This study examines the global demand for Chief Digital Officers (CDOs) to determine a universal CDO archetype in terms of competencies and tasks. It uses Bayesian statistics and Latent Dirichlet Allocation (LDA) topic modeling to measure multiple dimensions in a sample of 518 job postings for CDO positions. Findings show the hybrid nature of newly appointed CDOs, who feature a mixture of both business administration and technological skills. Further, the study highlights the pivotal role of CDOs in terms of strategic change in companies. The study has three major contributions. First, it showcases the value of LDA in job profiling research. Second, it bridges the existing knowledge gaps in CDO literature with empirical evidence from a global dataset and identifies a core CDO profile based on data extracted through LDA. Third, it illustrates the current market requirements for CDO positions, which is useful to both companies and candidates.

中文翻译：

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首席数字官角色的实证识别：潜在狄利克雷分配方法

本研究调查了全球对首席数字官 (CDO) 的需求，以确定能力和任务方面的通用 CDO 原型。它使用贝叶斯统计和潜在狄利克雷分配 (LDA) 主题建模来测量 518 个 CDO 职位职位发布样本中的多个维度。调查结果显示了新任命的 CDO 的混合性质，他们兼具企业管理和技术技能。此外，该研究还强调了 CDO 在公司战略变革方面的关键作用。该研究有三个主要贡献。首先，它展示了LDA在工作剖析研究中的价值。其次，它利用全球数据集的经验证据弥合了 CDO 文献中现有的知识差距，并根据通过 LDA 提取的数据确定了核心 CDO 概况。第三，它说明了当前CDO职位的市场需求，这对公司和候选人都有用。