• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.205-219
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• 2021

The present study identified determinants to user acceptance of artificial intelligence(AI)-based news anchor. Our conceptual model included three constructs of ability, benevolence, and integrity to determine whether these three constructs are predictive of trust perceived from AI news anchor. This work further examined the influences of social presence, anthropomorphism, perceived usefulness, understanding as well as trust as immediate determinants to user acceptance. The conceptual model was validated on survey data collected from 513 respondents. A series of scale refinement process was conducted by the examination of data normality, common method bias, structure of latent variables as well as internal consistency. In addition, a confirmatory factor analysis was performed to assess the extent to which the sample data collected from survey study measures the constructs adequately. The results from the analysis of structural equation model indicated that, (1) two constructs of ability and integrity were found to be significantly predictive of perceived trust, and (2) anthropomorphism, perceived usefulness, and trust emerged as significant and positive predictors of user acceptance of AI-based news anchor.

• Information Systems Review
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• v.25 no.1
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• pp.111-128
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• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.941-951
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• 2015

In the recent years, Korean construction companies have been awarded 680 billion USD in the oversea projects which lead to a successful quantitative growth. However, due to the lack of capability in the core technology and project management compared to the leading companies, in addition to low-price bidding, massive deficit projects have caused problems to the companies. In order to overcome the limitations of the lack of capabilities, the term constructability has been researched recently by developed countries to apply in the practical use. The concept of constructability must be applied for Korean companies to compete in the EPC construction projects. The term constructability is defined as the factor that affect the overall construction process of a project which is defined by the ease of construction and to secure the project quality. Therefore, this study aims to develop a constructability assessment model using the structural equation to assess the factors that affect the constructability in the design and construction stage. The purpose of using the structural equation is to analyze the direct and indirect correlation between each factor that affects the international construction projects. Total of 8 latent variables and 34 measured variables are derived through literature review, corporate reports, experts' interview and surveys. The result of the model suggests the constructability factors that are to be managed the most efficiently to reduce cost, time and improve the quality as well as a countermeasure strategy to successfully execute the target international construction projects.

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.57-63
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• 2009

With an exponential increase in electronic commerce (e-commerce), marketers are attempting to gain a competitive advantage by emphasizing service quality and post interaction service aspects, which leads to customer satisfaction or behavioral consequence. Particularly for apparel, service quality is one of the key determinants in encouraging customer e-loyalty, and hence the success of apparel retailing in the context of electronic commerce. Therefore, this study explores e-service quality (E-SERVQUAL) factors and their unique effects on e-loyalty for apparel online shopping based on Parasuraman et al' s (2005) framework. Specific objectives of this study are to identify underlying dimension of E-SERVQUAL, and analyze a structural model for examining the effect of E-SERVQUAL on e-loyalty for online apparel shopping. For the theoretical framework of service quality in the context of online shopping, literatures on traditional and electronic service quality factors were comparatively reviewed, and two aspects of core and recovery services were identified. This study hypothesized that E-SERVQUAL has an effect on e-loyalty; customer satisfaction has a positive effect on e-service loyalty for apparel online shopping; and customer satisfaction mediates in the effect of E-SERVQUAL on e-loyalty for apparel online shopping. A self-administered questionnaire was developed based on literatures. A total of 252 usable questionnaires were obtained from online consumers who had purchase experience with online shopping for apparel products and reside in standard metropolitan areas, in the United States. Factor analysis (e.g., exploratory, confirmatory) was conducted to assess the validity and reliability and the structural equation model including measurement and structural models was estimated via LISREL 8.8 program. Findings showed that the E-SERVQUAL of shopping websites for apparel consisted of five factors: Compensation, Fulfillment, Efficiency, System Availability, and Responsiveness. This supports Parasuraman (2005)'s E-S-QUAL encompassing two aspects of core service (e.g., fulfillment, efficiency, system availability) and recovery related service (e.g., compensation, responsiveness) in the context of apparel shopping online. In the structural equation model, there are five exogenous latent variables for e-SERVQUAL factors; and two endogenous latent variables (e.g., customer satisfaction, e-loyalty). For the measurement model, the factor loadings for each respective construct were statistically significant and were greater than .60 and internal consistency reliabilities ranged from .85 to .88. In the estimated structural model of the e-SERVEQUAL factors, the system availability was found to have direct and positive effect on e-loyalty, whereas efficiency had a negative effect on e-loyalty for apparel online shopping. However, fulfillment was not a significant predictor for explaining consequences of E-SERVQUAL for apparel online shopping. This finding implies that perceived service quality of system available was likely to increase customer satisfaction for apparel online shopping. However, it was not supported that e-loyalty was determined by service quality, because service quality has an indirect effect on e-loyalty (i.e., repurchase intention) by mediating effect of value or satisfaction in the context of online shopping for apparel. In addition, both compensation and responsiveness were found to have a significant impact on customer satisfaction, which influenced e-loyalty for apparel online shopping. Thus, there was significant indirect effect of compensation and responsiveness on e-loyalty. This suggests that the recovery-specific service factors play an important role in maximizing customer satisfaction levels and then maintaining customer loyalty to the online shopping site for apparel. The findings have both managerial and research implications. Fashion marketers can establish long-term relationship with their customers based on continuously measuring customer perceptions for recovery-related service quality, such as quick responses to problem and returns, and compensation for customers' problem after their purchases. In order to maintain e-loyalty, recovery services play an important role in the first choice websites for consumers to purchase clothing. Given that online consumers may shop anywhere, a marketing strategy for improving competitive advantages is to provide better service quality, maximize satisfaction, and turn to creating customers' e-loyalty for apparel online shopping. From a researcher's perspective, there are some limitations of this research that should be considered when interpreting its findings. For future research, findings provide a basis for the further study of this important topic along both theoretical and empirical dimensions. Based on the findings, more comprehensive models for predicting E-SERVQUAL's consequences can be developed and tested. For global fashion marketing, this study can expand to a cross-cultural approach into e-service quality for apparel by including multinational samples.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.39-51
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• 2016

