Assessing the impact of technological change on similar occupations: Implications for employment alternatives

BACKGROUND

The fast-changing labor market highlights the need for an in-depth understanding of occupational mobility impacted by technological change. However, we lack a multidimensional classification scheme that considers similarities of occupations comprehensively, which prevents us from predicting employment trends and mobility across occupations. This study fills the gap by examining employment trends based on similarities between occupations.

METHOD

We first demonstrated a new method that clusters 756 occupation titles based on knowledge, skills, abilities, education, experience, training, activities, values, and interests. We used the Principal Component Analysis to categorize occupations in the Standard Occupational Classification, which is grouped into a four-level hierarchy. Then, we paired the occupation clusters with the occupational employment projections provided by the U.S. Bureau of Labor Statistics. We analyzed how employment would change and what factors affect the employment changes within occupation groups. Particularly, we specified factors related to technological changes.

RESULTS

The results reveal that technological change accounts for significant job losses in some clusters. This poses occupational mobility challenges for workers in these jobs at present. Job losses for nearly 60% of current employment will occur in low-skill, low-wage occupational groups. Meanwhile, many mid-skilled and highly skilled jobs are projected to grow in the next ten years.

CONCLUSION

Our results demonstrate the utility of our occupational classification scheme. Furthermore, it suggests a critical need for skills upgrading and workforce development for workers in declining jobs. Special attention should be paid to vulnerable workers, such as older individuals and minorities.

Is intuition better than rationality? The effect of pre-decisional strategy on occupational interest forecasting in Chinese college students

Purpose

Previous studies showed that the unconscious-intuitive strategy resulted in a better choice for it is more predictive of actual interest. This benefit may be influenced by occupational engagement, for the dual process of career decisions takes it as a tool for multidevelopment and optimal adjustment. Thus, we replicated (and extended) the study of Motl et al. (2018) through two experiments to identify the role of three pre-decisional strategies and then explore the combined effects of occupational engagement and these strategies. The purpose of this paper is to address these issues.

Design/methodology/approach

The authors replicated (and extended) the study of Motl et al. (2018) through two experiments. First, both studies adopted generalized linear mixed-effects models for statistical analyses to distinguish random and fixed effects. Second, Study 2 used a computer-based process-tracing program called “Mouselab” to explore the effect of the pre-decisional strategy self-generated on participants' interest appraisals over time.

Findings

Study 1 found that engagement helped promote participants' interest experience when decisions as usual and the intuitive strategy did not produce optimal choices. Further, people with more prior knowledge about situations no longer achieved as many benefits from their allocated strategy (i.e. rational strategy) as those with less. Study 2 failed to find adequate advantages of the intuitive strategy. Specifically, people with less search depth (the heuristic-intuitive strategy) were more interested in their choices. Nevertheless, when the strategy was manipulated as variability of search (VS), it only found the promotion of engagement, but it neither found the interaction between engagement and strategy nor did strategy itself.

Originality/value

The present paper provides mixed support for adaptive career decision-making. Career counselors can use occupational engagement levels as a reference for pre-decisional strategy selection and coach clients to adopt a proper decision-making process/method to make interest forecasts.

Improving Graduate-School Admissions by Expanding Rather Than Eliminating Predictors

The article by Woo et al. (this issue) reviews the existing research on graduate-school admissions measures. The goal of this commentary is to expand on their review and suggest several ways of supplementing the Graduate Record Examination (GRE) to both increase the predictive validity of admissions decisions and improve the diversity of a graduate program. We rely on several decades of research to suggest assessing both conscientiousness and vocational interests and combining the scores from these predictors with the GRE to inform admissions decisions. In addition, we also propose several ways of expanding recruitment efforts to attract qualified underrepresented minority applicants to improve the diversity of the applicant pool.