A Market Orientation in Supply Chain

8/3/2019 A Market Orientation in Supply Chain

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ORIGINAL EMPIRICAL RESEARCH

A market orientation in supply chain management

Soonhong Min & John T. Mentzer & Robert T. Ladd

Received: 8 January 2007 /Accepted: 9 March 2007 /Published online: 24 March 2007# Academy of Marketing Science 2007

Abstract Despite the logical association between market

orientation (MO) and the supply chain management

concepts of supply chain orientation (SCO) and supply

chain management (SCM), and the potential mediating role

of SCO and SCM in the MO-firm business performance

(PERF) relationship, there have been few, if any, attempts

to investigate MO in a supply chain context. Thus, this

study tests the relationships between MO, SCO, SCM, and

PERF. Results indicate MO has a strong, positive impact on

SCO and SCM. Interestingly, SCO was found to have the

largest direct influence on PERF, followed by MO,

followed by SCM. Managers should realize that SCO is

critical to fulfilling customer requirements, i.e., a firms

efforts to work with supply chain partners will not pay

off if the firm is not supply chain-oriented. Although

overshadowed by SCO, MO is still a foundation for

managing the supply chain and has a positive impact on

PERF. Equally important, the fact that the contribution of

SCM to firm performance is overshadowed by MO and

SCO does not mean SCM is irrelevant in corporate strategy.

Managerial and future research implications of these

findings are discussed.

Keywords Market orientation . Supply chain orientation .

Supply chain management

Introduction

Market orientation (MO) plays a central role in marketing

management and strategy, with focus on creating superior

customer value while pursuing profits (Slater and Narver

1994). Different authors (e.g., Kohli and Jaworski 1990;

Slater and Narver 1994) agree that a firms MO focuses on

specific behaviors. Kohli and Jaworski (1990) proposed

that MO is a set of company-wide implementing activities

of the marketing concept (a business philosophy) so that

a market-oriented firm practices the three pillars of the

marketing concept (customer focus, coordinated market-

ing, and profit orientation) to satisfy customers. Slater

and Narver (1994) argue their definition of MO is

commensurable with Kohli and Jaworski (1990) since MO

consists of three behavioral components (customer orienta-

tion, competitor orientation, and interfunctional coordina-

tion) each of which involves intelligence generation,

dissemination, and managerial action. Deshpande and

Farley (1998) also contend MO is the cross-functional

activities that create and satisfy customers through contin-

uous needs assessment. Thus, MO focuses on three

company-wide behaviorsgenerating, disseminating, and

responding to market informationand operationalizes the

marketing concept (cf. Jaworski and Kohli 1993).

J. of the Acad. Mark. Sci. (2007) 35:507522

DOI 10.1007/s11747-007-0020-x

S. Min

Division of Marketing and Supply Chain Management,

Michael F. Price College of Business,

The University of Oklahoma,

307 West Brooks Room 1,

Norman, OK 73019-4001, USA

e-mail: [email protected]

J. T. Mentzer (*)

Department of Marketing and Logistics,

The University of Tennessee,

310 Stokely Management Center,

Knoxville, TN 37996-0530, USA


R. T. Ladd

Department of Management, The University of Tennessee,

410 Stokely Management Center,

Knoxville, TN 37996-0530, USA

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There are, however, several gaps in MO literature. First,

although a positive relationship between a firms MO and

its performance was found in numerous studies, weak or

lack of association has also been reported. Facing some-

what disparate findings, authors (e.g., Matsuno et al. 2002)

explored moderating variables in the MO-performance path,

but research on mediators is less extensive (Han et al.

1998). Second, except for a few studies (e.g., Siguaw et al.1998), the conceptualization and implications of MO to

date have been mainly in the context of individual firms,

in spite of the growing importance of supply chain

management (SCM). Market oriented-firms aim to better

serve customer requirements based on market information

obtained and shared inside the firm in a coordinative man-

ner (Kohli and Jaworski 1990). Social network literature

(Lee et al. 2004) suggests external networks with suppliers

and other partners (a supply chain) provide a firm with

information on new technological and market opportunities

and collaboration to exploit opportunities. Thus, firms

interact with supply chain partners to acquire external

resources and the necessary information to offer products

that attract and retain customers and, accordingly, obtain

performance superior to competition (cf. Lee et al. 2004).

However, the value of supply chain social ties is contingent

on such firm internal capabilities as market sensing through

a market orientation (Day 1994). That is, although SCM

concepts as the source of additional resources may mediate

the MO-performance relationship, MO as the impetus for

SCM concepts may still have direct, positive impact on

firm performance.

Despite apparent logical association between MO and

SCM concepts and the possible mediating role of SCM

concepts in the MO-firm performance link, there have been

few, if any, attempts to investigate MO in a supply chain

context. Thus, this study contributes to the body of

knowledge by testing the relationships between MO, SCM

concepts, and firm performance to examine (1) contradic-

tory findings on the MO-firm performance link (i.e., does

MO directly influence performance or indirectly via a

mediating factor like SCM), and (2) the commonly

proposed SCM-firm performance link (e.g., Fugate et al.

2006). Investigating the relationship between MO and SCM

concepts expands the boundaries of both MO and SCM

research, and examines the idea of interfunctional integra-

tion both inside and outside the firm to create customer

value (Kotler 1997).

Supply chain management concepts

Mentzer et al. (2001, p. 4) describe a supply chain as a set

of three or more organizations directly linked by one or

more of the upstream and downstream flows of products,

services, finances, and information from a source to a

customer. Thus, the nature of a supply chain is compre-

hensive and membership is open to any firm that performs a

flow function, including suppliers, manufacturers, third

party financial providers, 3PLs, and market research firms.

Mentzer et al. (2001) differentiate between supply chains as

phenomena that exist, and management of those supply

chains. That is, whether a firm likes it or not, it operates insupply chains that consist of suppliers, distributors, and

various forms of intermediaries. However, it is not feasible

for a firm to closely work with all firms in the supply chain,

because not every firm is equally capable of, and/or critical

to, customer value creation. Moreover, supply chain relations

are costly to maintain (Burt 1992). Thus, each firm must be

selective in managing relationships with a limited set of

partners. As such, managed supply chains are organized and

operated through agreed-upon goals and activities of the

partners. Since the focal firm is inseparable from its managed

supply chain, but not necessarily from supply chains as

natural phenomena, SCM phenomenaovert and collective

efforts of supply chain partnersshould be examined in the

context of managed supply chains (Mentzer et al. 2001).

