Yumi Asahi

Analysis Using Purchasing Data in Japan

Purchasing style of Japanese consumers have made their own development. Purchase of goods with a large amount once a month or once a few weeks is a kind of global standard. On the contrary, purchase of goods with a small amount once in couple of days is common in purchasing style of Japanese consumers. Purchase of goods with a large amount in a weekend is recently getting to increase however the interval is a week at the longest.

User needs search using text mining

In recent years, people came to write the opinion of them by social networking service, such as a twitter, mixi, a blog. However, it is the present conditions that we cannot analyze it though we can watch a lot of opinions. Answer to choice is important, but opinion in a free writing conveys a thought concretely. From it, the authors considered using text mining in the spot. By doing text mining, it can enumerate frequent appearance word and we can know users needs. The width of the analysis thereby spreads. For example, those who say a specific word find out in what kind of tendency it is. The authors can think about the product development that we matched with each user from there. In addition, it can compare the opinion by various approaches. In this way, Text mining is an effective way to take advantage of users voice.

Factor Analysis of the Batting Average

This study is factor analysis of the batting average in the professional baseball in Japan. We analyze the factor influencing the batting average using the Japanese professional baseball data. There is no established method to ensure a good shot at Japanese baseball. Based on the results, clarify factors that prevent pitchers from hitting hits and factors that batters increase hits. And establish baseball teaching methods based on the clarified factor. Finally, we aim to improve the level of the professional baseball world of Japan.

Characteristic Analysis of Each Store in Japanese Hair Salon

There are 223,645 Hair salons in Japan in 2011. Those same about quadruple amount of Japanese convenience store. From these things, we can know that there are many Hair salon in Japan. Hair salon moved and there are close stores about 9,000 a year. However new open chain stores about 12,000 therefore Hair salon increasing about 3,000 stores a year of Hair salon in Japan. Hair salon were group at Kanto region and Kinki region because they are high population density in Japan. The struggle for existence Hair salon are store excess also a lot of hair salon are small scale and they are micro enterprises. In that sense, Hair salon are faces severe competition. Customer’s hair salon usages frequency is woman 4.5 times a year, men 5.38 times a year. The amount of usage per one times is women 6429 yen, men 4067 yen. Men are more frequently used, and the usage amount is increasing. However, the usage women’s rate frequency of Hair salon more than men’s rate frequency of hair salon. We use the data is all over Japan of a certain hair salon chain stores of this study. This was provided by Joint Association Study group of Managements Science (JASMAC) 2017 Data Analysis Competition. According to basic statistics, there are many customers with one visit to the store in this hair salon thus high customer rates. A certain hair salon have many people who are 30 to 60 years old. One of 12 stores are a male salon. We used Quantification category 3 that infer the characteristics of customers also, we predict store characteristics from the characteristics of customers. However, it was mixed Mathematical data and Qualitative data thus we had to unify the scale. Therefore, we converted Mathematical data and Qualitative data. As a result, we used Quantification category 3. We Interpreted compound variable answer1 is “Neighboring a working woman and office worker who want to quietness”. Answer2 is a customer who emphasize of high temperature and high-quality care. Cluster analysis has Hierarchical approach and Nonhierarchical approach. Nonhierarchical approach be able used for small data on the other hands Hierarchical approach can be used to big data. Therefor we adopted Hierarchical approach. We needed to decide on a group when we used Hierarchical approach. However, it was objectively lacking, and it had disadvantages of reduced reliability if you have decided the number of groups before this analysis. Therefore, we did cluster analysis in several times in addition we decided the number of groups by squared residual sum of squares in cluster. We created an elbow diagram. The difference in the residual sum of squares within the group is It was shrinking sharply smaller than Groups 4 to 5 thus we decided the number of groups to 5 in addition we did k-means method. When initial value of each result, big differences occur in size of group and convergence value. K-means method needs the best solution in multiple analyzes. In this research, we had the purpose to stores characteristic. We developed one-way analysis of variance and multiple comparison by compound variable, answer1 and answer2. We had the purpose to develop that analysis. The purpose was if we did not have significant difference, we would not classify every characteristic. One-way analysis of variance used compound variable, answer1 and answer2. Therefore, we used nonparametric method because those were not normal distribution. Nonparametric method has multiple test method. We used Games-Howell method in this research. Games-Howell method was matching in this research because it did not assumption homoscedastic. We used result hierarchical approach cluster analysis from First time to fourth time. We developed one-way analysis of variance and multiple comparison. The result, we adopted 2’nd time because it is classified definite characteristic. In addition, first time, 3’rd time and fourth time had significant difference one-way analysis of variance. However, there were combination in multiple comparison that did not have significant difference. We developed one-way analysis of variance with result of 2’nd time and compound variable. If answer1 shows a large value to minus, we infer that the customer want glamorous and has enough time to coming from afar. If answer2 shows a large value to minus, we infer that customer important care for low temperature and low humidity. We founded by one-way analysis of variance that there was a difference each group. We divided for each store the group. Then we were find difference in store characteristics. In addition, we suggested optimal marketing strategy based on result of analysis against each store. We will increase the synthesis and make finer interpretations.

