• Industry Promotion Research
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• v.8 no.2
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• pp.21-27
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• 2023

This study studies the policies and use cases of the government and the financial sector for artificial intelligence, and the future policy tasks of the financial sector. want to derive According to Gartner, noteworthy technologies leading the financial industry in 2022 include 'generative AI', 'autonomous system', 'Privacy Enhanced Computation (PEC) was selected. The financial sector is developing new technologies such as artificial intelligence, big data, and blockchain. Developments are spurring innovation in the financial sector. Data loss due to the spread of telecommuting after the corona pandemic As interests in sharing and personal information protection increase, companies are expected to change in new digital technologies. Global financial companies also utilize new digital technology to develop products or manage and operate existing businesses. I n order to promote process innovation, I T expenses are being expanded. The financial sector utilizes new digital technology to prevent money laundering, improve work efficiency, and strengthen personal information protection. are applying In the era of Big Blur, where the boundaries between industries are disappearing, the competitive edge in the challenge of new entrants In order to preoccupy the market, financial institutions must actively utilize new technologies in their work.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.85-100
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• 2023

Corporate ESG performance (environmental, social, and corporate governance) reflecting a company's strategic sustainability has emerged as one of the main factors in today's investment decisions. The traditional ESG performance rating process is largely performed in a qualitative and subjective manner based on the institution-specific criteria, entailing limitations in reliability, predictability, and timeliness when making investment decisions. This study attempted to predict the corporate ESG rating through automated machine learning based on quantitative and disclosed corporate financial information. Using 12 types (21,360 cases) of market-disclosed financial information and 1,780 ESG measures available through the Korea Institute of Corporate Governance and Sustainability during 2019 to 2021, we suggested a deep neural network prediction model. Our model yielded about 86% of accurate classification performance in predicting ESG rating, showing better performance than other comparative models. This study contributed the literature in a way that the model achieved relatively accurate ESG rating predictions through an automated process using quantitative and publicly available corporate financial information. In terms of practical implications, the general investors can benefit from the prediction accuracy and time efficiency of our proposed model with nominal cost. In addition, this study can be expanded by accumulating more Korean and international data and by developing a more robust and complex model in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.399-408
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• 2009

The major changes in construction environment are that construction project is bigger and more complicated and the power of construction market changes from the supplier to the client or the user. Especially public construction enterprises have advanced to introduce the value engineering (VE) which is one of the cost management based on the owner's leading at the design phase for economical efficiency and quality improvement. According to the these efforts, the implementation of VE was legislated in the revised Construction Technology Management Act in 2000, governmental agencies, local autonomies, and construction public enterprises universally has taken the VE into consideration. In this circumstance, the scope that VE construction applied at 50 billion won projects from 2003 has been extended to 10 billion won projects in 2006. Therefore, the VE construction will be activated in the future. The cost savings and function improvement, which are the purpose of VE are not only construction public enterprises, but also every public client supported from government's budget or owned by the government. Therefore, the purpose of this study is to propose the improved process and performance index of VE for governmental agencies, local autonomies, and construction public enterprises which want to introduce or improve the VE process. This research also suggested the To-be design-phased VE process model. In addition, it suggested the To-be model of design management reflected the To-be design-phased VE process model, which is eliminated two problems reflected for the performance improvement of the As-is model of design management.

• Asia Marketing Journal
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• v.14 no.3
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• pp.49-68
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• 2012

