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This chapter examines the concepts of race and racism, critically reviewing their historical and contemporary applications in everyday life as well as in academic and policy debates. Racism has been extensively researched, with various theories and conceptualisations developed across social science. However, there is a great deal of disagreement regarding its nature, contemporary significance and empirical validation. This chapter examines these and attempts to synthesise some of the common definitions of racism provided in the literature. It explores related concepts and underlying themes pertaining to expressions of race and racism. Furthermore, it unpacks current knowledge about racial issues and discusses recent advances in the conceptual understanding of various forms of racism. It also elucidates the social, political and analytical applications of racism as a concept and the significance of racism in contemporary societies. The chapter concludes by highlighting how racism is a dynamic phenomenon, continuously evolving with the social, political and technological transformations in contemporary societies.

In this fast-changing world, digitization has become crucial to organizations, allowing decision-makers to alter corporate processes. Companies with a higher corporate social responsibility (CSR) level not only help encourage employees to focus on their goals, but they also show that they take their social responsibility seriously, which is increasingly important in today’s digital economy. So, this study aims to examine the relationship between digital transformation and CSR disclosure of Chinese A-share companies. Furthermore, this research investigates the moderating impact of governance heterogeneity, including CEO power and corporate internal control (INT) mechanisms.

This study used fixed effect estimation with robust standard errors to examine the relationship between digital transformation and CSR disclosure and the moderating effect of governance heterogeneity among Chinese A-share companies from 2010 to 2020. The whole sample consists of 17,266 firms, including 5,038 state-owned enterprise (SOE) company records and 12,228 non-SOE records. The whole sample data is collected from the China Stock Market and Accounting Research, the Chinese Research Data Services and the WIND databases.

The regression results lead us to three conclusions after classifying the sample into non-SOE and SOE groups. First, Chinese A-share businesses with greater levels of digitalization have lower CSR disclosures. Both SOE and non-SOE are consistent with these findings. Second, increasing CEO authority creates a more centralized company decision-making structure (Breuer et al., 2022; Freire, 2019), which improves the negative association between digitalization and CSR disclosure. These conclusions, however, also apply to non-SOE. Finally, INT reinforces the association between corporate digitization and CSR disclosure, which is especially obvious in SOEs. These findings are robust to alternative HEXUN CSR disclosure index. Heterogeneity analysis shows that the negative relationship between corporate digitalization and CSR disclosures is more pronounced in bigger, highly levered and highly financialized firms.

Digitalization and CSR disclosure are well studied, but few have examined their interactions from a governance heterogeneity perspective in China. Practitioners and policymakers may use these insights to help business owners implement suitable digital policies for firm development from diverse business perspectives.

There has been a paradigm shift within research exploring autistic experience in recent decades towards greater participation, agency and voice for autistic researchers and the autistic community more generally (Fletcher-Watson et al., 2019). This approach has shown a greater focus on research oriented towards the priorities or preferences of the autistic community (Fletcher-Watson & Happé, 2019; Pellicano et al., 2014), curtails concerns regarding epistemic injustice and has influenced understandings of autistic ontology and neurology. Co-produced research, characterised by the inclusion of diverse stakeholders, builds trust between participants. Nonetheless, co-production in research requires careful planning and support (Stark et al., 2021), sometimes proving ‘turbulent’ and ‘challenging’ (Worsley et al., 2021). This chapter explores the experiences and reflections of a team of autistic and non-autistic researchers conducting co-produced research amid the global COVID-19 pandemic. With research practices and systems altered due to increased remote work, online communication and limited in-person interaction, this topic is especially pertinent. With the increasing emphasis on involving members of the autistic community in research at all levels of development, the impact of the pandemic on how participatory research is carried out may be complex. This chapter has implications for planning and conducting co-produced research in our new reality, considering both the opportunities and obstacles it presents.

