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We introduce feature valuations, a new class of valuations that compactly capture preferences of agents who value items based on the features they possess. Such preferences are relevant in many important practical settings, such as Internet advertising markets (where impressions have associated attributes), labor markets (where workers' skills/titles correspond to features), and long-term bond markets (where coupon payments can be associated with features). We focus on settings where features can be organized in a tree network, and features possessed by items are captured by paths on the tree. In such settings, under appropriate consistency conditions, we establish that Walrasian equilibria exist. In addition, we provide a computationally tractable price update algorithm that terminates with market-clearing prices that support an efficient outcome. History: Accepted by Yinyu Ye, optimization. Supplemental Material: The e-companion is available at https://doi.org/10.1287/mnsc.2017.2917. Keywords: feature valuations * Walrasian equilibrium * games-group decisions * bidding-auctions * networks-graphs, 1. Introduction For many platforms and markets, facilitating efficient allocation of goods from sellers to buyers is a primary objective. Allocating goods efficiently, that is, in a way that maximizes [...]

Harvest Hope Food Bank (HHFB), based in South Carolina, serves primarily donated food to people in need in 20 counties across the state. It distributed 28 million pounds of food and fed over two million individuals in fiscal year 2014-2015. However, this constituted only 40 percent of the annual meal gap of about 70 million pounds in its service area. One of HHFB's major strategic goals is to efficiently utilize its operating budget and its human and technical resources to increase food and dollar donations, which it raises through events corresponding to various promotional initiatives. We worked with HHFB management and staff to develop resource-capacity bills (i.e., the consumption of each resource per event), and calculated the expected food and (or) dollar donation yield per event. We then developed an integer programming optimization model to determine the optimal number of events of each initiative per year with the objective of maximizing the total annual meals yield (i.e., the number of meals that could be served using the food and dollar donations), subject to resource constraints and the allowable number of events of each initiative as advised by HHFB management. With our recommended optimal strategy, HHFB can provide 1.72 million additional meals per year (an increase of 41 percent) from these promotional events within the existing resource limits, which can help bridge the meal gap in its service area. HHFB has embedded the optimization model in its strategic planning of promotional events, and the allocation of resources to support these initiatives, to ensure that it can meet its 5- and 10-year meal-coverage targets. Additionally, HHFB is disseminating the value of this integrated framework to its peer food banks within the national Feeding America consortium. History: This paper was refereed. Keywords: food bank operations * nonprofit organizations * resource allocation * integer programming, Food banks are a vital link between food waste and hunger, and they serve as an interconnected lifeline to the hungry (Global FoodBanking Network 2017). They collect excess food from [...]

Deadlines are often used to manage the time of valuable human capital. In this multimethod paper, we propose a theoretical framework grounded in a formal model that encapsulates the key drivers and consequences of deadline-related time pressures on workflows, task sorting, and work quality. We use large-scale data on patent filings, along with insights from primary data collection, to test our hypotheses. In line with our predictions, we find clustering of patent filings around month-ends, with month-end applications being more complex than those filed on other days. Consistent with time pressure reducing work quality, we find that work quality is lower for tasks completed at month-ends, more so for process measures of quality than for outcome measures. Calibration of our model to the data allows us to shed light on the benefits of deadlines and suggests small levels of task acceleration but potentially larger working capital-related benefits for law firms. History: Accepted by Lee Fleming, entrepreneurship and innovation. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2016.2663. Keywords: time pressure * innovation * productivity * deadlines * incentives, 1. Introduction A critical resource-allocation challenge for managers, particularly in knowledge-intensive, high-wage sectors, is optimally managing the time of valuable human capital. In particular, there are potential trade-offs between speed [...]

