Next Article in Journal
Evolution Characteristics of Rainfall and Runoff in the Upper Reaches of Zhang River Basin
Previous Article in Journal
Effects of Multispecies Probiotics on Growth, Hematology, and Gut Health of Stinging Catfish (Heteropneustes fossilis) in Biofloc System
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Investigating Heterogeneous Consumer Preference for Sustainable Sewerage Asset Management: The Case of South Korea

1
Department of Big Data Analytics, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin 17104, Republic of Korea
2
Department of Industrial and Management Systems Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin 17104, Republic of Korea
*
Author to whom correspondence should be addressed.
Water 2023, 15(14), 2520; https://doi.org/10.3390/w15142520
Submission received: 15 June 2023 / Revised: 3 July 2023 / Accepted: 4 July 2023 / Published: 10 July 2023
(This article belongs to the Section Water Resources Management, Policy and Governance)

Abstract

:
This study proposes a data-based strategy for prioritizing sewerage services and developing consumer-centric asset management systems. Sewerage systems are essential infrastructure, but resource-intensive, and governments have faced challenges due to limited budgets and aging facilities. Most countries are still in the early stages of adopting consumer-centric approaches. By using the mixed logit model, this study identified heterogeneous service preferences among consumers based on their priority for physical and social services. Groups who attributed their importance to physical services were more sensitive to sewerage bills; however, those who emphasized social services were more interested in water activity environment improvement and odor intensity reduction. This study also showed that people are willing to pay USD 10 for odor intensity reduction and USD 6 for water activities improvement on average, but those who prioritized sinkhole reduction and flood reduction answered less willingness to pay for each service improvement. Applying these heterogeneous service preferences to service improvement strategies can lead not only to higher consumer satisfaction and lower economic burden, but also to a deeper understanding of residents’ willingness to pay for service improvement in certain service preference areas. Therefore, the results contribute to the development of sustainable asset management strategies.

1. Introduction

Water and wastewater systems are essential for a high quality of life, public health, and national maintenance [1,2,3,4]. Industrialized countries have recently suffered from a huge financial burden to maintain aging public infrastructure, which was established at considerable expense in the 1980s and the 1990s [1,3,5]. Water and wastewater treatment systems consume considerable energy, accounting for 30–40% of the total global energy use [6]. In the United States, it was reported that USD 3 billion were used to operate and maintain their current sewerage service level in 2019 [7], and approximately USD 750 billion will be spent for the next 20 years [8]. China announced an investment of CNY 142 billion, which is 25% of the total expenses in the water treatment industry for upgrading sewage treatment facilities [9]. Moreover, the public budget for operating European wastewater treatment infrastructures accounted for approximately EUR 10.6 billion of their planned budget in the 2014–2020 Regional Policy [10]. As sewerage systems require a large amount of energy and cost for service provision, maintenance, and management, currently, people are increasingly concerned with how to maintain and manage old sewerage infrastructures, not how to establish them as in the past.
Governments have recently focused on sustainable sewerage infrastructure asset management [5,11,12]. Sewerage infrastructure asset management is a systematic process and effort to operate physical sewerage facilities in a cost- and energy-effective way to meet customer requirements [2,4,5,11,12,13,14,15]. Countries with advanced social overhead capital (SOC) investment, such as the U.K., Australia, New Zealand, and the U.S., have already developed their own asset management strategies for decades. At the beginning of asset management development, they focused on developing the public manual and systems to guide how to manage public infrastructures systematically. Recently, considering sustainable asset management, their attention has moved to maintaining high-quality service with considering the overall life-cycle and customer demand. They developed their own sustainable management systems for minimizing rate increases, improving the level of service (LoS), and handling problems owing to old and aging facilities. Companies have gradually focused on minimizing their life-cycle cost, developing algorithms, and optimization programs to maximize the quality of service and considering the weather effects.
Despite the high importance and great attention given to asset management, studies on aging sewerage facilities and their management in terms of asset management systems are still ongoing [5,16]. As there are numerous different wastewater treatment systems depending on the relative importance, regions, technologies, network, and operating process, more complicated strategies should consider these characteristics [6]. Although various types of technologies to enhance their energy efficiency and reduce costs have been developed, setting the appropriate criteria for long-term decision-making is also required, as it is impossible to apply all of them [17]. In addition, despite the important economic burden owing to the limited budget, it is still insufficient to develop cost-effective management systems to enhance system efficiency while considering service beneficiaries’ satisfaction [13,18].
Previous asset management practices primarily prioritized the physical aspects of sewerage facilities, leading to increased economic burdens and complaints from residents over time. However, the recognition of sewerage systems as not only physical problems, but also social and quality-of-life issues has amplified the importance of consumer-centric infrastructure asset management. With these trends, the method of asset management also needs to be changed. This study aimed to address these gaps by proposing a new data-based strategy for prioritizing asset management based on regional dissatisfaction sensitivity. It involves defining the level of each sewerage service and suggesting a consumer-centric asset management approach that identifies specific consumer-desired LoS to enhance satisfaction. By using the case of South Korea, which faces challenges related to rapidly aging sewerage facilities and integrating complaint data analysis, this study established sustainable asset management strategies by understanding consumer needs and sensitive services in each region. The choice experiment (CE) method and a mixed logit model with individual heterogeneity were used to analyze service sensitivity and consumer preferences, facilitating more meaningful discussions and insights.

2. Literature Review

2.1. Consumer-Centric Sewerage Infrastructure Asset Management

Infrastructure asset management, which aims to prolong the physical operation period and minimize mechanical failure, has become outdated [5,19]. Currently, companies focus on asset management methods that meet consumer needs and enhance service satisfaction by actively improving consumer experience [5,19,20,21]. The paradigm has shifted from a passive concept of maintaining and managing facilities from the providers’ perspective to an active and open method that meets consumer requirements and provides sustainable and safe public infrastructure services.
Consumer-centric asset management effectively reduces costs and improves efficiency. Existing provider-centered sewerage management rarely focuses on enhancing consumer utility efficiency because it operates services from the perspective of actual stakeholders [18]. However, as public infrastructure, such as sewerage systems, directly leads to residents’ comfort and satisfaction, it is important to maintain high-quality service levels for service beneficiaries [22]. Furthermore, some studies have noted that, even in the public service area, it is important to use complaint data to determine consumer satisfaction and understand consumer service demand [13,18,22]. Successful consumer-centric asset management is considered a strategic business tool that has a positive impact not only on the satisfaction of providers and beneficiaries, but also on business profitability [3,23]. It is also noteworthy in that consumer-centric services positively affect economic, environmental, and social efficiency, especially in policy management procedures, as this leads to sustainable environmental improvement with great public support and larger willingness to pay (WTP) [2,3,24].
The asset management process consists of four steps, as shown in Figure 1 [25]. First, the current state of an asset is identified by assessing its performance, residual life, and replacement costs. Second, the target LoSs are set, and decision-makers then determine critical business risks when service failures occur. In the fourth step, system managers optimize operations and maintenance (O&M) and capital investment and then build long-term asset management plans. This study focused on asset management strategies that understand consumer requirements in Step 2, where target LoSs were set to enhance their satisfaction.
To reflect consumer demand in the process of setting a more-accurate target LoS, it is important to understand consumer heterogeneity depending on the type and level of services [26,27]. It is necessary to follow consumers’ complex decision-making processes and grasp their heterogeneous preference characteristics to set a reasonable and agreeable target LoS and increase personal service satisfaction. Studies have been conducted on customer preferences for sewerage services [28,29,30,31], but most of them simply identify the average LoS, not considering their differences. From a more-realistic perspective, service beneficiaries’ initiatives and the WTP for service improvement can vary even with the same service demand depending on their different preferences [28,29,32]. However, previous studies have not fully taken this into account. Therefore, this study analyzed consumers’ heterogeneous service preferences depending on the service types that they consider important and presents the differences in their marginal WTP units.

