• Journal of Service Research and Studies
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• v.10 no.3
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• pp.67-80
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• 2020

The information system audit service has been recognized for its effectiveness in improving the management efficiency of informatization projects in the public sector and improving the quality of information systems. However, according to several recent studies, it is not very helpful in securing quality by indicating formal audit performance and incorrect functions or errors in a short audit period. So, if the effectiveness of audit is proved to ensure the quality of the information system from the perspective of the software life cycle and to successfully operate and maintain it, the use of audit for the successful construction of the information system will be an essential factor. Therefore, this study investigated whether the current audit service users are satisfied with the current information system audit and what they expect. If it is different from what was expected, the difference between expectations and performance was analyzed to improve user satisfaction, and a survey was conducted through interviews with experts in the information system field. Based on the empirical results through the questionnaire, in order to reduce the difference in expectations from the user's point of view in the information system audit service, a plan to improve the audit system suitable for the new audit environment was proposed.

• Korean Journal of Construction Engineering and Management
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• v.19 no.5
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• pp.111-120
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• 2018

Recently, Domestic public construction projects are experiencing a great deal of disputes because of the growing uncertainty about the criteria for calculating the prolongation cost. In addition, researchers have been studying various systems and proper cost estimates in an effort to reduce the uncertainty of these systems and the occurrence of disputes. However, there is no standard yet for social consensus. Meanwhile, The study on the classification system according to the recognition standard of accounting has been systematically studied. As a result, the concepts of accrual and cash basis are defined separately. The purpose of this study is to verify the possibility of applying the concept of 'accrual basis' to the Standard for calculation of prolongation cost. Therefore, As a result of analyzing the occurrence pattern of Job-site overhead cost, it is confirmed that actual costs can not be calculated by the cash-basis method. In particular, the implications of the necessity of the accrual-basis method should be more strictly indicated in the case of items such as indirect labor costs and welfare benefits. In addition, the contractor 's claim report and the appraisal report were examined. As a result, it was confirmed that the calculation situations of prolongation costs are biased to the cash-basis method. In this way, it is suggested that necessary to supplement the calculation standard of the actual costs from the point of view of accrual basis.

• Management & Information Systems Review
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• v.38 no.3
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• pp.113-125
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• 2019

This study empirically analyzes the effect of SNS informativeness, playfulness and reliability on purchase intention and the effect of consumer's purchase intention on business performance through structural equation model, In doing so, this study aims to suggest ways to enhance consumers' purchase intention and consequently increase the business performance through various SNS marketing strategies that can efficiently manage consumers. The questionnaires were distributed to adult men and women who are in their 20s through 60s, actively use SNS, and primarily reside in Daegu and Gyeongbukdo. The 400 copies of questionnaire were distributed from September 15 to October 1, 2018, of which 364 (91%) were used for the empirical analysis, except for 36 of the questionnaires that were unfaithful or unresponsive. Basic statistical analysis including frequency analysis was performed using SPSS 22.0 and AMOS 24.0, reliability and validity analysis were also performed, and finally hypotheses were tested by performing confirmatory factor analysis and path analysis of structural equation model. All of the SNS informativeness, playfulness and reliability were shown to have positive effects on the purchase intention. In addition, the effect of purchase intention on business performance was found to be significant. Companies should come up with a strategic SNS marketing plan to encourage consumers to enhance the willingness to purchase their products and services through SNS, and to make actual purchases, thereby improving business performance.

• Management & Information Systems Review
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• v.38 no.3
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• pp.187-210
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• 2019

Companies shall hold social responsibility as a member of the social community. Corporate social responsibility uses corporate resources, yet it plays important roles in reducing social imbalance. Their responsibilities are highly associated with the corporate sustainability. Many earlier studies on the association between corporate social responsibility and corporate sustainability have been attempted. Yet it should be mentioned that they do not show a variety of realities as linearity between dependent variables and independent variables were assumed. Thus, this study aims to analyze Markov blanket, a node of minimum descriptive variables that relieve a rigid assumption among variables and affect corporate sustainability by using Bayesian network. Sensitivity analysis was used to elicit how other variables affect by reflecting the complex reality when real factors are changed. As an important result of this study, the firm's future earnings sustainability is naturally related to operating earnings, and as the corporate governance structure is sound, the firm is able to steadily fulfill its social responsibility. However, the fact that the size of a company is large does not mean that it is in good compliance with corporate laws. This would not be unrelated to the fact that many of today's companies are not complying with the law and are suffering social condemnation. Results from this study will serve as a useful analytic tool when investors and creditors showing interests in corporate sustainability for assessing the value of companies and making investment decisions. Moreover, they can be used as references for relevant agency supervising capital markets to establish or improve appropriate institutions aimed at improving corporate sustainability.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.64-78
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• 2019

This paper explores key factors affecting taxi travel using global positioning system(GPS) data in Seoul, Korea, considering spatial dependence. We first analyzed the travel characteristics of taxis such as average travel time, average travel distance, and spatial distribution of taxi trips according to the time of the day and the day of the week. As a result, it is found that the most taxi trips were generated during the morning peak time (8 a.m. to 9 a.m.) and after the midnight (until 1 a.m.) on weekdays. The average travel distance and travel time for taxi trips were 5.9 km and 13 minutes, respectively. This implies that taxis are mainly used for short-distance travel and as an alternative to public transit after midnight in a large city. In addition, we identified that taxi trips were spatially correlated at the traffic analysis zone(TAZ) level through the Moran's I test. Thus, spatial regression models (spatial-lagged and spatial-error models) for taxi trips were developed, accounting for socio-demographics (such as the number of households, the number of elderly people, female ratio to the total population, and the number of vehicles), transportation services (such as the number of subway stations and bus stops), and land-use characteristics (such as population density, employment density, and residential areas) as explanatory variables. The model results indicate that these variables are significantly associated with taxi trips.

