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date: 05 March 2021

Behavioral Interventions as Policy Instruments to Manage Household Water Usefree

  • Leong ChingLeong ChingInstitute of Water Policy, National University of Singapore
  •  and Swee Kiat TaySwee Kiat TayUniversity of Wisconsin-Madison School of Journalism & Mass Communication

Summary

Water planners and policy analysts need to pay closer attention to the behavioral aspects of water use, including the use of nonprice measures such as norms, public communications, and intrinsic motivations. Empirical research has shown that people are motivated by normative as well as economic incentives when it comes to water. In fact, this research finds that after exposure to feedback about water use, adding an economic incentive (rebate) for reducing water use holds no additional power. In other cases, nonprice measures can be a way to increase the salience, and subsequently, effectiveness of any adopted pricing mechanisms. We review these empirical findings and locate them within more general literature on normative incentives for behavioral change. Given increasing water scarcity and decreasing water security in cities, policy planners need to make more room for normative incentives when designing rules for proenvironmental behavior.

Introduction

Measuring the direct use of water by households on a global scale is complex. In 2002, the Organisation for Economic Co-operation and Development (OECD) estimated that household use of water represents 8% of all total water consumption within its member countries while Ivanova et al. (2015) estimate the direct use of water by households globally to be only about 4%. These proportions may seem small compared to other uses of water (60% for agriculture and livestock, 15% for the service sector), but in absolute terms, they account for a large amount of water. In 2007, households directly consumed an estimated 69.3 trillion liters of water (Ivanova et al., 2015).

Nation-level estimates of household use also show the magnitude of household consumption. In Australia, for example, households are the second largest user of water (Chen et al., 2012), while in largely urbanized states such as Singapore, they account for as much as half (Luan, 2010).

In cities, the proportion of water use by households has increased significantly, a trend that will only continue as global urbanization rates continue to rise. Willis, Stewart, Giurco, Talebpour, and Mousavinejad (2013) note that 66% of water used in the city of Gold Coast, Australia is used directly by households. Among Korean cities, households consume the equivalent of 65.6% of all urban water (Lee, Park, & Jeong, 2012). Similarly, in U.S. cities, household use accounts for about 60% of urban water use, with average per capita use of water in the United States at about 314 liters per day (Dieter & Maupin, 2017).

The rising demand for water has become a challenge especially for Asian and African cities, which have the highest urban population growth rates in the world (Webster, 2013). There is also evidence that better supply drives up demand. For example, in India overall demand for water increases as urban water supplies become more reliable and allow residents continuous and on-demand use of water (Kumpel, Woelfle-Erskine, Ray, & Nelson, 2017); with at least 300 million urban inhabitants in low- and middle-income countries having only intermittent water supply (Kumpel & Nelson, 2016), developing cities are primed for a spike in demand somewhat paradoxically, as infrastructure improves.

Given the scale of global household water use, managing this demand is not deeply important, but it will become more critical in the future as climatic and governance issues continue to stress existing water supplies. Gosling and Arnell (2016) calculate that up to 32% of the world’s population already lives within watersheds facing water scarcity, a proportion expected to grow to over 50% by 2050. Recent severe droughts in populous American states have forced temporary curtailments of water consumption (Dieter & Maupin, 2017). Solander, Reager, Wada, Famiglietti, and Middleton (2017) note that water consumption in the Lower Colorado River Basin already periodically exceeds supply. Increased salination of fresh water in coastal regions—as groundwater sources are depleted—accelerates the threats to existing water supplies (Benini, Antonellini, Laghi, & Mollema, 2016; Fuller & Harhay, 2010). In 2017, a severe water crisis struck Cape Town, South Africa, the result of both poor supply management and sustained household consumption in the face of drought (Muller, 2017).

As household demand for water continues to outstrip replenishment in many parts of the world, questions arise with regard to the sustainability of the global water system (Hughes & Mullin, 2018). By 2025, water scarcity is expected to affect more than 1.8 billion people in both the wealthiest and poorest nations (United Nations Development Programme, 2014).

Still, it is by no means clear that the rise in demand need be inexorable. For one, research by the International Water Association (2016) shows huge variation in per capita domestic water use across 170 global cities, from below 20 liters per day in some Ugandan cities to as high as 538 liters per day in Denver, Colorado. A survey of the literature by Rathnayaka et al. (2014) also points to a wide variation in household water use within any given city. These variations suggest several things—that household consumption is not at equitable levels but is also at varying degrees of optimality. It is because of this latter concern that we make our case for better water demand management strategies. A second but related issue is that of the role of technology. The potable reuse of wastewater will release some of the stresses on water supply, as we argue in the concluding section.

