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THE IMPACT OF TECHNOLOGICAL CHANGES ON WOMEN'S EMPLOYMENT
Korea Report: Focus on the Manufacturing Sector
SECTION I. INTRODUCTION
1) Objectives and significance of research
2) Content, subject, and methodology of study
SECTION II. RESEARCH RESULTS
1) Analysis of results 1: Company surveys
2) Analysis of results 2: Individual surveys
3) Case studies: Focus on extent of automation
SECTION III. CONCLUSION
1) Summary of survey results
2) Demands for government policies regarding automation
Submitted: September 1994
Prepared for: United Nations University (UNU)
Institute for New Technologies (INTECH)
Prepared by: Korean Women Workers Associations United (KWWAU)
Kuro Ku, Kuro Bon Dong 409-54, Seoul, Korea
SECTION I. INTRODUCTION
I. Objectives and significance of research
The extent of automation in Korea's manufacturing sector is extremely low, particularly in labor-intensive industries (textiles, garments, some sectors of electronics) where women workers are concentrated. This is largely the result of the government's new industrial policies, implemented since 1986. These policies direct concentrated investment into industries judged to be competitive internationally (machinery, electrical equipment, electronics, automobiles, chemicals), funnel long-term technological investment into new, high-tech industries (semiconductors, computers, high-tech raw materials, aerospace, aviation), and suspend facilities investment in favor of offshore relocation for industries losing international competitiveness (shoes, toys, textiles, some sectors of electronics).
As a result of these policies, labor-intensive industries with large concentrations of women workers have been classified as "declining industries," and instead of raising international competitiveness through automation and technological investment, these industries have found ways to survive through shutdowns and mass worker lay-off's, business type transfers, offshore relocation, and subcontracting.
However, the severe impacts on workers that have resulted have not included the problem of outright unemployment. The reasons are that some single women have gotten married and not found new work, and others have been absorbed into the growing service sector. Married women workers have also entered small subcontract factories under harsh working conditions.
Women workers who were the main axis for economic growth in the 1960's and 1970's faced serious employment issues in the 1980's because of the turn towards heavy, chemical industries in government industrial policies. In the 1990's, industrial restructuring policies meant to strengthen Korea's international competitiveness are again creating employment instability for women workers. The government must pursue industrial policies to promote balanced growth among industries and to foster small and medium-sized industries; without these measures, labor-intensive industries, as well as small companies where women are concentrated, will continue to absorb the impacts of industrial restructuring through employment instability and worsening working conditions.
Against this background, our research proceeds with the following objectives: First, although the level of automation in female-dominated industries remains low, the existing technologies do have impacts on women workers. The research aims to outline these impacts of automation on women. Secondly, the research seeks to understand what concrete problems women workers face as a result of automation and how they themselves feel about these issues. Third, our report aims to propose policy solutions to resolve the issues of women workers arising from automation. This objective is especially important as drastic changes to the government's industrial and labor policies are deemed to be necessary.
This project holds significance because currently existing research on automation in Korea is in its beginning stages. Research on how automation impacts women workers in particular is not proceeding systematically in government agencies, government-run research institutes, or in university research centers. Given these circumstances, this research is significant in that it represents a more systematic and detailed account of automation and changes in women's employment. Because of the small sampling, out report focuses more on broadening social consciousness and knowledge regarding this issue than making quantitative or statistical generalizations. We hope and expect that this research will become the impetus for other research efforts in relation to this issue in the future. Our research is also significant in that our results will be presented to government representatives for purposes of improving government industrial and labor policies.
II. Content, subject, and methodology of study
A. Our research focuses on the following issues in regards to the impacts of
automation on women workers:
1) the extent of automation in female-dominated industries
2) automation and trends in women's employment
3) changes in work intensity
4) automation and its relationship to subcontracting
5) changes in work environment
6) health and safety issues
7) women workers and the response of labor unions
B. Subjects of research
As stated previously, the effort to strengthen competitiveness through automation is extremely weak in female-dominated industries. Because Korea is currently lacking in the accumulation of skills needed for automation, industries are unable to move towards complete factory automation. Large companies have moved to full automation of production lines, and smaller companies have only achieved partial automation through the introduction of unit machines with a low level of complexity. This shows that the level of automation in female-dominated industries remains low overall and that among these industries, differences occur by size and type of industry.
