Dynamic pricing for perishable items with costly price adjustments

El impacto de la fijación dinámica de precios en las percepciones de los clientes de restaurantes y en el sentimiento hacia los preciosResumenPropósitoEste estudio examina cómo la fijación dinámica de precios impacta en las percepciones de los clientes de los restaurantes y en el sentimiento hacia los precios a través de métricas de reputación en línea. Además, para profundizar en el debate sobre la fijación dinámica de precios, se propone una definición novedosa explorando las formas específicas de discriminación que pueden manifestarse en diferentes industrias.Diseño/metodología/enfoqueUtilizando un conjunto de datos exhaustivo de reseñas de restaurantes obtenidas de TripAdvisor, el estudio se centra en los restaurantes afiliados a uno de los mayores grupos de restaurantes en España. Empleamos un método cuasiexperimental (diferencias en diferencias) para estudiar cómo las estrategias de precios dinámicos influyen en las percepciones de valor de los clientes basándonos en las calificaciones numéricas. Mientras tanto, empleamos un modelo BERT en el componente textual de las reseñas para desentrañar los matices emocionales de la fijación dinámica de precios.HallazgosLos resultados no revelaron un impacto causal de las estrategias de precios dinámicos en las percepciones de los clientes. Además, el análisis de sentimiento no muestra una visión negativa aumentada después de introducir la fijación dinámica de precios en los restaurantes en comparación con el grupo de control. Contrariamente a lo que sugiere la literatura previa, nuestros hallazgos indican que la implementación de precios dinámicos no afecta negativamente las percepciones o los sentimientos de los clientes respecto a los precios en los restaurantes.Limitaciones/implicaciones de la investigaciónLa configuración cuasiexperimental del estudio presenta desafíos inherentes para establecer la causalidad que requieren una investigación más profunda utilizando entornos experimentales controlados. Sin embargo, nuestro estudio revela que los clientes de restaurantes no perciben la fijación de precios dinámica como injusta. Este hallazgo es crítico para los gerentes de restaurantes al considerar la implementación de la fijación de precios dinámica y estrategias de gestión de ingresos. Además, nuestro estudio resalta la importancia de considerar no solo las calificaciones numéricas sino también el análisis del sentimiento del cliente. Este enfoque más holístico para evaluar el impacto de las estrategias de precios puede dar a los gerentes de restaurantes una comprensión más profunda de las reacciones de los clientes. Además, se proporciona una definición de fijación de precios dinámica más rigurosa, aclarando su naturaleza y su distinción en el uso de diferentes discriminaciones de precios.Originalidad/valorEste estudio contribuye a la comprensión en evolución del impacto de las estrategias de fijación de precios dinámicos en las percepciones y sentimientos de los clientes en la industria restaurantera. Su objetivo es llenar el vacío en la comprensión de las reacciones de los clientes a los precios determinados algorítmicamente (a través de sistemas de gestión de ingresos (RMS) como DynamEat) en esta industria. La combinación de inferencia causal y análisis de sentimientos ofrece una perspectiva novedosa, arrojando luz sobre las conexiones matizadas entre la implementación de la fijación de precios dinámicos y las emociones de los clientes.

Peak reduction in decentralised electricity systems : Markets and prices for flexible planning

The study examined the effect of pricing strategies on the revenue of maize marketers in Benue State, Nigeria. A multistage and purposive sampling technique was used in selecting 400 registered maize Marketers in six Local Government Areas of the State. Primary data were collected using structured questionnaires and analyzed using descriptive and inferential statistics. The findings revealed that majority (91.7%) applied cost plus pricing strategy in marketing of maize; (87.0%) used competitive pricing strategy, while (57.1%) used value based pricing strategy. The results also showed that 56.1% adopted bundle pricing strategy; (49.4%) applied geographical pricing strategy; few marketers used dynamic pricing (16.4%), psychological pricing (6.5%), premium pricing (2.6%), penetration pricing (1.6%), and price skimming (0.5%) respectively. The findings revealed that marketers who used dynamic pricing strategy made the highest sales revenue of ₦122,484.803, marketers that used penetration pricing recorded the least sales revenue of ₦104,333.33. Evidence from the study shows that dynamic pricing strategy enhance sales revenue of maize marketers by ₦15,104.32. It was recommended that government should enhance maize marketer’s access to extension services in the state by conducting training sessions focusing on enlightening maize marketers on more profitable pricing strategies to adopt. The government should also encourage continued education among maize marketers in the state through workshops so as to enable them make informed marketing decisions.

