Informs Annual Meeting 2017

TE21

INFORMS Houston – 2017

TE19

2 - Structural Anatomy and Evolution of Supply Networks: A Multi-method Approach Hyunwoo Park, The Ohio State University, Columbus, OH, 43210, United States, park.2706@osu.edu, Marcus A. Bellamy, Rahul C. Basole We investigate the evolutionary dynamics of supply networks with a focus on the influence of structural, firm-, and industry-specific mechanisms. We characterize the dynamic relationship between the structural mechanisms on a longitudinal dataset of 2,221 unique firms and 13,668 firm-year observations. We find empirical support for negative crossover effects between two key structural mechanisms inherent in supply networks, a positive moderation of a firm’s absorptive capacity and a negative moderation of industry growth on the structural reinforcement. 3 - Engaged Scholarship and Co-Creating Knowledge: A Design Science Approach to Operations Management Research Aravind Chandrasekaran, Associate Professor, The Ohio State University, 600 Fisher Hall, 2100 Neil Avenue, Columbus, OH, 43210, United States, chandrasekaran.24@osu.edu, Joan Ernst Van Aken, Bradley R. Staats, Andrew H. Van de Ven We question whether the decline in business education is partly due to the research approach adopted by operations management scholars. We show how co-creating knowledge with practice through a design science approach can derive dual benefit of relevance and rigor through several examples. We also offer suggestions on when and how to use this research approach. 4 - Unpacking the Value of Novelty in Design We study how novelty in product form influences its economic value. We exploit a confidentiality feature specific to the design patent and use stock market reactions in the days subsequent to patent grant to estimate the private value of individual design patents granted to firms publicly listed in the US. We use the construct of styles—categories of product designs that are similar in form—to build various measures of novelty relative to designs of the same style, thus taking into account the context in which novelty is perceived. We show how different kinds of novelty positively or negatively affect value. Our results have implications on how firms should rely on novelty to seek value. Chair: Feng Li, University of Science and Technology of China, 96 Jinzhai Road, Anhui, 230026, China, lfeng90@mail.ustc.edu.cn 1 - Sourcing Uncertain Product Quality: Competition, Learning, and Volume Postponement Alexander Rothkopf, Julius-Maximilians-University Wuerzburg, Global-health buyers seek to introduce competition by incenting new generics suppliers with uncertain performance/quality to enter the market. We investigate the benefits of postponing a portion of the procurement volume to learn entrant’s performance and how the dynamics of learning and competition depend on the size of the postponed volume. 2 - A Method for Location, Allocation and Distribution of Critical Supplies After a Natural Disaster Ricardo Giesen, Associate Professor, Pontificia Universidad Catolica de Chile, Vicuna Mackenna 4860 Macul, Casilla 306 Cod. 105, Santiago, 7820436, Chile, giesen@ing.puc.cl Ricardo Giesen, Associate Professor, CIGIDEN, Santiago, 7820436, Chile, giesen@ing.puc.cl, José Ignacio Olave, Juan Carlos Herrera Humanitarian logistics after a natural disaster is normally characterized by lack of coordination, material convergence and shortage of critical supplies. This work proposes a mathematical programming method for location, allocation and distribution of critical supplies considering demand forecasting per item, operational costs and social costs including deprivation costs. Different scenarios are compared in terms of costs, considering water, food and shelter items. Carla-Henius-Straße 9, Wuerzburg, 97070, Germany, alexander.rothkopf@uni-wuerzburg.de, Felix Lauton Tian Chan, Emory University’s Goizueta Business School, 1300 Clifton Road, Atlanta, GA, 30322, United States, tian.chan@emory.edu TE21 342C Information Systems Contributed Session

342A Production and Scheduling Contributed Session Chair: Rajitha Meka, University of Texas at San Antonio, San Antonio, TX, United States, rajitha.meka@utsa.edu 1 - Minimizing the Warehouse Order Picking Costs Considering Probabilistic Risk The expansion of online shopping and supply chain in today’s world makes the warehouses as one of the main element of trading network. In this research first we give a brief review on different aspects of warehousing and in continue we present the order picking as one of the most common problems in this area. In our research we have focused on the problem of minimizing order lateness and picking cost by deciding on the number of pickers and the probabilistic risk of batching. This cost includes customer loyalty, internal transportation, and etc. We have used queuing theory to create an algorithm in order to produce an optimal or near optimal decision for batching and workforce level. 2 - A Comparison of Construction Productivity Ratings Atieh Madani, University at Buffalo (SUNY), 308 Bell Hall, Buffalo, NY, 14260, United States, atiehmad@buffalo.edu, Rajan Batta, Mark Henry Karwan Labor utilization rating model is used to calculate labor rating factor. Chi-square distribution is used to compare productivity ratings of three or more construction crews. Statistical test of hypothesis for proportions is utilized to decide if proportions of productive times between crews are equal or not. 3 - Reducing Manufacturing Electricity Costs by Controlling Dependence Between Production Parameters Hyun Woo Jeon, Assistant Professor, Louisiana State University, Manufacturing electricity costs are charged for energy consumption (EC in kWh) and peak demand (PD in kW). To model the costs accurately, EC and PD need to be considered together, but a model investigating the two factors has not been thoroughly studied. This study introduces a novel approach to estimating and reducing the costs by applying a multivariate probability model. The proposed model as a joint probability distribution characterizes important production parameters, and then EC and PD are evaluated from the model. From various examples, the proposed model provides a strategy to reduce the costs (EC + PD) by adjusting the production parameters and their dependence. 4 - An Active Learning Approach for Gaussian Processes Rajitha Meka, Graduate Student, University of Texas at San Antonio, 15801 Chase Hill Blvd, Apt 104, San Antonio, TX, 78256, United States, rajitha.meka@utsa.edu, Adel Alaeddini Gaussian process regression is a well-known non-parametric regression method that provides the estimate of uncertainty along with the predictions. Having the initial fit of the model with the points observed, active learning method helps to choose a promising point that improves the Gaussian process model. For the design space with large number of unobserved points, the main aim is to provide a good model with less number of evaluations by learning information about the design space at each evaluation. 3272X Patrick F. Taylor Hall, Mechanical and Industrial Engineering, Baton Rouge, LA, 70803, United States, hwjeon@lsu.edu Mostafa Ghandehari, Senior Lecturer, University of Texas- Arlington, Civil Engineering, Univ. of Texas at Arlington, Arlington, TX, 76019, United States, ghandeha@uta.edu

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342B Empirical Research in Innovation Sponsored: Technology, Innovation Management & Entrepreneurship Sponsored Session

Chair: Tian Chan, Emory University, tian.chan@emory.edu 1 - Exploring the Affect of Idea Sources on the Successful Evaluation of Ideas Nilam Kaushik, University College-London, London, United Kingdom, nilam.kaushik.13@ucl.ac.uk, Bilal Gokpinar In this project we explore the factors affecting the successful evaluation of ideas on a crowdsourcing platform. In particular we are interested in understanding how the diversity, semantic distance of source ideas from the problem domain and the ways in which sources recombine affect the likelihood of idea success. In this work, we leverage text mining techniques and information retrieval methods to understand the recombination process.

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