Resource pooling strategies have been widely used in industry to match supply with demand. However, effective implementation of these strategies can be challenging. Firms need to integrate the heterogeneous service level requirements of different customers into the pooling model and allocate the resources (inventory or capacity) appropriately in the most effective manner. The traditional analysis of inventory pooling, for instance, considers the performance metric in a centralized system and does not address the associated issue of inventory allocation. Using Blackwell's Approachability Theorem, we derive a set of necessary and sufficient conditions to relate the fill rate requirement of each customer to the resources needed in the system. This provides a new approach to studying the value of resource pooling in a system with differentiated service requirements. Furthermore, we show that with 'allocation flexibility,' the amount of safety stock needed in a system with independent and identically distributed demands does not. grow with the number of customers but instead diminishes to zero and eventually becomes negative as the number of customers grows sufficiently large. This surprising result holds for all demand distributions with bounded first and second moments. History: Accepted by Martin Lariviere, operations management. Funding: This work was supported in part by the National University of Singapore Initiatives in Operations Research and Analytics, Agency for Science Technology and Research [Grants 1122904020 and R314-000-091-305], the National Natural Science Foundation of China [Grants 71501077, 71131003, and 71420107024], and the Guangdong Natural Science Foundation [Grant 2014A030310212], Keywords: Blackwell's Approachability Theorem * inventory pooling * service levels * fill rates, 1. Introduction Sales in global retail e-commerce increased more than 20% worldwide in 2014--to almost $840 billion--and they are expected to hit close to $1 trillion by 2015, according to [...]

Many carriers, such as airlines and ocean carriers, collaborate through the formation of alliances. The rules of alliances are important for both the stability of the alliance and the profitability of the alliance members. In this paper, we address the design of resource exchange alliances, a type of alliance agreement widely used in practice, especially in the ocean cargo industry. Resource exchange alliances often increase competition among alliance members since the members can sell substitutable products after the exchange. We propose a resource exchange model that takes into account the resulting competition and alliance profit allocation among alliance members. The problem of determining the optimal amounts of resources to exchange is formulated as a stochastic mathematical program with equilibrium constraints (MPECs). Although MPEC problems are, in general, very difficult to solve, we successfully demonstrate an efficient solution approach and provide valuable insights for the resource exchange design problem. In particular, we show that the resource exchange alliance we propose can induce greater profit for the alliance members (both total and individual profits) even though it leads to greater competition. History: Accepted by Yinyu Ye, optimization. Funding: The research of S. Y. Chun was supported by the National Science Foundation [Awards CMMI-0700161 and DMS-0914785], The research of A. J. Kleywegt was supported by the National Science Foundation [Awards ITR/DMI-0427446 and CMMI-0700161]. The research of A. Shapiro was supported by the National Science Foundation [Awards DMS-0914785 and CMMI-1232623]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2016.2434. Keywords: alliance . resource exchange * pricing * revenue management * stochastic mathematical programming with equilibrium constraints * noncooperative game, 1. Introduction Alliances are collaborative agreements between two or more parties, made to achieve common goals and to improve competitiveness. Alliances are increasingly recognized as a key component of business [...]

Firms require demand forecasts at different levels of aggregation to support a variety of resource allocation decisions. For example, a retailer needs store-level forecasts to manage inventory at the store, but also requires a regionally aggregated forecast for managing inventory at a distribution center. In generating an aggregate forecast, a firm can choose to make the forecast directly based on the aggregated data or indirectly by summing lower-level forecasts (i.e., bottom up). Our study investigates the relative performance of such hierarchical forecasting processes through a behavioral lens. We identify two judgment biases that affect the relative performance of direct and indirect forecasting approaches: a propensity for random judgment errors and a failure to benefit from the informational value that is embedded in the correlation structure between lowerlevel demands. Based on these biases, we characterize demand environments where one hierarchical process results in more accurate forecasts than the other. Keywords: judgmental forecasting; nonstationary demand; covariation detection; behavioral operations; bottom-up forecasting; random judgment error History: Received August 10, 2012; accepted May 7, 2015, by Martin Lariviere, operations management. Published online in Articles in Advance December 18, 2015., 1. Introduction Operational decision making requires accurate demand forecasts at different product levels (i.e., stock-keeping unit versus product family) as well as at different market levels (i.e., regional versus global). [...]

