Corporation’s Characteristics and LIS(Logistics ...s-space.snu.ac.kr/bitstream/10371/1810/1/SJBv10n2_049.pdf · Corporation’s Characteristics and LIS(Logistics Information System)

Corporation’s Characteristics and LIS(LogisticsInformation System) Strategies

Soo Wook Kim*Seoul National University

Seoul, Korea

Abstract

Logistics Information System(LIS) is known as a critical factor inachieving logistics competitiveness. Most corporations, however, do notseem to have clear strategies in meeting the information systemsrequirements of this decade. This is partly due to a lack of understandingabout the causal relationship between a corporation’s characteristics andlogistics information system priorities. In this paper, a set of advisablestrategies for LIS utilization is derived from a relationship analysisconducted by means of LISREL.

From the analysis on 244 sample firms, this study finds that theutilization of LIS most directly affects logistics performance, while theutilization of LIS indirectly may affect performance by using acorporation’s characteristics as an intermediate mechanism, and thatsuch indirect utilization of LIS has greater influence on logisticsperformance than the direct utilization of LIS. Based on the abovefinding, this study suggests that the utilization strategy of LIS shouldbe established in the direction of Support function LIS Primaryfunction LIS → Connection function LIS.

Keywords: Logistics Information System, Support Function LIS,Primary Function LIS, Connection Function LIS.

1. Introduction

With a recent rise in the importance of logistics rationalizationas the last measure in strengthening corporate competitiveness,

Seoul Journal of BusinessVolume 10, Number 2 (December 2004)

* Assistant Professor of Operations Management, College of BusinessAdministration, Seoul National University([email protected]).

the construction of integrated LIS has been in keen demand inorder to effectively achieve logistics rationalization. Manycorporations, however, are not adequately meeting this demand.One of the main reasons for this is that the construction andutilization strategy of LIS do not take into consideration acorporation’s goals and specifications. This is partly becausemanagers often do not realize that the utilization performance ofLIS can differ according to corporate characteristics such as thecorporation’s strategy, the type of logistics organization, and thelevel of logistics technology and logistics administration ability.Therefore, the accurate understanding on the relationshipbetween LIS utilization and various corporate characteristics isvery meaningful. In this respect, this study suggests anadvisable LIS utilization strategy through an examination of therelationship between LIS utilization, logistics performance, and acorporation’s characteristics.

This paper is organized as follows. Section 2 refers to thenecessity of relationship analysis between LIS and acorporation’s characteristics, and in section 3, research modelcomponents of this study and related studies are introduced. Insection 4, after establishing the model setting and outlininghypotheses, research methodology used for testing the abovehypotheses is presented. Section 5 analyzes the relationshipmodel by means of LISREL, and characterizes a set of advisablestrategies for LIS utilization through additional experiment.Finally, concluding remarks are given in section 6.

2. The Necessity of Relationship Analysis between LIS andCorporation’s Characteristics

According to Moon(1994), a corporation’s decision making onlogistics is based on the following three concepts: The first is thetotal cost concept in which a decision is made through ananalysis of the trade-off relation between service level andlogistics cost. Second is the scalar decision making concept,where short- and long-term characteristics of decision makingon logistics are considered by classifying whether such decisionshave characteristics that are long-term and strategic or short-term and tactical. The third is the integrated logistics

50 Seoul Journal of Business

management concept covering all processes related to logisticsfrom raw material supply to final product delivery. This conceptrefers to logistics system from the viewpoint of supply chainmanagement.

The above three concepts provide the fundamental bases forexamining the significance of LIS utilization and the direction inwhich LIS should be utilized. The first decision-making conceptproposes that LIS should be used to maximize logisticsperformance such as logistics cost and customer service. Thesecond concept suggests that decision making on the utilizationof LIS should be made by sufficiently considering the scalar fitrelation between LIS and a corporation’s characteristics,including its general and functional characteristics related tologistics. Finally, the third concept dictates that the utilization ofLIS should be made in a direction in which logistics functionsare integrated and rationalized in terms of supply chainmanagement through an efficient connection between theinternal supply chain and external entities such as suppliersand customers as well as among a corporation’s internalfunctions.

With respect to hierarchical congruent relations between LISutilization and a corporation’s characteristics, the scalar conceptin particular can be regarded as the most important part of LISutilization. This is because the direction for integration andoperation by function of LIS as well as the ef fect of LISutilization on logistics performance may vary depending on thetype of relationship between the utilization of LIS and acorporation’s characteristics, and also a corporation’scharacteristics affecting the effective utilization of LIS can beaccurately analyzed and managed through this relationship(Stock and Lambert 1993).

3. Research Variables

A corporation’s characteristics that influence the relationshipbetween LIS utilization and logistics performance can be dividedinto company-level characteristics representing the overallstructure of a corporation and functional characteristicsrepresenting the company’s logistics capability. The strategic

Corporation’s Characteristics and LIS(Logistics Information System) Strategies 51

capability of a corporation and the status of its logisticsorganization can be considered company-level characteristics,while logistics technology and logistics administration ability canbe regarded as functional characteristics.

3.1. LIS Utilization

Managing logistics functions through information technologymakes it possible to attain higher efficiency and performancesthan the existing effectiveness-oriented logistics managementsystem. This is because LIS utilization ultimately provides anincentive for growth through the strengthening of overallcompetitiveness as well as simply the benefits of cost reductionand high quality(Groover and Wiginton 1984, Kaeli 1990,Kaltwasser 1990, Kaplan 1986, Shull 1987 Sullivan 1985).Previous authors claim that LIS utilization is essential ingenerating competitiveness and plays a crucial role in thedevelopment of logistics as a management discipline(Stenger1986, Stock and Lambert 1993). Bowersox(1990) and Germain(1989) verified empirically that logistics performance is higherfor corporations more susceptible to the innovation of logisticsinformation technology, while Bardi, Raghunathan and Bagghi(1994) assert that LIS determines the ef ficiency andcompetitiveness of a company in the marketplace, as well as itsability to optimize logistics costs and service levels. Williams,Nibbs, Irby and Finley(1997) insist that LIS utilization can makeboth suppliers and buyers more cost, product, and processefficient, which translates into advantages over their competitors.

3.2. Strategic Capability

The strategic capability of a corporation, which has thus farbeen a recurrent thesis in studies on structural relations, is asubstantial characteristic in that a company’s strategiccharacteristics are tightly bound with its functional decision-making activities(Kotha and Orne 1989). The strategic capabilityof a corporation indicates the corporation’s competency levelwithin its industry. The level of competition shows thecorporation’s competitive position and the level of competitivesuperiority within a specific industrial category, and competitive


status of a corporation carries significant meaning on thesuggestion of strategic direction(Montanari 1978). Robertson andGatignon(1985) also argue that adopting technical innovation ishighly correlated with the competitive environment of suppliersand customers.

Therefore, from this perspective, the proliferation of logisticsinformation technology for the effective execution of logisticsactivities can be seen as closely related to the competitivebusiness climate of suppliers and customers. Lenz andEngledow(1986) back up such assertion. They contend thatindividual corporations gain distinct levels of competencythrough opportunities and risks resulting from industrialenvironment, and the competitive position of a corporationwithin an industry has much to do with the acceptance ofinformation technology.

3.3. The Status of Logistics Organization

The problem on the status of logistics division can also belinked to LIS utilization by presenting the following two researchquestions. The first question is on the necessity and position ofan exclusive division in charge of logistics activities within theorganization, which should be dealt with in order to determinehow the institution of systematic logistics organization affectsthe improvement of LIS utilization performance. The secondquestion is concerned with whether the logistics division takesresponsibility for the utilization of LIS, and which relationship ithas with the existing information system division. This is also animportant research subject in that the effective utilization of LISmay be decided upon by the clarity of authority andresponsibility on LIS and organizational relationships betweenthe two divisions.

Scholars have conflicting opinions over the effects that thelevel of formalization and centralization of logistics organizationhave on LIS utilization(Bowersox et al. 1989, Kotha and Orne1989, Zaltman et al. 1973). Ein-Dor and Segev(1978) andRaymond(1985) assert that a formalized logistics organizationleads general logistics activities and institutes regulations andprocedures which facilitate daily decision-making. They alsocontend that more formalized corporations have more


sophisticated information systems and corporations with moreadvanced information systems utilize information technologymore effectively.