Does Money Work? Pricing as Strategy

For the past few decades, principle 4 of the Dublin Statement (1992) has served as the mantra of the water sector—water must be considered an economic good if efforts to ensure water remains available in the long term are to be successful (Cullet, 2018, p. 339). Household water use is responsive to price signals (Dalhuisen, Florax, de Groot, & Nijkamp, 2003; Renwick & Green, 2000), though a limited understanding remains of how and why consumers respond to such price signals (Garrone, Grilli, & Marzano, 2019). It also remains unclear how community-level as well as individual-level characteristics can affect consumers’ sensitivity to price signals and, consequently, the degree of efficiency and impact of water pricing strategies (Dieu-Hang, Grafton, Martínez-Espiñeira, & Garcia-Valiñas, 2017). Nevertheless, water pricing strategies have been the first and most natural approaches adopted to achieve water demand management goals (Olmstead, 2010).

A meta-analysis study (Sebri, 2014) examining factors influencing residential households’ sensitivity to water pricing found that price elasticities vary greatly across geographic location and development level of countries, meaning price-setting decisions have to take these location and context-specific factors into consideration. The same study also found households to be more sensitive to price in the summer (vs. the winter) and when water is used for outdoor purposes (as compared to indoor).

Another meta-analysis study (Garrone et al., 2019) found water scarcity (as measured at a basin level using the Water Stress Indicator (WSI) of the United Nations Environment Programme (Smakhtin, Revenga, & Döll, 2004)) to be negatively correlated with price elasticity (i.e., the greater the water shortage, the less a household is likely to be responsive to prices), although this effect is attenuated when the community exhibits high levels of concern for the environment. These findings reinforce the notion that contextual and community-level factors can impact water consumers’ responses to water price signals.

Research has also found individual-level attributes, such as attitudes, beliefs, habits, or routines and personal capabilities, to be important determinants of water consumption behaviors (Fielding, Russell, Spinks, & Mankad, 2012; Russell & Fielding, 2010). Increased income is associated with higher water consumption by households in both developed (Harlan, Yabiku, Larsen, & Brazel, 2009; Kenney, Goemans, Klein, Lowrey, & Reidy, 2008; Willis et al., 2013) and developing countries (Hussien, Memon, & Savic, 2016; Webster, 2013). In Korea, Lee et al. (2012) noted that since the 1980s, an increased adoption of a “Westernized” lifestyle has resulted in higher household water consumption through evolving norms in showering, bathing, and laundry use; a similar trend may arise globally as average incomes continue to rise.

Taken together, the existing research points to the need for policy instruments in addition to pricing and tariff reform in order to effectively reduce household water use in locations where water conservation is an important policy goal (see Peterson & Hendricks, 2018, for an overview). We propose that water management at the household level needs to be considered in situ, together with the environmental context, culture, and individuals involved. We further propose that behavioral interventions, a more recent trend in water studies, can serve as a useful guiding lens for policymakers to make better decisions on water-related policy mechanisms as a means of shifting water consumption behaviors or, more commonly, as a complementary strategy by making pricing more salient to consumers.

The Price Paradox: Tackling Water Scarcity and Equity

Given the evidence on increasing water scarcity, there has been global attention on water conservation goals (Garrone et al., 2019); at the same time, there is a lack of basic water for millions of people around the world (Cullet, 2018). Raising prices and water tariffs is a good way to ensure cost recovery, curb demand, and address water scarcity, yet raising prices is often politically fraught with the mistaken idea that higher prices reduce equity in water allocation.

The argument that keeping tariffs low to allow the “poor” to enjoy access to water is not borne out (Rogers, de Silva, & Bhatia, 2002). First the “poorest” in countries where the tariffs are meant to help might not even be connected to the water supply system. For instance, in Bangalore, the state-owned Bangalore Water Supply and Sewerage Board (BWSSB) services only approximately 10–30% of households in parts of the city (Ranganathan, 2018). In these parts, most residents rely almost entirely on groundwater sourced from borewells or water tankers, known colloquially as water mafias, to supplement their water supply. The poor are often left to purchase higher-priced water from vendors such as these water mafias. In Onitsha, Nigeria, the poor spend almost one-fifth of their income on water (Whittington, Lauria, & Mu, 1991) as compared to 1% for households in OECD countries (Organisation for Economic Co-operation and Development, 1999).

Second, the structure of provision of subsidies is flawed. A study by Fuente et al. (2016) on the distributional incidence of subsidies in Nairobi, Kenya found that high-income residential and nonresidential customers receive a disproportionate share of subsidies, and that subsidies are often poorly targeted even in households with private connections. So, while subsidies to the poor generally improve equity and access, when delivered by subsidized water prices from the first drop, it is regressive and leads to the rich being subsidized as well as the poor—and since the rich tend to use more water, they are subsidized more than the poor.

Hence, in some countries, increasing tariffs is a better approach to ensure that the poor get the clean water they need as it would encourage conservation (among the richer households which are connected to the water system) and ensure increased revenue for the utilities to improve water service coverage for the poor. In fact, the poor might even be willing to pay the “higher tariffs” (which might still be lower than the rates they are already paying) in exchange for timely, reliable water, such as for the agricultural farmers in Haryana, India (Rogers, Bhatia, & Huber, 1998).

In most locations, achieving the appropriate balance between addressing water scarcity and water equity will require policy instruments in addition to pricing and tariff reform. A broader consideration of multiple factors through a behavioral lens likely will be a more effective approach, such as examining the culture of water use through water mafias and residents’ attitudes toward such alternatives.

