scholarly journals Fuzzy regression model of the impact of technology on living standards

2020 ◽  
pp. 67-81
Author(s):  
Yury Zelenkov ◽  
Elizaveta Lashkevich
Keyword(s):  
Regression Model ◽  
Living Standards ◽  
Fuzzy Regression ◽  
Fuzzy Regression Model ◽  
Impact Of Technology ◽  
The Impact

Fuzzy regression model for forecasting impact of venture capital network and underwriter network on IPO premium

2021 ◽  
pp. 1-11
Author(s):  
Yuan Tian
Keyword(s):  
Venture Capital ◽  
Regression Model ◽  
Initial Public Offerings ◽  
Secondary Market ◽  
Fuzzy Regression ◽  
Central Position ◽  
Public Offerings ◽  
Fuzzy Regression Model ◽  
Market Premium ◽  
The Impact

In recent years, social network analysis is one of the top 20 fields of artificial intelligence. Based on the network signal theory, this study examines the influence of the dual network embeddedness on the price premiums of Chinese initial public offerings (IPOs). In this paper we proposed fuzzy regression model for forecasting the impact of venture capital network and underwriter network on IPO premium based on some hypothesis. We find that: (1) Enterprises embedded in the central position of venture capital network will increase the IPO secondary market premium; (2) Secondly, employing underwriter in the central position of underwriting network will increase the IPO secondary market premium; (3) As venture capital are getting closer to the central position of venture capital network, the influence of underwriter network centrality in underwriting network on the increase of IPO secondary market reaction will gradually weaken. The research shows that occupying central position both in venture capital syndication network and underwriting network have the functions of sending signals, then increase the IPO secondary market premium, but the functions of different network signals will replace each other.

A Composite-Model for E-Commerce Diffusion

2008 ◽  
pp. 2929-2947 ◽  
Author(s):  
Alexander Yap ◽  
Jayoti Das ◽  
John Burbridge ◽  
Kathryn Cort
Keyword(s):  
Cluster Analysis ◽  
Regression Model ◽  
Composite Model ◽  
Internet Usage ◽  
The Internet ◽  
Economic Factors ◽  
Cross Country ◽  
Impact Of Technology ◽  
The Impact ◽  
Socio Economic Factors

Why are some countries successful with e-commerce while others flounder? The purpose of this article is to study the impact of technology, cultural, and socio-economic factors on the global diffusion of e-commerce. While past studies have focused on technology reasons alone, this research includes cultural and socio-economic factors as well. Having access to the Internet does not necessarily translate to e-commerce usage. Fundamentally, culture and socio-economic factors are pivotal in bridging the gap between Internet usage and e-commerce diffusion. The objective is to provide a model that quantifies the aggregated influences of all factors on global e-commerce diffusion. A cross-country regression model analyzes the determinants of e-commerce diffusion and the results used in a cluster analysis to provide further evidence that the propensity for e-commerce depends on the interplay among the different factors. The results can provide firms with an improved understanding of strategies to employ while implementing e-commerce.

scholarly journals Quadrilateral Interval Type-2 Fuzzy Regression Analysis for Data Outlier Detection

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Pingping Gao ◽  
Yabin Gao
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Outlier Detection ◽  
Euclidean Distance ◽  
Fuzzy Numbers ◽  
Fuzzy Regression ◽  
Fuzzy Regression Analysis ◽  
Fuzzy Regression Model ◽  
Interval Type

This paper presents a fuzzy regression analysis method based on a general quadrilateral interval type-2 fuzzy numbers, regarding the data outlier detection. The Euclidean distance for the general quadrilateral interval type-2 fuzzy numbers is provided. In the sense of Euclidean distance, some parameter estimation laws of the type-2 fuzzy linear regression model are designed. Then, the data outlier detection-oriented parameter estimation method is proposed using the data deletion-based type-2 fuzzy regression model. Moreover, based on the fuzzy regression model, by using the root mean squared error method, an impact evaluation rule is designed for detecting data outlier. An example is finally provided to validate the presented methods.

Nephropathy forecasting in diabetic patients using a GA-based type-2 fuzzy regression model

2017 ◽  
Vol 37 (2) ◽  
pp. 281-289 ◽  
Author(s):  
Narges Shafaei Bajestani ◽  
Ali Vahidian Kamyad ◽  
Ensieh Nasli Esfahani ◽  
Assef Zare
Keyword(s):  
Regression Model ◽  
Fuzzy Regression ◽  
Diabetic Patients ◽  
Fuzzy Regression Model
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