The corona pandemic is accelerating the digitization of society. Under such circumstance, digital data will be a core management resource that leads to competitive advantage. However, how to manage data and the governance rules for data with trust have not yet been clarified. This special issue is a collection of research papers on these digital transformations and digital data management in various academic fields. I hope that this special edition leads to various discussions will take place not only in academic societies but also in industry and government.

This paper investigates the impact of big data on the business performances of Japanese companies by using the dataset of the questionnaire surveys conducted by RIETI in 2017 and 2020. There are three key findings.

First, the companies that benefit from big data have not been significantly increasing. But the majority of the companies expect to expand their data use in the future. The fact indicates that the base of data utilization in Japan is growing with expectation.

Second, measuring companies' data capability by data analytics competency (DAC) scores, we found the difference between manufacturing and service sectors. The DAC's effect in the service sector is statistically positive, whereas that in the manufacturing sector is not. This suggests that the benefit of data utilization is much evident in the service sector than that in the manufacturing sector.

Third, by plotting the DAC scores of each sector on the data capability map, we found out the similarity and superiority among sectors. From the map, financial and information sectors have similar data competencies and relatively superior to other sectors in the light of data utilization.

This study gives a good starting point for future research on sector comparison of the impact of big data and firms' capacity of data utilization.

Technologies companies have entered into financial industries with "Gig Data × Artificial Intelligence (AI)" as their weapons, and they have disrupted the industries. Meanwhile, traditional financial institutions have taken on innovations in order to compete against the technologies companies. In this article, I analyze digital transformation strategies at Amazon, Alibaba, Softbank and LINE as examples of technologies companies, as well as those at DBS, Goldman Sachs, and ING as examples of existing financial institutions.

This paper uses data from about 1,000 people obtained under the declared state of emergency to compare 1) a group that had telecommuting experience before the Corona disaster and was telecommuting under the declared state of emergency, 2) a group that experienced telecommuting for the first time, and 3) a group that was working in an office. First, the results show that an abnormal level of telecommuting was taking place under the declared state of emergency, which has not been assumed by existing studies. Second, people who were in the office communicated more, but incidental communication could be compensated to some extent by the experience of telecommuting. Third, unexpectedly, telecommuting for work that was thought to be only possible in the office led to a positive psychological state. Based on these findings, we will discuss how COVID-19 will change the way we work.

In the IoT ecosystem built by data platformers, algorithms are building further competitive advantages in large-scale teacher data and machine learning by increasing predictability through self-enhancement actions. It is hard to say that Japanese companies have a strong presence in the platform business, and it is not easy to build an advantage for Japanese companies from the viewpoint of population size and language. Therefore, in the business area which does not necessarily depend on large-scale data, we constructed deferred acceptance (da) algorithm and sought the area in which the optimal allocation of resources can be realized by providing them. As a result, it was suggested that the current assignment can be significantly improved by using the da algorithm. Japanese companies wonder if they can build a competitive advantage by steadily creating optimal algorithms in fields that do not rely on large-scale data or machine learning.

Data is one of the resources retained by all organizations, and is positioned as a seed that can establish new areas of research and development. In order to promote digital transformation in research and development (research DX) toward the realization of Society 5.0, as stated in the Sixth Science Basic Plan, it is required to conduct joint research through organization-to-organization industry-academia collaboration. In this paper, we point out the importance of perspectives for creating long-term value and valuing data as an intangible asset in order to eliminate bottlenecks in the establishment of organization-to-organization collaborations between universities and companies. In addition, we also focus on health and medical data as one of the seeds for the utilization of big data. In order to efficiently answer new research questions, it is necessary to construct life course data by linking diverse data retained by various institutions. Since the construction of such life course data, in which diverse data are collected and consolidated, requires a business design that maximizes the long-term interests of stakeholders, the effectiveness of establishing a consortium composed of relevant stakeholders is mentioned.

The health, clinic, and education information evaluation institute (HCEI) develop databases derived from nerborn to school age health check-ups under the contract with local governments in Japan, and epidemiological analyses are provided to both individuals and local governments. The anonymized database is maintained for the secondary epidemiology research by researchers. On the other hand, HCEI aldo develops anonymized clinical database (RWD-DB) derived from electric medical record of hosipitals in Japan. Eplidemiological analyses utilizing RWD-DB is provided to hosipitals for the purpose of improvement of clinical outcomes and safety. These initiatives are important not only for the research basis but also for the health policy and helath-related industry.

The essence of digital transformation (DX) in healthcare is to technologize the "tacit knowledge of clinicians." In healthcare, the clinician's role is to accurately assess the patient's condition, determine the best course of treatment, and inform other healthcare professionals of what to do next. Then, the treatment process begins, and the patient finally leads to the behavioral change by the various healthcare players. Thus, since all treatment processes begin with the "tacit knowledge of clinicians," it is none other than the essential element of healthcare. Therefore, from the perspective of competitive strategy, it is also a key factor for innovation. Furthermore, it can become Japan's unique core competence when combined with the Japanese universal insurance system. This next-generation medical DX platform, centered on the "tacit knowledge of clinicians," will lead the world in the future as a cutting-edge intelligence system and as a brand-new universal health insurance model.