Combat Workplace Sexual Harassment by Third Parties? Reframing Institutional Measures and Cultural Transformation in South Korea

Abstract

This study investigated the risk factors for workplace sexual harassment in South Korea using cross-sectional data of the 2014 and 2017 Korean Working Conditions Survey (KWCS). A generalized linear model specified with a Poisson distribution and log link function was performed. Females, younger adults, jobs in services or sales, tasks that involve visiting places where clients reside, and significant work time contribution to customers were associated with increased gender harassment and unwanted sexual attention. Evidence suggests that third parties and male-oriented culture may pose a serious threat to healthy working conditions.

Keywords

sexual harassment third parties culture

Introduction

The #MeToo movement around the world has drawn serious global attention to workplace sexual harassment by powerful men against women (Zarkov & Davis, 2018). In South Korea, the #MeToo movement became a monumental force with several silent victims courageously coming forward to tell their stories (Bicker, 2018). The explosion of accusations of sexual harassment suggests that work-related sexual harassment in South Korea is serious, pressuring the country’s conservative society to seriously combat sexual misbehaviors in the workplace.

Workplace sexual harassment causes victimized individuals to suffer serious consequences. Victims experience an enormous economic impact after being sexually harassed. Individuals with a history of being sexually harassed have a high risk of falling into poverty (Byrne et al., 1999) and bear substantial financial burdens for things such as health care and counseling to recover from the incidents (Seidman & Vickers, 2005). Furthermore, sexual harassment causes the victims to experience diminished performance, time lost from work, and potential job loss (Loya, 2015; Tjaden & Thoenners, 2006). From a public health perspective, sexual harassment is a substantial concern, as it can severely affect victimized individuals by causing post-traumatic stress disorders, anxiety, depression, and suicide (Ba & Bhopal, 2017; Jonathan et al., 1996; Richman et al., 1999). A recent systematic review also found that sexual harassment victims complain about social impacts that include abandonment by their spouse and rejection by their family members and the community (Ba & Bhopal, 2017).

Known as a male-oriented society, South Korea has a short history of recognizing sexual harassment at work. A breakthrough occurred in 1999 when workplace sexual harassment was defined in an amendment of the Gender Equality of Employment Act (Korean Ministry of Government Legislation, 2019). According to the law, workplace sexual harassment is any behavior that creates negative working conditions by sexually humiliating others physically and verbally or using retaliatory measures in a superior position to disadvantage an individual. In 2007, another amendment to the Gender Equality of Employment Act expanded the scope of potential workplace sexual harassment perpetrators to include third parties such as customers and clients. Most recently, the Gender Equality of Employment Act was again amended, effective in 2018, to impose stricter requirements for appropriate measures against workplace sexual harassment on employers. These measures included preventive education, timely investigation of incidents, a confidentiality policy, and paid leave for victims.

Despite these legislative achievements, workplace sexual harassment remains prevalent in the country. According to the Ministry of Gender Equality and Family, approximately 10% of female employees said they experienced some type of sexual harassment (Korean Ministry of Gender Equality and Family, 2015). Another finding from the report was that a majority of workplace sexual harassment incidents took place within organizations in settings such as after-work dinner meetings and a common workplace practice in the country. The report highlights how workplace sexual harassment is rooted in power differences between a superior and a subordinate, an observation found in previous studies (Berdahl, 2007; Tangri et al., 1982). Meanwhile, the Korean media has documented growing concerns over workplace sexual harassment by third parties by introducing cases about sexual harassment against call center employees, security guards, and street cleaners (Lee, 2015; Seo, 2018). Researchers have investigated sexual harassment issues triggered by individuals outside companies or organizations such as customers and clients in service sectors and clinical practice settings (Joo & Rhie, 2017; C. S. Kim & Aggarwal, 2016; S. K. Lee et al., 2011). A recent study argues that workers who have direct interactions with customers or clients are exposed to the high risk of workplace mistreatment, including sexual harassment (Chung et al., 2017). However, despite the mounting concerns regarding sexual harassment cases associated with persons outside organizations, this issue has been less studied in South Korea. Thus, there is scant knowledge about the risk factors that would potentially represent the role of perpetrators outside organizations in the prevalence of sexual harassment.

O’Hare et al. proposed a four-factor model accounting for multi-faceted risk factors for sexual harassment. It was designed to improve earlier models that represented limited dimensions of risk factors surrounding sexual harassment. Given the difficulty in assessing the harasser factors such as motivation and overcoming internal inhibitions against sexual harassment, the model focused on victim factors covering the environmental, organizational, and personal characteristics of victims. In this study, the environmental and organizational characteristics included co-worker’s gender, time contribution to customers, and tasks involving visits to places where customers reside and work (Chung et al., 2017; O’Hare & O’Donohue, 1998). Recent literature also suggests that gender discrimination is an important cultural aspect of organizations that contributes to the prevalence of sexual harassment in the workplace (Kearns et al., 2020). Personal characteristics included job type representing a range of jobs and employment type (Fine et al., 1999; Hennekam & Bennett, 2017). In addition, population characteristics were added to the identified risk factors (H. E. Lee et al., 2014).

