Individual Revenue Research Articles

Coordination Mechanism of Revenue Sharing Contracts in Port Supply Chains: A Case Study of China’s Nantong Port

Considering the port function’s importance, the supply chain’s overall and individual revenues, and the port supply chain’s uniqueness, a game model for a two-stage port supply chain composed of port service providers and port enterprises was developed. Using revenue sharing contracts (RSCs) as a coordination mechanism, game equilibriums were investigated under two conditions: price-sensitive or price-insensitive port logistics service demand. The results suggested that RSCs can achieve Pareto improvement in both cases, thereby coordinating port supply chain revenues. Led by the port logistics service provider and port enterprise, the coordination mechanisms based on RSCs of port supply chain were discussed using logistics service capacity as the coordination link. Despite differing decision orders, the RSC model can coordinate the port’s supply chain with its service provider, while the port and logistics service provider determine the retention ratio. This paper also proposed coordination measures for the Nantong Port, one of the most important ports in China, to maximize the logistics capacity of iron ore supply chain and enhance the port logistics’ value-added services.

Coalition Formation Game Based Information-Energy Collaboration in Vehicle Edge Computing Networks

In vehicle edge computing network (VECN), a key issue for the roadside unit (RSU) is how to handle computationally intensive tasks timely and use energy efficiently. When an RSU cannot finish the task on time, computation offloading will be an effective approach. However, when offloading tasks most RSUs neglect the energy supply and do not consider computation requirement and energy supply jointly. In this paper, we consider a VECN where there are multiple RSUs. When an RSU has a computational task with latency constraint, it will offload the task to the nearby RSUs and/or cloud servers, and purchase electricity from the neighbors and/or power grid if it is also short of power. To conserve energy and reduce cost, not only the collaboration between the VECN and the cloud/grid, but also the collaboration of RSUs within the VECN is investigated. Specifically, we first formulate the information-energy collaboration problem, and study how the strategies of computation offloading and energy sharing interact with each other, where the RSU's individual revenue is considered. Next, since the problem is a mixed nonlinear programming problem that is hard to be solved, we reformulate it into a double-level coalition formation game, based on which an algorithm with low complexity is proposed. Finally, we prove theoretically that through finite iterations, the game-based algorithm can converge to a stable Nash equilibrium which is the solution to the original problem. Simulation results show that our scheme is superior to the existing ones in reducing edge network expenses while improving individual revenue.

A genuine V2V market mechanism aiming for maximum revenue of each EV owner based on non-cooperative game model

As the number of electric vehicles (EVs) surges, EVs are expected to supply auxiliary services for power grid through the vehicle-to-grid (V2G) operation. Specifically, vehicle-to-vehicle (V2V), as a beneficial supplement of V2G, has received increasing attention owing to the capability for flexible EVs deployment and profitable individual interaction. In this paper, a genuine V2V market mechanism aiming for maximum revenue of each EV owner is proposed to construct a distributed electricity market. It reveals the dominance of EV owners from the perspective of market and allows the trade among EV owners in local distribution grid with charging points such as charging stations and auto parks. To this end, the implementation of V2V market mechanism is analyzed in detail, including the electricity price, the process and the integration with the internet of smart charging points (ISCP), a cyber-physical architecture. Then, EVs’ energy dispatching is formulated via the non-cooperative game model, in which each EV owner anticipates maximizing individual revenue by choosing feasible strategies. The existence and uniqueness of Nash Equilibrium (NE) in a non-cooperative game is proved by means of variation inequality (VI) theory. Finally, the ISCP-based optimal algorithm is developed to solve the NE efficiently, thereby maximizing reward of each EV owner. Comprehensive case studies show that the proposed V2V market mechanism can implement distributed dealing among EV owners with reducing individual charging cost and regional load variance effectively. Specially, the costs of EV1, EV8 and EV9 decrease by 31%, 36% and 34%, respectively. And V2V charging demonstrates much lower variance (10.5209) than regular charging (14.1124). Additionally, the convergence of the algorithm is also demonstrated, reaching the NE in less than 30 iterations for each EV.

