Measuring the arts: The case of Dade County nonprofits arts organizations

The theoretical analysis and research of cultural activities have been limited, for the most part, to the study of the role the public sector plays in the funding and support of nonprofit Arts organizations. The tools used to evaluate this intervention follow a macroeconomic perspective and fail to account for microeconomic principles and assumptions that affect the behavior of these organizations. This dissertation describes through conceptual models the behavior of the agents involved in the artistic process and the economic sectors affected by it. The first paper deals with issues related to economic impact studies and formulates a set of guidelines that should be followed when conducting this type of study. One of the ways to assess more accurately the impact culture has in a community is by assuming that artists can re-create the public space of a blight community and get it ready for a regeneration process. The second paper of this dissertation assumes just that and explains in detail all the cultural, political, economic and sociological interactions that are taking place in the Arts-led regeneration process in Miami Beach, Florida. The paper models the behavior of these agents by indicating what their goals and decision process mechanisms are. The results give support to the claim that the public space artists create in a city actually stimulate development. The third paper discusses the estimation of a demand function for artistic activities, specifically the New World Symphony (NWS) located in Miami Beach, Florida. The behavior of the consumers and producers of NWS' concerts is modeled. The results support the notion that consumers make their decisions based, among other things, on the perceived value these concerts have. Economists engage in the analysis of the effects of cultural activities in a community since many cities rely on them for their development. The history of many communities is not told by their assembly lines and machinery anymore but by their centers of entertainment, hotels and restaurants. Many cities in Europe and North America that have seen the manufacturing sector migrate to the South are trying to face the demands of the new economy by using the Arts as catalysts for development. ^

Analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.