2.2. Sewerage Infrastructure Asset Management in South Korea

The need for asset management has recently drawn attention, owing to the problems of aging facilities [33]. Thus, this study proposes a strategic sewerage asset management method using the case of South Korea. Sewerage facilities in Korea were rapidly installed for 20 years since 1992, and they were expected to exceed the duration period at the same time [5,34,35]. The domestic sewerage penetration rate is 93.9%, which means that the number of installations is sufficiently high. Advanced treatment applications also maintain a high quality of service [35]. However, as the ratio of old facilities of more than 20 years has reached 40% of the total, the need for a strategic asset management process is emphasized in advance to prevent huge expenses for overall replacement. Kang [5] predicted that, by 2035, the proportion of sewage treatment equipment and sewerage pipes will account for 83.6% and 51.5%, respectively.
The rapid aging of sewerage infrastructure has led to a great financial burden in system management. According to the ME and KEITI report [35], in 2018, approximately KRW 2.273 billion (which is approximately USD 1.75 million) was spent to maintain sewerage systems, and it was expected approximately KRW 19.208 billion (USD 14.79 million) will be spent until 2030 for retaining the old sewerage infrastructures in 20 years. In fact, as shown in Figure 2a, for a decade, the maintenance cost of sewerage has steadily increased from KRW 1.744 billion (USD 1.34 million) to KRW 3.648 billion (USD 2.80 million), which is more than double in 2020 [36,37].
Meanwhile, despite the government’s great investment in maintaining high-quality LoSs, there is a growing number of residents who are discontent with sewerage services. The number of complaints per 10,000 population was 11.47 in 2010, but tripled to 30.2 in 2020. In particular, the proportion of complaints about odor, sewerage pipes, drainage facilities, manholes, and purification systems has steadily increased over the last three years, from 2018 to 2020. Complaints related to odor were 10.03% of the total in 2018, but reached 12.79% in 2020. Dissatisfaction with sewerage pipes, drainage facilities, manholes, and purification systems in 2020 accounted for 59.37% of the total, which is 1.5-times larger than the 39.15% in 2018. This shows that consumers have experienced more inconvenience with aging sewerage systems and low-quality performance. However, the proportion of complaints about sewerage bills has decreased significantly from 21% in 2018 to 4% in 2020.
Therefore, the Korean government is highly interested in sustainable sewerage asset management and emphasizes the necessity of prolonging its life-cycle and cost management. Public agencies announced “The second national comprehensive sewerage plan” (2016–2025) and suggested the purpose and vision of the national sewerage policy to create future value and provide people-oriented services [35]. However, as sewerage asset management on a domestic scale is in the planning stage of building management systems and promoting pilot projects, more studies and efforts are required to establish sustainable management strategies. This study considered these domestic situations and proposes consumer-centric asset management systems by utilizing consumer sensitivity and regional complaint data depending on the type of sewerage services.

3. Methodology

The contingent valuation method (CVM) and choice experiment (CE) are widely used to determine consumer-centric LoSs [28,29,30,31,38,39,40]. The CVM identifies consumer preferences by directly asking for their WTP when a specific service is set. However, the CE was particularly more useful in this study for identifying consumer preferences regarding the unknown scenarios or different types and levels of services. In this study, the discrete choice model (DCM) was used to analyze the CE data. The DCM is based on utility-maximizing behaviors and is widely applied to analyze consumer preferences for public services [41]. The multinomial logit model in the DCM is easy to calculate by hand; however, the independence of irrelevant alternatives (IIAs) needs to be expressed in closed form [42]. The IIA restriction can sometimes be unrealistic because it assumes that the probability of selecting a specific alternative is not affected by the properties of other alternatives. In addition, it has difficulty reflecting heterogeneity because of fixed coefficients and unallowable correlations between alternatives.
To alleviate these limitations, the mixed logit model assumes a distribution of coefficients. The limitations of the existing logit model can be eased by reflecting heterogeneity and allowing correlations between alternatives [42,43,44,45]. Therefore, it is widely used in the analysis of consumer preferences for public goods [28,31], and it is appropriate to apply a mixed logit model in this sewage treatment service analysis. The utility function equation of the mixed logit model is expressed as Equation (1).
U n j = V n j + ε n j = β n X n j + ε n j ,   β n ~ f β | θ
U n j represents consumer n ’s utility when he/she chooses alternative j . V n j is the deterministic part that can be obtained by researchers, and ε n j is the random part, which is an unobservable individual characteristic. X n j is the vector of independent variables. β n j is the estimated parameter of X n j , which has a mean b and variance with a normal distribution. θ represents the distribution parameter. The choice probability of the mixed logit model is the same as that of the standard logit model multiplied by the coefficient distribution. Finally, the choice probability for consumer n ’s alternative j can be expressed as Equation (2):
P n i = ( e β x n i j = 1 J e β x n j ) f β | θ d β
The mixed logit model is estimated using the simulated maximum likelihood calculation parameter θ . The integrals were numerically approximated during the simulation process [31]. After randomly drawing β r from f β | θ , the average value of the choice probability P ˇ ni is calculated. The simulated log-likelihood (SLL) is given by Equation (3) (Train 2009):
SLL = n = 1 N ln P n i θ = n = 1 N ln P n i θ = n = 1 N ln e β x n i j = 1 J e β x n j f β | θ d β = n = 1 N ln P ˇ n i θ
The consumers’ utility function is obtained by estimating the coefficients of the variables through a simulation. Then, the WTP and relative importance of each attribute are calculated. The marginal WTP (MWTP) refers to the amount of respondents’ WTP for upgrading a specific feature. In other words, it refers to the variance of price-maintaining constant utility when the feature is changed by one level. The MWTP is estimated by dividing the coefficient by the negative coefficient of cost [46]. The relative importance (RI), which indicates how much each attribute influences respondents’ choices, is expressed as the ratio of the part-worth to the total. The part-worth is obtained by multiplying the coefficients and the difference between the highest and lowest levels of the attributes. The MWTP and RI can be written as Equations (4) and (5), respectively [28,47]:
M W T P k = U / x k U / x p r i c e = β k β p r i c e
RI k = p a r t w o r t h k l p a r t w o r t h l = β k x k ,   m a x x k , m i n l β l x l , m a x x l , m i n × 100

