• Journal of KIBIM
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• v.9 no.4
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• pp.75-83
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• 2019

Recent data development has made it possible to analyze each individual's daily commuting by using transportation card transaction. This research utilizes about 1 million observations from the subway line no.7 of Seoul metropolitan transportation data. By using such a massive dataset, the authors try to identify daily travel behavior of morning commute and its possible relationship between subway usage and socio-economic factors. There are 4 main types of users and their travel behavior, and top 15 stations with the most users for arrival and departure are selected. Accordingly, 15 stations have distinctive characteristics including population density and the number of businesses around stations. To identify this fact, the 4 most populated stations are selected and their socio-economic factors are examined. According to the analysis, the most departure stations are generally surrounded by hihgly populated residential areas, whereas the most arrival stations are stood within the job concentrated districts.

• The Journal of Bigdata
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• v.1 no.2
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• pp.1-8
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• 2016

User activity log includes lots of hidden information, however it is not structured and too massive to process data, so there are lots of parts uncovered yet. Especially, it includes time series data. We can reveal lots of parts using it. But we cannot use log data directly to analyze users' behaviors. In order to analyze user activity model, it needs transformation process through extra framework. Due to these things, we need to figure out user activity model analysis framework first and access to data. In this paper, we suggest a novel framework model in order to analyze user activity model effectively. This model includes MapReduce process for analyzing massive data quickly in the distributed environment and data architecture design for analyzing user activity model. Also we explained data model in detail based on real online service log design. Through this process, we describe which analysis model is fit for specific data model. It raises understanding of processing massive log and designing analysis model.

• Journal of the Korean Society for information Management
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• v.34 no.3
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• pp.89-107
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• 2017

This study aims to compare information seeking behavior of 1300K users on PC and mobile phone. Transaction logs of 1300K, a major Korean shopping search engine, were analyzed. These transaction logs were collected over 1 month period, from April 1 to April 31, 2016. The results of this study show that there are a little more mobile sessions than PC sessions. Users conducted slightly more browsing on PCs than mobile phones, whereas users submitted queries more than two times on mobile phones than on PCs. Users clicked more search results on PCs than mobile phones, whereas users made important decision makings such as product purchases more on mobile phones than PCs. Top queries and categories were similar between PCs and mobile phones. Queries and categories on mobile phones were more focused than queries on PCs. Overall, mobile search behavior is more simple, passive, and focused than PC search behavior. The results of this study can be implemented to the effective improvement and development of search services for different devices.

• Asia Marketing Journal
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• v.24 no.2
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• pp.51-61
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• 2022

The goal of this study is to scrutinize the impact of individual online convenience dimensions on mobile banking acceptance and use in Mongolia. A total of 211 valid responses were collected from Mongolian university students who currently use mobile banking application services from local banks. The SmartPLS 3.3 software was used to conduct the confirmatory factor analysis and test the hypotheses. Using structural equation modelling, this research discovered that access convenience, transaction convenience, and possession/post-possession convenience are the main constructs related to the adoption of mobile banking services. Perceived innovation showed a significant positive effect on the adoption of mobile banking technologies. Through practical and theoretical implications, this research aims to assist mobile banking service channels of local and international banks in Mongolia. Identifying which online convenience dimensions impact the adoption and use of mobile banking will contribute to the adoption of competitive strategies for financial institutions and banks.

• Korean Journal of Construction Engineering and Management
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• v.19 no.6
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• pp.135-143
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• 2018

Normally there is a one-time relationship between stakeholders in the construction projects. Thus, project participants are easily exposed to opportunistic behavior. According to the theory of transaction costs, a contract effectively influence the behavior of counter-party. The important role of contracts in limiting opponent opportunistic behavior has been academically acknowledged and studied in inter-firm relationships. The purpose of this study is to reveal the mediating effect of the contract on the power of the contractor in the contractor's behavior. Power is divided into mediated and non-mediated power. We surveyed construction companies' employees who have conducted construction projects. Based on the questionnaire response, we examined the influence of the Employer's power on the behavior of the contractor. Both non-mediated power and mediated power were significant for in-role and out-role behaviors. Both non-mediated power and mediated power were found to have a significant effect on the control and coordination function of contracts. The results show that the control function of the contract is significant for the in-role behavior and the extra-role behavior. Finally, the mediating effect of the contract function was significant only in the control function.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.21-29
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• 2018

