Present literatures highlight that the presence of Japanese-speaking human resources in Dalian, China has formed a high-tech agglomeration in Dalian, which attracts many Japanese companies. However, that is a simplistic answer. This paper identifies that the software development outsourcing industry in Dalian is formed by three phases, First, the major role played by Japanese companies in China on the creation of skilled labor in the initial phase of the agglomeration. Second, Chinese companies that have become the core companies of the agglomeration through doing business with Japanese companies developed Japanese-speaking human resources as their own as a means of attracting Japanese customers. Third, new comers can utilize the skilled labor market which is formed by those human resource spun off of foreign-owned firms and core local firms.
It is common knowledge that expansion in the scale of production leads to economies of scale. A correlation between economies and scale does exist. However, the reality on the shop floor, in Japanese, “gemba,” in actual manufacturing is that productivity increases and that there is expansion of production volumes through “flow creation” for the entire production process. Previous studies demonstrated how flow creation has led to increased productivity and expansion of production volumes even in relation to the production system for the Model T Ford, which is considered as a typical example of a large range cost reduction (i.e., an increase in productivity that was achieved through mass production). For example, expansion of production volumes occurs simultaneously as productivity increases due to a succession of standardizations such as the standardization of components, production processes, and operations. That is, there is highly likely a spurious correlation between productivity and production volumes. Increased production does not guarantee increased productivity. In fact, that was the case with the Model T Ford.
When explaining organizational decision making, there is often an implicit assumption that an organization makes decisions based on rational principles. However, there are situations in which rationality cannot explain all phenomena. Moreover, even a single organizational decision can be subject to heterogeneous interpretations depending on the model used in an analysis. This paper examines the significance of the models of organizational decision making as an analytical framework by referencing classic studies by Allison (1971) and Lynn (1982). Allison (1971) and Lynn (1982) use multiple models to explain organizational decision making in an effective manner. However, the method in which they use these models differs. Allison (1971) analyzes the Cuban Missile Crisis using three models, and provides three different interpretations concerning decisions made by the U.S. and Soviet Union. In other words, Allison uses more than one model to analyze a single phenomenon to explain the event from different perspectives. On the other hand, Lynn (1892), who explains the decision-making process of Japanese and U.S. steelmakers by analyzing their adoption of new technology, chooses a single model for each company. In providing an analysis, Lynn compares several models and selects the one that is likely to have the most explanatory power. To provide an analysis of organizational decision making in an effective manner, it is necessary to remember the importance of models as an analytical framework and then decide whether to adopt Allison's method (the use of multiple models that provide explanations from several perspectives) or Lynn's method (an explanation using the most optimal model). It is important to decide which method to use based on the purpose of the analysis.
The perspective index (Takahashi, 2014) was tested in a company that has been successful in the process of organizational reform, Company X. An exhaustive survey (Survey X) for all employees was conducted once a fiscal year from 2004 to 2013. According to Survey X, over 13,000 employees showed near-perfect linearity between perspective index and job satisfaction ratio/turnover candidate ratio. Each occupational and rank category also showed a near-straight line, although the values greatly varied per year before and after organizational reform. However, the incline and intercept points of the lines somewhat differed contingent on the occupational and rank category. This might explain the difference between data from Survey X and that of the JPC Survey conducted in Takahashi (2014).
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