Purpose This study aims to identify the most in-demand employability skills for Life Cycle Assessment (LCA) professionals by analysing job advertisements through textual big data techniques. The research addresses four main questions: (a) which skills are most frequently required for LC-related roles; (b) what thematic areas emerge in the skill profiles of LC professionals; (c) how these skills are correlated and co-requested across job postings; and (d) how future demand for key skills may evolve. The goal is to support employers, educators, and professionals in understanding the shifting landscape of skill requirements within sustainability-oriented industries, especially in light of the circular and digital twin transition. Methods Using a text mining approach, a corpus of 32,783 job descriptions relevant to life cycle professionals were obtained from major US job portals. Term frequency, stylometry, clustering and topic modeling identified critical skills in this domain. Subsequently, Markov Chain Monte Carlo simulations were applied to model interview scenarios and analyze skill correlations. Results and discussion Results revealed that the most frequently requested skills for life cycle professionals include energy transition planning, carbon footprint analysis, and environmental legislation compliance, indicating a strong emphasis on sustainability practices. Topic modeling and network analysis identified significant correlations between skills such as project management and performance quality management, underscoring their co-requirement in job ads. Conclusions Findings demonstrate that life cycle professionals must possess a comprehensive skill set that balances technical competencies in sustainability with leadership and project management abilities. As environmental regulations and corporate sustainability targets evolve, professionals with expertise in energy transition and environmental impact will be highly sought after. These results provide valuable insights for professionals aiming to remain competitive in a rapidly changing job market. Limitations The study’s data collection concluded in September 2024. Consequently, any trend changes beyond this point are not reflected, and would need to be addressed in subsequent studies. Furthermore, the methods employed in this study, while valuable and comprehensive, come with inherent limitations. Despite these constraints, significant insights into the skill requirements and employability landscape for life cycle professionals were provided. Recommendations It is recommended that both educational institutions and employers prioritize the development of the identified skills in their training programs. Additionally, further research would provide the opportunity to explore how emerging technologies, such as AI and machine learning, as well as regulatory shifts may impact the future demand for specific competencies in the field.

Profiling employability skills for life cycle professionals amid the circular and digital economy

Mainolfi G
2025-01-01

Abstract

Purpose This study aims to identify the most in-demand employability skills for Life Cycle Assessment (LCA) professionals by analysing job advertisements through textual big data techniques. The research addresses four main questions: (a) which skills are most frequently required for LC-related roles; (b) what thematic areas emerge in the skill profiles of LC professionals; (c) how these skills are correlated and co-requested across job postings; and (d) how future demand for key skills may evolve. The goal is to support employers, educators, and professionals in understanding the shifting landscape of skill requirements within sustainability-oriented industries, especially in light of the circular and digital twin transition. Methods Using a text mining approach, a corpus of 32,783 job descriptions relevant to life cycle professionals were obtained from major US job portals. Term frequency, stylometry, clustering and topic modeling identified critical skills in this domain. Subsequently, Markov Chain Monte Carlo simulations were applied to model interview scenarios and analyze skill correlations. Results and discussion Results revealed that the most frequently requested skills for life cycle professionals include energy transition planning, carbon footprint analysis, and environmental legislation compliance, indicating a strong emphasis on sustainability practices. Topic modeling and network analysis identified significant correlations between skills such as project management and performance quality management, underscoring their co-requirement in job ads. Conclusions Findings demonstrate that life cycle professionals must possess a comprehensive skill set that balances technical competencies in sustainability with leadership and project management abilities. As environmental regulations and corporate sustainability targets evolve, professionals with expertise in energy transition and environmental impact will be highly sought after. These results provide valuable insights for professionals aiming to remain competitive in a rapidly changing job market. Limitations The study’s data collection concluded in September 2024. Consequently, any trend changes beyond this point are not reflected, and would need to be addressed in subsequent studies. Furthermore, the methods employed in this study, while valuable and comprehensive, come with inherent limitations. Despite these constraints, significant insights into the skill requirements and employability landscape for life cycle professionals were provided. Recommendations It is recommended that both educational institutions and employers prioritize the development of the identified skills in their training programs. Additionally, further research would provide the opportunity to explore how emerging technologies, such as AI and machine learning, as well as regulatory shifts may impact the future demand for specific competencies in the field.
2025
Employability
Life Cycle Professionals
Markov Chain Monte Carlo
Text mining
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14090/12061
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
social impact