We propose that the SCM concept consists of different

terms to delineate different phenomena: a Supply Chain

Orientation (SCO) within a firm and Supply Chain Manage-

ment (SCM) across firms within a supply chain, both of

which are operationalizations of SCM philosophy. SCM

philosophy is a shared mental model or schema of joint

problem solving both inside and outside the firm within the

boundaries of a supply chain (cf. Madhavan and Grover

1998). That is, SCM philosophy is a team mental model,

based on shared prior knowledge of how things should be

(cf. Day and Nedungadi 1994). Welch and Wilkinson (2002)

propose such schemas as essential determinants of supply

chain relationships because it is the way managers make

sense of interactions taking place with other firms, and

represents a different kind of dynamic force shaping

relationships and networks. Specifically, SCM philosophy

(1) takes a systems approach to view the supply chain as a

whole rather than a set of fragmented parts, (2) seeks

synchronization of intrafirm and interfirm operational and

strategic capabilities into a unified, compelling marketplace

force, and (3) focuses supply chain partners on creating

customer value (Mentzer et al. 2001). Each supply chain

partner should arrange the systemic, strategic implications of

the coordinated activities in each supply chain process before

the partners perform joint actions to obtain improved,

balanced performance of individual firms and the supply

chain as a whole (Jennings and Mandani 1992). The

implication of SCM philosophy is that the focal firm is not

free from its macro environment (the managed supply chain)

since SCM philosophy steers and adjusts partners attitudes

toward collective actions within the managed supply chain.

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To initiate SCM philosophy, managers need specific

behavioral guidelines within the boundaries of the firm.

M en tz er e t a l. (2001) emphasize the importance of

embracing SCM philosophy within a firm and called it

Supply Chain Orientationimplementation by a firm of the

activities involved in systemically and strategically manag-

ing various flows in a supply chain. Without SCO inside a

firm, it is not possible to implement SCM philosophywithin the supply chain. SCM requires each firm in a

supply chain to be supply chain oriented, and to perform a

specific set of managerial actions within the supply chain in

a collective manner. Thus, Mentzer et al. (2001, p. 18)

define SCM as, the systemic, strategic coordination of the

traditional business functions and the tactics across these

business functions within a particular company and across

businesses within the supply chain, for the purposes of

improving the long-term performance of the individual

companies and the supply chain as a whole.

Organizations are multilevel systems in which micro

phenomena are embedded in macro contexts and macro

phenomenaemerge through the interaction and dynamics

of lower-level elements (Kozlowski and Klein 2000). A

managed supply chain is a multilevel system in which

supply chain partners are embedded. Thus, SCM phenom-

ena emerge through overt, collective efforts of supply chain

partners. This form of emergence is called composition,

which is based on assumptions of isomorphism (coales-

cence), and illustrates the convergence of similar low level

characteristics (supply chain partners actions) to generate a

higher level property (actions taken by a managed supply

chain as a whole) that is essentially the same as its

constituents. Our in-depth interviews revealed this type of

emergence: an interviewee stated, Our supply chain partner

thinks, breaths, and speaks as if our company. Firm

boundaries become blurred as firms become more depen-

dent on supply chain partners (Kotler1997), and every firm

function is included in SCM (Min and Mentzer 2000).

The relationship between SCO and SCM is explained by

the social network view. Hkansson and Snehota (1995)

propose three layers of business relationships and their

interplay in a supply chain setting: activity links, resource

ties, and actor bonds. Activities links (different firms

carrying out different parts of supply chain processes)

create unique performance for each firm, as well as other

firms involved in the business processes as a whole.

Resources uniquely available to each firm are tied together

(resources ties) to constitute new sources of capabilities. A

firms critical resources may extend beyond firm bound-

aries, and combine with those of other firms in unique ways

to create competitive advantage (Dyer and Singh 1998).

Actor bonds are prerequisites for activity links and resource

ties (Hkansson and Snehota1995). Firms in a supply chain

require actor bonds or interfirm ties (e.g., trust, commit-

ment, cooperative norms, shared identity), which both

constrain and enable behaviors (Tsai and Ghoshal 1998).

In the long term, actor bonds evolve, activity links and

resources ties change, and the three mutually adjust

(Hkansson and Snehota 1995). Eventually, such interfirm

cooperation translates into performance benefits for the

firms forming a network (Gulati 1998).

Days (1994) concepts of channel linking (relationship building) and channel bonding (interfirm cooperation) are

equivalent to Hknsson and Snehotas (1995) concepts of

actor bonds, and activity links and resource ties, respectively.

SCO established inside a firm in the form of actor bonds or

channel linking (e.g., trust, commitment, cooperative norms,

organizational compatibility, and top management support)

is a strong antecedent to SCM activities (activity links and

resources ties or channel bonding) across supply chain

partners. SCO and SCM are related, but different, concepts

in that SCO (actor bonds) is developed and maintained by a

firm, whereas SCM (activity links and resource ties) is

shared in relationships between supply chain partners.

As the previous discussion indicates, SCO and SCM

have much in common with MO: (1) creating value to

satisfy customers at a profit, (2) implemention through

interfunctional coordination, and (3) a strategic context.

There are differences, however: (1) MO concerns an

individual firm and is implemented within a firm, (2) SCO

concerns a supply chain and is implemented within a firm,

and (3) SCM concerns a supply chain and is implemented

by multiple firms within a supply chain. Based on the

similarities and differences between these concepts, we

investigate the strategic implications of the MOSCO

SCM path on firm performance by (1) examining the role

of MO in developing SCO and SCM, (2) confirming the

validity of the SCM constructs (SCO and SCM), and (3)

testing potential mediating effects of SCO and SCM on the

MO-firm performance relationship (Fig. 1).

Theoretical framework

The relationship between MO and firm performance has

been established in many studies (e.g., Jaworski and Kohli

1993; Matsuno et al. 2000; Slater and Narver 1994). Thus,

we posit a direct, positive impact of MO on firm perfor-

mance (PERF), but we also examine potential mediating

factors. MO enhances a firms business performance when it

is combined with the firms channel linking (SCO) and

channel bonding (SCM) capabilities (Day 1994). Market-

oriented firms realize the need for network competence,

defined as the degree of network management task

execution between firms (SCM) as well as the degree of

network management qualification possessed by people

handling the firms relationships (SCO) (Ritter et al. 2002).

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As such, if firms in a supply chain feel strongly tied (SCO)

and valuable information on customer needs is shared

between them (SCM), it is possible for the firms to collect

rich information about customer preferences and respond to

customer requirements. In sum, MO contributes directly to

firm performance, and indirectly via the SCOSCM path

across the boundaries of the firms in a supply chain.

