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Knowledge mapping for enhancing sustainability in large public sector funded urban redevelopmentGilmour, Daniel James January 2014 (has links)
The thesis describes a programme of research work to develop and apply knowledge mapping and knowledge management techniques to effectively assess and enhance sustainability within urban redevelopment projects. The research programme was initiated in collaboration with Dundee City Council to support sustainable development in a major programme of urban redevelopment. There is limited evidence that the body of knowledge arising from research in sustainable urban development is being holistically integrated within real life decision making practices to operationalise sustainability. Sustainability assessment has the potential to influence decision making and consequently by improving sustainability assessment practice project decision making should be enhanced. In addition, closer integration between assessment and decision making may not only lead to improve decisions, but also to the improved learning of those involved. This can be greatly facilitated by knowledge management, which can be used to understand and then facilitate greater learning amongst stakeholders. A theoretical framework for the assessment, monitoring and enhancement of sustainability was developed and applied in two parts to a case study, a monitoring component and an enhancement component. As a result of the case study a sustainability assessment and monitoring framework was successfully established for Dundee Waterfront in line with the assessment component of the theoretical framework. The indicators are now used by Dundee City Council at project and departmental level, providing the link across policies, programmes and projects. The key challenge addressed in developing the benchmark indicators was establishing robust governance for the monitoring framework. An enhancement framework was successfully established for Dundee Waterfront in line with the enhancement component of the theoretical framework. Decision mapping and knowledge elicitation techniques were successfully developed and applied to the case study to identify, key points in decision process, the information decision makers' need and which knowledge objects are being used in decision making. It is concluded that the knowledge elicitation and mapping approaches applied were effective at identifying both existing processes and knowledge objects used in infrastructure provision. This allowed a Knowledge Map for Sustainability to be developed to identify what information is currently used to influence sustainability and identify future opportunities to enhance practise. The map was effective in capturing the role of each stage in the process towards translating the sustainability vision as proved by user verification. The Map showed for the first time the aspects of sustainability in infrastructure provision and can be used to systematically operationalise sustainable development. However, the use of the map to embed sustainability into learning process could not be verified by practise in the currency of the thesis. A limitation of the case study application is that the integrated sustainability assessment and enhancement framework has been applied in a Scottish local authority context, to an organisation with a Quality Management System and outcome based indicators. These factors have been identified as contributing factors to the success of the sustainability assessment and enhancement framework as applied in the case study. This has the potential to limit the exportability of any findings. However, whilst considering the monitoring component it is recognised that similar outcome based indicators may exist at other local authorities and private organisations. In addition, the knowledge elicitation and mapping technique is an adaptive framework and as such is designed to respond to other organisation structures. Therefore by its nature it should be exportable to other applications. However three main questions remain to be addressed prior to the research question being answered in full. Firstly, uncertainty related to governance and long term use of the framework. Secondly, testing how the Knowledge Map for Sustainability is used in practice and thirdly the exportability of findings from the case study. It is recommended that these limitations be addressed in future work.
