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Initial preference algorithm of industrial project portfolio.

Authors :
Cihan, Ercan Emin
Alabaş-Uslu, Çiğdem
Kabak, Özgür
Source :
Kybernetes; 2023, Vol. 52 Issue 12, p6025-6048, 24p
Publication Year :
2023

Abstract

Purpose: This paper aims to develop an algorithm to pretest an industrial portfolio on a new scale. Portfolios include complex and uncertain projects at the front-end phase. The study, therefore, proposes a procedure that helps decision-makers to handle various complex projects and defines a common scale applicable to various kinds of industrial projects. Design/methodology/approach: Decision-makers can employ the preference algorithm to reach a common understanding. To this end, the current paper posits the organization of criteria in various project sets. A sexagesimal scale is developed based on project complexity and its ability to achieve broad impact, both these factors being gauged on a five-point scale of user-friendly numberings. Findings: The proposed algorithm shows the equivalence of industrial projects in different fields. Also, the algorithm articulates the status in terms of uncertainty, complexity, risk, and value of projects. The connections between decision-makers and criteria operate on the basis of the foreseen complexity, risk, and value. It can be said that this study exemplifies and visualizes the portfolio and criteria relationship. Research limitations/implications: The procedure covers contingency exercises at the front-end phase of a portfolio and supports decisions. However, updated information can change support positions. Originality/value: The paper presents original scoring guidance for portfolio complexity on a new scale. The scaling and scoring are adjustable and calibrated using the proposed sexagesimal system. It presents an original classification of project risk and value. The main contribution is the presented algorithm which can be used to pretest industrial portfolios composed of projects that vary in both size and context. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
ALGORITHMS
NUMBER systems

Details

Language :
English
ISSN :
0368492X
Volume :
52
Issue :
12
Database :
Complementary Index
Journal :
Kybernetes
Publication Type :
Periodical
Accession number :
173822867
Full Text :
https://doi.org/10.1108/K-04-2022-0644