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This study examines the impact of China’s mixed-ownership reform on the innovation of non-state-owned acquirers, with a particular focus on the impact on firms with high financing constraints, low-quality accounting information or less tangible assets.

We use a proprietary dataset of firms listed on the Shanghai and Shenzhen Stock Exchanges to investigate the impact of mixed ownership reform on non-state-owned enterprise (non-SOE) innovation. We employ regression analysis to examine the association between mixed ownership reform and firm innovation.

The study finds that non-state-owned firms can improve innovation by acquiring equity in state-owned enterprises (SOEs) under the reform. Eased financing constraints, lowered financing costs, better access to tax incentives or government subsidies, lowered agency costs, better accounting information quality and more credit loans are underlying the impact. Additionally, cross-ownership connections amongst non-SOE executives and government intervention strengthen the impact, whilst regional marketisation weakens it.

This study adds to the literature on the association between mixed ownership reform and firm innovation by focussing on the conditions under which this impact is stronger. It also sheds light on the policy implications for SOE reforms in emerging economies.

The study examines the impact of a recent mandate (Section 149 of the Indian Companies Act, 2013, where firms of a certain size are mandated to appoint at least one woman director on the board) on the earnings quality of firms. The study also examines the role of financial expertise and the presence of a woman director in the audit committee on the association between mandate and earnings quality.

Taking leverage of a quasi-natural experiment in India, the authors employ the ‘Difference-in-Difference’ (DiD) technique. DiD enables the author to filter out the impact of concurrent exogenous shocks while examining the issue. The propensity score matching and entropy balancing techniques have been employed to overcome the problem of endogeneity and self-selection bias.

Based on the sample of 538 Bombay Stock Exchange (BSE) listed firms, the author finds that magnitude of discretionary accruals has decreased among test firms (firms mandated to comply with Section 149) relative to benchmark marks (firms not mandated to comply with Section 149) during the post-legislation period, indicating the improved earning quality after the mandate. This finding is consistent with the notion of social role theory that women are less likely to be engaged in risky activities such as earnings management. Further, the author find that the financial expertise of the woman and presence of the woman on the audit committee strengthen the positive impact of the mandate on earnings quality. These results are robust to alternative measurements of discretionary accruals.

The study is among the pioneering attempts to make use of a quasi-natural experiment and investigate the impact of a woman director on earnings quality. The study is also one of the few studies to focus on a developing country like India having a culture dominated by men.

Racism occurs in many ways and varies across countries, evolving and adapting to sociocultural history, as well as contemporary economic, political and technological changes. This chapter discusses the multilevel dimensions of racism and its diverse manifestations across multiracial societies. It examines how different aspects of racism are mediated interpersonally, and embedded in institutions, social structures and processes, that produce and sustain racial inequities in power, resources and lived experiences. Furthermore, this chapter explores the direct and indirect ways racism is expressed in online and offline platforms and details its impacts on various groups based on their intersecting social and cultural identities. Targets of racism are those who primarily bear the adverse effects. However, racism also affects its perpetrators in many ways, including by limiting their social relations and attachments, and by imposing social and economic costs. This chapter thus analyses the many aspects of racism both from targets and perpetrators' perspectives.

This study aims to investigate whether the presence of women in the boardroom influences companies’ environmental, social and governance (ESG) performance. Furthermore, it examines whether the COVID-19 pandemic and family control affect the relationship.

This study uses nonfinancial firms listed on the Indonesia and Malaysia Stock Exchange during 2018-2021. Thomson Reuters’ database is used to collect the ESG scores. Using 312 firm-year observations, the authors apply multiple regressions and sensitivity testing to ensure the robustness of the results.

This study provides empirical evidence that the presence of women in the boardroom improves companies’ ESG and family control weakens the relationship. Meanwhile, there is no support on the moderating effect of the COVID-19 pandemic. The authors also conducted additional tests using ESG pillars (i.e. environment, social and governance pillars) as the dependent variable. The findings are robust to alternative samplings.

This research is limited to Indonesia and Malaysia, thus affecting the generalizability of the results to all developing countries. The sample size is relatively small due to data limitations related to the availability of ESG scores.

The findings of this study provide a basis for the government to establish mandatory regulations regarding sustainability performance. The positive relationship between women on boards and better ESG performance suggests that encouraging gender diversity in corporate leadership can improve sustainability practices. The government may consider implementing gender quota regulations to increase women's representation on corporate boards.

Shareholders can pursue investment portfolios in socially responsible companies, prioritizing ESG performance. In addition, investors should consider the presence of women in the company’s boardroom and whether family control exists when making investment decisions.

Overall, the originality and significance of this research lie in its comprehensive examination of the moderating factors, the inclusion of different governance systems in the sample, and the exploration of psychological aspects, contributing to a deeper and more nuanced understanding of the relationship between women on boards and ESG performance in the context of developing countries.

Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a trade-off between financial and environmental aspects of these decisions, this paper aims to determine an optimal location, among candidate locations, of a new logistics center, its capacity, as well as optimal network flows for an existing distribution network, while concurrently minimizing the total logistics cost and gas emission. In addition, uncertainty in transportation and warehousing costs are considered.

The problem is formulated as a fuzzy multiobjective mathematical model. The effectiveness of this model is demonstrated using an industrial case study. The problem instance is a four-echelon distribution network with 22 products and a planning horizon of 20 periods. The model is solved by using the min–max and augmented ε-constraint methods with CPLEX as the solver. In addition to illustrating model’s applicability, the effect of choosing a new warehouse in the model is investigated through a scenario analysis.

For the applicability of the model, the results indicate that the augmented ε-constraint approach provides a set of Pareto solutions, which represents the ideal trade-off between the total logistics cost and gas emission. Through a case study problem instance, the augmented ε-constraint approach is recommended for similar network design problems. From a scenario analysis, when the operational cost of the new warehouse is within a specific fraction of the warehousing cost of third-party warehouses, the solution with the new warehouse outperforms that without the new warehouse with respective to financial and environmental objectives.

The proposed model is an effective decision support tool for management, who would like to assess the impact of network planning decisions on the performance of their supply chains with respect to both financial and environmental aspects under uncertainty.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

The authors examine whether or not applicants and recipients of federal disability insurance (DI) inflate their self-assessed health (SAH) problems relative to others. To do this, the authors employ a technique which uses anchoring vignettes. This approach allows them to examine how various cohorts of the population interpret survey questions associated with subjective self-assessments of health. The results of the analysis suggest that DI participants do inflate the severity of a given health problem, but by a small but significant degree. This tendency to exaggerate the severity of disability problems is much more apparent among those with more education (especially those with a college degree). In contrast, racial minorities tend to underestimate severity ratings for a given disability vignette when compared to their white peers.