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This is to certify that the

dissertation entitled

The Effect of Information Quality on Supply Chain
Performance: An Interorganizational lnfonnation
System Perspective

presented by

Kenneth J. Petersen

has been accepted towards fulfillment
of the requirements for

Doctor of Philosophy degree in Business Administration

/W%%/7M

Major professor

July 15: 1999

MSU is an Affirmative Action/Equal Opportunity Institution 0- 12771

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1/93 mm.“

 

 

 

THE 1
PERFORM

THE EFFECT OF INFORMATION QUALITY ON SUPPLY CHAIN
PERFORMANCE: AN INTERORGANIZATIONAL INFORMATION SYSTEM
PERSPECTIVE
By

Kenneth James Petersen

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Department of Marketing and Supply Chain Management

1 999

THE EF
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This rt
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decisions ma}

The '3

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ABSTRACT

THE EFFECT OF INFORMATION QUALITY ON PERFORMANCE: AN
INTERORGANIZATIONAL INFORMATION SYSTEM PERSPECTIVE

By

Kenneth James Petersen

This research is conducted within the broad theme of how interorganizational
information systems may help firms to make better decisions and how these improved
decisions may lead to improved firm performance.

The theoretical model developed in this research reflects the notion that when
higher quality information is exchanged between supply chain partners, outcomes of joint
planning and decision-making processes will be improved, which will lead to improved
firm performance. Within this framework, one of the fimdamental propositions is that an
effective interorganizational information system will increase the quality of the
information exchanged between supply chain partners. The increased quality of
information associated with interorganizational information systems is expected to be
associated with better outcomes from joint planning and decision making processes,

Which are in turn expected to be associated with greater levels of performance.

The Ilicor
chain managers 2
equation modcln
associated \\ uh I

Key resa
significant impa
processes and it
outcomes. Funi
joint planning a
niaorganizatin

interorganizatic

The theoretical model was tested using a sample of 169 purchasing and supply
chain managers and executives primarily located in the United States. Structural
equation modeling (SEM) was employed in this research to estimate the parameters
associated with the relationships of interest.

Key results from this research include the finding that information quality has a
significant impact on the outcomes of eight different joint planning and decision making
processes and that these processes are associated with certain firm-level performance
outcomes. Further, within several of these processes, the effect of information quality on
joint planning and decision making outcomes is significantly larger for
interorganizational information system enabled information quality than for non-
interorganizational information system enabled information quality.

Theoretical and practical insight is developed within each of the eight joint

planning and decision making contexts.

Copyright by
KENNETH J. PETERSEN
1999

This research
”Tough this d

10hr

This research is dedicated to Sigrid, Erin, Andrew and John. Without your friendship,
this work would never have been completed. Sigrid - - your understanding and support
through this difficult process has been nothing short of phenomenal. Erin, Andrew and

John — each of you helped your dad along in your own special way.

 

Mould iii
to sapport this res
Chain Benchmark
financial support ;
thank the dissertat
(loss for their ins

Finally. I‘

hsliandeuidanct

ACKNOWLEDGMENTS

I would like to thank Dr. Robert Monczka for his patience, time and willingness
to support this research. I would also like to thank The Global Procurement and Supply
Chain Benchmarking Initiative at Michigan State University for graciously providing
financial support and access to the world’s most leading-edge companies. I would like to
thank the dissertation committee, Dr. Gary Ragatz, Dr. Robert Handfield and Dr. David
Closs for their insightful contributions to this work.

Finally, I would like to thank my father, Dr. Russell J. Petersen, for his support,

help and guidance.

vi

 

Abstract ..............
Table of Contents
list of Table .....

list olfigures

list of Abbrex ia:

Chapter 1 ...........

introduction .......
Research
lmportan
Research
Oi‘en'ie‘.
Scope of
HEPOlhe
OVEIVIET

[letter 7 ..........

Rois“ and SUV
Sarah I
This.

Table of Contents

Abstract ............................................................................................................................... ii
Table of Contents .............................................................................................................. vii
List of Tables .................................................................................................................... xii
List of Figures ................................................................................................................. xvii
List of Abbreviations ....................................................................................................... xix
Chapter 1 ............................................................................................................................. 1
Introduction ......................................................................................................................... 1
Research Question .................................................................................................. 1
Importance of the Research .................................................................................... 1
Interorganizational Integration Defined .......................................... 6

Interorganizational Information Systems Defined .......................... 7

Research Question .................................................................................................. 8
Overview of the Research ....................................................................................... 9

Scope of Research ................................................................................................. 10
Hypothesized Relationships .................................................................................. 11
Overview of Subsequent Chapters ........................................................................ 20
Chapter 2 ........................................................................................................................... 21
Review and Summary of the Literature ............................................................................ 21
Supply Chain Integration ...................................................................................... 21
Interorganizational Information Systems Theory ................................................. 23
Interorganizational Information System Typologies .................... 23

Information Quality ...................................................................... 25

vii

Charter 3 ...........
Research \lethot
.\TOthl Dz

Construct

Research

Environmental Uncertainty ........................................................... 26

Trust .............................................................................................. 28
Interdependence ............................................................................ 29

Business Results Attributed to Interorganizational Information
Systems ......................................................................................... 29
Interorganizational Integration ...................................................... 30
Chapter 3 ........................................................................................................................... 34
Research Methodology ..................................................................................................... 34
Model Description ................................................................................................ 34
Construct Definitions ............................................................................................ 36
Information Quality ...................................................................... 36
108 Enabled Communication ....................................................... 37
Non-IOS Enabled Communication ............................................... 37
Joint Planning and Decision-Making ............................................ 38
Context 1: Forecasting and Inventory Positioning ............ 39
Context 2: Inventory Visibility ......................................... 39
Context 3: Capacity Planning ........................................... 4O

Context 4: Post Supplier Selection Performance

Evaluation/Feedback and Conformance ......... 4O
Context 5: Sourcing and Supply Proposal Evaluation ...... 4O
Context 6: Part/Material Standardization .......................... 4O
Context 7: Supplier Scheduling ........................................ 41
Context 8: Joint Goal/Target Setting ................................ 41
Supply Uncertainty ....................................................................... 42
Trust .............................................................................................. 43
Interdependence ............................................................................ 44
Performance Outcomes ................................................................. 44
Research Design .................................................................................................... 45

viii

Unit of A

 

Data C Gilt

Confimiaz

‘o
‘-
'-
u
'-
'o

Unit of Analysis .................................................................................................... 45

Data Collection ..................................................................................................... 46

Data Collection Procedure ............................................................ 46

Survey Instrument Review/Pretest ................................................ 46

Primary Sample ............................................................................. 47

Non-Response Bias ....................................................................... 48

Measurement Development .......................................................... 48

Confirmatory Factor Analysis ............................................................................... 48
Convergent Validity ...................................................................... 49

Discriminant Validity .................................................................... 50

Nomological Validity .................................................................... 50

Structural Model ........................................................................... 50

Chapter 4 ........................................................................................................................... 52
Research Findings & Hypothesis Testing ......................................................................... 52
Preliminary Analysis ......................................................................................................... 52
Characteristics of the sample ................................................................................ 53
Non-Response Bias ............................................................................................... 55
Overall Construct Development ....................................................................................... 56
Measurement Validation ................................................................................................... 57
Descriptive Statistics ............................................................................................. 58
Measurement Reliability ....................................................................................... 59
Construct Validity ................................................................................................. 6O
Reliability .............................................................................................................. 61
Structural Equation Model .................................................................................... 65
Hypothesis Testing ........................................................................ 69

Chapter 5 ........................................................................................................................... 73
Discussion of Research Findings ...................................................................................... 73

ix

 
   

Discussion of C.
Forecasti
Inventory
C apacity 1
Post Supp
Sourcing
Part \latc
Suppherf
Joint Goa

hlanagcn'

Discussion of Critical Research Findings ......................................................................... 74

Forecasting and Inventory Positioning ................................................................. 77
Inventory Visibility ............................................................................................... 82
Capacity Planning ................................................................................................. 86

Post Supplier Selection Performance Evaluation/Feedback and Conformance 9O

Sourcing and Supply Proposal Evaluation ............................................................ 94
Part/Material Standardization ............................................................................... 99
Supplier Scheduling ............................................................................................ 103
Joint Goal/Target Setting .................................................................................... 107
Managerial Implications ..................................................................................... 1 1 1
Priority 1: Joint Goal/Target Setting ........................................... 114

Priority 1: Post Supplier Selection Performance
Evaluation/Feedback and Conformance ..................................... 115
Priority 1: Part/Material Standardization .................................... 115
Priority 1: Sourcing and Supply Proposal Evaluation ................ 116
Priority 2: Capacity Flaming ...................................................... 1 17
Priority 2: Supplier Scheduling ................................................... 117
Priority 3: Forecasting and Inventory Positioning ...................... 118
Priority 3: Inventory Visibility .................................................... 1 18
Summary and Conclusion ................................................................................... 120
Research Extensions ....................................................................................................... 121
Research Limitations ...................................................................................................... 121
Appendix A: Key Definitions ......................................................................................... 124
Appendix B: Structural Equation Methodology Symbols/Definitions ........................... 127
Appendix C: Survey Cover Letter .................................................................................. 129
Appendix D: Survey Fax-Back Response Form ............................................................. 131
Appendix E: Survey Instrument ...................................................................................... 133
Appendix F: Non-Response Bias .................................................................................... 142

Appendix G“. CO?

   
 
    

Forecast:
lnientor}
C apacits
Post Supp
Sourcing 111
Part \lateri
Supplier St

Joint Gdal

Appendix H: Strut

Forecastm
lnrentory
Capacityl
Post Sup;
Sourcing
Parthlat
Supplier
loint Gc
hppmdix 1: De
dependix J: P0
Appendix K: Ir
hlittendirr L: .\
Appendix Mil

Biblj

3??
“v

aphy

Appendix G: Confirmatory Factor Analysis ................................................................... 146

Forecasting and Inventory Positioning ............................................................... 147
Inventory Visibility ............................................................................................. 148
Capacity Planning ............................................................................................... 149

Post Supplier Selection Performance Evaluation/Feedback and Conformance . 150

Sourcing and Supply Proposal Evaluation .......................................................... 151
Part/Material Standardization ............................................................................. 152
Supplier Scheduling ............................................................................................ 153
Joint Goal/Target Setting .................................................................................... 154
Appendix H: Structural Equation Models ....................................................................... 155
Forecasting and Inventory Positioning ............................................................... 156
Inventory Visibility ............................................................................................. 157
Capacity Planning ............................................................................................... 158

Post Supplier Selection Performance Evaluation/Feedback and Conformance . 159

Sourcing and Supply Proposal Evaluation .......................................................... 160
Part/Material Standardization ............................................................................. 161
Supplier Scheduling ............................................................................................ 162
Joint Goal/Target Setting .................................................................................... 163
Appendix 1: Descriptive Statistics .................................................................................. 164
Appendix J: Post Hoc Analysis ....................................................................................... 168
Appendix K: Information Quality Paired Samples T-Tests ............................................ 173
Appendix L: Multiple Regression Difference Tests ....................................................... 178
Appendix M: University Committee on Research Involving Human Subjects .............. 183
Bibliography ................................................................................................................... l 85

xi

Table l: Bensaou t

 

 

Table 3: Zahecr an
Table 3.: Attributes
Tablet lOS Ena'o
Table 5: Non-lOS
Table 6: Supply L'-
Table 7: Trust (C u
Table 8: Trust (Za
Table 9: lnterdcpc
We 10'. Firm pe

Table ll: Data Cc

Table 12: Sthrctui

List of Tables

Table l: Bensaou (1997) Empirical Findings ................................................................... 31
Table 2: Zaheer and Venkatraman (1994) Empirical Findings ........................................ 32
Table 3: Attributes of Information Quality ....................................................................... 36
Table 4: IOS Enabled Information Communication ......................................................... 37
Table 5: Non-IOS Enabled Information Communication ................................................. 38
Table 6: Supply Uncertainty ............................................................................................. 43
Table 7: Trust (Cummings and Bromily) .......................................................................... 43
Table 8: Trust (Zaheer & Venkatraman, 1994) ................................................................ 43
Table 9: Interdependence (Lusch and Brown, 1994) ........................................................ 44
Table 10: Firm Performance ............................................................................................. 45
Table 11: Data Collection Procedure ................................................................................ 46
Table 12: Structural Equations .......................................................................................... 51
Table 13: Informant's Job Title ......................................................................................... 53
Table 14: Sample Demographic Information ................................................................... 54
Table 15: Effective Response Rate Calculation ............................................................... 55
Table 16: Fax-Back Response Form Results .................................................................... 55
Table 17: Reliability Estimates (Cronbach’s Alpha) ........................................................ 59
Table 18: Key Parameter Estimates (CFA) ...................................................................... 62
Table 19: Goodness of Fit Statistics (CFA) ...................................................................... 64
Table 20: Key Parameter Estimates (SEM) ...................................................................... 67
Table 21: Goodness of Fit Statistics (SEM) ..................................................................... 68
Table 22: Hypothesis Testing Summary ........................................................................... 72

xii

 

Table 23: C harac

   

Table 34: Bii'ari ‘-
Perfor:

Table 25: F orecas
Table 36: lni'ento.
Table 37: C apacit;

Table 38. Post Sup
Confon:

 

Table 39: Sourcin:
Table 30: Part \lat:
Table3l: Supplier
Table 32: Joint Go;
Tableii: CPA - Ft
Table 3.4: CPA - Fr-

Table 35: CPA - F,
Correlat

Table 36: C F A - lr
Table 3.7: CPA , Tr
Table3g; CPA ‘ Ir
7501639: CPA \ (
Tabled+0: CPA - (
Table 41: CPA \(

COnfon
Table 43. CPA

Table 23:
Table 24:

Table 25:
Table 26:
Table 27:
Table 28:

Table 29:
Table 30:
Table 31:
Table 32:
Table 33:
Table 34:
Table 35:

Table 36:
Table 37:
Table 38:
Table 39:
Table 40:
Table 41:
Table 42:

Table 43:

Table 44:

Table 45:
TIEII)IIE: 41(3:

Characteristics of Joint Planning and Decision Making Processes .................. 76

Bivariate Correlation’s Between JPDM Outcomes and Key Firm

Performance Indicators .................................................................................. l 13
Forecasting and Inventory Positioning - Non-Response Bias ........................ 143
Inventory Visibility - Non-Response Bias ...................................................... 143
Capacity Planning — Non-Response Bias ....................................................... 144
Post Supplier Selection Performance Evaluation/Feedback and

Conformance — Non-Response Bias .............................................................. 144
Sourcing and Supply Proposal Evaluation — Non-Response Bias .................. 144
Part/Material Standardization — Non-Response Bias ..................................... 145
Supplier Scheduling — Non-Response Bias .................................................... 145
Joint Goal/Target Setting — Non-Response Bias ............................................ 145
CFA - Forecasting & Inventory Positioning ................................................... 147
CFA - Forecasting & Inventory Positioning - Fit Statistics ........................... 147
CFA - Forecasting & Inventory Positioning — Measurement Error

Correlations .................................................................................................... 147
CFA - Inventory Visibility .............................................................................. 148
CFA - Inventory Visibility - Fit Statistics ...................................................... 148
CF A - Inventory Visibility — Measurement Error Correlations ...................... 148
CFA — Capacity Planning ............................................................................... 149
CFA - Capacity Planning - Fit Statistics ........................................................ 149
CFA - Capacity Planning — Measurement Error Correlations ....................... 149

CFA - Post Supplier Selection Performance Evaluation/Feedback and
Conformance .................................................................................................. 1 50

CFA — Post Supplier Selection Performance Evaluation/Feedback and
Conformance - Fit Statistics ........................................................................... 150

CFA — Post Supplier Selection Performance Evaluation/Feedback and

Conformance — Measurement Error Correlations .......................................... 150
CFA - Sourcing and Supply Proposal Evaluation .......................................... 151
CFA — Sourcing and Supply Proposal Evaluation - Fit Statistics .................. 151

xiii

Table 47: C FA —
C orrel.

 

 

Table 48: C FA -
Table 49: C F A -

 

Table 50: C FA — i

TableSl:CF.-\~5
i

Table 52: CFA — .\_

   
   
 

Table 53: CFA —» S
Table 54: CH — lr
Table551CFA — Tc
Table 56: CFA — lo;
Table 57: SENT - Fo
Table 58: SE31 ‘ lm
Table S9: SENT ~ Ca

Table 60: SENT ~ Po
C onforma

Tableol: SE.\1 ‘ So

Table 62: SENT ~ Pa

Table63zSE.\1 \ su

tare 64: scar ‘ r0
Table65:D ripti\
Table 66: DeSCfiPlir
Tablr'.‘67:D '

Table 47: CFA — Sourcing and Supply Proposal Evaluation — Measurement Error
Correlations .................................................................................................... 1 5 1
Table 48: CFA —- Part/Material Standardization ............................................................. 152
Table 49: CFA — Part/Material Standardization - Fit Statistics ...................................... 152
Table 50: CFA — Part/Material Standardization — Measurement Error Correlations ..... 152
Table 51: CFA — Supplier Scheduling ............................................................................ 153
Table 52: CFA — Supplier Scheduling - Fit Statistics ..................................................... 153
Table 53: CFA — Supplier Scheduling — Measurement Error Correlations .................... 153
Table 54: CFA - Joint Goal/Target Setting .................................................................... 154
Table 55: CFA — Joint Goal/Target Setting - Fit Statistics ............................................. 154
Table 56: CF A - Joint Goal/Target Setting — Measurement Error Correlations ............ 154
Table 57: SEM - Forecasting & Inventory Positioning - Fit Statistics ........................... 156
Table 58: SEM - Inventory Visibility — F it Statistics ..................................................... 157
Table 59: SEM — Capacity Planning — Fit Statistics ....................................................... 158

Table 60: SEM — Post Supplier Selection Performance Evaluation/Feedback and
Conformance — Fit Statistics .......................................................................... 159
Table 61: SEM — Sourcing and Supply Proposal Evaluation — Fit Statistics ................. 160
Table 62: SEM — Part/Material Standardization — Fit Statistics ..................................... 161
Table 63: SEM — Supplier Scheduling — Fit Statistics .................................................... 162
Table 64: SEM — Joint Goal/Target Setting — Fit Statistics ............................................ 163
Table 65: Descriptive Statistics - Forecasting and Inventory Positioning ...................... 165
Table 66: Descriptive Statistics - Inventory Visibility ................................................... 165
Table 67: Descriptive Statistics - Capacity Planning ...................................................... 165
Table 68: Descriptive Statistics - Post Supplier Selection Performance

Evaluation/Feedback and Conformance ........................................................ 166
Table 69: Descriptive Statistics - Sourcing and Supply Proposal Evaluation ................ 166
Table 70: Descriptive Statistics - Part/Material Standardization .................................... 166
Table 71: Descriptive Statistics - Supplier Scheduling ................................................... 167

xiv

Table 72: Desct‘.

Table 73: Foreca
and Dr

 

Table 74: 1mm
Malls.

Table 75: C apacr:

blahin:

Table 76: Post Sn;
C onion:
Outcom

 

Table 77: Sourcing
Planning
Dimensr

Table ’8: Panblar
Decisior

Table 79: Supplier
Making

Table 80: Joint Go.
Decisior

Table Sl: Paired S.
Table 82: Pal

Tab

red 3:

if 83: Paired S.

Table 84: Paired S.

Ei‘aluati

Table 85: Paired S
Table 36: Paired S
Tabled? PairEd S

Table 88'- Paired S

Table 72:
Table 73:

Table 74:

Table 75:

Table 76:

Table 77:

Table 78:

Table 79:

Table 80:

Table 81:
Table 82:
Table 83:
Table 84:

Table 85:
Table 86:
Table 87:
Table 88:
Table 89:
Table 90:
Table 91:

Descriptive Statistics - Joint Goal/Target Setting ........................................... 167

Forecasting and Inventory Positioning — Associations of Joint Planning
and Decision Making Outcomes and F inn Performance Dimensions ........... 169

Inventory Visibility — Associations of Joint Planning and Decision
Making Outcomes and Firm Performance Dimensions ................................. 169

Capacity Planning — Associations of Joint Planning and Decision
Making Outcomes and Firm Performance Dimensions ................................. 170

Post Supplier Selection Performance Evaluation/Feedback and
Conformance — Associations of Joint Planning and Decision Making
Outcomes and Firm Performance Dimensions .............................................. 170

Sourcing and Supply Proposal Evaluation — Associations of Joint
Planning and Decision Making Outcomes and Firm Performance
Dimensions ..................................................................................................... l 71

Part/Material Standardization — Associations of Joint Planning and
Decision Making Outcomes and Firm Performance Dimensions .................. 171

Supplier Scheduling — Associations of Joint Planning and Decision
Making Outcomes and Firm Performance Dimensions ................................. 172

Joint Goal and Target Setting — Associations of Joint Planning and

Decision Making Outcomes and Firm Performance Dimensions .................. 172
Paired Sample T-Test - Forecasting and Inventory ........................................ 174
Paired Sample T-Test - Inventory Visibility .................................................. 174
Paired Sample T~Test - Capacity Planning ..................................................... 175
Paired Sample T-Test - Post Supplier Selection Performance

Evaluation/Feedback and Conformance ........................................................ 175
Paired Sample T-Test - Sourcing and Supply Proposal Evaluation ............... 176
Paired Sample T-Test - Part/Material Standardization ................................... 176
Paired Sample T-Test - Supplier Scheduling .................................................. 177
Paired Sample T-Test - Joint Goal and Target Setting ................................... 177
Forecasting and Inventory Positioning Beta Difference Test ......................... 179
Inventory Visibility Beta Difference Test ...................................................... 179
Capacity Planning Beta Difference Test ......................................................... 180

XV

 

Table 92: Post S I
C onto
Table 93: Sourcr:|
Table 94: Part 31
Table 95: Supplie-

Table 96: Joint Ct

 

Table 92: Post Supplier Selection Performance Evaluation/Feedback and

Conformance Beta Difference Test ................................................................ 180
Table 93: Sourcing and Supply Proposal Evaluation Beta Difference Test ................... 181
Table 94: Part/Material Standardization Beta Difference Test ....................................... 181
Table 95: Supplier Scheduling Beta Difference Test ..................................................... 182
Table 96: Joint Goal/Target Setting Beta Difference Test .............................................. 182

xvi

 

 

 

 

 

Figare l: Explana:
Figure 2: Supplzer
Figurei: Model D
Figure 4: ln format
Figure 5: Model D
Figure 6: Key Bus
Figure 7: Suppl}: 6

Figure 8: L'nit of .-

List of Figures

Figure 1: Explanatory Model Overview ............................................................................. 9
Figure 2: Supplier Integration Processes (GEBN, 1996) .................................................. 11
Figure 3: Model Description (with Hypotheses) .............................................................. 12
Figure 4: Information Elements ........................................................................................ 14
Figure 5: Model Description (with Hypotheses) .............................................................. 34
Figure 6: Key Business Processes ..................................................................................... 39
Figure 7: Supply & Demand Uncertainty ......................................................................... 42
Figure 8: Unit of Analysis ................................................................................................. 47
Figure 9: Model Description (with Hypotheses) .............................................................. 52
Figure 10: Revised Explanatory Model ............................................................................ 57
Figure 11: Forecasting & Inventory Positioning Process Improvements ......................... 80
Figure 12: Inventory Visibility Process Improvements .................................................... 84
Figure 13: Capacity Planning Process Improvements ...................................................... 88
Figure 14: Post supplier selection performance evaluation/feedback and

conformance process improvements ................................................................ 93
Figure 15: Supply proposal evaluation process improvement .......................................... 96
Figure 16: Joint part/material standardization process improvements ........................... 102
Figure 17: Supplier Scheduling Process Improvements ................................................. 106
Figure 18: Joint Goal/Target Setting Process Improvements ......................................... 109
Figure 19: Joint Goal/Target Setting Process ................................................................. 110
Figure 20: IOS Development Priority Matrix ................................................................. 114

xvii

Figure 2l: SEM .
Figure 22: SEM -

Figure :3; srzsr -

 

 

 

Figure 24: SEM -
C ont'or'i

Figure 25: SEM; 5'
Figure 26: SEM - T
Figure 2“: SEM - C

Figure 28; SEM - Jr

Figure 21: SEM - Forecasting & Inventory Positioning ................................................. 156

Figure 22: SEM - Inventory Visibility ............................................................................ 157
Figure 23: SEM - Capacity Planning .............................................................................. 158
Figure 24: SEM - Post Supplier Selection Performance Evaluation/Feedback and
Conformance .................................................................................................. 159
Figure 25: SEM: Sourcing and Supply Proposal Evaluation .......................................... 160
Figure 26: SEM - Part/Material Standardization ............................................................ 161
Figure 27: SEM - Supplier Scheduling ........................................................................... 162
Figure 28: SEM - Joint Goal/Target Setting ................................................................... 163

xviii

BBNFI ............
BB.\.\'Fl

oooooooooo

CFA........,....

 

CFl..........,, .
EDI ..................
FCS......
lOS

lbl.....,,,

PFC .................

TCA........

List of Abbreviations

BBNFI ............................................ Bentler-Bonett Normed F it Index
BBNNFI .......................................... Bentler-Bonett Non-Normed Fit Index
CF A ............................................... Confirmatory Factory Analysis

CF I ................................................ Comparative Fit Index

EDI ................................................ Electronic Data Interchange

ERP .............................................................. Enterprise Resource Planning

F CS ................................................ Feedback Control System

108 .............................................................. Interorganizational Information System
LM ................................................ Lagrange Multiplier

IS .................................................. Information System

IT .................................................................. Information Technology

PEU .............................................................. Perceived Environmental Uncertainty
RFQ ............................................... Request for Quotation

TCA .............................................................. Transaction Cost Analysis

TCE .............................................................. Transaction Cost Economics

VAN ............................................................. Value Added Network

VMI .............................................................. Vendor Managed Inventory

VP ................................................. Vice President

XML ............................................................. Extensible Markup Language

xix

 

This research
quality affect interor;
atTect performance or
interorganizational in
stalled information q
outcomes. Furrhemro
manufacturing. proc ur

Ptocesses, Ans“ ering

metric literature as t

We)

{Wider to acbr

lift: Ollll' -

C!

Page their on
with [h l'

e. Participate. T

Chapter 1

The solution of today’s major social problems will come

from more and better technology - not from less

technology. For technology is just another name for human

knowledge. We need to deepen our scientific knowledge,

broaden our repository of alternatives, and strengthen our

technology of decision procedures. Above all, we need a

more profound understanding of man himself, for all

human problems have their roots in our own nature.

(Simon, 1973)

Introduction
Research Question
This research attempts to answer three primary questions: (1) Does information
quality affect interorganizational integration?; (2) Does interorganizational integration
affect performance outcomes?; (3) Is there a difference between the effect of
interorganizational information system and non-interorganizational information system
enabled information quality on interorganizational integration and performance
outcomes. Furthermore, this examination is done in the context of eight different
manufacturing, procurement and supply chain joint planning and decision making
processes. Answering these three research questions will fill a critical void in the
academic literature as well as provide practical insight that is usable by practitioners
today.
Importance of the Research
In order to achieve preeminence in today's competitive marketplace firms must

not only manage their own operations, but they must also manage the supply chains in

Which they participate. The role of each supply chain member in managing the supply

chain mal' "39
chain. HOWCVCT.
contribute in so".
emphasized this
customer is not g

that the leanest cl

 

 

A supplr‘r
manufacturing ant
intermediate and f
(Tee 8; Billington.
materials and com
Stpport of the obs.
that (3) these bette
Manning counte
Pttiorming SUppl)‘
(Anonymous, 199'
(Sheridan 199m ;
(Sheridan 1998).

HOW Well i
Sigm'ficam elTect o
3393 0i the firms tl
noted 3 particulars

cheer relates to h
o

chain may vary depending on the fianction of that supply chain member in the supply

chain. However, in order for the supply chain to function optimally, all members must
contribute in some way to the management of the supply chain. Jeff Trimmer of Chrysler
emphasized this point when he noted that "if any one of the links breaks or fails, the
customer is not going to be satisfied. And one thing that has become apparent to us is
that the leanest chain wins" (Sheridan, 1998).

A supply chain is defined in this research as an "organization of networks of
manufacturing and distribution sites that procure raw materials, transform them into
intermediate and finished products, and distribute the finished products to customers"
(Lee & Billington, 1992). This definition includes the suppliers from whom the raw
materials and components, subsystems and systems are purchased. There is evidence in
support of the observation that (1) there are indeed better performing supply chains and
that (2) these better performing supply chains are more competitive than their poorer

performing counterparts. A recent study conducted by PRTM revealed that top
Performing supply chains have achieved significant reductions in supply chain costs
(Anonymous, 1997 a) including 40% to 65% reductions in cash-to-cash cycle times
(Sheridan, 1998) and 50% to 80% reductions in inventory compared to competitors

(Sheridan, 1998).

