• Journal of Venture Innovation
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• v.6 no.3
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• pp.73-93
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• 2023

This study provides a prospect for the fast growing the smartwatch market by investigating the relationship between the satisfaction and the continuous use intention of Apple watch users, as well as the factors influencing their satisfaction. Based on the TAM, this study uses system quality, information quality, and self-efficacy as independent variables, perceived usefulness, perceived ease of use, and satisfaction as mediators, and continuous use intention as the dependent variable. We analyze the data of 256 individuals who completed an online survey with SPSS 26.0 and AMOS 26.0 software. This study conducts several tests and analyses to empirically evaluate the data including reliability analysis, factor analysis, feasibility analysis, path analysis, hypothesis verification, and mediation analysis. Our results investigate which factors may influence consumers' intention to continuously using Apple Watch devices in the future. In summary, satisfaction has a positive effect on the intention to continuously use smartwatchs. Perceived usefulness and perceived ease of use have a positive effect on satisfaction. Among the three factors (system quality, information quality, and self-efficacy), only self-efficacy has no significant impact on perceived usefulness but had a positive effect on perceived ease of use. In addition, system quality and information quality positively affect perceived usefulness, perceived ease of use, satisfaction, and continuous intention to use an Apple Watch. Taking the Apple Watch as the subject of our research topic, this study provides theoretical value by exploring the impact of user's satisfaction with their smartwatch on their continuous usage intention. This study further explains the influence of system quality, information quality, and self-efficacy on user satisfaction. Additionally, this research offers valuable insight to practitioners by confirming that information quality, system quality, and self-efficacy are important features for enhancing satisfactory user experiences which in turn may increase users' intention to continued using smartwatches.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.139-155
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• 2022

This paper presented a research model to investigate the relationship between the psychological traits of small business entrepreneurs and entrepreneurial orientation and the relationship between entrepreneurial orientation and performance. To verify the research model, a total of 202 entrepreneurs in Daegu were surveyed and the data obtained were used. The collected data were analyzed by SPSS and AMOS. The results of the analysis showed that all of the psychological traits except 'Agreeableness' and 'Extroversion' among the small business entrepreneur's psychological trait had a positive(+) effect on entrepreneurial orientation. In addition, it was confirmed that entrepreneurship orientation had a positive(+) effect on performance, and government policy funding had a moderating effect between entrepreneurship orientation and performance. In conclusion, the causal relationship between the small business entrepreneur's psychological traits and entrepreneurial orientation is examined, and the moderating effect of government support programs is examined to find out what psychological traits of small business entrepreneurs affect the expression of entrepreneurial orientation. In addition, since entrepreneurial orientation affects performance and government policy funds control, it suggests that continuous financial support for small business entrepreneurs is needed.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.39-50
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• 2024

Color is an essential visual element that has a significant impact on the formation of a city's image and people's perceptions. Quantitative analysis of color in urban environments is a complex process that has been difficult to implement in the past. However, with recent rapid advances in Machine Learning, it has become possible to analyze city colors using photos shared by tourists. This study selected Dali City, a popular tourist destination in China, as a case study. Photos of Dali City shared by tourists were collected, and a method to measure large-scale city colors was explored by combining machine learning techniques. Specifically, the DeepLabv3+ model was first applied to perform a semantic segmentation of tourist sharing photos based on the ADE20k dataset, thereby separating artificial elements in the photos. Next, the K-means clustering algorithm was used to extract colors from the artificial elements in Dali City, and an adjacency matrix was constructed to analyze the correlations between the dominant colors. The research results indicate that the main color of the artificial elements in Dali City has the highest percentage of orange-grey. Furthermore, gray tones are often used in combination with other colors. The results indicated that local ethnic and Buddhist cultures influence the color characteristics of artificial elements in Dali City. This research provides a new method of color analysis, and the results not only help Dali City to shape an urban color image that meets the expectations of tourists but also provide reference materials for future urban color planning in Dali City.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.102-108
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• 2024

In the initial stages of urban air mobility (UAM) operations, compliance with existing visual flight rules and instrument flight regulations for conventional human-crewed aircraft is crucial. Additionally, voice communication between the on board pilot and relevant UAM stakeholders, including vertiports, is essential. Consequently, very high frequency (VHF) aviation voice communication must be consistently provided throughout all phases of UAM operations. This paper presents the results of the VHF communication coverage analysis for the initial UAM demonstration areas, encompassing the Hangang River and Incheon Ara-Canal corridors, as well as potential vertiport candidate locations. By considering the influence of terrain and buildings through the utilization of a digital surface model (DSM), communication quality prediction results are obtained for the analysis areas. The three-dimensional coverage analysis results indicate that stable coverage can be achieved within altitude corridors ranging from 300 m to 600 m. However, there are shaded areas in the low-altitude vertiport regions due to the impact of high-rise buildings. Therefore, additional research to ensure stable coverage around vertiports in the lower altitude areas is required.

