Farmers' risk perception of concentrated rural settlement development after the 5.12 Sichuan Earthquake

Habitat International 71 (2018) 169–176

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Habitat International journal homepage: www.elsevier.com/locate/habitatint

Farmers' risk perception of concentrated rural settlement development after the 5.12 Sichuan Earthquake

T

Yi Penga, Xiaoting Zhub,∗, Fuying Zhangb, Li Huanga, Jibin Xuea, Yelin Xuc a

School of Public Administration, Zhejiang University of Finance & Economics, Hangzhou, PR China School of Business Administration, Zhejiang University of Finance & Economics, Hangzhou, PR China c Department of Engineering Management, Zhejiang Sci-Tech University, Hangzhou, PR China b

A R T I C L E I N F O

A B S T R A C T

Keywords: Concentrated rural settlement (CRS) Post-disaster reconstruction Farmers' risk perception ANOVA The 5.12 Sichuan Earthquake China

Rural housing reconstruction is critical in realizing sustainable recovery. Concentrated rural settlement (CRS) was widely promoted under the context of new countryside construction after the 5.12 Sichuan Earthquake in 2008. Farmers' risk perception of CRS and their corresponding actions affect realizing sustainable recovery. However, few studies have attempted to comprehend farmers' risk perception of such practices, and the impact factors of risk perception remain unknown. Therefore, this study investigates farmers' risk perception of CRS development using four cases in the hardest earthquake-hit area. ANOVA is employed to explore the factors that influence risk perception of CRS development, and in-depth discussions are conducted to explore the reasons behind such perceptions. Potential measures are proposed to reduce relevant risk factors. This study's findings can help local governments in understanding the concerns of farmers toward CRS and in identifying suitable approaches to mitigate risks in order to realize the sustainability of CRS development. This study also provides references for local government to address the specialized concerns when developing CRS within both disaster and non-disaster context.

1. Introduction Concentrated rural settlement (CRS) development is vital to rural post-disaster recovery, as proven in the efforts made after the 5.12 Sichuan Earthquake. Scattered villages were clustered together to attain moderately concentrated accommodation through CRS development. Concentrated settlement is one of the prerequisites for improving rural public services along with the quantity and quality of public infrastructure (Zheng, 2014). In addition, appropriate concentrated settlement and good management measures can facilitate community diversity and prevention, strengthen social capital, and accelerate disaster recovery (Allenby & Fink, 2005; Dye, 2008; Glaeser, 1998). Compared with the resettlement among villages after disasters, CRS can reduce the cost of public infrastructure and services while preserving the existing social network to avoid tense social relations (Peng, 2013). Compared with in situ reconstruction, CRS maintains established land and social resources and facilitates the low-cost provision of public infrastructure and services (Peng, 2015). Therefore, CRS was promoted after the 5.12 Sichuan Earthquake, especially within the context of new countryside construction, which emphasized concentrated accommodation. However, CRS development faces various challenges, especially for

new countryside construction under normal conditions. These challenges have been investigated based on economic, societal, and environmental perspectives (Li, Long, Liu, & Tu, 2015; Long, Li, Liu, Woods, & Zou, 2012; Wu, Ann, & Shen, 2017). Unreasonable CRS planning may result in high economic costs (Yu, Xiong, Li, Liu, & Li, 2008). For example, CRS situated away from farmlands increase the cost of agricultural production (Long & Li, 2012). Farmers who reside in four-to five-story apartments often find it difficult to carry on with their former agricultural livelihood. Moreover, farmers face poor income growth with the lack of a sustained non-agricultural industry near the CRS site (Zheng, 2009; Zhang & Zhang, 2009). Therefore, the key problem of how to re-employ surplus rural labors remains for the CRS development (Long, Liu, Li, & Chen, 2010). Farmers who are accustomed to a dispersed settlement should adapt to new production processes and lifestyle. The sense of belonging and identity with the land and the community should be rebuilt, although social problems may arise during the process (Yu et al., 2008). Environmental problems also challenge CRS development. At present, rural China faces serious problems due to limited environmental provisions and public awareness compared with those in urban China (Wu, Ann, Shen, & Liu, 2014). Zheng (2014) reported that pollution is mainly

∗

Corresponding author. E-mail addresses: [email protected] (Y. Peng), [email protected] (X. Zhu), [email protected] (F. Zhang), [email protected] (L. Huang), [email protected] (J. Xue), [email protected] (Y. Xu). https://doi.org/10.1016/j.habitatint.2017.11.008 Received 23 May 2017; Received in revised form 1 November 2017; Accepted 21 November 2017 0197-3975/ © 2017 Elsevier Ltd. All rights reserved.

