bluuebunny/crossref_metadata_2025_split huggingface dataset:
Forgetting and the Learning Curve: A Laboratory Study
Authors: Bailey Charles D. 
Published: November 2008

The industrial learning curve is widely used to predict costs and labor requirements wherever learning is taking place. Little is known, however, about the reverse of this process: the forgetting that occurs during production interruptions. The ability to estimate cost increases due to forgetting would be useful for economic lot size determinations, bidding on repeat orders, estimating the cost of strikes, and so on. Empirical studies apparently have not been published. Field data are difficult to obtain and easily confounded by extraneous variables. Thus a laboratory experiment was undertaken to test selected variables that should (or should not) affect forgetting. A review of relevant psychological literature reveals two key findings: (1) Forgetting may be negligible for “continuous control” tasks but considerable for “procedural” tasks. Bicycle riding is representative of continuous control, while operating a computer is clearly procedural. (2) Forgetting is a function of the amount learned and the passage of time, not of the learning rate or other variables. The experiment employed paid subjects who worked between four and eight hours to learn both a procedural task and a continuous control task (assembling and disassembling a mechanical apparatus). Each subject returned at an assigned time, up to 114 days later, and repeated the task for about four hours. Thirty-one of 35 subjects produced usable data. For purposes of the study, “forgetting” was defined as the excess of actual time over learning-curve-predicted time, summed over the first four trials after the interruption. “Amount learned” was defined as the achieved reduction in time-per-unit before interruption. As hypothesized, forgetting was a function of amount learned and elapsed time, with 71 percent of the variance being thereby explained in a regression equation. Forgetting rate does not appear to be related to learning rate, contrary to conventional wisdom in the learning curve literature. Additional findings are (1) that the relearning rate is not correlated with the learning rate, but may be related to skill factors and the degree of original learning; (2) that subjects have poor insight into their memory states; and (3) that, within the specific task, learning rate is highly correlated with the time taken to complete the first unit. Further research is indicated to investigate whether the forgetting rate may be constant, and therefore applicable across broad classifications of tasks. The determinants of relearning also are a suggested area of investigation. The results of this study apply to individual learning curves, and questions remain concerning the aggregation of individual performance into group performance.
Gaussian Influence Diagrams
Authors: Shachter Ross D. , Kenley C. Robert 
Published: November 2008

An influence diagram is a network representation of probabilistic inference and decision analysis models. The nodes correspond to variables that can be either constants, uncertain quantities, decisions, or objectives. The arcs reveal probabilistic dependence of the uncertain quantities and information available at the time of the decisions. The influence diagram focuses attention on relationships among the variables. As a result, it is increasingly popular for eliciting and communicating the structure of a decision or probabilistic model. This paper develops the framework for assessment and analysis of linear-quadratic-Gaussian models within the influence diagram representation. The “Gaussian influence diagram” exploits conditional independence in a model to simplify elicitation of parameters for the multivariate normal distribution. It is straightforward to assess and maintain a positive (semi-)definite covariance matrix. Problems of inference and decision making can be analyzed using simple transformations to the assessed model, and these procedures have attractive numerical properties. Algorithms are also provided to translate between the Gaussian influence diagram and covariance matrix representations for the normal distribution.
Computing Equilibrium Single Commodity Trade Flows Using Successive Overrelaxation
Authors: Güder Faruk , Morris James G. 
Published: November 2008

We consider a market economy that is composed of separate regions, each endowed with linear supply and demand curves and represented as a point on a transportation network. The problem addressed is to determine an equilibrium price in each region so that regional price differences do not exceed unit transportation costs, and when trade takes place between two regions, prices differ by the associated transportation cost. The problem has several quadratic programming formulations. We adopt an approach based on a net import relation. Properties are then given which lead to reductions in the quadratic program. A successive overrelaxation algorithm is proposed that is particularly well-suited to the task of solving the inherent large-scale instances of the problem, while at the same time is simple to implement.
Approximations for Product Departures from a Single-Server Station with Batch Processing in Multi-Product Queues
Authors: Bitran Gabriel R. , Tirupati D. 
Published: November 2008

