• Title/Summary/Keyword: Booth Management

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"Servicescape" Differentiation in a Hair Salon (헤어살롱 서비스스케이프 차별화 성공사례)

  • Lee, Sang-Hyun;Park, Chul-Ju
    • Journal of Distribution Science
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    • v.13 no.9
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    • pp.71-79
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    • 2015
  • Purpose - The purpose of this paper is to find out the effect of changes in the differentiated "servicescape" on the business performance in the hair salon industry using a case study. For this, we selected hair salon M located in Suwon. The shop is innovatively different from existing shops in terms of spatial layout and functionality. We conducted in-depth research, beginning with the launch of the shop concept through investment and ongoing stable sales. Research design, data, and methodology - The M hair salon is a start up shop providing a differentiated servicescape (physical environment where the service takes place) located in Suwon, Yeongtong-gu. We conducted research to investigate how spatial layout and functionality of the servicescape impact customers' perceived quality. The interview period and case analysis was May 2014 through March 2015, covering 11 months. To conduct the case analysis, we analyzed the spatial layout and functionality of existing shops and interviewed customers and experts about the difference between hair salon M and existing shops. Results - Our results found clues to the positive effect of spatial layout and functionality among servicescape factors on perceived service quality at the salon. The shop showed a fast payback of the principal investment, growth potential in contrast to competitors near the salon, and 45 percent returning customers. The problem with the spatial layout at existing shops was that customers were aware of the way other people were looking at them, since viewing angles overlapped, therefore there was a limitation to the relationship intensity with an exclusive hair designer. In contrast, the layout of the stands at the M salon kept the number of dressing stands limited to maximize the customer's emotional response. Additionally, because of the new layout of dressing stands hiding other customer voices and appearance in the salon, customers perceived their service space as independent. Therefore, they did not have to focus on their personal emotional response, which was one of the advantages of the new layout. Conclusions - This study conducted case study analysis by offering a new perspective focusing on spatial layout, previously not considered as an independent variable of quality evaluations and customer satisfaction in existing literature on hair salon management. Therefore, this study contributes to the field by offering an opportunity to discover the causal relationships between the overlooked physical environment and a customer's perceived quality. However, a process objectifying the results of the study through empirical analysis and hypotheses is needed to overcome the limitations of the case study approach and generalize the results. Moreover, it would be beneficial to conduct further empirical study of the relationship between the spatial layout provided in the case and a customer's emotional response and change in mood. In addition, an analysis is needed regarding how customers feel about the factors using the Kano Model. These suggestions would be considered in further study.

The Effect of Local Festival Service Quality to Purchasing Intention of Local Start-up Company Products: Focus on Hampyong Butterfly Festival (지역축제 서비스품질이 지역기반 창업기업 제품 구매의도에 미치는 영향: 함평나비축제를 중심으로)

  • Hong, Inki;Min, Kyung Se
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.12 no.1
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    • pp.61-71
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    • 2017
  • Local festival in Korea has developed quantitatively as well qualitatively. Driving force of local festival's development is local governments' active supports. Many Local government support local festival opening actively to accomplish economic activation. Activation of local festivals is good chance to local start-up companies. Local start-up companies don't have well known brand, and wide distribution network. But they can sell their products to visitors in local festival. And if fortune smiles upon them, they can get big buyers in local festivals. If so, what factors can contribute to a increase sales of local start-up companies? Different from existing research that focus on tour industrial outcome, we will focus on effect of festival service quality on increase sales. The survey is using structured questionnaire, we surveyed visitors who visit local start-up companies' booth in festival site. According to survey result, first, each dimensions of festival service quality do not effect on purchase intention directly except empathy dimension. Second, each dimensions of festival service quality effect on purchase intention by a medium of local image indirectly except assurance dimension. And purchase intention have a great effect on purchase action. Through the results, we can confirm festival service quality effect on purchase intention by a medium of local image indirectly. we suggest that improving festival service quality can effect on sales increase of local start-up companies, and for the purpose of sales increase, local government must improve local image at first.

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Comprehensive Analysis of Exposed Adverse Factors in Disaster Response Activities - Focused on Fire - (재난 대응 활동 시 노출가능 유해인자 종합분석 -화재 현장을 중심으로-)

  • Park, Chanseok
    • Journal of the Society of Disaster Information
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    • v.10 no.3
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    • pp.420-430
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    • 2014
  • Firefighters performing disaster response activities such as Fire Suppression Rescue First Aid in fire are being exposed in various adverse factors, heat, smoke, toxic gases, emotional stress, biological toxic factors and physical overload by unnatural ergonomic posture required for firefighters. But so far, there is the study for this problem only separately. There is no study about comprehesive analysis of exposed adverse factors in fire-related disaster response activities and countermeasures. The purpose of this study is to contiribute to solving the health problems and prevention of accidents of firefighters by extracting hazardous agents in disaster such as fire and by proposing countermeasures. After analyzing circumstances such as fire-suppression, rescue first aid and life-environment, exposure factors of fire are derived and exposure status is suggested according to physical chemical biological psychological aspects. The countermeasure against the noise of the physical exposure factors are proposed. The countermeasures such as protective equipment and clean room in chemical factors, infection prevention education, vaccination and periodic check system in biological factors, PTSD alleviation booth and mentoring in psychological factors are proposed.

The Treatment of Volatile Organic Compounds Using a Pilot-Scale Biofilter (Pilot 규모의 바이오필터를 이용한 휘발성유기화합물질 제거)

  • Son, Hyun-Keun
    • Journal of Environmental Health Sciences
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    • v.30 no.3
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    • pp.245-252
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    • 2004
  • Two biofilter tests were conducted under different operating conditions. Test # 1 was performed to treat VOCs generated from a paint booth. The second test was performed to treat VOCs generated from chemical manufacturing processes. The volume of biofilter media was 4.3 $m^3$. For the test # 1, the biofilter was operated for 30 days with 99.9% reduction ratio. Range of temperature of each stage of the biofilter media was measured between $34^{\circ}C$ and $73^{\circ}C$. All the temperatures of stages reduced gradually after the initial dramatic increase. For the test # 2, the biofilter experiment was conducted for 14 days. In this case, the biofilter was installed outdoor and the experiment was performed during wintertime. Therefore, temperature management for the biofilter was needed. Seven-centimeter thick fiberglass insulation and $150^{\circ}C$ steam heating were used to overcome the outside freezing cold weather during test # 2. Temperature of stage # 5 was measured the highest and that of stage # 1 was the lowest. More acclimation time and test period was needed to determine the maximum loading rate.

Case Analysis of the Promotion Methodologies in the Smart Exhibition Environment (스마트 전시 환경에서 프로모션 적용 사례 및 분석)

  • Moon, Hyun Sil;Kim, Nam Hee;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.171-183
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    • 2012
  • In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

The Audience Behavior-based Emotion Prediction Model for Personalized Service (고객 맞춤형 서비스를 위한 관객 행동 기반 감정예측모형)

  • Ryoo, Eun Chung;Ahn, Hyunchul;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.73-85
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    • 2013
  • Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.