scholarly journals A model for measuring healthcare accessibility using the behavior of demand: a conditional logit model-based floating catchment area method

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hoon Jang
Keyword(s):  
Health Services ◽  
Logit Model ◽  
Catchment Area ◽  
Choice Model ◽  
Healthcare Delivery ◽  
Obstetric Care ◽  
Access To Health Services ◽  
Conditional Logit Model ◽  
Conditional Logit ◽  
Willingness To Use

Abstract Background Estimating realistic access to health services is essential for designing support policies for healthcare delivery systems. Many studies have proposed a metric to calculate accessibility. However, patients’ realistic willingness to use a hospital was not explicitly considered. This study aims to derive a new type of potential accessibility that incorporates a patient’s realistic preference in selecting a hospital. Methods This study proposes a floating catchment area (FCA)-type metric combined with a discrete choice model. Specifically, a new FCA-type metric (clmFCA) was proposed using a conditional logit model. Such a model estimates patients’ realistic willingness to use health services. The proposed metric was then applied to calculate the accessibility of obstetric care services in Korea. Results The clmFCA takes advantage of patients’ realistic preferences. Specifically, it can represent each patient’s heterogeneous characteristics regarding hospital choice. Such characteristics include bypassing behavior, which could not be considered using prior FCA metrics. Empirical analysis reveals that the clmFCA avoids the misestimation of accessibility to health services to an extent. Conclusions The clmFCA offers a new framework that more realistically estimates patients’ accessibility to health services. This is achieved by accurately estimating the potential demand for a service. The proposed method’s effectiveness was verified through a case study using nationwide data.

scholarly journals A Deep Choice Model for Hiring Outcome Prediction in Online Labor Markets

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Yixuan Ma ◽  
Zhenji Zhang ◽  
Alexander Ihler
Keyword(s):  
Labor Markets ◽  
Logit Model ◽  
Choice Model ◽  
Hiring Decisions ◽  
Conditional Logit Model ◽  
Conditional Logit ◽  
Online Labor Markets ◽  
Non Linear ◽  
Linear Utility ◽  
Online Labor

A key challenge faced by online labor market researchers and practitioners is to understand how employers make hiring decisions from many job bidders with distinct attributes. This study investigates employer hiring behavior in one of the largest online labor markets by building a datadriven hiring decision prediction model. With the limitation of traditional discrete choice model (conditional logit model), we develop a novel deep choice model to simulate the hiring behavior from 722,339 job posts. The deep choice model extends the classical conditional logit model by learning a non-linear utility function identically for each bidder within of the job posts via a pointwise convolutional neural network. This non-linear mapping can be straightforwardly optimized using stochastic gradient approach. We test the model on 12 categories of job posts in the dataset. Results show that our deep choice model outperforms the linear-utility conditional logit model in predicting hiring preferences. By analyzing the model using dimensionality reduction and sensitivity analysis, we highlight the nonlinear combination of bidders’ features in impacting employers’ hiring decisions.

A Heterogeneous Conditional Logit Model of Choice

1988 ◽  
Vol 6 (3) ◽  
pp. 391 ◽  
Author(s):  
Joel H. Steckel ◽  
Wilfried R. Vanhonacker
Keyword(s):  
Logit Model ◽  
Conditional Logit Model ◽  
Conditional Logit

scholarly journals The Value of Social Interactions and Incentives on the Use of a Digital Contact Tracing Tool Post COVID-19 Lockdown in Singapore

2021 ◽  
Author(s):  
Zhilian Huang ◽  
Huiling Guo ◽  
Hannah YeeFen Lim ◽  
Kia Nam Ho ◽  
Evonne Tay ◽  
...  
Keyword(s):  
Social Interactions ◽  
Discrete Choice ◽  
Logit Model ◽  
Choice Experiment ◽  
Public Hospital ◽  
Contact Tracing ◽  
Monetary Incentives ◽  
Conditional Logit Model ◽  
Conditional Logit ◽  
Trade Offs

