IJERD – International Journal of Environmental and Rural Development (2017) 8-1

Research article
erd

Assessing Factors Influencing Farmers’ Perceptions on
Adaptation to Climate Change: A Case of Apple Farmers in
Cheongsong, Korea
SEONG YOON CHOI*
Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
Email: k147629@int.k.u-tokyo.ac.jp

EIJI YAMAJI
Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
Received 14 December 2016

Accepted 29 June 2017(*Corresponding Author)

Abstract One of the most important consequences of climate change in Korea is the moving of
the adequate cultivation area for apple. To respond adequately to such consequences, thefarmers require performing on the adaptation measures. Although Korean government puts
great efforts to develop adaptation measures, the livelihoods of agriculture and ruralcommunities are still posing great threats from climate variability and change. It is because themost of adaptation studies and policies fail to address the perception of farmers who decide andperform the adaptation measures. Without an understanding of farmers’ perceptions, private
adaptation strategies are unlikely to be effective. This paper, therefore, aims to investigate andanalyze factors influencing farmers’ perception on adaptation behaviors. To meet suchobjectives, this study based on theory, a Model of Private Proactive Adaptation to Climate
Change (MPPACC), explaining individual’s intention of adaptive behavior is based on sociocognitive aspects including perceived adaptation measure efficacy, self-efficacy and adaptation
costs. To analyze the factors influencing farmers’ perception and behavior of climate change
adaptation, 170 apple farmers in Cheongsong County is selected for farm household survey. By
analyzing through multiple linear regressions, the results were found that the farmers’
perceptions of adaptive efficacy are significantly associated with farm household demographic
and socioeconomic factors including investment in crop insurance, and contents and sources of
information. This implies that to enhance the farmers’ motivation to adaptation, the local
government should pay further attention to improve credibility of crop insurance efficacy andthe quality and source information to increase farmers’ adaptive capacity through increased
farmers’ perception on adaptation efficacy.
Keywords climate change, adaptation behaviors, perceived adaptation efficacy,
apple farming

INTRODUCTION
Agricultural communities in Korea have already experienced the impact of climate change, including
crop and livestock losses from severe drought and flooding, large-scale losses from weather-related
disasters, shifts in planning and harvesting times and cultivation lands (MoE, 2015). According toMinistry of Environment (2015), the assessment of the climate change vulnerability and its impact onapple cultivation in Korea indicated that adequate apple cultivation area, which has been in thesouthern, eastern parts of Korea, is moving to the northern parts of the Korean peninsula. Moreover, in
the Northern Provinces in Korea, it is already increasing apple production in the area. Although
Cheongsong County, one of the top apple-producing counties in southern parts, is increasing its appleⒸ ISERD

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production until recent years, the County is also projected to become inadequate to produce the apple
crops from the 2030s (RDA, 2015). Not only the projected climate is shown to change apple
cultivation in the County, the current climate variability already has been increasing farmers’
awareness on the climate variability and adaptation behaviors. To increase farmers’ resilience toclimate change, enhancing the adaptation capacity is vital. The farmers have been conducting
adaptation behaviors to prevent and lessen the damage of climate variability and change. The private
adaptation behaviors can be influenced by farmers’ perceptions and assessments on the specificadaptation measures. However, only limited studies has examined the factors influencing farmers’
perceptions on the adaptation behaviors.
The Model of Private Proactive Adaptation to Climate Change (MPPACC) is one of the limited
research to examine the socio-cognitive perspective of adaptation behaviors derived from discourses in
psychology and behavioral economics (Grothmann and Patt, 2005). According to this model,
individuals’ adaptation behavior to climate change can be influenced by some socio-cognitive factors
including perceived adaptation efficacy which is measured by individuals’ perceptions of 1) adaptation
measure efficacy (PME), 2) self-capacity to perform the adaptation measures (PSE), and 3) the costassociated with such performance (PAC). In this study, the factors hypothesized to influence such
perceptions are farm households’ characteristics (socioeconomic factors), previous experience withclimate change, and information (climate change, adaptation) from various sources. To enhance theapple farmers’ resilience to increasing climate risks, it is important to not only to develop adequate
adaptation measures but also to understand what factors may motivate the farmers to perform theadaptation measures.
OBJECTIVE
The main objective of this paper is to suggest some policy implications for enhancing farmers’
adaptation capacity by investigating and analyzing farmers’ perceptions on the effectiveness of private
climate change adaptation behaviors and the factors influencing such perceptions.
METHODOLOGYAs shown in Fig. (1), North Gyeongsang Province is located in the southeastern part of Korea andCheongsong County is located in the eastern part of the Province. The Province produced 372,627 tonsof apples in 2015 which is about 64 percent of total apple produced in Korea (RDA, 2015).
Cheongsong County is evaluated as one of the top County to produce the highest quality apples in
Korea (Cheongsong County, 2016). Because of its location, altitude and temerature, the County has
been well-suited for producing high-quality apples. The County is surrounded by mountains thatprovide a high diurnal range which is an advantage climate for apple cultivation. Moreover, the County
usually has less rainfall compared to neighbor Counties which are also an advantage climate factor forapple cultivation. The County’s annual average temperature, although increased from 12.5 in 2014, isrecorded as 12.9 in 2015 (KMA, 2016). Since the County has been known to have the suitableenvironment and climatic for apple cultivation, about 80% of farmers are engaged in apple cultivationin the County (Cheongsong County, 2016). The County, not only produces the high-quality apples, but
it also organizes several major events including the biggest apple festival in Korea. Apple cultivation is
not only an extremely important economic source, but it also has become a part of the lives of thepeople living in the County.
The farmers’ adaptation behaviors to climate change are collected through intensive review ofprevious studies and government reports. After listing all the adaptation measures that are applicable tothe apple farmers, the authors conducted interviews with the farmers and the local agricultural officials
for final selection. Finally, 9 adaptation measures were selected and analyzed in this study includes:Ⓒ ISERD

