• Journal of Korean Society for Quality Management
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• v.41 no.3
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• pp.381-394
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• 2013

Purpose: Nowadays, Mobile Cloud Storage services are used widely. For sustainable use of this service, we need to determine what factors affect satisfaction. Therefore, the purpose of this study is to identify the factors that influence satisfaction. Methods: To analyze factors that influence satisfaction, this study sets the factors into three dimensions such as service quality, perceived risk, and individual characteristics and analyze the causal relationship between influence factors and satisfaction through Structural Equation Model. Results: The results of this study are as follows; among service quality, user interface and reliability influenced satisfaction, but adaptability did not have any influence. Perceived risk of illegal access had a negative influence on satisfaction, while perceived risk of privacy leakage did not have significant influence on satisfaction in perceived risk. At last, self-efficacy had a significant influence on satisfaction. Conclusion: We identified the influence factors that influence satisfaction. Our findings will be necessary for Mobile Cloud Storage service providers to strengthen their service.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.289-314
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• 2015

Recently, Most of the companies and government offices are under consideration about the adoption of cloud office service to actualize the smart work policies. Comparing with traditional office software, a cloud office service have the advantage of the method of payment and coming over the physical limitations. Many cloud office service users tend to adopt an official evaluated the service without doubt. However after deciding to adopt cloud office service, many users are faced with a variety of problems and difficulties practically. In this study, researchers carried out interview about those problems and difficulties after adopting a cloud office service. Consequently, there are several problems and difficulties such as compatibility, document security, document lost and maladjusted to the new graphic user interface between traditional office software and a cloud office service. A cloud office service have still several advantages not only a competitive price but also ubiquitous attributes. Thus, researchers need to study about what kinds of reason variables can solve those problems and difficulties. In existing research, DeLone & McLean have suggested information system success model. They use three independent variables which are system quality, information quality, service quality. Parameters are user satisfaction, intention to use and use. Lastly, dependent variables are net benefits. However in this study, we need to change the scope of measurement. In other words, we have to replace parameters with dependent variables. Simply, user satisfaction, intention to use and use is going to be dependent variables. There are several reasons why we need changing variables. First, we aim at giving a some suggestions to a cloud service providers which independent variables do not work to satisfy for the users. Second, we need to find out how to maximize cloud office service user's satisfaction and intention to use. Third, we should firstly know that relationship between independent variables and dependent variables. Finally, those research results give for the cloud office service provider to solve the cloud office service adopting problems and difficulties.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.91-100
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• 2015

In this study, we propose an efficient two-phase heuristic policy, called an acceptance tolerance control policy, for Infrastructure as a Service (IaaS) cloud services that considers both the service provider and customer in terms of profit and satisfaction, respectively. Each time an IaaS cloud service is requested, this policy determines whether the service is accepted or rejected by calculating the potential for realizing the two performance objectives. Moreover, it uses acceptance tolerance to identify the possibility for error with the chosen decision while compensating for both future fluctuations in customer demand and error possibilities based on past decisions. We conducted a numerical experiment to verify the performance of the proposed policy using several actual IaaS cloud service specifications and comparing it with other heuristics.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.4
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• pp.65-77
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• 2017

We Investigated the Two Additional Effects Regarding the Causal Relationship between the Perceived Risks of cloud Services on the Intention to use the Abandonment Option. First, we Empirically Tested the Moderation Effect of IS Maturity on the Causal Relationship between these Two Variables. Second, we also Investigated the Mediation Effect of Cloud Service Satisfaction on the same Causal Relationship. We could find the Moderation and Mediation Effect only on the Influence of Relational Risk (Which Occurs from the Power Abuse of Cloud Service Providers) on the Intention to sue the Abandonment Option. So, we have better Understanding when and how the Abandonment Option is Attractive in Reducing the Potential Influence of the Relational Risk in using the Cloud Services.

• The Journal of Information Systems
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• v.30 no.3
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• pp.65-91
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• 2021

Purpose In this study, we investigated the impact of perceived risk and switching costs on switching intention to cloud service based on PPM (Pull-Push-Mooring) model. Design/methodology/approach We focused on revealing the switching factors of the switching intention to the cloud services. The switching factors to the cloud services were defined as perceived risk consisting of performance risk, economic risk, and security risk, and switching costs consisting of financial and learning costs. On the PPM model, we defined the pull factors consisting of perceived usefulness and perceived ease of use, and the push factor as satisfaction of the legacy system, and the mooring factor as policy supports. Findings The results of this study as follows; (1) Among the perceived risk factors, performance risk has a negative effect on the ease of use of pull factors, and finally it was found to affect the switching intention to the cloud services. Therefore, cloud service providers need to improve trust in cloud services, service timeliness, and linkage to the legacy systems. And it was found that economic risk and security risk among the perceived risk factors did not affect the switching intention to the cloud services. (2) Of the perceived risk factors, financial cost and learning cost did not affect the satisfaction of the legacy system, which is a push factor. It indicates that the respondents are positively considering switching to cloud service in the future, despite the fact that the respondents are satisfied with the use of the legacy system and are aware of the switching cost to cloud service. (3) Policy support was found to improve the switching intention to cloud services by alleviating the financial and learning costs required for cloud service switching.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.512-518
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• 2013

