Governance of learning mechanisms : evidence from construction firms

The focus of knowledge management (KM) in the construction industry is moving towards capability building for value creation. The study reported by this paper is motivated by recent assertions about the genesis and evolution of knowledge management capability (KMC) in the strategic management field. It attempts to shed light on the governance of learning mechanisms that develop KMC within the context of construction firms. A questionnaire survey was administered to a sample of construction contractors operating in the very dynamic Hong Kong market to elicit opinions on the learning mechanisms and business outcomes of targeted firms. On the basis of a total of 149 usable responses, structural equation modeling (SEM) analysis identified relationships among knowledge-governance mechanisms, knowledge processes, and business performance, thereby supporting the existence of strategic learning loops. The study findings provide evidence from the construction context for capability assertions that knowledge-governance mechanisms and processes form learning mechanisms that carry out strategic learning to create value, effect performance outcomes, and ultimately drive the evolution of KMC. The findings imply that it is feasible for managing construction firms to govern learning mechanisms through managing the capability-based holistic KM system, thereby reconfiguring KMC to match needs in the dynamic market environment over time.

Visualizing the evolution of knowledge management capability in construction firms

A firm, as a dynamic, evolving, and quasi-autonomous system of knowledge production and application, develops knowledge management capability (KMC) through strategic learning in order to sustain competitive advantages in a dynamic environment. Knowledge governance mechanisms and knowledge processes connect and interact with each other forming learning mechanisms, which carry out double loop learning that drives genesis and evolution of KMC to modify operating routines that effect desired performance. This paper reports a study that was carried out within a context of construction contractors, a type of project-based firms, operating within the dynamic Hong Kong construction market. A multiple-case design was used to incorporate evidence from the literature and interviews, with the help of system dynamics modeling, to visualize the evolution of KMC. The study demonstrates the feasibility to visualize how a firm's KMC matches its operating environment over time. The findings imply that knowledge management (KM) applications can be better planned and controlled through evaluation of KM performance over time from a capability perspective.

Exploring governance issues on collaborative contracts in the construction industry

This paper reports the findings of an in-depth literature review, which was designed as the first phase of a study that ultimately aims to rank the importance of key governance mechanisms on collaborative construction projects, in terms of impact on value-for-money. The absence of such information in the global knowledge base has prompted the current study. Seminal research completed recently concluded that deductive evidence with regard to the performance outcomes of collaborative procurement mechanisms is currently limited (Eriksson and Westerberg 2011). The authors aim to address this gap in current understanding. The literature review identifies key features of both formal and informal mechanisms which have been applied within collaborative contracting contexts. The literature review lays a solid foundation for designing a deductive research strategy to be implemented in the second phase of the study, which will employ a large-scale quantitative survey to shed light on the governance structures of collaborative contracts, and the ways in which they impact on realisation of VfM during project delivery in the Australian infrastructure industry. The current paper aims to identify the main categories of formal and informal governance mechanisms currently being employed globally. This will provide structure for the development of the survey in the second phase of the study.

The strategic importance of tacit knowledge management activities in construction

Purpose: Tacit knowledge is perceived as the most strategically important resource of the construction organisation, and the only renewable and sustainable base for its activities and competitiveness. Knowledge management (KM) activities that deal with tacit knowledge are essential in helping an organisation to achieve its long-term organisational objectives. The purpose of this paper is to provide empirical evidence for the stronger strategic role of tacit KM in comparison to explicit KM. Design/methodology/approach: A questionnaire survey was administered in 2005 to a sample of construction contractors operating in Hong Kong to elicit opinions on the internal business environment, intensity of KM activities as executed by targeted organisations, and contribution of these activities to business performance (BP). A total of 149 usable responses were received from 99 organisations representing about 38 per cent of the sampling frame. The statistical analyses helped to map the reported KM activities into two groups that, respectively, deal with tacit and explicit knowledge. The sensitivity to variations of organisational policies and strength of association with BP in relation to the two groups of KM activities were also compared empirically. A total of 15 interviews with the managerial and professional staff of leading contractors was undertaken to provide insightful narratives of KM implementations. Findings: The effective implementation of organisational policies, such as encouraging innovations and strengthening strategic guidance for KM, would facilitate human interactions of tacit KM. Higher intensity of activities in managing tacit knowledge would ultimately help the organisations to achieve economic gain in the long run. Originality/value: The stronger strategic role of tacit KM is empirically investigated and established within the context of construction organisations.