In response to increasing fears of workplace sexual harassment by third parties and demands for its investigation, our study has a research question of whether perpetrators outside organizations are associated with a greater risk for sexual harassment. We investigate the likelihood of sexual harassment focusing on risk factors that potentially represent the third parties’ role in the prevalence of sexual harassment.

Method

Data

This study uses the 2014 and 2017 Korean Working Conditions Survey (KWCS) data published by the Korean Occupational Safety and Health Research Institute. The nationally representative database was aimed to provide a wide range of information surrounding industrial safety and health to shape national policy for healthy working conditions. The survey has been conducted every 3 years since 2011 on employees aged 15 years or above to capture workers’ experience concerning their working conditions. The responses from participants were documented through a face-to-face (1:1) individual interview by trained interviewers using either paper and pen interviewing (PAPI) or computer-assisted personal interviewing (CAPI). The survey method relies on a stratified cluster random sampling method that accounted for a primary sampling unit and household as a secondary sampling unit as well as individuals for the final sampling unit. Weighting procedures have been performed to reduce potential bias resulting from the probabilities of the sample and improve the representation of the data. The response rate according to the American Association for Public Opinion Research (AAPOR) Response Rate 3 was 33% in 2014 and 45% in 2017. Researchers have verified the survey’s validity and reliability for scientific studies (Kim et al., 2013).

Measurement

Outcome variables

The outcome variable is gender harassment. Participants were asked, “Have you experienced gender harassment in your workplace?” Gender harassment was dichotomized as “yes” if the participant experienced gender harassment and “no” if not. Another outcome variable is unwanted sexual attention, considered to be a type of sexual harassment, which the survey separately collected (Fairchild et al., 2018). The survey participants were asked, “Have you experienced unwanted sexual attention in your workplace?” Unwanted sexual attention was coded as “yes” if the respondent reported any unwanted sexual attention and “no,” otherwise. In addition, the combined measure of gender harassment and unwanted sexual attention was created to serve as sexual harassment.

Covariates

Key independent variables consist of factors that potentially represent the third parties’ role in the prevalence of sexual harassment such as job type, work time contribution to customers or clients, and tasks that involve visits to places where customers reside and work. Participants were asked, “What is your current job type?” The job type had six categories, which included manager/professionals, clerk, services, sales, agriculture/fishing/craft/machine, and elementary occupations. Also, respondents were asked, “How much of work time do you contribute to interacting with customers or clients?” The response was categorized as “most of the time,” “equal to or more than half,” “equal to or more than one-fourth,” and “rarely.” Another survey question of interest was “Do your tasks involve visits to places where customers or clients reside and work?” It was dichotomized as “yes” if participants had such tasks and “no,” otherwise.

Co-workers’ gender captures the skewness of the gender ratio among employees sharing common tasks with respondents and it was categorized as male dominant, female dominant, balanced, and nobody. Employment type was categorized as self-employed, employed, or others that include working for family or relatives without financial compensation. Gender discrimination that serves as a measure of organizational culture was dichotomized as any experience of gender discrimination in the workplace or not.

Socioeconomic characteristics are gender, age, education, and income level. Age was categorized as 15–29, 30–39, 40–49, 50–59, and ≥65 years. Education had four categories: less than high school graduation, high school graduation, some college education, and college graduation. Monthly income was categorized as <$833, $833 to <$1,667, $1,667 to <$2,450, $2,450 to <$3,333, and ≥$3,333. The year indicator was coded as a binary variable.

Statistical analysis

We calculated the rate of gender harassment and unwanted sexual attention as well as a combined measure of these two types of harassment. Furthermore, the rate of gender harassment and unwanted sexual attention was calculated by perpetrators. In the multivariable analysis, a generalized linear model specified with a Poisson distribution and log link function using robust standard errors was performed to calculate adjusted prevalence ratios (APRs) for gender harassment and unwanted sexual attention while accounting for covariates. In addition, the study performed a generalized linear model among males and females separately to see whether there are different patterns of associations across genders. All statistical analyses were properly weighted to account for the multi-stage sampling and were conducted using STATA/MP 15.

Results

The study sample consisted of 57.5% (95% CI = [57.1, 57.9]) male and 42.5% (95% CI = [42.1, 42.9]) female, as shown in Table 1. The age of the sample was distributed from the lowest percentage (13.3%, 95% CI = [13.0, 13.6]) among individuals below 30 years to the highest percentage (29.0%, 95% CI = [28.6, 29.3]) among those aged 50 to 59 years. Most survey participants graduated from either high school (36.4%, 95% CI = [36.0, 36.7]) or college (34.4%, 95% CI = [34.0, 34.8]). Approximately half of the participants were concentrated in income categories, monthly earnings between $833 and $1,667 (25.8%, 95% CI = [25.4, 26.1]) or between $1,667 and $2,450 (24.8%, 95% CI = [24.5, 25.2]). The percentages of job types ranged between 10.5% (95% CI = [10.3, 10.7]) in elementary occupations and 21.6% (95% CI = [21.3, 21.9]) in agriculture/fishing/craft/machine. About 13.5% (95% CI = [13.5, 14.1]) of the participants had tasks that involved visits to places where clients reside and work. Approximately 36.0% (95% CI = [35.6, 36.3]) of the participants spent most of their work time with customers, while 47.0% (95% CI = [46.6, 47.4]) were rarely contacting customers at the workplace.