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Facts have proven that in situ reconstruction is the most cost-effective approach that can recover post-disaster production and daily living at the fastest possible time (Badri et al., 2006). Therefore, in-situ reconstruction is widely adopted in post-disaster reconstruction. However, it is argued to waste land resources, undermine livelihoods, and sustain poor living conditions (Peng, Shen, Shen, Lu, & Yuan, 2014b). In addition to security considerations, resettlement increases employment opportunities for farmers and allows them to gain better access to public services. Araya, Chotai, Komproe & Jong (2011) reported that the victims' quality of life significantly improved after resettlement. Yet, resettlement may result in unequal distribution of benefits and costs among relocated people, disrupted social network, and competition for limited resources, which generate resistance to resettlement (Arnall, 2014; Cronin & Guthrie, 2011; Oliver-Smith, 1991). Developing CRS in a village can increase resilience and provide a basis for sustainable recovery after natural disasters (Peng, 2015). Two approaches help deliver CRS: unified planning/self-reconstruction and unified planning/ unified-reconstruction (Peng, 2015). Unified planning is adopted to ensure better planning of the CRS site and housing layout. Self-reconstruction means that farmers reconstruct houses on the CRS site by themselves, whereas unified-reconstruction means that a village invites a professional construction company to conduct unified reconstruction. Zheng (2014) pointed out that CRS is the trend in rural reconstruction under the condition of new countryside construction in China. Guided by the policy of land consolidation in rural China, CRS has been actively promoted in rural areas after the 5.12 Sichuan Earthquake. At present, CRS is still a new concept; hence, its theory and implementation measures are not yet mature. This means that, in the process of CRS development, the economic, social, and ecological problems generated should be carefully investigated. The rural production ways and ecological space can be reshaped or even changed. Meanwhile, farmers participating in CRS spend most of their savings and also face changed production modes, which can increase their economic burden (Tan & Lu, 2014). Some farmers may lose their lands and may even lose their identities of farmers after CRS. This vague identity orientation affects the change of their lifestyle (Wang, Tian, Wang & Guo, 2011). For the new community, all living activities are concentrated in one area, which increases the ecological pressure. Whether disaster prevention and mitigation after CRS strengthens the community is still unknown, and this uncertainty can be a potential risk to villages and peasants (Wang, Tian, Ma, Su & Han, 2010; Wang et al., 2011; Li & Shen, 2011). Facing benefits and potential risk, it is critical to comprehend farmers' risk perception of CRS, which affect the implementation and sustainability objective of CRS in post-disaster reconstruction.

caused by household garbage, township industrial development, farming and animal husbandry, and rural tourism industry development during the CRS development process. Meanwhile, some studies have investigated the economic, social, and environmental problems of post-disaster reconstruction after the 5.12 Sichuan Earthquake. Tan and Lu (2014) verified that farmers spent resources for reconstruction, which increased their debt burden and vulnerability after the 5.12 Sichuan Earthquake. Fan (2015) validated that the lack of participation from local residents resulted in a misunderstanding between the farmers and the government, which triggered a series of social problems during the post-disaster reconstruction. Yang et al. (2014) affirmed that the ecological level remained unrecovered prior to the 5.12 Sichuan Earthquake despite the restoration of the ecological environment in 2013. Therefore, relevant stakeholders' implementation of the appropriate strategies is important during post-disaster reconstruction. Farmers' risk perception affects their reconstruction strategies and, eventually, the sustainable post-disaster reconstruction. Risk perception is defined as the perception of the identified risks that one may face (Bauer, 1960). Individual risk perception is crucial in determining the response of a person to natural hazards (Burn, 1999). Song and Kim (2013) confirmed that risk perception can weaken the risk severity of natural disasters. Rizalito (2016) highlighted the importance of understanding risk perception and response to natural disasters to ensure public participation in building resilience and increasing adaptive capacity. Farmers may take measures to reduce their exposure to future disaster risks if they have relevant risk perceptions. Therefore, understanding how farmers perceive the risks for developing and communicating reconstruction policies is advantageous (Hurley & Corotis, 2014). However, few studies have investigated farmers' risk perception of CRS after the 5.12 Sichuan Earthquake, which inhibits a thorough understanding of CRS reconstruction, potential problem solution, and sustainability achievement in China. Therefore, the current study investigates the factors that affect farmers' risk perception of CRS after the 5.12 Sichuan Earthquake. Section 2 provides a critical review of studies on farmer's risk perception and a solid basis is established for further analysis. Section 3 introduces the research method, which includes research logic, questionnaire design, and data collection. Section 4 presents the preliminary analysis and one-way analysis of variance to explore the impact factors of farmers' risk perception of CRS. Section 5 provides an in-depth discussion, and Section 6 concludes the research by specifying future research directions. 2. Literature review

