Unifying Rule Induction and Rule Refinement—Towards Discovering Anomaly from Granville's Law in a Stock Market Technical Analysis

This paper discusses a framework for refining an initial object-level rule base with a rule induction to learn meta-level rules which find a data set applicable to an object-level rule. A rule induction process such as ID3 tries to learn meta-level rules and classifies given training data sets into positive data sets and negative ones. The rule refinement process tries to refine an initial object-level rule base on classified data sets by using four refinement strategies. Unifying these two processes, one can obtain a refined object-level rule base with high performance where a meta-level rule selects a data set applicable to it. In order to evaluate the framework, an experiment on real Japanese stock price data shows that a refined object-level rule base, which comes from the initial object-level rule base for representing Granville's Law, has a performance beyond that of the average stock price. The performance is difficult for human technical analysts in a stock market to achieve. The result implies that the framework could create an anomaly from Granville's Law in a stock market technical analysis.     

Intangible Asset Valuation Model Using Panel Data

In this paper, we design a valuation model for intangible assets using panel data, and empirically investigate the model validity. The approach using panel data is an evaluation method that uses unobserved firm-specific effects based on panel analysis. Our model first estimates production function using panel analysis, and then develops cost function using a duality approach. Next, we discount added value and costs resulting from intangible assets using fixed effects. Empirical analysis using the model compares the estimated parameter values in the nonlinear profit function consisting of production function and cost function with those in the production function alone, which becomes linear after logarithmic conversion, and finds that the two are generally similar. Additionally, the market value of equity is more closely associated with both the book value of equity and the value of intangible assets than with the book value of equity alone. These results support the validity of the model for evaluating intangible assets. This model is easy to apply in practice and is based on a simple idea. Further discussion of this model is warranted given the increasing importance attached to the value of intangible assets.     

Implementing partial tax harmonization in an asymmetric tax competition game with repeated interaction

This paper investigates the conditions under which partial harmonization for capital taxation is sustained in a repeated interactions model of tax competition when there are three countries with heterogenous capital endowments. We show that regardless of the structure of the coalition (i.e., full or partial tax coordination), whether partial tax harmonization is sustainable or not crucially depends on the extent to which the capital endowment of the medium‐sized country is similar to that of the large or small country. The most noteworthy finding is that the closer the capital endowment of the median country is to the average one, the less likely the tax harmonization including the median country is to prevail and the more likely the partial tax harmonization excluding the median country is to prevail. We also show that partial tax harmonization makes the member countries of the tax union better off and non‐member countries worse off, which stands in sharpe contrast with previous studies, such as Konrad and Schjelderup (1999) and Bucovetsky (2009).     

Evaluation of a Multi-robot Cafe Based on Service Quality Dimensions

While AI applications are popular in many domains, they should work harmoniously with domain exerts and end users. Furthermore, to develop such harmonious AI applications, we need agile AI platforms for not only developers, but also domain experts. Currently, we have developed PRactical INTElligent aPplicationS (PRINTEPS), which is a user-centric platform to develop integrated intelligent applications. This paper reports on a multi-robot cafe as a practical application of PRINTEPS and evaluates its service quality at a university festival. It is not clear if robotic services are perceived as attractive and/or valuable, and how the concept of robotic services could lead to customer satisfaction. Therefore, the evaluation of the quality of such services is necessary to identify the key factors that could contribute to improving customer satisfaction. The purpose of this research is to identify key factors in improving customer satisfaction in robotic services by evaluating the service quality of the multi-robot cafe. We designed questionnaire items based on SERVQUAL which is one of the service quality evaluation measurement methods and conducted a questionnaire survey at a multi-robot cafe held at a university festival. From the collected data, we modeled and evaluated the relationship between service quality and customer satisfaction to identify key factors in robotic services using a Bayesian network. In addition, the experiment confirms the usefulness of PRINTEPS.     

