The contribution of Indian construction sector to the GDP is approximately 10%. Under new government policy, it is anticipated that $1000 Billion share for exclusively infrastructure segment would be completed within the next few years. Construction sector in developing country like India still depends on labor and the practice of mechanization, adopting to use of versatile construction equipment is not in force. The need for implementing new technologies and automation is essential to improve the quality, safety and efficiency. To meet the challenges ahead the construction, organizations should focus on utilization of machinery/equipment to achieve desirable results. Modern construction is characterized by the increase in utilization of equipment to accomplish numerous construction activities. The selection of construction equipment often affects the required amount of time and effort. It is therefore important for managements of construction organizations and planners to be familiar with the features of various types of equipment commonly used in construction activities. The selection of appropriate equipment is a crucial decision making process as it involves huge capital investment. The purpose of the present study is to develop a model pertaining to the factors influencing the selection of construction equipment by using interpretive structural modelling and the results indicate that productivity and safety are the important factors in selection of equipment in Indian construction organizations.

The main objective of this paper is to identify and understand the relationship dynamics among the quality enabled factors affecting the scheduling stage of production system life cycle. For this purpose, Interpretative structural modelling (ISM) approach has been utilized for developing the relationships among the various factors of the scheduling system stage. Afterwards, MICMAC (Matriced Impacts Croises Multiplication Appliqueeaun Classement) analysis has been carried out in order to classify the factors into different categories and to disclose the direct and indirect effects of each factor on the scheduling system. It is an approach for refining the decision making in the scheduling stage of production system life cycle.