How well information is shared between firms in a given supply chain can have 3
Significant effect on the performance of the supply chain as well as the performance of
each of the firms that belong to the supply chain. Lee, Padmanabhan and Whang (1997)
noted a particular supply chain problem they termed the "bullwhip effect." The bullwhip

effect relates to how "distorted information from one end of a supply chain to the other

 

can lead to UCITTL
senice. lost reye
production schec'
to have efficient r
supplychain mar~ .
onllne-inquiry acth
availability aggres-
I99'b).
lnterorganr.»

may share this infor

interorganizational i

 

lnfort
et ery
perfo:
also i
produ
it by

sight

technr

Balsrneier an

Integral

ton is market
”mutt informatio

possible without the

intonation exchan

.
‘-._'I
\‘

Tittle:

Dyer t.
their 0]
Dramar

can lead to tremendous inefficiencies: excessive inventory investment, poor customer
service, lost revenues, misguided capacity plans, ineffective transportation, and missed
production schedules" (Lee et al., 1997). Andreas Rulke (PRTM) believes that the need
to have efficient information flow within a supply chain is critical. Rulke wrote that "the
supply-chain management team must have full visibility of the product pipeline and
online-inquiry access to end-user demand, vendor supply actions, and current material
availability aggregated across the entire supply chain of its company" (Anonymous,

1 997b).

Interorganizational information systems provide a mechanism by which firms
may share this information. Porter and Millar (1985) described the importance of
interorganizational information systems to supply chain management when they wrote:

Information technology is permeating the value chain at
every point, transforming the way value activities are
performed and the nature of the linkages among them. It
also is affecting competitive scope and reshaping the way
products meet buyer needs. These basic effects explain
why information technology has acquired strategic
significance and is different from the many other
technologies businesses use.

Balsmeier and Voisin (1996) argue that the ultimate level of supply chain
integration is marked by members of the supply chain continuously exchanging all
necessary information. The authors believe that this level of information flow is not

POSSible without the use of information technology as a medium for interorganizational
inf Orniation exchange. Evans and Wurster (1997), adopting a more iconoclastic view,

Wrote:

Over the past decade, managers have focused on adapting
their operating processes to new information technologies.
Dramatic as those operating changes have been, a more

Roger Ste
quoted as saying.
through the Mich;
Benchmarking lnr
process. and seryic
mtt'ytluough purcl
competitive adi'ant.
companies that do L
that the lcey enabler

the changes that hay

 

Ittttod:

profound transformation of the business landscape lies
ahead. Executives - and not just those in high-tech or
information companies - will be forced to rethink the
strategic fundamentals of their businesses. Over the next
decade, the new economics of information will precipitate
changes in the structure of entire industries and in the ways

companies compete.

Roger Sterling, Vice President of Global Supply Management at Honeywell, was
quoted as saying, "I subscribe to the definition of supply chain management developed
through the Michigan State University Global Procurement and Supply Chain
Benchmarking Initiative. That is, 'efforts to link customer requirements, new product,
process, and service development, and order fulfillment activities (from customer order
entry through purchasing, manufacturing and operations, and distribution) so as to gain
competitive advantage in terms of cost, quality, time, or technology.‘ I believe that

companies that do this well will have a sustainable competitive advantage. I believe also
that the key enabler is an integrated information system" (Porter, 1997). Writing about
the changes that have occurred recently in supply chain management, Lawrence Gould

noted:

What is different today are the technologies that make
those fiandamentals [supply chain management] more
efficient and productive, and that give enterprises the
ability to respond to a customer's request quickly. Another

difference is that the concept of "supply chain" goes well
beyond the enterprise and includes both customers and

suppliers (Gould, 1998).

The role of information technology within organizations has undergone a key
tr"-‘tnSfonnation that has led us to expand our view of how information technology can and
should be employed. We once viewed information technology as a tool used to provide
improvements in efficiency through the automation of tasks. We now view information

technology as a key enabler to creating and maintaining a flexible business network of

uremrsanlla‘lo’
suppotl for This l

T}
S
Ct

I
Ct l
ct
“L
SL‘I'
lllt.‘

I
C037

KO'I

 

-—~‘

C ab and K
interorganizational

across company bor

 

lnpractice.i
.' . .
tnerorganizatronal i
lotrnterorganizatlon
Seen in the deyelopn'
.lctrt'ell'b

e Integratrr.

flatware, 1 9913/3) V

E”? . ,
”WIS? (So/Tit are

interorganizational arrangements (Venkatraman, 1994). Cash and Konsynski provided
support for this notion when they wrote:
These systems, defined as automated information systems
shared by two or more companies, will significantly
contribute to the enhanced productivity, flexibility, and
competitiveness of many companies. However, current
examples illustrate that some interorganizational systems
will radically change the balance of power in buyer-
supplier relationships, provide entry and exit barriers in
industry segments, and in most instances, shift the

competitive position of intra-industry competitors (Cash &
Konsynski, 1985).

Cash and Konsynski's writings underscore the critically important role that
interorganizational information systems will play in enabling the sharing of information
across company boundaries.

In practice, it is evident that many companies are attempting to adopt the spirit of
interorganizational information system enabled interorganizational integration. The push
for interorganizational information system enabled interorganizational integration may be

seen in the development of such software as CrossRoute Alliance (Software, 1998c),
Active Web Integration System (Software, 1998(1), Crossroads Customer Interaction
(Saftware, I998b), NEONet (Networks, 1998), Prospero (Software, 1998d), T IB/Active
Enterprise (Software, I 998e) and Vitria Business Agility (Technology, 1998) which are
all designed to allow disparate enterprise resource planning (ERP) implementations to
interconnect on a cross-enterprise basis. It is hoped that this interorganizational
"bridging" software will further enable companies to more seamlessly integrate different
types of interorganizational information flows, contributing to increased
inteI‘organizational integration. Further, it is estimated that the integration software

mar ket will grow from $650M in 1997 to $48 by 2002. This underscores the fact that

companiCS are P

 

interorganizatiotl

As anotl‘tl
Editorial Board t
Internet standard
standard is being I
World Wide \l'cb
Wt is an open SI

1997), The import

pushing hard/'0' 5

 

business processes

“his much
supply chain integr;
determine whether i
integrated. better pc
(1992; 1997) and 22
iIltftorganizational i
mmtganizational i

Into. ' '
organizational l

The notion o:

companies are placing a very high value on the ability to create and maintain

interorganizational information systems.

As another example, the XML Working Group (1998) (formerly the SGML
Editorial Board) chaired by John Bosak of Sun Microsystems has developed a new
Internet standard designated the "Extensible Markup Language" or "XML." This
standard is being developed as a reincarnation of EDI that is designed for use across the

World Wide Web, as opposed to the more traditional VAN frequently employed by EDI.
XML is an open standard that will very likely take the place of traditional EDI (Adams,
1997). The important take away from these two examples is that companies are

pushing hard for solutions that will allow effective electronic integration across key

business processes on an interorganizational basis.

While much has been written about interorganizational information systems and
supply chain integration in the popular press, little substantive research has been done to

determine whether interorganizational information systems help to create more

integrated, better performing supply chains. Two notable exceptions include Bensaou
( 1 992; 1997) and Zaheer and Venkatraman (1994) who each theorized that

interorganizational information systems act as an antecedent to successful

interorganizational integration.

Interorganizational Integration Defined

The notion of interorganizational integration is central to the theoretical

 

fratTlework adopted in this research. McGee noted that interorganizational integration is

marked by the extent to which interdependent activities which link interacting

organizational units are viewed, operated and managed as a single system (McGee,

i991). 5156“"

 

Wallzed 1mg:

interacting. (3) 5"

 

and (4) common
interorganization.
interorganization;
interorganiztrtrorn.
mppit (hum are t';

encompasses Clem

 

'...the extent to ssh
distinguished from I

motions. Reddi. 3;

L3,.”
AV

organizational 1
Cash and Ko

‘ f
lamination svstem l

interorganizational ll

dentition is simple

Intonnation system it

arldcOrrttnunications
a} .

d3hafelttforman‘or
def

.ne '
a“ ‘meTOIEaniz

1991). McGee also noted that interorganizational integration is often reflected in (1) a
specialized language system for interaction, (2) jointly developed procedures for
interacting, (3) subordination of individual performance measures to system performance,
and (4) common conceptual maps of the environment (McGee, 1991 ). This treatment of
interorganizational integration forms the foundation for the definition of
interorganizational integration that is adopted in this research. Specifically,
interorganizational integration is defined as the extent to which interacting members of a
supply chain are viewed, operated and managed as a single system. This definition also
encompasses Clemons’ notion of 'explicit coordination,’ which has been defined as

". . .the extent to which decisions reflect and are tailored to a specific relationship, and is
distinguished from the implicit coordination of the invisible hand of market competition"

(Clemons, Reddi, & Row, 1993; Clemons & Row, 1992).

Interorganizational Information Systems Defined

Cash and Konsynski (1985) developed the definition of an interorganizational
information system that will be adopted by this research. Many researchers studying
interorganizational information systems have employed this definition. While the
definition is simple, it captures the essential elements of an interorganizational
information system which include (1) the use of information technology (both computer
and communications technologies) to (2) enable different organizations to create, manage

and share information with other organizations. Specifically, Cash and Konsynski (1985)

define an interorganizational information system as:

 

This resear

 

quality ailect intert
affect performance
information system
quality on interorg;

Firms on at
lIL‘orrnation system
than in which the
WW interorganiz
block to creating be
Ml}; interorgam;

havering these thr

[a] system which ...[is]... built around information
technology, i.e., around the computer and communications
technology that facilitates the creation, storage,
transformation, and transmission of information. An
interorganizational system differs from an internal,
distributed information system by allowing information to
be sent across organizational boundaries. Access to stored
data and applications programs is shared, sometimes to
varying degrees, by the participants in an
interorganizational system.

Research Question
This research attempts to answer three primary questions: (1) Does information
quality affect interorganizational integration?; (2) Does interorganizational integration
affect performance?; (3) Is there a difference between the effect of interorganizational
information system and non-interorganizational information system enabled information
quality on interorganizational integration and performance.

Firms on a worldwide basis are in the process of purchasing and installing
information systems to enable the management of not just their own firms, but the supply
Chains in which their firms participate. The popular press has heralded the marked trend
toward interorganizational technology adoption often as both a solution and a stumbling

block to creating better performing supply chains. The relationship between information
quality, interorganizational integration and performance has yet to be empirically tested.
Answering these three research questions will fill a critical void in the academic literature

as Well as provide practical insight that is usable by practitioners today.

 

The th’L“

notion that whct‘.

NOT-JUN lid»;
// l'ti'tr‘nrtv i.-

 

 

 

Overview of the Research

The theoretical model to be tested in this research (see Figure 1) reflects the

notion that when higher quality information is exchanged between supply chain

 
     
 

.............................

Supply Uncertainty

.................................

Non-lOS Based

; lnformation Quality \ ---------- i ---------------- \
: Joint Planning and 3 3 Performance 5
I ' I :
‘ : Outcomes 5

: Decision Making .
5 Outcomes 3 """""""""""""""

,_._-_,__ffjtfff"jfjfifififiiffifffifi.------3

ilOS Based Information ; y .
I E 5 3 5 Interdependence g

   
   
   
 

Figure 1: Explanatory Model Overview

Partners, joint planning and decision-making outcomes will be improved, leading to
higher levels of performance. Within this framework, the fundamental proposition is that
the use of an interorganizational information system will increase the quality of the
information shared between supply chain partners. The increased quality of information
associated with interorganizational information systems is expected to be associated with
better joint planning and decision making process outcomes, which are in turn expected
to be associated with higher levels of performance. The joint planning and decision
ITia-king construct is developed as a proxy for the integration of supply chain partners on

ey busmess processes. This conceptualization IS conSistent With prevrous conceptions of

interorganizatiot
1991).
L'ncertair'

making processes
uncertainty exist~
making- processes
planning and deei~
decision making p:
uncertainty it ill ha-
tIIempt to it orlt to g
effective in doing sc

associated wi

 

 

 

 

th supp
of supply uncertainty
The trust an

expected to affect the

Partners. The greater

Mutts. the more lilo
making processes. 1}

Oldigning each of the

This research Vt

Chap"
M0” Specific pan

Wt .
e968 that are incl u
l

interorganizational integration (Clemons et al., 1993; Clemons & Row, 1992; McGee,
1991)

Uncertainty in supply is theorized to affect both the joint planning and decision
making processes outcomes, as well as overall performance. When greater supply
uncertainty exists, firms will be forced to improve their joint planning and decision-
making processes in order to make the best decisions. This improvement in joint
planning and decision making processes will be evidenced by better joint planning and
decision making process outcomes. Consistent with the same argument, supply
uncertainty will have a negative effect on overall performance. While these firms will
attempt to work together to reduce supply uncertainty, they will only be partially
effective in doing so. Through joint efforts, firms may be able to mitigate the risk
associated with supply uncertainty, but they will not be able to overcome the entire effect
of supply uncertainty on performance.

The trust and interdependence exhibited between supply chain partners is also
expected to affect the joint planning and decision-making processes of these supply chain
partners. The greater the degree of trust and interdependence between supply chain
partners, the more likely those partners are to participate in joint planning and decision
making processes. The interdependence between the supply chain partners has the effect
of aligning each of the supply chain partner’s individual goals with overall system goals.

Scope of Resea_1_rc_h_

This research will examine the interaction between organizations within a supply

chain for a specific part, assembly, service or commodity. Figure 2 is a depiction of the

processes that are included in an integrated approach to creating and managing an

10

integrated supp?

fulfillment cycle

 

 

 

part of an oyerai'
research. Partiei;
system that is use

Productl’rocess

 

 

AS preVlOUS
mt‘ ' l
«161 to be CVaani

ms exNarrators me

my:
at found in Ft.
(l

lite .
in. .‘
Escarch hi‘PO’h
U \ ‘

integrated supply chain. The focus of this research will be the customer order
fulfillment cycle. While the new product/process/service development cycle is a critical
part of an overall interorganizational integration strategy, it is outside of the scope of this
research. Participating firms must have an established interorganizational information
system that is used in the customer order fulfillment process with a focal supplier.

Product/Process/Service Development Cycle

 

   
   
  
 

 

 

 

C Pilot Test
ustomer Concept Design and
Needs
Ramp Up
Customer Order Fulfillment Cycle
' %
gs”
O 8? Pl . grder- Customer
Q? tbs’ anning e ivery Satisfaction
00 Coo Cycle
‘4 s0

 

Figure 2: Supplier Integration Processes (GEBN, 1996)
Hypothesized Relationships
As previous discussed, Figure 1 provides a simplified overview of the explanatory
model to be evaluated in this research. For clarity, definitions of the constructs used in
this explanatory model are summarized in Appendix A. Figure 3 is the same explanatory
model found in Figure l with the addition of the specific research hypotheses. Each of

the research hypotheses labeled in Figure 3 will be described in turn.

 
 
  
 

.............................

;' ---------------------- ; Supply Uncertainty

~'II.'_'.'<_'i'>_’.'l.'}i.5.'.’.'.'.'.'ff.2 "’

 
  
   

 

..................................

.............................

  
 

H) Joint Planning and H9 Performance
M1 (+) H10 if) 5 Decision Making 3 (+) 3 OUICOWS

5 Outcomes """""""""""""""
f """""""""""""""""" . ‘ (+1TH7 (HT H8
: lOS Based Information . ”3

 

3 H1 TruSt Interdependence

 

Quality

................................

  
 

..........................................

Figure 3: Model Description (with Hypotheses)

H1: Interorganizational information system (108) information quality has a direct
and positive effect on joint planning and decision-making outcomes

H2: Non-interorganizational information system (108) information quality has a
direct and positive effect on joint planning and decision-making outcomes

Information quality is defined as the degree to which the information exchanged
between organizations meets the needs of the organizations. Information quality is a
construct that has been employed in a variety of contexts (Bailey & Pearson, 1983; Jones
& McLeod, 1986; King & Epstein, 1983; Miller & Doyle, 1987; Rivard & Hugg, 1984;
Srinivasan, 1985). Several important dimensions of information quality (Goodhue, 1995)
fi'equently employed in the literature include information currency (Bailey & Pearson,
1983; Raymond, 1985), information completeness (Bailey & Pearson, 1983; Baroudi,
1988; Raymond, 1985), information validity and information reliability (Bailey &

Pearson, 1983; Baroudi, 1988; Raymond, 1985). Furthermore, information reliability has

12

be?” panlllOlle
mfonnation rele

1983; BafOUdl- i

 

infonnation has :
helpfulness of th.
information; (3 l 1
information; and 1
important dimensi

(Goodhue. 1995). l

 

Goodhue. 1995 l. C(
timeliness (Bailey 4

the set of tangible h

interorganizational
benefits include red

A higher deg
being exchanged by
and decision makini

been partitioned

ll ll
qaiiytHI i and nor
gratin (HT

. . ~l- e
re
Intonation flows i
s

‘. li -

flatly lhan llOI’l‘iOC

been partitioned into three dimensions that include information accuracy reliability,
information relevancy reliability and information precision reliability (Bailey & Pearson,
1983; Baroudi, 1988; Raymond, 1985). Zmud (1978) noted that the perception of
information has four dimensions, that include (1) the significance, usefulness, or
helpfulness of the information; (2) the accuracy, factualness, and timeliness of the
information; (2) the quality of format or physical presentation and readability of the
information; and (4) the meaningfulness or reasonableness of the information. Other
important dimensions of information quality include information compatibility
(Goodhue, 1995), locatability (Goodhue, 1995), authorization (Bailey & Pearson, 1983;
Goodhue, 1995), convenience of access (Bailey & Pearson, 1983; Raymond, 1985), and
timeliness (Bailey & Pearson, 1983; Raymond, 1985). Performance results are defined as
the set of tangible benefits that accrue to the organization as a result of closer
interorganizational integration with a supply chain partner. Examples of these tangible
benefits include reductions in inventory, cycle-time and cost.

A higher degree of information quality with respect to the information that is
being exchanged by supply chain partners is hypothesized to lead to better joint planning
and decision making outcomes between these supply chain partners. Information quality
has been partitioned into interorganizational information system enabled information
quality (H1) and non-interorganizational information system enabled information system
quality (H2). The reason for examining the information quality of both IOS and non-[OS

information flows is that 108 enabled information flows are hypothesized to be of greater

quality than non-lOS enabled information flows (see H10).

13

The eight joint planning and decision making processes that provide the context
for this research were selected because of their inherent need for the mutual exchange of
information. These joint planning and decision making processes have been summarized
in Figure 4. Each of these processes has been identified as being critical to effective

supply chain integration (Monczka & Morgan, 1998).

 

 

Joint Planning and Decision Making
Processes

 

 

 

Cl Forecasting and Inventory Positioning

Cl Inventory Visibility

Cl Capacity Planning

CI Post Supplier Selection Performance
Evaluation/Feedback and Conformance

CI Sourcing and Supply Proposal Evaluation

Cl Part/Material Standardization

Cl Supplier Scheduling

CI Joint Goal/Target Setting

 

 

 

Figure 4: Information Elements

H3: 108 information quality has a direct and positive effect on performance
H4: Non-lOS information quality has a direct and positive effect on performance
The better the quality of information exchanged between supply chain partners,
the better performance will be. Information quality has been partitioned into
interorganizational information system enabled information quality (H3) and non-
interorganizational information system enabled information quality (H4). The notion that

better information will lead to better decisions is well supported in the literature. The

14

range of possih

 

However. the jt‘
relationship betx
reflection of on?)
order fulfillment
although likely a:
quality and perfo:
performance thro:

processes.

 

 

 

 

115: Supply ui
decision 1

H6: Supply in
Supply uric

Supply states (Pfef:
0f material from 1h
Maniac

tunng 13““
on economics lite
exchange" (NOOTdE

Uncertainty
[Draining processes, 1
ois‘ts, firms wi ll be
under to make be

on
.ng processes it

is (H5
)- For

range of possible decisions that are likely to benefit from better information is quite large.
However, the joint planning and decision making construct (which mediates the
relationship between information quality and performance) was developed to be a
reflection of only a small subset of the decisions which might occur within the customer
order fulfillment process. As a result, it is intuitive that there will be a direct relationship,
although likely attenuated by missing mediating decision processes, between information
quality and performance. H3 and H4 capture the effect of information quality on
performance through these missing mediating joint planning and decision making
processes.

H5: Supply uncertainty has a direct and positive effect on joint planning and
decision making process outcomes

H6: Supply uncertainty has a direct and negative effect on performance

Supply uncertainty is defined as the degree of unpredictability in future material
supply states (Pfeffer & Salancik, 1978). The focus of supply uncertainty is on the supply
of material from the upstream supply chain partner that is used in the firm’s
manufacturing process. Supply uncertainty is more broadly defined in the transaction
cost economics literature as “unanticipated changes in circumstances surrounding an
exchange” (Noordewier, John, & Nevin, 1990).

Uncertainty in supply is theorized to affect both joint planning and decision
making processes, as well as overall performance. When greater supply uncertainty
exists, firms will be forced to improve their joint planning and decision-making processes
in order to make better decisions. This improvement in joint planning and decision
making processes will be evidenced by better joint planning and decision making process

outComes (H5). For the same reason, supply uncertainty will have a negative effect on

15

overall Perfomi
agreed“d”‘

in: trust '0 ,
results

H8: lnterdCT
onthct'

Trust is d:

 

confidence" (MOO

conceptualized €15

hiootrnan et al., 1t
1987). This resea
has been identified

identification-base]

Knc
prec
that
ITUS
IDOI

[rice
“in:
beca
the

each
ofth

Cale
that
SUSU
three
moti

Ofter
“he:

overall performance. Through joint efforts, firms may be able to mitigate the risk
associated with supply uncertainty, but they will not be able to overcome the entire effect
of supply uncertainty on performance (H6).

H7: Trust between firms within a supply chain has a direct and positive effect on the
results of joint planning and decision-making processes

H8: Interdependence of firms within a supply chain has a direct and positive effect
on the results of joint planning and decision-making processes

Trust is defined as a willingness to rely on an exchange partner in whom one has
confidence" (Moorman, Zaltman, & Deshpande, 1992). Trust is frequently
conceptualized as either a determinant of relationship quality (Anderson & Narus, 1990;
Moorman et al., 1992), or as a feature of relationship quality (Dwyer, Schurr, & Oh,
1987). This research conceptualizes trust as a determinant of relationship quality. Trust
has been identified as being of three generic types: (1) knowledge-based, (2)
identification-based and (3) calculus based (Bechtel, 1998):

Knowledge-based trust — Trust is grounded in
predictability — knowing the other party sufficiently well so
that the other’s behavior is anticipatable. Knowledge-based
trust relies on information rather than deterrence as a
motivator.

Identification-based trust — Trust is based on identification
with the other party’s desires and intentions. Trust exists
because the parties effectively understand and appreciate
the other’s wants. A mutual understanding develops as

each side clearly understands the motivations and problems
of the other side.

Calculus-based trust — Trust based on control or assuring
that the other party will do what they say. Trust is
sustained through a clear deterrent (punishment). The
threat of punishment is likely to be a more significant
motivator than promise of a reward. Calculus-based trust
often involves a high degree of monitoring to assess
whether a party is being opportunistic.

16

This 5!

calculus-hasCd *

 

Interdep.
partners to indix .

desired outcome

Pt‘et‘t‘er 8; Salanc:

 

degree to uhich L.

Handheld (1993.) ‘

...C
ma

3ch
on c
they
mea.
coll:
(“rte

Interdepend
muclures (interorgz
Processes) that are c

The trust (‘H'

318% .
ach eXPeCIEd to
will Chain Partner

in t -
.pn Chain Partner

That,
~ 1
Independence
they...

a yplyChajn par

”911011“ plafmj
0n perform.

This study specifically includes knowledge-based, identification-based, and
calculus-based conceptualizations of trust.

Interdependence is defined as the lack of ability on the pan of supply chain
partners to individually control all of the conditions necessary to achieve an action or
desired outcome. The central thesis of resource dependency theory (Emerson, 1962;
Pfeffer & Salancik, 1978) is that interorganizational behaviors can be explained by the
degree to which uncertainty within the relationship is reduced (Handfield, 1993).
Handfield (1993) wrote that:

.. .Organizations are believed to react in one of three
manners in the face of uncertainty: (1) they work towards
acquiring control over resources to minimize dependence
on other organizations (“absorbing the environment”); (2)
they attempt to control interdependence through legal
means (“creating the environment”); or (3) they establish

collective structures of interorganizational action
(“negotiating the environment”).

Interdependence in the context of this research deals directly with the collective
structures (interorganizational information systems/j oint planning and decision making
processes) that are developed in the face of uncertainty.

The trust (H7) and interdependence (H8) exhibited between supply chain partners
are each expected to affect the joint planning and decision-making outcomes of these
supply chain partners. The greater the degree of trust and interdependence between
SUpply chain partners, the more likely those partners are to share sensitive information.
The interdependence between the supply chain partners has the effect of aligning each of
the supply chain partner’s individual goals with overall system goals.

H9: Joint planning and decision making outcomes have a direct and positive effect
on performance

17

Joint 1
making proce
For instance.
capacity plant
capacity const
requirements.
reached. The t
context for this
tisibility. (3) c.
et'aluatiori feed
part material st;

Joint pl:
elWed to lead

and decision ma

Joint planning and decision making processes are defined as those decision
making processes that require bilateral information flow between supply chain partners.
For instance, there is a joint planning and decision making process for manufacturing
capacity planning. A supplying firm must inform its customers of its manufacturing
capacity constraints, just as a buying firm must inform its suppliers of its purchase
requirements. Only when this information is jointly shared may a better decision be
reached. The eight specific joint planning and decision making processes that provide the
context for this research include (1) forecasting and inventory positioning, (2) inventory
visibility, (3) capacity planning, (4) post supplier selection performance
evaluation/feedback and conformance, (5) sourcing and supply proposal evaluation, (6)
part/material standardization, (7) supplier scheduling and (8) joint goal/target setting.

Joint planning and decision-making activities between supply chain partners are
expected to lead to better performing supply chains. The notion that better joint planning
and decision making processes have a positive effect on joint business outcomes has been
previously studied in relation to supplier alliances (Mohr & Spekman, 1994; Monczka,
Petersen, Handfield, & Ragatz, 1998), supplier integration into new product development
(Ragatz, Handfield, & Scannell, 1997), supplier development (Krause, 1995; Krause,
1997), and a host of other supply chain related areas.

H10: The degree of association between interorganizational information system
enabled information quality and joint planning and decision making will be of
a significantly greater magnitude than the degree of association between non-
interorganizational information system enabled information quality and joint
planning and decision making.

It is expected that any given element of information required in the joint planning

and decision making process will be drawn through either an lOS-enabled information

18

El

 

communication)
channel. but no.

ofa higher quaTI
many reasons u 3
information qua?
information is he
betueen the data

world" (Orr. 1995

interorganizationa

 

qualitywhen the d
illustration of how

FCS theory are des.

RUlC 1. En“
Rule 2. Data

coll
Rule 3_ Data
RUlC 4. Data
RUle 5. The

trau:

Rule 6. Law
the c

me FCS Ilt

int” .-
omtdtton Sl’Stem t

d311, leadng [0 mere

A5 3110th EX
“WM 1995) ant

lilac
C635 lBaileV & P

communication channel or through a non lOS-enabled information communication
channel, but not through both. 108 based information communication is expected to be
of a higher quality than that of non-IOS based information communication. There are
many reasons why we might expect this to be the case. Several dimensions of
information quality depend directly on the underlying quality of the data on which the
information is based. Data quality has been defined as “the measure of the agreement
between the data views presented by an information system and that same data in the real
world” (Orr, 1998). Feedback control system (FCS) theory supports the notion that
interorganizational information system enabled information flows will be of higher
quality when the data that they contain is used more frequently. To provide an
illustration of how data quality can affect information quality, several rules offered by
FCS theory are described (Orr, 1998). These rules include:

Rule 1. Unused data cannot remain correct for very long;

Rule 2. Data quality in an information system is a function of its use, not its

collection;

Rule 3. Data quality will, ultimately, be no better than its most stringent use;

Rule 4. Data quality problems tend to become worse as the system ages;

Rule 5. The less likely some data attribute (element) is to change, the more

traumatic it will be when it finally does change;

Rule 6. Laws of data quality apply equally to data and metadata (the data about

the data)

From FCS theory, we may understand that the use of an interorganizational
information system to share information necessarily increases the use of the supporting
data, leading to increased data quality and then to increased information quality.

As another example, information compatibility (Goodhue, 1995), locatability

(Goodhue, 1995), authorization (Bailey & Pearson, 1983; Goodhue, 1995), convenience

of access (Bailey & Pearson, 1983; Raymond, 1985), and timeliness (Bailey & Pearson,

19

1983; Raymond, 1985) are likely to improve with the use of an interorganizational
information system when compared to more traditional information communication
channels.

M1: The association between the measurement errors for each like attribute of

information quality across the lOS-enabled information flows and the non-IOS
enabled information flows may be positive.

Because the same measures of the attributes of information quality are applied to
both IOS enabled information flows and non—IOS enabled information flows, the
measurement errors for each of the like attributes of information quality are likely to be
positively associated. This association is a product of the design of the research, and
does not represent any substantive finding. Chapter 4 will present a more detailed

analysis of these associated measurement errors.

Overview of Subsequent Chapt_er_s_

Chapter 2 examines the literature surrounding supply chain integration and
interorganizational information systems. Chapter 3 presents the research design that will
be used in Chapter 4 to test the theoretical model under examination in this research.
Chapter 5 provides a discussion of the research results with special emphasis drawn to

key academic and practically relevant findings.

20

The theor

lmouledge surroc

 

SEStems. Each of
applicability of ca

rttsearch.

