• Title/Summary/Keyword: Explanatory variable

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Analysis of The Relationships between Religions in Southeast Asia and Tourism Demand in Korea (동남아시아 지역 종교와 방한 관광수요의 영향 관계분석)

  • Kim, Do-Hoon
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.123-130
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    • 2023
  • As part of the research on cultural factors that determine international tourism demand, this study was conducted based on regional interest and the need for understanding religion. The purpose of this study is to empirically test how religious factors affect tourism demand in Korea to find out that religious factors are important considerations in establishing tourism policies and strategies. To achieve the purpose of this study, the research target areas were selected as Thailand, Indonesia, and the Philippines, which have relatively many tourists visiting Korea among Southeast Asian countries and are well known for their religious characteristics. GDP and nominal exchange rate, which are economic factors, were selected as explanatory variables. And religious diversity was selected as a characteristic factor variable of the tourism demand model based on the characteristic theory. An empirical analysis was conducted through a gravity model. As a result of the estimation, it was found that GDP has a positive effect on tourism demand in Korea. Nominal exchange rate variables and religious diversity variables were found to have a negative effect on tourism demand in Korea. We have confirmed that religion is an important factor in choosing tourist destinations for Filipino, Thai, and Malaysian tourists visiting Korea, and they choose religiously similar destinations.

An Analysis of The Relationship Among Nursing Students' Perception of Target Vulnerability and Target Advocacy, Child Rights Awareness, and Child Abuse Reporting Intention (간호대학생이 지각한 대상자 취약성 및 옹호, 아동권리인식, 아동학대 신고의도 간의 관계 분석)

  • Ji-Ah Song;Jae Woo Oh
    • Journal of Industrial Convergence
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    • v.22 no.3
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    • pp.155-163
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    • 2024
  • Nursing students, as prospective nurses, are expected to act as child abuse reporters and advocates for child targets. Therefore, this study aimed to provide a basis for developing a child abuse prevention education program for nursing students by determining the extent of nursing students' perceived target vulnerability and target advocacy, child rights awareness, and intention to report child abuse, and analyzing the relationships among the variables. This study is a descriptive survey study to identify the effects of target vulnerability, target advocacy, and child rights awareness on intention to report child abuse among 154 nursing students, and the data collection period was from July 3 to July 31, 2023, and the collected data were analyzed using SPSS 25.0 program. As a result of identifying the influential factors on nursing students' intention to report child abuse, child abuse education, championing social justice as a sub-variable of target advocacy, and target vulnerability, the explanatory power of these variables was 35.8%. Based on the results of this study, it is suggested that it is necessary to increase activities through the development and application of simulation education based on actual clinical cases in order to increase nursing students' interest in and education about child abuse.

A Study on the Self Perceived Fatigue of Dental Hygiene Students in Clinical Practice (일부 치위생과 학생의 임상실습 시 경험하는 피로수준에 관한 연구)

  • Han, Se-Young;Han, Yang-Keum
    • Journal of dental hygiene science
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    • v.14 no.3
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    • pp.325-331
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    • 2014
  • The purpose of this study was to examine the self-perceived fatigue among 262 dental hygiene students, who have recently experienced clinical practice. In this study, a structured self-reported questionnaire was used to assess and analyze the severity of fatigue among the population. This study was performed from January to September in 2013 to effectively encompass clinical practice. The results are as follows: The self-perceived fatigue of the subjects was significantly higher in a subjective unhealthy group than a subjective healthy group (p=0.000), in a group that was unsatisfied with their program than a group that was satisfied with it (p=0.000), in a group that had dissatisfaction in clinical practice than a group that had satisfaction with it (p=0.000), in a group that had over five weekly of clinical practice than a group that didn't (p=0.000), in a group that had more than 100 patients a day than a group that didn't (p=0.000), in a group that had conflicts between fellow staff than those who didn't (p=0.000), in a group that did not exercise regularly than a group that did (p=0.016). The result of using multiple regression analysis revealed that the variable factors affecting the degree of the self-perceived fatigue were; subjective health status, satisfaction with a clinical practice, the length of clinical practice, the number of patients, and staff conflicts. These variable factors have the explanatory power of 44.5%. In conclusion, to decrease fatigue and allow students in clinical practice to perform effectively, clinical practice educators need to actively participate as a community and develop programs that will decrease the fatigue of students. In addition, in-depth research is needed on the effects of outside factors and variables affecting fatigue.

