Abstract

It is commonly recognized in the field of water demand management that social comparison of water usage among people with a similar background is an effective measure to promote water efficiency. Many studies have used “neighborhood” to represent group similarity, but it is unclear how much geographic proximity is appropriate for defining a neighborhood. Therefore, the aim of this study is to clarify what neighborhood range is the most effective for promoting residential water use efficiency. We conducted a field experiment on social comparison feedback using two neighborhood ranges: narrow (condominium complex level) and wide (prefecture level), and analyzed changes in the water usage of 114 households residing in a condominium in the Tokyo metropolitan area, based on daily household water consumption data and an emoticon-based feedback system. As a result of classification of water consumption trend patterns using the K-means clustering method, it was suggested that those with low-consumption reduced their consumption as a result of the intervention, irrespective of neighborhood range. Despite the limited amount of data, the results provide insights into designing and implementing more effective feedback methods outside the US and European regions, especially in the context of residential water efficiency.

Highlights

  • Water management comprises both supply- and demand-side management strategies, which focus on water resource expansion and demand reduction, respectively

  • Because this study aimed to investigate the patterns of trends in water usage thoroughly, we adopted four clusters to consider more detailed patterns

  • In terms of trends, we named the four clusters “large reduction,” “small reduction,” “no shift,” and “increase.” The top panel of Table 1 shows the proportion of households classified into each cluster

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Summary

Introduction

Water management comprises both supply- and demand-side management strategies, which focus on water resource expansion and demand reduction, respectively. For water resource conservation and future water security, water demand management is a essential element (Brooks, 2006; Fielding et al, 2013; Koh, 2020). With the advent of smart water-meter technology, several ICT solutions have already been deployed to optimize operations in supply-side management. Demand-side management has lagged behind (Makropoulos et al, 2014), but it has recently begun to gain popularity. Demand-side management has been traditionally thought of as too inconvenient for consumers (Kanta and Berglund, 2015). The detailed and customized information about water usage provided by smart water-metering technology presents a new opportunity for demand-side management through consumer engagement, based on efficiency measures (Boyle et al, 2013; Liu et al, 2013). Water utilities have expressed significant interest in utilizing data from smart water metering, actual implementation

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