This paper investigates the intricate process of integrating historically excluded social groups into long-established routines. Drawing on a dialectical perspective, the research explores how persistence and change emerge through the interplay of opposing forces, shedding light on the dynamics of integrating new participants while ensuring stability in established routines. The empirical focus is on an Armed Forces’ ground combat training (GCT) course, examining the integration of the first female officers after the formal ban on their participation in close-combat roles was lifted. The findings reveal a nuanced evolution of routine adaptation and truce reformation, characterized by three dialectical cycles: tentative truces, experimental truces, and enactment truces. These cycles involve negotiations between continuity and reformation, accommodation and resistance, and modification and preservation, uncovering a dialectical dance where organizational actors invest intense effort in maintaining the status quo while accommodating ambiguity and settling tensions. The findings extend our understanding of routine dynamics by illuminating the performative aspect of truce-making, highlighting the effortful processes involved in accommodating new participants. This paper establishes a connection between routines and dialectics, providing novel avenues for exploring complex organizational challenges and emphasizing micro-strategies employed by routine participants to address differences in practice. It also contributes to the field of organizational inclusion by offering a dialectical understanding of integration, showcasing the intricate dynamics involved in integrating historically excluded groups into established routines.

This paper aims to answer the following important questions: Is public debt in Sub-Saharan African (SSA) countries sustainable? What are the determinants of public debt sustainability in these countries, and do these determinants exhibit heterogeneity due to regional, natural resource, and income differences among SSA countries?

This study analyzes the public debt sustainability in SSA countries using the theoretical model known as the Present Value Budget Constraint (PVBC) model developed by Hamilton and Flavin (1986), and adopts the econometric testing method proposed by Trehan and Walsh (1991). Moreover, to empirically investigate the determinants of public debt sustainability in SSA countries, the System-Generalized Method of Moments (System-GMM) method is applied. Furthermore, this study conducts heterogeneity analysis by categorizing the sample based on different regions, natural resource endowments, and income levels. The data of this study are sourced from the IMF and World Bank databases for 45 SSA countries from 2005 to 2021.

Findings reveal that public debt in SSA countries is not sustainable in the long run, with factors such as the previous government debt, long-term debt ratio, debt repayment capacity, economic growth rate, inflation rate, export to GDP, and government fiscal deficit rate influencing sustainability. Additionally, the factors exhibit heterogeneity attributed to regional, natural resource, and income variations among SSA countries.

The findings of our study will serve as a catalyst for policymakers in the SSA countries to embrace and sustain robust fiscal consolidation and debt stabilization measures. Moreover, countries with distinct characteristics should implement tailored approaches. Additionally, policymakers in SSA countries should implement economic measures to address public debt issues. These measures include improving the macroeconomic structure, promoting economic transformation and diversification of industries, fostering sustainable economic growth, ensuring price stability, and strengthening resilience against external shocks and debt risks. Specifically, countries endowed with indigenous species, resources, and tourism potential should adopt a well-coordinated strategy that utilizes agriculture, tourism, ecotourism, and the hospitality industry as instruments for sustainable local community and rural development.

Firstly, it assesses the sustainability of public debt and its determinants for countries in SSA, which distinguishes it from previous studies that only focus on either debt sustainability or determinants of debt separately. Secondly, by including multiple SSA countries in the analysis, this study stands out from prior research that predominantly concentrates on specific nations. Thirdly, the utilization of the System-GMM method for analyzing determinants adds a novel dimension to this study, departing from earlier literature primarily focused on debt thresholds. Lastly, the heterogeneity analysis conducted in this study provides an empirical foundation for tailoring policies to different countries, addressing a facet often overlooked in earlier literature.

The objective of this study is to analyse the integration of technology in Human Resources Management (HRM) with a special focus on Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT) and Big Data.

This study aims to contribute to the understanding of these trends by conducting a thorough bibliometric analysis using the Scopus database, encompassing research on HRM and Technology from 1991 to 2022. By employing citation analysis, co-citation analysis and co-word analysis, the study uncovers key patterns and trends in the field.

The findings indicate that AI, Big Data and ML are the focal points of research when exploring the intersection of Technology and HRM. These technologies offer promising prospects for enhancing Human Resource processes, such as Talent Acquisition, Performance Management and Employee Engagement.

In our study, we showcase the practical implications that offer guidance for HR researchers and professionals, enabling them to make informed decisions regarding the adoption and implementation of Information Technology.

This research can provide valuable insights to HR managers on the use of cutting-edge technology in HRM. It aims to enhance the manager’s awareness of how technology-enabled HRM can improve HR performance.

This study adds to the existing body of knowledge on how Modern Technology empowers HRM. It also proposes a conceptual framework for the use of Modern Technology along with Strategic Management and Knowledge Management to improve Human Resource Performance.