Theory Underpinning Behavioral Interventions

For demand-side interventions to be effective, understanding water use behavior can be as important, if not more, than technology or infrastructure for water demand strategies (Baumann, Boland, & Sims, 1984; Brooks, 2006). Theories predicting behavior and behavioral change abound, but one of the most widely cited is the theory of planned behavior (TPB) (Ajzen, 1985, 1991). At its core, the TPB proposes that any given behavior is most likely to occur when there is a strong intention to perform the behavior. This intention is in turn predicted by a trio of factors: an individual’s attitudes toward the behavior, social norms, and perception of the degree of control they have to enact the behavior (Ajzen, 1991).

Although frequently used to study health-related behaviors (Albarracín, Johnson, Fishbein, & Muellerleile, 2001; Webb, Joseph, Yardley, & Michie, 2010) and physical activity (Hagger, Chatzisarantis, & Biddle, 2002), the TPB has also been used to understand decisions to engage in a broad range of other behaviors including water conservation (Clark & Finley, 2007; Harland, Staats, & Wilke, 1999; Kantola, Syme, & Nesdale, 1983; Lam, 1999, 2006; Russell & Fielding, 2010).The model, however, has been argued to be inadequate in itself. For one, the TPB misses potentially important variables such as habits or routines, personal capabilities, personal dispositions, contextual forces, associative learning, and emotional processing (Addo, Thoms, & Parsons, 2018; Michie, van Stralen, & West, 2011; Russell & Fielding, 2010; Stern, 2000). While some of this feedback has been addressed (Ajzen, 2011), Ajzen concedes that some factors, such as past behavior as a proxy of habit strength, still needs to be explored further.

Michie et al. (2011) overcome some of the limitations of the TPB with a conceptual framework to examine effective behavior-change interventions for household water conservation (Addo et al., 2018; Michie et al., 2011). The Behavior Change Wheel (BCW) is a model of behavior which links sources of behaviors, intervention types, and policy categories (Michie et al., 2011). Three factors were identified as being necessary and sufficient conditions for performance of a specified volitional behavior: Capability, an individual’s psychological and physical capacity to enact the behavior concerned; Opportunity, factors that lie outside the individual—both external physical and social environment—that make the behavior possible; and, finally, Motivation, which refers to all the brain processes that energize and direct behavior (the COM-B (COM-Behavior) system) (Addo et al., 2018; Michie et al., 2011).

In the field of communications, Fishbein and Cappella (2006) also attempted to improve the TPB with an integrative model, which posits that any given behavior is most likely to occur if an individual has a strong intention to perform the behavior (as stipulated by the TPB), as well as having the necessary skills and abilities required to perform the behavior, and not having to face any environmental or other constraints preventing the enactment of that behavior (p. S2). Though devised years before the COM-B model (Michie et al., 2011), this integrative model overlaps conceptually with the COM-B model to a large extent. Having the required skills and abilities resemble the Capability dimension of the COM-B model, while environmental factors resemble the Opportunity dimension.

Finally, behavioral intentions, which form the backbone of the original TPB, resemble the Motivation dimension. In this light, the integrative model not only combines the key elements of the TPB and COM-B models but adds further value to the two models by integrating other background influences (such as past behavior/habit, mass media influence, and individual personal dispositions), which may serve as antecedents to behavioral intentions. Figure 1 shows how the two models overlap and illuminate different aspects of behavioral change.

Figure 1. An integrative model proposed by Fishbein and Cappella (2006, p. S2), with names in red from Michie et al. (2011).

Reprinted by permission of Oxford University Press.

We map onto this model the many behavioral studies that have come out since its introduction in 2006 and assess the empirical effectiveness and theoretical contributions of this framework. More importantly, we argue that among the different interventions that rely on approaches aligned with Capability, Opportunity, and Motivation, driving behavior change by modifying the individual’s intention/motivation had shown more consistent results and better efficacy. That is, normative incentives, whether we define them in the wide sense of “social norms” or a stricter sense of morally justified courses of actions, seem to work better.

We further examine the role of conformity in shaping norms, the precursor of motivation in the integrative model. Conformity refers to the act of changing one’s behavior to match the responses of others (Cialdini & Goldstein, 2004). Encouraging conformity by shifting perceptions of social norms has been found to be an effective method for behavioral change, including environmental conservation in hotels (Goldstein, Cialdini, & Griskevicius, 2008) and household energy conservation (Schultz, Nolan, Cialdini, Goldstein, & Griskevicius, 2007), and can also be usefully applied to water conservation efforts.

We also test this framework against recent findings to see if it requires any modification. We begin by examining research that had tapped on the Capability and Opportunity dimensions, before shifting our attention to Motivation.

Economic and Rational Incentives, I: Capabilities

Capability is defined as an individual’s innate ability to engage in the behavior desired and is broken further into physical and psychological capabilities (Michie et al., 2011). Physical capability refers to an individual’s physical skills, strength, or stamina to enact or change a behavior that reduces water consumption. Psychological capability refers to an individual’s knowledge and psychological skills to engage in the necessary mental processes of comprehension and reasoning (Addo et al., 2018).

