Abstract
Decision-makers’ intelligence is usually pre-assumed to be sufficient and contingent to satisfy various requirements in different decision support models. However, it can be hardly assured that decision-makers can be so intelligent as required in practical decision-making circumstances. This paper aims to demonstrate the influences of decision-makers’ intelligence level on decision-making models. Simulation and laboratory experiments are designed and carried out. In the simulation experiment, memory capacity and computation ability, two most important ingredients of intelligence, are introduced into the distribution-free newsvendor problem. Memory capacity is defined as the temporal length of historical data that newsvendor can memorize, and computation ability as intuitive complexity of the model applied to determine his optimal order. Then by setting up various intelligence levels, namely, different levels of memory capacity and computation ability, three typical ordering policies of various levels of intuitive complexity are simulated in the framework of the distribution-free newsvendor problem. Then, a laboratory experiment is executed. The ratio between the number of groups of historical demand and data analysis time length and the time length of order-making are defined as the comprehensive index of subject’s memory capacity and computation ability. The results of both the experiments demonstrate that the decision-maker’s memory capacity and computation ability have significant and positive influences on decision-maker’s expected profit. The results might present another piece of the reason that why decision-makers do not always act optimally.
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