스마트폰의 획기적인 사용량 증가에 따라 모바일 앱은 에너지 절감과 같은 공공 영역에서의 인간 행동변화를 가져오는 유력한 방법이 되었다. 이를 위해 앱과 행동 변화 간의 관계성을 인식하는 것은 공공 기관으로 하여금 보다 더 효과적인 공공 커뮤니케이션 전략을 수립하는데 유용한 활동이다. 본 연구는 디자인 과학 접근법을 기반으로 하여 개인화, 접근성, 표현의 풍부성과 같은 공공 서비스 중심의 모바일 앱의 디자인적 요인들이 사용자의 인지적, 감성적 태도에 미치는 영향을 조사하는 것이다. 분석 결과 대부분의 디자인적 요인들이 사용자의 인지적 감성적 태도에 유의한 영향을 주는 것으로 밝혀졌다. 또한, 인지적 태도는 사용자의 행동 변화와 감성적 태도에 영향을 미치며, 한편 감성적 태도는 공공 모바일 앱의 평균 사용시간과 에너지 절감이라고 하는 행동 변화에 긍정적인 작용을 하는 것으로 나타났다.

A novel activity recognition method is proposed based on acoustic information acquired from microphones in an unobtrusive and privacy-preserving manner. Behavior detection mechanisms may be useful in context-aware domains in everyday life, but they may be inaccurate, and privacy violation is a concern. For example, vision-based behavior detection using cameras is difficult to apply in a private space such as a home, and inaccuracies in identifying user behaviors reduce acceptance of the technology. In addition, activity recognition using wearable sensors is very uncomfortable and costly to apply for commercial purposes. In this study, an acoustic information-based behavior detection algorithm is proposed for use in private spaces. This system classifies human activities using acoustic information. It combines strategies of elimination and similarity and establishes new rules. The performance of the proposed algorithm was compared with that of commonly used classification algorithms such as case-based reasoning, k-nearest neighbors, support vector machine, and multiple regression.

Domestic and international energy and eco-friendly companies take advantage of social media for image enhancement and product promotion. However, there were no in-depth empirical analysis to verify specific effectiveness of social media use in these sectors. The purpose of this study is to reveal the key factors that are considered to use social media effectively for energy and eco-friendly companies. For this purpose, we regarded the effectiveness of social media as Post Awareness and Word of Mouth. Characteristics of social media as a medium were measured separately, media richness and media genre, as independent variables of social media effectiveness. We investigated 413 posts in Facebook brand page of energy and eco-friendly companies and conducted a content analysis. As a result, post awareness of users was greater when post has richer media such as video. For media genre, word of mouth appeared to be greater when the posts provide information.

Context-aware applications, which consist of a sensor system, a reasoning system and service artifacts such as mobile devices, kiosks and robots, require data from the sensors to be queried on a continuous basis. The smaller the sensing interval and the greater the amount of service time, the more accurate the service, but the more energy is consumed. Thus, use of context-aware applications always involves a trade-off. In this paper, we propose an automatic method of optimizing the level of personalization involving the sensing cycle and service time of a personalized application. The method proposes a quadratic form of total cost curve which demonstrated that the minimum identified value is always the global optimum. This eliminates the necessity of an exhaustive search for the minimum value for all levels of personalization. (C) 2014 Elsevier Ltd. All rights reserved.

IT vendors routinely use social media such as YouTube not only to disseminate their IT product information, but also to acquire customer input efficiently as part of their market research strategies. Customer responses that appear in social media, however, are typically unstructured; thus, a fairly large data set is needed for meaningful analysis. Although identifying customers' value structures and attitudes may be useful for developing targeted or niche markets, the unstructured and volume-heavy nature of customer data prohibits efficient and economical extraction of such information. Automatic extraction of customer information would be valuable in determining value structure and strength. This paper proposes an intelligent method of estimating causality between user profiles, value structures, and attitudes based on the replies and published content managed by open social network systems such as YouTube. To show the feasibility of the idea proposed in this paper, information richness and agility are used as underlying concepts to create performance measures based on media/information richness theory. The resulting deep sentiment analysis proves to be superior to legacy sentiment analysis tools for estimation of causality among the focal parameters. (C) 2013 Elsevier Ltd. All rights reserved.