Antecedents of Manufacturer's Private Label Program Engagement : A Focus on Strategic Market Management Perspective (제조업체 Private Labels 도입의 선행요인 : 전략적 시장관리 관점을 중심으로)

  • Lim, Chae-Un;Yi, Ho-Taek
    • Journal of Distribution Research
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    • v.17 no.1
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    • pp.65-86
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    • 2012
  • The $20^{th}$ century was the era of manufacturer brands which built higher brand equity for consumers. Consumers moved from generic products of inconsistent quality produced by local factories in the $19^{th}$ century to branded products from global manufacturers and manufacturer brands reached consumers through distributors and retailers. Retailers were relatively small compared to their largest suppliers. However, sometime in the 1970s, things began to slowly change as retailers started to develop their own national chains and began international expansion, and consolidation of the retail industry from mom-and-pop stores to global players was well under way (Kumar and Steenkamp 2007, p.2) In South Korea, since the middle of the 1990s, the bulking up of retailers that started then has changed the balance of power between manufacturers and retailers. Retailer private labels, generally referred to as own labels, store brands, distributors own private-label, home brand or own label brand have also been performing strongly in every single local market (Bushman 1993; De Wulf et al. 2005). Private labels now account for one out of every five items sold every day in U.S. supermarkets, drug chains, and mass merchandisers (Kumar and Steenkamp 2007), and the market share in Western Europe is even larger (Euromonitor 2007). In the UK, grocery market share of private labels grew from 39% of sales in 2008 to 41% in 2010 (Marian 2010). Planet Retail (2007, p.1) recently concluded that "[PLs] are set for accelerated growth, with the majority of the world's leading grocers increasing their own label penetration." Private labels have gained wide attention both in the academic literature and popular business press and there is a glowing academic research to the perspective of manufacturers and retailers. Empirical research on private labels has mainly studies the factors explaining private labels market shares across product categories and/or retail chains (Dahr and Hoch 1997; Hoch and Banerji, 1993), factors influencing the private labels proneness of consumers (Baltas and Doyle 1998; Burton et al. 1998; Richardson et al. 1996) and factors how to react brand manufacturers towards PLs (Dunne and Narasimhan 1999; Hoch 1996; Quelch and Harding 1996; Verhoef et al. 2000). Nevertheless, empirical research on factors influencing the production in terms of a manufacturer-retailer is rather anecdotal than theory-based. The objective of this paper is to bridge the gap in these two types of research and explore the factors which influence on manufacturer's private label production based on two competing theories: S-C-P (Structure - Conduct - Performance) paradigm and resource-based theory. In order to do so, the authors used in-depth interview with marketing managers, reviewed retail press and research and presents the conceptual framework that integrates the major determinants of private labels production. From a manufacturer's perspective, supplying private labels often starts on a strategic basis. When a manufacturer engages in private labels, the manufacturer does not have to spend on advertising, retailer promotions or maintain a dedicated sales force. Moreover, if a manufacturer has weak marketing capabilities, the manufacturer can make use of retailer's marketing capability to produce private labels and lessen its marketing cost and increases its profit margin. Figure 1. is the theoretical framework based on a strategic market management perspective, integrated concept of both S-C-P paradigm and resource-based theory. The model includes one mediate variable, marketing capabilities, and the other moderate variable, competitive intensity. Manufacturer's national brand reputation, firm's marketing investment, and product portfolio, which are hypothesized to positively affected manufacturer's marketing capabilities. Then, marketing capabilities has negatively effected on private label production. Moderating effects of competitive intensity are hypothesized on the relationship between marketing capabilities and private label production. To verify the proposed research model and hypotheses, data were collected from 192 manufacturers (212 responses) who are producing private labels in South Korea. Cronbach's alpha test, explanatory / comfirmatory factor analysis, and correlation analysis were employed to validate hypotheses. The following results were drawing using structural equation modeling and all hypotheses are supported. Findings indicate that manufacturer's private label production is strongly related to its marketing capabilities. Consumer marketing capabilities, in turn, is directly connected with the 3 strategic factors (e.g., marketing investment, manufacturer's national brand reputation, and product portfolio). It is moderated by competitive intensity between marketing capabilities and private label production. In conclusion, this research may be the first study to investigate the reasons manufacturers engage in private labels based on two competing theoretic views, S-C-P paradigm and resource-based theory. The private label phenomenon has received growing attention by marketing scholars. In many industries, private labels represent formidable competition to manufacturer brands and manufacturers have a dilemma with selling to as well as competing with their retailers. The current study suggests key factors when manufacturers consider engaging in private label production.

