• The Korean Journal of Franchise Management
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• v.13 no.3
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• pp.1-15
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• 2022

Purpose: In the restaurant sector, it has been known that consumers' positive perception of brands influences their positive WOM intention, and information sources play an important role in increasing credibility by enhancing consumer awareness and developing differentiated brands. This study examines the effects of information sources (e.g., advertisement, WOM, SNS) on trust (cognitive and affective) and, WOM and eWOM intention in the restaurant context. In the model, cognitive and affective trust play mediating roles in the relationships between information sources (e.g., advertisement, WOM, SNS) WOM and eWOM intention. Research design, data, and methodology: Research models and hypotheses were developed according to the research direction. The survey questionnaire items were developed and used appropriately according to the contents of this paper based on prior studies. All constructs were measured with multiple items developed and validated in prior studies. A total of 502 responses were collected from an online survey. The research model was evaluated using SmartPLS 4.0. Frequency analysis was performed to understand the demographic characteristics of the survey respondents. The reliability, convergent validity, and discriminant validity were assessed using measurement model analysis. The proposed model was verified using the structural equation model. Results: Advertisement, WOM, and SNS information sources all had a positive effect on affective trust, whereas only WOM had a significant effect on cognitive trust. In addition, affective trust had a positive effect on cognitive trust and eWOM intention but did not affect WOM intention. Finally, cognitive trust was found to have a positive effect on both WOM intention and eWOM intention. Conclusions: This study redefines the concept of where restaurant service companies should focus when providing consumers with information about their products and services. As a result, the conceptual framework of positive word of mouth intention to increase new customer visits to the restaurant brand has been expanded. In addition, this study not only presents an information source management strategy for restaurant brands, but also presents practical implications for resource allocation guidelines for customer management in the restaurant sector.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.663-670
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• 2023

Unlike previous studies that have looked at ESG management and ESG performance from a consumer perspective, this study aims to examine the relationship between attitudes toward ESG and ESG performance perception from the perspective of internal customers who are members of the organization. To this end, the impact of internal members' perceptions of the importance of each ESG area on the organization's ESG management necessity and performance perception was summarized into three research questions and the impact was identified using a structural equation model. As a result of the study, internal customers highly recognized the organization's ESG management needs when they recognized the E (environmental) and G (governance) areas as important, but there was no significant relationship with the ESG management needs in the S (social) area (Research Question 1). In addition, the relationship between the perception of importance in each ESG area and the organization's ESG management needs was found to be little different depending on internal customers' interest in ESG, the degree of ESG knowledge, and age (Research Question 2). Finally, it was found that internal customers who highly perceive the organization's ESG management needs were also positively aware of the organization's ESG performance level.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.101-124
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• 2009