Financial institutions use risk measures to calculate the marginal capital cost when expanding the exposure to a certain risk within their portfolio. We reverse this approach by calculating the marginal cost based on economic fundamentals for a profit-maximizing firm and then by identifying the risk measure delivering the correct marginal cost. The resulting measure depends on context. Whereas familiar measures can be recovered in some circumstances, other circumstances yield unfamiliar forms. In all cases, the risk preferences of the institution's claimants determine how the correct risk measure must weight various default states. Our results demonstrate that risk measures used for pricing and performance measurement should be chosen based on economic fundamentals and may not necessarily adhere to the mathematical properties typically imposed in the literature. Keywords: capital allocation; risk measure; profit maximization; counterparty risk History: Received May 15, 2013; accepted January 16, 2015, by Jerome B. Detemple, finance. Published online in Articles in Advance October 15, 2015., 1. Introduction Risk measures are widely used by financial institutions for pricing and performance measurement. (1) The question of which measure to use is thus of great practical importance and [...]

We study the allocation of heterogeneous services to agents with incomplete information and without monetary transfers. Agents have private, multidimensional utilities over services, drawn from commonly known priors. The social planner's goal is to maximize a potentially complex public objective. For tractability, we take an 'engineering' approach, in which we solve a large-market approximation, and convert the solution into a feasible finite-market mechanism that still yields good results. We apply this framework to real data from Boston to design a mechanism that assigns students to public schools, in order to maximize a linear combination of utilitarian and max-min welfare, subject to capacity and transportation constraints. We show how to optimally solve a large-market formulation with more than 868 types of students and 77 schools, and we translate the solution into a finite-market mechanism that significantly outperforms the baseline plan chosen by the city in terms of efficiency, equity, and predictability. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2015.2162. Keywords: market design; priors; assignment; school choice; optimal design; large-market approximation History: Received May 22, 2014; accepted November 30, 2014, by Martin Lariviere, operations management. Published online in Articles in Advance August 19, 2015., 1. Introduction In many settings, goods or services are allocated to agents without monetary transfers. Examples include the allocation of seats in public schools, spaces in college dorms or courses, [...]

We take a novel approach to decision problems involving binary activity-selection decisions competing for scarce resources. The literature approaches such problems by forming an optimal portfolio of activities. However, often practitioners instead form a rank-ordered list of activities and select those with the highest priority. We account for both viewpoints. We rank activities considering both the uncertainty in the problem parameters and the optimal portfolio that will be obtained once the uncertainty is revealed. We use stochastic integer programming as a modeling framework, and we apply our approach to a facility location problem and a multidimensional knapsack problem. We develop two sets of cutting planes to improve computation. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1865. Keywords: priority lists; activity-selection problem; stochastic programming; cutting planes History : Received December 20, 2011; accepted February 17, 2013, by Dimitris Bertsimas, optimization. Published online in Articles in Advance May 15, 2014., 1. Introduction Resource-constrained activity-selection problems (RCASPs) involve binary activity-selection decisions, which compete for scarce resources. The bulk of the current literature approaches RCASPs by forming an optimal portfolio of activities [...]

The main responsibility of resource and delivery managers at Hewlett-Packard (HP) Enterprise Services (HPES) involves matching resources (skilled professionals) with jobs that project opportunities require. The previous Solution Opportunity Approval [...]

Firms routinely allocate the costs of common corporate resources down to divisions. The main insight of this paper is that any efficient allocation rule must reflect the firm's underlying cost structure. We propose a new allocation rule (the polynomial rule), which achieves efficiency and approximate budget balance. Welfare losses due to linear allocation rules increase with firm size, so polynomial allocation rules dominate linear rules for larger firms. Key words: cost allocation; cost sharing; mechanism design; teams; efficiency History: Received October 5, 2010; accepted September 2, 2011, by Mary E. Barth, accounting. Published online in Articles in Advance May 18, 2012., 1. Introduction The multiple divisions within a firm often share a variety of common resources, such as information technology, legal services, human resource management, executive time, etc. Managerial accounting textbooks [...]

