According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

物件導向軟體之架構(Object-Oriented Software Construction)探討

How have Japanese companies become world leaders in the automotive and electronics industries, among others? What is the secret of their success? Two leading Japanese business experts, Ikujiro Nonaka and Hirotaka Takeuchi, are the first to tie the success of Japanese companies to their ability to create new knowledge and use it to produce successful products and technologies. In The Knowledge-Creating Company, Nonaka and Takeuchi provide an inside look at how Japanese companies go about creating this new knowledge organizationally. The authors point out that there are two types of knowledge: explicit knowledge, contained in manuals and procedures, and tacit knowledge, learned only by experience, and communicated only indirectly, through metaphor and analogy. U.S. managers focus on explicit knowledge. The Japanese, on the other hand, focus on tacit knowledge. And this, the authors argue, is the key to their success--the Japanese have learned how to transform tacit into explicit knowledge. To explain how this is done--and illuminate Japanese business practices as they do so--the authors range from Greek philosophy to Zen Buddhism, from classical economists to modern management gurus, illustrating the theory of organizational knowledge creation with case studies drawn from such firms as Honda, Canon, Matsushita, NEC, Nissan, 3M, GE, and even the U.S. Marines. For instance, using Matsushita's development of the Home Bakery (the world's first fully automated bread-baking machine for home use), they show how tacit knowledge can be converted to explicit knowledge: when the designers couldn't perfect the dough kneading mechanism, a software programmer apprenticed herself withthe master baker at Osaka International Hotel, gained a tacit understanding of kneading, and then conveyed this information to the engineers. In addition, the authors show that, to create knowledge, the best management style is neither top-down nor bottom-up, but rather what they call "middle-up-down," in which the middle managers form a bridge between the ideals of top management and the chaotic realities of the frontline. As we make the turn into the 21st century, a new society is emerging. Peter Drucker calls it the "knowledge society," one that is drastically different from the "industrial society," and one in which acquiring and applying knowledge will become key competitive factors. Nonaka and Takeuchi go a step further, arguing that creating knowledge will become the key to sustaining a competitive advantage in the future. Because the competitive environment and customer preferences changes constantly, knowledge perishes quickly. With The Knowledge-Creating Company, managers have at their fingertips years of insight from Japanese firms that reveal how to create knowledge continuously, and how to exploit it to make successful new products, services, and systems.

The knowledge-creating company

25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

Multiple Imputation for Nonresponse in Surveys

Statistical Analysis with Missing Data

Purpose – Data mining (DM) has been considered to be a tool of business intelligence (BI) for knowledge discovery. Recent discussions in this field state that DM does not contribute to business in a large‐scale. The purpose of this paper is to discuss the importance of business insiders in the process of knowledge development to make DM more relevant to business.Design/methodology/approach – This paper proposes a blog‐based model of knowledge sharing system to support the DM process for effective BI.Findings – Through an illustrative case study, the paper has demonstrated the usefulness of the model of knowledge sharing system for DM in the dynamic transformation of explicit and tacit knowledge for BI. DM can be an effective BI tool only when business insiders are involved and organizational knowledge sharing is implemented.Practical implications – The structure of blog‐based knowledge sharing systems for DM process can be practically applied to enterprises for BI.Originality/value – The paper suggests th...

A knowledge management approach to data mining process for business intelligence

Neural network techniques are widely used in solving pattern recognition or classification problems. However, when statistical data are used in supervised training of a neural network employing the back-propagation least mean square algorithm, the behavior of the classification boundary during training is often unpredictable. This research suggests the application of monotonicity constraints to the back propagation learning algorithm. When the training sample set is preprocessed by a linear classification function, neural network performance and efficiency can be improved in classification applications where the feature vector is related monotonically to the pattern vector. Since most classification problems in business possess monotonic properties, this technique is useful in those problems where any assumptions about the properties of the data are inappropriate.

Application of the Back Propagation Neural Network Algorithm with Monotonicity Constraints for Two‐Group Classification Problems*

Adaptive non-parametric efficiency frontier analysis: a neural-network-based model

Self-organising maps (SOM) have become a commonly-used cluster analysis technique in data mining. However, SOM are not able to process incomplete data. To build more capability of data mining for SOM, this study proposes an SOM-based fuzzy map model for data mining with incomplete data sets. Using this model, incomplete data are translated into fuzzy data, and are used to generate fuzzy observations. These fuzzy observations, along with observations without missing values, are then used to train the SOM to generate fuzzy maps. Compared with the standard SOM approach, fuzzy maps generated by the proposed method can provide more information for knowledge discovery.

https://link.springer.com/content/pdf/10.1007%2Fs00521-003-0372-1.pdf

Application of self-organising maps for data mining with incomplete data sets

Shared services have been widely spread in the government and private sectors. Unlike outsourcing, shared service is the standardization and consolidation of common functions across the multiple organizations to reduce information process duplication and increase information and knowledge sharing. Shared services should be viewed less as a phenomenon of cost saving and more as a challenge of organization redesign. Five general leading theories of organizational design are examined in the perspective of shared services. A quasi-general organizational design approach is proposed specifically for shared services projects. The proposed approach emphasizes the organizational support for the shared services strategy identification, collabora- tive partnership network design, optimal shared services process design, and policy and regulation system design.

Shouhong Wang

Papers

A knowledge management approach to data mining process for business intelligence

Application of the Back Propagation Neural Network Algorithm with Monotonicity Constraints for Two‐Group Classification Problems*

Adaptive non-parametric efficiency frontier analysis: a neural-network-based model

Application of self-organising maps for data mining with incomplete data sets

Shared services beyond sourcing the back offices: Organizational design