A Facile and General Approach to 3‑((Trifluoro­methyl)­thio)‑4<i>H</i>‑chromen-4-one

A facile and efficient synthetic strategy to 3-((trifluoro­methyl)­thio)-4<i>H</i>-chromen-4-one was developed. AgSCF₃ and trichloro­iso­cyanuric acid were employed here to generate active electrophilic trifluoromethylthio species in situ. This reaction could proceed under mild conditions in a short reaction time and be insensitive to air and moisture

Synthesis of Functionalized Chromeno­[2,3‑<i>b</i>]­pyrrol-4(1<i>H</i>)‑ones by Silver-Catalyzed Cascade Reactions of Chromones/Thiochromones and Isocyanoacetates

A novel and convenient approach to the synthesis of chromeno­[2,3-<i>b</i>]­pyrrol-4­(1<i>H</i>)-ones has been developed. Furthermore, the method involves a facile silver-catalyzed cascade cyclization reaction including an intramolecular C–O bond formation. The silver salt acts as a key promoter

Further research.

This paper theoretically analyzes and empirically examines the impact and mechanisms of automated machines on employment in manufacturing enterprises, drawing on task-based model and using micro data from listed Chinese manufacturing enterprises between 2012 and 2019. Our findings reveal that: (1) Automated machines in manufacturing enterprises leads to a substitution effect on the total labor force, with a substitution effect on low-skilled labor and a creation effect on high-skilled labor in terms of employment structure. (2) Further analysis indicates that automated machines primarily have a positive effect on R&D and technical staff, a non-significant effect on sales staff, and a negative impact on production, administrative, and financial staff. (3) The primary influencing mechanisms of automated machines on employment in manufacturing firms are productivity effects and output scale effects, based on the mediation effect model. (4) Considering the industry linkage effect, we employ the input-output method and the Input-Output Table and find that automated machines for upstream (downstream) manufacturing enterprises will result in a substitution effect on employment for downstream (upstream) enterprises. The novelties and research contributions are as follows: (1) we conduct a structural decomposition of total employment, and further decompose employment positions into production, R&D, sales, finance, and administration. (2) We try to investigate the industry linkage effect about the impact of automated machines on the employment of upstream and downstream enterprises. (3) We use data from listed manufacturing companies, and the data of existing research are about provincial and industry-level data.</div

Robustness tests.

This paper theoretically analyzes and empirically examines the impact and mechanisms of automated machines on employment in manufacturing enterprises, drawing on task-based model and using micro data from listed Chinese manufacturing enterprises between 2012 and 2019. Our findings reveal that: (1) Automated machines in manufacturing enterprises leads to a substitution effect on the total labor force, with a substitution effect on low-skilled labor and a creation effect on high-skilled labor in terms of employment structure. (2) Further analysis indicates that automated machines primarily have a positive effect on R&D and technical staff, a non-significant effect on sales staff, and a negative impact on production, administrative, and financial staff. (3) The primary influencing mechanisms of automated machines on employment in manufacturing firms are productivity effects and output scale effects, based on the mediation effect model. (4) Considering the industry linkage effect, we employ the input-output method and the Input-Output Table and find that automated machines for upstream (downstream) manufacturing enterprises will result in a substitution effect on employment for downstream (upstream) enterprises. The novelties and research contributions are as follows: (1) we conduct a structural decomposition of total employment, and further decompose employment positions into production, R&D, sales, finance, and administration. (2) We try to investigate the industry linkage effect about the impact of automated machines on the employment of upstream and downstream enterprises. (3) We use data from listed manufacturing companies, and the data of existing research are about provincial and industry-level data.</div

Results of baseline regression.

