Katsutoshi Yada

Katsutoshi Yada
Kansai University · Faculty of Business and Commerce

Doctor of Business Administration

About

110
Publications
43,102
Reads
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819
Citations
Introduction
Katsutoshi Yada is Professor of Management Information Systems in the Faculty of Business and Commerce, Kansai University and guest professor of Osaka University. He was a visiting scholar of School of business at Columbia University from 2006 to 2007. He is currently the director of Data Science Laboratory at Kansai University. His present research interests include data mining for business, and information strategy concerning data mining. His papers have appeared in several international journals, including Data Mining and Knowledge Discovery, Soft Computing, Decision Support Systems and others. He received Distinguished Professor Award from Kansai University and many international and domestic awards from academic societies.
Additional affiliations
April 2000 - present
Kansai University
Position
  • Professor (Full)

Publications

Publications (110)
Article
Full-text available
In field of location prediction, trajectory recognition is one of the most widely research issues. Since trajectory includes various information such as position, time, and speed, many scientific methods are applied to extracting meaningful features, and discovering valuable knowledges. This paper pays more attention on case study of in-store traje...
Article
During the last decade, an increasing number of supermarkets have begun to use RFID technology to track consumers' in-store movements to collect data on their shopping behavioral. Marketers hope that such new types of RFID data will improve the accuracy of the existing customer segmentation, and provide effective marketing positioning from the cust...
Article
Anecdotal evidence has shown that retail price promotions can help small and medium-sized retailers enhance their sales, and thus profits. However, most marketing managers usually stop a promotion after a certain duration. This study aims to explain why these retailers discontinue their price promotion. Our approach posits that overall contribution...
Book
This book constitutes extended, revised, and selected papers from the 12th International Symposium on Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2020. Organized in the Tokyo Institute of Technology, it was held virtually due to COVID-19 pandemic. The 19 full papers were carefully selected from 5...
Article
Full-text available
Studies based on the analysis of a new design of loyalty program, item-based loyalty programs (IBLPs), indicate that customers are more interested in item-based reward points than in traditional price discounts. However, we are still unaware of customer responses to the different point settings on IBLP items. This study investigates an analysis wit...
Book
This book presents selected and extended papers from the largest conference on artificial intelligence in Japan, which was expanded into an internationalized event for the first time in 2019: the 33rd Annual Conference of the Japanese Society for Artificial Intelligence (JSAI 2019), held on June 4–June 7, 2019 at TOKI MESSE in Niigata, Japan. The...
Chapter
Full-text available
The scope of this research lies in big data analysis. First of all, the urgency of the problem of not analyzing most of the information that can be recorded and analyzed to improve the functioning of any area of life is stated. Second, the case of a grocery store is used in order to identify useful dependencies. The data from the store contains inf...
Article
Full-text available
The purpose of this study is to develop a new method for handling social influence in the analysis of shopping path data by using the ecological system of ants. Social influence which shoppers effect on each other is believed to contained in shopping path data collected in a retail store. The existing study measured social influence by using “densi...
Article
Full-text available
The purpose of this research is to clarify what impact the regulatory resources of the customer have on search behavior and the resultant search benefit. Regulatory resources of the customer engendered by failure of self-control on the part of the customer change along with the string of purchase decisions made in-store. This paper examines the imp...
Article
Full-text available
Recent years have seen active research that utilizes information combining geographic data and sensor data, called geospatial information, in urban planning, medical care and marketing. In this study, we focus on RFID technology that records position information (i.e., spatial information) of shopping carts in a supermarket, and estimate the latent...
Conference Paper
Due to the development of ecommerce, recommendation systems are becoming increasingly common in daily life, and essential for business. Most conventional recommendation systems are based on purchase frequency obtained from sales data. We found no system based on similarity of purchase processes, like customers' in-store behavior. Therefore, we prop...
Article
Full-text available
This paper aims to use fractal dimensions to quantify the complexity of customer in-store movements, and proposes a purchase model factoring in the effects of complex customer movements on purchase behavior. We used the box-counting method to calculate the fractal dimension of shopping paths and investigated its relationships with basket size and s...
