Joan M. Donohue

A multi-method evaluation of journals in the decision and management sciences by US academics

Numerous studies published in the academic literature address the issue of journal quality. However, little has been done to evaluate the broad set of journals pertinent to academic research in the decision and management sciences. This study examines the quality of such journals from a US point of view using both survey- and citation-based measures of journal quality. The survey-based measure is the perceived quality ratings assigned by US academics in the management science field. The citation-based measure is the impact factor, an indication of how often the articles in a journal are cited. This study finds that perceived quality ratings of the journals are positively correlated with citation impact factors. Also, both of these quality measures are found to be positively correlated with journal circulation and negatively correlated with acceptance rate. Journal quality ratings appear to vary across reviewers with different research interest areas and reviewers seem to rate journals higher if they have published in them.

A Dynamic Programming Based Pruning Method for Decision Trees

This paper concerns a decision-tree pruning method, a key issue in the development of decision trees. We propose a new method that applies the classical optimization technique, dynamic programming, to a decision-tree pruning procedure. We show that the proposed method generates a sequence of pruned trees that are optimal with respect to tree size. The dynamic-programming-based pruning (DPP) algorithm is then compared with cost-complexity pruning (CCP) in an experimental study. The results of our study indicate that DPP performs better than CCP in terms of classification accuracy.

Simulation designs and correlation induction for reducing second-order bias in first-order response surfaces

Construction of simulation designs for the estimation of response surface metamodels is often based on optimal design theory. Underlying such designs is the assumption that the postulated model provides the correct representation of the simulated response. As a result, the location of design points and the assignment of pseudorandom number streams to these experiments are determined through the minimization of some function of the covariance matrix of the model coefficient estimators. In contrast, we assume that the postulated model may be incorrect. Attention is therefore directed to the development of simulation designs that offer protection against the bias due to possible model misspecification as well as error variance. The particular situation examined is the estimation of first-order response surface models in the presence of polynomials of order two. Traditional two-level factorial plans combined with one of three pseudorandom number assignment strategies define the simulation designs. Specification of the factor settings for these experimental plans are based on two integrated mean squared error criteria of particular interest in response surface studies. For both design criteria, comparisons of the optimal designs across the three assignment strategies are presented to assist experimenters in the selection of an appropriate simulation design.

A sequential experimental design procedure for the estimation of first- and second-order simulation metamodels

Simulation metamodels find apphcation m the study of complex systems that cannot be solved analytically. These metamodels represent efficient tools for studying the characteristics of the more comphcated simulation model, provide needed insight into the problems of computer model validation and verification, and allow for the prediction of both system performance and op’umum operating conditions. This article presents a procedure for the construction of sequential simulation designs for the estimation of response surface metamodels. The first set of experiments is defined as a fractional two-level factorial design augmented with rephcated center points. Information from these experiments 1s used to estimate the levels of the factorial design points that constitute the second stage of experimentation If observations on this two-stage, first-order design suggest the presence of unfitted quadratic terms, a thn-d set of observations corresponding to the axial portion of a central composite design M taken to allow for the estimation of a second-order metamodel, Two types of performance criteria are considered in the specdlcation of the factor settings in the second and third stages: (1) minimizing errors associated with predicting the response variable and (2) mimmizmg errors involved with estimating the response function slopes. Additionally, three methods of assigning random number streams to the stochastic components of the simulation model are considered: (1) independent streams, (2) common streams, and (3) the assignment rule blocking strategy, An example illustrating the use of the sequential design procedure is presented, and a Monte Carlo study investigates the performance of the two variance reduction techniques (common streams and the assignment rule) relatlve to independent stream sets. Empirical results mdlcate a preference for the assignment rule strategy for the estimation of both firstand second-order metamodels,

Outlets for operations management research: a DEA assessment of journal quality and rankings

Determining the quality of research outlets is important for Operations Management (OM) for reasons well documented in the published literature. Over the past few decades, utilising several different methodologies from a variety of perspectives, 15 studies have assessed the quality of journals that publish OM research. The published results are inconsistent in that the relative quality of journals varies from one study to the next and no single set of OM journals is unanimously recognised as being the top set. Historically, OM researchers have published in a wide variety of journals, utilised a variety of research methodologies and studied a broad range of topics. Given that each of the 15 studies assessed journal quality from a different perspective and utilised different methodologies, they represent a diversity of opinions regarding the OM field and add to the knowledge base regarding the quality of OM research outlets. In this paper, we combine the published results in a data envelopment analysis (DEA) model to assess the quality of the most visible journals that publish OM research. DEA is a linear programming tool for the evaluation of decision-making units and its use in our context (a meta-analysis of journal quality studies) is a new application of the technique. Our results suggest that the top 10 outlets for OM research include five journals that are considered OM dedicated, two Operations Research journals, one Engineering journal and two Interdisciplinary journals.

