Mon, 11/30/2020 - 10:59 — lac-admin
2020-11-30
By Labour Action China
September 17, 2020
This research aims to investigate the work resumption situation in the middle area of Guangdong (“Guangdong research”).
This research will take Research on the Work Resumption in Sichuan and Chongqing (“Sichuan research” conducted between April and July 2020) as a comparison. The similarities between the Sichuan research and the Guangdong research make the compassion feasible and meaningful. Questionnaires of these two research were distributed at similar times and the research participants of these two research are dominantly grassroots workers in similar industries [1].
Part 1: Methodology
This study retrieved 99 responses (95 valid responses). All the samples were collected by LAC’s partners and their volunteers in Mainland China through online questionnaires. The volunteers distributed the questionnaires among workers working in the Huizhou jewelry industry between early March and May. Besides, Guangzhou questionnaires were released on 5 May and retrieved on 27 August, and Shenzhen and Huizhou questionnaires were distributed between early July and mid-July. Samples collected at an earlier time may present a worse work resumption situation, as the economic recession was more serious at that time. However, because there are only three responses from the Huizhou jewelry industry, it is insignificant to the whole analysis result.
All the questionnaires in this study were collected through online platforms, including volunteers’ WeChat moments and WeChat groups. Additionally, this study also used snowball sampling: volunteers got in touch with individual research participants and invited them to distribute the questionnaire to other people. Therefore, this research only indicates the work resumption situation in a certain group of people in Guangdong.
Part 2: Background information of the research participants
Table 1 illustrates that the proportion of the female interviewees (56.84%) is 13.68% higher than the proportion of the male interviewees. 90.52% of the interviewees are middle-aged people aged 26 to 55 years old. Besides, interviewees with registered household (hukou)in Guangdong Province only account for 16.13%. It indicates that peasant workers are the majority in this study (27.96% from Sichuan and 17.20% from Hunan). Most interviewees work in Guangzhou (33.68%), Shenzhen (32.63%), and Huizhou (26.32%), and only a small number of interviewees work in Dongguan (7.37%). Furthermore, grassroots workers occupied 94.05% of the participants, and the jewelry industry (31.58%), hardware industry (13.68%), and household electrical appliance industry (11.58%) are three major industries. Lastly, most of the research participants are employed by middle-scaled and small-scaled companies, and nearly 50% of the participants work for companies with less than 50 employees, while 29.47% of them work for companies with 50 to 200 employees.
Table 1: Background information of the research participants
|
Type |
Option |
Ratio |
|
Gender |
Male |
43.16% |
|
Female |
56.84% |
|
|
Age |
16-25 |
6.32% |
|
26-35 |
32.63% |
|
|
36-45 |
29.47% |
|
|
46-55 |
28.42% |
|
|
≥56 |
3.16% |
|
|
Household Register (93 valid responses) |
Sichuan |
27.96% |
|
Hunan |
17.20% |
|
|
Guangdong |
16.13% |
|
|
Guizhou |
4.30% |
|
|
Jiangxi |
7.53% |
|
|
Henan |
3.23% |
|
|
Chongqing |
9.68% |
|
|
Guangxi |
6.45% |
|
|
Yunnan |
5.38% |
|
|
Fujian |
2.15% |
|
|
Location of the workplace |
Guangzhou |
33.68% |
|
Shenzhen |
32.63% |
|
|
Huizhou |
26.32% |
|
|
Dongguan |
7.37% |
|
|
Industry |
Hardware |
13.68% |
|
Furniture |
5.26% |
|
|
Household electrical appliance |
11.58% |
|
|
Plastic |
7.37% |
|
|
Construction |
2.11% |
|
|
Jewelry |
31.58% |
|
|
Other |
28.42% |
|
|
Job position |
Worker |
94.05% |
|
Clerk |
2.38% |
|
|
Sale |
3.57% |
|
|
Company scale |
<10 |
10.53% |
|
10~50 |
40% |
|
|
50~200 |
29.47% |
|
|
200~1000 |
9.47% |
|
|
>1000 |
10.53% |
Part 3: Work resumption situation
1. Delayed work resumption
(1) 87.37% of the interviewees delayed work resumption, and only 22.89% of them received full payment during the delayed period
In this research, 87.37% of the respondents delayed work resumption, which is similar to the result of the Sichuan research. Besides, Table 2 presents that all the research participants had returned to work when they filled out the questionnaire. However, 52.63% of the interviewees indicated that only part of the employees had returned to work in their companies.
