Search Results (41)

Diversified application scenarios and business models are effective ways to improve the utilization and economic benefits of energy storage systems. In response to the current problems of single application scenarios, high idle rates, and imperfect price formation mechanisms faced by energy storage on the power generation side, a robust two-stage optimization operation strategy for shared energy storage is proposed, taking into account leasing demand and multiple uncertainties, from the perspective of the sharing concept. A multi-scenario application framework for shared energy storage is established to provide leasing services for wind farm clusters, as well as auxiliary services for participating in the electric energy markets and frequency regulation markets, and the participation sequence is streamlined. Based on the operating and opportunity costs of shared energy storage, a pricing mechanism for leasing services is designed to explore the driving forces of wind farm clusters participating in leasing services from the perspective of cost assessment. Considering the uncertainty of wind power output and market electric prices, as well as the market operational characteristics, an optimized operation model for shared energy storage in the day-ahead and real-time stages is constructed. In the day-ahead stage, a Stackelberg game model is introduced to depict the energy sharing between wind farm clusters and shared energy storage, forming leasing prices, leasing capacities, and energy storage pre-scheduling plans at different time periods. In the real-time stage, the real-time prediction results of wind power output and electric prices are integrated with scheduling decisions, and an improved robust optimization model is used to dynamically regulate the pre-scheduling plan for leasing capacity and shared energy storage. Based on actual data from the electricity market in Guangdong Province, effectiveness verification is conducted, and the results showed that diversified application scenarios improve the utilization rate of shared energy storage in the power generation side by 52.87%, increasing economic benefits by CNY 188,700. The proposed optimized operation strategy has high engineering application value. Full article

The bullwhip effect is the phenomenon of distorted information that causes the amplification of variability of demand in supply chains. We examine the relationship between the bullwhip effect and cost behavior using a large sample of U.S. public firms from 1980 to 2019. Our empirical results show that the costs of firms with a higher intensity of bullwhip effect are significantly more responsive to changes in sales, suggesting that firms facing higher amplification of demand will adopt a less rigid short-term cost structure with lower fixed and higher variable costs. Furthermore, the bullwhip effect is associated with a higher elasticity of number of employees, operating leases, and rental expenses with respect to sales. The findings of mediation analyses suggest that firms are likely to lease capacity resources to increase the flexibility and manage the operating risk associated with the bullwhip effect. The results are robust to alternative model specifications. This study contributes to both the cost accounting and supply chain management literature, and documents large sample evidence on whether and how the bullwhip effect affects a firm’s choice of cost structure. Full article

Energy storage is a proficient means of enhancing power supply reliability and facilitating the use of renewable energy. To study the impact of policies on energy storage decisions in the power supply chain, this paper constructs an electricity supply chain and compares the equilibrium results under four scenarios based on the Stackelberg game theory. The research reveals that both discharge subsidy and investment subsidy play a beneficial role in improving the level of energy storage technology, regardless of whether power producers choose to invest in or lease energy storage equipment. Furthermore, when combined with the implementation of a renewable portfolio standard, these subsidies can have beneficial outcomes. During the early stages of development in the energy storage industry, investment subsidy proves more advantageous for enhancing both technology levels and electricity demand. Conversely, at later stages of industry development, discharge subsidies become increasingly advantageous for enhancing technological advancements and fulfilling electricity demand. Furthermore, implementing a strategy in which power generators invest in energy storage can enhance their profitability while concurrently advancing technological standards and satisfying electricity demand. Full article

Construction machinery operations are intrinsically linked to critical societal challenges, including safety risks and carbon emissions. In response to the high incidence of fatal accidents during installation and dismantling phases, the Chinese government has officially promoted integrated installation–dismantling services to enhance construction safety since 2023. However, the economic viability of this policy for leasing companies remains largely underexplored. To address this gap, this paper develops a leasing-oriented closed-loop construction machinery supply chain model that incorporates integrated installation–dismantling services under an industrial internet platform. The study first compares and analyzes the product leasing demand, installation and dismantling demand, and supply chain profits under both centralized and decentralized decision-making scenarios. Based on these analyses, a profit–cost sharing joint contract is designed to coordinate the supply chain. Furthermore, the interrelationships among key parameters are examined through a sensitivity analysis and numerical simulation. The results reveal that enhancing leasing information services increases both the demand for construction machinery and the platform’s operating costs. These costs are positively correlated with the product’s selling price, leading to higher purchasing costs for lessees. Similarly, improving information services for installation and dismantling raises the platform’s operating costs and enhances service levels, which in turn increases installation and dismantling costs for lessees. The findings demonstrate that within a certain range of cost-sharing and leasing-sharing proportional coefficients, the joint contract enables the supply chain to achieve Pareto optimization. This approach simultaneously alleviates economic pressure on lessees, improves construction safety, and promotes the integration of installation and dismantling services. Full article