When a channel is vertically separated, there can be inefficiencies, double marginalization. Channel coordination to amend this inefficiency has been an important issue in marketing and economics. Channel coordination deals with maximization of joint profit and achieving proper profit sharing among participants. In this paper, a manufacturer and heterogeneous multiple retailers with exclusive territory are assumed, and channel coordination with two-part tariff is considered. When multiple heterogeneous retailers are assumed, profit sharing can be an issue even though the tariffs based on marginal cost can maximize joint profit. In case of multiple heterogeneous retailers, the manufacturer earns the same profit (fixed fee) from each retailer. This means that a large retailer occupies all the gaps of channel profit between small and large markets. Then, the manufacturer, which generally plays the role of Stackelberg leader, will consider increasing fixed price or marginal price to earn more profit from large retailer. Those reactions can sacrifice maximization of joint profit by making small retailer withdraw or by changing the sales quantities. In this paper, to maximize joint profit and achieve proper profit sharing, two kinds of optional tariffs are considered. The first is an optional two-part tariff based on marginal cost and the second is an optional modified two-part tariff in which marginal prices are higher than the manufacturer's marginal cost. In both types of optional tariffs, maximization of joint profit in each market can be achieved. Moreover, optional tariffs alleviate the problem of profit sharing. Optional tariffs can provide a manufacturer more profit from a large retailer when profit from a small retailer is given. However, the analysis shows that the maximum share of manufacturer from a large retailer is restricted by the condition for self-selection. In case of optional two-part tariffs based on marginal cost, if the gap between demands is large, the maximum share of the manufacturer is sufficient to achieve proper profit sharing. If the gap between demands is not sufficiently large, the manufacturer cannot earn sufficient share from increased profit. An optional modified two-part tariff where marginal price is more than marginal cost of manufacturer is considered because of this scenario. The marginal price above the marginal cost may additionally control the distribution of the increased profit. However, the analysis shows that a manufacturer's maximum profit from a large retailer with given profit from a small retailer is the same as or lower than the maximum profit when optional two-part tariffs based on marginal cost are applied. Therefore, it can be concluded that the optional modified tariffs do not have additional contribution to profit sharing relative to the tariffs based on marginal cost. Although this paper does not cover all kinds of optional tariffs that are different from tariffs based on marginal cost, it shows the advantage of optional tariffs based on marginal cost and has important theoretical implications. The result of this paper also gives guide for channel coordination. Optional two-part tariff based on marginal cost can increase efficiency in channel coordination.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.191-205
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• 2023

Artificial Intelligence (AI), especially in the domain of text-generative services, has witnessed a significant surge, with forecasts indicating the AI-as-a-Service (AIaaS) market reaching a valuation of $55.0 Billion by 2028. This research set out to explore the quality dimensions characterizing synthetic text media software, with a focus on four key players in the industry: ChatGPT, Writesonic, Jasper, and Anyword. Drawing from a comprehensive dataset of over 4,000 reviews sourced from a software evaluation platform, the study employed the Latent Dirichlet Allocation (LDA) topic modeling technique using the Gensim library. This process resulted the data into 11 distinct topics. Subsequent analysis involved comparing these topics against established AI service quality dimensions, specifically AICSQ and AISAQUAL. Notably, the reviews predominantly emphasized dimensions like availability and efficiency, while others, such as anthropomorphism, which have been underscored in prior literature, were absent. This observation is attributed to the inherent nature of the reviews of AI services examined, which lean more towards semantic understanding rather than direct user interaction. The study acknowledges inherent limitations, mainly potential biases stemming from the singular review source and the specific nature of the reviewer demographic. Possible future research includes gauging the real-world implications of these quality dimensions on user satisfaction and to discuss deeper into how individual dimensions might impact overall ratings.

• Journal of Venture Innovation
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• v.5 no.3
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• pp.19-40
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• 2022

The purpose of this study is to analyze and evaluate the role and merits and demerits of insurance agencies, which are the main sales channels of the domestic insurance market, from a neutral standpoint, and to present a roadmap by finding ways and tasks for the sustainable development of the insurance agency industry. Recently, criticisms and regulations on independent distribution channels have been strengthened due to deterioration in growth potential and profitability, and increase in civil complaints of insurance companies. In the 2000s, as the center of insurance sales channels shifted to GA and bancassurance, the supervisory authorities regarded the irrationality of project costs and recruitment fees as the root causes and announced a regulatory improvement plan. In view of these circumstance, the operating status, problems of domestic insurance agencies and their contribution to the insurance industry were reviewed. In addition, we tried to find a mid-to-long term development plan by analyzing the case of insurance agency operation in Japan. This study identified the operating status and contribution of insurance agencies in South Korea, and focused on the major status of the Japanese insurance agency industry, ways to improve management efficiency, and the status and role of self-regulatory organizations for insurance agencies. Based on this, it was proposed to improve the professionalism of the sales organization, introduce a company specializing in insurance sales, and to strengthen the status of the association of the insurance agency as for the development plan of the insurance agency industry in South Korea.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.375-393
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• 2023