Article
Full-text available
The purpose of this study is to verify the effectiveness of a data-driven approach for financial statement analysis. In the area of accounting, variable selection for construction of models to predict firm's earnings based on financial statement data has been addressed from perspectives of corporate valuation theory, etc., but there has not been en...
Article
Full-text available
Data about the shopping paths of customers in stores are now available due to developments in radio frequency identifica- tion technology. In this study, we conducted clustering of the shopping paths of customers gathered in a grocery store in Japan. We obtained nine typical movement patterns from the clustering results. In addition, we associated...
Article
Full-text available
In grocery stores, large-scale transaction data with identification, such as point of sales (POS) data, is being accumulated as a result of the introduction of frequent shopper programs. We propose two recommendation systems based on transaction data of a grocery store. In recommending product items in grocery stores, data sparsity is a problem. Th...
Article
Full-text available
The purpose of this research paper is to render the customer-shopping path and customer existence probability visible such that people in the marketing field can easily grasp customer behaviors in store. To achieve this, we introduced the customer existence probability, which provides a visual of how long customers stay in each sales floor zone. Th...
Article
Full-text available
The purpose of this article is to verify the effect of previous purchases on later purchases, using shopping path data. We focus on the effect of vice category products bought before. In existing research, the effect of the prior purchase of virtue category products (which are relative necessities) on later purchases, is explained as licensing effe...
Conference Paper
In strategic management of retail industry, the advanced investigation by using radio frequency identification (RFID) technology to capture customers’ in-store behavior has been dramatically attracted scholars and practitioners in past ten years. As a small RFID tag attached to the shopping carts can be recognized as surrogates instead of enumerato...
Chapter
In this paper, we introduce a research project involving the use of various types of data mining technology to analyze Internet Mall Web log data. The objective of this paper is to clarify, using descriptive methods, the process of discovering new knowledge using WEB log data to investigate consumer behavior.
Article
Full-text available
Consumers classification is one of the most important task in the retail sector. RFID (Radio Frequency IDentification) - A wireless non-contact technology is made easier to classify the consumers’ in-store behavior, recently. This paper presents an extraction of consumer purchasing behavior using statistical learning theory SVM (Support Vector Mach...
Article
Full-text available
Basic necessities are generally said to be price inelastic in comparison with luxury goods. However, within the former group, it is not easy to differentiate between milk products using factors other price. Therefore, price could be an important factor when deciding between milk products. In this study, we verify the hypothesis that milk products a...
Conference Paper
This paper represents our recent studies about the prediction of purchase behavior and an advancement of in-store behavior with respect to RFID technology. In contrast to prior innovators in this research field, this paper has paid special attention to stay time spent on shopping in a target area rather than the whole supermarket, which can serve u...
Conference Paper
Full-text available
Effective category management by grocery stores requires product category evaluation. Previous studies have evaluated product categories using point-of-sales shopping behavior data. Recent developments in radio frequency identificatio technology facilitate the tracking of customer shopping paths within a store and aggregated stay time in sales area...
Article
Full-text available
Developments in radio frequency identification (RFID) technology have resulted in the availability of data on customers’ movement paths in various stores. In this paper, we propose a customer behavior model in a grocery store by using RFID and point-of-sales data. This model is based on a nonhomogeneous hidden Markov model with covariates and estim...
Chapter
In recent years, amidst advancing globalization of the global economy, in both developed and developing countries, the services sector is becoming increasingly important in various fields [2, 9]. In developed countries, service industries comprise a very high percentage of GDP, and even in manufacturing, in order to gain a competitive advantage, th...
Article
In this study, we propose a method to analyze shoppers' in-store behavior. Our method focuses on the migration of customer groups between areas placed on the inner side of a store. We represent this migration by a set of simple shopping path models based on left-to-right Hidden Markov Models. The parameters of the corresponding set of models provid...
