• Journal of Smart Tourism
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• v.4 no.2
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• pp.15-23
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• 2024

This study aims to present a framework involving smartness components and indicators of tourism destinations. This work had three phases. The first phase extracted the components and indicators of smartness evaluation in tourism destinations and validated them by experts' opinions. The second phase determined the effectiveness of each element of smartness using an online questionnaire tool, a survey of 320 tourism experts at the level of 12 selected urban tourism destinations, and a factor analysis method, in addition to measuring the level of their smartness. The third phase of the research analyzed the difference between the smartness of the selected urban tourism destinations using a One-Way Analysis of Variance and the Tukey Test. The results indicated six components and fifty-seven indicators. Also, a substantial difference between the smartness of urban tourism destinations was proved. This study substantially contributes to the existing body of knowledge by offering the smartness indicators within a detailed package of six components with a systemic, holistic, and integrated perspective. The results help policymakers and decision-makers evaluate and improve the smartness of tourism destinations. As a result, it is possible to achieve the goals of smartness of urban tourism destinations, including equality, livability, sustainability, and effectiveness of resource management by using different technologies, especially with the emphasis on two aspects: (1) increasing the quality of the tourism experience, and (2) improving the residents' quality of life.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.97-109
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• 2024

This research aims to investigate how major cities in Korea utilize smart city-related technologies, develop key performance indicators (KPIs) to measure the smartness and efficiency of cities, and propose a methodology for assessing and suggesting smart city policy directions based on Data Envelopment Analysis (DEA). Referring to the CITYkeys Smart City Performance Measurement Framework, 10 key performance indicators (KPIs) were derived. For each KPI, city statistical data were allocated to input and output variables, and 15 cities were assigned as Decision Making Units (DMUs). The DEA methodology was employed to evaluate the operational efficiency and scale profitability of cities, providing insights into the operational efficiency of each city. Finally, the operational efficiency among DMUs was ranked to propose smart city policy directions for each city.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.230-238
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• 2023

Small and medium-sized food manufacturing enterprises are largely reliant on manual labor, from inputting raw materials to palletizing the final product. Recently, there has been a trend toward smartness and digitization through the implementation of robotics and sensor data technology. In this study, we examined the effectiveness of improvement through 3D simulation on two repetitive work processes within a food manufacturing company. These processes involve workers whose speed cannot match the capacity of the applied equipment. Two manual processes were selected: the weighing and packing process performed by workers after skewer assembly, and the manual batch process of counting randomly delivered frozen foods, packing (both internal and external), and palletizing. The production volume, utilization rate, and number of workers were chosen as verification indicators. As a result of the simulation for improving the 3D process, production increased by 13.5% and 56.8% compared to the existing process, respectively. This was particularly evident in the process of applying palletizing robots. In both processes, as the utilization rate and number of input workers decreased, robots could replace tasks with high worker fatigue, thereby reducing work overload. This study demonstrates the potential to visually compare the process flow improvement using 3D simulations and confirms the possibility of pre-validation for improvement.