Table 1.

Characteristics of the Study Sample.

Characteristics	n	wt% [95% CI]
Gender
Female	51,258	42.5 [42.1, 42.9]
Male	48,954	57.5 [57.1, 57.9]
Age (years)
15–29	8,237	13.3 [13.0, 13.6]
30–39	16,802	20.5 [20.2, 20.9]
40–49	23,690	25.3 [24.0, 24.7]
50–59	32,573	29.0 [28.6, 29.3]
≥65	14,590	8.9 [8.7, 9.1]
Education
	20,211	13.3 [13.0, 13.5]
High school	39,002	36.4 [36.0, 36.7]
Some college	13,719	15.5 [15.2, 15.8]
≥College	26,820	34.4 [34.0, 34.8]
Income (monthly, $)
<833	17,635	14.5 [14.2, 14.7]
833 to <1,667	27,904	25.8 [25.4, 26.1]
1,667 to <2,450	23,860	24.8 [24.5, 25.2]
2,450 to <3,333	15,358	17.5 [17.2, 17.8]
≥3,333	10,262	13.0 [12.8, 13.3]
Environmental/organizational characteristics
Tasks involving visits to client’s places
No	87,304	85.8 [85.6, 86.1]
Yes	12,546	13.5 [13.5, 14.1]
Time contribution to customer/client
Significant	38,360	36.0 [35.6, 36.3]
Half	7,165	7.1 [6.9, 7.3]
Little	8,957	9.6 [9.3, 9.8]
Rare	45,404	47.0 [46.6, 47.4]
Co-worker gender
Male dominant	27,682	35.6 [35.2, 36.0]
Female dominant	25,311	23.6 [23.2, 23.9]
Balanced	23,932	25.4 [25.1, 25.8]
Nobody	21,525	13.9 [13.7, 14.2]
Gender discrimination
No	98,568	98.0 [97.9, 98.1]
Yes	1,453	1.8 [1.7, 1.9]
Personal characteristics
Job type
Manager/professionals	12,658	16.4 [16.0, 16.7]
Clerk	15,236	21.0 [20.7, 21.4]
Service	17,627	15.7 [15.4, 15.9]
Sales	19,428	14.8 [14.5, 15.0]
Agriculture/fishing/craft/machine	23,844	21.6 [21.3, 21.9]
Elementary occupations	11,319	10.5 [10.3, 10.7]
Employment type
Self-employed	34,541	21.8 [21.5, 22.1]
Employed	60,859	73.4 [73.1, 73.7]
Other	4,810	4.8 [4.6, 5.0]
Year
2014	50,007	49.9 [49.5, 50.3]
2017	50,205	50.1 [49.7, 50.5]

In Table 2, gender harassment was 0.82% (95% CI = [0.71, 0.91]) among females and 0.11% (95% CI = [0.07, 0.14]) among males, while the figures were 1.66% (95% CI = [1.51, 1.80]) and 0.33% (95% CI = [0.26, 0.39]) for unwanted sexual attention, respectively. Those below 30 years reported higher gender harassment (0.58%, 95% CI = [0.39, 0.78]) and unwanted sexual attention (1.60%, 95% CI = [1.30, 1.92]) than those in other age groups. Higher gender harassment was also found among survey participants working in the service (0.95%, 95% CI = [0.78, 1.14]) and sales (0.70%, 95% CI = [0.56, 0.83]) sectors, while the figure of unwanted sexual harassment was 1.91% (95% CI = [1.67, 2.16]) and 1.38% (95% CI = [1.18, 1.58]) in these sectors, respectively. Workers who spend most of their work time with customers reported the highest rate of both gender harassment (0.77%, 95% CI = [0.67, 0.88]) and unwanted sexual attention (1.53%, 95% CI = [1.38, 1.68]). When tasks involved travel to places of clients, gender harassment (0.54%, 95% CI = [0.40, 0.68]) and unwanted sexual attention (1.22%, 95% CI = [1.00, 1.44]) were greater than when tasks did not involve such activities. Participants surrounded by female-dominant work environments showed higher gender harassment (0.95%, 95% CI = [0.80, 1.10]) and unwanted sexual attention (1.61%, 95% CI = [1.42, 1.79]). Workers who reported gender discrimination showed greater gender harassment (3.81%, 95% CI = [2.69, 4.93]) and unwanted sexual attention (7.78%, 95% CI = [6.12, 9.44]) than workers who did not report gender discrimination.

Table 2.

Sexual Harassment Rates by Sample Characteristics.

