Predication and propagation : a method for analyzing evaluative meanings in technology policy

In this article I outline and demonstrate a synthesis of the methods developed by Lemke (1998) and Martin (2000) for analyzing evaluations in English. I demonstrate the synthesis using examples from a 1.3-million-word technology policy corpus drawn from institutions at the local, state, national, and supranational levels. Lemke's (1998) critical model is organized around the broad 'evaluative dimensions' that are deployed to evaluate propositions and proposals in English. Martin's (2000) model is organized with a more overtly systemic-functional orientation around the concept of 'encoded feeling'. In applying both these models at different times, whilst recognizing their individual usefulness and complementarity, I found specific limitations that led me to work towards a synthesis of the two approaches. I also argue for the need to consider genre, media, and institutional aspects more explicitly when claiming intertextual and heteroglossic relations as the basis for inferred evaluations. A basic assertion made in this article is that the perceived Desirability of a process, person, circumstance, or thing is identical to its 'value'. But the Desirability of anything is a socially and thus historically conditioned attribution that requires significant amounts of institutional inculcation of other 'types' of value-appropriateness, importance, beauty, power, and so on. I therefore propose a method informed by critical discourse analysis (CDA) that sees evaluation as happening on at least four interdependent levels of abstraction.

An innovative learning model for teaching architectural technology using building information modelling : a Queensland University of Technology perspective

In architecture courses, instilling a wider understanding of the industry specific representations practiced in the Building Industry is normally done under the auspices of Technology and Science subjects. Traditionally, building industry professionals communicated their design intentions using industry specific representations. Originally these mainly two dimensional representations such as plans, sections, elevations, schedules, etc. were produced manually, using a drawing board. Currently, this manual process has been digitised in the form of Computer Aided Design and Drafting (CADD) or ubiquitously simply CAD. While CAD has significant productivity and accuracy advantages over the earlier manual method, it still only produces industry specific representations of the design intent. Essentially, CAD is a digital version of the drawing board. The tool used for the production of these representations in industry is still mainly CAD. This is also the approach taken in most traditional university courses and mirrors the reality of the situation in the building industry. A successor to CAD, in the form of Building Information Modelling (BIM), is presently evolving in the Construction Industry. CAD is mostly a technical tool that conforms to existing industry practices. BIM on the other hand is revolutionary both as a technical tool and as an industry practice. Rather than producing representations of design intent, BIM produces an exact Virtual Prototype of any building that in an ideal situation is centrally stored and freely exchanged between the project team. Essentially, BIM builds any building twice: once in the virtual world, where any faults are resolved, and finally, in the real world. There is, however, no established model for learning through the use of this technology in Architecture courses. Queensland University of Technology (QUT), a tertiary institution that maintains close links with industry, recognises the importance of equipping their graduates with skills that are relevant to industry. BIM skills are currently in increasing demand throughout the construction industry through the evolution of construction industry practices. As such, during the second half of 2008, QUT 4th year architectural students were formally introduced for the first time to BIM, as both a technology and as an industry practice. This paper will outline the teaching team’s experiences and methodologies in offering a BIM unit (Architectural Technology and Science IV) at QUT for the first time and provide a description of the learning model. The paper will present the results of a survey on the learners’ perspectives of both BIM and their learning experiences as they learn about and through this technology.

At breaking point? Challenges for Australian film policy through the lens of genre (horror) films

Cultural policy settings attempting to foster the growth and development of the Australian feature film industry in era of globalisation are coming under increasing pressure. Global forces and emerging production and distribution models are challenging the “narrowness” of cultural policy – mandating a particular film culture, circumscribing certain notions of value and limiting the variety of films produced through cultural policy driven subvention models. Australian horror film production is an important case study. Horror films are a production strategy well suited to the financial limitations of the Australian film industry with competitive advantages for producers against international competitors. However, emerging within a “national” cinema driven by public subsidy and social/cultural objectives, horror films – internationally oriented with a low-culture status – have been severely marginalised within public funding environments. This paper introduces Australian horror film production, and examines the limitations of cultural policy, and the impacts of these questions for the Producer Offset.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Building Information Modelling for FM at Sydney Opera House

