001451984 000__ 06192cam\a2200673\i\4500
001451984 001__ 1451984
001451984 003__ OCoLC
001451984 005__ 20230310003335.0
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001451984 019__ $$a1354631696$$a1355219362$$a1355372067
001451984 020__ $$a9783031156441$$q(electronic bk.)
001451984 020__ $$a3031156447$$q(electronic bk.)
001451984 020__ $$z9783031156434
001451984 020__ $$z3031156439
001451984 0247_ $$a10.1007/978-3-031-15644-1$$2doi
001451984 035__ $$aSP(OCoLC)1356276898
001451984 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dFIE$$dEBLCP$$dOCLCQ$$dUKAHL
001451984 049__ $$aISEA
001451984 050_4 $$aT55.45
001451984 08204 $$a658.4/03$$223/eng/20221227
001451984 1112_ $$aINFORMS International Conference on Service Science$$d(2022 :$$cShenzhen Shi, China).
001451984 24510 $$aCity, society, and digital transformation :$$bproceedings of the 2022 INFORMS International Conference on Service Science /$$cRobin Qiu, Wai Kin (Victor) Chan, Weiwei Chen, Youakim Badr, Canrong Zhang, editors.
001451984 264_1 $$aCham :$$bSpringer,$$c[2022]
001451984 264_4 $$c©2022
001451984 300__ $$a1 online resource (viii, 477 pages) :$$billustrations (chiefly color).
001451984 336__ $$atext$$btxt$$2rdacontent
001451984 337__ $$acomputer$$bc$$2rdamedia
001451984 338__ $$aonline resource$$bcr$$2rdacarrier
001451984 4901_ $$aLecture notes in operations research
001451984 500__ $$aInternational conference proceedings.
001451984 504__ $$aReferences -- 3 Mitigating Braess's Paradox with Information Design -- Introduction -- Literature Review -- Model -- Full Information -- Information Design -- Conclusions -- References -- 4 The Impact of Electronic Shelf Label on Customer Well-Being in the Omnichannel Smart Retail -- Introduction -- Literature Review -- Electronic Shelf Label (ESl) -- Customer Wellbeing -- Method -- Samples and Data Collection Procedure -- Data Analysis -- Results and Discussions -- Conclusions and Implications -- References -- 5 Targeted Bayesian Persuasion in a Basic Selfish Routing Game -- Introduction
001451984 5050_ $$aIntro -- Contents -- 1 A Penalized Neural Network Model for Predicting Unobserved Scores of Construct Indicators and Reproducing Latent Scores of the Theoretical Constructs by Using Text Information -- Introduction -- Related Research -- Methods and Materials -- Proposed Model -- Data Collection and Preprocessing -- Model Estimation and Validation -- Results and Discussion -- Concluding Remarks -- References -- 2 Deep Learning-Based Prediction of Mechanical Ventilation Reintubation in Intensive Care Units -- Introduction -- Data Set -- Methods -- Experiments and Results -- Summary
001451984 5058_ $$aModel Setup -- Travellers' Equilibrium Route Choice -- Optimal Persuasion Policy -- Conclusion -- References -- 6 Stochastic Churn Modeling with Dynamic Attribution and Bayesian Estimation -- Introduction -- General Problem and Models -- Contractual Churn and Probability Modeling -- Probability Churn Models from Marketing -- Empirical Methods and Data -- EMS Workforce Data -- Bayesian Estimation and Inference -- Data Analysis -- Conclusion -- References -- 7 Trade Credit Pricing with Retailer's Capital Heterogeneity -- Introduction -- Literature Review -- Model -- Optimal Wholesale Pricing
001451984 5058_ $$aConclusions -- References -- 8 Systemic Risk Spillover Analysis of China's Banking Industry Based on Generalized Variance Decomposition Network -- Introduction -- Literature Review -- Model Construction and Description -- Volatility Model -- Risk Spillover Network Model -- Empirical Analysis of the Systemic Risk Spillover Effect -- Data Sources and Basic Statistical Analysis -- Static Risk Spillover Analysis -- Dynamic Risk Spillover Analysis -- Risk Spillover Network Analysis -- Conclusion -- References -- 9 Can We Apply Traditional Forecasting Models to Predicting Bitcoin? -- Introduction
001451984 5058_ $$aMethods -- Rejected Models -- Selected Models -- Variable Selection and Model Optimization -- Variable Selection and Model Optimization for ARIMA -- Data Analysis -- Data Analysis-Logistic Regression -- Model 1-Logistic Regression -- Model 2: Logistic Regression with Training/Testing Data -- Model 3: Logistic Regression with Moving Average -- Concerns of Correlation -- Data Analysis-ARIMA -- Model #4: ARIMA Model -- Dickey-Fuller Test -- ARIMA Analysis -- Model 5: ARIMA with Moving Average -- Summary -- References
001451984 506__ $$aAccess limited to authorized users.
001451984 520__ $$aThis book showcases recent research advances in service science and related fields. Including selected papers from the 2022 INFORMS International Conference on Service Science, held in Shenzhen, China from July 2 to 4, 2022, the book presents new theories and empirical results in the emerging, interdisciplinary field of digital transformation and society. Incorporating research, education and practice alike, the respective chapters highlight a host of ways to approach these challenges in service science.
001451984 588__ $$aDescription based on print version record.
001451984 650_0 $$aManagement science$$vCongresses.
001451984 650_0 $$aComputers and civilization$$vCongresses.
001451984 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001451984 655_7 $$aConference papers and proceedings.$$2lcgft
001451984 655_0 $$aElectronic books.
001451984 7001_ $$aQiu, Robin G.,$$eeditor.$$1https://isni.org/isni/0000000120010378
001451984 7001_ $$aChan, Wai Kin,$$eeditor.
001451984 7001_ $$aChen, Weiwei,$$eeditor.
001451984 7001_ $$aBadr, Youakim,$$d1969-$$eeditor.$$1https://isni.org/isni/0000000122148485
001451984 7001_ $$aZhang, Canrong,$$eeditor.
001451984 7102_ $$aInstitute for Operations Research and the Management Sciences$$1https://isni.org/isni/000000011015751X
001451984 77608 $$iPrint version:$$aINFORMS International Conference on Service Science (2022 : Shenzhen Shi, China), creator.$$tCity, society, and digital transformation.$$dCham : Springer, 2022$$z9783031156434$$w(OCoLC)1348390368
001451984 830_0 $$aLecture notes in operations research.
001451984 852__ $$bebk
001451984 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-15644-1$$zOnline Access$$91397441.1
001451984 909CO $$ooai:library.usi.edu:1451984$$pGLOBAL_SET
001451984 980__ $$aBIB
001451984 980__ $$aEBOOK
001451984 982__ $$aEbook
001451984 983__ $$aOnline
001451984 994__ $$a92$$bISE