The proposal and validity of the Customer Science Dual System--The key to corporate management innovation

A future successful global marketer must develop an excellent quality marketing system that impresses users and continuously provides excellent, quality products in a timely manner through corporate management. In this study, the authors proposed the Customer Science Dual System, CS-TMNS ＆ CS-SDSM. For the purpose of innovating strategic product development systems so called Customer Value Creative System, the Total Marketing Network System, CS-TMNS is established. In addition, for intelligent utilization of the established CS-TMNS, statistical science is incorporated so as to create the Strategic Designing Support Methods, CS-SDSM, as a new approach to the creation of wants that are vital to product planning and designing. Concretely, the author will also introduce the effectiveness of this system that reflects latent customer needs through scientific marketing application examples via Automobile Design Profile for the Younger Generation.     

Dual Technology Management Model of design and production utilizing CAE ＆ experiment

At present, one of the specific measures taken is an urgent improvement of intelligent productivity for the purpose of offering highly reliable products to create customer value in a short period of time. Against this background, the author focuses on the New Japan Production Model for establishing a development designing and production engineering system in the automotive industry. This paper presents the Dual Technology Management Model of design and production for establishing a development designing and production quality assurance system that is indispensable for CAE （Computer-Aided Engineering） and experiment in the automotive industry and its effectiveness is verified.     

Customer behavior analysis using motion pictures： Research on attractive flier design method

In this report, the authors would like to propose CMP-FDM （Customer Motion Pictures-Flier Design Method） to increase the willingness of consumers to visit the automobile dealership. CMP-FDM is a method of creating attractive fliers while using customer behavior analysis with videos. According to the analysis of how customers see fliers, the authors classify their behavior into three types and create attractive designs so that each guarantees each customer＇s satisfaction. Finally, the authors integrate the three types of fliers into one attractive to all customers by organizing the design features （design elements）, and then validate the method.     

Impact of immigration on the Japanese economy: A multi-country simulation model

To quantify the impacts of immigration and fiscal reconstruction on the Japanese economy, we present a dynamic computable general equilibrium OLG model with an overlapping generations structure. We use a total of 16 countries and regions, both including those that are industrialized, such as Japan, the US, and the EU, and developing countries, such as China, Brazil, the Philippines, and Peru.Our simulation results show that a permanent immigration flows of 150,000 will improve the Japanese economy and the welfare of current and future generations. On the other hand, a standalone increase in the consumption tax will not improve long-run welfare. The results indicate that substantially increased inflows of working-age immigrants would alleviate the need for future fiscal reform and also help to dramatically reduce the public pension burden on the working generations.     

Autoregressive stochastic volatility models with heavy-tailed distributions: A comparison with multifactor volatility models

This paper examines two asymmetric stochastic volatility models used to describe the heavy tails and volatility dependencies found in most financial returns. The first is the autoregressive stochastic volatility model with Student's t-distribution (ARSV-t), and the second is the multifactor stochastic volatility (MFSV) model. In order to estimate these models, the analysis employs the Monte Carlo likelihood (MCL) method proposed by Sandmann and Koopman [Sandmann, G., Koopman, S.J., 1998. Estimation of stochastic volatility models via Monte Carlo maximum likelihood. Journal of Econometrics 87, 271–301.]. To guarantee the positive definiteness of the sampling distribution of the MCL, the nearest covariance matrix in the Frobenius norm is used. The empirical results using returns on the S&P 500 Composite and Tokyo stock price indexes and the Japan–US exchange rate indicate that the ARSV-t model provides a better fit than the MFSV model on the basis of Akaike information criterion (AIC) and the Bayes information criterion (BIC).     

Policy reform and optimal inflation rate for Japan in computable OLG economy

We build a computable OLG model with monetary growth to calculate the optimal level of inflation rate for Japan, and to study policy reforms make any quantitative impacts on it. Four main results were obtained: (i) the optimal inflation rate for Japan is calculated around 1.0%; (ii) the calculated underlying inflation rate is about 9% under the present Japanese economic and fiscal situation; (iii) to prevent high inflation, fiscal reconstruction needs to be implemented; and (iv) if fundamental fiscal reform is conducted, the optimal inflation rate might be achieved. These results are very robust to calibration.     

Proposal and validity of Intelligent Customer Information Marketing Model： Strategic development of advanced TMS

In this paper, one vital point of the strategic marketing structure is its definition, marketing activities should be defined from ＂closed marketing activities＂ that are limited to the business and sales division to ＂open marketing activities＂ that can be performed through steady linkage with all other divisions in a company-wide framework. The aim is for an ＂Evolution of Market Creating＂ through ＂High Quality Assurance and Innovating Advertisement, Product planning and Dealers＇ Sales Activities＂ by utilizing the scientific approach of Advanced TMS. So, the authors present an ＂Intelligent Customer Information Marketing Model, ICIM＂ which takes the form of strategic marketing. As an example of the application of this research, the authors apply this model to advertising, product planning and dealers＇ sales activities and obtained the results shown.     

Team Roles and Hierarchic System in Group Discussion

Conventional systems for classifying team roles refer only to the function criterion and two categories, task and social; in addition, roles and behaviors are unspecialized, a one-to-one correspondence being assumed between them. These theoretical problems have resulted in overly fragmented roles as well as oversimplified categories. Therefore, this article aims to reveal essential roles and a unified system to classify them. In order to elucidate the team roles essential for discussion, a questionnaire survey was administered for Study 1, with the result that just ten discussant-roles were identified. For Study 2, in order to verify a classification system for the discussant-roles, participant groups were asked to discuss itineraries for an overnight group trip during the winter holiday. The results showed that a three-criterion model based on the deep roles is superior to the traditional model. In this hierarchical system, characteristic behaviors are expressed according to ten discussant-roles, which are divided into six categories, using a combination of three criteria. This system not only solves the theoretical issues but also contributes to improving members’ discussion behaviors.     

Web usage mining approaches to page recommendation and restructuring

As an increasing number of Web sites such as e-businesses consist of an increasing number of pages, users find it more difficult to rapidly reach their own target pages. Ill-structured design of Web sites also prevents the users from rapidly accessing the target pages. In this paper, we describe two complementary approaches to Web usage mining as a key solution to these issues. First, we describe an adaptable recommendation system called the L-R system, which constructs user models by classifying the Web access logs and by extracting access patterns based on the transition probability of page accesses and recommends the relevant pages to the users based on both the user models and the Web structures. We have evaluated the prototype system and have obtained the positive effects. Second, we describe another approach to constructing user models, which clusters Web access logs based on access patterns. The user models also help to discover unexpected access paths corresponding to ill-formed Web site design. Copyright © 2003 John Wiley & Sons, Ltd.