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    Descriptive Models of Sequential Decisions in Engineering Design: An Experimental Study

    Source: Journal of Mechanical Design:;2020:;volume( 142 ):;issue: 008
    Author:
    Chaudhari, Ashish M.
    ,
    Bilionis, Ilias
    ,
    Panchal, Jitesh H.
    DOI: 10.1115/1.4045605
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Engineering design involves information acquisition decisions such as selecting designs in the design space for testing, selecting information sources, and deciding when to stop design exploration. Existing literature has established normative models for these decisions, but there is lack of knowledge about how human designers make these decisions and which strategies they use. This knowledge is important for accurately modeling design decisions, identifying sources of inefficiencies, and improving the design process. Therefore, the primary objective in this study is to identify models that provide the best description of a designer’s information acquisition decisions when multiple information sources are present and the total budget is limited. We conduct a controlled human subject experiment with two independent variables: the amount of fixed budget and the monetary incentive proportional to the saved budget. By using the experimental observations, we perform Bayesian model comparison on various simple heuristic models and expected utility (EU)-based models. As expected, the subjects’ decisions are better represented by the heuristic models than the EU-based models. While the EU-based models result in better net payoff, the heuristic models used by the subjects generate better design performance. The net payoff using heuristic models is closer to the EU-based models in experimental treatments where the budget is low and there is incentive for saving the budget. This indicates the potential for nudging designers’ decisions toward maximizing the net payoff by setting the fixed budget at low values and providing monetary incentives proportional to saved budget.
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      Descriptive Models of Sequential Decisions in Engineering Design: An Experimental Study

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    contributor authorChaudhari, Ashish M.
    contributor authorBilionis, Ilias
    contributor authorPanchal, Jitesh H.
    date accessioned2022-02-04T14:19:57Z
    date available2022-02-04T14:19:57Z
    date copyright2020/02/14/
    date issued2020
    identifier issn1050-0472
    identifier othermd_142_8_081704.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4273447
    description abstractEngineering design involves information acquisition decisions such as selecting designs in the design space for testing, selecting information sources, and deciding when to stop design exploration. Existing literature has established normative models for these decisions, but there is lack of knowledge about how human designers make these decisions and which strategies they use. This knowledge is important for accurately modeling design decisions, identifying sources of inefficiencies, and improving the design process. Therefore, the primary objective in this study is to identify models that provide the best description of a designer’s information acquisition decisions when multiple information sources are present and the total budget is limited. We conduct a controlled human subject experiment with two independent variables: the amount of fixed budget and the monetary incentive proportional to the saved budget. By using the experimental observations, we perform Bayesian model comparison on various simple heuristic models and expected utility (EU)-based models. As expected, the subjects’ decisions are better represented by the heuristic models than the EU-based models. While the EU-based models result in better net payoff, the heuristic models used by the subjects generate better design performance. The net payoff using heuristic models is closer to the EU-based models in experimental treatments where the budget is low and there is incentive for saving the budget. This indicates the potential for nudging designers’ decisions toward maximizing the net payoff by setting the fixed budget at low values and providing monetary incentives proportional to saved budget.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleDescriptive Models of Sequential Decisions in Engineering Design: An Experimental Study
    typeJournal Paper
    journal volume142
    journal issue8
    journal titleJournal of Mechanical Design
    identifier doi10.1115/1.4045605
    page81704
    treeJournal of Mechanical Design:;2020:;volume( 142 ):;issue: 008
    contenttypeFulltext
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