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Improving prediction with POS and PLS consistent estimations: An illustration

机译:使用POS和PLS一致的估计来改进预测:一个例子

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Recent advances (Dijkstra and Henseler, 2015a, 2015b) have introduced methods that provide consistent PLSc estimates. In parallel, Becker et al. (2013) propose a novel prediction oriented segmentation (POS) approach which by taking into account unobserved heterogeneity increases the predictive power with regard to the dependent variables. Hence, the main objective of this paper is to show how the complementary use of PLSc and POS can increase the overall predictive ability of the PLS approach. A concrete example, carefully following the presentation guidelines provided by Henseler et al. (2016), in a Moroccan context demonstrates the plausibility of such a proposal and concretely shows the existence of three different groups of people with different reactions toward counterfeiting. The stability of this segmentation is verified as well as the causal asymmetry of data. Managerial implications with respect to these three groups are highlighted, thanks also to a complementary importance-performance matrix analysis. (C) 2016 Elsevier Inc. All rights reserved.
机译:最近的进展(Dijkstra和Henseler,2015a,2015b)引入了提供一致的PLSc估计的方法。同时,贝克尔等人。 (2013年)提出了一种新颖的面向预测的细分(POS)方法,该方法通过考虑未观察到的异质性来提高因变量的预测能力。因此,本文的主要目的是说明PLSc和POS的互补使用如何提高PLS方法的总体预测能力。一个具体的例子,认真遵循Henseler等人提供的演示准则。 (2016年)在摩洛哥的语境中证明了这一提议的合理性,并具体表明了存在三个对伪造有不同反应的不同人群。验证了这种分割的稳定性以及数据的因果不对称性。强调了对这三类人的管理意义,这也要归功于互补的重要性-绩效矩阵分析。 (C)2016 Elsevier Inc.保留所有权利。

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