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lII
EuPrRrclr, STUDY oF NEw ZBAND uAlrUFecTItRrNo pEAlfTgDonald George S1uti A
thesis
subnitted inthe requirements
for
fulfillnent of the degree of
DOCTOR OF PHTIOSOPHY
[n the
DEPARTI,IENT OF I.iANAGEMENT SCTENCE
AND TNFORMATTON SYSTEMS
THE UNIVERSITY OF AUCKIAND
L992
Advisers:
Dr.
I(anbiz MaaniSenior Lecturer
Management Science & fnformat.ion Systens
Dr.
lIartin putterill
Associate professor Accounting & Finance
.lillvB9ly oF AUCKLAND LTBRARY
_.,.,:
illlHilq
?.t--
l6L
((tt, L t-. tr,
ACKITOWLEDGET.TENTS
During the process of conducting this research of the impacts of trqualityrr on performance , I have had the pleasure of dealing with a number of people who have been only too witling to assist me in my endeavour. r wish to acknowledge rny thanks to these people.
I express appreciation to my two committee members who spent
long hours and great efforts on my behalf. Dr. Kanbiz Maani was
especially helpful in guiding me during the initial stage of the research. His feedback concerning the construction of the research model and the development of the guestionnaire helped to avoid some pitfatls which rnay have hindered the success of this research. Associate Professor Martin putterill was of great assistance throughout the process and gave especiar herp concerning the structure and presentation of the dissertation.
My committee members also demonstrated an aerareness of me as an
individual with needs, frustrations and goars. r wish to thank thern for this.
A debt of gratitude and appreciation is expressed to those manufacturing managers who gave of their time to provide the empirical data used in this study.
r wish to thank some of the other people who assisted me
along the way. professor craig Ansley and Dr. shoreh Maani for their advice on statistical procedures. Dr. Brian Murphy for his helpful commentary on questionnaire construction and presentation of resurts. Dr. Thomas Rohrer for his efforts to bring me to a
tl
competent understanding of the structural equations modelring methodorogy. Mr. Michaer Ford and Mrs. Lorri o'Brien for assistance in mastering sAS procedures. Mr. Edward orNeirr for help in the preparation and distribution of guestionnaires.
Margaret Tibbles and peter Beyer for their help in the final preparation of this manuscript. Mr. Bruce Hardie for general assistance- Dr. Lech Janczewski and Mr. rvan Farac for moral support.
r also wish to acknowledge the support provided to me during this research from grants frorn the University of Auckland Higher
Deqrees committee and the financial help given by the Department
of Management Science and fnformation Systems.
Fina1ly, a speciar message of rove and appreciation goes to ny family. Eraine, thanks for arl of the support, patience and
understanding which you gave to me during this important time of
my life and for shouldering the entire burden of having to deal
with the rrreal world'r during these past few years. Al_so , a special thanks from dad to Tom and Anne for being such wonderful children.
l't'l
ABSTRACT
This study was conducted to assess the inpacts of quality on
operational and business performance in manufacturing firms.
Data were provided by 184 diversified New zealand manufacturing plants- Quality is defined as the degree of conformance to specifications.
The first phase of the research was the construction of a
theoretical model to incorporate the impacts of. quarity on
nanufacturing performance, manufacturing productivity and business performance. The relationships of the model are based
on the guality managrement literature.
The second phase of the research was the design and
administration of a survey instrument for the collection of empirical performance data. The data were then used to evaluate the relationships represented in the model.
The final phase of the research used structural eguations nodelling in order to evaluate the relationships of the model.
Quality was found to have significant and positive irnpact,s on
operational performance measures for process utilization, process
output, production costs, work-in-process inventory levels and
on-time delivery rate. The anarysis found that change in quarity level was most strongly associated with change in process utilization. The findings for the irnpacts of quarity on
operatj-onal performance were cornpatibre with the guarity
management literature.
The impacts
of quarity
on business performance given bystructurar
eguations anarysiswere significant
and positivethe for
lv
productivtttr'-lndueed l,nproveslents
of quatlty.