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adjusting farming dates, adjusting use of pesticides, switching to different crop, paying attention toclimate information, diversifying crops, buying crop insurance, improving soil condition, changing toother apple variety and searching for non-farming job.

Fig. 1 Conceptual framework
From April to June 2016, a farm household survey with 170 apple farmers in Cheongsong County
was conducted with structured questionnaires, also, in-depth interviews and focus group discussions
were conducted to collect the data on farmers’ characteristics, experiences with climate change andclimate change and adaptation information from various sources including neighbors, community
leaders, local agricultural extension services, public media and cooperatives. Farmers were also asked
about their perceptions of the adaptation effectiveness including their perception of adaptation measureeffectiveness, self-ability to perform measures, and the costs performing the 9 specific adaptation
measures. For perceptions of measure effectiveness and self-capacity, farmers were asked to scale 1(not effective at all) to 4 (extremely effective) while on the costs were scaled as 1(extremely expensive)
to 4 (not expensive at all). Four linear regressions were conducted for analyzing the factors affecting
farmers’ perceptions on adaptation efficacies. For the regression, farmers’ adaptation assessments wererepresented by four dependent variables: perceived measure efficacy (PME), perceived self-efficacy(PSE), perceived adaptation cost (PAC) and overall perception of adaptation efficacy. The overall
perception of adaptation efficacy is calculated by adding three adaptation perceptions and divided bythree to weigh all three perceptions equally.
Overall Perceived Adaptation Efficacy = (PAE + PSE + PAC) / 3
The explanatory variables considered in the regression are farm household characteristics,
socioeconomic factors such as income, sales mechanisms, crop insurance status, previous experience inclimate risk and information from various sources. Previous studies on individuals’ adaptation
behavior found that some demographic and socioeconomic factors such as age, experience, gender,
income, education and sales mechanisms influence farmers’ adaptation behaviors (Bryan et al., 2013;
Deressa et al., 2011; Fujisawa and Kobayashi, 2011; Grothmann and Patt, 2005). Personal experience
with climate risk can also motivate private adaptation by influencing one’s cognitive factors(Grothmann and Patt, 2005). Moreover, information can play a vital role in the farmers’ perception on
the adaptation efficacies (Grothmann and Patt, 2005). Not only the contents itself but how farmers
receive such information can have a diverse effect on them. Therefore, in this study, both climate andadaptation information are considered to be disseminated by public media, neighbor farmers, village
leaders, agriculture extension service centers, and agricultural cooperation. This study assumes thatclimate change and adaptation information from different sources can have a different influence on the
farmers’ perception of three adaptation efficacies. The models were tested for the R-squares,
multicollinearity, normality, linearity and homoscedasticity of the residuals
Perceived Adaptation Efficacy = f (farm household characteristics, climate risk experiences,climate change information, adaptation information)Ⓒ ISERD

