175 resultados para Autonomic managers


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Universities are increasingly caught in the transition between college institutions of independant academics to become managed businesses of research and teaching and learning. This is introducing substantial issues with the work, approach and personal development needs of individual academics. It is causing even greater concerns for managers within universities. The developments in University Management have increasingly become driven towards issues of finance, quality and marketing. Organizational development in teaching and learning practices has been less commonly a point of focus. This paper outlines developments of this nature at the University of Salford. Through its combination of authors it does so at whole University, Faculty and School levels. It outlines the variety of ways in which teaching and learning developments can be supported within an organisation.

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In the rapidly growing knowledge economy, the talent and creativity of those around us will be increasingly decisive in shaping economic opportunity. Creativity can be described as the ability to produce new and original ideas and things. In other words, it is any act, idea, or product that changes an existing domain or transforms an existing domain into a new one. From an economic perspective, creativity can be considered as the generation of new ideas that is the major source of innovation and new economic activities. As urban regions have become the localities of key knowledge precincts and knowledge clusters across the globe, the link between a range of new technologies and the development of ‘creative urban regions’ (CURs) has come to the fore. In this sense, creativity has become a buzz concept in knowledge-economy research and policy circles. It has spawned ‘creative milieus,’ ‘creative industries,’ ‘creative cities,’ ‘creative class,’ and ‘creative capital.’ Hence, creativity has become a key concept on the agenda of city managers, development agents, and planners as they search for new forms of urban and economic development. CURs provide vast opportunities for knowledge production and spillover, which lead to the formation of knowledge cities. Urban information and communication technology (ICT) developments support the transformation of cities into knowledge cities. This book, which is a companion volume to Knowledge-Based Urban Development: Planning and Applications in the Information Era (also published by IGI Global) focuses on some of these developments. The Forward and Afterword are written by senior respected academic researchers Robert Stimson of the University of Queensland, Australia, and Zorica Nedovic-Budic of the University of Illinois at Urbana-Champaign, USA. The book is divided into four sections, each one dealing with selected aspects of information and communication technologies and creative urban regions.

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This paper focuses on the development and delivery of a core construction management (CM) unit, which forms the capstone of a four-unit CM stream in an undergraduate programme in the Faculty of Built Environment and Engineering at the Queensland University of Technology. UDB410 (Construction Management) is a final year unit that consolidates skills students have learned throughout their degree, hopefully graduating them as work-ready construction managers. It was developed in consultation with the Queensland Chapter of the Australian Institute of Building (AIB) and is a final year unit in the undergraduate Bachelor of Urban Development (CM) course. The unit uses various tools such as the OSIRIS business database (Bureau van Dijk Electronic Publishing, 2009), the AROUSAL (UK Version) construction business simulation (Lansley, 2009) and the Denison Organisational Culture Survey (Denison, 2000) to facilitate the development of skills in managing a construction company. The objectives of the paper are: • To track the rationale and development of the UDB410 unit sand describe the way in which this final year unit integrates learning from other parts of the course within which it is located as well as capping-off the CM stream of core units; • To highlight the difficulties of blending a balance of technology and management in a single unit; and • To explain how partnering with the construction industry benefited the learning quality of the unit.

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The purpose of this study is to demonstrate the appropriateness of “Japanese Manufacturing Management” (JMM) strategies in the Asian, ASEAN and Australasian automotive sectors. Secondly, the study assessed JMM as a prompt, effective and efficient global manufacturing management practice for automotive manufacturing companies to learn; benchmark for best practice; acquire product and process innovation, and enhance their capabilities and capacities. In this study, the philosophies, systems and tools that have been adopted in various automotive manufacturing assembly plants and their tier 1 suppliers in the three Regions were examined. A number of top to middle managers in these companies were located in Thailand, Indonesia, Malaysia, Singapore, Philippines, Viet Nam, and Australia and were interviewed by using a qualitative methodology. The results confirmed that the six pillars of JMM (culture change, quality at shop floor, consensus, incremental continual improvement, benchmarking, and backward-forward integration) are key enablers to success in adopting JMM in both automotive and other manufacturing sectors in the three Regions. The analysis and on-site interviews identified a number of recommendations that were validated by the automotive manufacturing company’s managers as the most functional JMM strategies.

