Nonparametric panel estimation of online auction price processes

2010 ◽  
Vol 40 (1) ◽  
pp. 51-68 ◽  
Author(s):  
Yu Yvette Zhang ◽  
Jingping Gu ◽  
Qi Li
Keyword(s):  
Online Auction ◽  
Panel Estimation ◽  
Auction Price

Tana and the Handbag

2011 ◽  
pp. 344-360
Author(s):  
Val A. Hooper ◽  
Sid L. Huff ◽  
Jon McDonald
Keyword(s):  
Brand Extension ◽  
Online Auction ◽  
Event Analysis ◽  
Considerable Influence ◽  
Site Factors ◽  
Sport Event ◽  
Brand Strength ◽  
Product Features ◽  
Auction Price ◽  
Auction Prices

Research into the determinants of online auction prices has tended to group them into buyer factors, seller factors and site factors. A case is presented which recounts how a $30 handbag was sold for $ 22,750 in an online auction shortly after a national sport event. Analysis of the case indicates that, in addition to the three groups of factors already identified, other factors can exert a considerable influence on the final auction price. A model is proposed which depicts five groups of factors impacting the final price: buyer factors, seller factors, site factors which are expanded to include timing of the auction, and site brand strength; product factors which include product features, brand strength, and brand extension/association; and promotion, which includes media publicity. While not all factors will impact on every auction, due consideration should be accorded each of them by both buyers and sellers.

The Snip Bidding in Online Auction: Empirical Evidence from the Single Unit Auction on www.taobao.com

2011 ◽  
Vol 58-60 ◽  
pp. 579-583
Author(s):  
Hao Fu ◽  
Rong Fang Qin ◽  
Zhan Kui Dong ◽  
Dong Zheng ◽  
Jian Pin Zha
Keyword(s):  
Empirical Evidence ◽  
Single Unit ◽  
Normative Data ◽  
Developed Countries ◽  
Online Auction ◽  
Bidding Behavior ◽  
Auction Market ◽  
Auction Price ◽  
Mature Market ◽  
The Relationship

This paper comparatively analyses the snip bidding intensity using the auction data of two kinds of goods from www.taobao.com by normative data collecting method, based on observation of the relationship between the bidding time and auction price in online auction. Our results indicate that it has obvious snip bidding behavior in online auction on www.taobao.com. The intensity of the snip bidding is different because of different goods categories. It primarily proves that in Chinese online auction market there exists similar snip bidding behavior in mature market of developed countries.

The Rugby Player and the Handbag

2009 ◽  
Vol 5 (4) ◽  
pp. 22-38 ◽  
Author(s):  
Val A. Hooper ◽  
Sid L. Huff ◽  
Jon MacDonald
Keyword(s):  
Final Analysis ◽  
Brand Extension ◽  
Rugby Player ◽  
Online Auction ◽  
Considerable Influence ◽  
Site Factors ◽  
Brand Strength ◽  
Product Features ◽  
Auction Price ◽  
Auction Prices

Research into the determinants of online auction prices has tended to group them into buyer factors, seller factors and site factors. A case is presented which records how a $30 handbag was sold for $ 22,750 in an online auction shortly after a national sport final. Analysis of the case indicates additional factors which can exert a considerable influence on the final auction price. A model is proposed which depicts five groups of factors impacting the final price: buyer factors, seller factors, site factors which are expanded to include timing of the “action”, and site brand strength; product factors which include product features, brand strength, and brand extension/association; and promotion, which includes media publicity. While not all factors will impact on every auction, due consideration should be accorded each of them.

The Bidder's Curse

2011 ◽  
Vol 101 (2) ◽  
pp. 749-787 ◽  
Author(s):  
Ulrike Malmendier ◽  
Young Han Lee
Keyword(s):  
Large Fraction ◽  
Online Auction ◽  
Limited Attention ◽  
Board Game ◽  
Fixed Price ◽  
Novel Approach ◽  
Auction Price ◽  
Fixed Prices ◽  
Auction Prices ◽  
Broad Cross Section

We employ a novel approach to identify overbidding in auctions. We compare online auction prices to fixed prices for the same item on the same webpage. In detailed data on auctions of a board game, 42 percent of auctions exceed the simultaneous fixed price. The result replicates in a broad cross-section of auctions (48 percent overbidding). A small fraction of overbidders, 17 percent of bidders, suf fices to generate the large fraction of auctions with overbidding. We show that the observed behavior is inconsistent with rational behavior, even allowing for uncertainty about prices and switching costs, since the expected auction price also exceeds the fixed price. Limited attention best explains our results. (JEL D12, D44)

Electricity consumption and economic growth in ASEAN

2017 ◽  
Vol 5 (2) ◽  
pp. 16
Author(s):  
Ahmad Ghazali Ismail ◽  
Arlinah Abd Rashid ◽  
Azlina Hanif
Keyword(s):  
Economic Growth ◽  
Energy Use ◽  
Electricity Consumption ◽  
Panel Estimation ◽  
Real Gdp ◽  
Long Run ◽  
Bidirectional Relationship ◽  
Short Run ◽  
Using Data ◽  
The Relationship

The relationship and causality direction between electricity consumption and economic growth is an important issue in the fields of energy economics and policies towards energy use. Extensive literatures has discussed the issue, but the array of findings provides anything but consensus on either the existence of relations or direction of causality between the variables. This study extends research in this area by studying the long-run and causal relations between economic growth, electricity consumption, labour and capital based on the neo-classical one sector aggregate production technology mode using data of electricity consumption and real GDP for ASEAN from the year 1983 to 2012. The analysis is conducted using advanced panel estimation approaches and found no causality in the short run while in the long-run, the results indicate that there are bidirectional relationship among variables. This study provides supplementary evidences of relationship between electricity consumption and economic growth in ASEAN.

Resource Allocation in Cloud using Multi Bidding Model with User Centric Behavior Analysis

2020 ◽  
Vol 13 (5) ◽  
pp. 1008-1019
Author(s):  
N. Vijayaraj ◽  
T. Senthil Murugan
Keyword(s):  
Resource Allocation ◽  
Behavior Analysis ◽  
User Behavior ◽  
Low Cost ◽  
Cloud Services ◽  
Online Auction ◽  
Analysis Model ◽  
Efficient Resource ◽  
User Centric ◽  
Cloud Resources

Background: Number of resource allocation and bidding schemes had been enormously arrived for on demand supply scheme of cloud services. But accessing and presenting the Cloud services depending on the reputation would not produce fair result in cloud computing. Since the cloud users not only looking for the efficient services but in major they look towards the cost. So here there is a way of introducing the bidding option system that includes efficient user centric behavior analysis model to render the cloud services and resource allocation with low cost. Objective: The allocation of resources is not flexible and dynamic for the users in the recent days. This gave me the key idea and generated as a problem statement for my proposed work. Methods: An online auction framework that ensures multi bidding mechanism which utilizes user centric behavioral analysis to produce the efficient and reliable usage of cloud resources according to the user choice. Results: we implement Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis. Thus the algorithm is implemented and system is designed in such a way to provide better allocation of cloud resources which ensures bidding and user behavior. Conclusion: Thus the algorithm Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis is implemented & system is designed in such a way to provide better allocation of cloud resources which ensures bidding, user behavior. The user bid data is trained accordingly such that to produce efficient resource utilization. Further the work can be taken towards data analytics and prediction of user behavior while allocating the cloud resources.

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