan is Professor of Operations Management at the University of Nevada, Las

Vegas. He received his Ph.D. in Production and Operations Management from Michigan State

University. He is a certified purchasing manager (C.P.M.) and is also certified in production and

inventory management (CPIM). He has published articles in the areas of quality management,

supply chain management, and operations scheduling in a number of professional magazines and

academic journals. He is a coauthor of the Principles of Supply Chain Management: A Balanced

Approach, 2nd edition. Dr. Tan has served as editor, co-guest editor, and on the editorial boards

of academic journals. He has received numerous research grants and awards. He is a recipient of

the UNLV Foundation Distinguished Teaching Award in 2009.

Vijay R. Kannan is Vernon Maughan Buehler & Maree C. Buehler Endowed Professor and

Professor of Operations Management in the Jon M. Huntsman School of Business, Utah State

University. Dr. Kannan earned his BSc. from the University of London, MBA from Indiana

University and Ph.D. in Operations Management from Michigan State University. He has

published extensively in the areas of cellular manufacturing, quality management, and supply

chain management, his articles appearing in journals including Decision Sciences, International

Journal of Production Research, International Journal of Operations and Production

Management, OMEGA, and International Journal of Physical Distribution and Logistics

Management. His current research examines the impact of buyer-supplier relationships in supply

chains.

Chin-Chun Hsu is Associate Professor of International Management at the University of

Nevada, Las Vegas. He received his Ph.D. in International Business from Saint Louis University.

He has published numerous articles in the areas of international strategic management, cross-

cultural management, marketing research, and supply chain management in a variety of journals,

including Journal of International Business Studies, Management International Review, Journal

of Business Research, OMEGA, International Journal of Production Research, International

Journal of Logistics Management, and International Journal of Physical Distribution and

Logistics Management.

G. Keong Leong is Professor and Chair of the Management Department in the College of

Business, University of Nevada Las Vegas. He holds a Bachelor of Mechanical Engineering

from the University of Malaya, an MBA and a Ph.D. from the University of South Carolina. He

has published articles in academic journals such as Journal of Operations Management, Decision

Sciences, Interfaces, Journal of Management, European Journal of Operational Research,

International Journal of Production Research, International Journal of Logistics Management,

and International Journal of Physical Distribution and Logistics Management. His current

research interests include supply chain management, international operations, operations

strategy, and technology management. He has co-authored three books, won research and

teaching awards, and received an Educator of the Year award from the Asian Chamber of

Commerce in Las Vegas. He has held leadership positions in Decision Sciences Institute such as

Editor of Decision Line, At-Large Vice-President, Chair of the Innovative Education Committee,

Chair of the Doctoral Student Affairs Committee, and Manufacturing Management Track Chair.

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Supply Chain Information and Relational Alignments:

Mediators of EDI on Firm Performance

Abstract

Purpose – This study examines the effects of inter-organization information exchange on supply

chain information and relational alignment. Drawing on literature on information systems,

supply chain management, and logistics, we present a multidimensional framework for

considering EDI adoption in supplier management and its effect on information and relational

alignment.

Design/methodology/approach – Theories drawn from resource-dependent and transaction cost

economics, and the resource-based view of the firm were used to establish hypotheses. Structural

equation modeling using survey data of manufacturing firms was used to test the hypotheses and

research model.

Findings – Results support the central premise that firms must consider EDI adoption in supplier

management to improve information and relational alignment between supply chain partners. It

is through this alignment that firms achieve superior performance.

Research limitations/implications – This study used a single respondent from each firm due to

cost considerations, and hence might have affected the inter-rater reliability of the survey data.

Practical implications – Results show that firms should consider EDI adoption in supplier

management because of its positive effect on information and relational alignment, which in turn

impacts firm performance. However, EDI does not affect performance directly.

Originality/value – The role of EDI adoption in supplier management was examined and shown

to indirectly affect firm performance via improved information and relational alignment.

Moreover, supply chain information alignment was found to enhance relational alignment among

supply chain partners.

Key Words – Supplier Management, Information Alignment, Relational Alignment, Electronic

Data Interchange, Firm Performance.

Classifications – Research Paper

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Introduction

Faced with intense global competition and shrinking product life cycles, firms have

recognized that the seamless integration of operations and processes with those of supply chain

partners can be a source of competitive advantage (Hammer, 2001). Firms have also embraced

inter-organizational information systems such as electronic data interchange (EDI) to facilitate

communication and information exchange with suppliers and customers (Subramani, 2004; Teo

et al., 2003). Inter-organizational information systems play a key role in achieving competitive

success (Hammer, 2001; Subramani, 2004). Indeed, research has shown that EDI use can help

firms establish cooperative relationships and share vital information (Grover et al., 2003; Son et

al., 2005). This can reduce the effects of information distortion which commonly manifests itself

via the bullwhip effect, reduce response times, and enable firms to effectively combine internal

process knowledge with that of suppliers’ to create unique, value adding capabilities.