Book
Virtually all nontrivial and modern service related problems and systems involve data volumes and types that clearly fall into what is presently meant as "big data", that is, are huge, heterogeneous, complex, distributed, etc. Data mining is a series of processes which include collecting and accumulating data, modeling phenomena, and discovering ne...
Conference Paper
Recently, a wireless non-contact technology named RFID(Radio Frequency Identification) has brought a new perspective on process of purchase decision. Via the RFID tag attached to a shopping cart, the position information of customers in a grocery store can be captured every moment. This paper presents our study based on this type of data. In this s...
Conference Paper
In grocery stores, discount flyers act as an important tool to provide discount information to customers and spur buying motivation among them. However, discount flyer have limited space. As customers purchase popular products even if they are not actively promoted, mentioning them on discount flyers is an ineffective strategy. Therefore, the prope...
Article
Full-text available
The development of sensor networks has enabled detailed tracking of customer behavior in stores. Shopping path data which records each customer’s position and time information is attracting attention as new marketing data. However, there are no proposed marketing models which can identify good customers from huge amounts of time series data on cust...
Article
Due to technological developments, data about how many items a customer buys and how long the customer spends in a supermarket are available. A major problem with the data, however, is that there is no framework that considers the heterogeneity hidden in the data. In this article, we propose a framework that considers heterogeneity in the number of...
Conference Paper
Developments in radio frequency identification (RFID) technology have made data on customer movement paths in supermarkets available. In this paper, we propose a method for customer behavior modeling by using RFID data and the hidden Markov model (HMM). In this method, "Stop" and "Pass by" behavior are estimated and the proposed method is evaluated...
Article
Full-text available
Thanks to the advancement of tracking technologies such as RFID (Radio Frequency Identification) in recent years, the study area of shopping behavior of consumers in retailing setting has globally regained increased interest. However, only few studies have attempted to analyze consumer shopping behavior using the RFID data. In this paper we postula...
Conference Paper
This study shows a method of determining and visualizing the existence probability of customers from shopping-path data in supermarkets using a database collected by a RFID (Radio Frequency Identification) technique, which allows us to analyze the detailed behaviors of customers. First, we present a method to estimate customer existence probability...
Conference Paper
This paper introduces an application of the data mining tool, MUSASHI (Mining Utilities and System Architecture for Scalable processing of Historical data), for scientific policy making. Recent advances in information systems have allowed researchers to gather enormous amounts of data on opinions about government policy. However, these gathered dat...
Article
In this study, the authors use radio-frequency identification RFID data, which show the position of a shopping cart through an RFID tag attached to the shopping cart. The RFID data contain valuable information for marketing, such as shopping time and distance as well as the number of shelf visits. The authors analyze customers' purchasing behavior...
Conference Paper
Due to developments in technology, movement data tracking a customer's movements in a supermarket in addition to conventional POS data are now available. A problem in analyzing such data is that an ordinary statistical model assuming customer homogeneity does not fit well to such data. In this article, we propose a framework for analyzing such data...
Conference Paper
Full-text available
RFID data obtained from customers' movements using radiofrequency identification (RFID) tags contain valuable information for marketing, such as shopping trip time and distance as well as the number of shelf visits. Customers' purchasing behavior and their in-store movements can be analyzed not only by using RFID data, but also by combining it with...
Conference Paper
Full-text available
Customer orientation is one of the important yet underresearched topics in the retailing management. In this paper we replicate and extend research by Groeppel-Klein and Bartmann (2008), analyzing the new type of data, namely RFID (Radio Frequency Identification) data, with the purpose to examine grocery shoppers' moving direction within the store...
Article
Full-text available
The sensor network technology developed in recent years has made it possible to accurately track the in-store behavior of customers which was previously indeterminable. The information on the in-store behavior of customers obtained by using this technology, namely information on their shopping path, provides us with useful information concerning th...
Conference Paper
Studying shopping behavior is an important and interesting topic for researchers and practitioners. With the improvement of technology in data collection and handling, it is possible and important to take full advantage of these data opportunities to analyze in-store shoppers' movements so as to understand shopping behavior from different standpoin...
