Ingoo Han

• Korea Advanced Institute of Science and Technology

Achieving the dual goal of improved environmental and financial performance has become a universal business concern. Our study distinguishes between firms’ environmental behaviors and their environmental performance, a distinction that has been largely disregarded in previous empirical studies that analyze the association between environmental perf...

The recent rapid transition in energy markets and technological advances in demand-side interventions has renewed attention on consumer behavior. A rich literature on potential factors affecting residential energy use or green technology adoption has highlighted the need to better understand the fundamental causes of consumer heterogeneity in build...

This study investigates the association between information asymmetry and the accrual anomaly. Prior literature argues that earnings management is pronounced among firms with high information asymmetry and that earnings management is the main phenomenon behind the accrual anomaly. Using 43 205 firm‐year observations from the CRSP/Compustat Merged (...

Investors use annual reports that companies mandatorily disclose every fiscal year-end when they make important investment-related decisions. The Securities and Exchange Commission in the United States has implemented and monitors the "Plain-English Rule" to create a transparent and readable annual report. However, only a general guideline exists f...

Purpose Social media have attracted attention as an information channel for content generated in heterogeneous internet services. Focusing on social media platforms, the purpose of this paper is to examine the factors behind social transmission with content crossover from other services through hypertext link (URL). The authors investigate the eff...

In response to the call for more research on impactful green IS, this paper examines one country-level environmental information disclosure system (EIDs), the U.S. Toxic Release Inventory (TRI), as a strategic tool or infrastructure of green IS and empirically tests the impact of environmental performance on financial performance in the chemical in...

Online communities' viability and success are dependent on current members' active participation and content contribution, as well as on the sustainable community registration of new members. Based on the member-life cycle perspective, this study attempted to discover mechanisms that might be employed to increase new members' community participatio...

The current study utilized regulatory focus theory to explain how online deliberations are processed differently depending on a participant’s information processing style and the characteristics of a discussion topic. An experiment was conducted to investigate the relationship between informational characteristics (hedonic vs. utilitarian) and atti...

Social media has attracted attention as an information channel for content generated in heterogeneous Internet services. Focusing on social media platforms, we examine the factors behind social transmission with content crossover from other services through hypertext link (URL). We investigate the effects of source influence and peer referrals on d...

This study investigates the association between information asymmetry and the accrual anomaly. Prior literature argues that earnings management is associated with information asymmetry (e.g., Dye, 1988; Schipper, 1989; Trueman and Titman, 1988) and that earnings management is the main phenomenon behind the accrual anomaly (e.g., Xie, 2001; Pincus e...

Attracting new users is critical for the success of new information and communication technologies (ICT) such as mobile data services (MDS). Given the rapid growth and large investments in ICT, it is important to understand the formation processes of user behaviors in the ICT environment. This study develops a theoretical framework to examine the r...

Purpose – With the increasing influence of online consumer reviews (OCRs) on a consumer's decision making, online sellers have begun to embed the OCRs in their advertisements (OEAs). This study has the following two research objectives: first, to investigate the effects of two types of (OCRs vs OEAs) on consumers' purchase intention from an informa...

Given the prevalence of community-driven knowledge sites (CKSs), such as Naver Knowledge In and Yahoo! Answers, it has become important to understand the key drivers of user decision-making processes. In the online environment, building and maintaining user trust belief is a significant challenge to the continuing growth and long-term viability of...

Rapid advancements in information and communication technologies (ICT) have allowed people some opportunities to access digitalized contents without restrictions in time or place. Mobile data service (MDS) is an important emerging ICT, thus many studies on information systems (IS) and marketing examine key predictors of MDS user behaviors. However,...

This study proposes a new and highly efficient dynamic combinatorial auction mechanism--the N-bilateral optimized combinatorial auction (N-BOCA). N-BOCA is a flexible iterative combinatorial auction model that offers more optimized trading for multiple suppliers and purchasers in the supply chain than one-sided combinatorial auction. We design the...

Mobile data services (MDS) are wireless value-added pay-per-use services that have attracted increased attention in recent years. In this paper, a theoretical framework is proposed to investigate key drivers of user behavior in wireless pay-per-use services based on a value perspective. This study examines the role of three evaluation criteria – ut...

Online discussion forum, which plays an important role in online criticism, provides useful information such as online commentaries generated by other users. The paper uses regulatory focus theory to explain how online commentaries are processed differently depending on the user's information processing style and how each self-regulatory mode moder...

