Research Center for Construction Innovation regarding the Advisory Services at your own risk. Construction Innovation expressly disclaims any liability or responsibility to anyone in respect of anything done or omitted to be done by anyone in reliance on this Report or the information provided. The impact of innovation on public policy is an area that has not yet been explored and which this report aims to address in part through an examination of the public policy implications of construction innovation research.
This report can be supplied to the Construction Industry Business Environment project, which has been generously funded by the CRC for Construction Innovation. This report undertakes an exploratory analysis of construction innovation research projects to answer the question "What are the public policy implications of construction innovation research?". The outcomes of the project were coded according to the policy area, along with the perceived likelihood and benefit of any policy intervention.
As the years progressed, the perceived likelihood that construction innovation research would have a policy impact increased. However, the remaining relationships could not be simplified due to the relatively small sample size.
INTRODUCTION
LITERATURE REVIEW
- Inputs into Construction Innovation research projects
- Innovation (outputs of Construction Innovation reseach projects)
- Types of innovation
- Stage of Innovation
- Phases of Construction
- Type of construction
- Public policy implications of construction innovation research (Outcomes)
- Policy areas
- Policy Impact
- Relationship between innovation and policy
- Research questions
- Cooperative Research Centres as examples of ‘triple helix’ innovation relationships
- Model for relationships between the innovations developed by research projects and
- Research Questions
According to the framework given in Figure 1, by focusing on the relationships between inputs, outputs and results, a framework for assessing the policy implications of research on Construction Innovation is possible. The year is also seen as a contribution, as the increased ability of Construction Innovation to deliver research projects and the increased relationships between research partners are likely to result in increased performance of the research portfolio. Within the CRC for Construction Innovation, different partners and projects focus on specific types of construction.
Together, this provides a more robust assessment of the policy implications of Construction Innovation research than just a policy area on its own. However, much of the construction innovation literature tends to focus on the relationship that public policy has on innovation, rather than the influence of innovation on policy. What relationship, if any, exists between Construction Innovation research – particularly the inputs, outputs and outcomes of innovation?”.
While exploring possible relationships between inputs, outputs and outcomes, a collection of information related to the operation of Construction Innovation itself will be developed. The Construction Innovation CRC is indeed an example of a collaborative approach to innovation between government, industry and university.
RESEARCH METHODS
Content analysis
Data constraints and considerations
DISCUSSION & ANALYSIS
Relationships between independent variables
- Descriptive analysis of independent variables
- Hypothesised relationships between independent variables
- Bivariate analysis of independent variables
- Analysis of variance between dependant variables
- Summary of relationships between independent variables
Relationships between the independent variables and the mediating variables
- Chi square analysis of relationships between mediating variables and independent
- Analysis of variance between mediating variables and independent variables
- Summary of relationships between independent variables and mediating variables
Relationships between the mediating variables
- Chi square of relationships between mediating variables
- Summary of relationships between mediating variables
- Chi squares of relationships between dependant variables and mediating variables
- Analysis of variables between dependent and mediating variables
- Summary of relationships between dependent and mediating variables
Relationships between the dependant variables and the independent variables
Multiple regression analysis to test the mediation variables effect on the independent
- Linear multiple regression analysis
- Results of Linear multiple regression
An analysis of variance was conducted to determine the relationship between total project support (budget plus in-kind) and innovation stage. An analysis of variance was conducted to investigate the relationship between the number of research participants and the type of innovation. An analysis of variance was conducted to determine the relationship between the number of research participants and the stage of innovation.
An analysis of variance was conducted to determine the relationship between the number of research participants and the innovation stage. A Chi-square was performed to determine any relationships between the type of innovation and the innovation phase. A chi-square was conducted to examine the relationship between construction phase and innovation type.
A chi-square was undertaken to examine the relationship between the type of innovation (product, process and organizational innovation) and the type of construction activity (building, infrastructure, or both). A chi-square analysis was undertaken to examine the relationship between construction phase (Design, construction, FM/AM, Procurement) and type of construction (building, infrastructure or both). A chi-square analysis was undertaken to examine the relationship between policy area and construction phase.
A chi-square analysis was undertaken to examine the relationship between policy area and type. An analysis of variance was undertaken to examine the relationship between the stage of innovation and the likelihood of a policy outcome. Thus, stage of innovation mediated the relationship between total support and likelihood of policy outcome.
Test for existence of a triple helix of relationships
The government does not only fund construction innovation, as government participants are actively engaged in research projects. The large dots in the center are the different types of participants - red for researchers, green for industry and black for government.
IMPLICATIONS OF THE RESEARCH
Implications for Gann and Salter (innovation as a system)
Implications of the research for the triple helix approach to innovation
Implications for future research
CONCLUSION 50
The practice of social research. 1996) "Steering not rowing: Coordination and control in the management of public services in Britain and Germany" International Journal of Public Sector Management 9(5/6), pp. Upper Saddle River, J.J.: Prentice Hall. 2000) “The Dynamics of Innovation: From National Systems and Mode 2 to a Triple Helix. 2005) Research and Evaluation in Education and Psychology: Integrating Diversity with Quantitative, Qualitative, and Mixed Methods. 2000) Social Research Methods: Qualitative and Quantitative Approaches.
The primary method in this case is policy analysis (document analysis), although some semi-structured interviews will be required. This phase will explicitly explore the idea of the triple helix for innovations developed within the CRC CI. The perceived impact by key stakeholders of the current regulatory framework in relation to productivity and innovation will be identified in stakeholder consultation.
Contributions will be sought from interested parties and data will be collected through interviews, focus groups and secondary text analysis. The CIBE project team will determine the terms of reference for such an investigation. Each study will result in a set of recommendations that promote coordination between jurisdictions in Australia and reduce the effects of the overlap noted above.
Each study will follow a case study methodology and will include focus groups, semi-structured interviews and document analysis. These case studies will be narrowed down in consultation with business and government and may include example projects that demonstrate the benefits of specific ICT tools for government and business.
Attachment B – List of Projects
To determine the relationship between resource allocation and innovation, a number of descriptive variables were used. Project title Unique identification To distinguish the projects from each other Year approved Scale To enable grouping of projects by year Research. Scale Number of research participants in each project Total support Scale Combined sum of total budget and in-kind.
In this research project, the type of innovation is seen as a moderating variable, as it is the specific research itself that is likely to influence policy outcomes, rather than the number of researchers, for example. Innovation Type Nominal To identify the type of innovation implemented in projects (product, process and organizational) Stage of. Nominal To identify the innovation stage (idea, development, proof of concept, alpha/beta, exploitation).
Nominal To identify which phase of construction the innovation is focused on (design, construction, asset management, procurement). The policy area was seen as a dependent variable, as the aim was to identify the policy implications of research into construction innovation. Nominal policy area To identify the main policy area for policy innovation (ICT, human policies such as working environment, organisation, sustainability, procurement).
Ordinal Each innovation was scored from little benefit to great benefit on a 5-point Likert scale for 4 policy instruments (education, finance, action, regulation). This variable reports the combined total of the total perceived benefit of policies associated with the innovation. Ordinal Each innovation was scored from unlikely to very likely on a 5-point Likert scale for 4 policy instruments (education, finance, action, regulation).
This variable is a combined count of the total perceived probability of a policy outcome related to the innovation.
Attachment C - Database form
Attachment D - Full table of Bivariate correlations between continuous variables