4. Empirical Analysis

4.1. Survey Design and Data

The Korea Environment Corporation [48] announced that 4072 public sewerage systems are being operated. For the empirical analysis, seven metropolitan cities (Seoul, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) were selected to conduct the survey, as their databases are well established. Proportional quota sampling was used to consider the characteristics of the population (aged 20–60 years) in South Korea. An online survey was conducted by a professional polling firm, Gallup Korea. To confirm whether respondents fully understood the questionnaire and the survey was well-designed, a pilot survey was conducted on 224 individuals in September 2020; after a month, the main survey on 1155 respondents was conducted.
The questionnaire consisted of three parts as follows. First, the overall questions, such as the perception of water resource services and importance of sewerage services, were asked in Part 1. Referring to previous studies, two of the most-important services were answered among the 12 sewerage services. In this process, we classified the 12 services into two groups, following the approach used by Tscheikner-Gratl et al. [18]. For the details, according to the previous study [18], to maintain sewerage facilities, there are two types of expenses: internal costs, which are paid by the service provider to deal with physical failures (e.g., old malfunctioning facilities), and social costs (externalities) to deal with consumer inconvenience (e.g., odor). Internal costs can be further divided into direct expenses for physical repairs, breakdowns, and indirect expenses in the business management process. From this perspective, the 12 types of sewerage services were classified into two categories, as shown in Table 1. A physical service is a service that requires the repair cost of infrastructure breakdowns. On the other hand, social services focus on service beneficiaries’ discomfort and dissatisfaction, rather than the facility.
Part 2 examined respondents’ preferences for sewerage services by describing their attributes and service levels. Part 3 asked about their demographic characteristics, including gender, age, educational level, job, number of family members, and monthly income. The results of the 1155 respondents’ demographic statistics are presented in Table 2.
The attributes and LoSs are presented to define the requirements of service beneficiaries, as described in Table 3. Based on previous studies and types of complaint data, inland flooding treatment capacity and efficiency of sewage treatment were used as physical service attributes. Social services included water activities, odor intensity, and response time to complaints. The sewerage bill represents consumers’ WTP, which is a monetary unit used to determine the preference level and importance of each service.
First, inland flooding treatment capacity, one of the physical services, consists of three levels: once a year, four times a year, and eight times a year. To set the levels of the attribute, statistics on the capacity, precipitation, and average duration of rainy seasons were considered. According to sewerage statistics [36,37], the average capacity of raindrop treatment systems was approximately 170 m3/m in five recent years. The annual average precipitation was 1306.3 mm [49], and the precipitation range between the minimum and maximum was from 146.2 mm to 696.5 mm in 10 recent years [50]. Given that the average duration of the rainy seasons is 30 days per year and the biggest typhoon in Korea had an effect of up to 7 days in 2020 [51], the affordable number of rainy days in this study was defined as between 1 and 8 days. In addition, according to the “Public sewerage service performance evaluation standards” [34] and “Special Act on the Safety Control and Maintenance of Establishments” [52], the efficiency of sewage treatment was classified into four levels: excellent, good, normal, and poor, except for the lowest level (very poor).
There are three social services, and their attributes and levels are described as follows: The Real-time Water Quality Index provided by the Korean Ministry of Environment [53] classifies water quality into five levels by considering seven indicators: water temperature, hydrogen ion concentration (pH), electrical conductivity (EC), dissolved oxygen (DO), total organic carbon (TOC), total nitrogen (TN), and total phosphorus (TP). Based on this index, without using the highest level (very good) and lowest level (very poor), the levels of water activities in this study were set at three levels: good, normal, and poor. “Good” refers to the level at which all kinds of water contact activities are approved, such as swimming, playing in the water, and fishing. The “normal” level means that the quality of water is generally good, but some of water contact activities are not allowed owing to occasional water pollution. “Poor” is the level that all water contact activities are prohibited owing to persistent water pollution. All descriptions about each level are additionally described in the survey to enhance respondents’ understanding. The intensity of the odor consisted of three levels: Levels 1, 2, and 2.5. This was based on a study about odor damage investigation and its compensation estimation method based on emission sources [54], which classifies the intensity of odor from Levels 0 to 5. With the minimum measured odor level (Level 1) and minimum recognized odor level (Level 2), Level 2.5 was set as the worst odor level, which is the limitation of odor intensity within a 1 km radius of public sewage treatment systems. To enhance readers’ understanding, the following explanations of each level were added in the survey contexts: Level 1 is the odor intensity level at which there is no damage from odor, but people can rarely observe the bad smell. Level 2 indicates the state with no damage, but people can recognize the odor from sewage treatment systems. Finally, Level 2.5 is the limitation of residential areas in which some people lodge complaints. Finally, the response time was described as four levels: very good, good, normal, and poor based on “The results of the 2021 public institutions’ management performance evaluation” [55] and the “Government Performance Evaluation Systems” [56].
The sewerage bill, which indicates consumers’ WTP, was determined by the average monthly sewerage bill for a four-person household. According to public domestic data [37,57], the average monthly sewerage bill for each household was KRW 12,701 (USD 9.78) in 2020. By considering this average amount, the attribute levels were set in the range of KRW 10,000 (USD 7.70) to KRW 40,000 (USD 30.79).
The total available number of alternatives by combining the attributes and levels was 1728 (3 × 3 × 3 × 4 × 4 × 4), and 32 alternatives were selected using the fractional factorial design. A total of 32 alternatives were grouped into eight sets, each with four options, and 8 alternative sets were randomly presented to the respondents. Table 4 presents an example of the alternative sets used in the survey.