While interventions tailored toward capability issues tend to focus on education and training to impart knowledge and skills to the individuals (Michie et al., 2011), the aim of the information provided is directed toward enabling an individual to perform water consumption–related actions (i.e., more technical information) rather than changing attitudes or perceptions. Examples of interventions include training to self-repair minor water leakages (Addo et al., 2018), using water-efficient devices properly (Kurz, Donaghue, & Walker, 2005), reading water meters correctly, or interpreting water billings accurately.

Interventions aimed at addressing the capability of individuals often rely on the idea of a “knowledge deficit” (Schultz, 2002), and that attitudes and behaviors can be encouraged by remedying these knowledge deficits. While effective in specific cases, there is potentially a ceiling effect for capability interventions in terms of its impact on water demand management. Seyranian, Sinatra, and Polikoff (2015), in a study of an affluent neighborhood in Los Angeles County, found that interventions that distributed handouts with only water-saving tips (to address the knowledge deficit) resulted in the contradictory results of higher, not lower, water consumption in both the long and short term for high water-use consumers.

Conventional wisdom might suggest that interventions that provide consumers with up-to-date information on the marginal price of water (such Smart Water Readers, Smart Showers, or weekly notifications), as well as the amounts they have consumed for the billing period, would encourage water conservation behavior by improving psychological capability. Research on water usage in Swiss households showed that the installation of Smart Water Readers providing real-time feedback of water consumption increases the salience of one’s desire for water conservation, thus leading to as much as a 22% decrease in consumption (Tiefenbeck et al., 2016)

However, there is also empirical research that has shown the opposite effect. Research conducted on nonvolunteers in Tokyo demonstrated that provision of information on actual and mean water consumption to consumers had no effect on water conservation (Otaki, Ueda, & Sakura, 2017). Other studies have even shown that the provision of up-to-date information leads to an increase in consumption of water. Data collected over two years in Durham, North Carolina (United States), where billings for water were changed from a bimonthly to a monthly basis, demonstrated that water consumption actually increased as a consequence of more frequent billing (Wichman, 2017).

This is likely due to the bounded rationality of consumers—Wichman posits that consumers tend to misperceive changes in prices and quantities consumed that are not salient—thus, a more frequent billing schedule increases the salience of prices, resulting in consumers consuming closer to their welfare-optimum quantity. Carter and Milon (2005) posited another theory based on data collected from electricity usage in Florida that demonstrated a similar trend: consumers simply tend to overestimate the price of services. Thus, with more consistent and current information, consumers make more economically rational decisions, leading to an increase in water consumption. That is, given the relatively low prices of environmental resources such as water, people provided with information about these low prices might tend to consume more rather than less.

This correlation is even starker when information is implemented in conjunction with an increasing block tariff structure. Starting in the 1980s, many utilities have shifted from pricing strategies in which the per-unit price declines or stays constant at high levels of use to an increasing block rate (IBT) design, in which the price of water increases now as volumetric consumption rises. One common rationale for an IBT tariff structure is to provide an incentive to conserve water use (and to ensure that poor households can access a limited amount of water—the lifeline block—at an affordable price).

Yet, the implementation of Smart Water Readers in Aurora, Colorado was found to lead to a 16% increase in water consumption among the group with said readers when under a three-tiered block tariff (Kenney et al., 2008). This was likely because prior to the installation of Smart Water Reader technology, consumers used less water as they were fearful of entering the third block of pricing—however, with information to track their consumption of water, they were able to budget consumption to make full use of the lower pricing blocks, leading to more extensive use of Blocks 1 and 2 but less consumption in Block 3.

Normative Incentives: Money or Morals?

Opportunity, the next source of behavioral change, is defined as the social and physical factors in the environment that lie outside the individuals who prompt or enable their behavior (Michie et al., 2011). In contrast to capability issues, which focus on factors innate to the individual, opportunity involves factors external to the individual and is often outside the individual’s locus of control.

As with capability factors, opportunity factors can be classified under two subtypes: social and physical. Social opportunities are factors afforded by the social and cultural environments that individuals are situated in, which then dictate the way they think about things (Addo et al., 2018; Michie et al., 2011). Factors include social cues and cultural norms, as well as social trust (i.e., trusting that other individuals and institutions are also minimizing water consumption) (Graymore & Wallis, 2010; Jorgensen, Graymore, & O’Toole, 2009). One example is a study by De Martino, Brick, and Visser (2017), which finds that external messages have an effect on water saving across the various treatments, resulting in 0.6–1.3% average reduction in water usage (see details in Table 1). Social recognition and public good are the most effective motivators for water conservation. Prima facie, therefore, there is reason to think that one modification of the integrative model requires an arrow from “norms” to “attitude” in Figure 1.

