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This chapter examines the patterns influencing the trajectory of fintech enterprises. With the looming challenge of climate change, the financial realm's responsibility in mitigating climate risks has surged into focus. This chapter investigates fintech enterprises' response to climate-related corporate social responsibility in six main domains: (1) climate risk assessment tools, (2) green bonds and sustainable investment tools, (3) ESG integration, (4) carbon trading and carbon credits, (5) sustainable banking, and (6) DeFi and climate initiatives. It also investigates how fintech firms recognize the impact of climate change within their official declarations and efforts to amplify consciousness about climate-related concerns. This chapter assesses climate-linked terminology and expressions using quantitative and qualitative approaches, illuminating these firms' dedication to assimilating climate risk within their operational blueprints.

Nuclear energy is a contested topic, requiring trade-offs in energy independence, ethicality and uncertainty. Anthropogenic climate change complicates these decisions further, with nuclear energy competing with other low-carbon and sustainable energy sources. Decisions about nuclear energy’s role, as part of a sustainable energy system, must be made in cooperation with all stakeholders. However, it is unclear how the public is involved in these decisions in the UK. This study aims to address this gap, exploring the degree to which public participation has occurred in the UK.

This paper conducted a scoping review of public participation in UK nuclear energy decision-making in the context of sustainable energy transitions, where the government retains and promotes nuclear energy as part of a sustainable energy system. Following a systematic literary search, this paper reviewed 28 academic and grey literature documents.

Public participation has primarily been conducted as consultations rather than active participation. There is limited evidence that consultations have meaningfully contributed to politically and socially responsible (i.e. individuals and groups working together for community benefit) decision-making, with public opinion on nuclear energy’s role being divided and is influenced by how it is framed.

Social aspects of nuclear energy development have historically received less attention than environmental and economic elements; the role of engagement and participation is relatively rare. Modern literature reviews in this context are largely absent, a gap this paper originally contribute to. This paper suggest ways in which how effective, inclusive engagement process could contribute to a fairer, responsible decision-making process and energy system in the UK.

This paper posits the need for English language arts (ELA) teachers to foster students’ use of languaging about their relations with ecosystems and peers, leading to their engaging in collective action to critique and transform status-quo systems impacting the climate crisis.

This paper reviews the current theory of languaging theory and research that focuses on the use of languaging to enact relations with ecosystems and others and voice emotions for transforming communities and reducing emissions contributing to climate change.

This review of languaging theory/research leads to identifying examples of teachers having students critique the use of languaging constituting status quo energy and community/transportation systems, respond to examples of characters using languaging in literary texts, using languaging in discussing or writing about the need to address climate change, critiquing languaging in media promoting consumption, using media to interact with audiences and using languaging through engaging in role-play activities.

This focus on languaging in ELA classrooms is a unique perspective application of languaging theory, leading students to engage in collective, communal action to address the climate crisis.

This study aims to assess the effects of natural disasters on food security in a sample of 40 sub-Saharan African countries. First, the authors assess the effects of natural disasters on the four dimensions of food security and second, the authors disaggregate natural disaster using the two dimensions that are most representative, namely, hydrological and biological disasters.

The regressions are based on the generalised method of moments on a data set covering the period 2005–2020. Natural disasters are measured by the total number of people affected and food security by its characteristics: access, availability, use and sustainability.

The results show that natural disasters increase the prevalence of undernourishment but reduce dependence on cereal imports. An increase in natural disasters by 1% increases the prevalence of undernourishment by the same proportion. As for import dependency, a 1% increase in natural disasters reduces dependency by 2.2%. The disaggregated effects show that hydrological disasters are more significant than biological disasters in impacting food security. Floods reduce the average energy supply adequacy but also dependence on cereal imports. Policy implications are discussed.

The study complements the extant literature by assessing the effects of natural disasters on food security in a region where food insecurity is one of the worst in the world.

