A Local-State Government Spatial Data Sharing Partnership

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A Local-State Spatial Data Sharing Partnership Model to Facilitate SDI Development correlations which may provide a useful insight into the final results of the regression analysis. Finally, the 13 factors were used as predictor variables in regression analysis to model the single outcome factor. This identified which of the grouped factors contributed more positively to the successful outcomes of the partnership. 6.4.2 Factor Analysis The variables used in the questionnaire included a range of measurement types including continuous numeric values (e.g. number of properties), descriptive ordinal/internal values (e.g. Likert scale – agree, strongly agree) and categorical or nominal values. The categorical or nominal variables were not suitable for factor analysis and were therefore not utilised. Prior to the factor analysis the continuous numeric variables and the ordinal Likert variables were transformed to numerical interval classes between 0 and 5. Factor analysis is a well documented technique that assists in identifying clusters of variables that may be logically grouped into a smaller set of these variables which have common underlying constructs or factors. Factor analysis generally can be applied when: 1. the range of variables being analysed are at least of an ordinal level of measurement; 2. the variables are normally distributed; 3. the relationship between variables is reasonably linear; 4. the sample is at least 100; 5. there are more participants than variables and extracted factors. 188 (Brace et al. 2006, p. 310) Once the appropriate transformations had been completed, the data from the LGA responses satisfied these criteria. The factor analysis was undertaken using the standard principal component analysis method to reduce the total number of independent variables from 36 to 13 grouped factor components. Table 6.4 lists the 13 new components (factors) and the original 36 independent variables with their factor loadings. A full listing of the factor analysis is given in Appendix 6
Chapter 6 – Results of Partnership Case Studies at Local Government Level Table 6.4 Factor analysis components and initial variables Components from Factor Analysis Initial Independent Variables for Factor Analysis (Factor Loadings) Component 1: Size Number of Properties (0.932) Number of Staff (0.937) Number of GIS staff (0.925) Component 2: Organisational Support and Attitudes 189 Assessment of ICT Capacity (0.695) Level of Management Support (0.670) Level of Resourcing of the GIS (0.777) Internal Policy Encourages Data Use (0.607) Staff know where to find data (0.503) Technology Has Made SI More Accessible (0.464) Capacity to Share (0.539) Component 3: Data Accessibility/Maturity Percentage of Staff with Access to GIS (0.419) Internet Web Mapping is available ((0.679 Overall maturity of SI (0.581) External Policy Encourages Data Use (0.486) Accessibility Improves Council's Business (0.633) Component 4: Internal Accessibility Level of integration (0.549) Percentage of Staff with Access to GIS (0.419) Staff know where to find data (0.483) Component 5: Access to State Data Cost of State data is acceptable (0.817) Limitations by state on data is acceptable (0.781) Component 6: Level of concern on data restrictions Legal liability limits sharing (0.688) Copyright limits sharing (0.647) Privacy limits sharing (0.832) Component 7: Standards and Metadata Consider standards in GIS development (0.682) Recording of metadata (0.678) Component 8: Use of State Data and Restrictions Place Restriction on Use of Data (0.737) Level of Use of State Data (0.731) Component 9: Organisational Change Level of Staff Turnover (0.822) Level of Organisational Restructuring (0.546) Average Level of Collaboration (-0.442) Component 10: Staff Growth and Training Trend in staff numbers (0.499) Access to Training (0.795) Component 11: Business Needs Share data to meet business needs (0.808) Length of time having GIS (-0.582) Component 12: Policy on External Access to Data Single metadata repository (0.764) Number of collaborations (-0.429) Component 13: Length of Collaboration Term of Collaboration (0.859) Note: Variables with factor loadings
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A Local-State Government Spatial Da
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Abstract In the past decade efforts
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Acknowledgements Completion of a Ph
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Table of Contents DECLARATION .....
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APPENDIX 5 - INTER-STATE DIFFERENCE
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FIGURE 6.7 USE OF WEB MAPPING .....
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List of Acronyms ACT AUSTRALIAN CAP
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Operational Definitions The followi
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1 Chapter 1 Introduction Chapter 1
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1.1 Background to Research 3 Chapte
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5 Chapter 1 - Introduction is havin
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7 Chapter 1 - Introduction enforcem
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9 Chapter 1 - Introduction The rese
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11 Chapter 1 - Introduction organis
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13 Chapter 1 - Introduction three c
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15 Chapter 2 - Spatial Data and SDI
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2.1 Introduction 17 Chapter 2 - Spa
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2.2.6 Property Information as a Fun
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Chapter 3 - Collaboration, Partners
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3.1 Introduction Chapter 3 - Collab
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Dimensions Actors Lower ranking mem
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91 Chapter 4 - Research Design and
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4.1 Introduction 93 Chapter 4 - Res
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Chapter 5 - Results of Partnership
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5.1 Introduction Chapter 5 - Result
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Employees '000s 500.0 450.0 400.0 3
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Data Exchange Process Chapter 5 - R
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Page 253 and 254: 235 References Cameron, D 2001, 'Th
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239 References Hesse, WJ & Williams
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241 References Masser, I 2002, Repo
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243 References Onsrud, HJ & Rushton
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Tashakkori, A & Teddlie, C (eds) 20
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247 References
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Appendix 1 - Publications Relating
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Appendix 1 - Publications Relating
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Appendix 2 - Semi Structured Interv
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Appendix 2 - Semi Structured Interv
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Appendix 3 257 Appendix 3 - Local G
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259 Appendix 3 - Local Government Q
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Part 1 - Your Organisation 261 Appe
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Q4e: The costs to acquire State gov
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Part 6 - About People 267 Appendix
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Appendix4 - Open Ended Questionnair
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54 Provision of Aerial photos at a
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APPENDIX 5 293 Appendix 5 - Inter-S
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ANOVA ANALYSIS 295 Appendix 5 - Int
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297 Appendix 5 - Inter-State Differ
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Kruskal Wallis Test Statistics(a,b)
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APPENDIX 6 FACTOR ANALYSIS 301 Appe
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Communalities 303 Appendix 6 - Fact
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305 Component Matrix(a) Component A
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APPENDIX 7 307 Appendix 7 - Correla
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Size_Index Org_support Ext_access_p
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APPENDIX 8 311 Appendix 8 - Multipl
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Variables Entered/Removed(b) Model
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A Local-State Government Spatial Data Sharing Partnership

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