“1610ij C
Millar Press. Ho‘

Mammy 511er u;

Chapter 2

Review and Summary of the Literature

The theoretical foundations for this research are derived from the body of
knowledge surrounding supply chain integration and interorganizational information
systems. Each of these bodies of literature will be explored with a focus on the
applicability of each of these broad bodies of research to the theories proposed by this
research.

Supplv Chain Integration

The topic of integrated supply chains has received considerable attention in the
popular press. However, little academic research has been done to address much of the
uncertainty surrounding integrating supply chains.

Monczka and Morgan (1997) wrote, "after almost a decade of existence, supply
chain management continues to be a poorly understood, badly explained, and wretchedly
implemented concept." Monczka and Morgan (1997) believe that the set of supply chain

management related issues that must be addressed include:

0 Fragmentation in the way supply chain management is understood and applied.

0 Failure of companies to develop true integration of the processes used to achieve
supply chain management.

0 Organizational resistance to the concept.
0 Lack of buy-in by many top corporate managers.

0 Lack of and/or slow development of needed measurement systems.

21

 

 

0 Lack ofgo.
and electro

 

0 Failure of 5:
companies.

Tm) er .2

when they \\ rot.

 

0pc

Further sup

The
prol
to-d
that
the

attei
gene
Chai

Kidding (I!

C i '
had] lmenglOn W

Leeanion;

[ht‘Gl‘o
Thom the supc

bfl’h
fin supp}y Chg

“It". ‘
’ “left dubbed th

0 Lack of good and sufficient information, including integrated information systems
and electronic commerce linking firms in the supply chain.

0 Failure of supply management thinking to push beyond the bounds of individual
companies.

Troyer and Cooper (1995) supported the ideas of Monczka and Morgan (1997)
when they wrote that:

Manufacturers, distributors, and retailers all are scrambling
under the guise of various industry initiatives such as
efficient consumer response, quick response, and just-in-
time manufacturing to gain advantage - whether it is in the
form of lower costs, better service, or a combination of
both. These programs all share a common essence:
integating the supply chain. Never before have companies
undertaken such intensive efforts to coordinate their
operations with their customers.

Further support for the notion that supply chain integration is critical to firms may
be found in the writings of Sengupta and Tumbill (1996):

The efficient solution to supply chain management
problems is now recognized as an integral part of the day-
to-day firnction of an organization. People have realized
that growing market share is not an infinite possibility since
the market itself is finite. This has turned corporate
attentions toward streamlining operations in order to
generate savings from a slimmer and more reactive supply
chain.

Radding (1998) wrote that "the supply-chain movement is forcing companies and
their trading partners to shorten product cycles and cut out unnecessary steps. Supply-
Chain integration will be accomplished largely through linking key business systems."

Lee and Billington (1992) addressed problems related to inventory positioning
thrOughout the supply chain that occur (in part) as a result of the lack of information flow

b(itWeen supply chain members. Lee, Padmanabhan and Whang (1997) addressed a

pr Oblem dubbed the "bullwhip effect" which is related to the lack of proper information

22

 

flow between T

   
  

have recently h
1997). In a \'.‘\
at customer loc.
Detailed sales a:
and the informa:.
Strategies" (C ottr

trading entity... 5'.

 

looking to create e

the whole chain ar

Interorganizationai

Barrett and

Intorrnation systerr

Emuped interorgan

l“refittganizational

Processing nOde (1

late '
mung networl

flow between members of a supply chain. Vendor Managed Inventory (VMI) programs
have recently begun to receive considerable treatment in the popular press (Cottrill,
1997). In a VMI program "the supplier assumes responsibility for managing inventories
at customer locations through the use of highly automated electronic messaging systems.
Detailed sales and demand information are exchanged between vendors and customers,
and the information is used to plan and implement product replenishment and sales
strategies" (Cottrill, 1997). Cottrill notes that "...the supply chain will itself become a
trading entity... supply chains will compete against other integrated supply chains,
looking to create economic value (the key objective of all participants in the chain) across
the whole chain and measuring performance using overall chain metrics" (Cottrill, 1997).
Interorganizational Information Systems Theory

Interorganizational Informalion System Typologies

Barrett and Konsynski (1982) studied a number of firms using interorganizational
information systems. The product of this research was a classification scheme that
grouped interorganizational information systems into five different levels of
interorganizational system participation including (1) remote [/0 node, (2) application
processing node, (3) multi-participant exchange node, (4) network control node, and (5)

integrating network node.

0 Level 1: Remote I/O Node participants have the simplest and least costly method of
interorganizational system participation. An example might include the electronic
exchange of orders, shipping status, etc. between a buyer and supplier.

0 Level 2: Application Processing Node participants "develop and share a specific
application such as an inventory query or order processing system." The cost
incurred in the development of this application is partially offset by the efficiencies
created by the application. An example might include a second-tier automotive
supplier providing shipping status to a first-tier automotive supplier through the first-
tier automotive supplier's proprietary application.

23

. Level 3: \
other l0“ C
include an
portfolio 0
second-tierI

 

o Level-3: X;
diverse set ~
clearinghot»

o IeyclS: lnt.
and proyide I
rnterorganri.

The class

 

that it helps to de

interorganizationa

 

that participation.

atiected by the ley

the participation st.
the internal IS deE
and Konsynski ( l 9:
panicipation to thre
soitn'are developmc
Barren and Konsyns
mmpt to create a c

ish
Ml 0” degree 0

0 Level 3: Multi-Participant Exchange Node participants provide the capability for
other lower-level participants and applications to be connected. An example might
include an automotive manufacturer who has developed and maintains a network and
portfolio of applications (inventory processing, exception handling, etc) for its
second-tier suppliers.

0 Level 4: Network Control Node participants develop and share a network with a
diverse set of applications and participants. An example is an automated
clearinghouse.

O Level 5: Integrating Network Node participants link all of the lower-level participants
and provide simultaneous processing capabilities. An example might be an
interorganizational credit facility such as TRW.

The classification scheme developed by Barrett and Konsynski is interesting in
that it helps to describe the relationship between the level of participation in an
interorganizational information system and potential costs and benefits associated with
that participation. Further, the authors argue that there are four factors that will be
affected by the level of participation in the interorganizational system which include (1)
the participation strategy, (2) the organization structure, (3) the user department, and (4)
the internal IS department. Cash and Konsynski (1985) refine the work done by Barrett
and Konsynski (1982) and in so doing reduce the five levels of interorganizational system
participation to three. These three levels include (1) information entry and receipt, (2)
sofiware development and maintenance, and (3) network processing management. Both
Barrett and Konsynski (Barrett & Konsynski, 1982) and Cash and Konsynski (1985)
attempt to create a classification system for interorganizational information systems that
is based on degree of interorganizational information system participation. Johnston and
Vitale (1988) develop a three-tiered framework for classifying interorganizational
information systems. The authors argue that an interorganizational system might be
classified "on the business purpose of the system, on the relationship between the

Sponsoring organization and the other participants, and on the information fianction in the

24

system.“ Malt

classified inter

 

facilitated elect

Venkat.’
transformation :
integration. (3) i

redefinition. \‘e

 

transformation us

Information ual

   

system." Malone, Yates and Benjamin (1987), relying on transaction cost economics,
classified interorganizational information systems based on whether or not they
facilitated electronic markets or electronic hierarchies.

Venkatraman (1994) developed a framework that classified IT-enabled business
transformation into five categories which included ( l) Localized exploitation, (2) Internal
integration, (3) Business process redesign, (4) Network redesign, and (5) Business scope
redefinition. Venkatraman developed these five levels of IT-enabled business
transformation using an action research methodology.

Information Quality

Information quality represents the degree to which the information exchanged
between organizations meets the needs of the organizations.

McGowan (1998) noted that the "output of an information system is perceived to
be useful only if it is of high quality, readily accessible, and provides accurate and
relevant information. Information quality has been employed in academic research in a
variety of capacities. DeLone and McLean (1992) and Seddon (1997) employed
information quality as an exogenous latent variable in a model of IS success. In their
research, the authors noted that "information quality is concerned with such issues as the
relevance, timeliness, and accuracy of information generated by an information system.
Not all applications of IT involve the production of information for decision-making
(e. g., word processor does not actually produce information) so information quality is not
a measure that can be applied to all systems" (Seddon, 1997). McGowan (1998)
employed information quality as an exogenous latent variable that was hypothesized to

impact the usefulness of an activity based costing management system. Studying

25

 

colllpum'mcL
informmlon qi
interorganizaii

PeopleSOft ER'

 

F urthet‘m
each other's systc
sharing is not con
(Stein l998 l.

These corr
information across

be compatible witl

Emirorunental L'n

computer-mediated communication, Kettinger and Grover (1997) hypothesized that
information quality was an exogenous latent variable that impacted the use of
interorganizational email. Speaking about Qualcomm, Inc.'s decision to implement the
PeopleSoft ERP package, Norm Fjieldheim (VP of IS at Qualcomm) noted:

At first, we were looking at PeopleSofi and Red Pepper

individually, but when PeopleSoft acquired Red Pepper,

that secured our decision. A bolt-on product is ok, but we

wanted to do a lot better than that. Now everything

happens within the same system. You don't have to

manually extract data generated in the planning engine and
then squeeze it back into the ERP system" (Stein, 1998).

Furthermore, one ERP user was quoted as saying "we want to be able to log on to
each other's systems and extract key information. From a technology standpoint, data
sharing is not completely there yet. But we expect the ERP vendors to carry the load"
(Stein, 1998).

These comments highlight the importance of the ability to electronically transport
information across organizational boundaries in a manner that allows that information to
be compatible with both the sender and the recipient of that information.

Environmental Uncertaimty

Environmental uncertainty has been found to play an important role in the ability
of organizations to integrate successfully (Bensaou, 1996; Bensaou & Anderson, 1997;
Bensaou & Venkatraman, 1996a; Bensaou, 1992; Bensaou, 1997; Bensaou &
Venkatraman, 19953; Bensaou & Venkatraman, 1995b; Bensaou & Venkatraman, 1996b;
Clemons & Row, 1992; Clemons & Row, 1993). Transaction cost economic theory
supports the notion that "uncertainty about the environment creates adaptation and

information processing problems for a firm. (Bensaou, 1997). Furthermore, Bensaou

26

notes that one

unpredictabilit

7’s '7- "

In other It

 

dimensions incltn
1995a). Capacity
grouth" and is sir
Aldrich's (1979) e
Complexity is def
(Bensaou & V'enl
contingencies rem

Change" (Bensaou

notes that one major type of environmental uncertainty is that of technological

unpredictability. Bensaou writes that:
In particular, the inability to forecast accurately new
technological or design requirements for the parts and
components exchanged within the relationship may be
managed more efficiently through no or loose coupling
(i.e., source selection can be done by competitive bidding
based only on price between a large number of suppliers
provided with detailed design specifications) and therefore
less investment in joint efforts, such as joint planning and
development" (Bensaou, 1997).

In other research, Bensaou partitions environmental uncertainty into three
dimensions including capacity, complexity, and dynamism (Bensaou & Venkatraman,
1995a). Capacity is defined as "the extent to which the environment can or does support
growth" and is similar in nature to Starbuck's (1976) environmental munificence and
Aldrich's (1979) environmental capacity constructs (Bensaou & Venkatraman, 1995a).
Complexity is defined as "the heterogeneity and range of an organization's activities"
(Bensaou & Venkatraman, 1995a). Dynamism is defined as the degree to which
contingencies remain basically the same over time or are in a continual process of
change" (Bensaou, 1992). Clemons and Row noted that under conditions of high
uncertainty it might be difficult to contract for all contingencies (Clemons & Row, 1992).
In fact, in the limiting case of high uncertainty, it may make more sense to vertically
integrate as opposed to contract with another organization (Clemons & Row, 1992).

Environmental uncertainty has received much attention in the academic literature
(Milliken, 1987; Rindfleisch & Heide, 1997). A large number of environmental
uncertainty measures have been employed. Particular focus has been directed toward the

perceived environmental uncertainty (PEU) scales developed by Miles and Snow (1978).

Support for the PEU scales have been established (Milliken, 1987) and the PEU scales

27

half been val.

(1994) conduc

 

 

and found [he :
tron noted "7
be the U10St pro

lust

ll'illiamS

 

rislt. u'tttramsor
expected 23m fro
Indeed. the decisl
Bruit Rat'indran
cooperation in int
been defined as "l
(Zaheer & V'enlca
relationship berm
(1994) found that
interorganizationa

that “.. .lrust shou.

BaT113. Rat‘indran

"3 Hlfofrnation sha

Sheddan mote the

Lee
fun
\yo

have been validated (Ireland, Hitt, Bettis, & De Porras, 1987; Milliken, 1987). Buchko
(1994) conducted research to determine the measurement properties of the PEU scales
and found the scales to be reliable (Cronbach, 1951). However, Rindfleisch and Heide
(1997) noted that "among all of the TCA constructs, environmental uncertainty seems to
be the most problematic from a measurement standpoint."
ILuit

Williamson (1996) wrote that social scientists often view trust as a subclass of
risk. Williamson noted that "according to this formulation, trust is warranted when the
expected gain from placing oneself at risk to another is positive, but not otherwise.
Indeed, the decision to accept such a risk is taken to imply trust" (Williamson, 1996).
Barua, Ravindran and Whinston (1997) noted that “even in a world of permanence,
cooperation in information sharing cannot emerge in the absence of trust." Trust has
been defined as “the extent to which negotiations are fair and commitments are upheld”
(Zaheer & Venkatraman, 1994) and has been found to be of critical importance in the
relationship between organizations attempting to integrate. Zaheer and Venkatraman
(1994) found that trust played a significant role in predicting the success of
interorganizational information system integration in the insurance industry and observed
that “. . .trust should be recognized as an important construct in future research efforts."
Barua, Ravindran and Whinston noted that "even in a world of permanence, cooperation
in information sharing cannot emerge in the absence of trust" (Barua et al., 1997).
Sheridan wrote that

Leading edge firms including Microsoft Corp. have looked

further into the future and are painting visions of a new
world where supply-chain-management platforms converge

28

 

“lien interdq
“pp“? relat

with Intemet-based electronic commerce to create real-time
"value chain" management systems.

However, from the standpoint of the user--the
manufacturing executive--there is a serious problem that
the software companies tend to gloss over: No amount of
expensive software can compensate for flawed human
thinking or for corporate cultures that create antagonistic
relationships within a supply chain. It is becoming
increasingly clear to many that information technology is
only part of the solution to the supply-chain puzzle.
Without good internal and external relationships, based on
such intangibles as trust and open sharing of information,
today's increasingly complex supply-chain structures will
continue to pose monstrously difficult management
challenges (Sheridan, 1998).

Interdependence

Resource dependence theory (Emerson, 1962; Pfeffer & Salancik, 1978) specifies
the conditions under which one social unit is able to obtain compliance with its demands
when interdependence is present. These relationships have been explored in empirical
studies, which investigate the relationship between dependence and control in buyer-
supplier relationships (Handfield, 1993). For instance, Provan and Skinner (1989) found
that dealers of agricultural equipment were less opportunistic when they depended on a
primary supplier, whereas suppliers with greater control over dealers‘ decisions exhibited
greater opportunism. Resource dependence can also influence other outcomes, including
supplier J IT delivery performance (Handfield, 1993).
Business Results Attributed to Interorganizational Information Systems

Business results represent the set of tangible and intangible benefits that accrue to
the organization as a result of closer interorganizational integration with a supply chain
partner. Chatfield and Bjorn-Anderson (1997) used a resource-based view of the firm to

study how the implementation of an interorganizational system (focused on Electronic

29

 

Data lntercha:

   
   
   

achieve impro
interorganizati-
increased comp
Interorganiratit

Caner a:
management let

B
m

Data Interchange and a Customer Reservation System) helped Japanese Airlines (J AL) to
achieve improved business results. The authors found that the implementation of an
interorganizational system lead J AL to experience (1) increased business growth, (2)
increased competitiveness, (3) accelerated response time, and (4) accelerated cycle time.
Interorganizational Integration
Carter and Narasimhan (1996), in a study of future purchasing and supply chain

management directions, noted that:

Beyond the traditional "cost focus," purchasing and supply

management increasingly will emphasize...a process focus

through interorganizational integration necessitated by

electronic interchange of product and manufacturing
process data.

Carter, Carter, Monczka and Slaight (1998) conducted focus group studies, an
environmental scan and conducted field interviews in attempt to make a five and ten year
forecast of the future of purchasing and supply. Their research findings clearly point to
the fact that supply chains will become increasingly integrated over the next 5-10 years.
Further, information system technology will play a key role in the integration of these
supply chains.

Bensaou (1992) studied the use of interorganizational information systems within
the context of interorganizational buyer-supplier relationships. With the hope of
establishing a common framework between three different theoretical bodies of literature
(organization theory, transaction cost economics, and political economy), Bensaou
examined three types of uncertainty (task uncertainty, partnership uncertainty, and
environment uncertainty) and three types of coordination mechanisms (structural
coordination, process coordination, and technological coordination). The resulting

analysis supported the notion that there are nine different naturally occurring

3O

configuration:

 

particular type
Venkatraman t
included (l ) Re
(4) Structural R
Bensaou
information tech
COOperation expe
hipothesized SC\
Wilding (ll em
Structure Of 1h 6 r

“as cOlldueted 0

JapaWand L1:

Melt.

 

 

configurations of these six factors that may be taken together to explain the use of a
particular type of interorganizational system. In later research, Bensaou and
Venkatraman (1995a) narrowed the list of significant configurations to five which
included (1) Remote Relationship, (2) Electronic Control, (3) Electronic Interdependence,
(4) Structural Relationships, and (5) Mutual Adjustment.

Bensaou (1997) later tested an explanatory model that included the scope of
information technology use as one of the antecedents to the degree of interorganizational
cooperation experienced in a focal buyer-supplier relationship. Bensaou also
hypothesized several other antecedents to the degree of interorganizational cooperation
including (1) environmental uncertainty, (2) partnership uncertainty, (3) the governance
structure of the relationship, and (4) the climate of the relationship. Bensaou's research
was conducted on a sample of 447 independent buyer-supplier relationships in both the
Japanese and U.S. automobile industry. Table 1 summarizes the findings of Bensaou's

research.

Table l: Bensaou (1997) Empirical Findings

 

 

 

 

 

 

 

 

Effect on Interorganizational
Integation
Factor U.S. Japan
Environmental Yes No
Uncertainty
Governance Structure Yes Yes
Climate of the Yes Yes
Relationship
Information Technology Marginal Yes

 

In a similar study, Zaheer and Venkatraman (1994) conducted research aimed at
discovering the antecedents to electronic integration in the insurance industry. Zaheer

and Venkatraman, using transaction cost economic theory (Williamson, 1975), defined

31

 

electronic int.
the deploymer
stages of the \ .
constructs that

Table 2: Zahee

Factor

 

 

bx
Business Procc
S cilicity
Trust

 

Konsyng'
“6“” Cllartnels of
Scale, better CUSI
[hal there Were SI
information part1
faEllllllcal 5km S
(4) coordjnaU-On

Nidumoh
llltfislmems will]
conducted this st

f .
Wsupmn {0]
hr

9
l‘ Org”

”mutton

hi9"; .
v; LlCAI
lmeraCtic

electronic integration as "a specific form of vertical quasi-integration achieved through
the deployment of dedicated information systems between relevant actors in adjacent
stages of the value-chain." The authors found support (see Table 2) for each of the

constructs that was hypothesized to impact the degree of electronic integration.

Table 2: Zaheer and Venkatraman (1994) Empirical Findings

 

 

 

 

 

Factor Hypothesized Significant
Relationship with Findings
[Ignition

Business Process Asset Positive Yes

Specificity

Trust Positive Yes

Reciprocal Investments Negative Marginal

Size Negative Yes

 

 

 

 

 

Konsynski and McFarlan (1990) noted that information partnerships can create
new channels of distribution, operational efficiencies, revenue enhancements, increased
scale, better customer service, and a new basis for differentiation. The authors also noted
that there were several factors that were important to the development of a successful
information partnership. These factors included (1) shared vision at the top, (2)
reciprocal skills in information technology, (3) concrete plans for an early success, and
(4) coordination on business policy.

Nidumolu (1995) studied the association of specialized interorganizational system
investments with the structure and climate of buyer-supplier relationships. Nidumolu
conducted this study in the insurance industry (with a distribution channel focus), and
found support for the notion that investments in specialized buyer-supplier
interorganizational information systems were associated with greater buyer-supplier

vertical interactions and a more favorable buyer-supplier transaction climate.

32

 

Grove

interorganizat

 

influenced the
l3l policy fact.
system factors.

compatibility. t.

research was tha

 

Grover (1993) investigated the factors affecting customer-based
interorganizational system (CIOS) adoption. Grover hypothesized that the factors that
influenced the adoption of a CIOS included (1) organizational factors, (2) support factors,
(3) policy factors, (4) enviromnental factors, (5) and interorganizational information
system factors. The interorganizational information system factors included (1)
compatibility, (2) relative advantage, and (3) complexity. One of the findings of this

research was that the [OS factors were strong predictors of C IOS adoption.

 

33

This ch.I

describe the me;

 

was used in the t

Chapter 3

Research Methodology

This chapter will (1) review the constructs included in the explanatory model, (2)
describe the measures for these constructs and (3) examine the research methodology that

was used in the testing of the explanatory model.

Model Description

 

,i Non-lOS Based
Information Quality

5 H2 = 5 ”6

  
 
  
 
 

..................................

if:If.iff.liEifIII "’

  
  
 

  
  

 

1' -----------------------------
.' , Jothlanmng and : . eronnance
M1“) H10 i“) (+) 5 Decision Making 5 (+) ’3 Outcomes
' 5 Outcomes """""""""""""""
‘ (+)TH7 (4”)? H8
5 105 Based Information . H1 3 """"""" I
5 Quality 5 Trust Interdependence E

 

................................

..........................................

Figure 5: Model Description (with Hypotheses)

Figure 5 provides a graphical depiction of the explanatory model that is the focus
of this research. Overlaid on this model are the hypotheses that have been tested in this
research. This theoretical model reflects the notion that when higher quality information

is exchanged between supply chain partners, joint planning and decision-making

34

 

outcomes Ni

   
  
 

framework. ll”
systems will i: .
partners. The
information 5}.
making outcom
performance. T
for the integrati
conceptualizatic
integration (‘Cle
L'ncerta
making process
Uncertainty exig
making process
al‘s’nltnema Stipp
mess firms will

outcomes will be improved, which will lead to higher levels of performance. Within this
fi'amework, the fundamental proposition is that the use of interorganizational information
systems will increase the quality of the information flows between the supply chain
partners. The increased quality of information associated with interorganizational
information systems is expected to be associated with better joint planning and decision
making outcomes, which are in turn expected to be associated with greater levels of
performance. The ‘joint planning and decision making’ construct is developed as a proxy
for the integration of supply chain partners on key business processes. This
conceptualization is consistent with previous conceptions of interorganizational
integration (Clemons et al., 1993; Clemons & Row, 1992; McGee, 1991).

Uncertainty in supply is theorized to affect both the joint planning and decision
making processes outcomes, as well as overall performance. When greater supply
uncertainty exists, firms will be forced to increase their joint planning and decision-
making processes in order to make the best decisions. Consistent with the same
argument, supply uncertainty will have a negative effect on overall performance. While
these firms will attempt to work together to reduce supply uncertainty, they will only be
partially effective in doing so.

The trust and interdependence exhibited between supply chain partners is
expected to affect the joint planning and decision-making processes of these supply chain
partners. The greater the degree of trust and interdependence between supply chain
partners, the more likely those partners are to participate in joint planning and decision
making processes. The interdependence between the supply chain partners has the effect

of aligning each of the supply chain partner’s individual goals with overall system goals.

35

This St

 

both an unders
lnformation Q;

Definirir.
exchanged betu

There an

 

previous researcl

in Table 3.

Table 3: Attribu

l l. Intormati
l

i ‘ Comenter

\

enabled Iinfomtatic

enabled informatic

gistruct Definitions

This section will establish a set of constructs with specific definitions to provide
both an understanding of the constructs and insight into their measurement.
Information Gum

Definition: Information quality is defined as the degree to which the information

exchanged between organizations meets the needs of the organizations.

There are a number of attributes of information quality that have been used in
previous research. This study employs the set of attributes of information quality found

in Table 3.

Table 3: Attributes of Information Quality

 

 

 

 

 

 

 

 

Information Quality

1. Information currency (Bailey & Pearson, 1983;
Raymond, 1985)

2. Information completeness (Bailey & Pearson, 1983; Baroudi,
1988; Raymond, 1985)

3. Information accuracy (Bailey & Pearson, 1983; Baroudi,
1988; Raymond, 1985)

4. Information compatibility (Goodhue, 1995)

5. Convenience of access to information (Bailey & Pearson, 1983;
Raymond, 1985)

 

 

The measures of information quality (see Table 3) were applied to both IOS
enabled information flows (see 108 Enabled Communication) as well as non-IOS
enabled information flows (see Non—IOS Enabled Communication). Designing the
research in this way allowed for (1) an examination of the quality of the information
available for use in the joint planning and decision making processes of the focal firm, (2)
an examination of the outcomes of the joint planning and decision making processes, (3)
and an examination of how these joint planning and decision making processes affect

performance. It is then possible to inspect the total effects (Bollen, 1989) of both 108

36

Cflabh

infom

researc
likely It
construt
infOt‘ma

include -

Enterprj.

enabled information communication on performance as well as non-lOS enabled
information communication on performance.
IOS Engbled Communication

Definition: All forms of interorganizational communication that are conducted
within an interorganizational information system.

The key joint planning and decision making processes that are employed in this
research are depicted in Figure 6. While the decisions made in these process areas are
likely to require both 103 enabled information and non-IOS enabled information, this
construct only includes the information that is enabled by an interorganizational
information system. Examples of communication methods included in this construct
include the sharing of information through EDI, the World Wide Web (WWW), linked

Enterprise Resource Planning Systems (ERP), etc (see Table 4).

Table 4: [OS Enabled Information Communication

 

IOS Enabled Information Communication - Examples
1. ERP (Entemrise Resource Planning) System
2. WWW (World Wide Web) Shared Resources
3. DRP (Distribution Requirements Planning) System
4. EDI (Electronic Data Interchange)

 

 

 

 

 

 

Non-IOS Enabled Communication

Definition: All forms of interorganizational communication that are outside of
the communication conducted within the interorganizational information system.

The joint planning and decision making processes that are employed in this
research are depicted in Figure 6. While the decisions made in these process areas are
likely to require both 108 enabled information and non-IOS enabled information, this
construct only includes the information that is not enabled by an interorganizational

information system. Examples of communication methods included in this construct are

37

 

postal mail.

meetings. vi

Table 5: No

Defin
bilateral infer
The fc
Strategjc nattn

information sl

l0lnt Plannin g

postal mail, telephone communications, facsimile copies, voice mail, face-to-face

meetings, video conferencing, etc. (see Table 5).

Table 5: Non-10S Enabled Information Communication

 

Non-lOS Enabled Information Communication — Examples

 

1. Email

 

2. Telephone

 

3. Facsimile

 

4. Voice Mail

 

5. Postal Mail

 

5. Face-to-face Meetings

 

 

6. Video Conferencing

 

 

Joint Planning and Decision-Making

Definition: The critical planning and decision-making processes that require
bilateral information flow between supply chain partners.

The focus of these joint planning and decision making processes is of a more
strategic nature and includes the broad categories found in Figure 6. The quality of the
information shared between supply chain partners within the context of each of these

joint planning and decision making processes was assessed.

38

 

 

 

D Forecasti1
D Inventor) i

: U Supplier SC
El Joint Goal'
\

Figure 6: Key Business I

Context 1: Forecas
Forecasting and in

available at the proper Ice

in example of infomiatio
of '

forecasted inventory let
Cl‘t ' '
. lemformation. etc

Context 2: Int'ento
Int '
entory VlSlbllll\

Dhldcally lOcated (tr
K . an

 

 

Joint Planning and Decision Making
Processes

 

 

 

CI Forecasting and Inventory Positioning

C] Inventory Visibility

Cl Capacity Planning

CI Post Supplier Selection Performance
Evaluation/Feedback and Conformance

Cl Sourcing and Supply Proposal Evaluation

Cl Part/Material Standardization

Cl Supplier Scheduling

Cl Joint Goal/Target Setting

 

 

 

Figure 6: Key Business Processes

Context 1: Forecasting and Inventog Positioning

Forecasting and inventory positioning is used to ensure that required items are
available at the proper location and in the proper form when needed in the supply chain.
An example of information sharing in support of inventory positioning is the joint sharing
of forecasted inventory levels by location and quantity, safety stock levels, replenishment
cycle information, etc.

Context 2: Inventory Visibility

Inventory visibility provides the ability to track where any given item is
physically located (transit, customs, supplier, etc.) or where it was used. An example of
information sharing in support of inventory visibility includes the joint sharing of current

inventory information by location and quantity.

39

 

Capac
produce or ”13
example of int
supplier shaft ll
buying compal

Post sui
on objective mi
about both the l
sharing in supp
include (1) the l
quality. deliver)
SUpplier sharing

Sourcing
conditions ofthe
lumtity. quantity
"PM Ofsourci
Scoring the supp
00mm“)? quote

Cont '
w

Context 3: Capacity Planning

Capacity planning is conducted to ensure that the supplier will have the ability to
produce or make available the required items/services in the required lead-time. An
example of information sharing in support of capacity planning would include (1) the
supplier sharing plant capacity utilization information with the buying company or (2) the
buying company sharing future demand forecasts and plans with the supplier.