This paper analyses the interlink between resource revenues and financial sector management in Russia and Kazakhstan. In the absence of a well functioning private financial sector the governments can substitute for the actions of the private actors by introducing dedicated financial vehicles. Specifically, these instruments allow the governments of Russia and Kazakhstan alternatives to direct ownership in their pursuit of national economic priorities. The focus of the paper is on two examples of dedicated state investment vehicles with clear industrial policy remits and roles as agents of their respective governments. The paper distinguishes between crisis management and systemic rote of these institutions. Comparative Economic Studies (2011) 53, 57-77. doi: 10.1057/ces.2010.26; published online 27 January 2011 Keywords: state intervention, state financial vehicles, Russia, Kazakhstan JEL Classifications: 013, 038, 043, INTRODUCTION The period of 2000-2007 could be characterised for Russia and Kazakhstan as an era of rapid real GDP growth and speedy catching up with the pre-transition level. At the [...]

Have the government policy of resource-rich economies in managing wealth succeeded in diversifying these economies and, in doing so, prevented them from being trapped by a Dutch Disease? Contributed to this symposium papers examine these issues in the settings of Russia, Azerbaijan, Kazakhstan and several other Central Asian countries. They assess SWFs' rules and performance by comparing them against best practice, review government policies in channeling wealth towards other (non) oil (or other natural resource) sectors via financial institutions and evaluate those funds' stabilizing and systemic roles during recent financial crisis. Comparative Economic Studies (2011) 53, 79-82. doi: 10.1057/ces.2010.25; published online 2 December 2010 Keywords: natural resources, sovereign wealth funds, transition economies JEL Classifications: Q3, Q4, O13, P28, This Symposium discusses issues that are very relevant for many transition economies, economies issues with respect to natural resource management. Intergenerational wealth maximization implies transforming oil or other natural resource [...]

The economic impact of resource abundance depends upon many factors. The literature emphasises that point resources are more likely to lead to rent-seeking than diffuse resources (Isham et al., 2003). [...]

The article examines the roles of resources, understanding of value, and provider relationships in the successful implementation of corporate strategy.

Each day, CSX Railway allocates hundreds of empty railcars among hundreds of customer car orders. In 1997, it implemented the US rail industry's first real-time, fully integrated equipment-distribution optimization system, [...]

The first step in transforming strategy from a hopeful statement about the future into an operational reality is to allocate resources to innovation and new product development (NPD) programs in a portfolio. Resource allocation and NPD portfolio decisions often span multiple levels of the organization's hierarchy, leading to questions about how much authority to bestow on managers and how to structure incentives for NPD. In this study, we explore how funding authority and incentives affect a manager's allocation of resources between existing product improvement (relatively incremental projects) and new product development (more radical projects). Funding may be either fixed or variable depending on the extent to which the manager has the authority to use revenue derived from existing product sales to fund NPD efforts. We find that the use of variable funding drives higher effort toward improving existing products and developing new products. However, variable funding has a subtle side effect: it induces the manager to focus on existing product improvement to a greater degree than new product development, and the relative balance in the NPD portfolio shifts toward incremental innovation. In addition, we highlight a substitution effect between explicit incentives (compensation parameters) and implicit incentives (career concerns). Explicit incentives are reduced as career concerns become more salient. Key words: innovation; new product development; authority; incentives; resource allocation; portfolio History: Received November 28, 2006; accepted March 22, 2009, by Christian Terwiesch, guest department editor, technological innovation, product development, and entrepreneurship. Published online in Articles in Advance July 10, 2009., 1. Introduction The question of which innovation programs to pursue is critical to a firm's success and is often cited as a key competitive dimension (Roussel et al. 1991, Wheelwright [...]

