“…This bibliometric analysis is the most extensive analysis in which mathematical and statistical methods are used to effectively measure, analyze and assess the bibliographic information of studies published on a specific subject such as Goyal and Kumar ( 2021 ), Xu et al ( 2018 ), Linnenluecke et al ( 2017 ) and Durisin and Puzone ( 2009 ), Bonilla et al ( 2015 ), Castillo-Vergara et al ( 2018 ), Wang et al ( 2020a , b ), Merediz-Sola and Bariviera ( 2019 ) in finance and economics, Elie et al ( 2021 ), Rosokhata et al ( 2021 ), Bortoluzzi et al ( 2021 ), Sarkodie and Owusu ( 2020 ), in renewable energy, Ellegaard and Wallin ( 2015 ), Merigo and Yang ( 2017 ), Fahimnia et al ( 2015 ), Zupic and Cater ( 2015 ) in management, Farrukh et al ( 2020 ), Ferreira et al ( 2011 ), Kumar et al ( 2021a , b ) in business strategy, Backhaus et al ( 2011 ), Miskiewicz ( 2020 ), Donthu et al ( 2020 ), Donthu et al ( 2021 ), Gao et al ( 2021 ) and Hu et al ( 2019 ) in marketing, Julius et al ( 2021 ), Sönmez ( 2020 ) in education. Today, despite the existence of numerous studies in different fields that use big data and machine learning algorithms it is observed that there are a few studies that examine big data and machine learning through bibliometric analysis.…”