scholarly journals Multiway data analysis for comparing time use in different countries - Application to timebudgets at different stages of life in six European countries

2006 ◽  
Vol 3 (1) ◽  
pp. 88-109 ◽  
Author(s):  
Mary Fraire
Keyword(s):  
Data Analysis ◽  
Time Use ◽  
European Countries ◽  
Multiway Data Analysis

scholarly journals Analysis of Time Use Surveys Using CO-STATIS: A Multiway Data Analysis of Gender Inequalities in Time Use in Colombia

2021 ◽  
Vol 13 (23) ◽  
pp. 13073
Author(s):  
Edith Johana Medina-Hernández ◽  
María José Fernández-Gómez ◽  
Inmaculada Barrera-Mellado
Keyword(s):  
Data Analysis ◽  
Time Use ◽  
Gender Stereotypes ◽  
Age Groups ◽  
Gender Inequalities ◽  
Socioeconomic Level ◽  
Low Socioeconomic ◽  
Analysis Technique ◽  
Multiway Data Analysis ◽  
Time Use Surveys

The aim of this article was to study 23 time use activities measured in the two latest Colombian National Time Use Surveys, taken in 2013 (with 119,899 participants over the age of 10) and in 2017 (with a sample of 122,620 participants), to identify similarities and differences between the years of the survey by gender, age group, and socioeconomic level. The study’s results were obtained using the CO-STATIS multiway multivariate data analysis technique, which is comprised of two X-STATIS analyses and co-inertia analysis. The results confirm the existence of gender issues related to time use in Colombia, which are associated with gender stereotypes that link women to unpaid work and home care, especially in low socioeconomic levels, where women face limitations in terms of the time available to earn their own income. Additionally, differences were found by socioeconomic level, where Colombians of high socioeconomic status in all age groups are able to devote more time to leisure and recreational activities.

scholarly journals The Risk of Residential Peak Electricity Demand: A Comparison of Five European Countries

2017 ◽  
Author(s):  
Jacopo Torriti
Keyword(s):  
Time Use ◽  
Electricity Markets ◽  
Electricity Market ◽  
Dynamic Pricing ◽  
Risk Model ◽  
European Countries ◽  
Peak Demand ◽  
Time Use Survey ◽  
Control Dynamic ◽  
Different Levels

The creation of a Europe-wide electricity market combined with the increased intermittency of supply from renewable sources calls for an investigation into the risk of aggregate peak demand. This paper makes use of a risk model to assess differences in time-use data from residential end-users in five different European electricity markets. Drawing on the Multinational Time-Use Survey database, it assesses risk in relation to the probability of electrical appliance use within households for five European countries. Findings highlight in which countries and for which activities the risk of aggregate peak demand is higher and link smart home solutions (automated load control, dynamic pricing and smart appliances) to different levels of peak demand risk.

NeuralCP: Bayesian Multiway Data Analysis with Neural Tensor Decomposition

2018 ◽  
Vol 10 (6) ◽  
pp. 1051-1061 ◽  
Author(s):  
Bin Liu ◽  
Lirong He ◽  
Yingming Li ◽  
Shandian Zhe ◽  
Zenglin Xu
Keyword(s):  
Data Analysis ◽  
Tensor Decomposition ◽  
Multiway Data Analysis

scholarly journals How Does Time Use Differ between Individuals Who Do More versus Less Foodwork? A Compositional Data Analysis of Time Use in the United Kingdom Time Use Survey 2014–2015

Nutrients ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2280
Author(s):  
Chloe Clifford Astbury ◽  
Louise Foley ◽  
Tarra L. Penney ◽  
Jean Adams
Keyword(s):  
Data Analysis ◽  
Time Use ◽  
Compositional Data ◽  
Unintended Consequences ◽  
Food Preparation ◽  
Compositional Data Analysis ◽  
Personal Care ◽  
Home Food ◽  
Time Use Survey ◽  
Home Food Preparation

Background: Increased time spent on home food preparation is associated with higher diet quality, but a lack of time is often reported as a barrier to this practice. We compared time use in individuals who do more versus less foodwork (tasks required to feed ourselves and our households, including home food preparation). Methods: Cross-sectional analysis of the UK Time Use Survey 2014–15, participants aged 16+ (N = 6143). Time use over 24 h was attributed to seven compositional parts: personal care; sleep; eating; physical activity; leisure screen time; work (paid and unpaid); and socialising and hobbies. Participants were categorised as doing no, ‘some’ (<70 min), or ‘more’ foodwork (≥70 min). We used compositional data analysis to test whether time-use composition varied between these participant groups, determine which of the parts varied between groups, and test for differences across population subgroups. Results: Participants who spent more time on foodwork spent less time on sleep, eating, and personal care and more time on work. Women who did more foodwork spent less time on personal care, socialising, and hobbies, which was not the case for men. Conclusion: Those who seek to encourage home food preparation should be aware of the associations between foodwork and other activities and design their interventions to guard against unintended consequences.

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