Online consumer reviews provide product information and recommendations from the customer perspective. This study investigates the effects of negative online consumer reviews on consumer product attitude. In particular, it examines the proportion and quality of negative online consumer reviews from the perspective of information processing. The ela...

The economic in Taiwan has been dramatically improved in the last two decades. During this period, the national health insurance was first conducted in 1995 and plans of health insurance payment have been modified several times. Demands of high quality ...

Double auction refers to a market system where multiple buyers and sellers submit their bids for standardized units of well-defined items or securities by stating how much and at what price they will trade. In double auction, each trader can express the subjective preference for the traded goods by using a utility function. Thus, how to properly de...

This study investigates how consumers evaluate a product when they read conflicting online consumer reviews of evaluations from previous consumers. If consumers are rational, as is assumed in economics, they prefer the product with the low-variance of review-rating scores rather than the product with the high- variance of review-rating scores becau...

The online infomediary, playing an important role in e-commerce, provides more unbiased and refined product information than usual advertisement provided by online retailers. Interestingly, depending on its capability, the quality of product information is likely to differ. Also, given the fact that it enables consumers to grasp market price disper...

Given the rapid growth and large investments in mobile data services (MDS), it has become important to examine how to enhance satisfaction with MDS (M-satisfaction) and how to build loyalty toward MDS (M-loyalty). This paper develops an integrated model to deeply understand the antecedents of M-loyalty through constructs prescribed by two establish...

Mobile data services (MDS) are wireless value-added pay-per-use services that have attracted increased attention in recent years. In the marketing and information system (IS) disciples, the ability of a service provider to offer a high level of value to its customers is regarded as a success. In this paper, a theoretical framework is proposed to in...

A recommender system is a kind of automated and sophisticated decision support system that is needed to provide a personalized solution in a brief form without going through a complicated search process. There have been a substantial number of studies to make recommender systems more accurate and efficient, however, most of them have a common criti...

As the Internet spreads widely, it has become easier for companies to obtain and utilize valuable information on their customers. Nevertheless, many of them have difficulty in using the information effectively because of the huge amount of data from their customers that must to be analyzed. In addition, the data usually contains much noise due to a...

On-line consumer reviews, functioning both as informants and as recommenders, are important in making purchase decisions and for product sales. Their persuasive impact depends on both their quality and their quantity. This paper uses the elaboration likelihood model to explain how level of involvement with a product moderates these relationships. T...

Many studies have tried to optimize parameters of case-based reasoning (CBR) systems. Among them, selection of appropriate features to measure similarity between the input and stored cases more precisely, and selection of appropriate instances to eliminate noises which distort prediction have been popular. However, these approaches have been applie...

We investigated the effect of playfulness on user acceptance of online retailing and tested the relationship between Web quality factors and user acceptance behavior. A survey of 942 users of Web-based online retailing was conducted to test our model.The results showed that playfulness plays an important role in enhancing user attitude and behavior...

Collaborative procurement has been considered as a vital link in many world-class supply chain strategies. Most of the previous studies or real-cases related to the e-marketplace or auction based collaborative procurement just covered the purchasing of distinct items. However, each buyer may have the purchase needs for multiple heterogeneous items...

This paper investigates one type of electronic word-of-mouth (eWOM), the online consumer review. The study considers two com- ponents of review structure: the type and the number of reviews. Using the cognitive fit theory, we show that the type of reviews can be a key moderating variable to explain the inconsistent relationship between consumer exp...

Case-based reasoning (CBR) often shows significant promise for improving the effectiveness of complex and unstructured decision-making. Consequently, it has been applied to various problem-solving areas including manufacturing, finance and marketing. However, the design of appropriate case indexing and retrieval mechanisms to improve the performanc...

Bankruptcy prediction is an important and widely studied topic since it can have significant impact on bank lending decisions and profitability. Recently, the support vector machine (SVM) has been applied to the problem of bankruptcy prediction. The SVM-based method has been compared with other methods such as the neural network (NN) and logistic r...

Multiple classifier combination is a technique that combines the decisions of different classifiers. Combination can reduce the variance of estimation errors and improve the overall classification accuracy. However, direct application of combination schemes developed for pattern recognition to solving business problems has some limitations, because...

Because of its convenience and strength in complex problem solving, case-based reasoning (CBR) has been widely used in various areas. One of these areas is customer classification, which classifies customers into either purchasing or non-purchasing groups. Nonetheless, compared to other machine learning techniques, CBR has been criticized because o...

Understanding user acceptance of the Internet, especially the usage intention of virtual communities, is important in explaining the fact that virtual communities have been growing at an exponential rate in recent years. This paper studies the trust of virtual communities to better understand and manage the activities of E-commerce. A theoretical m...