Conference Paper
Service science has been raised, and coming to be established as a research domain all over the world. This workshop in Tokyo has been motivated by the systems-design dimension of the service science. We aim to share and discuss a progressive vision to develop methods for innovating systems of service resources where novel values are created and su...
Conference Paper
Full-text available
In this paper we analyze the new type of information, namely RFID (Radio Frequency Identification) data, collected from the experiment in one of the supermarkets in Japan in 2009. This new type of data allows us to capture different aspects of actual in-store behavior of a customer, e. g. the length of her shopping path. The purpose of this paper i...
Conference Paper
Radio Frequency Identification (RFID) technology uses radio waves to track an object to which a small tag is attached. In a Japanese supermarket, we attach the RFID device to the cart and collect data on purchase behavior. In this article, we clarify the relation between purchase probability and the time customers spend in the store section by anal...
Conference Paper
The objective of this paper is to introduce further development of a data mining tool, MUSASHI (Mining Utilities and System Architecture for Scalable processing of HIstorical data), for service computing. Recent advances in information systems have allowed us to gather enormous amounts of data on marketing. However, these gathered data have been in...
Conference Paper
Recently, supermarkets have been using RFID tags attached to shopping carts to track customers’ in-store movements and to collect data on their paths. Path data obtained from customers’ movements recorded in a spatial configuration contain valuable information for marketing. Customers’ purchase behavior and their in-store movements can be analyzed...
Article
Financial crises are severely impacting financial institutions, and each bank must now create strategies for responses to various financial risks. This paper aims to propose models for deposit outflows caused by various financial crises, and to present a framework of knowledge discovery required for bank management to create branch strategies and c...
Article
The workshop is aimed at bringing together researchers from the areas of the service sector and data mining. We expect to encourage an exchange of ideas and perceptions through the workshop, which is focused on service and data mining.
Article
No abstract received.
Article
In recent years, financial crises have occurred frequently in each region, and banks are facing harsh management environments. Bank runs of customers during a financial crisis are one of a bank’s most serious risks. This research aims to build a bank run model for financial crises, use that model to estimate the amount of deposit funds which flow o...
Conference Paper
This purpose of this study is to propose a knowledge-discovery system that can abstract helpful information from character strings representing shopper visits to product sections associated with positive and negative purchasing events by applying character string parsing technologies to stream data describing customer purchasing behavior inside a s...
Article
Decision tree methodology has become an increasingly important tool set in the field of decision science. We develop a multivariate, tree-based decision system for a new application: the determination of whether a newly launched consumer product should be allowed to continue in a highly competitive market. The system is designed to overcome a short...
Article
The aim of this paper is to propose a new system for the strategic use of customer data that includes and integrates such differing data sources as company databases, mobile telephone networks and Internet data and is a consumer research support system for the discovery of new marketing opportunities. This system, called CODIRO, will be discussed i...
Conference Paper
In this research, we discuss the business application of process data, being the massive accumulated time series of changing conditions. Unlike the data resulting from daily operations, process data includes rich information on operational processes. It is unstructured and becomes massive in scale. In this paper, we introduce a project in which we...
Article
The purpose of this research is to develop a framework to analyze the content and a process of persuading process and its application to the communication for the debt-collecting process. It is possible for us to understand how the skilled workers have used the keyword groups concerning the motivation to pay, the payment methods and the payment con...
Conference Paper
The purpose of this research is to develop a framework to represent the content and process of persuasion communications for overdue payment collection, thus making it possible to examine how the skilled operators have used theme related keywords concerning motivations to pay, the payment methods and the payment confirmation in their negotiation to...
Conference Paper
It is difficult to carry out quantitative measurements of the persuasive power of business communications (i.e., persuasive skills) and such communications are likely to involve difficult to understand, unseen and unknown knowledge. However, using unstructured recorded communication data based on conversations with business customers, we have been...
