ECONOMIC EFFICIENCY OF CONSTRUCTION EQUIPMENT FLEET RENEWAL AT INDUSTRIAL CONSTRUCTION ENTERPRISES

Abstract

The article examines the economic efficiency of renewing the construction equipment fleet at industrial construction enterprises under conditions of a wartime economy and preparation for Ukraine's post-war recovery. It substantiates that the efficiency of renewal is determined not by the purchase price of an individual machine but by the total cost of ownership over its life cycle, discounted at a rate that adequately reflects inflationary and military risks. The relationship between static and dynamic methods of investment appraisal is analysed, and it is shown that the simple payback period systematically distorts managerial decisions under double-digit inflation, whereas net present value, internal rate of return, discounted payback and total cost of ownership provide a more economically sound basis for choice. Models of the optimal moment of equipment replacement are considered, in particular the Terborgh–Dean model and the minimum average total cost model, together with the impact of physical and moral depreciation on machine productivity. The features of enterprises' depreciation policy are outlined in accordance with national accounting standards and tax legislation, including the possibility of accelerated depreciation during martial law. The dynamics of industrial construction in Ukraine over 2020–2025, the structure of capital investment and the potential demand for equipment in the context of post-war recovery programmes are analysed. A comparison of forms of financing renewal is carried out, namely direct purchase, bank lending, financial and operating leasing, the state preferential lending programme, and the market of used and refurbished equipment. The impact of downtime, the technical availability ratio and fuel efficiency on the contractor's profitability is assessed. An author's hybrid fleet renewal strategy for medium-sized enterprises is proposed, with the definition of specific benchmarks for managerial decision-making.