In this paper we consider a single-server station processing jobs belonging to multiple product classes. The processing at the station is in batches of fixed size, r. Job arrivals in different product classes are independent of the arrivals in other classes. The arrivals within each product class and the service times are assumed to have general, independent and identical distributions. Based on approximate analyses, we present an estimate for the mean number of jobs and provide two complementary characterizations of the product departure streams. We present methods to compute the squared coefficient of variation of the departure intervals and the probability distribution of the lot sizes of product departures. The computational results reported in this paper demonstrate that the accuracy of the approximations is acceptable in most applications. Based on these results, we identify conditions under which the estimates can be expected to perform well. The methods developed in this paper complement the decomposition approach for open queueing networks proposed by Shanthikumar and Buzacott (Shanthikumar, J. G., J. A. Buzacott. 1981. Open queueing network models of job shops. Internat. J. Production Res. 19(3) 255–266.) and Whitt (Whitt, W. 1983. The queueing network analyzer. Bell System Tech. J. 62(9) 2779–2815.) and permit analysis of networks with some types of batch processing.
A Quantitative Analysis of U.S. and Japanese Practice and Performance in Software Development
Authors: Cusumano Michael A. , Kemerer Chris F. 
Published: November 2008

Since the early 1980s, there has been a mounting debate in industry literature and in U.S. government-sponsored reports over the relative performance of software developers in Japan versus those in the United States. This literature is somewhat divided between assertions of Japanese or U.S. superiority in this technology, although many observers in the popular business press continue to insist that the U.S. maintains an overwhelming lead in this technology. However, both sides of the debate have offered evidence that, to date, has been primarily qualitative or based on one or two cases. This paper contributes to the debate in two ways. First, it offers a comprehensive literature review that analyzes existing comparisons of Japanese and U.S. practice in software development and summarizes the major proposed differences in performance. Second, it presents the first set of quantitative data collected from a statistically comparable sample of 24 U.S. and 16 Japanese software-development projects, and uses these data to test propositions from the literature. The analyses indicate that Japanese software projects perform at least as well as their U.S. counterparts in basic measures of productivity, quality (defects), and reuse of software code. The data also make it possible to offer models that explain some of the differences in productivity and quality among projects in both countries.
Scheduling the Production of Several Items with Random Demands in a Single Facility
Authors: Gallego Guillermo 
Published: November 2008

Consider the problem of scheduling the production of several items in a single facility that can produce only one item at a time. This problem occurs since it is often economic to produce several items in a single facility. The objective is to reduce the long run average holding, backorder and setup costs. We assume that demands are random with constant expected rates. We allow backorders and charge holding and backlogging costs at linear time weighted rates. Items are produced at continuous constant rates. Setup times and setup costs are item dependent constants. These parameters, however, are independent of the order of setups. A real-time scheduling tool is developed in three steps. First, with demands replaced by their expectations, we compute an optimal or near-optimal target cyclic schedule. Next, we study the problem of scheduling the facility after a single disruption perturbs the inventories. The goal is to recover the target cyclic schedule at minimal excess over the average cost of the cyclic schedule. We formulate this as a control problem and obtain a linear recovery policy that is optimal for a large configuration of disruptions. Finally, we select safety stocks to minimize the long run average cost of following the target schedule with the recovery policy. We show that optimal safety stocks are unique and have the property that in the long run the proportion of time that an item is in stock is the ratio of backorder to holding plus backorder cost. We present an example that integrates the cyclic schedule, the control policy and the safety stocks.
The Effects of Brand Loyalty on Competitive Price Promotional Strategies
Authors: Raju Jagmohan S. , Srinivasan V. , Lal Rajiv 
Published: November 2008

This paper analyzes the role played by brand loyalty in determining optimal price promotional strategies used by firms in a competitive setting. (Loyalty is operationalized as the minimum price differential needed before consumers who prefer one brand switch to another brand.) Our objective is to examine how loyalties toward the competing brands influence whether or not firms would use price promotions in a product category. We also examine how loyalty differences lead to variations in the depth and frequency with which price discounts are offered across brands in the same product category. The analysis predicts that a brand's likelihood of using price promotions increases with an increase in the number of competing brands in a product category. In the context of a market in which a brand with a large brand loyalty competes with a brand with a low brand loyalty, it is shown that in equilibrium, the stronger brand (i.e., the brand with the larger loyalty) promotes less frequently than the weaker brand. The results suggest that the weaker brand gains more from price promotions. The analysis helps us understand discounting patterns in markets where store brands, weak national brands, or newly introduced national brands compete against strong, well known, national brands. The findings are based on the unique perfect equilibrium in a finitely repeated game. The predictions of the model are compared with the data on 27 different product categories. The data are consistent with the main findings of the model.
Optimal Investment in Product-Flexible Manufacturing Capacity
Authors: Fine Charles H. , Freund Robert M. 
Published: November 2008

