• Novel prototype district building energy system models were developed • Prototype district models support district-scale energy analysis and planning • Electricity load growth can significantly raise peak demand, e.g., 43% rise in CZ 5B • Demand flexibility measures reduced peak loads by 8.3%–16.5% • Optimal backup power solutions depend on location, utility rates, and climate zones Projected increases in electricity demand in the U.S. highlight the urgent need for effective loads management to ensure grid reliability. As the building sector accounts for approximately 75% of electricity usage, enhancing energy efficiency and flexibility in this sector is crucial. Adopting district-level approaches offers significant advantages over traditional individual building analyses by enabling shared infrastructure and economies of scale. To navigate the data and computational challenges associated with modeling energy at the district level, prototype district models have been proposed as holistic, system-level solutions that capture complex interactions within typical configurations. This study presents these models as a reference tool for analyzing district-scale energy systems across various climate zones in the U.S. Developed with input from stakeholders, these models integrate varied building characteristics, inter-building connections, and energy system interactions. A case study utilizing the Urban Edge prototype district model, implemented on the URBANopt™ platform, evaluates multiple demand scenarios and the impact of distributed energy resources such as fuel-fired backup generators, photovoltaic systems, and batteries. Findings suggest that while new electric systems can significantly reduce annual energy use, they may also elevate peak electricity loads, with a notable 43% increase in heating-dominant climate zone 5B. The optimal backup power solutions vary based on location, influenced by factors such as utility rates and incentives. For example, PV and batteries perform well in high-cost regions like New York City, while diesel backup generators are more suitable for backup needs in climate zone 3A, such as Atlanta. Thus, this research highlights the importance of prototype district models for future district-scale energy planning.

Hydrogen logistics is a key enabler in the energy transition. This study presents a disaggregated, reproducible, and quantitative framework for the techno-economic analysis of hydrogen transport via tube trailers and pipelines, covering a broad range of delivery capacities (0.5–10,000 t/day) and distances (10–1,000 km). The model explicitly separates capital and operating costs for each subsystem, enabling transparent identification of the main cost drivers and robust comparison between technologies. Results show that tube trailer transport is dominated by vessel costs and is economically viable only for short-to-medium distances (up to 250–350 km) and low-to-moderate demands; notably, for demands above 5–10 t/day, road transport costs tend to stabilize. In contrast, pipeline transport is characterized by high initial capital expenditure at low capacities, with compression operating costs becoming dominant at high capacities (>500 t/day). Strong economies of scale allow pipelines to maintain costs below 2 €/kg for demands above 200 t/day across all distances considered. Comparative cost maps generated by the model clearly delineate the optimal operational regimes and transition zones for each technology. Sensitivity analysis demonstrates that material cost most strongly affects tube trailer economics, while labor and electricity cost are most influential for pipelines, particularly at high capacities. The reproducibility and transparency of the framework ensure that the techno-economic boundaries between transport modes are robust to plausible cost fluctuations. These findings provide actionable insights for infrastructure planners and policymakers, supporting the efficient and cost-effective integration of hydrogen into future energy systems.

Allometric scaling laws, such as Kleiber's law for metabolic rate, highlight how efficiency emerges with size across living systems. The brain, with its characteristic sublinear scaling of activity, has long posed a puzzle: why do larger brains operate with disproportionately lower firing rates? Here we show that this economy of scale is a universal outcome of avalanche dynamics. We derive analytical scaling laws directly from avalanche statistics, establishing that any system governed by critical avalanches must exhibit sublinear activity-size relations. This theoretical prediction is then verified in integrate-and-fire (IF) neuronal networks at criticality and in classical self-organized criticality (SOC) models, demonstrating that the effect is not model-specific but generic. The predicted exponents align with experimental observations across mammal species, bridging dynamical criticality with the allometry of brain metabolism. Our results reveal avalanche criticality as a fundamental mechanism underlying Kleiber-like scaling in the brain.

