Flux-corrected dispersion-improved CABARET schemes for linear and nonlinear wave propagation problems

The new two-time-level dispersion improved CABARET scheme is developed as an upgrade of the original CABARET for improved wave propagation modelling in multiple dimensions and for nonlinear conservation laws including gas dynamics. The new upgrade retains many attractive features of the original CABARET scheme such as shock-capturing and low dissipation. It is simple for implementation in the existing CABARET codes and leads to a greater accuracy for solving linear wave propagation problems. A non-linear version of the dispersion-improved CABARET scheme is introduced to efficiently deal with contact discontinuities and shocks. The properties of the new linear and nonlinear CABARET schemes are analysed for numerical dissipation and dispersion error based on Von Neumann analysis and Pirrozolli's method. Numerical examples for one-dimensional and two-dimensional linear advection, the one-dimensional inviscid Burger's equation, and the isothermal gas dynamics problems in one and two dimensions are presented

CABARET Schemes for improved wave propagation and viscous flow modelling

PhD thesisThe dispersion improved Compact Accurately Boundary Adjusting high- REsolution Technique (CABARET) schemes are presented as an upgrade of the original CABARET for improved wave propagation modeling. The new modification retains many attractive features of the original CABARET scheme such as shock-capturing and low dissipation. It is simple for implementation in the existing CABARET codes and leads to greater accuracy for solving linear wave propagation problems. A non-linear version of the dispersion-improved CABARET scheme is introduced to deal with contact discontinuities and shocks efficiently. The properties of the new linear and nonlinear CABARET schemes are analyzed for numerical dissipation and dispersion error based on Von Neumann analysis. The properties of the new linear and nonlinear CABARET schemes are demonstrated for one-dimensional, two-dimensional, and three-dimensional flows. Furthermore, the viscous terms in the full three-dimensional CABARET unstructured Navier-Stokes solver have been updated from the vertex approach to the collocated approach, resulting in efficient computational time

Intermediated vs. Direct Sales and a No-Discrimination Rule

When sellers join a platform to sell their products, the platform operator may restrict their strategic decisions. In fact, several platform operators impose most-favored treatment or no-discrimination rules (NDRs), asking sellers not to offer better sales conditions elsewhere. In this paper, I analyze a model that allows for an endogenous split-up of consumers between sales channels. Competing sellers might set different prices across channels, depending on the platform tariff and presence of aNDR. I find that the platform operator imposes a NDR if he faces high transaction costs, if seller competition is weak, and if the initial distribution of consumers on channels is strongly skewed. Prohibiting NDRs can have both positive and negative effects on welfare

The diffusion of a new service: Combining service consideration and brand choice

We propose an individual-level model of a two-stage service diffusion process. In the first stage, customers decide whether to "consider" joining the service. This (Consideration) stage is modeled by a hazard model. Customers who decide to consider the service move on to the Choice stage, wherein they choose among the service alternatives and an outside No Choice option. This stage is modeled by a conditional Multinomial Logit model. The service provider does not observe the transition in the first stage of potential customers who have yet to choose a brand. Such potential customers may have started to consider joining the service, yet chose the outside alternative in each period thereafter. One of the main contributions of the model is its ability to distinguish between these two non-adopter types. We estimated the model using data on the adoption process of newly introduced service plans offered by a commercial bank. We employed the hierarchical Bayes Monte Carlo Markov Chain procedure to estimate individual as well as population parameters. The empirical results indicate that the model outperforms competing models in breadth of analysis, model fit, and prediction accuracy

Leveraging analytics to produce compelling and profitable film content

Producing compelling film content profitably is a top priority to the long-term prosperity of the film industry. Advances in digital technologies, increasing availabilities of granular big data, rapid diffusion of analytic techniques, and intensified competition from user generated content and original content produced by Subscription Video on Demand (SVOD) platforms have created unparalleled needs and opportunities for film producers to leverage analytics in content production. Built upon the theories of value creation and film production, this article proposes a conceptual framework of key analytic techniques that film producers may engage throughout the production process, such as script analytics, talent analytics, and audience analytics. The article further synthesizes the state-of-the-art research on and applications of these analytics, discuss the prospect of leveraging analytics in film production, and suggest fruitful avenues for future research with important managerial implications

Inferring Market Structure from Customer Response to Competing and Complementary Products

We consider customer influences on market structure, arguing that market structure should explain the extent to which any given set of market offerings are substitutes or complements. We describe recent additions to the market structure analysis literature and identify promising directions for new research in market structure analysis. Impressive advances in data collection, statistical methodology and information technology provide unique opportunities for researchers to build market structure tools that can assist “real-time” marketing decision-making.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46981/1/11002_2004_Article_5088105.pd