• Asia pacific journal of information systems
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• v.17 no.4
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• pp.113-132
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• 2007

Price rigidity involves prices that do not change with the regularity predicted by standard economic theory. It is of long-standing interest for firms, industries and the economy as a whole. However, due to the difficulty of measuring price rigidity and price adjustments directly, only a few studies have attempted to provide empirical evidence for explanatory theories from Economics and Marketing. This paper proposes and validates a research model to examine different theories of price rigidity and to predict what variables can explain the observed empirical regularities and variations in price adjustment patterns of Internet-based retailers. I specify and test a model using more than 3 million daily observations on 385 books, 118 DVDs and 154 CDs, sold by 22 Internet-based retailers that were collected over a 676-day period from March 2003 to February 2005. I obtained a number of interesting findings from the estimation of our logit model. First, quality seems to play a role-I find that both price levels as proxies for store quality, and information on the quality of a product consumers have, affect online price rigidity. Second, greater competition(i.e., less industry concentration) leads to less price rigidity(i.e., more price changes) on the Internet. I also find that Internet-based sellers more frequently change the prices of popular products, and the sellers with broader product coverage change prices less frequently, which seem due to economic forces faced by these Internet-based sellers. To the best of my knowledge, this research is the first to empirically assess price rigidity patterns for multiple industries in Internet-based retailing, and attempt to explain the variation in these patterns. I found that price changes are more likely to be driven by quality, competitive and economic considerations. These results speak to both the IS and economics literatures. To the IS literature these results suggest we take economic considerations into account in more sophisticated ways. The existence and variation in price rigidity argue that simplistic assumptions about frictionless and completely flexible digital prices do not capture the richness of pricing behavior on the Internet. The quality, competitive and economic forces identified in this model suggest promising directions for future theoretical and empirical work on their role in these technologically changing markets. To the economics literature these results offer new evidence on the sources of price rigidity, which can then be incorporated into the development of models of pricing at the firm, industry and even macro-economic level of analysis. It also suggests that there is much to be learned through interdisciplinary research between the IS, economics and related business disciplines.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.41-52
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• 2002

Most investment evaluations and economic assessments of road transport proposals in Korea omit a valuation of the time spent in transit for loads of freight. These days there were few attempts to estimate value of freight travel-time savings in Korea, but most of them included rail or marine with statewide area so that couldn't obtain unique travel-time savings for road freight transport. This study applied revealed Preference method and associated binominal logit models to estimate the value of travel-time savings in transit from an statewide survey of road freight transport in 1997. Data sets were segmented according to transport areas and business types. The results of this study showed that the value of freight travel-time savings varied wide ranges from 53,449 won per hour in urban transport to 29,397 won per hour in regional transport, that the use of statewide value of freight travel-time savings can drives wrong results into economic assessment, and that the use of adequate value of freight travel-time savings according to assessment area is very important.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.65-79
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• 2006

The ATIS(Advance Traveler Information System), as one part of ITS, is a system aiming to disperse traffic volume on transportation networks by providing traffic information to transportation users on pre-trip and en-route trips. One of tools in ATIS is usage of VMS(Variable Message Signs). It provides to the drivers with direct information about state of processing direction. which is considered as the most effective method in ATIS. The purposes of providing VMS information are classified two categories. One is to provide simple information to drivers for their convenience. The other is to manage traffic demand to improve transportation network performance. However, for more effective and reliable VMS information, several strategies should be taken into account. The main VMS management strategy is "Traffic Diversion Strategy for minimum delay" when traffic congestion or incident are occurred. For effective operation. firstly. reasonable diversion traffic volume is determined by network traffic condition Secondly, it is necessary to make providing information strategy which reflects driver response behavior for controling diversion traffic volume. This paper focuses on the providing real-time route guidance information by VMS when congestion is occurred by the incidents. This sturdy estimates time-dependent system optimal diversion rate that inflects travel time and queue lengths using traffic flow simulation model on base Cellular Automata. In addition, route choice behavior models are developed using binary logit model for traffic information variable by traffic system controller. Finally, this study provides time-dependent VMS massage contents and degree of providing information in order to optimize the traffic flow.