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Psychosocial Characteristics and Quality of Life in Patients with Functional Gastrointestinal Disorder (기능성위장질환 환자들의 정신사회적 특성과 삶의 질)

  • Lee, Dong-Ho;Lee, Sang-Yeol;Ryu, Han-Seung;Choi, Suck-Chei;Yang, Chan-Mo;Jang, Seung-Ho
    • Korean Journal of Psychosomatic Medicine
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    • v.28 no.1
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    • pp.20-28
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    • 2020
  • Objectives : The aim of this study was to compare psychosocial characteristics of the functional gastrointestinal disorders FGID group, non-FGID group, and control group and determine factors affecting the QOL of patients with FGID. Methods : 135 patients diagnosed with FGID were selected. 79 adults had no observable symptoms of FGID (control group) and 88 adults showed symptoms of FGID (non-FGID group). Demographic factors were investigated. The Korean-Beck Depression Inventory-II, Korean-Beck Anxiety Inventory, Korean-Childhood Trauma Questionnaire, Multidimensional Scale of Perceived Social Support, Connor-Davidson Resilience Scale, Patient Health Questionnaire-15 and WHO Quality of Life Assessment Instrument Brief Form were used to assess psychosocial factors. A one-way ANOVA was used to compare differences among groups. Pearson correlation test was performed to analyze the correlation of psychosocial factors and QOL of the FGID group. Further, a hierarchical regression analysis was conducted to determine factors affecting the QOL of the FGID group. Results : Between-group differences were not significant in demographic characteristics. Depression (F=48.75, p<0.001), anxiety (F=14.48, p<0.001), somatization (F=24.42, p<0.001) and childhood trauma (F=12.71, p<0.001) were significantly higher in FGID group than in other groups. Social support (F=39.95, p<0.001) and resilience (F=17.51, p<0.001) were significantly lower in FGID group than in other groups. Resilience (β=0.373, p<0.01) was the most important explanatory variable. The explained variance was 47.2%. Conclusions : Significantly more symptoms of depression, anxiety, childhood trauma, and somatization were observed for the FGID group. This group also had less social support, resilience, and quality of life than the non-FGID and control groups. The key factor for quality of life of the FGID group was resilience.

A Regression-Model-based Method for Combining Interestingness Measures of Association Rule Mining (연관상품 추천을 위한 회귀분석모형 기반 연관 규칙 척도 결합기법)

  • Lee, Dongwon
    • Journal of Intelligence and Information Systems
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    • v.23 no.1
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    • pp.127-141
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    • 2017
  • Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

The Selection of the Suitable Site for Forest Tree(Pinus thunbergii) (임목(林木)((해송(海松)) 적지선정(適地選定)에 관한 연구(硏究))

