Business process semi-automation based on business model management

It is important to respond to customers' requirements more rapidly than ever before due to the recent trend in e-business and its technologies. In order to achieve an agile response, we have to manage business models, to reflect the changes in the models and to develop or modify IT systems for further chances. This paper proposes a management framework of layered enterprise models. The proposed framework consists of a business model repository and a software repository, and defines three different grain sizes of modeling layers, namely business modeling, business process modeling and business application modeling, in order to support business modeling and application development. This framework helps us to develop business application in incremental deployment of analysis, design, and implementation to execute business processes. We have implemented a prototype environment using Java. Each repository's contents are described using XML so that the repositories are interoperable. Copyright © 2003 John Wiley & Sons, Ltd.     

Are regional asymmetries detrimental to tax coordination in a repeated game setting?

This paper reexamines the main findings of Cardarelli et al. [Cardarelli, R., Taugourdeau, E., Vidal, J.-P., 2002. A repeated interactions model of tax competition, Journal of Public Economic Theory 4, 19-38], and Catenaro and Vidal [Catenaro, M., Vidal, J.-P., 2006. Implicit tax co-ordination under repeated policy interactions, Recherches Economiques de Louvain 72, 1-17], who show that regional asymmetries undermine the implicit collusion of tax coordination in a repeated game model of capital tax competition. In particular, this paper investigates how increased regional differences in per capita capital endowments and/or production technologies affect the willingness of each region to cooperate in achieving tax coordination. It is shown that there may exist cases where as regional asymmetries in net capital exporting positions increase, regions are more likely to cooperate on capital taxes and thereby achieve tax coordination.     

DEBT FORGIVENESS AND STOCK PRICE REACTION OF LENDING BANKS: THEORY AND EVIDENCE FROM JAPAN

We provide a simple model for analyzing how debt forgiveness affects the stock price of a lending bank. Our model shows that although debt forgiveness increases shareholder wealth of a bank in healthy financial condition, it decreases shareholder wealth of a bank in unhealthy financial condition. We empirically investigate the announcement effect of debt forgiveness on bank stock prices in Japanese markets. On average, lending banks experience a significant negative announcement effect with respect to debt forgiveness. Consistent with the prediction of the model, we find a negative relation between the announcement effect and the net bad loan ratio as a proxy of the unhealthiness of the financial condition of the bank.     

Career progression and comparative advantage

This paper constructs and estimates a structural dynamic model of occupational choice in which all occupations are characterized in a skill requirement space using data from the Dictionary of Occupational Titles and the NLSY79. This skill requirement space approach has its merit in computational simplicity as well as ease of interpretation: it allows the model to include hundreds of occupations at the three-digit census classification level without a large number of parameters. Parameter estimates indicate that wages grow with the skill requirements of an occupation and that educated and experienced individuals are better rewarded in a cognitive and interpersonal skill demanding occupation. They also suggest that ignoring self-selection into occupations and individual heterogeneity may result in counter-intuitive and biased estimates of the returns to skill requirements.     

The Boosting Effect of E-WOM on Macro-level Consumption: A Cross-Industry Empirical Analysis in Japan

In this study, we carry out an empirical analysis on how electronic word-of-mouth (hereinafter “e-WOM”) marketing on e-WOM websites and electronic-commerce websites on the Internet boosts consumption on a macro-level. In our analysis, we conduct a model analysis of consumer behavior using data composed of more than 30,000 questionnaire surveys and quantitatively find the elasticity coefficient of the boost to consumption by performing a two-step GMM (generalized method of moments), which uses instrumental variables. The results of the analysis show e-WOM significantly increased expenditures in six fields: computers, electrical appliances, etc.; music; hobbies; clothing, accessories, etc.; beauty products, etc.; and goods for everyday life, etc. Furthermore, there was no field that had a significantly negative value. These results showed that, in the majority of the target fields, e-WOM had not only the effect of winning customers from the competition, but also the effect of boosting consumption on a macro-level. In addition, even from people’s subjective evaluations, there were many in all the generational groups who said that e-WOM boosted expenditures.     

Integrating Smart Glasses with Question-Answering Module in Assistant Work Environment

Recently, smart glasses have been applied in the field of maintenance, with which a worker goes well during work by contacting a support operator from a remote location. The worker, however, cannot go well if the support operator is not there. To solve the issues, this paper discusses how a work system should be developed by integrating smart glasses with a question-answering module. We design the work knowledge acquired from skilled people and manuals as a workflow for when type of question, rule base for how, goal tree for why, domain ontologies, and its RDF data for what. Workers can receive answers from the question-answering module incorporated with multiple knowledge bases for four types of question. The authors conducted a demonstration experiment and found that workers could perform the work more autonomously by importing the system.     

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.     

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.