Decent Work in the Chinese Apparel Industry: Comparative Analysis of Blue-Collar and White-Collar Garment Workers

Abstract

Addressing labor issues in the apparel industry is significantly important due to customers’ increasing awareness of poor working conditions and growing labor crises in apparel production locations worldwide. Decent work is a key element to achieving fair and harmonious employment, but is not always evident in global apparel production networks. This study examines the working conditions in China’s garment manufacturing industry, which employs more than 10 million workers. A survey was administered to 313 blue-collar workers and 228 white-collar workers on issues related to decent work, including workers’ concerns, satisfaction levels and attitudes towards decent work. Regression analysis showed that workers’ attitudes are significantly related to age, education level, service length and monthly wage. Gap analysis revealed poor understanding of decent work and low satisfaction with primary indicators of decent work. However, results suggest that workers increasingly value soft factors and the overall work experience, not only financial benefits. Cluster analysis identified four clusters of workers. This study contributes to understanding garment worker perceptions of decent work and provides implications for the operationalization of decent work in China’s garment manufacturing industry.

1. Introduction

Social aspects of sustainability, including working conditions and labor rights, are of increasing interest in academic research on global production networks, global value chains and supply chain management in the apparel industry [1,2,3,4]. Although the sector provides valuable employment opportunities to large numbers of low-income workers worldwide [5], it is also frequently associated with poor working conditions and labor crises, especially in labor-intensive garment manufacturing operations in lower labor cost countries [6,7,8,9,10]. To reduce its negative social impact in terms of worker exploitation, the apparel industry is increasingly engaging in corporate social responsibility (CSR) initiatives on a global scale, some of which are related to decent work [2,11,12,13].

Decent work was first introduced by Juan Somavia, the Director-General of the International Labor Organization (ILO) [14]. China, as the largest textile and apparel manufacturer and trader in the world, employs more than 10 million workers [15]. However, there is little evidence documenting working conditions of garment workers and little research has been done on decent work from the perspective of garment workers, even though references to and case studies of countries are common in recent literature [16,17,18,19,20]. Existence of CSR standards does not necessarily mean that companies rigidly follow them [21] but previous research has fallen short of providing figures on the satisfaction and concerns for decent work from the perspective of workers [16,17,22]. Therefore, an examination of decent work from the perspective of production line and office workers in garment manufacturing businesses could provide a more accurate reflection of working conditions in China. This study aims to provide a more detailed insight into perceptions and attitudes of today’s garment workers in China, which could assist HR managers to identify what workers care about and provide insight on how to improve job satisfaction in order to better recruit and retain employees, thus improving enterprises’ social and economic performance.

The paper is organized as follows. Firstly, the theoretical concept of decent work is reviewed, alongside the international standards, government standards and laws related to labor rights in the apparel industry. Next, the working conditions and attitudes towards decent work of Chinese garment workers are examined by analyzing survey data from a sample of 541 garment workers, in order to answer the following research questions (RQ):

RQ1:

How do workers perceive current working conditions in China’s garment manufacturing industry?

RQ2:

Which factors influence garment workers’ attitudes towards decent work?

RQ3:

What are garment workers’ attitudes towards decent work when seeking a new job?

RQ4:

Do blue-collars workers’ and white-collar garment workers’ attitudes towards decent work vary?

2. Literature Review

Apparel production networks are geographically complex and relatively long, including numerous activities from design, materials sourcing, manufacturing, distribution and retailing, with numerous business partners involved [23,24,25]. As manufacturers attempt to meet buyers’ cost and speed targets, the maintenance of labor standards in this highly labor-intensive industry sector becomes jeopardized. Since labor costs represent a significant part of overall costs, as sourcing costs rise, retail buyers explore new suppliers in lower-cost regions which may have lower labor standards [2,26]. Consequently, poor working conditions are commonly found in garment manufacturing [2,21,22]. Implications of poor working conditions include negative media attention and consumer boycotts in consumption locations, which are harmful to fashion brands’ reputations, as well as factory strikes in production locations, which hinder the smooth flow of product through the global production network. The changing nature of Chinese labor unrest suggests that today’s Chinese garment workers are becoming more assertive in their demands for more pay, greater respect from employers and better attention to workplace details [27].

For this study, a set of selected keywords such as “apparel industry” and “clothing industry” in combination with “working conditions”, “decent work”, and “labor/labour issues” were used to identify relevant literature in Scopus and Web of Science databases. Papers with a focus on both apparel industry and labor issues were then selected for review. In addition, references cited in these papers but not included in Scopus and Web of Science, such as ILO reports and Chinese textile and apparel industry rules and standards, were also selected to review. Thus, the literature review includes sources from two areas: the academic conceptual development of decent work and the application of decent work in the Chinese textile and apparel industry.

2.1. Decent Work

The concept of decent work was first introduced in 1999 by the ILO and was described as “opportunities for women and men to obtain decent and productive work in condition of freedom, equity, security and human dignity” [28]. It encompasses workers’ career expectations including effective work with sufficient income, security assurance with social protection for the family, prospects for personal development with social contribution, freely expression of their views and participation in decision-making, equal opportunity and gender equality. Since then, the general concept of decent work has been translated into understandable characteristics of work and identified statistical indicators by scholars, so that those characteristics can be measured with an acceptable degree of consistency, accuracy and cross-country comparability [29].

The concept of decent work is relevant for all countries. However, depending on the stage of development, decent work standards may vary between countries at any given time. The measurement criteria may thus be slightly altered according to the research aim and research methods. For example, Anker et al. [29] proposed six dimensions with 30 indicators to measure decent work, whilst Bescond et al. [30] compared decent work in 25 countries with seven decent work indicators. The criteria applied to measure the standard of decent work in the textile and apparel industry are extensive and vary according to research perspective, as summarized in

Table 1. Labor standards criteria for decent work in the textile and apparel industry.

