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Evolutionary learning methodology: A case study of R&D strategy development

机译:进化学习方法:R&D策略制定的案例研究

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摘要

This article concerns the notion of methodology in strategic management of R&D/technology. Though development of new tools and methods has received much attention during the recent decades, attention to understanding methodologies has remained disproportionally low. In this study we distinguish two methodologies that are used in strategic management of R&D/ technology: planning methodology and evolutionary learning methodology. We mainly focus on defining and describing the origins, nature, and characteristics of the latter. We propose a framework for methodology selection by investigating context, content, and process factors. Using this framework, we provide supportive evidence for appropriateness of evolutionary learning methodology to develop a robust R&D strategy for Iran's power industry. We then describe the details of operationalizing the methodology for the Iranian power industry. This study is particularly focused on delineating how evolutionary learning methodology can be applied as an effective framework to improve the formation method and content of R&D strategy. We conclude that methodological knowledge can provide a powerful lens with which to understand performance of methods, and we suggest that evolutionary learning methodology is particularly appropriate for the following situations: when the environment is uncertain or fast changing, when there exist many stakeholders with conflicting interests, and when a method needs to be applied in a context other than the one for which it was initially developed.
机译:本文涉及R / D /技术战略管理中的方法论概念。尽管在最近的几十年中,新工具和方法的开发受到了很多关注,但是对理解方法学的关注仍然不成比例。在这项研究中,我们区分了在R / D /技术的战略管理中使用的两种方法:计划方法和进化学习方法。我们主要集中于定义和描述后者的起源,性质和特征。我们通过调查背景,内容和过程因素,为方法选择提供了一个框架。使用此框架,我们为进化学习方法论的适当性提供支持性证据,以开发针对伊朗电力行业的稳健的研发策略。然后,我们描述了为伊朗电力行业实施方法论的细节。这项研究特别着重于描述如何将进化学习方法作为一种有效的框架来改进R&D策略的形成方法和内容。我们得出结论,方法论知识可以提供一个强大的视角来理解方法的性能,并且我们建议进化学习方法论尤其适用于以下情况:当环境不确定或快速变化时,当存在许多利益冲突的利益相关者时,以及何时需要在最初为其开发的环境之外的其他环境中应用该方法。

著录项

  • 来源
    《Technological forecasting and social change》 |2013年第5期|956-976|共21页
  • 作者单位

    Department of Social and Decision Sciences, Carnegie Mellon University. 5000 Forbes Avenue, BP208, Pittsburgh, PA 15213, USA,Catdlica Lisbon School of Business and Economics, Universidade Catdlica Portuguesa, Palma de Cima, 1649-023 Lisbon, Portugal,Institute/ Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pats, 1049-001 Lisbon, Portugal;

    Graduate School of Management and Economics, Sharif University of Technology, Azadi Ave, Tehran, Iran;

    Department of Social and Decision Sciences, Carnegie Mellon University. 5000 Forbes Avenue, BP208, Pittsburgh, PA 15213, USA,Department of Engineering and Public Policy, Carnegie Mellon University, 5000 Forbes Avenue, BP 208, Pittsburgh, PA 15213, USA;

    Niroo Research Institute (NRI), Poonak Bakhtari Ave., Shahrake Charb, Tehran, Iran;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Methodology; Evolutionary epistemology; Learning; RD strategy; Roadmapping; Expert judgment;

    机译:方法;进化认识论;学习;研发策略;路线图;专家判断;

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