Further, firms perform organizational learning, an inher-

ent, inseparable part of MO, through such external partners

as customers, distributors, and suppliers (Slater and Narver

1995). All strategic alliances are firm co-alignments where

partners seek to learn and acquire from each other products,

skills, technologies, and knowledge not available to com-

petitors (Lei et al. 1997). Strategic alliances are important

tactics within and across firms to learn and acquire new

capabilities (Mowery et al. 1996). Thus, MO cannot be

separated from interfirm relationships with customers,

suppliers, and other key constituencies (cf. Webster 1992).

Therefore, MO drives a firm toward a systems approach

(SCO) and cooperative actions with other firms (SCM) to

deal with the complexity of learning and building new

sources of competitive advantage beyond the firm.

Firm information generation, storage, and utilization are

essential to SCM. A market-oriented firm produces and

stores market information that is needed to build, maintain,

and enhance a systems approach to cooperative relationships

with other firms. A key component of SCM is information

sharing between supply chain partners (Min et al. 2005).

Information gathered via MO by individual firms can serve

as the basis for shared information among supply chain

partners, and thus, MO indirectly contributes to SCM. A

firm with information about customers, suppliers, and

sociopolitical and technological trends can answer such

questions as which supply chain best serves its customers,

with which firms to manage a supply chain, and what

should be accomplished in the supply chain.

Finally, many researchers found strong evidence of a positive

MOPERF association, whereas several researchers found

either a weak or nonexistent association. Although research on

moderators of the MOPERF relationship has been substantial

(e.g., Deshpande and Farley 1998), less exists on possible

mediators (Han et al. 1998). Considering that the MO-firm

performance path is well established and that there are potential

mediators of the relationship, we propose the following:

H1a: Firm MO directly and positively contributes to firm

business performance.

H1b: Firm MO positively contributes to firm business

performance indirectly via the SCOSCM path.

Markets include customers and distributors as well as

exogenous forces that affect their needs and preferences

(Kohli and Jaworski 1990) and interfirm collaboration

allows firms to generate intelligence about creating superior

customer value (Slater and Narver 2000). Thus, it is

important to understand both consumer behavior and the

trade (e.g., Lusch and Brown 1996). While the conceptu-

alization of MO suggests information sharing inside the

firm (Jaworski and Kohli 1993), SCM asserts broader

information sharing across firms, accessing supply chain

partners expertise, databases, and information systems

(Mentzer et al. 2001). Therefore, if a learning network is

based on openness (SCO) and cooperation (SCM) across

firms, the network enables firms to absorb, assimilate, and

apply external information to knowledge in each firm

(Dickson and Farris 2001). As such, a market-oriented firm

should be motivated to be supply chain oriented to obtain

Figure 1 The scope of the study and an overview of the structural model.

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information from supply chain partners. Siguaw et al.

(1998) found firm MO affects the other partners trust,

commitment, and cooperative norms, conceptualized in this

study as components of SCO. A market oriented firm

possesses a knowledge base, and thus, should recognize the

systemic, strategic implications of the managerial activities

involved in the various flows in a supply chain.

H2: Firm MO directly and positively contributes to firm

SCO.

Supply chain oriented firms build and maintain internal

behavioral elements (trust, commitment, cooperative

norms, organizational compatibility, and top management

support) to develop relationships with supply chain partners

(Mentzer et al. 2001). The dimensions of SCO are

evidenced in numerous studies (see Mentzer et al. 2000

for a review). Among these dimensions of SCO, trust and

commitment are the most mentioned relational variables,

both of which are proposed to promote intra-network

collaboration (c.f., Tsai and Ghoshal 1998). Cooperative

norms and organizational compatibility (business philoso-

phies, goals, and management style), however, regulate

intra-network collaboration, and shared values and norms

across firms affect the development and management of

supply chain partnerships (Park and Ungson 1997). In ad-

dition, top management glues together the sub-dimensions

of SCO, because without top management support and

recognition, members of the firm are not willing to pursue a

SCO that requires time, effort, and resources.

The key components of SCM are collective efforts for

managing supply chains as a whole (Cooper et al. 1997).

There should be agreement on the vision and focus of

serving customers (Lambert et al. 1998). Mutually sharing

information among supply chain members is required,

especially for planning, integrating, and monitoring pro-

cesses (e.g., Global Logistics Research Team at Michigan

State University 1995). Effective SCM requires sharing

risks and rewards to generate competitive advantage (Cooper

et al. 1997). Cooperationmutual, coordinated activities

performed by firms in a business relationship to produce

superior outcomes mutually expected over time (Anderson

and Narus 1990)among supply chain members is also

required. SCM requires partners to build, maintain, and

enhance long-term relationships (Mentzer et al. 2001).

Unless inter-firm relationships are maintained and further

developed while waste is reduced, coordinated actions to

dynamically respond to the needs of end customers in a

changing market environment may not be possible (Greene

1991). Finally, SCM practices (e.g., Efficient Customer

Response, Quick Response, Vendor Managed Inventory,

Collaborative Planning, Forecasting, and Replenishment)

require supply chain leadership to coordinate activities

across supply chain partners.

Although SCO and SCM are conceptualized in the

context of supply chain relationships, the locus of each

concept is different. SCO is a firms unilateral policy based

on past interactions with, and future expectations of, supply

chain partners. In contrast, SCM is observable, multilateral

efforts to manage supply chain processes in which all

supply chain partners participate. Accordingly, the mea-

surement scales used in this study (See Appendix) areworded to reflect the different loci of SCO (our business

unit) and SCM (our supply chain members).

Social categorization theory suggests fewer and more

intense relationships (e.g., managed supply chains) build

such relational variables as trust, commitment, cooperative

norms, and compatibility (SCO) (cf. Tajfel and Turner

1986), all of which promote supply chain information

sharing and collaboration. These relational variables are

prerequisites for firms to cooperate to accomplish common

goals (SCM). Where parties share goals, values, and

affective attachment, they act for the benefit of one another

(Gundlach et al. 1995). Furthermore, a firms internal

readinessinternal resources for networking, network orien-

tation of personnel, integration of intra-firm communica-

tion, and corporate culture open to external networkingis

an antecedent to successful execution of networking with

supply chain partners (Ritter et al. 2002). A firms internal

capabilities to strategically coordinate such activities as

alliance planning, negotiation, management, and termina-

tion and to manage alliance-related knowledge inside the

firm lead to strong, harmonious alliances and alliance-based

organizational learning (Kale et al. 2002)all parts of

SCM.

H3: Firm SCO directly and positively contributes to

SCM.

