Is construction ripe for disruption?

The notion of 'disruption' and particularly that of 'disruptive innovation' is now widely used by researchers as well as management practitioners, and the construction industry is being described as 'ripe for disruption'. By comparing this industry to healthcare (another massive, societally important industry also considered ripe for disruption), this paper applies the lens of disruption theory to analyse the current and anticipated status of the construction industry. To do so, we ask and answer three central questions: Why should construction be ripe for disruption? When will disruption potentially occur? How will disruption likely manifest? We find that both industries share a number of challenges, including a fragmented stakeholder network, complex incentive structures and a sense of being in a deadlock that makes change difficult. Furthermore, we find that in both industries the term 'ripe for disruption' describes a process rather than prescribe when disruption will occur. By applying central notions from disruption theory (disruptive technologies, low-end disruption, new-market disruption, and a focus on value creation), we identify several potential disruptors of the construction industry. To conclude, we discuss the benefits and limitations of applying disruption theory to the construction industry

Is construction ripe for disruption?

The notion of 'disruption' and particularly that of 'disruptive innovation' is now widely used by researchers as well as management practitioners, and the construction industry is being described as 'ripe for disruption'. By comparing this industry to healthcare (another massive, societally important industry also considered ripe for disruption), this paper applies the lens of disruption theory to analyse the current and anticipated status of the construction industry. To do so, we ask and answer three central questions: Why should construction be ripe for disruption? When will disruption potentially occur? How will disruption likely manifest? We find that both industries share a number of challenges, including a fragmented stakeholder network, complex incentive structures and a sense of being in a deadlock that makes change difficult. Furthermore, we find that in both industries the term 'ripe for disruption' describes a process rather than prescribe when disruption will occur. By applying central notions from disruption theory (disruptive technologies, low-end disruption, new-market disruption, and a focus on value creation), we identify several potential disruptors of the construction industry. To conclude, we discuss the benefits and limitations of applying disruption theory to the construction industry

Identifying Disruptive Technologies: Horizon Scanning in the Early Stages of Design

Technology development is accelerating, driving disruption. Design is seen as key differentiator in creating innovative offerings but few design methods consider future technologies explicitly. In this article, we explore how a foresight method, namely horizon scanning, may be applied in a design context to anticipate disruption of construction. By means of a 3-step horizon scan, we identify 133 potentially disruptive technologies from across industries. We find that when preparing for disruption, design may benefit from the future-oriented and technology-focused features of horizon scanning

Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment

The transition zone between land and water is difficult to map with conventional geophysical systems due to shallow water depth and often challenging environmental conditions. The emerging technology of airborne topobathymetric light detection and ranging (lidar) is capable of providing both topographic and bathymetric elevation information, using only a single green laser, resulting in a seamless coverage of the land–water transition zone. However, there is no transparent and reproducible method for processing green topobathymetric lidar data into a digital elevation model (DEM). The general processing steps involve data filtering, water surface detection and refraction correction. Specifically, the procedure of water surface detection and modelling, solely using green laser lidar data, has not previously been described in detail for tidal environments. The aim of this study was to fill this gap of knowledge by developing a step-by-step procedure for making a digital water surface model (DWSM) using the green laser lidar data. The detailed description of the processing procedure augments its reliability, makes it user-friendly and repeatable. A DEM was obtained from the processed topobathymetric lidar data collected in spring 2014 from the Knudedyb tidal inlet system in the Danish Wadden Sea. The vertical accuracy of the lidar data is determined to ±8 cm at a 95 % confidence level, and the horizontal accuracy is determined as the mean error to ±10 cm. The lidar technique is found capable of detecting features with a size of less than 1 m². The derived high-resolution DEM was applied for detection and classification of geomorphometric and morphological features within the natural environment of the study area. Initially, the bathymetric position index (BPI) and the slope of the DEM were used to make a continuous classification of the geomorphometry. Subsequently, stage (or elevation in relation to tidal range) and a combination of statistical neighbourhood analyses (moving average and standard deviation) with varying window sizes, combined with the DEM slope, were used to classify the study area into six specific types of morphological features (i.e. subtidal channel, intertidal flat, intertidal creek, linear bar, swash bar and beach dune). The developed classification method is adapted and applied to a specific case, but it can also be implemented in other cases and environments