Methods of Improvement Project Selection: A Literature Survey

Kucińska-Landwójtowicz, Aneta; Czabak-Górska, Izabela D.; Rudnik, Katarzyna

doi:10.1016/j.ifacol.2021.08.015

Cited by 3 publications

(1 citation statement)

References 29 publications

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“…The paper continues with the presentation of the mixed methodology used based on statistical analysis and multicriteria decision-making methods. In the field of project management, multi-criteria decision-making methods have already been used mainly in project selectionan extensive literature survey can be found in, e.g., [19], in the context of product and service development projects [20], in evaluating the outcomes of projects [21], and in project evaluationan extensive literature survey can be found in [22]. The exploratory factor analysis based on the extensive survey on AI in Slovenian companies along with the multicriteria measurement with an emphasis on value functions and pairwise comparisons in the analytic hierarchy process, was employed.…”

Section: Introductionmentioning

confidence: 99%

Multi-Criteria Measurement of AI Support to Project Management

Čančer,

Tominc,

Rožman

2023

IEEE Access

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This paper aims to measure the level of artificial intelligence (AI) support to project management (PM) in selected service sector activities. The exploratory factor analysis based on the extensive survey on AI in Slovenian companies along with the multi-criteria measurement with an emphasis on value functions and pairwise comparisons in the analytic hierarchy process, was employed. The synthesis and performance sensitivity analysis results show that in the service sector concerning all criteria, PM is with the level 0.276 best supported with AI in services of professional, scientific, and technical activities, which also stand out concerning the first-level goals, in using AI solutions in a project with the value 0.284, and in successful project implementation using AI with the value 0.301. Although the lowest level of AI support to PM, which is 0.220, is in services of wholesale and retail trade, and repair of motor vehicles and motorcycles, these services excel in adopting AI technologies in a project with a value of 0.277. Services of financial and insurance activities, with the level 0.257 second-ranked concerning all criteria have the highest value of 0.269 concerning the first-level goal of improving the work of project leaders using AI. The paper therefore contributes to the comparisons of AI support to PM in service sector activities. The results obtained can help AI development policy makers, which activities need to be supported and which ones should be set as an example. The presented methodological frame can serve to perform measurements and benchmarking in various research fields.

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Section: Introductionmentioning

confidence: 99%

Multi-Criteria Measurement of AI Support to Project Management

Čančer,

Tominc,

Rožman

2023

IEEE Access

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The Optimization of Long-Term Dynamic Defense Industry Project Portfolio Management with a Mixed and Holistic Project Prioritization Approach

Dağıstanlı,

Altundaş,

Kurtay

et al. 2024

Dyn Games Appl

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Sustainable Well Segment Operational Service Strategy through Standard Work Instruction Design Analysis

Christhia,

Khair,

Pratama

et al. 2023

E3S Web Conf.

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The maintenance and productivity of oil and gas wells heavily rely on well service, which is provided by various departments including Laboratory and Maintenance. Although existing work procedures are in place, operational effectiveness and quality are often inadequate, leading to errors, unstructured tasks, downtime, and safety hazards. In order to improve the quality of well service, a set of standardized work procedures based on DMAIC principles is proposed. This paper presents findings from field observations, performance index analysis, and HSE statistics. By implementing redesigned Standard Work Instructions, a reliable mitigation measure is found to be achievable, as evidenced by House of Risk data. The results suggest that a sustainable and effective operational service strategy for well segments can be established through a carefully designed set of Standard Work Instructions.

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Methods of Improvement Project Selection: A Literature Survey

Cited by 3 publications

References 29 publications

Multi-Criteria Measurement of AI Support to Project Management

Multi-Criteria Measurement of AI Support to Project Management

The Optimization of Long-Term Dynamic Defense Industry Project Portfolio Management with a Mixed and Holistic Project Prioritization Approach

Sustainable Well Segment Operational Service Strategy through Standard Work Instruction Design Analysis

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