Fredrickson(1986), on the other hand, argues that eventhough a high degree of formalization may eliminate theambiguity of roles, it restricts the organization members’discretionary rights in decision-making and disturbs the pursuitof new opportunities and innovation. Webster(1970) points outthat a strict and extremely formalized mechanical organizationcannot accept innovation, whereas Sapolsky(1967) states thatalthough an organization with a low degree of formalization andcentralization is far more open to and accepts innovation, it isdifficult to actually put into practice. Kennedy(1983) alsocomments that the effects of formalization depend upon thestage of innovation process, and that an organization is moresusceptible to innovation when it is less formalized in itsbeginning stages. Germain, Droge and Daugherty(1989)discovered that corporations with decentralized organizationalstructures utilize computers less than do those with centralizedstructures, through studies on logistics-related computersoftware and information variables. Their study indicates thatcentralization may increase the possibility of accepting andseeking innovation in logistics information technology. On theother hand, Fredrickson(1986) claims that centralization, ingeneral, delays the initiation of decision-making. Moch andMorse(1977) and Kennedy(1983) also claim that centralizationhas a negative effect on the acceptance of technology innovation.

3.4. Logistics Technology Level and Logistics Administration Ability

Logistics technology can be considered as the infrastructure oflogistics to support the efficient execution of logistics activities.Logistics administration ability is defined as the level of basicactivities that are prerequisites for the implementation andcontrol of logistics activity(Lynagh and Poist 1984). Bowersox(1990) classifies logistics management into logistics managementas a technology, which stresses traditional logistics managementconcept as a logical experiment on logistics managementtechniques, and logistics management as a system, whichadjusts and manages logistics service improvement activities


from top management with respect to integrated management.Ballou(1985) defines logistics management as “logistics activitiesimplemented to meet demands of customers or a method andsystem used to economically realize services”.

Viewed in the above perspectives, logistics technology andlogistics administration ability are essential elements thatshould be dealt with on a comprehensive, company-wide levelrather than on an individual or sectional dimension in that thesystemization and rationalization of those two factors mayindependently affect logistics performance and LIS utilization.

3.5. Logistics Performance

Performance measurement in logistics is critical because ofthe following two reasons: First, performance measurementmakes it possible to implement trade-off analysis on logisticscost and customer service(Tyworth 1992). Second, performancemeasurement is directly related to a corporation’s overallbusiness activities such as profitability or market share.Accordingly, a study on which criteria should be used tomeasure logistics performance and how it should be used can betreated as the most critical issue in promoting logistics efficiency(Kearney 1985).

Among the theories on logistics performance measurement,Germain(1989) developed a measurement matrix of logisticsperformance by dividing subjects into performance focus andstrategic focus, further classifying performance focus intointernal performance and external performance and classifyingstrategic focus into cost access and differentiation access.Kearney(1985) presents productivity, utility, and performance asthe three categories to evaluate the functionality of logistics,where productivity is defined as the ratio of output to actualinput, utility as the ratio of actual used capacity to availablecapacity, and where performance is measured by the ratio ofactual output to base output.

Meanwhile, Sterling and Lambert(1985) suggest logistics costand customer service as the most generalized standards for theevaluation of a logistics system, whereas Mentzer and Konrad(1991) assert that logistics performance should be analyzedaccording to effectiveness and efficiency. Collier(1977) relates



Tab

le 1

. Sum

mar

y o

f R

esea

rch V

aria

ble

s

Var

iable

Des

crip

tion

Lite

ratu

re

LIS U

tiliz

atio

n

Str

ateg

ic

Cap

abili

ty

The

Sta

tus

of

Logi

stic

s O

rgan

izat

ion

LIS u

tiliz

atio

n u

ltim

atel

y pro

vides

an i

nce

ntive

for

gro

wth

thro

ugh

the

stre

ngt

hen

ing

ofov

eral

l com

pet

itiv

enes

s as

wel

l as

sim

ply

the

ben

efits

of c

ost re

du

ctio

n a

nd h

igh q

ual

ity.

Log

isti

cs p

erfo

rman

ce i

s h

igh

er f

or c

orpor

atio

ns

mor

e su

scep

tible

to

the

inn

ovat

ion

of

logi

stic

s in

form

atio

n tec

hnol

ogy.

LIS d

eter

min

es t

he

effic

iency

and c

ompet

itiv

enes

s of

a c

ompan

y in

the

mar

ket

pla

ce, as

wel

las

its

abili

ty to

optim

ize

logi

stic

s co

sts

and s

ervi

ce le

vels

.

The

utiliz

atio

n o

f LI

S c

an m

ake

bot

h s

upplie

rs a

nd b

uye

rs m

ore

cost

, pro

du

ct, an

d p

roce

ssef

ficie

nt, w

hic

h tra

nsl

ates

into

adva

nta

ges

over

thei

r co

mpet

itor

s.

A c

ompan

y’s

stra

tegi

c ch

arac

teri

stic

s ar

e tigh

tly

bou

nd w

ith its

fu

nct

ional

dec

isio

n-m

akin

gac

tivi

ties

.

The

com

pet

itiv

e st

atu

s of

a c

orpor

atio

n c

arri

es s

ignifi

cant

mea

nin

g on

the

sugg

estion

of

stra

tegi

c dir

ection

and o

n c

orpor

atio

n’s

per

form

ance

.

Adop

tin

g te

chn

ical

in

nov

atio

n i

s h

igh

ly c

orre

late

d w

ith

th

e co

mpet

itiv

e en

viro

nm

ent

ofsu

pplie

rs a

nd c

ust

omer

s.

Th

e co

mpet

itiv

e pos

itio

n o

f a

corp

orat

ion

wit

hin

an

in

du

stry

has

mu

ch t

o do

wit

h a

corp

orat

ion’s

acc

epta

nce

of i

nfo

rmat

ion tec

hnol

ogy.

More

form

ali

zed

corp

ora

tion

s h

ave

more

sop

his

tica

ted

in

form

ati

on

sys

tem

s an

dco

rpor

atio

ns

with m

ore

adva

nce

d info

rmat

ion s

yste

ms

utiliz

e in

form

atio

n t

echnol

ogy

mor

eef

fect

ivel

y.

A h

igh d

egre

e of

for

mal

izat

ion r

estr

icts

the

orga

niz

atio

n m

ember

s’ d

iscr

etio

nar

y ri

ghts

in

dec

isio

n-m

akin

g an

d d

istu

rbs

the

pu

rsu

it o

f new

oppor

tunitie

s an

d in

nov

atio

n.

A s

tric

t an

d e

xtre

mel

y fo

rmal

ized

mec

han

ical

org

aniz

atio

n c

annot

acc

ept in

nov

atio

n.

Ka

eli

(19

90

),

Ka

ltw

asser

(1990), K

apla

n(1

986), S

hu

ll(1

987) S

ulli

van(1

985)

Bow

erso

(1990)

and G

erm

ain

(1989)

Bard

i, R

agh

un

ath

an

an

dB

aggh

i(1994)

Wil

liam

s, N

ibb

s, I

rby

an

dFin

ley(

1997)

Kot

ha

and O

rne(

1989)

Mon

tanar

i(1978)

Rob

ert

son

an

d G

ati

gn

on

(1985)

Lenz

and E

ngl

edow

(1986)

Ein

-Dor

an

d S

egev

(19

78

)an

d R

aym

ond(1

985)

Fre

dri

ckso

n(1

986)

Web

ster

(1970)


Tab

le 1

. C

onti

nued

Var

iable

Des

crip

tion

Lite

ratu

re

Logi

stic

s Tec

hnol

ogy

Leve

l and

Logi

stic

s A

dm

inis

trat

ion

Abili

ty

Logi

stic

s Per

form

ance

Althou

gh a

n o

rgan

izat

ion w

ith a

low

deg

ree

of f

orm

aliz

atio

n a

nd c

entr

aliz

atio

n i

s fa

r m

ore

open

to

and a

ccep

ts in

nov

atio

n, i

t is

diffic

ult to

actu

ally

pu

t in

to p

ract

ice.