2.2. Risk perception in disaster research 2.1. Rural housing reconstruction Risk perception is a hot topic in disaster management research (Butsch, Kraas, Namperumal, & Peters, 2016; Naomi, 2016; Walters & Gaillard, 2014). Traditional disaster management research see the physical world as an externality that causes damage to the human environment; thus, disaster management reduces the losses caused by disasters (Orhan, 2015). However, such an approach has shortcomings. Hence, contemporary approaches emphasize that pre-disaster policies not only result in the rationalization of resource allocation but also in increased investment efficiency for reducing risks. Risk perception plays a major role in effectively responding to disasters and facilitates decision-making in risk management and disaster mitigation (Lindell & Hwang, 2008; Lindell & Perry, 2000). Gangalal, Ryuichi, Ranjan, and Netra (2015) corroborated that large human casualties and the loss of properties in Nepal during natural disasters are caused by inadequate public awareness and technical knowledge in mitigating natural disasters. Song and Kim (2013) verified that risk perception can weaken the risk severity of natural disasters (e.g., storm and flood). Rizalito (2016) highlighted the importance of understanding risk perception and response to natural disasters from the social, economic, political,

Housing reconstruction is a top priority given that housing damage affects the lives of victims (Peng, 2015). Rural areas face more reconstruction disadvantages compared with urban areas due to insufficient infrastructure, lack of disaster mitigation education and social inequality (Peng, Shen, Tan, Tan, & Wang, 2013). Post-disaster reconstruction is a key link in natural disaster management, and aims to restore the community or society destroyed by natural disasters to its pre-disaster condition. Realizing the sustainability of housing reconstruction in developing countries is an important concern in light of the imbalanced development between urban and rural areas (Mileti, 1999). In situ reconstruction, resettlement, and CRS reconstruction are considered when rebuilding houses in rural areas. In situ reconstruction emphasizes the replacement of damaged houses with new ones on the original site (Jha, Barenstein, Phelps, Pittet, & Sena, 2010). Resettlement refers to the building of new houses on a new site, usually in another village with a lower risk of being hit by natural disasters (Badri, Asgary, Eftekhari, & Levy, 2006; Peng, Shen, Zhang, & Ochoa, 2014a). 170

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Table 1 The measurement of the risk perception. Category

Details

Scale

Category

Details

Scale

Economic

Agricultural output growth(E1) Non-agricultural output growth(E2) Public finance growth(E3) Infrastructure investment growth(E4) Electricity consumption growth(E5) Annual income growth(E6) Non-agricultural income growth(E7) Financial access(E8) Information access(E9) Population growth(E10) Employment skills (E11) Mismatch between living ways and production ways (E12) Plenty of farmland(En1) Plenty of ecological land (En2) Plenty of water resources(En3) Plenty of clean tap water(En4) Plenty of clean energy(En5) Recycling of domestic waste(En6) Waste disposal capacity(En7) Soil erosion(En8) Land degradation(En9) Excessive use of pesticides and fertilizers(En10)

1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5

Social

Higher education (above high school)(S1) Basic education (compulsory)(S2) Labor growth(S3) Elderly growth(S4) Public management of CRS(S5) Medicare coverage(S6) Poverty resulted by illness(S7) Pension(S8) Convenient traffic(S9) Entertainment satisfaction(S10) Poverty(S11) Income inequality(S12) Reasonable site selection(D1) Building safety(D2) Secondary disasters(D3) Plenty of emergency shelter(D4) Education of disaster mitigation and prevention(D5)

1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5 1–5

Environment

Disaster mitigation

Note:1 stands for extremely disagree, 2: disagree, 3: neutral, 4: agree,5: strongly agree.

perception of CRS and explores its influencing factors.

