Doctoral thesis of philosophy strategic information systems planning (sisp) in australia assessment and measurement

Strategic Information Systems Planning (SISP) in Australia: Assessment and Measurement A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Zijad Pita School of Business Information Technology Faculty of Business RMIT University February 2007 Declaration Declaration I certify that except where due acknowledgement has been made, the work is that of the author alone; the work has not been submitted previously, in whole of in part, to qualify for any other academic award; the content of the thesis is the result of work which has been carried out since the official commencement date of the approved research program; and, there has been no editorial work, paid or unpaid, carried out by a third party on this thesis Zijad Pita February 2007 ii Abstract Abstract Strategic Information Systems Planning (SISP) is an important activity for helping Chief Information Executives (CIOs) and top management identify strategic applications and align Information Technology (IT) with business needs Like all strategic planning, SISP requires measuring how well SISP is done and how planning is improving over time The measurement of these intangibles is a complex exercise There have been few efforts undertaken in the Information Systems (IS) literature to formally develop a model for assessing and measuring SISP efforts In this study, two models were proposed: a five-stage SISP maturity model for defining SISP maturity and another one for assessing the degree of SISP maturity The five SISP maturity levels were defined as: Rudimentary Planning, Ineffectual Planning, Attainable Planning, Sustainable Planning, and Adaptable Planning The assessment model was structured as a third-order system, where eight first-order dimensions were termed as Form and Content, Collaboration, Policies, Stakeholders’ Designation, Knowledge Bank, Technology, Time Dimension, and Viability The first-order dimensions were grouped into three second-order constructs, namely Effectiveness, Efficiency and Manoeuvrability, which ultimately characterise the level of SISP success This model was used to establish a theoretical benchmark for each SISP maturity level To model the level of SISP maturity, an ‘Integral Engineering’ approach was established and the Analytic Network Process (ANP) theory was used The study is a novel approach in using ANP to synthesize the measures of the various SISP constructs into a single overall measure of SISP maturity level A survey was performed and data collected from 260 Australian organisations to examine the degree of SISP maturity and the relationships among SISP constructs Structural equation modelling (SEM) was used to test the fit between the hypothesized model and the survey data The models were applied to the data collected and the findings suggested that the models fit the data well While Effectiveness and Efficiency are well recognised planning constructs, Manoeuvrability as a measure of planning dynamics is not acknowledged in the literature as an equally important construct This study confirmed a strong correlation between Manoeuvrability and SISP success and found it to be more important than the iii Abstract Efficiency construct The empirical data did not confirm the existence of Rudimentary and Ineffectual planning levels of SISP maturity Australia-wide SISP maturity in the majority of Australian organisations is at Sustainable and Attainable planning levels A small percentage of the surveyed organisations have actually reached the highest planning level (Adaptable planning) The empirical data showed that current SISP is lacking strategic dimension and that the recently popularised one-year planning horizon may not be the best choice Australian organisations did not consider the strategic relevance of IT as the key objective IT/IS was seen as a business enabler, thus the strategic advantage associated with IT came as a secondary objective iv Acknowledgements Acknowledgements It is impossible to name all the people who helped in this research for the last six years To all who helped, I am forever grateful for your contributions I would first of all like to thank my supervisor Dr France Cheong for the great support given to me during these hard years He provided me with the complete freedom to explore my own interests and his guidance assisted me throughout this research My special gratitude also goes out to Professor Brian Corbitt for his time and valuable direction The discussions held between us have improved my process of thinking and greatly contributed to the quality of research I would like to acknowledge the support given to me by my esteemed colleague Professor Dorothy Leidner, Professor of Information Systems at the Baylor University, USA Her support was a key motivator to endure the hard times I am also indebted to Rozann Saaty of the Creative Decisions Foundation, Pittsburgh and William Adams of Embry Riddle Aeronautical University, Florida who developed the