Expansion Costs Research Articles

ENTRY ORDER, PERFORMANCE, AND GEOGRAPHY: THE CASE OF THE CONVENIENCE‐STORE INDUSTRY IN JAPAN

AbstractEntry‐order effects on economic profits have not been extensively studied due to data limitations. This article empirically examines these effects on revenues and costs using a structural approach without requiring information on accounting profits and costs. Utilizing panel data from Japan's convenience‐store industry, I apply a two‐step estimator for many geographic markets. The results reveal that whereas early entrants gain 4.8% more revenue at the outlet level, subsequent entrants benefit from a 7.6% and 5.8% reduction in variable and expansion costs. Simulations suggest initial benefits from delayed entry, but these may dissipate over time, particularly in rapidly growing markets.

The role of hubs and economies of scale in network expansion

Freight distribution often operates on the basis of consolidation, which is achieved through the use of hub facilities that allow for economies of scale. Freight networks need to be expanded to meet future demand, to cater for new markets, and to accommodate trends in global supply chains, for which strategic decisions need to be made. These decisions mainly entail the number and location of new hubs to be established. As network expansions require significant capital, striking a balance between the benefits afforded by the new hubs and the expansion costs is crucial. This paper investigates a hub network expansion problem where the configuration of the resulting network is determined by the trade-off between the fixed costs of locating new hubs and new links, as well as routing costs of shipping commodities, and the cost reductions achieved through economies of scale, without imposing a predetermined network structure. This paper also describes a mixed integer programming formulation of the problem and a Benders decomposition algorithm that uses several enhancement techniques to efficiently solve the model to optimality. The application of the algorithm on a real-life case study arising in the expansion of the Indonesian freight transport network yields several managerial insights. In particular, expanding the network with additional hubs and links can yield substantial cost savings, averaging at 47.6%, although at the expense of an increase in the length of the commodity paths. Failing to operate the network at the selected level of economies of scale can result in an increase in the routing costs by up to 58.8%. Expanding the network with no additional hubs leads to a rise in total costs of up to 20.9%. Finally, lower economies of scale leads to an increase in the length of commodity paths, with the routing cost being identified as the most sensitive parameter.

Solving problems of volume scheduling for shipbuilding enterprises in conditions of limited resources

The shipbuilding industry development strategy for the period up to 2035 and beyond is aimed at creating a new competitive shipbuilding industry based on the development of scientific, technical and personnel potential, optimization of production capacities, their modernization and technical re-equipment [1]. The paper is devoted to solving problems of volume-calendar production planning for shipbuilding enterprises when coordinating the production capacity of the enterprise with the resource needs to fulfill obligations determined by the generated order portfolio. Shipbuilding and ship repair enterprises are typical representatives of enterprises with single and small-scale production and a long production cycle of the main products [2-4]. The problem is solved at the stage of forming a portfolio of orders, which is based on the limited volumes of resources available to the production system. It is required to determine the amount of missing resources by calendar periods that are necessary for the effective functioning of the production system. Non-stored resources such as labor resources, equipment operating time, are usually taken into account when solving the problems of volumetric or volume-scheduling planning. Such resources being unused in a certain planning cycle cannot be used in subsequent cycles. The procedure for finding missing volumes of resources is formulated as the problem of reducing an incompatible system of linear two-sided algebraic inequalities to a compatible one. To do this, it is proposed to “expand” the initial parameters of the system, taking into account the costs of expansion, so that the system becomes compatible. In the general case, formally, the problem under consideration is close to the problem of finding a Chebyshev point [5] for an incompatible system of linear algebraic equations, i.e. a point that is geometrically the least deviating from all hyperplanes formed by the system constraints. The paper proposes statements and solutions of volume-scheduling problems for the case when the structure of the problem constraints is modeled by a root-oriented weighted tree. This hierarchical structure is typical for shipbuilding enterprises [6].

