Jess S. Boronico

Quantitative modeling and technology driven departmental course scheduling

A multiple objective hierarchical mathematical model is presented which assists administrators at Monmouth Universitys School of Business with departmental course scheduling for undergraduate courses. The mathematical model is used in conjunction with a discrete event simulation model that projects student enrollment for courses. The results of the model suggest faculty schedules that address important priorities at the School of Business, including minimizing expected student course conflicts, constraining the use of adjunct faculty, and adhering to ex ante declared recommendations in the assignment of faculty to course sections.

Capacity planning for toll roadways incorporating consumer wait time costs

This paper reports the findings for an investigation concerning capacity planning analysis for toll-plaza operations. The study develops a cost minimizing capacity planning model that minimizes expected costs which include both operating and user costs. A reliability constraint is appended to the formulation to account for the service providers sensitivity to demand for quality. Optimal capacity levels are determined for both peak and off-peak hours. Subsequently, a work force policy is obtained through the utilization of a mathematical program. The research suggests that significant savings may accrue through the implementation of a decision support system which may be developed from the models presented.

An investigation into the costs and benefits of reliability of service

The continued movement towards a global economy has contributed to the tremendous growth of competition in many industries. In order for many of these entrants to remain competitively viable, considerable attention must be focused on the impact of service quality, both on the cost side and the demand side. While a considerable literature exists on the impact of service quality and reliability on demand or cost, less work has focused on the explicit impact of service quality and reliability jointly on demand for and the cost of providing services. This paper focuses on a service provider who, faced with competition, must determine the optimal level of service quality to provide in order to maximize profits. Service quality is assumed to impact on both demand for services and the cost of providing service. A reliability constraint is appended to the formulation in order to guarantee that the declared service quality is met. Conditions are developed which characterize optimal solutions. An illustrative example is presented in order to demonstrate how results from the model may be utilized.

Postal service pricing subject to reliability constraints on service quality

The 1980s and 1990s have seen competition emerge within industries traditionally imbued with monopoly status, for instance, the field of telecommunications. Within these industries, increased competition and the threat of the removal of statutory monopoly has resulted in greater awareness regarding the impact of quality on service and efficient pricing. Discusses, as an example, postal services, an industry of immense importance worldwide, suggests that the emphasis postal services place on the implementation of both timely and reliable service and competitive prices will inherently determine the success they will have withstanding the ever growing threat of international and national competition. While postal services and public utilities share similar peak‐load problems as discussed in the traditional natural monopoly literature, limited deferrability of mail service, together with service differentiated pricing, yields a framework sufficiently different so as to warrant a separate analysis. Presents a model which considers this analysis by developing welfare‐optimal prices, reliabilities and capacities under conditions of stochastic demand subject to reliability constraints on service quality and a minimum profit Ramsey constraint.

Multi-Tiered Playoffs and Their Impact on Professional Baseball

Abstract This article investigates multitiered playoffs in professional baseball. It is shown that although increasing the length of any playoff series decreases the probability of an upset, the introduction of a multitiered playoff system impacts the probability of an upset to the extent that upsets become highly probable. It is also shown that, given a fixed number of games within which to conduct multitiered playoffs, an allocation rule may be determined so that the distribution of games to each tier may be set in order to maximize the probability that the team with the highest winning percentage advances through all tiers successfully.

The application of reliability constrained stochastic capacity planning models to the service sector

Abstract Emphasis on quality management has recently permeated not only the manufacturing sector, but the service sector as well. Consequently, quality service and consumer satisfaction have become realities for many monopolistic service oriented industries facing competition. In order to effectively implement timely service within these industries (i) capacity plans must be developed which provide adequate staffing during both peakload and offpeak hours, as well as optimal (ii) prices and (iii) reliability of service. This paper builds on the results of Boronico (1992) in illustrating how reliability constrained marginal cost, within which optimal price is embodied, and minimum cost capacity plans may be determined for a service provider facing stochastic demand. Excess demand is not lost, but is deferred: a characteristic that typifies the operation of many delivery systems, such as postal services. Results indicate that marginal costs are convex with respect to reliability of service, while changes in the demand distributions variability may impact optimal capacity by either increasing or decreasing required capacity.

Customer service: the distribution of seasonal food products under risk

Addresses important logistical considerations in the distribution of a seasonal food product. While continued attempts have been made to maintain high levels of customer service within the food industry, the degree of uncertainty in the distribution channel itself often undermines management’s efforts to procure adequate stock of product during peak demand season. Develops a stochastic dynamic programming formulation which may serve as a decision‐support tool for managers faced with procuring product in a distribution channel in which receipt quantities are probabilistic. Provides numerical results, supporting the intuitive result that expected costs and the length of the required planning horizon are inversely related to the level of uncertainty in the distribution channel.

An empirically driven mathematical modelling analysis for play calling strategy in American football

This manuscript presents an empirically based mathematical model to assist in the determination of optimal American football play selection for first down and goal situations. The analysis utilises a game‐theoretic approach embedded within a stochastic dynamic programming formulation, resulting in a mixed strategy satisfying the ex‐ante declared objective of maximising the probability of scoring a touchdown. The results of this manuscript illustrate how a quantitative framework may be applied to a problem that impacts on team performance, and addresses a gap in the literature concerning the application of quantitative methods to sports. Empirical results are generated from the collection of data representing over 1700 football plays run by the Monmouth University football team during the past three seasons.

Ratemaking for postal services: a stochastic marginal cost pricing model

JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 7 NO. 4 1998, pp. 342-353

Unit selection and the sales comparison approach

Reports the results of an empirical investigation conducted for the purposes of exploring the issue of unit selection and the sales comparison approach. The proximate motivation of this study was in determining how non‐reinforcing appraisal estimates may be addressed. The investigation proceeds by exploring two possible criteria through which the reliability of appraisal estimates may be measured. The first involves the percentage error made in price per unit of comparison (UOC), while the second concerns the total valuation error in the appraisal of real property. Results involve the utilization of the coefficient of variation and the Markov inequality, and may assist appraisers when different units of comparison yield non‐reinforcing estimates of value. It is shown that maximum confidence in guaranteeing that the percentage error between the estimated and actual price per UOC lies within a tolerance level chosen ex‐ante obtains through choosing the UOC with the minimum coefficient of variation. Total valuation error is minimized as a function of the standard deviation for the price per UOC, the sample size, and the UOC’s value for the real property being appraised. While minimum per unit percentage error may be obtained utilizing a particular UOC, the minimization of total valuation error may imply the utilization of an alternative unit. It is shown for the empirical analysis conducted, that when two common units of comparison are considered ‐ acreage and front footage ‐ both percentage and total valuation error were minimized through the use of price per acre rather than price per front foot.