To explore the operation strategy of battery leasing and battery swapping services (the two services), this paper constructs a battery swapping supply chain consisting of the battery manufacturer and the vehicle company. Taking the battery manufacturer as a core enterprise, this paper examines four service operation strategies: two self-operated services, self-operated battery swapping services, self-operated battery leasing services and two outsourcing services. Through comparative analysis, the findings indicate that the optimal strategy for the battery manufacturers depends on the vehicle body price. Specifically, when the vehicle body price is low, self-operating both services maximizes profitability and effectively stimulates demand for battery-swapping vehicles. Conversely, when the price is high, a complete outsourcing strategy is preferable, as it is the most effective way to stimulate battery-swapping vehicle demand. Similarly, the optimal strategy for the vehicle company is influenced by the vehicle body price. The vehicle company should provide the two services only when the vehicle body price is low; otherwise, they should focus on producing battery-swapping vehicles. Moreover, to stimulate demand for battery-swapping services, the determination of the optimal strategy is contingent upon several key variables, including the vehicle body price, the battery-swapping service price sensitivity, and the battery-swapping operating cost-sharing ratio. Full article

Efficient supply–demand management in Product-as-a-Service (PaaS) markets requires tools to evaluate pricing strategies while integrating sustainability goals like reuse, efficiency, and carbon footprint reduction. This paper introduces a declarative modeling framework aimed at balancing the three pillars of profitability, cost optimization, and sustainability in PaaS markets. The framework addresses risks such as equipment failure, usage variability, and economic fluctuations, helping providers optimize pricing and operating costs while enabling customers to manage expenses. A declarative model is developed to assess the PaaS market balance to determine optimal leasing offers and requests for quotations. A case study is used to validate the framework, involving devices with specific rental prices and failure rates, as well as customer expectations and budget constraints. Computational experiments demonstrate the model’s practical applicability in real-world scenarios and it can be used by PaaS providers to develop competitive leasing strategies, policymakers to assess market stability, and enterprises to optimize procurement decisions. The findings show that the framework can guide decision making, offering insights into the impact of new technologies, compatibility conditions for leasing offers, and strategies for balancing providers’ profits and customers’ costs. The proposed framework has broad applicability across industries such as manufacturing, healthcare, logistics, and IT infrastructure leasing, where efficient resource allocation and lifecycle management are crucial. Full article

Emergency medical services (EMSs) are critical to reducing fatalities and improving patient outcomes in emergencies such as traffic accidents, where response time is a decisive factor. This study proposes a comprehensive and systematic approach to designing and optimizing EMS systems tailored for urban traffic accidents. By integrating Geographic Information Systems (GISs), hypercube queuing models, Economic Value Added (EVA) calculations, and multi-criteria decision-making (MCDM) techniques, we developed a model that balances service efficiency, financial sustainability, and equitable access to emergency care. The hypercube queuing model was applied to estimate key performance metrics, such as response time, coverage, and the GINI index for equity, under varying numbers of ambulances and demand scenarios. In addition, EVA was calculated for different configurations of leased and owned ambulances, offering a financial perspective to assess the viability of public–private partnerships (PPPs) in EMSs. Using the fuzzy Analytic Hierarchy Process (AHP) and CoCoSo (Combined Compromise Solution) methods, this study identified the optimal number of ambulances required to minimize response time, maximize coverage, and ensure financial sustainability. The proposed approach has been applied to a real case in Colombia. Furthermore, integrating leased ambulances offers a financially viable solution with positive EVA values that guarantee the long-term sustainability of the public–private partnership. This paper advances the literature by providing a practical framework for optimizing EMS systems, particularly in developing countries where financial constraints and resource limitations represent significant challenges. The proposed methodology improves service efficiency and economic sustainability and ensures equity in access to life-saving care. Full article

This paper introduces an innovative sell-type home reversion product aimed at monetizing Singapore’s public flats, serving as a new alternative to the existing Singapore Lease Buyback Scheme (LBS). This new product not only retains the LBS’s guaranteed period of residence in the property along with life annuity incomes but also enhances the product features to meet specific homeowner needs, including the ability to age in place, flexibility in retaining part of the property, options for bequests, and guaranteed principal return. By incorporating these additional features, the new product seeks to stimulate greater demand for monetizing public flats among asset-rich but cash-poor homeowners. An actuarial pricing model is developed to establish a transparent and fair framework for justifying the cost of each product feature. Additionally, we present a cost–benefit analysis from both the provider and consumer perspectives to highlight the major contributions of the new product when compared to the LBS. Full article