“SOH see significant benefit in digitising its drawings and operation and maintenance manuals. Since SOH do not currently have digital models of the Opera House structure or other components, there is an opportunity for this national case study to promote the application of Digital Facility Modelling using standardized Building Information Models (BIM)”. The digital modelling element of this project examined the potential of building information models for Facility Management focusing on the following areas: • The re-usability of building information for FM purposes • BIM as an Integrated information model for facility management • Extendibility of the BIM to cope with business specific requirements • Commercial facility management software using standardised building information models • The ability to add (organisation specific) intelligence to the model • A roadmap for SOH to adopt BIM for FM The project has established that BIM – building information modelling - is an appropriate and potentially beneficial technology for the storage of integrated building, maintenance and management data for SOH. Based on the attributes of a BIM, several advantages can be envisioned: consistency in the data, intelligence in the model, multiple representations, source of information for intelligent programs and intelligent queries. The IFC – open building exchange standard – specification provides comprehensive support for asset and facility management functions, and offers new management, collaboration and procurement relationships based on sharing of intelligent building data. The major advantages of using an open standard are: information can be read and manipulated by any compliant software, reduced user “lock in” to proprietary solutions, third party software can be the “best of breed” to suit the process and scope at hand, standardised BIM solutions consider the wider implications of information exchange outside the scope of any particular vendor, information can be archived as ASCII files for archival purposes, and data quality can be enhanced as the now single source of users’ information has improved accuracy, correctness, currency, completeness and relevance. SOH current building standards have been successfully drafted for a BIM environment and are confidently expected to be fully developed when BIM is adopted operationally by SOH. There have been remarkably few technical difficulties in converting the House’s existing conventions and standards to the new model based environment. This demonstrates that the IFC model represents world practice for building data representation and management (see Sydney Opera House – FM Exemplar Project Report Number 2005-001-C-3, Open Specification for BIM: Sydney Opera House Case Study). Availability of FM applications based on BIM is in its infancy but focussed systems are already in operation internationally and show excellent prospects for implementation systems at SOH. In addition to the generic benefits of standardised BIM described above, the following FM specific advantages can be expected from this new integrated facilities management environment: faster and more effective processes, controlled whole life costs and environmental data, better customer service, common operational picture for current and strategic planning, visual decision-making and a total ownership cost model. Tests with partial BIM data – provided by several of SOH’s current consultants – show that the creation of a SOH complete model is realistic, but subject to resolution of compliance and detailed functional support by participating software applications. The showcase has demonstrated successfully that IFC based exchange is possible with several common BIM based applications through the creation of a new partial model of the building. Data exchanged has been geometrically accurate (the SOH building structure represents some of the most complex building elements) and supports rich information describing the types of objects, with their properties and relationships.

Digital Modelling

This Digital Modelling Report incorporates the previous research completed for the FM Exemplar Project utilising the Sydney Opera House as a case study. The research has demonstrated significant benefits in digitising design documentation and operational and maintenance manuals. Since Sydney Opera House do not have digital models of its structure, there is an opportunity to investigate the application of Digital Facility Modelling using standardised Building Information Models (BIM). The digital modelling research project has examined the potential of standardised building information models to develop a digital facility model supporting facilities management (FM). The focus of this investigation was on the following areas: • The re-usability of standardised building information models (BIM) for FM purposes. • The potential of BIM as an information framework acting as integrator for various FM data sources. • The extendibility and flexibility of the BIM to cope with business specific data and requirements. • Commercial FM software using standardised building information models. • The ability to add (organisation-specific) intelligence to the model. • A roadmap for Sydney Opera House to adopt BIM for FM.

