116,619 research outputs found

    ILR Research in Progress 2011-12

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    The production of scholarly research continues to be one of the primary missions of the ILR School. During a typical academic year, ILR faculty members published or had accepted for publication over 25 books, edited volumes, and monographs, 170 articles and chapters in edited volumes, numerous book reviews. In addition, a large number of manuscripts were submitted for publication, presented at professional association meetings, or circulated in working paper form. Our faculty's research continues to find its way into the very best industrial relations, social science and statistics journals.Research_in_Progress_2011_12.pdf: 46 downloads, before Oct. 1, 2020

    Using simulation gaming to validate a mathematical modeling platform for resource allocation in disasters

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    The extraordinary conditions of a disaster require the mobilisation of all available resources, inducing the rush of humanitarian partners into the affected area This phenomenon called the proliferation of actors, causes serious problems during the disaster response phase including the oversupply, duplicated efforts, lack of planning In an attempt to reduce the partner proliferation problem a framework called PREDIS (PREdictive model for DISaster response partner selection) is put forward to configure the humanitarian network within early hours after disaster strike when the information is scarce To verify this model a simulation game is designed using two sets of real decision makers (experts and non-experts) in the disaster Haiyan scenario The result shows that using the PREDIS framework 100% of the experts could make the same decisions less than six hours comparing to 72 hours Also between 71% and 86% of the times experts and non-experts decide similarly using the PREDIS framewor

    Measuring Software Process: A Systematic Mapping Study

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    Context: Measurement is essential to reach predictable performance and high capability processes. It provides support for better understanding, evaluation, management, and control of the development process and project, as well as the resulting product. It also enables organizations to improve and predict its process’s performance, which places organizations in better positions to make appropriate decisions. Objective: This study aims to understand the measurement of the software development process, to identify studies, create a classification scheme based on the identified studies, and then to map such studies into the scheme to answer the research questions. Method: Systematic mapping is the selected research methodology for this study. Results: A total of 462 studies are included and classified into four topics with respect to their focus and into three groups based on the publishing date. Five abstractions and 64 attributes were identified, 25 methods/models and 17 contexts were distinguished. Conclusion: capability and performance were the most measured process attributes, while effort and performance were the most measured project attributes. Goal Question Metric and Capability Maturity Model Integration were the main methods and models used in the studies, whereas agile/lean development and small/medium-size enterprise were the most frequently identified research contexts.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2016-76956-C3-2- RMinisterio de Economía y Competitividad TIN2015-71938-RED

    Developing an inter-enterprise alignment maturity model: research challenges and solutions

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    Business-IT alignment is pervasive today, as organizations strive to achieve competitive advantage. Like in other areas, e.g., software development, maintenance and IT services, there are maturity models to assess such alignment. Those models, however, do not specifically address the aspects needed for achieving alignment between business and IT in inter-enterprise settings. In this paper, we present the challenges we face in the development of an inter-enterprise alignment maturity model, as well as the current solutions to counter these problems

    A requirements engineering framework for integrated systems development for the construction industry

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    Computer Integrated Construction (CIC) systems are computer environments through which collaborative working can be undertaken. Although many CIC systems have been developed to demonstrate the communication and collaboration within the construction projects, the uptake of CICs by the industry is still inadequate. This is mainly due to the fact that research methodologies of the CIC development projects are incomplete to bridge the technology transfer gap. Therefore, defining comprehensive methodologies for the development of these systems and their effective implementation on real construction projects is vital. Requirements Engineering (RE) can contribute to the effective uptake of these systems because it drives the systems development for the targeted audience. This paper proposes a requirements engineering approach for industry driven CIC systems development. While some CIC systems are investigated to build a broad and deep contextual knowledge in the area, the EU funded research project, DIVERCITY (Distributed Virtual Workspace for Enhancing Communication within the Construction Industry), is analysed as the main case study project because its requirements engineering approach has the potential to determine a framework for the adaptation of requirements engineering in order to contribute towards the uptake of CIC systems

    Used-habitat calibration plots: a new procedure for validating species distribution, resource selection, and step-selection models

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    “Species distribution modeling” was recently ranked as one of the top five “research fronts” in ecology and the environmental sciences by ISI's Essential Science Indicators (Renner and Warton 2013), reflecting the importance of predicting how species distributions will respond to anthropogenic change. Unfortunately, species distribution models (SDMs) often perform poorly when applied to novel environments. Compounding on this problem is the shortage of methods for evaluating SDMs (hence, we may be getting our predictions wrong and not even know it). Traditional methods for validating SDMs quantify a model's ability to classify locations as used or unused. Instead, we propose to focus on how well SDMs can predict the characteristics of used locations. This subtle shift in viewpoint leads to a more natural and informative evaluation and validation of models across the entire spectrum of SDMs. Through a series of examples, we show how simple graphical methods can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity. Identifying habitat characteristics that are not well-predicted by the model can provide insights into variables affecting the distribution of species, suggest appropriate model modifications, and ultimately improve the reliability and generality of conservation and management recommendations
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