The impact of national policies on Europe-wide power system transition towards net-zero 2050

This research aims to investigate the potential impact of national policies on the attainment of Europe's goal of achieving net-zero greenhouse gas emissions by 2050. Specifically, it analyses the effects of policies on the power sector, by evaluating capacity expansion portfolios, import reliance, and costs by 2050. A linear programming model, the IESA-EUPS, is utilized to optimize the expansion and operation of the power system, considering 28 nodes and hourly temporal resolution. The study includes five scenarios from 2020 to 2050, with varying levels of biomass and nuclear penetration based on existing member state policies. Results show that by 2050, changes mainly occur in the interplay between firm capacities and cross-border transmission levels. Limiting biomass can significantly increase nuclear energy generation, while enforcing all policies leads to a 40 % rise in cross-border transmission by 2050, due to imbalances between countries. Some member states, such as Spain and Finland, are less affected, whereas others are heavily reliant on firm nuclear capacities. Western European countries with strict biomass and nuclear restrictions may see a boost in nuclear installations in countries allowing it. Member states without both nuclear and biomass may rely more on variable renewables, resulting in surplus electricity and increased LCOE.

Design and analysis of government subsidies policy of capacity expansion under reselling and agency selling schemes

Major disruptions, such as the coronavirus disease of 2019 (COVID-19) pandemic and the US-China trade war, have significantly impacted businesses and the global economy, creating a turbulent environment for society and supply chains. Globally, fighting disruptions and ensuring the supply of essential goods has become a significant challenge for governments. One possible solution is to strategically expand essential product capacity to increase supply resilience. Governments must cooperate closely with suppliers through carefully designed subsidy policies. A theoretical model based on current industry practices was built to explore and analyze the partnerships between governments and essential product suppliers. Our proposed model includes four players: the government, the supplier, the selling agent, and the consumer. We considered government subsidy policies for capacity expansion in building supply chains subject to two pricing designs: (1) government pricing and (2) market pricing. The results indicate that once a disruption occurs, social welfare increases with the government-subsidized expansion of essential goods to increase supply chain capacity. We analytically show that if the government does not support production expansion, the supplier can expand production only if the expansion cost is trivial. Furthermore, without government pricing, the product price increases in the government subsidy ratio. Hence, we conclude that government intervention is required to stabilize the market with proper price control, especially in the essential goods supply chain.

Central Bank Independence and Inflation Under Asymmetric Information: Delegation vs. Seesaw Effects

Abstract Recent empirical research finds little or mixed evidence in favour of a negative relationship between central bank independence and inflation. In this paper, we construct a theory where the relationship between inflation and central bank independence depends on the extent of informational asymmetry regarding the government’s efficiency in its provision of public goods and also provide some empirical support for it. In the theoretical part of the paper, we introduce the degree of central bank independence as a fixed cost that is paid when the government (whose objective is to minimize output gap via inflation or costly fiscal expansion) rejects the monetary policy proposal of the central bank (which aims to minimize inflation) and determines both fiscal and monetary policies itself. Government efficiency in providing public goods, i.e. the cost of fiscal expansion, is the private information and the source of informational asymmetry in our model. In this setting, increasing the fixed cost of rejecting the central bank’s offer creates two opposite effects on inflation: delegation effect and seesaw effect (since fiscal and monetary expansion are substitutes for the government, now it relies more on fiscal expansion). We show that while the magnitude of the delegation effect is equal to or higher than the seesaw effect, the magnitude of each effect depends on the current level of the fixed cost. If the current fixed cost is not high enough, then a small improvement in central bank independence creates a relatively smaller delegation effect compared to the case where fixed cost is high enough and both efficient and inefficient government types accept the offer.

A sequential transit network design algorithm with optimal learning under correlated beliefs

Mobility service route design requires demand information to operate in a service region. Transit planners and operators can access various data sources including household travel survey data and mobile device location logs. However, when implementing a mobility system with emerging technologies, estimating demand becomes harder because of limited data resulting in uncertainty. This study proposes an artificial intelligence-driven algorithm that combines sequential transit network design with optimal learning to address the operation under limited data. An operator gradually expands its route system to avoid risks from inconsistency between designed routes and actual travel demand. At the same time, observed information is archived to update the knowledge that the operator currently uses. Three learning policies are compared within the algorithm: multi-armed bandit, knowledge gradient, and knowledge gradient with correlated beliefs. For validation, a new route system is designed on an artificial network based on public use microdata areas in New York City. Prior knowledge is reproduced from the regional household travel survey data. The results suggest that exploration considering correlations can achieve better performance compared to greedy choices and other independent belief-based techniques in general. In future work, the problem may incorporate more complexities such as demand elasticity to travel time, no limitations to the number of transfers, and costs for expansion.

