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Customer Demand (customer + demand)
Selected AbstractsBranch-and-Price Methods for Prescribing Profitable Upgrades of High-Technology Products with Stochastic Demands*DECISION SCIENCES, Issue 1 2004Purushothaman Damodaran ABSTRACT This paper develops a model that can be used as a decision support aid, helping manufacturers make profitable decisions in upgrading the features of a family of high-technology products over its life cycle. The model integrates various organizations in the enterprise: product design, marketing, manufacturing, production planning, and supply chain management. Customer demand is assumed random and this uncertainty is addressed using scenario analysis. A branch-and-price (B&P) solution approach is devised to optimize the stochastic problem effectively. Sets of random instances are generated to evaluate the effectiveness of our solution approach in comparison with that of commercial software on the basis of run time. Computational results indicate that our approach outperforms commercial software on all of our test problems and is capable of solving practical problems in reasonable run time. We present several examples to demonstrate how managers can use our models to answer "what if" questions. [source] Coordination of staffing and pricing decisions in a service firmAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 4 2008an A. Serel Abstract Customer demand is sensitive to the price paid for the service in many service environments. Using queueing theory framework, we develop profit maximization models for jointly determining the price and the staffing level in a service company. The models include constraints on the average waiting time and the blocking probability. We show convexity of the single-variable subproblem under certain plausible assumptions on the demand and staffing cost functions. Using numerical examples, we investigate the sensitivity of the price and the staffing level to changes in the marginal service cost and the user-specified constraint on the congestion measure. Copyright © 2008 John Wiley & Sons, Ltd. [source] Situational and dispositional predictors of displays of positive emotionsJOURNAL OF ORGANIZATIONAL BEHAVIOR, Issue 8 2003Hwee H. Tan The study examined the effects of situational (store busyness and customer demand) and dispositional (extraversion, neuroticism, and psychoticism) factors on the display of positive emotions. We found that for situational factors, customer demand was positively related to displayed positive emotions. For personality factors, extraversion was positively related to displayed positive emotions and neuroticism was negatively related to displayed positive emotions. Usefulness analysis showed that both situational and personality factors contributed significantly to explain the level of positive displayed emotion. Copyright © 2003 John Wiley & Sons, Ltd. [source] Bayesian strategies for dynamic pricing in e-commerceNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 3 2007Eric Cope Abstract E-commerce platforms afford retailers unprecedented visibility into customer purchase behavior and provide an environment in which prices can be updated quickly and cheaply in response to changing market conditions. This study investigates dynamic pricing strategies for maximizing revenue in an Internet retail channel by actively learning customers' demand response to price. A general methodology is proposed for dynamically pricing information goods, as well as other nonperishable products for which inventory levels are not an essential consideration in pricing. A Bayesian model of demand uncertainty involving the Dirichlet distribution or a mixture of such distributions as a prior captures a wide range of beliefs about customer demand. We provide both analytic formulas and efficient approximation methods for updating these prior distributions after sales data have been observed. We then investigate several strategies for sequential pricing based on index functions that consider both the potential revenue and the information value of selecting prices. These strategies require a manageable amount of computation, are robust to many types of prior misspecification, and yield high revenues compared to static pricing and passive learning approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007 [source] Optimal machine capacity expansions with nested limitations under stochastic demandNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 2 2004Metin Çakany This paper studies capacity expansions for a production facility that faces uncertain customer demand for a single product family. The capacity of the facility is modeled in three tiers, as follows. The first tier consists of a set of upper bounds on production that correspond to different resource types (e.g., machine types, categories of manpower, etc.). These upper bounds are augmented in increments of fixed size (e.g., by purchasing machines of standard types). There is a second-tier resource that constrains the first-tier bounds (e.g., clean room floor space). The third-tier resource bounds the availability of the second-tier resource (e.g., the total floor space enclosed by the building, land, etc.). The second and third-tier resources are expanded at various times in various amounts. The cost of capacity expansion at each tier has both fixed and proportional elements. The lost sales cost is used as a measure for the level of customer service. The paper presents a polynomial time algorithm (FIFEX) to minimize the total cost by computing optimal expansion times and amounts for all three types of capacity jointly. It accommodates positive lead times for each type. Demand is assumed to be nondecreasing in a "weak" sense. