Reasons for college major-job mismatch and labor market outcomes: Evidence from China

Jiang, Shengjun; Guo, Yuanbiao

doi:10.1016/j.chieco.2022.101822

Cited by 10 publications

(8 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The structural contradiction between employment difficulty and recruitment difficulty highlights the disharmony between the structure of higher education and the demand for talents of economic and social development ( 72 ). Moreover, during the COVID-19 epidemic, the structural mismatch between the skills owned by college graduates and the skills needed by jobs becomes the major challenge for college graduates’ employment in China ( 73 ). In addition, research has shown that the employment structural contradiction was more provident and become the main contradiction in the employment field under the impact of the COVID-19 ( 20 ).…”

Section: The Impacts On the Employment Of College Graduates Caused By...mentioning

confidence: 99%

Review of the impacts of COVID-19 pandemic on the employment of college graduates in China and countermeasures to it

Wang,

Wang

2024

Front. Public Health

View full text Add to dashboard Cite

The employment of college graduates has always been the focus issue of the whole society. Affected by the COVID-19, college graduates are facing a severe employment situation. In the present study, we explore the impacts of the COVID-19 on the employment of college graduates. We explore the employment promotion measures introduced by Chinese government and colleges and universities through a quick review and illustrate the difficulties that college graduates face. Furthermore, the present study explores the impacts of the COVID-19 on five aspects of the employment of college graduates: recruitment demand reduce, employment competition rise, employment channels change, psychological anxiety increase and employment structural contradiction intensify. In addition, we conclude that the employment promotion measures introduced by Chinese government and colleges and universities in respond to the impacts of the COVID-19 on the employment of college graduates have significantly promoted the employment of college graduates to a large extent and we provide implications based on the application of the study. The findings of the present study are of great significance for all countries worldwide to better cope with various similar emergency events, to alleviate employment pressure and to promote better and fuller employment of college graduates.

show abstract

Section: The Impacts On the Employment Of College Graduates Caused By...mentioning

confidence: 99%

Review of the impacts of COVID-19 pandemic on the employment of college graduates in China and countermeasures to it

Wang,

Wang

2024

Front. Public Health

View full text Add to dashboard Cite

show abstract

“…Scholars note that the causes of the skills mismatch differ according to the type of economy (formal or informal) and the type of country (lower income, middle income, or high income). Jiang and Guo (2022) argue that, unlike interest-mismatch workers, the skill-mismatch (and demand-mismatch) occurs due to structural reasons. Palmer (2017) notes information asymmetries and inadequacies, low education base of people, unequal access to training, underdeveloped markets for skills, lack of attention from public training providers to the needs, and constraints to training as some of the causes of skills mismatch in the informal economy.…”

Section: Causes and Consequences Of Skills Mismatchmentioning

confidence: 99%

“…According to Arayssi et al (2023), the Middle East and North Africa (MENA) area has substantial young unemployment due to skill mismatch, affecting employees' income, job satisfaction, and career development while lowering the company's productivity as well. Additionally, Jiang & Guo (2022) found that skill mismatch is linked to decreased chances of employment stability, promotion, and job satisfaction. The authors add that the effect is considerably stronger in demographic groups that include women, immigrants, and ethnic minorities.…”

Section: Causes and Consequences Of Skills Mismatchmentioning

confidence: 99%

Skills Mismatch in Entry-level Programmer Positions: Employer Expectations vs. Observations in Lalitpur, Nepal

Puri

2024

JER

View full text Add to dashboard Cite

Despite an annual influx of programming graduates from Information Technology (IT)-focused educational institutions, software companies struggle with the persistent challenge of finding qualified candidates for entry-level programming roles. In this context of skill shortage, this study explored the crucial issue of skill mismatch of IT graduates, by assessing the employers’ expectations and observations vital for entry-level programming positions. This study employed a quantitative survey approach to delve into this skills mismatch issue. Professionals within 128 software development companies in Lalitpur were surveyed, all holding managerial positions and possessing programming experience. Utilizing a Likert scale questionnaire distributed through Google Forms, these industry experts rated their expectations and real-world observations concerning the specific skills requisite for entry-level programming positions. The analysis of expectations of skills showed that learning attitude (personal), basic concepts of programming (technical), and organizational culture fit (interpersonal) were considered the most important skills. Personal or college projects and skills in version management and testing were considered equally important. The analysis of skill expectations versus observations uncovers noteworthy disparities, mostly observed in personal skills, with expectations significantly exceeding actual observations. Almost 50% of the skills were found to have high importance and high gaps, most of which were personal skills. The discrepancy was comparatively less in interpersonal and technical compared to personal skills. Perceptions regarding the alignment of knowledge, skills, and attitude (KSA) were mixed in which most of the respondents indicated moderate to strong alignment between expectations and observations for knowledge and skills, while weak alignment for attitudes. Statistical analysis confirmed significant mean differences between expected and observed skills across all skill categories, reaffirming the existence of a skills mismatch. Notably, employers overwhelmingly advocate ii addressing these skill mismatches through training and development initiatives. These findings shed light on the multifaceted nature of the skills mismatch challenge in Lalitpur’s entry-level programming job market, emphasizing the need for targeted interventions to bridge this gap and foster alignment between employer expectations and the skills of recent graduates. Aligning curriculum with industry needs and designing skill development approaches is of utmost importance to enhance graduates’ workforce readiness, facilitating a smoother transition for entry-level programmer positions.

