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ABSTRACTIn 1996 the Alan K. Campbell Institute in the Maxwell School of Citizenship and Public Affairs at Syracuse University was awarded a grant to rate management performance of state and local governments and selected federal agencies. The project includes several parallel initiatives to evaluate government performance. This article contains a description of a multilevel fuzzy rule‐based system developed to evaluate state government performance. The objective is to measure effectiveness in state financial management and produce a relative ranking of performance. The system incorporates evaluation criteria and expert judgment. It utilizes survey and other publicly available information relevant to state financial management. Fuzzy set theory is used to represent imprecision in evaluated information and judgments. The results of this evaluation are compared to a parallel journalistic effort to rank state performance. The article highlights the differences between the two approaches and outlines the advantages of the fuzzy rule‐based system.

Financial management is one of the most important management tasks of government. The complexity of financial management systems has discouraged overall evaluations of financial management. The objective of this article is to develop a method for evaluating government financial management that can handle this complexity. A fuzzy rule–based system (FRBS) is a methodology that can use many different types of data, produce robust input measures and can capture the complex contextual judgment of experts. Using data collected as part of the Government Performance Project survey of large cities, we develop an FRBS for city financial management.

AbstractOver the past few years, academics have undertaken initiatives to bridge the gap between theory and practice in the ever‐growing field of business analytics, including implementing real‐life student projects in all shapes and forms. Every year since 2015, Manhattan College has invited student teams from across North America and elsewhere in the world to its campus in order to participate in an intercollegiate business analytics competition (BAC@MC). This well‐received event and the objectives behind it are described in this article. The program is shown to serve as an effective experiential learning adventure for the undergraduate students as it hones their data analytic skills in the context of an engaging real‐world business problem. The roles various stakeholders play in this high‐impact practice are highlighted. Furthermore, an example of a recent competition question is presented (along with a summary of the analytical approaches attempted) by the student teams. Descriptive visualizations, regression, and cluster algorithms implemented using python, R, Excel, or Tableau are among the typical analyses utilized by participating students. As witnessed by the students, faculty advisors, and the industry practitioners who attended the event, competitions such as BAC@MC can be rewarding, community‐building, and transformative experiences for undergraduate students who will soon become tomorrow's business analysts.

Credit ratings remain a key feature of municipal debt management. The primary objective of this article is to develop a new methodology for evaluating the financial performance and creditworthiness of governments and to illustrate this approach for a sample of large American cities. Specifically, we develop a fuzzy rule–based system (FRBS) that uses economic, debt, and other financial information as well as a measure of financial management to produce rankings of city financial performance. The FRBS credit ratings are highly correlated with actual Moody's ratings for these cities. FRBS have the potential of enhancing the rating process by standardizing the information used and encouraging consistent rules about what combinations of inputs result in good, fair, or poor performance.

A growing body of research has focused on evaluating the effectiveness of human resource management systems, yet few efforts have been made to develop a set of criteria and a method for evaluating human resource management systems in the public sector As part of the Government Performance Project, the present study offers a framework and methodology to fill this gap The Government Performance Project worked with a panel of experts to identify relevant criteria to evaluate pubhc sector human resource systems and to construct a survey instrument aligned with the identified criteria After discussing the criteria and survey construction, the article introduces a method of evaluating human resource management systems, fuzzy logic, that models expert judgments and takes into account measurement imprecision