• Journal of Distribution Research
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• 제15권3호
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• pp.111-137
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• 2010

The basic purpose of this study is to investigate perceived quality and service personal value affecting the result of long-term relationship between service buyers and suppliers. This research presented a constructive model(perceived quality affecting the service personal value and the moderate effect of NFC) in the on off line and then propose the research model base on prior researches and studies about relationships among components of service. Data were gathered from respondents who visit at the education service market. For this study, Data were analyzed by AMOS 7.0. We integrate the literature on services marketing with researches on personal values and perceived quality. The SERPVAL scale presented here allows for the creation of a common ground for assessing service personal values, giving a clear understanding of the key value dimensions behind service choice and usage. It will lead to a focus of future research in services marketing, extending knowledge in the field and stimulating further empirical research on service personal values. At the managerial level, as a tool the SERPVAL scale should allow practitioners to evaluate and improve the value of a service, and consequently, to define strategies and actions to address services for customers based on their fundamental personal values. Through qualitative and empirical research, we find that the service quality construct conforms to the structure of a second-order factor model that ties service quality perceptions to distinct and actionable dimensions: outcome, interaction, and environmental quality. In turn, each has two subdimensions that define the basis of service quality perceptions. The authors further suggest that for each of these subdimensions to contribute to improved service quality perceptions, the quality received by consumers must be perceived to be reliable, responsive, and empathetic. Although the service personal value may be found in researches that explore individual values and their consequences for consumer behavior, there is no established operationalization of a SERPVAL scale. The inexistence of an established scale, duly adapted in order to understand and analyze personal values behind services usage, exposes the need of a measurement scale with such a purpose. This need has to be rooted, however, in a conceptualization of the construct being scaled. Service personal values can be defined as a customer's overall assessment of the use of a service based on the perception of what is achieved in terms of his own personal values. As consumer behaviors serve to show an individual's values, the use of a service can also be a way to fulfill and demonstrate consumers'personal values. In this sense, a service can provide more to the customer than its concrete and abstract attributes at both the attribute and the quality levels, and more than its functional consequences at the value level. Both values and services literatures agree, that personal value is the highest-level concept, followed by instrumental values, attitudes and finally by product attributes. Purchasing behaviors are agreed to be the end result of these concepts' interaction, with personal values taking a major role in the final decision process. From both consumers' and practitioners' perspectives, values are extremely relevant, as they are desirable goals that serve as guiding principles in people's lives. While building on previous research, we propose to assess service personal values through three broad groups of individual dimensions; at the self-oriented level, we use (1) service value to peaceful life (SVPL) and, at the social-oriented level, we use (2) service value to social recognition (SVSR), and (3) service value to social integration (SVSI). Service value to peaceful life is our first dimension. This dimension emerged as a combination of values coming from the RVS scale, a scale built specifically to assess general individual values. If a service promotes a pleasurable life, brings or improves tranquility, safety and harmony, then its user recognizes the value of this service. Generally, this service can improve the user's pleasure of life, since it protects or defends the consumer from threats to life or pressures on it. While building upon both the LOV scale, a scale built specifically to assess consumer values, and the RVS scale for individual values, we develop the other two dimensions: SVSR and SVSI. The roles of social recognition and social integration to improve service personal value have been seriously neglected. Social recognition derives its outcome utility from its predictive utility. When applying this underlying belief to our second dimension, SVSR, we assume that people use a service while taking into consideration the content of what is delivered. Individuals consider whether the service aids in gaining respect from others, social recognition and status, as well as whether it allows achieving a more fulfilled and stimulating life, which might then be revealed to others. People also tend to engage in behavior that receives social recognition and to avoid behavior that leads to social disapproval, and this contributes to an individual's social integration. This leads us to the third dimension, SVSI, which is based on the fact that if the consumer perceives that a service strengthens friendships, provides the possibility of becoming more integrated in the group, or promotes better relationships at the social, professional or family levels, then the