|
Cluster :
|
eBusiness
|
|
|
|
Session Information
|
: Sunday Oct 14, 13:30 - 15:00
|
|
|
|
Title:
|
Economics of Information Systems
|
|
Chair:
|
Mingfeng Lin,University of Arizona, 1130 E. Helen St, Tucson AZ 85721, United States of America, mingfeng@eller.arizona.edu
|
|
|
|
Abstract Details
|
|
|
|
Title:
|
Optimal Choice for Market Price Information
|
|
|
Presenting Author:
|
Chris Parker,Pennsylvania State University, Smeal College of Business, University Park PA 16802, United States of America, chris.parker@psu.edu
|
|
|
Co-Author:
|
Kamalini Ramdas,Professor, London Business School, Regent's Park, London NW1 4SA, United Kingdom, kramdas@london.edu
|
|
|
|
Nicos Savva,London Business School, Regnet's Park, London NW1 4SA, United Kingdom, nsavva@london.edu
|
|
|
|
Abstract:
|
Information is only valuable if it is both new and actionable. We model a seller's selection of a market for which to purchase price information. We discuss the results of the model in the context of farmers in rural India and use data to analyze whether actual decisions are in line with our model.
|
|
|
|
|
Title:
|
The Impact of IT on Economic Capacity
|
|
|
Presenting Author:
|
Dawei Zhang,University of Calgary, Haskayne School of Business, Calgary, Canada, dzhang@ucalgary.ca
|
|
|
Co-Author:
|
Barrie Nault,University of Calgary, Haskayne School of Business, Calgary, Canada, nault@ucalgary.ca
|
|
|
|
Abstract:
|
We define economic capacity as the output level that maximizes short-run industry profit, and empirically explore the impact of IT on economic capacity and CU under a production function framework.
|
|
|
|
|
Title:
|
Content Sharing in a Social Broadcasting Environment: Evidences from Twitter
|
|
|
Presenting Author:
|
Huaxia Rui,University of Texas at Austin, Austin TX, United States of America, huaxia@utexas.edu
|
|
|
|
Abstract:
|
We collect a detailed dataset about the information-sharing activity on Twitter, called retweet, and estimate an econometric model regarding tie strength and retweeting behavior. The empirical results convincingly support our model and we find that after an author posts a median quality (as defined in the sample) tweet, the likelihood that a unidirectional follower will retweet is significantly higher than the likelihood that a bidirectional follower will.
|
|
|
|
|
Title:
|
Geography in Online Peer-to-peer Lending
|
|
|
Presenting Author:
|
Mingfeng Lin,University of Arizona, 1130 E. Helen St, Tucson AZ 85721, United States of America, mingfeng@eller.arizona.edu
|
|
|
Co-Author:
|
Siva Viswanathan,University of Maryland, College Park, College Park MD, United States of America, sviswana@rhsmith.umd.edu
|
|
|
|
Abstract:
|
We study how geography affects investors' choice of loans to fund using data from Prosper.com, one of the largest online peer-to-peer lending websites. Using data from regular market conditions and from a natural experiment, we show that geography affects lender decisions, but this relationship is moderated by the nature of the loan request and the salience of geography in the marketplace.
|
|
|
|
|
|