Narrow Results

This paper studies a problem of dynamic pricing faced by a retailer with limited inventory, uncertain about the demand rate model, aiming to maximize expected discounted revenue over an infinite time horizon. The retailer doubts his demand model which is generated by historical data and views it as an approximation. Uncertainty in the demand rate model is represented by a notion of generalized relative entropy process, and the robust pricing problem is formulated as a two-player zero-sum stochastic differential game. The pricing policy is obtained through the Hamilton-Jacobi-Isaacs (HJI) equation. The existence and uniqueness of the solution of the HJI equation is shown and a verification theorem is proved to show that the solution of the HJI equation is indeed the value function of the pricing problem. The results are illustrated by an example with exponential nominal demand rate.

The manager is responsible for the operations of a distribution center (DC) and multiple retail outlets selling a seasonal product. Initially, the DC keeps the inventory, which is allocated to the outlets in the season. There are inventory holding costs at the DC and the outlets; variable shipment cost for transferring inventory from the DC; fixed ordering cost and shortage cost at an outlet. Exact demand at each outlet is a decreasing function of price. To maximize the expected profit of the season, the manager needs to determine the markdown prices for retail outlets and quantity of inventory allocated to them. The problem can be modeled as a dynamic program (DP) which takes too heavy computational effort to solve. We develop a DP-based heuristic for solving the problem. The heuristic takes light computational effort and yet has good accuracy. Insights streamlining the markdown operations are deduced from the numerical results.

Railway passenger transportation plays a fundamental role in China, reasonable revenue is the guarantee of railway's regularly development such as equipment replacement, technology enhancement, etc. Although many studies on the railway revenue models have been conducted, there is a lack of effective modeling which considers the multiple trains and the multiple levels of seats in real operation. Aiming to improve the revenue of railway transportation industry, this paper proposes a new optimization method for the train seat inventory control problem with the consideration of the multiple trains and the multiple levels of seats. As the in-depth research of this problem, an integer linear programming model is formulated which aims to maximize the total revenue of rail industry. The commercial software MATLAB with CPLEX solver is employed to obtain the approximate optimal solutions. The effectiveness and performance of the proposed approaches are testified by two examples implemented on a simple railway corridor and Wuhan–Guangzhou high-speed railway corridor. Moreover, sensitivity analysis experiments are given to explore the impact on the revenue if the model parameters are changed.

We investigate how Korean officers manage revenue and earnings to achieve cognitive reference points (round up). In Korea, revenue has traditionally served as one of the key financial statement figures. Thus, we study revenue management around cognitive reference points both in isolation and to influence earnings around cognitive reference points through a chain effect. Our study compares the distributions of the second (from the left) and first digits in revenue and various proxies for earnings with their corresponding Benford distributions (Benford, 1938). Also, we perform a logistic regression analysis and compute probabilities based on this analysis. The results show that revenue observations have more first digit 1’s and second digit 0’s and fewer first and second digits 9’s than under a Benford distribution. Korean managers appear to round up revenues with high second digits to improve first digits. In addition, we document that revenue observations with second digits of 0 are associated with higher proportions of positive earnings (gross margin and earnings from operations) with second digits of 0. This suggests that Korean firms simultaneously convert the second digits of revenue and earnings to improve the first digits of those numbers. Results from additional tests convey more upward management of the second digit of revenue for firms that have characteristics that indicate higher ex ante benefits and stronger ex post effects from revenue management.

We present a stochastic optimization model for hotel revenue management with multiple-day stays under an uncertain environment. Since a decision maker may face several scenarios when renting out rooms, we use a semi-absolute deviation model to measure the risk of hotel revenue, and only consider the risk of falling below the expected revenue. The method proposed in this paper can be changed to a linear programming model by applying linearization techniques. Some examples are presented to illustrate the efficiency of this method.

Cruising for leisure purposes, whether on the ocean, along coasts or rivers, has demonstrated consistent growth as a tourism activity. Cruising can be divided into a number of sub-markets, within which most supply is oligopolistic in nature, and concentration is increasing. Cruise lines pursue various strategies, but it is shown that pricing is not the most significant, as demand, cruise products and prices are amorphous. Unlike fixed-location tourism, cruising is a footloose product, where factor inputs may be sourced globally and cruise lines may have little connection with port destinations served on itineraries. Operationally, economies of scale, capacity and revenue management are important tools for operators, as vessel sizes increase and operational management and marketing become more sophisticated. The impacts on local and national economies are in many ways analogous to those of tourism in general.

Capacity control is a classical revenue management problem. Researchers and practitioners have proposed many mathematical models including dynamic programs for solving the capacity control problem. In this paper, we present an equivalent reformulation for the dynamic programming model for the capacity control problem in the single-leg flight setting.