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Key messageA combination approach to wood identification methods yields superior results when identifying timber originating from the Central African tropics. This is demonstrated by the performance of DART-TOFMS as a fine-tuning step after the microscopic analysis of wood anatomy. These identifications reveal species misdeclarations in small-scale timber markets in the Democratic Republic of the Congo with detrimental ecological and socio-economic effects.ContextIdentifying timber helps enforce international timber regulations. Both the conventional method of microscopic analysis of wood anatomy and chemical fingerprinting using Direct Analysis in Real-Time – Time-of-Flight Mass Spectrometry (DART-TOFMS) face challenges that make identifications difficult, especially in the central African tropics. Meanwhile, these methods are of immense value to help monitor forest exploitation and screen species declarations on the pivotal small-scale timber markets of the Democratic Republic of the Congo (DRC).AimsWe evaluated the performance of both wood anatomy and chemical fingerprinting to identify timber traded on local markets in the DRC and quantified the misdeclarations uncovered through these methods.MethodsWe examined wood anatomy using light microscopy and performed chemical fingerprinting using DART-TOFMS for 115 timber samples originating from local markets in Kisangani, DRC.ResultsMicroscopic analysis of wood anatomy performed better than DART-TOFMS (41 vs. 32 species identifications), but the performance can be improved significantly by combining both techniques (56 species identifications). Our identifications revealed that 26 samples were mislabelled.ConclusionWe recommend expanding the DART-TOFMS reference databases and recognizing the power of combining established and emerging identification methods. This will help expose misdeclarations in timber markets and ultimately halt the illegal timber trade.

Reliable access to electricity is still a challenge in many developing countries. Indeed, rural areas in sub-Saharan Africa and developing countries such as India still encounter frequent power outages. Local energy markets (LEMs) have emerged as a low-cost solution enabling prosumers with power supply systems such as solar PV to sell their surplus of energy to other members of the local community. This paper proposes a one-to-one automated negotiation framework for peer-to-peer (P2P) local trading of electricity. Our framework uses an autonomous agent model to capture the preferences of both an electricity seller (consumer) and buyer (small local generator or prosumer), in terms of price and electricity quantities to be traded in different periods throughout a day. We develop a bilateral negotiation framework based on the well-known Rubinstein alternating offers protocol, in which the quantity of electricity and the price for different periods are aggregated into daily packages and negotiated between the buyer and seller agent. The framework is then implemented experimentally, with buyers and sellers adopting different negotiation strategies based on negotiation concession algorithms, such as linear heuristic or Boulware. Results show that this framework and agents modelling allow prosumers to increase their revenue while providing electricity access to the community at low cost.

Learning and acquiring local market knowledge from foreign distributors are central to manufacturers' export market performance. Drawing from the resource-based view, we propose that manufacturers need to develop stronger local market competence while simultaneously minimizing the costs of distributor opportunism in order to compete successfully in the export market. Cultural distance and other barriers, however, may hinder the development of local market competence for the manufacturer while contributing to the occurrence of distributor opportunism. In order to overcome these barriers, we examine the impact of three alternative forms of manufacturer governance - trust, knowledge sharing, and contract-based relationship - in export channels. Findings suggest that all three governance mechanisms contribute to enhancing the manufacturer's competence to exploit local market opportunity. However, of the three, trust seems to be the only effective way to curtail distributor opportunism.

This article examines household gains and losses from migration within the Swedish urban hierarchy. The central questions focus on whether increases in disposable income outweigh the associated changes in housing costs, especially with movements up (and down) the urban hierarchy, to (and from) larger and more expensive population-growth regions. The questions are addressed using Swedish Census data for 3.5 million individuals and two fixed-effect panel models are estimated for four consecutive time-periods, 1993–2002. The results consistently show relatively higher increases in disposable income moving up the urban hierarchy. Taking changes in housing expenditure into account, this pattern is however reversed; the largest gains are made by households moving from larger to smaller labour markets, a significantly smaller share of total domestic migration. The results point to factors beyond short-term nominal income gains as important in explaining the bulk of domestic migration.

