Ephemeral State-Dependent Recommendation for Digital Content
References
- (2022) Congruence between leadership gender and organizational claims affects the gender composition of the applicant pool: Field experimental evidence. Organ. Sci. 33(1):393–413.Link, Google Scholar
- (2014) Optimization-based approaches for maximizing aggregate recommendation diversity. INFORMS J. Comput. 26(2):351–369.Link, Google Scholar
- (2005) Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Engrg. 17(6):734–749.Crossref, Google Scholar
- (2018) Effects of online recommendations on consumers’ willingness to pay. Inform. Systems Res. 29(1):84–102.Link, Google Scholar
- (2008) Choice construction versus preference construction: The instability of preferences learned in context. J. Marketing Res. 45(2):145–158.Crossref, Google Scholar
- (2016) Mobile ad effectiveness: Hyper-contextual targeting with crowdedness. Marketing Sci. 35(2):218–233.Link, Google Scholar
- (2018) Probabilistic topic model for hybrid recommender systems: A stochastic variational Bayesian approach. Marketing Sci. 37(6):987–1008.Link, Google Scholar
- (2017) Liquid consumption. J. Consumer Res. 44(3):582–597.Crossref, Google Scholar
- (2012) Liquid relationship to possessions. J. Consumer Res. 39(3):510–529.Crossref, Google Scholar
- (2021) Understanding influencer marketing: The role of congruence between influencers, products and consumers. J. Bus Res. 132(2021):186–195.Crossref, Google Scholar
- (1998) Constructive consumer choice processes. J. Consumer Res. 25(3):187–217.Crossref, Google Scholar
- (2008) Liquid consumption: Anti-consumerism and the fetishized de-fetishization of commodities. Cultural Stud. 22(5):599–623.Crossref, Google Scholar
- (2020) The effect of emoji incongruency in social media: An abstract. Marketing Opportunities Challenges Changing Global Marketplace Proc. 2019 Acad. Marketing Sci. AMS Annu. Conf. (Springer International Publishing, Cham, Switzerland), 171–172.Google Scholar
- (2023) Mysterious consumption: Preference for horizontal (vs. vertical) uncertainty and the role of surprise. J. Consumer Res. 49(6):987–1013.Crossref, Google Scholar
- (2021) Novelty and diversity in recommender systems. Ricci F, Rokach L, Shapira B, eds. Recommender Systems Handbook (Springer, Boston), 881–918.Google Scholar
- (2021) Recommendation system simulations: A discussion of two key challenges. Preprint, submitted August 25, https://arxiv.org/abs/2109.02475.Google Scholar
- (2018) How algorithmic confounding in recommendation systems increases homogeneity and decreases utility. RecSys’18 Proc. 12th ACM Conf. Recommender Systems (Association for Computing Machinery, New York), 224–232.Google Scholar
- (2007) Bounded rationality in pricing under state-dependent demand: Do firms look ahead, and if so, how far? J. Marketing Res. 44(3):434–449.Crossref, Google Scholar
- (2010) Social comparisons and contributions to online communities: A field experiment on MovieLens. Amer. Econom. Rev. 100(4):1358–1398.Crossref, Google Scholar
- (2013) Learning models: An assessment of progress, challenges, and new developments. Marketing Sci. 32(6):913–938.Link, Google Scholar
- (2019) When seeing helps believing: The interactive effects of previews and reviews on e-book purchases. Inform. Systems Res. 30(4):1164–1183.Link, Google Scholar
- (2003) The role of flow experience in cyber-game addiction. Cyberpsychol. Behav. 6(6):663–675.Crossref, Google Scholar
- (2009) My mobile music: An adaptive personalization system for digital audio players. Marketing Sci. 28(1):52–68.Link, Google Scholar
- (1995) Preference for consistency: The development of a valid measure and the discovery of surprising behavioral implications. J. Personality Soc. Psych. 69(2):318.Crossref, Google Scholar
- (2014) The fresh start effect: Temporal landmarks motivate aspirational behavior. Management Sci. 60(10):2563–2582.Link, Google Scholar
- (2008) Offering online recommendations with minimum customer input through conjoint-based decision aids. Marketing Sci. 27(3):443–460.Link, Google Scholar
- (2024) Social trading, communication, and networks. Inform. Systems Res. 35(4):1546–1564.Link, Google Scholar
- (2016) The hidden cost of personal quantification. J. Consumer Res. 42(6):967–984.Crossref, Google Scholar
- (2004) Reactance to recommendations: When unsolicited advice yields contrary responses. Marketing Sci. 23(1):82–94.Link, Google Scholar
- (2009) Blockbuster culture’s next rise or fall: The impact of recommender systems on sales diversity. Management Sci. 55(5):697–712.Link, Google Scholar