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The role of personality in the relationship between feeling bored and decision-making competence: a study of managers in the retail industryDu Preez, Magda January 2016 (has links)
Thesis
submitted in fulfilment of the requirements for the degree of
Doctor of Philosophy (PhD)
at the
Wits business school
University of the Witwatersrand
June 2016 / Despite the increased work on emotions in organizations, there is a lack of research on the impact of feeling bored in managerial decision-making contexts. Feeling bored was defined, and an expansion to the Hybrid Process Decision-Making Model was proposed. Using this revised definition of feeling bored and the Expanded Decision-Making Process Model, an empirical study with retail middle managers was conducted to examine the relationships between feeling bored and decision-making competence and the role of personality. Results found that feeling bored has a significant negative association with middle managers’ confidence levels, risk perception and decision rules. Results confirmed that personality plays a moderating role in the relationship between feeling bored and decision-making competence. Most notably, the personality trait learning neutralizes the negative effects of feeling bored on decision-making competence, whereas the personality trait sociability has a varied effect depending on which end of the valence/arousal continuum feeling bored is experienced. Limitations to the study, and practical implications for retail organizations, middle managers and for future research, are outlined / MB2016
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Visually informed support for design engineering decisionsCarey, Emily January 2016 (has links)
It is a truism that the amount of information being generated in the modern digital world is increasing at an exponential rate. This is influencing engineering as it is in other forms of business, as well as everyday life. Engineering has a significant visual dimension to it: drawings, diagrams, sketches, photographs, graphs are the everyday language of the engineer. Despite the prevalence of such visual information, the role that such information plays and how it affects, for example, how documents can be reused is an under-researched area. This thesis thus proposes the important role of visual representations and images for supporting informed decisions, in particular for complex domains such as Engineering Design. The particular context for this research is associated with in-service design knowledge and information requirements. The increasing number of actual products in-service, the requirement to create safe design solutions quickly, the amassment of service data and the importance of product services to organisational competitiveness are all increasing the information pressures upon Design teams. The pervasive nature of visual representations in Engineering Design and prevalent document information suggests that they are an important asset within document information resources. This research focusses upon the purpose of Engineering Design image utilisation for information processing, and hence supporting efficient decision making. Some of the additional challenges identified throughout this research are the immaturity of current image recognition technologies and thus limitations of automated media extraction tools for supporting Design Engineers. This is significantly contributed to by the complexity of the information media and formats that constitute design engineering information and the current knowledge management trend to capture information without clear “reuse” purpose. The methods used to conduct this research demonstrate the merits of underused techniques in design engineering such as storyboarding. This storyboarding method is used for investigating the facets of tacit knowledge and the underpinning cognitive processing of document information resources for critical Design Engineering informative content. The innovative research method developed provides a useful framework for the collection of rich data using simulated tasks. The data collection is a rich multi-stream recording of design engineers in industry conducting work based scenarios. In particular the focus is upon conducting efficient research in industrial working practices with minimal facing research time with design engineers and the rich data that can be collected from them in situ. This thesis illustrates that there are a number of pressing difficulties in reusing image media, both technical process related in nature. This is currently limiting the usefulness of valuable information resources in practice, but also significantly raises the information burden for design engineer. This thesis has attributed the value of reusing visual representations due to their important role in design engineering decisions. It has provided evidence of the intuitive and important human need for visual information to provide mental stimulation in particular for making confident design decisions. The storyboard research method has outlined an industrial data collection and decision coding framework that is reproducible and can be used to better understand human information processing, and thus supports the development of document information systems. Additional rich information utilisation patterns for design engineering document information have also been evidenced in the empirical research results provided. This thesis also provides practical industrial examples to suggest techniques that could overcome the current technological shortfalls limiting the “reuse” of visual information in documents for Design Engineers.
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The PRC decision-making process /Miller, Casey J. January 2002 (has links) (PDF)
Thesis (M.A.)--Naval Postgraduate School, 2002. / Thesis advisor(s): H. Lyman Miller, Harold D. Blanton. AD-A402 689. Includes bibliographical references. Also available online.
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DRACA: Decision-support for Root Cause Analysis and Change Impact AnalysisNadi, Sarah 12 1900 (has links)
Most companies relying on an Information Technology (IT) system for their
daily operations heavily invest in its maintenance. Tools that monitor network
traffic, record anomalies and keep track of the changes that occur in the system
are usually used. Root cause analysis and change impact analysis are two main
activities involved in the management of IT systems. Currently, there exists no
universal model to guide analysts while performing these activities. Although the
Information Technology Infrastructure Library (ITIL) provides a guide to the or-
ganization and structure of the tools and processes used to manage IT systems, it
does not provide any models that can be used to implement the required features.
This thesis focuses on providing simple and effective models and processes for
root cause analysis and change impact analysis through mining useful artifacts
stored in a Confguration Management Database (CMDB). The CMDB contains
information about the different components in a system, called Confguration Items
(CIs), as well as the relationships between them. Change reports and incident
reports are also stored in a CMDB. The result of our work is the Decision support
for Root cause Analysis and Change impact Analysis (DRACA) framework which
suggests possible root cause(s) of a problem, as well as possible CIs involved in a change set based on di erent proposed models. The contributions of this thesis are
as follows:
- An exploration of data repositories (CMDBs) that have not been previously
attempted in the mining software repositories research community.
- A causality model providing decision support for root cause analysis based
on this mined data.
- A process for mining historical change information to suggest CIs for future
change sets based on a ranking model. Support and con dence measures are
used to make the suggestions.
