Strategic delegation in a differentiated duopoly with asymmetric costs

This paper examines the impact of product differentiation on strategic delegation in a Cournot duopoly with asymmetric costs. We show that compared with the no-delegation case, when both firms delegate, although the cost-inefficient firm always gets worse, the efficient firm gets better when the degree of product differentiation is sufficiently low and/or the cost asymmetry is sufficiently large. Moreover, as products become closer substitutes, the efficient firm always makes its manager more aggressive, however, the inefficient firm may make its manager less aggressive.     

Flexibility in a Stackelberg leadership with differentiated goods

We study the effects of product differentiation in a Stackelberg model with demand uncertainty for the first mover. We do an ex-ante and ex-post analysis of the profits of the leader and of the follower firms in terms of product differentiation and of the demand uncertainty. We show that even with small uncertainty about the demand, the follower firm can achieve greater profits than the leader, if their products are sufficiently differentiated. We also compute the probability of the second firm having higher profit than the leading firm, subsequently showing the advantages and disadvantages of being either the leader or the follower firm.     

A differential oligopoly game with differentiated goods and sticky prices

We investigate a dynamic oligopoly game where goods are differentiated and prices are sticky. We study the open-loop and the closed-loop memoryless Nash equilibrium, and show that the latter equilibrium entails a larger level of steady state production as compared to the former; both equilibria entail a larger level of production in steady state than the static game. We also study the effects of price stickiness and product differentiation upon the steady state equilibrium allocation and profits. The per-firm equilibrium output is increasing in both product differentiation and price stickiness, while profits are increasing in both product differentiation and the speed of price adjustment. The steady state social welfare monotonically increases in the speed of price adjustment, and the overproduction entailed by dynamic competition has beneficial effect from a social standpoint.     

Optimal pricing and donation policy for fresh goods

This paper studies a socially responsible food-retailer’s operational planning problem for a continuously deteriorating inventory over two periods with the consideration of donation and quality-sensitive customers. Each year, millions of tonnes of food are wasted causing economic, environmental, and social misfortunes, while at the same time millions are undernourished. Besides expired items, edible foods are often deliberately disposed of to attract quality-sensitive consumers. We address this issue by presenting an optimization model that incorporates a retailer’s corporate social responsibility act, in the form of charitable donations, and makes use of the internet of things (IoT)-enabled condition tracking technologies to accurately estimate the effective (true) quality of the goods and its impacts on consumer demand. We formulate a quality-dependent newsvendor problem (QDNP) to determine the stocking quantity and the regular price of the goods at the beginning of the selling season, and the second-period price and donation policy at the end of the first period. The optimal donation policy at the end of the first period depends on the quality (time to expiration), on-hand inventory, and donation reward. Moreover, for a given inventory level, expected food waste is always greater in the absence of donations. QDNP outperforms the no-donation model, particularly when the uncertainty is high and/or the length of the second period is short. Interestingly, the two models react to an increase in uncertainty oppositely: QDNP orders more to alleviate future shortages, whereas, no-donation policy orders less to avoid future disposal costs at the end of the selling season.     

Two-phase pricing and inventory management for deteriorating and fashion goods under trade credit

This study models a finite horizon inventory problem for deteriorating and fashion goods under trade credit and partial backlogging conditions. Demand may vary with price or time. The supplier can extend credit to the retailer. As a result, the retailer does not have to pay for goods immediately upon acquiring them, and can instead earn interest on the retail price of the goods between the time they are sold and the end of the credit period. The proposed model considers two-phase pricing and inventory decisions. In other words, it determines both the optimal prices and the lengths of the in-stock and stock-out period. This paper is the first to consider different price decisions for in-stock and stock-out periods under trade credit. We develop an algorithm to determine the optimal pricing and replenishment strategy while still maximizing the total profit. Further, this study shows that the proposed two-phase pricing strategy is superior to a one-phase pricing strategy in terms of profit maximization. Computational analysis illustrates the solution procedures and the impacts of the related parameters on decisions and profits. The results of this study can serve as references for business managers or administrators.     

Optimal policy for inventory systems with capacity commitment and fixed ordering costs

This paper investigates a single-product, periodic-review, non-stationary inventory system with total maximum capacity commitment and fixed ordering costs over a finite planning horizon. We characterize the optimal ordering policy as a state-dependent ($s,S$) policy whose parameters only depend on the sum of the net inventory and the remaining capacity. We show that such policy can degenerate into two simple policies in two special cases respectively. We also derive bounds on parameters of the optimal ordering policy.     

Optimization of risk policy and dividends with fixed transaction costs under interest rate

In this paper, we consider the dividend optimization problem for a financial corporation with transaction costs. Besides the dividend control, the financial corporation takes proportional reinsurance to reduce risk and the surplus earns interest at the constant force ρ>0. Because of the presence of fixed transaction costs, the problem becomes a mixed classical-impulse stochastic control problem. We solve this problem explicitly and construct the value function together with the optimal policy.     

