Competitiveness of the Indonesian construction industry

Indonesia’s construction industry is important to the national economy. However, its competitiveness is considered low due to the lack of success of its development strategy and policy. A new approach known as the cluster approach is being used to make strategy and policy in order to develop a stronger, and more competitive industry. This paper discusses the layout of the Indonesian construction cluster and its competitiveness. The archival analysis research approach was used to identify the construction cluster. The analysis was based on the input-output (I/O) tables of the years 1995 and 2000, which were published by the Indonesian Central Bureau of Statistics. The results suggest that the Indonesian construction cluster consists of the industries directly involved in construction as the core, with the other related and supporting industries as the balance. The anatomy of the Indonesian construction cluster permits structural changes to happen within it. These changes depend on policies that regulate the cluster’s constituents

Supporting pre-tender construction planning with virtual prototyping

Purpose – Virtual prototyping technologies linked to building information models are commonplace within the aeronautical and automotive industries. Their use within the construction industry is now emerging. The purpose of this paper is to show how these technologies have been adopted on the pre-tender planning for a typical construction project. Design/methodology/approach – The research methodology taken was an “action research” approach where the researchers and developers were actively involved in the production of the virtual prototypes on behalf of the contractor thereby gaining consistent access to the decisions of the planning staff. The experiences from the case study were considered together with similar research on other construction projects. Findings – The findings from the case studies identify the role of virtual prototyping in components modelling, site modelling, construction equipment modelling, temporary works modelling, construction method visualization and method verification processes. Originality/value – The paper presents a state-of-the-art review and discusses the implications for the tendering process as these technologies are adopted. The adoption of the technologies will lead to new protocols and changes in the procurement of buildings and infrastructure.

An investigation into the barriers to the implementation of automation and robotics technologies in the construction industry

The rising problems associated with construction such as decreasing quality and productivity, labour shortages, occupational safety, and inferior working conditions have opened the possibility of more revolutionary solutions within the industry. One prospective option is in the implementation of innovative technologies such as automation and robotics, which has the potential to improve the industry in terms of productivity, safety and quality. The construction work site could, theoretically, be contained in a safer environment, with more efficient execution of the work, greater consistency of the outcome and higher level of control over the production process. By identifying the barriers to construction automation and robotics implementation in construction, and investigating ways in which to overcome them, contributions could be made in terms of better understanding and facilitating, where relevant, greater use of these technologies in the construction industry so as to promote its efficiency. This research aims to ascertain and explain the barriers to construction automation and robotics implementation by exploring and establishing the relationship between characteristics of the construction industry and attributes of existing construction automation and robotics technologies to level of usage and implementation in three selected countries; Japan, Australia and Malaysia. These three countries were chosen as their construction industry characteristics provide contrast in terms of culture, gross domestic product, technology application, organisational structure and labour policies. This research uses a mixed method approach of gathering data, both quantitative and qualitative, by employing a questionnaire survey and an interview schedule; using a wide range of sample from management through to on-site users, working in a range of small (less than AUD0.2million) to large companies (more than AUD500million), and involved in a broad range of business types and construction sectors. Detailed quantitative (statistical) and qualitative (content) data analysis is performed to provide a set of descriptions, relationships, and differences. The statistical tests selected for use include cross-tabulations, bivariate and multivariate analysis for investigating possible relationships between variables; and Kruskal-Wallis and Mann Whitney U test of independent samples for hypothesis testing and inferring the research sample to the construction industry population. Findings and conclusions arising from the research work which include the ranking schemes produced for four key areas of, the construction attributes on level of usage; barrier variables; differing levels of usage between countries; and future trends, have established a number of potential areas that could impact the level of implementation both globally and for individual countries.

Evaluating equal employment opportunity and its impact on the increased participation of men and women in the transport industry

This paper seeks to identify the approaches undertaken in implementing equal employment opportunity in the transport industry in Australia and the links between these approaches and indicators of increased participation of women. This male dominated industry employs limited numbers of women with fewer numbers of women in management. The study analyses data from a unique set of equal opportunity progress reports from all organisations in the transport industry that are required to provide public reports under Australian legislation. The findings indicate a correlation between some approaches to equal opportunity and increased numbers of women in some areas. The study is equally remarkable for what it does not find. Despite widespread equal opportunity implementation across a broad number of employment measures there are limited measures that predict increases in the numbers of women in management or in non-traditional roles. This study differs from others in that it identifies issues specific to one industry and links organisational approach to equal opportunity with the employment status of both women and men.

Universities, SMEs and innovation frameworks : think global, act local?

