scholarly journals Co-Movement between Tourist Arrivals of Inbound Tourism Markets in South Korea: Applying the Dynamic Copula Method Using Secondary Time Series Data

2021 ◽  
Vol 13 (3) ◽  
pp. 1283
Author(s):  
Ki-Hong Choi ◽  
Insin Kim
Keyword(s):  
Time Series ◽  
South Korea ◽  
Time Series Data ◽  
Tail Dependence ◽  
Tourism Industry ◽  
Series Data ◽  
Dynamic Copula ◽  
Source Countries ◽  
Secondary Time ◽  
Dependence Structures

Tourism demand is severely affected by unpredicted events, which has prompted scholars to examine ways of predicting the effects of positive and negative shocks on tourism, to ensure a sustainable tourism industry. The purpose of this study was to investigate if non-linear dependence structures exist between tourist flows into South Korea from five major source countries, as South Korea has undergone fluctuations in tourist arrivals due to diverse circumstances and has complex relations with tourism source countries. Additionally, the study examines the structures of extreme tail dependence, which is indicated in the case of unexpected events, and identifies how co-movements vary over time through dynamic copula–GARCH (generalized autoregressive conditional heteroskedasticity) tests. The secondary time series data for the 2005–2019 period of tourist arrivals to Korea were derived from the Korea Tourism Knowledge and Information System for testing the copula models. The copula estimations indicate significant dependencies among all market pairs as well as the strongest dependence between China and Taiwan. Moreover, extreme tail dependence structures show co-movements for four pairs of tourism markets in only negative shocks, for five pairs in both positive and negative conditions, but no co-movement in the China–Taiwan pair. Finally, the dynamic dependence structures reveal that the China–Taiwan dependence is higher than the other time-varying dependence structures, implying that the two markets complement each other.

A Phenology Modelling Using MODIS Time Series Data in South Korea.

2014 ◽  
Vol 47 (3) ◽  
pp. 186-193 ◽  
Author(s):  
Nam-Shin Kim ◽  
◽  
Yong-Chan Cho ◽  
Seung-Hwan Oh ◽  
Hye-Jin Kwon ◽  
...  
Keyword(s):  
Time Series ◽  
South Korea ◽  
Time Series Data ◽  
Series Data

scholarly journals Optimization Algorithm of Tourism Security Early Warning Information System Based on Long Short-Term Memory (LSTM)

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lei Feng ◽  
Yukai Hao
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Information System ◽  
Optimization Algorithm ◽  
Early Warning ◽  
Time Series Data ◽  
Tourism Industry ◽  
Series Data ◽  
Prediction Ability ◽  
Analyze Data

Tourism safety is the focus of the tourism industry. It is not only related to the safety of tourists’ lives and property, but also related to social stability and sustainable development of the tourism industry. However, the security early warning of many scenic spots focuses on the response measures and remedial plans after the occurrence of security incidents, and the staff of many scenic spots have limited security awareness and information analysis ability, which is prone to lag in information release, and do not pay attention to the information of potential security problems. Therefore, this paper studies the optimization algorithm of the tourism security early warning information system based on the LSTM model and uses the recurrent neural network and LSTM to improve the processing and prediction ability of time-series data. The experimental results show that the number of three hidden layers in the tourism security early warning information system based on the LSTM model can reduce the training time of the model and improve the performance. Compared with the tourism safety early warning information system based on the BP neural network, it has better accuracy and stability, has better processing and prediction ability for time series data, and can monitor and analyze data scientifically in real-time and dynamically analyze data.

scholarly journals Optimalisasi Ekspor Produk Ekonomi Kreatif Indonesia Menuju Peningkatan Dayasaing

2020 ◽  
Vol 2 (3) ◽  
pp. 273-284
Author(s):  
Sugiyono Madelan
Keyword(s):  
Time Series ◽  
Research Method ◽  
Time Series Data ◽  
Education Level ◽  
Series Data ◽  
Creative Economy ◽  
Labor Costs ◽  
Fashion Products ◽  
Export Competitiveness ◽  
Secondary Time

Indonesia’s creative economy product exports have not been optimal. The purpose of this study is to optimize the goals of creative economic development in Indonesia. This research was conducted using secondary time series data for the period 2010-2017. The research method uses linear programming and goal programming. The results showed that exports of creative economy products responded to an increase in export selling prices based on the demand behavior of the exports of creative economy products. The factor of export competitiveness of Indonesia’s creative economy products lies in the use of cheaper labor costs. Exports of creative economy products do not automatically increase, if the education level of the workforce increases, but rather comes from an increase in creativity. Fashion products are efficient products compared to producing exports of craft products and culinary products. Finally, the development of the creative economy is more optimal for the purpose of increasing exports of creative economy products than for the purpose of increasing employment, namely by producing fashion products.

scholarly journals Integration of InSAR Time-Series Data and GIS to Assess Land Subsidence along Subway Lines in the Seoul Metropolitan Area, South Korea

2020 ◽  
Vol 12 (21) ◽  
pp. 3505
Author(s):  
Muhammad Fulki Fadhillah ◽  
Arief Rizqiyanto Achmad ◽  
Chang-Wook Lee
Keyword(s):  
Time Series ◽  
South Korea ◽  
Metropolitan Area ◽  
Land Subsidence ◽  
System Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Seoul Metropolitan Area ◽  
Persistent Scatterers ◽  
Multiclass Classifier