Context 4: Post Supplier Selection Performance Evaluation/Feedback and
Conformance

 

Post supplier selection performance evaluation/ feedback and conformance (based
on objective measures) is used to ensure that there is joint understanding and agreement
about both the buying firm’s and the supplier's performance. Examples of information
sharing in support of post selection performance evaluation/ feedback and conformance
include (1) the buying company sharing supplier performance information related to
quality, delivery, responsiveness using agreed to metrics with the supplier or (2) the
supplier sharing similar performance information with the buying company.

Context 5: Sourcingand Supply Proposal Evaluation

Sourcing and supply proposal evaluation is the process of setting the terms and
conditions of the purchase. These terms and conditions frequently include price,
quantity, quantity discount, quality, technology, etc. Examples of information sharing in
support of sourcing and supply proposal evaluation include (1) the buying company
sending the supplier a request for quotation (RFQ) or (2) the supplier sending the buying
company a quote in response to an RFQ.

Context 6: Part/Material Standardization

4O

L‘T‘

Part/material standardization is used to reduce the number of unique
parts/materials maintained in the inventory system by using more standard and fewer
unique parts/materials. Examples of information sharing in support of part/material
standardization would include (1) a buying company sharing materials lists with a
supplier and (2) a supplier evaluating these lists and making recommendations to the
buying company about any possible standard part substitutions.

Context 7: Supplier Scheduling

The supplier scheduling process controls the releases of orders through MRP (or
other) and ensures communications of priorities, needs, and quantities between the
buying organization's production or operations management system and suppliers.
Examples of information sharing in support of supplier scheduling include the sharing of
information related to order date, quantity ordered, required due date, ship-to-location,
item identification, key contact person and so forth.

Context 8: Joint Goal/Target Setting

Joint goal/target setting ensures that there are mutually acceptable performance
targets that are rooted in common/aligned metrics. An example of information sharing in
support of joint goal/target setting includes the sharing of information by supply chain
partners related to establishing acceptable purchased-product quality levels (Cpk, ppm,

etc.), responsiveness, on-time delivery, cost improvements, etc.

41

 

l"
(1‘.
.3

“gm

mate

Supply Uncertainty
Definition: Supply uncertainty (from the buying company’s perspective) is

defined as the degree of unpredictability in future material supply states (Pfeffer &

Salancik, 1978).

 

Supplying Company

 

 

 

D” Supply Uncertainty

 

 

 

€13 tanPOJd

 

Focal Company

 

 

 

[ill Demand Uncertainty

 

 

 

<1: impala

 

Buying Company

 

 

 

Figure 7: Supply & Demand Uncertainty

Supply uncertainty is designed to capture the degree to which the supply of
material to the focal firrn’s manufacturing processes is stable (see Figure 7). Supply
uncertainty embodies a host of issues that might affect the stability of material supply
including the availability of qualified suppliers, achieved/expected prices,

current/predicted technology and timing (see Table 6).

42

.1 _lth_.l_l F- _.IL Tru_ tum mat. rm WHIClN- L iglk l\lN t\l\. IN ._ \ \l\ 7.1% \Tr..c\ .\ -Ntt\

Table 6: Supply Uncertainty

 

Definition: Trust is defined as a willingness to rely on an exchange partner in
whom one has confidence" (Moonnan et al., 1992).
This study will adopt a modified form of the measures of trust used by Cummings

and Bromily (1996) (see Table 7) and Zaheer and Venkatraman (1994) (see Table 8).

Table 7: Trust (Cummings and Bromily)

 

Trust (Cummings and Bromily)

I think the people in our partner firm tell the truth in negotiations

I think that our partner meets its negotiated obligations to our department
In my opinion this partner is reliable

I think that the pe0ple in our partner firm succeed by stepping on other people
I feel that our partner firm tries to get the upper hand

I think that our partner takes advantage of our problems

I feel that our partner negotiates honestly

I feel that our partner will keep their word

I think that our partner does not mislead us

10. I feel that our partner does not try to get out of commitments

11. I feel that our partner negotiates joint expectations fairly

12. I feel that our partner takes advantage of people who are vulnerable

 

 

 

 

 

 

 

 

 

PWF’P‘MPP’NT‘

 

 

 

 

 

 

Table 8: Trust (Zaheer & Venkatraman, 1994)

Trust (Zaheer & Venkatraman, 1994)
l. The degree to which there is mutual trust between the organizations
2. The degree to which the organizations work together as partners
3. The likelihood that inter-organizational agreements will be continued

 

 

 

 

 

 

 

43

Interdgpendence

Definition: Interdependence is defined as the lack of ability on the part of supply
chain partners to individually control all of the conditions necessary to achieve an action
or desired outcome.

Several studies have addressed the notion of interdependence (bilateral
dependence) including Ganesan (1996) and Lusch and Brown (1994).

This study will adopt a modified form of the measures of interdependence

developed by Lusch and Brown (1994) (see Table 9):

Table 9: Interdependence (Lusch and Brown, 1994)

Buyer-Supplier Dependence ,

1. We are dependent on this key supplier

2. Our major supplier would be difficult to replace

3. Our major supplier would be costly to loose
Supplier-Buyer Dependence

4. Our key supplier is dependent on us

5. Our major supplier would find it difficult to replace us

6. Our major supplier would find it costly to loose us

 

 

 

 

 

 

 

 

 

 

 

Perfcmance Outcomes

Definition: Performance outcomes are defined as the set of tangible benefits that
accrue to the organization as a result of closer interorganizational integration with a
supply chain partner.

The interorganizational information system literature supports the notion that the
effective use of an interorganizational information system will lead to improvements in
certain business-level performance outcomes which include cycle time, cost, quality,

delivery, and customer service. The measures for performance outcomes may be found

in Table 10.

be:

t l

Table 10: Firm Performance

Please indicate the degree to which you feel that your OVERALL BUSINESS
UNIT’S PERFORMANCE has changed over the past two years:
Return on investment (ROI)

Return on guity (ROE)

Profit margin

Cash-to-cash (file time

External customer service levels

Total inventory turnover rate

Supplier on-time delivery

Purchase price reduction

9. Purchase price reduction compared to market

10. Total cost reduction

1 l. Supplier qualLty performance

12. Supplier responsiveness

 

 

 

 

 

 

 

 

 

9°N9‘S‘PP’N!"

 

 

 

 

 

 

 

Research Desi gp
Much of the research that has been done in the area of interorganizational
information systems has employed a case study methodology (Vijayasarathy, 1994). To
extend the body of knowledge that exists within this area of academic endeavor, the few
empirical studies that exist will be synthesized and extended to form a higher-level
explanatory model (see Figure 5). The methodology adopted by this research is survey-
based in nature and was selected because it allows for the rigorous testing of the
explanatory model that is the focus of this research. This methodology is also a logical
extension of the field research-based methodologies that have thus far been prominent.
Unit of Analysis
The unit of analysis in this study is the interorganizational relationship that exists
between two members of a given supply chain. The only information flows examined
between the supply chain partners were those within the context of the customer order

firlfillment process (see Figure 2).

45

Data Collection

Data Collection Procedure

11.

The procedure that was used to collect the data for this study is shown in Table

Table 11: Data Collection Procedure

 

Step

Procedure

 

1.

Commitment Letter and Survey Mailing

A commitment letter (see Appendix C) and survey instrument (see Appendix F
and F) were mailed to a Chief Executive Officer or Senior Purchasing
Executive at a focal firm. The purpose of the commitment letter was to gain
top-level support for this research and to provide access to the finn’s employees
who are most qualified to participate in this research.

A fax-back response form (see Appendix WASD) was also included in this
mailing. The purpose of the fax-back response form was to gain an
understanding of the likely response rate and to aid in the tracking of informants
who had committed to returning the questionnaire.

 

 

 

Re-send Commitment Letter (45 Days)

The commitment letter (see Appendix C), survey instrument (see Appendix F
and F) and fax-back response form (see Appendix WASD) were mailed a
second time to director-level contacts who did not respond to the mailing within
the first 45 days. Director level contacts were chosen for the second mailing
based on the fact that they were likely to be more able to respond to the
questionnaire directly, where a CEO would have to route the questionnaire to
the appropriate personnel.

 

Survey Instrument Review/Pretest

To ensure face validity (Cook & Campbell, 1979), the survey instrument was

reviewed by a panel of faculty drawn from the Department of Marketing and Supply

Chain Management at Michigan State University. Upon completion of this review, the

survey instrument was then reviewed in detail by ten purchasing/sourcing directors from

46

 

3 cm
was I
valid
insm
The 1
Fight

mien
their
that z
a su;
(info

PM

P;

gare

a cross-section of the organizations in the primary sample. The purpose of this review
was to ensure that the survey instrument was unambiguous and had a high degree of face
validity. Each of the ten purchasing/sourcing directors also completed the survey
instrument.

Primary Sample

The primary sample was drawn from purchasing/sourcing managers and executives (see
Figure 12). Each informant responded to the survey specifically about an
interorganizational relationship that existed between their own company and a supplier of
their choice (see Figure 8). However, the informant was directed to choose a supplier
that also provided critical material to the informant's company. The purpose of selecting
a supplier of critical material was to increase the likelihood that the two firms
(informant's firm and supplier) were engaged in the joint planning and decision making

processes that are the focus of this research.

 

Supplier

Relationship of Interest JL I

Focal Company

 

 

 

 

 

 

 

 

Customer

 

 

 

Figure 8: Unit of Analysis

47

N0
Armstrong
that “suhjr
them. I
”have” ar
compared
“waxes“ ;
bynon-r:
anahzed
M in t
COHIUbu
Pmdu
mdfpen
trend:
”Placer

all rema

measure

‘thIfia

Non-Response Bia_s

Non-response bias was estimated in this study using a procedure outlined by
Armstrong and Overton (1977). An underlying primary assumption of this technique is
that "subjects who respond less readily are more like non-respondents" (Armstrong &
Overton, 1977). The non-response estimation method employed in this study is termed
"wave" analysis. The parameter estimates for each "wave" of survey receipts are
compared using regression analysis. If the regression estimates between the different
"waves" are within the same confidence interval, the data are assumed to not be affected
by non-response bias.
_M_ea_sgrement Development

The use of covariance structure analysis generally requires that the data to be
analyzed is free from any missing values (Bollen, 1989). In order to ensure that the data
used in this study were amenable to covariance structure analysis, cases/questions
contributing too heavily to the overall degree of missing data were discarded. This
procedure produced a data set that contained no missing data among the measures of the
independent constructs and a small rate of missing data rate among the measures of the
dependent constructs. The missing data values among the dependent measures were
replaced with a simple mean imputation (Anderson & Gerbing, 1982) calculated across
all remaining responses to a given question.

Confirmatory Factor Analysis

Confirmatory Factor Analysis (CF A) was used in this research to validate the

measurement model (Anderson & Gerbing, 1982). Generally, the measurement model

specifies the causal relations between the observed variables or indicators and the

48

at

th:

me

exi

dea

("Be

Fur

mOC

H163.

underlying latent variables or theoretical constructs, which are presumed to determine
responses to the observed measures. This measurement model was tested using EQS 5.7
with a maximum likelihood (Bentler, 1995) method.

All of the latent variables and their reflective manifest variables were placed into
a CFA which allowed for the variances and covariances between the latent variables ((1)),
the loadings of the manifest variables onto their respective latent variables (A) and
measurement errors ((95) to be estimated. No structural relationships were allowed to

exist between the latent variables (11 & é). An examination of the data to assess the
degree of correlated measurement error was conducted using Lagrange Multiplier (LM)
(Bentler, 1995) tests.

The overall fit of the measurement model was provided by the chi square statistic.
Furthermore, the Bentler-Bonett non-normed fit index (BBNNFI), Bentler-Bonett normed
fit index (BBNFI) and Comparative Fit Index (CF I) were used to provide evidence of
model fit. These fit statistics enabled conclusions regarding the overall fit of the
measurement model to be drawn (Bagozzi & Yi, 1988).

In addition to examining the overall fit of the measurement model, a careful
examination of convergent, discriminate and nomological validity was also undertaken.
Convergent Validity

Convergent validity was assessed by examining both the magnitude of the factor

loadings of the manifest variables on their respective latent variables (A) as well as

whether or not those factor loadings were statistically different from zero.

49

IS?-

mar

em;

me

later:

mod

the in

503i)»;

Discriminant Validity

Discriminant validity was assessed by examining the cross-factor loadings of one
manifest variable onto all latent constructs on which high loadings were not expected.
This analysis was conducted by examining the matrix of factor loadings (A) as well as by
employing Lagrange Multiplier tests (Bentler, 1995).
Nomological Validity

Nomological validity was assessed by examining the matrix of
variances/covariances ((1)) between the latent constructs to determine whether the
magnitude, statistical significance and direction of each of the relationships between the
latent constructs was consistent with the theory under evaluation.
Structuraflllodel

The measurement model assessed in the previous section using CFA was
modified in such a way as to allow for the inclusion of structural relationships between
the independent (é) and dependent (n) constructs.

The structural equations (see Table 14) were estimated using the EQS 5.7

software package (Bentler, 1995).

50

 

Table 12: Structural Equations

 

Variable
JPDM
SCP

Variable
JPDM
SCP
IQl

IQZ

SU

T

I

DJPDM
DSCP

Structural Equation
=IQ1+IQ2+SU+T+I+DJPDM
=IQ1 'l' IQ2 'l' SU ‘l‘ JPDM + Dgcp

Definition

Joint Planning and Decision Making
Performance

108 Based Information Quality
Non-IOS Based Information Quality
Supply Uncertainty

Trust

Interdependence

Disturbance Term

Disturbance Term

 

51

 

Chapter 4
Research Findings & Hypothesis Testing
This chapter presents the research results. The first section of this chapter
presents the characteristics of the sample. The next section provides a review and
discussion of the explanatory model (see Figure 9) which was evaluated within the
context of each of the eight joint planning and decision-making processes (see Figure 6).

The last section of this chapter will provide a summary of the results.

 
 
   
  
 
   

.............................

Supply Uncertainty

.................................

,Ey' Non-lOS Based

 
  

 

  
 

      
 
 

. . 3 ' ' H6
5 Information ualr . H2
: ................. 9 ..... t): ....... ' ml H5 (~)
,1 r ------------------------
5 (fl Joint Planning and H9 5 Performance
5 Ml (+) H10 :' (i) : Decision Making : 5 Outcomes
‘ I (+) I : (+) . I
'- § Outcomes : """""""""""""""
\‘ g--- - ...................... I
"""""""""""""""""" . ,.----__<:.>_l-_7 6*)le

”1 iTrust Interdependence

................................

Figure 9: Model Description (with Hypotheses)

Preliminary Analysis
This section describes the characteristics of the sample. Specific characteristics

evaluated included the informant’s position/title within the firm as well as the geographic

location of the firm.

52

Characteristics of the sample

The sample was largely composed of purchasing/sourcing Vice Presidents
(17.8%), Directors (46.2%) and Managers (28.4%), composing 92.4% of the total sample
(Table 12). The remaining identifiable responses were made by Chief Executive Officers

(2.4%). Several responses did not include any demographic information (5.2%).

Table 13: Informant's Job Title

 

 

 

 

 

 

 

 

Informant Position Number of Percentage of
Informants Informants

CEO 4 2.4%

Vice President 30 17.8%
Director 78 46.2%
Manager 48 28.4%

Other 9 5.2%

Total Responses 169 1 00%

 

 

 

 

The informants were primarily from companies located in the United States
(88.2%) (see Figure 13). Several firms were located in Western Europe (6.5%) while the
remaining firms were from Canada (1.8%), Japan (1.2%), Australia (.6%) and Asia

Pacific/Other (.6%). Two informants (1.2%) did not provide the location of their firms.

53

Table 14: Sample Demographic Information

 

 

 

 

 

 

 

 

 

 

Geography Number of Percentage of
Informants Informants

United States 149 88.2%

Western Europe 11 6.5%

Canada 3 1.8%

Japan 2 1.2%

Australia 1 .6%

Asia Pacific/Other 1 .6%

Missing Response 2 1.2%

Total Responses 1 69 100%

 

 

 

 

Approximated 3531 surveys were initially mailed. Of these, 386 were non-
deliverable. This provided an overall response rate to the survey of approximately 5.38%.
Additionally, of the 394 fax-back response forms (see Appendix D) returned, 60 fax-back
forms indicated that they would not respond and also indicated a reason for not
responding (see Tables 15 and 16). A closer examination of Table 16 reveals that many
firms (41.67%) did not respond because they were not using linked information systems.
Further, it is apparent that many firms did not feel that they had sufficient time (18.33%)
or the contact had retired or died (16.67%).

This analysis lends support to the notion that the data may be relatively free from
non-response bias. In order to gain additional support for this notion, a non-response bias

test was conducted. The results of this test are presented in the next section.

54

Table 15: Effective Response Rate Calculation

 

 

 

 

    
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

NAPM CM-US GEBN
Mailed 1907 1 574 50 3531
Undeliverable 1 97 1 89 386
Net Mailed 1710 1385 50 3145
Provided Explanation For Not Responding -60
Effective Mailed ' 3085
Received 166
Response Rate m
Table 16: Fax-Back Response Form Results
Fax Yes 35 19 24 128
Fax No 180 80 6 266
394
Explanations: Count Percentage
No Linked Information Systems 25 41.67%
Cannot Comlete Survey In Time To Meet Deadline 11 18.33%
Respondent Died/Retired 10 1 6.67%
Not Appropriate Company 6 10.00%
Our Firm Has Already Responded 2 3.33%
Respondent Lacks Sufficient Knowledge 2 3.33%
Too Many NAPM Studies 2 3.33%
Wrong Contact 1 1.67%
Comparly Does Not Participate In Survey Research 1 1.67%
60 100.00%

 

 

 

Non-Response Bias

A general approach to assessing non-response bias was undertaken for each set of
manifest variables that corresponded to a given joint planning and decision making
context (Armstrong & Overton, 1977).

The data set was reorganized into two separate groups. The first group contained
the manifest variables of the first 20 questionnaires returned. The second group
contained the manifest variables of the last 20 questionnaires returned. Non-response
bias testing was conducted individually within each joint planning and decision making
context. A simple paired-sample t-test (equal variances) was computed. The tables

found in Appendix F (Tables 25 - 32) describe the probabilities of rejecting the null

55

hypothesis that the means of each manifest variable are the same across the two groups
(first and last 20 questionnaires received).

These T-test comparisons revealed no significant difference between the first
group and the last group. This finding, taken in conjunction with the sample
characteristics (see Tables 14 & 15) and the explanations provided by contacts for not
responding (see Table 16), lends support to the notion that the data are relatively free
from non-response bias.

Overall Construct Development

Three of the constructs (trust, interdependence and supply uncertainty) included
in the overall research model (see Figure 9) failed to demonstrate adequate degrees of
convergent and discriminant validity to allow for their inclusion in the testing of the
exploratory model. These constructs were omitted from the explanatory model and their
associated hypotheses were not tested. These hypotheses included:

H5: Supply uncertainty has a direct and positive effect on joint planning and decision
making process outcomes

H6: Supply uncertainty has a direct and negative effect on performance

H7 : Trust between firms within a supply chain has a direct and positive effect on the
results of joint planning and decision-making processes

H8: Interdependence of firms within a supply chain has a direct and positive effect on the
results of joint planning and decision-making processes

Figure 10 represents the revised explanatory model that will be tested in the

following sections.

56

 

1
1

le'

use.

 

 

 

‘2' Non-[OS Based
' 3 Information Quality

   

.............................

Performance
Outcomes

.............................

Joint Planning and ”9
3 Decision Making 5 (of)
5 Outcomes i

..................................
1

lOS Based lnfomtation
‘5 Quality :

 

 

 

 

Figure 10: Revised Explanatory Model

Measurement Validation
It is imperative that the measurement model be closely examined prior to the
testing of a theoretical model and subsequent hypothesis testing. Important steps in the
validation of the measurement model include (1) an examination of univariate
distributions for excessive skewness or kurtosis, (2) an assessment of measurement

reliability and (3) and assessment of construct validity. Each of these topics will be

addressed in turn.

57

Descriptive Statistics

An examination of the univariate distributions within each joint planning and
decision making context was a critical first step in the analysis of this data. The data
were examined for excessive skewness and kurtosis. Also, the standard deviation of each
manifest variable was assessed to ensure that it was sufficiently large.

Appendix I (Tables 65-72) contains the descriptive statistics associated with the
manifest variables from each joint planning and decision making context. An
examination of the descriptive statistics reveals that the univariate distributions are
relatively normal.

While normality of the univariate distributions is necessary condition for multi-
variate normality (an assumption required by the maximum likelihood (ML) fit function),
it is not sufficient to establish multivariate normality (Bollen, 1989). Mardia’s coefficient
(Mardia, 1970) was calculated for the data within each of the eight joint planning and
decision making contexts. The assumption of multivariate normality was not met in any
of the eight joint planning and decision making contexts. As a result, the ML fit function
was not employed in the calculation of the parameter estimates for the explanatory
model. Instead, the generalized least squares (GLS) fit function was employed. The
GLS method does not assume multivariate normality and has been successfully employed

in previous studies where lack of multivariate normality precluded using the ML fit

function (Bollen, 1989).

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Construct Validigr

Eight measurement models were developed and tested using a confirmatory factor
analysis (CFA) technique. Each of the eight measurement models was used as a method of
establishing acceptable degrees of convergent and discriminant validity, enabling the subsequent
testing of the correspondent structural equation models (SEM). Tables 18 and 23 provide a
summary of some of the more important parameters and their associated test statistics. Measures
of overall model fit are provided in Table 19. A complete set of statistics related to the testing of
each of the measurement models may be found in Appendix G.

Most A’s demonstrated significant associations between correspondent latent variables
and their reflective manifest variables. The X’s associated with the measures of non-lOS enabled
information quality in the context of supplier scheduling did not demonstrate a sufficient degree
of statistical significance. A review of the Cronbach’s alpha reliability calculations presented in
Table 17 provides for an alpha of .964 in this joint planning and decision making context,
indicating that these manifest variables are reliable measures of non-IOS enabled information
quality.

The overall fit of each measurement model was acceptable as evidenced by non-
significant chi-square tests (see Table 19). Further, the Bentler-Bonnett Non—Normed Fit Indices
and the Comparative Fit Indices demonstrated acceptable levels of overall measurement model
fit in each of the eight joint planning and decision making contexts (see Table 19).

No measurement errors were allowed to correlate with the exception of the three
measures of information quality (currency, accuracy and completeness). Associations between
these measurement errors were allowed to exist because they were consistent with theoretical

underpinnings of this research. The same three measures of information quality were applied to

60

both the IOS enabled information flows as well as the non-IOS enabled information flows.
Developing the measurement model in this way provided for the expectation that each of the
three measures of the IDS enabled information flows would necessarily be associated to some
degree with its corresponding measure of the non-lOS enabled information flows. Appendix G
details the associations between these error terms within each of the eight CFAs.
Reliability

An assessment of measurement reliability was conducted using a split-half method
developed by Cronbach (1951). The results of the reliability calculations may be found in Table
17. The measures of non lOS-enabled information quality, 108 enabled information quality and
joint planning and decision making outcomes appear to be very reliable. Reliability estimates
(or) between .9 and .98. The measures of performance outcomes did not exhibit the same degree
of degree of reliability. Reliability estimates (or) for these measures range from .43 to .86.

The manifest variables exhibited sufficient reliability to be included in the subsequent
analysis. Further, an examination of the A coefficients that relate each manifest variable to a
latent variable also provided an indication of measurement reliability. This analysis is described

in the next section.

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Structtgal Equation Model

This section will develop and test each of the hypotheses (see Appendix H) within
the context of each of the eight joint planning and decision making processes.

Tables 20 and 21 provide a summary of some of the more important parameters
and their associated test statistics. A complete set of statistics related to the testing of
each of the structural equation models may be found in Appendix H.

The overall fit of each of the eight structural equation models was acceptable as
evidenced by non-significant chi-square tests (Table 21). Further, the Bentler-Bonnett
Non-Normed Fit Indices, Bentler—Bonnet Normed Fit Indices and the Comparative Fit
Indices demonstrated acceptable levels of overall measurement model fit (see Table 21)
in each of the eight joint planning and decision making contexts.

A test of difference between the B’s that relate both 108 enabled information
quality and non-IOS enabled information quality to joint planning and decision making
outcomes was performed in each of the eight joint planning and decision making
contexts. This difference test compared the chi-square obtained from the fit of the base
model with the chi-square obtained from the fit of a model where the two [3’s were
constrained to be equal. As the difference between two chi-squares is also distributed as
chi-square, calculating the statistical significance of the difference is straightforward.
The results of these chi-square difference test calculations may be found in Table 20. For
completeness, another set of difference tests were performed that tested the difference
between the B’s that relate both 108 enabled information quality and non-lOS enabled
information quality to joint planning and decision making outcomes was performed in

each of the eight joint planning and decision making contexts. This set of difference tests

65

 

 

was done using a multiple regression methodology. Each factor was reformed as a linear
average of each of the three manifest variables (information currency, quality and
completeness). Each [3 was estimated using an ordinary least squares (OLS) multiple
regression method. Once the B parameter estimates were obtained, 95% confidence
intervals were constructed around them. It follows that the test of difference between
these [3 parameter estimates (p=.05) is simply the comparison of their confidence
intervals to determine whether or not they overlap. If the confidence intervals overlap,
then the null hypothesis (the [3 parameter estimates are not different) may not be rejected.
The results of this analysis (see Appendix L, Tables 89 - 96) compared exactly to the
results of the analysis conducted above which employed a change in chi-squares

technique.

66

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68

Hypothesis Testing

This section will evaluate each of the hypotheses across the eight joint planning
and decision making contexts. Table 22 provides a summary of each of the hypothesis
tests and the magnitude of the parameter associated with the hypothesis test. A
description of key parameter values and test statistics for each of the joint planning and
decision making contexts may be found in Table 20. Appendix H contains a complete set
of all parameter values and test statistics for each of the eight joint planning and decision
making contexts.

H1: Interorganizational information system (108) information quality has a direct and
positive effect on joint planning and decision-making outcomes

H1 was supported in each of the eight joint planning and decision making
processes (see Table 22).
H2: Non-interorganizational information system (IOS) information quality has a direct
and positive effect on joint planning and decision-making outcomes
H2 was supported in 7 of the 8 joint planning and decision making contexts (see
Table 22). H2 was not supported in the joint planning and decision making context of

forecasting and inventory positioning.

H3: IOS information quality has a direct and positive effect on performance
H3 was not supported within any of the joint planning and decision making
contexts (see Table 22).

H4: Non-10S information quality has a direct and positive effect on performance

69

H4 was only supported in the joint planning and decision making context of joint
goal/target setting (see Table 22). H4 was not supported in the remaining 7 joint
planning and decision making contexts.

H9: Joint planning and decision making outcomes have a direct and positive effect on
performance.

H9 was supported for 5 of the 8 joint planning and decision making contexts
including (1) forecasting and inventory positioning, (2) inventory visibility, (3)
performance evaluation and feedback, (4) supply proposal evaluation and (5) supplier
scheduling (see Table 22). H9 was not supported in the remaining 3 joint planning and
decision making contexts.

H10: The degree of association between interorganizational information system enabled
information quality and joint planning and decision making will be of a
significantly greater magnitude than the degree of association between non-
interorganizational information system enabled information quality and joint
planning and decision making.

H10 was supported in 5 of the 8 joint planning and decision making contexts
including (1) forecasting and inventory positioning, (2) inventory visibility, (3) capacity
planning (marginal support), (4) supplier scheduling and (5) joint goal/target setting (see
Table 22). H10 was not supported in any of the remaining 3 joint planning and decision
making contexts.

M1: The association between the measurement errors for each like attribute of
information quality across the lOS-enabled information flows and the non-lOS
enabled information flows may be positive.

Support for M1 was varied across the 8 joint planning and decision making

contexts. In any given joint planning and decision making context, there was support for

none, one two or three of the individual correlated measures of information quality

70

(currency, accuracy and completeness). Appendix G contains the parameters and test
statistics associated with M1 within each of the 8 joint planning and decision making
contexts. Also, the term “partially supported” (as referred to in Table 22) indicates that
some number of the three correspondent measurement errors for the manifest variables

reflecting information quality had a significant association.

71

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72

Chapters
Discussion of Research Findings
Bill Gates, Chairman and CEO of Microsoft, wrote:
If the 19805 were about quality and the 19908 were about
reengineering, then the 20003 will be about velocity.
About how quickly the nature of business will change.
About how quickly business itself will be transacted.
About how information access will alter the lifestyle of
consumers and their expectations of business. Quality
improvements and business process improvements will
occur far faster. When the increase in velocity of business
is great enough, the very nature of business changes. A
manufacturer or retailer that responds to changes in sales in
hours instead of weeks is no longer at heart a product

company, but a service company that has a product offering
(Gates, 1999).