We conceptualize strategic decision-making processes within a manufacturing firm as streams of resources allocated to short- and long-term changes. The analogous ecological model, referred to as the Lotka-Volterra model, captures this dynamic tension between decisions made by the firm and its manufacturing operations. This representation leads to evolutionarily stable manufacturing strategies (ESMSs), which contribute to a firm's competitive advantage in different ways. Using a random sample of 30 firms from the U.S. semiconductor industry, we estimate parameters of the model and arrive at four ESMSs or strategic manufacturing groups that reflect theoretically and empirically distinctive adaptation patterns through their dynamic resource allocations. We observe that a majority of the firms were classified in one of the four groups, with relatively fewer firms in the other three. Notably, our classification based on ecology models agrees well with taxonomies in manufacturing and business strategy theory. Furthermore, our analysis shows significant differences among manufacturing practices and competitive capabilities of the four strategic groups. Managerially, these insights could provide the foundation to implement strategic changes that enable firms to leapfrog from one ESMS to another. This study also paves the way for development of a meso theory of the dynamics of manufacturing strategy. Key words: manufacturing strategy; resources; dynamics; competitive capabilities; ecology; complexity History: Received August 18, 2006; accepted November 23, 2008, by Paul H. Zipkin, operations and supply chain management., 1. Introduction In this paper, we study the diversity of manufacturing strategies pursued by firms in an industry by characterizing the dynamics of resource allocation within the firm and its [...]

We propose a new alternative preference measurement method, barter conjoint, to contrast with traditional choice-based conjoint (CBC) approaches. Barter conjoint collects a substantially larger amount of data compared to CBC and allows for information diffusion among respondents. We conducted two empirical studies that compare CBC (with and without incentive alignment) and barter conjoint. The studies employed a total of three product categories, each with two validation tasks (one follows immediately and one conducted two weeks later). Our results confirmed prior research that incentive alignment, in general, substantially improves out-of-sample predictive performance of CBC. Furthermore, we found barter conjoint performs substantially better than the incentive-aligned CBC. However, in the spirit of 'no free lunch,' barter conjoint is more taxing (in various ways) than CBC, suggesting a potential trade-off between consumer resource allocation (at the time of the task) and (managerial) predictive accuracy downstream. Given that this is the first study on barter conjoint, we discuss various limitations of the current implementation and fruitful directions for future research. Key words: marketing; new products; design of experiments; utility preference; conjoint analysis; mechanism design History: Received September 2, 2007; accepted January 18, 2009, by Wallace J. Hopp, marketing. Published online in Articles in Advance April 15, 2009., Introduction Conjoint analysis is a rigorous methodology designed to uncover individuals' preferences (Carroll and Green 1995) that has been applied to many contexts in marketing, including new product development (e.g., [...]

We investigate how dynamic resource substitution in service systems impacts capacity requirements and responsiveness. Inspired by the contrasting network strategies of FedEx and United Parcel Service (UPS), we study when two service classes (e.g., express or regular) should be served by dedicated resources (e.g., air or ground) or by an integrated network (e.g., air also serves regular). Using call center terminology, the question is whether to operate two independent queues or one N-network. We present analytic expressions for the delay distributions and the value of network integration through partial resource pooling. These show how the value of network integration depends on service quality (speed and reliability of service) and demand characteristics (volume averages and covariance matrix). Our results suggest that network integration is of little value and operating dedicated networks is a fine strategy if the firm primarily serves express requests with high reliability and if the correlation with regular requests is not strongly negative. In contrast, network integration offers significant gains for firms serving primarily regular requests, almost independent of correlation. Our analysis provides the intuition behind these findings in terms of three main drivers of integration value: arrival pooling, the substitution effect, and the correlation effect. Key words: network integration strategy; quality of service; flexible technology; N-network, skill-based routing; queueing History: Accepted by Michael Fu, stochastic models and simulation; received January 26, 2006. This paper was with the authors 1 year and 2 months for 2 revisions. Published online in Articles in Advance October 7, 2008., 1. Introduction and Summary In this paper, we study the value of dynamic resource substitution in service systems. Using a stylized analytic model of a firm that serves two separate [...]

