• Information Systems Review
• /
• v.11 no.2
• /
• pp.23-44
• /
• 2009

U-Services are inevitably essential for the realization of u-Cities. Most local governments in Korea have expressed much interest in introducing u-Cites and related u-Services. Since researchers anticipate that developing u-Cities will produce economic effects, the Korea government has support local governments to develop u-Cities and necessary u-Services. However, the technology issues have been dominiated in the field of U-City services and most of the U-City services do not reflects all the complicated and pluralistic sides of environment, which are caused by future uncertainties in developing u-Cites. For the purpose of addressing the above uncertainties, this paper attempts to develop the possible scenarios for U-City services through a scenario planning approach. A focus group interview and survey with professionals in the field of planning u-Cities was performed to identify these uncertainties. Then, in order to investigate the validity of the scenario planning methodology, the u-Service "u-Water purity monitoring" is adopted. After considering the relevant issues, we developed two possible scenarios: a mutual linkage service among u-Service related organization and a cooperating and coordinating service among local governments. On the basis of these scenarios, the strategies for potential U-City services are formulated. Various participants in developing U -City services are encouraged to use the scenarios as the foundation of predicting future features of u-Cities and developing the framework of the U-City service scenarios effectively.

• The Journal of Society for e-Business Studies
• /
• v.15 no.3
• /
• pp.99-129
• /
• 2010

The objective of this research is to identify the factors which influence users' intention to use mobile Internet. There are lots of researches based on Technology Acceptance Model trying to identify the factors which have influence on accepting mobile Internet and its related services. These researches, however, have some limitation in the sense that they focus only on the features of mobile Internet itself while users make overall decision after the comparison of a new service channel with existing service channels in many directions. Therefore, we are going to analyze the impact of users' perception on the difference between mobile and stationary Internet toward their intention to use mobile Internet. We identified the features like ubiquitous availability, context awareness, compatibility, friendliness, and economic value from literature review and developed a structural model about the impact of users' perception on the differences of these features between mobile and stationary Internet toward their intention to use mobile Internet through mediate variables such as perceived ease of use, perceived playfulness, and perceived usefulness. After that, we conducted an experimental analysis for the model, and addressed a solution to rev up the usage of mobile Internet based on the results of the analysis.

• The Journal of Society for e-Business Studies
• /
• v.18 no.2
• /
• pp.153-173
• /
• 2013

The ontology has been gaining increasing interests by recent arise of the semantic web and related technologies. The focus is mostly on inference query processing that requires high-level techniques for storage and searching ontologies efficiently, and it has been actively studied in the area of semantic-based searching. W3C's recommendation is to use RDFS and OWL for representing ontologies. However memory-based editors, inference engines, and triple storages all store ontology as a simple set of triplets. Naturally the performance is limited, especially when a large-scale ontology needs to be processed. A variety of researches on proposing algorithms for efficient inference query processing has been conducted, and many of them are based on using proven relational database technology. However, none of them had been successful in obtaining the complete set of inference results which reflects the five characteristics of the ontology properties. In this paper, we propose a new index structure called hyper cube index to efficiently process inference queries. Our approach is based on an intuition that an index can speed up the query processing when extensive inferencing is required.

• Journal of Intelligence and Information Systems
• /
• v.13 no.4
• /
• pp.1-16
• /
• 2007

According to the expansion of the Internet use and the utilization of e-business, there are an increasing number of studies of intelligent-based systems for the preparation of ubiquitous environment. In addition, expert systems have been developed from Stand Alone types to web-based Client-Server types, which are now used in various Internet environments. In this paper, we investigated the environment of development for web-based expert systems, we classified and analyzed them according to type, and suggested general typical models of web-based expert systems and their architectures. We classified the web-based expert systems with two perspectives. First, we classified them into the Server Oriented model and Client Oriented model based on the Load Balancing aspect between client and server. Second, based on the degree of knowledge and inference-sharing, we classified them into the No Sharing model, Server Sharing model, Client Sharing model and Client-Server Sharing model. By combining them we derived eight types of web-based expert systems. We also analyzed the location problems of Knowledge Bases, Fact Bases, and Inference Engines on the Internet, and analyzed the pros & cons, the technologies, the considerations, and the service types for each model. With the framework proposed from this study, we can develop more efficient expert systems in future environments.