An o

rgan

izat

ion is

mor

e su

scep

tible

to in

nov

atio

n w

hen

it is

less

form

aliz

ed in

its

begi

nnin

g st

ages

.

Cen

tral

izat

ion m

ay i

ncr

ease

the

pos

sibili

ty o

f ac

cepting

and s

eekin

g in

nov

atio

n i

n l

ogis

tics

info

rmat

ion tec

hnol

ogy.

Cen

tral

izat

ion d

elay

s th

e in

itia

tion

of d

ecis

ion-m

akin

g.

Cen

tral

izat

ion h

as a

neg

ativ

e ef

fect

on the

acce

pta

nce

of t

echnol

ogy

innov

atio

n.

Logi

stic

s te

chnol

ogy

and a

dm

inis

trat

ion a

bili

ty a

re p

rere

quis

ites

for

the

imple

men

tation

and

contr

ol o

f log

istics

act

ivity.

Logi

stic

s m

anag

emen

t co

uld

be

clas

sifie

d i

nto

log

istics

man

agem

ent

as a

tec

hnol

ogy

and

logi

stic

s m

anag

emen

t as

a s

yste

m.

Logi

stic

s m

anag

emen

t is

act

ivitie

s im

ple

men

ted t

o m

eet

dem

ands

of c

ust

omer

s or

a m

ethod

and s

yste

m u

sed to

econ

omic

ally

rea

lize

serv

ices

.

Per

form

ance

mea

sure

men

t m

akes

it

pos

sible

to

imple

men

t tr

adeo

ff a

nal

ysis

on l

ogis

tics

cost

and c

ust

omer

ser

vice

.

Per

form

ance

focu

s is

cla

ssifi

ed in

to c

ost ac

cess

and d

iffe

rentiat

ion a

cces

s.

Logi

stic

s co

st a

nd c

ust

omer

ser

vice

as

the

mos

t ge

ner

aliz

ed s

tandar

ds

for

the

eval

uat

ion o

fa

logi

stic

s sy

stem

.

Logi

stic

s per

form

ance

shou

ld b

e an

alyz

ed a

ccor

din

g to

effec

tive

nes

s an

d e

ffic

iency

.

Logi

stic

s per

form

ance

is r

elat

ed to

the

per

form

ance

of n

ew p

rodu

ct d

evel

opm

ent.

Obje

ctiv

e-or

iente

d a

nd p

roce

ss-o

rien

ted e

valu

atio

ns

shou

ld b

e ca

rrie

d o

ut

concu

rren

tly

inor

der

to

mea

sure

MIS

per

form

ance

.

Fiv

e ca

tego

ries

for

the

eval

uat

ion o

f lo

gist

ics

per

form

ance

: as

set

man

agem

ent, e

xpen

ses,

pro

du

ctiv

ity,

cu

stom

er s

ervi

ce, a

nd q

ual

ity.

Sap

olsk

y(1967)

Ken

ned

y(1983)

Ger

mai

n, D

roge

and

Dau

gher

ty(1

989)

Fre

dri

ckso

n(1

986)

Moc

h a

nd M

orse

(1977)

and

Ken

ned

y(1983)

Lyn

agh a

nd P

oist

(1984)

Bow

erso

x(1990)

Bal

lou

(1985)

Tyw

orth

(1992)

Ger

mai

n(1

989)

Ste

rlin

g an

d L

amber

t(1985)

Men

tzer

and K

onra

d(1

991)

Col

lier(

1977)

Sea

shor

e an

d Y

uch

man

(1

967)

Bow

erso

x(1989)

logistics performance to the performance of new productdevelopment and presents performance criteria of new productdevelopment, which is based on financial criteria such as salesrate and objective criteria that determine how much newproduct development contributes to the achievement ofprofitability, sales, profit growth rate, and other non-quantifiedobjectives. Seashore and Yuchman(1967) contend that objective-oriented and process-oriented evaluations should be carried outconcurrently to measure MIS performance. Bowersox(1989)presents five categories for the evaluation of logisticsperformance: asset management, expenses, productivity,customer service, and quality. His research is regarded as arepresentative study in evaluating logistics performance by anon-financial index.

As examined above, previous studies on the measurementcriteria of logistics performance do not prove to be consistent.However, if the ultimate objectives of logistics management andLIS utilization are cost reduction and customer serviceimprovement, the measurement criteria of logistics performanceshould be directly related to such objectives. Therefore logisticscost and customer service, which is the trade-off relationship,can be considered the most important measurement criteria oflogistics performance.

4. Methodology

4.1. Research Model and Hypotheses

Structural equation model in Figure 1 is constructed based onthe variables described in the preceding section.

This study set hypotheses in the perspective of notexplanatory but exploratory, because there is no research tosuggest specific causal relationships between the proposedlatent variables. The hypotheses in this research describe thedirect relationships between variables included in the researchmodel of Figure 1. Therefore, a total of 21 hypotheses areconstructed to test the statistical significances of all possiblepaths between the proposed variables as shown in the figure.LISREL is used for the analysis of the proposed structural


equation model.

4.2. Data Collection

For the purpose of this study, target corporations should belarge manufacturing corporations carrying out all functions suchas supply, production and distribution, as well as a continuedinterest and support in logistics management and LIS.Therefore, the necessary data were collected throughquestionnaires to logistics officers and logistics experts incomparatively large manufacturing corporations among listedand registered corporations, by making visits or mail or facsimileafter phone call.

Of 1000 companies, 244 companies replied, representing acollection ratio of 24.4%. Table 2 summarizes the samplecharacteristics according to industry type and size. As shown inthe table, sample corporations in this study have diversifiedindustry types and scales. The diversity of the sample wouldstrengthen the external validity of this study results.


Figure 1. Research Model.

4.3. Measurements

LIS utilization: In this study, in order to measure theutilization level of LIS, nine categories of traditional functionalLIS were identified based on previous researches(Ballou 1985,Gustin 1994, House 1985, Mentzer et al. 1990, Stenger 1986)presenting development and utilization strategies of LIS throughthe classification of functional LIS: plant and warehouse locationselection system, automatic ordering system, procurementinformation system, production plan and process controlsystem, inventory and warehouse management system,transportation management system, sale and price managementsystem, consumer service and customer management system,forecasting system.

We also added three more sub-functional information systems(the network plan and design system, office information system,and accounting information system) that laterally support theeffective utilization of the above nine major functional LIS. So, atotal of 12 functional LIS were conceptualized. In order to


Table 2. Sample Characteristics

Type of Industry*

Consumption Basic Industrial Electronic and TotalIndustry Material Industry Machinery Industry

No. of Firms 99(40.7%) 81(33.1%) 64(26.2%) 244

Organization Size

Below 50- 100- 200- 500- Above Total50 billion 100 200 500 1000 1000

No. of Sales 18 50 52 70 30 24 244

Firms Assets 14 34 60 64 38 34 244

* consumption industry: food processing, sweetmeats, pharmaceuticals,footwear, clothes, wood, furniture basic industrial material industry: textile,organic chemical, inorganic chemical, petrochemical, cement, paper, tire,fertilizer, fabric, pulp, metal electronics and machinery industry: computer,home appliances, communication equipment, electronic parts, automobile,automobile parts, machinery.

measure the utilization level of each of these twelve functionalLIS, a seven-point scale was set up as follows by combiningNolan’s research(1982) on the growth stage of informationsystems and Stephens’ research(1989) on the integration stageof supply chain management.

�---------�---------�--------�---------�---------�--------�No Planning Initialization Extension Functional Internal External

Response Stage Stage Stage Integration Integration Integration

Stage Stage Stage

Strategic Capability: In this study, 35 measurement variablesrepresenting strategic characteristics were constructed based onthe works of Porter(1980), Miles and Snow(1978), and Miller andRoth(1989) which are the most representative studies onstrategic characteristics that have undergone numerousvalidation processes by subsequent scholars. After theutilization degrees of these measurement variables weremeasured with the seven-point Likert scale, they weregeneralized into several strategic characteristic factors by factoranalysis, and “a corporation’s strategic capability”, a theoreticalvariable for LISREL, was constructed based on these factors.

