• Asia Marketing Journal
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• v.17 no.2
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• pp.73-96
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• 2015

This paper investigates how servicescape perception influences customer experience quality in hedonic service settings. In addition to the direct effect of servicescape quality on customer experience quality, the indirect effects of servicescape quality on customer experience quality via employee-to-customer interaction quality and peer-to-peer interaction quality are also investigated. We collected data through a self-administered survey. The proposed relationships were tested using structural equation modeling. The results show that servicescape quality influences customer experience quality both directly and indirectly through employee-to-customer interaction quality and peer-to-peer interaction quality, and customer experience quality influences customer loyalty. Additionally, we find that the indirect path via peer-to-peer interaction quality is significant only in a low-satisfaction customer group. The indirect effect of servicescape quality perception through peer-to-peer interaction quality is significant only in low-satisfaction customer groups. Therefore, if evaluations for this indirect effect fall below an acceptable level, it should be addressed first before improving on other attributes. However, after this point, further improvements offer few if any gains; therefore, service firms should allocate their resources to quality improvements to other factors. This study is the first to investigate the indirect effects of servicescape quality on customer experience quality via peer-to-peer interaction quality in hedonic service settings. Additionally, this study demonstrates that the significance of this indirect effect applies only to a low-satisfaction customer group.

• Asia pacific journal of information systems
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• v.33 no.2
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• pp.282-297
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• 2023

One of the emerging trends in the marketing field is digital video marketing. Online videos offer rich content typically containing more information than any other type of content (e.g., audible or textual content). Accordingly, previous researchers have examined factors influencing videos' popularity. However, few studies have examined what causes a video to remain popular. Some videos achieve continuous, ongoing popularity, while others fade out quickly. For practitioners, videos at the recommendation slots may serve as strong communication channels, as many potential consumers are exposed to such videos. So,this study will provide practitioners important advice regarding how to choose videos that will survive as long-lasting favorites, allowing them to advertise in a cost-effective manner. Using deep learning techniques, this study extracts text from videos and measured the videos' tones, including factual and emotional tones. Additionally, we measure the aesthetic score by analyzing the thumbnail images in the data. We then empirically show that the cognitive features of a video, such as the tone of a message and the aesthetic assessment of a thumbnail image, play an important role in determining videos' long-term popularity. We believe that this is the first study of its kind to examine new factors that aid in ensuring a video remains popular using both deep learning and econometric methodologies.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.175-181
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• 2024

The paper examines the impact of digital media art on urban creative products, analyzing opportunities and challenges in the digital era. It emphasizes the development of urban cultural and creative products, highlighting their significance and future growth potential. The digital media era provides unprecedented innovation opportunities, utilizing advanced tools for efficient design, production, and marketing. Trends like personalization, customization, AI, and big data offer new expressions and market prospects. Cultural products evolve in design, marketing, and sales channels due to digital media, with tools like social media and e-commerce platforms opening new promotion avenues. Case studies illustrate digital media's role in driving innovation and enhancing user experiences. The paper addresses challenges in market competition, copyright, and technological renewal, while recognizing opportunities from AI and big data. The creative industries must adapt and innovate to remain relevant. Looking ahead, urban creative products will evolve under digitalization, relying on digital means to attract consumers and enhance brand value. Cultural products, beyond economic entities, disseminate urban culture and creative spirit. In the digital era, urban creative products demonstrate potential and necessity, prompting a reevaluation of digital technology's role. Through continuous innovation, this field contributes to cultural and economic levels, impacting urban characteristics and heritage. Urban creative products play an increasingly vital role in the global cultural and creative economy.

