• The Korean Journal of Franchise Management
• /
• v.9 no.1
• /
• pp.27-39
• /
• 2018

Purpose - Recently, the mobile application field has been receiving astronomical attention from the past few years due to the growing number of mobile app downloads and withal due to the revenues being engendered. Especially delivery apps by mobile service market is experiencing rapid growth and competition is intensifying. Therefore, delivery apps' choice attributes has become important as a strategy for survival of franchise firms. Based on previous studies, this research proposed the theoretical framework about the structural relationships among customer satisfaction, trust and revisit intention on delivery apps' choice attributes. Research design, data, and methodology - This study examines the structural relationship between choice attributes of using the delivery app, satisfaction, trust, and revisit intention. More specifically, this study has been examined from the perspective of Generation Y who is enjoying electronic commerce and shopping with mobile phone. In this model, choice attributes of delivery app consists of three sub-dimensions such as service quality, system quality, interaction quality. So as to test the purposes of this study, research model and hypotheses were developed. After excluding 24 invalid respondent questionnaires, 201 valid questionnaires were coded and analyzed using frequency, confirmatory factor analysis, correlations analysis, and structural equation modeling with SPSS 21 and SmartPLS 3.0. Result - The results of the study are as follows. First, service quality and interaction quality had positive effects on satisfaction, and interaction quality had positive effects on trust, but system quality did not have a significant effect on both satisfaction and trust. Second, satisfaction had positive effects on both trust and revisit intention. Third, trust had positive effects on revisit intention. Conclusions - The implications of this study are following as: From the theoretical perspective, this study confirms the effect of delivery apps' choice attributes on satisfaction, trust, and revisit intention. In addition, it is significant that we examined the influence of choice attributes of delivery apps on their attitudes and behaviors of Generation Y familiar with mobile environment. Through this study, we hypothesized that the attributes of service quality and interaction quality of delivery apps have a significant effect on customer satisfaction, and this can be expected to provide meaningful implications for the development of franchise restaurant industry. To encourage continuous repurchase through customer satisfaction, franchise companies need to establish various strategic alliances with delivery app companies and new growth engines by providing diverse and high-quality services to customers in the smart age.

• The Journal of Bigdata
• /
• v.6 no.2
• /
• pp.151-159
• /
• 2021

Construction of a blockchain network needs a cumbersome and time consuming activity. To overcome these limitations, global IT companies such as Microsoft are providing cloud-based blockchain services. In this paper, we propose a blockchain-based construction and management tool that enables blockchain developers, blockchain operators, and enterprises to deploy blockchain more comfortably in their infrastructure. This tool is implemented using Hyperledger Fabric, one of the famous private blockchain platforms, and Ansible, an open-source IT automation engine that supports network-wide deployment. Instead of complex and repetitive text commands, the tool provides a user-friendly web dashboard interface that allows users to seamlessly set up, deploy and interact with a blockchain network. With this proposed solution, blockchain developers, operators, and blockchain researchers can more easily build blockchain infrastructure, saving time and cost. To verify the usefulness and convenience of the proposed tool, a blockchain network that conducts electronic voting was built and tested. The construction of a blockchain network, which consists of writing more than 10 setting files and executing commands over hundreds of lines, can be replaced with simple input and click operations in the graphical user interface, saving user convenience and time. The proposed blockchain tool will be used to build trust data infrastructure in various fields such as food safety supply chain construction in the future.

