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Social capital and efficiency of earthquake waste management in Japan
Author’s Accepted Manuscript Social capital and efficiency of earthquake waste management in Japan Kiyomi Kawamoto, Karl Kim
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To appear in: International Journal of Disaster Risk Reduction Received date: 23 July 2015 Revised date: 9 October 2015 Accepted date: 9 October 2015 Cite this article as: Kiyomi Kawamoto and Karl Kim, Social capital and efficiency of earthquake waste management in Japan, International Journal of Disaster Risk Reduction, http://dx.doi.org/10.1016/j.ijdrr.2015.10.003 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Social Capital and Efficiency of Earthquake Waste Management in Japan Kiyomi Kawamotoa*, Karl Kimb a
Regional Environmental Science, Regional Cooperation Course, Department of International and
Regional Studies, Hakodate, Hokkaido University of Education, 1-2 Hachiman-chou, Hakodate city, Hokkaido 040-8567, Japan. b
Department of Urban and Regional Planning and National Disaster Preparedness Training Center,
University of Hawaii at Manoa, 828 Fort Street Mall, Suite 320, Honolulu, Hawaii 96813, USA.
Abstract This paper examines how Social Capital (SC) affects the efficiency of waste management by citizens during and after earthquake disasters in Japan. The behavior of citizens is critical to understanding waste management and SC is an important element of community resilience. SC reveals the strength of relationships and the structure of networks in a community. There is, however, limited understanding about how SC affects waste management and other recovery activities, and how it changes over time. The coastal cities of Iwate and Miyagi prefectures were among the most heavily damaged communities during the Great East Japan Earthquake (GEJE) in March of 2011. Residents of these communities experienced many challenges related to waste management and recovery from the disaster. A web survey was used to collect data on waste management activities. Data Envelopment Analysis (DEA) with a Malmquist Productivity Index was used to analyze the 520 valid responses. This study defines inputs based on community and individual resilience attributes, including SC. Outputs are defined by the level of waste management activities, including collection, separation and transportation. Efficiency of waste management improved by the quality change in citizen skills and knowledge of earthquake waste management. The effect of quality change was larger than the quantity change in the operation rate. The quality change of earthquake waste management improved throughout the disaster. While the quality change of waste management persisted over the longer term recovery period the operation rate, however, declined.
Keywords: earthquake waste management, social capital, efficiency, Malmquist index, Great East Japan Earthquake
* Corresponding author. E-mail address: [email protected] (K. Kawamoto)
1. Introduction When large earthquakes occur, huge volumes of waste are typically generated. Brown et al. [1] provide a useful review of the literature on disaster waste management. They found that while community behavior is an essential factor in efficient waste management during non-disaster times there is limited understanding of waste management during and after disasters. A large volume of waste was generated from the Great East Japan Earthquake (GEJE). Following the disaster, the Japanese Ministry of the Environment released waste management guidelines [2]. Local governments also developed their own guidelines. While the Ministry of the Environment recommended this information be distributed to the communities, they did not clarify the role of citizens in disaster waste management. Community participation is particularly important to waste management, because public and private sector resources are limited and stretched during and after major disasters. Often the first priority is to save lives. During catastrophic events, the initial focus is on search and rescue, mass care, humanitarian relief, sheltering, and basic services. One way of stretching limited resources is to draw upon social capital. Social capital (SC) can be defined as both the nature of relationships and the structure of networks in a community. SC is an important component of community resilience [3, 4] . Aldrich [5] showed how networks and resources available through SC play a significant role in recovery during the post-disaster period. Joshi and Aoki [6] described how SC can improve policy implementation during recovery. Nakagawa and Shaw [7] showed that communities’ SC and leadership are the most critical elements to successful disaster recovery. Islam and Walkerden [8] described how SC contributes to the short-term and the long-term recovery from disasters. Although SC is recognized as a key factor in disaster recovery, few studies have focused on how SC improves waste management. This study also examines the changes in SC after the disaster, which is also not well understood. Waste management activities by citizens include the collection, separation, and transportation of waste. Performance measurements are needed to assess the efficiency of these activities. Data Envelopment Analysis (DEA) is a performance measurement technique for examining efficiency. In addition, DEA can be used to measure changes across time periods. Wo et al. [9] measured regional changes in energy efficiency using DEA. Camanho and Dyson [10] assessed the performance of banks using the Malmquist Index. One of the authors of this paper used the Malmquist Index to measure changes in the efficiency of municipal solid waste management [11]. The purpose of this study is to investigate how SC affects the efficiency of waste management by citizens following an earthquake disaster. We also consider efficiency measures over time to determine which changes in SC and waste management persist over the longer term recovery period.
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2. The Role of Social Capital 2.1 Social Capital Grube and Storr have pointed out that a community’s capacity for self-governance depends on SC [12]. This paper draws on Putnam’s [13] definition, whereby “SC refers to features of social organization, such as trust, norms, and networks that can improve the efficiency of society by facilitating coordinated actions.” The Cabinet Office of Japan [14] defines “social trust” as “general trust,” “norms” as “social participation,” and “networks” as “interaction and exchange” to measure Japanese SC. Accordingly, the terms “trust,” “social participation,” and “interaction and exchange” are used in this study. “Trust” is comprised of general and mutual trust. “Social participation” refers to participation in social activities. “Interaction and exchange” is measured in terms of the interactions with neighbors and social exchange. Table 1 displays the variable definitions of this study.
2.2 Social Capital in Community Resilience Resilience refers to the ability to resist impacts, absorb harmful forces and then to respond effectively and recover from disasters. Moreover, according to the Community and Regional Resilience Institute, resilience involves disciplines ranging from psychology to ecology [15]. This study focuses on how SC, an important feature of resilience affects the efficiency of earthquake waste management by citizens. Community resilience is a process linking specific capacities (resources with dynamic attributes) to adaptation after a disturbance [3]. Norris et al. have described how key attributes of communities contribute to resilience. According to Carpenter, social networks contribute to greater community resilience from all types of disasters [16]. Abramson et al. [17] have shown that resilience depends on a community’s and individual’s attributes, as well as access to social resources. As such, community and individual resilience attributes can be grouped into four categories: i) social capital, ii) economic capital, iii) political capital, and iv) human capital. In this study, access to social resources was replaced by the access to earthquake waste management, and Abramson et al.’s concepts were applied to earthquake waste management using community and individual level attributes. Fig. 1 shows the conceptual framework of the relationship between SC, resilience, and disaster waste management. The inputs are based on a community’s and individual’s resilience attributes, as well as SC, and the outputs are based on the levels of earthquake waste management activities (collection, separation and transportation). The disaster recovery potential is defined as the potential for recovery by residents following a disaster. This study includes an assessment of the disaster recovery potential, as proposed by Ishibashi et al. [18], and was used as a substitute index for human capital. In this study, the possibility of infrastructure development was measured based on the availability of space for storage sites around residential properties. In the case of some cities, local governments plan to use 3
public spaces like urban parks as storage sites. However, because of the volume of waste generated, there are not enough large public open space areas to accommodate the waste, hence some cities plan to use private spaces, like fields or amusement parks. The availability of private open space largely depends on the economic situation of the areas. Therefore, this factor was used as a substitute index for economic and political capital.
3. Study Areas 3.1 Case study cities The communities examined in this study include the 27 coastal cities of Iwate and Miyagi prefectures in Japan. Fig. 2 shows the cities included in this study. These cities suffered extensive damage from the GEJE. Because of the magnitude of this event, residents had considerable experience in managing debris caused by the earthquake and tsunami. The disaster generated a mix of debris that included contaminated radioactive waste from the Fukushima nuclear power plant. Because citizens were not typically involved in the handling of radioactive waste, Fukushima prefecture was excluded from this study.
3.2 Earthquake Waste Table 2 shows the categories of disaster waste [19]. There are three types of disaster waste: i) earthquake waste, ii) tsunami waste, and iii) evacuation waste. This study focuses on earthquake waste (i.e., household effects waste and earthquake rubble) and tsunami waste (i.e., water-soaked waste, waste generated from structures which collapsed because of the tsunami, tsunami generated sediment and marine waste). Automobiles and boating vessels were not included in this study. Fig. 3 illustrates the waste management activities following the earthquake in Japan. Citizens and communities participated in collection, separation, and transportation activates during the early stages of the recovery from the earthquake. This paper focuses on the main activities of earthquake waste management. Informal temporary storage sites were often provided n vacant lots or on the shoulders of roads near homes to facilitate the cleanup and repair of damaged properties. Formal temporary storage sites were provided in parks and other public spaces. An illustrative diagram of the temporal sequence of activities for Sendai is contained in Fig.3. Temporary storage sites were designated by the Sendai government on the fifth day after the earthquake. Fig. 4 shows photos of temporary storage sites.
4. Methodology 4.1 Data Collection Data were collected with a web-based survey administered in July of 2014. The target respondents 4
were males and females over the age 20 years who met the following criteria: i) have lived for over four years in the case study cities (in order to focus on members of communities before the GEJE.); ii) were residents of case study cities a week after the GEJE (because they were likely to have participated in the early stages of earthquake waste management); and iii) lived within 50 km away of the coastline. The survey was administered by a professional web survey company. The sampling procedure called for the collection of equal numbers of each age and gender group in the case study areas. Five age classes (20s, 30s, 40s, 50s and 60s and over) and two gender groups (Male and Female) were used, with each class consisting of 52 respondents. A total of 520 valid responses were collected in this study. The survey instrument included questions using a five level scale with five as the highest value and one as the lowest. Because questions referred to the extent and nature of damage caused by the earthquake, consent was obtained prior to administering the survey. Migration from these areas to other communities increased because of the extensive damage caused by the disaster. The number of valid responses for each city differed.