The imbalance between supply and demand for slot resources and empty containers has led to resource waste and excessive operating costs for liner companies. Moreover, intense competition among ports has made both container ship slots and port equipment resource allocation inefficient. To address these challenges, this paper aims to solve the collaborative optimization problem of slot allocation and empty container repositioning within port clusters concerning inventory control. A cooperative possession strategy and a hybrid (T, s) inventory control policy are incorporated in this paper. A novel mixed-integer programming model is proposed, enabling us to simultaneously track slot allocation, empty container repositioning, empty container leasing, and slot renting. To solve the model, a new branch-and-bound algorithm based on Lagrangian relaxation and the ascendancy principle (BBLRAP) is developed. Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and algorithm. The results show that the new collaborative optimization method, incorporating the cooperative possession strategy and (T, s) inventory policy, can increase liner company revenues by expanding market share, reducing costs, and improving the utilization of slot resources, ultimately achieving a win–win outcome for both liner companies and their partners. Compared to state-of-the-art studies, the following paper makes new contributions to proposing a cooperative possession strategy within port clusters for the first time. This paper ensures that liner companies and partners achieve a win–win situation in the cooperative game, expanding market shares and improving customer satisfaction. Full article

A double-layer robust optimization method for capacity configuration of shared energy storage considering cluster leasing of wind farms in a market environment is proposed based on the autonomy and profitability of shared energy storage. The feasibility of the leasing model of shared energy storage in the current market environment in China is discussed, and a commercial operation model for shared energy storage to provide leasing services and participate in spot market transactions is proposed. A robust optimization model of a master-–slave game for the capacity configuration of shared energy storage is constructed, considering output uncertainties of wind-driven generators and spot prices at multiple time scales. The upper layer of the model aims to minimize the annual cost of shared energy storage and determines the leasing prices and capacity-planning schemes for each period of shared energy storage in the scenario of an interactive game of wind farm clusters. The lower level of the model aims to minimize the assessment cost of the wind farm cluster and updates the leasing capacity for each time period by utilizing the leasing prices and the leasing demand of the wind turbine output power in the worst scenario. By comparing and analyzing multiple scenarios, the master–slave-game-formed lease improves the shared-storage lease benefit by $1.46 million compared to the fixed tariff, and the multi-timescale uncertainty promotes the shared-storage cost-effectiveness to be reduced by 8.7%, while the configuration result is more robust, providing new ideas for optimizing the capacity configuration of shared energy storage in multiple application scenarios. Full article

Although the Circular Economy (CE) has made remarkable technological progress by offering a wide range of alternative engineering solutions, an obstacle for its large-scale commercialization is nested in the adoption of those business and financial models that accurately depict the value generated from resource recovery. Recovering a resource from a waste matrix conserves natural reserves in situ by reducing demand for virgin resources, as well as conserving environmental carrying capacities by reducing waste discharges. The standard business model for resource recovery is Industrial Symbiosis (IS), where industries organize in clusters and allocate the process of waste matrices to achieve the recovery of a valuable resource at an optimal cost. Our work develops a coherent microeconomic architecture of Chemical Leasing (Ch.L.) contracts within the analytical framework of the Sherwood Plot (SP) for recovering a Value-Added Compound (VAC) from a wastewater matrix. The SP depicts the relationship between the VAC’s dilution in the wastewater matrix and its cost of recovery. ChL is engineered on the SP as a financial contract, motivating industrial synergies for delivering the VAC at the target dilution level at the market’s minimum cost and with mutual profits. In this context, we develop a ChL market typology where information completeness on which industry is most cost-efficient in recovering a VAC at every dilution level determines market dominance via a Kullback–Leibler Divergence (D_KL) metric. In turn, we model how payoffs are allocated between industries via three ChL contract pricing systems, their profitability limits, and their fitting potential by market type. Finally, we discuss the emerging applications of ChL financial engineering in relation to three vital pillars of resource recovery and natural capital conservation. Full article