Online privacy has consistently been a major concern for customers that has grown commensurately with the growth of e-services. Service providers have responded by making their privacy policies clearer for customers; however, most providers use legacy systems that are unable to actually change and adapt to user's concerns, which can lead to fewer customers using the system. Hence, the purpose of this paper is to propose a context-aware privacy policy negotiation service. To do so, we adopt a Galois lattice theory to generate policy concepts embedded in e-services. Based on the Galois lattice, we develop a process for generating privacy policy rules. To show the feasibility of the ideas proposed in this paper, we perform a simulation test with two different online auction sites as an illustrative case in terms of two metrics: the number of rules generated and success throughput. Desirable features in applying the Galois lattice approach to context-aware privacy policy negotiation service are discussed.

In a context-aware environment, privacy concerns of a user should be certainly considered in order to raise service receptiveness. The requirement for providing suitable privacy preserving service after forecast of privacy concern is increasing. An especially important factor is to provide a privacy protection level which is suitable to the privacy concern level of the user, rather than increasing the privacy protection level unconditionally. For this reason, it is necessary for each service provider to obtain the current privacy concern of the user so as to optimize the privacy preserving level. Existing measurements of privacy concern are carried out through a sample survey form that is composed of uncertain pre-forecast and untimely post-analysis. So, accurately measuring the privacy concern in a personalized manner is limited. This study is aimed at recognizing user regarding privacy concern, and then proposing measures for the service provider to supply a service which has a proper level of privacy preservation, based on the recognized results. For this purpose, this study developed a method of forecasting the privacy concern based on an index model of privacy concern and also an approach method of triggering the privacy preserving service.

As sustainability has grown into a key global issue, more and more information technology (IT) products have adopted these concepts to attract consumers. However, these products potentially require consumers’ physical or economic sacrifice at least for a short period of time. Therefore, the reason of consumers’ adoption of sustainable IT products cannot be fully explained by the two traditional values: hedonic and utility values. However, expectancy-value theory, which has been used to explain the relationship between value and behavior, still takes hedonic value and utility value into consideration. The purpose of this study is to suggest an amended expectancy-value theory to better explain the adoption of IT products that consider sustainability. For this purpose, two social values-the normative value based on the Schwartz’s model of moral norm and the eudemonic value of the Stoic philosophy-were added to the individual values to examine which value particularly influences the adoption of sustainable IT products. In addition, the moderating effect of perceived sustainability between four values and adoption of sustainable IT products was verified.

To date, plenty of theories, such as the expectation–confirmation model (ECM), have been proposed to explain why and how consumers are motivated to continue to use web-based services. In particular, various affective factors have been proposed to explain user satisfaction and continued use of web-based services recently in the IS community. In IS continuance research, several affective factors, such as perceived playfulness, perceived enjoyment and pleasure, have been examined. Affective factors discussed in the existing continuance intention-related studies are mostly short-term emotional factors like this. However, if a user’s continued usage of a web-based service can be interpreted as a long-term relationship between a user and the service, then the factors such as familiarity and intimacy which are the emotions created accumulatively over time based on an established relationship with the user can be helpful for better explaining the user’s continuance intention. Also, if relationships between consumers and web-based services have been built up due to repetitive usage, then we can assume that both affective and cognitive factors may explain consumers’ continuance intention. Hence, the purpose of this paper is to propose an extended ECM. We focus on two new constructs, familiarity and intimacy, as persistent affective factors. To investigate how cognitive and affective factors are interrelated in continuance intention, we conducted surveys focusing on users’ continued intention to use web-based services. The results indicate that continuance intention is affected conjointly by cognitive factors, such as perceived usefulness, and affective factors, such as familiarity and intimacy. However, the effects of affective factors such as intimacy were larger than those of cognitive factors such as perceived usefulness. In addition, the results indicate that intimacy, a purer affective concept than familiarity, affects users’ continuance intention more than familiarity.