• Journal of Service Research and Studies
• /
• v.12 no.1
• /
• pp.36-48
• /
• 2022

As the use of smartphones has rapidly increased due to the development of digital technology, the expansion of smartphones, and the COVID-19 incident, dependence on smartphones and the Internet is emerging as a serious social problem. As one of the solutions to the smartphone overdependence problem, the government and companies are releasing smartphone overdependence prevention applications. However, research on the effectiveness of smartphone overdependence prevention applications is insufficient. Therefore, this study selects 25 applications serviced in Korea as analysis targets and evaluates smartphone overdependence prevention applications in terms of function and service using the FGI survey method to identify problems and propose improvements. In the function evaluation, the functions of blocking illegal/harmful apps/websites, limiting smartphone usage time, and monitoring smartphone usage status are provided in most applications, so satisfaction scores are also highly evaluated. However, functions such as location check, smombie prevention, and body camphishing prevention served by some applications are evaluated low due to poor performance and poor accuracy. Classified by service provider, government-providing applications need to accurately perform functions and improve convenience of use. Mobile-Carrier-providing applications need to improve connectivity with other carriers and compatibility with other smart devices like smartphone, tablet, etc. Other private enterprise-providing applications need to open AS channels such as customer service centre and chatbot to improve service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.505-508
• /
• 2022

Artificial intelligence itself has the value of advancing technology, and it is used in various industrial fields to enhance the added value of products and services produced in various industries. Therefore, regulations and policies related to artificial intelligence should be considered from a broader perspective. However, researchers have different understandings, and there is no agreement on how to regulate artificial intelligence. Therefore, we will examine the direction of government regulation on artificial intelligence technology in an exploratory manner. First, accountability, transparency, stability, and fairness are derived as the goals of artificial intelligence regulation, and the system itself, development process, and utilization process are set as the scope of regulation, and users and developers are subject to regulation. The academic significance of this study can be seen as analyzing the current level of artificial intelligence technology and laying the foundation for consistent discussions on artificial intelligence regulations in the future. Considering the life cycle from AI development to application, what is important is the balance of promotion policies to promote the artificial intelligence industry and regulatory policies to respond to the resulting risks. The goal of law related to artificial intelligence is to establish a system in which artificial intelligence can be accommodated in a positive direction to all participants, including developers, companies, and users.

• Asia Marketing Journal
• /
• v.16 no.1
• /
• pp.1-12
• /
• 2014

The goal-gradient hypothesis states that the tendency to approach a goal increases with the increasing proximity of the goal (Hull 1932). It was initially supported with an evidence of animal experiments and since then, several papers have investigated the goal-gradient hypothesis in humans. Although there are some evidences related to the goal-gradient hypothesis in human behaviors, none of previous studies can properly explain its underlying mechanism, and what's more, they were not able to suggest useful managerial applications in human behaviors. From these perspectives, this work points out that there are some theoretical weaknesses to apply the goal-gradient hypothesis into the complicated human decision-making behaviors and proposes an alternative theoretical mechanismthat underlies the goal-gradient hypothesis in human. Finally, it offers insights into managerial implications of the goal-gradient hypothesis in the marketing field. This study focuses on the changes in motivations for achieving goals, in terms of how approaches to goals vary according to temporal distance from those goals. Specifically, the temporal construal theory (Liberman and Trope 1998) is considered as the underlying mechanism of the goal-gradient in that the temporal construal theory argues how the temporal distance from a goal makes people change their associated values regarding to that goal. According to the temporal construal theory, the value of distant future outcomes (near future outcomes) is construed on the basis of abstract and central features (concrete and peripheral features), and it argues that distant future situations are construed on a higher level than near future situations. This means that the value associated with the high-level construal is enhanced over delay, whereas the value associated with the low-level construal is discounted over delay. Our propositions suggest that the goal-gradient behavior in human can be motivated by the different aspects or characteristics of the goal as time changes based on the temporal construal theory. Thus, the following propositions are proposed. P 1-1: If the goal is far away, consumers put more value on the central features that are more associated with the desirability of the goal. P 1-2: If the goal is far away, consumers put more effort into accomplishing the goal that has more central features, regardless of its peripheral features. P 2-1: If a goal is near, consumers put more value on the peripheral features that are more associated with the feasibility of the goal. P 2-2: If a goal is near, consumers put more effort into accomplishing the goal that has more peripheral features, regardless of its central features. We hope to provide sufficient managerial implications for the companies as our research aims to show how consumers react differently as they progress toward the goal. Proposed propositions may provide guidance for companies developing a loyalty program, enabling them to understand what kinds of benefits or services they should provide or emphasize to consumers in loyalty programs on the basis of the time-dependent changes in outcome values (such as gifts, reward coupons). The effects of temporal distance from a goal should inform companies' marketing activities and help themto determine where emphasis should be placed in designing the benefits of their loyalty program.

