Building refurbishment contracts bid decision knowledge and its applicationan a knowledge based decision support system (ADJUBID)

Shafie, K (1995) Building refurbishment contracts bid decision knowledge and its applicationan a knowledge based decision support system (ADJUBID). PhD thesis, University of London, University College London, UK.

Abstract

Bidding or tendering is necessarily a decision-making process. Since the process of putting together a bid is known to be complex and the fact that optimum pricing quantitative bidding models are saddled with 'unresolved' practical problems that have hindered their application, the process of bid decision-making seems to put to the test contractors' bid decision-making abilities, skills and acumen. There is evidence to support this proposition. The manner and behaviour by which contractors' formulate the overall bidding strategy reflect not only the importance and dominance of these qualitative and judgmental elements in the decision-making process but rather more importantly the decision-making reality of the bidding problem. It is then not difficult to understand why contractors embrace a satisficing solution approach (which relies heavily on cognitive abilities, skills and cognitive strategies to win bids) to the problem, not because it is a matter of preference or an 'easy-way-out' but rather a better and logical alternative in resolving bidding problems without jeopardising the aim of the whole exercise. These observations, together with the fact that human cognitive abilities and strategies are cognitively "biased", suggest the need to study the cognitive aspect of bid decision-making and then of finding ways to use this knowledge to improve bidding performance. The characteristics displayed by expert systems suggest that subsequent progress in bidding performance can be achieved using the acquired bid decision-making knowledge. This thesis discusses the results of a study in the refurbishment sector of the construction industry suggested by the foregoing observations. The Repertory Grid Technique, a psychological tool to elicit, analyse and represent a person's underlying 'cognitive model', was used to investigate and acquire refurbishment contractors' cognitive bid pricing decision-making knowledge. The results of the investigations show that contractors' cognitive and expert bid decision-making knowledge may be extracted, systematised into a decision model, and then developed into an expert (knowledge based) decision support system called "AdjuBid". Although contractors' intuitive judgement may not be totally replaced by the system in the decision-making process, nevertheless, the systematised expert bid decision-making knowledge in AdjuBid would help to clarify and bring into focus their bid decision-thought processes in the changing competitive environment. This would highlight their current cognitive bidding strategies and forced them to re-evaluate earlier perceptions and reconsider what the best strategy should be. It may be concluded, the systematisation of cognitive bid decision-making knowledge and its application to expert systems were seen to suggest improvement to bidding performance.

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: bias; decision support; skills; bidding; expert system; pricing; refurbishment; tendering; bidding model; repertory grid technique
Index terms: repertory grid technique, building refurbishment, decision-making process, pricing, exercise, construction industry, investigation, strategy, decision support, bidding, preference, expert system, evidence, bias, cognitive ability, decision-making
Subjects: health behaviours and lifestyles, evaluation and assessment methods, data collection methods, economic analysis, bidding, probability and distributions, decision-making and reasoning, management, industry analysis, cognitive psychology, decision analysis, asset management, data management
Topics: Digital Applications, Research Practice, Business Strategy, Health and Safety, Procurement, Risk Management
Descriptive scope: 5 PCTEA

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