• Design & Manufacturing
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• v.18 no.3
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• pp.15-21
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• 2024

This study investigates the causes of wrinkle defects in PA12-insulated busbars used in electric vehicles and proposes an improvement method to address these issues. Busbars, essential components for efficient current transmission in electric vehicle battery modules, require complex three-dimensional bending to optimize internal layouts. For this study, oxygen-free copper busbars with a 0.8 mm PA12 insulation coating were subjected to three types of bending tests: flat bending, edge bending, and torsional bending. Experimental results showed that wrinkle defects only occurred during edge bending, while flat and torsional bending modes exhibited no significant issues. Cross-sectional analysis revealed that the PA12 insulation layer's thickness was uneven, with thinner sections on flat areas and thicker accumulation at the comers. This uneven distribution led to poor adhesion between the insulation and copper layers, resulting in the formation of wrinkles, particularly in areas with air gaps ranging from 75 to 250 ㎛. To further analyze the issue, finite element analysis (FEA) of the bending process was performed under adhesive and non-adhesive conditions. The results confirmed that wrinkles formed when the adhesion between the copper and PA12 coating was insufficient. Improved adhesion conditions, achieved through a heat treatment process at 120℃ for 2 hours, significantly reduced the occurrence of wrinkles during edge bending. This study demonstrates that optimizing the adhesion between the insulation coating and the copper busbar, through controlled heat treatment, can prevent wrinkle defects. The findings provide a pathway for enhancing the durability and performance of insulated busbars in electric vehicle applications.

• Journal of Distribution Science
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• v.9 no.2
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• pp.31-36
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• 2011

I conducted empirical analyses of what happens when an offline channel expands to an online channel and whether the pre-existing offline channel's competitive assets (e.g. brand reputation and level of service satisfaction) can be linked to online channel preference. I found that an offline channel's brand reputation and level of service satisfaction can have a direct influence on offline channel preference and a second-hand influence on online channel preference. Thus, if the competitiveness of the online channel is strong enough and its customers have a higher preference for the offline channel, they will be committed and loyal to the company. The resultant enhanced competitiveness of the offline channel will present opportunities for both present and future success. The main results are the following. First, the management of the distribution channel service quality is more important than that of the brand reputation. Customers' experiences of service and subjective evaluations are not important only as the leading factors in the long-term brand reputation management but also as influential factors in channel preference. SoThus, given that the service quality of the pre-existing channel is not the customers' main concern, a strategy of improving the level of service satisfaction aimed at present customers is more valuable than a wide brand positioning strategy aimed at general and new customers. Second, when an offline channel company establishes an internet shopping mall on an online channel, it is highly likely that the preference and subjective evaluation of the present customers will influence the online channel. This applies not only to the special case of an expansion from an offline intermediary channel to an online one, but also to an online channel acting as an expansion of the business model of a conventional manufacturing or service company: both cases are vertical integrations of marketing channels in an expansion of the distribution channel. My theory applies to a wide range of contexts. Third and finally, any business strategy can grasp the meaning of 'channel expansion. Fundamentally, it is an expansion of the sales activity channel and marketing activity. However, it is also a way of enhancing marketing and sales competitiveness through an expansion to an online or offline channel. The expansion of an offline company to an online channel could be seen not as improvement but as an innovation of the business process by which two goals are achieved with one technique. The former is expected to increase the sales of the offline company, and the latter is also expected to increase sales while also contributing to cost reduction.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.238-245
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• 2020

The objective of this study was to analyze the market structure of the Garak Agricultural Products Wholesale Market, which has the greatest influence among agricultural products wholesale markets and plays a key role in domestic agricultural products distribution. In addition, through analysis of the management efficiency of the wholesale market corporation, which is a major distributor of the Garak Market, the connection relationship between the market structure of the Garak Market and the management efficiency of the wholesale market corporation was able to be identified. From 2007 to 2018, it was found that the market structure of Garak Market was a monopoly. In addition, the average production efficiency of the five wholesale market corporations was 0.95, indicating that the wholesale market corporation in Garak Market has an efficient production structure with high output compared to input. Therefore, in order to activate the agricultural products wholesale market and protect the rights of producers and consumers based on the analysis results, it is necessary to implement a policy that can establish a competition system among agricultural products wholesale market distributors.

• Journal of Distribution Science
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• v.11 no.8
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• pp.5-14
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• 2013