4.2 Efficiency Change Measurement Data Envelopment Analysis (DEA) is a non-parametric linear programming method used to measure the efficiency of Decision Making Units (DMUs) [20]. The DMU can be used to convert inputs into outputs from which performance can be evaluated [21]. Multiple inputs and outputs are considered for each DMU, and a DEA-based Malmquist Index was used to estimate the efficiency of waste management over time. The Malmquist Index measures productivity changes over time. The productivity measured by distance functions. The index was originally developed by Malmquist [22] in 1953 and has improved over time. In 1994, Fare et al. [23] extended these concepts by applying an input-oriented index to the geometric mean of the Malmquist Index proposed by Caves et al. in 1982 [24]. The distance function is based on the DMU’s use of inputs Xt to produce outputs Yt in time period t. The input distance, D, function is D (Xt, Yt). The Malmquist Index, M, is shown as follows: [
] (1)
Technical efficiency change (EC) and technology change (TC) are estimated by rewriting (1) as follows: [
] (2)
5
[
] (3)
M >1 captures the progress in the total factor productivity of the DMU from time period t to t+1, while M<1 shows a decay in productivity. EC is also known as the “frontier productivity index,” and shows the relative distance between frontiers. Therefore, EC denotes the change of the operation rate. TC is the shift in the technology frontier between the time periods. TC, therefore, denotes quality change. In this study, t is 2011, the year that the GEJE occurred, and t+1 is the post-disaster time period (2014 was used). Data from two different time periods were collected.
4.3 Decision Making Units This study used six DMUs representing the level of SC and disaster damage. Earthquake waste management activities differ depending on the extent and nature of damage. The SC levels are based on the average scores of three components: trust, interaction and exchange, and social participation. The scores of the two time periods were averaged, then divided by the standard deviation, and then grouped into two levels of SC: high and low. Damage data were based on reported waste volumes per person, averaged and divided by the standard deviation, then grouped into three levels of waste: high, medium, and low. Table 3 presents the data values in the analysis, while Table 4 shows the distribution for each DMU by levels of damage and social capital.
4.4 Calculation of Input Data Five input and two output models were constructed in this study.
4.4.1 Disaster Recovery Potential Disaster recovery potential of individual i, Di, is shown as follows: D𝑖
A𝑖 +
𝑖
+ R 𝑖 + P𝑖 4 (4)
where, A𝑖 𝑖
Disaster prevention preparedness of individual 𝑖 during non − disaster time ; Disaster experience of individual 𝑖;
R𝑖
Recovery intention of individual 𝑖;
P𝑖
Residence continuity possibility of individual 𝑖. Distance is measured from the coast to
individual i’s house, 6
with 7
A𝑖= ∑ A𝑖𝑗 7 𝑗=
(5) where, A𝑖𝑗 𝑗
Disaster prevention preparedness factors of individual 𝑖 during non − disaster time 1…7 ;
A𝑖
Knowledge of potential danger of waste fire;
A𝑖
Knowledge of pests and odor associated with waste;
A𝑖3
Knowledge of household waste collection by the local government during disaster time;
A𝑖4
Separation of household waste by the rule at non − disaster time;
A𝑖5
ransportion of household waste to the drop − off site by the rule at non − disaster time;
A𝑖6
Generation of large − sized waste according to the rule at non − disaster time;
A𝑖7
Reduction measures for earthquake waste,
with, moreover, R𝑖
∑ R 𝑖𝑗 2 𝑗=
(6) where, R 𝑖𝑗
Recovery intention factors of individual 𝑖 𝑗
12 ;
R𝑖
Local attachment;
R𝑖
Intention of stay at the current place of residence.
4.4.2 SC SC (trust) of individual i, Ti, is shown as follows: 3 𝑖
∑
𝑖𝑗
3
𝑗=
(7) where, 𝑖𝑗
rust factors of individual 𝑖 𝑗
1…3 ;
𝑖
rust for residents of the whole city;
𝑖
rust for neighbors;
𝑖3
rust for friends and acquaintances
and SC (interaction and exchange) of individual i, AEi, is represented by:
7
3
A
∑A
𝑖
𝑖𝑗
3
𝑗=
(8) where, A
𝑖𝑗
Interaction and exchange factors of ndividual 𝑖 𝑗
A
𝑖
Interaction with neighbors;
A
𝑖
Number of acquaintances in the neighborhood;
A
𝑖3
Interaction with friends and acquaintances,
1…3 ;
and SC (social participation) of individual i, Si, is measured by: 4
S𝑖
∑ S𝑖𝑗 4 𝑗=
(9) where, S𝑖𝑗
Social participation factors of individual 𝑖 𝑗
1…4 ;
S𝑖
Participation to the community activities in the region;
S𝑖
Participation to the activities of regional protection in the region;
S𝑖3
Participation to the individual activities beyond the region;
S𝑖4
Participation to the activities with local government beyond the region.
4.4.3 Possibility of infrastructure development Possibility of infrastructure development around individual i, PIi, and is shown as follows: PI𝑖
∑ PI𝑖𝑗 2 𝑗=
(10) where, PI𝑖𝑗
Possibility of infrastructure development factors around individual 𝑖 𝑗
PI𝑖
Informal temporary storage sites;
PI𝑖
Formal temporary storage sites and waste storage sites.
12 ;
4.5 Calculation of Output Data The output is measured as the access level to temporary storage sites. Seventy percent of useable responses were provided by the residents of Sendai in this study. As mentioned previously, in Sendai, formal temporary storage sites were created by the local government on the fifth day after the GEJE. Therefore, this study divided access levels based on the availability of informal temporary storage sites within four days after the disaster and formal temporary storage sites from the fifth day after the 8
disaster. The earthquake waste management activities for citizens included collection, separation and transportation activities. Different stakeholders exhibit varying levels of risk reduction activity. Jain [25] analyzed stakeholder actions reducing disaster risk in a large scale infrastructure development, and showed that different stakeholders had varying degrees of influence in each project phase. Iwata et al. [26] found that public rather than private mitigation contributed to greater reduction of the damage resulting from natural disasters. Nakayachi and Ozaki [27] observed that the trust ratings of risk managers improved when they voluntarily shared information with the general public during disasters. Based on these findings, this study analyzed which types of cooperative action were most effective in promoting waste management outcomes during disaster recovery. The level of earthquake waste management of individual i, Mi, is shown as follows: M𝑖
M𝑖𝑎𝑚𝑗 + M𝑖𝑏𝑚𝑗 (11)
where, M𝑖𝑎
Management level toward informal temporary storage site of individual 𝑖 within
four days; M𝑖𝑏
Management level toward formal temporary storage sites of individual 𝑖 from the fifth
day; M𝑖𝑚
Kinds of earthquake waste management 𝑚
1…3 ;
m1 is collection, m2 is separation and m3 is transportation. M𝑖𝑗
ypes of cooperators 𝑗
1…7 ;
j1 is no cooperator, j2 is families and relatives, j3 is neighbors, j4 is friends and acquaintances, j5 is volunteers from external regions, j6 is local governmental agencies, and j7 is governmental agencies from external regions.
5. Results and Findings The results are contained in Table 5. The results show how SC affects the efficiency of earthquake waste management, and efficiency changes over the longer term recovery period. All Malmquist index values were shown to be larger than 1. This means that the efficiency of earthquake waste management in communities improved during the post-disaster period. The Malmquist index is a function of both
the technical efficiency change (EC) and the technology change (TC). The study focused specifically on EC>1.100 and TC>1.100 to estimate the improvements in earthquake waste management within the case study communities. The High SC group consisted of those individuals in the elderly age group, while the Low SC group was individuals in the young and middle age groups.
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5.1 Technical Efficiency Change (EC) 5.1.1 Collection The EC of the high SC group increased during the post-disaster period. This was especially the
case when those individuals in the elderly age group with high levels of disaster damage cooperated with volunteers from external regions (EC=1.119) and governmental agencies from external regions (EC=1.174). Many government staff members from cities outside the region assisted with waste management after the GEJE. Those in the elderly age group learned how to cooperate and create networks with those from external regions to collect waste throughout the disaster period (during and after), and thus the operation rate of the earthquake waste collection improved. The EC of the high SC group with medium disaster damage increased (EC=1.093, 1.056, 1.074, 1.006, 1.028, 1.015, 1.023). On the EC of the low SC group with medium disaster damage, on the other hand, decreased (EC=0.954, 0.954, 0.973, 0.905, 0.992, 0.952, 0.968). The EC of the low SC group with low disaster damage decreased (EC=0.948, 0.948, 0.933, 0.908,
0.911, 0.893, 0.876) during the post-disaster period. While those in the elderly age group with medium levels of disaster damage improved their rates of collection, those in the young and middle age groups with medium to low disaster damage, did not experience changes in the rate of collection. 5.1.2 Separation The EC of the high SC group increased during the post-disaster period. This is especially the case
for those in the elderly age group with high levels of disaster damage who cooperated with volunteers from external regions (EC=1.184) and governmental agencies from external regions (EC=1.254). It was reported that volunteers from external regions helped separate personal items, such as, photographs from the earthquake waste. Members of the elderly age group learned how to cooperate with those from the external regions to separate waste throughout the disaster period (during and after). The EC of the low SC group with high disaster damage increased, especially when those individuals in the young and middle age group cooperated with families or relatives (EC =1.116) and neighbors (EC =1.115). The earthquake waste included valuable personal items, so citizens needed to identify and separate valuable items from other waste. Individuals in the young and middle age group, as a result of this process, learned how to cooperate with other people involved with disaster waste management. 5.1.3 Transportation The EC of the high SC group increased during the post-disaster period. Especially when those in
the elderly age group with high disaster damage cooperated with volunteers from the external regions (EC=1.181) and governmental agencies from the external regions (EC=1.174). The EC of the low SC group with high disaster damage increased, especially when those in the 10
young and middle age group cooperated with their neighbors (EC =1.137). Citizens transported earthquake waste with their cars to the temporary storage site after the GEJE, even though cars and gasoline were in limited supply. Those in the elderly age group learned how to cooperate and share limited resources with those from the external regions, while those in the young and middle age group learned to cooperate with neighbors during the recovery process. The EC of all SC group with low disaster damage tended to decrease in the post-disaster period. In such cases, citizens did not feel the need to cooperate or create networks, therefore did not develop SC during the time of the disaster.
