What drives a researcher’s preferences for chemical compounds? Evidence from conjoint analysis

We investigated which attribute and attribute level affect researchers’ preferences for chemical compounds. Drawing on survey data for Korean researchers using chemical compounds provided by the Korean Chemical Bank (KCB), we conducted a conjoint analysis, through which the part-worth utility for each attribute’s level was estimated, the relative importance values of attributes were calculated, and user segmentation with different patterns was classified. The results of this study show that the structure database offers the highest part-worth utility to the researchers, followed by high new functionality, price, screening service, and drug action data provided only by the KCB. Notably, researchers view the offer of a structured database and high new functionality as more important in decision-making about the research and development (R&D) use of chemical compounds than other attributes. Furthermore, the results of user segmentation present different patterns of the use of chemical compounds: researchers group the most appealing to structure database and improved new functionality attributes. We discussed some policy and strategic implications based on the findings of this study and proposed some limitations.

本研究旨在探究哪些属性及属性水平会影响科研人员对化学化合物的偏好。本研究依托韩国化学银行（Korean Chemical Bank, KCB）提供的化学化合物相关调研数据，针对韩国科研人员开展研究，通过联合分析（conjoint analysis）方法，估算得到各属性水平的部分价值效用，计算出各属性的相对重要性分值，并对具有不同使用模式的用户进行了聚类细分。研究结果显示，结构数据库对科研人员的部分价值效用最高，其次为优异的新颖性功能、价格、筛选服务，以及仅由KCB提供的药物作用数据。值得注意的是，相较于其他属性，科研人员在化学化合物研发（R&D）使用决策中，更重视结构数据库与优异新颖性功能的提供。此外，用户细分结果呈现出不同的化学化合物使用模式：存在一类对结构数据库及优化型新颖性功能属性最为青睐的科研人员群体。本研究基于上述发现探讨了相关政策与战略启示，并提出了本研究的局限性。