In Germany enrolment in majors is of considerable interest to academic departments, because their budget depends on the number of enrolled students. Besides observed factors, we presume that unobserved latent variables influence the major‐choice decision of students. Using stated preferences data from a discrete choice experiment among students pursuing a bachelor’s degree in business administration at Hamburg Business School (HBS), we employ an integrated choice and latent variable model (ICLV). Thereby, we model the influence of a major‐specific latent variable, labeled image, on the major‐choice decision of the students. To identify the latent variables, we utilise ordered categorical indicators that we obtained from the assessment of major‐specific psychometric factors among students. Our findings reveal a significant impact of the latent variable image on the major‐choice decision. We further show the advantageous characteristic of an ICLV model by illustrating the cause‐and‐effect relationship compared to classic multinomial logit models. Based on our results, we examine practice‐oriented, requirements, research, and supervision to be the most relevant psychometric factors that lead to the identification of the latent variables and provide insights on how academic departments at HBS can raise their major’s attractiveness from the student’s perspective.

中文翻译：

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学生的看法，学术部门的形象以及企业管理研究的主要选择-以汉堡商学院为例

在德国，专业部门的入学兴趣很大，因为其预算取决于在校学生的数量。除了观察到的因素外，我们还假定未观察到的潜在变量会影响学生的主要选择决定。使用汉堡商学院（HBS）攻读工商管理学士学位的学生中的离散选择实验陈述的偏好数据，我们采用了综合选择和潜在变量模型（ICLV）。因此，我们对特定专业的潜在变量（标记图像）对学生的专业选择决策的影响进行建模。为了识别潜在变量，我们利用从学生对主要心理心理因素的评估中获得的有序分类指标。我们的发现揭示了潜在变量图像对主要选择决策的重大影响。通过说明与经典多项式logit模型相比的因果关系，我们进一步展示了ICLV模型的优势。根据我们的结果，我们将以实践为导向，需求，研究和监督作为最相关的心理计量因素，以识别潜在变量，并就哈佛商学院的学术部门如何提高学生的专业吸引力提供见解。看法。