While disagreement exists regarding the benefits and impact of EDI, its proponents report

significant gains from its adoption (Mukhopadhyay et al., 1995; Craighead et al., 2006). A

sizable body of literature in the information systems domain refers to the success of EDI

implementation in terms of integration and utilization (Son et al., 2005; Lee and Lim, 2005;

Sánchez and Pérez, 2005), and benefits such as enhanced data integrity, responsiveness, and

product quality (Craighead et al., 2006). However, the literature focuses largely on identifying

dimensions of EDI crucial to organizational success (Son et al., 2005), or key characteristics and

benefits of EDI adoption and implementation (Lee and Lim, 2005; Sánchez and Pérez, 2005).

Little attention has been given to the role of EDI in the context of supplier management and its

subsequent impact on performance.

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This study explores the impact of considering both buyer and supplier EDI capability in

supplier management decisions on supply chain information and relational alignment, and

performance. Firms must consider theirs and their supplier’s EDI capabilities when making

decisions regarding supply chain configuration. We argue that this is a precursor of the

information and relational alignment between supply chain partners that drives firm

performance. We define EDI capability as the scope of a firm’s technology infrastructure for

information exchange using EDI. Supply chain information alignment refers to the alignment of

information flows and the use of compatible information systems between the buyer and supplier

consistent with meeting strategic goals and customer requirements. The development of tightly

coupled information infrastructures is one of several guiding principles for the effective design

and execution of supply chain systems (Muckstadt et al., 2001). Supply chain information

alignment includes the evaluation of formal and informal information sharing agreements,

communication of future strategic needs, and creation of compatible information systems

between trading partners. Supply chain relational alignment addresses the consistency between

the buyer and supplier in terms of culture, relationship expectations, and flexibility to adapt to

changing market needs. A key factor in supply chain relational alignment is that decision-making

and actions are consistent among supply chain members. However, consistency exists only if

strategic processes and performance measures are dynamically linked (McAdam and Baile,

(2002). In the following section, the literature review and research hypotheses are presented. In

subsequent sections, the survey instrument and statistical analyses are addressed followed by

discussion of the results. Finally, conclusions and limitations of the study are provided.

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Literature Review

Information Technology, Information Sharing, and the Buyer-Supplier Relationship

Prior literature suggests that information technology (IT) is an enabler of information

sharing within the supply chain. Carr and Smeltzer (2002) observed a relationship between the

use of direct computer-computer links and the richness of information shared. Sanders and

Premus (2005) found that IT capability has a positive, direct effect on both internal and external

collaboration, noting that information sharing is a key dimension of collaboration. Kim et al.,

(2006) observed that both applied innovation and administrative innovation are positively related

to systems integration, the ability to use IT for collaborative purposes. They also found that both

systems integration and administrative innovation influence information sharing. Christiaanse

(2005) suggested that EDI use facilitates timely, frequent information exchange. Walton and

Gupta (1999) noted that information coupling between supply chain partners should be

collaborative for partners to achieve the benefits of EDI. Prior literature does not offer definitive

evidence of the role EDI plays in aligning information flows between supply chain partners and

how this is a source of competitive edge. Moreover, there is little evidence of the role EDI

capability plays in information alignment between buyers and suppliers.

Several studies have examined the relationship between IT deployment and the buyer-

supplier relationship. They concluded that IT can enhance coordination (Bensaou and Anderson,

1999; Kim et al., 2006), facilitate development of close relationships (Bensaou and Anderson,

1999), and reinforce and stabilize inter-organizational structures (Chae et al., 2005). Studies of

EDI offer similar results. Positive relationships between EDI use and buyer-supplier cooperation

(Bensaou, 1997), supplier perceptions of mutual understanding and cooperation (Sánchez and

Pérez, 2005), and supplier coordination (Hill and Scudder, 2002), have all been observed. Buyer-

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supplier trust, interdependence, and commitment positively influence the diversity of EDI use

(Lee and Lim, 2005), while customer power negative influences EDI usage (Son et al., 2005).

Reciprocal investments and cooperation are also positively related to both the diversity and

volume of EDI use (Son et al., 2005). Not only are trust and interdependence positively related

to EDI integration and utilization, high levels of cooperation strengthen the relationship between

reciprocal investments and diversity of EDI use (Lee and Lim, 2005). EDI use is also consistent

with reduced conflict (Carr and Smeltzer (2002).

Studies of buyer-supplier relationships refer to the link between these relationships and

information sharing. They suggest that cross-functional information sharing between buyer and

supplier is directly related to the strength of their relationship (Martin and Grbac, 2003).

Information sharing and trust also have a positive, direct effect on supply chain proximity, a

measure of the physical distance between the buyer and supplier and a proxy for the closeness of

the relationship (Narasimhan and Nair, 2005). The IT literature suggests a similar link. Kim et

al., (2006) noted that both the use of IT for collaborative purposes and information exchange

positively affect inter-organizational coordination. In the context of EDI specifically, Larson and

Kulchitsky (2000) found that the quality of information shared and the closeness of the buyer-

supplier relationship are related.