ABSTRACT Based on the agglomeration network perspective, this paper investigates the impact of robot application (RA) and agglomeration network (Aggn) on corporate green innovation (CGI) using data from Chinese A-share listed companies from 2011 to 2019. Research findings indicate that within a 30-kilometre effective spatial range, both RA and Aggn can effectively promote CGI. They primarily influence CGI through the technology spillover effect, the peer effect, information sharing, the scale economy effect and the factor allocation effect. Simultaneously, RA and Aggn exhibit synergistic promotional effects on CGI. This synergistic effect is more pronounced in heavily polluting firms. The contributions of this paper are threefold. First, we enrich the emerging literature on the economic consequences of corporate social networks by adopting an agglomeration network perspective, offering a novel lens for studying the effects of smart transformation. Second, we analyse the characteristics of Aggn from a social and spatial perspective, thereby expanding the boundaries of research on Aggn. Finally, this study delves into the underlying micro-mechanisms, providing micro-level evidence for pathways to enhance green innovation performance.

Financial viability can be a challenge in implementing school sealant programs (SSPs). We provided efficiency benchmarks for 2 measures-clinical labor time and labor cost per child-to help SSPs evaluate their performance and quantify the effect of implementation practices on these efficiency measures. We analyzed a convenience sample of data from 107 SSPs delivering sealants in 11 US states to 58 664 students during school years 2017-2018 through 2022-2023. We estimated measures of sealant service efficiency (SSE) per child sealed (SSEtime and SSElabor cost) and used multivariable linear regression models to identify associations between SSP practices and each SSE measure. Because of their skewed distributions, we log-transformed SSE measures. To aid interpretation, we converted resulting regression coefficients back to their original linear scales (hours and US dollars). The median SSEtime and SSElabor cost were 0.95 hours (IQR, 0.56-1.53) and $43.25 (IQR, $23.22-$74.91). The smallest SSP size (sealing 11-60 students) as compared with the largest (sealing 390-14 589 students) was associated with an increase in SSEtime of 0.34 hours (20 minutes; β = 0.399, SE = 0.189, P = .04) and SSElabor cost of $14.45 (β = 0.431, SE = 0.200, P = .03). The use of dentists as dental operators was also significantly associated with increased SSElabor cost at an increase of $3.61 (β = 0.126, SE = 0.140, P = .02). Our findings suggest that SSP labor efficiency could increase with program size (ie, economies of scale) and by using nondentist operators when possible.

Abstract The heterogeneity of different farmland sizes has been overlooked in the climate adaptation literature, yet it is crucial for identifying effective policy interventions to achieve national-scale climate resilience. Using U.S. Agricultural Census data from 2012, 2017, and 2022 aggregated by farm size groupings within states, we compare the temporal changes in adoption of three water-related climate adaptation practices (cover crops, tile drainage, and irrigation) across small, medium and large farms, individually. Specifically, we provide estimates of the role of multiple government programs and climate changes in shaping heterogeneous climate adaptation behaviors across farm sizes. Applying multilevel models within a Bayesian framework, we show that temporal changes of government programs and climate conditions correlate with temporal changes in adoption differently across farm sizes. For small and medium farms, insurance participation associates positively with adoption of cover crops and irrigation. Among large farms, federal programs correlate negatively with irrigation, while state programs and insurance are positively associated with cover crops. These results suggest the opportunity to enhance cover crops among small and medium operations by improving the distribution of insurance and state programs, where small farms often have low participation. Alternatively, crop insurance, and not climate, might be the major driver of irrigation expansion among smaller farms as a way to increase productivity and reduce premium subsidies. Finally, small farms’ adoption of irrigation and tile drainage shows uncertain or negative correlations with changing and uncertain climate, implying that diseconomies of scale might be limiting their adoption; meanwhile, uncertainty of returns under climate changes is preventing farms of all sizes from growing cover crops, specifically in the West for large and medium farms, and the Eastern regions for small farms. We conclude that encouraging the adoption of water-related climate adaptation practices may require adjusting current federal and local programs toward individualized farm-size policies