Strengthening of Logistics Organization: This study alsoestablished three measurement variables of logisticsorganization(i.e., the degree of complexity, the degree ofdecentralization, and the degree of formalization) by rearrangingthree organizational variables commonly dealt with in previousresearches(Bowersox et al. 1989, Daft 1986, Dalton et al. 1980,Germain et al. 1989, Ein-Dor and Segev 1978, Evers et al. 1976,Fredrickson 1986, Kennedy 1983, Moch and Morse 1977, Pierceand Delbecq 1977, Pugh et al. 1969, Raymond 1985, Sapolsky1967, Webster 1970, Zaltman et al. 1973). “Strengthening oflogistics organization,” a theoretical variable for LISREL analysis,was constructed based on these three variables. In order tomeasure the level of the above three logistics organizationalvariables, detailed measurement variables were constructedbased on the studies of Robbins(1987), Ford and Slocum(1977),Fredrickson(1986), Bowersox and Daugherty(1987), andmeasured with the seven-point Likert scale.

Logistics Technology Level: This study also sets up three



Tab

le 3

. M

easu

rem

ent

Var

iable

s

Res

earc

h V

aria

ble

Mea

sure

men

t It

ems

Ref

eren

ceSca

le

LIS U

tiliz

atio

n

Logi

stic

s Tec

hnol

ogy

Leve

l

-Pla

nt an

d w

areh

ouse

loca

tion

sel

ection

sys

tem

-A

uto

mat

ic o

rder

ing

syst

em

-Pro

cure

men

t in

form

atio

n s

yste

m

-Pro

du

ctio

n p

lan a

nd p

roce

ss c

ontr

ol s

yste

m

-Inve

nto

ry a

nd w

areh

ouse

man

agem

ent sy

stem

-Tra

nsp

orta

tion

man

agem

ent sy

stem

-S

ale

and p

rice

man

agem

ent sy

stem

-C

onsu

mer

ser

vice

and c

ust

omer

man

agem

ent sy

stem

-For

ecas

ting

syst

em-N

etw

ork p

lan a

nd d

esig

n s

yste

m

-Offic

e in

form

atio

n s

yste

m

-Acc

ounting

info

rmat

ion s

yste

m

Con

stru

ctio

n o

f Log

istics

Cen

ter

-The

appro

pri

aten

ess

of lo

gist

ics

cente

r lo

cation

-The

effic

iency

in the

oper

atio

n o

f log

istics

cen

ter

Logi

stic

s A

uto

mat

izat

ion

-Pac

kag

ing

stan

dar

diz

atio

n-T

ransp

orta

tion

mod

e-D

igital

Pic

kin

g sy

stem

-Unit lo

ad s

yste

m-A

uto

mat

ic r

etri

eval

sys

tem

Applic

atio

n o

f Adva

nce

d M

anag

emen

t Tec

hnol

ogy

-Ju

st-I

n-T

ime

-MR

P-D

RP(d

istr

ibu

tion

res

ourc

e pla

nnin

g)-P

ER

T-C

PM

-CR

AFT

Ballou

1985,

Gu

stin

1994,

Hou

se 1

985,

Men

tzer

et

al.

1990, S

tenge

r 1986

Yan

g(1

99

6),

Rao,

Ste

nger

an

d W

u(1

99

4),

Ger

main

,D

roge

and D

augh

erty

(1994)

Tw

elve

poi

nt

scal

es

Sev

en p

oint

Liker

tsc

ale

s(E

xtr

emel

yL

ow

-Ex

trem

ely

Hig

h)


Tab

le 3

. C

onti

nued

Res

earc

h V

aria

ble

Mea

sure

men

t It

ems

Ref

eren

ceSca

le

Logi

stic

s A

dm

inis

trat

ion

Cap

abili

ty

Str

en

gth

en

ing

of

Logi

stic

s O

rgan

izat

ion

Str

ateg

ic C

apab

ility

Sys

tem

atic

Con

stru

ctio

n o

f Log

istics

Pla

n-D

ocu

men

tation

of l

ogis

tics

str

ateg

y an

d p

olic

y-C

on

curr

ence

bet

wee

n m

an

age

men

t p

lan

nin

g an

d l

ogi

stic

spla

nnin

gPro

cure

men

t an

d T

rain

ing

of L

ogis

tics

Exp

ert

-Sys

tem

atic

edu

cation

and tra

inin

g on

logi

stic

s m

anag

emen

t-P

rocu

rem

ent of

logi

stic

s ex

per

tC

ontr

ol o

f Log

istics

Ou

tcom

e-C

ompu

tation

cri

teri

a fo

r lo

gist

ics

cost

-Accu

racy o

f m

ea

su

rem

en

t a

nd

eva

lua

tion

of

logis

tics

per

form

ance

Diffe

rentiat

ion

-No.

of w

ork a

nd r

ank in

logi

stic

s dep

artm

ent

-No.

of l

ogis

tics

dep

artm

ent dis

trib

ute

d lo

cally

-Ave

rage

dis

tance

bet

wee

n h

eadqu

arte

r an

d lo

cal d

epar

tmen

t-R

atio

of l

ocal

em

plo

yees

to

tota

l em

plo

yees

Dec

entr

aliz

atio

n-T

he

deg

ree

of d

eleg

atio

n b

y fu

nct

ion

-The

deg

ree

of d

eleg

atio

n b

y ra

nk

For

mal

izat

ion

-The

pos

itio

n o

f top

man

ager

in lo

gist

ics

dep

artm

ent

-The

par

tici

pat

ion o

f log

istics

man

ager

s in

str

ateg

ic p

lannin

g-T

he

doc

um

enta

tion

of

regu

lati

ons

and p

roce

du

res

of l

ogis

tics

rela

ted w

ork

-Ext

ensi

ve S

ales

& D

istr

ibu

tion

Abili

ty

-Adve

rtis

ing

& S

ales

Pro

mot

ion A

bili

ty-R

apid

ity

of P

rodu

ct S

upply

Res

earc

h r

epor

t pu

blis

hed

in

Feb

ruar

y 1990 b

y th

e K

orea

Pro

du

ctiv

ity

Cen

ter

Bow

erso

x et

al. 1

989,

Daft

19

86

, D

alt

on

et

al.

19

80

,G

erm

ain

et

al.

19

89

, E

in-

Dor

an

d S

egev

1978,

Eve

rset

al.

19

76

, F

red

rick

son

1986,

Ken

ned

y 1983,

Moc

han

d M

orse

1977,

Pie

rce

and

Del

bec

q 1

97

7,

Pu

gh e

t al.

19

69

, R

aym

on

d

19

85

,S

ap

ols

ky 1

96

7,

Web

ste

r1970, Z

altm

an e

t al

. 1973

Sev

en p

oint

Liker

tsc

ale

s(E

xtr

emel

yLow

Em

ph

asi

s -

Extr

em

ely

Hig

hE

mphas

is)

Sev

en p

oint

Liker

tsc

ale

s(E

xtr

emel

yLow

Em

ph

asi

s -

Extr

em

ely

Hig

hE

mphas

is)


