Qualitative identification of associated words with the respective online service ratings
Purpose Collectively knowledge is mentioned to surpass the traditional assets such as workers, property and financial investment. The research studies on how the existing knowledge can be merged with new knowledge for further development of organizational progress is moving from nascent to active state. In this context, the applications of online data pose a research gap in the domain of hospital review ratings. The purpose of this study is to explore how this raw tacit knowledge can be transformed to explicit keywords associated with individual review ratings of the hospital. Design/methodology/approach The authors have attempted to decrypt the tacit knowledge extracted from Facebook page of nine Indian hospitals (sources for the nine hospitals) using NVivo 12.3 to explain the resources associated with the poor or good review ratings. Findings Distinct patterns emerged with review ratings and associated words, which can be used to improve the facets of health-care services. Research limitations/implications The data used are only from India catering to national and international patients. Originality/value The sentiment analysis and word cloud associated with individual review rating can be further used for devising finer branding scales, as well as be practically used for real-time branding efforts by health-care industry.