Critical success factors for positioning Australian business talent in the global knowledge economy : a current research agenda

"Globalisation‟ and the "global knowledge economy‟ have become some of the most common "buzzwords‟ in Australian business, economic, and social sectors in the past decade. Further, knowledge service exports are a growing sector for Australia that utilise complex technical and creative capacities, increasingly rely on virtual work innovations, require new socio-technical systems to establish and maintain effective client relationships in global contexts; and – along with other innovations in the electronic age – may require novel coping abilities on the part of both managers and their employees to achieve desired outcomes (Bandura, 2002). Accordingly, this paper overviews such trends. The paper also includes a research agenda which is a "work-in-progress‟ with a major global company, Shell (Australia); it highlights both the objectives and proposed methodology of the study; it also outlines anticipated key benefits arising from the research.

Critical success factors of process modeling for enterprise systems

The integrated and process oriented nature of Enterprise Systems (ES) has led organizations to use process modeling as an aid in managing these systems. Enterprise Systems success factor studies explicitly and implicitly state the importance of process modeling and its contribution to overall Enterprise System success. However, no empirical evidence exists on how to conduct process modeling successfully and possibly differentially in the main phases of the ES life-cycle. This paper reports on an empirical investigation of the factors that influence process modeling success. An a-priori model with 8 candidate success factors has been developed to this stage. This paper introduces the research context and objectives, describes the research design and the derived model, and concludes by looking ahead to the next phases of the research design.

A model for assessing and correcting construction project health

Abstract Maintaining the health of a construction project can help to achieve the desired outcomes of the project. An analogy is drawn to the medical process of a human health check where it is possible to broadly diagnose health in terms of a number of key areas such as blood pressure or cholesterol level. Similarly it appears possible to diagnose the current health of a construction project in terms of a number of Critical Success Factors (CSFs) and key performance indicators (KPIs). The medical analogy continues into the detailed investigation phase where a number of contributing factors are evaluated to identify possible causes of ill health and through the identification of potential remedies to return the project to the desired level of health. This paper presents the development of a model that diagnoses the immediate health of a construction project, investigates the factors which appear to be causing the ill health and proposes a remedy to return the project to good health. The proposed model uses the well-established continuous improvement management model (Deming, 1986) to adapt the process of human physical health checking to construction project health.

Key performance indicators for measuring construction success

The construction industry is dynamic in nature. The concept of project success has remained ambiguously defined in the construction industry. Project success is almost the ultimate goal for every project. However, it means different things to different people. While some writers consider time, cost and quality as predominant criteria, others suggest that success is something more complex. The aim of this paper is to develop a framework for measuring success of construction projects. In this paper, a set of key performance indicators (KPIs), measured both objectively and subjectively are developed through a comprehensive literature review. The validity of the proposed KPIs is also tested by three case studies. Then, the limitations of the suggested KPIs are discussed. With the development of KPIs, a benchmark for measuring the performance of a construction project can be set. It also provides significant insights into developing a general and comprehensive base for further research.

A strategic marketing approach to national development initiatives involving large scale collaborative ventures (LSCV)

This paper relates to government initiatives which aim at advancing their country’s economic development and investor attractiveness. It identifies large scale projects that involve collaboration between government and business (termed: large scale collaborative venture – LSCV) as one aspect of competing in the new economy. The study pursued the research proposition that a LSCV can be effectively facilitated by following a theory based process similar to what is used in corporate practice. An approach to managing such ventures is outlined, based on strategic marketing theory applied to a major project, the Multifunction Polis. It is proposed that such an approach may enhance the success of a collaborative venture and thereby help countries participate more successfully in global competition through such ventures.

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.

A three species model to simulate application of hyperbaric oxygen therapy to chronic wounds