  • Chung, Young Gwan;Park, Nam Chang;Son, Yeong Mo
    • Journal of Korean Society of Forest Science
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    • v.82 no.4
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    • pp.420-430
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    • 1993
  • This study was conducted to investigate the effect of the forest environmental factors(5 items) and physico-chemical properties of soil(13 items) on the growth of Pinus thunbergii stands. The 218 plots were sampled over the coastal district of the whole country. In statistical analysis, the explanatory variables were soil and environmental factors(18 items), and the response variable was the site index of Pinus thunbergii stands. Data computation was processed in order of preparation of original data, computation of inner correlation matrix table by correlation analysis, calculation of partial correlation coefficients and coefficients of determination, estimation of regression equation by stepwise begression analysis, and stepwise regression analysis by factor score of factor analysis. The main results obtained were summarized as follows ; 1. The site index in Pinus thunbergii stands way highly correlated with effective soil depth(r=0.8668), slope percentage, organic matter, and total nitrogen. 2. According to the coefficients by partial correlation analysis, effective soil depth(r=0.6270), slope percentage (r=-0.5423) and base saturation(r=0.3278) among environmental factors had a great effect on tree growth. 3. With stepwise regression analysis, the factors effecting on the Pinus thunbergii stands growth were effective soil depth, slope percentage, organic matter, base saturation, soil pH, content of silt, exchangeable Ca, and etc. 4. Estimation equation for the site index of Pinus thunbergii stands was given by $Y=13.2691+0.0242\;X_2-1.2244\;X_4+0.6142\;X_5-0.3472\;X_{11}+0.0355\;X_{13}+0.1552\;X_{15}-0.1002\;X_{17}$. The coefficient of determination for the estimation model was 0.77, which was significant at the 1 percent level. 5. In result of factor analysis by the environmental factors, principal components were 6 factors, and communality contribution percentage was 71.1 percent. 6. By stepwise regression analysis between factor score and site index of Pinus thunbergii stands, the factor group effecting on site index was 5 principal components. The coefficients of determination was 85 percent, which was significant at the 1 percent level. In conclusion, on the occasion of analizing which factors to effect on the tree height growth in Pinus thunbergii stands the stepwise regression analysis proved to be greatly significant. Also the management of Pinus thunbergii stands should be working by the above selected growth factors.

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The Relationships between Dry Matter Yield and Days of Summer Depression in different Regions with Mixed Pasture (혼파초지에서 지역별 건물수량과 하고일수 간 관계)

  • Oh, Seung Min;Kim, Moonju;Peng, Jinglun;Lee, Bae Hun;Kim, Ji Yung;Chemere, Befekadu;Kim, Si Chul;Kim, Kyeong Dae;Kim, Byong Wan;Jo, Mu Hwan;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.38 no.1
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    • pp.53-60
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    • 2018
  • Yield prediction model for mixed pasture was developed with a shortage that the relationship between dry matter yield (DMY) and days of summer depression (DSD) was not properly reflected in the model in the previous research. Therefore, this study was designed to eliminate the data of the regions with distinctly different climatic conditions and then investigate their relationships DMY and DSD using the data in each region separately of regions with distinct climatic characteristics and classify the data based on regions for further analysis based on the previous mixed pasture prediction model. The data set used in the research kept 582 data points from 11 regions and 41 mixed pasture types. The relationship between DMY and DSD in each region were analyzed through scatter plot, correlation analysis and multiple regression analysis in each region separately. In the statistical analysis, DMY was taken as the response variable and 5 climatic variables including DSD were taken as explanatory variables. The results of scatter plot showed that negative correlations between DMY and DSD were observed in 7 out of 9 regions. Therefore, it was confirmed that analyzing the relationship between DMY and DSD based on each region is necessary and 5 regions were selected (Hwaseong, Suwon, Daejeon, Siheung and Gwangju) since the data size in these regions is large enough to perform the further statistical analysis based on large sample approximation theory. Correlation analysis showed that negative correlations were found between DMY and DSD in 3 (Hwaseong, Suwon and Siheung) out of the 5 regions, meanwhile the negative relationship in Hwaseong was confirmed through multiple regression analysis. Therefore, it was concluded that the interpretability of the yield prediction model for mixed pasture could be improved based on constructing the models using the data from each region separately instead of using the pooled data from different regions.

