• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.12
• /
• pp.5841-5859
• /
• 2018

The widespread adoption of the social computing paradigm has ushered in the development of online social innovation community (OSIC) as a promising method for solving social problems. Previous studies have not explicitly considered the conceptual factors that facilitate these communities' users' innovative activities, so it is vital to conduct empirical studies to verify the effectiveness of these factors. In this paper, the primary goals are to construct a theoretical model of the social innovation and empirically verify the casual relationship between theoretical factors and societal innovativeness. A survey of 398 OSIC users was conducted to empirically validate the theoretical model. The causal relationships between network characteristics and social innovativeness were experimentally tested. The results of this study indicated that ambiguity, switching, and multiplexity are important factors that facilitate social innovativeness, which contradicts the prior assumptions about innovation performance.

• The Journal of Information Systems
• /
• v.24 no.1
• /
• pp.67-94
• /
• 2015

Recently, the popularity of Social Network Service (SNS) along with the spread of smart phone, personal computer and tablet PC helps personal network to construct new forms of services in cyberspace. As such, SNS plays a significant role in constructing diverse online networks and there is a growing interest on SNS at societal level. In this vein, the purpose of the research was to find the factors affecting the continuance intention to use social network services. The major findings are summarized as follows. First, "System Quality", "Contents Quality", "Personal Innovativeness", "Self-Efficiency", "Honor Benefit" has significant effects on "Relationship Quality". Yet, "Economic Benefit" is not statistically significant on "Relationship Quality". Second, "Relationship Quality" has a significant effect on "Continuous Usage Intention". Last, our research discovered the relationship between exogenous variables which would serve as valuable inputs in the development of strategic guideline and plan for SNS companies and related services.

• Journal of the Economic Geographical Society of Korea
• /
• v.6 no.1
• /
• pp.61-77
• /
• 2003

Finns are central economic agents that play an important role in systems of innovation as they take responsibility for generating and diffusing knowledge in both organizational and societal context. They must be considered as learning organizations which interact with other finns and institutions that share their environment. The systems of innovation literature accentuates institutional conditions that influence innovation in sectoral, regional or national levels. Meanwhile, it tends to ignore the complex dimensions of finn practices in relation to learning and innovation activities. In this context, this paper attempts to examine what finns do for sustaining innovation and how they learn to innovate. This is not just critical to know individual finns innovativeness which depends on interactions with environments within and outside the organizational boundary but also to evaluate the regional innovation system potential. In short, it is important to see that finns would attempt to take advantage of distributed knowledge within and across the boundaries of the finn without sticking to particular regional innovation systems. I argue that the more finns of a cluster attempt not only to combine localized sources of knowledge and external sources of knowledge but also to become a learning organization, the more increased regional innovation system potentials can be.

• Journal of Korean Library and Information Science Society
• /
• v.53 no.1
• /
• pp.231-263
• /
• 2022

The understanding and capability to utilize artificial intelligence (AI) incorporated technology has become a required basic skillset for the people living in today's information age, and various members of the university have also increasingly become aware of the need for AI education. Amidst such shifting societal demands, both domestic and international university libraries have recognized the users' need for educational content centered on AI, but a user-centered service that aims to provide personalized recommendations of digital AI educational content is yet to become available. It is critical while the demand for AI education amongst university students is progressively growing that university libraries acquire a clear understanding of user intention towards an AI educational content recommender system and the potential factors contributing to its success. This study intended to ascertain the factors affecting acceptance of such system, using the Extended Technology Acceptance Model with added variables - innovativeness, self-efficacy, social influence, system quality and task-technology fit - in addition to perceived usefulness, perceived ease of use, and intention to use. Quantitative research was conducted via online research surveys for university students, and quantitative research was conducted through written interviews of university librarians. Results show that all groups, regardless of gender, year, or major, have the intention to use the AI-related Educational Content Recommendation System, with the task suitability factor being the most dominant variant to affect use intention. University librarians have also expressed agreement about the necessity of the recommendation system, and presented budget and content quality issues as realistic restrictions of the aforementioned system.