The rapid growth of the Indian construction sector over the last few decades and recurring failure in on-time delivery highlight the need for a systematic analysis of the factors influencing delay. A theoretical structural equation model representing the influence of four key latent variables on project delays in the Indian construction industry has been developed. Data collected from a questionnaire survey and personal interviews, with 77 valid responses from clients, contractors and designers or architects, were used to further formulate and analyse the model. The results of the structural equation model suggest that client’s influence is one of the most significant factors affecting time performance on Indian projects. Client’s influence is also found to be one of the key contributing factors resulting in lack of commitment and contractor’s inefficiency in the project. Lack of efficient construction planning plays the second key role in adverse time performance. While the effect of lack of commitment on contractor’s inefficiency is highly significant, neither of these two factors has any direct impact on time delay in projects. Contrary to the notion that the contractor is the only party responsible for delay in construction projects, the results clearly highlight the importance of the role of clients and technical expertise in planning in achieving satisfactory time performance on Indian projects. It is hoped that these research findings will contribute significantly to the Indian construction industry’s efforts in addressing the root causes of delay and enhancing the time performance on projects.

This paper studies the adoption of Building Information Modelling (BIM) in emerging markets. The factors responsible for the adoption of BIM are studied in the context of Indian architectural firms. The mechanisms of diffusion of BIM are analyzed through a questionnaire survey based on the Technology–Organization–Environment (TOE) framework which broadly categorizes the influencing factors along these three dimensions. Data were collected through a web-based questionnaire survey. The 184 valid responses were analyzed using descriptive statistics. The study found that full potential of BIM has been explored but not realized by many in the Indian construction sector. Findings of the study are analyzed and compared with other emerging and developed markets. Based on the survey results, recommendations for increasing the BIM adoption are provided. Further studies and learnings from mature markets can help Indian construction sector develop effective BIM implementation strategies.

Building information modelling (BIM) is being heralded as a remarkable innovation in the built environment sector with expectations of lofty sector-wide improvements. Some countries have shown remarkable levels of uptake of BIM, along the way documenting some evidence of benefits stemming from BIM. However, countries such as India and China are late entrants in the BIM adoption journey and are seeing a slower adoption rate. This study develops a model using the technology–organization–environment framework to study the factors influencing BIM adoption by architectural firms in India and reasons for this slow adoption. The proposed model of BIM adoption is tested using the partial least square method against responses collected from 184 industry professionals based in India. Findings reveal that the adoption of BIM by Indian architectural firms is at the ‘experimentation’ stage with variables such as expertise, trialability, and management support exhibiting a strong positive influence on BIM adoption. The study also explains the status of BIM adoption in India with the help of a multi-level social construct, which places the level of BIM adoption in India between the micro- and meso-levels of organizational scales. Similarities and dissimilarities with previous findings are discussed in the paper to highlight the findings of this study.

Due to the central role of cranes in construction operations, specialists in the construction industries have cooperated in the development of structured methods and software for crane selection. Most of these software tools are for crane model selection, and integrated systems that handle both crane type and model selection are not readily available. This paper presents the crane type selection features of IntelliCranes, a prototype integrated crane selection tool that assists in both crane type and crane model selection based on a set of inputs describing the construction operation under consideration. By using historical data and advanced artificial intelligence computing tools such as artificial neural networks, IntelliCranes automates crane type selection. Crane type and crane model selection are seamlessly integrated in a comprehensive crane selection tool, and consistency in the selection of cranes for similar situations is increased.