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Due to the complexity of real-world multi-criteria decision-making (MCDM) issues, analyzing different opinions from a group of decision makers needs to ensure appropriate decision making. The group decision-making methods collect preferences of the decision makers and present the best preferences using mathematical equations. The best–worst method (BWM) is one of the recently introduced MCDM methods that requires fewer pairwise comparisons to obtain the criteria weights than the other MCDM methods. In this research, we develop a novel approach to group decision-making problems based on the BWM called G-BWM. This approach helps us to analyze the preferences of decision makers to carry out democratic decision making using the BWM structure. In order to assess the applicability of the proposed methodology and represent its novelty, two numerical examples from the literature with the application to supply chain management (SCM) (i.e., green supplier selection and supplier development/segmentation) are examined and discussed. The results demonstrate the performance of our proposed G-BWM for group decision making in terms of a large number of decision makers, ease of use and achieving democratic decisions in the decision-making process.

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Digital Marketing strategies are sets of controllable e-marketing variables that organizations combine to achieve marketing goals and to meet customers' needs. These strategies are the most important factors that electronic-marketing managers pay attention to the best strategy in order to achieve sales and profitability. This study aims to investigate the effect of these strategies on the buying behavior of customers in online shopping stores in Tehran. For this purpose, five best-selling online stores in Tehran are selected and 79 samples are taken from each of them. For data collection, a 2-tuple fuzzy linguistic representation model is used in order to no lose the linguistic information obtained from customers. For data analyzing and extracting proper rules, two approaches of the rough set theory are used. Based on the results provided by Rosetta software, five rules governing customer behavior are identified as the most important factors affecting buying behavior in online shopping. To evaluate the result, a comparison is carried out between the extracted rules using the proposed rough set technique and the tree diagram of the data obtained by Rapidminer software. Almost all provided rules are confirmed through this comparison along with the opinions of experts. Some of key results according to the obtained rules indicate that the most important digital marketing strategy is the search engine optimization. Moreover, the social media marketing and recommender engine play as second important issue of the marketing management.