	Gender harassment			Unwanted sexual attention			Sexual harassment
Characteristics	n	wt% [95% CI]	p	n	wt% [95% CI]	p	n	wt% [95% CI]	p
	458	0.41 [0.36, 0.45]		912	0.89 [0.82, 0.96]		1,089	1.07 [0.99, 1.15]
Gender			<.001			<.001			<.001
Female	412	0.82 [0.72, 0.92]		778	1.66 [1.51, 1.81]		930	2.00 [1.84, 2.15]
Male	46	0.11 [0.07, 0.14]		134	0.33 [0.26, 0.39]		159	0.38 [0.31, 0.46]
Age (years)			<.001			<.001			<.001
15–29	48	0.58 [0.39, 0.78]		134	1.60 [1.30, 1.92]		154	1.89 [1.54, 2.23]
30–39	59	0.31 [0.22, 0.40]		159	0.84 [0.68, 1.00]		178	0.96 [0.79, 1.13]
40–49	126	0.41 [0.32, 0.50]		250	0.88 [0.74, 1.01]		292	1.02 [0.88, 1.16]
50–59	154	0.38 [0.30, 0.45]		265	0.70 [0.60, 0.80]		330	0.87 [0.76, 0.99]
≥65	16	0.13 [0.05, 0.20]		21	0.16 [0.07, 0.26]		30	0.25 [0.13, 0.36]
Education			<.001			<.001			<.001
	40	0.17 [0.11, 0.24]		60	0.32 [0.22, 0.42]		81	0.41 [0.30, 0.51]
High school	251	0.59 [0.50, 0.69]		471	1.15 [1.02, 1.28]		563	1.39 [1.25, 1.54]
College	81	0.49 [0.36, 0.62]		178	1.17 [0.97, 1.37]		203	1.35 [1.13, 1.57]
≥College	82	0.27 [0.20, 0.34]		200	0.73 [0.60, 0.86]		237	0.86 [0.72, 0.99]
Income (monthly, $)			<.001			.001			<.001
<833	47	0.31 [0.20, 0.41]		128	0.90 [0.72, 1.09]		139	0.97 [0.78, 1.16]
833 to <1,667	171	0.58 [0.47, 0.69]		284	1.07 [0.91, 1.22]		359	1.36 [1.18, 1.54]
1,667 to <2,450	117	0.43 [0.33, 0.53]		253	0.98 [0.83, 1.13]		294	1.16 [0.99, 1.32]
2,450 to <3,333	69	0.33 [0.23, 0.43]		134	0.76 [0.60, 0.92]		162	0.89 [0.71, 1.06]
≥3,333	39	0.29 [0.18, 0.40]		72	0.56 [0.38, 0.75]		87	0.68 [0.48, 0.88]
Environmental/organizational characteristics
Tasks involving visits to client’s places			.030			<.001			.001
No	372	0.39 [0.34, 0.44]		733	0.84 [0.77, 0.92]		878	1.02 [0.93, 1.10]
Yes	85	0.54 [0.40, 0.68]		175	1.22 [1.00, 1.44]		207	1.40 [1.17, 1.63]
Time contribution to customer/client			<.001			<.001			<.001
Most	328	0.77 [0.67, 0.88]		592	1.53 [1.38, 1.68]		713	1.84 [1.67, 2.00]
Half	20	0.29 [0.14, 0.46]		65	0.88 [0.57, 1.21]		73	1.04 [0.70, 1.37]
Little	33	0.32 [0.19, 0.45]		59	0.59 [0.41, 0.78]		73	0.73 [0.53, 0.94]
Rare	76	0.16 [0.12, 0.21]		190	0.46 [0.38, 0.54]		223	0.54 [0.46, 0.63]
Co-worker gender			<.001			<.001			<.001
Male dominant	48	0.14 [0.09, 0.18]		127	0.47 [0.37, 0.57]		149	0.52 [0.42, 0.63]
Female dominant	241	0.96 [0.81, 1.10]		408	1.61 [1.42, 1.79]		500	2.01 [1.80, 2.23]
Balanced	74	0.31 [0.22, 0.39]		177	0.82 [0.67, 0.97]		207	0.95 [0.80, 1.12]
Nobody	79	0.32 [0.24, 0.40]		178	0.85 [0.69, 1.01]		207	0.95 [0.80, 1.14]
Gender discrimination			<.001			<.001			<.001
No	390	0.35 [0.30, 0.39]		790	0.77 [0.70, 0.83]		946	0.92 [0.85, 0.99]
Yes	67	3.81 [2.69, 4.93]		119	7.78 [6.12, 9.44]		140	9.13 [7.36, 10.9]
Personal characteristics
Job type			<.001			<.001			<.001
Manager/professionals	38	0.26 [0.16, 0.36]		81	0.63 [0.47, 0.79]		101	0.79 [0.61, 0.98]
Clerk	48	0.32 [0.21, 0.42]		120	0.87 [0.68, 1.06]		143	1.00 [0.80, 1.20]
Service	183	0.96 [0.78, 1.14]		350	1.91 [1.67, 2.16]		412	2.28 [2.01, 2.56]
Sales	142	0.70 [0.56, 0.83]		265	1.38 [1.18, 1.58]		317	1.67 [1.45, 1.89]
Agriculture/fishing/craft/machine	28	0.14 [0.08, 0.21]		63	0.34 [0.24, 0.43]		76	0.40 [0.30, 0.51]
Elementary occupations	18	0.15 [0.06, 0.24]		33	0.30 [0.17, 0.43]		39	0.35 [0.21, 0.48]
Employment type			.012			.203			.030
Employed	154	0.39 [0.32, 0.47]		285	0.78 [0.67, 0.89]		336	0.90 [0.79, 1.01]
Self-employed	297	0.43 [0.37, 0.49]		595	0.93 [0.84, 1.02]		720	1.13 [1.03, 1.23]
Other	7	0.15 [0.03, 0.26]		32	0.88 [0.53, 1.23]		33	0.91 [0.56, 1.26]
Year			.002			.756			.123
2014	187	0.34 [0.28, 0.39]		452	0.88 [0.78, 0.98]		512	1.01 [0.90, 1.11]
2017	271	0.48 [0.41, 0.56]		460	0.91 [0.80, 1.02]		577	1.13 [1.01, 1.25]

