Improving prediction with POS and PLS consistent estimations: An illustration

被引:19
|
作者
Mourad, Siham [1 ]
Valette-Florence, Pierre [2 ,3 ]
机构
[1] ISCAE Grp, Km 9,500 Route Nouasseur BP 8114, Casablanca 20000, Morocco
[2] Grenoble Alpes Univ, IAE, Grenoble, France
[3] Grenoble Alpes Univ, CERAG, Grenoble, France
关键词
PLS prediction; Prediction oriented segmentation (POS); Consistent PLSc; Counterfeiting resistance; Luxury brand; Brand loyalty; UNOBSERVED HETEROGENEITY; FIT INDEXES; SQUARES; PERFORMANCE; VALIDITY; MODELS;
D O I
10.1016/j.jbusres.2016.03.057
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:4675 / 4684
页数:10
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