• 대한산업공학회지
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• 제21권3호
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• pp.409-428
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• 1995

Job shop scheduling with m different machines and n different jobs is a NP-hard problem of combinatorial optimization. The purpose of the paper is to develop the heuristic method using tabu search for job shop scheduling to minimize makespan or mean flowtime. To apply tabu search to job shop scheduling problem, in this paper we propose the several move methods that employ insert moves in order to generate the neighbor solutions, and present the efficient rescheduling procedure that yields active schedule for a changed operation sequence by a move of operations. We also discuss the tabu search techniques of diversifying the search of solution space as well as the simple tabu search. By experiments, we find the appropriate tabu list size and tabu attributes, and analyze the proposed tabu search techniques with respect to the quality of solutions and the efforts of computation. The experimental results show that the proposed tabu search techniques using long-term memory function have the ability to search a good solution, and are more efficient in the mean flowtime minimization problem than in the makespan minimization.

• 한국IT서비스학회지
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• 제11권3호
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• pp.103-127
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• 2012

With the advent of SNS (Social Network Services), the product reviews by friends in SNS are intensively utilized for online marketing. However, there is a lack of empirical evidence on the actual marketing effect of SNS reviews, although we need to identify who can be the target of SNS marketing in terms of customer attributes, preferences, or experiences. In this study, we investigate the moderating role of customer attributes in identifying the effect of SNS reviews on customer purchasing decision. As the moderating variables, we adopt 'information search experience' and 'perception of information overload'. Research results evidence that, in order to understand the effect of SNS reviews in a comprehensive manner, we need to examine it in the context of various related factors such as 'information search experience' and 'perception of information overload'. The results show that the persuading effect of SNS reviews for product purchasing is stronger for the customers with the lower information search experiences as well as the lower perception on the information overload on the web. This result delivers managerial implications on who can be the target customers of SNS marketing.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.686-687
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• 2022

기존의 의류 상품 검색은 텍스트 검색만으로 가능하여 사용자가 찾고자 하는 상품 검색이 제대로 이루어지지 않고, 원하는 상품 검색을 하기 위해 많은 시간이 걸렸다. 또한 소호몰 상품과 같이 브랜드 없는 상품 판매처를 알기 어려웠으며 패션 상품의 디테일한 속성을 검색하기도 어려웠다. 이를 해결하기 위해 학습된 이미지 검색을 통해 사용자가 원하는 정확한 정보를 검색할 수 있는 딥러닝 기법을 제안하고자 한다.

• Journal of Information Technology Applications and Management
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• 제10권4호
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• pp.29-50
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• 2003

This research provide the basic information to enhance the user-orientedness of usability design guidelines for software products and an effective empirical guidance to classify design attributes of internet shopping mall sites. The results of analysis show that design attributes can be classified into the procedural attribute group, the shopping tool attribute group, the visual attribute group, linguistic attribute group, and others. The results show that shopping tool attribute group can be divided further into the search tool attribute group and purchase tool attribute group and that the visual attribute group can be divided further into the screen condition attribute group and the character legibility attribute group. The research reveals that when designers design software interfaces and features they should take the compound effect of a group of design attributes into consideration to enhance the usability of the system.

• 한국의류학회지
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• 제28권11호
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• pp.1482-1494
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• 2004

This study identified convergent validity and discriminant validity of measurement variables by factor analysis using Spss program and tested covariance measurement model including latent variables such as the website attributes (interactivity, search and visual information of website), shopping values(utilitarian and hedonic value) and attitude toward website by AMOS program. The data were collected from a sample of 271 internet shopper of university students(male: 82, female: 189). They visited the website for apparel shopping and, after searching a casual clothing which they wanted to buy, requested to answer the questionnaire. The results were as follows: Variables that reduce validity were deleted in the several steps of factor analysis and initial measurement model testing. Final measurement model was constructed by valid variables was accepted. This measurement model will be input for testing causal research model that can explain how attributes of the website influences on consumer attitude toward the website.

