City, Society, and Digital Transformation: Proceedings of the 2022 INFORMS International Conference on Service Science

475 Pages·2022·14.195 MB·English

by  Robin Qiu, Wai Kin Victor Chan, Weiwei Chen, Youakim Badr, Canrong Zhang

Lecture Notes in Operations Research
Robin Qiu · Wai Kin Victor Chan · 
Weiwei Chen · Youakim Badr · 
Canrong Zhang Editors
City, Society,
and Digital
Transformation
Proceedings of the 2022 INFORMS
International Conference on Service
Science
Lecture Notes in Operations Research
Editorial Board
Ana Paula Barbosa-Povoa, University of Lisbon, Lisboa, Portugal
Adiel Teixeira de Almeida , Federal University of Pernambuco, Recife, Brazil
Noah Gans, The Wharton School, University of Pennsylvania, Philadelphia, USA
Jatinder N. D. Gupta, University of Alabama in Huntsville, Huntsville, USA
Gregory R. Heim, Mays Business School, Texas A&M University, College Station,
USA
Guowei Hua, Beijing Jiaotong University, Beijing, China
Alf Kimms, University of Duisburg-Essen, Duisburg, Germany
Xiang Li, Beijing University of Chemical Technology, Beijing, China
Hatem Masri, University of Bahrain, Sakhir, Bahrain
Stefan Nickel, Karlsruhe Institute of Technology, Karlsruhe, Germany
Robin Qiu, Pennsylvania State University, Malvern, USA
Ravi Shankar, Indian Institute of Technology, New Delhi, India
Roman Slowin´ski, Poznan´ University of Technology, Poznan, Poland
Christopher S. Tang, Anderson School, University of California Los Angeles
Los Angeles, USA
Yuzhe Wu, Zhejiang University, Hangzhou, China
Joe Zhu, Foisie Business School, Worcester Polytechnic Institute, Worcester, USA
Constantin Zopounidis, Technical University of Crete, Chania, Greece
Lecture Notes in Operations Research is an interdisciplinary book series which
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· · ·
Robin Qiu Wai Kin Victor Chan Weiwei Chen
·
Youakim Badr Canrong Zhang
Editors
City, Society, and Digital
Transformation
Proceedings of the 2022 INFORMS
International Conference on Service Science
Editors
Robin Qiu Wai Kin Victor Chan
Division of Engineering and Information Shenzhen International Graduate School
Science Tsinghua University
Pennsylvania State University Shenzhen, China
Malvern, PA, USA
Youakim Badr
Weiwei Chen Division of Engineering and Information
Department of Supply Chain Management Science
Rutgers, The State University of New Jersey Pennsylvania State University
New Jersey, NJ, USA Malvern, PA, USA
Canrong Zhang
Shenzhen International Graduate School
Tsinghua University
Shenzhen, China
ISSN 2731-040X ISSN 2731-0418 (electronic)
Lecture Notes in Operations Research
ISBN 978-3-031-15643-4 ISBN 978-3-031-15644-1 (eBook)
https://doi.org/10.1007/978-3-031-15644-1
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Contents
1 A Penalized Neural Network Model for Predicting Unobserved
Scores of Construct Indicators and Reproducing Latent
Scores of the Theoretical Constructs by Using Text Information ... 1
Toshikuni Sato
2 Deep Learning-Based Prediction of Mechanical Ventilation
Reintubation in Intensive Care Units ............................ 15
Hangtian Li and Xiaolei Xie
3 Mitigating Braess’s Paradox with Information Design ............ 23
Zhenxiao Chen, Yonghui Chen, and Qiao-Chu He
4 The Impact of Electronic Shelf Label on Customer Well-Being
in the Omnichannel Smart Retail ............................... 31
Darren Jonathan Ovani and Nila Armelia Windasari
5 Targeted Bayesian Persuasion in a Basic Selfish Routing Game .... 47
Yinlian Zeng, Qiao-Chu He, and Xiaoqiang Cai
6 Stochastic Churn Modeling with Dynamic Attribution
and Bayesian Estimation ....................................... 57
Ping Chou and Howard Hao-Chun Chuang
7 Trade Credit Pricing with Retailer’s Capital Heterogeneity ....... 73
Mingyu Zheng, Yonghui Chen, and Qiao-Chu He
8 Systemic Risk Spillover Analysis of China’s Banking Industry
Based on Generalized Variance Decomposition Network .......... 81
Xuejing Ji and Chuanmin Mi
9 Can We Apply Traditional Forecasting Models to Predicting
Bitcoin? ...................................................... 97
Matthew Bobea and Wesley Szuway Shu
v
vi Contents
10 Research on the Integration of Market Supervision Big
Data from the Perspective of Life Cycle—Take the Jiangsu
Provincial Market Supervision Bureau as an Example ............ 113
Ying Liu, Shan Li, and Wendi Pang
11 Group-Level Human Affect Recognition with Multiple Graph
Kernel Fusion ................................................. 127
Xiaohua Huang
12 An Anticipative Order Reservation and Online Order
Batching Algorithm Based on Machine Learning ................. 141
Zhiqiang Qu and Peng Yang
13 Human-Robotic Collaborative Mode Analysis
in Human-Robotic Collaborative Order Picking
Systems ...................................................... 157
Shanshan Song, Peng Yang, Zixin Shao, and Yeming Gong
14 Electric Power Personal Accident Evolution Analysis Based
on Event Evolutionary Graph .................................. 177
Fang Jing and Mi Chuanmin
15 Research on Suicide Risk Spectrum of Prisoners Based
on Fourier Transform ......................................... 191
Sainan Gao and Yang Shen
16 A Deep Learning Model for Mining Behavioral Preference
of Home Care Demanders to Suppliers .......................... 203
Hongying Fei and Mingzhu Xu
17 Dynamic Ranking of Physicians in Online Healthcare