service will contribute to social integration, and naturally the individual will recognize personal value in the service. Most of the research in business values deals with individual values. However, to our knowledge, no study has dealt with assessing overall personal values as well as their dimensions in a service context. Our final results show that the scales adapted from the Schwartz list were excluded. A possible explanation is that although Schwartz builds on Rokeach work in order to explore individual values, its dimensions might be especially focused on analyzing societal values. As we are looking for individual dimensions, this might explain why the values inspired by the Schwartz list were excluded from the model. The hierarchical structure of the final scale presented in this paper also presents theoretical implications. Although we cannot claim to definitively capture the dimensions of service personal values, we believe that we come close to capturing these overall evaluations because the second-order factor extracts the underlying commonality among dimensions. In addition to obtaining respondents' evaluations of the dimensions, the second-order factor model captures the common variance among these dimensions, reflecting the respondents' overall assessment of service personal values. Towards this fact, we expect that the service personal values conceptualization and measurement scale presented here contributes to both business values literature and the service marketing field, allowing for the delineation of strategies for adding value to services. This new scale also presents managerial implications. The SERPVAL dimensions give some guidance on how to better pursue a highly service-oriented business strategy. Indeed, the SERPVAL scale can be used for benchmarking purposes, as this scale can be used to identify whether or not a firms' marketing strategies are consistent with consumers' expectations. Managerial assessment of the personal values of a service might be extremely important because it allows managers to better understand what customers want or value. Thus, this scale allows us to identify what services are really valuable to the final consumer; providing knowledge for making choices regarding which services to include. Traditional approaches have focused their attention on service attributes (as quality) and service consequences(as service value), but personal values may be an important set of variables to be considered in understanding what attracts consumers to a certain service. By using the SERPVAL scale to assess the personal values associated with a services usage, managers may better understand the reasons behind services' usage, so that they may handle them more efficiently. While testing nomological validity, our empirical findings demonstrate that the three SERPVAL dimensions are positively and significantly associated with satisfaction. Additionally, while service value to social integration is related only with loyalty, service value to peaceful life is associated with both loyalty and repurchase intent. It is also interesting and surprising that service value to social recognition appears not to be significantly linked with loyalty and repurchase intent. A possible explanation is that no mobile service provider has yet emerged in the market as a luxury provider. All of the Portuguese providers are still trying to capture market share by means of low-end pricing. This research has implications for consumers as well. As more companies seek to build relationships with their customers, consumers are easily able to examine whether these relationships provide real value or not to their own lives. The selection of a strategy for a particular service depends on its customers' personal values. Being highly customer-oriented means having a strong commitment to customers, trying to create customer value and understanding customer needs. Enhancing service distinctiveness in order to provide a peaceful life, increase social recognition and gain a better social integration are all possible strategies that companies may pursue, but the one to pursue depends on the outstanding personal values held by the service customers. Data were gathered from 284 respondents in the korean discount store and online shopping mall market. This research proposed 3 hypotheses on 6 latent variables and tested through structural equation modeling. 6 alternative measurements were compared through statistical significance test of the 6 paths of research model and the overall fitting level of structural equation model. and the result was successful. and Perceived quality more positively influences service personal value when NFC is high than when no NFC is low in the off-line market. The results of the study indicate that service quality is properly modeled as an antecedent of service personal value. We consider the research and managerial implications of the study and its limitations. In sum, by knowing the dimensions a consumer takes into account when choosing a service, a better understanding of purchasing behaviors may be realized, guiding managers toward customers expectations. By defining strategies and actions that address potential problems with the service personal values, managers might ultimately influence their firm's performance. we expect to contribute to both business values and service marketing literatures through the development of the service personal value. At a time when marketing researchers are challenged to provide research with practical implications, it is also believed that this framework may be used by managers to pursue service-oriented business strategies while taking into consideration what customers value.