The proportion of gender harassment and unwanted sexual attention by perpetrators is shown in Table 3. Customers showed a greater proportion of gender harassment (77.0%, 95% CI = [71.6, 82.4]) compared with co-workers (23.0%, 95% CI = [17.6, 28.4]). Similarly, the proportion of unwanted sexual attention was considerably higher by customers (75.0%, 95% CI = [71.0, 79.0]) than by co-workers (25.0%, 95% CI = [21.0, 29.0]).

Table 3.

Bivariate Relationship Between Sexual Harassment and Perpetrators.

	Gender harassment			Unwanted sexual attention			Sexual harassment
Characteristics	n	wt% [95% CI]	p	n	wt% [95% CI]	p	n	wt% [95% CI]	p
Perpetrators			<.001			<.001			<.001
Co-workers	74	23.0 [17.6, 28.4]		154	25.0 [21.0, 29.0]		183	24.1 [20.5, 27.7]
Customers/clients	352	77.0 [71.6, 82.4]		699	75.0 [71.0, 79.0]		835	75.9 [72.3, 79.5]

The multivariate analysis in Table 4 shows that gender harassment (APR = 6.80, 95% CI = [3.70, 12.50]), unwanted sexual attention (APR = 5.13, 95% CI = [3.71, 7.09]), and sexual harassment (APR = 5.08, 95% CI = [3.77, 6.86]) were significantly higher in females than in males. All age groups compared with those aged between 15 and 29 years had a lesser likelihood of unwanted sexual attention and sexual harassment, with adults ≥65 years showing the lowest likelihood. Tasks that involve visiting places where clients reside were associated with higher gender harassment (APR = 1.75, 95% CI = [1.27, 2.41]), unwanted sexual attention (APR = 1.70, 95% CI = [1.36, 2.13]), and sexual harassment (APR = 1.62, 95% CI = [1.33, 1.99]). In the job type, the likelihood of gender harassment was significantly higher in service (APR = 2.48, 95% CI = [1.52, 4.05]) and sales (APR = 1.89, 95% CI = [1.15, 3.12]) occupations compared with managers or professionals. Similarly, the service and sales sectors showed greater gender harassment and unwanted sexual attention as APR 2.29 (95% CI = [1.63, 3.22]) and APR 1.75 (95% CI = [1.23, 2.47]), respectively, while clerical jobs were associated with increased unwanted sexual attention (APR = 1.48, 95% CI = [1.02, 2.14]). Workers who contribute most of their work time to customers than those who rarely do so reported a significantly higher likelihood of gender harassment (APR = 2.28, 95% CI = [1.60, 3.22]), unwanted sexual attention (APR = 1.97, 95% CI = [1.55, 2.51]), and sexual harassment (APR = 1.97, 95% CI = [1.57, 2.45]). When gender discrimination was reported, gender harassment and unwanted sexual attention were markedly higher (APR = 7.93, 95% CI = [5.43, 11.57]; APR = 6.83, 95% CI = [5.22, 8.94], respectively). While the year 2017 relative to 2014 showed greater gender harassment (APR = 1.32, 95% CI = [1.01, 1.74]), no significant difference was noted in unwanted sexual harassment and sexual harassment.

Table 4.

Adjusted Prevalence Ratios (APRs) for Sexual Harassment.