Cloud providers offer various purchasing options to enable users to tailor their costs according to their specific requirements, including on-demand, reserved instances, and spot instances. On-demand and spot instances satisfy short-term workloads, whereas reserved instances fulfill long-term instances. However, there are workloads that fall outside of either long-term or short-term categories. Consequently, there is a notable absence of services specifically tailored for medium-term workloads. On-demand services, while offering flexibility, often come with high costs. Spot instances, though cost-effective, carry the risk of termination. Reserved instances, while stable and less expensive, may have a remaining period that extends beyond the duration of users’ tasks. This gap underscores the need for solutions that address the unique requirements and challenges associated with medium-term workloads in the cloud computing landscape. This paper introduces a new cloud broker that introduces IaaS services for medium-term workloads. On one hand, this broker strategically reserves resources from providers, and on the other hand, it interacts with users. Its interaction with users is twofold. It collects users’ preferences regarding commitment term for medium-term workloads and then transforms the leased resources based on commitment term, aligning with the requirements of most users. To ensure profitability, the broker sells these services utilizing an auction algorithm. Hence, in this paper, an auction algorithm is introduced and developed, which treats cloud services as virtual assets and integrates the depreciation over time. The findings affirm the lack of services that fulfill medium workloads while ensuring the financial viabilty and profitability of the broker, given that the estimated return on investment (ROI) is acceptable. Full article

In order to understand the driving characteristics of electric heavy-duty trucks in practical application scenarios and promote their usage to replace diesel trucks, this study analyzed the actual usage of electric and diesel heavy-duty trucks in a steel factory based on vehicle-monitoring data and remote online monitoring data and estimated the emission reduction potential of the application of electric trucks by using a mileage-based method and the greenhouse gas emission model. The results showed that the electric heavy-duty trucks in the steel factory mostly operated for over 14 h, with a vehicle kilometers traveled (VKT) of 50–300 km each day, which could meet most of the demands of the transportation of the steel industry. The average daily energy consumption for most trucks falls within the range of 210–230 kWh/100 km, with higher consumption in winter than in summer, which can save approximately 18–26% in operating costs compared with diesel trucks. It is estimated that the usage of these electric heavy-duty trucks can achieve an annual reduction of 115.8 tons of NO_x emissions, 0.7 tons of PM emissions, and 18,000 tons of CO₂ emissions. To further promote the application of electric heavy-duty trucks in China, several policy suggestions, such as introducing priority road-right policies, promoting vehicle and battery leasing markets, and exempting zero-emission vehicles during heavy pollution days, were proposed. Full article

Carsharing is regarded as an efficient way to reduce parking difficulty and road congestion, and the sub-leasing type of round-trip carsharing is an innovative way to enhance the efficiency of carsharing. Meanwhile, with the help of sub-leasing, the turnover rate of a parking lot increases, and the parking operator can earn a certain profit when the parking lot acts as a sub-leasing station. This study aims at extending the application of sub-leasing carsharing by suggesting an integrated framework of parking and sub-leasing based on the concept of autonomous transportation systems (ATSs), which are believed to be able to correctly sense demand, give proper reactions, and reduce operator workloads. A detection approach based on this ATS-based integrated framework is proposed to identify potential sub-leasing customers from the parking users, which is the main contribution of this study. Furthermore, this detection approach was tested using Shenyang parking data, and the parking lots with the greatest potential were analyzed in detail. The results show that 48.4% of parking activities had the potential to be transformed into sub-leasing activities. Of these potential activities, 52.7% were made by people who used a monthly payment scheme, and the promotion of sub-leasing should focus on these people. Full article

Promoting sustainable production and consumption practices in the construction machinery industry is crucial for achieving energy savings and reducing carbon emissions. However, there is a lack of targeted studies addressing the challenge of scaling up leasing and recycling while maximizing economic benefits for enterprises. To fill this gap, this paper presents a lease-oriented closed-loop supply chain model that incorporates a carbon tax policy to investigate the impact of the carbon tax rate and consumer preferences for remanufactured products on the supply chain and introduces a leasing compensation–cost apportioning combined contract to achieve supply chain coordination in the construction machinery sector. The model considers differential selling and leasing prices for new and remanufactured products, as well as the recovery rate, under both centralized and decentralized decision-making approaches. The study explores the interrelationships between various parameters through sensitivity analysis and numerical simulation. The results demonstrate that within a certain range of the cost apportioning proportional coefficient and leasing compensation proportional coefficient, the combined contract can lead the supply chain to achieve Pareto optimality. As the carbon tax rate increases, it was observed that the profits for all parties in the supply chain tend to decrease. However, due to the increased demand for remanufactured products, the product recovery rate improves, resulting in a reduction in total carbon emissions in the closed-loop supply chain of construction machinery. Moreover, the profits of all parties and the total supply chain profits initially decrease and then increase with an increasing preference coefficient for remanufactured products among consumers. By leveraging these factors and adopting effective strategies, such as enhancing consumer recognition of remanufactured products and optimizing pricing and cost allocation, it is indeed possible for the profits of all parties and the total profits in the supply chain to surpass the initial values, even in the face of increasing carbon tax rates. This demonstrates the potential for aligning sustainability objectives with economic benefits in the construction machinery industry. Full article