• Journal of Intelligence and Information Systems
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• 제23권2호
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Journal of Intelligence and Information Systems
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• 제17권4호
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of the Korean Society of Food Science and Nutrition
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• 제42권7호
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• pp.1054-1064
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• 2013

The purpose of this study was to examine the question of whether there is any difference in dietary habits, climacteric symptoms, and general health characteristics of middle-aged women according to food supplements (FS) use. A total of 745 midlife females participated in a face-to-face interview conducted by qualified interviewers, which guaranteed a higher quality of data collection. Three levels of FS use were defined: None, Single, and Multi for 0, 1, and 2 or more types of FS use, respectively. None, Single, and Multi accounted for 33.56%, 33.29%, and 33.15% of total subjects, respectively. FS users (Single and Multi) exerted more interest in FS and were more likely to believe that FS is helpful for health promotion and amelioration of climacteric symptoms than None (P<0.0001). Self-perceived health status of Multi was lower than that of None, but not different from Single (P<0.05). Factor analysis extracted three factors for dietary habits: regularity, variety and moderation, and four factors for climacteric symptoms: emotional, physical, psycho-somatic, and hot flash. The factor scores for dietary variety as well as emotional, psycho-somatic, and hot flash symptoms were higher for FS user than for None (P<0.01). Single reported more frequent family meals compared to None. Findings of the present study elucidated potential links between the level of FS use, dietary habits, and climacteric symptoms of middle-aged women, suggesting a possible scenario: the greater the climacteric symptoms a woman perceives, the more likely the woman will adopt FS use, the greater the efforts toward dietary improvement, such as dietary variety. Based on that, in this study, more peri-menopausal women belonged to Single and Multi; further investigation on the association between FS use, dietary quality, and climacteric symptoms in conjunction with menopausal status may be needed.

• Progress in Medical Physics
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• 제26권1호
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• pp.12-17
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• 2015

The purpose of the Monte Carlo simulation study was to provide the optimized nozzle design to satisfy the beam conditions for biomedical researches in the Korean heavy-ion accelerator, RAON. The nozzle design was required to produce $C^{12}$ beam satisfying the three conditions; the maximum field size, the dose uniformity and the beam contamination. We employed the GEANT4 toolkit in Monte Carlo simulation to optimize the nozzle design. The beams for biomedical researches were required that the maximum field size should be more than $15{\times}15cm^2$, the dose uniformity was to be less than 3% and the level of beam contamination due to the scattered radiation from collimation systems was less than 5% of total dose. For the field size, we optimized the tilting angle of the circularly rotating beam controlled by a pair of dipole magnets at the most upstream of the user beam line unit and the thickness of the scatter plate located downstream of the dipole magnets. The values of beam scanning angle and the thickness of the scatter plate could be successfully optimized to be $0.5^{\circ}$ and 0.05 cm via this Monte Carlo simulation analysis. For the dose uniformity and the beam contamination, we introduced the new beam configuration technique by the combination of scanning and static beams. With the combination of a central static beam and a circularly rotating beam with the tilting angle of $0.5^{\circ}$ to beam axis, the dose uniformity could be established to be 1.1% in $15{\times}15cm^2$ sized maximum field. For the beam contamination, it was determined by the ratio of the absorbed doses delivered by $C^{12}$ ion and other particles. The level of the beam contamination could be achieved to be less than 2.5% of total dose in the region from 5 cm to 17 cm water equivalent depth in the combined beam configuration. Based on the results, we could establish the optimized nozzle design satisfying the beam conditions which were required for biomedical researches.