We divided our research into company surveys and individual surveys. The subjects of our company surveys include 29 companies from five female-dominated industries (pharmaceuticals, food processing, electronics, garments, and textiles) in which automation has proceeded to some extent. All industries selected include both large and small/medium-sized firms. For example, in the garment industry, two large companies (factory J and factory S) were surveyed through interviews, and two smaller factories were researched through written surveys. However, in the electronics industry, the monopoly capital-sized companies like Samsung, Goldstar, Daewoo, and Hyundai were not surveyed because of a lack of time. We plan to supplement information regarding these companies in the second round of research.
The subjects of our research are listed as follows:
<Table 1> Subjects of company surveys by industry type_____________________
P F G E T Totl
No. cases 3 4 2 6 14 29_________________
Note: P=Pharmaceuticals, F=Food processing, G=Garments, E=Electronics,
T=Textiles in all tables henceforth.
<Table 2> Subjects of company surveys by company size
P F G E T Totl
Aarge (500+) 1 2 0 2 10 15
S&M (under 500) 2 2 2 4 4 14
In addition, our surveys also targetted individual women workers. This is because we felt it important to conduct research on how women workers themselves feel and think about changes arising from automation. Our individual surveys include a total of 175 workers from 31 companies in the five industries selected. The distribution is as follows:
<Table 3> Subjects of individual surveys by industry type
P F G E T Totl
No. workers 96 9 3 11 56 175
C. Methodology
The research was conducted through a mixture of interviews and written surveys. The first round of research consisted of distributing written surveys to labor unions for the company surveys and to individual women workers for the individual surveys. The second round of research consisted of supplementary interviewing. Labor union representatives responded to the company surveys, and women workers working in automated sections of the production line answered the individual surveys.
The analysis of results consisted of analyses of the written surveys, as well as additional case studies. Case study analysis were selected from our written surveys and interviews; case studies in secondary materials were also consulted. Because the research was not intended for statistical purposes, the method of quantitative analysis was not selected.
SECTION II. RESEARCH RESULTS
I. Analysis of survey 1: Company surveys
A. Installation of automated equipment and disposal of aged machines
The installation of new automated equipment was not accompanied by the establishment of an entirely new factory in any of the companies surveyed. In most cases, new equipment was installed in order to replace aged machinery (15 companies), or a new production line was created within the same factory and equipped with new machinery (9 companies).
The majority of respondents (10 companies) stated that aged machinery were moved to other production lines within the factory. Others stated that aged equipment was moved to subcontract factories (6 companies) or moved to offshore sites (4 companies).
<Table 4> Methods of installing automation machinery
(more than one response allowed)
Installation Installation No response
after disposal in newly
of aged machines created areas
Pharmaceuticals 2 1 0
Food processing 2 1 1
Garments 2 0 0
Electronics 3 3 1
Textiles 6 4 4
Total 15 9 6
<Table 5> Methods of disposing of aged machinery
(more than one response allowed)
Movement Movement to Movement to Destruction of
wi/factory offshore sites subcontractors equipment
Pharmaceuticals 3 0 0 1
Food processing 2 0 3 1
Garments 0 0 0 1
(sold to retailer)
Electronics 2 3 1 1
Textiles 3 1 2 4
Total 10 4 6 8
The reason that many factories mentioned moving aged equipment to subcontract factories is that a high proportion of production currently taken up by subcontractors.
* In the food processing industry, three of four companies surveyed responded that aged machinery was moved to subcontract factories, indicating that the proportion of subcontract factories is high in this industry. In one company, nearly 40% of all production is taken up by subcontract companies.
* In the electronics industry, 3 of the 6 companies surveyed responded that aged equipment was moved to offshore sites, indicating a high rate of offshore relocation. When considering that over 70% of all production in the responding companies is intended for exports, it is evident that offshore relocation was a strategy that was attempted because of the crisis in low-cost, export-oriented production and the resulting drop in international competitiveness.
* It should be noted that though the rate of offshore relocation in the textile industry is shown to be low, this trend is limited to only those companies that actually responded to the survey. Follow-up questions confirms that aside from the one company cited in the survey, six other companies also cited movement of equipment abroad.