Chronic wounds are a significant socioeconomic problem for governments worldwide. Approximately 15% of people who suffer from diabetes will experience a lower-limb ulcer at some stage of their lives, and 24% of these wounds will ultimately result in amputation of the lower limb. Hyperbaric Oxygen Therapy (HBOT) has been shown to aid the healing of chronic wounds; however, the causal reasons for the improved healing remain unclear and hence current HBOT protocols remain empirical. Here we develop a three-species mathematical model of wound healing that is used to simulate the application of hyperbaric oxygen therapy in the treatment of wounds. Based on our modelling, we predict that intermittent HBOT will assist chronic wound healing while normobaric oxygen is ineffective in treating such wounds. Furthermore, treatment should continue until healing is complete, and HBOT will not stimulate healing under all circumstances, leading us to conclude that finding the right protocol for an individual patient is crucial if HBOT is to be effective. We provide constraints that depend on the model parameters for the range of HBOT protocols that will stimulate healing. More specifically, we predict that patients with a poor arterial supply of oxygen, high consumption of oxygen by the wound tissue, chronically hypoxic wounds, and/or a dysfunctional endothelial cell response to oxygen are at risk of nonresponsiveness to HBOT. The work of this paper can, in some way, highlight which patients are most likely to respond well to HBOT (for example, those with a good arterial supply), and thus has the potential to assist in improving both the success rate and hence the costeffectiveness of this therapy.

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.

Using data mining to improve building life cycle

The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.

Australian national survey: preliminary findings

The National survey was the third phase in an ongoing initiative to identify critical success factors in ICT mediated supply chains. This study has been designed to harness the tacit and explicit knowledge to be found on the subject from the widest range of appropriate sources. At its core is the assumption that, provided with the fullest list of candidate success factors, a representative sample of experienced industry-based practitioners will (with the aid of statistical analysis) reveal a set of critical success factors. A postal survey has been judged to be the most appropriate mechanism for achieving this outcome.

Trip to Sunshine Coast Queensland, September 2004 visit to bridge and foreshore

A trip was undertaken to look at concerns of Public Works and Main Roads Departments of Queensland. David Paterson and Wayne Ganther from CSIRO travelled to the Sunshine Coast with Alan Carse of Queensland Department of Main Roads and Michael Ball of Queensland Department of Public Works. We were also joined for part of the visits by Ed Bowers of QBuild which is a commercial unit of Public Works responsible for maintenance of Public Works. During the trip we visited a bridge on the David Low Way at Sunrise Beach near Noosa. This bridge was in a serve marine environment with high salt content in the concrete and corrosion of the galvanised guardrails and barriers. Also the foreshore at Coolum was visited and the use of stainless steel was examined. This is discussed in this report. Most problems stemmed from incorrect specification due to lack of awareness of the severity of the environment. The companion report Visit to Schools Report 2002-059-B No 7. covers the visit to four schools north of Caloundra.

Final Report

This project aims to assess the extent of economic sustainability of working in international markets by Australian construction design-related firms. This investigation also identified barriers and success factors firms experience, which ultimately increases or reduces their exposure to financial risk. This study explored new research territory by developing a detailed understanding of the way three successful firms have maintained their longevity in various international markets. The firms are not considered to be large firms by international standards. The manner in which the firms achieve long term sustainability, deal with problems and barriers in international markets and develop successful strategies rely upon being adaptable to different markets and changes within markets. A model was developed based upon a critical analysis of the literature. An adaptive performance framework for sustainability was developed which had three key areas; internationalisation process, market knowledge and design management. The sustainable business model is underpinned by the management of non-economic factors, which include social, cultural and intellectual capital. The ultimate aim of any firm and the ultimate indicator of success is financial capital. Firms typically develop their own highly sophisticated financial measures themselves however have only an implicit understanding of other softer and less tangible factors that impact upon sustainability. Adaptive performance is the firm’s continual adaptivity of business practices to respond to and thereby achieve client satisfaction by a combination of self, market and project needs assessment.

Long term sustainability in exporting creativity

This project aims to assess the extent of economic sustainability of working in international markets by Australian construction design-related firms. This investigation also identified barriers and success factors firms experience, which ultimately increases or reduces their exposure to financial risk. This study explored new research territory by developing a detailed understanding of the way three successful firms have maintained their longevity in various international markets. The firms are not considered to be large firms by international standards. The manner in which the firms achieve long term sustainability, deal with problems and barriers in international markets and develop successful strategies rely upon being adaptable to different markets and changes within markets. A model was developed based upon a critical analysis of the literature. An adaptive performance framework for sustainability was developed which had three key areas; internationalisation process, market knowledge and design management. The sustainable business model is underpinned by the management of non-economic factors, which include social, cultural and intellectual capital. The ultimate aim of any firm and the ultimate indicator of success is financial capital. Firms typically develop their own highly sophisticated financial measures themselves however have only an implicit understanding of other softer and less tangible factors that impact upon sustainability. Adaptive performance is the firm’s continual adaptivity of business practices to respond to and thereby achieve client satisfaction by a combination of self, market and project needs assessment.

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.