GenEralllr, the sup-port f:et Che iupactsof quality
on businergs petfornanoe v-hich_occur through
otlier
a,speets of,olrerational
performancewas
not siguriftcairt.Ttre LinLtatl.sns of tl,re
study,were speclftred.
TheimplicatLons of,. the :findirqrs
of tbe
stud11 f,or manufasturerrg $er€rrevi.ewed, atrong'wlth
the
directLslrsfor future
res-earch.TABIJ OF CONTETTS
ACKNOWLEDGEMENTS ... "..""
page
ii vi iv
ABSTRACT
TABLE OF
LIST OF LIST OF LIST OF
NOTE ON CHAPTER
1. INTRODUCTTON AND PROBLEM STATEMENT .... t
1. 1. A Very Cornpetitive Global Economy
L.2. consumers Demand Quality in the Global Market L.3. Introduction to the RoIe of Quality in
Manufacturing 1.4. What is Quality?
L.5. The fmpact of i'gualityrr in the Emerging View 1.5. Delays in Adopting a 'rQualityrr Focus
1-.7. The Research Environment: Manufacturing in
New Zealand L2
1.8. Research Objectives and Procedures L5
1.9. Outline of Dissertation L5
L. l-0. Contribution of Research 19
2. THE IMPACTS OF "QUALITYn ON PERFORMANCE: A REVIEW OF
THE LTTERATURE 22
2.L. A Search for the Evidence of the Irnpacts of ItQualityt'
2.2. Empirical
2.3 . Ernpirical
CONTENTS
TABLES .,... ix
ILLUSTRATIONS ... X
ABBREVIATIONS Xi
PRESENTATION FORMAT AND COMPUTER SOFTWARE Xii
Studies Based on PIMS Data
Studies that Ernploy Data from Several
1 2 3
3 7
tL
Ll-
23 25
Firms
Evidence from Case Examples
Ernpirical Evidence from Large-Scale Studies Theoretical Impacts of Improved rrQualitytt
other Related Quality Managernent Literature
Need for Further Research
3. A MODEL OF REI,ATIONSHIPS BETWEEN ''QUALTTYII AND
PERFORMANCE 57
3. L. Introduction . 58
3.2. Foundations of the rrQuality"-Performance Model 59 3.3. Integration of the Chain Reaction and Cost
Savings Models 64
3.4. Developnent of the |tQualityt,-Performance Model 66 3.5. Antecedent Expectations of Operational Links with
Business Unit, Performance 73
3.5. SummarY and Transition ' 75
3L
2.4.2.5.
2.6.2.7 .
2.8.
34 40 42 53 54
\/I
4. SELECTTON OF OPERATIONAL MEASURES AND page DATA COLLECTION
76 77 79 89 92 96 97 L00 LO2 L03 L03 105 L06 l.0B L10 r.L1 1,2L ]-27 L29 t 31 136
PROCEDURES
4.L. A Need for Empirical Data
4.2. Operational Measures Considered
4.3. Data Collection Technigue 4.!. Design of euestionnaire
4.5. Ensuring Respondent Confidentiality 4.6. Data Collection
4.7 . Summary
s.
A vrEw 5. t_.5.2.5.3 .
5.5.5.4.
5.6.5.7 .
5. 8.
5. 10.5.9.
5. 1L.
5.L2.
OF THE EMPIRICAL DATA: SUMMARY AND TESTS
Rgsumd .. o.. .. o...
Questionnaires Returned Creati.on of the Dataset
Sanple Representativeness Evaluated
coefficient Alpha Test of rnstrument and Data
Reliability
Adjustrnent of Response Scale Values
A Summary View of the Empirical Data
T Tests of Response Differences Factor Analysis Results
Operational Measures Rejected
An Initial View of the Association of leuality with Performance ...