B. Automation and increased subcontracting
The increase in subcontracting is a severe employment problem for women workers. Particularly in the garment industry, subcontract production is increasing rapidly. As complete automation is difficult to achieve in this industry, the strategy of giving design and sales rights to the parent company and entrusting all production to subcontractors is being attempted. The main goal of subcontracting is primarily to reduce labor costs and to flexibly deal with changing consumer demands through small-scale, diversified production.
In addition to this kind of domestic subcontracting, subcontracting on an international scale is also on the increase. Two strategies are being attempted: 1) sending all raw materials to Korean offshore producers in low-wage countries and re-exporting manufactured, finished goods back to Korea, and 2) selling subcontract production rights to domestic companies in Third World countries.
Examined by product type, textile goods that have lost competitiveness in high-priced goods; labor-intensive products like plastic, leather, and fur goods; and electronics parts and consumer electronics goods in the electronics industry have all increased in subcontract production intended to reduce labor costs. International subcontracting in Thailand and Malaysia, where wage levels are relatively high in the Southeastern region, is comparatively low, while offshore production in low-wage countries like China, Vietnam, and Indonesia is showing rapid increases.
C. Impacts of automation
1. Increased productivity
Twenty-five companies cited increases in productivity after the introduction of automation, and four companies gave no response. The failure to respond is interpreted as being due to the lack of information available to labor unions. From the fact that all companies surveyed responded that productivity has recently increased, we can conclude that automation has played a significant role in increasing productivity.
<Table 6> Increases in productivity after the introduction of automation
Yes No No response
Pharmaceuticals 3 0 0
Food processing 4 0 0
Garments 2 0 0
Electronics 6 0 0
Textiles 10 0 4
Total 25 0 4
2. Changes in employment
In response to the question of whether automation has had impacts on employment, 20 companies cited worker reductions; 5 cited no changes, and 1 company cited an increase. The results show that across industries, the majority of companies has experienced reductions in the number of workers. The reasons cited for worker reductions included voluntary exits and the refusal of the company to hire new personnel. Labor union members are shown to understand workers reductions as voluntary actions rather than as the direct result of automation. Because of these voluntary reductions, more visible consequences like mass lay-off's were not observed. Companies that did not attempt to raise productivity at all through automation investment experienced more outright lay-off's. In particular, the shoe, garment, and the electronics industries showed these tendencies.
<Table 7> Changes in the number of workers consequent to automation
Inc Dec No change No response
Pharmaceuticals 0 2 1 0
Food processing 0 4 0 0
Garments 0 1 1 0
Electronics 0 5 1 0
Textiles 1 8 2 3
Total 1 20 5 3
In response to the question of how companies dealt with retracted workers after introducing automation, 1 company cited mass lay-off's; 5 cited voluntary exits, and 14 responded that companies refuse to hire new personnel after voluntary reductions. These statistics show that companies are finding effective means of reducing personnel by not hiring new workers after voluntary reductions. This strategy makes it all the more difficult for labor unions to criticize and respond to the automation issue.
<Table 8> Ways of dealing with retracted workers after automation
Mass Voluntary No new No response
lay exits hiring
off's
Pharmaceuticals 0 0 1 2
Food processing 0 1 2 1
Garments 0 0 1 1
Electronics 1 1 5 0
Textiles 0 3 5 1
Total 1 5 14 2
In response to the question of whether the number of non-regular workers increased after the introduction of automated machines, 5 companies indicated an increase, and 11 responded no increase. This indicates that though automation has been one factor in the rapid increase in non-regular workers after 1989, the increase is also being brought about by other factors.
In the case of pharmaceutical companies responding to the survey, an increase in non-regular workers is not shown, but in reality, this increase is a well-known and wide-spread reality. The increase in non-regular workers in pharmaceutical companies is being judged by union leaders as a means of labor union suppression and labor control.
One pharmaceutical company surveyed indicated that the management attempted to increase non-regular employment by hiring dispatch workers. Through the struggle of the union, it was agreed that discussions between labor and management be made obligatory before the decision to hire non-regular workers.