Strategic stability in repeated signaling games

This paper extends selection rules now used in the signaling literature (such as the Intuitive Criterion of Cho and Kreps (1987)) to a class of repeated signaling games, where each player can exchange the messages conditioned on his private information. STABAC (STAbility and BACkward induction) is defined as a procedure whereby forward induction arguments (Kohlberg and Mertens (1986)) are applied in combination with the backward induction process. We specify the conditions under which any strategically stable outcome of a repeated signaling game includes an equilibrium that induces a stable equilibrium outcome in every subform, whence STABAC does not eliminate any stable outcome of the repeated signaling game.     

Optimal myopic policy for a stochastic inventory problem with fixed and proportional backorder costs

In this paper, we consider a single product, periodic review, stochastic demand inventory problem where backorders are allowed and penalized via fixed and proportional backorder costs simultaneously. Fixed backorder cost associates a one-shot penalty with stockout situations whereas proportional backorder cost corresponds to a penalty for each demanded but yet waiting to be satisfied item. We discuss the optimality of a myopic base-stock policy for the infinite horizon case. Critical number of the infinite horizon myopic policy, i.e., the base-stock level, is denoted by S. If the initial inventory is below S then the optimal policy is myopic in general, i.e., regardless of the values of model parameters and demand density. Otherwise, the sufficient condition for a myopic optimum requires some restrictions on demand density or parameter values. However, this sufficient condition is not very restrictive, in the sense that it holds immediately for Erlang demand density family. We also show that the value of S can be computed easily for the case of Erlang demand. This special case is important since most real-life demand densities with coefficient of variation not exceeding unity can well be represented by an Erlang density. Thus, the myopic policy may be considered as an approximate solution, if the exact policy is intractable. Finally, we comment on a generalization of this study for the case of phase-type demands, and identify some related research problems which utilize the results presented here.     

A genetic algorithm for optimizing defective goods supply chain costs using JIT logistics and each-cycle lengths

The competitive environment of global markets has forced many manufacturers to select the most appropriate supply chain network (SCN) for reduction of total costs and wasted time. Cost reduction and selection of the appropriate length of each period are two important factors in the competitive market that are often not addressed comprehensively by researchers. In our study, we proposed genetic algorithms (GAs) for optimising a novel mathematical model of the defective goods supply chain network (DGSCN). In the proposed model, we assumed that all imperfect-quality products are not repairable, whereas those considered as scrap are directly sold to customers at a low price. The objective of the proposed model is to minimise the costs of production, distribution, holding and backorder. In addition to minimising the costs, the model can determine the economic production quantity (EPQ), the appropriate length of each cycle (ALOEC) and the quantities of defective products, scrap products and retailer shortages using Just-In-Time logistics (JIT-L). We used the GAs and a Cplex solver with probability parameters and various dimensions for validation of the studied model in real-life situations, and we compared the outputs to demonstrate the performance of the model. Additionally, to identify the appropriate length of each cycle (ALOEC), we needed to solve the model using exact parameters and same dimensions and prefer to use Lingo for this application.     

On the optimality of a full-service policy for a queueing system with discounted costs

We provide weak sufficient conditions for a full-service policy to be optimal in a queueing control problem in which the service rate is a dynamic decision variable. In our model there are service costs and holding costs and the objective is to minimize the expected total discounted cost over an infinite horizon. We begin with a semi-Markov decision model for a single-server queue with exponentially distributed inter-arrival and service times. Then we present a general model with weak probabilistic assumptions and demonstrate that the full-service policy minimizes both finite-horizon and infinite-horizon total discounted cost on each sample path.     

An inventory model for non-instantaneous deteriorating items with quadratic demand rate and shortages under trade credit policy

noindent In this paper, we propose an appropriate inventory model for non-instantaneous deteriorating items over quadratic demand rate with permissible delay in payments and time dependent deterioration rate. In this model, the completely backlogged shortages are allowed. In several existing results, the authors discussed that the deterioration rate is constant in each cycle. However, the deterioration rate of items are not constant in real world applications. Motivated by this fact, we consider that the items are deteriorated with respect to time. To minimize the total relevant inventory cost, we prove some useful theorems to illustrate the optimal solutions by finding an optimal cycle time with the necessary and enough conditions for the existence and uniqueness of the optimal solutions. Finally, we discuss the numerical instance and sensitivity of the proposed model.     