Information Sharing and Performance

Considerable empirical evidence of the benefits of EDI exists. Its use is consistent with

cost reductions in broad terms (e.g., Manabe et al., 2005; Craighead et al., 2006) as well as in

specific costs such as freight, inventory, and information handling (Mukhopadhyay et al., 1995).

Improvements in several inventory related metrics are also reported (Dröge and Germain, 2000;

Manabe et al., 2005). EDI use leads to reductions in the time to process a purchase request, the

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timeliness and accuracy of supplier deliveries (Walton and Marucheck, 1996), customer

responsiveness (Craighead et al., 2006), as well as broader measures of time based competition

(Manabe et al., 2005). The speed and accuracy of EDI yields improvements in the management

of process uncertainties and resulting process disruptions. EDI use is also associated with

improvements in manufacturing processes (Manabe et al., 2005), product quality (Craighead et

al., 2006), overall competitiveness and performance, and growth in sales and market share

(Yusuf et al., 2004). EDI use also has benefits in terms of the ease of data entry and reductions in

data errors (Craighead et al., 2006).

Downing (2002) compared firms using traditional EDI technologies with those using

web-based EDI technologies. Results indicated that EDI use is consistent with high levels of

internal/partner operational efficiency and overall process performance attributable to the use of

IT. The use of web-based EDI was also consistent with higher levels of coordination with supply

chain partners and overall performance than the use of traditional EDI technologies. In a broader

IT context, Sanders and Premus (2005) found evidence of a direct relationship between IT

capability and performance, measured in terms of improvements in cost, product quality, new

product introduction time, and delivery speed.

Evidence of the influence of information flow on performance is limited. Kim et al.,

(2006) noted a direct positive relationship between information exchange and market

performance, defined in terms of sales growth, market and product development. They also

observed that information exchange positively influences the responsiveness of the partnership,

which in turn has a positive impact on market performance. Larson and Kultchitsky (2000) found

evidence of a positive and direct relationship between the quality of information shared and lead

time performance, measured in terms of cycle time and on time delivery, and an indirect

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relationship via the closeness of the buyer-supplier relationship. Walton and Marucheck (1996)

observed that sharing information on production plans and capacity is positively associated with

improvements in delivery performance.

Several studies suggest a positive relationship exists between the buyer-supplier

relationship and performance in the context of information exchange. Relationship strength has a

direct and positive impact on profitability and customer loyalty (Martin and Grbac, 2003), and

supply chain proximity has a positive impact on performance measured as a composite of

financial and market performance (Narasimhan and Nair, 2005). Kim et al., (2006) observed that

inter-firm coordination positively and directly influences supply chain responsiveness, but

influences market performance only indirectly via the positive influence of supply chain

responsiveness on market performance. Two studies specific to EDI provide further evidence.

Larson and Kultchitksy (2000) found that a close buyer-supplier relationship has a direct,

positive impact on lead-time performance. Lee and Lim (2005) noted that the extent of EDI

integration and utilization but not the diversity of its use, impact EDI performance, measured in

terms of response time, errors, trust, and processing efficiency. The literature on buyer-supplier

relationships also provides extensive evidence of the positive effect relationships can have on

performance (Johnston et al., 2004).

Research Hypotheses

Resource Dependence Theory

Resource dependence theory was developed to describe inter-firm relationships (Pfeffer

and Salancik, 1978). It proposes that firms seek to reduce uncertainty vis-à-vis scarce and valued

resources by establishing relationships with other organizations in the value chain. It also

suggests that organizations attempt to alter dependence relationships by reducing the dependency

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on some partners or increasing the dependency of others on them, thereby shifting the power

structure. The focus of the theory is not on resources themselves but on inter-organizational

relationships that firms rely on to exchange or acquire external resources. Cannon et al., (2008)

argued that the resource dependence perspective of information technology be assessed both on

its technical merits and on whether it affects exchange uncertainty for adopting firms. Carr et al.

(2008) claimed that suppliers who are dependent on a buyer for resources (i.e., sales) are more

likely to cooperate and comply with buyer demands to, for example, participate in new product

development or to modify processes to accommodate new product specifications.

The central premise of EDI is that it aids inter-organizational communication by

coordinating information and material flows. Supply chain members seek to reduce uncertainty

by utilizing formal and informal information sharing agreements, adopting compatible

information systems, and sharing information such as future strategic needs and feedback from

end users. Inter-organizational consistency in these activities leads to supply chain information

alignment. Possessing EDI capability is thus a precursor to it being able to facilitate alignment of

information needs between partner firms. Similarly, supply chain members attempt to reduce

uncertainty and their dependence on others by nurturing collaborative relationships with trading

partners. Organizations, particularly those that are highly dependent on others, are more willing

to accommodate the demands of supply chain members to ensure high customer service levels in

the presence of mutually beneficial buyer-supplier relationships. Consistency in efforts to

achieve these relationships leads to supply chain relational alignment. A partner’s technology

and data communication capabilities can affect efforts to foster cooperation and collaboration.

