Informs Annual Meeting 2017

TB51

INFORMS Houston – 2017

4 - Pricing in the ERA FF Omni-channel Retailing Nevin Mutlu, Assistant Professor, Eindhoven University of Technology, Eindhoven University of Technology, P.O. Box 513, Eindhoven, 5600 MB, Netherlands, n.r.mutlu@tue.nl In this research, we develop an analytical model to study an omni-channel retailer’s pricing policy across store and online channels, considering that different channels exhibit different cost structures, yet an inconsistent pricing scheme across channels may lead to consumer confusion, resulting in important long- term effects. 5 - It is Hard to Please the Consumers. the Impact of Omnichannel Operation on Firm Performance Xinyi Ren, PhD Student, University of Maryland-College Park, College Park, MD, 20742, United States, xinyi.ren@rhsmith.umd.edu, Philip Evers In this paper, we analyze the impact of omnichannel operation on firm performance. In particular, we predict that after a retailer launches the mobile app, it will not only affect the sales from the online platform, but also exert spillover effects to the Brick and Mortar (B&M) channel. In addition, because of the differences in regard to the information delivery mechanism, we propose that there exist distinguished return rate as well as cart abandonment decisions between the PC customers and mobile customers. By adopting econometric models, we empirically investigate the hypotheses using company level data. 361C Activity-based Modeling and Emerging Mobility Patterns Sponsored: TSL, Urban Transportation Sponsored Session Chair: Feixiong Liao, f.liao@tue.nl 1 - A Comprehensive Scenario Analysis of Household use of Autonomous Vehicles and On-demand Ride Sharing Yashar Khayati, State University of New York at Buffalo, Buffalo, NY, United States, yasharkh@buffalo.edu Yashar Khayati, State University of New York at Buffalo, Buffalo, NY, United States, yasharkh@buffalo.edu, Jee Eun Kang, Mark Karwan, Chase Murray We define a framework to model and evaluate potential household-level use of Autonomous Vehicles (AVs) and on-demand ridesharing (ODR) systems. We introduce a new formulation, the Household Activity Pattern Problem for AV and ODR, to simulate the travel patterns of people. A comprehensive scenario analysis is designed to assess the impact of various parameters such as parking availability in different urban areas, parking cost, ODR cost, value of travel time, AV operational cost, etc. on travel behavior changes. We define and measure new metrics to suggest new policies on parking locations, AV ownership, ODR coverage. 2 - Representing Carsharing Operators Competition in an TB50 In the past, almost all carsharing services were local monopolies of a sort. However, as carsharing is gaining momentum, competition among different operators in the same area is becoming a reality and research on this issue is required. Therefore, the goal of our ongoing work is twofold: 1) to implement a carsharing framework suitable to incorporate both land use information and socio demographic characteristics of people in the study area and 2) to model the competition of different free-floating carsharing operators. The simulations and analysis conducted will give us an opportunity to draw conclusions on the impacts on all involved parties of having a competing carsharing environment. 3 - Modeling Mode Choice and Parking Service for Commuting Trips in a Corridor: An Inclusion of Self-driving Cars Cong Zhao, Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai, China, Shanghai, 201804, China, zhc_tongji@163.com, Feixiong Liao, Yuchuan Du, Xinghua Li This paper studies multimodal travel patterns in a corridor with the presence of self-driving cars. We focus on the commuting trips along a corridor connecting two CBDs, where commuters are distributed and allowed to use public transit (PT), park-and-ride, and pick-up and drop-off services.. The proposed model integrate choice of mode, paring location and departure time within a dynamic traffic assignment (DTA) simulation system. Computational experiments are conducted to demonstrate the proposed formulations and potential applications for the evaluation of transport and land pricing policies. Agent-based Simulation of Transport Milos Balac, ETHZ, Zurich, Switzerland, milos.balac@ivt.baug.ethz.ch, Francesco Ciari

4 - Incorporating Free-floating Car Sharing into an Activity-based Dynamic User Equilibrium Model in Multi-state Super Network Qing Li, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China, liqing_321@hotmail.com, Feixiong Liao, Harry J.P. Timmermans, Haijun Huang, Jing Zhou Free-floating carsharing (FFC) has recently received increasing attention. Existing studies related to FFC have been rare to model the dynamic choice of free-floating shared cars (SC) in daily multi-modal multi-activity trip chains. This study proposes a tolerance-based multi-class dynamic activity-travel assignment model in an extended multi-state supernetwork representation. Dynamic traffic flows and supply-demand interactions of SC are formulated endogenously. Three numerical examples demonstrate that fleet size, distribution, rental and parking prices of SC significantly influence the choice of activity-travel patterns.

TB51

361D Platform Economics Sponsored: Information Systems Sponsored Session

Chair: Rakesh Reddy Mallipeddi, Texas A&M University, College Station, TX, 77843-4217, United States, rmallipeddi@mays.tamu.edu 1 - The Effects of Social Media Sentiment on Engagement Rakesh Reddy Mallipeddi, Texas A&M.University, 320 Wehner - 4217, Mays Business School, Dept of Info&Operations, College Station, TX, 77843-4217, United States, rmallipeddi@mays.tamu.edu Individual celebrities or “human brands” from different fields ranging from sports to art to politics use various social media platforms to connect and communicate with their target audience. We empirically analyze the effects of content generated by human brands on the popular social media platform, Twitter, on audience engagement. 2 - How Information Sharing Helps Firms Fight Return Abuse: A Network Perspective Serkan M. Akturk, Texas A&M.University, 4217 TAMU, Wehner 320 M, College Station, TX, 77843-4217, United States, makturk@mays.tamu.edu We study a setting where a service provider offers return information exchange (RIE) services, which exhibit network externalities for participating retailers and manufacturers. Firms can participate in the network by paying a subscription fee and benefit from shared databases. The RIE provider can offer customer proling, product tracking, and joint networks. Under different conditions of the network service, we derive the equilibrium subscription fees and the sizes of the customer profiling, product tracking, and joint networks. Our results provide strong managerial insights for retailers, manufacturers, and the RIE provider. 3 - Impact of Online Retail on Movement of Long Tail Products: An Empirical Study Samayita Guha, sguha@mays.tamu.edu, Rakesh Reddy Mallipeddi, Subodha Kumar Retailers have now started to pay attention to long tail products that individually have low demand but in aggregate can combine to create higher demand than few best-selling products. In this study, we propose an econometric model to examine the movement products in and out of long tail using data from a large retailer. 4 - How Much to Invest and How Much Information to Share for Information Security Yueran Zhuo, University of Massachusetts, 121 Presidents Drive, Amherst, MA, 01003, United States, yzhuo@som.umass.edu, Senay Solak In this study, we model the interplay between information sharing and technology investments for information security. As part of our findings, we identify policies defining optimal technology investments and information sharing levels for firms in different industries. We also present results on the value of sharing security information in different information security environments. 5 - How Information Sharing Helps Firms Fight Return Abuse: A Network Perspective Serkan M. Akturk, Texas A&M.University, 4217 TAMU, Wehner 320 M, College Station, TX, 77843-4217, United States, makturk@mays.tamu.edu In this paper, we study a setting where a service provider offers return information exchange (RIE) services that exhibit network externalities for participating retailers and manufacturers. Under different conditions of the network service, we derive equilibrium subscription fees and the sizes of the customer profiling, product tracking, and joint networks.

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