Experimental designs for simulation

Experimental design issues are an important and integral aspect of most simulation studies. The intent of this paper is to provide an overview of research on design issues that are unique to experimentation in a simulation environment. Tactical issues such as the length of simulation runs and number of replications are not discussed here. Instead, we focus our discussion on strategic issues such as the selection of design plans, statistical models, input variables, and random number stream assignments.

Some optimal simulation designs for estimating quadratic response surface functions

Presents some experimental design strategies for simulation studies involving the estimation of quadratic response surfaces. Optimal design plans are developed in four common second-order design classes (central composite, Box-Behnken, three-level factorial, and small composite designs) using a criterion which incorporates both the bias and variance of the predicted response variable. Three methods of assigning pseudorandom number streams to design points are considered: independent streams, common streams, and the simultaneous use of common and antithetic streams in an orthogonally blockable experimental design. Each method uses independent streams for replications of design points. The findings indicate that carefully planned experimental designs can substantially improve the estimation of quadratic response surface models.<<ETX>>

Twenty-six years of operations management research (1985–2010): authorship patterns and research constituents in eleven top rated journals

This paper investigates the research contributions over a 26-year time frame (1985–2010) of academic institutions and individual authors to the field of operations management (OM). We use two measures, shared articles and distributed articles, to assess the research productivity of institutions as well as individual researchers. Further we assess the contribution of institutions based on affiliated author research as well as the research of their PhD graduates. In order to accomplish this, we utilise the published OM research articles in 11 top-rated and well-known academic journals over the time period from 1985 to 2010. In addition to the research, contributions of academic institutions and individual authors, we look at several bibliometric statistics related to this body of published research. These measures indicate that the research constituency is growing as evidenced by increasing numbers of researchers and institutions represented. Lastly, the collaboration between researchers appears to be increasing as evidenced by an increasing percentage of articles with three or more authors and the average number of authors per article published.

The origins of research and patterns of authorship in the International Journal of Production Research

This paper evaluates the origins of the research that has been published in the International Journal of Production Research (IJPR) for the time period 1985–2010, which includes approximately 77% of all articles that have been published in IJPR since its inception. We assess the productivity of individual authors, the author’s affiliation at the time each article was published, the country the author’s affiliation is located, and the institution where the author was granted a Ph.D. degree. By analysing the countries in which author affiliations are located, we can determine which countries are having the greatest impact on defining the research published in IJPR. For international journals, it is important to publish research from an international constituency, thus maintaining one of its purposes. By analysing the affiliations of the authors as well as where the authors received their Ph.D. training, we can determine which institutions are having the greatest contributions to the research published in IJPR. We believe it is useful to consider both the affiliations of the authors and where the authors received their academic training since both are indicative of an institution’s true influence on a journal. To date, no published study has examined the individuals, institutions, and countries that have contributed to IJPR and, in particular, where the contributing researchers received their Ph.D. degrees.

Sequential experimental designs for simulation metamodeling

A procedure is developed for the construction of sequential simulation designs for the estimation of firstand second-order response surface met amodela. The first stage of experimentation involves the use of a fractional two-level factorial design augmented with replicated center points. Information obtained from this experimental design is used to estimate the “optimal” location of the factorial design points for the second stage of experimentation. Two types of performance criteria are considered in the specification of the factor settings: (1) integrated mean squared error of the predicted response variable, and (2) integrated mean squared error of the response function slopes. Additional data is collected in the second stage using a different fraction of the t we-level factorial design. If quadratic curvature is indicated, a third stage of experimentation is performed to collect data for the axial portion of a central composite design. Two performance criteria are considered in the specification of the optimal azial levels: (1) integrated variance error of the predicted response variable, and (2) integrated variance error of the response function slopes. The selection of factor levels in the second and third stages also depends on the strategy used in assigning random number streams to the stochastic components of the simulation model. We investigate three assignment methods (independent streams, common streams, and the assignment rule blocking strategy), and we develop sequential design plans for each strategy.