This however requires the buying firm to consider supplier EDI capability when making

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decisions about how to leverage the relationship. Possessing EDI capability also serves as a cue

to whether the buyer sees technology as a driver of relationship development. We posit that,

H1: Consideration of EDI capability in supplier management positively affects supply

chain information alignment.

H2: Consideration of EDI capability in supplier management positively affects supply

chain relational alignment.

Transaction Cost Economics Theory

Williamson (1981) argued that uncertainty and opportunistic behavior are key

determinants of transaction costs. Similar to resource dependence theory, transaction cost

economics theory suggests that organizations aim to avoid uncertainty. However, it suggests that

a reduction in exchange uncertainty is attractive only to the extent that it reduces transaction

costs (Cannon et al., 2008). Research grounded in transaction cost economics generally focuses

on the role of an organization as a mechanism to reduce exchange uncertainty. However, inter-

organizational exchange also increases the risks of opportunism, particularly when a firm invests

in an asset, such as information technology, that is specific to the exchange relationship. For

example, an opportunistic buyer may force a committed supplier to lower prices once the

supplier has invested in new assets for the exchange. Implementing a new technology such as

EDI is a means to reducing transaction costs if it improves information processing capabilities

and coordination. Information alignment among partner firms enhances visibility and reduces

uncertainty. When supply chain information alignment is achieved, supply chain partners can

reduce uncertainty and transaction costs by establishing collaborative relationships to achieve

supply chain relational alignment. For example, inspection of incoming raw materials, a non-

value added activity, can be eliminated by certifying supplier’s process or product. We posit that,

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H3: Supply chain information alignment has a positive impact on supply chain

relational alignment.

Resource-Based View Theory

While studies based on the theories of resource dependence and transaction cost

economics focus on reducing dependency and uncertainty, the resource-based view of the firm

(Wernefelt, 1984) argues that the key to a firm’s sustainable competitive advantage is how it

develops and exploits unique, inimitable resources. This has been used to explain how

information technology enhances process integration capability and thus firm performance

(Ordanini and Rubera, 2008), and how supplier involvement positively affects strategic

purchasing and performance. It also helps to explain why firms lacking certain competitive

capabilities will promote collaborative relationships with supply chain partners to secure those

capabilities (Oh and Rhee, 2008).

While encouraging suppliers to use EDI has been shown to affect purchasing procedures,

its impact on performance has not been explored. Walton and Gupta (1999) argued that EDI’s

effect on business processes is the key to understanding the impact of EDI on supply chain

management. It is apparent that technologies such as EDI can be an inimitable resource that has a

significant impact on manufacturing, information flow, and performance. The question that

remains is to what extent does consideration of EDI capability in supplier management decisions

affect performance? We posit that

H4: Consideration of EDI capability in supplier management positively affects firm

performance.

As suggested by past research, EDI use can aid a firm in effectively managing

manufacturing processes and uncertainty and can thus be an inimitable resource for achieving

competitive advantage. Its ability to do so however depends on aligning internal manufacturing

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processes, information systems, and relationships with those of supply chain partners.

Performance improvements result from sharing key information in a timely manner, and working

collaboratively towards common goals. Information technology, information sharing,

collaborative relationships and supply chain integration (Meile and Field, 2008) have been

shown to affect firm performance. The question that remains however is whether information

alignment or relational alignment affect performance. Hence, we posit that,

H5: Supply chain information alignment positively influences firm performance.

H6: Supply chain relational alignment positively influences firm performance.

Figure 1 summarizes the proposed research model and hypotheses.

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Insert Figure 1

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Survey Instrument, Respondent Profile and Reliability Analysis

A survey instrument was developed based on a review of pertinent literature and

interviews with practitioners and academics. A senior operations manager from a large

manufacturing firm in the U.S. assisted in the design of the initial survey instrument. Feedback

on the initial design was then obtained from academics familiar with empirical research in study

domain and senior operations managers. A revised survey instrument was finally pre-tested by a

group of practitioners. The instrument incorporated four constructs: Consideration of EDI

Capability in Supplier Management (EDI), Supply Chain Information Alignment (INFO), Supply

Chain Relational Alignment (REL), and Firm Performance (PERF) (see Appendix). To increase

measurement accuracy, multiple indicators were used to represent unobservable constructs

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(Bagozzi et al., 1991) and existing scales employed where possible. The EDI construct consisted

of three variables that address supplier EDI capability in supplier selection and performance

evaluation decisions, and buyer EDI capability in improving customer service (Sanders, 2007,

Kim and Rogers, 2005). The INFO construct consisted of six variables that examine the extent of

information sharing and communication, and the compatibility of inter-organizational

information systems (Savitskie 2007, Moberg et al. 2002). The REL construct consisted of five

measures that examine the role of the buyer-supplier relationship in achieving firm objectives

(Kannan and Tan, 2006, Golicic and Mentzer, 2006). Using a five-point Likert scale, respondents

were asked to indicate the importance of various practices in their firm’s efforts corresponding to

each of the constructs. Firm Performance (PERF) was measured by asking respondents to

indicate the level of their firm’s performance compared to that of major competitors on multiple

performance dimensions. This surrogate measure of performance is used commonly in empirical

research to overcome differences in performance attributable to industry and scale (e.g., Tan et

al., 1998; Narasimhan and Nair, 2005).