Analysis of Trends of Purchasers of Motorcycles in Latin America

The Latin American economy experienced the currency crisis and the associated confusion from the early 1990s through the early 2000s. Since 2003, rapid economic growth has been achieved. As a result, in Latin America “A” country, the impact of external demand led to the expansion of the consumer finance market. Furthermore, financial services expanded due to income disparity correction policy implemented from 2003 to 2010. By these, purchasers due to loans increased of motorcycle and automobile, but on the other hand rate of loans outstanding increased. In this research, we look for factors of loans outstanding from customer data. The data used in this study is customer data of anonymized motorcycles in Latin America “A” country from September 2010 to June 2012. From the usage data it turns out that the proportion of loans standing is high. Therefore, it is necessary to extract variables that are factors of loans outstanding. From there, it is necessary to grasp the characteristics of loans outstanding. The analysis flow is data cleaning, basic aggregation, grouping of data, variable extraction, binomial logistic regression analysis. Data is organized by data cleaning. Data was grouped by income amount by grouping of data Basic aggregation allows to determine the characteristics of the data. Next, we extract the variables that cause the factor of loans outstanding by AUC. Finally, binomial logistic regression analysis finds out how the variables extracted by AUC affect loans outstanding. In addition, analysis results and Beforehand studies have considered that specific variables greatly affect loans outstanding. Therefore, this studies deeply dig up that variable. Based on the results of the analysis, we explore the tendency of loans outstanding.

Analysis of Factor of Scoring of Japanese Professional Football League

In “The Japan Professional Football League (J League)”, the number of customers is increasing every year since 2011. The Japanese football team participates in the Russian World Cup in 2018. Therefore, J league market is expected to become more active. In this research, we analyze the score trend of the league with the aim of proposing tactics and training for the J League team. In each piece of data, position information obtained by dividing a field into an X-axis and a Y-axis are given. Therefore, in the data to use, this research pay attention to the data on the play involved in the score and the position where the play started. In this study, first, cluster analysis is performed to classify the start position of play involved in scores. After that, factor analysis and covariance structure analysis are carried out, and the play highly relevant to the score is discovered. Before analysis, data cleaning is carried out so that similar variables did not exhibit a strong correlation. First, the start position of the play involved in scores is classified by cluster analysis. From the score data, play related to the score was extracted and classified. After this, good results have been obtained with clusters showing mainly attacks from their own field. Therefore, in Japanese professional football, it can be predicted that there is some tendency in score from own field. Next, factor analysis/covariance structure analysis is performed on each cluster, and tactics related to scores are discovered. Factor analysis was conducted and latent variables related to the score were extracted. Define that latent variable as a score-related tactic and analyze the relationship between different tactics using covariance structure analysis. Those with low relevance are considered independent tactics. From the analysis results, in J League found that “side attack” and “pass to empty space” are strongly related to the score. Also, on the left side of the field, the score tendency using “dribbling” was weak. Japanese players, this can be expected to be related to having few players using left foot more than the right. Therefore, it is possible to propose “training of side attacker with excellent physical strength and speed” and “counterattack/strengthen side attack”. Furthermore, we found out that it is a task to put emphasis on cultivating left-handed players. This analysis focused on the attack from the own field. The future task is to analyze the attack pattern from the enemy field and judge whether it is haste from the length of attack time.

Career that Tend to be Unpaid for Motorcycles Sales Loans

Country A is in Latin America and GDP is lower than average. Prices of Japanese products such as motorcycles are on an upward trend. It was influenced by instability of the world economy. The customer selects loan payment. Among them, some customers cannot pay for the specified payment period. If this situation deteriorates, it will be difficult to recover manufacturing costs. Therefore, we analyze the characteristics of customers who loan bankruptcy.