This paper theoretically analyzes and empirically examines the impact and mechanisms of automated machines on employment in manufacturing enterprises, drawing on task-based model and using micro data from listed Chinese manufacturing enterprises between 2012 and 2019. Our findings reveal that: (1) Automated machines in manufacturing enterprises leads to a substitution effect on the total labor force, with a substitution effect on low-skilled labor and a creation effect on high-skilled labor in terms of employment structure. (2) Further analysis indicates that automated machines primarily have a positive effect on R&D and technical staff, a non-significant effect on sales staff, and a negative impact on production, administrative, and financial staff. (3) The primary influencing mechanisms of automated machines on employment in manufacturing firms are productivity effects and output scale effects, based on the mediation effect model. (4) Considering the industry linkage effect, we employ the input-output method and the Input-Output Table and find that automated machines for upstream (downstream) manufacturing enterprises will result in a substitution effect on employment for downstream (upstream) enterprises. The novelties and research contributions are as follows: (1) we conduct a structural decomposition of total employment, and further decompose employment positions into production, R&D, sales, finance, and administration. (2) We try to investigate the industry linkage effect about the impact of automated machines on the employment of upstream and downstream enterprises. (3) We use data from listed manufacturing companies, and the data of existing research are about provincial and industry-level data.</div

Result of mechanism test.

This paper theoretically analyzes and empirically examines the impact and mechanisms of automated machines on employment in manufacturing enterprises, drawing on task-based model and using micro data from listed Chinese manufacturing enterprises between 2012 and 2019. Our findings reveal that: (1) Automated machines in manufacturing enterprises leads to a substitution effect on the total labor force, with a substitution effect on low-skilled labor and a creation effect on high-skilled labor in terms of employment structure. (2) Further analysis indicates that automated machines primarily have a positive effect on R&D and technical staff, a non-significant effect on sales staff, and a negative impact on production, administrative, and financial staff. (3) The primary influencing mechanisms of automated machines on employment in manufacturing firms are productivity effects and output scale effects, based on the mediation effect model. (4) Considering the industry linkage effect, we employ the input-output method and the Input-Output Table and find that automated machines for upstream (downstream) manufacturing enterprises will result in a substitution effect on employment for downstream (upstream) enterprises. The novelties and research contributions are as follows: (1) we conduct a structural decomposition of total employment, and further decompose employment positions into production, R&D, sales, finance, and administration. (2) We try to investigate the industry linkage effect about the impact of automated machines on the employment of upstream and downstream enterprises. (3) We use data from listed manufacturing companies, and the data of existing research are about provincial and industry-level data.</div

Estimated coefficients and confidence intervals of column 1 in Table 3.

Estimated coefficients and confidence intervals of column 1 in Table 3.</p

Results of industry linkage effects.

This paper theoretically analyzes and empirically examines the impact and mechanisms of automated machines on employment in manufacturing enterprises, drawing on task-based model and using micro data from listed Chinese manufacturing enterprises between 2012 and 2019. Our findings reveal that: (1) Automated machines in manufacturing enterprises leads to a substitution effect on the total labor force, with a substitution effect on low-skilled labor and a creation effect on high-skilled labor in terms of employment structure. (2) Further analysis indicates that automated machines primarily have a positive effect on R&D and technical staff, a non-significant effect on sales staff, and a negative impact on production, administrative, and financial staff. (3) The primary influencing mechanisms of automated machines on employment in manufacturing firms are productivity effects and output scale effects, based on the mediation effect model. (4) Considering the industry linkage effect, we employ the input-output method and the Input-Output Table and find that automated machines for upstream (downstream) manufacturing enterprises will result in a substitution effect on employment for downstream (upstream) enterprises. The novelties and research contributions are as follows: (1) we conduct a structural decomposition of total employment, and further decompose employment positions into production, R&D, sales, finance, and administration. (2) We try to investigate the industry linkage effect about the impact of automated machines on the employment of upstream and downstream enterprises. (3) We use data from listed manufacturing companies, and the data of existing research are about provincial and industry-level data.</div

Estimated coefficients and confidence intervals of column 3 in Table 3.

Estimated coefficients and confidence intervals of column 3 in Table 3.</p

Estimated coefficients and confidence intervals of column 2 in Table 3.

Estimated coefficients and confidence intervals of column 2 in Table 3.</p