Universities are increasingly encouraged to take a leading role in economic development, particularly through innovation. Simultaneously, economic development policy itself is increasingly focused on small and medium-sized enterprises (SMEs), creating overlapping interactions in the roles of government policy, universities and SMEs and the processes of innovation creation and dissemination. This paper examines issues arising from these developments and relating to the key stakeholders (industry, government and universities in particular), the enabling mechanisms (network governance, relevant education, training and learning, and suitable structures), and local and cross-local links. The authors then use quantitative analysis of 450 SMEs in the UK to begin to evaluate the roles of universities and highlight areas for further theoretical development.

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.

Improving ICT integration in today’s AEC industry: recommendations & guidelines

The Cooperative Research Centre (CRC) for Construction Innovation research project 2001-008-C: ‘Project Team Integration: Communication, Coordination and Decision Support’, is supported by a number of Australian industry, government and university based project partners including: Queensland University of Technology (QUT); Commonwealth Scientific Industrial Research Organisation (CSIRO), University of Newcastle; Queensland Department of Public Works (QDPW); and the Queensland Department of Main Roads (QDMR). Supporting the various research aims and objectives of the 2001-008-C (Part B) QUT / Industry Partner agreements, and as a major deliverable for the project, this report is not intended as a comprehensive statement of Architectural, Engineering and Contractor (AEC) industry best practice recommendations. Rather it should read as a set of research and industry recommended guidelines, based on extensive literature reviews and two years worth of investigative activities examining both public and private industry uptake of innovative information and communication technology (ICT) solutions, whilst highlighting the overall need for culture change.

Industry culture: a need for change

Research indicates, one of the last available ‘mechanisms’ left for organisations to improve their competitive position within the construction industry is by considering its people (culture) along with its technology (Schein E. H. 1997). In other words, if one wants to make construction industry organisations, groups and project teams more efficient and effective, then one must better understand the role that culture plays within them.

Brite phase 1 report to industry : innovate – now

Trying to innovate or wanting to? Making a start is the most difficult step on any journey. Whether trying to innovate for the first time, or seeking improvements on current performance, organisations are confronted with a plethora of options. Innovate ― Now! makes action easier by presenting some of the key considerations for improving innovation performance. This guide has been based on the outcomes of a survey and case studies conducted between 2003 and 2005 in the Australian property and construction industry and therefore contains unique and up-to-date information, examples and suggestions tailored specifically to your industry needs.

Public acceptance of carbon dioxide capture and storage in a proposed demonstration area

With the rising levels of CO2 in the atmosphere, low-emission technologies with carbon dioxide capture and storage (CCS) provide one option for transforming the global energy infrastructure into a more environmentally, climate sustainable system. However, like many technology innovations, there is a social risk to the acceptance of CCS. This article presents the findings of an engagement process using facilitated workshops conducted in two communities in rural Queensland, Australia, where a demonstration project for IGCC with CCS has been announced. The findings demonstrate that workshop participants were concerned about climate change and wanted leadership from government and industry to address the issue. After the workshops, participants reported increased knowledge and more positive attitudes towards CCS, expressing support for the demonstration project to continue in their local area. The process developed is one that could be utilized around the world to successfully engage communities on the low carbon emission technology options.

Adoption in the construction industry

This report draws together the key findings from six case studies on the subject of ebusiness Adoption in Construction conducted in Australia by the University of Newcastle (UON) and Royal Melbourne Institute of Technology (RMIT) from 2005 through to mid-2006 under the auspices of the Cooperative Research Centre for Construction Innovation (CRC_CI). Reference to this timing is important because one of the key themes to emerge from the study is that the take-up of e-business is a dynamic phenomenon within the construction industry.

Innovate now : Improving performance in the building and construction industry

Trying to innovate or wanting to? Making a start is the most difficult step on any journey. Whether trying to innovate for the first time, or seeking improvements on current performance, organisations are confronted with a plethora of options. Innovate now! makes action easier by presenting some of the key considerations for improving innovation performance. This guide has been based on the outcomes of a survey and case studies conducted between 2003 and 2005 in the Australian property and construction industry and therefore contains unique and up-to-date information, examples and suggestions tailored specifically to your industry needs. The large-scale industry survey and 12 innovation case studies on which this guide are based were carried out by The BRITE (Building Research, Innovation, Technology and Environment) Project as part of research for the Cooperative Research Centre for Construction Innovation. The stakeholders volunteering to take part in BRITE research included over 400 businesses, 14 government organisations, 8 industry associations and 4 universities.