Timing when to buy

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2011, Pages 709-718

  Agrawal, Rakesh ^a   Ieong, Samuel ^a   Velu, Raja ^b  

^a MICROSOFT RESEARCH   (United States)

^b SYRACUSE UNIVERSITY   (United States)

Author keywords

automated shopping; recommendation

Indexed keywords

AUTOMATED SHOPPING; BEST STRATEGY; CONSUMER DURABLES; E-COMMERCE SITES; EXPERIMENTAL STUDIES; RECOMMENDATION;

KNOWLEDGE MANAGEMENT;

EID: 83055191310     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2063576.2063681     Document Type: Conference Paper

References (21)

1. R. Agrawal, S. Ieong, and R. Velu. Ameliorating buyer's remorse. In Proc. KDD, 2011.
2. R. Agrawal, S. Ieong, and R. Velu. Timing when to buy. Technical Report MSR-TR-2011-97, Microsoft Research, 2011.
3. G. Box, G. M. Jenkins, and G. Reinsel. Time Series Analysis: Forecasting and Control. Prentice Hall, 1994.
4. R. Burke. Hybrid recommender systems: Survey and experiments. User Model. & User-Adapted Inter., 12(4), 2002.
5. Y. S. Chow, H. Robbins, and S. D. Great Expectations: The Theory of Optimal Stopping. Houghton Mifflin Co, 1971.
6. W. H. Cummings and M. Venkatesan. Cognitive dissonance and consumer behavior: A review of the evidence. In M. J. Schlinger, editor, Advances in Consumer Research Volume 2, pages 21-32. Association for Conusmer Research, 1975.
7. R. N. Dino. Forecasting the price evolution of new electronic products. J. Forecasting, 4:39-60, 1985.
8. R. J. Dolan and A. P. Jeuland. Experience curves and dnamic demand models: Implications for optimal pricing strategies. J. Marketing, 45:52-62, 1981.
9. O. Etzioni, R. Tuchinda, C. A. Knoblock, and A. Yates. To buy or not to buy: mining airfare data to minimize ticket purchase price. In Proc. KDD, pages 119-128, 2003.
10. I. Fisher. Theory of Interest. Augustus M. Kelly, 1930.
11. G. Fulgoni. State of the U.S. retail economy in Q2 2009. Technical report, Comscore, August 2009.
12. C. Gonzales and P. Perny. GAI networks for utility elicitation. In Proc. 9th Int. Conf. Principles of Knowledge Representation and Reasoning, 2004.
13. J. C. Hull. Options, Futures, and Other Derivatives. Prentice Hall, 5th edition, 2002.
14. R. J. Hyndman, A. B. Koehler, J. K. Ord, and R. D. Snyder. Forecasting with Exponential Smoothing. Springer, 2008.
15. D. Jannach, M. Zanker, A. Felfering, and G. Friedrich. Recommender Systems: An Introduction. Cambridge University Press, 2010.
16. S. S. Oren. Comments on "pricing research in marketing: The state of the art". J. Business, 57:61-64, 1984.
17. P. Pazzani and D. Billsus. Content-based recommendation systems. In The Adaptive Web, 2007.
18. D. Prelec and G. Loewenstein. Beyond time discounting. Marketing Letters, 8:97-108, 1997. (Pubitemid 127542150)
19. V. R. Rao. Pricing research in marketing: The state of the art. J. Business, 57:39-60, 1984.
20. B. Sarwar, G. Karypis, J. Konstan, and J. Reidl. Item-based collaborative filtering recommendation algorithms. In WWW, 2001.
21. R. S. Winer. Discounting and its impact on durables buying decision. Marketing Letters, 8:109-118, 1997.