Heterogeneity in time and energy use of watching television

Sekar, Ashok; Williams, Eric; Chen, Roger

doi:10.1016/j.enpol.2016.02.035

Cited by 21 publications

(13 citation statements)

References 24 publications

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“…Several studies show that the socio-demographic conditions give rise to significant differences in time use of household members (López-Rodríguez et al 2013;Santiago et al 2014;Jones et al, 2015;Fisher et al 2015;Sekar et al, 2016;Matsumoto 2016).…”

Section: Consideration Of the Influence Of Socio-demographic Conditionsmentioning

confidence: 99%

A cross analysis of existing methods for modelling household appliance use

Yamaguchi

Yılmaz

Prakash

et al. 2018

Journal of Building Performance Simulation

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This paper presents a cross-analysis of the existing methods for modelling the use of household appliances and aims to provide insights into modelling approaches for researchers and designers. Five factors regarding appliance use modelling that have a significant impact on the modelling performance are defined: consideration of the intra/inter-household variation, consideration of the influence of socio-demographic conditions, time resolution of the data, quantification of model calibration parameters and applicability to a variety of modelling contexts. Four existing modelling methods commonly used in literature for modelling appliance use are studied to address these factors. Monitored data of 333 multi-family buildings in Japan and a Japanese time use survey are used in the cross-analysis to simulate the switch-on time profiles for the case of washing machines. The design of future research studies (including monitoring strategies, modelling and sample sizes) are discussed to further improve the ability to model home appliance use.

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Section: Consideration Of the Influence Of Socio-demographic Conditionsmentioning

confidence: 99%

A cross analysis of existing methods for modelling household appliance use

Yamaguchi

Yılmaz

Prakash

et al. 2018

Journal of Building Performance Simulation

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“…Although investigating the heterogeneity in the usage of products is often hampered by the lack of adequate data, a few studies are available that address this gap and demonstrate consumers’ usage heterogeneity. Sekar and colleagues () analyzed data from the American Time Use Survey and showed that extreme heterogeneity exists in consumers’ television usage. Sanquist and colleagues () suggested that users’ lifestyle profile may correlate to their PC usage.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In fact, a significant heterogeneity has been observed in consumer electronics consumption patterns (Sekar et al. ). This variability not only can skew the prognostications of the electricity consumption, but it can also affect any estimates of the corresponding greenhouse gas emissions or other environmental impacts.…”

Section: Introductionmentioning

confidence: 99%

Environmental Impact Assessment of the Heterogeneity in Consumers’ Usage Behavior: An Agent‐Based Modeling Approach

Mashhadi

Behdad

2017

J of Industrial Ecology

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The aim of this study is to develop a framework for understanding the heterogeneity and uncertainties present in the usage phase of the product life cycle through utilizing the capabilities of an agent-based modeling (ABM) technique. An ABM framework is presented to model consumers' daily product usage decisions and to assess the corresponding electricity consumption patterns. The theory of planned behavior (TPB), with the addition of the habit construct, is used to model agents' decision-making criteria. A case study is presented on the power management behavior of personal computer users and the possible benefits of using smart metering and feedback systems. The results of the simulation demonstrate that the utilization of smart metering and feedback systems can promote the energy conservation behaviors and reduce the total PC electricity consumption of households by 20%. Keywords:agent-based modeling consumer behavior energy consumption industrial ecology life cycle assessment Smart metering and feedback systems Supporting information is linked to this article on the JIE website Conflict of interest statement: The authors have no conflict to declare.

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“…The heterogeneity of TV watching patterns according to age and other demographic variables was analyzed in Sekar et al, 2016 [17].…”

Section: Elderly and Retired Individualsmentioning

confidence: 99%

“…Retired individuals spend more time sleeping and watching TV and less time traveling than working individuals. The heterogeneity of TV watching patterns according to age and other demographic variables was analyzed in Sekar et al, 2016 [17].…”

Section: Elderly and Retired Individualsmentioning

confidence: 99%

Impacts of Autonomous Vehicles on Consumers Time-Use Patterns

et al. 2017

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Abstract:We use the American Time Use Survey (ATUS) to characterize how different consumers in the US might use Autonomous Vehicles (AVs). Our approach is to identify sub-groups of the population likely to benefit from AVs and compare their activity patterns with an otherwise similar group. The first subgroup is working individuals who drive to work with long total travel times. Auto-travelers in the top 20% of travel time number 19 million and travel 1.6 h more on a workday than those in the bottom 80%. For car-commuting professionals, the additional travel time of the long-traveling group comes from 30 min less work, 29 min less sleep, and 30 min less television watching per day. The second subgroup is working individuals with a long travel time and who take public transport. Long public transit riders show very similar differences in activity times as the driving subgroup. Work, sleep, and video functionalities of AVs are presumably in high demand by both groups. The third sub-group identified is elderly retired people. AVs enable mobility-restricted groups to travel more like those without restrictions. We compare two age groups, 60-75 years and >75 years old, the latter, on average, experiencing more mobility restrictions than their younger counterparts. The retired population older than 75 years numbers 16 million and travels 14 min less per day than retirees aged 60-75 years. The main activity change corresponding to this reduced travel is 7 min per day less shopping and 8 min per day less socializing. If older retired people use AVs to match the lifestyle of the 60-75 years old group, this would induce additional personal travel and retail sector demand. The economic, environmental and social implications of AV are very difficult to predict but expected to be transformative. The contribution of this work is that it utilizes time-use surveys to suggest how AV adoption could induce lifestyle changes inside and outside the vehicle.

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Heterogeneity in time and energy use of watching television

Cited by 21 publications

References 24 publications

A cross analysis of existing methods for modelling household appliance use

A cross analysis of existing methods for modelling household appliance use

Environmental Impact Assessment of the Heterogeneity in Consumers’ Usage Behavior: An Agent‐Based Modeling Approach

Impacts of Autonomous Vehicles on Consumers Time-Use Patterns

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