Application of Ginni’s mean analysis for identifying the stationary driver enhancing modular construction adoption in the building industry

Abstract

Modular construction (MC) is recognized as an environmentally friendly and sustainable building method, and it is mandatory for assessing project sustainability. In developed countries, MC is acknowledged as a crucial approach for sustainable development, leading to increased adoption in these nations. However, implementing and incorporating MC in developing nations is a multifaceted task due to infrastructure limitations, economic inequalities, and resource constraints, which limit its widespread adoption. This study aims to find the stationary driver that increase MC usage in developing nations, especially in residential projects. To achieve this objective, a total of 120 building professionals participated in the questionnaire. Following this, the Relative Importance Index and Gini’s Mean analyses were employed to assess the significance of the top 5 ranked drivers and to pinpoint the stationary driver. According to the study results, the five major MC drivers are as follows: Determining the correct weights and dimensions of modules by optimal design; Considering the detailed survey of fabricators’ MC experience and competency; Early screening tests during the selection of fabricators and factories; Early engagement of the heavy lift team in relevant research; and Avoiding suboptimal modular equipment sizes that might restrict transportation options. Additionally, the Gini’s Mean analysis revealed the stationary driver that promotes MC adoption is the need for expert advice for equipment specifications, scheduling, and sequence. The research findings pave the way for the Egyptian construction industry to adopt MC, which will improve the construction sector, particularly residential construction. Furthermore, the results address a knowledge gap about the drivers that enhance the adoption of MC in developing nations.