Sharing unused storage in local energy markets utilizing physical storage rights: A non-cooperative game theoretic approach

This paper proposes a local market framework to allocate physical storage rights (PSRs). As a market product, PSRs are provided by the storage owners and enable the local market participants (including arbitrageurs, renewable producers, consumers and prosumers) to access the storage. That is, they can book storage in the form of PSRs and dispatch it at a given time aiming to maximize their utility function. Storage owners can monetize their unused capacity in the form of PSRs, while the rest of the remaining market participants aiming at additional flexibility, compete to obtain the PSRs on a short-term basis. To design a functional mechanism capable of handling the periodical PSR auctions efficiently, two different business options have been investigated: (i) market participants offer part of their unused storage, keeping however the priority on utilizing their resource, and (ii) storage is exclusively granted by an external supplier that makes profit by selling storage services solely in the form of PSRs. Considering the context above, we propose two distinct local market-clearing mechanisms, consisting of two equilibrium and two optimization models. We prove that the equilibrium models can be substituted with the equivalent optimization ones ensuring the same desirable market properties, such as efficiency and revenue adequacy. Numerical results from case studies show that storage presence in the energy community decreases the total system cost up to almost 10%, demonstrating at the same time the benefits of the proposed PSR allocation mechanism for the individual market participants. That is, the individual revenue is increased up to 39%, depending on the market participant.

Co‐opetitive mean field type game based task offloading strategy in multi‐access edge computing networks

In this paper, a novel co-operative mean field type game based task offloading strategy is proposed for multi-access edge computing networks. The objective is to optimally determine the tasks offloaded to each edge computing node (ECN) in the network so that to balance the overall system performance and individual revenue of each ECN. To do so, the utility function of each ECN is first formulated, which is the payback of his time and energy cost for processing the tasks, tailed with the penalty from the network for not processing the tasks on time. A mean field type game is then formulated, where each ECN can either cooperate or compete with each other to maximize their own utility. With respect to the proposed game, the direct method is applied to find the final solutions. Simulation results reveal that the proposed strategy can well balance the utility of each ECN and the overall efficiency of the system, leading to a better performance compared with its cooperative- and competitive-counterparts.

Multi-service based economic valuation of grid-connected battery energy storage systems

Grid-scale Battery Energy Storage (BES) technologies are advocated as key enablers for low-carbon pathways. High capital costs and limited revenue from capacity utilization for a specific service leave most of the storage assets under high investment risks. Economic viability of BES can be justified from their participation in multiple services. Most of the existing works on value stacking and economic viability assessment are limited to considering energy arbitrage, peak shaving, and frequency regulation. Non-consideration of other potential grid services like load following and ramp products results in inadequate economic feasibility assessment of storage projects. In this context, the paper attempts to analyze economic feasibility from stacked revenues of an optimally sized BES. Various combinations of six grid services - energy arbitrage, regulation, reserve, load following, peak shaving, and ramp products; are modeled to assess optimal portfolio of services for BES value stacking and economic viability. BES and conventional units are co-optimized for various services in hourly resolution and inter-day rolling horizon for a year using security-constrained scheduling framework. Economic analysis of BES is carried out using cash flows for various service combinations. Case studies conducted on IEEE RTS 24 and Great Britain test systems highlight that BES, with stacked services, can gain 80%–120% of the sum of individual revenues. BES investments are found to be economically viable with value stacking from 04 to 05 services.

Optimal Profit Distribution in Interplant Waste Heat Integration through a Hybrid Approach

Resource allocation among stakeholders has not been addressed equitably in interplant heat integration that simultaneously considers thermal engines. Therefore, this paper presents an approach to interplant heat integration and thermal engines that considers the equitable allocation of resources among the different industrial plants involved. A hybrid solution procedure based on iteration between metaheuristic optimization and deterministic optimization is used to solve the problem. Thermal engines (steam Rankine, organic Rankine, and absorption refrigeration cycles) are modeled through a process simulator and optimized using a link between MS Excel®-Visual Basic for Applications®-Aspen Plus®. Using the deterministic approach, a mathematical model is proposed to determine the individual revenues of the involved industrial plants. The incorporation of the Social Welfare, Rawlsian Welfare, and Nash schemes is proposed to find the fairest revenue allocation. A case study with four different scenarios is shown to evaluate the proposed approach. The results show different solutions for thermal engines, as well as different revenue distributions under the allocation schemes. Optimal operating conditions are found for thermal engines. Also, it is shown that for this case study the Rawlsian scheme provides a fair allocation of revenue and costs.