The aims of this research were to map and analyze the risk of land subsidence in the Seoul Metropolitan Area, South Korea using satellite interferometric synthetic aperture radar (InSAR) time-series data, and three ensemble machine-learning models, Bagging, LogitBoost, and Multiclass Classifier. Of the types of infrastructure present in the Seoul Metropolitan Area, subway lines may be vulnerable to land subsidence. In this study, we analyzed Persistent Scatterer InSAR time-series data using the Stanford Method for Persistent Scatterers (StaMPS) algorithm to generate a deformation time-series map. Subsidence occurred at four locations, with a deformation rate that ranged from 6–12 mm/year. Subsidence inventory maps were prepared using deformation time-series data from Sentinel-1. Additionally, 10 potential subsidence-related factors were selected and subjected to Geographic Information System analysis. The relationship between each factor and subsidence occurrence was analyzed by using the frequency ratio. Land subsidence susceptibility maps were generated using Bagging, Multiclass Classifier, and LogitBoost models, and map validation was carried out using the area under the curve (AUC) method. Of the three models, Bagging produced the largest AUC (0.883), with LogitBoost and Multiclass Classifier producing AUCs of 0.871 and 0.856, respectively.

scholarly journals ANALISIS PERTUMBUHAN DAN PERGESERAN SRUKTUR EKONOMI KABUPATEN INDUK DI PROVINSI BENGKULU

2020 ◽  
Vol 2 (1) ◽  
pp. 54-69
Author(s):  
Sunoto Sunoto ◽  
Bertha Iin Esti Indraswanti ◽  
Edy Rahmantyo Tarsilohadi
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Economic Development ◽  
Economic Performance ◽  
Time Series Data ◽  
Economic Structure ◽  
Series Data ◽  
Location Quotient ◽  
Dynamic Location ◽  
Secondary Time

The purpose of this research was to analyze economic growth and shifting of economic structure of the origin district in Bengkulu Province. Base on BPS secondary time series data (2001-2017), descriftive analysis was used to analyze economic growth and shifting economic structure, specialty after the region otonomous era (OTDA).  The DLQ and SSA method was used to determine the potential and leading sectors to increase economic performance. The result of this research was conclude that expansion of the the region in Bengkulu Provinsi has positif impact on economic development for the origin district. The economis structure was shifting from premier sector to secondary and tertier sector. The potential and leading sector after OTDA become more than before (from 4 or 5 sector to 7 untul 9 sector).  Keywords :  Dynamic Location Quotient 1, Shift Share Analysis 2, Economic Growth 3, Economic Structure 4, Potential and Leading Sector 5

scholarly journals ANALISIS PENGARUH INDUSTRI PARIWISATA TERHADAP PENYERAPAN TENAGA KERJA DI INDONESIA

2019 ◽  
Vol 7 (2) ◽  
pp. 155-159
Author(s):  
Annisa Nur Pita ◽  
Saiqa Ilham Akbar
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Cross Sections ◽  
Time Series Data ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Variable Number ◽  
Tourism Industry ◽  
Series Data ◽  
Tourism Sector

In 2017, the growth of the tourism sector in Indonesia ranked the ninth highest in the world (WTTC, 2018). Growth in the tourism sector also has an impact on employment in this sector. This study aims to estimate the effect of the development of the tourism industry on employment in the tourism sector and how much influence. The data used is secondary data from BPS. The form of data is panel data consisting of time series data and cross sections. The time series data is in 2010-2016 while the cross section data consists of 34 provinces in Indonesia. The analytical tool used is regression with panel data. The results of the fixed effect model panel regression can be seen that the probability value of each independent variable is less than the critical value of 5% (0.05). Then it can be concluded that the variable Number of Star Hotels, Number of Non-Star Hotels, Number of Domestic Tourists and Number of Foreign Tourists has a significant and positive effect on the Labor variable in Indonesia. The more the number of star hotels, the number of non-star hotels, the number of domestic tourists and the number of foreign tourists, the higher the absorption of the workforce in the tourism sector.

scholarly journals Discovering Spatial-temporal Patterns of COVID-19 Pandemic in South Korea: A Data-driven Approach using Dynamic Mode Decomposition

2021 ◽  
Author(s):  
Sungchan Kim ◽  
Minseok Kim ◽  
Sunmi Lee ◽  
Young Ju Lee
Keyword(s):  
Time Series ◽  
South Korea ◽  
Time Series Data ◽  
Temporal Patterns ◽  
Dynamic Mode Decomposition ◽  
Series Data ◽  
Dynamic Mode ◽  
Regional Patterns ◽  
Effective Prevention ◽  
Mode Decomposition

Abstract A novel severe acute respiratory syndrome coronavirus 2 emerged in December 2019, and it took only a few months for WHO to declare COVID-19 as a pandemic in March 2020. It is very challenging to discover complex spatial-temporal transmission mechanisms. However, it is crucial to capture essential features of regional-temporal patterns of COVID-19 to implement prompt and effective prevention or mitigation interventions. In this work, we develop a novel framework of compatible window-wise dynamic mode decomposition (CwDMD) for nonlinear infectious disease dynamics. The compatible window is a selected representative subdomain of time series data, in which compatibility between spatial and temporal resolutions is established so that DMD can provide meaningful data analysis. A total of four compatible windows have been selected from COVID-19 time-series data from January 20, 2020, to May 10, 2021, in South Korea. The spatiotemporal patterns of these four windows are then analyzed. Several hot and cold spots were identified, their spatial-temporal relationships, and some hidden regional patterns were discovered. Our analysis reveals that the first wave was contained in Daegu and Gyeongbuk area but it spread rapidly to the whole of South Korea after the second wave. Later on, the spatial distribution is seen to become more homogeneous after the third wave. Our analysis also identifies that some patterns are not related to regional relevance. These findings have then been analyzed and associated with the inter-regional and local characteristics of South Korea. Thus, the present study is expected to provide public health officials helpful insights for future regional-temporal specific mitigation plans.

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