The decoupling dilemma: Examining economic growth and carbon emissions in emerging economic blocs

This study explores whether emerging economic blocs can decouple economic growth from carbon emissions amidst global climate change concerns, integrating Environmental Kuznets Curve (EKC) theory, Stakeholder theory, and Ecological Modernization Theory (EMT). Using fuzzy-set qualitative comparative analysis (fsQCA), it examines the relationship between monetary policy and carbon emissions in two key blocs: ASEAN and GCC. Findings reveal that robust GDP growth in ASEAN correlates with higher ecological footprints, underscoring the environmental cost of rapid expansion. Conversely, the GCC region highlights renewable energy consumption as crucial for managing ecological footprints, despite challenges in energy mix adequacy. These insights offer region-specific understandings, challenging conventional views and guiding policymakers in aligning economic growth with environmental sustainability. The research underscores the need for tailored strategies to develop sustainable economic models that decouple growth from environmental degradation.

Visualizing a Sustainable Future in Rural Romania: Agrotourism and Vernacular Architecture

In Romania, rural communities grapple with decades of depopulation and economic decline, endangering the natural and cultural richness of their landscapes. The implementation of Romania’s 2030 sustainable development plan presents an opportunity to reverse these trends by merging economic and community development with cultural preservation. This paper examines the potential for creating new livelihood opportunities through a program that integrates sustainable agrotourism with culturally appropriate vernacular architecture in Romania’s distinct rural regions. Focusing on two such regions characterized by significant rural population decline yet endowed with ecological services capable of supporting a diverse rural economy, we collaborated with an architect and landscape engineer to devise three specific and detailed agritourist housing scenarios. These scenarios draw upon local architectural forms harmonious with the vernacular landscape, providing accommodations for agrotourism guests and facilitating craft workshops for visitors interested in rural crafts and traditions. We evaluated the cultural appropriateness of the architectural designs through a social survey and assessed the broader social utility of the development plan via an expansive cost–benefit analysis, treating the project’s sustainability features as quasi-public goods. Such interdisciplinary endeavours are essential for effectively bridging conceptually driven social analysis with pragmatic design and planning strategies, essential for achieving sustainable futures for rural communities and landscapes, as exemplified by rural Romania.

Improving path planning for mobile robots in complex orchard environments: the continuous bidirectional Quick-RRT* algorithm.

Efficient obstacle-avoidance path planning is critical for orchards with numerous irregular obstacles. This paper presents a continuous bidirectional Quick-RRT* (CBQ-RRT*) algorithm based on the bidirectional RRT (Bi-RRT) and Quick-RRT* algorithms and proposes an expansion cost function that evaluates path smoothness and length to overcome the limitations of the Quick-RRT* algorithm for non-holonomic mobile robot applications. To improve the zigzag between dual trees caused by the dual-tree expansion of the Bi-RRT algorithm, CBQ-RRT* proposes the CreateConnectNode optimization method, which effectively solves the path smoothness problem at the junction of dual trees. Simulations conducted on the ROS platform showed that the CBQ-RRT* outperformed the unidirectional Quick-RRT* in terms of efficiency for various orchard layouts and terrain conditions. Compared to Bi-RRT*, CBQ-RRT* reduced the average path length and maximum heading angle by 8.5% and 21.7%, respectively. In addition, field tests confirmed the superior performance of the CBQ-RRT*, as evidenced by an average maximum path lateral error of 0.334m, a significant improvement over Bi-RRT* and Quick-RRT*. These improvements demonstrate the effectiveness of the CBQ-RRT* in complex orchard environments.

