Khosrowshahi, F (1998) A hybrid of executive management decision support tools. In: Hughes, W (ed.) Proceedings of 14th Annual ARCOM Conference, 9-11 September 1998, Reading, UK.
Abstract
The performance of a contracting company is closely linked with the quality of the decisions at the strategic level. However, the increasing complexity of organizations' internal and external environments and the unstructured nature of decisions at the strategic level make the decision making a very complicated task. The number of influential variables is so large and their effects are so varied that any attempt to encapsulate them in a rational manner can indeed hinder the decision making process. To this end, this research explores the advantages of decision support tools and the benefit these tools can yield for the strategic management. Some of these tools are deterministic and structured: they rely on straightforward calculation or optimization techniques. The solution to the unstructured problems, however, has relied on heuristic approaches and judgement of the decision-maker. While deterministic problems have to a large extent been addressed and appropriate models and algorithm have been developed for them, the unstructured problems have remained relatively unattended and the research works in this area tend to focus on single issues. This research highlights the potential use of artificial intelligent techniques in assisting the managers with unstructured decisions. Further, it is argued that a strategic decision support system should assume an integrated structure, as many decision nodes, within the overall decision making structure, share common attributes and the inter-connection amongst these decision nodes has a complex structure. Therefore, the object-oriented approach will provide an efficient structure for the development of the overall framework. In this paper, the characteristics of decision types are identified and cross tabulated against the attributes of various decision tools. The latter consist of both traditional and AI techniques. The work forms part of a broader research work the aim of which is to develop a framework of executive decision support system that is based on a hybrid of decision support tools.
| Item Type: | Conference Paper (Paper) |
|---|---|
| Uncontrolled Keywords: | artificial intelligence; artificial neural network; decision support tools; executive information system; management decision structure |
| Index terms: | management decision, executive, decision-making, strategic management, complexity, artificial intelligence, information system, heuristic, decision support, optimization technique, manager, artificial neural network, decision-making process |
| Subjects: | practitioner, risk assessment, artificial intelligence, modelling and simulation, algorithms, decision-making and reasoning, management, information systems, systems engineering, decision analysis |
| Topics: | Roles and Professions, Risk Management, Business Strategy, Engineering Principles, Research Practice, Digital Applications |
| Descriptive scope: | 2 PC |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here