• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1481-1501
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• 2019

In opportunistic network, the behavior of a node is autonomous and has social attributes such as selfishness.If a node wants to forward information to another node, it is bound to be limited by the node's own resources such as cache, power, and energy.Therefore, in the process of communication, some nodes do not help to forward information of other nodes because of their selfish behavior. This will lead to the inability to complete cooperation, greatly reduce the success rate of message transmission, increase network delay, and affect the overall network performance. This article proposes a hybrid incentive mechanism (Mim) based on the Reputation mechanism and the Credit mechanism.The selfishness model, energy model (The energy in the article exists in the form of electricity) and transaction model constitute our Mim mechanism. The Mim classifies the selfishness of nodes and constantly pay attention to changes in node energy, and manage the wealth of both sides of the node by introducing the Central Money Management Center. By calculating the selfishness of the node, the currency trading model is used to differentiate pricing of the node's services. Simulation results show that by using the Mim, the information delivery rate in the network and the fairness of node transactions are improved. At the same time, it also greatly increases the average life of the network.

• Journal of Distribution Science
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• v.20 no.1
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• pp.13-26
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• 2022

Purpose: The Covid-19 pandemic has accelerated and triggered changes in online shopping especially in an emerging market. This paper develops a modification of SERVQUAL model to examine the relationship between individual dimensions of e-service quality, online trust and purchase intentions in singular online shopping platform. Research design, data and methodology: Data from an online survey of 385 Lazada's shoppers were used to test the research model. The structural equation modeling technique was performed to test the research model. Results: The analytical results revealed that five dimensions of e-service quality were positively correlated with one another whereas some dimensions were negatively correlated with purchase intentions. The results of this study provide new insight into the literature as well as practical implications for marketers especially in Thai online market. Conclusion: This study develops the instrument dimensions of e-service quality through modifying the SERVQUAL model to examine the e-commerce context and to testify how these individual dimensions are interlinked with one another. It also suggests that responsiveness has two-sided affects that in responses which are too prompt and insistent could make the customer feel uncomfortable and perhaps ending up with no interaction and transaction.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.125-131
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• 2023

OVO is a digital platform that provides simple payments and smart financial services, as well as one of the largest digital payment platforms in Indonesia. It has wide coverage and security when making payments, and supports multiple settlement currencies. The purpose of this study is to explore the history, business model, and future strategic direction of OVO, an Indonesian e-wallet. To date, OVO has built its own mobile payment ecosystem covering a wide range of consumer scenarios including e-commerce, travel, offline shopping and finance. And it supports mobile banking, online banking, debit cards or selected partner merchants. Its three largest transaction categories are in the transportation, retail and e-commerce sectors. With over 110 million consumers and 1.3 million merchant users, it is one of the dominant e-wallets in Indonesian market and has become the country's e-payment market leader. OVO eWallet's 'One Card' model offers convenience and choice for users, thus contributing to the rapid growth of OVO eWallet. And OVO eWallet competes fiercely with other competitors, but OVO eWallet continues to grow in terms of the number of users and market share. Finally, this study analyzes the strategic goals and plans of OVO eWallet, predicts its future direction. OVO eWallet has a huge success, but there are still competition and challenges to face.

• Asia pacific journal of information systems
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• v.33 no.3
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• pp.737-767
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• 2023

With the availability of big customer data and advances in machine learning techniques, the prediction of customer behavior at the session-level has attracted considerable attention from marketing practitioners and scholars. This study aims to predict customer purchase conversion at the session-level by employing customer profile, transaction, and clickstream data. For this purpose, we develop a multimodal deep learning fusion model with dynamic and static features (i.e., DS-fusion). Specifically, we base page views within focal visist and recency, frequency, monetary value, and clumpiness (RFMC) for dynamic and static features, respectively, to comprehensively capture customer characteristics for buying behaviors. Our model with deep learning architectures combines these features for conversion prediction. We validate the proposed model using real-world e-commerce data. The experimental results reveal that our model outperforms unimodal classifiers with each feature and the classical machine learning models with dynamic and static features, including random forest and logistic regression. In this regard, this study sheds light on the promise of the machine learning approach with the complementary method for different modalities in predicting customer behaviors.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.1-6
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• 2020