• 대한가정학회지
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• 제35권3호
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• pp.77-88
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• 1997

The purpose of this study was to examine the models of apparel store patronage behavior of various store types for each of two clothing categories in terms of lifestyle activities, information sources, shopping orientations and store attributes. The data were collected via a questionnaire from 326 adult females of ages over 20's living in satellite cities around Seoul and were analyzed by factor analysis, Multiple Regression analysis and path analysis. The results of this study were as follows: 1) There were significant relationships between lifestyle activities, information sources, shopping orientations and store attributes in both of formal wear and casual wear purchase. 2) Patronage behavior of department store in formal wear purchase was influenced by shopping activities, personal information sources, brand/store loyalty orientation. Regional store preference and store image attributes influenced the franchise store patronage behavior in formal wear purchase. Discount store patronage behavior in formal wear purchase was predicted by self-assurance/innovativeness and store image and service attributes. Information search of printed material/TV and store image and service attributes influenced off-price store patronage behavior for formal wear, while shopping activities and department store preference influenced off-price store patronage for casual wear. Traditional market patronage behavior for formal were was influenced only by brand/store loyalty, while traditional market patronage behavior for casual wear was influenced by sports activities, brand/store loyalty and price attributes.

• 한국정보처리학회논문지
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• 제3권6호
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• pp.1542-1552
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• 1996

본 논문에서는 문서 화일링 및 검색(DFR:Document Filing and Retrieval) 시스템 에서 DFR 객체의 속성(attribute)을 체계적으로 관리하여 DFR 객체의 효율적인 탐색 (search) 기능을 제공하기 위한 확장된 디렉토리 시스템의 설계 및 구현에 관하여 논 한다. 이를 위하여 DFR 시스템과 디렉토리 시스템 상호연동을 위한 구성 모델 및 두 응용 시스템 동작들 사이의 연계 매카니즘, 확장된 디렉토리 스키마(schema), 확장된 데릭토리 트리 구조(DIT:Directory Information Tree) 를 설계, 구현한다. 분산 환경 하에서 DFR 시스템과 ISODE(ISO Development Environment) 디렉토리 시스템인 QUIPU 8.0을 이용하여 구현한 확장된 디렉토리 시스템 사이의 연동 시험을 하고 본 논문의 결과를 기반으로 다양한 응용 시스템의 객체 탐색을 위한 확장된 디렉토리 시스템 모 델을 제시한다.

• Asia pacific journal of information systems
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• 제24권4호
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• pp.493-513
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• 2014

