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Positive Energy Districts (PED) are areas within cities that generate more renewable energy than they consume, contributing to cities’ energy system transformation toward carbon neutrality. Since PED is a novel concept, the implementation is very challenging. Within the European Cooperation in Science and Technology (COST) Action, which offers an open space for collaboration among scientists across Europe (and beyond), this paper asks what the needs for supporting the implementation of PEDs are. To answer this, it draws on Delphi process (expert reviews) as the main method alongside the literature review and also uses surveys as supplementary methods to identify the main challenges for developing PEDs. Initial findings reveal seven interacting topics that later were ranked as highest to the lowest as the following: governance, incentive, social, process, market, technology and context. These are interrelated and interdependent, implying that none can be considered in isolation of the others and cannot be left out in order to ensure the successful development of PEDs. The resources that are needed to address these challenges are a common need for systematic understanding of the processes behind them, as well as cross-disciplinary models and protocols to manage the complexity of developing PEDs. The results can be the basis for devising the conceptual framework on the development of new PED guides and tools.

There is an increasing strategic imperative for leading manufactures to rethink their operations, particularly within the context of the sustainable development goals (SDGs), and their environmental, social, and governance (ESG) commitments. Today, ESG performance is a critical component of business strategy, and a source of competitive advantage. From a strategic operations management perspective, an under explored dimension is the role mergers & acquisitions (M&A) plays in enhancing the ESG profile of an organisation, and that of its product supply chain. While outcomes from M&A may produce mixed financial results, the challenges of enhancing post-merger ESG performance is not well understood in the operations management literature, or practically considered during M&A, representing a gap of both theoretical and practical relevance. The objective of this research is to study sustainable supply chains enabled by M&A, by examining motivations, strategic considerations, and integration outcomes from a capabilities perspective. The research question is: How might sustainable supply chain perspectives inform M&A? A multiple case study research approach was adopted, drawing upon eight in-depth product-supply chain M&A transactions within the agri-food and energy sectors. These industries were selected based on their recent volume of M&A activity, and their increasing strategic significance on sustainability. This research contributes to two main streams of sustainable supply chain theory: theory describing supply chain strategies for competitive advantage, and those theories for developing organisational and performance processes for operations sustainability. This thesis contributes five new insights relevant to firms active in M&A, with ambitious sustainable supply chain goals. Firstly, a deal analysis and maturity model framework, integrating key concepts from sustainable supply chain management and the M&A process literature is defined. Secondly, existing merger motives that explain M&A target selection are expanded to include product stewardship, firm ESG performance, and network transformation as sustainable supply chain motivations. Thirdly, this research provides insight into the strategic considerations of relevance by M&A process phase when executing sustainability-targeted M&A. Fourthly, the integration outcomes that are enabled by sustainable supply chain M&A are identified. Finally, propositions for sustainable supply chains are identified that define the relationship between the merger motivations, strategic considerations, and integration outcomes. Together, these form a substantive sustainable supply chain management premise, and a new organisational process perspective for operations sustainability-enabled M&A. This research is of relevance to managerial practitioners in part due to the increasing stakeholder interest in operations sustainability and ESG performance. Industrial sectors and firms with ambitious ‘net-zero’ transition agendas will find the merger motives, strategic considerations, integration outcomes, and resulting operations-sustainability M&A deal archetypes of practical relevance. The four emergent deal archetypes are 1 (passive), 2 (pragmatic), 3 (ideological), and 4 (regenerative). Furthermore, private equity firms and corporate development officers exploring divestment opportunities might utilise this operations-sustainability enabled M&A perspective to inform due diligence and supply chain ESG risk management.

