• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.8
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• pp.1164-1171
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• 2011

The purpose of this study was to compare service quality between local and global coffee brand shops and to investigate improvement. Of 350 questionnaires distributed to customers of six brand coffee shops (three local brands, three global brands) located in Daejeon, 330 complete questionnaires (94.3%) were analyzed. The questionnaire included a seven-point multiple-item scale for measuring service quality. The 21 items measuring service quality were grouped into four factors, and the mean scores for the levels of "representativeness", "coffee sensory and beverage features", "employee attitude" and "physical environment" were 5.42, 4.77, 4.74, and 4.13, respectively. The levels of "coffee sensory and beverage features" and "employee attitude" of the high income customers were significantly lower than those of the low income customers. The results showed that the levels of "employee attitude" of local coffee brand shops was significantly higher (p=0.050) than that of global coffee brand shops. Whereas, the levels of "representativeness" of global coffee brand shops was significantly higher (p=0.003) than that of local coffee brand shops. Based on the results, the global coffee brand shops should pay attention to internal marketing and the local coffee brand shops must strive to improve service quality through strategies such as improving brand awareness and developing representative beverages and foods.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.28 no.5
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• pp.375-395
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• 2006

Purpose: Lingual nerve (LN) damage may be caused by either tumor resection or injury such as wisdom tooth extraction, Although autologous nerve graft is sometimes used to repair the damaged nerve, it has the disadvantage of necessity of another operation for nerve harvesting. Moreover, the results of nerve grafting is not satisfactory. The nerve growth factor (NGF) is well-known to play a critical role in peripheral nerve regeneration and its local delivery to the injured nerve has been continuously tried to enhance nerve regeneration. However, its application has limitations like repeated administration due to short half life of 30 minutes and an in vivo delivery model must allow for direct and local delivery. The aim of this study was to construct a well-functioning $rhNGF-{\beta}$ adenovirus for the ultimate development of improved method to promote peripheral nerve regeneration with enhanced and extended secretion of hNGF from the injured nerve by injecting $rhNGF-{\beta}$ gene directly into crush-injured LN in rat model. Materials and Methods: $hNGF-{\beta}$ gene was prepared from fetal brain cDNA library and cloned into E1/E3 deleted adenoviral vector which contains green fluorescence protein (GFP) gene as a reporter. After large scale production and purification of $rhNGF-{\beta}$ adenovirus, transfection efficiency and its expression at various cells (primary cultured Schwann cells, HEK293 cells, Schwann cell lines, NIH3T3 and CRH cells) were evaluated by fluorescent microscopy, RT-PCR, ELISA, immunocytochemistry. Furthermore, the function of rhNGF-beta, which was secreted from various cells infected with $rhNGF-{\beta}$ adenovirus, was evaluated using neuritogenesis of PC-12 cells. For in vivo evaluation of efficacy of $rhNGF-{\beta}$ adenovirus, the LNs of 8-week old rats were exposed and crush-injured with a small hemostat for 10 seconds. After the injury, $rhNGF-{\beta}$ adenovirus($2{\mu}l,\;1.5{\times}10^{11}pfu$) or saline was administered into the crushed site in the experimental (n=24) and the control group (n=24), respectively. Sham operation of another group of rats (n=9) was performed without administration of either saline or adenovirus. The taste recovery and the change of fungiform papilla were studied at 1, 2, 3 and 4 weeks. Each of the 6 animals was tested with different solutions (0.1M NaCl, 0.1M sucrose, 0.01M QHCl, or 0.01M HCl) by two-bottle test paradigm and the number of papilla was counted using SEM picture of tongue dorsum. LN was explored at the same interval as taste study and evaluated electro-physiologically (peak voltage and nerve conduction velocity) and histomorphometrically (axon count, myelin thickness). Results: The recombinant adenovirus vector carrying $rhNGF-{\beta}$ was constructed and confirmed by restriction endonuclease analysis and DNA sequence analysis. GFP expression was observed in 90% of $rhNGF-{\beta}$ adenovirus infected cells compared with uninfected cells. Total mRNA isolated from $rhNGF-{\beta}$ adenovirus infected cells showed strong RT-PCR band, however uninfected or LacZ recombinant adenovirus infected cells did not. NGF quantification by ELISA showed a maximal release of $18865.4{\pm}310.9pg/ml$ NGF at the 4th day and stably continued till 14 days by $rhNGF-{\beta}$ adenovirus infected Schwann cells. PC-12 cells exposed to media with $rhNGF-{\beta}$ adenovirus infected Schwann cell revealed at the same level of neurite-extension as the commercial NGF did. $rhNGF-{\beta}$ adenovirus injected experimental groups in comparison to the control group exhibited different taste preference ratio. Salty, sweet and sour taste preference ratio were significantly different after 2 weeks from the beginning of the experiment, which were similar to the sham group, but not to the control group.