Data was collected using standard mail survey procedures (Dillman, 1991) from senior

purchasing and supply managers in the U.S., Europe, and New Zealand, identified from the

Institute for Supply Management and the Association for Operations Management membership

lists, and the KOMPASS commercial database (Basnet et al., 2003). The survey targeted

respondents with the background and experience pertinent to the study. A total of 6,006

delivered surveys yielded 625 useable responses. The response rate of 10.41%, while lower than

those of other empirical studies, is comparable to those of studies using similar population

frames (e.g., Fawcett and Magnan, 2001; Frohlich and Westbrook, 2001). To test for non-

response bias, surveys were separated into two groups based on return date, late arriving

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questionnaires considered representative of non-respondents (Lambert and Harrington, 1990). t-

tests on responses to a set of randomly selected questions and the number of employees and

annual sales, indicated no statistically significant differences (α = 0.05) in mean responses,

suggesting the absence of non-response bias. The Harman one-factor method was used to assess

common method bias, exploratory factor analysis of each construct producing multiple factors

(Podsakoff et al., 2003).

For each construct, internal consistency was estimated using standardized Cronbach’s α

(Cronbach, 1951). Values of α in excess of 0.60 suggest that measurement scales are sufficiently

reliable (Nunnally, 1988). Cronbach’s for the four constructs ranged from 0.65 to 0.78.

Composite reliability, a more parsimonious measure of scale reliability, was also used to verify

the reliability of the constructs. Composite reliabilities in excess of 0.60 provided further

evidence of scale reliability (Podsakoff et al., 2003).

Structural Equation Modeling

The two-step structural equation modeling approach was used in which measurement

models were first tested individually and then simultaneously prior to testing the structural model

(Anderson and Gerbing, 1988). Analysis based on the maximum likelihood estimation method

was carried out using LISREL-SIMPLIS 8.72.

Measurement Models

The measurement scale for each latent variable was established by creating a reference

indicator and setting its value to one (Anderson and Gerbing, 1988). The EDI measurement

model has only three indicators and is thus a just-identified model with zero degrees of freedom.

Although a unique solution exists for parameter estimates in a just-identified model, one cannot

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reject the model due to it having zero degrees of freedom. While the model is thus not interesting

from a statistical perspective, factor loadings of its paths are statistically significant (Figure 2).

Each indicator loaded significantly on the construct providing evidence of convergent validity

(Jöreskog and Sörbom, 1993).

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Insert Figure 2

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The INFO measurement model exhibited evidence of correlation between the error terms

for two items related to formal and informal information sharing agreements with suppliers and

customers to facilitate collaboration (Q2A and Q2B). This is consistent with rapid advancements

in IT enabling supply chain members to e effectively collaborate and share information using

formal and informal agreements (Dröge and Germain, 2000; Sanders and Premus, 2005). A

corresponding error covariance term was added to the model. A second covariance term was

added between the need to communicate the firm’s future strategic needs (Q2C) and customers’

future strategic needs throughout the supply chain (Q2D). A firm committed to sharing

information on strategic needs with suppliers can be expected to see the value of sharing similar

information from customers. A third covariance term was added between the need to

communicate customers’ strategic needs (Q2D) and creating a compatible information system

with supply chain members (Q2E). The need to communicate future strategic needs will be

reduced if trading partners have compatible information systems that can exchange pertinent

information. Figure 2 shows the revised measurement model. Goodness of fit measures indicated

good model fit (χ2 = 5.73, df = 6, χ2/df = .96, RMSEA = .00, AGFI = .99, NFI = .99, CFI = 1.0).

Standardized factor loadings ranged from 0.45 to 0.73, exhibited the expected positive sign, and

were significant, thus demonstrating convergent validity.

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Analysis of the REL measurement model indicated the need to add error covariance

terms between the role of cultural match in supplier selection (Q3B) and both supplier

relationship (Q3C) and the firm’s demand/service flexibility in improving customer satisfaction

(Q3D). To build a mutually beneficial buyer-supplier relationship, there must be cultural

alignment between the buyer and the supplier. Over-emphasizing demand/service flexibility may

place unrealistic expectations on suppliers, and may indicate inadequate consideration of cultural

fit. Standardized factor loadings were again positive (0.32 to 0.69) and significant, and goodness

of fit indices consistent with good model fit (χ2 = 5.47, df = 3, χ2/df = 1.82, RMSEA = .04, AGFI

= .98, NFI = .99, CFI = .99).

