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The purpose of this paper is to make a comprehensive analysis of 354 publications about Pythagorean fuzzy sets (PFSs) from 2013 to 2020 in order to comprehensively understand their historical progress and current situation, as well as future development trend.

First, this paper describes the fundamental information of these publications on PFSs, including their data information, annual trend and prediction and basic features. Second, the most productive and influential authors, countries/regions, institutions and the most cited documents are presented in the form of evaluation indicators. Third, with the help of VOSviewer software, the visualization analysis is conducted to show the development status of PFSs publications at the level of authors, countries/regions, institutions and keywords. Finally, the burst detection of keywords, timezone review and timeline review are exported from CiteSpace software to analyze the hotspots and development trend on PFSs.

The annual PFSs publications present a quickly increasing trend. The most productive author is Wei Guiwu (China). Wei Guiwu and Wei Cun have the strongest cooperative relationship.

The implication of this study is to provide a comprehensive perspective for the scholars who take a fancy to PFSs, and it is valuable for scholars to grasp the hotspots in this field in time.

It is the first paper that uses the bibliometric analysis to comprehensively analyze the publications on PFSs. It can help the scholars in the field of PFSs to quickly understand the development status and trend of PFSs.

The purpose of this paper is to develop some picture uncertain linguistic aggregation operators based on Bonferroni mean operators, which is combined with multiple attribute decision-making (MADM) and has applied the proposed MADM model for selecting the service outsourcing provider of communications industry under picture uncertain linguistic environment.

The service outsourcing provider selection problem of communications industry can be regarded as a typical MADM problem, in which the decision information should be aggregated. In this paper, the authors investigate the MADM problems with picture uncertain linguistic information based on traditional Bonferroni mean operator.

The results show that the proposed model can solve the MADM problems within the context of picture uncertain linguistic information, in which the attributes are existing interaction phenomenon. Some picture uncertain aggregation operators based on Bonferroni mean have been developed. A case study of service outsourcing provider selection problem of communications industry is provided to illustrate the effectiveness and feasibility of the proposed methods. The results show that the proposed methods are useful to aggregate the picture uncertain linguistic decision information in which the attributes are not independent so as to select the most suitable supplier.

The proposed methods can solve the picture uncertain linguistic MADM problem, in which the interactions exist among the attributes. Therefore, it can be used to solve service outsourcing provider selection problems and other similar management decision problems.

This paper develops some picture uncertain aggregation operators based on Bonferroni mean and further presents two methods based on the proposed operators for solving MADM problems. It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.

It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.

The paper investigates the MADM problems with picture uncertain linguistic information based on traditional Bonferroni mean operator and develops the picture uncertain linguistic Bonferroni mean operator and picture uncertain linguistic geometric Bonferroni mean operator, picture uncertain linguistic weighted Bonferroni mean operator and picture uncertain linguistic weighted geometric Bonferroni mean operator for aggregating the picture uncertain linguistic information, respectively. Finally, a numerical example concerning the service outsourcing provider selection problem of communications industry is provided to illustrate the effectiveness and feasibility of the proposed methods.

In the supply chain disruption risk, the issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

Considering the influence of irrational emotions of decision makers, an evaluation model is designed by the regret theory and VIKOR method, which makes the decision-making process closer to reality.

The paper has some innovations in the evaluation index system and evaluation model construction. The method has good stability under the risk of supply chain interruption.

The mixed evaluation information is used to describe the attributes, and the evaluation index system is constructed by the combined method of the social network analysis method and the literature research method to ensure the accuracy and accuracy of the extracted attributes. The issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

The hotel and tourism industry forms a crucial economic sector for all the economies around the world. However, it suffered the worst hit during the COVID-19 outbreak. Considering the hotel and tourism sector's critical situation, this manuscript aims to emphasise the importance of resilience in the hotel and tourism supply chain (HTSC) and explores the crucial barriers that tend to disturb the inculcation of stability in the hotel and tourism sector. The present research analyses the factors influencing the hotel and tourism sector's resilience and also takes into consideration the various critical success factors (CSFs) needed to build a resilient HTSC.

A two-phase research approach has been proposed and used in this study. In the first phase, eight CSFs and sixteen factors influencing the hotel and tourism sector's resilience during the COVID-19 pandemic were identified. The basis of the identification of the CSFs and factors was literature and inputs received from experts. In the second phase, the grey-Entropy-EDAS, a qualitative and quantitative analysis, was used to analyse the identified CSFs and factors to determine the priority of concern.

In this research, the most imperative facet influencing the hotel and tourism sector's resilience has been identified, and the findings will assist hotel and tourism sector in managing and mitigating the repercussions of the COVID-19 pandemic. The analysis of the results indicates that out of all the critical success factors, supply chain visibility is the most crucial aspect in building HTSC's resilience, whereas economic catastrophe is the most influential factor. Sensitivity analysis is also conducted to examine the priority ranking stability.

The results of this study can be used by the hotel supply chain managers and policymakers to plan for various challenges faced by them as they try to implement resilience-based strategies in their supply chain.

This research is unique as it analyses the general factors hindering the pathway of resilience in the hotel and tourism supply chain. This is also the first kind of study that has used grey-Entropy to analyse the critical success factors and grey-EDAS for analysing the impact of various factors influencing the hotel and tourism sector's resilience.