and cultural perspectives to ensure public participation in building resilience and increasing adaptive capacity. Understanding farmers' risk perception is critical in facilitating effective post-disaster reconstruction. Often, the decision-making behavior of farmers is affected by uncertain situations, such as a sudden disaster (Keller, Siegrist, & Gutscher, 2006; Solberg, Rossetto, & Joffe, 2010). Misperceptions of risk may result in different opinions among project team members, misallocation of resources, and incidents during post-disaster reconstruction (Ivensky, 2016). Biswas et al. (2015) validated that secondary disasters and increasing threats to agriculture provide farmers with opportunities to increase the sustainability of their livelihood. Understanding how farmers perceive the risks can help policymakers develop and deliver decisions (Hurley & Corotis, 2014). Identifying influencing factors is important in understanding risk perception (Yang, 2015). Research on disaster risk perception requires psychological and socio-cultural approaches. Jacoby and Kaplan (1972) attributed the constraints of risk perception to two dimensions: personal factors and external environment. In terms of personal factors, the risk perception of farmers is influenced by gender, age, educational level, family economic conditions, and personal risk preference. In terms of the external environment, loss over the years, regional cultural characteristics, planting techniques, and farmland irrigation conditions affect the risk perception of farmers. Jiang, Yao, Bond, Wang, and Huang (2011) affirmed that risk perception and precaution activity are related to the socio-demographic characteristics and vulnerability of inhabitants in disaster-affected zones. Sun (2006) confirmed that the risk perception of the public during a crisis is related to the characteristics of the incident and the individual, and that the interaction among these factors often leads to people's cognitive bias and under- or over-estimation of risks. Biswas et al. (2015) confirmed that several socio-economic factors, such as age, gender, livelihood, and level of education, generate influences on risk perceptions. The perspectives of pre-disaster periods should be expanded, and recovery practices should be implemented by integrating their consequences over risk mitigation (Orhan, 2015). Therefore, farmers' risk perception of CRS and their corresponding actions are crucial in realizing sustainable development after concentration. However, few studies have examined farmers' risk perception of CRS development and its influencing factors. This research gap inhibits the formulation of effective policies to improve CRS management and realize the sustainable development of CRS. Thus, the present study investigates farmers' risk

3. Research method 3.1. Research logic The present study investigates farmers' risk perception of CRS development. Preliminary risk factors are identified by reviewing existing studies on CRS and post-disaster reconstruction. Critical risk factors are identified through a questionnaire survey distributed to residents of four villages located in the hardest earthquake-hit area after the 5.12 Sichuan Earthquake. The comparison of farmers' risk perception of CRS is conducted among the four villages. ANOVA is employed to determine the critical impact factors of risk perception. Feasible measures are proposed to reduce corresponding disaster risks. 3.2. Questionnaire design The content of the questionnaire is divided into three parts. The first part includes the basic background information of the villages, such as location, terrain, characteristic industry, and CRS reconstruction methods. The second part comprises the demographic characteristics of the farmers, such as gender, age, education degree, years working outside, and the degree of building damage reported by each respondent. The third part focuses on the respondents' risk perception of CRS. A five-point Likert scale (5 for “strongly agree” and 1 for “strongly disagree”) is used to measure the significance perception of each risk factor. The risk factors are divided into four categories: economic, social, environmental, and disaster mitigation. Each category has several items to measure (e.g., 12 items measure the risk perception from an economic view, Table 1). The language used in the questionnaire corresponds to the dominant language of the target respondents, which is Chinese (Peng et al., 2013). Due attention is paid to minimize information loss during translation. 3.3. Data collection The data used in this study came from a questionnaire survey and field research conducted between July and August 2016. Wufu and Dongsheng Villages in Mianyang and Fuxing and Chuanmu Villages in Deyang were selected for the case studies because of their accessibility. 171

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Table 2 Background information of the case villages. Case

A: Wufu Village

B: Dongsheng Village

C: Fuxing Village

D: Chuanmu Village

Terrain Areas of land/cultivated land (unit: hectare) Population/households Labors Percentage of Migrant workers to labors Characteristic industry

Mountain areas 24738.9/538.9

Hilly areas 930/480

Plain areas 2200/1400

Mountain areas 8400/4200

1457/416 803 64.6%

970/330 540 40%

3120/1117 1500 10%

3523/1581 2100 45%

Aquaculture: giant salamander; Planting: Chinese goldthread Tourism: drifting 416

