The spread and use of English as the lingua franca of international business -'corporate englishization' -has received increasing scholarly attention in recent years but the focus has mostly been on the communication benefits and challenges of using English as a shared language inside multinationals. In this paper, we examine how English is used externally in the provision of business services and apply a postcolonial perspective to frame our analysis. Drawing on fieldwork in India within the call center units of two outsourcing organizations serving Anglo-American firms, we show how corporate englishization (1) relies on, and contributes to producing, comprador managerial cadres; (2) serves to construct a transnational intra-linguistic hierarchy of power and privilege; and (3) undercuts its own effectiveness by simultaneously eliminating and maintaining the alterity of the 'Other' through processes of mimicry. We thus show how corporate englishization does not merely overcome or, conversely, worsen transnational communication problems; it also (re-)produces colonial-style power relations between the 'Anglosphere' and the 'Rest'. Our analysis deepens our understanding of corporate englishization and opens a new avenue for postcolonial research on the role of language in international business. Our analysis also advances the field of postcolonial organization studies and has implications for international business scholarship more generally.
PurposeThis paper reviews 105 Scopus-indexed articles to identify the degree, scope and purposes of machine learning (ML) adoption in the core functions of human resource management (HRM).Design/methodology/approachA semi-systematic approach has been used in this review. It allows for a more detailed analysis of the literature which emerges from multiple disciplines and uses different methods and theoretical frameworks. Since ML research comes from multiple disciplines and consists of several methods, a semi-systematic approach to literature review was considered appropriate.FindingsThe review suggests that HRM has embraced ML, albeit it is at a nascent stage and is receiving attention largely from technology-oriented researchers. ML applications are strongest in the areas of recruitment and performance management and the use of decision trees and text-mining algorithms for classification dominate all functions of HRM. For complex processes, ML applications are still at an early stage; requiring HR experts and ML specialists to work together.Originality/valueGiven the current focus of organizations on digitalization, this review contributes significantly to the understanding of the current state of ML integration in HRM. Along with increasing efficiency and effectiveness of HRM functions, ML applications improve employees' experience and facilitate performance in the organizations.
With a population of more than 1.3 billion people, India has a rapidly growing need for health care, particularly in rural areas. Along with a widespread increase in the incidence of cancer, diabetes, and cardiovascular disease, the nation also is suffering from a shortage of health-care professionals. At Apollo Hospitals Enterprise Limited, the use of robotic surgery and artificial intelli-
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