Pub Date : 2022-10-31DOI: 10.17825/klr.2022.32.5.77
Jinhee Lim, S. Woo
While the outbreak of Covid-19 brought in enormous damage throughout world economically, socially, and culturally, the aviation industry was severely damaged because air passenger transportation was barely active during the pandemic due to movement restrictions and blockades imposed in many countries. This study aims at investigating changes of air cargo transportation network which were made before and during the pandemic. To this end, this study collected air freight data among Korea, China, Japan, Hong Kong, and Macau as origin and destination countries. Freight revenue traffic data of On-flight origin and destination were collected from ICAO database from 2016 to 2020 with years of 2016 to 2019 being before the outbreak of Covid-19 and year of 2020 being after it. Social Network Analysis was undertaken using Netminer. It was found that nodes, links, density, and clustering of Northeast Asian air cargo networks significantly decreased after the outbreak of Covid-19 and network connection was also weakened.
{"title":"Changes of Northeast Asian Air Cargo Network During Covid-19 Pandemic","authors":"Jinhee Lim, S. Woo","doi":"10.17825/klr.2022.32.5.77","DOIUrl":"https://doi.org/10.17825/klr.2022.32.5.77","url":null,"abstract":"While the outbreak of Covid-19 brought in enormous damage throughout world economically, socially, and culturally, the aviation industry was severely damaged because air passenger transportation was barely active during the pandemic due to movement restrictions and blockades imposed in many countries. This study aims at investigating changes of air cargo transportation network which were made before and during the pandemic. To this end, this study collected air freight data among Korea, China, Japan, Hong Kong, and Macau as origin and destination countries. Freight revenue traffic data of On-flight origin and destination were collected from ICAO database from 2016 to 2020 with years of 2016 to 2019 being before the outbreak of Covid-19 and year of 2020 being after it. Social Network Analysis was undertaken using Netminer. It was found that nodes, links, density, and clustering of Northeast Asian air cargo networks significantly decreased after the outbreak of Covid-19 and network connection was also weakened.","PeriodicalId":430866,"journal":{"name":"Korean Logistics Research Association","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130034990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-31DOI: 10.17825/klr.2022.32.5.65
Yun-Jin Kim, Yong-Jeong Kim
The purpose of the study is to identify the degree of production induction effects and industrial synergy effects of the last mile delivery service industry. It also connects the industrial linkage structure of the last mile delivery industry with the concept of the supply chain. Ultimately, it identifies the structure of the service supply chain centered on the last mile delivery. It approaches research problems from a service science perspective. The philosophical basis of the study is the concept of service dominant logic. In addition, the research methodology is an inter-industry analysis of economics, and WIOD is used for analysis data. Petroleum product manufacturing and warehousing are the backward industries of the last mile delivery industry. And it seems clear that wholesale and retail industry are forward industries. Therefore, the last mile delivery industry plays a role in connecting the relationship between the supply industry, the manufacturing industry, and the distribution industry on the supply chain. In addition, the supply chain architecture of the last mile delivery service is significantly different from the existing manufacturing-oriented supply chain structure. Academically, the concept of a traditional manufacturing-oriented supply chain has been expanded to the service sector. And it identified the supply chain structure of the last mile delivery service. In practice, if a strategic industry is selected with limited resources, it will be an important indicator for determining investment priorities.
