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Fellows, Richard; Liu, Anita M.M.
doi: 10.1080/01446193.2013.794296pmid: N/A
Culture is an all-pervading construct of human existence but its conceptualization is contested. As such, it is problematic to define or measure culture as different paradigms adopt radically different approaches. Emic approaches are, essentially, inward-looking and, via a constructivist paradigm, assert that a culture can be investigated validly only from that culture’s own perspective (idiographic). Etic approaches are concerned with an outside view, especially for cross-cultural investigations, and so tend to adopt a positivist perspective using surveys, models and dimensions (nomothetic). With increasing acceptance of varying conceptualizations, multiple methodologies and methods of research, founded on alternative philosophical stances, differing approaches to researching culture are pursued. However, several important issues of debate remain and are addressed, especially surrounding the seminal work of Geert Hofstede. Further concerns relate to levels of analyses (notably, the ecological fallacy and its reverse), scales of measurement for data collection and analysis, and their combination into indices. How people adapt to and accommodate different cultures is addressed, including structuring of organizational relationships (alliances, etc.) and the enduring debate over whether culture can be managed and the likely consequences of cultural management endeavours. Thus, the approach of positive criticism is adopted in this review of theory and literature to address the main issues in both the topic of culture and its philosophical underpinnings, and of how research methodologies and methods have been used in researching culture. Aspects of good practice and of less good practice are identified throughout to assist researchers and to stimulate further rigorous research into culture in construction. Primary findings emphasize the imperative of coherent and consistent uses of models and levels of analysis, care and rigour in use of scales and attention to the impacts of language and culture on data from respondents.
Odeyinka, Henry A.; Lowe, John; Kaka, Ammar P.
doi: 10.1080/01446193.2013.802363pmid: N/A
Previous attempts have been made to model cash flow forecast at the tender stage using net cash flow, value flow and cost flow approaches. Despite these efforts, significant variations between the actual and modelled forecasts were still observable. The main cause identified is the issue of risk inherent in construction. Using the cost flow approach, a model is developed to assess the impacts of risk occurring during the construction stage on the initial forecast cost flow. A questionnaire survey and case study approach were employed. As a first step, a questionnaire survey was administered to UK construction contractors to determine the significant risk factors impacting on their cost flow forecast. Using mean ranking analysis, the survey yielded 11 significant risk factors. The second stage of data collection involves the collection of forecast and actual cost flow data from case study projects to establish their variations at predetermined time periods. Using the significant risk factors identified in the first phase, relevant construction professionals who worked on the case study projects were requested to score the extent of risk occurrence that resulted in the observed variations. A combination of these two sets of data was used to model the impact of risk on cost flow forecast using an artificial neural network back propagation algorithm. The model enables a contractor to predict the likely changes to a cost flow profile due to risks occurring in the construction stage.
Pinder, James; III, Robert Schmidt; Saker, Jim
doi: 10.1080/01446193.2013.798007pmid: N/A
Despite longstanding interest in the issue of adaptability, there has been very little research into the motives and obstacles to constructing more adaptable buildings, particularly from the perspective of the stakeholders involved in the building development process. The purpose of this study was to explore the reasons why more buildings are not constructed to be more adaptable, first through a review of the literature and then through interviews with industry stakeholders in the UK, including architects, developers, engineers, property agents and local authority planners. The literature review and stakeholder interviews revealed a wide range of motives for constructing for adaptability, such as a desire to reduce life cycle costs, to produce ‘future-proof’ buildings, and to ensure that buildings are easier to sell and let. However, the literature and interviews also revealed many obstacles to creating more adaptable buildings, including an assumption that adaptability always costs more, a lack of life cycle costing, uncertainty about the benefits of adaptability, fragmentation between industry stakeholders and short-term development models. The research highlighted the need to develop a better understanding of the costs and benefits of developing more adaptable buildings so that industry stakeholders can make more informed decisions about their buildings under conditions of uncertainty.
doi: 10.1080/01446193.2013.797095pmid: N/A
A neural network analysis was conducted on a quantitative occupational safety and health management system (OSHMS) audit with accident data obtained from the Singapore construction industry. The analysis is meant to investigate, through a case study, how neural network methodology can be used to understand the relationship between OSHMS elements and safety performance, and identify the critical OSHMS elements that have significant influence on the occurrence and severity of accidents in Singapore. Based on the analysis, the model may be used to predict the severity of accidents with adequate accuracy. More importantly, it was identified that the three most significant OSHMS elements in the case study are: incident investigation and analysis, emergency preparedness, and group meetings. The findings imply that learning from incidents, having well-prepared consequence mitigation strategies and open communication can reduce the severity and likelihood of accidents on construction worksites in Singapore. It was also demonstrated that a neural network approach is feasible for analysing empirical OSHMS data to derive meaningful insights on how to improve safety performance.
Espinoza, David; Morris, Jeremy W.F.
doi: 10.1080/01446193.2013.800946pmid: N/A
Despite its shortcomings, because of its simplicity, the net present value (NPV) technique (or its close relative, the internal rate of return) remains the valuation method most widely used by investors. In this method, all risks associated with a project are lumped into a single parameter (i.e. the risk premium) that is added to the risk-free interest rate to obtain a risk-adjusted discount rate; thus, in essence, the time value of money is adjusted for risk. However, because risk and time are two separate variables, accounting for risk in this manner can lead to substantial valuation errors, particularly for long-term investments which are typical for large infrastructure projects. In this paper, an alternative valuation method that decouples the time value of money from the risk associated with a project is presented. The proposed method, termed decoupled net present value (DNPV), is also simple yet flexible, consistent and robust. The method allows investors to integrate heuristic (i.e. experience based) techniques with sophisticated probabilistic and stochastic techniques to price the risk associated with the value of the asset created and/or the investment needed to create the asset. The proposed method results in a consistent valuation free from the problems typically associated with traditional net present value applications and, more importantly, allows a seamless integration of project risk assessment/management performed by technical experts into the project financial valuation.
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