The contribution of this paper is threefold: first, it accounts for the problem of Ukraine's forced internal displacement, following the Russian occupation of the Crimea and Donbas regions in 2014; second, this study applies a number of quantitative research methods to provide new insights into the way that individual and destination characteristics of the internally displaced people (IDPs) impact upon their destination preferences; finally, it draws four key policy lessons for dealing with today's worst humanitarian catastrophe in Europe since 1945. These lessons focus on the individual characteristics of forced migrants for understanding displacement patterns; and the need for full restoration of legitimate democratic government at home as the necessary condition for return. They also highlight that in the extraordinary circumstances of large-scale warfare, life-saving action takes precedence over any other motivations; and the host communities' perceived sympathy towards the forced migrants' home nation ultimately determines the choice of settlement.

Teaching artificial intelligence (AI) is challenging. It is a fast moving field and therefore difficult to keep people updated with the state-of-the-art. Educational offerings for students are ever increasing, beyond university degree programs where AI education traditionally lay. In this paper, we present an experience report of teaching an AI course to business executives in the United Arab Emirates (UAE). Rather than focusing only on theoretical and technical aspects, we developed a course that teaches AI with a view to enabling students to understand how to incorporate it into existing business processes. We present an overview of our course, curriculum and teaching methods, and we discuss our reflections on teaching adult learners, and to students in the UAE.

In the face of pressing environmental challenges, governments must pledge to achieve sustainability transitions within an accelerated timeline, faster than leaving these transitions to the market mechanisms alone. This had led to an emergent approach within the sustainability transition research (STR): Accelerated policy-driven sustainability transitions (APDST). Literature on APDST asserts its significance in addressing pressing environmental and development challenges as regime actors like policymakers enact change. It also assumes support from other incumbent regime actors like the industries and businesses. In this study, we identify the reasons for which incumbent industry and business actors might support APDST and whether their support can suffice for implementation. We examine the actor strategies by drawing empirical data from the Indian national government policy of mandatory leapfrog in internal combustion engine (ICE) vehicle emission control norms, known as Bharat Stage 4 to 6. This leapfrogging policy was introduced to speed up the reduction of air pollutants produced by the transport sector. A mixed-methods approach, combining multimodal discourse analysis and netnographic research, was deployed for data collection and analysis. The findings show that unlike the status quo assumption in STR, many incumbent industry and business actors aligned with the direction of the enacted policy due to the political landscape and expected gains. However, the degree of support varied throughout the transition timeline and was influenced by challenges during the transitioning process and the response of the government actors. The case suggests we pay more attention to the actors’ changing capacities and needs and consider internal and external influences in adapting the transition timelines. This study contributes to the ongoing discussion on the implementation of APDST, by examining the dynamism of actor strategies, and provides an overview of sustainability transitions in emerging economies.

Teaching artificial intelligence (AI) is challenging. It is a fast moving field and therefore difficult to keep people updated with the state-of-the-art. Educational offerings for students are ever increasing, beyond university degree programs where AI education traditionally lay. In this paper, we present an experience report of teaching an AI course to business executives in the United Arab Emirates (UAE). Rather than focusing only on theoretical and technical aspects, we developed a course that teaches AI with a view to enabling students to understand how to incorporate it into existing business processes. We present an overview of our course, curriculum and teaching methods, and we discuss our reflections on teaching adult learners, and to students in the UAE.