Incorporating quality in economic regulatory benchmarking

The Danish water regulator uses, amongst other things, Data Envelopment Analysis to create a pseudo-competitive environment for the water companies. The benchmarking results are used to set an individual revenue cap for each company. The benchmarking model is currently criticised for not including the companies’ supply quality and thereby having an omitted variable bias problem. One problem the regulator has encountered when trying to incorporate supply quality in the benchmarking model is that it tends to increase the revenue caps more than desired. The regulator does, however, not have any prior information about the marginal rates of substitution between the quality variables and costs, which makes it challenging to reduce the supply quality's impact on the revenue caps.In this paper, we analyse the facet structure when incorporating three quality variables into the existing benchmarking model. We argue that it is generally sensible to investigate the facet structure and ensure that it is trustworthy before calculating efficiency scores, to increase the credibility of the results.By using an outlier detection model on the estimated marginal rates of substitution, we use the insights into the facet structure to create weight restrictions between costs and quality. This can help the regulator incorporate quality in the model without allowing the efficiency scores to increase excessively due to the increase in dimensionality. In addition, our proposed method reduces the need to extract the companies’ private information about their marginal rates of substitution, which is costly to verify for both the companies and the regulator. Lastly, we propose to add weight restrictions based on the consumer's willingness to pay for quality to avoid the companies choosing a level of quality that is higher than what the consumers are willing to pay for.

Delay-Limited Computation Offloading for MEC-Assisted Mobile Blockchain Networks

The proof-of-work (PoW) mining process requires a large amount of intensive computing, which leads to some plights such as heavy equipment and fixed access nodes in traditional blockchain networks. A novel mobile blockchain network with the help of a mobile edge computing (MEC) server is presented, where all mobile users participate in the PoW mining process. The traditional Bitcoin network adjusts the target difficulty value to ensure a stable block time. However, for MEC-assisted mobile blockchain networks, the adjusted difficulty value needs to be broadcast to all mobile users, which results in expensive communication costs. To maintain a stable block time of mobile blockchain networks, we formulate the delay-limited computation offloading strategy of the PoW-based mining task as a non-cooperative game that maximizes an individual revenue in the MEC-assisted mobile blockchain network. Specifically, the non-cooperative game problem can be divided into multiple sub-game optimization problems to obtain final solutions for all users. We analyze the sub-game optimization problem and prove the existence of Nash equilibrium (NE) of the non-cooperative game. Moreover, we design an alternating iterative algorithm based on the continuous relaxation and greedy rounding (CRGR) to achieve the NE of this game. Given the sub-optimal delay-limited computation offloading results, we also derive the optimal transmit power for an individual user within the maximum mining delay range. From the analytical results, we can see that the proposed CRGR-based alternating iterative algorithm can efficiently attain the sub-optimal delay-limited computation offloading strategies of all mobile users in the polynomial time. The individual transmit power increases accordingly with the delay-limited computation offloading strategies of all users. Numerical results demonstrate that the proposed CRGR-based alternating iterative algorithm has fast convergence and good stability.

Cognitive and behavioral coping in response to wildlife disease: The case of hunters and chronic wasting disease

ABSTRACT The transactional model of stress and coping (TMSC) provides a conceptual framework for understanding adaptations to stressors like chronic wasting disease (CWD). Understanding hunter response to stressors is important because decreased participation and satisfaction can affect individual well-being, cultural traditions, agency revenue, and local economies. Using TMSC, we explored how deer hunters coped with CWD. We also compared involvement, and impacts and emotions related to CWD, inside and outside a CWD management zone. Then we examined coping related to CWD presence, and if the disease affected human health. Most hunters would cope using product shift (i.e., eating meat after a negative test result) rather than displacement (i.e., hunting elsewhere) or dropout. Hunters who may be displaced reported lower involvement in deer hunting, and increased worry about CWD. Results suggest that CWD information and testing may increase hunter worry. Funding expanded testing without prompting displacement or dropout are important management considerations.