• Korean Journal of Social Welfare
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• v.35
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• pp.85-105
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• 1998

This article examined the trend of 125 empirical researches which were published in Jr. of Korean Social Welfare from the first issue to no. 33. in terms of theoretical and methodological orientations. The content analysis was employed for the purpose of the study. Since 1979, the number of empirical researches was in the trend of increasing. The findings from this research were as follows. 1) Among 166 authors, 96.4% were majored in social welfare. Also 6.0% were practitioners and the rest of them were in the position of professors or researchers. The outcome of lack of interdisciplinary co-work and researcher-practitioner co-work led the article to conclude that the nature of applied social science of social welfare was not so actively pursued in Korea. 2) It was almost impossible to find researches which studied same theme or employed same analytical framework. This meant that the work of re-verifying and proving the contray could not be done although it was essential for theory-building. In other words, the disciplinary of social welfare was far behind in the process of theory-building. 3) The methodology upon which most of researches were relied was quantitative methodology(92.8%). The article concluded 'paradigm shift' was not begun in the disciplinary of social welfare yet. 4) The study concluded that the particularity of empirical researches of social welfare in Korea was descriptive-configurative study. Whereas 65.5% of 125 empirical studies were descriptive-configurative, 25% were hypothesis - model test and only 6% causal analysis. 5) The most applied statistic models through the period from 1979 to 1997 were descriptive statistics such as frequency, chi square test, Pearson's r. More advanced statistics such as logit regression, probit regression, path analysis, covariance structure analysis were shown since 1990.

• Korean Journal of Social Welfare
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• v.66 no.1
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• pp.251-276
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• 2014

This study scrutinizes the common sense in the field of disability employment that the bigger the size of a firm, the lower the employment rate of people with disabilities. This common sense has been established by conventional cross-tabulation and multiple regression analyses without taking into account possible interactions between the sizes of firms and the industries in which they operate. This study shows that the distribution of the disability employment rate violates the linearity and homoscedasticity assumptions of the OLS. In an effort to find models that explain the data better, this study fits the OLS model, the weighted linear regression model, and the multinomial logit model as well as the path analysis which is meant to examine the relationships between firm size and other variables relevant to disability employment. The result shows that, when an interaction term between firm size and industry is added to the model, firm size does not have any significant effect on disability employment rate for those firms with 100 or more regular employees, to the contrary of the findings of prior studies. It also demonstrates that other factors such as job setting, the extent of helpfulness of disability employment employers perceive, employers' care for disability, and employers' awareness of disability policies may matter more than does firm size. This study proposes that future research and policy implementation for disability employment should pay no less attention to industry and other factors mentioned above than to firm size.

• Journal of Intelligence and Information Systems
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• v.16 no.1
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• pp.93-116
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• 2010

Ensemble approach is applied to the detection modeling of illegal cash accommodation (ICA) that is the well-known type of fraudulent usages of credit cards in far east nations and has not been addressed in the academic literatures. The performance of fraud detection model (FDM) suffers from the imbalanced data problem, which can be remedied to some extent using an ensemble of many classifiers. It is generally accepted that ensembles of classifiers produce better accuracy than a single classifier provided there is diversity in the ensemble. Furthermore, recent researches reveal that it may be better to ensemble some selected classifiers instead of all of the classifiers at hand. For the effective detection of ICA, we adopt ensemble size reduction technique that prunes the ensemble of all classifiers using accuracy and diversity measures. The diversity in ensemble manifests itself as disagreement or ambiguity among members. Data imbalance intrinsic to FDM affects our approach for ICA detection in two ways. First, we suggest the training procedure with over-sampling methods to obtain diverse training data sets. Second, we use some variants of accuracy and diversity measures that focus on fraud class. We also dynamically calculate the diversity measure-Forward Addition and Backward Elimination. In our experiments, Neural Networks, Decision Trees and Logit Regressions are the base models as the ensemble members and the performance of homogeneous ensembles are compared with that of heterogeneous ensembles. The experimental results show that the reduced size ensemble is as accurate on average over the data-sets tested as the non-pruned version, which provides benefits in terms of its application efficiency and reduced complexity of the ensemble.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.113-129
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• 1999

It is widely recognized that the value of travel time (VOT) plays an important role both in choosing the transportation alternatives on an individual level, and in analyzing and evaluating transportation plans and other public policy makings on a collective level. There is, however, a great deal of difficulties to correctly estimate the VOT. In addition, although there are lots of methods to estimate the VOT so for, not many recommendations have been presented to reflect the localities associated with the VOT derivation in Korea. This study aims at deriving the VOT for different trip purposes and travel modes with their significances tested. To accomplish this purposes, a logit-based travel mode choice model based on revealed preference (RP) data has been formulated, calibrated using the discrete choice model of LIMDEP package for various trip purpose models. For each trip purpose and travel mode, the VOT has been calculated along with the significance testing of the derived VOTs. From the results given in this research, the VOTs for different purposes and modes are identified different, and they are statistically significant. The updated results here in this paper may be a yardstick in evaluating the transportation plans and policies by providing more detailed VOT information for different categories, especially in urban context.