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RESULTS AND DISCUSSION
To analyze the factors influencing farmers’ cognitive adaptation capacity, particularly on the cognitive
evaluation of adaptation behaviors are found from the four regression models. Table 1 shows the resultsof the regressions, and it was found that farmers’ perceptions of adaptation measure efficacy, selfefficacy, adaptation costs and overall adaptation behaviors are influenced by some farm household
characteristics, socioeconomic factors, and climate and adaptation information from various sources.
Moreover to all the regression coefficients presented in Table 1, Table 2 demonstrates the R 2, adjusted
R2, F-test (p-value) and VIF. The R2 for all models indicated that the statistically significant
explanatory variables could explain 46 to 57% of the variation of farmers’ adaptation perceptions. The
variance inflation factor (VIF) for all explanatory variables were less than 3and this indicates that there
is no multicollinearity problem found for the variables.
Farm Household Characteristics
Farm household characteristics found to have the significant influence on farmers’ assessment ofadaptation behaviors. According to the regression results, farmers’ age is statistically significant inrelation to farmers’ perception on the measure efficacy. The coefficient indicates that as the farmer isyounger, they perceive adaptation measures as more effective. Gender is also found to be a significant
factor. The female farmers than male farmers perceive overall adaptation behavior as effective. In
addition, years of education seems to be negatively related to the farmers’ perceptions, particularly
significant with the overall adaptation behaviors. Farm area is positively related to how farmers
perceive adaptation measure effectiveness while negatively correlated with adaptation cost. With
increasing farming area, farmers perceive adaptation measures as effective while the costs associatedwith the adaptation measures expensive. Income can play an important role in farmers’ assessment of
the cost of the measures. According to the results, a farmer with higher income can perceive theadaptation cost as more expensive. In general, farming is a family business that sons usually take overthe farm from their parents. Having successor can influence farmers’ perception on adaptation,
especially related to the perception on self-capacity to carrying on the measures on their farms.
Moreover, the number of participation in the agricultural training programs does show the significant
relation with how farmers assess their own adaptation capacity.
The apple farmers sell their apple through direct or indirect markets. Direct sellers can receive
feedbacks and new information. According to the regression model, the farmers with such market
channels can have a higher perception of the adaptation measure and overall adaptation behavior aseffective. Crop insurance plays an important role not only to recover the damages from the natural
disasters but to prevent and remedy farmers from future disasters. Farmers who bought the crop
insurance are more likely to perceive adaptation cost as less expensive and have a higher perception of
the overall adaptation behaviors. However, simply buying crop insurance and how many years thefarmers with crop insurance can have a different influence on their perceptions. Interestingly, as the
cumulative years of buying crop insurance increases, farmers’ perception on the adaptation measure,self –capacity and overall adaptation behaviors can diminish. This indicates that as the years offarmers’ buying crop insurance increases, they find the fraud in the system and feel that they do not get
any benefit of buying the insurance. This induces the necessity of improving the current insurance
system.
Climate Risk Experiences
Climate risk experiences with increasing temperature, changing patterns and intensity of precipitationand extreme weather events including typhoon can influence farmers’ motivation to perform adaptation
measures; however, according to the regression results in this study, climate risk experiences did notⒸ ISERD

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show any statistically significant influence on the farmers’ perceptions, particularly related to theadaptation efficacies. However, it could be worth of mentioning that according to previous studies, it
was found that previous climate-related risk experiences can have influence on farmers’ motivation or
intention to adaptation. Therefore, although not directly influencing the farmers’ perceptions related toadaptation measures, it could have an influence on other cognitive factors that influence farmers’
motivation to climate change adaptation behaviors.
Table 1 Multiple linear regression models on farmers’ perceptions of adaptation behaviors
Explanatory variables

Perceived
Measure Efficacy

Perceived
Self-efficacy

Perceived
Adaptation Costs

Overall
Perception

Farm household characteristics
Age (continuous)-0.0085***-0.0018***-0.0021****-0.0124***
Gender (1=male, 0= female)-0.1663***-0.1197***-0.0866***-0.3725***
Education level (continuous)-0.0224***-0.0113***-0.0259***-0.0597***
Farming area (continuous)-0.0966***-0.0664***-0.0960***-0.0671***
Farming Experience (continuous)-0.0032***-0.0001***-0.0017***-0.0013***
Income (continuous)-0.0047***-0.0398***-0.0822***-0.0471***%of income from apple (continuous)-0.0001***-0.0026***-0.0004***-0.0029***
Successor (1=yes, 0=no )-0.1136***-0.2233***-0.1030***-0.4399***
Agricultural training (continuous)-0.0040***-0.0230***-0.0119***-0.0151***
Smart-phone use (1=yes, 0=no)-0.1632***-0.0712***-0.2509***-0.4854***
Sales channels (1=indirect, 0=direct)-0.1084***-0.0658***-0.0181***-0.1562***
Land ownership (1=yes, 0=no)-0.0121***-0.0183***-0.0337***-0.0033***
Buying crop insurance (1=yes, 0=no)-0.1830***-0.0781***-0.4582***-0.7193***
Yrs. crop insurance (continuous)-0.0472***-0.0250***-0.0087***-0.0636***
Other crops (1=yes, 0=no)-0.0559***-0.0195***-0.0216***-0.0972***
Climate Risk Experiences (1=not at all, 2=barely, 3=have experience, 4=extremely)
Risk Experience (Temperature)-0.0207***-0.0085***-0.1027***-0.1149***
Risk Experience (Precipitation)-0.0605***-0.0998***-0.0224***-0.1827***
Risk Experience (Extreme weather)-0.0329***-0.0319***-0.0395***-0.0253***
Information (1=not at all, 2=sometimes, 3=often, 4=always)
Climate change info. (Public media)-0.1195***-0.1043***-0.0015***-0.2253***
Climate change info. (Neighbor farmers-0.0405***-0.0032***-0.0270***-0.0618***
Climate change info. (Village leader)-0.0837***-0.0220***-0.1639***-0.2256***
Climate change info. (Agri. Ext. center)-0.1138***-0.0943***-0.1130***-0.3210***
Climate change info. (Agri. Cooperative)-0.1414***-0.1479***-0.0208***-0.2686***
Adaptation Info. (Public media)-0.0428***-0.0403***-0.0387***-0.0444***
Adaptation Info. (Neighbor farmers)-0.0792***-0.2847***-0.0224***-0.3414***Adaptation Info. (Village leaders)-0.2003***-0.1358***-0.0635***-0.1281***
Adaptation Info. (Agri. Ext. center)-0.1734***-0.0134***-0.0952***-0.0916***Adaptation Info. (Agri. Cooperative)-0.1095***-0.0173***-0.0786***-0.0136****Significant at 10% level (p<0.1), ** significant at 5% level (p<0.05), *** significant at 1% level (p<0.001)

