**3. Survey design and distribution**

The Southeastern Community located in the United States of America was established in 1980s, and spans over 4,700 acres. There are about 3,300 homes, including condos and apartments, with 6,600 residents in total. Most of the resident population is retired, so the community is rather a homogenous group. The first incidents of pinhole leaks were reported in 2001.

In August 2007, a questionnaire was sent to 1600 households in the Southeastern Community. The community's Property Owners' Association provided a list of the residents' names and addresses, and the sample was randomly selected from this list. Members of the Assocaition's Board reviewed the survey questions. The Association encouraged participation of community residents in the study. The survey was distributed following the Dillman technique of mail surveying, which included mailing a questionnaire with postage-paid return envelope, sending a reminder card, and mailing a second copy of the survey to nonresponders (Dillman, 1978).

In 2007, two surveys were conducted by the Virginia Tech researchers to learn about the home plumbing issues and the preventive measures taken against future corrosion incidences. The first survey acquired information on the incidents of pinhole leaks in the residential area, the adoption rate of preventive measures against corrosion, the homeowners' preferences for corrosion risk, and the costs associated with a leak free environment. The second survey elicited preferences for three hypothetical plumbing materials with different attribute levels. The sample of respondents was based on the first Southeastern Community survey respondents, who were willing to participate in the follow-up questionnaire.

A follow-up survey was administered in October 2007 to learn household preferences for home plumbing materials. The follow-up survey was sent 363 Southeastern Community householders who responded to the first survey, and who agreed to participate in future surveys. The respondents were exposed to attributes of three hypothetical to them plumbing system materials, which were left unnamed to avoid a survey exposure bias2. The materials represented in the questionnaire were copper, plastic, and epoxy coating. Materials were left unnamed, because most homeowners were familiar with at least one material type (copper,

 2 Survey Exposure Bias represents the ability to skew respondents' responses, based on the information either presented during the study or known prior to the study (Champ et al., 2003).

Households' Preferences for Plumbing Materials 427

The empirical analysis of the Southeastern Community home plumbing data includes several econometric and statistical techniques. The first survey data analysis uses simple descriptive statistics, such as mean (average values), percentages (percent distribution across all responses), and total sums, in order to provide a summary view of the home plumbing issues faced by the Southeastern Community. These issues include the frequency of pipe failure, the location of the failure in the plumbing system, the costs and time associated with fixing pipe failures, and the preventive measure taken to avoid incidences in the future. The analysis preferred plumbing materials concentrates on estimating the household preferences for plumbing types based on the follow-up survey of the Southeastern Community. The data estimation process employs the Ordered Logit regressions, based on which the household preferences for plumbing materials are derived.

The paragraphs presented below describe the econometric models in more detail.

The second Southeastern Community survey data analysis employs the Conjoint Analysis (CA) methodology to analyze the preferences for plumbing materials. This type of analysis includes eliciting the preferred good / service choices based on the presented information / stimuli. Utility Maximization Theory is usually employed to guide the process, design, and analysis of the CA studies, and involves making a choice that yields the greatest satisfaction to the respondents, otherwise known as utility, based on their available financial resources. As a result, the preference maximization problem is defined mathematically, as maximization of a utility function based on a specified financial resource constraint (Varian,

where u(x) represents the utility function, and px ≤ m represents the financial resource constraint, with m being the fixed amount of money available to households (Champ et al.,

In this chapter, a household faces a choice among three plumbing material alternatives. The utility (satisfaction) obtained from choosing a plumbing material, i, by the nth household is Uni. The decision maker chooses the option yielding the highest level of utility, which implies the following behavioral model: Uni > Unj , where i≠j. The level of utility is not observed by the researcher, but the attributes of the plumbing alternatives (xni) in the choice set are observed, as well as the socioeconomic characteristics of the decision maker (zn). Based on the known variables, a representative utility function can be specified as: Vni = V

For this exercise, each respondent pair-wise rated the preferred plumbing material option. The rating scale ranges from 1 to 9, with 1 indicating a not preferred plumbing material option, and 9 indicating the most preferred option. The plumbing material rating exercise is based on the utility-maximizing behavior, as higher plumbing material rating results in an increased level of utility, and therefore, a higher preference level for a given alternative. The

Maximize utility function: u(x) (1)

Subject to: px ≤ m, where x is in X, (2)

**4. Empirical analysis** 

**4.1 Ordered logit model description** 

(xni, zn) for all alternatives (Train, 2003).

1992):

2003).

plastic, or epoxy coating), and positive or negative experiences with these materials could have influenced their responses. The questions included two stimuli, which are compared simultaneously. Each respondent rated each of the two alternatives on a scale from 1 to 9. The scale value of 1 indicates the plumbing material is not preferred, while 9 indicates an extremely preferred plumbing system. The material attributes are listed in Table 1.


aNames of the plumbing materials were not revealed to the study participants

Table 1. Description of plumbing materials.
