206,672 research outputs found

    Green BPM as a business-oriented discipline : a systematic mapping study and research agenda

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    Green Business Process Management (BPM) focuses on the ecological impact of business processes. This article provides a systematic mapping study of Green BPM literature to evaluate five attributes of the Green BPM research area: (1) scope, (2) disciplines, (3) accountability, (4) researchers and (5) quality control. The results allow developing a research agenda to enhance Green BPM as an approach for environmentally sustainable organizations. We rely on a dichotomy of knowledge production to present research directives relevant for both academics and practitioners in order to help close a rigor-relevance gap. The involvement of both communities is crucial for Green BPM to advance as an applied, business-oriented discipline

    Essential guidelines for computational method benchmarking

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    In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology.Comment: Minor update

    Evaluation of innovative technology market potential on the basis of technology audit

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    Enterprise innovation activity supposes coordinated technical and business processes of decision-making and its performance required for successful transformation of new product or service from concept to market. The purpose of this study is to develop valuation methods of innovative technology market potential and prospects of their introduction into the production enterprise activity. In order to achieve this goal, we used brand new evaluation tool, this is technology audit conception, application of which increased significantly the accuracy and reliability of technology market potential evaluation. Clarification of terminological essence of technological audit allowed the authors to discover the content of technology audit components required for the market research and thereupon to develop evaluation mechanism for innovative technology market potential using technology audit. This mechanism is built on structure evaluation table of technology market potential level detection as an object of commercialization. To ensure the efficiency of practical effect of the mechanism proposed, the authors systematized and completed methods of functional analysis and scanning of market environment for the purpose of qualitative comprehensive evaluation and innovative technology market potential forecasting. Introduction of the proposed evaluation method for technology market potential will result in the improvement of efficiency of enterprise innovation activity due to more rational distribution of available resources and immediate financing of developments with greater market potential

    Essential guidelines for computational method benchmarking

    Get PDF
    In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology
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