5.2 Technology Change (TC) All TC increased during the post-disaster period for all damage levels and all SC groups (TC>1). Most TC was shown to have a specific progressed value of TC>1.100. The frontier of earthquake waste management shifted in the post-disaster period, which means that the quality of community and individual earthquake waste management, in terms of citizens’ skills, knowledge, and SC, improved. Usually citizens’ skills and knowledge in the collection, separation, and transportation phases during periods of non-disasters is less than the skills and knowledge during periods of disaster. Skills and knowledge were shown to improve over the three year recovery period. Citizens obtained skills and knowledge regarding earthquake waste management through their experience during the disaster and this has persisted over the longer term recovery period.
6. Conclusions In previous studies it has been shown that the efficiency of waste management tends to change after the disaster. It depends on the change of the operation rate, in terms of human capital, economic capital and infrastructure. However, we found that the efficiency of earthquake waste management also improves because of the quality change in earthquake waste management, in terms of skills and knowledge. The effect of quality change was larger than that of the change in the operation rate. Additionally, we found that the quality change in earthquake waste management persists over the longer term recovery period, although the operation rate declined. This study showed how SC affects the efficiency of earthquake waste management and the efficiency changes for the longer term recovery period. Three findings emerged. First, the operation rate of earthquake waste management improved by cooperation and network creation especially in communities with high levels of damage. Moreover, the quality of earthquake waste management, in terms of citizens’ skills and knowledge, increased throughout the recovery period. We believe that the quality of earthquake waste management can be improved with enhanced training on cooperation, networking and strengthening social capital before a disaster occurs. 11
Second, the most cooperative partners depended SC particularly in communities with high levels of damage. The level of cooperation, moreover, varied by age group. When those in the elderly age group cooperated with volunteers and governmental agencies from external regions, the operation rate increased. Moreover, when those in the young and middle age group cooperated with family, relatives and neighbors, the operation rate increased. In these places with high levels of damage, strong cooperation improves efficiency. Strong leadership and efforts to motivate increased cooperation can create increased efficiencies in waste management. We suggest greater dissemination of information regarding different approaches to cooperative behavior related to disaster waste management activities. A more systematic inventory of the types of behaviors and the sharing of resources for collection, separation, and transportation of waste is needed. Third, communities that experienced low levels of disaster damage exhibited declining efficiencies in waste management during the post-disaster period. Citizens in these communities did not feel the need to cooperate or create networks. It also points to the positive social effects that occur in heavily impacted communities. Perhaps all communities can better prepare for disasters and the management of waste through the strengthening of social capital before disaster strikes. This study shows the role and possibilities of SC in earthquake waste management by using data inclusive of two time periods. SC, however, decreases if it is not frequently used. How can communities maintain the SC over the long term? What conditions are required to sustain high performance of SC? To answer these questions, time series data should be collected and analyzed. Earthquake waste management not only requires social capital and cooperative behavior, but also the understanding and use of waste management equipment as well as the need to address safety concerns during cleanup operations. When with increased involvement of citizens in the handling of earthquake waste, health and safety matters must always be considered. These remain as topics for further study.
Acknowledgement This research was financially supported by The Environment Research and Technology Development Fund (No. 3K143015) of the Ministry of the Environment, Japan. The authors gratefully acknowledge the funding support that made it possible to complete this study.
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Table 1. Variable Definition SC
Definition Original definition: “SC refers to features of social organization, such as trust, norms, and networks that can improve the efficiency of society by facilitating coordinated actions.” Putnam (1993) Interpretation to measure social capital: “trust” as “trust”, “norms” as “social participation”, and “networks” as “interaction and exchange” The Cabinet Office of Japan (2003) Component
Index
Questions a)
Answers
Trust
General trust
1) Do you think you can trust residents of whole city?
5: Strongly agree 4: Agree 3: Neutral 2: Disagree 1: Strongly disagree
Mutual trust
2) Do you think you can trust neighbors? 3) Do you think you can trust friends and acquaintances?
5: Strongly agree 4: Agree 3: Neutral 2: Disagree 1: Strongly disagree
Interaction with neighbors
1) How often do you interact with neighbors?
5: I come and go between each houses daily 4: I talk with neighbors daily 3: I only say greetings 2: I only know the faces of neighbors 1: I do not have any interactions with my neighbors
2) How many neighbors do you know?
5: More than 20 people 4: 10-20 people 3: 5-10 people 2: Less than 4 people 1: 0 people
3) How often do you interact with friends and acquaintances?
5: One time and up a week 4: 2 or 3 times a month 3: One time a month 2: Several times a year 1: No interaction
Interaction and exchange
Social exchange
Social participation Participation in social activities
1) 2) How many times do you participate to the 5: One time and up a week community activities/ activities of regional 4: 2 or 3 times a month 3: One time a month protection in the region? b) 3) 4) How many times do you participate to the 2: Several times a year 1: No participation individual activities/activities with local government beyond the region? b)
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Disaster recovery The potential for recovery by residents after a disaster. Ishibashi et al. (2009) potential a) Component Questions Disaster prevention preparedness during non-disaster time
Answers
1) Do you know about the potential danger of fire if you leave earthquake waste around your house? 2) Do you know the pests and odors associate with the storage of earthquake waste, when waste is not treated quickly? 3) Do you know if the local government collects household waste during disasters?
5: I know this very well 4: I know this well 3: Neutral 2: I do not know this well 1: I do not know anything
4) Can you separate household waste according to the local government's rules at the non-disaster time? 5) Can you transport household waste to the drop-off site on waste collection day at the non-disaster time? 6) Can you generate large-sized waste items according to local government rules at the nondisaster time?
5: I can do this very well 4: I can do this well 3: Neutral 2: I can not do this well 1: I can not do anything
7) What measures do you take to reduce earthquake waste?
5: I live far from the coast 4: I live in an earthquake-proof house 3: I fix the furniture 2: I reduce materials in the house 1: I do not do anything
Disaster experience
1) How much damage did you experience from 5: My family passed away or was the earthquake? injured 4: My house was destroyed and completely unlivable 3: A part of my house was destroyed 2: The furniture broke 1: I did not have any damage
Recovery intention
1) Do you like your current place of residence? 5: Strongly agree 2) Do you want to stay in your current place of 4: Agree residence? 3: Neutral 2: Disagree 1: Strongly disagree
Residence continuity possibility
1) What is the distance from the coast to your 5: Less than 1 km home? (Less than 15 minutes by foot) 4: About 1 km - less than 5 km (More than 15 minutes by foot, less than 10 minutes by car) 3: About 5 km - less than 10 km (About 10–15 minutes by car) 2: About 10 km - less than 20 km (About 15–30 minutes by car) 1: More than 20 km (More than 30 minutes by car)
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Possibility of infrastructure development
Space availability of storage sites around your current place of residence. Questions
a)
1) Do you think you can find space for an informal temporary storage site space around your current place? 2) Do you think you can find space for a formal temporary storage site and waste storage site around your current place?
Answers 5: strongly agree 4: agree 3: neutral 2: disagree 1: strongly disagree
Waste Management Targeted waste management is collection, separation and transportation. Overall quantity change shows as technical efficiency change, and overall quality change shows as technology change. a)
Component
Questions
Collection
1)2) How much disaster waste can you collect 5: I can collect all toward informal/formal temporally storage sites 4: I can make space only living and c) traffic by collection with each cooperator? 3. I can make space only living by collection 2: I can collect only dangerous materials 1: I can not collect anything
Separation
1)2) How much disaster waste can you 5: I can separate all separate on informal/formal temporally storage 4: I can separate only recyclable materials sites with each cooperator? c) 3. I can separate only valued personal goods 2: I can separate only dangerous materials 1: I can not separate anything
Transportation
1)2) How much disaster waste can you transport toward informal/formal temporally storage site with each cooperator? c) 1: No cooperator 2: families and relatives 3: Neighbors 4: Friends and acquaintances 5: Volunteers from external regions 6: Local governmental agencies 7: Governmental agencies from external regions
Disaster Damage
Answers
5: I can transport all 4: I can make space only living and traffic by transportation 3. I can make space only living by transportation 2: I can transport only dangerous materials 1: I can not transport anything
Disaster damage was classified by using disaster waste volume per person for each city.
a) Questions were asked about disaster and post-disaster time. b) Questions were asked about each activities. c) Questions were asked about informal (within 4 days) and formal temporary storage site (after 5th days) case.
