B. Jay Coleman

The Use of the ETS Major Field Test for Assurance of Business Content Learning: Assurance of Waste?.

Exit exams have become the currency of choice for both institutions and accrediting bodies seeking to demonstrate student learning. Most researchers have ignored the opportunity costs of these tests and the fundamental question of whether the exams add value to the assessment process already in place on college campuses (course testing and GPA). A statistical model that uses a students GPA, SAT score, and demographic characteristics predicts the students Major Field Test (ETSB) score quite well. Furthermore, the opportunity cost of administering these exams at the institution in question exceeds

Minimizing Game Score Violations in College Football Rankings

25,000 annually. The authors argue that the cost-benefit tradeoff of the ETSB exit exam is unfavorable.

Identifying the “Players” in Sports Analytics Research

One metric used to evaluate the myriad ranking systems in college football is retrodictive accuracy. Maximizing retrodictive accuracy is equivalent to minimizing game score violations: the number of times a past games winner is ranked behind its loser. None of the roughly 100 current ranking systems achieves this objective. Using a model for minimizing violations that exploits problem characteristics found in college football, I found that all previous ranking systems generated violations that were at least 38 percent higher than the minimum. A minimum-violations criterion commonly would have affected the consensus top five and changed participants in the designated national championship game in 2000 and 2001-but not in the way most would have expected. A final regular season ranking using the model was perhaps the best prebowl ranking published online in 2004, as it maximized retrodictive accuracy and was nearly the best at predicting the 28 bowl winners.

Voter Bias in the Associated Press College Football Poll

Despite a sports analytics research history that goes back more than 50 years and a recent dramatic rise in the level of scholarly interest in sports analytics, no prior research has attempted to identify its scope, scale, and growth in terms of the body of published refereed articles in the literature. Prior research has also not identified the “players” in the field: the journals and institutions that most commonly publish sports analytics research and are most commonly cited. To answer these questions, I examined 140 journals in operations research, statistics, applied mathematics, and applied economics, and identified 1,146 articles that address the application of analytics in sports. The results provide a picture of the size and nature of sports analytics research and its purveyors, and offer some perspective on the parameters of the field.

An Examination of NBA MVP Voting Behavior: Does Race Matter?

The authors investigate multiple biases in the individual weekly ballots submitted by the 65 voters in the Associated Press college football poll in 2007. Using censored Tobit modeling, they find evidence of bias toward teams (a) from the voter’s state, (b) in conferences represented in the voter’s state, (c) in selected Bowl Championship Series conferences, and (d) that played in televised games, particularly on relatively prominent networks. They also find evidence of inordinate bias toward simplistic performance measures—number of losses, and losing in the preceding week—even after controlling for performance using mean team strength derived from 16 so-called computer rankings.

A closer look at trading strategies for U.S. equity closed-end investment companies

The selection process of the most valuable player (MVP) in the National Basketball Association (NBA) was recently questioned as to whether African American players were treated unfairly based on their race. Using NBA voting data from the 1995-2005 seasons, two empirical models are developed to examine the role that a players race plays in the determination of this award. The estimates imply that after controlling for player, team, and market characteristics, there is no statistically significant effect of race on the likelihood that a player will appear on an MVP ballot or on the number of votes he will receive.

A quick and effective method for capacitated lot sizing with startup and reservation costs

Abstract Earlier studies of U.S. closed-end investment companies (CEICs) examined whether the discount between CEIC price and net asset value could be exploited to gain excess returns. We advance these studies by investigating many more trading strategies and various transaction costs. We find that the role of the span between buy and sell trigger points is highly significant in determining returns, and that transaction costs impact returns and mitigate the influence of the trigger point span. Moreover, the 10 most successful strategies for each transaction cost level exhibit lower coefficients of variation than does the Standard & Poor’s 500 (S&P 500) index.

A comparison of the performance of open-and closed-end investment companies

Abstract We present a pure zerp-one integer programming model for determining single-item production lot sizes in capacitated “long production run” environments, where each production period is dedicated to a single product, and where production of a given item may extend over more than one production period. All costs, as well as capacity, are time-varying, and include startup (changeover), reservation (opportunity), holding, and production costs. Holding and production cost may also vary within a period. The problem setting is effectively the single-item subproblem of the “multiple product cycling” case. Our a model is efficient primarily because of variable elimination strategies associated with capacity limitations. Although our formulation makes two simplifying assumptions versus previous research, these did not significantly hamper model performance. Experimentation on problems from the literature yielded a 93% optimality frequency, with less than 60 pivots required for 20 period problems, a tremendous efficiency improvement over previous models. As such, the model represents an excellent and practical first step toward efficiently solving multiple product problems on an industrial scale.

A Proposed Typology for the Production and Operations Management Core Course

This paper investigates the impact of corporate structure on the return performance and related operational characteristics of open- and closed-end investment companies. A statistical model is used to test for differences in several characteristics of these two different types of funds. The results show that there are differences in the returns of open-and closed-end funds, as well as differences in turnover and expenses of funds with different corporate structures. Moreover, the results are surprising in that they are significantly affected by the type of security held in the funds.

Team Travel Effects and the College Football Betting Market

In many business programs, a single production and operations management (POM) course is included in the core curriculum to provide a brief overview for students who do not pursue the subject as a major. This article offers a simple two-dimensional, four-cell typology, well grounded in various POM sources, for facilitating instruction under the constraints and requirements of such a course. The typology can also serve non-POM faculty who might be asked to teach the course, as well as authors and instructors providing reviews of POM in management principles courses and texts.