Purpose There is a growing need for private sector participation (PSP) in the provision of water infrastructure to boost availability and efficiency, especially in developing economies. This study investigates users' preference for PSP in water infrastructure provision in Lagos, Nigeria. Design/methodology/approach Using a multistage sampling, the study selected 57, 172 and 296 buildings in Shomolu, Surulere and Ikeja local government areas, respectively, in Lagos. Closed-ended questionnaires were administered to one adult resident in each building. From a total of 525 questionnaires, only 450 (85.71%) were returned and analyzed using descriptive and inferential statistical techniques. Findings The analysis revealed that users had a higher level of awareness of PSP in water infrastructure provision, though preference for PSP was slightly lower. Three key determinants of PSP acceptance were identified: effective management/policy framework, service competitiveness/effectiveness and price increase. While users recognize the advantages of improved service delivery, the positive attitudes are offset by concerns of increased costs. Anticipated price increases and reduced affordability diminish perceived behavioural control and present compatibility challenges. Regression analysis confirms that while governance and efficiency drive acceptance, affordability is a factor limiting support. Thus, users' preferences rely not solely on efficiency, but on equitable pricing, regulatory transparency and socioeconomic factors. Practical implications Evaluating end-users’ perspectives could encourage PSP in water infrastructure provision, thereby limiting environmental hazards, guaranteeing quality control and reducing individual expenses through economies of scale. Originality/value Quality water supply infrastructure significantly influences housing quality and property values. However, empirical research on the determinants of user preferences for PSP in developing countries remains scarce.

Banks operate branch networks that span multiple geographic markets. Building on theories of economies of scale, this paper examines how overlap in banks’ branch networks across markets affects cost efficiency. Using a panel of 866 U.S. bank holding companies from 1986 to 2024, we measure branch network overlap based on the similarity of banks’ branch presence across metropolitan statistical areas (MSAs). Fixed-effects estimates show that banks with greater branch network overlap exhibit significantly higher cost efficiency. Complementary instrumental-variable and robustness analyses yield qualitatively similar results. Mechanism analyses suggest that overlapping branch networks enhance cost efficiency primarily through the exploitation of economies of scale facilitated by spatial proximity. The paper contributes to the literature by extending scale economy theories to the context of banking studies and by introducing a new multi-bank measure of branch network overlap. From a managerial and policy perspective, the results inform decisions on branch expansion, consolidation, and the assessment of geographic competition in banking markets.

Financial cooperatives play an important role in promoting financial inclusion and community development. This study investigates how board characteristics, including size, gender diversity, and tenure, influence the financial performance of 930 Brazilian financial cooperatives between 2008 and 2022. Using panel data and the System Generalized Method of Moments (SYS-GMM), the results reveal that larger boards negatively affect performance due to coordination inefficiencies, while longer tenure on supervisory boards enhances stability and oversight. Female representation on the board of directors shows a significant negative association with financial performance, reflecting potential cultural and institutional challenges in governance. Cooperative size positively affects performance, reflecting economies of scale, while leverage and network affiliations pose financial challenges. The findings highlight the importance of designing governance structures that balance inclusivity, representation, and financial sustainability, providing insights for improving governance in cooperatives operating in emerging markets.

Energy infrastructure constitutes not merely technical hardware but a fundamental determinant of socioeconomic transformation and industrial evolution. While the engineering attributes of Ultra-High Voltage (UHV) transmission have been extensively documented, its role in shaping corporate behavior and catalyzing industrial upgrading remains underexplored. UHV transmission, operating at direct-current voltages of 800 kV and above or alternating-current voltages of 1000 kV and above, has been systematically deployed across China since 2007 to bridge the structural spatial mismatch between inland energy production centers and coastal consumption hubs. This study investigates the sociotechnical nexus between energy systems and firm-level innovation, employing China's large-scale UHV expansion (2007–2024) as an empirical setting with implications for global energy transition strategies. Integrating energy economics with organizational behavior theory, we adopt a staggered difference-in-differences approach to examine how enhanced energy accessibility influences automation innovation. The findings demonstrate that reliable energy infrastructure functions as a catalyst for intelligent manufacturing, operating primarily through the restructuring of business environments via cost reduction, risk mitigation, and the realization of economies of scale. Importantly, the analysis reveals substantial heterogeneity: policy effects are amplified among state-owned enterprises and regulated industries, reflecting the interplay between institutional arrangements and technology adoption. Furthermore, this study uncovers a significant resource redistribution effect whereby firms in net electricity-importing regions derive disproportionately greater benefits, suggesting that strategic infrastructure deployment can compensate for regional resource disadvantages. By situating these findings within a broader analytical framework, this research offers actionable insights for policymakers seeking to leverage energy infrastructure investments as instruments for advancing industrial modernization and fostering sustainable business practices. • Ultra-High Voltage (UHV) expansion significantly drives corporate automation. • Cost reduction and economies of scale mediate the impact. • Electricity-importing regions benefit more from the grid. • Effects are amplified in SOEs and regulated industries. • Energy infrastructure serves as a tool for industrial upgrading.