Reference	Criteria	Research Context
[17]	Sufficient work, adequate incomes, working conditions, duration and intensity, child labor, health and safety, strain and injury	Home-based enterprises in developing countries
[31]	Forced labor, child labor, compensation/minimum wage, benefits (legally mandated benefits), hours of work/overtime, environment, safety and health (ES&H)	Nike suppliers
[32]	Discrimination in employment, labor/management relations, occupational health and safety, training and education, diversity and equal opportunity	Textile suppliers
[20]	Occupational safety and health, employment contracts, social security, training, wages, overtime, work intensity, union representation	Apparel industry
[33]	Employment, social security, rights of workers and social dialogue	Apparel companies

.

Blue-collar workers in the garment industry are those who perform manual work on the factory floor, such as cutting, sewing, packing or quality control. White-collar workers perform professional jobs in office settings, such as designing, merchandising, marketing or HR administration. Most literature on garment workers’ working conditions focuses on blue-collar workers, also known as assembly line workers or first-line workers, but does not specifically consider their perceptions of decent work. Recent media reports have highlighted serious labor issues for these workers [6,7,8,9,10] whilst empirical research has focused on developing countries such as Bangladesh, India, Cambodia and Sri Lanka [3,34,35]. However, there is a lack of literature on perceptions of decent work from the perspective of white-collar workers.

2.2. Decent Work in China’s Textile and Apparel Industry

China, as the largest developing country in the world, has the largest population of workers. The importance of labor-intensive manufacturing to its economic development should not be under-estimated, as it created sustained employment and incomes for China’s large poor population. However, by the end of 2015, only 26 ILO conventions involving elements of decent work, such as minimum age for employment, minimum wage, working time and equal remuneration, were ratified by China [36].

In the textile and apparel industry, the Chinese government has initiated labor regulation reform in response to pressures from NGOs, trade unions and international buyers concerned about sweatshops in global production networks. Hence, decent work in the textile and apparel industry is expanding since China entered global apparel production networks [37]. A number of labor laws and regulations contain elements of and requirements for decent work, including the New Labor Contract Law, China Social Compliance for Textile Industry (CSC9000T), Trade Union Law, Production Safety Law and Regulations on Enterprise Minimum Wage. The New Labor Contract Law and CSC9000T are most closely aligned with the principles of decent work, as shown in

Table 2. Indicators of decent work and aspects of CSC9000T and New Labor Contract Law in China.

Decent Work [29]	CSC9000T [38]	New Labor Contract Law [39]
Employment opportunities	Discrimination	Fair treatment
Adequate earnings and productive work	Wages and welfare	Minimum wage requirement
Decent hours	Working hours	Working hours
Stability and security of work	Child labor and juvenile workers	Stable work
Balancing work and family life	Employment contract	Rest days and annual leave
Fair treatment in employment	Forced or compulsory labor	Necessary training
Safe work environment	Occupational health and safety	Labor protection
Social protection	Harassment and abuse	Social insurance
Social dialogue and workplace relations	Trade unions and collective bargaining	Trade unions and collective bargaining
Economic and social context of decent work	Promotion/enhancement of education	Economic and social context of decent work

.

The New Labor Contract Law came into effect in January 2008 and aimed to strengthen job security, ensure payment of proper wages and benefits, and curtail the widespread use of seasonal and temporary contracts in lieu of more stable contractual relations [39,40]. The Chinese social compliance standard CSC9000T is an achievement of the project “Corporate Social Responsibility (CSR) in the Chinese Textile Industry”, which is one of the ILO’s major technical cooperation projects with China [41]. The project aims to support the creation of a viable industry-wide framework for high quality business management (including labor management cooperation, productivity and quality upgrading, environment, human resources management, working conditions and occupational safety and health) for a sustainable development of the Chinese textile industry [42]. CSC9000T is a social compliance management system for China’s textiles and apparel sector, based on Chinese laws and regulations as well as relevant international conventions. The aims of CSC9000T include ensuring that workers’ rights are protected, assisting businesses in improving their CSR management, facilitating sustainable development of enterprises and promoting the international reputation of Chinese textile enterprises [38]. The standard was developed to address challenges arising from global expectations of CSR.

Previous research on the implementation and the influences of international standards such as ISO26000, SA8000 and CSC9000T concluded that implementation of international standards and labor laws would help improve the working conditions of the garment workers [40,43,44]. However, given the lack of a strong system of global justice [45] and the limited ability (or willingness, perhaps) of many country governments to enforce labor laws [46,47], it is questionable whether workers’ interests can be adequately promoted from the perspective of decent work [26]. Although implementation of CSR in Chinese enterprises is promoted by a number of stakeholders including the Chinese government, China’s stock exchanges, government agencies and NGOs [48,49], there is some resistance to the execution and enforcement of CSR-related laws and regulations [50], as evidenced by ongoing reports of garment worker exploitation [8]. Furthermore, as retailers and suppliers may have an interest in hiding labor violations, internal audits are not necessarily trustworthy [21,43]. Understanding workers’ perspectives may also shed light on challenges to implementing better working conditions. For example, Tran and Jeppesen [51] found that limited efficacy of CSR implementation in Vietnamese textile and apparel SMEs was due in part to a lack of understanding of the western concept of CSR by managers and workers. Therefore, examining perceptions of working conditions and decent work from the perspective of garment workers themselves could provide a valuable contribution to current understanding of decent work. It could also help to identify areas where manufacturers could improve and promote well-being in the workplace, which could lead to positive outcomes such as improved worker motivation and job performance, and influence perceptions of the sector as a whole.

