Junichiro Niimi

Meijo University · Department of Business Management

Nowadays, along with the popularity of E-Commerce, the marketing strategy of retail stores has been more complicated with O2O or Omni-Channel. Therefore, Customer Relationship Management (CRM) is one of the important issue for the retail stores. It can be difficult to predict customers future behavior with the simple quantitive information such as...

In the marketing field, understanding consumer heterogeneity, which is the internal or psychological difference among consumers that cannot be captured by behavioral logs, has long been a critical challenge. However, a number of consumers today usually post their evaluation on the specific product on the online platform, which can be the valuable s...

In recent years, various novel techniques have emerged in the realm of deep learning for enhanced pattern recognition. Multimodal learning is a widely used approach that enables simultaneous data input across multiple modalities, including video, audio, and text. For customer relationship management in the field of marketing, a comprehensive analys...

In this study, we aimed to understand and reduce the difference between self-report in a survey and the actual behavior. Thus, we investigated whether such a difference was caused by participants who engaged in insufficient effort responding (IER), which has been receiving increasing research attention. We collected and analyzed data of actual and...

Background Public perceptions and personal characteristics are heterogeneous between countries and subgroups, which may have different impacts on health-protective behaviors during the coronavirus disease 2019 (COVID-19) pandemic. To assess whether self-reported perceptions of COVID-19 and personal characteristics are associated with protective beh...

In recent years, machine learning methods, including deep learning, have continued to evolve rapidly. As examples, generative models capable of generating media data and large-scale language models capable of natural communication have emerged, and are having a significant impact in a wide range of fields, not only in the creation of simple applica...

It has become common for consumers to post texts online, such as opinions and product reviews. Various methods to analyze these data have been explored in the field of natural language processing. Recently, large language models (LLMs) are actively utilized. While many commercially available LLMs are provided as cloud services, the demand for local...

User-generated contents (UGCs) on online platforms allow marketing researchers to understand consumer preferences for products and services. With the advance of large language models (LLMs), some studies utilized the models for annotation and sentiment analysis. However, the relationship between the accuracy and the hyper-parameters of LLMs is yet...

User-generated contents (UGCs) on online platforms allow marketing researchers to understand consumer preferences for products and services. With the advance of large language models (LLMs), some studies utilized the models for annotation and sentiment analysis. However, the relationship between the accuracy and the hyper-parameters of LLMs is yet...

In recent years, various novel techniques have emerged in the realm of deep learning for enhanced pattern recognition. Multimodal learning is a widely used approach that enables simultaneous data input across multiple modalities, including video, audio, and text.For customer relationship management in the field of marketing, a comprehensive analysi...

In the marketing field, online service providers have recently implemented personalized recommendations on various mobile applications as a part of customer relationship management. However, there has long been an issue of consumer heterogeneity, where each customer has internal differences that are difficult to discern from behavioral logs. On the...

Today, the acquisition of various behavioral log data has enabled deeper understanding of customer preferences and future behaviors in the marketing field. In particular, multimodal deep learning has achieved highly accurate predictions by combining multiple types of data. Many of these studies utilize with feature fusion to construct multimodal mo...

In recent, the assessment of short-term usage behavior has relied on the Clumpiness index. However, it became evident that relying solely on Clumpiness is insufficient in capturing the nuances of such behavior. In response, this study systematically addresses the limitations of Clumpiness and introduces the Herfindahl-Hirschman Index (HHI) as an ad...

This study examines the impact of consumers' short-term intensive use of smartphone games on behavioral loyalty. In recent, short-term usage called clumpiness has received increasing attentions. However, if we utilize the indice in order to capture those short-term intensive use, several problems pop up. In this presentation, we sort the problems i...

Background: Public perceptions and personal characteristics are heterogeneous between countries and subgroups, which may have different impacts on health-protective behaviors during the coronavirus disease 2019 (COVID-19) pandemic. To assess whether self-reported perceptions of COVID-19 and personal characteristics are associated with protective be...

In recent, the concept of clumpiness has received increasing attention as a novelmethod called RFMC in Customer Relationship Management (CRM). However, it hasbeen not so long since clumpiness is proposed, there still remains difficulties. In thispaper we firstly identify the problems of clumpiness in both statistical and practicalfields, propose th...

In recent, the concept of clumpiness has received increasing attention as a novel method called RFMC in Customer Relationship Management (CRM). However, it has been not so long since clumpiness is proposed, there still remains difficulties. In this paper we firstly identify the problems of clumpiness in both statistical and practical fields, propos...

In recent, the concept of clumpiness has received increasing attention as a novel method called RFMC in Customer Relationship Management (CRM). However, it has been not so long since clumpiness is proposed, there still remains difficulties. In this paper we firstly identify the problems of clumpiness in both statistical and practical fields, propos...

Both in academia and practice various methods of Customer Relationship Management (CRM) have been in use especially RFMC (Zhang et al., 2014) which is recently proposed as a novel method due to its high performance of predicting competitive purchase. However, it still has difficulty identifying consumer heterogeneity compared to variety variables p...

Nowadays various kinds of data about customers behavior on online websites or applications can be collected for the marketing analysis. However, especially for the physical retailing stores, it is still difficult to acquire their behaviors on competing firms. In this research, we develop a novel approach of considering the usage of competitors We p...

Nowadays it is difficult for companies to formulate marketing strategy without considering their customers behavior in competing �rms. However, even in the big data era, combining large scale data in the company and the general lifestyle survey data is still tough. In this research we created the data fusion model with Deep Boltzmann Machine to com...

Nowadays, along with the popularity of E-Commerce, the marketing strategy of retail stores has been more complicated with O2O or Omni-channel. Therefore, Customer Relationship Management (CRM) is one of the important issue for the retail stores. It can be difficult to predict customers future behavior with the simple quantitive information such as...

It is important for the companies to get much information about their customers. For example, the information that how often each customer purchases from the competitors can be useful when we plan the promotion strategy. In this paper, we focus on the web services and predict customers' behaviors such as browses and purchases in two companies and t...

It is important for the companies to get much information about their customers. For example, the information that how often each customer purchases from the competitors can be useful when we plan the promotion strategy. In this paper, we focus on the web services and predict customers' behaviors such as browses and purchases in two companies...