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Beyond main effects assumption in conjoint analysis comparison of conjoint value analysis vs. choice-based conjoint. Statistical approach and construction of desings applied to new product development

机译：联合价值分析与基于选择的联合的联合分析中的联合分析中的主要影响假设。统计方法和设计应用于新产品开发

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The assumption of only main effects in Conjoint Analysis methods has created a debate whether to focus or not on the impact of interactions that were tested in this research.Different conjoint methodologies have been used in new product development studies and diverse results have come to which of them perform better to obtain information from respondents. A comparison of Conjoint Value Analysis CVA and Choice-Based Conjoint CBC surveys were undertaken to contrast them through utility scores, importance values of attributes and goodness-of-fit found in both methodologies using ready to drink beverages as the subject. The main effects assumption in the CVA composition rule was compared to the interaction terms in the CBC one. Two scenarios were developed;the first one considered inner characteristics of the subject and a sample size of 250 respondents. The second one considered the presentation characteristics of the subject and a sample size of 150 respondents. The attribute importance order in each methodology for Scenario 1 was different, while in Scenario 2 it was the same. Significant differences were encountered among attribute levels and within them; the same pattern was found in bothmethodologies and in both scenarios.The two higher total utility scores were obtained in the CBC using an interactive composition rule that considered beer, whereas in the CVA this level reported a negativeutility. In Scenario 1 a higher goodness-of-fit was found in the CBC, including significant interactions, in contrast with Scenario 2, where no interactions were found, and CVA had a higher goodness-of-fit.Despite the fact that the design and calculations of a Choice-Based Conjoint were not as straightforward and well-known as the design and calculations of a traditional conjoint analysis, the inclusion of interactions is valuable information that researchers in future studies should consider.
机译：联合分析方法中只有主要作用的假设引发了一场争论，即是否要关注本研究中测试的交互作用的影响。在新产品开发研究中使用了不同的联合方法，得出了哪些不同的结果？他们在从受访者那里获得信息方面表现更好。进行了联合价值分析CVA与基于选择的联合CBC调查的比较，以通过使用即饮饮料为主题的两种方法中的效用得分，属性重要性值和拟合优度来进行对比。将CVA组成规则中的主要影响假设与CBC中的交互作用项进行了比较。开发了两种方案；第一种方案考虑了主题的内部特征，并有250名受访者作为样本。第二个考虑了主题的呈现特征和150名受访者的样本量。方案1的每种方法中的属性重要性顺序不同，而方案2中的属性重要性顺序相同。属性级别之间以及属性级别之间存在重大差异；在两种方法和两种方案中都发现了相同的模式。在CBC中，使用考虑了啤酒的交互式成分规则获得了两个更高的总效用得分，而在CVA中，该水平报告为负效用。在方案1中，CBC中发现了较高的拟合优度，包括显着的交互作用，而在方案2中则没有交互，CVA则具有较高的拟合优度。基于选择的联合的计算并不像传统联合分析的设计和计算那样简单明了，众所周知，交互作用的包含是未来研究中研究人员应考虑的有价值的信息。

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