An empirical analysis of the discontinuance of business for startup contractors and property companies in Japan

Abstract

Purpose – 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. Design/methodology/approach – 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. Findings – 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. Originality/value – 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.

Influence of organizational configurations on startup performance

“…The search for entrepreneurial strategies, innovation, and high performance entails a major need for financial resources (Wiklund & Shepherd 2005). Similarly, Konno (2015) indicates access to financial capital as a factor that influences startup success, stating that those that manage to raise funds are more likely to survive.…”

“…However, analyzing them in comparison with ESI, it is noted that configurations C1 and C3 used more TSI (e.g. personal reserves) than ESI, which are more compatible with the idea of venture capital and major uncertainty of startups, which may suggest a greater capacity for success (Konno, 2015). These results highlight the predominance of choosing self-financing mechanisms, without the commitment of third-party investors, corroborating the information that the literature links to the context of startups, a scenario which, due to the lack of guarantees (Brown et al, 2012;Hyytinen et al, 2015;Minetti, 2011) and due to investments in innovation often being associated with long and uncertain recovery times (Brown et al, 2012;Minetti, 2011), restricts access to external financing (Berger & Udell, 2006;Hyytinen et al, 2015).…”

“…Samagaio et al (2018) and Crespo et al (2019) used that approach to analyze startup characteristics and their relationship with management control system adoption. In the startup literature, various factors have been used to explain organizational performance (Cacciolatti et al, 2020;Cassar, 2014;Crespo et al, 2019;Davila & Foster, 2005Konno, 2015;Lewrick et al, 2011;Miranda et al, 2016;Plummer et al, 2016;Shirokova et al, 2016), but those studies use models that test, in a reductionist way, the association of some variables with performance. One of the main weaknesses of the studies on control systems is their examination of one or two variables in isolation (Flaherty et al, 2014).…”

Integrating Indigenous enterprises into the Australian construction industry

“…Although there has been no research into barriers to entry for Indigenous enterprises into the construction industry, it is generally considered that the construction industry has relatively low barriers to entry (Murray and Smyth, 2011; de Valence, 2012). Evidence presented to support this view is the relatively high level of start-ups in the construction industry each year (Anikeeff and Sriram, 2008), although there is also considerable evidence that a large number of these new firms fail (Holt, 2013; Konno, 2015). Indeed, a recent report by ASIC (2014) identified the construction industry as one of Australia’s riskiest industries to operate within, consistently having one of the highest insolvency rates on any industry at around 23 per cent annually.…”

Methods Dealing with Complexity in Selecting Joint Venture Contractors for Large‐Scale Infrastructure Projects

“…The ANP-Monte Carlo simulated model proposed by El-Abbasy et al [19] is a novel approach where multiattribute is considered to select the best contractor for highway projects. Furthermore, analysis of the methodological approaches was based on the chosen categories of statistical/deterministic modelling [20], literature/documentary analysis [21], surveys [22], and other nondeterministic forms [23][24][25][26][27][28].…”