show abstract

“…However, when processing whole chickens, the processing plant follows a procedure where the chicken parts are first cut and then manually sorted. This manual sorting approach is inefficient, error prone, and does not provide a guarantee for product safety (Jiang, 2022; J. Li et al., 2021). As living standards continue to improve and the demand for food consumption increases, there is a growing demand for chicken products that cater to a variety of segmented taste preferences.…”

Section: Introductionmentioning

confidence: 99%

Research on automatic classification and detection of chicken parts based on deep learning algorithm

Chen,

Peng,

Cai

et al. 2023

Journal of Food Science

View full text Add to dashboard Cite

Accurate classification and identification of chicken parts are critical to improve the productivity and processing speed in poultry processing plants. However, the overlapping of chicken parts has an impact on the effectiveness of the identification process. To solve this issue, this study proposed a real‐time classification and detection method for chicken parts, utilizing YOLOV4 deep learning. The method can identify segmented chicken parts on the assembly line in real time and accurately, thus improving the efficiency of poultry processing. First, 600 images containing multiple chicken part samples were collected to build a chicken part dataset after using the image broadening technique, and then the dataset was divided according to the 6:2:2 division principle, with 1200 images as the training set, 400 images as the test set, and 400 images as the validation set. Second, we utilized the single‐stage target detector YOLO to predict and calculate the chicken part images, obtaining the categories and positions of the chicken leg, chicken wing, and chicken breast in the image. This allowed us to achieve real‐time classification and detection of chicken parts. This approach enabled real‐time and efficient classification and detection of chicken parts. Finally, the mean average precision (mAP) and the processing time per image were utilized as key metrics to evaluate the effectiveness of the model. In addition, four other target detection algorithms were introduced for comparison with YOLOV4‐CSPDarknet53 in this study, which include YOLOV3‐Darknet53, YOLOV3‐MobileNetv3, SSD‐MobileNetv3, and SSD‐VGG16. A comprehensive comparison test was conducted to assess the classification and detection performance of these models for chicken parts. Finally, for the chicken part dataset, the mAP of the YOLOV4‐CSPDarknet53 model was 98.86% on a single image with an inference speed of 22.2 ms, which was higher than the other four models of YOLOV3‐Darknet53, YOLOV3‐MobileNetv3, SSD‐MobileNetv3, and SSD‐VGG16 mAP by 3.27%, 3.78%, 6.91%, and 6.13%, respectively. The average detection time was reduced by 13, 1.9, 6.2, and 20.3 ms, respectively. In summary, the chicken part classification and detection method proposed in this study offers numerous benefits, including the ability to detect multiple chicken parts simultaneously, as well as delivering high levels of accuracy and speed. Furthermore, this approach effectively addresses the issue of accurately identifying individual chicken parts in the presence of occlusion, thereby reducing waste on the assembly line.Practical ApplicationThe aim of this study is to offer visual technical assistance in minimizing wastage and resource depletion during the sorting and cutting of chicken parts in poultry production and processing facilities. Furthermore, considering the diverse demands and preferences regarding chicken parts, this research can facilitate product processing that caters specifically to consumer preferences.

show abstract

Reasons for college major-job mismatch and labor market outcomes: Evidence from China

Cited by 10 publications

References 36 publications

Review of the impacts of COVID-19 pandemic on the employment of college graduates in China and countermeasures to it

Review of the impacts of COVID-19 pandemic on the employment of college graduates in China and countermeasures to it

Skills Mismatch in Entry-level Programmer Positions: Employer Expectations vs. Observations in Lalitpur, Nepal

Research on automatic classification and detection of chicken parts based on deep learning algorithm

Contact Info

Product

Resources

About