Evaluation of logistics centers in terms of sustainability via MCDM methods

KELEŞ, Nuh; Pekkaya, Mehmet

doi:10.1108/jamr-04-2022-0087

Cited by 11 publications

(5 citation statements)

References 22 publications

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“…Conversely, centers like Turkoglu/Kahramanmaras and Gokkoy/Balikesir demonstrated inefficiencies akin to previous studies [40,41], highlighting the imperative to rectify input redundancies for enhanced performance. On the other hand, the study emphasized Kayacik/Konya LC exhibited similar input redundancies, yet it was identified as a potential successful center in a study conducted by [42]. This evaluation took place before the center commenced operations, focusing solely on its sustainability potential.…”

Section: Discussionmentioning

confidence: 99%

“…The study revealed excess input factors in inefficient LCs and observed low cargo volume in these LCs. Assessing the performance rankings of LCs based on their potential efficiencies was conducted by Dumlu and Wolff [41] using the MOORA (Multi-objective Optimization by Ratio Analysis) method and by Keleş and Pekkaya [42] using the PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation)-CRITIC (Criteria Importance Through Inter-criteria Correlation) approach.…”

Section: Literature Reviewmentioning

confidence: 99%

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Evaluating the Efficiencies of Logistics Centers with Fuzzy Logic: The Case of Turkey

Karabacak,

Kutlu

2024

Sustainability

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The primary actor in today’s economic life, forming the backbone of the production-consumption cycle, is the distribution activities. Logistics centers (LCs) are organized areas where these activities are carried out together. Therefore, the efficiency and effectiveness of distribution activities are crucial for sustainability. This study incorporates fuzzy logic theory into the framework of data envelopment analysis (DEA) to measure the efficiency of LCs. Classical DEA assumes input and output data are precisely measured, making the efficiency scores unreliable and inconsistent when data precision is not always possible. The adoption of fuzzy logic is primarily to overcome possible uncertainties, errors, and ambiguities in data acquisition, preventing incorrect results. Hence, an approach assumes the data lie within specific intervals, was adopted to calculate the efficiencies of LCs based on α-cut levels. Officially obtained data on nine input and one output variable from twelve LCs operating in Turkey were used to calculate efficiency scores. As a result of the study, Köseköy/Izmit, Halkali/Istanbul, and Yenice/Mersin LCs were found to be fully efficient considering both lower and upper bound efficiencies. Moreover, the efficiency calculations using Fuzzy-DEA allowed for a more precise evaluation of LCs with high data sensitivity.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Evaluating the Efficiencies of Logistics Centers with Fuzzy Logic: The Case of Turkey

Karabacak,

Kutlu

2024

Sustainability

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“…The input parameter and assumption sensitivity can be limited in the study. Sustainability considerations were researched before deciding on a location for a logistics center [41]. The authors suggested improving decision-making using an ordered weighted average (OWA) operator and a similarity based TOPSIS technique.…”

Section: Geographic Informationmentioning

confidence: 99%

Optimizing Logistics and Transportation Locations in the China–Pakistan Economic Corridor: A Strategic Risk Assessment

Ilyas,

Jin,

Ullah

2024

Applied Sciences

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Logistics centers (LCs) have become a critical component of supply chain networks, playing an essential role in the development and implementation of logistics and supply chain management strategies. Recognizing the importance of LCs, Pakistan and China have initiated an extensive plan to establish and expand an LC system as part of the China–Pakistan Economic Corridor (CPEC) initiative. However, the implementation of this plan has faced challenges due to the inadequate prioritization of factors used to identify LCs. This research proposes a structured framework for selecting LC locations, employing a combination of fuzzy logic and the technique for order of preference by similarity to the ideal solution (TOPSIS). These widely used methods address various challenges encountered in location selection. The findings highlight crucial logistics hubs in China and Pakistan, emphasizing factors such as port accessibility, freight demand, and transportation costs. The prioritization of criteria for LC selection is determined through the evaluation of variables and alternatives. The proposed framework enhances decision-making based on multiple criteria by addressing uncertainty and subjective assessments.

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“…The study suggested using renewable energy to improve the sustainability of the targeted plants. Keles ¸and Pekkaya (2023) prioritize the sustainable performance of 12 Turkish logistical centers. CRITIC was employed in the study to provide weightage to the 12 sustainability criteria.…”

Section: Prioritizing the Attributesmentioning

confidence: 99%

“…Keleş and Pekkaya (2023) prioritize the sustainable performance of 12 Turkish logistical centers. CRITIC was employed in the study to provide weightage to the 12 sustainability criteria.…”

Section: Literature Reviewmentioning

confidence: 99%

Prioritizing the attributes of sustainable banking performance

Sharma,

Kumar

2023

IJPPM

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PurposeGrowing concern over sustainability adoption has presented an array of challenges to businesses. While vital to an economy's success, banking is not immune to societal, environmental and economic consequences of business practices. The study has examined the sustainable performance of banking institutions on the suggested multidimensional framework comprising economic, environmental, social, governance and financial dimensions and 52 sustainability indicators. The study benchmarks the significant performance indicators of leading banks indispensable to sustainable banking performance. The findings attempt to address research questions concerning the extent of sustainable banking performance, ranking the sustainability dimensions and indicators and standardizing sustainability adoption metrics.Design/methodology/approachTo determine the responsiveness of the banking industry to sustainability dimensions, content analysis was conducted using NVivo software for the year 2021–2022. Furthermore, a hybrid multicriteria decision-making (MCDM) approach is used by integrating entropy, the technique for order preference by similarity to ideal solution (TOPSIS) and VlseKriterijumska Optimizacija KOmpromisno Resenje (VIKOR) to provide relative weights to performance indicators and prioritize banks based on their sustainable performance. Sensitivity analysis is used to ensure the robustness of results.FindingsIn the context of the Indian banking industry, the pattern of sustainability reporting is inconsistent and concentrated on addressing environmental and social concerns. The results of the entropy methodology prioritized “Environmental” sustainability over other selected dimensions while “Financial” dimension has been assigned the least priority in the ranking order. The significant sustainable performance indicators delineated in this study should be used as standards to ensure the accountability and credibility of the sustainable banking industry. Additionally, the research findings will provide valuable inputs to policymakers and regulators to assure better contribution of the banking sector in meeting sustainability goals.Originality/valueConsidering the paucity of studies on sustainable banking performance, this study makes two significant contributions to the literature. First, the suggested multidimensional disclosure model integrating financial and nonfinancial indicators would facilitate banking institutions in addressing the five aspects of sustainability. As one of the first studies in the context of the Indian banking industry, the findings would pave the way for better diffusion of sustainability practices. Second, the inclusion of MCDM techniques prioritizes the significance of sustainability indicators and benchmarks the performance of leading banks to achieve better profits and more substantial growth.

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Evaluation of logistics centers in terms of sustainability via MCDM methods

Cited by 11 publications

References 22 publications

Evaluating the Efficiencies of Logistics Centers with Fuzzy Logic: The Case of Turkey

Evaluating the Efficiencies of Logistics Centers with Fuzzy Logic: The Case of Turkey

Optimizing Logistics and Transportation Locations in the China–Pakistan Economic Corridor: A Strategic Risk Assessment

Prioritizing the attributes of sustainable banking performance

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