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This study investigates the existence of intercultural adjustment in the multicultural construction workplaces by examining the leadership orientations (task-/people-orientation), communication and conflict resolution skills (high/low-context culture), and power relationship styles (high/low power distance) of local Chinese and the British expatriate project managers in the multinational construction companies in Hong Kong. A sample of project managers (N = 40) and their subordinates (N = 61) were surveyed using the structured questionnaires. Statistical techniques (independent-samples t-test, and Pearson correlation analysis) were employed to evaluate the data. The results revealed a number of interesting findings. First, it was found that both project manager groups equally considered the importance of task performance and interpersonal relationship. The results of correlations analysis provide support for the linkages of the length of working abroad with the change in task/people orientation for Chinese and expatriate managers. The analysis revealed that those Chinese managers who have the longest length of time living or working in Western countries tended to measure higher on task-orientation. Similarly, those British expatriate managers who have the longest period of working in Hong Kong tended to be less task-orientated. Second, local Chinese managers were found to be more confrontational when they strongly disagree with their team members than their British expatriate counterparts. It would appear that stress from project deadline which increase the directness and terseness in communication acts, and retain the composure of project managers in dealing with the subordinates. Finally, our findings show that there is significant difference between local Chinese and British expatriate managers in their power relationship with subordinates. This implies that although the intercultural adjustment might influence perceptions of local and expatriate managers, some dominant deep-rooted cultural values and beliefs are still not easily altered. Conclusions are presented along with suggestions for future studies.

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The literature on corporate identity management suggests that managing corporate identity is a strategically complex task embracing the shaping of a range of dimensions of organisational life. The performance measurement literature and its applications likewise now also emphasise organisational ability to incorporate various dimensions considering both financial and non-financial performance measures when assessing success. The inclusion of these soft non-financial measures challenges organisations to quantify intangible aspects of performance such as corporate identity, transforming unmeasurables into measurables. This paper explores the regulatory roles of the use of the balanced scorecard in shaping key dimensions of corporate identities in a public sector shared service provider in Australia. This case study employs qualitative interviews of senior managers and employees, secondary data and participant observation. The findings suggest that the use of the balanced scorecard has potential to support identity construction, as an organisational symbol, a communication tool of vision, and as strategy, through creating conversations that self-regulate behaviour. The development of an integrated performance measurement system, the balanced scorecard, becomes an expression of a desired corporate identity, and the performance measures and continuous process provide the resource for interpreting actual corporate identities. Through this process of understanding and mobilising the interaction, it may be possible to create a less obtrusive and more subtle way to control “what an organisation is”. This case study also suggests that the theoretical and practical fusion of the disciplinary knowledge around corporate identities and performance measurement systems could make a contribution to understanding and shaping corporate identities.

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Sales growth and employment growth are the two most widely used growth indicators for new ventures; yet, sales growth and employment growth are not interchangeable measures of new venture growth. Rather, they are related, but somewhat independent constructs that respond differently to a variety of criteria. Most of the literature treats this as a methodological technicality. However, sales growth with or without accompanying employment growth has very different implications for managers and policy makers. A better understanding of what drives these different growth metrics has the potential to lead to better decision making. To improve that understanding we apply transaction cost economics reasoning to predict when sales growth will be or will not be accompanied by employment growth. Our results indicate that our predictions are borne out consistently in resource-constrained contexts but not in resource-munificent contexts.

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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.

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Consumers' evolving relationships with their mobile devices and their desire to access mobile services (m-services) present new opportunities to marketers, yet little research has been conducted in the area of m-services. Using structural equation modelling, this paper examines the effect of hedonic and utilitarian value of mobile phones on product and purchase involvement. It also investigates the effect of involvement, innovativeness, and self-efficacy on use of m-services. Data were collected from a convenience sample of 250 respondents using an online survey and a modified snowball procedure. Findings are discussed, further implications for managers are suggested and directions for future research are proposed.

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The rapid uptake of mobile devices has created the capacity to provide services to consumers while they are on the move, and new mobile services (m-services) are constantly emerging. In past research, personal attributes have been found to be import ant in the adoption and use of information and communication technology. However, little research has been conducted in the area of m-services. To explore factors influencing the use of these services, this paper examines personal attributes in terms of motivational, attitudinal and demographic characteristics. Specifically, it investigates the influence of innovativeness, self- efficacy, involvement and impulsiveness, as well as age and gender on m-services use . Data were collected from a convenience sample of 250 respondents using an online survey and a modified snowball procedure. Age and gender were quite well balanced in the sample. The multiple regression model was significant and the hypotheses relating to the positive relationship between impulsiveness, involvement and gender and m-services were supported. Findings are discussed, further implications for managers are suggested and directions for future research are proposed.

