Enhancing Internal Trip Capture Estimation for Mixed-use Developments


Book Description

TRB's National Cooperative Highway Research Program (NCHRP) Report 684: Enhancing Internal Trip Capture Estimation for Mixed-Use Developments explores an improved methodology to estimate how many internal trips will be generated in mixed-use developments - trips for which both the origin and destination are within the development. The methodology estimates morning and afternoon peak-period trips to and from six specific land use categories: office, retail, restaurant, residential, cinema, and hotel. The research team analyzed existing data from prior surveys and collected new data at three mixed-use development sites. The resulting methodology is incorporated into a spreadsheet model, which is available online for download.




Dissertation Abstracts International


Book Description

Abstracts of dissertations available on microfilm or as xerographic reproductions.




Bayesian Non- and Semi-parametric Methods and Applications


Book Description

This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and marketing applications involve arbitrary distributional assumptions. As more data becomes available, a natural desire to provide methods that relax these assumptions arises. Peter Rossi advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. The Bayesian approach can use either a large but fixed number of normal components in the mixture or an infinite number bounded only by the sample size. By using flexible distributional approximations instead of fixed parametric models, the Bayesian approach can reap the advantages of an efficient method that models all of the structure in the data while retaining desirable smoothing properties. Non-Bayesian non-parametric methods often require additional ad hoc rules to avoid "overfitting," in which resulting density approximates are nonsmooth. With proper priors, the Bayesian approach largely avoids overfitting, while retaining flexibility. This book provides methods for assessing informative priors that require only simple data normalizations. The book also applies the mixture of the normals approximation method to a number of important models in microeconometrics and marketing, including the non-parametric and semi-parametric regression models, instrumental variables problems, and models of heterogeneity. In addition, the author has written a free online software package in R, "bayesm," which implements all of the non-parametric models discussed in the book.




Market-Share Analysis


Book Description

Foreword In April1971, Los Angeles and its satellite cities were treated to one of its least interesting and least publicized elections in years. Nothing seemed to be hotly contested. A few Los Angeles city councilmen were up for reelection as were some members of the Board of Ed ucation and the Board of Trustees of the Community Colleges. - Nakanishi, Cooper and Kassarjian [1974] Our colleague, Professor Harold H. Kassarjian, ran for one of the seats on the Board of Trustees and received 17,286 votes. While he lost the election, he had collected the data which he felt characterized voting in such /ow-invo/vement cases. He asked us to join him in writing a follow-up to a study of a similar election which had been published the previous faU in Public Opinion Quarter/y. Neither of us was content with the methods and models used in the prior study. Shares are different than other criteria, be they vote shares, market shares or retail stores' shares of customers. Different methods are needed to reflect their special nature. And thus began a research collaboration, running 17 years, so far. Though our combined research efforts have covered diverse areas of consumer choice behavior, in recent years we carne to the realization that our models and analytical methods might be very profitably employed in the analysis of market-share figures for consumer products.




Competition Policy


Book Description

This is the first book to provide a systematic treatment of the economics of antitrust (or competition policy) in a global context. It draws on the literature of industrial organisation and on original analyses to deal with such important issues as cartels, joint-ventures, mergers, vertical contracts, predatory pricing, exclusionary practices, and price discrimination, and to formulate policy implications on these issues. The interaction between theory and practice is one of the main features of the book, which contains frequent references to competition policy cases and a few fully developed case studies. The treatment is written to appeal to practitioners and students, to lawyers and economists. It is not only a textbook in economics for first year graduate or advanced undergraduate courses, but also a book for all those who wish to understand competition issues in a clear and rigorous way. Exercises and some solved problems are provided.




The Black Diamond


Book Description




Bayesian Statistics and Marketing


Book Description

The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new product introduction to pricing, and with a wide variety of different data sources. Bayesian Statistics and Marketing describes the basic advantages of the Bayesian approach, detailing the nature of the computational revolution. Examples contained include household and consumer panel data on product purchases and survey data, demand models based on micro-economic theory and random effect models used to pool data among respondents. The book also discusses the theory and practical use of MCMC methods. Written by the leading experts in the field, this unique book: Presents a unified treatment of Bayesian methods in marketing, with common notation and algorithms for estimating the models. Provides a self-contained introduction to Bayesian methods. Includes case studies drawn from the authors’ recent research to illustrate how Bayesian methods can be extended to apply to many important marketing problems. Is accompanied by an R package, bayesm, which implements all of the models and methods in the book and includes many datasets. In addition the book’s website hosts datasets and R code for the case studies. Bayesian Statistics and Marketing provides a platform for researchers in marketing to analyse their data with state-of-the-art methods and develop new models of consumer behaviour. It provides a unified reference for cutting-edge marketing researchers, as well as an invaluable guide to this growing area for both graduate students and professors, alike.







Predictive Marketing


Book Description

Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.




The Theory of Buyer Behavior


Book Description