Search

In this paper, a four-dimensional competition model, driven by the Riesz–Caputo operator, is established. Then, the presented model's uniqueness, existence, and stability are discussed. After that, the model is applied to describe the profit competition between Egyptian banks. Using the Hamiltonian definition of optimal control, we set a control strategy for banks' profits during crises as a pre-step measure to counteract their negative impact. Finally, the model is solved numerically using an extended Adams–Bashford scheme. The valid data between the end of 2016 and 2020 are used for numerical simulations, while the data between the end of 2021 and 2022 are used for prediction measurements. From the results, it can be seen that the COVID-19 crisis resulted in a sudden decrease in banks' profits during 2020, and if there were a control system enabled, it could have compensated for this decrease. [ABSTRACT FROM AUTHOR]

In this paper, a four-dimensional competition model, driven by the Riesz–Caputo operator, is established. Then, the presented model’s uniqueness, existence, and stability are discussed. After that, the model is applied to describe the profit competition between Egyptian banks. Using the Hamiltonian definition of optimal control, we set a control strategy for banks’ profits during crises as a pre-step measure to counteract their negative impact. Finally, the model is solved numerically using an extended Adams–Bashford scheme. The valid data between the end of 2016 and 2020 are used for numerical simulations, while the data between the end of 2021 and 2022 are used for prediction measurements. From the results, it can be seen that the COVID-19 crisis resulted in a sudden decrease in banks’ profits during 2020, and if there were a control system enabled, it could have compensated for this decrease.

Competition between times series often arises in sales prediction, when similar products are on sale on a marketplace. This article provides a model of the presence of cannibalization between times series. This model creates a "competitiveness" function that depends on external features such as price and margin. It also provides a theoretical guaranty on the error of the model under some reasonable conditions, and implement this model using a neural network to compute this competitiveness function. This implementation outperforms other traditional time series methods and classical neural networks for market share prediction on a real-world data set. Moreover, it allows controlling underprediction, which plagues traditional forecasts models. [ABSTRACT FROM AUTHOR]

The article presents research on the impact of competition and demand dependencies on category management (CM). Topics include a competition framework reconciling cross-sectional breadth with longitudinal depth, the concerns of category managers regarding best pricing strategies, sales and profits associated with such strategies, and which brands exert competitive impact on one another, and the use of a dynamic, parsimonious description of competitive effects in category management.

Developing the electricity market at the distribution level can facilitate the energy transactions in distribution networks with a high penetration level of distributed energy resources (DERs) and microgrids (MGs). However, the lack of comprehensive information about the marginal production cost of competitors leads to uncertainties in the optimal bidding strategy of participants. The electricity demand within the network and the price in the wholesale electricity market are two other sources of the uncertainties. In this paper, a day-ahead-market-based framework for managing the energy transactions among MGs and other participants in distribution networks is introduced. A game-theory-based method is presented to model the competition and determine the optimal bidding strategy of participants in the market. Robust optimization technique is employed to capture the uncertainties in the marginal cost of competitors. Additionally, the uncertainties in demand are modeled using a scenario-based stochastic approach. The results obtained from case studies reveal the merit of considering competition modeling and uncertainties.

This paper studies some quantitative aspects of the energy transition in Germany, the Energiewende , which envisages the complete abandonment of nuclear power and a strong reliance on photovoltaic and wind energy for electricity provision. The major aim is to shed light on, and measure with indirect tools, the possible social effects on competition and substitution dynamics characterizing such transition. In doing so, an analysis on the innovation diffusion framework is proposed through the application of two diffusion models for a duopolistic competition, unrestricted and standard UCRCD, to the annual time series of consumption of nuclear and renewables (wind and solar energy) in Germany, in order to test empirically the presence of such substitution effect. The obtained results confirm this conjecture and show that renewables have exerted a significant and measurable effect in determining the observed decline of nuclear power consumption. In particular we find that the diffusion of renewables – wind and solar – is characterized by a high within word-of-mouth, testifying the widespread belief of Germans towards the energy transition, while the parallel diffusion of nuclear power is characterized by a highly negative cross word-of-mouth, due to the competing role exerted by renewables. [ABSTRACT FROM AUTHOR]

Highlights: [•] A model to simulate population fitness in competitive environments is proposed. [•] Consumption, accumulation and use of resources over a period of time are followed. [•] Resource competition lowers fitness even in case of intraspecific competition. [•] Multiple limiting resources can improve fitness. [•] Multiple limiting resources can enable interspecific coexistence. [Copyright &y& Elsevier]

Abstract: A promising broadband business opportunity is the exploitation of the physical resources owned by municipalities and utility-based firms. In this study, the new broadband business opportunities owned by these authorities are analyzed through the development of a decision analysis model. The proposed model analyzes the broadband business into stages, integrates real options and game theory and provides business equilibrium in terms of the time of entry in the market, quantity offer and price definition. Finally, a real world case study is discussed showing how the model can be applied. [Copyright &y& Elsevier]