Table 2: Did you returned to work?
|
Option |
Number |
Ratio |
|
|
No |
0 |
0.00% |
|
|
Yes |
All the employees have returned to work in my workplace |
45 |
47.37% |
|
Only part of the employees has returned to work in my workplace |
50 |
52.63% |
|
Besides, the interviewees in this research returned to work much earlier than those in the Sichuan research. Specifically, 47.06% of the respondents returned to work in February and 41.18% in March (see Table 3). In the Sichuan research, 42% of the respondents did not come back to work until April, and the difference of economic development between these two provinces may cause this distinction.
Table 3: When did you return to work?
|
Option |
Number |
Ratio |
|
February |
50 |
47.06% |
|
March |
35 |
41.18% |
|
April |
8 |
9.41% |
|
May |
1 |
1.18% |
|
I have not returned to work |
1 |
1.18% |
|
85 valid responses |
||
In terms of the labour rights protection, 21.69% of the research participants did not receive any payment during the delayed period and 22.89% received full payment (see Table 4). In the Guangdong research, the proportion of the respondents who received no payment is less than that in the Sichuan research (-13.94%), while the proportion of delayed payment is similar in two research (-0.54%).
Table 4: Did you receive full payment during the delayed period?
|
Option |
Number |
Ratio |
|
Full payment |
19 |
22.89% |
|
Delayed payment |
11 |
13.25% |
|
Partial payment |
22 |
26.51% |
|
No payment |
18 |
21.69% |
|
Other |
13 |
15.66% |
|
83 valid responses |
||
(2) 28.42% of the respondents were quarantined, and only 33.33% of them received full payment during the quarantine period
According to Table 5, 28.42% of the interviewees were quarantined, and only 33.33% of them received full payment during the quarantine period. This figure was 9.53% lower than that in the Sichuan research. However, the proportion of the interviewees received “no payment” and “partial payment” is smaller in the Sichuan research (-9.52%).
Table 5: Did you receive full payment during the quarantine
|
Option |
Number |
Ratio |
|
No payment |
1 |
5.56% |
|
Partial Payment |
11 |
61.11% |
|
Full Payment |
6 |
33.33% |
|
18 valid responses (this table has excluded samples which choose “others” option) |
||
2. Labour rights condition
(1) 21.05% of the interviewees do not enjoy the social insurance protection
78.95% of the respondents indicated that their employers have paid their social insurance, which is 11.49% more than that in the Sichuan research. However, in this research, 21.05% of the employers did not purchase social insurance. It has violated the Labour Law.
(2) 70.35% of the respondents received free protective equipment
Concerning the health protective measures, 70.35% of the interviewees can get access to free protective equipment in their workplaces, and the corresponding number is 19.65% higher than that in the Sichuan research. Furthermore, free protective equipment that the interviewees received includes face masks (98.51%), sanitizer (5.97%), and hand wash (4.48%).
3. Working condition before and after the COVID-19 pandemic outbreak
(1) Salary level: 58.51% of the interviewees said that their salary declined and 84.48% of the interviewees’ employers did not negotiate with their employees about change of payment
58.51% of the participants said that their salary declined after the pandemic outbreak, while 40.43% of the participants’ salary remained the same. It is similar to the data in the Sichuan research (see Table 6). However, 84.48% of the participants complained that their employers did not negotiate with them about the salary change, but only 33.33% of the interviewees complained so in the Sichuan research. It shows that enterprises in Guangdong are more likely to disregard the legal rights of workers when they plan to adjust wage level, and the labour relations are more unequal.
Table 6: Did your salary level change after the pandemic outbreak?
|
Option |
Number |
Ratio |
|
No |
38 |
40.43% |
|
Declined |
55 |
58.51% |
|
Increased |
1 |
1.06% |
|
94 valid responses |
||
(2) Workload: 10.54% of the participants said their workload increased
Only a small number of the participants said that their workload increased after the pandemic outbreak while 89.47% of them stated that there was no change in workload.
(3) The scale of the companies: 61.05% of the interviewees indicate change in company scale, while alternative works and partial delayed resumption are two main reasons
In Table 7, more than half of the interviewees witnessed change in number of employees in their companies, and this figure is 16.93% higher than that in the Sichuan research. Additionally, partial delayed resumption to work (56.90%) is the primary reason, and alternative work (50.00%) is the second one. But redundancy (42%) is the primary reason in the Sichuan research. It shows that companies in Sichuan and Chongqing may encounter more economic difficulties than those in Guangdong do.