Platforms with Multiple Service Types .......................... 217
Ziwei Wang, Jie Song, and Jingtong Zhao
18 Analysis on Technological Innovation Efficiency in Equipment
Manufacturing Industry ....................................... 235
Min Liu and Sifeng Liu
19 Bikes Detention Game in Free-Float Bike Sharing Systems ........ 251
Shichen Zhao, Wenjuan Hou, Ziyao Wang, and Qiaochu He
20 On the Value of Orderly Charging in Improving Power Grid
Resilience .................................................... 263
Yuqiu Deng, Zihao Jiao, Mengqi Li, and Lun Ran
21 Mixed-Integer Linear Programming Formulations
for the Inbound Container Remarshaling Problem
in an Automated Container Terminal ........................... 277
Bo Jin, Zhishan Yu, and Mingzhu Yu
Contents vii
22 Products and Services Bundling Under Horizontal Market
Competitions ................................................. 293
Yimo Yu, Zhitong Liao, Qiaochu He, and Weiling Ke
23 Robust Facility Location Selection Under Facility Failure
in Close-Loop Supply Chain .................................... 303
Jianzhi Leng, Lun Ran, and Zihao Jiao
24 Analysis of Factors Influencing the Selection of Billing Model
for Whole-Process Engineering Consulting Services Based
on DEMATEL-ISM ........................................... 317
Ronghui Sun and Yanfeng Chu
25 Research on Critical Chain Project Buffer Management
Considering Activity Risk ...................................... 331
Meng Xiao and Yanfeng Chu
26 Complex Task Assignment of Aviation Emergency Rescue
Based on Multiagent Reinforcement Learning ................... 345
Che Shen and Xianbing Wang
27 Online Portfolio Management: A Survey of Data-Driven
Approaches ................................................... 357
Rudraksh Mishra, Abhay Chamu Haridas, Nikhitha Khunduru,
Ambika Chundru, Shahed Mahbub, and Dusan Ramljak
28 Comparing Twitter Data for Topic Modling, Clustering,
and Predictive Analysis Using LSTM Model ..................... 375
Md. Shamaun Islam and Sadat Bin Shahid
29 A Constructive Heuristic Algorithm for 3D Bin Packing
of Irregular Shaped Items ...................................... 393
Qiruyi Zuo, Xinglu Liu, and Wai Kin Victor Chan
30 Implications of Worker Classification in On-Demand Economy .... 407
Zhoupeng Jack Zhang, Ming Hu, and Jianfu Wang
31 Prediction of New COVID-19 Cases Considering Mitigation
Policies and Weather Data for European Countries ............... 425
Mohammad Fili, Kris De Brabanter, Luning Bi, and Guiping Hu
32 Optimal Unit Locations in Emergency Service Systems
with Bayesian Optimization .................................... 439
Wenqian Xing and Cheng Hua
viii Contents
33 NLP Integrated Hybrid Model of Semi-Supervised
and Supervised Learning for Online Misinformation
Classification ................................................. 453
Partha Mukherjee, Deeksha Joshi, Youakim Badr,
Raghvinder Sangwan, and Satish Srinivasan
34 Pattern Language for Designing Distributed AI Systems .......... 467
Satish Mahadevan Srinivasan, Shahed Mahbub,
Raghvinder S. Sangwan, Youakim Badr, and Partha Mukherjee
Chapter 1
A Penalized Neural Network Model
for Predicting Unobserved Scores
of Construct Indicators and Reproducing
Latent Scores of the Theoretical
Constructs by Using Text Information
Toshikuni Sato
Abstract This paper discusses a novel application of construct measurement with a
penalized neural network in a text analysis. Conducting a survey with the measures of
constructs is a traditional approach to scoring customers’ mental states, such as feel-
ings, perceptions, and attitudes. Numerous types of scales are continuously developed
for marketing and consumer behavior research. To connect this traditional method-
ology with machine learning and big data analysis, our proposed neural network
model uses two penalty functions, which specify the confirmatory factor model
as a measurement equation. In the empirical analysis, the proposed model shows
stable parameter estimates compared with a standard unconstrained neural network
and supports theoretical interpretations. By applying the learned proposed model,
predictive item scores of each questionnaire and alternative scores of theoretical
constructs can be obtained through text information. The proposed methodology
helps marketers and researchers visualize consumers’ representations of perceived
theoretical constructs without the survey. To enhance the proposed model’s accuracy
and validity, limitations and potential works are also discussed for future study.
· · ·
Keywords Penalized neural network Construct measurement Text analysis
Parameter identification
Introduction
The rapid growth of digital technologies promotes machine learning (ML)
approaches, such as face detection, image classification, and natural language
processing (NLP) in marketing and business applications. These methods remark-
ably help efficient handling of large-scale and unstructured data, such as movies,
images, and text messages [1–3]. Therefore, applying ML techniques or algorithms
B
T. Sato ( )
School of Commerce, Meiji University, Chiyoda, Tokyo 101-8301, Japan
e-mail: [email protected]
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 1
R. Qiu et al. (eds.), City, Society, and Digital Transformation, Lecture Notes in Operations
Research, https://doi.org/10.1007/978-3-031-15644-1_1