SuperDecisions software, working with Rozann Without the use of this software and invaluable direction from Rozann, this study would have been impossible to complete I would like to thank my family for being patient with me for all these years In particular, I am grateful to Emina Kustrich for her encouragement and generous support Also, I would like to show gratitude to my sons Sanko and Dinko for their assistance in the collection of the data for the research I also owe apologies to my little white dog Kiki, for all those walks to the park that he did not receive Last but not least, I am deeply grateful to my wife Senada from whom I selfishly stole much time but whose support was endless throughout this venture v Table of Contents Table of Contents Abstract iii LIST OF TABLES xi LIST OF FIGURES xiv LIST OF ABBREVIATIONS xvi GLOSSARY xvii CHAPTER 1 INTRODUCTION 1.1 Background 1.2 Motivation of the Research 1.3 Research Aim and Scope 1.4 Outline of the Thesis CHAPTER 10 A REVIEW of SISP LITERATURE 10 2.1 Introduction 10 2.2 SISP Definition 10 2.3 Why Engage in SISP? 13 2.3.1 The Need and the Purpose of SISP 13 2.3.2 SISP Success and Benefits 16 2.4 Assessment of SISP 19 2.4.1 Definition of a System 19 2.4.2 Definition of Information 20 2.4.3 Information Systems Definition 22 2.4.4 Information Feedback 22 2.4.4.1 A System as a Group of Processes 23 2.4.5 Feedforward and Feedback Control Loops 23 2.4.6 IS Subsystems 25 2.4.7 SISP Processes 27 2.4.8 Assessment of SISP System Behaviour 31 2.4.8.1 Gaps in SISP Behaviour Assessment 34 2.4.9 Assessment of SISP System Structure 35 2.4.9.1 Approaches to SISP Success 38 2.4.9.2 SISP-related Methodologies, Techniques, and Tools 40 2.4.9.3 SISP Problem Areas: the Internal Environment 42 2.4.9.4 Misalignment of SISP and Business Goals 47 2.4.9.5 Managerial Misalignment 50 2.4.9.6 Lack of Management Commitment 51 2.4.9.7 The Problem of Culture Gap 52 2.4.9.8 Problems with Resources 54 2.4.9.9 Lack of SISP Measurement and Revisions 55 2.4.9.10 SISP Problem Areas: External Environment 56 2.4.9.11 Political Factors 58 2.4.9.12 Changes in Economic Structure 59 vi Table of Contents 2.4.9.13 Shifts in Society 59 2.4.9.14 Legal Trends 59 2.4.9.15 Ecological Trends 60 2.4.9.16 Technological Barriers 60 2.4.9.17 Pressure Groups and Stakeholders 62 2.4.9.18 Competitive Forces: Suppliers and Customers 63 2.4.9.19 Failure to Analyse Major Competitors 64 2.4.9.20 Gaps in SISP Structure Assessment 64 2.4.10 Assessment of SISP System Evolution 65 2.4.10.1 The Three-Era Model 66 2.4.10.2 The Fourth Era Model 69 2.4.10.3 Gaps in SISP Evolution Assessment 71 2.5 Conclusion 71 CHAPTER 74 RESEARCH DESIGN and RESEARCH METHODOLOGY 74 3.1 Introduction 74 3.2 Conceptual Definitions 74 3.2.1 Ontological and Epistemological Conceptions 75 3.2.2 Ethics 77 3.2.3 Choice of Paradigm 77 3.3 Research Design 78 3.3.1 Comparative Judgement 79 3.3.2 Normative Judgment 79 3.3.3 Goal-centred Judgement 80 3.3.4 Improvement Judgement 80 3.3.5 Analytic Thinking Approach 80 3.3.6 Engineering Approach 82 3.3.7 Reasons for Adopting an Integral Engineering Approach 82 3.3.8 Research Generalisation 83 3.3.9 Hypothesis Study 84 3.3.10 Time Horizon of Data Collection 85 3.3.11 Types of Investigation 85 3.3.12 Extent of Researcher Interference 85 3.3.13 Unit of Analysis 86 3.4 Research Plan 86 3.5 Research Methodology 87 3.5.1 Measurement and Measures 88 3.5.1.1 Measurement Scales 88 3.5.1.2 Reliability 90 3.5.1.2.1 Internal Consistency of the Measuring Instrument 92 3.5.1.3 Validity 93 3.5.1.3.1 Validity of the Model as Whole 93 3.5.1.3.2 Validity of the Measuring Instrument 95 3.5.1.3.3 Construct Validity 96 3.5.2 Sampling Design 97 3.5.3 Data Collection 98 3.5.3.1 Questionnaire Design 99 3.5.3.2 Sampling Frame 100 3.5.3.3 Questionnaire Presentation 100 3.5.3.4 Pilot Survey 100 3.5.4 Data Analysis 101 3.6 Techniques and Tools Used For SISP Models 102 3.6.1 ANP/AHP Theory 102 3.6.1.1 Paired Comparison 103 3.6.1.2 The Supermatrix 104 3.6.1.3 The Consistency of a System 107 3.6.2 Steps in Developing the SISP Models using ANP/AHP 108 vii Table of Contents 3.6.3 3.6.4 3.7 Structural Equation Modelling 110 Summary of the Research Design and Methodology 113 Conclusion 114 CHAPTER 116 SISP MATURITY MODEL 116 4.1 Introduction 116 4.2 SISP Maturity Definition 117 4.3 The Five-Stage SISP Maturity Model 118 4.3.1 Rudimentary Planning 118 4.3.2 Ineffectual Planning 119 4.3.3 Attainable Planning (Causing Federalisation) 119 4.3.4 Sustainable Planning (Achieving Adhesion) 119 4.3.5 Adaptable Planning (Achieving Cohesion) 120 4.4 SISP Maturity Assessment Evaluation Criteria 121 4.4.1 SISP Maturity Criteria Definition 121 4.4.1.1 Effectiveness 122 4.4.1.2 Efficiency 123 4.4.1.3 Manoeuvrability 124 4.5 SISP Maturity Assessment Evaluation Subcriteria 125 4.5.1 SISP Maturity Subcriteria Definition 126 4.5.1.1 Policies 126 4.5.1.2 Knowledge Bank 128 4.5.1.3 Stakeholders’ Designation 130 4.5.1.4 Technology 132 4.5.1.5 Form & Content 133 4.5.1.6 Collaboration 135 4.5.1.7 Viability 136 4.5.1.8 Time Dimension 138 4.6 SISP