ABSTRACT
Purpose The investigation of the relationship between the future of humanity and the future of ecology is a pertinent issue. In this context, the study aimed to explore people's travel experience in the Himalayan region of India for transformation and well-being and how transformation induces their involvement in regenerative practices. The authors investigated if transformations contribute to the well-being of all living beings and the environment and induce involvement in regenerative practices? Design/methodology/approach The authors preferred qualitative research design and selected narrative inquiry as a research approach to bring individuals' life stories to the centre stage for examination. Accordingly, diachronic data was collected, and a paradigmatic type of narrative inquiry was applied that uses paradigmatic analytical procedures to produce thematic categories and taxonomies from the database. Findings Nine themes were identified and discussed in the light of existing literature. Transformational tourism promotes well-being and reduces mental health anomalies. The study participants used words like calm, compose, stress-free, and compassion, indicating enhanced consciousness. They also reported satisfaction and induced environmentally friendly behaviour after serving the community and environment at tourist destinations situated in Himachal Pradesh, Uttarakhand, and the Union territory of Ladakh of the Himalayan region of India. Originality/value The paper collates evidence to establish a correlation between transformation and regeneration. There is a suggestion that transformative travel leads to participation in regenerative activities. The paper is based on people's experiences described as green workers of the Indian Himalayas and provides empirical conclusions that support the argument of transformational induced regenerative tourism.
ABSTRACT
The 2020 world pandemic has brought into limelight an already existing and refurbished methodology of working known as 'Work from Home'. With preventive and curative treatments steadily reaching out most parts of the world now, the existence of Novel Coronavirus and its variants still cannot be denied. When more than 80% of the world was under lockdown and nearly a million people were at a risk of losing their lives, sectors like corporate, education, business and many others, on the recommendation of World Health Organization decided to allow their employees to work from remote locations where they can self-isolate themselves and prevent the spread on this infectious virus thereby some completely while others partially adhering to the work from home methodology. While being at home, people saw social media as a major platform to showcase their views and thinking over the ongoing and post-pandemic scenarios. The main aim of this study is to analyze public sentiments and emotions over Work from Home methodology based upon their views laid out on Twitter by using TextBlob, VADER and various Machine Learning Classification Algorithms to create a conclusive yet generalized picture of the presented positive, negative and neutral aspects of the viewpoints with the objective of identifying the most prominent one. Experimental evaluations show that people, in general, reflect 'positive to neutral' opinions towards the Work from Home methodology with Support Vector Classifier classifying the data into their respective sentiment classes with highest possible accuracy of 94.67%. © Grenze Scientific Society, 2021