Table 7: Factors that lead to change in company scale (could take more than one choice)
|
Option |
Number |
Ratio |
|
Layoffs |
18 |
31.03% |
|
Alternative work |
29 |
50.00% |
|
Delayed work resumption |
33 |
56.90% |
|
Others |
21 |
36.21% |
|
58 valid responses |
||
(4) Working relationship: 35.79% of the companies dismissed part of its employees, and economic redundancy is the primary reason
The proportion of the participants who witnessed redundancy in their workplaces in this research is much smaller than the data of the Sichuan research (-37.77%). Besides, both the Guangdong and Sichuan research also share a similar result. Economic redundancy is the primary reason for the dismissals (see Table 8).
Table 8: The reason for dismissals (could take more than one choice)
|
Option |
Number |
Ratio |
|
Economic redundancy |
14 |
43.75% |
|
End of labour contract |
9 |
28.13% |
|
Other |
29 |
90.63% |
|
32 valid responses |
||
4. Support from the government
Data show that the government provided enterprises with little support: 69.47% of the participants have no idea did the government provide their employers with support, and only 30.53% of them gave a positive response. Reduction or exemption of social insurance payment is still the primary supportive measure (86.96%), while tax relief (4.35%), and providing protective equipment (8.70%) were less adopted by the government. The readers are encouraged to refer to LAC’s previous reports on the labor conditions in other cities in China during the COVID-19 pandemic.
Part 4: Comparison among companies
Various findings could be identified by gender, industry, and company scale and these three variables may have a certain influence on the work resumption situation. But to ensure its reference and credibility, this study only analyzes how the variable, “company scale”, affects the work resumption situation and discusses the differences among the interviewees by gender and by industry at the end.
For comparison, this study divides the samples into three groups: (1) small-scaled companies with less than 50 employees (48 samples); (2) middle-scaled companies with 50 to 200 employees (28 samples); (3) large-scaled companies with more than 200 employees (19 samples) [2].
1. Labour rights condition
Table 9 shows that the larger company scale enterprises are, the more the enterprises provide social insurance to workers. 37.50% of the respondents who are in small-scaled companies did not enjoy social insurance protection, but nearly 100% of the respondents who work in middle-scaled and large-scaled companies enjoyed social insurance protection. In Mainland China, if the employees do not enjoy the social insurance protection, they will be very vulnerable when they are under crisis. For example, if the employers do not buy unemployment insurance, their employees cannot apply for the unemployment allowance, even though they suffer from unemployment during the pandemic.
Table 9: Do you enjoy social insurance protection?
|
Small-scaled |
Middle-scaled |
Large-scaled |
|
|
No |
37.50% |
7.14% |
0% |
|
Yes |
62.50% |
92.86% |
100% |
Similar result can also be found on labour rights condition during the period of delayed work resumption. As the company scale becomes larger, less workers received no payment or delayed payment and more workers received full payment. 75% of the respondents working in large-scaled companies received full payment and only 8.11% of them received full payment in the small-scaled companies (see Table 10).
Because there are less than ten valid responses under the questions “did you receive full payment during the quarantine” and “did your employers negotiate with you about the change of the wage level”, this study will not compare the data distribution of these two questions.
Table 10: Did you receive full payment during the period of delayed work resumption?
|
|
Small-scaled |
Middle-scaled |
Large-scaled |
|
No payment |
37.84% |
17.65% |
6.25% |
|
Delayed payment |
21.62% |
11.76% |
6.25% |
|
Partial payment |
32.43% |
47.06% |
12.50% |
|
Full payment |
8.11% |
23.53% |
75.00% |
Lastly, in terms of occupational health protection, more than 85% of the respondents who are work in middle-scaled and large-scaled companies can get access to free protective equipment in their workplaces. However, in the small-scaled companies, only half of the respondents receive free protective equipment (see Table 11).
Table 11: Did your companies provide free protective equipment?
|
Small-scaled |
Middle-scaled |
Large-scaled |
|
|
No |
45.84% |
14.29% |
10.53% |
|
Yes |
54.17% |
85.71% |
89.47% |
In conclusion, the data in this study show positive correlation between labour rights protection and company scale. Furthermore, the difference between the small-scaled companies and middle-scaled companies is much larger than the difference between the middle-scaled companies and large-scaled companies.