- (2015) Geo-conquesting: Competitive locational targeting of mobile promotions. J. Marketing Res. 52(5):726–735.Crossref, Google Scholar
- (2019) Targeted promotions on an e-book platform: Crowding out, heterogeneity, and opportunity costs. J. Marketing Res. 56(2):310–323.Crossref, Google Scholar
- (2009) Testing the value of customization: When do customers really prefer products tailored to their preferences? J. Marketing 73(5):103–121.Crossref, Google Scholar
- (2013) Slow down! Insensitivity to rate of consumption leads to avoidable satiation. J. Consumer Res. 39(5):993–1009.Crossref, Google Scholar
- (2012) Designing ranking systems for hotels on travel search engines by mining user-generated and crowdsourced content. Marketing Sci. 31(3):493–520.Link, Google Scholar
- (2015) The Netflix recommender system: Algorithms, business value, and innovation. ACM Trans. Management Inform. Systems 6(4):13.Google Scholar
- (2007) ItemRank: A random-walk based scoring algorithm for recommender engines. Sangal R, Mehta H, Bagga RK, eds. IJCAI’07 Proc. 20th Internat. Joint Conf. Artificial Intelligence (Morgan Kaufmann Publishers, Inc., San Francisco), 2766–2771.Google Scholar
- (2009) The marketplace management of illicit pleasure. J. Consumer Res. 35(5):759–771.Crossref, Google Scholar
- (2019) Knowledge is power: Prior knowledge aids memory for both congruent and incongruent events, but in different ways. J. Experiment. Psych. Gen. 148(2):325.Crossref, Google Scholar
- (2018) Selling the premium in freemium. J. Marketing 82(6):10–27.Crossref, Google Scholar
- (2019) Does time of day affect variety-seeking? J. Consumer Res. 46(1):20–35.Crossref, Google Scholar
- (2016) Contextual deliberation and preference construction. Management Sci. 62(10):2977–2993.Link, Google Scholar
- (1991) Time-inconsistent preferences and consumer self-control. J. Consumer Res. 17(4):492–507.Crossref, Google Scholar
- (2019) The sleepy consumer and variety seeking. J. Marketing Res. 56(2):179–196.Crossref, Google Scholar
- (2001) What causes the isolation effect? J Experiment. Psych. Learn. Memory Cognition 27(6):1359.Crossref, Google Scholar
- (2024) A genre-based analysis of new music streaming at scale. WEBSCI’24 Proc. 16th ACM Web Sci. Conf. (Association for Computing Machinery, New York), 191–201.Google Scholar
- (2016) Diversity, serendipity, novelty, and coverage: A survey and empirical analysis of beyond-accuracy objectives in recommender systems. ACM Trans. Interactive Intelligent Systems 7(1):2.Google Scholar
- (2002) Can consumers escape the market? Emancipatory illuminations from burning man. J. Consumer Res. 29(1):20–38.Crossref, Google Scholar
- (2019) Measuring the value of recommendation links on product demand. Inform. Systems Res. 30(3):819–838.Link, Google Scholar
- (2017) Diversity in recommender systems—A survey. Knowledge-Based Systems 123(2017):154–162.Crossref, Google Scholar
- (2015) Good times bad times: A study on recency effects in collaborative filtering for social tagging. RecSys’15 Proc. 9th ACM Conf. Recommender Systems (Association for Computing Machinery, New York), 269–272.Google Scholar
- (2021) Decisions, decisions: Variations in decision-making for access-based consumption. J. Marketing Theory Practice 29(3):358–374.Crossref, Google Scholar
- (2019) How do recommender systems affect sales diversity? A cross-category investigation via randomized field experiment. Inform. Systems Res. 30(1):239–259.Link, Google Scholar
- (2004) Explaining the special case of incongruity in advertising: Combining classic theoretical approaches. Marketing Theory 4(1–2):59–90.Crossref, Google Scholar
- (2020) Different but equal? A field experiment on the impact of recommendation systems on mobile and personal computer channels in retail. Inform. Systems Res. 31(3):892–912.Link, Google Scholar
- (2015) Online recommendation systems in a B2C E-commerce context: A review and future directions. J. Assoc. Inform. Systems 16(2):2.Google Scholar
- (2024) When variety seeking meets unexpectedness: Incorporating variety-seeking behaviors into design of unexpected recommender systems. Inform. Systems Res. 35(3):1257–1273.Link, Google Scholar
- (2022) How do recommender systems lead to consumer purchases? A causal mediation analysis of a field experiment. Inform. Systems Res. 33(2):620–637.Link, Google Scholar
- (2019) The spillover of spotlight: Platform recommendation in the mobile app market. Inform. Systems Res. 30(4):1296–1318.Link, Google Scholar
- (2003) Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Comput. 7(1):76–80.Crossref, Google Scholar