• Journal of Climate Change Research
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• 제2권1호
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• pp.55-68
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• 2011

The Intergovernmental Panel on Climate Change(IPCC) has identified the causes of climate change and come up with measures to address it at the global level. Its key component of the work involves developing and assessing future climate change scenarios. The IPCC Expert Meeting in September 2007 identified a new greenhouse gas concentration scenario "Representative Concentration Pathway(RCP)" and established the framework and development schedules for Climate Modeling (CM), Integrated Assessment Modeling(IAM), Impact Adaptation Vulnerability(IAV) community for the fifth IPCC Assessment Reports while 130 researchers and users took part in. The CM community at the IPCC Expert Meeting in September 2008, agreed on a new set of coordinated climate model experiments, the phase five of the Coupled Model Intercomparison Project(CMIP5), which consists of more than 30 standardized experiment protocols for the shortterm and long-term time scales, in order to enhance understanding on climate change for the IPCC AR5 and to develop climate change scenarios and to address major issues raised at the IPCC AR4. Since early 2009, fourteen countries including the Korea have been carrying out CMIP5-related projects. Withe increasing interest on climate change, in 2009 the COdinated Regional Downscaling EXperiment(CORDEX) has been launched to generate regional and local level information on climate change. The National Institute of Meteorological Research(NIMR) under the Korea Meteorological Administration (KMA) has contributed to the IPCC AR4 by developing climate change scenarios based on IPCC SRES using ECHO-G and embarked on crafting national scenarios for climate change as well as RCP-based global ones by engaging in international projects such as CMIP5 and CORDEX. NIMR/KMA will make a contribution to drawing the IPCC AR5 and will develop national climate change scenarios reflecting geographical factors, local climate characteristics and user needs and provide them to national IAV and IAM communites to assess future regional climate impacts and take action.

• Journal of Broadcast Engineering
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• 제24권1호
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• pp.118-131
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• 2019

In order to provide 8K UHD contents of terrestrial broadcasting with a large capacity, the terrestrial broadcasting system has various problems such as limited bandwidth and so on. To solve these problems, UHD contents transmission technology has been actively studied, and an 8K UHD broadcasting system using terrestrial broadcasting network and communication network has been proposed. The proposed technique is to solve the limited bandwidth problem of terrestrial broadcasting network by segmenting 8K UHD contents and transmitting them to heterogeneous networks through hierarchical separation. Through the terrestrial broadcasting network, the base layer corresponding to FHD and the additional enhancement layer data for 4K UHD are transmitted, and the additional enhancement layer data corresponding to 8K UHD is transmitted through the communication network. When 8K UHD contents are provided in such a way, user can receive up to 4K UHD broadcasting by terrestrial channels, and also can receive up to 8K UHD additional communication networks. However, in order to transmit the 4K UHD contents within the allocated bit rate of the domestic terrestrial UHD broadcasting, the compression rate is increased, so a certain level of image deterioration occurs inevitably. Due to the nature of UHD contents, video quality should be considered as a top priority over other factors, so that video quality should be guaranteed even within a limited bit rate. This requires packet scheduling of content generators in the broadcasting system. Since the multiplexer sends out the packets received from the content generator in order, it is very important to make the transmission time and the transmission rate of the process from the content generator to the multiplexer constant and accurate. Therefore, we propose a variable transmission scheduler between the content generator and the multiplexer to guarantee the image quality of a certain level of UHD contents in this paper.

• Journal of Intelligence and Information Systems
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• 제29권3호
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• pp.185-209
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• 2023

With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• 제17권4호
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• pp.193-204
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• 2022