The cooperative relationship between Employer and Contractor in the construction industry is the most important factor to achieve the project success. Employer shall draw the Contractor's cooperative behavior during executing the project. A study on the impact of the Owner's power on the contractor's cooperative behavior is rare in the construction industry in Korea even though the negative impact of the high-power distance between the Employer and the Contractor has been a hot issue in Korea. In this empirical study, it is shown that the Employer's power can address the contractor's cooperative behavior. The respondents were mostly employees in the domestic construction companies who have experienced in the construction projects. The total number of respondents was 317 effectively. The multiple regression analysis using SPSS 21.0 were conducted to verify the hypotheses. In conclusion, the Mediated Power is positively associated with the In-Role Behavior and with the Extra-Role Behavior. Some of Non-Mediated Power is positively associated with the In-Role Behavior and with the Extra-Role Behavior. It seems that the Contract underestimate the Employer's Expert Power. It was known that the cooperative power caused by Non-Mediated Power is good for long term relationship of the business to business transaction. So it is highly recommended that the Employer shall foster its expertise.

• Journal of Information Technology Applications and Management
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• v.23 no.4
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• pp.55-70
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• 2016

Recently, development of indoor positioning system and IoT such as beacon makes it possible to collect and analyze each customer's shopping behavior in off-line shopping malls. In this study, we propose a realtime brand recommendation scheme based on each customer's brand visiting history for off-line shopping mall with indoor positioning system. The proposed scheme, which apply collaborative filtering to off-line shopping mall, is composed of training and apply process. The training process is designed to make the base brand network (BBN) using historical transaction data. Then, the scheme yields recommended brands for shopping customers based on their behaviors and BBN in the apply process. In order to verify the performance of the proposed scheme, simulation was conducted using purchase history data from a department store in Korea. Then, the results was compared to the previous scheme. Experimental results showd that the proposed scheme performs brand recommendation effectively in off-line shopping mall.

• Journal of Distribution Science
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• v.13 no.5
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• pp.5-14
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• 2015

Purpose - Loyalty programs enable retailers to maintain longer and better customer relationships. In successful services, customers actively use and value these programs. As the proximity to the goal (goal gradient) might signal active participation, this study empirically examines customer's goal gradient behavior in a multi-vendor loyalty program. We also consider the effect of customer's accrual diversity on goal gradients, which is a differentiating feature in a multi-vendor loyalty program, and is further examined. Research Design, Data, and Methodology - The data consists of6,646 OK Cashbag members' individual transaction records from 2006 to 2009. The goal gradient hypothesis was tested as an increase in both the speed and the amount of accumulated award points. Result - The findings suggest that the goal gradient is also observed in a multi-vendor loyalty program, occurring more strongly among members with high accrual diversity. Conclusions - The results indicate that customers with high accrual diversity attend strongly to goal gradients in multi-vendor loyalty programs; hence, it is important for such program managers to better inform members about affiliated partners.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.9-24
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• 2022

With a view to attracting foreign investment and growing the economy, the Vietnamese government has hastened financial reforms, including the lifting of limitations on foreign investment, which has resulted in rapidly rising foreign ownership in recent years. To study the relationship between transactions of foreign investors and transactions of domestic investors on two stock exchanges in Vietnam Ho Chi Minh City Stock Exchange (HSX) and Hanoi Stock Exchange (HNX). This study applies a secondary dataset comprising daily market trading information of 912 stocks from 18 industries listed on 2 Vietnam stock exchanges, including HSX and HNX, which includes executed price, executed volume, daily Buy Orders, and Sell Orders categorized into domestic investors' orders and foreign investors orders from 01.04.2010 to 10.04.2018. The regression results show a significantly positive relationship between foreign investors' trading and domestic investors' transaction in all trading activities in both up and down markets. Therefore, these results indicate that domestic investors in Vietnam are concerned with foreign investors' trading as an important sign, and domestic investors tend to follow their counterparties without appropriate fundamental information. From there, there are signs of herding behavior of domestic investors following foreign investors in transactions on the stock market in Vietnam.

• 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.