In accordance to rapid aging of population, the accidents of elderly pedestrian and pedestrian safety are becoming very important issues. In terms of smartphone technologies, older people are increasingly looking for useful and friendly ICT services that which can add a value on their silver life. This paper introduced a new IT-based service for elderly walking assist using a smart-phone accompanied by a wearable watch. We describe the functional requirements and a systems architecture model with an interface between a smart-phone and wearable watch. Moreover, this study attempted to verify what services are needed and to estimate elderly pedestrians' WTP (willingness to pay) for IT-based walking assistance device. A total of 189 elderly pedestrians were randomly surveyed through face-to-face interviews. The questionnaire consisted of 3 categories: (1) questions pertaining to socio-economic status, (2) 12 questions regarding walking attitudes, and (3) a question to measure WTP. With this gathered data, factor analysis and path model estimating were conducted. The results identified the elderly user requirements and the use-value of new innovative products for IT-based walking assistance services by two groups(latent elderly and elderly). The modeling result shows that elderly's service preference would increase the possibilities for the commercialization of IT-based walking device with improving their walking safety.

• Journal of Distribution Science
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• v.13 no.5
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• pp.113-120
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• 2015

Purpose - As the rapid development of ICT has been made recently, many domestic companies are trying to introduce smart work infrastructure. The purpose of institution of smart work is to enhance their performance. To this end, it is necessary to advance the way of working. Developing employees' collective intelligence should be regarded as a prerequisite for advancing the way of working. Job satisfaction of the employees is another important factor to enhance organizational performance. So this study aims to provide the theoretical background of systematic approach to smart work quality by empirically analyzing the effect of smart work quality on collective intelligence and job satisfaction. Research design, data, and methodology - A structural equation model was designed to examine cause-and-effect relationships among three latent variables(smart work quality, collective intelligence, job satisfaction). Three hypotheses were formulated. The first hypothesis is that the effect of smart work quality on collective intelligence will be positively and statistically significant. Likewise, the second hypothesis is that the effect of smart work quality on job satisfaction will be positively and statistically significant. Finally, the third hypothesis is that the effect of collective intelligence on job satisfaction will be positively and statistically significant. Based on the previous researches, 34 questionnaire items were developed to measure the effect of the three variables. The survey was conducted on 162 employees who are working under smart work environment. The number of the effective questionnaires for the analysis was 154. PASW Statistics 18 and AMOS 18 were used for the statistical analysis. Results - The validity and reliability test for questionnaire items have been carried out. From the factor analysis, 1 out of 34 items was eliminated. As a result, 33 out of 34 items were used for analyzing. The values of Cronbach's α ranged from 0.701 to 0.910, indicating the acceptable reliability of the questionnaire items. The values of χ2, df, CFI, TLI, RMSEA of the model are 102.838, 51, 0.949, 0.935, 0.082, respectively. So the structural equation model was statistically significant. The first and third hypotheses were supported. But the second hypothesis was rejected. Conclusions - An analysis using structural equation model showed meaningful implications about the effect of smart work quality on collective intelligence and job satisfaction. First, as the five quality elements of the smart work improved, the level of collective intelligence increased. Second, the statistical analysis showed smart work didn't have a direct effect on job satisfaction, which is inconsistent with the prior findings. The main purpose of smart work is to help achieve greater performance. The companies also need to make efforts to improve job satisfaction of their employees along with achieving greater performance. Third, an organization with higher level of collective intelligence showed greater job satisfaction. The companies under smart work environment need to develop functions to encourage participation, sharing, openness, and collaboration. This research will provide useful information for the companies which want to introduce smart work, distribution information system, management information system, etc.