In its Research on The Work Resumption Situation in Jewelry Industry, LAC analyzes that in some small-scaled companies or workshops, employers are likely to keep short-term and informal employment relationship with their employees, and thus it is difficult for the labour laws to regulate this kind of companies and protect the labour rights.
2. Working condition
According to table 12, in middle-scaled companies and large-scaled companies, more than 60% of the research participants returned to work in February. However, less than 30% of the participants working for small-scaled companies could go back to work in February and more than half of them returned to work in March. Tables 10 and 12 indicate that employees in small-scaled companies are more likely to return to work later, and their labour rights are also more likely to be deprived during the delayed period.
Table 12: When did you return to work?
|
Small-scaled |
Middle-scaled |
Large-scaled |
|
|
February |
29.27% |
61.54% |
66.67% |
|
March |
53.66% |
26.92% |
33.33% |
|
April |
12.20% |
11.54% |
0.00% |
|
May |
2.44% |
0.00% |
0.00% |
|
Did not return to work |
2.44% |
0.00% |
0.00% |
Negative correlation is identified between the company scale and wages cut, but wages cut is likely to occur in middle-scaled and small-scaled enterprises. (see Table 13).
Table 13: Did your wage change after the pandemic?
|
Small-scaled |
Middle-scaled |
Large-scaled |
|
|
No |
29.17% |
39.29% |
73.68% |
|
Decline |
68.75% |
60.72% |
26.32% |
|
Increase |
2.08% |
0.00% |
0.00% |
Tables 14 and 15 indicate that both layoffs and change in company scale are more likely to occur in small-scaled companies. Only 5.26% of the large-scaled companies dismissed their workers after the pandemic, but 52.08% of the small-scaled companies did so. Meanwhile, change in company scale also occurred in 72.92% of the small-scaled companies. The factors include alternative work, partial delayed work resumption, layoffs, etc.
Table 14: Did layoffs happen in your workplace after the pandemic?
|
Small-scaled |
Middle-scaled |
Large-scaled |
|
|
No |
47.92% |
71.43% |
94.74% |
|
Yes |
52.08% |
28.57% |
5.26% |
Table 15: Did company scale change after the pandemic in your workplace?
|
Small-scaled |
Middle-scaled |
Large-scaled |
|
|
No |
27.08% |
32.14% |
78.95% |
|
Yes |
72.92% |
67.86% |
21.05% |
To sum up, employees are more likely to return to work later and face pay cut in small-scaled companies. Moreover, both layoffs and change in company scale are also more likely to occur in small companies. These problems may result from economic factors and loose law enforcement. On the one hand, large-scaled companies have more capital and orders and thus their risk-resistance capacity is stronger. On the other hand, because the employment relationship may be more formal in large-scaled companies, large companies are subject to tighter legal regulations, bear greater legal costs for illegal dismissal, wage default, and wage cuts, and therefore provide more protection to workers.
3. Other variables: gender and industry
Because this study did not take samples by an acceptable scientific rule, sampling bias could be identified. Table 16 shows that the gender distribution is unbalanced in middle-scaled and large-scaled companies: female to male ratio is nearly 2 to 1. It seems not to match the reality.
The study shows that women workers generally enjoyed more protection and better working condition than male workers did. It may be caused by sampling bias. Women workers became dominant in middle-scaled and large-scaled companies.
Table 16: Gender distribution among companies
|
Male |
Female |
|
|
Small-scaled |
50% |
50% |
|
Middle-scaled |
39.29% |
60.71% |
|
Large-scaled |
31.58% |
68.42% |
Sampling bias is also likely to occur in industry distribution. According to Table 17, in the small-scaled companies, almost half of the respondents come from the jewelry industry and those in the hardware industry comes the second. Both occupy 62.5%, almost two-thirds of the samples in the small-scaled companies. Moreover, the workers in three industries (jewelry, plastic and household electrical appliance) occupy more than 60% of the samples in the middle-scaled companies, but they share small part only in the large-scaled companies. The respondents working in other industries almost cover 70% in the large-scaled companies. In reality, there are large-scaled companies in the hardware, furniture, household appliance, and jewelry industries. Therefore, the analysis could be questionable if the comparison study goes on by industry.
Moreover, there should be more male respondents in the jewelry and hardware industry and more female respondents in the household electrical appliance, plastic, and “other” industry. Therefore, the sampling bias by both industry and company scale is likely to have biased correlations to gender issue.
