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In October 2020, Zambia failed to make a $42.5 million interest payment on $1 billion in Eurobonds maturing in 2024, becoming the first African country to default on its debt obligations in the aftermath of COVID-19. Zambia's default highlights the fragmented nature of governance in sovereign debt markets. The Zambian default also underscores the continuing impact of colonial hangover in former colonies in Africa. Fragmented governance and colonial overhang create incentives for both debtors and creditors that contribute to cycles of sovereign debt. These cycles of debt pose a particular hazard to residents within countries that issue such debt. In African contexts, this has led to flows of funds for debt repayment that may significantly jeopardize the well-being of people who are already poor. Zambia's default also reflects the increasing need of African countries to navigate among different external actors, particularly China, which has given loans throughout Africa for varied projects, including infrastructure lending as part of its Belt and Road Initiative. The Zambian default draws attention to the significant amount of Eurobond debt African countries have incurred in recent years and the burdens that such debt may impose. The circumstances of Zambia's default, as well as recent disputes about external debt in Mozambique, reflect continuing issues about transparency and public scrutiny of sovereign debt transactions and the broader societal impact of debt internally within African countries and in relations between African countries and varied external powers.

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

Since 1945, there have been significant changes in the pattern of Indian overseas immigration. Australia has become a popular destination for Indians, particularly skilled immigrants, during this time. Until the 1950s, Australia maintained a strict ‘White Australia’ immigration policy, which was eased by a formal agreement to favour immigrants from select European nations, particularly the United Kingdom. The policy’s original aim was to increase the population for defence purposes. Its goal in the 1950s and 1960s was to bring in workers to help with Australia’s industrial development. It wasn’t until the 1970s that Australia began to see the benefits of a multicultural immigration policy, a mostly bipartisan approach that has helped Australia’s economy grow and its society become one of the world’s most progressive. By the early 1990s, the immigration policy had become more flexible, incorporating humanitarian, social, and economic goals. Over the previous two decades, the policy has placed a strong focus on skilled immigration. As a result, Australia now has a genuinely global immigration policy that promotes a culturally diversified and socially united society. In Australia, the pattern of immigration has changed dramatically, and the Indian population is rapidly growing. Even though most of the research on cultural diversity in Australia has centred on unskilled foreign labour, many immigrants hold management positions. On a daily basis, however, several of them face prejudice, discrimination, and racism.

Purpose – To examine the cost-effectiveness of UK government policy with respect to the mitigation of carbon emissions from the transport sector.

Methodology/approach – Existing policy as set out by the Department for Transport in Low Carbon Transport: A Greener Future is examined. This document elaborates a Low Carbon Transport Strategy intended to achieve annual emissions savings of 17.7 MtCO2 by 2020. A wide range of policy areas where further action could be taken to reduce carbon emissions are examined and their cost-effectiveness considered.

Findings – Measures that influence behaviour including smarter choices, eco-driving across modes, freight best practice and modest price increases are highly cost-effective. More cost-effective routes to saving 17.7 MtCO2 are identified, as are further cost-effective savings.

Originality/value – It appears that government targets could be delivered and indeed exceeded at lower cost than the Low Carbon Transport Strategy. However, policy development is influenced by a wide range of factors which help to explain why cost-effective measures are not always fully exploited.