17
Fig. 1 Conceptual Framework of Relationships among Social Capital, Resilience and Disaster Waste Management
18
Fig. 2 Cities included in Study
Table 2. Categories of Disaster Waste Category Household effects waste Earthquake
Earthquake rubble Automobiles Tsunami-soaked waste Tsunami collapsed waste
Tsunami
Tsunami sediment Marine products
Summary Waste such as household effects destroyed, damaged due to earthquake Collapsed houses due to earthquake Waste soaked with sea water in areas damaged but not devastated by tsunami Collapsed houses and drenched with sea water due to tsunami Sediment accumulated on land due to tsunami Marine products, processed marine products transformed into waste due to disaster
Automobiles, vessels, Large- sized items, Concrete, Vegetation and Others General evacuation waste
General waste generated from evacuation shelter emitted and managed in a non-ordinary way due to the difficulty in securing lifelines
Medical waste
Medical waste generated from medical institutions, nursing homes, evacuation shelters
Evacuation
Sources: Asari M et al. (2013) , Japan Society of Material Cycles and Waste Management (2012) Notes: targeted waste in this study
19
Great East Japan Earthquake March 11,2011
Waste from disaster area
Collection/ Transportation/ Separation
Open: March 15, 2011 Close: May 10, 2011 Informal temporary storage site (ex: Open space beside houses)
Collection/ Transportation/ Separation
Formal temporary storage site
Primary waste storage site
Secondary waste storage site
Waste plant
Collection/Transportation/Separation Collection/Transportation/Separation From May 10, 2011(After closed formal temporary storage site) To September 30, 2011 Legend :
Citizens and the community can participate
Note1: Time schedule is for the case of Sendai (2011). Note2: City government support Start of evacuation waste collection: March 12, 2011 Start of household waste collection: March 15,2011 Start of household waste collection (Large size waste and recyclable waste): March 29, 2011 Start of earthquake waste individual collection (flooded area): March 24, 2011 Start of earthquake waste individual collection (elderly household): May 23, 2011 Sources: Asari M et al. (2013), Handout by Sendai city government (2014)
Fig. 3 Earthquake Waste Management by Citizens and Communities
Informal temporary storage site
Formal temporary storage site
Sources: Archive materials of Great East Japan Earthquake (Kesennuma city) Photo archives of Great East Japan Earthquake (Sendai city)
Fig.4 Temporary Storage Site
20
Table 3. Actual Data Value Class
SC
Disaster Damage
5 stage evaluation
b)
Frequency (%)
Data range
Standardization range
SD
c)
High
Male(60s and up) Female(50s and 60s and up)
30.000
2.760-2.924 a)b)
Low
Male(20s, 30s ,40s and 50s) Female(20s,30s and 40s)
70.000
2.476-2.519 a)b)
High
Ofunato, Kesennuma, Higashimatsushima,Tanohata, Kamaishi, Minamisanriku, Ishinomaki, Onagawa, Yamada, Otsuchi, Noda, Yamamoto and Rikuzentakata
82.746
18.558-63.605(t)/Person
Medium
Shiogama, Kuji, Tagajyo, Fudai, Iwaizumi, Matsushima, Natori, Iwanuma, Miyako, Shichigahama and Watari
16.624
2.284-14.579(t)/Person (-0.969)-(-0.165)
4.366
Rifu, Hirono and Sendai
0.630
0.500-1.293(t)/Person (-1.086)-(-1.034)
0.416
Low a)
Target individual (SC: Age group) (Disaster Damage: city of residence)
Average of 3 components
c)
0.677-1.622
0.104
(-1.222)-(-0.110) 0.063
0.095-3.042
12.969
Average=0, SD=1
Table 4. Distribution of DMUs by Damage and Social Capital
Disaster DMU Damage class 1 2 3 4 5 6
High High Medium Medium Low Low
The Frequency SC class number of (%) cases High Low High Low High Low
20 31 26 59 110 274
3.846 5.962 5.000 11.346 21.154 52.692
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Table 5. Technical Efficiency Change (EC) and Technology Change (TC) for Earthquake Waste Management Technical efficiency change (EC) a) Cooperators 1 2 3 SCH 4 5 6 7 1 2 3 SCL 4 5 6 7 a) EC>1.100
DH 1.015 1.069 1.002 1 1.119 1.033 1.174 1 1.005 1.028 1 1 1 1
Collection DM 1.093 1.056 1.074 1.006 1.028 1.015 1.023 0.954 0.954 0.973 0.905 0.992 0.952 0.968
DL 0.963 0.998 0.926 0.935 0.975 0.891 0.993 1 1 0.947 0.98 0.904 0.951 0.899
Transportation DH DM 1.008 0.93 1.021 1 1 1 1.008 0.987 1.181 1.042 1.017 1.066 1.174 1.023 1 0.91 1.099 0.946 1.137 0.977 1.058 0.979 1 0.969 1 0.968 1 0.968
DH 1.21 1.161 1.222 1.242 1.119 1.226 1.189 1.153 1.15 1.143 1.237 1.122 1.195 1.118
Collection DM 1.139 1.128 1.17 1.208 1.169 1.249 1.21 1.115 1.057 1.048 1.175 1.042 1.114 1.097
DL 1.056 1.045 1.113 1.159 1.081 1.202 1.13 1.097 1.092 1.071 1.113 1.121 1.151 1.161
Separation DM 1.257 1.216 1.248 1.233 1.243 1.272 1.207 1.174 1.125 1.161 1.175 1.102 1.154 1.104
DL 1.157 1.136 1.241 1.242 1.16 1.26 1.148 1.098 1.099 1.143 1.107 1.171 1.119 1.169
Transportation DH DM 1.324 1.283 1.259 1.226 1.263 1.251 1.276 1.256 1.144 1.156 1.233 1.187 1.213 1.21 1.273 1.195 1.236 1.129 1.179 1.103 1.217 1.08 1.138 1.044 1.153 1.068 1.132 1.083
DL 1.18 1.162 1.214 1.219 1.116 1.194 1.186 1.15 1.133 1.124 1.147 1.104 1.107 1.161
DH 1.228 1.241 1.224 1.242 1.252 1.266 1.396 1.153 1.156 1.175 1.237 1.122 1.195 1.118
Collection DM 1.245 1.192 1.256 1.215 1.202 1.268 1.238 1.063 1.008 1.019 1.063 1.034 1.061 1.062
Malmquist Index Separation DL DH DM 1.056 1.284 1.257 1.045 1.313 1.216 1.072 1.301 1.248 1.086 1.338 1.233 1.126 1.43 1.277 1.128 1.324 1.271 1.132 1.455 1.208 1.04 1.439 1.151 1.035 1.35 1.095 0.999 1.422 1.145 1.011 1.386 1.116 1.022 1.187 1.081 1.028 1.225 1.13 1.017 1.179 1.077
DL 1.114 1.133 1.15 1.162 1.131 1.122 1.14 1.098 1.099 1.083 1.085 1.059 1.065 1.051
Transportation DH DM 1.335 1.193 1.286 1.226 1.263 1.251 1.286 1.239 1.352 1.206 1.255 1.265 1.424 1.237 1.273 1.087 1.358 1.068 1.341 1.078 1.288 1.056 1.138 1.012 1.153 1.034 1.132 1.049
DL 1.062 1.089 1.109 1.136 1.095 1.117 1.144 1.081 1.069 1.065 1.042 1.037 1.052 1.017
DL 1 1 0.963 0.937 1.042 0.938 1.002 0.948 0.948 0.933 0.908 0.911 0.893 0.876
DH 1 1.039 1 1.007 1.184 1 1.254 1.179 1.116 1.115 1.093 1 1 1
Separation DM 1 1 1 1 1.027 0.999 1.001 0.981 0.973 0.986 0.949 0.981 0.979 0.976
DL 0.9 0.937 0.913 0.931 0.982 0.936 0.965 0.94 0.944 0.947 0.908 0.939 0.95 0.876
Technology change (TC) b) Cooperators 1 2 3 SCH 4 5 6 7 1 2 3 SCL 4 5 6 7 b) EC>1.100
SCH
SCL
Cooperators 1 2 3 4 5 6 7 1 2 3 4 5 6 7
Legend: SC classes SCH: high SCL: low Disaster damage classes DH: high DM: medium DL: low
DH 1.284 1.263 1.301 1.328 1.208 1.324 1.16 1.221 1.21 1.275 1.268 1.187 1.225 1.179
Cooperators 1: No cooperator (Base line) 2: Families and relatives 3: Neighbors 4: Friends and acquaintances 5: Volunteers from external regions 6: Local governmental agencies 7: Governmental agencies from external regions
22
www.elsevier.com/locate/ijdr
PII: DOI: Reference:
S2212-4209(15)30107-2 http://dx.doi.org/10.1016/j.ijdrr.2015.10.003 IJDRR280
To appear in: International Journal of Disaster Risk Reduction Received date: 23 July 2015 Revised date: 9 October 2015 Accepted date: 9 October 2015 Cite this article as: Kiyomi Kawamoto and Karl Kim, Social capital and efficiency of earthquake waste management in Japan, International Journal of Disaster Risk Reduction, http://dx.doi.org/10.1016/j.ijdrr.2015.10.003 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Social Capital and Efficiency of Earthquake Waste Management in Japan Kiyomi Kawamotoa*, Karl Kimb a
Regional Environmental Science, Regional Cooperation Course, Department of International and
Regional Studies, Hakodate, Hokkaido University of Education, 1-2 Hachiman-chou, Hakodate city, Hokkaido 040-8567, Japan. b
Department of Urban and Regional Planning and National Disaster Preparedness Training Center,
University of Hawaii at Manoa, 828 Fort Street Mall, Suite 320, Honolulu, Hawaii 96813, USA.