Ökologischer Umbau von Wirtschaft und Gesellschaft: Kosten und Nutzen

Abstract This article weighs up the costs and benefits of the expansion of renewable energy technologies for electricity generation in Germany. According to calculations of the German Ministry of Economic Affairs, this expansion has cost electricity consumers almost 300 billion euros since the introduction of the Renewable Energy Sources Act (EEG) in 2000. Moreover, payment obligations of a similar magnitude are already in place for the next two decades. However, with the accelerated expansion of renewables following Russia’s attack on Ukraine, politicians are accepting costs well in excess of this approximately 600 billion. Given the costs already incurred, a cost-benefit analysis is imperative, not least because further costs in the three-digit billion range are not included in the 600 billion figure, such as the costs for grid expansion, which would not be necessary to the same extent without the expansion of renewables. Against this backdrop, strict attention should be paid to cost discipline in the further expansion of renewables by ensuring that the Federal Network Agency only issues technology-neutral rather than technology-specific tenders for the expansion of renewables in future. This means that only the most cost-efficient renewable technologies will be installed. Consequently, there will be budgetary scope for future investments that could boost the growth potential of the German economy more than the expansion of renewable energies. Contrasting with the high costs, the benefits of expanding renewable energies are modest. For example, the share of renewables in primary energy consumption in 2022 was only around 17 %. With such a low share, achieving greenhouse gas neutrality in 2045 with renewables alone appears to be a tremendous challenge.

Identifying future district heating potentials in Germany: a study using empirical insights and distribution cost analysis

District heating will play an important role in the transition towards climate-neutral heating. Various studies on modelling the energy system show that district heating and the related expansion of the networks can have different levels of importance. A main reason is that the costs for distribution grid expansion are not well or not at all considered and empirical evidence for a threshold for cost-effective distribution costs is missing in such studies. In this paper, we aim to improve empirical evidence allowing to improve the representation of future district heating expansion in energy systems models. For that, the current status of district heating is analysed in high spatial resolution for Germany. The results show that with the currently accepted average costs, a large range of the possible future market share of district heating for buildings between 17 - 52% is possible by 2050, with the parameters of the connection rate and the renovation rate of the building stock. We conclude that the district heating share could be increased by the factor of 2 to 5 in the future, proving the importance of climate-neutral district heating in the transition.

Assessing the impact of renewable energy penetration and geographical allocation on transmission expansion cost: A comparative analysis of two large-scale systems

Ambitious renewable energy development plans require an efficient electricity grid connection of massive generation capacity. Significant transmission network investments are considered necessary to support the energy transition. This paper analyses the transmission grid reinforcement requirements of two large-scale electricity systems with notably different geographical distributions of renewable resource availability and load density. The results indicate that optimal transmission expansion accounts for less than 10% of total annualised system investment (generation capacity + transmission grid). This is true even in transmission systems with significant existing bottlenecks. The study includes a sensitivity analysis of the location of renewable energy source (RES) capacity. The sensitivities examine the impact of varying the concentration of RES in resource-rich areas, as well as the proportion of RES capacity connected at the distribution level. Both sensitivities are evaluated over a common base case scenario. The results show that a higher concentration of RES capacity in resource-rich network zones can more than double the optimal transmission expansion requirements. In contrast, the implementation of distributed generation (DG) leads to the allocation of generation closer to demand centres, resulting in transmission grid savings of up to 30%. These effects are more pronounced in networks where RES capacity is located further away from major demand centres. This is because existing bottlenecks are exacerbated by higher RES concentration and relieved as the share of DG increases.

Generation and Transmission Expansion Planning: Nexus of Resilience, Sustainability, and Equity

The problem of power grid capacity expansion focuses on adding or modernizing generation and transmission resources to respond to the rise in demand over a long-term planning period. Traditionally, the problem has been mainly viewed from technical and financial perspectives. However, with the rise in the frequency and severity of natural disasters and their dire impacts on society, it is paramount to consider the problem from a nexus of resilience, sustainability, and equity. This paper presents a novel multi-objective optimization framework to perform power grid capacity planning, while balancing the cost of operation and expansion with the life cycle impacts of various technologies. Further, to ensure equity in grid resilience, a social vulnerability metric is used to weigh the energy not served based on the capabilities (or lack thereof) of communities affected by long-duration power outages. A case study is developed for part of the bulk power system in the state of Colorado. The findings of the study show that, by considering life cycle impacts alongside cost, grid expansion solutions move towards greener alternatives because the benefits of decommissioning fossil-fuel-based generation outweigh the costs associated with deploying new generation resources. Furthermore, an equity-based approach ensures that socially vulnerable populations are less impacted by disaster-induced, long-duration power outages.