<Table 9> Increases in non-regular workers after automation
Yes No No response
Pharmaceuticals 0 3 0
Food processing 2 2 0
Garments 0 1 1
Electronics 1 5 0
Textiles 2 0 4
Total 5 11 5
3. Increased work intensity
The results of written surveys indicate 5 companies responding that work intensity increased greatly after automation; 15 companies indicated some intensification, and 4 indicated no change. This shows an overall intensification across all industries. Large increases in work intensity were seen particularly in the electronics industry. On the other hand, 2 companies indicated a weakening of work intensity subsequent to automation.
One example of this work intensification is in the H Electronics Company, which urged workers to adjust to newly introduced automation by using slogans such as, "Humans and machines are one." Originally, one person was made to handled one machine, but in 1992 after automation, this number changed to two; three in 1993 (Masan Changweon Democratic Workers Association 1993).
<Table 10> Changes in work intensity after automation
Great Increase No Weakened No response
increase change intensity
Pharmaceuticals 1 2 0 0 0
Food processing 0 3 0 1 0
Garment 0 1 1 0 0
Electronics 4 1 1 0 0
Textiles 0 8 2 1 3
Total 5 15 4 2 3
4. Changes in the characteristics of women's work
In response to the question of whether women have replaced men in male job positions, 4 companies indicated some replacement, while 21 companies indicated no such result. This indicates that despite the consequence of de-skilling arising from automation, work is still segregated into male and female roles. Moreover, even in cases where women do replace men, women continue to receive the same wages, plus a small machine operation bonus. These trends are a confirmation of the gender-discriminatory elements of Korean society.
<Table 11> Replacement of men by women in male job positions
Yes No No response
Pharmaceuticals 1 2 0
Food processing 0 4 0
Garments 1 1 0
Electronics 1 5 0
Textiles 1 9 4
Total 4 21 4
5. Changes in the work environment
In response to the question of what problems have arisen from automation, 16 companies indicated heightened work intensity; 10 companies, increased psychological stress; 9 companies, increased sense of isolation from lack of contact with co-workers; 8 companies, boredom from simple and repetitive work, and 4 companies, increase in industrial accidents. The increase in work intensity appeared as the largest problem, and isolation from co-workers appeared most among electronics companies. Increased psychological stress appeared as the second most mentioned symptom. This can be seen to be the result of increased physical work intensity, as well as psychological fatigue.
<Table 12> Problems in work environment after introduction
Boredom More More More Isolation No
work industrial stress response
intensity accidents
Pharmaceuticals 2 3 0 2 2 0
Food processing 1 3 2 2 0 0
Garment 2 0 0 0 0 0
Electronics 3 4 1 2 5 0
Textiles 0 6 1 4 2 4
Total 8 16 4 10 9 4
D. Automation and the response of labor unions
When asked about the reasons for the introduction of automated machines, respondents indicated increasing productivity (25 companies), lowering labor costs (23 companies), and alleviating labor shortages (16 companies). Other responses included improving product quality (9 companies), diversified and small-scale production (7 companies), reducing risks on the job (3 companies), and more effective labor management (3 companies)
These responses show that the motivations behind automation lie largely in increasing productivity, lowering labor costs, and alleviating labor shortages. As seen in Table 14, the effects of automation include increased productivity and lowered labor costs. These issues are also foremost in the understanding of labor unions regarding this issue. Particularly in the textile, food processing, and garment industries, the motivation of alleviating labor shortages are shown to be the most prevalent.
<Table 13> Reasons for the introduction of automation
(more than one response allowed)
Increase Small- Improve Lower Improve Labor Labor
produc- scale product labor work shortge mngment
tivity prod quality costs cond's
Pharm 3 1 1 3 0 1 1
Food 3 1 1 3 0 2 1
Garment 2 1 0 2 0 2 0
Electronics 6 0 2 5 0 2 2
Textiles 11 4 6 10 3 9 0
Total 25 7 9 23 3 16 3
<Table 14> Company evaluation of the effects of automation
Incr'd Lower Flex Better Effective Better No
produc- prod hiring work labor product resp
tivity cost cond control quality
Pharm 2 3 0 0 0 0 1
Food 3 3 0 1 1 2 0
Garment 2 1 1 1 0 2 0
Electronics 6 4 1 0 1 1 0
Textiles 8 9 2 6 0 8 1
Total 21 20 4 8 2 14 1
In response to the question of whether negotiations with labor unions were held, only 3 companies indicated such discussions, while 20 companies indicated no negotiations. Even when negotiations were held, they did not incorporate labor unions in the actual decision-making, but rather took the form of negotiating then reporting the results to the union.
