大竹 恒平

For retail industry such as supermarket and convenience store, it is important to understand customers. In marketing perspective, to match marketing activity to customer needs is one of the most important strategy for retail industry. In this study, we focus on trade area of retail store. If we can grasp the trade size of a store, manager can plan optimal strategy, e.g. how to spend for advertise activity and where we should open a new store. In this study, we use ID-POS data which is the purchase record with customer identification data of a super market chain and calculate the trade area radius, then we show the cause and effect model to estimate trade area size using store causal data. Moreover, we evaluate our model and discuss how to be decided the trade area size.

In this study, we analyze cancellation factors based on the characteristics of golf courses in reservation sites. Firstly, we classify each golf course using causal data such as price range, course type and capacity and review data using k-means clustering. As a result, golf courses were classified into four clusters and we analyzed characteristics of golf courses each cluster. Secondly, in order to identify factor of cancellation each characteristic of golf courses, we performed logistic regression analysis targeting on each cluster using golf course reservation data and user attribute data. From the result of these analysis, we identified same common cancellation factors and different cancellation factors by characteristics of each golf course.

In recent years, acquisition of repeat customers is emphasized for EC sites. On the other hand, the defection rate from the first purchase to the second purchase is the highest. There are much attention to acquire the repeat customers in the EC sites in this situation. The purpose of this study is to clarify factors necessary for acquiring repeat customers. Especially, we construct models that predict whether or not to repurchase within a certain period using membership information variables, purchase behavior variables and web browsing behavior variables. Using these models, we extract characteristics relate to presence or absence of repurchase and propose marketing measures to promote to repurchase.

Along with the growth of internet market a shopping, retailers such as supermarket chains need a strategy corresponding to customers in each store. The purpose of this research using ID-POS data of supermarket chain is to clarify customer characteristics and purchase behavior for each store. First of all, we categorize stores based on causal data concerning each store such as sales floor area and peripheral population. Second, we analyze customer’s purchasing behavior using ID-POS data for each class that we tried to classify above, and extract characteristic purchasing behavior. Finely we evaluate these results together and clarify customer characteristics and purchasing behavior for each store causal.

Computer programming education is being given increasing importance in many universities in Japan. But conventional classes do not allow enough time to cultivate computer programming skills. One of the effective methods for cultivating computer programming skills is a collaborative learning method in voluntary community. However, it is difficult to maintain a student’s motivation in such a voluntary community. On the other hand, Gamification has attracted much attention recently as a method to help users to maintain and improve their motivation. In this research, we propose a support system to emphasize collaborative learning in a voluntary community by using Gamification. The experimental results confirmed that our proposed system was effective in supporting the cultivation of computer programming skills.

Widespread popularization of social networking services (SNSs) promoted, many studies about marketing activities using SNSs. But, there are a few studies focused on tendencies of consumer communities on SNSs. In this paper, we focus on a fashion brand and "Instagram". And we study about tendencies of consumer communities on SNSs to present necessary information for users effectively. From the results of our analysis, we found that there was a community which was formed of users who had high degree of loyalty in "Fashion Brand A". Moreover, as the result of analysis of user behavior, the presence of loyal customers in the community was confirmed.

Recently Electronic Commerce (EC) have attracted much attention and widely popular. Whence recommendations which understand user's feelings and sort out the goods the user desires attract attention. On the other hand, cancellation behavior can be large risk at EC companies which handles use of service at facilities such as hotel rooms and golf courses as products. We try analyzing to decrease the canceling ratio caused by the inner factors which are come from customer's mind. We recommend item which understands customer's true needs by analyzing reservation and data of behavior log including actual cancellation. We also inspected the utility of the cancellation data and the constrain conditions for model building using a Bayesian network. We show that it is possible to contribute to accuracy improvement of a recommendation for the cancellation data.

In this study, we try to measure customer loyalty attract high attention from the viewpoint of customer relationship management (CRM). From this scape there are a few studies to measure the loyalty of the customers. However, these studies have not considered the potential customer features. In this study, we focus on EC site, then we additionaly consider the behavior out of the site as well as the behavior in the site for a customer. By doing so, we caught a wide variety of customer behavior by adding the behavior data out of the site and could identify a loyal customer more appropriately. In this study, we propose a model which is able to classify a loyal customer to discover a customer who has high loyalty to the EC site. For modeling, we used the behavior data out of the EC site in addition to RFM (Recency, Frequency, Monetary) gotten from purchasing data. In addition, based on the result of the precedent study, we adopted logistic regression to analyze the purchasing history of the loyal customer identified in the discriminant model. We try to grasp the purchasing tendency of a customer having high loyalty by analyzing the purchasing data of the loyal customer. In this study, We classified loyal customer into 3 classes CustomerA, Customer-B or Customer-C. We compared the precision by the RFM model and the our RFMO model. As a result, RFMO model can more classify loyal customer and the other customer with high precision compared with RFMmodel about CustomerA and Customer-B. In addition, it was shown that purchasing tendencies is difference at each loyal customers.