Analysis of the PERF measurement model suggested that overall product quality (Q4B)

is correlated with overall customer service level (Q4E). This is consistent with high product

quality leading to high levels of customer service (Tan et al., 1998). Analysis also suggested that

strong overall competitive position (Q4D) can adversely affect return on assets (Q4B). This can

occur if significant capital investments are needed, for example in new equipment and/or

research and development, to achieve or maintain performance levels. Each indicator had the

expected positive sign and loaded significantly on the construct. The revised measurement model

(Figure 2) again fits the data well (χ2 = 4.54, df = 3, χ2/df = 1.51, RMSEA = .03, AGFI = .99,

NFI = .99, CFI = 1.0).

The four measurement models were tested simultaneously by allowing the constructs to

freely correlate with each other. Goodness of fit measures again indicated good fit (χ2 = 321.5,

df = 139, χ2/df = 2.31, RMSEA = .05, AGFI = .93, NFI = .94, CFI = .97). To test for

discriminant validity, correlations between each pair of latent variables were examined. All

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correlation coefficients were significant and less than 0.5 in value, consistent with a high level of

discriminant validity (Anderson and Gerbing, 1988, Table 1).

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Insert Table 1

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Structural Equation Model

With the exception of the 2 p-value, goodness of fit indices (χ2 = 321.5, df = 139, χ2/df =

2.31, RMSEA = .046, AGFI = .93, NFI = .90, CFI = .94) suggested that the saturated structural

equation model (Figure 3) fit the data well1. The structural equation model supports hypotheses

H1 (1 = 0.35) and H2 (2 = 0.49) that consideration of EDI capability has a positive impact on

information and relational alignment respectively. It also supports hypothesis H3 (4 = 0.27) that

information alignment has a positive impact on relational alignment, and hypothesis H6 (6 =

0.42) that relational alignment has a positive influence on firm performance. However, support is

not found for either consideration of EDI capability (H4) or information alignment (H5) having a

direct effect on firm performance. Both affect performance only indirectly via their impact on

supply chain relational alignment.

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Insert Figure 3

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1 2 statistics are sensitive to sample size and departures from the assumption of multivariate normality, large (n >

200) sample sizes tending to result in significant 2 statistics (Schumacker and Lomax, 1996). The ratio of 2 to

degrees of freedom is thus a preferred measure.

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Discussion and Managerial Implications

Support for hypothesis H1 is consistent with the results of studies suggesting EDI use or

adoption facilitates information sharing. The result here however is significant for two reasons.

First, it illustrates the importance of considering firm and partner EDI capabilities as a driver of

information sharing in the context of supplier management, and in particular when selecting and

evaluating suppliers. It is the information sharing capabilities EDI provides that motivate

information flows, not merely the use of the technology itself. It behooves firms to evaluate how

information can and will be used, not just what data elements will be shared. This is similar in

principle to the importance of administrative innovation described by Kim et al., (2006). Second,

it demonstrates the importance of considering the strategic value of information flows, not

merely their transactional value. It is thus pertinent to consider how information will be

leveraged and how technology must facilitate this.

Evidence of the positive relationship between the consideration of EDI capability and

relational alignment (H2) highlights the significance of considering how, and for what purpose,

information might be shared in the context of developing supply chain relationships. As

suggested by prior research, merely sharing information across firm boundaries in a timely

manner can facilitate relational alignment. However, consciously considering how internal and

partner EDI capabilities might play a role in serving customers suggests a more strategic

objective underlying information sharing. This has important consequences for relationship

development. This finding is consistent with the conclusions of Son et al., (2005) and Grover et

al., (2003) that effective EDI use enables organizations to establish cooperative relationships to

share vital information. Support for hypothesis H4 further demonstrates that the perceived value

of EDI in linking firms goes beyond data transfer. The commitment to share strategic and not

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just tactical information, and the development of the infrastructure to facilitate this, play a key

role in binding firms to each other in support of common goals, and is a source of competitive

advantage (Hammer, 2001). This finding supports the argument in the literature that information

alignment enhances coordination (Bensaou and Anderson, 1999; Kim et al., 2006), facilitates

development of close relationships (Bensaou and Anderson, 1999), and reinforces existing inter-

organizational structures (Chae et al., 2005).

It is the binding of firms based on EDI capability, strategic use of information, and a

commitment to achieving shared goals, that drives performance (H6). As suggested by prior

research, information sharing from a transactional perspective plays an important role in

enabling firms to work together to achieve positive outcomes. The results here suggest that what

motivates this exchange is equally important. Technologies such as EDI are tools, and as with

other tools, the scope of their use has limits. Leveraging the tool for competitive advantage

requires appropriate definition of the context in which it will be deployed and establishment of

the necessary infrastructure. The failure to support hypotheses H4 and H5 reinforces this

conclusion. Merely considering EDI capability to be important or aligning information sharing,

will not lead to performance improvements. At first glance, this may appear to contradict results

of studies of EDI use. However, prior literature has emphasized only direct linkages between

EDI use and performance and with few exceptions (e.g., Larson and Kulchitsky, 2000) did not

examine the role of mediating variables. The results here are significant in demonstrating the role

of these mediating variables – supply chain information and relational alignment.