	APR [95% CI]
Characteristics	Gender harassment	Unwanted sexual attention	Sexual harassment
Gender
Male	—	—	—
Female	6.80 [3.70, 12.50]^‡	5.13 [3.71, 7.09]^‡	5.08 [3.77, 6.86]^‡
Age (years)
15–29	—	—	—
30–39	0.80 [0.50, 1.30]	0.68 [0.50, 0.92]*	0.68 [0.52, 0.90]^†
40–49	0.82 [0.52, 1.29]	0.60 [0.45, 0.79]^†	0.61 [0.47, 0.79]^‡
50–59	0.78 [0.48, 1.27]	0.51 [0.38, 0.69]^‡	0.57 [0.43, 0.75]^‡
≥65	0.59 [0.24, 1.46]	0.23 [0.11, 0.47]^‡	0.33 [0.17, 0.62]^†
Education
	—	—	—
High school	1.36 [0.79, 2.33]	1.34 [0.89, 2.03]	1.38 [0.94, 2.01]
College	0.92 [0.49, 1.74]	1.12 [0.70, 1.80]	1.11 [0.71, 1.72]
≥College	0.77 [0.40, 1.46]	0.92 [0.58, 1.48]	0.94 [0.61, 1.45]
Income (monthly, $)
<833	—	—	—
833 to <1,667	1.87 [1.18, 2.97]^†	1.06 [0.80, 1.40]	1.27 [0.98, 1.66]
1,667 to <2,450	1.96 [1.17, 3.29]*	1.32 [0.97, 1.78]	1.45 [1.09, 1.93]*
2,450 to <3,333	2.39 [1.31, 4.34]^†	1.55 [1.08, 2.21]*	1.75 [1.25, 2.44]^†
≥3,333	1.96 [1.01, 3.79]*	1.14 [0.68, 1.89]	1.36 [0.86, 2.13]
Environmental/organizational characteristics
Tasks involving visits to client’s places
No	—	—	—
Yes	1.75 [1.27, 2.41]^†	1.70 [1.36, 2.13]^‡	1.62 [1.33, 1.99]^‡
Time contribution to customer/client
Rare	—	—	—
Significant	2.28 [1.60, 3.22]^‡	1.97 [1.55, 2.51]^‡	1.97 [1.57, 2.45]^‡
Half	1.13 [0.58, 2.19]	1.31 [0.82, 2.08]	0.83 [0.84, 1.95]
Little	1.65 [0.98, 2.81]	1.08 [0.74, 1.59]	1.13 [0.80, 1.60]
Co-worker gender
Male dominant	—	—	—
Female dominant	1.40 [0.78, 2.53]	0.89 [0.64, 1.24]	0.98 [0.72, 1.33]
Balanced	1.12 [0.61, 2.06]	0.88 [0.64, 1.23]	0.93 [0.68, 1.26]
Nobody	0.85 [0.46, 1.55]	0.93 [0.60, 1.43]	0.98 [0.66, 1.45]
Gender discrimination
No	—	—	—
Yes	7.93 [5.43, 11.57]^‡	6.83 [5.22, 8.94]^‡	6.66 [5.19, 8.55]^‡
Personal characteristics
Job type
Manager/professionals	—	—	—
Clerk	1.31 [0.75, 2.28]	1.48 [1.02, 2.14]*	1.38 [0.99, 1.93]
Service	2.48 [1.52, 4.05]^‡	2.29 [1.63, 3.22]^‡	2.23 [1.63, 3.03]^‡
Sales	1.89 [1.15, 3.12]*	1.75 [1.23, 2.47]^†	1.72 [1.26, 2.36]^†
Agriculture/fishing/craft/machine	1.04 [0.47, 2.28]	1.09 [0.68, 1.76]	1.01 [0.65, 1.57]
Elementary occupations	0.72 [0.26, 1.98]	0.74 [0.38, 1.42]	0.61 [0.33, 1.12]
Employment type
Employed	—	—	—
Self-employed	0.91 [0.65, 1.26]	0.89 [0.67, 1.19]	0.79 [0.61, 1.03]
Other	0.32 [0.13, 0.82]*	0.74 [0.45, 1.22]	0.65 [0.40, 1.06]
Year
2014	—	—	—
2017	1.32 [1.01, 1.74]*	1.05 [0.87, 1.26]	1.13 [0.95, 1.33]

p < .05. ^†p < .01. ^‡p < .001.

Table 5 shows the risk of sexual harassment by genders. Among males, gender harassment was less common for those self-employed than those employed (APR = 0.40, 95% CI = [0.19, 0.82]). However, sexual harassment was more common among workers who contribute a significant time (APR = 3.31, 95% CI = [1.84, 5.95]) or little time (APR = 2.66, 95% CI = [1.33, 5.30]) to customers relative to those who rarely do so. Moreover, workers who reported gender discrimination showed notably higher sexual harassment (APR = 6.04, 95% CI = [2.79, 13.05]) than those who did not. Among females, all age groups relative to those between 15 and 29 years had a lower likelihood of sexual harassment. Tasks that involve visits to places of clients were associated with greater sexual harassment (APR = 1.87, 95% CI = [1.52, 2.32]). In job types, sexual harassment was noted in the clerical job (APR = 1.53, 95% CI = [1.06, 2.19]), service (APR = 2.36, 95% CI = [1.69, 2.31]), and sales (APR = 1.86, 95% CI = [1.31, 2.63]). Workers who contribute significant time to customers compared with those who rarely do so revealed a greater likelihood of sexual harassment (APR = 1.77, 95% CI = [1.41, 2.23]). Gender discrimination was associated with a considerably higher risk for sexual harassment (APR = 6.55, 95% CI = [5.06, 8.48]).