In this study, we propose an association inference model based on data bias optimization for road hazard detection. This is a mining model based on association analysis to collect user's personal characteristics and surrounding environment data and provide traffic accident prevention services. This creates transaction data composed of various context variables. Based on the generated information, a meaningful correlation of variables in each transaction is derived through correlation pattern analysis. Considering the bias of classified categorical data, pruning is performed with optimized support and reliability values. Based on the extracted high-level association rules, a risk detection model for personal characteristics and driving road conditions is provided to users. This enables traffic services that overcome the data bias problem and prevent potential road accidents by considering the association between data. In the performance evaluation, the proposed method is excellently evaluated as 0.778 in accuracy and 0.743 in the Kappa coefficient.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.163-171
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• 2020

Currently, most of the mobile game market releases games through Google play and App Store, which have a high share. Because it uses a third-party platform, only the payment API system provided must be used, and third-party platform pays the game company after excluding certain fees. Because game companies do not know whether or not to refund items and cannot get back items through third party transactions, users and professional websites are continuously appearing that exploit refunds. In this thesis, after analyzing problems of existing payment method and presenting a payment model using blockchain smart contract, we analyzed differences from existing model in terms of transparency, decentralization(fee), efficiency, and as a result, payment model using smart contract has low commission through P2P transaction without third parties and transparent transaction record, preventing item forgery and refund. Later, the proposed payment model would lead to the culling of companies acting on behalf of refunds for words that deviate from moral ethics such as "Refund OK even with items" and resolve the problem of unreasonable fees that arise through third-party platforms.

• The Journal of Fisheries Business Administration
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• v.39 no.1
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• pp.43-61
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• 2008

Excessive public loan with low interest and other tax benefits have been provided for fishermen, but much of them turned out to be little performed. There were the moral hazards of Suhyup in the process of executing the public loans. As the government gave the reimbursement on the financial loss of Suhyup resulting from the public loans, Suhyup had no responsibility of the bad debt loss. Therefore, Suhyup gave little efforts to reduce the non-performing. The government perceived this problem and tried to reduce the under-performing loans. Thus, the government decided to take limited responsibilities. Suhyup made the progress to reduce the under-performing public loans. Suhyup dealt with these situation and made the credit evaluation model of the fisherman's public loan. This paper is for the credit evaluation model in the fisherman's public loan, which explains the model development methodology and the model characteristics in detail. This evaluation model is composed of two sub-component model. the one is the quantitative model and the other is the qualitative model. The quantitative sub-model is for the identification of fishermen financial status and is based on the financial transaction information. Its development methodology is the CSS modeling for the consumer market. The qualitative sub-model is for the evaluation the business prospect and is based on the business information such as fisherman's management skills, technology, equipment. Its development methodology is the AHP. It provides the detailed information in the model development methodology, which is the ideal example such as the public loan. In addition it gives the information to the interest parties such as policy makers, suhyup and fishermen.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.4B no.4
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• pp.206-210
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• 2004

This paper deals with a parameter estimation of the DC-DC converter system for its diagnosis. Especially, we present the results of parameter estimation for the DC-DC converter model by the system identification method. The parameter estimation for the DC-DC converter system aims at the diagnosis of its operating status. For the operating status diagnosis of the DC-DC converter system, we assume that the DC-DC converter system is an equivalent model of the Buck converter and estimate the main parameter for on-line diagnosis. In addition, for verification of an estimated parameter, we compare a bode plot of the estimated system transfer function and measurement results of the HP4194 instrument. It is a control system analyzer for system transfer function measurement. Our results confirm that the main parameter for diagnosis of the DC-DC converter system can be estimated by the system identification method and that the aging status of the system can be predicted by these results on operating status.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.717-729
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• 2020

As the environmental pollution problem in modern society is rapidly changing with industrialization, the environmental pollution problem has a direct or indirect effect on various fields. In particular, heavy industry pollutants can be a significant variable in site selection and realestate value. Therefore, this study is based on transaction data of 13apartment complexes in Maanshan City, a representative steel city in China, and uses the Hedonic Price Model to study the effect on real estate prices, mainly on heavy industry pollution during environmental pollution. The conclusion shows that the farther away from the source of pollution, the higher values are.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.107-117
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• 2011

The appearance of Web has brought an substantial revolution to all fields of society such knowledge management and business transaction as well as traditional information retrieval. In this paper, we propose an EFASIT(Extended Fuzzy AHP and SImilarity Technology) model considering the emotion analysis. And we combine the Extended Fuzzy AHP Method(EFAM) with SImilarity Technology(SIT) based on the domain corpus information in order to efficiently retrieve the document on the Web. The proposed the EFASIT model can generate the more definite rule according to integration of fuzzy knowledge of various decision-maker, and can give a help to decision-making, and confirms through the experiment.