In our everyday life, we have lots of devices which perform specific functions. However, most of the devices have not used long-term according to the change of user requirements or preferences which is a serious problem in terms of sustainability. Recently, eco-effective or Cradle to Cradle strategy has been regarded as promising in enabling sustainable product development. However, the number of attempts to solve the devices’ sustainability concerns has been very few. Therefore, this paper newly suggests the metamorphosing intelligence based on the metamorphosis process in entomology, which is a representative autonomic growing system in the ecosystem. Then self-growing user interface is proposed. The metamorphosing intelligence enables the devices used more than once by automatically redesign the interface mechanism in response to the recognition of the environmental change or the change generated by the user.

Given the extensive role of IS in everyday life and the increasing presence of women in IS users, understanding gender differences in individual technology continuance usage decisions is an important issue. Nevertheless, much of the large body of research on gender differences has just examined mean differences between women and men in terms of abilities, usage habit, and traits. Even though lots of psychology studies have shown that women, more than men, were influenced by affective factors, gender-affection-continuance use linkage has not been examined in the context of on-line shopping services. Therefore, the primary purpose of this paper is to seek to examine gender differences in terms of influence of affective factor in the context of IS continuance use. Meanwhile, IS continuance has been an important subject of study in the IT research area. To date, to explain why and how users are motivated to continue to use on-line shopping services, lots of theory-based research such as expectation-confirmation model (ECM) has been proposed. In particular, various affective factors have been proposed to explain continuance use of on-line shopping services recently. Affective factors have been regarded as essential factors for increasing relational strength and satisfaction. Several affective factors have been studied by prior IS adoption and continuance studies. Among them are enjoyment and anxiety. In IS continuance research, positive affect has been commonly and narrowly conceptualized and measured as the enjoyment which a person derives from using computers. Hence, in this study, we introduced intimacy factor, which was conceptually related to the quality of interactions and relationships in previous research. It also has been regarded as essential factors for strengthening human relationships. As a result, we have observed gender effect while examining intimacy-continuance bond. As expected based on the previous literatures, women seem to be more sensitive in affective factors. The contribution point here is that we find evidence in the context of on-line shopping services.

Context-aware computing, as a core of smart space development, has been widely regarded as useful in realizing individual service provision. However, most of context-aware services so fat are in its early stage to be dispatched for actual usage in the real world, caused mainly by user's privacy concerns. Moreover, since legacy context-aware services have focused on acquiring in an automatic manner the extra-personal context such as location, weather and objects near by, the services are very limited in terms of quality and variety if the service should identify intra-personal context such as attitudes and privacy concern, which are in fact very useful to select the relevant and timely services to a user. Hence, the purpose of this paper is to propose a novel methodology to infer the user's privacy concern as intra-personal context in an intelligent manner. The proposed methodology includes a variety of stimuli from outside the person and then performs model-based reasoning with social theory models from model base to predict the user's level of privacy concern semi-automatically. To show the feasibility of the proposed methodology, a survey has been performed to examine the performance of the proposed methodology.

More than a decade has been passed since the birth of web-based services as novel network-based services. To explain why and how consumers are motivated to accept the web-based services, lots of technology acceptance theories such as technology acceptance model (TAM) and expectation-confirmation model (ECM) have been successfully proposed. However, the models do not fully explain why and how the consumers continue to use a specific web-based service. Meanwhile, affective factors such as intimacy have been regarded as essential factors for strengthening human relationships in consumer behavior. If a sort of relationships between consumers and web-based services has been built up due to repetitive usage, then we could assume that affective, as well as cognitive, factors may contribute to explain the consumers' continuous use. In light of this assumption, legacy ECM and human relationship-related theoretical models which include affective factors may be integrated for better explanation. Hence, the purpose of this paper is to propose an extended ECM which contains affective factors, as well as cognitive factors, related to maintaining relationship between consumers and service providers to explain why the consumers continue to use a specific information system. In this study, we mainly focus on two new constructs, familiarity and intimacy, and seek to examine how cognitive and affective factors are inter-related toward continuance intention. Moderating effects of emotion to alternatives, familiarity with alternative and intimacy with alternative, to IS continuance intention are also considered.