4.2. Results

Prior to the analysis, the basic statistical survey results on sewerage services conducted in Part 1 were as follows: First, half (50.1%) of the respondents were satisfied with the overall sewerage services. In particular, the odor intensity reduction service was the most-satisfying sector (53.9%), followed by the improvement of sewage treatment capacity (48.2%), sewerage bills (47.4%), sewerage backflow reduction (46.8%), and flood-reduction services (43.9%). Meanwhile, respondents recognized odor intensity reduction (53.0%) as the most-important service, followed by the improvement of sewage treatment capacity (27.4%), upgrading the aging sewerage systems/pipes (26.2%), sewerage backflow reduction (21.1%), and flood reduction (17.5%).
However, considering these results, there were differences between services that were regarded as important, where customers were satisfied and where people felt urgent improvement was needed. Upgrading the aging sewerage systems was the most-highly recognized service that needs urgent renovation, with 26.3% of the total respondents, but ranked third in terms of importance. Odor intensity reduction was considered the most-important factor with the highest satisfaction. In addition, some of the results changed depending on the respondents’ demographic characteristics. People in their 20s, 30s, and 60s responded a reduction in sinkholes in road service as the most-important service after odor intensity reduction; however, unnecessary water ingress into the pipe was considered the most0important service by those in their 40s and 50s. Regardless of where they lived, upgrading the aging sewerage systems/pipes and odor intensity reduction services ranked first and second, respectively, in terms of the services that urgently required renovations and upgrades. Although, after them, people living in Seoul considered flood-reduction service as the most-crucial problem; however, others emphasized the improvement of sewage treatment capacity.
As previously shown, it is necessary to analyze these heterogeneities when determining the service level of sewerage asset management by considering consumers’ characteristics and types of services. Therefore, the mixed logit model and simulated maximum likelihood estimation were used, as shown in Equation (6). Each attribute was assumed to have a normal distribution and the form of a continuous variable.
U n j = β 1 X A c t i v i t y + β 2 X S m e l l + β 3 X F l o o d + β 4 X E f f i c i e n c y + β 5 X T i m e + β 6 X C o s t + ε n j
Table 5 presents the base model estimation results for each sewage treatment service. People preferred a higher quality of services in sewage treatment efficiency, water activities, inland flooding treatment capacity, and a lower level of odor intensity. They also preferred a shorter response time and less-expensive sewerage bills. In that these results were consistent with typical consumer behavior patterns, this means that they were reasonably estimated. According to the results, the preferences on social services, such as water activities and intensity of odor, had individual heterogeneity. In addition, regarding the fact that respondents had heterogeneous preferences on response time to complaints and sewerage bills, people had different levels of initiative and the amount of time and cost they were willing to spend. Meanwhile, inland flooding treatment capacity and efficiency of sewage treatment did not show heterogeneous results, which means that physical improvement services from the providers’ perspective usually had common preferences. People answered that they were willing to pay KRW 12,908 (USD 9.94 USD) to reduce one level of sewerage odor and willing to pay KRW 7,833 (USD 6.03) to enhance one level of water activities. The WTP for improving one level of response time (KRW 3,927, USD 3.02), sewerage treatment efficiency (KRW 3614, USD 2.78) and inland flooding treatment capacity (KRW 1,656, USD 1.27) followed. The relative importance of sewerage services was ranked in the following order: intensity of odor (19.51%), water activities (15.79%), response time to complaints (11.87%), inland flooding treatment capacity (11.68%), and efficiency of sewage treatment (10.92%).
As presented in Table 1, sewerage services were classified into two groups: physical and social services. Among the 12 services, the importance of the top six services was used for interactions in Model 2. Upgrading the aging sewerage systems/pipes, improvement of sewage treatment capacity, and a reduction in sinkholes in roads were considered physical services, and their results are shown in Models 2-1, 2-2, and 2-3. Odor intensity reduction, flood reduction, and outfall pollution reduction were types of social services, as shown in Models 2-4, 2-5, and 2-6. The form of data that indicated people who considered each service the most-important was set as dummy variables; if they considered it to be the most-important, then it was set to 1; otherwise, it was set to 0. Table 6 presents the results of the interaction-included models.
First, the analysis results of people who prioritized physical services were as follows: Those who considered upgrading the aging sewerage systems/pipes as the most-important tended to be more sensitive to higher sewerage bills and had statistically significant heterogeneity in water activities and sewerage bills. People with high concern about the efficiency of sewage treatment were more-sensitive to sewage treatment efficiency, water activities, level of odor intensity, and sewerage bills. They were willing to pay up to KRW 3100 (USD 2.39) to upgrade one level of water activities, approximately KRW 8600 (USD 6.62) for odor intensity, and KRW 3400 (USD 2.62) for efficiency improvement. In addition, it was revealed that people who answered sinkhole reduction in roads as important tended to focus less on odor intensity, treatment efficiency, and sewerage bills. They were willing to pay KRW 9100 (USD 7.01) and KRW 5800 (USD 4.47) less than others for each service. They had the average level of customer heterogeneity in the sensitivity of water activities, odor intensity, complaint response time, and sewerage bills, which was similar to that of the other groups.
In social services, people who considered odor intensity as the most-crucial problem tended to react more sensitively to services related to water activities and odor intensity. They were willing to pay KRW 3400 (USD 2.62) more to enhance one level of water activities and KRW 7600 (USD 5.85) to reduce odor intensity. In particular, it was found that they had heterogeneous preferences for water activities, odor intensity reduction, response time to complaints, and sewerage bills. When people considered flood reduction as the most-important sewerage service, they were less sensitive to odor intensity, efficiency improvement, and sewerage bills than others and even were willing to pay KRW 6300 (USD 4.85), KRW 7500 (USD 5.77), and KRW 3700 (USD 2.85) less for each service, respectively. Respondents who gave importance to flood reduction and outfall pollution showed heterogeneity in customer utilities for providing one-level better services of odor intensity, response time, and sewerage bills.

5. Discussion

To summarize the results, respondents tended to prefer a shorter response time to complaints and a better quality of sewerage services with less-expensive sewerage bills. However, in terms of each sewerage service, there were different service preferences and sensitivity, depending on the perceived importance. This also led to the different amount of payment for each service. In terms of physical service, people who supported aging facilities’ and efficiency improvement were more likely to be sensitive about sewerage bills. Those who considered sinkholes in roads were crucial tended to be less sensitive to each service and showed average LoS preferences. Meanwhile, respondents who supported odor intensity and flood reduction responded more strongly to water activities and odor intensity. Those who recognized the importance of sewerage odor problems had heterogeneous preferences for odor intensity, response time, and sewerage bills. In terms of flood reduction and outfall pollution reduction, respondents showed an average level of preferences for most sewerage services.
When these results were combined with complaint data, as shown in previous studies [18,22], meaningful policy implications can be discussed. Figure 3 shows the most-filed complaints by region in 2020 [37]. As shown in Figure 3, there were more complaints related to physical services than to social services. Complaints about sewerage odor were most common in 19 regions; six in Seoul (Jongno-gu, Jung-gu, and Jungnang-gu), two in Incheon, one in Busan, two in Daegu, and so on. This showed that 11 regions, including Busan, Siheung, and Incheon, had filed complaints related to sewerage bills. Problems related to drainage systems were most-common in 51 regions, and complaints related to manholes were most-common in 21 areas. There were 56 regions who asked to solve problems related to sewerage pipes, and 7 regions urgently filed complaints about purifying systems.
By applying the analysis result, people living in Jongno-gu, or Jung-gu, which is one of the 19 regions where odor was the most-critical problem, tended to pay approximately KRW 20,000 (USD 15.40) more than other group members to solve this problem. As residents in this area focused on water activity services, they might have high satisfaction with related service improvements. According to the results, residents in areas where social services are prioritized showed less sensitive to increasing sewerage bills, suggesting that they may be more proactive in demanding service improvements.
As the 63 regions with high concerns about sewerage pipes and purifying systems are groups who focused on aging facilities and efficiency of sewage treatment, they may strongly make claims regarding unsatisfactory water activity environments, low-quality odor and sewage treatment, and an increase in sewerage bills. As these areas are particularly in a group with heterogeneous preferences in increasing sewerage bills, they were more likely to have larger difference on requiring service improvement than other groups. In other words, residents in these areas strongly required service improvements, but they also had a high sensitivity to increases in sewerage bills, which can create challenges in policy implementation owing to significant differences between service improvements and the related cost increases. Therefore, it is important to identify the level of service improvements while minimizing additional fee increases and gradually enhancing consumer satisfaction through incremental service improvements in these areas.
Moreover, there is a real-world example of a regional government that has already used complaint data and resident sensitivity in planning a sewerage service management budget. Daegu plans to establish an ICT-based smart sewerage management system for the entire management process by investing KRW 67.4 billion (USD 51.83 million) from 2022 to 2024, which is the first case in Korea [58]. Initially, in flood-prone areas such as Buk-gu and Dong-gu with a high number of complaints related to drainage facilities, sewerage simulation, monitoring, and control systems’ damage will be established to respond to floods. In areas with a large number of complaints about sewerage odor, projects using odor measurement equipment will be implemented as a priority. Facility information will be managed based on its database to effectively manage aging facilities. It is noteworthy that this will be the first step in applying a low-cost and high-efficiency management system, which is expected to enhance customer satisfaction with a limited budget, strengthen industrial competitiveness through technological innovation, and create new growth engines.