• Korean Journal of Culture and Social Issue
• /
• v.24 no.3
• /
• pp.473-489
• /
• 2018

Our society has an obligation and responsibility to respect and protect the character of the child. Recently, however, Korean society has been suffering from child abuse and abuse that is pouring out every day. In order to protect these children, the child protection system and the judicial system should be fundamentally child-friendly. The CASA(Court Appointed Special Advocates) volunteer program, which is being held in the United States with such a concern, is a continuing program of court attendance and emotional support services for abused children throughout the United States. In Korea, however, there are many similar programs such as mentoring projects, dream co-supporters project similar to the CASA program in various organizations of the region and the enactment of the Act on the Punishment of Child Abuse increases the involvement of the public system in child abuse. There is also an increased awareness of children's rights and strengthened government intervention through active monitoring to prevent recurrence of child abuse. These changes in the Korean society should be actively reviewed by the US CASA program and settled as a national project in the Korean society so that the system of protecting the safety and rights of the victims of child abuse will be established. It is anticipated to be a way to prevent social problems from occurring in advance.

• Journal of Internet Computing and Services
• /
• v.24 no.6
• /
• pp.119-125
• /
• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• Journal of Internet Computing and Services
• /
• v.24 no.6
• /
• pp.171-180
• /
• 2023

Hydrogen energy technology is gaining importance in the era of the Fourth Industrial Revolution, offering military advantages when applied to military vehicles due to its characteristics such as reduced greenhouse gas emissions, noise, and low vibration. Korea's military has initiated the Army Tiger 4.0 plan, focusing on hydrogen application, downsizing, and AI-based smart features. The Ministry of National Defense plans to collaborate with the Ministry of Environment to expand hydrogen charging stations nationwide, anticipating increased deployment of military hydrogen vehicles. However, considering the Jet Fire and VCE(Vapor Cloud Explosion) nature of hydrogen, ensuring safety during installation is crucial. Current military guidelines specify a minimum safety distance of 2m from adjacent buildings for charging stations. Scientific methods have been employed to quantitatively assess the accident damage range of hydrogen, proposing a minimum safety distance beyond the affected area.

• Information Systems Review
• /
• v.25 no.4
• /
• pp.89-112
• /
• 2023

In March 2020, as it was declared a COVID-19 pandemic, various quarantine measures were taken. Accordingly, many changes have occurred in the tourism and hospitality industries. In particular, quarantine guidelines, such as the introduction of non-face-to-face services and social distancing, were implemented in the restaurant industry. For decades, research on restaurant attributes has emphasized the importance of three attributes: atmosphere, service quality, and food quality. Nevertheless, to the best of our knowledge, research on restaurant attributes considering the COVID-19 situation is insufficient. To respond to this call, this study attempted an exploratory approach to classify new restaurant attributes based on understanding environmental changes. This study considered 31,115 online reviews registered in Naverplace as an analysis unit, with 475 general restaurants located in Euljiro, Seoul. Further, we attempted to classify restaurant attributes by clustering words within online reviews through TF-IDF and LDA topic modeling techniques. As a result of the analysis, the factors of "prevention of infectious diseases" were derived as new attributes of restaurants in the context of COVID-19 situations, along with the atmosphere, service quality, and food quality. This study is of academic significance by expanding the literature of existing restaurant attributes in that it categorized the three attributes presented by existing restaurant attributes and further presented new attributes. Moreover, the analysis results have led to the formulation of practical recommendations, considering both the operational aspects of restaurants and policy implications.

• Journal of Internet Computing and Services
• /
• v.24 no.5
• /
• pp.17-27
• /
• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.