A better method named MAGL (Multi-Attribute Gain Loss) is proposed to predict choices made by consumers in a multi-attribute setting. The MAGL method uses the tenets of prospect theory, Kauffman’s complexity theory, norm theory, and context-dependent choice theory. Since the choice processes are often found to be affected by the context or the choice set, the proposed MAGL method is able to model and predict the context-dependent choice behavior of consumers. The predictions of the MAGL method are useful to marketing/product managers in designing new products. The output of the MAGL method can be analyzed to determine which combination of attribute values is outperforming in a specific competitive market condition. A decision support system can be designed and developed for marketing/product managers where they can experiment by introducing, redesigning, or removing products and simulate the market share of various products for a similar consumer population.

提出了一种名为 MAGL（多属性增益损失）的更好方法来预测消费者在多属性设置中做出的选择。MAGL 方法使用前景理论、考夫曼复杂性理论、规范理论和上下文相关选择理论的原理。由于选择过程经常受到上下文或选择集的影响，因此所提出的 MAGL 方法能够建模和预测消费者依赖于上下文的选择行为。MAGL 方法的预测对于营销/产品经理设计新产品很有用。可以分析 MAGL 方法的输出，以确定哪种属性值组合在特定的竞争市场条件下表现出色。可以为营销/产品经理设计和开发决策支持系统，他们可以通过引入以下内容进行实验：