None

None

None

270

820

481

Unified planning; Self-reconstruction, unified planning; unified reconstruction

Unified planning; Self-reconstruction

Unified planning; Selfreconstruction

Unified planning; Unified reconstruction

Collapsed and severely damaged households CRS delivery approach

Table 3 Background information of the interviewees (N = 281). Case

A: Wufu Village

B:Dongsheng Village

Table 4 The average significance value of four classified risk perception of case villages. C: Fuxing Village

D: Chuanmu Village

Number of interviewees

50

40

95

96

Gender (%)

Male Female

44.00% 56.00%

62.50% 37.50%

44.21% 55.79%

58.33% 41.67%

Age (%)

16–24 25–40 41–60 61↑

22.00% 30.00% 46.00% 2.00%

25.00% 32.50% 35.00% 7.50%

26.32% 29.47% 35.79% 8.42%

10.42% 40.63% 40.63% 8.33%

Education level (%)

elementary↓ junior senior college↑

30.00% 34.00% 32.00% 4.00%

25.00% 27.50% 20.00% 27.50%

37.89% 33.68% 7.37% 21.05%

23.96% 26.04% 18.75% 31.25%

The year of working outside (%)

0 1–2 3–5 6↑

28.00% 14.00% 30.00% 28.00%

47.50% 12.50% 20.00% 20.00%

68.42% 15.79% 5.26% 10.53%

32.29% 33.33% 25.00% 9.38%

The damage degree of building (%)

Collapse Serious damaged Repair and reinforce

54.00% 42.00%

22.50% 37.50%

1.05% 86.32%

43.75% 47.92%

4.00%

40.00%

12.63%

8.33%

Village

Economic

Social

Environment

Disaster mitigation

Wufu Dongsheng Fuxing Chuanmu

2.28 2.24 1.95 2.46

2.44 2.43 2.44 2.36

2.15 2.12 2.03 2.29

1.72 1.86 1.92 2.36

demonstrating that the reliability of research questionnaire is good and can support further analysis. The farmers' risk perceptions of CRS in the four villages were compared across four categories (Table 4). The results confirm that the social risk perception in Wufu Village is the highest, which means they pay attention to social risk. Similar results are obtained for Dongsheng and Fuxing Villages. Disasters bring suffering to affected farmers so they desire good social forms. The affected farmers face a number of social problems once they lose their shelters. The scores of the risk perception of disaster mitigation in Wufu, Dongsheng, and Fuxing Villages are the lowest, whereas that in Chuanmu Village is high. Risk perception regarding disaster mitigation in Chuanmu Village is high because of its mountainous terrain; hence, landslides may occur after an earthquake and increase disaster risks. In addition, the average significance of risk perceptions in Chuanmu Village is higher than that in the other villages, and the possible reason is its location in a remote mountain district without any support industry. Such a situation contributes to various problems in economic, social, environmental, and disaster prevention aspects during the post-disaster reconstruction.

Table 2 presents the location and background information of the four villages. A total of 385 respondents were randomly selected in each village. A total of 281 valid responses were obtained, with a response rate of 72.99%. Table 3 summarizes the background information of the respondents.

4.2. Impact factors of risk perception ANOVA is conducted with SPSS software to analyze the relationship between impact factors and risk perception. The impact factors are classified into two categories: background characteristics of the villages and of the farmers. The characteristics of villages comprise location (V1), terrain (V2), characteristic industry (V3), and the CRS delivery approach (V4). The characteristics of farmers include gender (V5), age (V6), education level (V7), years of working outside (V8), and degree of building damage (V9). It was analyzed whether these factors affect the farmers' risk perception of CRS development with the significance testing value at 0.05. Factors with the significance value of less than 0.05 are considered insignificantly influential to risk perception (Tibesigawa, Hao, & Karumuna, 2017). Table 5 shows the analysis results. As can be seen, location, terrain, characteristic industry, and the CRS delivery approach have significant relationships with the vast majorities of risk perception of CRS development. The location of the village significantly affects farmers' risk

4. Findings and discussions 4.1. Preliminary analysis Reliability analysis was used to identify whether the measures for a particular variable have reliable internal consistency, which is measured by Cronbach's coefficient α. Data are considered reliable if α is greater than 0.7 (Shen, Liu, Peng, & Jiang, 2011). The SPSS software was used to conduct reliability analysis. The calculation results were 0.841 for the economic group, 0.830 for the social group, 0.878 for the environment group, and 0.878 for the disaster mitigation group. The Cronbach's coefficients for all four groups of indicators were greater than 0.7. Therefore, the questionnaire survey is reliable, thereby 172