• 한국벤처창업학회:학술대회논문집
• /
• 2008.11a
• /
• pp.257-282
• /
• 2008

RFID (Radio Frequency Identification) is regarded as a core technology of ubiquitous computing. Although it has some technical limitations such as technological standardization of RFID tags as well as economical limitations, many companies around the world have already accepted RFID to improve their management efficiency. In this regard, this study is to meet with results that the adoption of RFID technology willbring opportunities that companies' operational process are improved and customer satisfaction is highly strengthened. This research focuses on providing more understanding for building RFID marketing strategy to suppliers who want to sell their RFID products to customers through analyzing purchasing process. The findings are as follows; First, the study shows that buying center members usually take product reliability and precision of technical specification in the case of new-task buying situation while they put their first purchasing priority on prices in the straight rebuy. Second, the finding presents that in new-task buying situation and the straight rebuy purchasing personnel get information about new products through product performance test, organizational engineers, opinions from other companies' purchasing personnel, and checking out samples. Third, this research demonstrates when it comes to purchasing risk in their first purchasing, the persons who are in charge of material purchasing are inclined to be aware of the risk most in technical problems, followed by financial problems and time delay problems in order. And in addition to those risks are mentioned above, once-again-purchasers take the risk like an opportunity loss for better products into consideration. Fourth, the study shows that the role of concerning departments makes no difference in each purchasing stage. Accordingly marketers need to beef up the differentiated strategy to persuade their customers. Fifth, the findings of this study demonstrate that purchasing decision making is much influenced by the final users. So suppliers are supposed to perform the most active marketing strategy at the first stage of purchasing through various resources. Finally, the study presents that the suppliers who will have had close relationships with their customers need to give consistent information to them so that their customers can have lower motive in purchasing products from competitors.

• The Journal of Society for e-Business Studies
• /
• v.25 no.4
• /
• pp.33-60
• /
• 2020

Along with the rapid advance in internet technologies, ubiquitous mobile device usage has enabled consumers to access real-time information and increased interaction with others through various social media. Consumers can now get information more easily when making purchase decisions, and these changes are affecting the brand landscape. In a digitally connected world, brand image is not communicated to the consumers one-sidedly. Rather, with consumers' growing influence, it is a result of co-creation where consumers have an active role in building brand image. This explains a reality where people no longer purchase products just because they know the brand or because it is a famous brand. However, there has been little discussion on the matter, and many practitioners still rely on the traditional measures of brand indicators. The goal of this research is to present the limitations of traditional definition and measurement of brand and brand image, and propose a more direct and adequate measure that reflects the nature of a connected world. Inspired by the proverb, "A man is known by the company he keeps," the proposed measurement offers insight to the position of brand (or brand image) through co-purchased product networks. This paper suggests a framework of network analysis that clusters brands of cosmetics by the frequency of other products purchased together. This is done by analyzing product networks of a brand extracted from actual purchase data on Amazon.com. This is a more direct approach, compared to past measures where consumers' intention or cognitive aspects are examined through survey. The practical implication is that our research attempts to close the gap between brand indicators and actual purchase behavior. From a theoretical standpoint, this paper extends the traditional conceptualization of brand image to a network perspective that reflects the nature of a digitally connected society.

• Journal of Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.1-19
• /
• 2010

In offline environment, unlike traditional advertising model through TV, newspaper, and radio, online advertising model draws instantaneous responses from potential consumers and it is convenient to assess. This kind of characteristics of Internet advertising model has driven the growth of advertising model among various Internet business models. There are, conventionally classified, CPM (Cost Per Mile), CPC (Cost Per Click), and CPS (Cost Per Sales) models as Internet advertising expenditure model. These can be examined in manners regarding risks that stakeholders should stand and degree of responsibility. CPM model that is based on number of advertisement exposure is mechanically exposed to users but not actually recognized by users resulting in risk of wasted expenditure by advertisers without any advertising effect. While on aspect of media, CPS model that is based on conversion action is the most risky model because of the conversion action such as product purchase is determined by capability of advertisers not that of media. In this regard, while there are issue of CPM and CPS models disadvantageously affecting only one side of Internet advertising business model value network, CPC model has been evaluated as reasonable both to advertisers and media, and occupied the largest segment of Internet advertising market. However, CPC model also can cause fraudulent behavior such as click fraud because of the competition or dishonest amount of advertising expenditure. On the user aspect, unintentionally accessed advertisements can lead to more inappropriate expenditure from advertisers. In this paper, we suggest "CPCD"(Cost Per Coupon Download) model. This goes beyond simple clicking of advertisements and advertising expenditure is exerted when users download a coupon from advertisers, which is a concept in between CPC and CPS models. To achieve the purpose, we describe the scenario of advertiser perspective, processes, participants and their benefits of CPCD model. Especially, we suggest the new value in online coupon; "possibility of storage" and "complement for delivery to the target group". We also analyze the working condition for advertiser by a comparison of CPC and CPCD models through advertising expenditure simulation. The result of simulation implies that the CPCD model suits more properly to advertisers with medium-low price products rather than that of high priced goods. This denotes that since most of advertisers in CPC model are dealing with medium-low priced products, the result is very interesting. At last, we contemplate applicability of CPCD model in ubiquitous environment.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.109-130
• /
• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of Intelligence and Information Systems
• /
• v.20 no.3
• /
• pp.1-18
• /
• 2014