Empirical research in the area of interorganizational information systems is in its
infancy. Academics and practitioners alike are starved for meaningful research in this
arena. Within the context of manufacturing, purchasing and supply chain management,
even less empirically based research exists related to the use of interorganizational
information systems. The analysis conducted in Chapter 4 revealed a set of joint
planning and decision making processes whose outcomes are affected by the quality of
108 enabled and non-IOS enabled information flows. This chapter presents an in-depth
discussion centered on each of the eight joint planning and decision making contexts with

special attention paid to key academic and practical findings.

73

Discussion of Critical Research Findings

The following section will develop a discussion of the critical research findings in
each of the eight joint planning and decision making contexts. However, before this
discussion is undertaken, it is important to draw several broad observations across the set
of contexts.

A review of each of the joint planning and decision making processes areas will
reveal that each of these decision making process areas may be characterized by a
number of different attributes. The difference in these characteristics is important to
understand, as the discussion surrounding each of the eight joint planning and decision
making areas must be understood within this context.

Table 23 describes 5 key dimensions of each of the joint planning and decision
making processes areas. A closer examination of Table 23 reveals that the joint planning
and decision making contexts may be divided into two separate groups based on their
“structuredness,” “definateness,” regularity, frequency and “objectiveness.” For
clarification, each of these terms will be defined. “Structuredness” refers to the degree to
which the information required as an input to this joint planning and decision making
context is standardized and well defined. “Definateness” describes the degree to which
information shared in support of this joint planning and decision making context is
required for the successful completion of this process. Regularity describes whether or
not the information required in support of this joint planning and decision making process
is exchanged on consistent time intervals. Frequency describes whether or not the
information shared in support of this joint planning and decision making process is

shared on shorter or longer intervals. “Obj ectiveness” describes whether the information

74

shared is based on ‘hard’ information or rather whether it is of a more subjective nature
(‘soft’).

Forecasting and inventory positioning, inventory visibility, capacity planning and
supplier scheduling are all relatively structured, definite, regular and objective. These
characteristics may make these 4 joint planning and decision making areas particularly
conducive to the use of an interorganizational information system. However,
performance evaluation, supply proposal evaluation, part/material standardization and
joint goal/target setting are much less structured, definite, regular and objective. This
characterization helps to frame the notion that the latter joint planning and decision
making contexts may not be (currently) as well suited to the use of an interorganizational
information system. An alternative interpretation may have to do with the fact that the
latter joint planning and decision making processes are less developed than the former,
leading to the natural situation that they have yet to achieve the same degree of structure,
“dininiteness”, regularity and “obj ectivenss.” This interpretation leads to the observation
that these latter joint planning and decision making contexts may well be where the

rewards for using interorganizational information systems currently exist!

75

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76

F orecasting_and Inventory Positioning
Forecasting and inventory positioning is used to ensure
that required items are available at the proper location
and in the proper form when needed in the supply

chain. Another way to express this is that the right
items are at the right place at the right time.

Information that is exchanged between supply chain partners in this context is
typically very standardized and well defined. This information is typically also
exchanged on a pre-determined/standard schedule. This joint planning and decision
making context provides a natural/intuitive setting for an interorganizational information
system.

This research supports the notion that improved information quality is associated
with better joint forecasting and inventory positioning process outcomes. Further, within
the context of joint forecasting and inventory positioning, the resulting information
quality stemming from the use of an interorganizational information system appears to be
critical to making effective decisions. This may be seen when one compares the large

magnitude (.570) of the [3 that relates the quality of lOS-enabled information flows with

joint planning and decision making outcomes to the very small magnitude (.072) of the B
that relates the quality of non-10S enabled information flows with joint planning and
decision making outcomes. A statistical test of difference confirmed that these parameter
estimates are indeed different (p<.01).

The results also show that each element of information quality (currency,
accuracy, completeness, compatibility and convenience to access) had a significantly
higher mean score for the quality of IOS enabled information than for the quality of non-

IOS enabled information (see Table 81).

77

It is also apparent that information quality is associated with certain firm-level
performance results including responsiveness, on-time delivery and inventory turnover.
Specifically, the indirect effect (mediated by joint planning and decision making
outcomes) of 108 enabled information flows on performance outcomes (responsiveness,
on-time delivery and inventory turnover) is 0.35144. It is interesting to note that the
indirect effect (mediated by joint planning and decision making outcomes) of non-10S
enabled information flows on performance outcomes (responsiveness, on-time delivery
and inventory turnover) is .045224. This is a very strong argument in favor of employing
interorganizational information systems in the context of joint forecasting and inventory
positioning processes.

The use of an interorganizational information system is a key contributor to the
success of a firm’s joint forecasting and decision making processes, which in turn
positively affect the firm’s ability to respond to perturbations in production/delivery
schedules and ability to maintain reduced system-wide inventory levels. Managers with
responsibilities for forecasting and inventory positioning should examine these results in
the context of their specific business situation. However, the startling difference between
the quality of 108 enabled and non-10S enabled information flows taken with the large
indirect effect of the quality of 10S enabled information flows on firm performance
promises that use of interorganizational information systems in the arena of forecasting
and inventory positioning may well provide positive performance results.

While not a direct finding of this research, it is recognized that supply chains do
NOT have effective interorganizational information systems in place that link the

majority of the firms composing in the chain. Performance results discovered in this

78

research are very likely being achieved from the use of an interorganizational information
system spanning only two organizations. It seems clear that as supply chains become
more integrated through the use of interorganizational information systems, better
forecasting and inventory positioning outcomes and subsequent firm performance results
will be achieved.

To further examine what types of firm-level results might be expected from an
improved joint forecasting and inventory positioning process, a post-hoe analysis of the
association between forecasting and inventory positioning joint planning and decision
making outcomes and firm—level performance results was performed (see Table 73). The
results of this post-hoe analysis revealed that successful joint forecasting and decision
making processes were associated with:

. improved supplier on-time delivery (r=.35, p=0.00)

. improved supplier responsiveness (r=.26, p=0.00)

1
2
3. an increased rate of inventory turnover (F22, p=0.01)
4. improved cash-to-cash cycle time (r=.19, p=0.03)

5

. reduction of purchase price compared to market (r=.15, p=0.08)

These findings lend credence to Kalakota and Whinston’s (1997) notion that “to
support ‘pull’-based models, planning systems need to support three goals: to gather
information about consumer demand effectively; to accommodate fluctuations in
demand; and to use demand information for inventory investment, including safety stock,
inventory turns, and replenishment frequency. This involves integrating into one
seamless solution the process of (1) order generation and planning, which helps anticipate

customer demand through market forecasting; and (2) order taking and entry, which feeds

79

replenishment planning; this incorporates distribution requirements planning (DRP),
vendor managed inventory (V MI) and continuous replenishment (CRP). ”

This research points to the fact that firms are putting increased emphasis on their
forecasting and inventory positioning processes. Informants were asked to rate the
degree to which they felt that their joint forecasting and inventory positioning processes
had improved over the past two years (see Figure 11). It is clear that over the past two

years firms believe that they have improved their joint forecasting and inventory

 

 

 

   

 

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Given the findings relating to 10$ information quality to forecasting and
inventory positioning outcomes, the forward-thinking manager should make an
assessment of the status of their firm/industry/supply chain with respect to the use of
these interorganizational information system technologies. Issues should be addressed

not from the perspective of “how does my firm share information with firm X.” Rather,

80

the appropriate question is “how does my supply chain share information across all
supply chain members in a fashion to better achieve our common and individual goals?”
Industry leaders (OEMs, large suppliers, etc.) have the opportunity to play a key role in
shaping the technology standards that will be used for the next 20 years. If we invest the
time and resources into developing these interorganizational communication standards
correctly today, we will avoid creating another set of standards and technologies that are
not well deployed.

An interesting application of a joint forecasting and inventory positioning
planning and decision making tool can be found at Intel. Intel uses a number of web
based applications to provide electronic linkages to suppliers (Intel, 1999b). One of these
tools is called the “Automated Supplier Response to Forecast Tool” or ASRF. The ASRF
is a secure application that provides suppliers the ability to respond to Intel generated
forecasts. Another Intel web-based tool is called “Supplier Activated Materials” or SAM.
SAM allows materials suppliers to gain access to ( 1) Intel’s weekly demand
requirements, (2) 13 week historical (and current) and present inventory demands, (3) the
last five receipts for materials and (4) the ability to download these reports in MS Excel
97 format. These tools provide a mechanism by which Intel’s suppliers may (on an as-
needed basis) gain access to critical planning information that they might not otherwise

have easy access to.

81

Inventory Visibility
Inventory visibility provides the ability to track where
any given item is physically located (transit, customs,
supplier, etc.) or where it was used. An example of
information sharing in support of inventory visibility

includes the joint sharing of current inventory
information by location and quantity.

Information that is exchanged between supply chain partners in this context is
typically very standardized and well defined (i.e. location and quantity). Locating
inventory in the system may frequently be done on an ad-hoc basis in order to meet
changes in demand, changes in production schedules, etc. This joint planning and
decision making context provides a natural/intuitive setting for an interorganizational
information system.

This research supports the notion that better information quality leads to better
joint inventory visibility planning and decision making outcomes. Further, improvements
in the quality of both 108 enabled and non-10S enabled information flows are associated
with better joint inventory visibility outcomes. The B that associates IOS enabled
information flows with joint inventory visibility outcomes (0.565, p<.01) was of a very
large magnitude. The B that associates non-lOS enabled information flows with joint
inventory visibility outcomes (0.204, p<.01) was of a smaller, but still reasonably large
magnitude. A statistical test of difference revealed that these parameter estimates are
indeed different (p<.01). In a similar fashion to the forecasting and inventory positioning

joint planning and decision making context, each individual element of information
quality (currency, accuracy, completeness, compatibility and convenience to access) had
a significantly higher mean score for the quality of 108 enabled information than for the

quality of non-IOS enabled information (see Table 82).

82

Information quality is also associated with certain firm-level performance results
including on-time delivery and responsiveness. Specifically, the total effect (mediated by
joint planning and decision making outcomes) of 10S enabled information flows on
performance outcomes (responsiveness and on-time delivery) is 0.232. The total effect
(mediated by joint planning and decision making outcomes) of non-IOS enabled
information flows on performance outcomes (responsiveness and on-time delivery) is
.214. These total effects indicate that perhaps the quality of information exchanged by
supply chain partners has a more equal impact on performance outcomes, than on joint
planning and decision making outcomes. For instance, the quality of information passed
through an interorganizational information system is much greater than information
exchanged through traditional communication mechanisms. However, since the total
effects of information quality on performance outcomes are very similar, there must be
another mechanism afoot which accounts for the leveling of the total effects compared to
the direct effects within this joint planning and decision making context. One
explanation is that interorganizational information systems are employed for the more
routine/standard set of information transactions, while traditional communication
methods are employed for the non-standard or ‘out of the ordinary’ information
transactions. One might expect that a transaction that has attained the level of “standar ”
may not (at the margin) make the same contribution to bottom line firm performance as
the more ad-hoc “firefighting” information transaction that is frequently needed to
quickly adapt to the changing competitive environment. It is this “firefighting” that may

well be the source of the larger magnitude [3 which associates non-IOS information

83

quality directly with firm performance, and in so doing accounts for the leveling of the
effects of information quality on firm performance outcomes.

This finding is particularly interesting in that it clearly describes a situation in
which interorganizational information system technologies are not employed to their
fullest extent. It is also somewhat inconsistent with the finding that inventory visibility
joint planning and decision making processes had significantly improved over the past

two years (see Figure 12).

   
   
 
    

 

 

 

 

 

 

 

 

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Figure 12: Inventory Visibility Process Improvements

Because the quality of information is significantly better when received through
an interorganizational information system (as compared to traditional communication
method), firms should capitalize on this by leveraging interorganizational information
Systems to handle more ad-hoc/non-standard information transactions. The benefits of

leveraging interorganizational information system technologies in this fashion may come

84

from a variety of areas including (1) better results from joint planning and decision
making processes, (2) better use of human resources by freeing up time to focus on

longer-range issues and (3) better supply chain inventory management.

85

Capacity Planning

Capacity planning is conducted to ensure that the
supplier will have the ability to produce or make
available the required items/services in the required
lead-time. An example of information sharing in
support of capacity planning would include the sharing
of plant capacity utilization information between supply
chain partners.

Information that is exchanged between supply chain partners in this context is
typically very standardized and well defined (i.e. capacity utilization by time period).
Information is typically exchanged on a pre-determined/standard schedule. This joint
planning and decision making context provides a natural/intuitive setting for an
interorganizational information system.

This research supports the notion that better information quality is associated with
better joint capacity planning and decision making outcomes. Both the quality of 103
enabled and non-IOS enabled information flows are associated with improvements in
joint capacity planning outcomes. The B that associates IOS enabled information flows
with joint capacity planning (0.501, p<.01) was of a very large magnitude. The [3 that
associates non-lOS enabled information flows with joint capacity planning outcomes
(0.304, p<.01) was also of a large magnitude. A statistical test of difference revealed that
these parameters are different (p<.1). Consistent with the previous two joint planning
and decision making contexts, each individual element of information quality (currency,
accuracy, completeness, compatibility and convenience to access) had a significantly
higher mean score for the quality of [OS enabled information than for the quality of non-

IOS enabled information (see Table 83).

86

While the firm-level performance outcome construct included in the SEM
(reflected by R01, ROE and profit margin) did not appear to be significantly affected by
the quality of information exchanged between supply chain partners (either through an
IOS or traditional communication method), an examination of Table 75 clearly indicated
that certain firm-level performance outcomes are likely to be associated with improved
joint capacity planning and decision making outcomes. Specifically, these firm-level
performance outcomes included:

(1) total inventory turnover rate (r=.25, p<.01)

(2) purchase price reduction compared to market (r=.25, p<.01)
(3) supplier on-time delivery (r=.23, p<.05)

(4) supplier responsiveness (r=.22, p<.05)

(5) total cost reduction (r=.22, p<.05)

(6) return on investment (r=.20, p<.05)

(7) profit margin (r=.19, p<.05)

(8) return on equity (r=.19, p<.05)

(9) purchase price reduction (r=.18, p=.05)

These findings are of particular interest in that it appears that improvements in
joint capacity planning and decision making processes may very well lead to
improvements in a wide range of firm-level performance outcomes. Further, it is
important to note that the magnitude of the B that associates IOS enabled information
quality with joint capacity planning and decision making outcomes ([3:50]) is relatively
larger than the magnitude of the [3 that associates non-IOS enabled information quality
with joint capacity planning and decision making outcomes (5:343). It would appear
that the increased quality of information exchanged through an interorganizational
information system might have a greater direct affect on joint planning and decision

making outcomes and a greater indirect effect on firm-level performance.

87

The joint capacity planning and decision making context was described typically
requiring the sharing of information by supply chain partners and a regular/scheduled
basis. It is likely that the established schedule for sharing capacity planning information
is in many cases inadequate to meet the needs of the supply chain partners. In effect, this
may build a lag in information flow into the planning system. The use of a properly
implemented interorganizational information system may remove this lag in information

flow, providing higher quality information on an as-needed basis by the relevant supply

 

 

 

 

 

 

 

 

 

 

 

 

chainpartners.
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Figure 13: Capacity Planning Process Improvements

While firms reported that their capacity planning processes had improved over the
past two years (see Figure 13), they typically do not have well implemented
interorganizational information systems that extend across their supply chains. Hence,
capacity planning is likely done in pairs of firms, who at the time of the planning activity,

are not able to incorporate the capacity plans for other members of the supply chain. The

88

need for a supply-chain wide interorganizational information system seems clear. The
firms who are able to establish an effective supply chain—wide interorganizational
information system are likely to gain significant competitive advantage. It is very likely
that the increase in firm-level performance outcomes will be so great as to make it
difficult for competing firms/supply chains to catch up.

However, it is also the case that some firms are well on the way to establishing
interorganizational information systems that appear to be quite well implemented,
although typically not throughout the entire supply chain. For instance, DaimlerChrysler
has implemented an extended-enterprise system called “The Extended Enterprise .”
One of the features of The Extended EnterpriseTM is called SPIN for “Supply Part
Information Network.” One of the options available to a DaimlerChrysler supplier with
an active part/material contract is to be able to view financial and capacity planning

volumes (FPVs and CPVs) for parts for future model years.

89

Post Supplier Selection Performance Evaluation/Feedbacl_(_and Conformance
Post supplier selection performance
evaluation/feedback and conformance (based on
objective measures) is used to ensure that there is joint
understanding and agreement about both the buying
firm’s and the supplier's performance. Examples of
information sharing in support of post selection
performance evaluation/feedback and conformance
include mutual sharing of performance information
related to quality, delivery and responsiveness using
agreed to metrics.

Information that is exchanged between supply chain partners in this joint planning
and decision making context is typically (although not always) very standardized and
well defined. Information is usually exchanged on a well-defined schedule. The
exception occurs when the performance measurement process returns a finding that
performance has worsened. It may be the case that during the period of corrective action
following this finding, the types of information and the frequency that this information is
being exchanged deviates from the schedule.

This research supports the notion that better information quality is associated with
improved results from the joint performance evaluation/ feedback and conformance
planning and decision making process. Within this context, the quality of both IOS
enabled and non-lOS enabled information flows are associated with improved outcomes
fi'om this joint process. Both B’s that associated 108 and non-lOS enabled information
flows with joint performance evaluation/ feedback and conformance planning and
decision making outcomes (Bnon-ros=0-353. p<.Ol; (3105:0359, p<.01) were of a large
magnitude. Further, a statistical test of difference revealed that these parameter estimates

were not statistically different (p=.252).

90

Analysis of the information quality data revealed (see Table 84) that there was no
statistical difference between the accuracy, completeness or compatibility of information
shared through traditional or [OS methods. Interestingly though, IOS enabled
information flows were more current and more convenient to access than their non-IOS
counterparts.

A closer examination may reveal that firms are only now at the beginning stages
of using interorganizational information systems in the context of joint performance
evaluation/feedback and conformance planning and decision making. We may well
recognize that where these interorganizational information systems are implemented, they
have a similar impact on joint planning and decision making outcomes as their non-IOS
enabled systems. However, as the deployment of these interorganizational information
systems continues, the increased levels of information currency and convenience of
access to information may well serve to increase the effect of IOS enabled information
systems over their non-IOS enabled counterparts. Managers should take specific note of
these findings since this appears to be an area where [US may be employed to their

firm ’s direct benefit.

This research suggests that there are also certain firm-level performance outcomes
that may be obtained through the increased information quality associated with better
joint performance evaluation/ feedback and conformance planning and decision making.
The 7 that relates joint performance evaluation/ feedback and conformance planning and
decision making outcomes with firm performance was relatively large (y=.3 l 3, p<.01).

In this SEM, performance outcomes where characterized by quality and total cost

reduction (see Table 20). It is also true that there were other firm-level performance

91

outcomes associated with planning and decision making in this context (see Table 76),
including:

(1) supplier Responsiveness (F29, p<.01),

(2) supplier on-time delivery (F28, p<.01),

(3) purchase price reduction compared to market (F23, p<.01),
(4) supplier quality performance (F21, p<.05),

(5) return on investment (ROI) (F.18, p<.05),

(6) return on equity (ROE) (F.17, p<.1),

(7) total cost reduction (F.17, p<.1) and

(8) external customer service levels (F. 1 7, p<.1).

Managers currently recognize the importance of post supplier selection
performance evaluation/ feedback and conformance. In fact, this context appears to have
been a focus for improvement over the past two years for most informants in this study
(see Figure 14). However, managers must recognize that post supplier selection
performance evaluation/feedback and conformance is a planning and decision making
context into which interorganizational information systems must play a key role in order
to obtain better firm-level performance. It is simply not practical, nor is it an effective

use of an employee’s time to use traditional communication mechanisms to monitor

92

supplier performance (and own firm’s conformance) in most cases.

 

 

 

 

 

 

 

 

 

 

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Figure 14: Post supplier selection performance evaluation/feedback and
conformance process improvements

It is interesting to note that firms are doing some very interesting things related to
post supplier selection performance evaluation/feedback and conformance. Returning to
the DaimlerChrysler Extended Enterprise SystemTM example, “The Non-Conformance
System (a firnction of SPIN) measures suppliers at the plant, division and top-parent
levels; by individual Chrysler plants; and by Procurement and Supply directors,
purchasing agents, buyers, quality managers, quality specialists and commodity codes.
The Non-Conformance System improves communication and reduces time, waste and
redundancy. The process allows any user at a participating Chrysler location to create a
potential alert, which is a notification of a part problem. Users may attach illustrations of
the nonconforming parts to the tickets. The system also can fax tickets and illustrations to

Chrysler suppliers. (DaimlerChrysler, 1997)”

93

Sourcing and Supply Proposal Evaluation
Sourcing and supply proposal evaluation is the process
of setting the terms and conditions of a purchase. These
terms and conditions frequently include price, quantity,
quantity discount, quality, technology, etc. Examples of
information sharing in support of sourcing and supply
proposal evaluation include (1) the buying company
sending the supplier a request for quotation (RFQ) or
(2) the supplier sending the buying company a quote in
response to an RF Q.

Information that is exchanged between supply chain partners in this joint planning
and decision making context is frequently standardized and well defined over finite time
periods. Information is typically also exchanged on standardized schedules for finite
periods of time. When a source is selected and a contract is established for the supply of
certain materials in certain time periods, this defines a specific standard for the ensuing
information transactions. Outside of this contract window, the information and
periodicity of information exchange will typically be much more variable.

This research supports the notion that better information quality is associated with
improved outcomes from sourcing and supply proposal evaluation planning and decision
making processes. Within this context, the quality of both IOS enabled and non-IOS
enabled information flows were associated with improvements in this joint process. Both
B’s that associated IOS and non-IOS enabled information flows with sourcing and supply
proposal evaluation planning and decision making outcomes (Bum-105:0.276, p<.01;
3103:0327, p<.01) were of a large magnitude. Further, a statistical test of difference
revealed that these parameter estimates were not statistically different (p=.988). In
addition, the analysis revealed (see Table 85) that there were no statistical differences

between the currency, accuracy, completeness or compatibility of information shared

94

through traditional or IOS methods. Similar to the post selection supplier performance
evaluation/ feedback and conformance joint planning process, there was a statistical
difference on the convenience of information access between IOS and traditional
methods. IOS enabled information flows were more convenient to access than their non-
IOS counterparts. In a fashion very similar to that of post supplier selection performance
evaluation/feedback and conformance, the effects of both [08 and non-IOS enabled
information quality on joint performance evaluation/ feedback and conformance planning
and decision making outcomes were essentially equal. Again, an explanation is needed
for the fact that while IOS enabled information flows provide a more convenient
mechanism for information access, the effect of IOS quality on joint planning and
decision making outcomes is not statistically different between the IOS and non-IOS
enabled information communication mechanisms.

One possible explanation might be that this joint planning and decision making
context is one in which interorganizational information systems are frequently employed
between firms who have been doing business together for a significant length of time. In
the past, the most common IOS enabled method for sharing information related to this
joint planning and decision making context was that of EDI. However, because of the
high cost of establishing and operating an EDI system, most suppliers (certainly the
smaller ones) would not have had the resources necessary to implement such a system. It
is for this reason that it is very likely that the findings within this joint planning and
decision making context are skewed towards a few larger firms and larger suppliers.
However, it is absolutely critical to recognize that there are now many other mechanisms

by which firms may share information related to supply proposal evaluation. In fact, in

95

recent months, firms have begun to utilize the World Wide Web (W) for this
purpose. Further, a more general version of EDI based on the XML standard is being
developed that will employ the WWW in place of a VAN as well as provide a more
robust set of transaction elements.

The purchasing/sourcing community has placed great emphasis on this joint

planning and decision making process over the past two years (see Figure 15).

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Figure 15: Supply proposal evaluation process improvement

Purchasing managers are spending time and money to create more efficient/effective

supply proposal evaluation processes. Certain improvements have come in the area of

 

supplier quail” " ’ tificatiun. By pre-qualifying/certifying suppliers, the buying
company no longer has to spend time evaluating every reasonable source for a given

purchase requirement. With the use of a well—implemented interorganizational

96

information system, the speed/ flexibility of these information transactions may occur
with qualified/certified suppliers may be greatly enhanced.

Purchasing professionals frequently have difficulty including/selecting the
appropriate potential sources of supply in a sourcing/supply proposal evaluation decision.
It is this arena that the use of an interorganizational information system may have
significant advantages for the purchasing organization in the not-so-distant future. It is a
well-understood fact that human beings are not very good at documenting, storing and
disseminating knowledge over time. Information frequently exists randomly over a
system, with little or no integration between system elements (people, departments,
divisions, business units, etc.). The effect of this situation is that the people who need
critical information to make a decision either don’t have access to the information or
can’t find the information (i.e. it is not convenient to access the information). A well-
irnplemented information system may provide a mechanism by which critical
information/knowledge (performance reporting, procedural issues, contact information,
etc.) may be captured and retained by one firm, but in so doing, made available to all
firms participating in that interorganizational system. Hence, a geometric expansion of
information is available on each potential source of supply.

There are also certain firm-level performance outcomes that might be expected
from improved joint sourcing/supply proposal evaluation processes. The SEM included
(1) total cost reduction, (2) purchase price reduction and (3) purchase price reduction
compared to market as measures of firm—level performance outcomes. The 7 that related
joint source/supply proposal evaluation with performance outcomes was of a relative

large magnitude (y=.313, p<.01). While these cost/price performance outcomes are

97

clearly expected to result from improved joint source/supply proposal evaluation
processes, it is clear that there may well be other elements of firm-level performance that
may be affected by improvements in this process. Table 77 describes several other firm-
level performance outcomes that may well be expected from improvements in this joint
planning and decision making process area. Some of these potential firm-level
performance improvements include:

(1) total cost reduction (F.30, p<.01)

(2) purchase price reduction (F29, p<.01)

(3) supplier on-time delivery (F23, p<.01)

(4) purchase price reduction compared to market (F.19, p<.05)
(5) return on equity (ROE) (F.18, p<.05)

(6) supplier responsiveness (F.16, p<.1)

(7) return on investment (F.16, p<. 1)

It is clear that the joint planning and decision making context of sourcing and
supply proposal evaluation is one that is critically important to the success of the firm. It
is also clear that the role interorganizational information systems currently play within
this context is relatively limited. Managers must review these findings in the context of
their business situation to determine how best to employ an interorganizational

information system in a more effective way within this context.

98

Part/Material Standardization
Part/material standardization is used to reduce the
number of unique parts/materials maintained in the
inventory system by using more standard and fewer
unique parts/materials. Examples of information
sharing in support of part/material standardization
would include (1) a buying company sharing materials
lists with a supplier and (2) a supplier evaluating these
lists and making recommendations to the buying

company about any possible standard part
substitutions.

Information that is exchanged between supply chain partners within this joint
planning and decision making context is frequently both of a non-standardized nature and
done on an ad-hoc basis. Many firms are attempting to develop better ways to employ
interorganizational information systems to enable more effective part/material
standardization processes, but much work remains to be done. While interorganizational
information systems appear to offer the long-term solution to many of the problems
associated with the part/material standardization process, these solutions do not yet exist
in a widely useable form.

This research supports the notion that information quality plays a critical role in
the outcome of the joint part/material standardization planning and decision making
process. Within this context, improved information quality within both IOS enabled and
non-IOS enabled information flows are associated with improved joint planning and
decision making outcomes. Both B’s that associated IOS and non-IOS enabled
information flows with sourcing and supply proposal evaluation planning and decision
making outcomes (Bnon-Ios=0-404, p<.01; 8105:0445, p<.01) were of a large magnitude.
Further, a statistical test of difference revealed that these parameter estimates were not

statistically different (p=.868). In addition, the analysis revealed (see Table 86) that there

99

were no statistical differences between the accuracy, completeness or compatibility of
information shared through traditional or IOS methods. There was a statistical difference
on information currency and the convenience of information access between IOS and
traditional methods. IOS enabled information flows were more current and more
convenient to access than their non-IOS counterparts. Given these differences in the
elements of information quality and the fact that the effects of both IOS and non-IOS
enabled information quality on joint part/material standardization planning and decision
making outcomes were essentially equal, an explanation is required to reconcile these
inconsistencies.

It is very likely that the number of interorganizational information system
applications related to the joint part/material standardization processes are very few in
number. These applications are also likely to be implemented on a very narrow basis.
These results suggest that the overall impact that information quality has on joint
part/material standardization processes is essentially equal between IOS and non-IOS
enabled mechanisms. However, these findings do point to the fact that joint
part/material standardization processes are likely to be an area of large upside process
improvement potential. Specifically, the findings of this research demonstrate that
information used in the part/material standardization process is much more current and
much easier to access than the same information accessed through traditional
communication mechanisms. For obvious reasons, within the context of joint
part/material standardization, information currency is an absolutely essential. Further, if

the information available through an IOS enabled mechanism is more convenient to

100

access, it is more likely to be used, providing a greater likelihood that the purchasing
team will actually be successful in standardizing parts and materials.

