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The aim of this study is to assess the impacts of service properties, price expectancy, social influences, and switching costs on adoption intention of 4G in Vietnam. The research model was established by the theory of diffusion of innovation, technology acceptance model, service quality, social influences and switching costs. The result from customers using telecommunication services in Vietnam shows that adoption intention of 4G is affected directly by perceived usefulness, personal innovativeness, price expectancy, social influences, prior service quality and switching costs. Whereas, switching costs have negative effect on adoption intention. Other factors such as personal innovativeness, perceived ease of use and prior service quality have an indirect effect on adoption intention of 4G.

This study starts from the question, “Are people of the age 60 and over equally ‘old?’ ” As the aging population has rapidly become a global issue, it is a timely question to think about whether it is appropriate to classify people aged 60 and over as senior citizens monolithically based on their chronological age. Thanks to the advancement of medical technology and ever-increasing life expectancy, there may be more differences than we thought in terms of cognitive and behavioral patterns among the elderly population. In order to further investigate this question, this study focuses on technology acceptance behavior of 132 participants over the age of 60 towards a wearable healthcare device. The results show that there were interesting behavioral differences among participants depending on their cognitive capabilities. More specifically, participants with high cognitive capability (Superagers) consider the usefulness and the social aspects (social norm and image) of using wearable healthcare technology. Whereas for those with relatively low cognitive capability (non-Superagers), usefulness of using the technology was not a significant factor, and they mainly considered social norm and image. Our findings imply that the current monolithic application of chronological age to classify the elderly population should be carefully reconsidered because people aged over 60 years old may not always share homogeneous cognitive and behavioral patterns.

As data grows rapidly, the provision of appropriate information needed by individuals has become an area of new services, and customized services which is enabling the analysis of optimal services through collecting, storing, and analyzing personal data are emerging in many fields. However, due to the characteristics of customized services based on various information collected by customers during the use of the service, the problem of privacy infringement is raised at the same time, and many studies are being actively conducted to solve this problem. This study seeks to explore how the customer's in-depth and customized services has an impact on their customers, which has not been derived from quantitative research using the grounded theory methodology. Through this, 84 concepts, 33 subcategories, 13 Categories and paradigm models were derived. In addition, ‘Understanding and acceptance of online behavioral advertising (OBA)' was derived as a core category, and finally, acceptance types of OBA were classified into ‘positive acceptance type', ‘indifferent type', ‘calculating type', and ‘active resistance type' based on the key categories. This study divides the acceptance types of online behavioral advertising through the emotions and behaviors of the consumers throughout the procedure of online behavioral advertising experiences. In addition to the statistical and quantitative information currently used for providing behavioral advertising, it provides new criteria to reflect the refinement of behavioral advertising and personal tendencies or characteristics.

The purpose of this study is to find out the fast delivery route that several drones return a truck again after departing from it for delivery locations at each cluster while the truck goes through the cluster composed of several delivery locations. The main issue is to reduce the total delivery time composed of the delivery time by relatively slow trucks via clusters and the sum of maximum delivery times by relatively fast drones in each cluster. To solve this problem, we use a three-step heuristic approach. First, we cluster the nearby delivery locations with minimal number of clusters satisfying a constraint of drone flight distance to set delivery paths for drones in each cluster. Second, we set an optimal delivery route for a truck through centers of the clusters using the TSP model. Finally, we find out the moved centers of clusters while maintaining the delivery paths for the truck and drones and satisfying the constraint of drone flight. distance in the two-dimensional region to reduce the total delivery time. In order to analyze the effect of this study model according to the change of the number of delivery locations, we developed a R-based simulation prototype and compared the relative efficiency, and performed paired t-test between TSP model and the cluster-based models. This study showed its excellence through this experimentation.

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.

Recently, office workers are increasingly aware of the right to disconnect because of the pressure from strong connections with Internet messengers. In this study, we examined the reason why the perception of the right to disconnect increases and how to deal with it. This research model is that smart working and psychological attachment from work affect right to disconnect, and that open communication and gender moderate the intensity of these effects. To verify this research model, survey questionnaires were distributed to workers in smart working environments, and 400 data were collected and analyzed using Smart-PLS. As results of data analysis, it was verified that smart working and psychological attachment from work had a significant influence on right to disconnect, that open communication group had a lesser effect of psychological attachment from work on right to disconnect than closed communication group, and that women had a lesser effect of psychological attachment from work on right to disconnect than men. Organizations need to maintain a desirable level of right to disconnect in order to improve the quality of working life. But, if it is impossible, They need to change the way of communication more openly so as to absorb the burden of strong connection by Internet. And they need to perform task assignment or stress relief policy reflecting gender characteristics.

Public transportation systems play key roles in supporting dynamic activities and interaction between urban places. Especially, high efficient public transportation systems are required in order to support large traffic demands in urban areas. In this paper, we define a new metric, structural activation level (SAL), to replace the conventional transportation share ratio (TSR) measuring efficiency of public transportation systems. First of all, we access the Korea Transport Database (KTDB) and download origin-destination data by transport types to construct traffic networks with respect to transport types for each city. Then, we calculate the QAP (Quadratic Assignment Procedure) correlation between each traffic network and the total traffic network for each city to investigate SAL by comparing cities one another. The results of our investigation reveal inconsistency between TSR and SAL. In Daegu, TSR of public transportation systems is relatively low while SAL is high. In Deajeon, however, SAL is low while TSR is high. Therefore, we suggest to take into consideration SAL as well as TSR in order to investigate the degree of activation of public transportation.