This paper develops a preconditioning theory for the standard optimal control problem. Preconditioning is the execution of a coordinate transformation in order to increase the convergence rate of gradient based numerical algorithms. The transforming operator employed for this purpose is the square root of a symmetric positive definite matrix which is called the preconditioner. It was shown in [l] that the optimal preconditioner for nonlinear constrained mathematical programming problems is a matrix, denoted as 'H+, which is the positive definite reflection of the Hessian matrix 'H. By positive definite reflection, it is meant that matrix whose eigenvectors are identical to those of the Hessian and whose eigenvalues are the moduli of the latter's eigenvalues. It was demonstrated that the preconditioner 'H+ produces a transformed Hessian with a condition number of unity; it was further shown how H+ can be efficiently constructed from a singular value decomposition of 7-t. Since the Hessian is a function of the optimizing variables in a nonlinear problem, periodic application of the preconditioner is required for best results. Here, this preconditioning theory is extended to the standard optimal control problem using the direct approach of transcription. The optimal preconditioner, as well as suboptimal alternatives, are presented based on the Hessian of the resulting finite dimensional problem. Additionally, by allowing the discretization level to approach zero, the infinite-dimensional Hessian of the optimal control problem is obtained, which turns out to be a sparse matrix-valued hybrid surface consisting of ridges and discrete points. This is a nice geometrical result which provides great insight into the optimal control problem. It is shown for completeness, that as At -+ 0, the necessary conditions and the second differential of the mathematical programming problem converge to the necessary conditions and the second variation of the control problem. It is further shown that the second variation of the control problem has the form ;AZ~ 'HAZ, where the Hessian is a hybrid surface and Ar is an infinite-dimensional vector. For the second variation to be positive, the Hessian sur'Associate Fellow, AIAA 'Member, AIAA This paper is declared a work of the U.S. Government and is not subject to copyright protection in the United States. face must be positive definite with respect to surface multiplication, surface multiplication being the infinite-dimensional extension of matrix multiplication. Finally, it is noted that the extended theory is also valid in the indirect approach to optimal control provided a new integration implementation technique is employed, as shown in the separate work [2].

With the technical growth and the reduction of deployment cost for distributed energy resources (DERs), such as solar photovoltaic (PV), energy trading has been recently encouraged to energy consumers, which can sell energy from their own energy storage system (ESS). Meanwhile, due to the unprecedented rise of greenhouse gas (GHG) emissions, some countries (e.g., Republic of Korea and India) have mandated using a renewable energy certificate (REC) in energy trading markets. In this paper, we propose an energy broker model to boost energy trading between the existing power grid and energy consumers. In particular, to maximize the profits of energy consumers and the energy provider, the proposed energy broker is in charge of deciding the optimal demand and dynamic price of energy in an REC-based energy trading market. In this solution, the smart agents (e.g., IoT intelligent devices) of consumers exchange energy trading associated information, including the amount of energy generation, price and REC. For deciding the optimal demand and dynamic pricing, we formulate convex optimization problems using dual decomposition. Through a numerical simulation analysis, we compare the performance of the proposed dynamic pricing strategy with the conventional pricing strategies. Results show that the proposed dynamic pricing and demand control strategies can encourage energy trading by allowing RECs trading of the conventional power grid.