Tab

le 3

. C

onti

nued

Res

earc

h V

aria

ble

Mea

sure

men

t It

ems

Ref

eren

ceSca

le

Str

ateg

ic C

apab

ility

-Utiliz

atio

n o

f Innov

ativ

e M

arket

ing

Tec

hniq

ues

-Pro

du

ctiv

ity

Flu

ctu

atio

n A

bili

ty

-Pro

du

ct S

upply

Abili

ty b

y th

e D

ue

Dat

e-H

igh-q

ual

ity

Pro

du

ct S

upply

Abili

ty-S

ales

/Dis

trib

ution

Net

wor

k C

ontr

ol A

bili

ty-L

ow-p

rice

d P

rodu

ct S

upply

Abili

ty-B

rand D

evel

opm

ent A

bili

ty-E

labor

aten

ess

Abili

ty o

f Exi

stin

g Pro

du

cts

-Fu

nd R

aisi

ng

Abili

ty w

ithin

a C

ompan

y-P

rodu

ctiv

ity

and P

rofit

abili

ty A

nal

ysis

Abili

ty-P

rodu

ctio

n C

ost R

edu

ctio

n A

bili

ty-C

ompar

ison

/Con

trol

of G

oal a

nd P

erfo

rman

ce-I

nnov

atio

n o

f Man

ufa

ctu

ring

Pro

cess

-Sto

ck H

oldin

g A

bili

ty-G

row

th a

nd D

eman

d F

orec

asting

Abili

ty-I

nve

stm

ent in

Pro

du

ctio

n -

Qu

ality

Con

trol

Abili

ty-D

iver

sity

of M

anu

fact

uri

ng

Pro

cess

Tec

hnol

ogy

-Raw

-mat

eria

l Pro

cure

men

t A

bili

ty-P

rodu

ctio

n M

anpow

er P

rocu

rem

ent A

bili

ty-C

onsi

sten

t qu

ality

Pro

du

ct S

upply

Abili

ty-R

&D

Cos

t to

Sal

es -

Inve

stm

ent fo

r N

ew M

arket

-Intr

odu

ctio

n L

evel

of N

ew P

rodu

ct-A

nal

ysis

on C

ompet

itor

s an

d E

nvi

ronm

ent

-Siz

e of

Str

ateg

y-M

akin

g Tea

m-S

ellin

g E

xpen

ses

to S

ales

-S

upply

Abili

ty o

f Div

erse

Pro

du

cts

-Dem

and F

ocu

sed D

esig

n A

bili

ty

Por

ter

1980; M

iles

and S

now

1978; M

iller

and R

oth 1

994

Sev

en p

oint

Liker

tsc

ale

s(E

xtr

emel

yLow

Em

ph

asi

s -

Extr

em

ely

Hig

hE

mphas

is)


Tab

le 3

. C

onti

nued

Res

earc

h V

aria

ble

Mea

sure

men

t It

ems

Ref

eren

ceSca

le

Logi

stic

sPer

form

ance

Cos

t R

edu

ctio

n-P

urc

has

ing

cost

-O

per

atio

n c

ost

-Inve

nto

ry c

ost

-War

ehou

se c

ost

-Sal

es c

ost -D

istr

ibu

tion

/tra

nsp

orta

tion

cos

tC

ust

omer

Ser

vice

-On-t

ime

del

iver

y of

mat

eria

ls fr

om s

upplie

rs

-Per

cent of

acc

epta

ble

mat

eria

ls

-The

spee

d o

f su

pplie

rs’ o

rder

pro

cess

ing

-Th

e re

du

ctio

n o

f re

spon

se t

ime

in p

roce

ssin

g re

qu

ests

for

mat

eria

ls r

etu

rns

-Pro

du

ct in

nov

atio

n le

vel -

Pro

cess

innov

atio

n le

vel

-The

accu

racy

of o

rder

pro

cess

ing

for

cust

omer

s -T

he

redu

ctio

n d

egre

e of

pro

du

ct r

etu

rn r

atio

-T

he

spee

d o

f ord

er h

andlin

g -T

he

red

uct

ion

of

resp

on

se t

ime

in p

roce

ssin

g re

qu

ests

for

pro

du

ct r

etu

rns

or a

fter

-ser

vice

Lu

mm

us

et a

l. 1

998;

Bir

ouet

al.

1998;

Tan

et

al.

1998;

Zah

eer

et a

l. 1998

Sev

en p

oint

Liker

tsca

les(W

ors

t in

Ind

ust

ry-B

est

inIn

du

stry

)

factors such as the degree of logistics automatizaton, the abilityof construction and effective operation of logistics centers, andthe utilization degree of advanced management and quantitativetechniques, which have recently emerged as pivotal issues inrelation to the level of logistics technology, as the measurementvariables indicating the level of logistics technology. Detailedmeasurement variables for these three variables wereconstructed based on the studies of Yang(1996), Rao, Stengerand Wu(1994), Germain, Droge and Daugherty(1994), andmeasured with the seven-point Likert scale.

Logistics Administration Capability: Six survey questionsrelated to logistics administration ability among ten itemsproposed in a research report titled “The actual states andimprovement plans of the logistics management of Koreancorporations” published in February 1990 by the KoreaProductivity Center were extracted. These six items weremeasured with the seven-point Likert scale and reorganized intothree new variables such as the ability to systematicallyconstruct logistics management plans, the ability to procure,educate and train logistics experts, and the ability to controllogistics performance.

Logistics Performance: Logistics cost reduction andcustomer service improvement were selected as themeasurement variables of logistics performance, where logisticscost reduction was measured by comparing logistics costs tosales figures over the last three years, while customer serviceimprovement was measured by the accuracy of order processing,the reduction degree of product return ratio, the speed of orderhandling, and the reduction degree of response time inprocessing requests for product returns or after-service with theseven-point Likert scale.

5. Results

5.1. Factor Analyses and Reliability Test

Although measurement items presented in this study formeasuring LIS utilization degree and strategic capability havebeen used in previous empirical studies, it is extremely difficult



Tab

le 4

. Fac

tor

Anal

ysi

s

(a) L

IS U

tiliz

atio

n

Fac

tor

Con

nec

tion

Fu

nct

ion

Pri

mar

y Fu

nct

ion

Su

ppor

t Fu

nct

ion

Mea

sure

men

t It

em( α

=0.8

356)

(α=0

.9050)

(α=0

.8111)

Tra

nsp

orta

tion

Man

agem

ent Sys

tem

.860

For

ecas

ting

Sys

tem

.797

Au

tom

atic

Ord

erin

g Sys

tem

.733

Pro

cure

men

t In

form

atio

n S

yste

m.6

85

Pla

nt &

War

ehou

se L

ocat

ion S

elec

tion

Sys

tem

.655

Pro

du

ctio

n P

lan a

nd P

roce

ss C

ontr

ol S

yste

m.8

29

Sal

es a

nd P

rice

Man

agem

ent Sys

tem

.790

Con

sum

er S

ervi

ce a

nd C

ust

omer

Man

agem

ent Sys

tem

.760

Inve

nto

ry a

nd W

areh

ouse

Man

agem

ent Sys

tem

.688

Net

wor

k P

lan a

nd D

esig

n S

yste

m.7

86

Acc

ounting

Info

rmat

ion S

yste

m.6

66

Offic

e In

form

atio

n S

yste

m.6

23

Eig

enva

lue(

Pct

of V

ar)

3.9

084(.3

257)

2.5

5(.2

125)

1.3

98(.1

165)

