Anas A. Makki

Background: The retail sector has experienced significant growth in recent years, necessitating efficient supply chain management and sustainable logistics practices. Evaluating the performance of retail warehouses is crucial for meeting customer expectations and enhancing operational efficiency. Methods: This study employed a combined multi-criteria decision-making (MCDM) approach, using the group best–worst method (G-BWM) for weighting criteria and ranking the alternatives based on the trace-to-median index (RATMI) for warehouse ranking. The performance criteria were cost, quality, time, productivity, and safety. Data were collected from four mega retail warehouses in the western region of Saudi Arabia for evaluation and analysis. Results: The evaluation of retail warehouse performance using the MCDM approach provided valuable insights for decision-makers and warehouse experts. The criteria weights were determined using the G-BWM, and the RATMI enabled the ranking of the warehouses based on their weighted performance scores. The results highlight the strengths and weaknesses of each warehouse, facilitating strategic planning, resource allocation, and operational improvements. Conclusions: This study presents a novel combined MCDM performance evaluation approach for retail warehouses. The study has implications for effective decision-making processes, resource allocation, and operational efficiency. Furthermore, it serves as a foundation for future research, exploring additional dimensions of warehouse performance and enabling sustainable logistics within the broader supply chain context.

Multi-criteria decision-making (MCDM) assists in making judgments on complex problems by evaluating several alternatives based on conflicting criteria. Several MCDM methods have been introduced. However, real-world problems often involve uncertain and ambiguous decision-maker inputs. Therefore, fuzzy MCDM methods have emerged to handle this problem using fuzzy logic. Most recently, the method based on the removal effects of criteria using the geometric mean (MEREC-G) and ranking the alternatives based on the trace to median index (RATMI) were introduced. However, to date, there is no fuzzy extension of the two novel methods. This study introduces a new hybrid fuzzy MCDM approach combining fuzzy MEREC-G and fuzzy RATMI. The fuzzy MEREC-G can accept linguistic input terms from multiple decision-makers and generates consistent fuzzy weights. The fuzzy RATMI can rank alternatives according to their fuzzy performance scores on each criterion. The study provides the algorithms of both fuzzy MEREC-G and fuzzy RATMI and demonstrates their application in adopted real-world problems. Correlation and scenario analyses were performed to check the new approach’s validity and sensitivity. The new approach demonstrates high accuracy and consistency and is sufficiently sensitive to changes in the criteria weights, yet not too sensitive to produce inconsistent rankings.

Universities worldwide strive to achieve excellence in research, learning, teaching, and community services, which are the pillars of their strategic plans. However, satisfying international ranking criteria might not directly result in achieving their strategic objectives. This paper proposes a new approach to rank university colleges by evaluating their educational quality. Standard sets of criteria from multiple international university ranking systems and a university’s strategic plan’s Balanced Scorecard perspectives were cross-mapped for the evaluation. A new multi-criteria decision-making-based framework was applied to six colleges of a non-profit university in the Middle East. It revealed their performance rankings and contributions to the university’s educational quality objectives. This paper offers a novel approach for universities to develop strategies that satisfy multiple international ranking systems while achieving their strategic goals concurrently and as per their priorities. Implications include informing university leaders on the most contributing colleges and assisting in pinpointing quality shortcomings and their causes. This helps universities design better performance indicators and allocate resources to achieve educational excellence. This paper puts forward a new approach for universities to unify their efforts in satisfying the requirements of multiple international ranking systems while achieving their strategic goals.

The COVID-19 pandemic has impacted the financial performance of companies in different sectors. One of the most important sectors affected is the energy sector. Therefore, this research study aims to conduct a financial performance evaluation of companies in the Saudi energy sector in 2019, 2020, and 2021. This is to capture and analyze the effect on companies before, during, and post the COVID-19 pandemic, respectively. A hybrid multicriteria decision-making (MCDM) approach is followed to achieve the objective. The financial performance evaluation of energy companies is based on four financial dimensions and 11 performance indicators. Results revealed that energy companies’ efficiency and profitability were relatively the most important dimensions, followed by leverage and liquidity. Furthermore, results revealed the relative importance of the indicators from the most to the least important. Results also revealed the effect of COVID-19 on energy companies’ financial performance, demonstrating the change over the three years. Implications include providing insights for energy companies on the financial dimensions and indicators to be maintained and monitored in the case of pandemics. Furthermore, to assist decision-makers in the energy sector in developing strategies to mitigate financial performance disparities during and post-pandemics.