We consider a novel optimal control problem in which the terminal time is governed by a stopping constraint. This stopping constraint is a nonlinear equality constraint depending on the state variables, and the terminal time is defined as the first time at which this constraint is satisfied. Since the stopping constraint causes the terminal time to be an implicit function of the control, the optimal control problem we consider cannot be solved using conventional techniques. We propose a new computational approach that involves approximating the original problem by a standard optimal control problem with fixed terminal time. Our main result shows that this approximation, which depends on two adjustable parameters, can be made to arbitrarily high accuracy. On this basis, the original optimal control problem with stopping constraints can be transformed into a sequence of approximate problems, each of which can be solved readily using conventional optimal control techniques. We conclude the paper by demonstrating this approach with numerical simulations in three application areas: range maximization of a hang glider, range maximization of a hypersonic re-entry vehicle, and time-optimal control of a nuclear reactor.

In this paper, we formulate a joint dynamic pricing and freshness-keeping effort strategy for perishable products in a finite horizon. Based on the perishable nature of perishable products, this paper considers the product demand influenced by selling price, product freshness and stock level. Since the freshness level decreases with time, we assume that the freshness deteriorates exponentially. Besides, a freshness-keeping effort is introduced to reduce the deterioration rate of freshness. Our purpose is to determine the optimal joint dynamic pricing and freshness-keeping effort strategy to maximize profits. To solve the problem, the Pontryagin's maximum principle is applied. We present a numerical example in support to the theoretical results and propose the sensitivity analysis of the main parameters. In the end, some managerial guidelines are also provided. When the cost of freshness-keeping effort is high or the effect of freshness-keeping effort is low, not to adopt freshness-keeping effort is the optimal decision. However, if the cost of freshness-keeping effort is small or the effect of freshness-keeping effort is significant, adopting freshness-keeping effort is the best. In addition, managers can gain more profits by expanding market size and restraining inventory decay rate and freshness deterioration rate.

This paper constructs theoretical game models to explore the joint effects of tax rate disparity and consumers’ strategic purchasing behavior on brand’s foreign market encroachment strategy and the downstream enterprises’ pricing strategy, as well as supply chain members’ profit. Results show that (1) Under selling subsidiary encroachment, uniform pricing strategy is only adopted when strategic consumers’ patience level is relatively high and the tax rate disparity is sufficiently low. Under retail encroachment, the retailer prefers dynamic pricing strategy when strategic consumers’ patience level is relatively low, and uniform pricing strategy otherwise. (2) When dynamic pricing strategy is chosen, a larger tax rate disparity can benefit the selling subsidiary and higher strategic consumers’ patience level may benefit both the brand and the selling subsidiary. (3) When strategic consumers’ patience level is relatively low, with sufficiently large tax rate disparity, the brand would always choose retail encroachment strategy. With relatively small tax rate disparity, the brand may choose the selling subsidiary encroachment if the establishing cost is not so high, and retail encroachment otherwise. However, when strategic consumers’ patience level is relatively high, the brand may also choose selling subsidiary encroachment strategy even if the tax rate disparity is not that high, regardless of what the establishing cost is. This is probably due to retailer’s dynamic pricing strategy can bring more demand than the selling subsidiary’s uniform pricing strategy does.

Pricing is one of the main determinants of a successful carsharing business plan. Companies develop different pricing strategies to increase attractiveness, profit, and service usage. Using dynamic pricing strategies can lead to service improvement in terms of profit and better customer satisfaction. This paper presents a novel research contribution to the field of transportation policy by introducing a new framework for designing dynamic pricing strategies in carsharing operations. We develop two hybrid-pricing strategies to increase profit and user utility in car sharing and analyze the service key performance indicators. These two different hybrid-pricing strategies are based upon two different approaches: one relying on demand related information (i.e., fixed price and time-based dynamic price) and one relying on supply related characteristics (i.e., maximum profit price and availability-based dynamic price). By considering both user utility and company indicators, this model features a bi-level structure that allows for rapid implementation. The framework relies on real-world data, typically available to carsharing companies, including membership data, geographic distribution of users, fleet composition, and the location of vehicles and stations. Additionally, we propose a relocation procedure that relocates vehicles on a day-to-day adjustment process. We study the impact of these strategies in an agent-based environment capable to accurately replicate a real carsharing service that operated in the city of Munich, Germany. Once these policies are in place, results show how it is possible to increase profit and customers’ utility. Moreover, we show how an increment in profit corresponds to a reduction of the utility and vice versa. Overall, the effectiveness of the proposed hybrid-pricing strategies in improving key performance indicators such as profit and score in carsharing services is demonstrated through the positive impact of demand-based pricing combined with relocation operations, while supply-based pricing strategies were found to be ineffective in enhancing profit and booking time.