Table 5.

Adjusted Prevalence Ratios (APRs) for Sexual Harassment by Genders.

	APR [95% CI]
Characteristics	Male	Female
Age (years)
15–29	—	—
30–39	0.32 [0.13, 0.81]*	0.80 [0.60, 1.07]*
40–49	0.42 [0.16, 1.10]	0.65 [0.49, 0.85]^†
50–59	0.45 [0.18, 1.12]	0.57 [0.43, 0.77]^‡
≥65	0.52 [0.18, 1.52]	0.21 [0.09, 0.46]^‡
Education
	—	—
High school	1.75 [0.65, 4.67]	1.19 [0.80, 1.78]
College	2.07 [0.67, 6.38]	0.89 [0.46, 1.41]
≥College	2.26 [0.75, 6.81]	0.71 [0.45, 1.12]
Income (monthly, $)
<833	—	—
833 to <1,667	1.15 [0.54, 2.42]	1.30 [0.98, 1.72]
1,667 to <2,450	0.99 [0.44, 2.22]	1.54 [1.14, 2.09]
2,450 to <3,333	1.49 [0.61, 3.62]	1.81 [1.27, 2.59]
≥3,333	1.11 [0.34, 3.62]	1.46 [0.92, 2.31]
Environmental/organizational
Tasks involving visits to client’s places
No	—	—
Yes	1.08 [0.64, 1.81]	1.87 [1.52, 2.32]^‡
Time contribution to customer/client
Rare	—	—
Significant	3.31 [1.84, 5.95]^‡	1.77 [1.41, 2.23]^‡
Half	1.60 [0.29, 8.80]	1.20 [0.83, 1.75]
Little	2.66 [1.33, 5.30]^†	0.84 [0.57, 1.24]
Co-worker gender
Male dominant	—	—
Female dominant	1.95 [0.78, 2.52]	0.75 [0.55, 1.02]
Balanced	1.02 [0.61, 2.03]	0.75 [0.54, 1.04]
Nobody	2.98 [1.40, 6.35]^†	0.61 [0.40, 0.93]
Gender discrimination
No	—	—
Yes	6.04 [2.79, 13.05]^‡	6.55 [5.06, 8.48]^‡
Personal characteristics
Job type
Manager/professionals	—	—
Clerk	0.60 [0.20, 1.78]	1.53 [1.06, 2.19]*
Service	1.75 [0.86, 3.57]	2.36 [1.69, 2.31]^‡
Sales	1.15 [0.54, 2.46]	1.86 [1.31, 2.63]^‡
Agriculture/Fishing/craft/machine	1.01 [0.46, 2.23]	1.09 [0.65, 1.85]
Elementary occupations	0.93 [0.30, 2.78]	0.47 [0.22, 1.04]
Employment type
Employed	—	—
Self-employed	0.40 [0.19, 0.82]*	0.92 [0.70, 1.19]
Other	1.13 [0.15, 8.85]	0.63 [0.39, 1.03]
Year
2014	—	—
2017	1.02 [0.66, 1.57]	1.16 [0.97, 1.40]

p < .05. ^†p < .01. ^‡p < .001.

Discussion

This study examines the risk factors for workplace sexual harassment in South Korea focusing on perpetrators outside organizations, namely, third parties. Our findings confirm that females are vulnerable to workplace sexual harassment (Sadler et al., 2017; Talvi, 1997). This study also shows that the younger the workers, the higher the risk of sexual harassment. The recent spotlights on multiple allegations of sexual harassment by high-profile employees and government officials reflect the seriousness of sexual harassment within organizations in South Korea (J. Lee et al., 2018). However, while public attention to workplace sexual harassment has focused on power abuses within organizations, our study finds that third parties are a significant risk factor for workplace sexual harassment. For example, jobs in the service and sales industries are 2.48 times and 1.89 times higher for gender harassment compared with managers and professionals. At the same time, they show 2.29 times and 1.75 times greater unwanted sexual attention, respectively. Also, workers who spend most of their work time with customers are 2.28 times and 1.97 times more likely to experience gender harassment and unwanted sexual attention than those who rarely do so. Furthermore, for those whose tasks involve visiting places where customers reside, workplace sexual harassment is noted. A series of indicators represent that sexual harassment by third parties is a significant threat to safe working conditions and more noted among female workers. This also warrants the need to re-evaluate gaps in how Korean society combats workplace sexual harassment.

