Russell Ackoff Doctoral Student Fellowship for Research on Human Decision Processes and Risk Management: 2014 Application

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Russell Ackoff Doctoral Student Fellowship for Research on Human Decision Processes and Risk Management: 2014 Application What Drives Clumpy Consumption? Evan Weingarten Doctoral Student Wharton Marketing Department Mailing Address: Suite 700 Jon M. Huntsman Hall 3730 Walnut Street University of Pennsylvania Philadelphia, PA 19104 Email: ewein@wharton.upenn.edu Faculty Advisor: Dr. Patti Williams, Marketing Department Requested Support: $3,000

Descriptive Summary of Project Traditional models of satiation maintain that enjoyment of goods drops over the course of consumption: people adapt to positive experiences (Brickman and Campbell 1971; Coombs and Avrunin 1977; Nelson and Meyvis 2008). Yet, according to Netflix, sometimes 16% to 25% of viewers will finish an entire season of a television series over two days or a weekend (Jurgensen 2013). In this context, instead of watching episodes more slowly over time due to declining enjoyment, customers continue to view episodes rapidly. What factors give rise to these types of hyper consumption behaviors that seem to run counter to traditional views of satiation, and why might they be important? These periods of bunched consumption with temporal divides between them can be called clumpy consumption (Zhang et al. 2013, 2014). This clumpy consumption may have important implications for both health domains and even for customer lifetime value. While overconsumption of unhealthy foods may clearly lead to unsuccessful dieting goals for individuals (Carver and Scheier 2013; Fishbach and Converse 2013; Laran and Janiszewski 2009), firms may also gain from recognizing clumpiness. Zhang et al. (2014) find that incorporating terms for clumpiness into customer lifetime value metrics can be predictive of purchase behavior. Importantly, Zhang et al. (2014) find that sites with loads of consumable content such as Hulu and YouTube may have upwards of 50% of customers who exhibit clumpy behavior, which demonstrates a real-world context through content in which satiation may not be as pronounced. Given the importance of clumpy consumption behaviors to firms and to individuals, we seek to identify drivers of clumpy behavior in content consumption contexts to both determine how choice architecture may encourage or discourage clumpy behavior, and how consumers respond to their own clumpy consumption. As opposed to literature that concentrates on what may slow rate of satiation (Galak, Redden, and Kruger 2009; Redden 2008; Redden and Galak 2013), we focus on what factors may increase appetite or subsequent consumption. We first review relevant causes of increased consumption rather than satiation patterns according to extant literatures. We then propose future possibilities for research through an exploratory approach. First, clumpy consumption may be driven by high value cues being attached early on in consumption. Multiple pieces of evidence may serve as examples. First, Anzman-Frasca et al. (2012) discover that associative conditioning of disliked vegetables with favorable dips can improve children s subsequent consumption and rating of vegetables. Similarly, Wadhwa, Shiv, and Nowlis (2008) find that providing a high value food cue, such as milk chocolate, can cause increases in subsequent consumption and approach of rewarding products. This result can also occur in ironic contexts: consumption of goal-relevant, highly-valued healthy foods may lead to consumption of even more food. Across