There are a number of firm-level performance outcomes that might be expected
from better joint part/material standardization processes. The SEM included (1)
inventory turnover, (2) on-time delivery and (3) purchase price reduction as measures of
firm-level performance outcomes. While the 7 that related joint part/material
standardization with performance outcomes was not statistically significant, it is clear
that there are a number of expected firm-level performance outcomes that are associated
with improved joint part/material standardization processes (see Table 78). Several of
these firm-level performance areas include:

(1) cash-to-cash cycle time (F29, p<.01)

(2) supplier on-time delivery (F25, p<.01)

(3) supplier quality performance (F.19, p<.05)
(4) total inventory turnover rate (F. 1 8, p<.05)
(5) profit margin (F.17, p<.1)

It is clear that the joint planning and decision making context of part/material
standardization is one that is important to the success of the firm. It is also clear that the
role interorganizational information systems currently play within this context may be
limited. The part/material standardization process is one of the joint planning and
decision making processes that will likely never be completely implemented until a
supply chain-wide interorganizational information system is established. The shear
numbers of parts/materials that exist any given supply chain makes the problem of
part/material standardization (performed without and interorganizational information
system) an incredibly labor intensive process that is destined to bear sub-optimal results.

Unfortunately, to implement an interorganizational information system to improve the

101

joint part/material standardization process, a huge amount of labor must be used in order
to provide the fiamework for the standardized system (part specification comparison,
common coding, etc). An examination of Figure 16 supports this conclusion. Firms have
not achieved improvements in their joint part/material standardization processes to the
same degree as many of the other joint planning and decision making processes that have
been addressed in this research. This is very likely due to the fact that the problems
associated with joint part/material standardization are much more difficult to address than

many of the problems associated with other joint planning and decision making process

 

 

 

 

 

 

 

 

 

 

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Figure 16: Joint part/material standardization process improvements

102

S_llleier Scheduling
The supplier scheduling process controls the releases of
orders through MRP systems (or other systems) and
ensures communications of priorities, needs, and
quantities between the buying organization's
production or operations management system and
suppliers. Examples of information sharing in support
of supplier scheduling include the sharing of
information related to order date, quantity ordered,

required due date, ship-to-location, item identification,
key contact person and so forth.

Information that is exchanged between supply chain partners in this context is
typically very standardized and well defined. This information is frequently exchanged
on a relatively standard schedule. This joint planning and decision making context
provides a natural/intuitive setting for an interorganizational information system. In fact,
for pairs of firms, this is one of the joint planning and decision making processes that has
the most robust history of interorganizational information system use. While these
systems typically are not able to link directly through a supply chain (though a common
element), many firms in a supply chain are likely to be interconnected through pairs of
firms sharing information in support of this joint planning and decision making process.

This research supports the notion that information improved quality is associated
with better joint inventory visibility planning and decision making outcomes. Both the
quality of IOS enabled and non-IOS enabled information flows are associated with
improved joint inventory visibility planning and decision making outcomes. The B that
associates IOS enabled information flows with joint inventory visibility outcomes (0.556,
p<.01) was of a very large magnitude. The [3 that associates non-IOS enabled
information flows with joint inventory visibility outcomes (0.209, p<.01) was of a

smaller, but still reasonably large magnitude. A statistical test of difference revealed that

103

these parameter estimates were indeed different (p<.01). In a similar fashion to both
forecasting and inventory positioning and inventory visibility, each individual element of
information quality (currency, accuracy, completeness, compatibility and convenience to
access) had a significantly higher mean score for the quality of IOS enabled information
than for the quality of non-IOS enabled information (see Table 87).

Information quality is also associated with certain firm-level performance results
including on-time delivery, profit margin and cash-to-cash cycle time. Specifically, the
total effect (mediated by joint planning and decision making outcomes) of IOS enabled
information flows on performance outcomes (responsiveness and on-time delivery) is
0.188. The total effect (mediated by joint planning and decision making outcomes) of
non-IOS enabled information flows on performance outcomes (responsiveness and on-
time delivery) is .103. These total effects indicate that while there is a fairly stark
contrast in the effects of information quality on joint planning and decision making
outcomes between IOS and non-IOS enabled information mechanisms, this difference is
attenuated when the total effect on firm-level performance is examined. While it may
appear that this smaller difference between the total effects of IOS and non-IOS enabled
information quality firm-level performance outcomes (when compared to joint planning
and decision making outcomes) reduces the significance of these findings, this is not the
case. Firm-level performance outcomes are affected by a host of other variables (both
internal and external to the firm). When viewed in this light, it is clear that the supplier
scheduling joint planning and decision making context may very well be one of the
success stories for interorganizational information systems in the manufacturing arena

today. Clearly all five elements of information quality are significantly better than the

104

same elements for non-IOS enabled information quality. It is this increased quality of
information that allows better joint planning and decision making outcomes to occur.
These improved joint planning and decision making outcomes have a significant positive
affect on firm performance. In addition to the measures of firm-level performance
described above, this research supports the notion that there are several other firm-level
performance results that may be expected from improved joint supplier scheduling
planning and decision making outcomes (see Table 79). Several of these firm-level
performance measures include:

(1) total cost reduction (F.18, p<.01)

(2) inventory turnover (F23, p<.01)

(3) purchase price reduction compared to market (F22, p<.01)
(4) purchase price reduction (F22, p<.01)

(5) ROI (F20, p<.05)

(6) ROE (F20, p<.05)

(7) profit margin (F.19, p<.05)

(8) on-time delivery (F.18, p<.05)

(9) cash-to-cash cycle time (F.16, p<.l)

However, it is critical to note that the joint supplier scheduling planning and
decision making context is not devoid of potential for improvement. In fact, quite the
opposite is actually the case as firms reported that they have made substantial
improvements in their supplier scheduling planning and decision making processes over

the past two years (see Figure 17).

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106

Supplier Scheduling Process Improvements

Figure 17

Joint Goal/Target Setting

Joint goal/target setting ensures that there are mutually
acceptable performance targets that are rooted in
common/aligned metrics. An example of information
sharing in support of joint goal/target setting includes
the sharing of information by supply chain partners
related to establishing acceptable purchased-product
quality levels (Cpk, ppm, etc.), responsiveness, on-time
delivery, cost improvements, etc.

Information that is exchanged between supply chain partners in this joint planning
and decision making context is frequently non-standardized and not well defined.
Information is typically not shared on a standard or defined schedule. The joint
goal/target setting process is frequently done in the spirit of continuous improvement and
generally involves quite a bit of direct contact between key members in each of the
organizations. Typically this direct contact is undertaken through traditional
communication methods.

This research supports the notion that improved information quality is associated
with better outcomes from the joint goal/target setting planning and decision making
process. Within this context, the quality of both IOS enabled and non-IOS enabled
information flows are associated with improved outcomes of this joint process. Both B’s
that associated 108 and non-IOS enabled information flows within the joint goal/target
setting planning and decision making outcomes (Bnon-ros=0.209, p<.01; 0105:0556,
p<.01) were of a large magnitude. Further, a statistical test of difference revealed that
these parameter estimates were statistically different (p=.004). In addition, the analysis
revealed (see Table 85) that there were no statistical differences between the currency,
accuracy, completeness or compatibility or convenience of access of information shared

through traditional or IOS methods. This raises an interesting question. How is it

107

possible that while none of the individual measures of information quality were
statistically different (between IOS enabled and non-IOS enabled information flows),
there is a significant difference between the parameters that relate the higher order
information quality constructs to the join planning and decision making outcomes? The
answer to this question may be found by examining the B that relates non-IOS enabled
information quality directly to firm-level performance. This parameter is of a large
magnitude (B=.310,p<.01). Further, the parameter that relates joint goal/target setting
planning and decision making outcomes with firm-level performance was not of a large
magnitude (F062, p=.666). Hence, it is clear that there is some other mechanism at
work in this context. It is important to note that the SEM included only total cost
reduction and purchase price reduction as measures of firm-level performance. A brief
discussion will follow that will explain this apparent inconsistency in these findings.
Figure 19 depicts a very simple performance measurement process. The process
begins by establishing a set of joint goals/targets between firms. During this phase of the
process, it would be expected that information quality would have a direct and positive
effect on the joint planning and decision making outcomes. Indeed, these research
findings support this contention. However, it would not necessarily follow that at this
stage in the joint planning and decision making process, there would be a cost/price firm-
level performance result. These results may have to do with the fact that better quality
information is enabling better performance measurement which is itself leading to better
firm-level cost/price performance outcomes. As this study was cross-sectional in nature,
this effect may be attributed to the fact that the process we are examining is longitudinal

in nature, and the results of the process actually occur in a subsequent process stage.

108

Overall, firms reported that their joint goal/target setting processes had improved over the

past two years (see Figure 18).

60-

50-

 

40-

 

30- l

20-

Number oflnformants

10

 

 

 

 

 

 

 

 

131198 qonw .—
asroM roN
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Figure 18: Joint Goal/Target Setting Process Improvements

It is important to note that there were several other firm-level performance
outcomes which may also result from improved joint goal/target setting planning and
decision making (see Table 80). Several of these include:

(1) purchase price reduction compared to market (F.3, p<.01)
(2) purchase price reduction (F28, p<.01)

(3) total cost reduction (F25, p<.01)

(4) supplier responsiveness (F22, p<.01)

(5) supplier on-time delivery (F21, p<.05)

(6) total inventory turnover rate (F20, p<.05)

(7) return on equity (F.19, p<.05)

(8) return on investment (F.17, p<.1)

109

      

 

Establish Joint Goals/Targets

 

Report Out-
Take Corrective Action

     
 

; Measure Performance

Figure 19: Joint Goal/Target Setting Process

110

Managerial Implications

This research established that the quality of the information exchanged between
firms has a significant impact on a firm’s ability to make better decisions. It also shows
that linked information systems typically provide better quality information than more
traditional methods of communication (meetings, phone, fax, etc.). These findings
should reinforce the need for firms to develop their linked information systems within the
context of their own supply chain(s) specific needs.

Frequently, firms are achieving performance improvements (total cost, price,
quality, delivery, responsiveness, etc.) as a direct result of using linked information
systems with only a very few key suppliers. However, the development of these systems
is frequently done largely in a vacuum, without the context of the broader supply chain.
This development strategy is short-term in nature and at best will provide an unnecessary
period of “stumbling around” while the firms within a supply chain each create a variety
of one-off linked information systems. At worst, the lack of a supply chain focus in the
development of linked information systems will make it very difficult if not impossible to
fully realize the potential that these technologies are able to offer.

Consideration needs to be paid not only to the needs of each supply chain member
in the creation of the linked information system, but to the resources and capabilities of
each supply chain member as well. There are lessons to be learned from our last global
effort at creating a linked information system. EDI, while brilliant in its conception, was
not cost-effective to operate and required significant up-front expense to implement.
This necessarily excluded most firms (certainly smaller/less sophisticated ones) from

participating. We must not make these same mistakes again.

lll

We now have the technologies and network infrastructure available to allow for
the creation of a set of standards and technology-enabled mechanisms that will lay the
groundwork for a fully interchangeable/universally connectable system. Development of
linked-information systems should be done with this in mind.

Managers today should be working hard to discover where there is a logical place
to remove traditional cross-organizational processes and supplement (or replace) them
with linked information system enabled processes. The following is a brief review of
each of the eight joint planning and decision making process areas. Key applicability to
linked information systems is established and linkages to performance outcomes are
drawn.

The following sections review the eight joint planning and decision making areas
with particular attention paid to managerial implications. Further, Table 24 provides a
summary of the effects of improved joint planning and decision making processes on
firm level performance within each of the eight joint planning and decision making
contexts. Figure 20 provides a 2 X 2 matrix designed to aid in establishing the priority
for interorganizational information system development. Each of the eight areas is
discussed in light of its potential marginal contribution to overall firm performance. This
discussion should be taken in the context of the “average firm.” Firms who have
particularly strong or weak interorganizational information systems in each of these areas

should view these results within that context.

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113

 

High Hold/Maintain Maintain/Improve

- Forecasting & Inventory - Capacity Planning

Positioning
° Supplier Scheduling
- Inventory Visibility

 

Develop!
- Goal/Target Setting
- Performance

Evaluation/Feedback and
Conformance

Current IOS Sophistication

0 Supply Proposal Evaluation

 

 

 

LOW ' Standardization

 

Low Impact on Firm-Level Performance High

Figure 20: IOS Development Priority Matrix

Priority 1: Joint Goal/Targt Setting

Firms reported that their joint goal/target setting processes had improved
significantly over the past two years and that linked information system applications in
support of joint goal/target setting do provide a significantly higher degree of information
quality than their traditional counterparts. However, the many firms have not developed
joint goal/target setting IOS enabled interorganizational information systems to an extent
take full advantage of the wide range of firm level performance outcomes that are found
within this context. Specifically, Firms reported performance improvements in the areas
of purchase price reduction compared to market, purchase price reduction, total cost
reduction, supplier responsiveness, delivery, inventory turnover, return on equity and

return on investment.

114

Priority 1: Post Supplier Selection Performance Evaluation/Feedback and Conforma_nge_

This area provides quite a bit of potential for improvement. While this joint
planning and decision making context has received quite a bit of focus over the past
several years it is much less developed than many of the processes examined in this
research. It would appear that some firms are using linked information systems to
support performance measurement, but likely only in a very limited way. The focus of
these improvements must be undertaken within the spirit of a supply chain linked
information system. This area was selected as a “priority 1” area because of the fact that
interorganizational systems are not yet well developed and the finding that improvements
in this process area lead to a wide range of performance benefits including supplier
responsiveness, delivery, purchase price reduction compared to market, supplier quality
performance, return on investment, return on equity, total cost reduction and external
customer service levels.

An example of a firm who has implemented a linked information system includes
DaimlerChrysler. When material defects are discovered, users at DaimlerChrysler can
create alerts that may be sent online to suppliers. These alerts may contain illustrations or
scanned in images of the material defect problems. While this is much more simple
system than might be warranted, it is a vital initial step in the development of a more
inclusive performance measurement system.

Priority 1: Part/Materizfitandardization

Part/material standardization was selected as a “priority 1” area for

interorganizational information system development for a number of reasons. First, the

process by which standardization is achieved is very well-suited to an information system

115

enabled solution. Second this is the one area where firms did not report that significant
improvements had been made in the process over the past two years. While this may, in
part, be a function of the difficulty in solving some of the problems related to making
improvements in this area, it does leave room for a significant amount of both process
and technology development. Finally, firms reported that improvements in their joint
part/material standardization processes were associated with a wide range of firm-level
performance outcomes including cash-to-cash cycle time, delivery, quality, inventory
turnover and profit margin.
Priority 1: Sourcing and Supply Proposal Evaluamn

Sourcing and supply proposal evaluation was selected as a “priority 1” area for
interorganizational information system development for a number of reasons. First, there
is a large amount of organizational knowledge that must be considered in a
sourcing/supply proposal decision. There is no effective way to share this organizational
knowledge without the use of an interorganizational information system. It is only
through the use of a properly deployed knowledge management system that the best
source of supply may be selected. Further, interorganizational information systems
implemented in this areas leave room for substantial improvements. Finally, firms
reported that improvements in this joint planning and decision making area were
associated with a wide range of firm-level performance outcomes including on-time
delivery, supplier responsiveness, return on investment, return on equity, total cost
reduction, purchase price reduction and purchase price reduction compared to market.
Also, firms reported that the use of a linked information system was typically more

convenient than the use of traditional methods to support decision making. Given the

116

 

new technologies that are available, this process area provides an extremely high
opportunity for linked information system use.
Priorig 2: Capacity Planning

Capacity planning was selected as a “priority 2” area for development because
significant sophistication currently exists in joint capacity planning and decision making
systems. This is not to say that systems development should not be undertaken in this
area. However, systems development should be done with the knowledge that
development budgets are limited, and improvements in other areas may make a larger
contribution to the bottom line. The wide range of performance improvements reported
by firms in this study lend credence to the fact that this joint planning and decision
making context is one in which firms are currently having quite a bit of success.
Specifically, performance improvements were reported in the areas of inventory turnover,
purchase price reduction compared to market, delivery, supplier responsiveness, total cost
reduction, return on investment, profit margin, return on equity and purchase price
reduction.

It is also true that there are firms who have, to some degree, implemented basic
supply chain-wide capacity planning systems. For instance, DaimlerChrysler has
implemented a World Wide Web based system that allows any DaimlerChrysler supplier
with an active contract to view DaimlerChrysler capacity planning information.

Priority 2: Supplier Scheduling

Supplier scheduling was selected as a “priority 2” area because it has both

received the benefit of considerable process improvement and has been one of the

mainstay areas for the few linked information systems that exist today. Interestingly,

117

firms have reported making substantial improvements in their supplier scheduling
systems over the past two years and also reported performance improvements in the areas
of cash-to-cash cycle time, delivery, quality, inventory turnover and profit margin.
Priority 3: Forecasting and Inventory Positioning

Firms are working diligently to develop linked information systems designed to
enable improved forecasting and inventory positioning processes. The use of linked
information systems to facilitate this joint planning and decision making process is
natural and many of these systems exist today. However, work needs to be done to
transform these systems expanding the linkages to firms on a supply chain-wide basis.

Firms are achieving significant performance results in the areas of delivery,
supplier responsiveness, inventory turnover, cash-to-cash cycle time and reduction of
purchase price compared to market.
Priority 3: Inventory Visibility

F irrns are putting an emphasis on creating linked information systems to facilitate
better joint inventory visibility planning and decision making processes. However, these
systems may be more ofien employed for the more routine inventory location fimctions.
It would appear that firms might improve performance by implementing linked
information systems designed to facilitate ad-hoc inventory location purposes. In order
to achieve this goal, a focus on the supply chain-wide linked information system is
necessary. Additional development may need to be done in the area of “ad-hoe”

inventory visibility tools.

118

Firms reported performance results from this joint planning and decision making
context that included delivery, supplier responsiveness, purchase price reduction

compared to market, inventory turnover rate and return on equity.

119

Summa_ry_ and Conclusion

"Doing business over the internet has got to be the wave of
the future. If you look around the world today there's
perhaps 8 or 9 billion dollars worth of business done over
the intemet.

Forecasts are by the end of this decade there'll be hundreds
of billions of dollars in business done each year over the
intemet. The reasons for this are very simple: it's fast,
efficient, gives you access to information anytime,
anyplace, anywhere. It is the wave of the future.

That's the direction that Intel's going. That's [where] we
need your [suppliers] help. We're putting our tools up on
the intemet, [and] our information... That's how we want to
conduct business in the future. It's going to be the only way
that we conduct business in the future. We're looking
forward to working with you [suppliers], doing business
that way. Thanks. (Intel, 1999a)"

—Craig R. Barrett,
President and Chief Operating Officer, Intel Corporation
March 23, 1998

Craig Barrett, in the above speech to Intel’s suppliers sums this research up
nicely. Interorganizational information systems are not a luxury, rather they are well on
their way to becoming the predominant way in which firms will conduct business. This
research examined eight joint planning and decision making contexts and the quality of
information shared between organizations within each. It was clear that information
quality plays an absolutely critical role in joint planning and decision making processes.
Further, in many of these contexts, it was clear that the information quality afforded by
the use of an interorganizational information system was significantly greater than the
information quality inherent in traditional communication methods.

The message seems clear. Firms must recognize that they will necessarily be

using interorganizational information systems for more and more processes that were

120

traditionally performed using traditional communication methods. It is absolutely vital
that these new interorganizational systems and the standards that surround them are
implemented in a well thought through manner. If these systems are implemented
individually by firms without respect to other firms in the their supply chains, industries,
etc. the result will be an ineffective system that will fall substantially short of meeting
their potential. In ten years we will need to rebuild these systems as opposed to using
them as a foundation for greater achievements.

Research Extensions

This research employed a technique whereby the responding company selected a
supplier and responded to the questionnaire exclusively about the quality of the
information that is exchanged between the focal firm and the chosen supplier. A valuable
extension to this study would be to use a set of paired buying and supplying companies.
Each set of paired firms would respond regarding the quality of the information flowing
between the firms. This would provide for a more robust assessment of the quality of
information passing between the firms.

This research might also be extended by studying the effect of information quality
on joint decisions made in another part of the supply chain. For instance, there are many
firms today who are using the intemet to facilitate the sale of their wares (Dell, Gateway,
Amazon.com, etc.). An interesting extension to this research would be to apply this
research framework to an OEM-end consumer integrated information system.

Research Limitations
This research examined the effect of the quality of information flowing between

supply chain partners on joint planning and decision making outcomes and firm-level

121

performance. An improved assessment could be made if this research also measured the
quantity (or volume) of information flowing between supply chain partners. It would
bolster the findings of this research if the issue of information volume could be separated
from information quality.

The use of a single firm to respond regarding the quality of the information passed
between to supply chain partners is likely to create a bias in the estimates of information
quality. The responding company must guess as to the perceived quality of the
information from the perspective of the supplying company.

The sample used in the research was drawn primarily from firms located in the
United States of America. Firms from abroad must recognize this fact and employ an

extra measure of caution when applying the findings of this study to their own business

situations.

122

APPENDICES

123

Appendix A: Key Definitions

124

KEY DEFINITIONS

 

Key Term

Definition

 

Data Quality

“The measure of the agreement between the data views
presented by an information system and that same data in the
real world” (Orr, 1998).

 

Information Quality

The degree to which the information exchanged between
organizations meets the needs of the organizations.

 

 

Interdependence The lack of ability on the part of supply chain partners to
individually control all of the conditions necessary to achieve
an action or desired outcome.

Interorganizational A system which is built around information technology, i.e.,

Information Systems
(IOS)

around the computer and communications technology that
facilitates the creation, storage, transformation, and
transmission of information. An interorganizational system
differs from an internal, distributed information system by
allowing information to be sent across organizational
boundaries. Access to stored data and applications programs
is shared, sometimes by varying degrees, by the participants
in an interorganizational system (Cash & Konsynski, 1985).

 

 

 

Interorganizational The extent to which interdependent activities which link

Integration interacting organizational units are viewed, operated and
managed as a single system (McGee, 1991).

IOS enabled All forms of interorganizational communication that are

communication conducted within the interorganizational information system.

Joint Flaming and The critical planning and decision-making processes that

Decision Making require bilateral information flow between supply chain

partners. The focus of these joint planning and decision
making processes is of a more strategic nature and includes
the broad categories of supply planning, demand planning,
inventory management and goals and performance
measurement.

 

Non-IOS enabled

All forms of interorganizational communication that are

 

communication outside of the communication conducted within the
interorganizational information system.
Supply Chain An organization of networks of manufacturing and

distribution sites that procure raw materials, transform them
into intermediate and finished products, and distribute the
finished products to customers (Lee & Billington, 1992). In
addition, this definition includes the suppliers from whom the
raw materials and components, subsystems and systems are
purchased.

 

 

Performance Results

 

The set of tangible benefits that accrue to the organization as a

 

125

 

 

Key Term

Definition

 

result of closer interorganizational integration with a supply
chain partner.

 

Supply Planning
Business Processes

Supply planning business processes are those processes that
enable the supply of acceptable materials/services from your
supplier to your firm in a timely fashion. Some examples of
the supply planning business processes include (1) supplier
development, (2) lead-time/responsiveness planning, (3)
supplier product schedule visibility, (4) shared supplier cost
information, etc.

 

Supply Uncertainty

The degree of unpredictability in future material supply states
(Pfeffer & Salancik, 1978). Similarly defined in the TCE
literature as "unanticipated changes in circumstances
surrounding an exchange" (Noordewier, John, & Nevin,
1990)

 

 

Trust

 

A willingness to rely on an exchange partner in whom one has
confidence" (Moorrnan et al., 1992).'

 

126

 

Appendix B: Structural Equation Methodology Symbols/Definitions

127

STRUCTURAL EQUATION METHODOLOGY SYMBOLS/DEFINITIONS

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Symbol Definition (Bollen, 1989)

(~35 (Theta Delta) Covariance matrix of 5

Or: (Theta Epsilon) Covariance matrix of e

X Observed indicators of r]

y Observed indicators of g

5 Measurement errors for y

5 Measurement errors for x

‘1) (Lhi) Covariance matrix of E,

q (Eta) Latent endogenous variables

w (Psi) Covariance matrix of Q

g (Ksi) Latent exogenous variables

Q (Zeta) Latent errors in equation

Ax (Lambda x) Coefficient relating y to n

Ay (Lambda y) Coefficient relating x to g

B (Beta) Coefficient matrix for latent endogenous variables
F (Gamma) Coefficient matrix for latent exogenous variables

 

128

 

Appendix C: Survey Cover Letter

129

BROAD

THE ELI BROAD
GRADUATE SCHOOL
OF MANAGEMENT

IheGWPermdSrwfy
(7917me
Robert I. Monczka. Pti.D.

Diredor and

Pmiessor oi Strategic Sourcing
W and The National
Assouation oi Purchasrng
Management Protessor

Michigan State Universny
N505 North Busmess Complex
East Lansmq MIChlqan
48824-1 I22

517 1‘43? 2086

FAX 517 "432-2094

Email Jerwrlomi 7‘3'.‘ em.
WWW ”175 "Jeff TM; "ASL; >301;

MICHIGAN STATE

UNIVERSITY

 

Mr. First_Name I.ast_Namc
Tit|e_l

Title_2

Company_Namc

Address

City. State Zip

November 11, 1998
Dear First_Name:

The Global Procurement and Supply Chain Benchmarking Initiative in The Eli Broad Graduate School of
Management at Michigan State Universny is conducting a worldWide study to learn how the use of inter-
company integrated information systems may help to create better perfonning supply chains. We request
your firm's participation in this critical research. This project is in addition to both our current and
scheduled 1999-2000 work.

Establishing inter-company integrated information systems With appropriate suppliers may have a
significant impact on a finn's competitiveness through improvements in product development and orher
cycle times. quality. cost, technology, delivery and producUserVice value We Will determine what this
impact is. as well as relationships to key methods of integration.

In return for your participation, you Will receive an Executive Summary of the findings from this research
that we Will complete dunng the first quarter of I999. Tlus Executive Summary Will prowde your firm
With valuable strategic and tactical information for achievmg competitive advantage through the use of
integrated information systems. Some key outputs in the Executive Summary Will include;

0 An analysis/prioritization of which joint planning and decisron making activmes are better suited
for use with an integrated information system and which activrties are better left to more
traditional ways of sharing information.

0 A pnontization of which jomt planning and decr5ion making activities have greater impact on
bottom-line supply chain performance.

0 lnSight into Where firms are havrng the greatest success and the greatest difficulty in managing
the exchange of information With supply chain partners.

C] Recommendations to help improve these communication and jomt planning and dCClSlon making
processes.

Please complete and fax the enclosed Fax Participation Response Form indicating when we should
expect to receive your response (please return your completed survey not later than December l5, I998)
If you have any questions regarding items in the questionnaire. please call Ken Petersen. project manager,
at (5 l 7) 432-2086 ext. 273. or send email to peter131@pilot msu cdu

We strongly encourage your firm's pamcrpation in this important research and bClIC\'C the resulting
Executive Summary WI” be valuable iii enhancrng your firms COIIIPCIIIHCIICSS We look forward to your
partiCIpation

Sincerely.

/%.47‘/% MA

Robert M Monczka

130

Appendix D: Survey F ax-Back Response Form

131

 

 

The Global Procurement and Supply Chain Benchmarking Initiative

Eli Broad Graduate School of Management 0 Michigan State University

N505 North Business Complex 0 East Lansing, MI 48824-II22

Phone: SI7/432-2086 ext. 273 0 Fax: 517/432-2094 - Internet: peter131@pilot.msu.edu
a WWW: http://gebn.bus.msu.edu

 

DATE: November 11, 1998 Fax Participation

Response Form

FROM: Salutation First_Name Last_Name

1.

Company

The Impact of Information Systems on Achieving Supply Chain Integration

Please fill out the following form and fax it to The Global Procurement and Supply Chain
Benchmarking Initiative at 517-432-2094.

E] Yes — I will participate in The Impact of Information Systems on Achieving Supply Chain
Integration.

You will receive my response by:

U November 30, 1998

D December 15, I998 - If you are responding, we must have
your completed questionnaire by this date.

My fax number is:

 

C] No - I will not participate in this study.

 

' PLEASE FAX THIS FORM TO 517-432-2094

 

(REFERENCE: it)

132

Appendix E: Survey Instrument

133

 

 

THE GLOBAL PROCUREMENT AND S UPPL Y CHAIN
BENCHMARKIN G [N] TIA TI VE

“A Leader in Procurement and Supply Chain Research"

 

 

\\\\ ‘

 

 

The Eli Broad Graduate School of Management
Michigan State University

Director: Robert M. Monczka, Ph.D.

Principal Investigator: Kenneth J. Petersen

 

 

THE IMPA CT 0F INFORMA TION
S YS TEMS ON A CHIE VING S UPPL Y

CHAIN INTEGRATION

 

 

 

134

SECTION 1: BUSINESS UNIT BACKGROUND

Please fill in your contact information in the space provided:

onipany

Olll' me:

our

OIII’

 

l. Which description best characterizes your business unit? Please check ONE response only.

E] Company

C] Group

0 Division

Cl Plant/Site

D Other (Specify)

 

2. Where is your business unit located? Please check ONE response only.

C] U.S.A. [3 Japan El Western Europe
[3 Canada Cl Korea D Eastern Europe
0 Mexico or South America CI Hong Kong 0 Middle East

C] Australia 0 Asia Pacific - Other

3. Check the box that best describes the manufactaring/operations/service process in the business unit for which you are
responding. Please check ONE response only.

 

Manufacturing E] Service (Please describe below)
Cl Batch fabrication
Cl Batch process D Other (Please describe below)

CI Repetitive manufacturing/assembly
CI Continuous process

 

4. Please check the box that approximately represents the total annual sales revenue for the business unit for which you are
responding (U.S. Dollars). Please check ONE response only.