Over the past years RFID/SN has been an elementary technology in a diversity of applications for the ubiquitous environments, especially for Internet of Things. However, one of obstacles for widespread deployment of RFID technology is the inherent unreliability of the RFID data streams by tag readers. In particular, the problem of false readings such as lost readings and mistaken readings needs to be treated by RFID middleware systems because false readings ultimately degrade the quality of application services due to the dirty data delivered by middleware systems. As a result, for the higher quality of services, an RFID middleware system is responsible for intelligently dealing with false readings for the delivery of clean data to the applications in accordance with the tag reading environment. One of popular techniques used to compensate false readings is a sliding window filter. In a sliding window scheme, it is evident that determining optimal window size intelligently is a nontrivial important task in RFID middleware systems in order to reduce false readings, especially in mobile environments. In this paper, for the purpose of reducing false readings by intelligent window adaption, we propose a new adaptive RFID data cleaning scheme based on window sliding for a single tag. Unlike previous works based on a binomial sampling model, we introduce the weight averaging. Our insight starts from the need to differentiate the past readings and the current readings, since the more recent readings may indicate the more accurate tag transitions. Owing to weight averaging, our scheme is expected to dynamically adapt the window size in an efficient manner even for non-homogeneous reading patterns in mobile environments. In addition, we analyze reading patterns in the window and effects of decreased window so that a more accurate and efficient decision on window adaption can be made. With our scheme, we can expect to obtain the ultimate goal that RFID middleware systems can provide applications with more clean data so that they can ensure high quality of intended services.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.73-91
• /
• 2013

Advertising market has been facing new challenges due to dramatic change in advertising channels and the advent of innovative media such as mobile devices. Recent research related to mobile devices is mainly focused on the fact that mobile devices could identify users'physical location in real-time, and this sheds light on how location-based technology is utilized to achieve competitive advantage in advertising market. With the introduction of smartphone, the functionality of smartphone has become much more diverse and context awareness is one of the areas that require further study. This work analyses the influence of context awareness value resulted from the transformation of advertising channel in mobile communication market, and our research result reflects recent trend in advertising market environment which is not considered in previous studies. Many constructs has intensively been studied in the context of advertising channel in traditional marketing environment, and entertainment, irritation and information are considered to be the most widely accepted variables that has positive relationship with advertising value. Also, in smartphone advertisement, four main dimensions of context awareness value are recognized: identification, activity, timing and location. In this study, we assume that these four constructs has positive relationship with context awareness value. Finally, we propose that advertising value and context awareness value positively influence smartphone advertising attitude. Partial Least Squares (PLS) structural model is used in our theoretical research model to test proposed hypotheses. A well designed survey is conducted for college students in Korea, and reliability, convergent validity and discriminant validity of constructs and measurement indicators are carefully evaluated and the results show that reliability and validity are confirmed according to predefined statistical criteria. Goodness-of-fit of our research model is also supported. In summary, the results collectively suggest good measurement properties for the proposed research model. The research outcomes are as follows. First, information has positive impact on advertising value while entertainment and irritation have no significant impact. Information, entertainment and irritation together account for 38.8% of advertising value. Second, along with the change in advertising market due to the advent of smartphone, activity, timing and location have positive impact on context awareness value while identification has no significant impact. In addition, identification, activity, location and time together account for 46.3% of context awareness value. Third, advertising value and context awareness value both positively influence smartphone advertising attitude, and these two constructs explain 31.7% of the variability of smartphone advertising attitude. The theoretical implication of our research is as follows. First, the influence of entertainment and irritation is reduced which are known to be crucial factors according to previous studies related to advertising value, while the influence of information is increased. It indicates that smartphone users are not likely interested in entertaining effect of smartphone advertisement, and are insensitive to the inconvenience due to smartphone advertisement. Second, in today' ubiquitous computing environment, it is effective to provide differentiated advertising service by utilizing smartphone users'context awareness values such as identification, activity, timing and location in order to achieve competitive business advantage in advertising market. For practical implications, enterprises should provide valuable and useful information that might attract smartphone users by adopting differentiation strategy as smartphone users are sensitive to the information provided via smartphone. Also enterprises not only provide useful information but also recognize and utilize smarphone users' unique characteristics and behaviors by increasing context awareness values. In summary, our result implies that smartphone advertisement should be optimized by considering the needed information of smartphone users in order to maximize advertisement effect.