SCO directly influences firm performance. Firm trust and

commitment toward channel partners lead to better firm

financial performance (Siguaw et al. 1998). Firm cooperative

norms positively impact marketing and logistics perfor-

mance (Cannon et al. 2000). Trust positively affects a firms

cost savings and market share growth (Dyer and Chu 2003).

On the other hand, interfirm cooperation (SCM) mediates

the effect of SCO on firm performance. Trust promotes

interfirm coordination that, in turn, produces higher profit

(Jap 1999), and there is a positive trust-interfirm collabora-

tion-performance path (Hewett and Bearden 2001).

H4a: Firm SCO directly and positively contributes to firm


H4b: Firm SCO positively contributes to firm business

performance indirectly through SCM.

Firms pool skills and resources with supply chain

partners to achieve higher performance (cf. Lusch and

Brown 1996). Heide and John (1992) discussed quasi-

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integration, achieved in interfirm relationships by estab-

lishing vertical control for efficiency reasons. We propose

that managing a supply chain requires each firm to perform

a set of managerial actions in a collective manner under

supply chain leadership. Consequently, successful cooper-

ation in any managed supply chain represents a means for

each firm to improve its outcomes. SCM pursues lower

total required resources to provide the necessary customerservice (Cooper and Ellram 1993), and improve customer

service through increased product availability and reduced

order cycle times (Min and Keebler2001). As such, SCM is

concerned with improving efficiency (cost reduction) and

effectiveness (customer service) in a strategic context to

obtain competitiveness that improves profitability of indi-

vidual firms and the supply chain as a whole. For effective

survey-based data collection and analysis, the scope of

testing the hypotheses in this study was limited to the

SCMPERF path for individual firms (Fig. 1). Thus, testing

the performance of a supply chain as a whole is left for

future research.

H5: Firm SCM directly and positively contributes to firm


Methodology

Structural Equation Modeling (SEM), using SPSS-AMOS

5.0, was the main statistical analysis tool to purify

measurement items and test hypotheses. Target firms were

not limited to one industry, so a random sample was drawn

from the Council of Supply Chain Management Profes-

sionals. Target respondents were senior executives able to

identify at least one supply chain to which their firms

belong and responsible for SCM. There was a concern that

individuals in different functions (i.e., marketing versus

SCM) have unique perspectives on MO. Based upon

exploratory in-depth interviews with 28 senior executives

at 20 companies, it was concluded that target respondents

were qualified to provide valid responses to MO items.

During the pretest, t-tests were conducted on 30 pairs of

SCM respondents and their internal counterparts in mar-

keting, comparing responses on 22 MO questions. Results

support the contention that SCM respondents were quali-

fied to answer MO questions.1

Since managed supply chain relationships develop

common knowledge and understanding between partners

about each other and the ways they can and should interact

(Wilkinson and Young 2002), use of single informant

design was justified by multi-level theory (cf. Kozlowski

and Klein 2000)a single informant can provide relevant

data to measure higher level properties that emerge from

low level characteristics if descriptions of the observable, as

opposed to emotions, are measured. Thus, the SCM

measurement items address what the focal firm does with

its supply chain partners in a coalescent manner, usingobservable behavior-oriented items that help respondents

think about SCM activities objectively. Further, a single

informant is appropriate when the informant has unique

access to relevant information (Kozlowski and Klein 2000).

The key in a single informant design is to find the most

suitable respondent (John and Reves 1982). In this study,

respondents were able to identify at least one supply chain

to which their firms belong, and were well exposed to SCM

issues (more than 80% of the respondents held high ranking

corporate positions such as CEO, COO, CLO, President,

Vice President, General Manager, or Director, and the rest

held senior SCM positions).

Packets (cover letter, questionnaire, and return postage)

were distributed in three waves to 2,680 target respondents

(1,312 in the pretest and 1,368 in the final test) and 442

usable responses (140 in the pretest and 302 in the final

test) were received, for effective response rates of 12.4 and

24.67%, respectively, after undeliverable questionnaires

were eliminated. Nonresponse bias in both the pretest and

final test was checked by comparing early and late re-

spondents for all constructs through ANOVA, and produced

no significant differences (Armstrong and Overton 1977).

Nonresponse bias in the final test was also checked by com-

paring, through ANOVA, all respondents with 30 randomly-

contacted non-respondents for five non-demographic items

in the questionnaire (Mentzer and Flint 1997). No statisti-

cally significant differences were found, and so, nonre-

sponse bias was not considered a problem.

Measurement scales

MO, SCO, SCM, and PERF were proposed as second-order

constructs, and the items used to measure them as indirect

reflective measures (Edwards and Bagozzi 2000) of both

the second and first order factors associated with them

(Gerbing and Anderson 1988). Only in this way can cause

and effect relationships among the four general constructs

be viewed as important. Previous studies provided items

adoptable or adaptable to measure the constructs of MO,

SCO, SCM, and PERF. The adopted/adapted items were

tested for validity and reliability, along with newly

developed items, in the process of academic expert review,

industry expert debriefing, pretest, and final test. Some

items were newly developed based upon the literature, 28

in-depth interviews and debriefings with executives from

1 A difference was found for only one item (MODISS #1, a=0.01).

Since both groups had similar response patterns (5.83 for marketing

and 4.80 for SCM, both above the neutral point on the 1 to 7 scale),

we concluded there is no strong evidence the groups are different in

responding to MO questions.

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20 companies, and the pretest. To develop new items, the

iterative process recommended by Gerbing and Anderson

(1988) and Bienstock et al. (1997) was followed.

The Matsuno and Mentzer (2000) MO scaleintelligence

generation (MOGEN), intelligence dissemination (MO

DISS), and responsiveness (MORESP)was adopted for

this study. This MO scale is an enhanced measure of MO

that outperforms the Jaworski and Kohli (1993) MARKORscale in terms of psychometric properties under the same

conceptualization of MO (i.e., an implementation of the

marketing concept). The items to measure SCO were

borrowed from several studies and modified (based upon

qualitative interviews) to reflect supply chain relationships

rather than the dyadic interfirm relationships that were the

focus of the previous studies. The items for credibility

(SCOCRED) and commitment (SCOCOMM) were adap-

ted from Siguaw et al. (1998), benevolence (SCOBENE)

from Kumar et al. (1995), cooperative norms (SCONORM)

from Cannon and Perreault (1999), organizational compat-

ibility (SCOCOMP) from Bucklin and Sengupta (1993),

and top management support (SCOTOPM) from Jaworski

and Kohli (1993). The items to measure SCM tap such

integration factors as agreement on SCM vision and focus

(SCMVISN), information sharing (SCMINFO), supply

chain cooperation (SCMCOOP), process integration

(SCMINTG), and supply chain leadership (SCMLEAD);

as well as such relationship factors as risk and reward

sharing (SCMRISK) and building, maintaining, and en-

hancing long-term relationships (SCMREL). All SCM

items were newly developed, though informed by the

literature (e.g., Bowersox et al. 1999) and the qualitative

interviews.