C] SO - $250 million C] > SI billion - $5 billion
D >S2SO million - $500 million El Greater than $5 billion
C] >$500 million - SI billion

5. Please check the box that best represents your business unit's IMMEDIATE customer for your primary output. Please
check ONE response only.

Another business unit of the same company
Manufacturer

Wholesaler

Retailer

End user (consumer)

[30000

135

SECTION II: INF ORMA TION QUALITY AND PROCESS OUTCOMES

The following questions ask you about the Processes In Use between your business unit and the selected supplier.

6.

FORECASTING AND INVENTORY POSITIONING - Forecasting and inventory positioning is used to ensure that required
items are available at the proper location and in the proper form when needed in the supply chain. An example of information
sharing in support of inventory positioning is the joint sharing of forecasted inventory levels by location and quantity, safety stock
levels, replenishment cycle information, etc. The information shared between my BUSINESS UNIT and this SUPPLIER (in
support of FORECASTING AND INVENTORY POSITIONING):

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

When using Traditional Methods (phone, fax. meetings, postal When using Linked Information Systems (EDI, MRP. ERP,
mail. etc.) is: WWW, etc.) is:
Strongly Strongly Strongly Strongly
Agree Indifferent Disagree Agree Indifferent Disagree
a Current I 2 3 4 5 6 7 f. Current I 2 3 4 S 6 7
b. Accurate I 2 3 4 S 6 7 g. Accurate l 2 3 4 5 6 7
c. Complete I 2 3 4 5 6 7 h. Complete ' I 2 3 4 5 6 7
d. Compatible l 2 3 4 5 6 7 i. Compatible I 2 3 4 S 6 7
e. Convenient to l 2 3 4 5 6 7 j. Convenient to l 2 3 4 S 6 7
access access '
Strongly Strongly
Agree Indifferent Disagree
k. The forecasting and inventory positioning process in place with this I 2 3 4 S 6 7
supplier has helped MY BUSINESS UNIT to make effective decisions
I. The forecasting and inventory positioning process in place with this I 2 3 4 5 6 7
supplier has helped this SUPPLIER to make effective decisions
in. The forecasting and inventory positioning process in place With this I 2 3 4 5 6 7
supplier has provided positive results for MY BUSINESS UNIT
n. The forecasting and inventory positioning process in place with this I 2 3 4 5 6 7
supplier has provided positive results for this SUPPLIER
7. INVENTORY VISIBILITY - Inventory visibility provides the ability to track where any given item is physically located

(transit, customs, supplier, etc.) or where it was used. An example of information sharing in support of inventory visibility
includes the joint sharing of current inventory information by location and quantity. The information shared between my
BUSINESS UNIT and this SUPPLIER (in support of INVENTORY VISIBILITY):

 

 

 

 

 

 

 

 

 

 

 

 

 

 

When using Traditional Methods (phone, fax, meetings, postal When using Linked Information Systems (EDI. MRP. ERP,
mil. etc.) is: W, etc.) is:
Strongly Strongly Strongly Strongly
Agree Indifferent Disagree Agree Indifferent Disagree
a. Current I 2 3 4 5 6 7 f. Current I 2 3 4 S 6 7
b. Accurate l 2 3 4 5 6 7 g. Accurate l 2 3 4 5 6 7
c. Complete l 2 3 4 5 6 7 h. Complete I 2 3 4 5 6 7
d. Compatible I 2 3 4 S 6 7 i. Compatible I 2 3 4 5 6 7
e. Convenient to I 2 3 4 S 6 7 j. Convenient to I 2 3 4 5 6 7
access access
Strongly Strongly
Agree Indifferent Disagree
k. The inventory visibility process in place with this supplier has helped I 2 4 5 6 7
MY BUSINESS UNIT to make effective decisions
I. The inventory visibility process in place with this supplier has helped I 2 4 S 6 7
this SUPPLIER to make effective decisions
m. The inventory visibility process in place with this supplier has provided I 2 4 S 6 7
positive results for MY BUSINESS UNIT
n. The inventory visibility process in place With this supplier has provided I ‘ t s r» 7

positive results for this SUPPLIER

136

5'4

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

B. CAPACITY PLANNING - Capacity planning is conducted to ensure that the supplier will have the ability to produce or make
available the required items/services in the required lead-time. An example of information sharing in support of capacity
planning would include (I) the supplier sharing plant capacity utilization information with your business unit or (2) your business
unit sharing future demand forecasts and plans With the supplier. The information shared between my BUSINESS UNIT and
this SUPPLIER (in support of CAPACITY PLANNING):

When using Traditional Methods (phone, fax, meetings, postal When using Linked Information Systems (EDI. MRP. ERP.
"”"r “I ‘“ Strongly Strongly m ““l 3" Strongly Strongly
Agree Indifferent Disagree Agree Indifferent Disagree
a.Current l234567— {Current 1234567
b.Accurate I234567 g.Accurate I2 34567
c.CompIete1234S67 h.CompIetel234567
d. Compatible l 2 3 4 5 6 7 i. Compatible I 2 3 4 5 6 7
c.Convenientto I 2 3 4 5 6 7 j.Corivenientto l 2 3 4 S 6 7
access timers
Strongly Strongly
Agree Indifferent Disagree
k. The capacity planning process in place with this supplier has helped I 2 3 4 5 6 7
MY BUSINESS UNIT to make effective decisions
I. The capacity planning process in place with this supplier has helped I 2 3 4 5 6 7
this SUPPLIER to make effective decisions
m. The capacity planning process in place with this supplier has provided I 2 3 4 5 6 7
positive results for MY BUSINESS UNIT
n. The capacity planning process in place with this supplier has provided I 2 3 4 5 6 7
positive results for this SUPPLIER

9. POST SUPPLIER SELECTION PERFORMANCE EVALUATION/FEEDBACK AND CON FORMANCE - Post supplier
selection performance evaluation/feedback and conformance (based on objective measures) is used to ensure that there is joint
understanding and agreement about both your firm's and the supplier's performance. Examples of information sharing in support
of post selection performance evaluation/feedback and conformance include (I) your business unit sharing supplier performance
information about quality, delivery, responsiveness, using agreed to metrics with the supplier or (2) the supplier sharing similar
performance information with your business unit. The information shared between my BUSINESS UNIT and this
SUPPLIER (in support of POST SUPPLIER SELECTION PERFORMANCE EVALUATION/FEEDBACK AND

_ CON FORMANC E): When using Linked Information Systems (EDI, MRP, ERP,

When using Traditional Methods (phone, fax, meetings, postal WWW, etc.) is:

”m m) “' Strongly Strongly Strongly Strongly

Agree Indifferent Disagree Agree Indifferent Disagree
aTurrent l234567 f.Current l234567
b. Accurate l 2 3 4 5 6 7 g. Accurate I 2 3 4 5 6 7
c. Complete I 2 3 4 5 6 7 h.Completc l 2 3 4 S 6 7
d. Compatible I 2 3 4 5 6 7 i. Compatible I 2 3 4 S 6 7
e Convenient to I 2 3 4 5 6 7 j. Convenient to l 2 3 4 5 6 7

access access
Strongly Strongly
Agree Indifferent Disagree
k. The post selection supplier performance evaluationdeedback and I 2 3 4 S 6 7
conformance process in place with this supplier has helped MY
BUSINESS UNIT to make effective decisions
I. The post selection supplier performance evaluation/feedback and l 2 3 4 S 6 7
conformance process in place with this supplier has helped this
SUPPLIER to make effective decisions
in. The post selection supplier performance evaluationJeedbaclr and l 2 3 4 5 6 7
conformance process in place with this supplier has provided positive
results for MY BUSINESS UNIT
n. The post selection supplier performance evaluation/feedback and I 3 4 w (i ‘

conformance process in place with this supplier has provided positive
results for this SUPPLIER

137

 

I0. SOURCING AND SUPPLY PROPOSAL EVALUATION -

Sourcing and supply proposal evaluation is the process of setting

the terms and conditions of the purchase. These terms and conditions frequently include price, quantity, quantity discount,
quality. technology, etc. Examples of information sharing in support of sourcing and supply proposal evaluation include (I) your
firm sending the supplier a request for quotation (RFQ) or (2) the supplier sending your firm a quote in response to your firm’s
RFQ. The information shared between my BUSINESS UNIT and this SUPPLIER (in support of SOURCING AND

SUPPLY PROPOSAL EVALUATION):

 

 

 

 

 

 

 

 

 

 

 

 

 

 

When using Traditional Methods (phone, fax, meetings, postal When using Linked Information Systems (EDI, MRP, ERP,
"'0”. etc.) 3: Strongly Strongly W “5) ‘55 Strongly Strongly
Agree Indifferent Disagree Agree Indifferent Disagree
a. Current I 2 3 4 5 6 7 f. Current I 2 3 4 5 6 7
b. Accurate I 2 3 4 5 6 7 g. Accurate l 2 3 4 S 6 7
c. Complete l 2 3 4 S 6 7 h. Complete l 2 3 4 5 6 7
d. Compatible I 2 3 4 5 6 7 i. Compatible | 2 3 4 S 6 7
e. Convenient to I 2 3 4 5 6 7 j. Convenient to I 2 3 4 5 6 7
access access
Strongly Strongly
Agree Indifferent Disagree
k. The sourcing and supply proposal evaluation process in place with this I 2 3 4 5 6 7
supplier has helped MY BUSINESS UNIT to make effective decisions
I. The sourcing and supply proposal evaluation process in place with this I 2 3 4 5 6 7
supplier has helped this SUPPLIER to make effective decisions
m. The sourcing and supply proposal evaluation process in place with this I 2 3 4 5 6 7
supplier has provided positive results for MY BUSINESS UNIT
n. The sourcing and supply proposal evaluation process in place with this I 2 3 4 5 6 7

supplier has provided positive results for this SUPPLIER

 

II. PART/MATERIAL STANDARDIZATION - Part/material standardization is used to reduce the number of unique
parts/materials maintained in the inventory system by using more standard and fewer unique parts/materials. Examples of
information sharing in support of part/material standardization would include (I) your business unit sharing materials lists with
the supplier and (2) the supplier evaluating these lists and making recommendations to your business unit about any possible
standard part substitutions. The information shared between my BUSINESS UNIT and this SUPPLIER (in support of

PART/MATERIAL STANDARDIZATION):

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

When using Traditional Methods alhone, fax, meetings, postal When using Linked Information Systems (EDI, MRP, ERP.
mail, etc.) ‘3: Strongly Strongly WWW. 616-) 13: Strongly Strongly
Agree Indifferent Disagree Agree Indifferent Disagree
a. Current I 2 3 4 5 6 7 f. Current I 2 3 4 5 6 7
b. Accurate I 2 3 4 5 6 7 g. Accurate l 2 3 4 S 6 7
c. Complete l 2 3 4 5 6 7 h. Complete I 2 3 4 5 6 7
d. Compatible I 2 3 4 5 6 7 i. Compatible l 2 3 4 S 6 7
e. Convenient to I 2 3 4 5 6 7 j. Convenient to I 2 3 4 5 6 7
access access
Strongly Strongly
Agree Indifferent Disagree
k. The part/material standardization process in place with this supplier I 2 3 4 5 6 7
has helped MY BUSINESS UNIT to make effective decisions
I. The part/material standardization process in place with this supplier I 2 3 4 3 (7 7
has helped this SUPPLIER to make effective decisions
In. The part/material standardization process in place with this supplier I 2 3 4 5 6 7
has provided positive results for MY BUSINESS UNIT
n. The part/material standardization process in place with this supplier I 3 3 4 S 6 7

has provided positive results for this SUPPLIER

138

I2. SUPPLIER SCHEDULING — The supplier scheduling process controls the releases of orders through MRP (or other) and
ensures communications of priorities, needs. and quantities between the buying organization's production or operations
management system and suppliers. Examples of information sharing in support of supplier scheduling include the sharing of
information related to order date, quantity ordered, required due date. shipoto-Iocation, item identification, key contact person and
so forth. The information shared between my BUSINESS UNIT and this SUPPLIER (in support of SUPPLIER

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SCHEDULING):
When using Traditional Methods (phone, fax, meetings, postal When using Linked Information Systems (EDI, MRP, ERP,
mail. “GI 1‘: Strongly Strongly WWWv etc.) 1‘: Strongly Strongly
Agree Indifferent Disagree Agree Indifferent Disagree
a Current I 2 3 4 5 6 7 f. Current I 2 3 4 5 6 7
b. Accurate I 2 3 4 5 6 7 g. Accurate I 2 3 4 5 6 7
c. Complete l 2 3 4 5 6 7 h. Complete I 2 3 4 S 6 7
d. Compatible I 2 3 4 S 6 7 i. Compatible I 2 3 4 5 6 7
e. Convenient to I 2 3 4 S 6 7 j. Convenient to I 2 3 4 5 6 7
access access
Strongly Strongly
Agree Indifferent Disagree
k. The supplier scheduling process in place with this supplier has helped I 2 3 4 5 6 7
MY BUSINESS UNIT to make effective decisions
I. The supplier scheduling process in place with this supplier has helped I 2 3 4 5 6 7
this SUPPLIER to make effective decisions
at. The supplier scheduling procels in place with this supplier has I 2 3 4 5 6 7
provided positive results for MY BUSINESS UNIT
n. The supplier scheduling process in place with this supplier has I 2 3 4 5 6 7

provided positive results for this SUPPLIER

 

I3. JOINT GOAUI‘ARG ET SETTING - Joint goal/target setting ensures that there are mutually acceptable performance targets
that are rooted in common/aligned metrics. An example of information sharing in support of joint goal/target setting includes
when your business unit and a supplier share information when establishing acceptable purchased-product quality levels (Cpk,
ppm, etc.). responsiveness, on-time delivery, cost improvements, etc. The information shared between my BUSINESS UNIT
and this SUPPLIER (in support of JOINT GOAUI‘ARG ET SETTING):

 

 

 

 

 

 

 

 

 

 

 

 

 

 

When using Traditional Methods ethanol“. meetings postal When using Linked Information Systems (EDI, MRP, ERP,
mail, etc.) 13' Strongly Strongly ' etc.) is: Strongly Strongly
Agree Indifferent Disagree Agree Indifferent Disagree
a. Current I 2 3 4 S 6 7 f. Current I 2 3 4 S 6 7
b. Accurate I 2 3 4 5 6 7 g. Accurate I 2 3 4 5 6 7
c. Complete I 2 3 4 5 6 7 h. Complete I 2 3 4 5 6 7
d. Compatible I 2 3 4 5 6 7 i. Compatible l 2 3 4 S 6 7
e. Convenient to I 2 3 4 5 6 7 j. Convenient to I 2 3 4 5 6 7
access access
Strongly Strongly
Agree Indifferent Disagree

 

 

k. The joint goal/target setting process in place with this supplier has
helped MY BUSINESS UNIT to make effective decisions

I The joint goal/target setting process in place with this supplier has
helped this SUPPLIER to make effective decisions

m. The joint goal/target setting process in place with this supplier has
provided positive results for MY BUSINESS UNIT

n. The joint goal/target setting process in place with this supplier has
provided positive results for this SUPPLIER

139

I

2 3 4 S 6 7

IN)

I~J

b)

b.)

'JI

4 5 6 7

4 5 6 7

SECTION III: RELA TIONSHIP CHARA C TERIS TI CS

The following questions ask you about the RELATIONSHIP between your BUSINESS UNIT and the selected supplier.

#8335333???

SECTION IV: UNCER TAIN TY IN YOUR S UPPL Y ENVIRONMENT

The following questions ask you about the UNCERTAINTI’ in your SUPPLY ENVIRONMENT.

I think the people at this supplier firm tell the truth in negotiations

I think that this supplier meets its obligations to our department

In my opinion this supplier is reliable

I think that the people in this supplier firm succeed by stepping on other people
I feel that this supplier tries to get the upper hand

I think that this supplier takes advantage of our problems

I feel that this supplier negotiates honestly

I feel that the people at this supplier will keep their word

I think that this supplier does not mislead us

I feel that this supplier does not try to get out of commitments

I feel that this supplier negotiates joint expectations fairly

I feel that this supplier takes advantage of people who are vulnerable
We are dependent on this supplier

This supplier would be difficult to replace

This supplier would be costly to loose

This supplier is dependent on us

This supplier would find it difficult to replace us

This supplier would find it costly to lose us

The supply of material to my firm has been stable

The supply of material to my firm has been predictable

The price of material to my firm has been stable

The price of material to my firm has been predictable

There are many qualified suppliers from which to choose
Technology is relatively stable in my industry

Customer demand is relatively stable in my industry

My finn's product mix generally stays about the same

Our customers don't demand changes in technology very frequently
My industry is characterized by fierce and changing competition

140

Strongly
Agree

I
I
l
I
l
l
l
I
l
I
I
I
I
l
I
l
l

Strongly
Agree

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IJNNNI‘QNNNNN

Neither

Agree Nor

Disagree
4

wwwuwuwuwwwuwwwwww
b5bbbbbhk§bfibbhbb
MMMMMMMMMMMMMMMMMM

Neither

Agree Nor

Disagree
4

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MMMMMMMMMM

OQO‘ONO‘O‘O\O\ONO\O\O\O\O\OO\O~O\

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Strongly
Disagree
7

QQNQQNNNQNQQQQQQQ

Strongly
Disagree
7

\J\3\I\J\I\J\I\I\I

SECTION V: PERFORMANCE

Please indicate the degree to which you feel that your OVERALL BUSINESS UNIT‘S PERFORMANCE has changed over the
past two years;

Neither

Much Better Nor Much

Better Worse Worse
42. Return on investment (ROI) I 2 3 4 5 6 7
43. Return on equity (ROE) I 2 3 4 5 6 7
44. Profit margin l 2 3 4 S 6 7
45. Cash-to-cash cycle time I 2 3 4 5 6 7
46. External customer service levels I 2 3 4 S 6 7
47. Total inventory turnover rate I 2 3 4 5 6 7
48. Supplier on-t‘ane delivery I 2 3 4 5 6 7
49. Purchase price reduction I 2 3 4 5 6 7
50. Purchase price reduction compared to market I 2 3 4 S 6 7
SI. Total cost reaction I 2 3 4 5 6 7
52. Supplier quaI'ay performance I 2 3 4 5 6 7
53. Supplier responsiveness I 2 3 4 5 6 7

Much Better No Change Much Worse

54. How much have your OVERALL supply chain processes improved/worsened I 2 3 4 5 6 7

over the past two years? (check one)

Please indicate the degree to which you feel that each of the processes listed below has improved over the past two years:

Neither
Much Better Nor Much
Better Worse Worse
55. Forecasting ad Inventory Positioning I 2 3 4 5 6 7
56. Inventory Visibility I 2 3 4 S 6 7
57. Capacity Flaming I 2 3 4 5 6 7
58. Post Supplier Selection Performance Evaluation/Feedback and Conformance I 2 3 4 5 6 7
59. Sourcing and Supply Proposal Evaluation 1 2 3 4 5 6 7
60. Part/Material Standardization l 2 3 4 5 6 7
61. Supplier Scheduling l 2 3 4 5 6 7
62. Joint Goal/Target Setting I 2 3 4 S 6 7
Neither
Much Better Nor Much
Better Worse Worse
63. How much have your business unit‘s OVERALL joint planning and decision I 2 3 4 S 6 7
making processes changed over the past two years? (check one)
64. How much have your supplier’s OVERALL joint planning and decision making I 2 3 4 S 6 7
processes changed over the past two years? (check one)
65. To what extent have your business unit's and your supplier's joint planning and I 2 3 4 5 6 7

decision making processes jointly improved over the past two years? (check one)

66. By what degree have your supply chain processes improved your busmess unit‘s profitability over the past two years (as tl “rt. of
profits)? (check one)

 

C] < 0% U l l% - 15% C] 26% - 30%
D Io/o - 59/0 U [6°41 - 209/0 D 3I°/o - 350/0
D 60/0 - 109/0 0 210/0 - 25°26 D > 3500
Thank you! '
L We expect that the results ofthis research will be available to you in Spring. I990

 

 

141

'fi.

 

Appendix F: Non-Response Bias

142

Tables in this appendix contain the probability values associated with the null
hypothesis that there is no difference (on each given parameter) between the first twenty
cases received and the last twenty cases received. Probability values less than .05

indicate that the null hypothesis Should be rejected (95% confidence).

Table 25: Forecasting and Inventory Positioning - N on-
Response Bias

 

 

 

Currency Accuracy Completeness
Non-IOS Enabled 0.74 0.78 0.39
IOS Enabled 0.59 0.77 0.56
Effective Decisions 0.44
Positive Results 0.44
Inventory Turnover 1.00
On-Time Delivery 0.77
Responsiveness 0.66

 

 

 

Table 26: Inventory Visibility - Non-Response Bias

 

 

 

Currency Accuracy Completeness
Non-IOS Enabled 0.80 0.75 0.78
IOS Enabled 0.54 0.45 0.45
Effective Decisions 0.33
Positive Results 0.62
On-Time Delivery 0.85
Responsiveness 0.50

 

 

 

143

Table 27 : Capacity Planning — Non-Response Bias

 

 

 

 

Currency Accuracy Completeness
Non-IOS Enabled 0.86 0.92 0.67
IOS Enabled 0.72 0.69 0.85
Effective Decisions 0.85
Positive Results 0.84
ROI 0.83
ROE 0.91
Profit Margin 0.61

 

 

Table 28: Post Supplier Selection Performance Evaluation/Feedback and
Conformance — Non-Response Bias

 

 

 

Currency Accuracy Completeness
Non-IOS Enabled 1.00 0.67 0.50
IOS Enabled 0.09 0.16 0.13
Effective Decisions 0.07
Positive Results 0.24
On-Time Delivery 1.00
Total Cost Reduction 0.88
Supplier Quality Performance 0.73

 

 

 

Table 29: Sourcing and Supply Proposal Evaluation — Non-Response Bias

 

 

Currency [Accuracy [Completeness
Non-IOS Enabled 0.24 0.91 0.68
IOS Enabled 0.03 0.02 0.03
Effective Decisions 0.50
Positive Results 0.72
Purchase Price Reduction 0.91
Purchase Price Reduction 0.04
Compared to Market
Total Cost Reduction 0.76

 

 

 

 

144

Table 30: Part/Material Standardization — Non-Response Bias

 

Currency Accuracy Completeness

 

 

Non-IOS Enabled
IOS Enabled

Effective Decisions
Positive Results

Total Inventory Turnover
Supplier On-Time Delivery
Purchase Price Reduction

 

0.05
0.36

0.00
0.02

0.74
0.88
0.23

0.32 0.45
0.17 0.38

 

Table 31: Supplier Scheduling — Non-Response Bias

 

Currency Accuracy Completeness

 

 

Non-IOS Enabled
IOS Enabled

Effective Decisions
Positive Results

Profit Margin
Cash to Cash Cycle Time
Supplier On-Time Delivery

 

0.79
0.29

0.11
0.19

0.41
0.46
0.87

0.66 0.61
0.38 0.78

 

Table 32: Joint Goal/'1‘ arget Setting — Non-Response Bias

 

Currency Accuracy Completeness

 

 

Non-IOS Enabled
IOS Enabled

Effective Decisions
Positive Results

Purchase Price Reduction
Total Cost Reduction

 

0.70
0.02

0.04
0.44

0.62
0.89

0.38 0.75
0.02 0.01

 

145

 

 

 

Appendix G: Confirmatory Factor Analysis

146

Forecasting and Inventory Positioning

Table 33: CFA - Forecasting & Inventory Positioning

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manifest Latent Standardized Z-Value Statistical
Variable Variable 9t Significance
Current N-IOS 0.834 3.417 P<.01
Accurate N-IOS 0.961 3 .452 P<.01
Complete N-IOS 0.888 3.413 P<.01
Current IOS 0.870 6.644 P<.01
Accurate IOS 0.958 6.933 P<.01
Complete IOS 0.945 6.953 P<.01
Effective J PDM 0.921 7.083 P<.01
Decisions
Positive JPDM 0.947 7.349 P<.01
Results
Inventory Performance 0.470 3.321 P<.01
Turnover
On-Time Performance 0.81 7 4.510 P<.01
Delivery
Responsiveness Performance 0.589 3.666 P<.01

 

 

Table 34: CFA - Forecasting & Inventory Positioning - Fit Statistics

 

 

 

 

 

 

 

 

Chi-Square = 35.01

Degrees of Freedom = 37

P = 0.56263

BENTLER-BONETT NORMED FIT INDEX = 0.843
BENTLER-BONETT NONNORMED FIT INDEX = 1.018
COMPARATIVE FIT INDEX = 1.000

 

 

Table 35: CFA - Forecasting & Inventory Positioning — Measurement Error
Correlations

 

 

 

 

 

 

IOS — Enabled
m _U Current Accurate Complete
9 2 Current 0.190 (p<0.1 )
S ‘3 Accurate 0.036 (p=n.s.)
Z "4 Complete 0.430 (p<.01)

 

 

 

 

147

 

Inventorv Visibilitv

Table 36: CFA - Inventory Visibility

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manifest Latent Standardized Z—Value Statistical
Variable Variable x Significance
Current N-IOS 0.872 3.267 P<.01
Accurate N-IOS 0.959 3.275 P<.01
Complete N-IOS 0.896 3.222 P<.01
Current IOS 0.933 5.783 P<.01
Accurate IOS 0.960 5.779 P<.01
Complete IOS 0.964 5.886 P<.01
Effective JPDM 0.952 7.714 P<.01
Decisions Buying Co.
Positive J PDM 0.965 7.834 P<.01
Results Buying Co.
On-Time Performance 0.798 4.157 P<.01
Delivery
Responsiveness Performance 0.605 3. 1 3 5 P<.01
Table 37: CFA - Inventory Visibility - Fit Statistics
Chi-Square = 24.696
Degrees of Freedom = 28
P = 0.64435
BENTLER-BONETT NORMED FIT INDEX = 0.885
BENTLER-BONETT NONNORMED FIT INDEX = 1.031
COMPARATIVE FIT INDEX = 1.000

 

 

Table 38: CFA - Inventory Visibility — Measurement Error Correlations

 

 

 

 

 

 

 

IOS — Enabled
m '6 Current Accurate Complete
8.? 2 Current 0.068 (p=n.s.)
8 "E Accurate 0.201 (p=n.s.)
Z L“ Complete 0.199 (p=n.s.)

 

 

148

 

 

 

Capacig Planning

Table 39: CFA — Capacity Planning

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manifest Latent Standardized Z-Value Statistical
Variable Variable 2» Significance
Current N-IOS 0.892 5.397 P<.01
Accurate N-IOS 0.995 5.529 P<.01
Complete N-IOS 0.959 5.434 P<.01
Current IOS 0.956 6.366 P<.01
Accurate IOS 0.974 6.401 P<.01
Complete IOS 0.987 6.422 P<.01
Effective JPDM 0.959 8.364 P<.01
Decisions Buying Co.
Positive JPDM 0.958 8.495 P<.01
Results Buying Co.
ROI Performance 0.977 2.416 P<.01
ROE Performance 0.944 2.405
Profit Margin Performance 0.796 2.371 P<.01
Table 40: CFA - Capacity Planning - Fit Statistics
Chi-Square = 27.445
Degrees of Freedom = 37
P = 0.87380
BENTLER-BONETT NORMED FIT INDEX = 0.895
BENTLER-BONETT NONNORMED FIT INDEX = 1.069
COMPARATIVE FIT INDEX = 1.000

 

 

Table 41: CFA — Capacity Planning — Measurement Error Correlations

IOS — Enabled

 

 

 

 

 

 

 

 

Current Accurate Complete
(A 1: Current 0.317 (p<.01)
g % Accurate -0.127 (p=n.s.)
8 2 Complete 0.518
Z W (p<.01)

 

149

 

 

 

Post Supplier Selection Performance Eflluation/Feedback and Conformance

Table 42: CFA — Post Supplier Selection Performance Evaluation/Feedback and
Conformance

 

 

 

 

 

 

 

 

 

 

 

 

 

Manifest Latent Standardized Z-Value Statistical
Variable Variable A Significance
Current N-IOS 0.926 2.525 P<.01
Accurate N-IOS 0.971 2.532 P<.01
Complete N-IOS 0.975 2.526 P<.01
Current IOS 0.951 2.482 P<.01
Accurate IOS 0.985 2.488 P<.01
Complete IOS 0.980 2.475 P<.01
Effective JPDM 0.945 3.450 P<.01
Decisions Buying Co.
Positive JPDM 0.970 3.544 P<.01
Results Buying Co.
On—Time Performance 0.683 2. 1 84 P<.05
Delivery
Total Cost Performance 0.586 2.090 P<.05
Reduction
Supplier Quality Performance 0.719 2.246 P<.05
Performance

 

 

 

 

 

 

Table 43: CFA — Post Supplier Selection Performance Evaluation/Feedback and
Conformance - Fit Statistics

 

 

 

 

 

 

 

Chi-Square = 42.622

Degrees of Freedom = 37

P = 0.24072

BENTLER-BONETT NORMED FIT INDEX = 0.816
BENTLER-BONETT NONNORMED FIT INDEX = 0.952
COMPARATIVE FIT INDEX = 0.968

 

 

Table 44: CFA — Post Supplier Selection Performance Evaluation/Feedback and
Conformance — Measurement Error Correlations

 

 

 

 

 

IOS — Enabled
m 1: Current Accurate Complete
9 .2 Current 0.405 (p<.01)
5 “Pg Accurate -0531 (p<.01)
2 m Complete 0.422 (p<.l)

 

 

 

 

 

150

Table 45: CFA — Sourcing and Supply Proposal Evaluation

Sourcing and Supply Proposal Evaluation

 

 

 

 

 

 

 

 

 

 

 

 

 

Manifest Latent Standardized Z-Value Statistical
Variable Variable A Significance
Current N-IOS 0.907 2.571 P<.01
Accurate N-IOS 0.963 2.541 P<.01
Complete N-IOS 0.959 2.565 P<.01
Current IOS 0.969 2.970 P<.01
Accurate IOS 0.985 2.957 P<.01
Complete IOS 0.966 2.959 P<.01
Effective JPDM 0.828 3.808 P<.01
Decisions Buying Co.
Positive J PDM 0.960 4.340 P<.01
Results Buying Co.
Purchase Price Performance 0.870 3.127 P<.01
Reduction
Purchase Price Performance 0.836 3.049 P<.01
Reduction —
Compared to
Market
Total Cost Performance 0.833 3.014 P<.01
Reduction

 

 

 

 

 

Table 46: CFA — Sourcing and Supply Proposal Evaluation - Fit Statistics

 

 

 

 

 

 

 

 

Chi-Square = 35.832

Degrees of Freedom = 37

P = 0.52369

BENTLER-BONETT NORMED FIT INDEX = 0.839
BENTLER-BONETT NONNORMED FIT INDEX = 1.010
COMPARATIVE FIT INDEX = 1.000

 

 

Table 47: CFA — Sourcing and Supply Proposal Evaluation - Measurement Error
Correlations

 

 

 

 

 

 

 

 

IOS — Enabled
m '0 Current Accurate Complete
9 .2 Current 0.360 (p<.01)
8 "g Accurate -0.334 (p=n.s.)
Z ”J Complete 0.141 (p=n.s.)

