메뉴 건너뛰기




Volumn 25, Issue 2, 2014, Pages 285-306

Selling vs. profiling: Optimizing the offer set in web-based personalization

Author keywords

Electronic retailing; Optimal control; Web based personalization

Indexed keywords

WEB CRAWLER; WEBSITES;

EID: 84903886850     PISSN: 10477047     EISSN: 15265536     Source Type: Journal    
DOI: 10.1287/isre.2014.0518     Document Type: Article
Times cited : (31)

References (44)
  • 2
    • 32644464870 scopus 로고    scopus 로고
    • Personalization technologies: A process-oriented perspective
    • Adomavicius G, Tuzhilin A (2005) Personalization technologies: A process-oriented perspective. Comm. ACM 48(6):83-90.
    • (2005) Comm. ACM , vol.48 , Issue.6 , pp. 83-90
    • Adomavicius, G.1    Tuzhilin, A.2
  • 4
    • 79951883958 scopus 로고    scopus 로고
    • Accelerated learning of user profiles
    • Atahan P, Sarkar S (2011) Accelerated learning of user profiles. Management Sci. 57(6):215-239.
    • (2011) Management Sci. , vol.57 , Issue.6 , pp. 215-239
    • Atahan, P.1    Sarkar, S.2
  • 5
    • 0031649343 scopus 로고    scopus 로고
    • Exploring versus exploiting when learning user models for text recommendation
    • Balabanovic M (1998) Exploring versus exploiting when learning user models for text recommendation. User Modeling User-Adapted Interaction 8:71-102.
    • (1998) User Modeling User-Adapted Interaction , vol.8 , pp. 71-102
    • Balabanovic, M.1
  • 6
    • 0030194591 scopus 로고    scopus 로고
    • Manage marketing by the customer equity test
    • Blattberg RC, Deighton J (1996) Manage marketing by the customer equity test. Harvard Bus. Rev. 74(6):136-144.
    • (1996) Harvard Bus. Rev. , vol.74 , Issue.6 , pp. 136-144
    • Blattberg, R.C.1    Deighton, J.2
  • 7
    • 38849148708 scopus 로고    scopus 로고
    • Recommendation systems with purchase data
    • Bodapati A (2008) Recommendation systems with purchase data. J. Marketing Res. XLV:77-93.
    • (2008) J. Marketing Res. , vol.45 , pp. 77-93
    • Bodapati, A.1
  • 9
    • 33847255926 scopus 로고    scopus 로고
    • Dynamic assortment with demand learning for seasonal consumer goods
    • Caro F, Gallien J (2007) Dynamic assortment with demand learning for seasonal consumer goods. Management Sci. 53(6):276-292.
    • (2007) Management Sci. , vol.53 , Issue.6 , pp. 276-292
    • Caro, F.1    Gallien, J.2
  • 10
    • 0007093091 scopus 로고
    • Economics and the Competitive Process
    • New York University Press, New York
    • Case JH (1979) Economics and the Competitive Process (New York University Press, New York).
    • (1979)
    • Case, J.H.1
  • 11
    • 84903906045 scopus 로고    scopus 로고
    • Maximizing profit using recommender systems
    • WWW2010
    • Das A, Mathieu C, Ricketts D (2010) Maximizing profit using recommender systems. WWW2010.
    • (2010)
    • Das, A.1    Mathieu, C.2    Ricketts, D.3
  • 12
    • 20444454680 scopus 로고    scopus 로고
    • Counting your customers, the easy way: An alternative to the Pareto/NBD model
    • Fader PS, Hardie BGS, Lee KL (2005) Counting your customers, the easy way: An alternative to the Pareto/NBD model. Marketing Sci. 24(6):275-284.
    • (2005) Marketing Sci. , vol.24 , Issue.6 , pp. 275-284
    • Fader, P.S.1    Hardie, B.G.S.2    Lee, K.L.3
  • 13
    • 84871034003 scopus 로고    scopus 로고
    • A latent pairwise preference learning approach for recommendation from implicit feedback
    • (CIKM'12), October 29-November 2 (ACM, New York)
    • Fang Y, Si L (2012) A latent pairwise preference learning approach for recommendation from implicit feedback. Proc. 21st ACM Internat. Conf. Inform. Knowledge Management (CIKM'12), October 29-November 2 (ACM, New York), 2567-2570.
    • (2012) Proc. 21st ACM Internat. Conf. Inform. Knowledge Management , pp. 2567-2570
    • Fang, Y.1    Si, L.2
  • 14
    • 0034340397 scopus 로고    scopus 로고
    • Consumer decision making in online shopping environments: The effects of interactive decision aids
    • Haubl G, Trifts V (2000) Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing Sci. 19(6):4-21.
    • (2000) Marketing Sci. , vol.19 , Issue.6 , pp. 4-21
    • Haubl, G.1    Trifts, V.2
  • 15
  • 18
    • 0030521288 scopus 로고    scopus 로고
    • Hierarchical Bayes conjoint analysis: Recovery of partworth heterogeneity from reduced experimental designs