Since MO, SCO, and SCM are inter-functional in nature,

the performance scale is a combination of financial (ROA,

ROI, and ROS), marketing (sales growth and market share

growth), and logistics (availability, product and service

offerings, and timeliness) measures widely used in the

literature to reflect the multidimensional nature of firm

performance. Items to measure profitability (PERFPROF)

and growth (PERFGROW) were adapted from Matsuno et al.

(2000). Items to measure availability of products and services

(PERFAVAI), product and service offerings (PERFP&S),

and timeliness (PERFTIME) of a firm were adapted and

modified from the Global Logistics Research Team at

Michigan State University (1995), Bienstock et al. (1997),

and Bowersox et al. (1999). The rest were developed based

on the literature (e.g., Bienstock et al. 1997; Cooper and

Ellram 1993) and the interviews.

Due to practical considerations discussed earlier, only the

performance of individual firms was measured in this study.

Although firm performance has been measured subjectively

(e.g., Golden 1992) or objectively (e.g., Cronin and Page

1988), researchers using both subjective and objective

measures found a strong correlation between them (e.g.,

Robinson and Pearce 1988). Thus, antecedent justification

exists for using self-report perceptual performance measures.

Following Matsuno and Mentzer (2000), comparison mea-

sures (performance relative to major competitors) were

adapted to provide respondents with an anchor point to

more objectively assess firm performance.

Scale purification

The primary tools for measurement scale purification and

validation included Confirmatory Factor Analysis (CFA)

for validity, reliability or correlation analysis for internal

reliability, and qualitative analysis in both the pretest and

the final test (cf. Bienstock et al. 1997). The maximum

likelihood estimation (MLE) method was employed in CFA.

Based on the results of CFA and qualitative assessment of

the pretest data, a final test survey was prepared with the

reduced set of 96 items. After the two stages of the scale

refinement process (pretest and final test), 80 items were kept

(see Appendix). Cronbachs a values (or bivariate correla-

tion) for the final measurement model are presented in the

Appendix.

Justification for our use of the four general constructs

during hypotheses testing was made using an extension of

Widamans (1985) comparison models for convergent and

discriminant validity. The three comparison models include

Model 0 (individual items as unique factors in a construct),

Model 1 (individual items loaded on 1 first order factor),

and Model 2 (individual items loaded on any one of the

appropriate first order factors that, in turn, are loaded on the

second order factor). A significant improvement in fit of

Model 1 over Model 0 provides evidence of convergent

validity; a similar improvement in fit between Models 2 and

1 provides evidence of discriminant validity (Widaman

1985). To these models, we added Model 3, which allows

free association of the first-order constructs of Model 2.

Comparison of Models 2 and 3 allows assessment of the

measurement efficiency of using 4 second-order constructs

as opposed to 21 first-order constructs. Table 1 presents

these comparison models for each of the four general

constructs addressed in this study, along with similar

analysis addressing all four second-order constructs simul-

taneously. Using the absolute difference (Chi Sq.), root

mean square error of approximation (RMSEA), and

comparative fit index (CFI) as indicators, Model 1 was

consistently superior to Model 0 (convergent validity), and

Model 2 was consistently better than Model 1 (discriminant

validity). While Model 3 was better than Model 2 in

absolute terms (Chi Sq. tests), it shows only minimal

improvement in fit (RMSEA and CFI) and is always

inferior to Model 2 when the parsimony of the model is

considered (CAIC). These results suggest both discriminant

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and convergent validity for each construct considered in

this study, and the relative efficacy of using the second-

order factors in the hypotheses tests. Model 2 for all

constructs served as the measurement model on which all

subsequent hypotheses tests were conducted.

CFI values above .90 indicate good fit (Bentler 1990).

CFI of .865, although acceptable, falls below that level. CFI

for the residual model was acceptable when either SCO or

SCM was removed. Thus, before nomological validity was

assessed with the structural model, a comparison model test

Table 1 Model comparisons for convergent and discriminant validity tests

Model # and description Order and fit Chi-sq df Difference

Chi-sq

df-diff p-diff RMSEA p-Close CAIC CFI

Marketing orientation (MO)

0: No factors 3Unacceptable 1,295.1 136 0.168


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was performed to assure that SCO and SCM are closely

related but different concepts: Model A with SCO and SCM

as two correlated but distinctive second order factors, and

Model B with one second order factor to which all the first

order factors of SCO and SCM converged. The model

comparison yielded a Chi sq. difference of 264.5 at 2 df, and

represented significantly better fit for Model A (Table 2).

Thus, based upon the theory and the empirical test, SCOand SCM are related but different concepts.

Finally, since we used single-informants and SCO, SCM,

and PERF were believed to be closely related, we tested for

common-method bias, in which the extent of the relation-

ships might be inflated (Podsakoff and Organ 1986).

Common-method bias was checked with one-factor analy-

sis using Exploratory Factor Analysis (EFA) with varimax

rotation to see if only one general factor arises from all the

indicator variables or if one dominant factor explains most

of the covariance of the variables (MacKenzie et al. 2001).

The EFA results indicate that 14 different factors have

Eigen values of 1 or higher and the first factor explained

only 25 % of the variance. Thus, common-method bias was

not considered an issue.

Hypotheses testing

The structural model was constructed for hypotheses testing

by a partial aggregation approach in which a second-order,

higher-order latent variable was represented by multiple

first-order variables, each of which is represented by two

composites of 24 measurement items (Bagozzi and

Heatherton 1994). The proposed Test Model showed good

fit (CFI of 0.92 and NNFI of 0.91). RMSEA indicated

excellent fit (0.048) (Browne and Cudeck 1993). The

standardized coefficient weights and critical ratios (CR)

for each causal path are provided in Table 3. Both the direct

MOPERF path (H1a) and the indirect MOSCOSCM

PERF path (H1b) were rejected (CR for MOPERF of 1.89

(a=0.06) and for SCMPERF of1.50 (a=0.13)). H2 was

supported (CR for MOSCO of 4.88 (a=0.01) and the

standardized weight of 0.75). H3 was also supported (CR

for SCOSCM of 7.12 and the standardized weight of 0.67

(a=0.01)). H4a was also confirmed (CR= 2.15 for SCO

PERF and the standardized weight was 0.40 at a=0.05).