Sharing Profits in the Sharing Economy

A monopolist platform (the principal) shares profits with a population of affiliates (the agents), heterogeneous in skill, by offering them a common nonlinear contract contingent on individual revenue. The principal cannot discriminate across individual skill, but knows its distribution and aims at maximizing profits. This paper identifies the optimal contract, its implied profits, and agents' effort as the unique solution to an equation depending on skill distribution and agents' costs of effort. If skill is Pareto-distributed and agents' costs include linear and power components, closed-form solutions highlight two regimes: If linear costs are low, the principal's share of revenues is insensitive to skill distribution, and decreases as agents' costs increase. If linear costs are high, the principal's share is insensitive to the agents' costs and increases as inequality in skill increases.

Ten Thousand Commandments: An Annual Snapshot of the Federal Regulatory State (2020 Edition)

Ten Thousand Commandments: An Annual Snapshot of the Federal Regulatory State (2020 Edition)

The General Concept of the Revenue Model for Sustainability Growth

Since revenue streams provide financial stability for business development, companies are tasked with conducting an individual revenue model, that ensures their healthy and sustainable growth. Therefore, it is important to take into account the manner of creating revenues. This initiative relates to the revenue generation mechanism which describes how revenue is generated from the offer. Our research aims to find out whether the number of revenue streams (scope of the revenue model) and other financial and production indicators can predict the amount of revenue, as well as which factors can predict the scope of the revenue model. Concurrently we have focused on analyzing the sources of revenue streams and have selected key business variables in the wine producing industry. This sector had been selected as there is a significant difference between revenue streams based on manufacturing and those based on tourism activities. This concept was created by using theoretical knowledge about the value, pricing and segmentation. The goal of our research article was to design the General Concept of the Revenue Model and to identify variables with a strong influence on it. Results of the multiple linear regression analysis confirmed the significant influence of particular predictors on the scope of the revenue model, whereby the model explains up to 80% of the variance.

Analysing the commercial development of Australian rugby utilising financial reporting

The purpose of this paper is to explore the financial growth and development of the governing body of Rugby Union in Australia, now known as Rugby Australia. In doing so, the research observes Rugby Australia’s transformation from a small amateur organisation into a multi-million dollar enterprise. The study examines 39 years of annual financial reporting from which four key operational phases were identified. Through this analysis the exponential growth of the organisation is quantified. Correspondingly, the composition of the organisation’s specific revenue items was shown to have shifted significantly over the four phases. Furthermore, the changing accounting treatment of revenue line items within the financial reporting provides qualitative insight into the organisation’s historical philosophy toward individual revenue streams. The study contributes to an emerging field of sport research which utilises financial documents as a primary method to explore organisational performance and development. This offers new empirical insights into the transformation of sport into a sophisticated commercial industry. In doing so, it addresses academic calls for greater adoption of quantitative financial methods to explore both sport history and sport management.

Public Opinion Polarization by Individual Revenue from the Social Preference Theory.

Social conflicts occur frequently during the social transition period and the polarization of public opinion happens occasionally. By introducing the social preference theory, the target of this paper is to reveal the micro-interaction mechanism of public opinion polarization. Firstly, we divide the social preferences of Internet users (network nodes) into three categories: egoistic, altruistic, and fair preferences, and adopt the revenue function to define the benefits obtained by individuals with different preferences among their interaction process so as to analyze their decision-making behaviors driven by the revenue. Secondly, the revenue function is used to judge the exit rules of nodes in a network, and then a dynamic network of spreading public opinion with the node (individual) exit mechanism is built based on a BA scale-free network. Subsequently, the influences of different social preferences, as well as individual revenue on the effect of public opinion polarization, are analyzed through simulation experiments. The simulation results show that (1) Different social preferences demonstrate different influences on the evolution of public opinions, (2) Individuals tend to interact with ones with different preferences, (3) The network with a single preference or a high aggregation is more likely to form public opinion polarization. Finally, the practicability and effectiveness of the proposed model are verified by a real case.