Abstract This paper examines how Social Capital (SC) affects the efficiency of waste management by citizens during and after earthquake disasters in Japan. The behavior of citizens is critical to understanding waste management and SC is an important element of community resilience. SC reveals the strength of relationships and the structure of networks in a community. There is, however, limited understanding about how SC affects waste management and other recovery activities, and how it changes over time. The coastal cities of Iwate and Miyagi prefectures were among the most heavily damaged communities during the Great East Japan Earthquake (GEJE) in March of 2011. Residents of these communities experienced many challenges related to waste management and recovery from the disaster. A web survey was used to collect data on waste management activities. Data Envelopment Analysis (DEA) with a Malmquist Productivity Index was used to analyze the 520 valid responses. This study defines inputs based on community and individual resilience attributes, including SC. Outputs are defined by the level of waste management activities, including collection, separation and transportation. Efficiency of waste management improved by the quality change in citizen skills and knowledge of earthquake waste management. The effect of quality change was larger than the quantity change in the operation rate. The quality change of earthquake waste management improved throughout the disaster. While the quality change of waste management persisted over the longer term recovery period the operation rate, however, declined.
Keywords: earthquake waste management, social capital, efficiency, Malmquist index, Great East Japan Earthquake
* Corresponding author. E-mail address: [email protected] (K. Kawamoto)
1. Introduction When large earthquakes occur, huge volumes of waste are typically generated. Brown et al. [1] provide a useful review of the literature on disaster waste management. They found that while community behavior is an essential factor in efficient waste management during non-disaster times there is limited understanding of waste management during and after disasters. A large volume of waste was generated from the Great East Japan Earthquake (GEJE). Following the disaster, the Japanese Ministry of the Environment released waste management guidelines [2]. Local governments also developed their own guidelines. While the Ministry of the Environment recommended this information be distributed to the communities, they did not clarify the role of citizens in disaster waste management. Community participation is particularly important to waste management, because public and private sector resources are limited and stretched during and after major disasters. Often the first priority is to save lives. During catastrophic events, the initial focus is on search and rescue, mass care, humanitarian relief, sheltering, and basic services. One way of stretching limited resources is to draw upon social capital. Social capital (SC) can be defined as both the nature of relationships and the structure of networks in a community. SC is an important component of community resilience [3, 4] . Aldrich [5] showed how networks and resources available through SC play a significant role in recovery during the post-disaster period. Joshi and Aoki [6] described how SC can improve policy implementation during recovery. Nakagawa and Shaw [7] showed that communities’ SC and leadership are the most critical elements to successful disaster recovery. Islam and Walkerden [8] described how SC contributes to the short-term and the long-term recovery from disasters. Although SC is recognized as a key factor in disaster recovery, few studies have focused on how SC improves waste management. This study also examines the changes in SC after the disaster, which is also not well understood. Waste management activities by citizens include the collection, separation, and transportation of waste. Performance measurements are needed to assess the efficiency of these activities. Data Envelopment Analysis (DEA) is a performance measurement technique for examining efficiency. In addition, DEA can be used to measure changes across time periods. Wo et al. [9] measured regional changes in energy efficiency using DEA. Camanho and Dyson [10] assessed the performance of banks using the Malmquist Index. One of the authors of this paper used the Malmquist Index to measure changes in the efficiency of municipal solid waste management [11]. The purpose of this study is to investigate how SC affects the efficiency of waste management by citizens following an earthquake disaster. We also consider efficiency measures over time to determine which changes in SC and waste management persist over the longer term recovery period.
2
2. The Role of Social Capital 2.1 Social Capital Grube and Storr have pointed out that a community’s capacity for self-governance depends on SC [12]. This paper draws on Putnam’s [13] definition, whereby “SC refers to features of social organization, such as trust, norms, and networks that can improve the efficiency of society by facilitating coordinated actions.” The Cabinet Office of Japan [14] defines “social trust” as “general trust,” “norms” as “social participation,” and “networks” as “interaction and exchange” to measure Japanese SC. Accordingly, the terms “trust,” “social participation,” and “interaction and exchange” are used in this study. “Trust” is comprised of general and mutual trust. “Social participation” refers to participation in social activities. “Interaction and exchange” is measured in terms of the interactions with neighbors and social exchange. Table 1 displays the variable definitions of this study.
2.2 Social Capital in Community Resilience Resilience refers to the ability to resist impacts, absorb harmful forces and then to respond effectively and recover from disasters. Moreover, according to the Community and Regional Resilience Institute, resilience involves disciplines ranging from psychology to ecology [15]. This study focuses on how SC, an important feature of resilience affects the efficiency of earthquake waste management by citizens. Community resilience is a process linking specific capacities (resources with dynamic attributes) to adaptation after a disturbance [3]. Norris et al. have described how key attributes of communities contribute to resilience. According to Carpenter, social networks contribute to greater community resilience from all types of disasters [16]. Abramson et al. [17] have shown that resilience depends on a community’s and individual’s attributes, as well as access to social resources. As such, community and individual resilience attributes can be grouped into four categories: i) social capital, ii) economic capital, iii) political capital, and iv) human capital. In this study, access to social resources was replaced by the access to earthquake waste management, and Abramson et al.’s concepts were applied to earthquake waste management using community and individual level attributes. Fig. 1 shows the conceptual framework of the relationship between SC, resilience, and disaster waste management. The inputs are based on a community’s and individual’s resilience attributes, as well as SC, and the outputs are based on the levels of earthquake waste management activities (collection, separation and transportation). The disaster recovery potential is defined as the potential for recovery by residents following a disaster. This study includes an assessment of the disaster recovery potential, as proposed by Ishibashi et al. [18], and was used as a substitute index for human capital. In this study, the possibility of infrastructure development was measured based on the availability of space for storage sites around residential properties. In the case of some cities, local governments plan to use 3
public spaces like urban parks as storage sites. However, because of the volume of waste generated, there are not enough large public open space areas to accommodate the waste, hence some cities plan to use private spaces, like fields or amusement parks. The availability of private open space largely depends on the economic situation of the areas. Therefore, this factor was used as a substitute index for economic and political capital.
3. Study Areas 3.1 Case study cities The communities examined in this study include the 27 coastal cities of Iwate and Miyagi prefectures in Japan. Fig. 2 shows the cities included in this study. These cities suffered extensive damage from the GEJE. Because of the magnitude of this event, residents had considerable experience in managing debris caused by the earthquake and tsunami. The disaster generated a mix of debris that included contaminated radioactive waste from the Fukushima nuclear power plant. Because citizens were not typically involved in the handling of radioactive waste, Fukushima prefecture was excluded from this study.
3.2 Earthquake Waste Table 2 shows the categories of disaster waste [19]. There are three types of disaster waste: i) earthquake waste, ii) tsunami waste, and iii) evacuation waste. This study focuses on earthquake waste (i.e., household effects waste and earthquake rubble) and tsunami waste (i.e., water-soaked waste, waste generated from structures which collapsed because of the tsunami, tsunami generated sediment and marine waste). Automobiles and boating vessels were not included in this study. Fig. 3 illustrates the waste management activities following the earthquake in Japan. Citizens and communities participated in collection, separation, and transportation activates during the early stages of the recovery from the earthquake. This paper focuses on the main activities of earthquake waste management. Informal temporary storage sites were often provided n vacant lots or on the shoulders of roads near homes to facilitate the cleanup and repair of damaged properties. Formal temporary storage sites were provided in parks and other public spaces. An illustrative diagram of the temporal sequence of activities for Sendai is contained in Fig.3. Temporary storage sites were designated by the Sendai government on the fifth day after the earthquake. Fig. 4 shows photos of temporary storage sites.
4. Methodology 4.1 Data Collection Data were collected with a web-based survey administered in July of 2014. The target respondents 4
were males and females over the age 20 years who met the following criteria: i) have lived for over four years in the case study cities (in order to focus on members of communities before the GEJE.); ii) were residents of case study cities a week after the GEJE (because they were likely to have participated in the early stages of earthquake waste management); and iii) lived within 50 km away of the coastline. The survey was administered by a professional web survey company. The sampling procedure called for the collection of equal numbers of each age and gender group in the case study areas. Five age classes (20s, 30s, 40s, 50s and 60s and over) and two gender groups (Male and Female) were used, with each class consisting of 52 respondents. A total of 520 valid responses were collected in this study. The survey instrument included questions using a five level scale with five as the highest value and one as the lowest. Because questions referred to the extent and nature of damage caused by the earthquake, consent was obtained prior to administering the survey. Migration from these areas to other communities increased because of the extensive damage caused by the disaster. The number of valid responses for each city differed.