Big Data is growing remarkably with technological development. In the field of business, there is growing trend which try to find useful information to marketing activities from the enormous data. However, data analysis needs knowledge about data structures and programming skills. It is difficult for general employees to acquire these. In this study, we propose a system which visualizes the relation between the goods by using POS (point of sales) data with IDs of a supermarket. We think that the analysts do not have the pre-requisite skills of programming, they can understand the relation between the goods by using our proposal system easily. Then as the proposal system turns into a web application, they are able to share the result of analysis by using a web browser. It becomes clear that our proposal system is effective through a result of the interview evaluation.

Recently, reviews of goods are one of the important factors which have an influence on the consumer's buying behavior. Under the situation, information aggregation of reviews has attracted much attention in electronic commerce (EC) site. In this study we propose a review recommendation system target on golf EC site. In our proposal system, reviews are scored by the evaluation of characteristic words which were obtained by TF-IDF and reputation analysis. Moreover, our proposal system visualize concurrent network using concurrent relations between the characteristic words. In order to verify the effectiveness of our proposal system, we conducted an experimental evaluation. In the experimental evaluation, we compared our proposal reviews with other review (selected randomly, recently date and reference counts). As the result, it was found that the result score of our proposed reviews were almost the same as the result score of reference count. Moreover, we received positive evaluation about concurrent network. Through these experimental evaluate, we consider that the effectiveness of this system was successfully verified.

This study targets social login registrants on an EC site and aims to clarify the difference between the purchasing tendency of social login registrants and general members by analyzing product purchasing history. We focused on the golf portal site that is the subject of this research. We analyzed the purchasing data comparing social login registrants with general members. As the results, it became clear that social login registrants have less resistance to purchasing expensive products on an EC site compared with general members and golf clubs act as a bridge for purchasing.

Widespread popularization of social networking services (SNSs) prompted, for example, a voluntary community such as an orchestra club of a university to use an SNS to support their activities. However, it is not all-purpose and lacks functions to improve members' individual skills. Appropriate practice is a great help but we hardly find functions to motivate practices by, for instance, mutual evaluation, members' advice, and creating competing environment. In this paper, we focus on members' individual practices in an orchestra club and propose a SNS to foster and maintain their motivations to practice based on the analysis result of current conditions. As the first step of the system development, this paper introduces design of a prototype system and the results of a preliminary evaluation.

In this paper, we propose a method to visualize information regarding hobbies and interests of a person inferred from tweets on Twitter to support informal communication in the real world. Analysis of the current states and experiments on informal communication clarified that it is important and useful for a person to know information such as hobbies, interests and other attributes which indicate background of his/her partner to start and maintain a first and good meeting. Through experimental results, we demonstrated that our proposed social profile diagram was effective for informal communication.

In this research, we built a support system for improving motivation by utilizing gamification, targeting one university circle, the Senshu University Philharmonic Orchestra, as an example of voluntary communities. The purpose of this research was to maintain and improve the motives of each individual orchestra member for practice. Analysis of the current conditions clarified the following two factors as obstacles for improving the motivation of section members: «It is difficult to realize one's own practice achievements» and «Achievement level of practice of other members are unknown». In order to solve these problems, we built a system that visualized practice achievements and enabled sharing of the information among section members, with applying the concept of gamification in order to reinforce these functions. Through the experimental result, we consider that the effectiveness of this system was successfully verified. © 2014 Springer International Publishing Switzerland.

Recently, social games have attracted considerable attention. Building a relationship with other players can heighten the enjoyment derived from these games. However, many users play social games only with their fixed friends. There are functions to assist users to find friends in social games and SNS, but the existing functions are not simple enough to find friends easily. In our previous research, we proposed methods of reducing the barrier that hinders making contact with unknown users. In this study, we propose a function to facilitate finding new friends using these methods. © 2013 Springer-Verlag Berlin Heidelberg.

With the widespread of Internet, 'Contents' on Internet are increasing. And, contents offered on Internet are transformed from a unique service into an undifferentiated service (Commodification of the Internet contents). And users' concerns may be changing from the value of contents to other in the near future. In social games, we think that the selection criteria will change from the value of contents to the value of the community. So, it is important for Social Game suppliers to offer the function to improve the quality of community. In this paper, we aim to examine how to improve the quality of community. We focus on Q&amp A sites that have services to improve the quality of community. We analyze the structure of the community and consider the factors to improve the quality of community. © 2011 Springer-Verlag.