• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.107-121
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• 2023

The assessment of perceived naturalness aims to elucidate the human perception and explain the interaction between natural environments and humans. The perception of ecological assets that exhibit distinct characteristics within a specific region can manifest in various representations. Based on the users' perceptions and interviews regarding ecological assets, this study assessed the perceived naturalness from a cultural services perspective. Specifically, the discussions on Ansan City's ecological assets and revolved around the inherent value of naturalness in dimensions, such as the necessity for conservation and the sustainable development of ecological assets, the perception of ecosystem benefits, the representativeness as a local asset, and usability. Subsequently, the Q method was employed to present 25 representative ecological assets to 25 users. As a result, user groups with different value systems for each question were identified, and hypothetical personas for cultural service enjoyment were distinguished. The most representative persona among the 25 users was identified as AWP (a type that values the conservation of aquatic ecosystems, prefers waterfront landscapes, and enjoys walking). Since perceived naturalness is conceptually similar to the "benefits perceived by users" in evaluating ecosystem services, it can provide more practical evaluation criteria for cultural services.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.166-178
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• 2023

This study aims to introduce and assess CNN Deep Learning methods to analyze visual landscape images on social media with embedded user perceptions and experiences. This study analyzed visual landscape images by focusing on a healing place. For the study, seven adjectives related to healing were selected through text mining and consideration of previous studies. Subsequently, 50 evaluators were recruited to build a Deep Learning image. Evaluators were asked to collect three images most suitable for 'healing', 'healing landscape', and 'healing place' on portal sites. The collected images were refined and a data augmentation process was applied to build a CNN model. After that, 15,097 images of 'healing' and 'healing landscape' on portal sites were collected and classified to analyze the visual landscape of a healing place. As a result of the study, 'quiet' was the highest in the category except 'other' and 'indoor' with 2,093 (22%), followed by 'open', 'joyful', 'comfortable', 'clean', 'natural', and 'beautiful'. It was found through research that CNN Deep Learning is an analysis method that can derive results from visual landscape image analysis. It also suggested that it is one way to supplement the existing visual landscape analysis method, and suggests in-depth and diverse visual landscape analysis in the future by establishing a landscape image learning dataset.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.10
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• pp.309-318
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• 2023

Recently, each country has been moving to introduce an LCA (Life Cycle Assessment) to regulate greenhouse gas emissions. The LCA is a mean of measuring and evaluating greenhouse gas emissions generated over the entire life cycle of a vehicle. Reliable data for each electric vehicle component is needed to increase the reliability of the LCA results. To this end, studies on life cycle evaluation models using blockchain technology have been conducted. However, in the existing model, key product information is exposed to other participants. And each time parts data information is updated, it must be recorded in the blockchain ledger in the form of a transaction, which is inefficient. In this paper, we proposed a DID(Decentralized Identity)-based data collection model for LCA to collect vehicle component data and verify its validity effectively. The proposed model increases the reliability of the LCA by ensuring the validity and integrity of the collected data and verifying the source of the data. The proposed model guarantees the validity and integrity of collected data. As only user authentication information is shared on the blockchain ledger, the model prevents indiscriminate exposure of data and efficiently verifies and updates the source of data.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.5
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• pp.44-56
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• 2023

This research explores the enhancement of park operation and management by analyzing the changing demands of park users. While traditional methods depended on surveys, there has been a recent shift towards utilizing social media data to understand park usage trends. Notably, most research has focused on text data from social media, overlooking the valuable insights from image data. Addressing this gap, our study introduces a novel method of assessing park usage using social media image data and then applies it to actual city park evaluations. A unique image analysis tool, built on Visual Question Answering (VQA) deep learning technology, was developed. This tool revealed specific city park details such as user demographics, behaviors, and locations. Our findings highlight three main points: (1) The VQA-based image analysis tool's validity was proven by matching its results with traditional text analysis outcomes. (2) VQA deep learning technology offers insights like gender, age, and usage time, which aren't accessible from text analysis alone. (3) Using VQA, we derived operational and management strategies for city parks. In conclusion, our VQA-based method offers significant methodological advancements for future park usage studies.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.339-345
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• 2023

Design exists behind technology. Design is intertwined with the needs of daily life and market structures, and while dealing with technology, it can become insensitive to its meaning. Unlike other social media platforms, Instagram consists of image-based content. The purpose of this study is to examine the addictive design of Instagram. Furthermore, we discuss the ethical responsibilities that designers must have. A theoretical framework for understanding Instagram design is established through a review of major domestic and international literature that has been previously studied. Understand the history, structure, and functions of Instagram and identify Instagram designs that promote social media addiction. In this study, we introduced the mechanism by which Instagram promotes user addiction through design issues. (1) Pull-to-Refresh (2) Red color in push alarm (3) Profile photo border expression in Instagram Story. This design stimulates users' social desires and FOMO, forming the structure of obsessive Instagram usage habits. Instagram is an example that forces us to reconsider the ethical role of design and designers along with the advancement of technology. In today's world, the intrinsic value of what they create, including our society and life itself.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.51-68
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• 2023