Theoretical understanding of decent work has advanced since it was first introduced by the ILO [14], especially in terms of understanding structural and institutional challenges to its implementation in global production networks and in developing countries [26]. However, there is a lack of empirical research on how far garment workers themselves consider their job to be decent work. Workers are a key stakeholder group in the decent work agenda, but their voices are rarely heard in academic literature. For example, Ruwanpura [52] noted “the limited attentiveness to worker actions and labour voice” in previous studies of labor geographies and ethical trading. The working conditions of blue-collar garment workers have attracted much attention from the media [6,7,8,9,10] as well as academic researchers [5,43,52], but most studies focus their analysis at firm level, not worker level, or do not explicitly connect working conditions to the concept of decent work. Furthermore, although there are large numbers of white-collar office workers in the garment industry, these workers are disregarded in studies of the garment industry. To address these research gaps, this study provides an insight into workers’ perspectives of decent work, by comparing attitudes towards and perceptions of decent work in blue and white-collar workers in China’s garment industry. Understanding garment workers’ satisfaction with and concerns about decent work could assist in guiding managerial actions to address workers’ concerns, and thus help to improve enterprises’ social and economic performance.

3. Methodology

A quantitative approach was taken to address the research questions. Based on the definition of decent work in previous literature [17,29,32,53,54], a questionnaire was developed with ten measurement items of decent work: adequate income, work duration and intensity, work–life balance, fair and equitable treatment at work, work relations, existence and effectiveness of trade unions, social insurance, skills training, job security and company development. These ten items were selected according to the definition of decent work [28,29]. The descriptions of some items were slightly altered according to the Chinese rules and standards such as CSC9000T. Since decent work indicators should be easy to communicate to lay persons [29], simple descriptors were used for the selected measurement items. For many workers, the most important characteristic of work is pay. Besides providing adequate income, decent work must also address dynamic aspects of continued provision of adequate income. Work duration and intensity is included because excessive hours and atypical hours are often detrimental to physical and mental health, and they impede balance between work and family life [53]. The global garment industry is dominated by female workers [55]. As women have the main responsibility for family care and household work, work–life balance is important for measuring the decency of the work [17]. Fair and equitable treatment at work is included as it is an intrinsic human expectation [16,30]. Relations in the workplace help support equity and dignity at work, and it is much easier for workers to measure [32]. Another important dimension of decent work is the extent to which workers can express themselves on work-related matters and participate in determining their working conditions [29], therefore trade unions are included as a measurement item. Adequate social insurance is a defining feature of decent work around the world. Since 2011, providing social insurance for employees is mandatory in China. The Social Insurance Law requires all employers to enroll each employee in five insurance programs: pension, medical, work-related injury, unemployment and maternity insurance. Skills training which enables employees to maintain or improve their skills and income prospects in the future is regarded as an important measure of decent work in the garment industry [20]. Job security is defined as the probability that the current employment relationships will be terminated at the employer’s initiative within a certain period (one year, for example). Losing one’s job is a serious event and job security is seen by most people as an important aspect of decent work [43]. Sustainability and competitiveness of the company (company development) is included in the questionnaire since these factors would strengthen the likelihood of job security [55].

The questionnaire addressed garment workers’ current satisfaction with and concern for the 10 decent work criteria when seeking a new job, using a five-point Likert scale [56]. The questionnaire consisted of three parts: firstly, demographic information, since these factors may influence workers’ perceptions. Secondly, workers’ satisfaction with their current job was examined using a five-point Likert scale where 1 = very dissatisfied and 5 = very satisfied. Finally, workers were asked to rate their perceived importance of decent work criteria when looking for a new job, using a five-point Likert scale where 1 = very unimportant and 5 = very important.

3.1. Data Collection

Accessing the network of production is critical to understand the real conditions and attitudes of garment workers towards decent work implementation in the garment industry. The survey was administered to workers in four purposefully sampled garment manufacturing companies in the eastern coastal region of China during 2013. China exported $284 billion in textiles in 2013, accounting for more than 40% of global clothing exports [57]. Textile and apparel clusters first concentrated in coastal regions, which are now mature with convenient transportation, market vicinity and excellent information communication and transportation infrastructure in the area [58]. As shown in

Table 3. Breakdown of sample companies.

Co.	No. of Employees	Date Set Up	Typical Customers	No. of Factories	Location
A	3500	1990	Uniqlo, HAGGER, J.C. Penney, Lanvin, Paul Smith, Marui	6	Jiangsu
B	2000	1984	River Island, BCBG, MaxMara, Tommy Bahama, Miss Sixty, Calvin Klein, Diesel, Gerry Weber, Marks & Spencer	3	Zhejiang
C	800	1996	Cerruti 1881, United Arrow, Icicle	2	Shanghai
D	500	2008	Next, Gap, Banana Republic, Lee, Etam, Esprit, American Eagle, Calvin Klein, Uniqlo	1	Shandong

, the four sample companies are well established, represent a variety of business sizes in the industry and form part of several EU, U.S. and Japanese apparel retailers’ supply chain networks. The sample companies were all full-package suppliers, providing all material inputs and production services to convert retailers’ or brands’ designs into finished products that meet buyers’ required volumes on time and fulfill their quality standards. Some companies even offered product design for their buyers. Respondents included blue-collar workers in the production line and white-collar workers in the office.

