Computing equilibrium in network utility-sharing and discrete election games

Journal of Combinatorial Optimization - This paper studies the computation of pure Nash equilibrium (PNE) in network utility-sharing and discretized Hotelling–Downs games, and the interplay...     

Enterprise risk management for automation in correctional facilities with pandemic and other stressors

Real-time tracking of tool and equipment inventories is a critical function of many organizations and sectors. For prisons and correctional facilities, tracking and monitoring of assets such as cookware, hardware, keys, janitorial equipment, vocational/technical specialty tools, etc., is essential for safety, security, trust, efficiency, education, etc. The performance of automated systems for this purpose can be diminished by a variety of emergent and future sociotechnical factors alone and in combination. This article introduces a methodology for contractor evaluation and selection in acquisition of innovative asset management systems, with an emphasis on evolving system requirements under uncertainty. The methodology features a scenario-based preferences analysis of emergent and future conditions that are disruptive to the performance of the asset-control system. The conditions are across technologies, operating environments, regulations, workforce behaviors, offender behaviors, prices and markets, organizations, cyber threats, etc. The methodology addresses the influence and interaction of the conditions to disrupt system priorities. Examples include: (i) infectious disease disrupting priorities among requirements and (ii)  radio-frequency identification (RFID) and wireless-technology innovations disrupting priorities among stakeholders. The combinations of conditions that most and least matter for the system acquisition are characterized. The methodology constitutes a risk register for monitoring sources of risk to project performance, schedule, and cost throughout the system lifecycle. The results will be of interest to both practitioners and scholars engaged in systems acquisition as the pandemic interacts with other factors to affect risk, uncertainty, and resilience of organizational missions and operations.     

A Comparative Revenue Analysis of Hotel Yield Management Heuristics

Yield management is the dynamic pricing, overbooking, and allocation of perishable assets across market segments in an effort to maximize short-term revenues for the firm. Numerous optimization heuristics for allocation and overbooking exist for the airline industry, whose perishable asset is the airplane seat. When an airplane departs, no revenue is gained from the empty seat(s). In the hotel industry, the perishable asset is the hotel room-once a room is left empty for a night, that night's revenue cannot be recaptured. The literature on yield management heuristics for the hotel industry is sparse. For the hotel operating environment, no research has adequately (1) integrated overbooking with allocation, (2) modeled the phenomenon of hotel patrons extending or contracting their stay at a moment's notice, or (3) performed a realistic performance comparison of alternative heuristics. This research develops (1) two hotel-specific algorithms that both integrate overbooking with the allocation decisions, (2) a simulation model to reproduce realistic hotel operating environments, and (3) compares the performance of five heuristics under 36 realistic hotel operating environments. Seven conclusions are reached with regard to which heuristic(s) perform best in specific operating environments. Generally, heuristic selection is very much dependent on the hotel operating environment. A counterintuitive result is that in many operating environments, the simpler heuristics work as well as the more complex ones.     

An Interactive Framework for Multi-Person,Multiobjective Decisions

Group decision making in the presence of multiple conflicting objectives is complex and difficult. This paper describes and evaluates an iterative technique to facilitate multiple objective decision making by multiple decision makers. The proposed method augments an interactive multiobjective optimization procedure with a preference ranking tool and a consensus ranking heuristic. Two multiple objective linear programming (MOLP) solution approaches, the SIMOLP method of Reeves and Franz [39] and the interactive weighted Tchebycheff procedure of Steuer and Choo [49], are recommended optimization strategies to be used independently or in concert. Computational experience suggests that the proposed framework is an effective decision-making tool. The procedure quickly located excellent compromise solutions in a series of test problems with hypothetical decision makers. In addition, human decision makers gave positive evaluations of the procedure and the production plans the procedure provided for a resource allocation case problem.     

A Note on Determining Optimal Selling Price and Lot Size Under All-Unit Quantity Discounts

A recent study conducted by Abad [1] described a method of determining the optimal price and lot size when the supplier offers all-unit quantity discounts. The author developed a procedure using centralized and decentralized approaches. According to the author's suggestion, further study is necessary to determine if the decentralized approach always provides an optimal solution. In the present study, an attempt is made to investigate the uniformity between the centralized and decentralized approaches and to verify whether the decentralized approach always yields optimal solutions.     

An Inventory Model with Planned Shortages and Price Dependent Demand

Previous research has yielded a procedure for a retailer to determine the optimal lot size and selling price when a supplier offers all-unit quantity discounts and demand is a decreasing function of price. In this paper, we extend that research by allowing for shortages. An algorithm is presented that determines the optimal lot size, order level, and selling price for a class of demand functions, including the constant price-elasticity and linear demand functions.     

Production System Development for Expert Systems Using a Recursive Partitioning Induction Approach: An Application to Mortgage,Commercial, and Consumer Lending

The concepts of expert systems and decision support systems have received considerable attention recently. While systems have been proposed for various problem areas in business, difficulties still exist in the knowledge acquisition phase of development. This paper presents a recursive partitioning analysis (RPA) approach to knowledge acquisition. The RPA production system approach was applied to data sets representing the mortgage, commercial, and consumer lending problems. Comparison of the classification rates across these problems to the results of a generalized inductive inference production system (Quinlan's ID3 algorithm) and across the mortgage and commercial lending problems to traditional statistical modeling approaches indicated that the RPA approach provided superior results while using fewer variables.     

Bacterial communities in peat swamps reflect changes associated with catchment urbanisation

Urban Ecosystems - Like many peat wetlands around the world, Temperate Highland Peat Swamps on Sandstone (THPSS), located in the Sydney Basin, Australia, have been impacted by urban development. In...     

On the Repeated Test-Retest Reliability of the End-User Computing Satisfaction Instrument: A Comment*

This comment extends the test-retest reliability of the end-user computing satisfaction (EUCS) instrument by Torkzadeh and Doll [10]. Whereas Torkzadeh and Doll [10] reportedstability for two hour and two week EUCS test-retest reliability, we investigate the test-retest reliability of the EUCS instrument at two points in time, separated by a two yearinterval. We assess the end user computing satisfaction of personal computer, as well as mainframe, administrative end users in a large public organization. The results of the repeated test-retest using differing application platforms add further support for the reliability of the EUCS measure and highlight some areas of concern for managers of information systems.