- (2016) A video-based automated recommender (VAR) system for garments. Marketing Sci. 35(3):484–510.Link, Google Scholar
- (2014) Mobile targeting. Management Sci. 60(7):1738–1756.Link, Google Scholar
- (2004) Measuring expectations. Econometrica 72(5):1329–1376.Crossref, Google Scholar
- (1982) Variety seeking behavior: An interdisciplinary review. J. Consumer Res. 9(3):311–322.Crossref, Google Scholar
- (1994) Congruence and fit in professional role motivation theory. Organ. Sci. 5(1):86–97.Link, Google Scholar
- (1995) There’s something in the air: Effects of congruent or incongruent ambient odor on consumer decision making. J. Consumer Res. 22(2):229–238.Crossref, Google Scholar
- (2024) Where does advertising content lead you? We created a bookstore to find out. Marketing Sci. 43(5):925–1151.Link, Google Scholar
- (2023) The decoy effect and recommendation systems. Inform. Systems Res. 34(4):1533–1553.Link, Google Scholar
- (1980) A model for diagnosing organizational behavior. Organ. Dynam. 9(2):35–51.Crossref, Google Scholar
- (2013) Differentiate or imitate? The role of context-dependent preferences. Marketing Sci. 32(3):393–410.Link, Google Scholar
- (2012) The visible hand? Demand effects of recommendation networks in electronic markets. Management Sci. 58(11):1963–1981.Link, Google Scholar
- (2016) Research note—In CARSs we trust: How context-aware recommendations affect customers’ trust and other business performance measures of recommender systems. Inform. Systems Res. 27(1):182–196.Link, Google Scholar
- (1993) The Adaptive Decision Maker (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
- (2023) On the differences between view-based and purchase-based recommender systems. MIS Quart. 47(2):875–900.Crossref, Google Scholar
- (2020) More than words in medical question-and-answer sites: A content-context congruence perspective. Inform. Systems Res. 31(3):913–928.Link, Google Scholar
- (1989) Memory for real-world scenes: The role of consistency with schema expectation. J Experiment. Psych. Learn. Memory Cognition 15(4):587.Crossref, Google Scholar
- (2002) The impact of private versus public consumption on variety-seeking behavior. J. Consumer Res. 29(2):246–257.Crossref, Google Scholar
- (2016) Preference stability and choice consistency in discrete choice experiments. Environ. Resource Econom. 65(2):441–461.Crossref, Google Scholar
- (2009) The safety of objects: Materialism, existential insecurity, and brand connection. J. Consumer Res. 36(1):1–16.Crossref, Google Scholar
- (2012) All things considered? The role of choice set formation in diversification. J. Marketing Res. 49(3):320–335.Crossref, Google Scholar
- (2019) Metamemory expectancy illusion and schema-consistent guessing in source monitoring. J. Experiment. Psych. Learn. Memory Cognition 45(3):470–496.Crossref, Google Scholar
- (1998) Surprise and schema strength. J. Experiment. Psych. Learn. Memory Cognition 24(5):1182–1199.Crossref, Google Scholar
- (2016) Binge watching and advertising. J Marketing 80(5):1–19.Crossref, Google Scholar
- (2021) Trade-offs in choice. Annual Rev. Psych. 72(1):181–206.Crossref, Google Scholar
- (2020) State-dependent demand estimation with initial conditions correction. J. Marketing Res. 57(5):789–809.Crossref, Google Scholar
- (2019) When and how to diversify—A multicategory utility model for personalized content recommendation. Management Sci. 65(8):3737–3757.Link, Google Scholar
- (1996) Why switch? Product category–level explanations for true variety-seeking behavior. J Marketing Res. 33(3):281–292.Crossref, Google Scholar
- (2024a) How do product recommendations help consumers search? Evidence from a field experiment. Management Sci. 70(9):5776–5794.Abstract, Google Scholar
- (2024b) Retargeted versus generic product recommendations: When is it valuable to present retargeted recommendations? Inform. Systems Res. 35(3):1403–1421.Link, Google Scholar
- (2016) Products as self-evaluation standards: When owned and unowned products have opposite effects on self-judgment. J. Consumer Res. 42(6):915–930.Crossref, Google Scholar
- (2007) E-commerce product recommendation agents: Use, characteristics, and impact. MIS Quart. 31(1):137–209.Crossref, Google Scholar
- (2023) Diversity preference-aware link recommendation for online social networks. Inform. Systems Res. 34(4):1398–1414.Link, Google Scholar
- (2013) Understanding schema incongruity as a process in advertising: Review and future recommendations. J. Marketing Commun. 19(5):360–376.Crossref, Google Scholar