Consumer endorsements have along been used as an advertising strategy, and now, it is also easy to see consumer endorsements in online shopping sites. A positive Online Consumer Review (OCR) is a consumer endorsement in the web site. Although the sources of both OCR and consumer endorsement in advertisement (CEA) are typical consumers, trust in the...

An online consumer review is the information including experiences, evaluations and opinions on products from the consumer perspective. An online consumer review plays two roles - informant and recommender. Considering two factors of review structure (the number of reviews and review type), this study analyzes the effect of online consumer reviews...

In this paper, we introduce a new combinatorial auction mechanism -N-Bilateral Optimized Combinatorial Auction (N-BOCA). N-BOCA is a flexible iterative combinatorial auction model that offers optimized trading for multi-suppliers and multi-purchasers in the supply chain. We design the N-BOCA system from the perspectives of architecture, protocol, a...

Due to the explosion of e-commerce, recommender systems are rapidly becoming a core tool to accelerate cross-selling and strengthen customer loyalty. There are two prevalent approaches for building recommender systems – content-based recommending and collaborative filtering (CF). This study focuses on improving the performance of recommender system...

Collaborative filtering (CF) is the most successful recom- mendation technique, which has been used in a number of different ap- plications. In traditional CF, the ratings of all items are equally weighted when similarity measure is calculated. But, if the importance of features (or items) is different respectively, feature weighting structure need...

Collaborative filtering is the most successful recommendation tech- nique. In this paper, we apply the concept of time to collaborative filtering algo- rithm. We propose dynamic fuzzy clustering algorithm and apply it to collabo- rative filtering algorithm for dynamic recommendations. We add a time dimen- sion to the original input data of collabor...

Credit scoring is one of the most successful applications of quantitative analysis that helps organizations decide whether or not to grant credit to consumers who apply to them. However, standard credit risk models based on binary classifying approaches appear to have missed several important time-varying factors and censoring information. This pap...

As the market competition becomes keen, constructing a customer relationship management system is coming to the front for winning over new customers, developing service and products for customer satisfaction and retaining existing customers. However, decisions for CRM implementation have been hampered by inconsistency between information technology...

Due to the explosion of e-commerce, recommender systems are rapidly becoming a core tool to accelerate cross-selling and strengthen customer loyalty. There are two prevalent approaches for building recommender systems—content-based recommending and collaborative filtering. So far, collaborative filtering recommender systems have been very successfu...

Various predictive modeling approaches based on the customers' information may be used for selecting proper targets for a promoted product to entice customers into purchasers. However, there is a fundamental problem, the incomplete data which can yield biased results and deteriorate the accuracy of those approaches. So far, several methods such as...

Case-based reasoning (CBR) has been applied to various problem-solving areas for a long time because it is suitable to complex and unstructured problems. However, the design of appropriate case retrieval mechanisms to improve the performance of CBR is still a challenging issue. In this paper, we encode the feature weighting and instance selection w...

Internet shopping mall has the dual nature of Web-based application system and traditional shopping mall. This paper explores online and offline features of Internet shopping malls and their relationships with the acceptance behaviors of customers. The results from a Web survey of 932 users show that the technology acceptance model (TAM) is valid i...

In this paper, we propose a method for integrating cognitive maps and neural networks to gain competitive advantage using qualitative information acquired from news information on the World Wide Web. We have developed the KBNMiner, which is designed to represent the knowledge of domain experts with cognitive maps, to search and retrieve news inform...

Intellectual capital (IC) has prevailed as a measure of core competency and competitive advantage which explains the gap between the market value and book value of an organization at a time of decreasing usefulness of current financial reporting. In spite of the importance of IC management (ICM), few applicable ICM methodologies have been addressed...

Information technology and the Internet have been major drivers for changes in all aspects of business processes and activities. They have brought major changes to the financial statements audit environment as well, which in turn has required modifications in audit procedures. There exist certain difficulties, however, with current audit procedures...

This paper proposes the hybrid knowledge integration mechanism using the fuzzy genetic algorithm for the optimized integration of knowledge from several sources such as machine knowledge, expert knowledge and user knowledge. This mechanism is applied to the prediction of the Korea stock price index. Machine knowledge is generated by applying neural...

The disruption of operations due to IS failure becomes more important as IS has become an increasingly essential component of the organization’s operations and can affect its strategic objectives. Nevertheless, traditional IS risk analysis methods do not adequately reflect the loss from disruption of operations in determining the value of IS assets...