A resource allocation algorithm has a high impact on user satisfaction as well as the ability to accommodate and process services in a distributed cloud computing. In other words, service rejections, which occur when datacenters have no enough resources, degrade the user satisfaction level. Therefore, in this paper, we propose a resource allocation algorithm considering the cloud domain's remaining resources to minimize the number of service rejections. The resource allocation rate based on Q-Learning increases when the remaining resources are sufficient to allocate the maximum allocation rate otherwise and avoids the service rejection. To demonstrate, We compare the proposed algorithm with two previous works and show that the proposed algorithm has the smaller number of the service rejections.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.2
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• pp.73-91
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• 2016

This study sheds light on the quality aspect of cloud computing services as next IT platform. Three tasks of the research are to extract the quality factors of cloud service from the user's viewpoint, empirically analyze the perceptual differences between the user group and the provider group by applying the IPA technique, and suggest some quality factors that need to be improved. Based on the previous researches and focus group evaluation, 13 quality factors have been established. Two field surveys have been performed respectively to collect the perceptual importance and satisfaction level of the users and the providers. It is shown that the quality satisfaction of the user group is lower than the quality perceived by the providers. And there exist significant differences between two groups in respect to quality importance level and IPA matrix. In conclusion, 6 quality factors that need to be improved are suggested such as service functionality, service availability, interoperability, scalability, confidentiality, and provider's responsiveness.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.35-51
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• 2012

Cloud computing is internet-based computing where computing resources are offered over the Internet as scalable and on-demand services. In particular, in case a number of various cloud services emerge in accordance with development of internet and mobile technology, to select and provide services with which service users satisfy is one of the important issues. Most of previous works show the limitation in the degree of user satisfaction because they are based on so called concept similarity in relation to user requirements or are lack of versatility of user preferences. This paper presents cloud service selection reasoning which can be applied to the general cloud service environments including a variety of computing resource services, not limited to web services. In relation to the service environments, there are two kinds of services: atomic service and composite service. An atomic service consists of service attributes which represent the characteristics of service such as functionality, performance, or specification. A composite service can be created by composition of atomic services and other composite services. Therefore, a composite service inherits attributes of component services. On the other hand, the main participants in providing with cloud services are service users, service suppliers, and service operators. Service suppliers can register services autonomously or in accordance with the strategic collaboration with service operators. Service users submit request queries including service name and requirements to the service management system. The service management system consists of a query processor for processing user queries, a registration manager for service registration, and a selection engine for service selection reasoning. In order to enhance the degree of user satisfaction, our reasoning stands on basis of the degree of conformance to user requirements of service attributes in terms of functionality, performance, and specification of service attributes, instead of concept similarity as in ontology-based reasoning. For this we introduce so called a service attribute graph (SAG) which is generated by considering the inclusion relationship among instances of a service attribute from several perspectives like functionality, performance, and specification. Hence, SAG is a directed graph which shows the inclusion relationships among attribute instances. Since the degree of conformance is very close to the inclusion relationship, we can say the acceptability of services depends on the closeness of inclusion relationship among corresponding attribute instances. That is, the high closeness implies the high acceptability because the degree of closeness reflects the degree of conformance among attributes instances. The degree of closeness is proportional to the path length between two vertex in SAG. The shorter path length means more close inclusion relationship than longer path length, which implies the higher degree of conformance. In addition to acceptability, in this paper, other user preferences such as priority for attributes and mandatary options are reflected for the variety of user requirements. Furthermore, to consider various types of attribute like character, number, and boolean also helps to support the variety of user requirements. Finally, according to service value to price cloud services are rated and recommended to users. One of the significances of this paper is the first try to present a graph-based selection reasoning unlike other works, while considering various user preferences in relation with service attributes.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.377-395
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• 2018

Aiming at the problem of service reliability in resource reservation in cloud computing environments, a model of dynamic cloud resource reservation based on trust is proposed. A domain-specific cloud management architecture is designed in which resources are divided into different management domains according to the types of service for easier management. A dynamic resource reservation mechanism (DRRM) is used to test users' reservation requests and reserve resources for users. According to user preference, several resources are chosen to be candidate resources by fuzzy cluster analysis. The fuzzy evaluation method and a two-way trust evaluation mechanism are adopted to improve the availability and credibility of the model. An analysis and simulation experiments show that this model can increase the flexibility of resource reservation and improve user satisfaction.

• Journal of Korea Technology Innovation Society
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• v.18 no.1
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• pp.176-203
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• 2015

While the importance of adopting cloud computing service has been emerged, comparatively little research has been conducted on examining factors of an individual user's intention to switch toward cloud computing service. Hereafter, this study presents and empirically tests users' intention to switch to cloud computing. Our model posits that the characteristics of cloud computing such as effectiveness, economics, accessability, switching cost, security concern, and satisfaction toward existing IT service to cloud service affect perceived value, which in turn, influences intention to switch. An experimental study using student subjects provided empirical validation for our proposed model. Survey data from 204 respondents was used to test the model using partial least square analysis. As the result of the analysis, five hypotheses out of seven hypotheses were supported. According to our results, among the characteristics of cloud computing, effectiveness, economics, switching cost, and security concern were found to have significant impact on users' intention to switch that mediated by perceived value. Based on our research findings, we hope that this research will stimulate researchers' interest in the emerging area of cloud computing adoption.