Abstract:Labour demand and skill shortages have historically been difficult to assess given the high costs of conducting representative surveys and the inherent delays of these indicators. This is particularly consequential for fast developing skills and occupations, such as those relating to Data Science and Analytics (DSA). This paper develops a data-driven solution to detecting skill shortages from online job advertisements (ads) data. We first propose a method to generate sets of highly similar skills based on a se… Show more
“…Technologies of robots and artificial intelligence (AI) are expected to replace simple labor and make workplaces more skill-polarized [2,3]. Researchers tried to predict the future of the job market based on numerical data (e.g., labor employment [4] and statistics of graduates [5]) or textual data (e.g., job postings [6,7], job attributes [8], and Google trends [9]). However, these approaches were mainly focused on occupational data and limitedly considered changes in technology.…”
The rapid change in technology makes it challenging to forecast the future of jobs. Previous studies have analyzed economics and employment data or employed expert-based methods to forecast the future of jobs, but these approaches were not able to reflect the latest technology trends in an objective way. To overcome the issue, this study matches jobs with patents and forecasts the future of jobs based on changes in the number of patents with time. A word embedding model is trained by patent classification code and job description data and used to find similar patent classification codes of jobs. For an illustration purpose, we identify information technology-related jobs listed in O*NET and discover similar patent classification codes of the jobs. Based on the change in the number of patents, we find promising jobs presenting high technical demands. Several implications of our approach are also discussed.
“…Technologies of robots and artificial intelligence (AI) are expected to replace simple labor and make workplaces more skill-polarized [2,3]. Researchers tried to predict the future of the job market based on numerical data (e.g., labor employment [4] and statistics of graduates [5]) or textual data (e.g., job postings [6,7], job attributes [8], and Google trends [9]). However, these approaches were mainly focused on occupational data and limitedly considered changes in technology.…”
The rapid change in technology makes it challenging to forecast the future of jobs. Previous studies have analyzed economics and employment data or employed expert-based methods to forecast the future of jobs, but these approaches were not able to reflect the latest technology trends in an objective way. To overcome the issue, this study matches jobs with patents and forecasts the future of jobs based on changes in the number of patents with time. A word embedding model is trained by patent classification code and job description data and used to find similar patent classification codes of jobs. For an illustration purpose, we identify information technology-related jobs listed in O*NET and discover similar patent classification codes of the jobs. Based on the change in the number of patents, we find promising jobs presenting high technical demands. Several implications of our approach are also discussed.
“…A skill shortage tool was proposed in [122]; the tool detects skill shortages by correlating different features in the job ad such as its location, salary level and the job ad period being advertised. In [85], they developed a data-driven solution to detect skill shortages from online job ads data. To do so, they identified skills specific to data science and analysis, to capture the labor trends of such an occupation.…”
This work is supported by a Google Africa PhD fellowship. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied of Google.
“…Therefore, workers to work on soft skills such as their learning ability, adaptability, communication skills, problem-solving and decision-making, teamwork, and creative capacity. Furthermore, 309,000 vacancies in 169 professions of various professional levels in the United Kingdom (UK) was analyzed [40]. The research indicated that employers found it difficult to recruit suitable workers in 106,000 of these positions.…”
Human resource development is one of the main issues in the socio-economic development strategy and the transform of any regions in the context of the Industry 4.0. However, Vietnamese human resources have been poorly evaluated in the areas of quality, lack of dynamism, and creativity. Therefore, this paper presents fuzzy logic approach to ranking seven skills shortage in Vietnam’s Labor Market, namely lifelong learning, adaptive capacity, information technology capacity, creativity and innovation capacity, problem-solving capacity, foreign language competency, and organizing and managing competency. The result results shown that the problem solving skill is the largest gap between an enterprise’s requirements and the actual response of employees.
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