• Korean Journal of Occupational Health Nursing
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• v.8 no.2
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• pp.193-211
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• 1999

This study was carried out to investigate the management and support system affecting to the occupational health nursing services(OHNS) provided in group occupational health agencies(GOHA). Questionnaire was developed and distributed to 82 nurses who were working in GOHA and who agreed to participate in the survey. The results were as follow: 1. OH nurses responded were mostly in the age of twenty to thirties(89%), married(73.7%), technical college graduates(88.9%), worked in hospital(85.4%) and participated more than 1 year in group occupational health services (96.3%). 2. Fifty eight point four percent of the OH nurses worked in number of workplace more than 30 to less than 60 in the OHNS form. The figure of workplaces undertaken by nurses was ranged greatly from 9 to more than 100. Number of employees who cared by nurses were mostly under 5,000 peoples in 93.3%. The types of industry was mostly manufacturing and located in the order of factory complex area, suburban, urban and others. 3. Most OH nurses(87.8%) were fully involved in the OHNS for the SSE. Their working days to visit SSE was 5 days per week(77.8%) and one day in the GOHA at 41.3%. 4. The OH documents using by nurses were found in more than 23 different types. However, they were largely summarized in the types of 'Workplace Health Management Card', 'Personal Health Counselling Card', 'Daily Health Management Report', 'Visiting List of Workplace' and 'Sick Employee List'. 5. The items of laboratory test provided by GOHA were mostly achieved in the purpose of basic health examination. They were used to be the blood pressure check(98.8%), blood sugar test (98.8%), urine sugar and protein(91.4%), SGOT and SGPT(85.3% each), cholesterol (82.9%), hepa vaccine immunization(82.9%), r-GPT(81.7%), hemoglobin(79.3%) and triglyceride(75.5%). 6. The OH nurses(92.7%) followed the work pattern to visit the GOHA before and after small-scale enterprises(SSE) visit by car driven by nurses in 74.3%. They were payed by GOHA for transportation fees in certain amounts. However, nurse is the main person(75.0%) who covers up in case of traffic accident. If the GOHA has no transportation regulation for the formal workplace visit, data showed that nurses had been responsible to take charge(31.7%). 7. The personnel manager who takes in charge for nursing services was 'nurse' in 61.7% and 41.2% worked as the final decision maker related to nursing work. The OH nurses' opinions about factors affecting to the management were classified in the four areas such as 'Nature(Quality) of health professional'. 'Content of OHNS', 'Delivery system of the GOHS', and 'Others'. The factors were indicated highly in 'Authority as health professional', 'Level of perception of director on the OH' and 'Physical work condition for OHNS'. The things that this study suggests in the recommendation would be summarized in such as the management and supporting system working for SSE in the OHNS is necessary to reform thoroughly. The reconsidered aspects might be in the matters of number of workplaces undertaken by nurses, development of effectively practical health documents, preparation for guideline of the laboratory test in the workpleces, establishment of convenient and encouraging support system and cooperation between other health professionals with respect and skill.