• Management & Information Systems Review
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• v.38 no.1
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• pp.181-199
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• 2019

The purpose of this study is to examine whether or not the volatility of the 1997~1998 Asian crisis still affects the monthly stock returns of Korea, Japan, Singapore, Hong Kong and China from 1980 to 2018. This study investigated whether the volatility has already fallen to pre-crisis levels. To illustrate the possible structural changes in the unconditioned variance due to the Asian financial crisis, we use the MRS-GARCH model, which is a regime switching model. The main results of this study were as follows: First, the stock return of each country was weak in the high volatility regime except Japan resulted by the Asian financial crisis from 1997 to 1998 until March 2018, and the Asian stock market has not yet calmed down except for the global financial crisis period of 2007 and 2008. Second, the conditional volatility has been significantly and persistently decreased and eliminated after the Asian financial crisis. Thus, we could be judged that the Asian stock market was not fully recovered(stable) due to the Asian crisis including the capital liberalization high inflation, worsening current account deficit, overseas low interest rates and expansion of credit growth in 1997 and 1998, but the Asian stock market was largely settled down, except for the 2007 and 2008 in Global financial crises. Considering the similarity between the Asian stock markets and the similar correlation of the regime switching, it may be worthwhile to analyze the MRS-GARCH model.

• Safety and Health at Work
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• v.13 no.3
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• pp.263-268
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• 2022

Health care workers (HCWs) are more than ten times more likely to be infected with coronavirus infectious disease 2019 (COVID-19) than the general population, thus demonstrating the burden of COVID-19 among HCWs. Factors that expose HCWs to a differentially high-risk of COVID-19 acquisition are important to elucidate, enable appropriate public health interventions to mitigate against high risk and reduce adverse outcomes from the infection. We conducted a systematic review and meta-analysis to summarize and critically analyze the existing evidence on SARS-CoV-2 risk factors among HCWs. With no geographical limitation, we included studies, in any country, that reported (i) the PCR laboratory diagnosis of COVID-19 as an independent variable (ii) one or more COVID-19 risk factors among HCWs with risk estimates (relative risk, odds ratio, or hazard ratio) (iii) original, quantitative study design, and published in English or Mandarian. Our initial search resulted in 470 articles overall, however, only 10 studies met the inclusion criteria for this review. Out of the 10 studies included in the review, inadequate/lack of protective personal equipment, performing tracheal intubation, and gender were the most common risk factors of COVID-19. Based on the random effects adjusted pooled relative risk, HCWs who reported the use of protective personal equipment were 29% (95% CI: 16% to 41%) less likely to test positive for COVID-19. The study also revealed that HCWs who performed tracheal intubations were 34% (95% CI: 14% to 57%) more likely to test positive for COVID-19. Interestingly, this study showed that female HCWs are at 11% higher risk (RR 1.11 95% CI 1.01-1.21) of COVID-19 than their male counterparts. This article presents initial findings from a living systematic review and meta-analysis, therefore, did not yield many studies; however, it revealed a significant insight into better understanding COVID-19 risk factors among HCWs; insights important for devising preventive strategies that protect them from this infection.

• Industry Promotion Research
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• v.9 no.2
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• pp.69-75
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• 2024

Korea has entered the ranks of advanced countries in terms of economic size and technological competitiveness. However, its industrial accident fatality rate remains among the lowest in OECD countries, and recent incidents such as various building collapses have resulted in numerous deaths of workers or citizens, reminiscent of accidents in developing countries. According to the 2022 Industrial Accident Status Analysis by the Ministry of Employment and Labor, out of the 874 fatalities in work-related accidents in 2022 across all industries, 402 were in the construction industry, accounting for approximately 46% of all fatalities. In particular, the construction industry's fatality rate stands at 1.61, significantly higher than the overall industry fatality rate of 0.43, indicating its severity. Construction ranks highest in terms of fatality rates, with mining at 12.18 and fishing at 1.80. When categorizing construction projects into private and public, private projects show significantly higher figures in terms of contracts, contract amounts, accident numbers, and fatalities compared to public projects. However, unlike public agencies, many private clients lack adequate safety and health activities and lack established safety and health systems. This study aims to raise awareness among private clients about the need to establish safety and health systems and enhance safety and health activities, and to discuss the direction of future development of advanced safety and health practices among private clients.

• Information Systems Review
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• v.22 no.2
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• pp.77-99
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• 2020

Smart speaker is a device that provides an interactive voice-based service that can search and use various information and contents such as music, calendar, weather, and merchandise using artificial intelligence. Since AI technology provides more sophisticated and optimized services to users by accumulating data, early smart speaker manufacturers tried to build a platform through aggressive marketing. However, the frequency of using smart speakers is less than once a month, accounting for more than one third of the total, and user satisfaction is only 49%. Accordingly, the necessity of strengthening the user experience of smart speakers has emerged in order to acquire a large number of users and to enable continuous use. Therefore, this study analyzes the user experience of the smart speaker and proposes a method for enhancing the user experience of the smart speaker. Based on the analysis results in two stages, we propose ways to enhance the user experience of smart speakers by model. The existing research on the user experience of the smart speaker was mainly conducted by survey and interview-based research, whereas this study collected the actual review data written by the user. Also, this study interpreted the analysis result based on the smart speaker user experience dimension. There is an academic significance in interpreting the text mining results by developing the smart speaker user experience dimension. Based on the results of this study, we can suggest strategies for enhancing the user experience to smart speaker manufacturers.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.