Purpose - We live in a world of constant change and competition. Many airports have specific competitiveness goals and strategies for achieving and maintaining them. The global economic recession, financial crises, and rising oil prices have resulted in an increasingly important role for facility investment and renewal and the implementation of appropriate policies in ensuring the competitive advantage for airports. It is thus important to analyze the factors that enhance efficiency and productivity for an airport. This study aims to determine the efficiency levels of 20 major airports in East Asia, Europe, and North America. Further, this study also suggests suitable policies and strategies for their development. Research design, data, and methodology - This paper employs the DEA-CCR, DEA-BCC, and DEA-Malmquist production index analysis models to determine airport efficiency. The study uses data on the efficiency and productivity of the world's leading airports between 2006 and 2010. The input variables include the airport size, the number of runways, the size of passenger terminals, and the size of cargo terminals. The output variables include the annual number of passengers and the annual cargo volume. The study uses basic data from the 2010 World Airport Traffic Report (ACI). The world's top 20 airports (as rated by the ACI report) are investigated. The study uses the expanded DEA Model and the Super Efficiency Model to identify the most effective airports among the top 20. The Malmquist productivity index analysis is used to measure airport effectiveness. Results - This study analyzes longitudinal and cross-sectional data on the world's top 20 airports covering 2006 to 2010. A CCR analysis shows that the most efficient airports in 2010 were Gatwick Airport (LGW), Zurich Airport (ZRH), Vienna Airport (VIE), Leonardo da Vinci Fiumicino Airport (FCO), Los Angeles International Airport (LAX), Seattle-Tacoma Airport (SEA), San Francisco Airport (SFO), HongKong Airport (HKG), Beijing Capital International Airport (PEK), and Shanghai Pudong Airport (PVG). We find that changes in airport productivity are affected more by technical factors than by airport efficiency. Conclusions - Based on the study results, we offer four airport development proposals. First, a benchmark airport needs to be identified. Second, inefficiency must be reduced and high-cost factors need to be managed. Third, airport operations should be enhanced through technical innovation. Finally, scientific demand forecasting and facility preparation must become the focus of attention. This paper has some limitations. Because the Malmquist productivity index is based on the hypothesis of the, the identified production change could be over- or under-estimated. Further, as DEA estimates the relative efficiency. It also cannot generalize to include all airport conditions because the variables are limited. To measure airport productivity more accurately, other input variables and environmental variables such as financial and policy factors should be included.

• Journal of Distribution Science
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• v.14 no.1
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• pp.85-91
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• 2016

Purpose - Recently, the importance of rapid change in business models is more and more increasing as the change of information technology environment. Therefore, a variety of business models have emerged. On the other hand, there is no company that can generate revenue. Many enterprises are still maintained while they are changing only their appearance of the business model. Business model is important in e-commerce. However, a lot of researches are targeted only in Web sites. Thus, e-commerce companies do not have the infrastructure for measuring and business models. The purpose of paper is to evaluate factors which are related with the structuring of the e-commerce success. And it proposed a financial items and non-financial items. From the perspectives of administrators and managers, the paper researches the possibility for E-Commerce Evaluation Model as a valuable criteria in measuring business model. Research design, data and methodology - The methods are taken by the classification for the type of business-to-business transactions, transactions subject, and the degree of integration and innovation capabilities. Financial and Non-financial value is used to build E-Commerce Evaluation Model. Evaluation items in Administration's perspective are composed with enhance the effectiveness of the mission, improving efficiency of the administration, and control of costs. Evaluation items in the customer's perspective were measured by customer participation and cooperation with customer Satisfaction. In the case of researching the information system's perspective, three criteria are used such as adequacy of the development process, improvement of the quality of service, and maintenance of standardized information technology. In researching for the ICT competence's perspective, evaluation items were composed of enhanced user capabilities, utilizing new technologies, and empowerment of information workers. Results - In this paper, E-Commerce Evaluation Model with financial and non-financial perspectives shows the possibility to be criteria in the case of measuring business model. Moreover, it gives the positive expectation to be successful criteria. But the research may have ambiguity in its essential concept because it cannot avoid the limitation in selecting evaluation tools from merely the model. It is impossible to exclude the possibility in omitting specific properties which may take place in actual case study. Therefore, In hereafter research, it is necessary to include actual case study research in selecting evaluation tools in order to improve the limit point. Actual measurement items which are derived from actual case study should be subdivided, and it would be more effective to complete the research. Conclusions - In rapid change in business models, there are various kinds of business models. But it is general situation that companies which adopted business models have not brought in revenue. For this reason, E-Commerce Evaluation Model is needed as an important factor for the structuring of the e-commerce success. Although it has the limitation in selecting evaluation tools from model, E-Commerce Evaluation Model proposes the implication for measuring business models as a valuable criteria.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.1
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• pp.67-73
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• 2006

10 sites in building development areas were selected and the noise level were measured by the apartment floors of apartment complex. With the fitted regression analysis, the distribution ratio($R^2$) and correction coefficient(r) was 25%(0.5) in the NIER('87) and 7.5%(0.274) in the NIER('99), respectively. The measured values of the noise level on the seventh floor of complex did not show a good agreement with the predicted noise level in the NIER('87, '99) formula. However, the developed formula demonstrated that the measured values were reasonably close to the predicted values, indicating the validity and adequacy of the predicted models with the fitted vs residual analysis in the 95% of confidence interval and 95% of predict interval. The results suggested that application of this development model obtained by the results according to the apartment floor can be improved in road traffic noise.