(b) S

trat

egic

Cap

abili

ty

Fac

tor

Mar

ket

ing

&C

ost R

edu

ctio

n &

Diffe

rentiat

ion &

Mea

sure

men

t It

emC

ust

omer

Ser

vice

D

efen

sive

Con

trol

Pro

s. Inve

stm

ent

Ext

ensi

ve S

ales

& D

istr

ibu

tion

Abili

ty.8

38

Adve

rtis

ing

& S

ales

Pro

mot

ion A

bili

ty.8

30

Rap

idity

of P

rodu

ct S

upply

.717

Utiliz

atio

n o

f Innov

ativ

e M

arket

ing

Tec

hniq

ues

.702

Pro

du

ctiv

ity

Flu

ctu

atio

n A

bili

ty.6

97

Pro

du

ct S

upply

Abili

ty b

y th

e D

ue

Dat

e.6

25

Hig

h-q

ual

ity

Pro

du

ct S

upply

Abili

ty.6

19


Tab

le 4

. C

onti

nued

(b) S

trat

egic

Cap

abili

ty

Fac

tor

Mar

ket

ing

&C

ost R

edu

ctio

n &

Diffe

rentiat

ion &

Mea

sure

men

t It

emC

ust

omer

Ser

vice

D

efen

sive

Con

trol

Pro

s. Inve

stm

ent

Sal

es/D

istr

ibu

tion

Net

wor

k C

ontr

ol A

bili

ty.5

93

Low

-pri

ced P

rodu

ct S

upply

Abili

ty.5

80

Bra

nd D

evel

opm

ent A

bili

ty.5

71

Ela

bor

aten

ess

Abili

ty o

f Exi

stin

g Pro

du

cts

.561

Fu

nd R

aisi

ng

Abili

ty w

ithin

a C

ompan

y.5

07

Pro

du

ctiv

ity

and P

rofit

abili

ty A

nal

ysis

Abili

ty.8

28

Pro

du

ctio

n C

ost R

edu

ctio

n A

bili

ty.7

55

Com

par

ison

/Con

trol

of G

oal a

nd P

erfo

rman

ce.7

42

Innov

atio

n o

f Man

ufa

ctu

ring

Pro

cess

.708

Sto

ck H

oldin

g A

bili

ty.7

00

Gro

wth

and D

eman

d F

orec

asting

Abili

ty.6

72

Inve

stm

ent in

Pro

du

ctio

n.6

61

Qu

ality

Con

trol

Abili

ty.6

16

Div

ersi

ty o

f Man

ufa

ctu

ring

Pro

cess

Tec

hnol

ogy

.588

Raw

-mat

eria

l Pro

cure

men

t A

bili

ty.5

65

Pro

du

ctio

n M

anpow

er P

rocu

rem

ent A

bili

ty.5

37

Con

sist

ent qu

ality

Pro

du

ct S

upply

Abili

ty.5

25

R&

D C

ost to

Sal

es.8

05

Inve

stm

ent fo

r N

ew M

arket

.757

Intr

odu

ctio

n L

evel

of N

ew P

rodu

ct.7

09

Anal

ysis

on C

ompet

itor

s an

d E

nvi

ronm

ent

.666

Siz

e of

Str

ateg

y-M

akin

g Tea

m.6

43

Sel

ling

Exp

ense

s to

Sal

es.6

34

Su

pply

Abili

ty o

f Div

erse

Pro

du

cts

.625

Dem

and F

ocu

sed D

esig

n A

bili

ty.5

61

Eig

enva

lue(

Pct

of V

ar)

8.8

416(.2

763)

7.1

904(.2

274)

4.6

72(.1

460)

* Fac

tor

load

ings

bel

ow 0

.5 w

ere

not

pre

sente

d

to draw generalized characteristics from previous researches onLIS functions and strategic variables. This is due to the diversityof research approaches and the complications of relationsbetween characteristics compared with those for measuring thestrengthening of logistics organization, technology level, andadministration capability as aforementioned. Accordingly, factoranalyses were conducted on the measurement variables of LISutilization degree and strategic capability. Table 4 shows theresults of these factor analyses.

As can be seen, LIS can be divided into three major functions.The first is the primary function LIS that focuses on the effectiveoperation and control of related logistics functions, such as theproduction plan and process control system, inventory andwarehouse management system, sales and price managementsystem, and consumer service and customer managementsystem. The second is the connection function LIS that focuseson effective link between logistics functions within and outsideof a corporation, such as the plant and warehouse locationselection system, procurement information system, automaticordering system, transportation management system andforecasting system. The third is the support function LIS whichlaterally supports the effective operation of the primary andconnection function LIS such as the network plan and designsystem, office information system, and accounting informationsystem. The above classification is associated with the researchof Porter and Millar(1985) in classifying information technologyactivities into primary and support activities.

In the factor analysis on strategic capability measurements, 32items except three variables found to be inappropriate forgrouping are categorized under three factors with an eigenvalueof 1 or higher: marketing and customer service ability, costreduction and defensive control ability, and differentiation andprospective investment ability.

Cronbach α reliability tests were performed for all multi-itemscale measures, the results of which can be found in Table 5. Asshown in the table, the α value of items for connection functionLIS is highest at 0.9412 and the α value of those for thedifferentiation level of logistics organization is lowest at 0.6228.However, because it is generally known that there is no problemin evidencing the justification of an analysis if the α coefficient is


above 0.6, measurement items can be considered to besufficiently reliable to evidence the justification of analysisresults.

5.2. LISREL Analysis: the analysis of relationship between a corporation’scharacteristics

LISREL analysis was performed to test 21 hypotheses whichare established to examine structural relationship between acorporation’s characteristics. Maximum likelihood estimationmethod is used(Bagozzi 1991, Boomsma 1982). On the basis ofthis study’s latent and measurement variables that werepreviously mentioned, basic LISREL model is suggested asshown in Figure 2.

The GOF of the basic LISREL model is shown in Table 6.As shown in Table 6, the basic LISREL model in Figure 2 does

not meet the criteria of GOF, which indicates that it isinappropriate to accept this model as a theoretical model. This isbecause the model in Figure 2 itself is very complicated and does


Table 5. Reliability Test

No. of Cronbach αMeasurement Item

Items Coefficient

LIS Primary function LIS 4 0.9389

Utilization Connection function LIS 5 0.9412

Support function LIS 3 0.8484

Strengthening Differentiation of logistics organization 5 0.6228

Of Logistics Decentralization of logistics organization 12 0.8377

Organization Formulation of logistics organization 4 0.7238

Strategic Marketing & Customer service capability 12 0.8958

Capability Cost reduction & Defensive control capability 12 0.9078

Discrimination & Prospective investment capability 8 0.8257

Logistics Facility Automatization 5 0.6307

Technology Utilization of Advanced Mathmatical Methods 11 0.9388

Level Construction of Integrated Logistics Center 2 0.7305

Logistics Systemical Construction of Logistics Plan 2 0.8499

Administration Procurement & Training of Logistics Experts 2 0.8696

Ability Control Ability on Logistics Activity & Performance 2 0.8052

not correspond with actual data. To solve this problem, thepaths found to be insignificant at 95% significance level in thefirst LISREL analysis are removed and the adjusted LISRELmodel is constructed as shown in Figure 3, on which LISRELanalysis was repeated.

As shown in Table 6, the adjusted LISREL model satisfies all ofthe criteria which determines the concordance of the model, andit implies that the above adjusted LISREL model can beaccepted. Therefore, the hypotheses of this study were tested


Table 6. The Goodness of Fit of this research’s LISREL model

Degree of Standardχ2 Value GFI AGFI

Freedom Residual

Basic 496.42 98 0.775 0.648 0.172LISREL Model (P = 0.000)Adjusted 111.45 108 0.935 0.909 0.048LISREL Model (P = 0.377)

Figure 2. Basic LISREL Model.

based on the analysis results of the adjusted LISREL model,which are exhibited in Table 7.

Figure 4 demonstrates only the paths proven to be statisticallysignificant at 95% significance level from the above hypothesistest.

If paths indicated as having significant relations betweenvariables in Figure 4 are connected, four different routesthrough which LIS af fects logistics performance can besuggested as follows.�LIS Utilization → Logistics Performance �LIS Utilization → Logistics Technology Level → Strategic

Capability → Logistics Performance �LIS Utilization → Logistics Administration Ability →

Strategic Capability → Logistics Performance �LIS Utilization → Logistics Technology Level →

Strengthening of Logistics Organization → LogisticsAdministration Ability → Strategic Capability → Logistics


Figure 3. Adjusted LISREL Model.

Performance These four routes show that the utilization path of LIS

affecting logistics performance can be categorized into two types.The first is the structure through which LIS utilization directlyaffects logistics performance, and the second is the structurethrough which LIS utilization indirectly affects logisticsperformance by using a corporation’s characteristics as autilization mechanism. In other words, LIS utilization not onlydirectly affects logistics performance, but also may indirectlyaffect it through the utilization of a corporation’s characteristics.

As shown in Figure 4, the T -value is 2.487 when theutilization of LIS directly af fects logistics per formance.