When we consider the impacts that automation has had on working conditions, this indicates that despite institutional provisions, labor unions are excluded from the negotiation and decision-making processes. Government policies that prohibit labor unions from intervening in company management decisions also make it difficult for unions to be involved in automation-related decisions.
<Table 15> Negotiations with labor union when automation was introduced
Yes No No response
Pharmaceuticals 0 3 0
Food processing 0 4 0
Garments 0 0 2
Electronics 1 5 0
Textiles 2 8 4
Total 3 20 6
In response to the question of whether labor unions have plans for responding to issues related to automation, 3 companies indicated that they did; 15 companies indicated no such plans, and 9 companies gave no response. These trends can be said to be the result of the prohibition of union involvement in management decisions. It also indicates that the level of consciousness and response efforts for this issue in the labor union is still quite low.
<Table 16> Plans for labor union response to automation
Yes No No response
Pharmaceuticals 2 1 0
Food processing 0 3 1
Garments 0 0 2
Electronics 0 6 0
Textiles 1 5 8
Total 3 15 11
E. Automation and government policy
In response to the question of what government policies are deemed necessary in relation to automation, increased wages consequent to work intensification (14 companies) and expansion of job training necessary for new technologies (13 companies) were the most frequently cited. Eight companies cited the need for labor-management negotiations when automated machines are introduced, and 3 companies indicated the dissolution of male-female segregation in job positions.
<Table 17> Needed government policies in relation to automation
Job Inc'ed Dissolution Labor-management
training wages of M/F job negotiations
segregation
Pharmaceuticals 0 2 1 1
Food processing 2 2 1 2
Garments 1 2 0 0
Electronics 5 3 1 2
Textiles 5 5 0 3
Total 13 14 3 8
II. Analysis of survey 2: Individual surveys
A. Characteristics of work and extent of education and training after automation
When asked whether any special skills are necessary for the work currently being performed, 131 women workers responded that no special skills are needed, and 43 indicated the opposite. Hence, as most workers interviewed indicate no special skills needed for their work, the increased simplification of work consequent to automation can be seen.
On the other hand, even those workers indicating the need for some skills state that they have never had training for more than two months to learn these skills. Work in automated production lines are thus shown to consist of simple tasks that anyone could accomplish.
<Table 18> Need for special skills in work currently performed
Yes No No response
Pharmaceuticals 9 87 0
Food processing 4 5 0
Garments 1 1 1
Electronics 2 9 0
Textiles 27 29 0
Total 43 131 1
In response to the question of whether special training is being received in carrying out the currently performed tasks, 11 workers responded that they were, and 112 indicated no such training. This shows that women workers in automated lines are indeed carrying out simple, unskilled tasks. Moreover, even when training is received, it does not go beyond two months, indicating that the skills that are required do not go over this level.
We can consider the specific example of the garment industry in examining how de-skilling results from automation. In companies where line production is used, machine operators are characteried as A,B,C-level machinists in terms of skill and wage levels. The production is divided into smaller production steps, and A-level machine operators are placed in more difficult steps (such as collar attaching, specialized pocket making, and waistline making). It takes about three years for workers to become adept at these more difficult steps. However, after the introduction of automation, specialized pocket-making, which was a job reserved for A-class machinists, was made into a step that anyone could master with one day's training. The step has also become much more simpler. Before automation, each pocket had to be manually marked by the machinist, cut out by the assistant, then sewed together by the machinist. Now, newly introduced machines have certain settings for pocket-making, and all the machinist has to do is correctly position the pocket and push a button. The pocket-making process was previously spread over three production steps, but was reduced to one step through automation.
