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The purpose of this paper is to empirically examine the link between trade liberalization and employment through the export channel under Korea’s FTAs by distinguish firm heterogeneity (i.e. size) as well as sector-level international competitiveness (i.e. comparative advantage).

Using the firm-level data during 2000–2009, the authors drive the difference-in-difference-in-difference model on Wagner (2007) with the dependent variables of labor productivity and employments and the independent variables of free trade agreement, revealed comparative advantage, firm size and payroll costs.

The authors find that the economic benefit of FTAs in Korea is not concentrated in large enterprises or firms with comparative advantage. Accordingly, the authors conclude that FTA or trade liberalization brings positive effects to business as a whole, rather than to specific industries or group of firms.

The Korean Government has continued its policy of supporting small and medium-sized enterprises (SMEs) for a long time by recognizing them as socially underprivileged. According to the results of this study, an increase in export through FTAs improves firm’s labor productivity and increases employment, especially for SMEs, which can be a practical and efficient support for them.

The paper provides the empirical evidences that how the effects of trade liberalization on labor depend on firm heterogeneity, industrial competitiveness and/or both and thus how labor is reallocated in response to trade liberalization in Korea.

In this chapter, we examine the multifaceted challenges that feminist labor organizations face in decommodifying the lives and labor of poor and working-class women. Using an in-depth case study of domestic worker organizing in South Korea, we find that non-governmental organizations (NGOs) such as the National House Managers Cooperative and the Korean Women Workers Association became entangled in hegemonic state projects that linked support for women’s basic livelihoods to the proliferation of part-time, informal domestic work in the context of widespread crises. To challenge the discriminatory and market-driven logics of state-driven social protection efforts, these NGOs have advanced an emancipatory agenda to improve the working conditions, labor rights, and social dignity of domestic workers through consciousness-raising grassroots organizing methods and contentious policy advocacy campaigns. Their social movement transformation goals, however, have been constrained by the relative organizational isolation and limited organizational capacity of feminist labor NGOs in a broader context of neoliberal precaritization and gender-stratified labor markets. The myriad dilemmas facing domestic worker organizing in an era of global hegemonic market rule highlight the need to develop new political imaginaries to contest gender and economic injustice.

Shows how the US economy has witnessed both a massive influx of immigrant workers and a sharp decline in organized labour. Examines the struggles of Latino workers in Los Angeles, USA and shows just how immigrant workers and labour unions have a complicated relationship there. Explains how the problems were eventually eased.

This study aims to investigate the role of regional environmental transparency on corporate environmental disclosure.

This study uses the introduction of a nationwide automated air pollution monitoring network in China as a quasi-natural experiment and employs regression analysis. Robustness checks, including parallel trend test and placebo test, are performed to test the robustness of the results.

Sharing air pollution data with the public can improve corporate environmental disclosure. Firms with poorer environmental, social and governance (ESG) performance prefer to disclose less informative information after the automated network is implemented compared with firms with better ESG performance. The relationship between information sharing and corporate environmental transparency is more pronounced when local air pollution is severer, firms face stronger investor scrutiny and firms are from heavily polluting industries. The mechanism tests suggest the automated system can draw public environmental attention and improve governments’ aspiration for environmental governance. Finally, corporate environmental disclosure can reduce stock price crash risk and cost of equity.

Real-time pollution data reporting is an important solution to raising public environmental awareness and then enhancing the effectiveness of pollution control.

This study has implications for policy-making regarding environmental governance and environmental disclosure.

This study confirms that pollution information transparency can motivate firms to increase environmental disclosure.

Online reviews are regarded as a source of information for decision-making because of the abundance and ready availability of information. Whereas, the sheer volume of online reviews makes it hard for consumers, especially the older adults who perceive more difficulties in reading reviews and obtaining information compared to younger adults, to locate the useful ones. The main objective of this study is to propose an effective method to locate valuable reviews of mobile phones for older adults. Besides, the authors also want to explore what characteristics of the technology older adults prefer. This will benefit both e-retailers and e-commerce platforms.

After collecting online reviews related to mobile phones designed for older adults from a popular Chinese e-commerce platform (JD Mall), topic modeling, term frequency-inverse document frequency (TF-IDF), and linguistic inquiry and word count (LIWC) methods were applied to extract latent topics and uncover potential dimensions that consumers frequently referred to in their reviews. According to consumers' attitudes towards different popular topics, seven machine learning models were employed to predict the usefulness and popularity of online reviews due to their excellent performance in prediction. To improve the performance, a weighted model based on the two best-performing models was built and evaluated.

Based on the TF-IDF, topic modeling, and LIWC methods, the authors find that older adults are more interested in the exterior, sound, and communication functions of mobile phones. Besides, the weighted model (Random Forest: Decision Tree = 2:1) is the best model for predicting the online review popularity, while random forest performs best in predicting the perceived usefulness of online reviews.

This study’s findings can help e-commerce platforms and merchants identify the needs of the targeted consumers, predict reviews that will get more attention, and provide some early responses to some questions.

The results propose that older adults pay more attention to the mobile phones' exterior, sound, and communication function, guiding future research. Besides, this paper also enriches the current studies related to making predictions based on the information contained in the online reviews.