BUILDING DEVELOPMENT PLANS FOR A CONSTRUCTION COMPANY BASED ON A DYNAMIC ASSESSMENT OF ITS LEVEL OF COMPETITIVENESS

Abstract

Improving the competitiveness of Russian industrial enterprises (including the construction industry) is a priority task at the current stage of development of the country’s economy. The purpose of this study is to develop methodological tools that would allow building strategic plans for the development of a construction company using a dynamic method for assessing its competitiveness. The hypothesis is that the target parameters of the development of a construction company, which take into account the influence of competitive factors, inevitably increase its level. This article provides an analytical review of existing methods for assessing the competitiveness of enterprises, identifies their advantages and disadvantages. The authors have chosen the dynamic approach to assessing the competitiveness of an enterprise; they propose certain aspects of its modernization, taking into account the specifics of construction production; the main indicators and algorithms used in this approach are presented. The competitiveness of the PIK group, Russia’s largest construction company, was evaluated in comparison with the Swedish development company Skanska Group, which is successful on the world market. The most problematic performance indicators of the Russian company that have a negative impact on its competitiveness are identified. Modeling of the dependence of the company’s competitiveness level on these indicators is performed. The results show that the key tool for eliminating these shortcomings can be the introduction of integrated information modeling based on big data for the entire development cycle: building information modeling — BIM (Building Information Modeling), augmented and virtual reality (AR/VR) technologies, and customer relationship management systems (CRM), among some others. The authors show how the key performance indicators of the company change after the introduction of integrated information modeling of the entire development cycle and what the forecast level of the company’s competitiveness can be expected at the end of 2020.