With the development of related technologies, Location-Based Services (LBS) are growing fast and being used in many ways. Past LBS studies have focused on adoption of LBS because of the fact that LBS users have privacy concerns regarding revealing their location information. Meanwhile, the number of LBS users and revenues from LBS are growing rapidly because users can get some benefits by revealing their location information. Little research has been done on how LBS affects consumers' information search behavior in product purchase. The purpose of this paper is examining the effect of LBS information filtering on buyers' uncertainty and their information search behavior. When consumers purchase a product, they try to reduce uncertainty by searching information. Generally, there are two types of uncertainties - knowledge uncertainty and choice uncertainty. Knowledge uncertainty refers to the lack of information on what kinds of alternatives are available in the market and/or their important attributes. Therefore, consumers having knowledge uncertainty will have difficulties in identifying what alternatives exist in the market to fulfil their needs. Choice uncertainty refers to the lack of information about consumers' own preferences and which alternative will fit in their needs. Therefore, consumers with choice uncertainty have difficulties selecting best product among available alternatives.. According to economics of information theory, consumers narrow the scope of information search when knowledge uncertainty is high. It is because consumers' information search cost is high when their knowledge uncertainty is high. If people do not know available alternatives and their attributes, it takes time and cognitive efforts for them to acquire information about available alternatives. Therefore, they will reduce search breadth. For people with high knowledge uncertainty, the information about products and their attributes is new and of high value for them. Therefore, they will conduct searches more in-depth because they have incentive to acquire more information. When people have high choice uncertainty, people tend to search information about more alternatives. It is because increased search breadth will improve their chances to find better alternative for them. On the other hand, since human's cognitive capacity is limited, the increased search breadth (more alternatives) will reduce the depth of information search for each alternative. Consumers with high choice uncertainty will spend less time and effort for each alternative because considering more alternatives will increase their utility. LBS provides users with the capability to screen alternatives based on the distance from them, which reduces information search costs. Therefore, it is expected that LBS will help users consider more alternatives even when they have high knowledge uncertainty. LBS provides distance information, which helps users choose alternatives appropriate for them. Therefore, users will perceive lower choice uncertainty when they use LBS. In order to test the hypotheses, we selected 80 students and assigned them to one of the two experiment groups. One group was asked to use LBS to search surrounding restaurants and the other group was asked to not use LBS to search nearby restaurants. The experimental tasks and measures items were validated in a pilot experiment. The final measurement items are shown in Appendix A. Each subject was asked to read one of the two scenarios - with or without LBS - and use a smartphone application to pick a restaurant. All behaviors on smartphone were recorded using a recording application. Search breadth was measured by the number of restaurants clicked by each subject. Search depths was measured by two metrics - the average number of sub-level pages each subject visited and the average time spent on each restaurant. The hypotheses were tested using SPSS and PLS. The results show that knowledge uncertainty reduces search breadth (H1a). However, there was no significant correlation between knowledge uncertainty and search depth (H1b). Choice uncertainty significantly reduces search depth (H2b), but no significant relationship was found between choice uncertainty and search breadth (H2a). LBS information filtering significantly reduces the buyers' choice uncertainty (H4) and reduces the negative relationship between knowledge uncertainty and search breadth (H3). This research provides some important implications for service providers. Service providers should use different strategies based on their service properties. For those service providers who are not well-known to consumers (high knowledge uncertainty) should encourage their customers to use LBS. This is because LBS would increase buyers' consideration sets when the knowledge uncertainty is high. Therefore, less known services have chances to be included in consumers' consideration sets with LBS. On the other hand, LBS information filtering decrease choice uncertainty and the near service providers are more likely to be selected than without LBS. Hence, service providers should analyze geographically approximate competitors' strength and try to reduce the gap so that they can have chances to be included in the consideration set.

• 지식경영연구
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• 제16권1호
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• pp.95-115
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• 2015

This paper attempts to delineate and analyze the relationship between organizational search activities and organizational ambidexterity. A growing number of studies confirm that organizational ambidexterity is important for firm survival and long-term prosperity. However, research on how to achieve ambidexterity is still limited. To date, structural separation, contextul ambidexterity, and top management team attributes are proposed and examined as major antecedents of organizational ambidexterity. In this paper, I argue that orgnizational search may influence ambidexterity through its effect on exxploratory innovation and exploitative innovation. Since little study has been paid to uncover the relationship between knowledge search and ambidexterity, I develop theoretical arguments and propose some propositions rather than examine hypotheses. The propositions developed in the study are as follows; P1: The breadth of internal search is positively associated with exploratory innovation; P2: The breadth of external search has a reverse U-shaped relationship with exploratory innovation; P3: The depth of internal search is positively associated with exploitative innovation; P4: The depth of external search has a reverse U-shaped relationship with exploitative innovation; P5: The interaction between internal search breadth and internal search depth is positively associated with organizational ambidexterity; P6: The interaction between external search breadth and external search depth is positively associated with organizational ambidexterity. Based on the above propositions, I suggest some considerations for empirical research and propose avenues for future research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.744-768
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• 2016

As various pieces of information can be provided through the web, schemes that provide search results optimized for individual users are required in consideration of user preference. Since the existing social search schemes use users' profiles, the accuracy of the search deteriorates. They also decrease the reliability of a search result because they do not consider a search time. Therefore, a new social search scheme that considers temporal information as well as popularities and user preferences is required. In this paper, we propose a new mobile social search scheme considering popularities and user preferences based on temporal information. Popularity is calculated by collecting the visiting records of users, while user preference is generated by the actual visiting information among the search results. In order to extract meaningful information from the search target objects that have multiple attributes, a skyline processing method is used, and rank is given to the search results by combining the user preference and the popularity with the skyline processing result. To show the superiority of the proposed scheme, we conduct performance evaluations of the existing scheme and the proposed scheme.