• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.217-242
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• 2022

With the launch of Artificial Intelligence(AI)-based intelligent products on the market, innovative changes are taking place not only in business but also in consumers' daily lives. Intelligent products have the potential to realize technology differentiation and increase market competitiveness through advanced functions of artificial intelligence. However, there is no new product development methodology that can sufficiently reflect the characteristics of artificial intelligence for the purpose of developing intelligent products with high market acceptance. This study proposes a KANO-QFD integrated model as a methodology for intelligent product development. As a specific example of the empirical analysis, the types of consumer requirements for hair loss prediction and treatment device were classified, and the relative importance and priority of engineering characteristics were derived to suggest the direction of intelligent medical product development. As a result of a survey of 130 consumers, accurate prediction of future hair loss progress, future hair loss and improved future after treatment realized and viewed on a smartphone, sophisticated design, and treatment using laser and LED combined light energy were realized as attractive quality factors among the KANO categories. As a result of the analysis based on House of Quality of QFD, learning data for hair loss diagnosis and prediction, micro camera resolution for scalp scan, hair loss type classification model, customized personal account management, and hair loss progress diagnosis model were derived. This study is significant in that it presented directions for the development of artificial intelligence-based intelligent medical product that were not previously preceded.

• Information Systems Review
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• v.25 no.4
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• pp.47-65
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• 2023

In this paper, we investigate how the online voting system can be a trust-based system from a technical perspective. Under four principles of voting, we finely evaluate the existing belief that offline voting is safer and more reliable than online voting based on procedural processes, technical principles. Many studies have suggested the ideas for implementing online voting system, but they have not attempted to strictly examine the technologies of online voting system from the perspective of voting requirements, and usually verification has been insufficient in terms of practical acceptance. Therefore, this study aims to analyze how the technologies are utilized to meet the demanding requirements of voting based on the technologies proven in the field. In addition to general data encryption, online voting requires more technologies for preventing data manipulation and verifying voting results. Moreover, high degree of confidentiality is required because voting data should not be exposed not only to outsiders but also to managers or the system itself. To this end, the security techniques such as Blind Signature, Bit Delegation and Key Division are used. In the case of blockchain-based voting, Mixnet and Zero-Knowledge Proof are required to ensure anonymity. In this study, the current status of the online voting system is analyzed based on the field system that actually serves. This study will enhance our understanding on online voting security technologies and contribute to build a more trust-based voting mechanism.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.111-127
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• 2023

This study is a study on user perception of ChatGPT use. The goal of this study is to analyze the relationship between user policy expectations and user innovativeness on ChatGPT technology acceptance and intention to use using variables of TRA (Theory of Reasoned Action). The impact of policy expectations and user innovativeness on the intention to use by mediating usefulness and hedonic motivation, and the impact of subjective norms on the usefulness and intention to use were analyzed by dividing them into the MZ generation and the non-MZ generation. It was verified whether there was a moderating effect on the effect of age differences on usefulness by interacting with policy expectations. An online survey was conducted on 300 ChatGPT users using PLS (Partial Least Square) structural equations and SPSS Package, and statistical analysis was performed using PLS and SPSS. According to the analysis results, it was confirmed that the higher the initial user's innovativeness, the higher the intention to use ChatGPT. In addition, the moderating effect analysis comparing the differences between the MZ generation and the non-MZ generation showed that policy expectations had a negative effect on the usefulness of ChatGPT use.

• Information Systems Review
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• v.23 no.4
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• pp.23-43
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• 2021

Due to the recent transition to a non-face-to-face society, many organizations are quickly adapting to foster a smart work environment. The introduction of smart work does not simply end with incorporating ICT systems or solutions into business models since fundamental factors such as forms of employment and work styles need to be in line with the progression of technological advances. However, previous studies regarding smart work focus on improvements in productivity and efficiency from a technology acceptance perspective. Therefore, there is a lack of discussion on innovation resistance from employees and management control when ICT systems are introduced into the workplace. This study empirically analyzes the moderating effects of the organizational control method for employees and innovation resistance within a smart work environment. Additionally, this study aims to identify the structural characteristics that employees resist from an innovation resistance perspective when organizational innovation occurs. The empirical analysis of this study suggests that when smart work such as ICT technology is introduced into the workplace the level of innovation resistance decreases when there is a high level of relative advantage and self-efficacy, whereas the level of innovation resistance increases when there is a high level of use complexity. Moreover, this study revealed that the level of innovation resistance increases when the employees' behaviors were controlled. The results of this study intend to contribute to improving business management by suggesting factors worth considering when incorporating smart work into work places through a thorough case analysis.