    • Lenk PJ, DeSarbo WS, Green PE, Young MR (1996) Hierarchical Bayes conjoint analysis: Recovery of partworth heterogeneity from reduced experimental designs. Marketing Sci. 15(6):173-191.
    • (1996) Marketing Sci. , vol.15 , Issue.6 , pp. 173-191
    • Lenk, P.J.1    DeSarbo, W.S.2    Green, P.E.3    Young, M.R.4
  • 19
    • 40949142864 scopus 로고    scopus 로고
    • People who read this article also read
    • Linden G (2008) People who read this article also read. IEEE Spectrum 45(6):46-60.
    • (2008) IEEE Spectrum , vol.45 , Issue.6 , pp. 46-60
    • Linden, G.1
  • 20
    • 0001693343 scopus 로고
    • Design and analysis of simulated consumer choice or allocation experiments: An approach based on aggregate data
    • Louviere JJ, Woodworth G (1983) Design and analysis of simulated consumer choice or allocation experiments: An approach based on aggregate data. J. Marketing Res. 20:350-367.
    • (1983) J. Marketing Res. , vol.20 , pp. 350-367
    • Louviere, J.J.1    Woodworth, G.2
  • 23
    • 0040030246 scopus 로고    scopus 로고
    • Applying quantitative marketing techniques to the Internet
    • Montgomery AL (2001) Applying quantitative marketing techniques to the Internet. Interfaces 30(6):90-108.
    • (2001) Interfaces , vol.30 , Issue.6 , pp. 90-108
    • Montgomery, A.L.1
  • 24
    • 84867806110 scopus 로고    scopus 로고
    • To show or not to show: Using user profiling to manage ad campaigns at Chitika
    • Mookerjee R, Kumar S, Mookerjee V (2012) To show or not to show: Using user profiling to manage ad campaigns at Chitika. Interfaces 42(6):449-464.
    • (2012) Interfaces , vol.42 , Issue.6 , pp. 449-464
    • Mookerjee, R.1    Kumar, S.2    Mookerjee, V.3
  • 25
    • 0242624458 scopus 로고    scopus 로고
    • The role of the management sciences in research on personalization
    • Murthi BPS, Sarkar S (2003) The role of the management sciences in research on personalization. Management Sci. 49(6):1344-1362.
    • (2003) Management Sci. , vol.49 , Issue.6 , pp. 1344-1362
    • Murthi, B.P.S.1    Sarkar, S.2
  • 27
    • 0003902218 scopus 로고    scopus 로고
    • Enterprise One to One: Tools for Competing in the Interactive Age
    • Doubleday, New York
    • Peppers D, Rogers M (1997) Enterprise One to One: Tools for Competing in the Interactive Age (Doubleday, New York).
    • (1997)
    • Peppers, D.1    Rogers, M.2
  • 28
    • 47349092417 scopus 로고    scopus 로고
    • Approximate Dynamic Programming: Solving the Curses of Dimensionality
    • John Wiley & Sons, New York
    • Powell WB (2007) Approximate Dynamic Programming: Solving the Curses of Dimensionality (John Wiley & Sons, New York).
    • (2007)
    • Powell, W.B.1
  • 29
    • 0037257247 scopus 로고    scopus 로고
    • Customer lifetime duration: An empirical framework for measurement and explanation
    • January
    • Reinartz WJ, Kumar V (2003) Customer lifetime duration: An empirical framework for measurement and explanation. J. Marketing 67(January):77-99.
    • (2003) J. Marketing , vol.67 , pp. 77-99
    • Reinartz, W.J.1    Kumar, V.2
  • 30
    • 13244292360 scopus 로고    scopus 로고
    • Balancing acquisition and retention resources to maximize customer profitability
    • Reinartz WJ, Thomas SJ, Kumar V (2005) Balancing acquisition and retention resources to maximize customer profitability. J. Marketing 69(6):63-79.
    • (2005) J. Marketing , vol.69 , Issue.6 , pp. 63-79
    • Reinartz, W.J.1    Thomas, S.J.2    Kumar, V.3
  • 31
    • 79960335882 scopus 로고    scopus 로고
    • Active learning in recommender systems
    • Ricci F, Rokach L, Shapira B, Kantor PB, eds, Springer, New York
    • Rubens N, Kaplan D, Sugiyama M (2011) Active learning in recommender systems. Ricci F, Rokach L, Shapira B, Kantor PB, eds. Recommender Systems Handbook (Springer, New York), 735-767.
    • (2011) Recommender Systems Handbook , pp. 735-767
    • Rubens, N.1    Kaplan, D.2    Sugiyama, M.3
  • 32
    • 42149111681 scopus 로고    scopus 로고
    • Robustness of collaborative recommendation based on association rule mining
    • (ACM, New York)
    • Sandvig JJ, Mobasher B, Burke R (2007) Robustness of collaborative recommendation based on association rule mining. Proc. 2007 Conf. Recommender Systems (ACM, New York), 105-112.
    • (2007) Proc. 2007 Conf. Recommender Systems , pp. 105-112