6. Conclusions

In conclusion, this study was conducted in response to the increasing need for strategic sewerage asset management owing to rapidly aging facilities and heavy cost burden. It proposed cost-effective strategies that maximize service beneficiaries’ satisfaction in service-level decision-making within the asset management process. A customer preference analysis related to sewerage services was conducted using the CE method. To consider the characteristics of each service and respondents’ heterogeneity, various types of sewerage services were categorized into two groups: physical services and social services. By combining the analysis and complaint data, policy implications were also provided.
This study made the following three contributions. First, it presented a new data-based approaches for determining service level along with analyzing heterogeneous customer preferences at the level of each sewerage services. It helped to enhance management efficiency by proposing different asset management strategies depending on service sensitivities. It also provided insights into sewerage bill increases and service management by estimating respondents’ WTP for each service. The estimation results will help policy-makers assume the amount of residents’ support and to efficiently establish public budget planning to improve regional service levels. Finally, this study laid the groundwork for enhancing sewerage asset management strategies, and the findings can serve as a valuable resource for future research and development in wastewater system technologies by suggesting how to set the prioritize among the various service areas.
However, still, there are challenges in providing more-specific implications. The mismatch between complaint data and survey questionnaires, where some types of social and physical services are combined as a form of “others”, hinders more-detailed analysis results. Thus, additional implications for each service group should be identified in further applications. Moreover, as this study did not estimate the WTP for each service level, this could be conducted in future research to enhance the further findings of this study. When the specific service levels and scenarios are set, a more-precise cost–benefit analysis can be conducted and indicate further discussions related to the consumer-centric sewerage asset management.

Author Contributions

H.J.: data curation, formal analysis, investigation, and writing—original draft. S.P.: data curation and formal analysis. J.S.: conceptualization, methodology, supervision, and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry, and Energy (MOTIE) of the Republic of Korea (20224000000260). This study was also supported by the Korea Environment Institute (KEI).