Table 1. De Martino et al. (2017) Found That Behavioral Messages Across Different Treatments Result in Reduced Water Usage

De Martino et al. (2017)

Field experiment of about 400,000 free-standing houses with credit meter in Cape Town, South Africa from November 2015 to April 2016

Eight different treatments via messages sent through inserts with monthly utility bills: tips (for reducing usage), tariff graph, financial gain, financial loss, social norm message, intrinsic motivation, social recognition, & public good

Behavioral messages have significant effect on water saving across the various treatments (0.6%–1.3% average reduction in water usage); social recognition and public good are the most effective motivators for water conservation Norms affect attitude (arrow)

While social opportunity might feel similar to the norms that drive behavioral intentions under the TPB and the integrative model, the difference here is that social opportunity refers to the actual environment, whereas under the integrative model, norms refer to perceived norms by the individual in question. Correspondingly, interventions differ: the former requires a transformation in the social and cultural environment that the individual is immersed in, whereas the latter entails influencing the normative beliefs that individuals hold or their levels of motivation to comply to such norms.

Physical opportunity, the other subtype of opportunity issues afforded by the environment, can include time, resources, and location but also economic enablers of water demand management (e.g., being able to conserve water because of financial incentives or rebates to promote water-conservation measures) (Addo et al., 2018; Michie et al., 2011). Prior to the integration of behavioral theory into the study of water demand management, economists and policymakers had focused on relative prices as the primary external force in influencing consumption behavior. This is where economic prescriptions would call for the setting of prices which reflect the marginal social cost of consumption, in order to induce households to choose the socially optimal level of consumption through the manipulation of the external physical environment (physical opportunity).

Neoclassical economic theory assumes that (a) people are fully rational, (b) they engage in purely self-interested behavior to extract maximum value, and (c) they are free to act independently on the basis of full and relevant information (Weintraub, 2007). However, existing research suggests that households may not really be aware of the average and marginal prices they pay for water or even the quantities they use (Ito, Ida, & Tanaka, 2015; Jessoe & Rapson, 2014; Kahn & Wolak, 2013). Optimization errors on the part of the consumer could thus lead to uncertain outcomes with regard to water consumption levels (Borenstein, 2009).

It is commonly understood that consumption of water is price inelastic, as water is a necessity. Therefore, uniform increases in price, like through a simple uniform tariff, would result in a less-than-proportionate decrease in quantity demanded (Olmstead, Hanemann, & Stavins, 2007). Kenney et al. (2008) arrived at a point estimate of the price elasticity of demand (PED) of -0.60 using household data from the entire city of 309,000 residents in Aurora, Colorado. The same analysis also found, unsurprisingly, that price elasticities vary considerably among users with different water usage profiles—high water users were generally more responsive to price than low water users.

A recent intriguing experiment has given further pause to the use of price as the sole motivation for water conservation. In a field experiment involving 1,000 households in Singapore, researchers found that normative incentives (feedback and campaign messages) are as powerful as economic incentives (rebates) when it comes to motivating water-conserving behavior. The researchers compared households given feedback alone with another group given feedback as well as actual cash rebates amounting to about half their monthly bills. They found that there is no difference in the amount of water saved. Both groups saved between 4.9 to 10 liters per person per day (3–6% of mean baseline water use) (Goette, Leong, & Qian, 2019).

This demonstration of the force of normative incentives as well as earlier empirical work shows us that there is a clear link between external environment (including that of social norms) and attitude. This leads us to think that a further modification may be required of the integrative model as in Table 2.

Table 2. The Force of Normative Incentives Suggest a Link From the External Environment or Context to Consumer Attitudes

Author (Year)

Methods

Variables/Unit of analysis

Findings

Ito et al. (2015)

Field experiment and surveys on households in the Keihanna area of Kyoto, Japan

High-frequency data on household electricity usage using “smart meters”; two forms of treatment: “moral suasion” (intrinsic motivation) and “economic incentive” (extrinsic motivation)

Moral suasion led to significant short-run effects, but diminished quickly with repeated interventions; Economic incentives led to larger and more persistent effects which induced habit formation Environment or context can affect attitude (arrow)

Normative Incentives and Motivation: When External Interventions Fail

When changing individual capabilities and external interventions fail to lead to desired reductions in water consumption, the remaining approach is driving behavioral change by influencing motivations and behavioral intentions. The “Motivation” dimension is defined as all brain processes that energize and direct behavior, whether conscious (analytical decision-making) or subconscious (habitual action, emotional responding) (Michie et al., 2011). Motivation broadly involves evaluation mechanisms of water consumption behavior, general environmental attitudes, norms (personal and social), values, broad beliefs about the natural environment, water-peculiar beliefs, and conventional practices pertaining to water use (Addo et al., 2018). As with the other dimensions of Capability and Opportunity, Motivation is also characterized by two subtypes: reflective and automatic motivation.

Reflective motivation involves intentions and evaluations (beliefs about what is good and bad, conscious intentions, decisions, and plans) of the behavior (e.g., a householder intending to take shorter showers) (Addo et al., 2018). This more explicit rendition of normative incentives aligns closely with the TPB’s definition of behavioral intentions, which are indications of a person’s readiness to perform a behavior (Ajzen, 2011).