• Journal of Applied Reliability
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• v.15 no.4
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• pp.241-247
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• 2015

Purpose : The demand for higher fuel economy vehicles has helped develop fuel-efficient vehicles such as a CVVL called continuous variable valve lift. Existing CVVL has been applying DC type motor to control intake valve, but recently some car parts manufacturers have been developing a BLDC type CVVL motor for improvements of endurance performance. The purpose of this study is to find the potential failure mechanism of the CVVL BLDC moto in early stage of development based on the design properties and design the accelerated life test model. Methods : CVVL BLDC is consist of brushs, coil, magnetic, PCB, bearing and so on. Each component has a latent failure mechanism caused by temperature, humidity, vibration. By analysis result of the failure mechanism, thermal fatigue is the most important factor of a durability of CVVL BLDC motor. So, we designed a new accelerated life test model for guarantee of the CVVL BLDC motor. Results : A crack occurred on via hole in test using the conditions we designed, so we did change the design to avoid this failure. The via hole dimension is changed a little larger, as a result we achieve improvements in reliability of the CVVL BLDC motor. By applying various kinds and extreme level of stresses, we can find the operating limits of products. Conclusion : In thesis, We analyzed the failure mechanism of CVVL BLDC and designed an accelerated life test method to give a guarantee for reliability. Based on the test results, we could improve the reliability of developments by change of design.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.945-960
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• 2009

The purpose of this study is to define determinants of VoIP user acceptance and to verify significant causality among latent variables - performance expectancy, effort expectancy, cost expectancy, social influence, facilitating conditions, behavioral intend, use behavior - based on UTAUT model. We presented the expanded hypotheses including the new factor, cost expectancy and analyzed the moderating effect of user age, gender and usage experience variables. For a accuracy of predicted results, we focused on survey analysis with 641 real user samples. Compared to previous studies, it is meaningful that this research verified the conceptual difference between behavioral intention and usage behavior. As a result, all proposed hypotheses accepted and moderating effects are supported significantly in age and use experience moderating variables.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.1
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• pp.1-11
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• 2012

Human thermal sensation based on a human energy balance model was analyzed in the study areas, the Changwon and Nanaimo sites, on clear days during thesummer of 2009. The climatic input data were air temperature, relative humidity, wind speed and solar and terrestrial radiation. The most effective factors for human thermal sensation were direct beam solar radiation, building view factor and wind speed. Shaded locations had much lower thermal sensation, slightly warm, than sunny locations, very hot. Also, narrow streets in the Nanaimo site had higher thermal sensation than open spaces because of greater reflected solar radiation and terrestrial radiation from their surrounding buildings. Calm wind speed also produced much higher thermal sensation, which reduced sensible and latent heat loss from the human body. By adopting climatic factors into landscape architecture, the human thermal sensation analysis method promises to help create thermally comfortable outdoor areas. The method can also be used for urban heat island modification and climate change studies.

• Information Systems Review
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• v.23 no.4
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• pp.69-86
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• 2021

As artificial intelligence technology advances, personalized recommendation systems using big data have attracted huge attention. In the case of beauty products, product preferences are clearly divided depending on customers' skin types and sensitivity along with individual tastes, so it is necessary to provide customized recommendation services based on accumulated customer data. Therefore, by employing deep learning methods, this study proposes a neural network-based recommendation model utilizing both product search history and context information such as gender, skin types and skin worries of customers. The results show that our model with context information outperforms collaborative filtering-based recommender system models using customer search history.