Several factors may explain the high rate of workplace sexual harassment by third parties. A suggested contributing factor is the business culture in South Korea, which often touts slogans such as “the customer is king.” High standards for serving customers could lead to the power imbalance between customers and workers (Fine et al., 1999). Because of business attitudes toward customers, abusive behaviors toward workers can easily be ignored without appropriate countermeasures undertaken by victims. In addition, prioritizing customers could prevent victims from bringing their cases to the table, which would create further obstacles to solving these difficult problems (Joo & Rhie, 2017; Lee, 2015). The findings of the present study suggest that workers who frequently encounter customers at the workplace or who visit places where customers reside and work are vulnerable to workplace sexual harassment. When it comes to female workers, sexual harassment by third parties is more noted in the areas examined, such as the services and sales sectors and during tasks that involve visiting clients’ locations. Our study also revealed that the clerical job type received increased unwanted sexual attention. This may suggest that the service and sales sectors are at higher risk of an incident as well as jobs that involve frequent interactions with individuals outside the organizations—a fact that has often been overlooked. For example, it has been that public officials dealing with citizens’ affairs experience increased sexual harassment by third parties (Korean Occupational Safety and Health Research Institute, 2018). Workers in this job category who do not have an interest-based relationship, unlike employees in sales and service jobs, may not experience the same business pressure to satisfy third parties. Nevertheless, the findings in this study suggest that sexual harassment by third parties has been a significant threat to healthy working conditions and that the underlying issues fueling third parties’ misbehaviors must be addressed.

To address this critical challenge that undermines healthy working conditions, reframing of evidence-based regulations, policies, and organizational efforts is necessary. On one hand, the government may need to set specific legal guidelines and determine clear responsibility in cases of workplace sexual harassment by third parties while developing policies related to third-party harassment. On the other hand, businesses may reconsider slogans such as “the customer is king.” The relationship between businesses and customers should be built on mutual respect and shared responsibility to prevent any disrespectful behavior between parties. The efforts would also require organizations to take immediate and appropriate actions when workplace sexual harassment occurs to deter future incidents that may further exacerbate poor working conditions (Saguy, 2000).

On a final note, the widespread cases of workplace sexual harassment by third parties raise the question of whether institutional measures are sufficient to address this issue. The #MeToo movement in Korea has shed light on the country’s male-oriented culture. In our findings, workers who reported gender discrimination compared with those who did not showed a markedly higher risk for sexual harassment. Spurred by the #MeToo movement, Korean women are collectively demanding the elimination of sexual harassment by reshaping the country’s male-driven culture (J. Lee et al., 2018). If Korean society is serious about combating workplace sexual harassment in favor of safe and healthy working conditions, it may need a multi-faceted approach that encompasses both significant institutional improvements and cultural transformation.

Our study has several limitations. First, self-reported data may not reflect reality, as victims are typically hesitant to disclose their experiences. As a result, we may have not fully investigated the extent of workplace sexual harassment. In addition, the percentage of workplace sexual harassment found in our study differs from that given in the recent report by the Ministry of Gender Equity and Family, as our figures of sexual harassment are much smaller. This discrepancy points to the need for future studies to develop a standardized method for consistently and accurately evaluating workplace sexual harassment cases. Third, this study is in the context of South Korea, suggesting caution in interpreting the findings in other contexts. Nevertheless, the present study provides important implications for international communities where third parties can be a significant threat to healthy working conditions considering the nature of the relationship between employees and customers or clients. Also, it stresses the importance of an evidence-based policy for effectively and successfully combating workplace sexual harassment. Fourth, while we believe that our study reflects a significant part of the current situation of workplace sexual harassment in South Korea, additional studies need to focus on this issue to further improve the knowledge base. Finally, although our key explanatory variables may suggest the role of third parties in the prevalence of sexual harassment, our study did not directly examine the adjusted association between perpetrators and sexual harassment. Furthermore, the limitation of our cross-sectional study did not allow us to examine causal relationships between. Well-designed prospective studies will address this limitation.

Conclusion

In response to growing concerns over workplace sexual harassment by third parties in South Korea, our study uses nationally representative data to examine sexual harassment with an emphasis on risk factors that potentially represent the role of third parties in the prevalence of sexual harassment. Evidence suggests that third parties may be common perpetrators of sexual harassment, posing a serious threat to healthy working conditions. To combat workplace sexual harassment, combined efforts of reframing institutional measures and cultural transformation are necessary. This study represents an important step toward understanding workplace sexual harassment in South Korea and provides policy implications for healthy working conditions. Our findings also warrant further investigation on this topic to confirm our findings and advance the knowledge.

Footnotes

Acknowledgements

The authors would like to thank the Safety and Health Policy Research Department (Korean Occupational Safety and Health Research Institute [OSHRI]) for offering raw data of the KWCS (Korean Working Conditions Survey).

Authors’ Note

The contents of the paper are solely the responsibility of the authors and do not necessarily represent the official position of the OSHRI.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Jusung Lee

Author Biographies

Jusung Lee (PhD) is a research faculty member in the Department of Health Services Management and Policy at the East Tennessee State University. His research interest is in violence against vulnerable populations, such as women and older adults in work and public places. He has also engaged in research on reproductive health, mental health, and chronic conditions with an emphasis on individual behaviors and social or cultural contexts.

Mihyun Oh (MS) is a public official at South Korea’s Ministry of Employment and Labor (MOEL). Her primary work and research interests include policy implementation to remove gender disparities in workplaces and to improve gender inequality in employment. She holds a master’s degree in economics concentrating on econometrics. She employs quantitative data to analyze various labor issues and to disseminate findings for improving working conditions.

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