Analysis and Consideration of the Relationship Between Audience Rating and Purchasing Behaviors of TV Programs

Chocolate has been increasing in Japan domestic consumption. It is eaten regardless of the age from the adult to the child. Variety is abundant, it is one of convenient and familiar sweets for Japanese people. There are many days when we watch television on a confectionery company that sells such chocolate on TV. But, in Japan people who watch television are getting less. According to the Ministry of Internal Affairs and Communications data of 2013, the average viewing time of real-time TV on weekdays was 168.3 min [1]. The weekday average for the last year was 184.7 min. It was 16.4 min (about 9%) decrease. The average for 2011 (including holiday data) was 228.0 min. It was found to be 59.7 min difference. The total advertising expenditure in Japan totaled 5,769.6 billion yen in 2011. Terrestrial broadcasting usage is 1,723.7 billion yen (about 30.2%) [3]. Total in 2013 is 5,976.2 billion yen. Terrestrial broadcasting usage is 1,719.1 billion yen (about 30.0%). The total of advertising expenditure increased slightly in two years. It does not change that it occupies much of advertisement expenditure as present condition. We can think that Japanese television is still the main information dis-semination medium. Therefore, even if the TV viewing went down, we clarify whether there is a relationship with purchasing. We revealed it by decision tree analysis.

Analysis to the Customer of the EC Site User

Now, in Japan business of clothes with E-commerce(EC) is done activity. Sales of direct sales store and outlets is decreasing, so a number of its store to close are increasing. It’s expected that Sales with EC site and market size continue to increase from now on. In this circumstance, in order to develop EC site which scale shows a great growth, we have done a calculation of the factor score through the questionnaire items, and classification of customer with questionnaire date and customer’s record to purchase. After this, we have grasped the characteristics of classified customer information, and compared some clusters. As a result, the characteristics of customer cluster regarded as “fashionable” must be gotten close to its not customer cluster. “Not fashionable” customers have higher average value of “frequency of purchase” and “expenses of purchase” per customers, therefore, it’s expected increasing of sales and expand of its size.

Analysis of the Consumption Action Behavior that Considered a Season

In 2015, Internet use rate in Japan exceeded 82%, smartphone penetration rate exceeded 64%. And, utilization of online shopping was the third in the Japanese ICT services usage. In all ages, its utilization rate exceeded 68%. In the 2011 data that smartphones like iPhone and Android mobile phones began to spread, the use of net shopping was also the third most common. However, attention to utilization ratio, it is 64% in the 20s to 40s, slightly lower than in 2015. In the 50s, it is 51.5%, more than 10% lower. In the 60s and over, it is 36.7%, which is about half as low as 2015. Internet and smartphones popularized, and online shopping became familiar. Net business has become a big market in Japan. To the extent it can not be ignored. This report used purchase data of the Internet shopping site. From the basic statistics we found the following. Users are 65.9% for females and 34.1% for men. There are so many women to use. About the user’s age, the over 40’s (21.9%) is the most. Next was the result of early 30s (20.2%) and late 20s (19.2%). The population of Japan in 2015 is 59.00% in the over 40s. On the other hand, 5.99% in the early 30s and 5.40% in the latter half of the 20s. It is thought that users increase if the population number is large. Therefore, the main target is not over 40’s, it is considered to be in the early 30’s and the latter half of 20’s. About the time when it is selling. The month with the highest sales is January which accounts for 13.4% of the total. The month with second sales is 11.1% in February, the third is 9.2% in December. Conversely, the month with the lowest sales is May and September, 5.8% of the total. The second is 6.2%, which is April. From this fact, it would be considered sell well are those in the winter season. About customer information. By prefecture, the largest number of Tokyo is 17.5%. It is about 50% of the total in the top six prefectures including that Tokyo. (Kanagawa prefecture 8.4%, Osaka prefecture 7.9%, Saitama prefecture 5.5%, Aichi prefecture 5.5%, Chiba prefecture 4.9%). This is the same ranking as the population ranking by prefecture in Japan. The largest number of registrants to the population is Tokyo. Besides, Kanagawa, Osaka and Kyoto prefectures were more than other prefectures. These four prefectures are the center of the west and east city. The method used covariance analysis and factor analysis. We modeled it about seasonal consumption behavior. The axis of analysis is “When do people buy things?”