Determination of the optimal trade credit policy: a supplier-Stackelberg model

This paper considers a two-echelon supply chain, where one supplier sells through a retailer a product with a stable market demand. We focus on how the supplier induces the retailer through trade credit to order more to reduce his/her own inventory-related cost. Under a ‘supplier-Stackelberg’ setting, we provide the supplier with the method of determining two trade credit scenarios: unconditional and conditional trade credit. We show that the unconditional trade credit scenario is always beneficial to the retailer but harmful to the supplier in most situations, while the conditional trade credit scenario is always beneficial to both parties. In addition, we specify the conditions under which the provision of unconditional trade credit is beneficial to the supplier. The three insights obtained in this paper are the following: (i) When the retailer’s per-unit opportunity cost is less than his/her per-unit opportunity gain, unconditional trade credit can induce the retailer to order less instead of more. (ii) If the supplier offers the retailer unconditional trade credit, the length of trade credit offered will have an upper bound. (iii) A well-designed conditional trade credit policy can realize a win-win outcome but also enables the supplier to occupy all the savings in the channel's cost incurred by trade credit, but any unconditional trade credit policy does not.     

Integrated inventory models considering the two-level trade credit policy and a price-negotiation scheme

This paper develops the integrated inventory models with permissible delay in payment, in which customers’ demand is sensitive to the buyer’s price. The models consider the two-level trade credit policy in the vendor–buyer and buyer–customer relationships in supply chain management. A simple recursive solution procedure is proposed for the integrated models to determine the buyer’s optimal pricing and production/order strategy. Although the total profit from the buyer and vendor increases together, the buyer’s share lessens. To compensate the buyer’s loss due to the cooperative relationship, a negotiation system is presented in order to allocate the profit increase to the vendor and buyer to determine the pricing and production/order strategy. A numerical example and sensitivity analysis are provided to illustrate the proposed model. The results indicate that the total profit from the buyer and vendor together can increase, although a price discount is given to the buyer in the proposed models.     

A continuous review replenishment–disposal policy for an inventory system with autonomous supply and fixed disposal costs

In this study, we analyze an inventory system facing stochastic external demands and an autonomous supply (independent return flow) in the presence of fixed disposal costs and positive lead times under a continuous review replenishment–disposal policy. We derive the analytical expressions of the operating characteristics of the system; and, construct the objective function to minimize the total expected costs of ordering, holding, purchasing and disposal per unit time subject to a fill rate constraint. An extensive numerical analysis is conducted to study the sensitivity of the policy parameters and the benefit of employing a policy which allows for disposal of excess stock in this setting. We model the net demand process as the superposition of normally distributed external demand and inflows, which is expressed as a Brownian motion process. Our findings indicate that the disposal option results in considerable savings even (i) in the presence of non-zero fixed disposal costs, (ii) large actual demand rates with high return ratios (resulting in small net demands) and (iii) for moderate return ratios with high demand variability.     

Style goods pricing with demand learning

For many industries (e.g., apparel retailing) managing demand through price adjustments is often the only tool left to companies once the replenishment decisions are made. A significant amount of uncertainty about the magnitude and price sensitivity of demand can be resolved using the early sales information. In this study, a Bayesian model is developed to summarize sales information and pricing history in an efficient way. This model is incorporated into a periodic pricing model to optimize revenues for a given stock of items over a finite horizon. A computational study is carried out in order to find out the circumstances under which learning is most beneficial. The model is extended to allow for replenishments within the season, in order to understand global sourcing decisions made by apparel retailers. Some of the findings are empirically validated using data from U.S. apparel industry.     

Collateral in banking policy: On the possibility of signaling

In this paper we study the validity of the assertion that collateral is in a position to signal the degree of borrowers’ riskiness. We use a framework in which the cash flow from the risky project is described by means of a continuous density and projects are classified by second-order stochastic dominance. We show that if collateral is assumed bounded by the initial project outlay the positive role of collateral, namely truthfully conveying the private information about the project risk by the collateral amount, can no longer be ensured.     

Coalition formation with local public goods and group-size effect

Many public goods that are provided by coalitions have a group-size effect. Namely, people prefer to consume a public good in a larger coalition. This paper studies local public goods games with anonymous and separable group-size effect. The core is nonempty when coalition feasible sets are monotonic and players’ preferences over public goods satisfy a condition called cardinal connectedness. Moreover, a core allocation consists of connected coalitions.     

Manipulation games in economies with indivisible goods

In this paper we study the strategic aspects of the No-Envy solution for the problem of allocating a finite set of indivisible goods among a group of agents when monetary compensations are possible. In the first part of the paper we consider the case where each agent receives, at most, one indivisible good. We prove that the set of equilibrium allocations of any direct revelation game associated with a subsolution of the No-Envy solution coincides with the set of envy-free allocations for the true preferences. Under manipulation all the subsolutions of the No-Envy solution are equivalent. In the second part of the paper, we allow each agent to receive more than one indivisible good. In this situation the above characterization does not hold any more. We prove that any Equal Income Walrasian allocation for the true preferences can be supported as an equilibrium allocation of any direct revelation game associated with subsolutions of the No-Envy solution, but also non-efficient allocations can be supported.