• Journal of Fashion Business
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• v.19 no.6
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• pp.82-100
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• 2015

Mobile fashion apps present much opportunity for marketers to engage consumers, however not all apps provide enough functions for their targeted audience. This study aims to determine how mobile fashion apps can be used to build brand community with consumer engagement. Qualitative data on fashion mobile apps were collected from the Apple app store and Android market during the spring and summer of 2015. A total of 110 fashion mobile apps were collected;, 50 apps were identified as apparel brands that either manufacture or sell apparel to consumers, which we categorized as "brand" fashion apps, and the remaining 60 were categorized as "non-brand" fashion apps. The result of the study can be summarized as below. The 60 non-brand fashion apps were grouped into 5 app types: shopping, searching, sharing, organizational, and informational. The main functions are for informational use and shopping needs, since at least half (31 apps) are used for either retrieving information or for shopping. However, in contrast, social networking and location were infrequent and not commonly utilized by these apps. The most common type of non-brand fashion apps available were shopping apps;, many shopping apps enable users to shop from several different websites and save their items into one universal shopping cart so that they only check out once. Most of these apps are informational and help consumers make more informed decisions on purchases;, in addition many offer location services to help consumers find these items in store. While these apps perform several functions, they do not link to social media. The 50 brand apps were grouped into 5 brand types: athletic, casual, fast fashion, luxury, and retailer. These apps were also checked for attributes to determine their functionality. The result shows that the main functions of brand fashion apps are for information (82% of the 50 apps) as well as location searching (72% of 50 apps). Conversely, these apps do not offer any photo sharing, and very few have organizational or community functions. Fashion mobile apps and m-marketing elements: To build brand community, mobile apps can be designed to motivate consumer's engagement with brands. The motivations of fashion mobile apps are useful in developing fashion mobile apps. Entertainment motives can be fulfilled with multimedia attributes, functionality motives are satisfied with organizational and location-based features, information motives with informational service, socialization with community and social network, learning and intellectual stimulation from informational attributes, and trend following through photo sharing. The 8 key attributes of mobile apps can correspond to the 4 m-marketing elements (i.e., Informative content, multimedia, interactions, and product promotions) that are further intertwined with m-branding elements. App Attributes and M-Marketing aim to Build Brand Community;, the eight key attributes can impact on 4 m-branding elements, which further contribute to building brand community by affecting consumers' perceptions of brands preference and advocacy, and their likelihood to be loyal.

• Journal of Distribution Science
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• v.13 no.10
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• pp.83-91
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• 2015

Purpose - The purpose of this study is to identify whether the operation of cultural centers in discount stores contributes to their profitability. Thus, this study is aimed at exploring how the lifestyles of customers who use the cultural centers influence their intention to use the discount stores. Specifically, the effect of shopping value on the correlation between the lifestyle types and usage intention of the customers were examined through a structured research model. To verify the effect, a survey on 139 customers of the Cultural Center of Nonghyup Hanaro Club's S branch was conducted and the valid questionnaires were used for analysis. Research design, data, and methodology - The findings are as follows. First, the lifestyles seeking self-realization had a positive effect on utilitarian value, and lifestyles seeking pop cultures had a positive effect on hedonic value. Second, the mediating effect of shopping value on the correlation between the lifestyle types and usage intention of the customers is as follows. Utilitarian value had a mediating effect only on the lifestyles seeking self-realization. In case of lifestyles seeking pop cultures, the use of Cultural Center had no effect on the intention to use the discount store. Third, an analysis of a revised research model revealed that the store usage intention of lifestyles seeking pop cultures can be enhanced by boosting the utilitarian value through hedonic value. Results - The findings suggest the following. Customers with lifestyles seeking self-realization, who value what is beneficial to them with little attention to the perceptions of others, are highly interested in the benefits they can gain from shopping. As for customers with lifestyles seeking pop cultures, they are highly likely to consume products popular in a particular culture such as new products and sports, based on financial stability they pursue. Thus, they prefer more subjective, personal experience, unlike consumers pursuing utilitarian value. Conclusions - As a result, the former pursues hedonic value gained in the process of shopping with fun and joy, rather than doing shopping with a particular purpose in mind. Therefore, Cultural Centers need to offer information that fits the lifestyles of the users so that they are more likely to use the discount stores. However, if the Cultural Centers offer unified, profit-driven products and information, just to increase their store sales, it can backfire, which occurred in the past. On the other hand, if they provide information that fits the lifestyles of the users, it can actually increase the sales. Also, the findings suggest that sophisticated marketing strategies that can boost the hedonic value of customers by linking the educational contents of Cultural Centers to actual shopping, which is beneficial to consumers, should be set and operated by discount stores. In particular, customers with lifestyles seeking self-realization can be encouraged to use the stores by making them recognize the utilitarian value. However, the use of Cultural Centers doesn't necessarily lead to higher sales among customers with lifestyles seeking pop cultures. As mentioned previously, unified marketing strategy is not as effective for Cultural Centers of large discount stores.

