| Literature DB >> 35813366 |
Matthew Amengual1, Rita Mota2, Alexander Rustler1.
Abstract
Public pressure is essential for providing multinational enterprises (MNEs) with motivation to follow the standards of human rights conduct set in soft-law instruments, such as the United Nations Guiding Principles on Business and Human Rights. But how does the public judge MNE involvement in human rights violations? We empirically answer this question drawing on an original survey of American adults. We asked respondents to judge over 12,000 randomly generated scenarios in which MNEs may be considered to have been involved in human rights violations. Our findings reveal substantial gaps between public judgments and the standards set in soft law and the normative literature. We identify the attributes of episodes of human rights violations involving MNEs that influence public judgments, including the relationship between the MNE and the perpetrator, the practice of due diligence, and the type of abuse. These results provide insights as to when we might expect public pressure to drive MNE compliance with soft-law instruments, and they direct attention to specific standards that will likely require stronger, 'hard' law approaches or broader efforts to shift the public's view.Entities:
Keywords: Business and human rights; Multinational enterprises; Public opinion
Year: 2022 PMID: 35813366 PMCID: PMC9252567 DOI: 10.1007/s10551-022-05147-5
Source DB: PubMed Journal: J Bus Ethics ISSN: 0167-4544
Sample characteristics
| Sample ( | U.S. population over 18a (%) | |
|---|---|---|
| Age | ||
| 18–24 | 11.5 | 11.4 |
| 25–34 | 15.7 | 17.8 |
| 35–44 | 17.6 | 16.4 |
| 45–54 | 14.9 | 15.8 |
| 55–64 years | 17.6 | 16.8 |
| 65 years and over | 22.7 | 21.7 |
| Education | ||
| No high school diploma | 6.8 | 10.9 |
| High school or equivalent | 30.3 | 28.6 |
| Some college, less than 4-year degree | 29.6 | 28.2 |
| Bachelor's degree or higher | 33.3 | 32.3 |
| Race and ethnicityb | ||
| White alone | 65.8 | 62.9 |
| Black or African American alone | 12.4 | 12.0 |
| Hispanic | 13.0 | 16.6 |
| American Indian and Alaska Native alone | 0.8 | 0.8 |
| Asian alone | 6.2 | 6.0 |
| Native Hawaiian and other Pacific islander alone | 0.3 | 0.3 |
| Two or more races | 1.5 | 1.4 |
| Gender | ||
| Male | 46.9 | 48.4 |
| Female | 52.9 | 51.6 |
| Another gender identity | 0.3 | – |
aEducation, race, and gender from the 2018 current population survey. Age from the 2020 current population survey. We do not weight our sample
bThere was one non-response for the race and ethnicity question. Therefore, the N for this question is 2419
Structure of the vignettes
| Attribute | Wording |
|---|---|
| Large | [Company X] is a large company with a lot of influence in the foreign country |
| Small | [Company X] is a small company that is just starting out in the foreign country |
| Oil | Oil |
| Clothing | Clothing |
| Automobile | Auto manufacturing |
| Solar energy | Solar energy |
| Bicycle | Bicycle manufacturing |
| Subsidiary | [Company X] owns and controls a subsidiary business |
| Supplier | [Company X] buys inputs from a supplier in this foreign country |
| Beneficial complicity | [Company X] benefitted when this country’s government |
| Silent complicity | [Company X] did not speak out publicly to condemn this country's government |
| Employ child labor | Employ children |
| Pay less than living wage | Pay workers less than a living wage |
| Contaminate land | Contaminate a community’s land |
| Destroy sacred site | Destroy a sacred site |
| Violently repress protest | Violently repress protests |
| Discriminate against minorities | Discriminate against an ethnic minority |
| Should not | People in this country think that [the government/businesses] should not be able to [abuse] |
| Can sometimes | People in this country think that [the government/businesses] should sometimes be able to [abuse] |
| No due diligence | [Company X] did not try to find out whether [its subsidiary/its supplier/the government] might [abuse] |
| No action | [Company X] knew that [its subsidiary/its supplier/the government] might [abuse] but did nothing to prevent it |
| Tried to prevent | [Company X] knew that its subsidiary/its supplier/the government] might [abuse] and tried to prevent it |
Fig. 1Example vignette
Main results
| Supplier | − 0.0753*** |
| (0.0120) | |
| Beneficial complicity | − 0.102*** |
| (0.0122) | |
| Silent complicity | − 0.191*** |
| (0.0129) | |
| No action | 0.0660*** |
| (0.0106) | |
| Tried to prevent | − 0.147*** |
| (0.0116) | |
| Pay less than living wage | − 0.0521*** |
| (0.0151) | |
| Contaminate land | − 0.0711*** |
| (0.0156) | |
| Destroy sacred site | − 0.163*** |
| (0.0160) | |
| Violently repress protest | − 0.130*** |
| (0.0154) | |
| Discriminate against minorities | − 0.0545*** |
| (0.0148) | |
| Can sometimes | − 0.0343*** |
| (0.00895) | |
| Small | − 0.0338*** |
| (0.00854) | |
| Clothing | − 0.0182 |
