Estimation of the effects of price and billing frequency on household water demand using a panel of Wisconsin municipalities

Fenrick, Steven Andrew; Getachew, Lullit

doi:10.1080/13504851.2011.629977

Cited by 10 publications

(9 citation statements)

References 13 publications

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“…The conclusion reached was positive for the impact of monthly billing on water conservation. They determined a 3.7% reduction in household water usage for monthly billing against a longer billing frequency [81]. Their study confirmed a reduction in water demand through monthly billing to the utility through providing more information to their customers and creating an increased awareness of the costs of water.…”

Section: Usage Costmentioning

confidence: 88%

“…In the same study, Fenrick and Getachew also identified the impact of introducing water efficient appliances on total demand and determined a 1.1% reduction in per capita water use due to the household adoption of water efficient technology [81]. Digital water metering may improve the measurement of impact of appliance efficiency on total demand.…”

Section: Usage Costmentioning

confidence: 98%

“…From these new mathematical models, algorithms may be developed to improve water utility planning and operations [80]. In the area of customer end-use, Nguyen et al applied a hybrid combination of the Hidden Markov Model (HMM) and the Dynamic Time Warping algorithm (DTW) to disaggregate household flows [9], Cardell-Oliver applied cluster analysis to identify signature patterns [12], and Fenrick and Getachew advanced statistical methods to measure the impact of frequent billing on demand and to identify long-term appliance efficiency trends [81]. Huang et al applied dynamic time warping, supervised learning, and calculated the abnormality probability for real-time burst detection in DMAs [82].…”

Section: New Algorithmsmentioning

confidence: 99%

“…In 2012 Fenrick and Getachew [81], studying the impact of billing frequency, developed a demand function of residential water consumption using data from a 1997 to 2006 panel of 200 Wisconsin water utilities. Unlike previous studies which relied on regression, they assumed a double-log functional form and estimated parameters using a random effects model.…”

Section: Usage Costmentioning

confidence: 99%

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Revealing Unreported Benefits of Digital Water Metering: Literature Review and Expert Opinions

Monks

Stewart

Sahin

et al. 2019

Water

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Digital water meters can take Australian water utilities into the world of internet of things (IoT) and big data analytics. The potential is there for them to build more efficient processes, to enable new products and services to be offered, to defer expensive capital works, and for water conservation to be achieved. However, utilities are not mounting business cases with sufficient benefits to cover the project and operational costs. This study undertakes a literature review and interviews of industry experts in the search for unreported benefits that might be considered for inclusion in business cases. It identifies seventy-five possible benefits of which fifty-seven are classified as benefiting the water utility and forty are classified as benefiting customers (twenty-two benefit both). Many benefits may be difficult to monetize. Benefits to customers may have a small monetary benefit to the water utility but provide a significant benefit to customer satisfaction scores. However, for utilities to achieve these potential benefits, eight change enablers were identified as being required in their systems, processes, and resources. Of the seventy-five benefits, approximately half might be considered previously unreported. Finally, a taxonomy is presented into which the benefits are classified, and the enabling business changes for them to be realized are identified. Water utilities might consider the taxonomy, the benefits, and the changes required to enable the benefits when developing their business cases.

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Section: Usage Costmentioning

confidence: 88%

Section: Usage Costmentioning

confidence: 98%

Section: New Algorithmsmentioning

confidence: 99%

Section: Usage Costmentioning

confidence: 99%

See 2 more Smart Citations

Revealing Unreported Benefits of Digital Water Metering: Literature Review and Expert Opinions

Monks

Stewart

Sahin

et al. 2019

Water

View full text Add to dashboard Cite

show abstract

“…Panel data models are typically preferred to the time-series and cross-sectional models because they include the advantages of both models and can provide more accurate parameter estimates (Arbu es et al, 2003;Polebitski and Palmer, 2010). In recent years with increase in the data availability these models have been used more frequently (Nauges and Thomas, 2000;Martinez-Espiñeira, 2002;Arbu es et al, 2004Arbu es et al, , 2010Kenney et al, 2008;Polebitski and Palmer, 2010;Fenrick and Getachew, 2012). However, to the knowledge of the authors, the panel data model never has been used for the water demand analysis in the apartment sector.…”

Section: Introductionmentioning

confidence: 99%

A Multi‐Scale Analysis of Low‐Rise Apartment Water Demand through Integration of Water Consumption, Land Use, and Demographic Data

Ghavidelfar

Shamseldin

Melville

2016

J American Water Resour Assoc

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Over the past decades, multi‐unit housing developments have been vastly expanded across urban areas due to the population growth. To properly supply water to this growing sector, it is essential to understand the determinants of its water use. However, this task has largely remained unexplored through the empirical study of water demand mainly due to the scarcity of data in this sector. This study integrated apartment water consumption, property characteristics, weather, water pricing, and census microdata to overcome this issue. Using a rich source of GIS‐based urban databases in Auckland, New Zealand, the study developed a large dataset containing the information of 18,000 low‐rise apartments to evaluate the determinants of water use both in the household scale and aggregated scale. The household‐scale demand analysis helped to assess the heterogeneity in responses to the demand drivers specifically water price across different consumer groups, whereas the aggregated analysis revealed the determinants behind the spatial variation in water demand at the census area unit level. Through applying panel data models, the study revealed the household size as the most important determinant of apartment water use in Auckland, where other socioeconomic factors, building features, and water pricing were not significant determinants. This knowledge of determinants of water demand can help water planners to better manage water demand in the compact urban environments.

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Estimation of Tap Water Demand in Japan: A Panel Data Analysis

Nakayama

Urakami

2023

Kobe University Monograph Series in Social Science Research

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Estimation of the effects of price and billing frequency on household water demand using a panel of Wisconsin municipalities

Cited by 10 publications

References 13 publications

Revealing Unreported Benefits of Digital Water Metering: Literature Review and Expert Opinions

Revealing Unreported Benefits of Digital Water Metering: Literature Review and Expert Opinions

A Multi‐Scale Analysis of Low‐Rise Apartment Water Demand through Integration of Water Consumption, Land Use, and Demographic Data

Estimation of Tap Water Demand in Japan: A Panel Data Analysis

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