Ontology-based feature modeling for construction information extraction from a building information model

A building information model (BIM) provides a rich representation of a building's design. However, there are many challenges in getting construction-specific information from a BIM, limiting the usability of BIM for construction and other downstream processes. This paper describes a novel approach that utilizes ontology-based feature modeling, automatic feature extraction based on ifcXML, and query processing to extract information relevant to construction practitioners from a given BIM. The feature ontology generically represents construction-specific information that is useful for a broad range of construction management functions. The software prototype uses the ontology to transform the designer-focused BIM into a construction-specific feature-based model (FBM). The formal query methods operate on the FBM to further help construction users to quickly extract the necessary information from a BIM. Our tests demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

Querying a building information model for construction-specific spatial information

The design and construction community has shown increasing interest in adopting building information models (BIMs). The richness of information provided by BIMs has the potential to streamline the design and construction processes by enabling enhanced communication, coordination, automation and analysis. However, there are many challenges in extracting construction-specific information out of BIMs. In most cases, construction practitioners have to manually identify the required information, which is inefficient and prone to error, particularly for complex, large-scale projects. This paper describes the process and methods we have formalized to partially automate the extraction and querying of construction-specific information from a BIM. We describe methods for analyzing a BIM to query for spatial information that is relevant for construction practitioners, and that is typically represented implicitly in a BIM. Our approach integrates ifcXML data and other spatial data to develop a richer model for construction users. We employ custom 2D topological XQuery predicates to answer a variety of spatial queries. The validation results demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

A prototype system dynamic model for assessing the sustainability of construction projects

There is a worldwide demand for an increasingly sustainable built environment. This has resulted in the need for a more accurate evaluation of the level of sustainability of construction projects. To do this it involves the development of better measurement and benchmarking methods. One approach is to use a theoretical model to assess construction projects in terms of their sustainable development value (SDV) and sustainable development ability (SDA) for implementation in the project life cycle, where SDA measures the contribution of a project to development sustainability and as a major criterion for assessing its feasibility. This paper develops an improved SDA prototype model that incorporates the effects of dynamical factors on project sustainability. This involves the introduction of two major factors concerning technological advancement and changes in people's perceptions. A case study is used to demonstrate the procedures involved in simulation and modeling, one outcome of which is to demonstrate the greater influence of technological advancement on project sustainability than changes in perception.

Providing query support to leverage BIM for construction

Building information modeling (BIM) is an emerging technology and process that provides rich and intelligent design information models of a facility, enabling enhanced communication, coordination, analysis, and quality control throughout all phases of a building project. Although there are many documented benefits of BIM for construction, identifying essential construction-specific information out of a BIM in an efficient and meaningful way is still a challenging task. This paper presents a framework that combines feature-based modeling and query processing to leverage BIM for construction. The feature-based modeling representation implemented enriches a BIM by representing construction-specific design features relevant to different construction management (CM) functions. The query processing implemented allows for increased flexibility to specify queries and rapidly generate the desired view from a given BIM according to the varied requirements of a specific practitioner or domain. Central to the framework is the formalization of construction domain knowledge in the form of a feature ontology and query specifications. The implementation of our framework enables the automatic extraction and querying of a wide-range of design conditions that are relevant to construction practitioners. The validation studies conducted demonstrate that our approach is significantly more effective than existing solutions. The research described in this paper has the potential to improve the efficiency and effectiveness of decision-making processes in different CM functions.

Impact of the internal business environment on knowledge management within construction organisations

Purpose: Recent knowledge management (KM) literature suggests that KM activities are influenced by the elements of the internal business environment (BE) of organisations. This paper attempts to provide some unique insights into the contextual input of the KM process through empirically identifying the major factors (i.e. “forces”) within the internal BE of construction organisations operating in Hong Kong, and investigating their impact on the intensity of KM activities. Design/methodology/approach: A questionnaire survey was administered to a sample of construction contractors operating in Hong Kong to elicit opinions on the internal BE and intensity of KM activities as executed by targeted organisations. A total of 149 usable responses were received from 99 organisations representing about 38 percent of the research population. In parallel, to the survey, a total of 15 semi-structured interviews were undertaken to provide more insights into the phenomenon under investigation. Findings: Supported by the empirical and qualitative evidence, this study established that firstly, both organisational and technical environments have the capacity to either positively or negatively impact the intensity of KM activities, and both environments serve as stimuli in increasing each other's dynamism; secondly, certain types of KM activities are stronger “energy receivers” and easily to be “powered up” by manipulating factors representing these two environments. Then, through interactions between KM activities, the intensity of the whole strategic KM cycle will be increased thus helping to strengthen organisational competitive advantage.