Information
As explained in the previous section, the contents and the sources of information can influence
farmers’ perceptions. According to the regression results, information on climate change received frompublic media, agricultural extension center and cooperatives can positively influence farmers’
perceptions on measure efficacy, self-efficacy, and overall adaptation efficacy. However, theinformation from neighbor farmers and village leaders can negatively influence farmers’ perceptions,particularly on self-efficacy, costs and overall adaptation efficacy. From these results, it can beⒸ ISERD214

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analyzed that the farmers perceive adaptation efficacies positively associated with climate change
information from objective sources. Interestingly, unlike the climates change information, the farmers’
perception of adaptation efficacies is positively and significantly related with adaptation informationfrom neighbors and village leaders. It can be analyzed that the farmers’ perception on adaptation
efficacies, which would eventually increase farmers’ motivation to perform on the adaptation can beenhanced if adaptation information could be disseminated by neighbors and village leaders, who thefarmers are personally connected with. The inclusion of subjective opinion or the personal experiencein disseminating the information related to adaptation measures could bring greater success indelivering adaptation information to farmers.
Table 2 Assessing the fit of regression models and multicollinearity
Dependent variables in the models
Perceived measure efficacy
Perceived self-efficacy
Perceived adaptation costs
Overall perception

R2
0.53
0.49
0.46
0.57

Adjusted R2
0.38
0.33
0.28
0.43

F test, p-value
0.00
0.00
0.00
0.00

VIF
Max: 2.92
Min: 1.14

CONCLUSION
To enhance the adaptive capacity of farmers, this study aims to investigate and analyze the factors
affecting the cognitive capacity of the apple farmers, in Cheongsong, Korea. According to the
MPPACC, the cognitive capacity to motivate adaptive behavior includes individuals’ perception ofadaptation behaviors and adaptation perception can be measured through perceived measure efficacy,
perceived self-efficacy, and perceived adaptation costs. This study conducted multiple regressions, andas a result, demographic and socioeconomic factors and information from different sources can have an
influence on the farmers’ perceptions differently. In sum, among the demographic and socioeconomic
factors, crop insurance and years of buying the insurance seem to influence farmers’ perceptions on
adaptation assessment. Moreover, climate information from objective sources, such as public media
and public centers can have higher influence than neighbors and village leaders, however, with regard
to adaptation information, the farmers’ perception of adaptation behaviors can be influenced more by
information from neighbors and village leaders. There was no statistically significant correlation was
found with previous climate risk.
The results of this study suggest some directions for how to achieve successful dissemination ofadaptation policies in the agricultural sector. Not only the contents but sources and quality of
information should be considered as important due to the potential influences on farmers’ perceptions
and their adaptation evaluations. Moreover, an improvement on the system of crop insurance inaddition to increasing credibility is deemed a necessity for successful adaptation strategies in
Cheongsong County. By understanding different elements that induce farmers’ perception on
adaptation appraisal, apple farming communities can increase its adaptive capacity and lessen thedamage from the impacts. However, there is the tendency of ignoring the importance of cognitive
factors. Enhancing broader application of measuring cognitive capacity should have a clearer
understanding of climate change adaptation capacity in apple farming communities. Moreover, thisstudy can be more developed to be applied to other regions and other sectors to be referred in
integrated climate change vulnerability assessment of rural agricultural communities.
ACKNOWLEDGEMENTS
The authors are grateful to the apple farmers and Agricultural Government officers of Cheongsong
County for their active participations and supports for this study.
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