Qinan Wang

Multiattribute Utility Function for a Comprehensive Health Status Classification System Health Utilities Index Mark 2

The Health Utilities Index Mark 2 (HUI:2) is a generic multiattribute, preference-based system for assessing health-related quality of life. Health Utilities Index Mark 2 consists of two components: a seven-attribute health status classification system and a scoring formula. The seven attributes are sensation, mobility, emotion, cognition, self-care, pain, and fertility. A random sample of general population parents were interviewed to determine cardinal preferences for the health states in the system. The health states were defined as lasting for a 60-year lifetime, starting at age 10. Values were measured using visual analogue scaling. Utilities were measured using a standard gamble technique. A scoring formula is provided, based on a multiplicative multiattribute utility function from the responses of 194 subjects. The utility scores are death-anchored (death = 0.0) and form an interval scale. Health Utilities Index Mark 2 and its utility scores can be useful to other researchers in a wide variety of settings who wish to document health status and assign preference scores.

Coordination mechanisms of supply chain systems

Supply chain management (SCM) has become an important management paradigm. As supply chain members are often separate and independent economic entities, a key issue in SCM is to develop mechanisms that can align their objectives and coordinate their activities so as to optimize system performance. In this paper, we provide a review of coordination mechanisms of supply chain systems in a framework that is based on supply chain decision structure and nature of demand. This framework highlights the behavioral aspects and information need in the coordination of a supply chain. The identification of these issues points out several directions of future research in this area.

Discount pricing decisions in distribution channels with price-sensitive demand

Abstract In this paper, we evaluate the effectiveness of quantity discounts and volume discounts as coordination mechanisms in distribution channels with demand that is price-sensitive. We consider a single-vendor, single-retailer, distribution channel. Demand for the product arises only at the retailer. The demand faced by the retailer is assumed to be deterministic, but price elastic. The retailer in turn buys the product from the vendor. The vendor and the retailer act independently and rationally, each maximizing their own respective profit. The equilibrium point that specifies the vendor’s and buyer’s inventory and pricing policy is determined by the solution to a Stackelberg game. We consider the cases when quantity discount and volume discount respectively are offered. We develop methods to determine the optimal discount policy for these cases. We then consider the case where both volume and quantity discounts are offered simultaneously, and develop a method to determine the optimal simultaneous discount offer. The relative performance of the alternative discount schemes is then evaluated through a numerical study. The results of the study demonstrate that the effectiveness of volume discount as a coordination mechanism is higher when the sensitivity of demand to price changes is higher. The effectiveness of quantity discount, on the other hand, is higher with lower price sensitivity of demand. Finally, the results also demonstrate that perfect coordination is achieved when volume and quantity discounts are offered simultaneously.

DISCOUNTING DECISIONS IN A SUPPLIER-BUYER RELATIONSHIP WITH A LINEAR BUYER'S DEMAND

In this paper, we analyze discounting decisions for a supplier with a group of homogeneous customers. We focus on two aspects: the gaming nature of the discount problem and the demand consideration in the process. We use a general quantity discount schedule and start with the Stackelberg equilibrium of the problem. It is shown that, for the seller to gain from quantity discount, he has to set up his quantity discount schedule such that the buyer will order more than his EOQ. Both the seller and the buyer can gain significantly from quantity discount. The incentive for discount is twofold: reducing inventory related cost and attracting more demand from the customers. In addition, quantity discount schedule can be very efficient in obtaining the maximum gain the seller and the buyer can possibly obtain together.

A three-person game theory model arising in stochastic inventory control theory

Abstract In this paper, we build a game theory model for a single-period inventory problem where each of three retailers tries to determine his optimal order quantity. Their products are substitutable and have random demands. Therefore, multiple direction demand transfers occur when one or more retailers are sold out. It is shown that, by using Nash equilibrium, optimal decision exists for each retailer when they work independently. The optimal order quantity in this case is larger than that under the newsboy problem model. This is because substitution can be a source of sales and hence a justification for inventory. In situations where some retailer may act irrationally to inflict a damage on the others, the defensive strategy for the latter is to totally ignore the existence of the irrational player. We also study the cooperation of retailers by switching excess inventory to those who have excess demand both when side payments are and are not allowed. If side payments are not allowed, secure (Nash) strategies always exist for each retailer and cooperation will reduce inventory. The latter is especially true when the depreciation of value of the item and/or inventory carrying cost are large. We give conditions for cooperation in both cases and show that although all-player cooperation is often feasible it may not always be obtainable even if side payments are allowed.