Risk Assessment of Pine Tree Dieback in Sogwang-Ri, Uljin (울진 소광리 금강소나무 고사발생 특성 분석 및 위험지역 평가)

  • Kim, Eun-Sook;Lee, Bora;Kim, Jaebeom;Cho, Nanghyun;Lim, Jong-Hwan
    • Journal of Korean Society of Forest Science
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    • v.109 no.3
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    • pp.259-270
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    • 2020
  • Extreme weather events, such as heat and drought, have occurred frequently over the past two decades. This has led to continuous reports of cases of forest damage due to physiological stress, not pest damage. In 2014, pine trees were collectively damaged in the forest genetic resources reserve of Sogwang-ri, Uljin, South Korea. An investigation was launched to determine the causes of the dieback, so that a forest management plan could be prepared to deal with the current dieback, and to prevent future damage. This study aimedto 1) understand the topographic and structural characteristics of the area which experienced pine tree dieback, 2) identify the main causes of the dieback, and 3) predict future risk areas through the use of machine-learning techniques. A model for identifying risk areas was developed using 14 explanatory variables, including location, elevation, slope, and age class. When three machine-learning techniques-Decision Tree, Random Forest (RF), and Support Vector Machine (SVM) were applied to the model, RF and SVM showed higher predictability scores, with accuracies over 93%. Our analysis of the variable set showed that the topographical areas most vulnerable to pine dieback were those with high altitudes, high daily solar radiation, and limited water availability. We also found that, when it came to forest stand characteristics, pine trees with high vertical stand densities (5-15 m high) and higher age classes experienced a higher risk of dieback. The RF and SVM models predicted that 9.5% or 115 ha of the Geumgang Pine Forest are at high risk for pine dieback. Our study suggests the need for further investigation into the vulnerable areas of the Geumgang Pine Forest, and also for climate change adaptive forest management steps to protect those areas which remain undamaged.

Analysis of Urban Heat Island (UHI) Alleviating Effect of Urban Parks and Green Space in Seoul Using Deep Neural Network (DNN) Model (심층신경망 모형을 이용한 서울시 도시공원 및 녹지공간의 열섬저감효과 분석)

  • Kim, Byeong-chan;Kang, Jae-woo;Park, Chan;Kim, Hyun-jin
    • Journal of the Korean Institute of Landscape Architecture
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    • v.48 no.4
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    • pp.19-28
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    • 2020
  • The Urban Heat Island (UHI) Effect has intensified due to urbanization and heat management at the urban level is treated as an important issue. Green space improvement projects and environmental policies are being implemented as a way to alleviate Urban Heat Islands. Several studies have been conducted to analyze the correlation between urban green areas and heat with linear regression models. However, linear regression models have limitations explaining the correlation between heat and the multitude of variables as heat is a result of a combination of non-linear factors. This study evaluated the Heat Island alleviating effects in Seoul during the summer by using a deep neural network model methodology, which has strengths in areas where it is difficult to analyze data with existing statistical analysis methods due to variable factors and a large amount of data. Wide-area data was acquired using Landsat 8. Seoul was divided into a grid (30m × 30m) and the heat island reduction variables were enter in each grid space to create a data structure that is needed for the construction of a deep neural network using ArcGIS 10.7 and Python3.7 with Keras. This deep neural network was used to analyze the correlation between land surface temperature and the variables. We confirmed that the deep neural network model has high explanatory accuracy. It was found that the cooling effect by NDVI was the greatest, and cooling effects due to the park size and green space proximity were also shown. Previous studies showed that the cooling effects related to park size was 2℃-3℃, and the proximity effect was found to lower the temperature 0.3℃-2.3℃. There is a possibility of overestimation of the results of previous studies. The results of this study can provide objective information for the justification and more effective formation of new urban green areas to alleviate the Urban Heat Island phenomenon in the future.