• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.71-82
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• 2023

As an alternative to solving social problems, social economic actors are attracting attention as an important alternative. SPC is a private program that pays incentives according to the social performance measured by monetary value. This study measured efficiency by applying DEA to social enterprises that participated in the SPC program and analyzed the factors affecting efficiency through tobit regression. As a result of DEA analysis, it was found that 21% of social enterprises participating in SPC were efficient, but 66% needed to improve their efficiency. In the Tobit regression analysis, the efficiency was relatively low in the case of manufacturing sector, and when the square term of sales is included, the efficiency decreases as sales increase. Through this, it was estimated that external support is needed at a low level sales before crossing the critical point, and that the efficiency of social value creation increases when it grows above a certain level. Moreover, it is significant in that it combines the variables used in the analysis of traditional industrial efficiency while conducting efficiency analysis focusing on the social performance by monetary value, which is considered the most important achievement of social enterprises. It is believed that it will contribute to research related to the environment creation and the requirements of each field in creating social values for social enterprises in the future.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.57-69
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• 2023

In a situation where digital transformation using artificial intelligence is active around the world, the growth of domestic AI companies or AI industrial ecosystems is slow. Where a large amount of government funds related to AI are being invested to overcome the difficult economic situation, systematic research on the effect is insufficient. So, this study aimed to examine the policy effectiveness of the government artificial intelligence solution voucher support project for small and medium-sized enterprises (SMEs) using Propensity Score Matching (PSM) and Difference-in-Differences (DID) on the financial performance of beneficiary companies. For empirical analysis, PSM-DID analysis was performed using sales performance since 2019 for 461 companies with a history of voucher support among the AI SMEs data released by the National IT Industry Promotion Agency. As a result of the analysis, the beneficiary companies' asset growth, salary, and R&D expenses increased overall after government support, and no significant contribution could be confirmed in terms of profits. This study suggests that the voucher policy business directly contributed to the company's growth in the short term, but it requires a certain period of time to generate profits.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.289-296
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• 2009

All over the world more and more attention is being paid to green management which enables environment-friendly sustainable development. To keep up with these global trends and in response to the government's "low carbon green growth" policy, many efforts are being made in the port and logistics in order to drastically reduce carbon emissions and save operating expenses. To this end, the engine power source of the cranes in the container terminal is being replaced with electricity from fossil fuel. Among those cranes, especially e-RTGC has been proved to be practical and excellent in its performance through many previous studies. However, no empirical study has yet been made on its introduction effects when e-RTGC has been introduced to the container terminal. In the meantime, however, many domestic container terminals have introduced e-RTGC, and so some data have been accumulated for further research. Under these circumstances, this study has tried to make an empirical study through the case study of D container terminal, checking the restriction factors to be considered at the time of eURTGC introduction, and analyzing its introduction effects and problems. We have high expectations that this study will provide key consideration factors and empirical analysis data to the decision makers who plan to introduce an e-RTGC system, and also will be used as a reference to the development direction of e-RTGC.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.2
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• pp.23-31
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• 2009

Since 9.11 terrorist attacks against the USA, the new paradigm for "supply chain security" has been established. And at the same time a lot of researches are being made on supply chain security by many foreign companies or research institutes. However, domestically the terms "supply chain security" themselves are not yet familiar, and the paradigm of security are not being used in the logistics, while little researches are being made on them But recently along with development of "ConTracer," a supply chain security technology, which is to be used as the equipment for container cargo transportation safety based on RF1D technology, related researches have begun to be activated. The key issues for the development of equipment for container transportation safety are to obtain both a high recognition rate and enough recognition distance. To this end, this study has tested the ConTracer (433 MHz type and 2.4 GHz type) by using Taguchi Method. According to our test results, in the case of 433 MHz type, it is a little more effective that the reader faces to the front-right side, and in the case of 2.4 GHz, reader direction does not make difference in the view of sensitivity. The test also has proved that it is better that antenna location, as expected, is to be installed on the outside for both types alike.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.95-107
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• 2023

The purpose of this study is to investigate the impact of export promotion programs (EPPs) on the export performance of small- and medium-sized enterprises (SMEs), with a specific focus on the influence of EPPs for promising SMEs in the export market. Using data on SMEs provided by the Industrial Bank of Korea (IBK), we conducted a fixed-effects model analysis from 2016 to 2019. Our study shows that EPPs have a positive and significant relationship with export intensity. Further analysis reveals that SMEs utilizing the financing support system provided by EPPs tend to improve their export growth and financial performance relative to their counterparts. While EPPs can assist SMEs with their internationalization efforts, their similarity and redundancy are recognized as potential limitations. This study complements the existing literature that has mainly focused on surveys and cross-sectional analysis by specifying the research subject to promising SMEs in export, and analyzing the effects of the export promotion program supported by IBK Industrial Bank. The results of this study are expected to provide implications for improving SMEs' export capabilities.

