Academicians and practitioners have recently begun to accord Artificial Intelligence (AI) and Big Data Analytics (BDA) significant consideration when exploring emerging research trends in different fields. The technique of bibliometric review has been extensively applied to the AI and BDA literature to map out existing scholarships. We summarise 711 bibliometric articles on AI & its sub-sets and BDA published in multiple fields to identify academic disciplines with significant research contributions. We pulled bibliometric review papers from the Scopus Q1 and Q2 journal database published between 2012 and 2022. The Scopus database returned 711 documents published in journals of different disciplines from 59 countries, averaging 17.9 citations per year. Multiple software and Database Analysers were used to investigate the data and illustrate the most active scientific bibliometric indicators such as authors and co-authors, citations, co-citations, countries, institutions, journal sources, and subject areas. The USA was the most influential nation (101 documents; 5405 citations), while China was the most productive nation (204 documents; 2371 citations). The most productive institution was Symbiosis International University, India (32 documents; 4.5%). The results reveal a substantial increase in bibliometric reviews in five clusters of disciplines: (a) Business & Management, (b) Engineering and Construction, (c) Healthcare, (d) Sustainable Operations & I4.0, and (e) Tourism and Hospitality Studies, the majority of which investigate the applications and use cases of AI and BDA to address real-world problems in the field. The keyword co-occurrence in the past bibliometric analyses indicates that BDA, AI, Machine Learning, Deep Learning, NLP, Fuzzy Logic, and Expert Systems will remain conspicuous research areas in these five diverse clusters of domain areas. Therefore, this paper summarises the bibliometric reviews on AI and BDA in the fields of Business, Engineering, Healthcare, Sustainable Operations, and Hospitality Tourism and serves as a starting point for novice and experienced researchers interested in these topics.
Handling an unpredictable and ever-changing environment has become a pressing issue for the tax consulting industry, which has experienced unprecedented changes in technology and working practices in recent years. To respond, tax consulting firms need to become more agile. Prior research has focused on workforce agility at the organizational level, paying little attention to agility at the individual level; here we set out to examine the influence of demographic factors on workforce agility. The study is based on data from 220 full-time tax professionals in Bangalore, India, and validates a workforce agility score developed by combining seven attributes of workforce agility. It looks at the influence of age, professional qualifications, employer type, service type, and job level on agility level. The results show that workforce agility varies significantly across four out of these five dimensions (except service type) and both confirms and challenges previous work. This research also offers managers insights into the key demographics, skills, and attributes required to achieve workforce agility in technology-driven environments such as tax consulting.
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