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Table 5 ANOVA results for the risk perception. Indicators Economic

Social

Environmental

Risk mitigation

V1

V2

V3

E1 E2 E3 E4 E5 E6 E7 E8 E9 E10 E11 E12

.000 .000 .000 .045 .147 .002 .009 .000 .000 .008 .000 .000

** ** ** *

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12

.007 .000 .930 .000 .000 .002 .008 .001 .098 .352 .003 .000

** **

En1 En2 En3 En4 En5 En6 En7 En8 En9 En10

.039 .035 .420 .017 .911 .000 .000 .007 .005 .038

* *

** ** ** ** *

.052 .228 .401 .006 .769 .000 .000 .007 .002 .152

D1 D2 D3 D4 D5

.000 .000 .016 .000 .000

** ** * ** **

.114 .220 .265 .000 ** .743

** ** ** ** ** ** **

** ** ** ** **

** **

*

.008 .007 .000 .018 .070 .009 .007 .000 .000 .011 .000 .000

** ** ** **

.010 .004 .954 .656 .000 .120 .505 .051 .554 .232 .003 .707

** **

** ** ** ** * ** **

**

**

** ** ** ** **

.000 .003 .000 .257 .555 .001 .010 .248 .416 .784 .425 .000

V4

V6

V7

V8

V9

.886 .341 .023 * .781 .664 .029 * .454 .425 .335 .637 .214 .666

.001 ** .529 .938 .775 .600 .059 .039 * .104 .488 .781 .818 .694

.308 .772 .003 ** .069 .214 .331 .073 .240 .959 .511 .906 .199

.627 .296 .000 .130 .588 .450 .409 .002 .008 .007 .018 .374

.729 .060 .000 .014 .038 .014 .141 .019 .002 .088 .022 .308

.045 * .920 .936 .954 .577 .498 .659 .961 .628 .476 .814 .749

.203 .850 .099 .028 * .472 .034 * .291 .140 .298 .704 .273 .267

.026 * .721 .171 .434 .018 * .998 .337 .718 .805 .006 ** .584 .306

.175 .251 .053 .393 .017 * .764 .161 .186 .771 .559 .311 .006 **

.326 .350 .548 .077 .000 ** .317 .334 .438 .090 .015 * .317 .496

.670 .516 .606 .563 .735 .671 .823 .432 .755 .001 **

.288 .978 .868 .545 .473 .216 .165 .142 .012 ** .862

.043 * .076 .678 .055 .259 .384 .208 .525 .438 .662

.165 .398 .706 .516 .705 .109 .760 .027 * .009 ** .103

.056 .900 .931 .806 .193

.209 .895 .003 ** .504 .717

.198 .314 .165 .630 .834

.159 .052 .009 ** .001 ** .715

.000 .000 .000 .067 .660 .001 .003 .000 .000 .007 .000 .000

** ** **

* **

** **

.038 .001 .800 .000 .000 .001 .004 .001 .069 .220 .002 .000

.723 .173 .148 .163 .888 .005 ** .210 .006 ** .035 * .079

.018 .015 .283 .010 .990 .000 .000 .002 .002 .002

* *

** ** ** ** **

.869 .907 .474 .621 .714 .462 .673 .359 .865 .897

.000 ** .002 ** .083 .948 .000 **

000 000 006 000 000

** ** ** ** **

.391 .461 .764 .391 .268

.463 .000 .693 .000 .001 .000 .011 .000 .025 .837 .006 .000

** ** **

V5

** **

**

** ** ** ** * ** *

** ** ** ** ** ** **

** ** ** ** **

** **

**

**

** ** ** *

** * * * * ** * *

Note: **p < .01; *p < .05.

least concerns of farmers. Table 5 shows that public finance growth (E3), public management of CRS (S5), and land degradation (En9) are the most prevalent concerns. The government supported the reconstruction work after the earthquake, but the source of funds was reduced with the delay and became the biggest concern among the villagers. In addition, disaster and construction of CRS changed traditional production and lifestyle, which brought about new social problems. The villages also suffered from security risks as its geology changed after the earthquake. Risk mitigation focused on land and soil erosion because many farmers needed farmland with high output to support their livelihood. Electrical consumption growth (E5), labor growth (S3), convenient traffic (S9), entertainment satisfaction (S10), adequate water resources (En3), and sufficient clean energy (En5) are the least concerns. The risk of increasing the consumption of water, electricity, and natural gas in the questionnaire is not considered by the respondents given the abundance of water and natural gas resources in the survey area. Moreover, with the stability of society and natural population growth, paying attention to the risk of the number of laborers is not urgent. The villages also did not change entertainment satisfaction attributed to the earthquake. Thus, this point did not receive enough attention.