According to Wikipedia, virtual reality (VR) is defined as a technology that allows a user to interact with a computer-simulated environment. Due to a rapid growth in information technology (IT), the cost of virtual reality has been decreasing while the utility of virtual reality advertisements has dramatically increased. Nevertheless, only a few studies have investigated the effects of virtual reality advertisement on consumer behaviors. Therefore, the objective of this study is to empirically examine the effects of virtual reality advertisement. Compared to traditional online advertisements, virtual reality advertisement enables consumers to experience products realistically over the Internet by providing high media richness, interactivity, and telepresence (Suh and Lee, 2005). Advertisements with high media richness facilitate consumers' understanding of advertised products by providing them with a large amount and a high variety of information on the products. Interactivity also provides consumers with a high level of control over the computer-simulated environment in terms of their abilities to adjust the information according to their individual interests and concerns and to be active rather than passive in their engagement with the information (Pimentel and Teixera, 1994). Through high media richness and interactivity, virtual reality advertisements can generate compelling feelings of "telepresence" (Suh and Lee, 2005). Telepresence is a sense of being there in an environment by means of a communication medium (Steuer, 1992). Virtual reality advertisements enable consumers to create a perceptual illusion of being present and highly engaged in a simulated environment, while they are in reality physically present in another place (Biocca, 1997). Based on the characteristics of virtual reality advertisements, a research model has been proposed to explain consumer responses to the virtual reality advertisements. The proposed model includes two dimensions of consumer responses. One dimension is consumers' rational response, which is based on the Information Processing Theory. Based on the Information Processing Theory, product knowledge and perceived risk are selected as antecedents of intention to purchase. The other dimension is emotional response of consumers, which is based on the Attitude-Structure Theory. Based on the Attitude-Structure Theory, arousal, flow, and positive affect are selected as antecedents of intention to purchase. Because it has been criticized to have investigated only one of the two dimensions of consumer response in prior studies, our research model has been built so as to incorporate both dimensions. Based on the Attitude-Structure Theory, we hypothesized the path of consumers' emotional responses to a virtual reality advertisement: (H1) Arousal by the virtual reality advertisement increases flow; (H2) Flow increases positive affect; and (H3) Positive affect increases intension to purchase. In addition, we hypothesized the path of consumers' rational responses to the virtual reality advertisement based on the Information Processing Theory: (H4) Increased product knowledge through the virtual reality advertisement decreases perceived risk; and (H5) Perceived risk decreases intension to purchase. Based on literature of flow, we additionally hypothesized the relationship between flow and product knowledge: (H6) Flow increases product knowledge. To test the hypotheses, we conducted a free simulation experiment [Fromkin and Streufert, 1976] with 300 people. Subjects were asked to use the virtual reality advertisement of a cellular phone on the Internet and then answer questions about the variables. To check whether subjects fully experienced the virtual reality advertisement, they were asked to answer a quiz about the virtual reality advertisement itself. Responses of 26 subjects were dropped because of their incomplete answers. Responses of 274 subjects were used to test the hypotheses. It was found that all of six hypotheses are accepted. In addition, we found that consumers' emotional response has stronger impact on their intention to purchase than their rational response does. This study sheds much light into practical implications for both IS researchers and managers. First of all, while most of previous research has analyzed only one of the customers' rational and emotional responses, we theoretically incorporated and empirically examined both of the two sides. Second, we empirically showed that mediators such as arousal, flow, positive affect, product knowledge, and perceived risk play an important role between virtual reality advertisement and customer's intention to purchase. In addition, the findings of this study can provide a basis of practical strategies for managers. It was found that consumers' emotional response is stronger than their rational response. This result indicates that advertisements using virtual reality should focus on the emotional side, and that virtual reality can be served as an appropriate advertisement tool for fancy products that require their online advertisements to give an impetus to customers' emotion. Finally, even if this study examined the effects of virtual reality advertisement of cellular phone, its findings could be applied to other products that are suited for virtual experience. However, this research has some limitations. We were unable to control different kinds of consumers and different attributes of products on consumers' intention to purchase. It is, therefore, deemed important for future research to control the consumer and product types for more reliable results. In addition to the consumer and product attributes, other variables could affect consumers' intention to purchase. Thus, the future research needs to find ways t control other variables.

• 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.

• Journal of the Korean Institute of Gas
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• v.22 no.5
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• pp.1-17
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• 2018

Related incidents and accidents are frequent after 2000 years, such as the outbreak of the Taian peninsula crude oil spillage and Gumi hydrofluoric acid leakage accident. In the wake of such environmental pollution accidents, Consensus has been formed to enact legislation on liability for the compensation of environmental pollution in 2014 and the rescue, and has been in force since January 2016. Therefore, in the domestic insurance industry, the introduced environmental liability insurance system needs to be managed through the standardization formula of a new insurance model for managing the environmental risk. This study has been carried out by the emergence of a safe insurance model with a risky nature of the risk type, which is one of the services of the knowledge base. The verification of the six assurance media on the occurrence of environmental pollution such as chemical, waste, marine, soil, etc. is expressed through semantic interoperability through this possible ontology. The insurance model was designed and presented by deducing the relationship between the amount of money and the amount of money that was written in the area of existing expertise, In order to exclude the possible consequences, the concept of abstract is conceptualized in the form of a customer, and a plan for the future development of an ontology-based decision support system is proposed to reduce the cost and resources consumed every year. It is expected that standardization of the verification standard of the mass of mass will minimize errors and reduce the time and resources required for verification.

• Knowledge Management Research
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• v.21 no.3
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• pp.1-25
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• 2020

This study analyzed key success factors of Korean car-sharing enterprises, Socar and Greencar, and the responsive strategies of Korean car-manufacturing company, Hyundai Motor Group, in the face of emerging sharing economy under the specific economic and regulatory system in Korea. The outcomes of the analysis are as follows. 'Timely market entry' in early startup phase and 'use of external resources' in early growth phase were key success factors common to both Socar and Greencar. However, the differences in the eventual business directions of the two companies also resulted in different key success factors in the expansion phase of their business. For Socar which focused on maintaining its independence and the external growth of B2C business, customer relation marketing and sufficient capital raising were key success factors. For Greencar which became a part of a business group and focused on improving the efficiency of business operations, timely market entry (B2B market) was key success factor. The use of external resources and cooperation with large corporations emerged as key success factors common to both companies in the rapid growth phase. The responsive strategies of the Hyundai Motor Group were collaboration, investment and direct management of DeliveryCar. The short-term goal of the responsive strategy was the operation of test-bed in collaboration with car-sharing company while the mid/long term goal was planning new mobility services by utilizing collected data. Securing opportunities for early market dominance for autonomous car industry was also found to be an important goal.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.2
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• pp.274-291
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• 2012

