The application of building information modelling to enhance organisational learning

The construction industry is a knowledge-based industry where various actors with diverse expertise create unique information within different phases of a project. The industry has been criticized by researchers and practitioners as being unable to apply newly created knowledge effectively to innovate. The fragmented nature of the construction industry reduces the opportunity of project participants to learn from each other and absorb knowledge. Building Information Modelling (BIM), referring to digital representations of constructed facilities, is a promising technological advance that has been proposed to assist in the sharing of knowledge and creation of linkages between firms. Previous studies have mainly focused on the technical attributes of BIM and there is little evidence on its capability to enhance learning in construction firms. This conceptual paper identifies six functional attributes of BIM that act as triggers to stimulate learning: (1) comprehensibility, (2) predictability, (3) accuracy, (4) transparency, (5) mutual understanding and (6) integration

The impact of building information modelling (BIM) maturity and experience on contractor absorptive capacity

Building information modelling (BIM) has been adopted with increasing frequency by the construction industry in the last few years due to its potential to enhance construction business performance. While there is a general belief that higher BIM proficiency will lead to higher business performance, few empirical studies have tested this relationship. This research explores the extent to which a positive relationship exists between BIM adoption and organisational learning. The impact of BIM maturity and years of experience on the absorptive capacity (AC) of contractors to adopt new information for organisational learning is investigated through a survey of Australian building contractors. While BIM experience was found to be a significant predictor for contractor AC, the analysis of variance showed no significant relationship between BIM maturity and AC. The literature indicates a pervasive belief in a potent relationship between BIM maturity and organisational learning, yet it seems that factors traditionally viewed as more peripheral play a bigger role than expected in determining the impact of BIM on learning and business performance. Subsequent interviews found that (1) poor business ties, (2) willingness to share information and (3) organisational cultural values weaken the expected relationship between BIM maturity and AC. The results suggest that the extent of an organisation's experience with BIM is a greater predictor of learning performance than the complexity of BIM usage within the organisation. The main contribution of this paper is to reveal the complexity surrounding the relationship between BIM and business performance

Engaging residents from different ethnic and language backgrounds in disaster preparedness

Modern societies are increasingly a melting pot of people from different cultural and linguistic backgrounds which needs to be taken into consideration in disaster planning. People from different ethnic and language backgrounds are sometimes more vulnerable in a disaster due to a number of challenges including language barriers, cultural perceptions, social isolation, poor assimilation with the local community and distrust of authorities. The level of disaster preparedness differs significantly at a household level, yet there is little understanding of how an individual's attributes such as age, ethnicity, language skills and gender, influences and sustains the level of disaster preparedness. Past research has explored one or more of these attributes, but the relationship between ethnicity, language skills and disaster preparedness is least understood. To address this gap, this paper investigates how an individual's ethnicity and language skills influence their levels of disaster preparedness. A questionnaire survey was conducted with 180 residents from a variety of ethnic and language backgrounds in Logan City, a local government area in Australia. The survey results were analyzed using hierarchical regression analysis, and suggest that ethnicity and English Language skills, accounted for significant variations in levels of disaster preparedness in the case study location. The findings suggest that policy makers need to give due consideration to how different ethnic groups understand and prepare for disasters, and to design disaster management and communication plans that cater for different language ability

Disaster awareness and information seeking behaviour among residents from low socio-economic backgrounds

An individual's socio-economic status can increase their vulnerability to, and ability to prepare for and recover in the aftermath of a disaster. People from low socio-economic (LSE) backgrounds often face greater disaster risks, but are least prepared for disaster events due to a number of factors including a lack of housing affordability, low income and literacy levels. While there is an established relationship between a person's socio-economic status and disaster vulnerability, very little is understood about the disaster information seeking needs and preferences of LSE population groups and how this affects their levels of disaster awareness. This paper addresses this gap through a comparative study of LSE and non-LSE population groups to identify key disaster information sources and how it shapes levels of disaster awareness. A survey of 224 residents was conducted, and multivariate regression analysis of both LSE and non-LSE respondents revealed a trend of disaster passivity in both population groups. English language proficiency, occupation, familiarity with the local environment are the most important factors influencing disaster awareness among the LSE population groups. For non-LSE population groups, disaster awareness is gender-dependent with females showing higher levels of awareness. Overall, television was the most trusted information source regardless of socio-economic status. The results provide a better understanding of the underlying impact of socio-economic status on disaster awareness and information seeking behaviour, which can assist practitioners and policy makers in making informed decisions on disaster mitigation strategies to reduce the disaster risk vulnerability of targeted population groups