 

151

 

Table 48: CFA - Part/Material Standardization

Part/Material Standardization

 

 

 

 

 

 

 

 

 

 

 

 

 

Manifest Latent Standardized Z-Value Statistical
Variable Variable 1 Significance
Current N-IOS 0.913 4.209 P<.01
Accurate N-IOS 0.975 4.189 P<.01
Complete N-IOS 0.955 4.177 P<.01
Current IOS 0.956 4.326 P<.01
Accurate 108 0.977 4.366 P<.01
Complete IOS 0.950 4.328 P<.01
Effective J PDM 0.956 6.153 P<.01
Decisions Buying Co.
Positive JPDM 0.982 6.221 P<.01
Results Buying Co.
Total Inventory Performance 0.665 1.426 P<.2
Turnover
Supplier On- Performance 0.726 1.427 P<.2
Time Delivery
Purchase Price Performance 0.378 1.349 P<.2
Reduction

 

 

 

 

 

 

 

Table 49: CFA - Part/Material Standardization - Fit Statistics

 

 

 

 

 

Chi-Square = 34.738

Degrees of Freedom = 37

P = 0.57556

BENTLER-BONETT NORMED FIT INDEX = 0.850
BENTLER-BONETT NONNORMED FIT INDEX = 1.019
COMPARATIVE F IT INDEX = 1.000

 

 

 

Table 50: CFA — Part/Material Standardization — Measurement Error Correlations

 

 

 

 

 

 

IOS — Enabled
m 1: Current Accurate Complete
9 2 Current 0.334 (p<.01)
8 '5 Accurate 0.271 (p=n.s.)
2 F” Complete 0.359 (p<.05)

 

 

 

 

152

Table 51: CFA — Supplier Scheduling

Supplier Scheduling

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manifest Latent Standardized Z-Value Statistical
Variable Variable 1, Significance
Current N-IOS 0.922 1 .920 P<.1
Accurate N-IOS 0.979 1 .933 P<.1
Complete N-IOS 0.957 1.91 1 P<.1
Current IOS 0.91 1 3.214 P<.01
Accurate IOS 0.968 3.237 P<.01
Complete IOS 0.961 3.257 P<.01
Effective JPDM 0.943 3.933 P<.01
Decisions Buying Co.
Positive JPDM 0.955 3.972 P<.01
Results Buying Co.
Profit Margin Performance 0.711 2.269 P<.05
Cash to Cash Performance 0.796 2.357 P<.01
Cycle Time
Supplier On- Performance 0.442 2.065 P<.05
Time Delivery

 

 

Table 52: CFA — Supplier Scheduling - Fit Statistics

 

 

 

 

 

 

Chi-Square = 36.387

Degrees of Freedom = 37

P = 0.49757

BENTLER-BONETT NORMED FIT INDEX = 0.835
BENTLER-BONETT NONNORMED FIT INDEX = 1.005
COMPARATIVE FIT INDEX = 1.000

 

 

Table 53: CFA — Supplier Scheduling - Measurement Error Correlations

 

 

IOS — Enabled

 

 

 

 

 

 

 

 

m Current Accurate Complete

CH? 3 Current -0.62 (p=n.s.)

8 E Accurate -0.078 (p=n.s.)

Z ”J Complete 0.69 (p=n.s.)

 

153

 

Joint Goal/Target Setting

Table 54: CFA - Joint Goal/Target Setting

 

 

 

 

 

 

 

 

 

 

 

 

 

Manifest Latent Standardized Z-Value Statistical
Variable Variable 1 Significance
Current N-IOS 0.926 6.824 P<.01
Accurate N-IOS 0.964 6.769 P<.01
Complete N-IOS 0.944 6.679 P<.01
Current IOS 0.985 4.539 P<.01
Accurate lOS 0.993 4.549 P<.01
Complete IOS 0.961 4.521 P<.01
Effective J PDM 0.978 8.448 P<.01
Decisions Buying Co.
Positive J PDM 0.937 8.012 P<.01
Results Buying Co.
Purchase Price Performance 0.807 3.225 P<.01
Reduction
Total Cost Performance 0.785 3.056 P<.01
Reduction

 

 

 

 

 

 

 

Table 55: CFA — Joint Goal/Target Setting - Fit Statistics

 

 

 

 

 

 

 

Chi-Square = 31.439

Degrees of Freedom = 28

P = 0.29793

BENTLER-BONETT NORMED FIT INDEX = 0.864
BENTLER-BONETT NONNORMED FIT INDEX = 0.970
COMPARATIVE FIT INDEX = 0.981

 

 

Table 56: CFA — Joint Goal/Target Setting — Measurement Error Correlations

 

 

 

 

 

 

IOS — Enabled
m 1: Current Accurate Complete
9.? 2 Current 0.563 (p<.01)
8 E Accurate -0.461 Q)<.05)
Z L” Complete 0.393 (p<.01)

 

 

 

 

154

 

Appendix H: Structural Equation Models

155

Forecasting and Inventory Positioning

 

 

 

 

 

 

 

 

543—91 Currency

 

 

 

 

 

 

 

‘5' ' Completm

 

 

 

022

 

439—. Currency

 

 

284—0 Accuracy ‘
430

 

 

 

327fi Completeness

 

 

 

 

 

 

 

 

 

Figure 21: SEM - Forecasting & Inventory Positioning

Table 57: SEM - Forecasting & Inventory Positioning - Fit Statistics

 

 

 

 

 

 

Chi-Square = 35.518

Degrees of Freedom = 35

P = .53970

BENTLER-BONETT NORMED FIT INDEX = 0.850
BENTLER-BONETT NONNORMED FIT INDEX = 1.014
COMPARATIVE FIT INDEX = 1.000

 

 

 

156

481—‘9

284-—-—ol

201

361—9

200

266—0

Inventory Visibility

 

Currency

 

 

Accuracy

 

Non-IOS Enabled ‘ ‘
lnformaion Flow 3,
A

 

 

Completeness

 

 

     

 

   

Joint Planning
and Decision Making

 

 

 

  
 

IOS Enabled

 

 

 

 

 

 

 

 

 

 

 

ACCW)’ Information Flow -'
\v‘
C omvk'tms .991 Effective Positive
Decisions R650"!
301 .268

Figure 22: SEM - Inventory Visibility

Table 58: SEM — Inventory Visibility — Fit Statistics

 

 

806 578
l I
2?
a 29
2. 2' j
i 3 i
9

 

 

 

 

 

 

 
 
 
   
 

 

 

 

 

 

 

 

Chi-Square = 23.457

Degrees of Freedom 26

= 0.60701

p =

BENTLER-BONETT NORMED FIT INDEX = 0.890
BENTLER-BONETT NONNORMED FIT INDEX = 1.026
COMPARATIVE FIT INDEX = 1.000

 

157

 

Cgacig Planning

 

 

 

 

 

 

 

 

 

 

451—-¢ Currency

 

 

 

   

332

 

 
     

.994(p<.0|) Non-IOSEnabled ' ' '

Informuion Flow 30
f

 

 

233—. Completeness

 

030

 

293—o Currency

 

 

226——0 Accuracy
520

 

 

 

 

'59—’ Completeness

 

 

 

 

 

 

 

 

Figure 23: SEM - Capacity Planning

Table 59: SEM — Capacity Planning - Fit Statistics

 

 

 

 

 

 

 

Chi-Square = 27.000

Degrees of Freedom = 35

P = 0.83129

BENTLER-BONETT NORMED FIT INDEX = 0.896
BENTLER-BONETT NONNORMED FIT INDEX = 1.061
COMPARATIVE FIT INDEX = 1.000

 

 

158

Post Supplier Selection Performance Evaluation/Feedback and Conformance

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

.102 .785 .730
I I
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303-—-. Cunency

 

 

 

 

 

 

 

 

 

.0292“
l72-—-9 luxunny ‘ , ‘i
412
979(p<.01)
t?"
'96—, CW 9“ Effective Positive
Decisions w:

 

 

 

 

 

 

 

l l

352 .202

.‘

Figure 24: SEM - Post Supplier Selection Performance Evaluation/Feedback and

Conformance

Table 60: SEM — Post Supplier Selection Performance Evaluation/Feedback and

Conformance — Fit Statistics

 

 

 

 

 

 

 

Chi-Square = 40.701

Degrees of Freedom = 35

P = 0.23383

BENTLER-BONETT NORMED FIT INDEX = 0.824
BENTLER-BONETT NONNORMED FIT INDEX = 0.949
COMPARATIVE FIT INDEX = 0.968

 

159

 

Sourcing and Supply Promsal Evaluation

.546

§
‘3?

 

 

tum
Wit
aqua new

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

411——9 Curency 8
3
358 6 2
266—. Accuracy - -_ ’a R g
Tz 0900,; 0’1 3 a?
or)» y
232—" Completeness '1
Ionn‘ Planing 313( .s.)
-333 1"“
andl: . .0“ M. Perform-ice

 

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l

 

 

 

 

 

 

 

 

 

 

 

 

 

 

5 07“”)
0" -- 929
,174—-0 Accuracy ‘ ~ 7’
, 4
l ' 960(p<0l)
258—’ Canpleteness Positive
Mitt!!! Results
560 280

Figure 25: SEM: Sourcing and Supply Proposal Evaluation

Table 61: SEM - Sourcing and Supply Proposal Evaluation — Fit Statistics

 

 

 

 

 

 

Chi-Square = 34.900

Degrees of Freedom = 35

P = 0.47298

BENTLER-BONETT NORMED FIT INDEX = 0.843
BENTLER-BONETT NONNORMED FIT INDEX = 1.001
COMPARATIVE FIT INDEX = 1.000

 

 

 

160

Part/Material Standardization

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I I I
ti 22. g;-
Q'g 3 i 5
333 J 5
_ ‘32 a:
145 .0280hn'3} ~ 0” 3 60
2‘70 “mfg "59 (9'7”) Perform-Ice
293—-v Currency ‘ Q I
V4.5) '
214—0 Accuracy , ~ '06“ 982
36' 983 (p<01)
3"—’ Compielatess Positive
Decisions Results
2'93 185
Figure 26: SEM - Part/Material Standardization
Table 62: SEM - Part/Material Standardization — Fit Statistics
Chi-Square = 34.402
Degrees of Freedom = 35
P = 0.49678
BENTLER-BONETT NORMED FIT INDEX = 0.851
BENTLER-BONETT NONNORMED FIT INDEX = 1.005
COMPARATIVE FIT INDEX = 1.000

 

 

 

161

 

 

Supplier Scheduling

 

 

 

 

 

 

 

 

 

 

 

 

 

 

    

 

 

        

 

 

 

 

   
   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

397 629 677
I
:2:T :2
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. 202-—0 Accuracy $%_ é
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90—. Completeness ‘A
411—. CW ¢
45‘ I
IOS Enabled " \v’ 933
351-“ ACCWY ‘ Information Flow
073 ' 955(p<:on
273—. Completeness 96’ Effective Positive
Decisions Results
3L 297
Figure 27 : SEM - Supplier Scheduling
Table 63: SEM — Supplier Scheduling - Fit Statistics
Chi-Square = 34.945
Degrees of Freedom = 35
P = 0.47082
BENTLER-BONETT NORMED FIT INDEX = 0.842
BENTLER-BONETT NONNORMED FIT INDEX = 1.001
COMPARATIVE FIT INDEX = 1.000

 

 

 

162

 

Joint Goal/Target Setting

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

.645 534
I
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091’ $945) 9115
121—0 Accuracy ‘
388 936 (p<.01)
275—. CMW 9‘“ WA Effective Positive
Decisions Results
J10 .351
Figure 28: SEM - Joint Goal/Target Setting
Table 64: SEM - Joint Goal/Target Setting — Fit Statistics
Chi-Square = 27.442
Degrees of Freedom = 26
P = 0.38647
BENTLER-BONETT NORMED FIT INDEX = 0.881
BENTLER-BONETT NONNORMED FIT INDEX = 0.987
COMPARATIVE FIT INDEX = 0.992

 

 

 

163

 

 

Appendix 1: Descriptive Statistics

164

Table 65: Descriptive Statistics - Forecasting and

Inventory Positioning

 

Item Mean Std. Dev. Skewness Kurtosisi
IOS Currency 3.06 1.66 0.79 -0.20
IOS Accuracy 3.03 1.62 0.80 -0.07
lOS Completeness 3.13 1.62 0.71 .040
N-lOS-Currency 2.33 1 .64 1 .53 1 .47
N-IOS-Accuracy 2.53 1.54 1.25 1.12
N-lOS-Completeness 2.65 1.54 1.19 0.93
Effective Decisions 2.64 1.46 1.13 0.81

Positive Results 2.42 1.42 1.34 1.62
Inventory Turnover 3.07 1.21 0.43 -0.15
On-Time Delivery 2.87 1.03 0.44 0.24
Responsiveness 2.67 0.99 0.50 -0.33

 

 

 

Table 66: Descriptive Statistics - Inventory Visibility

 

Item Mean Std. Dey._ Skewness Kurtosis
IOS Currency 3.73 1.77 0.28 -1.07
108 Accuracy 3.64 1.73 0.41 -0.97
IOS Completeness 3.80 1.66 0.27 -0.85
N-lOS-Currency 2.57 1 .61 1 .42 1 .24
N-lOS-Accuracy 2.69 1 .59 1 .28 0.95
N-lOS-Completeness 2.78 1 .57 1 .22 0.96
Effective Decisions 2.88 1.56 0.93 0.40
Positive Results 2.81 1.53 0.92 0.32
Inventory Turnover 2.89 1.03 0.40 0.24
Responsiveness 2.67 0.99 0.50 -0.30

 

 

 

Table 67 : Descriptive Statistics - Capacity Planning

 

 

 

 

Item Mean Std. Dev. Skewness Kurtosis
lOS Currency 3.62 1.62 0.41 -0.54
IOS Accuracy 3.62 1.54 0.39 -0.31
lOS Completeness 3.68 1.57 0.37 -0.44
N-lOS-Currency 3.03 1 .63 0.89 0.15
N-lOS-Accuracy 3.1 1 1 .62 0.80 0.06
N-lOS-Completeness 3.13 1 .56 0.90 0.34
Effective Decisions 3.02 1.45 0.86 0.48
Positive Results 3.08 1.49 0.74 0.39
Inventory Turnover 3.12 1.24 0.31 -0.31
On-time Delivery 3.12 1.25 0.24 -0.51
Responsiveness 3.48 1 .50 0.32 -0.71

 

165

 

 

 

Table 68: Descriptive Statistics - Post Supplier Selection
Performance Evaluation/Feedback and Conformance

 

 

 

lit?!“ Mean Std. Dev. Skewness Kurtosis
lOS Currency 3.21 1.55 0.63 -0.36
lOS Accuracy 3.14 1.52 0.72 -0.17
IOS Completeness 3.30 1.61 0.59 -0.37
N-lOS-Currency 2.71 1 .58 1 .24 0.92
N-IOS-Accuracy 2.85 1 .57 1 .04 0.60
N-lOS-Completeness 2.92 1 .56 0.96 0.46
Effective Decisions 2.50 1.21 1.25 2.50
Positive Results 2.41 1.18 1.17 2.15
On-time Delivery 2.82 0.97 0.37 0.30
Cost Reduction 2.64 1.02 0.62 0.40
Quality 2.82 0.95 0.42 0.16

 

 

 

 

Table 69: Descriptive Statistics - Sourcing and Supply
Proposal Evaluation

 

 

 

Item Mean Std. Dev. Skewness Kurtosis
IOS Currency 2.53 1.36 1.07 "1705‘
IOS Accuracy 2.53 1.36 1.22 1.41
IOS Completeness 2.60 1.40 0.95 0.59
N-lOS—Currency 2.43 1.40 1 .28 1 .76
N-lOS-Accuracy 2.52 1 .41 1.28 1 .76
N-lOS-Completeness 2.59 1 .41 1 .20 1 .60
Effective Decisions 2.16 0.89 0.55 -0.02
Positive Results 2.14 0.88 0.56 0.09
On-time Delivery 2.74 1.14 0.70 0.89
Cost Reduction 2.91 1.05 0.27 034
Quality 2.62 1.03 0.62 0.39

 

 

 

 

Table 70: Descriptive Statistics - Part/Material
Standardization

 

Item Mean Std. Dev. Skewness Kurtosis
IOS Currency 3.31 1.56 0.51 -0.44
IOS Accuracy 3.28 1.55 0.58 -0.12
IOS Completeness 3.45 1.65 0.43 -0.54
N-lOS-Currency 2.98 1.56 0.81 0.32
N-IOS-Accuracy 3.00 1.58 0.81 0.22
N-lOS-Completeness 3.17 1.51 0.71 0.24
Effective Decisions 2.97 1.40 0.57 0.15
Positive Results 2.96 1.41 0.49 -0.01
Inventory Turnover 3.14 1.23 0.35 -0.32
On-time Delivery 2.86 0.99 0.29 0.21
Price Reduction 2.73 1.14 0.69 0.94

 

 

 

 

166

Table 71: Descriptive Statistics - Supplier Scheduling

 

Item Mean Std. Dev. Skewness Kurtosis
IOS Currency 3.12 1.62 0.62 -0.40
IOS Accuracy 3.15 1.61 0.81 0.08
IOS Completeness 3.15 1.50 0.62 -0.13
N-lOS-Currency 2.14 1 .28 1.60 2.86
N-IOS-Accuracy 2.28 1 .32 1.55 2.72
N-lOS-Completeness 2.34 1 .27 1.46 2.48
Effective Decisions 2.28 1.02 0.86 0.69
Positive Results 2.30 1.07 0.77 0.41
Profit Margin 3.41 1.49 0.36 -0.65
Cash-Cash Cycle Time 3.19 1.18 0.31 0.09
On-Time Delivery 2.82 0.96 0.32 0.32

 

 

 

 

Table 72: Descriptive Statistics - Joint Goal/Target Setting

 

Item Mean Std. Dev. Skewness Kurtosis
IOS Currency 2.90 1.41 0.76 0.06
IOS Accuracy 2.86 1.45 0.69 -0.11
IOS Completeness 3.01 1.45 0.57 -0.23
N-lOS-Currency 2.85 1 .63 0.97 0.33
N-lOS-Accuracy 2.88 1 .64 0.92 0.21
N-IOS-Completeness 2.98 1 .63 0.95 0.40
Effective Decisions 2.43 1.19 1.22 2.40
Positive Results 2.52 1.23 1.01 1.65
Price Reduction 2.74 1.13 0.73 0.97
Total Cost 2.65 1.01 0.64 0.42

 

 

 

 

167

Appendix J: Post Hoc Analysis

168

 

 

Note: shading in the following tables indicates statistical significance at the p<.1 level.

Table 73: Forecasting and Inventory Positioning — Associations of
Joint Planning and Decision Making Outcomes and Firm

Performance Dimensions

 

 

 

 

 

r p n
Supplier on-time delivery 0.35 0.00 129
Supplier responsiveness 0.26 0.00 129
Total inventory turnover rate 0.22 0.01 129
Cash-to-cash cycle time 0.19 0.03 129
Purchase price reduction compared to market 0.15 0.08 129
Supplier quality performance 0.14 0.11 129
Profit margin 0.11 0.23 129
Purchase price reduction 0.10 0.24 129
External customer service levels 0.10 0.26 129
Return on equity (ROE) 0.10 0.27 129
Total cost reduction 0.09 0.31 129
Return on investment(ROl) 0.08 0.38 129

 

Table 74: Inventory Visibility - Associations of Joint Planning and
Decision Making Outcomes and Firm Performance Dimensions

 

 

r p n
Supplier on-time delivery 0.37 0.00 131
Supplier responsiveness 0.29 0.00 131
Purchase price reduction compared to market 0.22 0.01 131
Total inventory turnover rate 0.22 0.01 131
Return on equity (ROE) 0.19 0.03 131
Cash-to-cash cycle time 0.19 0.03 131
Purchase price reduction 0.17 0.05 131
Return of investment(ROl) 0.17 0.06 131
Profit margin 0.12 0.17 131
Supplier quality performance 0.12 0.18 131
External customer service levels 0.11 0.20 131
Total cost reduction 0.10 0.25 131

 

 

 

 

169

 

 

 

Table 75: Capacity Planning — Associations of Joint Planning and

Decision Making Outcomes and Firm Performance Dimensions

 

 

r p n
Total inventory turnover rate 0.25 0.00 122
Purchase price reduction compared to market 0.25 0.01 122
Supplier on-time delivery 0.23 0.01 122
Supplier responsiveness 0.22 0.01 122
Total cost reduction 0.22 0.01 122
Return of investment(ROI) 0.20 0.03 122
Profit margin 0.19 0.04 122
Return on equity (ROE) 0.19 0.04 122
Purchase price reduction 0.18 0.05 122
Cash-to-cash cycle time 0.12 0.17 122
Supplier quality performance 0.12 0.20 122
External customer service levels 0.01 0.94 122

 

 

 

 

Table 76: Post Supplier Selection Performance

Evaluation/Feedback and Conformance — Associations of Joint

Planning and Decision Making Outcomes and Firm Performance

 

 

 

Dimensions
r p n

Supplier responsiveness 0.29 0.00 117
Supplier on-time delivery 0.28 0.00 117
Purchase price reduction compared to market 0.23 0.01 117
Supplier quality performance 0.21 0.02 117
Return of investment(ROI) 0.18 0.05 117
Return on equity (ROE) 0.17 0.06 117
Total cost reduction 0.17 0.07 1 17
External customer service levels 0.17 0.07 1 17
Profit margin 0.15 0.11 117
Total inventory turnover rate 0.14 0.12 117
Purchase price reduction 0.12 0.19 117
Cash-to-cash cycle time 0.11 0.25 117

 

 

 

 

170

 

 

Table 77: Sourcing and Supply Proposal Evaluation - Associations
of Joint Planning and Decision Making Outcomes and Firm

Performance Dimensions

 

 

 

 

 

 

r p n
Total cost reduction 0.30 0.00 119
Purchase price reduction 0.29 0.00 119
Supplier on-time delivery 0.23 0.01 119
Purchase price reduction compared to market 0.19 0.04 119
Return on equity (ROE) 0.18 0.05 119
Supplier responsiveness 0.16 0.08 119
Return of investment(ROI) 0.16 0.09 119
Supplier quality performance 0.14 0.13 119
Cash-to-cash cycle time 0.13 0.17 1 19
Total inventory turnover rate 0.12 0.20 119
Profit margin 0.09 0.31 119
External customer service levels 0.09 0.35 119

 

Table 78: Part/Material Standardization — Associations of Joint

Planning and Decision Making Outcomes and Firm Performance

 

 

 

 

 

 

Dimensions
r p n

Cash-to-cash cycle time 0.29 0.00 125
Supplier on-time delivery 0.25 0.01 125
Supplier quality performance 0.19 0.03 125
Total inventory turnover rate 0.18 0.04 125
Profit margin 0.17 0.06 125
Supplier responsiveness 0.14 0.12 125
External customer service levels 0.12 0.18 125
Purchase price reduction compared to market 0.12 0.20 125
Return on equity (ROE) 0.07 0.45 125
Total cost reduction 0.05 0.55 125
Return of investment(ROI) 0.02 0.81 125
Purchase price reduction -0.02 0.86 125

 

171

 

 

Table 79: Supplier Scheduling — Associations of Joint Planning and

Decision Making Outcomes and Firm Performance Dimensions

 

 

 

 

 

 

r p n
Cash-to-cash cycle time 0.29 0.00 125
Supplier on-time delivery 0.25 0.01 125
Supplier quality performance 0.19 0.03 125
Total inventory turnover rate 0.18 0.04 125
Profit margin 0.17 0.06 125
Supplier responsiveness 0.14 0.12 125
External customer service levels 0.12 0.18 125
Purchase price reduction compared to market 0.12 0.20 125
Return on equity (ROE) 0.07 0.45 125
Total cost reduction 0.05 0.55 125
Return of investment(ROI) 0.02 0.81 125
Purchase price reduction -0.02 0.86 125

 

Table 80: Joint Goal and Target Setting — Associations of Joint

Planning and Decision Making Outcomes and Firm Performance

 

 

 

Dimensions
r p n

Purchase price reduction compared to market 0.30 0.00 120
Purchase price reduction 0.28 0.00 120
Total cost reduction 0.25 0.01 120
Supplier responsiveness 0.22 0.01 120
Supplier on-time delivery 0.21 0.02 120
Total inventory turnover rate 0.20 0.03 120
Profit margin 0.19 0.03 120
Return on equity (ROE) 0.19 0.04 120
Return of investment(ROI) 0.17 0.06 120
Cash-to-cash cycle time 0.12 0.20 120
Supplier quality performance 0.10 0.29 120
External customer service levels 0.05 0.60 120

 

 

 

 

172

 

 

Appendix K: Information Quality Paired Samples T-Tests

173

 

 

 

 

 

 

 

 

 

 

 

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177

Appendix L: Multiple Regression Difference Tests

178

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Appendix M: University Committee on Research Involving Human Subjects

183

 

OFFICE OF
RESEARCH
AND
GRADUATE
STUDIES

Unlvarslty Commlttee on
Research Involving
Human Subjects
(UCRIIIS)

MichIgan State University
246 Administration Budding
East Lansing Michigan
48824.1046

517/355‘2180
FAX 517/353-2976

{he MIrnIoan Slate Hm Ive/Slip
”It AI IIs IInsI lul Ional {)I veIISI I)

t .nN-II-

MICHIGAN STATE
U N l V E R S I T Y
November 17, 1998

TO: Dr. Robert M. Monczka
N505 N. Business Complex
Eli Broad Grad School of Mgt
APPROVAL DATE: November 16, 1998
RE; [RB # 98744 CATEGORY: l-C

TITLE: THE IMPACT OF INFORMATION SYSTEMS ON ACHIEVING SUPPLY
CHAIN INTEGRATION

The University Committee on Research Involving Human Subjects' (UCRIHS) review of this
project is complete and I am pleased to advise that the rights and welfare of the human subjects
appear to be adequately protected and methods to obtain informed consent are appropriate.
Therefore, the UCRIHS approved this project.

RENEWALS: UCRIHS approval is valid for one calendar year, beginning with the approval date
shown above. Projects continuing beyond one year must be renewed with the green renewal form

A maximum of four such expedited renewals possible. Investigators wishing to continue a project
beyond that time need to submit it again for a complete review.

REVISIONS: UCRIHS must review any changes in procedures involving human subjects, prior to
initiation of the change. If this is done at the time of renewal, please use the green renewal form.

To revise an approved protocol at any other time during the year, send your written request to the
UCRIHS Chair, requesting revised approval and referencing the project's IRBII and title. Include

in your request a description of the change and any revised instrumaits, consent forms or
advertisements that are applicable.

vacuums/amass: Should either of the following arise during the course of the work, notify
UCRIHS promptly: l) problems (unexpected side effects, complaints, etc.) involving human
subjects or 2) changes in the research environment or new information indicating greater risk to

the human subjects than existed when the protocol was previously reviewed and approved.

lfwe can be offurther assistance, please contact us at 517 355-2180 or via email:
UCRIHS@piIotmsu.edu. Please note that all UCRIHS forms and instruction are located
via the web: http://wwwmsuedu/unit/vprgs/UCRIHS/

a. e) 0%"

David E Wright, Ph D
UCRIHS Chair

‘
DEW \\.

CC Kenneth Petersen

Sincerely,

184

Bibliography

185

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