In 2009, the tax system for the business succession of small-and medium-sized busibesses was introduced under the Special Taxation Measures Law, putting in place the preferential tax treatments (deferment of taxation and reduction of taxable amount for inheritance or gift of business assets). Although the provisions on conditions for accessing the system were partially amended in 2013, 2015 and 2017, the system was used in less than 3,000 cases in the 10 years since its establishment. In order to promote uptake of the system, the provisions of the Special Taxation Measures Law were drastically revised in 2018. As “special measures” for 10 years from 1 January 2018 to 31 December 2027, the conditions related to tax-deferred treatment of a company’s own shares were eased. This revision is expected to increase uptake of the preferential tax treatment. In this article, the implementation of these key uptake conditions of the tax system for business succession will be viewed alongside the “general measures” implemented before 2018. The challenges of the business succession tax system are rigorously highlighted.

This paper firstly evaluates the current status of experimental research in accounting research and various accounting fields and how experimental accounting is looking to the future from the perspective of “future-orientation”, “causal relationships”, and “unified strategy”. Next, we examine the significance of using pre-registration and online labor markets, which are attracting attention not only as new methodological initiatives but also for their potential to increase reproducibility and to solve external validity problems.

Furthermore, regarding the recent trend toward online experiments using Amazon Mechanical Turk, SurveyMonkey Audience, Qualtrics, etc., which are highly anticipated new research platforms for overcoming the problem of external validity, we compare these platforms in terms of cost, flexibility, and accessibility to interest groups. The latest experimental accounting research such as readability experiments, which have been increasing in recent years, is also reviewed. Finally, we review the prospects for interactive online experiments using tools such as “oTree”, which is gaining profile as a future research platform.

In this study, we examine the impact of pro bono experience on consultants for whom, it represents an interaction between two activity systems, and we analyze how consultants derive expansive learning from their experiences. The results of the analysis can be summarized as the following three points:

1. Information about the careers of consultants and the consultant personnel system were first obtained in interviews with human resources departments. Compared to typical managers, consultants progress to management in 3–4 years on average, but there is a lot of variation between individuals in terms of promotion to a position which demands managerial skill and diplomacy. If the career ladder cannot be climbed, employees either stagnate or end up leaving the company. They enter the pro bono activity system as a training program to overcome career hiatus.

2. The differences between consulting and pro bono activity systems are clear when delineated in terms of the following elements: subject, object, tools, community, rules and division of labor, as stated in the activity theory. The differences are likely to generate expansive learning.

3. Consultants who observed the four contradictions between activity systems tended to end up reflecting on their usual working style, conceptualizing their experience and developing new models. As a result, they showed changes in their behavior and attitude that led to success. Although a small number of cases was canvassed, it was found that the degree of expansive learning varied among individuals. The importance of questioning and critique when faced with issues during the pro bono practice is indicated. The deeper the recognition of contradictions, the more effective expansive learning becomes.

With the rise of social media, particularly Facebook, brands have started engaging with consumers in this digital space. Facebook pages have become an additional communication channel that could be integrated with the traditional ones, and a key challenge for marketers is how Facebook pages can be leveraged to engage consumers and enhance their relationship with brands. However, little academic research has been done on consumer engagement behaviors on Facebook pages. Through a questionnaire survey of 1,094 Facebook users, this study investigates whether and how the unique characteristics (such as benefits, trust, commitment, interactivity and brand loyalty) of Facebook pages affect consumer engagement behaviors. Consumer engagement behaviors are measured by intention to “like”, comment on and share Facebook pages. The findings of the empirical analysis are as follows:

“Like” intention: Hedonic benefit, trust, commitment, recommendation, and “like” experience have a positive influence on “like” intention. Hedonic benefit is significant only for “like” intention.

Comment intention: Social benefit, interactivity, commitment and recommendation have a positive effect. Social benefit is significant only for comment intention. “Like” experience is not significant and comment experience has a positive influence. In addition, men have a greater influence than women.

Share intention: Trust, interactivity, commitment, and recommendation are significant predictors. Comment experience also has a positive effect.