While many studies have looked into the determinants of yields on externally issued sovereign bonds of emerging economies, analysis of domestically issued bonds has hitherto been limited, despite their growing relevance. This paper finds that the extent to which fiscal variables affect domestic bond yields in emerging economies depends on the level of global risk aversion. During tranquil times in global markets, fiscal variables do not seem to be a significant determinant of domestic bond yields in emerging economies. However, when market participants are on edge, they pay greater attention to country-specific fiscal fundamentals, revealing greater alertness about default risk.

Disentangling the causal impact of media reporting from the impact of the events being reported is challenging. We solve this problem by comparing the behaviors of investors with access to different media coverage of the same information event. We use zip codes to identify 19 mutually exclusive trading regions corresponding with large U.S. cities. For all earnings announcements of S&P 500 Index firms, we find that local media coverage strongly predicts local trading, after controlling for earnings, investor, and newspaper characteristics. Moreover, local trading is strongly related to the timing of local reporting, a particular challenge to nonmedia explanations.

This paper presents a general description of local flexibility markets as a market-based management mechanism for aggregators. The high penetration of distributed energy resources introduces new flexibility services like prosumer or community self-balancing, congestion management and time-of-use optimization. This work is focused on the flexibility framework to enable multiple participants to compete for selling or buying flexibility. In this framework, the aggregator acts as a local market operator and supervises flexibility transactions of the local energy community. Local market participation is voluntary. Potential flexibility stakeholders are the distribution system operator, the balance responsible party and end-users themselves. Flexibility is sold by means of loads, generators, storage units and electric vehicles. Finally, this paper presents needed interactions between all local market stakeholders, the corresponding inputs and outputs of local market operation algorithms from participants and a case study to highlight the application of the local flexibility market in three scenarios. The local market framework could postpone grid upgrades, reduce energy costs and increase distribution grids’ hosting capacity.

Aligned with the objectives of the energy transition, the increased penetration levels of electric vehicles as part of the electrification of economy, especially within the framework of local energy communities and distributed energy resources, are crucial in shaping sustainable and decentralized energy systems. This work aims to assess the impact of escalating electric vehicles’ deployment on sustainable local energy community-based low-voltage distribution networks. Through comparative analyses across various levels of electric vehicle integration, employing different charging strategies and system management approaches, the research highlights the critical role of active system management instruments such as smart grid monitoring and active network management tools, which significantly enhance the proactive management capabilities of distribution system operators. The findings demonstrate that increased electric vehicle penetration rates intensify load violations, which strategic electric vehicle charging management can significantly mitigate, underscoring the necessity of load management strategies in alleviating grid stress in the context assessed. This study highlights the enhanced outcomes derived from active system management strategies which foster collaboration among distribution system operators, demand aggregators, and local energy communities’ managers within a local flexibility market framework. The results of the analysis illustrate that this proactive and cooperative approach boosts system flexibility and effectively averts severe grid events, which otherwise would likely occur. The findings reveal the need for an evolution towards more predictive and proactive system management in electricity distribution, emphasizing the significant benefits of fostering robust partnerships among actors to ensure grid stability amid rising electric vehicle integration.

To identify the trends in new flexibility markets, a set of market and aggregator platforms were selected and compared. The analyzed initiatives are relevant to consider alternative designs for European electricity markets. This review proposes a common methodology for analyzing these market models by comparing their description, market structure, market timing, and implementation. Furthermore, a range of policy implications and future research directions towards implementing these markets are presented. The results provide compelling evidence that the new market models represent a promising business with technical and economic justification, as they incentivize the uptake of flexibility from distributed resources by providing services to Distribution System Operators (DSOs) in coordination with Transmission System Operators (TSOs). Moreover, the interactions between these new market platforms and existing markets are of particular interest, and the contributions from aggregator platforms are also relevant to enhance the political vision of empowering the customers through their active participation in markets.

Based on a unique dataset concerning small firms operating in the machinery and equipment industry in Emilia Romagna (Italy), we estimate the separate effects of social capital and local market size on the probability to either fully or partially outsource parts of the production process. We are able to distinguish 29 different phases of the production cycle, from design, to early processing to post-production. Our estimates show that: (1) social capital influences the full outsourcing of core assembly and post-assembly activities, while local market size affects the full outsourcing of early processing activities; (2) neither social capital nor local market size have a statistically significant effect on the probability of partially outsourcing any step of the production process. Robustness tests confirm our results vis-àvis the endogeneity of the local market size and social capital, and the potential Modifiable Area Unit Problem relating to local market size.