Environmental, social, and governance risks and environmentally sensitive competitive strategies: A case study of a multinational logistics company

Abstract

Global climate change continues to have a negative impact on many sectors, particularly supply chains and logistics. Companies are progressively incorporating environmentally friendly practices into their strategies to tackle this global problem. Accordingly, the increase in environmental, social, and governance (ESG) risks has increased the importance of sustainable corporate governance. As a result, companies tend to place more emphasis on ESG initiatives. The study aims to analyze the importance levels of ESG criteria and to select the most ideal environmentally sensitive competitive strategy for multinational logistics companies. For this purpose, a set of criteria and alternatives for the businesses in the context of the related problem was defined, and a decision model was proposed to handle problems, which include uncertain information. In this context, q‐rung orthopair fuzzy (q‐ROF) weighted average technique was used for weighting the criteria and q‐ROF‐evaluation based on distance from average solution (q‐ROF‐EDAS) method was utilized for prioritizing the strategies. As a result, “greenhouse gas emissions” was identified as the most important criterion, while “eco‐efficiency” was selected as the best option for environmentally conscious competitive strategies.

How can organizations measure the integration of environmental, social, and governance (ESG) criteria? Validation of an instrument using item response theory to capture workers' perception

“…That said, assessing future oriented ESG criteria, such as climate change resilience or long-term social impact, presents additional challenges (Gündo gdu et al, 2023). These criteria require predictive models, scenario analysis, and assumptions about future developments, which introduce uncertainties into the measurement process.…”

A Novel Interval-Valued-q-Rung Orthopair Fuzzy-Additive Ratio Assessment Model for Evaluating Logistics Service Quality

“…The information obtained from the experts is generally ambiguous and imprecise. In such cases, decision-makers are advised to express their opinions using a subset of the closed interval [0, 1] [42], [44], [51]. In this study, IV-q-ROFS, an extension of q-ROFS, is preferred to efficiently express the uncertainties in the problem.…”

“…In this context, firstly, the results of criterion weight modifications will be examined. To investigate the consequences of changes in criterion weights, an approach in which each criterion takes the weight values of other criteria was adopted [51]. As a result, S1-S29 scenarios were produced.…”

“…A decision can be reached by assessing the data's processability and its implications on the solution while q = 1 q = 2 q = 3 q = 4 q = 5 q = 6 q = 7 q = 8 q = 9 q = 1 0 q = 2 0 q = 5 0 q = 6 0 q = 6 7 q = 1 0 0 Weight Coefficients accounting for various q values. In general, it is assumed that 𝑞 ≥ 3 is adequate to eliminate the different issues observed with 𝑞 = 1 and 𝑞 = 2 [42], [44], [51]. According to this framework, the solutions obtained for the studied problem are reliable and valid.…”

Does sustainability reporting affect firm performance? Evidence from the port sector

“…Because of this, they discovered that e-commerce customers placed the highest value on ESG activities in the following order: distribution in the social sector, partnership in the governance sector, operation of the distribution center in the social sector, packaging in the environmental sector, operation of the distribution center in the environmental sector, purchasing in the social sector, and distribution in the environmental sector. Additionally, Gündoğdu et al (2023) outlined a set of criteria and options for businesses, and a decision model was suggested to deal with challenges that involve ambiguous information. In this situation, the criteria were weighted using a fuzzy weighted average methodology, and the strategies were prioritized using an assessment based on distance from the average solution method.…”