Usefulness of the Data Confirmed
OF ANALYSIS OF Q-P MODEL VARIANTS
Introduction
6. ANALYSIS METHODOLOGY: 6.1. 6.2. serection Methodological and Advantages Requirements SELECTTON of structural AND DTscUsSIoN Eguations. 138139
Modell j.ng 141
5.3- coinposition of structurar Eguations Models , r45
6.4. Procedure for Moder construction and Testing 151_
6.5. Sample Size Requirernents of SEM Llrz
5.6. Description of EeS Software . 153
5.7. Summary . 161
7. RESULTS
7.t.
7 .2.
I62
l_63
165
t73
Description Functions
Functions of
Variants Focused on-
Operations...
7
-3.
conditionsfor
the useof structurar
Equations Modelling7.4.
Evaruativecriteria of Fit for
structural_ Pguations Models . 176
!-5. Findings: operations Functions Variants 1g3
7.6. Q-P Model performance Variants Linked to Business . Lg4
7.7. Findings: Confirmed Business performance
Variant
zoo7.8. Results for Unconfirmed ROS Variants ZOz
7.9. Summary of Findings 2o4
vll
8. DTSCUSSTON page206
8.1. fntroduction ... . ZO7
8.2. Review of e-p Model Links 2O7
8.3. EeS Findings for Confj-rmed Variants ... ZLO
8.4. EeS Findings for Unconfirmed Variants . ZL4
8.5. consideration of Lirnitations to the Findings of
the Study o... zL7
8.6. Directions for Further Research ... Z2Z
8-7. contribution of the study to the understanding of the rnpact of "eualityr on performance 224
APPENDICES
APPENDIX 1: SUPPLEMENTARY MATERIAL To CHAPTER 4
Questionnaire and Attachments
Pilot Test Materials
Manufacturer Newsletter Article
229 230 237 240 APPENDIX 2: SUPPLEMENTARY MATERTAL To CHAPTER 5 . 24L
Chi-Square Test Results . Z4Z
Coefficient Alpha Test Results 244
Factor Analysis Test Results . 246
APPENDTX 3: SUPPLEMENTARY MATERIAL To CHAPTER 7 247 EQS Test Results for e-p Model Variants 24g APPENDTX 4:
REFERENCES
SUPPLEMENTARY MATERTAL TO CHAPTER 8 .. 324 327
vf-J-a
Table 2.L2.2 2.35.1 5.25.3 5.4 5.5a5.5b
8.2
LIST OF TABLES
Findings of a Study of Quality and Market Share Findings of a Study of Quality and Quality Costs Findings of a Study of Quality and Productivity Position Title of Respondents
Comparison by Ernployment Size
Comparison by Organizational Legal Status Comparison by Standard Industrial Code
Classification ...
Adjusted Distribution of Interval Sca1e Responses
Adjusted Distribution of Responses to Estinated
page 28 33 33 105
LO7 LO7
108 LL2
Percentage Change 113
5.6 Use of Preventive and Appraisal Practices ... 119
5.7 Implernentation Barriers to Quality Improvement :... 119 5.8 T Tests Conparing Categories of Plants L24 5.9 OLS Results - Relationship of Scrap And Rework
with Measures of Perforrnance 133
5.L0 Comparison Based on Reduction of Scrap and Rework:
Most Reduction versus A11 others L34 5.1-L Comparison Based on Use of Preventive Quality
Management Practices ... 136
7.L Preliminary Fit Criteria of operations Functions
Variants L7A
7.2 Goodness-of-Fit of Operations Functions Variants 1.79 7.3 Fit of Internal Structure of Operations Functions
Variants
7.4 Prelinrinary Fit Criteria of RoS Variants L98 7.5 Goodness-of-Fit of ROS Variants L99
7.6 Fit of fnternal Structure of RoS Variants 2OO
8. L lmpacts of "Qualityrt on Performance
(Estinated Parameter Values of Confirmed Variants 2L3 Impacts of ttQualityrr on Business Performance
(Estirnated Parameter Values of Unconfirmed Variants.. 2L6
IX
Figure L.1L.2 1.32.L 2.2 2.3 2.42.5 3.L3.2 3.33.4
4.r4.2 4.3 5. l_
5.2 5.35.4 5.56.L 6.26.3 6.46.5 7.L7.2 7.37.4 7.57.6 7.7 7.87.9 7. L0 7 .LL
7 .12 7.L3
7.1,4
7.L5 7.168.L 8.28.3
LIST OF Illustrations
Traditional View of Manufacturing objectives Traditional View of Desired Quality Level ...