Finally, neither H4b nor H5 was supported because the CR

for SCMPERF was 1.50 (a=0.13). In sum, although MO

has a strong, positive impact on SCO, which has a strong,

positive influence on both SCM and PERF, neither the

direct MOPERF nor the indirect MOSCOSCMPERF

path was supported. The summary statistics of Hypotheses

15 are presented in Table 4.

Discussion and Post Hoc analysis

Contrary to many previous studies, a positive link between

MO and firm performance was not confirmed (H1a). Against

the theory proposed in this paper, the indirect contribution

of MO to firm performance via the SCOSCM path (H1b)

was also not supported. As theorized, however, a positive

MOSCO path was found (H2), as was a relationship

between SCO and SCM (H3). Mentzer et al. (2001)

proposed that firms implementing SCM collectively in a

supply chain must first have and implement a SCO inside

their firms, and thus, SCO is antecedent to SCM. The direct

impact of SCO on firm performance was supported (H4a)

while the indirect impact via SCM was not (H4b). That is,

internal firm readiness for SCM is essential for managing

supply chain processes across firms and improving firm

performance. Surprisingly, a significant SCMPERF path

was not found (H5).

To better understand the findings, we tested two post hoc

models (Fig. 2). In Post Hoc Model 1 the direct path between

SCO and PERF was removed. The rationale was that as both

the MOPERF and SCMPERF relationships were well

grounded theoretically and empirically, we suspected the

stronger influence of SCO on PERF overshadowed the

relatively weaker impacts of MO and SCM on PERF. Post

Hoc Model 1 demonstrated good fit (CFI=0.92, NNFI=0.91,

RMSEA=0.048), and as hypothesized, the MOPERF path

became statistically significant (CR=4.30, a=0.01). Appar-

ently, the weaker, positive impact of MO on PERF was

overshadowed by the stronger influence of SCO in the Test

Model. However, the SCMPERF path remained insignifi-

cant (CR=0.60, a=0.55) (Table 5). The insignificant

SCMPERF path in Post Hoc Model 1 led us to test Post

Hoc Model 2, in which both the MOPERF and SCOPERF

paths were removed. Post Hoc Model 2, which also showed

Table 2 Distinctiveness between SCO and SCM

Model # and description Order and fit Chi-sq df Difference

Chi-sq

df-diff p-diff RMSEA p-Close CAIC CFI

A: One factor 2Close 2,450.49 1,163 0.061


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good model fit (CFI= 0.91, NNFI=0.91, RMSEA=0.050),

confirmed a positive, significant relationship between SCMand PERF (CR=4.04, a=0.01) (Table 5). Thus, we argue

that the positive SCMPERF path is overshadowed by the

stronger impacts of MO and SCO on firm performance.

There are several possible explanations for the weaker effect

of SCM on firm performance. First, performance benefits of

a managed supply chain as a whole may improve dispro-

portionately for each supply chain partner. Second, there may

be a SCM-supply chain performance-firm performance path,

i.e., if a supply chain as a whole achieves higher levels of

efficiency and effectiveness, each partner benefits from the

supply chain performance. Thus, to properly capture firm levelperformance benefits derived from supply chain performance,

supply chain-specific performance measures should be devel-

oped in future research. Finally, the positive effect of SCM

may be realized only in the long run due to the complexity of

implementing SCM across firm boundaries and, in many

cases, across national borders (cf. Mentzer et al. 2001). On

average, U.S. firms have been actively involved in SCM for

less than 5 years, which has left individual partners with as yet

unrealized benefits from SCM (Min et al. 2005). Since this

Table 4 Summary statistics of hypotheses testing results: H1 through H5

Hypotheses Path(s) tested Reg. weight Std. error Std. weight CR Accept/ reject

H1a: MO PERF MO PERF 0.51 0.30 0.30 1.90 Rejected

H1b: MO SCO SCM PERF SCM PERF 0.09 0.06 0.15 1.50 Rejected

H2: MO SCO MO SCO 1.02 0.21 0.75 4.88 Accepted

H3: SCO SCM SCO SCM 1.50 0.21 0.68 7.12 Accepted

H4a: SCO PERF SCO PERF 0.49 0.23 0.39 2.15 Accepted

H4b: SCO SCM PERF SCM PERF 0.09 0.06 0.15 1.50 Rejected

H5: SCM PERF SCM PERF 0.09 0.06 0.15 1.50 Rejected

Table 3 Final SEM estimates, the partial aggregation structural model

Path Std. weights Critical ratios P

SCO MO 0.75 4.88 0.01

SCM SCO 0.68 7.12 0.01

PERF MO 0.30 1.89 0.06

PERF SCO 0.39 2.15 0.03

PERF SCM 0.15 1.50 0.13

Intelligence generation MO 0.67 4.75 0.01

Intelligence dissemination MO 0.82 5.46 0.01

Responsiveness MO 0.67 (Fixed)

Availability PERF 0.61 6.17 0.01

Product and services offering PERF 0.69 6.52 0.01

Timeliness PERF 0.60 5.65 0.01

Profitability PERF 0.69 (Fixed)

Growth PERF 0.63 7.54 0.01

Credibility SCO 0.61 (Fixed)

Benevolence SCO 0.60 6.37 0.01

Commitment SCO 0.68 4.18 0.01

Cooperative norm SCO 0.79 7.65 0.01

Compatibility SCO 0.82 8.00 0.01

Top management support SCO 0.72 6.90 0.01Supply chain vision SCM 0.77 13.07 0.01

Information sharing SCM 0.68 11.19 0.01

Risk and reward sharing SCM 0.86 15.94 0.01

Cooperation SCM 0.95 (Fixed)

Process integration SCM 0.98 15.94 0.01

Long-term relationships SCM 0.87 15.18 0.01

Supply chain leadership SCM 0.62 10.02 0.01

Only first and second order factors appear in this table.

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study captured only a snapshot of SCM, future longitudinal

studies should examine SCM-based performance, and resul-

tant firm performance benefits.

Implications

Managers should realize that SCO is critical to fulfilling

customer requirements. As the results illustrate, SCO

mediates the relationship between MO and business

performance. That is, a firms efforts to work with supply

chain members will not pay off if the firm is not supply

chain-oriented. Although overshadowed by SCO, MO is

still a foundation for managing the supply chain. MO has a

positive impact on firm performance (when SCO is

controlled) and, thus, implementing MO is not the

responsibility of marketing alone. Everyone in the firm

should promote MO and SCO inside the firm to create

effective SCM across the supply chain. Equally impor-

tantly, the fact that the contribution of SCM to firm

performance was overshadowed by MO and SCO does

not mean SCM is irrelevant in corporate strategy. Supply

chain partners should devise profit-sharing plans that allow

performance gains via collective efforts to be split to every

partners satisfaction. Joint performance metrics and profit

sharing plans should be included in long-term contracts,

and continuous adjustments made to perfect such complex

collaboration as SCM requires. Finally, managers should

use the framework of this research (the MOSCOSCM

PERF path) to diagnose business performance to find out

whether their lack of MO or SCO hinders managing theirsupply chains and obtaining better performance.