A framework for assessing social policy inclusion proposals

This document outlines a framework that could be used by government agencies in assessing policy interventions aimed at achieving social outcomes from government construction contracts. The framework represents a rational interpretation of the information gathered during the multi-outcomes construction policies project. The multi-outcomes project focused on the costs and benefits of using public construction contracts to promote the achievement of training and employment and public art objectives. The origin of the policy framework in a cost-benefit appraisal of current policy interventions is evidenced by its emphasis on sensitivity to policy commitment and project circumstances (especially project size and scope).The quantitative and qualitative analysis conducted in the multi-outcomes project highlighted, first, that in the absence of strong industry commitment to policy objectives, policy interventions typically result in high levels of avoidance activity, substantial administrative costs and very few benefits. Thus, for policy action on, for example, training or local employment to be successful compliance issues must be adequately addressed. Currently it appears that pre-qualification schemes (similar to the Priority Access Scheme) and schemes that rely on measuring, for example, the training investments of contractors within particular projects do not achieve high levels of compliance and involve significant administrative costs. Thus, an alternative is suggested in the policy framework developed here: a levy on each public construction project – set as a proportion of the total project costs. Although a full evaluation of this policy alternative was beyond the scope of the multi-outcomes construction policies project, it appears to offer the potential to minimize the transaction costs on contractors whilst enabling the creation of a training agency dedicated to improving the supply of skilled construction labour. A recommendation is thus made that this policy alternative be fully researched and evaluated. As noted above, the outcomes of the multi-outcomes research project also highlighted the need for sensitivity to project circumstances in the development and implementation of polices for public construction projects. Ideally a policy framework would have the flexibility to respond to circumstances where contractors share a commitment to the policy objectives and are able to identify measurable social outcomes from the particular government projects they are involved in. This would involve a project-by-project negotiation of goals and performance measures. It is likely to only be practical for large, longer term projects.

Nation & internation practices in decision support tools in road asset management

This document provides a review of international and national practices in investment decision support tools in road asset management. Efforts were concentrated on identifying analytic frameworks, evaluation methodologies and criteria adopted by current tools. Emphasis was also given to how current approaches support Triple Bottom Line decision-making. Benefit Cost Analysis and Multiple Criteria Analysis are principle methodologies in supporting decision-making in Road Asset Management. The complexity of the applications shows significant differences in international practices. There is continuing discussion amongst practitioners and researchers regarding to which one is more appropriate in supporting decision-making. It is suggested that the two approaches should be regarded as complementary instead of competitive means. Multiple Criteria Analysis may be particularly helpful in early stages of project development, say strategic planning. Benefit Cost Analysis is used most widely for project prioritisation and selecting the final project from amongst a set of alternatives. Benefit Cost Analysis approach is useful tool for investment decision-making from an economic perspective. An extension of the approach, which includes social and environmental externalities, is currently used in supporting Triple Bottom Line decision-making in the road sector. However, efforts should be given to several issues in the applications. First of all, there is a need to reach a degree of commonality on considering social and environmental externalities, which may be achieved by aggregating the best practices. At different decision-making level, the detail of consideration of the externalities should be different. It is intended to develop a generic framework to coordinate the range of existing practices. The standard framework will also be helpful in reducing double counting, which appears in some current practices. Cautions should also be given to the methods of determining the value of social and environmental externalities. A number of methods, such as market price, resource costs and Willingness to Pay, are found in the review. The use of unreasonable monetisation methods in some cases has discredited Benefit Cost Analysis in the eyes of decision makers and the public. Some social externalities, such as employment and regional economic impacts, are generally omitted in current practices. This is due to the lack of information and credible models. It may be appropriate to consider these externalities in qualitative forms in a Multiple Criteria Analysis. Consensus has been reached in considering noise and air pollution in international practices. However, Australia practices generally omitted these externalities. Equity is an important consideration in Road Asset Management. The considerations are either between regions, or social groups, such as income, age, gender, disable, etc. In current practice, there is not a well developed quantitative measure for equity issues. More research is needed to target this issue. Although Multiple Criteria Analysis has been used for decades, there is not a generally accepted framework in the choice of modelling methods and various externalities. The result is that different analysts are unlikely to reach consistent conclusions about a policy measure. In current practices, some favour using methods which are able to prioritise alternatives, such as Goal Programming, Goal Achievement Matrix, Analytic Hierarchy Process. The others just present various impacts to decision-makers to characterise the projects. Weighting and scoring system are critical in most Multiple Criteria Analysis. However, the processes of assessing weights and scores were criticised as highly arbitrary and subjective. It is essential that the process should be as transparent as possible. Obtaining weights and scores by consulting local communities is a common practice, but is likely to result in bias towards local interests. Interactive approach has the advantage in helping decision-makers elaborating their preferences. However, computation burden may result in lose of interests of decision-makers during the solution process of a large-scale problem, say a large state road network. Current practices tend to use cardinal or ordinal scales in measure in non-monetised externalities. Distorted valuations can occur where variables measured in physical units, are converted to scales. For example, decibels of noise converts to a scale of -4 to +4 with a linear transformation, the difference between 3 and 4 represents a far greater increase in discomfort to people than the increase from 0 to 1. It is suggested to assign different weights to individual score. Due to overlapped goals, the problem of double counting also appears in some of Multiple Criteria Analysis. The situation can be improved by carefully selecting and defining investment goals and criteria. Other issues, such as the treatment of time effect, incorporating risk and uncertainty, have been given scant attention in current practices. This report suggested establishing a common analytic framework to deal with these issues.

