2015 Informs Annual Meeting

MB76

INFORMS Philadelphia – 2015

MB75 75-Room 204B, CC Managing Search and Problem Solving in Innovation Settings Cluster: New Product Development Invited Session Chair: Sezer Ülkü Associate Professor, Georgetown University McDonough School of Business, 545 Hariri Building, 37 & O Streets, Washington, DC, 20057, United States of America, su8@georgetown.edu 1 - When to Leave the Building? Search and Pivoting in a Lean Startup Onesun Steve Yoo, University College London, Gower Street, London, WC1E 6BT, United Kingdom, o.yoo@ucl.ac.uk, Kenan Arifoglu, Tingliang Huang An early stage entrepreneurial firm with a new product concept must maximize the chance of successful product launch. To avoid developing an unwanted product, practitioners suggest a lean approach to development, i.e., a firm should iteratively launch an unfinished product to learn what the consumers want and to alter the final product goal whenever necessary. We formalize this approach via the Bayesian learning framework, and investigate the optimal development strategy. 2 - How (and When) to Encourage Cooperation Across Projects Fabian Sting, Erasmus University Rotterdam, Rotterdam School of Management, 3000 DR Rotterdam, Netherlands fsting@rsm.nl, Pascale Crama, Yaozhong Wu Inspired by an innovative practice, we model a Project Management system that incorporates and shapes cooperative problem solving. Help is at the core of this system, in which project managers may ask for and provide help. We find that companies should take a nuanced approach when designing help exchange and time-based incentives. 3 - Search under Constraints - An Experimental Study Sezer Ülkü, Associate Professor, Georgetown University McDonough School of Business, 545 Hariri Building, 37 & O Streets, Washington, DC, 20057, United States of America, su8@georgetown.edu In contexts of innovation, slack resources are required due to the many unknowns. At the same time, according to some, “necessity is the mother of invention”, and resource constraints might improve innovative performance. Through a series of experiments, we examine how constraints influence search strategies, and the ultimate performance. MB76 76-Room 204C, CC Simulation Optimization and Input Uncertainty Sponsor: Simulation Sponsored Session Chair: Enlu Zhou, Assistant Professor, Georgia Institute of Technology, 755 Ferst Drive, NW, Atlanta, GA, United States of America, enlu.zhou@isye.gatech.edu 1 - Insights on Ranking and Selection when there is Input Uncertainty Barry Nelson, Walter P. Murphy Professor, Northwestern University, Dept. of IEMS, 2145 Sheridan Road, C210, Evanston, IL, 60208, United States of America, nelsonb@northwestern.edu, Eunhye Song We examine the impact of input uncertainty (inaccuracies in the stochastic input models that have been estimated from real-world data) on the simplest form of simulation optimization: ranking and selection among a finite number of alternatives. We show that the conclusions from the optimization must be altered, establish the limits of what can be attained by increased simulation effort alone, and suggest alternative ways to attack the problem that lead to interpretable conclusions.

3 - A Competitive Dynamics Approach to Supply Chain Management: Competitive Action and Performance

Xinyi Ren, PhD Student, University of Maryland, 3330 Van Munching Hall, College Park, MD, 20742, United States of America, xinyi.ren@rhsmith.umd.edu, Christian Hofer, Curtis Grimm, David Cantor

This study investigates how the actions of supplier and manufacturer (focal firm) dyads impact focal firm’s performance. Grounded in competitive dynamics and the relational view, theory will be developed regarding actions and performance. A panel dataset will be built combining data from FACTSET, Compustat and LexisNexis. This paper will contribute to both the competitive dynamics literature and relational view by studying competitive actions in a supply chain context. MB74 74-Room 204A, CC Sustainable Operations in the Manufacturing Industry Sponsor: Quality, Statistics and Reliability Sponsored Session Chair: Wilkistar Otieno, Assistant Professor, University of Wisconsin- Milwaukee, 3200 N Cramer St, Milwaukee, WI, 53209, United States of America, otieno@uwm.edu 1 - Inventory Optimization in a Three Echelon Closed Loop Supply Chain with Stochastic Quality in Return Sajjad Farahani, PhD Student, University of Wisconsin- Milwuakee, 4046 N Wilson Dr Apt2, Milwaukee, WI, 53211, United States of America, farahani@uwm.edu, Farshid Zandi, Wilkistar Otieno We considered three echelon closed loop supply chain in which returned product arrive to the re-manufacturing system with different quality level inspect to estimate needed time to re-manufacture as a new product.We proposed an analytical queuing models with the time value of money consideration to optimize inventory level of two warehouses and the admission decision, which decides on the acceptance of returned products based on quality and processing time. 2 - A Simulation Based Model for Performance Evaluation of Control Drive Remanufacture Thomas Omwando, Graduate Student, University of Wisconsin_Milwaukee, 3200 N Cramer St. EMS 503, Milwaukee, WI, 53211, United States of America, tomwando@uwm.edu, Wilkistar Otieno Process complexities and uncertainties in product remanufacture affect system performance. In this study a discrete event simulation approach is employed to model process performance with the objective of improving system performance. A case study of two product families in control drive remanufacture is used to illustrate the applicability of the model. A sensitivity analysis is carried out to assess the effect of changes in various decision variables on the overall system performance. 3 - Warranty Analysis of Remanufactured Electrical Products Yuxi Liu, Graduate Student, University of Wisconsin-Milwuakee, 3438 N Oakland Ave #302, Milwaukee, WI, 53211, United States of America, yuxiliu@uwm.edu, Wilkistar Otieno This study considers a remanufactured electrical product under warranty. Warranty is key ensuring a good manufacturer-consumer relationship. Manufacturers hope to minimize warranty costs while consumers believe warranty promises product quality. This paper presents an optimal warranty period from the perspective of a manufacturer to maximize the total expected profits, while sustained consumer relation. We use data from a local company with a global supply chain to provide a numerical example.

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