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001480787 0247_ $$a10.1007/978-981-99-1241-4$$2doi
001480787 035__ $$aSP(OCoLC)1396816302
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001480787 08204 $$a519.2/33$$223/eng/20230912
001480787 24500 $$aRecent advances in modeling and forecasting Kaiyu :$$btools for predicting and verifying the effects of urban revitalization policy /$$cSaburo Saito, Kenichi Ishibashi, Kosuke Yamashiro, editors.
001480787 264_1 $$aSingapore :$$bSpringer,$$c[2023]
001480787 264_4 $$c©2023
001480787 300__ $$a1 online resource (xvii, 616 pages) :$$billustrations.
001480787 336__ $$atext$$btxt$$2rdacontent
001480787 337__ $$acomputer$$bc$$2rdamedia
001480787 338__ $$aonline resource$$bcr$$2rdacarrier
001480787 4901_ $$aNew frontiers in regional science. Asian perspectives ;$$vvolume 36
001480787 500__ $$aIncludes index.
001480787 5050_ $$aChapter 1. A disaggregate hierarchical decision Huff model incorporating consumer Kaiyu choices among shopping sites -- Chapter 2. A dynamical Huff model: Computing the competitive equilibrium distribution of shop floor areas over a city center commercial district using the Fixed-Point Algorithm -- Chapter 3. Kaiyu Markov model and evaluation of retail spatial structures -- Chapter 4. Basics of Kaiyu Markov models: Reproducibility theoremsa validation of infinite Kaiyu representation -- Chapter 5. Kaiyu Markov Model with Covariates to Forecast the Change of Consumer Kaiyu Behaviors caused by a Large-Scale City Center Retail Redevelopment -- Chapter 6. Estimation of Disaggregate Huff and Kaiyu Markov Model: A Lecture Note on Conditional Logit Model -- Chapter 7. A Disaggregate Kaiyu Markov Model to Forecast the Sales of Retail Establishments based on the Consumers Frequency of Visits -- Chapter 8. How Would the Kyushu Super-Express Railway Opening Change the Flow of Tourists from the Kansai Region within the Kyushu Wide Area, Japan? : A Micro Behavior Analysis of the Destinations Hub Function -- Chapter 9. A Micro Behavior Approach to Estimating and Forecasting the Intervening Opportunity Effects with a Multivariate Poisson Model: A Case for the New Terminal Complex of Kyushu Super-Express Railway, JR Hakata City -- Chapter 10. How would the opening of JR Hakata City, a new terminal complex of the Kyushu super-express railway, change the number of visitors, retail sales, and consumers Kaiyu flows in the city center commercial district of Fukuoka City? -- Chapter 11. How Many Customers Would be Brought Back from Suburban Shopping Malls to the City Center by Redeveloping the City Center Station Building, JR Oita City, Japan?: A Multivariate Poisson Model with Competitive Destinations -- Chapter 12. An Opportunity Cost Approach to Valuation of the River in a City Center Retail Environment: Another Application of Kaiyu Markov Model -- Chapter 13. Extraction of Long Sightseeing Kaiyu Routes in the Kyushu Wide Region, Japan -- Chapter 14. A Bayesian Network Model of Consumers Kaiyu Behaviors.
001480787 506__ $$aAccess limited to authorized users.
001480787 520__ $$aThis book is the first comprehensive presentation of a Kaiyu Markov model with covariates and a multivariate Poisson model with competitive destinations. These two models are core techniques when the authors and colleagues conduct their Kaiyu studies. The two models are usually used to forecast the effects of specific urban redevelopment on both the number of visitors and consumer shop-around or Kaiyu movements. Their Kaiyu studies originated from the constructions of a Kaiyu Markov model and the disaggregated hierarchical decision Huff model almost simultaneously around the early 1980s. This book retrospectively reviews how these models have evolved from the start to the present state, and previews the ongoing efforts to make further extensions of these models. The extension of the Huff model started from the disaggregated hierarchical decision Huff model with shop-arounds. In retrospect, the model formulated the consumers simultaneous choice of destinations as a joint probability. The mechanism to determine this joint probability was a recursive conditional probability system. Now the Huff model has shifted from joint probability to multivariate frequency Poisson with competitive destinations. On the other hand, the Kaiyu Markov model started from a descriptive model. Because it cannot forecast changes in shop-arounds or consumer Kaiyu behaviors, the Kaiyu Markov model with covariates was developed in which entrance and shop-around choice probabilities are explained by the respective two logit models with covariates such as distances and shop-floor areas. The noticeable point is that it can explain consumers probability of quitting their shop-arounds. Thus, the model enables one to evaluate the effects of urban revitalization policy that promotes consumers shop-arounds or Kaiyu behaviors. Furthermore, if the Kaiyu Markov model can estimate the actual numbers of flows of consumers shop-arounds among shopping sites, the corresponding money flows also can be estimated as economic effects. This book discusses from scratch the evolution of all these topics. Thus this book provides the basics of the Kaiyu Markov model, a tutorial for the theory and estimation of the conditional logit model, and a chapter serving as a practical research manual for forecasting changes caused by urban development based on consumers Kaiyu behaviors.
001480787 588__ $$aDescription based on print version record.
001480787 650_6 $$aProcessus de Markov$$xModèles mathématiques.
001480787 650_0 $$aMarkov processes$$xMathematical models.$$0(DLC)sh 85081369
001480787 655_0 $$aElectronic books.
001480787 7001_ $$aSaitō, Saburō,$$eeditor.
001480787 7001_ $$aIshibashi, Ken'ichi,$$eeditor.
001480787 7001_ $$aYamashiro, Kosuke,$$eeditor.
001480787 77608 $$iPrint version:$$tRecent advances in modeling and forecasting Kaiyu.$$dSingapore : Springer, 2023$$z9789819912407$$w(OCoLC)1381123689
001480787 830_0 $$aNew frontiers in regional science: Asian perspectives ;$$vv. 36.
001480787 852__ $$bebk
001480787 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-1241-4$$zOnline Access$$91397441.1
001480787 909CO $$ooai:library.usi.edu:1480787$$pGLOBAL_SET
001480787 980__ $$aBIB
001480787 980__ $$aEBOOK
001480787 982__ $$aEbook
001480787 983__ $$aOnline
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