Automatic motivation involves emotional reactions, desires (wants/needs), inhibitions, and reflex responses which activate or inhibit behavior (e.g., feeling good by thinking about conserving water for the next generation) (Addo et al., 2018). Additionally, Norgaard (2006) argues that emotions not only operate at the individual level but work through some form of emotional contagion. In environmental behavior, there is a form of “collective avoiding” which acts as a “social organization of denial” relating to climate change.

On the surface, this appears to be a shortfall of the TPB model, which emphasizes the controlled aspects of human information processing and decision-making and is concerned primarily with goal-directed behaviors and steered by conscious self-regulatory processes (reflective motivation). However, Ajzen (2011) argues that there is no assumption in the TPB that behavioral, normative, and control beliefs can only be formed in a rational, unbiased fashion or that they accurately represent reality—behavioral intentions are just as likely to be influenced by automatic motivations as they are by reflective motivations. Attitudes, subjective norms, and perceptions of control as well as intentions in relation to these kinds of automatically motivated behaviors are assumed to guide behavior implicitly without cognitive effort and often below conscious awareness (Ajzen, 2011; Ajzen & Fishbein, 2000).

In social sciences (psychology, communication, etc.) research, at least two models have attempted to articulate this difference between the rational reflective motivation and the emotional automatic motivation. The first, the Elaboration Likelihood Model developed by Petty and Cacioppo (1986) suggests that there are two routes to persuasion: one via a careful and rational assessment of arguments (central route), and the other based on some cognitive, affective, or behavioral cue present in the persuasion context that doesn’t require deep cognitive processing (peripheral route). The second, the Heuristic-Systematic Model developed by Chaiken (1987), suggests that people process information in two ways: superficially (heuristically) or effortfully (systematically).

Such models help to explain why behavior can sometimes be driven by nonrational decisions. For example, research in Tokyo has demonstrated that live feedback on consumers’ water consumption provided through visual and emotional stimuli like emoticons reduces water consumption (Otaki et al., 2017). Perhaps shifting information away from a model with concrete numbers quantifying consumption to one that creates emotional salience in the consumer (by forgoing the assumption of rational decision-making by people) will exhibit a stronger effect on household water use at times.

Two Forms of Normative Incentives: Social and Moral

The integrative model suggests that there are three primary determinants of behavioral intentions: attitude toward performing the behavior, perceived norms concerning performance of the behavior, and self-efficacy with respect to performing the behavior (Fishbein & Cappella, 2006, p. S2).

We have seen in previous sections that there are two ways of thinking about normative behaviors—hence it is worth spelling out explicitly how these locate themselves within our modified integrative model. The first type of normative incentive (NI (I)) has moral content and appeals to our desire to “do the thing.” This is the type of incentive, for example, that we see in research by Tiefenbeck et al. (2016) which showed that the effect of real-time feedback on water conservation in consumers who identified themselves as proenvironment was greater in magnitude than in those who did not.

NI (I) is also in operation when we see that exposure to messages that portrayed water conservation as performing an act beneficial and expected to the public was an effective motivator of water conservation, typically outperforming provision of procedural information like actual water consumption. This conservation effect as a consequence of normative messaging was found to be effective in Cape Town, where informational inserts were provided along with the utilities billing for the month (De Martino et al., 2017), with the provision of labels (to be placed on appliances that used water) to households in Perth, Western Australia (Kurz et al., 2005), as well as the provision of bathroom postcards to households in Queensland, Australia, detailing how to save water and how a majority of other households were saving water (Fielding et al., 2013).

Ferraro and Price (2013) found that households exposed to an appeal to prosocial preferences augmented with technical advice led to a substantially larger reduction in water use (10.0% for weak social norms and 12.0% for strong social norms) than households exposed to solely technical advice (8.4%). From a policy perspective, such results suggest that conservation informational initiatives should focus on explaining why customers should reduce water consumption rather than outlining how best to reduce water use (Ferraro & Price, 2013). That is, incentives with an explicitly moral content tend to work better than mere information.

A second type of normative incentive relates to force of numbers, quite independent of the moral content (NI (II)). Conformity is one example. A 2015 study by Francis et al. looked at the factors influencing acceptance and sustainability of an ongoing water quality intervention that tests the effectiveness of a high-throughput membrane filter for providing clean drinking water in southern India. The study highlighted the importance of conformity with male members of households—a lack of support from male members of households impeded the sustainability of the intervention.

Beyond the household, an earlier study by Askew and McGuirk (2004) developed an understanding of sociocultural factors influencing domestic water use within newly established prestige housing estate close to Lake Macquarie, south of Newcastle, NSW in Australia. Among the authors’ arguments is that strategies of social distinction and conformity influence patterns of suburban water use. Certain social practices necessitated the use of water to maintain a household’s respectability (e.g., a healthy lawn, a garden, and clean paths). Therefore, the authors found that the greater potential for reducing water demand seem to lie in the case of social conformity. For instance, the use of a rainwater tank by some houses revealing a degree of concern for questions of style, were outweighed by a stronger inclination toward social responsibility (Askew & McGuirk, 2004).

