Best Practices for Dealing with Price Volatility in Commercial Construction

Mscm, Justin E. Weidman; Miller, Kevin; Christofferson, Jay P.; Newitt, Jay S.

doi:10.1080/15578771.2011.552936

Cited by 17 publications

(10 citation statements)

References 4 publications

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“…Although many factors can impact the construction cost, 35 one of the main contributors to cost fluctuation is the prices changes in construction resources such as materials, labor, and equipment. 4,[36][37][38] Research methods…”

Section: Research Backgroundmentioning

confidence: 99%

Forecasting residential building costs in New Zealand using a univariate approach

Zhao

Mbachu

Zhang

2019

International Journal of Engineering Business Management

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Construction cost index has been widely used to prepare cost estimates, budgets, and bids for construction projects. It can also be regarded as an indicator of cost level, which makes it valuable to public authorities for understanding the conditions in the construction industry. Accurate forecasting of future construction cost index is essential for construction industry at both micro- and macro-level. To improve the accuracy of the cost forecasting, time series modeling techniques are adopted in this study. The performance of the exponential smoothing models and seasonal autoregressive integrated moving average (ARIMA) models for forecasting the building cost of five categories of residential building (one-story house, two-story house, town house, apartment, and retirement village building) in New Zealand is compared. Exponential smoothing models can produce more accurate forecasts for cost series of the one-story house and two-story house in New Zealand, while seasonal ARIMA models outperform exponential smoothing models across the cost series for town house, apartment, and retirement village building. This study contributes toward the development of the current state of knowledge in the area of cost index forecasting for New Zealand and provides insights that should be valuable from the practitioner perspectives.

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Section: Research Backgroundmentioning

confidence: 99%

Forecasting residential building costs in New Zealand using a univariate approach

Zhao

Mbachu

Zhang

2019

International Journal of Engineering Business Management

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“…However, some scholars are pointing to the fact that early cost estimates can be very inaccurate (Assaf and Al-Hejji, 2006). Furthermore, construction projects are capable of fluctuating as much as 10% or more of their cost value over periods as short as 6 months (Weidman et al, 2011), which makes "project costs" an even lessreliable parameter for time estimation. Some scholars are claiming that construction activities and their embedded production rates should be emphasized more in time planning and time estimation (Lucko et al, 2014), especially for linear infrastructure projects (i.e., roads, tunnels, and highways).…”

Section: Difficulties In Early Time Estimation Of Construction Projectsmentioning

confidence: 99%

Method for Base Estimation of Construction Time for Linear Projects in Front-end Project Phases

Dunović

Prebanić

Durrigl

2021

Organization, Technology and Management in Construction: An International Journal

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Even though horizontally linear projects have low complexity schedules, they are still not successful in meeting planned time. The deadlines are mostly based on estimations done in front-end project development when limited data are available. Early time estimation models in literature rely on few variables and, almost in all cases, one of them is the estimated cost. Early cost estimations can significantly deviate from actual costs and thus lead to unreliable time estimation. Time estimation models based on neural network and other alternative methods require databases and software, which complicates the process of time estimation. The purpose of this paper is to bridge the gap of scarce time estimation models and unreliable time estimates by developing a new method for time estimation. This research has been done on one large sewer system project. The case study shows how to extract several continuous activities for a pipeline project chosen from a sewer system. Moreover, a new algorithm for the calculation of project duration is devised based on the existing equation related to the linear scheduling method, and this algorithm works with continuous activities. The new method for construction time estimation is based on the extraction of linear continuous activities, usage of the algorithm for identification of minimal buffer between activities, and calculation of the project duration. To verify the algorithm, this method is used on another pipeline project from a sewer system. The limitation is that this method can be used only for base estimation. Further research needs to be done to include uncertainties and risks in the method.