Numerous studies on bankruptcy prediction have widely applied data mining techniques to finding out the useful knowledge automatically from financial databases, while few studies have proposed qualitative data mining approaches capable of eliciting and representing experts' problem-solving knowledge from experts' qualitative decisions. In an actual...

Collaborative filtering (CF) recommendation is a knowledge sharing technology for distribution of opinions and facilitating contacts in network society between people with similar interests. The main concerns of the CF algorithm are about prediction accuracy, speed of response time, problem of data sparsity, and scalability. In general, the efforts...

Recently, there has been much interest for knowledge sharing within professional group, especially physicians in hospital. This study investigates the factors affecting physician's knowledge sharing behavior within a hospital department by employing existing theories. The research models under investigation are the theory of reasoned action (TRA) a...

This paper investigates the asymmetric costs of false positive and negative errors to enhance the IDS performance. The proposed method utilizes the neural network model to consider the cost ratio of false negative errors to false positive errors. Compared with false positive errors, false negative errors incur a greater loss to organizations which...

The number of Internet users has increased dramatically,but many are reluctant to provide sensitive personal information to Web sites because they do not trust e-commerce security.This paper investigates the impact of customer perceptions of security control on e-commerce acceptance. Trust is examined as the mediating factor of the relationship, us...

This paper argues that the contingent evaluation approach can help an organization to evaluate the impact of information systems (IS) on business performance. The structure of IS is one of the most important factors in applying the contingent approach, because it reflects the evolution of the computing environment and is also aligned with business...

Activity-based costing (ABC) has received extensive attention since it achieves improved accuracy in estimating costs, by using multiple cost drivers to trace the cost of activities to the products associated with the resources consumed by those activities. However, it has some problems. The first problem is that ABC does not have general criteria...

Case-based reasoning (CBR) is a methodology for problem solving and decision-making in complex and changing business environments. Many CBR algorithms are derivatives of the k-nearest neighbor (k-NN) method, which has a similarity function to generate classification from stored cases. Several studies have shown that k-NN performance is highly sensi...

Two beliefs, ease of use and usefulness, have been considered to be fundamental in determining the acceptance of various IS in the past decades. These beliefs may not, however, fully explain the users’ behavior in an emerging environment such as Internet banking. In this study, we introduce trust as another belief that has an impact on the acceptan...

In this paper, we investigate ways to apply news information on the Internet to the prediction of interest rates. We developed the Knowledge-Based News Miner (KBNMiner), which is designed to represent the knowledge of interest rate experts with cognitive maps (CMs), to search and retrieve news information on the Internet according to prior knowledg...

Case-based reasoning (CBR) is a problem solving technique by re-using past cases and experiences to find a solution to problems. The central tasks involved in CBR methods are to identify the current problem situation, find a past case similar to the new one, use that case to suggest a solution to the current problem, evaluate the proposed solution,...

In recent years, a number of security problems with the Internet became apparent. New and current Internet users need to be aware of the likelihood of security incidents and the steps they should take to secure their sites. Before designing a secure system, it is advisable to identify the specific threats against which protection is required. The t...

This paper presents a hybrid data mining model for the prediction of corporate bond rating. This model uses a new case-indexing method of case-based reasoning (CBR), which utilizes the cluster information of financial data in order to improve classification accuracy. This method uses not only case-specific knowledge of past problems like convention...

The success of a case-based reasoning (CBR) system largely depends on an effective maintenance of its case-base. This study proposes a genetic algorithms (GAs) approach to the maintenance of CBR systems. This approach automatically determines the representation of cases and indexes relevant attributes to grasp the rapidly changing environment aroun...

We propose the rough set approach to the extraction of trading rules for discriminating between bullish and bearish patterns in the stock market. Rough set theory is quite valuable for extracting trading rules because it can be used to discover dependences in data while reducing the effect of superfluous factors in noisy data. In addition, it does...

We present a new protocol which allows multiple parties to exchange electronic items over the Internet in a secure and fair way. This allows either each party to get what it expects to receive, or neither party to receive anything. This protocol is applicable to various electronic businesses, for example, electronic shopping, group purchases, elect...

Suggests a new clustering forecasting system to integrate change-point detection and artificial neural networks. The basic concept of the proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to involve them in the forecasting model. The proposed models consist of two stages. The first stage (t...

The explosive growth of the virtual space such as Internet and on-line service networks as well as proprietary corporate networks will change the business environment of the 21st century fundamentally. Capability of the instantaneous communication among business partners and availability of the near perfect information on the marketplace will stren...

