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When 'significant' is not significant

机译:当“重要”不重要时

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摘要

Big data is here for some and coming for many. It promises access to new knowledge along with some challenges, but let's not forget the important lessons of the past to ensure that we are advancing knowledge and making the right decisions from the data we have. In this paper, we submit that marketing's emphasis on statistical significance is misplaced, especially in the new world of big data. We include case examples to demonstrate how statistical significance is easy to find, but not necessarily important. We will also discuss the alternative route for generating robust knowledge. Specifically, we espouse the tradition pioneered by Andrew Ehrenberg of Many Sets of Data (MSoD) and descriptive models as the way to advance marketing science, and as a solid foundation for data interpretation in market research studies. We offer insights for market research practitioners and marketers alike, to ensure they are getting the best from their data for robust marketing decision-making.
机译:大数据对于某些人来说是在这里,而对于许多人来说则是即将到来的。它有望获得新知识并带来一些挑战,但是我们不要忘记过去的重要经验,以确保我们不断发展知识并根据已有的数据做出正确的决策。在本文中,我们认为市场营销对统计意义的强调是错位的,尤其是在新的大数据世界中。我们提供了一些案例,以说明如何轻松找到统计意义,但不一定重要。我们还将讨论生成可靠知识的替代途径。具体来说,我们拥护多数据集(MSoD)的安德鲁·埃伦伯格(Andrew Ehrenberg)所倡导的传统和描述性模型,以此作为推进营销科学的方法,并为市场研究中的数据解释奠定了坚实的基础。我们为市场研究从业人员和市场营销人员提供见解,以确保他们从数据中获得最大的收益,以进行有效的市场营销决策。

著录项

  • 来源
    《International Journal of Market Research》 |2014年第5期|591-607|共17页
  • 作者单位

    Univ S Australia, Ehrenberg Bass Inst Mkt Sci, Adelaide, SA 5001, Australia;

    Univ S Australia, Ehrenberg Bass Inst Mkt Sci, Adelaide, SA 5001, Australia;

    Univ S Australia, Ehrenberg Bass Inst Mkt Sci, Adelaide, SA 5001, Australia;

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  • 正文语种 eng
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