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Chatzisymeon, E. Reducing the energy demands of wastewater treatment through energy recovery. In Sewage Treatment Plants; Stamatelatou, K., Tsagarakis, K.P., Eds.; IWA Publishing: London, UK, 2015; Volume 1, pp. 3–14. ISBN 9781780405025. [Google Scholar]
  2. De Jong, R.; Nentjes, A.; Wiersma, D. Inefficiencies in public environmental services. Environ. Resour. Econ. 2000, 16, 69–79. [Google Scholar] [CrossRef]
  3. Elnaboulsi, J.C. An Incentive Water Pricing Policy for Sustainable Water Use. Environ. Resour. Econ. 2009, 42, 451–469. [Google Scholar] [CrossRef]
  4. Molinos-Senante, M.; Maziotis, A.; Sala-Garrido, R. Changes in the total costs of the English and Welsh water and sewerage industry: The decomposed effect of price and quantity inputs on efficiency. Util. Policy. 2020, 66, 101063. [Google Scholar] [CrossRef]
  5. Kang, H. Challenges for water infrastructure asset management in South Korea. Water Policy. 2019, 21, 934–944. [Google Scholar] [CrossRef] [Green Version]
  6. Silva, C.; Alerge, H.; Rosa, M.J. Introduction to energy management in wastewater treatment plants. In Sewage Treatment Plants; Stamatelatou, K., Tsagarakis, K.P., Eds.; IWA Publishing: London, UK, 2015; Volume 3, pp. 33–55. ISBN 9781780405025. [Google Scholar]
  7. American Society of Civil Engineers (ASCE). A Comprehensive Assessment of America’s Infrastructure. 2021. Available online: https://www.cdfa.net/cdfa/cdfaweb.nsf/ordredirect.html?open&id=ASCE_2021_Infrastructure-Report-Card.html (accessed on 5 January 2023).
  8. National Association of Clean Water Agencies (NACWA). Water Sector Comes Together for Water Week 2022, Applauds Federal Infrastructure Investments and Calls for Sustained Support. 2022. Available online: https://www.nacwa.org/news-publications/press-release-details/2022/04/26/water-sector-comes-together-for-water-week-2022-applauds-federal-infrastructure-investments-and-calls-for-sustained-support (accessed on 5 January 2023).
  9. GCiS China Strategic Research. China’s 13th Five Year Plan and the Wastewater Treatment Industry. Available online: https://www.gcis.com.cn/china-insights-en/industry-articles-en/231-china-s-13th-five-year-plan-the-wastewater-treatment-industry (accessed on 4 September 2022).
  10. European Commission. Urban Waste Water: 10th Report on Implementation. 2020. Available online: https://ec.europa.eu/commission/presscorner/detail/en/qanda_20_1562 (accessed on 5 January 2023).
  11. Jones, M.; Williams, W.; Stillman, J. The evolution of asset management in the water industry. J. Am. Water Work Assoc. 2014, 106, 140–148. [Google Scholar] [CrossRef]
  12. Uddin, W.; Hudson, W.R.; Haas, R. Public Infrastructure Asset Management; McGraw-Hill Education: New York, NY, USA, 2013; ISBN 9780071820110. [Google Scholar]
  13. Jo, H.; Ryu, J.; Shin, J. Sewerage infrastructure asset management based on a consumer-centric approach. Environ. Sci. Pollut. R. 2022, 29, 53009–53021. [Google Scholar] [CrossRef]
  14. Moon, F.L.; Aktan, A.E.; Furuta, H.; Dogaki, M. Governing issues and alternate resolutions for a highway transportation agency’s transition to asset management. Struct. Infrastruct. Eng. 2009, 5, 25–39. [Google Scholar] [CrossRef]
  15. United States Environmental Protection Agency (EPA). Asset Management for Sewer Collection Systems. 2002. Available online: https://www3.epa.gov/npdes/pubs/assetmanagement.pdf (accessed on 5 January 2023).
  16. Huh, S.Y.; Shin, J.; Ryu, J. Expand, relocate, or underground? Social acceptance of upgrading wastewater treatment plants. Environ. Sci. Pollut. R. 2020, 27, 45618–45628. [Google Scholar] [CrossRef]
  17. Molinos-Senante, M.; Hanley, N.; Henández-Sancho, F.; Sala-Garrido, R. The principles of economic evaluation and cost-benefit analysis implemented in sewage treatment plants. In Sewage Treatment Plants; Stamatelatou, K., Tsagarakis, K.P., Eds.; IWA Publishing: London, UK, 2015; Volume 2, pp. 15–32. ISBN 9781780405025. [Google Scholar]
  18. Tscheikner-Gratl, F.; Caradot, N.; Cherqui, F.; Leitão, J.P.; Ahmadi, M.; Langeveld, J.G.; Le Gat, Y.; Scholten, L.; Roghani, B.; Rodríguez, J.P.; et al. Sewer asset management—State of the art and research needs. Urban Water J. 2019, 16, 662–675. [Google Scholar] [CrossRef] [Green Version]
  19. Cook, A.M.R.; Lucas, R.A.; Knight, S.P. Customer-centric asset management: An approach and applying it in practice. In Proceedings of the IET&IAM Asset Management Conference 2012, London, UK, 27–28 November 2012; pp. 1–3. [Google Scholar] [CrossRef]
  20. Han, S.; Chae, M.J.; Hwang, H.; Choung, Y. Evaluation of customer-driven level of service for water infrastructure asset management. J. Manag. Eng. 2015, 31, 04014067. [Google Scholar] [CrossRef]
  21. Ramanan, S.; Naylor, R.; Francisco, W.; Riesenweber, A.; Hunter, S.; Atkins, N.; Dominish, C. Harnessing Data to Help Water Utilities Become More Customer Centric. GHD Digital. 2021. Available online: https://www.ghd.com/en/perspectives/resources/pdf/GHD-Digital-Harnessing-data-to-help-water-utilities.pdf (accessed on 5 January 2023).
  22. Chang, T.; Chi, S.; Im, S.B. Understanding User Experience and Satisfaction with Urban Infrastructure through Text Mining of Civil Complaint Data. J. Constr. Eng. M. 2022, 148, 04022061. [Google Scholar] [CrossRef]
  23. Almeida, N.; Trindade, M.; Komlijenovic, D.; Finger, M. A conceptual construct on value for infrastructure asset management. Util. Policy. 2022, 75, 101354. [Google Scholar] [CrossRef]
  24. Mullen, J.D.; Calhoun, K.C.; Colson, G.J. Preferences for policy attributes and willingness to pay for water quality improvements under uncertainty. Water Resour. Res. 2017, 53, 2627–2642. [Google Scholar] [CrossRef]
  25. United States Environmental Protection Agency (EPA). Asset Management for Water and Wastewater Utilities. 2017. Available online: https://www.epa.gov/sustainable-water-infrastructure/asset-management-water-and-wastewater-utilities (accessed on 5 January 2023).
  26. Keane, M.; Wasi, N. Comparing alternative models of heterogeneity in consumer choice behavior. J. Appl. Econom. 2013, 28, 1018–1045. [Google Scholar] [CrossRef] [Green Version]
  27. Kim, D.; Hong, S.; Park, B.J.; Kim, I. Understanding heterogeneous preferences of hotel choice attributes: Do customer segments matter? J. Hosp. Tour. 2020, 45, 330–337. [Google Scholar] [CrossRef]
  28. Hensher, D.; Shore, N.; Train, K. Households’ Willingness to Pay for Water Service Attributes. Environ. Resour. Econ. 2005, 32, 509–531. [Google Scholar] [CrossRef]
  29. Palanca-Tan, R. Knowledge, attitudes, and willingness to pay for sewerage and sanitation services: A contingent valuation survey in Metro Manila, Philippines. J. Environ. Sci. Manag. 2015, 18, 44–52. [Google Scholar] [CrossRef]
  30. Veronesi, M.; Chawla, F.; Maurer, M.; Lienert, J. Climate change and the willingness to pay to reduce ecological and health risks from wastewater flooding in urban centers and the environment. Ecol. Econ. 2014, 98, 1–10. [Google Scholar] [CrossRef] [Green Version]
  31. Willis, K.G.; Scarpa, R.; Acutt, M. Assessing water company customer preferences and willingness to pay for service improvements: A stated choice analysis. Water Resour. Res. 2005, 41, 2. [Google Scholar] [CrossRef]
  32. Feick, L.; Higie, R.A. The Effects of Preference Heterogeneity and source Characteristics on Ad Processing and Judgements about Endorsers. J. Advert. 1992, 21, 9–24. [Google Scholar] [CrossRef]