• Journal of Korean Home Economics Education Association
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• v.18 no.3 s.41
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• pp.149-161
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• 2006

This study examined preferences for the clothing and textiles section of 'Technology and Home Economics' course, comparing males to females, and subdividing three groups based on the preference of the clothing and textiles section: a high-preference group, a medium-preference group, and a low-preference group. Their perceptions of the section. need to study, level of practice of teamed content, and learning needs were compared between males and females and among the three sub-groups. The subjects of this study were 176 male and 176 female high school students in Seoul. Data were collected using questionnaires with a 5-plint scale in September, 2004. Finally, 352 questionnaires were analyzed by the SPSS program. The results showed that all preferences for the clothing and textiles section were average and girls' preferences were higher than boys' preferences. General perceptions of the clothing and textiles section were positive, and there were no significant differences by gender. The perceptions of the high-preference group were more positive than those of the other two groups. The perceived importance of studying was high. especially with respect to clothing care and storage. Girls reported a greater need to study than boys did. Among both boys and girls, the high-preference group reported a greater need to study than the middle and low-preference groups did. The level of practice of learned content was leo, except for contents related to attire and the purchase of clothing. Girls practiced contents learned about attire more than boys did. Among boys, the high-preference group practiced contents teamed in all areas more than boys in the other two groups. However, among girls. only content related to attire was preferentially practiced by the high-preference group. Both boys and girls exhibited tile greatest learning need for fashion coordination. Girls had more learning needs than boys in all contents, except for clothing and environment. Among all students, the higher the level of preference, the higher their learning needs.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.195-211
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• 2010

An exhibition is defined as market events for specific duration to present exhibitors' main product range to either business or private visitors, and it also plays a key role as effective marketing channels. Especially, as the effect of the opinions of the visitors after the exhibition impacts directly on sales or the image of companies, exhibition organizers must consider various needs of visitors. To meet needs of visitors, ubiquitous technologies have been applied in some exhibitions. However, despite of the development of the ubiquitous technologies, their services cannot always reflect visitors' preferences as they only generate information when visitors request. As a result, they have reached their limit to meet needs of visitors, which consequently might lead them to loss of marketing opportunity. Recommendation systems can be the right type to overcome these limitations. They can recommend the booths to coincide with visitors' preferences, so that they help visitors who are in difficulty for choices in exhibition environment. One of the most successful and widely used technologies for building recommender systems is called Collaborative Filtering. Traditional recommender systems, however, only use neighbors' evaluations or behaviors for a personalized prediction. Therefore, they can not reflect visitors' dynamic preference, and also lack of accuracy in exhibition environment. Although there is much useful information to infer visitors' preference in ubiquitous environment (e.g., visitors' current location, booth visit path, and so on), they use only limited information for recommendation. In this study, we propose a booth recommendation methodology using Sequential Association Rule which considers the sequence of visiting. Recent studies of Sequential Association Rule use the constraints to improve the performance. However, since traditional Sequential Association Rule considers the whole rules to recommendation, they have a scalability problem when they are adapted to a large exhibition scale. To solve this problem, our methodology composes the confidence database before recommendation process. To compose the confidence database, we first search preceding rules which have the frequency above threshold. Next, we compute the confidences of each preceding rules to each booth which is not contained in preceding rules. Therefore, the confidence database has two kinds of information which are preceding rules and their confidence to each booth. In recommendation process, we just generate preceding rules of the target visitors based on the records of the visits, and recommend booths according to the confidence database. Throughout these steps, we expect reduction of time spent on recommendation process. To evaluate proposed methodology, we use real booth visit records which are collected by RFID technology in IT exhibition. Booth visit records also contain the visit sequence of each visitor. We compare the performance of proposed methodology with traditional Collaborative Filtering system. As a result, our proposed methodology generally shows higher performance than traditional Collaborative Filtering. We can also see some features of it in experimental results. First, it shows the highest performance at one booth recommendation. It detects preceding rules with some portions of visitors. Therefore, if there is a visitor who moved with very a different pattern compared to the whole visitors, it cannot give a correct recommendation for him/her even though we increase the number of recommendation. Trained by the whole visitors, it cannot correctly give recommendation to visitors who have a unique path. Second, the performance of general recommendation systems increase as time expands. However, our methodology shows higher performance with limited information like one or two time periods. Therefore, not only can it recommend even if there is not much information of the target visitors' booth visit records, but also it uses only small amount of information in recommendation process. We expect that it can give real?time recommendations in exhibition environment. Overall, our methodology shows higher performance ability than traditional Collaborative Filtering systems, we expect it could be applied in booth recommendation system to satisfy visitors in exhibition environment.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.131-145
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• 2010

