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This chapter describes the scenario technique used for the integrative methodological approach (IMA) of the German global change project GLOWA Elbe. It is outlined how regional scenarios are systematically derived to analyze water use conflicts and their resolution in the context of global change for the German Elbe river basin. Through the combination of frameworks of development and policy strategies a consistent set of developmental scenarios can be generated that makes it possible to examine the regional impact of policy strategies under conditions of different future global change development paths. The scenario analysis of the framework of development starts on the global level with qualitative IPCC storylines, translates them to the regional level, and quantifies their regional effects by means of modeling and statistical estimation methods. The policy strategies are derived in close cooperation with regional stakeholders.

This paper investigates, theoretically and empirically, differences between blacks and whites in the United States concerning the intergenerational transmission of occupational skills and the effects on sons’ earnings. The father–son skill correlation is measured by the correlation coefficient (or cosine of the angle) between the father’s skill vector and the son’s skill vector. The skill vector comprises an individual’s occupational characteristics from the Dictionary of Occupational Titles (DOT). According to data from the U.S. National Longitudinal Survey of Youth (NLSY79), white sons earn higher wages in occupations that require skills similar to those of their fathers, whereas black sons in such circumstances incur a wage loss. A large portion of the racial wage gap is explained by the father–son skill correlation. However, a significant unexplained racial wage gap remains at the lower tail of the wage distribution.

In this chapter, the integrative methodological approach (IMA) of the research project GLOWA Elbe is introduced, which represents a scientific methodology to support water management under uncertainty regarding future paths of global change. The approach paves the way for integration of research work of many disciplines, of different assessment methods, of various policy fields, and the involvement of relevant stakeholders and decision makers. IMA can be roughly described by four research elements (scenario derivation, indicator and criteria identification, model-based impact analysis, and final scenario assessment based on combined benefit–cost and multi-criteria analysis), which lay the basis for the IMA activities of the global change research sequence. Its practical application is demonstrated by a case study on the Spree and Schwarze Elster river basins. Specific results of Chapter 4 (on scenario derivation) and Chapter 11 (on integrating economic evaluation into water management simulation) in this volume are picked up in order to focus on the illustration of the integrated assessment results for this German case study.

This study investigates how organizations in Brazil address sustainability concerns through collaborative governance efforts with strategic stakeholders. Organizations from New Zealand were considered as benchmarks for comparison.

This study is based on a qualitative exploratory research, supported by semistructured interviews. Ten organizations are interviewed, five from each country. Thematic analysis is used to analyze the interview data. Central management practices adopted by organizations are presented, and the goals, benefits, and limitations associated with collaborative initiatives are investigated.

The findings reveal that organizations in Brazil and in New Zealand are employing similar management and sustainability practices. Companies in both countries observe that collaborative efforts with strategic stakeholders improve their ability to meet market demands and jointly develop innovative solutions toward sustainability goals while exchanging knowledge and enhancing their operational effectiveness. Organizations perceive a number of tangible and nontangible value creation outcomes from sustainability practices, such as brand and reputational gains, improved supply chain management, and risk management attainments. The results also present limitations, such as internal limitations of organizations concerning how their executives and general staff incorporate sustainability issues into their organizations’ strategic planning and operational decisions.

Market pressures toward greener and more responsible operations equally affected organizations in both countries, without differentiation in operation between an emerging country such as Brazil and a developed country such as New Zealand. Directions for future research are presented. These are based on how organizations measure sustainability outcomes of management practices and collaborative alliances, and how organizations map upcoming market demands and opportunities to deliver more value to society as the sustainable development debate continues to evolve.

As universities operate in a global environment, internationalisation is inevitable for higher education (HE), as it is driven externally by political, economic, and socio-cultural globalisation forces. Through decoding and deconstructing the English language proficiency of international students and the international student experience at universities in the UK, this chapter investigates how university academics should consider employing both scaffolding strategies and cultural intelligence in their teaching and learning to enhance the international student experience and bridge the gap in educational attainment between home and international students. This calls for academics to re-assess and re-conceptualise what teaching, and learning means in a culturally and linguistically diverse context. It also aims to encourage further research around the convergence of English language and the disciplines, as well as the internationalisation and equality, diversity and inclusivity of HE policies and strategies.

In this chapter I characterize the relationship between macroeconomic variables and the terms structure of interest rates using the recent macro-finance approach adapted to the case of an emerging economy and applying it to Brazil. I find that macro variables help to explain the dynamics of the yield curve in emerging markets, specially in periods of high volatility. Moreover, the notion of great external vulnerability of emerging economies is confirmed by the strong role of the nominal exchange rate change, which explains up to 37% of the variation in yields in Brazil. However, the model does a poor job in forecasting yields during the financial crisis of 2008. This fact seems to be related to the strong fall in international commodity and industrial goods prices (in dollar terms), which limited the passthrough from the strong depreciation of the exchange rate to inflation.

Purpose: Nowadays, many terms like computer vision, deep learning, and machine learning have all been made possible by recent artificial intelligence (AI) advances. As new types of employment have risen significantly, there has been significant growth in adopting AI technology in enterprises. Despite the anticipated benefits of AI adoption, many businesses are still struggling to make progress. This research article focuses on the influence of elements affecting the acceptance procedure of AI in organisations.

Design/Methodology/Approach: To achieve this objective, propose a hierarchical paradigm for the same by developing an Interpretive Structural Modelling (ISM). This paper reveals the barriers obstructing AI adoption in organisations and reflects the contextual association and interaction amongst those barriers by emerging a categorised model using the ISM approach. In the next step, cross-impact matrix multiplication is applied for classification analysis to find dependent, independent and linkages.

Findings: As India is now focusing on the implementation of AI adoption, therefore, it is essential to identify these barriers to AI to conceptualise it systematically. These findings can play a significant role in identifying essential points that affect AI adoption in organisations. Results show that low regulations are the most critical factor and functional as the root cause and further lack of IT infrastructure is the barrier. These two factors require the most attention by the government of India to improve AI adoption.

Implications: This study may be utilised by organisations, academic institutions, Universities, and research scholars to fill the academic gap and faster implementation of AI.