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004. [source] A Bayesian analysis on the effect of multiple supply options in a quick response environmentNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 8 2003Hag-Soo Kim Abstract In the apparel industry, vendors often suffer from high mismatches in supply and demand. To cope with this problem, they procure the same style product from different suppliers with different manufacturing costs. Especially in the quick response environment, which allows vendors to monitor trends in customer demand and search for available suppliers through the electronic market, they have additional opportunities to improve their decision-making. In this paper, we propose an analytical profit maximization model and develop efficient decision tools to help both the middle and lower level managers pursuing this strategy. Furthermore, we have shown how significantly the vendors' potential competitive edge can be improved by exploiting multiple supply options, even at the expense of high premium procurement costs for late orders. The effect is critical, especially in a highly competitive market, and it has important implications for the top managers. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003 [source] A single-period inventory placement problem for a serial supply chainNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 6 2001Chia-Shin Chung Abstract This article addresses the inventory placement problem in a serial supply chain facing a stochastic demand for a single planning period. All customer demand is served from stage 1, where the product is stored in its final form. If the demand exceeds the supply at stage 1, then stage 1 is resupplied from stocks held at the upstream stages 2 through N, where the product may be stored in finished form or as raw materials or subassemblies. All stocking decisions are made before the demand occurs. The demand is nonnegative and continuous with a known probability distribution, and the purchasing, holding, shipping, processing, and shortage costs are proportional. There are no fixed costs. All unsatisfied demand is lost. The objective is to select the stock quantities that should be placed different stages so as to maximize the expected profit. Under reasonable cost assumptions, this leads to a convex constrained optimization problem. We characterize the properties of the optimal solution and propose an effective algorithm for its computation. For the case of normal demands, the calculations can be done on a spreadsheet. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:506,517, 2001 [source] Coping with Time-Varying Demand When Setting Staffing Requirements for a Service SystemPRODUCTION AND OPERATIONS MANAGEMENT, Issue 1 2007Linda V. Green We review queueing-theory methods for setting staffing requirements in service systems where customer demand varies in a predictable pattern over the day. Analyzing these systems is not straightforward, because standard queueing theory focuses on the long-run steady-state behavior of stationary models. We show how to adapt stationary queueing models for use in nonstationary environments so that time-dependent performance is captured and staffing requirements can be set. Relatively little modification of straightforward stationary analysis applies in systems where service times are short and the targeted quality of service is high. When service times are moderate and the targeted quality of service is still high, time-lag refinements can improve traditional stationary independent period-by-period and peak-hour approximations. Time-varying infinite-server models help develop refinements, because closed-form expressions exist for their time-dependent behavior. More difficult cases with very long service times and other complicated features, such as end-of-day effects, can often be treated by a modified-offered-load approximation, which is based on an associated infinite-server model. Numerical algorithms and deterministic fluid models are useful when the system is overloaded for an extensive period of time. Our discussion focuses on telephone call centers, but applications to police patrol, banking, and hospital emergency rooms are also mentioned. [source] Toward a hybrid model for usability resource allocation in industrial software product developmentHUMAN FACTORS AND ERGONOMICS IN MANUFACTURING & SERVICE INDUSTRIES, Issue 3 2007Colleen M. Duffy The organizational aspects of user-centered software development in a financial services company are presented. The financial services industry sector is one of the industrial sectors to embark on the development of computer software as a consumer product. The nature of business in the service sector predisposes it to encounter difficulties in developing software aimed at meeting customer demands. Lack of familiarity and experience with the product design and implementation processes, as well as reliance on usability for acceptance, are major obstacles encountered. Difficulties, insights, and lessons learned regarding organizational ergonomics issues faced by a user-centered design group are provided, and a hybrid resource distribution model is proposed to guide other service sector companies in their future software development efforts. © 2007 Wiley Periodicals, Inc. Hum Factors Man 17: 245,262, 2007. [source] Integrated multi-echelon supply chain design with inventories under uncertainty: MINLP models, computational strategiesAICHE JOURNAL, Issue 2 2010Fengqi You Abstract We address in this article a problem that is of significance to the chemical industry, namely, the optimal design of a multi-echelon supply chain and the associated inventory systems in the presence of uncertain customer demands. By using the guaranteed service approach to model the multi-echelon stochastic inventory system, we develop an optimization model to simultaneously determine the transportation, inventory, and network structure of a multi-echelon supply chain. The model is an MINLP with a nonconvex objective function including bilinear, trilinear, and square root terms. By exploiting the properties of the basic model, we reformulate this problem as a separable concave minimization program. A spatial decomposition algorithm based on the integration of Lagrangean relaxation and piecewise linear approximation is proposed to obtain near global optimal solutions with reasonable computational expense. Examples for specialty chemicals and industrial gas supply chains with up to 15 plants, 100 potential distribution centers, and 200 markets are presented. © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source] Demand and Production Management with Uniform Guaranteed Lead TimePRODUCTION AND OPERATIONS MANAGEMENT, Issue 4 2005Uday S. Rao Recently, innovation-oriented firms have been competing along dimensions other than price, lead time being one such