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This study aims to analyse, from a corporate finance and governance perspective, the reasons why managers decide to delist their companies from a stock exchange. On the basis of the five hypotheses of voluntary delisting, this study examines why listed companies delist themselves voluntarily in the construction and real estate sectors.

By using actual data to examine contractors and real estate companies listed on the Tokyo Stock Exchange between 2004 and 2014, this study analyses whether these companies delist themselves voluntarily. The pooled binary logit model is used as the statistical method.

In both the construction and real estate sectors, the concentration of shareholders has a significantly positive effect on voluntary delisting, thus supporting the transfer of wealth effect hypothesis. In construction, market capitalisation has a significantly negative effect on voluntary delisting, thus supporting the maintenance cost reduction hypothesis. In the real estate sector, the ratio of market capitalisation to total assets has a significantly negative effect on voluntary delisting, thus supporting the undervalue elimination hypothesis.

By comparing the construction and real estate sectors, this study reveals both unique and common reasons for voluntary delisting in each sector. It also offers valuable insights to managers, regulators setting standards in securities markets and investors.

The purpose of this paper is to examine the factors that affect the discontinuance of business of start-up contractors and property companies in Japan. It will help managers of start-up contractors and property companies to effectively manage their companies. Furthermore, it will be useful for stakeholders with links to start-up companies to analyse the credit risks associated with these businesses.

This study uses data from the Japan Finance Corporation Business Startup Panel Survey to empirically examine the factors that affect the discontinuance of business of start-up companies. A binary logit model is used as the statistical method. Utilising the resource-based view theory, this study explores the relationships between resources and company capabilities at both start-up and discontinuance of business.

Start-up contractors tend to discontinue their business, as managers grow older and when a sufficient workforce cannot be found at start-up. On the other hand, start-up property companies tend to discontinue business when securing of orderers is not sufficient at start-up.

This study analyses start-up contractors and property companies and finds that factors that affect the discontinuance of business differ across construction and property industries, with each industry facing important, sector-specific issues.

The purpose of this paper is to examine the factors influencing defaults and exits from public works by prime contractors of small and medium-sized enterprises in the Japanese construction industry. By analysing the data for several years as panel data, this study determines the extent of influence of changes in company characteristics on the defaults and exits.

Using construction company evaluation (Keiei Jikou Sinsa or Keisin) data and by employing the panel binary logit random effect model, this study empirically analyses the construction industry.

This study shows that defaulting and exiting companies have different characteristics. The result shows financial performance indicators, non-financial performance indicators and Keisin scores to significantly affect defaults and exits. In particular, this study finds non-financial performance indicators, such as whether a firm draws insurance, to significantly affect its likelihood to default or exit and the influence varies on the basis of insurance type.

The feature of this study is that its analysis focuses not only on defaulting companies but also on exiting companies, defined as those that stop operating as prime contractors for public works but otherwise stay in business. In contrast to existing research, this study distinguishes between defaults and exits and analyses the factors that influence a firm following one of these two outcomes. Moreover, although Keisin data are usually used to determine whether companies qualify to enter bids for public works, they can be applied for an attribution analysis of corporate defaults and exits.

The purpose of this study is to examine what factors affect the exit of small and medium-sized enterprises (SMEs) from tendering for public works in the Japanese construction industry using the Keiei Jikou Sinsa or Keisin (the database for evaluation of construction companies in Japan).

This study empirically analyzes SMEs’ exit using the binary logit model. For the empirical analysis, it uses the scores as well as financial and non-financial performance indicators of Keisin data.

The Keisin scores (the total score and W score), financial performance indicators (cash flow from operations and capital) and non-financial performance indicators (having unemployment insurance and operating years) significantly affect SME exits. Although the Keisin data are used for bid entry qualifications of public works, they can be applied to a factor analysis of the exit of SMEs in the construction industry.

As there exists little empirical analysis of the exit of SMEs globally, this study contributes to the research on this phenomenon.