• International journal of advanced smart convergence
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• v.10 no.1
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• pp.176-183
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• 2021

The purpose of this study is was to analyze customer experience attribute of professional baseball. To achieve objectives of this study, a method was used the in-depth interview and experts' consultation which understanding the attributes and structure of customer experience attribute of professional baseball. As a result, the professional baseball customer experience attributes are 'viewing plan & purchase', 'stadium movement', 'entrance stadium', 'move to seat', 'game viewing', 'amenities/services', 'events/cheering', 'move after match'. The review of the experience section and attributes derived through in-depth interviews with professional baseball fans was verified through an expert' consultation to secure content validity. Through this process, 8 experience section and 41 attributes were analyzed. The customer experience journey was analyzed for a more in-depth analysis of the viewing experience of professional baseball fans. The customer experience journey was presented based on the needs of fans and discomfort in each experience section activity.

• Journal of Korean Association for Spatial Structures
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• v.16 no.4
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• pp.91-100
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• 2016

A retractable-roof spatial structure is frequently used for a stadium and sports hall. A retractable-roof spatial structure allows natural lighting, ventilation, optimal conditions for grass growth with opened roof. It can also protects users against various weather conditions and give optimal circumstances for different activities. Dynamic characteristics of a retractable-roof spatial structure is changed based on opened or closed roof condition. A tuned mass damper (TMD) is widely used to reduce seismic responses of a structure. When a TMD is properly tuned, its control performance is excellent. Opened or closed roof condition causes dynamic characteristics variation of a retractable-roof spatial structure resulting in off-tuning. This dynamic characteristics variation was investigated. Control performance of a passive TMD and a smart TMD were evaluated under off-tuning condition.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.23-31
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• 2023

In this study, a smart bench was developed and researched smart benches that can contribute to user convenience and satisfaction by installing them in parks, bus stops, and tourist attractions in line with the rapidly changing construction of smart cities. The smart bench is automatically operated by the control system according to the external temperature and provides additional functions such as charging, lighting, and advertising to improve general bench functions as well as heating in winter and cooling in summer, making it suitable for smart urbanization. The developed smart bench is designed to be strong enough to withstand loads of about 2,500 N. It minimizes the visible parts such as assembled bolts and 220V power supply wires, It can also give aesthetic effects. The development was carried out with the aim of waterproofing and dustproofing of IP44 grade in accordance with the climate of Republic of Korea, which has four seasons, and it is advantageous for long-term use because the paint was selected for the weather ability (discoloration) grade 3 or higher. If smart bench is commercialized, it is believed that various options can be provided to the smart bench market, where buyers had few product options, as the parts were developed in an assembled type so that all functions can be responded in an optional form according to the installation environment and the buyer's budget.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.231-238
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• 2020

The main purpose of this current study was to identify the structural relationships between the variables of team attachment, location-based service, and future fan behaviors by utilizing Technology Acceptance Model (TAM). Among the 10 KBO franchises, SK Wyverns and KT Wiz were qualified to have their own smart applications programs and the relevant infrastructure at their home venues. Thus, a total of 500 surveys were collected from SK Wyverns and KT Wiz games during September of 2019 and a total of 448 were used for data analysis after deleting 52 surveys due to the missing data. According to the results of a structural equation modeling, 12 positive (+) causality out of 14 hypotheses were confirmed that there must be causal relationships among the variables of location-based service at the smart stadium, TAM, fan attachment, and future fan behavior. It is hoped that this study can be contributing to the foundational developments of marketing strategies by adopting the new technological advancement in the Korean sport industry in the future.

• Smart Structures and Systems
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• v.29 no.2
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• pp.321-336
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• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.819-829
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• 2022

Professional baseball is one of the spectator sports that has been loved for a long time by the citizens as a recreational activity since its establishment in 1982, and has been playing pivotal role as a national sport. However, there has been decline in the number of audiences since 2019. Hence, this research paper aimed to provide strategic direction for planning and improvement of professional baseball stadiums by applying the concept of servicescape. In this research, five key factors of servicescape that affects players performance and the level of immersion of spectators were derived through literature review, and based on these key factors, case study analysis were carried out for 51 domestic and foreign baseball stadiums while focusing on the factors derived. Domestic baseball stadiums highly concentrate on spectatorship without effectively responding to change in spectators demand and its effective use of space rather than baseball games. As in foreign cases, it is critical to modify mangement process and planning direction, and improve policies while perceiving baseball stadium as recreational and cultural space.

• Smart Structures and Systems
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• v.15 no.1
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• pp.151-167
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• 2015

Instrumentation on structural health monitoring system imposes critical issues for applying the structural monitoring system to real world structures, for which not only on the configuration and geometry, but also aesthetics on the system to be monitored should be considered. To illustrate this point, two real world structural health monitoring systems, the structural health monitoring system of Shenzhen Vanke Center and the structural health monitoring system of Shenzhen Bay Stadium in China, are presented in the paper. The instrumentation on structural health monitoring systems of real world structures is addressed by providing the description of the structure, the purpose of the structural health monitoring system implementation, as well as details of the system integration including the installations on the sensors and acquisition equipment and so on. In addition, an intelligent algorithm on stress identification using measurements from multi-region is presented in the paper. The stress identification method is deployed using the fuzzy pattern recognition and Dempster-Shafer evidence theory, where the measurements of limited strain sensors arranged on structure are the input data of the method. As results, at the critical parts of the structure, the stress distribution evaluated from the measurements has shown close correlation to the numerical simulation results on the steel roof of the Beijing National Aquatics Center in China. The research work in this paper can provide a reference for the design and implementation of both real world structural health monitoring systems and intelligent algorithm to identify stress distribution effectively.

• Smart Media Journal
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• v.7 no.1
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• pp.16-23
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• 2018

In this paper, we used the Deep Neural Network (DNN) to predict the number of daily spectators of Gwangju - KIA Champions Field in order to provide marketing data for the team and related businesses and for managing the inventories of the facilities in the stadium. In this study, the DNN model, which is based on an artificial neural network (ANN), was used, and four kinds of DNN model were designed along with dropout and batch normalization model to prevent overfitting. Each of four models consists of 10 DNNs, and we added extra models with ensemble model. Each model was evaluated by Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The learning data from the model randomly selected 80% of the collected data from 2008 to 2017, and the other 20% were used as test data. With the result of 100 data selection, model configuration, and learning and prediction, we concluded that the predictive power of the DNN model with ensemble model is the best, and RMSE and MAPE are 15.17% and 14.34% higher, correspondingly, than the prediction value of the multiple linear regression model.