The drop in crude oil price during late 2014 has had a significant impact on all nations. While some countries have reaped the benefits of low oil prices, others have suffered greatly. As a result, it is no surprise that many academics have attempted to develop reliable models to forecast crude oil price. In the age of information and social media, the role of Twitter and Facebook has become increasingly more relevant in understanding our environment. Many academics have exploited this wealth of data to extract features including sentiment and word frequency to build reliable forecasting models for financial instruments such as stocks. These methodologies, however, remain unexplored for the prediction of crude oil prices. The purpose of this investigation to develop a novel model that uses sentiment of United States foreign policy and oil companies' to forecast the direction of weekly WTI crude oil prices. The investigation is divided into three parts: 1) a methodology of collecting tweets relevant to US foreign policy and oil companies'; 2) a statistical analysis of the novel features using Granger Causality Test; 3) the development and evaluation of three machine learning classifiers including Naive Bayes, ANNs, and SVM to predict the direction of weekly WTI crude oil. The findings of the statistical analysis showed strong correlation between the novel inputs and WTI crude oil price. The results of the statistical tests were then used in the development of the predictive model. SVM was found to provide best forecasting performance. Furthermore, using these novel features, the predictive accuracy exceeded that of existing models mentioned in literature

Abstract We conduct a systematic and interdisciplinary review of empirical literature assessing evidence on induced innovation in energy and related technologies. We explore links between demand-drivers (both market-wide and targeted); indicators of innovation (principally, patents); and outcomes (cost reduction, efficiency, and multi-sector/macro consequences). We build on existing reviews in different fields and assess over 200 papers containing original data analysis. Papers linking drivers to patents, and indicators of cumulative capacity to cost reductions (experience curves), dominate the literature. The former does not directly link patents to outcomes; the latter does not directly test for the causal impact of on cost reductions. Diverse other literatures provide additional evidence concerning the links between deployment, innovation activities, and outcomes. We derive three main conclusions. (a) Demand-pull forces enhance patenting; econometric studies find positive impacts in industry, electricity and transport sectors in all but a few specific cases. This applies to all drivers—general energy prices, carbon prices, and targeted interventions that build markets. (b) Technology costs decline with cumulative investment for almost every technology studied across all time periods, when controlled for other factors. Numerous lines of evidence point to dominant causality from at-scale deployment (prior to self-sustaining diffusion) to cost reduction in this relationship. (c) Overall innovation is cumulative, multi-faceted, and self-reinforcing in its direction (path-dependent). We conclude with brief observations on implications for modelling and policy. In interpreting these results, we suggest distinguishing the economics of active deployment, from more passive diffusion processes, and draw the following implications. There is a role for policy diversity and experimentation, with evaluation of potential gains from innovation in the broadest sense. Consequently, endogenising innovation in large-scale models is important for deriving policy-relevant conclusions. Finally, seeking to relate quantitative economic evaluation to the qualitative socio-technical transitions literatures could be a fruitful area for future research.

A model is presented in this work for simulating endogenously the evolution of the marginal costs of production of energy carriers from non-renewable resources, their consumption, depletion pathways and timescales. Such marginal costs can be used to simulate the long term average price formation of energy commodities. Drawing on previous work where a global database of energy resource economic potentials was constructed, this work uses cost distributions of non-renewable resources in order to evaluate global flows of energy commodities. A mathematical framework is given to calculate endogenous flows of energy resources given an exogenous commodity price path. This framework can be used in reverse in order to calculate an exogenous marginal cost of production of energy carriers given an exogenous carrier demand. Using rigid price inelastic assumptions independent of the economy, these two approaches generate limiting scenarios that depict extreme use of natural resources. This is useful to characterise the current state and possible uses of remaining non-renewable resources such as fossil fuels and natural uranium. The theory is however designed for use within economic or technology models that allow technology substitutions. In this work, it is implemented in the global power sector model FTT:Power. Policy implications are given. 18 pages, 7 figures, 8 pages of supplementary information

This paper describes the nexus of energy justice, supply and security. It advances the case that energy justice is the relatively new concept in this triangle of issues and an area requiring research. There are three central tenets of energy justice: distributional, procedural and recognition justice. Each of these tenets figures at certain stages in the energy supply chain and as a consequence there is an effect on energy supply. An example of the wind energy sector in Denmark is presented which demonstrates how the application and promotion of energy justice can enable the growth of an industry supply chain. This in turn contributes to increased energy security and national economic growth.