A number of context-aware systems have been developed over the last decade. However, according to the recent studies, concerns of overflowing context information have been increased. Better understanding and classification of information privacy concepts under context-aware computing environments are highly needed. Hence, the purpose of this paper is to develop the measurement criteria for information privacy in context-aware computing environments and then prioritize the criteria. Overall technology characteristics are considered to establish a mutually exclusive set of criteria which measure information privacy in context-aware computing environments in a unique and complete manner. To do so, Delphi method was adopted to obtain the reliable opinion from the experts in information privacy, as well as context-aware systems. Based on this analysis, the panels emphasize context-awareness, tracking, recording, sensors, infrastructure, and hence, they are added to our evaluation model as main criteria.

Online privacy has consistently been a major concern for customers, growing commensurately with the growth of online commerce. Individuals often have serious concerns that their online activities are being monitored, which can prevent them from using online services. With this concern in view, service providers have started making their privacy policies more clear to customers. However, legacy systems often lack flexibility and the inability to adapt to user's interests, which are often the main reasons for inappropriate agreement. Negotiation between the service provider and user can be a possible solution to reach an agreement which seems appealing and profitable to both parties. In this paper we have developed a negotiation mechanism using the concept lattice approach. Using concept lattices in a privacy policy makes it flexible and allows both the parties to sacrifice a few interests for mutual benefits and appropriate agreement.

Recommendation systems are widely used to help deal with the problem of information overload. Over the past decades, a variety of recommendation systems have been developed as the amount of information in the world increases far more quickly than our ability to process it. This paper aims to analyze existing developed recommendation systems, provide systemic review, and present some basic issues on improvement action. Through this, we also suggest useful implications for better recommendation systems and give some ideas to recommendation system developers to improve their system. Especially, this study focuses on researches on recommendation system. In our research, we analyze the studies along with four different keys dimensions：their domain, objective, underlying model, and evaluation method of recommendation systems and portray the results as statistics or statistical graphics or table form.

Ubiquitous Smart Space(USS) like u-City has been expected to create a high added value. However, developing USS has a high risk because it should use future technologies and development methodologies that have been never tried in the past. Hence, it has to be considered thoroughly in the very first stage of development. Moreover, USS usually uses several ubiquitous computing technologies combinationally because of the nature of USS. Despite of this, existing technology selection methodologies or technology evaluation methodologies only focus on a single technology. This leads us to develop a methodology of optimal technology combination for developing a specific USS. The purpose of this paper is to propose the methodology and to apply it to develop a real USS. We use portfolio theory and constraint satisfaction problem to determine an optimal technology combination. We also apply our methodology to the national ubiquitous computing project which carries out at present to validate it.

Development and realization of ubiquitous services in physical space is now in progress to develop ubiquitous smart space (USS). As the development methodologies for USS, scenario development is performed before requirement analysis and design, or vice versa. However, even though lots of redundant elements could be found between scenarios and requirement analysis results, a sort of structural approaches to join them together has been still very rare. Hence, the aim of this paper is to propose a system which generates ubiquitous service senarios and system analysis specifications according to a novel integration methodology. To do so, scenario and requirement analysis are integrated in a structured manner.

Ubiquitous smart space (USS) has been regarded as a promising extension of ubiquitous services, and it is currently the subject of world-wide development. In one USS development methodology, scenario development is performed before system analysis and design. However, even though many redundant elements can be found between scenarios and system analysis results, developers have not been taking any structural approaches to join them together for more consistency and eventually higher productivity. Hence, the aim of this paper is to propose a methodology to increase the consistency in the early steps of USS development. To do so, scenario and requirement analysis are integrated in a structured manner.