Using project demand profiling to improve the effectiveness and efficiency of infrastructure projects

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Abstract


Purpose
The purpose of this paper is to explore the applicability and utility of supply chain (SC) segmentation through demand profiling to improve the effectiveness and efficiency of infrastructure projects by identifying different types of project demand profiles.

Design/methodology/approach
A three-stage abductive research design was adopted. Stage 1 explored the applicability of SC segmentation, through demand profiling, to the portfolio of infrastructure projects in a utility company. Stage 2 was an iterative process of “theory matching”, to the portfolio, programme and project management literature. In stage 3, theoretical saturation was reached and “theory suggestions” were made through four propositions.

Findings
Four propositions outline how SC segmentation through project demand profiling could improve the effectiveness and efficiency of infrastructure projects. P1: the ability to recognise the different demand profiles of individual projects, and groups thereof, is a portfolio management necessity. P2: projects that contribute to the strategic upgrade of a capital asset should be considered a potential programme of inter-related repeatable projects whose delivery would benefit from economies of repetition. P3: the greater the ability to identify different demand profiles of individual/groups of projects, the greater the delivery efficiency. P4: economies of repetition developed through efficient delivery of programmes of repeatable projects can foster greater efficiency in the delivery of innovative projects through economies of recombination.

Originality/value
This work fills a gap in the portfolio management literature, suggesting that the initial screening, selection and prioritisation of project proposals should be expanded to recognise not only the project type, but also each project’s demand profile.

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Original languageEnglish
Pages (from-to)1422-1442
Number of pages21
JournalInternational Journal of Operations and Production Management
Volume38
Issue number6
DOIs
Publication statusPublished - 4 Jun 2018

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© Emerald Publishing Limited 2018 Published by Emerald Publishing Limited Licensed re-use rights only

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