• Asia Marketing Journal
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• v.15 no.1
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• pp.155-168
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• 2013

This study describes consumers' movie choices in conjunction with other group members and attempts to reassess the effect of the online word of mouth (WOM) source in a joint decision context. The tendency of many people to go to movies in groups has been mentioned in previous literature but there is no modeling research that studies movie choice from the group decision perspective. We found that ignoring the group movie-going perspective can result in a misunderstanding, especially underestimation of genre preference and the impact of the WOM variables. Most of the studies to measure online WOM effects were done at the aggregate level, and the role of online WOM variables(volume vs valence) is mixed in the literature. We postulate that group-level analysis might offer insight to resolve these mixed understanding of WOM effects in the literature. We implemented the study via a random effect model with group-level heterogeneity. Romance, drama, and action were selected as genre variables; valence and volume were selected as online WOM variables. A choice-based conjoint survey was used for data collection and the models was estimated via Bayesian MCMC method. The empirical results show that (i) both genre and online WOM are important variables when consumers choose movies, especially as group, and (ii) the WOM valence effect are amplified more than the volume effect does as individuals are engaged in group decision. This research contributes to the literature in several ways. First, we investigate movie choice from a group movie-going perspective that is more realistic and consistent with the market behavior. Secondly, the study sheds new light on the WOM effect. At group-level, both valence and volume significantly affect movie choices, which adds to the understanding of the role of online WOM in consumers' movie choice.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.213-225
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• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

• Journal of information and communication convergence engineering
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• v.1 no.3
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• pp.150-156
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• 2003

This paper explored the use of an algorithm for the data mining and method in handling missing data which had generated enhanced association patterns observed using the data illustrated here. The evaluations showed that more association patterns are generated in the second analysis which suggests more meaningful rules than in the first situation. It showed that the model offer more precise and important association rules that is more valuable when applied for business decision making. With the discovery of accurate association rules or business patterns, strategies could be efficiently planned out and implemented to improve marketing schemes. This investigation gives rise to a number of interesting issues that could be explored further like the effect of outliers and missing data for detecting fraud and devious database entries.

• International Commerce and Information Review
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• v.8 no.2
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• pp.165-183
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• 2006

Sea transport industry is service industry and basic industry that permit efficient division of the human and material resources of industry. Also, owing to geographical situation which korea is having, utilization ratio of sea logistics industry is high than other transport ways. Sea transport industry chieves role that promote economy activity of other industry field as well as offer of transport way. Specially, because unit anger of freight by container is introduced, it was achived reduction of transport unit cost and mechanization of loading and unloading by this result. For efficeint connection of each other transport, contianer had offerd to large ship. Quality of service has much dimensions, and is considered while it is important that understand quality of service of sea transport industry through marketing and research of customer connection field because perceive of quality of serviceis different in shipowner/service viscount or shipper/freight owner. This research presented decision factors of sea transport quality of service which shipper and transport agent recognize under these background.

• Culinary science and hospitality research
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• v.13 no.1 s.32
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• pp.192-203
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• 2007

The purpose of this study is to figure out the plans to improve business in Hotel French restaurants. This study conducts documentary study and empirical study. To achieve the purpose, a survey was conducted by 172 staffs of Hotel French restaurants in Seoul. The result of this research is as follows. Hotel restaurant operators recognize the importance of promotion and development of new sales goods. But they haven't done long-term marketing directions focusing on cost-saving and ephemeral sales promotion effects. Hotel restaurants should establish public information strategies uniformly and look for the plans that offer customers adequate information. Also, they should make a differentiation strategy within the same industry, can always give recency to customers, and enhance the event-connecting promotion menu and business activation.