Ethical considerations were taken into account with reference to the institution’s ethical standards for research involving human participants. The research protocol was reviewed and approved by the institutional review board. The questionnaire was accompanied by a cover letter stating the purpose of the study and an assurance of confidentiality and anonymity to respondents, who were also verbally assured beforehand that the information gathered would be treated with the strictest confidentiality and their anonymity would be preserved. It was important for respondents to feel confident that they could give their responses honestly and without fear of identification or prejudice, therefore the survey was conducted without the presence of management.

To access blue-collar workers, two factory workshops were randomly selected in each company to access manual workers in cutting, sampling, sewing, ironing, packing, quality control and warehouse functions. To access white-collar workers, all office workers in each company were invited to participate in the survey, and these included designers, traders, marketers, merchandisers, finance executives and HR executives. Researchers administered the questionnaires separately within factory floor and office environments, to ensure all workers were correctly classified into blue collar or white collar groups. Workers were also asked to state their job title in the questionnaire, to ensure accuracy of classification. Given the relatively low education level of garment workers, researchers first introduced the definition of decent work to respondents and then administered the survey face-to-face, so that workers could ask for help if they did not understand the questions.

3.2. Sample Overview

A total of 541 valid questionnaires were returned from the original 600 distributed (valid response rate 90.2%), as shown in

Table 4. Questionnaire distribution and valid response rates.

Co.	Blue-Collar Workers			White-Collar Workers
	No. Distributed	No. Received	Valid Response %	No. Distributed	No. Received	Valid Response %
A	96	88	91.7%	78	72	92.3%
B	88	76	86.4%	67	61	91.0%
C	84	76	90.5%	55	50	90.9%
D	83	73	88.0%	49	45	91.8%
Total	351	313	89.2%	249	228	91.6%

. Of these, 313 blue-collar workers (57.9%) worked as cutting workers, sewing workers, ironing workers, sample machinists, quality inspectors, etc. while 228 white-collar workers (42.1%) worked as merchandisers, designers, technicians, human resource executives, etc., as shown in

Table 5. Demographic breakdown of respondents.

	Items	Blue-Collar Workers		White-Collar Workers
		Frequency	Percentage	Frequency	Percentage
Gender	Male	63	20.1	56	24.6
	Female	250	79.9	172	75.4
Age	Under 20	3	1.0	0	0
	20–23	50	16.0	42	18.4
	24–33	133	42.5	159	69.7
	34–43	99	31.6	24	10.5
	44–53	26	8.3	3	1.3
	54 or over	2	0.6	0	0
Education level	Below high school	220	70.3	9	3.9
	High school or secondary school	83	26.5	27	11.8
	College	10	3.2	54	23.7
	Bachelor’s degree	0	0.0	108	47.4
	Master’s degree	0	0.0	30	13.2
Length of service in garment industry	Less than 1 year	3	1.0	66	28.9
	1–3 years	63	20.1	72	31.6
	4–5 years	55	17.6	42	18.4
	6–10 years	93	29.7	18	7.9
	More than 10 years	99	31.6	30	13.2
Monthly wage (RMB)	Less than 1000	0	0.0	0	0.0
	1000–1999	106	33.9	15	6.6
	2000–2999	133	42.5	43	18.9
	3000–3999	68	21.7	54	23.7
	4000–4999	5	1.6	51	22.4
	More than 4999	1	0.3	65	28.5

. Almost 80% of the sample was female and the age profile of white-collar workers was younger than the blue-collar workers. The education level of most blue-collar workers (70.3%) was below high school, whilst most white-collar workers (84.2%) were college graduates or above. Blue-collar workers had longer length of service in the garment industry than white-collar workers. Most blue-collar workers (78.9%) had worked for more than four years, while most white-collar workers (60.5%) had worked for less than four years, which corresponds with the age distribution. White-collar workers had higher monthly wages than blue-collar workers. The monthly wage of most blue-collar workers (76.4%) was less than 3000 RMB, whilst most white-collar workers (74.6%) earned more than 3000 RMB per month.

3.3. Data Analysis

Gap analysis was used for examining the evaluation and expectations of the working conditions of garment workers. This technique has been widely adopted in previous research to provide insight on gaps that arise from inconsistent perceptions of expectations and experience [59,60,61]. To examine if the characteristics of the garment workers are related to their perceptions of decent work, multiple regression analysis was performed to examine the relationships. This is an appropriate technique to analyze relationships among selected variables [62,63,64]. Finally, factor analysis and cluster analysis were performed to explore garment workers’ attitudes when seeking a new job and the variation in attitudes between blue-collar and white-collar workers.

4. Results and Discussion

The findings are grouped into three subsections. Firstly, the means of satisfaction with and importance of the decent work criteria are examined by gap analysis and compared across blue and white collar workers. Secondly, the factors influencing workers’ attitudes to decent work are explored. Thirdly, workers’ attitudes towards decent work are examined by factor analysis and cluster analysis, with a comparison of white-collar workers and blue-collar workers.

4.1. Gap Analysis

The reliability of the measurement was supported as the scales exhibited acceptable reliability with Cronbach’s alpha 0.863 for the satisfaction scale and 0.862 for the importance scale [65].

Table 6. Means and standard deviation of satisfaction and importance.

