Decoding excellence: Mapping the demand for psychological traits of
  operations and supply chain professionals through text mining
S. Di Luozzo A. Fronzetti Colladon M. M. Schiraldi
The current study proposes an innovative methodology for the profiling of
psychological traits of Operations Management (OM) and Supply Chain Management
(SCM) professionals. We use innovative methods and tools of text mining and
social network analysis to map the demand for relevant skills from a set of job
descriptions, with a focus on psychological characteristics. The proposed
approach aims to evaluate the market demand for specific traits by combining
relevant psychological constructs, text mining techniques, and an innovative
measure, namely, the Semantic Brand Score. We apply the proposed methodology to
a dataset of job descriptions for OM and SCM professionals, with the objective
of providing a mapping of their relevant required skills, including
psychological characteristics. In addition, the analysis is then detailed by
considering the region of the organization that issues the job description, its
organizational size, and the seniority level of the open position in order to
understand their nuances. Finally, topic modeling is used to examine key
components and their relative significance in job descriptions. By employing a
novel methodology and considering contextual factors, we provide an innovative
understanding of the attitudinal traits that differentiate professionals. This
research contributes to talent management, recruitment practices, and
professional development initiatives, since it provides new figures and
perspectives to improve the effectiveness and success of Operations Management
and Supply Chain Management professionals.