Sharing Profits in the Sharing Economy

A monopolist platform (the principal) shares profits with a population of affiliates (the agents), heterogeneous in skill, by offering them a common nonlinear contract contingent on individual revenue. The principal cannot discriminate across individual skill but knows its distribution and aims at maximizing profits. This paper identifies the optimal contract, its implied profits, and agents' effort as the unique solution to an equation depending on skill distribution and agents' costs of effort. If skill is Pareto-distributed and agents' costs include linear and power components, then closed-form solutions highlight two regimes: If linear costs are low, the principal's share of revenues is insensitive to skill distribution and decreases as agents' costs increase. If linear costs are high, then the principal's share is insensitive to the agents' costs and increases as inequality in skill increases.

Collaborative flexibility scheduler using zonal intelligence

Swanbarton's experience in real-world local energy trading in the Innovate UK-funded EMBLEM and LEMDEx projects shows that high-resolution scheduling can deliver flexibility by reducing peak flows across market boundaries. Building on these findings, this study presents a new concept for automatically meeting sourcing flexibility requirements from multiple, commercially separate providers with the lowest overall cost. This novel approach enables prequalified providers to opportunistically join and leave flexibility markets, maximising individual revenues and minimising disruption of primary commercial activities through collaboration. Distribution system operators also save costs by being freed from complex scheduling, coordinating and dispatching of flexibility. With sufficiently granular and distributed network metering and improvements in meteorology, power flows may be measured and forecast with much higher fidelity, so enabling accurate quantification of near-term flexibility requirements. Rather than being locked into lengthy delivery windows against discrete settlement periods, flexibility needs are best expressed by shapes plotted on a continuous rolling power-time signal since these can exactly follow arbitrary fluctuations of local renewables or high penetrations of electric vehicles. To meet such flexibility requirements, these shapes may then be in-filled by the available local demand-side response processes, also expressed as shapes, on an automated, ongoing basis by the zonal flexibility scheduler.

Individual Income Tax Revenue and Its Determinants: A Case Study in Vietnam

Individual income tax revenue accounts for a high proportion of Vietnam's total tax revenues. The purpose of the article is to study the factors affecting individual income tax revenue in Vietnam. The findings show that there are three factors to be the strongest impact on the individual income tax revenue including GDP at current prices, individual income tax burden and inflation. Based on the empirical results, the article proposes some policy implications that can increase the individual income tax revenue without exceeding the people's endurance.

Penalizing passenger’s transfer time in computing airlines revenue

Airline strategic alliances result in a form of cooperation where firms can access the resources of others network members in order to create added value for their passengers. The shortcoming of this process is that each member of the network makes individual revenue management decisions to maximize its own income, resulting in a sub-optimal income for the network members.To deal with this problem, this paper suggests a resource allocation based on a transfer pricing mechanism, to cooperatively divide the revenue of a passenger between network members. The method penalizes the total time that a passenger takes for reaching the final destination. The model takes into consideration that the profit is independent of the number of available seats (with a maximum determined for each airline). The method computes the optimal transfer pricing and, at the same time, optimizes the quantity of seats (the booking limits). The solution results in a strong Nash equilibrium, which incorporate both the transfer prices and booking limits. We describe the transfer pricing process using an ergodic, finite and continuous-time Markov game model for multiple players. The revenue of each airline in the supply chain will depend on the number of flight transfers and the transit time of the passenger at the airports: the longer the time to the final destination, the lower the price. We compute a collaborative equilibrium point, useful for understanding the resulting revenue of each member of the network. For solving the game, we employ an iterative method based on a proximal approach that involves time penalization. In our final contribution, we present results from a numerical example, which validates the proposed Markov game model and measures the benefits of the transfer pricing resource allocation.

Implications of Commodity Programs and Crop Insurance Policies for Wheat Producers

AbstractWe analyze the effects of Price Loss Coverage (PLC), Agriculture Risk Coverage (ARC), individual revenue protection insurance (RP), and Supplemental Coverage Option (SCO) on the RP coverage level, certainty equivalent, and program payments. The model is calibrated to a representative wheat farm in Mitchell County in Kansas to analyze the effects of various policies. The result highlights that when insurance is framed as an investment, cumulative prospect theory predicts farmers’ coverage decisions accurately at 70%. ARC or PLC program increases the RP coverage level to 75%, but PLC and SCO jointly decrease the RP coverage level to 70%.