In this paper, we propose Business Model Accomplishment Diagram that describes the causal relationship between the elements of business model and can explain the reason for business model success. And, we describe the diagram in logical programming language Prolog to apply to business chance discovery and business partnering problem. We develop a simple program in Prolog of business partnering example between companies about subscription business, and examine possibilities for chance discovery.

Product-harm crises occurred worldwide, and the effects are reflected not only on customers but also on enterprise value. In our study, we analyzed specific sites which publish scandals in Japanese and identified the keywords of product-harm crises using co-occurrence analysis. Based on the results, we can analyze news data to understand the effects of product-harm crises via event study. We will also analyze the news in different countries by natural language processing and aim at finding a difference in product-harm crisis management.

This study examines the impact of career development on employees and companies.The background of this study is that career development, which has originally been a part of human resource development for employees, is often said to be a human resource policy for companies to retain their employees. However, in reality, some companies believe that implementing career development as a part of human resource development will cause employees to develop the intention to leave the company, resulting in a series of resignations. This study intends to investigate the effects of career development on both employees and companies. The purpose of this study is three points. First, the study clarifies how career development implemented by firms helps retain human resources over the medium to long term and how it improves their commitment to the firm. Second, it simulates how employees behave in firms that implement career development in the labor market and in firms that do not in order to clarify how differences in firm commitment emerge. Third, it identifies how changes in employee networks affect firms.

For the promotion of people's health and industrial development in the life science field, smooth provision of medical data for the utilization of artificial intelligence in life science research is very important issue. Various social systems have been enacted so far, but it is not easy to provide medical data smoothly because stakeholders involved in the provision have various expectations and concerns. In this research, in order to promote research in the life science field, utilizing artificial intelligence through the smooth provision of medical data, we will survey the expectations and concerns of related stakeholders and design a mechanism to promote the provision of medical data suitable for them. This paper proposes a basic framework to promote the smooth provision of medical data, and describes future activities for social implementation of the framework.

To overcome the economic recession caused by the COVID-19 epidemic, the government launched the "Go To Travel" project in July 2020. However, the project was suspended in December 2020 due to the re-spread of the infection and has not resumed as of September 2022. On the other hand, apart from the national "Go To Travel" project, many local governments are implementing closed "prefectural discount" programs (regional tourism business supports) in their own limited areas to support the local tourism industry. This paper focuses on the economic impact of the prefectural discounts. Taking Hiroshima Prefecture as an example, an Internet survey was conducted to obtain accurate information regarding travel using the prefectural discounts. We then propose a stochastic estimation of the economic ripple effects using an input-output table and Monte Carlo simulation.

In this study, we developed the valuation model for new compounds of drug candidate by utilizing historical drug development and sales data which includes the target therapeutic areas of the compounds, clinical trial outcomes (success/failure), and post-launch sales data. Furthermore, for economic evaluation, we applied the scenario tree approach with Monte-Carlo simulation, which takes into account the option value of future withdrawal/expansion, instead of the conventional DCF method. Case studies showed the increases of value due to future flexibility of investment decisions and that indicated the scenario tree types simulation is valuable for the valuation of innovation in pharma industry.

In this research, we will create a model that estimates the attributes of followers based on the information of utterances on SNS as clues about what kind of customers support e-sports teams and their sponsor companies, and compare the attributes. The purpose is to clarify the sponsor's integrity by The survey targets e-sports teams that operate Twitter accounts and their sponsor companies. Using the information posted on Twitter, we will compare the attributes of followers between target accounts and analyze the trend of followers. Based on the analysis results, we propose indicators for optimal matching of teams and sponsors.

SASSEN was selected as a suitable sport for the subject experiment. Players were recruited and the experiment was conducted with and without incentives depending on the outcome of the game. We proposed a method to verify the relationship between the players' attitude toward the game with and without incentives and the change in their engagement in the sport before and after the game by combining a questionnaire survey and EEG measurement. We conducted an actual experiment and discussed the results of the questionnaire and points to be improved.

Crypto asset (Virtual currency) transactions have long been in the limelight. Crypto assets use cryptography to achieve decentralized management by participants on the Internet. Since they can be used by an unspecified number of people and there is no intermediary in the transaction, they are often misused for money laundering and terrorist financing. In this study, we adapt various machine learning methods to ELLIPTIC DATA, which is BITCOIN transaction data used in many previous studies. As a first step, we examine parameter optimization of random forests, feature refinement, sampling methods, and so on...

This paper analyzes the relationship between accelerator programs and startup financing in terms of external network structure. In recent years, interest in accelerator programs (AP) as a method for nurturing venture/startup companies (hereafter referred to as "startups") has been growing both domestically and internationally. The purpose of this paper is to examine the relationship between startup incubation and funding from the perspective of network structure, with the aim of clarifying the impact and effects of APs on startups.