Abstract WP174: A Reassessment of Cost Effectiveness and Clinical Effectiveness of Anticoagulation Reversal in Direct Oral Anticoagulant - Related Intracerebral Hemorrhage

Introduction: Anticoagulation use is associated with increased risk of hematoma expansion (HE) in patients with intracerebral hemorrhage (ICH). We sought to assess rates of HE in patients with ICH on direct oral anticoagulants (DOAC) and annual cost associated with anticoagulation reversal and occurrence of HE. Methods: We performed an observational cohort study on consecutive patients with ICH on DOAC admitted to a Comprehensive Stroke Center over 3 years, using data from an institutional ICH registry. We prospectively collected baseline demographic and clinical variables, neuroimaging data on baseline and follow-up hematoma volumes (HV) and HE and outcomes on discharge via modified Rankin scale (mRS). Hemostatic efficacy on hematoma size was adjudicated based on the Andexanet Alfa, a Novel Antidote to the Anticoagulation Effects of Factor Xa Inhibitors-4 (ANNEXA-4) trial, with a ≤20% increase in HV compared to baseline considered “excellent” and a ≤ 35% increase in HV compared to baseline considered “good.” Weighted hematoma expansion cost was estimated based on common odds ratio of mRS increase with HE and distributions of mRS with HE. Results: We identified 103 patients who met inclusion criteria: mean age 75.8 (± 11.4) years, 55.3% female. 92 patients (89.3%) received anticoagulation reversal with prothrombin complex concentrate (PCC), of which 19 (20.7%) had HE. A more severe coagulopathy (antiXa > 0.5) was associated with increased risk of HE (p<0.05). 74 patients (80.4%) achieved good or excellent hemostasis. Use of PCC was associated with a 19.6% hematoma expansion rate using the definition above, which translates into a $6700 increase in annual cost per every ICH patient attributed to HE. Conclusion: Cost effective and clinically effective treatments for anticoagulation reversal are needed to reduce the risk and cost associated with HE in anticoagulation-related ICH.

The internal geography of firms

We document that plants belonging to small and mid-sized firms are geographically concentrated, while large firms are much more dispersed. These differences are sizable; firms with 2 plants have a dispersion that is 5 log points lower than predicted by industry location patterns, while the corresponding figure is less than 2 log points for firms with 40 plants and less than a half log point for firms with 100 or more plants. These patterns are qualitatively robust across industries, time periods, and alternative specifications. We also find that plants that are farther from the firm headquarters employ less workers than closer plants within the same firm, and that this relationship is attenuated in large firms. We interpret these findings through the lens of a model of plant location in which more productive firms endogenously choose to lower their cost of geographic expansion.

The Optimal Transportation Option in an Underground Hard Coal Mine: A Multi-Criteria Cost Analysis

The issue of transport in underground hard coal mines is very rarely described in the literature. The financial aspects of this issue are even less often analyzed. Publications in this area focus on technical issues and the safety of mining crews. More attention is paid to transport in open-pit mines. The above premises and practical needs imply the need to conduct economic analyses of transport systems in underground hard coal mines. This paper is a scientific communication, which presents the concept of a multi-criteria cost analysis as a tool to support the selection of the optimal transportation option in an underground hard coal mine. Considerations in this area have not been carried out in the relevant literature, and the problem of selecting a transportation option is a complex and necessary issue in the practice of underground mines with extensive mine workings. The methodology presented includes five cost criteria (costs of carrying out the transportation task; route expansion costs; rolling stock maintenance costs; depreciation costs; and additional personnel costs). The simultaneous application of criteria relating to utility properties in addition to cost criteria makes it possible to adopt a specific technical and organizational model of the transportation system based on the indication of the optimal solution, resulting from the mathematical construction of functions of objectives relating to utility and cost. The optimal variant of the designed system and configuration of the material transportation system in underground workings takes into consideration the following: (1) seven utility criteria (KU1—transportation task completion time; KU2—compatibility of transportation systems; KU3—continuous connectivity; KU4—co-use with other transportation tasks; KU5—safety; KU6—inconvenience; KU7—operation under overplanning conditions) and (2) five cost criteria (KK1—costs of implementing the transportation task; KK2—costs of route expansion; KK3—rolling stock maintenance costs; KK4—depreciation costs; KK5—additional personnel costs). Based on the aforementioned criteria, two objective functions are built for each option: utility and cost. They present divergent goals; therefore, they are non-cooperative functions. Both utility and costs strive for the maximum. In the developed methodology, an ideal point is usually a fictitious solution representing a set of maximum values among all the achievable values in a set of solutions, but it is impossible to achieve this simultaneously based on all the criteria. This point illustrates the maximum utility and lowest cost among the alternatives considered, which is obviously impossible for any of the variants to meet at the same time, although it indicates the possibilities of the technique and the range of costs. For the developed method, a so-called “PND” nadir point is also determined, representing the least-preferred level of achievement of all goals simultaneously, determined from the set of optimal points in the Pareto sense. The originality of the conceptual considerations undertaken stems from: filling the gap in the economic methodology of complex transportation systems evaluation; embedding considerations in the trend concerning complex transportation systems of underground mines; and focusing considerations on the pre-investment phase, making it possible to optimize costs before expenditures are incurred.