Decent Work Criteria	Means of Satisfaction	Standard Deviation	Means of Importance	Standard Deviation
Adequate income	2.97	0.87	4.18	0.71
Company development	3.72	0.88	4.07	0.82
Work relations	4.04	0.69	4.07	0.83
Work duration and intensity	3.26	0.82	4.06	0.80
Work–life balance	3.34	0.96	3.96	0.78
Fair and equitable treatment at work	3.66	0.89	3.94	0.82
Job security	3.73	0.91	3.85	0.80
Social insurance	3.84	0.82	3.82	0.95
Skills training	3.07	0.91	3.60	0.95
Trade unions	3.09	1.02	3.55	1.00

Notes: A five-point scale is used: 1 = very unimportant; 5 = very important; 1 = very dissatisfied; 5 = very satisfied.

provides an overview of respondents’ rankings of satisfaction with and importance of the ten decent work criteria, listed in descending order according to importance. These data address RQ1 (workers’ perceptions of current working conditions) and RQ3 (workers’ attitudes to decent work when seeking a new job). The satisfaction means of the items are all above neutral, except income, suggesting that workers’ perceive their current working conditions (with the exception of wages) to be fairly good. However, as the means of importance are significantly higher than the means of satisfaction, especially in aspects of salary and working conditions, workers appeared to place greater importance on the decent work criteria when seeking a new job.

The gap between satisfaction and importance is largest for income, which is most valued in terms of importance but ranked lowest in terms of satisfaction both in white-collar and blue-collar workers, which suggests that garment workers’ pay demands remain unsatisfied. Since garment manufacturing is often a starter industry in a developing country, wages are relatively lower than other industries. However, it is hopeful to find that a certain percentage of workers value the soft conditions in their work, not only hygiene factors such as pay.

Work relations were scored as the second most important, with the highest satisfaction rating among all ten criteria. This highlights the importance of guanxi (good relationship) with co-workers in the factory. A closer look at the data indicates that the gap between satisfaction and importance of work relations is the lowest. Compared with strained labor relations in other lower labor-cost countries [22,66], employment relations in the Chinese garment industry seem relatively good. Furthermore, satisfaction scores for fair and equitable treatment at work, job security, company development and social insurance are over 3.5, with a small gap between satisfaction and importance, which suggests that workers are relatively satisfied with their current working conditions in terms of these criteria.

Work intensity and work–life balance are of great importance for workers, but satisfaction scores for these two items are relatively low. Trade unions and skills training are least important for the workers, and the satisfaction scores of these two criteria are second and third from the bottom as well, which may be explained by the trade unions’ insufficient effect on the workers and poor access to skills training. Since skilled workers are the foundation of quality and productivity, and skilled labor shortages are growing [67], garment factories should invest in skills training, rather than attempting to recruit skilled workers.

To address RQ4 (variance between blue and white-collar workers), the ranked results are split between blue and white-collar workers, as shown in

Table 7. Comparison of blue-collar and white-collar workers’ means of satisfaction and importance.

Decent Work Criteria	Blue-Collar Workers		White-Collar Workers
	Satisfaction Means	Importance Means	Satisfaction Means	Importance Means
Adequate income	2.96	4.19	2.99	4.16
Work relations	4.06	4.10	4.00	4.03
Work duration and intensity	3.19	4.09	3.36	4.03
Company development	3.81	3.97	3.61	4.20
Social insurance	3.93	3.95	3.72	3.65
Work–life balance	3.30	3.91	3.39	4.02
Job security	3.77	3.79	3.68	3.94
Fair and equitable treatment at work	3.59	3.78	3.76	4.17
Skills training	3.16	3.68	2.95	3.49
Trade unions	3.33	3.58	2.75	3.51
Average	3.40	4.13	3.45	4.07

Notes: A five-point scale is used: 1 = very unimportant; 5 = very important; 1 = very dissatisfied; 5 = very satisfied.

and Figure 1. Blue-collar workers are less satisfied with work duration, work–life balance and fair and equitable treatment at work, which may reflect the constant shadow of overtime work for production-line garment factory workers. Blue-collar workers are more satisfied with soft criteria in their current job, such as company development, social insurance, skills training and trade unions. Previous studies emphasized the importance of trade unions in garment factories in order to avoid sweatshop conditions [58,66]. However, it seems that these are more accessible for production-line workers (satisfaction mean = 3.33) than for white-collar workers (satisfaction mean = 2.75). Overall, white-collar workers attach more importance to soft conditions, such as company development, fair and equitable treatment at work and job security, when seeking a new job.

4.2. Relationship between Worker Status, Age, Education Level, Length of Service, Monthly Wage and Attitudes toward Decent Work

The regression analysis in

Table 8. Statistical relationship between work status, age, education level, length of service, monthly wage and decent work attitude.

Dependent Variables	Independent Variables					Model F	p-Value	Adjusted R2
	Work Status	Age	Education Level	Length of Service	Monthly Wage
Adequate income	−0.035 (0.425)	−0.187 (0.000 **)	−0.108 (0.016 *)	−0.044 (0.323)	0.046 (0.297)	9.827	0.000 **	0.034
Work duration and intensity	−0.102 (0.024 *)	−0.037 (0.409)	−0.354 (0.000 **)	−0.119 (0.028 *)	0.209 (0.000 **)	8.011	0.000 **	0.052
Work–life balance	−0.064 (0.151)	−0.085 (0.056)	−0.037 (0.410)	−0.012 (0.780)	0.185 (0.000 **)	17.914	0.000 *	0.032
Social insurance	−0.000 (0.999)	−0.071 (0.110)	−0.143 (0.001 **)	−0.078 (0.078)	−0.037 (0.399)	10.550	0.001 **	0.018
Skills training	−0.065 (0.144)	−0.109 (0.015 *)	−0.192 (0.000 **)	0.033 (0.462)	0.083 (0.062)	10.328	0.000 **	0.035
Trade unions	0.013 (0.774)	−0.119 (0.007 **)	−0.029 (0.511)	−0.027 (0.544)	−0.014 (0.754)	7.240	0.007	0.012
Job security	−0.052 (0.245)	−0.024 (0.583	0.059 (0.187)	−0.076 (0.087)	0.153 (0.001 **)	12.166	0.001 **	0.021
Fair and equitable treatment at work	−0.040 (0.371)	−0.019 (0.674)	0.017 (0.697)	−0.204 (0.000 **)	0.223 (0.000 **)	27.782	0.000 **	0.095
Work relations	/	/	/	/	/	/	/	/
Company development	−0.025 (0.575)	−0.019 (0.666)	0.009 (0.084)	−0.108 (0.014 *)	0.147 (0.001 **)	9.401	0.000 **	0.032