The recently implemented Wal-Mart Remix initiatives support the findings and

demonstrate the critical role of supply chain information and relational alignment in improving

firm performance. As part of its quest to improve in-stock position and inventory turnover while

20 | P a g e

simultaneously reducing inventory, Wal-Mart embarked on the initiatives to limit inventory

growth to no more than half of sales growth (Hoffman, 2006). Wal-Mart asked suppliers to

deliver small quantities with high frequency to its distribution centers. However, this led to an

increase in the number of less-than-truckload (LTL) shipments from vendors and created

congestion at the distribution centers. To overcome this, third-party logistics providers were used

to consolidate LTL shipments from multiple vendors into truck-load shipments at five

strategically located consolidation centers throughout the U.S. Although the use of these logistics

providers added another layer to the distribution system, Wal-Mart’s Retail Link information

system allowed suppliers and logistics providers to coordinate shipment and order information

effectively. This would not have been possible if the suppliers’ information systems were not

compatible and aligned with the Retail Link system.

Another notable initiative associated with Remix is that a velocity-based approach

replaced the traditional category-based approach to managing the distribution network. The

5,000 items with the greatest turnover are delivered to stores in specially marked Remix trailers,

and goods transferred directly to display shelves instead of to the backroom. Small trolleys called

Rocket Carts that are narrow enough to navigate store aisles are used to restock empty shelves

during busy shopping hours. This eliminates the need to wait until store traffic is low and use

large pallets. The ability to restock during busy shopping hours allows Wal-Mart to reduce the

size of its display shelves, reduce inventory, and improve inventory turnover. In the fiscal year

ending January 31, 2007, Wal-Mart’s sales increased 10.45 percent but its inventory increased by

only 4.64 percent. The ability to exploit the Retail Link system to achieve information and

relational alignment with suppliers was a key driver of this improved performance by enabling

21 | P a g e

the sharing of demand information with suppliers and allowing them to track inventory in the

distribution system all the way to the store.

Conclusion

EDI has been viewed largely as a technology to allow firms to exchange data. However,

EDI also serves as a means for alignment around shared objectives. The results show that merely

considering EDI capability to be important or aligning information sharing will not lead to better

performance. Prior literature, with few exceptions, has emphasized direct linkages between EDI

use and performance without examining the role of mediating variables. The major contribution

of this study is in demonstrating the role of supply chain information and relational alignment as

mediating variables. The study not only illustrates the importance of attitudes towards EDI in

facilitating this alignment, it demonstrates that the value of EDI comes in part, if not

significantly, from efforts to build inter-firm relationships and aligning information flows in the

context of these relationships. Developing elements of the ‘soft’ infrastructure including

information and relationships is thus a key to enabling firms to work together for mutual benefit.

This in turn requires that firms carefully consider their own as well as partner EDI capabilities

when managing suppliers.

The study is not without its limitations. A challenge in conducting empirical research is

the difficulty of obtaining a adequate sample. Multiple data sources were used to develop the

sampling frame, respondents were pre-screened to ensure they had the knowledge and expertise

to provide valid responses, and the survey instrument was extensively tested to ensure questions

would be interpreted correctly. However, this cannot guarantee adequacy of the sample. This

limitation is compounded by the reliance on a single respondent per firm which precludes testing

for inter-rater reliability. The challenge of sampling, and specifically of acquiring sufficient data

22 | P a g e

from, for example, individual industry sectors, firms at different positions in the supply chain,

and partner firms with different power relationships, also precludes conducting detailed

contingency analysis. This however represents an opportunity for further research. Another area

where additional data can facilitate further study is the breadth of the supply chain that firms

actively engage. One might reasonably infer that information and relational alignment is related

to whether a firm engages only partners proximate in the supply chain or also partners who are

more than one tier away. Whether alignment drives broad engagement or the desire to involve

more distant partners drives alignment is unclear, but is an important issue, particularly with high

levels of outsourcing and a corresponding need to rely on supply chain partners. With

increasingly disaggregated global supply chains, this takes on even greater significance. An

additional avenue for future research is to examine, simultaneously, actual EDI capability and

use. This will make it possible to make nuanced judgments about the influence of EDI on supply

chain relationships, and help to develop a better understanding of the relationship between

information sharing strategy, tactics, and performance in a supply chain context. As firms

recognize the increasing importance of information that is rich in context as opposed to often

context free data, how they create synergy between IT tools and inter-organizational

relationships will take on greater significance.

