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The aim of this paper is to develop a methodology of computer‐assisted roadmapping to supplement an expert‐based approach, which is time‐consuming and subjective.

A computer‐based approach using citation network analysis is used to depict technology trends, and build the first draft of science and technology roadmaps. A case study in energy research is performed, and emerging research domains are tracked in it by citation network analysis.

The analysis confirms that the fuel cell and solar cell are rapidly growing domains in energy research. The detailed research structures were investigated further by clustering. Each citation cluster has characteristic research topics, and there is a variety of growth trends among the clusters.

Constructing a corpus to analyze is not an easy task and one that affects the results, and therefore further research to evaluate the adequacy and validity of the corpus before citation network analysis is necessary. Including patents and analyzing relationships between academic papers and patents for roadmapping is a challenging future research topic.

While science and technology roadmaps are an attractive tool in R&D management and have been widely used, they are typically constructed by gathering and stimulating expert opinion and therefore highly time‐consuming. As demonstrated in this paper, a computer‐based approach using citation network analysis is a powerful tool to support roadmapping. By using the approach, planners and R&D managers can make decisions on effective investment in promising and emerging technologies, especially under circumstances of limited resources with the broader coverage of scientific and technological research.

By using citation network analysis, we can track emerging research domains among a range of publications efficiently and effectively.

Recently, the requirement of the printed wiring boards (PWBs) of environmental harmony type has risen rapidly. We have developed the core technologies of halogen‐free. They consist of resin system technology and high filler content technology. The point of the resin technology is the development of a new resin system (RO resin) which takes nitrogen into the molecule frame in a large quantity. The point of the high filler content technology is the development of a new filler interphase control system (FICS) which enables the high dispersion of fillers. A variety of halogen‐free substrates which can be applied to the diversified needs have been developed by combining these technologies. They are MCL‐RO‐67G, thin laminate for the multi‐layer PWBs, MCF‐4000G, build‐up material for high density interconnect (HDI) , and MCL‐E‐679F(G), high Tg laminate for the advanced plastic IC packages (PKGs) and PWBs. These materials have excellent heat‐resistance, and are suitable for lead‐free solder as well. The robustness towards temperature, humidity and frequency of those materials is better than that of current materials. The synthetic board design of the environmental harmony type is facilitated by combined use of these materials. We are also developing several multi‐layer and build‐up materials, HDI for high frequency, high speed and high reliability application to meet the requirement of PWBs and advanced PKGs for the near future.

This paper aims to present a methodology by which future knowledge flow can be predicted by predicting co-citations of patents within a technology domain using a link prediction algorithm applied to a co-citation network.

Several methods and approaches are used: a dynamic analysis of a patent citation network to identify technology life cycle phases, patent co-citation network mapping from the patent citation network and the application of link prediction algorithms to the patent co-citation network.

The results of the presented study indicate that future knowledge flow within a technology domain can be predicted by predicting patent co-citations using the preferential attachment link prediction algorithm. Furthermore, they indicate that the patent – co-citations occurring between the end of the growth life cycle phase and the start of the maturation life cycle phase contribute the most to the precision of the knowledge flow prediction. Finally, it is demonstrated that most of the predicted knowledge flow occurs in a time period closely following the application of the link – prediction algorithm.

By having insight into future potential co-citations of patents, a firm can leverage its existing patent portfolio or asses the acquisition value of patents or the companies owning them.

It is demonstrated that the flow of knowledge in patent co-citation networks follows a rich get richer intuition. Moreover, it is show that the knowledge contained in younger patents has a greater chance of being cited again. Finally, it is demonstrated that these co-citations can be predicted in the short term when the preferential attachment algorithm is applied to a patent co-citation network.

In Japan, health-care systems have long been supported by physicians' long working hours. To solve this problem, there is an urgent need to improve the working environment for physicians while practicing patient-centered medicine and controlling health-care costs. This paper aims to examine the effect of task shifting to nurses and discuss its usefulness from the perspective of health-care value co-creation.

This paper analyzes task shifting to nurses in acute care hospitals in Japan as a solution for the shortage of anesthesiologists. The authors discuss how the value was created from the perspective of the health-care ecosystem, with conceptual consideration of the value co-creation mechanism through patient-centered practices.

The study showed that task shifting initiatives in Japan can improve the motivation of nurses through human resource development while maintaining high quality. The study also suggested that task shifting from physicians to nurses may contribute to improving net income and maintaining the health-care system.

The findings are highly reproducible and can be immediately applied to initiatives at other medical institutions in Japan. Furthermore, it is suggested that these findings might provide some perspective on the realignment of fragmented healthcare in the USA.

It was confirmed in practical terms that micro-level initiatives have an impact on the macro level as well. In addition, the academic presentation of the concept has contributed to the deepening of value research.

This paper aims to explore the impact of supply chain centralities on sales performance moderated by reputation and stock listing.

Empirical data on supply chain relationships were drawn from the context of electronics and electrical appliance industries in Tokyo, sourced from Teikoku Data Bank in year 2017–2018. On average, the authors analyzed an industrial network of 4,181 focal firms with 3.6 and 3.8 supplier and customer ties, respectively, using social networks and moderated regression analyses.

The authors find that in-(out-)degree, closeness and betweenness centralities are positively related to the focal firm’s annual sales performance. Hubs and authorities as ways of measuring reputation are found to not directly affect performance; hubs negatively moderate the relationship between betweenness and performance. Stock-listing was also found to negatively moderate the relationship between in-degree centrality and performance.

This study adds to existing literature by conducting a supply network analysis in a new industrial context, introducing a new method for assessing firm reputation in supply networks and showing how the structural characteristics of supply networks influence business performance.