Conference Paper
The purpose of this paper is to introduce a process for implementing optimal pricing that uses PRISM to maximize store profits. PRISM is a system and process that uses data mining technology to process large volumes of data, then develops a probability model for customer purchases, and which then uses a heuristic approach to identify the pricing pa...
Conference Paper
The knowledge on the relation between a financial state of an enterprise and its future profit will efficiently and securely reduce the negative risk and increase the positive risk on the decision making needed in the management of the enterprise and the investment in stock markets. Generally speaking, the relation is considered to have a highly co...
Conference Paper
The aim of this paper is to discuss the development of a system for the discovery of valuable new knowledge and to create effective sales strategies based on that knowledge by using massive amounts of click stream data generated by site visitors. This paper discusses and clarifies the process as to how detailed consumer behavior patterns are extrac...
Conference Paper
In this paper, we discuss how graph mining system is applied to sales transaction data so as to understand consumer behavior. First, existing research of consumer behavior analysis for sequential purchase pattern is reviewed. Then we propose to represent the complicated customer purchase behavior by a directed graph retaining temporal information i...
Conference Paper
The objective of this paper is to present and discuss methods for formulating optimum pricing strategies for maximizing store profit levels using consumer purchase data. In order to maximize outlet profit levels, it is necessary to seek such pricing strategies after achieving an in-depth understanding of the various features of consumer purchase be...
Conference Paper
With the rapid spread of the Internet and the computerization of trading a huge amount of data on the Internet and of transaction database in enterprises has been accumulated. The purpose of this paper is to explain the significance of the technology to process of exabyte-scale data and presents the business application, CODIRO, which will make it...
Chapter
The aim of this paper is to propose a new system for the strategic use of customer data that includes and integrates such differing data sources as company databases, mobile telephone networks and Internet data and is a consumer research support system for the discovery of new marketing opportunities. This system, called CODIRO, will be discussed i...
Conference Paper
We have recently developed an E-BONSAI (Extended BONSAI) for discovering useful knowledge from time-series purchase transaction data, developed by improving and adding new features to a machine learning algorithm for analyzing string pattern such amino acid sequence, BONSAI, proposed by Shimozono et al. in 1994. E-BONSAI we developed can create a g...
Conference Paper
MUSASHI is a set of commands which enables us to effi- ciently execute various types of data manipulations in a flexible manner, mainly aiming at data processing of huge amount of data required for data mining. Data format which MUSASHI can deal with is either an XML table written in XML or plain text file with table structure. In this paper we sha...
Article
We develop a new method for extracting useful knowledge from individual purchase history of customers by combining information fusion techniques with a data mining tool – string pattern analysis. We demonstrate through several case studies how the method helps firms predict how and when a customer is likely to switch from one brand to another, who...
Conference Paper
This paper presents a new application for discovering useful knowledge from purchase history that can be helpful to create effective marketing strategy, using a machine learning algorithm, BONSAI, proposed by Shimozono et al. in 1994 which was originally developed for analyzing string patterns developed for knowledge discovery from amino acid seque...
Article
Analyzingply hase history of customers enables us to discover valuable knowledge that ishelp for develop e#ective salespesq In thisresp ect, we shall introduce a new notion, association strength, defined forpq hase history which quantitatively evaluates brand loyalty and brand switching behavior among severalcomp eting brands in certain commodity c...
Chapter
The data mining activities studied in this chapter concern the early identification of potential high-value customers. Member stores can use this information to establish a close relationship with this select group of customers, thus reducing the chances of losing them. Traditionally, Japanese drugstore chains, unlike their American counterparts, h...
Conference Paper
Analyzing the purchase history of customers enables us to discover valuable knowledge that is helpful for developing effective sales promotion. In this respect, the authors introduce a new notion, association strength among brand loyalties, which is defined for every ordered pair of brands. If the association strength between loyalties of brands A...
Conference Paper
The problem about brand choice or brand switching has been discussed for a long time in a marketing research field [1][2][3][6]. They focus on revealing a probability of brand switching and what factors are related to the brand switching. However, brand choice behavior of individual customer has been neglected in most of existing literature. In thi...

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