Yoo, Min-JungNaciri, SouleimanBadulescu, YvonneGlardon, Remy2018-01-152018-01-152018-01-15201710.1016/j.cie.2017.04.037https://infoscience.epfl.ch/handle/20.500.14299/143900WOS:000418207900069This paper presents a methodology for eliciting the behavioural model of purchasers' decision-making in a supply chain environment. The objective of the work is to explicitly describe the relationship between a human user's behaviour and the resulting performance in inventory level and service satisfaction. The key research findings include: (i) How to identify a categorised pattern of a human decision model, particularly concerning purchasing operations; and (ii) Which metrics would be relevant in the objective of carrying out a quantitative analysis on decision behaviour. The order placement behaviour is studied as one of daily operational decisions. The work demonstrates how to analyse a potential relationship between each category of behaviour and selected measures of supply chain performance, i.e., average inventory level and delivery satisfaction. We developed a specialised tool for supply chain simulation aimed at collecting data such as information consultations and decision-making actions of purchasing operations. The methodology is composed of sub-processes, such as data log file generation, data parsing and information generation, behaviour profile identification through clustering, and the analysis of supply performance regarding each category of decision-making behaviour. Through experimentation with industrial purchasing agents, we validated the effectiveness of the approach and demonstrated how to achieve a quantitative analysis of decision making behaviour and its impact on supply performance. (C) 2017 Elsevier Ltd. All rights reserved.Human decision modellingOperational decisionSimulationBehaviour metricsSupply chain efficiencyQuantitative analysisA pilot study on eliciting human operations decision in purchasing and measuring their impact on supply chain efficiencytext::conference output::conference proceedings::conference paper