{"title":"An Exploratory Study on the Supply Chain Structure of the Last Mile Delivery Industry Using Inter-Industry Analysis","authors":"Yun-Jin Kim, Yong-Jeong Kim","doi":"10.17825/klr.2022.32.5.65","DOIUrl":"https://doi.org/10.17825/klr.2022.32.5.65","url":null,"abstract":"The purpose of the study is to identify the degree of production induction effects and industrial synergy effects of the last mile delivery service industry. It also connects the industrial linkage structure of the last mile delivery industry with the concept of the supply chain. Ultimately, it identifies the structure of the service supply chain centered on the last mile delivery. It approaches research problems from a service science perspective. The philosophical basis of the study is the concept of service dominant logic. In addition, the research methodology is an inter-industry analysis of economics, and WIOD is used for analysis data. Petroleum product manufacturing and warehousing are the backward industries of the last mile delivery industry. And it seems clear that wholesale and retail industry are forward industries. Therefore, the last mile delivery industry plays a role in connecting the relationship between the supply industry, the manufacturing industry, and the distribution industry on the supply chain. In addition, the supply chain architecture of the last mile delivery service is significantly different from the existing manufacturing-oriented supply chain structure. Academically, the concept of a traditional manufacturing-oriented supply chain has been expanded to the service sector. And it identified the supply chain structure of the last mile delivery service. In practice, if a strategic industry is selected with limited resources, it will be an important indicator for determining investment priorities.","PeriodicalId":430866,"journal":{"name":"Korean Logistics Research Association","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121469762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-31DOI: 10.17825/klr.2022.32.5.89
Dong-Yun Kim, Hee-Yeon Jo, Yunhong Min
Since the untact trend brought on by the COVID-19 pandemic, one of the fastest growing industries is the meal delivery industry. Unlike in the past, the meal delivery industry has been restructured to focus on ordering using delivery apps as the spread of mobile devices expands, and competition between the three major platform(Baemin, Yogiyo, Coupang Eats) is ongoing. A special turning point came in the competition between them in 2019, and that is “One order per trip” service introduced by Coupang Eats, a latecomer. This service was later introduced to other platforms due to high customer satisfaction, but it caused a problem in rider revenue under insufficient rider supply, causing a social issue. This study is based on the fact that this service fee does not take into account the number of deliveries, but only the simple delivery distance, and using simulation of rider-order matching, analyzes the correlation between the number of deliveries and the delivery distance and the imbalance in the delivery distance of riders. As a result of the simulation experiment conducted by fixing the number of riders and changing the number of orders, the ratio of the number of deliveries and the delivery distance is constant on average. And as the ratio of number of orders/number of riders increases, the standard deviation decreases. In addition, as the ratio of the number of orders to the number of passengers increases, the standard deviation of the travel distance decreases. This is also true when the locations of restaurants are concentrated, but in this case the absolute value of the standard deviation is smaller.
{"title":"A Simulation Study on Rider-order Matching in Meal Delivery Service","authors":"Dong-Yun Kim, Hee-Yeon Jo, Yunhong Min","doi":"10.17825/klr.2022.32.5.89","DOIUrl":"https://doi.org/10.17825/klr.2022.32.5.89","url":null,"abstract":"Since the untact trend brought on by the COVID-19 pandemic, one of the fastest growing industries is the meal delivery industry. Unlike in the past, the meal delivery industry has been restructured to focus on ordering using delivery apps as the spread of mobile devices expands, and competition between the three major platform(Baemin, Yogiyo, Coupang Eats) is ongoing. A special turning point came in the competition between them in 2019, and that is “One order per trip” service introduced by Coupang Eats, a latecomer. This service was later introduced to other platforms due to high customer satisfaction, but it caused a problem in rider revenue under insufficient rider supply, causing a social issue. This study is based on the fact that this service fee does not take into account the number of deliveries, but only the simple delivery distance, and using simulation of rider-order matching, analyzes the correlation between the number of deliveries and the delivery distance and the imbalance in the delivery distance of riders. As a result of the simulation experiment conducted by fixing the number of riders and changing the number of orders, the ratio of the number of deliveries and the delivery distance is constant on average. And as the ratio of number of orders/number of riders increases, the standard deviation decreases. In addition, as the ratio of the number of orders to the number of passengers increases, the standard deviation of the travel distance decreases. This is also true when the locations of restaurants are concentrated, but in this case the absolute value of the standard deviation is smaller.","PeriodicalId":430866,"journal":{"name":"Korean Logistics Research Association","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126809509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-31DOI: 10.17825/klr.2022.32.4.69
Xinyue Tian, Xindan Zhang, Kihyung Bae
The purpose of this study is to make econometric analysis on the economic effects of China’s logistics industry by using the China industry association table, and provide help for the promotion of China’s logistics industry policy in the future. For this reason, 17 industrial fields, including 5 fields of transportation equipment and 12 fields of transportation service industry, are classified as logistics industry in the 2020 industrial association table issued by the China Bureau of statistics in 2022, and the industrial association table of China’s logistics industry for all 28 industries is compiled and analyzed. The analysis results show that, first of all, the production inducement coefficient of China’s logistics industry is 2.7956, and the line cooperation coefficient is 4.6270, indicating that China’s logistics industry is a basic strategic industry supporting the development of national economy. Second, the influence coefficient (backward chain effect) of China’s logistics industry is 1.0466, and the sensitivity coefficient (forward chain effect) is 1.7322, both greater than 1. China’s logistics industry is an intermediate demand manufacturing industry. Third, the final demand of China’s logistics industry is 8382 billion yuan for input into the national economy. The total production induced amount is 626916.8 trillion yuan (38783.5 trillion yuan, 6.2%) and the value-added induced amount is 224227.75 billion yuan (13718.8 trillion yuan, 6.1%) respectively. The income induced amount is 11420.4 trillion yuan (691.34 billion yuan, 6.1%) respectively, The induced amount of production tax is 23469.2 billion yuan (1379.3 trillion yuan, 5.9%) in the logistics industry. Fourth, China’s logistics industry has a total of 30627 labor inducing effects, including 849 direct labor inducing personnel and 29778 indirect labor inducing personnel, showing its role as an employment creating industry.
