The Impact of Risk Attitude on the Optimal Compensation Plan in a Multi-product Situation

This paper examines the role of uncertainty and risk in determining the optimal commission rates a company should choose for each product of a salesman's product line. We assume that sales for each product are a stochastic function of the time (sales effort) allocated to that product. When sales are assumed to be deterministic, we achieve optimality when each product's commission is the same fraction of its gross margin. However, we determine here that when sales are stochastic this may no longer be true. Optimality conditions require explicit consideration of the utility function of the salesman and the moments of the sales response function.     

多产品销售薪酬机制的最优提成率研究

多产品销售的提成率由于其直接影响销售人员的精力投入和分配，一直是销售人员薪酬合同设计的焦点。以往最优提成率研究没有区分环境因素和销售努力对销售量的影响。本文运用代理理论设计了一种基于销售人员对产品销售的贡献的多产品销售合同模型，论证了该合同具有激励销售人员努力销售和使其如实上报定额的特性，并对多产品销售相对独立的情况下销售提成率设置进行了分析，推出了各产品提成率与销售反应参数之间的关系特点，提出了一些指导性结论。     

产品销售相关环境下的提成率研究

以往多产品销售的最优提成率研究多基于多产品销售相互独立的假设之上。本文将一种多产品销售的合同模型拓展到产品销售相互影响的环境中,对不同的销售相关性情况下销售提成率的设置进行了分析,推出了不同情况下各产品提成率之间的关系特点和指导性结论。最后研究了当厂商兼顾短期利润和长期利润时对主副产品销售提成率的影响,提出了根据产品所处生命周期的不同阶段,用价值权重向量来动态调整、优化负责销售主、副产品的销售人员薪酬合同参数设计的方法。     

Sales Commission for Multiproduct Sales Forces

In the early 1970s several papers computed commission rateswith the criterion that they be chosen so that the optimal timeallocations for salesmen were the same as the optimal timesfor the firm. Recent papers have considered a principal-agentmodel for a single-product firm in which the firm sets commissionrates knowing how the sales force will allocate time for anygiven rates. These papers assume that the probability distributionof sales is a function of sales effort. In this paper, we alsoconsider a principal-agent model, but for deterministic salesof a multiproduct firm. A computational procedure is illustrated.     

Setting Commission Rates for the Control of the Salesperson's Client-prospect Effort Allocation

The literature on setting optimal commission rates for decentralized controls over salespeople's time allocations has used the sales of various product lines as the relevant selling activities. When the time allocation is between calls to prospects versus customers, the problem should account for specific aspects, such as: (1) the conversion pattern of prospects for the various product lines; (2) the attrition rate in the sales force; (3) the salespeople's attitudes toward delayed income. These variables recognize that several calls over some period of time are typically needed for converting prospects, and that salespeople will be able to cash commissions only at the conversion time and provided they are still in charge of the same accounts. Using a simple Markovian structure, this paper shows that under typical conditions, commissions on sales to prospects during the conversion period should always be larger than commissions on sales to customers. Managerial implications and implementation issues are discussed.     

Optimal Salesmen's Compensation Plans: A Multiperiod Approach

Conditions to induce an income maximizing salesman to allocate his time among product lines so as to maximize the firm's long-run profits are derived. These conditions highlight the need to take explicitly into account the carryover effects of salesmen's activities in determining the relative importance of the commission rates to be paid for the various product lines.     

A dual control problem and application to marketing

The general approach to adaptive and dual control is to formulate an optimal stochastic control problem. However, for such an approach only mathematical representations of the solution are available which allow little insight into the structure of the optimal controller. Here, an alternative deterministic approach is presented based upon determining a control in which a disturbance attenuation function remains bounded for all allowable (L₂ functions) disturbances. The disturbance attenuation function is composed of the ratio of an L₂ function of the desired outputs over an L₂ function of the disturbance inputs. This disturbance attenuation problem is converted to a differential game. For this game, the optimal control law, in a closed-form, is obtained by performing a minmax operation with respect to a quadratic cost function subjected to a bilinear system. The resulting controller is time-varying and depends nonlinearly on the state and the parameter estimates vector, and on an associated Riccati-type matrix. We provide insights into the structure of the resulting dual controller and illustrate the method by two examples. One of the examples is an application to marketing, to set promotional spending of a company, considering that the effect of promotional effort on sales is unknown.     

Dividend Maximization when Cash Reserves Follow a Jump-diffusion Process

This paper deals with the dividend optimization problem for an insurance company, whose surplus follows a jump-diffusion process. The objective of the company is to maximize the expected total discounted dividends paid out until the time of ruin. Under concavity assumption on the optimal value function, the paper states some general properties and, in particular, smoothness results on the optimal value function, whose analysis mainly relies on viscosity solutions of the associated Hamilton-Jacobi-Bellman （HJB） equations. Based on these properties, the explicit expression of the optimal value function is obtained. And some numerical calculations are presented as the application of the results.     

