Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

WB67

n WB66 West Bldg 105A Practice- Data Mining in Business Applications I Contributed Session Chair: Amir Hossein Abolhassani, West Virginia University, Dearborn, MI, 48120, United States 1 - Fatigue Management System for Manufacturing Occupations Zahra Sedighi, Auburn University, Auburn, AL, 36830, United States From a firm’s perspective, managing fatigued workers is an important issue with ethical, operational and financial considerations. We propose and delineate a framework for using wearable sensors to manage worker fatigue in manufacturing environments. A framework is proposed instead of a model to allow for the detection/diagnosis of multiple fatigue modes. The proposed framework is made of four phases: (a) detection, (b) identification, (c) diagnosis, and (d) recovery. We present the capability of our proposed framework in two case studies. 2 - Identifying Long Term Organizational Well Being Hamidreza Ahady Dolatsara, Auburn University, 227 Lowder Hall, 405 West Magnola Ave., Auburn, AL, 36830, United States, Ashish Gupta, David Paradice This study uses machine learning approaches to understand the concept of long term organizational well-being. i.e., organizational health (OH). A composite OH index is developed based on long term financial performance. Time series of financial indicators are driven from sequential financial data over the past several years. Multivariate time series classification models are then developed for grouping companies into clusters based on their composite OH index. 3 - How Enterprises Can Emulate Those Better Than Themselves Liao Wei-Chih, Doctorial Student, National Chung-Hsing University, Taichung, Taiwan, Lin Chin-Shien, Chang Ruei-Yuan This paper aims to explore how enterprises can find appropriate strategic learning objects and what they shall pay attention to while choosing such objects. This study fitted the hierarchical linear models to test the hypotheses.The results show that company-level strategic fit has a significant impact on performance and the cross-level group variables and industrial variables have significant moderating effects. Therefore, when choosing a learning object, enterprises must confirm that the homogeneity of the strategic group is enough and understand the content of the ideal configuration. We need to pay more attention to the content of the ideal configuration to obtain better performance. 4 - Implications of Renegotiation on Testing Time for Software Outsourcing Contract Choice Hongyan Xu, Chongqing University, School of Economics & Business Admin, Chongqing, 400030, China, He Huang, Minhui Hu We examine two commonly used software outsourcing contracts with renegotiation on testing time, i.e., fixed-price and time-and-material contracts, and investigate the impacts of renegotiation on contract choice. 5 - Preventative Maintenance Forecast for Powertrain Capacity Planning Amir Abolhassani, Analytics Scientist, Ford Motor Company, Dearborn, MI, 48120, United States, Rajeev Kalamdani The current method of estimating planned preventative maintenance consists of adding 10% excess capacity (16.8 hours/week). This method may be over- estimating and leading to over capacity for a required production volume. An algorithm was developed to predict weekly downtime and labor impact of preventative, predictive, and autonomous maintenance based on line configuration and different available operations on seven bill of process (BoPs).

n WB67 West Bldg 105B Session on Digital Platforms Sponsored: Information Systems Sponsored Session Chair: Ni Huang, Arizona State University, Gilbert, AZ, 85233, United States 1 - Understanding Continuous Citizen Participation in a Green Commuting Platform: The Roles of Public Value and Private Value Luning Liu, PhD, Harbin Institute of Technology, Harbin, 150001, China, Jingrui Ju, Yuqiang Feng E-participation platforms encourage citizens to create public value for public affairs. Prior literature mostly focused on the role of participation in facilitating socially public value creation, with less attention paid to individual private value acquisition. However, the provision of private incentives can promote the production of public goods. Thus, this study develops a model according to theories of citizen participation and incentives to examine what antecedents respectively affect participation in creating public value and acquiring private value and the roles of the two values on continuous participation by using a field survey data. 2 - Impacts of the Platform-based Sharing Economy on the U.S. Labor Market: Evidence from Uber Entry Ziru Li, Arizona State University, Tempe, AZ, United States, Yili Hong, Zhongju Zhang We study how brand impacts consumer demand in the context of museum memberships in a metropolitan city in the United States. Over the course of our sample, one major museum with a highly recognized brand closed. During the closure, it sequentially co-branded with two established local museums. The closure and co-branding events combined with individual panel data on museum memberships allow us to measure how these changes in brand affect demand. Co-branding with the closed museum lifts demand for the partner museum, however this aggregate increase masks two counter-acting forces. First, customers with no history of buying membership from either museum enter the market, consistent with the prominent brand providing a signal of vertical quality. Second, a sub-group of customers who previously purchased from either or both of the museums display decreased demand. This is consistent with a model of brand providing information about horizontal match value, with decreasing demand from the broadening of brand being an example of brand dilution. The magnitude of these offsetting forces varies between co-branding events. These results have implications for the treatment of brand intercepts in counterfactuals when studying consumer demand. 3 - Everyone Can Be a Star: Quantifying Grassroots Online Sellers’ Live Streaming Effects on Product Sales Cheng Chen, University of Illinois at Chicago, Chicago, IL, 60607, United States, Yuheng Hu, Yili Hong, Yingda Lu The emergence of live streaming services provides online sellers a new channel to sell products. In this paper, we examine the effect of sellers’ adoption of live streaming on their online product sales. We found that the adoption of live streaming strategy significantly boosts sellers’ online product sales. 4 - Skill-Biased Technological Change Again? The Impacts of Matching Platforms on Local Labor Markets Zhi (Aaron) Cheng, Temple University, Philadelphia, PA, 19130, United States, Xue Guo, Paul Pavlou Do online matching platforms affect offline labor markets? To answer this question, we exploit a quasi-experiment setting, where a large internet-based matching platform, TaskRabbit, has gradually entered different U.S. cities since 2008. Our difference-in-differences estimation shows that the introduction of TaskRabbit is associated with a decrease in the number of local full-time workers in the traditional housekeeping industry. Moreover, the negative effect is mainly driven by a significant decrease in the number of cognitive routine workers (e.g., first line managers) after the TaskRabbit entry, given a non-significant change in that of manual non-routine workers (e.g., janitors). 5 - Why Gender Wage Gap does not Necessarily Mean Gender Bias? Chen Liang, Arizona State University, Tempe, AZ, United States, Yili Hong, Bin Gu We explore whether there exists gender wage gap in the gig economy and examine to what degree gender differences in job application strategy could account for the gap. With a large-scale dataset from a leading online labor market, we show that females only earn 81.4% of the hourly wage of males and explore three main aspects of job application strategy, namely, bid timing, choice of jobs based on hourly wage, and avoidance of monitoring. We find that females tend to bid later, prefer jobs with a lower hourly wage budget, and have a higher willingness to pay (WTP) for the avoidance of monitoring. Overall, our study underscores the importance of gender differences in job application strategy on gender wage gap.

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