Computing and Information Systems - Theses
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ItemMaximizing benefits from enterprise systems( 2001)This study investigates how organizations can maximize benefits from their Enterprise Systems (ES). The results suggest that making optimal use of an Enterprise System is an on-going challenge best managed by successive cycles of system exploration, redesign, and use. Each cycle results in successively better configured software and enhanced organizational processes. Each cycle requires core process managers' commitment and management initiatives to explore and control the positive and negative effects caused by the four distinctive characteristics of Enterprise Systems: pre-packaged features, evolving functionality, sophisticated knowledge, and application infrastructure. The study was conducted over three connected phases that sought answers to three research questions: • What business benefits can be realized from the use of Enterprise Systems? • How and when do organizations realize net benefits from Enterprise Systems? • How can organizations manage the use of Enterprise Systems to maximize net benefits? Phase one answers question one, by developing a comprehensive framework of ES benefits organized around five business dimensions: operational, managerial, strategic, IT infrastructure, and organizational. This framework was synthesized from the literature on ES and IT effectiveness, enhanced by analyzing benefits identified from 233 Web cases, and tested in 34 confirmatory cases. This phase established the basis for further analysis of ES benefits. Phase two applies the ES business benefit framework from phase one to answer question two. Business benefit realization processes are tracked over three to four years in in-depth case studies of four Australian utilities. Patterns of Perceived Net Benefit Flow are identified and graphed in each of the five benefit dimensions. The results show that ES benefit realization is a life-long process, with different benefits being developed in different patterns in the five different dimensions, with results possibly varying across core processes within the one organization. The duration and intensity of benefits also varied among the companies. Using cross-case analysis, the types of ES benefit and the interrelationships between different benefit dimensions are explained. Moreover, various causes of benefit variation were analyzed, with the finding that benefits are mainly driven by management of the four ES-specific characteristics of ES use identified above. Following from the case analysis in phase two, phase three answers question three by further exploring ES management in the four case-study organizations. Six propositions are induced from the four case studies and tested for reasonableness with seven additional ES adopters in different industries. Based on this in-depth case exploration, four different strategies for ES management are identified: process replication, system modification, process modification, and system exploration. By comparing business conditions and the implications of the different ES management strategies, the study suggests that the most effective strategy is system exploration. System exploration involves results in a series of business-led initiatives involving changes to both the ES software and business processes that lead to incremental improvements to the Enterprise System.
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ItemFundamentals of agent computation theory: semantics( 2001)About 5 years ago, the idea of software agents escaped from an obscure existence within the arcane field of Artificial Intelligence, and it is now running rampant through computer science, the software industry and the media, mutating violently as it goes and infecting many who come into contact with it. Despite humble origins in the study of Philosophy of Mind, the term agent has come to be applied to a diverse and disparate range of software constructs, and threatens soon to displace object from its primal position. Every computer scientist knows what agents are, or should be, although scant agreement upon definitions has been achieved, as so many variously qualified uses of the label now flourish. In the Artificial Intelligence research community where it was nurtured, however, the term still has a reasonably specific meaning: an agent is a situated or embedded system which participates in an ongoing interaction with some environment which it can observe and act upon. By assumption, an agent's behaviour is purposeful or motivated: it is thought of as wanting to perform some set of activities or achieve some set of goals and trying to do so when suitable opportunities present; in general it may be viewed as monitoring and controlling itself and its environment so as to bring about or maintain internal or external situations that it in some sense prefers. A very concrete example would be a robot, situated in the physical world, tasked to achieve certain objectives, but required to make its own moment-to-moment decisions about how and when to do so. But more often than not an agent inhabits an entirely artificial environment, within a single computer or a distributed network such as the Internet. It is with agents in this sense that this thesis is concerned. (From introduction)