City Research Online

Abstract

As competition has shifted from the company to the Supply Chain level, gaining a competitive edge becomes an issue of efficient collaboration amongst SC partners. Within the e-business era the level of competitiveness is determined by the ability of an SC to react and adjust rapidly to market and industrial changes and to overcome burdens originating both from inside and outside the SC borders. These features create the framework for defining agility within supply chains. Managing turbulence in SCs, while maintaining customer satisfaction at a low operational cost requires proactive dynamics towards risk factors. An agile Supply Chain addresses direct and indirect sources of risk, which expand outside the SC boundaries. Supply risk is related to the potential occurrence of an incident such as inbound supplies failure that results in customer dissatisfaction. Sources of risk in the SC have various origins which due to their dynamic nature cannot always be predicted, such as turbulence in oil or currency prices, physical or manmade disasters, production failures, product recalls and so on. Organizations need to respond to events as certain unexpected events can cause chaos in the SC and form patterns with negative impact, such as the bullwhip effect, backlogs etc. Chaos in the SC originates from managerial and computer control decisions and actions but apart from the internal sources, chaotic spikes in the SC demand can also originate from external changes.

This thesis proposes that Internet based Information Systems support is required for responsive Supply Chains, in order to address risk origins under a holistic perspective. An event driven architectural framework is proposed in the context of SC operations, which enables flexibility and agility in an e-business setting. The concept of events is explored within the Supply Chain domain and the information regarding patterns of occurring events is identified and disseminated. Initially the theoretical ground for event identification is set and unexpected events in a SC context are classified. Building on the events classification, a notation (EPN) to model event patterns is described. Finally an architecture (SCEDRA) which captures unexpected events and forms and disseminates event patterns is proposed.

Publication Type:	Thesis (Doctoral)
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments:	School of Science & Technology > Computer Science > Human Computer Interaction Design School of Science & Technology > School of Science & Technology Doctoral Theses Doctoral Theses

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