• Information Systems Review
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• v.21 no.4
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• pp.125-141
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• 2019

With the advent of deep learning technology, which is represented by AlphaGo, artificial intelligence (A.I.) has quickly emerged as a key theme of digital transformation to secure competitive advantage for businesses. In order to understand the trends of A.I. based digital transformation, a clear comprehension of the A.I. business ecosystem should precede. Therefore, this study analyzed the A.I. business ecosystem from the multi-actor network perspective and identified the A.I. platform strategy type. Within internal three layers of A.I. business ecosystem (infrastructure & hardware, software & application, service & data layers), this study identified four types of A.I. platform strategy (Tech. vertical × Biz. horizontal, Tech. vertical × Biz. vertical, Tech. horizontal × Biz. horizontal, Tech. horizontal × Biz. vertical). Then, outside of A.I. platform, this study presented five actors (users, investors, policy makers, consortiums & innovators, CSOs/NGOs) and their roles to support sustainable A.I. business ecosystem in symbiosis with human. This study identified A.I. business ecosystem framework and platform strategy type. The roles of government and academia to create a sustainable A.I. business ecosystem were also suggested. These results will help to find proper strategy direction of A.I. business ecosystem and digital transformation.

• Journal of Practical Agriculture & Fisheries Research
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• v.26 no.1
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• pp.22-29
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• 2024

In this study, we summarized the definition of smart vegetable seedling production technology, analysis of smart seedling production system, a hardware and software configuration model for smart seedling production system, research and development trends in smart seedling production system, and proposed future research and development plans for smart seedling production technology. Smart vegetable seedling production is a data-based seedling production, management, and distribution system that utilizes 4th Industrial Revolution technology to improve seedling productivity and quality. The production of vegetable seedlings using smart seedling production technology can be efficiently managed by collecting, analyzing, and managing information on seedlings, environment, and tasks at each stage of production by linking with the smart seedling integrated management system. However, there is still a lack of standardization of seedling standards and quality for each vegetable crop to establish smart seeding production technology, as well as development of smart seedling production element technology, which requires national wide R&D support.

• Industry Promotion Research
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• v.9 no.3
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• pp.295-309
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• 2024

With the implementation of the Northeast Revitalization Strategy, the tourism industry in Heilongjiang Province had an increasingly greater impact on regional economic development. Based on the tourism panel data of Heilongjiang Province from 2005 to 2021, this paper used DEA-BCC and Malmquist Index to analyze the static and dynamic changes of the tourism industry.The results of the study were as follows: (1) Static: The OE value reached strong DEA effectiveness in 2010, 2013, and 2019, indicated that tourism resources had been fully utilized. The SE value changed dramatically between 0.354 and 1, and the PTE value approached 1. OE was mainly affected by SE changes. (2) Dynamic: The total factor productivity (TFP) was overall greater than 1 and grew at an average annual rate of 13.8%. The variation in TFP was primarily influenced by the index of technological progress, indicated that the tourism industry in Heilongjiang Province made full use of technology for resource development, with a relatively high level of development efficiency. Therefore, the future focus of Heilongjiang Province's tourism industry will be on adjustments in industrial scale, technological innovation, and policy optimization.

• Journal of Korea Port Economic Association
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• v.40 no.1
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• pp.87-118
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• 2024

Coastal ports play an essential role in developing a country and a city. Port efficiency is an important factor affecting port trade, and the importance of port efficiency for port performance has been recognized in previous literature. DEA (Data Envelopment Analysis) and SFA (Stochastic Frontier Analysis) are widely used in this field of research. However, these two methods are limited in selecting input and output variables. In addition, the literature studies on Chinese coastal ports mainly focus on the study of port clusters in local areas, which lacks a holistic approach and generally lacks up-to-date data. Therefore, to fill the gap in this area of research, this paper introduces a model combining principal component analysis and data envelopment analysis to analyze the operational efficiency of the top 17 coastal ports in China in terms of throughput based on the most recent data available in 2021. This paper identifies container throughput as the output variable, and 13 second indicators are selected as input variables from four primary indicators: land, capital, labor, and infrastructure. Four principal components were selected from 13 second indicators using PCA.After that, DEA (BBC) and DEA (CCR) were used to analyze the 17 ports, among which five were Shanghai, Ningbo-Zhoushan, Guangzhou, Xiamen, and Dongguan, respectively, DEA efficient, and the remaining 12 ports were non-DEA efficient. Finally, improvement directions for each port are derived, and brief suggestions are made. This paper provides some reference value for developing and constructing coastal ports in China.

• Journal of the Korean Society for information Management
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• v.41 no.3
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• pp.269-288
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• 2024

In the era of digital transformation, discussions about digital curation have become increasingly active not only in academia but also in various fields. The primary purpose of this study is to analyze the conceptual changes in digital curation over time, particularly by examining the definition statements related to digital curation as described in academic literature. To achieve this, academic research papers from 2009, when the term "digital curation" was first mentioned, to 2023 were collected, and definition statements that explained relevant concepts were extracted. Basic statistical analyses were conducted. Using DMR topic modeling and word networks, the relationships among keywords and the changes in their importance over time were examined, and a conceptual map of digital curation was made focusing on the main topics. The results revealed that the concept of digital curation is primarily centered around the themes of "data preservation," "traditional curator roles," and "product recommendation curation." Depending on the researchers' intentions for utilizing digital curation, the concept was expanded to include topics such as "content distribution and classification," "information usage," and "curation models." This study is significant in that it analyzed the concept of digital curation through definition statements reflecting the perspectives of researchers. Additionally, the study holds value in explicitly identifying changes in the concepts that researchers emphasize over time through the trends in topic prevalence.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.107-118
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• 2016

The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.