• Journal of Family Relations
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• v.21 no.2
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• pp.129-147
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• 2016

Objective: This study examined the role of siblings with respect to living arrangements between married children and their parents. Previous studies have rarely considered the possibility that family context such as siblings may be associated with intergenerational residential proximity. Method: Using data from first wave of the Korean Longitudinal Study of Ageing (2006), I investigated if, among married children, their sibling characteristics may be associated with the probability of their coresiding with the parent(s), living nearby (within a 30-minute distance from parent(s) by public transportation), or living further away. Specifically, the total numbers of sisters and brothers, the numbers of siblings coresiding with the parent(s) and living nearby, their relative position in the sibling network (first-born son, later-born son, first-born daughter, later-born daughter), and sibship existence and gender configurations (only child, son with brother(s) only, son with sister(s) only, son with both brother(s) and sister(s), daughter with brother(s) only, daughter with sister(s) only, daughter with both brother(s) and sister(s)) were evaluated in the study. For data analysis, multinomial logit models with robust standard errors were estimated using the Stata mlogit procedure. Results: Results suggest that the probability of a married child living together with the parent(s), relative to living close by, was significantly higher the more sisters he or she has. Being a son, especially first-born son, was associated with a higher probability of intergenerational coresidence compared to near residence, respectively. Also, the numbers of siblings coresiding with the parent(s) and living in close proximity were linked to a higher risk of intergenerational coresidence and near residence. Supplementary analyses revealed that the last finding was held over and above the total number of siblings, their relative position in the sibling network, as well as sibling existence and gender configurations. Conclusion: Overall, the study findings indicate that sibling characteristics have significant impacts on intergenerational living arrangement. The influence of traditional patrilineal norm of intergenerational coresidence and a trend towards modified extended family have emerged when siblings characteristics are taken into consideration as determinants of intergenerational living arrangement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.248-258
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• 2021

The study analyzed the financial determinants of corporate R&D intensity that require more attention from academics and practitioners in the Korean capital market. Domestic small and medium enterprises (SMEs) may face with developing substitutes by making more R&D investments in scale and scope, given the unprecedented economic conditions such as the limitation of importing core components and materials from other nation(s). KOSDAQ-listed SMEs were selected as sample data, whose R&D expenditures may be less than those of large firms during the post-global financial turmoil period (2010~2018). Static panel data model was applied, along with Tobit and stepwise regression models, for examining the validity of results. Logit, probit, and complementary log-log regressions were also employed for a relative analysis. R&D expenditures in the prior year, the interaction effect between the previous R&D intensity and high-tech sector, firm size, and growth rate were significant to determine R&D intensity. Moreover, a majority of explanatory variables were found to change between the years 2011 and 2018, while time-lagged effects between the R&D intensity and growth rate exist. Results of the study are expected to be used for future research to detect optimal levels of R&D expenditures for the value maximization of SMEs.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.347-364
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• 2022

Fraudulent companies or sellers strategically manipulate reviews to influence customers' purchase decisions; therefore, the reliability of reviews has become crucial for customer decision-making. Since customers increasingly rely on online reviews to search for more detailed information about products or services before purchasing, many researchers focus on detecting manipulated reviews. However, the main problem in detecting manipulated reviews is the difficulties with obtaining data with manipulated reviews to utilize machine learning techniques with sufficient data. Also, the number of manipulated reviews is insufficient compared with the number of non-manipulated reviews, so the class imbalance problem occurs. The class with fewer examples is under-represented and can hamper a model's accuracy, so machine learning methods suffer from the class imbalance problem and solving the class imbalance problem is important to build an accurate model for detecting manipulated reviews. Thus, we propose an OpenAI-based reviews generation model to solve the manipulated reviews imbalance problem, thereby enhancing the accuracy of manipulated reviews detection. In this research, we applied the novel autoregressive language model - GPT-3 to generate reviews based on manipulated reviews. Moreover, we found that applying GPT-3 model for oversampling manipulated reviews can recover a satisfactory portion of performance losses and shows better performance in classification (logit, decision tree, neural networks) than traditional oversampling models such as random oversampling and SMOTE.