| (0.0137) | |
| Auto | − 0.00962 |
| (0.0139) | |
| Solar | − 0.00889 |
| (0.0139) | |
| Bicycle | − 0.00630 |
| (0.0138) | |
| Constant | 0.829*** |
| (0.0177) | |
| Observations | 12,100 |
| 0.066 |
Robust standard errors clustered by respondent in parentheses
*p < 0.05, **p < 0.01, ***p < 0.001
Fig. 2Type of involvement
Fig. 3Focal firm characteristics
Fig. 4Abuses
Fig. 5Political action
Political action
| Would never (= 1) (%) | Might | Have in the distant past | Have in the last year | |
|---|---|---|---|---|
| Signed a petition related to a business | 30 | 47 | 12 | 11 |
| Participated in a protest or demonstration about a business’ actions | 48 | 42 | 6 | 4 |
| Boycotted certain products for political, ethical, or environmental reasons | 32 | 30 | 16 | 22 |
| Deliberately bought certain products for political, ethical, or environmental reasons | 34 | 32 | 13 | 21 |
| Signed a petition related to a government policy | 23 | 37 | 18 | 22 |
| Participated in a protest or demonstration about a government policy | 49 | 36 | 9 | 6 |
| Donated money or raised funds for a political activity | 44 | 27 | 13 | 16 |
| Contacted or attempted to contact a politician or civil servant to express your views | 33 | 35 | 14 | 18 |
Justifications related to type of involvement
| Code | Examples | % | Responses with code | Responses without code | |
|---|---|---|---|---|---|
| Responsive | “This company tried to do the ethical thing and protect the community and the environment by attempting to block the government from doing damage. No violations were committed” | 38.7 | 0.64 | 0.61 | 0.47 |
| Association | “It benefitted from discrimination which means they took part in said discrimination. Ergo they violated human rights” | 7.7 | 0.69 | 0.62 | 0.24 |
| Causal | “They did not directly employ the kids…” | 10.1 | 0.51 | 0.64 | 0.03 |
| Appropriate | “It is not that company’s job to take political action when they themselves are not violating anybody’s rights. A small clothing company is not responsible for the government’s actions” | 3.3 | 0.00 | 0.64 | < 0.01 |
Percentage of codable responses. N = 848. Responses could have multiple codes. p-value from a test of the difference in means of the DV between responses with the code, and those without
Comparisons of all industries and abuses
| Null hypothesis | ||
|---|---|---|
| 1.52 | 0.2184 | |
| 46.96 | < 0.001 | |
| 23.66 | < 0.001 | |
| 0.03 | 0.87 | |
| 33.7 | < 0.001 | |
| 13.6 | < 0.001 | |
| 1.17 | 0.28 | |
| 3.84 | 0.05 | |
| 46 | < 0.001 | |
| 24 | < 0.001 | |
| 0.38 | 0.54 | |
| 0.45 | 0.50 | |
| 0.73 | 0.39 | |
| 0.00 | 0.96 | |
| 0.06 | 0.81 | |
| 0.03 | 0.85 |
F(1, 2419). Not all hypotheses were prespecified (see analysis plan). We report all for completeness
Justifications related to abuses
| Code | Example | % | Mean DV with code | Mean DV without code | |
|---|---|---|---|---|---|
| Categorical fit | “Destroying a sacred site does not involve human rights” | 19.1 | 0.62 | 0.63 | 0.91 |
| Legal reference | “Using kids as employees is illegal” | 6.4 | 0.72 | 0.62 | 0.13 |
| Deontological | “Discrimination is wrong, and should not be tolerated” | 14.5 | 0.85 | 0.59 | < 0.01 |
| Consequential | “They are endangering the lives of people by letting contaminants go into areas that sustain life and are willing to let the contaminants damage the ecosystem” | 3.9 | 0.87 | 0.61 | < 0.01 |
| ‘American’ values | “Company A may not be in violation in that country but as an American company it is” | 1.2 | 1.00 | 0.62 | < 0.01 |
| Local norms | “If the people are aware of this practice and appear to accept it then the oil company was acting on the approval of the country's government. No violations took place” | 5.2 | 0.39 | 0.64 | < 0.01 |
Percentage of codable responses. N = 848. Responses could have multiple codes. p-value from a test of the difference in means of the DV between responses with the code, and those without
Codes by abuse
| All vignettes (%) | Child labor (%) | Living wage (%) | Contamination (%) | Sacred site destruction (%) | Protest (%) | Discrimination (%) | |
|---|---|---|---|---|---|---|---|
| Responsive | 38.7 | 34.0 | 35.4 | 45.3 | 36.3 | 40.0 | 42.0 |
| Association | 7.7 | 9.5 | 5.5 | 5.4 | 6.7 | 9.6 | 10.1 |
| Causal | 10.1 | 6.8 | 5.5 | 12.2 | 12.6 | 16.3 | 8.4 |
| Appropriate | 3.3 | 1.4 | 3.1 | 2.7 | 3.0 | 5.9 | 4.2 |
| Categorical | 19.1 | 17.7 | 21.3 | 14.2 | 22.2 | 16.3 | 23.5 |
| Legal | 6.4 | 13.6 | 11.0 | 2.7 | 4.4 | 3.0 | 1.7 |
| Deontological | 14.5 | 20.4 | 20.1 | 8.1 | 15.6 | 10.4 | 10.9 |
| Consequential | 3.9 | 4.1 | 3.1 | 11.5 | 0.7 | 3.0 | 0.0 |
| American values | 1.2 | 0.7 | 1.2 | 0.7 | 1.5 | 3.0 | 0.0 |
| Local norms | 5.2 | 10.9 | 4.9 | 6.1 | 5.2 | 2.2 | 0.8 |
| Other | 5.5 | 4.8 | 4.9 | 3.4 | 5.9 | 6.7 | 8.4 |
| Number of codable responses | 848 | 147 | 164 | 148 | 135 | 135 | 119 |
Percentage of codable responses by the abuse included in the vignette. Overall, 152 of 1000 responses were not codable