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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.

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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.

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Objectives The procurement research of Sydney Opera House FM Exemplar Project aims to develop innovative methods and guidelines for the procurement of FM services, applicable to iconic and / or performing arts centre facilities, or facilities with similar FM functions. The initial procurement report in June 2005 analysed the strategic objectives and operational requirements that provide ‘demand statements’ as evaluation criteria in the service procurement process. The subsequent interim procurement report in September 2005 discussed the elements contributing to the criteria for decision-making in the service procurement process. This procurement report concentrates on the research on procurement strategies and innovative methods using a case study approach. The objectives of this report are: • to investigate service procurement methods and process in iconic and/or performing arts centre facilities; • to showcase FM innovation in Sydney Opera House through a case study; • to establish a preliminary decision-making framework and guidelines for selection of appropriate FM procurement routes to provide a useful model for FM community. Findings Findings from this procurement research are presented as follows. • FM innovation and experience of Sydney Opera House • Innovative procurement methods and processes, drawn from a case study of Sydney Opera House as exemplar • An integrated performance framework to link maintenance service functions to high level organisational objective and strategies • Procurement methods and contract outcomes, focusing on building maintenance and cleaning services of Sydney Opera House • Multi-dimensional assessment of Service Providers • General decision-making strategies and guidelines for selection of appropriate FM procurement routes Further Research Whilst the Sydney Opera House case study emphasises the experience of Sydney Opera House, a study of procurement strategies and methods from published research and FM good practice will supply facilities managers with alternative procurement routes. Further research on the procurement theme will develop a final decision-making model for the procurement of FM services, drawn from the evaluation of the case study outcomes, as well as FM good practice and findings from current published research.

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This report fully summarises a project designed to enhance commercial real estate performance within both operational and investment contexts through the development of a model aimed at supporting improved decision-making. The model is based on a risk adjusted discounted cash flow, providing a valuable toolkit for building managers, owners, and potential investors for evaluating individual building performance in terms of financial, social and environmental criteria over the complete life-cycle of the asset. The ‘triple bottom line’ approach to the evaluation of commercial property has much significance for the administrators of public property portfolios in particular. It also has applications more generally for the wider real estate industry given that the advent of ‘green’ construction requires new methods for evaluating both new and existing building stocks. The research is unique in that it focuses on the accuracy of the input variables required for the model. These key variables were largely determined by market-based research and an extensive literature review, and have been fine-tuned with extensive testing. In essence, the project has considered probability-based risk analysis techniques that required market-based assessment. The projections listed in the partner engineers’ building audit reports of the four case study buildings were fed into the property evaluation model developed by the research team. The results are strongly consistent with previously existing, less robust evaluation techniques. And importantly, this model pioneers an approach for taking full account of the triple bottom line, establishing a benchmark for related research to follow. The project’s industry partners expressed a high degree of satisfaction with the project outcomes at a recent demonstration seminar. The project in its existing form has not been geared towards commercial applications but it is anticipated that QDPW and other industry partners will benefit greatly by using this tool for the performance evaluation of property assets. The project met the objectives of the original proposal as well as all the specified milestones. The project has been completed within budget and on time. This research project has achieved the objective by establishing research foci on the model structure, the key input variable identification, the drivers of the relevant property markets, the determinants of the key variables (Research Engine no.1), the examination of risk measurement, the incorporation of risk simulation exercises (Research Engine no.2), the importance of both environmental and social factors and, finally the impact of the triple bottom line measures on the asset (Research Engine no. 3).

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Much has been written about affecting change in the workplace, including how to help employees prepare for the process. However, little is known about how participation influences employees' emotions and attitudes at the start of an intervention. By qualitatively analyzing conversations that were triggered by an organizational change effort, we explored how different inquiry strategies influence readiness for change. We examined four inquiry strategies by combining strength or deficit frames with individual or organizational focus. Distinctive conversational patterns emerged within each strategy, which we believe influence peoples' change readiness. In this article we present four readiness modes to describe these patterns and conclude with implications for managers who seek to shape their change efforts more effectively.