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Corporations would utilize advanced information technologies for generating corporate social responsibility (CSR) reports and communicating with their stakeholders. However, corporations often could not determine whether their CSR websites are capable of effective communication with the stakeholders. The purpose of this study would be to analyze websites of benchmark companies for establishing an evaluation model to be a reference for CSR website design. Information from expert interviews carried out in this study underwent DEMATEL method for analyzing the mutual relationships between the quality criteria and dimensions of CSR websites. DANP was then used to calculate the weight of each criterion. Finally, we would make use VIKOR method to prioritize the performance CSR website satisfaction. The following provides the recommended improvement priorities according to results of the expert interviews: service quality (C) followed by information quality (B) followed by technical quality (A).

In recent years several previous scholars made attempts to develop, extend, propose and apply Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for solving problems in decision making issues. Indeed, there are questions, how TOPSIS can help for solving these problems? Or does TOPSIS solved decision making problems in the real world? Therefore, this study shows the recent developments of TOPSIS approach which are presented by previous scholars. To achieve this objective, there are 105 reviewed papers which developed, extended, proposed and presented TOPSIS approach for solving DM problems. The results of the study indicated that 49 scholars have extended or developed TOPSIS technique and 56 scholars have proposed or presented new modifications for problems solution related to TOPSIS technique from 2000 to 2015. In addition, results of this study indicated that, previous studies have modifications related to this technique in 2011 more than other years.

The single-valued neutrosophic set (SVNS) is considered as an attractive tool for handling highly uncertain and vague information. With this regard, different from the most current distance-based technique for order preference by similarity to ideal solution (TOPSIS) methods, this study proposes a correlation-based TOPSIS model for addressing the single-valued neutrosophic (SVN) multiple attribute decision making (MADM) problems. To achieve this aim, we first develop a novel conception of SVN correlation coefficient, whose significant feature is that it lies in the interval [$-1$,1], which is in accordance with the classical correlation coefficient in statistics, whereas all the existing SVN correlation coefficients in the literature are within unit interval [0,1]. Afterwards, a weighted SVN correlation coefficient is also introduced to infuse the importance of attributes. Moreover, a correlation-based comprehensive index is further proposed to establish the central structure of TOPSIS model, called the SVN correlation-based TOPSIS approach. Finally, a numerical example and relevant comparative analysis are implemented to explain the applicability and effectiveness of the mentioned methodology.

This study aims to present a multiattribute decision-making (MADM) and clustering method to explore the ranking, classifications and evolution mechanisms of the research fronts in the Web of Science Essential Science Indicators (ESI) database. First, bibliometrics are used to reveal the characteristics of the 57 ESI research fronts with more than 40 ESI highly cited papers (ESI-HCPs) for each research front. Second, the eight representative indicators are discovered to get answers to the following two questions: (i) Who publishes the ESI-HCPs that form a research front? and (ii) Where citations to these ESI-HCPs come from on a research front? Next, we investigate the ranking and clusters among the 57 ESI research fronts using the MADM and $k$-means clustering method and uncover the evolution process of the research fronts in different clusters based on the representative indicators. We also compare the performances of different countries in these research fronts and find that the USA and China are the leading countries in most research fronts. However, the two countries behave differently with regard to the rankings, the classifications and the evolution.