Social acceptance is especially important in the implementation of interventions that may carry some social stigma. For example, the use of reclaimed water has been found to trigger the “Yuck Factor”—a feeling of disgust toward something generally perceived as harmful. In a nationally representative survey conducted in Singapore conducted by Timm and Deal (2018), it was found that the largest driver of acceptance of NEWater was the attitude toward NEWater. Using a simple choice experiment, Leong and Lebel (2020) find that conformity is a strong motivation to increase acceptance of recycled drinking water (RDW). Students provided the information that a community with high acceptance of RDW was more likely to choose RDW over mineral water, given the same prices.

It has also been found that there is a fundamental difference in the efficacy of norm-based messages across low- and high-use households. From a policy perspective, heterogeneity in the effectiveness of norm-based appeals across all households is notable, as high-use households tend to be less price sensitive than others (Mansur & Olmstead, 2007). Therefore, nonpecuniary strategies provide a useful and viable complement to pecuniary measures, where they are most effective among the group that is least sensitive to price changes (high-use households).

Apart from the intended change in behavior, normative messaging may also provide positive spillover effects in different but related fields of consumption. Carlsson, Torres, and Villegas (2016) explored the impact of a social information campaign targeting water conservation in households on the use of residential electricity. They found that the social information campaign within monthly bills reduced water use for households with inefficient and efficient water consumption in the preintervention period. However, positive spillover effects were only observed for the latter group, where after 11 months, it consumed 9% less electricity than the control group on average.

Whether we deploy NI (I) or (II), however, we should note that the effectiveness of such nonpecuniary informational strategies will wane over time (Curtis & Price, 2009; Ferraro, Miranda, & Price, 2011; Ferraro & Price, 2013; Fielding et al., 2013; Gneezy & List, 2006; Landry, Lange, List, Price, & Rupp, 2010) (see Appendix 1 for a review of research methods of water use). Indeed, Allcott and Rogers (2014) find that the impact of social feedback on electricity consumption in households vanishes a few months after treatment exposure if the treatment is not repeated.

Appendix 1. Review of Research Methods of Water Use

Author (Year)

Methods

Variables/Unit of analysis

Findings

Jessoe and Rapson (2014)

Field experiment in Bridgeport and New Haven areas of Connecticut

High-frequency data on household electricity usage using advanced meters; two forms of treatment: price-only, and price+IHD (in-home display) which showed real-time information on electricity usage

Informed households (through IHD) are more responsive to temporary price increases

Kahn and Wolak (2013)

Field experiment with two California electric utilities

Treatment takes form of educational program on IBT pricing structure

Education led to reduction in daily average electricity consumption; households near high-end of price block reduced consumption whereas households near low-end of price block increased consumption

Olmstead et al. (2007)

Data from 1,082 households in 11 urban areas in the United States and Canada, served by 16 public water utilities

Structural discrete/continuous choice (DCC) model to test the effect of Increasing Block Prices (IBP) and Uniform Price (UP)

Greater price elasticity under IBPs

Kenney et al. (2008)

Case study of Aurora, Colorado during drought period (2000–2005)

Monthly billing records from Aurora Water; examines price, pricing structures, and consumption

High-volume households are more responsive to price interventions; households consume less water under IBR pricing than Uniform Rate pricing; ownership of Water Smart Readers led to higher demand for water

Borenstein (2009)

Household level billing data from Southern California Edison from 1999 to 2006

Price elasticity of demand based on changes in Increasing Block Price schedule

Most consumers are responding to expected marginal price or less precise information about what marginal price they will face

Ma et al. (2014)

1,104 households in Beijing

Effects of water price information on consumption behavior under IBTs

Middle-income group treats IBT as the same as uniform pricing; highest income group is insensitive to price changes; and lowest income groups respond most to marginal price under IBT

Otaki et al. (2017)

246 participants (one from each household) in the Tokyo commuting area

Treatment includes three types of water consumption feedback: actual and mean (Tokyo) consumption, dummy consumption rank (among 100 participating households), and emoticons with written information

Water use in high consumers decreased when they received emoticons, whereas that in low consumers decreased when they saw that their use had decreased

Wichman (2017)

Residential billing records for Durham, North Carolina

Effect of billing frequency on consumption behavior

Customers increase consumption by 3.5–5% in response to more frequent information

Carter and Milon (2005)

Billing records for 742 households of three North-Central Florida water utilities

Simultaneous equation model with endogenous switching

Price knowledge increased consumption for each group, possibly because they overestimated the price of service

Kurz et al. (2005)

Water, electricity, and gas meter readings of 166 households in Melville, Perth, Western Australia

Socioecological framework: experimental design to study influence of information leaflets, attunement labels, and socially comparative feedback

Labels led to 23% reduction in water consumption, but not the other treatments. None of the treatments had effect on energy consumption

Fielding et al. (2013)

Smart water readings from 221 households in South East Queensland

Field experiment with three interventions: water saving information alone, information plus a descriptive norm manipulation, and information plus tailored end-user feedback

All interventions led to water savings; reduction in water use resulting from the interventions eventually dissipated after 12 months

Ferraro and Price (2013)

