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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.

Multinational enterprises (MNEs) own and control technological resources and capabilities that make them critical actors in accelerating the transition toward net zero. Even beyond the energy sector, stakeholders are putting increasing pressure on MNEs to reduce the carbon intensity of their operations, that is, to improve their carbon performance. While there is unambiguous evidence that national climate policy is a critical catalyst for long-term carbon performance improvements, there is limited research on how MNEs’ carbon strategies react to climate policies. This chapter reviews the concepts, drivers, and strategies connected to carbon performance in the broader sustainability and management literature to clarify potential complementarities to international business (IB). The authors then highlight how MNEs will face increasing institutional complexity along two dimensions: (1) the structural diversity of institutional environments and (2) institutional dynamism, primarily reflected by public policy. The proposed conceptual framework maps these two dimensions to national and subnational levels, and the authors present two data sources that allow the quantitative analysis of country differences in the diversity and dynamism of national climate policy. The authors conclude that there are ample opportunities for IB researchers to explore MNEs’ strategic reactions to climate policy and to inform policymakers about the consequences of national climate policy in the global economy.

This chapter is one of five chapters dedicated to anti-racism, specifically focusing on its conceptual foundations. Drawing from critical scholarship on ideas that have inspired political debates and policies about racism, I address key questions pertaining to anti-racism as an idea, policy framework and as a catalyst for sociopolitical action. This chapter engages with the fundamental principles that underpin anti-racism endeavours, ranging from community engagement to political activism and civil rights movements. It critically examines the ongoing debates on whether the goals of anti-racism, such as racial justice and dismantling of institutional racism/privilege, align with existing sociopolitical order. In addition, this chapter contributes to anti-racism scholarship that has evolved over the past five decades, by synthesising how anti-racism relates to various societal goals. Furthermore, this discussion incorporates themes such as the promotion of tolerance, equality, social justice and recognition within the context of anti-racism.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

Corporate site visits increase labor investment efficiency.

Our empirical model for the baseline analysis follows those of Jung et al. (2014) and Ghaly et al. (2020).

We show that corporate site visits are associated with significantly higher labor investment efficiency; more specifically, site visits reduce both over-hiring and under-hiring of employees. The effect of site visits on labor investment efficiency is more pronounced for firms with higher labor adjustment costs, greater financial constraints, weaker corporate governance and lower financial reporting quality. We also find that site visits mitigate labor cost stickiness.

First, while the literature has suggested how the presence of institutional investors and analysts may affect labor investment decisions, we focus on institutional investors and analysts’ activities and interactions with firm executives. We provide direct evidence that institutional investors and analysts may use corporate site visits to improve labor investment efficiency. Second, our study adds to a line of recent studies on how corporate site visits reduce information asymmetry and agency conflicts. We show that corporate site visits allow institutional investors and analysts to influence labor investment efficiency. We also provide new evidence that corporate site visits reduce labor cost stickiness.

This study aims to determine the effect of bank ownership on the credit risk of Indonesian Islamic local banks (ILBs).

This study uses the system generalized method of moments (GMM) estimation technique with a sample of 155 Islamic local banks in Indonesia from 2012 to 2019.

The results show that commissioner board (D.COW) ownership has a negative effect on credit risk. This indicates that an increase in the number of shares of Islamic local banks owned by the commissioner board reduces credit risk. On the other hand, government ownership (D.GOW), the Sharia supervisory board (D.SOW) and the director board (D.DOW) do not affect credit risk.

The government, Sharia supervisory board and director board need opportunities to easily own more Islamic local bank shares. Therefore, the provisions regarding the share ownership rights of the government, Sharia supervisory board and director board need to be improved to increase their role in reducing credit risk.

Previous researchers have not studied the effect of government ownership, the commissioner board, the Sharia supervisory board and the ownership of directors on credit risk at the ILB in Indonesia.

This study investigates how firms’ awareness of sustainability affects the revision of their internationalization strategy. Adopting a resource-based view (RBV) approach, the authors argue that sustainable-oriented firms have a higher propensity to de-internationalize (i.e., to go back to their home country) when confronted with the need to relocate foreign manufacturing subsidiaries, as the shortening of value chains would allow the reduction of transportation emissions and enhanced corporate image as green-oriented entities. Furthermore, the authors explore the role exerted by a stringent regulatory setting in the home country on the likelihood of de-internationalization. The empirical test conducted on a sample of relocations performed across European nations in 2002–2014 reveals that multinational enterprises (MNEs) – regardless of their sustainability orientation – have a higher probability to de-internationalize when their home countries have strict institutional contexts in place.

This study examines the non-linear impact of financial development on income inequality and analyses the mediators through which financial development affects income inequality.

The study uses a dynamic panel threshold method with an endogeneous threshold variable on a comprehensive sample of 85 countries over the period of 1996-2015.

The author finds that financial development activities increase income inequality in developed countries. However, financial development promotes income equality in developing countries. Further, the study finds that education and institutional quality are the channels through which financial development has non-linear impacts on income inequality.

The study explores relatively new method to examine the nonlinear impact of financial development and also considers new dataset for the main explanatory variable.

The current chapter proposes a theoretical framework to assess the sustainability of economic growth in the Gulf Cooperation Council (GCC) States. The authors integrate insights from endogenous growth models and consider the unique socioeconomic characteristics of the GCC region to provide a comprehensive and tailored approach to understanding the determinants of economic growth and formulating effective policy measures to foster sustainable development and growth. This chapter highlights the environmental challenges faced by GCC; based on this, the authors suggested indicators to construct a theoretical framework (Economic Growth, Climatic Indicators, Energy Indicators, Social Indicators, and Economic Resources Indicators). The authors propose that policymakers and researchers in GCC States should take these factors into account when devising policies or conducting research aimed at fostering sustainable economic growth. Overall, this chapter presents significant insights for policymakers, researchers, and stakeholders involved in promoting the sustainable economic advancement of the GCC States.