Fair vs Optimal Salesmen's Compensation Plans

This paper suggests that a "fair" compensation plan (i.e. a compensation plan which remunerates salesmen proportionally to their efforts and competence) should include commissions on sales and bonuses pending on sales increases over a reference period. It also shows that under general conditions, a straight commission plan is not a fair compensation structure to the salesmen. Finally, it discusses the conditions under which the proposed fair compensation structure can lead to a jointly optimal allocation of a salesman's time among selling activities.     

New product launch decisions with robust optimization

We consider a problem where a company must decide the order in which to launch new products within a given time horizon and budget constraints, and where the parameters of the adoption rate of these new products are subject to uncertainty. This uncertainty can bring significant change to the optimal launch sequence. We present a robust optimization approach that incorporates such uncertainty on the Bass diffusion model for new products as well as on the price response function of partners that collaborate with the company in order to bring its products to market. The decision-maker optimizes his worst-case profit over an uncertainty set where nature chooses the time periods in which (integer) units of the budgets of uncertainty are used for worst impact. This leads to uncertainty sets with binary variables. We show that a conservative approximation of the robust problem can nonetheless be reformulated as a mixed integer linear programming problem, is therefore of the same structure as the deterministic problem and can be solved in a tractable manner. Finally, we illustrate our approach on numerical experiments. Our model also incorporates contracts with potential commercialization partners. The key output of our work is a sequence of product launch times that protects the decision-maker against parameter uncertainty for the adoption rates of the new products and the response of potential partners to partnership offers.     

Dynamic Pricing via Dynamic Programming<Superscript>1</Superscript>

This article specifies an efficient numerical scheme for computing optimal dynamic prices in a setting where the demand in a given period depends on the price in that period, cumulative sales up to the current period, and remaining market potential. The problem is studied in a deterministic and monopolistic context with a general form of the demand function. While traditional approaches produce closed-form equations that are difficult to solve due to the boundary conditions, we specify a computationally tractable numerical procedure by converting the problem to an initial-value problem based on a dynamic programming formulation. We find also that the optimal price dynamics preserves certain properties over the planning horizon: the unit revenue is linearly proportional to the demand elasticity of price; the unit revenue is constant over time when the demand elasticity is constant; and the sales rate is constant over time when the demand elasticity is linear in the price. ¹We acknowledge professor robert e. kalaba for initiating this work and suggesting solution methods.     

A Travelling Salesman Model for the Sequencing of Duties in Bus Crew Rotas

The paper addresses one aspect of the rostering problem posed to the public transport company operating in Porto, Portugal. The specific problem dealt with in this paper is that of sequencing the duties within each rota (rotating schedule) so as to minimize the variance of the rest periods between successive duties while satisfying constraints on their minimum value. This problem is formulated as a travelling salesman problem. Solutions derived from two heuristics are compared with the optimal ones.     

Dynamic pricing of inventory/capacity with infrequent price changes

We consider a problem of dynamically pricing a single product sold by a monopolist over a short time period. If demand characteristics change throughout the period, it becomes attractive for the company to adjust price continuously to respond to such changes (i.e., price-discriminate intertemporally). However, in practice there is typically a limit on the number of times the price can be adjusted due to the high costs associated with frequent price changes. If that is the case, instead of a continuous pricing rule the company might want to establish a piece-wise constant pricing policy in order to limit the number of price adjustments. Such a pricing policy, which involves optimal choice of prices and timing of price changes, is the focus of this paper.We analyze the pricing problem with a limited number of price changes in a dynamic, deterministic environment in which demand depends on the current price and time, and there is a capacity/inventory constraint that may be set optimally ahead of the selling season. The arrival rate can evolve in time arbitrarily, allowing us to model situations in which prices decrease, increase, or neither. We consider several plausible scenarios where pricing and/or timing of price changes are endogenized. Various notions of complementarity (single-crossing property, supermodularity and total positivity) are explored to derive structural results: conditions sufficient for the uniqueness of the solution and the monotonicity of prices throughout the sales period. Furthermore, we characterize the impact of the capacity constraint on the optimal prices and the timing of price changes and provide several other comparative statics results. Additional insights are obtained directly from the solutions of various special cases.     

Modelling imperfect advance demand information and analysis of optimal inventory policies

We consider an inventory control problem where it is possible to collect some imperfect information on future demand. We refer to such information as imperfect Advance Demand Information (ADI), which may occur in different forms of applications. A simple example is a company that uses sales representatives to market its products, in which case the collection of sales representatives’ information as to the number of customers interested in a product can generate an indication about the future sales of that product, hence it constitutes imperfect ADI. Other applications include internet retailing, Vendor Managed Inventory (VMI) applications and Collaborative Planning, Forecasting, and Replenishment (CPFR) environments. We develop a model that incorporates imperfect ADI with ordering decisions. Under our system settings, we show that the optimal policy is of order-up-to type, where the order level is a function of imperfect ADI. We also provide some characterizations of the optimal solution. We develop an expression for the expected cost benefits of imperfect ADI for the myopic problem. Our analytical and empirical findings reveal the conditions under which imperfect ADI is more valuable.     