The demand for Less than Container Load (LCL) has been on the rise due to the growing need for various small-scale production items and the expansion of the e-commerce market. Consequently, more companies in the International Freight Forwarder are now handling LCL. Given the variety in cargo sizes and the diverse interests of stakeholders, there's a growing need for a container loading algorithm that optimizes space efficiency. However, due to the nature of the current situation in which a cargo loading plan is established in advance and delivered to the Container Freight Station (CFS), there is a limitation that variables that can be identified at industrial sites cannot be reflected in the loading plan. Therefore, this study proposes a container loading methodology that makes it easy to modify the loading plan at industrial sites. By allowing the characteristics of cargo and the status of the container to be considered, the requirements of the industrial site were reflected, and the three-dimensional space was manipulated into a two-dimensional planar layer to establish a loading plan to reduce time complexity. Through the methodology presented in this study, it is possible to increase the consistency of the quality of the container loading methodology and contribute to the automation of the loading plan.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.351-368
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• 2024

Purpose: In general, traffic accidents occur sporadically, so there are various limitations in terms of time and cost when conducting field investigations to prepare prevention and prevention measures. In particular, with the transition to a non-face-to-face society after the COVID-19, there is a greater need to prepare a replacement for field surveys. Therefore, in this study, Roadview provided by various websites was used as an alternative to field surveys in Sasang-gu, Busan City. The possibility was evaluated. Method: The research method was to extract vulnerable points for traffic accidents that occurred between 2016 and 22 and analyze road views based on the field survey evaluation items provided in the Traffic Safety Diagnosis Guidelines. Result: The main result was that Sasang-gu was most vulnerable to accidents involving elderly pedestrians at Sasang-ro, Daedong-ro, and Hakjang-ro. As a result of a detailed analysis of vulnerable points through Road View, Sasang-ro needed control of commercial vehicles and protection of the transportation vulnerable in the market commercial area. Daedong-ro was vulnerable to illegal on-street parking and slope merging sections, and Hakjang-ro was vulnerable to roads that were prone to speeding. When evaluating the possibility of replacing Roadview's field survey based on the results of this analysis, Roadview was able to effectively evaluate most items, such as separation of sidewalks and the location and spacing of safety facilities. However, there were limitations in items such as actual measurement performance. Conclusion: In other words, the road view can replace most field surveys, and the actual measurement evaluation items can be judged to be useful as auxiliary data, resulting in time and cost savings and high efficiency.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.3
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• pp.121-129
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• 2024

The rapid advancement of digital technology and the COVID-19 pandemic have significantly accelerated the growth of online commerce, highlighting the need for support mechanisms that enable small business owners to effectively respond to these market changes. In response, this paper presents a foundational technology leveraging the Online to Offline (O2O) strategy to automatically capture products displayed on retail shelves and utilize these images to create virtual stores. The essence of this research lies in precisely identifying and recognizing the location and names of displayed products, for which a single-class-targeted, lightweight model based on YOLOv8, named ESD-YOLOv8, is proposed. The detected products are identified by their names through feature-point-based technology, equipped with the capability to swiftly update the system by simply adding photos of new products. Through experiments, product name recognition demonstrated an accuracy of 74.0%, and position detection achieved a performance with an F2-Score of 92.8% using only 0.3M parameters. These results confirm that the proposed method possesses high performance and optimized efficiency.

• The Journal of Bigdata
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• v.8 no.2
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• pp.149-163
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• 2023

Due to the continuous growth of the E-commerce market, the volume of orders that fulfillment centers have to process has increased, and various customer requirements have increased the complexity of order processing. Along with this trend, the operational efficiency of fulfillment centers due to increased labor costs is becoming more important from a corporate management perspective. Using historical performance data as training data, this study focused on real-time box recommendations applicable to packaging areas during fulfillment center shipping. Four types of data, such as product information, order information, packaging information, and delivery information, were applied to the machine learning model through pre-processing and feature-engineering processes. As an input vector, three characteristics were used as product specification information: width, length, and height, the characteristics of the input vector were extracted through a feature engineering process that converts product information from real numbers to an integer system for each section. As a result of comparing the performance of each model, it was confirmed that when the Gradient Boosting model was applied, the prediction was performed with the highest accuracy at 95.2% when the product specification information was converted into integers in 21 sections. This study proposes a machine learning model as a way to reduce the increase in costs and inefficiency of box packaging time caused by incorrect box selection in the fulfillment center, and also proposes a feature engineering method to effectively extract the characteristics of product specification information.