The growing popularity of electronic data interchange (EDI) in business operations has led to a growing recognition of the need to implement proper control procedures. The requirements for control systems vary according to organizational context. A research model proposes that the organization, technological, and task characteristics as well as par...

Electronic data interchange (EDI) has been increasingly adopted in Korean industries to facilitate their online transactions with customers and suppliers. We investigate organizational factors affecting successful implementation of EDI in current Korean industries. Regression models are developed and tested using survey results from 110 Korean comp...

This paper proposes genetic algorithms (GAs) approach to feature discretization and the determination of connection weights for artificial neural networks (ANNs) to predict the stock price index. Previous research proposed many hybrid models of ANN and GA for the method of training the network, feature subset selection, and topology optimization. I...

Interest rates are one of the most closely watched variables in the economy. They have been studied by a number of researchers as they strongly affect other economic and financial parameters. Contrary to other chaotic financial data, the movement of interest rates has a series of change points owing to the monetary policy of the US government. The...

The purpose of this paper is to introduce EDIRDB (EDI controls design support system using a relational database system), a prototype audit support system based on a relational database designed to act as a decision aid for EDI auditors. This paper describes how EDIRDB operates; explicates the manner in which a relational database is utilized to su...

Detecting the features of significant patterns from historical data is crucial for good performance in time-series forecasting. Wavelet analysis, which processes information effectively at different scales, can be very useful for feature detection from complex and chaotic time series. In particular, the specific local properties of wavelets can be...

Data filtering methods are so much crucial to get good performance in time series forecasting. There are a few preprocessing methods (i.e. ARMA outputs as time domain filters, and Fourier transform or wavelet transform as time-frequency domain filters) for handling time series. In particular, the time-frequency domain filters describe the fractal s...

EDI control design is ill-structured and demands consideration of the complex causal relationships among various components of the controls, which may be broadly classified into formal, informal, and automated types. Each of these can, in turn, be categorized as internal or external. However, it is difficult even for EDI experts to predict the caus...

The evaluation of EDI controls is important in ensuring the high performance of an EDI system. Although penetration level is strongly associated with performance, the benefits derived arise from the usage level of EDI controls. This suggests that EDI controls affect the relationship between EDI implementation and performance. Research hypotheses ha...

Wavelet analysis as a recently data filtering method (or multi-scale decomposition) is particularly useful for describing signals with sharp spiky, discontinuous or fractal structure in financial markets. This study investigates the optimal several wavelet thresholding criteria or techniques to support the multi-signal decomposition methods of a da...

Electronic commerce (EC) appears to be essential for an organization's survival and growth. Then the security of the EC systems, which ensures authorized and correct transaction processing, becomes one of the most critical issues in implementing the systems. The analysis of risk that a system faces is the core part of security management since risk...

A critical issue in case-based reasoning (CBR) is to retrieve not just a similar past case but a usefully similar case to the problem. For this reason, the integration of domain knowledge into the case indexing and retrieving process is highly recommended in building a CBR system. However, this task is difficult to carry out as such knowledge often...

Advances in EDI (Electronic Data Interchange) demand appropriate controls in order to realize the potential benefits from it. Formal, informal, and automated controls are basic parts of EDI controls. The state of one of three controls is suggested to affect performance indirectly through their effect on another controls in the research model. The c...

We propose a knowledge integration mechanism that yields a cooperated knowledge by integrating user knowledge, expert knowledge and machine knowledge within the fuzzy logic-driven framework, and then refines it with a fuzzy associative memory (FAM) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the...

Detecting the features of significant patterns from their own historical data is crucial in obtaining optimal performance, especially in time series forecasting. Wavelet analysis, which processes information effectively at different scales, can be very useful in accomplishing this. One of the most critical issues to be solved in the application of...

Integration of machine and human knowledge is more effective rather than a single kind of knowledge in solving unstructured problems. This paper proposes the knowledge integration of machine and human knowledge to achieve a better reasoning performance in the stock price index prediction problem. Causal model and the evaluation by experts generate...

This paper gives a description of EDICBR (EDI Controls design using Case-Based Reasoning), a case-based reasoning model for generating recommendations of EDI controls. The case base of EDICBR is composed of slots that include environmental and EDI controls. This system makes it possible to propose the EDI controls most needed in certain organizatio...

Electronic data interchange (EDI) has significantly changed business practices by eliminating paper and related audit trails and by allowing transactions to be processed at high speed without human intervention. The dependence of an organization on its trading partners and value-added network (VAN) increases with the number of partners and allows t...