• Information Systems Review
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• v.23 no.3
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• pp.177-200
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• 2021

Recently, the use of prepaid electronic payments such as electronic wallets, digital currency and prepaid points is gradually increasing. Prepaid electronic payments has the characteristic of being used after charging first. This study empirically investigated the factors affecting the intention to use online charging in order to help improve the service that require prepaid recharge by applying transformed TAM. Since there are not many previous studies for the intention to use online charging, we extract factors through preceding researches for electronic cash and mobile easy payment. Also we analyze the intention to use online charging for transportation card users, focusing on the moderating effects. As a result of the study, it was found that 'convenience', 'ubiquity', and 'self-efficacy' among the independent variables had a positive (+) effect on mediation variable 'perceived usefulness'. 'Perceived usefulness' was analyzed to have a significant influence on the dependent variable 'usage intention'. According to users' gender, internet usage time, internet shopping frequency, online charging frequency and transportation card usage type, the moderating effect was significant on 'perceived usefulness' and 'usage intention'. As an implication, it was suggested that service improvement and differentiated marketing are needed in direction of increasing the usefulness of services. Additional research directions were proposed for services such as e-wallets, prepaid points and digital currencies by adding other factors and moderate variables.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.155-169
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• 2014

With the rapid advances in technologies, organizations are more likely to depend on information systems in their decision-making processes. Business Intelligence (BI) systems, in particular, have become a mainstay in dealing with complex problems in an organization, partly because a variety of advanced computational methods from statistics, machine learning, and artificial intelligence can be applied to solve business problems such as demand forecasting. In addition to the ability to analyze past and present trends, these predictive analytics capabilities provide huge value to an organization's ability to respond to change in markets, business risks, and customer trends. While the performance effects of BI system use in organization settings have been studied, it has been little discussed on the use of predictive analytics technologies embedded in BI systems for forecasting tasks. Thus, this study aims to find important factors that can help to take advantage of the benefits of advanced technologies of a BI system. More generally, a BI system can be viewed as an advisor, defined as the one that formulates judgments or recommends alternatives and communicates these to the person in the role of the judge, and the information generated by the BI system as advice that a decision maker (judge) can follow. Thus, we refer to the findings from the advice-giving and advice-taking literature, focusing on the role of explanations of the system in users' advice taking. It has been shown that advice discounting could occur when an advisor's reasoning or evidence justifying the advisor's decision is not available. However, the majority of current BI systems merely provide a number, which may influence decision makers in accepting the advice and inferring the quality of advice. We in this study explore the following key factors that can influence users' advice taking within the setting of a BI system: explanations on how the box-office grosses are predicted, types of advisor, i.e., system (data mining technique) or human-based business advice mechanisms such as prediction markets (aggregated human advice) and human advisors (individual human expert advice), users' evaluations of the provided advice, and individual differences in decision-makers. Each subject performs the following four tasks, by going through a series of display screens on the computer. First, given the information of the given movie such as director and genre, the subjects are asked to predict the opening weekend box office of the movie. Second, in light of the information generated by an advisor, the subjects are asked to adjust their original predictions, if they desire to do so. Third, they are asked to evaluate the value of the given information (e.g., perceived usefulness, trust, satisfaction). Lastly, a short survey is conducted to identify individual differences that may affect advice-taking. The results from the experiment show that subjects are more likely to follow system-generated advice than human advice when the advice is provided with an explanation. When the subjects as system users think the information provided by the system is useful, they are also more likely to take the advice. In addition, individual differences affect advice-taking. The subjects with more expertise on advisors or that tend to agree with others adjust their predictions, following the advice. On the other hand, the subjects with more knowledge on movies are less affected by the advice and their final decisions are close to their original predictions. The advances in predictive analytics of a BI system demonstrate a great potential to support increasingly complex business decisions. This study shows how the designs of a BI system can play a role in influencing users' acceptance of the system-generated advice, and the findings provide valuable insights on how to leverage the advanced predictive analytics of the BI system in an organization's forecasting practices.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.7-29
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• 2012

Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.25-51
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• 2008