This study also offers a conceptualization of SCO as an

operationalization of supply chain philosophy that is

actuated inside individual firms, and SCM as the sum of

all management actions undertaken to realize that philoso-

phy across firms. Further, the specifics of implementing

SCO within a firm and SCM across firms were docu-

mented. With such guidelines, managers should realize the

collective implementation of SCM in the supply chain must

first have SCO inside the firm. Managers can also use the

SCO and SCM measurement items in the Appendix to

evaluate their performance.

The theory of MO in SCM means expansion of the

domain of marketing by combining an important concept in

marketing (MO) with one in business (SCM). Despite the

long-standing argument that the marketing concept (the

philosophical foundation of MO) is an important business

philosophy, the investigation of the role of MO outside the

firm has been limited. In this study, however, MO was

Table 5 Changes of statistical significance on proposed causal paths and model comparisons

Models Test model Post hoc model 1 Post hoc model 2

Path tested Std. weight CR P Std. weight CR P Std. weight CR P

MO PERF 0.30 1.90 0.06 0.61 4.30 0.01 NA NA NA

MO SCO 0.75 4.48 0.01 0.79 5.00 0.01 0.74 4.63 0.01

SCO SCM 0.68 7.12 0.01 0.67 7.13 0.01 0.69 7.10 0.01

SCO PERF 0.39 2.15 0.03 NA NA NA NA NA NA

SCM PERF 0.15 1.50 0.13 0.05 0.59 0.55 0.30 4.04 0.01

Model comparison Post hoc model 1Test model Post hoc model 2Test model

Chi sq. 1343.351338.98=4.37 1381.511338.98=42.53

Df 794793=1 795793=2

Figure 2 Post Hoc test models.

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hypothesized to nurture a systems approach to see the

supply chain as the source of necessary resources and skills

for a firms success, promoting cooperative partner activ-

ities, and thus, extends the domain of MO research to other

disciplines. The confirmed MOSCOSCM path supports

assertions (Day 1994) that MO has positive impacts on

functional coordination with suppliers, distributors, and

consumers.This study also raises the need for further building and

testing of MO in SCM theory. For example, although the

finding that MO-firm performance is mediated by SCO

supports existing literature that posits MO is not sufficient

for a firms market competitiveness (e.g., Han et al. 1998),

further research is needed to investigate any firm-specific or

market-specific conditions that might trigger the mediating

role of SCO on MOPERF path. As such, this study may

help researchers further understand potential limitations of

the role of MO, as well as its interactions with environ-

mental factors while influencing firm performance. Finally,

although the purpose of this study was to explore the causal

relationships between the second-order constructs, the

causal relationships between the various first-order con-

structs provide a fertile area for future research.

Through the literature review and executive interviews,

we adopted and tested a definition of SCO and SCM.

However, theory development in SCM research needs

further advancement. We do not argue that our conceptu-

alization of SCO is complete, or that it is the only

antecedent of SCM. Constructs such as alliance capability

(Kale et al. 2002), and network competence (Ritter et al.

2002) are potential dimensions of SCO. What is common

across different studies, including ours, is that before a set

of activities are implemented across supply chain partners,

each individual partner should be ready to contribute

particular parts of the collective effort. Unless the focal

firm is ready to actively pursue cooperation with other

firms, SCM cannot be successfully accomplished. Contrary

to the commonly accepted proposition that SCM has strong

positive impact on firm performance (e.g., Fugate et al.

2006), however, the impact of SCM on PERF was weak.

As discussed earlier, the weak SCMPERF link may be because supply chain performance mediates the SCM

PERF link or because SCM only affects firm long-term

performance due to the complexity of operationalizing

SCM across firms. Thus, future research is called for to

investigate the role of supply chain performance and/or the

longitudinal effect of SCM on firm performance.

Finally, we believe single informant design in SCM re-

search is, though theoretically and methodologically ade-

quate, not ideal. A multiple informant design with triadic

data (supplier firm, focal firm, and customer firm) more fully

reflects the supply chain. Although Kozlowski and Klein

(2000) propose a single informant design is relevant in

multilevel analysis if observable, descriptive data are

collected from well-informed respondents to measure com-

position-type emergence, they recommend both within-group

(within managed supply chains) and between-group (be-

tween managed supply chains) variance whenever possible.

Identifying multiple, well-qualified respondents in triads is

problematic, not to mention the difficulty of obtaining a

reasonable response rate (SEM requires 80 items5 =400

triads, or 1,200 matched respondents). Although potential

common method bias was not found in our study, we do

hope future research arises in which triadic data are collected

to test both within-group and between-group variance to

further our understanding of SCM.

Appendix

Table 6

Table 6 Measurement item descriptions

Measurement items

MOGENE (Intelligence generation): Cronbachs a=0.66a

We poll end users at least once a year to assess the quality of our products and services.

In our business unit, intelligence on our competitors is generated independently by several departments.We periodically review the likely effect of changes in our business environment (e.g., regulation) on customers.

In this business unit, we frequently collect and evaluate general macro economic information (e.g., interest rate, exchange rate, GDP, industry

growth rate, inflation rate).

In this business unit, we collect and evaluate information concerning general social trends (e.g., environmental consciousness, emerging

lifestyles) that might affect our business.

In this business unit, we spend time with our suppliers to learn more about various aspects of their business (e.g., manufacturing process,

industry practices, clientele).

MODISS (Intelligence dissemination): Cronbachs !=0.84

Marketing personnel in our business unit spend time discussing customers future needs with other functional departments.

Our business unit periodically circulates documents (e.g., reports, newsletters) that provide information on our customers.

We have cross-functional meetings very often to discuss market trends and developments (e.g., customers, competition, suppliers).

Appendix

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Table 6 (continued)

Measurement items

Technical people in this business unit spend a lot of time-sharing information about technology for new products with other departments.

Market information spreads quickly through all levels in this business unit.

MORESP (Response to intelligence): Cronbachs !=0.70

For one reason or another, we tend to ignore changes in our customers product or service needs. (R)

The product lines we sell depend more on internal politics than real market needs. (R)We are slow to start business with new suppliers even though we think they are better than existing ones. (R)

If a major competitor were to launch an intensive campaign targeted at our customers, we would implement a response immediately.

