19,261 research outputs found
Bayesian nonparametric Plackett-Luce models for the analysis of preferences for college degree programmes
In this paper we propose a Bayesian nonparametric model for clustering
partial ranking data. We start by developing a Bayesian nonparametric extension
of the popular Plackett-Luce choice model that can handle an infinite number of
choice items. Our framework is based on the theory of random atomic measures,
with the prior specified by a completely random measure. We characterise the
posterior distribution given data, and derive a simple and effective Gibbs
sampler for posterior simulation. We then develop a Dirichlet process mixture
extension of our model and apply it to investigate the clustering of
preferences for college degree programmes amongst Irish secondary school
graduates. The existence of clusters of applicants who have similar preferences
for degree programmes is established and we determine that subject matter and
geographical location of the third level institution characterise these
clusters.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS717 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Application of Natural Language Processing to Determine User Satisfaction in Public Services
Research on customer satisfaction has increased substantially in recent
years. However, the relative importance and relationships between different
determinants of satisfaction remains uncertain. Moreover, quantitative studies
to date tend to test for significance of pre-determined factors thought to have
an influence with no scalable means to identify other causes of user
satisfaction. The gaps in knowledge make it difficult to use available
knowledge on user preference for public service improvement. Meanwhile, digital
technology development has enabled new methods to collect user feedback, for
example through online forums where users can comment freely on their
experience. New tools are needed to analyze large volumes of such feedback. Use
of topic models is proposed as a feasible solution to aggregate open-ended user
opinions that can be easily deployed in the public sector. Generated insights
can contribute to a more inclusive decision-making process in public service
provision. This novel methodological approach is applied to a case of service
reviews of publicly-funded primary care practices in England. Findings from the
analysis of 145,000 reviews covering almost 7,700 primary care centers indicate
that the quality of interactions with staff and bureaucratic exigencies are the
key issues driving user satisfaction across England
Pedestrians moving in dark: Balancing measures and playing games on lattices
We present two conceptually new modeling approaches aimed at describing the
motion of pedestrians in obscured corridors:
* a Becker-D\"{o}ring-type dynamics
* a probabilistic cellular automaton model.
In both models the group formation is affected by a threshold. The
pedestrians are supposed to have very limited knowledge about their current
position and their neighborhood; they can form groups up to a certain size and
they can leave them. Their main goal is to find the exit of the corridor.
Although being of mathematically different character, the discussion of both
models shows that it seems to be a disadvantage for the individual to adhere to
larger groups. We illustrate this effect numerically by solving both model
systems. Finally we list some of our main open questions and conjectures
Integrating latent variables in discrete choice models – How higher-order values and attitudes determine consumer choice
Integrated choice and latent variable (ICLV) models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM) for latent variables. Despite their conceptual appeal, to date applications of ICLV models in marketing are still rare. The present study on travel mode choice clearly demonstrates the value of ICLV models to enhance understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonisms as well as attitudes such as a desire for flexibility impact on travel mode choice. Further, we can show that it is possible to estimate ICLV models with the widely available structural equation modeling package Mplus. This finding is likely to encourage wider usage of this appealing model class in the marketing field.Hybrid choice models; Mode choice; Values; Value-attitude hierarchy; Mplus
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