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“…In general, Delphi studies use different sizes of panels [63]. Weidman and colleagues (2011) did not specify the number of panelists needed for a Delphi study; however, it is recognized that a minimum appropriate size should include 7 or 8 panelists [79]. Mitchell and McGoldrick (1994) argued that the size should be no less than 8 to 10 members [38].…”

Section: Panelist Selection Invitation and Participationmentioning

confidence: 99%

“…Moreover, many studies [63][64][65][66][67][68][69][70][71][72][73][74][75][76][77] have showed that Delphi can be useful to (a) obtain accurate information that is unavailable, (b) handle complex Sustainability 2019, 11, 3166 3 of 32 problems that require more judgmental analysis, (c) define areas where there is considerable uncertainty and/or a lack of agreed knowledge or disagreement, (d) allow for combining fragmentary perspectives into a collective understanding, (e) model a real world phenomena involving a range of viewpoints and for which there is little established quantitative evidence, and (f) highlight topics of concern and assess uncertainty in a quantitative manner. In particular, based on the summary explained in Appendix A [78][79][80][81][82][83][84], this research accordingly chose the Delphi technique to develop sustainable city indicators (SCIs) for Cambodia through three-round panel surveys. Delphi Round 1 initially developed the indicators.…”

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confidence: 99%

Developing Sustainable City Indicators for Cambodia through Delphi Processes of Panel Surveys

Chan

Lee

2019

Sustainability

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Currently, Cambodia does not have sustainable city indicators, and green and clean city indicators are also limited compared to UN Sustainable Development Goal 11 (SDG 11) indicators. Therefore, this research aims to develop sustainable city indicators for Cambodia and to address the questions "Are the green and clean city indicators limited in terms of sustainability?" and "Are the UN SDG 11 indicators suitable for Cambodia?" Delphi processes of panel surveys were conducted to develop the indicators in Round 1, pre-validate the indicators in Round 2, and validate the indicators in Round 3. The results showed that 69 initial indicators were obtained from Round 1; 41 pre-validated indicators were obtained from Round 2; and finally, 32 validated indicators were obtained from Round 3. All of the 32 indicators reached consensus. Based on the consensus indicators, the green and clean city indicators were found to be limited in terms of sustainability, and the UN SDG 11 has nine indicators suitable for Cambodia. These findings could be useful for applying the UN SDG 11 indicators to Cambodia and transforming the green and clean city indicators to sustainable city indicators. The 32 consensus indicators could be used as alternative sustainable city indicators for Cambodia.Sustainability 2019, 11, 3166 2 of 32 planning methodology document that "The development of green and sustainable cities in Cambodia is a key policy priority for the NCSD" [9] (p. iv). Furthermore, the government through its NCSD is currently developing the Code for Environment and Natural Resources. One chapter of the Code titled Sustainable Cities (Chapter 4) [10] is specifically to deal with the UN SDG 11 "Make cities and human settlements inclusive, safe, resilient, and sustainable" [11][12][13][14]. Moreover, Cambodia launched the clean city standard in order to improve urban quality and development by monitoring and evaluating cities through a clean city contest every three years [15], as well as the green city development program. The goal is to develop cities to be clean, green, and competitive while offering a safe and quality lifestyle to its residents [9,16,17].Based on the above reviewed sustainable city governance and development progress, Cambodia currently does not have indicators to monitor and assess the development of sustainable cities yet. Therefore, this research firstly aims to develop sustainable city indicators for Cambodia. The concept of sustainable development comprises three dimensions: Economic, social, and environmental [18][19][20][21][22]. The development must integrate the overlapping intersections of these dimensions, such as equitable (interaction between the economic and social dimension), liveable (correspondence of the environment to social needs), and viable [23-26] (economic development must abide by the supportive capacity of the ecosystems, and depletion of non-renewable resources must be avoided) [23] (p. 407). In this sense, sustainable city indicators need to be reached not only in terms of environmental di...

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Best Practices for Dealing with Price Volatility in Commercial Construction

Cited by 17 publications

References 4 publications

Forecasting residential building costs in New Zealand using a univariate approach

Forecasting residential building costs in New Zealand using a univariate approach

Method for Base Estimation of Construction Time for Linear Projects in Front-end Project Phases

Developing Sustainable City Indicators for Cambodia through Delphi Processes of Panel Surveys

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