<Table 19> Training for currently performed work
Yes No No response
Pharmaceuticals 4 92 0
Food processing 1 8 0
Garments 1 2 0
Electronics 3 8 0
Textiles 2 2 2
Total 11 112 2
In response to the question of whether safety training was conducted for jobs in automated lines, 81 workers indicated such training, while 92 cited no training. This shows that despite their conducting automated processes, very little safety training is being conducted. Considered by industry, we can see that textile industry workers receive the most safety training.
<Table 20> Training for currently performed work
Yes No No response
Pharmaceuticals 21 75 0
Food processing 4 5 0
Garments 0 3 0
Electronics 3 8 0
Textiles 53 1 2
Total 81 92 2
B. Automation and the work environment
The results of the company surveys have already indicated the consequence of increased work intensity as a result of automation. In response to whether women workers can control their work speed on their own, 111 workers responded that they could, and 61 indicated that they could not.
The pharmaceuticals industry shows about equal positive and negative responses, and all industries aside from the textiles industry show that women workers cannot control their own work speed. The high percentage of workers responding in the affirmative in the textiles industry is explained by the fact that workers in this industry have relatively more freedom to control the unit machines that they are assigned to. While this freedom is comparatively high, textile workers receive more psychological stress because of greater breakdowns and operation failures in textile machines.
It is necessary to point out that greater freedom to control one's machinery does not always indicate a more pleasant work environment for workers. This is validated in the fact that work intensity has increased as a result of automation, as will be shown later. Even if workers are able to control work speed, this freedom is given only under the condition that a certain production levels are reached, resulting in increases in work intensity.
<Table 21> Possibility of controlling work speed
Yes No No response
Pharmaceuticals 52 43 1
Food processing 6 3 0
Garments 2 1 0
Electronics 5 6 0
Textiles 46 8 2
Total 111 61 3
Regarding the question of whether automation has led to increases in the frequency of industrial accidents, 43 workers responded increased frequency, and 115 workers responded no change. Hence, while some tasks have become easier because of automation, work intensity has increased, and the chance of accidents while performing extremely repetitive tasks has increased. An increase in industrial accidents is cited in the food processing industry in particular.
<Table 22> Increase in the frequency of industrial accidents
Yes No No response
Pharmaceuticals 22 65 9
Food processing 5 4 0
Garments 0 3 0
Electronics 5 5 1
Textiles 11 38 7
Total 43 115 17
Changes in the work environment resulting from automation have included increases in background noise (75 workers), discomfort from high temperatures (64 workers), and problems of ventilation (29 workers) in order of frequent responses. In the textile industry, more workers complained of high temperatures than of background noise and ventilation problems. Nevertheless, workers in all industries mentioned increases in background noise as a major consequence of automation.
<Table 23> Changes in work environment after automation
(more than one response allowed)
Incred Ventilation Discomfort No response
background problems from high
noise temperatures
Pharmaceuticals 47 10 40 0
Food processing 7 3 4 0
Garments 0 1 0 2
Electronics 10 4 2 0
Textiles 11 11 18 19
Total 75 29 64 21
C. Automation and health
Aside from 3 workers, all women workers placed in automated lines cite health-related problems, indicating the severity of health problems as a consequence of automation. The most frequently cited problems experienced by women workers, in order of frequent responses, include shoulder aches (83 workers), pains of the fingers and wrists (51 workers), inflammation of the ankles and knees (46 workers), intestinal impediments (35 workers), indigestion (28 workers), bronchial impediments (24 workers), weakened nerves (16 workers), and hip pains (14 workers).
The reason that shoulder, neck, and joint inflammations appear so often lies in the fact that workers are often made to repeat the same tasks for a long period of time. Also, the appearance of weakened nerves (16 workers) as one response show that even when workers are doing simple tasks, they are receiving more stress. Aside from these symptoms, deterioration of sight and headaches are also cited in the electronics, textile, and pharmaceuticals industries.
<Table 24> Health problems arising from work conducted
Neck, Hip Finger, Intestinal Weakened Ankle, Indig- Bronchial
shoulder pains wrist trouble nerves knee estion trouble
pains pains inflamm
P 45 1 33 9 3 10 16 7
F 8 3 6 3 2 4 3 1
G 2 1 0 1 0 2 1 0
E 7 3 3 1 1 4 1 3
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