Informs Annual Meeting 2017

TA49

INFORMS Houston – 2017

TA47

Many online retailers provide real-time inventory availability information. Customers can learn from the inventory level and update their beliefs about product quality. Based on a unique setting from Amazon lightning deals, which displays the percentage of inventory consumed in real time, we explore whether and how consumers learn from inventory availability information. We run randomized field experiments on Amazon and run a panel data analysis. We find evidence of consumer learning from inventory information: a decrease in product availability causally attracts more sales in the future; in particular, a 10% increase in past sales leads to a 2.08% increase in cart add-ins in the next hour. 2 - When You Work with a Super Man, Will You Also Fly? An Empirical Study of the Impact of the Coworkers on Workers’ Performance Fangyun Tan, Southern Methodist University, 6212 Bishop Blvd, Dallas, TX, 75275, United States, ttan@cox.smu.edu, Serguei Netessine We examine a large operational data set in a casual restaurant setting to study how coworkers’ sales ability level affects other workers’ sales performance. We find that waiters react non-linearly to their coworkers’ ability. Our empirical findings imply that to maximize sales, managers should mix waiters with heterogeneous ability levels during the same shift. 3 - Last Place Aversion in Queues Ryan Buell, Harvard Business School, Morgan Hall 429, Boston, MA, 02163, United States, rbuell@hbs.edu, Michael Norton, Jay Chakraborty Waiting in queues is an all-too-common source of customer frustration, disrupting the customer experience and - when queues or waits are sufficiently long - causing customers to switch queues, or forgo the experience altogether by reneging. While the number of people in front of a customer in a queue logically predicts such behaviors - the more people, the longer the wait - we examine an underexplored trigger of frustration: how many people are behind the customer in the queue. In particular, in a series of lab and field experiments, we explore whether being in or near last place in a queue predicts switching and reneging, independent of how many people are ahead in the queue. 4 - Fixed or Random Supplier? Evidence from an Order Allocation Game Chao Xue, Tsinghua University, Beijing, 100084, China, xuec15@mails.tsinghua.edu.cn, Xiaobo Zhao, Jinghuo Chen We present an experimental study to investigate the impact of fairness concerns on supplier selection strategies. In the game, a manufacturer needs to allocate its orders to two identical suppliers, and the relationships are established through either fixed or random pairings. It is observed that order allocations over time by the manufacturer follow a U-shaped curve under the fixed matching. To capture such learning dynamics, we propose a behavioral model in which the manufacturer updates his belief about the supplier’s fairness preferences through repeated interactions. Our results provides useful insights for how to adopt supplier selection strategies appropriately. 361B Practice/eBusiness I Contributed Session Chair: Rajiv Misra, XLRI-Xavier School of Management, C H Area (East), Jamshedpur, 831001, India, rajiv@xlri.ac.in 1 - How to Compare Two Products? A Framework to Make a Better Decision for Consumers Based on Online Word-of-mouth Information Song Gao, Tongji University, 1 Zhangwu Road, Tongji Block A, Shanghai, 200092, China, hardygao@outlook.com, Hongwei Wang It is an essential part for consumers to make a purchase decision by comparing different products. And online WOM can guide consumers to judge which one is better. This paper proposes a framework to compare two products based on three comparison types. The first one is comparing two products using the direct comparison opinions presented by other consumers. If they have no direct relation, we construct stable comparison relation by introducing a common comparison object, which has the direct relation with them respectively. The third type focuses on two products, which have no direct relation and no common object. We compare them using the comparison between consumer’s opinion and past experience. TA49

360F Ebusiness and Social networks Sponsored: EBusiness Sponsored Session Chair: Jie Zhang, University of Texas, Arlington, TX, 76019, United States, jiezhang@uta.edu 1 - On the Spillover Effects of User-generated Reviews on Purchases: Evidence from Clickstream Data Gene Moo Lee, University of Texas at Arlington, 6746 Deseo #112B, Arlington, TX, 75039, United States, gmlee7@gmail.com, Young Kwark, Paul Pavlou, Liangfei Qiu We analyze the spillover effect of the online reviews of related products on the purchases of a focal product using clickstream data from a large retailer by investigating (a) whether the related, co-visited products are complementary or substitutive; (b) whether the related products are from the same or a different brand, and (c) the choice of media channel (mobile or PC) used. The result shows that the mean rating of the online reviews of substitutive products has a negative effect on the purchasing of the focal product, while the mean rating of complementary products has a positive effect. 2 - Social Processes and Earnings Management: Evidence from Employee Reviews Feng Mai, Stevens Institute of Technology, 1 Castle Point on Hudson, Hoboken, NJ, 07030, United States, feng.mai@stevens.edu, Xinyan Yan We study the link between corporate culture and earnings management. Using data from a leading employee review site, we show that the use of discretionary accruals to manipulate reported earnings is more pronounced at those firms having stronger social affiliation among employees. Our results suggest that employee reviews can provide pertinent information about corporate ethics. 3 - Augment Reality Game’s Spillover Jie Zhang, University of Texas at Arlington, Arlington, TX, 76011, United States, jie.zhang2@mavs.uta.edu, Yuan Zhang This study empirically examined how the introduction of augmented reality games, such as Pokemon Go affects the reputation of local businesses. 4 - Social Learning and Early Purchase under Product Fit Uncertainty and Price Uncertainty Xuying Zhao, University of Notre Dame, 361 Mendoza College Of Business, Notre Dame, IN, 46556, United States, xzhao1@nd.edu, Zhan Pang, Jie Zhang The first period buyers make purchase decisions under future price uncertainty. Social learning increases this uncertainty because the second period price may depend on the review valence then, which is uncertain in the first period. So social learning has the increasing-price-uncertainty effect, which changes early buyers’ waiting incentives and may hurt or benefit the firm in different scenarios. 5 - Competitive Poaching in Search Advertising: A Randomized Field Experiment Siddharth Bhattacharya, Temple University, Philadelphia, PA, United States, tug79848@temple.edu, Jing Gong, Sunil Wattal A key strategy firm’s are following in search advertising is to generate traffic by bidding on not only their own keywords but also competitors’ keywords. This strategy, known as competitive poaching, is prevalent in multiple industries. However, little research has empirically examined the effectiveness of competitive poaching. The objective of this research is to examine the effect of ad copy variations with respect to competitor keywords on driving click-through and conversion. We further expect this relationship to be moderated by quality and location of competitor. We run a 4-month randomized field experiment in collaboration with a business school.Managerial implications are discussed. 361A Empirical Behavioral Operations Sponsored: Behavioral Operations Management Sponsored Session Chair: Dennis Zhang, University City, MO, 63124, United States, denniszhang@wustl.edu 1 - Learning from Inventory Availability Information: Field Evidence from Amazon Ruomeng Cui, Goizueta Business School, Emory University, 1300 Clifton Rd, Atlanta, GA, 30322, United States, ruomeng.cui@gmail.com, Dennis Zhang, Achal Bassamboo TA48

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