Who explores further? Evidence on R&D outsourcing from the survey of research and development

Building off the resource‐based view and the knowledge‐based view, our study aims to examine determinants of firms’ R&D outsourcing, using annually‐conducted firm‐level survey data of Japanese R&D companies from 1984–2012. This survey allows us to measure strategic R&D outsourcing, isolated from those more for cost‐reducing, such as prototyping, testing and inspecting. The results corroborate the argument of complementarity in scale between internal R&D and R&D outsourcing. We also find that firms employing more doctorate holders and diversifying in knowledge spaces tend to make more use of R&D outsourcing. This study sheds light on firms’ absorptive capacity, associated both with higher‐order R&D human capital and diversified knowledge spaces, as determinants of R&D outsourcing.     

Inflexibility of Share Repurchases*

This paper investigates the flexibility inherent in open market share repurchases. Open market share repurchases are recognized as being flexible, since managers believe that they are not an ongoing commitment. However, I find that such returns significantly decrease upon announcing the completion of a repurchase program if firms do not concurrently announce new program authorizations. I also find that announcement returns significantly decline with completion rates and that a high completion rate acts as a negative signal, revealing that firms have finished the repurchasing activities and do not intend to continue share repurchasing in the foreseeable future. These results indicate that share repurchases are less flexible than they were previously thought to be.     

A Practical Teacher–Robot Collaboration Lesson Application Based on PRINTEPS

To support elementary school teachers in teaching by encouraging active learning while maintaining the interest of pupils, this study focuses on supporting teaching, learning, and monitoring the progress of students through a Teacher–Robot collaboration lesson application using not only laptops and tablets, but also robots and sensors. Since developing a lesson application is time consuming for teachers, we have developed an integrated intelligent application development platform named PRactical INTElligent aPplicationS (PRINTEPS) to aid Teacher–Robot collaboration. However, several functions and interfaces for education are missing. Therefore, in this study, we extend several functions for education to PRINTEPS. In addition, since it is necessary in learning and monitoring the progress of students to present learning content suitable to each pupil’s level of understanding, we also have provided support through the use of a tablet quiz system based on ontologies and rule bases. In the case study, we developed a Teacher–Robot collaboration lesson application and conducted lessons for sixth-grade pupils at an elementary school. From the case study, we have confirmed the effectiveness of our platform and the application.     

PRINTEPS: An Integrated Intelligent Application Development Platform based on Stream Reasoning and ROS

Although AI and service robot applications have become very popular in many domains recently, many of them are specific applications and it is still difficult to develop integrated intelligent applications such as a robot teahouse and teaching assistant robots. To develop such integrated intelligent applications, we need integrated intelligent application platforms that have AI integration and agile process facilities. From the above background, we are currently developing PRactical INTElligent aPplicationS (PRINTEPS), which is a platform for developing integrated intelligent applications by combining only five types of modules, namely knowledge-based reasoning, spoken dialogue, image sensing, motion management, and machine learning. This paper proposes a workflow editor in PRINETPS based on a service-oriented architecture and a Robot Operating System that enables real-time parallel processing for multiple robots and sensors by integrating the five types of modules. The editor also supports not only developers but also domain experts in updating workflows frequently. This paper also proposes a novel method to integrate signals acquired through image sensing with knowledge (ontologies and business rules) using C-SPARQL and Semantic Web Rule Language. To evaluate PRINTEPS, we developed a robot teahouse application including customer reception and guidance to table services using a humanoid robot with PRINTEPS. Through this case study, we demonstrated that the behaviors of the robot can be modified by changing the workflow, the ontology, and the rules.     

Important attributes of lodgings to gain repeat business: A comparison between individual travels and group travels

The purpose of this study is to investigate the attributes of the satisfaction that are related to the lodging-guests’ tendency to revisit the lodgings and to compare these attributes among the different travel styles, such as individual travel, travel with friends or as a couple, and travel with family. We examine 6351 guest evaluations from a highly popular travel reservations website. Multinomial logistic regression analyses are performed and they show that the important attributes for lodgings to gain repeat business vary among their guest's travel styles.