4.2 Efficiency Change Measurement Data Envelopment Analysis (DEA) is a non-parametric linear programming method used to measure the efficiency of Decision Making Units (DMUs) [20]. The DMU can be used to convert inputs into outputs from which performance can be evaluated [21]. Multiple inputs and outputs are considered for each DMU, and a DEA-based Malmquist Index was used to estimate the efficiency of waste management over time. The Malmquist Index measures productivity changes over time. The productivity measured by distance functions. The index was originally developed by Malmquist [22] in 1953 and has improved over time. In 1994, Fare et al. [23] extended these concepts by applying an input-oriented index to the geometric mean of the Malmquist Index proposed by Caves et al. in 1982 [24]. The distance function is based on the DMU’s use of inputs Xt to produce outputs Yt in time period t. The input distance, D, function is D (Xt, Yt). The Malmquist Index, M, is shown as follows: [
] (1)
Technical efficiency change (EC) and technology change (TC) are estimated by rewriting (1) as follows: [
] (2)
5
[
] (3)
M >1 captures the progress in the total factor productivity of the DMU from time period t to t+1, while M<1 shows a decay in productivity. EC is also known as the “frontier productivity index,” and shows the relative distance between frontiers. Therefore, EC denotes the change of the operation rate. TC is the shift in the technology frontier between the time periods. TC, therefore, denotes quality change. In this study, t is 2011, the year that the GEJE occurred, and t+1 is the post-disaster time period (2014 was used). Data from two different time periods were collected.
4.3 Decision Making Units This study used six DMUs representing the level of SC and disaster damage. Earthquake waste management activities differ depending on the extent and nature of damage. The SC levels are based on the average scores of three components: trust, interaction and exchange, and social participation. The scores of the two time periods were averaged, then divided by the standard deviation, and then grouped into two levels of SC: high and low. Damage data were based on reported waste volumes per person, averaged and divided by the standard deviation, then grouped into three levels of waste: high, medium, and low. Table 3 presents the data values in the analysis, while Table 4 shows the distribution for each DMU by levels of damage and social capital.
4.4 Calculation of Input Data Five input and two output models were constructed in this study.
4.4.1 Disaster Recovery Potential Disaster recovery potential of individual i, Di, is shown as follows: D𝑖
A𝑖 +
𝑖
+ R 𝑖 + P𝑖 4 (4)
where, A𝑖 𝑖
Disaster prevention preparedness of individual 𝑖 during non − disaster time ; Disaster experience of individual 𝑖;
R𝑖
Recovery intention of individual 𝑖;
P𝑖
Residence continuity possibility of individual 𝑖. Distance is measured from the coast to
individual i’s house, 6
with 7
A𝑖= ∑ A𝑖𝑗 7 𝑗=
(5) where, A𝑖𝑗 𝑗
Disaster prevention preparedness factors of individual 𝑖 during non − disaster time 1…7 ;
A𝑖
Knowledge of potential danger of waste fire;
A𝑖
Knowledge of pests and odor associated with waste;
A𝑖3
Knowledge of household waste collection by the local government during disaster time;
A𝑖4
Separation of household waste by the rule at non − disaster time;
A𝑖5
ransportion of household waste to the drop − off site by the rule at non − disaster time;
A𝑖6
Generation of large − sized waste according to the rule at non − disaster time;
A𝑖7
Reduction measures for earthquake waste,
with, moreover, R𝑖
∑ R 𝑖𝑗 2 𝑗=
(6) where, R 𝑖𝑗
Recovery intention factors of individual 𝑖 𝑗
12 ;
R𝑖
Local attachment;
R𝑖
Intention of stay at the current place of residence.
4.4.2 SC SC (trust) of individual i, Ti, is shown as follows: 3 𝑖
∑
𝑖𝑗
3
𝑗=
(7) where, 𝑖𝑗
rust factors of individual 𝑖 𝑗
1…3 ;
𝑖
rust for residents of the whole city;
𝑖
rust for neighbors;
𝑖3
rust for friends and acquaintances
and SC (interaction and exchange) of individual i, AEi, is represented by:
7
3
A
∑A
𝑖
𝑖𝑗
3
𝑗=
(8) where, A
𝑖𝑗
Interaction and exchange factors of ndividual 𝑖 𝑗
A
𝑖
Interaction with neighbors;
A
𝑖
Number of acquaintances in the neighborhood;
A
𝑖3
Interaction with friends and acquaintances,
1…3 ;
and SC (social participation) of individual i, Si, is measured by: 4
S𝑖
∑ S𝑖𝑗 4 𝑗=
(9) where, S𝑖𝑗
Social participation factors of individual 𝑖 𝑗
1…4 ;
S𝑖
Participation to the community activities in the region;
S𝑖
Participation to the activities of regional protection in the region;
S𝑖3
Participation to the individual activities beyond the region;
S𝑖4
Participation to the activities with local government beyond the region.
4.4.3 Possibility of infrastructure development Possibility of infrastructure development around individual i, PIi, and is shown as follows: PI𝑖
∑ PI𝑖𝑗 2 𝑗=
(10) where, PI𝑖𝑗
Possibility of infrastructure development factors around individual 𝑖 𝑗
PI𝑖
Informal temporary storage sites;
PI𝑖
Formal temporary storage sites and waste storage sites.
12 ;
4.5 Calculation of Output Data The output is measured as the access level to temporary storage sites. Seventy percent of useable responses were provided by the residents of Sendai in this study. As mentioned previously, in Sendai, formal temporary storage sites were created by the local government on the fifth day after the GEJE. Therefore, this study divided access levels based on the availability of informal temporary storage sites within four days after the disaster and formal temporary storage sites from the fifth day after the 8
disaster. The earthquake waste management activities for citizens included collection, separation and transportation activities. Different stakeholders exhibit varying levels of risk reduction activity. Jain [25] analyzed stakeholder actions reducing disaster risk in a large scale infrastructure development, and showed that different stakeholders had varying degrees of influence in each project phase. Iwata et al. [26] found that public rather than private mitigation contributed to greater reduction of the damage resulting from natural disasters. Nakayachi and Ozaki [27] observed that the trust ratings of risk managers improved when they voluntarily shared information with the general public during disasters. Based on these findings, this study analyzed which types of cooperative action were most effective in promoting waste management outcomes during disaster recovery. The level of earthquake waste management of individual i, Mi, is shown as follows: M𝑖
M𝑖𝑎𝑚𝑗 + M𝑖𝑏𝑚𝑗 (11)
where, M𝑖𝑎
Management level toward informal temporary storage site of individual 𝑖 within
four days; M𝑖𝑏
Management level toward formal temporary storage sites of individual 𝑖 from the fifth
day; M𝑖𝑚
Kinds of earthquake waste management 𝑚
1…3 ;
m1 is collection, m2 is separation and m3 is transportation. M𝑖𝑗
ypes of cooperators 𝑗
1…7 ;
j1 is no cooperator, j2 is families and relatives, j3 is neighbors, j4 is friends and acquaintances, j5 is volunteers from external regions, j6 is local governmental agencies, and j7 is governmental agencies from external regions.
5. Results and Findings The results are contained in Table 5. The results show how SC affects the efficiency of earthquake waste management, and efficiency changes over the longer term recovery period. All Malmquist index values were shown to be larger than 1. This means that the efficiency of earthquake waste management in communities improved during the post-disaster period. The Malmquist index is a function of both
the technical efficiency change (EC) and the technology change (TC). The study focused specifically on EC>1.100 and TC>1.100 to estimate the improvements in earthquake waste management within the case study communities. The High SC group consisted of those individuals in the elderly age group, while the Low SC group was individuals in the young and middle age groups.
9
5.1 Technical Efficiency Change (EC) 5.1.1 Collection The EC of the high SC group increased during the post-disaster period. This was especially the
case when those individuals in the elderly age group with high levels of disaster damage cooperated with volunteers from external regions (EC=1.119) and governmental agencies from external regions (EC=1.174). Many government staff members from cities outside the region assisted with waste management after the GEJE. Those in the elderly age group learned how to cooperate and create networks with those from external regions to collect waste throughout the disaster period (during and after), and thus the operation rate of the earthquake waste collection improved. The EC of the high SC group with medium disaster damage increased (EC=1.093, 1.056, 1.074, 1.006, 1.028, 1.015, 1.023). On the EC of the low SC group with medium disaster damage, on the other hand, decreased (EC=0.954, 0.954, 0.973, 0.905, 0.992, 0.952, 0.968). The EC of the low SC group with low disaster damage decreased (EC=0.948, 0.948, 0.933, 0.908,
0.911, 0.893, 0.876) during the post-disaster period. While those in the elderly age group with medium levels of disaster damage improved their rates of collection, those in the young and middle age groups with medium to low disaster damage, did not experience changes in the rate of collection. 5.1.2 Separation The EC of the high SC group increased during the post-disaster period. This is especially the case
for those in the elderly age group with high levels of disaster damage who cooperated with volunteers from external regions (EC=1.184) and governmental agencies from external regions (EC=1.254). It was reported that volunteers from external regions helped separate personal items, such as, photographs from the earthquake waste. Members of the elderly age group learned how to cooperate with those from the external regions to separate waste throughout the disaster period (during and after). The EC of the low SC group with high disaster damage increased, especially when those individuals in the young and middle age group cooperated with families or relatives (EC =1.116) and neighbors (EC =1.115). The earthquake waste included valuable personal items, so citizens needed to identify and separate valuable items from other waste. Individuals in the young and middle age group, as a result of this process, learned how to cooperate with other people involved with disaster waste management. 5.1.3 Transportation The EC of the high SC group increased during the post-disaster period. Especially when those in
the elderly age group with high disaster damage cooperated with volunteers from the external regions (EC=1.181) and governmental agencies from the external regions (EC=1.174). The EC of the low SC group with high disaster damage increased, especially when those in the 10
young and middle age group cooperated with their neighbors (EC =1.137). Citizens transported earthquake waste with their cars to the temporary storage site after the GEJE, even though cars and gasoline were in limited supply. Those in the elderly age group learned how to cooperate and share limited resources with those from the external regions, while those in the young and middle age group learned to cooperate with neighbors during the recovery process. The EC of all SC group with low disaster damage tended to decrease in the post-disaster period. In such cases, citizens did not feel the need to cooperate or create networks, therefore did not develop SC during the time of the disaster.