  33. Kim, T.; Shin, J.; Hyung, J.; Kim, K.; Koo, J.; Cha, Y. Willingness to pay for improved water supply services based on asset management: A contingent valuation study in South Korea. Water 2021, 13, 2040. [Google Scholar] [CrossRef]
  34. Korean Ministry of Environment (ME); Korea Environment Corporation. A Study on the Evaluation of Existing Age-Old Public Sewage Treatment Infrastructures and the Feasibility of Its Improvement. 2019. Available online: http://www.me.go.kr/home/web/policy_data/read.do?menuId=10264&seq=7526 (accessed on 5 January 2023).
  35. Korean Ministry of Environment (ME); Korea Environmental Industry and Technology Institute (KEITI). A Report on Water and Wastewater System R&D Technology Trends in 2020. 2021. Available online: https://www.keiti.re.kr/site/keiti/ex/board/View.do?cbIdx=318&bcIdx=32870 (accessed on 5 January 2023).
  36. Korean Ministry of Environment (ME). 2017 Statistics of Sewerage. 2018. Available online: http://www.me.go.kr/home/web/policy_data/read.do?pagerOffset=0&maxPageItems=10&maxIndexPages=10&searchKey=&searchValue=&menuId=10259&orgCd=&condition.orderSeqId=7141&condition.rnSeq=270&condition.deleteYn=N&seq=7146 (accessed on 5 January 2023).
  37. Korean Ministry of Environment (ME). 2020 Statistics of Sewerage. 2021. Available online: https://me.go.kr/home/web/policy_data/read.do?pagerOffset=0&maxPageItems=10&maxIndexPages=10&searchKey=&searchValue=&menuId=10264&orgCd=&condition.toInpYmd=null&condition.code=A5&condition.fromInpYmd=null&condition.orderSeqId=6430&condition.rnSeq=110&condition.deleteYn=N&condition.deptNm=null&seq=7809 (accessed on 5 January 2023).
  38. Ahn, J.; Moon, H.; Shin, J.; Ryu, J. Social benefits of improving water infrastructure in South Korea: Upgrading sewage treatment plants. Environ. Sci. Pollut. R. 2020, 27, 11202–11212. [Google Scholar] [CrossRef] [PubMed]
  39. Bravo-Moncayo, L.; Naranjo, J.L.; García, I.P.; Mosquera, R. Neural based contingent valuation of road traffic noise. Trasport. Res. D-TR E. 2017, 50, 26–39. [Google Scholar] [CrossRef]
  40. Mogas, J.; Riera, P.; Bennett, J. A Comparison of Contingent Valuation and Choice Modelling: Estimating the Environmental values of Catalonian Forests. 2002. Available online: http://hdl.handle.net/10440/1177 (accessed on 5 January 2023).
  41. van den Broek-Altenburg, E.; Atherly, A. Using discrete choice experiments to measure preferences for hard to observe choice attributes to inform health policy decisions. Health Econ. Rev. 2020, 10, 1–8. [Google Scholar] [CrossRef]
  42. Train, K.E. Discrete Choice Methods with Simulation; Cambridge University Press: New York, NY, USA, 2009. [Google Scholar]
  43. Scarpa, R.; Thiene, M.; Hensher, D.A. Preferences for tap water attributes within couples: An exploration of alternative mixed logit parameterizations. Water Resour. Res. 2012, 48, 1. [Google Scholar] [CrossRef] [Green Version]
  44. Syuhada, C.I.N.; Mahirah, K.; Roseliza, M.A. Dealing with attributes in a discrete choice experiment on valuation of water services in East Peninsula Malaysia. Util. Policy 2020, 64, 101037. [Google Scholar] [CrossRef]
  45. Unterberger, C.; Olschewski, R. Determining the insurance value of ecosystems: A discrete choice study on natural hazard protection by forests. Ecol. Econ. 2021, 180, 106866. [Google Scholar] [CrossRef]
  46. Rambonilaza, M.; Point, P.; Dachary-Bernard, J. Stability of the WTP measurements with successive use of choice experiments method and multiple programmes method. Rev. Econ. Polit. 2007, 117, 719–735. [Google Scholar] [CrossRef] [Green Version]
  47. Byun, H.; Shin, J.; Lee, C.Y. Using a discrete choice experiment to predict the penetration possibility of environmentally friendly vehicles. Energy 2018, 144, 312–321. [Google Scholar] [CrossRef]
  48. Korea Environment Corporation. Recent Status of Public Wastewater Treatment Systems. 2021. Available online: https://www.data.go.kr/data/3073222/fileData.do (accessed on 5 January 2023).
  49. Korea Meteorological Administration (KMA). Domestic Climate Characteristics. Available online: https://www.weather.go.kr/w/obs-climate/climate/korea-climate/korea-char.do (accessed on 8 December 2022).
  50. Open MET Data Portal. Korea Meteorological Administration. Statistics about Rainy Seasons. Available online: https://data.kma.go.kr/climate/rainySeason/selectRainySeasonList.do (accessed on 8 December 2022).
  51. Korea Meteorological Administration (KMA). 2020 Climate Crisis in Point of Social and Economic Damage. 2021. Available online: http://www.climate.go.kr/home/bbs/view.php?code=58&bname=newsreport&vcode=6497&skind=&sword=&category1=&category2= (accessed on 5 January 2023).
  52. Korean Ministry of Land, Infrastructure and Transport (MOLIT). Daegu Metropolitan City Government Establishes the Smart Sewerage Management System Based on ICT. 2021. Available online: https://smartcity.go.kr/2022/03/16/%EB%8C%80%EA%B5%AC%EC%8B%9C-ict%EA%B8%B0%EB%B0%98-%EC%8A%A4%EB%A7%88%ED%8A%B8%ED%95%98%EC%88%98%EB%8F%84-%EA%B4%80%EB%A6%AC%EC%B2%B4%EA%B3%84-%EA%B5%AC%EC%B6%95 (accessed on 5 January 2023).
  53. Water Environment Information System (WEIS). Real Time Water Quality Index. Available online: https://water.nier.go.kr/web/contents/contentView/;jsessionid=A623E5155FB7BDBCF1B214E094B6A06A?pMENU_NO=68 (accessed on 5 September 2022).
  54. National Environmental Dispute Resolution Commission in Korean Ministry of Environment (ECC). A Study on the Odor Damage Investigation and Its Compensation Estimation Method Based on Emission Sources. 2008. Available online: http://e-learning.nhi.go.kr/oer/view/oerCntnsView.do?id=112290&cid=NB000120061207100091168&oid=0000000006&mid=view (accessed on 5 July 2023).
  55. Korean Ministry of Economy and Finance (MOEF). The Results of the 2021 Public Institutions’ Management Performance Evaluation. 2022. Available online: https://www.korea.kr/news/pressReleaseView.do?newsId=156512436 (accessed on 5 January 2023).
  56. Government Performance Evaluation Committee (South Korea). Comprehensive Evaluation of Complaint Service (Ministry of the Interior and Safety). Government Performance Evaluation System. Available online: https://www.evaluation.go.kr/web/page.do?menu_id=28 (accessed on 5 September 2022).
  57. Korean Statistical Information Service (KOSIS). Households and Household Members by Type of Household. 2021. Available online: https://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1JC1501&conn_path=I2&language=en (accessed on 5 January 2023).
  58. Korean Ministry of Land, Infrastructure and Transport (MOLIT). Special Act on the Safety Control and Maintenance of Establishments. 2022. Available online: https://elaw.klri.re.kr/kor_mobile/viewer.do?hseq=56563&type=sogan&key=4 (accessed on 5 January 2023).
Figure 1. The asset management progress. Source: EPA (2020) Asset Management for Water and Wastewater Utilities.
Figure 1. The asset management progress. Source: EPA (2020) Asset Management for Water and Wastewater Utilities.
Water 15 02520 g001
Figure 2. (a) Renovation and maintenance expenses trends in South Korea. (b) Number of complaints about the domestic sewerage services in recent years (2018–2020). Source: ME (2018) 2017 Statistics of Sewerage, ME (2021) 2020 Statistics of Sewerage.
Figure 2. (a) Renovation and maintenance expenses trends in South Korea. (b) Number of complaints about the domestic sewerage services in recent years (2018–2020). Source: ME (2018) 2017 Statistics of Sewerage, ME (2021) 2020 Statistics of Sewerage.
