Analysis of stock management gaming experiments and alternative ordering formulations

This paper investigates two different yet related research questions about stock management in feedback environments. The first purpose is to analyse the effects of selected experimental factors on the performances of subjects (players) in a stock management simulation game. In light of these results, our second objective is to evaluate the adequacy of standard decision rules typically used in dynamic stock management models and to seek improvement formulations. To carry out the research, the generic stock management problem is chosen as the interactive gaming platform. In the first part, gaming experiments are designed to test the effects of three factors on decision-making behaviour: different patterns of customer demand, minimum possible order decision (‘review’) interval and, finally, the type of receiving delay. ANOVA results of these three-factor, two-level experiments show which factors have significant effects on 10 different measures of behaviour (such as max–min range of orders, inventory amplitudes, periods of oscillations and backlog durations). In the second phase of research, the performances of subjects are compared against some selected ordering heuristics (formulations). First, the patterns of ordering behaviour of subjects are classified into three basic types. Comparing these three pattern types with simulation results using different decision rules, we observe that the common linear ‘anchoring and adjustment rule’ can represent the smooth and gradually damping type of behaviour, but cannot generate the non-linear and/or discrete ordering dynamics. Thus, several alternative non-linear rules are formulated and tested against subjects' behaviour patterns. Some standard discrete inventory control rules (such as (s, S)) common in the inventory management literature are also formulated and tested. These non-linear and/or discrete rules, compared with the linear stock adjustment rule, are found to be more representative of the subjects' ordering behaviour in many cases, in the sense that these rules can generate non-linear and/or discrete ordering behaviours. Another major finding is the fact that the well-documented oscillatory dynamic behaviour of the inventory is a quite general result, not just an artifact of the linear anchor and adjust rule. When the supply line is ignored or underestimated, large inventory oscillations result also with the non-linear rules, as well as the standard inventory management rules. Furthermore, depending on parameter values, non-linear ordering rules are more prone to yield unstable oscillations—even if the supply line is taken into account. Further methodological and experimental research questions are suggested. Copyright © 2004 John Wiley & Sons, Ltd.