perception toward CRS development. For example, villages close to economic development zones or tourist areas can take the opportunity to develop the economy but may face the risk of ecological damage. Terrains are also important in that different terrains have different ecological resources that determine the production and social life of farmers. The characteristic industry feeds the farmers and inherits and carries forward the local culture. The CRS delivery approach follows the preference of residents. The benefit of unified reconstruction is easy financial saving, convenience, and quality assurance. Self-reconstruction can also facilitate self-initiative among farmers. Hence, choosing an appropriate way to solve the relationship among the neighborhoods and other social problems can protect the environment and promote unified disaster prevention and mitigation work. Furthermore, the personal characteristics of farmers can influence their risk perception on CRS development, which is less significant than the characteristics of villages. Some reasons can explain this phenomenon. First, the sources of the sample are scattered and come from four different villages, which contributes to cognitive deviation. Second, the benefits of the farmers are protected, and they profit from CRS after the disaster and village reconstruction. Therefore, the farmers have yet to recognize short-term potential risks. Third, the education level in the four villages is comparatively low, which may result in low-risk perception. From Table 5, we can also identify the prevalent concerns and the 173

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5. Discussions

economy and solve the problem of employment for farmers by providing sustainable livelihoods and enhancing their own rural hematopoietic function. However, in the process of industry construction, ecological protection should be promoted simultaneously to gain a coordinative development of economy and ecology. The CRS delivery approach is vital. Some of the victims gain permanent housing by way of exchanging their original housing with that of unified planning and unified reconstruction. Such efforts reduce the fund pressure of CRS reconstruction through government subsidies, bank loans, or borrowing reconstruction money from relatives and friends. However, reconstruction is a development opportunity, and people should not keep out of reconstruction and completely depend on external assistance (Usamah & Haynes, 2012). Instead, they should activate the internal mechanism of action as soon as possible to improve the resilience of the disaster area, which pushes the transformation of “relief” model reconstruction to “development” model reconstruction. Therefore, no matter choosing self-reconstruction or unified reconstruction, the farmers should be mobilized and empowered to participate in the process of CRS planning and reconstruction. Such measures can facilitate to improve the farmers' sense of identity with CRS, which further promotes social sustainability after concentration. Measures should also be taken to address the prevent concerns of farmers and facilitate to realize sustainability objective of CRS reconstruction. The earthquake disaster relief and reconstruction efforts in China are achieved by financial allocations. Therefore, dealing with the risk of public finance growth (E3) is important. Not setting aside any kind of financial support for a village after completing reconstruction is inevitable. In this case, the government should merge the financial needs of daily management and CRS development in the village. Attention should be paid to strengthen infrastructure development and public maintenance, which require more support from the government. The market should also be mobilized to initiate sustained economic development because public finances cannot be constantly allocated to CRS development. For the public management of CRS (S5), the government should focus on re-establishing the social network and the management system of CRS. The field study confirmed that many new problems occur after concentration (e.g., public hygiene). Some economic incentive mechanisms constrained by limited budget and labor can be made for the public management of CRS. For example, property management fees can be collected to improve public management. However, if the household can provide services for public hygiene or security, then their property management fees can be exempted. In addition, public education should be conducted to help farmers adapt to a new lifestyle. Volunteers and non-governmental organization (NGOs) play an important role in such practices. Meanwhile, land degradation (En9) has a tremendous damaging effect on land resources, national economy, and ecological environment. The critical measure is to develop non-agricultural industries with high salaries, which can attract rural labor and leave time and space to restore the farmland. However, as this vision requires long-term effort, the government and relevant NGOs should make efforts, including technology and finance, to consolidate land and improve farmland quality. Farmers should also be educated to help them appropriately utilize chemical fertilizers and pesticides. Market measures should be taken to encourage farmers to plant organic fruits without abusing the use of fertilizers and pesticides, which often leads to land degradation.