The purpose of this study is to propose methods that contribute to brand management by using qualitative analysis (QCA: Qualitative Comparative Analysis) and MDSO-MSDO approach) and quantitative methods (soft clustering).

QCA is set-theoretic methods based on Boolean algebra. In this study, it is applied to clarify the diversity of individual brand evaluation structures and causal condition.

MDSO and MSDO is an acronym for “Most Different cases, Similar Outcome/Most Similar cases, and Different Outcome”. MDSO is used to identify “the case with the most different evaluation criteria in groups with similar results”, and MSDO is used to identify “the case with the most similar evaluation criteria between groups with different results”. In this study, it applies to the purpose of extracting the subjects which should be examined in detail from the target customers.

However, in the MDSO-MSDO approach, extremely unusual targets may be extracted, and there remains concern that the identified targets should be considered deeply. Therefore, we also propose a procedure for cross examining the extremity of the targets by using soft clustering.

In recent years, corporate social innovations (CSI) through their businesses are required all over the world. CSI is deeply connected to corporate social responsibility (CSR). Previous studies have shown that CSR has emphasized the potential for innovation. Legitimacy has to be proven to stakeholders for resource mobilization to implement CSI. This study explores the CSI process and their legitimacies through two case studies in Japan. It also provides an insight into a new concept of “exclusiveness” in CSI, and into social entrepreneurs decision-making processes. This paper highlighted the following: first, social entrepreneurs emphasize moral or cognitive legitimacy in the promotion of CSI as well as paying attention to pragmatic legitimacy. Second, we can draw out four types of CSI legitimacies: social environmental factors, external human resource factors, internal cultural factors, and internal technical factors. And third, social entrepreneurs have their own unique reasons for these CSIs implementation, and therefore have to decrease their “exclusiveness” in CSI process.

The strategic use of intellectual property in industrial clusters is important in creating new industries such as tech start-ups, as well as for revitalizing regional economies.

In this paper, of all businesses participating in industrial clusters, R & D-basedindustries, research institutions and similar organizations (“R&D-based industries”) which are particularly competitive and value-adding, are the main focus of this study.

These industrial clusters also accumulate regionally distinctive intellectual property (patents for the purpose of this paper).

It is assumed that the accumulation of IP means that the knowledge of the inventors of the IP is also accumulated.

Furthermore, if we can capture this phenomenon of knowledge clustering and harness the mechanism, it should be possible to derive regional industrial policies for regional economic revitalization.

This paper focuses on three regions that connect the Tokyo metropolitan area and rural areas as industrial cluster regions. Patent information is used to derive a group of IP clusters formed from regional IP clusters, and regional industrial policy planning methods are examined using the results of the analysis. (178)

New drug discovery typically involves “science-based” research and development, and as such, basic research is often cited as significantly contributing to new drug discovery. However, basic biomedical research primarily aims to elucidate biological functions, not to discover new drugs. This means that the ability to select correctly from numerous basic research discoveries, such as new physiological molecules and mechanisms that can lead to drug discovery (or the “drug target selection capability,” as referenced in this paper), is crucial for new drug discovery researchers.

Nevertheless, past studies have hardly considered the “drug target selection capability” concept. This paper indicates that the drug target selection capability of researchers to appropriately select new drug target molecules and mechanisms for drug discovery is a potential factor generating competitive advantage for drug researchers, based on detailed analysis of the research process behind innovative drug discovery cases in Japan. The paper also describes the necessity for deep understanding and insight regarding the mechanism of pathogenesis for diseases in fostering drug target selection capacity, as well as the pharmacodynamics of existing drugs and an understanding of basic physiological functions. The academic and practical implications of this study are also discussed.

Digital technology is widely used in everything from design and development of industrial products to production.

Because of its characteristics, digital technology has various effects on business management, manufacturing sites and elsewhere.

Of these characteristics, this paper focuses on the “standardization of technology”, examining how it affects the small and medium-sized manufacturing sector from case studies, and discussing the strategies for dealing with digital technologies in small and medium-sized manufacturing.