This paper presents a model and an analysis of the cost-flexibility tradeoffs involved in investing in product-flexible manufacturing capacity. Flexible capacity provides a firm with the ability to respond to a wide variety of future demand outcomes, but at the expense of the increased cost of acquiring flexible manufacturing capacity, as compared with dedicated or nonflexible capacity. We formulate the product-flexible manufacturing capacity investment decision as a two-stage stochastic program. In the first stage, the firm must make its investment decision in manufacturing capacity, before the resolution of uncertainty in product demand. In the second stage, after demand for products are known, the firm implements its production decisions, constrained by the first-stage investments. The main contributions of this paper are threefold. First, we develop a model of the firm's flexible manufacturing investment decision that conceptually captures some of the key characteristics of this complex decision problem. Second, with the aid of the model, we characterize the necessary and sufficient conditions for a firm to invest in flexible capacity to protect efficiently against uncertainty in demand for all of its products. Third, we explore the sensitivity of the firm's optimal capacity investment decision to key problem components, namely to the cost of flexible and nonflexible production capacity, to the underlying distribution of product demand, and to the level of risk.
Market Share Pioneering Advantage: A Theoretical Approach
Authors: Fershtman Chaim , Mahajan Vijay , Muller Eitan 
Published: November 2008

In this paper we present an industry in which a pioneer has entered, accumulated capital in the form of goodwill, and in his monopoly period has also reduced his cost of production as a result of some form of learning by doing. At some later date a newcomer enters. His production cost is higher than that of the monopolist at that date. However due to diffusion of information, the costs of the two firms equate at some future date. Once the new firm enters the market a duopolistic game begins in which the firms choose prices and investment rates. Analyzing this game we discover the conditions under which the final market shares no longer depend on the order of entry, the initial cost advantage, the length of the monopoly period, or the length of time it took the newcomer to overcome the pioneer's cost advantage. We analyze the speed and pattern of convergence to the final market shares and the capital path of the pioneer in his monopoly period, depending on his beliefs concerning the possibility of entry.
Sufficient Working Subsets for the Tour Scheduling Problem
Authors: Easton Fred F. , Rossin Donald F. 
Published: November 2008

Mathematical programs to schedule service employees at minimum cost represent each feasible schedule, or tour, with an integer variable. In some service organizations, policies governing employee scheduling practices may permit millions of different tours. A common heuristic strategy is to reformulate the problem from a small working subset of the feasible tours. Solution quality depends on the number and types of schedules included in the model. This paper describes a working subset heuristic based on column generation. The method is general and can accommodate a mix of full- and part-time employees. Experiments revealed its formulations had objective values indistinguishable from those of models using all feasible tours, and significantly lower than those generated by alternative working subset procedures.
Ordering and Production Decisions with Supply Quality and Demand Uncertainty
Authors: Bassok Y. , Akella R. 
Published: November 2008

In this paper, we solve a production planning problem that has a direct bearing on the cost to a facility of vendor quality and reliability. This solution is also an important first step in solving the multi-plant coordination problem. We consider a manufacturing facility with one critical raw material, and one or more products whose demand needs to be met. It is assumed that demand for finished goods and the arrival process for raw material are stochastic. We calculate simultaneously the optimal production level, and the raw material order quantity which minimize the total expected cost subject to capacity and release level constraints. The results obtained by our model (the integrated model) show that the production level should be no larger than the production level obtained by solving the traditional (nonintegrated) models, and that major savings are obtained by solving the integrated model. We are also able to characterize and evaluate the cost of reliable supplies of raw material. In addition we solve the above problem in the presence of capacity constraints. A procedure which allocates capacity to different products is presented.
Shared Preferences and State-Dependent Utilities
Authors: Schervish Mark J. , Seidenfeld Teddy , Kadane Joseph B. 
Published: November 2008

This investigation combines two questions for expected utility theory: 1. When do the shared preferences among expected utility maximizers conform to the dictates of expected utility? 2. What is the impact on expected utility theory of allowing preferences for prizes to be state-dependent? Our principal conclusion (Theorem 4) establishes very restrictive necessary and sufficient conditions for the existence of a Pareto, Bayesian compromise of preferences between two Bayesian agents, even when utilities are permitted to be state-dependent and identifiable. This finding extends our earlier result (Theorem 2, 1989a) which applies provided that all utilities are state-independent. A subsidiary theme is a decision theoretic analysis of common rules for “pooling” expert probabilities. Against the backdrop of “horse lottery” theory (Anscombe and Aumann 1963) and subject to a weak Pareto rule, we show, generally, that there is no Bayesian compromise between two Bayesian agents even when state-dependent utilities are entertained in an identifiable way. The word “identifiable” is important because, if state-dependence is permitted merely by dropping the Anscombe-Aumann axiom (Axiom 4 here) for “state-independence,” though a continuum of possible Bayesian compromises emerges, also it leads to an extreme underdetermination of an agent's personal probability and utility given the agent's preferences. Instead, when state-dependence is monitored through (our version of) the approach of Karni, Schmeidler, and Vind (1983), the general impossibility of a Bayesian, Pareto compromise in preferences reappears.
Accounting Implications of Corporate Diversification
Authors: Amit Raphael , Livnat Joshua , Zarowin Paul 
Published: November 2008