{"title":"An Analysis of the Economic Effects of Logistics Industry through I-O Table: Focusing on China’s logistics industry","authors":"Xinyue Tian, Xindan Zhang, Kihyung Bae","doi":"10.17825/klr.2022.32.4.69","DOIUrl":"https://doi.org/10.17825/klr.2022.32.4.69","url":null,"abstract":"The purpose of this study is to make econometric analysis on the economic effects of China’s logistics industry by using the China industry association table, and provide help for the promotion of China’s logistics industry policy in the future. For this reason, 17 industrial fields, including 5 fields of transportation equipment and 12 fields of transportation service industry, are classified as logistics industry in the 2020 industrial association table issued by the China Bureau of statistics in 2022, and the industrial association table of China’s logistics industry for all 28 industries is compiled and analyzed. The analysis results show that, first of all, the production inducement coefficient of China’s logistics industry is 2.7956, and the line cooperation coefficient is 4.6270, indicating that China’s logistics industry is a basic strategic industry supporting the development of national economy. Second, the influence coefficient (backward chain effect) of China’s logistics industry is 1.0466, and the sensitivity coefficient (forward chain effect) is 1.7322, both greater than 1. China’s logistics industry is an intermediate demand manufacturing industry. Third, the final demand of China’s logistics industry is 8382 billion yuan for input into the national economy. The total production induced amount is 626916.8 trillion yuan (38783.5 trillion yuan, 6.2%) and the value-added induced amount is 224227.75 billion yuan (13718.8 trillion yuan, 6.1%) respectively. The income induced amount is 11420.4 trillion yuan (691.34 billion yuan, 6.1%) respectively, The induced amount of production tax is 23469.2 billion yuan (1379.3 trillion yuan, 5.9%) in the logistics industry. Fourth, China’s logistics industry has a total of 30627 labor inducing effects, including 849 direct labor inducing personnel and 29778 indirect labor inducing personnel, showing its role as an employment creating industry.","PeriodicalId":430866,"journal":{"name":"Korean Logistics Research Association","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124803567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-31DOI: 10.17825/klr.2022.32.4.93
Eun-Young Park
Anthropomorphizing chatbots can produce more effective consumer interactions owing to the human warmth provided by the chatbot. This study expands the scope of previous studies by examining the influence of loneliness, a personal consumer characteristic, on the acceptance intention of a chatbot recommendation. Additionally, the moderating effect of chatbot conversation style (warmth vs. competence) on this relationship was examined. To verify this hypothesis, we conducted two pretests and one laboratory experiment. The results of the analysis indicate that the higher the degree of loneliness, the stronger the tendency to accept chatbot recommendations (Hypothesis 1). Particularly, when the chatbot interacts in a warm manner, consumers who are experiencing loneliness are more likely to accept chatbot recommendations. However, when the chatbot interacts competently, the degree of loneliness does not affect the acceptance intention of the chatbot recommendation (Hypothesis 2). This finding contributes to the literature on chatbot anthropomorphism and provides practical information for chatbot conversation decisions in relation to consumer characteristics.
{"title":"Effects of Consumer Loneliness on Chatbot Recommendation Intention: Moderating Effects of Chatbot Conversation Style","authors":"Eun-Young Park","doi":"10.17825/klr.2022.32.4.93","DOIUrl":"https://doi.org/10.17825/klr.2022.32.4.93","url":null,"abstract":"Anthropomorphizing chatbots can produce more effective consumer interactions owing to the human warmth provided by the chatbot. This study expands the scope of previous studies by examining the influence of loneliness, a personal consumer characteristic, on the acceptance intention of a chatbot recommendation. Additionally, the moderating effect of chatbot conversation style (warmth vs. competence) on this relationship was examined. To verify this hypothesis, we conducted two pretests and one laboratory experiment. The results of the analysis indicate that the higher the degree of loneliness, the stronger the tendency to accept chatbot recommendations (Hypothesis 1). Particularly, when the chatbot interacts in a warm manner, consumers who are experiencing loneliness are more likely to accept chatbot recommendations. However, when the chatbot interacts competently, the degree of loneliness does not affect the acceptance intention of the chatbot recommendation (Hypothesis 2). This finding contributes to the literature on chatbot anthropomorphism and provides practical information for chatbot conversation decisions in relation to consumer characteristics.","PeriodicalId":430866,"journal":{"name":"Korean Logistics Research Association","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129454144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-31DOI: 10.17825/klr.2022.32.4.1
Intaek Gong, Dong-Yun Kim, Moo-Young Kim, Yunhong Min
As economies of scale in container transport are maximized with the introduction of mega container ships, ports and terminals are also making great efforts to prepare for an increase in their capacities. One example of such efforts is the use of a new type of quay crane that can simultaneously lift more than one container at a time. This quay crane can lift one or more containers depending on its lifting mode. However, scheduling of this crane is more complicated than scheduling of existing quay cranes because it is necessary to consider the weight limit of containers to be lifted, and the set-up time required for changing the lifting mode. Previous study has already mentioned the importance of this problem and suggested solutions for it, but since there are not many, verification of various approaches is necessary. This paper addresses the scheduling problem of dual-spreader quay crane that can lift up-to two containers at a time. We propose a Markov decision process (MDP) model for the problem. In order to reduce the computation time required to obtain a solution, instead of applying dynamic programming, we propose a heuristic that only considers a subset of states and transition functions used for searching solutions. Since this heuristic does not consider all possible states and transition functions, it cannot guarantee that an optimal solution is derived. However, as confirmed through experiments, it finds a solution close to the optimal solution for relatively small-sized instances. And, for larger-sized instances, while commercial software did not find an optimal solution for one hour, this heuristic can find a solution. Moreover, the solution from the proposed heuristic has better quality than the solution found by commercial software for one hour.
{"title":"A Study on the Dynamic Programming-based Algorithm for the Dual-spreader Quay Crane Scheduling","authors":"Intaek Gong, Dong-Yun Kim, Moo-Young Kim, Yunhong Min","doi":"10.17825/klr.2022.32.4.1","DOIUrl":"https://doi.org/10.17825/klr.2022.32.4.1","url":null,"abstract":"As economies of scale in container transport are maximized with the introduction of mega container ships, ports and terminals are also making great efforts to prepare for an increase in their capacities. One example of such efforts is the use of a new type of quay crane that can simultaneously lift more than one container at a time. This quay crane can lift one or more containers depending on its lifting mode. However, scheduling of this crane is more complicated than scheduling of existing quay cranes because it is necessary to consider the weight limit of containers to be lifted, and the set-up time required for changing the lifting mode. Previous study has already mentioned the importance of this problem and suggested solutions for it, but since there are not many, verification of various approaches is necessary. This paper addresses the scheduling problem of dual-spreader quay crane that can lift up-to two containers at a time. We propose a Markov decision process (MDP) model for the problem. In order to reduce the computation time required to obtain a solution, instead of applying dynamic programming, we propose a heuristic that only considers a subset of states and transition functions used for searching solutions. Since this heuristic does not consider all possible states and transition functions, it cannot guarantee that an optimal solution is derived. However, as confirmed through experiments, it finds a solution close to the optimal solution for relatively small-sized instances. And, for larger-sized instances, while commercial software did not find an optimal solution for one hour, this heuristic can find a solution. Moreover, the solution from the proposed heuristic has better quality than the solution found by commercial software for one hour.","PeriodicalId":430866,"journal":{"name":"Korean Logistics Research Association","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129501178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-31DOI: 10.17825/klr.2022.32.4.115
C. Ryu, Joungho Lee
Environmental disclosures entail costs, yet increasingly, large listed firms are making higher and better quality disclosures. The purpose of this study is to examine the link between a firm’s environmental effort and financial performance. Specifically, this study investigates the direction of the casual relationship between the environmental disclosures and return on sales in logistics industry. Drawing on literature streams in socio-political theory, legitimacy theory, resource-based view, and voluntary disclosure theory, this study develops and tests the Ganger casualty model of relationships between constructs that form the basis of the proposed theories. Conducting an empirical study of 154 Korean listed firms in logistics industry, this study provides empirical evidences for the direction of the casual relationship between environmental effort and financial performance. Empirical results of this study show that past profitability drives current environmental disclosures. Further analysis reveals that firms that make higher financial performance have higher environmental effort. These findings are consistent with the voluntary disclosure theory and the resource based view of the firm, suggesting that firms with greater economic resources make more extensive environmental disclosures which yield net positive profitability.
{"title":"The Relationship between Corporate Environmental Effort and Financial Performance: Focusing on Logistics Industry","authors":"C. Ryu, Joungho Lee","doi":"10.17825/klr.2022.32.4.115","DOIUrl":"https://doi.org/10.17825/klr.2022.32.4.115","url":null,"abstract":"Environmental disclosures entail costs, yet increasingly, large listed firms are making higher and better quality disclosures. The purpose of this study is to examine the link between a firm’s environmental effort and financial performance. Specifically, this study investigates the direction of the casual relationship between the environmental disclosures and return on sales in logistics industry. Drawing on literature streams in socio-political theory, legitimacy theory, resource-based view, and voluntary disclosure theory, this study develops and tests the Ganger casualty model of relationships between constructs that form the basis of the proposed theories. Conducting an empirical study of 154 Korean listed firms in logistics industry, this study provides empirical evidences for the direction of the casual relationship between environmental effort and financial performance. Empirical results of this study show that past profitability drives current environmental disclosures. Further analysis reveals that firms that make higher financial performance have higher environmental effort. These findings are consistent with the voluntary disclosure theory and the resource based view of the firm, suggesting that firms with greater economic resources make more extensive environmental disclosures which yield net positive profitability.","PeriodicalId":430866,"journal":{"name":"Korean Logistics Research Association","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126960041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-31DOI: 10.17825/klr.2022.32.4.55
Joonhyeong Joseph Kim
This research aims to highlight issues related to logistics and robot applying a text mining technique to Naver news article big data at the time of paying much attention to AI and big data technology as well as agenda on fourth industrial revolution. In ordr to analyze the role of robots in the logistics industry, this study employed 609 NAVER news articles from January 21, 2020 to December 31, 2020 for the analysis, excluding redundant and irrelevant articles. News article frequency analysis, news article keyworkd analysis, cosine similarity and co-occurence frequency analysis were conducted for the visualization of the research findings employing R program in order to invegstigate into the main issues related to news articles.. Cosine similarity and co-occurrence frequency as well as wordcloud analysis was visualized. It was found that the the news articles dealing with robots and logistics addressed the subjects related to corporations, robot, technology, and logistics together, presenting these keywords in the ranking of keyword frequency from the various perspectives. It is suggested that specific projects on delivery of products/services in an efficent manner needs to be initiated in order to apply the technology of robotics to not only the logistics industry, but also service industry (e.g., hotel and tourism-related businesses). This study has contributed to the presentation of the issue on robot among the fourth industrial revolution technologies.
{"title":"Text Mining Analysis on Robot and Logistics: Employing NAVER News Article Big Data","authors":"Joonhyeong Joseph Kim","doi":"10.17825/klr.2022.32.4.55","DOIUrl":"https://doi.org/10.17825/klr.2022.32.4.55","url":null,"abstract":"This research aims to highlight issues related to logistics and robot applying a text mining technique to Naver news article big data at the time of paying much attention to AI and big data technology as well as agenda on fourth industrial revolution. In ordr to analyze the role of robots in the logistics industry, this study employed 609 NAVER news articles from January 21, 2020 to December 31, 2020 for the analysis, excluding redundant and irrelevant articles. News article frequency analysis, news article keyworkd analysis, cosine similarity and co-occurence frequency analysis were conducted for the visualization of the research findings employing R program in order to invegstigate into the main issues related to news articles.. Cosine similarity and co-occurrence frequency as well as wordcloud analysis was visualized. It was found that the the news articles dealing with robots and logistics addressed the subjects related to corporations, robot, technology, and logistics together, presenting these keywords in the ranking of keyword frequency from the various perspectives. It is suggested that specific projects on delivery of products/services in an efficent manner needs to be initiated in order to apply the technology of robotics to not only the logistics industry, but also service industry (e.g., hotel and tourism-related businesses). This study has contributed to the presentation of the issue on robot among the fourth industrial revolution technologies.","PeriodicalId":430866,"journal":{"name":"Korean Logistics Research Association","volume":"168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115845250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-31DOI: 10.17825/klr.2022.32.4.105
M. Cho, Taeyong Kim, Bowon Lee
In the field of logistics, port congestion can cause a seriously negative impact on the cost and efficiency of port operations, due to increased container processing time. Although numerous logistics companies are trying to make their transportation system more efficient, solving the port congestion problem has seldom been studied. In this paper, we explore methods for turn-time prediction of container trucks for efficient port operations. For the dataset, real-world data containing complex data such as truck license plate number, time, and loading/unloading information accumulated for five years at a port terminal company are used and the turn-time prediction algorithm based-on the LSTM model was constructed. For the implementation of the turn-time prediction algorithm, a given time series data was classified into three types: time, day, and week, and used as the input data for the model. When constructing a prediction algorithm based on the time type, it was found that when the input time interval was 7 hours, the time error was 18.31 minutes, which is about a 27% decrease in the time error compared to the time error of 25.17 minutes at 20 hours, which is the lowest input time interval. In the case of the day type, when the time interval is longer, the higher the prediction accuracy can be obtained. When setting the time interval to 20 days, the time error was the highest at 18.18 minutes and the time error was decreased by 30% compared to the time error of 25.82 minutes at the time interval of the 3-day with the lowest accuracy. For the week type, the time error was the lowest at 32.03 minutes when set to a three-week time interval. On the other hand, when the time interval was set to 7 weeks, the time error was 14.13 minutes, showing the time error reduction of more than 57% and the best performance among the total results. In addition, in order to increase the utilization of the above prediction model, we introduced a system consisting of various components such as data acquisition, processing, and analysis along with a mobile user application.
{"title":"Turn-time Prediction System Implementation of Container Trucks at the Port Terminal","authors":"M. Cho, Taeyong Kim, Bowon Lee","doi":"10.17825/klr.2022.32.4.105","DOIUrl":"https://doi.org/10.17825/klr.2022.32.4.105","url":null,"abstract":"In the field of logistics, port congestion can cause a seriously negative impact on the cost and efficiency of port operations, due to increased container processing time. Although numerous logistics companies are trying to make their transportation system more efficient, solving the port congestion problem has seldom been studied. In this paper, we explore methods for turn-time prediction of container trucks for efficient port operations. For the dataset, real-world data containing complex data such as truck license plate number, time, and loading/unloading information accumulated for five years at a port terminal company are used and the turn-time prediction algorithm based-on the LSTM model was constructed. For the implementation of the turn-time prediction algorithm, a given time series data was classified into three types: time, day, and week, and used as the input data for the model. When constructing a prediction algorithm based on the time type, it was found that when the input time interval was 7 hours, the time error was 18.31 minutes, which is about a 27% decrease in the time error compared to the time error of 25.17 minutes at 20 hours, which is the lowest input time interval. In the case of the day type, when the time interval is longer, the higher the prediction accuracy can be obtained. When setting the time interval to 20 days, the time error was the highest at 18.18 minutes and the time error was decreased by 30% compared to the time error of 25.82 minutes at the time interval of the 3-day with the lowest accuracy. For the week type, the time error was the lowest at 32.03 minutes when set to a three-week time interval. On the other hand, when the time interval was set to 7 weeks, the time error was 14.13 minutes, showing the time error reduction of more than 57% and the best performance among the total results. In addition, in order to increase the utilization of the above prediction model, we introduced a system consisting of various components such as data acquisition, processing, and analysis along with a mobile user application.","PeriodicalId":430866,"journal":{"name":"Korean Logistics Research Association","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125359434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-31DOI: 10.17825/klr.2022.32.4.79
Hw Lee, M. Ha
This study is the second step in a series of research on risk management and evaluation of container ports in Korea and focuses on the development of the risk evaluation framework. And then, the framework was applied to Incheon port to evaluate the risk levels of the selected risk factors and the total risk level in the context of container operations. The port risk evaluation framework developed in this study is a hybrid model of the FER algorithm and Utility Techniques by incorporating AHP to evaluate the weights and risk level of each risk factor, leading to driving the weighted risk level of the individual risk factor as well as the total risk level of the alternative port. Consequently, the results obtained by the risk evaluation model are expected to be used by port risk managers as diagnostic tools to mitigate port risk or to improve risk management practices. In addition, the results will be used as basic data for the risk control options(RCOs) selection and the cost-benefit(C/B)analysis for further study.
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