    • Sandvig, J.J.1    Mobasher, B.2    Burke, R.3
  • 33
    • 0001829885 scopus 로고
    • Counting your customers:Who are they and what will they do next?
    • Schmittlein D, Morrison D, Colombo R (1987) Counting your customers:Who are they and what will they do next? Management Sci. 33(1):1-24.
    • (1987) Management Sci. , vol.33 , Issue.1 , pp. 1-24
    • Schmittlein, D.1    Morrison, D.2    Colombo, R.3
  • 34
    • 0003509246 scopus 로고    scopus 로고
    • Optimal Control Theory: Applications to Management Science and Economics
    • Kluwer Academic Publishers, Norwell, MA
    • Sethi SP, Thompson GL (2000) Optimal Control Theory: Applications to Management Science and Economics (Kluwer Academic Publishers, Norwell, MA).
    • (2000)
    • Sethi, S.P.1    Thompson, G.L.2
  • 36
    • 37249049318 scopus 로고    scopus 로고
    • Capturing user interests by both exploitation and exploratio
    • Proc. 11th Internat. Conf. User Modeling
    • Sia KC, Zhu S, Chi Y, Hino K, Tseng BL (2007) Capturing user interests by both exploitation and exploratio. Proc. 11th Internat. Conf. User Modeling 4511:334-339.
    • (2007) , vol.4511 , pp. 334-339
    • Sia, K.C.1    Zhu, S.2    Chi, Y.3    Hino, K.4    Tseng, B.L.5
  • 37
    • 85132026293 scopus 로고
    • Integrated architectures for learning, planning and reacting based on approximation dynamic programming
    • Proc. 7th Internat. Conf. Machine Learn. (Morgan Kaufmann, San Francisco)
    • Sutton RS (1990) Integrated architectures for learning, planning and reacting based on approximation dynamic programming. Proc. 7th Internat. Conf. Machine Learn. (Morgan Kaufmann, San Francisco), 216-224.
    • (1990) , pp. 216-224
    • Sutton, R.S.1
  • 38
    • 25844473207 scopus 로고    scopus 로고
    • Web personalization as a persuasion strategy:An elaboration likelihood model perspective
    • Tam YK, Ho YS (2005) Web personalization as a persuasion strategy:An elaboration likelihood model perspective. Inform. Systems Res. 16(6):271-291.
    • (2005) Inform. Systems Res. , vol.16 , Issue.6 , pp. 271-291
    • Tam, Y.K.1    Ho, Y.S.2
  • 39
    • 1442283678 scopus 로고    scopus 로고
    • Polyhedral methods for adaptive choice-based conjoint analysis
    • Toubier O, Hauser JR, Simester DJ (2004) Polyhedral methods for adaptive choice-based conjoint analysis. J. Marketing Res. 41:116-131.
    • (2004) J. Marketing Res. , vol.41 , pp. 116-131
    • Toubier, O.1    Hauser, J.R.2    Simester, D.J.3
  • 40
    • 36349012471 scopus 로고    scopus 로고
    • Optimal customer relationship management using Bayesian decision theory: An application for customer selection
    • Venkatesan R, Kumar V, Bohling T (2007) Optimal customer relationship management using Bayesian decision theory: An application for customer selection. J. Marketing Res. 44(6):579-594.
    • (2007) J. Marketing Res. , vol.44 , Issue.6 , pp. 579-594
    • Venkatesan, R.1    Kumar, V.2    Bohling, T.3
  • 41
    • 0000010163 scopus 로고
    • An operations-research study of sales response to advertising
    • Vidale ML, Wolfe HB (1957) An operations-research study of sales response to advertising. Oper. Res. 5(6):370-381.
    • (1957) Oper. Res. , vol.5 , Issue.6 , pp. 370-381
    • Vidale, M.L.1    Wolfe, H.B.2
  • 42
    • 84903886324 scopus 로고    scopus 로고
    • Firm mines offline data to target online ads
    • Wall Street Journal, October 17
    • Wall Street Journal (2007) Firm mines offline data to target online ads. (October 17).
    • (2007)
  • 43
    • 30344458463 scopus 로고    scopus 로고
    • Learning users' interest by quality classification in market-based recommender systems
    • Wei YZ, Moreau L, Jennings NR (2005) Learning users' interest by quality classification in market-based recommender systems. IEEE Trans. Knowledge Data Engrg. 17(6):1678-1688.
    • (2005) IEEE Trans. Knowledge Data Engrg. , vol.17 , Issue.6 , pp. 1678-1688
    • Wei, Y.Z.1    Moreau, L.2    Jennings, N.R.3
  • 44
    • 84964556767 scopus 로고    scopus 로고
    • Building a recommender agent for e-learning systems
    • (ICCE'02) (IEEE, Piscataway, NJ)
    • Zaiane OR (2002) Building a recommender agent for e-learning systems. Proc. Internat. Conf. Comput. Ed. (ICCE'02) (IEEE, Piscataway, NJ).
    • (2002) Proc. Internat. Conf. Comput. Ed.
    • Zaiane, O.R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.