Performance evaluation using data envelopment analysis - stepwise modeling approach: A case study of construction industries in Indonesia - Putri, Erni Puspanantasari; Parinov, Ivan A.; Plando, Almaceley S. (Universitas Serang Raya, 2024)
The construction industries are inextricably linked to employment, investment, the quantity of infrastructure building projects, and other economic sectors in Indonesia. They serve as catalysts for the expansion of goods and service production. Apart from having a strategic role in the national economic, construction companies also experience various obstacles to developing their businesses. These obstacles include weakening the IDR exchange rate against the US dollar, regulatory and legal frameworks, labor and skills shortages, economic and financial instability, and environmental and sustainability concerns. In order for the construction industry to survive, develop, and remain competitive in the face of international competition, it is crucial to evaluate its performance constantly. This research aims to evaluate the construction industry's performance in Indonesia. There are 151,183 construction companies included in this study. Hence, these companies will continue to survive, grow, and compete in the face of global competition. The methods applied in this research are an input-oriented DEA envelopment model and a stepwise modeling approach. The research results indicated that 3% of the Indonesian construction industry is made up of efficient DMUs, and the remaining 97% are inefficient DMUs. DMUs are classified according to the distribution of efficiency scores. It is considered that for the classification of inefficient DMU, there exist four ranges, Rs: R1 (ES = 0.16-0.99), R2 (ES = 0.050-0.15), R3 (ES = 0.015-0.049), and R4 (ES = 0.000-0.014). The criteria for each classification, in terms of the level of effectiveness, are as follows: i) R0 Range (ES = 1]): Effective; ii) R1 Range (ES = 0.16-0.99): Relatively Low Ineffectiveness; iii) R2 Range (ES = 0.050-0.15): Moderate Ineffectiveness; iv) R3 Range (ES = 0.015-0.049): Significant Ineffectiveness; and v) R4 Range (ES = 0.000-0.014): Very High Ineffectiveness. The percentage of each classification is as follows: inefficient DMU-R1 0%, inefficient DMU-R2 30%, inefficient DMU-R3 37%, inefficient DMU-R4 30%.