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Volume 2, Issue 3, 2024
Open Access
Research article
Addressing the Crucial Factors Affecting the Implementation of Carbon Credit Concept Using a Comprehensive Decision-Making Analysis: A Case Study
qian su ,
yanjun qiu ,
mouhamed bayane bouraima ,
babatounde ifred paterne zonon ,
ibrahim badi ,
ndiema kevin maraka
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Available online: 09-24-2024

Abstract

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As global focus on climate change intensifies, carbon credits have become an important tool for reducing greenhouse gas emissions. Africa, with its abundant natural resources and potential for sustainable development, is well-positioned to capitalize on this growing market. This article explores how Africa can enhance its participation in the carbon credit market, transforming environmental initiatives into economic opportunities by addressing key implementation challenges. By utilizing the Stepwise Weight Assessment Ratio Analysis (SWARA) method within an interval-valued spherical fuzzy (IVSF) framework, the study supports collective decision-making. It identifies three crucial factors: access to financing issue, the absence of clear policies and legal frameworks, and the lack of capacity and expertise within governments, businesses, and communities. The research provides practical recommendations for governments aiming to effectively implement the carbon credit concept.

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This paper investigates the search for an exact analytic solution to a temporal first-order differential equation that represents the number of customers in a non-stationary or time-varying $M / D / 1$ queueing system. Currently, the only known solution to this problem is through simulation. However, a study proposes a constant ratio, $\beta$ (Ismail's ratio), that relates the time-dependent mean arrival and mean service rates, offering an exact analytical solution. The stability dynamics of the time-varying $M / D / 1$ queueing system are then examined numerically in relation to time, $\beta$, and the queueing parameters. On another note, many potential queueing-theoretic applications to traffic management optimization are provided. The paper concludes with a summary, combined with open problems and future research pathways.

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When the word "disaster" is used, it usually refers to both human-caused situations that have a negative impact on the community and its environment as well as natural disasters like hurricanes, earthquakes, floods, and similar phenomena. Good logistics management is crucial to reducing the bad effects of these kinds of circumstances. This typically entails tasks like planning, organizing, acquiring, moving, and other associated duties. The distribution of supplies to impacted individuals in an effort to save lives is the main objective of humanitarian logistics. The location of humanitarian goods and equipment, which are kept in makeshift humanitarian logistics centers, is crucial for ensuring prompt response in such circumstances. As a result, when deciding where to locate these centers, it is crucial to take into account particular local factors. Numerous factors might impact this kind of selection, which is why finding a location for a humanitarian logistics center is considered a multi-criteria challenge. This research suggests using the ADAM (Axial-Distance-Based Aggregated Measurement Method) and SWARA (Stepwise Weight Assessment Ratio Analysis) techniques to solve this kind of issue. An example of their application is provided by a case study that centers on where Serbia's humanitarian logistics hub is located. The creation of a framework and a special set of standards for choosing the locations of humanitarian logistics centers are the main results of this study. This can help decision-makers, authorities, individuals, non-governmental groups, and logistical service providers make well-informed decisions that have the potential to save countless lives.

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The Logistics Performance Index (LPI) represents a tool developed by the World Bank that is used to measure the efficiency and effectiveness of a country’s logistics sector, and comprises of six components. This indicator is used to compare the logistics performance of different countries, identify challenges in global supply chains, and help policymakers improve their logistics infrastructure and service quality. Given the importance of this indicator, every country aims to achieve a higher LPI score and, consequently, a more favorable ranking. The objective of this paper is to propose a new methodology for calculating the LPI score for transport routes. To validate the proposed methodology, the study analyzes seven cases involving import and export flows from Serbia. Based on the results, the analysis identifies which transport routes achieve the highest scores and which require specific preventive and corrective actions to improve their performance.
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