Energing View of Manufacturing Objectives
PIMS Based Quality Research
Studies of Manufacturing Quality (Data from Several Firns)
page
4 5 6 27 32
82 9l_
94 115 115 L22 L28
1,3 0
L45 L49 150 L54 155 L64 L67 L67 158 158 169 L74 184
1"84
185 L97 L97 t-98 20L 243 203 208 2LL 2L4
Studies
of
Manufacturing Quality(Data from Many
Firrns) ...
41"Aspects
of
ManufacturingPerformance
47Conponents
of
Qualitycosts
49The Chain Reaction
Mode1
5LThe Cost Savings Model
A Transitional Model
The 'rQualitytt - Performance Model Proposed Operational Measures
Comparison of Survey Data Collection Methods Questionnaire Reference for Proposed Measures
Product Line Size
Manufacturing Process Employed
Groups Tested for Response Difference
Factors, Latent Constructs, and Observed Measures.
Operational Measures of Q-P Model Constructs Structural Portion
Measurement Portion
An fntegrated Structural Equations Model
EQS Software Package
Evaluation Criteria of Model Fit Structural Equations Mode1 Elements
Inventory Variant of the Q-P Model
Delivery Variant of the Q-P Model
Manufacturing Cost Variant l- of the Q-P Model
Manufacturing Cost Variant 2 of the Q-P Model
Flexibility Variant of the Q-P Model
Conditions Pertaining to Appropriateness of Theoretical Models for Confirmatory Analysis
EQS Results fnventory Variant
EQS ResuLts - Delivery Variant
EQS Results - Manufacturing Cost Variant 2 ..
Inventory-ROS Variant of the Q-P Model
Delivery-Ros Variant of the Q-P Model
Manufacturing Cost-ROS Variant of the Q-P Model EQS Results Delivery-ROs Variant
EQS Results Inventory-ROS Variant
EQS Results - Manufacturing Cost-ROS Variant
rrQual itytt -Performance ModeI
Q-P Model Links Supported by Findings Q-P Model Links NoT Supported by Findings
63 55 67
AGPS
dfCN EQs
JIT
LISREL usA oLs
PFC PIMS ROA ROr
ROS SEM
SIC sMcc sQcTFI
TQc WIP
I.TST OF ABBREVTAETOIIs
Australian covernment publishing Sewice
Critical
NDegrees
of
FreedomA Structural Eguations Modelling Softtrare
Package
Just-in-Tirne
A Structural Equations Modelling Softerare
Package
Measure
of
Sampling AdequacyOrdinary Least Squares Prelininary
Fit criteria
Profit
Inpactof
Marketing Strategy Return on AssetsReturn on InvesLment
Return on Sales
Structural
Eguations Modelling Standardfndustrial Classificition
Standard
Multiple
Correlation CoefficientStatisticat
euaLity ControtTotal
Factor IndexesTotal
Quality ControlWork-in-process
xl-
NOTE OTT PRESEIITATION FORITAT AIID COUPUTER COFIrARE
The presentation fonnat followed in this
dissertation follows Turabian's(L973)
recommendations.Text is in
couriertype-style.
Oxford Dictionarvspelling is
used.Text and tables use
the
IBM Displaywrite4 (1986)
software package- Graphicsin figures
are obtained by useof the
HarrrardGraphics
(1990) and Lotus L.2.3.
(r.985)software
packages.carculations are made using sAS (r.9g5) and Ees
(Bentler,
1989)softvare packages.
xll