Notes: * < 0.05; ** < 0.01. Variables Entered Method: Stepwise (Criteria: Probability-of-F-to-enter ≤ 0.050, Probability-of-F-to-remove ≥ 0.100). Predictors: (Constant), Work Status, Age, Education level, Length of service, Monthly wage.

addresses RQ2 (factors influencing garment workers’ attitudes towards decent work) and shows several significant relationships between decent work variables and worker characteristics.

Significant relationships were found between working conditions and work status, suggesting that blue-collar workers are more likely to value work duration and intensity (β = −0.102, p = 0.024 < 0.05) than white-collar workers. The attitudes toward aspects of decent work between blue-collar workers and white-collar workers will be further analyzed in Section 4.3. Satisfaction levels with several decent work criteria such as adequate income (β = −0.1847, p = 0.000 < 0.01), skills training (β = −0.109, p = 0.015 < 0.05) and trade unions (β = −0.119, p = 0.007 < 0.01) are related to age, which suggests that younger workers pay more importance to these aspects of decent work. This is consistent with the recruitment situation in China’s textile and apparel industry, where firms find it hard to recruit young workers [19,37]. The results also suggest that workers with lower education levels are more likely to pay attention to income (β = −0.108, p = 0.016 < 0.05), work duration and intensity (β = −0.354, p = 0.000 < 0.01), social insurance (β = −0.143, p = 0.001 < 0.01) and skills training (β = −0.192, p = 0.000 < 0.01). Significant relationships were found between length of service and decent work criteria, suggesting that workers with shorter service are more likely to value work duration and intensity (β = −0.119, p = 0.028 < 0.05), fair and equitable treatment at work (β = −0.204, p = 0.000 < 0.01) and company development (β = −0.108, p = 0.014 < 0.05). The results show that workers earning higher monthly wages are more likely to value work duration and intensity (β = 0.209, p = 0.000 < 0.01), work–life balance (β = 0.185, p = 0.000 < 0.01), job security (β = 0.153, p = 0.001 < 0.01), fair and equitable treatment at work (β = 0.223, p = 0.000 < 0.01) and company development (β = 0.147, p = 0.001 < 0.01). This suggests that higher paid employees would pay more importance to soft factors of the work.

No significant relationships were found between work relations and work status, age, education level, length of service or monthly wage. This suggests that work relations are valued equally amongst workers, notwithstanding differences in work status, age, education level, length of service or monthly wage.

4.3. Attitudes toward Decent Work of Different Clusters

To understand the underlying structure of associations for the ten decent work measurement items, factor analysis was performed to simplify a matrix of correlations such that they could be explained in terms of a few underlying factors [67]. From the factor analysis, identifiable factors could be obtained. Bartlett’s Test and Kaiser–Meyer–Olkin’s (KMO) measure of sampling adequacy were performed, confirming that factor analysis was appropriate to use in this study. Based on the results (KMO = 0.852, sig. = 0.000), the items were confirmed to be appropriate for factor analysis [65].

Principle component analysis with varimax rotation using the minimum eigenvalue of one as the criterion to control the number of factors extracted, was chosen as the method for estimating the factors. An initial factor analysis was performed and yielded ten factors. A scree-test plot confirmed that three factors should be extracted. The resulting factors were used as scales, to measure the different components of respondents’ attitudes about decent work. The resulting factor structures are shown in

Table 9. Results of rotated component matrix.

Variable	Communalities	Factor 1	Factor 2	Factor 3
Fair and equitable treatment at work	0.802	0.827
Work relations	0.669	0.781
Company development	0.678	0.764
Job security	0.632	0.714
Trade unions	0.761		0.855
Skills training	0.760		0.810
Social insurance	0.710		0.810
Work duration and intensity	0.699			0.789
Work–life balance	0.671			0.755
Adequate income	0.623			0.746
Eigenvalues		2.616	2.292	2.097
Variance explained (total: 70.045%)		26.156%	22.916%	20.973%

Notes: A five-point scale is used where 1 = very unimportant and 5 = very important. Extraction method: principle component analysis. Rotation method: varimax with Kaiser normalization. Rotation converged in 5 iterations.

. Factor loadings ranged from 0.623 to 0.802, and the total percentage of variance was 70.045%.

From the results of the rotated component matrix, the factors are clearly identifiable. Factor 1 includes the variables of company development, job security, fair and equitable treatment at work and work relations. Thus, factor 1 was named Company development and culture. Factor 2 includes the variables of skills training, trade unions and social insurance. Therefore, factor 2 was named Welfare and benefits. Factor 3 includes work duration and intensity, work–life balance and adequate income; hence, this factor was named Work conditions and salary. As shown in

Table 10. Reliability analysis of the three factors (N = 541).

Factor 1: Company development and culture	Cronbach’s alpha = 0.837
• Company development
• Job security
• Fair and equitable treatment at work
• Work relations
Factor 2: Welfare and benefits	Cronbach’s alpha = 0.828
• Skills training
• Trade unions
• Social insurance
Factor 3: Work conditions and salary	Cronbach’s alpha = 0.753
• Work duration and intensity
• Work–life balance
• Adequate income

, Cronbach’s alpha for three factors were 0.753, 0.828 and 0.837, all of which were greater than the minimum level for acceptability [68].

