Kohei Otake

Proposal of the Support Tool for After-Class Work based on the Online Threaded Bulletin Board

In this paper, based on the assumption that after-class work in an exercise-based course accompanied by group work is done on an online threaded bulletin board system, the authors propose a support tool for the instructors. Specifically, while focusing on the factors that compose a discussion on the online bulletin board, the users who comment, the topics, and the items (keywords) to be discussed, the authors try to visualize the relationships among these factors as network diagrams. The authors also propose indexes, the comment degree and the activation degree, to evaluate communities formed there. Our experiments in which group work was actually implemented with the application of the proposed tool demonstrated that use of the network diagrams and the evaluation indexes served to distinguish the differences between those groups with properly-proceeding discussions and those without such discussions. The authors confirmed that this can enable the instructors to easily discover those students who do not participate in the discussion and groups with sluggish discussions.

A Proposal of an SNS to Support Individual Practices in a Voluntary Community

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.

A Proposal of SNS to Improve Member's Motivation in Voluntary Community Using Gamification

Recently, the number of voluntary communities such as local communities and university club activities are in- creasing. In these communities, since there are various types of members and there are no binding forces, it is usually difficult to maintain and improve members motivation. To maintain and improve members motivation, most of these communities use social networking services (SNSs). However, since existing SNS offer few functions for voluntary community, it is difficult to solve this problem. This research focused on the concept of gami- fication and proposed an SNS to improve members motivation of voluntary community. First, the authors analyzed the current conditions and members of a voluntary community. Based on this analysis, the authors found that an SNS to improve members motivation of voluntary community requires functions which support members personal activities and also functions which increase social activities. Next, the authors built an SNS that had these functions by applying the concept of gamification. The authors implemented the SNS for a University clubs activities for one month and showed the effectiveness of our SNS.

Examination of the effect of social login through analysis of user's purchasing tendency

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.

Evaluation of Network Structure Using Similarity of Posts on Twitter

Social networking service (SNS) is very popular in our lives, with expanding internet environments and mobile device. Through the SNS, user can submit their opinion or reputation freely, anytime and anywhere. These activities are getting great attention on a various business scenes in recently. Twitter is one of the most popular SNS, and used by numerous people in the world. In addition, since various information is posted on Twitter, it is expected to be utilized as a business strategy, and there have been many studies on the marketing using Twitter data. Moreover, we can get some information about user’s network in Twitter. In this research, we attempt to evaluate the network structure using similarity of post on Twitter. We created the user network using similarity of posts mentioned about four titles of Japanese TV drama, and we grasped the post categories that is easy to get user’s interest. From the result, we discussed the difference between TV drama and suggestions for promotion strategies of TV drama production company.

Evaluation of Store Layout Using Eye Tracking Data in Fashion Brand Store

In this study, we conducted purchasing simulation experiment using eye tracking device in fashion brand store. Using the gaze measurement data obtained through experiments, we conducted several analyses to evaluate the store layout. Firstly, we divided the inside of the store into several areas. We tried to identify the areas that can become areas that are easily visible (Golden Zone) by performing multiple comparison on visual time for each area. Through the result, we identify the area that could be Golden Zone. In addition, it became clarifying that the characteristics of the areas which can become Golden Zone. Secondly, we tried to clarify that relationship between good impression item and visual time. It is clarified that there had a positive correlation between “Purchasing time” and “The number of item held in hand.” Moreover, “Purchasing time” and “The number of good impression item” also had a positive correlation. From the results, we proposed improvement plans for better store layout.

Proposal of Learning Support SNS Utilizing Gamification.

Recently, a learning support system using the internet is often used in the field of education. However, many of them focus only on improving academic ability and communication among students. Also, as education problem in Japan, there is a lack of voluntary and learning motivation. In this research, we aim to propose a system to promote student’s self-learning motivation to learn and establishment of learning habits. The proposed system enables well communication not only among students but also between students and teachers. We also utilize gamification for the proposed system. We believe that propose system can effectively promote student’s self-learning motivation and establishment of learning habits. Finally, we describe an experiment plan using the propose system.

Analysis of the Characteristics of Repeat Customer in a Golf EC Site

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.

Analysis of Trade Area for Retail Industry Store Using Consumer Purchase Record

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.

Analysis of Cancellation Factors Based on the Characteristics of Golf Courses in Reservation Sites

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.