Even if we came up with a great marketing plan, we probably would not be able to implement it in a timely fashion. (R)

We tend to take longer than our competitors to respond to a change in regulatory policy. (R)

SCOCRED (Credibility): Cronbachs !=0.79

Promises made to our supply chain members by our business unit are reliable.

Our business unit is knowledgeable regarding our products and/or services when we are doing business with our supply chain members.

Our business unit does not make false claims to our supply chain members.

Our business unit is not open in dealing with our supply chain members.

SCOBENE (Benevolence): Cronbachs !=0.87

When making important decisions, our supply chain members are concerned about our welfare.

When we share our problems with our supply chain members, we know they will respond with understanding.

In the future we can count on our supply chain members to consider how their decisions and actions will affect us.When it comes to things that are important to us, we can depend on our supply chain members support.

SCOCOMM (Commitment): Bivariate correlation=0.34 at .01 level (two-tailed).

We defend our supply chain members when outsiders criticize them, if we trust them.

We are patient with our supply chain members when they make mistakes that cause us trouble but are not repeated.

SCONORM (Cooperative norms): Cronbachs !=0.66b

Our business unit is willing to make cooperative changes with our supply chain members.

We believe our supply chain members must work together to be successful.

We view our supply chain as a value added piece of our business.

SCOCOMP (Organizational compatibility): Bivariate correlation= 0.47 at 0.01 level (two-tailed).

Our business units goals and objectives are consistent with those of our supply chain members.

Our CEO and the CEOs of our supply chain members have similar operating philosophies.

SCOTOPM (Top management support): Cronbachs !=0.84.

Top managers repeatedly tell employees that this business units survival depends on its adapting to supply chain management.

Top managers repeatedly tell employees that building, maintaining, and enhancing long-term relationships with our supply chain members arecritical to this business units success.

Top managers repeatedly tell employees that sharing valuable strategic/tactical information with our supply chain members is critical to this

business units success.

Top managers repeatedly tell employees that sharing risk and rewards is critical to this business units success.

Top management offers various education opportunities about supply chain management.

SCMVISN (Agreement on supply chain vision and goals): Cronbachs !=0.86.

Our supply chain members have common, agreed to goals for supply chain management.

Our supply chain members are actively involved in standardizing supply chain practices and operations.

Our supply chain members clearly define roles and responsibilities of each other cooperatively.

We all know which supply chain members are responsible for what activity within the supply chain.

SCMINFO (Information sharing): Cronbachs !=0.75.

Our supply chain members practice Electronic Data Interchange, either via VAN or Internet.

Our supply chain members regularly (at least once a quarter) exchange supply and demand forecasts with each other.Our supply chain members frequently (at least once a month) exchange demand change information with each other to facilitate operational

plans and reduce reliance on second-guesses.

SCMRISK (Risk and reward sharing): Cronbachs !=0.80.

Our supply chain members share risks and rewards.

Our supply chain members help each other finance capital equipment.

Our supply chain members share research and development costs and results with each other.

SCMCOOP (Cooperation): Cronbachs !=0.88.

Our supply chain members have a record of allowing each other to participate in strategic decisions.

Our supply chain members share the results of performance measures with each other to improve the efficiency and effectiveness of the supply

chain processes.

Our supply chain members improve the quality of products and services to the end users in a collaborative manner.



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Table 6 (continued)

Measurement items

Our supply chain members actively propose and implement cost reduction ideas.

Our supply chain members are actively involved in our business units new product development and commercialization process.

Our supply chain members jointly manage logistics and inventory in the supply chain.

SCMINTG (Process integration): Cronbachs !=0.80.

Our supply chain members reduced formal organizational structures to more fully integrate operations with each other.Our supply chain members place personnel at the business facilities of each other to facilitate cooperation.

An interfunctional team from our business unit, together with the teams from our supply chain members, has meetings to figure out how to serve

our mutual customers better.

One of our supply chain members owns and/or manages one of the supply chain processes (e.g., manufacturing, transportation, warehousing,

distribution, marketing, etc.) for the rest of our supply chain members.

Our supply chain members successfully integrate operations with each other by developing interlocking programs and activities.

SCMREL (Building/maintaining/enhancing relationships): Cronbachs !=0.86.

Our supply chain members substantially reduced channel complexity over the past three years to closely work with a selected set of supply chain

members.

Our supply chain members have guidelines for developing, maintaining, and monitoring long term supply chain relationships with each other.

Our supply chain members have facilitated a strong and long-term supply chain relationship fostering cooperation with each other.

SCMLEAD (Agreement on supply chain leadership): Cronbachs !=0.90.

In our supply chain, there exists a firm that provides supply and/or demand forecasting, which is critical to the other members supply chain

planning and activities.

In certain situations in our supply chain, one firm sets the standards for all supply chain members to follow.

In our supply chain, there exists a firm that acts as a management consultant for other members supply chain practices.

In our supply chain, there exists a firm that benchmarks best practices/processes and shares the results.

In our supply chain, there exists a firm that imposes rules and standards for sharing information about product orders, shipments, and inventory.

In our supply chain, there exists a firm that maintains an integrated database and access method to facilitate information sharing with other

supply chain members.

PERFAVAI (Inventory availability): Bivariate correlation= 0.77 at 0.01 level (two-tailed).

Our business units stock availability relative to our competitors.

Our business unit does a better job of consistently maintaining available stock than our major competitors.

PERFP&S (Product and service offerings): Cronbachs !=0.63c.

Our business units product/service offerings in terms of variety of features, options, sizes, and/or colors relative to our competitors.

Our business units product/service offerings in terms of quality relative to our competitors.

Our business units product /service offerings in terms of handling difficult, nonstandard orders to meet special customer specifications relative

to our competitors.

PERFTIME (Timeliness): Cronbachs !=0.79.

Our business units customer order-to-delivery cycle time specifications relative to our competitors.

Our business units customer order-to-delivery cycle time consistency relative to our competitors.

Our business unit does a better job providing our customers real time information about their orders than our major competitors.

PERFPROF (Profitability): Cronbachs !=0.95.

Our business units return on assets (ROA) relative to our competitors.

Our business units return on investment (ROI) relative to our competitors.

Our business units return on sales (ROS) relative to our competitors.

PERFGROW (Growth): Bivariate correlation=0.83 at 0.01 level (two-tailed).

Our business units sales growth relative to our competitors.

Our business units market share growth relative to our competitors.

a

We acknowledge that the standardized Cronbachs alpha for Generation was under Nunnallys (1978) threshold value (0.663


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A Market Orientation in Supply Chain