Highlights Quarantine decisions during a pandemic directly affect the hospitality industry. A DEMATEL method is proposed for quarantine decision due to COVID-19 Pandemic. A real life case study in Turkey is conducted in this paper. Istanbul has an essential impact on the rest of all regions in Turkey.

Purpose The purpose of this paper is to analyze the wind energy technologies using the social network analysis based on patent information. Analysis of patent documents with social network analysis is used to identify the most influential and connected technologies in the field of wind energy. Design/methodology/approach In the literature, patent data are often used to evaluate technologies. Patents related to wind energy technologies are obtained from the United States Patent and Trademark Office database and the relationships among sub-technologies based on Corporate Patent Classification (CPC) codes are analyzed in this study. The results of two-phase algorithm for mining high average-utility itemsets algorithm, which is one of the utility mining algorithm in data mining, is used to find associations among wind energy technologies for social network analysis. Findings The results of this study show that it is very important to focus on wind motors and technologies related to energy conversion or management systems reducing greenhouse gas emissions. The results of this study imply that Y02E, F03D and F05B CPC codes are the most influential CPC codes based on social network analysis. Originality/value Analysis of patent documents with social network analysis for technology evaluation is extremely limited in the literature. There is no research related to the analysis of patent documents with social network analysis, in particular CPC codes, for wind energy technology. This paper fills this gap in the literature. This study explores technologies related to wind energy technologies and identifies the most influential wind energy technologies in practice. This study also extracts useful information and knowledge to identify core corporate patent class (es) in the field of wind energy technology.

Purpose This study aims to propose a novel approach based on utility mining to find the associations among wind energy technologies. Design/methodology/approach The proposed approach uses patent documents and utility mining. Associations among wind energy technologies have been evaluated to show how the proposed approach works in practice. Findings Determining the relationships between wind energy technologies provide essential information to investors and decision-makers. Therefore, a real-life case study of wind energy technology is performed to show how the proposed approach works in practice. The proposed approach founds technology classes associated with wind energy technology. Furthermore, the strongest associations among technologies are also obtained by the proposed approach. The results of the case study show that the proposed approach can be easily used in practice. The maximum size of itemsets is 18-level itemsets. Y02E and F03D cooperative patent classification (CPC) codes appear on all itemsets. As the technologies of Y02E and F03D are directly correlated, they will be mutually developed in the future. Additionally, the number of patent corresponding to Y02E and F03D CPC codes are 7,494 and 6,577, respectively. Originality/value This is the first study that applies the utility mining-based approach to patent documents. Different levels of importance among technologies based on patent citations and the number of repetitions of each technology class are considered in the proposed approach.

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