Прегледај по Аутор "Qiu, Yanjun"

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    A Decision-Making Model for Prioritizing Low-Carbon Policies in Climate Change Mitigation
    (Librello Publishing House, 2024) Qiu, Yanjun; Bouraima, Mouhamed Bayane; Badi, Ibrahim; Stević, Željko; Simic, Vladimir
    Climate change (CC) represents a paramount environmental challenge, necessitating the deployment of sustainable, low-carbon strategies particularly in developing regions such as Africa. This study introduces a novel decision-making framework aimed at enhancing the prioritization of policies to combat the adverse effects of CC. The proposed two-stage model employs the integration of Step-Wise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregated Sum Product Assessment (WASPAS) under spherical fuzzy (SF) conditions to address the strategic sequencing of sustainable policies. Initially, SF-SWARA is utilized to ascertain the relative significance of diverse criteria. Subsequently, the SF-WASPAS method ranks these policies, facilitating informed decision-making. The primary obstacles identified include limited institutional capacity, insufficient financial resources, and technological constraints, for which strategic alternatives are proposed. Moreover, rigorous sensitivity and comparative analyses affirm the model's applicability. By systematically delineating and prioritizing necessary policies, this study contributes significantly to the scholarly discourse on climate mitigation (CM) in an African context.
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    ASSESSING THE PERFORMANCE OF SUB-SAHARAN AFRICAN (SSA) RAILWAYS BASED ON AN INTEGRATED ENTROPY-MARCOS APPROACH
    (2021) Bouraima, Mouhamed Bayane; Stević, Željko; Tanackov, Ilija; Qiu, Yanjun
    In this study, the performance of Sub-Saharan African railways systems (SSA) is assessed by using an integrated Entropy-MARCOS (Measurement Alternatives and Ranking according to COmpromise Solution) - based methodology. In the first phase, the Entropy method is employed to determine the weights of each sub-criterion of the decision model. This process identifies six main criteria, i.e., safety, security, internal business aspect, intermodal aspect, innovation, and learning aspect, and customer satisfaction which are further supplemented by 13 sub-criteria. In the second phase, the MARCOS method is used to rank the countries based on their railway performance assessment. Based on the results from the proposed method, a sensitivity analysis was carried out through a comparative analysis with seven other multicriteria decision-making (MCDM) methods. The results of the study indicate that the most weighted sub-criterion is the labor productivity (internal business perspective criteria) followed by the terrorist incidence (security criteria) and the number of employees going through training/exposure sessions (innovation and learning perspective criteria). Moreover, it was revealed that Kenya is the best alternative in terms of its railway performance followed by Ethiopia, Cameroon, Nigeria, and Ghana. Based on the findings from this study, decision-makers can be assisted during the operative, designing, and planning investigations of the railway system through the consideration of these parameters as insert indicators. Also, the findings can help as a benchmark for the performance analysis of other railway systems in other African countries
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    Assessment of Causes of Delays in the Road Construction Projects in the Benin Republic Using Fuzzy PIPRECIA Method
    (Hindawi, 2022) Stević, Željko; Bayane Bouraima, Mouhamed; Subotić, Marko; Qiu, Yanjun; Antwi Buah, Peter; Maraka Ndiema, Kevin; Magloire Ndjegwes, Christian
    Purpose. The purpose of this study is to examine the causes of delays in road construction projects in the Benin Republic from the consultant, client, and contractor perspectives. Design/Methodology/Approach. Through construction project reports, 20 factors that could cause delays in road construction projects were identified. The factors were arranged into a questionnaire, which was distributed to three separate experts. The fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Relevance Assessment) method was used to calculate the independent importance of each delay factor. The Spearman and Pearson correlation coefficients were used to test the method’s consistency. Findings. The top five road construction project delays in the Benin Republic, according to the analysis of the 20 factors considered, are project funding, slowness during the client-endorsed payment process, scarcity of professional personnel, delay in indemnifying reimbursement (land-owners), and price escalation. This shows that of the various types of delays, the financial delay group is the most crucial. Originality/value. This study evaluates the causes of delays in road construction projects in the Benin Republic for the first time in literature. This study also examined the top 5 delay factors in road construction projects. This study is based on reports from road construction projects and a performed questionnaire survey. Based on the findings, measures have been formulated to aid project managers to alleviate the road construction delays in the Benin Republic. In addition, this study is practical for both scholars and road construction parties and provides a complete and verifiable analysis of the progress of a road construction project to make it easier and attain a competitive level of time, cost, and quality for successful road construction.