The Critical Risk Factors that Influence Production-oriented Projects in the United Arab Emirates: A ‘Best-worst Method’ (BWM) Analysis

Khan, Sharfuddin Ahmed; Ojiako, Udechukwu; Marshall, Alasdair; Dalalah, Doraid; Ceylan, Serkan; Shabani, Naser Nader Ali; Sharqawi, Salama Imad Al

doi:10.1080/10429247.2022.2041963

Cited by 9 publications

(3 citation statements)

References 99 publications

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“…By paying attention to the fair treatment of technology, organization, and employees, project managers can motivate employees to actively participate in the project and improve their performance, which further promotes the realization of organizational justice. Khan et al used pairwise comparisons to evaluate the importance and ranking of factors under the three different backgrounds of technology, organization, and environment [95]. They found that if employees perceive that technical factors such as automation and cycle time are valued highly in projects, then they perform better.…”

Section: Fostering Organizational Justice and Ai's Role In Enhancing ...mentioning

confidence: 99%

The Impact of Artificial Intelligence on Organizational Justice and Project Performance: A Systematic Literature and Science Mapping Review

Zhang,

Antwi-Afari,

Zhang

et al. 2024

Buildings

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By adopting a systematic literature and science mapping review, this paper aims to explore the impact of artificial intelligence (AI) on organizational justice and project performance. A total of 47 bibliographic records from the Scopus database were analyzed. The results revealed the annual publication trends of research articles and relevant peer-reviewed journals in the studied domain. It was found that while AI technology has made significant progress in several fields, its application areas in project management and organizational justice are still relatively low. Moreover, it objectively discussed the co-occurrence analysis of keywords, co-authors, countries/regions, and documents in the fields, revealing the current research topics. The main research topics include the (1) AI’s influence on organizational justice, decision analysis, and digital transformation, (2) fostering organizational justice and AI’s role in enhancing project performance, and (3) improving organizational performance approaches. Furthermore, this paper proposed research gaps and future research directions, including (1) advancing business intelligence strategies, (2) unlocking AI technology potential on organizational justice and project performance, (3) the adaption of cultural, diversity, environmental, and social factors, (4) the impact of AI on complex and challenging leadership styles, and (5) developing a comprehensive understanding of the agile framework. The findings of this paper could contribute to a better understanding of how AI shapes project/construction management and organizational justice, providing practical solutions for innovative development for researchers and policymakers.

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Section: Fostering Organizational Justice and Ai's Role In Enhancing ...mentioning

confidence: 99%

The Impact of Artificial Intelligence on Organizational Justice and Project Performance: A Systematic Literature and Science Mapping Review

Zhang,

Antwi-Afari,

Zhang

et al. 2024

Buildings

View full text Add to dashboard Cite

show abstract

“…BWM excels in conducting a thorough comparison of criteria and alternatives, laying a solid foundation for determining optimal weights in scenarios characterized by ambiguity, known as grey environments [26]. This method has been effectively applied in various problem-solving contexts (e.g., Tavana et al [27], Khan et al [28], Görc ¸ün and Dogan [29]. In contrast, the COBRA method, as conceptualized by Krstić et al [30], is based on the principle of calculating comprehensive distances from a spectrum of solutions, integrating both Euclidean and taxicab distances.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluating Governance Models in Intermodal Terminal Operations: A Hybrid Grey MCDM Approach

Krstić,

Tadić,

Agnusdei

2023

JIMD

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Intermodal transportation, crucial for contemporary logistics, enhances supply chain efficiency through integrated multimodal coordination. Central to this ecosystem, intermodal terminals act as pivotal points for seamless mode transitions, significantly influencing cost reduction and environmental sustainability. This research delves into the complex dynamics of intermodal terminal governance, striving to discern the most effective models while establishing a robust evaluative framework. A meticulous examination of seven distinct governance models is conducted against nine criteria, encompassing aspects such as efficiency, cost-effectiveness, regulatory compliance, and socio-economic impact. Employing a novel hybrid Multiple Criteria Decision-Making (MCDM) model, which amalgamates the Best-Worst Method (BWM) and Comprehensive Distance-based Ranking (COBRA) within a grey analytical context, the study facilitates a nuanced, uncertainty-accommodating assessment. Findings highlight the Public-Private Partnership, Concession Agreement, and Cooperative Governance models as exemplary, underscoring the benefits of synergistic public-private cooperation and community engagement. The research contributes significantly by identifying key governance models, providing a comprehensive evaluation framework, and introducing the hybrid MCDM model as an instrumental tool for decision-making within the transportation sector. Structured into five sections, the analysis progresses from an extensive literature review to a detailed methodology of the hybrid model, followed by the presentation of evaluative results, a discussion on the broader implications, and a conclusion synthesizing the principal insights. This investigation offers vital contributions to academic discourse and practical decision-making, laying groundwork for future exploration in this vital field.

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“…Rezaei [24] introduced the MCDM technique known as the best worst method (BWM). The BWM approach has been applied by several researchers in a wide range of industries and fields [25]. It can be used to evaluate alternatives in light of the criteria and examine the applicability of the criteria that are applied when coming up with a solution to reach the main goal(s) of the problem.…”

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confidence: 99%

Two New Approaches (RAMS‐RATMI) in Multi‐Criteria Decision‐Making Tactics

Abdulaal

Bafail

2022

Journal of Mathematics

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When a decision must be made, a tool called multi-criteria decision-making (MCDM) is used to assess and select alternatives among numerous criteria. For a wide variety of complex problems, MCDM methods have demonstrated usefulness in finding the optimal solutions. Despite the abundance of MCDM methods available today, there has been slow progress in developing new methodologies in MCDM in the past decade. In this context, this paper presents new MCDM tools which ranks alternatives based on median similarity (RAMS) between optimal alternatives and other alternatives. RAMS is an extension to the most recently developed technique that used perimeter similarity (RAPS). This paper also introduces a further tool that combines the RAMS method with the multiple criteria ranking by alternative trace (MCRAT) methodology using a majority index and the concept of the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. This tool is ranking the alternatives based on the trace to median index (RATMI). An illustration of the use of RAMS and RATMI is given through a case study of ranking different materials for the selection of break booster valve body in a vehicle. The validity of the new two techniques was tested against seven well-known MCDM techniques (ARAS, SAW, TOPSIS, COPRAS, VIKOR, WASPAS, and MOORA) using fifteen real problems data taken from the literature. The RATMI technique was more promising than RAPS and RAMS for 87% and 93% of the fifteen difficulties, respectively, according to the results of the correlation coefficient tests between the developed techniques and the selected seven techniques.

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The Critical Risk Factors that Influence Production-oriented Projects in the United Arab Emirates: A ‘Best-worst Method’ (BWM) Analysis

Abstract: The critical risk factors that influence production-oriented projects in the United Arab Emirates: a 'best-worst method' (BWM) analysis

Cited by 9 publications

References 99 publications

The Impact of Artificial Intelligence on Organizational Justice and Project Performance: A Systematic Literature and Science Mapping Review

The Impact of Artificial Intelligence on Organizational Justice and Project Performance: A Systematic Literature and Science Mapping Review

Evaluating Governance Models in Intermodal Terminal Operations: A Hybrid Grey MCDM Approach

Two New Approaches (RAMS‐RATMI) in Multi‐Criteria Decision‐Making Tactics

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