5.2 Technology Change (TC) All TC increased during the post-disaster period for all damage levels and all SC groups (TC>1). Most TC was shown to have a specific progressed value of TC>1.100. The frontier of earthquake waste management shifted in the post-disaster period, which means that the quality of community and individual earthquake waste management, in terms of citizens’ skills, knowledge, and SC, improved. Usually citizens’ skills and knowledge in the collection, separation, and transportation phases during periods of non-disasters is less than the skills and knowledge during periods of disaster. Skills and knowledge were shown to improve over the three year recovery period. Citizens obtained skills and knowledge regarding earthquake waste management through their experience during the disaster and this has persisted over the longer term recovery period.
6. Conclusions In previous studies it has been shown that the efficiency of waste management tends to change after the disaster. It depends on the change of the operation rate, in terms of human capital, economic capital and infrastructure. However, we found that the efficiency of earthquake waste management also improves because of the quality change in earthquake waste management, in terms of skills and knowledge. The effect of quality change was larger than that of the change in the operation rate. Additionally, we found that the quality change in earthquake waste management persists over the longer term recovery period, although the operation rate declined. This study showed how SC affects the efficiency of earthquake waste management and the efficiency changes for the longer term recovery period. Three findings emerged. First, the operation rate of earthquake waste management improved by cooperation and network creation especially in communities with high levels of damage. Moreover, the quality of earthquake waste management, in terms of citizens’ skills and knowledge, increased throughout the recovery period. We believe that the quality of earthquake waste management can be improved with enhanced training on cooperation, networking and strengthening social capital before a disaster occurs. 11
Second, the most cooperative partners depended SC particularly in communities with high levels of damage. The level of cooperation, moreover, varied by age group. When those in the elderly age group cooperated with volunteers and governmental agencies from external regions, the operation rate increased. Moreover, when those in the young and middle age group cooperated with family, relatives and neighbors, the operation rate increased. In these places with high levels of damage, strong cooperation improves efficiency. Strong leadership and efforts to motivate increased cooperation can create increased efficiencies in waste management. We suggest greater dissemination of information regarding different approaches to cooperative behavior related to disaster waste management activities. A more systematic inventory of the types of behaviors and the sharing of resources for collection, separation, and transportation of waste is needed. Third, communities that experienced low levels of disaster damage exhibited declining efficiencies in waste management during the post-disaster period. Citizens in these communities did not feel the need to cooperate or create networks. It also points to the positive social effects that occur in heavily impacted communities. Perhaps all communities can better prepare for disasters and the management of waste through the strengthening of social capital before disaster strikes. This study shows the role and possibilities of SC in earthquake waste management by using data inclusive of two time periods. SC, however, decreases if it is not frequently used. How can communities maintain the SC over the long term? What conditions are required to sustain high performance of SC? To answer these questions, time series data should be collected and analyzed. Earthquake waste management not only requires social capital and cooperative behavior, but also the understanding and use of waste management equipment as well as the need to address safety concerns during cleanup operations. When with increased involvement of citizens in the handling of earthquake waste, health and safety matters must always be considered. These remain as topics for further study.
Acknowledgement This research was financially supported by The Environment Research and Technology Development Fund (No. 3K143015) of the Ministry of the Environment, Japan. The authors gratefully acknowledge the funding support that made it possible to complete this study.
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[19] Asari M, Sakai S, Yoshioka T, Tojo Y, Tasaki T, Takigami H, Watanabe K. Strategy for separation and treatment of disaster waste: a manual for earthquake and tsunami disaster waste management in Japan. Journal of Material Cycles and Waste Management 2013; 15(3): 290-299. [20] Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. European Journal of Operational Research 1978; 2:429–44. [21] Cooper WW, Seiford, Tone K. Introduction to data envelopment analysis and its uses, New York: Springer; 2006, 21-39. [22] Malmquist S. Index numbers and indifference surfaces. Trabajos de Estadistica 1953; 4:209-42. [23] Fare R, Grosskopf F, Lindgren B, Roos P. Productivity developments in Swedish hospitals: a Malmquist output index approach. In: Charnes A, Cooper WW, Lewin AY, Seiford LM (eds) Data Envelopment Analysis: theory, methodology and applications. Boston: Kluwer Academic Publishers; 1994, 253–72. [24] Caves DW, Christensen LR, Diewert WE. The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica 1982; 50(6):1393–414. [25] Jain G. The role of private sector for reducing disaster risk in large scale infrastructure and real estate development: Case of Delhi. International Journal of Disaster Risk Reduction, in press. [26] Iwata K, Ito Y, Managi S. Public and private mitigation for natural disaster in Japan. . International Journal of Disaster Risk Reduction 2014; 7: 39-50. [27] Nakayachi K, Ozaki T. A method to improve trust in disaster risk managers: Voluntary action to share a common fate. International Journal of Disaster Risk Reduction 2014; 10: 59-66.
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Table 1. Variable Definition SC
Definition Original definition: “SC refers to features of social organization, such as trust, norms, and networks that can improve the efficiency of society by facilitating coordinated actions.” Putnam (1993) Interpretation to measure social capital: “trust” as “trust”, “norms” as “social participation”, and “networks” as “interaction and exchange” The Cabinet Office of Japan (2003) Component
Index
Questions a)
Answers
Trust
General trust
1) Do you think you can trust residents of whole city?
5: Strongly agree 4: Agree 3: Neutral 2: Disagree 1: Strongly disagree
Mutual trust
2) Do you think you can trust neighbors? 3) Do you think you can trust friends and acquaintances?
5: Strongly agree 4: Agree 3: Neutral 2: Disagree 1: Strongly disagree
Interaction with neighbors
1) How often do you interact with neighbors?
5: I come and go between each houses daily 4: I talk with neighbors daily 3: I only say greetings 2: I only know the faces of neighbors 1: I do not have any interactions with my neighbors
2) How many neighbors do you know?
5: More than 20 people 4: 10-20 people 3: 5-10 people 2: Less than 4 people 1: 0 people
3) How often do you interact with friends and acquaintances?
5: One time and up a week 4: 2 or 3 times a month 3: One time a month 2: Several times a year 1: No interaction
Interaction and exchange
Social exchange
Social participation Participation in social activities
1) 2) How many times do you participate to the 5: One time and up a week community activities/ activities of regional 4: 2 or 3 times a month 3: One time a month protection in the region? b) 3) 4) How many times do you participate to the 2: Several times a year 1: No participation individual activities/activities with local government beyond the region? b)
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Disaster recovery The potential for recovery by residents after a disaster. Ishibashi et al. (2009) potential a) Component Questions Disaster prevention preparedness during non-disaster time
Answers
1) Do you know about the potential danger of fire if you leave earthquake waste around your house? 2) Do you know the pests and odors associate with the storage of earthquake waste, when waste is not treated quickly? 3) Do you know if the local government collects household waste during disasters?
5: I know this very well 4: I know this well 3: Neutral 2: I do not know this well 1: I do not know anything
4) Can you separate household waste according to the local government's rules at the non-disaster time? 5) Can you transport household waste to the drop-off site on waste collection day at the non-disaster time? 6) Can you generate large-sized waste items according to local government rules at the nondisaster time?
5: I can do this very well 4: I can do this well 3: Neutral 2: I can not do this well 1: I can not do anything
7) What measures do you take to reduce earthquake waste?
5: I live far from the coast 4: I live in an earthquake-proof house 3: I fix the furniture 2: I reduce materials in the house 1: I do not do anything
Disaster experience
1) How much damage did you experience from 5: My family passed away or was the earthquake? injured 4: My house was destroyed and completely unlivable 3: A part of my house was destroyed 2: The furniture broke 1: I did not have any damage
Recovery intention
1) Do you like your current place of residence? 5: Strongly agree 2) Do you want to stay in your current place of 4: Agree residence? 3: Neutral 2: Disagree 1: Strongly disagree
Residence continuity possibility
1) What is the distance from the coast to your 5: Less than 1 km home? (Less than 15 minutes by foot) 4: About 1 km - less than 5 km (More than 15 minutes by foot, less than 10 minutes by car) 3: About 5 km - less than 10 km (About 10–15 minutes by car) 2: About 10 km - less than 20 km (About 15–30 minutes by car) 1: More than 20 km (More than 30 minutes by car)
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Possibility of infrastructure development
Space availability of storage sites around your current place of residence. Questions
a)
1) Do you think you can find space for an informal temporary storage site space around your current place? 2) Do you think you can find space for a formal temporary storage site and waste storage site around your current place?