• Journal of Distribution Science
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• v.14 no.5
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• pp.97-106
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• 2016

Purpose - Social commerce is a certain way of how people buy some products together with others through the internet sites with mutual interactions among customers with the benefits of SNS when buying some products. At present, China market has some problems due to its rapid growing. However, empirical research or academic approach to social commerce has not been made enough. So, it is important for Chinese social market to develop and enlarge the customers with stability under the reliability and satisfaction. Also it is important for them to have repurchase intention. Nowadays, it is necessary to find the factors on customer satisfaction and trust, whereas consumers' dissatisfaction and unreliability are increasing on social commerce recently. In addition, researches on social commerce have been actively pursued by a variety of domestic and foreign scholars. However, researches on social commerce and Chinese market are short of, and they have some limitations because of the rapid growth of the market even though it is the early stage. The current situation requires researches on consumers' repurchase intention for continuing growth in the future according to the growth of Chinese social commerce. Research design, data, and methodology - The literature and the empirical studies are combined in order to achieve the purpose of the study. Deriving social commerce features and consumer properties as factors affecting the repurchase intention through the literature, and these factors have modeled a series of assumptions about the impact on satisfaction and trust, and have established hypotheses to verify them. The survey which is conducted to test the hypothesis and questionnaires are derived based on the variables discussed in the previous study. Appropriate measures were developed and tested on 227 respondents in China with a cross-sectional questionnaire survey. The path relationships of the research model were analyzed by SPSS 23.0 and Amos 23.0. Results - Research results about social commerce characteristics and factors affecting the repurchase intention are presented to Chinese market companies that adopt business models and consumer characteristics. In addition, this study focuses on the characteristics of social commerce, from two-dimensional characteristics of the consumer satisfaction, trust and the impact on the repurchase. Therefore, social commerce features and consumer properties based on the results of this study may lead the strategic implications that may increase the repurchase intention. Conclusions - The classification reviewing the previous findings related to social commerce and social commerce features affects social commerce repurchase (price discount, interactivity) and consumer characteristics (impulsivity, innovation, collectivism). It affects repurchase on factors and analyzes empirically. The empirical results identify major characteristics (social commerce characteristics, attributes) that affect the repurchase intention, and give the practical implications as well as the business strategies that are able to enhance social commerce repurchase consumers. Social commerce is a certain way of how people buy some products together with others through the internet sites with mutual interactions among customers with the benefits of SNS when buying some products.

• Journal of Distribution Research
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• v.12 no.4
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• pp.49-77
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• 2007

The purpose of this study is to examine a relationship between the headquarters and the sales offices of a car manufacturing company by comparing their channel types. It examines how the level of communication and commitment of sales offices on their headquarters differently affects some mediating effects between participation and relationship performance. It also tries to find out what kind of mechanisms are needed in order to improve the relationship. Through the data analysis of a total of 200 sales offices which are directly managed stores and agency stores by a domestic car manufacturing company, the following conclusions were reached: Participation, one of the variables in bureaucratic structuring, influences all dimensions of communication. Also, it has found that communication dimensions influence commitment dimensions differently by the type of channels, and commitment dimensions influence relationship performance by the type of channels. Recently, import car makers are accelerating their moves in the domestic market, and the importance of a customer-oriented retail innovation and a relationship management in an auto manufacturing industry is increasing. This study will give an useful suggestion on how to improve a long term relationship of distributors through an enhancement of communication and commitment.

• The Journal of Industrial Distribution & Business
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• v.9 no.3
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• pp.45-56
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• 2018

Purpose - The Korean university education system is facing innovation and change, including cooperation between industry and university, Therefore It is important to activate the industry-university cooperation. This paper aims to demonstrate the factors that activate industry-university cooperation, particularly about the voluntary participation induction by industry and researching in path dependency perspectives. Research design, data, and methodology - The subject of this research were companies that are aware of the industry-university cooperation program. This research hypothesis is derived from the literature of previous studies of industry-university cooperation, This study have constructs that was defined operationally with reference to previous studies, this research model design to figure out structural relationship among technology leadership of university, university specialization, local network strength, fixation of local economy, recognition of path dependence, participation by industry, performance of industry-university cooperation. From 2017 July. 1 to Sept. 31, questionnaire survey targeting company staff who is involving in industry-university cooperation. 257 questionnaire survey had conducted. 249 investigated data were used for empirical analysis except wrong data. This data were used for AMOS(structural equation) & Regression statistics to verify hypothesis which developed by researcher. Results - The results of this study are as follows. First, technology leadership of universities has a significant effect on voluntary participation by industry. University specialization has significant effect on voluntary participation by industry. Second, local network strength has significant effect on voluntary participation by industry. but fixation of local economy does not affect voluntary participation by industry. Third, recognition of path dependence has moderating effect between Independent(university, company characteristics) and dependent variables(voluntary participation by industry) When recognition level of path dependence is high, preceding factors have a significant effect on voluntary participation by industry than recognition level of path dependence is low. As a result, the degree of recognition of path dependence was shown important variables that induce voluntary participation of industry for industry-university cooperation program. Conclusions - This study suggests that voluntary participation of industry is a very important factor in the achievement of industry-university cooperation. Recognition of interdependence as well as leading factors that encourage voluntary participation of industry is also just as important. If recognition of path dependence was high, Industry's voluntary participation was high.