Good metrics are well-defined formulae (often involving averaging) that transmute multiple measures of raw numerical performance (e.g., dollar sales, referrals, number of customers) to create informative summary statistics (e.g., average share of wallet, average customer tenure). Despite myriad uses (benchmarking, monitoring, allocating resources, diagnosing problems, explanatory variables), most uses require metrics that contain information summarizing multiple observations. On this criterion, we show empirically (with people data) that although averaging has remarkable theoretical properties, supposedly inferior nonaveraging metrics (e.g., maximum, variance) are often better. We explain theoretically (with exact proofs) and numerically (with simulations) when and why. For example, when the environment causes a correlation between observed sample sizes (e.g., number of past purchases, projects, observations) and latent underlying parameters (e.g., the likelihood of favorable outcomes), the maximum statistic is a better metric than the mean. We refer to this environmental effect as the Muth effect, which occurs when rational markets provide more opportunities (i.e., more observations) to individuals and organizations with greater innate ability. Moreover, when environments are adverse (e.g., failure-rich), nonaveraging metrics correctly overweight favorable outcomes. We refer to this environmental effect as the Anna Karenina effect, which occurs when less-favorable outcomes convey less information. These environmental effects impact metric construction, selection, and employment. Key words: metrics; metric selection; metric evaluation; summary statistics; environmental effects; natural correlations; forecasting; benchmarking; monitoring; statistical biases; choosing explanatory variables History: Accepted by Jagmohan S. Raju, marketing; received June 5, 2006. This paper was with the authors 10 1/2 months for 2 revisions. Published online in Articles in Advance September 30, 2008., 1. Our Objectives Metrics are widely used by both practitioners and academics (Gupta et al. 2004, Gupta and Zeithaml 2006). Unlike models, metrics are well-defined formulae (often involving averaging) that [...]

The article, originally published in 1995, introduces the resource-centered view of the company. It provides guidelines on assessing the value of resources, such as slow depreciation and superiority to competitors' similar resources.

Data envelopment analysis is used to construct and evaluate portfolios for selecting and allocating funds for research and development projects.

Additivity is used to determine the allocation of a discrete estate among claiming agents.

A method for handling the resource allocation problem in PERT networks by using a multi-objective model and optimization techniques is presented.

A new technique for allocation of welfare resources using fast smart market auction is presented.

A study of the linear programming solution for a resource-sharing and scheduling problem in a manufacuring company is presented.

The usage of multi-issue allocation games for resolving problems of division amongst agents whose claims are multi-dimensional is discussed.

A method of solving the scheduling problems associated with multi-mode resource constrained project, which generate positive discounted cash flows, is presented. Four different payment models are considered for the project. Simulated annealing and tabu search are suggested for solving the problems associated with scheduling.

A study on the B2B exchanges is presented. The study suggests that the participating firms can add value from managing internal activities and inter-organizational participation. Resources that support these value creating activities are also discussed.

A Resource Allocation Policy Matrix is suggested for optimizing results in product development, resource allocation, rework cycle and concurrent development using control theoretic models and system dynamics. Suggested model is expected to be very helpful in project management and scheduling.

The allocation decisions for made-to-order items as a unit to facilitate sourcing has been presented. A heuristic procedure based on Lagrangian relaxation technique has been developed to solve the problem of buyer's vendor selection.

Application of data envelopment analysis to develop empirical model for allocation of fixed costs and resources in organizations is described.

A system dynamics view of the decomposition of research and development (R&D) efforts into explorative and exploitative activities and the resultant knowledge-specific and performance outcomes from the decision to focus on one type of activity or another. Four factors are shown to affect the relative value of innovative knowledge to the organization.

