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Ahn, S and Lee, S (2015) Methodology for Creating Empirically Supported Agent-Based Simulation with Survey Data for Studying Group Behavior of Construction Workers. Journal of Construction Engineering and Management, 141(01).
Arroyo, P, Tommelein, I D and Ballard, G (2015) Comparing AHP and CBA as Decision Methods to Resolve the Choosing Problem in Detailed Design. Journal of Construction Engineering and Management, 141(01).
Borg, L and Song, H (2015) Quality Change and Implications for Productivity Development: Housing Construction in Sweden 1990–2010. Journal of Construction Engineering and Management, 141(01).
Caldas, C H, Kim, J, Haas, C T, Goodrum, P M and Zhang, D (2015) Method to Assess the Level of Implementation of Productivity Practices on Industrial Projects. Journal of Construction Engineering and Management, 141(01).
Castillo, G, Alarcón, L F and González, V A (2015) Implementing Lean Production in Copper Mining Development Projects: Case Study. Journal of Construction Engineering and Management, 141(01).
Goh, Y M (2015) Empirical Investigation of the Average Deployment Force of Personal Fall-Arrest Energy Absorbers. Journal of Construction Engineering and Management, 141(01).
Ha, S K, Jang, J G, Park, S H and Lee, H K (2015) Advanced Spray Multiple Layup Process for Quality Control of Sprayed FRP Composites Used to Retrofit Concrete Structures. Journal of Construction Engineering and Management, 141(01).
Hu, H and Zhu, Y (2015) Social Welfare–Based Concession Model for Build/Operate/Transfer Contracts. Journal of Construction Engineering and Management, 141(01).
Inayat, A, Melhem, H and Esmaeily, A (2015) Critical Success Factors in an Agency Construction Management Environment. Journal of Construction Engineering and Management, 141(01).
Matthews, J C and Stowe, R (2015) Critical Data Needs Associated with Asbestos Cement Pipe Renewal Methods. Journal of Construction Engineering and Management, 141(01).
Patel, D A and Jha, K N (2015) Neural Network Model for the Prediction of Safe Work Behavior in Construction Projects. Journal of Construction Engineering and Management, 141(01).
Roofigari-Esfahan, N, Paez, A and N.Razavi, S (2015) Location-Aware Scheduling and Control of Linear Projects: Introducing Space-Time Float Prisms. Journal of Construction Engineering and Management, 141(01).
Younes, B, Bouferguène, A, Al-Hussein, M and Yu, H (2015) Overdue Invoice Management: Markov Chain Approach. Journal of Construction Engineering and Management, 141(01).
- Type: Journal Article
- Keywords: Invoice lead time; Markov modeling; Probabilistic sensitivity analysis; Invoice processing improvement; Quantitative methods;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000913
- Abstract:
The gross domestic product (GDP) of the Canadian construction industry in 2012 amounted to $111 billion, all having been exchanged in the form of invoices. In fact, a typical construction company processes tens of thousands of invoices for payment annually. There are two significant challenges associated with this invoice processing: (1) process costs due to remuneration of the construction owner’s highly paid personnel, and (2) the cost of delayed invoice payments, which is typically a cost absorbed by the contractor that is consequently added to the overall project cost. Ensuring on-time payment of invoices, even when funds are available, can be a challenging exercise because of variety, volume, and the unpredictable number of received invoices. These realities make overdue invoices a pressing problem to be addressed, which in the long term leads to loss in profit and damaged reputation for both contractors and owners. The research presented in this paper utilizes a cohort Markov model to evaluate invoice processing. It seeks to identify and rank bottlenecks to highlight and prioritize opportunities for process improvement, thereby leading to a null-overdue invoice-processing approach. Furthermore, given the stochastic nature of invoice processing, various probabilistic sensitivity analyses are proposed, including an empirical approach that can be used at the experimental design stage where data are either limited or unavailable.