Water 15 02520 g002aWater 15 02520 g002b
Figure 3. Largest number of complaints by region. Source: ME (2021) 2020 Statistics of Sewerage.
Figure 3. Largest number of complaints by region. Source: ME (2021) 2020 Statistics of Sewerage.
Water 15 02520 g003
Table 1. Two types of wastewater treatment services in this study.
Table 1. Two types of wastewater treatment services in this study.
Physical ServiceSocial Service
The amount of unnecessary water ingress into the pipe (not only sewerage)Odor intensity reduction
The amount of discharged unpurified wastewater in the confluent drainage during rainfallFlood reduction
Outfall pollution reduction
Reduction in sinkholes in roadThe amount of public information related to sewerage systems
Upgrading the aging sewerage systems/pipesThe quality of complaints’ response and its time
Improvement of sewage treatment capacitySewerage bills
Table 2. Respondents’ demographic characteristics.
Table 2. Respondents’ demographic characteristics.
CategoryCharacteristicRespondents (n)Percentage (%)
Total 1155100.0
GenderMale60952.7
Female54647.3
Age20–2921818.9
30–3925922.4
40–4926823.2
50–5925321.9
60–6915713.6
IncomeBelow KRW 3 million27523.8
KRW 3–4 million37132.1
KRW 4–5 million27323.6
Above KRW 5 million23620.4
Table 3. Attributes and levels for the wastewater treatment services.
Table 3. Attributes and levels for the wastewater treatment services.
AttributeLevelsDetails
Inland flooding treatment capacity
(per year)
Once a year
Four times a year
Eight times a year
Sewerage system capacity limitations holding the inland flooding problems over the durations
Efficiency of sewage treatment (%)Very good (above 90%),
Good (70–90%),
Normal (50–70%),
Poor (under 50%)
The level at which sewerage is appropriately transported to treatment systems
Water activitiesGood, normal, and poorThe level of water activities related to sewerage service
Intensity of odorLevels 1, 2, and 2.5The intensity of odor from sewerage services
Response time to complaints
(for each complaint)
Very good (less than 2 h),
Good (more than 2 h, less than 5 h),
Normal (more than 5 h, less than 30 h),
Poor (more than 30 h)
Response time to sewerage service complaints, which means the time for responding to each complaint
Sewerage bills
(KRW, monthly)
KRW 10,000, KRW 20,000,
KRW 30,000, KRW 40,000
Average monthly sewerage bill
Note: According to the Bank of Korea, USD 1.00 was KRW 1,298.06; www.bok.or.kr (accessed on 5 July 2023).
Table 4. Sample of the CE survey.
Table 4. Sample of the CE survey.
AttributeType AType BType CType D
Inland flooding treatment capacity
(per year)
Once a yearFour times a yearOnce a yearEight times a year
Efficiency of sewage treatment (%)Poor
(below 50%)
Very good
(above 90%)
Good
(70–90%)
Good
(70–90%)
Water activitiesGoodNormalPoorNormal
Intensity of odorLevel 2Level 1Level 2.5Level 2.5
Response time to complaints
(for each complaint)
Good
(more than 2 h, less than 5 h)
Good
(more than 2 h, less than 5 h)
Good
(more than 5 h, less than 30 h)
Poor
(more than 30 h)
Sewerage bills
(KRW, monthly)
KRW 40,000KRW 10,000KRW 30,000KRW 10,000
Table 5. Estimation results of mixed logit model for sewage treatment services (base model).
Table 5. Estimation results of mixed logit model for sewage treatment services (base model).
Model 1
AttributeAssumed DistributionMean of βSD of βMWTP (KRW)RI (%)
Inland flooding treatment capacity
(per year)
Normal−0.0636***0.0026 1656.311.68
Efficiency of sewage treatment (%)Normal−0.1388***0.0030 3613.610.92
Water activitiesNormal−0.3009***0.1755**7832.915.79
Intensity of odorNormal−0.4958***0.6563***12,907.419.51
Response time to complaints
(for each complaint)
Normal−0.1508***0.2404***3926.611.87
Sewerage bills
(KRW, monthly)
Normal−0.0384***0.0547***-10.92
No. of observations18,480
Log likelihood−5651.4
Notes: *** significant at the 1% level; ** significant at the 5% level. According to the Bank of Korea USD 1.00 was KRW 1298.06; www.bok.or.kr (accessed on 5 July 2023).
Table 6. Estimation results of mixed logit model for sewage treatment services (interaction included).
Table 6. Estimation results of mixed logit model for sewage treatment services (interaction included).
Model 2-1Model 2-2Model 2-3Model 2-4Model 2-5Model 2-6
Important 1Old FacilitiesEfficiency of Sewage TreatmentSinkholes in RoadOdor Intensity ReductionFlood ReductionOutfall Pollution
Attribute
Mean
of β
Inland flooding treatment capacity−0.0634***−0.0578***−0.0618***−0.0639***−0.0650***−0.0634***
Treatment efficiency−0.1273***−0.1011***−0.1544***−0.1124***−0.1555***−0.1358***
Water activity−0.2799***−0.2654***−0.3107***−0.2354***−0.3321***−0.2968***
Odor intensity−0.4983***−0.3956***−0.5185***−0.3560***−0.5342***−0.4811***
Response time−0.1450***−0.1496***−0.1572***−0.1413***−0.1499***−0.1577***
Sewerage bills−0.0339***−0.0353***−0.0406***−0.0352***−0.0399***−0.0374***
Inland flooding treatment capacity × important0.0005 −0.0227 −0.0131 −0.0002 0.0099 −0.0041
Treatment efficiency × important−0.0460 −0.1595***0.1224**−0.0509 0.1009**−0.0343
Water activity × important−0.0826 −0.1463***0.0847 −0.1204***0.1863***−0.0111
Odor intensity × important0.0111 −0.4065***0.1908*−0.2672***0.2217**−0.1751
Response time × important−0.0114 0.0172 0.0696 −0.0140 0.0278 0.1378*
Sewerage bills × important−0.0167***−0.0119**0.0196***−0.0046 0.0104*−0.0092
SD
of β
Inland flooding treatment capacity0.0027 0.0009 0.0021 0.0059 0.0001 0.0009
Treatment efficiency0.0113 0.0069 0.0010 0.0007 0.0071 0.0016
Water activity0.0310 0.1674**0.1488*0.1152 0.1330 0.1277
Odor intensity0.6416***0.6186***0.6542***0.5864***0.6310***0.6536***
Response time0.2294***0.2470***0.2380***0.2221***0.2237***0.2333***
Sewerage bills0.0518***0.0535***0.0543***0.0488***0.0547***0.0541***
Inland flooding treatment capacity × important0.0177 0.0207 0.0005 0.0256 0.0030 0.0034
Treatment efficiency × important0.0803 0.0859 0.0361 0.0013 0.0314 0.1004
Water activity × important0.3341***0.1053 0.1554 0.0927 0.0499 0.2867
Odor intensity × important0.2767 0.4028**0.0015 0.3635**0.3453 0.0189
Response time × important0.1522 0.0006 0.0198 0.1585**0.1669 0.2036
Sewerage bills × important0.0341**0.0253*0.0010 0.0358***0.0058 0.0316
No. of observations18,480
Log likelihood−5644.5−5624.5−5638.3−5638.6−5634.5−5647.1
Note: ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. 1 “Important” means the attribute that respondents considered the most-important wastewater service.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Jo, H.; Park, S.; Shin, J. Investigating Heterogeneous Consumer Preference for Sustainable Sewerage Asset Management: The Case of South Korea. Water 2023, 15, 2520. https://doi.org/10.3390/w15142520

AMA Style

Jo H, Park S, Shin J. Investigating Heterogeneous Consumer Preference for Sustainable Sewerage Asset Management: The Case of South Korea. Water. 2023; 15(14):2520. https://doi.org/10.3390/w15142520

Chicago/Turabian Style

Jo, Hanseul, Soyeong Park, and Jungwoo Shin. 2023. "Investigating Heterogeneous Consumer Preference for Sustainable Sewerage Asset Management: The Case of South Korea" Water 15, no. 14: 2520. https://doi.org/10.3390/w15142520

APA Style

Jo, H., Park, S., & Shin, J. (2023). Investigating Heterogeneous Consumer Preference for Sustainable Sewerage Asset Management: The Case of South Korea. Water, 15(14), 2520. https://doi.org/10.3390/w15142520

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop