Yelin Ko, Sora Shin, Yong Seok Choi, Byung-Hee Hong, Sang-Yoon Park and Joo-Young Lee
The purpose of the study was to explore heat-accumulative and thermal-conductive characteristics of copper-graphene composite film (Cu-G film) while applying it to a human-skin…
Abstract
Purpose
The purpose of the study was to explore heat-accumulative and thermal-conductive characteristics of copper-graphene composite film (Cu-G film) while applying it to a human-skin analogue.
Design/methodology/approach
In the preliminary experiment, the authors evaluated the thermal conductive characteristics of the Cu-G film in three covered conditions (no film, copper film, and Cu-G film conditions). For the first factorial experiment, the heat-accumulative properties over heated pig skin were compared at air temperatures of 10, 25 and 35°C. For the second factorial experiment, 105 trials were conducted on pig skin by combining air temperatures, trapped air volumes, and numbers of film layers.
Findings
The results from the preliminary experiment showed that the Cu-G film distributed the surface heat to the outside of the Cu-G film, which resulted in even distribution of heat inside and outside the Cu-G film, whereas the copper film accumulated heat inside the copper film. The human-skin analogue of pig skin, however, showed the opposite tendency from that of the plastic. The pig-skin temperatures beneath the Cu-G film were higher than those beneath the copper film, and those differences were remarkable at the air temperature of 10°C. The accumulative heat was affected by the trapped air volume, fit to the skin, and number of Cu-G film layers.
Originality/value
In conclusion, the Cu-G film more effectively accumulated heat on the human-skin analogue than copper film, and those effects were more marked in cold environments than in mild or hot environments.
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Minyoung Park, Jung Ung Min and Sang-Yoon Lee
Recent advancements in information and communication technologies have led to the rapid growth of electronic commerce market. In the United States, e-commerce retail sales for…
Abstract
Recent advancements in information and communication technologies have led to the rapid growth of electronic commerce market. In the United States, e-commerce retail sales for 2002 reached $45.6 billion, indicating an increase of 26.9% from 2001 while total retail sales increased 3.1% during the same period. Although e-commerce sales account for only 1.4% of total sales in this country, forecasts show that the magnitude of digital economy will continue to expand. The logistical requirements of e-commerce goods that extend to each customer's address stimulate greater complexity in traditional supply chain management, potentially causing higher costs for freight supply chain participants. To harness the economic potential of e-commerce, it is important to encourage the development of a freight transportation system that will support its steady growth, while avoiding the possible negative effects from the changes in freight transportation. Due to the intrinsic nature of e-commerce goods, advances in home delivery have the potential to promote the growth of e-commerce as well as to create sustainable urban freight transportation systems. Based on the case study of the United States, this paper presents an in-depth discussion of the key challenges arising in home delivery operations, and proposes potential solution strategies that will lead to more efficient and reliable home delivery systems.
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Kyong Han Lee and Sang-Yoon Lee
The purpose of this study is to empirically analyze the impact of logistics efficiency on trade volume growth, and to examine the effects of lower tariffs resulting from free…
Abstract
The purpose of this study is to empirically analyze the impact of logistics efficiency on trade volume growth, and to examine the effects of lower tariffs resulting from free trade agreements. In order to measure the impact of logistics efficiency on trade volume growth, the export and import trade volume among 53 countries was introduced as the dependent variable. Macroeconomic indicators including annual average tariff rate, logistics efficiency indicators for port, air, railroad, road and container vessel connectivity, as well as dummy variables such as whether a free trade agreement was signed, were introduced as the explanatory variables. Bilateral panel data between trading nations was used to estimate the gravity panel model, and analysis followed the categorization: 1) separate inputs of the five logistics efficiency variables and 2) one aggregated input of the five variables as a single indicator. The analysis found that logistics efficiency had a statistically significant impact on bilateral trade volume growth, while the impact of lowering tariff rates on increasing trade was insignificant. In addition, logistics efficiency was found to have a greater impact on increasing trade volume than free trade agreements. These results imply that trade can be promoted more effectively by establishing and efficiently operating logistics-related infrastructure rather than traditional methods of reducing trade barriers such as lowering tariffs and signing free trade agreements.
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Xin Yue Zhang and Sang Yoon Lee
In the current dynamic business environment, Internet of Things (IoT) is employed by a number of companies in the logistics industry to achieve intelligent sorting, network…
Abstract
Purpose
In the current dynamic business environment, Internet of Things (IoT) is employed by a number of companies in the logistics industry to achieve intelligent sorting, network optimization, real-time tracking and simplifying last-mile service. Although logistics entities are trying to introduce IoT into their business areas, users' perception of this new technology is still limited. This paper aims to develop a research model for the factors influencing the user adoption of IoT technology in the logistics industry.
Design/methodology/approach
In this study, based on the major theories on the application of new technologies such as technology acceptance model (TAM), technology–organization–environment (TOE) and innovation diffusion theory (IDT), a new research model was established to identify factors affecting customers' behavioral intention (BI) to adopt IoT technology provided by logistics companies. In addition, the authors surveyed unspecified customers of Cainiao Logistics Network, which is in charge of the logistics operation of Alibaba Group, China's largest e-commerce company, and tested the causality between the latent variables presented in the model using the structural equation model (SEM).
Findings
This empirical study shows that the support system of a logistics company and users' innovative propensity significantly affect perceived ease of use (PEOU) and BI for logistics services to which IoT technology is applied. It also presents that users' perceived security and enjoyment significantly affect perceived usefulness (PU) and BI. In addition, it was possible to confirm that the causal structure between variables suggested by TAM that PEOU has a significant effect on PU and BI, and PU has a substantial effect on BI.
Practical implications
Logistics companies should expand and upgrade technical support systems so that customers can flexibly accept logistics services with IoT technology and make efforts to alleviate customers' concerns about personal information leakage. In addition, it is necessary to find customers with an inclusive attitude toward using new technologies, to induce them to become leading users of logistics devices with IoT technology and to find various ways to amplify their enjoyment. Through a strategic approach to these technical and individual factors, it will be possible to boost customers' intention to use IoT logistics services.
Originality/value
As far as the authors know, this paper is the first study to set significant factors that affect users' BI to use IoT technology-applied logistics services provided by logistics companies and empirically analyze the causal relationships between proposed latent variables.
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Hyelim Lee, Xiaochen Angela Zhang, Yoon Hi Sung, Sihyeok Lee and Jeong-Nam Kim
This research aims to examine how two management strategies (symmetrical communication and inclusive management) work in handling workplace conflicts (interpersonal/organizational…
Abstract
Purpose
This research aims to examine how two management strategies (symmetrical communication and inclusive management) work in handling workplace conflicts (interpersonal/organizational levels), especially with regard to employee advocacy and job turnover intentions.
Design/methodology/approach
A total of three employee survey datasets were used to test hypotheses and research questions. Two secondary datasets were obtained in South Korea (N = 600 and N = 285), and one dataset was collected in the USA (N = 381). A series of hierarchical multiple regressions were performed for each dataset.
Findings
All three studies showed that interpersonal workplace conflict increased not only job turnover but also advocacy. In addition, in South Korean employees, both symmetrical communication and inclusive management increased employee advocacy and decreased job turnover intentions. However, in the US data, only symmetrical communication had such effects, enhancing employee advocacy and lowering job turnover intentions.
Originality/value
The study provides insights for practitioners into how to handle workplace conflicts from the perspective of communication (symmetrical communication) and/or behavioral strategies (inclusive management). Also, as an index to examine the effectiveness of management strategies, this study suggests advocacy behavior of employees given its effect of “rallying the troops.”
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Roberta A. Scull and Barbara S. Kavanaugh
Bobbie Scull's bibliography of federal government bibliographies was begun in 1971 as an annual informational publication primarily intended for the faculty at Louisiana State…
Abstract
Bobbie Scull's bibliography of federal government bibliographies was begun in 1971 as an annual informational publication primarily intended for the faculty at Louisiana State University. Later she distributed it to libraries all over the state of Louisiana. In 1973 RSR began to publish these lists on an annual basis. This is the fourth such appearance. In the meantime these bibliographies were cumulated and published in two volumes: Bibliography of U.S. Government Bibliographies 1968–73 and 1974–76. (Pierian Press, 1975, 1979). RSR is proud to continue the annual supplements which are now computer produced at LSU. Although this supplement appears in Volume 8:1 (1980) in the future they will appear in the final issue of the year.
Yoon-Sung Kim, Hae-Chang Rim and Do-Gil Lee
The purpose of this paper is to propose a methodology to analyze a large amount of unstructured textual data into categories of business environmental analysis frameworks.
Abstract
Purpose
The purpose of this paper is to propose a methodology to analyze a large amount of unstructured textual data into categories of business environmental analysis frameworks.
Design/methodology/approach
This paper uses machine learning to classify a vast amount of unstructured textual data by category of business environmental analysis framework. Generally, it is difficult to produce high quality and massive training data for machine-learning-based system in terms of cost. Semi-supervised learning techniques are used to improve the classification performance. Additionally, the lack of feature problem that traditional classification systems have suffered is resolved by applying semantic features by utilizing word embedding, a new technique in text mining.
Findings
The proposed methodology can be used for various business environmental analyses and the system is fully automated in both the training and classifying phases. Semi-supervised learning can solve the problems with insufficient training data. The proposed semantic features can be helpful for improving traditional classification systems.
Research limitations/implications
This paper focuses on classifying sentences that contain the information of business environmental analysis in large amount of documents. However, the proposed methodology has a limitation on the advanced analyses which can directly help managers establish strategies, since it does not summarize the environmental variables that are implied in the classified sentences. Using the advanced summarization and recommendation techniques could extract the environmental variables among the sentences, and they can assist managers to establish effective strategies.
Originality/value
The feature selection technique developed in this paper has not been used in traditional systems for business and industry, so that the whole process can be fully automated. It also demonstrates practicality so that it can be applied to various business environmental analysis frameworks. In addition, the system is more economical than traditional systems because of semi-supervised learning, and can resolve the lack of feature problem that traditional systems suffer. This work is valuable for analyzing environmental factors and establishing strategies for companies.