Due to its success and acceptance in the airline and hospitality industry and the growing availability of behavioral, engagement, and attitudinal consumer data, dynamic pricing strategies are gaining popularity. The purpose of this systematic literature review is to answer the research question about how do dynamic pricing strategies affect customer perceptions and behaviors to avoid negative consumer reactions. The synthesis of over 50 articles revealed eight different research streams like for example the factors moderating the impact of dynamic pricing on customer behavior, strategic purchasing behavior in response to dynamic pricing, effect of dynamic pricing on customer perception of fairness, personalized dynamic pricing (PDP) and channel differentiated pricing. To advance future research, this systematic literature review identified the six propositions for further research like for example the assessment of the efficacy of different types of communication by firms seeking to mitigate the negative impacts of dynamic pricing and the assessment of the role and relevant importance of consumers’ personal characteristics upon their perceptions of price changes. The findings of this study have a practical impact for managers and scholars. Scholars may use them to update their research agendas and managers to optimize their pricing strategies to increase revenues.

Given the importance of determining the traffic level in celebrity endorsement management and prominent impacts from strategic consumers, this paper utilizes mathematical modelling to study the optimal traffic level and pricing strategy as well as relevant influencing factors in the context of celebrity endorsement. The results show that optimal traffic level is highest under uniform high pricing strategy and lowest under uniform low pricing strategy, with that of dynamic pricing strategy lying in between. Aside from the proportion of strategic consumers, optimal pricing strategy is also determined by the joint effects of celebrity endorsement characteristics, such as the premium effect of celebrity endorsement, the market demand expansion effect, and the traffic using cost. It depends on the tradeoff between the positive effects (premium effect and market demand expansion effect) and the negative effects (endorsement fee of unit traffic) of the celebrity endorsement.

Dynamic pricing strategies for efficient inventory management with auto-correlative stochastic demand forecasting using exponential smoothing method

Reasonable price strategy is of great significance to the safe and economic operation of a microgrid. To reduce the power exchange fluctuation between the main grid and a microgrid and to enhance the profit of a microgrid, a dynamic price strategy based on modified particle swarm optimization (PSO) is proposed. Then, a multi-objective optimization model considering the income of a microgrid and load fluctuation of distribution network is presented. To validate the proposed price strategy and the optimization model, a series of numerical simulations are conducted to demonstrate their effect on the power exchange fluctuation and the profit of the microgrid. The result shows that the proposed dynamic price strategy markedly increases the profit of the microgrid and strengthen the effect on power peak shaving and valley filling compared with time-of-use(TOU) price strategy and the fixed electricity price strategy.

Discrete-time hybrid control in Borel spaces: Average cost optimality criterion

This paper studies optimal noncompetitive pricing strategies when the evolution of demand is the result of intertemporal considerations. Two different hypotheses of price expectations (myopia and perfect foresight) are treated. The major implication is that the slight modification from an instantaneous to a very fast consumer reaction may completely modify a monopolist's price strategy. More precisely, the price strategy should be volatile if the equilibrium demand is convex, independent whether the consumers act myopically or employ rational expectations. On the other hand, asynchronous dynamics (e.g., due to competitive fringe supply or different segments of demand) cannot explain even damped price oscillations. The equilibrium price strategy of the noncompetitive supplier exceeds the static rule if consumers employ myopic expectations; rational expectations may lead to prices above or below the static rule depending on the rate of discount.