The farmers' risk perception level is relatively low given that the average significance risk perception is less than three in the four villages. With the continuous socio-economic development in recent years, public disaster education has received increasing attention from the government and community. However, the disaster prevention and mitigation education in rural China remain at the initial stage. The three aspects of the problem of public disaster education include the lack of respective departments for public disaster prevention and mitigation education, an inability to deal with emergencies, and limited opportunities for disaster prevention training and exercise. This insufficiency presents barriers of conducting disaster prevention and mitigation and realizing sustainability objective of post-disaster reconstruction. Therefore, the overall level of disaster prevention and disaster awareness in China should be raised, and knowledge in selfsecurity should be reinforced by enhancing public education. Geographic location, terrain, characteristic industry, and the CRS delivery approach are closely related to farmers' risk perception of the economy, society, environment, and disaster prevention and mitigation. This scenario implies that proper planning is needed to well implement CRS reconstruction efforts. A reasonable geographic location should also be selected to achieve good CRS reconstruction. A reasonable location can strengthen effective risk communication and reduce losses, which are useful for economic growth, social stability, and environment improvement (Wang, Hironori, & Ryuichi, 2013). Good rural infrastructure is related to the improvement of rural production, living conditions, and overall appearance. Reconstruction planning should focus on rural development, land conservation, and the intensive use of land. The improvement of rural public facilities, the accelerated construction of rural roads, and the active development of suitable areas for wind, solar, and other clean energies can also promote the appearance and environment of CRS. Such reasonable planning can facilitate to promote better economic development, which further reduce farmers' worries of income and improve the economic sustainability in the long term. Moreover, terrain can offer a number of advantages. Taking advantage of specific terrain features can help in disaster prevention and mitigation and allow farmers to live and work in peace, thus reducing the fear caused by disasters. For example, if the terrain is flat, then the area of cultivated land is favorable for the development of the planting industry. Convenient transportation can also be established in this type of land, which is conducive for the rational distribution of various industries. A hilly area near a mountain is an important habitat for flood control and wildlife protection, and this area can be converted into a tourist destination given its unique scenery. Building designs should also adapt to the changes of the terrain. Transportation is inconvenient in the mountains, but the best advantage of this terrain is that natural resources are preserved with vast vegetation and land. Tourism, rural home inns, homestay, fruit planting, and open terrace industries can be developed in this area. Unique folk customs in the mountains can also be promoted. Any development of the terrain should be carried out under the premise of a detailed geological survey. Village committees should regularly disseminate disaster prevention and mitigation information, with emphasis on the geological hazards in the village. The CRS reconstruction therefore should be implemented by utilizing the advantages of terrain rather than following the same pattern. Characteristic industry development should also be included in CRS planning based on existing resources and concerns resulting from earthquakes. As a critical basis for sustainable development, income growth should be paid due attentions. Developing characteristic industry is an important approach to improve income level and facilitate farmers to adapt to the new lifestyle after concentration. Villages should depend on their own merits to improve themselves by expanding the scale of land circulation to encourage the development of ecological agriculture. The development of a new industry can also drive the local

6. Conclusions After the 5.12 Sichuan Earthquake in China, the government widely promoted CRS under the context of new countryside construction because of its efficacy. Previous studies examined issues, such as critical determinant factors, decision process, and the comparison of different approaches, to implement CRS reconstruction. However, only a few studies have attempted to comprehend farmers' risk perception of CRS 174

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and discussed its relevant influencing factors. The present study investigates farmers' risk perception of CRS development using four cases in the hardest earthquake-hit area. Critical risk factors are identified through a random questionnaire survey distributed to farmers living in the four villages. ANOVA is employed to explore the influencing factors on risk perception. In-depth discussions are conducted to explore the reasons behind farmers' risk perception of CRS development. Potential measures to mitigate relevant critical risks are proposed and raising the farmers' risk perception of being prepared for danger is emphasized. The findings of this study provide references for local governments to reduce the worries of farmers about CRS and presents approaches that are suitable for mitigating risks and strengthening the relationship between the government and the farmers. By being aware of the willingness of the people, post-disaster reconstruction can realize the vision of sustainable CRS development. It also provides references for local government to address specialized concerns and constraints when developing CRS within both disaster context and non-disaster context. However, this study has some limitations. First, although the paper reveals a preliminary understanding of the influencing factors. The internal mechanisms of the involved variables should be further explored. Second, the results are only based on four villages after the 5.12 Sichuan Earthquake. Future research should be conducted to compare risk perceptions in other disaster-affected areas, which can deepen our understanding of post-disaster management theories.

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