Irem Dikmen, M. Talat Birgonul, Beliz Ozorhon and Nurdan Egilmezer Sapci
The paper seeks to identify the determinants of business failure in construction and to predict the failure likelihood of construction companies by assessing their current…
Abstract
Purpose
The paper seeks to identify the determinants of business failure in construction and to predict the failure likelihood of construction companies by assessing their current situation based on both company‐specific and external factors.
Design/methodology/approach
A conceptual model is designed based on an extensive literature survey. The analytical network process together with the Delphi method is utilised to compute the importance weights of variables on business failure through interviews and discussions with experts. The applicability of the proposed model is tested on five companies to estimate their failure likelihood by using the findings derived from the analysis.
Findings
The results suggest the importance of organisational and managerial factors, including the efficiency of the value chain at the corporate level, the appropriateness of organisational decisions, and the availability of intangible resources for the survival of construction companies.
Research limitations/implications
The findings of the analysis are limited to the experiences of three professionals in the Turkish construction industry. The performance of the model is only tested in five companies. The accuracy of the model may be improved by using the diverse experiences of a larger group of experts.
Practical implications
The proposed tool may act as an early warning system for construction companies by estimating the level of their failure likelihood. Companies may benefit from the findings of the model to assess their current situations and take necessary action to avoid possible business failures.
Originality/value
The knowledge and experiences of experts are used to obtain a complete model that accommodates both external and company‐specific variables, and more importantly the inter‐relations among them. Similar models may also be developed for companies in other industries to diagnose their bankruptcy or failure likelihood.