Evaluation of project management knowledge areas using grey incidence model and AHP

Abstract

Project success (and failure) leads to the success (and failures) of business/organizational strategies thus projects are becoming integral part of organizations operating in today's competitive environment (see, Serra, 2017; PMI, 2013). Today, project management is being applied in diverse range of professions and industries that includes both manufacturing and service sectors (Kerzner, 2009). Moreover, a competent and knowledgeable project manager is vital to project success (Hwang & Ng, 2013; PMI, 2013) and in a world where project failure rate is too high to ignore (Serra, 2017) understanding the mind and preferences of this extremely important individual becomes necessity. Project Management Institute (USA) distributes the project management knowledge into ten interlinked areas (PMI, 2013). The completeness or incompleteness of the number of these project management knowledge areas (PMKAs) can be debatable nevertheless the importance of these knowledge areas for project success is established across the board. The ten PMKAs are i. Project Integration Management (PIM) ii. Project Scope Management (PSM) iii. Project Time Management (PTM) iv. Project Cost Management (PCoM) v. Project Quality Management (PQM) vi. Project Human Resource Management (PHRM) vii. Project Communications Management (PCmM) viii. Project Risk Management (PRM) ix. Project Procurement Management (PPM) x. Project Stakeholder Management (PSHM) The current study views a project as a grey system and intends to evaluate the project management knowledge areas (PMKAs) in manufacturing and service industries by establishing relationships between the ten PMKAs and, then, prioritizing them, using the absolute degree grey incidence analysis (ADGIA) model and analytic hierarchy process (AHP). In this way, the study is pioneer in its evaluation of ten PMKAs. Data was collected, from thirty-two project management-related professionals, in Lahore, Pakistan. Since the sample size was small so application of the grey system theory was considered appropriate because, unlike statistical methods, the grey systems concepts (including GIA) work fine with small data samples as well. Absolute degree of grey incidence was calculated using the method proposed in Liu et al. (2016). To solve the problem using AHP, the simplest way adopted by Taha (2014) was followed. Literature suggests that complexity, risk, uncertainty and unpredictability are key attributes associated with a project, project environment and project management process. These are the attributes that distinguish a temporary organizational setup (project) from the permanent organizational setups (companies and firms) thus the application of grey system theory in project management discipline can be considered an appropriate initiative with huge scope of applicability within this discipline. The results reveal that Project Quality Management, the most important knowledge area, is most strongly related to Project Communication Management, and least strongly related to Project Integration Management. In manufacturing industry, Quality, Time and Scope related knowledge areas turned out to be the most important PMKAs and in the service sector, the knowledge areas associated with Cost, Quality and Communication are considered most important.

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