Researchers have been continuously interested in the adoption of information technology (IT) since it is of great importance to the information systems success and it is also an important stage to the success. Adoption alone, however, does not ensure information systems success because it does not necessarily lead to achieving organizational or individual objectives. When an organization or an individual decide to adopt certain information technologies, they have objectives to accomplish by using those technologies. Adoption itself is not the ultimate goal. The period after adoption is when users continue to use IT and intended objectives can be accomplished. Therefore, continued IT use in the post-adoption period accounts more for the accomplishment of the objectives and thus information systems success. Previous studies also suggest that continued IT use in the post-adoption period is one of the important factors to improve long-term productivity. Despite the importance there are few empirical studies focusing on the user behavior of continued IT use in the post-adoption period. User behavior in the post-adoption period is different from that in the pre-adoption period. According to the technology acceptance model, which explains well about the IT adoption, users decide to adopt IT assessing the usefulness and the ease of use. After adoption, users are exposed to new experiences and they shape new beliefs different from the thoughts they had before. Users come to make decisions based on their experiences of IT use whether they will continue to use it or not. Most theories about the user behaviors in the pre-adoption period are limited in describing them after adoption since they do not consider user's experiences of using the adopted IT and the beliefs formed by those experiences. Therefore, in this study, we explore user's experiences and beliefs in the post-adoption period and examine how they affect user's intention to continue to use IT. Through deep literature reviews on the construction of subjective beliefs by experiences, we draw three meaningful constructs which theoretically have great impacts on the continued use of IT: perceived habit, confirmation, and computer self-efficacy. Then, we examine the role of the subjective beliefs on the cognitive/affective attitudes and intention to continue to use that IT. We set up a research model and conducted survey research. Since IT use implies interactions among a user, IT, and a task, we carefully selected the sample of users using same/similar IT to perform same/similar tasks, to exclude unwanted influences of other factors than subjective beliefs on the IT use. We also considered that the sample of users were able to make decisions to continue to use IT volitionally or at least quasi-volitionally. For each construct, we used measurement items recognized for reliability and widely used in the previous research. We slightly modified some items proper to the research context and a pilot test was carried out for forty users of a portal service in a university. We performed a full-scale survey after verifying the reliability of the measurement. The results show that the intention to continue to use IT is strongly influenced by cognitive/affective attitudes, perceived habits, and computer self-efficacy. Confirmation affects the intention to continue indirectly through cognitive/affective attitudes. All the constructs representing the subjective beliefs built by the experiences of IT use have direct and/or indirect impacts on the intention of users. The results also show that the attitudes in the post-adoption period are formed, at least partly, by the experiences of IT use and newly shaped beliefs after adoption. The findings suggest that subjective beliefs built by the experiences have deep impacts on the continued use. The results of the study signify that while experiencing IT in the post-adoption period users form new beliefs, attitudes, and intentions which may be different from those of the pre-adoption period. The results of this study partly demonstrate that the beliefs shaped by the behaviors, those are the experiences of IT use, influence users' attitudes and intention. The results also suggest that behaviors (experiences) also change attitudes while attitudes shape behaviors. If we combine the findings of this study with the results of the previous research on IT adoption, we can propose a cycle of IT adoption and use where behavior shapes attitude, the attitude forms new behavior, and that behavior shapes new attitude. Different from the previous research, the study focused on the user experience after IT adoption and empirically demonstrated the strong influence of the subjective beliefs formed in the post-adoption period on the continued use. This partly confirms the differences between attitudes in the pre-adoption and in the post-adoption period. Users continuously change their attitudes and intentions while experiencing (using) IT. Therefore, to make users adopt IT and to make them use IT after adoption is a different problem. To encourage users to use IT after adoption, experiential variables such as perceived habit, confirmation, and computer self-efficacy should be managed properly.

• Food Science and Preservation
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• v.16 no.6
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• pp.900-907
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• 2009

Chiffon cakes were prepared using various concentrations of aloe gel to develop functional baking procedures. The quality characteristics of chiffon cakes prepared after addition of 20%, 40%, or 60% (w/w) aloe gel, substituting for the same levels of wheat flour, were investigated. No significant weight difference between cakes was observed. The height of cakes containing aloe gel was significantly greater than that of control cakes. The baking loss rate (BLR) of aloe gel decreased as the amount of gel increased, and cakes prepared using 60% (w/w) aloe gel had the lowest BLR. Moisture contents of cakes prepared using aloe gel were higher than that of control cakes. Cakes with 60% (w/w) aloe gel had the highest moisture content. The pore size of cakes with 60% (w/w) aloe gel was the smallest of all groups. Crumb color became whiter as the proportion of aloe gel increased. Lightness (L value) of control cake was lower than that of cake containing aloe gel. Redness (a value) of aloe chiffon cakes increased as the proportion of aloe gel rose. Yellowness (b value) of cakes with 40% (w/w) aloe gel was significantly higher than that of the control group. Other cakes showed no difference in b value compared with control cake. Hardness in all cakes prepared with aloe gel was significantly lower than that of the control group. Adhesiveness of control cake was significantly lower than that of other cakes. No significant between-group difference in springiness was observed. The cohesiveness of cakes with 40% (w/w) aloe gel was significantly lower than that of the control group and that of cakes with 20% (w/w) aloe gel. The gumminess and chewiness of control cakes were significantly higher than those of other cakes. The yellowness of cake with 60% (w/w) aloe gel was significantly lower than that of the other groups. Pore size decreased after the addition of aloe gel. There was no significant difference in appearance among cakes thus, all cakes were acceptable to potential consumers. Although no perceptible difference in aloe odor was evident, cakes with 60% (w/w) aloe gel scored significantly lower in flavor acceptance compared with other cakes. No significant between-cake difference in taste acceptance, perceived moisture level, or texture acceptability was observed. Cakes with 40% and 60% (both w/w) aloe gel were of significantly higher density than other cakes. Overall, the acceptability of cakes with 60% (w/w) aloe gel was lower than that of other cakes. Ultimately, the results indicated that quality can be enhanced by adding less than 40% (w/w) aloe gel to chiffon cakes as a substitute for wheat flour.