• Information Systems Review
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• v.25 no.4
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• pp.89-112
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• 2023

In March 2020, as it was declared a COVID-19 pandemic, various quarantine measures were taken. Accordingly, many changes have occurred in the tourism and hospitality industries. In particular, quarantine guidelines, such as the introduction of non-face-to-face services and social distancing, were implemented in the restaurant industry. For decades, research on restaurant attributes has emphasized the importance of three attributes: atmosphere, service quality, and food quality. Nevertheless, to the best of our knowledge, research on restaurant attributes considering the COVID-19 situation is insufficient. To respond to this call, this study attempted an exploratory approach to classify new restaurant attributes based on understanding environmental changes. This study considered 31,115 online reviews registered in Naverplace as an analysis unit, with 475 general restaurants located in Euljiro, Seoul. Further, we attempted to classify restaurant attributes by clustering words within online reviews through TF-IDF and LDA topic modeling techniques. As a result of the analysis, the factors of "prevention of infectious diseases" were derived as new attributes of restaurants in the context of COVID-19 situations, along with the atmosphere, service quality, and food quality. This study is of academic significance by expanding the literature of existing restaurant attributes in that it categorized the three attributes presented by existing restaurant attributes and further presented new attributes. Moreover, the analysis results have led to the formulation of practical recommendations, considering both the operational aspects of restaurants and policy implications.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.151-171
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• 2023

For the efficient establishment of a channel strategy for banks, this study aims to propose a channel model by classifying channels into types, and carrying out a correspondence analysis per type. A survey of bankers was conducted to visualize categorical data and create a positioning map. As a result, first, 12 banking channels were classified into 4 types based on business processing subjects and places, which were then, further grouped into the categories of full-banking and self-banking. Second, a correspondence analysis according to the classified types was carried out, and it was found that the branch-type is suitable for product description and customer management, while the banking-type is suitable for efficient business processing without time and space constraints. Furthermore, the analysis also showed that the machine-type and banking-type are inappropriate for customer management, and the mobility-type demonstrates low operational effectiveness due to a lack of awareness. The aforementioned findings suggest the need for a hybrid convergence channel that reflects the characteristics of banking tasks and fills in the gaps between the different channels. Third, a channel model was derived by adding a common area to the 2×2 model consisting of the business processing subjects and places. Therefore, this study is meaningful in that it examines the diversification of channels and factors in the division of roles by channel type based on customers' banking channel selection factors, and presents basic research findings for future channel strategy establishment and efficient channel operation.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.1-14
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• 2023

Soybeans are one of the world's top five staple crops and a major source of plant-based protein. Due to their susceptibility to climate change, which can significantly impact grain production, the National Agricultural Science Institute is conducting research on crop phenotypes through growth analysis of various soybean varieties. While the process of capturing growth progression photos of soybeans is automated, the verification, recording, and analysis of growth stages are currently done manually. In this paper, we designed and trained a YOLOv5s model to detect soybean leaf objects from image data of soybean plants and a Convolution Neural Network (CNN) model to judgement the unfolding status of the detected soybean leaves. We combined these two models and implemented an algorithm that distinguishes layers based on the coordinates of detected soybean leaves. As a result, we developed a program that takes time-series data of soybeans as input and performs growth analysis. The program can accurately determine the growth stages of soybeans up to the second or third compound leaves.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.200-215
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• 2023

With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.207-228
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• 2023

After COVID-19, organizations have widely adopted platforms such as zoom or developed their proprietary online real-time systems for remote work, with recent forays into incorporating the metaverse for meetings and publicity. While ongoing studies investigate the impact of avatar customization, expansive virtual environments, and past virtual experiences on participant satisfaction within virtual reality or metaverse settings, the utilization of the metaverse as a dedicated workspace is still an evolving area. There exists a notable gap in research concerning the factors influencing the performance of the metaverse as a workspace, particularly in non-immersive work-type metaverses. Unlike studies focusing on immersive virtual reality or metaverses emphasizing immersion and presence, the majority of contemporary work-oriented metaverses tend to be non-immersive. As such, understanding the factors that contribute to the success of these existing non-immersive metaverses becomes crucial. Hence, this paper aims to empirically analyze the factors impacting personal outcomes in the non-immersive metaverse workspace and derive implications from the results. To achieve this, the study adopts the Embodied Social Presence (ESP) model as a theoretical foundation, modifying and proposing a research model tailored to the non-immersive metaverse workspace. The findings validate that the impact of presence on task engagement and task involvement exhibits a moderating effect based on the metaverse platform used. Following interviews with participants engaged in non-immersive metaverse workplaces (specifically Gather Town and Ifland), a survey was conducted to gather comprehensive insights.