23 | P a g e

Appendix

1. EDI Capability in Supplier Management (EDI)

How important are the following issues in your firm’s supply chain management efforts? (5 =

very important, 1 = not important)

A) Supplier EDI capability in their performance evaluation

B) Supplier EDI capability in supplier selection decisions

C) Your EDI capability in improving customer service

2. Supply Chain Information Alignment (INFO)



A) Use of informal information sharing agreements with suppliers and customers

B) Use of formal information sharing agreements with suppliers and customers

C) Communicating your firm's future strategic needs to your suppliers

D) Communicating customers’ future strategic needs throughout the supply chain

E) Creating a compatible information system with suppliers and customers

F) Contacting end users to get feedback on performance and customer service

3. Supply Chain Relational Alignment (REL)



A) Supplier volume flexibility in supplier performance evaluation

B) Cultural match in supplier selection decisions

C) Supplier relationships in supplier selection decisions

D) Your demand/service flexibility in improving customer satisfaction

E) Your customer service system in improving customer satisfaction

4. Firm Performance (PERF)

Please indicate the level of your firm’s performance compared to your major industrial

competitors in terms of: (5 = high, 1 = low)

A) Market share

B) Return on assets

C) Overall product quality

D) Overall competitive position

E) Overall customer service levels

24 | P a g e

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Table 1: Correlation Matrix of Latent Variables

Research Constructs EDI INFO REL PERF

EDI in Supplier Management (EDI) 1

Supply Chain Information Alignment (INFO) .430 1

Supply Chain Relational Alignment (REL) .437 .475 1

Firm Performance (PERF) .243 .201 .370 1

Note: all correlation coefficients are significant at p < .01

Supply Chain

Information

Alignment

(INFO)

Supply Chain

Relational

Alignment

(REL)

EDI in

Supplier

Management

(EDI)

Firm

Performance

(PERF)

H4

H1

H2 H6

H5

H3

Figure 1: Research Model and Hypotheses

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(A) Consideration of EDI Capability in

Supplier Management (B) Supply Chain Information Alignment

(C) Supply Chain Relational Alignment (D) Firm Performance

Figure 2: Measurement Models

PERF

Q4A

Q4B

Q4C

Q4D

Q4E

0.54

0.75

0.44

1.00

0.46

0.70

0.44

0.80

0.00

0.78

0.25

-0.31PERFPERF

Q4AQ4A

Q4BQ4B

Q4CQ4C

Q4DQ4D

Q4EQ4E

0.54

0.75

0.44

1.00

0.46

0.70

0.44

0.80

0.00

0.78

0.25

-0.31

INFO

Q2A

Q2B

Q2C

Q2D

Q2E

0.76

0.80

0.74

0.58

0.47

Q2F0.64

0.49

0.45

0.51

0.65

0.73

0.60

0.24

0.21

-0.12

INFOINFO

Q2AQ2A

Q2BQ2B

Q2CQ2C

Q2DQ2D

Q2EQ2E

0.76

0.80

0.74

0.58

0.47

Q2FQ2F0.64

0.49

0.45

0.51

0.65

0.73

0.60

0.24

0.21

-0.12

EDI

Q1A

Q1B

Q1C

0.84

0.70

0.68

0.30

0.51

0.53

EDIEDI

Q1AQ1A

Q1BQ1B

Q1CQ1C

0.84

0.70

0.68

0.30

0.51

0.53

REL

Q3A

Q3B

Q3C

Q3D

Q3E

0.54

0.44

0.32

0.69

0.61

0.71

0.81

0.90

0.52

0.62

0.23

-0.17

RELREL

Q3AQ3A

Q3BQ3B

Q3CQ3C

Q3DQ3D

Q3EQ3E

0.54

0.44

0.32

0.69

0.61

0.71

0.81

0.90

0.52

0.62

0.23

-0.17

Supply Chain

Information

Alignment

(INFO)

Supply Chain

Relational

Alignment

(REL)

EDI in

Supplier

Management

(EDI)

Firm

Performance

(PERF)

0.05*

0.35

0.49 0.42

-0.07*

0.27

* indicates insignificant path

Supply Chain

Information

Alignment

(INFO)

Supply Chain

Relational

Alignment

(REL)

EDI in

Supplier

Management

(EDI)

Firm

Performance

(PERF)

0.05*

0.35

0.49 0.42

-0.07*

0.27


Supply Chain

Information

Alignment

(INFO)

Supply Chain

Relational

Alignment

(REL)

EDI in

Supplier

Management

(EDI)

Firm

Performance

(PERF)

0.05*

0.35

0.49 0.42

-0.07*

0.27

Supply Chain

Information

Alignment

(INFO)

Supply Chain

Information

Alignment

(INFO)

Supply Chain

Relational

Alignment

(REL)

Supply Chain

Relational

Alignment

(REL)

EDI in

Supplier

Management

(EDI)

EDI in

Supplier

Management

(EDI)

Firm

Performance

(PERF)

Firm

Performance

(PERF)

0.05*

0.35

0.49 0.42

-0.07*

0.27


Figure 3: Structural Equation Model

Supply Chain Information and Relational Alignments ...

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