Service outsourcing under co-opetition and information asymmetry

Co-opetition refers to the phenomenon that firms simultaneously cooperate and compete in order to maximize their profits. This paper studies the contracting for an outsourcing supply chain (a user company vs. a service provider) in the presence of co-opetition and information asymmetry. The user company outsources part of his service capacity at a discount price to the service provider for sale. The service provider charges a commission for doing outsourcing work and competes with the user company for the service capacity to satisfy their respective demands. We solve for the service provider’s optimal commission decision and the user company’s optimal outsourcing decisions (outsourcing volume and price discount) when the user company has private information about his service capacity. Specifically, we highlight the following observations. For the service provider, a menu of two-part tariffs that consist of a fixed commission and a per-volume commission can reveal the true type of the user company’s capacity; the user company’s optimal outsourcing proportion is quasi-convex and the optimal price discount is non-decreasing in his capacity volume, which is counterintuitive.     

Optimal Product Attributes in Single Choice Models

Product positioning is concerned with the determination of new product attributes such that certain objectives can be met. Recently, Zufryden proposed a model for optimal product positioning with respect to sales. It relies on the single choice assumption, i.e. consumers choose that product closest to their ideal product perceptions. To improve solvability, Zufryden suggests to solve his model via an approximate procedure, called ZIPMAP. This procedure is compared with an exactly optimising algorithm for the same problem, called PROPOSAS. Comparisons are drawn with respect to the solution values of the objective functions and the CPU-time requirements. The results indicate a superiority of PROPOSAS for a vast number of problem types.     

A numerical method to approximate optimal production and maintenance plan in a flexible manufacturing system

The simultaneous planning of the production and the maintenance in a flexible manufacturing system is considered in this paper. The manufacturing system is composed of one machine that produces a single product. There is a preventive maintenance plan to reduce the failure rate of the machine. This paper is different from the previous researches in this area in two separate ways. First, the failure rate of the machine is supposed to be a function of its age. Second, we assume that the demand of the manufacturing product is time dependent and its rate depends on the level of advertisement on that product. The objective is to maximize the expected discounted total profit of the firm over an infinite time horizon. In the process of finding a solution to the problem, we first characterize an optimal control by introducing a set of Hamilton–Jacobi–Bellman partial differential equations. Then we realize that under practical assumptions, this set of equations can not be solved analytically. Thus to find a suboptimal control, we approximate the original stochastic optimal control model by a discrete-time deterministic optimal control problem. Then proposing a numerical method to solve the steady state Riccati equation, we approximate a suboptimal solution to the problem.     

Note on inventory model with a mixture of back orders and lost sales

Competitiveness is an important means of determining whether a company will prosper. Business organizations compete with one another in a variety of ways. Among these competitive methods are time and cost factors. The purpose of this paper is to examine the inventory models presented by Padmanabhan and Vrat [International Journal of Systems Sciences 21 (1990) 1721] with a mixture of back orders and lost sales. We develop the criterion for the optimal solution for the total cost function. If the criterion is not satisfied, this model will degenerate into one cycle inventory model with a finite inventory period. This implies an extension of shortage period as long as possible to produce lower cost. However, we know that time is another important factor in company competitiveness. Customers will not indefinitely wait for back orders. A tradeoff will be made between the two most important factors; time and cost. The minimum total cost is evaluated under the diversity cycle time and illustrations are applied to explain the calculation process. This work provides a reference for decision-makers.     

Scheduling vessels and container-yard operations with conflicting objectives

We consider the problem of coordinating the operations of two supply chain partners: a foreign shipping company and a domestic port. The two partners have conflicting business objectives, and the issue is to determine the optimal cycle time, by which the shipping company removes the empty containers from the domestic port, so that the joint profit of the two partners is maximized. The domestic port prefers a shorter cycle time to mitigate its empty container accumulation and land use problems, while the shipping company wishes a longer cycle time to save its expensive vessel capacities. We propose an iterative procedure to search for this optimal cycle time. In each iteration, a candidate cycle time is evaluated by solving a deterministic vessel scheduling problem and a stochastic container-yard capacity optimization problem. We prove the properties of the vessel scheduling problem, derive the optimality condition under which the vessel scheduling problem can be decomposed, and show that the profit function of the domestic port is convex and thus the optimal container-yard capacity can be determined efficiently. Empirical observations on the algorithm computational performance collected from over 300 randomly generated test cases under various problem settings are reported.     

Inventory policy for products with price and time-dependent demands

This paper investigates the problem of jointly determining the order size and optimal prices for a perishable inventory system under the condition that demand is time and price dependent. It is assumed that a decision-maker has the opportunity to adjust prices before the end of the sales season to influence demand and to improve revenues. A mathematical model is developed to find the optimal number of prices, the optimal prices and the order quantity. Analytical results show that a stationary solution to the Kuhn–Tucker necessary conditions can be found and it is shown to be the optimal solution. The analytical results lead us to derive a solution procedure for determining the optimal order size and prices.