Personalized Assortment Optimization under Consumer Choice Models with Local Network Effects

2020 ◽  
Author(s):  
Tong Xie ◽  
Zizhuo Wang
Keyword(s):  
Consumer Choice ◽  
Network Effects ◽  
Choice Models ◽  
Local Network ◽  
Assortment Optimization

Consumer Choice Models with Endogenous Network Effects

2017 ◽  
Vol 63 (11) ◽  
pp. 3944-3960 ◽  
Author(s):  
Ruxian Wang ◽  
Zizhuo Wang
Keyword(s):  
Consumer Choice ◽  
Network Effects ◽  
Choice Models

Consumer Choice Models with Endogenous Network Effects

2014 ◽  
Author(s):  
Ruxian Wang ◽  
Zizhuo Wang
Keyword(s):  
Consumer Choice ◽  
Network Effects ◽  
Choice Models

scholarly journals Consumer choice and local network effects in mobile telecommunications in Turkey

2013 ◽  
Vol 37 (4-5) ◽  
pp. 334-344 ◽  
Author(s):  
Mehmet Karacuka ◽  
A. Nazif Çatık ◽  
Justus Haucap
Keyword(s):  
Consumer Choice ◽  
Network Effects ◽  
Local Network ◽  
Mobile Telecommunications

Data pruning in consumer choice models

2006 ◽  
Vol 4 (3) ◽  
pp. 267-287 ◽  
Author(s):  
Elaine L. Zanutto ◽  
Eric T. Bradlow
Keyword(s):  
Consumer Choice ◽  
Choice Models ◽  
Data Pruning

The asymmetric effects of local and global network ties on firms’ innovation performance

2018 ◽  
Vol 33 (3) ◽  
pp. 377-389 ◽  
Author(s):  
Lei Wang ◽  
Jun Li ◽  
Shaoqing Huang
Keyword(s):  
Structural Equation ◽  
Network Effects ◽  
Institutional Environment ◽  
Innovation Performance ◽  
Global Network ◽  
Local Network ◽  
Network Ties ◽  
Content Type ◽  
Asymmetric Effects ◽  
Absorptive Capacities

Purpose The purpose of this paper is to develop and empirically test a theoretical framework examining how local network ties and global network ties affect firms’ innovation performance via their absorptive capacities. Design/methodology/approach The conceptual framework is empirically tested in a field study with multi-source data collected from a sample of 297 manufacturing firms located in four. Manufacturing clusters in the south-eastern Yangtze River Delta of China. Hypotheses were tested with the use of path analysis with maximum likelihood robust estimates through the structural equation modelling approach. Findings The asymmetry between local network ties (LNT) and global network ties (GNT) in terms of influences on firms’ innovation performance is confirmed by empirical tests. LNT not only significantly and positively contribute to firms’ innovation performance directly but also enhance it indirectly via absorptive capability, whereas GNT exhibit only marginal influence on innovation performance. GNT are shown to boost innovation performance (IP) only indirectly via firms’ absorptive capacities. Knowledge heterogeneity and the difference between domestic and multinational firms’ institutional environment are considered to be the main causes of the asymmetric effects. Originality/value While the previous literature either focused on the mediating role of firms’ knowledge absorptive capacities or investigated the effects of social networks separately, this study incorporates both mechanisms into a single analytical framework to better account for the interactions between network effects and absorptive capacities. The results challenge some previous studies positing that GNT are stronger determinants than LNT in shaping a local firm’s innovation capacity in emerging economies, and the findings emphasize the importance of absorptive capacity in helping local enterprises to leverage external linkages to enhance firm’s innovation performance.

Optimal and Competitive Assortments with Endogenous Pricing Under Hierarchical Consumer Choice Models

2011 ◽  
Vol 57 (9) ◽  
pp. 1546-1563 ◽  
Author(s):  
A. Gürhan Kök ◽  
Yi Xu
Keyword(s):  
Consumer Choice ◽  
Choice Models

scholarly journals Assortment Optimization Under Consider-Then-Choose Choice Models

2020 ◽  
Author(s):  
Ali Aouad ◽  
Vivek Farias ◽  
Retsef Levi
Keyword(s):  
Predictive Power ◽  
Optimization Problems ◽  
Choice Models ◽  
Empirical Literature ◽  
Data Sets ◽  
Prediction Errors ◽  
Programming Framework ◽  
Assortment Optimization ◽  
Computational Aspects ◽  
Two Phases

Consider-then-choose models, borne out by empirical literature in marketing and psychology, explain that customers choose among alternatives in two phases, by first screening products to decide which alternatives to consider and then ranking them. In this paper, we develop a dynamic programming framework to study the computational aspects of assortment optimization under consider-then-choose premises. Although nonparametric choice models generally lead to computationally intractable assortment optimization problems, we are able to show that for many empirically vetted assumptions on how customers consider and choose, our resulting dynamic program is efficient. Our approach unifies and subsumes several specialized settings analyzed in previous literature. Empirically, we demonstrate the predictive power of our modeling approach on a combination of synthetic and real industry data sets, where prediction errors are significantly reduced against common parametric choice models. In synthetic experiments, our algorithms lead to practical computation schemes that outperform a state-of-the-art integer programming solver in terms of running time, in several parameter regimes of interest. This paper was accepted by Yinyu Ye, optimization.

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