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Many jurisdictions fine illegal cartels using penalty guidelines that presume an arbitrary 10% overcharge. This article surveys more than 700 published economic studies and judicial decisions that contain 2,041 quantitative estimates of overcharges of hard-core cartels. The primary findings are: (1) the median average long-run overcharge for all types of cartels over all time periods is 23.0%; (2) the mean average is at least 49%; (3) overcharges reached their zenith in 1891–1945 and have trended downward ever since; (4) 6% of the cartel episodes are zero; (5) median overcharges of international-membership cartels are 38% higher than those of domestic cartels; (6) convicted cartels are on average 19% more effective at raising prices as unpunished cartels; (7) bid-rigging conduct displays 25% lower markups than price-fixing cartels; (8) contemporary cartels targeted by class actions have higher overcharges; and (9) when cartels operate at peak effectiveness, price changes are 60–80% higher than the whole episode. Historical penalty guidelines aimed at optimally deterring cartels are likely to be too low.

Energy production and distribution is undergoing a revolutionary transition with the advent of disruptive technologies such as the Internet of Energy (IoE), 5G and artificial intelligence (AI). IoE essentially involves automating and enhancing the energy infrastructure: the power grid from grid operators to energy generators and distribution utilities. The IoE also relies on powerful connectivity networks such as 5G, big data analytics and AI to optimise its operation. By incorporating the technology that employs ubiquitous devices such as smartphones, tablets or smart electric vehicles, it will be possible to fully exploit the potential of IoE using 5G networks. 5G networks will provide high speed connections between devices such as drones, tractors and cloud networks, to transfer huge amounts of sensor data. Additionally, there are many sources of isolated data across the main energy production units (generation, transmission and distribution), and the data is increasing at phenomenal rates. By applying AI to these data, major improvements can be brought at each stage of the energy production chain. Tying renewable energy to the telecommunications sector and leveraging on the potential of data analytics is something which is gaining major attention among researchers and industry experts. This chapter therefore explores the combination of three of the most promising technologies i.e. IoE, 5G and AI for achieving affordable and clean energy, which is SDG 7 in the UN Sustainable Development Goals (SDGs).

Purpose – The purpose of this study was to determine the efficacy value of national street lighting on energy conservation and carbon dioxide (CO₂) emission reduction.

Design/Methodology/Approach – The methods used are the measurement of electrical parameters (low voltage network), the national road illumination level with SON lamp specification, 400 W, 180 W, and 110 Lumen/W, the simulation of energy conservation calculation, and the CO₂ emission reduction obtained by utilizing panel solar cells as a source of energy and LED lights for illumination.

Finding – The results show the efficacy of a 100-W light bulb at an altitude of 8 m for the following specification of light bulbs: LED, 130 Lumens/W, SON, 110 Lumen/W, and MBF, 53 Lumen/W gives the illumination level respectively 13,913 Lux, 11,773 Lux, and 5,672 Lux. By replacing the 180 W SON lamp with an LED, 100 W, of energy conservation by 3.171 GW h is obtained, which is equivalent to a CO₂ emission reduction of 3.641 kTon CO₂.

Originality/Value – This study is a continuation of a study of energy conservation with the utilization of solar cells as an electrical power source for an LED bulb that replaces low-voltage networks as a power source for the bulb type SON.

This chapter presents a South American perspective on the environmental and financial sustainability of energy integration incorporating recent financial lessons from the United States and Europe. An illustrative project called UNASUR-GRID is presented to highlight new thinking on funding ecologically sensitive development (post-carbon electricity generation) and regional energy sovereignty via a new regional development bank for the Union of South American Nations (UNASUR) called Bank of the South, Banco del Sur (BDS) ^1,2 . Sustainable BDS finance rules are presented that aim to break the link between development funding, environmental damage, and sovereign debt owed to banks outside the region, tapping into alternative finances to buffer the region against changes in global financial flows from core nations in the Great Recession.

The author attended presidential meetings of MERCOSUR and UNASUR supplementing this with presidential declarations comparing these with ongoing development planning from IIRSA, also interviewing a COSIPLAN representative. He also cooperated (as an independent researcher) with the Ecuadorian Central Bank research group called ‘New Architectures for Regional Finance’ (NAFR) and conducted technical interviews at South American energy institutes specialising in integration.

Development finance must reflect changes in both energy supply and demand while replacing fossil fuel inputs in electricity generation. Demand planning is necessary to attain sovereignty over a post-carbon electricity supply while maintaining dependability.

Successful energy cooperation is more than just energy infrastructure (UNASUR-GRID), cross-border confidence building is also required, reinforced by commercial treaties for energy exports and imports. Public and private national and regional energy companies need real incentives to trade internationally (improving competition) or renationalisation of supply and distribution may be necessary.

Highly original, this chapter incorporates government, UN and civil NGO inputs into primary research. BDS policy sources include government, ministerial and presidential speeches with interviews and participation in meetings with social movements. For indigenous ecological and social economic concepts such as Sumak Kawsay, the author has travelled extensively in South America and was an active participant at the first World People’s Conference on Climate Change and the 2010 Rights of Mother Earth (World Conference on Indigenous Peoples, 2014) in Cochabamba, Bolivia, along with ecologists and tribal representatives.

Nowadays, the increase in the capacity of batteries has laid the foundations for a broader diffusion of electric mobility. However, electric mobility is causing a growing electricity demand as well as the need to increase the diffusion of suitable charging stations. Within these last challenges, drawing on the recent literature, this chapter provides a critical and wide-ranging review of papers dealing with the formulation of the problem of the localisation of electric vehicle (EV) charging points. This problem is approached considering the electric charging infrastructure technologies, localisation criteria and related methodologies. This review shows how the ‘electric mobility revolution’ applies the technological innovations provided by the energy supply systems, and the location of these systems within the urban contexts. Since the technological innovations have different options, achieving an international standard of charging systems is still far away. Moreover, as there are several criteria, parameters and methodologies, and some analytical approaches for the localisation of electric vehicle charging points, the formulation of the ‘localisation’ problem should require the application of multi-criteria analysis to be addressed. Finally, the results show that there is no consensus on technologies, criteria, and methodologies to be adopted. Therefore, this wide-ranging analysis of the literature would be useful to support possible benchmarking and systematisation accordingly.

This chapter focuses on networks comprised of explicit data sources and information and non-human machines as actors. As non-human actors, we include intelligent agents, robotics, and other forms of interactive artificial intelligence. All six facets of knowledge networks are explored. Given these networks’ peculiar nature, three facets have particular importance, including geography, topology, and relationships. The authors provide profiles of seven networks, including semantic and citation networks, webpage networks, communications and computer networks, and energy grids.