dimension. Increasingly, customers are favoring lead time guarantees as a means to hedge supply chain risks. For a make-to-order environment, we explicitly model the impact of a lead time guarantee on customer demands and production planning. We study how a firm can integrate demand and production decisions to optimize expected profits by quoting a uniform guaranteed maximum lead time to all customers. Our analysis highlights the increasing importance of lead time for customers, as well as the tradeoffs in achieving a proper balance between revenue and cost drivers associated with lead-time guarantees. We show that the optimal lead time has a closed-form solution with a newsvendor-like structure. We prove comparative statics results for the change in optimal lead time with changes in capacity and cost parameters and illustrate the insights using numerical experimentation. [source] A framework for capturing and analyzing the failures due to system/component interactionsQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 3 2008Bimal P. Nepal Abstract To keep up with the speed of globalization and growing customer demands for more technology-oriented products, modern systems are becoming increasingly more complex. This complexity gives rise to unpredictable failure patterns. While there are a number of well-established failure analysis (physics-of-failure) models for individual components, these models do not hold good for complex systems as their failure behaviors may be totally different. Failure analysis of individual components does consider the environmental interactions but is unable to capture the system interaction effects on failure behavior. These models are based on the assumption of independent failure mechanisms. Dependency relationships and interactions of components in a complex system might give rise to some new types of failures that are not considered during the individual failure analysis of that component. This paper presents a general framework for failure modes and effects analysis (FMEA) to capture and analyze component interaction failures. The advantage of the proposed methodology is that it identifies and analyzes the system failure modes due to the interaction between the components. An example is presented to demonstrate the application of the proposed framework for a specific product architecture (PA) that captures interaction failures between different modules. However, the proposed framework is generic and can also be used in other types of PA. Copyright © 2007 John Wiley & Sons, Ltd. [source] An asymptotically optimal greedy heuristic for the multiperiod single-sourcing problem: The cyclic caseNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 5 2003H. Edwin Romeijn The dynamics of the environment in which supply chains evolve requires that companies frequently redesign their logistics distribution networks. In this paper we address a multiperiod single-sourcing problem that can be used as a strategic tool for evaluating the costs of logistics network designs in a dynamic environment. The distribution networks that we consider consist of a set of production and storage facilities, and a set of customers who do not hold inventories. The facilities face production capacities, and each customer's demand needs to be delivered by a single facility in each period. We deal with the assignment of customers to facilities, as well as the location, timing, and size of inventories. In addition, to mitigate start and end-of-study effects, we view the planning period as a typical future one, which will repeat itself. This leads to a cyclic model, in which starting and ending inventories are equal. Based on an assignment formulation of the problem, we propose a greedy heuristic, and prove that this greedy heuristic is asymptotically feasible and optimal in a probabilistic sense. We illustrate the behavior of the greedy heuristic, as well as some improvements where the greedy heuristic is used as the starting point of a local interchange procedure, on a set of randomly generated test problems. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 412,437, 2003 [source] Scheduling of depalletizing and truck loading operations in a food distribution systemNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 3 2003Zhi-Long Chen Abstract This paper studies a scheduling problem arising in a beef distribution system where pallets of various types of beef products in the warehouse are first depalletized and then individual cases are loaded via conveyors to the trucks which deliver beef products to various customers. Given each customer's demand for each type of beef, the problem is to find a depalletizing and truck loading schedule that fills all the demands at a minimum total cost. We first show that the general problem where there are multiple trucks and each truck covers multiple customers is strongly NP-hard. Then we propose polynomial-time algorithms for the case where there are multiple trucks, each covering only one customer, and the case where there is only one truck covering multiple customers. We also develop an optimal dynamic programming algorithm and a heuristic for solving the general problem. By comparing to the optimal solutions generated by the dynamic programming algorithm, the heuristic is shown to be capable of generating near optimal solutions quickly. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003 [source] THE DETERMINANTS OF THE QUANTITY-QUALITY BALANCE IN MONOPOLY,AUSTRALIAN ECONOMIC PAPERS, Issue 1 2009HUGH SIBLY This paper describes how a monopolist manipulates the balance of quantity and quality in order to increase revenue when its customers treat quantity and quality as substitutes. This ,skewing' of quality depends on the characteristics of customer's demand for quality. Customers differ in demand for quality, because they differ in either (i) their preferences and/or (ii) their time cost per unit. The monopolist is constrained to supply the same quality of good to all customers. The price and quality per unit are described under the assumption the monopolist (i) profit maximises; (ii) maximises social welfare subject to a profit constraint. The determinants of the skewing of quantity and quality are found under third-degree price discrimination and uniform pricing. [source] | ||||||||||||||||