Can involving clients in simulation studies help them solve their future problems? A transfer of learning experiment

It is often stated that involving the client in operational research studies increases conceptual learning about a system which can then be applied repeatedly to other, similar, systems. Our study provides a novel measurement approach for behavioural OR studies that aim to analyse the impact of modelling in long term problem solving and decision making. In particular, our approach is the first to operationalise the measurement of transfer of learning from modelling using the concepts of close and far transfer, and overconfidence. We investigate learning in discrete-event simulation (DES) projects through an experimental study. Participants were trained to manage queuing problems by varying the degree to which they were involved in building and using a DES model of a hospital emergency department. They were then asked to transfer learning to a set of analogous problems. Findings demonstrate that transfer of learning from a simulation study is difficult, but possible. However, this learning is only accessible when sufficient time is provided for clients to process the structural behaviour of the model. Overconfidence is also an issue when the clients who were involved in model building attempt to transfer their learning without the aid of a new model. Behavioural OR studies that aim to understand learning from modelling can ultimately improve our modelling interactions with clients; helping to ensure the benefits for a longer term; and enabling modelling efforts to become more sustainable

Industry Structure Similarities, Trade Agreements, and Business Cycle Synchronization

This paper analyzes the effects of industry structure similarities, free trade agreements, and geographic borders on regional business cycle correlation, using fifty US states, 10 Canadian provinces, and 1 Canadian territory as a case study. Using two cross-sectional OLS regressions and one panel data OLS regression, this study finds that pair-wise gross territorial product growth correlation decreased significantly after NAFTA ratification for state-state, province-province, and state-province territorial pairs, contrary to previous literature’s results. NAFTA effectively decoupled intra-national business cycles in the US and Canada while also desynchronizing cross-border pair-wise GSP growth correlation, but cross-border pair-wise GSP growth correlation was much less desynchronized post-NAFTA relative to intra-national pairs. These results indicate that NAFTA and the US-Canada border may produce two opposing forces that dampen each other’s desynchronizing effects

Similarity measures for mid-surface quality evaluation

Mid-surface models are widely used in engineering analysis to simplify the analysis of thin-walled parts, but it can be difficult to ensure that the mid-surface model is representative of the solid part from which it was generated. This paper proposes two similarity measures that can be used to evaluate the quality of a mid-surface model by comparing it to a solid model of the same part. Two similarity measures are proposed; firstly a geometric similarity evaluation technique based on the Hausdorff distance and secondly a topological similarity evaluation method which uses geometry graph attributes as the basis for comparison. Both measures are able to provide local and global similarity evaluation for the models. The proposed methods have been implemented in a software demonstrator and tested on a selection of representative models. They have been found to be effective for identifying geometric and topological errors in mid-surface models and are applicable to a wide range of practical thin-walled designs

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Department of Management EngineeringFirms participating in printer industries have invested their constrained resources into technology development in order to sustain their competitiveness in the industry. Considering the fast-changing market circumstances, each firm???s own investment decisions on technology portfolio may directly affect their performance. In this study, we analyzed patent data, namely number of forward citations and technological classification data (CPC). Using this data, the technological portfolio of a specific firm can be identified, which can further help our understanding on firms??? R&D investment strategies. Number of studies mainly focused on patent class combinations of individual technology level, but portfolios of patent class at a firm level have been understudied. In this study, we tracked the change of class composition within each firms??? technological patents??? portfolio and attempted to identify practical and theoretical implications to portfolio management. We utilized Entropy Index, Co-occurrence and cosine similarities measurements for each indicating diversification, patent scope and portfolio similarities within each patents??? classification subclasses. Additionally, performance evaluation of each portfolio is conducted using forward citation data. This paper shows that in-depth patent data analysis can allow us to explore deeper insights at various levels, individual technology, products and product lines, and firms sufficing different stories.ope

Topic Similarity Networks: Visual Analytics for Large Document Sets

We investigate ways in which to improve the interpretability of LDA topic models by better analyzing and visualizing their outputs. We focus on examining what we refer to as topic similarity networks: graphs in which nodes represent latent topics in text collections and links represent similarity among topics. We describe efficient and effective approaches to both building and labeling such networks. Visualizations of topic models based on these networks are shown to be a powerful means of exploring, characterizing, and summarizing large collections of unstructured text documents. They help to "tease out" non-obvious connections among different sets of documents and provide insights into how topics form larger themes. We demonstrate the efficacy and practicality of these approaches through two case studies: 1) NSF grants for basic research spanning a 14 year period and 2) the entire English portion of Wikipedia.Comment: 9 pages; 2014 IEEE International Conference on Big Data (IEEE BigData 2014