This study analyzed the degree of influence of measurement and improvement of customer satisfaction level targeting kiosk users. In modern times, due to the development of technology and the improvement of the online environment, the probability that simple labor tasks will disappear after 10 years is close to 90%. Even in domestic research, it is predicted that 'simple labor jobs' will disappear due to the influence of advanced technology with a probability of about 36%. there is. In particular, as the demand for non-face-to-face services increases due to the Corona 19 virus, which is recently spreading globally, the trend of introducing kiosks has accelerated, and the global market will grow to 83.5 billion won in 2021, showing an average annual growth rate of 8.9%. there is. However, due to the unmanned nature of these kiosks, some consumers still have difficulties in using them, and consumers who are not familiar with the use of these technologies have a negative attitude towards service co-producers due to rejection of non-face-to-face services and anxiety about service errors. Lack of understanding leads to role conflicts between sales clerks and consumers, or inequality is being created in terms of service provision and generations accustomed to using technology. In addition, since kiosk is a representative technology-based self-service industry, if the user feels uncomfortable or requires additional labor, the overall service value decreases and the growth of the kiosk industry itself can be suppressed. It is important. Therefore, interviews were conducted on the main points of direct use with actual users centered on display color scheme, text size, device design, device size, internal UI (interface), amount of information, recognition sensor (barcode, NFC, etc.), Display brightness, self-event, and reaction speed items were extracted. Afterwards, using the questionnaire, the Kano model quality attribute classification of each expected evaluation item was carried out, and Timko's customer satisfaction coefficient, which can be calculated with accurate numerical values The PCSI Index analysis was additionally performed to determine the improvement priorities by finally classifying the improvement impact of the kiosk expected evaluation items through research. As a result, the impact of improvement appears in the order of internal UI (interface), text size, recognition sensor (barcode, NFC, etc.), reaction speed, self-event, display brightness, amount of information, device size, device design, and display color scheme. Through this, we intend to contribute to a comprehensive comparison of kiosk-based research in each field and to set the direction for improvement in the venture industry.

• Journal of Intelligence and Information Systems
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• 제26권4호
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• pp.149-171
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• 2020

The period at university is to make decision about getting an actual job. As our society develops rapidly and highly, jobs are diversified, subdivided, and specialized, and students' job preparation period is also getting longer and longer. This study analyzed the log data of college students to see how the various activities that college students experience inside and outside of school might have influences on employment. For this experiment, students' various activities were systematically classified, recorded as an activity data and were divided into six core competencies (Job reinforcement competency, Leadership & teamwork competency, Globalization competency, Organizational commitment competency, Job exploration competency, and Autonomous implementation competency). The effect of the six competency levels on the employment status (employed group, unemployed group) was analyzed. As a result of the analysis, it was confirmed that the difference in level between the employed group and the unemployed group was significant for all of the six competencies, so it was possible to infer that the activities at the school are significant for employment. Next, in order to analyze the impact of the six competencies on the qualitative performance of employment, we had ANOVA analysis after dividing the each competency level into 2 groups (low and high group), and creating 6 groups by the range of first annual salary. Students with high levels of globalization capability, job search capability, and autonomous implementation capability were also found to belong to a higher annual salary group. The theoretical contributions of this study are as follows. First, it connects the competencies that can be extracted from the school experience with the competencies in the Human Resource Management field and adds job search competencies and autonomous implementation competencies which are required for university students to have their own successful career & life. Second, we have conducted this analysis with the competency data measured form actual activity and result data collected from the interview and research. Third, it analyzed not only quantitative performance (employment rate) but also qualitative performance (annual salary level). The practical use of this study is as follows. First, it can be a guide when establishing career development plans for college students. It is necessary to prepare for a job that can express one's strengths based on an analysis of the world of work and job, rather than having a no-strategy, unbalanced, or accumulating excessive specifications competition. Second, the person in charge of experience design for college students, at an organizations such as schools, businesses, local governments, and governments, can refer to the six competencies suggested in this study to for the user-useful experiences design that may motivate more participation. By doing so, one event may bring mutual benefits for both event designers and students. Third, in the era of digital transformation, the government's policy manager who envisions the balanced development of the country can make a policy in the direction of achieving the curiosity and energy of college students together with the balanced development of the country. A lot of manpower is required to start up novel platform services that have not existed before or to digitize existing analog products, services and corporate culture. The activities of current digital-generation-college-students are not only catalysts in all industries, but also for very benefit and necessary for college students by themselves for their own successful career development.