Determinants of domestic water consumption in Hermosillo, Sonora, Mexico

Cruz, Arturo Ojeda de la; Álvarez-Chávez, Clara Rosalía; Ramos-Corella, Marco A.; Soto-Hernandez, Fernando

doi:10.1016/j.jclepro.2016.11.094

Cited by 42 publications

(15 citation statements)

References 17 publications

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“…Table 2 shows the statistically significant variables at 5% and 10% levels (p-value < 0.05 and p-value < 0.10), as well as their correlation coefficient. As in the study by Cruz et al, [10], although most of the coefficients presented low values, with absolute values lower than 0.3 in the scale from zero to one, the correlations were statistically significant. The results indicated that 13 variables were associated with monthly water consumption, while 11 were related to per capita water consumption.…”

Section: Correlation Between Variablessupporting

confidence: 72%

“…Table 2 shows the statistically significant variables at 5% and 10% levels (p-value < 0.05 and p-value < 0.10), as well as their correlation coefficient. As in the study by Cruz et al, [10], although most of the coefficients presented low values, with absolute values lower Per capita consumption ranged from 50.64 liters/person/day to 389.54 liters/person/day, with an average of 144.91 liters/person/day. Figure 3b shows that about 90% of the single-family households consumed less than 225 liters/person/day.…”

Section: Correlation Between Variablessupporting

confidence: 59%

“…In Madrid, González, Rueda, and Les [31] obtained a similar result, where consumption is influenced by the number of bathrooms, plumbing devices, and number of bedrooms. Cruz et al, [10] also observed that the increase in the number of bathrooms increased the water consumption of Mexican households. The age of the property was related to monthly water consumption (r = 0.168, p < 0.10), i.e., the older the house is, the higher the monthly water consumption is.…”

Section: Constructive Featuresmentioning

confidence: 93%

“…Monthly water consumption increases based on an increase in the number of women in the residence (r = 0.204, p < 0.05), but per capita water consumption decreases (r = −0.208, p < 0.05), as illustrated in Figure 6. In Mexico, Cruz et al, [10] also identified that consumption increased based on the number of female inhabitants. The per capita consumption is significant related to the educational level (r=−0.226, p<0.05) as shown in Figure 8, indicating that the higher the educational level, the lower the household per capita water consumption is.…”

Section: Socioeconomic and Demographic Characteristicsmentioning

confidence: 98%

“…Consequently, a logarithmic transformation was employed, the same criterion adopted by Cruz et. al [10]. Then, the normality hypothesis was accepted since the probability value resulting from the test were 0.631 for LNMonthlyConsumption and 0.116 for LNPerCapitaConsumption.…”

Section: Explanatory Data and Correlation Analysismentioning

confidence: 99%

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Identifying the Drivers of Water Consumption in Single-Family Households in Joinville, Southern Brazil

Garcia

Salfer

Kalbusch

et al. 2019

Water

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This study aims to identify the factors that may influence water consumption in single-family households in the city of Joinville, Southern Brazil. Through questionnaires, data were collected from 108 households in several neighborhoods of the city. The questionnaires contained open-ended and closed-ended questions involving the surrounding infrastructure, socio-economic and demographic characteristics, constructive characteristics, installed plumbing fixtures, and water-use habits, totaling 57 variables. The independent variables were correlated to monthly water consumption (m3/month/household) and per capita consumption (liters/person/day) of each household. The statistically significant variables that affected households water consumption were related to demographic characteristics such as number of residents and educational level, construction features (i.e., number of bathrooms, building age, and built area), the presence of water-efficient appliances and water conservation habits. The results obtained can contribute to the development of new studies on water consumption and sustainable policies and awareness on the importance of water conservation.

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Section: Correlation Between Variablessupporting

confidence: 72%

“…Table 2 shows the statistically significant variables at 5% and 10% levels (p-value < 0.05 and p-value < 0.10), as well as their correlation coefficient. As in the study by Cruz et al, [10], although most of the coefficients presented low values, with absolute values lower Per capita consumption ranged from 50.64 liters/person/day to 389.54 liters/person/day, with an average of 144.91 liters/person/day. Figure 3b shows that about 90% of the single-family households consumed less than 225 liters/person/day.…”

Section: Correlation Between Variablessupporting

confidence: 59%

Section: Constructive Featuresmentioning

confidence: 93%

Section: Socioeconomic and Demographic Characteristicsmentioning

confidence: 98%

Section: Explanatory Data and Correlation Analysismentioning

confidence: 99%

See 3 more Smart Citations

Identifying the Drivers of Water Consumption in Single-Family Households in Joinville, Southern Brazil

Garcia

Salfer

Kalbusch

et al. 2019

Water

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Promotion of residential water conservation measures in South Africa: the role of water-saving equipment

Thiam

Dinar

Ntuli

2020

Environ Econ Policy Stud

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In many urban settings around the world the severity of water scarcity has induced changes in household behavior, leading to reduction in the volume of water demanded. One of the most widely used strategies is the adoption of water-saving equipment that collects, stores and eventually treats wastewater from various sources within the household. This paper investigates the factors that drive adoption of water-saving equipment in Cape Town, South Africa, following the catastrophic "Day Zero" water crisis in 2018. First, the paper develops a disaggregated technology diffusion model. Second, we make use of choice experiments to determine the attribute levels and socioeconomic characteristics that influence adoption of watersaving equipment in urban communities in South Africa. Data collected from a sample of 465 representative households in Cape Town are used in a choice modelling framework. Latent class analysis (LCA) is compared with both multinomial logit and conditional logit models to estimate marginal willingness to pay (MWTP) for adoption of water-saving equipment. The LCA identified three household classes with distinct preferences, suggesting divergence in adoption of water-saving equipment.

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