This study investigates the direct effects of corporate diversification on accounting reports, and the implications of these effects for accounting research. The study shows that firms which diversify into unrelated areas of business devote a larger proportion of their capital investments to acquisitions and are, therefore, characterized by smaller differences between replacement-cost and historical-cost values of assets than undiversified firms. The implications of these findings, as well as other operating characteristics of diversified firms, for the following areas of accounting research are subsequently examined. (1) Inflation-adjusted data. Inflation-adjusted data of diversified firms have less incremental information content (beyond historical-cost) than those of undiversified firms. (2) Earnings Response Coefficients. Diversified firms have stronger market associations with earnings changes, and their earnings are more persistent. (3) Selection of accounting methods. Diversified firms select, ceteris paribus, more liberal accounting methods than their undiversified counterparts.
Strategic Interpolative Design of Dynamic Manufacturing Systems Layouts
Authors: Montreuil Benoit , Venkatadri Uday 
Published: November 2008

This paper presents a proactive strategic methodology for designing dynamic layouts for the expansion (or decline) phase of manufacturing systems. The methodology first estimates probable scenarios of the system requirements at its maturity level, strategically designs mature layouts given the set of scenarios, then tactically interpolates intermediate layouts, backward to the initial facilities plan. For manufacturing systems with rigid facilities, the paper provides a linear programming model sustaining this proactive strategic methodology. The model efficiently generates optimal layouts for all intermediate expansion phases given a goal layout for the final mature phase of the expansion plan, the phased cell sets, the phased flow and relationships sets, and various design constraints, for an array of objectives.
Algorithms for the Multi-Resource Generalized Assignment Problem
Authors: Gavish Bezalel , Pirkul Hasan 
Published: November 2008

The multi-resource generalized assignment problem is encountered when a set of tasks have to be assigned to a set of agents in a way that permits assignment of multiple tasks to an agent subject to the availability of a set of multiple resources consumed by that agent. This problem differs from the generalized assignment problem in that an agent consumes not just one but a variety of resources in performing the tasks assigned to him. This paper develops effective solution procedures for the multi-resource generalized assignment problem. Various relaxations of the problem are studied and theoretical relations among these relaxations are pointed out. Rules for reducing problem size are discussed and are shown to be effective through computational experiments. Heuristic solution procedures and an efficient branch and bound procedure are developed. Results of computational experiments testing these procedures are reported.
Strict vs. Weak Ordinal Relations for Multipliers in Data Envelopment Analysis
Authors: Ali Agha Iqbal , Cook Wade D. , Seiford Lawrence M. 
Published: November 2008

In a recent paper, Golany (1988) proposes an interesting extension of Data Envelopment Analysis to the situation where ordinal relations among weights corresponding to certain dimensions exist. However, the development of the extended model contains mathematical errors and the proposed equivalence is incorrect. We establish the correct model equivalence and prove that weak ordinal relations require a nonstandard DEA model. We also show that the case of strict ordinal relations can be handled with the standard DEA model. These results hold for the CCR, BCC, additive, and multiplicative models and for relations involving both input and output multipliers.
Designing Telecommunications Networks for the Reseller Market
Authors: Bard Jonathan F. , Bejjani Wassim A. 
Published: November 2008

This paper presents an algorithm for minimizing the monthly cost of telecommunications networks characterized by multichannel queues with forced balking and hierarchical routing plans. The problem is of major interest to resellers of long distance services and corporate network managers who lease their lines from AT&T and Other Common Carriers. The algorithm can be used to select the most economical combination of lines to meet a desired grade of service, set here to an average blockage rate of 1% during the busy hour. Because of the nonlinearities involved, the problem is formulated as a dynamic program and solved with forward recursion. The Erlang loss formula is used to determine blockage in the case of Poisson arrivals, while Wilkinson's equivalent random theory is adopted when the input traffic is peaked. Model validation is achieved with a SLAM II simulation. The algorithm is applied to the network of National Telecommunications of Austin, which consists of 5 hierarchical levels and 52 candidate nodes, and carries about 2.3 million minutes of monthly traffic. Current services range from FX connections to Specialized WATS. The results indicate that cost reductions of over 18%, or $30,000 per month, can be achieved by periodically adjusting trunk group sizes to match the forecast demand.