multiple studies, Finkelstein and Fishbach (2010) find that participants who ate healthy foods reported greater hunger than participants who did not eat or even ate tasty food. Although this last result relies on people feeling they ve made progress with health goals and subsequently pursuing other goals, it still demonstrates that valuable items in consumption may chain into more rather than less consumption. Second, clumpy consumption may also result from goal-mediated processes. One possibility is that content-related contexts such as Netflix, Hulu, and YouTube have more general goals that are not easily fulfilled, i.e., to be entertained. Activation of a general goal in the clumpy consumption context may lead to increased accessibility and value of that goal, and pursuit of it until its completion or until another goal becomes a higher priority (Forster et al. 2005, 2007; Laran and Janiszewski 2009). Moreover, since these general goals are not easily fulfilled, their disengagement may not occur until after complete consumption in the clumpy context, which would give rise to clumpy data patterns (Fischbach and Ferguson 2007; Forster et al. 2005, 2007). We propose an exploratory approach to test for possible goal, motivation-increasing, and structural explanations for clumpy consumption. To supplement field data demonstrating clumpy consumption patterns, we plan to conduct lab studies with experimental paradigms in which individuals are to watch several clips from TV, webseries, and music. We plan to manipulate such factors as website category framing (general clip genre versus specific series), clip order (logical progression, random, selected versus imposed), clip relatedness (same or cross category, series, or actor/musician), desirability of clips early in the sequence, goal specificity (instructions for spending time on the site), number of options for further content, and wait time and partitions between consumed content (short or long wait) as venues by which to test if lack of goal satiation, heightened initial content value, or flow among content may account for accelerated consumption. These manipulations will require a series of studies in both the Wharton Behavioral Lab and potentially Amazon Mechanical Turk. We also plan to follow up by examining, for visitors who exhibit clumpy consumption patterns, if those people have more positive evaluations of those sites and would be more likely to recommend content (compared to non-clumpy individuals) both during and after following clumpy episodes, and if these people will have better recall for content. This perspective will complement studying what causes clumpy consumption by informing the consequents of clumpy behavior for individual hedonics and word-of-mouth. I hope the Ackoff Fellowship will enable me to conduct lab studies to test plausible psychological processes that drive clumpy consumption when consumption whets rather than satiates appetites. I thank you for your consideration of my proposal, and I welcome any contact regarding questions.

Budget of Anticipated Expenses Item Cost per Unit Number Total Subject Payment 2 1500 3000 Total Costs 3000 References Anzman-Frasca, Stephanie, Jennifer S. Savage, Michele E. Marini, Jennifer O. Fisher, and Leann L. Birch (2012), Repeated exposure and associative conditioning promote preschool children s liking of vegetables, Appetite, 58, 543-53. Carver, Charles S., and Michael F. Scheier (2013), Self-Regulation of Action and Affect, in Kathleen D. Vohs and Roy F. Baumeister (Eds.) Handbook of Self- Regulation, 2 nd Edition, 3-21. Coombs, Clyde H., and George S. Avrunin (1977), Single-Peaked Functions and the Theory of Preference, Psychological Review, 84 (2), 216-30. Fishbach, Ayelet, and Benjamin A. Converse (2013), Identifying and Battling Temptation, in Kathleen D. Vohs and Roy F. Baumeister (Eds.) Handbook of Self-Regulation, 2 nd Edition, 244-60. Fishbach, Ayelet, and Melissa J. Ferguson (2007), The Goal Construct in Social Psychology, in A.W. Kruglanski and E.T. Higgins (Eds.) Social Psychology: Handbook of Basic Principles. Finkelstein, Stacey R., and Ayelet Fishbach (2010), When Healthy Food Makes You Hungry, Journal of Consumer Research, 37 (October), 357-67. Galak, Jeff, Joseph P. Redden, Justin Kruger (2009), Variety Amnesia: Recalling Past Variety Can Accelerate Recovery from Satiation, Journal of Consumer Research, 36 (December), 575-84. Jurgensen, John (2013), Netflix Says Binge Viewing is No House of Cards, Wall Street Journal, December 12. Laran, Juliano, and Chris Janiszewvski (2009), Behavioral Consistency and Inconsistency in the Resolution of Goal Conflict, Journal of Consumer Research, 35 (April), 967-84. Nelson, Leif D., and Tom Meyvis (2008), Interrupted Consumption: Disrupting Adaptation to Hedonic Experiences, Journal of Marketing Research, 45 (December), 654-64.

Redden, Joseph P. (2008), Reducing Satiation: The Role of Categorization Level, Journal of Consumer Research, 34 (February), 624-34. Redden, Joseph P., Jeff Galak (2013), The Subjective Sense of Feeling Satiated, Journal of Experimental Psychology: General, 142 (1), 209-17. Wadhwa, Monica, Baba Shiv, and Stephen M. Nowlis (2008), A Bite to Whet the Reward Appetite: The Influence of Sampling on Reward-Seeking Behaviors, Journal of Marketing Research, 45 (August), 403-13. Zhang, Yao, Eric T. Bradlow, and Dylan S. Small (2013), New Measures of Clumpiness for Incidence Data,, Annals of Applied Statistics, to appear. Zhang, Yao, Eric T. Bradlow, and Dylan S. Small (2014), Capturing Clumpiness when Valuing Customers: From RFM to RFMC, Marketing Science, under review.