Collective sampling and analysis of high order tensors for chatroom communications

This work investigates the accuracy and efficiency tradeoffs between centralized and collective (distributed) algorithms for (i) sampling, and (ii) n-way data analysis techniques in multidimensional stream data, such as Internet chatroom communications. Its contributions are threefold. First, we use the Kolmogorov-Smirnov goodness-of-fit test to show that statistical differences between real data obtained by collective sampling in time dimension from multiple servers and that of obtained from a single server are insignificant. Second, we show using the real data that collective data analysis of 3-way data arrays (users x keywords x time) known as high order tensors is more efficient than centralized algorithms with respect to both space and computational cost. Furthermore, we show that this gain is obtained without loss of accuracy. Third, we examine the sensitivity of collective constructions and analysis of high order data tensors to the choice of server selection and sampling window size. We construct 4-way tensors (users x keywords x time x servers) and analyze them to show the impact of server and window size selections on the results.

Scheduling decisions and their dynamic consequences on construction performance

Construction practitioners often experience unexpected results of their scheduling-related decisions. This is mainly due to lack of understanding of the dynamic nature of construction system. However, very little attention has been given to its significant importance and few empirical studies have been undertaken on this issue. This paper, therefore, analyzes the effect of aggressive scheduling, overtime, resource adding, and schedule slippage on construction performance, focusing on workers’ reactions to those scheduling decisions. Survey data from 102 construction practitioners in 38 construction sites are used for the analysis. The results indicate that efforts to increase work rate by working overtime, resource adding, and aggressive scheduling can be offset due to losses in productivity and quality. Based on the research findings, practical guidelines are then discussed to help site managers to effectively deal with the dynamics of scheduling and improve construction performance.

Reasoning about component similarity in building product models from the construction perspective

Identifying the design features that impact construction is essential to developing cost effective and constructible designs. The similarity of building components is a critical design feature that affects method selection, productivity, and ultimately construction cost and schedule performance. However, there is limited understanding of what constitutes similarity in the design of building components and limited computer-based support to identify this feature in a building product model. This paper contributes a feature-based framework for representing and reasoning about component similarity that builds on ontological modelling, model-based reasoning and cluster analysis techniques. It describes the ontology we developed to characterize component similarity in terms of the component attributes, the direction, and the degree of variation. It also describes the generic reasoning process we formalized to identify component similarity in a standard product model based on practitioners' varied preferences. The generic reasoning process evaluates the geometric, topological, and symbolic similarities between components, creates groupings of similar components, and quantifies the degree of similarity. We implemented this reasoning process in a prototype cost estimating application, which creates and maintains cost estimates based on a building product model. Validation studies of the prototype system provide evidence that the framework is general and enables a more accurate and efficient cost estimating process.

Deriving construction features from an IFC model

In recent years, there has been a growing interest from the design and construction community to adopt Building Information Models (BIM). BIM provides semantically-rich information models that explicitly represent both 3D geometric information (e.g., component dimensions), along with non-geometric properties (e.g., material properties). While the richness of design information offered by BIM is evident, there are still tremendous challenges in getting construction-specific information out of BIM, limiting the usability of these models for construction. In this paper, we describe our approach for extracting construction-specific design conditions from a BIM model based on user-defined queries. This approach leverages an ontology of features we are developing to formalize the design conditions that affect construction. Our current implementation analyzes the component geometry and topological relationships between components in a BIM model represented using the Industry Foundation Classes (IFC) to identify construction features. We describe the reasoning process implemented to extract these construction features, and provide a critique of the IFC’s to support the querying process. We use examples from two case studies to illustrate the construction features, the querying process, and the challenges involved in deriving construction features from an IFC model.

Effects of schedule pressure on construction performance

Accelerating a project can be rewarding. The consequences, however, can be troublesome if productivity and quality are sacrificed for the sake of remaining ahead of schedule, such that the actual schedule benefits are often barely worth the effort. The tradeoffs and paths of schedule pressure and its causes and effects are often overlooked when schedule decisions are being made. This paper analyses the effects that schedule pressure has on construction performance, and focuses on tradeoffs in scheduling. A research framework has been developed using a causal diagram to illustrate the cause-and-effect analysis of schedule pressure. An empirical investigation has been performed by using survey data collected from 102 construction practitioners working in 38 construction sites in Singapore. The results of this survey data analysis indicate that advantages of increasing the pace of work—by working under schedule pressure—can be offset by losses in productivity and quality. The negative effects of schedule pressure arise mainly by working out of sequence, generating work defects, cutting corners, and losing the motivation to work. The adverse effects of schedule pressure can be minimized by scheduling construction activities realistically and planning them proactively, motivating workers, and by establishing an effective project coordination and communication mechanism.