Over 100,000 households in Atlanta, Georgia in summer 2007

Natural field experiment using three norm-based messages (additively): information dissemination; voluntary restriction of usage; and social comparisons

Social comparison messages had greater influence than other treatments, and is particularly effective for high users; effectiveness wanes over time

Francis et al. (2015)

Eight focus group discussions with parents of young children and three key-informant interviews with village headmen of three villages in Tamil Nadu, India

Effectiveness of a commercially available, high throughput membrane filter for providing clean drinking water among residents

Lack of support from male members of the household impeded acceptance and long-term use of the intervention

Askew and McGuirk (2004)

Case study of newly established prestige housing estate close to Lake Macquarie, south of Newcastle, NSW

Understanding the sociocultural dimensions of water consumption: social distinction and social conformity

Social conformity is more likely than social distinction to lead to reductions in water consumption

Timm and Deal (2018)

National household survey of 218 households

Key behavioral influences behind high public acceptance rate of reclaimed water, and adoption of targeted domestic water conservation behaviors

Positive attitude toward reclaimed water was most significant in predicting level of approval; most widely adopted behaviors were fixing water leaks promptly ad monitoring water bills

Mansur and Olmstead (2007)

Data from 1,082 households in 11 urban areas in the United States and Canada, served by 16 public water utilities

Welfare implications of urban water rationing in response to drought

Use restrictions have costly welfare implications, primarily due to household heterogeneity in willingness to pay for scarce water

Ferraro et al. (2011)

Over 100,000 households in Atlanta, Georgia over the period 2007–2009

Natural field experiment using three norm-based messages (additively): technical advice; weak social norm; and strong social norm

Norm-based messages provide an effective means to promote short-run conservation efforts; Social comparison (strong social norm) messages are more persistent over time

Allcott and Rogers (2014)

Field experiment across three sites across US (one Midwest, two West Coast) comprising 234,000 single-family households

Treatment involves mailing of social comparison-based home energy reports to households

Initial reports reduce immediate electricity use markedly, but decay rapidly if treatment is not repeated; effects are relatively persistent if treatment is discontinued after two years; consumers are slow to habituate

Looking to the Future: Normative Incentives Within an Integrative Model

Overall, we have argued that the normative incentives are important tools to promote water consumption behavior. We have also shown that the empirical research on water use can be usefully located within more general behavioral theories such as the theory of planned behavior as well as an integrative theory. We have proposed some modifications and a simpler heuristic for thinking about incentives as being economic and normative, with a further typology of NI (I) and NI (II)—the first referring to “normative” as encompassing some moral content and the second, a social observation of others’ behavior.

Given our exploration of normative incentives, we have proposed two further causal chains in the integrative model (see Figure 2), with environmental factors (N1) and norms (N2 working in the causal chain from motivation) affecting attitudes.

Figure 2. Modified integrative model.

Managing the use of resources is critical in an age of Anthropocene, a time when human behavior has a large impact on our natural environment. This requires us to distinguish between real demand and profligacy, with behavioral aspects of water targeting the latter. Furthermore, managing water scarcity can have spillover effects on other areas. Urban centers may be forced to turn to more energy-intensive water sources, such as water recycling, desalination, or long-distance transport (Lam, Kenway, & Lant, 2017; Morales, Heaney, Friedman, & Martin, 2013).

A behavioral understanding of water use also targets polluting behaviors. Piped sewage collection and wastewater treatment tend to lag behind piped water distribution networks (van den Berg & Danilenko, 2011). Billions of people in urban and semiurban regions of Africa, Asia, and Latin America collect sewage locally, which is then ultimately disposed of directly into open land or water sources without treatment (Mateo-Sagasta, Raschid-Sally, & Thebo, 2015). In most African countries, less than 10% of urban areas are serviced by sewer systems. Untreated wastewater pollutes surface water sources and contaminates groundwater aquifers (Webster, 2013). Many cities in the Global South are unprepared to deal with additional wastewater that will be collected as the construction of sewage networks proceeds.

A last area where behavioral research can have a large impact is recycled water. Even in cities with advanced infrastructure, citizens are often still opposed to the direct consumption of recycled wastewater. Recycled water projects are often postponed or cancelled (Christen, 2005), utilized only for nonconsumption purposes (Marks, Martin, & Zadoroznyj, 2008; World Bank, 2018), or are directed back into the water table (Schmidt, 2008). Understanding the basis for such reluctance and changing adoptive behavior will allow new supplies into the hydrological equation.

Many people have stated that they are willing to change behavior to protect the environment (Rosa, Diekmann, Dietz, & Jaeger, 2010). Yet the translation of this avowal into actual behavior has been underresearched, with sociologists Shove and Warde (2002) characterizing this as “inconspicuous consumption.” She argues that the study of such consumption requires us to move from thinking of such consumption as discrete consumer behavior to what she calls “collective convention”—what we have called normative incentives in this article.

We have argued simply that we can tap on our best selves and adopt proenvironmental behavior when the incentive structures are set right. In that sense, environmental behavior mimics economic behavior. Managing water will be an ongoing challenge, requiring an improved understanding of institutions in different settings and the choices of individuals acting within them.

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