Abstracts – Browse Results

Search or browse again.

Click on the titles below to expand the information about each abstract.
Viewing 13 results ...

Abotaleb, I S and El-adaway, I H (2017) Construction Bidding Markup Estimation Using a Multistage Decision Theory Approach. Journal of Construction Engineering and Management, 143(01).

Chang, C and Ko, J (2017) New Approach to Estimating the Standard Deviations of Lognormal Cost Variables in the Monte Carlo Analysis of Construction Risks. Journal of Construction Engineering and Management, 143(01).

Francis, A (2017) Simulating Uncertainties in Construction Projects with Chronographical Scheduling Logic. Journal of Construction Engineering and Management, 143(01).

Franz, B, Leicht, R, Molenaar, K and Messner, J (2017) Impact of Team Integration and Group Cohesion on Project Delivery Performance. Journal of Construction Engineering and Management, 143(01).

Gambatese, J A, Pestana, C and Lee, H W (2017) Alignment between Lean Principles and Practices and Worker Safety Behavior. Journal of Construction Engineering and Management, 143(01).

Huang, C and Wong, C K (2017) Discretized Cell Modeling for Optimal Facility Layout Plans of Unequal and Irregular Facilities. Journal of Construction Engineering and Management, 143(01).

Li, D and Lu, M (2017) Automated Generation of Work Breakdown Structure and Project Network Model for Earthworks Project Planning: A Flow Network-Based Optimization Approach. Journal of Construction Engineering and Management, 143(01).

Moussavi Nadoushani, Z S, Hammad, A W A and Akbarnezhad, A (2017) Location Optimization of Tower Crane and Allocation of Material Supply Points in a Construction Site Considering Operating and Rental Costs. Journal of Construction Engineering and Management, 143(01).

Patel, D A and Jha, K N (2017) Developing a Process to Evaluate Construction Project Safety Hazard Index Using the Possibility Approach in India. Journal of Construction Engineering and Management, 143(01).

RazaviAlavi, S and AbouRizk, S (2017) Genetic Algorithm–Simulation Framework for Decision Making in Construction Site Layout Planning. Journal of Construction Engineering and Management, 143(01).

Swei, O, Gregory, J and Kirchain, R (2017) Probabilistic Approach for Long-Run Price Projections: Case Study of Concrete and Asphalt. Journal of Construction Engineering and Management, 143(01).

Umer, W, Li, H, Szeto, G P Y and Wong, A Y L (2017) Identification of Biomechanical Risk Factors for the Development of Lower-Back Disorders during Manual Rebar Tying. Journal of Construction Engineering and Management, 143(01).

Zhang, S, Bogus, S M, Lippitt, C D and Migliaccio, G C (2017) Estimating Location-Adjustment Factors for Conceptual Cost Estimating Based on Nighttime Light Satellite Imagery. Journal of Construction Engineering and Management, 143(01).

  • Type: Journal Article
  • Keywords: Construction costs; Estimation; Remote sensing; Construction management; Pricing; Cost and schedule;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001216
  • Abstract:
    A fundamental process in construction cost estimation is the appropriate adjustment of costs to reflect project location. Unfortunately, location adjustment factors are not available for all locations. To overcome this lack of data, cost estimators in the United States often use adjustment factors from adjacent locations, referred to as the nearest neighbor (NN) method. However, these adjacent locations may not have similar economic conditions, which limit the accuracy of the NN method. This research proposes a new method of using nighttime light satellite imagery (NLSI) to estimate location adjustment factors where they do not exist. The NLSI method for estimating location adjustment factors was evaluated against an established cost index database, and results show that NLSI can be used to effectively estimate location adjustment factors. When compared with NN and other alternative proximity-based location adjustment methods, the proposed NLSI method leads to a 25–40% reduction of the median absolute error. This work contributes to the body of knowledge by introducing a more accurate method for estimating location adjustment factors which can improve cost estimates for construction projects where location adjustment factors do not currently exist.