Maturity Assessment Evaluation Clusters and Nodes 139 4.7 Criteria Priorities 143 4.7.1 Main Criteria Priorities 143 4.7.2 Subcriteria Priorities 146 4.8 The Clusters and Nodes Priorities 149 4.9 SISP Maturity Model Synthesis 159 4.9.1 How the Alternatives Contributions Fed Forward 160 4.9.1.1 Rudimentary Planning 162 4.9.1.2 Ineffectual Planning 162 4.9.1.3 Attainable Planning - Causing Federalisation 163 4.9.1.4 Sustainable Planning (Achieving Adhesion) 163 4.9.1.5 Adaptable Planning–achieving Cohesion 164 4.10 Usage of the SISP Maturity Model 164 4.10.1 The SISP Assessment Model 165 4.11 The SISP Maturity Model Sensitivity Analysis 165 4.12 Validation of the SISP Assessment Model 168 4.13 Conclusion 169 CHAPTER 171 SEM: SISP MEASUREMENT and STRUCTURAL MODEL 171 5.1 Introduction 171 5.1.1 Reliability of Subscales Used in SEM 171 5.1.2 SEM: Testing for the Factorial Validity of Scores from a Measuring Instrument (FirstOrder CFA model) 174 viii Table of Contents 5.1.2.1 Hypothesis 1: SISP is a First-Order Single-Factor Model 175 5.1.2.2 Hypothesis 2: SISP is a First-Order Three-Factor Model 177 5.1.2.3 Hypothesis 3: SISP is a First-Order Six-Factor Model 179 5.1.2.3.1 Model Misspecification 182 5.1.2.3.2 Post Hoc Analyses 183 5.1.2.4 Testing for Factorial Validity of SISP subcriteria (First-Order CFA Model) 185 5.1.2.4.1 Test for Convergent Validity 185 5.1.2.4.2 Test for Discriminant Validity 186 5.1.3 SEM: Testing Measurement Model (Second Order CFA model) 188 5.2 SEM: Testing the Structural Model (Third-Order Model) 190 5.3 Conclusion 195 CHAPTER 197 DATA ANALYSIS 197 6.1 Introduction 197 6.1.1 Data Preparation 197 6.2 Response Analysis 198 6.3 Characteristics of Organisations that not Perform SISP 200 6.3.1 Company Locations 200 6.3.2 Industry Type and Size by Turnover 200 6.3.3 Industry Size by Number of Employees 202 6.3.4 Industry: Other Characteristics 202 6.3.4.1 Dependency on IT/IS 202 6.4 Characteristics of Surveyed Organisations that Perform SISP 204 6.4.1 Company Locations 204 6.4.2 Industry Type and Size by Turnover 205 6.4.3 Industry Size by Number of Employees 206 6.4.4 Industry: Other Characteristics 208 6.4.4.1 Dependency on IT/IS Structure 208 6.4.4.2 Perception of IS/IT Function 210 6.5 Characteristics of the Respondents 213 6.6 Levels of SISP Maturity and SISP Success in Australian Organisations 216 6.6.1 SISP Maturity versus Company Size 223 6.6.2 SISP Maturity and Benefits from SISP Relations 225 6.7 The Key Issues in IT Management 228 6.7.1 Key Reasons for SISP Formulation Failure in Australia 229 6.7.2 Key Reasons for the SISP Implementation Failure in Australia 233 6.8 Assessment of SISP System Behaviour and Structure 235 6.8.1 Effectiveness 235 6.8.1.1 Collaboration 235 6.8.1.1.1 Strategic Alignment 236 6.8.1.1.2 Communication and Coordination 241 6.8.1.1.3 Confirming Latent Factor ‘Collaboration’ 243 6.8.1.2 SISP Form and Content 244 6.8.1.2.1 SISP Approaches 244 6.8.1.2.2 Company Size and SISP Approaches Relationship 251 6.8.1.2.3 SISP Methodologies 252 6.8.1.2.4 SISP Content 258 6.8.1.2.5 SISP Focus 262 6.8.1.2.6 Confirming Latent Factor ‘Form & Content’ 264 6.8.1.3 Policy 265 6.8.1.3.1 Confirming Latent Factor ‘Policy’ 268 6.8.1.4 Knowledge Bank 269 6.8.1.4.1 Confirming Latent Factor ‘Knowledge Bank’ 275 6.8.2 Efficiency 276 6.8.2.1 Stakeholders’ Designation 276 6.8.2.1.1 SISP Commitment 277 ix Table of Contents 6.8.2.1.2 SISP Participation 282 6.8.2.1.3 Confirming Latent Factor ‘Stakeholder’s Designation’ 291 6.8.2.2 Technology 292 6.8.2.2.1 Confirming Latent Factor ‘Technology’ 295 6.8.3 Manoeuvrability 296 6.8.3.1 Viability 296 6.8.3.1.1 Confirming Latent Factor ‘Viability 302 6.8.3.2 Time Dimension 302 6.8.3.2.1 Confirming Latent Factor ‘Time Dimension’ 306 6.9 SISP Measurement 307 6.9.1 SISP Measurement Methods 307 6.9.2 Quality of SISP Measurement 308 6.9.3 Scope of SISP Measurement 310 6.9.4 Objectives of SISP Measurement 311 6.9.5 Success of SISP Measurement 312 6.10 Conclusion 314 CHAPTER 317 DISCUSSION AND CONCLUSIONS 317 7.1 Introduction 317 7.2 Summary of the Research Work 317 7.2.1 Context and Issues 317 7.2.2 SISP Theoretical Models 319 7.2.2.1 The SISP Evolution Model 320 7.2.2.2 The Model for Assessing SISP Evolution 322 7.2.3 Assessment of SISP Maturity in Australian Organisations 324 7.2.4 Discussion –Revisiting the SISP Literature 325 7.2.5 Research Hypotheses 331 7.3 Implications for SISP Theory 332 7.4 Implications for SISP Practice 337 7.5 Limitations of the Research 340 7.6 Suggestions for Future Research 342 References 344 APPENDICES 363 Appendix A 363 Appendix B 372 Appendix C 408 Appendix D 421 Appendix E 435 Appendix F 438 Appendix G 452 x Appendix F Estimate S.E C.R P Label Technology < > Collaboration 041 021 1.971 049 par_16 Technology < > Viability 061 026 2.373 018 par_17 Time_Dimension < > Technology 021 010 2.103 035 par_18 Form & Content < > Stakeholders'_Designation 074 025 2.955 003 par_19 Stakeholders'_Designation < > Collaboration 125 046 2.744 006 par_20 Time_Dimension < > Viability 089 023 3.907 *** par_21 e6 < > e12 131 043 3.021 003 par_22 Correlations: (Group number - SISP six-factor measurement model - respecified) Estimate Form & Content < > Collaboration 347 Time_Dimension < > Form & Content 253 Form & Content < > Viability 275 Technology < > Form & Content 290 Time_Dimension < > Stakeholders'_Designation 261 Viability < > Stakeholders'_Designation 292 Technology < > Stakeholders'_Designation 537 Time_Dimension < > Collaboration 313 Viability < > Collaboration 415 Technology < > Collaboration 209 Technology < > Viability 272 Time_Dimension < > Technology 231 Form & Content < > Stakeholders'_Designation 366 Stakeholders'_Designation < > Collaboration 239 Time_Dimension < > Viability 444 e6 < > e12 288 Variances: (Group number - SISP six-factor measurement model - respecified) Estimate S.E C.R P Label Time_Dimension 081 024 3.414 *** par_23 Technology 102 027 3.819 *** par_24 Form & Content 057 019 3.081 002 par_25 Viability 495 108 4.579 *** par_26 Stakeholders'_Designation 711 127 5.590 *** par_27 Collaboration 384 095 4.049 *** par_28 e4 354 083 4.264 *** par_29 e3 348 082 4.248 *** par_30 e10 103 023 4.448 *** par_31 e9 123 022 5.650 *** par_32 e7 142 024 5.955 *** par_33 e5 468 094 4.984 *** par_34 e6 429 118 3.617 *** par_35 e11 250 092 2.737 006 par_36 e12 483 073 6.654 *** par_37 e2 066 016 4.175 *** par_38 e8 115 029 3.998 *** par_39 e1 076 017 4.395 *** par_40 Squared Multiple Correlations: (Group number - SISP six-factor measurement model - respecified) Estimate Q45.7 541 Q20.5 430 Q23.1 445 Q28.4 404 Q28.1 664 Q26.2 687 Q24.4 603 Q30.4 419 Appendix F 440 Appendix F Estimate Q18.5 397 Q44.5 470 Q36.3 524 Q36.4 523 Model Fit Summary CMIN Model SISP six-factor measurement model - respecified Saturated model Independence model RMR, GFI Model SISP six-factor measurement model - respecified Saturated model Independence model Baseline Comparisons Model SISP six-factor measurement model - respecified Saturated model Independence model Parsimony-Adjusted Measures Model SISP six-factor measurement model - respecified Saturated model Independence model NCP Model SISP six-factor measurement model - respecified Saturated model Independence model FMIN Model SISP six-factor measurement model - respecified Saturated model Independence model RMSEA Model SISP six-factor measurement model - respecified Independence model AIC Model SISP six-factor measurement model - respecified Saturated model Independence model ECVI Model SISP six-factor measurement model - respecified Saturated model Independence model HOELTER Model SISP six-factor measurement model - respecified Independence model Appendix F NPAR 40 78 12 CMIN 52.428 000 693.628 DF 38 66 P 060 CMIN/DF 1.380 000 10.510 RMR 018 000 145 GFI 967 1.000 635 AGFI 932 PGFI 471 569 538 NFI Delta1 924 1.000 000 RFI rho1 869 IFI Delta2 978 1.000 000 TLI rho2 960 000 PRATIO 576 000 1.000 PNFI 532 000 000 NCP 14.428 000 627.628 LO 90 000 000 546.759 FMIN 202 000 2.678 F0 056 000 2.423 AIC 132.428 156.000 717.628 BCC 136.656 164.244 718.896 HOELTER 05 264 33 HI 90 37.564 000 715.945 LO 90 000 000 2.111 LO 90 000 179 LO 90 456 602 2.459 977 1.000 000 PCFI 563 000 000 RMSEA 038 192 ECVI 511 602 2.771 000 CFI HI 90 145 000 2.764 HI 90 062 205 PCLOSE 772 000 BIC 274.855 433.733 760.356 HI 90 601 602 3.112 CAIC 314.855 511.733 772.356 MECVI 528 634 2.776 HOELTER 01 303 36 441 Appendix F SISP Maturity Model: Full Structural Equation Model Analysis Analysis Summary Date and Time Date: Tuesday, 18 July 2006 Time: 11:35:10 PM Title SISP structural model: Tuesday, 18 July 2006 11:35 PM Notes for Group (Group number 1) The model is recursive Sample size Variable Summary (Group number 1) Your model contains the following variables (Group number 1) Observed, endogenous variables Q28.4, Q28.1, Q23.1, Q20.5, Q30.4, Q18.5, Q44.5, Q36.3, Q36.4, Q24.4, Q26.2, Q45.7 Unobserved, endogenous variables Form & Content Technology Viability Efficiency Manoeuvrability Effectiveness Stakeholders'_Designation Collaboration Time_Dimension Unobserved, exogenous variables e12, e11, e2, e1,e7, e9, e10, d1, d6, SISP, r2, r3, r1, e3, e4, e5, e6, d4, e8, d5, d2, d3 Variable counts (Group number 1) Number of variables in your model: Number of observed variables: Number of unobserved variables: Number of exogenous variables: Number of endogenous variables: = 260 43 12 31 22 21 Parameter summary (Group number 1) Weights Covariances Variances Fixed 31 0 Labeled 0 Unlabeled 11 22 Total 42 22 Means 0 0 Assessment of normality (Group number 1) Variable max skew c.r Q45.7 1.000 2.000 -.015 -.101 Q26.2 1.000 5.000 -.287 -1.888 Q24.4 1.000 5.000 -.261 -1.721 Q36.4 1.000 5.000 -.337 -2.219 Q36.3 1.000 5.000 -.155 -1.021 Q44.5 000 1.000 -1.063 -6.996 Q18.5 000 1.000 -.955 -6.284 Q30.4 1.000 2.000 311 2.050 Q20.5 000 1.000 1.878 12.366 Q23.1 000 1.000 2.094 13.781 Q28.1 1.000 5.000 -.289 -1.902 Q28.4 1.000 5.000 -.409 -2.692 Multivariate kurtosis -2.000 -1.019 -.947 1.309 708 -.871 -1.089 -1.903 1.529 2.383 797 594 23.398 Intercepts 0 0 Total 31 34 65 c.r -6.582 -3.353 -3.116 4.309 2.330 -2.866 -3.583 -6.264 5.031 7.843 2.623 1.954 10.291 Sample Moments (Group number 1) Sample Covariances (Group number 1) Appendix F 442 Appendix F Q45.7 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 Q45.7 250 Q26.2 193 1.379 Q24.4 182 825 1.179 Q36.4 049 210 146 743 Q36.3 018 082 077 386 732 Q44.5 026 071 073 044 059 195 Q18.5 036 068 076 067 062 086 204 Q30.4 118 162 122 056 068 012 017 Q20.5 009 094 098 053 054 015 003 Q23.1 034 077 055 054 042 025 024 Q28.1 047 207 143 186 206 090 086 Q28.4 036 318 158 099 133 099 060 Condition number = 39.177 Eigenvalues 2.488 1.243 857 462 366 333 287 249 158 120 110 063 Determinant of sample covariance matrix = 000 Sample Correlations (Group number 1) Q45.7 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 Q45.7 1.000 Q26.2 329 1.000 Q24.4 335 647 1.000 Q36.4 114 208 156 1.000 Q36.3 042 082 083 524 1.000 Q44.5 118 136 151 115 156 1.000 Q18.5 158 129 154 173 160 432 1.000 Q30.4 476 279 227 131 162 056 074 Q20.5 049 220 248 170 174 093 016 Q23.1 197 189 147 181 141 165 154 Q28.1 110 205 153 250 278 236 220 Q28.4 080 300 162 127 172 249 147 Condition number = 10.514 Eigenvalues 3.176 1.538 1.266 1.142 1.101 978 599 545 464 447 441 302 Q30.4 Q20.5 Q23.1 Q28.1 Q28.4 244 026 026 099 067 133 055 039 066 119 039 038 746 407 814 Q30.4 Q20.5 Q23.1 Q28.1 Q28.4 1.000 142 153 233 150 1.000 438 125 201 1.000 130 122 1.000 523 1.000 Notes for Model (SISP Maturity - Full SAM Model) Computation of degrees of freedom (SISP Maturity - Full SAM Model) Number of distinct sample moments: 78 Number of distinct parameters to be estimated: 34 Degrees of freedom (78 - 34): 44 Result (SISP Maturity - Full SAM Model) Minimum was achieved Chi-square = 56.157 Degrees of freedom = 44 Probability level = 103 Estimates (Group number - SISP Maturity - Full SAM Model) Scalar Estimates (Group number - SISP Maturity - Full SAM Model) Maximum Likelihood Estimates Regression Weights: (Group number - SISP Maturity - Full SAM Model) Estimate S.E C.R P Label Efficiency < - SISP 3.187 997 3.197 001 par_2 Maneuverability < - SISP 1.029 447 2.301 021 par_3 Effectiveness < - SISP 1.000 Stakeholders'_Designation < - Efficiency 1.000 Appendix F 443 Appendix F Form & Content Technology Viability Time_Dimension Collaboration Q23.1 Q30.4 Q24.4 Q26.2 Q36.3 Q36.4 Q18.5 Q44.5 Q28.1 Q28.4 Q20.5 Q45.7 < - Effectiveness < - Efficiency < - Maneuverability < - Maneuverability < - Effectiveness < - Form & Content < - Technology < - Stakeholders'_Designation < - Stakeholders'_Designation < - Collaboration < - Collaboration < - Time_Dimension < - Time_Dimension < - Viability < - Viability < - Form & Content < - Technology Estimate S.E 1.000 329 105 2.922 891 1.000 2.544 843 999 248 1.000 1.000 1.180 154 1.000 1.119 235 1.000 1.094 261 1.000 878 163 1.000 1.150 223 C.R P Label 3.124 002 par_9 3.277 001 par_10 3.017 003 par_11 4.022 *** par_1 7.670 *** par_4 4.760 *** par_5 4.200 *** par_6 5.378 *** par_7 5.169 *** par_8 Standardized Regression Weights: (Group number - SISP Maturity - Full SAM Model) Estimate Efficiency < - SISP 653 Maneuverability < - SISP 809 Effectiveness < - SISP 986 Stakeholders'_Designation < - Efficiency 790 Form & Content < - Effectiveness 583 Technology < - Efficiency 678 Viability < - Maneuverability 740 Time_Dimension < - Maneuverability 613 Collaboration < - Effectiveness 593 Q23.1 < - Form & Content 679 Q30.4 < - Technology 647 Q24.4 < - Stakeholders'_Designation 768 Q26.2 < - Stakeholders'_Designation 839 Q36.3 < - Collaboration 687 Q36.4 < - Collaboration 763 Q18.5 < - Time_Dimension 621 Q44.5 < - Time_Dimension 695 Q28.1 < - Viability 786 Q28.4 < - Viability 661 Q20.5 < - Form & Content 644 Q45.7 < - Technology 736 Covariances: (Group number - SISP Maturity - Full SAM Model) Estimate S.E C.R P Label e12 < > e6 130 043 3.027 002 par_12 Correlations: (Group number - SISP Maturity - Full SAM Model) Estimate e12 < > e6 301 Variances: (Group number - SISP Maturity - Full SAM Model) Estimate S.E C.R P Label SISP 018 009 1.946 052 par_13 r2 249 117 2.124 034 par_14 r3 010 008 1.339 181 par_15 Appendix F 444 Appendix F r1 d1 d6 d4 d5 d2 d3 e12 e11 e2 e1 e7 e9 e10 e3 e4 e5 e6 e8 Estimate S.E .001 006 036 012 208 092 055 018 049 017 224 066 261 118 457 074 286 084 064 014 078 015 142 022 125 021 101 023 387 077 310 091 483 092 407 119 115 027 C.R .086 2.934 2.274 3.087 2.955 3.377 2.207 6.209 3.410 4.452 5.197 6.318 5.907 4.307 5.022 3.419 5.244 3.413 4.300 P 931 003 023 002 003 *** 027 *** *** *** *** *** *** *** *** *** *** *** *** Label par_16 par_17 par_18 par_19 par_20 par_21 par_22 par_23 par_24 par_25 par_26 par_27 par_28 par_29 par_30 par_31 par_32 par_33 par_34 Squared Multiple Correlations: (Group number - SISP Maturity - Full SAM Model) Estimate Effectiveness 972 Maneuverability 654 Efficiency 426 Time_Dimension 375 Collaboration 352 Stakeholders'_Designation 624 Viability 547 Technology 460 Form & Content 340 Q45.7 541 Q26.2 704 Q24.4 590 Q36.4 582 Q36.3 471 Q44.5 483 Q18.5 386 Q30.4 419 Q20.5 415 Q23.1 461 Q28.1 617 Q28.4 437 Appendix F 445 Appendix F Matrices (Group number - SISP Maturity - Full SAM Model) Implied (for all variables) Covariances (Group number - SISP Maturity - Full SAM Model) SISP SISP Effective ness Manoeuv rability Efficienc y Time_Di mension Collabor ation Stakehol ders'_De signation Viability Technolo gy Form & Content Q45.7 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 Q30.4 Q20.5 Q23.1 Q28.1 Q28.4 Effectiv ManeuveraEfficiency Time_Dim Collabo Stakeholders' Viability Technol Form & Q45.7 eness bility ension ration _Designation ogy Content 018 018 019 019 019 029 058 058 060 434 019 019 029 060 079 046 048 048 148 048 345 058 058 060 434 060 148 696 055 019 055 019 086 020 175 143 086 020 139 049 175 143 460 057 102 018 019 019 058 019 048 058 055 019 055 022 068 058 052 046 021 019 019 018 018 055 048 022 068 058 053 048 021 019 019 019 019 055 048 023 070 060 053 048 032 029 020 019 019 086 076 164 512 434 165 148 065 060 143 058 058 175 153 023 070 060 053 048 086 079 020 019 019 086 076 056 174 148 386 345 052 048 049 048 048 139 122 164 821 696 165 148 065 060 143 058 058 175 153 066 206 175 156 139 094 086 057 055 055 460 404 118 169 143 054 049 022 020 102 019 019 057 050 022 068 058 053 048 021 019 019 055 055 055 048 Appendix F 446 250 194 164 063 056 025 023 118 022 022 066 058 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 Q30.4 Q20.5 Q23.1 Q28.1 Q28.4 1.376 821 195 174 077 070 169 068 068 206 311 119 055 048 1.179 165 743 148 386 065 058 060 053 143 054 058 053 058 053 175 156 153 137 732 052 048 049 048 048 139 122 195 086 022 021 020 094 083 204 020 019 019 086 076 244 019 019 057 050 133 055 055 048 746 404 812 Appendix F Implied (for all variables) Correlations (Group number - SISP Maturity - Full SAM Model) SISP SISP Effectivenes s Manoeuvra bility Efficiency Time_Dime nsion Collaboratio n Stakeholder s'_Designati on Viability Technology Form & Content Q45.7 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 Q30.4 Q20.5 Q23.1 Q28.1 Q28.4 EffectiveManoeuvr Efficiency Time_DimeCollabora Stakeholde Viability TechnoloForm & ness ability nsion tion rs'_Design gy Content ation 1.000 986 1.000 809 797 1.000 653 495 643 488 528 613 1.000 323 1.000 585 593 473 382 290 1.000 516 508 417 790 255 301 1.000 598 443 575 590 436 583 740 358 465 390 678 375 453 219 285 350 259 346 308 536 296 1.000 265 344 1.000 254 1.000 326 433 396 446 401 344 308 287 370 390 470 396 321 426 390 452 407 339 303 282 376 396 463 390 263 350 320 361 325 426 381 232 299 316 581 489 499 663 607 291 262 225 201 439 242 255 307 258 161 214 196 221 199 695 621 142 183 193 356 300 190 253 232 763 687 201 180 167 223 235 275 231 394 839 768 230 207 177 159 347 191 201 242 204 195 259 237 267 240 315 281 171 221 234 786 661 736 450 412 197 178 152 136 647 164 173 208 175 Appendix F 187 249 228 264 237 198 177 165 644 679 270 227 447 Q45.7 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 Q30.4 Q20.5 Q23.1 Q28.1 Q28.4 1.000 331 303 145 131 112 100 476 121 127 153 129 1.000 644 193 174 149 133 291 160 169 203 294 1.000 177 159 136 122 266 147 155 186 157 1.000 524 153 137 128 170 179 210 176 1.000 138 124 115 153 161 189 159 1.000 432 099 127 134 247 208 1.000 088 114 120 221 186 1.000 106 112 135 113 1.000 438 1.000 174 183 1.000 146 154 519 1.000 Appendix F Implied Covariances (Group number - SISP Maturity - Full SAM Model) Q45.7 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 Q30.4 Q45.7 250 Q26.2 194 1.376 Q24.4 164 821 1.179 Q36.4 063 195 165 743 Q36.3 056 174 148 386 732 Q44.5 025 077 065 058 052 195 Q18.5 023 070 060 053 048 086 204 Q30.4 118 169 143 054 049 022 020 244 Q20.5 022 068 058 053 048 021 019 019 Q23.1 022 068 058 053 048 020 019 019 Q28.1 066 206 175 156 139 094 086 057 Q28.4 058 311 153 137 122 083 076 050 Implied Correlations (Group number - SISP Maturity - Full SAM Model) Q45.7 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 Q30.4 Q45.7 1.000 Q26.2 331 1.000 Q24.4 303 644 1.000 Q36.4 145 193 177 1.000 Q36.3 131 174 159 524 1.000 Q44.5 112 149 136 153 138 1.000 Q18.5 100 133 122 137 124 432 1.000 Q30.4 476 291 266 128 115 099 088 1.000 Q20.5 121 160 147 170 153 127 114 106 Q23.1 127 169 155 179 161 134 120 112 Q28.1 153 203 186 210 189 247 221 135 Q28.4 129 294 157 176 159 208 186 113 Residual Covariances (Group number - SISP Maturity - Full SAM Model) Q45.7 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 Q30.4 Q45.7 000 Q26.2 -.001 003 Q24.4 018 004 000 Q36.4 -.013 015 -.020 000 Q36.3 -.038 -.092 -.070 000 000 Q44.5 001 -.006 007 -.015 007 000 Q18.5 013 -.002 016 014 014 000 000 Q30.4 000 -.007 -.021 001 020 -.009 -.003 000 Q20.5 -.013 026 040 000 007 -.006 -.016 006 Q23.1 012 008 -.003 000 -.006 005 005 007 Q28.1 -.019 002 -.031 030 066 -.004 -.001 042 Q28.4 -.022 007 005 -.038 010 016 -.016 016 Q20.5 Q23.1 Q28.1 Q28.4 133 055 055 048 119 055 048 746 404 812 Q20.5 Q23.1 Q28.1 Q28.4 1.000 438 174 146 1.000 183 154 1.000 519 1.000 Q20.5 Q23.1 Q28.1 Q28.4 000 000 -.015 018 000 -.016 -.010 000 003 002 Q28.1 Q28.4 000 055 033 Standardized Residual Covariances (Group number - SISP Maturity - Full