Table 7. Hypothesis Test Results

Basic Adjusted

Model Model LISRELHypothesis

T T Indirect Result

Value Value Effect

LIS Utilization → Logistics Performance 5.301 2.487 0.314 Accept*

LIS Utilization →Strategic Capability -1.293 Reject

LIS Utilization →Organization Intensification -1.78 Reject

LIS Utilization → Technology Level 6.472 7.519 Accept

LIS Utilization →Administration Ability 4.664 3.203 0.094 Accept

Technology Level → Logistics Performance 1.114 Reject

Technology Level →Strategic Capability 5.311 3.401 0.082 Accept

Technology Level →Organization Intensification 7.333 4.546 -0.084 Accept

Technology Level →Administration Ability -1.429 Reject

Administration Ability → Logistics Performance 2.218 0.870 0.574 Reject

Administration Ability →Strategic Capability 15.932 3.738 -0.044 Accept

Administration Ability →Organization Intensification 0.87 1.469 0.045 Reject

Administration Ability → Technology Level 0.522 Reject

Strategic Capability → Logistics Performance 11.563 2.862 Accept

Strategic Capability →Organization Intensification 0.408 Reject

Strategic Capability → Technology Level -1.776 Reject

Strategic Capability →Administration Ability 1.02 Reject

Organization Intensification → Logistics Performance 2.571 1.429 0.148 Reject

Organization Intensification →Strategic Capability -1.632 Reject

Organization Intensification → Technology Level 1.259 Reject

Organization Intensification →Administration Ability 7.941 2.546 -0.055 Accept

*Statistically significant at 95% significance level.

Meanwhile, T-values of all related paths are spread from aminimum of 2.546 to a maximum of 7.519, when it indirectlyaffects logistics performance. The analysis of relationshipbetween variables except LIS indicates that three paths(β42

(logistics administration ability → strengthening of logisticsorganization), β52(logistics administration ability → logisticsperformance), β54(strengthening of logistics organization →logistics performance)) are not statistically significant. Thismeans that organizational and administrative factors such asthe strengthening of logistics organization or logisticsadministration ability do not directly af fect logisticsperformance. However, as shown in Table 7, the indirect effectsof these variables on logistics performance are very high (β52:0.574, β54: 0.148).

In conclusion, it can be determined that even though thestrengthening of logistics organization and logisticsadministration ability do not directly af fect logisticsperformance, they indirectly affect logistics performance througha process in which the strengthening of logistics organizationaffects logistics administration ability and such logisticsadministration ability subsequently affects strategic capability.


LIS ㅕ

Level

of Logistics

Technology

Logistics

Administration

Ability

Strategic

Capa bility

Strengthening

of Logistics

Organization

Logistics

Performance

0.262 (T=3.401)

0.518 (T=7.519)

0.232 (T=3.203)

1.687 (T=2.862)

0.343 (T=3.738)

0.426 (T=2.546)

0.646 (T=4.546)

0.204 (T=2.487)

Utilization

Figure 4. Structural Model Test Results

The fact that the three paths(β24: strengthening of logisticsorganization → logistics administration ability, β32: logisticsadministration ability → strategic capability, β53: strategiccapability → logistics performance) have statistical significanceas shown in Figure 4 proves the validity of the above analysis.

6. Conclusion

The results of empirical test above mentioned indicate that inorder to maximize logistics performance, decision-making on LISutilization should be made by sufficiently considering the scalarfit relation with a corporation’s general characteristics andlogistics related factors, and in a direction where the integrationof logistics is accomplished through the efficient connection ofeach logistics function.

The result of relationship analysis between LIS utilization anda corporation’s characteristics by LISREL demonstrates that LISutilization most directly affects logistics performance, while LISutilization indirectly af fects per formance through theimprovement of logistics technology/logistics administrationability and the strengthening of logistics organization, and suchindirect utilization of LIS has greater influence on logisticsperformance than the direct utilization of LIS.

Therefore, the utilization strategy of LIS should be establishedin the direction where, on the basis of support function LIS,primary function LIS which can influence directly on logisticsperformance is used to realize the automation within eachlogistics function and efficient linkage between related functionsin the short-term, and connection function LIS which can affectindirectly logistics performance is utilized to accomplish theintegration of all internal functions within a company and theexternal integration with suppliers and consumers in the long-term. This is a significant contribution in this paper in that itsuggests a set of concrete and advisable strategies for LISutilization, which have rarely been studied in spite of theirnoteworthy importance, from the three-dimensional analyses onthe relation structure between a corporation’s characteristics bymeans of LISREL.

However, this study also has limitations as follows. First, only


quantified characteristics were introduced as theoreticalvariables because not only it is extremely difficult to quantifyqualitative variables, but multi-colinearity may also exist in sucha complicated LISREL model. Second, this study does notsuggest a detailed connection algorithm between logisticsinformation systems by function because this paper places thefocus on the suggestion of advisable LIS utilization directions.These issues will undoubtedly be addressed in future research.

References

Bagozzi, R. P. (1991), “Evaluating Structural Equation Models withUnobservable Variables and Measurement Error: A Coment,”Journal of Marketing Research, 18(August), 375-381.

Ballou, R. A. (1985), Business Logistics Management, Prentice-Hall,Englewood Cliffs, New Jersey.

Bardi, E. J., T. S. Raghunathan, and P. K. Bagchi (1994), “LogisticsInformation Systems: The Strategic Role of Top Management,”Journal of Business Logistics, 15, 1, 71-85.

Boomsma, A. (1982), The Robustness of LISREL Against Small SampleSize in Factor Analysis Models. in K. G. Joreskog and H. Wold(eds.),Systems Under Indirect Observation: Causality, Structure,Predection, Amsterdam: North Holland.

Bowersox, D. J. (1989), “Logistics In The Integrated Enterprise,” PaperPresented at the Annual Conference of the Council of LogisticsManagement, St. Louis, MO.

—————. (1990), “The Strategic Benefits of Logistics Alliances,” HarvardBusiness Review, July-August, 36-45.

————— and P. J. Daugherty (1987), “Emerging Patterns of LogisticalOrganization,” Journal of Business Logistics, 8, 1, 46-60.

—————, —————, C. L. Droge, D. S. Rogers, and D. L. Wardlow (1989),Leading Edge Logistics Competitive Positioning for the 1990s, OakBrook, IL: Council of Logistics Management.

Byrne, P. M. and W. J. Markham (1991), Improving Quality andProductivity in the Logistics Processes: Achieving CustomerSatisfaction Breakthroughs, Oak Brook, IL: Council of LogisticsManagement.

Collier, D. W. (1977), “Measuring the Performance of R&DDepartments,” Research Management, 20, 2, 30-34.

Daft, R. L. (1986), Organization Theory and Design, 2nd Edition, WestPublishing Company.

Dalton, D. R., W. D. Tudor, M. J. Spendolini, G. J. Fielding, and L. W.


Porter (1980), “Organization Structure and Performance,” Academyof Management Review, 5, 1, 49-64.

Ein-Dor, P. and E. Segev (1978), “Organizational Context and thesuccess of MIS,” Management Science, 24, 10, 1064-1073.

Ellram, L. M. (1992), “Partners in International Alliances,” Journal ofBusiness Logistics, 13, 1, 1-25.

Evers, F. T., J. M. Bohlen, and R. D. Warren (1976), “The Relationshipsof Selected Size and Structure Indicators in EconomicOrganizations,” Administrative Science Quarterly, 21, 4, 326-343.

Ford, J. and J. W. Slocum, Jr. (1977), “Size, Technology, Environmentand the Structure of Organization,” Academy of ManagementReview, 2, 4, 561-575.

Fredrickson, J. W. (1986), “The Strategic Decision Process andOrganizational Structure,” Academy of Management Review, 11, 2,280-297.

Gustin, C. M. (1994), Distribution Information System. The DistributionManagement Handbook, McGraw-Hill, New York.

Germain, R. (1989), “The Effect of Output Standardizational onLogistical Structure, Strategy, and Performance,” InternationalJournal of Physical Distribution and Materials Management, 19, 1,20-29.

—————, C. Droge, and P. J. Daugherty (1989), “Servcing the ExchangeRelationship: Organizational Configuration and its effects on Intra-Firm and Buyer-Seller Communications,” Paper Presented at theAnnual Conference of the Council of Logistics Management, St.Louis, MO.

—————, —————, and —————. (1994), “A Cost and Impact Typology ofLogistics Technology and the Effect of its Adoption on OrganizationalPractice,” Journal of Business Logistics, 15, 2, 227-248.