Since apparel workers’ attitudes to decent work vary, cluster analysis was applied to identify which workers in a set held similar attitudes. Creating clusters of apparel workers based on their attitudes to decent work could improve understanding of workers’ motivations, enabling firms to create appropriate incentives and measures to enhance workers’ perceptions of well-being, which could lead to higher levels of productivity, commitment and loyalty.

Cluster analysis was applied to the factor scores derived in the previous section (i.e., Company development and culture, Welfare and benefits, and Work conditions and salary). The hierarchical cluster analysis using Ward’s hierarchical and the average linkage (within groups) method suggested a four-cluster solution, as shown in Table 10. The cluster centers were used in K-means clustering as recommended by Hair et al. [69].

As shown in

Table 11. Sample means and cluster means.

Factor	Total (N = 541)	Cluster 1 (N = 178)	Cluster 2 (N = 95)	Cluster 3 (N = 156)	Cluster 4 (N = 112)	F	Sig.	Scheffe’s Test (p < 0.05)
Company development and culture	3.48	3.93	4.26	3.10	2.62	216.768	0.000	C2 > C1 > C3 > C4
Welfare and benefits	3.02	3.90	1.86	2.79	2.92	207.772	0.000	C1 > C3, C4 > C2
Work conditions and salary	3.57	3.65	3.94	2.76	4.23	215.144	0.000	C4 > C2 > C1 > C3

Notes: A five-point scale is used where 1 = very unimportant and 5 = very important.

, the composite (arithmetic mean) scores of each construct were compared across the different clusters following Young [70], using Scheffe’s test to examine pairwise differences. Differences were found along all constructs and the clusters displayed distinctive differences in their attitudes to the criteria of decent work. Figure 2 shows the cluster means along the three constructs.

To verify the membership of the four clusters obtained, step-wise discriminant analysis was performed using the factor scores and class memberships given by the cluster analysis. Examination of the canonical discriminant functions revealed large canonical correlations (0.694, 0.736 and 0.779) on the three functions. All of the full model tests of Functions 1–3, Functions 2–3 and Function 3 were significant at p < 0.001 (see

Table 12. Multivariate results for the four-group discriminant analysis.

Function	Eigenvalue	% of Variance	Cumulative %	Canonical Correlation	Test of Function(s)	Wilks’ Lambda	Chi-Square	Df	Sig.
1	1.462 a	42.1	42.1	0.779	1–3	0.093	1272.482	9	0.000
2	1.131 a	32.4	74.5	0.736	2–3	0.237	772.254	4	0.000
3	0.964 a	25.5	100.0	0.694	3	0.518	353.099	1	0.000

Note: ^a First three canonical discriminant functions were used in the analysis.

). These results indicated that the discriminant functions fitted the data very well.

With classification results of discriminant analysis and cluster analysis (see

Table 13. Discriminant analysis classification results.

Actual Group	Number of Cases	Predicted Group Membership
		1		2		3		4
		n	%	n	%	n	%	n	%
1	179	174	97.8	0	0.0	3	1.7	1	0.6
2	95	1	1.1	94	98.9	0	0.0	0	0.0
3	156	1	0.6	0	0.0	154	98.7	1	0.6
4	112	0	0.0	1	0.9	2	1.8	109	97.3

Note: 98.2% of original grouped cases correctly classified.

), the percentage of samples correctly classified was 98.2%, suggesting that the classification results of cluster analysis were valid.

Table 14. Cluster distribution of blue-collar and white-collar workers.

Cluster	Blue-Collar Workers		White-Collar Workers
	Number of Cases	Percentage (%)	Number of Cases	Percentage (%)
1	108	34.5	70	30.7
2	36	11.5	59	25.9
3	89	28.4	67	29.4
4	80	25.6	32	14.0
Total	313	100.0	228	100.0

and Figure 3 show the cluster distribution of blue and white-collar workers. The next section discusses these findings in greater detail.

• Cluster 1: Demanding Workers

Workers in Cluster 1 valued all aspects of decent work when seeking a new job. This group had high means in company development and culture (3.93), welfare and benefits (3.90) and work condition and salary (3.65). The apparel industry is seen as a springboard for national development and has developed significantly in China over the past 25 years since the country became a world-class exporter in labor-intensive consumer products in the 1990s [23]. Industrial upgrading over the years has led to difficulties in recruitment of skilled workers for garment manufacturing firms [71], and workers have become more assertive in their demands for better working conditions and pay [27]. Over a third of respondents fell into this category, split fairly equally between blue-collar workers (34.5%) and white-collar workers (30.7%). This suggests that a significant number of garment workers in blue-collar as well as white-collar roles value soft conditions which are associated with higher levels of human motivation, not only hygiene factors such as work conditions and salary. HR managers looking to recruit and retain these workers should ensure job roles are attractive in all aspects to both blue-collar and white-collar workers.

• Cluster 2: Enterprise-Focused Workers

Compared with Cluster 1, this group valued company development and culture (4.26) as well as work conditions and salary (3.94). The mean of welfare and benefits is the lowest in this group (1.86), which suggests that these workers would place greater importance on the organizational culture of the company they work for and feeling a sense of belonging than access to skills training, social insurance or trade union presence. Enterprise-focused workers made up over a quarter of all white-collar workers (25.9%), twice more than the proportion of blue-collar workers (11.5%). HR managers looking to recruit and retain these workers should seek to promote a healthy organizational culture in the workplace, for example, through setting and communicating appropriate norms and values, or by organizing team building activities such as sports days.

