1,352 research outputs found
Map cases in Hilton M. Briggs Library at South Dakota State University in 1989
No full textStudents Jason Overby (left) and Troy Forbes are looking at maps in a map case in the lower level of Hilton M. Briggs Library on the campus of South Dakota State Universit
Improving customer service within Asian culture at Hilton hotel
No full textThe purpose of this thesis is investigating specific perspective which perceives Asian service culture among international standard to reinforce customer service in hospitality.
The research presents customer service at the Hilton Hotel and Resorts, the importance of customer service in the Hospitality industry, customer satisfaction analysis model, definition about SERVQUAL, which stands for five dimensions of service quality, the value of perceiving Asian culture to improve customer service for Asian guests. The qualitative research method for this thesis is completed by interviewing two different groups of people.
The thesis puts an effort to clarify several facts about Asian culture, which is related to the Hospitality industry, such as habit lifestyle, etiquette, special traditional culture, hobby, and so on. The author is gathering authentic information from expert people who are currently working in the Hilton Hotel and Resorts, and in other hotels, opinions of some Asian guests are also collected to analyze.
This research concentrates on the improvement of customer service within Asian culture at the Hilton Hotel. In detail, the research is to understand Asian culture and serve Asian customers better by the Hilton Hotel system over the world. The author used qualitative method to analyze the improvement of Asian culture at the Hilton Hotel. The instrument tool in the research was the interview. The result of findings showed that Hilton Helsinki Kalastajatorppa could improve their customer service by helping customers, supporting them, and answering all questions within their ability. In addition, the hotel was better to study Asian culture; for example, providing popular food in Asia such as instant noodles would make customer satisfied. The language was a problem to make customer service better. The result of the interview revealed that employees of the hotel should take a trip to another Hilton in Asia to study, experience, and more understand local people. The second result of the interview presented that in order to improve customer service, employees must put themselves in the shoes of customers so that they could understand what customers want and need. Training course about customer service is extremely necessary to enhance the professional skills of employees
Erengul Dodd, Jonathan J Forster and Jason Hilton's contribution to the Discussion of 'Some statistical aspects of the Covid-19 response' by Wood et al.
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Statistical analysis of agent-based models
No full textIn the video, Dr Jason Hilton and Professor Jakub Bijak introduce the basic concepts related to the design of experiments used to help understand the behaviour of complex computational models, such as agent-based models. They look at the relations between inputs and outputs of models, types of experimental design, and methods of analysing the results of simulation experiments. This video also explores the statistical emulators – or metamodels – and methods for uncertainty and sensitivity analysis
Choosing the Choice: Reflections on modelling decisions and behaviour in demographic agent-based models
No full textThis paper investigates the problems associated with choosing appropriate models of choice for demographic agent-based models. In particular, the importance of context, time-preference and dealing with uncertainty in decision modelling are discussed, together with the heterogeneity between agents in their decision-making strategies. The paper concludes by advocating empirically driven, modular, and multi-model approaches to designing simulations of human decision-making, given the lack of a canonical strategy for dealing with any of these issues. Furthermore, it is suggested that an iterative process of data collection and simulation experiments, with the latter informing future empirical data collection, should form the basis of such an endeavour. The discussion is illustrated with reference to selected demographic agent-based models, in particular those relating to migration
Statistical Emulation
No full textStatistical emulation is a technique for studying the behavior of computational simulation models. With this approach, a statistical function is fitted to the observed relations between model inputs and outputs based on systematic experimentation with the simulation model. The resulting function provides information about the general behavior of the simulation model and can be used, for example, for model simplification, optimization, and calibration. In this article, we discuss the general principles of statistical emulation, introduce readers to regression metamodels and Gaussian process emulators as two examples of commonly used statistical functions, and point readers to experimental designs that can be used for fitting these types of functions.sponsorship: André Grow has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement no. 312290 for the GENDERBALL project. Jason Hilton acknowledges funding from the Economic and Social Research Council grant Centre for Population Change – Phase II (ES/K007394/1).status: Published onlin
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