Public policy implications of construction innovation research

This report undertakes an exploratory analysis of Construction Innovation research projects in order to answer the question “What are the public policy implications of Construction Innovation research?”

A primer in public policy for the construction industry

The purpose of this document is to introduce non-specialists to the discipline and practice of public policy, particularly in relation to the construction sector in Australia. In order to do this, a brief overview of Australia’s government structure, and some of the main approaches to public policy analysis are outlined. Reference to construction related examples are provided to ensure issues discussed are relevant and understandable to construction professionals. Government is a significant player in the construction industry, and has multiple roles: adjudicator, regulator, constructor, purchaser and client of construction projects. Moreover there are many spheres of government that are typically engaged in construction projects at multiple stages. The machinery of government can be difficult to understand, even for long term public servants. Demystifying the processes within government can help to improve communication and therefore performance in the industry. A better understanding of how policy-making and government policies affect the construction industry will enhance communication and assist construction professionals and academics to understand and work with government. Additionally the document will provide an opportunity to demonstrate the relevance of policy analysis to inquiries of construction policies and regulation.

Modelling construction business performance

Searching academic databases for records on ‘business failure’, ‘business distress’ or ‘bankruptcy’ yields a large body of studies on qualitative, empirical, theoretical and simulation aspects. It is a central part of this research to distil from this large quantity of potentially relevant reports and methodologies those which can both flag and predict business failure in the construction industry. An additional search term, such as, ‘construction’, ‘construction industry’ or ‘contractor’ yields a much smaller number of hits, many of which emphasize the construction industry’s distinctive characteristics. We scientists need first to understand the subject of investigation and the environment in which it lives. To do so, an analysis of existing successful and failed approaches to particular research questions is helpful before embarking on new territory. This guides the structure of the following report for we first review papers that specifically report on aspects of business failure in the construction industry followed by, (a) an overview of promising candidates borrowed from other disciplines and industries, and (b) a possible novel approach. An Australian (Queensland) perspective on the topic will also drive this investigation as most of the published research has been applied to the US and UK construction industries.

The public management issues of access to electronic gaming machines (EGMs) : a case study of policy in Victoria, its effects and requirements for evaluation

Wynne and Schaffer (2003) have highlighted both the strong growth of gambling activity in recent years, and the revenue streams this has generated for governments and communities. Gambling activities and the revenues derived from them have, unsurprisingly, therefore also been seen as a way in which to increase economic development in deprived areas (Jinkner-Lloyd, 1996). Consequently, according to Brown et al (2003), gambling is now a large taxation revenue earner for many western governments, at both federal and state levels, worldwide (for example UK, USA, Australia). In size and importance, the Australian gambling industry in particular has grown significantly over the last three decades, experiencing a fourfold increase in real gambling turnover. There are, however, also concerns expressed about gambling and Electronic Gaming in particular, as illustrated in economic, social and ethical terms in Oddo (1997). There are also spatial aspects to understanding these issues. Marshall’s (1998) study, for example, highlights that benefits from gambling are more likely to accrue at the macro as opposed to the local level, because of centralised tax gathering and spending of tax revenues, whilst localities may suffer from displacement of activities with higher multipliers than the institutions with EGMs that replace them. This also highlights a regional context of costs, where benefits accrue to the centre, but the costs accrue to the regions and localities, as simultaneously resources leave those communities through both the gambling activities themselves (in the form of revenue for the EGM owners), and the government (through taxes).