A queueing model for managing small projects under uncertainties

We consider a situation in which a home improvement project contractor has a team of regular crew members who receive compensation even when they are idle. Because both projects arrivals and the completion time of each project are uncertain, the contractor needs to manage the utilization of his crews carefully. One common approach adopted by many home improvement contractors is to accept multiple projects to keep his crew members busy working on projects to generate positive cash flows. However, this approach has a major drawback because it causes "intentional" (or foreseeable) project delays. Intentional project delays can inflict explicit and implicit costs on the contractor when frustrating customers abandon their projects and/or file complaints or lawsuits. In this paper, we present a queueing model to capture uncertain customer (or project) arrivals and departures, along with the possibility of customer abandonment. Also, associated with each admission policy (i.e., the maximum number of projects that the contractor will accept), we model the underlying tradeoff between accepting too many projects (that can increase customer dissatisfaction) and accepting too few projects (that can reduce crew utilization). We examine this tradeoff analytically so as to determine the optimal admission policy and the optimal number of crew members. We further apply our model to analyze other issues including worker productivity and project pricing. Finally, our model can be extended to allow for multiple classes of projects with different types of crew members

Older Shopper Types from Store Image Factors

This study aims to characterise the older shopper by exploring unobserved heterogeneity within the segment and developing an older shopper typology from an empirically derived store image scale. Store attribute theory informed a two-stage research design. Firstly, a ‘pool’ of salient store attributes was identified through in-depth interviews. Scales were then developed and quantitatively tested using data collected through a household postal survey. Seven store image factors emerged, forming the basis of the typology. Five clusters were subsequently profiled using behavioural and demographic variables: Prudent neutrals, All-Round demanders, Reluctant casuals, Demanding sociables, and Affluent utilitarians. A discussion of the resultant classification's utility in terms of retail strategy, including opportunities for better targeting through adjustment of the retail offer, is presented. This study develops a store image scale that reflects the importance of store choice decisions of older shoppers, extending store image research by providing contemporary insights into the requirements of older shoppers in a changing retail environment

Teaching of critical path networks using software packages

The aim of this paper is to review a published paper, Using computer software packages to enhance the teaching of Engineering Management Science: Part 1 –Critical path networks'. Excel in Microsoft Office 2007 was discovered to be able to solve critical path network problems with some programming. The capabilities of the two previously evaluated packages, Microsoft Project 2007 and Quantitative Methods – Production and Operations Management (POM-QM) for Windows 3 were cited and Excel usage is explained for each of the objective of the module, critical path networks. A pseudo quantity scoring system was developed to evaluate the capabilities of the software packages in meeting the 5 objectives of the module. It was found that POM-QM for Windows 3 scored the highest points. However, Excel in MS can be argued to provide the best learning outcomes as it endeavours students to understand the concepts of critical path networks clearly before they can program and solve the problems

Note--On the Maximal Covering Location Problem and the Generalized Assignment Problem

In many public sector location problems, it is often desirable to locate facilities in such a way to minimize the number (or cost) of facilities while insuring tint all demand centers are within a stated maximal service time front any facility. However, when insufficient resources exist to allow die construction of enough facilities to serve all demand centers within the alloted time, the location problem is frequently restated in order to locate the budgeted facilities to serve the serviced population. Problems of the latter type are generally known as maximal covering location problems, which may have a number of extensions, including mandatory closeness constraints which place an upper bound on the maximal service time requirement for the entire population. This note demonstrates how this class of frequently encountered problems can be formulated as generalized assignment problems within the conceptual framework presented by Ross and Soland (Ross, G. T., R. Soland. 1977. Modeling facility location problems as generalized assignment problems. Management Sci. 24 (3, November) 345-357.) for other discrete public and private location problems.facility location, assignment problem

The p-Median Problem for Cluster Analysis: A Comparative Test Using the Mixture Model Approach

Recently, Mulvey and Crowder (Mulvey, J., H. Crowder. 1979. Cluster analysis: an application of Lagrangian relaxation. Management Sci. 25 329--340.) suggested that the p-median problem might be useful for cluster analysis problems (where the goal is to group objects described by a vector of characteristics in such a way that objects in the same group are somehow more alike than objects in different groups). The intent of this paper is to test Mulvey and Crowder's proposal using the mixture model approach; i.e., by applying a number of algorithms (including one for the p-median problem) to a set of objects randomly sampled from a number of known multivariate populations and comparing the ability of each algorithm to detect the original populations. In order to evaluate the results, a generalized partition comparison measure and its distribution are developed. Using this measure, results from various algorithms are compared.statistics: cluster analysis, programming: integer, applications, facilities/equipment planning: location

New Product Introduction: Timing, Design, and Pricing

In this paper, we consider the case when two profit-maximizing firms enter a new market with a competing product that has a finite (and known) life cycle. Both firms make design decisions simultaneously without information about the other firm's decisions. The order of entry is a function of the two firms' product design levels and design capabilities. The first firm entering the market sets a monopoly price for its product and enjoys a monopoly situation until the second firm enters the market. When the second firm enters the market, both firms simultaneously set (or reset) their product prices knowing the design of both products at that time (and we assume those prices are fixed for the remainder of the product's life). We develop a game-theoretic model that represents the new product introduction process and show that a subgame-perfect Nash equilibrium occurs under certain conditions defined by the expected product life span, product cost, development time, and customer preferences. Our model shows that product differentiation always arises at equilibrium due to the joint effects of resource utilization, price competition, and product life cycle. A critical parameter for our model is a product-specific index B that we define; we show how it can be easily calculated from existing data. We then use a numerical example to illustrate managerial implications for a new product development process when the product life span is finite. We show that the strategy of time-based competition is the natural result of firms' improving development capability, reducing product cost, and increasing customer preference. In other words, it is not wise for profit-maximizing firms to arbitrarily shorten product life cycle for the sake of competition, because all firms are worse off. Our results also indicate that the first entrant into the market does not necessarily earn the greatest profit, and that a firm with low-cost advantage or fast design capability might not choose to come to market first to maximize its profit in the product life cycle.new product development, game theory, product index

Measuring the Impact of a Delay Buffer on Quality Costs with an Unreliable Production Process

In this paper, we consider an unreliable production process which produces nondefective items when operating in control, but produces defective items with a probability \alpha when the process has shifted to an out-of-control state. Following a JIT philosophy, we stop the entire line and repair the machine as soon as detect that the process has shifted to an out-of-control state. To test whether a process shift has occurred, we inspect the last m units for every n units produced and stop the machine if a defective unit is found. More important, we place a "delay buffer" immediately after the unreliable process, which serves to delay the movement of items from the unreliable machine to other processes (or customers) downstream in the production system. When we detect that the machine has shifted to an out-of-control state, we stop the entire line and examine all previously uninspected items in the delay buffer; in this way, the buffer serves to reduce the expected rework and penalty (e.g., warranty) costs downstream when a process shift has occurred. In this paper, we develop a model for this approach and use this model to test the operating characteristics of our system. Computational results illustrate our hypothesis that a delay buffer may significantly reduce expected total costs of a quality control process.quality management, sampling/inspection policies, unreliable production processes, delay buffer