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The chapter aims to reflectively discuss a participatory research project concerning the future of higher education in Hungary. This project can be understood as an ongoing methodological experiment which attempts to engage teachers and students, in order to reveal how key stakeholders think about the future of higher education. In line with this, this methodologically oriented chapter shows how different participatory methodologies can be combined in a so-called backcasting framework. This approach starts by describing the present situation, then moves beyond the present conditions so as to identify the cornerstones of an ideal future state. On the one hand, the chapter gives a detailed introduction to how our participatory research process was set up and what particular methodologies we used during this process. On the other hand, it critically reflects on the methodological and ethical challenges involved.

This chapter provides a brief overview of the need to study sustainable futures. It provides an outline of the importance of inventing futures in the third decade of the twenty-first century. It offers conceptual tools for building sustainable futures scenarios and discusses the importance of long-term thinking in business, government and society. This chapter is divided into four sections. Section One presents the opportunities to invent futures and the role of long-term scenarios. Section Two describes the contest for reimagination and the reinvention of futures. Section Three provides the historic background of the evolution of scenario methodology. Section Four offers a concise introduction to futures studies and futurology. Finally, a short preamble on the empirical research on Sustainable Futures for Latin America and the Caribbean considers climate change.

This chapter applies strategic thinking and four-futures approach to developing a knowledge preservation and curation strategy. The authors explain how using the four futures as a baseline refocuses traditional strategy development from linear projections from the present to complex future situations, options, and choices. The refocus also shifts the end stage from evaluation and judgment to continuous assessments of activities, learning, and refresh. A baseline structure is presented as a model for readers. The authors also discuss operationalizing, assessing, and sustaining a knowledge preservation and curation strategy.

Purpose – To consider the emerging qualitative approaches that consider the future, exploring ways in which these may be better used to complement and extend established practice in global climate models.

Methodology/approach – A review of contemporary modelling approaches that consider the future for transport applications, with a focus on complexity and uncertainty issues, the search for foresight, the role of engagement and the credibility of qualitative foresight.

Findings – The importance of the need to incorporate socio-economic scenarios in climate change models and the possibilities offered by the tool of systematic qualitative foresight are demonstrated.

Originality/value – Explores limitations of quantitative modelling approaches to foresight and introduces a potentially complementary, innovative approach based on the systematic use of qualitative methodologies.

Due to the more pressing need, the majority of material in this book has dealt with mitigation; interventions to reduce emissions of greenhouse gases (IPCC, 2001) away from a scenario of ‘business as usual’. An early academic review on climate change mitigation and transport appeared in 2007 (Chapman, 2007), a year before the United Kingdom committed itself to the highly ambitious Climate Change Act 2008. The final act sought an ambitious 80% cut in greenhouse gas emissions by 2050. Although criticised in this book as being unrealistic, this is the level of intervention required if ‘dangerous’ climate change is to be avoided (defined as greater than 2°C rise in global temperatures). As Chapter 8 (a policy perspective) explains, such targets, however unrealistic, are informed by considerable input from expert opinion (e.g. Delphi studies) and require a detailed knowledge of current emissions as well as accurate predictions/scenarios of future emissions. For this reason, scenarios and the control of uncertainty were discussed in Chapter 2 towards the start of this book. Indeed, the commonly quoted ‘business as usual’ scenario is in itself too simplistic and highly improbable, not only due to mitigation measures imposed by governments, but also because of the future scarcity of oil which will force change in the medium term regardless. Backcasting is the key tool used to model the continuum of socio-economic scenarios which exist between ‘business as usual’ and the equally unlikely case of all targets being met. However, the science is inherently difficult and the end result is a wide range of permutations and storylines, largely dependent on mitigation. Early progress towards the 80% target has not been promising, but the decarbonisation of the transport sector is still seen as key in meeting the demands of the Climate Change Act 2008. There is a need to tackle the three primary culprits of greenhouse gas emissions in the transport sector: aviation, freight and car ownership (Chapman, 2007). This book has examined in detail how this could be achieved in all these sectors using a range of aspects relating to technological and behavioural change.

The analysis of the main stages of the Belarusian economy's development from 2000 to 2018 has been carried out, the main factors and limitations of economic growth considered. The known models of economic growth applied to the Belarusian economy are shown. It is grounded that the correct use of endogenous growth models based on production functions is hampered by the significant influence of exogenous factors on the Belarusian economy, and it is more preferable to use models based on the balance of payments under these conditions. The methodology for modeling the balanced economic growth based on Input–Output tables' data is proposed, the results of its use are shown. Three scenarios for the growth of the Belarusian economy until 2025 are analyzed: baseline, adverse, and target; the desired structural changes are identified for the implementation of the target scenario.