NormNormalization is an essential step in data analysis and for MCDM methods. This study aims to outline the positive and negative features of the normalization techniques that can be used in MCDM problems. In order to compare the different normalization techniques, fourteen sets representing different scenarios of decision problems were used. According to the results, if the decision-maker chooses to take the alternative with the highest value in the criteria and avoid the one with the lowest value, or vice versa, optimization-based normalization techniques should be preferred, whereas the reference-based normalization techniques are considered appropriate for situations where there are ideal values determined by the decision-maker for each criterion. However, if the decision-maker believes that the values in the criteria do not represent the monotonous increasing or decreasing benefit/cost, then non-linear normalization techniques should be used. Also, in the event of a change in the conditions mentioned above, the decision maker may opt for mixed normalization techniques. However, some data structures, such as the presence of zero, and negative values in the decision matrix, can prevent the use of some normalization techniques. The choice of the normalization technique may also be affected by the problem of rank reversal, the range of normalized values, obtaining the same optimization aspect for all criteria, and the validity of results.

Integrating green approaches and digital marketing strategies for Information and Communication Technologies (ICTs), which reduce environmental risks to desired levels by eliminating emissions and pollution, is considered one of the most promising solutions for logistics companies. The study strives to bring a practical and applicable solution to the decision problem involving the selection of indicators for green approaches and digital marketing strategies for ICTs in the logistics sector. An integrated Fermatean Fuzzy Step-wise Weight Assessment Ratio Analysis (FF–SWARA) and Fermatean Fuzzy Complex Proportional Assessment (FF–COPRAS) methodology is applied to evaluate green approaches and digital marketing strategies. Concerning the findings, the foremost criterion is “data management,” whereas the best strategy is “programmatic advertising.” To the best of the authors’ knowledge, there is no other study that both offers a strategy selection for the logistics industry and considers environmental protection, sustainability, digital transformation, energy costs, and social and economic factors. The study is a part of ongoing research on productivity, sustainability, the environment, digitization, recycling and estimating levels of waste reduction, as well as business practices, competitiveness and ensuring employee satisfaction and resource efficiency. Also, it investigates the similarities and dissimilarities in the green approach practices of business in logistics and determines the extent to which these practices could be reflected. It is expected to ensure a roadmap for green approach practices and to support sustainable and ecological awareness efforts for ICTs in the logistics sector. Logistics companies can select an integrated digital strategy based on green informatics that suits them using the decision model employed in this study, which can handle uncertainties effectively. In this regard, the study’s findings, which focus on reaching customers and the most precise target audience in digital applications for businesses, are critical for developing strategy, plan and process.

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.

Purpose: Nowadays, companies have required new alternatives and strategies to handle environmental sustainability difficulties, primarily as ecological and social awareness has grown. In this context, the aim is to determine the green transportation indicators in companies with corporate identity and logistics activities at the international level in Giresun, Ordu, Gümüshane, Artvin, Rize, and Trabzon in the Eastern Black Sea Region in Turkey. At the same time, the study contributes to providing an effective and applicable solution to decision-making problems involving the assessment of green transportation indicators and smart network strategies in the logistics sector, which is a critical sector for countries. The purpose of this paper is to address these issues.Design/methodology/approach: This study aims to propose a model for the selection of smart network strategy and to determine the criteria weights used in green transportation indicators, and establish an ideal smart network strategy. In achieving the outlined goals of the study, the authors believe that the model proposed in the study will draw the focus to green logistics which will aid the environmental, economic and social efforts of businesses and governments through the provision of efficient use of scarce resources, which will, in turn, ensure that we leave a sustainable environment for future generations and businesses enjoy a competitive advantage. At the same time, different smart network strategies and green transportation indicators in companies show the success rate of social, economic and environmental indicators in green logistics practices. In addition to providing innovative, reliable and sustainable transportation systems, smart network strategies are critical for businesses to create cost advantages. Through the green transportation indicators and smart network strategies selection model outlined in this study, it is clear that the contribution will not only be limited to businesses, as the society and governments will also benefit from the important indicators on sustainability, as well as the protection of the environment and nature.Findings: According to the findings, “economic indicators” is the essential green transportation indicator in logistics companies with a corporate identity and worldwide transportation operations. Besides, the “mixed access model strategy” is the most appropriate smart network strategy in logistics firms with corporate identity and worldwide transportation activities. Currently, it is possible to assume that logistics organizations prefer to profit from all smart network strategies in terms of cost optimization and competitiveness rather than from just one. The study, on the other hand, which is a road map that will help sustainability practices in the logistics sector due to green transportation, also examines the similarities and differences of green transportation practices in companies in the relevant sector and to what extent they can be reflected. As a result, the study provides a practical road map for selecting green transport indicators and a smart network strategy process for the logistics industry.Originality/value: This study examined logistics companies with a corporate identity and international transportation activities in provinces in the Eastern Black Sea Region such as Ordu, Giresun, Trabzon, Rize, Artvin and Gümüshane. Novel picture fuzzy level based weight assessment (PF-LBWA) and picture fuzzy combined compromise solution (PF-CoCoSo) methods are developed to solve the decision-making problem.