Abstract BackgroundWe assessed the preferences and trade-offs for social interactions, incentives, and being traced by a digital contact tracing (DCT) tool post lockdown in Singapore.MethodsWe conducted a discrete choice experiment (DCE) among visitors of a large public hospital in Singapore between July 2020 – February 2021. Respondents were sampled proportionately by gender and four age categories (21 – 80 years). The DCE questionnaire had three attributes (1. Social interactions, 2. Being traced by a DCT tool, 3. Incentives to use a DCT tool) and two levels each. The final dataset comprised 3839 respondents after dropping 53 with “irrational” responses. Panel fixed conditional logit model was used to analyze the data.ResultsRespondents were more willing to trade being traced by a DCT tool for social interactions than incentives and unwilling to trade social interactions for incentives. The proportion of respondents preferring no incentives and could only be influenced by their family members increases with age. Among proponents of monetary incentives, the preferred median value for a month’s usage of DCT tools amounted to S$10 (USD7.25) and S$50 (USD36.20) for subsidies and lucky draw.ConclusionsDCE can be used to elicit profile-specific preferences to optimize the uptake of DCT tools during a pandemic. Social interactions are highly valued by the population, who are willing to trade them for being traced by a DCT tool during the COVID-19 pandemic. Although a small amount of incentive is sufficient to increase the satisfaction of using a DCT tool, incentives alone may not increase DCT tool uptake.

Valuing biodiversity of Dachigam National Park: a choice experiment application

2020 ◽  
Vol 31 (6) ◽  
pp. 1569-1585
Author(s):  
Mohammad Younus Bhat ◽  
M.S. Bhatt ◽  
Arfat Ahmad Sofi
Keyword(s):  
Logit Model ◽  
Choice Experiment ◽  
National Park ◽  
Conditional Logit Model ◽  
Content Type ◽  
Biological Resources ◽  
Conditional Logit ◽  
Park Area ◽  
Dachigam National Park ◽  
Research And Education

PurposeBiodiversity loss has become widespread since current rates are potentially catastrophic for species and habitat integrity, and the Dachigam National Park in Jammu and Kashmir (India) is not a distinctive case. Therefore, the main objective of this study is to elicit the willingness to pay (WTP) for biodiversity conservation of the Park.Design/methodology/approachA survey-based choice experiment method was carried out at the Dachigam National Park, an area that is threatened by several anthropogenic pressures. Attributes selected for analysis through choice experiments were endangered species, national park area, research and education opportunities the park withholds. To estimate WTP, a monetary variable involving an increase in entry fee was also incorporated. To obtain the estimates, the authors use the augmented conditional logit model.FindingsWTP for the selected attributes per visitor turned out to be ₹302.07 for enhancing the population of endangered species, ₹121.91 for improvement in the park area and ₹171.64 for increasing research and education opportunities the park withholds.Research limitations/implicationsThough the study uncovers very important aspects of evaluating the biological resources, albeit with some limitations. The study estimates WTP for biodiversity conservation using a conditional logit model, which is based on a specific area and population sample. It would be better if a broader sample is considered to trace out the findings for meaningful generalization. Besides, the results can be replicated for similar kinds of samples.Practical implicationsWith the use of benefits transfer method, this study aims to provide policymakers with useful information to manage biodiversity attributes across the Himalayan region.Originality/valueThe main contribution of this study is to provide a critical understanding of the valuation to facilitate the concerned body for better planning and management of biological resources. The findings of the present study can be used as an indicator of the inherent economic importance of biological resources across the Himalayan range for their better management and conservation that can help in ensuring sustainable utilization of these resources.

scholarly journals Work, childcare, or both? Experimental evidence on the efficacy of childcare subsidies in raising parental labor supply

2019 ◽  
Author(s):  
Christoph Zangger ◽  
Janine Widmer ◽  
Sandra Gilgen
Keyword(s):  
Labor Supply ◽  
Logit Model ◽  
Marginal Utility ◽  
Factorial Survey ◽  
Conditional Logit Model ◽  
High Expectations ◽  
Expected Effect ◽  
Conditional Logit ◽  
Policy Tool ◽  
Using Data

As a policy tool aimed at raising parental labor supply, childcare subsidies come with high expectations. Using data from a factorial survey, we examine whether childcare subsidies reach their goal. Because of the simultaneity of the decision to take up a job and arranging childcare, we experimentally alter hypothetical income (e.g., gross earnings from a job, income from other sources) as well as aspects of the childcare setting including subsidy levels. Using an alternative specific conditional logit model, we show that subsidies have the expected effect of increasing parents’ labor supply. Moreover, the results from simulations based on the estimated utility function show that varying subsidy levels have different effects on subgroups of parents. Subsidies are especially efficient in raising the labor supply of high income, Swiss-born parents, and especially for women. We also find that subsidies already have the desired effect at 25% of total childcare costs and that the marginal utility of higher subsidy levels decreases quite sharply beyond that threshold. Subsidies covering 25% of the total costs for childcare lead to an approximately 3 hours per week increase in the labor supply of women.

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