The framework for making a coordinated decision for large-scale facilities has become an important issue in supply chain(SC) management research. The competitive business environment requires companies to continuously search for the ways to achieve high efficiency and lower operational costs. In the areas of production/distribution planning, many researchers and practitioners have developedand evaluated the deterministic models to coordinate important and interrelated logistic decisions such as capacity management, inventory allocation, and vehicle routing. They initially have investigated the various process of SC separately and later become more interested in such problems encompassing the whole SC system. The accurate quotation of ATP(Available-To-Promise) plays a very important role in enhancing customer satisfaction and fill rate maximization. The complexity for intelligent manufacturing system, which includes all the linkages among procurement, production, and distribution, makes the accurate quotation of ATP be a quite difficult job. In addition to, many researchers assumed ATP model with integer time. However, in industry practices, integer times are very rare and the model developed using integer times is therefore approximating the real system. Various alternative models for an ATP system with time lags have been developed and evaluated. In most cases, these models have assumed that the time lags are integer multiples of a unit time grid. However, integer time lags are very rare in practices, and therefore models developed using integer time lags only approximate real systems. The differences occurring by this approximation frequently result in significant accuracy degradations. To introduce the ATP model with time lags, we first introduce the dynamic production function. Hackman and Leachman's dynamic production function in initiated research directly related to the topic of this paper. They propose a modeling framework for a system with non-integer time lags and show how to apply the framework to a variety of systems including continues time series, manufacturing resource planning and critical path method. Their formulation requires no additional variables or constraints and is capable of representing real world systems more accurately. Previously, to cope with non-integer time lags, they usually model a concerned system either by rounding lags to the nearest integers or by subdividing the time grid to make the lags become integer multiples of the grid. But each approach has a critical weakness: the first approach underestimates, potentially leading to infeasibilities or overestimates lead times, potentially resulting in excessive work-inprocesses. The second approach drastically inflates the problem size. We consider an optimized ATP system with non-integer time lag in supply chain management. We focus on a worldwide headquarter, distribution centers, and manufacturing facilities are globally networked. We develop a mixed integer programming(MIP) model for ATP process, which has the definition of required data flow. The illustrative ATP module shows the proposed system is largely affected inSCM. The system we are concerned is composed of a multiple production facility with multiple products, multiple distribution centers and multiple customers. For the system, we consider an ATP scheduling and capacity allocationproblem. In this study, we proposed the model for the ATP system in SCM using the dynamic production function considering the non-integer time lags. The model is developed under the framework suitable for the non-integer lags and, therefore, is more accurate than the models we usually encounter. We developed intelligent ATP System for this model using genetic algorithm. We focus on a capacitated production planning and capacity allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using an evolutionary system to solve it efficiently. This method makes it possible for the population to reach the approximate solution easily. Moreover, we designed and utilized a representation scheme that allows the proposed models to represent real variables. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solutions converge to the optimum quickly.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.179-192
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• 2014

Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.123-138
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• 2016

This study investigates intents of acquisitions in information technology industries. Mergers and acquisitions are a strategic decision at corporate-level and have been an important tool for a firm to grow. Plenty of firms in information technology industries have acquired startups to increase production efficiency, expand customer base, or improve quality over the last decades. For example, Google has made about 200 acquisitions since 2001, Cisco has acquired about 210 firms since 1993, Oracle has made about 125 acquisitions since 1994, and Microsoft has acquired about 200 firms since 1987. Although there have been many existing papers that theoretically study intents or motivations of acquisitions, there are limited papers that empirically investigate them mainly because it is challenging to measure and quantify intents of M&As. This study examines the intent of acquisitions by measuring specific intents for M&A transactions. Using our measures of acquisition intents, we compare the intents by four acquisition types: (1) the acquisition where a hardware firm acquires a hardware firm, (2) the acquisition where a hardware firm acquires a software/IT service firm, (3) the acquisition where a software/IT service firm acquires a hardware firm, and (4) the acquisition where a software /IT service firm acquires a software/IT service firm. We presume that there are difference in reasons why a hardware firm acquires another hardware firm, why a hardware firm acquires a software firm, why a software/IT service firm acquires a hardware firm, and why a software/IT service firm acquires another software/IT service firm. Using data of the M&As in US IT industries, we identified major intents of the M&As. The acquisition intents are identified based on the press release of M&A announcements and measured with four categories. First, an acquirer may have intents of cost saving in operations by sharing common resources between the acquirer and the target. The cost saving can accrue from economies of scope and scale. Second, an acquirer may have intents of product enhancement/development. Knowledge and skills transferred from the target may enable the acquirer to enhance the product quality or to expand product lines. Third, an acquirer may have intents of gain additional customer base to expand the market, to penetrate the market, or to enter a foreign market. Fourth, a firm may acquire a target with intents of expanding customer channels. By complementing existing channel to the customer, the firm can increase its revenue. Our results show that acquirers have had intents of cost saving more in acquisitions between hardware companies than in acquisitions between software companies. Hardware firms are more likely to acquire with intents of product enhancement or development than software firms. Overall, the intent of product enhancement/development is the most frequent intent in all of the four acquisition types, and the intent of customer base expansion is the second. We also analyze our data with the classification of production-side intents and customer-side intents, which is based on activities of the value chain of a firm. Intents of cost saving operations and those of product enhancement/development can be viewed as production-side intents and intents of customer base expansion and those of expanding customer channels can be viewed as customer-side intents. Our analysis shows that the ratio between the number of customer-side intents and that of production-side intents is higher in acquisitions where a software firm is an acquirer than in the acquisitions where a hardware firm is an acquirer. This study can contribute to IS literature. First, this study provides insights in understanding M&As in IT industries by answering for question of why an IT firm intends to another IT firm. Second, this study also provides distribution of acquisition intents for acquisition types.

• Journal of the Korean Institute of Landscape Architecture
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• v.16 no.3
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• pp.21-37
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• 1989

Environmental design pattern of the nine Small Urban Spaces at C.B.D. in City of Seoul are surveyed and analyzed for user's satisfaction and behavior under the environmental design evaluation by using Christopher Alexander's Pattern Language. Small Urban Spaces as a part of streetscape are formed by physical factors as well as visual environment and interacting user's behavior. Therefore, user's satisfaction and behavior at the nine Urban Small Spaces were investigated under the further search for some possibilities of application of those Pattern Languages. A pattern language has a structure of a network. It is used in sequence, going through the patterns, moving always from large patterns to smaller, always from the ones which create comes simply from the observation that most of the wonderful places of the city were not blade by architects but by the people. It defines the limited number of arrangements of spaces that make sense in any given culture. And it actually gives us the power to generate these coherent arrangement of space. As a results, 'Plaza', 'Seats'and 'Aecessibility' related design Patterns are highly evaluated by Pattern Frequency, Pattern Interaction and their Composition ranks, thus reconfirm Whyte's Praise of urban Small Spaces in our inner city design environments. According to the multiple regression analysis of user's evaluation, the environmental functions related to the satisfaction were 'Plaza', 'Accessibility' and 'Paving'. According to the free response, user's prefer such visually pleasing environmental design object as 'Waterscape' and 'Setting'. In addition to, the basic needs in Urban Small Spaces are amenity facilities as bench, drinking water and shade for rest.