• Journal of the Korea Institute of Building Construction
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• v.21 no.6
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• pp.677-687
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• 2021

If a fire breaks out in a building, occupants can evacuate more rapidly if they are able to identify the location of the fire, the exits, and themselves. This study derives the requirements of system development, such as distance non-limitation, a non-additional device, a non-centralized server system, and low power for an emergency, to identify information about the fire and the location of evacuees. The objective is to receive and transmit information and reduce the time and effort of the database for location tracking. Accordingly, this study develops a server-independent system that collects information related to a building fire and an evacuee's location and provides information to the evacuee on their mobile device. The system is composed of a transmitting unit to disseminate fire location information and a mobile device application to determine the locations of the fire and the evacuee. The developed system can contribute to reducing the damage to humans because evacuees can identify the location of the fire, exits, and themselves regardless of the impaired server system by fire, the interruption of power source, and the evacuee's location. Furthermore, this study proposes a theoretical basis for reducing the effort required for database construction of the k-nearest neighbor fingerprint.

• The Korean Journal of Franchise Management
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• v.13 no.2
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• pp.17-31
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• 2022

Purpose: With the development of the Internet, consumers can quickly access the electronic word-of-mouth. Consumers seek to reduce uncertainty by referring to the opinions of other consumers about products and services when making purchase decisions. In the food service industry, evaluating a restaurant before an actual visitation is difficult. Therefore, electronic word-of-mouth is important to interact with the customer in restaurants. as it can be used as an exchange of information in which consumers participate and interact with other customers. This study was conducted to verify how online word-of-mouth characteristics (Consensus, Vividness, Neutrality) on attitudes and visit intention from the perspective of social exchange theory. And it was performed to verify the structural relationship between short-term visit intention, mid-term visit and long-term visit intention. Research design, data, and methodology: A survey was conducted on customers who have visited restaurants. Of a total of 312 responses, 306 responses were used, excluding insincere responses and missing values for factors analysis. SPSS 25.0 and AMOS 25.0 were used for statistical analysis, and hypothesis testing was conducted after verifying the validity and reliability of the questionnaire items. Result: The result of the analysis showed that, consensus and neutrality have a positive effect on attitude but not much on vividness. In addition, consensus, vividness, and neutrality have no effect on the short-term visit intention. Finally, the short-term visit intention has a positive effect on mid-term visit intention, and mid-term visit intention has a positive effect on long-term visit intention. Conclusions: Based on the results, this study suggested that it is necessary to have practical implications for marketing and monitoring restaurant reviews in consideration of the characteristics of electronic word-of-mouth. When managing electronic-word-of-mouth, it is necessary to manage the consensus and neutrality is essential to provide sufficient information about the restaurant. The focus should not only be on vividness, such as photos and videos. In addition, restaurants should also provide a good experience for first-time visitors as the short-term visit intention positively affects mid-term and long-term visit intention.

• The Korean Journal of Franchise Management
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• v.13 no.2
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• pp.53-66
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• 2022

Purpose: How to build the attitude on brand is very important, because it affects the positive word of mouth and revisit intention. Brand attachment, brand name, and image congruence play important role on consumer behavior in terms of reinforcing consumers' perception of food service companies and differentiating them from competing brands. Following the planned behavior theory, this paper examines the effect of linking brand attitude to word-of-mouth and revisit intentions in the restaurant sector. Research design, data, and methodology: This paper examines the structural relationship among brand attachment, brand name, image congruence, brand attitude, WOM, and revisit intention. In order to test the purposes of this study, research model and hypotheses were developed. The questionnaire items were modified and used according to the content of this study based on previous studies. All constructs were measured by multiple items tested and developed in the previous research. The study is based on the quantitative method and considered 519 questionnaires fulfilled by customers of restaurants. The data were explored employing the partial least square-structural equation modelling (PLS-SEM). Frequency analysis was conducted to identify the general characteristics of the survey subjects. To measure the reliability and validity of the measurement tools, confirmatory factor analysis was conducted. Structural model analysis was conducted to verify the research model. Result: The findings demonstrate that brand attachment and brand name had positive effects on attitude while image congruence did not have. Also, attitude had positive effect on WOM and revisit intention. Conclusions: This study expands the literature about WOM and revisit intentions. This study expands prior research in a similar field to which the theory of planned behavior (TPB) is applied, and reveals that brand attachment, brand name, and brand image congruence play an important role in developing brand attitude that affect revisit intention and WOM. And provide guidelines on how to enhance competitiveness in the restaurant sector based on understanding of linking brand attitude to customer loyalty and repeat business. By putting into practice these suggestions in the restaurant industry, brands can easily build up their attitude and boost a positive WOM and the intention to revisit.

• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• Knowledge Management Research
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• v.24 no.1
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• pp.73-97
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• 2023

Recently, the MyData market has been growing as the importance of data and issues related to personal information protection have drawn much attention together. MyData refers to the concept of guaranteeing an individual's right to personal information and providing and utilizing one's data according to individual consent. MyData service providers can combine and analyze customer information to provide personalized services. In the early days, the MyData business was activated mainly by private companies and the financial industry, but recently, public institutions are also actively taking advantage of MyData. Meanwhile, the importance of an individual's intention to provide MyData for the success of MyData businesses continues to increase, but research related to this is lacking. Moreover, existing studies have been mainly conducted on individual benefits of MyData; there are not enough studies in which both public benefit and perceived risk factors are considered at the same time. In this regard, this study intends to derive factors affecting the intention to provide MyData based on the privacy calculus model, examine their influencing mechanism, and further verify the moderating effects of individual capabilities and institutional type. This study can find academic significance in that it expanded and demonstrated the privacy calculus model in the context of MyData providing intention. In addition, the results of this study are expected to offer practical guidelines for developing and managing new services in MyData businesses.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.27-33
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• 2023

Countries around the world are calling for stronger law enforcement to combat the production and distribution of child sexual exploitation images, such as child grooming. Given the scale and importance of this social problem, it requires extensive cooperation between law enforcement, government, industry, and government organizations. In the wake of the Nth Room Case, there have been some amendments to the Enforcement Decree of the Telecommunications Business Act regarding additional telecommunications services provided by precautionary operators in Korea. While Naver and others in Korea use Electronics and Telecommunications Research Institute's own technology to filter illegal images, Microsoft uses its own PhotoDNA technology. Microsoft's PhotoDNA is so good at comparing and identifying illegal images that major global operators such as Twitter are using it to detect and filter images. In order to meet the Korean government's testing standards, Microsoft has conducted more than 16 performance tests on "PhotoDNA for Video 2.0A," which is being applied to the Bing service, in cooperation with the Korea Communications Commission and Telecommunications Technology Association. In this paper, we analyze the cases that did not pass the standards and derive improvement measures related to adding logos. In addition, we propose to use three video datasets for the performance test of filtering against illegal videos.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.169-189
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• 2023

The study aims to synthesize the discussion of the innovation district and suggest an alternative to the governance system of the innovation district. Cluster policies that focus on industrial specialization, networking, value chains, and industrial ecosystems have shown some problems and limits in advanced industrial economies. The innovation district, suitable for the era of urban innovation, convergence of industry, housing, leisure, and related variety, emphasizes cooperation through the convergence of various innovations, workshops and industries, and communities. It is important to build a quintuple helix based on cooperative governance through public-private partnerships, integrate the physical and cultural atmosphere, and service industries that strengthen the place prestige. Beyond the industrial aspect, innovation districts can facilitate changes in urban amenities and lifestyles and creative atmosphere, such as diversity, lifestyle, charms, and openness, and promote social vitality and economic interactions. The governance of innovative districts can promote inter-organizational exchanges, and combinations. When knowledge is created through exchanges between companies, it also affects changes in the governance system, evolving from a rigid and centralized system to an open, dynamic, and organic system. Through the innovation policy, the existing Central Business Districts (CBD) can be able to be transformed into a Central Lifestyle Districts (CLD).

• Information Systems Review
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• v.22 no.4
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• pp.185-203
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• 2020

With the advent of 4th industrial revolution, the manufacturing industry is converging with ICT and changing into the era of smart manufacturing. In the smart factory, all machines and facilities are connected based on ICT, and thus security should be further strengthened as it is exposed to complex security threats that were not previously recognized. To reduce the risk of security incidents and successfully implement smart factories, it is necessary to identify key security factors to be applied, taking into account the characteristics of the industrial environment of smart factories utilizing ICT. In this study, we propose a 'hierarchical classification model of security factors in smart factory' that includes terminal, network, platform/service categories and analyze the importance of security factors to be applied when developing smart factories. We conducted an assessment of importance of security factors to the groups of smart factories and security experts. In this study, the relative importance of security factors of smart factory was derived by using AHP technique, and the priority among the security factors is presented. Based on the results of this research, it contributes to building the smart factory more securely and establishing information security required in the era of smart manufacturing.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.