• Cluster 3: Undemanding Workers

A total of 28.8% of respondents fell into this group, fairly equally split amongst 28.4% of blue-collar and 29.4% of white-collar workers. Compared with Cluster 1, undemanding workers have lower means on all three factors. This group had the lowest mean for work conditions and salary (2.76) and lower means in welfare and benefits (2.79) and company development and culture (3.10). The low means of these factors indicate that these workers may have less enthusiasm for their career, or may be unaware of their labor rights.

• Cluster 4: Benefits-Focused Workers

A total of 20.7% of respondents fell into this category. This group had the highest means for work conditions and salary (4.23) and a relatively high mean for welfare and benefits (2.92). However, the mean of company development and culture was ranked lowest (2.62) in this group. This suggests that workers have less sense of belonging in the company, so may resign when they find a job with higher salary and better welfare. In total, 25.6% of blue-collar workers fell into this cluster, but only 14.0% of white-collar workers, which suggests that many blue-collar workers would be less concerned with the organizational culture, access to training or a sense of belonging in a workplace. Instead, these workers may be more likely to seek jobs which simply offer good wages and better working conditions. These workers may be confident that their skills and experience make them marketable and easily capable of finding a new job, such that job security and work relations are less important to them; or may be willing to forgo these aspects in favor of better conditions and salary. HR managers could consider developing new induction processes to communicate company culture and foster a greater sense of belonging, which could help transform benefits-focused workers into dedicated employees and reduce labor turnover.

5. Conclusions

Gap analysis results suggest that: (1) Chinese garment workers are beginning to comprehend the nature of decent work, despite the fact that not all companies have yet implemented CSC9000T in the textile and apparel industry [50]; (2) the relatively poor satisfaction scores for the primary indicators of decent work, such as salary and work duration and intensity, suggest these should be improved; (3) workers still feel unsatisfied with their wages, although the Chinese government has taken measures to increase wages, for example via minimum wage increases, implementation of New Labor Contract Laws and CSC9000T; and (4) white-collar workers attach more importance to soft conditions, whilst blue-collar workers are more satisfied with soft criteria in their current job. Increasing wages has implications for the cost competitiveness of enterprises, and rising costs could affect export competitiveness when compared to other lower labor cost garment producing nations [72,73]. However, monetary reward is not the only means of making workers feel valued, and it may be possible to provide a more appealing working environment so that workers feel valued and motivated, despite relatively low wages.

Overall, the results suggest that: (1) younger workers pay more importance to decent work in their current job; (2) workers with lower education levels value income, work duration and intensity, social insurance and skills training; (3) workers with less service are more likely to value work duration and intensity, fair and equitable treatment at work and company development; (4) higher paid employees would pay more importance to soft factors of the work; and (5) white-collar workers are more enterprise-focused, while blue-collar workers are more benefits-focused. Overall, the results show that workers differ in their attitudes towards decent work, and there is evidence that soft factors are becoming more important across both blue-collar and white-collar levels in garment factories. Employee attraction and retention is especially important in the Chinese garment industry, a labor-intensive sector where wages are relatively low, workers are becoming more demanding and enterprises increasingly struggle to recruit skilled workers.

The findings could also help the government, NGOs and industry associations to implement decent work. Given the low satisfaction scores for some decent work criteria, the local and national government should work to raise awareness of the importance and benefits of decent work in garment enterprises. Profitability and provision of quality jobs are not necessarily mutually exclusive, and improving job quality can lead to better organizational performance [74]. Steurer et al. [75] highlighted EU member states’ awareness raising initiatives through various informational instruments, including educational activities (e.g., conferences, seminars, training), information resources (e.g., websites, brochures, reports), and government-sponsored guidelines (e.g., German Corporate Governance Code). Similar tactics could be employed by the Chinese government and the China National Textile and Apparel Council (CNTAC) to raise awareness of decent work amongst garment enterprises and workers. NGOs and industry associations could also take steps to help enterprises raise awareness and effectiveness of decent work implementation, for example by providing training to overcome weak managerial skills or lack of decent work knowledge in enterprises.

There are several limitations in this study. The relatively small sample size and the limited geographical area mean the findings may not be representative of the entire industry. As the education level of garment industry workers is relatively low, it is possible that some respondents did not fully comprehend all the questions. Furthermore, the survey items were mainly drawn from Western concepts and frameworks for decent work studies, which may not be perfectly applicable in a non-Western context. As data were collected in 2013, caution should be drawn when interpreting the results as business and political environments have since changed. Although China was relatively slow to ratify ILO conventions on decent work indicators [38], recent reports suggest that the younger generation of the labor force is better educated and has greater expectations in terms of financial reward and quality of life [76]. However, despite minimum wage increases, low wage workers often struggle to make ends meet due to rising living costs, and too many wage increases could harm China’s cost competitiveness compared to other Asian nations [73]. Rising labor costs, currency appreciation, and lower demand from export markets [71] place further pressures on garment manufacturers to balance social and economic sustainability. Although today’s workers may have higher salaries and better understanding of decent work than the sample from 2013, it is questionable whether satisfaction with conditions may have improved.

As apparel production operations progressively shift to western regions of China [71], future research studies could focus on different regions. Longitudinal studies could track trends for implementation, concern and attitudes of decent work over the course of time, while qualitative research could uncover deeper reasons behind workers’ attitudes. Addressing workers’ concerns whilst maintaining cost competitiveness deserve further consideration. Studies exploring the connection between decent work and employee productivity, recruitment and retention could provide further insight on how to achieve decent work while maintaining cost competitiveness for social and economic sustainability.