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 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)

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

scholarly journals PRICING IN ONLINE AUCTION PROCUREMENT A REVIEW OF EMPIRICAL METHODS AND CURRENT UNDERSTANDINGS

2012 ◽  
Vol 09 (03) ◽  
pp. 1250017
Author(s):  
MING ZHOU ◽  
WILLIAM Y. JIANG ◽  
MENGLIN CAO
Keyword(s):  
Supply Chain ◽  
Empirical Studies ◽  
Online Auctions ◽  
Online Auction ◽  
Empirical Methods ◽  
Major Interest ◽  
Auction Prices ◽  
Auction Pricing

The online auction has become an important channel for procurement and sourcing management. As firms often expect lower procurement prices through online auctions, how the prices are determined in online auctions should be of major interest to procurement managers and supply chain researchers. Despite the abundant empirical studies on online auction prices, an aggregated view is still absent. This study fills this gap with a review of extant studies. More specifically, this study provides summaries of all major theories behind online auction pricing, defines and analyzes often encountered econometric issues, and discusses how the treatments of these issues have been operationalized. Towards the end, existing findings on determinants of online auction prices are integrated and examined. The purpose of this study is to provide a convenient and precise package of current studies for researchers and professionals.

What Type of Title Would You Put on Your Paintings?: The Impact on the Price of Artwork According to Its Title

2021 ◽  
pp. 027623742199470
Author(s):  
JooYeon Park ◽  
JiHye Park ◽  
Ji Hyon Park
Keyword(s):  
Positive Impact ◽  
Purchase Decisions ◽  
Art Collectors ◽  
Auction Price ◽  
Negative Effect ◽  
Auction Prices ◽  
The Impact ◽  
Positive Effect

This paper investigated the impact of the type of title on the price of the artwork effects using the hammer price of the paintings auctioned in Korea during a two-year period from December 2017 to November 2019. The results of the analysis showed that a descriptive title had a negative effect on the prices fetched, whereas a more elaborate title had a positive effect on auction prices. Also, it was found that elaborate titles for abstract paintings had a significant positive impact on the hammer price. In the case of unknown artists, a descriptive title had a negative effect on the auction price, while the absence of a title had a positive impact. The findings of this study suggest that artists must make careful decisions when titling their work because the title of the work affects the purchase decisions of art collectors.

scholarly journals An Empirical Study on Forecasting Production and Price of Tea in India

2021 ◽  
pp. 150-160
Author(s):  
M. Priyadharshini ◽  
D. Murugananthi ◽  
A. Rohini ◽  
R. Vasanthi
Keyword(s):  
South India ◽  
Export Price ◽  
Production Yield ◽  
North India ◽  
Positive Trend ◽  
Annual Growth Rate ◽  
Tea Industry ◽  
Auction Price ◽  
Price Auction ◽  
Auction Prices

Tea is a very indispensable beverage for Indian population as we rank the world’s largest consumer of black tea. Indian tea industry had been facing many downfalls for the past few years in terms of low price, excess supply, losing flavour and all this as a whole had affected the performance of the tea industry in India. With India being the second largest producer of tea globally, the production of tea in India can be subdivided into North India and South India. The current study focuses on the comparative analysis between North India, South India and India in terms of their trends in area, production, yield, export quantity, export price, auction price and auction quantity of tea. Compounded Annual growth rate (CAGR) was the tool used to find the trends of various variables. This study also focuses on the forecasting the production and auction prices of tea in India till 2023using Autoregressive Integrated Moving Average (ARIMA) model. The results of the present study areindicating that all the variables like area, production, yield, export quantity, export price, auction price and auction quantity of tea had shown a positive trend annually, except for that of North India’s export quantity. Production and auction prices were forecasted till 2023 using different ARIMA models amongst which ARIMA (1,1,0) proved to be the best fit model for study period.

scholarly journals Drivers of autonomous vehicles—analyzing consumer preferences for self-driving car brand extensions

2021 ◽  
Author(s):  
Felix Eggers ◽  
Fabian Eggers
Keyword(s):  
Autonomous Vehicles ◽  
Brand Management ◽  
Consumer Preferences ◽  
Brand Extension ◽  
Disruptive Innovation ◽  
Discrete Choice Experiments ◽  
Brand Strength ◽  
Parent Brand ◽  
Autonomous Cars ◽  
Self Driving Cars

AbstractAutonomous cars are considered to be the next disruptive innovation that will affect consumers. It can be expected that not only traditional automakers will enter this market (e.g., Ford) but also technology companies (e.g., Google) and newer companies dedicated to self-driving cars (e.g., Tesla). We take a brand extension perspective and analyze to what extent consumers prefer autonomous cars from these brand categories. Our empirical study is based on discrete choice experiments about adopting autonomous vehicles in a purchase scenario and in a renting context. Our findings show that brands play a central role when making autonomous driving decisions. Brand preferences differ systematically when buying versus renting a self-driving car. While technology brands are most preferred overall, consumers favor automaker brands over new brands only when purchasing, not when renting. We further disentangle the brand strength into the marginal effects of image associations. For example, Google’s strong brand positioning can be explained by experiences with the parent brand, but it could still improve brand strength by highlighting the relevance of the associated brand portfolio for self-driving cars. The effect of these brand extension success factors differs between parent-brand categories and also between the renting and purchasing scenarios, which requires a dedicated brand management.

Sign in / Sign up

Export Citation Format

Share Document