Groover, M. P. and J. C. Wiginton (1984), “CIM and the FlexibleAutomated Factory of the Future,” Industrial Engineering, 16, 6, 28-37.

Hage, J. and Aiken, M. (1970), Social Change in Complex Organizations,New York: Random House.

Heskett, J. L. (1989), Leadership Through Integration: The SpecialChallenge of Logistics Management, Annual Conference Proceedingof the 1988 Council of Logistics Management.

Hewitt, F. (1994), “Supply Chain Redesign,” The International Journal ofLogistics Management, 5, 2, 1-8.

House, R. G. (1985), The Distribution Handbook, New York: Free Press;London: Collier Macmillan Publishers.

Jorescog, K. G. and D. Sorbom (1987), LISREL: Analysis of LinearStructural Relationships, Preliminary Version, October.

Kaeli, J. K. (1990), “A Company-Wide Perspective to Identify Evaluate,


and Rank the Potential for CIM,” Industrial Engineering, 22, 7, 23-26.

Kaltwasser, C. (1990), “Know How to Choose the Right CIM SystemsIntegrator,” Industrial Engineering, 22, 7, 27-29.

Kaplan, R. S. (1986), “Must CIM be Justified by Faith Alone?,” HarvardBusiness Review, 64, 2, 87-97.

Kearney, A. T., Inc. (1985), Measuring and Improving Productivity inPhysical Distribution, Chicago, Council of Logistics Management.

Kennedy, A. M. (1983), “The Adoption and Diffusion of New IndustrialProducts: A Literature Review,” European Journal of Marketing,17(3), 31-88.

Korea Productivity Center (1990), The actual states and improvementplans of the logistics management of Korean corporations, February.

Kotha, S. and D. Orne (1989), “Generic Manufacturing Strategies: AConceptual Synthesis,” Strategic Management Journal, 10, 3, 211-232.

Lambert, D. M. and J. U. Sterling (1985), “A Methodology for IdentifyingPotential Cost Reductions in Transportation and Warehousing,”Journal of Business Logistics, 5, 2, 1-13.

————— and Stock, J. R. (1982), Strategic Physical DistributionManagement, Homewood I11: Richard D. Irwin, Inc.

————— and —————. (1987), Strategic Logistics Management, 2nd ed.,Homewood I11: Richard D. Irwin, Inc.

————— and —————. (1993), Strategic Logistics Management, 3rd ed.,Homewood I11: Richard D. Irwin, Inc.

Lenz, R. T. and J. I. Engledow (1986), “Environmental Analysis Unitsand Strategic Decision- Making: A Filed Study of Selected LeadingEdgy Corporations,” Strategic Management Journal, 7, 1, 69-89.

Lynagh, P. M. and R. F. Poist (1984), “Managing Physical Distribution/Marketing Inter face Activities: Cooperation or Conflict,”Transportation Journal, 23, 3, 35.

Mentzer, J. T. (1993), “Managing Channel Relations in the 21stCentury,” Journal of Business Logistics, 14, 1, 27-42.

————— and B. P. Konrad (1991), “An Efficiency/Effectiveness Approachto Logistics Performance Analysis,” Journal of Business Logistics,12, 1, 33-62.

—————, C. P. Schuster, and D. J. Roberts (1990), “MicrocomputerVersus Mainframe Usage in Logistics,” Logistics and TransportationReview, 26, 2, 115-132.

Miles, R. E. and C. C. Snow (1978), Organization Strategy, Structure,and Process, McGraw-Hill, New York.

Miller, J. G. and A. V. Roth (1989), A Taxonomy of ManufacturingStrategies, Working Paper, Boston University, March.

Moch, M. K., and E. V. Morse (1977), “Size, Centralization and


Organizational Adoption of Innovations,” American SociologicalReview, October, 716-725.

Montanari, J. R. (1978), “Managerial Discrietion: An Expanded Model ofOrganization Choice,” Academy of management Review, 3, 2, 231-241.

Moon, S. W. (1994), “The development direction of mathematical modelfor the decision making on logistics,” Korea Journal of ManagementScience, 11, 99-131.

Nolan, R. L. (1982), “Managing Information Systems by Committee,”Harvard Business Review, 60, 4, 72-79.

Pierce, J. L. and A. L. Delbecq (1977), “Organization Structure,Individual Attitudes and Innovations,” Academy of ManagementReview, 2, 1, 27-37.

Porter, M. E. (1980), Competitive Strategy: Technology for AnalyzingIndustries and Competitors, The Free Press.

————— and V. E. Millar (1985), “How Information Gives YouCompetitive Advantage,” Harvard Business Review, 63, 4, 149-160.

Pugh, D. S., D. J. Hickson, C. R. Hinings, and C. Turner (1969), “TheContext of Organizational Structures,” Administrative ScienceQuarterly, 14, 1, 91-126.

Rao, K., A. J. Stenger, and H. J. Wu (1994), “Training Future LogisticsManagers: Logistics Strategies Within the Corporate PlanningFramework,” Journal of Business Logistics, 15, 2, 249-272.

Ray, D., J. Gattorna, and M. Allen (1980), “Handbook of DistributionCosting and Control,” International Journal of Physical Distributionand Materials Management, 10, 5, 207-429.

Raymond, L. (1985), “Organizational Characteristics & MIS Success inthe Context of Small Business,” MIS Quarterly, 9, 1, 37-52.

Richard, G. (1989), “The Effect of Output Standardization on LogisticalStructure, Strategy, & Performance,” International Journal ofPhysical Distribution and Materials Management, 19, 1, 20-29.

Robbins, S. P. (1987), Organization Theory. 2nd Edition, Prentice-Hall.Robertson, T. S. and H. Gatignon(1985), “A Propositional Inventory for

New Diffusion Research,” Journal of Customer Research, 11, 4,849-867.

Rushton, A and J. Oxley (1994), Handbook of Logistics and DistributionManagement, Kogan Page Ltd., pp.248-249.

Sapolsky, H. (1967), “Organizational Structure and Innovation,” Journalof Business, 40, 4, 497-510.

Seashore, S. E. and E. Yuchman (1967), “Factor Analysis ofOrganizational Performance,” Administively Science Quarterly, 12,12, 377.

Segev, A. (1989), “A Systematic Comparative Analysis and Synthesis ofTwo Business-Level Strategic Typologies,” Strategic Management


Journal, 10, 5, 487-505.Shull, D. (1987), “Migrating Toward CIM,” Control Engineering, May,

161-164. Stenger, A. (1986), “Information System in Logistics Management: Past,

Present, and Future,” Transportation Journal, Fall, 65-82. Stephens, G. (1989), “Integrating the Supply Chain,” International

Journal of Physical Distribution and Materials Management, 19, 8,3-8.

Sullivan, C. H. Jr. (1985), “System Planning in Information Age,” SloanManagement Review, 26, 2, 3-11.

Tilanus, B. (1997), Information Systems in Logistics and Transportation,1st ed., Elsevier Science Ltd.

Tyworth, J. E. (1992), “Modeling Transportation-Inventory TradeOffs ina Stochastic Setting,” Journal of Business Logistics, 13, 2, 27-39.

Williams, L. R., A. Nibbs, D. Irby, and T. Finley (1997), “LogisticsIntegration: The Effect of Information Technology, TeamComposition, and Corporate Competitive Positioning,” Journal ofBusiness Logistics, 18, 2, 31-41.

Webster, F. E. Jr. (1970), “Informal Communication in IndustrialMarkets,” Journal of Marketing Research, 7, 5, 186-189.

Yang, I. M. (1996), Logistics Strategies and Performance in theManufacturing Industries, Ph.D. Dissertation, Kon-Kuk University.

Zaltman, G., R. Duncan, and J. Holbeck (1973), Innovations andOrganization, New York: John Wiley and Sons.


Corporation’s Characteristics and LIS(Logistics ...s-space.snu.ac.kr/bitstream/10371/1810/1/SJBv10n2_049.pdf · Corporation’s Characteristics and LIS(Logistics Information System)

Documents