In previous studies on the textile industry and production areas, the success factors of the Fukuyama production area have often been discussed in terms of the success of KAIHARA, a company specializing in denim production with an integrated manufacturing process encompassing spinning, dyeing, weaving, and finishing. As a result, Fukuyama has often been viewed less as an area known for textile production and more through the lens of KAIHARA’s corporate success. However, in reality, the region is home to several long-established small- and medium-sized enterprises, that are neither subcontractors nor spin-offs of KAIHARA. These enterprises have each taken on specialized roles in spinning, weaving, dyeing, and processing. They have collaborated horizontally in a way that rivals the capabilities of KAIHARA, while also making efforts to facilitate the entry of younger generations into the industry. These efforts have contributed to the revitalization of the entire production area, countering the issue of an aging workforce that has affected other regions.

Japanese companies are actively hiring highly skilled international talents, making their cross-cultural adaptation a critical issue. This study found that highly skilled international talents adapted to their workplace through proactive behaviors such as “learning behaviors” and “relationship-building behaviors.” Furthermore, many talents could be classified under the “integration” category of acculturation. While this finding may indicate that highly skilled international talents are adapting smoothly to Japanese workplaces, it also implies assimilation into Japanese culture. This assimilation may raise concerns for employers as it does not align with their original goal of leveraging diverse talents from overseas.

Expanding on his study of the social construction of technology, Bijker used a technological frame to explain the factors involved in the success development of Bakelite. It is generally accepted that the successful synthesis of Bakelite was particularly helped by the fact that the inventor, Baekeland, was more deeply included in the technological frame of electrochemical engineers rather than that of celluloid chemists. However, a careful reading of Bijker's case study reveals that (i) the technological frame contributing to the synthesis of Bakelite is separate from the technological frame of electrochemical engineers and (ii) it was formed by collecting components of the technological frame (called technological frame parts in this paper) of the community to which Baekeland belonged and in which he was included as well as the technological frames of celluloid chemists and electrochemical engineers.

Research on firm growth shows that results vary depending on the measure of growth used. Many empirical studies have tested the comparability of firm growth measures. This study examined concurrent validity among the growth measures of professional service firms (PSFs). Specifically, we examined the absolute and relative growth rates of 87 patent firms from 1998 to 2008 using five growth variables—firm sales, total number of patent applications, number of domestic patent applications, number of patent attorneys, and number of employees. We found that concurrent validity was high only between number of total patent applications and number of domestic patent applications. The reason may be that for patent firms, other factors are in play, such as level of business diversification and outsourcing, range of clients, and number of support personnel who are not formally qualified. This shows that PSFs and private sector firms exhibit different growth paths. However, this also suggests that it is not sufficient to measure firm growth using growth measures that do not consider differences among private sector firms in different sectors or firms within the same sector but with different structures.

In influencer marketing, influencers are usually selected based on the number of followers. But is this the right selection method? In this study, we conducted a preliminary survey of SDG-related words on Instagram. Among accounts with posts that included hashtags “#food loss” and “#renewable energy,” we selected one account with a high view count for each hashtag. Then, for these two accounts, we conducted a network analysis using mutual following relationships as ties and accounts as nodes. We found that the former account had a broadcasting-type network, whereas the latter account had a community-type network. In a community type network, users are very like-minded, and influencers with community-type networks are considered more effective at the purchase decision stage. Owing to a higher rate and number of comments for the community-type network, these two values could be used as substitute indicators for network structure.