Melt‐reprocessable linear low‐density polyethylene/cyclic olefin copolymer blends with low dielectric constant and low thermal expansion

AbstractInsulation materials with low dielectric constants, low coefficients of thermal expansion (CTE), low densities, renewability, and low cost are urgently needed in the fields of communication, control and signal cables. Here we report that combining cyclic olefin copolymer (COC) with linear low‐density polyethylene (LLDPE) by melt blending achieves the above goals. The dielectric constant and CTE of LLDPE/COC blends are minimized at 20 wt% COC content, reaching a value of 2.23 at 1000 Hz and 1.21 × 10−4 K−1, respectively. The density of the blend increases by only 1.6% compared with LLDPE, whereas the tensile modulus increases by 56%, which is conducive to the blends to improve mechanical strength while preserving lightweight. The rheological tests show that the zero‐shear viscosity, storage modulus, and loss modulus of the LLDPE/COC blends do not change much compared with pristine LLDPE, maintaining their good melt processability at 160°C. The cyclic rigid structure of COC causes a decrease in CTE, and the increase in free volume between molecular chains is responsible for the reduced dielectric constant. The present work provides a promising route to the design and fabrication of melt‐reprocessable polymer composites with low dielectric constant and low thermal expansion.

Challenges in Global Access to CAR-T cells: an Asian Perspective.

The use of cell therapy for clinical applications has seen a dramatic increase in recent years, primarily in oncology, especially with the use of chimeric antigen receptor (CAR) T-cell therapies. However, there are some barriers to the widespread adoption of CAR-T cell therapies globally, primarily because of the high cost of manufacturing these cells and clinical infrastructure considerations. We reviewed the different strategies adopted across Asia to implement CAR-T cell therapy and found that these included patient assistance programs, close engagement with funders, cost-effectiveness studies, on-site manufacturing of CAR-T cells, and joint ventures between local partners and foreign pharmaceutical companies. Although on-site manufacturing can reduce the cost of genetic engineering and expansion, it does not address many other hidden costs and quality considerations. Future growth in large-scale regional manufacturing, facilitated by cutting-edge science and innovation, could reduce costs through economies of scale and facilitate the eagerly needed global access.

Research on Comprehensive Evaluation Model of Regional Power Grid Construction Cost Based on Combined Weight

With the introduction of the "carbon peak, carbon neutrality" action plan, it has become an inevitable trend to invest in promoting supply-side structural adjustment and demand-side response to achieve bilateral development. Therefore, the construction expansion and construction cost assessment of key areas of power grid in the future are the focus of power enterprises. In this paper, a comprehensive evaluation model of regional power grid construction cost suitable for various environments is proposed. The ANP-CRITIC method, which combines the analytic hierarchy process with the CRITIC objective evaluation method, is used to determine the subjective and objective weights of the indicators. The comprehensive evaluation results are obtained by calculating the combined weights based on Euclidean distance. In terms of model verification, based on PEST theory, this paper constructs a regional power grid construction cost index system from 4 levels: political environment, economic environment, social environment and technical environment. Through the evaluation and analysis of regional examples, the rationality of the model is verified, and the lowest expected construction cost area is selected to assist enterprise decision-making and ensure the effective realization of power grid construction benefits.