- Empirical results from applying the proposed change impact analysis process
to industrial data. Our results show that the change sets in the CMDB were
highly predictive, and that with a confidence threshold of 80% and a half
life of 12 months, an overall recall of 69.8% and a precision of 88.5% were
achieved.
- An overview of lessons learned from using a CMDB, and the observations we
made while working with the CMDB.
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DRACA: Decision-support for Root Cause Analysis and Change Impact AnalysisNadi, Sarah 12 1900 (has links)
Most companies relying on an Information Technology (IT) system for their
daily operations heavily invest in its maintenance. Tools that monitor network
traffic, record anomalies and keep track of the changes that occur in the system
are usually used. Root cause analysis and change impact analysis are two main
activities involved in the management of IT systems. Currently, there exists no
universal model to guide analysts while performing these activities. Although the
Information Technology Infrastructure Library (ITIL) provides a guide to the or-
ganization and structure of the tools and processes used to manage IT systems, it
does not provide any models that can be used to implement the required features.
This thesis focuses on providing simple and effective models and processes for
root cause analysis and change impact analysis through mining useful artifacts
stored in a Confguration Management Database (CMDB). The CMDB contains
information about the different components in a system, called Confguration Items
(CIs), as well as the relationships between them. Change reports and incident
reports are also stored in a CMDB. The result of our work is the Decision support
for Root cause Analysis and Change impact Analysis (DRACA) framework which
suggests possible root cause(s) of a problem, as well as possible CIs involved in a change set based on di erent proposed models. The contributions of this thesis are
as follows:
- An exploration of data repositories (CMDBs) that have not been previously
attempted in the mining software repositories research community.
- A causality model providing decision support for root cause analysis based
on this mined data.
- A process for mining historical change information to suggest CIs for future
change sets based on a ranking model. Support and con dence measures are
used to make the suggestions.
- Empirical results from applying the proposed change impact analysis process
to industrial data. Our results show that the change sets in the CMDB were
highly predictive, and that with a confidence threshold of 80% and a half
life of 12 months, an overall recall of 69.8% and a precision of 88.5% were
achieved.
- An overview of lessons learned from using a CMDB, and the observations we
made while working with the CMDB.
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Window Based Digital Mapping And Feeder Management Decision Support SystemChen, Sheng-Wuen 06 June 2001 (has links)
With the performance enhancement of personal computers and the popularity of Microsoft Windowing Geographic Information System (GIS), it is becoming more viable in performing the distribution automated mapping and facility management (AM/FM). In this thesis, the relative structure of the graphic and attribute data of the distribution system with four feeders (LB33, LB34, LB35 and LB38) of the Taiwan Power Company (TPC) were built according to the true geography, referring to the street background. The related applications of the GIS included Distribution Information System (DIS) and Feeder Management Decision Support (FMDS) system by using MS Visual Basic object oriented programming.
The proposed DIS links graphic objects and facility attribute data through the DDE connect and WinGIS Software, and provides a user-friendly Man-Machine Interface to manage the distribution database.
As for FMDS, it is complicated to operate with colossal system information of the distribution systems. To enhance the operational efficiency and reduce cost, a fast and effective Feeder Management Decision Support is critical. With a user-friendly graphical user interface provided by mapping, effective database interface and related distribution system management algorithms, it is capable of providing the decision support, so a good decision can be made both normal and emergency conditions:
1. Decision support under the normal operation
The decision system can reduce the line loss and maintain bus voltages with load transferal through feeder reconfiguration strategy.
2. Decision support under the emergency operation
With fuzzy reasoning algorithm, security analysis will examine network security and an optimal switching strategy can solve the load recovery problem fast and effectively.
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Relational project modeling and risk projection frameworkGould, Brian D. January 1900 (has links)
Thesis (M.S.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains ix, 161 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 49).
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Computer-mediated communication in small group decisional stages /Olaniran, Bolanle Abodunrin. January 1991 (has links)
Thesis (Ph. D.)--University of Oklahoma, 1991. / Includes bibliographical references (leaves 89-100).
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Decision-making processes for a sample of southeastern Arizona crop farmers: conceptualization and analysis of the expansion decisionLeathers, Kenneth L. January 1968 (has links)
No description available.
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