SAM Model) Q45.7 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 Q30.4 Q20.5 Q23.1 Q45.7 000 Q26.2 -.020 025 Q24.4 503 044 000 Q36.4 -.496 242 -.333 000 Q36.3 -1.416 -1.459 -1.202 000 000 Q44.5 093 -.199 241 -.610 291 000 Q18.5 930 -.063 519 573 581 000 000 Q30.4 000 -.177 -.613 046 747 -.678 -.222 000 Q20.5 -1.136 956 1.617 -.003 340 -.554 -1.572 577 000 Q23.1 1.122 317 -.123 022 -.324 493 543 652 000 000 Q28.1 -.686 024 -.529 641 1.419 -.174 -.025 1.564 -.778 -.853 Q28.4 -.781 100 082 -.774 211 652 -.621 584 869 -.515 Appendix F 448 Appendix F Factor Score Weights (Group number - SISP Maturity - Full SAM Model) Q45.7 Q26.2 Q24.4 Q36.4 Q36.3 Q44.5 Q18.5 SISP 023 014 013 028 020 034 025 Effectiveness 022 014 013 030 021 033 024 Manoeuvrability 019 007 012 022 016 069 051 Efficiency 264 196 137 051 037 063 046 Time_Dimensio 009 004 006 011 008 305 224 n Collaboration 023 014 013 356 255 034 025 Stakeholders'_D 107 406 272 023 016 033 024 esignation Viability 034 -.025 038 033 023 098 072 Technology 316 032 022 008 006 010 008 Form & Content 011 007 006 015 011 016 012 Q30.4 016 016 013 186 Q20.5 049 051 038 087 Q23.1 059 062 046 106 Q28.1 031 031 062 074 Q28.4 013 013 032 -.015 007 019 023 031 016 016 052 063 032 013 076 039 047 065 -.080 024 222 008 056 014 255 067 017 309 436 012 015 246 -.002 006 Modification Indices (Group number - SISP Maturity - Full SAM Model) Covariances: (Group number - SISP Maturity - Full SAM Model) M.I Par Change d2 < > r2 1.023 -.033 d1 < > r2 1.233 016 e8 < > r1 1.099 -.006 e8 < > d5 2.119 013 e8 < > d2 1.416 -.021 e8 < > d6 2.996 -.033 e5 < > e8 1.513 026 e4 < > d3 1.396 044 e4 < > e6 2.672 062 e3 < > r3 3.412 019 e3 < > r2 4.284 -.074 e3 < > d3 4.388 -.077 e3 < > d6 2.719 054 e3 < > e8 2.683 -.031 e3 < > e6 2.789 -.063 e10 < > e4 1.340 -.020 e9 < > e8 1.778 014 e7 < > d5 2.518 -.014 e7 < > d6 4.844 043 e7 < > e5 1.594 -.027 e7 < > e3 3.308 035 e1 < > d5 3.339 -.012 e1 < > d3 3.661 032 e1 < > d4 2.470 -.011 e1 < > e8 5.828 -.021 e1 < > e5 4.886 036 e1 < > e9 4.198 -.017 e2 < > d5 2.192 009 e2 < > d6 1.812 -.019 e2 < > d4 3.070 012 e2 < > e8 4.544 017 e2 < > e5 1.723 -.020 e2 < > e9 1.294 009 e11 < > d2 3.926 058 e11 < > d1 2.488 -.020 e11 < > e8 1.501 -.023 e11 < > e5 1.140 -.038 e11 < > e3 1.594 040 e11 < > e7 4.583 040 e11 < > e1 1.527 -.018 e12 < > d2 1.686 -.039 e12 < > e4 2.631 -.054 e12 < > e10 2.137 026 e12 < > e9 1.341 -.021 e12 < > e1 3.651 028 Appendix F 449 Appendix F Variances: (Group number - SISP Maturity - Full SAM Model) M.I Par Change Regression Weights: (Group number - SISP Maturity - Full SAM Model) M.I Q45.7 < Collaboration 1.541 Q45.7 < Viability 1.966 Q45.7 < Q36.3 3.057 Q45.7 < Q18.5 1.316 Q45.7 < Q20.5 3.501 Q45.7 < Q23.1 1.017 Q45.7 < Q28.1 2.283 Q45.7 < Q28.4 1.488 Q24.4 < Q20.5 2.838 Q36.4 < Q26.2 1.148 Q36.4 < Q28.4 1.183 Q36.3 < Efficiency 1.533 Q36.3 < Stakeholders'_Designation 3.038 Q36.3 < Viability 1.513 Q36.3 < Q45.7 1.953 Q36.3 < Q26.2 3.769 Q36.3 < Q24.4 1.691 Q36.3 < Q28.1 1.997 Q44.5 < Q28.4 1.075 Q18.5 < Q45.7 1.301 Q18.5 < Q20.5 2.416 Q30.4 < Maneuverability 1.117 Q30.4 < Collaboration 1.107 Q30.4 < Viability 3.150 Q30.4 < Q36.3 3.069 Q30.4 < Q20.5 1.077 Q30.4 < Q28.1 4.781 Q30.4 < Q28.4 1.086 Q20.5 < Time_Dimension 1.859 Q20.5 < Stakeholders'_Designation 1.201 Q20.5 < Q45.7 2.870 Q20.5 < Q24.4 3.867 Q20.5 < Q18.5 4.384 Q20.5 < Q28.4 1.557 Q23.1 < Technology 1.487 Q23.1 < Q45.7 3.604 Q23.1 < Q18.5 1.544 Q28.1 < Collaboration 2.007 Q28.1 < Form & Content 1.036 Q28.1 < Q36.4 1.745 Q28.1 < Q36.3 2.611 Q28.1 < Q30.4 2.645 Q28.1 < Q20.5 1.800 Q28.4 < Q36.4 2.046 Q28.4 < Q44.5 1.019 Q28.4 < Q20.5 2.290 Par Change -.066 -.064 -.054 067 -.135 077 -.046 -.036 234 041 -.054 -.106 -.104 095 -.125 -.074 -.054 073 028 057 -.106 215 056 081 054 076 067 031 -.122 029 -.068 036 -.093 028 087 072 052 126 -.239 068 084 146 -.163 -.077 105 192 Model Fit Summary CMIN Model SISP Maturity - Full SAM Model Saturated model Independence model NPAR 34 78 12 RMR, GFI Model SISP Maturity - Full SAM Model Saturated model Independence model RMR 021 000 145 CMIN 56.157 000 693.628 GFI 965 1.000 635 DF 44 66 P 103 CMIN/DF 1.276 000 10.510 AGFI 937 PGFI 544 569 538 Baseline Comparisons Appendix F 450 Appendix F SISP Maturity - Full SAM Model Saturated model Independence model NFI Delta1 919 1.000 000 Parsimony-Adjusted Measures Model SISP Maturity - Full SAM Model Saturated model Independence model PRATIO 667 000 1.000 PNFI 613 000 000 NCP Model SISP Maturity - Full SAM Model Saturated model Independence model NCP 12.157 000 627.628 LO 90 000 000 546.759 FMIN Model SISP Maturity - Full SAM Model Saturated model Independence model FMIN 217 000 2.678 RMSEA Model SISP Maturity - Full SAM Model Independence model RMSEA 033 192 LO 90 000 179 AIC Model SISP Maturity - Full SAM Model Saturated model Independence model AIC 124.157 156.000 717.628 BCC 127.750 164.244 718.896 ECVI Model SISP Maturity - Full SAM Model Saturated model Independence model ECVI 479 602 2.771 Model RFI rho1 879 IFI Delta2 981 1.000 000 000 F0 047 000 2.423 LO 90 432 602 