Answers 5: strongly agree 4: agree 3: neutral 2: disagree 1: strongly disagree
Waste Management Targeted waste management is collection, separation and transportation. Overall quantity change shows as technical efficiency change, and overall quality change shows as technology change. a)
Component
Questions
Collection
1)2) How much disaster waste can you collect 5: I can collect all toward informal/formal temporally storage sites 4: I can make space only living and c) traffic by collection with each cooperator? 3. I can make space only living by collection 2: I can collect only dangerous materials 1: I can not collect anything
Separation
1)2) How much disaster waste can you 5: I can separate all separate on informal/formal temporally storage 4: I can separate only recyclable materials sites with each cooperator? c) 3. I can separate only valued personal goods 2: I can separate only dangerous materials 1: I can not separate anything
Transportation
1)2) How much disaster waste can you transport toward informal/formal temporally storage site with each cooperator? c) 1: No cooperator 2: families and relatives 3: Neighbors 4: Friends and acquaintances 5: Volunteers from external regions 6: Local governmental agencies 7: Governmental agencies from external regions
Disaster Damage
Answers
5: I can transport all 4: I can make space only living and traffic by transportation 3. I can make space only living by transportation 2: I can transport only dangerous materials 1: I can not transport anything
Disaster damage was classified by using disaster waste volume per person for each city.
a) Questions were asked about disaster and post-disaster time. b) Questions were asked about each activities. c) Questions were asked about informal (within 4 days) and formal temporary storage site (after 5th days) case.
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Fig. 1 Conceptual Framework of Relationships among Social Capital, Resilience and Disaster Waste Management
18
Fig. 2 Cities included in Study
Table 2. Categories of Disaster Waste Category Household effects waste Earthquake
Earthquake rubble Automobiles Tsunami-soaked waste Tsunami collapsed waste
Tsunami
Tsunami sediment Marine products
Summary Waste such as household effects destroyed, damaged due to earthquake Collapsed houses due to earthquake Waste soaked with sea water in areas damaged but not devastated by tsunami Collapsed houses and drenched with sea water due to tsunami Sediment accumulated on land due to tsunami Marine products, processed marine products transformed into waste due to disaster
Automobiles, vessels, Large- sized items, Concrete, Vegetation and Others General evacuation waste
General waste generated from evacuation shelter emitted and managed in a non-ordinary way due to the difficulty in securing lifelines
Medical waste
Medical waste generated from medical institutions, nursing homes, evacuation shelters
Evacuation
Sources: Asari M et al. (2013) , Japan Society of Material Cycles and Waste Management (2012) Notes: targeted waste in this study
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Great East Japan Earthquake March 11,2011
Waste from disaster area
Collection/ Transportation/ Separation
Open: March 15, 2011 Close: May 10, 2011 Informal temporary storage site (ex: Open space beside houses)
Collection/ Transportation/ Separation
Formal temporary storage site
Primary waste storage site
Secondary waste storage site
Waste plant
Collection/Transportation/Separation Collection/Transportation/Separation From May 10, 2011(After closed formal temporary storage site) To September 30, 2011 Legend :
Citizens and the community can participate
Note1: Time schedule is for the case of Sendai (2011). Note2: City government support Start of evacuation waste collection: March 12, 2011 Start of household waste collection: March 15,2011 Start of household waste collection (Large size waste and recyclable waste): March 29, 2011 Start of earthquake waste individual collection (flooded area): March 24, 2011 Start of earthquake waste individual collection (elderly household): May 23, 2011 Sources: Asari M et al. (2013), Handout by Sendai city government (2014)
Fig. 3 Earthquake Waste Management by Citizens and Communities
Informal temporary storage site
Formal temporary storage site
Sources: Archive materials of Great East Japan Earthquake (Kesennuma city) Photo archives of Great East Japan Earthquake (Sendai city)
Fig.4 Temporary Storage Site
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Table 3. Actual Data Value Class
SC
Disaster Damage
5 stage evaluation
b)
Frequency (%)
Data range
Standardization range
SD
c)
High
Male(60s and up) Female(50s and 60s and up)
30.000
2.760-2.924 a)b)
Low
Male(20s, 30s ,40s and 50s) Female(20s,30s and 40s)
70.000
2.476-2.519 a)b)
High
Ofunato, Kesennuma, Higashimatsushima,Tanohata, Kamaishi, Minamisanriku, Ishinomaki, Onagawa, Yamada, Otsuchi, Noda, Yamamoto and Rikuzentakata
82.746
18.558-63.605(t)/Person
Medium
Shiogama, Kuji, Tagajyo, Fudai, Iwaizumi, Matsushima, Natori, Iwanuma, Miyako, Shichigahama and Watari
16.624
2.284-14.579(t)/Person (-0.969)-(-0.165)
4.366
Rifu, Hirono and Sendai
0.630
0.500-1.293(t)/Person (-1.086)-(-1.034)
0.416
Low a)
Target individual (SC: Age group) (Disaster Damage: city of residence)
Average of 3 components
c)
0.677-1.622
0.104
(-1.222)-(-0.110) 0.063
0.095-3.042
12.969
Average=0, SD=1
Table 4. Distribution of DMUs by Damage and Social Capital
Disaster DMU Damage class 1 2 3 4 5 6
High High Medium Medium Low Low
The Frequency SC class number of (%) cases High Low High Low High Low
20 31 26 59 110 274
3.846 5.962 5.000 11.346 21.154 52.692
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Table 5. Technical Efficiency Change (EC) and Technology Change (TC) for Earthquake Waste Management Technical efficiency change (EC) a) Cooperators 1 2 3 SCH 4 5 6 7 1 2 3 SCL 4 5 6 7 a) EC>1.100
DH 1.015 1.069 1.002 1 1.119 1.033 1.174 1 1.005 1.028 1 1 1 1
Collection DM 1.093 1.056 1.074 1.006 1.028 1.015 1.023 0.954 0.954 0.973 0.905 0.992 0.952 0.968
DL 0.963 0.998 0.926 0.935 0.975 0.891 0.993 1 1 0.947 0.98 0.904 0.951 0.899
Transportation DH DM 1.008 0.93 1.021 1 1 1 1.008 0.987 1.181 1.042 1.017 1.066 1.174 1.023 1 0.91 1.099 0.946 1.137 0.977 1.058 0.979 1 0.969 1 0.968 1 0.968
DH 1.21 1.161 1.222 1.242 1.119 1.226 1.189 1.153 1.15 1.143 1.237 1.122 1.195 1.118
Collection DM 1.139 1.128 1.17 1.208 1.169 1.249 1.21 1.115 1.057 1.048 1.175 1.042 1.114 1.097
DL 1.056 1.045 1.113 1.159 1.081 1.202 1.13 1.097 1.092 1.071 1.113 1.121 1.151 1.161
Separation DM 1.257 1.216 1.248 1.233 1.243 1.272 1.207 1.174 1.125 1.161 1.175 1.102 1.154 1.104
DL 1.157 1.136 1.241 1.242 1.16 1.26 1.148 1.098 1.099 1.143 1.107 1.171 1.119 1.169
Transportation DH DM 1.324 1.283 1.259 1.226 1.263 1.251 1.276 1.256 1.144 1.156 1.233 1.187 1.213 1.21 1.273 1.195 1.236 1.129 1.179 1.103 1.217 1.08 1.138 1.044 1.153 1.068 1.132 1.083
DL 1.18 1.162 1.214 1.219 1.116 1.194 1.186 1.15 1.133 1.124 1.147 1.104 1.107 1.161
DH 1.228 1.241 1.224 1.242 1.252 1.266 1.396 1.153 1.156 1.175 1.237 1.122 1.195 1.118
Collection DM 1.245 1.192 1.256 1.215 1.202 1.268 1.238 1.063 1.008 1.019 1.063 1.034 1.061 1.062
Malmquist Index Separation DL DH DM 1.056 1.284 1.257 1.045 1.313 1.216 1.072 1.301 1.248 1.086 1.338 1.233 1.126 1.43 1.277 1.128 1.324 1.271 1.132 1.455 1.208 1.04 1.439 1.151 1.035 1.35 1.095 0.999 1.422 1.145 1.011 1.386 1.116 1.022 1.187 1.081 1.028 1.225 1.13 1.017 1.179 1.077
DL 1.114 1.133 1.15 1.162 1.131 1.122 1.14 1.098 1.099 1.083 1.085 1.059 1.065 1.051
Transportation DH DM 1.335 1.193 1.286 1.226 1.263 1.251 1.286 1.239 1.352 1.206 1.255 1.265 1.424 1.237 1.273 1.087 1.358 1.068 1.341 1.078 1.288 1.056 1.138 1.012 1.153 1.034 1.132 1.049
DL 1.062 1.089 1.109 1.136 1.095 1.117 1.144 1.081 1.069 1.065 1.042 1.037 1.052 1.017
DL 1 1 0.963 0.937 1.042 0.938 1.002 0.948 0.948 0.933 0.908 0.911 0.893 0.876
DH 1 1.039 1 1.007 1.184 1 1.254 1.179 1.116 1.115 1.093 1 1 1
Separation DM 1 1 1 1 1.027 0.999 1.001 0.981 0.973 0.986 0.949 0.981 0.979 0.976
DL 0.9 0.937 0.913 0.931 0.982 0.936 0.965 0.94 0.944 0.947 0.908 0.939 0.95 0.876
Technology change (TC) b) Cooperators 1 2 3 SCH 4 5 6 7 1 2 3 SCL 4 5 6 7 b) EC>1.100
SCH
SCL
Cooperators 1 2 3 4 5 6 7 1 2 3 4 5 6 7
Legend: SC classes SCH: high SCL: low Disaster damage classes DH: high DM: medium DL: low
DH 1.284 1.263 1.301 1.328 1.208 1.324 1.16 1.221 1.21 1.275 1.268 1.187 1.225 1.179
Cooperators 1: No cooperator (Base line) 2: Families and relatives 3: Neighbors 4: Friends and acquaintances 5: Volunteers from external regions 6: Local governmental agencies 7: Governmental agencies from external regions
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