Optimising multi-leg renewable hydrogen networks under deterministic and stochastic demand: Scale economies and operational dynamics with BOG

Living smaller, consuming more? The energy implications of aging and shrinking households in Spain

A two-stage stochastic optimization framework for integrated passenger-freight bus transport under time-varying capacity constraints

In order to understand the dynamics of globalization and how international trade and globalization impact corporate behavior, this study examines the difficulties associated with market entry and how they affect the rate of internationalization. According to EFAS matrix analysis, market opportunities are typically greater than threats. However, little is known about how these difficulties specifically affect strategic decision-making in the context of global expansion. In order to close this gap, we used a qualitative case study methodology to investigate how businesses deal with difficulties entering new markets as a result of international competition. According to our research, companies with better strategic and analytical skills are comparatively better positioned to get past internationalization obstacles more quickly than their counterparts. Additionally, we list some financial advantages of overcoming these barriers, such as improved market accessibility, reduced expenses, and longer product life cycles that enhance businesses' operational results. This study provides valuable insights into the relationship between internationalization speed and entry barriers. It also offers useful advice for businesses looking to improve their global competitiveness by investing in economies of scale and increased purchasing power in order to consistently create new market strategies.

Despite extensive international research on economies of scale in municipal service delivery, the topic remains underexplored in South Africa and Africa. This study aims to address this gap by examining the relationship between municipality size—measured by population size and staff numbers—and economies of scale in the municipal service delivery. Drawing on data from district and metropolitan municipalities between 2016/17 and 2019/20 and employing regression analysis, the results show a significant U-shaped relationship between both population size and total expenditure and staff numbers and total expenditure. Importantly, these effects vary between metropolitan and district municipalities. For example, expenditure tends to decrease with increasing population size up to a threshold of approximately 158,000 residents, beyond which diseconomies of scale emerge. These insights offer practical implications for regional planning and service delivery strategies, particularly in guiding decisions on municipal consolidation and resource allocation.

ABSTRACT Wastewater treatment plants (WWTPs) are essential for sustainable water management, yet efficiency gaps in achieving effective operation remain an important policy challenge in many countries, including South Korea. Using plant-level panel data for 2017–2021, this study applies stochastic frontier analysis (SFA) to assess productive efficiency and its determinants. The results show that economies of scale associated with plant size expansion exist up to a certain level. Large-scale WWTPs exhibit higher productive efficiency and increasing returns to scale at the plant-level, whereas small-scale plants operate below optimal scale and experience lower efficiency. However, these results primarily reflect plant-level efficiency and do not necessarily imply system-level cost-effectiveness where sewerage network and collection costs are considered. Ageing effects are found to be heterogeneous, with small-scale plants experiencing a pronounced decline in utilization rates and productive efficiency after approximately 25–30 years of operation, while larger plants benefit from accumulated operational experience and persistently high demand associated with their locations. Outsourcing arrangements also matter. Outsourcing to private agencies is associated with higher short-run productive efficiency based on treated volume, whereas outsourcing to public corporations is linked to stronger effluent quality performance.

China's expanding electric-vehicle fleet drives large battery retirements, yet national-scale evidence linking retirement geography to cost-optimal network design and prospective life-cycle impacts remains limited. To address this, we integrate city- and chemistry-resolved retirements, network optimization, and prospective LCA to minimize total system cost and quantify environmental impacts. We compare a hydrometallurgical baseline (Hydro pathway; shipping intact packs) with a high-voltage pulsed-discharge variant (HVPD pathway; shipping delaminated powder), sharing downstream hydrometallurgical refining. Modeling 10.4 Mt yr-1 of retirements (average over 2040-2050), optimization identifies two distinct configurations: Hydro favors a distributed mesh near hotspots, whereas HVPD supports centralized hub-and-spoke structures. Using 1 kg NMC811 (LiNi0.8Mn0.1Co0.1O2) cathode material production from end-of-life packs as the functional unit, HVPD lowers total cost by about 10% versus Hydro under their respective cost-optimal networks, driven by scale economies and reduced transport burdens. Across prospective background scenarios (reflecting evolving electricity systems and upstream supply chains), recycling reduces global warming potential (1-42%), fossil-fuel potential (3-28%), surplus ore potential (about 67%), and carcinogenic human toxicity potential (20-30%) relative to primary production, with HVPD consistently lower. Overall, shifting the shipped form from packs to powder reshapes cost-optimal network geometry while reducing total system cost and life-cycle impacts.