In many storybooks in the Philippines, the presence of a sibling is a commonplace in writing the child protagonist's world. More specifically, the kuya, which is the Filipino term for older brother, is a male character that can influence the child protagonists. In this chapter, my goal is to analyse the positionalities of the kuya as male characters in four storybooks from the Philippines that feature the bond between a younger child and the older brother/s. These storybooks are Salo-Salo Para Kay Kuya (A Feast for Big Brother), Sandosenang Kuya (A Dozen Big Brothers), Ang Kuya Kong Zombie (My Big Brother Zombie) and Ang Misteryo ng Patong-Patong na Damit ni Hulyan (The Mystery Behind Hulyan's Layered Clothes).

Through this chapter, I aim to theorise the roles that male characters play vis-à-vis their relationships with their younger siblings. The male characters' narrative journeys, character developments and roles in the context of the story are analysed through what Michael White calls ‘subordinate storylines’, which is character information that cannot be accessed by mere conversation among children. Thus, in the chapter, I investigate the values; intensions; knowledge and skills; and social, relational and cultural genesis of the male characters vis-à-vis the narratives and their interplay with the child protagonists in the story.

This study aims to respond to the latest research calls to precisely revisit the nexus between corporate green innovation (CGI) and financial decisions through deeply investigating the mediating effect of corporate environmental performance measured by the effectiveness of emission reduction.

This study analyzes nonfinancial-listed firms on the Australian Securities Exchange from 2002 to 2019 using multiple regression analysis on a panel data set. Initially, different static panel data approaches were used. To account for the potential endogeneity issue and generate robust outcomes, the authors apply the one-step system generalized method of moment, two-stage least squares and lagged model approaches.

The results provide a clear indication that the practices of green innovation can favorably contribute to the level of environmental performance, which in turn affect the firm’s ability in opening the new financial doors and shape solid capital structure. In this context, the effective environmental performance fully mediates the nexus between CGI and capital structure of a firm. More importantly, the outcomes are robust and coherent across different estimation techniques.

The originality of this study lies in its utilization of mediation analysis to explore the relationship between CGI and a firm's financial structure. This approach distinguishes it from previous research by offering a thorough and nuanced understanding of how green innovation practices influence the financing decisions of a firm.

Drawing insights from institutional theory, this paper aims to examine whether and to what extent banks have reconfigured their management control systems (MCSs) in response to growing institutional pressures towards sustainability, understood as environmental, social and governance (ESG) issues.

The authors conducted an exploratory study at the three largest Italian banking groups to shed light on changes made in MCSs to account for ESG issues. The analysis is based on 12 semi-structured interviews with managers from the sustainability and controls areas, as well as from other relevant operational areas particularly concerned with the integration process of ESG issues. Additionally, secondary data sources were used. The Malmi and Brown (2008) MCS framework, consisting of a package of five types of formal and informal control mechanisms, was used to structure and analyse the empirical data.

The examined banks widely implemented numerous changes to their MCSs as a response to the heightened sustainability pressures from regulatory bodies and stakeholders. In particular, with the exception of action planning, the results show an extensive integration of ESG issues into the five control mechanisms of Malmi and Brown’s framework, namely, long-term planning, cybernetic, reward/compensation, administrative and cultural controls.

By identifying the approaches banks followed in reconfiguring traditional MCSs, this research sheds light on how adequate MCSs can promote banks’ “sustainable behaviours”. The results can, thus, contribute to defining best practices on how MCSs can be redesigned to support the integration of ESG issues into the banks’ way of doing business.

Overall, the findings support the theoretical assertion that institutional pressures influence the design of banks’ MCSs, and that both formal and informal controls are necessary to ensure a real engagement towards sustainability. More specifically, this study reveals that MCSs, by encompassing both formal and informal controls, are central to enabling banks to appropriately understand, plan and control the transition towards business models fully oriented to the integration of ESG issues. Thereby, this allows banks to effectively respond to the increased stakeholder demands around ESG concerns.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.