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Full-Text Articles in Business
Bayesian Mixtures Of Autoregressive Models, Sally Wood, Ori Rosen, Robert Kohn
Bayesian Mixtures Of Autoregressive Models, Sally Wood, Ori Rosen, Robert Kohn
Sally Wood
In this paper we propose a class of time-domain models for analyzing possibly nonstationary time series. This class of models is formed as a mixture of time series models, whose mixing weights are a function of time. We consider specifically mixtures of autoregressive models with a common but unknown lag. The model parameters, including the number of mixture components, are estimated via Markov chain Monte Carlo methods. The methodology is illustrated with simulated and real data.
Planning: The Nexus Between Proactiveness And Innovation, Jennifer Harrison, Stephen Kelly
Planning: The Nexus Between Proactiveness And Innovation, Jennifer Harrison, Stephen Kelly
Adjunct Professor Stephen J Kelly
No abstract provided.
Measuring Service Quality In A Corporatised Public Sector Environment, Karen Mcfadyen, Jennifer Harrison, Stephen Kelly, Don Scott
Measuring Service Quality In A Corporatised Public Sector Environment, Karen Mcfadyen, Jennifer Harrison, Stephen Kelly, Don Scott
Adjunct Professor Stephen J Kelly
Using a modified SERVQUAL scale, this paper measures perceived service quality in a corporatised public sector environment. Five factors were identified: personalised proficiency, empathic professionalism, reliability, tangibles and access; explaining 61% of overall variance. Further analysis using multiple regression also indicated that 45% of the variability in customer satisfaction and 43% of the variability in overall service quality was explained by the five factors. The research was conducted in response to calls for the application of this measure and following a review of extant literature that indicated the limited number of studies undertaken within the public sector that assessed service …
Rejoinder: Estimation Issues For Copulas Applied To Marketing Data, Peter Danaher, Michael Smith
Rejoinder: Estimation Issues For Copulas Applied To Marketing Data, Peter Danaher, Michael Smith
Michael Stanley Smith
Estimating copula models using Bayesian methods presents some subtle challenges, ranging from specification of the prior to computational tractability. There is also some debate about what is the most appropriate copula to employ from those available. We address these issues here and conclude by discussing further applications of copula models in marketing.
Forecasting Television Ratings, Peter Danaher, Tracey Dagger, Michael Smith
Forecasting Television Ratings, Peter Danaher, Tracey Dagger, Michael Smith
Michael Stanley Smith
Despite the state of flux in media today, television remains the dominant player globally for advertising spend. Since television advertising time is purchased on the basis of projected future ratings, and ad costs have skyrocketed, there is increasing pressure to forecast television ratings accurately. Previous forecasting methods are not generally very reliable and many have not been validated, but more distressingly, none have been tested in today’s multichannel environment. In this study we compare 8 different forecasting models, ranging from a naïve empirical method to a state-of-the-art Bayesian model-averaging method. Our data come from a recent time period, 2004-2008 in …
Improving Hurricane Disaster Preparedness: Models For Optimal Reallocation Of Hospital Capacity, Jomon Paul, Rajan Batta
Improving Hurricane Disaster Preparedness: Models For Optimal Reallocation Of Hospital Capacity, Jomon Paul, Rajan Batta
Jomon Aliyas Paul
This research presents significant improvements to the hospital capacity planning models for hurricane disaster proposed by Paul and Batta. Firstly, we develop a model that reallocates hospital capacities taking into account the effect of casualty severity on medical care demands and travel time to hospitals on casualty outcomes. Secondly, travel time to hospitals, a key input to the model, is estimated using a stochastic simulation. Thirdly, in order to meet with challenges that arise as disaster evolves, we develop an algorithm that dynamically updates the pre-disaster plans to post-disaster reality. The algorithm evaluates prior decisions by dynamically updating the hospital …
Exploring Managerial Response To Inventory Ordering When Faced With Supply And Demand Disruption Probabilities, Maria R. Ibanez
Exploring Managerial Response To Inventory Ordering When Faced With Supply And Demand Disruption Probabilities, Maria R. Ibanez
Maria Ibanez
The purpose of this article is to describe the effects of demand and supply uncertainty and risk aversion on organizational decision making for inventory level.