Abstract Bank mergers have become increasingly common as financial institutions seek economies of scale, improved operational efficiency, and expanded market presence. However, mergers present significant regulatory compliance challenges due to differences in systems, processes, and regulatory reporting frameworks. Ensuring compliance with financial regulations such as anti-money laundering (AML), know-your-customer (KYC), and Basel III requirements becomes critical during post-merger integration. This study examines the role of information technology (IT) solutions in ensuring regulatory compliance during bank mergers. Using a case study approach of a mid-sized banking merger scenario, the research analyzes how integrated IT platforms—including core banking systems, regulatory reporting tools, AML monitoring systems, and data governance frameworks—support regulatory compliance throughout the merger process. The findings indicate that strategic deployment of IT solutions significantly reduces compliance risks, enhances transparency, and improves regulatory reporting accuracy. **Keywords—**Bank mergers, regulatory compliance, banking IT systems, AML, KYC, core banking integration, financial regulation.

Shrinking and aging societies undermine the economic viability of network-based infrastructure once supported by economies of scale and network externalities. This paper develops a conceptual framing of “Denetworking” as a possible reconfiguration strategy in the contraction phase: reducing dependence on highly asset-specific dedicated networks (e.g., pipes and rail tracks) and shifting service functions to distributed systems or generic shared networks (e.g., roads) while maintaining minimum service standards. Rather than presenting a calibrated optimization model or full life-cycle cost (LCC) estimation, the paper proposes a heuristic decision condition for comparing a “keep” scenario (renew and maintain the dedicated network) with a “shift” scenario (Denetworking) and uses quantitative anchors from public sources to illustrate the associated fiscal and institutional trade-offs. Two Japanese cases are used as contrasting illustrations: physical Denetworking, referring to the reduction in or substitution of dedicated physical network assets, in wastewater services (centralized sewerage to decentralized treatment); and functional Denetworking, referring to the transfer of service functions from dedicated networks to more generic shared networks, in regional mobility (local rail to bus/BRT on the road network). The cross-case discussion suggests that Denetworking may become a rational policy option under certain conditions, particularly when demand density declines near renewal-investment peaks and asset specificity increases lock-in. The paper contributes a conceptual vocabulary and comparative policy framing for discussing infrastructure reconfiguration in shrinking societies and highlights practical issues of timing, cost sharing, phased implementation, and stakeholder engagement.

The article analyzes the impact of agro‑industrial integration (AII) on the reproduction of fixed assets (FA) in agriculture over the period 2020-2025. Based on data from the Russian Federal State Statistics Service (Rosstat) and the Ministry of Agriculture of the Russian Federation, as well as reports from agro‑holdings and the results of a survey of the heads of 45 agricultural enterprises in the Central Federal District, the study employed statistical and comparative analysis, econometric modeling, and expert assessments. The findings reveal that integrated structures demonstrate significantly higher performance compared to non‑integrated enterprises: the level of investment in the renewal of machinery and equipment is 25–35 % higher; the average annual rate of machinery renewal reaches 8.9 % (compared to 4.3 % for non‑integrated farms); the level of equipment depreciation by 2025 is 41.6 % (versus 57.8 % for non‑integrated enterprises); and the payback period for capital investments is reduced to 5.1 years (compared to 7.3 years). In addition, the share of agricultural machinery equipped with precision farming systems in agro‑holdings reaches 34 % by 2025, while it is only 13 % among individual farms. The key factors contributing to this efficiency include centralization of resources, economies of scale, access to preferential loans, and the adoption of modern technologies. However, a risk of imbalance in the development of small and medium‑sized agricultural producers has been identified, which calls for adjustments to government support policies–such as subsidized leasing programs and cooperative models for machinery use. The results obtained can be used to improve development strategies for the agro‑industrial complex (AIC).