With the emergence of the internet and the increasing use of online communities for over 20 years, the age range of users has also been rising. This study explores the linguistic changes that have occurred as the user age in online communities has increased. To do this, data was collected and analyzed from an online community that has been actively operating, despite new member registrations being closed nine years ago. By comparing the posts over an 11-year period from 2012 to 2022, changes such as an increase in average comments, a decrease in interrogative sentences, and a decrease in imperative statements were observed. The study also proposed loneliness due to aging and a decline in curiosity and confidence as potential causes of these changes. In South Korea, which is rapidly entering an aging society unprecedentedly fast on a global scale, the increase in single-person households has evolved loneliness from a personal issue to a social problem, manifested in an increase in solitary deaths and reclusive individuals. This research sheds light on one aspect of these social phenomena through the analysis of data from a large online community.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.129-164
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• 2023

In a situation where the use and introduction of Large Language Models (LLMs) is expanding due to recent developments in generative AI technology, it is difficult to find actual application cases or implementation methods for the use of internal company data in existing studies. Accordingly, this study presents a method of implementing generative AI services using the LLM application architecture using the most widely used LangChain framework. To this end, we reviewed various ways to overcome the problem of lack of information, focusing on the use of LLM, and presented specific solutions. To this end, we analyze methods of fine-tuning or direct use of document information and look in detail at the main steps of information storage and retrieval methods using the retrieval augmented generation (RAG) model to solve these problems. In particular, similar context recommendation and Question-Answering (QA) systems were utilized as a method to store and search information in a vector store using the RAG model. In addition, the specific operation method, major implementation steps and cases, including implementation source and user interface were presented to enhance understanding of generative AI technology. This has meaning and value in enabling LLM to be actively utilized in implementing services within companies.

• Information Systems Review
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• v.23 no.4
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• pp.23-43
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• 2021

Due to the recent transition to a non-face-to-face society, many organizations are quickly adapting to foster a smart work environment. The introduction of smart work does not simply end with incorporating ICT systems or solutions into business models since fundamental factors such as forms of employment and work styles need to be in line with the progression of technological advances. However, previous studies regarding smart work focus on improvements in productivity and efficiency from a technology acceptance perspective. Therefore, there is a lack of discussion on innovation resistance from employees and management control when ICT systems are introduced into the workplace. This study empirically analyzes the moderating effects of the organizational control method for employees and innovation resistance within a smart work environment. Additionally, this study aims to identify the structural characteristics that employees resist from an innovation resistance perspective when organizational innovation occurs. The empirical analysis of this study suggests that when smart work such as ICT technology is introduced into the workplace the level of innovation resistance decreases when there is a high level of relative advantage and self-efficacy, whereas the level of innovation resistance increases when there is a high level of use complexity. Moreover, this study revealed that the level of innovation resistance increases when the employees' behaviors were controlled. The results of this study intend to contribute to improving business management by suggesting factors worth considering when incorporating smart work into work places through a thorough case analysis.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.138-157
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• 2024

Due to recent developments in smartphones, lifestyles centred around their use are rapidly changing across many societal areas. Mobility apps, widely used by a large number of people, have also become popular among tourists for travel purposes. This trend is exemplified by the premium taxi industry, which champions smart mobility services-an essential component of smart tourism-to attract tourists as customers. This study investigates how smart mobility service attributes influence memorable user experiences from the perspective of both residents and tourists. It also examines the consequent image of smart mobility and users' intentions to reuse these services. To this end, a survey and analysis were conducted with 320 registered customers of domestic premium taxi companies, which are expanding their services to cater to both residents and tourists. The analysis confirmed all hypotheses. Among the attributes of smart mobility, involvement played a crucial role in shaping the image of smart mobility, more so than refreshment or novelty. Furthermore, the image of smart mobility significantly impacted the intention to reuse it. Based on these findings, this study presents practical implications regarding which empirical factors should be managed from a smart mobility perspective to foster a positive image and encourage reuse.

• Knowledge Management Research
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• v.25 no.2
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• pp.135-153
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• 2024

With the recent emergence of smart tourist cities, premium mobility is being considered an important means of transportation in the tourism. However, there has been insufficient research conducted on the experience of premium mobility among its users. Accordingly, this study used CIT to analyze the components of the user experience of customers who used premium mobility. In order to specifically identify the factors that make up the premium mobility experience, 366 cases of satisfaction and 13 cases of dissatisfaction were collected through a total of 273 online surveys. As a result of the study, based on the customer's experience using premium mobility, CIT was applied to derive 6 categories and 9 sub-factors that constitute the perception of premium mobility. In particular, this study is different from existing studies in that convenience was added as a new category out of the 6 categories, and wide ride comfort and high price were derived as new sub-factors among the 9 sub-factors. Because of this, it has academic significance. Therefore, if scales suitable for quantitative research are developed based on the derived constructs, they could be widely applied to various topics related to premium mobility in the tourism field.