Table 17: Industry distribution among companies
|
Small-scaled |
Middle-scaled |
Large-scaled |
|
|
Hardware |
14.58% |
14.29% |
10.53% |
|
Furniture |
6.25% |
7.14% |
0.00% |
|
Household Electrical appliance |
6.25% |
17.86% |
15.79% |
|
Plastic |
2.08% |
21.43% |
0.00% |
|
Construction |
4.17% |
0.00% |
0.00% |
|
Jewelry |
47.92% |
21.43% |
5.26% |
|
Other |
18.75% |
17.86% |
68.42% |
4. Discussion
Part 3 of this study has pointed out the correlation between company scale and work resumption situation. Employees in small-scaled companies enjoy less labour rights protection. Their economic condition is also worse than workers’ in middle-scaled and large-scaled companies.
Besides, it is observed that employment relationship in small-scaled companies is more likely to be informal and employers are less likely to sign labour contracts with their employees. It is more difficult for the employees to protect their labour rights. Furthermore, both the pandemics and long-lasting structural factors also gave rise to layoffs, outstanding wages, and other labour deprivation in small-scaled companies, including lack of legal protection on sub-standard employment and short-term contracting.
Appendix
In this study, significant correlations can be identified among three groupings, industry, gender, and company scale. But which one can provide us with more significant and meaningful analysis to the real situation of workers in Guangdong?
Firstly, this study tries to make the correlations between gender to industry and between gender to company scale respectively (see Tables a and b). It seems that the data collected are biased to a specific industry and to a specific company scale, respectively. Sampling bias could be identified. Gender may not be the best variable to integrate the whole study.
Secondly, the exact sample sizes in different industries are small. The size is still small even though we may divide the respondents into two groups: male-dominated industries and female-dominated industries [3]. Therefore, it could not be significant and reliable enough to study the correlations by industry based on small samplings.
Lastly, this study chooses the company scale as the main variable for data analyze (see Part 3). By this, coherent, convincing, integrative and significant correlations can be identified. It makes the study more creditable and meaningful in our understanding about the general labour conditions in Guangdong under the pandemic.
For transparency of the study, the data distribution among different groups of samples are listed in the following tables.
Table a: Industry distribution among the female and male respondents
|
Female |
Male |
|
|
Hardware |
7.41% |
21.95% |
|
Furniture |
3.70% |
7.32% |
|
Household electrical appliance |
14.81% |
7.32% |
|
Plastic |
12.96% |
0.00% |
|
Construction |
0.00% |
4.88% |
|
Jewelry |
20.37% |
46.34% |
|
Other |
40.74% |
12.20% |
Table b: Company scale distribution among the female and male respondents
|
Female |
Male |
|
|
Less than 10 people |
9.26% |
12.20% |
|
10 ~ 50 people |
35.19% |
46.34% |
|
50 ~ 200 people |
31.48% |
26.83% |
|
200 ~ 1000 people |
7.41% |
12.20% |
|
More than 1000 people |
16.67% |
2.44% |
Table c: Company scale distribution among industries
|
Hardware and jewelry |
Plastic and household electrical appliance |
|
|
Less than 10 people |
18.60% |
0.00% |
|
10~50 people |
51.16% |
22.22% |
|
50~200 people |
23.26% |
61.11% |
|
200~1000 people |
6.98% |
11.11% |
|
More than 1000 people |
0.00% |
5.56% |
Table d: Gender distribution among different industries
|
Hardware and jewelry |
Plastic and household electrical appliance |
|
|
Male |
65.12% |
16.67% |
|
Female |
32.88% |
83.33% |
Note
[1] In the Sichuan research, 60.32% of the respondents are grassroots workers and 24.60% of the respondents are in other job positions.
[2] In the commercial field, the division of small-scaled, middle-scaled and large-scaled enterprises usually refers to the enterprises with 200 or less workers, the ones with 201-1,000 workers and the ones with more than 1,000 workers, respectively. The division here does not follow this classification.
[3] Sample size of each industry: hardware (5), furniture (5), household electrical appliance (11), plastic (7), construction (2), jewelry (30), male-dominated industry (hard ware & jewelry: 43), female-dominated industry (plastic & household electrical appliance: 18).
* The author owns the copyright. It is prohibited to reprint this article without the author's permission.
議題聚焦:
