• Asia Marketing Journal
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• v.12 no.1
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• pp.1-30
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• 2010

Customers often experience waiting for buying service. Managing customers' waiting time is important for service providers since customers who are dissatisfied with waiting, secede from a service place at last. Not a few studies have been done to solve waiting time problem and improve customers' waiting experience. Hui & Tse(1996) identify evaluation factors in customers' behavioral mechanism as customers wait. That is, customers experience perceived waiting time, waiting acceptability and emotional response to the wait when they wait. Since customers evaluate the wait using these factors, service provider should manage these factors in order to minimize customers' dissatisfaction. Therefore, this study explores that evaluation factors of waiting are influenced by customers' situational and experiential characteristics, which include customer loyalty, transaction importance for customer and waiting expectation level. Those situational and experiential characteristics are usually given to service providers so they can't control these at waiting point. The major findings derived from two exploratory studies can be summarized as follows. First, according to the result from the study 1 (restaurant setting), customers' transaction importance has the greatest positive influence on waiting experience. The results show restaurant service provider could prevent customers' separation effectively through strategies which raise customers' transaction importance, like giving special coupons for important events. Second, in study 2 (amusement part setting) customer loyalty has large positive impact on waiting experience as well as transaction importance. This results show that service provider could minimize customers' dissatisfaction using strategies which raise customer loyalty continuously. This results show customer perceives waiting experience differently according to characteristics of service place and service itself. Therefore, service provider should grasp the unique customers' situational and experiential characters for each service and service place. It could provide an effective strategy for waiting time management. Third, the study finds transaction importance and waiting expectation level have direct influence customers' waiting experience as independent variables, while existing studies treated them as moderators. Customer loyalty which has not been incorporated in previous waiting time research is known to affect waiting experience. It suggests that marketing strategy which builds up customer loyalty for long period of time is also quite effective, compared to short term tactics to help customers endure waiting time. Fourth, this study reveals the importance of actual waiting time along with perceived waiting time. So far most studies only focus on customers' perceived waiting time. Especially, this study incorporates the concept of patient limit on waiting time to investigate effect of actual waiting time. The results show that there were various responses to the wait depending on how actual waiting time exceeds individual's patent limit on waiting time or not, even though customers wait about the same period of time. Finally, using structural equation model, conceptual path between behavioral responses is verified. As customer perceives waiting time, then she decides whether she can endure it or not, and then her emotional response occurs. This result are somewhat different from Hui & Tse(1996)'s study. The study also includes theoretical contributions as well as practical implications.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.107-127
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• 2022

Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.2
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• pp.157-166
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• 2015

Purpose : Cyber-Knife tumor tracking system, based on the correlation relationship between the position of a tumor which moves in response to the real time respiratory cycle signal and respiration was obtained by the LED marker attached to the outside of the patient, the location of the tumor to predict in advance, the movement of the tumor in synchronization with the therapeutic device to track real-time tumor, is a system for treating. The purpose of this study, in the cyber knife tumor tracking radiation therapy, trying to evaluate the accuracy of tumor tracking radiation therapy system due to the change in the form of unpredictable sudden breathing due to cough and sleep. Materials and Methods : Breathing Log files that were used in the study, based on the Respiratory gating radiotherapy and Cyber-knife tracking radiosurgery breathing Log files of patients who received herein, measured using the Log files in the form of a Sinusoidal pattern and Sudden change pattern. it has been reconstituted as possible. Enter the reconstructed respiratory Log file cyber knife dynamic chest Phantom, so that it is possible to implement a motion due to respiration, add manufacturing the driving apparatus of the existing dynamic chest Phantom, Phantom the form of respiration we have developed a program that can be applied to. Movement of the phantom inside the target (Ball cube target) was driven by the displacement of three sizes of according to the size of the respiratory vertical (Superior-Inferior) direction to the 5 mm, 10 mm, 20 mm. Insert crosses two EBT3 films in phantom inside the target in response to changes in the target movement, the End-to-End (E2E) test provided in Cyber-Knife manufacturer depending on the form of the breathing five times each. It was determined by carrying. Accuracy of tumor tracking system is indicated by the target error by analyzing the inserted film, additional E2E test is analyzed by measuring the correlation error while being advanced. Results : If the target error is a sine curve breathing form, the size of the target of the movement is in response to the 5 mm, 10 mm, 20 mm, respectively, of the average $1.14{\pm}0.13mm$, $1.05{\pm}0.20mm$, with $2.37{\pm}0.17mm$, suddenly for it is variations in breathing, respective average $1.87{\pm}0.19mm$, $2.15{\pm}0.21mm$, and analyzed with $2.44{\pm}0.26mm$. If the correlation error can be defined by the length of the displacement vector in the target track is a sinusoidal breathing mode, the size of the target of the movement in response to 5 mm, 10 mm, 20 mm, respective average $0.84{\pm}0.01mm$, $0.70{\pm}0.13mm$, with $1.63{\pm}0.10mm$, if it is a variant of sudden breathing respective average $0.97{\pm}0.06mm$, $1.44{\pm}0.11mm$, and analyzed with $1.98{\pm}0.10mm$. The larger the correlation error values in both the both the respiratory form, the target error value is large. If the motion size of the target of the sine curve breathing form is greater than or equal to 20 mm, was measured at 1.5 mm or more is a recommendation value of both cyber knife manufacturer of both error value. Conclusion : There is a tendency that the correlation error value between about target error value magnitude of the target motion is large is increased, the error value becomes large in variation of rapid respiration than breathing the form of a sine curve. The more the shape of the breathing large movements regular shape of sine curves target accuracy of the tumor tracking system can be judged to be reduced. Using the algorithm of Cyber-Knife tumor tracking system, when there is a change in the sudden unpredictable respiratory due patient coughing during treatment enforcement is to stop the treatment, it is assumed to carry out the internal target validation process again, it is necessary to readjust the form of respiration. Patients under treatment is determined to be able to improve the treatment of accuracy to induce the observed form of regular breathing and put like to see the goggles monitor capable of the respiratory form of the person.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.6
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• pp.84-97
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• 2016

This study was to investigate the user's thermal environments of the children's parks according to pavements and sunscreen types during periods of heat waves. The measurements were conducted at the sand pits, rubber chip pavement, shelters, and green shade ground of the two children's parks located in Jinju, Korea(Chilam: $N\;35^{\circ}11^{\prime}1.4{^{\prime}^{\prim}}$, $E\;128^{\circ}5^{\prime}31.7{^{\prime}^{\prime}}$, elevation 38m, Gaho: $N\;35^{\circ}09^{\prime}56.8{^{\prime}^{\prime}}$, $E\;128^{\circ}6^{\prime}41.1{^{\prime}^{\prime}}$, elevation 24m) over three days during 11-13, August, 2016. The highest ambient air temperatures at the Jinju Meteorological Office during the three measurement days were $35.9{\sim}36.8^{\circ}C$, which corresponded with the extremely hot weather. A series of experiments measured air temperature, relative humidity, wind velocity, black globe temperature, and long-wave and short-wave radiation of the six directions 0.6 m above ground level. The wet bulb globe temperature(WBGT) and the universal thermal climatic index(UTCI) were used to evaluate thermal stress. Surface temperature images of the play equipment were also taken using infrared thermography. Surface temperatures of the play equipment and grounds were used to evaluate burn risk through contact with playground materials. The results showed the following. The maximum air temperatures averaged over 1-hour period for three days were $36.6{\sim}39.4^{\circ}C$. The sun shades reduced those temperatures by up to $2.8^{\circ}C$(green shade) and $1.0^{\circ}C/2.3^{\circ}C$(shelters). The minimum relative humidity values averaged over 1-hour period for three days were 44~50%. The sun shades increased those humidity values by up to 6%(green shade) and 4%/6%(shelters). The risk of heat related illness at the measurement sites of the children's parks were extreme and high in the daytime hours. The maximum WBGT values averaged over a 30-minute period for three days were $31.2{\sim}33.6^{\circ}C$. The sun shades reduced those WBGT values by up to $2.4^{\circ}C$(green shade) and $0.5^{\circ}C/2.1^{\circ}C$(shelters) compared to sandpits, but would not block the risk of heat related illness in the daytime hours. The category of heat stress at the measurement sites of the children's parks were extreme and very strong in the daytime hours. The maximum UTCI values averaged over a 30-minute period for three days were $39.9{\sim}48.1^{\circ}C$. The sun shades reduced those UTCI values by up to $7.8^{\circ}C$(green shade) and $4.1^{\circ}C/8.2^{\circ}C$(shelters) compared to sandpits, but could not lower heat stress category from extreme and very strong to strong and moderate in the daytime hours. According to the burn threshold criteria when skin was in contact with playground materials, the maximum surface temperature of the stainless steels($70.8^{\circ}C$) surpassed three seconds $60^{\circ}C$ threshold for uncoated steel, that of the rubber chip($76.5^{\circ}C$) surpassed five seconds $74^{\circ}C$ threshold for the plastic, that of the plastic slide($68.5^{\circ}C$) and seats($71.0^{\circ}C$) surpassed the one min $60^{\circ}C$ threshold for plastic, respectively. The surface temperatures of shaded play equipment were lower approximately $20^{\circ}C$ than those of play equipment exposed to the sun. Therefore, sun shades can block the risk of burns in daytime hours. Because of the extreme and high risk of heat related illness and extreme and high heat stress at the children's parks during periods of heat waves, parents and administrators must protect children from the use of playgrounds. The risk of burn when contact with play equipments and grounds at the children's parks during periods of heat waves, was very high. The sun shades are essential to block the risk of burn from play equipments and grounds at the children's parks during heat waves.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.