2.459 TLI rho2 971 000 CFI 981 1.000 000 PCFI 654 000 000 HI 90 35.534 000 715.945 LO 90 000 000 2.111 HI 90 137 000 2.764 HI 90 056 205 PCLOSE 881 000 BIC 245.220 433.733 760.356 HI 90 570 602 3.112 CAIC 279.220 511.733 772.356 MECVI 493 634 2.776 HOELTER Model SISP Maturity - Full SAM Model Independence model Appendix F HOELTER 05 279 33 HOELTER 01 317 36 451 Appendix G Appendix G Hypothesis H14 Organisational Size versus SISP Maturity Regression Weights Estimate S.E C.R Size of Organisation < - SISP Maturity 1.000 Q12 < - Size of Organisation 1.000 Q11 < - Size of Organisation 848 064 13.283 SISP_levels < - SISP Maturity 370 083 4.476 Q10 < - Size of Organisation 795 077 10.296 P Label *** par_1 *** par_2 *** par_3 Residual Covariances SISP_levels Q12 Q11 Q10 SISP_levels 000 039 -.003 -.074 Q12 Q11 Q10 000 -.005 -.009 000 015 000 Hypothesis H1 SISP Benefit versus SISP Maturity Regression Weights Estimate Benefit of SISP < - SISP Maturity 1.000 Q41.5 < - Benefit of SISP 1.000 Q41.4 < - Benefit of SISP 948 Q41.6 < - Benefit of SISP 932 SISP_levels < - SISP Maturity 475 Q41.8 < - Benefit of SISP 1.011 Q41.13 < - Benefit of SISP 991 S.E .058 054 070 057 057 C.R P 16.299 17.121 6.748 17.842 17.342 *** *** *** *** *** Label par_1 par_2 par_3 par_4 par_5 Residual Covariances Q41.13 SISP_levels Q41.5 Q41.6 Q41.4 Q41.8 Q41.13 000 -.037 000 011 034 -.010 SISP_levels Q41.5 Q41.6 Q41.4 Q41.8 000 042 002 -.050 -.003 000 -.029 -.027 020 000 078 -.003 000 -.037 000 Hypothesis H4 SISP Alignment versus SISP Maturity Regression Weights Estimate SISP/Business_Alignment < - SISP Maturity 1.000 Business/SISP_Alignment < - SISP Maturity 1.088 Q36.1 < - SISP/Business_Alignment 1.000 Q36.3 < - SISP/Business_Alignment 1.033 Q36.7 < - Business/SISP_Alignment 1.000 Q36.10 < - Business/SISP_Alignment 826 Q36.11 < - Business/SISP_Alignment 1.044 Q36.5 < - SISP/Business_Alignment 1.293 Q36.6 < - SISP/Business_Alignment 1.098 Q36.12 < - Business/SISP_Alignment 931 Appendix G S.E C.R P Label 138 7.860 *** par_10 092 11.262 *** par_1 121 123 111 135 107 6.821 8.474 11.679 8.148 8.738 *** *** *** *** *** par_2 par_3 par_4 par_5 par_6 452 Appendix G Estimate S.E C.R < - SISP Maturity 1.000 < - SISP/Business_Alignment 1.197 121 9.885 SISPlevel Q36.4 P *** Label par_7 Residual Covariances Q36.4 007 069 -.006 -.004 001 010 039 -.013 013 038 Q36.4 Q36.12 Q36.6 Q36.5 SISPlevel Q36.11 Q36.10 Q36.7 Q36.3 Q36.1 Q36.12 Q36.6 Q36.5 SISPlevel Q36.11 Q36.10 Q36.7 Q36.3 Q36.1 000 015 015 -.001 -.018 -.019 -.005 037 053 006 035 -.039 -.042 -.133 -.112 016 038 005 -.020 -.002 -.032 028 025 064 -.019 -.036 -.052 -.011 039 051 -.001 062 021 052 059 000 026 -.020 -.037 000 028 -.005 036 056 075 Hypothesis H2 SISP Alignment versus SISP Maturity Regression Weights Estimate SISP Approach < - SISP Success 1.000 Q21.6 < - SISP Approach 1.095 Q21.4 < - SISP Approach 1.174 Q21.3 < - SISP Approach 1.135 Q21.2 < - SISP Approach 1.000 Q21.5 < - SISP Approach 1.003 Q42.1 < - SISP Success 1.000 S.E C.R P Label 171 164 148 6.422 7.146 7.663 *** *** *** par_1 par_2 par_3 162 6.201 *** par_4 Residual Covariances Q42.1 Q21.4 Q21.6 Q21.5 Q21.3 Q21.2 Q42.1 000 -.020 -.006 008 020 059 Q21.4 Q21.6 Q21.5 Q21.3 Q21.2 000 008 005 -.012 004 000 -.015 019 -.028 000 005 -.005 000 000 000 Hypothesis H11 SISP Content versus SISP Maturity Regression Weights Estimate SISP Content < - SISP Maturity Level 057 Q19.4 < - SISP Content 5.764 Q28.2 < - SISP Content 1.000 Q28.1 < - SISP Content 1.095 Q28.3 < - SISP Content 1.152 Q19.3 < - SISP Content 4.397 Q19.5 < - SISP Content 4.776 SISP_levels < - SISP Maturity Level 1.000 S.E C.R .015 3.854 1.063 5.422 P *** *** Label par_2 par_1 258 218 824 903 *** *** *** *** par_3 par_4 par_5 par_6 4.252 5.288 5.333 5.288 Residual Covariances Q19.5 Q19.3 Q28.3 Q28.1 SISP_levels Q19.4 Q28.2 Q19.5 000 -.011 -.035 000 029 003 012 Q19.3 Q28.3 Q28.1 SISP_levels Q19.4 Q28.2 000 -.018 011 -.012 011 -.007 004 008 010 014 006 000 031 -.017 010 000 -.018 034 000 -.012 000 Hypothesis H7 SISP Policy versus SISP Success Appendix G 453 Appendix G Regression Weights Estimate S.E C.R SISP Cultural_Policy < - SISP Success 1.000 Q33.4 < - SISP Cultural_Policy 1.000 Q33.5 < - SISP Cultural_Policy 851 050 16.964 Q42.1 < - SISP Success 1.000 Q33.7 < - SISP Cultural_Policy 896 057 15.610 P Label *** par_1 *** par_2 Residual Covariances Q33.7 Q42.1 Q33.5 Q33.4 Q33.7 000 026 -.016 007 Q42.1 Q33.5 Q33.4 000 028 -.032 000 003 000 Hypothesis H8 SISP Team Knowledge versus SISP Success Regression Weights Estimate SISP Team Knowledge < - SISP Success 1.000 Q20.2 < - SISP Team Knowledge 1.000 Q20.3 < - SISP Team Knowledge 971 Q20.6 < - SISP Team Knowledge 1.008 Q20.5 < - SISP Team Knowledge 952 Q42.1 < - SISP Success 1.000 Q20.1 < - SISP Team Knowledge 1.009 S.E C.R P Label 049 051 051 19.971 19.639 18.783 *** *** *** par_1 par_2 par_3 047 21.421 *** par_4 Residual Covariances Q20.1 Q20.5 Q20.6 Q42.1 Q20.3 Q20.2 Q20.1 000 -.010 -.002 008 -.014 021 Appendix G Q20.5 Q20.6 Q42.1 Q20.3 Q20.2 000 000 -.024 028 -.014 000 007 020 -.022 000 -.010 008 000 -.008 000 454