Modeling and analysis of high risk patient queues

Abstract For many medical procedures, patients face substantial risk of complication or death when treatment is delayed. When a queue is formed in such a situation, it is imperative to assess the suffering and risk faced by patients in queue and plan adequate medical capabilities in advance to address the concerns. We develop in this paper a patient queue model that considers the condition and its changes over time for a patient in a queue. The risk faced by a patient is characterized under this model as a function of the arrival rate, the service capacity and the hazard rate of the disease. This characterization provides an approach to the planning and management of medical services based on the risk faced by patients. When the condition of patients is heterogeneous, a priority patient queue model is developed to minimize the overall risk for all patients. The operational characteristics of the priority queue, particularly the risk faced by different groups of patients, are derived. Managerial issues induced by prioritization are also addressed. In general, patients of heterogeneous condition should be prioritized in as many urgency classes as possible to maximize survival.

A duopolistic model of dynamic competitive advertising

Abstract This paper proposes a differential game model of competitive advertising decisions for non-durable products by extending the Lanchester model and the Deal model of competitive advertising in the literature. The proposed model is compared empirically with the Lanchester model for model fitting and forecast accuracy. It is shown that the model is suitable for an actual market and out-performs the Lanchester model in forecast accuracy. The model provides a sensible modeling alternative to the Lanchester model for the study of dynamic competitive advertising decisions. Necessary and sufficient conditions for open-loop and closed-loop Nash equilibrium solutions to the model are discussed. A numerical algorithm for open-loop and closed-loop Nash strategies to the model is developed.

Health-related quality-of-life assessment of prenatal diagnosis: chorionic villi sampling and amniocentesis.

This study assesses the health-related quality-of-life (HRQL) effects of chorionic villi sampling (CVS) and genetic amniocentesis (GA), including both process and outcomes of prenatal diagnosis. The HRQL of 126 women participating in a randomized controlled clinical trial of CVS versus GA in Toronto and Hamilton, Ontario, was assessed in four interviews at weeks 8, 13, 18, and 22 of pregnancy. Statistical analyses included analysis of variance, repeated measures analysis of covariance, chi-square, Fishers exact test, Students t-tests, and paired t-tests. Utility scores for patients undergoing CVS exceeded those for GA patients at week 18 (p = 0.04). Utility scores for hypothetical health states did not differ significantly by trial arm. CVS results in slightly improved HRQL during prenatal diagnosis. This advantage needs to be weighed against the high disutility patients attach to infrequent outcomes associated with pregnancy losses, equivocal diagnoses, and diagnostic inaccuracy.

Static game theory models and their applications in management science

Abstract In the present paper, we give a brief review of static game models and their applications in management science. Our intention here is twofold: On the one hand, we would like to provide the reader with an overview of game theory and its applications in management science. On the other hand, we intent to explore the mathematical tractability of management science problems when formulating them as game theory models. To make the paper not too extensive, we restrict our attention to static game theory models and five management science related areas. Our discussion starts by a general description of static game theory models and their solution schemes and follows by an investigation of game theory applications. At the end of the survey, we provide a brief description of some other approaches of game theory.

Designs of control charts with optimal manpower deployment

This article proposes an algorithm for managing and deploying manpower (equipped with adequate measuring instrument) to a statistical process control (SPC) scheme so that the resultant control chart (referred to as M-chart) minimizes the expected total cost C total incurred in the implementation of SPC. Unlike in the economic chart designs, most input specifications required by the design of an M-chart can be easily determined by practitioners. The design of an M-chart also takes into account the probability distribution of the random process shifts. The results of an example and a comprehensive study show that the M-chart can reduce the total cost by about 66%, on average, compared with the conventional control charts. It is also found that, in most SPC schemes, the allocated manpower is far less than needed and, consequently, the total cost can be significantly reduced by making some managerial arrangement to increase SPC manpower. Some useful guidelines are provided in this article to aid the management and determination of the appropriate amount of manpower for a particular application. Even though the M-chart is discussed in detail only for the chart detecting mean shifts, the general idea can be applied to many other charts (e.g. the CUSUM and EWMA charts) and to monitoring both process mean and variance.