Since the advent of the internet as representative of the development of information communication technology (ICT), information transfer forms have changed rapidly these days. In the new techno-economic paradigms, I would ultimately consider how spatial structures of a knowledge-based service industry have been altered dynamically. To delve into this background, this study conducts an empirical case study of the internet advertising industry, particularly, among the whole advertising industry. Therefore, the primary objective of this study is to identify dynamic characteristics of spatial networks among actors for knowledge creation in Korea's internet advertising industry. In addition, it also is to analyze the formative elements of spatial networks which would have an influence on constructing the space of new economic activities. There are multilateral approaches. This research is classified into types of actors such as inter-firm, intra-firm, and firm-customer, and categorized according to spatial ranges such as local, regional, global levels. In the meanwhile, formative factors of the spatial networks could draw a conclusion from two aspects: inter-firm networks in the process of business in the internet advertising industry, and individual networks in the nonoccupational aspect. Accordingly, the results of this study suggest that actors' networks of two perspectives would make mutually complementary relationships and create new relational spaces in the digital economy.

• Korean Journal of Environment and Ecology
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• v.34 no.2
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• pp.179-187
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• 2020

The study was conducted on Godeoksan, Gangdong-gu, Seoul, for the study of elderly people's park use and satisfaction. For the analysis, frequency analysis was performed on all items, and reliability analysis was performed to check the validity of the items. Factor analysis was used to identify items that have a significant effect on the customer's satisfaction. Multiple regression analysis was performed using the derived factors. As a result of factor analysis, it was found that the factors affecting satisfaction were composed of three factors and 69.50% of the total variance was explained. The KMO value, which means the sample fit between items, was analyzed as .756. Factors were classified into usage aspect, ecological aspect, and amenityt aspect by reflecting the characteristics of the item. As a result of the multiple regression analysis through the derived factors, the multiple regression equation for the elderly's park use satisfaction was analyzed to be Y = 3.678 + 0.202X₁ + 0.125X₂ + 0.236X₃. In this study, there are limitations in conducting a questionnaire survey for the elderly who lack professional knowledge. In the future, evaluation studies should be conducted for the elderly with specialized knowledge, and it is judged that a comparative study of ecological, utilization, and climatic aspects by age is necessary.

• Journal of the Economic Geographical Society of Korea
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• v.13 no.1
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• pp.1-18
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• 2010

This paper examines characteristics of producer service networks by comparing the Capital region with Gyeongsang region in Korea and provides implications for regional policies of producer services. We employ the data of the Korea Innovation Survey, compiled by Science & Technology Policy Institute in 2006 and analyze producer service networks in the two regions. According to the results of production networks analysis, producer service firms in Gyeongsang region serve to relatively limited areas of market whereas those in the Capital region serve to a larger market. No difference is found between producer service firms in the Capital region and those in Gyeongsang region for the types of major customers. Analysis of knowledge/information networks demonstrates that firms in the Capital region mostly count on informal networks while those in Gyeongsang region primarily rely on their suppliers as a source of key information. Firms in Gyeongsand region often gain key information from the Capital region. The results of Social Network Analysis show that both of the innovation networks for two regions are poorly connected. In order to promote producer services, each region needs strategic approach reflecting regional characteristics and demands of regional industries.

• Knowledge Management Research
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• v.22 no.4
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• pp.27-40
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• 2021

Click-Through Rate (CTR) prediction is a key function that determines the ranking of candidate items in the recommendation system and recommends high-ranking items to reduce customer information overload and achieve profit maximization through sales promotion. The fields of natural language processing and image classification are achieving remarkable growth through the use of deep neural networks. Recently, a transformer model based on an attention mechanism, differentiated from the mainstream models in the fields of natural language processing and image classification, has been proposed to achieve state-of-the-art in this field. In this study, we present a method for improving the performance of a transformer model for CTR prediction. In order to analyze the effect of discrete and categorical CTR data characteristics different from natural language and image data on performance, experiments on embedding regularization and transformer normalization are performed. According to the experimental results, it was confirmed that the prediction performance of the transformer was significantly improved when the L2 generalization was applied in the embedding process for CTR data input processing and when batch normalization was applied instead of layer normalization, which is the default regularization method, to the transformer model.