A resource allocation approach to minimise cost of defective production in multistage production systems is presented.

Each year the Operational Support Office of the US National Reconnaissance Office searches for ways to provide better space-reconnaissance information to military and national leaders. We used future value analysis, [...]

A genetic annealing-based metaheuristic is proven to be superior to other metaheuristics and the conventional integer programming approach in solving real-size manpower allocation problems. Factors determined as instrumental in the success of the metaheuristic as a manpower alocation tool have been determined as encoding, selection of operators and the selection and acceptance methods used.

The tabu search methods is proven to be effective in determining stochastic and deterministic solutions to the resource constrained randomized activity duration project scheduling problem. The approach employs tabu lists, randomized short-term memory and multiple starting schedules and was tested on three aircraft maintenance projects. The approach is a valuable tool in improving project schedules and may be applied to other problems of the same nature.

Determining the optimal forward-reserve allocation figures in a warehouse with unit-load replenishments may be done by the use of a binary programming model. The greedy knapsack heuristic is proven to be an effective tool in finding a feasible solution in the number of unit-loads to be stored with consideration to the time polynomial. Evaluation results show that the approach is much closer to the optimum level than the performance guarantee indicates.

An extension of the Lanchester model may be effectively used to solve resource allocation in promotional budgets within a competitive framework. The model is proven to be a global Nash equilibrium that may be applied to both open- and closed-loop strategies with the proportion of allocated budget invariant with time and dependent only on the effectiveness of the instrument.

A target-based resource allocation (TABRA) model is presented as a way to connect performance measurement and resource allocation in multiunit multilevel organizations (MULOs). A combination of data envelopment analysis and goal programming methods were applied. A principal-agent concept was applied with central and decision-making unit management as the principal and agent, respectively. TABRA was developed from a goal programming model that finds the effect of individual agents with regards to marginal rates of conversion between inputs and outputs of the operation, the impact of the principals with regards to global performance goals and the modeling of the measures of equitable distribution. Said model was demonstrated through a sample of 20 fire departments.

A model for resource allocation with constraint problems takes into account renewable, nonrenewable and doubly constrained resources by the introduction of resource driven activity realization times and interruption costs. The method has been found to be effective in generating balanced histograms depicting graphical representations of resources and restructured activities at desired levels.

Introduction Manufacturing capability is a critical strategic factor in determining firms' competitiveness (Hayes et al., 1996), and closely correlates with firms' productivity. This paper investigates one class of decision making [...]

Bottleneck resource-allocation models are applicable to manufacturing and service operations that involve selecting integer-valued levels for different activities vying for limited, common resources to optimize the minimum return or productivity over all the activities. These models are useful for such activities as line balancing, raw material allocation, maintenance planning and storage allocation. The bisection method is proposed as a solution to complex planning problems in multiproduct assemble-to-forecast environments with part commonality. This approach is simple and versatile. It can deal with a broad range of discrete, monotonic bottleneck resource-allocation problems with additional side constraints and auxiliary variables.

Introduction The world is moving too fast for the old, traditional means of control. Customers are demanding more than ever. The rapid advances in technology are making it necessary to [...]

A decision theory-based solution to the short-term capacity allocation problem encountered by make-to-order manufacturers is developed. The problem arises when firms anticipate total demand in excess of their production capacity. To solve it, a capacity rationing policy that allows firms to discriminate between different product categories is introduced. In addition, its effectiveness is evaluated with respect to total profit, capacity utilization, and fill rate of each product category.

Critical resources are scarce, defendable, difficult to market and to imitate, and can form the basis for long-term competitive advantage Introduction In recent years, a new model of how firms [...]

A two-phase method has been developed for achieving optimum job load assignment in computer, telecommunication and manufacturing systems. The method employs three design objectives to assign load interactively, namely, system time, operating costs and job availability. Its reliability has been validated using a nonlinear programming technique.